diff --git "a/train/x_entries_out.jsonl" "b/train/x_entries_out.jsonl" new file mode 100644--- /dev/null +++ "b/train/x_entries_out.jsonl" @@ -0,0 +1,3582 @@ +{"package": "x", "pacakge-description": "UNKNOWN"} +{"package": "x01replace", "pacakge-description": "No description available on PyPI."} +{"package": "x0m-quickserver", "pacakge-description": "Installationpip install x0m-quickserver#LicenseMIT#Infoquickserver is a simple appliucation for starting quick server from your terminalStarting a ServerquickserverOwnershipThis package is made as an extension of x0mb3 Foundation !"} +{"package": "x-1000", "pacakge-description": "No description available on PyPI."} +{"package": "x100daemon", "pacakge-description": "NAMEx100daemon - Make daemon for your programSYNOPSISfrom x100daemon import Daemon\n\npidfile = '/var/pid/hello.pid'\nd = Daemon(pidfile)\nd.daemonize()\n\n#your program districtDESCRIPTIONx100daemon make daemon for your programMETHODSpidfileAssgin your pidfile pathdaemonizemake daemonSUPPORTED PYTHON VERSIONSdaemonize only supports python 3.3 or newer.EXAMPLESexamplefrom x100daemon import Daemon\n\npidfile = '/var/pid/hello.pid'\nd = Daemon(pidfile)\nd.daemonize()\n\n#your program district"} +{"package": "x100http", "pacakge-description": "NAMEx100http, web framework support customing file upload processingSYNOPSISfrom x100http import X100HTTP\n\napp = X100HTTP()\n\ndef hello_world(request):\n remote_ip = request.get_remote_ip()\n response = \"hello, \" + remote_ip + \"\"\n return response\n\napp.get(\"/\", hello_world)\napp.run(\"0.0.0.0\", 8080)DESCRIPTIONx100http is a lite webframework designed for processing HTTP file upload.CLASS X100HTTPX100HTTP()return a instance of x100http which wrapped below functions.run(listern_ip, listen_port)run a forking server on addresslistern_ip:listern_portget(url, handler_function)set a route acl of HTTP \u201cGET\u201d method.handler_functionwill be called whenurlbe visited.handler_functionmust return a string as the HTTP response body to the visitor.structrequest(will explain below) will be passed to the handlder function when it is called.post(url, handler_function)set a route acl of HTTP \u201cPOST\u201d method with header \u201cContent-Type: application/x-www-form-urlencoded\u201d.handler_functionwill be called when HTTP client submit a form with the actionurl.handler_functionmust return a string as the HTTP response body to the visitor.structrequest(will explain below) will be passed to the handlder function when it is called.static(url_prefix, file_path, cors=allow_domain)set a route acl for static fileStatic file request withurl_prefixwill be routing to the file infile_path.Default value of cors is \u201c*\u201d, allow all CORS request matching this route rule.upload(url, upload_handler_class)set a route acl of HTTP \u201cPOST\u201d method with header \u201cContent-Type: multipart/form-data\u201d.A new instance of classupload_handler_classwill be created when file upload start.struct \u201crequest\u201d (will explain below) will be passed toupload_handler_class.upload_start().upload_handler_class.upload_process()will be called every time when the buffer is full when file uploading.two args will be passed toupload_handler_class.upload_process().first arg is the name of the input in the form, second arg is the content of the input in the form.the binary content of the upload file will be passed by the second arg.struct \u201crequest\u201d (will explain below) will NOT be passed toupload_handler_class.upload_finish().upload_handler_class.upload_finish()will be called when file upload finished, this function must return a string as the HTTP response body to the visitor.struct \u201crequest\u201d (will explain below) will be passed toupload_handler_class.upload_finish().set_upload_buf_size(buf_size)set the buffer size of the stream reader while file uploading.the unit ofbuf_sizeis byte, default value is 4096 byte.upload_handler_class.upload_process()will be called to process the buffer every time when the buffer is full.ROUTINGx100http route accept a url and a function/class/path.There are three four of routes - get, post, static and upload.app.get(\"/get_imple\", get_simple)\napp.post(\"/post_simple\", post_simple)\napp.upload(\"/upload_simple\", UploadClass)\napp.static(\"/static/test/\", \"/tmp/sta/\")routing for HTTP GET can be more flexible like this:app.get(\"/one_dir/_.py?abc=def\", regex_get)allow all domain for CORS like this:app.static(\"/static/test/\", \"/tmp/sta/\", cors=\"*\")CLASS X100REQUESTA instance of classX100Requestwill be passed into every handler function.get_remote_ip()Return the IP address of the visitor.get_body()Return the body section of the HTTP request.Will be empty when the HTTP method is \u201cGET\u201d or \u201cPOST - multipart/form-data\u201d.get_query_string()Return the query string of the page was accessed, if any.get_arg(arg_name)args parsed fromquery_stringwhen the request is sent by \u201cGET\u201d or \u201cPOST - multipart/form-data\u201d.args parsed frombodywhen the request is sent by \u201cPOST - application/x-www-form-urlencoded\u201d.get_header(header_name)Return the header`s value of theheader_name, if any.CLASS X100RESPONSEset_body(content)Set the response data to visitor.Type \u2018str\u2019 and type \u2018bytes\u2019 are both accepted.set_header(name, value)Set the HTTP header.HTTP ERROR 500visitor will get HTTP error \u201c500\u201d when the handler function of the url he visit raise an error or code something wrong.SUPPORTED PYTHON VERSIONSx100http only supports python 3.4 or newer, because ofre.fullmatchandos.sendfile.EXAMPLESget visitor ipfrom x100http import X100HTTP\n\napp = X100HTTP()\n\ndef hello_world(request):\n remote_ip = request.get_remote_ip()\n response = \"hello, \" + remote_ip + \"\"\n return response\n\napp.get(\"/\", hello_world)\napp.run(\"0.0.0.0\", 8080)post method routefrom x100http import X100HTTP\n\napp = X100HTTP()\n\ndef index(request):\n response = \"\" \\\n + \"
\" \\\n + \"\" \\\n + \"\" \\\n + \"
\" \\\n + \"\"\n return response\n\ndef post_handler(request):\n remote_ip = request.get_remote_ip()\n abc = request.get_arg('abc')\n response = \"hello, \" + remote_ip + \" you typed: \" + abc\n return response\n\napp.get(\"/\", index)\napp.post(\"/form\", post_handler)\napp.run(\"0.0.0.0\", 8080)process file uploadfrom x100http import X100HTTP, X100Response\n\nclass UploadHandler:\n\n def upload_start(self, request):\n self.content = \"start\"\n\n def upload_process(self, key, line):\n self.content += line.decode()\n\n def upload_finish(self, request):\n return \"upload succ, content = \" + self.content\n\napp = X100HTTP()\napp.upload(\"/upload\", UploadHandler)\napp.run(\"0.0.0.0\", 8080)set http headerfrom x100http import X100HTTP, X100Response\n\ndef get_custom_header(request):\n remote_ip = request.get_remote_ip()\n response = X100Response()\n response.set_header(\"X-My-Header\", \"My-Value\")\n response.set_body(\"hello, \" + remote_ip + \"\")\n return response\n\napp = X100HTTP()\napp.upload(\"/\", get_custom_header)\napp.run(\"0.0.0.0\", 8080)more flexible routingfrom x100http import X100HTTP\n\ndef regex_get(request):\n first = request.get_arg(\"arg_first\")\n second = request.get_arg(\"arg_second\")\n abc = request.get_arg(\"abc\")\n return \"hello, \" + first + second + abc\n\napp = X100HTTP()\napp.get(\"/one_dir/_.py?abc=def\", regex_get)\napp.run(\"0.0.0.0\", 8080)"} +{"package": "x100idgen", "pacakge-description": "NAMEx100idgen - Id generator require no centralized authoritySYNOPSISimport x100idgen\n\ndef get_id(hash_string):\n idgen = x100idgen.IdGen()\n your_id = idgen.gen_id(hash_string)\n return (your_id)\n\ndef validate_id(your_id):\n idgen = x100idgen.IdGen()\n if idgen.validate_id(your_id):\n return True\n else:\n return False\n\nif __name__ == '__main__':\n hash_string = \"111.206.116.190Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_3) AppleWebKit/600.6.3 (KHTML, like Gecko) Version/8.0.6 Safari/600.6.3\"\n your_id = get_id(hash_string)\n print(\"Get id : \" + your_id)\n\n id_valid = str(validate_id(your_id))\n print(\"The id \" + your_id + \" is \" + id_valid)Ouput:Get id : ytmaWHUzDikIGwOLl6\nThe id ytmaWHUzDikIGwOLl6 is TrueDESCRIPTIONx100idgen is an id generator require no centralized authority like uuidgen, shorter and more customizable.This module helps generate unique ids like \u2018ytmaWHUzDikIGwOLl6\u2019 (/^[0-9a-zA-Z]{18}$/) easy and fast."} +{"package": "x10_any", "pacakge-description": "Wrapper module to control X10 devices.Table of ContentsInformationGetting StartedInformationInitial focus is supporting:Mochad (or compatible) servers to controlhttps://sourceforge.net/projects/mochad/for CM15A RF (radio frequency) and PL (power line) controller and the CM19A RF controllerhttps://bitbucket.org/clach04/mochad_firecracker/works under Windows and Linux and can control CM17A serial FirecrackerCM17A serial Firecracker X10 unit, builtin support for CM17A over regular serial port. Also known to work with CM19A USB Firecracker device. For control via GPIO on Raspberry Pi manually install:https://bitbucket.org/cdelker/python-x10-firecracker-interfacecan be used on Raspberry Pi to control GPIO, not (yet) Python 3 compatible and does not support ALL on/offImplemented in pure Python. Known to work with:Python 2.7Python 3.4.4Python 3.5Getting StartedTo get started and install the latest version fromPyPi:pip install x10_anyIf installing/working with a source checkout issue:pip install -r requirements.txtThen run tests via:python -m x10_any.test.testsSerial Port Permissions under LinuxUnder Linux most users do not have serial port permissions,\neither:give user permission (e.g. add to group \u201cdialout\u201d) - RECOMMENDEDrun this demo as root - NOT recommended!Giver user dialout (serial port) access:# NOTE requires logout/login to take effect\nsudo usermod -a -G dialout $USERSampleMochad:import x10_any\n\nx10_any.default_logger.setLevel(x10_any.logging.DEBUG) # DEBUG\n\ndev = x10_any.MochadDriver()\ndev.x10_command('A', 1, x10_any.ON)\ndev.x10_command('A', 1, x10_any.OFF)Firecracker:import x10_any\n\nx10_any.default_logger.setLevel(x10_any.logging.DEBUG) # DEBUG\n\ndev = x10_any.FirecrackerDriver()\n#dev = x10_any.FirecrackerDriver('COM11')\n#dev = x10_any.FirecrackerDriver('/dev/ttyUSB0')\ndev.x10_command('A', 1, x10_any.ON)\ndev.x10_command('A', 1, x10_any.OFF)"} +{"package": "x10-blackjack", "pacakge-description": "BlackjackUsagePerform the equivalent of the below line;pipenv install --python 3.7 x10-blackjack(Tip: can also replacepipenv install --python 3.7with justpip).And then, from within the same (hopefully virtual) environment you've now installedx10-blackjackinto, execute with something equivalent to;pipenv run blackjackIf you instead want to install via GitEnsure you've gotpython3.7andpipenvavailable on$PATH.PS:https://pipenv.pypa.io/en/latest/install/#installing-pipenvThen performmake installas referenced in Developer/Installation steps.Developer UsageAutomatic pipelineThis repository has a pipeline triggering on any and all commits pushed.\n(Also merge-requests created).So, if pipeline passes okay, then all is good.\nRead on for further details on how to set-up dev-environment locally/manually.Requirementspipenvavailable through PATH (e.g. installed throughpipsiso as to contain it to USER PATH env).python3.7DockerExecute the equivalent of theMakefilesmake docker(and thus nothing besidesdockeris required on developer machine).Installation stepsgit clone cd make installDevelopment iteration stepsmake check_all(ormake check_quickif you don't want to run slower integration tests).make runRepeat any steps (or sequence of them) as needed untilmake check_allpasses before pushing tomasterbranch (ideally...).Upload to PyPI manuallyFirst create package;make packageThen uploadpipenv run twine upload dist/*Note: The command in list-item #2 relies on the variablesTWINE_USERNAME=\"__token__\"andTWINE_PASSWORD=having been set.Upload to PyPI automatically (read: with (GitLab) pipeline)Push agit tagwhere the name of the tag is a semantic version (..)."} +{"package": "x11-automation", "pacakge-description": "x11-automationModule for x11 automationPrerequisites- Python3.5 or newerInstallion$ python3 -m pip install x11_automationOR$ python3 -m pip install git+https://github.com/jok4r/x11_automation.gitUsageWill be later\nMIT LicenseCopyright (c) 2021 Dmitry YakovlevPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "x11_hash", "pacakge-description": "Python module for Dash\u2019s X11 hashing.InstallPython 2.7 is required as well as gcc.$ python setup.py installTestAfter installation, test hash.$ python test.pyCreditsModule written by @chaeplinhttps://github.com/chaeplin/xcoin-hashModule maintained by @eduffieldhttps://github.com/darkcoinproject/xcoin-hashModule maintained by @flarehttps://github.com/nightlydarkcoin/xcoin-hashModule maintained by @vertoehttps://github.com/vertoe/darkcoin_hashModule maintained by @jakehaashttps://github.com/jakehaas/x11_hash"} +{"package": "x11-hashw", "pacakge-description": "No description available on PyPI."} +{"package": "x11pygrid", "pacakge-description": "x11PyGridx11pygrid is a small utility which allows you to easily organize your open windows\nby tiling, resizing and positioning them to make the best use of your desktop\nreal estate. It's easy to configure and supports multiple monitors.Notice that, package is renamed from pygrid to x11pygrid.Previous name was too similar to the other package in PyPi.RequirementsPython3X11-based desktoppython3-gipython3-xlibsingle_processDefault ShortcutsALT+CTRL+NUMPAD-1- Move window to bottom left.ALT+CTRL+NUMPAD-2- Move window to bottom.ALT+CTRL+NUMPAD-3- Move window to bottom right.ALT+CTRL+NUMPAD-4- Move window to left.ALT+CTRL+NUMPAD-5- Move window to center.ALT+CTRL+NUMPAD-6- Move window to right.ALT+CTRL+NUMPAD-7- Move window to top left.ALT+CTRL+NUMPAD-8- Move window to top.ALT+CTRL+NUMPAD-9- Move window to top right.ALT+CTRL+NUMPAD-0- Maximize window.ALT+CTRL+NUMPAD-ENTER- Cycle window between monitors.Repeatedly press one of the defined keybindings to cycle through window sizes\navailable at the desired location on the screen.ConfigurationConfiguration is done via a JSON file located at~/.config/x11pygrid.json,\nwhich will be created with default options if not found when starting up.If you have old, customized configuration file, named by old package name\n(i.e. in~/.config/pygrid.jsoninstead of~/.config/x11pygrid.json),\nyou can justmv ~/.config/pygrid.json ~/.config/x11pygrid.json.The default configuration is below. If you introduce top level sections'monitor0': {...}or'monitor1': {...}to provide different options for each monitor on your\nsystem. Any settings not defined will fall back to user-defined defaults, then\nglobal defaults. NOTE: Updating configuration in this JSON file doesnotrequire you to restart PyGrid.{'default':{'xdivs':3,// number of x divisions for the screen.'ydivs':2,// number of y divisions for the screen.'padding':[0,0,0,0],// additional top, right, bottom, left padding in pixels.'spacing':4,// spacing between windows in pixels.'minwidth':0.25,// min percent width of window.'maxwidth':0.67,// max percent width of window.'minheight':0.33,// min percent height of window.'maxheight':0.67,// max percent height of window.'snaptocursor':false,// window will be moved to cursor's monitor},'monitor0':{...},// Repeat any settings above specific for monitor 0.'monitor1':{...},// Repeat any settings above specific for monitor 1.'monitor':{...},// Repeat any settings above specific for monitor .'keys':{'accelerator':'','commands':{'KP_1':'bottomleft',// Set KP-1 to cycle bottom left window sizes.'KP_2':'bottom',// Set KP-2 to cycle bottom window sizes.'KP_3':'bottomright',// Set KP-3 to cycle bottom right window sizes.'KP_4':'left',// Set KP-4 to cycle left window sizes.'KP_5':'middle',// Set KP-5 to cycle centered window sizes.'KP_6':'right',// Set KP-6 to cycle right window sizes.'KP_7':'topleft',// Set KP-7 to cycle top left window sizes.'KP_8':'top',// Set KP-8 to cycle top window sizes.'KP_9':'topright'// Set KP-9 to cycle top right window sizes.'KP_0':'maximize',// Set KP-0 to maximize the window.'KP_Enter':'cycle-monitor',// Set KP-ENTER to cycle window between monitors.}}}Available Commandsbottomleft- cycle window sizes which touch both bottom and left screen edges.bottom- cycle window sizes which touch the bottom screen edge and are centered horizontally.bottomright- cycle window sizes which touch both bottom and right screen edges.left- cycle window sizes which touch the left screen edge and are centered vertically.middle- cycle window sizes which are centered both horizontally and vertically.right- cycle window sizes which touch the right screen edge and are centered vertically.topleft- cycle window sizes which touch both top and left screen edges.top- cycle window sizes which touch the top screen edge and are centered horizontally.topright- cycle window sizes which touch both top and right screen edges.noclampleft- cycle window sizes on the left of the screen with the same vertical size.noclampright- cycle window sizes on the right of the screen with the same vertical size.noclamptop- cycle window sizes at the top of the screen with the same horizontal size.noclampbottom- cycle window sizes at the bottom of the screen with the same horizontal size.InstallationpipThe simpliest method, just oneliner:pipinstall--userx11pygridpipxIsolated environments maintained bypipxare great, but not always totally free.\nAccording to thePycairo's documentation, before installing pycairo, you need to provide few\npackages (dependencies): pkg-config and cairo with it's headers. (Indeed, it's a bit paradoxical.)Obviously, you also need python3-pip, python3-venv and pipx itself. Unfortunately(?), they are not marked\nas dependencies of pipx, so you may need to install it first. More about that in thepipx's documentation.\nNow let's assume you have already installed fully operational pipx.So, before you execute universal:pipxinstallx11pygridyou need to install dependencies. Obviously \u2013 with corresponding to your distro packages manager.Ubuntu / Debiansudoaptinstalllibcairo2-devpkg-configpython3-dev\npipxinstallx11pygridArch Linuxsudopacman-Scairopkgconf\npipxinstallx11pygridFedorasudodnfinstallcairo-develpkg-configpython3-devel\npipxinstallx11pygridopenSUSEsudozypperinstallcairo-develpkg-configpython3-devel\npipxinstallx11pygridFreeBSDsudopkginstall-ydevel/pkgconf\npipxinstallx11pygridyou can also install pkgconf from ports:cd/usr/ports/devel/pkgconf/\nsudomakeinstallclean\npipxinstallx11pygridFrom sourceThe only file you really need to install isx11pygrid.py, which you can place anywhere you want.\nFor example:mkdir-p~/.local/bin/cd~/.local/bin/\nwgethttps://raw.githubusercontent.com/pkkid/x11pygrid/master/src/x11pygrid/x11pygrid.py\nmvx11pygrid.pyx11pygrid\nchmod+xx11pygridAlso you should check if choosen directory is inecho $PATHand install dependencies by hand.\nBecause of that and many other reasons, the best solution ispipxor at leastpip.AutostartIt is propably the most natural to just addx11pygridto theStartup ApplicationsakaAutostart.\nDepending on distro and window manager, it can be done in many ways.\nIt is not recomended to do it bycron, because it's X11-dependent.Credit & LicensePyGrid was originally a fork ofQuickTile by ssokolow,\nbut rewritten to allow a much easier configuration as well as updated code to\nrun on Python3 & GTK3. Code released under GPLv2 License."} +{"package": "x11util", "pacakge-description": "x11util Packagex11util - Wrapper fucntions to make X11 low-level Xlib programming easierDESCRIPTIONThis manual page documentsx11utilmodule, a Python module providing\nseveral wrapper function for Xlib programming easier.EXAMPLEimporttimefromXlibimportX,displayfromx11utilimportcreate_window,create_gcs,load_font,draw_str,flushdisp=display.Display()font=load_font(disp)screen=disp.screen()window=create_window(disp,screen,width=320,height=240,x=100,y=200)gcs=create_gcs(disp,screen,window,font)draw_str(disp,screen,window,gcs,'Hello, World!',10,20)draw_str(disp,screen,window,gcs,'Hello, World!',11,21,level=50)flush(disp,screen)time.sleep(10)FUNCTIONSx11utilmodule provides the following functions.create_window(disp, screen, width=640, height=480, x=0, y=0, override=1, mask=X.ExposureMask)Create a new window on screen SCREEN in display DISP with given WIDTH and\nHEIGHT, which is placed at the geometry of (X, Y) using Xlib's\nXCreateWindow. override_redirect and event_mask can specified by OVERRIDE\nand MASK, respectively.load_font(disp, font=None)Load bitmap font FONT in display DISP, and return the loaded font object.\nIf font loading failed, return None.create_gcs(disp, screen, window, font)Create GCs (Graphics Content) on screen SCREEN in display DISP for window\nWINDOW with font FONT. GCs are returned as a dictionary, whose key is the\ncolor name (e.g., 'SteelBlue') and the value is a dictionary, whose items\nare (LEVEL, GC), where LEVEL is a brightness between 0 and 100 and GC is the\nGC for that brightness.clear(window)Erase the window WINDOW.draw_str(disp, screen, window, gcs, astr, col=0, row=0, color='PaleGreen', level=100, reverse=False)Render a string ASTR on window WINDOW on screen SCREEN in display DISP using\ngraphics contents GC. Text color and brightness can be specified by COLOR\nand LEVEL, respectively. Reverse video is enabled if REVERSE is True.flush(disp, screen)Flush all pending X11 requests.CUSTOMIZATIONOn startup,x11utilmodule loads per-user RC script (~/.x11utilrc) if it\nexists. The RC script is any valid Python script. You can change the\nbehavior ofx11utilusing the RC file.An example~/.x11utilrcfile is as follows.globalFONT_NAMEFONT_NAME='-hiro-fixed-medium-r-normal--8-80-75-75-c-80-iso646.1991-irv'INSTALLATIONpip3installx11utilAVAILABILITYThe latest version ofx11utilmodule is available at PyPI\n(https://pypi.org/project/x11util/) .SEE ALSOXlib - C Language X Interfacepython3-xlib (https://pypi.org/project/python3-xlib/)AUTHORHiroyuki Ohsaki "} +{"package": "x12306", "pacakge-description": "x1230612306\u67e5\u7968\u52a9\u624b\uff0c\u4e3b\u8981\u529f\u80fd\u662f\u53ef\u4ee5\u4e00\u952e\u67e5\u8be2\u6cbf\u9014\u6240\u6709\u7ad9\u70b9\u3002\u5f53\u5168\u7a0b\u7968\u552e\u7f44\u7684\u65f6\u5019\uff0c\u65b9\u4fbf\u67e5\u8be2\u4e2d\u95f4\u7ad9\u70b9\u4f59\u7968\uff0c\u5148\u4e0a\u8f66\u540e\u8865\u7968\u3002\u5de5\u5177\u4ec5\u7528\u4e8e\u67e5\u8be2\u4f59\u7968\uff0c\u4e0d\u652f\u6301\u8d2d\u7968\uff0c\u5efa\u8bae\u572812306\u5b98\u65b9\u5e73\u53f0\u8d2d\u7968\u3002\u4ec5\u652f\u6301Python3\uff0c\u63a8\u8350Python3.5+\u4f7f\u7528\u524d\u9700\u8981\u4fee\u6539glovar.py\u4e2d\u7684QUERY_URL\u548cJSESSIONID\u83b7\u53d6QUERY_URL\u548cJSESSIONID\u6253\u5f00\u6d4f\u89c8\u5668\uff0c\u8bbf\u95eehttps://www.12306.cn/index/\u968f\u4fbf\u67e5\u8be2\u4e00\u4e2a\u8f66\u6b21\uff0c\u5982\u4e0a\u6d77 > \u5317\u4eac\u6309F12\uff08\u6216CMD+Option+I\uff09\u6253\u5f00\u6d4f\u89c8\u5668\u63a7\u5236\u53f0\uff0c\u6253\u5f00\u7f51\u7edc\uff08Network\uff09\u9009\u9879\u5361\u627e\u5230\u67e5\u8be2\u8f66\u6b21\u7684\u8bf7\u6c42\uff0c\u5982\u679c\u6ca1\u627e\u5230\uff0c\u53ef\u4ee5\u518d\u70b9\u4e00\u4e0b\u67e5\u8be2\u5728glovar.py\u4e2d\u4fee\u6539QUERY_URL\u548cJSESSIONID\u5b89\u88c5\u8fd0\u884c\u624b\u52a8\u5b89\u88c5\uff1agitclonehttps://github.com/0xHJK/x12306cdx12306&&makeinstall\u4e0d\u5b89\u88c5\u76f4\u63a5\u8fd0\u884c\uff1agitclonehttps://github.com/0xHJK/x12306cdx12306\npython3x12306.py-f<\u51fa\u53d1\u5730>-t<\u76ee\u7684\u5730>-d-z\u4f7f\u7528\u65b9\u6cd5$ x12306 --help\nUsage: x12306.py [OPTIONS]\n\n 12306\u67e5\u7968\u52a9\u624b https://github.com/0xHJK/x12306\n\n Example\uff1apython x12306.py -f \u4e0a\u6d77 -t \u5317\u4eac -d \"2019-03-01\" -n \"G16 G18 G22\" -r\n\n \u5982\u679c\u67e5\u8be2\u5931\u8d25\u7684\u8bdd\uff0c\u8bf7\u4fee\u6539glovar.py\u4e2d\u7684QUERY_URL\u548cJSESSIONID\n\nOptions:\n --version Show the version and exit.\n -f, --from-station TEXT \u51fa\u53d1\u5730\n -t, --to-station TEXT \u76ee\u7684\u5730\n -d, --date TEXT \u65e5\u671f\n -s, --seats TEXT \u9650\u5236\u5ea7\u4f4d\n -n, --train-no TEXT \u9650\u5236\u8f66\u6b21\n -z, --zmode \u9ad8\u7ea7\u6a21\u5f0f\uff0c\u67e5\u8be2\u4e2d\u95f4\u7ad9\u70b9\n -zz, --zzmode \u7ec8\u6781\u6a21\u5f0f\uff0c\u67e5\u8be2\u6240\u6709\u4e2d\u95f4\u7ad9\u70b9\n -r, --remaining \u53ea\u770b\u6709\u7968\n --gcd \u53ea\u770b\u9ad8\u94c1\u52a8\u8f66\u57ce\u9645\n --ktz \u53ea\u770b\u666e\u5feb\u7279\u5feb\u76f4\u8fbe\u7b49\n --proxies-file TEXT \u4ee3\u7406\u5217\u8868\u6587\u4ef6\n --stations-file TEXT \u7ad9\u70b9\u4fe1\u606f\u6587\u4ef6\n --cdn-file TEXT CDN\u6587\u4ef6\n --help Show this message and exit.\u4f7f\u7528\u793a\u4f8bLICENSEMIT License"} +{"package": "x12-utils", "pacakge-description": "No description available on PyPI."} +{"package": "x13", "pacakge-description": "No description available on PyPI."} +{"package": "x13bcd_hash", "pacakge-description": "No description available on PyPI."} +{"package": "x13-hash", "pacakge-description": "Credits: MaruCoin\u2019s Developer Team:https://github.com/MaruCoinOfficial/x13-hash"} +{"package": "x13-rs-py", "pacakge-description": "No description available on PyPI."} +{"package": "x16cli", "pacakge-description": "X16 Command Line InterfaceX16 Command Line Interface is a tool for assembly projects. Features:Downloading and building of compiler, emulator and romDefault configuration should just workBuild and run with one commandEasy to read configuration fileDetailsThe first command you should use in your project folder isx16 init. X16Cli downloads the compilation tools in a hidden folder and creates atomlconfiguration file.Thehello worldproject does nothing. You are free to start from themain.asmfile.If you want to change thestarting pointyou just have to edit the config file undercompiler.sourcesection.Multiple FilesEvery other.asmfile (except themain) should be added to the config file in themoduleslist. The include files (.inc) shouldn't be added.The modules compiled this way shouldexportthe right symbols (please look at cc65 documentation for that).RequirementsX16Cli is actively developed and tested on Linux Ubuntu. If you are a Mac or Windows user you may consider to help me supporting these platforms too. Thank you.Linux UbuntuPython >= 3.6sudo apt install build-essential gitIf something is missing here, please reach out to me.InstallYou should only need to do this in the right environment:pip install x16cliOr, something like that for user level:pip3 install x16cli --userYou should have thepip3user binary folder in your systemPATHto have easy access tox16script.Getting Startedmkdirmyprj-foldercdmyprj-folder\nx16init\nx16run"} +{"package": "x16r-hash", "pacakge-description": "x16r_hashPython module for the x16r hash functionInstallationpip install x16r_hash"} +{"package": "x16rt-hash", "pacakge-description": "# x16rt_hash\nPython bindings for the x16rt hash function used in Veil cryptocurrency PoW.## Prerequisites` sudoapt-getinstallpython-dev`## InstallationTo install this module, clone this repository and run:` python setup.py install `You can verify the installation by running:` python test.py `"} +{"package": "x16rv2-hash", "pacakge-description": "x16rv2_hashPython module for the x16rv2 hash functionInstallationpip install x16rv2_hash"} +{"package": "x16s-hash", "pacakge-description": "# x16s_hash\nPython module for the x16s hash function## Prerequisites` sudoapt-getinstallpython-dev`## InstallationTo install this module, clone this repository and run:` pip installx16s-hash`"} +{"package": "x17_hash", "pacakge-description": "No description available on PyPI."} +{"package": "x1-icl", "pacakge-description": "enzymeX-1 ML System anywhwereInstallOS - Rocky Linux 9.\nDocker should be installed.git clone -b x1 https://github.com/aregm/enzyme.git\ncd enzyme\n./scripts/deploy/kind.shWhat's in Package?Out of the box X1 will provide an integrated set of Intel-optimized data science libraries:Pandas/ModinScikit-Learn/Intel SciKit-Learn ExtensionsXGBoostIntel PyTorch Extensions/Intel Tensorflow ExtensionsRayMatplotLibQuick startThe cluster's endpoints are accessible only from localhost:http://dashboard.localtest.mehttp://jupyter.localtest.mehttp://minio.localtest.mehttp://prefect.localtest.meIn your browser, navigate tohttp://jupyter.localtest.me.Define a flowCurrently, ICL usesPrefectfor defining basic workflow building blocks:flow and tasks.Create a Python filemy_flow.pythat defines a single flowmy_flow:fromprefectimportflow@flowdefmy_flow():print('Hello from my_flow')Note this is a regular Python file, so it can be developed, tested, and executed locally.Deploy and run a flowThe following code deploys and runs flowmy_flowin the default infrastructure:importx1program=awaitx1.deploy('my_flow.py')awaitprogram.run()Linksdocs/kind.md"} +{"package": "x1prod", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "x20157576-sns-pkg", "pacakge-description": "No description available on PyPI."} +{"package": "x20246935cpplib", "pacakge-description": "No description available on PyPI."} +{"package": "x21", "pacakge-description": "x21"} +{"package": "x21143641PythonLib", "pacakge-description": "No description available on PyPI."} +{"package": "x21145059CppCA", "pacakge-description": "No description available on PyPI."} +{"package": "x21218315", "pacakge-description": "No description available on PyPI."} +{"package": "x21e8", "pacakge-description": "0x21e8 RDDL Interaction ServiceThe 0x21e8 service is usually installed and executed on RDDL compatible hardware wallets (HW-03). The service utilizes the hardware wallet and enables the HW-03 devices to interact with the RDDL network (Planetmint and liquid).Besides the pure wallet functionality it works as the core service to launch any RDDL specific use cases:storage of (un/encrypted) data (w3storage (IPFS))attestation of dataattestation of machinesissuing of tokenslookup of datalookup of tokenscombination of data & tokensThe current version runs with a software-based keystore. Production based versions will use keystores based on secure elements. Initialization and configuration of the keystores is currently enabled via API.The service exposes all features via a RESTFul API. The documentation of the API is exposed via /docs.WARNINGuse this code only for demonstrational purposes. Production code must not rely on this service.Prepare the EnvironmentPlease run the following scripts to install 0x21e8 service ()### For a RPI: some architectures need to get a zenroom and dependencies build from source (glibc compatibility)bashinstall.shThe script basically prepares your system to build the service and installs some requirements for this.Very often, poetry can be used directly without any indication to build some packages from source. Then, the following instruction will be sufficient:curl-sSLhttps://install.python-poetry.org|python3-# installs poetrypoetryinstall\npoetryshellService ConfigurationThe service needs the following configurations:RDDL network planetmint services (RESTFul)RDDL network liquid services (RPC)RPC URLRPC portRPC userRPC passwordweb3storage token to store dataRDDL asset registration endpointRDDL CID resolverRDDL Authentication service to be able to authenticate with EdDSA to RDDL servicesThe configuration is set via environment variables such asLQD_RPC_PORTLQD_RPC_USERLQD_RPC_PASSWORDLQD_RPC_HOSTPLNTMNT_ENDPOINTWEB3STORAGE_TOKENRDDL_ASSET_REG_ENDPOINTCID_RESOLVERRDDL_AUTHAlternatively, the variables can be defined within the.envfile of the project. A exampleenv.examplefile can be adjusted and copied to.env.Service Executionuvicorn--log-leveldebug--reloadx21e8.main:appService deploymentIn order to deploy the service within an production environment adjust the user and group names if needed and execute the following commands:sudocp0x21e8.service/etc/systemd/system# that's the folder where main.py is located withinsudosystemctldaemon-reload\nsudosystemctlenable0x21e8.service\nsudosystemctlstart0x21e8.serviceCurrent state of Liquid Part:The liquid transactions are created the following way:Confidential Address DerivationA master key is generated from a mnemonic phraseThis key is derived once (1) and a child key is acquired.The child key is used to derive a liquid address....Through various steps a confidential address is created. This address is passed along the private key that was used to create the confidential address. This private key is not used anywhere. Apparently, the address is also not used anywhere.Asset Issuancetheissue_assetfunction is called which makes a rpc call in the background. The issue here is the confidential address created before is not used.where do we use the confidential address ? its not used anywhere elseThis part is solely handled by RPC calls.Is the trusted gw also make rpc calls ? or is it going to delegate this to some other backend service ?After we are done here, we get some kind of receipt for our transaction which will be used later on.Asset Id RegistrationThe asset id will be registered to our trusted domain.Is this a one time thing ? Are we going to use the same asset / token for every activity ? As far as i have understood, the asset issuer (r&c) does this only once.Asset Id Registration on Liquid NetworkThe asset id and the corresponding contract is registered on liquid as the final step.Is this also done only by (r&c) and done only once ?It seems like there is a confusion around creating/issuing an asset and actually distributing it to users. The steps here resemble a one-time asset issuance rather than asset distribution (which is called asset re-issuance.\nHere is the official documentation :https://docs.blockstream.com/liquid/developer-guide/developer-guide-index.html#proof-of-issuance-blockstream-s-liquid-asset-registry.\nThe trusted gateway should ask for a re-issuance of token and this service should do it. The hw should focus on generating an address (from a mnemonic), post the planetmint tx first get the id from this tx and send it along the issuance request to the service so the service can determine how much token will be issued. Maybe its not like this and the issued asset represents a NFT on Liquid Network so for every create tx from planet mint there will be another asset issued on Liquid."} +{"package": "x22220445-custom-apparel-calc", "pacakge-description": "Custom Apparel LibraryThe Custom Apparel Library is a Python library for representing custom apparel with pricing. It allows users to create instances of custom apparel, set various attributes such as color, size, neck type, sleeve length, design preference, and custom design details, and calculate the total price based on the chosen options.FeaturesCustomApparel Class: The main class representing custom apparel with pricing.Attributes: Color, size, neck type, sleeve length, design preference, custom design details.Pricing Constants: Additional pricing factors based on neck type, sleeve length, and design preference.Price Calculation: Calculate the total price based on the chosen options and quantity.Installationpipinstallx22220445-custom-apparel-calc"} +{"package": "x23323distributions", "pacakge-description": "No description available on PyPI."} +{"package": "x25519", "pacakge-description": "x25519 (curve25519)A pure Python implemention of curve25519 like Go packagex/crypto/curve25519:packagemainimport(\"fmt\"\"bytes\"\"golang.org/x/crypto/curve25519\")funcmain(){varpublicKey[32]byteprivateKey:=(*[32]byte)(bytes.Repeat([]byte(\"1\"),32))curve25519.ScalarBaseMult(&publicKey,privateKey)fmt.Printf(\"%x\\n\",publicKey)varsharedSecret[32]bytepeerPublicKey:=(*[32]byte)(bytes.Repeat([]byte(\"2\"),32))curve25519.ScalarMult(&sharedSecret,privateKey,peerPublicKey)fmt.Printf(\"%x\\n\",sharedSecret)}/* output:04f5f29162c31a8defa18e6e742224ee806fc1718a278be859ba5620402b8f3aa6d830c3561f210fc006c77768369af0f5b3e3e502e74bd3e80991d7cb7bfa50*/Usage of this package:# this code supports both python 2 and 3frombinasciiimporthexlifyimportx25519private_key=b'1'*32public_key=x25519.scalar_base_mult(private_key)print(hexlify(public_key))peer_public_key=b'2'*32shared_secret=x25519.scalar_mult(private_key,peer_public_key)print(hexlify(shared_secret))'''output:b'04f5f29162c31a8defa18e6e742224ee806fc1718a278be859ba5620402b8f3a'b'a6d830c3561f210fc006c77768369af0f5b3e3e502e74bd3e80991d7cb7bfa50''''Generally, other C implementions are much faster:importpysodiumprivate_key=b'1'*32public_key=pysodium.crypto_scalarmult_curve25519_base(private_key)print(public_key.hex())peer_public_key=b'2'*32shared_secret=pysodium.crypto_scalarmult_curve25519(private_key,peer_public_key)print(shared_secret.hex())'''output:04f5f29162c31a8defa18e6e742224ee806fc1718a278be859ba5620402b8f3aa6d830c3561f210fc006c77768369af0f5b3e3e502e74bd3e80991d7cb7bfa50'''"} +{"package": "x256", "pacakge-description": "x256 can convert colors from rgb or hex to xterm 256 colors, and convert colors from xterm 256 colors to rgb or hex."} +{"package": "x256-img", "pacakge-description": "No description available on PyPI."} +{"package": "x2c", "pacakge-description": "x2c - XML to CSVA simple cli app to convert XML files to CSV, with user-defined columns.UsageIt takes three arguments:-i --infile input file\n -o --outfile output file\n -c --column columnsExample:x2c -i example.xml -o example.csv -c col1,col2,col3The column names must match the xml tags.InstallationThe script can be installed withpip:pip install x2cOr from source (deprecated):python -m setup.py install"} +{"package": "x2cdict", "pacakge-description": "Installationpip3 install --verbose x2cdictUsageEnvironment settingDICT_DB_HOSTis127.0.0.1by defaultDICT_DB_USERisdictby defaultDICT_DB_PASSisturingmachineby defaultDEEPL_AUTH_KEYhas to be set by yourselfThe dictionary db IS NOT BUILT in this project, you HAVE TO install the DB by yourself, refer toBaJiu Dictionary Installation.Binary UsageSearch vocabs with PoS assginedx2cdict_vocab --fromlang en --tolang cn --pos ADJ --word happy --external False\nx2cdict_vocab --helpSearch vocabs without PoSx2cdict_vocab_without_pos --fromlang en --tolang cn --word happy --external False\nx2cdict_vocab_without_pos --helpSearch phrasex2cdict_phrase --fromlang en --tolang cn --phrase \"overcome the problem\"\nx2cdict_phrase --helpIssuesPATH issue:The folder where the exectuable is installed may not be in yourPATH. For Linux, check the$HOME/.local/binto see whether the executablex2cdict_*is installed.Addexport PATH=\"$HOME/.local/bin:$PATH\"in$HOME/.bashrchpack issue:pip3 uninstall hpack\npip3 install hpack==3.0.0Package Usagefrom x2cdict import VocabDict, PhraseDict\ndef search_vocab(word, pos, fromlang, tolang, external):\n vd = VocabDict(fromlang, tolang)\n r = vd.search(word, pos, external)\n print(r)\n\ndef search_vocab_without_pos(word, fromlang, tolang, external):\n vd = VocabDict(fromlang, tolang)\n r = vd.search_without_pos(word, external)\n print(r)\n\ndef search_phrase(phrase, fromlang, tolang):\n vd = PhraseDict(fromlang, tolang)\n r = vd.search(phrase)\n print(r)From above,externalis a boolean variable to switch whether using external translation, default isTrue.DevelopmentClone the projectgit clone https://github.com/qishe-nlp/x2cdict.gitInstallpoetryInstall dependenciespoetry updateTestpoetry run pytest -rPwhich run tests undertests/*Executepoetry run x2cdict_vocab --help\npoetry run x2cdict_vocab_without_pos --help\npoetry run xc2dict_phrase --helpBuildChangeversioninpyproject.tomlx2cdict/__init__.pytests/test_x2cdict.pyBuild python package bypoetry buildPublish from local dev envSet pypi test environment variables in poetry, refer topoetry docPublish to pypi test bypoetry publish -r testPublish through CIGithub action build and publish package totest pypi repogit tag [x.x.x]\ngit push origin masterManually publish topypi repothroughgithub action"} +{"package": "x2embedding", "pacakge-description": "\ud83d\udd25x2embedding\ud83d\udd25Installpipinstall-Ux2embeddingDocsUsagesfrom x2embedding.zoo import Bert4Vec\n\ns2v = Bert4Vec()\ns2v.encode(['\u4e07\u7269\u7686\u53efembedding'])TODO=======\nHistory0.0.0 (2022-03-15)First release on PyPI."} +{"package": "x2graph", "pacakge-description": "x2graphPython library of creating graph objects from dataCreated byBaihan Lin, Columbia University"} +{"package": "x2paddle", "pacakge-description": "X2Paddle is a toolkit for converting trained model to PaddlePaddle from other deep learning frameworks.Usage: x2paddle --framework tensorflow --model tf_model.pb --save_dir paddle_modelGitHub: https://github.com/PaddlePaddle/X2PaddleEmail: dltp-sz@baidu.com"} +{"package": "x2paper", "pacakge-description": "x2paperPython library of academic reference and note management systemCreated byBaihan Lin, Columbia University"} +{"package": "x2polygons", "pacakge-description": "This Python package allows the calculation of distance between two polygons. Polygons may have thematic attributes (e.g. name) to add further description.The available geometric distance functions between polygons are:Hausdorff distanceChamfer distancePoLis distanceTurn function distanceThe avaiable thematic distance functions are:Levenshtein distanceFor Windows:Follow the steps describedhereto download geopandas.Resolve thegeos_c.dll file missingerror by runningconda install shapelyas describedhere."} +{"package": "x2prod", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "x2py", "pacakge-description": "No description available on PyPI."} +{"package": "x2t", "pacakge-description": "No description available on PyPI."} +{"package": "x2vec", "pacakge-description": "x2vecPython library of word2vec-based similiarity embeddingsCreated byBaihan Lin, Columbia University"} +{"package": "x2webrtc", "pacakge-description": "x2webrtcx2webrtc is a command-line tool for forwarding an X window as a media track through WebRTC.\nIt is a simple tool; it just grabs screenshots for the window with Xlib and send them via a WebRTC stream, but it can realize the following features:You can send an X window through the NAT.A media stream is transported using a secure method. (compared to the standard VNC)You can easily install it by pip.You don't necessarily have admin access to the system.InstallNote that Python 3.6+ and X Window System are required to use the tool.pipinstallx2webrtcThe tool requiresaiortcto work with WebRTC.\nPlease refer tothe install instructionofaiortcif you failed to install it automatically.QuickstartNOTE:\nCurrently, hand signaling is required to start a WebRTC session.\nI am planning to implement a plug-in system so that a user can customize its signaling method.Start x2webrtc.x2webrtcforwardIfDISPLAYenvironment is not set to your environment, pass--displayargument to specify an X server.x2webrtcforward--display:0(tentative) Copy a WebRTC offer.\nYou will see the following message on your terminal:--Pleasesendthismessagetotheremoteparty--{\"sdp\":\"...\",\"type\":\"offer\"}Please copy the offer json.(tentative) Openthe web viewerand clickConnectbutton.(tentative) Paste the offer json intoInput Offertext-area (A) and clickCreate Answerbutton (B). Then you will get an answer json (C). Copy the json again.(tentative) Go back to your terminal. Paste the answer json into the terminal, then press Enter.Now you will see your screen in the web viewer.Usageusage:x2webrtc[-h][-v]COMMANDS...\n\nCommands:forwardforwardXWindowinfoshowwindowinformationoftheXserver\n\noptionalarguments:-h,--helpshowthishelpmessageandexit-v,--verboseverbose;canbeusedupto3timestoincreaseverbosityx2webrtc forwardForward a specified X window.usage:x2webrtcforward[-h][--displayDISPLAY]optionalarguments:-h,--helpshowthishelpmessageandexit--displayDISPLAYdisplay_nameoftheXservertoconnectto(e.g.,hostname:1,:1.)x2webrtc infoShow information on a specified X server.usage:x2webrtcinfo[-h][--displayDISPLAY][--props]optionalarguments:-h,--helpshowthishelpmessageandexit--displayDISPLAYdisplay_nameoftheXservertoconnectto(e.g.,hostname:1,:1.)--propsshowallpropertiesofeachwindowConfigurationThe order of preference is the$X2WEBRTC_CONFIGenvironment variable, then.x2webrtcfile of the working directory, and then~/.x2webrtc.\nThe config file must be in the YAML format.\nHere is an example of a configuration file:signaling_plugin:\"path/to/signaling_plugin.py\"# optionalpeer_connection:# optionalice_servers:-url:stun:stun.example.com-url:turn:turn.example.comusername:shamiko# optionalcredential:momo# optionalFor more details, please refer tox2webrtc/config.py.PluginYou can customize the signaling method that x2webrtc uses for a WebRTC peer connection by using a plugin.\nHere is an example of a plugin implementation:fromtypingimportTypefromaiortcimportRTCPeerConnectionfromx2webrtc.pluginimportSignalingPluginclassSomePlugin(SignalingPlugin):asyncdef__call__(self,pc:RTCPeerConnection)->bool:returnTruedefplugin()->Type[SignalingPlugin]:returnSomePluginA plugin file must have apluginfunction that returns a subclass ofSignalingPlugin.\nThe plugin file is required to specify in a configuration file, as already mentioned in the Configuration section.For more details, please refer toCopyAndPasteSignalingclass located inx2webrtc/signaling.py.FAQFailed to install PyAVPyAVusesAV_CODEC_CAP_HARDWAREmacro in its source code, but it seems to be available inlibavcodec >= 58.0. Check the version of libavcodec and try again."} +{"package": "x2wincur", "pacakge-description": "Usewin2xcurinstead."} +{"package": "x2x", "pacakge-description": "x2xCommands to convert radixes.x2b - convert to binaryx2o - convert to octalx2d - convert to decimalx2h - convert to heaxadecimalx2x - convert any radix to any radixInstallingPyPIpip install x2xFrom sourcepython setup.py installVersions0.9 (Jan, 2016)first release"} +{"package": "x2y", "pacakge-description": "Convert line ending between DOS, Mac (pre OS X) and UnixWhere:DOS = \u2018\\r\\n\u2019Mac = \u2018\\r\u2019 (OS9)Unix = \u2018\\n\u2019Note: Mac here is OS9 and earlier. OS X line endings are Unix.ExamplesConvert From Unix To DOS Line Endings$x2y-funx-tdosfile.txtThe above command will convert Unix line ending to DOS line endings. The\nresult is written back in to the source file.If you want to write to another file use the -o or -d options (see\nbelow).$x2y-ooutput.txt-funx-tdosfile.txtWill write the converted file to output.txt$x2y-doutputs-funx-tdosfile.txtWill save converted files to the outputs directory.To back up the source file use the -b option. For example:$x2y-bbak-funx-tdosfile.txtWill rename the source file with a \u201c.bak\u201d extensions before writing the\nconverted file.Installationpipinstallx2yUsageusage:x2y[options]--fromline-ending--toline-endingFile[File...]x2y:convertlineendingbetweenDOS,Mac(preOSX)andUnixpositionalarguments:FileFilestoconvertoptionalarguments:-h,--helpshowthishelpmessageandexit--versionshowprogram'sversionnumberandexit--debugTurnondebuglogging.--debug-logFILESavedebugloggingtoFILE.-bBACKUPEXTENTSION,--backupBACKUPEXTENTSIONSaveabackupoftheinputfilebyrenamingwithBACKUPEXTENTSION.Ignoredifthe-ooptionisgiven.Default:None.-dDIRECTORY,--directoryDIRECTORYSaveextractedtexttoDIRECTORY.Ignoredifthe-ooptionisgiven.-f{dos,mac,unx},--from{dos,mac,unx}Lineendingtoconvertfrom.-oFILE,--outputFILESaveextractedtexttoFILE.Ifnotgiven,theoutputfileisnamedthesameastheinputfilebutwithatxtextension.Theextensioncanbechangedwiththe-eoption.Filesareopenedinappendmodeunlessthe-Xoptionisgiven.-t{dos,mac,unx},--to{dos,mac,unx}Lineendingtoconvertto.-A,--suppress-file-access-errorsDonotprintfile/directoryaccesserrors."} +{"package": "x3d", "pacakge-description": "Python packagex3dThis project creates thePython X3D Packagewhich is available for import viaPyPi.Web3D Consortiummaintains this package under a BSD-styleopen-source license.Package installation (choose one)pip install x3dpython -m pip install x3dPackage upgrade (choose one)pip install x3d --upgradepython -m pip install x3d --upgradeDeveloper NotesPackagex3d.pyprovides full support for theExtensible 3D (X3D) GraphicsInternational Standard.This package is also known asX3DPSAIL, X3D Python Scene Access Interface Library.Code is autogenerated fromX3D Unified Object Model (X3DUOM)matching next-generationX3D4.ContactDesigners and package maintainers:Don Brutzman and Loren Peitso NPSMail list:x3d-public@web3D.org(subscribe)Contributors are gratefully acknowledged: Masaki Aono, John Carlson, Hans Moritz Guenther, Myeong Won Lee, Rick Lentz, and Vince Marchetti"} +{"package": "x3dase", "pacakge-description": "x3dasePython module for drawing and rendering atoms and molecules objects using X3DOM. X3dase can be used as a viewer for the molecule structure in the Jupyter notebook.Functions:Support all file-formats using by ASE, including cif, xyz, cube, pdb, json, VASP-out and so on.Ball & stickSpace fillingPolyhedralIsosurfaceShow element and indexMeasure distance and angleAnimationFor the introduction of ASE , please visithttps://wiki.fysik.dtu.dk/ase/index.htmlAuthorXing Wangxingwang1991@gmail.comDependenciesPythonASESkimageInstallation using pippipinstall--upgrade--userx3daseInstallation from sourceYou can get the source using git:gitclonehttps://github.com/superstar54/x3dase.gitThen add it to your PYTHONPATH and PATH. On windows, you can edit the system environment variables.exportPYTHONPATH=/path-to-x3dase:$PYTHONPATHExamplesDraw molecule in Jupyter notebooksShortcutkeyfunctionbball-and-stick modelsspacefilling modelppolyhedra model1view top2view front3view right4view element5view indexShow different modelsMeasure distance and angle between atomsUsing Ctrl + click to select atoms.Selectionmeasurementsingle atomxyz position and atomic symboltwo atomsinteratomic distancethree atomsthree internal anglesPolyhedra for crystalIsosurface for electron densityAnimationimages=[atoms1,atoms2,atoms3]X3D(images)"} +{"package": "x3deep", "pacakge-description": "No description available on PyPI."} +{"package": "x3-profit-review", "pacakge-description": "x3 profit reviewpip3x3profitreview"} +{"package": "x448-python", "pacakge-description": "x448-pythonImplementation of x448 formerly used withinnoiseprotocol package.Although it should be compliant with RFC 7748 and is tested (on import) with the vectors provided in RFC, these are all the promises you can get. The implementation may be vulnerable to side channel attacks or worse. You have been warned."} +{"package": "x4i3", "pacakge-description": "x4i3 - The EXFOR Interface [for Python 3]This packagex4i3is a fork of the originalx4ideveloped by David A. Brown (LLNL, Livermore CA, 94550). This pure python software acts as an interface toExperimental Nuclear Reaction Data (EXFOR)that theInternational Atomic Energy Agency (IAEA)actively maintains.The database resembles a collection of experimental and evaluated nuclear data files in the EXFOR format (*.x4), a structured markup language. The mark-up language is quite complex and the data has legacy issues, such as data sets entered by hand or issues with the strict alignment criteria of FORTRAN-era punch cards. The documentation by David A. Brown describes a few basics of the format. Please use thisdocumentation, the references therein and the other files in thedocfolder. Please also cite the papers about the database if you use these data in your research.The main purpose of this fork is to ensure that such a valuable and complex tool does stays available. Also, the original link for this code is dead and Python 2 is deprecated. As a standalone pure Python package on pip, it may cure derived works from a potential GPL infection.Latest release 1.2.0Update to EXFOR database version dated 2021/03/08.HistoryThis fork emerged originally in 2016 when we tried to benchmark current photo-nuclear interaction codes against experimental data in a project related to Ultra-High Energy Cosmic Rays. One paper that came outhas a quite useful plot (Figure 1). Actually, this figure isan interactive matplotlib applicationthat used the originalx4ias a backend. When a box is clicked x4i gathers experimental data from EXFOR, applies some filtering and visualizes the data against pre-computed model predictions.ExamplesNothing very useful yet. To check out if the installation is successful, try:python examples/get-entry.py --data -s 10504002It should print some fission cross section to stdout.Contributions..are welcome. Also feel free to say hi since I don't know if there is a community who may find this interface useful.Currently there is no development goals beyond basic maintenance.Requirements~1 GB of hard drive spaceInstallationpip install x4i3Note that on first import ~600MB will be downloaded and 22k files will be decompressed to the data directory.Support toolsTo reduce the weight of this package, the database management tools have been moved to a different projectx4i3_toolssince these are for advanced users anyways.DocumentationThere is currently no separate documentation forx4i3. Please use the originaldocumentation. The installation instruction are not valid anymore. There is a detailed but auto-generatedAPI-doc documentation. Untar and enjoy theindex.htmlif you need this.AuthorsDavid A. Brown (LLNL)(x4i)Anatoli Fedynitch(x4i3)Copyright and licenseThis code is distributed under theGNU General Public License (GPLv2) (see LICENSE)without any warranty or guaranty. The full disclaimer and license information is located in theLICENSE. Very unfortunately, the original code is GPLv2 infecting in a nontransparent way all derived works such as this. Be warned!"} +{"package": "x4xl", "pacakge-description": "x4xlA simple tool to ease import/export operation to and from Excelx4xl is simple toolset that wraps an import/export workflow from excel into Pandas Dataframe objects and vice-versa.\nIt is composed of two main routines:loadExcelSheet(file, sheet, parsef)\n\nsaveExcelSheet(file, sheet, parsef)x4d3sign @ 2023"} +{"package": "x5", "pacakge-description": "x5 NexT Gen Project Manager"} +{"package": "x509", "pacakge-description": "This is a fork of a fork of a fork of the original project:py3x509 - Python library for parsing X.509\nCopyright (C) 2009-2012 CZ.NIC, z.s.p.o. (http://www.nic.cz)Forked fromhttps://github.com/ph4r05/px509Forked fromhttps://github.com/erny/pyx509Forked fromhttps://github.com/hiviah/pyx509Updates by me rename the module to \u2018x509\u2019 and update to Python3 only.Copyright (C) 2017 (https://github.com/cniemira/py3x509)Work in progress!DescriptionThis is probably the most complete parser of X.509 certificates in python.Code is in alpha stage! Don\u2019t use for anything sensitive. I wrote it (based on\nprevious work of colleagues) since there is no comprehensive python parser for\nX.509 certificates. Often python programmers had to parse openssl output.AdvantagesI find it less painful to use than parsing output of \u2018openssl x509\u2019\nsomewhat stricter in extension parsing compared to opensslDisadvantagesIt\u2019s slow compared to openssl (about 2.3x compared to RHEL\u2019s openssl-1.0-fips)Currently not very strict in what string types in RDNs it acceptsAPI is still rather ugly and has no documentation yet; code is nasty at some\nplaces (and there\u2019s some old dangling code like pkcs7/verifier.py)Dependenciespyasn1 >= 0.1.7InstallationInstall with pip:pip install py3x509LicenseLGPL v2 or later.See LICENSE.txt.Known bugs and quirksSubject alternative name doesn\u2019t show all subtypes,\nbut \u2018DNS\u2019, \u2018dirName\u2019 and \u2018email\u2019 are supported.Name constraints don\u2019t distinguish among various GeneralName subtypesSome extensions are not shown very nicely when put in string formatNot all extensions are supportedString types accepted for various RDN subelements are rather too permissiveRDN string conversion does not conform to RFC 4514Badly formed extensions are ignored if not marked criticaleasy to switch to more strict behaviorother clients do this as well; RFC 5280 specifies behavior for unknown\nelements in extensions in appendix B.1, but does not cover all cases (e.g.\nelement exists, but with string type different from spec)TODOCleanup: This module has it\u2019s own pyasn1 models. Look if we can\nreuse the pyasn1_modules.rfc2459 X509 cert model.Cleanup: Currently, the signature verifier does not work."} +{"package": "x5092json", "pacakge-description": "x5092jsonProvides a parser and JSON serializer for x509 certificates.This tool can be used to creating a large database of analyzed\ncertificates. Provides a command-line tool as well as an importable\nmodule. Over 400 Million certificates parsed so far.MotivationPyCA-Cryptography (https://github.com/pyca/cryptography) provides a\nfull set of cryptographic operations for Python programmers, but the\nfocus of that library is on safety and correctness. For that reason,\nmany certificates which one finds \"in the wild\" are not intializable\nas cryptography objects out-of-the-box. The x5092json package takes\nthe safety belts off of cyrptography to provide a parser which is\nrobust to the nonsense which one finds when processing the X509\ncertificates deployed in the wilds of the Internet.InstallationRequires Python3. Tested against Python3.5, 3.6, 3.7. May work\nagainst earlier Py3Ks. Because this package relies on pyOpenSSL,\nwhich relies on libssl C bindings, your system will need to be able to\nbuild a wheel. That, in turn, may require such header files asand. See your distribution's\npackage manager for these dependencies (or, in the future, I may be\nable to push out a pre-compiled package for some systems)---file an\nissue if you are interested in this.From PyPI:$pip3installx5092jsonFrom source :$gitclonehttps://github.com/jcrowgey/x5092jsonUsageCan be used as a command line tool:$catmycert.pem|x5092jsonFor example, the above invocation reads a PEM formatted x509\nCertificate from STDIN by default, the JSON document is printed on\nSTDOUT.Can also be imported as a module within a python program.fromx5092jsonimportx509parser# load a pem file from the filesystemf=open('mycert.pem',mode='rb')cert=x509parser.load_certificate(f)x509parser.parse(cert)See the manual for more usage examples and options.AuthorJoshua Crowgey"} +{"package": "x509creds", "pacakge-description": "Python x509 utilities to work load, dump a certificate, key and trust chain that can be used as credentials"} +{"package": "x509generator", "pacakge-description": "No description available on PyPI."} +{"package": "x509middleware", "pacakge-description": "x509middleware: Working with (client) certificatesThis Python package contains middleware classes for working with\ncertificates. Currently it only contains support for extracting client\ncertificates from the ASGI scope and from headers set by a reverse\nproxy.Note: The package is rather small but solves an immediate need for some\nprojectes of mine while possibly being generally helpful to other\npeople. As I chose a rather generic package name, patches or pull\nrequests with support for other protocols than ASGI as well as\nadditional functionallty are very welcome.Installation$pipinstallx509middlewareRequirementsPython v3.3+ (only 3.6+ is beingtested).Theasn1cryptopackage.Contentsx509middleware.asgi.ClientCertificateMiddlewareThis middlware class will try to find and parse a client certificate for\na ASGI http or websocket request. It supports the proposedtls extensionto the ASGI\nprotocol as well as pulling the certificate from a header supplied by a\nreverse proxy your app is deployed behind.It will set the keyscope['client_cert']to aasn1crypto.x509.Certificateobject orNoneif it can't find or parse\na certificate.Parametersapp(async callable)\u2013 ...use_tls_extension(bool=True)\u2013 ...proxy_header(str=None)\u2013 Name of the header to try parsing as a\nclient certificate orNoneto disable proxy header support. The\nheader value can be line-folded, URL/percent-encoded or base64 encoded\nas well as in PEM or DER format. The correct way to decode will be\ndetected automatically.Configuring your reverse proxyYou will need to choose a header name when configuring your reverse proxy\nas well as the middlware class. Commonly used names are:CLIENT-CERT\u2013IETF Draft.X-SSL-CLIENT-CERTX-CLIENT-CERTX-CLIENT-CERTIFICATEX-CLIENT-CRTX-SSL-CERTSSLClientCertb64\u2013 F5 products seem to use or suggest this.Apache / mod_proxy & mod_headersProxyPass/http://127.0.0.1:8000/RequestHeaderunsetCLIENT-CERTRequestHeadersetCLIENT-CERT\"%{SSL_CLIENT_CERT}s\"NGINXlocation/{proxy_passhttp://127.0.0.1:8000/;proxy_set_headerCLIENT-CERT$ssl_client_escaped_cert;}HAProxySupport for passing the certificate as a DER blob is available starting\nversion 1.6-dev1. Since DER is a binary format this needs to be base64\nencoded.backend back\n mode http\n server app 127.0.0.1:8000\n http-request set-header CLIENT-CERT %[ssl_c_der,base64]Using it in Starlettefromstarlette.applicationsimportStarlettefromstarlette.configimportConfigfromstarlette.middlewareimportMiddlewarefromstarlette.responsesimportResponsefromstarlette.routingimportRoutefromx509middleware.asgiimportClientCertificateMiddlewareasyncdefhello_common_name(request):client_cert=request.scope.get('client_cert')ifclient_cert:cn=client_cert.subject.native['common_name']else:cn='unknown'returnResponse(f'Hello,{cn}!',media_type='text/plain')config=Config('.env')app=Starlette(routes=[Route('/',hello_common_name)],middleware=[Middleware(ClientCertificateMiddleware,proxy_header=config('CLIENT_CERT_HEADER',default=None))])Using it directlyfromosimportenvironfromx509middleware.asgiimportClientCertificateMiddlewareasyncdefhello_common_name(scope,receive,send):client_cert=scope.get('client_cert')ifclient_cert:cn=client_cert.subject.native['common_name']else:cn='unknown'awaitsend({'type':'http.response.start','status':200,'headers':[(b'content-type',b'text/plain; charset=utf-8'),]})awaitsend({'type':'http.response.body','body':f'Hello,{cn}!'.encode('utf8'),})app=ClientCertificateMiddleware(hello_common_name,proxy_header=environ.get('CLIENT_CERT_HEADER'),)"} +{"package": "x509sak", "pacakge-description": "x509sakX.509 Swiss Army Knife (x509sak) is a toolkit written in Python that acts as a\nboilerplate on top of OpenSSL to ease creation of X.509 certificates,\ncertificate signing requests and CAs. It can automatically find CA chains and\noutput them in a specifically desired format, graph CA hierarchies and more.The tool is used similarly to OpenSSL in its syntax. The help page is meant to\nbe comprehensive and self-explanatory. These are the currently available commands:$ ./x509sak.py\nError: No command supplied.\nSyntax: ./x509sak.py [command] [options]\n\nAvailable commands:\n\nversion: x509sak v0.0.2\n\nOptions vary from command to command. To receive further info, type\n ./x509sak.py [command] --help\n buildchain Build a certificate chain\n graph Graph a certificate pool\n findcrt Find a specific certificate\n createca Create a new certificate authority (CA)\n createcsr Create a new certificate signing request (CSR) or\n certificate\n signcsr Make a certificate authority (CA) sign a certificate\n signing request (CSR) and output the certificate\n revokecrt Revoke a specific certificate\n createcrl Generate a certificate revocation list (CRL)\n genbrokenrsa Generate broken RSA keys for use in penetration testing\n genbrokendsa Generate broken DSA parameters for use in penetration\n testing\n dumpkey Dump a key in text form\n examinecert Examine an X.509 certificate\n forgecert Forge an X.509 certificate\n scrape Scrape input file for certificates, keys or signatures\n hashpart Hash all substrings of a file and search for a\n particular hash valueDependenciesx509sak requires Python3, pyasn1 and pyasn1_modules support. It also relies on\nOpenSSL. If you want graph support, then you also need to install the Graphviz\npackage as well. Note that pyasn1_modules inside the Ubuntu tree (up until\n3'2018, Ubuntu Artful MATE, v0.0.7-0.1) is broken and you'll need to use a\nnewer version (0.2.1 works). In later Ubuntu versions (Bionic) this is already\nincluded by default:# apt-get install openssl python3-pyasn1 python3-pyasn1-modules graphvizIf you want to run all the tests, you should also have SoftHSM2, OpenSC and the\nPKCS#11 OpenSSL engine driver installed to be able to do PKCS#11 testing:# apt-get install opensc softhsm2 libengine-pkcs11-opensslUsing x509sak with hardware tokensx509sak works nicely with hardware tokens such as the NitroKey HSM. It does not\nallow key generation for these devices, but can use the pre-generated keys for\nCA management. For example, let's say you used atool like\nnitrotoolto generate an ECC\nkeypair that is called \"my_secure_key\". You now want a CA that's based off that\nkey. Quite an easy task:$ ./x509sak.py createca -w \"pkcs11:object=my_secure_key;type=private\" -s \"/CN=My Secure CA\" my_secure_ca\nEnter PKCS#11 token PIN for UserPIN (SmartCard-HSM): 123456You enter your Pin, hit return and it's done! The CA has been created:$ openssl x509 -in my_secure_ca/CA.crt -text -noout\nCertificate:\n Data:\n Version: 3 (0x2)\n Serial Number:\n c3:86:c2:43:4b:2d:62:12\n Signature Algorithm: ecdsa-with-SHA256\n Issuer: CN = My Secure CA\n Validity\n Not Before: Jul 14 10:47:49 2018 GMT\n Not After : Jul 14 10:47:49 2019 GMT\n Subject: CN = My Secure CA\n Subject Public Key Info:\n Public Key Algorithm: id-ecPublicKey\n Public-Key: (256 bit)\n pub:\n 04:8a:8f:c7:99:3b:b1:cf:63:5f:c7:c8:87:50:80:\n 26:4d:22:96:9f:2f:67:f8:ea:f6:f2:1b:96:e4:e2:\n 4b:af:15:fe:79:77:52:50:d1:f6:a3:20:7b:ca:ce:\n 5e:bc:25:5e:30:2d:1a:71:cb:8f:ff:79:46:4f:ec:\n 58:04:e1:f7:f0\n ASN1 OID: prime256v1\n NIST CURVE: P-256\n X509v3 extensions:\n X509v3 Basic Constraints: critical\n CA:TRUE\n X509v3 Key Usage: critical\n Digital Signature, Certificate Sign, CRL Sign\n X509v3 Subject Key Identifier: \n 9B:4E:14:4E:0D:C5:23:D9:06:06:06:7D:39:8F:3C:88:1D:66:35:55\n Signature Algorithm: ecdsa-with-SHA256\n 30:45:02:20:79:a2:91:1e:ca:2d:18:5b:26:59:14:b1:f1:0c:\n 2f:0f:41:d8:ab:bc:02:2f:e9:c2:dc:97:c1:19:67:9e:c7:8d:\n 02:21:00:ef:73:02:6a:a4:ad:e8:f0:ef:49:02:cf:34:08:b7:\n 2e:fa:82:16:47:8c:44:7f:bb:ad:f0:c0:be:7a:e6:e1:81It's similarly easy to create certificates off this hardware-backed CA:$ ./x509sak.py createcsr -s \"/CN=Software Key Client\" -t tls-client -c my_secure_ca client.key client.crt\nEnter PKCS#11 token PIN for UserPIN (SmartCard-HSM):Again, with one command you've created the client certificate:$ openssl x509 -in client.crt -text -noout\nCertificate:\n Data:\n Version: 3 (0x2)\n Serial Number: 1 (0x1)\n Signature Algorithm: ecdsa-with-SHA256\n Issuer: CN = My Secure CA\n Validity\n Not Before: Jul 14 10:50:19 2018 GMT\n Not After : Jul 14 10:50:19 2019 GMT\n Subject: CN = Software Key Client\n Subject Public Key Info:\n Public Key Algorithm: id-ecPublicKey\n Public-Key: (384 bit)\n pub:\n 04:5a:68:1b:f2:ea:29:71:23:39:66:bd:b7:6a:9c:\n 0c:69:8d:a9:e8:7f:93:a8:32:21:d7:f2:93:e8:52:\n c5:83:65:7b:13:62:04:9f:64:c6:54:fd:24:8a:64:\n d2:49:cd:8d:27:61:b3:41:44:d3:89:51:39:78:29:\n b2:ff:1a:3a:b6:e0:74:c6:15:92:26:f9:42:2b:0d:\n 04:74:1b:3d:13:f8:78:53:a5:be:6f:13:04:01:05:\n f7:40:4b:6a:89:4c:54\n ASN1 OID: secp384r1\n NIST CURVE: P-384\n X509v3 extensions:\n X509v3 Authority Key Identifier: \n keyid:9B:4E:14:4E:0D:C5:23:D9:06:06:06:7D:39:8F:3C:88:1D:66:35:55\n\n X509v3 Basic Constraints: critical\n CA:FALSE\n X509v3 Extended Key Usage: \n TLS Web Client Authentication\n X509v3 Key Usage: critical\n Digital Signature, Key Encipherment, Key Agreement\n Netscape Cert Type: \n SSL Client\n X509v3 Subject Key Identifier: \n 0C:1F:31:4C:BA:E2:C6:33:65:9D:ED:DA:FC:16:29:27:E0:95:AF:E2\n Signature Algorithm: ecdsa-with-SHA256\n 30:44:02:20:3f:84:40:bb:50:2e:7c:8c:3b:2f:51:80:f9:20:\n a7:bb:7d:17:58:c6:44:70:20:eb:74:46:5a:ae:95:4e:9e:81:\n 02:20:0c:98:35:63:8d:2f:1b:ad:32:d4:06:2f:c8:e7:2c:8a:\n 79:b7:5a:e0:21:51:63:0b:39:82:9f:ff:8d:ee:c3:e2For simplicity, you can specify either a full pkcs11-URI according to RFC7512\nor you can use certain abbreviations that make it easier. All of the following\nwork for a key that's named 'my key' and that has ID 0xabcd:pkcs11:object=my%20key;type=private\npkcs11:id=%ab%cd;type=private\nlabel=my key\nid=0xabcd\nid=43981The latter variants (label=..., id=...) will automatically be converted to\npkcs11 URIs internally.buildchainThe \"buildchain\" command is useful if you want to have a complete (or partial)\ncertificate chain from a given leaf certificate and a bundle of CAs. x509sak\nwill figure out which of the CAs are appropriate (if any) and generate a chain\nin the order you want (root to leaf or leaf to root) including the certs you\nwant (e.g., all certificates, all except root cert, etc.). This is useful if\nyou have, for example, a webserver certificate and want to automatically find\nthe chain of trust that you can use to deploy on your webserver.usage: ./x509sak.py buildchain [-s path] [--inform {pem,der}]\n [--order-leaf-to-root] [--allow-partial-chain]\n [--dont-trust-crtfile]\n [--outform {rootonly,intermediates,fullchain,all-except-root,multifile,pkcs12}]\n [--private-key filename]\n [--pkcs12-legacy-crypto]\n [--pkcs12-no-passphrase | --pkcs12-passphrase-file filename]\n [-o file] [-v] [--help]\n crtfile\n\nBuild a certificate chain\n\npositional arguments:\n crtfile Certificate that a chain shall be build for, in PEM\n format.\n\noptional arguments:\n -s path, --ca-source path\n CA file (PEM format) or directory (containing\n .pem/.crt files) to include when building the chain.\n Can be specified multiple times to include multiple\n locations.\n --inform {pem,der} Specifies input file format for certificate. Possible\n options are pem, der. Default is pem.\n --order-leaf-to-root By default, certificates are ordered with the root CA\n first and intermediate certificates following up to\n the leaf. When this option is specified, the order is\n inverted and go from leaf certificate to root.\n --allow-partial-chain\n When building the certificate chain, a full chain must\n be found or the chain building fails. When this option\n is specified, also partial chain matches are\n permitted, i.e., not going up to a root CA. Note that\n this can have undesired side effects when no root\n certificates are found at all (the partial chain will\n then consist of only the leaf certificate itself).\n --dont-trust-crtfile When there's multiple certificates in the given\n crtfile in PEM format, they're by default all added to\n the truststore. With this option, only the leaf cert\n is taken from the crtfile and they're not added to the\n trusted pool.\n --outform {rootonly,intermediates,fullchain,all-except-root,multifile,pkcs12}\n Specifies what to write into the output file. Possible\n options are rootonly, intermediates, fullchain, all-\n except-root, multifile, pkcs12. Default is fullchain.\n When specifying multifile, a %d format must be\n included in the filename to serve as a template;\n typical printf-style formatting can be used of course\n (e.g., %02d).\n --private-key filename\n When creating a PKCS#12 output file, this private key\n can also be included. By default, only the\n certificates are exported.\n --pkcs12-legacy-crypto\n Use crappy crypto to encrypt a PKCS#12 exported\n private key.\n --pkcs12-no-passphrase\n Do not use any passphrase to protect the PKCS#12\n private key.\n --pkcs12-passphrase-file filename\n Read the PKCS#12 passphrase from the first line of the\n given file. If omitted, by default a random passphrase\n will be generated and printed on stderr.\n -o file, --outfile file\n Specifies the output filename. Defaults to stdout.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.graphThe graph utility can be used to plot multiple certificates and their\ncertificate hierarchy. Some metadata is displayed within the graph as well.\nHere's an example of some certificates that I've plotted:usage: ./x509sak.py graph [-c {certtype,expiration,keytype,sigtype}]\n [--abbreviate-to charcnt] [-l text]\n [-f {dot,png,ps,pdf}] -o file [-v] [--help]\n crtsource [crtsource ...]\n\nGraph a certificate pool\n\npositional arguments:\n crtsource Certificate file (in PEM format) or directory\n (containting PEM-formatted .pem or .crt files) which\n should be included in the graph.\n\noptional arguments:\n -c {certtype,expiration,keytype,sigtype}, --color-scheme {certtype,expiration,keytype,sigtype}\n Color scheme to use when coloring the certificates.\n Can either color by expiration date, by certificate\n type (client/server/CA/...), key type (RSA/ECC/etc),\n signature type (used hash function) or overall\n security level. Defaults to expiration.\n --abbreviate-to charcnt\n Abbreviate each line to this amount of characters.\n Defaults to 30 characters.\n -l text, --label text\n Label that is printed in the certificate nodes. Can be\n given multiple times to specify multiple lines.\n Substitutions that are supported are derhash,\n filebasename, filename, subject, subject_rfc2253,\n valid_not_after. Defaults to ['%(filebasename)s\n (%(derhash)s)', '%(subject)s', '%(valid_not_after)s'].\n -f {dot,png,ps,pdf}, --format {dot,png,ps,pdf}\n Specifies the output file format. Can be one of dot,\n png, ps, pdf. When unspecified, the file extension out\n the output file is used to determine the file type.\n -o file, --outfile file\n Specifies the output filename. Mandatory argument.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.findcrtWhen looking for a bunch of certificates (some of which might be in PEM format)\nby their authoritative hash (i.e., the SHA256 hash over their\nDER-representation), findcrt can help you out. You specify a bunch of\ncertificates and the hash prefix you're looking for and x509sak will show it to\nyou.usage: ./x509sak.py findcrt [-h hash] [-v] [--help] crtsource [crtsource ...]\n\nFind a specific certificate\n\npositional arguments:\n crtsource Certificate file (in PEM format) or directory\n (containting PEM-formatted .pem or .crt files) which\n should be included in the search.\n\noptional arguments:\n -h hash, --hashval hash\n Find only certificates with a particular hash prefix.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.createcaCreating a CA structure that can be used with \"openssl ca\" is tedious. The\n\"createca\" command does exactly this for you in one simple command. The created\nOpenSSL config file directly works with \"openssl ca\" for manual operation but\ncan also be used with other x509sak commands (e.g., creating or revoking\ncertificates). x509sak takes care that you have all the necessary setup files\nin place (index, serial, etc.) and can just as easily create intermediate CAs\nas it can create root CAs.usage: ./x509sak.py createca [-g keyspec | -w pkcs11uri]\n [--pkcs11-so-search path]\n [--pkcs11-module sofile] [-p capath] [-s subject]\n [-d days] [-h alg] [--serial serial]\n [--allow-duplicate-subjects]\n [--extension key=value] [-f] [-v] [--help]\n capath\n\nCreate a new certificate authority (CA)\n\npositional arguments:\n capath Directory to create the new CA in.\n\noptional arguments:\n -g keyspec, --gen-keyspec keyspec\n Private key specification to generate. Examples are\n rsa:1024 or ecc:secp256r1. Defaults to ecc:secp384r1.\n -w pkcs11uri, --hardware-key pkcs11uri\n Use a hardware token which stores the private key. The\n parameter gives the pkcs11 URI, e.g.,\n 'pkcs11:object=mykey;type=private'\n --pkcs11-so-search path\n Gives the path that will be searched for the \"dynamic\"\n and \"module\" shared objects. The \"dynamic\" shared\n object is libpkcs11.so, the \"module\" shared object can\n be changed by the --pkcs11-module option. The search\n path defaults to\n /usr/local/lib:/usr/lib:/usr/lib/x86_64-linux-\n gnu:/usr/lib/x86_64-linux-\n gnu/openssl-1.0.2/engines:/usr/lib/x86_64-linux-\n gnu/engines-1.1.\n --pkcs11-module sofile\n Name of the \"module\" shared object when using PKCS#11\n keys. Defaults to opensc-pkcs11.so.\n -p capath, --parent-ca capath\n Parent CA directory. If omitted, CA certificate will\n be self-signed.\n -s subject, --subject-dn subject\n CA subject distinguished name. Defaults to /CN=Root\n CA.\n -d days, --validity-days days\n Number of days that the newly created CA will be valid\n for. Defaults to 365 days.\n -h alg, --hashfnc alg\n Hash function to use for signing the CA certificate.\n Defaults to sha384.\n --serial serial Serial number to use for root CA certificate.\n Randomized by default.\n --allow-duplicate-subjects\n By default, subject distinguished names of all valid\n certificates below one CA must be unique. This option\n allows the CA to have duplicate distinguished names\n for certificate subjects.\n --extension key=value\n Additional certificate X.509 extension to include on\n top of the default CA extensions. Can be specified\n multiple times.\n -f, --force By default, the capath will not be overwritten if it\n already exists. When this option is specified the\n complete directory will be erased before creating the\n new CA.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.createcsrThe \"createcsr\" command can (as the name suggests) create CSRs, but also can\ndirectly generate CRTs that are signed by a previously created CA. The\nadvantage over using OpenSSL manually is that the API is quite simple to\nconfigure the certificate manually for most cases (e.g., webserver certificates\nwith X.509 Subject Alternative Name set), but also is flexible enough for\ncustom stuff by including your custom extensions directly into the extension\nfile configuration used by OpenSSL.usage: ./x509sak.py createcsr [-g keyspec] [-k {pem,der,hw}] [-s subject]\n [-d days] [-h alg]\n [-t {rootca,ca,tls-server,tls-client}]\n [--san-dns FQDN] [--san-ip IP]\n [--extension key=value] [-f] [-c capath] [-v]\n [--help]\n in_key_filename out_filename\n\nCreate a new certificate signing request (CSR) or certificate\n\npositional arguments:\n in_key_filename Filename of the input private key or PKCS#11 URI (as\n specified in RFC7512 in case of a hardware key type.\n out_filename Filename of the output certificate signing request or\n certificate.\n\noptional arguments:\n -g keyspec, --gen-keyspec keyspec\n Private key specification to generate for the\n certificate or CSR when it doesn't exist. Examples are\n rsa:1024 or ecc:secp256r1.\n -k {pem,der,hw}, --keytype {pem,der,hw}\n Private key type. Can be any of pem, der, hw. Defaults\n to pem.\n -s subject, --subject-dn subject\n Certificate/CSR subject distinguished name. Defaults\n to /CN=New Cert.\n -d days, --validity-days days\n When creating a certificate, number of days that the\n certificate will be valid for. Defaults to 365 days.\n -h alg, --hashfnc alg\n Hash function to use for signing when creating a\n certificate. Defaults to the default hash function\n specified in the CA config.\n -t {rootca,ca,tls-server,tls-client}, --template {rootca,ca,tls-server,tls-client}\n Template to use for determining X.509 certificate\n extensions. Can be one of rootca, ca, tls-server, tls-\n client. By default, no extensions are included except\n for SAN.\n --san-dns FQDN Subject Alternative DNS name to include in the\n certificate or CSR. Can be specified multiple times.\n --san-ip IP Subject Alternative IP address to include in the\n certificate or CSR. Can be specified multiple times.\n --extension key=value\n Additional certificate X.509 extension to include on\n top of the extensions in the template and by the SAN\n parameters. Can be specified multiple times.\n -f, --force Overwrite the output file if it already exists.\n -c capath, --create-crt capath\n Instead of creating a certificate signing request,\n directly create a certificate instead. Needs to supply\n the CA path that should issue the certificate.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.signcsrThe signcsr command allows you to turn a CSR into a certificate by signing it\nby a CA private key.usage: ./x509sak.py signcsr [-s subject] [-d days] [-h alg]\n [-t {rootca,ca,tls-server,tls-client}]\n [--san-dns FQDN] [--san-ip IP]\n [--extension key=value] [-f] [-v] [--help]\n capath in_csr_filename out_crt_filename\n\nMake a certificate authority (CA) sign a certificate signing request (CSR) and\noutput the certificate\n\npositional arguments:\n capath Directory of the signing CA.\n in_csr_filename Filename of the input certificate signing request.\n out_crt_filename Filename of the output certificate.\n\noptional arguments:\n -s subject, --subject-dn subject\n Certificate's subject distinguished name. Defaults to\n the subject given in the CSR.\n -d days, --validity-days days\n Number of days that the newly created certificate will\n be valid for. Defaults to 365 days.\n -h alg, --hashfnc alg\n Hash function to use for signing. Defaults to the\n default hash function specified in the CA config.\n -t {rootca,ca,tls-server,tls-client}, --template {rootca,ca,tls-server,tls-client}\n Template to use for determining X.509 certificate\n extensions. Can be one of rootca, ca, tls-server, tls-\n client. By default, no extensions are included except\n for SAN.\n --san-dns FQDN Subject Alternative DNS name to include in the\n certificate. Can be specified multiple times.\n --san-ip IP Subject Alternative IP address to include in the CRT.\n Can be specified multiple times.\n --extension key=value\n Additional certificate X.509 extension to include on\n top of the extensions in the template and by the SAN\n parameters. Can be specified multiple times.\n -f, --force Overwrite the output certificate file if it already\n exists.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.revokecrtWith revokecrt it's possible to easily revoke a certificate that you've\nprevious generated. Simply specify the CA and the certificate that you want to\nrevoke and you're set.usage: ./x509sak.py revokecrt [-v] [--help] capath crt_filename\n\nRevoke a specific certificate\n\npositional arguments:\n capath CA which created the certificate.\n crt_filename Filename of the output certificate.\n\noptional arguments:\n -v, --verbose Increase verbosity level. Can be specified multiple times.\n --help Show this help page.createcrlThe createcrl command does what it suggests: It creates a CRL for a given CA\nthat is valid for a specified duration and that's signed with a given hash\nfunction.usage: ./x509sak.py createcrl [-d days] [-h alg] [-v] [--help]\n capath crl_filename\n\nGenerate a certificate revocation list (CRL)\n\npositional arguments:\n capath CA which should generate the CRL.\n crl_filename Filename of the output CRL.\n\noptional arguments:\n -d days, --validity-days days\n Number of days until the CRLs 'nextUpdate' field will\n expire. Defaults to 30 days.\n -h alg, --hashfnc alg\n Hash function to use for signing the CRL. Defaults to\n sha256.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.genbrokenrsaWith genbrokenrsa it is possible to generate deliberately malformed or odd RSA\nkeys. For example, RSA keys with a custom value for the public exponent e, or\nRSA keys which have a very small exponent d (e.g, 3) and a correspondingly\nlarge exponent e. Note that keys generated by this tool areexclusively for\ntesting purposesand may not, under any circumstances, be used for actual\ncryptographic applications. They arenot secure.usage: ./x509sak.py genbrokenrsa [-d path] [-b bits] [-e exp] [--switch-e-d]\n [--accept-unusable-key]\n [--carmichael-totient] [--generator file]\n [--gcd-n-phi-n | --close-q]\n [--q-stepping int] [-o file] [-f] [-v]\n [--help]\n\nGenerate broken RSA keys for use in penetration testing\n\noptional arguments:\n -d path, --prime-db path\n Prime database directory. Defaults to . and searches\n for files called primes_{bitlen}.txt in this\n directory.\n -b bits, --bitlen bits\n Bitlength of modulus. Defaults to 2048 bits.\n -e exp, --public-exponent exp\n Public exponent e (or d in case --switch-e-d is\n specified) to use. Defaults to 0x10001. Will be\n randomly chosen from 2..n-1 if set to -1.\n --switch-e-d Switch e with d when generating keypair.\n --accept-unusable-key\n Disregard integral checks, such as if gcd(e, phi(n))\n == 1 before inverting e. Might lead to an unusable key\n or might fail altogether.\n --carmichael-totient By default, d is computed as the modular inverse of e\n to phi(n), the Euler Totient function. This computes d\n as the modular inverse of e to lambda(n), the\n Carmichael Totient function, instead.\n --generator file When prime database is exhausted, will call the prime\n generator program as a subprocess to generate new\n primes. Otherwise, and the default behavior, is to\n fail.\n --gcd-n-phi-n Generate a keypair in which gcd(n, phi(n)) != 1 by\n specially constructing the prime q. This will lead to\n a size disparity of p and q and requires 3-msb primes\n as input.\n --close-q Use a value for q that is very close to the value of p\n so that search starting from sqrt(n) is\n computationally feasible to factor the modulus. Note\n that for this, the bitlength of the modulus must be\n evenly divisible by two.\n --q-stepping int When creating a close-q RSA keypair, q is chosen by\n taking p and incrementing it repeatedly by a random\n int from 2 to (2 * q-stepping). The larger q-stepping\n is therefore chosen, the further apart p and q will\n be. By default, q-stepping is the minimum value of 1.\n -o file, --outfile file\n Output filename. Defaults to broken_rsa.key.\n -f, --force Overwrite output file if it already exists instead of\n bailing out.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.genbrokendsaSimilar to the previous command, this can be used to create DSA domain\nparameters that are insecure and/or undesirable (e.g., because the generator is\nnot verifiable).usage: ./x509sak.py genbrokendsa [-d path] [--generator file] [-o file] [-f]\n [-v] [--help]\n L_bits N_bits\n\nGenerate broken DSA parameters for use in penetration testing\n\npositional arguments:\n L_bits Bitlength of the modulus p, also known as L.\n N_bits Bitlength of q, also known as N.\n\noptional arguments:\n -d path, --prime-db path\n Prime database directory. Defaults to . and searches\n for files called primes_{bitlen}.txt in this\n directory.\n --generator file When prime database is exhausted, will call the prime\n generator program as a subprocess to generate new\n primes. Otherwise, and the default behavior, is to\n fail.\n -o file, --outfile file\n Output filename. Defaults to broken_dsa.key.\n -f, --force Overwrite output file if it already exists instead of\n bailing out.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.dumpkeyThe dumpkey facility can be used to dump the public/private key parameters of a\ngiven PEM keyfile into Python-code for further processing.usage: ./x509sak.py dumpkey [-t {rsa,ecc,eddsa}] [-p] [-v] [--help]\n key_filename\n\nDump a key in text form\n\npositional arguments:\n key_filename Filename of the input key file in PEM format.\n\noptional arguments:\n -t {rsa,ecc,eddsa}, --key-type {rsa,ecc,eddsa}\n Type of private key to import. Can be one of rsa, ecc,\n eddsa, defaults to rsa. Disregarded for public keys\n and determined automatically.\n -p, --public-key Input is a public key, not a private key.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.examinecertUsing the examinecert facility you can plausibilize certificates and check them\nfor all kinds of errors that can happen. It also gives a security estimate of\nthe used algorithms and highlights things that are unusual. For example, RSA\nwith large exponents is something that is entirely safe, but definitely\nunusual. Missing key usage flags or important extensions will also be reported\nalong with standards violations (mainly RFC5280) -- it also gives you the exact\nlocation of the RFC (including section) that has been violated.usage: ./x509sak.py examinecert [-p {ca,tls-server,tls-client}] [-n fqdn]\n [-f {ansitext,text,json}]\n [-i {pemcrt,dercrt,json,host}] [-r pemfile]\n [--no-automatic-host-check] [--fast-rsa]\n [--include-raw-data] [--pretty-json]\n [-o filename] [-v] [--help]\n filename/uri [filename/uri ...]\n\nExamine an X.509 certificate\n\npositional arguments:\n filename/uri Filename of the input certificate or certificates in\n PEM format.\n\noptional arguments:\n -p {ca,tls-server,tls-client}, --purpose {ca,tls-server,tls-client}\n Check if the certificate is fit for the given purpose.\n Can be any of ca, tls-server, tls-client, can be\n specified multiple times.\n -n fqdn, --server-name fqdn\n Check if the certificate is valid for the given\n hostname.\n -f {ansitext,text,json}, --out-format {ansitext,text,json}\n Determine the output format. Can be one of ansitext,\n text, json, defaults to ansitext.\n -i {pemcrt,dercrt,json,host}, --in-format {pemcrt,dercrt,json,host}\n Specifies the type of file that is read in. Can be\n either certificate files in PEM or DER format, a pre-\n processed JSON output from a previous run or a\n hostname[:port] combination to query a TLS server\n directly (port defaults to 443 if omitted). Valid\n choices are pemcrt, dercrt, json, host, defaults to\n pemcrt.\n -r pemfile, --parent-certificate pemfile\n Specifies a parent CA certificate that is used to run\n additional checks against the certificate.\n --no-automatic-host-check\n By default, when the input format is a given hostname,\n the server name is assumed as well and the purpose is\n assumed to be a TLS server. When this option is\n specified, these automatic checks are omitted.\n --fast-rsa Skip some time-intensive number theoretical tests for\n RSA moduli in order to speed up checking. Less\n thorough, but much faster.\n --include-raw-data Add the raw data such as base64-encoded certificate\n and signatures into the result as well.\n --pretty-json Prettyfy any generated JSON output.\n -o filename, --output filename\n Specify the output file. Defaults to stdout.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.forgecertWith the forgecert tool you can forge a certificate chain. The input PEM file\nmust begin with a self-signed root certificate and each following certificate\nmust descend from its predecessor. The functionality is rather simplistic\ncurrently. The purpose is to create certificates which look and feel like their\n\"original\" counterparts, but are obviously fakes. This is for white hat testing\nof implementations.usage: ./x509sak.py forgecert [--key_template path] [--cert_template path]\n [-r] [-f] [-v] [--help]\n crt_filename\n\nForge an X.509 certificate\n\npositional arguments:\n crt_filename Filename of the input certificate or certificates PEM\n format.\n\noptional arguments:\n --key_template path Output template for key files. Should contain '%d' to\n indicate element in chain. Defaults to\n 'forged_%02d.key'.\n --cert_template path Output template for certificate files. Should contain\n '%d' to indicate element in chain. Defaults to\n 'forged_%02d.crt'.\n -r, --recalculate-keyids\n By default, Subject Key Identifier and Authority Key\n Identifier X.509 extensions are kept as-is in the\n forged certificates. Specifying this will recalculate\n the IDs to fit the forged keys.\n -f, --force Overwrite key/certificate files.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.scrapeWith the scrape tool you can analyze binary blobs or whole disks and search\nthem for PEM or DER-encoded blobs. This is interesting if, for example, you're\ndoing firmware analysis. DER analysis is quite slow because for every potential\nsequence beginning (0x30), decoding of all supported schema is attempted. It\ncan be sped up if you're only looking for a particular data type instead of all\nof them. In contrast, scanning for PEM data is much faster because PEM markers\nhave a much smaller false positive rate. For every occurrence that is found\ninside the analyzed file, the contents are written to a own file in the output\ndirectory.usage: ./x509sak.py scrape [--no-pem] [--no-der] [-i class] [-e class]\n [--extract-nested] [--keep-original-der]\n [--allow-non-unique-blobs]\n [--disable-der-sanity-checks] [--outmask mask]\n [-w filename] [-o path] [-f] [-s offset]\n [-l length] [-v] [--help]\n filename\n\nScrape input file for certificates, keys or signatures\n\npositional arguments:\n filename File that should be scraped for certificates or keys.\n\noptional arguments:\n --no-pem Do not search for any PEM encoded blobs.\n --no-der Do not search for any DER encoded blobs.\n -i class, --include-dertype class\n Include the specified DER handler class in the search.\n Defaults to all known classes if omitted. Can be\n specified multiple times and must be one of crt,\n dsa_key, dsa_sig, ec_key, pkcs12, pubkey, rsa_key.\n -e class, --exclude-dertype class\n Exclude the specified DER handler class in the search.\n Can be specified multiple times and must be one of\n crt, dsa_key, dsa_sig, ec_key, pkcs12, pubkey,\n rsa_key.\n --extract-nested By default, fully overlapping blobs will not be\n extracted. For example, every X.509 certificate also\n contains a public key inside that would otherwise be\n found as well. When this option is given, any blobs\n are extracted regardless if they're fully contained in\n another blob or not.\n --keep-original-der When finding DER blobs, do not convert them to PEM\n format, but leave them as-is.\n --allow-non-unique-blobs\n For all matches, the SHA256 hash is used to determine\n if the data is unique and findings are by default only\n written to disk once. With this option, blobs that\n very likely are duplicates are written to disk for\n every occurrence.\n --disable-der-sanity-checks\n For DER serialization, not only is it checked that\n deserialization is possible, but additional checks are\n performed for some data types to ensure a low false-\n positive rate. For example, DSA signatures with short\n r/s pairs are discarded by default or implausible\n version numbers for EC keys. With this option, these\n sanity checks will be disabled and therefore\n structurally correct (but implausible) false-positives\n are also written.\n --outmask mask Filename mask that's used for output. Defaults to\n scrape_%(offset)07x_%(type)s.%(ext)s and can use\n printf-style substitutions offset, type and ext.\n -w filename, --write-json filename\n Write the stats with detailed information about\n matches into the given filename.\n -o path, --outdir path\n Output directory. Defaults to scrape.\n -f, --force Overwrite key/certificate files and proceed even if\n outdir already exists.\n -s offset, --seek-offset offset\n Offset to seek into file. Supports hex/octal/binary\n prefixes and SI/binary SI (k, ki, M, Mi, etc.)\n suffixes. Defaults to 0.\n -l length, --analysis-length length\n Amount of data to inspect at max. Supports\n hex/octal/binary prefixes and SI/binary SI (k, ki, M,\n Mi, etc.) suffixes. Defaults to everything until EOF\n is hit.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.hashpartThe hashpart facility allows the user to have all substrings of a file hashed\nwith different hash algorithms in a brute-force manner. So for example, if you\nhave a three-byte file \"ABC\" then the strings \"A\", \"AB\", \"ABC\", \"BC\" and \"C\"\nwould be hashed by all selected hash functions. A search parameter allows you\nto have the tool only print those hexadecimal hash values which have a\nsubstring match. This makes sense when you for example have a hash value of a\nblob contained inside a larger blob but are unsure which hash function was used\nstarting from which offset and which length the hash is computed over. A simple\nexample is that you know the Subject Key Identifier (SKI) of a DER-encoded\ncertificate and want to bruteforce the offsets over which it is calculated.usage: ./x509sak.py hashpart [-h alg] [-o offset] [--max-offset offset]\n [-a length] [-l length] [-s hexpattern] [-v]\n [--help]\n filename\n\nHash all substrings of a file and search for a particular hash value\n\npositional arguments:\n filename File that should be hashed.\n\noptional arguments:\n -h alg, --hash-alg alg\n Hash function(s) that should be tried. Can be\n specified multiple times and defaults to all available\n hash functions. Can be any of blake2b, blake2s, md4,\n md5, md5-sha1, ripemd160, sha1, sha224, sha256,\n sha384, sha3_224, sha3_256, sha3_384, sha3_512,\n sha512, sha512_224, sha512_256, shake_128, shake_256,\n sm3, whirlpool, all, but defaults to md5, sha1,\n sha256, sha384, sha512. Special value 'all' means all\n supported functions.\n -o offset, --seek-offset offset\n Offset to seek into file. Supports hex/octal/binary\n prefixes and SI/binary SI (k, ki, M, Mi, etc.)\n suffixes. Defaults to 0.\n --max-offset offset Largest offset to consider. By default, this is end-\n of-file. Supports hex/octal/binary prefixes and\n SI/binary SI (k, ki, M, Mi, etc.) suffixes.\n -a length, --variable-hash-length length\n For hash functions which have a variable output\n length, try all of these hash lenghts. Length is given\n in bits and must be a multiple of 8. Can be supplied\n multiple times. Defaults to 128, 256, 384.\n -l length, --analysis-length length\n Amount of data to inspect at max. Supports\n hex/octal/binary prefixes and SI/binary SI (k, ki, M,\n Mi, etc.) suffixes. Defaults to everything until EOF\n is hit.\n -s hexpattern, --search hexpattern\n Hexadecimal pattern that is expected in the hashing.\n -v, --verbose Increase verbosity level. Can be specified multiple\n times.\n --help Show this help page.LicenseGNU GPL-3. Thanks to thex509test projectfor the excellent testsuite of broken certificates (included in the\nx509sak/tests/data/certs/google/ subdirectory)."} +{"package": "x52", "pacakge-description": "X52A easy-to-use package to utilize the MFD on the Throttle of the X52 and X52 Pro, with features like displaying text, navigating pages of content and callbacks.The Package is available onPyPiUsage Examplefromsysimportexit# import necessary items from the x52 packagefromx52importX52,X52Page# Setup callback functions for later usedefcallback_func_1():print('hello from callback_func_1')defcallback_func_2():print('hello from callback_func_2')defcallback_func_3():print('hello from callback_func_3')# instantiate an X52 Object and initialize it# if the X52 Object gets garbage collected it gets# deinitializedx52=X52()x52.init()x52Devices=x52.get_x52devices()# Exit if there is no X52 connectedifnotx52Devices:exit(-1)# Select the first detected devicex52Device=x52Devices[0]# Create pages using the X52Page Constructorpage1=X52Page(('This is Item1',callback_func_1),('This is Item2',callback_func_2),('This is Item3',callback_func_3),True)page2=X52Page(('This is a non',None),('non interactive',None),('Page, with cycling text',None),False)# Add pages to the MFDx52Device.page_add(page1)x52Device.page_add(page2)# Endless loop, else program exitswhileTrue:pass"} +{"package": "x52-control", "pacakge-description": "Logitech X52/X52Pro moduleMost of the information about how to configure the devices comes from a GUI program called gx52, created by Roberto Leinardi. His project can be found athttps://github.com/leinardi/gx52. Many thanks to him for his efforts, if you need a GUI app to set up your HOTAS, consider using his program.If you want a command line tool, there is a utility called x52pro-linux, by nirenjan, available athttps://github.com/nirenjan/x52pro-linux. It has a C library that you can use in your own software and a CLI tool to set you HOTAS. It's even available as packages in Debian and Arch.How to use itInitializing the modulefromx52importx52# locate all devicesjoystick=x52()# list devicesprint(joystick.devices)Setting button colors# sets POV LED to green on device 0joystick.set_led_color(joystick.devices[0],'pov','green')# Blinks I button and POV Hat 1joystick.set_led_blink(joystick.devices[0],'blink')# stops blinkingjoystick.set_led_blink(joystick.devices[0],'solid')Valid colors for POV Hat 2 and Throtlle areonandoff. For all other buttons values areamber,red,greenoroff.For blinking status, values areblinkandsolid.LED and MFD brightnessBrightness of LEDs and MFD can be set to values between 0 (which turns them off) and 127 (maximum).You can set the brightness like this:# set brightness to 60joystick.set_brightnes(joystick.devices[0],'mfd',60)joystick.set_brightnes(joystick.devices[0],'led',60)# turns the lighting offjoystick.set_brightnes(joystick.devices[0],'mfd',0)joystick.set_brightnes(joystick.devices[0],'led',0)Sets the clock and date.WARNING: The clock does NOT update itself. You need to call this method and update clock 1 everytime you want it to advance.Setting the date is only possible when also setting the main clock (identified by 1) When setting clocks 2 and 3, is not possible to set the date, since those 2 only accept offsets from the main clock. The offsets are a number of minutes, between -1023 and 1023.When setting the date, you can choose the format, valid options are 'DMY' (Day.Month.Year), 'MDY' (Mont.Day.Year) or 'YMD' (Year.Month.Day). The clocks can also be set to 24h or AM/PM modes.Setting time and date:# set current date and time to clock 1, usind DMY and 24h formatsnowtime=datetime.nowjoystick.set_clock(device=joystick.devices[0],clock=1,cur_time=nowtime,date_format='DMY',is24h=True)# set clock 2 to 45min aheadjoystick.set_clock(device=joystick.devices[0],clock=2,cur_time=45)Shift indicatorThis indicator does nothing to the actual performance or functionality of the X52. It's just there so the official software can tell you when it's using different settings.You can turn it on or off like this:#turn it onjoystick.set_shift(joystick.devices[0],'on')#turn it offjoystick.set_shift(joystick.devices[0],'off')MFD TextYou can write on the 3 text lines of the MFD. Lines are limited to 16 characters, anything beyond that will be discarded. There are issues with non-US ASCII text, so try not to write anything fancy. Just call the method with the line number (1 to 3) and the text. A blank line ('') erases the line.Examples:# write a text to line 1joystick.write_mfd(joystick.devices[0],1,'A line of Text')joystick.write_mfd(joystick.devices[0],1,'This text is too big and will be truncated')# Erases line 1joystick.write_mfd(joystick.devices[0],1,'')"} +{"package": "x5qautils", "pacakge-description": "No description available on PyPI."} +{"package": "x64rdbgpy", "pacakge-description": "No description available on PyPI."} +{"package": "x64trace", "pacakge-description": "No description available on PyPI."} +{"package": "x690", "pacakge-description": "Pure PythonX.690implementationThis module contains a pure Python implementation of the \u201cx690\u201d standard for\nBER encoding/decoding. Other encodings are currently unsupported but\npull-requests are welcome.Supporting New TypesSome applications may need to support types which are not defined in the X.690\nstandard. This is supported by this library but the types must be defined and\nregistered.To register a type, simply subclassx690.types.Type. This will take care of\nthe registration. Make sure that your new type is imported before using it.New types should define the following 3 class-variables:TYPECLASSA value fromx690.util.TypeClassNATUREA value fromx690.util.TypeNatureTAGA numerical identifier for the typeRefer to the x690 standard for more details on these values. As a general\nrule-of-thumb you can assume that the class is either \u201ccontext\u201d or\n\u201capplication\u201d (it might be good to keep the \u201cuniversal\u201d class reserved for\nx690). The nature should be \u201cprimitive\u201d for simple values and \u201cconstructed\u201d for\ncomposed types. The tag is free to choose as long as you don\u2019t overlap with an\nexisting type.To convert raw-bytes into a Python object, overridex690.Type.decode_rawand conversely alsox690.Type.encode_raw. Refer to the docstrings for more\ndetails.Reverse Engineering BytesAll types defined in thex690library provide a.pretty()method which\nreturns a prettyfied string.If you are confronted with a bytes-object encoded using X.690 but don\u2019t have\nany documentation, you can write the following loop:from x690 import decode\n\ndata = open(\"mydatafile.bin\", \"rb\").read()\n\nvalue, nxt = decode(data)\nprint(value.pretty())\n\nwhile nxt < len(data):\n value, nxt = decode(data, nxt)\n print(value.pretty())This should get you started.If the data contain non-standard types, they will get detected as \u201cUnknownType\u201d\nand will print out the type-class, nature and tag in the pretty-printed block.This will allow you to define your own subclass ofx690.types.Typeusing\nthose values. Overridedecode(...)in that class to handle the unknown\ntype.ExamplesEncoding to bytesEncoding to bytes can be done by simply calling the Python builtingbytes()on instances fromx690.types:Encoding of a single value>>>importx690.typesast>>>myvalue=t.Integer(12)>>>asbytes=bytes(myvalue)>>>repr(asbytes)b'\\x02\\x01\\x0c'Encoding of a composite value using Sequence>>>importx690.typesast>>>myvalue=t.Sequence(...t.Integer(12),...t.Integer(12),...t.Integer(12),...)>>>asbytes=bytes(myvalue)>>>repr(asbytes)b'0\\t\\x02\\x01\\x0c\\x02\\x01\\x0c\\x02\\x01\\x0c'Decoding from bytesDecode bytes by callingx690.types.decodeon your byte data. This will\nreturn a tuple where the first value contains the decoded object, and the\nsecond one will contain any remaining bytes which were not decoded.>>>importx690>>>data=b'0\\t\\x02\\x01\\x0c\\x02\\x01\\x0c\\x02\\x01\\x0c'>>>decoded,nxt=x690.decode(data)>>>decodedSequence(Integer(12),Integer(12),Integer(12))>>>nxt11Type-Hinting & EnforcingNew in 0.3.0When decoding bytes, it is possible to specify an expcted type which does two\nthings: Firstly, it tells tools likemypywhat the return type will be and\nsecondly, it runs an internal type-check whichensuresthat the returned\nvalue is of the expected type.x690.exc.UnexpectedTypeis raised otherwise.This does of course only work if you know the type in advance.>>>importx690>>>importx690.typesast>>>data=b'0\\t\\x02\\x01\\x0c\\x02\\x01\\x0c\\x02\\x01\\x0c'>>>decoded,nxt=x690.decode(data,enforce_type=t.Sequence)>>>decodedSequence(Integer(12),Integer(12),Integer(12))>>>nxt11Strict DecodingNew in 0.3.0When decoding usingdecodeand you don\u2019t expect any remaining bytes, usestrict=Truewhich will raisex690.exc.IncompleteDecodingif there\u2019s any\nremaining data.>>>importx690>>>data=b'0\\t\\x02\\x01\\x0c\\x02\\x01\\x0c\\x02\\x01\\x0cjunk-bytes'>>>decoded,nxt=x690.decode(data,strict=True)Traceback(mostrecentcalllast):...x690.exc.IncompleteDecoding:Strictdecodingstillhad10remainingbytes!"} +{"package": "x7", "pacakge-description": "Top level project for X7 libraries."} +{"package": "x735-v2.5", "pacakge-description": "# x735-v2.5\nThis is the safe shutdown script and some python sample code.## InstallAssuming your system is updated, add these packages:### Install dependencies` sudoapt-getinstallpython-smbussudoapt-getinstall pigpiopython3-pigpio`### Add package` sudo pip3 installx735-v2.5`### Add service to systemdcat > sudo /etc/systemd/system/x735fan.service <<- EOM\n[Unit]\nDescription=Run fan for x735 board\nAfter=multi-user.target\n\n[Service]\nType=simple\nRestart=always\nRestartSec=1\nExecStart=/usr/bin/python3 /usr/local/bin/x735fan run\n\n[Install]\nWantedBy=multi-user.target\nEOM\n\nsudo systemctl daemon-reload\nsudo systemctl enable x735fan.service\nsudo systemctl start x735fan.service\nsudo systemctl status x735fan.service## Update` sudo pip3 installx735-v2.5-U`# Use` x735fan run # Run set speed x735fan info # Get fan information `# Develop` python3-mvenv venv pip install-e. `## Deploy to pypi` python setup.py register-rpypi python setup.py sdist upload-rpypi `"} +{"package": "x7-geom", "pacakge-description": "Library providing some basic geometry types and operations:PointVectorLineBezierCurveA distinguishing feature of this library is that it is designed for\nmodeling, so there are also classes likePointRelativewhich\nautomatically updates when the underlying point is moved. This\nis used by the morphing and animation capabilities."} +{"package": "x7-lib", "pacakge-description": "X7 low level library"} +{"package": "x7-testing", "pacakge-description": "Helpers forunittestbased tests:maketeststo create test/update unittest stubsTestCaseExtendedto support more kinds ofalmostEqualsand stored test results for simple regression tests"} +{"package": "x7-view", "pacakge-description": "An extensible viewer/editor for X7 geom Elems."} +{"package": "x84", "pacakge-description": "An experimental python 2 Telnet (and SSH) BBSthis project is abandoned, so please don\u2019t get too excited! Maybe you\nwould be more interested inENiGMA\u00bdThe primary purpose of x/84 is to provide a server framework for building\nenvironments that emulate the feeling of an era that predates the world wide web.It may be used for developing a classic bulletin board system (BBS) \u2013 one is\nprovided as the \u2018default\u2019 scripting layer. It may also be used to develop a MUD,\na text-based game, or a game-hosting server such as done by dgamelaunch.You may access the \u201cdefault board\u201d provided by x/84 at telnet host 1984.ws:telnet 1984.wsSeeclientsfor a list of compatible clients, though any terminal should be just fine.QuickstartNote that only Linux, BSD, or OSX is supported. Windows might even work, but hasn\u2019t been tested.Installpython2.7andpip. More than likely this is possible through your\npreferred distribution packaging system.Install x/84:pip install x84[with_crypto]Or, if C compiler and libssl, etc. is not available, simply:pip install x84Please note however that without the[with_crypto]option, you\nwill not be able to run any of the web, ssh, and sftp servers, and\npassword hashing (and verification) will be significantly slower.If you receive an error aboutsetuptools_extnot being found, you\nmay need to upgrade your installed version of setuptools and try again:pip install -U setuptools pipLaunch thex84.enginepython module:x84Telnet to 127.0.0.1 6023, Assuming absd telnetclient:telnet localhost 6023All data files are written to~/.x84/. To create a custom board,\nyou might copy thedefaultfolder of thex/84python module to a\nlocal path, and point thescriptpathvariable of~/.x84/default.inito point to that folder.Simply edit and save changes, and re-login to see them. Adjust theshow_tracebackvariable to display any errors directly to your\ntelnet or ssh client.Documentation, Support, Issue TrackingSeeDocumentationfor API and general tutorials, especially thedeveloperssection for preparing a developer\u2019s environment if you wish to contribute\nupstream. Of note, theTerminalinterface is used for keyboard input\nand screen output, and is very well-documented inblessed.This project isn\u2019t terribly serious (for example, there are no tests). See the project ongithubfor source tree. Please note that this project isabandoned. Feel free to do whatever the heck\nyou want with it, though, it is Open Source and ISC licensed!"} +{"package": "x86bmi", "pacakge-description": "No description available on PyPI."} +{"package": "x86cpu", "pacakge-description": "Usescpuidinstruction to get\ninformation about CPU.QueriesOS as well as cpuidto see if the OS / CPU supports AVX instructions.Quickstart>>> from x86cpu import info\n>>> print(info.model_display, info.family_display)\n(69, 6)\n>>> print(info.vendor)\nGenuineIntel\n>>> print(info.brand)\n'Intel(R) Core(TM) i5-4250U CPU @ 1.30GHz'You can run thecpuidcommand directly. The argument tocpuidgoes\ninto theEAXregister before calling the CPUID instruction:>>> from x86cpu import cpuid\n>>> cpuid(1)\n{'eax': 263761L, 'ebx': 17827840L, 'ecx': 2147154879L, 'edx': 3219913727L}Some CPUID commands also care about the value in theECXregister. You\ncan set this with a second optional argument tocpuid:>>> cpuid(13, 1)\n{'eax': 1, 'ebx': 0, 'ecx': 0, 'edx': 0}The package installs a command line toolx86reportgiving output like\nthis:$ x86report\nx86cpu report\n-------------\nbrand : Intel(R) Core(TM) i5-4250U CPU @ 1.30GHz\nvendor : GenuineIntel\nmodel (display) : 69\nfamily (display) : 6\nmodel : 5\nfamily : 6\nextended model : 4\nextended family : 0\nstepping : 1\nprocessor type : 0\nsignature : 263761\nMMX : True\n3DNow! : True\nSSE : True\nSSE2 : True\nSSE3 : True\nSSSE3 : True\nSSE4.1 : True\nSSE4.2 : True\nsupports AVX : True\nsupports AVX2 : TrueCodeSeehttps://github.com/matthew-brett/x86cpuReleased under the BSD two-clause license - see the fileLICENSEin the\nsource distribution.The latest released version is athttps://pypi.python.org/pypi/x86cpuSupportPlease put up issues on thex86cpu issue tracker."} +{"package": "x9", "pacakge-description": "X9 by PymoduledevNOTE:X9 only works in Python 3.1+Updates1.0.1 - bug fixes in description1.0.0 - initial releaseWhat is X9?X9 is a comprehensive Python module developed bypymoduledev, offering three essential classes that cater to various programming needs. The module includes the following classes:gui: Provides functionalities for creating and managing graphical user interfaces (GUIs) usingtkinter.web: Enables the development of web applications usingwsgiref.simple_server'smake_serverandlogging.maths: An improved version of the standardmathmodule, offering additional mathematical capabilities made usingmath.How to Install X9You can easily install X9 usingpip:pip install x9How do I use X9?X9 is very easy to understand, and you can take an tutorial here right now.GUI ClassTheguiclass facilitates the creation of user-friendly graphical interfaces. Here's a simple example:from x9 import gui\n\nwindow = gui.new()\nwindow.bg(color='#000000')\nwindow.title('My Window')\nwindow.favicon('path/to/favicon.ico')\nwindow.resize(\"1880x600\")\n\ntextbox = window.textbox(placeholder='type here...')\ntextbox.resize(100)\n\ntext = gui.label('Hey!')\ngui.font(text, 'Arial', 16, is_bold=True)\n\nbutton = window.button(value='submit',command=lambda: print(textbox.get()))\n\nwindow.run()Web ClassWith thewebclass, you can effortlessly build web applications and APIs. Here's a basic example:from x9 import web\n\napp = web() #Create the web instance\n\ndef index():\n return '

Hello, World!

'\n\ndef render_html():\n return app.html('index.html') #This will get the contents of the index.html file assuming it is in the same directory as the Python file\n\napp.new(index, '/')\n\napp.new(render_html, '/render-html')\n\napp.run()Maths ClassThemathsclass extends the capabilities of the standardmathmodule. Take advantage of its additional functions:from x9 import maths as ImprovedMath\n\n# Using Algebra functions\na, b, c = 1, -3, 2\nroots = ImprovedMath.Algebra.quadratic_formula(a, b, c)\nprint(f\"The roots of the quadratic equation {a}x^2 + {b}x + {c} = 0 are: {roots}\")\n\n# Using Calculus functions\ncoefficients = [1, 2, 3]\nx = 2\nderivative_at_x = ImprovedMath.Calculus.differentiate_polynomial(coefficients, x)\nprint(f\"The derivative of the polynomial {coefficients} at x={x} is: {derivative_at_x}\")\n\n# Using Statistics functions\ndata = [2, 4, 6, 8, 10]\nmean_value = ImprovedMath.Statistics.mean(data)\nprint(f\"The mean of the data {data} is: {mean_value}\")\n\nvariance_value = ImprovedMath.Statistics.variance(data)\nprint(f\"The variance of the data {data} is: {variance_value}\")ContributionsWe welcome contributions from the community to enhance X9 further. Feel free to share your ideas, report bugs, or request new features at the official PyModuleDev website(pymoduledev.neocities.org)LicenseX9 is distributed under the Apache License 2.0. A copy of the License can be found athttps://www.apache.org/licenses/LICENSE-2.0.txt.ContactFor any questions or support, you can reach out to pymoduledev atpxcom@mail.com."} +{"package": "x9k3", "pacakge-description": "Install|Use|CUE-OUT|CUE-IN|SCTE-35 Tags|Sidecar SCTE35|Byterange|playlist|Live|BugsHLS + SCTE35 =x9k3x9k3is a HLS segmenter with SCTE-35 injection and parsing, powered by threefive.Current Version:v.0.2.57Theonly supported version is the current version. Keep up.Some of the new stuff:x9k3 can now generatebyterangem3u8 files with-bor--byterangePlaylistscan now be used as input.Segmentstart timeis now always read, never calculated.Segmentduration verificationfor segments that exceed thetarget duration.adbreakscript to generate SCTE-35 Cues.m3u8 files as input. Resegment and add SCTE-35 to an existing m3u8.-i INPUT,--input INPUTcontinue an m3u8 file.Segments may be added to an existing m3u8, VOD or live.-c,--continue_m3u8discontinuity tagsmay now beomitted.-n,--no_discontinuityautoCUE-INlivethrottlingcan bedisabledwith the-N,--no_throttleflagHeads Upadbreakincluded with x9k3adbreak generates SCTE35 Cues for CUE-OUT and CUE-IN in a sidecar file.$adbreak-husage:adbreak[-h][-dDURATION][-pPTS][-sSIDECAR]options:-h,--help show this help message and exit-dDURATION,--duration DURATIONsetdurationofadbreak.[default:60.0]-pPTS,--pts PTS set start pts for ad break. Not setting pts willgenerateaSpliceImmediateCUE-OUT.[default:0.0]-sSIDECAR,--sidecar SIDECARSidecarfileofSCTE-35(pts,cue)pairs.[default:sidecar.txt]Usage:adbreak--pts 1234.567890 --duration 30 --sidecar sidecar.txtsidecar file has SCTE-35 Cues for CUE-OUT and CUE-IN1234.56789,/DAlAAAAAAAAAP/wFAUAAAABf+/+Bp9rxv4AKTLgAAEAAAAAhzvmvQ==1264.56789,/DAgAAAAAAAAAP/wDwUAAAABf0/+BsiepgABAAAAAPh51T0=pass to x9k3x9k3-iinput.ts-ssidecar.txtFeaturesSCTE-35 CuesinMpegts Streamsare Translated intoHLS tags.SCTE-35 Cues can be added from aSidecar File.Segments areSplit on SCTE-35 Cuesas needed.SegmentsStart on iframes.Supportsh264andh265.Multi-protocol.Input sources may beFiles, Http(s), Multicast, and Unicast UDP streams.SupportsLiveStreaming.amt-playuses x9k3.Requirespython 3.6+ or pypy3threefivenew_readeriframesInstallUse pip to install the the x9k3 lib and executable script x9k3 (will install threefive, new_reader and iframes too)#python3python3-mpipinstallx9k3#pypy3pypy3-mpipinstallx9k3\u21ea topDetailsX-SCTE35,X-CUE,X-DATERANGE, orX-SPLICEPOINTHLS tags can be generated. set with the--hls_tagswitch.reading from stdin now availableSegments are cut on iframes.Segment time is 2 seconds or more, determined by GOP size. Can be set with the-tswitch or by settingX9K3.args.timeSegments are named seg1.ts seg2.ts etc...For SCTE-35, Video segments are cut at the the first iframe >= the splice point pts.If no pts time is present in the SCTE-35 cue, the segment is cut at the next iframe.SCTE-35 cues with a preroll are inserted at the splice point.How to Useclia@fu:~/x9k3-repo$x9k3-husage:x9k3[-h] [-iINPUT] [-b] [-c] [-d] [-l] [-n] [-N] [-oOUTPUT_DIR] [-p]\n [-r] [-sSIDECAR_FILE] [-S] [-tTIME] [-THLS_TAG]\n [-wWINDOW_SIZE] [-v]optionalarguments:-h,--helpshowthishelpmessageandexit-iINPUT,--inputINPUTTheInputvideocanbempegtsorm3u8withmpegtssegments,oraplaylistwithmpegtsfilesand/ormpegtsm3u8files.Theinputcanbealocalvideo,http(s),udp,multicastorstdin.-b,--byterangeFlagforbyterangehls[default:False]-c,--continue_m3u8Resumewritingindex.m3u8[default:False]-d,--deletedeletesegments(enables--live) [default:False]-l,--liveFlagforaliveevent(enablesslidingwindowm3u8)\n [default:False]-n,--no_discontinuityFlagtodisableadding#EXT-X-DISCONTINUITYtagsatsplicepoints[default:False]-N,--no-throttledisablelivethrottling[default:False]-oOUTPUT_DIR,--output_dirOUTPUT_DIRDirectoryforsegmentsandindex.m3u8(createdifneeded) [default:'.']-p,--program_date_timeFlagtoaddProgramDateTimetagstoindex.m3u8(enables--live) [default:False]-r,--replayFlagforreplayakalooping(enables--live,--delete)\n [default:False]-sSIDECAR_FILE,--sidecar_fileSIDECAR_FILESidecarfileofSCTE-35(pts,cue)pairs.[default:None]-S,--shulgaFlagtoenableShulgaiframedetectionmode[default:False]-tTIME,--timeTIMESegmenttimeinseconds[default:2]-THLS_TAG,--hls_tagHLS_TAGx_scte35,x_cue,x_daterange,orx_splicepoint[default:x_cue]-wWINDOW_SIZE,--window_sizeWINDOW_SIZEslidingwindowsize(enables--live) [default:5]-v,--versionShowversionExample Usagelocal file as inputx9k3-ivideo.mpegtsmulticast stream as input with a live sliding windowx9k3--live-iudp://@235.35.3.5:3535Live mode works with a live source or static files.x9k3 will throttle segment creation to mimic a live stream.x9k3--live-i/some/video.tslive sliding window and deleting expired segmentsx9k3-iudp://@235.35.3.5:3535--deletehttps stream for input, and writing segments to an output directorydirectory will be created if it does not exist.x9k3-ihttps://so.slo.me/longb.ts--output_dir/home/a/variant0https hls m3u8 for input, and inserting SCTE-35 from a sidecar file, and continuing from a previously create index.m3u8 in the output dirx9k3-ihttps://slow.golf/longb.m3u8--output_dir/home/a/variant0-continue_m3u8-ssidecar.txtusing stdin as inputcatvideo.ts|x9k3live m3u8 file as input, add SCTE-35 from a sidecar file, change segment duration to 3 and output as live streamx9k3-ihttps://example.com/rendition.m3u8-ssidecar.txt-t3-l\u21ea topProgrammaticallyUp and Running in three Linesfromx9k3importX9K3#1x9=X9K3('/home/a/cool.ts')#2x9.decode()#3Writing Code with x9k3you can get a complete set of args and the defaults like thisfromx9k3importX9K3x9=X9K3()>>>>{print(k,':',v)fork,vinvars(x9.args).items()}input:<_io.BufferedReadername=''>continue_m3u8:Falsedelete:Falselive:Falseno_discontinuity:Falseno_throttle:Falseoutput_dir:.program_date_time:Falsereplay:Falsesidecar_file:Noneshulga:Falsetime:2hls_tag:x_cuewindow_size:5version:Falseor just>>>>print(x9.args)Namespace(input=<_io.BufferedReadername=''>,continue_m3u8=False,delete=False,live=False,no_discontinuity=False,no_throttle=False,output_dir='.',program_date_time=False,replay=False,sidecar_file=None,shulga=False,time=2,hls_tag='x_cue',window_size=5,version=False)Setting parametersfromx9k3importX9K3x9=X9K3()input sourcex9.args.input=\"https://futzu.com/xaa.ts\"hls_tagcan be x_scte35, x_cue, x_daterange, or x_splicepointx9.args.hlstag=x_cueoutput directorydefault is \".\"x9.args.output_dir=\"/home/a/stuff\"livex9.args.live=Truereplay(loop video) ( also sets live )x9.args.replay=Truedeletesegments when they expire ( also sets live )x9.args.delete=Trueaddprogram date timetags ( also sets live )x9.args.program_date_time=Truesetwindow sizefor live mode ( requires live )x9.args.window_size=5runx9.decode()\u21ea topbyterangewith the cli toolusefull path to video filewhen creating byterange m3u8.x9k3-i/home/a/input.ts-bprogrammaticallyfromx9k3importX9K3x9=X9K3()x9.self.args.byterange=Truex9.decode()output#EXTM3U#EXT-X-VERSION:4#EXT-X-TARGETDURATION:3#EXT-X-MEDIA-SEQUENCE:0#EXT-X-DISCONTINUITY-SEQUENCE:0#EXT-X-X9K3-VERSION:0.2.55#EXTINF:2.000000,#EXT-X-BYTERANGE:135548@0msnbc1000.ts#EXTINF:2.000000,#EXT-X-BYTERANGE:137992@135548msnbc1000.ts#EXTINF:2.000000,#EXT-X-BYTERANGE:134796@273540msnbc1000.ts#EXTINF:2.000000,#EXT-X-BYTERANGE:140436@408336msnbc1000.ts#EXTINF:2.000000,#EXT-X-BYTERANGE:130096@548772msnbc1000.tsplaylistsplaylists can be used as inputplaylist files must end in.playlistlines are video or video, sidecarif video,sidecar, the sidecar file only applies to that videoplaylists can have mpegts video, mpegts m3u8, and playlists.example playlistf10.ts,f10sidecar.txt#commentscanbeheref17.tsf60.tsflat-striped.ts#Commentscangoheretoo.flat.tsinput.tsnmax.tsnmx.ts,nmx-sidecar.txthttps://futzu.com/xaa.tshttps://example.com/index.m3u8,another-sidecar.txtusingx9k3-iout.playlistSidecar Filesload scte35 cues from a Sidecar fileSidecar Cues will be handled the same as SCTE35 cues from a video stream.line format for text fileinsert_pts, cuepts is the insert time for the cue, A four second preroll is standard.\ncue can be base64,hex, int, or bytesa@debian:~/x9k3$catsidecar.txt38103.868589,/DAxAAAAAAAAAP/wFAUAAABdf+/+zHRtOn4Ae6DOAAAAAAAMAQpDVUVJsZ8xMjEqLYemJQ==38199.918911,/DAsAAAAAAAAAP/wDwUAAABef0/+zPACTQAAAAAADAEKQ1VFSbGfMTIxIxGolm0=x9k3-inoscte35.ts-ssidecar.txtIn Live Mode you can do dynamic cue injection with aSidecar filetouchsidecar.txtx9k3-ivid.ts-ssidecar.txt-l#Openanotherterminalandprintfcuesintosidecar.txtprintf'38103.868589, /DAxAAAAAAAAAP/wFAUAAABdf+/+zHRtOn4Ae6DOAAAAAAAMAQpDVUVJsZ8xMjEqLYemJQ==\\n'>sidecar.txtSidecar filescan now accept 0 as the PTS insert time for Splice Immediate.Specify 0 as the insert time, the cue will be insert at the start of the next segment.Using 0 only works in live modeprintf'0,/DAhAAAAAAAAAP/wEAUAAAAJf78A/gASZvAACQAAAACokv3z\\n'>sidecar.txt\u21ea topA CUE-OUT can be terminated early using asidecar file.In the middle of a CUE-OUT send a splice insert with the out_of_network_indicator flag not set and the splice immediate flag set.\nDo the steps above ,\nand then do thisprintf'0,/DAcAAAAAAAAAP/wCwUAAAABfx8AAAEAAAAA3r8DiQ==\\n'>sidecar.txtIt will cause the CUE-OUT to end at the next segment start.#EXT-X-CUE-OUT13.4./seg5.ts:start:112.966667end:114.966667duration:2.233334#EXT-X-CUE-OUT-CONT2.233334/13.4./seg6.ts:start:114.966667end:116.966667duration:2.1#EXT-X-CUE-OUT-CONT4.333334/13.4./seg7.ts:start:116.966667end:118.966667duration:2.0#EXT-X-CUE-OUT-CONT6.333334/13.4./seg8.ts:start:117.0end:119.0duration:0.033333#EXT-X-CUE-INNone./seg9.ts:start:119.3end:121.3duration:2.3Using 0 only works in live modeCUESCUE-OUTA CUE-OUT is defined as:A Splice Insert Commandwith:theout_of_network_indicatorset toTrueabreak_duration.A Time Signal Commandand a Segmentation Descriptor with:asegmentation_durationasegmentation_type_idof:0x22: \"Break Start\",0x30: \"Provider Advertisement Start\",0x32: \"Distributor Advertisement Start\",0x34: \"Provider Placement Opportunity Start\",0x36: \"Distributor Placement Opportunity Start\",0x44: \"Provider Ad Block Start\",0x46: \"Distributor Ad Block Start\",\u21ea topCUE-INA CUE-IN is defined as:A Splice Insert Commandwith theout_of_network_indicatorset toFalseA Time Signal Commandand a Segmentation Descriptor with:asegmentation_type_idof:0x23: \"Break End\",0x31: \"Provider Advertisement End\",0x33: \"Distributor Advertisement End\",0x35: \"Provider Placement Opportunity End\",0x37: \"Distributor Placement Opportunity End\",0x45: \"Provider Ad Block End\",0x47: \"Distributor Ad Block End\",For CUE-OUT and CUE-IN,only the first Segmentation Descriptor will be usedSupported HLS Tags#EXT-X-CUE#EXT-X-DATERANGE#EXT-X-SCTE35#EXT-X-SPLICEPOINTx_cueCUE-OUT#EXT-X-DISCONTINUITY#EXT-X-CUE-OUT:242.0#EXTINF:4.796145,seg32.tsCUE-OUT-CONT#EXT-X-CUE-OUT-CONT:4.796145/242.0#EXTINF:2.12,CUE-IN#EXT-X-DISCONTINUITY#EXT-X-CUE-IN#EXTINF:5.020145,seg145.tsx_scte35CUE-OUT#EXT-X-DISCONTINUITY#EXT-X-SCTE35:CUE=\"/DAvAAAAAAAAAP/wFAUAAAKWf+//4WoauH4BTFYgAAEAAAAKAAhDVUVJAAAAAOv1oqc=\",CUE-OUT=YES#EXTINF:4.796145,seg32.tsCUE-OUT-CONT#EXT-X-SCTE35:CUE=\"/DAvAAAAAAAAAP/wFAUAAAKWf+//4WoauH4BTFYgAAEAAAAKAAhDVUVJAAAAAOv1oqc=\",CUE-OUT=CONT#EXTINF:2.12,seg33.tsCUE-IN#EXT-X-DISCONTINUITY#EXT-X-SCTE35:CUE=\"/DAqAAAAAAAAAP/wDwUAAAKWf0//4rZw2AABAAAACgAIQ1VFSQAAAAAtegE5\",CUE-IN=YES#EXTINF:5.020145,seg145.tsx_daterangeCUE-OUT#EXT-X-DISCONTINUITY#EXT-X-DATERANGE:ID=\"1\",START-DATE=\"2022-10-14T17:36:58.321731Z\",PLANNED-DURATION=242.0,SCTE35-OUT=0xfc302f00000000000000fff01405000002967fefffe16a1ab87e014c562000010000000a00084355454900000000ebf5a2a7#EXTINF:4.796145,seg32.tsCUE-IN#EXT-X-DISCONTINUITY#EXT-X-DATERANGE:ID=\"2\",END-DATE=\"2022-10-14T17:36:58.666073Z\",SCTE35-IN=0xfc302a00000000000000fff00f05000002967f4fffe2b670d800010000000a000843554549000000002d7a0139#EXTINF:5.020145,seg145.tsx_splicepointCUE-OUT#EXT-X-DISCONTINUITY#EXT-X-SPLICEPOINT-SCTE35:/DAvAAAAAAAAAP/wFAUAAAKWf+//4WoauH4BTFYgAAEAAAAKAAhDVUVJAAAAAOv1oqc=#EXTINF:4.796145,seg32.tsCUE-IN#EXT-X-DISCONTINUITY#EXT-X-SPLICEPOINT-SCTE35:/DAqAAAAAAAAAP/wDwUAAAKWf0//4rZw2AABAAAACgAIQ1VFSQAAAAAtegE5#EXTINF:5.020145,seg145.ts\u21ea topVODx9k3 defaults to VOD style playlist generation.All segment are listed in the m3u8 file.LiveActivated by the--live,--delete, or--replayswitch or by settingX9K3.live=True--liveLike VOD except:M3u8 manifests are regenerated every time a segment is writtenSegment creation is throttled when using non-live sources to simulate live streaming. ( like ffmpeg's \"-re\" )default Sliding Window size is 5, it can be changed with the-wswitch or by settingX9k3.window.size--deleteimplies--livedeletes segments when they move out of the sliding window of the m3u8.--replayimplies--liveimplies--deleteloops a video file and throttles segment creation to fake a live stream.\u21ea top"} +{"package": "xa", "pacakge-description": "xaAccessing information on population in the word.To install:pip install xa"} +{"package": "xaal.bugone", "pacakge-description": "No description available on PyPI."} +{"package": "xaalis-point", "pacakge-description": "No description available on PyPI."} +{"package": "xabier-burgos-AE-PEC2-xburgos", "pacakge-description": "PEC-2 Analitica Escalable - UAH - Master DS."} +{"package": "xac", "pacakge-description": "Powering your AI with human friendly explanationsXaipient API Client (xac)Status: Alpha, Version: 0.3.0Documentation:https://xaipient.github.io/xaipient-docs/RequirementsPython 3.6+Installation$pipinstallxacPython APIfromxacimportExplainerExplainer.login('user@domain.com')withExplainer()asgerman_explainer:german_explainer.from_config('tests/sample/configs/german-keras.yaml')global_imps=german_explainer.get_global_importances()global_aligns=german_explainer.get_global_alignments()global_rules=german_explainer.get_global_rules()local_attrs=german_explainer.get_local_attributions(feature_row=4)local_rules=german_explainer.get_global_rules(feature_row=4)counterfactuals=german_explainer.get_counterfactuals(feature_row=4)print(global_imps)print(global_aligns)print(global_rules)print(local_attrs)print(local_rules)print(counterfactuals)See Documentation for more detailsCommandline interface$xaclogin--emailuser@domain.com$xacsessioninit-fgerman-keras.yaml-ngerman_credit$xacjobsubmit-s-elocal_attributions-eglobal_importances--start4--end5$xacjoboutput-o/tmp/explns.jsonCommands:\n config Generate Xaipient YAML config files for customization\n info Display key information about API\n job Manage and Generate Explanations with Xaipient API\n jobs List explanation jobs.\n login Login with email and password.\n logout Logout and purge any tokens.\n session Manage and Create Sessions for Explanations\n sessions List all created sessions.\n version Display current version of client and API.See Documentation for more details"} +{"package": "xacc", "pacakge-description": "XACC provides a language and hardware agnostic programming framework for hybrid classical-quantum applications."} +{"package": "x-access-dumper", "pacakge-description": "X-Access-DumperDumps everything web accessible: git repos, files from.DS_Store, sql dumps, backups, configs...Use asdf or pyenv to install latest python version.Install:$pipinstallx-access-dumper\n$pipxinstallx-access-dumperUsage:$ x-access-dumper -h\n$ x-access-dumper url1 url2 url3\n$ x-access-dumper < urls.txt\n$ command | x-access-dumper\n$ x-access-dumper -vv https://target 2> log.txtTODO:exclude images and media files by default"} +{"package": "xacc-vqe", "pacakge-description": "XACC provides a language and hardware agnostic programming framework for hybrid classical-quantum applications."} +{"package": "xac-lib", "pacakge-description": "readme"} +{"package": "xacro", "pacakge-description": "No description available on PyPI."} +{"package": "xacro4sdf", "pacakge-description": "xacro4sdfxacro4sdfis a simple tool to define and parse XML macro forsdf (sdformat), you can usexacro4sdfto write modularized SDF xml (not nest model)xacro4sdf is similar, but different fromros/xacrowhich is desiged for urdf.xacro4sdf is more simple, but it's also more easy to use.Reference:ros/xacroWith Xacro, you can construct shorter and more readable XML files by using macros that expand to larger XML expressions.Attention:is departed after version2.0.0, you can use the tag with version1.2.6.1. UsageInstallation#install by pippipinstallxacro4sdf# or install from source code# git clone https://github.com/gezp/xacro4sdf.git# cd xacro4sdf && sudo python3 setup.py installcreate model.sdf.xmacro filerefer to files intest/(for exampletest/model.sdf.xmacro)generate model.sdf#cd testxacro4sdfmodel.sdf.xmacroit will generate model.sdf (the result should be same as test/model.sdf)more examples can be foundtestfolder.summary of XML Tagsdefinition of property and macro : core functionandinclude:include definition of property and macro from other xmacro fileuse of property and macro:${xxx}: use of property ,it's very useful to use math expressions.: use of macro, it's very useful for modular modeling.Tip:the xacro defination (,and) must be child node of root node.2. FeaturesPropertiesMacrosMath expressionsInclude2.1. PropertiesProperties are named values that can be inserted anywhere into the XML documentxacro definitiongenerated xml2.2. MacrosThe main feature ofxacro4sdfis macros.Define macros with the macro tag, then specify the macro name and a list of parameters. The list of parameters should be whitespace separated.The usage of Macros is to definewhich will be replaced withblock according to the paramname.xacro definition${m}${m*(y*y+z*z)/12}00${m*(x*x+z*z)/12}0${m*(x*x+z*z)/12}000.02000generated xml000.020000.20.0008333333333333335000.00216666666666666700.002166666666666667only support simple parameters (string and number),but block parameters isn't supported.it's supported to use otherxacro_macroinxacro_define_macrowhich is recursive definition.it's not recommended to define macro recursively (only support <=5).2.3. Math expressionswithin dollared-braces${xxxx}, you can also write simple math expressions.refer to examples ofPropertiesandMacrosit's implemented by callingeval()in python, so it's unsafe for some cases.2.4. Including other xmacro filesdefinition includeYou can include other xmacro files using thetag ,include other xmacro files according to paramuri.it will only include the definition of properties with tagand macros with tag.The uri formodelmeans to search file in a list of folders which are defined by environment variableIGN_GAZEBO_RESOURCE_PATHandGAZEBO_MODEL_PATHThe uri forfilemeans to open the file directly.it try to open the file with relative pathsimple_car/model.sdf.xmacro.you can also try to open file with absolute path/simple_car/model.sdf.xmacrowith urifile:///simple_car/model.sdf.xmacro.Tips:supports to include recursively.Don't use same name for xacro definition (the paramnameofand) , otherwise the priority of xacro definition need be considered.Be carefully when usingand2.5 pre-defined common.xmacroyou can directly use these macros in your xmacro file.3. Custom usage in pythonyou can use xacro4sdf in python easilyfromxacro4sdf.xacro4sdfimportXMLMacroxmacro=XMLMacro()#case1 parse from filexmacro.set_xml_file(inputfile)xmacro.generate()xmacro.to_file(outputfile)#case2 parse from xml stringxmacro.set_xml_string(xml_str)xmacro.generate()xmacro.to_file(outputfile)#case3 generate to stringxmacro.set_xml_file(inputfile)xmacro.generate()xmacro.to_string()#case4 custom propertyxmacro.set_xml_file(inputfile)# use custom property dictionary to overwrite global property# defined by (only in 'inputfile')kv={\"rplidar_a2_h\":0.8}xmacro.generate(custom_property=kv)xmacro.to_file(outputfile)#case5 set model staticxmacro.set_xml_file(inputfile)xmacro.generate()xmacro.set_static(True)xmacro.to_file(outputfile)4. Maintainer and Licensemaintainer : Zhenpeng Ge,zhenpeng.ge@qq.comxacro4sdfis provided under MIT License."} +{"package": "xacrodoc", "pacakge-description": "xacrodocxacrodoc is a tool for programmatically compilingxacro'd URDF files. It is fully functional\nwhether ROS is installed on the system or not.Why?Compile xacro files without a ROS installation.Avoid the clutter of redundant compiled raw URDFs; only keep the xacro\nsource files.Programmatically compose multiple xacro files and apply substitution\narguments to build a flexible URDF model.Convenient interfaces to provide URDF strings and URDF file paths as needed.\nFor example, many libraries (such asPinocchio) accept a URDF\nstring to build a model, but others (likePyBullet)\nonly load URDFs directly from file paths.See the documentationhere.Installationxacrodoc requires at least Python 3.8. Note that ROSdoes notneed to be\ninstalled on the system, but xacrodoc will also use its infrastructure to look\nfor packages if it is available.From pip:pip install xacrodocFrom source:git clone https://github.com/adamheins/xacrodoc\ncd xacrodoc\npip install .UsageBasicA basic use-case of compiling a URDF from a xacro file:fromxacrodocimportXacroDocdoc=XacroDoc.from_file(\"robot.urdf.xacro\")# or relative to a ROS package# e.g., for a file located at some_ros_package/urdf/robot.urdf.xacro:doc=XacroDoc.from_package_file(\"some_ros_package\",\"urdf/robot.urdf.xacro\")# convert to a string of URDFurdf_str=doc.to_urdf_string()# or write to a filedoc.to_urdf_file(\"robot.urdf\")# or just work with a temp file# this is useful for working with libraries that expect a URDF *file* (rather# than a string)withdoc.temp_urdf_file_path()aspath:# do stuff with URDF file located at `path`...# file is cleaned up once context manager is exitedFinding ROS packagesxacro files often make use of$(find )directives to resolve paths\nrelative to a given ROS package.\nIf ROS is installed on the system, xacrodoc automatically looks for ROS\npackages using the usual ROS infrastructure. If not, or if you are working\nwith packages outside of a ROS workspace, you'll need to tell xacrodoc where to\nfind packages. There are a few ways to do this:importxacrodocasxd# `from_file` automatically resolves packages by looking in each parent# directory of the given path to check for required ROS packages (as marked by# a package.xml file)doc=xd.XacroDoc.from_file(\"robot.urdf.xacro\")# if you want to disable this, pass `walk_up=False`:doc=xd.XacroDoc.from_file(\"robot.urdf.xacro\",walk_up=False)# we can also tell xacrodoc to walk up a directory tree manuallyxd.packages.walk_up_from(\"some/other/path\")# or we can give paths to directories to search for packages# packages can located multiple levels deep from the specified directories,# just like in a ROS workspace - the same package # search logic is used (since# we actually use rospkg under the hood)xd.packages.look_in([\"somewhere/I/keep/packages\",\"another/directory/with/packages\"])Multiple URDFsWe can also build a URDF programmatically from multiple xacro files:importxacrodocasxd# setup where to look for packages, if needed; for example:xd.packages.look_in([\"somewhere/I/keep/packages\"])# specify files to compose (using xacro include directives)includes=[\"robot_base.urdf.xacro\",\"robot_arm.urdf.xacro\",\"tool.urdf.xacro\"]doc=xd.XacroDoc.from_includes(includes)# includes can also use $(find ...) directives:includes=[\"$(find my_ros_package)/urdf/robot_base.urdf.xacro\",\"$(find another_ros_package)/urdf/\"robot_arm.urdf.xacro\",\"tool.urdf.xacro\"]doc=xd.XacroDoc.from_includes(includes)Substitution argumentsWe can also pass in substitution arguments to xacro files. For example, suppose our\nfilerobot.urdf.xacrocontains the directive.\nOn the command line, we could writexacro robot_base.urdf.xacro -o robot_base.urdf mass:=2to set the mass value. Programmatically, we dofromxacrodocimportXacroDocdoc=XacroDoc.from_file(\"robot.urdf.xacro\",subargs={\"mass\":\"2\"})Resolving file names with respect to packagesFinally, one feature of URDF (not just xacro files) is that file names (e.g.,\nfor meshes) can be specified relative to a package by usingpackage:///relative/path/to/meshsyntax, which depends on ROS and is not\nsupported by other non-ROS tools. xacrodoc automatically expands these\npaths out to full absolute paths, but this can be disabled by passingresolve_packages=Falseto theXacrodocconstructor.TestingTests usepytest. Some tests depend on additional submodules, which you can\nclone using:git submodule update --init --recursiveThen do:cd tests\npytest .LicenseMIT"} +{"package": "xacs", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xact", "pacakge-description": "Xact is a tool for configuring and deploying software intensive systems,\nfrom simulations running on cloud infrastructure to distributed intelligent\nsensing systems running on edge devices.Xact defines a unified configuration data structure for specifying component\ndependencies and for configuring various types of messaging middleware,\nenabling distributed dataflow systems to be rapidly and conveniently\ndescribed and deployed.It is intended to support model based systems and software engineering\nprocesses and to be a foundation for future design automation tools."} +{"package": "x-action", "pacakge-description": "No description available on PyPI."} +{"package": "xacto", "pacakge-description": "XactoCLI Analyzer/GeneratorIntrospect, compose, marshal and export arbitrary callables into a unified,\nhierarchical, command-line interface (CLI)Featuresauto-find tools\nscan signatures and export as CLI nodeWhyFAST! EASY! natural import usage!--helpis decent!QuickstartInstall:# pip install xactoPrepare:# ln -s $(which xacto) doCreate python file attools/work.py:frompprintimportpprint__all__=[\"easy\",\"hard\",\"manual\"]defeasy(method,speed=16,*tasks):\"\"\"The simple version\"\"\"pprint(locals())defhard(method,speed=32,*tasks,**params):\"\"\"The difficult version\"\"\"pprint(locals())classmanual(object):\"\"\"The laborious version\"\"\"def__call__(self,method,speed,*tasks):pprint(locals())defmethod(self,process):\"\"\"Howto perform operation\"\"\"defspeed(self,ops=64):\"\"\"Operations per second\"\"\"deftasks(self,pri,sec,ter):\"\"\"Various tasks\"\"\"View--help:# ./do work --help\nusage: do work OBJECT ...\n\nadditional modules:\n OBJECT := { .do.work }\n easy The simple version\n hard The difficult version\n manual\n The laborious versionView object-level--help:# ./do work manual --help\nusage: do work manual --method PROCESS --speed [OPS] [tasks [tasks ...]]\n\nThe laborious version\n\npositional arguments:\n tasks Various tasks\n\noptional arguments:\n --method PROCESS Howto perform operation\n --speed [OPS] Operations per second\n\nThe laborious versionRun tool (function):# ./do work hard --method=cheat --code=iddqd taskN\n{'method': 'cheat',\n 'params': {'code': 'iddqd'},\n 'speed': 32,\n 'tasks': ('taskN',)}Run tool (class):# ./do work manual --method=cheap --speed=256 taskN\n{'method': 'cheap',\n 'self': ,\n 'speed': '256',\n 'tasks': ('taskN',)}Limitationstrue/false quirkyness (default=True means \u2013default flips to False)TODORELEASE!testing: set-like functions, import semantics.. everythinghandle bools betterdetect outputstandard output structureprettify to ttylazy load toolslazy import globals (cpython)bytecode cacheargument forwarding/chainingintegrate with zippy.shelltab-completionauto-reduce common components for aliasesmake xacto object accessible to tools"} +{"package": "xactor", "pacakge-description": "XActor is a framework for doing distributed computing in Python,\nusing the actor model of programming.XActor\u2019s documentation is hosted athttps://xactor.readthedocs.io/en/latestCompiling latest documentationTo compile the latest version of the documentation from source,\nplease checkdocs/source/index.rst.XActor depends on mpi4py which requires a MPI implementation\nand compiler tools be installed on the system.Installing MPICH and mpi4py inside a conda environmentTo create a new virtual environment with conda,\nhave Anaconda/Miniconda setup on your system.\nInstallation instructions for Anaconda can be foundhere.\nAfter installation of Anaconda/Miniconda\nexecute the following commands:$condacreate-nxactor-cconda-forgepython=3mpichmpi4pyThe above command creates a new conda environment calledxactorwith python, mpich and mpi4py installed.The following commands assume you are inside the above conda environment.Building the documentation from sourceTo build and view the documentation as HTML, execute the following commands:$gitclonehttps://github.com/NSSAC/xactor.git$cdxactor$pipinstall-e.$pipinstall-rdocs/requirements.txt$make-Cdocs$docs/build/html/index.html"} +{"package": "xaddpy", "pacakge-description": "Python Implementation of XADDThis repository implements the Python version of XADD (eXtended Algebraic Decision Diagrams) which was first introduced inSanner et al. (2011); you can find the original Java implementation fromhere.Our Python XADD code usesSymEnginefor symbolically maintaining all variables and related operations, andPULPis used for pruning unreachable paths. Note that we only check linear conditionals. If you have Gurobi installed and configured in the conda environment, then PULP will use Gurobi for solving (MI)LPs; otherwise, the default solver (CBC) is going to be used. However, we do not actively support optimizers other than Gurobi for now.Note that the implementation forEMSPO--- Exact symbolic reduction of linear Smart Predict+Optimize to MILP (Jeong et al., ICML-22) --- has been moved to the branchemspo.You can find the implementation for theCPAIOR-23work --- A Mixed-Integer Linear Programming Reduction of Disjoint Bilinear Programs via Symbolic\nVariable Elimination --- inexamples/dblp.InstallationLoad your Python virtual environment then type the following commands for package installationpipinstallxaddpy# Optional: if you want to use Gurobi for the 'reduce_lp' method# that prunes out unreachable partitions using LP solverspipinstallgurobipy# If you have a licenseInstalling pygraphviz for visualizationWithpygraphviz, you can visualize a given XADD in a graph format, which can be very useful. Here, we explain how to install the package.To begin with, you need to install the following:graphvizpygraphvizMake sure you have activated the right conda environment withconda activate YOUR_CONDA_ENVIRONMENT.Step 1: Installing graphvizFor Ubuntu/Debian users, run the following command.sudoapt-getinstallgraphvizgraphviz-devFor Fedora and Red Hat systems, you can do as follows.sudodnfinstallgraphvizgraphviz-develFor Mac users, you can usebrewto installgraphviz.brewinstallgraphvizUnfortunately, we do not provide support for Windows systems, though you can refer to thepygraphviz documentationfor information.Step 2: Installing pygraphvizLinux systemspipinstallpygraphvizMacOSpython-mpipinstall\\--global-option=build_ext\\--global-option=\"-I$(brew--prefixgraphviz)/include/\"\\--global-option=\"-L$(brew--prefixgraphviz)/lib/\"\\pygraphvizNote that due to the default installation location bybrew, you need to provide some additional options forpipinstallation.Using xaddpyYou can find useful XADD usecases in thexaddpy/tests/test_bool_var.pyandxaddpy/tests/test_xadd.pyfiles. Here, we will first briefly discuss different ways to build an initial XADD that you want to work with.Loading from a fileIf you know the entire structure of an initial XADD, then you can create a text file specifying the XADD and load it using theXADD.import_xaddmethod. It's important that, when you manually write down the XADD you have, you follow the same syntax rule as in the example file shown below.Below is a part of the XADD written inxaddpy/tests/ex/bool_cont_mixed.xadd:...\n ( [x - y <= 0]\n ( [2 * x + y <= 0]\n ([x])\n ([y])\n )\n ( [b3]\n ([2 * x])\n ([2 * y])\n )\n )\n...Here,[x-y <= 0]defines a decision expression; its true branch is another node with the decision[2 * x + y <= 0], while the decision of the false branch is a Boolean variableb3. Similarly, if[2 * x + y <= 0]holds true, then we get the leaf value[x]; otherwise, we get[y].All expressions should be wrapped with brackets, including Boolean variables.A SymEngineSymbolobject will be created for each unique variable.To load this XADD, you can do the following:fromxaddpyimportXADDcontext=XADD()fname='xaddpy/tests/ex/bool_cont_mixed.xadd'orig_xadd=context.import_xadd(fname)Following the Java implementation, we call the instantiated XADD objectcontext. This object maintains and manages all existing/new nodes and decision expressions. For example,context._id_to_nodeis a Python dictionary that stores mappings from node IDs (int) to the correspondingNodeobjects. For more information, please refer to theconstructor of theXADDclass.To check whether you've got the right XADD imported, you can print it out.print(f\"Imported XADD:\\n{context.get_repr(orig_xadd)}\")TheXADD.get_reprmethod will returnrepr(node)and the string representation of each XADD node is implemented inxaddpy/xadd/node.py. Beware that the printing method can be slow for a large XADD.Recursively building an XADDAnother way of creating an initial XADD node is by recursively building it with theapplymethod. A very simple example would be something like this:fromxaddpyimportXADDimportsymengine.lib.symengine_wrapperascorecontext=XADD()x_id=context.convert_to_xadd(core.Symbol('x'))y_id=context.convert_to_xadd(core.Symbol('y'))sum_node_id=context.apply(x_id,y_id,op='add')comp_node_id=context.apply(sum_node_id,y_id,op='min')print(f\"Sum node:\\n{context.get_repr(sum_node_id)}\\n\")print(f\"Comparison node:\\n{context.get_repr(comp_node_id)}\")You can check that the print output showsSum node:\n( [x + y] ) node_id: 9\n\nComparison node:\n( [x <= 0] (dec, id): 10001, 10\n ( [x + y] ) node_id: 9 \n ( [y] ) node_id: 8 \n)which is the expected outcome!Check out a much more comprehensive example demonstrating the recursive construction of a nontrivial XADD from here:pyRDDLGym/XADD/RDDLModelXADD.py.Directly creating an XADD nodeFinally, you might want to build a constant node, an arbitrary decision expression, and a Boolean decision directly. To this end, let's consider building the following XADD:([b]\n ([1])\n ([x + y <= 0]\n ([0])\n ([2])\n )\n)To do this, we will first create an internal node whose decision is[x + y <= 0], the low and the high branches are[0]and[2](respectively). UsingSymEngine'sSfunction (or you can usesympify), you can turn an algebraic expression involving variables and numerics into a symbolic expression. Given this decision expression, you can get its unique index usingXADD.get_dec_expr_indexmethod. You can use the decision ID along with the ID of the low and high nodes connected to the decision to create the corresponding decision node, usingXADD.get_internal_node.importsymengine.lib.symengine_wrapperascorefromxaddpyimportXADDcontext=XADD()# Get the unique ID of the decision expressiondec_expr:core.Basic=core.S('x + y <= 0')dec_id,is_reversed=context.get_dec_expr_index(dec_expr,create=True)# Get the IDs of the high and low branches: [0] and [2], respectivelyhigh:int=context.get_leaf_node(core.S(0))low:int=context.get_leaf_node(core.S(2))ifis_reversed:low,high=high,low# Create the decision node with the IDsdec_node_id:int=context.get_internal_node(dec_id,low=low,high=high)print(f\"Node created:\\n{context.get_repr(dec_node_id)}\")Note thatXADD.get_dec_expr_indexreturns a boolean variableis_reversedwhich isFalseif the canonical decision expression of the given decision has the same inequality direction. If the direction has changed, thenis_reversed=True; in this case, low and high branches should be swapped.Another way of creating this node is to use theXADD.get_dec_nodemethod. This method can only be used when the low and high nodes are terminal nodes containing leaf expressions.dec_node_id=context.get_dec_node(dec_expr,low_val=core.S(2),high_val=core.S(0))Note also that you need to wrap constants with thecore.Sfunction to turn them intocore.Basicobjects.Now, it remains to create a decision node with the Boolean variableband connect it to its low and high branches.fromxaddpy.utils.symengineimportBooleanVarb=BooleanVar(core.Symbol('b'))dec_b_id,_=context.get_dec_expr_index(b,create=True)First of all, you need to import and instantiate aBooleanVarobject for a Boolean variable. Otherwise, the variable won't be recognized as a Boolean variable in XADD operations!Once you have the decision ID, we can finally link this decision node with the node created earlier.high:int=context.get_leaf_node(core.S(1))node_id:int=context.get_internal_node(dec_b_id,low=dec_node_id,high=high)print(f\"Node created:\\n{context.get_repr(node_id)}\")And we get the following print outputs.Output:\nNode created:\n( [b] (dec, id): 2, 9\n ( [1] ) node_id: 1 \n ( [x + y <= 0] (dec, id): 10001, 8\n ( [0] ) node_id: 0 \n ( [2] ) node_id: 7 \n ) \n)XADD OperationsXADD.apply(id1: int, id2: int, op: str)You can perform theapplyoperation to two XADD nodes with IDsid1andid2. Below is the list of the supported operators (op):Non-Boolean operations'max', 'min''add', 'subtract''prod', 'div'Boolean operations'and''or'Relational operations'!=', '==''>', '>=''<', '<='XADD.unary_op(node_id: int, op: str) (unary operations)You can also apply the following unary operators to a single XADD node recursively (also checkUNARY_OPinxaddpy/utils/global_vars.py). In this case, an operator will be applied to each and every leaf value of a given node. Hence, the decision expressions will remain unchanged.'sin, 'cos', 'tan''sinh', 'cosh', 'tanh''exp', 'log', 'log2', 'log10', 'log1p''floor', 'ceil''sqrt', 'pow''-', '+''sgn' (sign function... sgn(x) = 1 if x > 0; 0 if x == 0; -1 otherwise)'abs''float', 'int''~' (negation)Thepowoperation requires an additional argument specifying the exponent.XADD.evaluate(node_id: int, bool_assign: dict, cont_assign: bool, primitive_type: bool)When you want to assign concrete values to Boolean and continuous variables, you can use this method. An example is provided in thetest_mixed_evalfunction defined inxaddpy/tests/test_bool_var.py.As another example, let's say we want to evaluate the XADD node defined a few lines above.x,y=core.symbols('x y')bool_assign={b:True}cont_assign={x:2,y:-1}res=context.evaluate(node_id,bool_assign=bool_assign,cont_assign=cont_assign)print(f\"Result:{res}\")In this case,b=Truewill directly leads to the leaf value of1regardless of the assignment given toxandyvariables.bool_assign={b:False}res=context.evaluate(node_id,bool_assign=bool_assign,cont_assign=cont_assign)print(f\"Result:{res}\")If we change the value ofb, we can see that we get2. Note that you have to make sure that all symbolic variables get assigned specific values; otherwise, the function will returnNone.XADD.substitute(node_id: int, subst_dict: dict)If instead you want to assign values to a subset of symbolic variables while leaving the other variables as-is, you can use thesubstitutemethod. Similar toevaluate, you need to pass in a dictionary mapping SymEngineSymbols to their concrete values.For example,subst_dict={x:1}node_id_after_subs=context.substitute(node_id,subst_dict)print(f\"Result:\\n{context.get_repr(node_id_after_subs)}\")which outputsResult:\n( [b] (dec, id): 2, 16\n ( [1] ) node_id: 1 \n ( [y + 1 <= 0] (dec, id): 10003, 12\n ( [0] ) node_id: 0 \n ( [2] ) node_id: 7 \n ) \n)as expected.XADD.collect_vars(node_id: int)If you want to extract all Boolean and continuous symbols existing in an XADD node, you can use this method.var_set=context.collect_vars(node_id)print(f\"var_set:{var_set}\")Output:\nvar_set: {y, b, x}This method can be useful to figure out which variables need to have values assigned in order to evaluate a given XADD node.XADD.make_canonical(node_id: int)This method gives a canonical order to an XADD that is potentially unordered. Note that theapplymethod already callsmake_canonicalwhen theopis one of('min', 'max', '!=', '==', '>', '>=', '<', '<=', 'or', 'and').Variable EliminationSum out:XADD.op_out(node_id: int, dec_id: int, op: str = 'add')Let's say we have a joint probability distribution function over Boolean variablesb1, b2, i.e.,P(b1, b2)as in the following example.P(b1, b2)=( [b1]\n ( [b2] \n ( [0.25] )\n ( [0.3] )\n )\n ( [b2]\n ( [0.1] )\n ( [0.35] )\n )\n)Notice that the values are non-negative and sum up to one, making this a valid probability distribution. Now, one may be interested in marginalizing out a variableb2to getP(b1) = \\sum_{b2} P(b1, b2). This can be done in XADD by using theop_outmethod.Let's directly dive into an example:# Load the joint probability as XADDp_b1b2=context.import_xadd('xaddpy/tests/ex/bool_prob.xadd')# Get the decision index of `b2`b2=BooleanVar(core.Symbol('b2'))b2_dec_id,_=context.get_dec_expr_index(b2,create=False)# Marginalize out `b2`p_b1=context.op_out(node_id=p_b1b2,dec_id=b2_dec_id,op='add')print(f\"P(b1):\\n{context.get_repr(p_b1)}\")Output: \nP(b1): \n( [b1] (dec, id): 1, 26\n ( [0.55] ) node_id: 25 \n ( [0.45] ) node_id: 24 \n)As expected, the obtainedP(b1)is a function of onlyb1variable, and the probabilities sum up to1.Prod outSimilarly, if we specifyop='prod', we can 'prod out' a Boolean variable from a given XADD.Max out (or min out) continuous variables:XADD.min_or_max_var(node_id: int, var: VAR_TYPE, is_min: bool)One of the most interesting and useful applications of symbolic variable elimination is 'maxing out' or 'minning out'continuousvariable(s) from a symbolic function. SeeJeong et al. (2023)andJeong et al. (2022)for more detailed discussions. Look up themin_or_max_varmethod in the xadd.py file. For now, we only support optimizing a linear or disjointly bilinear expressions at the leaf values and decision expressions.As a concrete toy example, imagine the problem of inventory management. There is a Boolean variabledwhich denotes the level of demand (i.e.,d=Trueif demand is high; otherwised=False). Let's say the current inventory level of a product of interest isx \\in [-1000, 1000]. Suppose we can place an order of amounta \\in [0, 500]for this product. And we will have the following reward based on the current demand, inventory level, and the new order:( [d]\n ( [x >= 150]\n ( [150 - 0.1 * a - 0.05 * x ] )\n ( [(x - 150) - 0.1 * a - 0.05 * x] )\n )\n ( [x >= 50]\n ( [50 - 0.1 * a - 0.05 * x] )\n ( [(x - 50) - 0.1 * a - 0.05 * x] )\n )\n)Though it is natural to consider multi-step decisions for this kind of problem, let's only focus on optimizing this reward for a single step, for the sake of simplicity and illustration.So, given this reward, what we might be interested in is the maximum reward we can obtain, subject to the demand level and the current inventory level. That is, we want to computemax_a reward(a, x, d).# Load the reward function as XADDreward_dd=context.import_xadd('xaddpy/tests/ex/inventory.xadd')# Update the bound information over variables of interesta,x=core.Symbol('a'),core.Symbol('x')context.update_bounds({a:(0,500),x:(-1000,1000)})# Max out the order quantitymax_reward_d_x=context.min_or_max_var(reward_dd,a,is_min=False,annotate=True)print(f\"Maximize over a:\\n{context.get_repr(max_reward_d_x)}\")Output:\nMaximize over a: \n( [d] (dec, id): 1, 82\n ( [-150 + x <= 0] (dec, id): 10002, 81\n ( [-150 + 0.95*x] ) node_id: 72 anno: 0 \n ( [150 - 0.05*x] ) node_id: 58 anno: 0 \n ) \n ( [-50 + x <= 0] (dec, id): 10003, 51\n ( [-50 + 0.95*x] ) node_id: 42 anno: 0 \n ( [50 - 0.05*x] ) node_id: 29 anno: 0 \n ) \n)To obtain this result, note that we should provide the bound information over the continuous variables. If not, then(-oo, oo)will be used as the bounds.If we want to know which values ofawill yield the optimal outcomes, we can apply the argmax operation. Specifically,argmax_a_id=context.reduced_arg_min_or_max(max_reward_d_x,a)print(f\"Argmax over a:\\n{context.get_repr(argmax_a_id)}\")Output:\nArgmax over a: \n( [0] ) node_id: 0Trivially in this case, not ordering any new products will maximize the one-step reward, which makes sense. A more interesting case would, of course, be when we have to make sequential decisions taking into account stochastic demands and the product level that changes according to the order amount and the demand. For this kind of problems, we suggest you take a look atSymbolic Dynamic Programming (SDP).Now, if we further optimize themax_reward_d_xoverxvariable, we get the following:# Max out the inventory levelmax_reward_d=context.min_or_max_var(max_reward_d_x,x,is_min=False,annotate=True)print(f\"Maximize over x:\\n{context.get_repr(max_reward_d)}\")# Get the argmax over xargmax_x_id=context.reduced_arg_min_or_max(max_reward_d,x)print(f\"Argmax over x:\\n{context.get_repr(argmax_x_id)}\")Output:\nMaximize over x: \n( [d] (dec, id): 1, 105\n ( [142.5] ) node_id: 102 anno: 99 \n ( [47.5] ) node_id: 89 anno: 85 \n)\nArgmax over x: \n( [d] (dec, id): 1, 115\n ( [150] ) node_id: 99 \n ( [50] ) node_id: 85 \n)The results tells us that the maximum achievable reward is 142.5 whend=True, x=150or 47.5 whend=False, x=50.Max (min) out Boolean variables withXADD.min_or_max_varEliminating Boolean variables with max or min operations can be easily done by using the previously discussedmin_or_max_varmethod. You just need to pass the Boolean variable to the method.Definite IntegralGiven an XADD node and a symbolic variable, you can integrate out the variable from the node. Seetest_def_int.pywhich provides examples of this operation.CitationPlease use the following bibtex for citations:@InProceedings{pmlr-v162-jeong22a,\n title = \t {An Exact Symbolic Reduction of Linear Smart {P}redict+{O}ptimize to Mixed Integer Linear Programming},\n author = {Jeong, Jihwan and Jaggi, Parth and Butler, Andrew and Sanner, Scott},\n booktitle = \t {Proceedings of the 39th International Conference on Machine Learning},\n pages = \t {10053--10067},\n year = \t {2022},\n volume = \t {162},\n series = \t {Proceedings of Machine Learning Research},\n month = \t {17--23 Jul},\n publisher = {PMLR},\n}"} +{"package": "xades", "pacakge-description": "XaDES XML Signature created with cryptography and lxml"} +{"package": "xadix.argparse-tree", "pacakge-description": "# This is title` More text ... `"} +{"package": "xadix-cloudflare", "pacakge-description": "No description available on PyPI."} +{"package": "xadix-dnspod", "pacakge-description": "No description available on PyPI."} +{"package": "xadmin", "pacakge-description": "Drop-in replacement of Django admin comes with lots of goodies, fully extensible with plugin support, pretty UI based on Twitter Bootstrap.Live Demohttp://demo.xadmin.ioUser: adminPassword: adminFeaturesDrop-in replacement of Django adminTwitter Bootstrap based UI with theme supportExtensible with plugin supportBetter filter, date range, number range, etc.Built-in data export with xls, csv, xml and json formatDashboard page with widget supportIn-site bookmarkingFull CRUD methodsScreenshotsGet StartedInstallXadmin is best installed via PyPI. To install the latest version, run:pipinstallxadminor Install from github source:pipinstallgit+git://github.com/sshwsfc/xadmin.gitInstall Requiresdjango>=1.9django-crispy-forms>=1.6.0 (For xadmin crispy forms)django-reversion([OPTION] For object history and reversion feature, please select right version by your django, seechangelog)django-formtools([OPTION] For wizward form)xlwt([OPTION] For export xls files)xlsxwriter([OPTION] For export xlsx files)DocumentationEnglish (coming soon)ChineseChangelogs0.6.0Compact with Django1.9.Add Clock Picker widget for timepicker.Fixed some userface errors.0.5.0Update fontawesome to 4.0.3Update javascript files to compact fa icons new versionUpdate tests for the new instance method of the AdminSite classAdded demo graphsAdded quickfilter plugin.Adding apps_icons with same logic of apps_label_title.Add xlsxwriter for big data export.Upgrade reversion models admin list page.Fixed reverse many 2 many lookup giving FieldDoesNotExist error.Fixed user permission check in inline model.DetailOnline GroupQQ\u7fa4 : 282936295Run Demo Locallycddemo_app./manage.pymigrate./manage.pyrunserverOpenhttp://127.0.0.1:8000in your browser, the admin user password isadminHelpHelp Translate :http://trans.xadmin.io"} +{"package": "xadmin2", "pacakge-description": "All rights reserved.Redistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice,\nthis list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in the\ndocumentation and/or other materials provided with the distribution.Neither the name of Django Xadmin nor the names of its contributors may be used\nto endorse or promote products derived from this software without\nspecific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \u201cAS IS\u201d AND\nANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR\nANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON\nANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\nDownload-URL:https://github.com/beeguess/xadmin/archive/master.zipDescription: # Xadmin [![Build Status](https://travis-ci.org/sshwsfc/xadmin.png?branch=master)](https://travis-ci.org/sshwsfc/xadmin)Drop-in replacement of Django admin comes with lots of goodies, fully\nextensible with plugin support, pretty UI based on Twitter Bootstrap.## Live DemoUser: adminPassword: admin## FeaturesDrop-in replacement of Django adminTwitter Bootstrap based UI with theme supportExtensible with plugin supportBetter filter, date range, number range, etc.Built-in data export with xls, csv, xml and json formatDashboard page with widget supportIn-site bookmarkingFull CRUD methods## Screenshots![](https://raw.github.com/sshwsfc/django-xadmin/docs-chinese/docs/images/plugins/action.png)![](https://raw.github.com/sshwsfc/django-xadmin/docs-chinese/docs/images/plugins/filter.png)![](https://raw.github.com/sshwsfc/django-xadmin/docs-chinese/docs/images/plugins/chart.png)![](https://raw.github.com/sshwsfc/django-xadmin/docs-chinese/docs/images/plugins/export.png)![](https://raw.github.com/sshwsfc/django-xadmin/docs-chinese/docs/images/plugins/editable.png)## Get Started### InstallXadmin is best installed via PyPI. To install the latest version, run:`{.sourceCode.bash} pip install xadmin2 `or Install from github source:`{.sourceCode.bash} pip installgit+git://github.com/wgbbiao/xadmin.git`## Install Requires[django](http://djangoproject.com) >=3[django-crispy-forms](http://django-crispy-forms.rtfd.org) >=1.8.1\n(For xadmin crispy forms)[django-reversion](https://github.com/etianen/django-reversion)>=3.0.4\n([OPTION] For object history and reversion feature, please select\nright version by your django, see\n[changelog](https://github.com/etianen/django-reversion/blob/master/CHANGELOG.rst)\n)[django-formtools](https://github.com/django/django-formtools)>=2.1\n([OPTION] For wizward form)[xlwt](http://www.python-excel.org/)>=1.3.0 ([OPTION] For export xls files)[xlsxwriter](https://github.com/jmcnamara/XlsxWriter) >=1.2.6([OPTION] For\nexport xlsx files)## DocumentationEnglish (coming soon)[Chinese](https://xadmin.readthedocs.org/en/latest/index.html)## Changelogs### 2.0.4Compact with Django4.0, Django3.0.### 2.0.1Compact with Django2.0.### 0.6.0Compact with Django1.9.Add Clock Picker widget for timepicker.Fixed some userface errors.### 0.5.0Update fontawesome to 4.0.3Update javascript files to compact fa icons new versionUpdate tests for the new instance method of the AdminSite classAdded demo graphsAdded quickfilter plugin.Adding apps_icons with same logic of apps_label_title.Add xlsxwriter for big data export.Upgrade reversion models admin list page.Fixed reverse many 2 many lookup giving FieldDoesNotExist error.Fixed user permission check in inline model.Detail_[detail](./changelog.md)## Online GroupQQ \u7fa4 : 282936295## Run Demo Locally`{.sourceCode.bash} cd demo_app ./manage.py migrate ./manage.py runserver `Open in your browser, the admin user password isadmin## HelpHelp Translate : Keywords: admin,django,xadmin,bootstrap\nPlatform: UNKNOWN\nClassifier: Development Status :: 4 - Beta\nClassifier: Environment :: Web Environment\nClassifier: Framework :: Django\nClassifier: Intended Audience :: Developers\nClassifier: License :: OSI Approved :: BSD License\nClassifier: Operating System :: OS Independent\nClassifier: Programming Language :: JavaScript\nClassifier: Programming Language :: Python\nClassifier: Programming Language :: Python :: 3.4\nClassifier: Topic :: Internet :: WWW/HTTP\nClassifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content\nClassifier: Topic :: Software Development :: Libraries :: Python Modules\nDescription-Content-Type: text/markdown\nProvides-Extra: Reversion\nProvides-Extra: Excel"} +{"package": "xadmin-captcha", "pacakge-description": "this a xadmin captcha package"} +{"package": "xadmin-croxlink", "pacakge-description": "No description available on PyPI."} +{"package": "xadmin-croxlink2", "pacakge-description": "All rights reserved.Redistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice,\nthis list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in the\ndocumentation and/or other materials provided with the distribution.Neither the name of Django Xadmin nor the names of its contributors may be used\nto endorse or promote products derived from this software without\nspecific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \u201cAS IS\u201d AND\nANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR\nANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON\nANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\nDownload-URL:https://github.com/CROXLINK/django-xadmin/archive/django2.zipDescription: UNKNOWN\nKeywords: admin,django,xadmin,bootstrap\nPlatform: UNKNOWN\nClassifier: Development Status :: 4 - Beta\nClassifier: Environment :: Web Environment\nClassifier: Framework :: Django\nClassifier: Intended Audience :: Developers\nClassifier: License :: OSI Approved :: BSD License\nClassifier: Operating System :: OS Independent\nClassifier: Programming Language :: JavaScript\nClassifier: Programming Language :: Python\nClassifier: Programming Language :: Python :: 2.7\nClassifier: Programming Language :: Python :: 3.4\nClassifier: Topic :: Internet :: WWW/HTTP\nClassifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content\nClassifier: Topic :: Software Development :: Libraries :: Python Modules\nProvides-Extra: Excel\nProvides-Extra: Reversion"} +{"package": "xadmind3", "pacakge-description": "No description available on PyPI."} +{"package": "xadmin-django", "pacakge-description": "All rights reserved.Redistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice,\nthis list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in the\ndocumentation and/or other materials provided with the distribution.Neither the name of Django Xadmin nor the names of its contributors may be used\nto endorse or promote products derived from this software without\nspecific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \u201cAS IS\u201d AND\nANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR\nANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON\nANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\nDownload-URL:http://github.com/liangdongchang/django-xadmin/master.zipDescription: Based on xadmin.Drop-in replacement of Django admin comes with lots of goodies, fully extensible with plugin support, pretty UI based on Twitter Bootstrap.\nKeywords: admin,django,xadmin,bootstrap\nPlatform: UNKNOWN\nClassifier: Development Status :: 4 - Beta\nClassifier: Environment :: Web Environment\nClassifier: Framework :: Django\nClassifier: Intended Audience :: Developers\nClassifier: License :: OSI Approved :: BSD License\nClassifier: Operating System :: OS Independent\nClassifier: Programming Language :: JavaScript\nClassifier: Programming Language :: Python\nClassifier: Programming Language :: Python :: 2.7\nClassifier: Programming Language :: Python :: 3.4\nClassifier: Topic :: Internet :: WWW/HTTP\nClassifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content\nClassifier: Topic :: Software Development :: Libraries :: Python Modules\nProvides-Extra: Excel\nProvides-Extra: Reversion"} +{"package": "xadmin-nimbus", "pacakge-description": "A Python Extended for Django.Supports Python 2.7, 3.4 or 3.5+Free software: Apache License 2.0On thePython Package Index (PyPI)Python Package Index (PyPI):https://pypi.python.org/pypi/xadmin_nimbus/InstallEasiest installation is viapippip install xadmin_nimbusQuick UsageCopyright and LicenseCopyright (c) 2001-2017william.ren@live.cnAll rights reserved.This software is licensed under the Apache License, Version 2.0. The\nApache License is a well-established open source license, enabling\ncollaborative open source software development.See the \u201cLICENSE\u201d file for the full text of the license terms."} +{"package": "xadmin-py3", "pacakge-description": "Xadmin-py3\u4f7f\u7528 Xadmin \u60a8\u53ea\u9700\u5b9a\u4e49\u60a8\u6570\u636e\u7684\u5b57\u6bb5\u7b49\u4fe1\u606f\uff0c\u5373\u53ef\u5373\u523b\u83b7\u5f97\u4e00\u4e2a\u529f\u80fd\u5168\u9762\u7684\u7ba1\u7406\u7cfb\u7edf\u3002\u4e0d\u4ec5\u5982\u6b64\uff0c\u60a8\u8fd8\u53ef\u4ee5\u65b9\u4fbf\u7684\u6269\u5c55\u66f4\u591a\u7684\u5b9a\u5236\u529f\u80fd\u548c\u7cfb\u7edf\u754c\u9762\u3002\u5728\u7ebf\u6f14\u793a\u5f85\u66f4\u65b0...\u529f\u80fd\u66f4\u597d\u7684\u8fc7\u6ee4\u5668\uff0c\u65e5\u671f\u8303\u56f4\uff0c\u6570\u91cf\u8303\u56f4\u7b49\u3002\u57fa\u4e8eBootstrap3\uff0c\u652f\u6301\u5728\u591a\u79cd\u5c4f\u5e55\u4e0a\u65e0\u7f1d\u6d4f\u89c8\uff0c\u5e76\u652f\u6301Bootstrap\u4e3b\u9898\u6a21\u677f\u5185\u7f6e\u4e30\u5bcc\u7684\u63d2\u4ef6\u529f\u80fd\u3002\u5305\u62ec\u6570\u636e\u5bfc\u51fa\u3001\u4e66\u7b7e\u3001\u56fe\u8868\u3001\u6570\u636e\u6dfb\u52a0\u5411\u5bfc\u53ca\u56fe\u7247\u76f8\u518c\u7b49\u591a\u79cd\u6269\u5c55\u529f\u80fd\u63d2\u4ef6\u5f00\u53d1\u7b80\u5355\uff0c\u5b89\u88c5\u65b9\u4fbf\u3002\u622a\u56fe\u5f85\u66f4\u65b0...\u5165\u95e8\u5b89\u88c5\u901a\u8fc7PyPI\u5b89\u88c5\uff0c\u8bf7\u8fd0\u884c\uff1apip install xadmin-py3\u6216\u4eceGitHub\u6e90\u5b89\u88c5\uff1apip install git+git://github.com/ldsxp/xadmin-py3.git\u5b89\u88c5\u9700\u8981django>=1.9django-crispy-forms>=1.6.0 (For xadmin crispy forms)django-reversion([OPTION] For object history and reversion feature, please select right version by your django, seechangelog)django-formtools([OPTION] For wizward form)xlwt([OPTION] For export xls files)xlsxwriter([OPTION] For export xlsx files)\u6587\u6863Chinese\u66f4\u6539\u65e5\u5fd7\u5728\u672c\u5730\u8fd0\u884cDemocd demo_app\n./manage.py migrate\n./manage.py runserverhttp://127.0.0.1:8000\u5728\u6d4f\u89c8\u5668\u4e2d\u6253\u5f00http://127.0.0.1:8000\uff0c\u7ba1\u7406\u5458\u7528\u6237\u5bc6\u7801\u4e3aadmin\u3002"} +{"package": "xadmin-x", "pacakge-description": "All rights reserved.Redistribution and use in source and binary forms, with or without modification,\nare permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice,\nthis list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in the\ndocumentation and/or other materials provided with the distribution.Neither the name of Django Xadmin nor the names of its contributors may be used\nto endorse or promote products derived from this software without\nspecific prior written permission.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \u201cAS IS\u201d AND\nANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED\nWARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR\nANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES\n(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON\nANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT\n(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Download-URL:http://github.com/sshwsfc/django-xadmin/archive/master.zipDescription: # Xadmin-xDrop-in replacement of Django admin comes with lots of goodies, fully extensible with plugin support, pretty UI based on Twitter Bootstrap.## FeaturesDrop-in replacement of Django adminTwitter Bootstrap based UI with theme supportExtensible with plugin supportBetter filter, date range, number range, etc.Built-in data export with xls, csv, xml and json formatDashboard page with widget supportIn-site bookmarkingFull CRUD methods## Install Requiresdjango>=3.0django-crispy-forms>=1.6.0 (For xadmin crispy forms)django-reversion`([OPTION] For object history and reversion feature, please select right version by your django, see `changelog)django-formtools([OPTION] For wizward form)xlwt([OPTION] For export xls files)xlsxwriter([OPTION] For export xlsx files)## DocumentationEnglish (coming soon)[Chinese](https://xadmin.readthedocs.org/en/latest/index.html)## Changelogs### 0.6.0Compact with Django1.9.Add Clock Picker widget for timepicker.Fixed some userface errors.### 0.5.0Update fontawesome to 4.0.3Update javascript files to compact fa icons new versionUpdate tests for the new instance method of the AdminSite classAdded demo graphsAdded quickfilter plugin.Adding apps_icons with same logic of apps_label_title.Add xlsxwriter for big data export.Upgrade reversion models admin list page.Fixed reverse many 2 many lookup giving FieldDoesNotExist error.Fixed user permission check in inline model.[Detail](./changelog.md)## HelpHelp Translate :http://trans.xadmin.ioKeywords: admin,django,xadmin,bootstrap,django 3.x\nPlatform: UNKNOWN\nClassifier: Development Status :: 4 - Beta\nClassifier: Environment :: Web Environment\nClassifier: Framework :: Django\nClassifier: Intended Audience :: Developers\nClassifier: License :: OSI Approved :: BSD License\nClassifier: Operating System :: OS Independent\nClassifier: Programming Language :: JavaScript\nClassifier: Programming Language :: Python\nClassifier: Programming Language :: Python :: 2.7\nClassifier: Programming Language :: Python :: 3.4\nClassifier: Topic :: Internet :: WWW/HTTP\nClassifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content\nClassifier: Topic :: Software Development :: Libraries :: Python Modules\nDescription-Content-Type: text/markdown\nProvides-Extra: Excel\nProvides-Extra: Reversion"} +{"package": "xadnacos", "pacakge-description": "xadnacosxadnacos\u662f\u4e00\u4e2a\u7528\u6765\u8c03\u7528naccos\u7684sdk, \u57fa\u4e8eKcangNacos\u8fdb\u884c\u4fee\u6539\u53c2\u8003:\n*https://github.com/KcangYan/nacos-python-sdk.gitFree software: MIT license\u6587\u6863\u5bfc\u5165dkimageapp\u5e93:from xadnacos import xadnacos as nacos\u521b\u5efanacos\u8fde\u63a5\u5bf9\u8c61:nacosServer = nacos.nacos(ip=nacosIp,port=nacosPort)\u5c06\u672c\u5730\u914d\u7f6e\u6ce8\u5165\u5230nacos\u5bf9\u8c61\u4e2d\u5373\u53ef\u83b7\u53d6\u8fdc\u7a0b\u914d\u7f6e:GlobalConfig={}\nnacosServer.config(dataId=\"demo-python.json\",group=\"dev\",tenant=\"python\",myConfig=GlobalConfig)\u6ce8\u518cnacos\u670d\u52a1:serverHost = socket.gethostbyname(socket.gethostname())\nmetadata = {\n \"tier\": \"backend\",\n \"projectid\": \"THID89782455-HJ45678963\"\n}\nclusterName = myConfig.region\n\nnacosServer.registerService(serviceIp=serverHost,servicePort=myConfig.port,serviceName=\"python-provider\",\n namespaceId=\"python\",groupName=\"dev\",clusterName=clusterName,metadata=metadata)\u5f00\u542f\u76d1\u542c\u914d\u7f6e\u7ebf\u7a0b\u548c\u670d\u52a1\u6ce8\u518c\u5fc3\u8df3\u8fdb\u7a0b\u7684\u5065\u5eb7\u68c0\u67e5\u8fdb\u7a0b:nacosServer.healthyCheck()FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2023-02-04)First release on PyPI."} +{"package": "xadrpy", "pacakge-description": "Django and python tool with many useful packages, modules."} +{"package": "x-ae-a-12", "pacakge-description": "X-AE-A-12Command line application for displaying random facts from wikipedia on the console.\nAvailable as a python package onPyPI:pip install x-ae-a-12Documentation available at:X-AE-A-12 docsTable of contentsBuilt WithFeaturesCode ExamplePrerequisitesInstallationTestsDeploymentContributionsBug / Feature RequestAuthorsLicenseBuilt WithPython 3.8- The programming language used.Poetry- The dependency manager used.Nox- The automation tool used.Pytest- The testing framework used.Flake8- The linting tool used.Sphinx- The documentation generator used.GitHub Actions- CI-CD tool used.FeaturesDisplay random facts from Wikipedia.Select Wikipedia language edition to be used.Code Exampledefmain(language:str)->None:\"\"\"The X-AE-A-12 Python project.\"\"\"page=wikipedia.random_page(language=language)click.secho(page.title,fg=\"green\")click.echo(textwrap.fill(page.extract))PrerequisitesWhat things you need to install the software and how to install thempython 3.8Linux:sudo apt-get install python3.8Windows:Download frompython.orgMac OS:brew install python3pipLinux and Mac OS:pip install -U pipWindows:python -m pip install -U pippoetrycurl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | pythonnoxpip install --user --upgrade noxInstallationClone this repository:git clone https://github.com/SpencerOfwiti/X-AE-A-12To set up virtual environment and install dependencies:poetry installTo run application (by default the English language edition is selected):poetry run x-ae-a-12To run Swahili language edition:poetry run x-ae-a-12 -l swTestsThis system uses pytest to run automated tests.To run automated tests:nox -s testsDeploymentTo deploy application on PyPI(Python Package Index):poetry buildpoetry publishContributionsTo contribute, follow these steps:Fork this repository.Create a branch:git checkout -b .Make your changes and commit them:git commit -m ''Push to the original branch:git push origin /Create the pull request.Alternatively see the GitHub documentation oncreating a pull request.Bug / Feature RequestIf you find a bug (the website couldn't handle the query and / or gave undesired results), kindly open an issuehereby including your search query and the expected result.If you'd like to request a new function, feel free to do so by opening an issuehere. Please include sample queries and their corresponding results.AuthorsSpencer Ofwiti-Initial workSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details"} +{"package": "xaero", "pacakge-description": "No description available on PyPI."} +{"package": "xaero2", "pacakge-description": "No description available on PyPI."} +{"package": "xagen37-fast-hist", "pacakge-description": "No description available on PyPI."} +{"package": "xagen37-fast-hist-conflict", "pacakge-description": "No description available on PyPI."} +{"package": "xagents", "pacakge-description": "No description available on PyPI."} +{"package": "xagg", "pacakge-description": "xaggA package to aggregate gridded data inxarrayto polygons ingeopandasusing area-weighting from the relative area overlaps between pixels and polygons.InstallationThe easiest way to install the latest version ofxaggis usingcondaormamba:conda install -c conda-forge xagg==0.3.1.1\n\n# or\nmamba install -c conda-forge xagg==0.3.1.1If you're running into anImportErrorinvolvingESMF, please see the discussionherefor a workaround until it is fixed.Alternatively, you can usepip, though current dependency issues (esmpyis no longer updated on PyPI) is limitingpipto only installingxagg<=0.1.4:pip install xaggDocumentationSee the latest documentation athttps://xagg.readthedocs.io/en/latest/index.htmlIntroScience often happens on grids - gridded weather products, interpolated pollution data, night time lights, remote sensing all approximate the continuous real world for reasons of data resolution, processing time, or ease of calculation.However, living things don't live on grids, and rarely play, act, or observe data on grids either. Instead, humans tend to work on the county, state, township, okrug, or city level; birds tend to fly along complex migratory corridors; and rain- and watersheds follow valleys and mountains.So, whenever we need to work with both gridded and geographic data products, we need ways of getting them to match up. We may be interested for example what the average temperature over a county is, or the average rainfall rate over a watershed.Enterxagg.xaggprovides an easy-to-use (2 lines!), standardized way of aggregating raster data to polygons. All you need is some gridded data in anxarrayDataset or DataArray and some polygon data in ageopandasGeoDataFrame. Both of these are easy to use for the purposes ofxagg- for example, all you need to use a shapefile is to open it:import xarray as xr\n import geopandas as gpd\n \n # Gridded data file (netcdf/climate data)\n ds = xr.open_dataset('file.nc')\n\n # Shapefile\n gdf = gpd.open_dataset('file.shp')xaggwill then figure out the geographic grid (lat/lon) inds, create polygons for each pixel, and then generate intersects between every polygon in the shapefile and every pixel. For each polygon in the shapefile, the relative area of each covering pixel is calculated - so, for example, if a polygon (say, a US county) is the size and shape of a grid pixel, but is split halfway between two pixels, the weight for each pixel will be 0.5, and the value of the gridded variables on that polygon will just be the average of both.Here is a sample code run, using the loaded files from above:import xagg as xa\n\n # Get overlap between pixels and polygons\n weightmap = xa.pixel_overlaps(ds,gdf)\n\n # Aggregate data in [ds] onto polygons\n aggregated = xa.aggregate(ds,weightmap)\n\n # aggregated can now be converted into an xarray dataset (using aggregated.to_dataset()), \n # or a geopandas geodataframe (using aggregated.to_geodataframe() or aggregated.to_dataframe()\n # for a pure pandas result), or directly exported to netcdf, csv, or shp files using\n # aggregated.to_csv()/.to_netcdf()/.to_shp()Researchers often need to weight your data by more than just its relative area overlap with a polygon (for example, do you want to weight pixels with more population more?).xagghas a built-in support for adding an additional weight grid (anotherxarrayDataArray) intoxagg.pixel_overlaps().Finally,xaggallows for direct exporting of the aggregated data in several commonly used data formats:NetCDFCSV for STATA, RShapefile for QGIS, further spatial processingBest of all,xaggis flexible. Multiple variables in your dataset?xaggwill aggregate them all, as long as they have at leastlat/londimensions. Fields in your shapefile that you'd like to keep?xaggkeeps all fields (for example FIPS codes from county datasets) all the way through the final export. Weird dimension names?xaggis trained to recognize all versions of \"lat\", \"Latitude\", \"Y\", \"nav_lat\", \"Latitude_1\"... etc. that the author has run into over the years of working with climate data; and this list is easily expandable as a keyword argument if needed.Use CasesClimate econometricsMany climate econometrics studies use societal data (mortality, crop yields, etc.) at a political or administrative level (for example, counties) but climate and weather data on grids. Oftentimes, further weighting by population or agricultural density is needed.Area-weighting of pixels onto polygons ensures that aggregating weather and climate data onto polygons occurs in a robust way. Consider a (somewhat contrived) example: an administrative region is in a relatively flat lowlands, but a pixel that slightly overlaps the polygon primarily covers a wholly different climate (mountainous, desert, etc.). Using a simple mask would weight that pixel the same, though its information is not necessarily relevant to the climate of the region. Population-weighting may not always be sufficient either; consider Los Angeles, which has multiple significantly different climates, all with high densities.xaggallows a simple populationandarea-averaging, in addition to export functions that will turn the aggregated data into output easily used in STATA or R for further calculations.Project based on thecookiecutter science project template."} +{"package": "xagg-no-xesmf-deps", "pacakge-description": "xaggA package to aggregate gridded data inxarrayto polygons ingeopandasusing area-weighting from the relative area overlaps between pixels and polygons.InstallationThe easiest way to install the latest version ofxaggis usingconda:conda install -c conda-forge xagg(There may be a version issue withnumba- in which case downgradingnumpyusingpip install numpy==1.21.0should fix the problem)Alternatively, you can usepip, though current dependency issues (esmpyis no longer updated on PyPI) is limitingpipto only installingxagg<=0.1.4:pip install xaggDocumentationSee the latest documentation athttps://xagg.readthedocs.io/en/latest/index.htmlIntroScience often happens on grids - gridded weather products, interpolated pollution data, night time lights, remote sensing all approximate the continuous real world for reasons of data resolution, processing time, or ease of calculation.However, living things don't live on grids, and rarely play, act, or observe data on grids either. Instead, humans tend to work on the county, state, township, okrug, or city level; birds tend to fly along complex migratory corridors; and rain- and watersheds follow valleys and mountains.So, whenever we need to work with both gridded and geographic data products, we need ways of getting them to match up. We may be interested for example what the average temperature over a county is, or the average rainfall rate over a watershed.Enterxagg.xaggprovides an easy-to-use (2 lines!), standardized way of aggregating raster data to polygons. All you need is some gridded data in anxarrayDataset or DataArray and some polygon data in ageopandasGeoDataFrame. Both of these are easy to use for the purposes ofxagg- for example, all you need to use a shapefile is to open it:import xarray as xr\n import geopandas as gpd\n \n # Gridded data file (netcdf/climate data)\n ds = xr.open_dataset('file.nc')\n\n # Shapefile\n gdf = gpd.open_dataset('file.shp')xaggwill then figure out the geographic grid (lat/lon) inds, create polygons for each pixel, and then generate intersects between every polygon in the shapefile and every pixel. For each polygon in the shapefile, the relative area of each covering pixel is calculated - so, for example, if a polygon (say, a US county) is the size and shape of a grid pixel, but is split halfway between two pixels, the weight for each pixel will be 0.5, and the value of the gridded variables on that polygon will just be the average of both.Here is a sample code run, using the loaded files from above:import xagg as xa\n\n # Get overlap between pixels and polygons\n weightmap = xa.pixel_overlaps(ds,gdf)\n\n # Aggregate data in [ds] onto polygons\n aggregated = xa.aggregate(ds,weightmap)\n\n # aggregated can now be converted into an xarray dataset (using aggregated.to_dataset()), \n # or a geopandas geodataframe (using aggregated.to_dataframe()), or directly exported \n # to netcdf, csv, or shp files using aggregated.to_csv()/.to_netcdf()/.to_shp()Researchers often need to weight your data by more than just its relative area overlap with a polygon (for example, do you want to weight pixels with more population more?).xagghas a built-in support for adding an additional weight grid (anotherxarrayDataArray) intoxagg.pixel_overlaps().Finally,xaggallows for direct exporting of the aggregated data in several commonly used data formats:NetCDFCSV for STATA, RShapefile for QGIS, further spatial processingBest of all,xaggis flexible. Multiple variables in your dataset?xaggwill aggregate them all, as long as they have at leastlat/londimensions. Fields in your shapefile that you'd like to keep?xaggkeeps all fields (for example FIPS codes from county datasets) all the way through the final export. Weird dimension names?xaggis trained to recognize all versions of \"lat\", \"Latitude\", \"Y\", \"nav_lat\", \"Latitude_1\"... etc. that the author has run into over the years of working with climate data; and this list is easily expandable as a keyword argument if needed.Use CasesClimate econometricsMany climate econometrics studies use societal data (mortality, crop yields, etc.) at a political or administrative level (for example, counties) but climate and weather data on grids. Oftentimes, further weighting by population or agricultural density is needed.Area-weighting of pixels onto polygons ensures that aggregating weather and climate data onto polygons occurs in a robust way. Consider a (somewhat contrived) example: an administrative region is in a relatively flat lowlands, but a pixel that slightly overlaps the polygon primarily covers a wholly different climate (mountainous, desert, etc.). Using a simple mask would weight that pixel the same, though its information is not necessarily relevant to the climate of the region. Population-weighting may not always be sufficient either; consider Los Angeles, which has multiple significantly different climates, all with high densities.xaggallows a simple populationandarea-averaging, in addition to export functions that will turn the aggregated data into output easily used in STATA or R for further calculations.Project based on thecookiecutter science project template."} +{"package": "xai", "pacakge-description": "XAI - An eXplainability toolbox for machine learningXAI is a Machine Learning library that is designed with AI explainability in its core. XAI contains various tools that enable for analysis and evaluation of data and models. The XAI library is maintained byThe Institute for Ethical AI & ML, and it was developed based on the8 principles for Responsible Machine Learning.You can find the documentation athttps://ethicalml.github.io/xai/index.html. You can also check out ourtalk at Tensorflow Londonwhere the idea was first conceived - the talk also contains an insight on the definitions and principles in this library.YouTube video showing how to use XAI to mitigate undesired biasesThisvideo of the talk presented at the PyData London 2019 Conferencewhich provides an overview on the motivations for machine learning explainability as well as techniques to introduce explainability and mitigate undesired biases using the XAI Library.Do you want to learn about more awesome machine learning explainability tools? Check out our community-built\"Awesome Machine Learning Production & Operations\"list which contains an extensive list of tools for explainability, privacy, orchestration and beyond.0.1.0If you want to see a fully functional demo in action clone this repo and run theExample Jupyter Notebook in the Examples folder.What do we mean by eXplainable AI?We see the challenge of explainability as more than just an algorithmic challenge, which requires a combination of data science best practices with domain-specific knowledge. The XAI library is designed to empower machine learning engineers and relevant domain experts to analyse the end-to-end solution and identify discrepancies that may result in sub-optimal performance relative to the objectives required. More broadly, the XAI library is designed using the 3-steps of explainable machine learning, which involve 1) data analysis, 2) model evaluation, and 3) production monitoring.We provide a visual overview of these three steps mentioned above in this diagram:XAI QuickstartInstallationThe XAI package is on PyPI. To install you can run:pip install xaiAlternatively you can install from source by cloning the repo and running:python setup.py installUsageYou can find example usage in the examples folder.1) Data AnalysisWith XAI you can identify imbalances in the data. For this, we will load the census dataset from the XAI library.importxai.datadf=xai.data.load_census()df.head()View class imbalances for all categories of one columnims=xai.imbalance_plot(df,\"gender\")View imbalances for all categories across multiple columnsim=xai.imbalance_plot(df,\"gender\",\"loan\")Balance classes using upsampling and/or downsamplingbal_df=xai.balance(df,\"gender\",\"loan\",upsample=0.8)Perform custom operations on groupsgroups=xai.group_by_columns(df,[\"gender\",\"loan\"])forgroup,group_dfingroups:print(group)print(group_df[\"loan\"].head(),\"\\n\")Visualise correlations as a matrix_=xai.correlations(df,include_categorical=True,plot_type=\"matrix\")Visualise correlations as a hierarchical dendogram_=xai.correlations(df,include_categorical=True)Create a balanced validation and training split dataset# Balanced train-test split with minimum 300 examples of# the cross of the target y and the column genderx_train,y_train,x_test,y_test,train_idx,test_idx=\\xai.balanced_train_test_split(x,y,\"gender\",min_per_group=300,max_per_group=300,categorical_cols=categorical_cols)x_train_display=bal_df[train_idx]x_test_display=bal_df[test_idx]print(\"Total number of examples: \",x_test.shape[0])df_test=x_test_display.copy()df_test[\"loan\"]=y_test_=xai.imbalance_plot(df_test,\"gender\",\"loan\",categorical_cols=categorical_cols)2) Model EvaluationWe are able to also analyse the interaction between inference results and input features. For this, we will train a single layer deep learning model.model = build_model(proc_df.drop(\"loan\", axis=1))\n\nmodel.fit(f_in(x_train), y_train, epochs=50, batch_size=512)\n\nprobabilities = model.predict(f_in(x_test))\npredictions = list((probabilities >= 0.5).astype(int).T[0])Visualise permutation feature importancedefget_avg(x,y):returnmodel.evaluate(f_in(x),y,verbose=0)[1]imp=xai.feature_importance(x_test,y_test,get_avg)imp.head()Identify metric imbalances against all test data_=xai.metrics_plot(y_test,probabilities)Identify metric imbalances across a specific column_=xai.metrics_plot(y_test,probabilities,df=x_test_display,cross_cols=[\"gender\"],categorical_cols=categorical_cols)Identify metric imbalances across multiple columns_=xai.metrics_plot(y_test,probabilities,df=x_test_display,cross_cols=[\"gender\",\"ethnicity\"],categorical_cols=categorical_cols)Draw confusion matrixxai.confusion_matrix_plot(y_test,pred)Visualise the ROC curve against all test data_=xai.roc_plot(y_test,probabilities)Visualise the ROC curves grouped by a protected columnprotected=[\"gender\",\"ethnicity\",\"age\"]_=[xai.roc_plot(y_test,probabilities,df=x_test_display,cross_cols=[p],categorical_cols=categorical_cols)forpinprotected]Visualise accuracy grouped by probability bucketsd=xai.smile_imbalance(y_test,probabilities)Visualise statistical metrics grouped by probability bucketsd=xai.smile_imbalance(y_test,probabilities,display_breakdown=True)Visualise benefits of adding manual review on probability thresholdsd=xai.smile_imbalance(y_test,probabilities,bins=9,threshold=0.75,manual_review=0.375,display_breakdown=False)"} +{"package": "xaib", "pacakge-description": "No description available on PyPI."} +{"package": "xai-benchmark", "pacakge-description": "xai-benchmarkOpen and extensible benchmark for XAI methodsDescriptionXAIB is an open benchmark that provides a way to compare different XAI methods using broad set of metrics that measure different aspects of interpretabilityInstallationpip3installxai-benchmarkRemember to create virtual environment if you need one.After the installation you can verify the package by printing out its version:importxaibprint(xaib.__version__)To use all explainers you should also installexplainers_requirements.txtwhich can be done\ndirectlypip3install-rhttps://raw.githubusercontent.com/oxid15/xai-benchmark/master/explainers_requirements.txtResultsUpdated results table can be foundhosted hereHow to useIntroductionXAIB is build to bring various data, models and explainers together and\nmeasure quality of an explainer in different ways.The setup is formed from particular Dataset, Model and Explainer.Case stands for some interpretability quality which we are trying to proxy numerically\nusing Metrics. Since there are always more than one way to measure something, one Case\nmay (and should ideally) have several metrics inside.Read more onCasesandMetricsin documentation.ReproduceFull run will be available soon.Until then, there are regularpipelinesFor the implementation of the evaluation procedure, you can visitxaib/evaluationTry methodAll explanation methods in XAIB have the same input and output interface which allows to\nuse them easily and compare.If you want to run an Explainer and see the results you can do this:fromxaib.explainers.feature_importance.lime_explainerimportLimeExplainerfromxaib.evaluationimportDatasetFactory,ModelFactory# Get the dataset and train the modeltrain_ds,test_ds=DatasetFactory().get('synthetic')model=ModelFactory(train_ds,test_ds).get('svm')# You can also get the default one using ExplainerFactoryexplainer=LimeExplainer(train_ds,labels=[0,1])# Obtain batch from datasetsample=[test_ds[i]['item']foriinrange(10)]# Obtain explanationsexplanations=explainer.predict(sample,model)print(explanations)Evaluate methodTo evaluate some existing method on all\ncases you should create a default setup and run itfromxaib.evaluationimportDatasetFactory,ModelFactoryfromxaib.evaluation.example_selectionimportExplainerFactory,ExperimentFactoryfromxaib.evaluation.utilsimportvisualize_resultstrain_ds,test_ds=DatasetFactory().get('synthetic')model=ModelFactory(train_ds,test_ds).get('knn')explainer=ExplainerFactory(train_ds,model).get('knn')# Run all experiments on chosen methodexperiment_factory=ExperimentFactory(repo_path='results',explainers={'knn':explainer},test_ds=test_ds,model=model,batch_size=10)experiments=experiment_factory.get('all')fornameinexperiments:experiments[name]()# Save plot to the results foldervisualize_results('results','results/results.png')How to contributeAny contributions are welcome! You can help to extend\nthe picture of XAI-methods quality by adding:New DatasetNew ModelNew ExplainerNew MetricNew Case (?)- please, fill the issue first to discussAdd datasetNew datasets may extend our understanding of how different explainers\nbehave in context of different domains and tasks.To add your dataset, you should provide a Wrapper, which will\ndownload or access prepared data from disk.Create data wrapperFirst you need to create a wrapper with required interface and fieldsimportnumpyasnpfromxaibimportDatasetclassNewDataset(Dataset):\"\"\"Here the documentation on data should be filled\"\"\"def__init__(self,split,*args,**kwargs)->None:super().__init__(*args,**kwargs)# It is important to set the name# the name will be used to identify a datasetself.name='new_dataset'# While creating you can download and cache data,# define splits, etcifsplit=='train':self._data=[(0,1,2),(3,4,5),(6,7,8)]self._labels=[0,1,0]elifsplit=='test':self._data=[(9,10,11),(12,13,14)]self._labels=[1,0]def__getitem__(self,index):# This form of returning items is required - Dict[str, np.ndarray[Any]]return{'item':np.asarray(self._data[index]),'label':np.asarray(self._labels[index])}def__len__(self):returnlen(self._data)Test new datasetBefore adding your implementation directly into source code, it would be useful to\ntest how it will work with standard XAIB setupfromxaib.evaluationimportDatasetFactory,ModelFactoryfromxaib.evaluation.feature_importanceimportExplainerFactory,ExperimentFactoryfromxaib.evaluation.utilsimportvisualize_results# Here you create your datatrain_ds,test_ds=NewDataset('train'),NewDataset('test')# And then pass it furthermodel=ModelFactory(train_ds,test_ds).get('svm')explainers=ExplainerFactory(train_ds,model,labels=[0,1]).get('all')experiment_factory=ExperimentFactory(repo_path='results',explainers=explainers,test_ds=test_ds,model=model,batch_size=10)experiments=experiment_factory.get('all')fornameinexperiments:experiments[name]()visualize_results('results','results/results.png')Integrate new datasetFinally you can integrate your dataset into the source code.To do that you need to add it intoxaib.datasetsmodule\nand then make a constructor for the Factory.# xaib/evaluation/dataset_factory.py# ...from..datasets.new_datasetimportNewDataset# ...# Create a constructor - function that will build your dataset# it should provide all defaults neededdefnew_dataset():returnNewDataset('train'),NewDataset('test')classDatasetFactory(Factory):def__init__(self)->None:# ...# add it to the factoryself._constructors['new_dataset']=lambda:new_dataset()Add modelNew models and model classes provide information on how good explainers\nare in some particular cases.Create model wrapperFirst model wrapper should be implemented. It has many\nrequired methods that should be implemented.\nFor examplefitandevaluatemethods are needed\nto be able to train the model on different datasets\nsee specification inxaib/baseand examples inxaib/evaluation/model_factory.pyimportnumpyasnpfromxaibimportModelclassNewModel(Model):\"\"\"Here the documentation on model should be filled\"\"\"def__init__(self,const,*args,**kwargs):super().__init__(*args,**kwargs)self.const=const# It is important to set the name# the name will be used to identify a modelself.name='new_model'deffit(self,x,y):passdefevaluate(self,x,y):passdefpredict(self,x):returnnp.array([self.constfor_inrange(len(x))])defsave(self,filepath,*args,**kwargs):withopen(filepath,'w')asf:f.write(str(self.const))defload(self,filepath,*args,**kwargs):withopen(filepath,'r')asf:self.const=float(f.read())# load does not return anything - just fills# internal stateTest new modelBefore adding your implementation directly into source code, it would be useful to\ntest how it will work with standard XAIB setupfromxaib.evaluationimportDatasetFactoryfromxaib.evaluation.feature_importanceimportExplainerFactory,ExperimentFactoryfromxaib.evaluation.utilsimportvisualize_results# Create your modelmodel=NewModel(const=1)train_ds,test_ds=DatasetFactory().get('synthetic')explainers={'shap':ExplainerFactory(train_ds,model,labels=[0,1]).get('shap')}experiment_factory=ExperimentFactory(repo_path='results',explainers=explainers,test_ds=test_ds,model=model,# and put it herebatch_size=10)experiments=experiment_factory.get('all')fornameinexperiments:experiments[name]()visualize_results('results','results/results.png')Integrate new modelFinally you can integrate your model into the source code.To do that you need to add it intoxaib.modelsmodule\nand then make a constructor for the Factory.# xaib/evaluation/model_factory.py# ...from..models.new_modelimportNewModel# ...# Create a constructor - function that will build your modeldefnew_model(const):returnNewModel(const=const)classModelFactory(Factory):def__init__(self)->None:# ...# add it to the factoryself._constructors['new_model']=lambda:new_model(const=1)Add explainerExplainers are the heart of this benchmark, they are being thorougly tested\nand the more of them added, the more we knowCreate wrapperExplainers wrappers are less demanding than model's which makes them\neasier to be implementedimportnumpyasnpfromxaibimportExplainerclassNewExplainer(Explainer):def__init__(self,*args,**kwargs):super().__init__(*args,**kwargs)# name is essential to put explainer into# results table correctlyself.name='new_explainer'defpredict(self,x,model,*args,**kwargs):returnnp.random.rand(len(x),len(x[0]))Test new explainerBefore adding your implementation directly into source code, it would be useful to\ntest how it will work with standard XAIB setupfromxaib.evaluationimportDatasetFactory,ModelFactoryfromxaib.evaluation.feature_importanceimportExperimentFactoryfromxaib.evaluation.utilsimportvisualize_resultstrain_ds,test_ds=DatasetFactory().get('synthetic')model=ModelFactory(train_ds,test_ds).get('svm')explainers={'new_explainer':NewExplainer()}experiment_factory=ExperimentFactory(repo_path='results',explainers=explainers,test_ds=test_ds,model=model,batch_size=10)experiments=experiment_factory.get('all')fornameinexperiments:experiments[name]()visualize_results('results','results/results.png')Integrate new explainerFinally you can integrate your explainer into the source code.To do that you need to add it intoxaib.explainersmodule\nand then make a constructor for the Factory.# xaib/evaluation/feature_importance/explainer_factory.py# ...from...explainers.feature_importance.new_explainerimportNewExplainer# ...# Create a constructor - function that will build your explainerdefnew_explainer():returnNewExplainer()classExplainerFactory(Factory):def__init__(self)->None:# ...# add it to the factoryself._constructors['new_explainer']=lambda:new_explainer()Add metricMetrics are ways to numerically assess the quality of explainers and are parts of\nCasesCreate metricFirst you need to create a Metric object - which will accept and explainer and data\nand return some valuefromxaibimportMetricclassNewMetric(Metric):def__init__(self,ds,model*args,**kwargs):super().__init__(ds,model,*args,**kwargs)self.name='new_metric'self.direction='down'defcompute(self,explainer,*args,batch_size=1,expl_kwargs=None,**kwargs):ifexpl_kwargsisNone:expl_kwargs={}dl=SimpleDataloader(self._ds,batch_size=batch_size)forbatchintqdm(dl):# get explanationsex=expl.predict(batch['item'],self._model,**expl_kwargs)# Here compute and return your metricreturnnp.random.rand()Test new metricBefore adding your implementation directly into source code, it would be useful to\ntest how it will work with standard XAIB setupSince metrics are more low-level objects, they need special treatment\nwhen tested. Basically you need to create metric and append it to the existing\nCase of choice.fromxaib.evaluationimportDatasetFactory,ModelFactoryfromxaib.evaluation.feature_importanceimportExplainerFactoryfromxaib.evaluation.utilsimportvisualize_results,experimenttrain_ds,test_ds=DatasetFactory().get('synthetic')model=ModelFactory(train_ds,test_ds).get('svm')explainers=ExplainerFactory(train_ds,model,labels=[0,1]).get('all')metric=NewMetric(test_ds,model)@experiment('results',explainers=explainers,metrics_kwargs={'other_disagreement':dict(expls=list(explainers.values()))})defcoherence():case=CoherenceCase(test_ds,model)case.add_metric('new_metric',metric)returncasecoherence()visualize_results('results','results/results.png')Integrate new metric# xaib/cases/feature_importance/coherence_case.py# ...from...metrics.feature_importanceimportNewMetricclassCoherenceCase(Case):def__init__(self,ds:Dataset,model:Model,*args:Any,**kwargs:Any)->None:super().__init__(ds,model,*args,**kwargs)# ...self._metric_objs['new_metric']=NewMetric(ds,model)LicenseMITVersionsThis project follows Semantic Versioning -semver.org"} +{"package": "xai-explainer", "pacakge-description": "InstallationAll stable versions can be installed fromPyPIby usingpipor your favorite package managerpip install xai-explainerDevelopmentRequirements:Python 3.9 or higherpoetry1.7makeConfigure poetry for vscodepoetryconfigvirtualenvs.in-projecttrueFor installing the development environment runmakeinstall-devRun scripts using poetrypoetryrunpythonscript_name.py"} +{"package": "xai-hello", "pacakge-description": "No description available on PyPI."} +{"package": "xai-image-widget", "pacakge-description": "No description available on PyPI."} +{"package": "xai-inference-engine", "pacakge-description": "XAI Inference EngineThis package is a wrapper for CNN-based PyTorch models that is capable of performing XAI inferencing. It wraps a trained PyTorch CNN model and allows it to return the predictions, sorted prediction indices and saliency maps when provided with a preprocessed input. For the saliency maps the library uses theFM-G-CAMmethod. More types of saliency map generation methods will be added in the future. The package also provides a method to superimpose the saliency maps on the input image.Users can also use the package to create their own inference engine by extending theXAIInferenceEngineclass.Advanced Tutorials: Coming Soon...Github|PyPiRequirementsPython 3.8+PyTorch 2.0+InstallationExecute the following command in your terminal to install the package.pipinstallxai-inference-engineUsageFollow the example below to use the package. Copy and paste the code into a python script and run it. Make sure you have the requirements installed. \ud83d\ude0aprint(\"[INFO]: Testing XAIInferenceEngine...\")print(\"[INFO]: Importing Libraries...\")fromxai_inference_engineimportXAIInferenceEnginefromtorchvision.modelsimportresnet50,ResNet50_Weightsdevice=torch.device(\"cuda:0\"iftorch.cuda.is_available()else\"cpu\")print(\"[INFO]: Device:{}\".format(device))print(\"[INFO]: Loading Model...\")# Modelmodel=resnet50(weights=ResNet50_Weights.IMAGENET1K_V2).to(device)weights=ResNet50_Weights.DEFAULTpreprocess=weights.transforms()# Model config# Set model to eval modemodel.eval()last_conv_layer=model.layer4[2].conv3class_count=5class_list=weights.meta[\"categories\"]img_h=224print(\"[INFO]: Image Preprocessing...\")# Image Preprocessingurl=\"https://raw.githubusercontent.com/utkuozbulak/pytorch-cnn-visualizations/master/input_images/cat_dog.png\"r=requests.get(url,allow_redirects=True)open(\"dog-and-cat-cover.jpg\",\"wb\").write(r.content)img=Image.open(\"dog-and-cat-cover.jpg\")img=img.resize((img_h,img_h),resample=Image.BICUBIC)img_tensor=preprocess(img).to(device)print(\"[INFO]: Creating XAIInferenceEngine...\")xai_inferencer=XAIInferenceEngine(model=model,last_conv_layer=last_conv_layer,device=device,)print(\"[INFO]: Running XAIInferenceEngine.predict()...\")preds,sorted_pred_indices,super_imp_img,saliency_maps=xai_inferencer.predict(img=img,img_tensor=img_tensor,)print(\"[INFO]: Saving Results to the root folder...\")super_imp_img.save(\"super_imp_img.jpg\")saliency_maps.save(\"saliency_maps.jpg\")print(\"[INFO]: Displaying Results...\")print(\" Predictions:{}\".format(preds.shape))print(\" Sorted Prediction Indices:{}\".format(sorted_pred_indices.cpu().numpy()[:10]))print(\" Heatmaps shape:{}\".format(saliency_maps))print(\" Super Imposed Image:{}\".format(super_imp_img))ResultsFollowing image shows comparison between the saliency maps generated by the FM-G-CAM method and the Grad-CAM method.AuthorRavidu Silva"} +{"package": "xai-kit", "pacakge-description": "XAI (eXplainable Artificial Intelligence) LibraryOverviewThe XAI (eXplainable Artificial Intelligence) Library is a powerful toolkit designed to empower data scientists and machine learning practitioners in their journey to understand, interpret, and visualize complex machine learning models. In an era of advanced AI algorithms, transparency and interpretability are paramount. XAI addresses these needs by offering a suite of advanced visualizations tailored for regression analysis, curated datasets, pre-trained regression models, and comprehensive documentation.FeaturesAdvanced Visualizations: Explore a rich collection of visualizations in theXAI Regression Visualizations Moduledesigned to unravel the intricacies of your regression models.Datasets and Models: Access curated datasets and pre-trained regression models to streamline your regression analysis process.Model-Agnostic Explanations: Enjoy model-agnostic explanations for compatibility with a wide array of machine learning models.Interpretability for Diverse Data Types: XAI is built to cater to diverse data types, including tabular data, image data, and natural language processing (NLP) models.Continuous Improvement: Expect regular updates with additional features and support for various machine learning tasks.Getting StartedTo harness the power of the XAI Library, follow these steps:Install the Library: Begin by including the library in your Python environment.Explore Documentation: Refer to theGetting Started Guideto understand the library's objectives and scope.Usage Guide: Dive into theUsage Guidefor detailed instructions on using the library's features.ExamplesExplore practical examples demonstrating the library's capabilities in theExample Notebooksdirectory.DocumentationGetting Started Guide: Learn about the library's objectives and scope.Usage Guide: Detailed instructions on using the library's features.Index: The main page with information about the library and its creator.AuthorZeed Almelhem (GitHub)ContactFor inquiries and feedback, please feel free to contact the author:Email (z@zeed-almelhem.com)Personal WebsiteKaggleGitHubMediumInstagramLinkedInTwitterBlogProjectsContactLicenseThis project is licensed under the MIT License - see theLICENSEfile for details."} +{"package": "xai-metrics", "pacakge-description": "XAI-metricsA package for analysis and evaluating metrics for machine learning models explainability.InstallationInstall from PyPI:pip install xai-metricsUsageExamples of usage:Perturbation based on permutation importancesfrom xai_metrics import examine_interpretation\n\nX_train.columns = ['0','1','2','3']\nX_test.columns = ['0','1','2','3']\nxgb_model = xgb.XGBClassifier()\nxgb_model.fit(X_train, y_train)\nperm = PermutationImportance(xgb_model, random_state=1).fit(X_test, y_test)\nperm_importances = perm.feature_importances_\n\nexamine_interpretation(xgb_model, X_test, y_test, perm_importances, epsilon=4, resolution=50, proportionality_mode=0)Perturbation based on local importancesfrom xai_metrics import examine_local_fidelity\n\nexamine_local_fidelity(xgb_model, X_test, y_test, epsilon=3)Gradual eliminationfrom xai_metrics import gradual_elimination\n\ngradual_elimination(f_forest, f_X_test, f_y_test, f_shap)Seeherefor notebooks with full examples of usage."} +{"package": "xain", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xain-aggregators", "pacakge-description": "No description available on PyPI."} +{"package": "xain-fl", "pacakge-description": "Disclaimer: This is work-in-progress and not production-ready, expect errors to occur! Use at your own risk! Do not use for any security related issues!XAINThe XAIN project is building a privacy layer for machine learning so that AI projects can meet compliance such as\nGDPR and CCPA. The approach relies on Federated Learning as enabling technology that allows production AI\napplications to be fully privacy compliant.Federated Learning also enables different use-cases that are not strictly privacy related such as connecting data\nlakes, reaching higher model performance in unbalanced datasets and utilising AI models on the edge.This repository contains the source code for running the Coordinator. The Coordinator is the component of Federated\nLearning that selects the Participants for training and aggregates the models using federated averaging.The Participants run in a separate environment than the Coordinator and connect to it using an SDK. You can findherethe source code for it.Quick StartXAIN requiresPython 3.6.4+. To install thexain-flpackage just run:$python-mpipinstallxain-flInstall from sourceClone this repository:gitclonehttps://github.com/xainag/xain-fl.gitInstall this project with thedevprofile (NOTE: it is\nrecommended to install the project in a virtual environment):cdxain-fl\npipinstall-e'.[dev]'Verify the installation by running the testspytestBuilding the DocumentationThe project documentation resides underdocs/. To build the documentation\nrun:$cddocs/\n$makedocsThe generated documentation will be underdocs/_build/html/. You can open the\nroot of the documentation by openingdocs/_build/html/index.htmlon your\nfavorite browser or simply run the command:$makeshowRunning the Coordinator locallyTo run the Coordinator on your local machine, you can use theexample-config.tomlfile:# If you have installed the xain_fl package,# the `coordinator` command should be directly availablecoordinator--configconfigs/example-config.toml# otherwise the coordinator can be started by executing the# `xain_fl` package:pythonxain_fl--configconfigs/example-config.tomlRun the Coordinator from a Docker imageThere are two docker-compose files, one for development and one for release.Development imageTo run the coordinator's development image, first build the Docker image:$dockerbuild-txain-fl-dev-fDockerfile.dev.Then run the image, mounting the directory as a Docker volume:$dockerrun-v$(pwd):/app-v'/app/xain_fl.egg-info'xain-fl-devcoordinatorThe command above uses a default configuration but you can also use a\ncustom config file:For instance, if you have a./custom_config.tomlfile that you'd\nlike to use, you can mount it in the container and run the coordinator\nwith:dockerrun\\-v$(pwd)/custom_config.toml:/custom_config.toml\\-v$(pwd):/app\\-v'/app/xain_fl.egg-info'\\xain-fl-dev\\coordinator--config/custom_config.tomlRelease imageTo run the coordinator's release image, first build it:$dockerbuild-txain-fl.And then run it (this example assumes you'll want to use the default port):$dockerrun-p50051:50051xain-flDocker-composeThe coordinator needs a storage service that provides an AWS S3\nAPI. For development, we useminio. We providedocker-composefiles that start coordinator container along with aminiocontainer,\nand pre-populate the appropriate storage buckets.DevelopmentTo start both the coordinator and theminioservice use:docker-compose-fdocker-compose-dev.ymlupIt is also possible to only start the storage service:docker-compose-fdocker-compose-dev.ymlupminio-devinitial-bucketsRelease$docker-composeupRelated Papers and ArticlesAn introduction to XAIN\u2019s GDPR-compliance Layer for Machine LearningCommunication-Efficient Learning of Deep Networks from Decentralized DataAnalyzing Federated Learning through an Adversarial LensTowards Federated Learning at Scale: System Design"} +{"package": "xain-proto", "pacakge-description": "Disclaimer: This is work-in-progress and not production-ready, expect errors to occur! Use at your own risk! Do not use for any security related issues!XAIN Proto"} +{"package": "xain-sdk", "pacakge-description": "No description available on PyPI."} +{"package": "xaiographs", "pacakge-description": "XAIoGraphsXAIoGraphs (eXplainabilityArticicialIntelligenceoverGraphs) is an Explicability and Fairness\nPython library for classification problems with tabulated and discretized data.The explainability methods in this library don't make any hypotheses about the data, so it does not require the AI model.\nSimply need data and predictions (or decisions), being able to explain AI models, rule models, and reality.This library includes the following functionalities:Global Explainability: Explains predictions or decisions as a whole, focusing on the variables that have the most influence.Local Explainability: Explains the prediction of a single element.Reliability Measureof local explainability.Reason Why:explanation in natural languageof the classification of each element.Fairness Scoring: highlights potential discriminations in classifications based on sensitive features.To understand orinterpret the explanationsusesXAIoWeb, aweb interfacerunning in local mode (127.0.0.1:8080).\nIt displays the explanations' outcomes in three sections: Global, Local and Fairness.\ud83d\ude80 Quickstart\ud83d\udd28 Installation XAIoGraphsCreate a virtual environment using conda for easier management of dependencies and packages.\nFor installing conda, follow the instructions on theofficial conda website>>condacreate--namexaio_envpython=3.7>>condaactivatexaio_envUse a python version 3.7 or higherFrom PyPI repository>>pipinstallxaiographs\ud83d\udcdd Start with your first exampleUse the following entry point to view an example run with the virtual environment enabled:>>titanic_exampleAlternatively, you may run the code below to view a full implementation of all XAIoGraphs functionalities:fromxaiographsimportExplainerfromxaiographsimportWhyfromxaiographsimportFairnessfromxaiographs.datasetsimportload_titanic_discretized,load_titanic_whyLANG='en'# LOAD DATASETS & SEMANTICSdf_titanic,feature_cols,target_cols,y_true,y_predict=load_titanic_discretized()df_values_semantics,df_target_values_semantics=load_titanic_why(language=LANG)# EXPLAINERexplainer=Explainer(importance_engine='LIDE',verbose=1)explainer.fit(df=df_titanic,feature_cols=feature_cols,target_cols=target_cols)# WHYwhy=Why(language=LANG,explainer=explainer,why_values_semantics=df_values_semantics,why_target_values_semantics=df_target_values_semantics,verbose=1)why.fit()# FAIRNESSf=Fairness(verbose=1)f.fit(df=df_titanic[feature_cols+[y_true]+[y_predict]],sensitive_cols=['gender','class','age'],target_col=y_true,predict_col=y_predict)Following execution, a folder called \"xaioweb files\" is created, which contains a set of '.json' files that will\nbe used to present the results in the XAIoWeb graphical interface.\ud83d\udcca Launching XAIoWebXAIoWeb is a local web interface that displays the outcomes of the explanations in three sections: Global, Local,\nand Fairness. To launch the web (with the virtual environment enabled), run the following entry point:>>xaioweb-dxaioweb_files-oThis entry point takes the following parameters:-do--data[REQUIRED]: JSON files path-po--port[OPTIONAL]: Web server port. 8080 by default-oo--open[OPTIONAL]: Open web in browser-fo--force[OPTIONAL]: Force building the web from scratch, overwriting the existing one\ud83e\udd1d ContributorsXAIoGraphs has been developed byApplied AI & Privacyteam (Telef\u00f3nica Innovaci\u00f3n Digital - Chief Data Officer)Ricardo MoyaMatteo SalvatoriEnrique FernandezAlejandro Manuel ArranzManuel Mart\u00ednMario VillaizanCesar Garc\u00edaDavid CadenasAlejandra Maria AlonsoMiguel Angel Mart\u00ednOriol Arnau\ud83d\udce5 ContactContact with@Ricardo Moya"} +{"package": "xair-api", "pacakge-description": "Xair APIThis package offers a python interface for theBehringer XAir,Midas MRseries of digital rack mixers. I only have access to an MR18 for testing so if there is an error in the kind maps feel free to raise an issue or PR.For an outline of past/future changes refer to:CHANGELOGPrerequisitesPython 3.10 or greaterInstallationpip install xair-apiUsageConnectionA toml file named config.toml, placed into the current working directory of your code may be used to configure the mixers ip. A validconfig.tomlmay resemble:[connection]ip=\"\"Alternatively you may pass it as a keyword argument.Exampleimportxair_apidefmain():kind_id=\"XR18\"ip=\"\"withxair_api.connect(kind_id,ip=ip)asmixer:mixer.strip[8].config.name=\"sm7b\"mixer.strip[8].mix.on=Trueprint(f\"strip 09 ({mixer.strip[8].config.name}) on has been set to{mixer.strip[8].mix.on}\")if__name__==\"__main__\":main()xair_api.connect(kind_id, ip=ip, delay=0.02, connect_timeout=2)Currently the following devices are supported:MR18XR18XR16XR12TheX32is partially supported. However, this document covers specifically theXAirseries.The following keyword arguments may be passed:ip: ip address of the mixerport: mixer port, defaults to 10023 for x32 and 10024 for xairdelay: a delay between each command (applies to the getters). Defaults to 20ms.a note about delay, stability may rely on network connection. For wired connections the delay can be safely reduced.connect_timeout: amount of time to wait for a validated connection. Defaults to 2s.APIXAirRemote class (higher level)mixer.lrA class representing Main LR channelmixer.stripA Strip tuple containing a class for each input strip channelmixer.busA Bus tuple containing a class for each output bus channelmixer.dcaA DCA tuple containing a class for each DCA groupmixer.fxAn FX tuple containing a class for each FX channelmixer.fxsendAn FXSend tuple containing a class for each FX Send channelmixer.fxreturnAn FXReturn tuple containing a class for each FX Return channelmixer.auxreturnA class representing auxreturn channelmixer.configA class representing the main config settingsLRContains the subclasses:\n(Config,Dyn,Insert,EQ,Mix)StripContains the subclasses:\n(Config,Preamp,Gate,Dyn,Insert,GEQ,EQ,Mix,Group,Automix,Send)BusContains the subclasses:\n(Config,Dyn,Insert,EQ,Mix,Group)FXSendContains the subclasses:\n(Config,Mix,Group)FXRtnContains the subclasses:\n(Config,Preamp,EQ,Mix,Group,Send)AuxRtnContains the subclasses:\n(Config,Preamp,EQ,Mix,Group,Send)SubclassesFor each subclass the corresponding properties are available.Configname: stringcolor: int, from 0, 16inputsource: intusbreturn: intPreampon: boolusbtrim: float, from -18.0 to 18.0usbinput: boolinvert: boolhighpasson: boolhighpassfilter: int, from 20 to 400Gateon: boolmode: str, one of ('gate', 'exp2', 'exp3', 'exp4', 'duck')threshold: float, from -80.0 to 0.0range: int, from 3 to 60attack: int, from 0 to 120hold: float, from 0.02 to 2000release: int, from 5 to 4000keysource, from 0 to 22filteron: boolfiltertype: int, from 0 to 8filterfreq: float, from 20 to 20000Dynon: boolmode: str, one of ('comp', 'exp')det: str, one of ('peak', 'rms')env: str, one of ('lin', 'log')threshold: float, from -60.0 to 0.0ratio: int, from 0 to 11knee: int, from 0 to 5mgain: float, from 0.0 to 24.0attack: int, from 0 to 120hold: float, from 0.02 to 2000release: int, from 5 to 4000mix: int, from 0 to 100keysource: int, from 0 to 22auto: boolfilteron: boolfiltertype: int, from 0 to 8filterfreq: float, from 20 to 20000Inserton: boolsel: intGEQThe following method names preceded byslider_20,25,31_5,40,50,63,80,100,125,160,200,250,315,400,500,630,800,1k,1k25,1k6,2k,2k5,3k15,4k,5k,6k3,8k,10k,12k5,16k,20k: float, from -15.0 to 15.0for example:slider_20,slider_6k3etc..EQon: boolmode: str, one of ('peq', 'geq', 'teq')For the subclasses:low,low2,lomid,himid,high2,highthe following properties are available:type: int, from 0 to 5frequency: float, from 20.0 to 20000.0gain: float, -15.0 to 15.0quality: float, from 0.3 to 10.0for example:eq.low2.typeMixon: boolfader: float, -inf, to 10.0lr: boolGroupdca: int, from 0 to 15mute: int, from 0 to 15Automixgroup: int, from 0 to 2weight: float, from -12.0 to 12.0DCAon: boolname: strcolor: int, from 0 to 15ConfigThe following method names preceded bychlink1_2,3_4,5_6,7_8,9_10,11_12,13_14,15_16The following method names preceded bybuslink1_2,3_4,5_6for example:chlink1_2,buslink5_6etc..link_eq: boollink_dyn: boollink_fader_mute: boolamixenable: boolamixlock: boolFor the subclassmonitorthe following properties are availablelevel: float, -inf to 10.0source: int, from 0 to 14sourcetrim: float, from -18.0 to 18.0chmode: boolbusmode: booldim: booldimgain: float, from -40.0 to 0.0mono: boolmute: booldimfpl: boolfor example:config.monitor.chmodemute_grouptuple containing a class for each mute groupon: bool, from 0 to 3for example:config.mute_group[0].on = TrueSendlevel: float, -inf to 10.0for example:mixer.strip[10].send[3].level = -16.5XAirRemote class (lower level)Send an OSC command directly to the mixersend(osc command, value)for example:mixer.send(\"/ch/01/mix/on\",1)mixer.send(\"/bus/2/config/name\",\"somename\")Query the value of a command:query(osc command)for example:print(mixer.query(\"/ch/01/mix/on\"))Errorserrors.XAirRemoteError: Base error class for XAIR Remote.errors.XAirRemoteConnectionTimeoutError:Exception raised when a connection attempt times out.The following attributes are available:ip: IP of the mixer.port: Port of the mixer.TestsUnplug any expensive equipment before running tests.\nSave your current settings to a snapshot first.First make sure you installed thedevelopment dependenciesTo run all tests:pytest -v.LicenseThis project is licensed under the MIT License - see theLICENSEfile for detailsDocumentationXAir OSC CommandsX32 OSC CommandsSpecial ThanksPeter Dikantfor writing the base class"} +{"package": "xairos-arc", "pacakge-description": "No description available on PyPI."} +{"package": "xai-sdk", "pacakge-description": "xAI SDKInstallationpipinstallxai-sdkLicensexai-sdkis distributed under the terms of theMITlicense."} +{"package": "xai-tabular-widget", "pacakge-description": "No description available on PyPI."} +{"package": "xaitk-saliency", "pacakge-description": "XAITK - SaliencyThexaitk-saliencypackage is an open source, Explainable AI (XAI) framework\nfor visual saliency algorithm interfaces and implementations, built for\nanalytics and autonomy applications.Seeherefor a more formal introduction to the topic of XAI and visual saliency\nexplanations.This framework is a part of theExplainable AI Toolkit (XAITK).Supported AlgorithmsThexaitk-saliencypackage provides saliency algorithms for a wide range of image understanding\ntasks, including image classification, image similarity, object detection, and reinforcement learning.\nThe current list of supported saliency algorithms can be foundhere.Target AudienceThis toolkit is intended to help data scientists and developers who want to\nadd visual saliency explanations to their workflow or product.\nFunctionality provided here is both directly accessible for targeted\nexperimentation, and throughStrategyandAdapterpatterns to allow for\nmodular integration into systems and applications.InstallationInstall the latest release via pip:pipinstallxaitk-saliencySome plugins may require additional dependencies in order to be utilized at\nruntime.\nSuch details are describedhere.Seehere for more installation documentation.Getting StartedWe provide a number of examples based on Jupyter notebooks in the./examples/directory to show usage of thexaitk-saliencypackage in a number of\ndifferent contexts.Contributions are welcome!\nSee theCONTRIBUTING.mdfile for details.DocumentationDocumentation snapshots for releases as well as the latest master are hosted onReadTheDocs.The sphinx-based documentation may also be built locally for the most\nup-to-date reference:# Install dependenciespoetryinstall# Navigate to the documentation root.cddocs# Build the docs.poetryrunmakehtml# Open in your favorite browser!firefox_build/html/index.htmlXAITK Saliency Demonstration ToolThisassociated projectprovides a local web-application that provides a demonstration of visual\nsaliency generation in a user-interface.\nThis provides an example of how visual saliency, as generated by this package,\ncan be utilized in a user-interface to facilitate model and results\nexploration.\nThis tool uses thetrame framework."} +{"package": "xaitk-saliency-demo", "pacakge-description": "XAITK Saliency functionality demonstration via an interactive Web UI that can run locally, in jupyter or in the cloud.\nA docker image is available for cloud deployment or local testing (kitware/trame:xaitk).\nThis application has been mainly tested on Linux but should work everywhere assuming all the dependencies manage to install on your system.LicenseThis application is provided under the BSD Open Source License.InstallingOn Linux,pipis enough to install this Python library.python3.9 -m venv .venv\nsource .venv/bin/activate\npip install -U pip xaitk-saliency-demoThen from that virtual-environment you can run the application like below#Executablexaitk-saliency-demo#Moduleapproachpython -m xaitk_saliency_demo.appWithin Jupyter you can do the followingfrom xaitk_saliency_demo.app.jupyter import create_app\nxaitk = await create_app()\nxaitk.guiDocker imageFor each commit to master the CI will push a newkitware/trame:xaitkimage to dockerhub.\nSuch image can be ran locally using the following command line.docker run -it --rm --gpus all -p 8080:80 kitware/trame:xaitk"} +{"package": "xaiz", "pacakge-description": "XAI (eXplainable Artificial Intelligence) LibraryOverviewThe XAI (eXplainable Artificial Intelligence) Library is a powerful toolkit designed to empower data scientists and machine learning practitioners in their journey to understand, interpret, and visualize complex machine learning models. In an era of advanced AI algorithms, transparency and interpretability are paramount. XAI addresses these needs by offering a suite of advanced visualizations tailored for regression analysis, curated datasets, pre-trained regression models, and comprehensive documentation.FeaturesAdvanced Visualizations: Explore a rich collection of visualizations in theXAI Regression Visualizations Moduledesigned to unravel the intricacies of your regression models.Datasets and Models: Access curated datasets and pre-trained regression models to streamline your regression analysis process.Model-Agnostic Explanations: Enjoy model-agnostic explanations for compatibility with a wide array of machine learning models.Interpretability for Diverse Data Types: XAI is built to cater to diverse data types, including tabular data, image data, and natural language processing (NLP) models.Continuous Improvement: Expect regular updates with additional features and support for various machine learning tasks.Getting StartedTo harness the power of the XAI Library, follow these steps:Install the Library: Begin by including the library in your Python environment.Explore Documentation: Refer to theGetting Started Guideto understand the library's objectives and scope.Usage Guide: Dive into theUsage Guidefor detailed instructions on using the library's features.ExamplesExplore practical examples demonstrating the library's capabilities in theExample Notebooksdirectory.DocumentationGetting Started Guide: Learn about the library's objectives and scope.Usage Guide: Detailed instructions on using the library's features.Index: The main page with information about the library and its creator.AuthorZeed Almelhem (GitHub)ContactFor inquiries and feedback, please feel free to contact the author:Email (z@zeed-almelhem.com)Personal WebsiteKaggleGitHubMediumInstagramLinkedInTwitterBlogProjectsContactLicenseThis project is licensed under the MIT License - see theLICENSEfile for details."} +{"package": "xaj", "pacakge-description": ".. warning::\nThis version ofXAJworks only withjaxandjaxlib0.3.\nButjaxlib0.3 is not available on PyPI.\nTo install this version ofXAJ, please first installjaxlibwith:.. code-block:: bash\n pip install jaxlib==0.3.25 -f https://storage.googleapis.com/jax-releases/jax_releases.htmlXAJOrdinary differential equation (ODE) integrator compatible withGoogle's JAX.XAJimplements the Runge-Kutta Dormand-Prince 4/5 pair (DP5) with\nadaptive step control and dense output according to theNumerical Recipes.\nIt provides a fast and efficient way to solve non-stiff ODEs.\nThe programming interface is designed so it feels similar to the\nderivative functions inJAX.Specifically,XAJprovides a single functionodeint().\nApplying it to another functionrhs()and the initial conditions\nreturns the numerical solution as a callablens, which interpolates\nthe dense output.from xaj import odeint\nfrom jax import numpy as np\n\nrhs = lambda x, y: y\nx0 = 0\ny0 = 1\n\nns = odeint(rhs, x0, y0, 1)\n\nx = np.linspace(0, 5)\ny = ns(x)The numerical integration happens in a \"lazy\" way, which is triggered\nby the extreme values of the argument ofns.\nAlternatively, it is possible to obtain the numerical solutions at the\nfull steps byxs = ns.xs\nys = ns.ysDemos on how to useXAJcan be found in thedemosdirectory."} +{"package": "xako", "pacakge-description": "Xako - Document sharing transport layerOverviewXako is document sharing transport layer system with a simple REST API. It\nallows application to send files to other peers. Xako handles the job of\ncommunicating with the peers and make the dispatch.Xako ensures data integrity at delivery/arrival of documents.See the documentation for more information.BackendsXako uses backends to send the documents fragments. At this moment xako only\nhas a single backend: email. This means you must provide each xako domain a\nPOP/SMTP pair to send and receive documents.See the email backend documentation.ChangelogSeries 0.x2018-11-20. Release 0.7.0Initial release for Python 3."} +{"package": "xal", "pacakge-description": "xalis a Python library which provides\nanhigh-level API to interact with system resources(files, commands, \u2026)\nandlow-level executionvia third-parties (stdlib, Fabric, Salt, \u2026).The concept is you open a session in system, then you run commands within the\nsession:session is specific, it holds the execution context, it knows the low-level\nimplementation.commands use a generic API. You could run the same commands in another\nsession.Tip\u201cxal\u201d is the acronym of \u201ceXecution Abstraction Layer\u201d.ExampleLet\u2019s initialize a session on local system:>>> import xal\n>>> local_session = xal.LocalSession()In this session, we can manage files:>>> path = local_session.path('hello-xal.txt')\n>>> path.exists()\nFalse\n>>> written = path.open('w').write(u'Hello world!')\n>>> path.exists()\nTrue\n>>> print path.open().read()\nHello world!\n>>> path.unlink()\n>>> path.exists()\nFalseWe can also execute sh commands:>>> result = local_session.sh.run(u\"echo 'Goodbye!'\")\n>>> print result.stdout\nGoodbye!\nNow let\u2019s make a function that does the same. It takes the session as input\nargument:>>> def hello(session):\n... path = session.path('hello-xal.txt')\n... path.open('w').write(u\"Hello world!\")\n... print path.open().read()\n... path.unlink()\n... print session.sh.run(u\"echo 'Goodbye!'\").stdoutOf course, we can run it in local session:>>> hello(local_session)\nHello world!\nGoodbye!\nWhat\u2019s nice is that we can reuse the same function in another session. Let\u2019s\ncreate a remote SSH session using Fabric\u2026>>> remote_session = xal.FabricSession(host='localhost')\u2026 then just run the same function with this remote session:>>> hello(remote_session)\nHello world!\nGoodbye!\nMotivationsxalideas are:Python users (including sysadmins and devops) have a consistent and unified\nAPI to write scripts that perform operations on system.such scripts are portable, i.e. they can be executed in various environments.\nWhatever the operating system, whatever the protocol to connect to and\ncommunicate with the system\u2026Python community can share libraries that are compatible with tools such as\nFabric, zc.buildout, Salt, Ansible\u2026it is easier to switch from one tool to another: reconfigure the session,\ndon\u2019t change the scripts. Develop scripts locally, test them remotely via\nFabric, distribute them using Salt\u2026 or vice-versa.Project\u2019s statusToday:xalis a proof-of-concept. It focuses on sample implementation of\nbasic features such as managing files and directories, or executing sh\ncommands. The idea is that, as a Python user, you can give it a try and, if you\nlike it, use it for simple tasks.Tomorrow, depending on feedback from community,xalmay improve or be\ndeprecated. Asxal\u2019s author, I would like the following things to happen:increased stability and performances for current features.more execution contexts (i.e. sessions): Salt, Fabric as sudoer, \u2026more resources: users, system packages, \u2026better API, preferrably built as PEPs. Just asxal\u2019s proof of concept tries\nto mimicpathlib, there could be a PEP related to every resource. Sh\ncommands (a.k.a. replacement for subprocess) are an epic example.Asxal\u2019s author, I can\u2019t do it alone. If you\u2019d like to help:provide feedback. Do you likexal? What do you dislike inxal? Your\nfeedback matters!join the project on Github.RessourcesDocumentation:https://xal.readthedocs.orgPyPI:https://pypi.python.org/pypi/xalCode repository:https://github.com/benoitbryon/xalBugtracker:https://github.com/benoitbryon/xal/issuesContinuous integration:https://travis-ci.org/benoitbryon/xal"} +{"package": "xalanih", "pacakge-description": "What is Xalanih ?Xalanih is a python script made to help you version your SQL database. You can use it to manage the creation or update the database of your project.Technical RequirementsPython 3.6mysqlclientsqlparseHow to install Xalanihpip3 install xalanihHow to use XalanihCreate the dbpython3-mxalanihcreatewhere must be replaced by the name of the database.Update the dbpython3-mxalanihupdatewhere must be replaced by the name of the database.OptionsDifferents options can be given to the script. You can find all of them using the following command:python3 xalanih -hWorking directory-d Specify the directory where all the database scripts are.Default value: \".\"Database type-t Specify the type of database to which the script has to connect.Accepted value: mysql |Default value: mysqlHost-H The address of the host of the database.Default value: localhostPort-p The port of the database.Default value: 3306User-u The user used to connectDefault value: rootPassword-pwd The password used to connect to the database.Socket-s The path to the mysql socket if it is not at the default location(/tmp/mysql.sock).LoggingThese options are linked to the logging.Verbosity-v The verbosity of the logs in standard output.Accepted values: 0,1,2,3,4 |Default value: 30: No logs.1: Only errors.2: Errors and warnings.3: Informations, warnings and errors.4: Debugs, informations, warnings and errors.Log file-l The name of the file where the logs are saved. It is not affected by the verbosity options (It is always set at 4). If no file specified, no file are created.last update-to Define the last update that will be applied. Must be an update not included inincluded_updates.no update-nuHas only an effect with the create option. If specified, the script will only execute the creation script and will not apply the updates.How to structure the directory containing the database scriptsThe structure to use for the directory that contains all the scripts you have for your database.L creation (directory)\n L creation.sql (file)\n L included_updates (file)\nL update (directory)\n L script01.sql (file)\n L ...creation(directory)Thecreationdirectory will contains the scripts that will be used to create the baseline of the database. These will only be called when the database is created from zero. That means that they will not be used in case of a database update.creation.sql(file)The scriptcreation.sqlis the entrypoint of Xalanih to create the database. This file must contains all the needed script to create the baseline of your database.included_updates(file)When you will have a lot of update file, you will want to create the database directly with these modification instead of applying them after. In order to do that, you will have to add the modification directly to yourcreation.sql. But in order for Xalanih to not apply the update scripts, you have to add the name of all update scripts already integrated to the fileincluded_updates. There should be one filename by line.update(directory)Theupdatedirectory must contains all your update scripts (and nothing else). There is not realy a nomenclature for the update scripts but the alphabetical order should correspond to their chronological order. Also, no patch can be namedinitial_install. This is because this name is associated to the creation of the databaseTable created by xalanih: xalanih_updatesThe table xalanih_patches contains 3 columns:\nid, update_name, and update_apply_time.\nIt is used by the script to detect which patches have already been applied. The patch name associated to the initial creation of the database isinitial_install."} +{"package": "xalc", "pacakge-description": "Xalc is a hexadecimal calculator for embedded systems programmers, implemented\nas a pre-processor for Python expressions, with a console interface based on\nIPython.Features:Mixed calculations with hex, decimal, binary and binary prefix literalsSupport for undecorated hex literals. Ambiguous literals can be forced to hex by either prefixing or suffixing with \u2018x\u2019.Display in hex, decimal, binary (with bit position ruler) and binary prefixes (sizes)Simple bit mask constructionBit field extraction operatorFrom IPython: Support for arbitrary Python expressions (minus the ones that conflict with the pre-processed syntax), command history, access to previous results with _* variables, etc.The following \u201cscreenshot\u201d demonstrates some of the features of Xalc. The real\nprogram displays the different bases in different colors, if your console\nsupports that:$ xalc\nIn [1]: deadbeef\n0xdeadbeef\nOut[1]:\n3735928559 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n0xdeadbeef \u2502 1101 1110 1010 1101 1011 1110 1110 1111\n3 Gi + 490 Mi + 879 Ki + 751\n\nIn [2]: deadbeef $ m5t13\n0xdeadbeef >> 5 & ((0x3fe0) >> 5)\nOut[2]:\n 503 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0x000001f7 \u2502 0000 0000 0000 0000 0000 0001 1111 0111\n\nIn [3]: _ ^ cafe\n_ ^ 0xcafe\nOut[3]:\n 51977 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0x0000cb09 \u2502 0000 0000 0000 0000 1100 1011 0000 1001\n 50 Ki + 777\n\nIn [4]: 7f000000 - 35000000x\n0x7f000000 - 0x35000000\nOut[4]:\n 1241513984 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0x4a000000 \u2502 0100 1010 0000 0000 0000 0000 0000 0000\n 1 Gi + 160 Mi\n\nIn [5]: m2p0_5_8t9_29_31t31\n(0x3|0x20|0x300|0x20000000|0x80000000)\nOut[5]:\n 2684355363 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0xa0000323 \u2502 1010 0000 0000 0000 0000 0011 0010 0011\n 2 Gi + 512 Mi + 803\n\nIn [6]: 2g | m12\n0x80000000 | (0x1000)\nOut[6]:\n 2147487744 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0x80001000 \u2502 1000 0000 0000 0000 0001 0000 0000 0000\n 2 Gi + 4 Ki\n\nIn [7]: -45\n-45\nOut[7]:\n -45 \u2502 28\u2500\u256e 24\u2500\u256e 20\u2500\u256e 16\u2500\u256e 12\u2500\u256e 8\u2500\u256e 4\u2500\u256e 0\u2500\u256e\n 0xffffffd3 \u2502 1111 1111 1111 1111 1111 1111 1101 0011Install with pip:pip install --upgrade xalcOr by cloning thegit repoand running:python setup.py installRunxalcafter installation."} +{"package": "xaled-scrapers", "pacakge-description": "A collection of helper functions for scraping web sites."} +{"package": "xaled-utils", "pacakge-description": "Frequently used functions library for Python3 By Khalid Grandi (github.com/xaled)."} +{"package": "xaler", "pacakge-description": "No description available on PyPI."} +{"package": "xalglib", "pacakge-description": "# ALGLIBALGLIB is a cross-platform numerical analysis and data processing library.Homepage:https://www.alglib.net## Install with pip`bash pip install xalglib `## Quickstart`python3 from xalglib import xalglib `"} +{"package": "xalgorithm", "pacakge-description": "My Implementation of Data Structure and Algorithms in PythonBuild and Update Packagemake upload version=a.b.cInstall This Packagepip install xalgorithmList of ImplementationsXalgorithm FunctionEffect@tag_meTag each function with a label and access the function using that label@print_mePrint the functon, its argument and result, helpful in debugging@ctrl_cAsk the user for confirmation to exit the program@record_itMeasure either the execution time or the execution count of a functionopathReturn the absolute path, expanding any user shortcutsojoinJoin multiple path components and optionally creates the path if it doesn't existosimplifyNormalize a pathxprintPrint text in styled format, please see my changelog for detailed usagesOut FunctonEffectmake_classificationGenerates a synthetic classification datasetdescribe_dfPerforms exploratory analysis on each featureprint_dfPrint a pandas DataFrame with rich APIBenchmarkThis class evaluates several well-known machine learning algorithms for a classification problem and provides multiple classification metrics for comparative analysis%py_versionPrint the current version of Python%%csvParses the cell into a DataFrame and then prints the DataFrame to the console in the specified format (rich-format, plain-format, markdown-format)%%timeDisplay the execution time of code within a cell in secondsOds FunctionEffectpower_analysisCalculate sample size for power analysis using effect size, significance, power, and population stdRFMSegment and Target customers for personalized marketing strategies using Recency, Frequency, Monetary analysisparse_vdsDownload Youtube subtitles, seexalgorithm --helpfor guidance. The Spacy English pipeline can be optionally loaded to segment sentences within subtitle scriptsArray AlgorithmDefinition:white_large_square: Sliding Window:white_check_mark: HuaRongDaoSolve a puzzle where the goal is to start from initial state and end in final stateAdvanced Algorithms and Data Structures (La Rocca, M., 2021)TopicNoteFinish DateChp 2: d-way heapsPriority Queue:white_large_square:Chp 2: huffman compressionxxxx:white_large_square:ChangeLogAll updates are tracked inthis file.CreditsTo better prepare myself for the challenges of algorithmic problems, I have included code fromOpen Data Structures. I will probably to rewrite some functions to make them compatible with my project as I continue to read this book. I owe huge gratitude for their work in jumping start my learning journey."} +{"package": "xalign", "pacakge-description": "xAlign: Hassle-free transcript quantificationxAlign is an efficient python package to align FASTQ files against any Ensembl reference genomes. The currently supported alignment algorithms arekallisto(https://pachterlab.github.io/kallisto/) andSalmon(https://salmon.readthedocs.io/en/latest/salmon.html). The package contains modules for Ensemble ID mapping to gene symbols via themygene.infopython package and SRA download capabilities. When using this package please cite the corresponding alignment algorithm.Installationpip3 install git+https://github.com/MaayanLab/xalign.gitRequirementsThe alignment algorithms require a minimum of around 5GB of memory to run. When downloading SRA files, make sure that there is sufficient available disk space.xalignis currently only working onLinuxoperating systems.UsageThe recommended usage isxalign.align_folder()if there are multiple FASTQ files. These FASTQ files can be aligned one by one, and gene level counts can be aggregated using the functionxalign.ensembl.agg_gene_counts()Align a single FASTQ file in single-read modeTo align a single RNA-seq file we first download an example SRA file and save it in the folderdata/example_1relative to the working directory. The functionxalign.align_fastq()will generate the required cDNA index from the Ensembl reference genome when the index is not already built.resultis a dataframe with transcript IDs, gene counts, and TPM.When the alignment is run against a new species, the initial setup will take a few minutes to complete because building a new index and creating gene mapping files are required.importxalignxalign.sra.load_sras([\"SRR14457464\"],\"data/example_1\")result=xalign.align_fastq(\"homo_sapiens\",\"data/example_1/SRR14457464.fastq\",t=8)Align a single FASTQ file in paired-end modeTo align a single RNA-seq file in paired-end mode we first download an example SRA file and save it in folderdata/example_2relative to the working directory. If the SRA file is a paired-end sample, two files will be generated with the two suffixes_1and_2. The functionxalign.align_fastq()will generate the required cDNA index from the Ensembl reference genome when the index is not already built.resultis a dataframe with transcript IDs, gene counts, and TPM.When the alignment is run against a new species, the initial setup will take a couple of minutes to built the index and to create the gene mapping files.importxalign# the sample is paired-end and will result in two files (SRR15972519_1.fastq, SRR15972519_2.fastq)xalign.sra.load_sras([\"SRR15972519\"],\"data/example_2\")result=xalign.align_fastq(\"homo_sapiens\",[\"data/example_2/SRR15972519_1.fastq\",\"data/example_2/SRR15972519_2.fastq\"],t=8)Align FASTQ files in a directoryxaligncan automatically align all files in a given folder, instead of callingxalign.align_fastq()multiple times. In this casexalign.align_folder()will automatically detect whether the folder contains paired- or single-end samples and group the samples accordingly without manual input. The output will be two dataframes.gene_countwill contain gene level counts that can be aggregated for different gene identifiers (symbol:default, ensembl_id, entrezgene_id). Transcripts that can not be mapped to corresponding identifiers are discarded.transcript_countcontains the read counts at transcript level.importxalign# this will download multiple GB of samplesxalign.sra.load_sras([\"SRR15972519\",\"SRR15972520\",\"SRR15972521\"],\"data/example_3\")gene_count,transcript_count=xalign.align_folder(\"homo_sapiens\",\"data/example_3\",t=8,overwrite=False)Mapping transcript counts to gene-level countsWhen FASTQ files are aligned individually usingxalign.align_fastq()the output is in transcript-level. To aggregate counts to gene-level the functionxalign.ensembl.agg_gene_counts()can be used.importxalignxalign.sra.load_sras([\"SRR14457464\"],\"data/example_4\")result=xalign.align_fastq(\"homo_sapiens\",\"data/example_4/SRR15972519.fastq\",t=8)# identifier can be symbol/ensembl_id/entrezgene_idgene_counts=xalign.ensembl.agg_gene_counts(result,\"homo_sapiens\",identifier=\"symbol\")"} +{"package": "xalpha", "pacakge-description": "xalpha\u57fa\u91d1\u6295\u8d44\u7684\u5168\u6d41\u7a0b\u7ba1\u7406\u573a\u5916\u57fa\u91d1\u7684\u4fe1\u606f\u4e0e\u51c0\u503c\u83b7\u53d6\uff0c\u7cbe\u786e\u5230\u5206\u7684\u6295\u8d44\u8d26\u6237\u8bb0\u5f55\u6574\u5408\u5206\u6790\u4e0e\u4e30\u5bcc\u53ef\u89c6\u5316\uff0c\u7b80\u5355\u7684\u7b56\u7565\u56de\u6d4b\u4ee5\u53ca\u6839\u636e\u9884\u8bbe\u7b56\u7565\u7684\u5b9a\u65f6\u6295\u8d44\u63d0\u9192\u3002\u5c24\u5176\u9002\u5408\u8d44\u91d1\u53cd\u590d\u8fdb\u51fa\u7684\u5b9a\u6295\u578b\u548c\u7f51\u683c\u578b\u6295\u8d44\u7684\u6982\u89c8\u4e0e\u7ba1\u7406\u5206\u6790\u3002\ud83c\udf89 0.3 \u7248\u672c\u8d77\u652f\u6301\u901a\u7528\u65e5\u7ebf\u548c\u5b9e\u65f6\u6570\u636e\u83b7\u53d6\u5668\uff0c\u7edf\u4e00\u63a5\u53e3\u4e00\u884c\u53ef\u4ee5\u83b7\u5f97\u51e0\u4e4e\u4efb\u4f55\u5e02\u573a\u4e0a\u5b58\u5728\u4ea7\u54c1\u7684\u4ef7\u683c\u6570\u636e\uff0c\u8fdb\u884c\u5206\u6790\u3002\ud83c\udf6d 0.9 \u7248\u672c\u8d77\u652f\u6301\u6301\u4ed3\u57fa\u91d1\u7ec4\u5408\u7684\u5e95\u5c42\u6301\u4ed3\u914d\u7f6e\u548c\u80a1\u7968\u7ec6\u8282\u900f\u89c6\uff0c\u638c\u63e1\u5e95\u5c42\u6301\u4ed3\u548c\u8ddf\u8e2a\u673a\u6784\u80a1\u7968\u6c60\u4e0e\u4e70\u5356\u7279\u70b9\uff0c\u4ece\u672a\u5982\u6b64\u7b80\u5355\u3002\u4e00\u884c\u62ff\u5230\u57fa\u91d1\u4fe1\u606f\uff1anfyy=xa.fundinfo(\"501018\")\u4e00\u884c\u6839\u636e\u8d26\u5355\u8fdb\u884c\u57fa\u91d1\u7ec4\u5408\u5168\u6a21\u62df\uff0c\u548c\u5b9e\u76d8\u5b8c\u5168\u76f8\u7b26:jiaoyidan=xa.record(path)# \u989d\u5916\u4e00\u884c\u5148\u8bfb\u5165 path \u5904\u7684 csv \u8d26\u5355shipan=xa.mul(status=jiaoyidan)# Let's rockshipan.summary()# \u770b\u6240\u6709\u57fa\u91d1\u603b\u7ed3\u6548\u679cshipan.get_stock_holdings()# \u67e5\u770b\u5e95\u5c42\u7b49\u6548\u80a1\u7968\u6301\u4ed3\u4e00\u884c\u83b7\u53d6\u5404\u79cd\u91d1\u878d\u4ea7\u54c1\u7684\u5386\u53f2\u65e5\u7ebf\u6570\u636e\u6216\u5b9e\u65f6\u6570\u636exa.get_daily(\"SH518880\")# \u6caa\u6df1\u5e02\u573a\u5386\u53f2\u6570\u636exa.get_daily(\"USD/CNY\")# \u4eba\u6c11\u5e01\u4e2d\u95f4\u4ef7\u5386\u53f2\u6570\u636exa.get_rt(\"commodities/crude-oil\")# \u539f\u6cb9\u671f\u8d27\u5b9e\u65f6\u6570\u636exa.get_rt(\"HK00700\",double_check=True)# \u53cc\u91cd\u9a8c\u8bc1\u9ad8\u7a33\u5b9a\u6027\u652f\u6301\u7684\u5b9e\u65f6\u6570\u636e\u4e00\u884c\u62ff\u5230\u6307\u6570\uff0c\u884c\u4e1a\uff0c\u57fa\u91d1\u548c\u4e2a\u80a1\u7684\u5386\u53f2\u4f30\u503c\u548c\u5373\u65f6\u4f30\u503c\u5206\u6790\uff08\u6307\u6570\u90e8\u5206\u9700\u8981\u805a\u5bbd\u6570\u636e\uff0c\u672c\u5730\u8bd5\u7528\u7533\u8bf7\u6216\u76f4\u63a5\u5728\u805a\u5bbd\u4e91\u5e73\u53f0\u8fd0\u884c\uff09xa.PEBHistory(\"SH000990\").summary()xa.PEBHistory(\"F100032\").v()\u4e00\u884c\u5b9a\u4ef7\u53ef\u8f6c\u503axa.CBCalculator(\"SH113577\").analyse()\u4e00\u884c\u4f30\u7b97\u57fa\u91d1\u51c0\u503c (QDII \u57fa\u91d1\u9700\u81ea\u5df1\u63d0\u4f9b\u6301\u4ed3\u5b57\u5178)xa.QDIIPredict(\"SH501018\",positions=True).get_t0_rate()xalpha \u4e0d\u6b62\u5982\u6b64\uff0c\u66f4\u591a\u7279\u6027\uff0c\u6b22\u8fce\u63a2\u7d22\u3002\u4e0d\u53ea\u662f\u6570\u636e\uff0c\u66f4\u662f\u5de5\u5177\uff01\u6587\u6863\u5728\u7ebf\u6587\u6863\u5730\u5740\uff1ahttps://xalpha.readthedocs.io/\u6216\u8005\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5728\u672c\u5730doc/build/html\u5185\u9605\u8bfb\u6587\u6863\u3002$cddoc\n$makehtml\u5b89\u88c5pipinstallxalpha\u76ee\u524d\u4ec5\u652f\u6301 python 3 \u3002\u82e5\u60f3\u8981\u5c1d\u8bd5\u6700\u65b0\u7248\uff0c$gitclonehttps://github.com/refraction-ray/xalpha.git\n$cdxalpha&&python3setup.pyinstall\u7528\u6cd5\u672c\u5730\u4f7f\u7528\u7531\u4e8e\u4e30\u5bcc\u7684\u53ef\u89c6\u5316\u652f\u6301\uff0c\u5efa\u8bae\u914d\u5408 Jupyter Notebook \u4f7f\u7528\u3002\u53ef\u4ee5\u53c2\u7167\u8fd9\u91cc\u7ed9\u51fa\u7684\u793a\u4f8b\u8fde\u63a5\uff0c\u5feb\u901f\u638c\u63e1\u5927\u90e8\u5206\u529f\u80fd\u3002\u90e8\u5206\u6548\u679c\u5982\u4e0b\uff1a\u5728\u91cf\u5316\u5e73\u53f0\u4f7f\u7528\u8fd9\u91cc\u4ee5\u805a\u5bbd\u4e3a\u4f8b\uff0c\u6253\u5f00\u805a\u5bbd\u7814\u7a76\u73af\u5883\u7684 jupyter notebook\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1a>>> !pip3 install xalpha --user\n>>> import sys\n>>> sys.path.insert(0, \"/home/jquser/.local/lib/python3.6/site-packages\")\n>>> import xalpha as xa\u5373\u53ef\u5728\u91cf\u5316\u4e91\u5e73\u53f0\u6b63\u5e38\u4f7f\u7528 xalpha\uff0c\u5e76\u548c\u4e91\u5e73\u53f0\u63d0\u4f9b\u6570\u636e\u65e0\u7f1d\u7ed3\u5408\u3002\u5982\u679c\u60f3\u5728\u4e91\u5e73\u53f0\u7814\u7a76\u73af\u5883\u5c1d\u8bd5\u6700\u65b0\u5f00\u53d1\u7248 xalpha\uff0c\u6240\u9700\u914d\u7f6e\u5982\u4e0b\u3002>>> !git clone https://github.com/refraction-ray/xalpha.git\n>>> !cd xalpha && python3 setup.py develop --user\n>>> import sys\n>>> sys.path.insert(0, \"/home/jquser/.local/lib/python3.6/site-packages\")\n>>> import xalpha as xa\u7531\u4e8e xalpha \u6574\u5408\u4e86\u90e8\u5206\u805a\u5bbd\u6570\u636e\u6e90\u7684 API\uff0c\u5728\u4e91\u7aef\u76f4\u63a5xa.provider.set_jq_data(debug=True)\u5373\u53ef\u6fc0\u6d3b\u805a\u5bbd\u6570\u636e\u6e90\u3002\u81f4\u8c22\u611f\u8c22\u96c6\u601d\u5f55\u5bf9\u672c\u9879\u76ee\u7684\u652f\u6301\u548c\u8d5e\u52a9\uff0c\u53ef\u4ee5\u5728\u8fd9\u91cc\u67e5\u770b\u57fa\u4e8e xalpha \u5f15\u64ce\u6784\u5efa\u7684 QDII \u57fa\u91d1\u51c0\u503c\u9884\u6d4b\u3002\u535a\u5ba2xalpha \u8bde\u751f\u8bb0xalpha \u8bbe\u8ba1\u54f2\u5b66\u53ca\u5176\u4ed6"} +{"package": "xam", "pacakge-description": "A CLI utility for searching and listing XBMC Addon Repositories.Setup$ pip install xam\n$ xam --helpLinkswebsite"} +{"package": "xamarin-legos", "pacakge-description": "No description available on PyPI."} +{"package": "xamcheck_utils", "pacakge-description": "## xamcheck-utilsUtility functions used in python projects of [Xamcheck](http://xamcheck.com).[![Build Status](https://travis-ci.org/psjinx/xamcheck-utils.svg?branch=master)](https://travis-ci.org/psjinx/xamcheck-utils)"} +{"package": "xaml", "pacakge-description": "an easier way for humans to write xml and htmlif a line starts with any xaml component ( ~ @ . # $ ) that line represents\nan xml/http element:- an element continues until eol, or an unquoted :\n- an element can be continued to the next line(s) using unquoted parensif a line starts with a \u201c:\u201d it is specifying how the following lines should\nbe interpreted:- :css -> cascading style sheets that are inserted with a

{{letter}}

bot.pyfromstringimportascii_lettersasyncdefserve(self,request):letter=choice(ascii_letters)rendered=self.template.render(letter=letter)returnself.respond(rendered)Please note the use of thereturnkeyword here. Theservefunction must\nreturn a response that will be passed to the web server. Also, theasynckeyword. This function can handle asynchronous operations and must be marked as\nsuch. You can return any content type that you might find on the web (e.g.\nHTML, XML, JSON, audio and maybe even video) but you must specify thecontent_type=...keyword argument forrespond.See thelist of available content\ntypesfor more.If you want to pass data from yourdirect/groupfunctions to theservefunction, you'll need to make use ofsome type of persistent\nstorage. Yourservefunction can read from the storage\nback-end and then respond. This is usually as simple as accessing theself.dbattribute.InvitationsAs long as the--no-auto-joinoption is not set (via the configuration file\nor environment also), then your bot will automatically join any room it is\ninvited to. Rooms that your bot has been invited to will be stored in the.xbotlib/data.jsonfile. If your bot is turned off or fails for some reason\nthen it will read this file when turned back on to see what rooms it should\nre-join automatically. Thedata.jsonfile can be edited freely by hand.API ReferenceWhen writing your own bot, you always sub-class theBotclass provided fromxbotlib. Then if you want to respond to a direct message, you write adirectfunction. If you want to respond to a group chat\nmessage, you write agroupfunction. That's it for the\nbasics.Bot.direct(message)Respond to direct messages.Arguments:message: received message (seeSimpleMessagebelow for available attributes)Bot.group(message)Respond to a message in a group chat.Arguments:message: received message (seeSimpleMessagebelow for available attributes)Bot.serve(request)Serve requests via the built-in web server.Seethis sectionfor more.Arguments:request: the web requestBot.routes()Register additional routes for web serving.Seethis sectionfor more.This is an advanced feature. Useself.web.add_routes.fromaiohttp.webimportgetdefroutes(self):self.web.add_routes([get(\"/foo\",self.foo)])Bot.setup()Run some setup logic before starting your bot.SimpleMessageA simple message interface.Attributes:text: the entire text of the messagecontent: the text of the message after the nicksender: the user the message came fromroom: the room the message came fromreceiver: the receiver of the messagenick: the nickname of the sendertype: the type of messageurl: The URL of a sent fileBotBot.reply(message, to=None, room=None)Send a reply back.Arguments:message: the message that is sentto: the user to send the reply toroom: the room to send the reply toBot.respond(response, content_type=\"text/html\")Return a response via the web server.Arguments:response: the text of the responsecontent_type: the type of responseOther useful attributes on theBotclass are:self.db: Thestorage back-endChatroomWe're lurking inxbotlibtest@muc.vvvvvvaria.orgif\nyou want to chat or just invite your bots for testing.More ExamplesSee more examples ongit.vvvvvvaria.org.Deploy your botsDocumentation comingsoon.RoadmapSee theissue tracker.ChangesSee theCHANGELOG.md.LicenseSee theLICENSE.ContributingAny and all contributions most welcome! Happy to hear how you use the library\nor what could be improved from a usability perspective.To test, installTox(pip install tox) and runtoxto run the test suite locally."} +{"package": "xboto", "pacakge-description": "Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiInstall# via pippipinstallxboto# via poetrypoetryaddxbotoQuick StartImport Boto Client/Resource# Use imported `dynamodb` just like dynamodb boto resourcefromxboto.resourceimportdynamodb# Use imported `ssm` just like ssm boto clientfromxboto.clientimportssm# These are for overriding/injecting settings.fromxbotoimportBotoResources,BotoClients,BotoSession# Can use them like normal:dynamodb.table(...)ssm.get_object(...)# Or you can override settings if you wish:withBotoResources.DynamoDB(region_name='us-west-2'):# Use us-west-2 when using dynamodb boto resource:dynamodb.table(...)withBotoClients.Ssm(region_name='us-west-2'):# Use us-west-2 when using ssm boto client:ssm.get_object(...)withBotoSession(region_name='us-west-3'):# Use us-west-3 when using any client/resource# we are setting it at the boto-session level;# the session is used by all boto client/resources.ssm.get_object(...)# Can use them like decorators as well:@BotoClients.Ssm(region_name='us-west-2')defsome_method():ssm.get_object(...)Grab Any Client/Resource# Can easily ask these for any client/resourcefromxbotoimportboto_clients,boto_resources# These are for overriding/injecting settings.fromxbotoimportBotoResources,BotoClients,BotoSession# Can use them like normal:boto_clients.dynamodb.table(...)boto_resources.ssm.get_object(...)# Or you can override settings if you wish:withBotoResources.DynamoDB(region_name='us-west-2'):# Use us-west-2 when using dynamodb boto resource:boto_resources.dynamodb.table(...)withBotoClients.Ssm(region_name='us-west-2'):# Use us-west-2 when using ssm boto client:boto_clients.ssm.get_object(...)withBotoSession(region_name='us-west-3'):# Use us-west-3 when using any client/resource# we are setting it at the boto-session level;# the session is used by all boto client/resources.boto_clients.ssm.get_object(...)# Can use them like decorators as well:@BotoClients.Ssm(region_name='us-west-2')defsome_method():boto_clients.ssm.get_object(...)"} +{"package": "xbout", "pacakge-description": "xBOUTDocumentation:https://xbout.readthedocs.ioExamples:https://github.com/boutproject/xBOUT-examplesxBOUT provides an interface for collecting the output data from aBOUT++simulation into anxarraydataset in an efficient and scalable way, as well as accessor methods\nfor common BOUT++ analysis and plotting tasks.Currently only in alpha (until 1.0 released) so please report any bugs,\nand feel free to raise issues asking questions or making suggestions.InstallationWith pip:pipinstall--userxboutWith conda:condainstall-cconda-forgexboutYou can test your installation ofxBOUTby runningpytest --pyargs xbout.xBOUT requires other python packages, which will be installed when you\nrun one of the above install commands if they are not already installed on\nyour system.Loading your dataThe functionopen_boutdataset()uses xarray & dask to collect BOUT++\ndata spread across multiple NetCDF files into one contiguous xarray\ndataset.The data from a BOUT++ run can be loaded with justbd=open_boutdataset('./run_dir*/BOUT.dmp.*.nc',inputfilepath='./BOUT.inp')open_boutdataset()returns an instance of anxarray.Datasetwhich\ncontains BOUT-specific information in theattrs, so represents a\ngeneral structure for storing all of the output of a simulation,\nincluding data, input options and (soon) grid data.BoutDataset Accessor MethodsxBOUT defines a set ofaccessormethods on the loaded Datasets and DataArrays, which are called byds.bout.method().This is where BOUT-specific data manipulation, analysis and plotting\nfunctionality is stored, for exampleds['n'].bout.animate2D(animate_over='t',x='x',y='z')ords.bout.create_restarts(savepath='.',nxpe=4,nype=4)Extending xBOUT for your BOUT moduleThe accessor classesBoutDatasetAccessorandBoutDataArrayAccessorare intended to be subclassed for specific BOUT++ modules. The subclass\naccessor will then inherit all the.boutaccessor methods, but you\nwill also be able to override these and define your own methods within\nyour new accessor.For example to add an extra method specific to theSTORMBOUT++\nmodule:fromxarrayimportregister_dataset_accessorfromxbout.boutdatasetimportBoutDatasetAccessor@register_dataset_accessor('storm')classStormAccessor(BoutAccessor):def__init__(self,ds_object):super().__init__(ds_object)defspecial_method(self):print(\"Do something only STORM users would want to do\")ds.storm.special_method()Out [1]: Do something only STORM users would want to doThere is included an example of aStormDatasetwhich contains all the data from aSTORMsimulation, as well as\nextra calculated quantities which are specific to the STORM module.ContributingFeel free to raise issues about anything, or submit pull requests,\nthough I would encourage you to submit an issue before writing a pull\nrequest.\nFor a general guide on how to contribute to an open-source python\nproject seexarray's guide for contributors.The existing code was written using Test-Driven Development, and I would\nlike to continue this, so please includepytesttests with any pull\nrequests.If you write a new accessor, then this should really live with the code\nfor your BOUT module, but it could potentially be added as an example to\nthis repository too.DevelopersClone the repository with:gitclonegit@github.com:boutproject/xBOUT.gitThe recommended way to work withxBOUTfrom the git repo is to do an editable\ninstall with pip. Run this command from thexBOUT/directory:pipinstall--user-e.which will also install all the required dependencies. Dependencies can also be\ninstalled using pippipinstall--user-rrequirements.txtor condaconda install --file requirements.txtIt is possible to usexBOUTby adding thexBOUT/directory to your$PYTHONPATH.Test by runningpytestin thexBOUT/directory.Development planThings which definitely need to be included (see the 1.0 milestone):More tests, both with\nand against the originalboutdata.collect()Speed test against old collectThings which would be nice and I plan to do:Infer concatenation order from global indexes (seeissue)Real-space coordinatesVariable names and units (following CF conventions)Unit-aware arraysVariable normalisationsThings which might require a fair amount of effort by another developer but\ncould be very powerful:Using real-space coordinates to create tokamak-shaped plotsSupport for staggered grids using xgcmSupport for encoding topology using xgcmAPI for applying BoutCore operations (hopefully usingxr.apply_ufunc)"} +{"package": "xbow", "pacakge-description": "A system to ease the use of cloud resources for MD simulations."} +{"package": "xbowflow", "pacakge-description": "A system to ease the use of cloud resources for MD simulations."} +{"package": "xbox", "pacakge-description": "AboutThis project is a wrapper around Microsoft\u2019s set of private APIs in use\nby the Xbox One and related apps.GoalsThe main goals of this project are to achieve a decent, usable API,\neverything else is secondary.InstallationInstall usingpip$ pip install xboxUsage>>>importxbox>>>xbox.client.authenticate(login='joe@example.org',password='hunter2')>>># get a gamer>>>gt=xbox.GamerProfile.from_gamertag('JoeAlcorn')>>>gt.gamerscore22056>>>gt.gamerpic'http://images-eds.xboxlive.com/image?url=z951ykn43p4FqWbbFvR2Ec.8vbDhj8G2Xe7JngaTToBrrCmIEEXHC9UNrdJ6P7KIFXxmxGDtE9Vkd62rOpb7JcGvME9LzjeruYo3cC50qVYelz5LjucMJtB5xOqvr7WR'>>># get iterator of recorded clips>>>clips=gt.clips()>>># convert iterator to a list so we can index it>>>clips=list(clips)>>>clip=clips[0]>>>clip.media_url'http://gameclipscontent-d2005.xboxlive.com/asset-886c5b78-8876-4823-b31b-fbc77d8caa67/GameClip-Original.MP4?sv=2012-02-12&st=2014-09-03T22%3A40%3A58Z&se=2014-09-03T23%3A45%3A58Z&sr=c&sp=r&sig=Q5qvyDvFRM2Bn2tztJ%2F%2BEf9%2FQOpkTPuFniByvE%2Bc9cc%3D&__gda__=1409787958_f22b516f9d29da56911b7cac03f15d05'>>>clip.views4>>>clip.state'Published'>>>clip.duration54>>>clip.thumbnails.large'http://gameclipscontent-t2005.xboxlive.com/00090000014d6bae-7638b9fd-2a19-4ef1-b621-505a6ac93488/Thumbnail_Large.PNG'LinksCodeIssues & BugsDocumentationPyPIRoadmap"} +{"package": "xbox360controller", "pacakge-description": "xbox360controllerA pythonic Xbox360 controller API built on top of thexpadLinux kernel driver.This Python Package aims to provide a pythonic and complete API for your Xbox360 and similar game controllers.\nCurrently it's built on top of the Linux kernel driverxpadso you can use it on almost any Linux distribution including your Rasperry Pi projects etc.The following features are supported:Registering callbacks forallButtons, Axes, Triggers and Hat in agpiozero-inspired waySetting the LED circle; allxpadprovided options are possible: blinking, rotating, setting individual LEDs on and off, ...Rumbling, both the left and right side can be controlled from 0 to 100 percentInstallationYou will need Python 3.4 or above.Any Linux distribution:pip3 install -U xbox360controllerYou might also use avirtual environmentor do a per-user install by providing the--userflag to above command.\nGlobal installations might require the usage ofsudoor working directly from a root shell but arenot recommended.If thepip3command cannot be found, trypipor make sure to have pip installed properly:sudo apt install python3-pipOf course you don't needsudowhen working from a root shell.UsageBasicsimportsignalfromxbox360controllerimportXbox360Controllerdefon_button_pressed(button):print('Button{0}was pressed'.format(button.name))defon_button_released(button):print('Button{0}was released'.format(button.name))defon_axis_moved(axis):print('Axis{0}moved to{1}{2}'.format(axis.name,axis.x,axis.y))try:withXbox360Controller(0,axis_threshold=0.2)ascontroller:# Button A eventscontroller.button_a.when_pressed=on_button_pressedcontroller.button_a.when_released=on_button_released# Left and right axis move eventcontroller.axis_l.when_moved=on_axis_movedcontroller.axis_r.when_moved=on_axis_movedsignal.pause()exceptKeyboardInterrupt:passThe above code will run untilCtrl+Cis pressed. Each time on of the left or right axis is moved, the event will be processed. Additionally, the events of the A button are being processed.See theAPI referencefor a more detailed explanation of theXbox360Controllerclass and how to use all available buttons, axes and the hat.Rumblingimporttimefromxbox360controllerimportXbox360ControllerwithXbox360Controller()ascontroller:controller.set_rumble(0.5,0.5,1000)time.sleep(1)This will enable rumble on both sides of the controller with each 50% strength for one second (1000ms). Note that the method call is non-blocking, thus we need to manually wait one second for the rumble to finish. You won't need this in a regular use case withsignal.pause().LEDimporttimefromxbox360controllerimportXbox360ControllerwithXbox360Controller()ascontroller:controller.set_led(Xbox360Controller.LED_ROTATE)time.sleep(1)controller.set_led(Xbox360Controller.LED_OFF)This will let the LED circle rotate for one second and then turn it off.See theAPI referencefor all available LED modes.Debug informationfromxbox360controllerimportXbox360ControllerwithXbox360Controller()ascontroller:controller.info()Development/contributingThis project is now in a somewhat stable state, and I really appreciate all kinds of contributions - may it be new or improved code, documentation or just a simple typo fix.\nJust provide me a PR and I'll be happy to include your work!For feature requests, general questions or problems you face regarding this package pleaseopen an issue.Release HistoryPlease seeCHANGES.mdfor a complete release history.AuthorsLinus Groh (@linusg) \u2013mail@linusgroh.deLicenseAll the code and documentation are distributed under the MIT license. SeeLICENSEfor more information."} +{"package": "xboxapi", "pacakge-description": "DescriptionThis is a Python wrapper for the unofficialXbox APIInstallationFor now you will have to install manually, as I didn't upload the initial version to pypi (pip).Clone this repoPlace thexboxapidirectory in your projectThe only dependency isrequestslibrary.UsageThis is a basic example of how to create a client and fetch a gamers profile information from their gamertag.fromxboxapiimportClientclient=Client(api_key=)gamer=client.gamer('voidpirate')profile=gamer.get('profile')Clientclass constructor takes the following optional arguments exceptapi_key.ArgumentValueShort Descriptionapi_keystringapi token fromXbox APItimeoutinthow long until the request times out (seconds)langstringcountry language code (e.g. for German (de-DE))Clientclass public methods.MethodValueOptionalShort Descriptiongamer(gamertag=)stringxuid=gamertag to lookupcalls_remaining()n/an/aReturn headers about api rate limitsA note about the gamer method. If you already know the gamers xuid you can use that instead to avoid an additional api call when using only a gamertag.Gamerclass public methods, returned from gamer method inClient.MethodValueOptionalShort Descriptionget(method=)stringterm=API calls.send_message(message=)stringn/aSend a message to gamersend_activity(message=)stringn/aUpdate your activity feed with a messagePagination is supported in this client and all handled throughgetmethod. It works by detecting the response header for pagination, any subsequent calls to the same api endpoint will return paged data. If another api call is made to a different endpoint, the pagination token will be cleared and results will not be paged."} +{"package": "xboxcontroller", "pacakge-description": "No description available on PyPI."} +{"package": "xbox-drive-converter", "pacakge-description": "Xbox One External HDD ToolWhatConvert an Xbox One configured external hard drive to work with Windows.Convert a GPT+NTFS configured external hard drive to work with the Xbox One.RequirementsXbox One.External Hard drive greater than 256GB.Python 3.xAdministrator rights.InstructionsXbox One to Windows PCUse an Xbox One to correctly configure an external hard drive.Physically connect the now Xbox One configured external hard drive to a Windows PC.Run the script with the appropriate paramaters (see xboxoneexternal.py --help, or below).Power cycle the external hard drive.Windows PC to Xbox OneUse a Windows PC to correctly configure a GPT disk with an NTFS partition.Run the script with the appropriate paramaters (see xboxoneexternal.py --help, or below).Physically connect the now Xbox One configured external hard drive to a Windows PC.Parametersusage: xboxoneexternal.py [-h] (--toxbox | --topc) drive\n\nXbox One/Series External Drive Converter\n\npositional arguments:\n drive The target physical drive\n\noptions:\n -h, --help show this help message and exit\n --toxbox Convert the drive from Xbox to PC\n --topc Convert the drive from PC to XboxExamplesDisplay current 'Boot Signature' and 'NT Disk Signature'xboxoneexternal.py \\\\.\\PhysicalDrive5\n\nNT Disk Signature: 0x12345678\nBoot Signature: 0x99ccXbox One to Windows PCxboxoneexternal.py \\\\.\\PhysicalDrive5 --toxbox \n\nNT Disk Signature: 0x12345678\nBoot Signature: 0x99cc\nOperation: Xbox One->PC\n\nWriting new MBR ... done.Windows PC to Xbox Onexboxoneexternal.py \\\\.\\PhysicalDrive5 --topc\n\nNT Disk Signature: 0x12345678\nBoot Signature: 0x55aa\nOperation: PC->Xbox One\n\nWriting new MBR ... done.What to ExpectF:\\>dir /p\n Volume in drive F is Pluto\n Volume Serial Number is xxxx-xxxx\n\n Directory of F:\\\n\n01/06/2014 09:39 AM 2,191,065,088 520FCE1F-7BF6-48AE-AF3A-A469574766D9 (Peggle 2)\n01/06/2014 09:39 AM 4,096 520FCE1F-7BF6-48AE-AF3A-A469574766D9.xvi (Peggle 2)\n01/06/2014 09:41 AM 5,367,975,936 F57F7834-5D73-4CAA-8479-3107957CC0AB (Trials Evolution)\n01/06/2014 09:41 AM 4,096 F57F7834-5D73-4CAA-8479-3107957CC0AB.xvi (Trials Evolution)\n01/06/2014 09:40 AM 16 LastConsole (Console GUID(?))\n 5 File(s) 7,559,049,232 bytes\n 0 Dir(s) 504,384,786,432 bytes free\n\nF:\\>tree /f /a\nFolder PATH listing for volume Pluto\nVolume serial number is xxxxxxxx xxxx:xxxx\nF:.\n 520FCE1F-7BF6-48AE-AF3A-A469574766D9 (Peggle 2 - MD5:8F06F76D0BEE9681FF5F9A3E4187AB1D)\n 520FCE1F-7BF6-48AE-AF3A-A469574766D9.xvi (Peggle 2 - MD5:A0B247B79954C469B6CF635FAA7BBF6D)\n F57F7834-5D73-4CAA-8479-3107957CC0AB (Trials Evolution - MD5:ED511CDD51A8BB2FE09CC0A4538AC71F)\n F57F7834-5D73-4CAA-8479-3107957CC0AB.xvi (Trials Evolution - MD5:A66BD3E8125650C6D1FE84D73EC591FA)\n LastConsole\n\nNo subfolders existHow?The Xbox One initializes the external drive with a GPT (GUID Partition Table).The original Boot Signature of the device 0x99CC (0x1FE-0x1FF) doesn't appear to allow the drive to be seen as initialized in Windows.Swapping the two Boot Signature bytes with the traditional 0x55AA allows the NTFS partition to be seen be Windows.Original 'Protective MBR':Offset(h) 00 01 02 03 04 05 06 07 08 09 0A 0B 0C 0D 0E 0F\n\n0000000000 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000010 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000020 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000030 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000040 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000050 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000060 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000070 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000080 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000090 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000A0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000B0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000C0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000D0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000E0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000F0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000100 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000110 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000120 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000130 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000140 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000150 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000160 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000170 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000180 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000190 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001A0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001B0 00 00 00 00 00 00 00 00 12 34 56 78 00 00 00 00 .........4Vx....\n00000001C0 00 00 EE 00 00 00 01 00 00 00 AE 12 9E 3B 00 00 ..\u00ee.......\u00ae.\u017e;..\n00000001D0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001E0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001F0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 99 CC ..............\u2122\u00ccModified 'Protective MBR':Offset(h) 00 01 02 03 04 05 06 07 08 09 0A 0B 0C 0D 0E 0F\n\n0000000000 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000010 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000020 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000030 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000040 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000050 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000060 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000070 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000080 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000090 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000A0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000B0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000C0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000D0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000E0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000000F0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000100 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000110 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000120 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000130 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000140 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000150 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000160 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000170 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000180 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n0000000190 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001A0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001B0 00 00 00 00 00 00 00 00 12 34 56 78 00 00 00 00 .........4Vx....\n00000001C0 00 00 EE 00 00 00 01 00 00 00 AE 12 9E 3B 00 00 ..\u00ee.......\u00ae.\u017e;..\n00000001D0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001E0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 ................\n00000001F0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 55 AA ..............\u2122\u00ccNotesWindows will offer to initialize an Xbox One formatted disk. Don't do this unless you want to start everything again.If the Boot Signature matches 0x99CC, the Xbox One will be able to read the partitions. Windows PC will not.If the Boot Signature matches 0x55AA, a Windows PC will be able to read the partitions. Xbox One will not.Windows might complain that there is something wrong with the disk and will want to run a chkdsk. I don't reccomend doing this.Make sure you specify the right disk - don't come to me when it hits the fan."} +{"package": "x-boxes-package-Phnx", "pacakge-description": "x_boxespython package for s_boxes"} +{"package": "xboxgamertag", "pacakge-description": "xboxgamertagPython module to get data fromwww.xboxgamertag.comUsageInstallationpip install xboxgamertagSimple examplefromxboxgamertagimportgamertaguser=Gamertag('WoolDoughnut310')# My gamertag is WoolDoughnut310, by the way# Get my amount of gamerscoreprint(user.gamerscore)# If you want to see how many games I have played in totalprint(user.total_games_played)"} +{"package": "xbox-remote", "pacakge-description": "xbox.pyPython class to support reading xbox 360 wired and wireless controller input under Linux. Makes it easy to get real-time input from controller buttons, analog sticks and triggers. Built and tested on RaspberryPi running Raspbian.Requires that xboxdrv be installed first:sudo apt-get install xboxdrvTo test the driver, issue the following command and see if the controller inputs are recognizedsudo xboxdrv --detach-kernel-driverSeehttp://pingus.seul.org/~grumbel/xboxdrv/for details on xboxdrvDownload the python module and sample code with the following:wget https://raw.githubusercontent.com/FRC4564/Xbox/master/xbox.py\nwget https://raw.githubusercontent.com/FRC4564/Xbox/master/sample.pyYou can run the sample code to see how the Joystick class works.sudo python sample.pyExample class usage:import xbox\njoy = xbox.Joystick() #Initialize joystick\n\nif joy.A(): #Test state of the A button (1=pressed, 0=not pressed)\n print 'A button pressed'\nx_axis = joy.leftX() #X-axis of the left stick (values -1.0 to 1.0)\n(x,y) = joy.leftStick() #Returns tuple containing left X and Y axes (values -1.0 to 1.0)\ntrigger = joy.rightTrigger() #Right trigger position (values 0 to 1.0)\n\njoy.close() #Cleanup before exitNote:\nRun your code with sudo privileges to allow xboxdrv the necessary control over USB devices.\nIf you want, you can provide your user account with the proper access, so you needn't use sudo.First, add your user to the root group. Here's how to do this for the user \u2018pi\u2019sudo usermod -a -G root piCreate a permissions file using the nano text editor.sudo nano /etc/udev/rules.d/55-permissions-uinput.rulesEnter the following rule and save your entry.KERNEL==\"uinput\", MODE=\"0660\", GROUP=\"root\"TroubleshootingI find that xboxdrv occasionally has trouble connecting to the controller. You may see a USB device error or something similar. Issuing the following command will detach and reconnect the controller.sudo xboxdrv --detach-kernel-driverYou should now be able to move the joysticks and press buttons to see the controller state display for all inputs. Just press Ctrl-C to exit and then relaunch your python code that uses xbox.py.If your wireless controller still won't connect, press the sync button on the controller and the receiver (both devices need to be powered).UsageA good application for an XBox controller is for robot control. Check outBasic PiBotfor more details."} +{"package": "xbox-sdk", "pacakge-description": "Xbox SDK"} +{"package": "xbox-smartglass-auxiliary", "pacakge-description": "This package is deprecated and won\u2019t receive any updates.Its codebase has moved into the core library.You can still install this meta package - it will simply install the core library\nas its only dependency then.Core library:GithubPyPi"} +{"package": "xbox-smartglass-core", "pacakge-description": "Xbox-Smartglass-CoreThis library provides the core foundation for the smartglass protocol that is used\nwith the Xbox One Gaming consoleFor in-depth information, check out the documentation:https://openxbox.org/smartglass-documentationNOTE: Since 29.02.2020 the following modules are integrated into core: stump, auxiliary, rest-serverNOTE: Nano module is still offered seperatelyFeaturesPower on / off the consoleGet system info (running App/Game/Title, dashboard version)Media player control (seeing content id, content app, playback actions etc.)Stump protocol (Live-TV Streaming / IR control)Title / Auxiliary stream protocol (f.e. Fallout 4 companion app)Trigger GameDVR remotelyREST ServerMajor frameworks usedXbox WebAPIhttps://github.com/OpenXbox/xbox-webapi-pythonconstruct - Binary parsinghttps://construct.readthedocs.io/cryptography - cryptography magichttps://cryptography.io/en/stable/dpkt - pcap parsinghttps://dpkt.readthedocs.io/en/latest/FastAPI - REST APIhttps://github.com/tiangolo/fastapiurwid - TUI apphttps://github.com/urwid/urwidpydantic - JSON modelshttps://github.com/samuelcolvin/pydanticInstallVia pippip install xbox-smartglass-coreSee the end of this README for development-targeted instructions.How to useThere are several command line utilities to check out::xbox-cliSome functionality, such as GameDVR record, requires authentication\nwith your Microsoft Account to validate you have the right to trigger\nsuch action.To authenticate / get authentication tokens use::xbox-authenticateREST serverStart the server daemonUsage informationExample localhost:# Serve on '127.0.0.1:5557'$xbox-rest-server\nINFO:Startedserverprocess[927195]INFO:Waitingforapplicationstartup.\nINFO:Applicationstartupcomplete.\nINFO:Uvicornrunningonhttp://127.0.0.1:5557(PressCTRL+Ctoquit)Example local network:192.168.0.100is the IP address of your computer running the server:xbox-rest-server--host192.168.0.100-p1234INFO:Startedserverprocess[927195]INFO:Waitingforapplicationstartup.\nINFO:Applicationstartupcomplete.\nINFO:Uvicornrunningonhttp://192.168.0.100:1234(PressCTRL+Ctoquit)REST APISince the migration from Flask framework to FastAPI, there is a nice\nOpenAPI documentation available:http://{IPAddress}:{port}/docsAuthenticationIf your server runs on something else than 127.0.0.1:5557 or 127.0.0.1:8080 you\nneed to register your own OAUTH application onAzure ADand supply appropriate\nparameters to the login-endpoint of the REST server.Check out:https://github.com/OpenXbox/xbox-webapi-python/blob/master/README.mdFallout 4 relay serviceTo forward the title communication from the Xbox to your local host\nto use third-party Fallout 4 Pip boy applications or extensionsxbox-fo4-relayScreenshotsHere you can see the SmartGlass TUI (Text user interface):Development workflowReady to contribute? Here's how to set upxbox-smartglass-core-pythonfor local development.Fork thexbox-smartglass-core-pythonrepo on GitHub.Clone your fork locallygit clone git@github.com:your_name_here/xbox-smartglass-core-python.gitInstall your local copy into a virtual environment. This is how you set up your fork for local developmentpython -m venv ~/pyvenv/xbox-smartglass\nsource ~/pyvenv/xbox-smartglass/bin/activate\ncd xbox-smartglass-core-python\npip install -e .[dev]Create a branch for local development::git checkout -b name-of-your-bugfix-or-featureMake your changes.Before pushing the changes to git, please verify they actually workpytestCommit your changes and push your branch to GitHub::git commit -m \"Your detailed description of your changes.\"\ngit push origin name-of-your-bugfix-or-featureSubmit a pull request through the GitHub website.Pull Request GuidelinesBefore you submit a pull request, check that it meets these guidelines:Code includes unit-tests.Added code is properly named and documented.On major changes the README is updated.Run tests / linting locally before pushing to remote.CreditsKudos tojoeldayfor figuring out the AuxiliaryStream / TitleChannel communication first!\nYou can find the original implementation here:SmartGlass.CSharpThis package uses parts ofCookiecutterand theaudreyr/cookiecutter-pypackage project templateCHANGELOG1.3.0 (2020-11-02)Drop Python 3.6 supportDeprecate Authentication via TUIMajor rewrite (Migration from gevent -> asyncio)Rewrite of REST Server (Migration FLASK -> FastAPI)Adjust to xbox-webapi-python v2.0.8New OAUTH login flow1.2.2 (2020-04-03)Fix: Assign tokenfile path to flask_app (aka. REST server instance)1.2.1 (2020-03-04)cli: Python3.6 compatibility changeHOTFIX: Add xbox.handlers to packages in setup.py1.2.0 (2020-03-04)CLI scripts rewritten, supporting log/loglevel args now, main script is called xbox-cli nowAdd REPL / REPL server functionalityUpdates to README and REST server documentation1.1.2 (2020-02-29)Drop support for Python 3.5crypto: Fix deprecated cryptography functionstests: Speed up REST server tests (discovery, poweron)Update all dependencies1.1.1 (2020-02-29)FIX: Include static files for REST server in distributable packageREST: Remove deprecated packages from showing in /versions endpoint1.1.0 (2020-02-29)Clean up dependenciesMerge inxbox-smartglass-rest, deprecate standalone packageMerge inxbox-smartglass-stump, deprecate standalone packageMerge inxbox-smartglass-auxiliary, deprecate standalone packagetui: Fix crash when bringing up command menu, support ESC to exit1.0.12 (2018-11-14)Python 3.7 compatibility1.0.11 (2018-11-05)Add game_dvr_record to Console-classFix PCAP parserAdd last_error property to Console-class1.0.10 (2018-08-14)Safeguard around connect() functions, if userhash and xsts_token is NoneType1.0.9 (2018-08-11)Fix for Console instance poweronReset state after poweroffLittle fixes to TUISupport handling MessageFragments1.0.8 (2018-06-14)Use aenum library for backwards-compat withenum.Flagon py3.51.0.7 (2018-05-16)CoreProtocol.connect: Treat ConnectionResult.Pending as errorconstants.WindowsClientInfo: Update ClientVersion 15 -> 39Make CoreProtocol.start_channel take optional title_id / activity_id arguments1.0.1 (2018-05-03)First release on PyPI."} +{"package": "xbox-smartglass-core-asyncio", "pacakge-description": "Xbox-Smartglass-CoreThis library provides the core foundation for the smartglass protocol that is used\nwith the Xbox One Gaming consoleFor in-depth information, check out the documentation: (https://openxbox.org/smartglass-documentation)NOTE: Since 29.02.2020 the following modules are integrated into core: stump, auxiliary, rest-serverNOTE: Nano module is still offered seperatelyFeaturesPower on / off the consoleGet system info (running App/Game/Title, dashboard version)Media player control (seeing content id, content app, playback actions etc.)Stump protocol (Live-TV Streaming / IR control)Title / Auxiliary stream protocol (f.e. Fallout 4 companion app)Trigger GameDVR remotelyREST ServerFrameworks usedconstruct - Binary parsing (https://construct.readthedocs.io/)cryptography - cryptography magic (https://cryptography.io/en/stable/)dpkt - pcap parsing (https://dpkt.readthedocs.io/en/latest/)Flask - REST API (https://pypi.org/project/Flask/)InstallVia pip:pip install xbox-smartglass-coreSee the end of this README for development-targeted instructions.How to useThere are several command line utilities to check out:$ xbox-cliSome functionality, such as GameDVR record, requires authentication\nwith your Microsoft Account to validate you have the right to trigger\nsuch action.To authenticate / get authentication tokens use:$ xbox-authenticate\n\n# Alternative: Use the ncurses terminal ui, it has authentication integrated\n$ xbox-tuiREST ServerStart the REST server:$ xbox-rest-serverFor more information consultRestFAQFallout 4 relay serviceTo forward the title communication from the Xbox to your local host\nto use third-party Fallout 4 Pip boy applications or extensions:xbox-fo4-relayScreenshotsHere you can see the SmartGlass TUI (Text user interface):Development workflowReady to contribute? Here\u2019s how to set upxbox-smartglass-core-pythonfor local development.Fork thexbox-smartglass-core-pythonrepo on GitHub.Clone your fork locally:$ git clone git@github.com:your_name_here/xbox-smartglass-core-python.gitInstall your local copy into a virtual environment. This is how you set up your fork for local development:$ python -m venv ~/pyvenv/xbox-smartglass\n$ source ~/pyvenv/xbox-smartglass/bin/activate\n$ cd xbox-smartglass-core-python\n$ pip install -e .[dev]Setup auto-linting before each commit viapre-commit:$ pre-commit installCreate a branch for local development:$ git checkout -b name-of-your-bugfix-or-featureMake your changes.Before pushing the changes to git, please verify they actually work:$ pre-commit run -a\n$ pytest\n\n# For more extensive testing on several frameworks:\n$ toxCommit your changes and push your branch to GitHub:$ git commit -m \"Your detailed description of your changes.\"\n$ git push origin name-of-your-bugfix-or-featureSubmit a pull request through the GitHub website.Pull Request GuidelinesBefore you submit a pull request, check that it meets these guidelines:Code includes unit-tests.Added code is properly named and documented.On major changes the README is updated.Run tests / linting locally before pushing to remote.CreditsKudos tojoeldayfor figuring out the AuxiliaryStream / TitleChannel communication first!\nYou can find the original implementation here:SmartGlass.CSharp.This package uses parts ofCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History1.2.1 (2020-03-04)cli: Python3.6 compatibility changeHOTFIX: Add xbox.handlers to packages in setup.py1.2.0 (2020-03-04)CLI scripts rewritten, supporting log/loglevel args now, main script is called xbox-cli nowAdd REPL / REPL server functionalityUpdates to README and REST server documentation1.1.2 (2020-02-29)Drop support for Python 3.5crypto: Fix deprecated cryptography functionstests: Speed up REST server tests (discovery, poweron)Update all dependencies1.1.1 (2020-02-29)FIX: Include static files for REST server in distributable packageREST: Remove deprecated packages from showing in /versions endpoint1.1.0 (2020-02-29)Clean up dependenciesMerge inxbox-smartglass-rest, deprecate standalone packageMerge inxbox-smartglass-stump, deprecate standalone packageMerge inxbox-smartglass-auxiliary, deprecate standalone packagetui: Fix crash when bringing up command menu, support ESC to exit1.0.12 (2018-11-14)Python 3.7 compatibility1.0.11 (2018-11-05)Add game_dvr_record to Console-classFix PCAP parserAdd last_error property to Console-class1.0.10 (2018-08-14)Safeguard around connect() functions, if userhash and xsts_token is NoneType1.0.9 (2018-08-11)Fix for Console instance poweronReset state after poweroffLittle fixes to TUISupport handling MessageFragments1.0.8 (2018-06-14)Use aenum library for backwards-compat with _enum.Flag_ on py3.51.0.7 (2018-05-16)CoreProtocol.connect: Treat ConnectionResult.Pending as errorconstants.WindowsClientInfo: Update ClientVersion 15 -> 39Make CoreProtocol.start_channel take optional title_id / activity_id arguments1.0.1 (2018-05-03)First release on PyPI."} +{"package": "xbox-smartglass-nano", "pacakge-description": "Xbox-Smartglass-NanoThe gamestreaming part of the smartglass library, codename NANO.Currently supported version:NANO v1 (Xbox One family)XCloud and new XHome streaming are Nano v3, required for Xbox Series S/X.For in-depth information, check out the documentation: (https://openxbox.github.io)FeaturesStream from your local Xbox One (OG/S/X) consoleDependenciesPython >= 3.7xbox-smartglass-corepyav (https://pyav.org/docs/develop/)pysdl2 (https://pysdl2.readthedocs.io/en/latest/install.html)Installpip install xbox-smartglass-nanoHow to usexbox-nano-clientKnown issuesVideo / Audio / Input is not smooth yetChatAudio and Input Feedback not implementedDevelopment workflowReady to contribute? Here's how to set upxbox-smartglass-nano-pythonfor local development.Fork thexbox-smartglass-nano-pythonrepo on GitHub.Clone your fork locallygit clone git@github.com:your_name_here/xbox-smartglass-nano-python.gitInstall your local copy into a virtual environment. This is how you set up your fork for local developmentpython -m venv ~/pyvenv/xbox-smartglass\nsource ~/pyvenv/xbox-smartglass/bin/activate\ncd xbox-smartglass-nano-python\npip install -e .[dev]Create a branch for local development::git checkout -b name-of-your-bugfix-or-featureMake your changes.Before pushing the changes to git, please verify they actually workpytestCommit your changes and push your branch to GitHub::git commit -m \"Your detailed description of your changes.\"\ngit push origin name-of-your-bugfix-or-featureSubmit a pull request through the GitHub website.Pull Request GuidelinesBefore you submit a pull request, check that it meets these guidelines:Code includes unit-tests.Added code is properly named and documented.On major changes the README is updated.Run tests / linting locally before pushing to remote.CreditsThis package uses parts ofCookiecutterand theaudreyr/cookiecutter-pypackage project templateCHANGELOG0.10.0 (2020-12-12)Change of license -> MIT licenseDeprecated Python 3.6, Added Python 3.9Migration from gevent to asyncio (in sync with smartglass-core)Migration from marshmallow objects to pydanticFixed controller and closing issues (#15)0.9.4 (2020-02-29)Fix KeyError for debug printsPyAV 0.4.1 -> 6.1.0 compatibility0.9.3 (2018-11-14)Python 3.7 compatibility0.9.2 (2018-09-30)Fix TravisCI dependency on ffmpeg0.9.1 (2018-09-29)First release on PyPI."} +{"package": "xbox-smartglass-rest", "pacakge-description": "This module is DEPRECATED.META PACKAGEThis package is deprecated and won\u2019t receive any updates.Its codebase has moved into the core library.You can still install this meta package - it will simply install the core library\nas its only dependency then.Core library:GithubPyPi"} +{"package": "xbox-smartglass-stump", "pacakge-description": "This package is deprecated and won\u2019t receive any updates.Its codebase has moved into the core library.You can still install this meta package - it will simply install the core library\nas its only dependency then.Core library:GithubPyPi"} +{"package": "xbox-webapi", "pacakge-description": "Xbox-WebAPIXbox-WebAPI is a python library to authenticate with Xbox Live via your Microsoft Account and provides Xbox related Web-API.Authentication is supported via OAuth2.Register a new application inAzure ADName your appSelect \"Personal Microsoft accounts only\" under supported account typesAddhttp://localhost/auth/callbackas a Redirect URI of type \"Web\"Copy your Application (client) ID for later useOn the App Page, navigate to \"Certificates & secrets\"Generate a new client secret and save for later useDependenciesPython >= 3.8How to useInstallpip install xbox-webapiAuthenticationNote: You must use non child account (> 18 years old)Token save location: If tokenfile is not provided via cmdline, fallback of/tokens.jsonis used as save-locationSpecifically:Windows:C:\\\\Users\\\\\\\\AppData\\\\Local\\\\OpenXbox\\\\xboxMac OSX:/Users//Library/Application Support/xbox/tokens.jsonLinux:/home//.local/share/xboxFor more information, see:https://pypi.org/project/appdirsand module:xbox.webapi.scripts.constantsxbox-authenticate --client-id --client-secret Example: Search Xbox Live via cmdline tool# Search Xbox One Catalog\n xbox-searchlive \"Some game title\"API usageimportasyncioimportsysfromhttpximportHTTPStatusErrorfromxbox.webapi.api.clientimportXboxLiveClientfromxbox.webapi.authentication.managerimportAuthenticationManagerfromxbox.webapi.authentication.modelsimportOAuth2TokenResponsefromxbox.webapi.common.signed_sessionimportSignedSessionfromxbox.webapi.scriptsimportCLIENT_ID,CLIENT_SECRET,TOKENS_FILE\"\"\"This uses the global default client identification by OpenXboxYou can supply your own parameters here if you are permitted to createnew Microsoft OAuth Apps and know what you are doing\"\"\"client_id=CLIENT_IDclient_secret=CLIENT_SECRETtokens_file=TOKENS_FILE\"\"\"For doing authentication, see xbox/webapi/scripts/authenticate.py\"\"\"asyncdefasync_main():# Create a HTTP client sessionasyncwithSignedSession()assession:\"\"\"Initialize with global OAUTH parameters from above\"\"\"auth_mgr=AuthenticationManager(session,client_id,client_secret,\"\")\"\"\"Read in tokens that you received from the `xbox-authenticate`-script previouslySee `xbox/webapi/scripts/authenticate.py`\"\"\"try:withopen(tokens_file)asf:tokens=f.read()# Assign gathered tokensauth_mgr.oauth=OAuth2TokenResponse.model_validate_json(tokens)exceptFileNotFoundErrorase:print(f\"File{tokens_file}isn`t found or it doesn`t contain tokens! err={e}\")print(\"Authorizing via OAUTH\")url=auth_mgr.generate_authorization_url()print(f\"Auth via URL:{url}\")authorization_code=input(\"Enter authorization code> \")tokens=awaitauth_mgr.request_oauth_token(authorization_code)auth_mgr.oauth=tokens\"\"\"Refresh tokens, just in caseYou could also manually check the token lifetimes and just refresh themif they are close to expiry\"\"\"try:awaitauth_mgr.refresh_tokens()exceptHTTPStatusErrorase:print(f\"\"\"Could not refresh tokens from{tokens_file}, err={e}\\nYou might have to delete the tokens file and re-authenticateif refresh token is expired\"\"\")sys.exit(-1)# Save the refreshed/updated tokenswithopen(tokens_file,mode=\"w\")asf:f.write(auth_mgr.oauth.json())print(f\"Refreshed tokens in{tokens_file}!\")\"\"\"Construct the Xbox API client from AuthenticationManager instance\"\"\"xbl_client=XboxLiveClient(auth_mgr)\"\"\"Some example API calls\"\"\"# Get friendslistfriendslist=awaitxbl_client.people.get_friends_own()print(f\"Your friends:{friendslist}\\n\")# Get presence status (by list of XUID)presence=awaitxbl_client.presence.get_presence_batch([\"2533274794093122\",\"2533274807551369\"])print(f\"Statuses of some random players by XUID:{presence}\\n\")# Get messagesmessages=awaitxbl_client.message.get_inbox()print(f\"Your messages:{messages}\\n\")# Get profile by GTprofile=awaitxbl_client.profile.get_profile_by_gamertag(\"SomeGamertag\")print(f\"Profile under SomeGamertag gamer tag:{profile}\\n\")asyncio.run(async_main())ContributeReport bugs/suggest featuresAdd/update docsAdd additional xbox live endpointsCreditsThis package uses parts ofCookiecutterand theaudreyr/cookiecutter-pypackageproject template.\nThe authentication code is based onjoealcorn/xboxInformations on endpoints gathered from:XboxLive REST ReferenceXboxLiveTraceAnalyzer APIMapXbox Live Service APIDisclaimerXbox, Xbox One, Smartglass and Xbox Live are trademarks of Microsoft Corporation. Team OpenXbox is in no way endorsed by or affiliated with Microsoft Corporation, or any associated subsidiaries, logos or trademarks."} +{"package": "xbox-webapi-ex", "pacakge-description": "Xbox-WebAPI-EXXbox-WebAPI is a python library to authenticate with Xbox Live via your Microsoft Account and provides Xbox related Web-API.Authentication via credentials or tokens is supported, Two-Factor-Authentication ( 2FA ) is also possible.DependenciesPython >= 3.5Libraries: requests, demjson, appdirs, urwidHow to useInstall:pip install xbox-webapi-exAuthentication:# Token save location: If tokenfile is not provided via cmdline, fallback\n# of /tokens.json is used as save-location\n#\n# Specifically:\n# Windows: C:\\\\Users\\\\\\\\AppData\\\\Local\\\\OpenXbox\\\\xbox\n# Mac OSX: /Users//Library/Application Support/xbox/tokens.json\n# Linux: /home//.local/share/xbox\n#\n# For more information, see: https://pypi.org/project/appdirs and module: xbox.webapi.scripts.constants\n\nxbox-authenticate --tokens tokens.json --email no@live.com --password abc123\n\n# NOTE: If no credentials are provided via cmdline, they are requested from stdin\nxbox-authenticate --tokens tokens.json\n\n# If you have a shell compatible with ncurses, you can use the Terminal UI app\nxbox-auth-ui --tokens tokens.jsonFallback Authentication:# In case this authentication flow breaks or you do not trust the code with your credentials..\n# Open the following URL in your web-browser and authenticate\nhttps://login.live.com/oauth20_authorize.srf?display=touch&scope=service%3A%3Auser.auth.xboxlive.com%3A%3AMBI_SSL&redirect_uri=https%3A%2F%2Flogin.live.com%2Foauth20_desktop.srf&locale=en&response_type=token&client_id=0000000048093EE3\n\n# Once you finished auth and reached a blank page, copy the redirect url from your browser address-field\n# Execute the script with supplied redirect url\nxbox-auth-via-browser 'https://login.live.com/oauth20_desktop.srf?...access_token=...&refresh_token=...'Example: Search Xbox Live via cmdline tool:# Search Xbox One Catalog\nxbox-searchlive --tokens tokens.json \"Some game title\"\n\n# Search Xbox 360 Catalog\nxbox-searchlive --tokens tokens.json -l \"Some game title\"API usage:import sys\n\nfrom xbox.webapi.api.client import XboxLiveClient\nfrom xbox.webapi.authentication.manager import AuthenticationManager\nfrom xbox.webapi.common.exceptions import AuthenticationException\n\n\"\"\"\nFor doing authentication in code, see xbox/webapi/scripts/authenticate.py\nor for OAUTH via web-brower, see xbox/webapi/scripts/browserauth.py\n\"\"\"\n\ntry:\n auth_mgr = AuthenticationManager.from_file('/path_to/tokens.json')\nexcept FileNotFoundError as e:\n print(\n 'Failed to load tokens from \\'{}\\'.\\n'\n 'ERROR: {}'.format(e.filename, e.strerror)\n )\n sys.exit(-1)\n\ntry:\n auth_mgr.authenticate(do_refresh=True)\nexcept AuthenticationException as e:\n print('Authentication failed! Err: %s' % e)\n sys.exit(-1)\n\nxbl_client = XboxLiveClient(auth_mgr.userinfo.userhash, auth_mgr.xsts_token.jwt, auth_mgr.userinfo.xuid)\n\n# Some example API calls\n\n# Get friendslist\nfriendslist = xbl_client.people.get_friends_own()\n\n# Get presence status (by list of XUID)\npresence = xbl_client.presence.get_presence_batch([12344567687845, 453486346235151])\n\n# Get messages\nmessages = xbl_client.message.get_message_inbox()\n\n# Get profile by GT\nprofile = xbl_client.profile.get_profile_by_gamertag('SomeGamertag')ScreenshotsHere you can see the Auth TUI (Text user interface):Known issuesThere are a lot of missing XBL endpointsContributeReport bugs/suggest featuresAdd/update docsAdd additional xbox live endpointsCreditsThis package uses parts ofCookiecutterand theaudreyr/cookiecutter-pypackageproject template.\nThe authentication code is based onjoealcorn/xboxInformations on endpoints gathered from:XboxLive REST ReferenceXboxLiveTraceAnalyzer APIMapXbox Live Service APIDisclaimerXbox, Xbox One, Smartglass and Xbox Live are trademarks of Microsoft Corporation. Team OpenXbox is in no way endorsed by or affiliated with Microsoft Corporation, or any associated subsidiaries, logos or trademarks.History1.1.7 (2018-11-10)Fix parsing of WindowsLive auth response1.1.6 (2018-09-30)Consider (User-)privileges of (XSTS) userinfo optionalFix: Always return bool for @Property AuthenticationManager.authenticated1.1.5 (2018-08-11)Make propertyauthenticatedin AuthenticationManager check token validityBreak out of windows live auth early if cookies were cached previously1.1.4 (2018-07-01)Implement convenience functions for Partner Service Authentication1.1.3 (2018-06-16)Gracefully fail on wrong account passwordFix \u201cValueError: tui: Unexpected button pressed: Cancel\u201dprovider.lists: Correct headers, GET list worksTitlehub: Support getting title history by xuid1.1.2 (2018-05-06)Fixing appdir (aka. token save location) creation on windows1.1.1 (2018-05-03)Removed python-dateutil dependencyAdd auth-via-browser fallback scriptSmall changes1.1.0 (2018-04-17)Auth: Updated 2FA authentication to meet current windows live auth flowAuth: Redesigned 2FA authentication procedureAuth: Implemented xbox-auth-ui script (xbox.webapi.scripts.tui: urwid terminal ui)Auth: For password masking, getpass instead or raw input() is usedScripts: Default to appdirs.user_data_dir if no tokenfile provided via cmdline argument (see README)1.0.9 (2018-03-30)ExtendGameclipsprovider with title id filtering and saved clipsAddScreenshotsproviderAddTitlehubprovider1.0.8 (2018-03-29)AddedUserstatsendpointUpdated README1.0.7 (2018-03-28)Support supplying auth credentials via stdinAdded tests for all endpointsAdded tests for authenticationAddedQCSendpointAddedProfileendpointAddedAchievementsendpointAddedUsersearchendpointAddedGameclipsendpointAddedPeopleendpointAddedPresenceendpointAddedMessageendpointRemovedGamerpicsendpoint1.0.3 - 1.0.6 (2018-03-17)Metadata changes1.0.2 (2018-03-17)More metadata changes, rendering on PyPi is fine now1.0.1 (2018-03-17)Metadata changes1.0.0 (2018-03-17)First release on PyPI."} +{"package": "xbp", "pacakge-description": "[\u7ffb\u8a33\u8005\u52df\u96c6\u4e2d]BuildPy: \u65b0\u3057\u3044\u7c21\u5358\u3067\u30b7\u30f3\u30d7\u30eb\u306a\u30d3\u30eb\u30c9\u30b9\u30af\u30ea\u30d7\u30c8\u4f7f\u3044\u65b9\u3042\u306a\u305f\u306e c/cpp \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u4e2d\u306b\u30b5\u30d6\u30e2\u30b8\u30e5\u30fc\u30eb\u3068\u3057\u3066\u3053\u306e\u30ea\u30dd\u30b8\u30c8\u30ea\u3092\u30af\u30ed\u30fc\u30f3\u3057\u307e\u3059\u3002\u305d\u3057\u3066\u3001\u540c\u3058\u5834\u6240\u306b.buildpy\u3068\u3044\u3046\u540d\u524d\u3067\u3001\u30d3\u30eb\u30c9\u30b9\u30af\u30ea\u30d7\u30c8\u3092\u7528\u610f\u3057\u307e\u3059\u3002\u30d3\u30eb\u30c9\u30d3\u30eb\u30c9\u3059\u308b\u3068\u304d\u306b\u3001\u4ee5\u4e0b\u306e\u30b3\u30de\u30f3\u30c9\u3092\u5b9f\u884c\u3057\u307e\u3059\u62e1\u5f35\u5b50\u306f\u81ea\u52d5\u3067\u8ffd\u52a0\u3055\u308c\u308b\u306e\u3067\u3001\u66f8\u304f\u5fc5\u8981\u306f\u3042\u308a\u307e\u305b\u3093\u3002python3 BuildPy/__main__.py \u30b9\u30af\u30ea\u30d7\u30c8\u306e\u30b5\u30f3\u30d7\u30ebfolders {\n include = include\n source = src\n}\n\nbuild {\n .fast = true\n .use_glob = true\n .no_overwrite = copy_folder\n\n compiler {\n c = clang\n cpp = clang++\n }\n\n extensions {\n c { c }\n cpp { cc cxx cpp }\n }\n\n flags {\n opti = -O2\n c = $opti -Wno-switch -Wimplicit-fallthrough\n cpp = $c -std=c++20\n link = -Wl,--gc-sections\n }\n\n objects_folder = build\n linker = $compiler.cpp\n}Contribute\u3069\u3093\u306a\u30d7\u30eb\u30ea\u30af\u30a8\u30b9\u30c8\u3067\u3082\u9060\u616e\u306a\u304f\u6295\u7a3f\u3057\u3066\u304f\u3060\u3055\u3044\uff01"} +{"package": "xbpch", "pacakge-description": "xpbchis a simple utility for reading the proprietary binary punch format\n(bpch) outputs used in versions of GEOS-Chem earlier than v11-02. The utility\nallows a user to load this data into an xarray/dask-powered workflow without\nnecessarily pre-processing the data using GAMAP or IDL."} +{"package": "xbr", "pacakge-description": "TheXBR Protocolenables secure peer-to-peer data-trading and -service microtransactions inOpen Data Marketsbetween multiple independent entities.XBR as a protocol sits on top ofWAMP, an open messaging middleware and service mesh technology,\nand enables secure integration, trusted sharing and monetization of data and data-driven microservices\nbetween different parties and users.The XBR Protocol specification is openly developed and freely usable.The protocol is implemented insmart contractswritten inSolidityand open-source licensed (Apache 2.0).\nSmart contracts are designed to run on theEthereum blockchain.\nAll source code for the XBR smart contracts is developed and hosted in the\nproject mainGitHub repository.The XBR Protocol and reference documentation can be foundhere.Contract addressesContract addresses for local development on Ganache, using theexport XBR_HDWALLET_SEED=\"myth like bonus scare over problem client lizard pioneer submit female collect\"which result in the following contract addresses (when the deployment is the very first transactions on Ganache):export XBR_DEBUG_TOKEN_ADDR=0xCfEB869F69431e42cdB54A4F4f105C19C080A601\nexport XBR_DEBUG_NETWORK_ADDR=0xC89Ce4735882C9F0f0FE26686c53074E09B0D550\nexport XBR_DEBUG_MARKET_ADDR=0x9561C133DD8580860B6b7E504bC5Aa500f0f06a7\nexport XBR_DEBUG_CATALOG_ADDR=0xD833215cBcc3f914bD1C9ece3EE7BF8B14f841bb\nexport XBR_DEBUG_CHANNEL_ADDR=0xe982E462b094850F12AF94d21D470e21bE9D0E9CApplication developmentThe XBR smart contracts primary build artifacts are thecontract ABIs JSON files.\nThe ABI files are built during compiling thecontract sources.\nTechnically, the ABI files are all you need to interact and talk to the XBR smart contracts deployed to a blockchain\nfrom any (client side) language or run-time that supports Ethereum, such asweb3.jsorweb3.py.However, this approach (using the raw XBR ABI files directly from a \u201cgeneric\u201d Ethereum client library) can be cumbersome\nand error prone to maintain. An alternative way is using a client library with built-in XBR support.The XBR project currently maintains the followingXBR-enabled client libraries:XBR (contract ABIs package)for PythonAutobahn|Pythonfor Python (uses the XBR package)Autobahn|JavaScriptfor JavaScript, in browser and NodeJSAutobahn|Java(beta XBR support) for Java on Android and Java 8 / NettyAutobahn|C++(XBR support planned) for C++ 11+ and Boost/ASIOXBR support can be added to anyWAMP client librarywith a language run-time that has packages for Ethereum application development."} +{"package": "xbrain", "pacakge-description": "xbrainPython library of standardized neural data analysis pipelinesCreated byBaihan Lin, Columbia University"} +{"package": "xbridge", "pacakge-description": "xbridgeAn xrpc based tool for securely transmitting in a local networkCommand line UsageInstallsuggest usingpipxto install commandpipxinstallxbridge\u5e2e\u52a9xbridge[-h|--help]\u641c\u7d22\u670d\u52a1xbridge-d\u542f\u52a8\u670d\u52a1xbridge[-c]start\u662f\u672c\u5730\u914d\u7f6e\u76ee\u5f55, \u5305\u542b\u5bc6\u94a5\u548c\u672a\u7ed3\u675f\u7684sessions. \u9ed8\u8ba4\u8def\u5f84$HOME/.xbridge\u662f\u5efa\u8bae\u7684\u670d\u52a1\u540d, \u5b9e\u9645\u670d\u52a1\u540d\u4ee5\u542f\u52a8\u540e\u4e3a\u51c6\u53d1\u8d77\u8bf7\u6c42\u4e00\u822c\u547d\u4ee4\u683c\u5f0fxbridge[-c]request[[--with-files]]\u53ef\u4ee5\u662f\u670d\u52a1\u540d, \u4e5f\u53ef\u4ee5\u662f[protocal://]ip:port\u683c\u5f0f\u5b57\u7b26\u4e32\u5feb\u6377\u5b50\u547d\u4ee4\u67e5\u770b\u670d\u52a1\u652f\u6301\u7684\u6240\u6709\u8bf7\u6c42xbridgeinfo# \u7b49\u4ef7\u4e8e:xbridgerequestinfo\u53d1\u9001\u6587\u4ef6:xbridgesend# \u7b49\u4ef7\u4e8e:xbridgerequestsend_files--with-files\u83b7\u53d6\u6587\u4ef6xbridgeget# \u7b49\u4ef7\u4e8e:xbridgerequestget_files\u5217\u51fa\u6587\u4ef6xbridgels[]# \u7b49\u4ef7\u4e8e:xbridgerequestlist_files[]\u65ad\u70b9\u7ee7\u7eedxbridge[-c]resume[[--with-files]]: reply/done/get_fileConfigurationconfiguration dir is by default located in$HOME/.xbridge/.\nYou can specify the dir by-c RSA keysrsa key\u7528\u6765\u8868\u660e\u81ea\u5df1\u7684\u8eab\u4efd.prikey.pem\u79c1\u94a5pubkey.pem\u516c\u94a5\u5bc6\u94a5\u4f1a\u5728\u9996\u6b21\u4f7f\u7528\u65f6\u81ea\u52a8\u751f\u6210Permissions// permissions.json[{\"client_hash\":\"xxxx\",\"allow_connect\":true,\"always_allow_actions\":{\"send_files\":true,\"get_files\":false,\"list_files\":true,}}]Sessions\u8be5\u76ee\u5f55\u7528\u6237\u5b58\u653e\u6240\u6709\u672a\u7ed3\u675f\u7684sessions"} +{"package": "xbridge-cli", "pacakge-description": "xbridge-cliInstallpipinstallxbridge-cliNOTE: if you're looking at the repo before it's published, this won't work. Instead, you'll do this:gitclonehttps://github.com/xpring-eng/xbridge-cli.gitcdxbridge-cli# install poetrycurl-sSLhttps://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py|python-\npoetryinstall\npoetryshellInstall rippled and the xbridge witness.rippled:https://xrpl.org/install-rippled.htmlwitness:https://github.com/seelabs/xbridge_witnessGet startedexportXCHAIN_CONFIG_DIR={filepathwhereyouwantyourconfigfilesstored}exportRIPPLED_EXE={rippledexefilepath}exportWITNESSD_EXE={witnessdexefilepath}./scripts/tutorial.shTo stop the servers:xbridge-cliserverstop--allUse Commandsxbridge-cli--helpEach subcommand also has a--helpflag, to tell you what fields you'll need."} +{"package": "xbrief", "pacakge-description": "No description available on PyPI."} +{"package": "xbrl", "pacakge-description": "Features(P0) Parse XBRL instance documents(P0) Parse XBRL linkbases(P2) Calculation linkbase(P2) Definition linkbase(P1) Label linkbase(P0) Presentation linkbase(P0) Parse XBRL schemasClassesXBRL InstanceDocumentclassXBRL(list):\"\"\"An XBRL instance document\"\"\"...FactclassFact(dict):\"\"\"An XBRL fact: concept, context, value\"\"\"...ConceptclassConcept(dict):\"\"\"An XBRL concept\"\"\"...ContextclassContext(dict):\"\"\"An XBRL context: company, segment, period\"\"\"...classPeriod(dict):\"\"\"An XBRL period: start date, end date\"\"\"...ValueclassValue(dict):\"\"\"An XBRL value: amount, unit\"\"\"...classUnit(dict):\"\"\"An XBRL unit\"\"\"...XBRL LinkbaseLinkbaseclassLinkbase(list):\"\"\"An XBRL linkbase\"\"\"...classCalculationLinkbase(Linkbase):\"\"\"An XBRL calculation linkbase\"\"\"...classDefinitionLinkbase(Linkbase):\"\"\"An XBRL definition linkbase\"\"\"...classLabelLinkbase(Linkbase):\"\"\"An XBRL label linkbase\"\"\"...classPresentationLinkbase(Linkbase):\"\"\"An XBRL Presentation linkbase\"\"\"...LinkclassLink(dict):\"\"\"An XBRL link\"\"\"...classCalculationLink(Link):\"\"\"An XBRL calculation link\"\"\"...classDefinitionLink(Link):\"\"\"An XBRL definition link\"\"\"...classLabelLink(Link):\"\"\"An XBRL label link\"\"\"...classPresentationLink(Link):\"\"\"An XBRL Presentation link\"\"\"...UsageXBRL Instancebrka=XBRL(file='brka-20151231.xml')brka=XBRL('BRKA',2015)brka=XBRL('BRKA',2015,'FY')brka=XBRL(file='brka-20160331.xml')brka=XBRL('BRKA',2016,'Q1')facts=list(brka)contexts=list(brka.contexts)units=list(brka.units)XBRL Linkbasebrka_cal=CalculationLinkbase(file='brka-20151231_cal.xml')brka_cal=CalculationLinkbase('BRKA',2015)brka_cal=CalculationLinkbase('BRKA',2015,'FY')brka_def=DefinitionLinkbase(file='brka-20151231_def.xml')brka_def=DefinitionLinkbase('BRKA',2015)brka_def=DefinitionLinkbase('BRKA',2015,'FY')brka_lab=LabelLinkbase(file='brka-20151231_lab.xml')brka_lab=LabelLinkbase('BRKA',2015)brka_lab=LabelLinkbase('BRKA',2015,'FY')brka_pre=PresentationLinkbase(file='brka-20151231_pre.xml')brka_pre=PresentationLinkbase('BRKA',2015)brka_pre=PresentationLinkbase('BRKA',2015,'FY')"} +{"package": "xbrl2rdf", "pacakge-description": "xbrl2rdf> #### DISCLAIMER - BETA PHASE\n> This XBRL to RDF parser is currently in a beta phase.\n>Python package to convert XBRL instance and taxonomy files to RDFFree software: GNU GENERAL PUBLIC LICENSE, v2Documentation:https://xbrl2rdf.readthedocs.io.FeaturesHere is what the package does:\n- convert XBRL instance file and related taxonomy files (schemas and linkbases) to RDF and RDF-starQuick overviewTo install the packagepip install xbrl2rdfHow to runTo parse an XBRL-instance file run in the root of the projectpython -m xbrl2rdf.xbrl2rdfCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-02-05)First release on PyPI."} +{"package": "xbrl2-server-api", "pacakge-description": "No description available on PyPI."} +{"package": "xbrl-config-client", "pacakge-description": "No description available on PyPI."} +{"package": "xbrl-dart", "pacakge-description": "This is made for some specific environment.\nThis contains \u2026"} +{"package": "xbrl-explorer", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xbrl-filings-api", "pacakge-description": "XBRL Filings APIPython API for filings.xbrl.org XBRL report repository.NoteThis library is still under development.The library is not connected to XBRL International.Table of ContentsInstallationLicenseInstallationpip install xbrl-filings-apiLicensexbrl-filings-apiis distributed under the terms of theMITlicense."} +{"package": "xbrl-orchestrator-api", "pacakge-description": "No description available on PyPI."} +{"package": "xbrl_parser", "pacakge-description": "to parse xbrl docs from the sec"} +{"package": "xbrl-reports-indexes", "pacakge-description": "XBRL Reports Indexes (xri)xricreates and updates a database for indexes of ESEF filings and SEC XBRL filings and filers (only filings metadata NOT filings contents). SEC XBRL filings index is based on data extracted fromSEC Monthly RSS Feedsfor XBRL filings, ESEF XBRL filings index is based on data extracted fromfilings.xbrl.org.This package is useful for easily collecting and organizing up to date information about XBRL filings available on SEC, including latest filings (updated every 10 minutes during working hours), and the same for ESEF filings. Data can be stored insqlite,postgresormysqldatabases (sqliterecommended).A downloadable sqlite example database is available on google drivehere, contains filings data until 2022-09-14.Installationpipinstallxbrl-reports-indexFrom sourceClonerepo, then build and install locally or install editable:# editablepipinstall-e.# buildpython-mbuild\npipinstalldist/*.whlUsageCommand lineFor options and help:$ xri-db-tasks -h# initialize sqlite database update data (requires internet connection)$xri-db-task--initialize-database--update-sec--update-secInitializing the database and loading data may take a long time for SEC information, but subsequent updates should take less than a minute. when usingpostgresormysql, database must be created on the server first and connection information should be provided as follows:$xri-db-taskdatabase_name,product,user,password,host,port,timeout--initialize-database--update-sec--update-secproduct: sqlite (default), postgres or mysql.To search filings:$xri-db-tasks--search-filingssec--form-type10-q--added-date-from2022-08-10--added-date-to2022-08-10--sec-industry-tree70--limit-result1000--output-filesearch.rss2022-09-1403:48:32,220[rss-db.initialize-db]Verified/Initialized2022-09-1403:48:33,269[rss-db.info]Createdsearch.rssfor186filings.The above command returns SEC filings for forms 10-K and 10-Q filed between 2022-08-10 and 2022-08-12 inclusive, result is saved as an rss file similar to SEC rss feed, this file can be used byarellefor further processing.Python scriptThis package usesSQLAlchemyas anORM. Usage is as follows:fromxbrlreportsindexes.core.index_dbimportXbrlIndexDBfromsqlalchemy.ormimportSession# create a db objectdb=XbrlIndexDB('scratches/xdb_test.db')# create a query objectqry=db.search_filings(filing_system='sec',publication_date_from='2022-08-10',publication_date_to='2022-08-12',form_type='10-q',industry_code_tree='70',limit=1000,)# execute query and print out countwithSession(db.engine)assession:result=qry.with_session(session)print(result.count())Result:>>> 186Or we can go directly to the industry table:# import SEC modelfromxbrlreportsindexes.modelimportSECsession=Session(db.engine)# filter for industry 70industry=session.query(SEC.SecIndustry).filter(SEC.SecIndustry.industry_classification=='SEC',SEC.SecIndustry.industry_code==70,).first()print(industry.industry_description)industry name>>> 'Services'# get filings of that industryfilings=industry.all_industry_tree_filings(session)# filter filingsfilings.filter(SEC.SecFiling.pub_date>='2022-08-10',SEC.SecFiling.pub_date<'2022-08-13',SEC.SecFiling.form_type.like('%10-Q%'),).count()result of count>>> 186All other tools fromSQLAlchemycan be used to query and analyze the data, for example, here is the to 5 forms by count of filings for August 2022:fromsqlalchemyimportfunc,descform_type=SEC.SecFiling.form_typefilings_august_qry=session.query(form_type,func.count(form_type).label('count_forms')).group_by(form_type).order_by(desc('count_forms')).limit(5)forfinfilings_august_qry:print(f[0],'->',f'{f[1]:,}','forms')8-K -> 8,193 forms\n10-Q -> 5,343 forms\n8-K/A -> 198 forms\n485BPOS -> 173 forms\n10-K -> 167 formsData updateA cron job can be setup to collect information about new filing from SEC site every 10 minutes during working hours as follows:*/106-22**1-5xri-db-task--update-sec# note timezone differencesLicenseApache-2.0"} +{"package": "xbrl-search-client", "pacakge-description": "No description available on PyPI."} +{"package": "xbrl-us", "pacakge-description": "AboutThe XBRL US Python Wrapper is a powerful tool for interacting with the XBRL US API,\nproviding seamless integration of XBRL data into Python applications.\nThis wrapper simplifies the process of retrieving and analyzing financial data in XBRL format,\nenabling users to access a wide range of financial information for companies registered with the U.S.\nSecurities and Exchange Commission (SEC).It\u2019s important to note that while the XBRL US Python Wrapper is free and distributed under the permissive MIT license,\nthe usage of the underlying XBRL US API is subject to the policies and terms defined by XBRL US.\nThese policies govern the access, usage, and restrictions imposed on the API data and services.\nUsers of the XBRL US Python Wrapper should review and comply with the XBRL US policies to ensure appropriate\nusage of the API and adherence to any applicable licensing terms.ImportantAny and all use of the XBRL APIs to return\ndata from the XBRL US Database of Public Filings is in explicit consent and\nagreement with theXBRL API Terms of Agreement.NoteIf you are utilizing the XBRL US Python Wrapper for research purposes, we kindly request that you cite the following paper:[FILL: Insert Paper Title][FILL: Authors][FILL: Publication Details]Tutorial \u270f\ufe0f\ud83d\udcd6\ud83d\udcdaThis tutorial will guide you through using the XBRL-US Python library to interact with the XBRL API.\nThe XBRL-US library provides a convenient way to query and retrieve financial data from the XBRL API using Python.1. PrerequisitesBefore you begin, ensure you have the following:Python installed on your system.\nThe XBRL-US library supports Python 3.8 and above.XBRL-US API credentials.\nYou can obtain your credentials by registering for a\nfree XBRL-US account athttps://xbrl.us/home/use/xbrl-api/.XBRL-US OAuth2 Access.\nYou can obtain your client ID and client secret by registering for a\nfilling the request form athttps://xbrl.us/home/use/xbrl-api/access-token/.You can install this package using pip:pipinstallxbrl-usIf you are using Jupyter Notebook, you can install the package using the following command:!pipinstallxbrl-usCaution!The XBRL US Python Wrapper is currently in beta and is subject to change.\nWe welcome your feedback and suggestions for improvement.\nPlease submit any issues or feature requests to\ntheGitHub repository.DocumentationFor detailed information about the XBRL-US Python\nlibrary, you can refer to the documentation athttps://python-xbrl-us.readthedocs.io/en/latest/.Official DocumentationFor more information about the XBRL API and its endpoints, refer to the original API documentation athttps://xbrlus.github.io/xbrl-api.2. Choose Your Preferred ApproachThere are two distinct ways to use the XBRL-US Python package:Code-Based Approach: Import the XBRL-US Python package directly into your Python\nenvironment for in-depth, custom analysis (seeCode-Based Approach)Browser Interface: For a no-code experience, navigate to theBrowser Interface.\nThis interface allows for easy exploration and analysis of XBRL data directly in your web\nbrowser.2.1. Code-Based ApproachImport the XBRL LibraryTo start using the XBRL-US library,\nyou need to import it into your Python script:fromxbrl_usimportXBRLCreate an Instance of XBRL ClassNext, you need to create an instance of theXBRLclass,\nproviding your authentication credentials\n(client ID, client secret, username, and password) as parameters:xbrl=XBRL(client_id='Your client id',client_secret='Your client secret',username='Your username',password='Your password')Make sure to replaceYour client id,Your client secret,Your username, andYour passwordwith your actual credentials.Query the XBRL APIThe XBRL-US library provides a query method to search\nfor data from the XBRL API. You can specify various\nparameters and fields to filter and retrieve the\ndesired data.Here\u2019s an example of using the query method to search\nfor specific financial facts:response=xbrl.query(method='fact search',parameters={\"concept.local-name\":['OperatingIncomeLoss','GrossProfit','OperatingExpenses','OtherOperatingIncomeExpenseNet'],\"period.fiscal-year\":[2009,2010],\"report.sic-code\":range(2800,2899)},fields=['report.accession','period.fiscal-year','period.end','period.fiscal-period','fact.ultimus','unit','concept.local-name','fact.value','fact.id','entity.id','entity.cik','entity.name','report.sic-code',],limit=100,as_dataframe=True)In this example, we are searching for facts related\nto specific concepts, fiscal years, and SIC codes.\nWe are also specifying the fields we want to retrieve\nin the response. Thelimitparameter restricts the\nnumber of facts returned to 100, andas_dataframe=Trueensures the response is returned as aPandas DataFrame.Alternatively, you can use theParametersandFieldsclasses provided by the library to make the query more\nreadable, less prone to errors, and easier to maintain:fromxbrl_us.utilsimportParameters,Fieldsresponse=xbrl.query(method='fact search',parameters=Parameters(concept_local_name=['OperatingIncomeLoss','GrossProfit','OperatingExpenses','OtherOperatingIncomeExpenseNet'],period_fiscal_year=[2009,2010],report_sic_code=range(2800,2899)),fields=[Fields.REPORT_ACCESSION,Fields.PERIOD_FISCAL_YEAR,Fields.PERIOD_END,Fields.PERIOD_FISCAL_PERIOD,Fields.FACT_ULTIMUS,Fields.UNIT,Fields.CONCEPT_LOCAL_NAME,Fields.FACT_VALUE,Fields.FACT_ID,Fields.ENTITY_ID,Fields.ENTITY_CIK,Fields.ENTITY_NAME,Fields.REPORT_SIC_CODE,],limit=100,as_dataframe=True)This alternative approach also allows you to\ntake advantage of the autocomplete feature of your IDE to\neasily find the parameters and fields.Perform Additional QueriesYou can use the same query method to call other API\nendpoints by changing the method parameter and\nproviding the relevant parameters and fields.Here\u2019s an example of using the query method to\nsearch for a specific fact by its ID:response=xbrl.query(method='fact id',parameters={'fact.id':123},fields=['report.accession','period.fiscal-year','period.end','period.fiscal-period','fact.ultimus','unit','concept.local-name','fact.value','fact.id','entity.id','entity.cik','entity.name','report.sic-code',],as_dataframe=False)Congratulations! You have learned how to use the XBRL-US Python library to interact with the XBRL API.\nIn this example you will receive the data in json format as theas_dataframeparameter is set toFalse.2.2 Browser Interface \ud83d\udda5\ufe0fThis feature is designed to make our package even more user-friendly, allowing users to interact and work with XBRL data\ndirectly through a graphical interface, in addition to the existing code-based methods.The browser interface streamlines data visualization, simplifies navigation, and enhances user interactions.\nWith this intuitive, user-friendly interface, you can easily explore, interpret, and analyze XBRL data in real-time,\nright from your web browser.Key Features:Create Real-time queries right in your browserIntuitive navigation and search featuresFiltering and sorting optionsSeamless integration with the existing XBRL-US Python APIGetting started is as simple as ever.\nUpdate your XBRL-US Python package to the latest version and launch the new Browser Interface from the package menu.Getting Started with the Browser InterfaceGetting started is as simple as ever.\nFirst, ensure you have the latest version ofxbrl-usinstalled by running the following code:pipinstallxbrl-us--upgradeor if you are on a Jupyter Notebook:!pipinstallxbrl-us--upgradeNext, launch the new Browser Interface from the package menu:python-mxbrl_usor if you are on a Jupyter Notebook:!python-mxbrl_usThat is it!\nYou should now see the new Browser Interface open in your default web browser.Happy data exploring!NotePlease note, while we have tested the interface extensively, this is its initial release.\nWe encourage users to provide feedback to help us further improve the tool. We value your input!\nYou can also find tutorials, example codes, and more resources to help you get started.DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:WindowssetPYTEST_ADDOPTS=--cov-appendtoxOtherPYTEST_ADDOPTS=--cov-appendtoxChangelog0.0.41 (2023-08-04)Bug fixes0.0.40 (2023-08-03)Improved Browser Interfaceimproved error handling for requestsBug fixes0.0.32 (2023-07-17)Improved Browser InterfaceAddeduniquekeyword toquerymethodBug fixes0.0.31 (2023-07-14)fixed dependency issuesBug fixes0.0.3 (2023-07-14)Backward compatibility with Python 3.8 and 3.9Bug fixes0.0.2 (2023-07-12)Bug fixesEnhanced error handlingImprovedmethodsattributesAdded the ability to print the query stringImplemented a feature to handle queries with large limitsNEW: Introduced a web interface for the API, making it even easier to use0.0.1 (2023-07-09)First release on PyPI."} +{"package": "xbrowser-automation", "pacakge-description": "xbrowser_automationxbrowser guiInstallation & setupInstall PythonAs this is a Python package, please install a Python version first. We recommend to use our ownBENTELER Anaconda Installer, see some instructions in ourPython wikiInstallxbrowser_automationAfterwards you can install the package by opening thePython Command PromptorPython PowerShell Promptand typecondainstallxbrowser_automationUsageimportxbrowser_automationDevelopmentTo develop the package first install its dependencies. Open thePython Command PromptorPython PowerShell Promptand typecondainstall--filerequirements.txt--filerequirements_test.txt--filedocs/requirements_docs.txtTo make the package usable in you Python installation install it in--editablemode:pipinstall--no-deps--editable."} +{"package": "xbrr", "pacakge-description": "XBRR: eXtensible Business Report ReaderFeatures:API: Download the documents from official publication site.Reader: Extract contents from XBRL.Supported documents:JapanAPI:EDINETReader: Mainly supports annual reports disclosed on EDINET.AmericaAPI: Comming soonReader: Comming soonWe are welcome the contribution to support other countries API & Documents!Installpip install xbrrHow to use(Examples are Japanese EDINET API and annual report).1. APIDownload the documents fromEDINET.1.1 Get document list of specific dayimportxbrrdocuments=xbrr.edinet.api.documents.get(\"2019-01-31\")print(f\"Number of documents is{len(documents.list)}\")print(f\"Title of first document is{documents.list[0].title}\")1.2 Get document by document idfrompathlibimportPathimportxbrrxbrl_path=xbrr.edinet.api.document.get_xbrl(\"S100FGR9\",save_dir=Path.cwd())pdf_path=xbrr.edinet.api.document.get_pdf(\"S100FGR9\",save_dir=Path.cwd())Each XBRL includes taxonomy information. If you want to deal with these files, execute the following.xbrl_dir=xbrr.edinet.api.document.get_xbrl(\"S100FGR9\",save_dir=Path.cwd(),expand_level=\"dir\")2. ReaderExtract contents from XBRL.xbrl=xbrr.edinet.reader.read(\"path/to/xbrl/file\")content=xbrl.extract(xbrr.edinet.aspects.Business).policy_environment_issue_etc.valueExtract financial statements.xbrl_dir=xbrr.edinet.reader.read(\"path/to/xbrl/dir\")xbrl_dir.extract(xbrr.edinet.aspects.Finance).bs.to_csv(\"bs.csv\",index=False)Please refer to the supported aspects from the following links.EDINET"} +{"package": "xbrz.py", "pacakge-description": "xbrz.pyxbrz.py is a simple ctypes-based binding library forxBRZ, a high-quality pixel-art image scaling algorithm.InstallationWheels are available for many platforms. If there isn't one for your platform, make sure you have a C++ compiler handy.pip install xbrz.pyUsageimportxbrz# pixels is a list of 32 bit ints representing RGBA colors.# It is 32 * 24 long.pixels=...scaled_pixels=xbrz.scale(pixels,6,32,24,xbrz.ColorFormat.RGBA)# scaled_pixels is a 32 * 24 * 6 ** 2 long list of 32 bit ints representing the scaled image.Wand / Pillow supportYou can pass a Wand image toxbrz.scale_wand(img, factor)or a Pillow image toxbrz.scale_pillow(img, factor).\nNeither libraries are required to use xbrz.py, however they can be installed via:pip install xbrz.py[wand]\n# or\npip install xbrz.py[pillow]xbrz.py as an executable modulePassing raw RGBA pixels topython3 -m xbrz via stdin will output scaled raw RGBA pixels to stdout.LicenseAGPLv3, see LICENSE.md. The original xBRZ code is GPLv3 licensed.lib/ is based on code provided by Zenju under the GPLv3 license. See lib/License.txt for details.\nSome changes were made:Added someextern \"C\"declarations to the functions I intended to call from python.Removed some namespace use to avoid being mangled.Replaced a C++ template with a simple function that takes two arguments.Converted the library to use RGBA instead of ARGB.xbrz.py is based on lib/ and is released under the AGPLv3 license, see LICENSE.md for details."} +{"package": "xbsryzmvon", "pacakge-description": "Xbsryzmvon=================This API SDK was automatically generated by [APIMATIC Code Generator](https://apimatic.io/).This SDK uses the Requests library and will work for Python ```2 >=2.7.9``` and Python ```3 >=3.4```.How to configure:=================The generated code might need to be configured with your API credentials.To do that, open the file \"Configuration.py\" and edit its contents.How to resolve dependencies:===========================The generated code uses Python packages named requests, jsonpickle and dateutil.You can resolve these dependencies using pip ( https://pip.pypa.io/en/stable/ ).1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r requirements.txt```Note: You will need internet access for this step.How to test:=============You can test the generated SDK and the server with automatically generated testcases. unittest is used as the testing framework and nose is used as the testrunner. You can run the tests as follows:1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r test-requirements.txt```3. Invoke ```nosetests```How to use:===========After having resolved the dependencies, you can easily use the SDK following these steps.1. Create a \"xbsryzmvon_test.py\" file in the root directory.2. Use any controller as follows:```pythonfrom __future__ import print_functionfrom xbsryzmvon.xbsryzmvon_client import XbsryzmvonClientapi_client = XbsryzmvonClient()controller = api_client.clientresponse = controller.get_basic_auth_test()print(response)```"} +{"package": "xbstrap", "pacakge-description": "xbstrap: Build system for OS distributionsxbstrap is a build system designed to build \"distributions\" consisting of multiple (usually many) packages.\nIt does not replace neithermakeandninjanorautoconf,automake,mesonorcmakeand similar utilities.\nInstead, xbstrap is intended to invoke those build systems in the correct order, while respecting inter-package dependencies.Official Discord server:https://discord.gg/7WB6Ur3Installationxbstrap is available from PyPI. To install it using pip, use:pip3 install xbstrapBasic usageSee theboostrap-managarm repositoryfor an examplebootstrap.ymlfile.Installing all tools (that run on the build system) is done using:xbstrap install-tool --allInstalling all packages to a sysroot (of the host system):xbstrap install --allIt is often useful to rebuild specific packages. Rebuilding packagefoobarcan be done by:xbstrap install --rebuild foobarIf theconfigurescript shall be run again, use instead:xbstrap install --reconfigure foobarLocal developmentWhen developingxbstrap, you must install your local copy instead of the one provided by thepiprepositories. To do this, run:pip install --user -e .Development with DockerFor containerized builds, mostxbstrapcommands will run in two stages: once on the host, then again on the container to\nactually execute the build steps. Therefore, installingxbstraplocally (as shown above) is not sufficient in this case.In addition, you must change yourDockerfileso that instead of grabbingxbstrapfrom thepiprepositories, it installs from the host:Add the following lines (replace/local-xbstrapat your convenience):ADDxbstrap/local-xbstrapRUNpip3install-e/local-xbstrapCopy or symlink your localxbstrapinto the same folder that contains theDockerfile, so that it can be accessed by the previous step.Rebuild the docker container as usual.Enabling the pre-commit hook for linting (optional)To avoid running into the CI complaining about formatting, linting can be done in a pre-commit hook. To enable this, run:git config core.hooksPath .githooks"} +{"package": "xbTools", "pacakge-description": "About the xbeach-toolboxWelcome to the xbeach-toolbox!This package contains a set of general tools to setup and postprocess 1D and 2D XBeach models.The tools have been written in Python, please see the sections below for further instructions.Information about this package and its contents can also be viewed on:https://xbeach-toolbox.readthedocs.io/en/latest/Information about the use of the XBeach model itself can be found on:https://xbeach.readthedocs.io/en/latest/.Getting started / installationPip packages are hosted on the pypi server and can be installed as usual.Release notesReleasenotes0.0.1first release!0.0.2future contentUsage / examplesBasic examples have been added to the examples folder in the project.For both a 1D and 2D simulation these python notebooks show how the tools can be used to setup a model.Contributingfork, issue, branch, commit, review, approve, mergeContactMenno de Ridder -menno.deridder@deltares.nlCas van Bemmelen -cas.van.bemmelen@witteveenbos.com"} +{"package": "xbundle", "pacakge-description": "xbundleconverts back and forth between OLX and \u201cxbundle\u201d style XML\nformats. The xbundle format is a single XML file.The OLX format is defined inthis\ndocumentation.Installationpython setup.py installThis will installxbundleand thexbundle_convertcommand-line\ntool.Using xbundle in your codeTo convert from xbundle to OLXfromxbundleimportXBundlebundle=XBundle()# get input_path and output_path from user inputbundle.load(input_path)bundle.export_to_directory(output_path)To convert from OLX to xbundlefromxbundleimportXBundlebundle=XBundle()# get input_path and output_path from user inputbundle.import_from_directory(input_path)bundle.save(output_path)Using the command-line toolxbundle_convert convert /path/to/course /path/to/output.xmlorxbundle_convert convert /path/to/output.xml /path/to/courseRun testsxbundle_convert test"} +{"package": "xbus", "pacakge-description": "No description available on PyPI."} +{"package": "xbus.broker", "pacakge-description": "xbus.brokerxbus.broker is the central piece of the Xbus project.Related projects:xbus.file_emitter xbus.monitor xbus_monitor_js xbus.clearinghouse XbusXbus is an Enterprise service bus. As such it aims to help IT departments\nachieve a better application infrastructure layout by providing a way to\nurbanize the IT systems.The goals of urbanization are:high coherencelow couplingMore information about Xbus:Documentation: Website: InstallingGet requirements: python3-dev, 0mq, python3 and redis:$ sudo apt-get install libzmq3-dev python3 python3-dev redis-server virtualenvwrapperSet up a virtualenv with Python 3:$ mkvirtualenv -p /usr/bin/python3 xbusInstall the xbus.broker package:$ pip install xbus.brokerConfiguringCreate configuration files (eg for the 0.1.3 version):$ wget https://bitbucket.org/xcg/xbus.broker/raw/0.1.3/etc/config.ini-example -O config.ini\n$ wget https://bitbucket.org/xcg/xbus.broker/raw/0.1.3/etc/logging.ini-example -O logging.iniEdit the files following comments written inside.\nNote: Ensure the path to the logging file is an absolute path.Initialize the databaseRun the \u201csetup_xbusbroker\u201d program:$ setup_xbusbroker -c config.iniMigrating an existing databaseUse the \u201cmigrate_xbus_broker\u201d project. Instructions are on\n.RunningRun the \u201cstart_xbusbroker\u201d program:$ start_xbusbroker -c config.iniContributorsSorted by commit date:Florent Aide, J\u00e9r\u00e9mie Gavrel, Houz\u00e9fa Abbasbhay, Alexandre Brun, Vincent Hatakeyama, Patrice Journoud, Changelog0.2.0 (2016-06-27)Better message state tracking.Undelivered messages are re-sent when the recipient comes back.More logging.Documentation improvements.Upgrade step: Migrate the DB to version 1 using\n.0.1.5 (2015-05-25)Update requirements.0.1.4 (2015-05-18)Update the setup script wrt permission changes.Define required package versions in setup.py and document why some are\nfrozen.0.1.3 (2015-05-11)Improve the README and configuration file paths.0.1.2 Initial release (2015-05-11)Initial implementation of the Xbus broker in Python 3."} +{"package": "xbus.file_emitter", "pacakge-description": "xbus.file_emitterGeneric Xbus file emitter.XbusXbus is an Enterprise service bus. As such it aims to help IT departments\nachieve a better application infrastructure layout by providing a way to\nurbanize the IT systems.The goals of urbanization are:high coherencelow couplingMore information about Xbus:Documentation: Website: Presentation: Requirementspyjon.descriptors (directly from pypi)ContributorsSorted by commit date:J\u00e9r\u00e9mie Gavrel, Houz\u00e9fa Abbasbhay, Florent Aide, Changelog0.1.2 (2015-05-12)Better release setup.0.1.1 Initial release (2015-05-12)Initial implementation of the Xbus file emitter."} +{"package": "xbus.monitor", "pacakge-description": "xbus.monitorThis package provides tools to monitor and administer Xbus .The monitor serves a REST API; it also includes a backbone.js client app:xbus_monitor_js : Single-page\nJavaScript Backbone application that communicates with xbus.monitor via its\nREST API.XbusXbus is an Enterprise service bus. As such it aims to help IT departments\nachieve a better application infrastructure layout by providing a way to\nurbanize the IT systems.The goals of urbanization are:high coherencelow couplingMore information about Xbus:Documentation: Website: Presentation: InstallingSet up a virtualenv:$ mkvirtualenv -p /usr/bin/python3 xbusInstall the xbus.monitor package:$ pip install xbus.monitorConfiguringFollow the xbus.broker README file to set it up.Xbus monitor settings are within the etc/production-example.ini file; grab it\nfrom bitbucket (eg for the 0.1.2 version):$ wget https://bitbucket.org/xcg/xbus.monitor/raw/0.1.2/etc/production-example.ini -O monitor.iniEdit the file following comments written inside.Localization:Edit the \u201cpyramid.default_locale_name\u201d variable. Note: Only \u201cen_US\u201d and\n\u201cfr_FR\u201d are supported for now.RunningRun as a regular Pyramid program:$ pserve monitor.iniRun testsnosetestsDevelopmentWhen running the monitor for development purposes, it is recommended to deactivate thecookie.secureoption in the configuration file:cookie.secure = falseGenerate the translation templatepip install Babel lingua\npython setup.py extract_messagesOther translation tasksSee .python setup.py [init_catalog -l en_US] [update_catalog] [compile_catalog]Thanksxbus.monitor uses the following external projects; thanks a lot to their respective authors:pyramid pyramid_httpauth ContributorsSorted by commit date:J\u00e9r\u00e9mie Gavrel, Florent Aide, Houz\u00e9fa Abbasbhay, Alexandre Brun, Brendan Masson, Changelog0.2.1 (2016-07-04)Fix inclusion of the monitor_js client-side app into the package.0.2.0 (2016-06-27)Add new consumer event type settings (related to optional data lookup\u201d /\nclearing features).Resolve aiozmq endpoints beforehand.Safer consumer getter.Log Xbus requests by default in the example configuration file.Simplified deployment; this application now includes a default client.Reworked the login system to apply on the whole client app instead of\ntriggering on specific JS requests.Adapt to message tracking changes done in xbus.broker.0.1.4 (2015-05-25)Event types: Allow setting the \u201cimmediate reply\u201d flag.Update requirements.0.1.3 (2015-05-18)Define required package versions in setup.py and document why some are\nfrozen.0.1.2 Initial release (2015-05-12)Initial implementation of the Xbus monitor."} +{"package": "xbutil-gui", "pacakge-description": "xbutil-guiA Python Tkinter GUI for Xilinx Vitis xbutil programInstallationOSxbutil-gui has been tested on CentOS 7.8 and Ubuntu 16.04.Xilinx XRTXilinx XRTversion 2.8.0 or newer is required\non every host with Xilinx Alveo Accelerator Cards.SSH authentication keyxubtil-gui supports scaning hosts within a cluster. All hosts in the cluster\nneed to have SSH authentication key set up so you can run commands on remote\nhosts with your username and without password. Follow instructions\non theSSH Login without passwordpage to set up SSH authentication key.PythonThis program requires Python 3.6 or newer to run.Ubuntu 16.04The default Python on Ubuntu 16.04 is version 3.5. Run the commands below to\ninstall Python 3.6sudo add-apt-repository ppa:deadsnakes/ppa\nsudo apt-get update\nsudo apt-get install python3.6 python3.6-venv python3.6-tkRedhat/CentOS 7.8The default Python on CentOS 7.8 is already version 3.6. You only need to\ninstall Python Tkinter.sudo yum install python36-tkinterCreate and activate a Python3 virtual environmentpython3.6 -m venv venv\n. venv/bin/activateInstall xbutil GUI as a regular userpip install xbutil_guiInstall xbutil GUI as a contributorgit clone https://github.com/jimw567/xbutil-gui.git\ncd xbutil-gui\npip install -r requirements.txt`\npython setup.py developRun xbutil-guixbutil_guiSnapshotsMain window showing all hosts/devices/compute units in a clustertop windowPower/temperature plotVccint/Iccint plotPublish xbutil_gui to PyPI./scripts/publish-pypi.shThe following modules may need to be upgraded or installed:pip install --upgrade pip\npip install twine"} +{"package": "xbutils", "pacakge-description": "Some Python utility classes"} +{"package": "xbwt", "pacakge-description": "XBWTThis library allows to compute the xbwt transform. The following link refers to the article in which it was defined:https://www.semanticscholar.org/paper/Compressing-and-indexing-labeled-trees%2C-with-Ferragina-Luccio/8c4f49913e8db00dc09c31af480bf4dc37a853d9.Documentationhttps://htmlpreview.github.io/?https://github.com/dolce95/xbw-transform/blob/main/doc/xbwt.htmlInstallationpipinstallxbwtUsage from Python as a moduleIt is possible to usexbwtdirectly in a python script by import it.importxbwtxbwt_obj=xbwt.readAndImportTree(r'C:\\Users\\dolce\\OneDrive\\Desktop\\tree.txt')xbwt=xbwt_obj.computeXBWT()xbwt_obj.printXBWT(xbwt)\"\"\"*** XBW TRANSFORM OF THE TREE T ***[S_LAST, S_ALPHA][0, ['A', 0]][0, ['C', 0]][0, ['D', 0]][1, ['D', 0]][1, ['a', 1]][1, ['a', 1]][1, ['c', 1]][0, ['C', 0]][0, ['a', 1]][1, ['B', 0]][1, ['b', 1]][1, ['E', 0]][0, ['B', 0]][0, ['a', 1]][1, ['B', 0]][1, ['c', 1]]\"\"\"Input formatThe trees to be imported to build the xbw transform must comply with the format below. In particular, nodes must be specified through the [NODE] ... [\\NODE] tag. It is important that the root node has the identifier \"root\" in its definition. Instead, the edges are specified via the [EDGE] ... [\\EDGES] tag. In the latter case, for each node it is necessary to insert the respective nodes with which the edge is formed in the respective order.[NODES]\nroot = 'label1'\nn1 = 'label2'\nn2 = 'label3'\nn3 = 'label4'\nn4 = 'label5'\n[\\NODES]\n\n[EDGES]\nroot = [n1, n2]\nn1 = [n3, n5]\n[\\EDGES]"} +{"package": "xbx", "pacakge-description": "No description available on PyPI."} +{"package": "xbyte-test-module", "pacakge-description": "No description available on PyPI."} +{"package": "xbyte-tool", "pacakge-description": "No description available on PyPI."} +{"package": "xc", "pacakge-description": "xc is a simple calculator meant to be used entirely from the command-line. It automatically displays results in both decimal and hexadecimal. It is focused on convenience and ease of use."} +{"package": "xc3-model-py", "pacakge-description": "xc3_model_pyPython bindings toxc3_modelfor high level and efficient data access to model files for Xenoblade 1 DE, Xenoblade 2, and Xenoblade 3.InstallationThe package can be installed for Python version 3.9, 3.10, 3.11, or 3.12 using pip on newer versions of Windows, Linux, or MacOS. The prebuilt wheels (.whl files) are included only for situations where pip might not be available such as for plugin development for applications. The wheels are zip archives and can be extracted to obtain the compiled .pyd or .so file.Installing:pip install xc3_model_pyUpdating:pip install xc3_model_py --upgradeIntroductionParsing and processing happens in optimized Rust code when callingxc3_model_py.load_maporxc3_model_py.load_model. All characters, models, and maps are converted to the same scene hierarchy representation. This avoids needing to add any special handling for maps vs characters. Pregenerated shader JSON databases are available fromxc3_lib.importxc3_model_py# Get a list of model roots.roots=xc3_model_py.load_map(\"xenoblade3_dump/map/ma59a.wismhd\",database_path=\"xc3.json\")forrootinroots:forgroupinroot.groups:formodelsingroup.models:formaterialinmodels.materials:print(material.name)# The shader contains assignment information when specifying a JSON database.ifmaterial.shaderisnotNone:# Find the image texture and channel used for the ambient occlusion output.ao=material.shader.sampler_channel_index(2,'z')ifaoisnotNone:sampler_index,channel_index=aoimage_texture_index=material.textures[sampler_index].image_texture_indeximage_texture=root.image_textures[image_texture_index]print(image_texture.name,'xyzw'[channel_index])formodelinmodels.models:# prints (num_instances, 4, 4)print(len(model.instances.shape))# This returns only a single root.root=xc3_model_py.load_model(\"xenoblade3_dump/chr/chr/01012013.wimdo\",database_path=\"xc3.json\")forgroupinroot.groups:formodelsingroup.models:formodelinmodels.models:# prints (1, 4, 4)print(len(model.instances.shape))# Access vertex and index data for this model.buffers=group.buffers[model.model_buffers_index]forbufferinbuffers.vertex_buffers:forattributeinbuffer.attributes:print(attribute.attribute_type,attribute.data.shape)Certain types like matrices and vertex atribute data are stored usingnumpy.ndarray. This greatly reduces conversion overhead and allows for more optimized Python code. xc3_model_py requires the numpy package to be installed. Blender already provides the numpy package, enabling the use of functions likeforeach_getandforeach_setfor efficient property access.# blenderblender_mesh.vertices.add(positions_array.shape[0])blender_mesh.vertices.foreach_set('co',positions_array.reshape(-1))Animations can be loaded from a file all at once. The track type is currently opaque, meaning that implementation details are not exposed. The values can be sampled at the desired frame using the appropriate methods.importxc3_model_pypath=\"xenoblade3_dump/chr/ch/ch01027000_event.mot\"animations=xc3_model_py.load_animations(path)foranimationinanimations:print(animation.name,animation.space_mode,animation.play_mode,animation.blend_mode)print(f'frames:{animation.frame_count}, tracks:{len(animation.tracks)}')track=animation.tracks[0]# Each track references a bone in one of three ways.bone_index=track.bone_index()bone_hash=track.bone_hash()bone_name=track.bone_name()ifbone_indexisnotNone:passelifbone_hashisnotNone:# Use xc3_model_py.murmur3(bone_name) for hashing the skeleton bones.passelifbone_nameisnotNone:pass# Sample the transform for a given track at each frame.# This essentially \"bakes\" the keyframes of the animation.forframeinrange(animation.frame_count:)print(track.sample_scale(frame),track.sample_rotation(frame),track.sample_translation(frame))print()xc3_model_py enables Rust log output by default to use with Python'sloggingmodule.\nLogging can be disabled entirely if not needed usinglogging.disable().importlogging# Configure log messages to include more information.FORMAT='%(levelname)s%(name)s%(filename)s:%(lineno)d%(message)s'logging.basicConfig(format=FORMAT,level=logging.INFO)DocumentationSee thepyi stub filefor complete function and type information. This also enables autocomplete in supported editors like the Python extension for VSCode. The Python API attempts to match the Rust functions and types in xc3_model as closely as possible.InstallationThe compiled extension module can be imported just like any other Python file. On Windows, renamexc3_model_py.dlltoxc3_model_py.pyd. If importingxc3_model_pyfails, make sure the import path is specified correctly and the current Python version matches the version used when building. For installing in the current Python environment, installmaturinand usematurin develop --release.BuildingBuild the project withcargo build --release. This will compile a native python module for the current Python interpreter. For use with Blender, make sure to build for the Python version used by Blender. The easiest way to do this is to use the Python interpreter bundled with Blender. See thePyO3 guidefor details. Some example commands are listed below for different operating systems.Blender 4.0 on Windowsset PYO3_PYTHON = \"C:\\Program Files\\Blender Foundation\\Blender 4.0\\4.0\\python\\bin\\python.exe\"\ncargo build --releaseBlender 4.0 on MacOSPYO3_PYTHON=\"/Applications/Blender.app/Contents/Resources/4.0/python/bin/python3.10\" cargo build --releaseLimitationsAll data should be treated as immutable. Attempting to set fields will result in an error. Modifying list elements will appear to work, but changes will not be reflected when accessing the elements again. Types fromxc3_model_pyalso cannot be constructed in any way from Python. These limitations may be lifted in the future. Write support may be added in the future as xc3_lib and xc3_model develop."} +{"package": "xcache", "pacakge-description": "It\u2019s likelru_cachesbut can be cleared automatically or via context managers.Why?There are only two hard things in Computer Science: cache invalidation and naming things.\u2013 Phil KarltonSo, caches are fairly easy, but their invalidation is kind of hard to get right.What type of cache is used?The default implementation is the lru_cache of the stdlib but you can drop in your own.How?Python features garbage collection aka. automatic memory management. Let\u2019s make use of it:fromxcacheimportcache_genrequest_cache=cache_gen(lambda:request)# default cache_impl=lru_cacheHere, we defined our own cache that needs the global request for invalidating the cache.\nAs soon asrequestis garbage-collected, the cached data is freed.@request_cache()deffib(n):returnfib(n-1)+fib(n-2)ifn>1else1Here, we see how to decorate a function to work like a lru_cache.Now, let\u2019s see how this works:classRequest():passrequest=Request()print(fib(10))print(fib(20))print(fib.cache_info())# fib cache contains 2 itemsrequest=Request()# invalidates all cachesprint(fib.cache_info())# fib cache contains 0 itemsprint(fib(10))print(fib(20))Context Manager for more more control over cache invalidationIf you need more control, the context managerclean_cachesis what you need:fromxcacheimportcached,clean_caches@cached()deffib(n):returnfib(n-1)+fib(n-2)ifn>1else1withclean_caches():print(fib(10))print(fib(20))print(fib.cache_info())# fib cache contains 2 itemsprint(fib.cache_info())# fib cache contains 0 itemsYou can even specify what object the caches should be attached to:@cached()deffib(n):returnfib(n-1)+fib(n-2)ifn>1else1withclean_caches(Request())asrequest:print(fib(10))print(fib(20))print(fib.cache_info())# fib cache contains 2 itemsprint(fib.cache_info())# fib cache contains 0 itemsCan these context managers be nested?Sure. At each entrance and and exit of each context, all associated caches are emptied.ConclusionGoodcache invalidation done easyworks via garbage collectionworks via context managersworks with Python2 and Python3Badunkown ;-)Ideas are always welcome. :-)"} +{"package": "xcache-lib", "pacakge-description": "XCache: A simplest and thread-safe LRU cache, which support key-func, release-func and hit-stat.Setuppipinstallxcache-libKey FeaturesLRU cacheThread safeSupport special key functionSupport special release functionHas detail hit statCore Function Descriptor: xcache@xcache(cache_size,key_func=None,release_func=None,log_keys=False)Param ValueDescriptioncache_sizesize of cache storagekey_funspecial key functionrelease_funcspecial release functionlog_keyslog keys, forDEBUGQuick Startfromxcacheimportxcache,show_xcache_hit_stat@xcache(3,key_func=lambdax,y:x,log_keys=True)defcalc(x,y):print(\"calc{},{}\".format(x,y))returnx+yif__name__==\"__main__\":print(calc(5,6))print(calc(5,6))print(calc(5,6))print(calc(5,5))print(calc(4,6))print(calc(3,6))print(calc(2,6))print(calc(1,6))print(calc(9,6))print(json.dumps(show_xcache_hit_stat(x),indent=4))# show detail hit statoutputs:calc5,6111111calc5,510calc4,610calc3,69calc2,68calc1,67calc9,615{\"hit_rate\":22.22222222222222,\"dup_calc_rate\":0.6666666666666666,\"hit\":[2,7],\"keys_num\":1,\"detail\":{\"key_detail\":{\"1\":6,\"3\":1},\"hit_detail\":{\"2\":1}}}"} +{"package": "xcal3d", "pacakge-description": "Python library for loading and manipulating Cal3D avatars without requiring Cal3DPublished also on PyPi ashttps://pypi.python.org/pypi/xcal3d"} +{"package": "xcaliber-webhooks", "pacakge-description": "IntroductionVerify webhook events from xcaliberUsage:Install package using following command - pip install xcaliber_webhooksUse the below example to verify webhook -from xcaliber_webhooks import Webhooksecret=\"\" //secret key for webhookwebhook = Webhook(secret)headers = {\"svix-id\": \"\",\"svix-timestamp\": \"\",\"svix-signature\": \"\",}payload = '{}' //sample payloadwebhook.verify(payload, headers)"} +{"package": "xcalibrate", "pacakge-description": "Placeholder Text November 2022xcalibrate v. 0.0.1A Bayesian algorithm for calibration of radiometer devices used in 21-cm astrophysics experiments.Ian Roque, Will Handley & Nima Razavi-GhodsContact:ilvr2@cam.ac.ukBase methodology:arxiv:2011.14052Please cite the xcalibrate papers:I. L. V. Roque, W. J. Handley, N. Razavi-Ghods, Bayesian noise wave calibration for 21-cm global experiments,Monthly Notices of the Royal Astronomical Society, Volume 505, Issue 2, August 2021, Pages 2638\u20132646.https://academic.oup.com/mnras/article/505/2/2638/6279678"} +{"package": "xcalibu", "pacakge-description": "Xcalibuauthor: Cyril Guilloud ESRF BCU 2013-2023Xcalibu is a python library to manage calibrations tables or polynomia.\nIt includes a PyTango device server in order to optionaly run it as a server.xcalibu.py : python library\nXcalibuds.py : PyTango device serverXcalibu name comes from the first use of this library to deal with undulators calibrations at ESRF.https://en.wikipedia.org/wiki/Undulatorhttps://en.wikipedia.org/wiki/European_Synchrotron_Radiation_FacilityinstallationAvailable on PyPi or anaconda.orgusageto plot:./xcalibu.py -pto debug:./xcalibu.py -d10plot a file:./xcalibu.py -p examples/xcalibu_calib_poly.calibExamplesTABLE + INTERPOLimportnumpyimportxcalibucalib=xcalibu.Xcalibu()calib.set_calib_file_name(\"mycalib.calib\")calib.set_calib_type(\"TABLE\")calib.set_reconstruction_method(\"INTERPOLATION\")calib.set_calib_time(\"1234.5678\")calib.set_calib_name(\"CAL\")calib.set_calib_description(\"dynamic calibration created for demo\")calib.set_raw_x(numpy.linspace(1,10,10))calib.set_raw_y(numpy.array([3,6,5,4,2,5,7,3,7,4]))calib.plot()calib.save()# create a file named `mycalib.calib` in your current directory.TABLE + POLYFITimportnumpyimportxcalibucalib=xcalibu.Xcalibu()calib.set_calib_file_name(\"mycalib.calib\")calib.set_calib_type(\"TABLE\")calib.set_reconstruction_method(\"POLYFIT\")calib.set_calib_time(\"1234.5678\")calib.set_calib_name(\"CAL\")calib.set_calib_description(\"dynamic calibration created for demo\")calib.set_raw_x(numpy.linspace(1,10,15))calib.set_raw_y(numpy.array([4.1,3.5,3.6,4.2,4.5,4,3.9,3.8,4.5,4.6,6,6.2,4.7,5,4]))calib.set_fit_order(6)calib.fit()calib.plot()POLY% cat mycalib.calib\n# XCALIBU CALIBRATION\n\nCALIB_NAME=CAL\nCALIB_TYPE=TABLE\nCALIB_TIME=1234.5678\nCALIB_DESC=dynamic calibration created for demo\n\nCAL[1.000000] = 3.000000\nCAL[2.000000] = 6.000000\nCAL[3.000000] = 5.000000\nCAL[4.000000] = 4.000000\nCAL[5.000000] = 2.000000\nCAL[6.000000] = 5.000000\nCAL[7.000000] = 7.000000\nCAL[8.000000] = 3.000000\nCAL[9.000000] = 7.000000\nCAL[10.000000] = 4.000000command line usageOptions:\n-h: help\n-p: plot\n-d: debug-t type\n-r reconstruction_method\n-k kind of interpolation\n-n nameexample:\n./xcalibu.py -n calinou -t TABLE -r INTERPOLATION -k cubic examples/U32a_1_table.dat -p"} +{"package": "xcall", "pacakge-description": "Xcall for python."} +{"package": "xcal_raman", "pacakge-description": "This module provides functions for wavenumber calibration of Raman\nspectrometers. Currently it works only with binary SPE files, produced,\nfor example, by winspec (Princeton Instruments software). Supported\nsubstances so far are polystyrene and cyclohexan (or any other, if you\nhave a table with Raman shifts and 15 minutes of time).One of the key features is that the script provides a detailed report of\ncalibration in PDF format with a lot of plots.Typical usage looks like this:#!/usr/bin/env python\n\nimport xcal_raman as xcal\nimport winspec\ncal_f, p = xcal.calibrate_spe(\"polystyrene.SPE\", \"dark.SPE\",\n material=\"polystyrene\", figure=figure())\nsavefig(\"xcal-report-polystyrene.pdf\")\n# We have calibration function, lets plot spectrum of some substance\ns = winspec.Spectrum(\"substance.SPE\")\ns.background_correct(\"dark.SPE\")\nplot(cal_f(s.wavelen), s.lum)\nxlabel(\"Wavenumber, cm$^{-1}$\")\nylabel(\"Counts\")Thanks toThe SPE files are read by script winspec.py, which was written by James Battat\nand Kasey Russell. I modified it and commented out the calibration."} +{"package": "xcam", "pacakge-description": "Driver to control the XCAM rack.Build and Test CommandsInstall this package:pip install xcam --extra-index-url http://lab-linux-server.estec.esa.int/pypiserver --trusted-host lab-linux-server.estec.esa.intInstall build and test tools:pip install docutils\npip install coverage\npip install pylint\npip install nose\npip install tox\npip install plantumlFrom the root directory (rpc) run the following commands:pylint --rcfile=pylint.cfg xcam\nnosetests --with-coverage --cover-erase --cover-html\ncoverage run -m unittest discover -b -v -s .\ncoverage report\npython -m unittest discover\npython setup.py bdist_wheelTo build the README.rst documentation:pygmentize -S default -f html -a .python > style.css\npython %VIRTUAL_ENV%/Scripts/rst2html.py --link-stylesheet --cloak-email-addresses --toc-top-backlinks --syntax-highlight=short --stylesheet-dirs=. --stylesheet README.css README.rst esapy_rpc.htmlSyntax highlighting using pygments:http://pygments.org/docs/cmdline/PyPI Register / Upload commands:python setup.py bdist_wheel\n# For PyPI LIVE use: https://pypi.python.org/pypi\npython setup.py register -r https://testpypi.python.org/pypi\n# For PyPI LIVE use: pypi\npython setup.py bdist_wheel upload -r pypitest\n# or,\npython setup.py bdist_wheel upload -r http://lab-linux-server.estec.esa.int:9999To authenticate automatically create a file named.pypircin your $HOME directory,:[distutils]\nindex-servers =\n sci-fv\n\n[sci-fv]\nrepository: http://lab-linux-server.estec.esa.int/packages\nusername: lab\npassword: Now the upload command can be executed without an authentication prompt using,:python setup.py bdist_wheel upload -r sci-fvIf the above hasMake sure the.pypircfile is defined in your home folder before running\nthe above commands."} +{"package": "xcamera", "pacakge-description": "XCamera: Android-optimized camera widgetXCamera is a widget which extends the standard Kivy Camera widget with more\nfunctionality. In particular:it displays a \"shoot button\", which the user can press to take pictureson Android, it uses the native APIs to take high-quality pictures,\nincluding features such as auto-focus, high resolution, etc.it includes a method to force landscape mode. On Android, it is often\ndesirable to switch to landscape mode when taking pictures: you can\neasily do it by callingcamera.force_landscape(), and latercamera.resource_orientation()to restore the orientation to whatever it\nwas before.Screenshot:Notes:On Android, theresolutionproperty of theXCamera(and also of the\nplainCamera) widget controls thepreview size: in other words, it\nonly affects the quality of the preview, not the size of the pictures\ntaken.As it is now, the camera will shoot using the default setting for the\npicture size, which seems to be what the camera think it is \"the best\". In\ntheory, we could add a method to retrieve the list of all possible picture\nsizes, and add a property to control it. It would also be nice to add a\nnew button to allow the user to manually select the preferred size. Pull\nrequests are welcome :)Install & Usagexcamera is available on PyPI.\nTherefore it can be installed viapip.pip3installxcameraOnce installed, the demo should be available in yourPATHand can be ran from the command line.xcameraAnd the widget can be imported via:fromkivy_garden.xcameraimportXCameraDemoA full working demo is available insrc/kivy_garden/xcamera/main.py.\nYou can run it via:makerunDevelop & ContributeTo play with the project, install system dependencies and Python requirements using theMakefile.makeThen verify everything is OK by running tests.maketestIf you're familiar withDocker, the project can also run in a fully isolated container.\nFirst build the image.makedocker/buildThen you can run tests within the container.makedocker/run/testOr the application itself.makedocker/run/app"} +{"package": "xcanvas", "pacakge-description": "No description available on PyPI."} +{"package": "xcaptcha", "pacakge-description": "xcaptcha"} +{"package": "x-captcha", "pacakge-description": "A simple and powerful captcha generation library.FeaturesEasy to use.Parameterization.Powerful.Continuous updating.InstallationInstall x-captcha with pip:$ pip install x-captchaUsageImage captcha:fromxcaptcha.imageimportCaptcha# defaultgenerator=Captcha()captcha,image=generator.generate()# parametersize=(200,100)characters='1234567890abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'number=6font='data/msyhbd.ttf'generator=Captcha(size,characters,number,font)captcha,image=generator.generate()# configgenerator=Captcha()size=(200,100)characters='1234567890abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'number=6font='data/msyhbd.ttf'generator.config(size,characters,number,font)captcha,image=generator.generate()# savegenerator=Captcha()generator.save()generator.save('captcha/captcha.png')This is the APIs for your daily works.Contribution"} +{"package": "xcash", "pacakge-description": "XCASH Foundation ecosystem python API wrapperWhat is it?Is a client Python wrapper library around XCASH Foundation ecosystem products.IntegrationsBlockchain Explorer api wrapperDelegates Explorer api wrapperShared Delegate api wrapperRPCDaemonWalletDpopsPyPi publishedSetupInstall required packagePackage can be installed withpip, the python package index.pip3installxcashorpipinstallxcashEcosystem accessible productsTo access products you are required to import packages and initiate them:# Access to blockchain datafromxcash.blockchainExplorerimportBlockchainExplorerblockchain_api=BlockchainExplorer()# Access Delegates Explorer of DPOPS systemfromxcash.delegatesExplorerimportDelegatesExplorerdelegates_api=DelegatesExplorer()# Access Shared delegate through apifromxcash.sharedDelegateimportSharedDelegatedelegate_api=SharedDelegate(delegate_url=\"DELEGATE URL\")RPC server Daemon, Wallet and Dpops wallet (delegate)Pre-requirements -> Start the RPC server!In order to be able to execute calls to RPC you are required to first initiate RPC server.Cd to the wallet folderbinwherexcash-wallet-rpcis located, and open the location with eithercmd(\nWindows) or terminal (Ubuntu)Initiate PRC server either with:Local daemon# Windowsxcash-wallet-rpc.exe--wallet-file--password--rpc-bind-port18285--disable-rpc-login--confirm-external-bind--trusted-daemon#Ubuntu./xcash-wallet-rpc--wallet-file--password--rpc-bind-port18285--disable-rpc-login--confirm-external-bind--trusted-daemonRemote daemon# Windowsxcash-wallet-rpc.exe--wallet-file--password--rpc-bind-port18285--disable-rpc-login--confirm-external-bind--daemon-address:18281# Ubuntu./xcash-wallet-rpc--wallet-file--password--rpc-bind-port18285--disable-rpc-login--confirm-external-bind--daemon-address:18281Import desired packages to python script# Access endpoints for XCASH Daemonfromxcash.rpcimportXcashDaemonRpcdaemon=XcashDaemonRpc()# Access endpoints for XCASH walletfromxcash.rpcimportXcashWalletRpcwallet=XcashWalletRpc()# Access endpoints on wallet dedicated for delegate.fromxcash.rpcimportXcashDpopsWalletRpcdpops=XcashDpopsWalletRpc()ExamplesBlockchain Explorer Apifromxcash.blockchainExplorerimportBlockchainExplorerfrompprintimportpprint# Initiate blockchain explorer clientblockchain_api=BlockchainExplorer()# Get blockchain datablockchain_data=blockchain_api.get_blockchain_data()# Print datapprint(blockchain_data)Examples on all available methods to communicate with XCASH blockchain Rest API can be\nfoundhereDelegates Explorer Apifromxcash.delegatesExplorerimportDelegatesExplorerfrompprintimportpprint# Initiate delegates explorer clientdelegates_api=DelegatesExplorer()# Get delegates/DPOPS statisticsstatistics=delegates_api.get_delegate_website_statistics()# Print datapprint(statistics)Examples on all available methods to communicate with XCASH DPOPS Delegates Explorer Rest API can be\nfoundhereShared Delegate Apifromxcash.sharedDelegateimportSharedDelegatefrompprintimportpprint# Initiate shared delegate and provide delegates address as param to access APIurl=\"http://xpayment.x-network.eu\"delegate_api=SharedDelegate(delegate_url=url)# Delegate statistics data from delegate websitestatistics=delegate_api.get_delegate_website_statistic()# Print datapprint(statistics)Examples on all available methods to communicate with Shared Delegate Rest API can be\nfoundhereDaemon RPC callfromxcash.rpcimportXcashDaemonRpcfrompprintimportpprintdaemon=XcashDaemonRpc()# Get the daemon versionversion=daemon.get_version()pprint(version)Examples on all available methods to communicate with Daemon RPC API can be\nfoundhereWallet RPC callfromxcash.rpcimportXcashWalletRpcfrompprintimportpprintwallet=XcashWalletRpc()# Get balancebalance=wallet.get_balance()pprint(balance)Examples on all available methods to communicate with Wallet RPC API can be\nfoundhereDPOPS Wallet RPC callfromxcash.rpcimportXcashDpopsWalletRpcfrompprintimportpprintdpops_wallet=XcashDpopsWalletRpc()status=dpops_wallet.register_delegate(delegate_name=\"Animus-Test\",delegate_ip_address=\"100.100.00.00\")pprint(status)Examples on all available methods to communicate with DPOPS wallet RPC API can be\nfoundhereReferenceshttps://docs.xcash.foundation/applications/rpc-calls/json-rpc-methodshttps://docs.xcash.foundation/applications/rpc-calls/xcash-wallet-rpchttps://docs.xcash.foundation/applications/rpc-calls/xcash-wallet-rpc/dpops-wallet-rpc-callsContributors"} +{"package": "xcat", "pacakge-description": "XCatXCat is a command line tool to exploit and investigate blind XPath injection vulnerabilities.For a complete reference read the documentation here:https://xcat.readthedocs.io/en/latest/It supports an large number of features:Auto-selects injections (runxcat injectionsfor a list)Detects the version and capabilities of the xpath parser and\nselects the fastest method of retrievalBuilt in out-of-bound HTTP serverAutomates XXE attacksCan use OOB HTTP requests to drastically speed up retrievalCustom request headers and bodyBuilt in REPL shell, supporting:Reading arbitrary filesReading environment variablesListing directoriesUploading/downloading files (soon TM)Optimized retrievalUses binary search over unicode codepoints if availableFallbacks include searching for common characters previously retrieved firstNormalizes unicode to reduce the search spaceInstallRunpip install xcatRequires Python 3.7. You can easily install this withpyenv:pyenv install 3.7.1Example applicationThere is a complete demo application you can use to explore the features of XCat.\nSee the README here:https://github.com/orf/xcat_app"} +{"package": "xcauto", "pacakge-description": "xcautoArbitrary order exchange-correlation functional derivatives usingJAXThis library computes arbitrary-order exchange-correlation function(al) derivatives\nusingJAX.The emphasis of this project is onease of useandease of adding\nfunctionalsinPython. The focus is not (yet) on performance. Our hope is\nthat this project can make it easier to test new implementations of functional\nderivatives but maybe also used directly to provide functional derivatives in a\ndensity functional theory program.The code is in proof of concept stage. We haveideas for more.Acknowledgements and recommended citationJAXdoes all the heavy lifting by\nautomatically differentiating the exchange-correlation functions. Please\nacknowledge their authors when using this code:https://github.com/google/jax#citing-jax:@software{jax2018github,\n author = {James Bradbury and Roy Frostig and Peter Hawkins and Matthew James Johnson and Chris Leary and Dougal Maclaurin and Skye Wanderman-Milne},\n title = {{JAX}: composable transformations of {P}ython+{N}um{P}y programs},\n url = {http://github.com/google/jax},\n version = {0.1.55},\n year = {2018},\n}We have usedLibxcas reference to\ndouble check the computed derivatives.The functional definitions for VWN and PBE were ported to Python based on the\nfunctional definitions found inXCFun(Copyright Ulf Ekstr\u00f6m and contributors, Mozilla Public License v2.0).AuthorsRadovan BastRoberto Di RemigioUlf Ekstr\u00f6mInstallationYou can install this code from PyPI:$ pip install xcautoInstalling a development version:$ git clone https://github.com/dftlibs/xcauto\n$ cd xcauto\n$ python -m venv venv\n$ source venv/bin/activate\n$ pip install -r requirements.txt\n$ flit install --symlinkUsing on the Hylleraas FleetThe machines in the Fleet are properly set up to run JAX on their GPUs. The instructions to installxcautoare slightly modified, since we'll need a GPU-aware version ofJAX:$ git clone https://github.com/dftlibs/xcauto\n$ cd xcauto\n$ python -m venv venv\n$ source venv/bin/activate\n$ pip install -r requirements.txt\n$ pip install --upgrade https://storage.googleapis.com/jax-releases/`nvidia-smi | sed -En \"s/.* CUDA Version: ([0-9]*)\\.([0-9]*).*/cuda\\1\\2/p\"`/jaxlib-0.1.51-`python3 -V | sed -En \"s/Python ([0-9]*)\\.([0-9]*).*/cp\\1\\2/p\"`-none-manylinux2010_x86_64.whl jax\n$ flit install --symlinkTo run:$ env XLA_FLAGS=--xla_gpu_cuda_data_dir=/lib/cuda python -m pytest tests/test.pyThe environment variableis important: JAX won't be able to use the GPU otherwise.ExampleIn this example we only go up to first-order derivatives\nbut no problem to ask for higher-order derivatives (mixed or not).Firstpip install xcauto, then:# use double precision floatsfromjax.configimportconfigconfig.update(\"jax_enable_x64\",True)fromxcauto.functionalsimportpbex_n_gnn,pbec_n_gnn,pbec_a_b_gaa_gab_gbbfromxcauto.dervimportdervdefpbe_unpolarized(n,gnn):returnpbex_n_gnn(n,gnn)+pbec_n_gnn(n,gnn)print('up to first-order derivatives for spin-unpolarized pbe:')n=0.02gnn=0.05d_00=derv(pbe_unpolarized,[n,gnn],[0,0])d_10=derv(pbe_unpolarized,[n,gnn],[1,0])d_01=derv(pbe_unpolarized,[n,gnn],[0,1])print(d_00)# -0.006987994564372291print(d_10)# -0.43578312569769495print(d_01)# -0.004509994863217848print('few derivatives for spin-polarized pbec:')fun=pbec_a_b_gaa_gab_gbba=0.02b=0.05gaa=0.02gab=0.03gbb=0.04d_00000=derv(fun,[a,b,gaa,gab,gbb],[0,0,0,0,0])d_10000=derv(fun,[a,b,gaa,gab,gbb],[1,0,0,0,0])d_01000=derv(fun,[a,b,gaa,gab,gbb],[0,1,0,0,0])d_00100=derv(fun,[a,b,gaa,gab,gbb],[0,0,1,0,0])d_00010=derv(fun,[a,b,gaa,gab,gbb],[0,0,0,1,0])d_00001=derv(fun,[a,b,gaa,gab,gbb],[0,0,0,0,1])print(d_00000)# -0.0002365056872298918print(d_10000)# -0.020444840022142356print(d_01000)# -0.015836702168478496print(d_00100)# 0.0030212897704793786print(d_00010)# 0.006042579540958757print(d_00001)# 0.0030212897704793786For more examples, see thetests folder.FunctionalsList of implemented functions:slaterx_n\nslaterx_a_b\nvwn3_n\nvwn3_a_b\nvwn5_n\nvwn5_a_b\npbex_n_gnn\npbex_a_b_gaa_gbb\npbec_n_gnn\npbec_a_b_gaa_gab_gbb\nb88_n_gnn\nb88_a_b_gaa_gbb\nlyp_n_gnn\nlyp_a_b_gaa_gab_gbbWhere are all the other functionals?We will be adding more but our hope is\nthat the community will contribute these also. It is very little work to define\na functional so please send pull requests! All the derivatives you get \"for\nfree\" thanks toJAX.IdeasHere we list few ideas that would be good to explore but which we haven't done\nyet:Check performanceTry how the code offloads to GPU or TPUVerify numerical stability for small densitiesAdding more functionalsDirectional derivativesContracting derivatives with perturbed densities"} +{"package": "xcbl", "pacakge-description": "List ends with an \u2018Other:\u2019 element that can be filled in by hand.\nAny number of new options can be specified.\nMochiKit 1.4 required for optimal appearance."} +{"package": "xcc", "pacakge-description": "No description available on PyPI."} +{"package": "xccdfparser", "pacakge-description": "xccdfparserExtensible parser forXCCDFBenchmark/Result XML files.pip install xccdfparserProduces a human-readable JSON from an incomprehensible XCCDF schema/result file:For every TestResult tag in the input file,Benchmark DetailsBenchmark IDRule IDTitle/DescriptionFixtextDictionaryMetadataTimestampTarget MachineIP address(es)XCCDF DomainResultsRule IDValueTo run the parser on a file input.xml, just use:xccdfparser -o output.json input.xmlORxccdfparser input.xmlTesting xccdfparserTo test the pre-built tox environments:First, install tox if you don't have it:pip install toxThen in the package directory:toxOr for a specific environment:tox -e py36"} +{"package": "xcdb", "pacakge-description": "Stand-alone version of django module for xchem db. See github.com/xchem/xchem_db for more info"} +{"package": "xcell", "pacakge-description": "# xCell command-line interface and python module\nA command-line interface and python module for pipeline deployment of Aran et. al.\u2019s xCellhttps://doi.org/10.1186/s13059-017-1349-1"} +{"package": "xcept", "pacakge-description": "xceptxceptis a Python package for the convenience of creating exceptions.Installationpip install xceptUsageBuilt-inExceptionUsually exceptions are created like this:classError(Exception):# Base error class of your application or librarypassclassFooError(Error):# Concrete error classpassclassBarError(Error):# Concrete error classpassIt looks pretty simple.\nLet's try to create exceptions with arguments:classError(Exception):def__init__(self,message:str):self.message=messagedef__str__(self):returnself.messageclassFooError(Error):def__init__(self,message:str,a:str):super().__init__(message=message)self.a=aclassBarError(Error):def__init__(self,message:str,b:str,c:int):super().__init__(message=message)self.b=bself.c=cIn the simplest case we have to usesupereach time to initialize a new exception. And we also pass an already prepared message.This does not allow us from getting a modified message when the attributes change:>>>a=\"value\">>>error=FooError(f\"Error (a='{a}')!\",a)>>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.FooError:Error(a='value')!>>>>>>error.a=\"new_value\">>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.FooError:Error(a='value')!xceptException_The idea ofxceptis based on use ofdataclasses:fromdataclassesimportdataclassfromxceptimportException_@dataclassclassError(Exception_):pass@dataclassclassFooError(Error):a:str@dataclassclassBarError(Error):b:strc:intThe first argument is always a message template with replacement fields:>>>error=FooError(\"Error ({a=})!\",a=\"value\")>>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.FooError:Error(a='value')!>>>>>>error.a=\"new_value\">>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.FooError:Error(a='new_value')!Format syntax is presented here:https://docs.python.org/3.7/library/string.html#format-string-syntaxNote:Only keyword replacement fields are supported.Note:Additionally, there is an expression with the=. It allows you to set a value along with a name:>>>error=FooError(\"{a}\",a=\"a_value\")>>>print(error)a_value>>>>>>error=FooError(\"{a=}\",a=\"a_value\")>>>print(error)a='a_value'If a message template does not contain all replacement fields and all replacement fields is required, theMissingFieldWarningoccurs:>>>error=FooError(\"Error!\",a=\"value\"):1:MissingFieldWarning:Nothereplacementfield'a'inthetemplate'Error!'(FooError)!>>>>>>error=BarError(\"Error ({b=})!\",b=\"value\",c=\"value\"):1:MissingFieldWarning:Nothereplacementfield'c'inthetemplate'Error ({b=})!'(BarError)!>>>>>>error=BarError(\"Error!\",b=\"value\",c=\"value\"):1:MissingFieldWarning:Nothereplacementfields'b','c'inthetemplate'Error!'(BarError)!If for some reason you don't need to include all attributes in a message, defineALL_REPLACEMENT_FIELDS_IS_REQUIRED = False(defaultTrue) to disable checks and warnings:>>>@dataclass...classSomeError(Exception_):...ALL_REPLACEMENT_FIELDS_IS_REQUIRED=False...a:str...b:str...>>>error=SomeError(\"Error ({a=})!\",a=\"a_value\",b=\"b_value\")>>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.SomeError:Error(a='a_value')!If a message template contains unknown replacement fields, theUnknownFieldWarningoccurs and the value is set to:>>>error=FooError(\"Error ({a=}, {b=}, {c=})!\",a=\"a_value\"):1:UnknownFieldWarning:Unknownthereplacementfields'b','c'inthetemplate'Error ({a=}, {b=}, {c=})!'(FooError)!>>>raiseerrorTraceback(mostrecentcalllast):File\"\",line1__main__.FooError:Error(a='a_value',b=,c=)!If there is no a message template and all replacement fields is required, theMissingTemplateWarningoccurs:>>>@dataclass...classSomeError(Exception_):...pass...>>>error=SomeError(None)# Message template is None:1:MissingTemplateWarning:Noatemplate(SomeError)!You can set a default message template:>>>@dataclass...classSomeError(Exception_):...DEFAULT_TEMPLATE=\"Default message template ({a=})!\"...a:str...>>>raiseSomeError(None,a=\"a_value\")# Message template is NoneTraceback(mostrecentcalllast):File\"\",line1__main__.SomeError:Defaultmessagetemplate(a='a_value')!"} +{"package": "xcert", "pacakge-description": "##Getting startedThis script communicates with the Xolphin API to manage certificates.The script is pretty basic and doesnt contain much error handling.\nalso the output is plain json sometimes. But it gets the job done.InstallationRun (preferably in a venv environment):python3 -m pip install xcertUsageusage: xcert [-h] [--create-pem filename] [--kube-secret filename] [--list-requests]\n [--retry-validation domain_name] [--download-certificate domain_name]\n [--list-certificates] [--request-status domain_name]\n [--request-certificate domain_name] [--renew-certificate domain_name]\n\noptional arguments:\n -h, --help show this help message and exit\n --create-pem filename\n Creates a .pem file with the certificate(.crt), the intermediates(.ca) and the key(.key). And a .cer file with the Certificate and the intermediates. Requires the following files: FILENAME.crt ,FILENAME.ca and FILENAME.key\n --kube-secret filename\n Prints a kubernetes secret in yaml format generated from a cert/key. Requires a FILENAME.cer and a FILENAME.key\n --list-requests Lists all pending requests at Xolphin\n --retry-validation domain_name\n Triggers a validation of the certificate request with DOMAIN_NAME\n --download-certificate domain_name\n Downloads the certificate for DOMAIN_NAME and saves it as DOMAIN_NAME.cer. Also downloads the corresponding intermediate certificates as DOMAIN_NAME.ca\n --list-certificates Lists all current certificates at Xolphin\n --request-status domain_name\n Gets the status of the request with the DOMAIN_NAME. If DOMAIN_NAME is \"all\" then list the status of all requests\n --request-certificate domain_name\n Request a new certificate from Xolphin, and saves the generated DOMAIN_NAME.csr and DOMAIN_NAME.key\n --renew-certificate domain_name\n Renews an existing certificate from Xolphin, and saves the generated DOMAIN_NAME.csr and DOMAIN_NAME.key\n\nadditional information:\n This program needs 2 environment variables to be set with your Xolphin credentials:\n XOLPHIN_USER='foo@bar.nl'\n XOLPHIN_PASSWORD='secret_password'\n It will use these credentials to authenticate to the Xolphin API.##TODO\nAdd build and publish instructions"} +{"package": "xcessiv", "pacakge-description": "# Xcessiv[![PyPI](https://img.shields.io/pypi/v/xcessiv.svg)]()\n[![license](https://img.shields.io/github/license/reiinakano/xcessiv.svg)]()\n[![PyPI](https://img.shields.io/pypi/pyversions/xcessiv.svg)]()\n[![Build Status](https://travis-ci.org/reiinakano/xcessiv.svg?branch=master)](https://travis-ci.org/reiinakano/xcessiv)### Xcessiv is a tool to help you create the biggest, craziest, and mostexcessivestacked ensembles you can think of.Stacked ensembles are simple in theory. You combine the predictions of smaller models and feedthoseinto another model. However, in practice, implementing them can be a major headache.Xcessiv holds your hand through all the implementation details of creating and optimizing stacked ensembles so you\u2019re free to fully define only the things you care about.## The Xcessiv process### Define your base learners and performance metrics![define_base_learner](docs/_static/baselearner.gif)### Keep track of hundreds of different model-hyperparameter combinations![list_base_learner](docs/_static/listbaselearner.gif)### Effortlessly choose your base learners and create an ensemble with the click of a button![ensemble](docs/_static/ensemble.gif)## FeaturesFully define your data source, cross-validation process, relevant metrics, and base learners with Python codeAny model following the Scikit-learn API can be used as a base learnerTask queue based architecture lets you take full advantage of multiple cores and embarrassingly parallel hyperparameter searchesDirect integration with [TPOT](https://github.com/rhiever/tpot) for automated pipeline constructionAutomated hyperparameter search through Bayesian optimizationEasy management and comparison of hundreds of different model-hyperparameter combinationsAutomatic saving of generated secondary meta-featuresStacked ensemble creation in a few clicksAutomated ensemble construction through greedy forward model selectionExport your stacked ensemble as a standalone Python file to support multiple levels of stacking## Installation and DocumentationYou can find installation instructions and detailed documentation hosted [here](http://xcessiv.readthedocs.io/).## FAQ#### Where does Xcessiv fit in the machine learning process?Xcessiv fits in the model building part of the process after data preparation and feature engineering. At this point, there is no universally acknowledged way of determining which algorithm will work best for a particular dataset (see [No Free Lunch Theorem](https://en.wikipedia.org/wiki/No_free_lunch_theorem)), and while heuristic optimization methods do exist, things often break down into trial and error as you try to find the best model-hyperparameter combinations.Stacking is an almost surefire method to improve performance beyond that of any single model, however, the complexity of proper implementation often makes it impractical to apply them in practice outside of Kaggle competitions. Xcessiv aims to make the construction of stacked ensembles as painless as possible and lower the barrier for entry.#### I don\u2019t care about fancy stacked ensembles and what not, should I still use Xcessiv?Absolutely! Even without the ensembling functionality, the sheer amount of utility provided by keeping track of the performance of hundreds, and even thousands of ML models and hyperparameter combinations is a huge boon.#### How does Xcessiv generate meta-features for stacking?You can choose whether to generate meta-features through cross-validation (stacked generalization) or with a holdout set (blending). You can read about these two methods and a lot more about stacked ensembles in the [Kaggle Ensembling Guide](https://mlwave.com/kaggle-ensembling-guide/). It\u2019s a great article and provides most of the inspiration for this project.## ContributingXcessiv is in its very early stages and needs the open-source community to guide it along.There are many ways to contribute to Xcessiv. You could report a bug, suggest a feature, submit a pull request, improve documentation, and many more.If you would like to contribute something, please visit our [Contributor Guidelines](CONTRIBUTING.md).## Project StatusXcessiv is currently in alpha and is unstable. Future versions are not guaranteed to be backwards-compatible with current project files."} +{"package": "xcffib", "pacakge-description": "No description available on PyPI."} +{"package": "xcfont", "pacakge-description": "No description available on PyPI."} +{"package": "xcfsyslogger", "pacakge-description": "UNKNOWN"} +{"package": "xcg-test", "pacakge-description": "No description available on PyPI."} +{"package": "xcgui", "pacakge-description": "No description available on PyPI."} +{"package": "xchain", "pacakge-description": "No description available on PyPI."} +{"package": "xchainer", "pacakge-description": "No description available on PyPI."} +{"package": "xchainpy2-binance", "pacakge-description": "@xchainjs/xchain-binanceBinance Beacon chainclient package of XChainPy2 library."} +{"package": "xchainpy2-client", "pacakge-description": "XChainPy2 Wallet Client InterfaceA specification for a generalised interface for crypto wallets clients, to be used by XChainPy2 implementations.\nThe client should not have any functionality to generate a key, instead,\ntheasgardex-crypto(todo: is there such lib for Py?) library should be used to ensure cross-chain compatible keystores are handled.\nThe client is only ever passed a master BIP39 phrase, from which a temporary key and address is decoded."} +{"package": "xchainpy2-cosmos", "pacakge-description": "xchainpy2_cosmosCosmos chain client."} +{"package": "xchainpy2-crypto", "pacakge-description": "How it worksTypically keystore files encrypt a seed to a file, however this is not appropriate or UX friendly, since the phrase\ncannot be recovered after the fact.Crypto design:[entropy] -> [phrase] -> [seed] -> [privateKey] -> [publicKey] -> [address]Instead, XCHAIN-CRYPTO stores the phrase in a keystore file, then decrypts and passes this phrase to other clients:[keystore] -> XCHAIN-CRYPTO -> [phrase] -> ChainClientThe ChainClients can then convert this into their respective key-pairs and addresses. Users can also export their\nphrases after the fact, ensuring they have saved it securely. This could enhance UX onboarding since users aren't forced\nto write their phrases down immediately for empty or test wallets."} +{"package": "xchainpy2-mayachain", "pacakge-description": "@xchainpy/xchain-mayachainMayaChain client package ofxchainpylib."} +{"package": "xchainpy2-mayanode", "pacakge-description": "xchainpy2-mayanodeMayanode REST API.This Python package is automatically generated by theSwagger Codegenproject:API version: 1.108.1Package version: 1.107.3Build package: io.swagger.codegen.v3.generators.python.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importxchainpy2_mayanodeSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxchainpy2_mayanodeGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportxchainpy2_mayanodefromxchainpy2_mayanode.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=xchainpy2_mayanode.HealthApi(xchainpy2_mayanode.ApiClient(configuration))try:api_response=api_instance.ping()pprint(api_response)exceptApiExceptionase:print(\"Exception when calling HealthApi->ping:%s\\n\"%e)Documentation for API EndpointsAll URIs are relative to/ClassMethodHTTP requestDescriptionHealthApipingGET/mayachain/pingLiquidityProvidersApiliquidity_providerGET/mayachain/pool/{asset}/liquidity_provider/{address}LiquidityProvidersApiliquidity_providersGET/mayachain/pool/{asset}/liquidity_providersMayanamesApimayanameGET/mayachain/mayaname/{name}MimirApimimirGET/mayachain/mimirMimirApimimir_adminGET/mayachain/mimir/adminMimirApimimir_keyGET/mayachain/mimir/key/{key}MimirApimimir_nodeGET/mayachain/mimir/node/{address}MimirApimimir_nodesGET/mayachain/mimir/nodes_allNetworkApibanGET/mayachain/ban/{address}NetworkApiconstantsGET/mayachain/constantsNetworkApiinbound_addressesGET/mayachain/inbound_addressesNetworkApilastblockGET/mayachain/lastblockNetworkApilastblock_chainGET/mayachain/lastblock/{chain}NetworkApinetworkGET/mayachain/networkNetworkApiragnarokGET/mayachain/ragnarokNetworkApiversionGET/mayachain/versionNodesApinodeGET/mayachain/node/{address}NodesApinodesGET/mayachain/nodesPOLApipolGET/mayachain/polPoolsApipoolGET/mayachain/pool/{asset}PoolsApipoolsGET/mayachain/poolsQueueApiqueueGET/mayachain/queueQueueApiqueue_outboundGET/mayachain/queue/outboundQueueApiqueue_scheduledGET/mayachain/queue/scheduledQuoteApiquotesaverdepositGET/mayachain/quote/saver/depositQuoteApiquotesaverwithdrawGET/mayachain/quote/saver/withdrawQuoteApiquoteswapGET/mayachain/quote/swapSaversApisaverGET/mayachain/pool/{asset}/saver/{address}SaversApisaversGET/mayachain/pool/{asset}/saversTSSApikeysignGET/mayachain/keysign/{height}TSSApikeysign_pubkeyGET/mayachain/keysign/{height}/{pubkey}TSSApimetricsGET/mayachain/metricsTSSApimetrics_keygenGET/mayachain/metric/keygen/{pubkey}TransactionsApitxGET/mayachain/tx/{hash}TransactionsApitx_signersGET/mayachain/tx/{hash}/signersVaultsApiasgardGET/mayachain/vaults/asgardVaultsApivaultGET/mayachain/vaults/{pubkey}VaultsApivault_pubkeysGET/mayachain/vaults/pubkeysVaultsApiyggdrasilGET/mayachain/vaults/yggdrasilDocumentation For ModelsBanResponseChainHeightCoinConstantsResponseInboundAddressInboundAddressesResponseKeygenMetricKeygenMetric1KeygenMetric2KeygenMetricsResponseKeysignInfoKeysignMetricsKeysignResponseLPBondedNodeLastBlockLastBlockResponseLiquidityProviderLiquidityProviderResponseLiquidityProviderSummaryLiquidityProvidersResponseMayanameMayaname1MayanameAliasMayanameResponseMetricsResponseMimirNodesResponseMimirResponseMimirVoteNetworkResponseNodeNodeBondProviderNodeBondProvidersNodeJailNodeKeygenMetricNodePreflightStatusNodePubKeySetNodeResponseNodesResponseObservedTxOutboundResponsePOLResponsePingPoolPoolResponsePoolsResponseQueueResponseQuoteFeesQuoteSaverDepositResponseQuoteSaverWithdrawResponseQuoteSwapResponseSaverSaverResponseSaversResponseScheduledResponseTssKeysignMetricTssMetricTxTxOutItemTxResponseTxSignersResponseVaultVaultAddressVaultInfoVaultPubkeysResponseVaultResponseVaultRouterVaultsResponseVersionResponseDocumentation For AuthorizationAll endpoints do not require authorization.Authordevs@mayachain.org"} +{"package": "xchainpy2-midgard", "pacakge-description": "xchainpy2-midgardThe Midgard Public API queries THORChain and any chains linked via the Bifr\u00f6st and prepares information about the network to be readily available for public users. The API parses transaction event data from THORChain and stores them in a time-series database to make time-dependent queries easy. Midgard does not hold critical information. To interact with THORChain protocol, users should query THORNode directly.This Python package is automatically generated by theSwagger Codegenproject:API version: 2.18.2Package version: 2.18.2Build package: io.swagger.codegen.v3.generators.python.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importxchainpy2_midgardSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxchainpy2_midgardGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportxchainpy2_midgardfromxchainpy2_midgard.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=xchainpy2_midgard.SpecificationApi(xchainpy2_midgard.ApiClient(configuration))try:# Documentationapi_instance.get_docs()exceptApiExceptionase:print(\"Exception when calling SpecificationApi->get_docs:%s\\n\"%e)# create an instance of the API classapi_instance=xchainpy2_midgard.SpecificationApi(xchainpy2_midgard.ApiClient(configuration))try:# Swagger Fileapi_instance.get_swagger()exceptApiExceptionase:print(\"Exception when calling SpecificationApi->get_swagger:%s\\n\"%e)Documentation for API EndpointsAll URIs are relative to/ClassMethodHTTP requestDescriptionSpecificationApiget_docsGET/v2/docDocumentationSpecificationApiget_swaggerGET/v2/swagger.jsonSwagger FileDefaultApiget_actionsGET/v2/actionsActions ListDefaultApiget_balanceGET/v2/balance/{address}Current balance for an addressDefaultApiget_borrower_detailGET/v2/borrower/{address}Borrower DetailsDefaultApiget_borrowers_addressesGET/v2/borrowersBorrowers ListDefaultApiget_churnsGET/v2/churnsChurns ListDefaultApiget_depth_historyGET/v2/history/depths/{pool}Depth and Price HistoryDefaultApiget_earnings_historyGET/v2/history/earningsEarnings HistoryDefaultApiget_healthGET/v2/healthHealth InfoDefaultApiget_known_poolsGET/v2/knownpoolsKnown Pools ListDefaultApiget_liquidity_historyGET/v2/history/liquidity_changesLiquidity Changes HistoryDefaultApiget_member_detailGET/v2/member/{address}Member DetailsDefaultApiget_members_adressesGET/v2/membersMembers ListDefaultApiget_network_dataGET/v2/networkNetwork DataDefaultApiget_nodesGET/v2/nodesNodes ListDefaultApiget_poolGET/v2/pool/{asset}Details of a PoolDefaultApiget_pool_statsGET/v2/pool/{asset}/statsPool StatisticsDefaultApiget_poolsGET/v2/poolsPools ListDefaultApiget_saver_detailGET/v2/saver/{address}Saver DetailsDefaultApiget_savers_historyGET/v2/history/savers/{pool}Savers Units and Depth HistoryDefaultApiget_statsGET/v2/statsGlobal StatsDefaultApiget_swap_historyGET/v2/history/swapsSwaps HistoryDefaultApiget_thor_name_detailGET/v2/thorname/lookup/{name}THORName DetailsDefaultApiget_thor_names_by_addressGET/v2/thorname/rlookup/{address}Gives a list of THORNames by reverse lookupDefaultApiget_thor_names_owner_by_addressGET/v2/thorname/owner/{address}THORName ownerDefaultApiget_tvl_historyGET/v2/history/tvlTotal Value Locked HistoryDocumentation For ModelsActionActionMetaAddLiquidityMetadataBalanceBlockRewardsBondMetricsBorrowerDetailsBorrowerPoolBorrowersChurnItemChurnsCoinCoinsDepthHistoryDepthHistoryIntervalsDepthHistoryItemDepthHistoryItemPoolDepthHistoryMetaEarningsHistoryEarningsHistoryIntervalsEarningsHistoryItemEarningsHistoryItemPoolGenesisInfHealthHeightTSInlineResponse200KnownPoolsLiquidityHistoryLiquidityHistoryIntervalsLiquidityHistoryItemMemberDetailsMemberPoolMembersMetadataNetworkNetworkFeesNodeNodesPoolDetailPoolDetailsPoolStatsDetailRefundMetadataReverseTHORNamesSaverDetailsSaverPoolSaversHistorySaversHistoryIntervalsSaversHistoryItemSaversHistoryMetaStatsDataStreamingSwapMetaSwapHistorySwapHistoryIntervalsSwapHistoryItemSwapMetadataTHORNameDetailsTHORNameEntryTVLHistoryTVLHistoryIntervalsTVLHistoryItemTransactionWithdrawMetadataDocumentation For AuthorizationAll endpoints do not require authorization.Authordevs@thorchain.org"} +{"package": "xchainpy2-thorchain", "pacakge-description": "@xchainjs/xchain-thorchainThorchain Module for XChainPY Clients"} +{"package": "xchainpy2-thornode", "pacakge-description": "xchainpy2-thornodeThornode REST API.This Python package is automatically generated by theSwagger Codegenproject:API version: 1.125.0Package version: 1.125.0Build package: io.swagger.codegen.v3.generators.python.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importxchainpy2_thornodeSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxchainpy2_thornodeGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportxchainpy2_thornodefromxchainpy2_thornode.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=xchainpy2_thornode.BlockApi(xchainpy2_thornode.ApiClient(configuration))height=789# int | optional block height, defaults to current tip (optional)try:api_response=api_instance.block(height=height)pprint(api_response)exceptApiExceptionase:print(\"Exception when calling BlockApi->block:%s\\n\"%e)Documentation for API EndpointsAll URIs are relative to/ClassMethodHTTP requestDescriptionBlockApiblockGET/thorchain/blockBorrowersApiborrowerGET/thorchain/pool/{asset}/borrower/{address}BorrowersApiborrowersGET/thorchain/pool/{asset}/borrowersCloutApiswapper_cloutGET/thorchain/clout/swap/{address}HealthApipingGET/thorchain/pingInvariantsApiinvariantGET/thorchain/invariant/{invariant}InvariantsApiinvariantsGET/thorchain/invariantsLiquidityProvidersApiliquidity_providerGET/thorchain/pool/{asset}/liquidity_provider/{address}LiquidityProvidersApiliquidity_providersGET/thorchain/pool/{asset}/liquidity_providersMimirApimimirGET/thorchain/mimirMimirApimimir_adminGET/thorchain/mimir/adminMimirApimimir_keyGET/thorchain/mimir/key/{key}MimirApimimir_nodeGET/thorchain/mimir/node/{address}MimirApimimir_nodesGET/thorchain/mimir/nodes_allMimirApimimir_v2GET/thorchain/mimirV2MimirApimimir_v2_idsGET/thorchain/mimirV2/idsNetworkApibanGET/thorchain/ban/{address}NetworkApiconstantsGET/thorchain/constantsNetworkApiinbound_addressesGET/thorchain/inbound_addressesNetworkApilastblockGET/thorchain/lastblockNetworkApilastblock_chainGET/thorchain/lastblock/{chain}NetworkApinetworkGET/thorchain/networkNetworkApiragnarokGET/thorchain/ragnarokNetworkApiversionGET/thorchain/versionNodesApinodeGET/thorchain/node/{address}NodesApinodesGET/thorchain/nodesPOLApipolGET/thorchain/polPoolsApidpoolGET/thorchain/dpool/{asset}PoolsApidpoolsGET/thorchain/dpoolsPoolsApipoolGET/thorchain/pool/{asset}PoolsApipoolsGET/thorchain/poolsQueueApiqueueGET/thorchain/queueQueueApiqueue_outboundGET/thorchain/queue/outboundQueueApiqueue_scheduledGET/thorchain/queue/scheduledQueueApiqueue_swapGET/thorchain/queue/swapQuoteApiquoteloancloseGET/thorchain/quote/loan/closeQuoteApiquoteloanopenGET/thorchain/quote/loan/openQuoteApiquotesaverdepositGET/thorchain/quote/saver/depositQuoteApiquotesaverwithdrawGET/thorchain/quote/saver/withdrawQuoteApiquoteswapGET/thorchain/quote/swapSaversApisaverGET/thorchain/pool/{asset}/saver/{address}SaversApisaversGET/thorchain/pool/{asset}/saversStreamingSwapApistream_swapGET/thorchain/swap/streaming/{hash}StreamingSwapApistream_swapsGET/thorchain/swaps/streamingTSSApikeysignGET/thorchain/keysign/{height}TSSApikeysign_pubkeyGET/thorchain/keysign/{height}/{pubkey}TSSApimetricsGET/thorchain/metricsTSSApimetrics_keygenGET/thorchain/metric/keygen/{pubkey}ThornamesApithornameGET/thorchain/thorname/{name}TransactionsApitxGET/thorchain/tx/{hash}TransactionsApitx_signersGET/thorchain/tx/details/{hash}TransactionsApitx_signers_oldGET/thorchain/tx/{hash}/signersTransactionsApitx_stagesGET/thorchain/tx/stages/{hash}TransactionsApitx_statusGET/thorchain/tx/status/{hash}VaultsApiasgardGET/thorchain/vaults/asgardVaultsApivaultGET/thorchain/vault/{pubkey}VaultsApivault_pubkeysGET/thorchain/vaults/pubkeysVaultsApiyggdrasilGET/thorchain/vaults/yggdrasilDocumentation For ModelsBanResponseBaseQuoteResponseBlockResponseBlockResponseHeaderBlockResponseHeaderVersionBlockResponseIdBlockResponseIdPartsBlockTxBlockTxResultBorrowerBorrowerResponseBorrowersResponseChainHeightCoinConstantsResponseDerivedPoolDerivedPoolResponseDerivedPoolsResponseInboundAddressInboundAddressesResponseInvariantResponseInvariantsResponseKeygenMetricKeygenMetricsResponseKeysignInfoKeysignMetricsKeysignResponseLastBlockLastBlockResponseLiquidityProviderLiquidityProviderResponseLiquidityProviderSummaryLiquidityProvidersResponseMetricsResponseMimirNodesResponseMimirResponseMimirV2IDsResponseMimirVoteMsgSwapNetworkResponseNodeNodeBondProviderNodeBondProvidersNodeJailNodeKeygenMetricNodePreflightStatusNodePubKeySetNodeResponseNodesResponseObservedTxOutboundResponsePOLResponsePingPoolPoolResponsePoolsResponseQueueResponseQuoteFeesQuoteLoanCloseResponseQuoteLoanOpenResponseQuoteSaverDepositResponseQuoteSaverWithdrawResponseQuoteSwapResponseSaverSaverResponseSaversResponseScheduledResponseStreamingSwapStreamingSwapResponseStreamingSwapsResponseSwapQueueResponseSwapperCloutResponseThornameThornameAliasThornameResponseTssKeysignMetricTssMetricTxTxDetailsResponseTxOutItemTxResponseTxSignersResponseTxStagesResponseTxStagesResponseInboundConfirmationCountedTxStagesResponseInboundFinalisedTxStagesResponseInboundObservedTxStagesResponseOutboundDelayTxStagesResponseOutboundSignedTxStagesResponseSwapFinalisedTxStagesResponseSwapStatusTxStagesResponseSwapStatusStreamingTxStatusResponseTxStatusResponsePlannedOutTxsVaultVaultAddressVaultInfoVaultPubkeysResponseVaultResponseVaultRouterVaultsResponseVersionResponseDocumentation For AuthorizationAll endpoints do not require authorization.Authordevs@thorchain.org"} +{"package": "xchainpy2-utils", "pacakge-description": "@xchainpy/xchain-utilUtility helpers for XChain clientsModules (in alphabetical order)asset- Utilities for handling assetsamount- Utilities for handling amountsInstallationpip install xchainpy-util"} +{"package": "xchainpy-binance", "pacakge-description": "xchainpy/xchainpy_binanceBinance Module for XChainPy ClientsModulesclient- Custom client for communicating with binance_chainmodels- model wrapper for binance_chain typesutil- Utitilies for using binance_chainFollowing dependencies have to be installed into your projectsecp256k1Crypto - py-binance-chain - pywallet - mnemonicpipinstallxchainpy_binanceBinance Client moduleInitialize a clientfromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClient# Note: This phrase is created by https://iancoleman.io/bip39/ and will never been used in a real-worldphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Mainnet,phrase=phrase))# if you want to change phrase after initialize the clientclient.set_phrase('wheel leg dune emerge sudden badge rough shine convince poet doll kiwi sleep labor hello')# if you want to change network after initialize the clientawaitclient.purge_client()client.set_network(Network.Mainnet)# get python-binance-chain clientclient.get_bnc_client()# when you are done with the client, call thisawaitclient.purge_client()Address methodsfromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Mainnet,phrase=phrase))address=client.get_address()is_valid=client.validate_address(address)# boolprint(address)print(is_valid)Feesfromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Mainnet,phrase=phrase))fees=awaitclient.get_fees()multi_send_fees=awaitclient.get_multi_send_fees()single_and_multi_fees=awaitclient.get_single_and_multi_fees()print(f'''fees:average:{fees.average}fast:{fees.fast}fastest:{fees.fastest}\\n''')print(f'''multi_send_fees:average:{multi_send_fees.average}fast:{multi_send_fees.fast}fastest:{multi_send_fees.fastest}\\n''')print(f'''single_and_multi_fees:single:average:{single_and_multi_fees['single'].average}fast:{single_and_multi_fees['single'].fast}fastest:{single_and_multi_fees['single'].fastest}multi:average:{single_and_multi_fees['single'].average}fast:{single_and_multi_fees['single'].fast}fastest:{single_and_multi_fees['single'].fastest}''')Balancefromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Testnet,phrase=phrase))address=client.get_address()account=awaitclient.get_account(address=address)balances=awaitclient.get_balance(address=address)forbalanceinbalances:print(f'asset:{balance.asset}, amount:{balance.amount}')Transactions and Transaction_datafromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientfromxchainpy_client.models.tx_typesimportTxHistoryParamsphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Testnet,phrase=phrase))address=client.get_address()params=TxHistoryParams(address=address,limit=1)transactions=awaitclient.get_transactions(params)# type of transactions is xchainpy_client.models.tx_types.TxPaget=transactions.txs[0]print(t.asset)print(t.tx_from[0].amount)print(t.tx_from[0].address)print(t.tx_to[0].amount)print(t.tx_to[0].address)print(t.tx_date)print(t.tx_type)print(t.tx_hash)transaction=awaitclient.get_transaction_data(t.tx_hash)# transaction object is equal by t objectTransferfromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientfromxchainpy_client.models.tx_typesimportTxParamsfromxchainpy_util.assetimportAssetBTCphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Testnet,phrase=phrase))address=client.get_address()params=TxParams(asset=AssetBNB,amount=0.0001,recipient=address,memo='memo')tx_hash=awaitclient.transfer(params)print(tx_hash)Explorer urlfromxchainpy_client.models.typesimportNetwork,XChainClientParamsfromxchainpy_binance.clientimportClientfromxchainpy_client.models.tx_typesimportTxParamsphrase='rural bright ball negative already grass good grant nation screen model pizza'client=Client(XChainClientParams(network=Network.Testnet,phrase=phrase))print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))awaitclient.purge_client()client.set_network(Network.Mainnet)print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))Crypto modulefrompy_binance_chain.environmentimportBinanceEnvironmentfromxchainpy_binanceimportcrypto# Note: This phrase is created by https://iancoleman.io/bip39/ and will never been used in a real-worldphrase='rural bright ball negative already grass good grant nation screen model pizza'env=BinanceEnvironment.get_testnet_env()seed=crypto.mnemonic_to_seed(mnemonic=phrase)print(seed)private_key=crypto.mnemonic_to_private_key(mnemonic=phrase,index=0,env=env)print(private_key)public_key=crypto.private_key_to_public_key(private_key=private_key)print(public_key)address=crypto.private_key_to_address(private_key=private_key,prefix='tbnb')print(address)address=crypto.public_key_to_address(public_key=public_key,prefix='tbnb')print(address)is_valid=crypto.check_address(address=address,prefix='tbnb')print(is_valid)TestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?$python-mpytestxchainpy/xchainpy_binance/tests"} +{"package": "xchainpy-bitcoin", "pacakge-description": "xchainpy/xchainpy_bitcoinBitcoin Module for XChainPy ClientsModulesclient- Custom client for communicating with bitcoinlibmodels- model wrapper for bitcoin required typesutil- Utitilies for using bitcoinlib and bitcoin chainFollowing dependencies have to be installed into your projectbip_utils, bitcoinlib , http3 , xchainpy_client , xchainpy_crypto , xchainpy_utilService ProvidersThis package uses the following service providers:FunctionServiceNotesBalancesSochainhttps://sochain.com/api#get-balanceTransaction historySochainhttps://sochain.com/api#get-display-data-address,https://sochain.com/api#get-txTransaction details by hashSochainhttps://sochain.com/api#get-txTransaction feesBitgohttps://app.bitgo.com/docs/#operation/v2.tx.getfeeestimateTransaction broadcastSochainhttps://sochain.com/api#send-transactionExplorerBlockstreamhttps://blockstream.infoSochain API rate limits:https://sochain.com/api#rate-limits(300 requests/minute)Installationpipinstallxchainpy_bitcoinBefore install the package on M1 Mac, execute these commands:brewinstallgmpopenblasopensslautoconfautomakelibffilibtoolpkg-configCFLAGS=-I/opt/homebrew/opt/gmp/includeLDFLAGS=-L/opt/homebrew/opt/gmp/libpip3installfastecdsaCFLAGS=-I$(brew--prefixopenssl)/includeLDFLAGS=-L$(brew--prefixopenssl)/libpip3installscryptexportOPENBLAS=\"$(brew--prefixopenblas)$OPENBLAS\"Bitcoin Client moduleInitialize a clientfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParams# Note: This phrase is created by https://iancoleman.io/bip39/ and will never been used in a real-worldphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoinClientParams(phrase=phrase,network=Network.Testnet))# if you want to change phrase after initialize the clientclient.set_phrase('caution pear excite vicious exotic slow elite marble attend science strategy rude')# if you want to change network after initialize the clientclient.purge_client()client.set_network(Network.Mainnet)# when you are done with the client, call thisclient.purge_client()Address methodsfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()is_valid=client.validate_address(client.network,address)# boolprint(address)print(is_valid)# change indexaddress=client.get_address(1)is_valid=client.validate_address(client.network,address)# boolprint(address)print(is_valid)Feesfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParamsclient=Client(BitcoinClientParams())# Get feeRate estimationsfee_rates=awaitclient.get_fee_rates()# Get fee estimationsfees=awaitclient.get_fees()# Get fee estimations with memomemo='SWAP:THOR.RUNE'fees_with_memo=awaitclient.get_fees(memo)print(f'''fee rates:average:{fee_rates.average}fast:{fee_rates.fast}fastest:{fee_rates.fastest}\\n''')print(f'''fees:average:{fees.average}fast:{fees.fast}fastest:{fees.fastest}\\n''')print(f'''fees with memo:average:{fees_with_memo.average}fast:{fees_with_memo.fast}fastest:{fees_with_memo.fastest}\\n''')Balancefromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()balance=awaitclient.get_balance(address=address)balance=balance[0]print(f'asset:{balance.asset}, amount:{balance.amount}')Transactions and Transaction_datafromxchainpy_client.models.tx_typesimportTxHistoryParamsfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=TxHistoryParams(address=address,limit=1)transactions=awaitclient.get_transactions(params)# type of transactions is xchainpy_client.models.tx_types.TxPaget=transactions.txs[0]print(t.asset)print(t.tx_from[0].amount)print(t.tx_from[0].address)print(t.tx_to[0].amount)print(t.tx_to[0].address)print(t.tx_date)print(t.tx_type)print(t.tx_hash)transaction=awaitclient.get_transaction_data(t.tx_hash)# transaction object is equal by t objectTransferfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParams,BitcoinTxParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=BitcoinTxParams(amount=0.0000001,recipient=address,memo='memo')tx_hash=awaitclient.transfer(params)print(tx_hash)Explorer urlfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoin.clientimportClientfromxchainpy_bitcoin.models.client_typesimportBitcoinClientParamsclient=Client(BitcoinClientParams())print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))client.purge_client()client.set_network(Network.Mainnet)print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))TestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?$python-mpytestxchainpy/xchainpy_bitcoin/tests"} +{"package": "xchainpy-bitcoincash", "pacakge-description": "xchainpy/xchain-bitcoincashBitcoin-Cash Module for XChainPy ClientsModulesclient- Custom client for communicating with bitcash , haskoin apimodels- Model wrapper for bitcoin-cash and haskoin required typesutil- Utitilies for using bitcash and haskoinFollowing dependencies have to be installed into your projectbitcash - cashaddress - mnemonic - bip_utilsService ProvidersThis package uses the following service providers:FunctionServiceNotesBalancesHaskoinhttps://api.haskoin.com/#/Address/getBalanceTransaction historyHaskoinhttps://api.haskoin.com/#/Address/getAddressTxsFullTransaction details by hashHaskoinhttps://api.haskoin.com/#/Transaction/TransactionTransaction feesBitgohttps://app.bitgo.com/docs/#operation/v2.tx.getfeeestimateTransaction broadcastbitcore.iohttps://api.bitcore.ioExplorerBlockchain.comhttps://www.blockchain.comHaskoin API rate limits: NoBitgo API rate limits:https://app.bitgo.com/docs/#section/Rate-Limiting(10 requests/second)Installationpipinstallxchainpy_bitcoincashBefore install the package on M1 Mac, execute these commands:brewinstallgmpopenblasopensslautoconfautomakelibffilibtoolpkg-configCFLAGS=-I/opt/homebrew/opt/gmp/includeLDFLAGS=-L/opt/homebrew/opt/gmp/libpip3installfastecdsaCFLAGS=-I$(brew--prefixopenssl)/includeLDFLAGS=-L$(brew--prefixopenssl)/libpip3installscryptexportOPENBLAS=\"$(brew--prefixopenblas)$OPENBLAS\"Bitcoincash Client moduleInitialize a clientfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParams# Note: This phrase is created by https://iancoleman.io/bip39/ and will never been used in a real-worldphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoincashClientParams(phrase=phrase,network=Network.Testnet))# if you want to change phrase after initialize the clientclient.set_phrase('caution pear excite vicious exotic slow elite marble attend science strategy rude')# if you want to change network after initialize the clientclient.purge_client()client.set_network(Network.Mainnet)# when you are done with the client, call thisclient.purge_client()Address methodsfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoincashClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()is_valid=client.validate_address(address)# boolprint(address)print(is_valid)# change indexaddress=client.get_address(1)is_valid=client.validate_address(address)# boolprint(address)print(is_valid)Feesfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParamsclient=Client(BitcoincashClientParams())# Get feeRate estimationsfee_rates=awaitclient.get_fee_rates()# Get fee estimationsfees=awaitclient.get_fees()# Get fee estimations with memomemo='SWAP:THOR.RUNE'fees_with_memo=awaitclient.get_fees(memo)print(f'''fee rates:average:{fee_rates.average}fast:{fee_rates.fast}fastest:{fee_rates.fastest}\\n''')print(f'''fees:average:{fees.average}fast:{fees.fast}fastest:{fees.fastest}\\n''')print(f'''fees with memo:average:{fees_with_memo.average}fast:{fees_with_memo.fast}fastest:{fees_with_memo.fastest}\\n''')Balancefromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoincashClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()balance=awaitclient.get_balance(address=address)balance=balance[0]print(f'asset:{balance.asset}, amount:{balance.amount}')Transactions and Transaction_datafromxchainpy_client.models.tx_typesimportTxHistoryParamsfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoincashClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=TxHistoryParams(address=address,limit=1)transactions=awaitclient.get_transactions(params)# type of transactions is xchainpy_client.models.tx_types.TxPaget=transactions.txs[0]print(t.asset)print(t.tx_from[0].amount)print(t.tx_from[0].address)print(t.tx_to[0].amount)print(t.tx_to[0].address)print(t.tx_date)print(t.tx_type)print(t.tx_hash)transaction=awaitclient.get_transaction_data(t.tx_hash)# transaction object is equal by t objectTransferfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParams,BitcoincashTxParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(BitcoincashClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=BitcoincashTxParams(amount=0.0000001,recipient=address,memo='memo')tx_hash=awaitclient.transfer(params)print(tx_hash)Explorer urlfromxchainpy_client.models.typesimportNetworkfromxchainpy_bitcoincash.clientimportClientfromxchainpy_bitcoincash.models.client_typesimportBitcoincashClientParamsclient=Client(BitcoincashClientParams())print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))client.purge_client()client.set_network(Network.Mainnet)print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))TestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?$python-mpytestxchainpy/xchainpy_bitcoincash/tests"} +{"package": "xchainpy-client", "pacakge-description": "XChainPy Wallet Client InterfaceA specification for a generalised interface for crypto wallets clients, to be used by XChainPy\nimplementations. The client should not have any functionality to generate a key, instead, theasgardex-cryptolibrary should be used to ensure cross-chain compatible keystores are handled. The client is only ever passed a master BIP39 phrase, from which a temporary key and address is decoded.ConfigurationInitialise and set up the client to connect to its necessary third-party services to fulfil basic functionality. The third-party services used must be at a minimum to fulfil the wallet functionality, such as displaying balances and sending transactions.During configuration, the following can be passed in:Network choice (default is TESTNET)Phrase (mandatory)Service Keys (optional, if null, client will use config defaults or free service limits.)QueryingQuerying the client for balances and transaction history. Transaction history is optional.Optional blockchain-specific queries can be added here, such as Binance Chain market information.TransactionsMaking transfers.Optional blockchain-specific transactions can be added here, such as Binance Chain freeze/unfreeze.Class VariablesClientClient Implementationclassclient(IXChainClient)NetworkNetwork types are'mainnet'and'testnet'stringsAddressPublic variable that returns the address decoded from the private key during initialisation. type of address isstrConfig and SetupSet NetworkUsed to set a type ofNetwork, which is either'mainnet'or'testnet'.set_network(net:str)Set PhraseUsed to set the master BIP39 phrase, from which the private key is extracted and the address decoded.set_phrase(phrase:str)->strThe function should store the private key and address, then return the address generated by the phrase.QueryingGet Explorer URLsReturns the correctly formatted url string with paths for:AddressesTransactionsThe default Explorer URL can be hard-coded, or passed in as a service. It will be provided byget_explorer_urlget_explorer_url()->strTo get explorer's URL for an address, useget_explorer_address_urlby passing anaddress.get_explorer_address_url=(address:str)->strTo get explorer's URL for a transaction, useget_explorer_tx_urlby passing a transaction ID.get_explorer_tx_url=(tx_id:str)->strAll functions should return the correctly formatted url string.Examplehttps://blockchair.com/bitcoin/transaction/d11ff3352c50b1f5c8e2030711702a2071ca0e65457b40e6e0bcbea99e5dc82e\nhttps://blockchair.com/bitcoin/address/19iqYbeATe4RxghQZJnYVFU4mjUUu76EA6\n\nhttps://explorer.binance.org/tx/94F3A6257337052B04F9CC09F657966BFBD88546CA5C23F47AB0A601D29D8979\nhttps://explorer.binance.org/address/bnb1z35wusfv8twfele77vddclka9z84ugywug48gn\n\nhttps://etherscan.io/tx/0x87a4fa498cc48874631eaa776e84a49d28f42f01e22c51ff7cdfe1f2f6772f67\nhttps://etherscan.io/address/0x8eb68e8f207be3dd1ec4baedf0b5c22245cda463Get BalanceReturns the balance of an address.If address is not passed, gets the balance of the current client address.Optional asset can be passed, in which the query will be specific to that asset, such as ERC-20 token.Returns an array of assets and amounts, with assets in chain notationCHAIN.SYMBOL-IDBalance model :get_balance(address:str=None,asset:str=None)->BalanceExample of third-party service queries to get balances:https://sochain.com/api/v2/get_address_balance/BTCTEST/tb1q2pkall6rf6v6j0cvpady05xhy37erndvku08wp\nhttps://api.ethplorer.io/getAddressInfo/0xb00E81207bcDA63c9E290E0b748252418818c869?apiKey=freekey\nhttps://dex.binance.org/api/v1/account/bnb1jxfh2g85q3v0tdq56fnevx6xcxtcnhtsmcu64mExample of returned array:[{# xchainpy_client.models.balance.Balanceasset:{# xchainpy_util.asset.Assetchain:\"BNB\",symbol:\"BNB\",ticker:\"BNB\"},amount:100000000}]Get TransactionsGets a simplied array of recent transactions for an address.# Defined in xchainpy_client/models/tx_types.pyclassTxHistoryParams:def__init__(self,address:str,offset:int=None,limit:int=None,start_time=None,asset:Asset=None):self._address=addressself._offset=offsetself._limit=limitself._start_time=start_timeself._asset=assetget_transactions(params:TxHistoryParams)->xchainpy_client.models.tx_types.TxPageExample of third party services to help:// get UTXOS for address\nhttps://sochain.com/api/v2/get_tx_unspent/BTC/34xp4vRoCGJym3xR7yCVPFHoCNxv4Twseo\n// get tx details\nhttps://sochain.com/api/v2/get_tx/BTC/ff0bd969cce99b8d8086e452d7b63167fc178680fee796fc742cb14a9a6ef929\n\nhttps://api.ethplorer.io/getAddressTransactions/0xb297cacf0f91c86dd9d2fb47c6d12783121ab780?apiKey=freekey\nhttps://dex.binance.org/api/v1/transactions?address=bnb1jxfh2g85q3v0tdq56fnevx6xcxtcnhtsmcu64mExample of return:[# xchainpy_client.models.tx_types.TxPagetotal:1,txs:[{# # xchainpy_client.models.tx_types.TXtx_hash:\"980D9519CCB39DC02F8B0208A4D181125EE8A2678B280AF70666288B62957DAE\",tx_from:[# xchainpy_client.models.tx_types.TxFrom{address:\"tbnb1t95kjgmjc045l2a728z02textadd98yt339jk7\",amount:100}],tx_to:[# xchainpy_client.models.tx_types.TxTo{address:\"tbnb1t95kjgmjc045l2a728z02textadd98yt339jk7\",amount:100}],tx_amount:100,tx_fee:2500,tx_memo:\"transfer\"tx_date:datetime.datetime(2021,8,2,12,50,10,407000),asset:{# xchainpy_util.asset.Assetchain:\"BNB\",symbol:\"BNB\",ticker:\"BNB\"},}]]Due to the complexity of this function and dependence of third-party services, this function can be omitted in early versions of the client.TransactionsGet FeesThis function calculates and returns the fee object in a generalised way for a simple transfer function.Since this depends on optional third-party services, sensible defaults should be hardcoded if there are errors.The fastest fee rate should be guaranteed next block (1.5x Fast), fast should be 1-2 blocks (1x next block fee rate), average should be 2-3 blocks (0.5x Fast).Don't over-complicate this. PoW blockchains have no guarantees.Type should specify the units to display, or if flat fees, simply \"flat\". The client should interpret and display this, such as showing the user the fee rates and their units.Fastest (target of next block)Fast (target of 1-2 blocks)Average (target of 2-3 blocks)Third party services:\nBitcoin - returns next block feeRate (fast). Use multiples of this to extrapolate to Fastest/Average.https://api.blockchair.com/bitcoin/statsEthereum - returns fastest/fast/averagehttps://ethgasstation.info/api/ethgasAPI.json?api-key=XXAPI_Key_HereXXXget_fees()->xchainpy_client.models.types.FeesExample# Binance Chain{# xchainpy_client.models.types.Feesfastest:0.0001125fast:0.0001125average:0.0001125}TransferGeneral transfer function that should be signed and broadcast using a third party service.\nThe fee should always berate, which is units per transaction size. The size should be calculated on the fly or hardcoded:Bitcoin: 250 bytes is typical, so feeRate of 10 is 10 sats per byte, eg, 2500 satsEthereum: gwei is standard, so a feeRate of 20 would be interpreted as 20 GWEIBinance Chain: fixed size, so the feeRate is ignored.Broadcast URLshttps://api.blockchair.com/{:chain}/push/transaction\nhttps://dex.binance.org/api/v1/broadcastclassTxParams:def__init__(self,asset:Asset,amount,recipient,memo='',wallet_index=None):self._asset=assetself._amount=amountself._recipient=recipientself._memo=memoself._wallet_index=wallet_indextransfer(params:tx_types.TxParams)->strThe function should return the hash of the finalised transaction.PurgeWhen a wallet is \"locked\" the private key should be purged in each client by setting it back to null. Also the phrase has to be clearedself.phrase = ''purge_client()"} +{"package": "xchainpy-crypto", "pacakge-description": "XCHAIN-CRYPTOThe XCHAIN CRYPTO package is a crypto package used by allXCHAINclients.XCHAIN-CRYPTO encrypts a master phrase to a keystore. This keystore can then be exported to other XCHAIN wallets or stored securely.Users can export their phrase and import them into other wallets since it is a BIP39 compatible phrase.DesignTypically keystore files encrypt aseedto a file, however this is not appropriate or UX friendly, since the phrase cannot be recovered after the fact.Crypto design:[entropy] -> [phrase] -> [seed] -> [privateKey] -> [publicKey] -> [address]Instead, XCHAIN-CRYPTO stores the phrase in a keystore file, then decrypts and passes this phrase to other clients:[keystore] -> XCHAIN-CRYPTO -> [phrase] -> ChainClientThe ChainClients can then convert this into their respective key-pairs and addresses.\nUsers can also export their phrases after the fact, ensuring they have saved it securely. This could enhance UX onboarding since users aren't forced to write their phrases down immediately for empty or test wallets.# Crypto Constants for xchainCIPHER=AES.MODE_CTRNBITS=128KDF=\"pbkdf2\"PRF=\"hmac-sha256\"DKLEN=32C=262144HASHFUNCTION=SHA256META=\"xchain-keystore\"Installationpipinstallxchainpy_cryptoBefore install the package on M1 Mac, execute this command:brewinstallautoconfautomakelibffilibtoolpkg-configUsageBasic usagefromxchainpy_crypto.cryptoimportvalidate_phrase,encrypt_to_keystore,decrypt_from_keystore,generate_mnemonicphrase=generate_mnemonic(size=12,language='english')print(phrase)is_correct=validate_phrase(phrase)print(is_correct)password='thorchain'keystore=awaitencrypt_to_keystore(phrase,password)phrase_decrypted=awaitdecrypt_from_keystore(keystore,password)print(phrase_decrypted)Keystore ModelclassKeystore:def__init__(self,crypto:CryptoStruct,id:str,version:int,meta:str):self._crypto=cryptoself._id=idself._version=versionself._meta=meta@classmethoddeffrom_dict(cls,keystore):new_keystore=cls.__new__(cls)forkeyinkeystore:setattr(new_keystore,key,keystore[key])returnnew_keystore@propertydefcrypto(self):returnself._crypto@crypto.setterdefcrypto(self,crypto):ifisinstance(crypto,dict):self._crypto=CryptoStruct.from_dict(crypto)else:self._crypto=crypto@propertydefid(self):returnself._id@id.setterdefid(self,id):self._id=id@propertydefversion(self):returnself._version@version.setterdefversion(self,version):self._version=version@propertydefmeta(self):returnself._meta@meta.setterdefmeta(self,meta):self._meta=metadefto_json(self):returnjson.dumps(self,default=lambdao:{key.lstrip('_'):valueforkey,valueino.__dict__.items()})CipherParamsclassCipherParams:def__init__(self,iv:str):self._iv=iv@classmethoddeffrom_dict(cls,cipherparams):new_cipherparams=cls.__new__(cls)forkeyincipherparams:setattr(new_cipherparams,key,cipherparams[key])returnnew_cipherparams@propertydefiv(self):returnself._iv@iv.setterdefiv(self,iv):self._iv=ivCryptoStructclassCryptoStruct:def__init__(self,cipher:int,ciphertext:str,cipherparams:CipherParams,kdf:str,kdfparams:KdfParams,mac:str,):self._cipher=cipherself._ciphertext=ciphertextself._cipherparams=cipherparamsself._kdf=kdfself._kdfparams=kdfparamsself._mac=mac@classmethoddeffrom_dict(cls,crypto):new_crypto=cls.__new__(cls)forkeyincrypto:setattr(new_crypto,key,crypto[key])returnnew_crypto@propertydefcipher(self):returnself._cipher@cipher.setterdefcipher(self,cipher):self._cipher=cipher@propertydefciphertext(self):returnself._ciphertext@ciphertext.setterdefciphertext(self,ciphertext):self._ciphertext=ciphertext@propertydefcipherparams(self):returnself._cipherparams@cipherparams.setterdefcipherparams(self,cipherparams):ifisinstance(cipherparams,dict):self._cipherparams=CipherParams.from_dict(cipherparams)else:self._cipherparams=cipherparams@propertydefkdf(self):returnself._kdf@kdf.setterdefkdf(self,kdf):self._kdf=kdf@propertydefkdfparams(self):returnself._kdfparams@kdfparams.setterdefkdfparams(self,kdfparams):ifisinstance(kdfparams,dict):self._kdfparams=KdfParams.from_dict(kdfparams)else:self._kdfparams=kdfparams@propertydefmac(self):returnself._mac@mac.setterdefmac(self,mac):self._mac=macKdfParamsclassKdfParams:def__init__(self,prf:str,dklen:int,salt:str,c:int):self._prf=prfself._dklen=dklenself._salt=saltself._c=c@classmethoddeffrom_dict(cls,kdfparams):new_kdfparams=cls.__new__(cls)forkeyinkdfparams:setattr(new_kdfparams,key,kdfparams[key])returnnew_kdfparams@propertydefprf(self):returnself._prf@prf.setterdefprf(self,prf):self._prf=prf@propertydefdklen(self):returnself._dklen@dklen.setterdefdklen(self,dklen):self._dklen=dklen@propertydefsalt(self):returnself._salt@salt.setterdefsalt(self,salt):self._salt=salt@propertydefc(self):returnself._c@c.setterdefc(self,c):self._c=cTestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?$python-mpytestxchainpy/xchainpy_crypto/tests"} +{"package": "xchainpy-ethereum", "pacakge-description": "xchainpy/xchainpy_ethereumEthereum Module for XChainPy ClientsEnvironmenttested with Python Virtual Environment 3.8 3.9Installationpython3 setup.py installService ProvidersInfura WSS APIwas used to interact with ethereum blockchain, head tohttps://infura.io/to get your own websocket token.If interaction withnon-ERC20 tokenis needed, head tohttps://etherscan.io/to get your etherscan token.Initialization of ClientPass in your infura WSS api token as network, and pass your ether token as ether_api (not enforced).Initialize mainnet client:client = Client(phrase=\"mnemonimic\", network=\"wss://mainnet.infura.io/ws/v3/...\", network_type=\"mainnet\", ether_api=\"...\")Initialize ropsten(testnet) client:client = Client(phrase=\"mnemonimic\", network=\"wss://ropsten.infura.io/ws/v3/...\", network_type=\"ropsten\", ether_api=\"...\")Head totest/test_ropsten_client.pyto see a\nmore comprehensive way to using this client.TestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?cd test/Ropsten$pytesttest_ropsten_client.pyMainnet$pytesttest_mainnet_client.py"} +{"package": "xchainpy-litecoin", "pacakge-description": "xchainpy/xchain-litecoinLitecoin Module for XChainPy ClientsModulesclient- Custom client for communicating with bitcoinlib , sochain apimodels- Model wrapper for litecoin and sochain required typesutil- Utitilies for using bitcoinlib and sochainFollowing dependencies have to be installed into your projectbip_utils, bitcoinlib , xchainpy_client , xchainpy_crypto , xchainpy_util , http3Service ProvidersThis package uses the following service providers:FunctionServiceNotesBalancesSochainhttps://sochain.com/api#get-balanceTransaction historySochainhttps://sochain.com/api#get-display-data-address,https://sochain.com/api#get-txTransaction details by hashSochainhttps://sochain.com/api#get-txTransaction feesBitgohttps://app.bitgo.com/docs/#operation/v2.tx.getfeeestimateExplorerBitapshttps://ltc.bitaps.comTransaction broadcastSochainhttps://sochain.com/api/#send-transactionSochain API rate limits:https://sochain.com/api#rate-limits(300 requests/minute)Bitgo API rate limits:https://app.bitgo.com/docs/#section/Rate-Limiting(10 requests/second)Litecoin Client moduleInitialize a clientfromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParams# Note: This phrase is created by https://iancoleman.io/bip39/ and will never been used in a real-worldphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(LitecoinClientParams(phrase=phrase,network=Network.Testnet))# if you want to change phrase after initialize the clientclient.set_phrase('caution pear excite vicious exotic slow elite marble attend science strategy rude')# if you want to change network after initialize the clientclient.purge_client()client.set_network(Network.Mainnet)# when you are done with the client, call thisclient.purge_client()Address methodsfromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(LitecoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()is_valid=client.validate_address(client.network,address)# boolprint(address)print(is_valid)# change indexaddress=client.get_address(1)is_valid=client.validate_address(client.network,address)# boolprint(address)print(is_valid)Feesfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParamsclient=Client(LitecoinClientParams())# Get feeRate estimationsfee_rates=awaitclient.get_fee_rates()# Get fee estimationsfees=awaitclient.get_fees()# Get fee estimations with memomemo='SWAP:THOR.RUNE'fees_with_memo=awaitclient.get_fees(memo)print(f'''fee rates:average:{fee_rates.average}fast:{fee_rates.fast}fastest:{fee_rates.fastest}\\n''')print(f'''fees:average:{fees.average}fast:{fees.fast}fastest:{fees.fastest}\\n''')print(f'''fees with memo:average:{fees_with_memo.average}fast:{fees_with_memo.fast}fastest:{fees_with_memo.fastest}\\n''')Balancefromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(LitecoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()balance=awaitclient.get_balance(address=address)balance=balance[0]print(f'asset:{balance.asset}, amount:{balance.amount}')Transactions and Transaction_datafromxchainpy_client.models.tx_typesimportTxHistoryParamsfromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(LitecoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=TxHistoryParams(address=address,limit=1)transactions=awaitclient.get_transactions(params)# type of transactions is xchainpy_client.models.tx_types.TxPaget=transactions.txs[0]print(t.asset)print(t.tx_from[0].amount)print(t.tx_from[0].address)print(t.tx_to[0].amount)print(t.tx_to[0].address)print(t.tx_date)print(t.tx_type)print(t.tx_hash)transaction=awaitclient.get_transaction_data(t.tx_hash)# transaction object is equal by t objectTransferfromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParams,LitecoinTxParamsphrase='atom green various power must another rent imitate gadget creek fat then'client=Client(LitecoinClientParams(phrase=phrase,network=Network.Testnet))address=client.get_address()params=LitecoinTxParams(amount=0.0000001,recipient=address,memo='memo')tx_hash=awaitclient.transfer(params)print(tx_hash)Explorer urlfromxchainpy_client.models.typesimportNetworkfromxchainpy_litecoin.clientimportClientfromxchainpy_litecoin.models.client_typesimportLitecoinClientParamsclient=Client(LitecoinClientParams())print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))client.purge_client()client.set_network(Network.Mainnet)print(client.get_explorer_url())print(client.get_explorer_address_url('testAddressHere'))print(client.get_explorer_tx_url('testTxHere'))TestsThese packages needed to run tests:pytestpip install pytestpytest-asynciopip install pytest-asyncioHow to run test ?$python-mpytestxchainpy/xchainpy_litecoin/tests"} +{"package": "xchainpy-thorchain", "pacakge-description": "xchainpy-thorchainThorchain wrapperTestingNeed this packages before using unit testing:pytestpytest-asyncioInstallation with pip :$pipinstallpytest\n$pipinstallpytest-asyncioTesting :$python-mpytestxchainpy/xchainpy_thorchain/test/test_clients.pycan use other parameter like-rPor-rxfor sysout"} +{"package": "xchainpy-util", "pacakge-description": "xchainpy/xchainpy-utilUtitity helpers for XChain clientsModules (in alphabetical order)asset- Utilities for handling assetschain- Utilities for multi-chainUsagepipinstallxchainpy_utilAssetfromxchainpy_util.assetimportAssetasset=Asset(chain='BNB',symbol='RUNE-67C')print(asset.chain)print(asset.symbol)print(asset.ticker)asset=Asset(chain='BNB',symbol='RUNE-67C',ticker='RUNE')print(asset)Chainfromxchainpy_utilimportchainfromxchainpy_util.chainimportChainis_chain=chain.is_chain(Chain.Binance)print(is_chain)is_chain=chain.is_chain('BNB')print(is_chain)TestsThese packages needed to run tests:pytestpip install pytestHow to run tests?$python-mpytestxchainpy/xchainpy_util/tests"} +{"package": "xchange", "pacakge-description": "xchangeMany cryptocurrency exchange APIs, a single and unified API client \ud83d\ude4cInstallationThe project is hosted in PyPi, and you can install it usingpiporpip3:pip3 install xchangeExample of usage>>>importos>>>fromxchange.factoriesimportExchangeClientFactory>>>fromxchange.constantsimportexchanges,currencies# construct your API client>>>ClientClass=ExchangeClientFactory.get_client(exchanges.KRAKEN)>>>client=ClientClass(**{...\"api_key\":os.environ.get('KRAKEN_KEY'),...\"api_secret\":os.environ.get('KRAKEN_SECRET')...})# request API resources in an unified way>>>ticker=client.get_ticker(currencies.BTC_USD)>>>ticker{'ask':Decimal('8590.00000'),'bid':Decimal('8589.90000'),'low':Decimal('8317.90000'),'high':Decimal('8610.00000'),'last':Decimal('8590.00000'),'volume':Decimal('1856.51064490')}# API responses are wrapped into normalized models>>>type(ticker)# dynamic attribute assignation of response fields>>>ticker.lastDecimal('8638.10000')Polymorphic requests>>>forexchangeinexchanges.EXCHANGES:...client=ExchangeClientFactory.get_client(exchange)(**{...\"api_key\":\"YOUR_KEY\",...\"api_secret\":\"YOUR_SECRET\"...})...ticker=client.get_ticker(currencies.BTC_USD)...print(\"%s: $%d\"%(exchange,ticker.last))...bitfinex:$8633okex:$8749kraken:$8633"} +{"package": "xchange-mail", "pacakge-description": "\ud83d\udce7 Sending emails with basic formatting using exchangelib \ud83d\udce7Table of contentsAbout xchange_mailPackage StructureInstalling the PackageExamplesContributionSocial MediaAbout xchange_mailThis python package was build for making the mail sending processing through exchangelib a little bit easier. The idea is to create some custom functions for a limited use cases, so the user won't need to configure or define details on Account or Config exchangelib classes, but rather execute basic functions for sending basic emails.Theexamplessection will clarify some use cases ofxchange_mailpackage for helping users to send basic emails through MS Exchange. Keep watching this documentation.Package StructureAt this time, the package is built around just one module calledmail. This module contains some functions for helping users connecting with Exchange server and also sending basic mails with plain text or HTML body messages. The table below has the explanation of the main componentes of thismailmodule.FunctionShort Descriptionconnect_exchange()Receives some user credentials for connecting to Exchange and returning an Account objectattach_file()Stores a pandas DataFrame object on buffers and returns a two-elements list containing the attach name and the attach objectformat_mail_body()Creates a HTMLBody object. If a DataFrame is passed as an argument, it usespretty_html_tablepackage for customizing a table before creating the HTMLBodysend_simple_mail()Sends a simple mail through exchange with possibilities for attaching one file, sending a DataFrame object on mail body, sending an image on mail body or attached or using html code for customizing mailsend_mail_mult_files()Can send multiple files attached or multiple DataFrames on bodyBiblioteca python constru\u00edda para facilitar o gerenciamento e envio de e-mails utilizando a bibliotecaexchangelibcomo ORM da caixa de e-mails Exchange.Installing the PackageThe latest version ofxchange_mailpackage are published and available onPyPI repository:pushpin:Note:as a good practice for every Python project, the creation of avirtual environmentis needed to get a full control of dependencies and third part packages on your code. By this way, the code below can be used for creating a new venv on your OS.# Creating and activating venv on Linux$python-mvenv/\n$source//bin/activate# Creating and activating venv on Windows$python-mvenv/\n$//Scripts/activateWith the new venv active, all you need is execute the code below using pip for installing the package (upgrading pip is optional):$pipinstall--upgradepip\n$pipinstallxchange_mailThe xchange_mail package is built in an upper layer above some other python packages like exchangelib and pandas. So, when installing mlcomposer, the pip utility will also install all dependencies linked to the package.ExamplesAfter introducing the package, it's time to explain it in a deeper way: through examples. On this Github repository, it's possible to find some good uses of xchange_mail onexamples/folder. In practice, for sending a basic email it's possible to execute thesend_simple_mail()function with few parameter configuration as seen below:fromxchange_mail.mailimportsend_simple_mail# Extracting environment variables from a .env file (optional)USERNAME=os.getenv('MAIL_FROM')PWD=os.getenv('PASSWORD')SERVER='outlook.office365.com'MAIL_BOX=os.getenv('MAIL_BOX')MAIL_TO=os.getenv('MAIL_TO')# Sending a basic mailsend_simple_mail(username=USERNAME,password=PWD,server=SERVER,mail_box=MAIL_BOX,subject='This is a xchange_mail test',mail_body='Testing the package by sending a simple mail',mail_signature='Regards, xchange_mail developers',mail_to=MAIL_TO)Done! Almost all other package features are built around thissend_simple_mail()function and the other one calledsend_mail_mult_files(). Just to clarify, there are some parameters that can be set on the function above for sending a pandas DataFrame attached on mail body, for example. There is also a feature for sending an image embedding on mail body. The code below is an example of sending a simple mail with a DataFrame object attached, on mail body with an image saved locally.importpandasaspdfromxchange_mail.mailimportsend_simple_mail# Extracting environment variables from a .env file (optional)USERNAME=os.getenv('MAIL_FROM')PWD=os.getenv('PASSWORD')SERVER='outlook.office365.com'MAIL_BOX=os.getenv('MAIL_BOX')MAIL_TO=os.getenv('MAIL_TO')# Sending a basic mailsend_simple_mail(username=USERNAME,password=PWD,server=SERVER,mail_box=MAIL_BOX,subject='This is a xchange_mail test',mail_body='Testing the package by sending a simple mail',mail_signature='Regards, xchange_mail developers',mail_to=MAIL_TO,df_on_body=True,df_on_attachment=True,df=df,attachment_filename='pandas_dataframe.csv',image_on_body=True,image_location='/home/user/image_dir/image.png')For new use cases, please take a look atexamples/folder on this repository.ContributionThe xchange_mail python package is an open source implementation and the more people use it, the more happy the developers will be. So if you want to contribute with xchange_mail, please feel free to follow the best practices for implementing coding on this github repository through creating new branches, making merge requests and pointig out whenever you think there is a new topic to explore or a bug to be fixed.Thank you very much for reaching this and it will be a pleasure to have you as xchange_mail user or developer.Social MediaFollow me on LinkedIn:https://www.linkedin.com/in/thiago-panini/See my other Python packages:https://github.com/ThiagoPanini"} +{"package": "xchanger-suite-integration", "pacakge-description": "xchanger_suite_integrationThis package facilitates integrating Xchanger Suite capabilities with applications using Python"} +{"package": "xchat", "pacakge-description": "\ud83d\udd25xchat\ud83d\udd25Installpipinstall-UxchatDocsUsagesimport xchatTODO"} +{"package": "xchatbot", "pacakge-description": "The Xtensible XMPP Chat BotXChatBotis a xmpp bot library written in python using thenbxmpp library from Gajimhttps://xchatbot.readthedocs.io/requirementspython 3pygobjectnbxmppoptionallypipenvinstallpip install xchatbotgitgit clone https://git.sr.ht/~fabrixxm/xchatbotinstall required packages:with pipenv$ pipenv --site-packages --python 3\n$ pipenv install\n$ pipenv run ./xchatbot.pyon osxyou need first to install python3 with brew:$ brew install python3 pipenv pygobject3 libsoupon Arch# pacman -S python-gobject python-nbxmppon Debian# apt install python3-gi python3-nbxmpp"} +{"package": "xchembku", "pacakge-description": "xchembkuXChem Business Knowledge Unit. Service, Client, API, persistent store.Database service for other XChem Lifesupport services.For documentation see:https://diamondlightsource.github.io/xchembku"} +{"package": "xchem-chimp", "pacakge-description": "CHiMP (Crystal Hits in My Plate) is a deep learning system to help researchers work with micrographs of protein crystallisation experiments. XChem CHiMP consists of one component:1.CHiMP Detector. This uses an object detection network to find the position of any crystals and drops in the image and uses this information to\ncalculate a coordinate for dispensing compound using the Echo.Installationpip install chimpflow\n\nchimpflow --versionModel file for xchem-chimpThe model file is saved in:https://gitlab.diamond.ac.uk/xchem/xchem-chimp-modelsThis file is too large for github.For GitHub pytest to find the file in its CI/CD Actions, this file has been uploaded to zenodo:https://zenodo.org/record/7810708/2022-12-07_CHiMP_Mask_R_CNN_XChem_50eph_VMXi_finetune_DICT_NZ.pytorchThe tests/conftest.py fetches this file automatically.Runningrm -rf detector_output\npython -m detect_folder_chimp \\\n --echo --preview \\\n --num_classes=3 \\\n --MODEL_PATH=src/xchem_chimp/detector/model/2022-12-07_CHiMP_Mask_R_CNN_XChem_50eph_VMXi_finetune_DICT_NZ.pytorch \\\n --IMAGE_PATH=tests/SubwellImages/97wo_2021-09-14_RI1000-0276-3dropyou can expect something like:20-Mar-23 08:09:21 - INFO - Loading libraries...\n20-Mar-23 08:09:21 - DEBUG - Loading model from src/xchem_chimp/detector/model/2022-12-07_CHiMP_Mask_R_CNN_XChem_50eph_VMXi_finetune_DICT_NZ.pytorch\n20-Mar-23 08:09:21 - INFO - Making directory for detector output: /27/xchem-chimp/detector_output\n20-Mar-23 08:09:21 - DEBUG - extracting coordinates...\n20-Mar-23 08:09:25 - DEBUG - create_detector_output_dict: 97wo_01A_1.jpg - Number of objects found: 33\n20-Mar-23 08:09:25 - DEBUG - 1 drops, 32 crystals over prob threshold\n20-Mar-23 08:09:26 - DEBUG - Extracting Echo coordinate from distance transform.\n20-Mar-23 08:09:27 - DEBUG - Calculating well centroids...\n20-Mar-23 08:09:27 - DEBUG - Loading background images\n20-Mar-23 08:09:27 - DEBUG - Well centroid found at (504, 600)Development questionsIs the folder src/xchem_chimp/detector/background_images needed in the distribution?Where best to put model_file for unit testing?Is torchvision a necessary dependency for runtime?How are the model files built?Why are there so many mypy problems in coord_generator.py and detector_utils.py?How significant is this: DeprecationWarning: Please use gaussian_filter from the scipy.ndimage namespace, the scipy.ndimage.filters namespace is deprecated.Do we need to keep anything in the zocalo directory?Is there some example image where target_position is properly calculated?DocumentationSeehttps://www.cs.diamond.ac.uk/chimpflowfor more detailed documentation.Building and viewing the documents locally:git clone git+https://gitlab.diamond.ac.uk/scisoft/bxflow/chimpflow.git\ncd chimpflow\nvirtualenv /scratch/$USER/venv/chimpflow\nsource /scratch/$USER/venv/chimpflow/bin/activate\npip install -e .[dev]\nmake -f .chimpflow/Makefile validate_docs\nbrowse to file:///scratch/$USER/venvs/chimpflow/build/html/index.htmlTopics for further documentation:TODO list of improvementschange log"} +{"package": "xchem-db", "pacakge-description": "=====XChemDB=====This is a simple Django app to get a RESTFul API of XChem data.Detailed documentation is in the \"docs\" directory.Quick start-----------1. Add \"xchem_db\" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [...'xchem_db',]2. Run `python manage.py migrate` to create the xchem_db models."} +{"package": "xchem-ot", "pacakge-description": "No description available on PyPI."} +{"package": "xcherryapi", "pacakge-description": "xcherryapiThis APIs between xCherry service and SDKsThis Python package is automatically generated by theOpenAPI Generatorproject:API version: 0.0.3Package version: 0.0.3Build package: org.openapitools.codegen.languages.PythonClientCodegenRequirements.Python 3.7+Installation & Usagepip installIf the python package is hosted on a repository, you can install directly using:pipinstallgit+https://github.com/xcherryio/apis.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/xcherryio/apis.git)Then import the package:importxcherryapiSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxcherryapiTestsExecutepytestto run the tests.Getting StartedPlease follow theinstallation procedureand then run the following:importtimeimportxcherryapifromxcherryapi.restimportApiExceptionfrompprintimportpprint# Defining the host is optional and defaults to http://localhost# See configuration.py for a list of all supported configuration parameters.configuration=xcherryapi.Configuration(host=\"http://localhost\")# Enter a context with an instance of the API clientwithxcherryapi.ApiClient(configuration)asapi_client:# Create an instance of the API classapi_instance=xcherryapi.DefaultApi(api_client)process_execution_describe_request=xcherryapi.ProcessExecutionDescribeRequest()# ProcessExecutionDescribeRequest | (optional)try:# describe a process executionapi_response=api_instance.api_v1_xcherry_service_process_execution_describe_post(process_execution_describe_request=process_execution_describe_request)print(\"The response of DefaultApi->api_v1_xcherry_service_process_execution_describe_post:\\n\")pprint(api_response)exceptApiExceptionase:print(\"Exception when calling DefaultApi->api_v1_xcherry_service_process_execution_describe_post:%s\\n\"%e)Documentation for API EndpointsAll URIs are relative tohttp://localhostClassMethodHTTP requestDescriptionDefaultApiapi_v1_xcherry_service_process_execution_describe_postPOST/api/v1/xcherry/service/process-execution/describedescribe a process executionDefaultApiapi_v1_xcherry_service_process_execution_publish_to_local_queue_postPOST/api/v1/xcherry/service/process-execution/publish-to-local-queuesend message(s) to be consumed within a single process executionDefaultApiapi_v1_xcherry_service_process_execution_rpc_postPOST/api/v1/xcherry/service/process-execution/rpcexecute a RPC method of a process executionDefaultApiapi_v1_xcherry_service_process_execution_start_postPOST/api/v1/xcherry/service/process-execution/startstart a process executionDefaultApiapi_v1_xcherry_service_process_execution_stop_postPOST/api/v1/xcherry/service/process-execution/stopstop a process executionDefaultApiapi_v1_xcherry_worker_async_state_execute_postPOST/api/v1/xcherry/worker/async-state/executeinvoking AsyncState.execute APIDefaultApiapi_v1_xcherry_worker_async_state_wait_until_postPOST/api/v1/xcherry/worker/async-state/wait-untilinvoking AsyncState.waitUntil APIDefaultApiapi_v1_xcherry_worker_process_rpc_postPOST/api/v1/xcherry/worker/process/rpcexecute a RPC method of a process execution in the workerDefaultApiinternal_api_v1_xcherry_notify_immediate_tasks_postPOST/internal/api/v1/xcherry/notify-immediate-tasksfor api service to tell async service that there are new immediate tasks added to the queueDefaultApiinternal_api_v1_xcherry_notify_timer_tasks_postPOST/internal/api/v1/xcherry/notify-timer-tasksfor api service to tell async service that there are new timer tasks added to the queueDocumentation For ModelsApiErrorResponseAppDatabaseColumnValueAppDatabaseConfigAppDatabaseErrorAppDatabaseErrorHandlingAppDatabaseReadRequestAppDatabaseReadResponseAppDatabaseRowReadResponseAppDatabaseRowWriteAppDatabaseTableConfigAppDatabaseTableReadRequestAppDatabaseTableReadResponseAppDatabaseTableRowSelectorAppDatabaseTableWriteAppDatabaseWriteAsyncStateConfigAsyncStateExecuteRequestAsyncStateExecuteResponseAsyncStateWaitUntilRequestAsyncStateWaitUntilResponseCommandRequestCommandResultsCommandStatusCommandWaitingTypeContextDatabaseLockingTypeEncodedObjectErrorSubTypeKeyValueLoadLocalAttributesRequestLoadLocalAttributesResponseLocalAttributeConfigLocalQueueCommandLocalQueueMessageLocalQueueMessageResultLocalQueueResultNotifyImmediateTasksRequestNotifyTimerTasksRequestProcessExecutionDescribeRequestProcessExecutionDescribeResponseProcessExecutionRpcRequestProcessExecutionRpcResponseProcessExecutionStartRequestProcessExecutionStartResponseProcessExecutionStopRequestProcessExecutionStopTypeProcessIdReusePolicyProcessRpcWorkerRequestProcessRpcWorkerResponseProcessStartConfigProcessStatusPublishToLocalQueueRequestRetryPolicyStateDecisionStateFailureRecoveryOptionsStateFailureRecoveryPolicyStateMovementThreadCloseDecisionThreadCloseTypeTimerCommandTimerResultWorkerApiTypeWorkerErrorResponseWriteConflictModeDocumentation For AuthorizationEndpoints do not require authorization.Author"} +{"package": "xchg", "pacakge-description": "Exchange SimulatorSimulator of a currency exchange. Key features:Very minimalistic (300 lines in code), written in a functional style;You can download a sample data from poloniex.com or provide your data in .csv files;You can set an initial balance, use basic functions like buy, sell, go to the next time step;More advanced features like a total capital calculation, and make portfolio, more about that at the link below;Trading fees and minimum order amounts are supported.Full API documentation is here:https://sergei-bondarenko.github.io/xchg/Quick startThe package is available onpypi.org, so you can install it via pip:pipinstallxchgThen we need a market data. For tutorial purposes you can download it with this command which will be available after package installation:download_candlesIt will download 50 candles for ETC, ETH, LTC and XMR cryptocurrencies frompoloniex.comexchange and put it insample_data/directory in the current path. Or you can downloadsample_data/directory from this repository.Later you can view these .csv files and use your own data in the same format. You can have a different number of currecies, and different set of columns. The only mandatory column is \"close\" price, as it will used for trading. Just ensure that you have the same time range for different currencies and have no gaps in data.Prices in .csv files are expressed in a base currency, which will be calledcash(if you are curious, in the sample data cash currency is BTC).Now let's trade!fromxchgimportXchg# Set an initial balance. Let's set that we have only cash currency at the# start.balance={'cash':100,'ETC':0,'ETH':0,'LTC':0,'XMR':0}# Set a trading fee which will be paid for each buy or sell trade (in this# example it's 1%). You can set 0 if you don't want any fee to be paid.fee=0.01# Set a minimum order size expressed in a cash currency. You can not place# orders less than that value. You can use also set 0 here if you don't# want to limit a minimum order size.min_order_size=0.001# Create an exchange.ex=Xchg(fee,min_order_size,data_path='sample_data/',balance=balance)# Let's buy some coins.ex=ex.buy('ETC',7500)ex=ex.buy('LTC',15000)print(ex.balance)# Output: {'cash': 2.2024749999999926, 'ETC': 7425.0, 'ETH': 0.0, 'LTC': 14850.0, 'XMR': 0.0}# All done, now we want to wait for 30 time periods.for_inrange(30):ex=ex.next_step()# Now we want to sell.ex=ex.sell('ETC',7425)ex=ex.sell('LTC',14850)print(ex.balance)# Output: {'cash': 101.1232084225, 'ETC': 0.0, 'ETH': 0.0, 'LTC': 0.0, 'XMR': 0.0}# We made more than 1 BTC profit, yay!For developersInstall testing modules:pipinstallpytestpytest-flake8pytest-covUse the following command to run tests locally:pytest--flake8--cov=xchg--cov-reportterm-missing-vvvAnd do not forget to increase a version inxchg/__init__.pybefore commiting."} +{"package": "xchk-core", "pacakge-description": "No description available on PyPI."} +{"package": "xchk-git-content", "pacakge-description": "No description available on PyPI."} +{"package": "xchk-multiple-choice-strategies", "pacakge-description": "No description available on PyPI."} +{"package": "xchk-mysql-comparison-strategies", "pacakge-description": "No description available on PyPI."} +{"package": "xchk-regex-strategies", "pacakge-description": "No description available on PyPI."} +{"package": "xchk-tmux-content", "pacakge-description": "No description available on PyPI."} +{"package": "xchrome", "pacakge-description": "Decrypto chrome saved passwords.."} +{"package": "xchtools", "pacakge-description": "ConfigIn your own project, there should be asettings.tomland a.envfile.settings.tomlstores the common config.To use connections module,[default.db]is a must..envstores secret things like passwords.Usageconnections modulemysqldb connection example toml:[default.db]host=\"replace with your host\"port=3306user=\"root\"password=\"@format {env[MYSQLDB_PASSWORD]}\"Usage in your code:fromxchtoolsimportXCHConnectionsxc=XCHConnections(os.path.dirname(os.path.abspath(__file__)))config=xc.settingsprint(config.db)xc.sql2df(\"show databases\")For developerBuild and ReleaseConfig pypi API tokenpoetry config pypi-token.pypi poetry buildpoetry publish"} +{"package": "xc_ip_info", "pacakge-description": "===================ip_info\uff1a\u83b7\u53d6ip\u4fe1\u606f===================\u63cf\u8ff0\uff1a\u5f53\u524d\u6700\u53f3\u4f1a\u5bf9\u7528\u6237ip\u8fdb\u884c\u5730\u57df\u8bc6\u522b\uff0c\u5728\u654f\u611f\u65f6\u671f\u53ef\u80fd\u4f1a\u5bf9\u67d0\u4e9b\u7279\u5b9a\u7684\u5730\u533a\u3001\u7701\u4efd\u3001\u56fd\u5bb6\u7684ip\u505a\u7279\u6b8a\u7684\u6807\u8bb0\u5904\u7406\u3002\u8bf4\u660e\uff1a\u5f53\u524d\u6b64\u9879\u76ee\u7528\u5230\u4e86ipip\u4e0a\u7684\u514d\u8d39\u7248ip\u9274\u5b9a\u672c\u5730\u5305\uff0c\u5bf9\u4e8e\u65e0\u6cd5\u9274\u5b9a\u7684ip\u518d\u7528\u6dd8\u5b9dip\u514d\u8d39ip\u9274\u5b9a\u63a5\u53e3\u52a0\u4ee5\u8f85\u52a9\u3002\u4f7f\u7528\uff1afrom xc_ip_info.ip_info import IPSearcherIPSearcher.search('123.125.71.38')IPSearcher.validate('61.128.101.255')\u5373\u53ef\uff0c\u5177\u4f53case\u53ef\u4ee5\u89c1test\u4e0b\u6d4b\u8bd5\u7528\u4f8b\u3002\u5b89\u88c5\uff1a\u7528\u7684\u662f\u6700\u5185\u5185\u90e8\u7684\u79c1\u6709pip\u670d\u52a1\u5668\u3002\u56e0\u6b64\u9700\u8981\u5728\u5185\u7f51\u73af\u5883\u4e0b\u5b89\u88c5\u3002\u7b2c\u4e00\u6b21\uff1asudo pip install xc_ip_info -i 'http://172.16.111.203:8081' --trusted-host '172.16.111.203'\u4e4b\u540e\uff1asudo pip install --upgrade xc_ip_info -i 'http://172.16.111.203:8081' --trusted-host '172.16.111.203'\u56de\u6eda\u5230\u67d0\u4e2a\u7248\u672c\uff1asudo pip install xc_ip_info==0.5 -i 'http://172.16.0.173:8080' --trusted-host '172.16.0.173'\u67e5\u770b\u6240\u6709\u7248\u672c\u4fe1\u606f\u7684web\u524d\u7aef\u8bbf\u95ee\uff1ahttp://172.16.0.173:8080\u4e0a\u4f20\uff1a1.\u9996\u5148\u9700\u8981\u83b7\u53d6\u4f60\u7684\u79c1\u6709pypi\u8d26\u6237\u548c\u5bc6\u7801\uff0c\u53ef\u4ee5\u627eop\u6743\u6d32\u30022.\u4fee\u6539\u4f60\u7684~/.pypirc\uff0c\u6700\u7b80\u5355\u7684\u5305\u62ec\u5982\u4e0b\u51e0\u884c\uff1a[distutils]index-servers =local[local]repository: http://172.16.0.173:8080username: yournamepassword: yourpassword3.\u6784\u5efa\uff1apython setup.py sdist build4.\u4e0a\u4f20\uff1apython setup.py sdist upload -r local"} +{"package": "xcirculardichro", "pacakge-description": "No description available on PyPI."} +{"package": "xcix", "pacakge-description": "No description available on PyPI."} +{"package": "xcj", "pacakge-description": "TabooThis is the procject for taboo. We are still working on the project.We will try to finish it soon."} +{"package": "xcl", "pacakge-description": "No description available on PyPI."} +{"package": "xclarity_client", "pacakge-description": "No description available on PyPI."} +{"package": "xclass-sdk", "pacakge-description": "xclass-sdk DocumentationInstallationTo install thexclass-sdk, use the following pip command:pipinstallxclass-sdkUsage# Chat bot appfromxclass_sdk.chat_bot_appimportChatBotApp# General appfromxclass_sdk.general_appimportGeneralApp# Math appfromxclass_sdk.math_appimportMathApp# Profile appfromxclass_sdk.profileimportProfileAppExamplesPlease see the test insrc/*.py"} +{"package": "xclean", "pacakge-description": "xcleanFile de-duplication utilityusage: xclean [-h] [-m MAIN] [-t TARGET] [-a ARCHIVE_TO] [-e [EXTENSIONS ...]] [--remove] [--trash] [--clean]\n\noptions:\n -h, --help show this help message and exit\n -m MAIN, --main MAIN\n Directory where master files reside\n -t TARGET, --target TARGET\n Directory where duplicate files may reside\n -a ARCHIVE_TO, --archive-to ARCHIVE_TO\n Archive duplicates to folder\n -e [EXTENSIONS ...], --extensions [EXTENSIONS ...]\n Extensions\n --remove Remove duplicate files\n --trash Trash duplicate files\n --clean Clean database\n --xmp Include XMP files as well"} +{"package": "xcleanup", "pacakge-description": "CleanupThis is a test"} +{"package": "xclearx", "pacakge-description": "No description available on PyPI."} +{"package": "xcli", "pacakge-description": "xcliUtilities for writing command-line applications in Python.Why?Because I write a lot of command-line scripts in Python and I'm opinionated about things."} +{"package": "xclient", "pacakge-description": "No description available on PyPI."} +{"package": "xclientai", "pacakge-description": "No description available on PyPI."} +{"package": "xclim", "pacakge-description": "VersionsDocumentation and SupportOpen SourceCoding StandardsDevelopment Statusxclimis an operational Python library for climate services, providing numerous climate-related indicator tools\nwith an extensible framework for constructing custom climate indicators, statistical downscaling and bias\nadjustment of climate model simulations, as well as climate model ensemble analysis tools.xclimis built usingxarrayand can seamlessly benefit from the parallelization handling provided bydask.\nIts objective is to make it as simple as possible for users to perform typical climate services data treatment workflows.\nLeveraging xarray and dask, users can easily bias-adjust climate simulations over large spatial domains or compute indices from large climate datasets.For example, the following would compute monthly mean temperature from daily mean temperature:importxclimimportxarrayasxrds=xr.open_dataset(filename)tg=xclim.atmos.tg_mean(ds.tas,freq=\"MS\")For applications where metadata and missing values are important to get right, xclim provides a class for each index\nthat validates inputs, checks for missing values, converts units and assigns metadata attributes to the output.\nThis also provides a mechanism for users to customize the indices to their own specifications and preferences.xclimcurrently provides over 150 indices related to mean, minimum and maximum daily temperature, daily precipitation,\nstreamflow and sea ice concentration, numerous bias-adjustment algorithms, as well as a dedicated module for ensemble analysis.Quick Installxclimcan be installed from PyPI:$pipinstallxclimor from Anaconda (conda-forge):$condainstall-cconda-forgexclimDocumentationThe official documentation is athttps://xclim.readthedocs.io/How to make the most of xclim:Basic Usage ExamplesandIn-Depth Examples.ConventionsIn order to provide a coherent interface,xclimtries to follow different sets of conventions. In particular, input data should follow theCF conventionswhenever possible for variable attributes. Variable names are usually the ones used inCMIP6, when they exist.However, xclim willalwaysassume the temporal coordinate is named \u201ctime\u201d. If your data uses another name (for example: \u201cT\u201d), you can rename the variable with:ds=ds.rename(T=\"time\")Contributing to xclimxclimis in active development and is being used in production by climate services specialists around the world.If you\u2019re interested in participating in the development ofxclimby suggesting new features, new indices or report bugs, please leave us a message on theissue tracker.If you have a support/usage question or would like to translatexclimto a new language, be sure to check out the existingfirst!If you would like to contribute code or documentation (which is greatly appreciated!), check out theContributing Guidelinesbefore you begin!How to cite this libraryIf you wish to citexclimin a research publication, we kindly ask that you refer to our article published in The Journal of Open Source Software (JOSS):https://doi.org/10.21105/joss.05415To cite a specific version ofxclim, the bibliographical reference information can be found throughZenodoLicenseThis is free software: you can redistribute it and/or modify it under the terms of theApache License 2.0. A copy of this license is provided in the code repository (LICENSE).Creditsxclimdevelopment is funded throughOuranos, Environment and Climate Change Canada (ECCC), theFonds vertand the Fonds d\u2019\u00e9lectrification et de changements climatiques (FECC), the Canadian Foundation for Innovation (CFI), and the Fonds de recherche du Qu\u00e9bec (FRQ).This package was created withCookiecutterand theaudreyfeldroy/cookiecutter-pypackageproject template."} +{"package": "xclingo", "pacakge-description": "xclingoA tool for explaining and debugging Answer Set Programs.IMPORTANT:This is a new version ofxclingo. This version is intended to replace the previous one in the future.xclingois a clingo-based tool which produces text explanations for the solutions of ASP programs. The original program must be annotated with clingo-friendly annotations and then provided to xclingo.All the directives start with a%character, so they are recognized by clingo as comments and therefore they don't modify the meaning of the original program. In other words: a xclingo-annotated ASP program will still produce the original output when called with clingo.InstallationInstall with python3python3-mpipinstallxclingoShort usagexclingo must be provided with a maximum number of solutions to be computed for the original program and with the maximum number of explanations to be printed for each solution.An example (all the solutions and 2 explanations):xclingo -n 0 2 examples/drive.lpDefaults are 1 solution and 1 explanation.ExampleWe have any ASP program:% examples/dont_drive_drunk.lp\n\nperson(gabriel;clare).\n\ndrive(gabriel).\nalcohol(gabriel, 40).\nresist(gabriel).\n\ndrive(clare).\nalcohol(clare, 5).\n\npunish(P) :- drive(P), alcohol(P,A), A>30, person(P).\npunish(P) :- resist(P), person(P).\n\nsentence(P, prison) :- punish(P).\nsentence(P, innocent) :- person(P), not punish(P).And we write some special comments:% examples/dont_drive_drunk.lp\n\nperson(gabriel;clare).\n\ndrive(gabriel).\nalcohol(gabriel, 40).\nresist(gabriel).\n\ndrive(clare).\nalcohol(clare, 5).\n\n%!trace_rule {\"% drove drunk\", P}\npunish(P) :- drive(P), alcohol(P,A), A>30, person(P).\n\n%!trace_rule {\"% resisted to authority\", P}\npunish(P) :- resist(P), person(P).\n\n%!trace_rule {\"% goes to prison\",P}\nsentence(P, prison) :- punish(P).\n\n%!trace_rule {\"% is innocent by default\",P}\nsentence(P, innocent) :- person(P), not punish(P).\n\n%!trace {\"% alcohol's level is %\",P,A} alcohol(P,A).\n%!trace {\"% was drunk\",P} alcohol(P,A).\n\n%!show_trace sentence(P,S).We will call those commentsannotationsfrom now on.Now we can obtain the answer sets of the (annotated) program with clingo (clingo -n 0 examples/dont_drive_drunk.lp):Answer: 1\nperson(gabriel) person(clare) alcohol(gabriel,40) alcohol(clare,5) drive(gabriel) drive(clare) punish(gabriel) resist(gabriel) sentence(clare,innocent) sentence(gabriel,prison)\nSATISFIABLEBut also very fashion natural language explanations of with xclingo (xclingo -n 0 0 examples/dont_drive_drunk.lp):Answer 1\n *\n |__clare is innocent by default\n\n *\n |__gabriel goes to prison\n | |__gabriel drove drunk\n | | |__gabriel alcohol's level is 40;gabriel was drunk\n\n *\n |__gabriel goes to prison\n | |__gabriel resisted to authorityNote:for this small example almost all the rules and facts of the program have its own text label (this is, they have beenlabelled). Actually, only labelled rules are used to build the explanations so you can still obtain clear, short explanations even for most complex ASP programs.Annotations%!trace_ruleAssigns a text to the atom in the head of a rule.%!trace_rule {\"% resisted to authority\", P}\npunish(P) :- resist(P), person(P).%!traceAssigns a text to the set of atoms produced by a conditional atom.%!trace {\"% alcohol's level is above permitted (%)\",P,A} alcohol(P,A) : A>40.%!show_traceSelects which atoms should be explained via conditional atoms.%!show_trace sentence(P,S).%!muteMark some atoms asuntraceable. Therefore, explanations will not include them, nor will atoms cause them.%!mute punish(P) : vip_person(P).Usageusage: xclingo [-h] [--version] [--only-translate | --only-translate-annotations | --only-explanation-atoms] [--auto-tracing {none,facts,all}] [-n N N] infiles [infiles ...]\n\nTool for explaining (and debugging) ASP programs\n\npositional arguments:\n infiles ASP program\n\noptional arguments:\n -h, --help show this help message and exit\n --version Prints the version and exists.\n --only-translate Prints the internal translation and exits.\n --only-translate-annotations\n Prints the internal translation and exits.\n --only-explanation-atoms\n Prints the atoms used by the explainer to build the explanations.\n --auto-tracing {none,facts,all}\n Automatically creates traces for the rules of the program. Default: none.\n -n N N Number of answer sets and number of desired explanations.Differences with respect to the previous versionChoice rules and poolingThey are now supported.n(1..20).\nswitch(s1;s2;s3;s4).\n2{num(N):n(N)}4 :- n(N), N>15.Then can be traced with%!trace_ruleannotations.Multiple labels for the same atomIn theprevious version, multiple labels for the same atom lead to alternative explanations. In this version a single explanation is be produced in which labels are concatenated.As an example, the following situation:%!trace {\"% alcohol's level is above permitted (%)\",P,A} alcohol(P,A) : A>40.\n%!trace {\"% was drunk\",P} alcohol(P,A) : A>40.would lead to the following result in the previous version:*\n |__gabriel goes to prison\n | |__gabriel drove drunk\n | | |__gabriel alcohol's level is 40\n\n*\n |__gabriel goes to prison\n | |__gabriel drove drunk\n | | |__gabriel was drunkwhile the new version will produce:*\n |__gabriel goes to prison\n | |__gabriel drove drunk\n | | |__gabriel alcohol's level is 40;gabriel was drunk"} +{"package": "x-clip", "pacakge-description": "No description available on PyPI."} +{"package": "xclone", "pacakge-description": "Inference of Clonal Copy Number Variation in Single CellsXClone is an algorithm to infer allele- and haplotype-specific copy numbers\nin individual cells from low-coverage and sparse single-cell RNA sequencing data\n(e.g., those generated by 10x Genomics, Smart-seq, etc.).\nThe full description of the algorithm and its application on published cancer datasets are described in full-textXClone: detection of allele-specific subclonal copy number variations from single-cell transcriptomic data.The demo of XClone and results on the 3 processed cancer datasets are available atxclone-data.Please frequently read thetutorials and release historyand keep software up to date since XClone is being updated\nand improved frequently at this stage.InstallationMain ModuleXClone requires Python 3.7 or later (recommend 3.7).\nWe recommend to use Anaconda environment for version control and to avoid potential conflicts:conda create -n xclone python=3.7\nconda activate xcloneXClone package can be conveniently installed via PyPI:pip install xcloneor directly from GitHub repository (for development version):pip install git+https://github.com/single-cell-genetics/XClonePreprocessing via xcltkxcltk is a toolkit for XClone preprocessing.\nxcltk is avaliable through pypi. To install, type the following command line, and add -U for upgrading:pip install -U xcltkAlternatively, you can install from this GitHub repository for latest (often development) version by following command line:pip install -U git+https://github.com/hxj5/xcltk"} +{"package": "xcloud", "pacakge-description": "No description available on PyPI."} +{"package": "xCloudPy", "pacakge-description": "No description available on PyPI."} +{"package": "x_cloud_py", "pacakge-description": "No description available on PyPI."} +{"package": "xcltk", "pacakge-description": "xcltkxcltk is a toolkit for XClone (warning: under development, not stable)All release notes are available atdoc/release.rstInstallationxcltk is avaliable throughpypi. To install, type the following command\nline, and add-Ufor upgrading:pipinstall-UxcltkAlternatively, you can install from this GitHub repository for latest (often\ndevelopment) version by following command linepipinstall-Ugit+https://github.com/hxj5/xcltkIn either case, if you don't have write permission for your current Python environment,\nwe suggest creating a separatecondaenvironment or add --user for your\ncurrent one.ManualYou can check the full parameters withxcltk -h.Program: xcltk (Toolkit for XClone)\nVersion: 0.1.16\n\nUsage: xcltk [options]\n\nCommands:\n -- BAF calculation\n fixref Fix REF, ALT and GT.\n rpc Reference phasing correction.\n pileup Pileup, support unique counting.\n\n -- RDR calculation\n basefc Basic feature counting.\n\n -- Region operations\n convert Convert different region file formats.\n\n -- Others\n -h, --help Print this message and exit.\n -V, --version Print version and exit."} +{"package": "xcluster", "pacakge-description": "xclusterPython library of clustering algorithmsCreated byBaihan Lin, Columbia University"} +{"package": "xcmd", "pacakge-description": "Table of Contentstl;drInstallingUsageDependenciestl;drXCmd provides convenient parameters parsing on top of cmd.CmdInstallingFrom PyPI:$ pip install xcmdOr running from the source:$ cd xcmd\n$ export FROM_SOURCE=1; bin/xcmd-shellUsage(more to come: porting zk-shell over to xcmd)DependenciesPython 2.7, 3.3, 3.4, 3.5 or 3.6Testing and DevelopmentPlease seeCONTRIBUTING.rst."} +{"package": "xcmocean", "pacakge-description": "xcmoceanxarray accessor for automating choosing colormaps, aimed at geosciences.Also optional dependence oncf-xarray.Project based on thecookiecutter science project template.Installation:You can pip install from PyPI:pip install xcmoceanor install from conda-forge withconda install -c conda-forge xcmoceanExample usage:import xcmocean\n\nds.salt.cmo.contourf(x='lon', y='lat')which would make acontourfplot of theds.saltdata using thecmoceanhalinecolormap. More examples in the docs.Dev installation for local workClone the repo:$ git clone https://github.com/pangeo-data/xcmocean.gitIn thexcmoceandirectory, install conda environment:$ conda env create -f environment.ymlTo also develop this package, install additional packages with:$ conda install --file requirements-dev.txtTo then check code before committing and pushing it to github, locally run$ pre-commit run --all-files"} +{"package": "xcmp", "pacakge-description": "xcmp"} +{"package": "xcm-parser", "pacakge-description": "Executable Class Model ParserParses an *.xcm file (Executable Class Model) to yield an abstract syntax tree using python named tuplesWhy you need thisYou need to process an *.xcm file in preparation for populating a database or some other purposeInstallationCreate or use a python 3.11+ environment. Then% pip install xcm-parserAt this point you can invoke the parser via the command line or from your python script.From your python scriptYou need this import statement at a minimum:from xcm-parser.parser import ClassModelParserYou can then specify a path as shown:result = ClassModelParser.parse_file(file_input=path_to_file, debug=False)In either case,resultwill be a list of parsed class model elements. You may find the header of thevisitor.pyfile helpful in interpreting these results.From the command lineThis is not the intended usage scenario, but may be helpful for testing or exploration. Since the parser\nmay generate some diagnostic info you may want to create a fresh working directory and cd into it\nfirst. From there...% xcm elevator.xcmThe .xcm extension is not necessary, but the file must contain xcm text. See this repository's wiki for\nmore about the xcm language. The grammar is defined in theclass_model.pegfile. (if the link breaks after I do some update to the code,\njust browse through the code looking for the class_model.peg file, and let me know so I can fix it)You can also specify a debug option like this:% xcm elevator.xcm -DThis will create a scrall-diagnostics folder in your current working directory and deposite a coupel of PDFs defining\nthe parse of both the class model grammar:class_model_tree.pdfand your supplied text:class_model.pdf.You should also see a file namedxcm-parser.login a diagnostics directory within your working directory"} +{"package": "xcms", "pacakge-description": "calculated extended contact mode score provided the query and template protein-ligand structures"} +{"package": "xcn-translate", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content.xcn_translate Release Notesv0.0.7new function is_webdriver_available in webdriver.py"} +{"package": "xcodearchive", "pacakge-description": "No description available on PyPI."} +{"package": "xcodelocalize", "pacakge-description": "XCodeLocalizeRequirmentsPython3.9+InstallationUsing pip:pip3 install xcodelocalize\u0410lso available installations via poetry or .whl file from github releasesUsagePrepare your xcode projectCreate Localizable.strings file and fill it with strings you want to localize./* optional description */\n\"[key]\" = \"[string]\";\n\n/* Example: */\n\"welcome text\" = \"Welcome to XCodelocalize\";Go to the project settings, add the desired languages.Create localization (.strings) files for all selected languages.There is a nice tutorial about ios app localization by kodeco (the new raywenderlich.com)Localizecdto project root folder and runxcodelocalize [OPTIONS]orpython3 -m xcodelocalize [OPTIONS]Options--base-language: code of the language from which all strings will be translated.[default: 'en']--override / --no-override: a boolean value that indicates whether strings that already exist in the file will be translated. Retranslate ifoverride, skip ifno-override.[default: no-override]--format-base / --no-format-base: sort base file strings by key.[default: no-format-base]--file: Names of the strings files to be translated. Multiple files can be specified. If not specified, all files will be translated.[default: None]Example:xcodelocalize --file InfoPlist\nxcodelocalize --file InfoPlist --file MainStoryboard --file Localizable--key: Keys of the strings to be translated. Multiple keys can be specified. If not specified, all keys will be translated.[default: None]--language: Language codes of the strings files to be translated. Multiple language codes can be specified. If not specified, all files will be translated.[default: None]--log-level: One from [progress|errors|group|string].[default: group]--help: Show infoFeatures:The tool looks for .strings files in the current directory recursively, grouping and translating fully automatically. You can even run it in the root directory and localize all your projects at once.Regular .strings, Info.plist, storyboards and intentdefinition files are supported.Formated strings with %@ are supported.Multiline strings are supported.Comments are supported and will be copied to all files. Comments mustnot contain substrings in localizable strings format with comment, such as/*[comment]*/ \"[key]\" = \"[value]\";.AutomationYou can go toTarget -> Build Phases -> New Run Script Phasein your xcode project and pastexcodelocalizethere. It will localize necessary strings during build and your localization files will always be up to date.BonusNice swift extension that allows you to do this\"welcome text\".localized// will return \"Welcome to XCodelocalize\"extensionString{varlocalized:String{NSLocalizedString(self,tableName:nil,bundle:.main,value:self,comment:\"\")}funclocalized(_arguments:String...)->String{String(format:self.localized,locale:Locale.current,arguments:arguments)}}"} +{"package": "xcodeproj", "pacakge-description": "xcodeprojxcodeprojis a utility for interacting with Xcode's xcodeproj bundle format.It expects some level of understanding of the internals of the pbxproj format and schemes. Note that this tool only reads projects. It does not write out any changes. If you are looking for more advanced functionality like this, I recommend looking at the Ruby gem of the same name (which is unaffiliated in anyway).To learn more about the format, you can look at any of these locations:http://www.monobjc.net/xcode-project-file-format.htmlhttps://www.rubydoc.info/gems/xcodeproj/Xcodeproj/ProjectGetting StartedLoading a project is very simple:project=xcodeproj.XcodeProject(\"/path/to/project.xcodeproj\")From here you can explore the project in different ways:# Get all targetsfortargetinproject.targets:print(target.name)# Print from the root level, 2 levels deep (.project is a property on the root# project as other properties such as .schemes are also available)foritem1inproject.project.main_group.children:print(item1)ifnotisinstance(item1,xcodeproj.PBXGroup):continueforitem2initem1.children:print(\"\\t\",item2)# Check that all files referenced in the project exist on diskforiteminproject.fetch_type(xcodeproj.PBXFileReference).values():assertos.path.exists(item.absolute_path())# You can access the raw objects map directly:obj=project.objects[\"key here\"]# For any object you have, you can access its key/identifier via the# `.object_key` propertykey=obj.object_keyNote: This library is \"lazy\". Many things aren't calculated until they are used. This time will be inconsequential on smaller projects, but on larger ones, it can save quite a bit of time due to not parsing the entire project on load. These properties are usually stored though so that subsequent accesses are instant.Note on Scheme SupportThere's no DTD for xcscheme files, so the implementation has been guessed. There will definitely be holes that still need to be patched in it though. Please open an issue if you find any, along with a sample xcscheme file.ContributingThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visithttps://cla.opensource.microsoft.com.When you submit a pull request, a CLA bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct.\nFor more information see theCode of Conduct FAQor\ncontactopencode@microsoft.comwith any additional questions or comments.TrademarksThis project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft\ntrademarks or logos is subject to and must followMicrosoft's Trademark & Brand Guidelines.\nUse of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.\nAny use of third-party trademarks or logos are subject to those third-party's policies."} +{"package": "xcode_releasemaker", "pacakge-description": "UNKNOWN"} +{"package": "xcodestream", "pacakge-description": "XCode StreamPython XCode stream api loader"} +{"package": "xcodetool", "pacakge-description": "No description available on PyPI."} +{"package": "xcode-toolbox", "pacakge-description": "xcode-toolboxA CLI tool which aims to provide a convenient operation toolbox on XCode project. It's faster and cleaner thanxed. You can use it to:(1) Open XCode project or workspace. \n(2) Remove project's derived data, or just the Build or Index folder.\n(3) [WIP] Force kill XCode process. \n(4) [WIP] Generate Objective-C function signatures.The argumentpathis a path to the directory containing at least 1.xcodeprojor.xcworkspacefile, default\nto the current directory..xcworkspacehas higher priority than.xcodeproj.Installationpip3installxcode-toolboxRequirementsPython 3.6+requestsclickUsageUsage: xc [OPTIONS] [PATH]\n\n A CLI tool which aims to provide a convenient operation toolbox on XCode\n project. It's faster and cleaner than `xed`. You can use it to: (1) open\n XCode project or workspace. (2) remove project's derived data. (3) [WIP]\n force kill XCode process. (4) [WIP] generate Objective-C function\n signatures.\n\n The argument `path` is a path to the directory containing at least 1\n `.xcodeproj` or `.xcworkspace` file, default to the current directory.\n `.xcworkspace` has higher priority than `.xcodeproj`.\n\n Contribute: https://github.com/zlrs/xcode-opener\n\nOptions:\n --rm-all Remove the project's derived data in\n ~/Library/Developer/Xcode/DerivedData.\n\n --rm-build Similar to --rm-all, but only remove the `Build` subdirectory.\n --rm-index Similar to --rm-all, but only remove the `Index` subdirectory.\n --help Show this message and exit.Exampleopen a XCode project or workspacespecify folder explicitlygitclonegit@github.com:SDWebImage/SDWebImage.git~/GitHub\nxc~/GitHub/SDWebImage/Examplesopen project/workspace of current folder without parametersgitclonegit@github.com:SDWebImage/SDWebImage.gitcdSDWebImage/Examples\nxcclear project derived folder# remove project's index from derived data\nxc --rm-index\n\n# remove project's build from derived data\nxc --rm-build\n\n#remove project's all derived data\nxc --rm-allTodo featurestoolbox subcommandskillsubcommand. To kill all running XCode processes, equivalent to the following shell command.kill$(psaux|grep'Xcode'|awk'{print $2}')findsubcommand. Find a source file/project file(s) under the given directory tree.generate Objective-C method signature.clear XCode project index folderclear XCode project derivedData folderContributionComments, pull requests or other kind of contributions are welcome!Also if you have any requirements or you encounter any bugs, feel free to open an issue or create a pull request!LICENSEMIT @ zlrs"} +{"package": "xcodex", "pacakge-description": "Please, cite this package as:Laurito, H., La Scala, N., Rolim, G. S., 2023. Extracting XCO2-NASA Daily data with XCODEX:\nA Python package designed for data extraction and structuration. Jaboticabal, SP, BR, (...)Welcome to XCODEX - XCO2 Daily EXtractorHi there! My name is Henrique.The creation of this Python package was intended to create a simple solution for extracting daily data from XCO2 retrieved from the GES DISC platform.I will attach the links containing the GitHub profile of the researchers who helped me in the development of this package along with graphical visualization of the data and the citation of the OCO-2 project.I hope it's useful to you.Long live science!Installing the packageTo install the package, use the command:pip install xcodexUsing XCODEXThere's the possibility to download the .nc4 files directly here:# Setting historical serie\n\nfrom xcodex.main import download_file\n\nstart_date = \"1st of January, 2022\"\nend_date = \"31st of January, 2022\"\n\n# Downloading .nc4 files\ndownload_file(start_date, end_date)Note that ERROR 401 usually is related to unavailable data.Once the download is completed, adownloaded_datafolder will be created in your current path.After that, let's usexco2_extract()to retrieve XCO2 data from the .nc4 files:from glob import glob\nfrom os.path import join\nfrom os import getcwd\n\n# Selecting the folder with .nc4 files\n\narquive_folder = glob(join(getcwd(), \"downloaded_data\", \"*.nc4\")) \n\n# Setting desired locations to build a time series XCO2 data\n\nlocations = dict(Mauna_loa=[19.479488, -155.602829],\n New_York=[40.712776, -74.005974],\n Paris=[48.856613, 2.352222])\n\nfrom xcodex.main import xco2_extract\n\ndf = xco2_extract(path=arquive_folder,\n start=start_date,\n end=end_date,\n missing_data=False,\n **locations); df # Extracting XCO2Note1: The location used in this example was Mauna Loa, New York and Paris. Any location can be usedas long the format \"Location[lat, lon]\" is respected. The values oflatitude and longitude must be in decimal degrees.for more information, please execute the command:help(xco2_extractor)Finally, you will have apandas.Dataframeas result. Now it's up to you how you'llhandle it. I recomend checking theGithub profilesbelow for data visualization.Data visualizationHere we can plot in a map the locations:## set mapbox access token\n\nimport plotly.express as px\nimport plotly.graph_objs as go\n\npx.set_mapbox_access_token('pk.eyJ1Ijoic2FnYXJsaW1idTAiLCJhIjoiY2t2MXhhMm5mNnE5ajJ3dDl2eDZvNTM2NiJ9.1bwmb8HPgFZWwR8kcO5rOA')\n\n# Plotly configs\n\nfig= px.scatter_mapbox(df,\n lat= 'lat',\n lon= 'lon',\n color= 'xco2',\n zoom= .85,\n width=960,\n height=540,\n size_max=10,\n hover_name='city',\n color_continuous_scale=px.colors.cyclical.IceFire)\n\nfig.update_layout(mapbox_style=\"dark\") #\"open-street-map\"\n\n\nlayout = go.Layout(margin=go.layout.Margin(\n l=0,\n r=0,\n b=0,\n t=0))\n\n\nfig.update_layout(layout,\n autosize=False,\n height=540,\n width=960,\n hovermode=\"closest\")\n\n# Saving the output image\n\n#fig.write_html('xcodex_map.html')\n#fig.write_image(\"xcodex_map.png\", scale=2)\n\nfig.show()And finally a way to observe the XCO2 behavior during the time serie:# Showing XCO2 behavior in time serie\n\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nplt.figure(figsize=(10,5))\n\nsns.set_theme(font_scale=1, style=\"white\")\n\nsns.lineplot(data=df,\n x=\"jd\",\n y='xco2',\n hue='city',\n errorbar=('ci',0),\n palette=\"tab10\")\n\nplt.xlabel(\"\")\nplt.ylabel(\"XCO2 (ppm)\")\n\nplt.xlim(min(df.jd), max(df.jd))\nplt.ylim(min(df.xco2), max(df.xco2))\n\nsns.despine(right=False,\n top=False)\n\nplt.legend(ncol=3)\n\nplt.tight_layout()\n\n#plt.savefig(\"xcodex_locations.png\", dpi=300)\n\nplt.show()GitHub profiles:https://github.com/GlaucoRolim(Co-author)https://github.com/kyuenjpl/ARSET_XCO2https://github.com/sagarlimbu0/OCO2-OCO3Data source citation:Brad Weir, Lesley Ott and OCO-2 Science Team (2022), OCO-2 GEOS Level 3 daily,\n0.5x0.625 assimilated CO2 V10r, Greenbelt, MD, USA, Goddard Earth Sciences Data\nand Information Services Center (GES DISC), Accessed: 10/31/2022,\ndoi: 10.5067/Y9M4NM9MPCGH"} +{"package": "xcofdk-se", "pacakge-description": "Project DescriptionXCOFDKis an eXtensible,Customizable andObject-orientedFrameworkDevelopmentKit with the primary\npurpose of providing:complete, reliablelife cycle management,ready-to-use runtime environment formultithreading.XCOFDK is designed by the concept ofhigh-level abstractionand implemented to enable rapid development of reliable (embedded) applications\nby providing a software framework composed ofbuilding blocks calledsubsystems. Subsystems are defined and designed by focusing on their\nassociated, high-level functionality and responsibility represented thru their respective API (Application Programming Interface).Key characteristics of the design of XCOFDK are:completely object-oriented,inspired by the design principle KISS,general-purpose composition in terms of a software framework,applicable for multiple programming languages, e.g. Python, C++, Java,applicable for multiple operating systems, e.g Linux, Windows, macOS,highly configurable, thus customizable and extensible,composed of a collection of well-defined subsystems,provides a runtime environment as its major service for execution of tasks,thus enabling multithreading by a clear, manageable API to start/stop/abort tasks,enabling development of event (or message) driven applications,support for (aliveness) monitoring of tasks,support for transparant communication subsystem(s),support for full life cycle management,support for well-defined, coordinated shutdown sequence,support for tracking, handling and report of detected failures.InstallationXCOFDK Starter Edition (SE)is available as thefree-of-chargeversion ofXCOFDKforPython 3.11, Linux.NoteBy installing you agree to the terms and conditions of use of the software (see sectionLicensingbelow).Install usingpip:$>python3.11-mpipinstallxcofdk-seQuick StartExample below illustrates most simple way to startXCOFDKin Python:# file: defaultmxu.py\n\nfrom xcofdk import fwapi\n\n\ndef RunQuickStart() -> bool:\n print('Welcome to quick start of XCOFDK.')\n\n # indicate that main task is finished / stopped by returning 'False'\n return False\n\n\ndef Main() -> int:\n mxu = fwapi.StartXcoFW(fwStartMXU_=RunQuickStart, bAutoStartMXU_=True)\n res = mxu is not None\n if res:\n res = fwapi.StopXcoFW()\n if not fwapi.JoinXcoFW():\n res = False\n return 0 if res else 1\n\n\nif __name__ == \"__main__\":\n exit(Main())When executed the output of the program should like this:$>python3.11-mdefaultmxu------------------------------------------------------------------------------------------XCOFDKStarterEdition(SE)-v1.0----------NOTE:-----ThisversionofXCOFDKissubjecttopre-buildlimitationswithregard-----tobothconfigurationandruntimefeatures.--------------------------------------------------------------------------------[15:43:06.062XWNG]NoMainXcoUnitinstancepassedto,willcreateadefaultoneservingasmainxcounit.[15:43:06.146KPI]Doneinitial(resource)loading:0.273[15:43:06.147KPI]Frameworkisupandrunning:0.081[15:43:06.147INF]Startedframework.[15:43:06.149INF]StartingmainxcounitdefaultMainXU...WelcometoquickstartofXCOFDK.[15:43:06.154INF][XTd_501001]ExecutionofmainxcounitdefaultMainXUdoneaftersuccessfulstart.[15:43:06.155INF][XTd_501001]Gotrequesttostopframework.[15:43:06.155KPI][XTd_501001]Startingcoordinatedshutdown...[15:43:06.155INF][XTd_501001]Gotrequesttojoinframework.[15:43:06.156INF][XTd_501001]Waitingforframeworktocompleteshutdownsequence...[15:43:06.222KPI]Finishedcoordinatedshutdown.[15:43:06.255KPI]Frameworkactivetrackingduration:0.163--------------------------------------------------------------------------------Fatals(0),Errors(0),Warnings(0),Infos(6)Totalprocessingtime:0.472---------------------------------------------------------------------------------------------------------------------------------------------------------------------ResultedLCstatus:SUCCESS-----LcState[0x3500]:LcStopped,TMgrStopped,FwMainStopped,MainXcoUnitStopped-------------------------------------------------------------------------------------$>LicensingUse ofXCOFDK Starter Edition (SE)is subject to\nthe terms and conditions of the software. For more information refert to theXCOFDK Starter Edition (SE) Licensing page.LinksDocumentation:https://www.xcofdk.de/"} +{"package": "xcoll", "pacakge-description": "xcollCollimation in xtrack simulationsDescriptionGetting StartedDependenciespython >= 3.8numpypandasxsuite (in particular xobjects, xdeps, xtrack, xpart)Installingxcollis packaged usingpoetry, and can be easily installed withpip:pipinstallxcollFor a local installation, clone and install in editable mode (need to havepip>22):gitclonegit@github.com:xsuite/xcoll.git\npipinstall-excollExampleFeaturesAuthorsFrederik Van der Veken(frederik@cern.ch)Despina DemetriadouAndrey AbramovGiovanni IadarolaVersion History0.1Initial ReleaseLicenseThis project isApache 2.0 licensed."} +{"package": "xcollection", "pacakge-description": "xcollectionCIDocsPackageLicensexcollection extendsxarray's data modelto be able to handle a dictionary of xarray Datasets.Seedocumentationfor more information.Installationxcollection can be installed from PyPI with pip:python-mpipinstallxcollectionIt is also available fromconda-forgefor conda installations:condainstall-cconda-forgexcollection"} +{"package": "xcolor", "pacakge-description": "xcolor\u652f\u6301UNIX\u53ca\u7c7bUNIX\u64cd\u4f5c\u7cfb\u7edf\n\u652f\u6301Python\u7248\u672c\u4e3aPython3.0+\u989c\u8272\u503c:\u6bcf\u79cd\u989c\u8272\u6709\u4e24\u79cd\u76f8\u8fd1\u7684\u989c\u8272,\u4ee51\u548c2\u533a\u5206.\n\"Black1\",\"Red1\",\"Green1\",\"Yellow1\",\"Blue1\",\"Magenta1\",\"Cyan1\",\"White1\"\n\"Black2\",\"Red2\",\"Green2\",\"Yellow2\",\"Blue2\",\"Magenta2\",\"Cyan2\",\"White2\"\u5b57\u4f53\u98ce\u683c:\"Bold\":\u9ad8\u4eae\u52a0\u7c97\"Italic\":\u659c\u4f53\"Underline\":\u4e0b\u5212\u7ebf\"Flash\":\u95ea\u70c1\"Throughline\":\u5220\u9664\u7ebf\u5185\u7f6e\u5bf9\u8c61:\u5b57\u4f53\u98ce\u683c\u9700\u8981\u7ec8\u7aef\u652f\u6301\u5e38\u89c4\u989c\u8272\u98ce\u683cblack1,red1,green1,yellow1,blue1,magenta1,cyan1,white1black2,red2,green2,yellow2,blue2,magenta2,cyan2,white2\u659c\u4f53\u98ce\u683ciblack1,ired1,igreen1,iyellow1,iblue1,imagenta1,icyan1,iwhite1iblack2,ired2,igreen2,iyellow2,iblue2,imagenta2,icyan2,iwhite2\u4e0b\u5212\u7ebf\u98ce\u683cublack1,ured1,ugreen1,uyellow1,ublue1,umagenta1,ucyan1,uwhite1ublack2,ured2,ugreen2,uyellow2,ublue2,umagenta2,ucyan2,uwhite2\u5220\u9664\u7ebf\u98ce\u683ctblack1,tred1,tgreen1,tyellow1,tblue1,tmagenta1,tcyan1,twhite1tblack2,tred2,tgreen2,tyellow2,tblue2,tmagenta2,tcyan2,twhite2\u95ea\u70c1\u98ce\u683cfblack1,fred1,fgreen1,fyellow1,fblue1,fmagenta1,fcyan1,fwhite1fblack2,fred2,fgreen2,fyellow2,fblue2,fmagenta2,fcyan2,fwhite2\u7c97\u4f53\u98ce\u683cbblack,bred,bgreen,byellow,bblue,bmagenta1,bcyan,bwhiteeg.if __name__ == \"__main__\":\n import logging\n import xcolor\n # \u6d4b\u8bd5\u989c\u8272\n xcolor.test_color()\n # \u6d4b\u8bd5\u5185\u7f6e\u989c\u8272\u5bf9\u8c61\n xcolor.test_style()\n # \u84dd\u8272\u5b57\u4f53\n # print\u65b9\u6cd5\u4e0e\u5185\u5efaprint\u65b9\u6cd5\u53c2\u6570\u76f8\u540c\n xcolor.blue1.print(\"hello world!\")\n\n # \u7528Color\u5bf9\u8c61\u4f5c\u4e3a\u88c5\u9970\u5668,\u6539\u53d8\u88ab\u88c5\u9970\u51fd\u6570\u5185\u7684\u6807\u51c6\u8f93\u51fa\n @xcolor.yellow1\n def test():\n print(\"*\"*60)\n\n test()\n\n std_handler = logging.StreamHandler()\n std_handler.setLevel(logging.DEBUG)\n logger = logging.getLogger(\"test\")\n logger.setLevel(logging.DEBUG)\n logger.addHandler(logging.StreamHandler())\n logger.error=xcolor.red1(logger.error)\n logger.warning=xcolor.bred(logger.warning)\n logger.info = xcolor.green2(logger.info)\n logger.debug = xcolor.iblue2(logger.debug)\n logger.error(\"error\")\n logger.warning(\"warn\")\n logger.info(\"info\")\n logger.debug(\"debug\")\n #\u8bbe\u7f6e\u7ec8\u7aef\u989c\u8272\n xcolor.byellow.setenv()\n print(\"abc\")\n #\u6e05\u9664\u7ec8\u7aef\u989c\u8272\n xcolor.clear()\n print(\"efg\")"} +{"package": "xcolumns", "pacakge-description": "xConsistent Optimization of Label-wise Utilities in Multi-label classificatioNsxCOLUMNs is a small Python library aims to implement different methods for optimization of general family of label-wise utilities (performance metrics) in multi-label classification, which scale to large (extreme) datasets.InstallationThe library can be installed using pip:pipinstallxcolumnsIt should work on all major platforms (Linux, Windows, Mac) and with Python 3.8+.Repository structureThe repository is organized as follows:docs/- Sphinx documentation (work in progress)experiments/- a code for reproducing experiments from the papersxcolumns/- Python package with the libraryMethods, usage, and how to citeThe library implements the following methods:Block Coordinate Ascent/Descent (BCA/BCD)The method is described in the paper:Erik Schultheis, Marek Wydmuch, Wojciech Kot\u0142owski, Rohit Babbar, Krzysztof Dembczy\u0144ski. Generalized test utilities for long-tail performance in\nextreme multi-label classification. NeurIPS 2023.Frank-Wolfe (FW)Description is work in progress."} +{"package": "xcom", "pacakge-description": "Home-page: UNKNOWN\nAuthor: Vinogradov Dmitry\nAuthor-email:dgrapes@gmail.comLicense: MIT\nDescription: UNKNOWN\nPlatform: UNKNOWN\nClassifier: Programming Language :: Python :: 3\nClassifier: License :: OSI Approved :: MIT License\nClassifier: Operating System :: OS Independent"} +{"package": "xcom-232i", "pacakge-description": "xcom-232iPython library to access Studer-Innotec Xcom-232i device through RS-232 over a serial port.NOTE: This lib is still WiP, so functionality is still limited, but feel free to create apull requestif you want to contribute ;)DISCLAIMER: This library is NOT officially made by Studer-Innotec.The complete official documentation is available on:Studer-Innotec Download Center-> Software and Updates -> Communication protocol Xcom-232iGetting StartedRequirementsHardwareXcom-232i connected to your installationXcom-232i connected to PC using USB to RS-232 adapter (1)PC with at least USB2.0 or faster (works on Raspberry Pi 3/4 as well)(1) I personally am successfully using an adapter with the PL2303 chipset likethis oneSoftwareany Linux based OS (x86 / ARM)python3 >= 3.6python3-pipInstallationpip3installxcom-232iimportant: make sure you select the USB to RS-232 adapter as thesocket_device, usually on Linux it is/dev/ttyUSB[0-9]ExamplesReading valuesfromxcom_232iimportXcomRS232fromxcom_232iimportXcomCascIO=XcomRS232(socket_device='/dev/ttyUSB0',baudrate=115200)lademodus=IO.get_value(c.OPERATION_MODE)batt_phase=IO.get_value(c.BAT_CYCLE_PHASE)solarleistung=IO.get_value(c.PV_POWER)*1000# convert from kW to Wsonnenstunden=IO.get_value(c.NUM_SUN_HOURS_CURR_DAY)ladestand=IO.get_value(c.STATE_OF_CHARGE)# in %stromprod=IO.get_value(c.PROD_ENERGY_CURR_DAY)batt_strom=IO.get_value(c.BATT_CURRENT)batt_spann=IO.get_value(c.BATT_VOLTAGE)print(f\"LModus:{lademodus}| Batt_Phase:{batt_phase}| Solar_P:{solarleistung}| SonnenH:{sonnenstunden}| Batt_V:{batt_spann}| SOC:{ladestand}\")Writing valuesfromxcom_232iimportXcomRS232fromxcom_232iimportXcomCascIO=XcomRS232(socket_device='/dev/ttyUSB0',baudrate=115200)# write into RAMIO.set_value(c.SMART_BOOST_LIMIT,100)# set smart boost limitIO.set_value(c.FORCE_NEW_CYCLE,1,property_id=c.VALUE_QSP)# force new charge cycle# explanation for property_id:c.VALUE_QSP# write into Flash memory (important: you should write into flash only if you *really* need it!)c.UNSAVED_VALUE_QSP# write into RAM (default)"} +{"package": "xcom2modsync", "pacakge-description": "UNKNOWN"} +{"package": "xcom485i", "pacakge-description": "Python library to access Studer-Innotec Xcom-485i device through Modbus RTU over a serial portPrerequisitesPlease read the complete documentation available on :Studer Innotec SA-> Support -> Download Center -> Software and Updates -> Communication protocols Xcom-CANGetting Started1. Package installation$pipinstallxcom485i2. Hardware installationConnect yourXcom-485i(Studer side) to your installation using the cable provided with the deviceConnect yourXcom-485i(External side) to your controller (personal computer, Raspberry Pi, etc.) using aUSBtoRS-485adapterPlease refer to theXcom-485imanual for more information about commissioning the device3. Serial configurationThis package rely onpyserialstandard package, in order to use thexcom485ipackage make sure to instantiate it like :importserialserial_port=serial.Serial(SERIAL_PORT_NAME,SERIAL_PORT_BAUDRATE,parity=serial.PARITY_EVEN,timeout=1)whereSERIAL_PORT_NAMEis your serial port interface, for example set it to\u2018COM4\u2019(string argument) when usingWindowsotherwise you may set it to\u2018/dev/ttyUSB0/\u2019onLinuxwhereSERIAL_PORT_BAUDRATEis the baudrate used by your serial port interface (must be set to 9600, 19200, 38400 or 115200 according toXcom-485idip-switches)Xcom-485i Dip switches baud rate selectionN\u00b0 7N\u00b0 8BaudrateOFFOFF9600 bpsOFFON19200 bpsONOFF38400 bpsONON115200 bps4. Address offsetSet the modbus offset corresponding to the internal dip-switches of yourXcom-485idevice, it must be set to 0, 32, 64 or 128.It is done when instantiate theXcom485iclass like :xcom485i=Xcom485i(serial_port,OFFSET,debug=True)whereserial_portis the previously created object withSerialwhereOFFSETis your actual modbus address offset set by the dip-switches inside yourXcom-485iwheredebugenables you to get some useful console information for debugging purposeXcom-485i Dip switches address offset selectionN\u00b0 1N\u00b0 2Address offsetAddress rangeOFFOFF01 to 63OFFON3233 to 95ONOFF6465 to 127ONON128129 to 1925. Run an example from/examplesfolderGo to/examplesfolder with a terminal and execute this script$pythonex_read_info.pyCheckclient fileto understand it.6. Open documentationOpen documentation fromRead The DocsWarningsPleasecheck carefully the serial configuration, theXcom-485idip-switches configuration as well as the jumper for D+, D- and GND signalsUsedevices addresses generated intoaddresses fileIt is strongly recommendedNOTto spam theXcom-485iwith multiple requests. The correct way to communicate with theXcom-485iis to send a request and towaitfor the response before sending the next request. If no response comes from theXcom-485iafter a delay of 1 second, we can consider that the timeout is over and another request can be send. It is also howModbus RTUis intended to work.AuthorsStuder Innotec SA-Initial work-Studer Innotec SALicenseThis project is licensed under the MIT License - see theLICENSEfile for details"} +{"package": "xcomcan", "pacakge-description": "Python library to access Studer-Innotec Xcom-CAN with theStuder Public Protocolusing CAN 2.0B framesPrerequisitesPlease read the complete documentation available on :Studer Innotec SA-> Support -> Download Center -> Software and Updates -> Communication protocols Xcom-CANGetting Started1. Package installation$pipinstallxcomcan2. Hardware installationConnect yourXcom-CAN(Studer side) to your installation using the cable provided with the deviceConnect yourXcom-CAN(External side) to your controller (personal computer, Raspberry Pi, etc.) using aUSBtoCANadapter (Kvaser, etc.)Please refer to theXcom-CANmanual for more information about commissioning the device3. Xcom-CAN Protocol selectionInteraction with the Xtender/Vario systems through third party devices such as PLC or SCADA requires to selectStuder Public Protocolwith dip switches as shown below. There\u2019s two operation modes available :Exclusive : This configuration is recommended when there is onlyonedevice communicating with theStuder Public Protocolon the external CAN interface. TheXcom-CANwill send a response to every frame that appears on the external CAN interface. For frames which do not fit theStuder Public Protocolspecifications, theXcom-CANwill send an error frame message. This mode is practical for debugging as every frame sent by the PLC/SCADA will get a response. It will also detect any frame that could be corrupted when transmission occurs.Tolerant : This configuration is recommended when there areseveraldevices communicating with different protocols on the external CAN interface. TheXcom-CANwill only send a response to the frames that completely fit theStuder Public Protocolspecifications. This mode enable the installer to extend the CAN bus on the external interface and to add others devices that can communicate with the PLC/SCADA on the same physical support as theXcom-CAN.Xcom-CAN Dip switches protocol selectionN\u00b0 1N\u00b0 2N\u00b0 3N\u00b0 4Studer PublicOFFONOFFOFFExclusive ProtocolOFFONOFFONTolerant Protocol4. Software configurationSet the Studer CAN public client as follow :StuCanPublicClient(0x00,CAN_BUS_SPEED,bustype='kvaser',debug=True)where \u20180x00\u2019 is the source addresswhereCAN_BUS_SPEEDis your CAN bus bitrate as selected inside the XcomCAN device with the dip-switches, it must be set to 10000, 20000, 50000, 100000, 125000, 250000, 500000 or 1000000wherebustypeis the CAN interface name has specified here :python-canwheredebugenables you to get some useful console information for debugging purposeXcom-CAN Dip switches CAN bus speed selectionN\u00b0 6N\u00b0 7N\u00b0 8CAN bus speedOFFOFFOFF10 kbpsOFFOFFON20 kbpsOFFONOFF50 kbpsOFFONON100 kbpsONOFFOFF125 kbpsONOFFON250 kbpsONONOFF500 kbpsONONON1 Mbps5. Run an example from/examplesfolderGo to/examplesfolder with a terminal and execute this script$pythontry_stu_can_public_client.pyCheckclient fileto understand it.6. Open documentationOpen documentation fromRead The DocsWarningsPleasecheck carefully theXcom-CANdip switches configuration as well as the jumper for CAN-H, CAN-L and GND signalsUsedevices addresses generated intoaddresses fileIt is strongly recommendedNOTto spam theXcom-CANwith multiple requests. Even if theXcom-CANhas a frame buffer, the response will not be faster because of internal Studer bus load. The correct way to communicate with theXcom-CANis to send a request and towaitfor the response before sending the next request. If no response comes fromXcom-CANafter a delay of 1 second, we can consider that the timeout is over and another request can be send.AuthorsStuder Innotec SA-Initial work-Studer Innotec SALicenseThis project is licensed under the MIT License - see theLICENSEfile for details"} +{"package": "xcomfort", "pacakge-description": "xcomfort-pythonUnofficial python package for communicating with Eaton xComfort BridgeUsageimportasynciofromxcomfortimportBridgedefobserve_device(device):device.state.subscribe(lambdastate:print(f\"Device state [{device.device_id}] '{device.name}':{state}\"))asyncdefmain():bridge=Bridge(,)runTask=asyncio.create_task(bridge.run())devices=awaitbridge.get_devices()fordeviceindevices.values():observe_device(device)# Wait 50 seconds. Try flipping the light switch manually while you waitawaitasyncio.sleep(50)# Turn off all the lights.# for device in devices.values():# await device.switch(False)## await asyncio.sleep(5)awaitbridge.close()awaitrunTaskasyncio.run(main())Testspython-mpytest"} +{"package": "xComfortMQTT", "pacakge-description": "xComfortMQTTInstallingYou can installxComfortMQTTdirectly from PyPI:sudopip3install-UxComfortMQTTConfigInsert this snippet to the file /etc/xComfortMQTT.yml:---\nshc:\n host: 192.168.0.2\n username: admin\n password: very-strong-password\n\nmqtt:\n host: 192.168.0.1UsageUpdate /etc/xComfortMQTT.yml and runxComfortMQTT-c/etc/xComfortMQTT.ymlSystemdInsert this snippet to the file /etc/systemd/system/xComfortMQTT.service:[Unit]\nDescription=xComfortMQTT\nAfter=network.target\n\n[Service]\nType=simple\nUser=pi\nExecStart=/usr/local/bin/xComfortMQTT -c /etc/xComfortMQTT.yml\nRestart=always\nRestartSec=5\nStartLimitIntervalSec=0\n\n[Install]\nWantedBy=multi-user.targetEnable the service start on boot:sudosystemctlenablexComfortMQTT.serviceStart the service:sudosystemctlstartxComfortMQTT.serviceView the service log:journalctl-uxComfortMQTT.service-fPM2pm2start/usr/bin/python3--name\"xComfortMQTT\"--/usr/local/bin/xComfortMQTT-c/etc/xComfortMQTT.yml\npm2saveDevelopmentgit clone git@github.com:blavka/xComfortMQTT.git\ncd xComfortMQTT\n./test.sh\nsudo python3 setup.py develop"} +{"package": "xcomfortshc", "pacakge-description": "Eaton xComfort Smart Home Controller communinication library"} +{"package": "xcommand", "pacakge-description": "\u5feb\u901f\u5f00\u59cb\u5b89\u88c5pipinstallxcommand\u4f7f\u7528xreportxreport--help\n>>>Usage:xreport[OPTIONS]COMMAND[ARGS]...\u62a5\u544a\u76f8\u5173\u5de5\u5177\uff0c\u53ef\u6781\u5927\u63d0\u9ad8\u51fa\u62a5\u544a\u6216\u5176\u4ed6\u6a21\u677f\u5f0fword\u6587\u6863\u7684\u6548\u7387\n\nOptions:--helpShowthismessageandexit.\n\nCommands:genrpt\u6839\u636eword\u6a21\u677f\u81ea\u52a8\u8bfb\u53d6excel\u4e2d\u6307\u5b9a\u6570\u636e\u751f\u6210\u62a5\u544a\u6587\u6863xreportgenrpt--help\n>>>Usage:xreportgenrpt[OPTIONS]\u6839\u636eword\u6a21\u677f\u81ea\u52a8\u8bfb\u53d6excel\u4e2d\u6307\u5b9a\u6570\u636e\u751f\u6210\u62a5\u544a\u6587\u6863\n\nOptions:-t,--templateFILE\u5fc5\u8981\u53c2\u6570\uff0c\u6307\u5b9aword\u6a21\u677f\u6587\u4ef6\u5730\u5740-f,--fileFILE\u6307\u5b9aexcel\u6570\u636e\u6587\u4ef6\u5730\u5740\uff0c\u4e0e-d\u53c2\u6570\u5fc5\u987b\u4e8c\u9009\u4e00-d,--dirDIRECTORY\u6307\u5b9aexcel\u6570\u636e\u6587\u4ef6\u5939\u5730\u5740\uff0c\u4e0e-f\u53c2\u6570\u5fc5\u987b\u4e8c\u9009\u4e00\uff0c\u6b64\u6a21\u5f0f\u4e0b\u6700\u7ec8\u7684word\u8f93\u51fa\u6587\u6863\u540d\u4e0eexcel\u6570\u636e\u6587\u4ef6\u540d\u4e00\u81f4-o,--outPATH\u6307\u5b9aword\u8f93\u51fa\u6587\u4ef6\u6216\u6587\u4ef6\u5939\u5730\u5740\u3002\u5f53\u9009\u62e9-f\u53c2\u6570\u65f6\uff0c\u9ed8\u8ba4\u4e3a\u201c./out.docx\u201d\uff1b\u5f53\u9009\u62e9-d\u53c2\u6570\u65f6\uff0c\u9ed8\u8ba4\u4e3a\u201c./out/\u201d-h,--hide\u9690\u85cf\u8fd0\u884c\u8fc7\u7a0b\u4e2doffice\u8f6f\u4ef6\u7a97\u53e3--helpShowthismessageandexit.xpdfxpdf--help\n>>>Usage:xpdf[OPTIONS]COMMAND[ARGS]...\u5feb\u901f\u5408\u5e76\u6216\u62c6\u5206pdf\u6587\u4ef6\n\nOptions:--helpShowthismessageandexit.\n\nCommands:toimg\u5c06\u5355\u4e2apdf\u6587\u4ef6\u7684\u6bcf\u4e00\u9875\u5bfc\u51fa\u4e3a\u56fe\u7247topdf\u5c06\u6307\u5b9a\u56fe\u7247\u53ca\u6307\u5b9a\u6587\u4ef6\u5939\u4e2d\u56fe\u7247\u5408\u5e76\u4e3a\u4e00\u4e2apdf\u6587\u4ef6\uff0c\u6587\u4ef6\u5939\u4e2d\u56fe\u7247\u987a\u5e8f\u6309\u7167\u6587\u4ef6\u540d\u5347\u5e8f\u6392\u5217xpdftoimg--help\n>>>Usage:xpdftoimg[OPTIONS]PATH\u5c06\u5355\u4e2apdf\u6587\u4ef6\u7684\u6bcf\u4e00\u9875\u5bfc\u51fa\u4e3a\u56fe\u7247\n\nOptions:-o,--outPATH\u6307\u5b9a\u56fe\u7247\u8f93\u51fa\u6587\u4ef6\u5939\u5730\u5740[default:out/]-s,--scaleFLOAT\u6307\u5b9a\u8f93\u51fa\u56fe\u7247\u7684\u7f29\u653e\u6bd4\u4f8b[default:2]-p,--prefixTEXT\u6bcf\u5f20\u56fe\u7247\u7684\u6587\u4ef6\u540d\u524d\u7f00-f,--format[jpeg|png]\u6bcf\u5f20\u56fe\u7247\u7684\u6587\u4ef6\u683c\u5f0f[default:jpeg]--helpShowthismessageandexit.xpdftopdf--help\n>>>Usage:xpdftopdf[OPTIONS]PATH...\u5c06\u6307\u5b9a\u56fe\u7247\u53ca\u6307\u5b9a\u6587\u4ef6\u5939\u4e2d\u56fe\u7247\u5408\u5e76\u4e3a\u4e00\u4e2apdf\u6587\u4ef6\uff0c\u6587\u4ef6\u5939\u4e2d\u56fe\u7247\u987a\u5e8f\u6309\u7167\u6587\u4ef6\u540d\u5347\u5e8f\u6392\u5217\n\nOptions:-o,--outPATH\u6307\u5b9apdf\u8f93\u51fa\u6587\u4ef6\u5730\u5740[default:out.pdf]-s,--size[A3|A4|A5|B4|B5]\u6307\u5b9apdf\u8f93\u51fa\u6587\u4ef6\u6bcf\u4e00\u9875\u7684\u56fa\u5b9a\u5c3a\u5bf8[default:A4]-r,--reverse\u53cd\u8f6c\u9875\u9762\u7684\u957f\u548c\u9ad8\uff0c\u914d\u5408\u201c--size\u201d\u4f7f\u7528\uff0c\u6dfb\u52a0\u8be5\u53c2\u6570\u540e\u9875\u9762\u4e3a\u6a2a\u5411-f,--free\u81ea\u7531\u5c3a\u5bf8\uff0c\u6dfb\u52a0\u8be5\u53c2\u6570\u540e\u201c--size\u201d\u548c\u201c--reverse\u201d\u65e0\u6548\uff0c\u6bcf\u4e00\u9875\u4fdd\u6301\u6e90\u56fe\u7247\u7684\u5f62\u72b6\u548c\u5c3a\u5bf8--helpShowthismessageandexit."} +{"package": "xcompact3d-toolbox", "pacakge-description": "Xcompact3d ToolboxIt is a Python package designed to handle the pre and postprocessing of\nthe high-order Navier-Stokes solverXCompact3d. It aims to help users and\ncode developers to build case-specific solutions with a set of tools and\nautomated processes.The physical and computational parameters are built on top oftraitlets,\na framework that lets Python classes have attributes with type checking, dynamically calculated default values, and \u2018on change\u2019 callbacks.\nIn addition toipywidgetsfor an user friendly interface.Data structure is provided byxarray(seeWhy xarray?), that introduces labels in the form of dimensions, coordinates and attributes on top of rawNumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. It integrates tightly withdaskfor parallel computing andhvplotfor interactive data visualization.Finally, Xcompact3d-toolbox is fully integrated with the newSandbox Flow Configuration.\nThe idea is to easily provide everything that XCompact3d needs from aJupyter Notebook, like initial conditions, solid geometry, boundary conditions, and the parameters (see examples).\nIt makes life easier for beginners, that can run any new flow configuration without worrying about Fortran and2decomp.\nFor developers, it works as a rapid prototyping tool, to test concepts and then compare results to validate any future Fortran implementation.Useful linksDocumentation;Changelog;Suggestions for new features and bug report;See what is coming next (Project page);Xcompact3d's repository.InstallationIt is possible to install using pip:pipinstallxcompact3d-toolboxThere are other dependency sets for extra functionality:pipinstallxcompact3d-toolbox[visu]# interactive visualization with hvplot and otherspipinstallxcompact3d-toolbox[doc]# dependencies to build the documentationpipinstallxcompact3d-toolbox[dev]# tools for developmentpipinstallxcompact3d-toolbox[test]# tools for testingpipinstallxcompact3d-toolbox[all]# all the aboveTo install from source, clone de repository:gitclonehttps://github.com/fschuch/xcompact3d_toolbox.gitAnd then install it interactively with pip:cdxcompact3d_toolbox\npipinstall-e.You can install all dependencies as well:pipinstall-e.[all]Now, any change you make at the source code will be available at your local installation, with no need to reinstall the package every time.Try it OnlineClick on any link above to launchBinderand interact with our notebooks in a live environment!ExamplesImporting the package:importxcompact3d_toolboxasx3dLoading the parameters file (both.i3dand.prmare supported, see#7) from the disc:prm=x3d.Parameters(loadfile=\"input.i3d\")prm=x3d.Parameters(loadfile=\"incompact3d.prm\")Specifying how the binary fields from your simulations are named, for instance:If the simulated fields are named likeux-000.bin:prm.dataset.filename_properties.set(separator=\"-\",file_extension=\".bin\",number_of_digits=3)If the simulated fields are named likeux0000:prm.dataset.filename_properties.set(separator=\"\",file_extension=\"\",number_of_digits=4)There are many ways to load the arrays produced by your numerical simulation, so you can choose what best suits your post-processing application.\nAll arrays are wrapped intoxarrayobjects, with many useful methods for indexing, comparisons, reshaping and reorganizing, computations and plotting.\nSee the examples:Load one array from the disc:ux=prm.dataset.load_array(\"ux-0000.bin\")Load the entire time series for a given variable:ux=prm.dataset[\"ux\"]Load all variables from a given snapshot:snapshot=prm.dataset[10]Loop through all snapshots, loading them one by one:fordsinprm.dataset:# compute somethingvort=ds.uy.x3d.first_derivative(\"x\")-ds.ux.x3d.first_derivative(\"y\")# write the results to the discprm.dataset.write(data=vort,file_prefix=\"w3\")Or simply load all snapshots at once (if you have enough memory):ds=prm.dataset[:]It is possible to produce a new xdmf file, so all data can be visualized on any external tool:prm.dataset.write_xdmf()User interface for the parameters with IPywidgets:prm=x3d.ParametersGui()prmCopyright and LicenseAll content is underGPL-3.0 License."} +{"package": "xcompare", "pacakge-description": "xcompare - A collection of comparison operations for xarray-based objectsxcompareprovides Python-based tools for climate model and gridded\nobservational dataset comparisons."} +{"package": "xcomposite", "pacakge-description": "XComposite OverviewThis module exposes the composite design pattern in an easy to use way\nwhich attempts to minimalise the repetitive overhead.The composite design pattern is an alternative to top-down inheritance\nwhen there is no clear hierarchical chain. Examples might include assigning\nroles to entities - where an entity can have any variation of roles.Methods between composite parts can return all manor of variable types,\ntherefore xcomposite gives you a library of decorators which you can utilise\nto define how the collective set of results should be wrangled and returned.InstallationYou can install this using pip:pip install xcompositeAlternatively you can get the source from:https://github.com/mikemalinowski/xcompositeExamplesYou can utilise this pattern like this:.. code-block:: python\n\n >>> import xcomposite\n >>>\n >>>\n >>> # -- The composition class defines the decoration rules for\n >>> # -- each method which requires compositing. This must inherit\n >>> # -- from the xcomposite.Composition class.\n >>> class A(xcomposite.Composition):\n ...\n ... @xcomposite.extend_results\n ... def items(self):\n ... return ['a', 'b']\n >>>\n >>>\n >>> # -- The class(es) being bound to the composition do not need\n >>> # -- to inherit from the composition. Equally their functions\n >>> # -- do not need to be decorated either\n >>> class B(object):\n ...\n ... def items(self):\n ... return ['x', 'y']\n >>>\n >>>\n >>> # -- We instance the composition, then bind any amount of classes\n >>> # -- to that composition. All classes being bound to a composition\n >>> # -- *must* be class instances.\n >>> a = A()\n >>> a.bind(B())\n >>>\n >>> # -- Call the items method, noting that the result is the expected\n >>> # -- list of items from the 'items' call of both A and B\n >>> # -- The composition cycles through all the bound classes, and \n >>> # -- where it finds a class with the same method name it will be\n >>> # -- called.\n >>> print(a.items())Another, similiar example might be:>>>importxcomposite>>>>>>>>># -- Inheriting off the composition class means that your class can>>># -- immediately bind any other class which is of a Composition type.>>># -- You should declare (through composite decorators) what the>>># -- expactation is of any bound methods. This allows you to tailor>>># -- exactly how the results should be combined/returned.>>>classDefinition(xcomposite.Composition):......@xcomposite.extend_results...defitems(self):...return['a','b']>>>>>>>>>classMyObject(object):......defitems(self):...return['x','y']>>>>>>>>>classMyOtherObject(object):......defitems(self):...return[1,2]>>>>>>>>># -- Instance any one of the classes, and bind it to the instance>>># -- of the other>>>definition=Definition()>>>definition.bind(MyObject())>>>definition.bind(MyOtherObject())>>>>>># -- Call the items method, noting that the result is the expected>>># -- list of items from the 'items' call of both A and B>>>print(definition.items())['a','b','x','y',1,2]DecoratorsAll composition rules are defined as decorators which you can apply to your\nmethods on your classes. The following decorators:take_min\ntake_max\ntake_sum\ntake_range\ntake_average\ntake_first\ntake_last\nany_true\nany_false\nabsolute_true\nabsolute_false\nappend_unique\nappend_results\nextend_results\nextend_unique\nupdate_dictionaryRestrictionsVersion 2.0.0 onward is significantly different to version 1.x, and is therefore\nnot compatible without changes.All methods decorated with xcomposite decorators are expected to be instance\nmethods and not class methods.Functions which are decorated with xcomposite decorators may be decorated\nwith other decorators, but any additional decorators should sit atop of the\nxcomposite decorator.Testing and StabilityThere are currently unittests which cover most of composite's core, but it is not yet exhaustive.CompatabilityThis has been tested under Python 2.7.13 and Python 3.6.6 on both Ubuntu and Windows.ContributeIf you would like to contribute thoughts, ideas, fixes or features please get in touch!mike@twisted.space"} +{"package": "xcom-proto", "pacakge-description": "xcom-protocolPython library implementing Studer-Innotec Xcom protocol for Xcom-232i and Xcom-LAN (TCP/UDP).NOTE: This lib is still WiP, so functionality is still limited, but feel free to create apull requestif you want to contribute ;)DISCLAIMER: This library is NOT officially made by Studer-Innotec.The complete official documentation is available on:Studer-Innotec Download Center-> Software and Updates -> Communication protocol Xcom-232iGetting StartedRequirementsHardwareXcom-232i or Xcom-LAN connected to your installationXcom-232i connected to PC using USB to RS-232 adapter (1) or PC in same local network as Xcom-LAN devicePC with at least USB2.0 or faster (works on Raspberry Pi 3/4 as well)(1) I personally am successfully using an adapter with the PL2303 chipset likethis oneSoftwareany Linux based OS (x86 / ARM)python3 >= 3.9python3-pipInstallationpipinstallxcom-protoImportantmake sure you select the USB to RS-232 adapter as theserialDevice, usually on Linux it is/dev/ttyUSB[0-9]when using Xcom-LAN UDP make sure MOXA is set up properly and reachable via a static IP in the local networkwhen using Xcom-LAN TCP make sure your device IP is static, reachable in the local network and specified in the MOXAMOXA Setup for Xcom-LAN TCPaddress to Studer Portal is optional and can be removed if you don't need their web interfaceData Packinghas to be set exactly as shown, you will getAssertionErrorotherwiseImportantIf you want Studer Portal to still keep working, make sure you wait for at least 5 - 10 seconds to give it time to send data.Adressing DevicesMake sure you are setting the correct destination AddressdstAddrotherwise read / write operations might not work.By defaultgetValueandsetValueuse the address100, which is a multicast address for all XTH, XTM and XTS devices, it does NOT include VarioTrack, VarioString or BSP.Furthermore if you have more than one device of each type (VarioString, VarioTrack, XTS etc.) then using the multicast address is probably not desired either.NOTE:for code examples see belowAll used addresses of Studer devices can be found in the Studer documentation (page 8, section 3.5):ExamplesReading valuesfromxcom_protoimportXcomPasparamfromxcom_protoimportXcomCfromxcom_protoimportXcomRS232fromxcom_protoimportXcomLANUDPxcom=XcomRS232(serialDevice=\"/dev/ttyUSB0\",baudrate=115200)# OR (default ports are 4002 and 4001)xcom=XcomLANUDP(\"192.168.178.110\")# OR overwriting portsxcom=XcomLANUDP(\"192.168.178.110\",dstPort=4002,srcPort=4001)boostValue=xcom.getValue(param.SMART_BOOST_LIMIT)pvmode=xcom.getValue(param.PV_OPERATION_MODE)pvpower=xcom.getValue(param.PV_POWER)*1000# convert from kW to Wsunhours=xcom.getValue(param.PV_SUN_HOURS_CURR_DAY)energyProd=xcom.getValue(param.PV_ENERGY_CURR_DAY)soc=xcom.getValue(param.BATT_SOC)battPhase=xcom.getValue(param.BATT_CYCLE_PHASE)battCurr=xcom.getValue(param.BATT_CURRENT)battVolt=xcom.getValue(param.BATT_VOLTAGE)# please look into the official Studer parameter documentation to find out# what type a parameter haspvmode_manual=xcom.getValueByID(11016,XcomC.TYPE_SHORT_ENUM)# using custom dstAddr (can also be used for getValueByID())solarPowerVS1=xcom.getValue(param.VS_PV_POWER,dstAddr=701)solarPowerVS2=xcom.getValue(param.VS_PV_POWER,dstAddr=702)print(boostValue,pvmode,pvpower,sunhours,energyProd,soc,battPhase,battCurr,battVolt)XcomLAN TCPfromxcom_protoimportXcomPasparamfromxcom_protoimportXcomCfromxcom_protoimportXcomRS232fromxcom_protoimportXcomLANTCPwithXcomLANTCP(port=4001)asxcom:boostValue=xcom.getValue(param.SMART_BOOST_LIMIT)# same as aboveWriting valuesIMPORTANT:setValue()has an optional named parameterpropertyIDwhich you can pass either:XcomC.QSP_UNSAVED_VALUE: writes value into RAM only (default when not specified)XcomC.QSP_VALUE: writes value into flash memory;you should write into flash only if youreallyneed it, write cycles are limited!fromxcom_protoimportXcomPasparamfromxcom_protoimportXcomCfromxcom_protoimportXcomRS232fromxcom_protoimportXcomLANUDPxcom=XcomRS232(serialDevice=\"/dev/ttyUSB0\",baudrate=115200)# OR (default ports are 4002 and 4001)xcom=XcomLANUDP(\"192.168.178.110\")# OR overwriting portsxcom=XcomLANUDP(\"192.168.178.110\",dstPort=4002,srcPort=4001)xcom.setValue(param.SMART_BOOST_LIMIT,100)# writes into RAMxcom.setValue(param.FORCE_NEW_CYCLE,1,propertyID=XcomC.QSP_VALUE)# writes into flash memory# using custom dstAddr (can also be used for setValueByID())xcom.setValue(param.BATTERY_CHARGE_CURR,2,dstAddr=101)# writes into RAMxcom.setValue(param.BATTERY_CHARGE_CURR,2,dstAddr=101,propertyID=XcomC.QSP_VALUE)# writes into flash memoryXcomLAN TCPfromxcom_protoimportXcomPasparamfromxcom_protoimportXcomCfromxcom_protoimportXcomRS232fromxcom_protoimportXcomLANTCPwithXcomLANTCP(port=4001)asxcom:xcom.setValue(param.SMART_BOOST_LIMIT,100)# writes into RAMxcom.setValue(param.FORCE_NEW_CYCLE,1,propertyID=XcomC.QSP_VALUE)# writes into flash memory# same as aboveTroubleshootingWriting value returnsPermission DeniederrorUsually this is caused by using the default multicast address to write values that are not part of the default address range. Seeabovefor more information.AssertionError(invalid header / frame)Usually this is caused by a wrong MOXA setup when using UDP / TCP, make sureData Packingis set correctly in the MOXA. Seeabovefor more information.When using Xcom-232i then checksum errors and AssertionErrors can be caused by a bad RS232 connection or a wrong BAUD rate setting."} +{"package": "xcon", "pacakge-description": "IntroductionDocumentationQuick StartInstallUsing ItQuick OverviewPlaces Configuration is Retrieved FromParam Store Provider SpecificsSecrets Manager Provider SpecificsCase SensitivityAdd PermissionsCachingTime to liveTable Layout DetailsUnit TestsLicensingIntroductionHelps retrieve configuration information from aws/boto services such as Ssm's Param Store and Secrets Manager,\nwith the ability the cache a flattened list into a dynamodb table.Right now this ispre-release software, as the dynamo cache table and related need further documentation and testing.Retrieving values from Param Store and Secrets Manager should work and be relatively fast, as we bulk-grab values\nat the various directory-levels that are checked.More documentation and testing will be coming soon, for a full 1.0.0 release sometime in the next month or so.Seexcon docs.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiQuick StartInstall# via pippipinstallxcon# via poetrypoetryaddxconUsing ItFrom the get-go and by default, environmental variables will 'just work'.The main class isConfigviafrom xcon import Config.This class usesxinjectto do dependency injection.\nYou can easily inject a new version/configuration of the object without having to couple you code too close\ntogether to get your configuration settings.You get the current Config object via:fromxconimportConfigcurrent_config=Config.grab()setting_value=current_config.get('some_setting')An easier way to always use the current Config object is to use a proxy object.# Instead of importing the class, we import a proxy to the currently injected instance:fromxconimportconfigsetting_value=config.get('some_setting')Alternatively, ou can also useConfig.proxy()to get a proxy.# Importing proxy object to current Config injectable dependency.# You can use it as if you did `Config.grab()`, as it does this# for you each time you get something from it.fromxconimportconfigimportos# Setting a environmental variable value to showcase retrieving it.os.environ['SOME_CONFIG_VARIABLE']=\"my-value\"# If you had an environmental variable called `SOME_CONFIG_VARIABLE`, this would find it:assertconfig.get('some_config_variable')==\"my-value\"# Alternate 'dict; syntax, works just like you would expect.# Just like dict, it will raise an exception if value not found.assertconfig['some_config_variable']==\"my-value\"Config names are case-insensitive (although directory names are case-sensitive).By default,Config{target=_blank} will look at environmental variables first,\nand then other remote places second (the order and where to look is all configurable).Quick OverviewPlaces Configuration is Retrieved FromAs a side note for the below paths theSERVICE_NAMEandAPP_ENVvariables\ncome fromxcon.xcon_settings.environmentandxcon.xcon_settings.service.\nBy default, these settings will use theSERVICE_NAMEandAPP_ENVenvironmental variables. You can also set/override them expiclity\nby setting a value onexcon.xcon_settings.environmentand/orxcon.xcon_settings.service.By default, Config will look in these paths (first)./{APP_NAME}/{APP_ENV}/{variable_name}/{APP_NAME}/all/{variable_name}/global/{APP_ENV}/{variable_name}/global/all/{variable_name}Details:Standard Directory PathsDirectory ChainFor each directory/path, we go through these providers (second):Environmental VariablesDynamo Config CacheWill be skipped if table/permissions don't exist.AWS Secrets ManagerWill be skipped if needed permissions not in placeAWS Param StoreWill be skipped if needed permissions not in placeDetails:Provider ChainSupported Providers** TODO In the order they are specified above (seeStandard Lookup Order).Param Store Provider SpecificsValues are exclusively retrieved via \"GetParametersByPath\"; which allows for bulk-retrieval of settings.All settings in a particular directory are retrieved in one request, and then whatever value is needed is returned.\nThese values are cached within the provider retriever object, so when other config values are asked for\nthere is a good chance it can return a value without having to go back to param store to ask for another value.Secrets Manager Provider SpecificsSecrets manager does not allow for bulk-retrieval of values.\nInstead, you can bulk-request get a list of available secret names viaListSecretVersionIds.The secrets provider will grab the full list, and then use that to know what is or is not available to get.\nThis makes it much faster, as it can quickly determine if it should attempt to retrieve a value or not based on this list.Case SensitivityThe directory/path is case-sensitive; but theVARIABLE_NAMEpart at the end is case-insensitive.So environmental variables are entirely case-insensitive, as they only have theVAIRABLE_NAMEand no directory path.So you can doconfig.get('some_var_name'), and it would still find a value for it,\neven if the name in the source/provider of values isSOME_VAR_NAME.Add PermissionsIf you want to receive values from remote locations, the app will need the correct permissions.For example, AWS's Param Store service will restrict access to the param values by path/directory.There is a serverless permission resource template yaml file you can use directory or copy\nand change as needed for your purposes.AWS Configuration Store Permissions:Param StoreSecrets ManagerIf you want to use a dynamo table cache (seecachingin next section), use these:DynamoDB Cache Table:App PermissionsTable DefinitionFor more details, seePermissions.CachingThe purpose of the cache is to limit calls to the providers,\nto prevent throttling from them.For example, the AWS Param Store will throttle calls if there are too many per-second,\nwhich could happen if several lambdas get launched and each lookup configuration simultaneously.By default, values that are remotely looked up (ie: non-environmental variables)\nare cached in a dynamo table.\nEach of these lambdas can first check a DynamoDB cache table first, and if the value they need\nis in there it will use that instead of attempting to retrieve values from the providers.When something is not in the cache table, Config will look at each configured provider\nand when it finds the value (or lack of a value), it will store what it found in the\ndynamo cache table for later faster lookup.The cache is a flattened list of all resolved values from all configured sources.\nIt will correctly cache according to the current providers, paths, and app environment + service.\nAny of these variables can dynamically change, this information is added to each cached\nentry so the correct value will be used in any situation.Time to liveThe cache table is configured with a time-to-live attribute (namedttl).\nThe value is set for 12 hours, after which the item will expire.There is an logarithm built intoConfigcaching mechanism that will\npre-expire items sooner than normal randomly.\nThe algorith makes it more likely a particular item in the cache will expire\nsooner as the expire-time approaches.This means something that will expire in one hour will be more likely to\nbe pre-expired than something that has 10 hours left.This helps ensure that if a lambda is very busy and has many concurrent\ninstances running that it's likely only one of the lambdas would pre-expire\nthe cached items and 'refresh' them by re-looking up the values from the\nproviders and re-caching the newly looked up values.This is a way to coordinate cache expiring and refreshing without\nhaving to actually have any coordinating communication happening.This allows the configuration refreshing to automatically scale\nwith the lambda activity in such a way as to limit the possibility\nof being throttled from param store or secrets manager.Table Layout DetailsThe dynamo table has a two-part primary key.The first part of the primary key is a hash key made up of appsxcon.xcon_settings.environmentandxcon.xcon_settings.servicevalues.\nThis is the 'partition' key in the DynamoDB table, and AWS policies can allow\nor deny access based on this hash key.\nThis allows the table to limit access to cached items by app's environment + service.The second part of the primary key is a range-key made up of all provider names\nand directory paths in the order they are looked up in. This allows multiple\nvalues to be stored for the same config setting, depending on which providers\nand directory paths were used to lookup the config setting.This allows all looked up values for all dynamic situations to be cached\nand used correctly.For details seeCaching Details,Historical Background.Unit TestsBy default, unit tests will always start with a Config object that has caching disabled,\nand only uses the environmental provider (ie: only looks at environmental variables).This is accomplished via an autouse fixture in a pytest plugin module\n(see plugin modulexcon.pytest_pluginor fixturexcon.pytest_plugin.xcon).If a project hasxconas a dependency, pytest will find this plugin module\nand automatically use it. Nothing more to do.As an FYI/side-note: There is axinject.pytest_plugin.xyn_contextthat will also\nautomatically configure a blank context for each unit test.This does mean you must configure Config using a fixture or at the top of your unit test method,\nas any changes at the module-level will be forgotten.The reason we do this is it guarantees that resources/config changes won't be propagaed/leak\ninto another unit test.The end result is there is need to worry about these basics,\nas they are taken care of for you automatically as long as the library is installed\nas a dependency.LicensingThis library is licensed under the \"The Unlicense\" License. See the LICENSE file."} +{"package": "xconf", "pacakge-description": "xconf- Dataclasses and TOML for command configurationDemoAn example of how to usexconf.Command,xconf.field, andxconf.configis indemo.py. Run it to see its configuration keys.$ python demo.py demo_command -h\ndemo_command: Demo command\nusage: demo.py demo_command [-c CONFIG_FILE] [-h] [-v] [--dump-config] [vars ...]\n\npositional arguments:\n vars Config variables set with 'key.key.key=value' notation\n\noptional arguments:\n -c CONFIG_FILE, --config-file CONFIG_FILE\n Path to config file (default: demo_command.conf.toml)\n -h, --help Print usage information\n -v, --verbose Enable debug logging\n --dump-config Dump final configuration state as TOML and exit\nconfiguration keys:\n collections\n dict[str, ExtendedThingie]\n collections..name\n str\n collections..extended\n bool\n either_one\n [int, str]\n should_bar\n bool\n (default: False)\n should_foo\n bool\n Whether demo should foo\n number_list\n list[int]\n List of favorite numbers\n sequence\n list[ExtendedThingie]Default config fileThe command name,demo_command, is generated from the class name and used to find a default configuration file (demo_command.conf.toml) in the current directory.Providing arguments at the command lineAny configuration key from the help output can be supplied on the command line in adotted.name=valueformat.For lists of primitive types (str,int,float), you can just use commas to separate the values on the right hand side of the=. Example:number_list=1,2,3.To override a single entry in a list, usesome_name[#]ordotted[#].name=valuewhere#is an integer index will work. Example:number_list[0]=99String values are bare (i.e. no quotation marks aroundvalue). Boolean values are case-insensitivetrue,t, or 1 for True,false,f, or 0 for False.Structuring the commandSeedemo.pyfor an example. Note that commands must subclassxconf.Commandandapply the@xconf.configdecorator. Options are defined by a hierarchy of dataclasses. (For uninteresting reasons, they aren'tstrictly speakingimport dataclassdataclasses.)LicenseAll code outsidexconf/vendor/is provided under the terms of theMIT License, except fordemo.pyanddemo_command.conf.toml, which are released into the public domain for you to build off of.Note that code underxconf/vendor/is used under the terms of the licenses listed there."} +{"package": "xconfig", "pacakge-description": "python-lib-templateconfig=Config('./ciao.yaml')# writes a new field in configconfig.write(f'cose.cosa','ciao')print(config['cose']['cosa'])# ciao# pushes a new obj in configconfig.push(f'arrays.array_id',1)config.push(f'arrays.array_id',2)print(config['arrays']['array_id'])# [1, 2]cose:cosa:ciaoarrays:array_id:-1-2"} +{"package": "xConfigparser", "pacakge-description": "No description available on PyPI."} +{"package": "xconnectpy", "pacakge-description": "UNKNOWN"} +{"package": "xcookie", "pacakge-description": "Thexcookiemodule. A helper for templating python projects.Read the docshttps://xcookie.readthedocs.ioGithubhttps://github.com/Erotemic/xcookiePypihttps://pypi.org/project/xcookieThe goal is to be able to setup and update Python project structures with consistent\nboilerplate for things like CI,setup.py, and requirements.It handles:Multiple version control remotes:GithubGitlabpure python packagespython packages with scikit-build binary extensionsrotating secretsCI scripts for github or gitlab where the general pattern is:Lint the projectBuild the pure python or binary wheelsTest the wheels in the supported environments (i.e. different operating systems / versions of Python)Optionally sign the wheels with online GPG keysUpload the wheels to test pypi or live pypi.This is primarily driven by the needs of my projects and thus has some logic\nthat is specific to things I\u2019m doing. However, these are all generally behind\nchecks for the \u201cerotemic\u201d tag. I am working on slowly making this into a proper\nCLI that is externally usable.The top level CLI is:positional arguments:\n repodir path to the new or existing repo\n\noptions:\n -h, --help show this help message and exit\n --repodir REPODIR path to the new or existing repo (default: .)\n --repo_name REPO_NAME\n defaults to ``repodir.name`` (default: None)\n --mod_name MOD_NAME The name of the importable Python module. defaults to ``repo_name`` (default: None)\n --pkg_name PKG_NAME The name of the installable Python package. defaults to ``mod_name`` (default: None)\n --rel_mod_parent_dpath REL_MOD_PARENT_DPATH\n The location of the module directory relative to the repository root. This defaults to simply placing the module in\n \".\", but another common pattern is to specify this as \"./src\". (default: .)\n --rotate_secrets [ROTATE_SECRETS], --no-rotate_secrets\n If True will execute secret rotation (default: auto)\n --refresh_docs [REFRESH_DOCS], --no-refresh_docs\n If True will refresh the docs (default: auto)\n --os OS all or any of win,osx,linux (default: all)\n --is_new IS_NEW If the repo is detected or specified as being new, then steps to create a project for the repo on github/gitlab and\n other initialization procedures will be executed. Otherwise we assume that we are updating an existing repo. (default:\n auto)\n --min_python MIN_PYTHON\n --typed TYPED Should be None, False, True, partial or full (default: None)\n --supported_python_versions SUPPORTED_PYTHON_VERSIONS\n can specify as a list of explicit major.minor versions. Auto will use everything above the min_python version (default:\n auto)\n --ci_cpython_versions CI_CPYTHON_VERSIONS\n Specify the major.minor CPython versions to use on the CI. Will default to the supported_python_versions. E.g. [\"3.7\",\n \"3.10\"] (default: auto)\n --ci_pypy_versions CI_PYPY_VERSIONS\n Specify the major.minor PyPy versions to use on the CI. Defaults will depend on purepy vs binpy tags. (default: auto)\n --ci_versions_minimal_strict CI_VERSIONS_MINIMAL_STRICT\n todo: sus out (default: min)\n --ci_versions_full_strict CI_VERSIONS_FULL_STRICT\n --ci_versions_minimal_loose CI_VERSIONS_MINIMAL_LOOSE\n --ci_versions_full_loose CI_VERSIONS_FULL_LOOSE\n --remote_host REMOTE_HOST\n if unspecified, attempt to infer from tags (default: None)\n --remote_group REMOTE_GROUP\n if unspecified, attempt to infer from tags (default: None)\n --autostage AUTOSTAGE\n if true, automatically add changes to version control (default: False)\n --visibility VISIBILITY\n or private. Does limit what we can do (default: public)\n --version VERSION repo metadata: url for the project (default: None)\n --url URL repo metadata: url for the project (default: None)\n --author AUTHOR repo metadata: author for the project (default: None)\n --author_email AUTHOR_EMAIL\n repo metadata (default: None)\n --description DESCRIPTION\n repo metadata (default: None)\n --license LICENSE repo metadata (default: None)\n --dev_status DEV_STATUS\n --enable_gpg ENABLE_GPG\n --defaultbranch DEFAULTBRANCH\n --xdoctest_style XDOCTEST_STYLE\n type of xdoctest style (default: google)\n --ci_pypi_live_password_varname CI_PYPI_LIVE_PASSWORD_VARNAME\n variable of the live twine password in your secrets (default: TWINE_PASSWORD)\n --ci_pypi_test_password_varname CI_PYPI_TEST_PASSWORD_VARNAME\n variable of the test twine password in your secrets (default: TEST_TWINE_PASSWORD)\n --regen REGEN if specified, any modified template file that matches this pattern will be considered for re-write (default: None)\n --tags [TAGS ...] Tags modify what parts of the template are used. Valid tags are: \"binpy\" - do we build binpy wheels? \"erotemic\" - this\n is an erotemic repo \"kitware\" - this is an kitware repo \"pyutils\" - this is an pyutils repo \"purepy\" - this is a pure\n python repo \"gdal\" - add in our gdal hack # TODO \"cv2\" - enable the headless hack \"notypes\" - disable mypy in lint\n checks (default: auto)\n --interactive INTERACTIVE\n --yes YES Say yes to everything (default: False)\n --linter LINTER if true enables lint checks in CI (default: True)Invocations to create a new github repo:# Create a new python repopython-mxcookie.main--repo_name=cookiecutter_purepy--repodir=$HOME/code/cookiecutter_purepy--tags=\"github,purepy\"# Create a new binary repopython-mxcookie.main--repo_name=cookiecutter_binpy--repodir=$HOME/code/cookiecutter_binpy--tags=\"github,binpy,gdal\"Given an initalized repository the general usage pattern is to edit the\ngeneratedpyproject.tomland modify values in the[tool.xcookie]section and then rerunxcookiein that directory. It will then present you\nwith a diff of the proposed changes that you can reject, accept entirely, or\naccept selectively.For some files where the user is likely to do custom work, xcookie won\u2019t try to\noverwrite the file unless you tell it to regenerate it. Thesetup.pyis\nthe main example of this, so if you want xcookie to update your setup.py you\nwould runxcookie--regensetup.pyFor rotating secrets, the interface is a bit weird. I haven\u2019t gotten it to work\nwithin an xcookie invocation due to the interactive nature of some of the\nsecret tools, but if you runxcookie--rotate-secrets, when it ask you\"Ready to rotatesecrets?\", say no, and it will list the commands that it\nwould have run. So you can just copy / paste those manually. I hope to make\nthis easier in the future."} +{"package": "xcope-daemon", "pacakge-description": "PyXcope.DaemonHow to compile protobufThediagnose_daemon.protois a grpc protobuf file. It should keep consistent with the server endpoint.\nWhenever it changes, we must regenerate with commands on linux(dont' use on windows):cdsrc\npython3-mgrpc_tools.protoc-I=.--python_out=.--pyi_out=.--grpc_python_out=../xcope_daemon/*.proto"} +{"package": "xcore", "pacakge-description": "Xcore is a crystallographic space group library written in Python.Usage>>> from xcore import UnitCell, SpaceGroup\n\n>>> spgr = SpaceGroup(\"Pnma\")\n>>> spgr.info()\nSpace group Pnma\n\n Number 62\n Schoenflies D2h^16\n Hall -P 2ac 2n\n H-M symbol Pnma\n\nLaue group mmm\nPoint group mmm\nOrthorhombic\nCentrosymmetric\n\nOrder 8\nOrder P 8\n\n# +(0.0 0.0 0.0), Inversion Flag = 0\nx,y,z\n-x+1/2,-y,z+1/2\nx+1/2,-y+1/2,-z+1/2\n-x,y+1/2,-z\n# +(0.0 0.0 0.0), Inversion Flag = 1\n-x,-y,-z\nx+1/2,y,-z+1/2\n-x+1/2,y+1/2,z+1/2\nx,-y+1/2,zor:>>> cell = UnitCell((19.9020, 10.1561, 24.6892, 105.88), \"P21/c\", name=\"SSO\", composition=\"Si80 O163\")\n>>> cell.info()\nCell SSO (Si80 O163)\n a 19.9020 al 90.00\n b 10.1561 be 105.88\n c 24.6892 ga 90.00\nVol. 4799.90\nSpgr P121/c1Installationpip install xcoreRequirementsPython2.7NumpyPandasInspired by (and built on)sginfo."} +{"package": "xcoscmd", "pacakge-description": "\u4ecb\u7ecd\u817e\u8baf\u4e91COS\u547d\u4ee4\u884c\u5de5\u5177, \u76ee\u524d\u53ef\u4ee5\u652f\u6301Python2.6\u4e0ePython2.7\u4ee5\u53caPython3.x\u3002\u5b89\u88c5\u6307\u5357python setup.py install\ncd dist\nsudo easy_install coscmd-1.8.6.3-py3.6.egg # \u63d0\u524d\u5b89\u88c5easy_install\nln -s {{PYTHON_DIR}}/bin/coscmd xcoscmd # [\u53ef\u9009]\u4e3a\u907f\u514d\u548c\u5b98\u65b9coscmd\u51b2\u7a81\uff0c\u901a\u8fc7\u8f6f\u94fe\u4f7f\u7528\u6b64\u7248\u672c\u6539\u9020\u4e0a\u4f20\u547d\u4ee4\uff0c\u652f\u6301\u4e0a\u4f20\u540c\u540d\u6587\u4ef6\u4e0d\u8986\u76d6\uff0c\u76f4\u63a5\u8df3\u8fc7\u547d\u4ee4:xcoscmd -rm ./app /app\u4e0a\u4f20\u7ed3\u679c\u8f93\u51fa\u4f18\u5316\uff1a\u4e0a\u4f20\u5931\u8d25\u7684log\u7ea2\u8272\u663e\u793a\uff0c\u4e0a\u4f20\u6210\u529f\u7684log\u7eff\u8272\u663e\u793a\uff0c\u66f4\u52a0\u76f4\u89c2\u7684\u663e\u793a\u4e0a\u4f20\u7ed3\u679c\u4f7f\u7528\u65b9\u6cd5\u4f7f\u7528coscmd\uff0c\u53c2\u7167https://cloud.tencent.com/document/product/436/10976"} +{"package": "xcover", "pacakge-description": "xcoverA python package for solving exact cover with colours problems.InstallationThis package can be installed using pip:pip install xcoverThe only dependency isnumba.UsageA simple example of anexact coverproblem is the following. Given the set of 6 options\n0:={1, 4, 7}; 1:={1, 4}; 2:={4, 5, 7}; 3:={3, 5, 6}; 4:={2, 3, 6, 7}; 5:={2, 7}, each of which are subsets of a set of seven items (the numbers 1 to 7), find a subset of the options which contains each item once and only once. Such a problem can be solved using the package asfrom xcover import covers\n\noptions = [[1, 4, 7], [1, 4], [4, 5, 7], [3, 5, 6], [2, 3, 6, 7], [2, 7]]\nprint(list(covers(options)))[[1, 3, 5]]which outputs a list of possible exact covers. In this case there is a single solution: cover by the options 1:={1, 4}, 3:={3, 5, 6}, and 5:={2, 7}.Thecoversfunction returns apython generator, an object that can be used in aforloop. This is useful in the case of multiple solutions if you want to do something immediately with each solution as it is calculated. If you just want to find the next solution you can use thenextfunction on the generator.Exact cover with coloursThe package supports two extensions to the standard exact cover problem. The first extension is the addition of secondary items. These are items that do not need to be covered, but may be covered once if required. The second extension is the ability to colour the secondary items in each option. In the coloured case the secondary item may be covered multiple times, so long as it is coloured the same way in each cover. A simple example of an exact cover with colours problem is the followingprimary = [\"p\", \"q\", \"r\"]\nsecondary = [\"x\", \"y\"]\noptions = [\n [\"p\", \"q\", \"x\", \"y:A\"],\n [\"p\", \"r\", \"x:A\", \"y\"],\n [\"p\", \"x:B\"],\n [\"q\", \"x:A\"],\n [\"r\", \"y:B\"],\n]\n\nprint(list(covers(options, primary=primary, secondary=secondary, colored=True)))[[3, 1]]In this problem there are three primary itemsp,q, andrthat must be covered, and two secondary itemsxandythat may be covered. The exact cover is given by the two sets {p,r,x:A,y} and {q,x:A}. In this cover the itemxis covered twice, but that is acceptable as both instances are coloredA. The xcover package denotes the colouring of items by a colon followed by a label.Boolean arraysAn alternative way of specifying an exact cover problem is in terms of aboolean incidence matrix. The package provides acovers_boolfunction for directly solving such problems.import numpy as np\nfrom xcover import covers_bool\n\nmatrix = np.array([\n [1, 0, 0, 1, 0, 0, 1],\n [1, 0, 0, 1, 0, 0, 0],\n [0, 0, 0, 1, 1, 0, 1],\n [0, 0, 1, 0, 1, 1, 0],\n [0, 1, 1, 0, 0, 1, 1],\n [0, 1, 0, 0, 0, 0, 1]\n ], dtype=bool)\nprint(next(covers_bool(matrix)))[1, 3, 5]Dancing cellsThe algorithm used for finding the exact covers isDonald Knuth'salgorithm C which uses \"dancing cells\". A full description of the algorithm can be found in hisdraft manuscript. The main algorithm is inxcover.dancing_cells.algorithm_cand can be called directly if desired.NumbaTo accelerate the performance of the solver this package usesnumbato perform Just In Time (JIT) compilation of the main algorithm. This means the first call to the solver may be slow (a few seconds) while numba compiles the function. However, later calls will be fast, as numba uses a cache to avoid repeated compilation. JIT compilation can be disabled by explicitly configuring numba before importing thexcoverpackage.from numba import config\nconfig.DISABLE_JIT = TrueApplicationsMany recreational mathematical puzzles can be naturally cast as exact cover problems. Examples include pentomino tiling, sudoku, and the n-queens problem. Donald Knuth'sArt of Computing volume 4Bhas an extensive discussion of many such problems. Exact cover problems areNP-completewhich means solve times can get very long very quickly as problems get larger. Be warned!LicenseThis package is licenced under the GNU Lesser General Public License v3.0."} +{"package": "xcover-expression-language", "pacakge-description": "A DSL that evaluates against Python API."} +{"package": "xcover-python", "pacakge-description": "\u00b7 xcover-python \u00b7xcover-pythonis a Python API Client forXCover.Installationxcover-pythonis available on PyPI. To install the latest version run:pip install xcover-pythonorpoertry install xcover-pythonFeaturesAuthenticationSimple configuration using env variables(WIP) High-level API to perform partner operations on quotes and bookingsConfigurationConfig objectThe library providesXCoverConfigdataclass that can be used as shown:fromxcoverimportXCover,XCoverConfigclient=XCover(XCoverConfig(# minimal config, check autocomplete for more optionsbase_url=\"https://api.xcover.com/xcover\",partner_code=\"--PARTNER_CODE--\",auth_api_key=\"--API_KEY--\",auth_api_secret=\"--API_SECRET--\",))Env variablesAlternatively, it is possible to use env variables.The full list of configuration options:XC_BASE_URL(XCoverConfig.base_url): XCover base URL (e.g.https://api.xcover.com/api/v2/).XC_PARTNER_CODE(XCoverConfig.partner_code): Partner code (e.g.LLODT).XC_HTTP_TIMEOUT(XCoverConfig.http_timeout): HTTP timeout in seconds. Default value is10.XC_AUTH_API_KEY(XCoverConfig.auth_api_key): API key to use.XC_AUTH_API_SECRET(XCoverConfig.auth_api_secret): API secret to use.XC_AUTH_ALGORITHM(XCoverConfig.auth_algorithm): HMAC encoding algorithm to use. Default ishmac-sha512.XC_AUTH_HEADERS(XCoverConfig.auth_headers): Headers to sign. Default is(request-target) date.XC_RETRY_TOTAL(XCoverConfig.retry_total): Total number of retries. Default is5.XC_RETRY_BACKOFF_FACTOR(XCoverConfig.retry_backoff_factor): Backoff factor for retries timeout. Default is2.Usage exampleUsing low-levelcallmethodimportrequestsfromxcover.xcoverimportXCover# Env variables are usedclient=XCover()# Prepare payloadpayload={\"request\":[{\"policy_type\":\"event_ticket_protection\",\"policy_type_version\":1,\"policy_start_date\":\"2021-12-01T17:59:00.831+00:00\",\"event_datetime\":\"2021-12-25T21:00:00+00:00\",\"event_name\":\"Ariana Grande\",\"event_location\":\"The O2\",\"number_of_tickets\":2,\"tickets\":[{\"price\":100},],\"resale_ticket\":False,\"event_country\":\"GB\",}],\"currency\":\"GBP\",\"customer_country\":\"GB\",\"customer_region\":\"London\",\"customer_language\":\"en\",}# Calling XCover APIresponse:requests.Response=client.call(method=\"POST\",url=\"partners/LLODT/quotes/\",payload=payload,)quote=response.json()print(quote)RetriesThis client will automatically retry certain operations when it is considered safe to do this.\nThe retry number and intervals could be controlled via XC_RETRY_TOTAL and XC_RETRY_BACKOFF_FACTOR\nenvironment variables ot the same config options.Auto retry logic can be enabled/disabled per operation. However, further fine-tuning is possible\nvia extending XCover class if required."} +{"package": "xcp", "pacakge-description": "A simple API for parsing (small) XML config files and building an object model\nof the XML data. This package relies on the expat parser to parse the XML data."} +{"package": "xcpcio-board-spider", "pacakge-description": "xcpcio/board-spiderDevelopment# run testpoetryrunpytest\npoetryrunpytest--snapshot-update# releasepoetryversionpatchSponsorsLicenseMITLicense \u00a9 2020 - PRESENTXCPCIO"} +{"package": "xcpengine-container", "pacakge-description": "functional connectivity after preprocessing with FMRIPREP.Home-page: https://github.com/pennbbl/xcpEngineAuthor:Author-email:Maintainer:Maintainer-email:License: 3-clause BSDDescription: This package is a basic wrapper for xcpEngine that generates the appropriateDocker commands, providing an intuitive interface to running xcpEngineworkflow in a Docker environment.Platform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: Science/ResearchClassifier: License :: OSI Approved :: BSD LicenseClassifier: Programming Language :: Python :: 3.6"} +{"package": "xcp-esgar", "pacakge-description": "xcp_esgarA transformer based Q&A solution for experimentation with BERT - Q&A system based decision processes.FeaturesTODOCreditsThis package was created withCookiecutterand therayniervanegmond/pypackageproject template."} +{"package": "xcppcloud", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xcproxy", "pacakge-description": "No description available on PyPI."} +{"package": "xcpy", "pacakge-description": "No description available on PyPI."} +{"package": "xcpythontool", "pacakge-description": "\u6d4b\u8bd5\u4e0a\u4f20pip\u2026"} +{"package": "xcrawler", "pacakge-description": "A multi-threaded, open source web crawlerFeaturesUse multiple threads to visit web pagesExtract web page data using XPath expressions or CSS selectorsExtract urls from a web page and visit extracted urlsWrite extracted data to an output fileSet HTTP session parameters such as: cookies, SSL certificates, proxiesSet HTTP request parameters such as: header, body, authenticationDownload files from the urlsSupports Python 2 and Python 3Installationpip install xcrawlerWhen installinglxmllibrary on Windows you may encounterMicrosoft Visual C++ is requirederrors.To installlxmllibrary on Windows:Download and install Microsoft Windows SDK:For Python 2.6, 2.7, 3.0, 3.1, 3.2:Microsoft Windows SDK for .NET Framework 3.5 SP1For Python 3.3, 3.4:Microsoft Windows SDK for .NET Framework 4.0Click the Start Menu, search for and open the command prompt:For Python 2.6, 2.7, 3.0, 3.1, 3.2:CMD ShellFor Python 3.3, 3.4:Windows SDK 7.1 Command PromptInstalllxmlsetenv /x86 /release && SET DISTUTILS_USE_SDK=1 && set STATICBUILD=true && pip install lxmlUsageData and urls are extracted from a web page by a page scraper.To extract data and urls from a web page use the following methods:extractreturns data extracted from a web pagevisitreturns next Pages to be visitedA crawler can be configured before crawling web pages. A user can configure such settings of the crawler as:* the number of threads used to visit web pages* the name of an output file* the request timeoutTo run the crawler call:crawler.run()Examples how to use xcrawler can be found at:https://github.com/cardsurf/xcrawler/tree/master/examplesXPath ExamplefromxcrawlerimportXCrawler,Page,PageScraperclassScraper(PageScraper):defextract(self,page):topics=page.xpath(\"//a[@class='question-hyperlink']/text()\")returntopicsstart_pages=[Page(\"http://stackoverflow.com/questions/16622802/center-image-within-div\",Scraper())]crawler=XCrawler(start_pages)crawler.config.output_file_name=\"stackoverflow_example_crawler_output.csv\"crawler.run()CSS ExamplefromxcrawlerimportXCrawler,Page,PageScraperclassStackOverflowItem:def__init__(self):self.title=Noneself.votes=Noneself.tags=Noneself.url=NoneclassUrlsScraper(PageScraper):defvisit(self,page):hrefs=page.css_attr(\".question-summary h3 a\",\"href\")urls=page.to_urls(hrefs)return[Page(url,QuestionScraper())forurlinurls]classQuestionScraper(PageScraper):defextract(self,page):item=StackOverflowItem()item.title=page.css_text(\"h1 a\")[0]item.votes=page.css_text(\".question .vote-count-post\")[0].strip()item.tags=page.css_text(\".question .post-tag\")[0]item.url=page.urlreturnitemstart_pages=[Page(\"http://stackoverflow.com/questions?sort=votes\",UrlsScraper())]crawler=XCrawler(start_pages)crawler.config.output_file_name=\"stackoverflow_css_crawler_output.csv\"crawler.config.number_of_threads=3crawler.run()File ExamplefromxcrawlerimportXCrawler,Page,PageScraperclassWikimediaItem:def__init__(self):self.name=Noneself.base64=NoneclassEncodedScraper(PageScraper):defextract(self,page):url=page.xpath(\"//div[@class='fullImageLink']/a/@href\")[0]item=WikimediaItem()item.name=url.split(\"/\")[-1]item.base64=page.file(url)returnitemstart_pages=[Page(\"https://commons.wikimedia.org/wiki/File:Records.svg\",EncodedScraper())]crawler=XCrawler(start_pages)crawler.config.output_file_name=\"wikimedia_file_example_output.csv\"crawler.run()Session ExamplefromxcrawlerimportXCrawler,Page,PageScraperfromrequests.authimportHTTPBasicAuthclassScraper(PageScraper):defextract(self,page):returnpage.__str__()start_pages=[Page(\"http://192.168.1.1/\",Scraper())]crawler=XCrawler(start_pages)crawler.config.output_file_name=\"router_session_example_output.csv\"crawler.config.session.headers={\"User-Agent\":\"Custom User Agent\",\"Accept-Language\":\"fr\"}crawler.config.session.auth=HTTPBasicAuth('admin','admin')crawler.run()Request ExamplefromxcrawlerimportXCrawler,Page,PageScraperclassScraper(PageScraper):defextract(self,page):returnpage.__str__()start_page=Page(\"http://192.168.5.5\",Scraper())start_page.request.cookies={\"theme\":\"classic\"}crawler=XCrawler([start_page])crawler.config.request_timeout=(5,5)crawler.config.output_file_name=\"router_request_example_output.csv\"crawler.run()DocumentationFor more information about xcrawler see the source code and Python Docstrings:source codeThe documentation can also be accessed at runtime with Python\u2019s built-inhelpfunction:>>>importxcrawler>>>help(xcrawler.Config)# Information about the Config class>>>help(xcrawler.PageScraper.extract)# Information about the extract method of the PageScraper classLicenceGNU GPL v2.0"} +{"package": "xcresult", "pacakge-description": "xcresult"} +{"package": "xcross", "pacakge-description": "xcross\"Zero setup\" cross-compilation for a wide variety of architectures. xcross includes compact dockerimagesand a build utility for minimal setup C/C++ cross-compiling, inspired byrust-embedded/cross. xcross provides toolchains for a wide variety of architectures and C libraries, and targets both bare-metal and Linux-based systems, making it ideal for:Testing cross-platform support in CI pipelines.Building and deploying cross-compiled programs.Each Docker image comes pre-installed with:C and C++ cross compiler and standard libraryAutotoolsBinutilsCMakeNinjaIn addition, each xcross providesimagespre-installed with popular C/C++ package managers and addition build tools:ConanvcpkgMesonNote that this project is similar todockcross, however, xcross supports more targets and build tools than dockcross. If you need Docker images of common architectures, dockcross should have better support.Table of ContentsMotivationGetting StartedInstallingxcrossBuild ToolsrunDockerTravis CI ExampleSandboxingPackage ManagersUsing xcrossOther UtilitiesBuilding/Running DockerfilesImagesDevelopment DependenciesToolchain FilesDeveloping New ToolchainsPlatform SupportLicenseContributingMotivationUnlike 10 years ago, we no longer live in an x86 world. ARM architectures are nearly ubiquitous in mobile devices, and popular in embedded devices, servers, and game systems. IBM's POWER and z/Architecture can run some high-end servers. PowerPC systems are popular in embedded devices, and used to be popular architectures for game systems, desktops, and servers. MIPS has been integral to autonomous driving systems and other embedded systems. RISC-V is rapidly being adopted for a wide variety of use-cases. The IoT market has lead to an explosion in embedded devices.At the same time, modern software design builds upon a body of open source work. It is more important than ever to ensure that foundational libraries are portable, and can run on a wide variety of devices. However, few open source developers can afford a large selection of hardware to test code on, and most pre-packaged cross-compilers only support a few, common architectures.Normally, cross compilers are limited by long compile times (to build the cross-compiler) and non-portable toolchain files, since the toolchain cannot be added to the path. Docker images pre-installed with cross-compiler toolchains solve this, by isolating the toolchain from the host, enabling building, testing, and deploying cross-compiled code in seconds, rather than hours. Each toolchain is installed on-path, and cross-compilation configurations are injected for each build system, enabling out-of-the-box cross-compilation for CMake, Autotools, Makefiles, and Meson. Finally, a Python scriptxcrosshandles all Docker configurations to make cross-compiling as easy as compiling on the host machine.It just works.Getting StartedThis shows a simple example of building and running a C++ project on DEC Alpha, a 64-bit little-endian system.Installingxcross may be installed viaPyPi:pipinstallxcross--userOr xcross may be installed via git:gitclonehttps://github.com/Alexhuszagh/xcrosscdxcross\npipinstall.--userxcrossxcross is a Python script to provide \"zero-setup\" cross-compiling, similar to Rust'scross. To use it, merely addxcrossbefore any command along with a valid target. To configure, build, and make a CMake project, run:exportCROSS_TARGET=alpha-unknown-linux-gnu\nxcrosscmake..\nxcrossmake-j5runxcross includes aruncommand for most images, which uses Qemu to run the cross-compiled binaries.xcrossrunpath/to/filerunworks for both statically and dynamically-linked binaries, ensuring linked libraries are in Qemu's search path.DockerFor more fine-tuned control, you can also run an interactive session within a container. An extended example is:# Pull the Docker image, and run it interactively, entering the container.xcross--targetalpha-unknown-linux-gnu# Clone the repository, build and run the code in the container using CMake.gitclonehttps://github.com/Alexhuszagh/cpp-helloworld.gitcdcpp-helloworld\nmkdirbuild&&cdbuild# Build a default executable: no toolchain file required.cmake..\nmake# Just works, as long as `add_custom_target` uses# `${CMAKE_CROSSCOMPILING_EMULATOR} $`# This uses Qemu as a wrapper, so running the executable# only works on some architectures.makerun# Can also run executables manually.runhello# Build a statically-linked executable.rm-rf./*\ncmake..-DCMAKE_TOOLCHAIN_FILE=/toolchains/static.cmake\nmake\nmakerun\nrunhello# Clean, and build a dynamically-linked executable.rm-rf./*\ncmake..-DCMAKE_TOOLCHAIN_FILE=/toolchains/shared.cmake\nmake# Just works, since `run` has the proper library search path.makerun\nrunhello# Can also use Makefiles normally. Here we prefer shared linking.# This environment only adds or removes the `-static` flag when# compiling: nothing else is modified.cd..source/toolchains/shared\nmake\nrunhelloworld# Can also use static linking.source/toolchains/static\nmakeclean\nmake\nrunhelloworld# We can also invoke `c++` and `cc` commands directly.# It's really that simple.c++helloworld.cc-fPIC\nruna.out\n\nc++helloworld.cc-static\nruna.outTravis CI ExampleA simple example of integrating cross images is as follows:language:cppdist:bionicservices:-dockeraddons:apt:update:truepackages:-python3-python3-pip# Use a matrix with both native toolchains and cross-toolchain images.matrix:include:-arch:amd64os:linux-arch:amd64os:linuxenv:-TARGET=\"mips64\"before_install:-|if [ \"$TARGET\" != \"\" ] ; thenpip install xcrossdocker pull ahuszagh/cross:\"$TARGET\"fiscript:-|mkdir build && cd buildbuild=if [ \"$TARGET\" != \"\" ] ; thenbuild=xcross --target=\"$TARGET\"fi$build cmake ..$build make -j 5$build run tests/testSandboxingBy default, xcross shares your root directory with the image, running with the same permissions as the current user. However, you can limit the shared directories with the--diroption, allowing you to limit the build system to only the project files. This is useful for compiling untrusted code, providing an extra layer of security relative to running it on the host computer.For these reasons, commands run via xcross are not given root access. If you need to install build dependencies, there a few options:Get a non-root package manager such asjunestorhomebrew.Install dependencies locally viaapt downloadandapt-rdepends, to install to a local prefix withdpkg -force-not-root --root=$HOME.Creating a new Docker image that uses an xcross toolchain as a base image, for exampleFROM ahuszagh/cross:.Package ManagersWhen using xcross with the--with-package-managersoption, xcross will run images that come pre-installed with vcpkg and Conan.If run in detached mode (via--detach), no limitations exist. Otherwise, a new Docker container is run for each command, losing any changes outside the shared volume, so the following caveats apply:conan installinstalls packages relative to the CWD. Changing the CWD may lead to missing dependencies.vcpkg installonly works with manifests, not with global installs.Seetest/zlibfor an example project for the following code samples:An example of using xcross with vcpkg is:exportCROSS_TARGET=alpha-unknown-linux-gnuexportCROSS_WITH_PACKAGE_MANAGERS=1exportCROSS_DETACH=1xcrossvcpkginstall\nxcrosscmake..\nxcrosscmake--build.\nxcross--stopAn example of using xcross with conan is:exportCROSS_TARGET=alpha-unknown-linux-gnuexportCROSS_WITH_PACKAGE_MANAGERS=1exportCROSS_DETACH=1xcrossconaninstall..\nxcrosscmake..\nxcrosscmake--build.\nxcross--stopConan Issue:Note that Conan with CMake must be used with conan_define_targets()andtarget_link_libraries( CONAN_PKG::)`. With global defines, Conan fails to link the desired libraries. With target defines, it fails to find the include directories. Therefore, both must be used in conjunction.Using xcrossMost of the magic happens via xcross, which allows you to transparently execute commands in a Docker container. Although xcross provides simple, easy-to-use defaults, it has more configuration options for extensible cross-platform builds. Most of these command-line arguments may be provided as environment variables.WARNINGBy default, the root directory is shared with the Docker container, for maximum compatibility. In order to mitigate any security vulnerabilities, we run any build commands as a non-root user, and escape input in an attempt to avoid any script injections. If you are worried about a malicious build system, you may further restrict this using the--diroption.ArgumentsFallthroughAll arguments that are not xcross-specific are passed into the container.Any trivial arguments can be passed through without issue.# Just worksxcrossmake-j5To avoid shell expansion, pass entire complex commands as a single, quoted string.Please note that due to shell expansion, some things may evaluate on the host, and therefore may not work as expected. For example:# This does not work in POSIX shells, since it evaluates `$CXX` in the local shell.xcross-ECXX=cpp$CXXmain.c-omainIn order to mitigate this, we only allow characters that could be expanded by the local shell to be passed as a single string to the container:# Although this is escaped, we can't tell if we want a literal `$CXX`# or want to expand it. xcross rejects this.xcross-ECXX=cpp'$CXX'main.c-omain# Instead, pass it as a single string. Works now.xcross-ECXX=cpp'$CXX main.c -o main'Any environment variables and paths should be passed in POSIX style.Although non-trivial paths that exist on Windows will be translated to POSIX style, ideally you should not rely on this.# Doesn't work, since we use a Windows-style path to an output file.xcrossc++main.c-otest\\basic# This does work, since it uses a POSIX-style path for the output.xcrossc++main.c-otest/basic# This won't work, since we use a Windows-style environment variable.# We don't know what this is used for, so we can't convert this.xcross-EVAR1=cpp\"^%VAR1^% main.c -o main\"# Works in Windows CMD, since $X doesn't expand.xcross-EVAR1=cpp\"$VAR1main.c -o main\"xcross Arguments--target,CROSS_TARGET: The target architecture to compile to.# These two are identical, and build for Alpha on Linux/glibcxcross--target=alpha-unknown-linux-gnu...CROSS_TARGET=alpha-unknown-linux-gnuxcross...--dir,CROSS_DIR: The directory to share to the container as a volume.# These two are identical, and share only from the# current working directory.xcross--dir=....CROSS_DIR=.xcross...-E,--env: Pass environment variables to the container.If no value is passed for the variable, it exports the variable from the current environment.# These are all identical.xcross-EVAR1-EVAR2=x-EVAR3=y\nxcross-EVAR1-EVAR2=x,VAR3=y\nxcross-EVAR1,VAR2=x,VAR3=y--cpu,CROSS_CPU: Set the CPU model to compile/run code for.If not provided, it defaults to a generic processor model for the architecture. If provided, it will set the register usage and instruction scheduling parameters in addition to the generic processor model.# Build for the PowerPC e500mc CPU.exportCROSS_TARGET=ppc-unknown-linux-gnu\nxcross--cpu=e500mcc++helloworld.cc-ohello\nxcross--cpu=e500mcrunhelloCROSS_CPU=e500mcxcrossrunhelloIn order to determine valid CPU model types for the cross-compiler, you may use either of the following commands:# Here, we probe GCC for valid CPU names for the cross-compiler.exportCROSS_TARGET=ppc-unknown-linux-gnu\nxcrosscc-cpu-list# 401 403 405 405fp ... e500mc ... rs64 titan# Here, we probe Qemu for the valid CPU names for the emulation.xcrossrun-cpu-list# 401 401a1 401b2 401c2 ... e500mc ... x2vp50 x2vp7These are convenience functions aroundgcc -mcpu=unknownandqemu-ppc -cpu help, listing only the sorted CPU types. Note that the CPU types might not be identical for both, so it's up to the caller to properly match the CPU types.--server,CROSS_SERVER: The server to fetch container images from.This defaults todocker.ioif not provided, however, it may be explicit set to an empty string. If the server is not empty, the server is prepended to the image name.# These are all identical.xcross--server=docker.io...CROSS_SERVER=docker.ioxcross...--username,CROSS_USERNAME: The Docker Hub username for the Docker image.This defaults toahuszaghif not provided, however, it may be explicit set to an empty string. If the username is not empty, the image has the format$username/$repository:$target, otherwise, it has the format$repository:$target.# These are all identical.xcross--username=ahuszagh...CROSS_USERNAME=ahuszaghxcross...--repository,CROSS_REPOSITORY: The name of the repository for the image.This defaults tocrossif not provided or is empty.# These are all identical.xcross--repository=cross...CROSS_REPOSITORY=crossxcross...--image-version,CROSS_VERSION: The version of the image to use.If not provided, this will always use the latest version.# These are all identical.xcross--image-version=0.1...CROSS_VERSION=crossxcross...--with-package-managers,CROSS_WITH_PACKAGE_MANAGERS: Use images pre-installed with package managers.By default, xcross uses minimal images, with a basic set of build tools and utilities. If--with-package-managersis provided, then xcross will instead use images with Conan and vcpkg pre-installed, at the cost of larger image sizes.# These are all identical.xcross--with-package-managers...CROSS_WITH_PACKAGE_MANAGERS=1xcross...--engine,CROSS_ENGINE: The command for the container engine executable.If not provided or empty, this searches fordockerthenpodman.# These are all identical.xcross--engine=docker...CROSS_ENGINE=dockerxcross...--non-interactive,CROSS_NONINTERACTIVE: Disable interactive shells.This defaults to using interactive shells if--non-interactiveis not provided and ifCROSS_NONINTERACTIVEdoes not exist, or is set to an empty string.# These are all identical.xcross--non-interactive...CROSS_NONINTERACTIVE=1xcross...--detach,CROSS_DETACH: Start an image in detached mode and run command in image.This allows multiple commands to be run without losing any non-local changes after command. After running all commands, you can stop the image via--stop.# These are all identical.xcross--detach...CROSS_DETACH=1xcross...--stop: Stop an image started in detached mode.xcross--stop--target=alpha-unknown-linux-gnu--update-image,CROSS_UPDATE_IMAGE: Update the container image before running.This defaults to using the existing container version if not--update-imageis not provided and ifCROSS_UPDATE_IMAGEdoes not exist, or is set to an empty string.# These are all identical.xcross--update-image...CROSS_UPDATE_IMAGE=1xcross...--remove-image,CROSS_REMOVE_IMAGE: Remove the container image from local storage after running the command.# These are all identical.xcross--remove-image...CROSS_REMOVE_IMAGE=1xcross...--quiet,CROSS_QUIET: Silence any warnings when running the image.# These are all identical.xcross--quiet...CROSS_QUIET=1xcross...--verbose,CROSS_VERBOSE: Print verbose debugging output when running the image.# These are all identical.xcross--verbose...CROSS_VERBOSE=1xcross...Other UtilitiesEach image also contains a few custom utilities to probe image configurations:cc-cpu-list: List the valid CPU values to pass to--cpufor the C/C++ compiler.run-cpu-list: List the valid CPU values to pass to--cpufor Qemu.target-specs: Print basic specifications about the target architecture.target-specs-full: Print extensive specifications about the target architecture.$exportCROSS_TARGET=ppc-unknown-linux-gnu\n$xcrosstarget-specs{\"arch\":\"ppc\",\"os\":\"linux\",\"eh-frame-header\":true,\"linker-is-gnu\":true,\"target-endian\":\"big\",\"pic\":null,\"pie\":null,\"char-is-signed\":false,\"data-model\":\"ilp32\"}Building/Running DockerfilesTo build all Docker images, runpython3 setup.py build_imagesn--with-package-managers=1. Note that can it take up to a week to build all images. To build and run a single docker image, use:image=ppcle-unknown-linux-gnu\npython3setup.pyconfigure\npython3setup.pybuild_image--target\"$image\"# Runs the image without the xcross abstraction.dockerrun-it\"ahuszagh/cross:$image\"/bin/bash# Runs the image using xcross, for a simpler interface.xcrossbash--target\"$image\"ImagesFor a list of pre-built images, seeahuszagh/crossandahuszagh/pkgcross. To remove local, installed images from the pre-built, cross toolchains, run:# On a POSIX shell.images=$(dockerimages|grep-E'ahuszagh/(pkg)?cross')images=$(echo\"$images\"|tr-s' '|cut-d' '-f1,2|tr' ':)dockerrmi$imagesImage TypesThere are two types of images:Images with an OS layer, such asppcle-unknown-linux-gnu.Bare metal images, such asppcle-unknown-elf.The bare metal images use the newlib C-runtime, and are useful for compiling for resource-constrained embedded systems. Please note that not all bare-metal images provide complete startup routines (crt0), and therefore might need to be linked against standalone flags (-nostartfiles,-nostdlib,-nodefaultlibs, or-ffreestanding) with a custom startup.Other images use a C-runtime for POSIX-like build environment (such as Linux, FreeBSD, or MinGW for Windows), and include:musl (*-musl)glibc (*-gnu)uClibc-ng (*-uclibc)android (*-android, only available on some architectures)mingw (*-w64-mingw32, only available on x86)If you would like to test if the code compiles (and optionally, runs) for a target architecture, you should generally use alinux-gnuimage.TriplesAll images are named asahuszagh/cross:$tripleorahuszagh/pkgcross:$triple, where$tripleis the target triple. The target triple consists of:arch, the CPU architecture (mandatory).vendor, the CPU vendor.os, the OS the image is built on.system, the system type, which can comprise both the C-runtime and ABI.For example, the following image names decompose to the following triples:avr, or(avr, unknown, -, -)i386-w64-mingw32, or(i386, unknown, w64, mingw32)mips-unknown-o32,(mips, unknown, -, o32)mips-unknown-linux-gnu,(mips, unknown, linux, gnu)If an$arch-unknown-linux-gnuis available, then$archis an alias for$arch-unknown-linux-gnu.OS/Architecture SupportIn general, the focus of these images is to provide support for a wide variety of architectures, not operating systems. We will gladly accept Dockerfiles/scripts to support more operating systems, like FreeBSD. We do not support Darwin/iOS for licensing reasons, since reproduction of the macOS SDK is expressly forbidden. If you would like to build a Darwin cross-compiler, seeosxcross. We also do not support certain cross-compilers for popular architectures, like Hexagon, due to proprietary linkers (which would be needed for LLVM support).VersioningImage names have an optional, trailing version, which will always use a compatible host OS, GCC, and C-runtime version. Images without a version will always use the latest available version.No Version: Alias for the latest version listed.0.1: GCC 10.x, glibc 2.31+, musl 1.2.2, uCLibc-NG 1.0.31, Android r22b, and Ubuntu 20.04.Pre-1.0, minor versions signify backwards-incompatible changes to toolchains. Patch increments signify bug fixes, and build increments signify the addition of new toolchains.DependenciesIn order to usexcrossor build toolchains, you must have:python (3.6+)docker or podmanEverything else runs in the container.Toolchain FilesThese cross-compilation configurations are automatically injected if not provided. Manually overriding these defaults allows finer control over the build process.CMake Toolchain Files/toolchains/toolchain.cmake, which contains the necessary configurations to cross-compile./toolchains/shared.cmake, for building dynamically-linked binaries./toolchains/static.cmake, for building statically-linked binaries.To include an additional toolchain in addition to the default, passCROSS_CHAINLOAD_TOOLCHAIN_FILEduring configuration.Bash Environment Files/env/base, base environment variables for cross-compiling./env/shared, for building dynamically-linked binaries./env/static, for building statically-linked binaries.Meson Cross Files/toolchains/cross.meson, which contains the necessary configurations to cross-compile.Conan Settings~/.conan/settings.yml, default base settings for Conan.~/.conan/profiles/default, default Conan profile.Developing New ToolchainsTo add your own toolchain, the general workflow (for crosstool-NG or buildroot) is as follows:List toolchain samples.Configure your toolchain.Move the config file toct-ngorbuildroot.Patch the config file.Add the image toconfig/images.json.After the toolchain is created, this shows a sample image configuration to auto-generate the relevant Dockerfile, CMake toolchains, and toolchain symlinks:config/images.json[\n // ...\n {\n // COMMON CONFIGURATIONS\n\n // Image type (mandatory). Valid values are:\n // 1. android\n // 2. crosstool\n // 3. debian\n // 4. musl-cross\n // 5. riscv\n // 6. other\n //\n // The following values are for crosstool images,\n // which are by far the most prevalent.\n \"type\": \"crosstool\",\n // The name of the target, resembling an LLVM triple (mandatory).\n \"target\": \"alphaev4-unknown-linux-gnu\",\n // Actual LLVM triple name, which will be the compiler prefix.\n // For example, gcc will be `alphaev4-unknown-linux-gnu-gcc`.\n // Optional, and defaults to `target`.\n \"triple\": \"alphaev4-unknown-linux-gnu\",\n // The crosstool-NG target to use. This is useful\n // when the same configuration for a multilib compiler\n // can be reused. Optional, defaults to `target`.\n \"config\": \"alphaev4-unknown-linux-gnu\",\n // Enable qemu userspace emulation (optional). Default false.\n \"qemu\": true,\n // Flags to provide to the C compiler (optional).\n // This is useful when targeting a specific ABI,\n // or for example, to skip the default start code\n // to provide your own crt0.\n \"flags\": \"-nostartfiles\",\n // Optional flags to provide to the C compiler (optional).\n // These are flags that will not clobber existing settings,\n // for example, if `march=armv6` is provided as an optional\n // flag, then passing `-march=armv6z` will override that setting.\n \"optional_flags\": \"\",\n // Name of the processor for Qemu user-space emulation\n // and for setting the toolchain alias.\n \"processor\": \"alpha\"\n\n // OTHER CONFIGURATIONS\n\n // Numerous other configurations are also supported, such as:\n // * `cpulist` - A hard-coded list of valid CPU values.\n // This will override any values from `run-cpu-list` and `cc-cpu-list`.\n // For example, on HPPA, `\"cpulist\": \"1.0\"`.\n //\n // * `system` - Override the system component of a triple.\n // For example, `\"system\": \"gnuabi64\"`.\n //\n // * `os` - Override the OS component of a triple.\n // For example, `\"os\": \"linux\"`.\n //\n // * `vendor` - Override the vendor component of a triple.\n // For example, `\"vendor\": \"unknown\"`.\n //\n // * `arch` - Override the arch component of a triple.\n // In almost all cases, it's preferable to use `processor`,\n // which exists for this purpose.\n //\n // * `extensions` - Specify hardware extensions for the architecture.\n // Not available for all targets.\n // For example, `\"extensions\": \"imadc\"`.\n //\n // * `abi` - Specify ABI details for the architecture.\n // Not available for all targets.\n // For example, `\"abi\": \"lp64d\"`.\n //\n // * `library_path` - Specify the `LD_LIBRARY_PATH` variable for Qemu.\n // When the C-library differs but the host and target architecture\n // are the same, it can be necessary to set this value. You may\n // use the `$LIBPATH` variable, which specifies the sysroot for\n // Qemu's library search path.\n // For example, `\"library_path\": \"$LIBPATH/lib64\"`.\n //\n // * `preload` - Specify the `LD_PRELOAD` variable for Qemu.\n // For example, `\"preload\": \"$LIBPATH/lib64/libstdc++.so.6\"`.\n },\n // ...\n]For an example bare-metal crosstool-NG config file, seect-ng/ppcle-unknown-elf.config. For a Linux example, seect-ng/ppcle-unknown-linux-gnu.config. Be sure to add your new toolchain toconfig/images.json, and run the test suite with the new toolchain image.Platform SupportFor a complete list of targets, seehere. For a complete list of images, seeahuszagh/crossandahuszagh/pkgcross.Currently, we only create images that are supported by:crosstool-NG with official sourcesDebian packagesAndroid NDK'smusl-cross-make.buildrootRISCV GNU utils.We therefore support:ARM32 + Thumb (Linux, Android, Bare-Metal)ARM32-BE + Thumb (Linux, Android, Bare-Metal)ARM64 (Linux, Android, Bare-Metal)ARM64-BE (Linux, Android, Bare-Metal)alpha (Linux)ARC (Linux, Bare-Metal)ARC-BE (Linux, Bare-Metal)AVR (Bare-Metal)CSKY (Linux)HPPA (Linux)i386-i686 (Bare-Metal)i686 (Linux, MinGW, Android)m68k (Linux)MicroBlaze (Linux)MicroBlaze-LE (Linux)MIPS (Linux, Bare-Metal)MIPS-LE (Linux, Bare-Metal)MIPS64 (Linux, Bare-Metal)MIPS64-LE (Linux, Bare-Metal)Moxie (Bare-Metal: Moxiebox and ELF)Moxie-BE (Bare-Metal: ELF-only)NIOS2 (Linux, Bare-Metal)PowerPC (Linux, Bare-Metal)PowerPC-LE (Linux, Bare-Metal)PowerPC64 (Linux, Bare-Metal)PowerPC64-LE (Linux, Bare-Metal)OpenRISC (Linux)RISCV32 (Linux, Bare-Metal)RISCV64 (Linux, Bare-Metal)s390 (Linux)s390x (Linux)SH1-4 (Linux, Bare-Metal)Sparc (LEON3 and v8, Linux)Sparc64 (Linux)x86_64 (Linux, MinGW, Android, Bare-Metal)xtensa-BE (Linux)wasmPlatform-specific details:Xtensa does not support newlib, glibc, or musl.LicenseThe code contained within the repository, except when another license exists for a directory, is unlicensed. This is free and unencumbered software released into the public domain.However, this only pertains to the actual code contained in the repository: this project derives off of numerous other projects which use different licenses, and the images of the resulting toolchains contain software, such as Linux, GCC, glibc, and more that are under different licenses.For example, projects used by xcross and their licenses include:crosstool-NG: GNU GPLv2musl-cross-make: MITbuildroot: GNU GPLv2Android NDK: BSD 3-Clausenewlib: MIT and BSD-like licensesGCC: GNU GPLv3glibc: GNU LGPLv2.1 or latermusl: MITmusl: MITuClibc-ng: GNU LGPLv2.1emscripten: MIT or University of Illinois/NCSALLVM: Apache 2.0binutils: GNU GPLv2Linux: GNU GPLv2MinGW: BSD 3-Clause and GNU GPLv2Ubuntu: A variety of FOSS licensesLikewise, the diffs used to patch the toolchains are subject to the licensed of the original software. Seediff/README.mdfor detailed license information.The test suites for bare-metal toolchains also derive from other projects, including:newlib-examples: GNU GPLv3ppc_hw: BSD 3-Clausex86-bare-metal-examples: GNU GPLv3These licenses are only relevant if you distribute a toolchain or you redistribute the software used to build these images: for merely compiling and linking code as part of a standard toolchain, the usual linking exceptions apply.ContributingUnless you explicitly state otherwise, any contribution intentionally submitted for inclusion in xcross by you, will be unlicensed (free and unencumbered software released into the public domain).Please note that due to licensing issues, you may not submit code that uses Github Copilot, even though Github deceptively claims you retain ownership of generated code."} +{"package": "xcrun", "pacakge-description": "xcrunThis is a Python wrapper around thexcrunutility that Apple provides for interacting with the various Xcode developer tools.simctlsimctlis the tool for interacting with the iOS simulator and is the main focus of this module. The syntax is designed to remain as close to that which would be used on the command line as possible. For example, to list all runtimes on the command line you would do:xcrun simctl list runtimesWith this module you can print the result of:xcrun.simctl.listall.runtimes()Most functions are on the item that they affect. So instead of running something on a device like:xcrun simctl do_thing arg1 arg2 ...You can do this:iPhone7 = xcrun.simctl.device.from_name(\"iPhone 7\")\niPhone7.do_thing(arg1, arg2, ...)TestingTo run the tests, all you need to do is runpython3 -m tox(can be installed by runningpython3 -m pip install tox)."} +{"package": "xcrypt", "pacakge-description": "XCryptAboutThis was initially a project to prove that I could make a strong encryption but I decided to publish it so that the internet people could improve it and use it. While it is still kinda basic it will get stronger and more efficient hopefully.To UseTo install XCrypt use the following commandpip install xcryptorpython -m pip install xcrypt. After you install it be sure to import it with:importxcryptNow you can start to actually use XCrypt. XCrypt is a key file based encryption, so the first step in using it is to obtain a key. You can have someone else give you a key or you can generate one yourself. If you want to generate a key you can use thexcrypt.make_key()function. The return value of this function is equal to the key name (as a string). You will need this to encrypt and decrypt information.importxcryptprint(\"Generating key\")keyName=xcrypt.make_key()print(\"Key Name is \"+keyName)Now that you have a key file generated, the next step is to encrypt some information, the encrypted information must be a string. If it isn't a string it should be automatically converted. If you want to encrypt information the function you would use isxcrypt.encrypt(keyName, Data). This function takes the key name (required for correct encryption) and the data/message to encrypt.importxcryptkeyName=xcrypt.make_key()encryptedData=xcrypt.encrypt(keyName,\"Hello World!\")print(encryptedData)# This should output to a bunch of random characters.After you have some information encrypted you probably want to decrypt it. The easiest and only way to do that is through thexcrypt.decrypt(keyName, Data)function. It takes two variables, keyName (for the key file name, same as the encryption function) and data (the encrypted text seen in variableencryptedDatapreviously).importxcrpytkeyName=\"\"encryptedData=\"\"decryptedData=xcrypt.decrypt(keyName,encryptedData)print(decryptedData)# If everything worked then this should be \"Hello World!\".Alright, now that we know exactly how to do everything lets put it together into one new file and test it. Each line will be commented explaining its purpose.importxcrypt# Import xcrypt so we can use the functions.keyName=xcrypt.make_key()# Generate a key file and save the name to a variable.initialData=input(\"Message To Encrypt/Decrypt: \")# Allow a user imputed message.encryptedData=xcrypt.encrypt(keyName,initialData)# Save encrypted message to variable.decryptedData=xcrypt.decrypt(keyName,encryptedData)# Save decrypted message to variable.print(\"Message: \"+initialData)# Display the initial message submitted.print(\"Encrypted: \"+encryptedData)# Display the encrypted form of the message.print(\"Decrypted: \"+decryptedData)# Display the decrypted form of the message.Your finished! You have made a program that uses xcrypt to encrypt and decrypt messages.A more rough example can be seen in theexample.pyfile.If There Are IssuesThe only library it requires is random and that comes with python.Make sure your using the right key file when encrypting and decrypting.Make sure that your python version is compatable with XCrypt.If you would like to report and issue please do so by one of the following methods:Making a GitHub issue.Joining my Discord server.Emailing me.Copyright (c) 2021 kgsensei."} +{"package": "xcrypto", "pacakge-description": "No description available on PyPI."} +{"package": "xcs", "pacakge-description": "Accuracy-based Learning Classifier Systems for Python 3LinksProject HomeTutorialSourceDistributionThe package is available for download under the permissiveRevised BSD\nLicense.DescriptionXCS is a Python 3 implementation of the XCS algorithm as described in\nthe 2001 paper,An Algorithmic Description of\nXCS, byMartin\nButzandStewart Wilson. XCS is a type\nofLearning Classifier System\n(LCS), amachine learningalgorithm that utilizes agenetic\nalgorithmacting on\na rule-based system, to solve areinforcement\nlearningproblem.In its canonical form, XCS accepts a fixed-width string of bits as its\ninput, and attempts to select the best action from a predetermined list\nof choices using an evolving set of rules that match inputs and offer\nappropriate suggestions. It then receives a reward signal indicating the\nquality of its decision, which it uses to adjust the rule set that was\nused to make the decision. This process is subsequently repeated,\nallowing the algorithm to evaluate the changes it has already made and\nfurther refine the rule set.A key feature of XCS is that, unlike many other machine learning\nalgorithms, it not only learns the optimal input/output mapping, but\nalso produces a minimal set of rules for describing that mapping. This\nis a big advantage over other learning algorithms such asneural\nnetworkswhose models are largely opaque to human analysis, making XCS an\nimportant tool in any data scientist\u2019s tool belt.The XCS library provides not only an implementation of the standard XCS\nalgorithm, but a set of interfaces which together constitute a framework\nfor implementing and experimenting with other LCS variants. Future plans\nfor the XCS library include continued expansion of the tool set with\nadditional algorithms, and refinement of the interface to support\nreinforcement learning algorithms in general.Related ProjectsPier Luca Lanzi\u2019sXCS Library\n(xcslib)(C++)Ryan J. Urbanowicz\u2019sLCS Implementations for SNP\nEnvironmentandExSTraCS(Python)Martin Butz\u2019sJavaXCSF(Java)"} +{"package": "xcsc-tushare", "pacakge-description": "http://101.226.250.236:7173/document/1"} +{"package": "xcsf", "pacakge-description": "XCSF learning classifier systemAn implementation of the XCSFlearning classifier systemthat can be built as a stand-alone binary or as a Python library. XCSF is an accuracy-basedonlineevolutionarymachine learningsystem with locally approximating functions that compute classifier payoff prediction directly from the input state. It can be seen as a generalisation of XCS where the prediction is a scalar value. XCSF attempts to find solutions that are accurate and maximally general over the global input space, similar to most machine learning techniques. However, it maintains the additional power to adaptively subdivide the input space into simpler local approximations.See the projectwikifor details on features, how to build, run, and use as a Python library."} +{"package": "x-csfd-scraper", "pacakge-description": "No description available on PyPI."} +{"package": "xcsoar", "pacakge-description": "XCSoar flight analysis toolsContentsXCSoar python packageThe XCSoar python package contains a wrapper for compiling the xcsoar python\nmodule.Import thexcsoarpackage to take advantage of the module. See the\nsource code and the test_xcsoar.py script in thexcsoar.submodule/python/test/directory.InstallationYou can install the XCSoar tools like any other python script by callingpython setup.py install. It will automatically compile the tools and\ninstall them to an appropriate location.You will most likely need to install a few of XCSoar\u2019s build dependencies.\nOn a standard Ubuntu machine callingapt-getinstall makelibcurl4-openssl-devshould get you started. Please read the XCSoar\ndocumentation if there are more libraries missing.LicenseXCSoar Glide Computer - http://www.xcsoar.org/\nCopyright (C) 2000-2013 The XCSoar Project\nA detailed list of copyright holders can be found in the file \"AUTHORS\".\n\nThis program is free software; you can redistribute it and/or\nmodify it under the terms of the GNU General Public License\nas published by the Free Software Foundation; either version 2\nof the License, or (at your option) any later version.\n\nThis program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\nGNU General Public License for more details.\n\nYou should have received a copy of the GNU General Public License\nalong with this program; if not, write to the Free Software\nFoundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA."} +{"package": "xcsr", "pacakge-description": "xcsrA simple comic scraper.What's new?Scraping fromgetcomics.infois now possible."} +{"package": "xcs-rc", "pacakge-description": "XCS-RCAccuracy-based Learning Classifier SystemswithRule Combiningmechanism, shortlyXCS-RCfor Python3, loosely based on Martin Butz's XCS Java code (2001). Read my PhD thesisherefor the complete algorithmic description.Rule Combiningis novel function that employs inductive reasoning, replacingall Darwinian genetic operation like mutation and crossover. It can handlebinariesandreal, reaching bettercorrectness rateandpopulation sizequicker than several XCS instances. My earlier papers comparing them can be obtained athereandhere.Relevant linksPyPIGithub repoExamples:Classic problems: multiplexer, Markov envChurn datasetFlappy BirdOpenAI GymInstallationpip install xcs-rcInitializationimport xcs_rc\nagent = xcs_rc.Agent()Classic Reinforcement Learning cycle# input: binary string, e.g., \"100110\" or decimal array\nstate = str(randint(0, 1))\n\n# pick methods: 0 = explore, 1 = exploit, 2 = explore_it\naction = agent.next_action(state, pick_method=1)\n\n# determine reward and apply it, e.g.,\nreward = agent.maxreward if action == int(state[0]) else 0.0\nagent.apply_reward(reward)Partially Observable Markov Decision Process (POMDP) environment# create env and agent\nenv = xcs_rc.MarkovEnv('maze4') # maze4 is built-in\nenv.add_agents(num=1, tcomb=100, xmax=50)\nagent = env.agents[0]\n\nfor episode in range(8000):\n steps = env.one_episode(pick_method=2) # returns the number of taken stepsData classificationagent.train(X_train, y_train)\ncm = agent.test(X_test, y_test) # returns the confusion matrix\npreds, probs = agent.predict(X) # returns lists of predictions and probabilitiesPrint population, save it to CSV file, or use append modeagent.pop.print(title=\"Population\")\nagent.save('xcs_population.csv', title=\"Final XCS Population\")\nagent.save('xcs_pop_every_100_cycles.csv', title=\"Cycle: ###\", save_mode='a')Finally, inserting rules to population# automatically load the last set (important for append mode)\nagent.load(\"xcs_population.csv\", empty_first=True)\nagent.pop.add(my_list_of_rules) # from a list of classifiersMain ParametersXCS-RC Parameterstcomb:combining period, number of learning cycles before the next rule combiningpredtol:prediction tolerance, maximum difference between two classifiers to be combinedprederrtol:prediction error tolerance, threshold for deletion of inappropriately combined rulesHow to Setagent.tcomb = 50 # perform rule combining every 50 cycles\nagent.predtol = 20.0 # combines rules whose prediction value differences <= 20.0\nagent.prederrtol = 10.0 # remove if error > 10.0, after previously below itParameters from original XCSall related to mutation and crossover is removedthe others are kept and accessible (e.g.,agent.alpha = 0.15)ResultsClassical Problems:multiplexerandMarkov environment:Flappy Bird from PyGame Learning Environment:Youtube: CartPole-v0 Benchmark from OpenAI Gym:"} +{"package": "xcsv", "pacakge-description": "xcsvxcsv is a package for reading and writing extended CSV files.Extended CSV formatExtended header section of parseable atttributes, introduced by '#'.Header row of variable and units for each column.Data rows.ExampleExtended header sectionNo leading/trailing whitespace.Each line introduced by a comment ('#') character.Each line contains a single header item.Key/value separator ': '.Multi-line values naturally continued over to the next lines following the line introducing the key.Continuation lines that contain the delimiter character in the value must be escaped by a leading delimiter.Preferably use a common vocabulary for attribute name, such asCF conventions.Preferably include recommended attributes fromAttribute Convention for Data Discovery (ACDD).Preferably use units fromUnified Code for Units of Measureand/orUdunits.Units in parentheses.Certain special keys are used tofurther process the data, for example themissing_valuekey.# id: 1\n# title: The title\n# summary: This dataset...\n# The second summary paragraph.\n# : The third summary paragraph. Escaped because it contains the delimiter in a URL https://dummy.domain\n# authors: A B, C D\n# latitude: -73.86 (degree_north)\n# longitude: -65.46 (degree_east)\n# elevation: 1897 (m a.s.l.)\n# [a]: 2012 not a complete yearHeader rowNo leading/trailing whitespace.Preferably use a common vocabulary for variable name, such asCF conventions.Units in parentheses.Optional notes in square brackets, that reference an item in the extended header section.time (year) [a],depth (m)Data rowNo leading/trailing whitespace.2012,0.575Automated post-processing of the dataDepending on the presence of special keys in the extended header section, these will be used to automatically post-process the data. To turn off this automatic behaviour, either remove or rename these keys, or setparse_metadata=Falsewhen reading in the data.missing_value: This is used to define those values in the data that are to be considered as missing values. This is typically a value that is outside the domain of the data such as-999.99, or can be a symbolic value such asNA. All such values appearing in the data will be masked, appearing as anNAvalue to pandas (i.e.pd.isna(value)returnsTrue). Note that pandas itself will automatically do this for certain values regardless of this key, such as for the stringsNaNorNA, or the constantNone.InstallThe package can be installed from PyPI:$pipinstallxcsvUsing the packageThe package has a generalXCSVclass, that has ametadataattribute that holds the parsed contents of the extended file header section and the parsed column headers from the data table, and adataattribute that holds the data table (including the column headers as-is).Themetadataattribute is adict, with the following general structure:{'header':{},'column_headers':{}}and thedataattribute is apandas.DataFrame, and so has all the features of thepandaspackage.The package also has aReaderclass for reading an extended CSV file into anXCSVobject, and similarly aWriterclass for writing anXCSVobject to a file in the extended CSV format. In addition there is aFileclass that provides a convenient context manager for reading and writing these files.ExamplesSimple read and printRead in a file and print the contents tostdout. This shows how the contents of the extended CSV file are stored in theXCSVobject. Note how multi-line values, such assummaryhere, are stored in a list. Given the following script called, say,simple_read.py:importargparseimportxcsvparser=argparse.ArgumentParser()parser.add_argument('filename',help='filename.csv')args=parser.parse_args()withxcsv.File(args.filename)asf:content=f.read()print(content.metadata)print(content.data)Running it would produce:$python3simple_read.pyexample.csv{'header':{'id':'1','title':'The title','summary':['This dataset...','The second summary paragraph.','The third summary paragraph. Escaped because it contains the delimiter in a URL https://dummy.domain'],'authors':'A B, C D','latitude':{'value':'-73.86','units':'degree_north'},'longitude':{'value':'-65.46','units':'degree_east'},'elevation':{'value':'1897','units':'m a.s.l.'},'[a]':'2012 not a complete year'},'column_headers':{'time (year) [a]':{'name':'time','units':'year','notes':'a'},'depth (m)':{'name':'depth','units':'m','notes':None}}}time(year)[a]depth(m)020120.575120111.125220102.225Simple read and print with missing valuesIf the above example header section included the following:# missing_value: -999.99and the data section looked like:time (year) [a],depth (m)\n2012,0.575\n2011,1.125\n2010,2.225\n2009,-999\n2008,999\n2007,-999.99\n2006,999.99\n2005,NA\n2004,NaNRunning it would produce:$python3simple_read.pymissing_example.csv{'header':{'id':'1','title':'The title','summary':['This dataset...','The second summary paragraph.','The third summary paragraph. Escaped because it contains the delimiter in a URL https://dummy.domain'],'authors':'A B, C D','latitude':{'value':'-73.86','units':'degree_north'},'longitude':{'value':'-65.46','units':'degree_east'},'elevation':{'value':'1897','units':'m a.s.l.'},'missing_value':'-999.99','[a]':'2012 not a complete year'},'column_headers':{'time (year) [a]':{'name':'time','units':'year','notes':'a'},'depth (m)':{'name':'depth','units':'m','notes':None}}}time(year)[a]depth(m)020120.575120111.125220102.22532009-999.00042008999.00052007NaN62006999.99072005NaN82004NaNNote that the-999.99value has been automatically masked as a missing value (shown asNaNin the printed pandasDataFrame), as well as theNAandNaNstrings in the original data, which pandas automatically masks itself, irrespective of themissing_valueheader item.Simple read and plotRead a file and plot the data:importargparseimportmatplotlib.pyplotaspltimportxcsvparser=argparse.ArgumentParser()parser.add_argument('filename',help='filename.csv')args=parser.parse_args()withxcsv.File(args.filename)asf:content=f.read()content.data.plot(x='depth (m)',y='time (year) [a]')plt.show()Simple read and writeRead a file in, manipulate the data in some way, and write this modifiedXCSVobject out to a new file:importargparseimportxcsvparser=argparse.ArgumentParser()parser.add_argument('in_filename',help='in_filename.csv')parser.add_argument('out_filename',help='out_filename.csv')args=parser.parse_args()withxcsv.File(args.in_filename)asf:content=f.read()# Manipulate the data...withxcsv.File(args.out_filename,mode='w')asf:f.write(xcsv=content)"} +{"package": "xcsv-plot", "pacakge-description": "xcsv-plotxcsv-plot is a subpackage ofxcsv. It's main purpose is to provide a simple CLI for plotting extended CSV (XCSV) files.InstallThe package can be installed from PyPI:$pipinstallxcsv-plotUsing the packageXCSV data can be plotted directly, as the data table is apandastable:content.data.plot(x='time (year) [a]',y='depth (m)')and of course for more control over the plot, the data can be plotted usingmatplotlib, say.But an XCSV file with anACDD-compliantextended header section, and well-annotated column-headers, already provides much of the text needed to make an informative plot, so we can just plot the XCSV file directly from the command line. This is the purpose of thexcsv-plotsubpackage. For example:$python3-mxcsv.plot-x0-y1example.csvNote here that we're callingxcsv-plotas amodule main. As a convenience, this invocation is wrapped as a console script when installing the package, hence the following invocation is equivalent:$xcsv_plot-x0-y1example.csvIn addition to using the CLI, the package can be used as a Python library. The main class isPlotwhich provides methods to plot a given list of datasets (XCSV objects):importxcsvimportxcsv.plotasxpfilenames=['example1.csv','example2.csv','example3.csv']datasets=[]forfilenameinfilenames:withxcsv.File(filename)asf:datasets.append(f.read())plotter=xp.Plot()plotter.plot_datasets(datasets,xidx=0,yidx=1)Command line usageCalling the script with the--helpoption will show the following usage:$python3-mxcsv.plot--help\nusage:xcsv_plot[-h][-xXIDX|-XXCOL][-yYIDX|-YYCOL][--x-labelXLABEL][--y-labelYLABEL][--invert-x-axis][--invert-y-axis][--titleTITLE][--captionCAPTION][--label-keyLABEL_KEY][-sFIGSIZEFIGSIZE][-bBG_IMG_PATH][-oOUT_FILE][-PPLOT_OPTS][-S][-V]in_file[in_file...]plotthegivenXCSVfiles\n\npositionalarguments:in_fileinputXCSVfile(s)optionalarguments:-h,--helpshowthishelpmessageandexit-xXIDX,--x-idxXIDXcolumnindex(zero-based)containingvaluesforthex-axis-XXCOL,--x-columnXCOLcolumnlabelcontainingvaluesforthex-axis-yYIDX,--y-idxYIDXcolumnindex(zero-based)containingvaluesforthey-axis-YYCOL,--y-columnYCOLcolumnlabelcontainingvaluesforthey-axis--x-labelXLABELtexttobeusedfortheplotx-axislabel--y-labelYLABELtexttobeusedfortheploty-axislabel--invert-x-axisinvertthex-axis--invert-y-axisinvertthey-axis--titleTITLEtexttobeusedfortheplottitle--captionCAPTIONtexttobeusedfortheplotcaption--label-keyLABEL_KEYkeyoftheheaderitemintheextendedheadersectionwhosevaluewillbeusedfortheplotlegendlabel-sFIGSIZEFIGSIZE,--figsizeFIGSIZEFIGSIZEsizeofthefigure(widthheight)-bBG_IMG_PATH,--background-imageBG_IMG_PATHpathtoanimagetoshowinthebackgroundoftheplot-oOUT_FILE,--out-fileOUT_FILEoutputplotfile-PPLOT_OPTS,--plot-optionsPLOT_OPTSoptionsfortheplot,specifiedasasimpleJSONobject-S,--scatter-plotsetplotoptions(see-P)toproduceascatterplot-V,--versionshowprogram'sversionnumberandexitExamples\n\nGivenanXCSVfilewithanACDD-compliantextendedheadersection,andasinglecolumn(atcolumn0)ofdatavalues:# id: 1# title: The titledepth(m)0.5751.1252.225\n\nThenthefollowinginvocationwillplottheonlycolumnonthey-axis,withthex-axistheindicesofthedatapoints:\n\npython3-mxcsv.plotinput.csv\n\nIfthefilealsocontainsasuitablevariableforthex-axis:# id: 1# title: The titletime(year)[a],depth(m)2012,0.5752011,1.1252010,2.225thenthecolumnstobeusedforthex-andy-axescanbespecifiedthus:\n\npython3-mxcsv.plot-x0-y1input.csv"} +{"package": "xcsv-plot-map", "pacakge-description": "xcsv-plot-mapxcsv-plot-map is a subpackage ofxcsv. It's main purpose is to provide a simple CLI for plotting extended CSV (XCSV) files, and locating the data on a map, given an extended header section with geographical coordinates. These will typically detail where the data were acquired. It inherits from thexcsv-plotsubpackage of xcsv.InstallThe package can be installed from PyPI:$pipinstallxcsv-plot-mapNotes on installing Cartopyxcsv-plot-map has a dependency on Cartopy. In turn, Cartopy requires the Proj library. If you find that you can't install Cartopy because the version of the Proj library on your system is too old, then you can build a local version of the Proj library. This should be a fairly straightforward build. You may then find that the Cartopy package installs OK, but that you get the following segfault at runtime when trying to use xcsv-plot-map:free():invalidsize\nAborted(coredumped)This is a known issue. A suggested fix for this is to reinstall the Pythonshapelypackage. First remove it:$pipuninstallshapelyand then reinstall it with specificpipoptions:$pipinstall--no-binary:all:shapelyThis may take a while, but should resolve the segfault issue and everything should work.Using the packageAn XCSV file with anACDD-compliantextended header section, including geographical coordinates inlongitudeandlatitudeheader items, and well-annotated column-headers, already provides much of the text needed to make an informative plot and map, so we can just plot the XCSV file directly from the command line. This is the purpose of thexcsv-plot-mapsubpackage. For example:$python3-mxcsv.plot_map-x0-y1example.csvNote here that we're callingxcsv-plot-mapas amodule main. As a convenience, this invocation is wrapped as a console script when installing the package, hence the following invocation is equivalent:$xcsv_plot_map-x0-y1example.csvIn addition to using the CLI, the package can be used as a Python library. The main class isPlot. This is inherited from thexcsv-plot.Plotclass, with some overridden methods. The class provides methods to plot a given list of datasets (XCSV objects), and locate them on a map:importxcsvimportxcsv.plot_mapasxpmfilenames=['example1.csv','example2.csv','example3.csv']datasets=[]forfilenameinfilenames:withxcsv.File(filename)asf:datasets.append(f.read())plotter=xpm.Plot()plotter.plot_datasets(datasets,xidx=0,yidx=1)Command line usageCalling the script with the--helpoption will show the following usage:$python-mxcsv.plot_map--help\nusage:xcsv_plot_map[-h][-xXIDX|-XXCOL][-yYIDX|-YYCOL][--x-labelXLABEL][--y-labelYLABEL][--invert-x-axis][--invert-y-axis][--titleTITLE][--captionCAPTION][--label-keyLABEL_KEY][-sFIGSIZEFIGSIZE][-pPROJECTION][-m][-bBG_IMG_PATH][-oOUT_FILE][-PPLOT_OPTS][-S][-V]in_file[in_file...]plotthegivenXCSVfilesandlocatethedataonamap\n\npositionalarguments:in_fileinputXCSVfile(s)optionalarguments:-h,--helpshowthishelpmessageandexit-xXIDX,--x-idxXIDXcolumnindex(zero-based)containingvaluesforthex-axis-XXCOL,--x-columnXCOLcolumnlabelcontainingvaluesforthex-axis-yYIDX,--y-idxYIDXcolumnindex(zero-based)containingvaluesforthey-axis-YYCOL,--y-columnYCOLcolumnlabelcontainingvaluesforthey-axis--x-labelXLABELtexttobeusedfortheplotx-axislabel--y-labelYLABELtexttobeusedfortheploty-axislabel--invert-x-axisinvertthex-axis--invert-y-axisinvertthey-axis--titleTITLEtexttobeusedfortheplottitle--captionCAPTIONtexttobeusedfortheplotcaption--label-keyLABEL_KEYkeyoftheheaderitemintheextendedheadersectionwhosevaluewillbeusedfortheplotlegendlabel-sFIGSIZEFIGSIZE,--figsizeFIGSIZEFIGSIZEsizeofthefigure(widthheight)-pPROJECTION,--map-projectionPROJECTIONprojectiontousefordisplayingthesitecoordinatesonthemap(oneoftheCRSclassesprovidedbyCartopy)-m,--plot-on-mapinsteadofaplotalongsideasitemap,showjustamapandplotthecoordinatedatadirectlyonthemap-bBG_IMG_PATH,--background-imageBG_IMG_PATHpathtoanimagetoshowinthebackgroundoftheplot-oOUT_FILE,--out-fileOUT_FILEoutputplotfile-PPLOT_OPTS,--plot-optionsPLOT_OPTSoptionsfortheplot,specifiedasasimpleJSONobject-S,--scatter-plotsetplotoptions(see-P)toproduceascatterplot-V,--versionshowprogram'sversionnumberandexitExamples\n\nGivenanXCSVfilewithanACDD-compliantextendedheadersection,includinggeographicalcoordinatesinlongitudeandlatitude,andasinglecolumn(atcolumn0)ofdatavalues:# id: 1# title: The title# latitude: -73.86 (degree_north)# longitude: -65.46 (degree_east)depth(m)0.5751.1252.225\n\nThenthefollowinginvocationwillplottheonlycolumnonthey-axis,withthex-axistheindicesofthedatapoints,andwilllocatethecoordinatesonamap:\n\npython3-mxcsv.plot_mapinput.csv\n\nIfthefilealsocontainsasuitablevariableforthex-axis:# id: 1# title: The title# latitude: -73.86 (degree_north)# longitude: -65.46 (degree_east)time(year)[a],depth(m)2012,0.5752011,1.1252010,2.225thenthecolumnstobeusedforthex-andy-axescanbespecifiedthus:\n\npython3-mxcsv.plot_map-x0-y1input.csv"} +{"package": "xcsv-utils", "pacakge-description": "xcsv-utilsxcsv-utils is a subpackage ofxcsv. It's main purpose is to provide utilities for working with extended CSV (XCSV) files.InstallThe package can be installed from PyPI:$pipinstallxcsv-utilsUsing the packageXCSV data can be printed directly, as the data table is apandastable:>>>content.datatime(year)[a]depth(m)020120.575120111.125220102.225320092.825420083.508........3871625132.2403881624132.4263891623132.6803901622132.8803911621133.180[392rowsx2columns]But an XCSV object usually contains an extended header section as well as the data. Pandas doesn't handle this header, but the XCSV object does. In addition, the XCSV object parses the data table column headers and makes their content machine-readable.Thexcsv-utilssubpackage provides simple access and visual inspection of the attributes of an XCSV object - themetadata(headerandcolumn_headers) and thedata. The main class isPrint, which provides a formatted, themed view of an XCSV object, and can pretty-print an XCSV file directly from the command line. This is the purpose of thexcsv-utilssubpackage. For example:$python3-mxcsv.utilsexample.csvid:1title:Thetitle\nsummary:Thisdataset...\nThesecondsummaryparagraph.\nThethirdsummaryparagraph.EscapedbecauseitcontainsthedelimiterinaURLhttps://dummy.domain\nauthors:AB,CD\nlatitude:-73.86(degree_north)longitude:-65.46(degree_east)elevation:1897(ma.s.l.)[a]:2012notacompleteyear\n+----+--------------+-------------+||time|depth(m)|||(year)[a]|||----+--------------+-------------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+--------------+-------------+All the colour theming is handled by theblessedpackage, and the data table formatting is handled by thetabulatepackage.Note here that we're callingxcsv-utilsas amodule main. As a convenience, this invocation is wrapped as a console script (calledxcsv_print) when installing the package, hence the following invocation is equivalent:$xcsv_printexample.csvA key feature of the CLI, is that the attributes of the XCSV object can be inspected individually. When called with no options, the header is printed in a themed and formatted way, followed by the data table, which is also themed and formatted. This is more readable than simplycating the file. The modes of the CLI are:No options: Print the header, followed by the data table.-H: Print the header only.-C: Print the column headers only. These are printed with a numeric index, so that optionally a subset of columns can be specified when printing the data table.-D: Print the data table only. The rows have a leading row index column (as per usual withpandasdataframes), so that optionally a subset of rows can be specified when printing the data table.For example:$xcsv_printexample.csv-H\nid:1title:Thetitle\nsummary:Thisdataset...\nThesecondsummaryparagraph.\nThethirdsummaryparagraph.EscapedbecauseitcontainsthedelimiterinaURLhttps://dummy.domain\nauthors:AB,CD\nlatitude:-73.86(degree_north)longitude:-65.46(degree_east)elevation:1897(ma.s.l.)[a]:2012notacompleteyear$xcsv_printexample.csv-C0time(year)[a]1depth(m)$xcsv_printexample.csv-D\n+----+--------------+-------------+||time|depth(m)|||(year)[a]|||----+--------------+-------------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+--------------+-------------+These modes are mutually exclusive. Each of these options can be combined with the verbose (-v) option, to highlight how that attribute was parsed. For example, when verbosely printing the header, any numeric values with units, and any list items, will be highlighted:$xcsv_printexample.csv-Hv\nid:1title:Thetitle\nsummary:['This dataset...','The second summary paragraph.','The third summary paragraph. Escaped because it contains the delimiter in a URL https://dummy.domain']authors:AB,CD\nlatitude:value:-73.86,units:degree_north\nlongitude:value:-65.46,units:degree_east\nelevation:value:1897,units:ma.s.l.[a]:2012notacompleteyearSimilarly for the column headers:$xcsv_printexample.csv-Cv0name:time,units:year,notes:a1name:depth,units:m,notes:Noneand the data table:$xcsv_printexample.csv-Dv\n+----+---------------+---------------+||name:time|name:depth|||units:year|units:m|||notes:a|notes:None||----+---------------+---------------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+---------------+---------------+The data table also has an extra verbose (-vv) option whereby it will resolve any table notes to the notes text from the coresponding header item:$xcsv_printexample.csv-Dvv\n+----+-----------------------------------+---------------+||name:time|name:depth|||units:year|units:m|||notes:a->2012notacomplete|notes:None|||year|||----+-----------------------------------+---------------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+-----------------------------------+---------------+There are further useful options for printing the data table:-c: Specify a subset of columns to print. This can be useful when the data table contains a large number of columns.-r: Similarly, specify a subset of rows to print.--head: Convenience function. Print only the first 10 data rows.--tail: Convenience function. Print only the last 10 data rows.All column and row indices are zero-based, and can be ascertained from the-Cand-Doptions respectively. They can be specified as comma-separated lists and/or hyphen-separated (inclusive) ranges.Of course the OSheadandtail(andless) commands can be used to limit the output of the table, but doing so will lose the theming. Moreover though, if the output includes the header, thenheadwill apply to the header, and will likely not get as far as showing any of the data table.For example:$xcsv_print-D--headA68_icebergs_positions_and_dimensions_2020-21-A68A.csv\n+----+------------+--------------------+--------------------+---------------------------+---------------------------+---------------------------+---------------------------+-------------------------+--------------------------+-------------+-----------------------------------------------------------------+||Date|A68A_Central_Lat|A68A_Central_Lon|A68A_Long_axis_end_Lat1|A68A_Long_axis_end_Lon1|A68A_Long_axis_end_Lat2|A68A_Long_axis_end_Lon2|A68A_Long_axis_length|A68A_Short_axis_length|A68A_Area|Dimensions_source||||(degree_north)|(degree_east)|(degree_north)|(degree_east)|(degree_north)|(degree_east)|(km)|(km)|(km2)|||----+------------+--------------------+--------------------+---------------------------+---------------------------+---------------------------+---------------------------+-------------------------+--------------------------+-------------+-----------------------------------------------------------------||0|2020-09-01|-59.42|-49.47|-59.63|-50.51|-59.26|-47.98|nan|nan|nan|9999||1|2020-09-02|-59.42|-49.49|-59.8|-50.52|-59.11|-48.3|nan|nan|nan|9999||2|2020-09-03|-59.46|-49.7|-60.04|-50.18|-58.88|-48.9|149.375|49.875|4451.66|s1a-ew-grd-hh-20200903t223918-20200903t224018-034200-03f92b-001||3|2020-09-04|-59.43|-49.72|-60.11|-49.77|-58.78|-49.43|nan|nan|nan|9999||4|2020-09-05|-59.45|-49.72|-60.06|-49.49|-58.73|-49.72|nan|nan|nan|9999||5|2020-09-06|-59.44|-49.66|-59.98|-49.19|-58.69|-50.02|nan|nan|nan|9999||6|2020-09-07|-59.38|-49.69|-59.84|-49|-58.69|-50.27|nan|nan|nan|9999||7|2020-09-08|-59.31|-49.66|-59.73|-48.85|-58.7|-50.48|nan|nan|nan|9999||8|2020-09-09|-59.29|-49.68|-59.72|-48.85|-58.67|-50.47|nan|nan|nan|9999||9|2020-09-10|-59.26|-49.7|-59.7|-48.85|-58.64|-50.45|nan|nan|nan|9999|+----+------------+--------------------+--------------------+---------------------------+---------------------------+---------------------------+---------------------------+-------------------------+--------------------------+-------------+-----------------------------------------------------------------+\n$xcsv_print-CA68_icebergs_positions_and_dimensions_2020-21-A68A.csv0Date1A68A_Central_Lat(degree_north)2A68A_Central_Lon(degree_east)3A68A_Long_axis_end_Lat1(degree_north)4A68A_Long_axis_end_Lon1(degree_east)5A68A_Long_axis_end_Lat2(degree_north)6A68A_Long_axis_end_Lon2(degree_east)7A68A_Long_axis_length(km)8A68A_Short_axis_length(km)9A68A_Area(km2)10Dimensions_source\n$xcsv_print-D--head-c0-2A68_icebergs_positions_and_dimensions_2020-21-A68A.csv\n+----+------------+--------------------+--------------------+||Date|A68A_Central_Lat|A68A_Central_Lon||||(degree_north)|(degree_east)||----+------------+--------------------+--------------------||0|2020-09-01|-59.42|-49.47||1|2020-09-02|-59.42|-49.49||2|2020-09-03|-59.46|-49.7||3|2020-09-04|-59.43|-49.72||4|2020-09-05|-59.45|-49.72||5|2020-09-06|-59.44|-49.66||6|2020-09-07|-59.38|-49.69||7|2020-09-08|-59.31|-49.66||8|2020-09-09|-59.29|-49.68||9|2020-09-10|-59.26|-49.7|+----+------------+--------------------+--------------------+\n$xcsv_print-D--head-c0,3-6A68_icebergs_positions_and_dimensions_2020-21-A68A.csv\n+----+------------+---------------------------+---------------------------+---------------------------+---------------------------+||Date|A68A_Long_axis_end_Lat1|A68A_Long_axis_end_Lon1|A68A_Long_axis_end_Lat2|A68A_Long_axis_end_Lon2||||(degree_north)|(degree_east)|(degree_north)|(degree_east)||----+------------+---------------------------+---------------------------+---------------------------+---------------------------||0|2020-09-01|-59.63|-50.51|-59.26|-47.98||1|2020-09-02|-59.8|-50.52|-59.11|-48.3||2|2020-09-03|-60.04|-50.18|-58.88|-48.9||3|2020-09-04|-60.11|-49.77|-58.78|-49.43||4|2020-09-05|-60.06|-49.49|-58.73|-49.72||5|2020-09-06|-59.98|-49.19|-58.69|-50.02||6|2020-09-07|-59.84|-49|-58.69|-50.27||7|2020-09-08|-59.73|-48.85|-58.7|-50.48||8|2020-09-09|-59.72|-48.85|-58.67|-50.47||9|2020-09-10|-59.7|-48.85|-58.64|-50.45|+----+------------+---------------------------+---------------------------+---------------------------+---------------------------+\n$xcsv_print-D--head-c0,7-8A68_icebergs_positions_and_dimensions_2020-21-A68A.csv\n+----+------------+-------------------------+--------------------------+||Date|A68A_Long_axis_length|A68A_Short_axis_length||||(km)|(km)||----+------------+-------------------------+--------------------------||0|2020-09-01|nan|nan||1|2020-09-02|nan|nan||2|2020-09-03|149.375|49.875||3|2020-09-04|nan|nan||4|2020-09-05|nan|nan||5|2020-09-06|nan|nan||6|2020-09-07|nan|nan||7|2020-09-08|nan|nan||8|2020-09-09|nan|nan||9|2020-09-10|nan|nan|+----+------------+-------------------------+--------------------------+# Replicate the combined --head and --tail functionality with the -r option$xcsv_print-D-c0,7-8-r0-9,218-227A68_icebergs_positions_and_dimensions_2020-21-A68A.csv\n+-----+------------+-------------------------+--------------------------+||Date|A68A_Long_axis_length|A68A_Short_axis_length||||(km)|(km)||-----+------------+-------------------------+--------------------------||0|2020-09-01|nan|nan||1|2020-09-02|nan|nan||2|2020-09-03|149.375|49.875||3|2020-09-04|nan|nan||4|2020-09-05|nan|nan||5|2020-09-06|nan|nan||6|2020-09-07|nan|nan||7|2020-09-08|nan|nan||8|2020-09-09|nan|nan||9|2020-09-10|nan|nan||218|2021-04-07|nan|nan||219|2021-04-08|nan|nan||220|2021-04-09|nan|nan||221|2021-04-10|nan|nan||222|2021-04-11|nan|nan||223|2021-04-12|nan|nan||224|2021-04-13|nan|nan||225|2021-04-14|nan|nan||226|2021-04-15|nan|nan||227|2021-04-16|nan|nan|+-----+------------+-------------------------+--------------------------+In general, the default theme works OK in a dark- or light- background terminal. The default theme (light) assumes a dark background. If highlighted text is difficult to read on a light background, then specify thedarktheme instead (-t dark).In addition to using the CLI, the package can be used as a Python library. The main class isPrintwhich provides methods to pretty-print a given dataset (XCSV object):>>>importxcsv>>>importxcsv.utilsasxu>>>filename='example.csv'>>>withxcsv.File(filename)asf:>>>dataset=f.read()>>>printer=xu.Print(metadata=dataset.metadata,data=dataset.data)>>>printer.print_data()+----+--------------+-------------+||time|depth(m)|||(year)[a]|||----+--------------+-------------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+--------------+-------------+# To access the formatted and themed string, we can do the following>>>output=printer.format_data()>>>output'+----+----------+---------+\\n| |\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190mtime\\x1b[m\\x1b[m\\x1b[m |\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190mdepth\\x1b[m\\x1b[m |\\n| |\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m(year)\\x1b[m\\x1b[m |\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m(m)\\x1b[m\\x1b[m\\x1b[m |\\n| |\\x1b[38;2;190;190;190m\\x1b[38;2;190;190;190m[a]\\x1b[m\\x1b[m\\x1b[m | |\\n|----+----------+---------|\\n| 0 | 2012 | 0.575 |\\n| 1 | 2011 | 1.125 |\\n| 2 | 2010 | 2.225 |\\n+----+----------+---------+'>>>print(output)+----+----------+---------+||time|depth|||(year)|(m)|||[a]|||----+----------+---------||0|2012|0.575||1|2011|1.125||2|2010|2.225|+----+----------+---------+>>>printer.columns=[1]>>>printer.print_data()+----+---------+||depth|||(m)||----+---------||0|0.575||1|1.125||2|2.225|+----+---------+>>>printer.print_header()id:1title:Thetitlesummary:Thisdataset...Thesecondsummaryparagraph.Thethirdsummaryparagraph.EscapedbecauseitcontainsthedelimiterinaURLhttps://dummy.domainauthors:AB,CDlatitude:-73.86(degree_north)longitude:-65.46(degree_east)elevation:1897(ma.s.l.)[a]:2012notacompleteyear>>>printer.verbose=1>>>printer.print_header()id:1title:Thetitlesummary:['This dataset...','The second summary paragraph.','The third summary paragraph. Escaped because it contains the delimiter in a URL https://dummy.domain']authors:AB,CDlatitude:value:-73.86,units:degree_northlongitude:value:-65.46,units:degree_eastelevation:value:1897,units:ma.s.l.[a]:2012notacompleteyear>>>printer.print_column_headers()0name:time,units:year,notes:a1name:depth,units:m,notes:NoneCommand line usageCalling the script with the--helpoption will show the following usage:$python3-mxcsv.utils--help\nusage:xcsv_print[-h][-H][-C][-D][-cCOLUMNS][-rROWS][--head][--tail][-t{light,dark}][-v][-V]in_file\n\nprintxcsvfile\n\npositionalarguments:in_fileinputXCSVfile\n\noptionalarguments:-h,--helpshowthishelpmessageandexit-H,--header-onlyshowtheextendedheadersectiononly-C,--column-headers-onlyshowthedatatablecolumnheadersonly-D,--data-onlyshowthedatatableonly-cCOLUMNS,--columnsCOLUMNScolumnstoincludeinthedatatable(specifymultiplecolumnsseparatedbycommasand/orashyphen-separatedranges)-rROWS,--rowsROWSrowstoincludeinthedatatable(specifymultiplerowsseparatedbycommasand/orashyphen-separatedranges)--headonlyshowthefirst10rowsofthedatatable--tailonlyshowthelast10rowsofthedatatable-t{light,dark},--theme{light,dark}usethenamedthemetoapplystylingtotheoutput-v,--verboseshowincrementallyverboseoutput-V,--versionshowprogram'sversionnumberandexit"} +{"package": "xctemplateutils", "pacakge-description": "===========xctemplateutils===========xctemplateutils provides a list of useful command line programs thathelps ease the pain of manually dealing with messy .xctemplate files.How to use it=========* Installpip install xctemplateutils* Generate and for elementgenerate_xctemplate.py -d For example, suppose you have MagicalRecord copied intoa subfolder MagicalRecord/ of your .xctemplate folder @MyXCTemplate.xctemplate/MagicalRecord. You can:cd MyXCTemplate.xctemplate; generate_xctemplate.py -d MagicalRecord* Generate for elementgenerate_xctemplate.py -n "} +{"package": "xctool", "pacakge-description": "UNKNOWN"} +{"package": "xctools", "pacakge-description": "output color text to terminal"} +{"package": "xctools-kamaalio", "pacakge-description": "XcTools"} +{"package": "xctrl", "pacakge-description": "No description available on PyPI."} +{"package": "xcube", "pacakge-description": "#|hide\n#| eval: false\n! [ -e /content ] && pip install -q condacolab && python3 -c \"import condacolab; condacolab.install()\" # create conda environment in colab\n! [ -e /content ] && pip install -Uqq xcube # upgrade xcube on colab#| hide\nfrom xcube.text.all import *\n\n%load_ext autoreload\n%autoreload 2xcubexcube trains and explains XMTC modelsEXplainable EXtreme Multi-Label TeXt Classification:What is XMTC?Extreme Multi-Label Text Classification (XMTC) addresses the problem of automatically assigning each data point with most relevant subset of labels from an extremely large label set. One major application of XMTC is in the global healthcare system, specifically in the context of the International Classification of Diseases (ICD). ICD coding is the process of assigning codes representing diagnoses and procedures performed during a patient visit using clinical notes documented by health professionals.Datasets?Examples of ICD coding dataset:MIMIC-IIIandMIMIC-IV. Please note that you need to be a credentialated user and complete a training to acces the data.What is xcube?xcube trains and explains XMTC models using LLM fine-tuning.InstallCreate new conda environment:condacreate-nxxxpython=3.10condaactivatexxxInstall PyTorch with cuda enabled: [Optional]condasearchpytorchuse the build string that matches the python and cuda version, replacing the pytorch version and build string appropriately:condainstallpytorch=2.0.0=cuda118py310h072bc4cpytorch-cuda=11.8-cpytorch-cnvidiaUpdate cuda-toolkit:sudoaptinstallnvidia-cuda-toolkitVerify cuda is available: Runpythonandimport torch; torch.cuda.is_available()Install using:pipinstallxcubeConfigure accelerate by:accelerateconfigHow to useYou can either clone the repo and open it in your own machine. Or if you don't want to setup a python development environment, an even easier and quicker approach is to open this repo usingGoogle Colab. You can open this readme page in Colab using thislink.IN_COLAB = is_colab()source_mimic3 = untar_xxx(XURLs.MIMIC3_DEMO)\nsource_mimic4 = untar_xxx(XURLs.MIMIC4)\npath = Path.cwd().parent/f\"{'xcube' if IN_COLAB else ''}\" # root of the repo\n(path/'tmp/models').mkdir(exist_ok=True, parents=True)\ntmp = path/'tmp'Check your GPU memory! If you are running this on google colab be sure to turn on the GPU runtime. You should be able to train and infer all the models with atleast 16GB of memory. However, note that training the full versions of the datasets from scratch requires atleast 48GB memory.cudamem()Train and Infer on MIMIC3-rare50MIMIC3-rare50 refers to a split ofMIMIC-IIIthat contains the 50 most rare codes (Refer toKnowledge Injected Prompt Based Fine-Tuning for Multi-label Few-shot ICD Codingfor split creation).data = join_path_file('mimic3-9k_rare50', source_mimic3, ext='.csv')\n!head -n 1 {data}df = pd.read_csv(data,\n header=0,\n names=['subject_id', 'hadm_id', 'text', 'labels', 'length', 'is_valid', 'split'],\n dtype={'subject_id': str, 'hadm_id': str, 'text': str, 'labels': str, 'length': np.int64, 'is_valid': bool, 'split': str})\ndf.head(2)To launch the training of an XMTC model on MIMIC3-rare50:os.chdir(path/'scripts')\n!./run_scripts.sh --script_list_file script_list_mimic3_rare50trainTrain and Infer on MIMIC3-top50MIMIC3-top50 refers to a split ofMIMIC-IIIthat contains 50 most frequent codes (Refer toExplainable Prediction of Medical Codes from Clinical Textfor split creation)data = join_path_file('mimic3-9k_top50', source_mimic3, ext='.csv')\n!head -n 1 {data}df = pd.read_csv(data,\n header=0,\n names=['subject_id', 'hadm_id', 'text', 'labels', 'length', 'is_valid', 'split'],\n dtype={'subject_id': str, 'hadm_id': str, 'text': str, 'labels': str, 'length': np.int64, 'is_valid': bool, 'split': str})\ndf.head(2)To infer one our pretrained XMTC models on MIMIC3-top50 (Metrics for inference - Precision@3,5,8,15):model_fnames = L(source_mimic3.glob(\"**/*top50*.pth\")).map(str)\nprint('\\n'.join(model_fnames))\nfname = Path(shutil.copy(model_fnames[2], tmp/'models')).name.split('.')[0]\nprint(f\"We are going to infer model {fname}.\")os.chdir(path/'scripts')\n!./launches/launch_top50_mimic3 --fname {fname} --no_running_decoder --infer 1To launch the training of an XMTC model on MIMIC3-top50 from scratch:#| eval: false\nos.chdir(path/'scripts')\n!./run_scripts.sh --script_list_file script_list_mimic3_top50trainTrain and Infer on MIMIC3-full:MIMIC3-full refers to the fullMIMIC-IIIdataset. (Refer toExplainable Prediction of Medical Codes from Clinical Textfor details of how the data was curated)data = join_path_file('mimic3-9k_full', source_mimic3, ext='.csv')\n!head -n 1 {data}df = pd.read_csv(data,\n header=0,\n names=['subject_id', 'hadm_id', 'text', 'labels', 'length', 'is_valid', 'split'],\n dtype={'subject_id': str, 'hadm_id': str, 'text': str, 'labels': str, 'length': np.int64, 'is_valid': bool, 'split': str})\ndf.head(2)Lets's look at some of the ICD9 codes description:des = load_pickle(source_mimic3/'code_desc.pkl')\nlbl_dict = dict()\nfor lbl in df.labels[1].split(';'):\n lbl_dict[lbl] = des.get(lbl, 'NF')\npd.DataFrame(lbl_dict.items(), columns=['icd9_code', 'desccription'])To infer one our pretrained XMTC models on MIMIC3-full (Metrics for inference - Precision@3,5,8,15):model_fnames = L(source_mimic3.glob(\"**/*full*.pth\")).map(str)\nprint('\\n'.join(model_fnames))\nfname = Path(shutil.copy(model_fnames[0], tmp/'models')).name.split('.')[0]\nprint(f\"Let's infer the pretrained model {fname}.\")os.chdir(path/'scripts')\n!./launches/launch_complete_mimic3 --fname {fname} --infer 1 --no_running_decoderTrain and Infer on MIMIC4-full:MIMIC4-full refers to the fullMIMIC-IVdataset using ICD10 codes. (Refer toAutomated Medical Coding on MIMIC-III and MIMIC-IV: A Critical Review and Replicability Studyfor details of how the data was curated)data = join_path_file('mimic4_icd10_full', source_mimic4, ext='.csv')\n!head -n 1 {data}df = pd.read_csv(data,\n header=0,\n usecols=['subject_id', '_id', 'text', 'labels', 'num_targets', 'is_valid', 'split'],\n dtype={'subject_id': str, '_id': str, 'text': str, 'labels': str, 'num_targets': np.int64, 'is_valid': bool, 'split': str})\ndf.head(2)Let's look at some of the descriptions of ICD10 codes:stripped_codes = [''.join(filter(str.isalnum, s)) for s in df.labels[0].split(';')]\ndesc = get_description(stripped_codes)\npd.DataFrame(desc.items(), columns=['icd10_code', 'desccription'])To infer one our pretrained XMTC models on MIMIC4-full (Metrics for inference - Precision@5,8,15):print('\\n'.join(L(source_mimic4.glob(\"**/*full*.pth\")).map(str)))\nmodel_fname = Path('/home/deb/.xcube/data/mimic4/mimic4_icd10_clas_full.pth')\nfname = Path(shutil.copy(model_fname, tmp/'models')).name.split('.')[0]\nprint(f\"Let's infer the pretrained model {fname}.\")#| eval: false\nos.chdir(path/'scripts')\n!./launches/launch_complete_mimic4_icd10 --fname mimic4_icd10_clas_full --no_running_decoder --infer 1AcknowledgementThis repository is my attempt to create Extreme Multi-Label Text Classifiers using Language Model Fine-Tuning as proposed byJeremy HowardandSebastian RuderinULMFit. I am also heavily influenced by thefast.ai'scoursePractical Deep Learning for Codersand the excellent libraryfastai. I have adopted the style of coding fromfastaiusing the jupyter based dev environmentnbdev. Since this is one of my fast attempt to create a full fledged python library, I have at times replicated implementations from fastai with some modifications. A big thanks to Jeremy and his team fromfast.aifor everything they have been doing to make AI accessible to everyone."} +{"package": "xcube-4d-viewer", "pacakge-description": "xcube_4d_viewerThis repository is a plugin for the xcube server.xcube (https://xcube.readthedocs.io/en/latest/overview.html) is a Python package for generating and exploiting data\ncubes powered by xarray, dask, and zarr. It also provides a web API and server which can be used to access and\nvisualise these data cubes.This repository serves as an API extension to the xcube server, allowing xcube data cubes to be analysed and\nvisualised within Earthwave's 4D viewer. It computes configuration details and\nheatmap/3D heatmap/terrain tiles from the server's data cubes and provides them in a format expected by the 4D viewer.In order to connect to Earthwave's 4D viewer, the xcube server needs to be registered within a Middle Tier service.\nPlease contactsupport@earthwave.co.ukfor information on how to proceed.This work is done as part of the DeepESDL project (https://deepesdl.readthedocs.io/en/latest/)."} +{"package": "xcube-jl-ext", "pacakge-description": "xcube_jl_extxcubeJupyterLab integrationThis extension is composed of a Python package namedxcube_jl_extfor the JupyterLab server extension and a NPM package namedxcube-jl-extfor the JupyterLab frontend extension.The extension adds the following features to JupyterLab:Allows running a configurable xcube Viewer as widget in the JupyterLab.Allows using xcube Server and Viewer from within Jupyter Notebooks,\neven if JupyterLab is running remotely, i.e., spawned by JupyterHub.NOTEThis extension is still experimental and has neither been packaged\nnor deployed. Refer to the sectionDevelopmentbelow for dev installs.RequirementsJupyterLab >= 3.0xcube >= 0.13InstallTo install the extension, execute:pipinstallxcube_jl_extUninstallTo remove the extension, execute:pipuninstallxcube_jl_extTroubleshootIf you are seeing the frontend extension, but it is not working, check\nthat the server extension is enabled:jupyterserverextensionlistIf the server extension is installed and enabled, but you are not seeing\nthe frontend extension, check the frontend extension is installed:jupyterlabextensionlistDevelopmentSetup environmentBuildxcube Viewerresources\nfrom sources. Note you'll needyarnto be installed on your system.cd${projects}gitclonehttps://github.com/dcs4cop/xcube-viewer.gitcdxcube-viewer\nyarninstall\nyarnbuildNow set environment variableXCUBE_VIEWER_PATHto point\nto the xcube Viewer build directory:export XCUBE_VIEWER_PATH=${projects}/xcube-viewer/buildMake sure to have a source installation\nofxcubein a\ndedicated xcube Python environment.cd${projects}gitclonehttps://github.com/dcs4cop/xcube.gitcdxcube\nmambaenvcreateActivatexcubeenvironment and install xcube in editable (development) mode:condaactivatexcube\npipinstall-ve.Update environment with required packages for building and running\nthe JupyterLab extension.Note, the version of thejupyterlabin our development environment\nshould match the version of the target system. We also installjupyter-server-proxy.mambainstall-cconda-forge-cnodefaultsjupyterlab=3.4.0jupyter-server-proxyAlso install some packaging and build tools:mambainstall-cconda-forge-cnodefaultsnodejsjupyter-packaging\npipinstallbuildRefer also to theJupyterLab Extension Tutorialfor the use these tools.Install extension from sourcesMake sure,xcubeenvironment is active:condaactivatexcubeClone xcube JupyterLab extension repository next to thexcubesource\nfolder:cd${projects}gitclonehttps://github.com/dcs4cop/xcube-jl-ext.gitcdxcube-jl-extInstall the initial project dependencies and install the extension into\nthe JupyterLab environment. Copy the frontend part of the extension into\nJupyterLab. We can run this pip install command again every time we make\na change to copy the change into JupyterLab.pipinstall-ve.Create a symbolic link from JupyterLab to our source directory.\nThis means our changes are automatically available in JupyterLab:jupyterlabextensiondevelop--overwrite.If successful, we can run JupyterLab and check if the extension\nworks as expected:jupyterlabBuild after changesRun the following to rebuild the extension. This will be required\nafter any changes ofpackage.jsonor changes of frontend TypeScript\nfiles and other resources.jlpmrunbuildIf you wish to avoid building after each change, you can run thejlpmrunwatchfrom your extension directory in another terminal.\nThis will automatically compile the TypeScript files as they\nare changed and saved.ContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the xcube_jl_ext directory# Install package in development modepipinstall-e\".[test]\"# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Server extension must be manually installed in develop modejupyterserverextensionenablexcube_jl_ext# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstall# Server extension must be manually disabled in develop modejupyterserverextensiondisablexcube_jl_ext\npipuninstallxcube_jl_extIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedxcube-jl-extwithin that folder.Testing the extensionServer testsThis extension is usingPytestfor Python code testing.Install test dependencies (needed only once):pipinstall-e\".[test]\"# Each time you install the Python package, you need to restore the front-end extension linkjupyterlabextensiondevelop.--overwriteTo execute them, run:pytest-vv-rap--covxcube_jl_extFrontend testsThis extension is usingJestfor JavaScript code testing.To execute them, execute:jlpm\njlpmtestIntegration testsThis extension usesPlaywrightfor the integration tests (aka user level tests).\nMore precisely, the JupyterLab helperGalatais used to handle testing the extension in JupyterLab.More information are provided within theui-testsREADME.Packaging the extensionSeeRELEASE"} +{"package": "xcut", "pacakge-description": "# Xcut\nXcut is an Enhanced cut command, which is used to help grep column.[![](https://img.shields.io/pypi/pyversions/xcut.svg?longCache=True)](https://pypi.org/pypi/xcut/)\n[![](https://img.shields.io/pypi/v/xcut.svg?maxAge=36000)](https://pypi.org/pypi/xcut/)\n[![Build Status](https://travis-ci.org/ahuigo/xcut.svg?branch=master)](https://travis-ci.org/ahuigo/xcut)## Installpip install xcut\npip3 install xcutxcut \u2013help## Usage\nLet\u2019s test a file namedtest.csv> ~ cat test/test.csv\nname,gender,job\nJack,male,coder\nLucy,female,artistCut fields> ~ xcut -f job,name test/test.csv\njob,name\ncoder,Jack\nartist,Lucy### Set title type\nThe default title type is head:-t head> ~ xcut -f name,gender test/test.csvSet title type to index:-t index> ~ xcut -f 1,3 -t index test/test.csv\n1,3\nname,job\nJack,coder\nLucy,artistSet title type to custom(\u2013titles TITLES)> ~ xcut -f \u2018\u804c\u4e1a,\u59d3\u540d\u2019 \u2013titles \u2018\u59d3\u540d,\u6027\u522b,\u804c\u4e1a\u2019 test/test.csv -od $\u2019t\u2019\n\u804c\u4e1a \u59d3\u540d\njob name\ncoder Jack\nartist LucySet title type to kv(-t kv)> ~ echo \u2018key1=v1,key2=v2,key3=v3\u2019 | xcut -f key3,key2 -t kv\nkey3,key2\nv3,v2### Set input delimiter(d)> ~ xcut -f job,name test/test.csv -d \u2018,\u2019 -od \u2018`\u2019\njob`name\ncoder`Jack\nartist`Lucy### Set output delimiter(od)> ~ xcut -f job,name test/test.csv -od \u2018`\u2019\njob`name\ncoder`Jack\nartist`Lucy### pretty output\nYou could set the output delimiter(od), also you can print it viapretty> ~ xcut -f \u2018\u804c\u4e1a,\u59d3\u540d\u2019 \u2013titles \u2018\u59d3\u540d,\u6027\u522b,\u804c\u4e1a\u2019 test/test.csv -od $\u2019tt\u2019 \u2013pretty\n\u804c\u4e1a \u59d3\u540d\n\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014-\njob name\ncoder Jack\nartist Lucy### Use csv format\nNot only you could parse csv format file with\u2013from-csv:$ echo \u2018Lucy,\u201d98,99\u201d,23\u2019 | python xcut -f scores,name \u2013titles name,scores,age\nscores,name\n\u201c98,Lucy$ echo \u2018Lucy,\u201d98,99\u201d,23\u2019 | python xcut -f scores,name \u2013titles name,scores,age \u2013from-csv\nscores,name\n98,99,LucyYou could also save the output to csv format with(\u2013to-csv)$ echo \u2018Lucy,\u201d98,99\u201d,23\u2019 | python xcut -f scores,name \u2013titles name,scores,age \u2013from-csv \u2013to-csv\nscores,name\n\u201c98,99\u201d,Lucy## Required\n1. python>=3.5\n2. click"} +{"package": "xcute", "pacakge-description": "No description available on PyPI."} +{"package": "xcv", "pacakge-description": "xcv"} +{"package": "xcwarnings", "pacakge-description": "xcwarningsxcwarningsis a tool that helps Xcode developers set up a quality gate to catch new build warnings introduced to their codebase. This gate is meant to run on Pull Requests or Continuous Integration pipelines.[Features|Requirements|Installation|Usage|Running Tests|Contributing|Trademarks]FeaturesChecks for build warnings in your Xcode build output log, and fails if unexpected warnings are encountered.Can excludes a certain list of warnings, provided in an optional known warnings configuration file, from triggering a failure. The configuraiton file is easy to read and in JSON format.Generates a baseline known warnings file for current Xcode build output log. This is useful when onboarding to the tool, or when you're upgrading major Xcode version.Note: If your project is already at zero warnings, you can turn all warnings into errors using theTreat Warnings as Errorsbuild setting, and rely on the build failing.RequirementsPython 3.6 or aboveTested with logs from Xcode 12.4.Installation$ pip install xcwarningsNote: it is recommended to run the above commands in the context of a python 3 virtual environment. For more about setting one up, seeGetting Started with Python.Usageusage: xcwarnings.py [-h]\n [--known_build_warnings_file_path KNOWN_BUILD_WARNINGS_FILE_PATH]\n --source_root SOURCE_ROOT [--generate_baseline]\n xcode_build_output_file_path\n\npositional arguments:\n xcode_build_output_file_path\n Path to the xcode output file\n\noptional arguments:\n -h, --help show this help message and exit\n --known_build_warnings_file_path KNOWN_BUILD_WARNINGS_FILE_PATH\n Full path to a file with known build warnings\n --source_root SOURCE_ROOT\n File path for the root of the source code\n --generate_baseline Whether a new baseline of known issues should be\n generated.ExamplesGenerating baseline configuration filesTo generate a baseline configuration on the desktop, for the sample xcode log file at./tests/xcwarnings_tests/test_output_file_warnings.txt, you can run the command:$ python3 -m xcwarnings.xcwarnings ./tests/xcwarnings_tests/test_output_file_warnings.txt \\\n --known_build_warnings_file_path ~/Desktop/generated_known_issues.json \\\n --source_root ~/Documents/XCWarningsDemo \\\n --generate_baselineTo get a baseline for your project, you first compile your project, storing the output in a log file:$ xcodebuild build -project [PATH_TO_YOUR_PROJ.xcodeproj] >~/Desktop/log_output.logFollowed by:$ python3 -m xcwarnings.xcwarnings ~/Desktop/log_output.log \\\n --known_build_warnings_file_path ~/Desktop/generated_known_issues.json \\\n --source_root ~/Documents/XCWarningsDemo \\\n --generate_baselineChecking for regressionsTo check whether xcode build log contains new warnings not referenced in a given configuration file:$ python3 -m xcwarnings.xcwarnings ./tests/xcwarnings_tests/test_output_file_warnings.txt \\\n --known_build_warnings_file_path ~/Desktop/generated_known_issues.json \\\n --source_root ~/Documents/XCWarningsDemoNote: it is recommended to run the above commands in the context of a python 3 virtual environment. For more about setting one up, seeGetting Started With Python.An Example Configuration FileConfiguration file is expected to be in JSON format. It is an array of expected warning. Each warning should include the warning statement and the number of times it's expected. If the warning is at the file level, then file_path should be provided. file_path should be relative to SOURCE_ROOT. If the warning is at the target level, then target and project should be provided. See the example below.[\n {\n \"warning\": \"'statusBarOrientation' was deprecated in iOS 13.0: Use the interfaceOrientation property of the window scene instead.\",\n \"file_path\": \"XCWarningsDemo/ContentView.swift\",\n \"count\": 2\n },\n {\n \"warning\": \"'deprecatedApi()' is deprecated\",\n \"file_path\": \"XCWarningsDemo/ContentView.swift\",\n \"count\": 1\n },\n {\n \"warning\": \"AddressBookUI is deprecated. Consider migrating to ContactsUI instead.\",\n \"target\": \"XCWarningsDemoTarget\",\n \"project\": \"XCWarningsDemo\",\n \"count\": 1\n }\n]Running TestsOnce you have yourvirtualenvactivated and all the dependencies installed, run the tests:python3 -m pytestContributingThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visithttps://cla.opensource.microsoft.com.When you submit a pull request, a CLA bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct.\nFor more information see theCode of Conduct FAQor\ncontactopencode@microsoft.comwith any additional questions or comments.TrademarksThis project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft\ntrademarks or logos is subject to and must followMicrosoft's Trademark & Brand Guidelines.\nUse of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.\nAny use of third-party trademarks or logos are subject to those third-party's policies."} +{"package": "xcyl", "pacakge-description": "PythonTemplateSimple Template"} +{"package": "xcy-MVtest", "pacakge-description": "\ud83d\udce6 setup.py (for humans)========================Distribution-Free Test of Independence Based on Mean Variance Index.If you have any problems or advice, send them to my Email cs_xcy@126.com\u2728\ud83c\udf70\u2728"} +{"package": "xcynester", "pacakge-description": "No description available on PyPI."} +{"package": "xcy-Zscore", "pacakge-description": "No description available on PyPI."} +{"package": "xd", "pacakge-description": "A list of handy commands which makes life easier.Installpip install xd -U\n# pip install git+https://github.com/damnever/xd.git@master -UUsageUsage: xd [OPTIONS] COMMAND [ARGS]...\n\n A list of handy commands which makes life easier.\n\nOptions:\n --help Show this message and exit.\n\nCommands:\n batch Execute a program multiple times in parallel.\n config Manipulate config files: json, yaml, ini and toml.\n gitinit Init a git project, or creates a LICENSE/.gitignore file.\n version Show version.\n watch Execute a program periodically.xd --help\nxd --help"} +{"package": "xd35-cspcheck", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xd35-pnscan", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xda", "pacakge-description": "No description available on PyPI."} +{"package": "xdaemonocle", "pacakge-description": "daemonocle is a library for creating your own Unix-style daemons written in Python. It solves many\nproblems that other daemon libraries have and provides some really useful features you don\u2019t often\nsee in other daemons.Table of ContentsInstallationBasic UsageRationaleThe ProblemThe SolutionOther Useful FeaturesThestatusActionSlightly SmarterrestartActionSelf-ReloadShutdown CallbackNon-Detached ModeFile Descriptor HandlingDetailed UsageActionsIntegration with mitsuhiko\u2019s clickBugs, Requests, Questions, etc.InstallationTo install via pip:pip install daemonocleOr download the source code and install manually:git clone https://github.com/jnrbsn/daemonocle.git\ncd daemonocle/\npython setup.py installBasic UsageHere\u2019s areally reallybasic example:importsysimporttimeimportdaemonocle# This is your daemon. It sleeps, and then sleeps again.defmain():whileTrue:time.sleep(10)if__name__=='__main__':daemon=daemonocle.Daemon(worker=main,pidfile='/var/run/daemonocle_example.pid',)daemon.do_action(sys.argv[1])And here\u2019s the same example with logging and aShutdown Callback:importloggingimportsysimporttimeimportdaemonocledefcb_shutdown(message,code):logging.info('Daemon is stopping')logging.debug(message)defmain():logging.basicConfig(filename='/var/log/daemonocle_example.log',level=logging.DEBUG,format='%(asctime)s[%(levelname)s]%(message)s',)logging.info('Daemon is starting')whileTrue:logging.debug('Still running')time.sleep(10)if__name__=='__main__':daemon=daemonocle.Daemon(worker=main,shutdown_callback=cb_shutdown,pidfile='/var/run/daemonocle_example.pid',)daemon.do_action(sys.argv[1])And here\u2019s what it looks like when you run it:user@host:~$ python example.py start\nStarting example.py ... OK\nuser@host:~$ python example.py status\nexample.py -- pid: 1234, status: running, uptime: 1m, %cpu: 0.0, %mem: 0.0\nuser@host:~$ python example.py stop\nStopping example.py ... OK\nuser@host:~$ cat /var/log/daemonocle_example.log\n2014-05-04 12:39:21,090 [INFO] Daemon is starting\n2014-05-04 12:39:21,091 [DEBUG] Still running\n2014-05-04 12:39:31,091 [DEBUG] Still running\n2014-05-04 12:39:41,091 [DEBUG] Still running\n2014-05-04 12:39:51,093 [DEBUG] Still running\n2014-05-04 12:40:01,094 [DEBUG] Still running\n2014-05-04 12:40:07,113 [INFO] Daemon is stopping\n2014-05-04 12:40:07,114 [DEBUG] Terminated by SIGTERM (15)For more details, see theDetailed Usagesection below.RationaleIf you think about it, a lot of Unix daemons don\u2019t really know what the hell they\u2019re doing. Have you\never found yourself in a situation that looked something like this?user@host:~$ sudo example start\nstarting example ... ok\nuser@host:~$ ps aux | grep example\nuser 1234 0.0 0.0 1234 1234 pts/1 S+ 12:34 0:00 grep example\nuser@host:~$ sudo example start\nstarting example ... ok\nuser@host:~$ echo $?\n0\nuser@host:~$ tail -f /var/log/example.log\n...Or something like this?user@host:~$ sudo example stop\nstopping example ... ok\nuser@host:~$ ps aux | grep example\nuser 123 0.0 0.0 1234 1234 ? Ss 00:00 0:00 /usr/local/bin/example\nuser 1234 0.0 0.0 1234 1234 pts/1 S+ 12:34 0:00 grep example\nuser@host:~$ sudo example stop\nstopping example ... ok\nuser@host:~$ ps aux | grep example\nuser 123 0.0 0.0 1234 1234 ? Ss 00:00 0:00 /usr/local/bin/example\nuser 1240 0.0 0.0 1234 1234 pts/1 S+ 12:34 0:00 grep example\nuser@host:~$ sudo kill -9 123\n...Or something like this?user@host:~$ sudo example status\nUsage: example {start|stop|restart}\nuser@host:~$ ps aux | grep example\n...These are just a few examples of unnecessarily common problems. It doesn\u2019t have to be this way.Note:You might be thinking, \u201cWhy not just write a smarter start/stop shell script wrapper\nfor your daemon that checks whether or not it actually started, actually stopped, etc.?\u201d\nSeriously?It doesn\u2019t have to be this way.I believe daemons should be more self-aware. They\nshould handle their own problems most of the time, and your start/stop script should only be a\nvery thin wrapper around your daemon or simply a symlink to your daemon.The ProblemIf you\u2019ve ever dug deep into the nitty-gritty details of how daemonization works, you\u2019re probably\nfamiliar with thestandard \u201cdouble fork\u201d paradigmfirst introduced\nby W. Richard Stevens in the bookAdvanced Programming in the UNIX Environment. One of the problems with the standard way to implement this is that\nif the final child dies immediately when it gets around to doing real work, the original parent\nprocess (the one that actually had control of your terminal) is long gone. So all you know is that\nthe process got forked, but you have no idea if it actually kept running for more than a fraction of\na second. And let\u2019s face it, one of the most likely times for a daemon to die is immediately after\nit starts (due to bad configuration, permissions, etc.).The next problem mentioned in the section above is when you try to stop a daemon, it doesn\u2019t\nactually stop, and you have no idea that it didn\u2019t actually stop. This happens when a process\ndoesn\u2019t respond properly to aSIGTERMsignal. It happens more often than it should. The problem\nis not necessarily the fact that it didn\u2019t stop. It\u2019s the fact that you didn\u2019tknowthat it didn\u2019t\nstop. The start/stop script knows that it successfully sent the signal and so it assumes success.\nThis also becomes a problem when yourrestartcommand blindly callsstopand thenstart,\nbecause it will try to start a new instance of the daemon before the previous one has exited.These are the biggest problems most daemons have in my opinion. daemonocle solves these problems and\nprovides many other \u201cfancy\u201d features.The SolutionThe problem with the daemon immediately dying on startup and you not knowing about it is solved by\nhaving the first child (the immediate parent of the final child) sleep for one second and then callos.waitpid(pid, os.WNOHANG)to see if the process is still running. This is what daemonocle\ndoes. So if you\u2019re daemon dies within one second of starting, you\u2019ll know about it.This problem with the daemon not stopping and you not knowing about it is solved by simply waiting\nfor the process to finish (with a timeout). This is what daemonocle does. (Note: When a timeout\noccurs, it doesn\u2019t try to send aSIGKILL. This is not always what you\u2019d want and often not a\ngood idea.)Other Useful FeaturesBelow are some other useful features that daemononcle provides that you might not find elsewhere.ThestatusActionThere is astatusaction that not only displays whether or not the daemon is running and its\nPID, but also the uptime of the daemon and the % CPU and % memory usage of all the processes in the\nsame process group as the daemon (which are probably its children). So if you have a daemon that\nlaunches mulitple worker processes, thestatusaction will show the % CPU and % memory usage of\nall the workers combined.It might look something like this:user@host:~$ python example.py status\nexample.py -- pid: 1234, status: running, uptime: 12d 3h 4m, %cpu: 12.4, %mem: 4.5Slightly SmarterrestartActionHave you ever tried to restart a daemon only to realize that it\u2019s not actually running? Let me\nguess: it just gave you an error and didn\u2019t start the daemon. A lot of the time this is not a\nproblem, but if you\u2019re trying to restart the daemon in an automated way, it\u2019s more annoying to have\nto check if it\u2019s running and do either astartorrestartaccordingly. With daemonocle, if\nyou try to restart a daemon that\u2019s not running, it will give you a warning saying that it wasn\u2019t\nrunning and then start the daemon. This is often what people expect.Self-ReloadDaemons that use daemonocle have the ability to reload themselves by simply callingdaemon.reload()wheredaemonis yourdaemonocle.Daemoninstance. The execution of the\ncurrent daemon halts whereverdaemon.reload()was called, and a new daemon is started up to\nreplace the current one. From your code\u2019s perspective, it\u2019s pretty much the same as a doing arestartexcept that it\u2019s initiated from within the daemon itself and there\u2019s no signal handling\ninvolved. Here\u2019s a basic example of a daemon that watches a config file and reloads itself when the\nconfig file changes:importosimportsysimporttimeimportdaemonocleclassFileWatcher(object):def__init__(self,filename,daemon):self._filename=filenameself._daemon=daemonself._file_mtime=os.stat(self._filename).st_mtimedeffile_has_changed(self):current_mtime=os.stat(self._filename).st_mtimeifcurrent_mtime!=self._file_mtime:self._file_mtime=current_mtimereturnTruereturnFalsedefwatch(self):whileTrue:ifself.file_has_changed():self._daemon.reload()time.sleep(1)if__name__=='__main__':daemon=daemonocle.Daemon(pidfile='/var/run/daemonocle_example.pid')fw=FileWatcher(filename='/etc/daemonocle_example.conf',daemon=daemon)daemon.worker=fw.watchdaemon.do_action(sys.argv[1])Shutdown CallbackYou may have noticed from theBasic Usagesection above that ashutdown_callbackwas defined.\nThis function gets called whenever the daemon is shutting down in a catchable way, which should be\nmost of the time except for aSIGKILLor if your server crashes unexpectedly or loses power or\nsomething like that. This function can be used for doing any sort of cleanup that your daemon needs\nto do. Also, if you want to log (to the logger of your choice) the reason for the shutdown and the\nintended exit code, you can use themessageandcodearguments that will be passed to your\ncallback (your callback must take these two arguments).Non-Detached ModeThis is not particularly interesting per se, but it\u2019s worth noting that in non-detached mode, your\ndaemon will do everything else you\u2019ve configured it to do (i.e.setuid,setgid,chroot,\netc.) except actually detaching from your terminal. So while you\u2019re testing, you can get an\nextremely accurate view of how your daemon will behave in the wild. It\u2019s also worth noting that\nself-reloading works in non-detached mode, which was a little tricky to figure out initially.File Descriptor HandlingOne of the things that daemons typically do is close all open file descriptors and establish new\nones forSTDIN,STDOUT,STDERRthat just point to/dev/null. This is fine most of\nthe time, but if your worker is an instance method of a class that opens files in its__init__()method, then you\u2019ll run into problems if you\u2019re not careful. This is also a problem if you\u2019re\nimporting a module that leaves open files behind. For example, importing therandomstandard library module in Python 3\nresults in an open file descriptor for/dev/urandom.Since this \u201cfeature\u201d of daemons often causes more problems than it solves, and the problems it\ncauses sometimes have strange side-effects that make it very difficult to troubleshoot, this feature\nis optional and disabled by default in daemonocle via theclose_open_filesoption.Detailed UsageThedaemonocle.Daemonclass is the main class for creating a daemon using daemonocle. Here\u2019s the\nconstructor signature for the class:classdaemonocle.Daemon(worker=None,shutdown_callback=None,prog=None,pidfile=None,detach=True,uid=None,gid=None,workdir='/',chrootdir=None,umask=022,stop_timeout=10,close_open_files=False)And here are descriptions of all the arguments:workerThe function that does all the work for your daemon.shutdown_callbackThis will get called anytime the daemon is shutting down. It should take amessageand acodeargument. The message is a human readable message that explains why the daemon is\nshutting down. It might useful to log this message. The code is the exit code with which it\nintends to exit. SeeShutdown Callbackfor more details.progThe name of your program to use in output messages. Default:os.path.basename(sys.argv[0])pidfileThe path to a PID file to use. It\u2019s not required to use a PID file, but if you don\u2019t, you won\u2019t\nbe able to use all the features you might expect. Make sure the user your daemon is running as\nhas permission to write to the directory this file is in.detachWhether or not to detach from the terminal and go into the background. SeeNon-Detached Modefor more details. Default:TrueuidThe user ID to switch to when the daemon starts. The default is not to switch users.gidThe group ID to switch to when the daemon starts. The default is not to switch groups.workdirThe path to a directory to change to when the daemon starts. Note that a file system cannot be\nunmounted if a process has its working directory on that file system. So if you change the\ndefault, be careful about what you change it to. Default:\"/\"chrootdirThe path to a directory to set as the effective root directory when the daemon starts. The\ndefault is not to do anything.umaskThe file creation mask (\u201cumask\u201d) for the process. Default:022stop_timeoutNumber of seconds to wait for the daemon to stop before throwing an error. Default:10close_open_filesWhether or not to close all open files when the daemon detaches. Default:FalseActionsThe default actions arestart,stop,restart, andstatus. You can get a list of\navailable actions using thedaemonocle.Daemon.list_actions()method. The recommended way to call\nan action is using thedaemonocle.Daemon.do_action(action)method. The string name of an action\nis the same as the method name except with dashes in place of underscores.If you want to create your own actions, simply subclassdaemonocle.Daemonand add the@daemonocle.expose_actiondecorator to your action method, and that\u2019s it.Here\u2019s an example:importdaemonocleclassMyDaemon(daemonocle.Daemon):@daemonocle.expose_actiondeffull_status(self):\"\"\"Get more detailed status of the daemon.\"\"\"passThen, if you did the basicdaemon.do_action(sys.argv[1])like in all the examples above, you can\ncall your action with a command likepython example.pyfull-status.Integration with mitsuhiko\u2019s clickdaemonocle also provides an integration withclick, the \u201ccomposable\ncommand line utility\u201d. The integration is in the form of a custom command classdaemonocle.cli.DaemonCLIthat you can use in conjunction with the@click.command()decorator\nto automatically generate a command line interface with subcommands for all your actions. It also\nautomatically daemonizes the decorated function. The decorated function becomes the worker, and the\nactions are automatically mapped from click to daemonocle.Here\u2019s an example:importtimeimportclickfromdaemonocle.cliimportDaemonCLI@click.command(cls=DaemonCLI,daemon_params={'pidfile':'/var/run/example.pid'})defmain():\"\"\"This is my awesome daemon. It pretends to do work in the background.\"\"\"whileTrue:time.sleep(10)if__name__=='__main__':main()Running this example would look something like this:user@host:~$ python example.py --help\nUsage: example.py [] []...\n\n This is my awesome daemon. It pretends to do work in the background.\n\nOptions:\n --help Show this message and exit.\n\nCommands:\n start Start the daemon.\n stop Stop the daemon.\n restart Stop then start the daemon.\n status Get the status of the daemon.\nuser@host:~$ python example.py start --help\nUsage: example.py start []\n\n Start the daemon.\n\nOptions:\n --debug Do NOT detach and run in the background.\n --help Show this message and exit.Thedaemonocle.cli.DaemonCLIclass also accepts adaemon_classargument that can be a\nsubclass ofdaemonocle.Daemon. It will use your custom class, automatically create subcommands\nfor any custom actions you\u2019ve defined, and use the docstrings of the action methods as the help text\njust like click usually does.This integration is entirely optional. daemonocle doesn\u2019t enforce any sort of argument parsing. You\ncan use argparse, optparse, or just plainsys.argvif you want.Bugs, Requests, Questions, etc.Please create anissue on GitHub."} +{"package": "xdagtool", "pacakge-description": "Xdag slicing toolcopy specific time range data files.requirementpython >= 3.7installpip install xdagtoolusagexdag-slice --help"} +{"package": "xdaLibs", "pacakge-description": "No description available on PyPI."} +{"package": "xdantic", "pacakge-description": "xdanticLightweight configuration library on top of PydanticGetting startedThis notebook shows some example usages of xdantic.It explains how to provide values to the configuration object, how to\naccess values and how nested configurations work.The configuration management is simple, including the config object\nitself with all the fields that you implementfromtypingimportLiteralfrompydanticimportHttpUrl,FieldfromxdanticimportXConfigclassDemoConfig(XConfig):\"\"\"The object `DemoConfig` is the central config object thatwill hold your values and can be extended to your needs with new values.Here, you can leverage the power of Pydantic and Python typehints to create a configurationthat is safe, documented and easy to use.Check https://pydantic-docs.helpmanual.io/usage/types/ to learn more about field types in Pydantic.\"\"\"DB_HOST:HttpUrl# will be validate to be a httpUrlDB_PORT:int=Field(default=3333,le=64000,ge=1024)# will be validated to be in the given rangeDB_TYPE:Literal[\"postgres\",\"mysql\"]=\"mysql\"# can only take on values present in the `Literal` definitionCreate a configTo create a config object with parsed values you can simply call the\ninitializer method and XConfig will automatically create the object\nusing values from e.g. environment variables.Now that we have theDemoConfigwe are ready to use our config in the\ncode. The next cell provides an example of parsing values to the config\nfrom environment variables and accessing them:importosos.environ['DB_PORT']='8888'# note, how this value will take presedence over the defaultos.environ['DB_HOST']='https://postgres-develop.cluster.svc.local'os.environ['DB_TYPE']='postgres'print(DemoConfig())Nested configurationSometime, it is desired to nest configurations to have a structure likeconfig.db.usernamne. This can be easily achieved by creating a\nseparate class that inherits frompydantic.BaseModeland add it as an\nattribute to the config object (DemoConfig). In the cell below, we\noverwrite the definitions from above to create the nested config object:frompydanticimportBaseModel,PositiveFloat,HttpUrl# for objects that will be nested into the root config object, inherit from `BaseModel`classModelConfig(BaseModel):lr:PositiveFloat=1e-3# overwrite the `XConfig` definition from above to include the sub-config object.classDemoConfig(XConfig):MODEL_CFG:ModelConfig=ModelConfig()DB_HOST:HttpUrl# will be validate to be a httpUrlDB_PORT:int=Field(default=3333,le=64000,ge=1024)# will be validated to be in the given rangeDB_TYPE:Literal[\"postgres\",\"mysql\"]=\"mysql\"# can only take on values present in the `Literal` definitionos.environ['MODEL_CFG__LR']='0.1'print(DemoConfig())Reading from .env file {#reading-from-env-file}In the notebooks folder there is a file called '.env' containing some\nconfig values. XConfig objects will also parse .env files automatically\nif they exist.os.environ.pop('MODEL_CFG__LR',None)print(ModelConfig())"} +{"package": "xdart", "pacakge-description": "xdartX-ray Data Analysis in Real TimeInstallationRecommended method:Install Anaconda if you don't already have it (Miniconda recommended)https://docs.conda.io/en/latest/miniconda.htmlFrom the terminal, create a new environment with python < 3.12:conda create -n xdart python=3.11Activate the xdart environment:conda activate xdartInstall xdart using pip:pip install xdart --upgradeAlternative:If you already have conda installed and a working environment you want to use, you can simply install xdart in that environment:pip install xdart --upgradeRunningOnce installed you can run the program by simply typingxdartin the terminal.Important: Make sure you have activated the conda environment xdart was installed in.conda activate xdart\nxdart"} +{"package": "xdas", "pacakge-description": "No description available on PyPI."} +{"package": "xdat", "pacakge-description": "What isxdat?xdat (eXtended Data Analysis Toolkit), is a set of utilities that help streamline data science projects.Monkey-patches common packages to add useful functionalityHelps with standardization of plots in projectsIncludes useful tools (like caching)Warning: this isn't even in \"alpha\" yet, and will likely have changes that are not backwards-compatible.InstallationUbuntu 20.04> pip install xdatOptionally, can also install::> sudo apt -q -y install libeigen3-dev\n> pip install git+https://github.com/madrury/py-glm.git"} +{"package": "xdata", "pacakge-description": "UNKNOWN"} +{"package": "x-data-processing", "pacakge-description": "x-data-processingIt is a base app to start the x-data processing"} +{"package": "xdatasets", "pacakge-description": "VersionsDocumentation and SupportOpen SourceCoding StandardsDevelopment StatusEasy access to Earth observation datasets with xarray.Free software: MIT licenseDocumentation:https://xdatasets.github.io/xdatasetsFeaturesTODOCreditsThis package was created withCookiecutterand theOuranosinc/cookiecutter-pypackageproject template."} +{"package": "xdatbus", "pacakge-description": "xdatbusXdatbus is a Python package designed specifically for Vienna Ab-initio Simulation Package (VASP) users conducting\nab-initio molecular dynamics (AIMD) simulations, as well as biased MD simulations. The name of the package is derived\nfrom XDATCAR, which represents the combined AIMD trajectories generated by VASP. Documentation for the package can be\naccessedhereand the Jupyter\nNotebooktutorialis also available.InstallationMake sure you have a Python interpreter, preferably version 3.10 or higher. Then, you can simply install xdatbus from\nPyPI usingpip:pipinstallxdatbusIf you'd like to use the latest unreleased version on the main branch, you can install it directly from GitHub:pipinstall-Ugit+https://github.com/jcwang587/xdatbusThe package is also availabe from conda-based installation. It is generally recommended you first create a separate\nenvironment, then you can install via the xdatbus channel on Anaconda cloud:condainstall--channelxdatbusxdatbusIf you plan to use PLUMED to analyze biased MD sampling results, you can also install the conda version of PLUMED\ntogether:condainstall-cxdatbus-cconda-forgexdatbusplumedGet StartedThis is a brief example demonstrating how to use the basic function of xdatbus to aggregate multiple xdatcar files into\na single file and unwrap the coordinates into an .xyz file:importosfromxdatbusimportxdc_aggregate,xdc_unwrapxdc_dir=\"./xdatcar_dir\"xdb_dir=os.path.dirname(xdc_dir)xdb_path=os.path.join(xdb_dir,\"XDATBUS\")xyz_path=os.path.join(xdb_dir,\"XDATBUS_unwrap.xyz\")xdc_aggregate(xdc_dir=xdc_dir,output_dir=xdb_dir)xdc_unwrap(xdc_path=xdb_path,output_path=xyz_path)There are also entry points included with the installation for the Command Line Interface (CLI) to perform similar\ntasks (do not include the$when copying):$xdc_aggregate--xdc_dir./xdatcar--output_dir./$xdc_unwrap--xdc_path./XDATBUS--output_path./XDATBUS_unwrap.xyzMajor Changelog0.2.2Enabled CLI with enhanced interaction through therichpackage.0.2.0Implemented the preparation of training data forMACEmachine learning\ninteratomic potentials."} +{"package": "xdb", "pacakge-description": "The goal ofxdbis to offer a single API for any database in Python. Once a module has been written for a particular database, it is as easy as changing the 1) import statement and 2) server information to switch between backends. Let\u2019s say 2-5 lines of code, total."} +{"package": "xdbx", "pacakge-description": "[toc]\u9879\u76ee\u80cc\u666f\u76ee\u524d\u6bcf\u6b21\u6211\u4eec\u5b58\u6570\u636e\u5e93\u7684\u65f6\u5019\u90fd\u4f1a\u6709\u8fd9\u6837\u7684\u95ee\u9898\uff0c\u6240\u6709\u7684\u6570\u636e\u5728\u540c\u6b65\u3002\u6216\u8005\u8bf4\u5728\u5165\u5e93\u65f6\u6211\u4eec\u9700\u8981\u5199\u5165\u5e93\u7684\u76f8\u5173\u4ee3\u7801\u3010day by day\u3011\uff0c\u672c\u7740\uff1aDRY - Don't Repeat Yourself(\u4e0d\u8981\u91cd\u590d\u4f60\u81ea\u5df1)\u539f\u5219\u4e8e\u662f\u6211\u60f3\u5230\u4e86\u6211\u4eec\u53ef\u4ee5\u5f02\u6b65\u53ca\u6279\u91cf\u6570\u636e\u64cd\u4f5c\u5668\u3002\u9879\u76ee\u6784\u60f3\u6211\u4eec\u53ea\u9700\u8981\u5173\u6ce8\u6570\u636e\u7684\u95ee\u9898\uff0c\u4e0d\u7528\u518d\u592a\u591a\u8d39\u5fc3\u64cd\u4f5c\u76f8\u5173\u7684\u521b\u5efa\u8868\uff0c\u4fee\u6539\u8868\u76f8\u5173\u5b57\u6bb5\u95ee\u9898\u9879\u76ee\u652f\u6301\u7684\u6570\u636e\u5e93\u7c7b\u578bMysqlSqlServerPostgresKafKaElasticSearchMongo\u6587\u4ef6\u8bf4\u660eDBOP(Database Operation)\u6570\u636e\u5e93\u64cd\u4f5c\u76f8\u5173\u4ee3\u7801x_sqlserver.py\u6587\u4ef6\u7528\u6765\u5b58\u50a8\u5904\u7406x_sqlserver\u6570\u636e\u7684\u7ba1\u9053x_mysql.py\u6587\u4ef6\u7528\u6765\u5b58\u50a8\u5904\u7406x_mysql\u6570\u636e\u7684\u7ba1\u9053x_kafka.py\u6587\u4ef6\u7528\u6765\u5b58\u50a8\u5904\u7406kafka\u6570\u636e\u7684\u7ba1\u9053x_mongo.py\u6587\u4ef6\u7528\u6765\u5b58\u50a8\u5904\u7406Mongo\u6570\u636e\u7684\u7ba1\u9053SqlServer\u5c06SqlServer\u8fdb\u884c\u4e86\u5c01\u88c5\uff0c\u4f1a\u81ea\u52a8\u667a\u80fd\u7684\u53bb\u521b\u5efa\u4e00\u4e9b\u8868\u548c\u5b57\u6bb5\u76f8\u5173\u7684\u4e1c\u897f\uff0c\u4f1a\u7701\u722c\u866b\u5f00\u53d1\u8005\u4e00\u4e9b\u65f6\u95f4MySQL\u5c06MySQL\u8fdb\u884c\u4e86\u5c01\u88c5\uff0c\u4f1a\u81ea\u52a8\u667a\u80fd\u7684\u53bb\u521b\u5efa\u4e00\u4e9b\u8868\u548c\u5b57\u6bb5\u76f8\u5173\u7684\u4e1c\u897f\uff0c\u4f1a\u7701\u722c\u866b\u5f00\u53d1\u8005\u4e00\u4e9b\u65f6\u95f4\u3002\u56e0\u4e3amysql<=5.5\u7248\u672c\u53ef\u80fd\u6709\u4e9b\u521b\u5efa\u66f4\u65b0\u65f6\u95f4\u4e0d\u7a33\u5b9a\u7684\u95ee\u9898\uff0c\u6211\u5df2\u7ecf\u628a\u76f8\u5173\u7684\u4ee3\u7801\u5148\u6682\u65f6\u4e0d\u5f00\u653e\uff0c\u5982\u679c\u6709\u66f4\u597d\u7684\u65b9\u6848\u6211\u4eec\u518d\u4f18\u5316\u4e00\u4e0b\u3002PostgreSQL\u5c06PostgreSQL\u8fdb\u884c\u4e86\u5c01\u88c5\uff0c\u4f1a\u81ea\u52a8\u667a\u80fd\u7684\u53bb\u521b\u5efa\u4e00\u4e9b\u8868\u548c\u5b57\u6bb5\u76f8\u5173\u7684\u4e1c\u897f\uff0c\u4f1a\u7701\u722c\u866b\u5f00\u53d1\u8005\u4e00\u4e9b\u65f6\u95f4\u3002Kafka\u5c06Kafka\u8fdb\u884c\u4e86\u5c01\u88c5,\u5bf9\u5e73\u65f6\u6211\u4eec\u722c\u866b\u7684\u4e00\u4e9b\u5e38\u89c4\u6570\u636e\u5b58\u50a8\u505a\u64cd\u4f5c\uff0c\u5229\u7528\u5355\u4f8b\u6a21\u5f0f\u5f00\u53d1\u652f\u6301\u591a\u7ebf\u7a0b\u64cd\u4f5c\u3010\u52a0\u9501\u3011\u57fa\u672c\u5b9e\u4f8b# \u5bfc\u5165mysqlfromxdbximportx_mysql# \u5bfc\u5165sqlserver# from xdbx import x_mssql# \u6570\u636e\u5e93ipx_mysql.host='127.0.0.1'# \u6570\u636e\u5e93\u7aef\u53e3 \u3010mysql\u9ed8\u8ba4\u4e3a3306\u3011x_mysql.port=3306# \u6570\u636e\u5e93\u7528\u6237\u540dx_mysql.username='root'# \u6570\u636e\u5e93\u5bc6\u7801x_mysql.password='123456'# \u6570\u636e\u5e93\u540d\u3010\u9700\u8981\u5148\u521b\u5efa\u597d\u7684\u6570\u636e\u5e93\u3011x_mysql.db='test'# \u63d2\u5165\u4e00\u6761x_mysql.insert_one(item={'a':1,'b':2},table='ceshi_20211229')# \u63d2\u5165\u591a\u6761x_mysql.insert_many(items=[{'a':1,'b':2},{'a':1,'b':2},{'a':1,'b':2},{'a':1,'b':2}],table='ceshi_20211229')TODO-LIST\u652f\u6301\u6570\u636e\u5e93\u7684\u8fde\u63a5\u53c2\u6570\u91cd\u5199\u64cd\u4f5c\u667a\u80fd\u521b\u5efa\u8868\u548c\u5b57\u6bb5\u64cd\u4f5c\u6570\u636e\u540c\u4e00\u4e2a\u8868\u5b57\u6bb5\u4e0d\u540c\u65f6\uff0c\u4f1a\u5230\u8868\u4e2d\u667a\u80fd\u589e\u52a0\u5b57\u6bb5\u6279\u91cf\u6570\u636e\u63d2\u5165\u64cd\u4f5c\u652f\u6301\u5355\u4f8b\u591a\u7ebf\u7a0b\u52a0\u9501\u64cd\u4f5c\u521b\u5efa\u8868\u65f6\u4f1a\u81ea\u52a8\u62a5\u8b66\u9489\u9489\u901a\u77e5\u6d88\u606f\u6dfb\u52a0\u67e5\u8be2\u529f\u80fd\u6dfb\u52a0\u66f4\u65b0\u529f\u80fd\u6dfb\u52a0\u4e3b\u952e\u529f\u80fd\u652f\u6301\u5b57\u7b26\u4e32,\u5b57\u5178\u548c\u5217\u8868\u7c7b\u578bQ&AQ0:\u89e3\u51b3\u89e6\u53d1\u5668\u7684\u95ee\u9898\u6ce8\uff1a\u76f8\u540c\u6570\u636e\u5e93\u4e2d\u4e0d\u80fd\u6709\u76f8\u540c\u7684\u89e6\u53d1\u5668\uff0c\u867d\u7136\u4f5c\u7528\u4e8e\u8fd9\u4e2a\u8868\uff0c\u4f46\u662f\u4ed6\u7684\u8303\u56f4\u662f\u76f8\u5bf9\u4e8e\u6570\u636e\u5e93\uff0c\u76f8\u5f53\u4e8e\u51fd\u6570\u540dQ1:\u89e3\u51b3\u5b57\u6bb5\u540d\u5927\u5c0f\u5199\u4e0d\u540c\u5224\u65ad\u6709\u8bef\u7684\u95ee\u9898\u4f7f\u7528\u5b57\u6bb5\u505a\u5bf9\u6bd4\u65f6\u5168\u8fdb\u884c\u8f6c\u6362\u6210\u5c0f\u5199\u540e\u518d\u5bf9\u6bd4"} +{"package": "xdcc-dl", "pacakge-description": "XDCC DownloadermasterdevelopAn XDCC File downloader based on theirclibframework.InstallationEither install the program usingpip install xdcc-dlorpython setup.py installPlease not that python 2 is no longer supported, the project requires python 3 to run.UsageMessage-based CLIXDCC Packlists usually list xdcc commands in the following form:/msg xdcc send #By supplying this message as a positional parameter, the pack can be downloaded.Examples:# This is the xdcc message: '/msg the_bot xdcc send #1'\n\n# This command downloads pack 1 from the_bot\n$ xdcc-dl \"/msg the_bot xdcc send #1\"\n\n# It's possible to download a range of packs (1-10 in this case):\n$ xdcc-dl \"/msg the_bot xdcc send #1-10\"\n\n# Range stepping is also possible:\n$ xdcc-dl \"/msg the_bot xdcc send #1-10;2\"\n# (This will download packs 1,3,5,7,9)\n\n# Explicitly specifying the packs to download as a comma-separated list:\n$ xdcc-dl \"/msg the_bot xdcc send #1,2,5,8\"\n# (This will download packs 1,2,5,8)\n\n# you can also specify the destination file or directory:\n$ xdcc-dl \"/msg the_bot xdcc send #1\" -o /home/user/Downloads/test.txt\n\n# if the bot is on a different server than irc.rizon.net, a server\n# has to be specified:\n$ xdcc-dl \"/msg the_bot xdcc send #1\" --server irc.freenode.org\n\n# To specify different levels of verbosity, pass the `--verbose` or\n# `--quiet` flag\n$ xdcc-dl -v ...\n$ xdcc-dl -q ...As a library:xdcc-dl is built to be used as a library for use in other projects.\nTo make use of the XDCC downloader in your application, you will first need to\ncreate a list ofXDCCPackobjects.This can be done manually using the constructor, the XDCCPack.from_xdcc_message\nclass method or by using anXDCC Search EngineOnce this list of XDCCPacks is created, use thedownload_packsfunction in\nthexdcc module.An example on how to use the library is listed below:fromxdcc_dl.xdccimportdownload_packsfromxdcc_dl.pack_searchimportSearchEnginesfromxdcc_dl.entitiesimportXDCCPack,IrcServer# Generate packsmanual=XDCCPack(IrcServer(\"irc.rizon.net\"),\"bot\",1)from_message=XDCCPack.from_xdcc_message(\"/msg bot xdcc send #2-10\")search_results=SearchEngines.SUBSPLEASE.value.search(\"Test\")combined=[manual]+from_message+search_results# Start downloaddownload_packs(combined)Projects using xdcc-dltoktokkieFurther InformationChangelogLicense (GPLv3)GitlabGithubProgstatsPyPi"} +{"package": "xdcetl", "pacakge-description": "XDC ETLXDC ETL lets you convert blockchain data into convenient formats like CSVs and relational databases.Do you just want to query XDC data right away? Use thepublic dataset in BigQuery.Full documentation available here.QuickstartInstall XDC ETL:pip3installxdc-etlExport blocks and transactions (Schema,Reference):>xdcetlexport_blocks_and_transactions--start-block0--end-block100000\\--blocks-outputblocks.csv--transactions-outputtransactions.csv\\--provider-uriHttps://rpc.XDC.orgExport ERC20 and ERC721 transfers (Schema,Reference):>xdcetlexport_token_transfers--start-block0--end-block500000\\--provider-urifile://$HOME/Library/Ethereum/geth.ipc--outputtoken_transfers.csvExport traces (Schema,Reference):>xdcetlexport_traces--start-block0--end-block500000\\--provider-urifile://$HOME/Library/Ethereum/parity.ipc--outputtraces.csvStream blocks, transactions, logs, token_transfers continually to console (Reference):>pip3installxdc-etl[streaming]>xdcetlstream--start-block500000-eblock,transaction,log,token_transfer--log-filelog.txt\\--provider-uriHttps://rpc.XDC.orgFind other commandshere.For the latest version, check out the repo and call>pip3install-e.>python3xdcetl.pyRunning Tests>pip3install-e.[dev,streaming]>exportETHEREUM_ETL_RUN_SLOW_TESTS=True\n>exportPROVIDER_URL=\n>pytest-vvRunning Tox Tests>pip3installtox\n>toxRunning in DockerInstall Docker:https://docs.docker.com/get-docker/Build a docker image> docker build -t xdc-etl:latest .\n > docker image lsRun a container out of the image> docker run -v $HOME/output:/xdc-etl/output xdc-etl:latest export_all -s 0 -e 5499999 -b 100000 -p Https://rpc.XDC.org\n > docker run -v $HOME/output:/xdc-etl/output xdc-etl:latest export_all -s 2018-01-01 -e 2018-01-01 -p Https://rpc.XDC.orgRun streaming to console or Pub/Sub> docker build -t xdc-etl:latest .\n > echo \"Stream to console\"\n > docker run xdc-etl:latest stream --start-block 500000 --log-file log.txt\n > echo \"Stream to Pub/Sub\"\n > docker run -v /path_to_credentials_file/:/xdc-etl/ --env GOOGLE_APPLICATION_CREDENTIALS=/xdc-etl/credentials_file.json xdc-etl:latest stream --start-block 500000 --output projects//topics/crypto_ethereumIf running on Apple M1 chip add the--platform linux/x86_64option to thebuildandruncommands e.g.:docker build --platform linux/x86_64 -t xdc-etl:latest .\ndocker run --platform linux/x86_64 xdc-etl:latest stream --start-block 500000Projects using Ethereum ETLGoogle- Public BigQuery Ethereum datasetsNansen- Analytics platform for EthereumUseful Links on Orginal ETH ETLSchemaCommand ReferenceDocumentationPublic Datasets in BigQueryExporting the BlockchainQuerying in Amazon AthenaQuerying in Google BigQueryQuerying in KaggleAirflow DAGsPostgres ETLEthereum 2.0 ETL"} +{"package": "xdcget", "pacakge-description": "xdcget: a command line tool to collect webxdc apps from git repositoriesThe main purpose for this tool is to maintain a cache of released webxdc apps\nand to export release files so they can be imported from thexdcstore botwhich in turn can be contacted by Delta Chat users\nin order to be able to search and share webxdc apps in chats.Getting startedInstallxdcgetcommand line tool from a local checkout:pip install -e .Initialize config files:xdcget initEditxdcget.iniand make sure that you set environment variables\ncontaining your credentials for Codeberg/Github API usage.\nSee below for how to get API credentials.Run theupdatecommand to retrieve newest webxdc app releases\nfor repositories listed inxdcget.iniand export them to theexportdirectory:xdcget updateGetting a Codeberg API access tokenLogin with Codeberg and openhttps://codeberg.org/user/settings/applicationsto generate a new token. This token does not need any special \"scopes\"\nit's only used for querying releases of public repositories.\nYou can copy the resulting API token into your clipboard\nand then set it into the environment variables you declared in the config file:# bash example\nexport XDCGET_CODEBERG_USER=\nexport XDCGET_CODEBERG_TOKEN=Getting a Github API access tokenLogin with github and openhttps://github.com/settings/tokensto generate a new token. This token does not need any access\nto your private repos -- it's only used for querying releases\nof public repositories. You may give it 90 days or other expiration\ntimes as you feel fine with.\nYou can copy the resulting API token into your clipboard\nand then set it into the environment variables you declared in the config file:# bash example\nexport XDCGET_GITHUB_USER=\nexport XDCGET_GITHUB_TOKEN=ContributingInstall tox:pip install toxWe useblackto format the code andruffas linter. After modifying the code, run:tox -e lintRun automated tests with:toxIMPORTANT:Pull Requests with new features / bug fixes should come with automated tests.Building and publishing xdcget releasesQuick notes on requirements for testing and releasing:pip install tox build twineto install development dependenciestoxto run testspython -m buildto build the distribution filescreate API-tokens on PyPIto be able to upload to PyPI repositories.Use git to tag a release before uploading (e.g. \"git tag\" and \"git push --tags\")\nThe version of xdcget (also obtained viaxdcget --version) is dynamically\ncomputed usingsetuptools-scmtwine upload dist/*to upload all built distribution files"} +{"package": "xdclient", "pacakge-description": "XDClient is a command line git log collector client for agilean/lean team effectiveness analysis toolX-Developer.Currently it supports both python 2.7.x and 3.5+.Why Should I Use This?The reason to use xdclient is that it provides ability to intergrate team effectiveness analysis with CI(Continuous Intergration Server) via command line.It allows you to pre-install the package and add anexec commandin your pipeline file.FeaturesConfig APPID/KEY and TeamID via parametersGenerates git logSpecify master/dev(default) branchesCommunicates with X-Developer analysis server and response statusSend git log to X-Developer and start analysisInstallationpip install xdclientUsageSpecify theappidappkeyteamidfrom your X-Developer account.python -m xdclient -i {appid} -k {appkey} -t {teamid}Options--version show program's version number and exit\n -h, --help show this help message and exit\n -i APPID, --appid=APPID\n The information of appid in your home page\n -k APPKEY, --appkey=APPKEY\n The information of appkey in your home page\n -t TEAM, --team=TEAM The team id you created\n -p PATTERN, --pattern=PATTERN\n Sensitive words\n -f FORCE, --force=FORCE\n Force Analysis\n -m MASTER, --master=MASTER\n MasterResourcesX-Developer"} +{"package": "xdcs-agent", "pacakge-description": "No description available on PyPI."} +{"package": "xdc-sdk", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xd-cwl-utils", "pacakge-description": "Tools actively under development. Documentation will be updated when ready for outside use!"} +{"package": "xddos", "pacakge-description": "UNKNOWN"} +{"package": "xdeap", "pacakge-description": "xdeapExtensions to DEAP"} +{"package": "xdebug-exploit", "pacakge-description": "No description available on PyPI."} +{"package": "xdebugtoolkit", "pacakge-description": "Installationsudoeasy_installxdebugtoolkit[xdot]orsudopipinstallxdebugtoolkit[xdot]Toolscg2dot- converter fromXdebug cachegrindfiles to thedotformat.cgsplit- splitter for appended cachegrind files. May be useful in\ncase yourxdebug.profiler_appendoption is set to 1.xdot-pygoocanvas- completely rewrittenxdotin order to make\nit utilize PyGooCanvas which gives extra performance on large graphs.\nYou\u2019ll need to install PyGooCanvas in addition toxdot\nrequirements."} +{"package": "xdecoder", "pacakge-description": "No description available on PyPI."} +{"package": "x-decorator", "pacakge-description": "X Decorator is a python package for decorators that used for a variety of purposes, such as logging, memoization, and\nmore.SetupYou can install this package by using the pip tool and installing:$ pip install x-decoratorDocsSee docs:-https://shokr.github.io/x_decorator/."} +{"package": "xdeen", "pacakge-description": "xdeen-core"} +{"package": "x-deep", "pacakge-description": "XdeepXdeep is an open source software library for automated Interpretable Machine Learning. It is developed byDATA Labat Texas A&M University. The ultimate goal of Xdeep is to provide easily accessible interpretation tools to people who want to figure out why the model predicts so. Xdeep provides a variety of methods to interpret a model locally and globally."} +{"package": "xdeepctr", "pacakge-description": "DeepCTRDeepCTR is aEasy-to-use,ModularandExtendiblepackage of deep-learning based CTR models along with lots of\ncore components layers which can be used to easily build custom models.You can use any complex model withmodel.fit()\uff0candmodel.predict().Providetf.keras.Modellike interface forquick experiment.exampleProvidetensorflow estimatorinterface forlarge scale dataanddistributed training.exampleIt is compatible with bothtf 1.xandtf 2.x.Some related projects:DeepMatch:https://github.com/shenweichen/DeepMatchDeepCTR-Torch:https://github.com/shenweichen/DeepCTR-TorchLet'sGet Started!(Chinese\nIntroduction) andwelcome to join us!Models ListModelPaperConvolutional Click Prediction Model[CIKM 2015]A Convolutional Click Prediction ModelFactorization-supported Neural Network[ECIR 2016]Deep Learning over Multi-field Categorical Data: A Case Study on User Response PredictionProduct-based Neural Network[ICDM 2016]Product-based neural networks for user response predictionWide & Deep[DLRS 2016]Wide & Deep Learning for Recommender SystemsDeepFM[IJCAI 2017]DeepFM: A Factorization-Machine based Neural Network for CTR PredictionPiece-wise Linear Model[arxiv 2017]Learning Piece-wise Linear Models from Large Scale Data for Ad Click PredictionDeep & Cross Network[ADKDD 2017]Deep & Cross Network for Ad Click PredictionsAttentional Factorization Machine[IJCAI 2017]Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention NetworksNeural Factorization Machine[SIGIR 2017]Neural Factorization Machines for Sparse Predictive AnalyticsxDeepFM[KDD 2018]xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender SystemsDeep Interest Network[KDD 2018]Deep Interest Network for Click-Through Rate PredictionAutoInt[CIKM 2019]AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural NetworksDeep Interest Evolution Network[AAAI 2019]Deep Interest Evolution Network for Click-Through Rate PredictionFwFM[WWW 2018]Field-weighted Factorization Machines for Click-Through Rate Prediction in Display AdvertisingONN[arxiv 2019]Operation-aware Neural Networks for User Response PredictionFGCNN[WWW 2019]Feature Generation by Convolutional Neural Network for Click-Through Rate PredictionDeep Session Interest Network[IJCAI 2019]Deep Session Interest Network for Click-Through Rate PredictionFiBiNET[RecSys 2019]FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate PredictionFLEN[arxiv 2019]FLEN: Leveraging Field for Scalable CTR PredictionBST[DLP-KDD 2019]Behavior sequence transformer for e-commerce recommendation in AlibabaIFM[IJCAI 2019]An Input-aware Factorization Machine for Sparse PredictionDCN V2[arxiv 2020]DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank SystemsDIFM[IJCAI 2020]A Dual Input-aware Factorization Machine for CTR PredictionFEFM and DeepFEFM[arxiv 2020]Field-Embedded Factorization Machines for Click-through rate predictionSharedBottom[arxiv 2017]An Overview of Multi-Task Learning in Deep Neural NetworksESMM[SIGIR 2018]Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion RateMMOE[KDD 2018]Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-ExpertsPLE[RecSys 2020]Progressive Layered Extraction (PLE): A Novel Multi-Task Learning (MTL) Model for Personalized RecommendationsCitationWeichen Shen. (2017). DeepCTR: Easy-to-use,Modular and Extendible package of deep-learning based CTR\nmodels.https://github.com/shenweichen/deepctr.If you find this code useful in your research, please cite it using the following BibTeX:@misc{shen2017deepctr,author={Weichen Shen},title={DeepCTR: Easy-to-use,Modular and Extendible package of deep-learning based CTR models},year={2017},publisher={GitHub},journal={GitHub Repository},howpublished={\\url{https://github.com/shenweichen/deepctr}},}DisscussionGroupGithub DiscussionsWechat Discussions\u516c\u4f17\u53f7\uff1a\u6d45\u68a6\u5b66\u4e60\u7b14\u8bb0\u5fae\u4fe1\uff1adeepctrbot\u5b66\u4e60\u5c0f\u7ec4\u52a0\u5165\u4e3b\u9898\u96c6\u5408Main contributors(welcome to join us!)\u200b\u200bShen Weichen\u200bAlibaba Group\u200bZan Shuxun\u200bAlibaba Group\u200b\u200b\u200bHarshit PandeAmazon\u200b\u200b\u200bLai MincaiByteDance\u200b\u200b\u200bLi ZichaoByteDance\u200b\u200bTan TingyiChongqing Universityof Posts andTelecommunications\u200b"} +{"package": "xdeeprank", "pacakge-description": "xDeepRank"} +{"package": "xdelta3", "pacakge-description": "Fast delta encoding in python using xdelta3.RequirementsPython 3.5 or 3.6- it\u2019s 2017, you should be using python 3.6 by now anyway.linux- compilation only tested on ubuntu, might work on other platform.Installationpipinstallxdelta3Usageimportxdelta3value_one=b'wonderful string to demonstrate xdelta3, much of these two strings is the same.'value_two=b'different string to demonstrate xdelta3, much of these two strings is the same.'delta=xdelta3.encode(value_one,value_two)# delta is an unreadable byte string: b'\\xd6\\xc3 ... \\x01different\\n\\x13F\\x00'print(f'New string length:{len(value_two)}, delta length:{len(delta)}')value_two_rebuilt=xdelta3.decode(value_one,delta)ifvalue_two_rebuilt==value_two:print('Boo Ya! Delta encoding successful.')(with xdelta3 installed this code should run \u201cas is\u201d, just copy it into ipython or a file and run)How fast?xdelta3-pythonis a thin wrapper aroundxdelta 3.1.1which is a highly optimised c library for delta calculation and compression.\nIt can encode a delta and decode it again for 5 small changes in a 5.5 million character string\n(the complete works of shakespeare) in around 10ms (or 30ms with the highest compression level). Boom.\nSeeperformance.py."} +{"package": "xdelta3-accemate", "pacakge-description": "Fast delta encoding in python using xdelta3.RequirementsPython 3.5 or 3.6- it\u2019s 2017, you should be using python 3.6 by now anyway.linux- compilation only tested on ubuntu, might work on other platform.Installationpipinstallxdelta3Usageimportxdelta3value_one=b'wonderful string to demonstrate xdelta3, much of these two strings is the same.'value_two=b'different string to demonstrate xdelta3, much of these two strings is the same.'delta=xdelta3.encode(value_one,value_two)# delta is an unreadable byte string: b'\\xd6\\xc3 ... \\x01different\\n\\x13F\\x00'print(f'New string length:{len(value_two)}, delta length:{len(delta)}')value_two_rebuilt=xdelta3.decode(value_one,delta)ifvalue_two_rebuilt==value_two:print('Boo Ya! Delta encoding successful.')(with xdelta3 installed this code should run \u201cas is\u201d, just copy it into ipython or a file and run)How fast?xdelta3-pythonis a thin wrapper aroundxdelta 3.1.1which is a highly optimised c library for delta calculation and compression.\nIt can encode a delta and decode it again for 5 small changes in a 5.5 million character string\n(the complete works of shakespeare) in around 10ms (or 30ms with the highest compression level). Boom.\nSeeperformance.py."} +{"package": "xdem", "pacakge-description": "xDEM: robust analysis of DEMs in Python.xDEMis an open source project to develop a core Python package for the analysis of digital elevation models (DEMs).It aims atproviding modular and robust tools for the most common analyses needed with DEMs, including both geospatial\noperations specific to DEMs and a wide range of 3D alignment and correction methods from published, peer-reviewed studies.\nThe core manipulation of DEMs (e.g., vertical alignment, terrain analysis) areconveniently centered aroundDEManddDEMclasses(that, notably, re-implements all tools\nofgdalDEM). More complex pipelines (e.g., 3D rigid coregistration, bias corrections, filtering) arebuilt around\nmodularCoreg,BiasCorrandFilterclasses that easily interface between themselves. Finally, xDEM includes advanced\nuncertainty analysis tools based on spatial statistics ofSciKit-GStat.Additionally, xDEM inherits many convenient functionalities fromGeoUtilssuch asimplicit loading,numerical interfacingandconvenient object-based geospatial methodsto easily perform\nthe most common higher-level tasks needed by geospatial users (e.g., reprojection, cropping, vector masking). ThroughGeoUtils, xDEM\nrelies onRasterio,GeoPandasandPyprojfor georeferenced calculations, and onNumPyandXarrayfor numerical analysis. It allows easy access to\nthe functionalities of these packages through interfacing or composition, and quick inter-operability through object conversion.If you are looking for an accessible Python package to write the Python equivalent of yourGDALcommand lines, or of yourQGISanalysis pipelinewithout a steep learning curveon Python GIS syntax, xDEM is perfect for you! For more advanced\nusers, xDEM also aims at being efficient and scalable by supporting lazy loading and parallel computing (ongoing).DocumentationFor a quick start, full feature description or search through the API, see xDEM's documentation at:https://xdem.readthedocs.io.Installationmambainstall-cconda-forgexdemSeemamba's documentationto installmamba, which will solve your environment much faster thanconda.Citing methods implemented in the packageWhen using a method implemented in xDEM, pleasecite both the package and the related study:Citing xDEM:Citing the related study:Coregistration:Horizontal shift from aspect/slope relationship ofNuth and K\u00e4\u00e4b (2011),Iterative closest point (ICP) ofBesl and McKay (1992),Bias correction:Along-track multi-sinusoidal noise by basin-hopping ofGirod et al. (2017),Uncertainty analysis:Heteroscedasticity and multi-range correlations from stable terrain ofHugonnet et al. (2022),Terrain attributes:Slope, aspect and hillshade of eitherHorn (1981)orZevenbergen and Thorne (1987),Profile, plan and maximum curvature ofZevenbergen and Thorne (1987),Topographic position index ofWeiss (2001),Terrain ruggedness index of eitherRiley et al. (1999)orWilson et al. (2007),Roughness ofDartnell (2000),Rugosity ofJenness (2004),Fractal roughness ofTaud et Parrot (2005).ContributingWe welcome new contributions, and will happily help you integrate your own DEM routines into xDEM!After discussing a new feature or bug fix in an issue, you can open a PR to xDEM with the following steps:Fork the repository, make a feature branch and push changes.When ready, submit a pull request from the feature branch of your fork toGlacioHack/xdem:main.The PR will be reviewed by at least one maintainer, discussed, then merged.More details onour contributing page."} +{"package": "xdeps", "pacakge-description": "Data dependency managerThis package is part of the Xsuite collection."} +{"package": "xdepy", "pacakge-description": "No description available on PyPI."} +{"package": "xdesign", "pacakge-description": "XDesign is an open-source Python package for generating configurable\nx-ray imaging phantoms, simulating data acquisition, and benchmarking x-ray\ntomographic image reconstruction."} +{"package": "xdetection", "pacakge-description": "No description available on PyPI."} +{"package": "xdev", "pacakge-description": "Xdev - Excellent DeveloperRead the docshttps://xdev.readthedocs.ioGithubhttps://github.com/Erotemic/xdevPypihttps://pypi.org/project/xdevXdev is an excellent developer tool for excellent developers.\nIt contains miscellaneous and/or interactive debugging tools.This started as a project for myself to contain development related tools that\nI wouldn\u2019t want to ship with a package itself (where asubeltcontains the tools used in programs\nthemselves). I\u2019ve polished it up over the years, and it\u2019s become a reasonably\nuseful package with tools I could see others making use of.This is the CLI:usage: xdev [-h] [--version] {info,codeblock,sed,find,tree,pint,pyfile,pyversion,editfile,format_quotes,freshpyenv,docstubs,available_package_versions,dirstats} ...\n\nThe XDEV CLI\n\nA collection of excellent developer tools for excellent developers.\n\noptions:\n -h, --help show this help message and exit\n --version show version number and exit (default: False)\n\ncommands:\n {info,codeblock,sed,find,tree,pint,pyfile,pyversion,editfile,format_quotes,freshpyenv,docstubs,available_package_versions,dirstats}\n specify a command to run\n info Info about xdev\n codeblock Remove indentation from text.\n sed Search and replace text in files\n find Find matching files or paths in a directory.\n tree List a directory like a tree\n pint (convert_unit)\n Converts one type of unit to another via the pint library.\n pyfile (modpath) Prints the path corresponding to a Python module.\n pyversion (modversion)\n Detect and print the version of a Python module or package.\n editfile (edit) Opens a file in your visual editor determined by the ``VISUAL``\n format_quotes Use single quotes for code and double quotes for docs.\n freshpyenv Create a fresh environment in a docker container to test a Python package.\n docstubs (doctypes)\n Generate Typed Stubs from Docstrings (experimental)\n available_package_versions (availpkg)\n Print a table of available versions of a python package on Pypi\n dirstats Analysis for code in a repositoryThis is the top level API:fromxdevimportalgofromxdevimportautojitfromxdevimportclass_reloaderfromxdevimportclifromxdevimportdesktop_interactionfromxdevimportembedingfromxdevimportformat_quotesfromxdevimportinteractive_iterfromxdevimportintrospectfromxdevimportmiscfromxdevimportpatternsfromxdevimportprofilerfromxdevimportregex_builderfromxdevimportsearch_replacefromxdevimporttracebacksfromxdevimportutilfromxdevimportutil_networkxfromxdevimportutil_pathfromxdev.algoimport(edit_distance,knapsack,knapsack_greedy,knapsack_ilp,knapsack_iterative,knapsack_iterative_int,knapsack_iterative_numpy,number_of_decimals,)fromxdev.autojitimport(import_module_from_pyx,)fromxdev.class_reloaderimport(reload_class,)fromxdev.desktop_interactionimport(editfile,startfile,view_directory,)fromxdev.embedingimport(EmbedOnException,embed,embed_if_requested,embed_on_exception,embed_on_exception_context,fix_embed_globals,)fromxdev.format_quotesimport(DOUBLE_QUOTE,SINGLE_QUOTE,TRIPLE_DOUBLE_QUOTE,TRIPLE_SINGLE_QUOTE,format_quotes,format_quotes_in_file,format_quotes_in_text,)fromxdev.interactive_iterimport(InteractiveIter,)fromxdev.introspectimport(distext,get_func_kwargs,get_stack_frame,iter_object_tree,test_object_pickleability,)fromxdev.miscimport(byte_str,difftext,nested_type,quantum_random,set_overlaps,textfind,tree_repr,)fromxdev.patternsimport(MultiPattern,Pattern,PatternBase,RE_Pattern,our_extended_regex_compile,)fromxdev.profilerimport(IS_PROFILING,profile,profile_globals,profile_now,)fromxdev.regex_builderimport(PythonRegexBuilder,RegexBuilder,VimRegexBuilder,)fromxdev.search_replaceimport(GrepResult,find,grep,grepfile,greptext,sed,sedfile,)fromxdev.tracebacksimport(make_warnings_print_tracebacks,)fromxdev.utilimport(bubbletext,conj_phrase,take_column,)fromxdev.util_networkximport(AsciiDirectedGlyphs,AsciiUndirectedGlyphs,UtfDirectedGlyphs,UtfUndirectedGlyphs,generate_network_text,graph_str,write_network_text,)fromxdev.util_pathimport(ChDir,sidecar_glob,tree,)RemarksPerhaps I should just useipdbbut I often just like to directly embed with\nIPython whenever I want:importxdevxdev.embed()Or wherever I want whenever there is an exception.importxdevwithxdev.embed_on_exception:some_code()I don\u2019t feel like I needipdb\u2019s other features.I also like todeffunc(a=1,b=2,c=3):\"\"\"\n Example:\n >>> from this.module import * # import contextual namespace\n >>> import xinspect\n >>> globals().update(xinspect.get_func_kwargs(func)) # populates globals with default kwarg value\n >>> print(a + b + c)\n 6\n \"\"\"But I know these things are a little dirty.But these aren\u2019t production practices. These are development tricks and life\nhacks to make working faster.Also seexinspectfor things likeautogen_imports>>>importubeltasub>>>source=ub.codeblock(>>>'''\n>>> p = os.path.dirname(join('a', 'b'))\n>>> glob.glob(p)\n>>> ''')>>># Generate a list of lines to fix the name errors>>>lines=autogen_imports(source=source)>>>print(lines)['import glob','from os.path import join','import os']The CLIThe xdev CLI is getting kinda nice, although it is a bit of a hodgepodge of\nfunctionality (much like this library).pip install xdev\nxdev --helpIt contains functionality that I generally use when developing on my setup, but\nI often find lacking in the setup of others.For instance thetreeUNIX\ncommand is amazing, but not everyone has it installed, and getting it viaaptrequires sudo privileges. Meanwhile xdev can be installed in user space\nvia pip, so this provides me with an easy way to gettreeon someone\u2019s\nsystem while helping them debug.Other examples aresed,find,pyfile, andpyversion. Look at\nthe--helpfor more info on them.Thedirstatsfunction is like a buffed uptree. In addition to printing\nthe directory tree structure it inspects the contents of the tree and\nsummarizes things like: number of lines per type of file. For Python files it\nbreaks up the analysis into code-lines and docstring lines to give a better\nsense of project complexity.For repo maintence I use this package in conjunction withxcookie. I use xcookie to generate the package\nstructure and then xdev helps fill in the details. Specifically theavailpkganddocstubscommands.Theavailpkgcommand has been indispensable for me when writing\nrequirements.txt files. If you need to find good versions of a package \u2014\nespecially a binary one, e.g. numpy \u2014 for different versions of Python and\nwould like the appropirate requirements.txt syntax to be generated for you,\ntake a look atavailpkg. It also provides an overview of what versions of a\npackage are available for what operating systems / CPU architectures.Thedocstubscommand is designed to turn google-style docstrings into\nproper type annotation stubs. It \u201cworks on my machine\u201d and currently requires\na custom monkey patched mypy. See the code for details, it is possible to use,\nbut it is still very raw. I do think it can evolve into a tool."} +{"package": "xdevice", "pacakge-description": "No description available on PyPI."} +{"package": "xdevs", "pacakge-description": "No description available on PyPI."} +{"package": "xdf4mne", "pacakge-description": "No description available on PyPI."} +{"package": "xdg", "pacakge-description": "xdgxdghas been renamed toxdg-base-dirsdue to an import collision withPyXDG. Therefore thexdgpackage is deprecated. Installxdg-base-dirsinstead."} +{"package": "xdgappdirs", "pacakge-description": "This is a fork and almost drop-in replacement ofappdirsthat follows the XDG BaseDir Spec on macOS\nwhen the relevantXDG_*environment variables are available. For instance,\non macOS, whenXDG_CONFIG_HOMEis set to/Users/steve/.config,user_config_dir('foo')evaluates to/Users/steve/.config/foo, whereas\nwhenXDG_CONFIG_HOMEis not set or empty, it evaluates to/Users/steve/Library/Application Support/foo. This gives XDG fans a choice\nwhile not mandating.configfor everyone else, especially for GUI apps.Other changes:RevertsActiveState/appdirs#100. On macOS,user_config_dirandsite_config_direvaluates to subdirs of~/Library/Application Supportand/Library/Application Support(unless\nthe relevantXDG_*env vars are set and non-empty), rather than subdirs of~/Library/Preferencesand/Library/Preferences, which are specifically\nfor plists and not suitable for anything else. You don\u2019t needappdirsto\ntell you where to write plists.Properly handle emptyXDG_*env vars. According to XDG BaseDir Spec,\ndefaults should be used when the env vars are empty.Support for returningpathlib.Path([contributed](https://github.com/zmwangx/xdgappdirs/pull/1) by @pmav99).The original README forappdirsfollows.the problemWhat directory should your app use for storing user data? If running on macOS, you\nshould use:~/Library/Application Support/If on Windows (at least English Win XP) that should be:C:\\Documents and Settings\\\\Application Data\\Local Settings\\\\or possibly:C:\\Documents and Settings\\\\Application Data\\\\forroaming profilesbut that is another story.On Linux (and other Unices) the dir, according to theXDG\nspec, is:~/.local/share/appdirsto the rescueThis kind of thing is what theappdirsmodule is for.appdirswill\nhelp you choose an appropriate:user data dir (user_data_dir)user config dir (user_config_dir)user cache dir (user_cache_dir)site data dir (site_data_dir)site config dir (site_config_dir)user log dir (user_log_dir)and also:is a single module so other Python packages can include their own private copyis slightly opinionated on the directory names used. Look for \u201cOPINION\u201d in\ndocumentation and code for when an opinion is being applied.some example outputOn macOS:>>> from appdirs import *\n>>> appname = \"SuperApp\"\n>>> appauthor = \"Acme\"\n>>> user_data_dir(appname, appauthor)\n'/Users/trentm/Library/Application Support/SuperApp'\n>>> site_data_dir(appname, appauthor)\n'/Library/Application Support/SuperApp'\n>>> user_cache_dir(appname, appauthor)\n'/Users/trentm/Library/Caches/SuperApp'\n>>> user_log_dir(appname, appauthor)\n'/Users/trentm/Library/Logs/SuperApp'On Windows 7:>>> from appdirs import *\n>>> appname = \"SuperApp\"\n>>> appauthor = \"Acme\"\n>>> user_data_dir(appname, appauthor)\n'C:\\\\Users\\\\trentm\\\\AppData\\\\Local\\\\Acme\\\\SuperApp'\n>>> user_data_dir(appname, appauthor, roaming=True)\n'C:\\\\Users\\\\trentm\\\\AppData\\\\Roaming\\\\Acme\\\\SuperApp'\n>>> user_cache_dir(appname, appauthor)\n'C:\\\\Users\\\\trentm\\\\AppData\\\\Local\\\\Acme\\\\SuperApp\\\\Cache'\n>>> user_log_dir(appname, appauthor)\n'C:\\\\Users\\\\trentm\\\\AppData\\\\Local\\\\Acme\\\\SuperApp\\\\Logs'On Linux:>>> from appdirs import *\n>>> appname = \"SuperApp\"\n>>> appauthor = \"Acme\"\n>>> user_data_dir(appname, appauthor)\n'/home/trentm/.local/share/SuperApp\n>>> site_data_dir(appname, appauthor)\n'/usr/local/share/SuperApp'\n>>> site_data_dir(appname, appauthor, multipath=True)\n'/usr/local/share/SuperApp:/usr/share/SuperApp'\n>>> user_cache_dir(appname, appauthor)\n'/home/trentm/.cache/SuperApp'\n>>> user_log_dir(appname, appauthor)\n'/home/trentm/.cache/SuperApp/log'\n>>> user_config_dir(appname)\n'/home/trentm/.config/SuperApp'\n>>> site_config_dir(appname)\n'/etc/xdg/SuperApp'\n>>> os.environ['XDG_CONFIG_DIRS'] = '/etc:/usr/local/etc'\n>>> site_config_dir(appname, multipath=True)\n'/etc/SuperApp:/usr/local/etc/SuperApp'AppDirsfor convenience>>> from appdirs import AppDirs\n>>> dirs = AppDirs(\"SuperApp\", \"Acme\")\n>>> dirs.user_data_dir\n'/Users/trentm/Library/Application Support/SuperApp'\n>>> dirs.site_data_dir\n'/Library/Application Support/SuperApp'\n>>> dirs.user_cache_dir\n'/Users/trentm/Library/Caches/SuperApp'\n>>> dirs.user_log_dir\n'/Users/trentm/Library/Logs/SuperApp'Per-version isolationIf you have multiple versions of your app in use that you want to be\nable to run side-by-side, then you may want version-isolation for these\ndirs:>>> from appdirs import AppDirs\n>>> dirs = AppDirs(\"SuperApp\", \"Acme\", version=\"1.0\")\n>>> dirs.user_data_dir\n'/Users/trentm/Library/Application Support/SuperApp/1.0'\n>>> dirs.site_data_dir\n'/Library/Application Support/SuperApp/1.0'\n>>> dirs.user_cache_dir\n'/Users/trentm/Library/Caches/SuperApp/1.0'\n>>> dirs.user_log_dir\n'/Users/trentm/Library/Logs/SuperApp/1.0'appdirs Changelogxdgappdirs 1.4.5Add support for returningpathlib.Path(#1).xdgappdirs 1.4.4.3Rename module toxdgappdirsto allow coexistence withappdirs.xdgappdirs 1.4.4Deviate from appdirs (see top of README)[PR #92] Don\u2019t import appdirs from setup.py which resolves issue #91Add Python 3.7 supportRemove support for end-of-life Pythons 2.6, 3.2, and 3.3Project officially classified as Stable which is important\nfor inclusion in other distros such as ActivePython.appdirs 1.4.3[PR #76] Python 3.6 invalid escape sequence deprecation fixesFix for Python 3.6 supportappdirs 1.4.2[PR #84] Allow installing without setuptools[PR #86] Fix string delimiters in setup.py descriptionAdd Python 3.6 supportappdirs 1.4.1[issue #38] Fix _winreg import on Windows Py3[issue #55] Make appname optionalappdirs 1.4.0[PR #42] AppAuthor is now optional on Windows[issue 41] Support Jython on Windows, Mac, and Unix-like platforms. Windows\nsupport requiresJNA.[PR #44] Fix incorrect behaviour of the site_config_dir methodappdirs 1.3.0[Unix, issue 16] Conform to XDG standard, instead of breaking it for\neverybody[Unix] Removes gratuitous case mangling of the case, since *nix-es are\nusually case sensitive, so mangling is not wise[Unix] Fixes the utterly wrong behaviour insite_data_dir, return result\nbased on XDG_DATA_DIRS and make room for respecting the standard which\nspecifies XDG_DATA_DIRS is a multiple-value variable[Issue 6] Add*_config_dirwhich are distinct on nix-es, according to\nXDG specs; on Windows and Mac return the corresponding*_data_dirappdirs 1.2.0[Unix] Putuser_log_dirunder thecachedir on Unix. Seems to be more\ntypical.[issue 9] Makeunicodework on py3k.appdirs 1.1.0[issue 4] AddAppDirs.user_log_dir.[Unix, issue 2, issue 7] appdirs now conforms toXDG base directory spec.[Mac, issue 5] Fixsite_data_dir()on Mac.[Mac] Drop use of \u2018Carbon\u2019 module in favour of hardcoded paths; supports\nPython3 now.[Windows] Append \u201cCache\u201d touser_cache_diron Windows by default. Useopinion=Falseoption to disable this.Addappdirs.AppDirsconvenience class. Usage:>>> dirs = AppDirs(\"SuperApp\", \"Acme\", version=\"1.0\")\n>>> dirs.user_data_dir\n'/Users/trentm/Library/Application Support/SuperApp/1.0'[Windows] Cherry-pick Komodo\u2019s change to downgrade paths to the Windows short\npaths if there are high bit chars.[Linux] Change defaultuser_cache_dir()on Linux to be singular, e.g.\n\u201c~/.superapp/cache\u201d.[Windows] Addroamingoption touser_data_dir()(for use on Windows only)\nand change the defaultuser_data_dirbehaviour to use anon-roaming\nprofile dir (CSIDL_LOCAL_APPDATAinstead ofCSIDL_APPDATA). Why? Because\na large roaming profile can cause login speed issues. The \u201conly syncs on\nlogout\u201d behaviour can cause surprises in appdata info.appdirs 1.0.1 (never released)Started this changelog 27 July 2010. Before that this module originated in theKomodoproduct asapplib.pyand then\nasapplib/location.py(used byPyPMinActivePython). This is basically a fork of\napplib.py 1.0.1 and applib/location.py 1.0.1."} +{"package": "xdg-base-dirs", "pacakge-description": "xdg-base-dirsxdg-base-dirsis a Python module that provides functions to return paths to\nthe directories defined by theXDG Base Directory Specification, to save\nyou from duplicating the same snippet of logic in every Python utility you write\nthat deals with user cache, configuration, or data files. It has no external\ndependencies.:warning:xdg-base-dirswas previously namedxdg, and was renamed due to an\nimport collision withPyXDG. If you usedxdgprior to the rename, update by changing the dependency name fromxdgtoxdg-base-dirsand the import fromxdgtoxdg_base_dirs.InstallationTo install the latest release fromPyPI, usepip:python3-mpipinstallxdg-base-dirsThe latest release ofxdg-base-dirscurrently implements version 0.8 of the\nspecification, released on 8th May 2021.In Python projects usingPoetryorPDMfor dependency management, addxdg-base-dirsas a dependency withpoetry add xdg-base-dirsorpdm add xdg-base-dirs. Alternatively, sincexdg-base-dirsis only a single\nfile you may prefer to just copysrc/xdg_base_dirs/__init__.pyfrom the source\ndistribution into your project.Usagefromxdg_base_dirsimport(xdg_cache_home,xdg_config_dirs,xdg_config_home,xdg_data_dirs,xdg_data_home,xdg_runtime_dir,xdg_state_home,)xdg_cache_home(),xdg_config_home(),xdg_data_home(), andxdg_state_home()returnpathlib.Pathobjectscontaining the value of\nthe environment variable namedXDG_CACHE_HOME,XDG_CONFIG_HOME,XDG_DATA_HOME, andXDG_STATE_HOMErespectively, or the default defined in\nthe specification if the environment variable is unset, empty, or contains a\nrelative path rather than absolute path.xdg_config_dirs()andxdg_data_dirs()return a list ofpathlib.Pathobjects containing the value, split on colons, of the environment variable namedXDG_CONFIG_DIRSandXDG_DATA_DIRSrespectively, or the default defined in\nthe specification if the environment variable is unset or empty. Relative paths\nare ignored, as per the specification.xdg_runtime_dir()returns apathlib.Pathobject containing the value of theXDG_RUNTIME_DIRenvironment variable, orNoneif the environment variable is\nnot set, or contains a relative path rather than an absolute path.CopyrightCopyright \u00a9Scott Stevenson.xdg-base-dirsis distributed under the terms of theISC license."} +{"package": "xdg-binary-cache", "pacakge-description": "xdg-binary-cacheThis is a simple library that is used to download a pre-compiled binary\ninto the$XDG_CACHEdirectory. The library is meant to be used bypre-commithooks that I've authored.HackingYou'll want to install the developer dependencies:pip install -e .[develop]This will includenose2which is the test runner of choice. After you make modifications you can run tests withnose2When you're satisfied you'll want to update the version number and do build-and-upload:python setup.py sdist bdist_wheel\ntwine upload dist/* --verbose"} +{"package": "xdg-cache", "pacakge-description": "Installation$[sudo]pipinstallxdg-cacheExamples>>>importxdg_cache>>>xdg_cache.write(\"key\",'value')>>>xdg_cache.read(\"key\")'value'>>>xdg_cache.path(\"key\")'~/.cache/key'>>>xdg_cache.exists(\"key\")True>>>xdg_cache.rm(\"key\")readme42.com"} +{"package": "x-dgcnn", "pacakge-description": "No description available on PyPI."} +{"package": "xdgconfig", "pacakge-description": "XDGConfigEasy access to~/.config.InstallationUsing pipSimply runpip3 install --upgrade xdgconfig.By default,xdgconfigonly supports JSON as its serializer, but you can install support for\nother serializers by specifiying the format in square brackets, i.e.pip3 install xdgconfig[xml].\nThe following are available:jsonc: JSON, with commentsini: INI filesxml: eXtensible Markup Language filestoml: Tom's Markup language filesyaml: YAML Ain't Markup Language filesFurthermore there is anallrecipe to install support for every markup supported,\nand you can combine them by using a+between 2 targets, i.e.pip3 install xdgconfig[xml+toml]From sourceSimply clone this repo and runpython3 setup.py install.FeaturesConfigobjects use a shared single reference.Serializing to many common formats, including JSON, XML, TOML, YAML, and INIdict-like interfaceAutosaving on mutation of theConfigobject.Smart config loading, especially on Unix-based platformslooks in/etc/prog/config, then in~/.config/prog/configSupports setting a config file path in an environment variable namedPROG_CONFIG_PATHAccessing the config using dot notation (config.keyfor instance). See limitations for guidance.UsagefromxdgconfigimportJsonConfig# Instanciate the JsonConfig object# If you'd rather use a different format, there also are config classes# for TOML, YAML, INI (configparser), and XML.# This will save your configuration under `~/.config/PROG/configconfig=JsonConfig('PROG',autosave=True)config['foo']='bar'# Save a value to the config# Access the value later onprint(config['foo'])# It behaves like a collections.defaultdict as wellconfig['oof']['bar']='baz'# Prints {'oof': {'bar': 'baz'}, 'foo': 'bar'}print(config)Adding onto the libraryCustom serializersYou can add custom serializers support by using a Mixin class, as well as\na serializer class which must have adumpsand aloadsmethod, which will\nbe used to store and load data from the config file. The data is always\nrepresented as a pythondictobject, but you can serialize any data you want\ninside of it.Look at the following example for an implementation guide.fromtypingimportAny,DictfromxdgconfigimportConfigclassMySerializer:defdumps(data:Dict[str,Any])->str:return'\\n'.join(f'{k}:{v}'fork,vindata.items())defloads(contents:str)->Dict[str,Any]:returndict(s.split(':')forsincontents.split('\\n'))classMySerializerMixin:_SERIALIZER=MySerializerclassMyConfig(MySerializerMixin,Config):...Setting default valuesYou can set default values by creating aMixinclass with a_DEFAULTSclass attribute, such as :frompathlibimportPathfrompprintimportpprintfromxdgconfigimportJsonConfigclassDefaultConfig:_DEFAULTS={'logger.level':'info','logger.verbosity':3,'app.path':str(Path.cwd()),'app.credentials.username':'user','app.credentials.password':'password',}classConfig(DefaultConfig,JsonConfig):...config=Config('PROG','config.json')pprint(config)# Prints the following dict :# {# 'logger': {# 'level': 'info',# 'verbosity': 3# },# 'app': {# 'path': '$CWD',# 'credentials': {# 'username': 'user',# 'password': 'password'# }# }# }Known limitationsUsing anIniConfigobject prevents you from using periods (.) in key names, as they are separators for subdicts.Methods and attributes of theConfigobject all start with a leading underscore (_), hence, using key names with the same convention is discouraged, as it could break the object due to the way dot (.) accessing works. The only exception is thesavemethod, which doesn't start with a leading underscore.There can only be one document per config file, and a config file is a dictionary.Depending on the serializer used, some data types may or may not be available. You can circumvent that by using custom serializers.Configuration files with comments will have their comments dropped when the configuration is saved."} +{"package": "xdgenvpy", "pacakge-description": "xdgenvpyxdgenvpyis yet another Python utility for theXDG Base Directory Specification,\nbut one that provides Pythonic access as well as a CLI utility.xdgenvpyadheres to the XDG Base Directory spec on Unix systems, and also provides\nsimilar for Windows-based systems.How to usePythonThere are three main ways to use xdgenvpy as a Python package,Retrieve XDG environment variables, or the specification defaults.Determinepackagespecific directories based on the XDG spec.Or pedantically createpackagespecific directories before attempting to\nuse the directory.To use xdgenvpy as a simple XDG base directory getter, simply create a newxdgenvpy.XDGobject and use the properties it exposes.fromxdgenvpyimportXDGxdg=XDG()print(xdg.XDG_DATA_HOME)# /home/user/.local/shareprint(xdg.XDG_CONFIG_HOME)# /home/user/.configprint(xdg.XDG_CACHE_HOME)# /home/user/.cacheprint(xdg.XDG_RUNTIME_DIR)# /run/user/1000print(xdg.XDG_DATA_DIRS)# /home/user/.local/share:/usr/local/share/:/usr/share/print(xdg.XDG_CONFIG_DIRS)# /home/user/.config:/etc/xdgBut sometimes you want to use package specific directories derived from the XDG\nbase directories. This can be done with thexdgenvpy.XDGPackageclass.fromxdgenvpyimportXDGPackagexdg=XDGPackage('mypackage')print(xdg.XDG_DATA_HOME)# /home/user/.local/share/mypackageprint(xdg.XDG_CONFIG_HOME)# /home/user/.config/mypackageprint(xdg.XDG_CACHE_HOME)# /home/user/.cache/mypackageprint(xdg.XDG_RUNTIME_DIR)# /run/user/1000/mypackageprint(xdg.XDG_DATA_DIRS)# /home/user/.local/share/mypackage:/usr/local/share/:/usr/share/print(xdg.XDG_CONFIG_DIRS)# /home/user/.config/mypackage:/etc/xdg')Lastly, you could also usexdgenvpy.XDGPedanticPackageto ensure each of the\npackage specific directories exist before the calling code attempts to use the\ndirectory. Instances of thexdgenvpy.XDGPedanticPackageclass will not create\nsystem level directories, only package directories on the DATA, CONFIG, CACHE,\nand RUNTIME variables.fromxdgenvpyimportXDGPedanticPackagexdg=XDGPedanticPackage('mypackage')print(xdg.XDG_DATA_HOME)# /home/user/.local/share/mypackageprint(xdg.XDG_CONFIG_HOME)# /home/user/.config/mypackageprint(xdg.XDG_CACHE_HOME)# /home/user/.cache/mypackageprint(xdg.XDG_RUNTIME_DIR)# /run/user/1000/mypackageprint(xdg.XDG_DATA_DIRS)# /home/user/.local/share/mypackage:/usr/local/share/:/usr/share/print(xdg.XDG_CONFIG_DIRS)# /home/user/.config/mypackage:/etc/xdgCLIxdgenvpy also includes a runnable module, which is easily accessible via the\nscriptxdg-env. Pip will normally install scripts under something like:~/.local/binThe installedxdg-envcommand essentially takes a list of XDG variables, and\nan optional package name. For each XDG variable specified,xdg-envwill\nprint its corresponding value based on the specification. It can optionally\ntake the name of a package and include that into the variable's values.But can't we justechothe XDG variables like so?echo${XDG_DATA_HOME}echo${XDG_CONFIG_HOME}echo${XDG_CACHE_HOME}echo${XDG_RUNTIME_DIR}echo${XDG_DATA_DIRS}echo${XDG_CONFIG_DIRS}Well, yes. But there is a problem when the variables are not defined. Thexdg-envcommand willalwaysprint a value that adheres to the spec. If the\nenvironment variable does not exist, then the default value will be returned, as\ndefined by theXDG Base Directory Specification.Although the Python package supports apedanticmode, thexdg-envcommand\nwill not change the file system. Even if a package name is supplied and the\ndirectories do not exist,xdg-envwill not create any files/directories. This\nwas simply a design decision to keep the shell command as file-system safe as\npossible.How to installInstall locally as a normal user:pip3install--userxdgenvpyOr install globally as the all powerful root:sudopip3installxdgenvpyA Word About WindowsTheXDG Base Directory Specification.\ndoes not mention how the spec should be implemented on Windows-based platforms.\nThat said, many applications on Windows still follow a very similar convention\nto the XDG base directory spec. And that is to generally place config files\nunder%APPDATA%/MyPackage/configs.If we squint, it kind of looks like we can simply replace the POSIX tilde~with the Windows%APPDATA%variable. Then there's a directory that is the\napplication's name. And finally, any configs or data files the application\nneeds to save is under that directory.Generally, xdgenvpy works in this way on Windows-based platforms. Though this\nis not a perfect solution as Windows applications can put configs and data files\nunder any of the directoriesLocal,LocalLow, andRoaming(where theRoamingdirectory typically is pointed to by%APPDATA%). Additionally, some\nXDG variables do not make much sense on Windows-based platforms.XDG_RUNTIME_DIRis one such example. On Unix systems it defaults to/run/user/USERID. There is no close equivalent to a Windows-based directory.\nAs such, xdgenvpy does not do anything fancy other than prepend%APPDATA%to\nmost directories and drop any.prefixes for hidden directories/files.That said, if you use xdgenvpy extensively on Windows platforms and would like\nbetter support, create GitLab issues on the project or submit Merge Requests.\nLet's all make xdgenvpy as useful as possible, even if it needs to implement XDG\nbase directory spec-like features on non-Unix platforms."} +{"package": "xdggs", "pacakge-description": "No description available on PyPI."} +{"package": "xdgmenu", "pacakge-description": "A ncurses application menu.The missing stone of my i3 setup.DescriptionA simple and lightweight alternative to Desktop Environment\u2019s\napplication menu. To be used when you do not remember the name of this\nnew pdf reader you just installed yesterday night\u2026Dependencies:PyXdg: python\u2019s freedesktop bindings, used in order to generate\nthe menu.Urwid: a framework build on top of ncurses.Keybindings (case insensitive):j,k,l,m or arrow: Navigate between menu entries.c: Cycle through submenu.e: on an application entry, launch it without exiting.b: on a submenu to go back to the parent menu.InstallationPip:pip install xdgmenusetuptools:python setup.py installConfigurationSince i am using i3, a quick how-to integrate it in nicely. Add to your.i3/config:set $term \n\nbindsym $term -e 'xgmenu' --title xdgmenu\nfor window [title=\"xdgmenu\"] floating enableRoadmapImplement entry description on \u2018d\u2019 keypress (a simple text widget\ndisplaying the programm help).Implement a search mode.Find how to correctly handle logging with urwid application.Separate the urwid logic from the application one.Package and upload to pypi.TestsNo test yet but contribution are welcomed ;)"} +{"package": "xdgpspconf", "pacakge-description": "XDGPlatformSuitedProjectCONFigurationGistSource Code RepositoryRepositoryDocumentationBadgesDescriptionHandle platform suited xdg-base toRead configuration from standard locations.supported formats:yamljsontomlconf (ini)Write configuration to most general, writable xdg-locationLocate standard directories:xdg_cachexdg_configxdg_dataxdg_stateXDG SpecificationView xdg specificationshere.What does it doReads standard Windows/POSIX locations, current folder and optionally all ancestors and custom locations for xdg-configurationPlatform-specific locations:Windows Locations: Environment Variable%LOCALAPPDATA%\\or%USERPROFILE%\\AppData\\Local\\POSIX [Linux/MacOS] Locations: Environment Variable$XDG_CONFIG_HOME/or$HOME/.config/Environment-declared variable:%RC%for Windows or$for POSIXCustom configuration path: supplied in functionRelative path:$PWD/.rcAncestors: Any of the parents, till project root or mountpoint, that contains__init__.py, where,project root is the directory that containssetup.cfgorsetup.pymountpoint is checked usingpathlib.Path.driveon windows orpathlib.Path.is_mount()on POSIXLists possible xdg-locations (existing and prospective)XDG_CACHE_HOMEis supported for cache locationsXDG_CONFIG_HOME,XDG_CONFIG_DIRSare supported for configuration locationsXDG_DATA_HOME,XDG_DATA_DIRSare supported for data locationsXDG_STATE_HOME,XDG_STATE_DIRSare supported for state locationsTODOImplementation for following variables:XDG_RUNTIME_DIROtherXDG specifications.Arbitrarily definedXDG_.*environment variables"} +{"package": "xdgspec", "pacakge-description": "xdgspec Python packagexdgspecis a simple Python package to provideconvenientaccess to the\nvariables defined in theXDG Base Directory\nSpecification.What canxdgspecdo?Withxdgspecyou can:Access theXDG Base Directory variableswith Appropriate FallbacksfromxdgspecimportXDGDirectoryprint(XDGDirectory(\"XDG_CONFIG_HOME\").path)print(XDGDirectory(\"XDG_CACHE_HOME\").path)print(XDGDirectory(\"XDG_DATA_HOME\").path)# ...Use a Context Manager to Automatically Create One of theXDG Base Directoriesif it doesn't existfromxdgspecimportXDGDirectorywithXDGDirectory(\"XDG_CONFIG_HOME\")aspath:print(\"{}is now definitely existing\".format(path))Access and Create Package DirectoriesfromxdgspecimportXDGPackageDirectorywithXDGPackageDirectory(\"XDG_CONFIG_HOME\",\"mypackage\")aspath:# path = ~/.config/mypackageprint(\"{}is now definitely existing\".format(path))Loop Over Existing XDG System DirectoriesfromxdgspecimportXDGDirectories# variable contentprint(XDGDirectories(\"XDG_CONFIG_DIRS\").paths)# generator of actually existing, unique directoriesprint(list(XDGDirectories(\"XDG_CONFIG_DIRS\").existing_paths))InstallationThexdgspecpackage is best installed viapip. Run from anywhere:python3-mpipinstall--userxdgspecThis downloads and installs the package from thePython Package\nIndex.You may also installxdgspecfrom the repository root:python3-mpipinstall--user.DocumentationDocumentation of thexdgspecpackage can be foundhere on\nGitLab."} +{"package": "xdgterm", "pacakge-description": "# xdgtermScript to launch the user\u2019s preferred terminal using the XDG terminal intent (https://zbrown.pages.freedesktop.org/term-rendered/)"} +{"package": "xdh-config", "pacakge-description": "# config\nsimple library for making a read-only, lazy-evaluated tree structure"} +{"package": "xdh-dice", "pacakge-description": "# dice\nPythonic implementation of dice-rolling mechanics as a numeric datatype"} +{"package": "xdialog", "pacakge-description": "A cross-platform python wrapper for native dialogs. Portable as it only uses the standard library."} +{"package": "xdiamond-jiayun", "pacakge-description": "xdiamond_jiayun sdk for python"} +{"package": "xdice", "pacakge-description": "xdicexdiceis a lightweight python library for managing dice, scores, and\ndice-notation patterns.Parse almost any Dice Notation pattern: \u20181d6+1\u2019, \u2018d20\u2019, \u20183d%\u2019, \u20181d20//2 - 2*(6d6+2)\u2019, \u2018max(1d4+1,1d6)\u2019, \u20183D6L2\u2019, \u2018R3(1d6+1)\u2019, \u20183dF\u2019\u2026etc.API help you to easily manipulate dices, patterns, and scores as objectsA command line tool for conveniencePython Versionsxdicehas been tested withpython 3.4+DocumentationFor more, see theDocumentationExamples:import dice\n\n# Roll simple dices with rolldice()\n # eg: 2d6\n\nscore = rolldice(6, amount=2)\n\n# manipulates the score as an integer\n\nprint(score)\n>> 11\nprint(score * 2)\n>> 22\nprint(score == 11)\n>> True\n\n# Or iterates over the results\n\nfor result in score:\n print(result)\n>> 5\n>> 6\n\n# Parse patterns with roll() and get a PatternScore object\n\nps = roll(\"2d6+18\")\n\nprint(ps)\n>> 28\nprint(ps.format())\n>> '[5,6]+18'\n\n # Use special notations, as selective dice\nps = roll(\"6D%L2\")\n\nprint(ps)\n>> 315\nprint(ps.format(verbose=True))\n>> '6D%L2(scores:[80, 70, 76, 89], dropped:[2, 49])'CLIRunpython roll.py [options] usage: roll [-h] [-V] [-n] [-v] expression [expression ...]\n\nCommand Line Interface for the xdice library\n\npositional arguments:\n expression mathematical expression(s) containing dice d patterns\n\noptional arguments:\n -h, --help show this help message and exit\n -V, --version print the xdice version string and exit\n -n, --num_only print numeric result only\n -v, --verbose print a verbose resultCONTRIBUTIONAny opinion / contribution is welcome, please contact us.TO INSTALLpip install xdiceLicensexdiceis under GNU LicenseAuthorOlivier Massot, 2017Tagsdice roll d20 game random parser dices role board"} +{"package": "xdict", "pacakge-description": "refer to .md files inhttps://github.com/ihgazni2/dlixhict-didactic"} +{"package": "xdiff", "pacakge-description": "# XDiffA CLI tool to compare data structures, files, folders, http responses, etc.## Install```bash$ python setup.py install```## Usage```text$ xdiff -husage: xdiff [-h] [--log-level LOG_LEVEL][--compare-files COMPARE_FILES [COMPARE_FILES ...]][--compare-folders COMPARE_FOLDERS [COMPARE_FOLDERS ...]]A CLI tool to compare data structures, files, folders, http responses, etc.optional arguments:-h, --help show this help message and exit--log-level LOG_LEVELSpecify logging level, default is INFO.--compare-files COMPARE_FILES [COMPARE_FILES ...]Specify origin file and new file to be compared.--compare-folders COMPARE_FOLDERS [COMPARE_FOLDERS ...]Specify origin folder and new folder to be compared.```"} +{"package": "x-diff-cover", "pacakge-description": "Automatically find diff lines that need test coverage.\nAlso finds diff lines that have violations (according to tools such\nas pycodestyle, pyflakes, flake8, or pylint).\nThis is used as a code quality metric during code reviews.OverviewDiff coverage is the percentage of new or modified\nlines that are covered by tests. This provides a clear\nand achievable standard for code review: If you touch a line\nof code, that line should be covered. Code coverage\niseverydeveloper\u2019s responsibility!Thediff-covercommand line tool compares an XML coverage report\nwith the output ofgit diff. It then reports coverage information\nfor lines in the diff.Currently,diff-coverrequires that:You are usinggitfor version control.Your test runner generates coverage reports in Cobertura, Clover\nor JaCoCo XML format.Supported XML coverage reports can be generated with many coverage tools,\nincluding:Cobertura(Java)Clover(Java)JaCoCo(Java)coverage.py(Python)JSCover(JavaScript)lcov_to_cobertura(C/C++)diff-coveris designed to be extended. If you are interested\nin adding support for other version control systems or coverage\nreport formats, see below for information on how to contribute!InstallationTo install the latest release:pipinstalldiff_coverTo install the development version:gitclonehttps://github.com/Bachmann1234/diff-cover.gitcddiff-coverpythonsetup.pyinstallGetting StartedSet the current working directory to agitrepository.Run your test suite under coverage and generate a [Cobertura, Clover or JaCoCo] XML report.\nFor example, usingpytest-cov:pytest--cov--cov-report=xmlThis will create acoverage.xmlfile in the current working directory.NOTE: If you are using a different coverage generator, you will\nneed to use different commands to generate the coverage XML report.Rundiff-cover:diff-covercoverage.xmlThis will compare the currentgitbranch toorigin/mainand print\nthe diff coverage report to the console.You can also generate an HTML, JSON or Markdown version of the report:diff-covercoverage.xml--html-reportreport.htmldiff-covercoverage.xml--json-reportreport.jsondiff-covercoverage.xml--markdown-reportreport.mdMultiple XML Coverage ReportsIn the case that one has multiple xml reports form multiple test suites, you\ncan get a combined coverage report (a line is counted as covered if it is\ncovered in ANY of the xml reports) by runningdiff-coverwith multiple\ncoverage reports as arguments. You may specify any arbitrary number of coverage\nreports:diff-covercoverage1.xmlcoverage2.xmlQuality CoverageYou can use diff-cover to see quality reports on the diff as well by runningdiff-quality.diff-quality--violations=Wheretoolis the quality checker to use. Currentlypycodestyle,pyflakes,flake8,pylint,checkstyle,checkstylexmlare supported, but more\ncheckers can (and should!) be supported. See the section \u201cAddingdiff-quality`Support for a New Quality Checker\u201d.NOTE: There\u2019s no way to runfindbugsfromdiff-qualityas it operating\nover the generated java bytecode and should be integrated into the build\nframework.Likediff-cover, HTML, JSON or Markdown reports can be generated withdiff-quality--violations=--html-reportreport.htmldiff-quality--violations=--json-reportreport.jsondiff-quality--violations=--markdown-reportreport.mdIf you have already generated a report usingpycodestyle,pyflakes,flake8,pylint,checkstyle,checkstylexml, orfindbugsyou can pass the report\ntodiff-quality. This is more efficient than lettingdiff-qualityre-runpycodestyle,pyflakes,flake8,pylint,checkstyle, orcheckstylexml.# For pylint < 1.0pylint-fparseable>pylint_report.txt# For pylint >= 1.0pylint--msg-template=\"{path}:{line}: [{msg_id}({symbol}), {obj}] {msg}\">pylint_report.txt# Use the generated pylint report when running diff-qualitydiff-quality--violations=pylintpylint_report.txt# Use a generated pycodestyle report when running diff-quality.pycodestyle>pycodestyle_report.txtdiff-quality--violations=pycodestylepycodestyle_report.txtNote that you must use the-fparseableoption to generate\nthepylintreport for pylint versions less than 1.0 and the--msg-templateoption for versions >= 1.0.diff-qualitywill also accept multiplepycodestyle,pyflakes,flake8,\norpylintreports:diff-quality--violations=pylintreport_1.txtreport_2.txtIf you need to pass in additional options you can with theoptionsflagdiff-quality--violations=pycodestyle--options=\"--exclude='*/migrations*' --statistics\"pycodestyle_report.txtCompare BranchBy default,diff-covercompares the current branch toorigin/main. To specify a different compare branch:diff-covercoverage.xml--compare-branch=origin/releaseFail UnderTo havediff-coveranddiff-qualityreturn a non zero status code if the report quality/coverage percentage is\nbelow a certain threshold specify the fail-under parameterdiff-covercoverage.xml--fail-under=80diff-quality--violations=pycodestyle--fail-under=80The above will return a non zero status if the coverage or quality score was below 80%.Exclude/Include pathsExplicit exclusion of paths is possible for bothdiff-coveranddiff-quality, while inclusion is\nonly supported fordiff-quality(since 5.1.0).The exclude option works withfnmatch, include withglob. Both options can consume multiple values.\nInclude options should be wrapped in double quotes to prevent shell globbing. Also they should be relative to\nthe current git directory.diff-covercoverage.xml--excludesetup.pydiff-quality--violations=pycodestyle--excludesetup.pydiff-quality--violations=pycodestyle--includeproject/foo/**The following is executed for every changed file:check if any include pattern was specifiedif yes, check if the changed file is part of at least one include patterncheck if the file is part of any exclude patternIgnore/Include based on file status in gitBothdiff-coveranddiff-qualityallow users to ignore and include files based on the git\nstatus: staged, unstaged, untracked:--ignore-staged: ignore all staged files (by default include them)--ignore-unstaged: ignore all unstaged files (by default include them)--include-untracked: include all untracked files (by default ignore them)Quiet modeBothdiff-coveranddiff-qualitysupport a quiet mode which is disable by default.\nIt can be enabled by using the-q/--quietflag:diff-covercoverage.xml-qdiff-quality--violations=pycodestyle-qIf enabled, the tool will only print errors and failures but no information or warning messages.Configuration filesBoth tools allow users to specify the options in a configuration file with\u2013config-file/-c:diff-covercoverage.xml--config-filemyconfig.tomldiff-quality--violations=pycodestyle--config-filemyconfig.tomlCurrently, only TOML files are supported.\nPlease note, that only non-mandatory options are supported.\nIf an option is specified in the configuration file and over the command line, the value of the\ncommand line is used.TOML configurationThe parser will only react to configuration files ending with.toml.\nTo use it, installdiff-coverwith the extra requirementtoml.The option names are the same as on the command line, but all dashes should be underscores.\nIf an option can be specified multiple times, the configuration value should be specified as a list.[tool.diff_cover]compare_branch=\"origin/feature\"quiet=true[tool.diff_quality]compare_branch=\"origin/feature\"ignore_staged=trueTroubleshootingIssue:diff-coveralways reports: \u201cNo lines with coverage information in this diff.\u201dSolution:diff-covermatches source files in the coverage XML report with\nsource files in thegit diff. For this reason, it\u2019s important\nthat the relative paths to the files match. If you are usingcoverage.pyto generate the coverage XML report, then make sure you rundiff-coverfrom the same working directory.Issue:GitDiffTool._execute()raises the error:fatal:ambiguousargument'origin/main...HEAD':unknownrevisionorpathnotintheworkingtree.This is known to occur when runningdiff-coverinTravis CISolution: Fetch the remote main branch before runningdiff-cover:gitfetchoriginmaster:refs/remotes/origin/mainIssue:diff-qualityreports \u201cdiff_cover.violations_reporter.QualityReporterError:\nNo config file found, using default configuration\u201dSolution: Your project needs apylintrcfile.\nProvide this file (it can be empty) anddiff-qualityshould run without issue.Issue:diff-qualityreports \u201cQuality tool not installed\u201dSolution:diff-qualityassumes you have the tool you wish to run against your diff installed.\nIf you do not have it then install it with your favorite package manager.Issue:diff-qualityreports no quality issuesSolution: You might use a pattern likediff-quality--violationsfoo *.py. The last argument\nis not used to specify the files but for the quality tool report. Remove it to resolve the issueLicenseThe code in this repository is licensed under the Apache 2.0 license.\nPlease seeLICENSE.txtfor details.How to ContributeContributions are very welcome. The easiest way is to fork this repo, and then\nmake a pull request from your fork.NOTE:diff-qualitysupports a plugin model, so new tools can be integrated\nwithout requiring changes to this repo. See the section \u201cAddingdiff-quality`Support for a New Quality Checker\u201d.Setting Up For DevelopmentThis project is managed withpoetrythis can be installed withpippoetry manages a python virtual environment and organizes dependencies. It also\npackages this project.pipinstallpoetrypoetryinstallI would also suggest running this command after. This will make it so git blame ignores the commit\nthat formatted the entire codebase.gitconfigblame.ignoreRevsFile.git-blame-ignore-revsAddingdiff-quality`Support for a New Quality CheckerAdding support for a new quality checker is simple.diff-qualitysupports\nplugins using the popular Pythonpluggy package.If the quality checker is already implemented as a Python package, great! If not,create a Python packageto host the plugin implementation.In the Python package\u2019ssetup.pyfile, define an entry point for the plugin,\ne.g.setup(...entry_points={'diff_cover':['sqlfluff = sqlfluff.diff_quality_plugin'],},...)Notes:The dictionary key for the entry point must be nameddiff_coverThe value must be in the formatTOOL_NAME = YOUR_PACKAGE.PLUGIN_MODULEWhen your package is installed,diff-qualityuses this information to\nlook up the tool package and module based on the tool name provided to the--violationsoption of thediff-qualitycommand, e.g.:$diff-quality--violationssqlfluffThe plugin implementation will look something like the example below. This is\na simplified example based on a working plugin implementation.fromdiff_cover.hookimporthookimplasdiff_cover_hookimplfromdiff_cover.violationsreporters.baseimportBaseViolationReporter,ViolationclassSQLFluffViolationReporter(BaseViolationReporter):supported_extensions=['sql']def__init__(self):super(SQLFluffViolationReporter,self).__init__('sqlfluff')defviolations(self,src_path):return[Violation(violation.line_number,violation.description)forviolationinget_linter().get_violations(src_path)]defmeasured_lines(self,src_path):returnNone@staticmethoddefinstalled():returnTrue@diff_cover_hookimpldefdiff_cover_report_quality():returnSQLFluffViolationReporter()Important notes:diff-qualityis looking for a plugin function:Located in your package\u2019s module that was listed in thesetup.pyentry point.Marked with the@diff_cover_hookimpldecoratorNameddiff_cover_report_quality. (This distinguishes it from any other\nplugin typesdiff_covermay support.)The function should return an object with the following properties and methods:supported_extensionsproperty with a list of supported file extensionsviolations()function that returns a list ofViolationobjects for\nthe specifiedsrc_path. For more details on this function and other\npossible reporting-related methods, see theBaseViolationReporterclasshere.Special ThanksShout out to the original author of diff-coverWill Dalyand the original author of diff-qualitySarina Canelake.Originally created with the support ofedX."} +{"package": "xdi-pandas", "pacakge-description": "# XDI PandasThis modules lets you parse XDI files into Pandas dataframes.```pythonfrom xdi_pandas import parsedf = parse('file.chir')print(df.metadata)print(df.metadata['Version'])print(df.metadata['Element']['symbol'])print(df['fit'])print(df['residual'])df2 = parse('file2.lcf')```### FieldsXDI Pandas being developed primarily to help generate in batch graphs forAthena generated files, it supports several Athena extension fields.Fields are defined and validated in [./xdi-pandas/xdi_types.py] following the spec.List of supported fields :```bash$ python -c 'from xdi_pandas.xdi_types import xdi_fields; print(\"\\n\".join(xdi_fields.keys()))'Beamline.collimationBeamline.focusingBeamline.harmonic_rejectionBeamline.nameDetector.i0Detector.itDetector.ifDetector.irElement.edgeElement.symbolElement.referenceElement.ref_edgeMono.d_spacingMono.nameFacility.currentFacility.energyAthena.bkg_kweightAthena.clampsAthena.dkAthena.drAthena.e0Athena.edge_stepAthena.eshiftAthena.fixed_stepAthena.importanceAthena.k_rangeAthena.kweightAthena.normalization_rangeAthena.phase_correctionAthena.plot_multiplierAthena.post_edge_polynomialAthena.pre_edge_lineAthena.pre_edge_rangeAthena.r_rangeAthena.rbkgAthena.spline_range_energyAthena.spline_range_kAthena.standardAthena.windowAthena.y_offsetScan.start_timeScan.end_timeScan.edge_energySample.nameSample.idSample.stoichiometrySample.prepSample.experimentersSample.temperature```### Tests`nosetest` is used for the tests.`make test` will run the tests### Repository structureThanks to Kenneth Reitz for is super useful python module directory structure."} +{"package": "xdis", "pacakge-description": "xdisA Cross-Python bytecode disassembler, bytecode/wordcode and magic-number manipulation library/package.IntroductionThe Pythondismodule allows you to disassemble bytecode from the same\nversion of Python that you are running on. But what about bytecode from\ndifferent versions?That\u2019s what this package is for. It can \u201cmarshal load\u201d Python\nbytecodes from different versions of Python. The command-line routinepydisasmwill show disassembly output using the most modern Python\ndisassembly conventions.Also, if you need to modify and write bytecode, the routines here can\nbe of help. There are routines to pack and unpack the read-only tuples\nin Python\u2019s Code type. For interoperability between Python 2 and 3 we\nprovide our own versions of the Code type, and we provide routines to\nreduce the tedium in writing a bytecode file.This package also has an extensive knowledge of Python bytecode magic\nnumbers, including Pypy and others, and how to translate fromsys.sys_infomajor, minor, and release numbers to the corresponding\nmagic value.So If you want to write a cross-version assembler, or a\nbytecode-level optimizer this package may also be useful. In addition\nto the kinds of instruction categorization thatdis`offers, we have\nadditional categories for things that would be useful in such a\nbytecode optimizer.The programs here accept bytecodes from Python version 1.0 to 3.10 or\nso. The code requires Python 2.4 or later and has been tested on\nPython running lots of Python versions.When installing, except for the most recent versions of Python, use\nthe Python egg or wheel that matches that version, e.g.xdis-6.0.2-py3.3.egg,xdis-6.0.2-py33-none-any.whl.\nOf course for versions that pre-date wheel\u2019s, like Python 2.6, you will have to use eggs.To install older versions for from source in git use the branchpython-2.4-to-2.7for Python versions from 2.4 to 2.7,python-3.1-to-3.2for Python versions from 3.1 to 3.2,python-3.3-to-3.5for Python versions from 3.3 to 3.5. The master\nbranch handles Python 3.6 and later.InstallationThe standard Python routine:$ pip install -e .\n$ pip install -r requirements-dev.txtA GNU makefile is also provided somake install(possibly as root or\nsudo) will do the steps above.Testing$ make checkA GNU makefile has been added to smooth over setting running the right\ncommand, and running tests from fastest to slowest.If you haveremakeinstalled, you can see the list of all tasks\nincluding tests viaremake--tasks.UsageRun$ ./bin/pydisasm -hfor usage help.As a drop-in replacement for disxdisalso provides some support as a drop in replacement for the\nthe Python librarydismodule. This is may be desirable when you want to use the improved API\nfrom Python 3.4 or later from an earlier Python version.For example:>>> # works in Python 2 and 3\n>>> import xdis.std as dis\n>>> [x.opname for x in dis.Bytecode('a = 10')]\n['LOAD_CONST', 'STORE_NAME', 'LOAD_CONST', 'RETURN_VALUE']There may some small differences in output produced for formatted\ndisassembly or how we show compiler flags. We expect you\u2019ll\nfind thexdisoutput more informative though.See Alsohttps://pypi.org/project/uncompyle6/: Python Bytecode Deparsinghttps://pypi.org/project/decompyle3/: Python Bytecode Deparsing for Python 3.7 and 3.8https://pypi.org/project/xasm/: Python Bytecode Assemblerhttps://pypi.org/project/x-python/: Python Bytecode Interpreter written in Python"} +{"package": "xdisplayinfo", "pacakge-description": "X Display InfoLinux CLI utility to easily get information of the current display, the one the\nmouse is hovered over, in systems using X server.DependenciesTested with the following dependencies, installed by default in most Linux\ndistributions using X:bash:4.3+xdotool:3.20160805+xrandr:1.5.0+grep:3.4+InstallationOption A: Usingpippip3installxdisplayinfoOption B: Adding source script to$PATHgitclonehttps://github.com/lu0/current-x-display-infocdcurrent-x-display-info/src/scripts/\nln-srfxdisplayinfo~/.local/bin/xdisplayinfoUsageRunxdisplayinfo -hto see the list of available options.Get information of the current display on systems using X.\n\nUSAGE:\n xdisplayinfo [OPTION]\n\nOPTIONS:\n --window-id ID of the active window (decimal).\n --offset-y Y coordinate of the top-left corner.\n --offset-x X coordinate of the top-left corner.\n --resolution Resolution as [width]x[height].\n --height Resolution along the Y axis.\n --width Resolution along the X axis.\n --name Name of the current display.\n --all All properties."} +{"package": "xdisplayselect", "pacakge-description": "XDisplaySelectThis is a simple python utility allowing you to configure your monitors using xrandr.This project is still heavily work in progress."} +{"package": "xdist", "pacakge-description": "xdistPython library of pairwise distance computationCreated byBaihan Lin, Columbia University"} +{"package": "xdist-scheduling-exclusive", "pacakge-description": "xdist-scheduling-exclusivepytest-xdist scheduler that runs some tests on dedicated workers.Can significantly improve runtime by running long tests on separate\nworkers.Installationpipinstallxdist-scheduling-exclusivepytest-xdistUsageTo integrate with your pytest setup, update conftest.py as follows:fromxdist_scheduling_exclusiveimportExclusiveLoadScopeSchedulingdefpytest_xdist_make_scheduler(config,log):\"\"\"xdist-pytest hook to set scheduler.\"\"\"returnExclusiveLoadScopeScheduling(config,log)Available Schedulers:ExclusiveLoadSchedulingSchedule tests fromexclusive_tests.txtfirst and on dedicated nodes.ExclusiveLoadFileScheduling: Place tests fromexclusive_tests.txtto uniquescopes.\nOther tests are grouped as in--dist loadfile: tests from the same file run on the same node.ExclusiveLoadScopeScheduling: Schedule tests fromexclusive_tests.txtfirst and on dedicated nodes.\nOther tests are grouped as in--dist loadfile: tests from the same file run on the same node.Optimizing for Long-Running Tests:To identify long-running tests for the exclusive list, utilize pytest's--durationsoption to sort tests by execution time.DevelopersDo not forget to run. ./activate.sh.To see how tests were scheduled use something likepython -m pytest -n 4 --xdist-report -sScriptsmake helpCoverage reportCodecovCoveralls"} +{"package": "xdistutils", "pacakge-description": "Authors:Ralf Schmitt Version:0.2.0Date:2012-02-08Download:http://pypi.python.org/pypi/xdistutilsCode:https://github.com/schmir/xdistutilsTable of ContentsInstallationThe recompress commandThe bdist_msi_fixed commandxdistutils currently provides a recompress command for python\u2019s\nsetup.py scripts. It uses theadvancecomppackage in order to achieve\nbetter compression on .zip, .egg and .tar.gz files. Other extensions\nfor distutils may be included in future xdistutils releases.Installationxdistutils can be installed with pip or easy_install. In order to\nenable the recompress command, you\u2019ll have to register the package\nwith distutils. This can be done by adding the following to\n~/.pydistutils.cfg:[global]\ncommand-packages=xdistutilsTheadvancecomppackage must be installed on your system.The recompress commandEvery setup.py script now understands a recompress command, which will\ncall advzip or advdef on any .zip, .egg or .tar.gz file generated by\nprevious commands:> python setup.py sdist bdist_egg recompress\nrunning sdist\nmake: Nothing to be done for `all'.\nrunning check\nreading manifest template 'MANIFEST.in'\nwriting manifest file 'MANIFEST'\ncreating gevent-1.0dev\ncreating gevent-1.0dev/c-ares\n...\nwriting build/bdist.linux-x86_64/egg/EGG-INFO/native_libs.txt\ncreating 'dist/gevent-1.0dev-py2.7-linux-x86_64.egg' and adding 'build/bdist.linux-x86_64/egg' to it\nremoving 'build/bdist.linux-x86_64/egg' (and everything under it)\nrunning recompress\nadvzip -z -4 dist/gevent-1.0dev.zip\n 1300236 1243960 95% dist/gevent-1.0dev.zip\n 1300236 1243960 95%\nadvzip -z -4 dist/gevent-1.0dev-py2.7-linux-x86_64.egg\n 366596 354053 96% dist/gevent-1.0dev-py2.7-linux-x86_64.egg\n 366596 354053 96%The bdist_msi_fixed commandbdist_msi is used on windows in order to create a .msi\ninstalller. It\u2019s part of standard distutils. Though abugin distutils\nmakes it impossible to upload those .msi files to the python package\nindex with the upload command. bdist_msi_fixed provides a workaround:> python setup.py bdist_msi_fixed\nrunning bdist_msi_fixed\nrunning bdist_msi\n...\n> python setup.py bdist_msi_fixed upload"} +{"package": "xditya", "pacakge-description": "This is a Wrapper to interact with Aditya.Spam here >>Aditya.Don't beg me for this."} +{"package": "xdjango", "pacakge-description": "UNKNOWN"} +{"package": "x-django-app", "pacakge-description": "x-django-appDjango application for all my custom stuffFeatures:Models:XActivityto store all user activities in the projectCREATEEDITDELETERESETDOWNLOADBACKUPRESTOREEXPORTIMPORTPUBLISHACCEPTREJECTENABLEDISABLEACTIVATEDEACTIVATEViews:XListViewfor searching in selected fieldsXCreateViewto record create activity inXActivitymodel, also addcreated_byfor the requested userXUpdateViewto record edit activity inXActivitymodel, also addedited_byfor the requested userx_record_delete_objectfunction to record delete activity inXActivitymodelNOTE:x_record_delete_objectis a function not a view used asx_record_delete_object(request, object, message)Tags:class_namereturn the class name for the objectdetect_languagereturn language code to the textget_datachange '' to \"\" for Jason useto_stringchange number to stringtrunctrnucate text for any selected lengthmake_clearreplace all ' _ ' to ' 'permission_checkcheck if user has specific permission regardless if user is superuser or notx_sortsort model data with selected fieldInstall:Install python > 3.8.8Install using pippip install x-django-appAdd \"x_django_app\" to your INSTALLED_APPS settings:INSTALLED_APPS = [...'x_django_app',]Use:For viewsfrom x_django_app.views import XListView, XCreateView, XUpdateView, x_record_delete_objectFor tags{% load x_tags %}For paginations{% include 'x_django_app/_pagination.html' %}"} +{"package": "xdj-datamap", "pacakge-description": "No description available on PyPI."} +{"package": "xdj-oauth", "pacakge-description": "#usage\n##installpip install xdj-oauth##setting\n###additionalWX_APP_ID = 'xxxx'\nWX_APP_SECRET = 'xxxxx'\nWX_AC_TOKEN = 'xxxx'###modificationINSTALLED_APPS = [\n ...\n 'xdj_oauth',\n]"} +{"package": "xdj-system", "pacakge-description": "#usage\n##installpip install xdj-system##setting\n###modificationINSTALLED_APPS = [\n ...\n 'xdj_system',\n]"} +{"package": "xdj-utils", "pacakge-description": "#usage\n##installpip install xdj-utils##setting\n###additionalUSERNAME_FIELD = 'username'\nROLE_MODEL = 'xdj_system.Role'\nDEFAULT_ROLE = ['']\nANONYMOUS_ROLE = ['']###modificationUSERNAME_FIELD = 'username'\nROLE_MODEL = 'xdj_system.Role'\nDEFAULT_ROLE = ['']\nANONYMOUS_ROLE = ['']\n\n#settings for modifying\nMIDDLEWARE = [\n ...\n xdj_utils.middleware.ApiLoggingMiddleware\n]\n\nREST_FRAMEWORK = {\n ...\n 'DEFAULT_FILTER_BACKENDS':(\n 'xdj_utils.filters.CustomDjangoFilterBackend',\n ...\n ),\n 'DEFAULT_PAGINATION_CLASS': 'xdj_utils.pagination.CustomPagination',\n 'DEFAULT_AUTHENTICATION_CLASSES':(\n ...\n 'xdj_utils.authentications.AnonymousAuthenticated',\n ),\n 'EXCEPTION_HANDLER': 'xdj_utils.exception.CustomExceptionHandler',\n}\n\nAUTHENTICATION_BACKENDS = [\n 'xdj_utils.backends.CustomBackend',\n ...\n]\n\nSWAGGER_SETTINGS = {\n ...\n 'DEFAULT_AUTO_SCHEMA_CLASS': 'xdj_utils.swagger.CustomSwaggerAutoSchema',\n}"} +{"package": "xdl", "pacakge-description": "# xdl\nDeep Learning with Xarray"} +{"package": "xdlink", "pacakge-description": "No description available on PyPI."} +{"package": "xdmenu", "pacakge-description": "Extensible wrapper fordmenu.dmenu is a dynamic menu for X, originally designed for dwm. It manages\nlarge numbers of user-defined menu items efficiently.Source code on GitHubLatest documentationxdmenuis free software and licensed under the GNU Lesser General Public\nLicense v3.FeaturesMany options available in patches built inAdditional options can be addedEasy to extend for other tools such asRofiCreditsThis package was created withCookiecutterand thecblegare/pythontemplateproject template."} +{"package": "xdmf-dolfin-fix", "pacakge-description": "xdmf_dolfin_fixThere is an xdmf import issue in FEniCS/DOLFIN. Quadratic triangles and tetrahedrons\nare imported incorrectly. The CLI toolxdmf-dolfin-fixfixes this issue by reordering element numbers.Example usagexdmf-dolfin-fix old.xdmf # fix old.xdmf\nxdmf-dolfin-fix old.xdmf new.xdmf # create fixed new.xdmf\nxdmf-dolfin-fix old.geo -d3 # create fixed old.xdmf from gmsh\nxdmf-dolfin-fix old.msh new.xdmf # create fixed new.xdmf from gmshProblemAt some point of the simulation FEniCS/DOLFIN orders the vertices of all elements\nin numerically accending order. Nodes on the edges of elements -- as present\nin quadratic triangles and quadratic tetrahedrons -- are not swapped.So internally, the node numbers of an arbitrary quadratic tetrahedron[ vertices | edges ]\n[ 51 74 12 | 14 72 1003 ]would be reordered to[ 12 51 74 | 14 72 1003 ]Now, the vertex nodes[12 51 74]are sorted, but the edge nodes[14 72 1003]are left unchanged. This results in a twisted geometry.Fixxdmf-dolfin-fixsorts the vertex nodesandreorders the edge nodes accordingly. This\nwill result in[ 12 51 74 | 1003 14 74 ]A further sorting within DOLFIN has no effect and, thus, will not mess up\nthis ordering."} +{"package": "xdmod-data", "pacakge-description": "xdmod-dataAs part of theXDMoDData Analytics Framework, this Python package provides API access to the data warehouse of an instance of XDMoD version \u226510.5.The package can be installed from PyPI viapip install xdmod-data.It has dependencies onNumPy,Pandas,Plotly, andRequests.Example usage is documented through Jupyter notebooks in thexdmod-notebooksrepository.API Token AccessUse of the Data Analytics Framework requires an API token. To obtain an API token, follow the steps below to obtain an API token from the XDMoD portal.First, if you are not already signed in to the portal, sign in in the top-left corner:Next, click the \"My Profile\" button in the top-right corner:The \"My Profile\" window will appear. Click the \"API Token\" tab:Note:If the \"API Token\" tab does not appear, it means this instance of XDMoD is not configured for the Data Analytics Framework.If you already have an existing token, delete it:Click the \"Generate API Token\" button:Copy the token to your clipboard. Make sure to paste it somewhere for saving, as you will not be able to see the token again once you close the window:Note:If you lose your token, simply delete it and generate a new one.SupportFor support, please seethis page. If you email for support, please include the following:xdmod-dataversion number, obtained by running this Python code:from xdmod_data import __version__\nprint(__version__)Operating system version.A description of the problem you are experiencing.Detailed steps to reproduce the problem.Licensexdmod-datais released under the GNU Lesser General Public License (\"LGPL\") Version 3.0. See theLICENSEfile for details.ReferenceWhen referencing XDMoD, please cite the following publication:Jeffrey T. Palmer, Steven M. Gallo, Thomas R. Furlani, Matthew D. Jones, Robert L. DeLeon, Joseph P. White, Nikolay Simakov, Abani K. Patra, Jeanette Sperhac, Thomas Yearke, Ryan Rathsam, Martins Innus, Cynthia D. Cornelius, James C. Browne, William L. Barth, Richard T. Evans, \"Open XDMoD: A Tool for the Comprehensive Management of High-Performance Computing Resources\",Computing in Science & Engineering, Vol 17, Issue 4, 2015, pp. 52-62. DOI:10.1109/MCSE.2015.68"} +{"package": "xdmod-ondemand-export", "pacakge-description": "See [https://github.com/ubccr/xdmod-ondemand/tree/main/tools/xdmod-ondemand-export](the README) for instructions on use."} +{"package": "xdnlp", "pacakge-description": "xdnlpA highly efficient and easy-to-use natural language processing library.Installpipinstallxdnlporgitclonehttps://github.com/mikuh/xdnlp\npipinstall./xdnlp/APISThere are still some function introductions that have not been written for the time being, wait for my follow-up update.TextNormalizeCharacter normalization.fromxdnlpimportTexttext=Text()text.normalize(\"\ufa09\u9f8d\u2474\u2467\u638c\")# \ufa09\u9f8d\u2474\u2467\u638c -> \u964d\u9f9918\u638cKeyword ExtractExtract keywords from sentence.fromxdnlpimportTexttext=Text()text.add_keywords_from_list([\"c++\",'python','java','javascript'])text.extract_keywords(\"\u5c0f\u660e\u5b66\u4e60\u4e86python c++ javascript\",longest_only=True)# return [\"python\", 'c++', 'javascript']# batch modetext.batch_extract_keywords([\"\u5c0f\u660e\u5b66\u4f1a\u4e86c++\",\"python\u548cc++\u6709\u4ec0\u4e48\u533a\u522b\",\"Javascript\u548cjava\u662f\u540c\u4e00\u4e2a\u4e1c\u897f\u5417\"])# return [['c++'], ['python', 'c++'], ['java']]Keyword ReplaceReplace keywords in sentence.fromxdnlpimportTexttext=Text()text.add_keywords_replace_map_from_dict({\"java\":\"golang\",\"javascript\":\"node\"})text.replace_keywords(\"\u5c0f\u660e\u5b66\u4e60\u4e86python c++ javascript\")# return \u5c0f\u660e\u5b66\u4e60\u4e86python c++ node# batch modetext.batch_replace_keywords([\"\u5c0f\u660e\u5b66\u4f1a\u4e86c++\",\"python\u548cc++\u6709\u4ec0\u4e48\u533a\u522b\",\"javascript\u548cjava\u662f\u540c\u4e00\u4e2a\u4e1c\u897f\u5417\"])# return [\"\u5c0f\u660e\u5b66\u4f1a\u4e86c++\", \"python\u548cc++\u6709\u4ec0\u4e48\u533a\u522b\", \"node\u548cgolang\u662f\u540c\u4e00\u4e2a\u4e1c\u897f\u5417\"]Text cleanRemove extraneous characters from a sentence.fromxdnlpimportTexttext=Text()text.clean(\"aaaaaaAAAAA9123123\u6211\u662f \u4e2d\u56fd\u4eba-=[]:<>aaa\",max_repeat=2)# return aa9123123\u6211\u662f \u4e2d\u56fd\u4eba aa# batch modetext.batch_clean([\"aaaaaaAAAAA9123123\u6211\u662f \u4e2d\u56fd\u4eba-=[]:<>aaa\",\"666666\"],max_repeat=2)\\# return [\"aa9123123\u6211\u662f \u4e2d\u56fd\u4eba aa\", '66']Text encodeA text encoder.fromxdnlpimportTexttext=Text()text.encode(\"wo\u64cd\u4f60\u5988\u3001\u30d5\u3061ql\u30d5q\u3001\")# return {'contact': 1, 'unknown': 1, 'specify': 0, 'length': 13, 'low_frequency': 0, 'zh_scale': 0.6153846153846154, 'en_num_scale': 0.0, 'zh_piece_scale': 0.6666666666666666, 'not_zh_piece_scale': 0, 'pinyin': 'wocaonima\u3001\u30d5\u3061ql\u30d5q\u3001'}Text batch cut wordsBatch cut words from a iteratorfromxdnlpimportTextimportjiebatext=Text()text_list=[\"\u767e\u6218\u5927\u4f6c \u8981\u4e0d\u8981\u67656\u7ebf\u5e2e\u6253\u6253\",\"\u5bf9\u5440\uff0c\u89c9\u5f97\u540e\u9762\u7684\u65f6\u95f4\u624d\u662f\u81ea\u5df1\u7684\",\"\u4ea1\u8005\u914b\u957f\u5934\u9970\u56fe\u7eb8\u5f88\u8d35\u54df\",\"\u55ef,\u4e0d\u61c2,\u5feb\u51c9\u4e86,\u54c8\u54c8,\u521a\u770b\u523010\u6708\u5c31\u62a2\u4e86\"]*1000000out=text.batch_cut(text_list,jieba,n_jobs=20,batch_size=1000)# return [['\u767e\u6218', '\u5927\u4f6c', ' ', '\u8981', '\u4e0d\u8981', '\u6765', '6', '\u7ebf\u5e2e', '\u6253\u6253'], ['\u5bf9', '\u5440', '\uff0c', '\u89c9\u5f97', '\u540e\u9762', '\u7684', '\u65f6\u95f4', '\u624d', '\u662f', '\u81ea\u5df1', '\u7684'],...]Word DiscoverFound vocabulary from massive textfromxdnlpimportWordDiscoverwd=WordDiscover()wd.word_discover([\"path/to/the.txt\"],save_ngram=True)ClassifyTextCNNimportosimporttensorflowastffromxdnlp.classifyimportTextCNNfromxdnlp.classify.utilsimportload_data_from_directory,get_vectorize_layermax_features=50000max_len=100batch_size=64epochs=20data_dir=\"path/to/your/data/dir\"train_ds,val_ds,test_ds,class_names=load_data_from_directory(data_dir,batch_size=batch_size)vectorize_layer=get_vectorize_layer(max_features,max_len,train_ds)model_config=dict(input_shape=(max_len,),class_names=class_names,model_dir=\"models\",vectorize_layer=vectorize_layer,embedding_size=128,hidden_size=256,filter_sizes=[3,4,5],num_filters=256,dropout=0.2,is_train=True)model=TextCNN(**model_config)model.train(train_ds,val_ds,1)# predictmodel_save_path=\"your model save path\"# load from ckptconfig=TextCNN.get_model_config(model_save_path)vectorize_layer=get_vectorize_layer(config[\"max_features\"],config[\"max_len\"],vocabulary=config[\"vocabulary\"])model_config=dict(input_shape=(config[\"max_len\"],),vectorize_layer=vectorize_layer,class_names=config[\"class_names\"],embedding_size=config[\"embedding_size\"],hidden_size=config[\"hidden_size\"],filter_sizes=config[\"filter_sizes\"],num_filters=config[\"num_filters\"],dropout=config[\"dropout\"],is_train=False)model=TextCNN(**model_config)# load from pbmodel=tf.keras.models.load_model(os.path.join(model_save_path,\"my_model\"))res=model(tf.constant([\"\u8fd9 \u4ec0\u4e48 \u5783\u573e \u6e38\u620f\"]))print(config[\"class_names\"][tf.argmax(res[0]).numpy()])TextRNNfromxdnlp.classifyimportTextRNNfromxdnlp.classify.utilsimportload_data_from_directory,get_vectorize_layerimporttensorflow.kerasaskerasmax_features=50000max_len=100batch_size=64data_dir=\"path/to/your/data/dir\"model_dir=\"dir/for/save/model\"embedding_size=128rnn_hidden_size=256fc_hidden_size=128num_layers=2dropout=0.2epochs=2train_ds,val_ds,test_ds,class_names=load_data_from_directory(data_dir,batch_size)vectorize_layer=get_vectorize_layer(max_features,max_len,train_ds)model=TextRNN(vectorize_layer=vectorize_layer,class_names=class_names,model_dir=model_dir,embedding_size=embedding_size,rnn_hidden_size=rnn_hidden_size,fc_hidden_size=fc_hidden_size,num_layers=num_layers,dropout=dropout,is_train=True)model.train(train_ds,val_ds,epochs)model.evaluate(test_ds)# load from ckptmodel_config_path=\"path/to/model_config\"checkpoint_path=\"path/to/checkpoint/for/loading\"batch_size=64model_config=TextRNN.get_model_config(model_config_path)vectorize_layer=get_vectorize_layer(model_config[\"max_features\"],model_config[\"max_len\"],vocabulary=model_config[\"vocabulary\"])model=TextRNN(vectorize_layer=vectorize_layer,class_names=model_config[\"class_names\"],embedding_size=model_config[\"embedding_size\"],rnn_hidden_size=model_config[\"rnn_hidden_size\"],fc_hidden_size=model_config[\"fc_hidden_size\"],num_layers=model_config[\"num_layers\"],dropout=model_config[\"dropout\"],is_train=False)model.compile(optimizer='adam',loss='categorical_crossentropy',metrics=['accuracy'])model.load_weights(checkpoint_path)# load from pbmodel_save_path=\"path/to/model/for/loading\"model=keras.models.load_model(model_save_path)model.evaluate(test_ds)Bert or Albert classifyfromxdnlp.classifyimportBertClassifyhandle_encoder=\"\"# bert or albert pre train encoder,set local savedmodel dir or tfhub model urlhandle_preprocess=\"\"# bert preprocess,set local savedmodel dir or tfhub model urlmodel=BertClassify(handle_encoder,handle_preprocess,categories=2)# set train and test data dirtrain_ds,val_ds,test_ds=model.load_data(\"../../bert/aclImdb/train\",\"../../bert/aclImdb/test\",)model.preview_train_data(train_ds)model.preview_classify()model.train(train_ds,val_ds)"} +{"package": "xdnn", "pacakge-description": "No description available on PyPI."} +{"package": "xDNN-classifier", "pacakge-description": "No description available on PyPI."} +{"package": "xdo", "pacakge-description": "No description available on PyPI."} +{"package": "x-docker", "pacakge-description": "No description available on PyPI."} +{"package": "xdocs", "pacakge-description": "XDocs is a fast and simple documentation generator that\u2019s geared towards building project documentation. Documentation source files are written in YAML, and configured with a single YAML configuration file."} +{"package": "xdoctest", "pacakge-description": "Xdoctest - Execute doctests. A Python package for executing tests in\ndocumentation strings!What is adoctest?\nIt is example code you write in a docstring!\nWhat is adocstring?\nIts a string you use as a comment! They get attached to Python functions and\nclasses as metadata. They are often used to auto-generate documentation.\nWhy is it cool?\nBecause you can write tests while you code!Tests are good. Documentation is good. Examples are good. Doctests have low\nboilerplate, you write them in the same file you write your code. It often can\nhelp you write the function. Write down how to construct minimal demo inputs\n(it helps to have tools to create these) in your file. Copy that code into\nIPython/Jupyter, and play with your implementation. Copy your finished code\ninto the body. Write down how to call the function with the demo inputs. If you\nfeel inclined, check that the result matches an expected result (while asserts\nand checks are nice, a test that just shows how to run the code is better than\nno test at all).defan_algorithm(data,config):\"\"\"\n Example:\n >>> data = '([()[]])[{}([[]])]'\n >>> config = {'outer': sum, 'inner': ord}\n >>> an_algorithm(data, config)\n 1411\n \"\"\"# I wrote this function by first finding some interesting demodata# then I wrote the body in IPython and copied it back in.# Now I can re-use this test code I wrote in development as a test!# Covered Code is much easier to debug (we have a MWE)!result=config['outer'](map(config['inner'],data))returnresultThe problem? How do you run the code in your doctest?Xdoctest finds and executes your doctests for you.\nJust runxdoctest.\nIt plugs into pytest to make it easy to run on a CI. Install and runpytest--xdoctest.Thexdoctestpackage is a re-write of Python\u2019s builtindoctestmodule. It replaces the old regex-based parser with a new\nabstract-syntax-tree based parser (using Python\u2019sastmodule). The\ngoal is to make doctests easier to write, simpler to configure, and\nencourage the pattern of test driven development.Read the docshttps://xdoctest.readthedocs.ioGithubhttps://github.com/Erotemic/xdoctestPypihttps://pypi.org/project/xdoctestPyCon 2020Youtube VideoandGoogle SlidesQuick StartInstallation: from pypiXdoctest is distributed on pypi as a universal wheel and can be pip installed on\nPython 3.6+ (Python 2.7 and 3.4 / 3.5 support was removed in Version 1.1.0).\nInstallations are tested on CPython and PyPy implementations.pip install xdoctestDistributions on pypi are signed with a GPG public key:D297D757. If you\ncare enough to check the gpg signature (hopefully pip will just do this in the\nfuture), you should also verify this agrees with the contents ofdev/public_gpg_key.Usage: run your doctestsAfter installing, the fastest way to run all doctests in your project\nis:python -m xdoctest /path/to/your/pkg-or-module.pyor if your module has been pip-installed / is in the PYTHONPATH runpython -m xdoctest yourmodnameGetting StartedThere are two ways to usexdoctest: viapytestor via the native\ninterface. The native interface is less opaque and implicit, but its\npurpose is to run doctests. The other option is to use the widely usedpytestpackage. This allows you to run both unit tests and doctests\nwith the same command and has many other advantages.It is recommended to usepytestfor automatic testing (e.g. in your\nCI scripts), but for debugging it may be easier to use the native\ninterface.Check if xdoctest will work on your packageYou can quickly check ifxdoctestwill work on your package\nout-of-the box by installing it via pip and runningpython-mxdoctest all, whereis the path to your\npython package / module (or its name if it is installed in yourPYTHONPATH).For example with you might test ifxdoctestworks onnetworkxorsklearnas such:python-mxdoctest networkx all/python-mxdoctest sklearn all.Using the pytest interfaceWhenpytestis run,xdoctestis automatically discovered, but is\ndisabled by default. This is becausexdoctestneeds to replace the builtindoctestplugin.To enable this plugin, runpytestwith--xdoctestor--xdoc.\nThis can either be specified on the command line or added to youraddoptsoptions in the[pytest]section of yourpytest.iniortox.ini.To run a specific doctest,xdoctestsets uppytestnode names\nfor these doctests using the following pattern::::. For example a doctest for a\nfunction might look like thismymod.py::funcname:0, and a class\nmethod might look like this:mymod.py::ClassName::method:0Using the native interface.In addition to thepytestplugin, xdoctest has a native doctest runner.\nYou can use thexdoctestcommand line tool that is installed with the\npackage and point it a module directory or a particular file.You can also make it such that invoking your module as__main__invokes the\nxdoctest native runner using the using thexdoctest.doctest_module(path)method, which can be placed in the__main__section of any module as such:if__name__=='__main__':importxdoctestxdoctest.doctest_module(__file__)This sets up the ability to invoke thexdoctestcommand line\ninterface.python-m .However, it is typically prefered to just use thexdoctestexecutable and\npass it the path to your file, or the name of an installed module. In this case\nit is invoked likexdoctest-m .Using either of these methods you can natively invoke xdoctest on a module or\npackage, which exposes the command line interface. Both of these expose the\ncommand line interface, allowing you to pass a command to xdoctest.Ifisall, then each enabled doctest in the module\nis executed:python-m allIfislist, then the names of each enabled doctest\nis listed.Ifisdump, then all doctests are converted into a format\nsuitable for unit testing, and dumped to stdout (new in 0.4.0).Ifis acallname(name of a function or a class and\nmethod), then that specific doctest is executed:python-m . Note: you can execute disabled\ndoctests or functions without any arguments (zero-args) this way.For example if you created a modulemymod.pywith the following\ncode:deffunc1():\"\"\"\n Example:\n >>> assert func1() == 1\n \"\"\"return1deffunc2(a):\"\"\"\n Example:\n >>> assert func2(1) == 2\n >>> assert func2(2) == 3\n \"\"\"returna+1You couldUse the commandxdoctest-mmymod listto list the names of all functions with doctestsUse the commandxdoctest-mmymod allto run all functions with doctestsUse the commandxdoctest-mmymod func1to run only func1\u2019s doctestUse the commandxdoctest-mmymod func2to run only func2\u2019s doctestPassing--helpto either way of invoking the native runner will result in\nsomething similar to the following that outlines what other options are\navailable:usage: xdoctest [-h] [--version] [-m MODNAME] [-c COMMAND] [--style {auto,google,freeform}] [--analysis {auto,static,dynamic}] [--durations DURATIONS] [--time]\n [--colored COLORED] [--nocolor] [--offset] [--report {none,cdiff,ndiff,udiff,only_first_failure}] [--options OPTIONS] [--global-exec GLOBAL_EXEC]\n [--verbose VERBOSE] [--quiet] [--silent]\n [arg ...]\n\nXdoctest 1.0.1 - on Python - 3.9.9 (main, Jun 10 2022, 17:45:11)\n[GCC 11.2.0] - discover and run doctests within a python package\n\npositional arguments:\n arg Ignored if optional arguments are specified, otherwise: Defaults --modname to arg.pop(0). Defaults --command to arg.pop(0). (default: None)\n\noptional arguments:\n -h, --help show this help message and exit\n --version Display version info and quit (default: False)\n -m MODNAME, --modname MODNAME\n Module name or path. If specified positional modules are ignored (default: None)\n -c COMMAND, --command COMMAND\n A doctest name or a command (list|all|). Defaults to all (default: None)\n --style {auto,google,freeform}\n Choose the style of doctests that will be parsed (default: auto)\n --analysis {auto,static,dynamic}\n How doctests are collected (default: auto)\n --durations DURATIONS\n Specify execution times for slowest N tests.N=0 will show times for all tests (default: None)\n --time Same as if durations=0 (default: False)\n --colored COLORED Enable or disable ANSI coloration in stdout (default: True)\n --nocolor Disable ANSI coloration in stdout\n --offset If True formatted source linenumbers will agree with their location in the source file. Otherwise they will be relative to the doctest itself. (default:\n False)\n --report {none,cdiff,ndiff,udiff,only_first_failure}\n Choose another output format for diffs on xdoctest failure (default: udiff)\n --options OPTIONS Default directive flags for doctests (default: None)\n --global-exec GLOBAL_EXEC\n Custom Python code to execute before every test (default: None)\n --verbose VERBOSE Verbosity level. 0 is silent, 1 prints out test names, 2 additionally prints test stdout, 3 additionally prints test source (default: 3)\n --quiet sets verbosity to 1\n --silent sets verbosity to 0Zero-args runnerThe native interface has a \u201czero-args\u201d mode in thexdoctestrunner. This allows you to run functions in your modules\nvia the command line as long as they take no arguments. The purpose is\nto create a quick entry point to functions in your code (becausexdoctestis taking the space in the__main__block).For example, you might create a modulemymod.pywith the following\ncode:defmyfunc():print('hello world')if__name__=='__main__':importxdoctestxdoctest.doctest_module(__file__)Even thoughmyfunchas no doctest it can still be run using the\ncommandpython-mmymod myfunc.Note, even though \u201czero-arg\u201d functions can be run via this interface\nthey are not run bypython-mmymod all, nor are they listed bypython-mmymod list.However, if you are doing this often, you may be better served byfire.EnhancementsThe main enhancementsxdoctestoffers overdoctestare:All lines in the doctest can now be prefixed with>>>. There is\nno need for the developer to differentiate betweenPS1andPS2lines. However, old-style doctests wherePS2lines are\nprefixed with...are still valid.Additionally, the multi-line strings don\u2019t require any prefix (but\nits ok if they do have either prefix).Tests are executed in blocks, rather than line-by-line, thus\ncomment-based directives (e.g.# doctest: +SKIP) can now applied\nto an entire block (by placing it one the line above), in addition to having\nit just apply to a single line (by placing it in-line at the end).Tests without a \u201cwant\u201d statement will ignore any stdout / final\nevaluated value. This makes it easy to use simple assert statements\nto perform checks in code that might write to stdout.If your test has a \u201cwant\u201d statement and ends with both a value and\nstdout, both are checked, and the test will pass if either matches.Ouptut from multiple sequential print statements can now be checked by\na single \u201cgot\u201d statement. (new in 0.4.0).See code indev/_compare/demo_enhancements.pyfor a demo that illustrates\nseveral of these enhancements. This demo shows cases wherexdoctestworks\nbutdoctestfails. As of version 0.9.1, there are no known syntax backwards\nincompatability. Please submit an issue if you can find any backwards\nincompatible cases.ExamplesHere is an example demonstrating the new relaxed (and\nbackwards-compatible) syntax:deffunc():\"\"\"\n # Old way\n >>> def func():\n ... print('The old regex-based parser required specific formatting')\n >>> func()\n The old regex-based parser required specific formatting\n\n # New way\n >>> def func():\n >>> print('The new ast-based parser lets you prefix all lines with >>>')\n >>> func()\n The new ast-based parser lets you prefix all lines with >>>\n \"\"\"deffunc():\"\"\"\n # Old way\n >>> print('''\n ... It would be nice if we didnt have to deal with prefixes\n ... in multiline strings.\n ... '''.strip())\n It would be nice if we didnt have to deal with prefixes\n in multiline strings.\n\n # New way\n >>> print('''\n Multiline can now be written without prefixes.\n Editing them is much more natural.\n '''.strip())\n Multiline can now be written without prefixes.\n Editing them is much more natural.\n\n # This is ok too\n >>> print('''\n >>> Just prefix everything with >>> and the doctest should work\n >>> '''.strip())\n Just prefix everything with >>> and the doctest should work\n\n \"\"\"Xdoctest Parsing StyleThere are currently two main doctest parsing styles:googleandfreeform, as well as a third style:auto, which is a hybrid.The parsing style can be set via the--stylecommand line argument in the\nXdoctest CLI, or via the--xdoctest-styleif using pytest.Setting--style=google(or--xdoctest-style=googlein pytest) enables\ngoogle-style parsing.\nAGoogle-styledoctest is\nexpected to exist in Google \u201cdocblock\u201d with anExample:orDoctest:tag. All code in this block is parsed out as a single doctest.Setting--style=freeform(or--xdoctest-style=freeformin pytest) enables\nfreeform-style parsing.\nA freeform style doctest is any contiguous block of lines prefixed by>>>.\nThis is the original parsing style of the builtin doctest module. Each block is\nlisted as its own test.By default Xdoctest sets--style=auto(or--xdoctest-style=autoin\npytest) which will pull all google-style blocks out as single doctests, while\nstill all other>>>prefixed code out as a freeform doctest.Notes On Got/Want TestsThe new got/want tester is very permissive by default; it ignores\ndifferences in whitespace, tries to normalize for python 2/3\nUnicode/bytes differences, ANSI formatting, and it uses the old doctest\nELLIPSIS fuzzy matcher by default. If the \u201cgot\u201d text matches the \u201cwant\u201d\ntext at any point, the test passes.Currently, this permissiveness is not highly configurable as it was in\nthe original doctest module. It is an open question as to whether or not\nthis module should support that level of configuration. If the test\nrequires a high degree of specificity in the got/want checker, it may\njust be better to use anassertstatement.Backwards CompatibilityThere are no known syntax incompatibilities with original doctests. This is\nbased on running doctests on real life examples inboltons,ubelt,networkx,pytorch, and on a set of extensive testing suite. Please\nraise an issue or submit a merge/pull request if you find any incompatibility.Despite full syntax backwards compatibility, there some runtime\nincompatibilities by design. Specifically, Xdoctest enables a different set of\ndefault directives, such that the \u201cgot\u201d/\u201dwant\u201d checker is more permissive.\nThus, a test that fails indoctestbased on a \u201cgot\u201d/\u201dwant\u201d check, may pass\ninxdoctest. For this reason it is recommended that you rely on codedassert-statements for system-critical code. This also makes it much easier\nto transform yourxdoctestinto aunittestwhen you realize your\ndoctests are getting too long.One Last ExampleXDoctest is a good demonstration of itself. After pip installing xdoctest, try\nrunning xdoctest on xdoctest.xdoctestxdoctestIf you would like a slightly less verbose output, tryxdoctestxdoctest--verbose=1# orxdoctestxdoctest--verbose=0You could also consider running xdoctests tests through pytest:pytest$(python-c'import xdoctest, pathlib; print(pathlib.Path(xdoctest.__file__).parent)')--xdoctestIf you would like a slightly more verbose output, trypytest-s--verbose--xdoctest-verbose=3--xdoctest$(python-c'import xdoctest, pathlib; print(pathlib.Path(xdoctest.__file__).parent)')If you ran these commands, the myriad of characters that flew across your\nscreen are lots more examples of what you can do with doctests."} +{"package": "xdocx", "pacakge-description": "OverView\u8be5\u8f6f\u4ef6\u7684\u4e3b\u8981\u76ee\u7684\u662f\u5728\u4fdd\u6301\u6b63\u786e\u7684\u524d\u63d0\u4e0b\u5c3d\u53ef\u80fd\u5730\u52a0\u5feb\u8f6f\u4ef6\u53d1\u5e03\u3002"} +{"package": "xdol", "pacakge-description": "xdolExtended Data Object Layers - dol-based toolsTo install:pip install xdol"} +{"package": "xdot", "pacakge-description": "xdot.py is an interactive viewer for graphs written in Graphviz\u2019s dotlanguage.It uses internally the graphviz\u2019s xdot output format as an intermediate\nformat, and PyGTK and Cairo for rendering.xdot.py can be used either as a standalone application from command\nline, or as a library embedded in your python application."} +{"package": "xdotool", "pacakge-description": "XDOTOOLLibrary to use xdotool with python.PrerequisitesUbuntusudoapt-getinstallxdotoolInstalationYou can installxdotoolfromPypi. It's going to install the library itself and its prerequisites as well.pipinstallxdotoolYou can installxdotoolfrom its source code.gitclonehttps://github.com/Tlaloc-Es/xdotool.gitcdxdotool\npipinstall-e."} +{"package": "xdot-rs", "pacakge-description": "xdotThe main function of this package isparse.\nIt parses node/edge attributes on graphviz graphs created byxdotinto drawable shapes.usexdot::{parse,ShapeDraw};letshapes:Vec=parse(\"c 7 -#ff0000 p 4 4 4 36 4 36 36 4 36\");EachShapeDrawstruct contains ashapewith geometry and apenwith drawing attributes (such as color, line style, and font).\nIf you have thelayoutfeature active, you can also uselayout_and_draw_graph(anddraw_graph):usegraphviz_rust::parse;usegraphviz_rust::dot_structures::Graph;usexdot::{layout_and_draw_graph,ShapeDraw};letgraph:Graph=parse(\"graph { a -- b}\").unwrap();letshapes:Vec=layout_and_draw_graph(graph).unwrap();Release processA commit tomaincauses creation or update of a release PR. (releaseworkflow)Merging a release PR causes the creation of a Git tag and GitHub release, and the upload of a Rust crate tocrates.io.(alsoreleaseworkflow)Publishing this GitHub release in turn triggers building and uploading a Python package. (publishworkflow)"} +{"package": "xdow", "pacakge-description": "xdowVideo Downloader (Mostly Porn)This is a video downloader for porn. To download youtube videos you\ncan useyoutube-dlHow to useCurrently Only Pornhub is supportedGet Direct link of any video and pass the link as argument to console scriptxdowe.gxdow https://www.pornhub.com/view_video.php?viewkey=ph5e5afa917d4fdPlease report bug by raising a issue atgithub issuesor sending me an email by clicking the author hyperlink"} +{"package": "xdp-test-harness", "pacakge-description": "XDP test harnessA test harness that can be used to test the implementation of XDP and XDP\nprograms.RequirementsPython 3.5, bcc, Pyroute2, ScapyUsageRunningTo start the test harness, runpython3 -m xdp_test_harness.runnerin a folder\ncontaining tests as a superuser. There are three commands that can be used:clientStart a client, running tests using network interfaces to process packets by XDP\nprogram. One can further specify which tests to run, usingunittest's format.\nThat is modules, classes and methods separated by dots, for examplepython3 -m xdp_test_harness.runner client test_general.ReturnValuesBasic.bptrSimilar to theclientcommand, but uses theBPF_PROG_TEST_RUNsyscall\ncommand instead of a server to process packets by an XDP program.serverStarts a server, used byclientcommand to send packets.ConfigurationConfiguration of interfaces to be used for testing is done in theconfig.pyfile. In the configuration file there are two variables:local_server_ctxA variable specifying the interface of the server, used for testing, and\nthe interface of the server used for communication with a client.local_server_ctx=ContextServer(ContextLocal(\"enp0s31f6\"),ContextCommunication(\"192.168.0.106\",6555),)remote_server_ctxsList of contexts specifying one physical testing interface and one virtual\ntesting interface. Elements of the list are eitherContextClientobjects,\nfor physical interfaces, or objects created bynew_virtual_ctxfunction,\nfor virtual interfaces.remote_server_ctxs=ContextClientList([ContextClient(ContextLocal(\"enp0s31f6\",xdp_mode=XDPFlag.SKB_MODE),ContextCommunication(\"192.168.0.107\",6555)),new_virtual_ctx(ContextLocal(\"a_to_b\",xdp_mode=XDPFlag.DRV_MODE),ContextCommunication(\"192.168.1.1\"),\"test_b\",ContextLocal(\"b_to_a\",xdp_mode=XDPFlag.DRV_MODE),ContextCommunication(\"192.168.1.2\",6000),),])Creating new testsTo create a new test, create a class inheriting fromXDPCase. This class\nshould be located in a file named with atest_prefix and placed in thetestsfolder. Each method of this class, that should be run while testing,\nhas to be named with atest_prefix.Each test should either call bothload_bpfandattach_xdpmethods in this\norder, before callingsend_packets, or be decorated withusingCustomLoaderand attach own XDP program to the interface. After\nattaching attaching an XDP program, callingsend_packets, returns aSendResultobject, containing lists of packets that arrived to each\ninterface engaged in testing."} +{"package": "xdress", "pacakge-description": "XDress is an automatic wrapper generator for C/C++ written in pure Python. Currently,\nxdress may generate Python bindings (via Cython) for C++ classes & functions\nand in-memory wrappers for C++ standard library containers (sets, vectors, maps).\nIn the future, other tools and bindings will be supported.The main enabling feature of xdress is a dynamic type system that was designed with\nthe purpose of API generation in mind.Go here for the latest version of the docs!Contentstutorial\nadvtut\nlibclang\nlibref/index\nrcdocs\nprevious/index\nother/index\nfaq\nauthorsInstallationSince xdress is pure Python code, thepiporeasy_installmay be used\nto grab and install the code:$ pip install xdress\n\n$ easy_install xdressThe source code repository for xdress may be found at theGitHub project site.\nYou may simply clone the development branch using git:git clone git://github.com/xdress/xdress.gitAlso, if you wish to have the optional BASH completion, please add the\nfollowing lines to your~/.bashrcfile:# Enable completion for xdress\neval \"$(register-python-argcomplete xdress)\"DependenciesXDress currently has the following external dependencies,Run Time:Clang/LLVM, optional for C/C++pycparser, optional for CGCC-XML, optional for C++dOxygen, optional for docstringslxml, optional (but nice!)argcomplete, optional for BASH completionCompile Time:CythonNumPyTest Time:noseCMake, optional for integration testsExamples of UseTo see examples of xdress in action (and sample run control files), here are a\nfew places to look:xdress/tests/cproj:\nThis is a fully functioning sample C project which uses xdress locally.xdress/tests/cppproj:\nThis is a fully functioning sample C++ project which uses xdress locally.PyNE: This uses xdress to generate STL container wrappers.Bright: This uses xdress to automatically\nwrap a suite of interacting C++ class. This was the motivating use case for the\nxdress project.TestingXDress has two major test types: unit tests which test library functionality and\nintegration tests which test the command line tool, the parsers, compilers, etc.\nThe unit tests are generally fast while the integration are slower. From thetests/directory you may use nose to run the tests together or individually:# Go into the tests dir\n$ cd tests\n\n# Run just the unit tests\ntests $ nosetests -a unit\n\n# Run just the integration tests\ntests $ nosetests -a integration\n\n# Run all of the tests together\ntests $ nosetestsNote that the integration tests require CMake in order to build the sample\nprojects.Contact UsIf you have questions or comments, please sign up for the the mailing list\nathttps://groups.google.com/forum/#!forum/xdressand send an email toxdress@googlegroups.com. Alternatively, please contact the authors directly or\nopen an issue on GitHub.ContributingWe highly encourage contributions to xdress! If you would like to contribute,\nit is as easy as forking the repository on GitHub, making your changes, and\nissuing a pull request. If you have any questions about this process don\u2019t\nhesitate to ask the mailing list (xdress@googlegroups.com).Helpful LinksDocumentationMailing list websiteMailing list address"} +{"package": "xdrgen", "pacakge-description": "No description available on PyPI."} +{"package": "xdrlib2", "pacakge-description": "No description available on PyPI."} +{"package": "xdrlib3", "pacakge-description": "xdrlib3A forked version ofxdrlib, a module for encoding and decoding XDR (External Data Representation) data in Python.xdrlibis planned to be removed in Python 3.13 and later versions, therefore this fork has been created to add type hints and maintain compatibility with future versions of Python.InstallationYou can installxdrlib3using pip:pipinstallxdrlib3Usagexdrlib3has the same functions and methods asxdrlib. Here's an example of how to use it:importxdrlib3packer=xdrlib3.Packer()packer.pack_int(16)packed_data=packer.get_buffer()unpacker=xdrlib3.Unpacker(packed_data)unpacked_data=unpacker.unpack_int()Licensexdrlib3is a fork ofxdrlib, so please refer tothe LICENSE filefor the original code's licensing agreement, while other parts of the code are released under the MIT license."} +{"package": "xdrone", "pacakge-description": "This project is available onGithubandPypi.To UseRunpip install xdronefor to install the xdrone package.Then runxdrone [--validate | --simulate | --fly] --code --config to validate the code, simulate in the simulator, or fly real drones.Note that to run the simulation,xDroneWebSimulatormust be running on the localhost.Runxdrone --helpfor more information.To DevelopClone the Github repo for the source code.The terminal commands are similar as before, but withxdronereplaced bypython -m cmdline.xdrone, e.g.python -m cmdline.xdrone --helpLanguage SpecPlease readxDrone Spec."} +{"package": "xdrparser", "pacakge-description": "xdrparserCommand line tool to parse the .xdr files written to the history archive of a stellar-core and print their data as json.CompatibilityPython >= 3.4Tested on Linux, Mac OS, and Windows.InstallationFrom PyPI:pip install xdrparserFrom the repository:pip install git+git://github.com/kinecosystem/xdrparser#egg=xdrparserUsage$ xdrparser --help\n\nUsage: xdrparser [OPTIONS] XDR_FILE\n\n Command line tool to parse Stellar's xdr history files.\n\nOptions:\n --with-hash Calculate tx hashes, only for a 'transactions' xdr file,\n must be used with --network-id\n --network-id TEXT Network-id/network paraphrase, needed for --with-hash\n --indent INTEGER Number of spaces to indent the json output with\n --help Show this message and exit."} +{"package": "xdr-parser", "pacakge-description": "XDR-Parser"} +{"package": "xdrt", "pacakge-description": "XDRT (XDR Tools)XDRT is a python toolkit to work with the XDR file format used e.g. by Elekta to store cone-beam CT images and as reconstructed by XVI.\nThe reading of.xvifiles is also supported, allowing to find the map the XDR file to the moment of acquistion\n(which fraction, what type of scan).Free software: Apache Software License 2.0. Decompression library is public domain, but has a differentlicense.Documentation:https://docs.aiforoncology.nl/xdrt/.FeaturesUtilities to read (compressed) 3D and 4D XDR files in python.Ability to read XVI files and link planning scans with cone-beam CT scans.xdr2imgcommand line utility to convert xdr images to ITK supported formats.xvi2imgcommand line utility converts all fractions to ITK supported formats.How to useThe package needs to compile the decompression library, which can be done with:python setup.py installor withpip install git+https://github.com/NKI-AI/xdrt.gitor from PyPi usingpip install xdrt.The command line programxdr2img image.xdr image.nrrdconverts images from XDR\nto any ITK supported format. For more details checkxdr2img --help.The command line programxvi2imgreads XVI files and combined with the XDR files, writes\nto a new directory and image format. For more details checkxvi2img --help.Work in progressThis package is work in progress, if you have an image which is not properly parsed\nbyxdrt, create an issue with the image and expected output.The following is not yet supported:Origin is not yet always properly parsed.Onlyuniformgrids are currently supported.Protocol is not detected from the XVI file (e.g. 4D-CBCT + SBRT). Images in fraction are output consecutively.Create anissueif this is an urgent issue for you."} +{"package": "xds", "pacakge-description": "Python codes for loading xds data structure"} +{"package": "xdserver", "pacakge-description": "Durusis an object database for Python. It allows multiple clients\nto operate on a single database via a wire protocol, and allows one\nprocess at a time to directly access a database file.xdserver is a client/server extension for Durus providing these\nenhancements:Serve multiple databases with one server process. Operate on\nmultiple databases with one connection.Asynchronous server, usingcogento offer platform-specific\nperformance enhancements.Adevelopment versionis available."} +{"package": "xdsl", "pacakge-description": "xDSL: A Python-native SSA Compiler FrameworkxDSLis a Python-native compiler framework built around\nSSA-based intermediate representations (IRs). Users of xDSL build a compiler by\nassembling predefined domain-specific IRs and, optionally, defining their own custom IRs. xDSL uses multi-level IRs, meaning\nthat during the compilation process, a program will be lowered through several\nof these IRs. This allows the implementation of abstraction-specific\noptimization passes, similar to the structure of common DSL compilers (such as\nDevito, Psyclone, and Firedrake). To simplify the writing of these passes, xDSL\nuses a uniform data structure based on SSA, basic blocks, and regions, which\nadditionally enables the writing of generic passes.The design of xDSL is influenced byMLIR, a compiler\nframework developed in C++, that is part of the LLVM project. An inherent\nadvantage of a close design is the easy interaction between the two frameworks,\nmaking it possible to translate abstractions and programs back and forth. This\nresults in one big SSA-based abstraction ecosystem that can be worked with\nthrough Python, making analysis through simple scripting languages possible.\nAdditionally, xDSL can leverage MLIR's code generation and low-level\noptimization capabilities.InstallationGetting StartedxDSL Developer SetupDeveloper InstallationTestingFormattingInstallationTo use xDSL as part of a larger project for developing your own compiler,\njust installxDSL via pip:pipinstallxdslNote:This version of xDSL is validated against a specific MLIR version,\ninteroperability with other versions may result in problems. The supported\nMLIR version is commit98e674c9f16d677d95c67bc130e267fae331e43c.Getting StartedTo get familiar with xDSL, we recommend starting with our Jupyter notebooks. The\nnotebooks consist of examples and documentation concerning the core xDSL data\nstructures and the xDSL's Python-embedded abstraction definition language, as\nwell as examples of implementing custom compilers, like a database compiler.\nThere also exists a small documentation showing how to connect xDSL with MLIR\nfor users interested in that use case.A Database exampleA simple introductionA DSL for defining new IRsConnecting xDSL with MLIRWe provide a Makefile containing a lot of common tasks, which might provide\nan overview of common actions.xDSL Developer SetupTo contribute to the development of xDSL follow the subsequent steps.Developer Installationgitclonehttps://github.com/xdslproject/xdsl.gitcdxdsl# set up the venv and install everythingmakevenv# activate the venvsourcevenv/bin/activateTestingThe xDSL project uses pytest unit tests and LLVM-style filecheck tests. They can\nbe executed from the root directory:# Executes pytests which are located in tests/pytest# Executes filecheck testslittests/filecheck# run all tests using makefilemaketestsFormatting and TypecheckingAll python code used in xDSL usesblackto\nformat the code in a uniform manner.To automate the formatting, we use pre-commit hooks from thepre-commitpackage.# Install the pre-commit on your `.git` foldermakeprecommit-install# to run the hooks:makeprecommit# alternatively, running black on all staged files:makeblack# or simply black $(git diff --staged --name-only)Furthermore, all python code must run throughpyrightwithout errors. Pyright can be run on all staged files through the\nmakefile usingmake pyright.DiscussionYou can also join the discussion at ourZulip chat room, kindly supported by community hosting fromZulip."} +{"package": "xdsmjs", "pacakge-description": "Python module to distribute [XDSMjs](https://github.com/OneraHub/XDSMjs#xdsmjs) js/css resources"} +{"package": "xdspider", "pacakge-description": "No description available on PyPI."} +{"package": "xds-protos", "pacakge-description": "Package \u201cxds-protos\u201d is a collection of ProtoBuf generated Python files for xDS protos (or thedata-plane-api). You can find the source code of this project ingrpc/grpc. For any question or suggestion, please post tohttps://github.com/grpc/grpc/issues.Each generated Python file can be imported according to their proto package. For example, if we are trying to import a proto located at \u201cenvoy/service/status/v3/csds.proto\u201d, whose proto package is \u201cpackage envoy.service.status.v3\u201d, then we can import it as:# Import the message definitions\nfrom envoy.service.status.v3 import csds_pb2\n# Import the gRPC service and stub\nfrom envoy.service.status.v3 import csds_pb2_grpc"} +{"package": "xdtools", "pacakge-description": "UNKNOWN"} +{"package": "xdtransform", "pacakge-description": "usage: xdtransform [-h] [-s SOURCE] [-d DESTINATION] -t TRANSFORM\n\noptional arguments:\n -h, --help show this help message and exit\n -s SOURCE, --source SOURCE\n The source XML file (you can specify - to mean stdin)\n -d DESTINATION, --destination DESTINATION\n The destination XML file (you can specify - to mean stdout)\n -t TRANSFORM, --transform TRANSFORM\n The transformation XML file"} +{"package": "xdtreader", "pacakge-description": "No description available on PyPI."} +{"package": "xdump", "pacakge-description": "XDumpXDump is a utility to make a consistent partial dump and load it into the database.The idea is to provide an ability to specify what to include in the dump via SQL queries.InstallationXDump can be obtained withpip:$ pip install xdumpUsage exampleMake a dump (on production replica for example):>>>fromxdump.postgresqlimportPostgreSQLBackend>>>>>>backend=PostgreSQLBackend(dbname='app_db',user='prod',password='pass',host='127.0.0.1',port='5432')>>>backend.dump('/path/to/dump.zip',full_tables=['groups'],partial_tables={'employees':'SELECT * FROM employees ORDER BY id DESC LIMIT 2'})Load a dump on your local machine:>>>backend=PostgreSQLBackend(dbname='app_db',user='local',password='pass',host='127.0.0.1',port='5432')# If you need a clear DB>>>backend.recreate_database()# or `backend.truncate()`>>>backend.load('/path/to/dump.zip')Dump is compressed by default. Compression level could be changed with passingcompressionargument todumpmethod.\nValid options arezipfile.ZIP_STORED,zipfile.ZIP_DEFLATED,zipfile.ZIP_BZIP2andzipfile.ZIP_LZMA.The verbosity of the output could be customized viaverbosity(with values 0, 1 or 2) argument of a backend class.There are two options to control the content of the dump:dump_schema- controls if the schema should be includeddump_data- controls if the data should be includedAutomatic selection of related objectsYou don\u2019t have to specify all queries for related objects - XDump will load them for you automatically. It covers\nboth, recursive and non-recursive relations.\nFor example, if theemployeestable has foreign keysgroup_id(togroupstable) andmanager_id(toemployeestable) the resulting dump will have all objects related to selected employees\n(as well as for objects related to related objects, recursively).Command Line Interfacexloadprovides an ability to create a dump.Signature:xdump[postgres|sqlite][OPTIONS]Common options:-o, --output TEXT output file name [required]\n-f, --full TEXT table name to be fully dumped. Could be used\n multiple times\n-p, --partial TEXT partial tables specification in a form\n \"table_name:select SQL\". Could be used\n multiple times\n-c, --compression [deflated|stored|bzip2|lzma]\n dump compression level\n--schema / --no-schema include / exclude the schema from the dump\n--data / --no-data include / exclude the data from the dump\n-D, --dbname TEXT database to work with [required]\n-v, --verbosity verbosity levelPostgreSQL-specific options:-U, --user TEXT connect as specified database user\n [required]\n-W, --password TEXT password for the DB connection\n-H, --host TEXT database server host or socket directory\n-P, --port TEXT database server port numberxloadloads a dump into a database.Signature:xload[postgres|sqlite][OPTIONS]Common options:-i, --input TEXT input file name [required]\n-m, --cleanup-method [recreate|truncate]\n method of DB cleaning up\n-D, --dbname TEXT database to work with [required]\n-v, --verbosity verbosity levelPostgreSQL-specific options are the same as forxdump.RDBMS supportAt the moment only the following are supported:PostgreSQLSQLite >= 3.8.3Django supportAddxdump.extra.djangoto yourINSTALLED_APPSsettings:INSTALLED_APPS=[...,'xdump.extra.django',]AddXDUMPto your project settings file. It should contain minimum two entries:FULL_TABLES - a list of tables that should be fully dumped.PARTIAL_TABLES - a dictionary withtable_name:select SQLXDUMP={'FULL_TABLES':['groups'],'PARTIAL_TABLES':{'employees':'SELECT * FROM employees WHERE id > 100'}}Optionally you could use a custom backend:XDUMP={...,'BACKEND':'importable.string',}Runxdumpcommand:$ ./manage.py xdump dump.zipRunxloadcommand:$ ./manage.py xload dump.zipPossible options to both commands:-a/--alias- allows you to choose database config fromDATABASES, that is used during the execution;-b/--backend- importable string, that leads to custom dump backend class.Options forxdumpcommand:-s/--dump-schema- controls if the schema should be included;-d/--dump-data- controls if the data should be included.Options forxloadcommand:-m/--cleanup-method- optionally re-creates DB or truncates the data.NOTE. If the dump has no schema inside, DB won\u2019t be re-created.The followingmakecommand could be useful to get a configured dump from production to your local machine:sync-production:ssh-t$(TARGET)\"DJANGO_SETTINGS_MODULE=settings.production /path/to/manage.py xdump /tmp/dump.zip\"scp$(TARGET):/tmp/dump.zip./dump.zipssh-t$(TARGET)\"rm /tmp/dump.zip\"DJANGO_SETTINGS_MODULE=settings.local$(PYTHON)manage.pyxload./dump.zipAnd the usage is:$makesync-productionTARGET=john@production.comPYTHON=/path/to/python/in/venvPython supportXDump supports Python 2.7, 3.4 - 3.7 and PyPy 2 & 3."} +{"package": "xdutools", "pacakge-description": "No description available on PyPI."} +{"package": "xdv", "pacakge-description": "ContentsIntroductionInstallationRules file syntaxandandOrder of rule executionBehaviour if theme or content is not matchedAdvanced usageConditional rulesIncluding external contentModifying the theme on the flyInline XSL directivesXIncludeCompilationAbsolute prefixTesting the compiled themeCompiling the theme in Python codeDeploymentPloneWSGInginxIncluding external contentVarnishApacheChangelog0.3 - 2010-05-290.3rc2 - 2010-05-250.3rc1 - 2010-05-23IntroductionXDV is an implementation of theDeliveranceconcept using pure XSLT. In\nshort, it is a way to apply a style/theme contained in a static HTML web page\n(usually with related CSS, JavaScript and image resources) to a dynamic\nwebsite created using any server-side technology.Consider a scenario where you have a dynamic website, to which you want to\napply a theme built by a web designer. The web designer is not familiar with\nthe technology behind the dynamic website, and so has supplied a \u201cstatic HTML\u201d\nversion of the site. This consists of an HTML file with more-or-less semantic\nmarkup, one or more style sheets, and perhaps some other resources like\nimages or JavaScript files.Using XDV, you could apply this theme to your dynamic website as follows:Identify the placeholders in the theme file that need to be replaced with\ndynamic elements. Ideally, these should be clearly identifiable, for\nexample with a unique HTMLidattribute.Identify the corresponding markup in the dynamic website. Then write a\n\u201creplace\u201d or \u201ccopy\u201d rule using XDV\u2019s rules syntax that replaces the theme\u2019s\nstatic placeholder with the dynamic content.Identify markup in the dynamic website that should be copied wholesale into\nthe theme. CSS and JavaScript links in theare often treated\nthis way. Write an XDV \u201cappend\u201d or \u201cprepend\u201d rule to copy these elements\nover.Identify parts of the theme and/or dynamic website that are superfluous.\nWrite an XDV \u201cdrop\u201d rule to remove these elements.The rules file is written using a simple XML syntax. Elements in the theme\nand \u201ccontent\u201d (the dynamic website) can be identified using CSS3 or XPath\nselectors.Once you have a theme HTML file and a rules XML file, you compile these using\nthe XDV compiler into a single XSLT file. You can then deploy this XSLT file\nwith your application. An XSLT processor (such as mod_transform in Apache)\nwill then transform the dynamic content from your website into the themed\ncontent your end users see. The transformation takes place on-the-fly for\neach request.Bear in mind that:You never have to write, or even read, a line of XSLT (unless you want to).The XSLT transformation that takes place for each request is very fast.Static theme resources (like images, stylesheets or JavaScript files) can\nbe served from a static webserver, which is normally much faster than\nserving them from a dynamic application.You can leave the original theme HTML untouched, with makes it easier to\nre-use for other scenarios. For example, you can stitch two unrelated\napplications together by using a single theme file with separate rules\nfiles. This would result in two compiled XSLT files. You could use location\nmatch rules or similar techniques to choose which one to invoke for a given\nrequest.We will illustrate how to set up XDV for deployment below.InstallationTo install XDV, you should install thexdvegg. You can do that usingeasy_install,piporzc.buildout. For example, usingeasy_install(ideally in avirtualenv):$ easy_install -U xdvIf usingzc.buildout, you can use the followingbuildout.cfgas a\nstarting point. This will ensure that the console scripts are installed,\nwhich is important if you need to execute the XDV compiler manually:[buildout]\nparts =\n xdv\n\n[xdv]\nrecipe = zc.recipe.egg\neggs = xdvNote thatlxmlis a dependency ofxdv, so you may need to install the\nlibxml2 and libxslt development packages in order for it to build. On\nDebian/Ubuntu you can run:$ sudo apt-get install libxslt1-devOn some operating systems, notably Mac OS X, installing a \u201cgood\u201dlxmlegg\ncan be problematic, due to a mismatch in the operating system versions of thelibxml2andlibxsltlibraries thatlxmluses. To get around that,\nyou can compile a staticlxmlegg using the following buildout recipe:[buildout]\n# lxml should be first in the parts list\nparts =\n lxml\n xdv\n\n[lxml]\nrecipe = z3c.recipe.staticlxml\negg = lxml\nlibxml2-url = http://xmlsoft.org/sources/libxml2-2.7.6.tar.gz\nlibxslt-url = http://xmlsoft.org/sources/libxslt-1.1.26.tar.gz\n\n[xdv]\nrecipe = zc.recipe.egg\neggs = xdvOnce installed, you should findxdvcompilerandxdvrunin yourbindirectory.Rules file syntaxThe rules file, conventionally calledrules.xml, is rooted in a tag\ncalled:\n\n\n ...\n\nHere we have defined two namespaces: the default namespace is used for rules\nand XPath selectors. Thecssnamespace is used for CSS3 selectors. These\nare functionally equivalent. In fact, CSS selectors are replaced by the\nequivalent XPath selector during the pre-processing step of the compiler.\nThus, they have no performance impact.XDV supports complex CSS3 and XPath selectors, including things like thenth-childpseudo-selector. You are advised to consult a good reference\nif you are new to XPath and/or CSS3.The following elements are allowed inside theelement:Used to replace an element in the theme entirely with an element in the\ncontent. For example:The (near-)equivalent using CSS selectors would be:The result of either is that theelement in the theme is\nreplaced with the<title />element in the (dynamic) content.<copy />Used to replace the contents of a placeholder tag with a tag from the\ntheme. For example:<copy css:theme=\"#main\" css:content=\"#portal-content > *\" />This would replace any placeholder content inside the element with idmainin the theme with all children of the element with idportal-contentin the content. The usual reason for using<copy />instead of<replace />, is that the theme has CSS styles or other\nbehaviour attached to the target element (with idmainin this case).<append />and<prepend />Used to copy elements from the content into an element in the theme,\nleaving existing content in place.<append />places the matched\ncontent directly before the closing tag in the theme;<prepend />places\nit directly after the opening tag. For example:<append theme=\"/html/head\" content=\"/html/head/link\" />This will copy all<link />elements in the head of the content into\nthe theme.As a special case, you can copy individualattributesfrom a content\nelement to an element in the theme using<prepend />:<prepend theme=\"/html/body\" content=\"/html/body/@class\" />This would copy theclassattribute of the<body />element in\nthe content into the theme (replacing an existing attribute with the\nsame name if there is one).<before />and<after />These are equivalent to<append />and<prepend />, but place\nthe matched content before or after the matched theme element, rather\nthan immediately inside it. For example:<before css:theme=\u201d#content\u201d css:content=\u201d#info-box\u201d />This would place the element with idinfo-boxfrom the content\nimmediately before the element with idcontentin the theme. If we\nwanted the box below the content instead, we could do:<after css:theme=\"#content\" css:content=\"#info-box\" /><drop />Used to drop elements from the theme or the content. This is the only\nelement that accepts eitherthemeorcontentattributes (or theircss:equivalents), but not both:<drop css:content=\"#portal-content .about-box\" />\n<copy css:theme=\"#content\" css:content=\"#portal-content > *\" />This would copy all children of the element with idportal-contentin\nthe theme into the element with idcontentin the theme, but only\nafter removing any element with classabout-boxinside the content\nelement first. Similarly:<drop theme=\"/html/head/base\" />Would drop the<base />tag from the head of the theme.Order of rule executionIn most cases, you should not care too much about the inner workings of the\nXDV compiler. However, it can sometimes be useful to understand the order\nin which rules are applied.<before />rules are always executed first.<drop />rules are executed next.<replace />rules are executed next, provided no<drop />rule was\napplied to the same theme node.<prepend />,<copy />and<append />rules execute next,\nprovided no<replace />rule was applied to the same theme node.<after />rules are executed last.Behaviour if theme or content is not matchedIf a rule does not match the theme (whether or not it matches the content),\nit is silently ignored.If a<replace />rule matches the theme, but not the content, the matched\nelement will be dropped in the theme:<replace css:theme=\"#header\" content=\"#header-element\" />Here, if the element with idheader-elementis not found in the content,\nthe placeholder with idheaderin the theme is removed.Similarly, the contents of a theme node matched with a<copy />rule will\nbe dropped if there is no matching content. Another way to think of this is\nthat if no content node is matched, XDV uses an empty nodeset when copying or\nreplacing.If you want the placeholder to stay put in the case of a missing content node,\nyou can make this a conditional rule:<replace css:theme=\"#header\" content=\"#header-element\" if-content=\"\" />See below for more details on conditional rules.Advanced usageThe simple rules above should suffice for most use cases. However, there are\na few more advanced tools at your disposal, should you need them.Conditional rulesSometimes, it is useful to apply a rule only if a given element appears or\ndoes not appear in the markup. Theif-contentattribute can be used with\nany rule to make it conditional.if-contentshould be set an XPath expression. You can also usecss:if-contentwith a CSS3 expression. If the expression matches a node\nin the content, the rule will be applied:<copy css:theme=\"#portlets\" css:content=\".portlet\"/>\n<drop css:theme=\"#portlet-wrapper\" if-content=\"not(//*[@class='portlet'])\"/>This will copy all elements with classportletinto theportletselement. If there are no matching elements in the content we drop theportlet-wrapperelement, which is presumably superfluous.Here is another example using CSS selectors:<copy css:theme=\"#header\" css:content=\"#header-box > *\"\n css:if-content=\"#personal-bar\"/>This will copy the children of the element with idheader-boxin the\ncontent into the element with idheaderin the theme, so long as an\nelement with idpersonal-baralso appears somewhere in the content.Above, we also saw the special case of an emptyif-content(which also\nworks with an emptycss:if-content). This is a shortcut that means \u201cuse\nthe expression in thecontentorcss:content`attribute as the\ncondition\u201d. Hence the following two rules are equivalent:<copy css:theme=\"#header\" css:content=\"#header-box > *\"\n css:if-content=\"#header-box > *\"/>\n<copy css:theme=\"#header\" css:content=\"#header-box > *\"\n css:if-content=\"\"/>If multiple rules of the same type match the same theme node but have\ndifferentif-contentexpressions, they will be combined as an\nif..else if\u2026else block:<copy theme=\"/html/body/h1\" content=\"/html/body/h1/text()\"\n if-content=\"/html/body/h1\"/>\n<copy theme=\"/html/body/h1\" content=\"//h1[@id='first-heading']/text()\"\n if-content=\"//h1[@id='first-heading']\"/>\n<copy theme=\"/html/body/h1\" content=\"/html/head/title/text()\" />These rules all attempt to fill the text in the<h1 />inside the body.\nThe first rule looks for a similar<h1 />tag and uses its text. If that\ndoesn\u2019t match, the second rule looks for any<h1 />with idfirst-heading, and uses its text. If that doesn\u2019t match either, the\nfinal rule will be used as a fallback (since it has noif-content),\ntaking the contents of the<title />tag in the head of the content\ndocument.Including external contentNormally, thecontentattribute of any rule selects nodes from the\nresponse being returned by the underlying dynamic web server. However, it is\npossible to include content from a different URL using thehrefattribute\non any rule (other than<drop />). For example:<append css:theme=\"#left-column\" css:content=\"#portlet\" href=\"/extra.html\"/>This will resolve the URL/extra.html, look for an element with idportletand then append to to the element with idleft-columnin the\ntheme.The inclusion can happen in one of three ways:Using the XSLTdocument()function. This is the default, but it can\nbe explicitly specified by adding an attributemethod=\"document\"to the\nrule element. Whether this is able to resolve the URL depends on how and\nwhere the compiled XSLT is being executed:<append css:theme=\"#left-column\" css:content=\"#portlet\"\n href=\"/extra.html\" method=\"document\" />Via a Server Side Include directive. This can be specified by setting themethodattribute tossi:<append css:theme=\"#left-column\" css:content=\"#portlet\"\n href=\"/extra.html\" method=\"ssi\"/>The output will look something like this:<!--# include wait=\"yes\" virtual=\"/extra.html?;filter_xpath=//*[@id%20=%20'portlet']\" -->This SSI instruction would need to be processed by a fronting web server\nsuch as Apache or nginx. Also note the;filter_xpathquery string\nparameter. Since we are deferring resolution of the referenced document\nuntil SSI processing takes place (i.e. after the compiled XDV XSLT transform\nhas executed), we need to ask the SSI processor to filter out elements in\nthe included file that we are not interested in. This requires specific\nconfiguration. An example for nginx is included below.For simple SSI includes of a whole document, you may omit thecontentselector from the rule:<append css:theme=\"#left-column\" href=\"/extra.html\" method=\"ssi\"/>The output then renders like this:<!--# include wait=\"yes\" virtual=\"/extra.html\" -->Via an Edge Side Includes directive. This can be specified by setting themethodattribute toesi:<append css:theme=\"#left-column\" css:content=\"#portlet\"\n href=\"/extra.html\" method=\"esi\"/>The output is similar to that for the SSI mode:<esi:include src=\"/extra.html?;filter_xpath=//*[@id%20=%20'portlet']\"></esi:include>Again, the directive would need to be processed by a fronting server, such\nas Varnish. Chances are an ESI-aware cache server would not support\narbitrary XPath filtering. If the referenced file is served by a dynamic\nweb server, it may be able to inspect the;filter_xpathparameter and\nreturn a tailored response. Otherwise, if a server that can be made aware\nof this is placed in-between the cache server and the underlying web server,\nthat server can perform the necessary filtering.For simple ESI includes of a whole document, you may omit thecontentselector from the rule:<append css:theme=\"#left-column\" href=\"/extra.html\" method=\"esi\"/>The output then renders like this:<esi:include src=\"/extra.html\"></esi:include>Modifying the theme on the flySometimes, the theme is almost perfect, but cannot be modified, for example\nbecause it is being served from a remote location that you do not have access\nto, or because it is shared with other applications.XDV allows you to modify the theme using \u201cinline\u201d markup in the rules file.\nYou can think of this as a rule where the matchedcontentis explicitly\nstated in the rules file, rather than pulled from the response being styled.For example:<xdv:rules\n xmlns:xdv=\"http://namespaces.plone.org/xdv\"\n xmlns:css=\"http://namespaces.plone.org/xdv+css\"\n xmlns:xsl=\"http://www.w3.org/1999/XSL/Transform\"\n >\n\n <xdv:append theme=\"/html/head\">\n <style type=\"text/css\">\n /* From the rules */\n body > h1 { color: red; }\n </style>\n </xdv:append>\n\n</xdv:rules>Notice how we have placed the rules in an explicitxdvnamespace, so that\nwe can write the \u201cinline\u201d HTML without a namespace prefix.In the example above, the<append />rule will copy the<style />attribute and its contents into the<head />of the theme. Similar rules\ncan be constructed for<copy />,<replace />,<prepend />,<before />or<after />.It is even possible to insert XSLT instructions into the compiled theme in\nthis manner. Having declared thexslnamespace as shown above, we can do\nsomething like this:<xdv:replace css:theme=\"#details\">\n <dl id=\"details\">\n <xsl:for-each css:select=\"table#details > tr\">\n <dt><xsl:copy-of select=\"td[1]/text()\"/></dt>\n <dd><xsl:copy-of select=\"td[2]/node()\"/></dd>\n </xsl:for-each>\n </dl>\n</xdv:replace>Note that css expressions are converted to \u201cplaceless\u201d XPath expressions,\nsocss:select=\"table#details> tr\"converts toselect=\"//table[@id='details]/tr\". This means it would not be possible to\nusecss:select=\"td:first-child> *\"as you want a relative selector here.\nYou can, of course, just use a manual XPath in aselectattribute instead.Inline XSL directivesYou may supply inline XSL directives in the rules to tweak the final output,\nfor instance to strip space from the output document use:<rules xmlns:xsl=\"http://www.w3.org/1999/XSL/Transform\">\n\n <xsl:strip-space elements=\"*\" />\n\n</rules>Note: this may effect the rendering of the page on the browser.To use a strict doctype:<xsl:output\n doctype-public=\"-//W3C//DTD XHTML 1.0 Strict//EN\"\n doctype-system=\"http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd\"/>XIncludeYou may wish to re-use elements of your rules file across multiple themes.\nThis is particularly useful if you have multiple variations on the same theme\nused to style different pages on a particular website.Rules files may be included using the XInclude protocol.Inclusions use standard XInclude syntax. For example:<rules\n xmlns=\"http://namespaces.plone.org/xdv\"\n xmlns:css=\"http://namespaces.plone.org/xdv+css\"\n xmlns:xi=\"http://www.w3.org/2001/XInclude\">\n\n <xi:include href=\"standard-rules.xml\" />\n\n</rules>CompilationOnce you have written your rules file, you need to compile it to an XSLT for\ndeployment. In some cases, you may have an application server that does this\non the fly, e.g. if you are using thecollective.xdvpackage with Plone.\nFor deployment to a web server like Apache or nginx, however, you will need\nto perform this step manually.The easiest way to invoke the XDV compiler is via thexdvcompilercommand\nline script which is installed with thexdvegg. To see its help output,\ndo:$ bin/xdvcompiler --helpTo run the compiler withrules.xmloperating ontheme.html:$ bin/xdvcompiler rules.xml theme.htmlThis will print the compiled XSLT file to the standard output. You can save\nit to a file instead using:$ bin/xdvcompiler -o theme.xsl rules.xml theme.htmlThe following command line options are available:Use-pto pretty-print the output for improved readability. There is a\nrisk that this could alter rendering in the browser, though, as browsers\nare sensitive to some kinds of whitespace.Use-ato set an absolute prefix - see below.Use-ito set the default external file inclusion mode to one ofdocument,ssioresi.Use--traceto output trace logging during the compilation step. This\ncan be helpful in debugging rules.Check the output of the--helpoption for more details.Absolute prefixThe compiler can be passed an \u201cabsolute prefix\u201d. This is a string that will be\nprefixed to anyrelativeURL referenced an image, link or stylesheet in the\ntheme HTML file, before the theme is passed to the compiler. This allows a\ntheme to be written so that it can be opened and views standalone on the\nfilesystem, even if at runtime its static resources are going to be served\nfrom some other location.For example, say the theme is written with relative URLs for images and\nexternal resources, such as<imgsrc=\"images/foo.jpg\"/>. When the\ncompiled theme is applied to a live site, this is unlikely to work for\nany URL other than a sibling of theimagesfolder.Let\u2019s say the theme\u2019s static resources are served from a simple web server\nand made available under the directory/static. In this case, we can\nset an absolute prefix of/static. This will modify the<img />tag\nin the compiled theme so that it becomes an absolute path that will work for\nany URL:<imgsrc=\"/static/images/foo.jpg\"/>Testing the compiled themeTo test the compiled theme, you can apply it to a static file representing\nthe content. The easiest way to do this is via thexdvrunscript:$ bin/xdvrun theme.xsl content.htmlThis will print the output to the standard output. You can save it to a file\ninstead with:$ bin/xdvrun -o output.html theme.xsl content.htmlFor testing, you can also compile and run the theme in one go, by using the-r(rules) and-t(theme) arguments toxdvrun:$ bin/xdvrun -o output.html -r rules.xml -t theme.html content.htmlTo see the built-in help for this command, run:$ bin/xdvrun --helpCompiling the theme in Python codeYou can run the XDV compiler from Python code using the following helper\nfunction:>>> from xdv.compiler import compile_themeThis method takes the following arguments:rulesis the rules file, given either as a file name or a string with\nthe file contents.themeis the theme file, given either as a file name or a string with\nthe file contentsextrais an optional XSLT file with XDV extensions, given as a URI\n(depracated, use inline xsl in the rules instead)csscan be set to False to disable CSS syntax support (providing a\nmoderate speed gain)xincludecan be set toFalseto enable XInclude support (at a\nmoderate speed cost). If enabled, XInclude syntax can be used to split the\nrules file into multiple, re-usable fragments.absolute_prefixcan be set an string to be used as the \u201cabsolute prefix\u201d\nfor relative URLs - see above.updatecan be set toFalseto disable the automatic update support\nfor the old Deliverance 0.2 namespace (for a moderate speed gain)tracecan be set to True to enable compiler trace informationincludemodecan be set to \u2018document\u2019, \u2018esi\u2019 or \u2018ssi\u2019 to change the way\nin which includes are processedparsercan be set to an lxml parser instance; the default is an\nHTMLParsercompiler_parser`can be set to an lxml parser instance; the default is a\nXMLParserrules_parsercan be set to an lxml parser instance; the default is a\nXMLParse.The parser parameters may be used to add custom resolvers for external content\nif required. See thelxmldocumentation for\ndetails.compile_theme()returns an XSLT document inlxml\u2019sElementTreeformat. To set up a transform representing the theme and rules, you can do:from lxml import etree\nfrom xdv.compiler import compile_theme\n\nabsolute_prefix = \"/static\"\n\nrules = \"rules.xml\"\ntheme = \"theme.html\"\n\ncompiled_theme = compile_theme(rules, theme,\n absolute_prefix=absolute_prefix)\n\ntransform = etree.XSLT(compiled_theme)You can now use this transformation:content = etree.parse(some_content)\ntransformed = transform(content)\n\noutput = etree.tostring(transformed)Please see thelxmldocumentation for more details.DeploymentBefore it can be used, the deployed theme needs to be deployed to a proxying\nweb server which can apply the XSLT to the response coming back from another\nweb application.In theory, any XSLT processor will do. In practice, however, most websites\ndo not produce 100% well-formed XML (i.e. they do not conform to the XHTML\n\u201cstrict\u201d doctype). For this reason, it is normally necessary to use an XSLT\nprocessor that will parse the content using a more lenient parser with some\nknowledge of HTML. libxml2, the most popular XML processing library on Linux\nand similar operating systems, contains such a parser.PloneIf you are working with Plone, the easiest way to use XDV is via thecollective.xdvadd-on. This\nprovides a control panel for configuring the XDV rules file, theme and\nother options, and hooks into a transformation chain that executes after\nPlone has rendered the final page to apply the XDV transform.Even if you intend to deploy the compiled theme to another web server,collective.xdvis a useful development tool: so long as Zope is in\n\u201cdevelopment mode\u201d, it will re-compile the theme on the fly, allowing you\nto make changes to theme and rules on the fly. It also provides some tools\nfor packaging up your theme and deploying it to different sites.WSGIIf you are using a WSGI stack, you can use thedv.xdvservermiddleware to apply an XDV\ntheme. This supports all the core XDV options, and can be configured to\neither re-compile the theme on the fly (useful for development), or compile\nit only once (useful for deployment.)It is also possible to use this with the Pasteproxymiddleware to\ncreate a standalone XDV proxy for any site. See thedv.xdvserverdocumentation for details.nginxTo deploy an XDV theme to thenginxweb server, you\nwill need to compile nginx with a special version of the XSLT module that\ncan (optionally) use the HTML parser from libxml2.In the future, the necessary patches to enable HTML mode parsing will\nhopefully be part of the standard nginx distribution. In the meantime,\nthey are maintained in thehtml-xsltproject.Using a properly patched nginx, you can configure it with XSLT support like\nso:$ ./configure --with-http_xslt_moduleIf you are using zc.buildout and would like to build nginx, you can start\nwith the following example:[buildout]\nparts =\n ...\n nginx\n\n...\n\n[nginx]\nrecipe = zc.recipe.cmmi\nurl = http://html-xslt.googlecode.com/files/nginx-0.7.65-html-xslt-2.tar.gz\nextra_options =\n --conf-path=${buildout:directory}/etc/nginx.conf\n --sbin-path=${buildout:directory}/bin\n --error-log-path=${buildout:directory}/var/log/nginx-error.log\n --http-log-path=${buildout:directory}/var/log/nginx-access.log\n --pid-path=${buildout:directory}/var/nginx.pid\n --lock-path=${buildout:directory}/var/nginx.lock\n --with-http_stub_status_module\n --with-http_xslt_moduleIf libxml2 or libxslt are installed in a non-standard location you may need to\nsupply the--with-libxml2=<path>and--with-libxslt=<path>options.\nThis requires that you set an appropriateLD_LIBRARY_PATH(Linux / BSD) orDYLD_LIBRARY_PATH(Mac OS X) environment variable when running nginx.For theming a static site, enable the XSLT transform in the nginx\nconfiguration as follows:location / {\n xslt_stylesheet /path/to/compiled-theme.xsl;\n xslt_html_parser on;\n xslt_types text/html;\n}nginx may also be configured as a transforming proxy server:location / {\n xslt_stylesheet /path/to/compiled-theme.xsl;\n xslt_html_parser on;\n xslt_types text/html;\n rewrite ^(.*)$ /VirtualHostBase/http/localhost/Plone/VirtualHostRoot$1 break;\n proxy_pass http://127.0.0.1:8080;\n proxy_set_header Host $host;\n proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;\n proxy_set_header X-XDV \"true\";\n proxy_set_header Accept-Encoding \"\";\n}Removing the Accept-Encoding header is sometimes necessary to prevent the\nbackend server compressing the response (and preventing transformation). The\nresponse may be compressed in nginx by settinggzip on;- see thegzip\nmodule documentationfor\ndetails.In this example an X-XDV header was set so the backend server may choose to\nserve different different CSS resources.Including external contentAs an event based server, it is not practical to adddocument()support to\nthe nginx XSLT module for in-transform inclusion. Instead, external content is\nincluded through SSI in a sub-request. The SSI sub-request includes a query\nstring parameter to indicate which parts of the resultant document to include,\ncalled;filter_xpath- see above for a full example. The configuration\nbelow uses this parameter to apply a filter:worker_processes 1;\nevents {\n worker_connections 1024;\n}\nhttp {\n include mime.types;\n gzip on;\n server {\n listen 80;\n server_name localhost;\n root html;\n\n # Decide if we need to filter\n if ($args ~ \"^(.*);filter_xpath=(.*)$\") {\n set $newargs $1;\n set $filter_xpath $2;\n # rewrite args to avoid looping\n rewrite ^(.*)$ /_include$1?$newargs?;\n }\n\n location @include500 { return 500; }\n location @include404 { return 404; }\n\n location ^~ /_include {\n # Restrict _include (but not ?;filter_xpath=) to subrequests\n internal;\n error_page 404 = @include404;\n # Cache page fragments in Varnish for 1h when using ESI mode\n expires 1h;\n # Proxy\n rewrite ^/_include(.*)$ $1 break;\n proxy_pass http://127.0.0.1:80;\n # Protect against infinite loops\n proxy_set_header X-Loop 1$http_X_Loop; # unary count\n proxy_set_header Accept-Encoding \"\";\n error_page 500 = @include500;\n if ($http_X_Loop ~ \"11111\") {\n return 500;\n }\n # Filter by xpath\n xslt_stylesheet filter.xsl\n xpath=$filter_xpath\n ;\n xslt_html_parser on;\n xslt_types text/html;\n }\n\n location / {\n xslt_stylesheet theme.xsl;\n xslt_html_parser on;\n xslt_types text/html;\n ssi on; # Not required in ESI mode\n }\n }\n}In this example the sub-request is set to loop back on itself, so the include\nis taken from a themed page.filter.xsl(in the lib/xdv directory) andtheme.xslshould both be placed in the same directory asnginx.conf.An example buildout is available innginx.cfgin this package.VarnishTo enable ESI in Varnish simply add the following to your VCL file:sub vcl_fetch {\n if (obj.http.Content-Type ~ \"text/html\") {\n esi;\n }\n}An example buildout is available invarnish.cfg.ApacheXDV currently requires a version of mod_transform with html parsing support\nand a disabled mod_depends. The latest patched versions may be downloaded from\nthehtml-xslt project page.As well as the libxml2 and libxslt development packages, you will require\nlibapreq2 and the Apache development pacakges:$ sudo apt-get install libxslt1-dev libapache2-mod-apreq2 libapreq2-dev \\\n> apache2-threaded-devInstall mod_depends then mod_transform using the standard procedure:$ ./configure\n$ make\n$ sudo make installAn example virtual host configuration is shown below:NameVirtualHost *\nLoadModule depends_module /usr/lib/apache2/modules/mod_depends.so\nLoadModule transform_module /usr/lib/apache2/modules/mod_transform.so\n<VirtualHost *>\n\n FilterDeclare THEME\n FilterProvider THEME XSLT resp=Content-Type $text/html\n\n TransformOptions +ApacheFS +HTML\n TransformSet /theme.xsl\n TransformCache /theme.xsl /etc/apache2/theme.xsl\n\n <LocationMatch \"/\">\n FilterChain THEME\n </LocationMatch>\n\n</VirtualHost>The +ApacheFS directive enables XSLTdocument()inclusion.Unfortunately it is not possible to theme error responses (such as a 404 Not\nFound page) with Apache as these do not pass through the filter chain.Changelog0.3 - 2010-05-29Added access control defaults, xdv.utils.AC_READ_NET, xdv.utils.AC_READ_FILE0.3rc2 - 2010-05-25Note: the current lxml Windows binaries are unable to load files over the\nnetwork.Fixed bug resolving the rules files while use a network theme.\n[elro]0.3rc1 - 2010-05-23Nested <rules> are now allowed, so you can simply:``<xi:include href=\"standard-rules.xml\" />``[elro]XInclude processing is now enabled by default\n[elro]XSL directives inlined in the rules file are now supported (e.g.\n<xsl:strip-space elements=\u201d*\u201d />). With the inline XSL support, there should\nnow be no need for extra.xsl.\n[elro]libxml2 quotes CR characters on output, causing Firefox to insert extra\nblank lines in<pre>blocks. As HTTP specified CRLF line endings for\nform this was a problem for us. This is now caught by the compiled XSL.\n[elro]Support for including complete fragment documents with SSI/ESI.\n[elro]A bug on namespace upgrade is fixed, but you should update your namespace tohttp://namespaces.plone.org/xdvanyway.\n[elro]First release candidate.\n[elro]"} +{"package": "xdvtheme.inventions", "pacakge-description": "xdv.inventions ver 1.0xdv.inventions is a plone look and feel customization using collective.xdv.DependenciesPlone 3.3rc5 or bigger. Tested with Plone 4.0b5.\nxdv.inventions depends on collective.xdv To setup collective.xdv you can follow its instructions atpackage\u2019s page.SetupAdd collective.xdv and install it on your plone site using quickinstaller.Add xdvtheme.inventions to your buildout:[buildout]\n...\neggs =\n ...\n collective.inventions\n\n[instance]\n...\nzcml =\n collective.inventionsRerun buildout and restart your Plone instance.Go to site setup, Theme transform, and fill the xdv form enabling it and to use the static resources. For example:Enabled: yes\nDomains: www.mysite.com:port\nTheme template: http://xxx.xx.xx.xxx:port/demo/static/index\nRules file: /absolute_path_to_instance/themes/rules.xmlwhere www.mysite.com are the domains which you\u2019re going to use to access the site,http://xxx.xx.xx.xxxis the ip number of the site, or a file system path in your server to reach the file index.html. Click on save and if you access using www.mysite.com you should get the inventions look and feel customization.If you\u2019re trying it locally, it could be something like:Domains: localhost:8080\nTheme template: http://127.0.0.1:8080/MY-PLONE-SITE/index\nRules file: /PATH-TO-BOULDOUT-EGGS/xdvtheme.inventions/rules.xmlDocumentationhttp://plone.org/documentation/manual/theminghttp://pypi.python.org/pypi/collective.xdvCreditsinventions is a design made by sdworkz,http://www.oswd.org/user/profile/id/11103xdv.inventions is rewritten for xdv by Roberto Allende -rover@menttes.comcollective.xdv is developed by Martin AspeliCopyrightxdvtheme.inventions is copyright by Menttes and it\u2019s published with GPLv2 Licence.This program is free software; you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Foundation; either version 2 of the License, or\n(at your option) any later version.This program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\nGNU General Public License for more details.You should have received a copy of the GNU General Public License\nalong with this program; if not, write to the Free Software\nFoundation, Inc., 59 Temple Place, Suite 330, Boston,\nMA 02111-1307 USA.Changelog1.0dev (unreleased)Initial release"} +{"package": "xdvtheme.sparkling", "pacakge-description": "xdvtheme.sparkling is a customized version of the Sparkling theme originally released by CSS Templates. For an example of this theme see:http://www.freecsstemplates.org/preview/sparkling/.In order to install this theme within your version of Plone you need to install collective.xdv.\nChangelog\n=========1.0-beta - Nov 22, 2010Initial release"} +{"package": "xdwarf", "pacakge-description": "xdwarfMining XML to tabular data, FAAAAAASTInstallpipinstallxdwarfThe library is an wrapping onrust_dwarf, a rust based mining tool.Mining# finding in glob pattern, project name, use all - 2 CPUsdwarf=Dwarf.from_glob(\"../test/data/*.xml\",\"PMC\",-2)Define the mining detail as xpath query pattern, chaining multistage mining is well supported.dwarf.find_one('article-meta > article-id[pub-id-type=pmid]',\"pmid\")dwarf.find_one(\"abstract\",\"abstract\").find_many(\"p\",\"paragraph\")# mining stage can be chained to longer detialsreference=dwarf.find_one(\"ref-list\",\"ref_list\").find_many(\"ref\",\"reference\")reference.find_one(\"pub-id[pub-id-type=pmid]\",\"ref_id\")reference.find_one(\"pub-id[pub-id-type=doi]\",\"doi\")ref_name=reference.find_many(\"name\",\"ref_name\")ref_name.find_one(\"surname\",\"ref_surname\")dwarf.set_necessary(\"pmid\")dwarf.create_children()Mining startresult=dwarf()See resultresult.child_df().head(2)See child resultresult['ref_list'].child_df().head()"} +{"package": "xdwlib", "pacakge-description": "2023-08-30 HAYASHI Hideki <hideki@hayasix.com>Welcome to the xdwlib source releaseXdwlib is a DocuWorks library for Python.This document provides some general information about xdwlib source release.\nDetailed description is available in docs/ only in Japanese at the moment.Report problems with this release to the author.LicenseCopyright (C) 2010 HAYASHI HidekiXdwlib is provided under The Zope Public License (ZPL) Version 2.1,\nwhich is included in \u2018LICENSE.rst\u2019. Send your feedback about the license\nto the author.InstallationSystem RequirementsMicrosoft Windows (versions compatible with DocuWorks 7+)Python 3.7+DocuWorks 7+ (Japanese version; English version may also work)Install from archiveSet PATH environment variable properly and issue the following command:python3 setup.py installThis will install xdwlib in $PYTHONPATH/xdwlib.Install from PyPIXdwlib is also delivered via Python Package Index (PyPI). The latest\nversion of xdwlib will be installed by issuing:pip3 install xdwlibIf you have installed older version of xdwlib already, try:pip3 install --upgrade xdwlibOptional ModulesPIL (Python Imaging Library)Xdwlib has been working with PIL (Python Imaging Library) if available,\nto rotate pages for desired degrees other than right angles, and to copy\nbitmap annotations. Unfortunately the original PIL has not been ported\non Python 3 yet.There is an alternative library calledPillowwhich will be a good\nsubstitution. Install Pillow by issuing:pip3 install pillowcx_FreezeThe attached command line toolxdw2text.pycan be compiled to .exe\nwith cx_Freeze package, a popular successor of py2exe. To build your\nownxdw2text.exe, try:pip3 install cx_Freeze\npython3 cx_setup.py buildgoogle-cloud-visionNative OCR is not available in DocuWorks >=9.1, so xdwlib offers OCR\nby Microsoft Azure AI Vision or Google Cloud Vision (credentials required\nfor the services). To use Google Cloud Vision, install this module:pip3 install google-cloud-visionDocumentationDetailed documents are available in Japanese atRead the Docs.Python\u2019s help() also gives brief descriptions in English.Typical UseThe following code will appy OCR and paste a date stamp on every page\nas an annotation:import time\n\nfrom xdwlib import xdwopen, Point\n\n...\n\nwith xdwopen(PATHNAME, autosave=True) as doc:\n position = Point(pg.size - 100, pg.size - 20)\n datestamp = time.strftime(\"%Y-%m-%d\")\n for pg in doc:\n pg.rotate(auto=True)\n pg.ocr(strategy=\"accuracy\")\n ann = pg.add_text(position=position, text=datestamp)\n ann.fore_color = \"red\"Reporting bugsThe author appreciate bugs reports from you by email.Have fun!"} +{"package": "xdxf2html", "pacakge-description": "DescriptionThis is a Python module that converts XDXF formatted dictionary texts into HTML, written in modern C++.It depends on nothing except for a C++11-compliant compiler. The parser does no error checking to minimise overhead.Installationpipinstallxdxf2htmlBuildingpython3setup.pybuildUsage>>>importxdxf2html>>>xdxf2html.convert('''<k>Liverpool</k>... <blockquote><dtrn>a large city and port in north-west England, on the River Mersey. It first became important during the <kref>Industrial Revolution</kref>, producing and exporting cotton goods. It was also a major port for the slave trade, receiving profits from the sale of slaves in America. In the 20th century the city became famous as the home of the <kref>Beatles</kref> and for Liverpool and Everton football clubs. Among its many famous buildings are the Royal Liver Building with its two towers, the Anglican and Roman Catholic cathedrals, and the <kref>Walker Art Gallery</kref>.</dtrn> <rref>portlpool.jpg</rref></blockquote>... <blockquote>See also <kref>Mersey beat</kref>.</blockquote>''','test_dict')'<h3 class=\"headword\">Liverpool</h3><div class=\"xdxf-definition\" style=\"margin-left: 0em;\">a large city and port in north-west England, on the River Mersey. It first became important during the <a href=\"/api/lookup/test_dict/Industrial Revolution\">Industrial Revolution</a>, producing and exporting cotton goods. It was also a major port for the slave trade, receiving profits from the sale of slaves in America. In the 20th century the city became famous as the home of the <a href=\"/api/lookup/test_dict/Beatles\">Beatles</a>and for Liverpool and Everton football clubs. Among its many famous buildings are the Royal Liver Building with its two towers, the Anglican and Roman Catholic cathedrals, and the <a href=\"/api/lookup/test_dict/Walker Art Gallery\">Walker Art Gallery</a>.<img src=\"/api/cache/test_dict/portlpool.jpg\" alt=\"portlpool.jpg\"/></div><div class=\"xdxf-definition\" style=\"margin-left: 0em;\">See also <a href=\"/api/lookup/test_dict/Mersey beat\">Mersey beat</a>.</div>'The module has only one method:convert, which takes two arguments: the XDXF text and the name of the dictionary. It returns the HTML text.Appendix: a hopefully complete listing of XDXF tags, both standard and non-standardThis section will only include tags found within the dictionary 'body', i.e.<lexicon>.Representational tags<b>,<i>,<u>,<sub>,<sup>,<tt>,<br>: Could be directly translated into HTML.<c>: Colour, indicated by the attributec. Converted to a<span>with the stylecolor: c. The default colour isdarkgreen.<div>like tags<ar>: Article, ignored in this project.<def>: Definition, converted to a<div>with the classxdxf-definition. If the attributecmtis present, write it as a<span>with the classcommentinside the<div>; if the attributefreqis present, write it as a<span>with the classfrequencyinside the<div>.<ex>: Example, converted to a<div>with the classexampleand the stylemargin-left: 1em; color: grey;.<co>: Comment, converted to a<div>with the classcomment.<sr>: 'Semantic relations', converted to a<div>with the classsemantic-relations.<etm>: Etymology, converted to a<div>with the stylecolor: grey;.<blockquote>: Not in the specification, but I've seen it. Converted to a<p>.<span>like tags<k>: Keyword, namely the headword, converted to an<h3>with the classheadword.<opt>: Optional part of the keyword, converted to a<span>with the classoptional.<deftext>: Definition text, ignored in this project.<gr>: Grammatical information, converted to a<span>with the stylefont-style: italic; color: darkgreen;.<pos>,<tense>: Ignored.<tr>: Transcription, converted to a<span>with the classtranscription.<kref>: Keyword reference, converted to an<a>with thehrefattribute properly set (in this project, to/api/lookup/name of dictionary/keyword). If the attributetypeis set, prepend the value of the attribute to the keyword with a colon and a space.<iref>: External reference, could be directly converted to an<a>.<dtrn>: Definition translation, in practice used as an equivalent of<def>. So we'd better ignore it.<abbr>,<abr>: Abbreviation, converted to a<span>with the classabbreviationand the stylecolor: darkgreen; font-style: italic;.<ex_orig>,<ex_trn>: Example original and translation, converted to a<span>with the classexample-originalandexample-translationrespectively.<exm>,<prv>,<oth>: Used inside<ex>, ignored in this project.<mrkd>: Marked text, converted to a<span>with the stylebackground-color: yellow;.<nu>: Not-used, not explained in the specification. Ignored in this project.<di>: 'Don't index', ignored in this project.<syn>, <ant>, <hpr>, <hpn>, <par>, <spv>, <mer>, <hol>, <ent>, <rel>, <phr>: Phrasemes (don't know really what they are).<syn>and<ant>are converted to<span>with the classsynonymandantonymrespectively, and the tag name is prepended to the text content with:. The rest are ignored.<categ>: Category, ignored in this project.Media filesAlways in an<rref>tag. The standard prescribes that the filename should be specified in thelctnattribute, but in practice, the filename is just the text child of the tag. Converted to<img>,<audio>,<video>or<a>depending on the file extension."} +{"package": "xdyn", "pacakge-description": "No description available on PyPI."} +{"package": "xdyna", "pacakge-description": "xdynaTools to study beam dynamics in xtrack simulations, like dynamic aperture calculations, PYTHIA integration, dynamic indicators, ...Dynamic aperture studiesThexdynapackage provides theDAclass which serves as a simple front-end for setting up and running dynamic aperture studies.To start, axtrack.lineobject is required.\nThe following code then sets up the study and launches the trackingimportxdynaasxdda=xd.DA(name='name_of_your_study',# used to generate a directory where files are storednormalised_emittance=[1,1],# provide normalized emittance for particle initialization in [m]max_turns=1e5,# number of turns to trackuse_files=False# in case DA studies should run on HTC condor, files are used to collect the information# if the tracking is performed locally, no files are needed)# initialize a grid of particles using 5 angles in x-y space, in a range from 0 to 20 sigmas in steps of 5 sigma.da.generate_initial_radial(angles=5,r_min=0,r_max=20,r_step=5,delta=0.)da.line=line# associate prev. created line, holding the lattice and context, with DA objectda.track_job()# start the trackingda.survival_data# returns a dataframe with the number of survived turns for the initial position of each particleTo use on a platform like HTCondor, perform the same setup as before but usinguse_files=True.\nEach HTCondor job then only requires the following linesimportxdynaasxd# This will load the existing DA based on the meta file with the same name found in the working directory.# If the script is ran somewhere else, the path to the metafile can be passed with 'path=...'.DA=xd.DA(name=study,use_files=True)# Do the tracking, here for 100 particles.# The code will automatically look for particles that are not-submitted yet and use these.DA.track_job(npart=100)"} +{"package": "xdynamo", "pacakge-description": "This is pre-release software, and needs to be refactored in a few ways and needs more natural documentation with examples. Right now the documentation is in the (API Reference) documentation section. The natural overview/high-level docs have yet to be writtenHere are a few other related libraries I wrote written that are in a much better state with good documentation, if you want to see other examples of my work:https://github.com/xyngular/py-xinjectA simple dependency injection libraryhttps://github.com/xyngular/py-xconFast dynamic configuration retrieverCan create a flat list of config values based on various config sources and paths environment (for environmental differences and so on).https://github.com/xyngular/py-xsettingsCentralize settings for a project.Can be used with xcon (see above).Know immediately if a setting can't be found as soon as it's asked for vs letting the incorrect setting value cause a problem/crash it happen later on, and then having to back-track it.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiGetting Startedwarning \"Alpha Software!\"This is pre-release Alpha software, based on another code base and\nthe needed changes to make a final release version are not yet\ncompleted. Everything is subject to change; and documentation needs\nto be written.poetryinstallxdynamoorpipinstallxdynamo"} +{"package": "xdzx-chenjili-base-python-tools", "pacakge-description": "No description available on PyPI."} +{"package": "xe", "pacakge-description": "xestands for eXecutable Environment.There are a ton of \u201cbest practices\u201d for python projects. We can all\nagree that you should use avirtualenvand a test runner such aspytestornose.Pipis another good tool to use.Sphinxis great\nfor documentation. The list goes on.The problem is that while we agree on the tools, we seldom agree on\nhow we should use the tools. Some people usevirtualenvwrapperand\nprefer to hide all their virtualenv\u2019s in a hidden directory. Others\nprefer to create a directory within the project root. Others like to\ndo avirtualenv .to create a virtualenv for a project so activation\ndoes the \u201cRight Thing\u201d with the prompt and uses the project name. Not\nto mention tools liketoxthat help create virtualenvs for different\nversions of Python and make sure your dev environment doesn\u2019t mix with\nyour test environment.While I\u2019m positive that I can\u2019t bring the Python world together in\nharmony, I can write a tool to make this sort of environment\nmanagement and automate my own standard practices. I\u2019m calling this\ntoolxe.Project Opinionsxeis slightly opinionated in decisions it makes regarding a\nproject\u2019s dev environment. These opinions are never meant to be\ncontroversial! In fact the goal is to be as benign as possible in\nhopes thatxewill easily support any developer\u2019s workflow.With that in mind, there are some ideals thatxetries to maintain\nin order to be general and easy to work with.all commands should be runnable without a required \u201cactivation\u201d\nstepa project should have its own environmentAvoiding ActivationIf you\u2019ve ever deployed a project only to realize that you failed to\nupdate a dependency, then there is a good chance you were bitten by a\nfragile environment. While it is handy to be able to \u201cactivate\u201d your\nenvironment, it makes it really easy to miss things when you are\nupdating dependencies.Xe explicitly avoids shell level activation and instead finds your\nvirtualenv on every command.The Right Environment for Every CommandAnother areaxehelps is when you use an IDE type tool. Most editors\nand IDEs have the idea of a project. In the project settings you can\nconfigure builds that typically map to running tests or project\ntasks. If you are using a non-virtualenv aware tool, you usually have\nto configure environment variables in order to make sure the correct\nvirtualenv is used. Even if your tool does understand virtualenvs, you\nstill need to supply some configuration to the correct environment.Usingxeyou can easily configure the default build asxe test\n$fn. There is not a list of environment variables you have to setup\nand configure. You don\u2019t have to specify a virtualenv directory or\ntesting tool. You can letxetakes care of it.Isolating Your EnvironmentA project should have its own environment because you should be\ntesting and using that project in isolation. That doesn\u2019t mean you\nshouldn\u2019t have subrepos or install other packages as editable. It\nsimply means that if you are working in a project directory, you\nshould be using that project\u2019s environment.Along similar lines, a project environment should be easy to delete\nand rebuild from scratch. Usingxe, the default behavior is to\ncreate a directory local virtualenv that can be removed and rebuilt\nfrom scratch when necessary.Standard Project Files and DirectoriesHere are the standard project files and directories thatxeutilizes.setup.pyrequirements.txtdev_requirements.txtvenv/ (virtualenv directory)Most of these can be configured to point to other non-root\ndirectories, but if you use these files,xewill try to work out of\nthe box without extra configuration.It would be nice to eventually support different build tools, but I\nimagine that will be implemented via plugins. The idea being that an\norganization could implement their own build entry points and usexeto run them correctly.Getting StartedTypically you\u2019d read this first, but as this is our code we\u2019re talking\nabout we needed to get the prereq\u2019s out of the way and make sure that\nyour project isn\u2019t going to get borked byxe. Assuming things look\nreaonable, you can get started by doing:$ xe bootstrapxewill create a virtualenv if one hasn\u2019t been created yet. It will\nthen look for adev_requirements.txtand run that in the newly\ncreate environment. From there you can usexeto run tasks. A good\ndefault is simply running python:$ xe pythonThat will start up the python in thexevirtualenv. If you are using\na django project you can use the following shortcut to have access to\nyourmanage.pycommands:$ xe manage runserverIf you use pytest, you can run your tests too:$ xe test -xSay you build your docs with make, you can usexeto run make and be\nconfident your environment will be in place.$ xe make htmlWorking with Virtual MachinesAnother concept of an environment is to work on a remote machine or\nvirtual machine such asVagrant.xesupportsrdofor running\ncommands on remote machines.To userdofor all commands, add to your.xerc:USE_RDO:trueIf you only want to userdofor specific commands, specify them via\ntheRDO_COMMANDSfield:RDO_COMMANDS:-make-python"} +{"package": "xe2", "pacakge-description": "\ufeffTodo"} +{"package": "xe2layout", "pacakge-description": "LayoutLayout template for all our applications.Working with static base layoutTo build static base layout, without scripts, styles and other resources for each domain, execute command line :npm installTo start local server, execute command line :npm start"} +{"package": "xe-admix", "pacakge-description": "aDMIXPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: BSD licenseDocumentation:https://advance-data-management-in-xenon.readthedocs.io/en/latest/FeaturesImprove in Rucio uploads on a multi-scale levelCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-02-05)First release on PyPI."} +{"package": "xeasy-ml", "pacakge-description": "xeasy-ml1. What is xeasy-mlXeasy-ml is a packaged machine learning framework. It allows a beginner to quickly bui\n-ld a machine learning model and use the model to process and analyze his own data. At the same time, we have also realized the automatic analysis of data. During data proces\n-sing, xeasy-ml will automatically draw data box plots, distribution histograms, etc., and perform feature correlation analysis to help users quickly discover the value of data.2.InstallationDependenciesxeasy-ml requires:Scikit-learn >= 0.24.1\n\nPandas >= 0.24.2\n\nNumppy >= 1.19.5\n\nMatplotlib >= 3.3.4\n\nPydotplus >= 2.0.2\n\nXgboost >= 1.4.2User installationpip install xeasy-ml3. Quick Start1.Create a new projectCreate a new python file named pro_init.py to initialize the project.fromxeasy_ml.project_init.create_new_demoimportcreate_project\nimportospro_path=os.getcwd()create_project(pro_path)Now you can see the following file structure in your project.\u251c\u2500\u2500 Your_project\n ...\n\u2502 \u251c\u2500\u2500 pro_init.py\n\u2502 \u251c\u2500\u2500 project\n\u2502 \u2502 \u2514\u2500\u2500 your_project2.Run examplecdproject/your_project\n\npython__main__.py3.View Resultscdproject/your_project_name/result/v1\nls-l\u251c\u2500\u2500 box (Box plot)\n\u251c\u2500\u2500 cross_predict.txt \uff08Cross-validation prediction file\uff09\n\u251c\u2500\u2500 cross.txt \uff08Cross validation effect evaluation\uff09\n\u251c\u2500\u2500 deleted_feature.txt \uff08Features that need to be deleted\uff09\n\u251c\u2500\u2500 demo_feature_weight.txt \uff08Feature weights\uff09\n\u251c\u2500\u2500 demo.m \uff08Model\uff09\n\u251c\u2500\u2500 feature_with_feature \uff08Feature similarity\uff09\n\u251c\u2500\u2500 feature_with_label \uff08Similarity between feature and label \uff09\n\u251c\u2500\u2500 hist \uff08Distribution histogram\uff09\n\u251c\u2500\u2500 model\n\u251c\u2500\u2500 predict_result.txt \uff08Test set prediction results\uff09\n\u2514\u2500\u2500 test_score.txt \uff08Score on the test set\uff09"} +{"package": "xeauth", "pacakge-description": "Authentication client for the Xenon edark matter experiment.Free software: MITDocumentation:https://xeauth.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xebec", "pacakge-description": "xebecSnakemake pipeline for microbiome diversity effect size benchmarkingNOTE: Please note that xebec is still under active development.InstallationTo use xebec, you will need several dependencies.\nWe recommend usingmambato install these packages when possible.mamba install -c conda-forge -c bioconda biom-format h5py==3.1.0 snakemake pandas unifrac scikit-bio bokeh unifrac-binaries jinja2\n\npip install evident>=0.4.0 gemelli>=0.0.8To install xebec, run the following command from the command line:pip install xebecUsageIf you runxebec --help, you should see the following:$ xebec --help\nUsage: xebec [OPTIONS]\n\nOptions:\n --version Show the version and exit.\n -ft, --feature-table PATH Feature table in BIOM format. [required]\n -m, --metadata PATH Sample metadata in TSV format. [required]\n -t, --tree PATH Phylogenetic tree in Newick format.\n [required]\n -o, --output PATH Output workflow directory. [required]\n --max-category-levels INTEGER Max number of levels in a category.\n [default: 5]\n --min-level-count INTEGER Min number of samples per level per\n category. [default: 3]\n --rarefy-percentile FLOAT Percentile of sample depths at which to\n rarefy. [default: 10]\n --n-pcoa-components INTEGER Number of PCoA components to compuate.\n [default: 3]\n --validate-input / --no-validate-input\n Whether to validate input before creating\n workflow. [default: validate-input]\n --help Show this message and exit.To create the workflow structure, pass in the filepaths for the feature table, sample metadata, and phylogenetic tree.\nYou must also pass in a path to a directory in which to create the workflow.\nAdditionally, you can provide parameters for determining how to process your sample metadata.After running this command, navigate inside the output directory you created.\nThere should be two subdirectories:workflow/andconfig/.To start the pipeline , run the following command:snakemake --cores 1You should see the Snakemake pipeline start running the jobs.\nIf this pipeline runs sucessfully, the processed results will be located atresults/.\nIncluded in the results are the concatenated effect size values as well as interactive plots summarizing the effect sizes for each metadata column for each diversity metric.\nThese plots are generated usingBokehand can be visualized in any modern web browser.Workflow Overviewxebec performs four main steps, some of which have substeps.Process data (filter metadata, rarefaction)Run diversity analysesCalculate effect sizes (concatenate together)Generate visualizationsAn overview of the DAG is shown below:ConfigurationDiversity Metricsxebec allows configuration of what alpha and beta diversity metrics are included in the workflow.\nTo add or remove metrics, modify theconfig/alpha_div_metrics.ymlandconfig/beta_div_metrics.ymlfiles.\nFor alpha diversity, any metric that can be passed intoskbio.alpha_diversityshould work.\nFor beta diversity, any non-phylogenetic metric that can be passed intoskbio.beta_diversityshould work.\nValid phylogenetic beta diversity are those that can be passed intoStriped UniFrac.\nMake sure that any additional diversity metrics are annotated withphyloornon_phyloso xebec knows how to process them.Snakemake OptionsThe xebec workflow can be decorated with many configuration options available in Snakemake, including resource usage and HPC scheduling.\nWe recommend reading through theSnakemake documentationfor details on these options.\nNote that some of these options may require creating new configuration files."} +{"package": "xeberus-core-library", "pacakge-description": "Xeberus Core Python LibraryXeberus Core Python Library is a repository of reusable Python components to be shared by some Python projects using the Xeberus RESTful API.These components have minimal dependencies on other libraries, so that they can be deployed easily. In addition, these components will keep their interfaces as stable as possible, so that other Python projects can integrate these components without having to worry about changes in the future."} +{"package": "xeberus-restful-api-client-library", "pacakge-description": "Perseus Tracker RESTful API Client Python LibraryRepository of classes that provide Pythonic interfaces to connect to a RESTful API server developed with Perseus RESTful API Framework."} +{"package": "xeberus-restful-api-server-library", "pacakge-description": "Xeberus RESTful API Server Python Library"} +{"package": "xebus-core-library", "pacakge-description": "Xebus Core Python LibraryXebus Core Python Library is a repository of reusable Python components to be shared by Python projects using the Xebus RESTful API.These components have minimal dependencies on other libraries, so that they can be deployed easily. In addition, these components will keep their interfaces as stable as possible, so that other Python projects can integrate these components without having to worry about changes in the future."} +{"package": "xebus-id-card-image-generator", "pacakge-description": "Xebus ID Card GeneratorXebus ID Card Generatoris a Command-Line Interface (CLI) written in Python used to generate JPEG images of Xebus ID cards.This script generates images which size has the same portrait ratio asISO/IEC 7810 Identification cards ID-1(3 3\u20448 in \u00d7 2 1\u20448 in, 54mm x 85.6mm).InstallationXebus ID Card Generatorcan be easily installed with [pipenv]cod(https://github.com/pypa/pipenv):$pipenv--python3.8shell\n$pipenvinstallxebus-id-card-image-generatorNote: As of October 2020, the Python Image Library (PIL) is not yet compatible with Python 3.9.Execution$./bin/xidgen--help\nusage:xidgen[-h][-cTYPE]-fFILE[-dCHAR][-qCHAR][-eCHAR][-sGEOMETRY][-pSIZE]--header-fileFILE[--font-nameNAME]XebusIDCardImagesGenerator\n\noptionalarguments:-h,--helpshowthishelpmessageandexit-cTYPE,--card-typeTYPEspecifythetypeofIDcardstogenerate(driver,guardian,securityguard,student)-fFILE,--csv-fileFILEspecifytheabsolutepathandnameoftheCSVfilecontainingtheinformationofIDcardstogenerate-dCHAR,--delimiterCHARspecifythecharacterusedtoseparateeachfield(defaulttocharacter[,])-qCHAR,--quotecharCHARspecifythecharacterusedtosurroundfieldsthatcontainthedelimitercharacter(defaulttocharacter[\"]).-e CHAR, --escapechar CHARspecify the character used to escape the delimitercharacter, in case quotes aren't used (default tocharacter [None]).-s GEOMETRY, --size GEOMETRYspecify the width and/or height in pixels of the imageto build, with the ratio of a CR80 standard creditcard size ID-1 in portrait mode (54mm x 85.6mm)-p SIZE, --padding SIZEspecify the space in pixels or percentage to generatearound the ID card--header-file FILE specify the absolute path name of the header imagefile--font-name NAME specify the name of the font to display the full nameof each ID card--name-format FORMAT specify the format of ID card file name--debug LEVEL specify the logging level (value between 0 and 4, fromcritical to debug)For example:$xidgen--card-typestudent--header-filelfiduras_logo.jpg--csv-filelfiduras-students.csvThe user can specify the file name of the ID card images by passing the argumentname-format. A ID card file name format MUST be composed of field names to build this file name with. These field names MUST be defined in braces, each field names separated with a character underscore. For example:{id}_{first name}_{grade level}Note: The accepted field names correspond to the CSV field names.CSV FileThe CSV file passed to the script MUST contain a first row corresponding to the header fields in whatever order:#(optional): The identification of the registration file of the card owner (as provided by the organization that manages this list)ID(required): The identification of the card ownerCard Type(optional): Specify the type of the ID card (driver,guardian,securityguard, orstudent)Class Name(optional)First Name(optional)Full Name(required)Grade Level(optional): The number of the year a pupil has reached in this given educationalGrade Name(optional): THe name given to this gradeLast Name(optional)For example:#IDFirst NameLast NameFull NameGrade LevelGrade Name862-295-7293a72a73e-c57b-11ea-8e0d-0008a20c190fC\u00e9lineCAUNEC\u00e9line Kim Anh CAUNE L\u00dd16Terminale873-774-763d8be1eef-2493-11eb-9dcf-0007cb040bccAlineCAUNEAline Minh Anh CAUNE L\u00dd15Premi\u00e8re457-128-612f6315b69-11af-11eb-bb6b-0007cb040bcc\u00c9lineCAUNE\u00c9line Xu\u00e2n Anh CAUNE NGUY\u1ec4N2PSAvailable FontsAmorino_betaCalibri LightOpificio_light_roundedBarlow-BlackCalibri RegularOpificio_regularBarlow-BlackItalicCaviarDreamsOpificio_roundedBarlow-BoldCaviarDreams_BoldPirataOne-RegularBarlow-BoldItalicCaviarDreams_BoldItalicPlayfairDisplay-BlackBarlow-ExtraBoldCaviarDreams_ItalicPlayfairDisplay-BlackItalicBarlow-ExtraBoldItalicChampagne & Limousines Bold ItalicPlayfairDisplay-BoldBarlow-ExtraLightChampagne & Limousines BoldPlayfairDisplay-BoldItalicBarlow-ExtraLightItalicChampagne & Limousines ItalicPlayfairDisplay-ExtraBoldBarlow-ItalicChampagne & LimousinesPlayfairDisplay-ExtraBoldItalicBarlow-LightForgotbiPlayfairDisplay-ItalicBarlow-LightItalicForgottbPlayfairDisplay-MediumBarlow-MediumForgottePlayfairDisplay-MediumItalicBarlow-MediumItalicForgottiPlayfairDisplay-RegularBarlow-RegularForgottsPlayfairDisplay-SemiBoldBarlow-SemiBoldGiorginoPlayfairDisplay-SemiBoldItalicBarlow-SemiBoldItalicJura-BoldQuicksand-BoldBarlow-ThinJura-LightQuicksand-LightBarlow-ThinItalicJura-MediumQuicksand-MediumBebasNeue-BoldJura-RegularQuicksand-RegularBebasNeue-BookJura-SemiBoldQuicksand-SemiBoldBebasNeue-LightLibreBaskerville-BoldRothwellBebasNeue-RegularLibreBaskerville-ItalicSkarpa regularBebasNeue-ThinLibreBaskerville-RegularSkarpaLtBedizenMerriweather-BlackSteinerlightBlacker-Display-Bold-italic-trialMerriweather-BlackItalicTeko-BoldBlacker-Display-Bold-trialMerriweather-BoldTeko-LightBlacker-Display-ExtraBold-Italic-trialMerriweather-BoldItalicTeko-MediumBlacker-Display-ExtraBold-trialMerriweather-ItalicTeko-RegularBlacker-Display-Heavy-Italic-trialMerriweather-LightTeko-SemiBoldBlacker-Display-Heavy-trialMerriweather-LightItalicVerdanaBlacker-Display-Light-Italic-trialMerriweather-RegularquarthckBlacker-Display-Light-trialMontserrat-BlackquarthinBlacker-Display-Medium-Italic-trialMontserrat-BlackItalicrokikierBlacker-Display-Medium-trialMontserrat-BoldrokikiercBlacker-Display-Regular-Italic-trialMontserrat-BoldItalicrokikierciBlacker-Display-Regular-trialMontserrat-ExtraBoldrokikiereBlacker-Text-Bold-Italic-trialMontserrat-ExtraBoldItalicrokikiereiBlacker-Text-Bold-trialMontserrat-ExtraLightrokikieriBlacker-Text-Book-Italic-trialMontserrat-ExtraLightItalicrokikierlBlacker-Text-Book-trialMontserrat-ItalicrokikierlaBlacker-Text-Heavy-Italic-trialMontserrat-LightrokikierlaiBlacker-Text-Heavy-trialMontserrat-LightItalicrokikierpBlacker-Text-Light-Italic-trialMontserrat-MediumrokikierpiBlacker-Text-Light-trialMontserrat-MediumItalicrokikiersBlacker-Text-Medium-Italic-trialMontserrat-RegularrokikierseBlacker-Text-Medium-trialMontserrat-SemiBoldrokikiersiBlacker-Text-Regular-Italic-trialMontserrat-SemiBoldItalicsaunderBlacker-Text-Regular-trialMontserrat-ThinvibrocebCalibri Bold ItalicMontserrat-ThinItalicvibroceiCalibri BoldOpificio_BoldvibrocenCalibri ItalicOpificio_Bold_roundedvibrocexCalibri Light ItalicOpificio_lightDevelopment and PublicationXebus ID Card GeneratorusesPoetry, a packaging and dependency management for Python. To install the required packages, execute the following command:poetryinstallTo activate the virtual environment, run the following command:poetryshellTo publish a new version of the libraryXebus ID Card Generatorto thePython Package Index (PyPI), execute the following command:poetrypublish--build--username$PYPI_USERNAME--password$PYPI_PASSWORDNote: If you are storing the PyPi credentials in a.envfile, you can get this file automatically loaded when activating your virtual environment. You need to install the Poetry pluginpoetry-dotenv-plugin:poetryselfaddpoetry-dotenv-plugin"} +{"package": "xebus-restful-api-client-library", "pacakge-description": "Xebus RESTful API Client Python LibraryXebus RESTful API Client Python Library is a repository of\nclasses that provide Pythonic interfaces to the Xebus RESTful RESTful API server.This library requires:Xebus Common Python LibraryPerseus Common Python LibraryPerseus RESTful API Client Python Library"} +{"package": "xebus-sis-connector-core-library", "pacakge-description": "Xebus SIS Connector Core Python LibraryReusable Python components to develop a SIS connector"} +{"package": "xebus-sis-connector-eduka", "pacakge-description": "Xebus Eduka SIS ConnectorConnector to fetch data from a school's Eduka information system.\"Code identifiant\";\"Nom\";\"Pr\u00e9nom\";\"Nom complet\";\"Nationalit\u00e9 1\";\"Langue maternelle\";\"Date de naissance\";\"Age\";\"Branche scolaire\";\"Classe\";\"Code identifiant R1\";\"Code identifiant R2\";\"Pr\u00e9nom R1\";\"Pr\u00e9nom R2\";\"Nom R1\";\"Nom R2\";\"Nom complet R1\";\"Nom complet R2\";\"Langue(s) parl\u00e9e(s) R1\";\"Langue(s) parl\u00e9e(s) R2\";\"Nationalit\u00e9(s) R1\";\"Nationalit\u00e9(s) R2\";\"Adresse e-mail R1\";\"Adresse e-mail R2\";\"T\u00e9l\u00e9phone mobile R1\";\"T\u00e9l\u00e9phone mobile R2\";\"Street R1\";\"Street R2\"\n\"12046S3485\";\"CAUNE NGUYEN\";\"\u00c9line Xu\u00e2n Anh Aurora\";\"CAUNE NGUYEN \u00c9line Xu\u00e2n Anh Aurora\";\"French\";\"Vietnamese\";\"23/12/2016\";\"7\";\"Elementaire \u00bb Cours \u00e9l\u00e9mentaire 1 (Ce1)\";\"CE1 B\";\"12046G3483\";\"12046G3482\";\"Thi Thanh Truc\";\"Daniel\";\"NGUYEN\";\"CAUNE\";\"NGUYEN Thi Thanh Truc\";\"CAUNE Daniel\";\"French, English, Vietnamese\";\"French, English, Vietnamese\";\"Vietnamese\";\"French\";\"thithanhtruc.nguyen@gmail.com\";\"daniel.caune@gmail.com\";\"+84 822 170 781\";\"+84 812 170 781\";\"18A V\u00f5 Tr\u01b0\u1eddng To\u1ea3n, P. An Ph\u00fa, Qu\u1eadn 2, TP.HCM\";\"18A V\u00f5 Tr\u01b0\u1eddng To\u1ea3n, P. An Ph\u00fa, Qu\u1eadn 2, TP.HCM\"List of the CSV fields:SectionChildEduka Field NameDescriptionXebus Field NameCode identifiantThe child\u2019s unique identifier as referenced in the school organization\u2019s information system (SIS).SIS IDPr\u00e9nomThe given name of the child.First NameNomThe surname of the child.Last NameNom completThe complete personal name of the child, including their last name, first name and middle name(s).Full NameLangue maternelleThe spoken language of the child.LanguageNationalit\u00e9 1The primary nationality of the child.NationalityDate de naissanceThe date of birth of the child, in the formatDD/MM/YYYY.Branche scolaireThe name of the education grade that the child has reached for the current or the coming school year.Grade NameClasseThe name of the class that the child has enrolled for the current or the coming school year.Class NameSectionPrimary ParentEduka Field NameDescriptionXebus Field NameCode identifiant R1The primary parent\u2019s unique identifier as referenced in the school organization\u2019s information system (SIS).SIS IDPr\u00e9nom R1The first name (also known as the given name) of the primary parent.First NameNom R1The surname of the primary parent.Last NameNom complet R1The complete personal name of the primary parent, including their surname, first name and middle name(s).Full NameLangue(s) parl\u00e9e(s) R1The preferred language of the primary parent.LanguageNationalit\u00e9(s) R1The primary nationality of the primary parent.NationalityAdresse e-mail R1The email address of the primary parent.Email AddressT\u00e9l\u00e9phone mobile R1The international mobile phone number of the primary parent.Phone NumberStreet R1The address of the home where the primary parent accommodates their child.Home AddressSectionSecondary ParentEduka Field NameDescriptionXebus Field NameCode identifiant R2The secondary parent\u2019s unique identifier as referenced in the school organization\u2019s information system (SIS).SIS IDPr\u00e9nom R2The first name (also known as the given name) of the secondary parent.First NameNom R2The surname of the secondary parent.Last NameNom complet R2The complete personal name of the secondary parent, including their surname, first name and middle name(s).Full NameLangue(s) parl\u00e9e(s) R2The preferred language of the secondary parent.LanguageNationalit\u00e9(s) R2The primary nationality of the secondary parent.NationalityAdresse e-mail R2The email address of the secondary parent.Email AddressT\u00e9l\u00e9phone mobile R2The international mobile phone number of the secondary parent.Phone NumberStreet R2The address of the home where the secondary parent accommodates their child.Home AddressLanguages & NationalitiesNameDutchEnglishFrenchGermanItalianJapaneseMandarin ChinesePolishPortugueseRussianSpanish"} +{"package": "xebus-sis-connector-google-sheet", "pacakge-description": "Xebus Google Sheet SIS ConnectorConnector to fetch family data from a school's Google Sheet document.Google Service AccountXebus Google Sheet SIS Connector needs to use theservice accountxebus-family-list-google-sheet@xebus-323504.iam.gserviceaccount.comto get access to the Google sheet that contains the families data of a school organization.Aservice accountis a special kind of account typically used by an application, rather than a person. A service account is identified by its email address, which is unique to the account. Applications use service accounts to make authorized API calls by authenticating as either the service account itself. When an application authenticates as a service account, it has access to all resources that the service account has permission to access."} +{"package": "xecd-rates", "pacakge-description": "Xecd Rates Python: Free currency rates converterWhat is it?This project is free version of XE Currency Data (XECD) product.Xecd-Rates-Python librariy gives you access to daily or live rates and historic mid-market conversion rates between all of our supported currencies.You can access the paid version of this project via thislink.Where to get itThe preferred way to install this package is pip.pip install xecd-ratesOr get the latest version from git:pip install git+https://github.com/doguskidik/xecd-rates-python.gitDependenciesrequestslxmlUsage>>>fromxecd_ratesimportXecd>>>xecd=Xecd()>>>xecd.available_currencies{'AFN':'Afghan Afghani','ALL':'Albanian Lek','AMD':'Armenian Dram','ANG':'Dutch Guilder','AOA':'Angolan Kwanza','ARS':'Argentine Peso','AUD':'Australian Dollar','AWG':'Aruban or Dutch Guilder','AZN':'Azerbaijan Manat','BAM':'Bosnian Convertible Mark','BBD':'Barbadian or Bajan Dollar','BDT':'Bangladeshi Taka','BGN':'Bulgarian Lev','BHD':'Bahraini Dinar','BIF':'Burundian Franc','BMD':'Bermudian Dollar','BND':'Bruneian Dollar','BOB':'Bolivian Bol\u00c3\u00adviano','BRL':'Brazilian Real','BSD':'Bahamian Dollar','BTN':'Bhutanese Ngultrum','BWP':'Botswana Pula','BYN':'Belarusian Ruble','BZD':'Belizean Dollar','CAD':'Canadian Dollar','CDF':'Congolese Franc','CHF':'Swiss Franc','CLP':'Chilean Peso','CNY':'Chinese Yuan Renminbi','COP':'Colombian Peso','CRC':'Costa Rican Colon','CUC':'Cuban Convertible Peso','CUP':'Cuban Peso','CVE':'Cape Verdean Escudo','CZK':'Czech Koruna','DJF':'Djiboutian Franc','DKK':'Danish Krone','DOP':'Dominican Peso','DZD':'Algerian Dinar','EGP':'Egyptian Pound','ERN':'Eritrean Nakfa','ETB':'Ethiopian Birr','EUR':'Euro','FJD':'Fijian Dollar','FKP':'Falkland Island Pound','GBP':'British Pound','GEL':'Georgian Lari','GGP':'Guernsey Pound','GHS':'Ghanaian Cedi','GIP':'Gibraltar Pound','GMD':'Gambian Dalasi','GNF':'Guinean Franc','GTQ':'Guatemalan Quetzal','GYD':'Guyanese Dollar','HKD':'Hong Kong Dollar','HNL':'Honduran Lempira','HRK':'Croatian Kuna','HTG':'Haitian Gourde','HUF':'Hungarian Forint','IDR':'Indonesian Rupiah','ILS':'Israeli Shekel','IMP':'Isle of Man Pound','INR':'Indian Rupee','IQD':'Iraqi Dinar','IRR':'Iranian Rial','ISK':'Icelandic Krona','JEP':'Jersey Pound','JMD':'Jamaican Dollar','JOD':'Jordanian Dinar','JPY':'Japanese Yen','KES':'Kenyan Shilling','KGS':'Kyrgyzstani Som','KHR':'Cambodian Riel','KMF':'Comorian Franc','KPW':'North Korean Won','KRW':'South Korean Won','KWD':'Kuwaiti Dinar','KYD':'Caymanian Dollar','KZT':'Kazakhstani Tenge','LAK':'Lao Kip','LBP':'Lebanese Pound','LKR':'Sri Lankan Rupee','LRD':'Liberian Dollar','LSL':'Basotho Loti','LYD':'Libyan Dinar','MAD':'Moroccan Dirham','MDL':'Moldovan Leu','MGA':'Malagasy Ariary','MKD':'Macedonian Denar','MMK':'Burmese Kyat','MNT':'Mongolian Tughrik','MOP':'Macau Pataca','MRU':'Mauritanian Ouguiya','MUR':'Mauritian Rupee','MVR':'Maldivian Rufiyaa','MWK':'Malawian Kwacha','MXN':'Mexican Peso','MYR':'Malaysian Ringgit','MZN':'Mozambican Metical','NAD':'Namibian Dollar','NGN':'Nigerian Naira','NIO':'Nicaraguan Cordoba','NOK':'Norwegian Krone','NPR':'Nepalese Rupee','NZD':'New Zealand Dollar','OMR':'Omani Rial','PAB':'Panamanian Balboa','PEN':'Peruvian Sol','PGK':'Papua New Guinean Kina','PHP':'Philippine Peso','PKR':'Pakistani Rupee','PLN':'Polish Zloty','PYG':'Paraguayan Guarani','QAR':'Qatari Riyal','RON':'Romanian Leu','RSD':'Serbian Dinar','RUB':'Russian Ruble','RWF':'Rwandan Franc','SAR':'Saudi Arabian Riyal','SBD':'Solomon Islander Dollar','SCR':'Seychellois Rupee','SDG':'Sudanese Pound','SEK':'Swedish Krona','SGD':'Singapore Dollar','SHP':'Saint Helenian Pound','SLL':'Sierra Leonean Leone','SOS':'Somali Shilling','SPL':'Seborgan Luigino','SRD':'Surinamese Dollar','STN':'Sao Tomean Dobra','SVC':'Salvadoran Colon','SYP':'Syrian Pound','SZL':'Swazi Lilangeni','THB':'Thai Baht','TJS':'Tajikistani Somoni','TMT':'Turkmenistani Manat','TND':'Tunisian Dinar','TOP':\"Tongan Pa'anga\",'TRY':'Turkish Lira','TTD':'Trinidadian Dollar','TVD':'Tuvaluan Dollar','TWD':'Taiwan New Dollar','TZS':'Tanzanian Shilling','UAH':'Ukrainian Hryvnia','UGX':'Ugandan Shilling','USD':'US Dollar','UYU':'Uruguayan Peso','UZS':'Uzbekistani Som','VEF':'Venezuelan Bol\u00c3\u00advar','VES':'Venezuelan Bol\u00c3\u00advar','VND':'Vietnamese Dong','VUV':'Ni','WST':'Samoan Tala','XAF':'Central African CFA Franc BEAC','XAG':'Silver Ounce','XAU':'Gold Ounce','XBT':'Bitcoin','XCD':'East Caribbean Dollar','XDR':'IMF Special Drawing Rights','XOF':'CFA Franc','XPD':'Palladium Ounce','XPF':'CFP Franc','XPT':'Platinum Ounce','YER':'Yemeni Rial','ZAR':'South African Rand'}>>>xecd.convert_from(cfrom='TRY',cto=['EUR','USD']){'timestamp':'2020-06-29 12:38 UTC','from':'TRY','to':[{'quotecurrency':'USD','mid':'0.1458731540'},{'quotecurrency':'EUR','mid':'0.1293255181'}]}>>>xecd.historic_rate(cdate='2020-01-01',cfrom='TRY',cto=['EUR','USD']){'timestamp':'2020-01-01 17:00 UTC','from':'TRY','to':[{'quotecurrency':'USD','mid':'0.1681044260'},{'quotecurrency':'EUR','mid':'0.1501472598'}]}>>>xecd.historic_rate_period(sdate='2020-01-01',edate='2020-01-05',cfrom='TRY',cto=['EUR','USD']){'from':'TRY','to':{'USD':[{'mid':'0.1678214515','timestamp':'2020-01-02 17:00 UTC'},{'mid':'0.1673405691','timestamp':'2020-01-03 17:00 UTC'},{'mid':'0.1673821113','timestamp':'2020-01-04 17:00 UTC'},{'mid':'0.1673821113','timestamp':'2020-01-04 17:00 UTC'},{'mid':'0.1674115622','timestamp':'2020-01-05 17:00 UTC'}],'EUR':[{'mid':'0.1502682495','timestamp':'2020-01-02 17:00 UTC'},{'mid':'0.1497847442','timestamp':'2020-01-03 17:00 UTC'},{'mid':'0.1499997714','timestamp':'2020-01-04 17:00 UTC'},{'mid':'0.1499997714','timestamp':'2020-01-04 17:00 UTC'},{'mid':'0.1499838691','timestamp':'2020-01-05 17:00 UTC'}]}}Available CurrenciesCurrency CodeDescriptionAFNAfghan AfghaniALLAlbanian LekAMDArmenian DramANGDutch GuilderAOAAngolan KwanzaARSArgentine PesoAUDAustralian DollarAWGAruban or Dutch GuilderAZNAzerbaijan ManatBAMBosnian Convertible MarkBBDBarbadian or Bajan DollarBDTBangladeshi TakaBGNBulgarian LevBHDBahraini DinarBIFBurundian FrancBMDBermudian DollarBNDBruneian DollarBOBBolivian Bol\u00c3\u00advianoBRLBrazilian RealBSDBahamian DollarBTNBhutanese NgultrumBWPBotswana PulaBYNBelarusian RubleBZDBelizean DollarCADCanadian DollarCDFCongolese FrancCHFSwiss FrancCLPChilean PesoCNYChinese Yuan RenminbiCOPColombian PesoCRCCosta Rican ColonCUCCuban Convertible PesoCUPCuban PesoCVECape Verdean EscudoCZKCzech KorunaDJFDjiboutian FrancDKKDanish KroneDOPDominican PesoDZDAlgerian DinarEGPEgyptian PoundERNEritrean NakfaETBEthiopian BirrEUREuroFJDFijian DollarFKPFalkland Island PoundGBPBritish PoundGELGeorgian LariGGPGuernsey PoundGHSGhanaian CediGIPGibraltar PoundGMDGambian DalasiGNFGuinean FrancGTQGuatemalan QuetzalGYDGuyanese DollarHKDHong Kong DollarHNLHonduran LempiraHRKCroatian KunaHTGHaitian GourdeHUFHungarian ForintIDRIndonesian RupiahILSIsraeli ShekelIMPIsle of Man PoundINRIndian RupeeIQDIraqi DinarIRRIranian RialISKIcelandic KronaJEPJersey PoundJMDJamaican DollarJODJordanian DinarJPYJapanese YenKESKenyan ShillingKGSKyrgyzstani SomKHRCambodian RielKMFComorian FrancKPWNorth Korean WonKRWSouth Korean WonKWDKuwaiti DinarKYDCaymanian DollarKZTKazakhstani TengeLAKLao KipLBPLebanese PoundLKRSri Lankan RupeeLRDLiberian DollarLSLBasotho LotiLYDLibyan DinarMADMoroccan DirhamMDLMoldovan LeuMGAMalagasy AriaryMKDMacedonian DenarMMKBurmese KyatMNTMongolian TughrikMOPMacau PatacaMRUMauritanian OuguiyaMURMauritian RupeeMVRMaldivian RufiyaaMWKMalawian KwachaMXNMexican PesoMYRMalaysian RinggitMZNMozambican MeticalNADNamibian DollarNGNNigerian NairaNIONicaraguan CordobaNOKNorwegian KroneNPRNepalese RupeeNZDNew Zealand DollarOMROmani RialPABPanamanian BalboaPENPeruvian SolPGKPapua New Guinean KinaPHPPhilippine PesoPKRPakistani RupeePLNPolish ZlotyPYGParaguayan GuaraniQARQatari RiyalRONRomanian LeuRSDSerbian DinarRUBRussian RubleRWFRwandan FrancSARSaudi Arabian RiyalSBDSolomon Islander DollarSCRSeychellois RupeeSDGSudanese PoundSEKSwedish KronaSGDSingapore DollarSHPSaint Helenian PoundSLLSierra Leonean LeoneSOSSomali ShillingSPLSeborgan LuiginoSRDSurinamese DollarSTNSao Tomean DobraSVCSalvadoran ColonSYPSyrian PoundSZLSwazi LilangeniTHBThai BahtTJSTajikistani SomoniTMTTurkmenistani ManatTNDTunisian DinarTOPTongan Pa'angaTRYTurkish LiraTTDTrinidadian DollarTVDTuvaluan DollarTWDTaiwan New DollarTZSTanzanian ShillingUAHUkrainian HryvniaUGXUgandan ShillingUSDUS DollarUYUUruguayan PesoUZSUzbekistani SomVEFVenezuelan Bol\u00c3\u00advarVESVenezuelan Bol\u00c3\u00advarVNDVietnamese DongVUVNiWSTSamoan TalaXAFCentral African CFA Franc BEACXAGSilver OunceXAUGold OunceXBTBitcoinXCDEast Caribbean DollarXDRIMF Special Drawing RightsXOFCFA FrancXPDPalladium OunceXPFCFP FrancXPTPlatinum OunceYERYemeni RialZARSouth African RandContributingxecd_rates_python is an open-source project. Submit a pull request to contribute!Testingto run individual test suitespython-munittesttests/test_integration.py"} +{"package": "xecd-rates-client", "pacakge-description": "XE Currency Data Client - PythonXE.com Inc. is the World's Trusted Currency Authority. This project provides an SDK to interface with our XE Currency Data (XECD) product.XE Currency Data is a REST API that gives you access to daily or live rates and historic mid-market conversion rates between all of our supported currencies.You will need an api key and secret to use this sdk. Sign up for afree trialor register for afull account.This client will work with both python2 and python3.InstallationThe preferred way to install this package is pip.pip install xecd-rates-clientOr get the latest version from git:pip install git+https://github.com/XenonLab/xecd-rates-client-python.gitThis package followssemantic versioning.Usage>>>fromxecd_rates_clientimportXecdClient>>>xecd=XecdClient('ACCOUNT_ID','API_KEY')>>>xecd.account_info(){'id':'11111111-1111-1111-1111-111111111111','organization':'YOUR_ORG','package':'ENTERPRISE_LIVE_INTERNAL','service_start_timestamp':'2018-01-01T00:00:00Z'}>>>xecd.convert_from(\"EUR\",\"CAD\",55){'terms':'http://www.xe.com/legal/dfs.php','privacy':'http://www.xe.com/privacy.php','from':'EUR','amount':55.0,'timestamp':'2018-08-21T15:31:00Z','to':[{'quotecurrency':'CAD','mid':82.7121317322}]}>>>xecd.convert_to(\"RUB\",\"CAD\",55){'terms':'http://www.xe.com/legal/dfs.php','privacy':'http://www.xe.com/privacy.php','to':'RUB','amount':55.0,'timestamp':'2018-08-21T15:32:00Z','from':[{'quotecurrency':'CAD','mid':1.0652293852}]}>>>xecd.historic_rate(\"2016-12-25\",\"12:34\",\"EUR\",\"CAD\",55){'terms':'http://www.xe.com/legal/dfs.php','privacy':'http://www.xe.com/privacy.php','from':'EUR','amount':55.0,'timestamp':'2016-12-25T13:00:00Z','to':[{'quotecurrency':'CAD','mid':77.8883951909}]}>>>xecd.historic_rate_period(55,\"EUR\",\"RUB\",\"2016-02-28T12:00\",\"2016-03-03T12:00\"){'terms':'http://www.xe.com/legal/dfs.php','privacy':'http://www.xe.com/privacy.php','from':'EUR','amount':55.0,'to':{'RUB':[{'mid':4590.1222691671,'timestamp':'2016-02-28T12:00:00Z'},{'mid':4545.42879069,'timestamp':'2016-02-29T12:00:00Z'},{'mid':4433.0643335184,'timestamp':'2016-03-01T12:00:00Z'},{'mid':4409.6291908683,'timestamp':'2016-03-02T12:00:00Z'},{'mid':4396.2068371801,'timestamp':'2016-03-03T12:00:00Z'}]}}>>>xecd.monthly_average(55,\"CAD\",\"EUR\",2017,5){'terms':'http://www.xe.com/legal/dfs.php','privacy':'http://www.xe.com/privacy.php','from':'CAD','amount':55.0,'year':2017,'to':{'EUR':[{'monthlyAverage':36.5976590134,'month':5,'daysInMonth':31}]}}DocumentationTechnical SpecificationsContributingxecd_rates_client_python is an open-source project. Submit a pull request to contribute!Testingpython3-mtest.UnitTest\npython3-mtest.IntegrationTest\npython-mtest.IntegrationTestNote: the UnitTest must be ran with python3 due to its use of unittest.mock (which is not present as of python2.7). Despite this, the client itself is usable with both python 2 and 3.Security IssuesIf you discover a security vulnerability within this package, pleaseDO NOTpublish it publicly. Instead, contact us atsecurity [at] xe.com. We will follow up with you as soon as possible.About UsXE.com Inc.is The World's Trusted Currency Authority. Development of this project is led by the XE.com Inc. Development Team and supported by the open-source community."} +{"package": "xecs", "pacakge-description": "Documentation:https://xecs.readthedocs.ioxecsis a Python library (written in Rust!) for a performant\nentity component system (ECS). You can use it to write simulations, games\nor any other high-performance piece of software.If you are familiar withBevyandNumPy\u2013 the API ofxecsshould be\nfamiliar to you.The goals ofxecsare as follows:Fast: Operations are executed in parallel as much as possible\nand the library is written in Rust to be cache friendly and performant.Simple: Data is defined with a dataclass-like syntax and systems are regular\nPython functions.Typed: Types form an integral part of the API, making code clean but\nalso easily verified with type checkers.NumPy-friendly: Our data types can be used seamlessly with NumPy.Python-friendly: User code is regular Python code, allowing\nfull integration with the Python ecosystem. We avoid things like Numba\nwhich cause pain during debugging and limit use of pure Python libraries.Code PreviewimportxecsasxxclassVelocity(xx.Component):value:xx.Vec2defupdate_positions(query:xx.Query[tuple[xx.Transform2,Velocity]])->None:(transform,velocity)=query.result()transform.translation+=velocity.valueInstallationpipinstallxecs"} +{"package": "xecs-pygame", "pacakge-description": "A plugin forxecs, allowing you to render your entities withpygame.UsageFirst, add the plugin to yourxecsapp.importxecsasxxfromxecs_pygameimportPyGamePlugindefmain()->None:app=xx.RealTimeApp()app.add_plugin(PyGamePlugin())Now, when you spawn entities, you can give them aCircle,Polygon,Rectanglecomponent. If you do that,\nyour entities will be rendered on the screen:importxecsasxxfromxecs_pygameimportCircle,PyGamePlugindefspawn_three_circles(commands:xx.Commands,world:xx.World)->None:transformi,_=commands.spawn((xx.Transform2,Circle),3)transform=world.get_view(xx.Transform2,transformi)transform.translation.x.fill([0,15,30])defmain()->None:app=xx.RealTimeApp()app.add_plugin(PyGamePlugin())app.add_startup_system(spawn_three_circles)app.add_pool(Circle.create_pool(3))app.add_pool(xx.Transform2.create_pool(3))app.run()if__name__==\"__main__\":main()Further examplesdraw shapesmoving circlesboidsmouse pressesmouse positiontextkeyboardInstallationpipinstallxecs-pygame"} +{"package": "xecta-data-api-client", "pacakge-description": "No description available on PyPI."} +{"package": "xed", "pacakge-description": "xedxed is a command-line tool for performing basic text transformations, modeled\nafter the utilitysed.Example invocation:$ echo \"Hello, world!\" | xed replace Hello Goodbye\nGoodbye, worldFor more information,visit xed's website."} +{"package": "xeda", "pacakge-description": "Xeda/\u02c8zi\u02d0d\u0259/is a cross-platform, cross-EDA, cross-target simulation and synthesis automation platform.\nIt assists hardware developers in verification, evaluation, and deployment of RTL designs. Xeda supports flows from multiple commercial and open-source electronic design automation suites.Xeda is the one tool to rule 'em all!For further details, visit theXeda's documentations(Work In Progress).InstallationPython 3.8 or newer is required. To install the latest published version frompypirun:python3 -m pip install -U xedaDevelopmentgit clone --recursive https://github.com/XedaHQ/xeda.git\ncd xeda\npython3 -m pip install -U --editable . --config-settings editable_mode=strictUsageRunxeda --helpto see a list of available commands and options.Design DescriptionXeda design-specific descriptions and settings are organized through project files specified inTOML. Every project contains one or more HDL designs. The default name for the project file isxedaproject.toml.Sample Xeda design descriptionfile:name=\"sqrt\"description=\"Iterative computation of square-root of an integer\"language.vhdl.standard=\"2008\"[rtl]sources=[\"sqrt.vhdl\"]top=\"sqrt\"clock_port=\"clk\"parameters={G_IN_WIDTH=32}# parameters = { G_IN_WIDTH = 32, G_ITERATIVE = true, G_STR= \"abcd\", G_BITVECTOR=\"7'b0101001\" }[tb]sources=[\"tb_sqrt.py\"]cocotb=true# top = \"tb_sqrt\" # FIXME[flows.vivado_synth]fpga.part='xc7a12tcsg325-1'clock_period=5.0FlowsAToolis an abstraction for an executable which is responsible for one or several steps in an EDA flow. AToolcan be executed as a native binary already installed on the system, in a virtualized container (e.g.docker), or on a remote system.\nAFlowis a collection of steps performed by one or several tools. A XedaFlowimplements the following methods:init(optional): initializations which need to happen after the instantiation of aFlowinstance. At this stage, the flow can specify and customize dependency flows, which will be run before execution of the flow. Seperation of this stage form Python__init__enables greater flexibility and more effective control over the execution of flows.run: main execution of the flow which includes generation of files, scripts, and tool arguments as well as execution of one or several tools. All dependencies have been already executed beforerunbegins, and the completed dependencies (and their results and artifacts) will be available.parse_results(optional): evaluate and interpret generated reports or other artifacts.Supported Tools and FlowsAMD-XilinxVivadoDesign Suitevivado_synth: FPGA synthesis and implementation.vivado_sim: functional simulation of RTL designvivado_postsynthsim: Post-implementation functional and timing simulation and power analysisvivado_power: Post-implementation power estimation based on post-implementation timing simulation with real-world target testvectorsAMD-XilinxISEDesign SuiteGHDLVHDL simulatorghdl_simIntelQuartus Prime(Lite/Pro Editions):quartus: FPGA synthesis and implementation flowLattice Diamonddiamond_synth: FPGA synthesis and implementation flowMentor (Siemens)ModelSimmodelsimRTL and netlist simulationnextpnrportable FPGA place and route toolopenFPGAloader: Open-source and multi-platform universal utility for programming FPGAs. Compatible with many boards, cables and FPGA from major manufacturers.OpenROAD: integrated chip physical design flow that takes a design from RTL sources to routed layout.Synopsys Design CompilerSynopsys VCS simulatorVerilator: the fastest (open-source) Verilog/SystemVerilog simulator.Bluespec: Compiler, simulator, and tools for the Bluespec Hardware Description Language.YosysOpen SYnthesis Suite (FPGA and ASICs synthesis)Runxeda list-flowsfor the full list of supported flows in the installed version."} +{"package": "xedocs", "pacakge-description": "xedocs is meant to replace cmt and bodega as well as helping tracking all shared documents especially if\nthey need to be versioned.What does Xedocs give youData readingRead data from multiple formats (e.g. mongodb, pandas) and locations with a simple unified interface.Custom logic implemented on the document class, e.g. creating a tensorflow model from the data etc.Multiple APIs for reading data, fun functional, ODM style, pandas and xarray.Read data as objects, dataframes, dicts, json.Writing dataWrite data to multiple storage backends with the same interfaceCustom per-collection rules for data insertion, deletion and updating.Schema validation and type coercion so storage has uniform and consistent data.OtherCustom panel widgets for graphical representation of data, web clientAuto-generated API server and client + openapi documentationCLI for viewing and downloading dataBasic UsageExplore the available schemasimportxedocs>>>xedocs.list_schemas()>>>['detector_numbers','fax_configs','plugin_lineages','context_lineages','pmt_area_to_pes','global_versions','electron_drift_velocities',...]>>>xedocs.help('pmt_area_to_pes')>>>Schemaname:pmt_area_to_pesIndexfields:['version','time','detector','pmt']Columnfields:['created_date','comments','value']Read/write data from the shared development database,\nthis database is writable from the default analysis username/passwordimportxedocsdb=xedocs.development_db()docs=db.pmt_area_to_pes.find_docs(version='v1',pmt=[1,2,3,5],time='2021-01-01T00:00:00',detector='tpc')to_pes=[doc.valuefordocindocs]# passing a run_id will attempt to fetch the center time of that run from the runs dbdoc=db.pmt_area_to_pes.find_one(version='v1',pmt=1,run_id=25000,detector='tpc')to_pe=doc.valueRead from the straxen processing database, this database is read-only for the default analysis username/passwordimportxedocsdb=xedocs.straxen_db()...Read from the the corrections gitub repository, this database is read-onlyimportxedocsdb=xedocs.corrections_repo(branch=\"master\")...If you cloned the corrections gitub repo to a local folder, this database can be read tooimportxedocsdb=xedocs.local_folder(PATH_TO_REPO_FOLDER)...Read data from alternative data sources specified by path,\ne.g csv files which will be loaded by pandas.fromxedocs.schemasimportDetectorNumberg1_doc=DetectorNumber.find_one(datasource='/path/to/file.csv',version='v1',field='g1')g1_value=g1_doc.valueg1_error=g1_doc.uncertaintyThe path can also be a github URL or any other URL supported by fsspec.fromxedocs.schemasimportDetectorNumberg1_doc=DetectorNumber.find_one(datasource='github://org:repo@/path/to/file.csv',version='v1',field='g1')Supported data sourcesMongoDB collectionsTinyDB tablesJSON filesREST API clientsPlease open an issue onrframeif you want support for an additional data format.If you want a new datasource to be available from a schema class, you can register it to the class:fromxedocs.schemasimportDetectorNumberDetectorNumber.register_datasource('github://org:repo@/path/to/file.csv',name='github_repo')# The source will now be available under the given name:g1_doc=DetectorNumber.github_repo.find_one(version='v1',field='g1')DocumentationFull documentation hosted byReadthedocsCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xedro", "pacakge-description": "What is Kedro?Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code. It borrows concepts from software engineering and applies them to machine-learning code; applied concepts include modularity, separation of concerns and versioning.How do I install Kedro?To install Kedro from the Python Package Index (PyPI) simply run:pip install kedroIt is also possible to install Kedro usingconda:conda install -c conda-forge kedroOurGet Started guidecontains full installation instructions, and includes how to set up Python virtual environments.What are the main features of Kedro?A pipeline visualisation generated usingKedro-Viz| Feature | What is this? ||----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|| Project Template | A standard, modifiable and easy-to-use project template based onCookiecutter Data Science. || Data Catalog | A series of lightweight data connectors used to save and load data across many different file formats and file systems, including local and network file systems, cloud object stores, and HDFS. The Data Catalog also includes data and model versioning for file-based systems. || Pipeline Abstraction | Automatic resolution of dependencies between pure Python functions and data pipeline visualisation usingKedro-Viz. || Coding Standards | Test-driven development usingpytest, produce well-documented code usingSphinx, create linted code with support forflake8,isortandblackand make use of the standard Python logging library. || Flexible Deployment | Deployment strategies that include single or distributed-machine deployment as well as additional support for deploying on Argo, Prefect, Kubeflow, AWS Batch and Databricks. |How do I use Kedro?TheKedro documentationincludes three examples to help get you started:A typical \"Hello World\" example, for anentry-level description of the main Kedro conceptsAnintroduction to the project templateusing the Iris datasetA more detailedspaceflights tutorialto give you hands-on experienceWhy does Kedro exist?Kedro is built upon our collective best-practice (and mistakes) trying to deliver real-world ML applications that have vast amounts of raw unvetted data. We developed Kedro to achieve the following:To address the main shortcomings of Jupyter notebooks, one-off scripts, and glue-code because there is a focus oncreatingmaintainable data science codeTo enhanceteam collaborationwhen different team members have varied exposure to software engineering conceptsTo increase efficiency, because applied concepts like modularity and separation of concerns inspire the creation ofreusable analytics codeThe humans behind KedroKedro is maintained bya product teamand a number ofcontributors from across the world.Can I contribute?Yes! Want to help build Kedro? Check out ourguide to contributing to Kedro.Where can I learn more?There is a growing community around Kedro. Have a look at theKedro FAQsto find projects using Kedro and links to articles, podcasts and talks.Who likes Kedro?There are Kedro users across the world, who work at start-ups, major enterprises and academic institutions likeAbsa,Acensi,Advanced Programming Solutions SL,AI Singapore,Augment Partners,AXA UK,Belfius,Beamery,Caterpillar,CRIM,Dendra Systems,Element AI,GetInData,GMO,Indicium,Imperial College London,ING,Jungle Scout,Helvetas,Leapfrog,McKinsey & Company,Mercado Libre Argentina,Modec,Mosaic Data Science,NaranjaX,NASA,Open Data Science LatAm,Prediqt,QuantumBlack,Retrieva,Roche,Sber,Soci\u00e9t\u00e9 G\u00e9n\u00e9rale,Telkomsel,Universidad Rey Juan Carlos,UrbanLogiq,Wildlife Studios,WovenLightandXP.Kedro has also wonBest Technical Tool or Framework for AIin the 2019 Awards AI competition and a merit award for the 2020UK Technical Communication Awards. It is listed on the 2020ThoughtWorks Technology Radarand the 2020Data & AI Landscape.How can I cite Kedro?If you're an academic, Kedro can also help you, for example, as a tool to solve the problem of reproducible research. Use the \"Cite this repository\" button onour repositoryto generate a citation from theCITATION.cff file."} +{"package": "xedu", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xee", "pacakge-description": "Xee: Xarray + Google Earth EngineAn Xarray extension for Google Earth Engine.How to useInstall with pip:pipinstall--upgradexeeInstall with conda:condainstall-cconda-forgexeeThen, authenticate Earth Engine:earthengineauthenticate--quietNow, in your Python environment, make the following imports:importeeimportxarrayNext, initialize the EE client with the high volume API:ee.Initialize(opt_url='https://earthengine-highvolume.googleapis.com')Open any Earth Engine ImageCollection by specifying the Xarray engine as'ee':ds=xarray.open_dataset('ee://ECMWF/ERA5_LAND/HOURLY',engine='ee')Open all bands in a specific projection (not the Xee default):ds=xarray.open_dataset('ee://ECMWF/ERA5_LAND/HOURLY',engine='ee',crs='EPSG:4326',scale=0.25)Open an ImageCollection (maybe, with EE-side filtering or processing):ic=ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY').filterDate('1992-10-05','1993-03-31')ds=xarray.open_dataset(ic,engine='ee',crs='EPSG:4326',scale=0.25)Open an ImageCollection with a specific EE projection or geometry:ic=ee.ImageCollection('ECMWF/ERA5_LAND/HOURLY').filterDate('1992-10-05','1993-03-31')leg1=ee.Geometry.Rectangle(113.33,-43.63,153.56,-10.66)ds=xarray.open_dataset(ic,engine='ee',projection=ic.first().select(0).projection(),geometry=leg1)Open multiple ImageCollections into onexarray.Dataset, all with the same projection:ds=xarray.open_mfdataset(['ee://ECMWF/ERA5_LAND/HOURLY','ee://NASA/GDDP-CMIP6'],engine='ee',crs='EPSG:4326',scale=0.25)Open a single Image by passing it to an ImageCollection:i=ee.ImageCollection(ee.Image(\"LANDSAT/LC08/C02/T1_TOA/LC08_044034_20140318\"))ds=xarray.open_dataset(i,engine='ee')Seeexamplesordocsfor more uses and integrations.How to run integration testsThe Xee integration tests only pass on Xee branches (no forks). Please run the\nintegration tests locally before sending a PR. To run the tests locally,\nauthenticate usingearthengine authenticateand run the following:USE_ADC_CREDENTIALS=1python-munittestxee/ext_integration_test.pyLicenseThis is not an official Google product.Copyright 2023 Google LLC\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n https://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xeemon", "pacakge-description": "Application Monitoring Server"} +{"package": "xeet", "pacakge-description": "No description available on PyPI."} +{"package": "xefab", "pacakge-description": "Fabric based task execution for the XENON dark matter experimentInstallationTo install xefab, its recomended to usepipx:$pipxinstallxefabAlternatively you can install it using pip:$pipinstallxefabUsageYou can list the available tasks and options by running xf/xefab without any options.$xfUsage: xf [--core-opts] [<host>] [<subcommand>] task1 [--task1-opts] ... taskN [--taskN-opts]\n\nCore options:\n\n--complete Print tab-completion candidates for given parse remainder.\n--hide=STRING Set default value of run()'s 'hide' kwarg.\n--print-completion-script=STRINGPrint the tab-completion script for your preferred shell (bash|zsh|fish).\n--prompt-for-login-password Request an upfront SSH-auth password prompt.\n--prompt-for-passphrase Request an upfront SSH key passphrase prompt.\n--prompt-for-sudo-password Prompt user at start of session for the sudo.password config value.\n--write-pyc Enable creation of .pyc files.\n-d, --debug Enable debug output.\n-D INT, --list-depth=INT When listing tasks, only show the first INT levels.\n-e, --echo Echo executed commands before running.\n-f STRING, --config=STRING Runtime configuration file to use.\n-F STRING, --list-format=STRING Change the display format used when listing tasks. Should be one of: flat (default), nested,\n json.\n-h [STRING], --help[=STRING] Show core or per-task help and exit.\n-H STRING, --hosts=STRING Comma-separated host name(s) to execute tasks against.\n-i, --identity Path to runtime SSH identity (key) file. May be given multiple times.\n-l [STRING], --list[=STRING] List available tasks, optionally limited to a namespace.\n-p, --pty Use a pty when executing shell commands.\n-R, --dry Echo commands instead of running.\n-S STRING, --ssh-config=STRING Path to runtime SSH config file.\n-t INT, --connect-timeout=INT Specifies default connection timeout, in seconds.\n-T INT, --command-timeout=INT Specify a global command execution timeout, in seconds.\n-V, --version Show version and exit.\n-w, --warn-only Warn, instead of failing, when shell commands fail.\n\n\nSubcommands:\n\nshow-context Show the context being used for tasks.\nadmin.user-db\ndali.download-file Download a file from a remote server.\ndali.sbatch Create and submit a job to SLURM job queue on the remote host.\ndali.show-context Show the context being used for tasks.\ndali.squeue (dali.job-queue) Get the job-queue status.\ndali.start-jupyter Start a jupyter analysis notebook on the remote host and forward to local port via ssh-tunnel.\ndali.upload-file Upload a file to a remote server.\ngithub.clone\ngithub.is-private\ngithub.is-public\ngithub.token\ngithub.xenon1t-members\ngithub.xenonnt-keys\ngithub.xenonnt-members\ninstall.chezmoi\ninstall.get-system\ninstall.github-cli (install.gh)\ninstall.gnupg (install.gpg)\ninstall.go\ninstall.gopass\ninstall.miniconda (install.conda)\ninstall.which\nmidway.download-file Download a file from a remote server.\nmidway.sbatch Create and submit a job to SLURM job queue on the remote host.\nmidway.show-context Show the context being used for tasks.\nmidway.squeue (midway.job-queue) Get the job-queue status.\nmidway.start-jupyter Start a jupyter analysis notebook on the remote host and forward to local port via ssh-tunnel.\nmidway.upload-file Upload a file to a remote server.\nmidway3.download-file Download a file from a remote server.\nmidway3.sbatch Create and submit a job to SLURM job queue on the remote host.\nmidway3.show-context Show the context being used for tasks.\nmidway3.squeue (midway3.job-queue)Get the job-queue status.\nmidway3.start-jupyter Start a jupyter analysis notebook on the remote host and forward to local port via ssh-tunnel.\nmidway3.upload-file Upload a file to a remote server.\nosg.condorq (osg.job-queue)\nosg.mc-chain Run a full chain MC simulation\nsecrets.setup\nsecrets.setup-utilix-config\nsh.exists\nsh.get-system\nsh.is-dir\nsh.is-file\nsh.path\nsh.shell (sh) Open interactive shell on remote host.\nsh.whichYou can get help for a specific task by running e.g.$xf--helpmidway3.start-jupyter\u256d\u2500 start-jupyter \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 xf [--core-opts] start-jupyter [--options][other tasks here ...] \u2502\n\u2502 \u2502\n\u2502 Start a jupyter analysis notebook on the remote host and forward to local port via ssh-tunnel. \u2502\n\u2502 \u2502\n\u2502 Options: \u2502\n\u2502 --image-dir=STRING Directory to look for singularity images \u2502\n\u2502 --remote-port=STRING Port to use for jupyter server to on the worker node \u2502\n\u2502 --=INT, --local-port=INT Local port to attempt to forward to (if free) \u2502\n\u2502 -a INT, --max-hours=INT Maximum number of hours to run for \u2502\n\u2502 -b, --bypass-reservation Dont attempt to use the xenon notebook reservation \u2502\n\u2502 -c INT, --cpu=INT Number of CPUs to request \u2502\n\u2502 -d, --detached Run the job and exit, dont perform cleanup tasks. \u2502\n\u2502 -e STRING, --env=STRING Environment to run on \u2502\n\u2502 -f, --force-new Force a new job to be started \u2502\n\u2502 -g, --gpu Use a GPU \u2502\n\u2502 -i STRING, --binds=STRING Directories to bind to the container \u2502\n\u2502 -j STRING, --jupyter=STRING Type of jupyter server to start (lab or notebook) \u2502\n\u2502 -l, --local-cutax Use user installed cutax (from ~/.local) \u2502\n\u2502 -m INT, --timeout=INT Timeout for the job to start \u2502\n\u2502 -n STRING, --node=STRING Node to run on \u2502\n\u2502 -o STRING, --notebook-dir=STRING Directory to start the notebook in \u2502\n\u2502 -p STRING, --partition=STRING Partition to run on (xenon1t or dali) \u2502\n\u2502 -r INT, --ram=INT Amount of RAM to allocate (in MB) \u2502\n\u2502 -t STRING, --tag=STRING Tag of the container to use \u2502\n\u2502 -u, --debug Print debug information \u2502\n\u2502 -w, --no-browser Dont open the browser automatically when done \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256fSome tasks are registered to run on a specific host. When you run them, the \u2013hosts option will be ignored.e.g. if you run$xfmidway3start-jupyterThe task will be run on the midway3 host, not the host you specified with \u2013hosts.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xeger", "pacakge-description": "XegerLibrary to generate random strings from regular expressions.To install, type:pip install xegerTo use, type:>>> from xeger import Xeger\n>>> x = Xeger(limit=10) # default limit = 10\n>>> x.xeger(\"/json/([0-9]+)\")\nu'/json/15062213'AboutCode adapted and refactored from the Python libraryrstr by Leapfrog Online(now iProspect),\nin turn inspired by the Java libraryXeger."} +{"package": "xeHentai", "pacakge-description": "E-Hentai D\u014djinshi Downloader\u7b80\u4f53\u4e2d\u6587\u7e41\u9ad4\u4e2d\u6587xeHentai WebUITL;DRWindows users can download packed binaries fromhereorhere. The package is built usingPyInstaller.Or run directly from source code:pipinstall-Urequests[socks]gitclonehttps://github.com/fffonion/xeHentai.gitcdxeHentai\npython./setup.pyinstall\nxeHThe program is running in non-interactive mode by default. To run interactively, usexeH.py -i.For prosConfiguration fileIf you are running from source code, please copyxeHentai/config.pyto your current directory first. Use that file as your config file.The priority of configuration is: Interactive inputs > Command line options > User config.py > Internal config.py.Configuration keys\uff1adaemonSet to run in default mode, can only use on posix-compatible systems. Refer toRunning Modes. Default toFalse.dirDownload directory. Default to current directory.download_oriSet to download original images or not. Default toFalse.jpn_titleSet to select Japanese title or not. If set toFalse, English or Romaji title will be used. Default toTrue.rename_oriSet to rename images to their orginal names. If set toFalse, image will be named in sequence numbers. Default toFalse.proxyProxy list. Refer toProxies.proxy_imageSet to use proxy both on downloading images and scanning webpages. Default toTrue.proxy_image_onlySet to use proxy only on downloading images. Default toFalse.rpc_interfaceRPC server binding IP. Refer toJSON-RPC. Default tolocalhost.rpc_portRPC server binding port. Default tonone(not serving).rpc_secretRPC secret key. Default toNone.delete_task_filesSet to delete downloaded files when deleting a task. Default toFalse.make_archiveSet to make a ZIP archive after download and delete downloaded directory. Default toFalse.download_rangeSet image download range. Refer toDownload range. Default to download all images.scan_thread_cntThread count for scanning webpages. Default to1.download_thread_cntThread count for downloading images. Default to5.download_timeoutTimeout of download images. Default to10s.ignored_errorsSet the error codes to ignore and continue downloading. Default toempty. Error codes can be obtained fromconst.py.log_pathSet log file path. Default toeh.log.log_verboseSet log level with integer from 1 to 3. Bigger value means more verbose output. Default to2.save_tasksSet to save uncompleted tasks inh.json. Default toFalse.Command line optionsUsage: xeH [-u USERNAME] [-k KEY] [-c COOKIE] [-i] [--daemon] [-d DIR] [-o]\n [-j BOOL] [-r BOOL] [-p PROXY] [--proxy-image | --proxy-image-only]\n [--rpc-interface ADDR] [--rpc-port PORT] [--rpc-secret ...]\n [--delete-task-files BOOL] [-a BOOL] [--download-range a-b,c-d,e]\n [-t N] [--timeout N] [-f] [-l /path/to/eh.log] [-v] [-h]\n [--version]\n [url [url ...]]\n\nxeHentai Downloader NG\n\npositional arguments:\n url gallery url(s) to download\n\noptional arguments:\n -u USERNAME, --username USERNAME\n username\n -k KEY, --key KEY password\n -c COOKIE, --cookie COOKIE\n cookie string, will be overriden if given -u and -k\n -i, --interactive interactive mode, will be ignored in daemon mode\n (default: False)\n --daemon daemon mode, can't use with -i (default: False)\n -d DIR, --dir DIR set download directory (current:\n /Users/fffonion/Dev/Python/xeHentai)\n -o, --download-ori download original images, needs to login (current:\n True)\n -j BOOL, --jpn-title BOOL\n use Japanese title, use English/Romaji title if turned\n off (default: True)\n -r BOOL, --rename-ori BOOL\n rename gallery image to original name, use sequence\n name if turned off (default: False)\n -p PROXY, --proxy PROXY\n set download proxies, can be used multiple times,\n currenlty supported: socks5/4a, http(s), glype.\n Proxies are only used on webpages by default (current:\n ['socks5h://127.0.0.1:16963'])\n --proxy-image use proxies on images and webpages (default: True)\n --proxy-image-only only use proxies on images, not webpages (current:\n False)\n --rpc-interface ADDR bind jsonrpc server to this address (current:\n localhost)\n --rpc-port PORT bind jsonrpc server to this port (default: 8010)\n --rpc-secret ... jsonrpc secret string (default: None)\n --delete-task-files BOOL\n delete downloaded files when deleting a task (default:\n True)\n -a BOOL, --archive BOOL\n make an archive (.zip) after download and delete\n directory (default: False)\n --download-range a-b,c-d,e\n specify ranges of images to be downloaded, in format\n start-end, or single index, use comma to concat\n multiple ranges, e.g.: 5-10,15,20-25, default to\n download all images\n -t N, --thread N download threads count (default: 5)\n --timeout N set image download timeout (default: 10s)\n -f, --force download regardless of quota exceeded warning\n (default: False)\n -l /path/to/eh.log, --logpath /path/to/eh.log\n define log path (current:\n /Users/fffonion/Dev/Python/xeHentai/eh.log)\n -v, --verbose show more detailed log (default: 3)\n -h, --help show this help message and exit\n --version show program's version number and exitIf options are not defined, values fromconfig.pywill be used.JSON-RPCIfrpc_interfaceandrpc_portare set, xeHentai will start a RPC server. The request and response follows theJSON-RPC 2.0standard.$ curl localhost:8010/jsonrpc -d '{\"jsonrpc\": \"2.0\", \"id\": 1, \"method\":\"xeH.addTask\", \"params\":[[args],{kwargs}]}'\n{\"jsonrpc\": \"2.0\", \"id\": 1, \"result\": \"36df423e\"}rpc_secretis a secret key to your RPC server. If it's set, client should include this value in the request. For example whenrpc_secretis set tohentai:$ curl localhost:8010/jsonrpc -d '{\"jsonrpc\": \"2.0\", \"id\": 1, \"method\":\"xeH.addTask\", \"params\":[\"token:hentai\",[args],{kwargs}]}'\n{\"jsonrpc\": \"2.0\", \"id\": 1, \"result\": \"36df423e\"}The method filed should start withxeH.and should be a public class method ofxeHentaifromcore.py. And change the name fromlower_case_with_underscoresnotation tolowerCamelCasenotation. For example,add_taskbecomesaddTask.Refer toxeHentaiclass fromcore.pyfor parameters list.If your browser has a Userscript plugin, you can usexeHentaiHelper.user.jsto create tasks directly on e-hentai website. Chrome user will need to installTampermonkey, for firefoxGreasemonkey, and ViolentMonkey for Opera and Maxthon users.Because e-hentai has enabled https, Chrome user will needs to click on the shield icon in the far right of the address bar and click \"Load anyway\" or \"Load unsafe scripts\"Running modesIf xeHentai is ran from command line interface or interative mode, the program will exit after it finishes the tasks inh.json(if exists) and given URL.If there's no URL given from command line, the program will exit after it finishes the tasks inh.json(if exists).If program is running on daemon mode (-dis set ordaemonis set toTrue), the program will keep running in background.ProxiesxeHentai supports three types of proxies:socks proxy:socks5h://127.0.0.1:1080. If you want to resolve DNS on client side, usesocks5://127.0.0.1:1080.http(s) proxy:http://127.0.0.1:8080.glype proxy:http://example.com/browse.php?u=a&b=4. Please set value ofbaccordingly. glype is a widely used PHP proxy script. When using, uncheckEncrypt URL,Remove Scriptsand checkAllow Cookiesand open a random URL. The paste the address into configuration.Multiple proxies can be specified at the same time. The format can be like :['socks5h://127.0.0.1:1080', 'http://127.0.0.1:8080'].By default proxies are used to download images and scan webpages. If you don't want to use proxy on downloading images, setproxy_imagetoFalse.glype users are encouraged to setproxy_imagetoFalse\u3002If you only want to use proxy to download image, setproxy_image_onlytoTrueinconfig.pyor use the--proxy-image-onlyCLI option. If bothproxy_imageandproxy_image_onlyare set toTrue,proxy_imagewill be ignored.Download rangeDownload ranges are set in formatstart_positoin-end_positoin. For example,5-10means number download first 5 to 10 images, including 5 and 10. Or use15to download number 15 only.Multiple ranges can be seperated with comma. For example,5-10,15.If no range is given, xeHentai will download all images.MiscImage limitDownloading images will be count towards image limit. This is calculated regarding the popularity of gallery, the server load and/or Hentai@Home bandwidth by e-hentai server.LicenseGPLv3BlogChangelog2.020\u589e\u52a0RPC\u5e2e\u52a9\u51fd\u6570\uff1aget_info\uff0cget_config\uff0cupdate_config\uff0cget_image\u589e\u52a0\u901a\u8fc7RPC\u770b\u56fe\u548c\u4e0b\u8f7d\u538b\u7f29\u5305\u529f\u80fd\u589e\u52a0delete_task_files\u9009\u9879\uff0c\u8bbe\u7f6e\u662f\u5426\u5220\u9664\u4efb\u52a1\u65f6\u540c\u65f6\u5220\u9664\u4e0b\u8f7d\u7684\u6587\u4ef6\u4fee\u590dWindows\u6587\u4ef6\u5939\u4e0d\u80fd\u4ee5\u7a7a\u683c\u7ed3\u5c3e\u4ee5\u53ca\u6587\u4ef6\u4e0d\u80fd\u4ee5.\u7ed3\u5c3e\u4fee\u590d\u4e0b\u8f7d\u65f6\u7684\u4e34\u65f6\u6587\u4ef6\u5728Windows\u4e0b\u62a5\u9519Error 32\u7684\u95ee\u98982.019\u589e\u52a0\u56fe\u7247\u5730\u5740\u89e3\u6790\u65f6\u7684\u9519\u8bef\u5904\u7406\u589e\u52a0\u4f7f\u7528\u6d41\u6a21\u5f0f\u4e0b\u8f7d\u56fe\u7247\uff0c\u4f18\u5316\u5224\u65ad\u4e27\u5c38\u7ebf\u7a0b\u4fee\u590d\u65e0\u6cd5\u4ece\u73af\u5883\u53d8\u91cf\u4e2d\u83b7\u5f97LOCALE\u65f6\u7684\u95ee\u9898\u4fee\u590dunichr\u88ab\u5f53\u6210\u5c40\u90e8\u53d8\u91cf\u7684\u95ee\u9898\u4fee\u590d\u4ea4\u4e92\u6a21\u5f0f\u5728Python3\u4e2d\u7684\u4e00\u4e2a\u95ee\u98982.018\u589e\u52a0jpn_title\u9009\u9879\uff0c\u9009\u62e9\u662f\u5426\u4f7f\u7528\u65e5\u8bed\u6807\u9898\u589e\u52a0download_range\u9009\u9879\uff0c\u9009\u62e9\u4e0b\u8f7d\u8303\u56f4\u589e\u52a0timeout\u9009\u9879\uff0c\u8bbe\u7f6e\u4e0b\u8f7d\u56fe\u7247\u7684\u8d85\u65f6\u589e\u52a0proxy_image_only\u9009\u9879\uff0c\u8bbe\u7f6e\u4ec5\u4f7f\u7528\u4ee3\u7406\u4e0b\u8f7d\u56fe\u7247\u547d\u4ee4\u884c\u589e\u52a0--force\u9009\u9879\uff0c\u8bbe\u7f6e\u5ffd\u7565\u914d\u989d\u7ee7\u7eed\u4e0b\u8f7d; 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the last step is to point your WSGI server toxelpaste.wsgi.ConfigurationXelpaste will read all configuration files matching/etc/xelpaste/*.ini.\nThose are ini-style files, defining the following parameters:Application ([app])General behavior of the application.Options:modestr, the application mode.\nUsedevfor local development andprodotherwise.debugbool, whether to enable debug.\nValid values:on,offsecret_keystr,REQUIREDinprodmode.\nA secret key for Django security hooksSite ([site])Hosting and URLs.Options:namestr, the name of your site (xelpaste,mypaster, \u2026).base_urlstr, where your site is hosted.\nA trailing slash isrequired.assets_urlstr, the URL where assets (CSS, JS, \u2026) are served.\nMay be a relative URL.admin_mailstr, the email where the admin should be notified.allowed_hostsstr list, comma-separated list of validHost:HTTP headers.\nSee Django docs for details.Database ([db])Required; these define where snippets will be stored.\nValid options are:enginestr, the engine to choose.\nMust be one ofsqlite,mysql,postgresql; default issqlite.namestr, the name of the database, or its path for sqlite.\nDefaults to/var/lib/xelpaste/db.sqlite.hoststr, the host of the database server.portint, the port of the database server.userstr, the login to use to connect to the database server.passwordstr, the password for the databaseExamples:; A Postgresql configuration; uses default psql port.[db]engine=postgresqlname=xelpastehost=psql42.local; A sample sqlite configuration.[db]engine=sqlitename=/data/replicated/xelpaste/db.sqliteSnippets ([snippets])Options for snippets behavior.slug_lengthint, the length of the snippet tags.max_contentsize, the maximum size of code snippets.\nValid values include10kB,2MB, \u2026max_filesize, the maximum size for uploads\nValid values include10kB,2MB, \u2026Uploads ([uploads])Options related to private file uploads.dirpath, storage folder for uploads.\nMust be writable by the WSGI process.Example:/var/www/xelpaste/uploadsservestr, the file serving mode.xelpasterelies ondjango-sendfileto enhance performance and protection.Valid options:simple,nginx,xsendfile,mod_wsgi.internal_urlstr, the internal URL used by django-sendfile to serve the files."} +{"package": "xEmail", "pacakge-description": "No description available on PyPI."} +{"package": "xemc3", "pacakge-description": "xemc3A library for working with EMC3 simulations using the xarray framework.ExamplesExamples can be found underdocs/examplesand you can try themonline on binderDocumentationThe documentation can be found onread the docsInstallationpipinstallxemc3CitationIf you use xemc3, please cite it usingDOI: 10.5281/zenodo.5562265"} +{"package": "xemd", "pacakge-description": "No description available on PyPI."} +{"package": "xemeler", "pacakge-description": "xemelerThe best way to work with XML in Python."} +{"package": "xem-wrapper", "pacakge-description": "No description available on PyPI."} +{"package": "xena", "pacakge-description": "null"} +{"package": "xena-gdc-etl", "pacakge-description": "Extract, transform and loadGDC dataontoUCSC Xena.Table of ContentsDependenciesInstallationBasic usage with command line toolsAdvanced usage with XenaDataset and its subclassesGDC ETL settingsDocumentationDependenciesSpecific versions mentioned below have been tested. Eariler versions may still work but not guaranteed.Python 2.7, 3.5+This pipeline has been tested with python 2.7, 3.5, 3.6 and 3.7. It may also\nwork with other python 3 versions since it was originally designed to besingle-source Python 2/3 compatible.Requestsv1.2.3Numpyv1.15.0Pandasv0.23.2Jinja2v2.10.1: used for generating metadata JSON.lxmlv4.2.0: used for parsing TCGA phenotype dataxlrdv1.1.0: used for reading TARGET phenotype dataInstallationFirst clone the repository from GitHub by runninggit clonehttps://github.com/ucscXena/xena-GDC-ETL.git. Now,cdintoxena-GDC-ETLdirectory and install the package using pip:pip install .If you are developing the package, you can usepip\u2019s edit mode for\ninstallation:pip install-e..You can also directly usepipto install the package. To get the latest\ncode from GitHub master branch, run:pip installgit+https://github.com/ucscXena/xena-GDC-ETL.\nTo get the latest stable version, run:pip installxena-GDC-ETL.Dependencies can be installed either before or after cloning this repository.\nYou can install them by runningpip install-rrequirements.txt.In general,gdc.pycontains functionalities related to GDC API, which requires no other modules in this package;xena_dataset.pycontains core functionalities for importing data from GDC to Xena and needs thegdc.pymodule in this package;gdc2xena.pydefinesa command line toolwhich requires bothgdc.pymodule andxena_dataset.pymodule in this package;gdc_check_new.pydefinesa command line toolwhich requiresthegdc.pymodule in this package.Basic usage with command line toolsImport selected project(s) and selected type(s) of data from GDC to Xenaxgeetl[-h][-rROOT][-pPROJECTS[PROJECTS...]|-PNOT_PROJECTS[NOT_PROJECTS...]][-tDATATYPE[DATATYPE...]|-TNOT_DATATYPE[NOT_DATATYPE...]][-DDELETE]This tool will perform a full import of dataset(s) into the root directory (specified by the-roption) with a default directory tree. In general, a full import has 3 steps: downloading raw data, making Xena matrix from raw data and generating matrix associated metadata. Data from each step will be saved to corresponding directories, whose structure is like this:root\n\u2514\u2500\u2500 projects\n \u251c\u2500\u2500 \"Raw_Data\"\n \u2502 \u2514\u2500\u2500 xena_dtype\n \u2502 \u251c\u2500\u2500 data1\n \u2502 \u251c\u2500\u2500 data2\n \u2502 \u251c\u2500\u2500 ...\n \u2502 \u2514\u2500\u2500 dataN\n \u2514\u2500\u2500 \"Xena_Matrices\"\n \u251c\u2500\u2500 projects.xena_dtype(1).tsv\n \u251c\u2500\u2500 projects.xena_dtype(1).tsv.json\n \u251c\u2500\u2500 projects.xena_dtype(2).tsv\n \u251c\u2500\u2500 projects.xena_dtype(2).tsv.json\n \u251c\u2500\u2500 ...\n \u251c\u2500\u2500 projects.xena_dtype(N).tsv\n \u2514\u2500\u2500 projects.xena_dtype(N).tsv.jsonA dataset is defined by its project and data type. Projects of interest are provided through-por-Poption, and data types of interest are provided through the-tor-Toption. Multiple inputs separated by whitespace are allowed and will be treated separately with all possible combinations. Valid projects should be valid project_id on GDC. Valid data types includes (without quotation marks): \u2018htseq_counts\u2019, \u2018htseq_fpkm\u2019, \u2018htseq_fpkm-uq\u2019, \u2018mirna\u2019, \u2018masked_cnv\u2019, \u2018muse_snv\u2019, \u2018mutect2_snv\u2019, \u2018somaticsniper_snv\u2019, \u2018varscan2_snv\u2019, \u2018phenotype\u2019, and \u2018survival\u2019. Upper case options (-Por-T) are mutually exclusive with corresponding lower case options, and they are used to define datasets of interest by excluding selections from either all projects on GDC or all supported data types. For example, the following command line imports 3 types of RNA-seq data for all but FM-AD projects from GDC to /home/user/xena_root:mkdir-p/home/user/xena_rootxgeetl-PFM-AD-thtseq_countshtseq_fpkmhtseq_fpkm-uqNotes:Root directory must be existingPlease check the next section foradvanced usage with XenaDataset and its subclasses, if you want to customize the importing process with selected (rather than all possible) combinations of your input projects and data types or selected (rather than all 3) importing step(s).Generate metadata of a xena matrixxgemetadata--projectTCGA-BRCA--datatypehtseq_counts--matrixpath/to/matrix.tsv--release10This tool generates metadata for a xena matrix. For the shown example, metadata\nis generated for the matrixmatrix.tsvfor release10, projectTCGA-BRCAand datatypehtsep_counts. Note that, metadata JSON file is\nsaved at the same directory as thematrix.tsvfile.Check against a list of updated files for affected dataset(s)xgegdc_check_new[-h]URLThis tool takes in a file (either a URL or a local file readable bypandas.read_csv) of table and read one of its columns named as \u201cNew File UUID\u201d. It then checks all file UUIDs in this table on GDC and summarize all their associated project(s), data type(s) and analysis workflow type(s). Such tables are usually provided in GDC\u2019s data release note. With the summarized info, you can design specific imports to just update datasets which are updated on GDC. For example, the following command:xgegdc_check_newhttps://docs.gdc.cancer.gov/Data/Release_Notes/DR9.0_files_swap.txt.gzshould give you:analysis.workflow_typecases.project.project_iddata_typeHTSeq-FPKMTARGET-NBLGeneExpressionQuantificationHTSeq-FPKM-UQTARGET-NBLGeneExpressionQuantificationHTSeq-CountsTARGET-NBLGeneExpressionQuantificationShows the current version of xena_gdc_etlxge--versionCheck equality of two xena matricesxgexena-eqlpath/to/matrix1.tsvpath/to/matrix2.tsvThis tool takes path to two xena matrices and output if they are equal or not.Merge xena matricesxgemerge-xena-fpath/to/matrix1.tsvpath/to/matrix2.tsv-thtseq_counts-opath/to/output-nnew_name.tsv-cTCGA-BRCAThis tool merges xena matrices and outputs the merged matrix. For the given\nexample the tool will mergematrix1.tsvandmatrix2.tsvmatrices and\nstore the merged matrix inpath/to/outputdirectory with the namenew_name.tsv. Note that, had the argument-nnot been\nspecified, the merged matrix would have been saved asTCGA-BRCA.htseq_counts.tsv.Advanced usage with XenaDataset and its subclassesTheXenaDatasetclassThough this is not an abstract class, it is designed as a generalized class representing one Xena dataset and its importing process. For doing an import of GDC data, use itssubclasses, which have preloaded with some default settings, might be simpler.A Xena dataset is defined by its study project (cohort) and the type of data in this dataset. A typical importing process has the following 3 steps:Download raw data from the source.Thedownload_mapproperty defines a dict of raw data to be downloaded, with the key being the URL and the value being the path, including the filename, for saving corresponding downloaded file. Thedownloadmethod will read thedownload_mapand perform the downloading, creating non-existing directories as needed. After downloading all files, a list of paths for downloaded files will be recorded in theraw_data_listproperty. Thedownloadmethod needs only a validdownload_map. It will return the object itself, therefore can be chained withtransform.Transform raw data into valid Xena matrix.One assumption for data transformation is that there might be multiple raw data (in theraw_data_list) supporting the single Xena matrix in a dataset. Therefore, thetransformmethod will first merge data and then process merged matrix as needed. It will open the file one by one accordingly (by extension), and read the file object and transform its data with a function defined byread_raw. The list of transformed single data will be merged and processed by a function defined byraws2matrix, which gives the finalized Xena matrix. Thetransformmethod requires a valid list of raw data, besidesread_rawandraws2matrix. A valid list of raw data can be either explicitly defined byraw_data_listor can be derived fromraw_data_dirwith all files underraw_data_dirbeing treated as raw data. It will return the object itself, therefore can be chained withmetadata.Generate metadata for the new Xena matrix.Metadata for Xena matrix is a JSON file rendered by themetadatamethod withmetadata_vars(dict) through Jinja2 frommetadata_template. This JSON file will be saved under the same directory as the matrix, with a filename being the matrix name plus the \u2018.json\u2019 postfix. Themetadatamethod requires an existing file of Xena matrix.root_diris both an optional instantiation arguments and a property. By default, it points to the current working directory. It is worth mentioning that the default directory structure mentioned above is implemented in the class. However, you are free to changed the setting with the following properties:Pass an argument forroot_dirduring instantiation or set theroot_dirproperty explicitly after instantiation.Downloaded raw data will be saved underraw_data_dir.Newly transformed Xena matrix will be saved asmatrixundermatrix_dir. The directory path inmatrixhas the priority overmatrix_dir. By default, Xena matrix will be saved under the \u201cmatrix_dir\u201d as \u201c<projects>.<xena_dtype>.tsv\u201d.Metadata will always have the specific pattern of name and be together withmatrix(i.e. no way to change this behavior).Build GDC importing pipelines withGDCOmicset,GDCPhenosetorGDCSurvivalsetclassesGDCOmicset,GDCPhenosetandGDCSurvivalsetare subclasses ofXenaDatasetand are preloaded with settings for importing GDC genomic data, TCGA phenotype data on GDC, TARGET phenotype data on GDC and GDC\u2019s survival data respecitively. These settings can be customized by setting corresponding properties described below. For more details, please check thenext sectionand thedocumentation.The script forgdc2xena.pycommand line is a good example for basic usage of these classes. Similar toXenaDataset, a GDC dataset is defined byprojects, which is one or a list of valid GDC \u201cproject_id\u201d. ForGDCOmicset, a dataset should also be defined with one of the supportedxena_dtype(find out with the class methodGDCOmicset.get_supported_dtype()). Thexena_dtypeis critical for aGDCOmicsetobject selecting correct default settings. ForGDCPhenosetandGDCSurvivalset, data type are self-explanatory and cannot be changed. Therefore, you can instantiate these classes like this:fromxena_datasetimportGDCOmicset,GDCPhenoset,GDCSurvivalset,GDCAPIPhenosetgdc_omic_cohort=GDCOmicset('TCGA-BRCA','htsep_counts')# Won't check if the ID is of TCGA program or not.tcga_pheno_cohort=GDCPhenoset('TCGA-BRCA')# Won't check if the ID is of TARGET program or not.target_pheno_cohort=GDCPhenoset('TARGET-NBL')gdc_survival_cohort=GDCSurvivalset('TCGA-BRCA')gdc_api_pheno_cohort=GDCAPIPhenoset('CPTAC-3')With such a dataset object, it is fine to calldownload,transformand/ormetadatamethod(s). These methods will use preloaded settings and save files underroot_diraccordingly. You are free to call/chain some but not all 3 methods; just keep in mind the pre-requisites for each method and set related properties properly. Aside fromdirectory related settingsdescribed above, you can change some default importing settings through the following properties.CustomizeGDCOmicsetAttributesUsageType and Format1Default settingsgdc_filterUsed for deriving defaultdownload_mapas the GDC search filters.dict: the key is 1 GDC available file field and the value is either a string or a list, meaning the value of the file field matches a string or number in (a list)CheckGDC download settingsfor details.gdc_prefixUsed for deriving defaultdownload_mapas the GDC search fields.str: 1 GDC available file field whose value will be the prefix of the filename of corresponding downloaded file.CheckGDC download settingsfor details.download_mapUsed by thedownloadmethod for downloading GDC raw data supporting this dataset.dict: the key is download URL and the value is the desired path for saving the downloaded file.Download URLs are in the pattern of \u201chttps://api.gdc.cancer.gov/data/<FILE UUID>\u201d, and paths are in the pattern of \u201c<raw_data_dir>/<value of gdc_prefix>.<GDC file UUID>.<file extension>\u201d.read_rawUsed by thetransformmethod when reading a single GDC raw data.callable: takes only 1 file object as its argument and returns an arbitrary result which will be put in a list and passed on toraws2matrix.CheckGDC genomic transform settingsfor detailsraws2matrixUsed by thetransformmethod and responsible for both merging multiple GDC raw data into one Xena matrix and processing new Xena matrix as needed.callable: takes only 1 list ofread_rawreturns as its argument and returns an object (usually a pandas DataFrame) which has ato_csvmethod for saving as a file.CheckGDC genomic transform settingsfor detailsmetadata_templateUsed by themetadatamethod for rendering metadata by Jinja2.jinja2.environment.Templateorstr: ajinja2.environment.Templateused directly by Jinja2; if it\u2019s a string, it is a path to the template file which will be silently read and converted tojinja2.environment.Template.Resourcesmetadata_varsUsed by themetadatamethod for rendering metadata by Jinja2.dict: used directly by Jinja2 which should match variables inmetadata_template.{\n 'project_id': <``projects``>,\n 'date': <the time of last modification of ``matrix``>,\n 'gdc_release': <``gdc_release``>,\n 'xena_cohort': <Xena specific cohort name for TCGA data or GDC project_id for TARGET data, with (for both) \"GDC \" prefix>\n}* The first element of the \u201curl\u201d field in metadata will be \u201cgdc_release\u201d URL, and the second will be specific URL for raw data file if there is only 1 raw data file for this dataset; or it will be just \u201chttps://api.gdc.cancer.gov/data/\u201d.gdc_releaseUsed by themetadatamethod for rendering metadata, showing the GDC data release of this dataset.str: an URL pointing to corresponding GDC Data Release Note.Current data release version when thegdc_releaseis being used/called, queried through \u201chttps://api.gdc.cancer.gov/status\u201d.1. GDC API Available File Fields:https://docs.gdc.cancer.gov/API/Users_Guide/Appendix_A_Available_Fields/#file-fieldsCustomizeGDCPhenosetfor TCGA projectsTCGA phenotype data for Xena includes both clinical data and biospecimen data, asdetailed below. Downloading and transformation of clinical data and biospecimen data are in fact delegated by two independentGDCOmicsetobject respecitively. Corresponding subdatasets can be accessed throughclin_datasetandbio_datasetattributes and hence can be customized as mentioned above. Because of such complexity of TCGA phenotype data, thedownloadandtransformmethods are coded specifically and overrode corresponding methods of the base class,XenaDataset. Customization for downloading and matrix transformation is very limited and should be done in the following steps:Instantiate aGDCPhenoset;Instantiate and customize one or twoGDCOmicsetobjects for clinical data and/or biospecimen data as needed;Assign customizedGDCOmicsetobjects to corresponding attributes,clin_datasetandbio_dataset;Call desired method(s) (downloadand/ortransform).CustomizedownloadstepThis step can be customized only through customizedclin_datasetandbio_dataset, since the whole downloading process is delegated by these two GDCOmicset objects.CustomizetransformstepThe first part oftransformis delegated bytransformmethods ofclin_datasetandbio_dataset. Therefore, the only way to customized this process is to customizeclin_datasetandbio_dataset. How the two matrices are then merged into one Xena phenotype matrix is hard coded and cannot be customized. It is worth noting that if you want to calltransfrombut skip the downloading step, you will need to defineclin_datasetandbio_datasetbefore callingtransform.CustomizemetadatastepDifferent fromdownloadandtransform, there is no special settings for themetadatamethod ofGDCPhenoset. Therefore, similar to that ofGDCOmicset, this step can be customized throughmetadata_template,metadata_varsandgdc_releaseproperties. And to call just themetadatamethod, an existingmatrixis enough.CustomizeGDCPhenosetforTARGET projectsTARGET phenotype data for Xena contains only the clinical data (no biospecimen data), asdetailed below. The importing process is quite similar to that of aGDCOmicset. You can customizeTARGETPhenosetwithdownload_map,read_raw,raws2matrix,metadata_template,metadata_varsandgdc_releasein the same way as that ofGDCOmicset.CustomizeGDCSurvivalsetGDC data supporting Xena survival matrix does not come any GDC files. It comes from the \u201canalysis/survival\u201d endpoint of GDC API. Therefore, thedownloadandtransformmethods are re-designed, overriding those of the base class,XenaDataset. Aside from redefiningdownloadandtransformmethods, there is no simple way to customizedownloadandtransformsteps. You can still calltransformwithoutdownloadby just defining a valid list of raw data withraw_data_listorraw_data_dir. However, only this first file in the list will be read and used.Different fromdownloadandtransform, there is no special settings for themetadatamethod ofGDCSurvivalset. Therefore, similar to that ofGDCOmicset, this step can be customized throughmetadata_template,metadata_varsandgdc_releaseproperties. To call just themetadatamethod, an existingmatrixis enough.CustomizeGDCAPIPhenosetThe data for this class comes from GDC API only. Therefore, thedownloadandtransformmethods are re-designed, overriding those of the base class,XenaDataset. Aside from redefiningdownloadandtransformmethods,\nthere is no simple way to customizedownloadandtransformsteps.Different fromdownloadandtransform, there is no special settings\nfor themetadatamethod ofGDCAPIPhenoset. Therefore, similar to that\nofGDCOmicset, this step can be customized throughmetadata_template,metadata_varsandgdc_releaseproperties. To call just themetadatamethod, an existingmatrixis enough.GDC ETL settingsSettings for downloading/getting raw data (files) from GDCxena_dtypeGDC API endpointGDC data filterFile count/LevelGDC file field for filename prefixdata_typeanalysis.workflow_typehtseq_countsdataGene Expression QuantificationHTSeq - Counts1/Sample vialcases.samples.submitter_idhtseq_fpkmdataGene Expression QuantificationHTSeq - FPKM1/Sample vialcases.samples.submitter_idhtseq_fpkm-uqdataGene Expression QuantificationHTSeq - FPKM-UQ1/Sample vialcases.samples.submitter_idmirnadatamiRNA Expression QuantificationBCGSC miRNA Profiling1/Sample vialcases.samples.submitter_idmirna_isoformdataIsoform Expression QuantificationBCGSC miRNA Profiling1/Sample vialcases.samples.submitter_idcnvdataCopy Number SegmentDNAcopy1/Sample vialcases.samples.submitter_idmasked_cnvdataMasked Copy Number SegmentDNAcopy1/Sample vialcases.samples.submitter_idgisticdataGene Level Copy Number ScoresGISTIC - Copy Number Score1/Projectsubmitter_idstar_countsdataSTARCountsSTAR - Counts1/Sample vialcases.samples.submitter_idmuse_snvdataMasked Somatic MutationMuSE Variant Aggregation and Masking1/Projectsubmitter_idmutect2_snvdataMasked Somatic MutationMuTect2 Variant Aggregation and Masking1/Projectsubmitter_idsomaticsniper_snvdataMasked Somatic MutationSomaticSniper Variant Aggregation and Masking1/Projectsubmitter_idvarscan2_snvdataMasked Somatic MutationVarScan2 Variant Aggregation and Masking1/Projectsubmitter_idclinicaldataClinical SupplementN/A0 or 1/Casecases.submitter_idbiospecimendataBiospecimen SupplementN/A1/Casecases.submitter_idsurvivalanalysis/survivalN/A (filtered by just the \u201cproject.project_id\u201d)1 Record/Case (Non-file)N/A (filename will be \u201c<projects>.GDC_survival.tsv\u201d)Settings for transform \u201cOmic\u201d data into Xena matrixxena_dtypeRaw data has header?Select columns (in order)Row indexSkip rows start with?Merge into matrix asProcess matrixhtseq_countsNo1, 2\n[Ensembl_ID, Counts]Ensembl_ID_1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)htseq_fpkmNo1, 2\n[Ensembl_ID, Counts]Ensembl_ID_1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)htseq_fpkm-uqNo1, 2\n[Ensembl_ID, Counts]Ensembl_ID_1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)mirnaYes1, 3\n[miRNA_ID, RPM]miRNA_IDN/A1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)mirna_isoformYes2, 4\n[isoform_coords, RPM]isoform_coordsN/A1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)cnvYes2, 3, 4, 6\n[Chromosome, Start, End, Segment_Mean]sampleN/ANew rows based on column nameRename columns as:{\n 'Chromosome': 'Chrom',\n 'Segment_Mean': 'value'\n}masked_cnvYes1, 2, 3, 5\n[Chromosome, Start, End, Segment_Mean]sampleN/ANew rows based on column nameRename columns as:{\n 'Chromosome': 'Chrom',\n 'Segment_Mean': 'value'\n}gisticYes1\n[Ensembl_ID]Ensembl_ID_N/ADrop \u201cGene ID\u201d and \u201cCytoband\u201d column;Map \u201csamples.portions.analytes.aliquots.aliquot_id\u201d into \u201csamples.submitter_id\u201d using GDC API and use it as index.muse_snv\nmutect2_snv\nsomaticsniper_snv\nvarscan2_snvYes13, 37, 5, 6, 7, 40, 42, 52, 1, 11, 16, 111\n[Tumor_Seq_Allele2, HGVSp_Short, Chromosome, Start_Position, End_Position, t_depth, t_alt_count, Consequence, Hugo_Symbol, Reference_Allele, Tumor_Sample_Barcode, FILTER]N/A#N/ACalculate variant allele frequency (dna_vaf) by \u201ct_alt_count\u201d/\u201dt_depth\u201d;Delete \u201ct_alt_count\u201d and \u201ct_depth\u201d columns;Trim \u201cTumor_Sample_Barcode\u201d to sample vial level;Rename columns as:{\n 'Hugo_Symbol': 'gene',\n 'Chromosome': 'chrom',\n 'Start_Position': 'start',\n 'End_Position': 'end',\n 'Reference_Allele': 'ref',\n 'Tumor_Seq_Allele2': 'alt',\n 'Tumor_Sample_Barcode': 'sampleid',\n 'HGVSp_Short': 'Amino_Acid_Change',\n 'Consequence': 'effect',\n 'FILTER': 'filter'\n}star_countsYes1, 2\n[Ensembl_ID, Counts]Ensembl_ID_1 new column based on indexAverage if there are multiple data from the same sample vial;log2(counts + 1)Settings for transform phenotype data into Xena matrixGDC programGDC raw dataRaw data formatSingle data file transformationMerge and matrix processingTCGAClinical Supplement and Biospecimen SupplementBCR XMLFor clincial data, info will be extracted and organized into a per patient based pandas DataFrame. It will have a column named \u201cbcr_patient_barcode\u201d which will be used to join with biospecimen matrix later on.The XML scheme are quite different for different projects. Therefore, to get as much info as possible while still keeping things clear, texts, if any, from all elements that have non-element children are extracted first. After such a \u201cdirty\u201d extraction, two clean ups will be done:For \u201crace\u201d info, it will be converted into a comma separated list of races, in case there are more than one entry in <clin_shared:race_list> in the clinical XML.When there is one or more follow ups, the most recent follow up will be find out. All info in the most recent follow up will be used to replace/add to previously extracted matrix.For biospecimen data, there is one coherent XML scheme for all TCGA projects. There are two parts to be considered for biospecimen data: per sample/sample specific data and patient data (which is common for all samples). Info from both parts will be extracted and finally organized into a per sample based matrix, having a column named \u201cbcr_patient_barcode\u201d, which will be used to join with clinical matrxi later on. In general, info extraction has the following 3 steps:Common patient data will be extracted first, including texts from direct children of <admin:admin> and <bio:patient>. A new field of \u201cprimary_diagnosis\u201d will be added by mapping \u201cdisease_code\u201d toTCGA study name.Samples from <bio:patient/bio:samples> will be processed and have comman patient data attached one by one. Non-empty texts from direct children of sample will be extracted, i.e. details from nodes like <bio:portions> will be dropped. Samples havingtype code 10are dropped.A column of \u201cbcr_patient_barcode\u201d from <bio:patient/shared:bcr_patient_barcode> will be added to the final biospecimen matrix (same for the whole table).Multiple clinical data are concatenated directly by row with all empty columns removed.Multiple biospecimen data are concatenated directly by row with all empty columns removed.Merged clinical matrix and merged biospecimen matrix are further merged on \u201cbcr_patient_barcode\u201d. For conflict/overlapping columns, non-empty value from the clinical data has the priority.TARGETClinical Supplement onlyXLSXThe excel file is converted to a pandas DataFrame.Multiple DataFrames will be concatenated directly by row, and arriage return and line feed are replaced by a single space.Clinical data is per case(patient) based, while Xena phenotype matrix is per sample based. All related samples for each case/patient will be identified and phenotype data will be mapped to corresponding samples.Settings for transform survival data into Xena matrixGDC survival data is returned as JSON from GDC API. During the downloading process, it can and will be converted directly to pandas DataFrame and saved as tab delimited table. During transformation, columns in \u201cprimary\u201d Xena survival matrix can be mapped directly (without further processing/calculation) from the raw table like this:Primary Xena columnGDC source columnOS.timetimeOScensored_PATIENTsubmitter_idGDC survival data is per case(patient) based and so is \u201cprimary\u201d Xena survival matrix, while Xena survival matrix is per sample based. All related samples for each case/patient will be identified and survival data will be mapped to corresponding samples.CPTAC-3 CohortCPTAC-3 data consists of RNAseq data (as discussed inGDCOmicset) and\nclinical data from the API. The cases and expand for clinical data are\ndefined in theconstants.pyfile.DocumentationCheck documentation for GDC module and Xena Dataset modulehere."} +{"package": "xenalib", "pacakge-description": "UNKNOWN"} +{"package": "xenapi-python", "pacakge-description": "Unofficial python bindings to XAPI (Xen API) for python 2 and 3This is just copied from the official xenapi repository and packaged\nas a standalone repository for installation as a package.https://github.com/xapi-project/xen-api/tree/master/scripts/examples/pythonUsageimport XenAPIInstallationpip install xenapi-pythonAuthorsSamuel D.Lotzmade this repo for\nconvenience copyrights, authors and licenses are in the code."} +{"package": "xenaPython", "pacakge-description": "No description available on PyPI."} +{"package": "xenarix", "pacakge-description": "No description available on PyPI."} +{"package": "xenavalkyrie", "pacakge-description": "Python OO API for Xena Valkyrie traffic generator.FunctionalityThe current version supports the following test flow:Load/Build configuration -> Change configuration -> Start/Stop traffic -> Get statistics/captureSupported operations:Login, connect to chassis and reserve portsLoad existing configuration fileBuild configuration from scratchGet/set attributesStart/Stop - transmit, captureStatistics - ports, streams (end to ends) and TPLDsCapture - get captured packetsRelease ports and disconnectMigrate from pyxenamanagerPackage renamed from xenamanager to xenavalkyrieXenaStreamsStats.statistics['rx']:Returns all RX statistics indexed by RX port instead of TPLD object.Installationpip install xenavalkyrieGetting startedUnderxenavalkyrie.test.xena_samplesyou will find some basic samples.See inside for more info.Documentationhttp://pyxenavalkyrie.readthedocs.io/en/latest/Usage notesDo not create XenaManager manually but use the init_xena factoryWhen loading configuration files, first load all files only then manipulate the configuration.Related worksThe package replaces pyxenamanager -https://github.com/xenadevel/PyXenaManagerContactFeel free to contact me with any question or feature request atyoram@ignissoft.com"} +{"package": "xenavalkyrie-rest", "pacakge-description": "This package implements stand-alone REST API server to manage Xena Valkyrie chassis.FunctionalityFull REST API with functionality equivalent to the CLI.Installationpip instsll xenavalkyrie-restGetting startedStart the servergunicorn2 xenavalkyrie_rest.wsgi:app -c xenavalkyrie_rest/settings.pyStart the development server./xena_rest_server.pyDocumentationXena CLI does not distinguish between attributes, operations and statistics. All are flat, unstructured, commands.Each object has the following sub-routes - commands, attributes, statistics, operations.\nNote that for some objects some of the sub-routes are not applicable and in this case the sub-route is missing.Commands:\n- Any raw CLI command.The following sub-routes are abstractions on top of the raw CLI commands represented in the commands sub-route.Attributes:\n- Returns all attributes in one call as dictionary\n- Allows set of group of attributesStatistics:\n- Structured statistics.Operations:\n- Strcutured operations. Not supported in first release.CLI documentation -\nswagger UI -http://<SERVER>:<PORT>/api\nswagger version 2.0 JSON -http://<SERVER>:<PORT>/api/swagger.jsonRelated worksxenavalkyrieContactFeel free to contact me with any question or feature request atyoram@ignissoft.com"} +{"package": "xenballoond", "pacakge-description": "No description available on PyPI."} +{"package": "xen-bridge", "pacakge-description": "XEN BridgeAn object-oriented Xen API for pythonTested on XCP-ng, but should also work on XenServerInstallfrom pypi usingpip install xen-bridgeUsagefromxenbridgeimportXenConnectionxen=XenConnection('http://XEN_HOSTNAME','root','password')xoa_vm=xen.VM.get_by_uuid('UUID_OF_VM')# Or by name-label:# xoa_vm = xen.VM.get_by_name_label('XOA')[0]print(f'{xoa_vm.name_label}({xoa_vm.uuid})')print(f'VM is a template:{xoa_vm.is_a_template}')xoa_vm.name_description='This is a VM'xoa_vm.start()# Spin up the VMExceptionsWhile calling API methods, XEN might return an error. When this happens, aXenErroris raised. When catching the exception, the error code can be accessed through theerror_codeattribute# Assuming VM is already running:try:xoa_vm.start()# Should throw an errorexceptxenbridge.XenErrorase:print(e.error_code)# Prints 'VM_BAD_POWER_STATE'How it worksFirstly,xenboject.pydefines some helper functions and baseclasses for the endpoints that do the actual work of calling the XMLRPC API and casting the data to the corresponding types.For each class, there is a file corresponding to that class - for example,vm.py. In here, a class that defines the methods and properties can be found. All methods are wrapped using the@XenMethoddecorator that copies the function's signature and replaces its functionality.classVM(XenObject):@XenMethoddefstart(self,start_paused:bool,force:bool)->None:\"\"\"Start the specified VM. This function can only be called with the VM is in theHalted State.\"\"\"power_state:VmPowerState=XenProperty(XenProperty.READONLY)As the API responds with a string for numbers, enums and Xen objects, the return type annotations are used to cast the objects to the correct type.The XenConnection class is the object that is used to interact with the APIMissing methodsAll API methods are generated from theXenAPI documentationusingdocscraper.py. If there is a method that is missing, you can either:Add it to the corresponding class in the module yourselfCall it using the class'scall(methodname, *args)method and manually cast it to the correct data type"} +{"package": "xendit", "pacakge-description": "Xendit Python LibraryThis library is the abstraction of Xendit API for access from applications written with Python.Table of ContentsXendit Python LibraryTable of ContentsAPI DocumentationRequirementsInstallationUsageAPI KeyGlobal VariableUse Xendit InstanceHeadersObject CreationBalance ServiceGet BalanceCredit CardCreate AuthorizationReverse AuthorizationCreate ChargeCapture ChargeGet ChargeCreate RefundCreate PromotioneWalletsCreate OVO PaymentCreate DANA PaymentCreate LinkAja PaymentGet Payment StatusDirect DebitCreate CustomerGet Customer by Reference IDInitialize Linked Account TokenizationValidate OTP for Linked Account TokenRetrieve Accessible Accounts by Linked Account TokenCreate Payment MethodGet Payment Methods by Customer IDCreate Direct Debit PaymentCreate Recurring Payment with Direct DebitValidate OTP for Direct Debit PaymentGet Direct Debit Payment Status by IDGet Direct Debit Payment Status by Reference IDVirtual Account ServiceCreate Virtual AccountGet Virtual Account BanksGet Virtual AccountUpdate Virtual AccountGet Virtual Account PaymentRetail Outlet ServiceCreate Fixed Payment CodeUpdate Fixed Payment CodeGet Fixed Payment CodeInvoice ServiceCreate InvoiceGet InvoiceExpire InvoiceList All InvoiceRecurring PaymentCreate Recurring PaymentGet Recurring PaymentEdit Recurring PaymentStop Recurring PaymentPause Recurring PaymentResume Recurring PaymentDisbursement ServiceCreate DisbursementGet Disbursement by IDGet Disbursement by External IDGet Available BanksContributingTestsRunning the TestCreating Custom HTTP ClientAPI DocumentationPlease checkXendit API Reference.RequirementsPython 3.7 or laterInstallationTo use the package, runpip install xendit-pythonUsageAPI KeyTo add API Key, you have 2 option: Use global variable or use Xendit instanceGlobal Variableimportxenditxendit.api_key=\"test-key123\"# Then just run each class as staticfromxenditimportBalanceBalance.get()Use Xendit Instanceimportxenditx=xendit.Xendit(api_key=\"test-key123\")# Then access each class from x attributeBalance=x.BalanceBalance.get()HeadersYou can add headers by using the following keyword parametersX-IDEMPOTENCY-KEY:x_idempotency_keyVirtualAccount.create(x_idempotency_key=\"your-idemp-key\")for-user-id:for_user_idBalance.get(for_user_id='subaccount-user-id')X-API-VERSION:x_api_versionBalance.get(x_api_version='2020-01-01')Object CreationIf an API need an object as its parameter, you can use either dictionary for that class or a helper method e.g:items=[]item={id:\"123123\",name:\"Phone Case\",price:100000,quantity:1}items.append(item)EWallet.create_linkaja_payment(external_id=\"linkaja-ewallet-test-1593663498\",phone=\"089911111111\",items=items,amount=300000,callback_url=\"https://my-shop.com/callbacks\",redirect_url=\"https://xendit.co/\",)is equivalent withitems=[]item=xendit.EWallet.helper_create_linkaja_item(id=\"123123\",name=\"Phone Case\",price=100000,quantity=1)items.append(item)EWallet.create_linkaja_payment(external_id=\"linkaja-ewallet-test-1593663498\",phone=\"089911111111\",items=items,amount=300000,callback_url=\"https://my-shop.com/callbacks\",redirect_url=\"https://xendit.co/\",)Balance ServiceGet BalanceTheaccount_typeparameter is optional.fromxenditimportBalanceBalance.get()Balance.AccountType(account_type=BalanceAccountType.CASH,)Usage example:fromxenditimportBalance,BalanceAccountTypeBalancebalance=Balance.get(account_type=BalanceAccountType.CASH,)# To get the JSON viewprint(balance)# To get only the valueprint(balance.balance)Will return{'balance': 1000000000}\n1000000000Credit CardCreate AuthorizationfromxenditimportCreditCardcharge=CreditCard.create_authorization(token_id=\"5f0410898bcf7a001a00879d\",external_id=\"card_preAuth-1594106356\",amount=75000,card_cvn=\"123\",)print(charge)Will return{\n \"status\": \"AUTHORIZED\",\n \"authorized_amount\": 75000,\n \"capture_amount\": 0,\n \"currency\": \"IDR\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"merchant_id\": \"xendit_ctv_agg\",\n \"merchant_reference_code\": \"5f0421faa98815a4f4c92a0d\",\n \"external_id\": \"card_preAuth-1594106356\",\n \"eci\": \"07\",\n \"charge_type\": \"MULTIPLE_USE_TOKEN\",\n \"masked_card_number\": \"400000XXXXXX0002\",\n \"card_brand\": \"VISA\",\n \"card_type\": \"CREDIT\",\n \"descriptor\": \"XENDIT*XENDIT&#X27;S INTERN\",\n \"bank_reconciliation_id\": \"5941063625146828103011\",\n \"approval_code\": \"831000\",\n \"created\": \"2020-07-07T07:19:22.921Z\",\n \"id\": \"5f0421fa8cc1e8001973a1d6\"\n}Reverse AuthorizationfromxenditimportCreditCardreverse_authorization=CreditCard.reverse_authorizatiton(credit_card_charge_id=\"5f0421fa8cc1e8001973a1d6\",external_id=\"reverse-authorization-1594106387\",)print(reverse_authorization)Will return{\n \"status\": \"SUCCEEDED\",\n \"currency\": \"IDR\",\n \"credit_card_charge_id\": \"5f0421fa8cc1e8001973a1d6\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"card_preAuth-1594106356\",\n \"amount\": 75000,\n \"created\": \"2020-07-07T07:19:48.896Z\",\n \"id\": \"5f0422148cc1e8001973a1dc\"\n}Create ChargefromxenditimportCreditCardcharge=CreditCard.create_charge(token_id=\"5f0410898bcf7a001a00879d\",external_id=\"card_charge-1594106478\",amount=75000,card_cvn=\"123\",)print(charge)Will return{\n \"status\": \"CAPTURED\",\n \"authorized_amount\": 75000,\n \"capture_amount\": 75000,\n \"currency\": \"IDR\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"merchant_id\": \"xendit_ctv_agg\",\n \"merchant_reference_code\": \"5f0422746fc1d25bd222df2e\",\n \"external_id\": \"card_charge-1594106478\",\n \"eci\": \"07\",\n \"charge_type\": \"MULTIPLE_USE_TOKEN\",\n \"masked_card_number\": \"400000XXXXXX0002\",\n \"card_brand\": \"VISA\",\n \"card_type\": \"CREDIT\",\n \"descriptor\": \"XENDIT*XENDIT&#X27;S INTERN\",\n \"bank_reconciliation_id\": \"5941064846646923303008\",\n \"approval_code\": \"831000\",\n \"created\": \"2020-07-07T07:21:25.027Z\",\n \"id\": \"5f0422752bbbe50019a368b5\"\n}Capture ChargefromxenditimportCreditCardcharge=CreditCard.capture_charge(credit_card_charge_id=\"5f0422aa2bbbe50019a368c2\",amount=75000,)print(charge)Will return{\n \"status\": \"CAPTURED\",\n \"authorized_amount\": 75000,\n \"capture_amount\": 75000,\n \"currency\": \"IDR\",\n \"created\": \"2020-07-07T07:22:18.719Z\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"merchant_id\": \"xendit_ctv_agg\",\n \"merchant_reference_code\": \"5f0422aa6fc1d25bd222df32\",\n \"external_id\": \"card_preAuth-1594106532\",\n \"eci\": \"07\",\n \"charge_type\": \"MULTIPLE_USE_TOKEN\",\n \"masked_card_number\": \"400000XXXXXX0002\",\n \"card_brand\": \"VISA\",\n \"card_type\": \"CREDIT\",\n \"descriptor\": \"XENDIT*XENDIT&#X27;S INTERN\",\n \"bank_reconciliation_id\": \"5941065383296525603007\",\n \"approval_code\": \"831000\",\n \"mid_label\": \"CTV_TEST\",\n \"id\": \"5f0422aa2bbbe50019a368c2\"\n}Get ChargefromxenditimportCreditCardcharge=CreditCard.get_charge(credit_card_charge_id=\"5f0422aa2bbbe50019a368c2\",)print(charge)Will return{\n \"status\": \"CAPTURED\",\n \"authorized_amount\": 75000,\n \"capture_amount\": 75000,\n \"currency\": \"IDR\",\n \"created\": \"2020-07-07T07:22:18.719Z\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"merchant_id\": \"xendit_ctv_agg\",\n \"merchant_reference_code\": \"5f0422aa6fc1d25bd222df32\",\n \"external_id\": \"card_preAuth-1594106532\",\n \"eci\": \"07\",\n \"charge_type\": \"MULTIPLE_USE_TOKEN\",\n \"masked_card_number\": \"400000XXXXXX0002\",\n \"card_brand\": \"VISA\",\n \"card_type\": \"CREDIT\",\n \"descriptor\": \"XENDIT*XENDIT&#X27;S INTERN\",\n \"bank_reconciliation_id\": \"5941065383296525603007\",\n \"approval_code\": \"831000\",\n \"mid_label\": \"CTV_TEST\",\n \"metadata\": {},\n \"id\": \"5f0422aa2bbbe50019a368c2\"\n}Create RefundfromxenditimportCreditCardrefund=CreditCard.create_refund(credit_card_charge_id=\"5f0422aa2bbbe50019a368c2\",amount=10000,external_id=\"card_refund-1594106755\",)print(refund)Will return{\n \"status\": \"REQUESTED\",\n \"currency\": \"IDR\",\n \"credit_card_charge_id\": \"5f0422aa2bbbe50019a368c2\",\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"amount\": 10000,\n \"external_id\": \"card_refund-1594106755\",\n \"created\": \"2020-07-07T07:25:56.872Z\",\n \"updated\": \"2020-07-07T07:25:57.740Z\",\n \"id\": \"5f0423848bb8da600c57c44f\",\n \"fee_refund_amount\": 290\n}Create PromotionfromxenditimportCreditCardpromotion=CreditCard.create_promotion(reference_id=\"BRI_20_JAN-1594176600\",description=\"20% discount applied for all BRI cards\",discount_amount=10000,bin_list=['400000','460000'],start_time=\"2020-01-01T00:00:00.000Z\",end_time=\"2021-01-01T00:00:00.000Z\",)print(promotion)Will return{\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"reference_id\": \"BRI_20_JAN-1594176600\",\n \"description\": \"20% discount applied for all BRI cards\",\n \"start_time\": \"2020-01-01T00:00:00.000Z\",\n \"end_time\": \"2021-01-01T00:00:00.000Z\",\n \"type\": \"CARD_BIN\",\n \"discount_amount\": 10000,\n \"bin_list\": [\n \"400000\",\n \"460000\"\n ],\n \"currency\": \"IDR\",\n \"id\": \"c65a2ae7-ce75-4a15-bbec-55d076f46bd0\",\n \"created\": \"2020-07-08T02:50:02.296Z\",\n \"status\": \"ACTIVE\"\n}eWalletsCreate OVO PaymentfromxenditimportEWalletovo_payment=EWallet.create_ovo_payment(external_id=\"ovo-ewallet-testing-id-1593663430\",amount=\"80001\",phone=\"08123123123\",)print(ovo_payment)Will return{\n \"amount\": 80001,\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"ovo-ewallet-testing-id-1593663430\",\n \"ewallet_type\": \"OVO\",\n \"phone\": \"08123123123\",\n \"created\": \"2020-07-02T04:17:12.979Z\",\n \"status\": \"PENDING\"\n}Create DANA PaymentfromxenditimportEWalletdana_payment=EWallet.create_dana_payment(external_id=\"dana-ewallet-test-1593663447\",amount=\"1001\",callback_url=\"https://my-shop.com/callbacks\",redirect_url=\"https://my-shop.com/home\",)print(dana_payment)Will return{\n \"external_id\": \"dana-ewallet-test-1593663447\",\n \"amount\": 1001,\n \"checkout_url\": \"https://sandbox.m.dana.id/m/portal/cashier/checkout?bizNo=20200702111212800110166820100550620×tamp=1593663450389&mid=216620000000261692328&sign=XS3FMKj1oZHkTWu0EXk8PBwzjR1VtwSedqbKX%2BgMF6CyZvbA5xhAmMUR%2FlhD4QkBODbbTPcju1YDFnHmSdzmjbqPfGcQGtkCPgLwVOZo1ERPmoUhhGJIbQXkfZ1Z8eA1w1RSqDzdmDB%2B%2FlvHaTbYPiUlvjzs%2BfgkM33YFFEl0BG1kUFz0%2FKb9OoT1QKyoHxw6ge4SWPF3Po6BwNtjqUZe2n43s7y0CvSrcNiNLHT3k2XHSlIdguwCGjNHh2zClgtv9XbSCecnD96nuIuohYARX8Ai%2BaYo%2FEDO1VEch4XditfIXvyBhL0TocxhYxda7yKNNjkZj56Rl9ds8u7Wyv1eQ%3D%3D\",\n \"ewallet_type\": \"DANA\"\n}Create LinkAja PaymentfromxenditimportEWallet,LinkAjaItemitems=[]items.append(LinkAjaItem(id=\"123123\",name=\"Phone Case\",price=100000,quantity=1))linkaja_payment=EWallet.create_linkaja_payment(external_id=\"linkaja-ewallet-test-1593663498\",phone=\"089911111111\",items=items,amount=300000,callback_url=\"https://my-shop.com/callbacks\",redirect_url=\"https://xendit.co/\",)print(linkaja_payment)Will return{\n \"checkout_url\": \"https://ewallet-linkaja-dev.xendit.co/checkouts/c627cf1f-0470-420f-a0f4-3931ef384bf4\",\n \"transaction_date\": \"2020-07-02T04:18:21.729Z\",\n \"amount\": 300000,\n \"external_id\": \"linkaja-ewallet-test-1593663498\",\n \"ewallet_type\": \"LINKAJA\"\n}Get Payment StatusfromxenditimportEWalletovo_payment_status=EWallet.get_payment_status(ewallet_type=EWalletType.OVO,external_id=\"ovo-ewallet-testing-id-1234\",)print(ovo_payment_status)Will return{\n \"amount\": \"8888\",\n \"business_id\": \"5ed75086a883856178afc12e\",\n \"ewallet_type\": \"OVO\",\n \"external_id\": \"ovo-ewallet-testing-id-1234\",\n \"status\": \"COMPLETED\",\n \"transaction_date\": \"2020-06-30T01:32:28.267Z\"\n}Direct DebitCreate CustomerfromxenditimportDirectDebitcustomer=DirectDebit.create_customer(reference_id=\"merc-1594279037\",email=\"t@x.co\",given_names=\"Adyaksa\",)print(customer)Will return{\n \"id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"reference_id\": \"merc-1594279037\",\n \"description\": null,\n \"given_names\": \"Adyaksa\",\n \"middle_name\": null,\n \"surname\": null,\n \"mobile_number\": null,\n \"phone_number\": null,\n \"email\": \"t@x.co\",\n \"nationality\": null,\n \"addresses\": null,\n \"date_of_birth\": null,\n \"employment\": null,\n \"source_of_wealth\": null,\n \"metadata\": null\n}Get Customer by Reference IDfromxenditimportDirectDebitcustomer=DirectDebit.get_customer_by_ref_id(reference_id=\"merc-1594279037\",)print(customer)Will return[{\n \"id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"reference_id\": \"merc-1594279037\",\n \"description\": null,\n \"given_names\": \"Adyaksa\",\n \"middle_name\": null,\n \"surname\": null,\n \"mobile_number\": null,\n \"phone_number\": null,\n \"email\": \"t@x.co\",\n \"nationality\": null,\n \"addresses\": null,\n \"date_of_birth\": null,\n \"employment\": null,\n \"source_of_wealth\": null,\n \"metadata\": null\n}]Initialize Linked Account TokenizationfromxenditimportDirectDebitcard_linking=DirectDebit.helper_create_card_link(account_mobile_number=\"+62818555988\",card_last_four=\"8888\",card_expiry=\"06/24\",account_email=\"test.email@xendit.co\",)linked_account=DirectDebit.initialize_tokenization(customer_id=\"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",channel_code=\"DC_BRI\",properties=card_linking,)print(linked_account)Will return{\n \"id\": \"lat-f325b757-0aae-4c24-92c5-3661e299e154\",\n \"customer_id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"channel_code\": \"DC_BRI\",\n \"authorizer_url\": null,\n \"status\": \"PENDING\",\n \"metadata\": null\n}Validate OTP for Linked Account TokenfromxenditimportDirectDebitlinked_account=DirectDebit.validate_token_otp(linked_account_token_id=\"lat-f325b757-0aae-4c24-92c5-3661e299e154\",otp_code=\"333000\",)print(linked_account)Will return{\n \"id\": \"lat-f325b757-0aae-4c24-92c5-3661e299e154\",\n \"customer_id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"channel_code\": \"DC_BRI\",\n \"status\": \"SUCCESS\",\n \"metadata\": null\n}Retrieve Accessible Accounts by Linked Account TokenfromxenditimportDirectDebitaccessible_accounts=DirectDebit.get_accessible_account_by_token(linked_account_token_id=\"lat-f325b757-0aae-4c24-92c5-3661e299e154\",)print(accessible_accounts)Will return[{\n \"channel_code\": \"DC_BRI\",\n \"id\": \"la-08b089e8-7035-4f5f-bdd9-94edd9dc9480\",\n \"properties\": {\n \"card_expiry\": \"06/24\",\n \"card_last_four\": \"8888\",\n \"currency\": \"IDR\",\n \"description\": \"\"\n },\n \"type\": \"DEBIT_CARD\"\n}]Create Payment MethodfromxenditimportDirectDebitpayment_method=DirectDebit.create_payment_method(customer_id=\"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",type=DirectDebitPaymentMethodType.DEBIT_CARD,properties={'id':'la-fac7e744-ab40-4100-a447-cbbb16f29ded'},)print(payment_method)Will return{\n \"customer_id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"type\": \"DEBIT_CARD\",\n \"properties\": {\n \"id\": \"la-fac7e744-ab40-4100-a447-cbbb16f29ded\",\n \"currency\": \"IDR\",\n \"card_expiry\": \"06/24\",\n \"description\": \"\",\n \"channel_code\": \"DC_BRI\",\n \"card_last_four\": \"8888\"\n },\n \"status\": \"ACTIVE\",\n \"metadata\": {},\n \"id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"created\": \"2020-07-13T07:28:57.716Z\",\n \"updated\": \"2020-07-13T07:28:57.716Z\"\n}Get Payment Methods by Customer IDfromxenditimportDirectDebitpayment_methods=DirectDebit.get_payment_methods_by_customer_id(customer_id=\"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",)print(payment_methods)Will return[{\n \"id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"customer_id\": \"ed20b5db-df04-41fc-8018-8ea4ac4d1030\",\n \"status\": \"ACTIVE\",\n \"type\": \"DEBIT_CARD\",\n \"properties\": {\n \"id\": \"la-fac7e744-ab40-4100-a447-cbbb16f29ded\",\n \"currency\": \"IDR\",\n \"card_expiry\": \"06/24\",\n \"description\": \"\",\n \"channel_code\": \"DC_BRI\",\n \"card_last_four\": \"8888\"\n },\n \"metadata\": {},\n \"created\": \"2020-07-13T07:28:57.716Z\",\n \"updated\": \"2020-07-13T07:28:57.716Z\"\n}]Create Direct Debit PaymentfromxenditimportDirectDebitpayment=DirectDebit.create_payment(reference_id=\"direct-debit-ref-1594718940\",payment_method_id=\"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",currency=\"IDR\",amount=\"60000\",callback_url=\"http://webhook.site/\",enable_otp=True,idempotency_key=\"idemp_key-1594718940\",)print(payment)Will return{\n \"failure_code\": null,\n \"otp_mobile_number\": null,\n \"otp_expiration_timestamp\": null,\n \"id\": \"ddpy-eaa093b6-b669-401a-ba2e-61ac644b2aff\",\n \"reference_id\": \"direct-debit-ref-1594718940\",\n \"payment_method_id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"channel_code\": \"DC_BRI\",\n \"currency\": \"IDR\",\n \"amount\": 60000,\n \"is_otp_required\": true,\n \"basket\": null,\n \"description\": \"\",\n \"status\": \"PENDING\",\n \"metadata\": null,\n \"created\": \"2020-07-14T09:29:02.614443Z\",\n \"updated\": \"2020-07-14T09:29:02.614443Z\"\n}Create Recurring Payment with Direct DebitYou can useCreate Recurring Paymentto use this feature.Validate OTP for Direct Debit PaymentfromxenditimportDirectDebitpayment=DirectDebit.validate_payment_otp(direct_debit_id=\"ddpy-eaa093b6-b669-401a-ba2e-61ac644b2aff\",otp_code=\"222000\",)print(payment)Will return{\n \"failure_code\": null,\n \"otp_mobile_number\": null,\n \"otp_expiration_timestamp\": null,\n \"id\": \"ddpy-eaa093b6-b669-401a-ba2e-61ac644b2aff\",\n \"reference_id\": \"direct-debit-ref-1594718940\",\n \"payment_method_id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"channel_code\": \"DC_BRI\",\n \"currency\": \"IDR\",\n \"amount\": 60000,\n \"is_otp_required\": true,\n \"basket\": null,\n \"description\": \"\",\n \"status\": \"PENDING\",\n \"metadata\": null,\n \"created\": \"2020-07-14T09:29:02.614443Z\",\n \"updated\": \"2020-07-14T09:29:02.614443Z\"\n}Get Direct Debit Payment Status by IDfromxenditimportDirectDebitpayment=DirectDebit.get_payment_status(direct_debit_id=\"ddpy-38ef50a8-00f0-4019-8b28-9bca81f2cbf1\",)print(payment)Will return{\n \"failure_code\": null,\n \"otp_mobile_number\": null,\n \"otp_expiration_timestamp\": null,\n \"id\": \"ddpy-38ef50a8-00f0-4019-8b28-9bca81f2cbf1\",\n \"reference_id\": \"direct-debit-ref-1594717458\",\n \"payment_method_id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"channel_code\": \"DC_BRI\",\n \"currency\": \"IDR\",\n \"amount\": 60000,\n \"is_otp_required\": false,\n \"basket\": null,\n \"description\": \"\",\n \"status\": \"PENDING\",\n \"metadata\": null,\n \"created\": \"2020-07-14T09:04:20.031451Z\",\n \"updated\": \"2020-07-14T09:04:20.031451Z\"\n}Get Direct Debit Payment Status by Reference IDfromxenditimportDirectDebitpayments=DirectDebit.get_payment_status_by_ref_id(reference_id=\"direct-debit-ref-1594717458\",)print(payments)Will return[{\n \"amount\": 60000,\n \"basket\": null,\n \"channel_code\": \"DC_BRI\",\n \"created\": \"2020-07-14T09:04:20.031451Z\",\n \"currency\": \"IDR\",\n \"description\": \"\",\n \"failure_code\": null,\n \"id\": \"ddpy-38ef50a8-00f0-4019-8b28-9bca81f2cbf1\",\n \"is_otp_required\": false,\n \"metadata\": null,\n \"otp_expiration_timestamp\": null,\n \"otp_mobile_number\": null,\n \"payment_method_id\": \"pm-b6116aea-8c23-42d0-a1e6-33227b52fccd\",\n \"reference_id\": \"direct-debit-ref-1594717458\",\n \"status\": \"PENDING\",\n \"updated\": \"2020-07-14T09:04:20.031451Z\"\n}]Virtual Account ServiceCreate Virtual AccountfromxenditimportVirtualAccountvirtual_account=VirtualAccount.create(external_id=\"demo_1475459775872\",bank_code=\"BNI\",name=\"Rika Sutanto\",)print(virtual_account)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"bank_code\": \"BNI\",\n \"merchant_code\": \"8808\",\n \"name\": \"Rika Sutanto\",\n \"account_number\": \"8808999956275653\",\n \"is_single_use\": false,\n \"status\": \"PENDING\",\n \"expiration_date\": \"2051-06-22T17:00:00.000Z\",\n \"is_closed\": false,\n \"id\": \"5ef174c48dd9ea2fc97d6a1e\"\n}Get Virtual Account BanksfromxenditimportVirtualAccountvirtual_account_banks=VirtualAccount.get_banks()print(virtual_account_banks)Will return[{\n \"name\": \"Bank Mandiri\",\n \"code\": \"MANDIRI\"\n}, {\n \"name\": \"Bank Negara Indonesia\",\n \"code\": \"BNI\"\n}, {\n \"name\": \"Bank Rakyat Indonesia\",\n \"code\": \"BRI\"\n}, {\n \"name\": \"Bank Permata\",\n \"code\": \"PERMATA\"\n}, {\n \"name\": \"Bank Central Asia\",\n \"code\": \"BCA\"\n}]Get Virtual AccountfromxenditimportVirtualAccountvirtual_account=VirtualAccount.get(id=\"5eec3a3e8dd9ea2fc97d6728\",)print(virtual_account)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"bank_code\": \"BNI\",\n \"merchant_code\": \"8808\",\n \"name\": \"Rika Sutanto\",\n \"account_number\": \"8808999917965673\",\n \"is_single_use\": true,\n \"status\": \"ACTIVE\",\n \"expiration_date\": \"2051-06-18T17:00:00.000Z\",\n \"is_closed\": false,\n \"id\": \"5eec3a3e8dd9ea2fc97d6728\"\n}Update Virtual AccountfromxenditimportVirtualAccountvirtual_account=VirtualAccount.update(id=\"5eec3a3e8dd9ea2fc97d6728\",is_single_use=True,)print(virtual_account)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"bank_code\": \"BNI\",\n \"merchant_code\": \"8808\",\n \"name\": \"Rika Sutanto\",\n \"account_number\": \"8808999917965673\",\n \"is_single_use\": true,\n \"status\": \"PENDING\",\n \"expiration_date\": \"2051-06-18T17:00:00.000Z\",\n \"is_closed\": false,\n \"id\": \"5eec3a3e8dd9ea2fc97d6728\"\n}Get Virtual Account PaymentfromxenditimportVirtualAccountvirtual_account_payment=VirtualAccount.get(payment_id=\"5ef18efca7d10d1b4d61fb52\",)print(virtual_account)Will return{\n \"id\": \"5ef18efcf9ce3b5f8e188ee4\",\n \"payment_id\": \"5ef18efca7d10d1b4d61fb52\",\n \"callback_virtual_account_id\": \"5ef18ece8dd9ea2fc97d6a84\",\n \"external_id\": \"VA_fixed-1592889038\",\n \"merchant_code\": \"88608\",\n \"account_number\": \"9999317837\",\n \"bank_code\": \"MANDIRI\",\n \"amount\": 50000,\n \"transaction_timestamp\": \"2020-06-23T05:11:24.000Z\"\n}Retail Outlet ServiceCreate Fixed Payment CodefromxenditimportRetailOutletretail_outlet=RetailOutlet.create_fixed_payment_code(external_id=\"demo_fixed_payment_code_123\",retail_outlet_name=\"ALFAMART\",name=\"Rika Sutanto\",expected_amount=10000,)print(retail_outlet)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_fixed_payment_code_123\",\n \"retail_outlet_name\": \"ALFAMART\",\n \"prefix\": \"TEST\",\n \"name\": \"Rika Sutanto\",\n \"payment_code\": \"TEST56147\",\n \"expected_amount\": 10000,\n \"is_single_use\": False,\n \"expiration_date\": \"2051-06-23T17:00:00.000Z\",\n \"id\": \"5ef2f0f8e7f5c14077275493\",\n}Update Fixed Payment CodefromxenditimportRetailOutletretail_outlet=RetailOutlet.update_fixed_payment_code(fixed_payment_code_id=\"5ef2f0f8e7f5c14077275493\",name=\"Joe Contini\",)print(retail_outlet)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_fixed_payment_code_123\",\n \"retail_outlet_name\": \"ALFAMART\",\n \"prefix\": \"TEST\",\n \"name\": \"Joe Contini\",\n \"payment_code\": \"TEST56147\",\n \"expected_amount\": 10000,\n \"is_single_use\": False,\n \"expiration_date\": \"2051-06-23T17:00:00.000Z\",\n \"id\": \"5ef2f0f8e7f5c14077275493\",\n}Get Fixed Payment CodefromxenditimportRetailOutletretail_outlet=RetailOutlet.get_fixed_payment_code(fixed_payment_code_id=\"5ef2f0f8e7f5c14077275493\",)print(retail_outlet)Will return{\n \"owner_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_fixed_payment_code_123\",\n \"retail_outlet_name\": \"ALFAMART\",\n \"prefix\": \"TEST\",\n \"name\": \"Rika Sutanto\",\n \"payment_code\": \"TEST56147\",\n \"expected_amount\": 10000,\n \"is_single_use\": False,\n \"expiration_date\": \"2051-06-23T17:00:00.000Z\",\n \"id\": \"5ef2f0f8e7f5c14077275493\",\n}Invoice ServiceCreate InvoicefromxenditimportInvoiceinvoice=Invoice.create(external_id=\"invoice-1593684000\",amount=20000,payer_email=\"customer@domain.com\",description=\"Invoice Demo #123\",)print(invoice)Will return{\n \"id\": \"5efdb0210425db620ec35fb3\",\n \"external_id\": \"invoice-1593684000\",\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"status\": \"PENDING\",\n \"merchant_name\": \"Xendit&#x27;s Intern\",\n \"merchant_profile_picture_url\": \"https://xnd-companies.s3.amazonaws.com/prod/1591169469152_279.png\",\n \"amount\": 20000,\n \"payer_email\": \"customer@domain.com\",\n \"description\": \"Invoice Demo #123\",\n \"expiry_date\": \"2020-07-03T10:00:01.148Z\",\n \"invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5efdb0210425db620ec35fb3\",\n \"available_banks\": [\n {\n \"bank_code\": \"MANDIRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"8860846854335\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"2621554807492\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BNI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"880854597383\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"PERMATA\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"821456659745\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BCA\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"1076619844859\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n }\n ],\n \"available_retail_outlets\": [\n {\n \"retail_outlet_name\": \"ALFAMART\",\n \"payment_code\": \"TEST34956\",\n \"transfer_amount\": 20000\n }\n ],\n \"available_ewallets\": [],\n \"should_exclude_credit_card\": false,\n \"should_send_email\": false,\n \"created\": \"2020-07-02T10:00:01.285Z\",\n \"updated\": \"2020-07-02T10:00:01.285Z\",\n \"currency\": \"IDR\"\n}Get InvoicefromxenditimportInvoiceinvoice=Invoice.get(invoice_id=\"5efda8a20425db620ec35f43\",)print(invoice)Will return{\n \"id\": \"5efda8a20425db620ec35f43\",\n \"external_id\": \"invoice-1593682080\",\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"status\": \"EXPIRED\",\n \"merchant_name\": \"Xendit&#x27;s Intern\",\n \"merchant_profile_picture_url\": \"https://xnd-companies.s3.amazonaws.com/prod/1591169469152_279.png\",\n \"amount\": 20000,\n \"payer_email\": \"customer@domain.com\",\n \"description\": \"Invoice Demo #123\",\n \"expiry_date\": \"2020-07-02T09:55:47.794Z\",\n \"invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5efda8a20425db620ec35f43\",\n \"available_banks\": [\n {\n \"bank_code\": \"MANDIRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"8860846853111\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"2621554806292\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n }\n ],\n \"available_retail_outlets\": [\n {\n \"retail_outlet_name\": \"ALFAMART\",\n \"payment_code\": \"TEST34950\",\n \"transfer_amount\": 20000\n }\n ],\n \"available_ewallets\": [],\n \"should_exclude_credit_card\": false,\n \"should_send_email\": false,\n \"created\": \"2020-07-02T09:28:02.191Z\",\n \"updated\": \"2020-07-02T09:55:47.794Z\",\n \"currency\": \"IDR\"\n}Expire InvoicefromxenditimportInvoiceinvoice=Invoice.expire(invoice_id=\"5efda8a20425db620ec35f43\",)print(invoice)Will return{\n \"id\": \"5efda8a20425db620ec35f43\",\n \"external_id\": \"invoice-1593682080\",\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"status\": \"EXPIRED\",\n \"merchant_name\": \"Xendit&#x27;s Intern\",\n \"merchant_profile_picture_url\": \"https://xnd-companies.s3.amazonaws.com/prod/1591169469152_279.png\",\n \"amount\": 20000,\n \"payer_email\": \"customer@domain.com\",\n \"description\": \"Invoice Demo #123\",\n \"expiry_date\": \"2020-07-02T09:55:47.794Z\",\n \"invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5efda8a20425db620ec35f43\",\n \"available_banks\": [\n {\n \"bank_code\": \"MANDIRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"8860846853111\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"2621554806292\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n }\n \"available_retail_outlets\": [\n {\n \"retail_outlet_name\": \"ALFAMART\",\n \"payment_code\": \"TEST34950\",\n \"transfer_amount\": 20000\n }\n ],\n \"available_ewallets\": [],\n \"should_exclude_credit_card\": false,\n \"should_send_email\": false,\n \"created\": \"2020-07-02T09:28:02.191Z\",\n \"updated\": \"2020-07-02T09:55:47.794Z\",\n \"currency\": \"IDR\"\n}List All InvoicefromxenditimportInvoiceinvoices=Invoice.list_all(limit=3,)print(invoices)Will return[\n ...\n {\n \"id\": \"5efda8a20425db620ec35f43\",\n \"external_id\": \"invoice-1593682080\",\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"status\": \"EXPIRED\",\n \"merchant_name\": \"Xendit&#x27;s Intern\",\n \"merchant_profile_picture_url\": \"https://xnd-companies.s3.amazonaws.com/prod/1591169469152_279.png\",\n \"amount\": 20000,\n \"payer_email\": \"customer@domain.com\",\n \"description\": \"Invoice Demo #123\",\n \"expiry_date\": \"2020-07-02T09:55:47.794Z\",\n \"invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5efda8a20425db620ec35f43\",\n \"available_banks\": [\n {\n \"bank_code\": \"MANDIRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"8860846853111\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n },\n {\n \"bank_code\": \"BRI\",\n \"collection_type\": \"POOL\",\n \"bank_account_number\": \"2621554806292\",\n \"transfer_amount\": 20000,\n \"bank_branch\": \"Virtual Account\",\n \"account_holder_name\": \"XENDIT&#X27;S INTERN\",\n \"identity_amount\": 0\n }\n \"available_retail_outlets\": [\n {\n \"retail_outlet_name\": \"ALFAMART\",\n \"payment_code\": \"TEST34950\",\n \"transfer_amount\": 20000\n }\n ],\n \"available_ewallets\": [],\n \"should_exclude_credit_card\": false,\n \"should_send_email\": false,\n \"created\": \"2020-07-02T09:28:02.191Z\",\n \"updated\": \"2020-07-02T09:55:47.794Z\",\n \"currency\": \"IDR\"\n }\n ...\n]Recurring PaymentCreate Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.create_recurring_payment(external_id=\"recurring_12345\",payer_email=\"test@x.co\",description=\"Test Curring Payment\",amount=100000,interval=\"MONTH\",interval_count=1,)Will return{\n \"status\": \"ACTIVE\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 1,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:22:55.994Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\",\n \"last_created_invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5f05825ff9f52d3ed204c688\"\n}Get Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.get_recurring_payment(id=\"5f05825ff9f52d3ed204c687\",)Will return{\n \"status\": \"ACTIVE\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 1,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:22:55.994Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\",\n \"last_created_invoice_url\": \"https://invoice-staging.xendit.co/web/invoices/5f05825ff9f52d3ed204c688\"\n}Edit Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.edit_recurring_payment(id=\"5f05825ff9f52d3ed204c687\",interval_count=2,)Will return{\n \"status\": \"ACTIVE\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 2,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:24:58.295Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\"\n}Stop Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.stop_recurring_payment(id=\"5f05825ff9f52d3ed204c687\",)Will return{\n \"status\": \"STOPPED\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 2,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:26:32.464Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\"\n}Pause Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.pause_recurring_payment(id=\"5f05825ff9f52d3ed204c687\",)Will return{\n \"status\": \"PAUSED\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 2,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:25:44.580Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\"\n}Resume Recurring PaymentfromxenditimportRecurringPaymentrecurring_payment=RecurringPayment.resume_recurring_payment(id=\"5f05825ff9f52d3ed204c687\",)Will return{\n \"status\": \"ACTIVE\",\n \"should_send_email\": false,\n \"missed_payment_action\": \"IGNORE\",\n \"recurrence_progress\": 1,\n \"recharge\": true,\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"recurring_12345\",\n \"payer_email\": \"test@x.co\",\n \"description\": \"Test Curring Payment\",\n \"amount\": 100000,\n \"interval\": \"MONTH\",\n \"interval_count\": 2,\n \"start_date\": \"2020-07-08T08:22:55.815Z\",\n \"currency\": \"IDR\",\n \"created\": \"2020-07-08T08:22:55.817Z\",\n \"updated\": \"2020-07-08T08:26:03.082Z\",\n \"id\": \"5f05825ff9f52d3ed204c687\"\n}Disbursement ServiceCreate DisbursementfromxenditimportDisbursementdisbursement=Disbursement.create(external_id=\"demo_1475459775872\",bank_code=\"BCA\",account_holder_name=\"Bob Jones\",account_number=\"1231242311\",description=\"Reimbursement for shoes\",amount=17000,)print(disbursement)Will return{\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"amount\": 17000,\n \"bank_code\": \"BCA\",\n \"account_holder_name\": \"Bob Jones\",\n \"disbursement_description\": \"Reimbursement for shoes\",\n \"status\": \"PENDING\",\n \"id\": \"5ef1c4f40c2e150017ce3b96\",\n}Get Disbursement by IDfromxenditimportDisbursementdisbursement=Disbursement.get(id=\"5ef1befeecb16100179e1d05\",)print(disbursement)Will return{\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"amount\": 17000,\n \"bank_code\": \"BCA\",\n \"account_holder_name\": \"Bob Jones\",\n \"disbursement_description\": \"Disbursement from Postman\",\n \"status\": \"PENDING\",\n \"id\": \"5ef1befeecb16100179e1d05\"\n}Get Disbursement by External IDfromxenditimportDisbursementdisbursement_list=Disbursement.get_by_ext_id(external_id=\"demo_1475459775872\",)print(disbursement_list)Will return[\n {\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"amount\": 17000,\n \"bank_code\": \"BCA\",\n \"account_holder_name\": \"Bob Jones\",\n \"disbursement_description\": \"Reimbursement for shoes\",\n \"status\": \"PENDING\",\n \"id\": \"5ef1c4f40c2e150017ce3b96\",\n },\n {\n \"user_id\": \"5ed75086a883856178afc12e\",\n \"external_id\": \"demo_1475459775872\",\n \"amount\": 17000,\n \"bank_code\": \"BCA\",\n \"account_holder_name\": \"Bob Jones\",\n \"disbursement_description\": \"Disbursement from Postman\",\n \"status\": \"PENDING\",\n \"id\": \"5ef1befeecb16100179e1d05\",\n },\n ...\n]Get Available BanksfromxenditimportDisbursementdisbursement_banks=Disbursement.get_available_banks()print(disbursement_banks)Will return[\n ...\n {\n \"name\": \"Mandiri Taspen Pos (formerly Bank Sinar Harapan Bali)\",\n \"code\": \"MANDIRI_TASPEN\",\n \"can_disburse\": True,\n \"can_name_validate\": True,\n },\n {\n \"name\": \"Bank QNB Indonesia (formerly Bank QNB Kesawan)\",\n \"code\": \"QNB_INDONESIA\",\n \"can_disburse\": True,\n \"can_name_validate\": True,\n }\n]ContributingFor any requests, bugs, or comments, please open anissueorsubmit a pull request.To start developing on this repository, you need to have Poetry installed for package dependency. After that, you can runpoetry installto install the dependency. To enter the environment, runpoetry shellTestsRunning the TestMake sure the the code passes all tests.Run the test:python -m pytest tests/Run with coverage:python -m pytest tests/ --cov=xendit/Creating Custom HTTP ClientTo create your own HTTP Client, you can do it by implementing interface atxendit/network/http_client_interface.py. Our default HTTP Client are wrapper ofrequests, which can be found atxendit/network/_xendit_http_client.py. To attach it to your instance, add it to your xendit parameter.importxenditxendit_instance=xendit.Xendit(api_key='',http_client=YourHTTPClientClass)"} +{"package": "xenditclient", "pacakge-description": "Python Xendit Client APIXendit REST API Client for PythonDocumentationInstallInstall xenditclient with pip by the following command:pipinstallxenditclientUsageConfigure the XenditClient with the secret key that you can obtained on your Xendit Dashboard Account.fromxenditclientimportXenditClientclient=XenditClient(api_key='<your-secret-key>')Get Balanceres_dict=client.balance.get_balance('CASH')print(res_dict)# {# 'balance': 1000137690# }EWalletsCreate Paymentparams={'ewallet_type':'OVO','external_id':'21345','amount':10000,'phone':'081234567890'}res_dict=client.ewallet.create(params)print(res_dict)# {# \"business_id\": \"12345678\",# \"external_id\": \"21345\",# \"amount\": \"10000\",# \"phone\": \"081234567890\",# \"ewallet_type\": \"OVO\",# \"status\": \"PENDING\",# \"created\": \"2020-04-04T00:00:00.000Z\",# }Get Payment Statusres_dict=client.ewallet.get_payment_status(external_id='21345',payment_method='OVO')print(res_dict)# {# \"amount\": \"10000\",# \"business_id\": \"12345678\",# \"ewallet_type\": \"OVO\",# \"external_id\": \"21345\",# \"status\": \"COMPLETED\",# \"transaction_date\": \"2020-04-04T11:48:47.903Z\"# }QR Codes (QRIS)Get QRCode clientqrcode=client.qrcodes# orfromxenditclient.qrcodesimportQRCodesClientqrcode=QRCodesClient(client)Create QRCode for paymentdata=qrcode.create(\"DYNAMIC\",\"DS-INV-01\",\"https://dwisulfahnur.com/api/xendit/callback\",10200)print(data)# {# \"id\": \"qr_a706814a-d18b-4109-9b71-7a76f9855e123\",# \"external_id\": \"DS-INV-01\",# \"amount\": 10200,# \"qr_string\": \"00022312321226660014ID.LINKAJA.WWW0118912312300241148000215200423041141230303UME51450015ID.OR.GPNQR.WWW0215000111111111110303UME520454995802ID5920Placeholder merchant6007Jakarta6106123456623801152QiFZi5qT12307152QiFZi5qThdA4M753033605405102006304D9CM\",# \"callback_url\": \"https://dwisulfahnur.com/api/xendit/callback\",# \"type\": \"DYNAMIC\",# \"status\": \"ACTIVE\",# \"created\": \"2020-07-27T07:44:31.420Z\",# \"updated\": \"2020-07-27T07:44:31.420Z\"# }Get QRCode detail paymentdata=qrcode.get_payment_detail(\"DS-INV-01\")print(data)# {# \"id\": \"qr_a706814a-d18b-4109-9b71-7a76f9855e123\",# \"external_id\": \"DS-INV-01\",# \"amount\": 10200,# \"qr_string\": \"00022312321226660014ID.LINKAJA.WWW0118912312300241148000215200423041141230303UME51450015ID.OR.GPNQR.WWW0215000111111111110303UME520454995802ID5920Placeholder merchant6007Jakarta6106123456623801152QiFZi5qT12307152QiFZi5qThdA4M753033605405102006304D9CM\",# \"callback_url\": \"https://dwisulfahnur.com/api/xendit/callback\",# \"type\": \"DYNAMIC\",# \"status\": \"ACTIVE\",# \"created\": \"2020-07-27T07:44:31.420Z\",# \"updated\": \"2020-07-27T07:44:31.420Z\"# }Virtual AccountGet Virtual Account Clientva_client=client.virtual_account# orfromxenditclient.virtual_accountsimportVirtualAccountClientqrcode=VirtualAccountClient(client)Get Virtual Account Banksdata=va_client.get_va_banks()print(data)# [# {'name': 'Bank Mandiri', 'code': 'MANDIRI'},# {'name': 'Bank Negara Indonesia', 'code': 'BNI'},# {'name': 'Bank Rakyat Indonesia', 'code': 'BRI'},# {'name': 'Bank Permata', 'code': 'PERMATA'},# {'name': 'Bank Central Asia', 'code': 'BCA'}# ]Create Virtual Account Paymentfromxenditclientimportvirtual_accountsdata=va_client.create(external_id=\"DS-INV-01\",bank_code=virtual_accounts.BNI,name=\"Dwi Sulfahnur\",)\"\"\"You can add the following additional optionsfor the Virtual Account as arguments:- virtual_account_number: str // Optional- suggested_amount: int // Optional- is_closed: bool // Optional- expected_amount: int // Optional- expiration_date: UTC datetime // Optional- is_single_use: bool // Optional- description: str // Optional\"\"\"print(data)# {# \"is_closed\": true,# \"status\": \"PENDING\",# \"currency\": \"IDR\",# \"owner_id\": \"5efab44e31890e1415bb70e9\",# \"external_id\": \"ZICARE-01\",# \"bank_code\": \"MANDIRI\",# \"merchant_code\": \"88908\",# \"name\": \"Dwi Sulfahnur\",# \"account_number\": \"889089999000001\",# \"suggested_amount\": 15500,# \"expected_amount\": 15500,# \"is_single_use\": true,# \"expiration_date\": \"2051-07-27T17:00:00.000Z\",# \"id\": \"5f1fd5470af2e8475877ba21\"# }Get Virtual Account Payment Detaildata=va_client.get_payment_detail(\"5f1fd5470af2e8475877ba21\")print(data)# {# \"is_closed\": true,# \"status\": \"PENDING\",# \"currency\": \"IDR\",# \"owner_id\": \"5efab44e31890e1415bb70e9\",# \"external_id\": \"ZICARE-01\",# \"bank_code\": \"MANDIRI\",# \"merchant_code\": \"88908\",# \"name\": \"Dwi Sulfahnur\",# \"account_number\": \"889089999000001\",# \"suggested_amount\": 15500,# \"expected_amount\": 15500,# \"is_single_use\": true,# \"expiration_date\": \"2051-07-27T17:00:00.000Z\",# \"id\": \"5f1fd5470af2e8475877ba21\"# }Update Virtual Account Payment Detailfromdatetimeimportdatetimedata=va_client.update_payment_detail(payment_id=\"5f1fd5470af2e8475877ba21\",suggested_amount=20000,expected_amount=20000,expiration_date=datetime(2020,12,31,00,00,00).isoformat(),is_single_use=True,description=\"Subscription Payment\",)print(data)# {# \"is_closed\": true,# \"status\": \"PENDING\",# \"currency\": \"IDR\",# \"owner_id\": \"5efab44e31890e1415bb70e9\",# \"external_id\": \"ZICARE-01\",# \"bank_code\": \"MANDIRI\",# \"merchant_code\": \"88908\",# \"name\": \"Dwi Sulfahnur\",# \"account_number\": \"889089999000001\",# \"suggested_amount\": 20000,# \"expected_amount\": 20000,# \"is_single_use\": true,# \"expiration_date\": \"2020-12-31T17:00:00.000Z\",# \"id\": \"5f1fd5470af2e8475877ba21\",# \"description\": \"Subscription Payment\",# }LegalDisclaimer: This library is not affliated with Xendit. This is an independent and unofficial Library."} +{"package": "xendit-python", "pacakge-description": "Xendit Python SDKThe official Xendit Python SDK provides a simple and convenient way to call Xendit's REST API\nin applications written in Python.Package version: 4.2.0RequirementsPython >= 3.10Getting StartedInstallationInstall directly from Xendit's Github Repository:pipinstallgit+https://github.com/xendit/xendit-python.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/xendit/xendit-python.git)Then import the package:importxenditSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxenditAuthorizationThe SDK needs to be instantiated using your secret API key obtained from theXendit Dashboard.\nYou can sign up for a free Dashboard accounthere.importxenditfromxendit.apisimportBalanceApifrompprintimportpprintxendit.set_api_key('XENDIT_API_KEY')client=xendit.ApiClient()try:response=BalanceApi(client).get_balance('CASH')pprint(response)exceptxendit.XenditSdkExceptionase:print(\"Exception when calling BalanceApi->get_balance:%s\\n\"%e)DocumentationFind detailed API information and examples for each of our product's by clicking the links below,InvoicePaymentRequestPaymentMethodRefundBalanceTransactionCustomerPayoutAll URIs are relative tohttps://api.xendit.co. For more information about our API, please refer tohttps://developers.xendit.co/.Further ReadingXendit DocsXendit API Reference"} +{"package": "xend-python-sdk", "pacakge-description": "Xend-python SDKThe Xend Finance SDK arms python developers with the ability to build DeFi applications withXend Financewithout needing to understand the complexities of the underlying blockchain or layer2 infrastructure.Note: For easier navigation, please use the documentation hosted on theGithub Repository.Table of contentWant to ContributeInstallationUsageAvailable Strategies exposed by the SDKWant to contribute?Contributions are welcome! Kindly refer to thecontribution guidelines.InstallationTo install this sdk, run the command:pip install xend-python-sdkUsageimportxend_financefromxend_financeimportXendFinanceInstantiate the XendFinance class like so:xend=XendFinance(your_chain_id,private_key,{\"env\":\"testnet\"})You can use Xend Finance in as many scenario's you can come up with, but there are 2 examplesUse one general address for all your transactionsCreate a new address for each of your users and use for their transactionsNote:The env field is one oflocal,testnetandmainnet.the chain_id of the network. a chain id of 1 represents the ethereum mainnet, 56 represents the Binance Smart Chain(BSC) mainnet, 137 represents the polygon mainnet while 0 denotes a localnet.Protocol TypeThis is the structure of a protocol to be used by the SDK and will be helpful when using the SDK on your local machine with an instance of tools like ganache.{\"name\":\"\",\"code\":\"\",\"addresses\":{\"PROTOCOL_ADAPTER\":\"\",\"PROTOCOL_SERVICE\":\"\",\"GROUPS\":\"\",\"CYCLES\":\"\",\"ESUSU_SERVICE\":\"\",\"ESUSU_STORAGE\":\"\",\"ESUSU_ADAPTER\":\"\",\"COOPERATIVE\":\"\",\"PERSONAL\":\"\",\"CLIENT_RECORD\":\"\",\"XEND_TOKEN\":\"\",\"TOKEN\":\"\",\"PROTOCOL_CURRENCY\":\"\",}}Available Strategies exposed by the SDKRefer to the officialdocumentationfor more information about the exposed strategiesThe following services are available with this SDK1.GeneralCreate WalletRetrieve WalletWallet BalanceGet PPFS2.Personal SavingsFlexible DepositFixed DepositGet fixed deposit recordGet flexible deposit recordFixed WithdrawalFlexible Withdrawal3.EsusuCreate Esusu CycleGet Cycles CountGet Cycle IdGet Esusu InfoJoin Esusu GroupStart Esusu CycleWithdraw InterestWithdraw CapitalIs MemberAccrue Interest CapitalCreate Esusu GroupGet Esusu GroupEsusu ContributionsNo of ContributionsGet cycles in group4.Cooperative SavingsCreate Cooperative CylceJoin Cooperative CycleGet Cooperative InfoIs Cooperative MemberStart Cooperative CycleWithdraw From Ongoing CycleWithdraw From Completed CycleCreate Cooperative GroupGet Cooperative GroupCooperative ContributionsCooperative cycles in group5.GroupsCreate GroupGet GroupGet GroupsGet rewards6.XautoApproveDepositWithdrawGet Price per shareShare Balance7.XvaultApprove vaultDeposit vaultWithdraw vaultGet Price per share vaultShare Balance vault1. GeneralThis strategy provides utility methods such as creating a wallet, getting wallet balance and getting price per full share.Create WalletThis method allows a user to create a wallet on a specific node.create_wallet=xend.create_wallet()Retrieve WalletThis method allows a user retrieve the details of a wallet such as wallet address and private key.retrieve_wallet=xend.retrieve_wallet()Wallet BalanceThis method allows a user retrieve the balance details of a walletwallet_balance=xend.wallet_balance()Get PPFSThis method allows a user retrieve the price per full share of his/her walletget_ppfs=xend.get_ppfs()2. Personal SavingsThis strategy provides methods for users to interact with their savings from Xend finance.Flexible DepositThis method allows users to create a flexible deposit on their walletcreate_flexible_deposit=xend.personal.flexible_deposit(\"20\")Parameters supportedParametersData typeRequiredDescriptiondeposit_amountstringtrueThe amount to be deposited.Fixed DepositThis method allows users to create a fixed deposit on their wallet for a specific period of timecreate_fixed_deposit=xend.personal.fixed_deposit(\"40\",30000)Parameters supportedParametersData typeRequiredDescriptiondeposit_amountstringtrueThe amount to be deposited.lock_periodintegertrueThe lock period in seconds.Get fixed deposit recordThis method allows users to get a list of all fixed deposits on their walletfixed_deposit_record=xend.personal.get_fixed_deposit_record()Get flexible deposit recordThis method allows users to get a list of all flexible deposits on their walletflexible_deposit_record=xend.personal.get_flexible_deposit_record()Fixed WithdrawalThis method allows users to perform fixed withdrawals on their walletfixed_withdrawal=xend.personal.fixed_withdrawal(10)Parameters supportedParametersData typeRequiredDescriptionrecord_idstringtrueThe id of the savings to be withdrawn from.Flexible WithdrawalThis method allows users to perform flexible withdrawals on their walletflexible_withdrawal=xend.personal.flexible_withdrawal(\"30.0\")Parameters supportedParametersData typeRequiredDescriptionamountstring or floattrueThe amount a user wants to withdraw.3. EsusuThis strategy provides methods for users to interact with an esusu style of contributions/savings from Xend finance.Create Esusu CycleThis method allows users to create esusu cyclesargs={\"group_id\":1,\"deposit_amount\":\"300\",\"payout_interval_in_seconds\":3600,\"start_time_in_seconds\":1579014400,\"max_members\":10}create_esusu_cycle=xend.esusu.create_esusu(args)Parameters supportedParametersData typeRequiredDescriptiongroup_idintegertrueThe group a user wants to create the cycle ondeposit_amountstringtrueThe amount a user wants to deposit while creating the cyclepayout_interval_in_secondsintegertrueThe payout interval in seconds.start_time_in_secondsintegertrueThe start time in seconds.max_membersintegertrueThe maximum number of members in the cycle.Get Cycles CountThis method returns the number of esusu cycles a user has/is present inget_esusu_cycles_count=xend.esusu.get_cycles_count()Get Cycle IdThis method returns the cycle id of a cycle at the specified position in the list of cycles created by the userget_esusu_cycle_id=xend.esusu.get_cycle_id_from_cycles_created(6)Parameters supportedParametersData typeRequiredDescriptionpositionintegertrueThe position of the cycleGet Esusu InfoThis method returns the information about an esusu cycle/groupget_esusu_info=xend.esusu.get_esusu_info(5)Parameters supportedParametersData typeRequiredDescriptionesusu_idintegertrueThe id of the esusu group/cycleJoin Esusu GroupThis method allows users to join an esusu group or cyclejoin_esusu_cycle=xend.esusu.join(9)Parameters supportedParametersData typeRequiredDescriptionidintegertrueThe id of the esusu group/cycleStart Esusu CycleThis method allows users to start an esusu cyclestart_esusu_cycle=xend.esusu.start(3)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of the esusu cycleWithdraw InterestThis method allows users to withdraw their interest from an esusu group/cyclewithdraw_interest=xend.esusu.withdraw_interest(8)Parameters supportedParametersData typeRequiredDescriptionesusu_idintegertrueThe id of the esusu group/cycleWithdraw CapitalThis method allows users to withdraw their capital from an esusu group/cyclewithdraw_capital=xend.esusu.withdraw_capital(14)Parameters supportedParametersData typeRequiredDescriptionesusu_idintegertrueThe id of the esusu group/cycleIs MemberThis method checks if a particular user is in an esusu cycleis_member_of_esusu_cycle=xend.esusu.is_member_of_cycle(9)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of the esusu cycleAccrue Interest CapitalThis method returns the accrued interest and capital of a user from an esusu cycleget_interest_capital=xend.esusu.accrue_interest_capital(16)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of the esusu cycleCreate Esusu GroupThis methods allows users to create an esusu groupcreate_esusu_group=xend.esusu.create_group('test','TXT')Parameters supportedParametersData typeRequiredDescriptiongroup_namestringtrueThe name of the groupsymbolstringtrueThe group's symbolGet Esusu GroupThis method returns all the esusu groups a user is associated withget_esusu_group=xend.esusu.get_groups()Esusu ContributionsThis methods returns all the contributions a user has made in the esusu groups/cycles he is associated withesusu_contributions=xend.esusu.contributions()No Of ContributionsThis methods returns the contributions count of a user in the groups/cycles he is associated withno_of_contributions=xend.esusu.no_of_contributions()Get cycles in GroupThis method returns the esusu cycles present in a particular esusu groupesusu_cycles_in_group=xend.esusu.cycles_in_group(11)Parameters supportedParametersData typeRequiredDescriptiongroup_idintegertrueThe id of the esusu group4. Cooperative SavingsThis strategy provides methods for users to interact with cooperative savings and contributions from Xend finance.Create Cooperative CycleThis method allows users to create cooperative cyclesargs={\"group_id\":1,\"cycle_stake_amount\":\"0.1\",\"payout_interval_in_seconds\":3600,\"start_time_in_seconds\":1579014400,\"max_members\":10}create_cooperate=xend.cooperative.create(args)Parameters supportedParametersData typeRequiredDescriptiongroup_idintegertrueThe group the user wants to create the cycle oncycle_stake_amountstringtrueThe stake amount the user wants to deposit while creating the cyclepayout_interval_in_secondsintegertrueThe payout interval in seconds.start_time_in_secondsintegertrueThe start time in seconds.max_membersintegertrueThe maximum number of members in the cycle.Join Cooperative CycleThis method allows users to join a cooperative cyclejoin_cooperative=xend.cooperative.join(10,25)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cyclenumber_of_stakesintegertrueThe stake amount the user wants to deposit while joining the cycleGet Cooperative InfoThis method returns the information about a cooperatve cyclecooperative_cycle_info=xend.cooperative.info(5)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cycleIs Cooperative MemberThis method checks if a particular user is in a cooperative cycledoes_member_exist=xend.cooperative.cycle_member_exist(5)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cycleStart Cooperative CycleThis method allows users to start a cooperative cyclestart_cycle=xend.cooperative.start_cyle(5)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cycleWithdraw From Ongoing CycleThis method allows users to withdraw tokens from an ongoing cooperative cyclewithdraw_ongoing_cycle=xend.cooperative.withdraw_from_ongoing_cycle(7)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cycleWithdraw From Completed CycleThis method allows users to withdraw tokens from a completed cooperative cyclewithdraw_completed_cycle=xend.cooperative.withdraw_completed(10)Parameters supportedParametersData typeRequiredDescriptioncycle_idintegertrueThe id of to the cooperative cycleCreate Cooperative GroupThis method allows users to create a cooperative groupcreate_cooperative_group=xend.cooperative.create_group('test','TST')Parameters supportedParametersData typeRequiredDescriptiongroup_namestringtrueThe name of the groupsymbolstringtrueThe group's symbolGet Cooperative GroupThis method returns all the cooperative groups a user is associated withget_cooperative_groups=xend.cooperative.get_cooperative_groups()Cooperative ContributionsThis methods returns all the contributions a user has made in the cooperative groups/cycles he is associated withcooperative_cycles_contributions=xend.cooperative.contributions()Cooperative cycles in groupThis method returns the cooperative cycles present in a particular cooperative groupcycles_in_cooperative_group=xend.cooperative.cycles_in_group(1)Parameters supportedParametersData typeRequiredDescriptiongroup_idintegertrueThe id of the cooperative group5. GroupsThis strategy provides utility methods for groups related operations such as creating a group, getting a group/groups and getting group rewardsCreate GroupThis method allows a user to create a group.create_group=xend.group.create('mnt','MNT')Parameters supportedParametersData typeRequiredDescriptiongroup_namestringtrueThe name of the groupsymbolstringtrueThe group's symbolGet GroupThis method allows a user retrieve the details of a group.get_single_group=xend.group.get_single_group(3)Parameters supportedParametersData typeRequiredDescriptiongroup_idintegertrueThe id of the cooperative groupGet GroupsThis method returns all the groups a user is associated withget_groups=xend.group.get_groups()Get rewardsThis method allows a user redeem any xend rewards earnedget_xend_rewards=xend.group.get_xend_rewards()6. XautoThis strategy provides utility methods for auto yield related operations on the xAuto protocol.ApproveThis method approves the amount of tokens to be spent from a user's walletapprove_token=xend.xauto.approve(\"TNT\",300)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be approvedamountintegertrueThe amount of tokens to be approvedDepositThis method deposits an amount of tokens to a user's walletdeposit_token=xend.xauto.deposit(\"BSC\",150)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be depositedamountintegertrueThe amount of tokens to be depositedWithdrawThis method withdraws an amount of tokens from a user's walletwithdraw_token=xend.xauto.withdraw(\"DAI\",240)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be withdrawnamountintegertrueThe amount of tokens to be withdrawnGet Price per ShareThis method returns the price per share of a tokenget_ppfs=xend.xauto.ppfs(\"DAI\")Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token nameShare BalanceThis method returns the balance of a token in a user's walletget_share_balance=xend.xauto.share_balance(\"DAI\")Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token name7. XvaultThis strategy provides utility methods for auto yield related operations on the xVault protocolApprove vaultThis method approves the amount of tokens to be spent from a user's walletapprove_token=xend.xvault.approve(\"BSC\",250)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be approvedamountintegertrueThe amount of tokens to be approvedDeposit vaultThis method deposits an amount of tokens to a user's walletdeposit_token=xend.xvault.deposit(\"BSC\",150)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be depositedamountintegertrueThe amount of tokens to be depositedWithdraw vaultThis method withdraws an amount of tokens from a user's walletwithdraw_token=xend.xvault.withdraw(\"DAI\",240)Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token to be withdrawnamountintegertrueThe amount of tokens to be withdrawnGet Price per Share vaultThis method returns the price per share of a tokenget_ppfs=xend.xvault.ppfs(\"DAI\")Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token nameShare Balance vaultThis method returns the balance of a token in a user's walletget_share_balance=xend.xvault.share_balance(\"DAI\")Parameters supportedParametersData typeRequiredDescriptiontokenstringtrueThe token name"} +{"package": "xenget", "pacakge-description": "XenGetA library for Python to get information from a XenForo forum.UsageInstallation:pipinstallxengetDocumentationThis documentation is temporary, and will be moved to a better place soon.importxengetForumReturns a Forum class. Usage:forum=xenget.Forum(\"https://yourforum.com\")Forum.get_member(id)Returns a Member class. Usage:member=forum.get_member(12345)MemberMember.get_avatar()Returns an image. Usage:member=member.get_avatar()Member.get_banner()Returns an image. Usage:member=member.get_banner()Member.get_username()Returns a string. Usage:member=member.get_username()Member.get_joindate()Returns a string. Usage:member=member.get_joindate()"} +{"package": "xengine", "pacakge-description": "Mu (wip)"} +{"package": "xengsort", "pacakge-description": "xengsort: Fast lightweight accurate xenograft sortingThis tool, xengsort, uses 3-way bucketed Cuckoo hashing to efficiently solve the xenograft sorting problem.For a description of the method an evaluation on several datasets, please see ourarticle in \"Algorithms for Molecular Biology\", or the initialWABI 2020 publication.\n(There was also apreprint on bioRxiv.)\nBibTeX entrys for citation can be found at the end of this README file.In case of problems,please read the tutorial and/or usage guide in this file carefully,check the troubleshooting section below if your problem is solved there,and file an issue in the issue tracker if this does not help or you have discovered an error in the documentation.See CHANGELOG.md for recent changes.\nThank you!Tutorial: Classification of human-captured mouse exomesWe here provide an example showing how to run xengsort on a human-captured mouse exome (part of one of the datasets described in the paper).\nThis tutorial uses the workflow management systemSnakemaketo run the example.\nThis is, however, not necessary to usexengsort.\nPlease refer to the Usage Guide below to learn how to runxengsorton your own data manually.Our softwarexengsortis provided as a Python package.\nFor efficiency, it uses just-in-time compilation provided by thenumbapackage.\nWe here use the package managercondato manage Python packages and to use a separate environment forxengsort.Install the conda package manager (miniconda)Go tohttps://docs.conda.io/en/latest/miniconda.htmland download the Miniconda installer:\nChoose Python 3.10 (or higher), your operating system, and preferably the 64 bit version.\nFollow the instructions of the installer and append the conda executable to your PATH (even if the installer does not recommend it).\nYou can let the installer do it, or do it manually by editing your.bashrcor similar file under Linux or MacOS, or by editing the environment variables under Windows.\nTo verify that the installation works, open a new terminal and executeconda --version # ideally 22.9.xx or higher\npython --version # ideally 3.10.xx or higherInstallation via condaxengsortis available via bioconda. To create a new environment includingxengsort, runconda create --name xengsort -c bioconda xengsortIf you want to install xengsort into an existing environment, activate it withconda activate MYEVIRONMENTand executeconda install -c bioconda xengsortManual installation via gitlabObtain or update xengsortOur software can also be obtained by cloning this public git repository:git clone https://gitlab.com/genomeinformatics/xengsort.gitIf you need to update xengsort later, you can do so by just executinggit pullwithin the cloned directory tree.Create and activate a conda environmentTo run our software, acondaenvironment with the required libraries needs to be created.\nA list of needed libraries is provided in theenvironment.ymlfile in the cloned repository;\nit can be used to create a new environment:cd xengsort # the directory of the cloned repository\nconda env createwhich will create an environment namedxengsortwith the required dependencies,\nusing the providedenvironment.ymlfile in the same directory.A more explicit alternative is to runconda create --name xengsort -c conda-forge -c bioconda --file requirements.txtwhich will do the same thing using the packages mentioned inrequirements.txt.Note:While xengsort works on Windows/Mac without problems, some of the required packages may currently not exist for Windows/Mac.Setting up the environment may take some time, as conda searches and downloads packages.\nAfter all dependencies are resolved, you activate the environment and install the package from the repository into this environment.\nMake sure that you are in the root directory of the cloned repository (where thisREADME.mdfile or theCHANGELOG.mdfile is) and runconda activate xengsort # activate environment\npip install -e . # install xengsort package using pipRun the Snakemake example workflowYou can in principle removesnakemake-minimalandsra-toolkitfrom the list of packages.\nHowever, you will not be able to automatically run the provided example workflow or download sequence datasets from SRA.We provide an example Snakemake workflow (for publicly available mouse exomes), which downloads all needed reference FASTA files and exome FASTQ files, generates a hash table as an index and classifies the reads.To run this workflow,you will need space for the downloaded datasets and result files, so snakemake should be executed in a separate working directory with lots of space for the datset.you will additionally need thesnakemake-minimalpackage.\nMake sure you are in the working directory, that your conda environment calledxengsortis active, and then additionally install Snakemake:condainstall-cbiocondasnakemake-minimalensure that xengsort'sSnakefileis present in the working directory.\nIt can be symbolically linked, such as:cd/path/to/workdir\nln-s/path/to/xengsort/SnakefileSnakefileNow Snakemake can be run as follows:snakemake-n# dry-run: What will happen?snakemake-j16--use-conda# execute with 16 threadsThe-n(or--dry-run) option first performs a dry run and prints out what will be done.\nIn the real invocation, the-j 16option uses up to 16 CPU cores to execute 16 separate jobs in parallel or one job that uses 16 threads, or any combination.You can examine the (commented) Snakefile to see what happens in each step:Reference sequences (human and mouse genome and transcriptome) will be downloaded from Ensembl in FASTA format.The k-mer index (for k=25) will be built from the FASTA files (xengsort index).An example dataset (a human-captured mouse exome) will be downloaded from SRA using sra-toolkit and saved in FASTQ format (paired-end reads).The paired-end reads in the dataset will be classified according to species (xengsort classify)This will run for quite some time (especially downloads and index creation), best leave it overnight.\nThe results will appear in theresults/directory.To run your own human/mouse xenograft analysis, you can continue to use the same index.\nAll reference files, including the index in ZARR format (.zarr) are in theref/directory.\nYou can follow the structure of the Snakefile to create your own custom workflow.\nAdditional information on how to usexengsortis given in the usage guide below.Usage Guidexengsort is a multi-command tool with several subcommands (like git), in particularxengsort indexbuilds an index (a bucketed 3-way Cuckoo hash table)xengsort classifyclassifies a sequences sample (FASTQ files) using an existing indexIt is a good idea to runxengsort index --helpto see all available options.\nUsing--helpworks on any subcommand.How to build an indexTo build an index for xengsort, several parameters must be provided, which are described in the following.First, a file name and a path for the index must be chosen.\nThe index is stored in two files. We will usemyindexto store the index in the current folder.Second, two reference genomes (host and graft) must be provided (in FASTA files).\nWe assume that they are given ashost.fa.gzandgraft.fa.gz.\nThe files can be provided as an uncompressed file or compressed usinggzip,bzip2orxz.\nThe corresponding options are-Hor--hostand-Gor--graft.\nEach option can take several arguments as files.xengsort index --index myindex -H host.fa.gz -G graft.fa.gz -n 4_500_000_000 [OPTIONS]We must specify the size of the hash table:-nor--nobjects: number of k-mers that will be stored in the hash table. This depends on the used refernece genomes and must be estimated beforehand! As a precise estimate of the number of different k-mers can be difficult, you can err on the safe side and provide a generously large estimate, examine the final (low) load factor and then rebuild the index with a smaller-nparameter to aechieve the desired load. There are also some tools that quickly estimate the number of distinct k-mers in large files, such asntCardorKmerEstimate. As a guide: Human and mouse genome and transcriptome together comprise around 4.5 billion 25-mers, as shown in the examples above.This option must be specified; there is no default!We may further specify additional properties of the hash table:-por--pagesizeindicates how many elements can be stored in one bucket (or page). This is 4 by default.--fillbetween 0.0 and 1.0 describes the desired fill rate or load factor of the hash table.\nTogether with-n, the number of slots in the table is calculated asceil(n/fill). In our experiments we used 0.88. (The number of buckets is then the smallest odd integer that is at leastceil(ceil(n/fill)/p).)--alignedor--unaligned: indicates whether each bucket should consume a number of bits that is a power of 2. Using--alignedensures that each bucket stays within the same cache line, but may waste space (padding bits), yielding faster speed but possibliy (much!) larger space requirements. With--unaligned, no bits are used for padding and buckets may cross cache line boundaries. This is slightly slower, but may save a little or a lot of space (depending on the bucket size in bits). The default is--unaligned, because the speed decrease is small and the memory savings can be significant.--hashfunctionsdefines the parameters for the hash functions used to store the key-value pairs. If the parameter is unspecified, different random functions are chosen each time. The hash functions can be specified using a colon separated list:--hashfunctions linear945:linear9123641:linear349341847. It is recommended to have them chosen randomly unless you need strictly reproducible behavior, in which case the example given here is recommended.The final important parameter is about paralellization:-Tdefines how many threads are used to calculate weakk-mers.The following hash table options should not be modified from their default values and are for internal development only:-Por--parameterscan be used to combine all parameters stated above into one string (see the--helptext)How to classifyTo classify a FASTQ sample (one or several single-end or paired-end files), make sure you are in an environment where xengsort and its dependencies are installed.\nThen run thexengsort classifycommand with a previously built index, such asxengsort classify --index myindex --fastq single.fq.gz --prefix myresults --mode countfor single-end reads, orxengsort classify --index myindex --fastq paired.1.fq.gz --pairs paired.2.fq.gz --prefix myresults --mode countfor paired-end reads.Out tool offers three different classification modes. The algorithm can be specified using the--modeparameter.count: Classifies the read based on the number of $k$-mers that belong to host or graft.coverage: Classifies the read based on the proportions covered by $k$-mers of each class.quick: Classifies the read only based on the third and third last $k$-mer.The parameter--prefixor equivalently--outis required and defines the prefix for all output files; this can be a combination of path and file prefix, such as/path/to/sorted/samplename. Typically, there will be 5 output files for each of the first and the second read pair:{prefix}.host.1.fq.gz: host reads{prefix}.graft.1.fq.gz: graft reads{prefix}.both.1.fq.gz: reads that could originate from both{prefix}.neither.1.fq.gz: reads that originate from neither host nor graft{prefix}.ambiguous.1.fq.gz: (few) ambiguous reads that cannot be classified,and similarly with.2.fq.gz. For single-end reads, there is only.fq.gz(no numbers).The compression type can be specified using the--compressionparameter.\nCurrently we supportgz(default),bzip,xzandnone(uncompressed).Further parameters and options are:-Tdefines how many threads are used for classification (4 to 8 is recommended).--filter: With this flag, only the graft reads are output.--count: With this flag, only the number of reads in each category is counted, but the reads are not sorted.Please report aGitLab issuein case of problems.Happy sorting!TroubleshootingSnakemake throws errors when attempting to download the example dataset from SRA.This may happen for several reasons:The dataset is quite large, over 20 GB. Make sure you have sufficient space (also temporary space) and sufficient disk quota (on a shared system) to store all of the files.Another source of trouble may be that for some reason and older version ofsra-toolsgets called. We use thefasterq-dumptool to download the data, which did not exist in older verisons. To use a clean environment with a recent version ofsra-tools, you can run snakemake assnakemake -j 16 --use-conda, which will generate a separate environment only for the download (this takes additional time, but may resolve the problem).In earlier versions, the dataset was downloaded from a different location which is no longer available. Please check that you are using at least v1.1.0 (xengsort --version). If not, please do a fresh clone and follow the tutorial to set up a new environment (delete the old one first) and runpip install -e ., as explained above in the tutorial.Indexing stops after a few seconds with a failure.The most likely cause of this is that you have not specified the size of the hash table (-nparameter).\n(From version 1.0.1, the-nparameter is required, and the error cannot occur anymore. Please update to the latest version!)\nFor the human and mouse genomes this is approximately-n 4_500_000_000(4.5 billion).\nIt is unfortunately a limitation of the implementation that the hash table size has to be specified in advance.\nIf uncertain, use a generous overestimate (e.g., add the sizes of the two genomes) and look in the output for the line that starts withchoice nonzero.\nThis is the exact number of k-mers stored.\nYou can use this value to re-index everything in a second iteration.Thexengsort classifystep throws an error aboutNoneTypevs.str.This can happen if you do not specify the--outor--prefixparameter.\n(From version 1.0.2, this parameter is required, and the error cannot occur anymore. Please update to the latest version!)CitationIf you use xengsort, please cite the article in \"Algorithms for Molecular Biology\".\nThe BibTeX entry is provided here:@Article{pmid33810805,\n Author=\"Jens Zentgraf and Sven Rahmann\",\n Title=\"Fast lightweight accurate xenograft sorting\",\n Journal=\"Algorithms Mol Biol\",\n Year=\"2021\",\n Volume=\"16\",\n Number=\"1\",\n Pages=\"2\",\n Month=\"Apr\"\n}In addition, you may also cite the WABI 2020 proceedigs paper:@InProceedings{ZentgrafRahmann2020xengsort,\n author =\t{Jens Zentgraf and Sven Rahmann},\n title =\t{Fast Lightweight Accurate Xenograft Sorting},\n booktitle =\t{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},\n pages =\t{4:1--4:16},\n series =\t{Leibniz International Proceedings in Informatics (LIPIcs)},\n ISBN =\t{978-3-95977-161-0},\n ISSN =\t{1868-8969},\n year =\t{2020},\n volume =\t{172},\n editor =\t{Carl Kingsford and Nadia Pisanti},\n publisher =\t{Schloss Dagstuhl--Leibniz-Zentrum f{\\\"u}r Informatik},\n address =\t{Dagstuhl, Germany},\n URL =\t\t{https://drops.dagstuhl.de/opus/volltexte/2020/12793},\n URN =\t\t{urn:nbn:de:0030-drops-127933},\n doi =\t\t{10.4230/LIPIcs.WABI.2020.4},\n annote =\t{Keywords: xenograft sorting, alignment-free method, Cuckoo hashing, k-mer}\n}"} +{"package": "xengsort-cubic", "pacakge-description": "No description available on PyPI."} +{"package": "xenia", "pacakge-description": "UNKNOWN"} +{"package": "xenia-generic", "pacakge-description": "# xenia generic libs"} +{"package": "xeniorn-dna-mutation-quantifier", "pacakge-description": "DnaMutationQuantifierQuantification of .ab1 Sanger sequencing trace files.\nA-G substitutions."} +{"package": "xenny", "pacakge-description": "XennyXenny's toolUsageInstallpip3installxennyandPython3.9.9(main,Nov212021,03:22:47)[Clang12.0.0(clang-1200.0.32.29)]ondarwin\nType\"help\",\"copyright\",\"credits\"or\"license\"formoreinformation.\n>>>importxenny.xenny\n\nHiI'mXenny.\n\u6b22\u8fce\u4f7f\u7528\u672c\u5305\u3002\n\u4e5f\u8bf7\u4e0d\u8981\u4ec5\u4f9d\u8d56\u672c\u5305\u3002\nDonotgogentleintothatgoodnight\u3002\n\n>>>"} +{"package": "xeno", "pacakge-description": "xeno: The Python dependency injector from outer space.xenoat its core is a simple Python dependency injection framework. Use it when\nyou need to manage complex inter-object dependencies in a clean way. For the\nmerits of dependency injection and IOC, seehttps://en.wikipedia.org/wiki/Dependency_injection.xenoshould feel pretty familiar to users of Google Guice in Java, as it\nis somewhat similar, although it is less focused on type names and more\non named resources and parameter injection.xenoalso offersxeno.build, a build automation framework built atop the core\ndependency injection inspired byInvoke. It is\nintended to come with batteries-included tools for making C/C++ projects,\nexecuting shell scripts, batching, and more. It is built on the concept of\ncomposable \"recipes\", which are generic instructions for building different\ntypes of filesystem targets.InstallationInstallation is simple. With python3-pip, do the following:$ sudo pip install -e .Or, to install the latest version available on PyPI:$ sudo pip install xenoUsageAs a build automation frameworkTo usexeno.buildto build a simple C software project, first create a file\ncalledbuild.pyin your repo (it can be called anything, but this is\ncustomary). Follow this template example for guidance:#!/usr/bin/env python3\nfrom xeno.build import *\n\n# TODO: Add recipes, providers, and tasks here.\n\nbuild()Then, you can import thecompilerecipe fromxeno.recipes.c:from xeno.recipes.c import compile, ENVENVhere is the default environment variables thatcompilewill use by\ndefault. It defaults to usingclangto compile C projects, you can change\nthat here, and you can add additional compile-time flags. TheENVobject is\nof typexeno.shell.Environment, which allows for some complex shlex-based\njoining and recombining of flags, such that you can additively compose the\nenviornment with defaults and/or what may be specified outside the build script.\nYou can also provide your own environment variables via theenv=parameter tocompile.ENV['CC'] = 'gcc'\nENV += dict(\n LDFLAGS='-g'\n)Let's create a provider that lists all of our source files and another that\nlists our headers. This will be useful for defining our tasks and using thecompilerecipe.from pathlib import Path\n\n@provide\ndef source_files():\n return Path.cwd().glob(\"src/*.c\")\n\n@provide\ndef header_files():\n return Path.cwd().glob(\"include/*.h\")Next, let's define a single default task that builds our program.@task(default=True)\ndef executable(source_files, header_files):\n return compile(source_files, target=\"my_program\", headers=header_files)compilecan take iterables of source files and/or combinations of strings and\nlists in*args. In this case, we elected to specify a target name for the\nprogram. If this wasn't the case, the name of the resulting target would be\nbased on the name of the first source file. This is ideal if there is only one\nsource being provided or if the main source file is always provided first and is\nthe desired name of the executable, but in this case it would be whatever came\nfirst in the directory order which isn't deterministic or ideal.Specifying theheaders=parameter here links the recipe to our header files\nas static file dependencies. If these files change, the recipe is acknowledged\nto beoutdated, and will be rebuilt the next time the build script is run even\nif an executable target already exists.That's it! Let's put it all together, and then we'll have a build script for\nour program.#!/usr/bin/env python3\nfrom xeno.build import *\nfrom xeno.recipes.c import compile, ENV\nfrom pathlib import Path\n\nENV['CC'] = 'gcc'\nENV += dict(\n LDFLAGS='-g'\n)\n\n@provide\ndef source_files():\n return Path.cwd().glob(\"src/*.c\")\n\n@provide\ndef header_files():\n return Path.cwd().glob(\"include/*.h\")\n\nbuild()Mark this script as executable and run it as./build.py, or usepython build.py. Be sure to check out./build.py --helpfor a list of command line\noptions and running modes.xeno.buildis smart and can create addressable\ntargets from a variety of different nested recipe construction scenarios, so\nbuild more complex scripts and try out./build.py -Lto see them all!Watch this space for more in-depth documentation to come in the near future.As an IOC frameworkTo usexenoas a dependency injection framework, you need to create a\nxeno.Injector and provide it with modules. These modules are regular\nPython objects with methods marked with the@xeno.providerannotation. This annotation tells theInjectorthat this method\nprovides a named resource, the same name as the method marked with@provider. These methods should either take no parameters (other\nthanself), or take named parameters which refer to other resources\nby name, i.e. the providers can also be injected with other resources in\norder to build a dependency chain.Once you have anInjectorfull of resources, you can use it to\ninject instances, functions, or methods with resources.To create a new object instance by injecting resources into its\nconstructor, useInjector.create(clazz), whereclazzis the\nclass which you would like to instantiate. The constructor of this class\nis called, and all named parameters in the constructor are treated as\nresource references. Once the object is instantiated, any methods marked\nwith@injectare invoked with named resources provided.Resources can be injected into normal functions, bound methods, or\nexisting object instances viaInjector.inject(obj). If the parameter\nis an object instance, it is scanned for methods marked with@injectand these methods are invoked with named resources provided.ExampleIn this simple example, we inject an output stream into an object.import sys\nfrom xeno import *\n\nclass OutputStreamModule:\n @provide\n def output_stream(self):\n return sys.stdout\n\nclass VersionWriter:\n def __init__(self, output_stream):\n self.output_stream = output_stream\n\n def write_version(self):\n print('The python version is %s' % sys.version_info,\n file=self.output_stream)\n\ninjector = Injector(OutputStreamModule())\nwriter = injector.create(VersionWriter)\nwriter.write_version()Checkouttest.pyin the git repo for more usage examples.Change LogVersion 7.3.0: Oct 9 2023xeno.buildtargets can now receive arguments! All args after a lone '@' arg are packed into an\nimplicitargvresource that can be injected into targets automatically.Fixed brokenrun_asfunctionality inShellRecipe.Version 7.2.2: Oct 7 2023Add a**kwargspass-thru forxeno.shell.check()for passing args tosubprocess.check_output().Version 7.2.1: Sep 15 2023Allow recipe factories to return empty results as None (or no explicit return value).Version 7.2.0: Sep 15 2023Improvements to the busy spinner: it now loops through pending recipe sigils\nto let the user know what is blocking in the build.Improved xeno.recipes.checkout() now opensbuild.pyand checks its Python AST\nfor references to \"xeno\" before trying to run \"./build.py deps\" if \"build.py\"\nis present in the resulting repository.Version 7.1.0: Sep 09 2023Add aupdate()override toxeno.shell.Environmentwhich takes\nthe same arguments asselect()but updates the dictionary in-place\ninstead of making and returning a new one.Version 7.0.0: Sep 09 2023Lift various build recipes from different projects into a\n\"batteries-included\" set of build tools underxeno.recipes.**.New enriched focus on backwards compatibility between minor versons.Restructuring and refactoring,xeno.cookbookis deprecated.From now on, legacy features will be marked as deprecated and made to\ncontinue to work until the next major version, during which they\nwill be removed.Version 4.12.0: Aug 07 2022Changes to support Python 3.10, older versions are now deprecated.Version 4.10.0: Oct 28 2021Allow recipes to be specified with glob-style wildcards, as perfnmatch.Version 4.9.0: Jan 03 2021Deprecate@recipefactory decorator for@factory.Allow recipes to specify asetuprecipe, which is not part\nof the recipe inputs or outputs but is needed to fulfill the task.Version 4.8.0: Dec 29 2020All recipe resources are loaded before targets are determined.Recipe names are now valid targets for a build.Version 4.7.0: Dec 16 2020Fixed a bug where build would continue resolving with outdated results.Added@recipedecorator toxeno.buildto denote recipe functions.Version 4.4.0: Nov 2 2020Added experimentalxeno.buildmodule, a declarative build system driven by IOC.Addedxeno.coloroffering basic ANSI color and terminal control.Version 4.3.0: May 9 2020Allow methods to be decorated with@injector.provide, eliminating the need for modules\nin some simple usage scenarios.Version 4.2.0: May 8 2020SplitInjectorintoAsyncInjectorandSyncInjectorto allow injection to be performed\nin context of another event loop if async providers are not used.FixedAsyncInjectorto actually support asynchronous resolution of dependencies.Version 4.1.0: Feb 3 2020AddedInjector.get_ordered_dependenciesto get a breadth first list of\ndependencies in the order they are built.Version 4.0.0: May 12 2019BACKWARDS INCOMPATIBLE CHANGERemoved support for parameter annotation aliases. Use@aliason methods instead.\nThis was removed to allowxenocode to play nicely with PEP 484 type hinting.Version 3.1.0: August 29 2018Add ClassAttributes.for_object convenience methodVersion 3.0.0: May 4 2018BACKWARDS INCOMPATIBLE CHANGEProvide injection interceptors with an alias map for the given param map.This change breaks all existing injection interceptors until the new param is added.Version 2.8.0: May 3 2018Allow decorated/wrapped methods to be properly injected if their'params'method attribute\nis carried forward.Version 2.7.0: April 20 2018TheInjectornow adds a'resource-name'attribute to resource methods allowing\nthe inspection of a resource's full canonical name at runtime.Version 2.6.0: March 27 2018Bugfix release: Remove support for implicit asynchronous resolution of\ndependencies. Providers can still be async, in order to await some other\nset of coroutines, but can no longer themselves be run in sync. The\nbenefits do not outweigh the complexity of bugs and timing concerns\nintroduced by this approach.Version 2.5.0: March 2, 2018AddedInjector.provide_async(). Note that resource are always run within an\nevent loop and should not useinject(),provide(), orrequire()directly, instead they should useinject_async(),provide_async(), andrequire_async()to dynamically modify resources.Version 2.4.1: January 30, 2018AddedInjector.scan_resources()to allow users to scan for resource names with the given attributes.AddedAttributes.merge()to assist with passing attributes down to functions which are wrapped in a decorator.AddedMethodAttributes.wraps()static decorator to summarize a common use case of attribute merging.AddedMethodAttributes.add()as a simple static decorator to add attribute values to a method's attributes.Version 2.4.0: January 21, 2018Dropped support for deprecatedNamespace.enumerate()in favor ofNamespace.get_leaves().Version 2.3.0: January 21, 2018Added support for asyncio-based concurrency and async provider coroutines with per-injector event loops (injector.loop).Version 2.2.0: September 19, 2017Expose the Injector's Namespace object viaInjector.get_namespace(). This is useful for users who want to list the contents of namespaces.Version 2.1.0: August 23rd, 2017Allow multiple resource names to be provided toInjector.get_dependency_graph().Version 2.0.0: July 25th, 2017BACKWARDS INCOMPATIBLE CHANGEChange the default namespace separator and breakout symbol to '/'Code using the old namespace separator can be made to work by overriding the value of xeno.Namespace.SEP:import xeno\nxeno.Namespace.SEP = '::'Version 1.10: July 25th, 2017Allow names prefixed with::to escape their module's namespace, e.g.::top_level_itemVersion 1.9: May 23rd, 2017Add@const()module annotation for value-based resourcesAddInjector.get_dependency_tree()to fetch a tree of dependency names for a given resource name.Version 1.8: May 16th, 2017AddMissingResourceErrorandMissingDependencyErrorexception types.Version 1.7: May 16th, 2017Major update, adding support for namespaces, aliases, and inline resource parameter aliases. See the unit tests in test.py for examples.Added@namespace('Name')decorator for modules to specify that all resources defined in the module should be scoped within 'Name::'.Added@name('alt-name')to allow resources to be named something other than the name of the function that defines them.Added@alias('alt-name', 'name')to allow a resource to be renamed within either the scope of a single resource or a whole module.Added@using('NamespaceName')to allow the contents of the given namespace\nto be automatically aliases into either the scope of a single resource or\na whole module.Added support for resource function annotations via PEP 3107 to allow\ninline aliases, e.g.def my_resource(name: 'Name::something-important'):Version 1.6: April 26th, 2017Changed howxeno.MethodAttributesworks: it now holds a map of attributes\nand provides methodsget(),put(), andcheck()Version 1.5: April 26th, 2017Added injection interceptorsRefactored method tagging to usexeno.MethodAttributesinstead of named\nobject attributes to make attribute tagging more flexible and usable by\nthe outside world, e.g. for the new injectors.Version 1.4: August 30th, 2016Added cycle detection.Version 1.3: August 29th, 2016Have the injector offer itself as a named resource named 'injector'."} +{"package": "xeno-canto", "pacakge-description": "xeno-canto API Wrapperxeno-canto-py is an API wrapper designed to help users download xeno-canto.org recordings and associated information in an efficient manner. Download requests are processed concurrently using theasyncio,aiohttpandaiofileslibraries to optimize retrieval time. The wrapper also offers delete and metadata generation functions for recording library management.Created to aid in data collection and filtering for the training of machine learning models.Installationxeno-canto-py is available onPyPiand can be downloaded with the package managerpipto install xeno-canto-py.pipinstallxeno-cantoThe package can then be used straight from the command-line:xeno-canto-dlBeardedBellbirdOr imported into an existing Python project:importxenocantoFor users who want more control over the wrapper, navigate to your desired file location in a terminal window and then clone the repository with the following command:gitclonehttps://github.com/ntivirikin/xeno-canto-pyThe only file required for operation isxenocanto.py, so feel free to remove the others or movexenocanto.pyto another working directory.WARNING:Please exercise caution usingtest.pyas executing the tests viaunittestor other test harness will delete anydatasetfolder in the working directory following completion of the tests.UsageThe xeno-canto-py wrapper supports the retrieval of metadata and audio from the xeno-canto database, as well as library management functions such as deletion of recordings matching input tags, removal of folders with an insufficient amount of audio recordings and generation of a single JSON metadata file for a given path containing xeno-canto audio recordings. Examples of command usage are given below.Metadata Downloadxeno-canto -m [parameters]Downloads metadata as a series of JSON files and returns the path to the metadata folder.Example: Metadata retrieval for Bearded Bellbird recordings of quality Axeno-canto -m Bearded Bellbird q:AAudio Recording Downloadxeno-canto -dl [parameters]Retrieves the metadata for the request and uses it to download audio recordings as MP3s from the database.Example: Download Bearded Bellbird recordings from the country of Brazilxeno-canto -dl Bearded Bellbird cnt:BrazilDelete Recordingsxeno-canto -del [parameters]Delete recordings withANYof the parameters given as input.Example: DeleteALLquality D recordings andALLrecordings from Brazilxeno-canto -del q:D cnt:BrazilPurge FoldersRemoves any folders within thedataset/audio/directory that have less recordings than the input valuenum.xeno-canto -p [num]Example: Remove recording folders with less than 10 recordings (not inclusive)xeno-canto -p 10Generate MetadataGenerates metadata for the xeno-canto database recordings at the input path, defaulting todataset/audio/within the working directory if none is given.xeno-canto -g [path]Example: Generate metadata for the recordings located inbird_rec/audio/within the working directoryxeno-canto -g bird_rec/audio/parametersare given in tag:value form in accordance with the API search guidelines. For help in building search terms, consult thexeno-canto API guideand thisarticle. The only exception is when providing English bird names as an argument to the delete function, which must be preceded withen:and have all spaces be replaced with underscores.Directory StructureFiles are saved in the working directory under the folderdataset/. Metadata and audio recordings are separated intometadata/andaudio/folders by request information and bird species respectively. For example:dataset/\n - audio/\n - Indigo Bunting/\n - 14325.mp3\n - Northern Cardinal/\n - 8273.mp3\n - metadata/\n - library.json\n - IndigoBuntingcnt_Canada/\n - page1.json\n - NorthernCardinalq_A/\n - page1.jsonMetadata is retrieved as a JSON file and contains information on each of the audio recordings matching the request parameters provided as input. The metadata also contains the download links used to retrieve the audio recordings. Thelibrary.jsonfile is generated by running the metadata generation command-g.Error 503If an Error 503 is given when attempting a recording download, try passing a value lower than 4 as the num_chunks value in download(filt, num_chunks). This can either be done by changing the default value in the function definition fordownload(filt, num_chunks), or by passing a value intodownload(params)in the body ofmain()as shown below.# Running with default 4 locks on semaphoreasyncio.run(download(params))# Running with 3 locks rather than defaultasyncio.run(download(params,3))Alternatively, you can try experimenting with higher values for num_chunks to see some performance improvements.ContributingAll pull requests are welcome! If any issues are found, please do not hesitate to bring them to my attention.AcknowledgementsThank you to the team at xeno-canto.org and all its contributors for putting together such an amazing database.LicenseMIT"} +{"package": "xeno-canto-utils-nbm", "pacakge-description": "BirdSoundClassifHow to install the package:pip install xeno-canto-utils-nbmHow to use it:xeno -s \"pluvialis squatarola\" -t \"nocturnal flight call\" -lt 30 -q D -o output_folder"} +{"package": "xenoGI", "pacakge-description": "Code for reconstructing genome evolution in clades of microbes.RequirementsNCBI blast+We need blastp and makeblastdb executables (ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/).MUSCLE V5 (https://www.drive5.com/muscle/). For creating protein or DNA alignments.FastTree (http://www.microbesonline.org/fasttree/). For making gene trees.GeneRax (https://github.com/BenoitMorel/GeneRax). For making (species tree aware) gene trees. This is optional but recommended.Python 3Python package dependenciesBiopython (http://biopython.org/). This is for parsing genbank files and can be installed using pip:pip3 install biopythonParasail (https://github.com/jeffdaily/parasail). This is an optimized alignment library, used in calculating scores between proteins. It can also be installed using pip:pip3 install parasailNumpy (http://www.numpy.org/).pip3 install numpyScipy (https://www.scipy.org/).pip3 install scipy(The pip you use needs to correspond to a version of Python 3. In some cases it may just be called pip instead of pip3).Additional dependenciesIf you make use of themakeSpeciesTreeflag orxlMode.py, you will also need the followingASTRAL (https://github.com/smirarab/ASTRAL/).Comments on platforms.xenoGI is developed on Linux. The docker image (linked below) is the easiest way to run on Mac and Windows.InstallationVia pip:pip3 install xenoGI(You will separately need to install blast+, MUSCLE, FastTree, and optionally GeneRax and ASTRAL.)Via docker. For some instructions on using docker, go here:https://hub.docker.com/r/ecbush/xenogiUsing docker, xenoGI get\u2019s run within a virtual machine. This is nice because you don\u2019t have to worry about all the dependencies above (they\u2019re provided in our image). This does come at some cost in terms of performance.CitationIf you use xenoGI in a publication, please cite the following:Bush EC, Clark AE, DeRanek CA, Eng A, Forman J, Heath K, Lee AB, Stoebel DM, Wang Z, Wilber M, Wu H. xenoGI: reconstructing the history of genomic island insertions in clades of closely related bacteria. BMC Bioinformatics. 19(32). 2018.Liu J, Mawhorter R, Liu I, Santichaivekin S, Bush E, Libeskind-Hadas R. Maximum Parsimony Reconciliation in the DTLOR Model. BMC Bioinformatics. 22(394). 2021.How to useAnexample/directory is included in this repository.The sections below give some instructions about how to run xenoGI on this example. You can use this to make sure you\u2019ve installed it properly and so forth. The github repository also contains a TUTORIAL which you can run through after completing the README.The basic method works on a set of species with known phylogenetic relationships. In the example, these species are: E. coli K12, E. coli ATCC 11775, E. fergusonii and S. bongori. In cases where you don\u2019t know the species tree, xenoGI has methods to help you reconstruct it.Required filesThe working directory must contain:A parameter file. In the providedexample/directory this is calledparams.py.A newick format tree representing the relationships of the strains. In the example this is calledexample.tre. Note that branch lengths are not used in xenoGI, andexample.tredoes not contain branch lengths. Also note that internal nodes should be given names in this tree. In the example.tre we label them s0, s1 etc. The parameterspeciesTreeFNinparams.pyhas the path to this tree file. If a strain tree is not available, xenoGI has some accessory methods, described below, to help obtain one.A subdirectory of sequence files. In the example, this is calledncbi/. Contained in this subdirectory will be genbank (gbff) files for the species. The parametergenbankFilePathinparams.pyhas the path to these files.Naming of strainsThe system needs a way to connect the sequence files to the names used in the tree.In the example, the sequence files have names corresponding to their assembly accession number from ncbi. We connect these to the human readable names in example.tre using a mapping given in the filencbiHumanMap.txt. This file has two columns, the first giving the name of the genbank file, and the second giving the name for the strain used in the tree file. Inparams.pythe parameterfileNameMapFNis set to point to this file.Note that the strain names should not contain any dashes, spaces, commas or special characters.Another approach is to change the names of the sequence files to match what\u2019s in the tree. If you do this, then you should setfileNameMapFN = Noneinparams.py. (This is not necessary in the example, which is already set to run the other way).Pointing xenoGI to various executablesBefore running xenoGI you\u2019ll have to ensure that it knows where various executables are. Editparams.pyusing a text editor such as emacs, vim, nano, Visual Studio Code etc. You should edit the following to give the absolute (full) path to the directory where theblastpandmakeblastdbexecutables reside:blastExecutDirPath = '/usr/bin/'(Change \u2018/usr/bin/\u2019 to correspond to the right location on your system).Also make sure that the absolute paths to MUSCLE and FastTree are correct inparams.py(the parametersmusclePathandfastTreePath). If you intend to use generax to make species tree aware gene trees, then you also need to setgeneRaxPath. (The default parameter file is set to use generax, so unless you change theuseGeneRaxToMakeSpeciesTreesparameter, described below, you\u2019ll need to supply ageneRaxPath).If you will be using the makeSpeciesTree functionality, then you will also need to specifyastralPathandjavaPath.Running the codeIf you install via pip, then you should have an executable script in your path called xenoGI.You run the code from within the working directory. To run the example, you would cd into theexample/directory. You will need to ensure that theparams.pyparameters file contains the correct path to the directory with the blastp and makeblastdb executables in it, as well as the MUSCLE and FastTree executables. Then, the various steps of xenoGI can be run all at once like this:xenoGI params.py runAllThey can also be run individually:xenoGI params.py parseGenbank\nxenoGI params.py runBlast\nxenoGI params.py calcScores\nxenoGI params.py makeFamilies\nxenoGI params.py makeIslands\nxenoGI params.py refine\nxenoGI params.py printAnalysis\nxenoGI params.py createIslandBedIf for some reason you don\u2019t want to install via pip, then you can download the repository and run the code like this:python3 path-to-xenoGI-github-repository/xenoGI-runner.py params.py runAll(In this case you will have to make sure all the python package dependencies are satisfied.)What the steps doparseGenbankruns through the genbank files and produces input files that are used by subsequent code. This step pulls out every CDS feature that has a/translationtag. The fields that are recorded (if present) are locus_tag, protein_id, product (that is gene description), and chromosomal coordinates as well as the protein sequence. If the parameterdnaBasedGeneTreesis True, the DNA sequence for each gene is kept as well.runBlastdoes an all vs. all protein blast of the genes in these strains. The number of processes it will run in parallel is specified by thenumProcessesparameter in the parameter file. Before running a particular comparison, runBlast checks to see if the output file for that comparison already exists (e.g. from a previous run). If so it skips the comparison.calcScorescalculates similarity and synteny scores between genes in the strains. It is also (mostly) parallelized.makeFamiliescalculates gene families using blast, FastTree, GeneRax (optionally), and a customized variant of the DTL reconciliation algorithm called DTLOR. This approach considers synteny in the family formation process.makeIslandsgroups families according to their origin, putting families with a common origin together as islands. It is partly parallelized.refinereconsiders certain families in light of the output of makeIslands. In particular, this step looks at cases where there are multiple most parsimonious reconciliations, and chooses the reconciliation that is most consistent with neighboring families. It then re-runs makeIslands.printAnalysisproduces a number of analysis/output files intended for the end user.createIslandBedproduces bed files for each genome.Locus families and locus islandsA brief illustration will allow us to define some terminology used in xenoGI\u2019s output. The basic goal of xenoGI is to group genes with a common origin and map them onto a phylogenetic tree.Consider a clade of three species: (A,B),C. In this group, A and B are most closely related, and C is the outgroup. Gene a in species A has an ortholog b in species B. These two genes have high synteny, but have no ortholog in C. We call a and b alocus familybecause they are descended from a common ancestor, and occur in the same syntenic location.When a genomic island inserts as a part of a horizontal transfer event, it typically brings in multiple locus families at the same time. xenoGI will attempt to group these into alocus island. In the a/b case, if there were several other locus families nearby that also inserted on the branch leading to the A,B clade, we would group them together into a single locus island.Initial families, origin families and the DTLOR modelIn fact, a locus family has several possible origins. It may be due to a horizontal transfer event coming from some other genome. Alternatively, it may reflect a rearrangement event within a genome, moving genes to a new syntenic location (for example in conjunction with a duplication event). A final possibility is that it is a core family and originated in the common ancestor of the strains under consideration. One of xenoGI\u2019s goals is to distinguish between these possibilities for each locus family (and also for the locus islands that contain them).xenoGI does this during the process of family formation. It begins by forming large gene groupings using single linkage clustering and sequence similarity as determined by blast. It then takes these \u201cblast families\u201d, breaks up the larger ones (which must be done for reasons of time efficiency in later steps), and uses them as a basis for making a set of families which we call initial families. For each initial family, xenoGI creates a gene tree using MUSCLE and FastTree (the user can determine whether this should be done with DNA or protein by setting the input parameter dnaBasedGeneTrees). It then reconciles each resulting gene tree to the species tree using the DTLOR model.DTLOR is an extension we have developed to the DTL (duplication-transfer-loss) reconciliation model. It is especially suited to reconciliation in clades of closely related microbes because it allows some of the evolution of a gene family to occur outside of the given species tree. In particular, it allows multiple entry events into the species tree (where DTL allows only one). To facilitate the recognition of such entry events, the model also keeps track of thesyntenic regionof each gene as it evolves in the species tree. Two genes are said to be in the same syntenic region if they share a substantial fraction of core genes in a relatively large window around them and, second, they share a certain amount of similarity among all genes in a smaller window around them. Thus, in addition to duplication, transfer, and loss events, the DTLOR model addsoriginevents to indicate that a gene is transferred from outside of the species tree andrearrangementevents that account for changes in the syntenic regions of genes within the same the genome.xenoGI obtains a reconciliation for each initial family, and then uses these to break the initial families up according to origin events. The new families that result from this are calledorigin familiesbecause each one has an origin event at its base. Origin events can either correspond to core genes (if they occur at the root of the species tree) or to horizontal transfer events (if they occur below the root). In general, users will be more interested in origin families than initial families. However the class representing initial families does contain some information (the raw reconciliation output) which isn\u2019t present in the origin families, and may occasionally be of interest.It may be helpful to give an example of the sort of thing one might find in an origin family. Consider a clade of four species: ((W,X),Y),Z:_____ W\n ____|s2\n ____|s1 |_____ X\n | |\n_|s0 |__________ Y\n |\n |_______________ ZWe\u2019ve labeled the internal nodes on this tree s0,s1, and s2.Imagine that genes w1 and x1 represent a locus family in the W,X clade. They are orthologs sharing high synteny. (And they have no ortholog in species Y or Z). Imagine that there is also a paralog x2 that occurs in a different syntenic region (and that there is no w2, y2 or z2, ie W, Y and Z have no paralogs in this syntenic region). This situation could arise if there had been a horizontal transfer from outside the clade on the lineage leading to s2, and then a subsequent duplication and rearrangement after s2 on the lineage leading to X. If this were the case, xenoGI would place x1, y1, and x2 into a single origin family. w1 and x1 would be put in one locus family, and x2 in another. (In general, an origin family consists of one or more locus families.)Notes on several input parametersrootFocalCladedefines the focal clade where we will do the reconstruction. It is specified by giving the name of an internal node in the species tree. It should be chosen such that there are one or more outgroups outside the focal clade. These outgroups help us to better recognize core genes given the possibility of deletion in some lineages.numProcessesdetermines how many separate processes to run in parts of the code that are parallel. If you have a machine with 32 processors, you would typically set this to 32 or less.dnaBasedGeneTreesspecifies what will be used to make gene trees. If this is set to True, the method will use DNA based alignments, otherwise it will use protein alignments.useGeneRaxToMakeSpeciesTrees. If set to True, xenoGI uses GeneRax in addition to FastTree to make species trees. GeneRax produces species-tree-aware gene trees, which are known to be of higher quality than gene trees calculated from gene sequences alone. (The cost is that GeneRax is slower). If using GeneRax then you also need to specify the parametergeneRaxPath.The DTLOR cost parameters:duplicationCost,transferCost,lossCost,originCost,rearrangeCost. The parsimony based reconciliation algorithm finds the minimum cost mapping of a gene tree onto the species tree. These parameters specify the costs for each of the DTLOR operations. The params.py file included in the example directory contains a set of costs we have found to work reasonably well, however users may potentially want to adjust these. The same parameters are used for all reconciliations, with one exception (see next bullet).reconcilePermissiveOriginGeneListPath. This parameter is commented out by default, and will only be useful in certain situations. There are some genomic islands that insert repeatedly in the same syntenic region. An example is the SCCmec element inStaphylococcus aureus. In such cases, it is desirable to do the reconciliation with cost parameters that are permissive to origin events. xenoGI allows users to identify families that should be handled in this way. The first step is to create a file of xenoGI genes belonging to such families (one gene per line). We then set thereconcilePermissiveOriginGeneListPathto point to this file. The scriptgetProteinsWithBlastHitsVsMultifasta.pyin the misc/ directory may be useful in producing this file. The documentaiton for the misc directory has some further information.Output filesThe last two steps, printAnalysis and createIslandBed make the output files relevant to the user.printAnalysisThis script produces a set of species specific genome files. These files all have the namegenesin their stem, followed by the strain name, and the extension .tsv. In the example/ data set,genes-E_coli_K12.tsvis one such. These files contain all the genes in a strain laid out in the order they occur on the contigs. Each line corresponds to one gene and contains:\n+ gene name\n+ origin of the gene, specified by a single character: a C indicating core gene, or an X indicating xeno horizontal transfer. This field is an interpretation of the O event from the DTLOR reconcilation based on its placement in the species tree.\n+ gene history, specified by a string. This gives the history of the gene from its origin until the tip of the gene tree, and consists of single letters corresponding to the operations in the reconcilation model. D, duplication; T, transfer (within the species tree); O, origin; R, rearrangement; S, cospeciation.\n+ locus island number\n+ initial family number\n+ origin family number\n+ locus family number\n+ gene descriptionislands.tsvtab delimited listing of locus islands. Each line corresponds to one locus island. The first field is the locus island number, the second field is its mrca (most recent common ancestor), and the third is a string giving the origin of each locus family in the locus island (possible values for each locus family are C for core gene, X for xeno HGT, and R for rearrangement). Subsequent fields give the locus families in this locus island. Each locus family is listed with its number, and then the genes it contains, separated by commas.islandsSummary.txtA more human readable summary of locus islands, organized by node. This includes a tabular printout of the island, as well as a listing of each gene and its description if any.createIslandBedcreates a subdirectory called bed/ containing bed files for each genome showing the locus islands in different colors. (Color is specified in the RGB field of the bed).Interactive analysisAfter you have done runAll, it is possible to bring up the interpreter for interactive analysis:xenoGI params.py interactiveAnalysisFrom within python, you can then run functions such asprintLocusIslandsAtNodeUsage:printLocusIslandsAtNode('s2') # All locus islands at node s2\nprintLocusIslandsAtNode('E_coli_K12') # All locus islands on the E. coli K12 branchfindGeneUsage:findGene('gadA')Find information about a gene. Searches all the fields present in the geneInfo file, so the search string can be a locus tag, protein ID, a common name, or something present in the description. For each hit, prints the gene, LocusIsland, initialFamily, originFamily, LocusFamily and gene description.printLocusIslandSay we\u2019ve identified locus island 1550 as being of interest. We can print it like this:printLocusIsland(1550,10) # First argument is locus island id, second is the number of genes to print to each sideprintLocusIsland prints the locus island in each strain where it\u2019s present. Its output includes the locus island and family numbers for each gene, the most recent common ancestor (mrca) of the family, and a description of the gene.printFamPrint scores within a particular gene family, and also with similar genes not in the family:printFam(originFamiliesO,5426)This function also prints a summary of the reconciliation between the gene tree for this family and the species tree.Note that this function takes a family number, not a locus family number.Obtaining a species tree if you don\u2019t already have oneHaving an accurate species tree is a key to the xenoGI method.The package does include some functions that may be helpful if you don\u2019t have a species tree. These use MUSCLE and FastTree to make gene trees, and ASTRAL to consolidate those gene trees into a species tree.You begin by running the first three steps of xenoGI:xenoGI params.py parseGenbank\nxenoGI params.py runBlast\nxenoGI params.py calcScoresYou can then runmakeSpeciesTree:xenoGI params.py makeSpeciesTreeIn theparams.pyfile, the parameterdnaBasedGeneTreesdetermines whether DNA or protein are used to make genes trees. (If True, DNA is used).In order to usemakeSpeciesTree, you will also need to add one parameter toparams.py. There should be a parameter outGroup which specifies a single outgroup species to be used in rooting the species tree.OncemakeSpeciesTreehas completed, you can proceed with the rest of xenoGI:xenoGI params.py makeFamilies\nxenoGI params.py makeIslands\nxenoGI params.py refine\nxenoGI params.py printAnalysis\nxenoGI params.py createIslandBedAdditional flagsPrint the version number:xenoGI params.py versionCalculate the amino acid identity between strains:xenoGI params.py aminoAcidIdentityThis uses blast output, and so should be run after the runBlast step. It identifies the best reciprocal hits between each pair of strains. It then averages protein identity across these, weighted by alignment length.Produce a set of pdf files showing histograms of scores between all possible strains:xenoGI params.py plotScoreHistsAdditional filesThe github repository also contains an additional directory called misc/. This contains various python scripts that may be of use in conjunction with xenoGI. Installation via pip does not include this, so to use these you need to clone the github repository. There is some brief documentation included in the misc/ directory."} +{"package": "xenoglossia", "pacakge-description": "IntroductionA programming language specifically designed such that ASTs generated by markov chain are likely to produce programs with meaningful effect\u2014mcc (@mcclure111)July 11, 2015Xenoglossia is a simple string manipulation language, akin to sed. It\nwas created with the goal of producing surprising, fun-to-read programs\nwhich can be generated in novel manners by a computer.An introduction to the language and its syntax can be found in thedesign document, and the documentation of the\nbuiltin functions can currently be found in the docstrings of thebuiltins module.UsageXenoglossia will install an executable namedxg. To run a program,\ncallxg--inputSTRING \"xenoglossia program\"; for example:xg--input\"This is the input string\"\"sub 'input' 'output'\"You can also pipe input into stdin:echo\"This is the input string\"|xg\"sub 'input' 'output'\"Sample programsReplace two words in a sentence:gsub \"favorite\" \"favourite\" gsub \"color\" \"colour\"Rearrange the words in a sentence, then capitalize the new sentence:burst \" \" shuffle capitalize"} +{"package": "xenolith", "pacakge-description": "XenolithXenolith is a command-line based tool that allows for files to be encrypted with public keys and decrypted by users who have . With the main components being FiloSottile'sageand str4d'sragelibrary for encryption, Xenolith usesssh-rsa,ssh-ed25519, and age/rages'skeygenas keys.InstallationRequirementsInstallageorrageUsePython 3.8.4or higherInstallationInstall using pippip install xenolithUsageXenolith uses 5 commands:- xenolith\nContains a list of all the commands\n\n\n- xenolith init [--encryption, -e]\nInitializes the project in the given directory by creating a .secret folder. This folder contains a `recipients.txt` and `config.json` file.\n\nOptions:\n-e, --encryption Specifies an encryption library (age, rage). Defaults to age\n\n\n- xenolith encryption [age/rage]\nChanges the encryption library to age or rage\n\n\n- xenolith add [key]\nAdds a public key (Recipient) to the list of recipients that can access an encrypted file.\n\n\n- xenolith remove [key]\nRemoves a public key from the list of recipients. The key must match one of the keys found in `.secret/recipients.txt`\n\n\n- xenolith encrypt [file_name]\nWith a given set of recipients, encrypts the given file and appends an .age suffix at the end.\n\n\n- xenolith decrypt [key_file] [file_path]\nWith a given key and file, decrypts a file that have been previously encrypted.ContributingTo get started:DownloadPython 3.8.4Set upPython's Virtual Environmentpython3 -m venv venvDownload the project's requirements and run venvpip install -r requirements.txt\nsource ./venv/bin/activateInstallageandrageTo test the application locally, run:pip install --editable .Tests can be run by executingrun_tests.shfound in thebin/folderLicenseThis project uses theMITlicense."} +{"package": "xenomake", "pacakge-description": "No description available on PyPI."} +{"package": "xenon", "pacakge-description": "Xenon is a monitoring tool based onRadon.\nIt monitors your code\u2019s complexity. Ideally, Xenon is run every time you\ncommit code. Through command line options, you can set various thresholds for\nthecomplexityof your code. It will fail (i.e. it will exit with a\nnon-zero exit code) when any of these requirements is not met.InstallationWith Pip:$pipinstallxenonOr download the source and run the setup file (requires setuptools):$pythonsetup.pyinstallXenon is tested with all versions of Python from2.7to3.6as well asPyPy.UsageTypically you would use Xenon in two scenarios:As agit commithook: to make sure that your code never exceeds some\ncomplexity values.On acontinuous integrationserver: as a part of your build, to keep\nunder control, as above, your code\u2019s complexity. See Xenon\u2019s.travis.yml filefor an example usage.The command lineEverything boils down to Xenon\u2019s command line usage.\nTo control which files are analyzed, you use the options-e,--excludeand-i,--ignore. Both accept a comma-separated list of glob patterns. The\nvalue usually needs quoting at the command line, to prevent the shell from\nexpanding the pattern (in case there is only one). Every filename is matched\nagainst theexcludepatterns. Every directory name is matched against theignorepatterns. If any of the patterns matches, Xenon won\u2019t even descend\ninto them.The actual threshold values are defined through these options:-a,--max-average: Threshold for theaveragecomplexity (across all the\ncodebase).-m,--max-modules: Threshold formodulescomplexity.-b,--max-absolute:Absolutethreshold forblockcomplexity.All of these options are inclusive.An actual example$xenon--max-absoluteB--max-modulesA--max-averageAor, more succinctly:$xenon-bB-mA-aAWith these options Xenon will exit with a non-zero exit code if any of the\nfollowing conditions is met:At least one block has a rank higher thanB(i.e.C,D,EorF).At least one module has a rank higher thanA.The average complexity (among all of the analyzed blocks) is ranked withBor higher.Other resourcesFor more information regarding cyclomatic complexity and static analysis in\nPython, please refer to Radon\u2019s documentation, the project on which Xenon is\nbased on:More on cyclomatic complexity:http://radon.readthedocs.org/en/latest/intro.htmlMore on Radon\u2019s ranking:http://radon.readthedocs.org/en/latest/commandline.html#the-cc-command"} +{"package": "xenon1234", "pacakge-description": "UNKNOWN"} +{"package": "xenon-fuse", "pacakge-description": "XENON fuseFramework forUnifiedSimulation ofEventsfuse is the refactored version of the XENONnT simulation chain. The goal of this project is to unifyepixandWFSiminto a single program. fuse is based on thestrax framework, so that the simulation steps are encoded in plugins with defined inputs and outputs. This allows for a flexible and modular simulation chain.InstallationWith all requirements fulfilled (e.g., on top of theXENONnT montecarlo_environment):python -m pip install xenon-fuseor install from source:git clone git@github.com:XENONnT/fuse\ncd fuse\npython -m pip install . --userPlugin StructureThe full simulation chain in split into multiple plugins. An overview of the simulation structure can be found below."} +{"package": "xenon-gcp-sdk", "pacakge-description": "No description available on PyPI."} +{"package": "xenon-lfp-analysis", "pacakge-description": "Xenon LFP Analysis PlatformIntroductionThis is an interactive platform for analyzing bandpass filtered (1 to 2048 Hz) Local Field Potential (LFP) activity and seizure-like activity. This Graphical User Interface (GUI) is built in Python using Plotly's Dash library for interactive visualizations, this includes several features to generate summary measures, plots, trace LFP activity over time, and for people familiar with basic Python this can also serve as a boiler plate to customize, add functions and visualization based on individual researchers\u2019 analysis requirements. We demonstrate this new python-based software tool for analysis and tracking of local field potential activity using the 3Brain MEA recording system but it can easily be adapted to any MEA recording platform. This GUI is also easily adaptable to large-scale EEG recordings and likely can provide a useful mapping tool for In-Vivo LFP activity. Our current GUI has a particular utility for analysis of seizure-like activity but can be used for analysis of any network LFP signal.Installation:pip install xenon_lfp_analysisRun the Xenon LFP Analysis GUI:After installation you can run the GUI by running the following command in the terminal:$>run_lfp_analysisDocumentationhttps://xenon-lfp-analysis.readthedocs.io/en/latest/index.htmlPrePrinthttps://www.biorxiv.org/content/10.1101/2022.03.25.485521v1"} +{"package": "xenon_player", "pacakge-description": "UNKNOWN"} +{"package": "xenonpy", "pacakge-description": "No description available on PyPI."} +{"package": "xenon_tools", "pacakge-description": "UNKNOWN"} +{"package": "xenon-view-sdk", "pacakge-description": "xenon-view-sdkThe Xenon View Python SDK is the Python SDK to interact withXenonView.Table of contents:What's NewIntroductionSteps To Get StartedIdentify Business OutcomesIdentify Customer Journey MilestonesEnumerate Technical StackInstallationInstrument Business OutcomesInstrument Customer Journey MilestonesDetermine Commit Points(Optional) Group Customer JourneysAnalysisPerform ExperimentsDetailed UsageInstallationInitializationService/Subscription/SaaS Business OutcomesEcommerce Business OutcomesCustomer Journey MilestonesFeatures UsageContent InteractionCommit PointsHeartbeatsPlatformingExperimentsCustomer Journey GroupingOther Considerations(Optional) Error Handling(Optional) Custom Customer Journey Milestones(Optional) Journey IdentificationLicenseWhat's Newv0.1.9 - Added: Abandonment Watchdog Feature, leadAttribution outcomev0.1.8 - Added: Term for all subscriptions.v0.1.7 - Added: changed value to price.v0.1.6 - Added: Downsell, Ad, Content Archive, Subscription Pause and included price for all subscriptionsv0.1.5 - remove journeys callv0.1.4 - Rename tag to variantv0.1.3 - Readme updatev0.1.2 - typo fixedv0.1.1 - duplicates for new SDK handledv0.1.0 - SDK redesignIntroductionEveryone should have access to world-class customer telemetry.You should be able to identify the most pressing problems affecting your business quickly.\nYou should be able to determine if messaging or pricing, or technical challenges are causing friction for your customers.\nYou should be able to answer questions like:Is my paywall wording or the price of my subscriptions causing my customers to subscribe less?Is my website performance or my application performance driving retention?Is purchasing a specific product or the product portfolio driving referrals?With the correct approach to instrumentation coupled with AI-enhanced analytics, you can quickly answer these questions and much more.back to topGet Started With The Following Steps:The Xenon View SDK can be used in your application to provide a new level of customer telemetry. You'll need to embed the instrumentation into your website/application via this SDK.Instrumentation will vary based on your use case; are you offering a service/subscription (SaaS) or selling products (Ecom)?In a nutshell, the steps to get started are as follows:Identify Business Outcomes and Customer Journey Milestones leading to those Outcomes.Instrument the Outcomes/Milestones.Analyze the results.Step 1 - Business OutcomesRegardless of your business model, your first step will be identifying your desired business outcomes.Example - Service/Subscription/SaaS:Lead CaptureAccount SignupInitial SubscriptionRenewed SubscriptionUpsold SubscriptionReferralExample - Ecom:Place the product in the cartCheckoutUpsoldPurchase:memo: Note: Each outcome has an associated success and failure.Step 2 - Customer Journey MilestonesFor each Business Outcome, identify potential customer journey milestones leading up to that business outcome.Example - Service/Subscription/SaaS forLead Capture:View informational contentAsks question in the forumViews FAQsViews HowToRequests info productExample - Ecom forPlace product in cart:Search for product informationLearns about productRead reviewsStep 3 - Enumerate Technical StackNext, you will want to figure out which SDK to use. We have some of the most popular languages covered.Start by listing the technologies involved and what languages your company uses. For example:Front end - UI (Javascript - react)Back end - API server (Java)Mobile app - iPhone (Swift)Mobile app - Android (Android Java)Next, figure out how your outcomes spread across those technologies. Below are pointers to our currently supported languages:ReactNext.JsAngularHTMLPlain JavaScriptiPhone/iPadMacJavaAndroid JavaPythonFinally, continue the steps below for each technology and outcome.Step 4 - InstallationAfter you have done the prework ofStep 1andStep 2, you are ready toinstall Xenon View.\nOnce installed, you'll need toinitialize the SDKand get started instrumenting.Step 5 - Instrument Business OutcomesWe have provided several SDK calls to shortcut your instrumentation and map to the outcomes identified inStep 1.These calls will roll up into the associated Categories during analysis. These rollups allow you to view each Category in totality.\nAs you view the categories, you can quickly identify issues (for example, if there are more Failures than Successes for a Category).Service/Subscription/SaaS Related Outcome Calls(click on a call to see usage)CategorySuccessDeclineLead AttributionleadAttribution()Lead CaptureleadCaptured()leadCaptureDeclined()Account SignupaccountSignup()accountSignupDeclined()Application InstallationapplicationInstalled()applicationNotInstalled()Initial SubscriptioninitialSubscription()subscriptionDeclined()Subscription RenewedsubscriptionRenewed()subscriptionCanceled()/subscriptionPaused()Subscription UpsellsubscriptionUpsold()subscriptionUpsellDeclined()/subscriptionDownsell()Ad ClickedadClicked()adIgnored()Referralreferral()referralDeclined()Ecom Related Outcome Calls(click on a call to see usage)CategorySuccessDeclineLead AttributionleadAttribution()Lead CaptureleadCaptured()leadCaptureDeclined()Account SignupaccountSignup()accountSignupDeclined()Add To CartproductAddedToCart()productNotAddedToCart()Product Upsellupsold()upsellDismissed()CheckoutcheckedOut()checkoutCanceled()/productRemoved()Purchasepurchased()purchaseCanceled()Promise FulfillmentpromiseFulfilled()promiseUnfulfilled()Product DispositionproductKept()productReturned()Referralreferral()referralDeclined()Step 6 - Instrument Customer Journey MilestonesNext, you will want to instrument your website/application/backend/service for the identified Customer Journey MilestonesStep 2.\nWe have provided several SDK calls to shortcut your instrumentation here as well.During analysis, each Milestone is chained together with the proceeding and following Milestones.\nThat chain terminates with an Outcome (described inStep 4).\nAI/ML is employed to determine Outcome correlation and predictability for the chains and individual Milestones.\nDuring theanalysis step, you can view the correlation and predictability as well as the Milestone chains\n(called Customer Journeys in this guide).Milestones break down into two types (click on a call to see usage):FeaturesContentfeatureAttempted()contentViewed()featureFailed()contentCreated()/contentEdited()featureCompleted()contentDeleted()/contentArchived()contentRequested()/contentSearched()Step 7 - Commit PointsOnce instrumented, you'll want to select appropriatecommit points. Committing will initiate the analysis on your behalf by Xenon View.Step 8 (Optional) - Group Customer JourneysAll the customer journeys (milestones and outcomes) are anonymous by default.\nFor example, if a Customer interacts with your brand in the following way:Starts on your marketing website.Downloads and uses an app.Uses a feature requiring an API call.Each of those journeys will be unconnected and not grouped.To associate those journeys with each other, you candeanonymizethe Customer. Deanonymizing will allow for a deeper analysis of a particular user.Deanonymizing is optional. Basic matching of the customer journey with outcomes is valuable by itself. Deanonymizing will add increased insight as it connects Customer Journeys across devices.Step 9 - AnalysisOnce you have released your instrumented code, you can head toXenonViewto view the analytics.Step 10 - Perform ExperimentsThere are multiple ways you can experiment using XenonView. We\"ll focus here on three of the most common: time, platform, and variant based cohorts.Time-based cohortsEach Outcome and Milestone is timestamped. You can use this during the analysis phase to compare timeframes. A typical example is making a feature change.\nKnowing when the feature went to production, you can filter in the XenonView UI based on the timeframe before and the timeframe after to observe the results.Variant-based cohortsYou can identify a journey collection as anexperimentbefore collecting data. This will allow you to run A/B testing-type experiments (of course not limited to two).\nAs an example, let\"s say you have two alternate content/feature variants and you have a way to direct half of the users to Variant A and the other half to Variant B.\nYou can name each variant before the section of code that performs that journey. After collecting the data, you can filter in the XenonView UI based on each variant to\nobserve the results.Platform-based cohortsYou canPlatformany journey collection before collecting data. This will allow you to experiment against different platforms:Operating System NameOperating System versionDevice model (Pixel, iPhone 14, Docker Container, Linux VM, Dell Server, etc.)A software version of your application.As an example, let's say you have an iPhone and Android mobile application and you want to see if an outcome is more successful on one device verse the other.\nYou can platform before the section of code that performs that flow. After collecting the data, you can filter in the XenonView UI based on each platform to\nobserve the results.back to topDetailed UsageThe following section gives detailed usage instructions and descriptions.\nIt provides code examples for each of the calls.The SDK supports Python 3+.InstallationYou can install the View Python SDK fromPyPI:pipinstallxenon-view-sdkback to topInstantiationThe View SDK is a Python module you'll need to include in your application. After inclusion, you'll need to init the singleton object:fromxenon_view_sdkimportXenon# start by initializing Xenon ViewXenon('<API KEY>')-OR-fromxenon_view_sdkimportXenon# to initialize Xenon View after constructionXenon('TBD')Xenon().key('<API KEY>')Of course, you'll have to make the following modifications to the above code:Replace<API KEY>with yourapi keyback to topService/Subscription/SaaS Related Business OutcomesLead AttributedUse this call to track Lead Attribution (Google Ads, Facebook Ads, etc.)\nYou can add a source and identifier string to the call to differentiate as follows:leadAttributed()fromxenon_view_sdkimportXenonsource='Google Ad'identifier='Search'# Successful Lead Attributed to Google AdXenon().leadAttributed(source)#...# Successful Lead Attributed to Google Search AdXenon().leadAttributed(source,identifier)Lead CaptureUse this call to track Lead Capture (emails, phone numbers, etc.)\nYou can add a specifier string to the call to differentiate as follows:leadCaptured()fromxenon_view_sdkimportXenonemailSpecified=\"Email\"phoneSpecified=\"Phone Number\"# Successful Lead Capture of an emailXenon().leadCaptured(emailSpecified)# ...# Successful Lead Capture of a phone numberXenon().leadCaptured(phoneSpecified)leadCaptureDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonemailSpecified=\"Email\"phoneSpecified=\"Phone Number\"# Unsuccessful Lead Capture of an emailXenon().leadCaptureDeclined(emailSpecified)# ...# Unsuccessful Lead Capture of a phone numberXenon().leadCaptureDeclined(phoneSpecified)Account SignupUse this call to track when customers signup for an account.\nYou can add a specifier string to the call to differentiate as follows:accountSignup()fromxenon_view_sdkimportXenonviaFacebook=\"Facebook\"viaGoogle=\"Google\"viaEmail=\"Email\"# Successful Account Signup with FacebookXenon().accountSignup(viaFacebook)# ...# Successful Account Signup with GoogleXenon().accountSignup(viaGoogle)# ...# Successful Account Signup with an EmailXenon().accountSignup(viaEmail)accountSignupDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonviaFacebook=\"Facebook\"viaGoogle=\"Google\"viaEmail=\"Email\"# Unsuccessful Account Signup with FacebookXenon().accountSignupDeclined(viaFacebook)# ...# Unsuccessful Account Signup with GoogleXenon().accountSignupDeclined(viaGoogle)# ...# Unsuccessful Account Signup with an EmailXenon().accountSignupDeclined(viaEmail)Application InstallationUse this call to track when customers install your application.applicationInstalled()fromxenon_view_sdkimportXenon# Successful Application InstallationXenon().applicationInstalled()applicationNotInstalled():memo: Note: You want consistency between success and failure.fromxenon_view_sdkimportXenon# Unsuccessful or not completed Application InstallationXenon().applicationNotInstalled()Initial SubscriptionUse this call to track when customers initially subscribe.\nYou can add a specifier string to the call to differentiate as follows:initialSubscription()fromxenon_view_sdkimportXenontierSilver=\"Silver Monthly\"tierGold=\"Gold\"tierPlatium=\"Platium\"annualSilver=\"Silver Annual\"method=\"Stripe\"# optionalprice='$25'#optionalterm=\"30d\"#optional# Successful subscription of the lowest tier with StripeXenon().initialSubscription(tierSilver,method)# Successful subscription of the lowest tier with Stripe for $25 for termXenon().initialSubscription(tierSilver,method,price,term)# ...# Successful subscription to the middle tierXenon().initialSubscription(tierGold)# ...# Successful subscription to the top tierXenon().initialSubscription(tierPlatium)# ...# Successful subscription of an annual periodXenon().initialSubscription(annualSilver)subscriptionDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenontierSilver=\"Silver Monthly\"tierGold=\"Gold\"tierPlatium=\"Platium\"annualSilver=\"Silver Annual\"method=\"Stripe\"# optionalprice='$25'# optionalterm=\"30d\"# optional# Unsuccessful subscription of the lowest tierXenon().subscriptionDeclined(tierSilver)# ...# Unsuccessful subscription of the middle tierXenon().subscriptionDeclined(tierGold)# ...# Unsuccessful subscription to the top tierXenon().subscriptionDeclined(tierPlatium)# ...# Unsuccessful subscription of an annual period with StripeXenon().subscriptionDeclined(annualSilver,method)# Unsuccessful subscription of an annual period for $25 for termXenon().subscriptionDeclined(annualSilver,method,price,term)Subscription RenewalUse this call to track when customers renew.\nYou can add a specifier string to the call to differentiate as follows:subscriptionRenewed()fromxenon_view_sdkimportXenontierSilver=\"Silver Monthly\"tierGold=\"Gold\"tierPlatium=\"Platium\"annualSilver=\"Silver Annual\"method=\"Stripe\"#optionalprice='$25'# optionalterm=\"30d\"#optional# Successful renewal of the lowest tier with StripeXenon().subscriptionRenewed(tierSilver,method)# Successful renewal of the lowest tier with Stripe for $25 for termXenon().subscriptionRenewed(annualSilver,method,price,term)# ...# Successful renewal of the middle tierXenon().subscriptionRenewed(tierGold)# ...# Successful renewal of the top tierXenon().subscriptionRenewed(tierPlatium)# ...# Successful renewal of an annual periodXenon().subscriptionRenewed(annualSilver)subscriptionCanceled():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenontierSilver=\"Silver Monthly\"tierGold=\"Gold\"tierPlatium=\"Platium\"annualSilver=\"Silver Annual\"method=\"Stripe\"#optionalprice='$25'# optionalterm=\"30d\"#optional# Canceled subscription of the lowest tierXenon().subscriptionCanceled(tierSilver)# ...# Canceled subscription of the middle tierXenon().subscriptionCanceled(tierGold)# ...# Canceled subscription of the top tierXenon().subscriptionCanceled(tierPlatium)# ...# Canceled subscription of an annual period with StripeXenon().subscriptionCanceled(annualSilver,method)# Canceled subscription of an annual period with Stripe for $25Xenon().subscriptionCanceled(annualSilver,method,price,term)subscriptionPaused():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenontierSilver=\"Silver Monthly\"tierGold=\"Gold\"tierPlatium=\"Platium\"annualSilver=\"Silver Annual\"method=\"Stripe\"#optionalprice='$25'# optionalterm=\"30d\"#optional# Paused subscription of the lowest tierXenon().subscriptionPaused(tierSilver)# ...# Paused subscription of the middle tierXenon().subscriptionPaused(tierGold)# ...# Paused subscription of the top tierXenon().subscriptionPaused(tierPlatium)# ...# Paused subscription of an annual period with StripeXenon().subscriptionPaused(annualSilver,method)# Paused subscription of an annual period with Stripe for $25 for termXenon().subscriptionPaused(annualSilver,method,price,term)Subscription UpsoldUse this call to track when a Customer upgrades their subscription.You can add a specifier string to the call to differentiate as follows:subscriptionUpsold()fromxenon_view_sdkimportXenontierGold=\"Gold Monthly\"tierPlatium=\"Platium\"annualGold=\"Gold Annual\"method=\"Stripe\"#optionalprice='$25'# optionalterm=\"30d\"#optional# Assume already subscribed to Silver# Successful upsell of the middle tier with StripeXenon().subscriptionUpsold(tierGold,method)# Successful upsell of the middle tier with Stripe for $25 for termXenon().subscriptionUpsold(tierGold,method,price,term)# ...# Successful upsell of the top tierXenon().subscriptionUpsold(tierPlatium)# ...# Successful upsell of middle tier - annual periodXenon().subscriptionUpsold(annualGold)subscriptionUpsellDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenontierGold=\"Gold Monthly\"tierPlatium=\"Platium\"annualGold=\"Gold Annual\"method=\"Stripe\"#optionalprice='$25'# optionalterm=\"30d\"#optional# Assume already subscribed to Silver# Rejected upsell of the middle tierXenon().subscriptionUpsellDeclined(tierGold)# ...# Rejected upsell of the top tierXenon().subscriptionUpsellDeclined(tierPlatium)# ...# Rejected upsell of middle tier - annual periodXenon().subscriptionUpsellDeclined(annualGold,method)# Rejected upsell of middle tier - annual period with Stripe for $25 for termXenon().subscriptionUpsellDeclined(annualGold,method,price,term)subscriptionDownsell():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenontierGold=\"Gold Monthly\"tierPlatium=\"Platium\"annualGold=\"Gold Annual\"method=\"Stripe\"#optionalprice='$15'#optionalterm=\"30d\"#optional# Assume already subscribed to Platium# Downsell to GoldXenon().subscriptionDownsell(tierGold)# ...# Downsell to Gold annual with methodXenon().subscriptionDownsell(annualGold,method)# Downsell to Gold - annual period with Stripe for $15 for termXenon().subscriptionDownsell(annualGold,method,price,term)Ad ClickedUse this call to track when customers click on an Advertisement.\nYou can add a specifier string to the call to differentiate as follows:adClicked()fromxenon_view_sdkimportXenonprovider=\"AdMob\"id=\"ID-1234\"# optionalprice=\"$0.25\"# optional# Click an Ad from AdMobXenon().adClicked(provider)# ...# Click an Ad from AdMob identfied by ID-1234Xenon().adClicked(provider,id)# ...# Click an Ad from AdMob identfied by ID-1234 with priceXenon().adClicked(provider,id,price)adIgnored()fromxenon_view_sdkimportXenonprovider=\"AdMob\"id=\"ID-1234\"# optionalprice=\"$0.25\"# optional# No action on an Ad from AdMobXenon().adIgnored(provider)# ...# No action on an Ad from AdMob identfied by ID-1234Xenon().adIgnored(provider,id)# ...# No action on an Ad from AdMob identfied by ID-1234 with priceXenon().adIgnored(provider,id,price)ReferralUse this call to track when customers refer someone to your offering.\nYou can add a specifier string to the call to differentiate as follows:referral()fromxenon_view_sdkimportXenonkind=\"Share\"detail=\"Review\"#optional# Successful referral by sharing a reviewXenon().referral(kind,detail)# -OR-Xenon().referral(kind)referralDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonkind=\"Share\"detail=\"Review\"#optional# Customer declined referralXenon().referralDeclined(kind,detail)# -OR-Xenon().referralDeclined(kind)back to topEcommerce Related OutcomesLead AttributedUse this call to track Lead Attribution (Google Ads, Facebook Ads, etc.)\nYou can add a source and identifier string to the call to differentiate as follows:leadAttributed()fromxenon_view_sdkimportXenonsource='Google Ad'identifier='Search'# Successful Lead Attributed to Google AdXenon().leadAttributed(source)#...# Successful Lead Attributed to Google Search AdXenon().leadAttributed(source,identifier)Lead CaptureUse this call to track Lead Capture (emails, phone numbers, etc.)\nYou can add a specifier string to the call to differentiate as follows:leadCaptured()fromxenon_view_sdkimportXenonemailSpecified=\"Email\"phoneSpecified=\"Phone Number\"# Successful Lead Capture of an emailXenon().leadCaptured(emailSpecified)# ...# Successful Lead Capture of a phone numberXenon().leadCaptured(phoneSpecified)leadCaptureDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonemailSpecified=\"Email\"phoneSpecified=\"Phone Number\"# Unsuccessful Lead Capture of an emailXenon().leadCaptureDeclined(emailSpecified)# ...# Unsuccessful Lead Capture of a phone numberXenon().leadCaptureDeclined(phoneSpecified)Account SignupUse this call to track when customers signup for an account.\nYou can add a specifier string to the call to differentiate as follows:accountSignup()fromxenon_view_sdkimportXenonviaFacebook=\"Facebook\"viaGoogle=\"Facebook\"viaEmail=\"Email\"# Successful Account Signup with FacebookXenon().accountSignup(viaFacebook)# ...# Successful Account Signup with GoogleXenon().accountSignup(viaGoogle)# ...# Successful Account Signup with an EmailXenon().accountSignup(viaEmail)accountSignupDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonviaFacebook=\"Facebook\"viaGoogle=\"Facebook\"viaEmail=\"Email\"# Unsuccessful Account Signup with FacebookXenon().accountSignupDeclined(viaFacebook)# ...# Unsuccessful Account Signup with GoogleXenon().accountSignupDeclined(viaGoogle)# ...# Unsuccessful Account Signup with an EmailXenon().accountSignupDeclined(viaEmail)Add Product To CartUse this call to track when customers add a product to the cart.\nYou can add a specifier string to the call to differentiate as follows:productAddedToCart()fromxenon_view_sdkimportXenonlaptop=\"Dell XPS\"keyboard=\"Apple Magic Keyboard\"# Successful adds a laptop to the cartXenon().productAddedToCart(laptop)# ...# Successful adds a keyboard to the cartXenon().productAddedToCart(keyboard)productNotAddedToCart():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonlaptop=\"Dell XPS\"keyboard=\"Apple Magic Keyboard\"# Doesn't add a laptop to the cartXenon().productNotAddedToCart(laptop)# ...# Doesn't add a keyboard to the cartXenon().productNotAddedToCart(keyboard)Upsold Additional ProductsUse this call to track when you upsell additional product(s) to customers.\nYou can add a specifier string to the call to differentiate as follows:upsold()fromxenon_view_sdkimportXenonlaptop='Dell XPS'laptopValue='$1459'#optionalkeyboard='Apple Magic Keyboard'keyboardValue='$139'#optional# upsold a laptopXenon().upsold(laptop)# ...# upsold a keyboard with priceXenon().upsold(keyboard,keyboardValue)upsellDismissed():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonlaptop='Dell XPS'keyboard='Apple Magic Keyboard'keyboardValue='$139'#optional# Doesn't add a laptop during upsellXenon().upsellDismissed(laptop)# ...# Doesn't add a keyboard during upsellXenon().upsellDismissed(keyboard,keyboardValue)Customer Checks OutUse this call to track when your Customer is checking out.checkedOut()fromxenon_view_sdkimportXenon# Successful CheckoutXenon().checkedOut()checkoutCanceled()fromxenon_view_sdkimportXenon# Customer cancels check out.Xenon().checkoutCanceled()productRemoved()fromxenon_view_sdkimportXenonlaptop=\"Dell XPS\"keyboard=\"Apple Magic Keyboard\"# Removes a laptop during checkoutXenon().productRemoved(laptop)# ...# Removes a keyboard during checkoutXenon().productRemoved(keyboard)Customer Completes PurchaseUse this call to track when your Customer completes a purchase.purchased()fromxenon_view_sdkimportXenonmethod=\"Stripe\"price='$2011'# optional# Successful PurchaseXenon().purchased(method)# Successful Purchase for $2011Xenon().purchased(method,price)purchaseCanceled()fromxenon_view_sdkimportXenonmethod=\"Stripe\"#optionalprice='$2011'# optional# Customer cancels the purchase.Xenon().purchaseCanceled()# -OR-Xenon().purchaseCanceled(method)# -OR-Xenon().purchaseCanceled(method,price)Purchase ShippingUse this call to track when your Customer receives a purchase.promiseFulfilled()fromxenon_view_sdkimportXenon# Successfully Delivered PurchaseXenon().promiseFulfilled()promiseUnfulfilled(()fromxenon_view_sdkimportXenon# Problem Occurs During Shipping And No DeliveryXenon().promiseUnfulfilled()Customer Keeps or Returns ProductUse this call to track if your Customer keeps the product.\nYou can add a specifier string to the call to differentiate as follows:productKept()fromxenon_view_sdkimportXenonlaptop=\"Dell XPS\"keyboard=\"Apple Magic Keyboard\"# Customer keeps a laptopXenon().productKept(laptop)# ...# Customer keeps a keyboardXenon().productKept(keyboard)productReturned():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonlaptop=\"Dell XPS\"keyboard=\"Apple Magic Keyboard\"# Customer returns a laptopXenon().productReturned(laptop)# ...# Customer returns a keyboardXenon().productReturned(keyboard)ReferralsUse this call to track when customers refer someone to your offering.\nYou can add a specifier string to the call to differentiate as follows:referral()fromxenon_view_sdkimportXenonkind=\"Share Product\"detail=\"Dell XPS\"# Successful referral by sharing a laptopXenon().referral(kind,detail)referralDeclined():memo: Note: You want to be consistent between success and failure and match the specifiersfromxenon_view_sdkimportXenonkind=\"Share Product\"detail=\"Dell XPS\"# Customer declined referralXenon().referralDeclined(kind,detail)back to topCustomer Journey MilestonesAs a customer interacts with your brand (via Advertisements, Marketing Website, Product/Service, etc.), they journey through a hierarchy of interactions.\nAt the top level are business outcomes. In between Outcomes, they may achieve other milestones, such as interacting with content and features.\nProper instrumentation of these milestones can establish correlation and predictability of business outcomes.As of right now, Customer Journey Milestones break down into two categories:Feature UsageContent InteractionFeature UsageFeatures are your product/application/service's traits or attributes that deliver value to your customers.\nThey differentiate your offering in the market. Typically, they are made up of and implemented by functions.featureAttempted()Use this function to indicate the start of feature usage.fromxenon_view_sdkimportXenonname=\"Scale Recipe\"detail=\"x2\"# optional# Customer initiated using a featureXenon().featureAttempted(name,detail)# -OR-Xenon().featureAttempted(name)featureCompleted()Use this function to indicate the successful completion of the feature.fromxenon_view_sdkimportXenonname=\"Scale Recipe\"detail=\"x2\"# optional# ...# Customer used a featureXenon().featureCompleted(name)# -OR-# Customer initiated using a featureXenon().featureAttempted(name,detail)# ...# feature code/function calls# ...# feature completes successfullyXenon().featureCompleted(name,detail)# -OR-Xenon().featureCompleted(name)featureFailed()Use this function to indicate the unsuccessful completion of a feature being used (often in the exception handler).fromxenon_view_sdkimportXenonname=\"Scale Recipe\"detail=\"x2\"# optional# Customer initiated using a featureXenon().featureAttempted(name,detail)try:# feature code that could failexceptExceptionase:# feature completes unsuccessfullyXenon().featureFailed(name,detail)# -OR-Xenon().featureFailed(name)back to topContent InteractionContent is created assets/resources for your site/service/product.\nIt can be static or dynamic. You will want to mark content that contributes to your Customer's experience or buying decision.\nTypical examples:BlogBlog postsVideo assetsCommentsReviewsHowTo GuidesCharts/GraphsProduct/Service DescriptionsSurveysInformational productcontentViewed()Use this function to indicate a view of specific content.fromxenon_view_sdkimportXenoncontentType=\"Blog Post\"identifier=\"how-to-install-xenon-view\"# optional# Customer view a blog postXenon().contentViewed(contentType,identifier)# -OR-Xenon().contentViewed(contentType)contentEdited()Use this function to indicate the editing of specific content.fromxenon_view_sdkimportXenoncontentType=\"Review\"identifier=\"Dell XPS\"# optionaldetail=\"Rewrote\"# optional# Customer edited their review about a laptopXenon().contentEdited(contentType,identifier,detail)# -OR-Xenon().contentEdited(contentType,identifier)# -OR-Xenon().contentEdited(contentType)contentCreated()Use this function to indicate the creation of specific content.fromxenon_view_sdkimportXenoncontentType=\"Blog Comment\"identifier=\"how-to-install-xenon-view\"# optional# Customer wrote a comment on a blog postXenon().contentCreated(contentType,identifier)# -OR-Xenon().contentCreated(contentType)contentDeleted()Use this function to indicate the deletion of specific content.fromxenon_view_sdkimportXenoncontentType=\"Blog Comment\"identifier=\"how-to-install-xenon-view\"# optional# Customer deleted their comment on a blog postXenon().contentDeleted(contentType,identifier)# -OR-Xenon().contentDeleted(contentType)contentArchived()Use this function to indicate archiving specific content.fromxenon_view_sdkimportXenoncontentType=\"Blog Comment\"identifier=\"how-to-install-xenon-view\"# optional# Customer archived their comment on a blog postXenon().contentArchived(contentType,identifier)# -OR-Xenon().contentArchived(contentType)contentRequested()Use this function to indicate the request for specific content.fromxenon_view_sdkimportXenoncontentType=\"Info Product\"identifier=\"how-to-efficiently-use-google-ads\"# optional# Customer requested some contentXenon().contentRequested(contentType,identifier)# -OR-Xenon().contentRequested(contentType)contentSearched()Use this function to indicate when a user searches.fromxenon_view_sdkimportXenoncontentType=\"Info Product\"# Customer searched for some contentXenon().contentSearched(contentType)back to topCommit PointsBusiness Outcomes and Customer Journey Milestones are tracked locally in memory until you commit them to the Xenon View system.\nAfter you have created (by either calling a milestone or outcome) a customer journey, you can commit it to Xenon View for analysis as follows:commit()fromxenon_view_sdkimportXenon# you can commit a journey to Xenon ViewXenon().commit()This call commits a customer journey to Xenon View for analysis.back to topHeartbeatsBusiness Outcomes and Customer Journey Milestones are tracked locally in memory until you commit them to the Xenon View system.\nYou can use the heartbeat call if you want to commit in batch.The heartbeat call will update a last-seen metric for customer journeys that have yet to arrive at Business Outcome.\nThe last-seen metric is useful when analyzing stalled Customer Journeys.Usage is as follows:heartbeat()fromxenon_view_sdkimportXenon# you can heartbeat to Xenon ViewXenon().heartbeat()This call commits any uncommitted journeys to Xenon View for analysis and updates the last accessed time.:memo: Note:Optionally, you can set abandonment timers via the watchdog parameter. This will allow you to indicate the failed to\nreach outcomes if no activity is recorded before a specified timeout.Usage is as follows:heartbeat(watchdog={params})fromxenon_view_sdkimportXenon# you can set up an abandonment watchdogXenon().heartbeat(watchdog={'if_abandoned':{'superOutcome':'Checkout','outcome':'abandoned','result':'fail'},'expires_in_seconds':600,#10-mins})# you can remove an active watchdogXenon().heartbeat(watchdog={'remove':True})back to topPlatformingAfter you have initialized Xenon View, you can optionally specify platform details such as:Operating System NameOperating System versionDevice model (Pixel, Docker Container, Linux VM, Dell Server, etc.)A software version of your application.platform()fromxenon_view_sdkimportXenonsoftwareVersion=\"5.1.5\"deviceModel=\"Pixel 4 XL\"operatingSystemVersion=\"12.0\"operatingSystemName=\"Android\"# you can add platform details to outcomesXenon().platform(softwareVersion,deviceModel,operatingSystemName,operatingSystemVersion)This adds platform details for each outcome (Saas/Ecom). Typically, this would be set once at initialization:fromxenon_view_sdkimportXenonXenon().init('<API KEY>')softwareVersion=\"5.1.5\"deviceModel=\"Pixel 4 XL\"operatingSystemVersion=\"12.0\"operatingSystemName=\"Android\"Xenon().platform(softwareVersion,deviceModel,operatingSystemName,operatingSystemVersion)back to topExperimentsAfter you have initialized Xenon View, you can optionally name variants of customer journeys.\nNamed variants facilitate running experiments such as A/B or split testing.:memo: Note: You are not limited to just 2 (A or B); there can be many. Additionally, you can have multiple variant names.variant()fromxenon_view_sdkimportXenonvariant=\"subscription-variant-A\"# you can add variant details to outcomesXenon().variant([variant])This adds variant names to each outcome while the variant in play (Saas/Ecom).\nTypically, you would name a variant once you know the active experiment for this Customer:fromxenon_view_sdkimportXenonXenon().init('<API KEY>')experimentName=getExperiment()Xenon().variant([experimentName])resetVariants()fromxenon_view_sdkimportXenon# you can clear all variant names with the resetVariants methodXenon().resetVariants()back to topCustomer Journey GroupingXenon View supports both anonymous and grouped (known) journeys.All the customer journeys (milestones and outcomes) are anonymous by default.\nFor example, if a Customer interacts with your brand in the following way:Starts on your marketing website.Downloads and uses an app.Uses a feature requiring an API call.Each of those journeys will be unconnected and not grouped.To associate those journeys with each other, you can usedeanonymize(). Deanonymizing will allow for a deeper analysis of a particular user.Deanonymizing is optional. Basic matching of the customer journey with outcomes is valuable by itself. Deanonymizing will add increased insight as it connects Customer Journeys across devices.Usage is as follows:deanonymize()fromxenon_view_sdkimportXenon# you can deanonymize before or after you have committed the journey (in this case, after):person={'name':'Python Testing','email':'pytest@example.com'}Xenon().deanonymize(person)# you can also deanonymize with a user ID:person={'UUID':\"<some unique ID>\"}Xenon().deanonymize(person)This call deanonymizes every journey committed to a particular user.:memo: Note:With journeys that span multiple platforms (e.g., Website->Android->API backend), you can group the Customer Journeys by deanonymizing each.back to topOther OperationsThere are various other operations that you might find helpful:Error handlingIn the event of an API error, an exception occurs with the response from the API asRequests response object::memo: Note:The default handling of this situation will restore the journey (appending newly added pageViews, events, etc.) for future committing. If you want to do something special, you can do so like this:fromxenon_view_sdkimportXenon,ApiExceptiontry:Xenon().commit()exceptApiExceptionase:print(str(e.apiResponse().status_code))Custom MilestonesYou can add custom milestones if you need more than the current Customer Journey Milestones.milestone()fromxenon_view_sdkimportXenon# you can add a custom milestone to the customer journeycategory=\"Function\"operation=\"Called\"name=\"Query Database\"detail=\"User Lookup\"Xenon().milestone(category,operation,name,detail)This call adds a custom milestone to the customer journey.Journey IDsEach Customer Journey has an ID akin to a session.\nAfter committing an Outcome, the ID remains the same to link all the Journeys.\nIf you have a previous Customer Journey in progress and would like to append to that, you can get/set the ID.:memo: Note:For Python, the Xenon object is a singleton. Subsequent Outcomes for multiple threads or async operations will reuse the Journey ID.After you have initialized the Xenon singleton, you can:Use the default UUIDSet the Customer Journey (Session) IDRegenerate a new UUIDRetrieve the Customer Journey (Session) IDid()fromxenon_view_sdkimportXenon# by default has Journey IDprint(str(Xenon().id()))# you can also set the idtestId='<some random uuid>'Xenon().id(testId)assertXenon().id()==testId# Lastly, you can generate a new Journey ID (useful for serialized async operations that are for different customers)Xenon().newId()back to topLicenseApache Version 2.0SeeLICENSEback to top"} +{"package": "xenopict", "pacakge-description": "XenopictXenopict is a package for generating publication quality 2D depictions of small molecules,\nwith special attention to \"shading\" molecules with atom or bond level properties. This package\nrelies on RDKit generation an initial SVG depiction of the input molecule.Read thedocumentationfor more information.This package is in beta. It's API is still subject to substantial revisions. It is in active use by our laboratory,\nand several bugs and features are added frequently."} +{"package": "xenoponics", "pacakge-description": "XenoponicsA repository for scripts and other tools to run hydroponics systems in a smarter way.Configured Scriptscontrol.pySummaryThe management script for our current Raspberry Pi setup.\nUsesTyper,python-requests, and Python stdlib to perform POST requests toXenoAPI, which is a GraphQL API that handles database interactions.RequirementsPython 3.8+SetupImplicit purchase a Raspberry Pi and sensors and set it up goes hereMake a virtualenvpython3-mvenv.xenovenvActivate the virtualenvsource./xenovenv/bin/activateInstallpip3installxenoponicsUsageSeexenoponics --helpfor usage information.\"I've been a plant lady since birth.\" -McCDouble21"} +{"package": "xenopt", "pacakge-description": "XenoPTGarnet two-pyroxene thermobarometry package.https://pypi.org/project/xenopt/"} +{"package": "xenopy", "pacakge-description": "XenoPyXenoPyis a python library that builds uponxeno-canto API 2.0.InstallInstall frompip.pipinstallxenopyCheckout thebirdDatabranch to implement XenoPy from source. (ps: birdData is the former name of XenoPy)Usage SnippetYou can directly search for bird data for a specific species. For instance, we retrieve data forAfrican Silverbillwhom'squalitybetter thanCsince2020-01-01.fromxenopyimportQueryq=Query(name=\"African silverbill\",q_gt=\"C\",since=\"2020-01-01\")Retrieve Metafiles# retrieve metadatametafiles=q.retrieve_meta(verbose=True)Retrieve Recordings# retrieve recordingsq.retrieve_recordings(multiprocess=True,nproc=10,attempts=10,outdir=\"datasets/\")The retrieved recordings will be located indatasets/, organized by bird species names.The default downloading mode is single-threaded.multiprocessflag controls the usage of multiple downloading processes.nprocis only applicable when themultiprocessflag is on. The saving directory can be specified atoutDir.Two files will be generated while runningretrieve_recordings,kill_multiprocess.sh, andfailed.txt. To interrupt multiprocess data retrieval, one can runbash kill_multiprocess.shin the terminal. 'failed.txt' contains recordings that failed the retrieval, if any. The two files will be removed automatically removed after downloading finishes.failed.txtwill preserve if not empty so that you can check the failed recordings out.Define aQueryAs you can tell from theUsage Snippet, defining a query is the most important step in communicating with the API. We determined the following interface to form a query based on the xeno-cantosearch tips.name: Species Name. Specify the name of bird you intend to retrieve data from. Both English names and Latin names are acceptable.\ngen: Genus. Genus is part of a species' latin name, so it is searched by default when performing a basic search (as mentioned above).\nssp: subspecies\nrec: recordist. Search for all recordings from a particular recordist.\ncnt: country. Search for all recordings from a particular country.\nloc: location. Search for all recordings from a specific location.\nrmk: remarks. Many recordists leave remarks about the recording,and this field can be searched using the rmk tag. For example, rmk:playback will return a list of recordings for which the recordist left a comment about the use of playback. This field accepts a 'matches' operator.\nlat: latitude.\nlon: longtitude\nbox: search for recordings that occur within a given rectangle. The general format of the box tag is as follows: box:LAT_MIN,LON_MIN,LAT_MAX,LON_MAX. Note that there must not be any spaces between the coordinates.\nalso: To search for recordings that have a given species in the background.\ntype: Search for recordings of a particular sound type, e.g., type='song'\nnr: number. To search for a known recording number, use the nr tag: for example nr:76967. You can also search for a range of numbers as nr:88888-88890.\nlc: license.\nq: quality ratings. \nq_lt: quality ratings less than\nq_gt: quality ratings better than\n Usage Examples:\n Recordings are rated by quality. Quality ratings range from A (highest quality) to E (lowest quality). To search for recordings that match a certain quality rating, use the q, q_lt, and q_gt tags. For example:-q:A will return recordings with a quality rating of A.-q:0 search explicitly for unrated recordings-q_lt:C will return recordings with a quality rating of D or E.-q_gt:C will return recordings with a quality rating of B or A.\nlen: recording length control parameter.\nlen_lt: recording length less than\nlen_gt: recording length greater than\n Usage Examples:\n len:10 will return recordings with a duration of 10 seconds (with a margin of 1%, so actually between 9.9 and 10.1 seconds)\n len:10-15 will return recordings lasting between 10 and 15 seconds.\n len_lt:30 will return recordings half a minute or shorter in length.\n len_gt:120 will return recordings longer than two minutes in length.\narea: continents. Valid values for this tag: africa, america, asia, australia, europe.\nsince: \n Usage Examples:-since=3, since the past three days-since=YYYY-MM-DD, since the particular date\nyear: year\nmonth: month. year and month tags allow you to search for recordings that were recorded on a certain date.Update Historyv0.0.4Support Query by birdname.Cut inessential processes in query traffic.Optimized query assignment strategy in recording retrieval.todocreate query object for single species, containing features likeretrieve metedataretrieve bird songsadd multiprocessing downloading featureOpen SourceThe first generation ofxenocantopackageis hard to use also inefficient. Thus I wrapped the2.0 APIversion in a more straightforward and efficient interface.\nFeel free to file an issue had you encountered any bugs, or prompt a PR toXenoPyto join me in maintenance and optimization."} +{"package": "xenos", "pacakge-description": "No description available on PyPI."} +{"package": "xenosimager", "pacakge-description": "Date:2012-03-08 16:22Tags:Openstack, Nova Compute, Nova, Glance, Imaging, XenServerCategory:*nixAuthor:Kevin CarterCreate an Image from within an InstanceGeneral OverviewThis application has been created to work with Openstack if using the XenServer Hypervisor. At this time the code base supports Openstack as a whole, however the application has only been tested on Rackspace Cloud Servers.Overview:XenOsImagerwill create an image from information obtained from within the instance. The application will look at the \u201cxenstore\u201d data to determine the UUID of the instance, and the region. The user is only required to input their OpenStack API Credentials into a simple configuration file. These credentials are only used to make API calls for image creation.Simply the application will allow you to create images of instances as a simple automation task; CRON job, on demand, or anythine else you can think of.Prerequisites :Python => 2.6 but < 3.0python-setuptoolsInstallation is simple :from Python.org, IE \u201cpip\u201dpipinstallxenosimagerfrom Github, which is Trunk.gitclonegit://github.com/cloudnull/transporter.gitcdtransporterpythonsetup.pyinstallSetup is Simple too edit the file \u201c/etc/xenosimager/config.cfg\u201d :vi/etc/xenosimager/config.cfgIn the previous file, add your credentials. If you feel so inclined, you can also add your mail relay information and the system will send you a message when the images are created or if there are overall issues.Available Options in the config file or on the CLI :Required Variables from CLIsystem-config| Where your config file existsimage-name| the name of the imageOpenStack Variablesos_user| YOUos_apikey| SuperSecretInformationos_auth_url| Authentication URLos_rax_auth| A-LOCATIONos_verbose| True or Falseos_password| SuperSecretInformationos_tenant| UsernameGenerallyos_region| WhereIsThisInstanceos_version| v2.0Mail Variablesmail-main-contact| WhoReadsEmailmail_debug| True or Falsemail_url| AURLmail_user| Usernamemail_password| Passwordmail_cert| /location/certmail_key| KeyForCertmail_tls| True or Falsemail_port| Port NumberHow to use this toolApplication is simple to use. Simply follow this command and add your own custom name to the end.xenosimager--system-config/etc/xenosimager/config.cfg--image-name$NAME_OF_THE_IMAGELogs are created for all interaction of the imager, and can be found here :/var/log/xenosimager.logFor automated image create please have a look at the example.cron.txt file, which is where you can find cron job examples, but with little to no ingenuity I am sure you could figure out other methods for automated command execution.Get SocialDownloadable onPyPiDownloadable onGitHubSee MyGitHub Issues Pagefor any and all Issues or Feature requestsSeehttps://github.com/cloudnull/transporter/issuesfor Issues or Feature requestsLicenseCopyright [2013] [Kevin Carter]Licensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xenosite", "pacakge-description": "This is the core package for XenoSite.This package primarily serves as a namespace package for the xenosite family of packages, while also including an extensible command line interface. All useful functionality requires installing one of the XenoSite subpackages."} +{"package": "xenosite-fragment", "pacakge-description": "Xenosite FragmentA library for processing molecule fragments.Install from pypi:pip install xenosite-fragmentCreate a fragment from a SMILES or a fragment SMILES string:>>> str(Fragment(\"CCCC\")) # Valid smiles\n'C-C-C-C'\n\n>>> str(Fragment(\"ccCC\")) # not a valid SMILES\n'c:c-C-C'Optionally, create a fragment of a molecule from a string and (optionally) a list of nodes\nin the fragment.>>> F = Fragment(\"CCCCCCOc1ccccc1\", [0,1,2,3,4,5])\n>>> str(F) # hexane\n'C-C-C-C-C-C'If IDs are provided, they MUST select a connected fragment.>>> F = Fragment(\"CCCCCCOc1ccccc1\", [0,10]) \nTraceback (most recent call last):\n ...\nValueError: Multiple components in graph are not allowed.Get the canonical representation of a fragment:>>> Fragment(\"O-C\").canonical().string\n'C-O'\n>>> Fragment(\"OC\").canonical().string\n'C-O'\n>>> Fragment(\"CO\").canonical().string\n'C-O'Get the reordering of nodes used to create the canonical\nstring representation. If remap=True, then the ID are remapped to the input\nrepresentation used to initalize the Fragment.>>> Fragment(\"COC\", [1,2]).canonical(remap=True).reordering\n[2, 1]\n>>> Fragment(\"COC\", [1,2]).canonical().reordering\n[1, 0]Match fragment to a molecule. By default, the ID\ncorrespond with fragment IDs. If remap=True, the ID\ncorresponds to the input representation when the Fragment\nwas initialized.>>> smiles = \"CCCC1CCOCN1\"\n>>> F = Fragment(\"CCCCCC\") # hexane as a string\n>>> list(F.matches(smiles)) # smiles string (least efficient)\n[(0, 1, 2, 3, 4, 5)]\n\n>>> import rdkit\n>>> mol = rdkit.Chem.MolFromSmiles(smiles)\n>>> list(F.matches(mol)) # RDKit mol\n[(0, 1, 2, 3, 4, 5)]\n\n>>> mol_graph = Graph.from_molecule(mol)\n>>> list(F.matches(mol, mol_graph)) # RDKit mol and Graph (most efficient)\n[(0, 1, 2, 3, 4, 5)]Matches ensure that the fragment string of matches is the same as\nthe fragment. This is different than standards SMARTS matching,\nandpreventsrings from matching unclosed ring patterns:>>> str(Fragment(\"C1CCCCC1\")) # cyclohexane\n'C1-C-C-C-C-C-1'\n\n>>> assert(str(Fragment(\"C1CCCCC1\")) != str(F)) # cyclohexane is not hexane\n>>> list(F.matches(\"C1CCCCC1\")) # Unlike SMARTS, no match!\n[]Efficiently create multiple fragments by reusing a\nprecomputed graph:>>> import rdkit\n>>>\n>>> mol = rdkit.Chem.MolFromSmiles(\"c1ccccc1OCCC\")\n>>> mol_graph = Graph.from_molecule(mol)\n>>>\n>>> f1 = Fragment(mol_graph, [0])\n>>> f2 = Fragment(mol_graph, [6,5,4])Find matches to fragments:>>> list(f1.matches(mol))\n[(0,), (1,), (2,), (3,), (4,), (5,)]\n\n>>> list(f2.matches(mol))\n[(6, 5, 4), (6, 5, 0)]Fragments know how to report if they are canonically the same as each other or strings.>>> Fragment(\"CCO\") == Fragment(\"OCC\")\nTrue\n>>> Fragment(\"CCO\") == \"C-C-O\"\nTrueNote, however, that strings are not converted to canonical form. Therefore,>>> Fragment(\"CCO\") == \"CCO\"\nFalseEnumerate and compute statistics on all the subgraphs in a molecule:>>> from xenosite.fragment.net import SubGraphFragmentNetwork\n>>> N = SubGraphFragmentNetwork(\"CC1COC1\")\n>>> fragments = N.to_pandas()\n>>> list(fragments.index)\n['C-C', 'C', 'C-O-C', 'C-O', 'O', 'C-C1-C-O-C-1', 'C1-C-O-C-1', 'C-C-C-O', 'C-C(-C)-C', 'C-C-O', 'C-C-C']\n>>> fragments[\"size\"].to_numpy()\narray([2, 1, 3, 2, 1, 5, 4, 4, 4, 3, 3])Better fragments can be enumerated by collapsing all atoms in a ring into a single node\nduring subgraph enumeration.>>> from xenosite.fragment.net import RingFragmentNetwork\n>>> N = RingFragmentNetwork(\"CC1COC1\")\n>>> fragments = N.to_pandas()\n>>> list(fragments.index)\n['C-C1-C-O-C-1', 'C', 'C1-C-O-C-1']\n>>> fragments[\"size\"].to_numpy()\narray([5, 1, 4])"} +{"package": "xenoslib", "pacakge-description": "No description available on PyPI."} +{"package": "xenqore-project", "pacakge-description": "No description available on PyPI."} +{"package": "xenqu-api", "pacakge-description": "No description available on PyPI."} +{"package": "xenrtapi", "pacakge-description": "No description available on PyPI."} +{"package": "xensispy", "pacakge-description": "XensisPY is a fork of FortnitePY, but working :)\nIf Terbau seeing this, please let me know if you do not want to keep this, so I will remove it."} +{"package": "xent", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xenterval", "pacakge-description": "xentervalXenharmonic theory utilities and more.Usageimport xenterval"} +{"package": "xentica", "pacakge-description": "GPU-Accelerated Engine For Multi-Dimensional Cellular AutomataXenticais the core framework for theArtipixoids!project,\nhelping us to build GPU-accelerated models for multi-dimensional\ncellular automata. Given pure Python definitions, Xentica generates\ncorresponding C code and runs it on GPU hardware.For more information, please refer to the officialXentica Documentation.Another point of interest isThe Conceptdocument, explaining the\nmain goals of the project and giving formal definitions to all features\nof the Core Framework.The project is Open Source,contributionsare welcome."} +{"package": "xenum", "pacakge-description": "Xenum offers a simple alternative to Python 3 enums that\u2019s\nespecially useful for (de)serialization. When you would like\nto model your enum values so that they survive jumps to and\nfrom JSON, databases, and other sources cleanly as strings,\nXenum will allow you to do so extremely easily.InstallationInstallation is simple. With python3-pip, do the following:$ sudo pip install -e .Or, to install the latest version available on PyPI:$ sudo pip install xenumUsageJust create a basic class with attributes and annotate it with the@xenumattribute. This will convert all of the class attributes\ninto Xenum instances and allow you to easily convert them to strings\nviastr(MyEnum.A)and from strings viaMyEnum.by_name(\"MyEnum.A\").Examplefrom xenum import xenum, ctor\n\n@xenum\nclass Actions:\n INSERT = ctor('insert')\n UPDATE = ctor('update')\n DELETE = ctor('delete')\n\n def __init__(self, name):\n self.name = name\n\nassert Actions.INSERT == Actions.by_name('Actions.INSERT')\nassert Actions.INSERT().name == 'insert'Checkouttest.pyin the git repo for more usage examples.Change LogVersion 1.4: September 5th, 2016Add \u2018xenum.sref()\u2019 allowing enum values to be instances of the\n@xenum annotated class, whos*argsis prepended with the\nXenum instance itself for self-reference.Version 1.3: September 4th, 2016Add \u2018xenum.ctor()\u2019 allowing enum values to be instances of the\n@xenum annotated class.Made Xenum instances callable, returning the enum\u2019s internal value.Version 1.2: September 4th, 2016Add \u2018values()\u2019 method to @xenum annotated classes for fetching\nan ordered sequence of the Xenum entities created.Version 1.1: August 31st, 2016Made Xenum instances hashable, removed value() as a function."} +{"package": "xenv", "pacakge-description": "xenv consists in classes and functions to manipulate the environment in a\nplatform independent way.In particular it allows to describe the changest to the environment in an XML\nfile that can be used by the scriptxenv(similar to the Unixenvcommand) to run a command in the modified environment."} +{"package": "xenvman", "pacakge-description": "Python client for xenvmanThis is a Python client library forxenvman.InstallationInstalling is a simple as running:pipinstallxenvmanUsageThe very first thing to do is to create a client:importxenvmancl=xenvman.Client()ifaddressargument is not provided, the defaulthttp://localhost:9876will be used. Also if shell environment variableXENV_API_SERVERis set,\nit will be used instead.Once you have a client, you can create environment:env=cl.new_env(xenvman.InputEnv(\"python-test\",description=\"Python test!\",templates=[xenvman.Tpl(\"db/mongo\")],))And that's it! Oncenew_env()returns, you have an environment which you can\nstart using in your integration tests.cont=env.get_container(\"db/mongo\",0,\"mongo\")# Get the full mongo url with exposed portmongo_url=\"{}:{}\".format(env.external_address(),cont.ports[\"27017\"])Don't forget to terminate your env after you're done:env.terminate()"} +{"package": "xenzen", "pacakge-description": "A Django UI for managingXenServerin the simplest possible way.Getting startedTo install XenZen run:$ git clone https://github.com/praekeltfoundation/xenzen.git\n$ cd xenzen/\n$ virtualenv ve\n$ . ./ve/bin/activate\n$ pip install -e .To start a development server listening on127.0.0.1:8000, with a SQLite database, run:$ export DJANGO_SETTINGS_MODULE=xenserver.testsettings\n$ django-admin syncdb\n$ django-admin collectstatic\n$ django-admin runserverTo configure XenZen further, create the filelocal_settings.pycontaining extra Django settings. For example, to configure a PostgreSQL database:DATABASES = {\n 'default': {\n 'ENGINE': 'django.db.backends.postgresql_psycopg2',\n 'NAME': 'xenzen',\n 'USER': 'postgres',\n 'PASSWORD': '',\n 'HOST': 'localhost',\n 'PORT': '',\n }\n}"} +{"package": "xeofs", "pacakge-description": "VersionsBuild & TestingCode QualityDocumentationCitation & LicensingUser EngagementOverviewxeofsis a dedicated Python package for dimensionality reduction in the realm of climate science, offering methods like PCA, known as EOF analysis within the field, and related variants. Seamlessly integrated withxarrayandDask, it's tailored for easy handling and scalable computation on large, multi-dimensional datasets, making advanced climate data analysis both accessible and efficient.Multi-Dimensional: Designed forxarrayobjects, it applies dimensionality reduction to multi-dimensional data while maintaining data labels.Dask-Integrated: Supports large datasets viaDaskxarray objectsExtensive Methods: Offers various dimensionality reduction techniquesAdaptable Output: Provides output corresponding to the type of input, whether single or list ofxr.DataArrayorxr.DatasetMissing Values: HandlesNaNvalues within the dataBootstrapping: Comes with a user-friendly interface for model evaluation using bootstrappingEfficient: Ensures computational efficiency, particularly with large datasets through randomized SVDModular: Allows users to implement and incorporate new dimensionality reduction methodsInstallationTo install the package, use either of the following commands:condainstall-cconda-forgexeofsorpipinstallxeofsQuickstartIn order to get started withxeofs, follow these simple steps:Import the package>>>importxarrayasxr# for example data only>>>importxeofsasxeLoad example data>>>t2m=xr.tutorial.open_dataset(\"air_temperature\")>>>t2m_west=t2m.isel(lon=slice(None,20))>>>t2m_east=t2m.isel(lon=slice(21,None))EOF analysisInitiate and fit the EOF/PCA model to the data>>>eof=xe.models.EOF(n_modes=10)>>>eof.fit(t2m,dim=\"time\")# doctest: +ELLIPSIS<xeofs.models.eof.EOFobjectat...>Now, you can access the model's EOF components and PC scores:>>>comps=eof.components()# EOFs (spatial patterns)>>>scores=eof.scores()# PCs (temporal patterns)Varimax-rotated EOF analysisInitiate and fit anEOFRotatorclass to the model to obtain a varimax-rotated EOF analysis>>>rotator=xe.models.EOFRotator(n_modes=3)>>>rotator.fit(eof)# doctest: +ELLIPSIS<xeofs.models.eof_rotator.EOFRotatorobjectat...>>>>rot_comps=rotator.components()# Rotated EOFs (spatial patterns)>>>rot_scores=rotator.scores()# Rotated PCs (temporal patterns)Maximum Covariance Analysis (MCA)>>>mca=xe.models.MCA(n_modes=10)>>>mca.fit(t2m_west,t2m_east,dim=\"time\")# doctest: +ELLIPSIS<xeofs.models.mca.MCAobjectat...>>>>comps1,comps2=mca.components()# Singular vectors (spatial patterns)>>>scores1,scores2=mca.scores()# Expansion coefficients (temporal patterns)Varimax-rotated MCA>>>rotator=xe.models.MCARotator(n_modes=10)>>>rotator.fit(mca)# doctest: +ELLIPSIS<xeofs.models.mca_rotator.MCARotatorobjectat...>>>>rot_comps=rotator.components()# Rotated singular vectors (spatial patterns)>>>rot_scores=rotator.scores()# Rotated expansion coefficients (temporal patterns)To further explore the capabilities ofxeofs, check out theavailable documentationandexamples.\nFor a full list of currently available methods, see theReference API.DocumentationFor a more comprehensive overview and usage examples, visit thedocumentation.ContributingContributions are highly welcomed and appreciated. If you're interested in improvingxeofsor fixing issues, please read ourContributing Guide.LicenseThis project is licensed under the terms of theMIT license.ContactFor questions or support, please open aGithub issue.CreditsRandomized PCA:scikit-learnEOF analysis: Python packageeofsby Andrew DawsonMCA: Python packagexMCAby YefeeCCA: Python packageCCA-Zooby James ChapmanROCK-PCA: Matlab implementation byDiego BuesoHow to cite?When usingxeofs, kindly remember to cite the original references of the methods employed in your work. Additionally, ifxeofsis proving useful in your research, we'd appreciate if you could acknowledge its use with the following citation:@article{rieger_xeofs_2024,author={Rieger, Niclas and Levang, Samuel J.},doi={10.21105/joss.06060},journal={Journal of Open Source Software},month=jan,number={93},pages={6060},title={{xeofs: Comprehensive EOF analysis in Python with xarray}},url={https://joss.theoj.org/papers/10.21105/joss.06060},volume={9},year={2024}}Contributors"} +{"package": "xeo-simple-calc", "pacakge-description": "xeo-simple-calcThis is my first python library. It is a simple calculator.How to useFirst, install the librarypipinstallxeo-simple-calcNext, import itfromxeosimplecalcimport*Then doc=Calc()Commandsc.add(num1,num2)Adds two numbers.c.subtract(num1,num2)Subtracts two numbers.c.multiply(num1,num2)Multiplies two numbers.c.divide(num1,num2)Divides two numbers. (returns a float)c.exponentiation(num,degree)Exponentiates a number to a certain degree. (Sorry the English is bad :-))c.square_root(num)Returns the square root of num. (returns a float)Change Log0.0.7 (07.07.2020)Moved all functions into a class."} +{"package": "xep", "pacakge-description": "No description available on PyPI."} +{"package": "xepmts", "pacakge-description": "A helper package for managing the PMT database used by the XENONnT Dark Matter Experiment.Basic Usageimportxepmts# If you are using a notebook:xepmts.notebook()# use v1 clientdb=xepmts.login(\"v1\",token='YOUR-API-TOKEN')# or the v2 clientdb=xepmts.login(\"v2\")# set the number of items to pull per pagedb.tpc.installs.items_per_page=25# get the next pagepage=db.tpc.installs.next_page()# iterate over pages:forpageindb.tpc.installs.pages():df=page.df# do something with data# select only top arraytop_array=db.tpc.installs.filter(array=\"top\")# iterate over top array pagesforpageintop_array.pages():df=page.df# do something with dataquery=dict(pmt_index=4)# get the first page of results for this query as a list of dictionariesdocs=db.tpc.installs.find(query,max_results=25,page_number=1)# same as find, but returns a dataframedf=db.tpc.installs.find_df(query)# insert documents into the databasedocs=[{\"pmt_index\":1,\"position_x\":0,\"position_y\":0}]db.tpc.installs.insert_documents(docs)Free software: MITDocumentation:https://xepmts.readthedocs.io/FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xepmts-endpoints", "pacakge-description": "Endpoint definitions for xepmts apiFree software: MITDocumentation:https://xepmts-endpoints.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xepmts-server", "pacakge-description": "Server for the xepmts apiFree software: MITDocumentation:https://xepmts-server.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xepor", "pacakge-description": "XeporXepor(pronounced/\u02c8z\u025bf\u0259/, zephyr) is a web routing framework for reverse engineers and security researchers.\nIt provides a Flask-like API for hackers to intercept and modify HTTP requests and/or HTTP responses in a human-friendly coding style.This project is meant to be used withmitmproxy. Users write scripts withxepor, and run the scriptinsidemitmproxy withmitmproxy -s your-script.py.If you want to step from PoC to production, from demo(e.g.http-reply-from-proxy.py,http-trailers.py,http-stream-modify.py) to something you could take out with your WiFi Pineapple, then Xepor is for you!FeaturesCode everything with@api.route(), just like Flask! Write everything inonescript and noif..elseany more.Handle multiple URL routes, even multiple hosts in oneInterceptedAPIinstance.For each route, you can choose to modify the requestbeforeconnecting to server (or even return a fake response without connection to upstream), or modify the responsebeforeforwarding to user.Blacklist mode or whitelist mode. Only allow URL endpoints defined in scripts to connect to upstream, blocking everything else (in specific domains) with HTTP 404. Suitable for transparent proxying.Human readable URL path definition and matching powered byparseHost remapping. define rules to redirect to genuine upstream from your fake hosts. Regex matching is supported.Best for SSL stripping and server-side license cracking!Plus all the bests frommitmproxy!ALLoperation modes (mitmproxy/mitmweb+regular/transparent/socks5/reverse:SPEC/upstream:SPEC) are fully supported.Use CaseEvil AP and phishing through MITM.Sniffing traffic from target device by iptables + transparent proxy, modify the payload with xepor on the fly.Cracking cloud-based software license. Seeexamples/krisp/as an example.Write a complicated web crawler in~100 lines of code. Seeexamples/polyv_scrapper/as an example.... and many more.SSL stripping is NOT provided by this project.InstallationpipinstallxeporQuick startTake the script fromexamples/httpbinas an example.mitmweb-sexample/httpbin/httpbin.pySet your Browser HTTP Proxy tohttp://127.0.0.1:8080, and access the web interface athttp://127.0.0.1:8081/.Send a GET request fromhttp://httpbin.org/#/HTTP_Methods/get_get, Then you could see the modification made by Xepor in mitmweb interface, browser dev tools or Wireshark.Thehttpbin.pydo two things.When user accesshttp://httpbin.org/get, inject a query string parameterpayload=evil_paraminside HTTP request.When user accesshttp://httpbin.org/basic-auth/xx/xx/(we just pretend we don't know the password), sniffAuthorizationheaders from HTTP requests and print the password to the attacker.Just what mitmproxy always does, but with code written inxeporway.# https://github.com/xepor/xepor-examples/tree/main/httpbin/httpbin.pyfrommitmproxy.httpimportHTTPFlowfromxeporimportInterceptedAPI,RouteTypeHOST_HTTPBIN=\"httpbin.org\"api=InterceptedAPI(HOST_HTTPBIN)@api.route(\"/get\")defchange_your_request(flow:HTTPFlow):\"\"\"Modify URL query param.Test at:http://httpbin.org/#/HTTP_Methods/get_get\"\"\"flow.request.query[\"payload\"]=\"evil_param\"@api.route(\"/basic-auth/{usr}/{pwd}\",rtype=RouteType.RESPONSE)defcapture_auth(flow:HTTPFlow,usr=None,pwd=None):\"\"\"Sniffing password.Test at:http://httpbin.org/#/Auth/get_basic_auth__user___passwd_\"\"\"print(f\"auth @{usr}+{pwd}:\",f\"Captured{'successful'ifflow.response.status_code<300else'unsuccessful'}login:\",flow.request.headers.get(\"Authorization\",\"\"),)addons=[api]"} +{"package": "xepto50", "pacakge-description": "No description available on PyPI."} +{"package": "xer2csv", "pacakge-description": "xer2csvThis package provides tools to convert XER files to CSV files.InstallationUse the package managerpipto installxer2csv.pip install xer2csvTestingtest.py file will parse all the \".xer\" files from theinput_dirlocation and will parse them to theoutput_dirdirectory. For each table from XER file a separate CSV file will be created (within a subdirectory with the name of the original XER file).\nusage:python test.py input_dir output_dirLicenseMIT"} +{"package": "xerial", "pacakge-description": "xerial - Terminal Based Serial ConsoleGithub: github.com/nickpetty/xerialTravis-CI: travis-ci.org/nickpetty/xerial.svg?branch=masterxerial Copyright (C) 2016 Nicholas Petty, GPL V3\nThis program comes with ABSOLUTELY NO WARRANTY.\nThis is free software, and you are welcome to redistribute it\nunder certain conditions; type `xerial -license' for details.Install:pip install xerialUsage:# Minimal Usage:\n> xerial -p COM1 # default parameters are 9600 8/N/1\n\n\n# Arguments:\n-p <port> # Connect to serial port.\n-a <b/p/s> # -a bytesize/parity/stopbits (default 8/N/1).\n # Parity options 'N','E','O','M','S'.\n-b <speed/baudrate> # 9600, 115200, etc.\n-CR # Carriage Return '\\r'.\n-LF # Linefeed (newline) '\\n'.\n-hw # Enable Hardware Handshake (rtscts).\n-ls # List available ports.\n-t <seconds> # Timeout (in seconds).\n-s <presetName> # Save flags to preset file. Must be the last flag. Will not connect with flag.\n # Usage: i.e., xerial -c /dev/tty.usbserial-A01293 -b 115200 -CR -s myPreset\n-l <presetName> # Load preset. Usage: xerial -l myPreset\n-lp # List presets in preset folder\n # Optional: '-lp <presetname>' Lists parameters for given preset.\n-h # This menu.\n-log # Log all terminal activity to file in current working directory.\n-license # Display LicenseNotes:Type>qat anytime to exit serial terminal.Please submit all pull requests to thedevelopmentbranch.Platforms:OSXLinuxWindows"} +{"package": "xerier", "pacakge-description": "No description available on PyPI."} +{"package": "xerlok_api", "pacakge-description": "No description available on PyPI."} +{"package": "xero-db-connector", "pacakge-description": "Xero Database ConnectorConnects Xero to a database to transfer information to and fro.InstallationThis project requiresPython 3+.Download this project and use it (copy it in your project, etc).Install it frompip.$ pip install xero-db-connectorUsageTo use this connector you'll need Xero credentials - specifically the keyfile and consumer key.Here's example usage.fromxero_db_connector.extractimportXeroExtractConnectorfromxero_db_connector.loadimportXeroLoadConnectorimportsqlite3importloggingimportosfromxeroimportXerofromxero.authimportPrivateCredentialsdefxero_connect():XERO_PRIVATE_KEYFILE=os.environ.get('XERO_PRIVATE_KEYFILE',None)XERO_CONSUMER_KEY=os.environ.get('XERO_CONSUMER_KEY',None)ifXERO_PRIVATE_KEYFILEisNone:raiseException('XERO_PRIVATE_KEYFILE is not set')ifXERO_CONSUMER_KEYisNone:raiseException('XERO_CONSUMER_KEY is not set')withopen(XERO_PRIVATE_KEYFILE)askeyfile:rsa_key=keyfile.read()credentials=PrivateCredentials(XERO_CONSUMER_KEY,rsa_key)# used to connect to xeroreturnXero(credentials)dbconn=sqlite3.connect('/tmp/xero.db',detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)xero=xero_connect()x=XeroExtractConnector(xero=xero,dbconn=dbconn)x.create_tables()y=XeroLoadConnector(xero=xero,dbconn=dbconn)y.create_tables()x.extract_contacts()x.extract_tracking_categories()x.extract_accounts()# do some transformations and populated invoice tables xero_load_invoices and xero_load_invoice_lineitemsforinvoice_idiny.load_invoices_generator():xero_invoice_id=y.get_xero_invoice_id(invoice_id=invoice_id)print(f'posted invoice{invoice_id}for which xero returned{xero_invoice_id}')ContributeTo contribute to this project follow the stepsFork and clone the repository.Runpip install -r requirements.txtSetup pylint precommit hookCreate a file.git/hooks/pre-commitCopy and paste the following lines in the file -#!/usr/bin/env bashgit-pylint-commit-hookMake necessary changesRun unit tests to ensure everything is fineUnit TestsTo run unit tests, run pytest in the following manner:python -m pytest test/unitYou should see something like this:================================================================== test session starts ==================================================================\nplatform darwin -- Python 3.7.4, pytest-5.2.2, py-1.8.0, pluggy-0.13.0\nrootdir: /Users/siva/src/xero-db-connector, inifile: pytest.ini\nplugins: mock-1.11.2, cov-2.8.1\ncollected 3 items \n\ntest/unit/test_mocks.py::test_xero_mock_setup PASSED [ 33%]\ntest/unit/test_mocks.py::test_dbconn_mock_setup PASSED [ 66%]\ntest/unit/test_mocks.py::test_xec_mock_setup PASSED [100%]\n\n=================================================================== 3 passed in 0.10s ===================================================================Integration TestsTo run unit tests, you will need a mechanism to connect to a real Xero account. Specifically, you'll need a keyfile and a consumer key, both of which can be obtained from the xero developer portal. Set the following environment variables before running the integration tests:export XERO_PRIVATE_KEYFILE=<path_to_keyfile>\nexport XERO_CONSUMER_KEY=<string>\n\npython -m pytest test/integrationCode coverageTo get code coverage report, run this command:python-mpytest--cov=xero_db_connector<snippedoutput>NameStmtsMissCover---------------------------------------------------xero_db_connector/__init__.py00100%xero_db_connector/extract.py1060100%xero_db_connector/load.py520100%---------------------------------------------------TOTAL1580100%To get an html report, run this command:python-mpytest--cov=xero_db_connector--cov-reporthtml:cov_htmlWe want to maintain code coverage of more than 95% for this project at all times.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details"} +{"package": "xero-python", "pacakge-description": "xero-pythonThe xero-python SDK makes it easy for developers to access Xero's APIs in their python code, and build robust applications and software using small business & general ledger accounting data.Table of ContentsAPI Client documentationSample ApplicationsXero Account RequirementsInstallationConfigurationAuthenticationCustom ConnectionsApp Store SubscriptionsAPI ClientsHelper MethodsUsage ExamplesSDK conventionsParticipating in Xero\u2019s developer communityContributingAPI Client documentationThis SDK supports full method coverage for the following Xero API sets:API SetDescriptionAccountingThe Accounting API exposes accounting functions of the main Xero application(most commonly used)AssetsThe Assets API exposes fixed asset related functions of the Xero Accounting applicationFilesThe Files API provides access to the files, folders, and the association of files within a Xero organisationProjectsXero Projects allows businesses to track time and costs on projects/jobs and report on profitabilityPayroll (AU)The (AU) Payroll API exposes payroll related functions of the payroll Xero applicationPayroll (UK)The (UK) Payroll API exposes payroll related functions of the payroll Xero applicationPayroll (NZ)The (NZ) Payroll API exposes payroll related functions of the payroll Xero applicationSample ApplicationsSample apps can get you started quickly with simple auth flows and advanced usage examples.Sample AppDescriptionScreenshotstarter-appBasic getting started code samplesfull-appComplete app with more complex examplescustom-connections-starterBasic app showing Custom Connections - a Xeropremium optionfor building M2M integrations to a single orgXero Account RequirementsCreate afree Xero user accountLogin to your Xero developerdashboardand create an API applicationCopy the credentials from your API app and store them using a secure ENV variable strategyDecide theneccesary scopesfor your app's functionalityInstallationTo install this SDK in your project:pip install xero-pythonConfiguration# -*- coding: utf-8 -*-importosfromfunctoolsimportwrapsfromioimportBytesIOfromlogging.configimportdictConfigfromflaskimportFlask,sessionfromflask_oauthlib.contrib.clientimportOAuth,OAuth2Applicationfromflask_sessionimportSessionfromxero_python.accountingimportAccountingApifromxero_python.assetsimportAssetApifromxero_python.projectimportProjectApifromxero_python.payrollauimportPayrollAuApifromxero_python.payrollukimportPayrollUkApifromxero_python.payrollnzimportPayrollNzApifromxero_python.fileimportFilesApifromxero_python.api_clientimportApiClient,serializefromxero_python.api_client.configurationimportConfigurationfromxero_python.api_client.oauth2importOAuth2Tokenfromxero_python.exceptionsimportAccountingBadRequestException,PayrollUkBadRequestExceptionfromxero_python.identityimportIdentityApifromxero_python.utilsimportgetvalueimportlogging_settingsfromutilsimportjsonify,serialize_modeldictConfig(logging_settings.default_settings)# configure main flask applicationapp=Flask(__name__)app.config.from_object(\"default_settings\")app.config.from_pyfile(\"config.py\",silent=True)ifapp.config[\"ENV\"]!=\"production\":# allow oauth2 loop to run over http (used for local testing only)os.environ[\"OAUTHLIB_INSECURE_TRANSPORT\"]=\"1\"# configure persistent session cacheSession(app)# configure flask-oauthlib applicationoauth=OAuth(app)xero=oauth.remote_app(name=\"xero\",version=\"2\",client_id=app.config[\"CLIENT_ID\"],client_secret=app.config[\"CLIENT_SECRET\"],endpoint_url=\"https://api.xero.com/\",authorization_url=\"https://login.xero.com/identity/connect/authorize\",access_token_url=\"https://identity.xero.com/connect/token\",refresh_token_url=\"https://identity.xero.com/connect/token\",scope=\"offline_access openid profile email accounting.transactions \"\"accounting.transactions.read accounting.reports.read \"\"accounting.journals.read accounting.settings accounting.settings.read \"\"accounting.contacts accounting.contacts.read accounting.attachments \"\"accounting.attachments.read assets projects \"\"files \"\"payroll.employees payroll.payruns payroll.payslip payroll.timesheets payroll.settings\",)# type: OAuth2Application# configure xero-python sdk clientapi_client=ApiClient(Configuration(debug=app.config[\"DEBUG\"],oauth2_token=OAuth2Token(client_id=app.config[\"CLIENT_ID\"],client_secret=app.config[\"CLIENT_SECRET\"]),),pool_threads=1,)# configure token persistence and exchange point between flask-oauthlib and xero-python@xero.tokengetter@api_client.oauth2_token_getterdefobtain_xero_oauth2_token():returnsession.get(\"token\")@xero.tokensaver@api_client.oauth2_token_saverdefstore_xero_oauth2_token(token):session[\"token\"]=tokensession.modified=TrueAuthenticationAll API requests go through Xero's OAuth 2.0 gateway and require a validaccess_tokento be set on theclientwhich appends theaccess_tokenJWTto the header of each request.If you are making an API call for the first time:Send the user to the Xero authorization URL@app.route(\"/login\")deflogin():redirect_url=url_for(\"oauth_callback\",_external=True)session[\"state\"]=app.config[\"STATE\"]try:response=xero.authorize(callback_uri=redirect_url,state=session[\"state\"])exceptExceptionase:print(e)raisereturnresponseThe user will authorize your application and be sent to yourredirect_uri. This is when and where to check that the returned \"state\" param matches that which was previously defined. If the \"state\" params match, calling the oauth library'sauthorized_response()method will swap the temporary auth code for an access token which you can store and use for subsequent API calls.@app.route(\"/callback\")defoauth_callback():ifrequest.args.get(\"state\")!=session[\"state\"]:return\"Error, state doesn't match, no token for you.\"try:response=xero.authorized_response()exceptExceptionase:print(e)raiseifresponseisNoneorresponse.get(\"access_token\")isNone:return\"Access denied: response=%s\"%responsestore_xero_oauth2_token(response)returnredirect(url_for(\"index\",_external=True))Call the Xero API like so:@app.route(\"/accounting_invoice_read_all\")@xero_token_requireddefaccounting_invoice_read_all():code=get_code_snippet(\"INVOICES\",\"READ_ALL\")#[INVOICES:READ_ALL]xero_tenant_id=get_xero_tenant_id()accounting_api=AccountingApi(api_client)try:invoices_read=accounting_api.get_invoices(xero_tenant_id)exceptAccountingBadRequestExceptionasexception:output=\"Error: \"+exception.reasonjson=jsonify(exception.error_data)else:output=\"Total invoices found:{}.\".format(len(invoices_read.invoices))json=serialize_model(invoices_read)#[/INVOICES:READ_ALL]returnrender_template(\"output.html\",title=\"Invoices\",code=code,output=output,json=json,len=0,set=\"accounting\",endpoint=\"invoice\",action=\"read_all\")It is recommended that you store this token set JSON in a datastore in relation to the user who has authenticated the Xero API connection. Each time you want to call the Xero API, you will need to access the previously generated token set, initialize it on the SDKclient, and refresh theaccess_tokenprior to making API calls.Token Setkeyvaluedescriptionid_token:\"xxx.yyy.zzz\"OpenID Connecttoken returned ifopenid profile emailscopes acceptedaccess_token:\"xxx.yyy.zzz\"Bearer tokenwith a 30 minute expiration required for all API callsexpires_in:1800Time in seconds till the token expires - 1800s is 30mrefresh_token:\"XXXXXXX\"Alphanumeric string used to obtain a new Token Set w/ a fresh access_token - 60 day expiryscope:[\"email\", \"profile\", \"openid\", \"accounting.transactions\", \"offline_access\"]The Xero permissions that are embedded in theaccess_tokenExample Token Set JSON:{\n \"id_token\": \"xxx.yyy.zz\",\n \"access_token\": \"xxx.yyy.zzz\",\n \"expires_in\": 1800,\n \"token_type\": \"Bearer\",\n \"refresh_token\": \"xxxxxxxxx\",\n \"scope\": [\"email\", \"profile\", \"openid\", \"accounting.transactions\", \"offline_access\"]\n}Custom ConnectionsCustom Connections are a Xeropremium optionused for building M2M integrations to a single organisation. A custom connection uses OAuth 2.0'sclient_credentialsgrant which eliminates the step of exchanging the temporary code for a token set.To use this SDK with a Custom Connections:# -*- coding: utf-8 -*-importosfromfunctoolsimportwrapsfromioimportBytesIOfromlogging.configimportdictConfigfromflaskimportFlask,url_for,render_template,session,redirect,json,send_filefromflask_sessionimportSessionfromxero_python.accountingimportAccountingApi,ContactPerson,Contact,Contactsfromxero_python.api_clientimportApiClient,serializefromxero_python.api_client.configurationimportConfigurationfromxero_python.api_client.oauth2importOAuth2Tokenfromxero_python.exceptionsimportAccountingBadRequestExceptionfromxero_python.identityimportIdentityApifromxero_python.utilsimportgetvalueimportlogging_settingsfromutilsimportjsonify,serialize_modeldictConfig(logging_settings.default_settings)# configure main flask applicationapp=Flask(__name__)app.config.from_object(\"default_settings\")app.config.from_pyfile(\"config.py\",silent=True)# configure persistent session cacheSession(app)# configure xero-python sdk clientapi_client=ApiClient(Configuration(debug=app.config[\"DEBUG\"],oauth2_token=OAuth2Token(client_id=app.config[\"CLIENT_ID\"],client_secret=app.config[\"CLIENT_SECRET\"]),),pool_threads=1,)# configure token persistence and exchange point between app session and xero-python@api_client.oauth2_token_getterdefobtain_xero_oauth2_token():returnsession.get(\"token\")@api_client.oauth2_token_saverdefstore_xero_oauth2_token(token):session[\"token\"]=tokensession.modified=True@app.route(\"/get_token\")defget_token():try:# no user auth flow, no exchanging temp code for tokenxero_token=api_client.get_client_credentials_token()exceptExceptionase:print(e)raise# todo validate state valueifxero_tokenisNoneorxero_token.get(\"access_token\")isNone:return\"Access denied: response=%s\"%xero_tokenstore_xero_oauth2_token(xero_token)returnredirect(url_for(\"index\",_external=True))@app.route(\"/accounting_invoice_read_all\")@xero_token_requireddefaccounting_invoice_read_all():code=get_code_snippet(\"INVOICES\",\"READ_ALL\")#[INVOICES:READ_ALL]accounting_api=AccountingApi(api_client)try:invoices_read=accounting_api.get_invoices('')exceptAccountingBadRequestExceptionasexception:output=\"Error: \"+exception.reasonjson=jsonify(exception.error_data)else:output=\"Total invoices found:{}.\".format(len(invoices_read.invoices))json=serialize_model(invoices_read)#[/INVOICES:READ_ALL]returnrender_template(\"output.html\",title=\"Invoices\",code=code,output=output,json=json,len=0,set=\"accounting\",endpoint=\"invoice\",action=\"read_all\")Because Custom Connections are only valid for a single organisation you don't need to pass the xero-tenant-id as the first parameter to every method, or more specifically for this SDK xeroTenantId can be an empty string.Because the SDK is generated from the OpenAPI spec the parameter remains. For now you are required to pass an empty string to use this SDK with a Custom Connection.App Store SubscriptionsIf you are implementing subscriptions to participate in Xero's App Store you will need to setupApp Store subscriptionsendpoints.When a plan is successfully purchased, the user is redirected back to the URL specified in the setup process. The Xero App Store appends the subscription Id to this URL so you can immediately determine what plan the user has subscribed to through the subscriptions API.With your app credentials you can create a client viaclient_credentialsgrant_type with themarketplace.billingscope. This unique access_token will allow you to query any functions inAppStoreApi. Client Credentials tokens to query app store endpoints will only work for apps that have completed the App Store on-boarding process.# configure xero-python sdk clientapi_client=ApiClient(Configuration(debug=app.config[\"DEBUG\"],oauth2_token=OAuth2Token(client_id=app.config[\"CLIENT_ID\"],client_secret=app.config[\"CLIENT_SECRET\"]),),pool_threads=1,)try:# pass True for app_store_billing - defaults to False if no value providedxero_token=api_client.get_client_credentials_token(True)exceptExceptionase:print(e)raiseapp_store_api=AppStoreApi(api_client)subscription=app_store_api.get_subscription(subscription_id)print(subscription){'current_period_end':datetime.datetime(2021,9,2,14,8,58,772536,tzinfo=tzutc()),'end_date':None,'id':'03bc74f2-1237-4477-b782-2dfb1a6d8b21','organisation_id':'79e8b2e5-c63d-4dce-888f-e0f3e9eac647','plans':[{'id':'6abc26f3-9390-4194-8b25-ce8b9942fda9','name':'Small','status':'ACTIVE','subscription_items':[{'end_date':None,'id':'834cff4c-b753-4de2-9e7a-3451e14fa17a','price':{'amount':Decimal('0.1000'),'currency':'NZD','id':'2310de92-c7c0-4bcb-b972-fb7612177bc7'},'product':{'id':'9586421f-7325-4493-bac9-d93be06a6a38','name':'','type':'FIXED','seat_unit':None},'start_date':datetime.datetime(2021,8,2,14,8,58,772536,tzinfo=tzutc()),'test_mode':True}]}],'start_date':datetime.datetime(2021,8,2,14,8,58,772536,tzinfo=tzutc()),'status':'ACTIVE','test_mode':True}You should use the subscription data to provision user access/permissions to your application.App Store Subscription WebhooksIn additon to a subscription Id being passed through the URL, when a purchase or an upgrade takes place you will be notified via a webhook. You can then use the subscription Id in the webhook payload to query the AppStore endpoints and determine what plan the user purchased, upgraded, downgraded or cancelled.Refer to Xero's documenation to learn more about setting up and receiving webhooks.https://developer.xero.com/documentation/guides/webhooks/overview/API ClientsYou can access the different API sets and their available methods through the following:accounting_api=AccountingApi(api_client)read_accounts=accounting_api.get_accounts(xero_tenant_id)asset_api=AssetApi(api_client)read_assets=asset_api.get_assets(xero_tenant_id)# ... all the API sets follow the same patternHelper MethodsOnce you have a valid Token Set in your datastore, the next time you want to call the Xero API simply initialize a newclientand refresh the token set.# configure xero-python sdk clientapi_client=ApiClient(Configuration(debug=app.config[\"DEBUG\"],oauth2_token=OAuth2Token(client_id=app.config[\"CLIENT_ID\"],client_secret=app.config[\"CLIENT_SECRET\"]),),pool_threads=1,)# configure token persistence and exchange point between app session and xero-python@api_client.oauth2_token_getterdefobtain_xero_oauth2_token():returnsession.get(\"token\")@api_client.oauth2_token_saverdefstore_xero_oauth2_token(token):session[\"token\"]=tokensession.modified=True# get existing token settoken_set=get_token_set_from_database(user_id);//examplefunctionname# set token set to the api clientstore_xero_oauth2_token(token_set)# refresh token set on the api clientapi_client.refresh_oauth2_token()# call the Xero APIaccounting_api=AccountingApi(api_client)read_accounts=accounting_api.get_accounts(xero_tenant_id)A full list of the SDK client's methods:methoddescriptionparamsreturnsapi_client.oauth2_token_saverA decorator to register a callback function for saving refreshed token while the old token has expiredtoken_saver: the callback function acceptingtokenargumenttoken_saver to allow this method be used as decoratorapi_client.oauth2_token_getterA decorator to register a callback function for getting oauth2 tokentoken_getter: the callback function returning oauth2 token dictionarytoken_getter to allow this method be used as decoratorapi_client.revoke_oauth2_tokenRevokes a users refresh token and removes all their connections to your appN/Aempty OAuth2 tokenapi_client.refresh_oauth2_tokenRefreshes OAuth2 token setN/Anew token setapi_client.set_oauth2_tokenSets OAuth2 token directly on the clientdict token: standard token dictionaryN/Aapi_client.get_oauth2_tokenGet OAuth2 token dictionaryN/AdictUsage ExamplesAccounting APIfromxero_python.accountingimportAccountingApifromxero_python.utilsimportgetvalueaccounting_api=AccountingApi(api_client)# Get Accountsread_accounts=accounting_api.get_accounts(xero_tenant_id)account_id=getvalue(read_accounts,\"accounts.0.account_id\",\"\")# Get Account by IDread_one_account=accounting_api.get_account(xero_tenant_id,account_id)# Create Invoice# get contactread_contacts=accounting_api.get_contacts(xero_tenant_id)contact_id=getvalue(read_contacts,\"contacts.0.contact_id\",\"\")# get accountwhere=\"Type==\\\"SALES\\\"&&Status==\\\"ACTIVE\\\"\"read_accounts=accounting_api.get_accounts(xero_tenant_id,where=where)account_id=getvalue(read_accounts,\"accounts.0.account_id\",\"\")# build Invoicescontact=Contact(contact_id=contact_id)line_item=LineItem(account_code=account_id,description=\"Consulting\",quantity=1.0,unit_amount=10.0,)invoice=Invoice(line_items=[line_item],contact=contact,due_date=dateutil.parser.parse(\"2020-09-03T00:00:00Z\"),date=dateutil.parser.parse(\"2020-07-03T00:00:00Z\"),type=\"ACCREC\")invoices=Invoices(invoices=[invoice])created_invoices=accounting_api.create_invoices(xero_tenant_id,invoices=invoices)invoice_id=getvalue(read_invoices,\"invoices.0.invoice_id\",\"\")# Create Attachmentinclude_online=Truefile_name=\"helo-heros.jpg\"path_to_upload=Path(__file__).resolve().parent.joinpath(file_name)open_file=open(path_to_upload,'rb')body=open_file.read()content_type=mimetypes.MimeTypes().guess_type(file_name)[0]created_invoice_attachments_by_file_name=accounting_api.create_invoice_attachment_by_file_name(xero_tenant_id,invoice_id,file_name,body,include_online,)SDK conventionsQuerying & FilteringDescribe the support for query options and filtering# configure api_client for use with xero-python sdk clientapi_client=ApiClient(Configuration(debug=false,oauth2_token=OAuth2Token(client_id=\"YOUR_CLIENT_ID\",client_secret=\"YOUR_CLIENT_SECRET\"),),pool_threads=1,)api_client.set_oauth2_token(\"YOUR_ACCESS_TOKEN\")defaccounting_get_invoices():api_instance=AccountingApi(api_client)xero_tenant_id='YOUR_XERO_TENANT_ID'if_modified_since=dateutil.parser.parse(\"2020-02-06T12:17:43.202-08:00\")where='Status==\"DRAFT\"'order='InvoiceNumber ASC'ids=[\"00000000-0000-0000-0000-000000000000\"]invoice_numbers=[\"INV-001\",\"INV-002\"]contact_ids=[\"00000000-0000-0000-0000-000000000000\"]statuses=[\"DRAFT\",\"SUBMITTED\"]include_archived='true'created_by_my_app='false'summary_only='true'api_response=api_instance.get_invoices(xero_tenant_id,if_modified_since,where,order,ids,invoice_numbers,contact_ids,statuses,page,include_archived,created_by_my_app,unitdp,summary_only)Participating in Xero\u2019s developer communityThis SDK is one of a number of SDK\u2019s that the Xero Developer team builds and maintains. We are grateful for all the contributions that the community makes.Here are a few things you should be aware of as a contributor:Xero has adopted the Contributor CovenantCode of Conduct, we expect all contributors in our community to adhere to itIf you raise an issue then please make sure to fill out the Github issue template, doing so helps us help youYou\u2019re welcome to raise PRs. As our SDKs are generated we may use your code in the core SDK build instead of merging your codeWe have acontribution guidefor you to follow when contributing to this SDKCurious about how we generate our SDK\u2019s? Have aread of our processand have a look at ourOpenAPISpecThis software is published under theMIT LicenseFor questions that aren\u2019t related to SDKs please refer to ourdeveloper support page.ContributingPRs, issues, and discussion are highly appreciated and encouraged. Note that the majority of this project is generated code based onXero's OpenAPI specs- PR's will be evaluated and pre-merge will be incorporated into the root generation templates.VersioningWe do our best to keep OS industrysemverstandards, but we can make mistakes! If something is not accurately reflected in a version's release notes please let the team know.History0.1.0 (2020-03-02)First release on PyPI."} +{"package": "xerosdk", "pacakge-description": "xero-sdk-pyPython SDK to access Xero APIsRequirementsPython 3+RequestslibraryInstallationInstall Xero SDK usingpipas follows:pip install xerosdkUsageThis SDK requires OAuth2 authentication credentials such asclient ID,client secretandrefresh token.Create a connection using the XeroSDK class.fromxerosdkimportXeroSDKconnection=XeroSDK(base_url='<XERO_BASE_URL>',client_id='<YOUR CLIENT ID>',client_secret='<YOUR CLIENT SECRET>',refresh_token='<YOUR REFRESH TOKEN>')# tenant_id is required to make a call to any APItenant_id=connection.tenants.get_all()[0]['tenantId']connection.set_tenant_id(tenant_id)Access any of the API classes\"\"\"USAGE: <XeroSDK INSTANCE>.<API_NAME>.<API_METHOD>(<PARAMETERS>)\"\"\"# Get a list of all Invoicesresponse=connection.invoices.get_all()# Get a list of all Invoices using generatorforresponseininvoices.list_all_generator():print(response)# Get an Invoice by idresponse=connection.invoices.get_by_id(<invoice_id>)NOTE: Only Tenants, Invoices, Accounts, Contacts, Items and TrackingCategories\nAPI classes are defined in this SDK.Integration TestsInstallpytestpackage using pip as follows:pip install pytestCreate a 'test_credentials.json' file at project root directory and enter Xero OAuth2 authentication credentials of\nyour Xero app.{\"base_url\":\"<xero_base_url>\",\"client_id\":\"<client_id>\",\"client_secret\":\"<client_secret>\",\"refresh_token\":\"<refresh_token>\"}Run integration tests as follows:python -m pytest tests/integration"} +{"package": "xerox", "pacakge-description": "Xeroxis a copy + paste module for python. It\u2019s aim is simple: to be as incredibly simple as possible.Supported platforms are currently OS X, X11 (Linux, BSD, etc.), and Windows.If you can make it simpler, please fork.UsageUsage is as follows:xerox.copy(u'some string')And to paste:>>> xerox.paste()\nu'some string'On Linux you can optionally also copy into the X selection clipboard for\nmiddle-click-paste capability:xerox.copy(u'Some string', xsel=True)And you can choose to paste from the X selection rather than the system\nclipboard:xerox.paste(xsel=True)And, that\u2019s it.Command LineTo copy:$ xerox some stringor:$ echo some string | xeroxTo paste:>>> xerox\nsome stringInstallationTo install Xerox, simply:$ pip install xeroxNote: If you are installing xerox on Windows, you will also need to install thepywin32module.Legal StuffMIT License.(c) 2016 Kenneth Reitz."} +{"package": "xerparser", "pacakge-description": "xerparserRead the contents of a P6 .xer file and convert it into a Python object.Disclaimers:It's helpfull if you are already familiar with the mapping and schemas used by P6 during the export process.\nRefer to theOracle Documentationfor more information regarding how data is mapped to the XER format.Tested on .xer files exported as versions 15.2 through 19.12.InstallWindows:pipinstallxerparserLinux/Mac:pip3installxerparserUsageImport theXerclass fromxerparserand pass the contents of a .xer file as an argument. Use theXerclass variableCODECto set the proper encoding to decode the file.fromxerparserimportXerfile=r\"/path/to/file.xer\"withopen(file,encoding=Xer.CODEC,errors=\"ignore\")asf:file_contents=f.read()xer=Xer(file_contents)Do not pass the the .xer file directly as an argument to theXerclass. The file must be decoded and read into a string, which can then be passed as an argument. Or, pass the .xer file into theXer.readerclassmethod, which accepts:str or pathlib.Path objects for files stored locally or on a server.Binary files from requests, Flask, FastAPI, etc...fromxerparserimportXerfile=r\"/path/to/file.xer\"xer=Xer.reader(file)AttributesThe tables stored in the .xer file are accessable as either Global, Project specific, Task specific, or Resource specific:Globalxer.export_info# export dataxer.activity_code_types# dict of ACTVTYPE objectsxer.activity_code_values# dict of ACTVCODE objectsxer.calendars# dict of all CALENDAR objectsxer.financial_periods# dict of FINDATES objectsxer.notebook_topics# dict of MEMOTYPE objectsxer.projects# dict of PROJECT objectsxer.project_code_types# dict of PCATTYPE objectsxer.project_code_values# dict of PCATVAL objectsxer.tasks# dict of all TASK objectsxer.relationships# dict of all TASKPRED objectsxer.resources# dict of RSRC objectsxer.udf_types# dict of UDFTYPE objectsxer.wbs_nodes# dict of all PROJWBS objectsProject Specific# Get first projectproject=list(xer.projects.values())[0]project.activity_codes# list of project specific ACTVTYPE objectsproject.calendars# list of project specific CALENDAR objectsproject.project_codes# dict of PCATTYPE: PCATVAL objectsproject.tasks# list of project specific TASK objectsproject.relationships# list of project specific TASKPRED objectsproject.user_defined_fields# dict of `UDFTYPE`: `UDF Value` pairsproject.wbs_nodes# list of project specific PROJWBS objectsTask Specific# Get first tasktask=project.tasks[0]task.activity_codes# dict of ACTVTYPE: ACTVCODE objectstask.memos# list of TASKMEMO objectstask.periods# list of TASKFIN objectstask.resources# dict of TASKRSRC objectstask.user_defined_fields# dict of `UDFTYPE`: `UDF Value` pairsResource Specific# Get first task resourceresource=list(task.resources.values())[0]resource.periods# list of TRSRCFIN objectsresource.user_defined_fields# dict of `UDFTYPE`: `UDF Value` pairsError CheckingSometimes the xer file is corrupted during the export process. If this is the case, aCorruptXerFileException will be raised during initialization. A list of the errors can be accessed from theCorruptXerFileException, or by using thefind_xer_errorsfunction.Option 1 -errorsattribute ofCorruptXerFileexception (preferred)fromxerparserimportXer,CorruptXerFilefile=r\"/path/to/file.xer\"try:xer=Xer.reader(file)exceptCorruptXerFilease:forerrorine.errors:print(error)Option 2 -find_xer_errorsfunctionfromxerparserimportparser,file_reader,find_xer_errorsfile=r\"/path/to/file.xer\"xer_data=parser(file_reader(file))file_errors=find_xer_errors(xer_data)forerrorinfile_errors:print(error)ErrorsMinimum required tables - an error is recorded if one of the following tables is missing:CALENDARPROJECTPROJWBSTASKTASKPREDRequired table pairs - an error is recorded if Table 1 is included but not Table 2:Table 1Table 2NotesTASKFINFINDATESFinancial Period Data for TaskTRSRCFINFINDATESFinancial Period Data for Task ResourceTASKRSRCRSRCResource DataTASKMEMOMEMOTYPENotebook DataACTVCODEACTVTYPEActivity Code DataTASKACTVACTVCODEActivity Code DataPCATVALPCATTYPEProject Code DataPROJPCATPCATVALProject Code DataUDFVALUEUDFTYPEUser Defined Field DataNon-existent calendars assigned to tasks.Non-existent resources assigned to task resources."} +{"package": "xerra", "pacakge-description": "No description available on PyPI."} +{"package": "xer-reader", "pacakge-description": "Xer-ReaderRead the contents of a Primavera P6 XER file using Python.Xer-Reader makes it easy to read, parse, and convert the data in a XER file to other formats.Refer to theOracle Documentationfor more information regarding how data is mapped to the XER format.Tested on XER files exported as versions 15.2 through 19.12.InstallWindows:pipinstallxer-readerLinux/Mac:pip3installxer-readerUsageImport theXerReaderclass fromxer_reader.fromxer_readerimportXerReaderCreate a new instance of anXerReaderobject by passing in the XER file as an argument.XerReadercan accept the file path represented as astror pathlibPathobject, or a Binary file received as a response from requests, Flask, FastAPI, etc...file=r\"/path/to/file.xer\"reader=XerReader(file)Attributesdata[str] -The contents of the XER file as a string.export_date[datetime] -The date the XER file was exported.export_user[str] -The P6 user who export the XER file.export_version[str] -The P6 verison used to export the XER file.file_name[str] -The name of the file without the '.xer' extension.Methodscheck_errors()->list[str]Checks the XER file for missing tables and orphan data, and returns the results as a list of errors.Missing tables can occur when an entry inTable 1points to an entry inTable 2butTable 2does not exist at all.Orphan data occurs when an entry inTable 1points to an entryTable 2but the entry inTable 2does not exist.delete_tables(*table_names: str)->strDelete a variable number of tables (table_names) from the XER file data and returns a new string (Does not modifyXerReader.dataattribute).In the following example the tables associated with User Defined Fields are removed from the XER file contents and stored in a new variablenew_xer_data, which can then be written to a new XER file:new_xer_data=reader.delete_tables(\"UDFTYPE\",\"UDFVALUE\")withopen(\"New_XER.xer\",\"w\",encoding=XerReader.CODEC)asnew_xer_file:new_xer_file.write(new_xer_data)get_table_names()->list[str]Returns a list of table names included in the XER file.get_table_str(table_name: str)->strReturns the tab seperated text for a specific table in the XER file.has_table(table_name: str)->boolReturn True if table (table_name) if found in the XER file.parse_tables()->dict[str, Table]Returns a dictionary with the table name as the key and aTableobject as the value.to_csv(file_directory: str | Path)->NoneGenerate a CSV file for each table in the XER file using 'tab' as the delimiter. CSV files will be created in the current working directory.Optional: Pass a string or Path object (file_directory) to speficy a folder to store the CSV files in.to_excel()->NoneGenerate an Excel (.xlsx) file with each table in the XER file on its own spreadsheet. The Excel file will be create in the\ncurrent working directory.to_json(*tables: str)->strGenerate a json compliant string representation of the tables in the XER file.Optional: Pass in specific table names to include in the json string."} +{"package": "xersplitter", "pacakge-description": "XER-SplitterA tool to handle the parsing of Oracles Primavera P6 .XER output files.\nConvert your .XER files into seperate CSVs for parsing and transforming in other tools (eg. PowerBI for reporting)Features includeCSV or XLSX output of .XER filesGUI and CLI availableOptionally ignore problematic RISKTYPE & POBS tablesBasic metrics (Total tables & rows)Sample XERshereInstallationCommand lineUsepipto install XER-Splitter:pip install xersplitterThis puts xersplitter on the PATH, allowing you to invoke the gui or use the command line arguments.GUIAlternatively if you just want the gui, the latest build (windows .exe) can be foundhereor you can build the file yourself usingpyinstallerfrom the root folderpyinstaller xersplitter/Splitter.py --onefileUsageusage: xersplitter [-h] [-csv | -xlsx] [-i] [-o] [-cli] [-a]\n\nA script to parse those pesky .xer files from Primavera P6\n\noptional arguments:\n -h, --help show this help message and exit\n -csv Comma seperated output\n -xlsx Excel file output\n -i , --inputFile The path to the input .xer file\n -o , --outputDir The directory where the output files will be placed\n -cli, --suppressGui Hide the GUI - opens by default\n -a, --allTables Parse all tables - Skips possibly problematic RISKTYPE & POBS tables by defaultLicenseGPL v3.0"} +{"package": "xertocsv", "pacakge-description": "No description available on PyPI."} +{"package": "xerxes-protocol", "pacakge-description": "xerxes-protocol"} +{"package": "xes", "pacakge-description": "This project is on Github:https://github.com/jsumrall/xesThis is a simple library which has methods for generating XES files.\nWith this library you will be able to take your raw event data and\ngenerate an XES file with a standard header. From the XES-Standard web page,\n\u201cXES is an XML-based standard for event logs. Its purpose is to provide a\ngenerally-acknowledged format for the interchange of event log data between\ntools and application domains. Its primary purpose is for process mining,\ni.e. the analysis of operational processes based on their event logs.\u201dAs usual, examples are the best way to see what this does.Example usage looks like this:#!/usr/bin/env python\n\nimport xes\n\ntraces = [\n [\n {\"concept:name\" : \"Register\", \"org:resource\" : \"Bob\"},\n {\"concept:name\" : \"Negotiate\", \"org:resource\" : \"Sally\"},\n {\"concept:name\" : \"Negotiate\", \"org:resource\" : \"Sally\"},\n {\"concept:name\" : \"Sign\", \"org:resource\" : \"Dan\"},\n {\"concept:name\" : \"Sendoff\", \"org:resource\" : \"Mary\"}\n ],\n [\n {\"concept:name\" : \"Register\", \"org:resource\" : \"Bob\"},\n {\"concept:name\" : \"Negotiate\", \"org:resource\" : \"Sally\"},\n {\"concept:name\" : \"Sign\", \"org:resource\" : \"Dan\"},\n {\"concept:name\" : \"Sendoff\", \"org:resource\" : \"Mary\"}\n ],\n [\n {\"concept:name\" : \"Register\", \"org:resource\" : \"Bob\"},\n {\"concept:name\" : \"Negotiate\", \"org:resource\" : \"Sally\"},\n {\"concept:name\" : \"Sign\", \"org:resource\" : \"Dan\"},\n {\"concept:name\" : \"Negotiate\", \"org:resource\" : \"Sally\"},\n {\"concept:name\" : \"Sendoff\", \"org:resource\" : \"Mary\"}\n ],\n [\n {\"concept:name\" : \"Register\", \"org:resource\" : \"Bob\"},\n {\"concept:name\" : \"Sign\", \"org:resource\" : \"Dan\"},\n {\"concept:name\" : \"Sendoff\", \"org:resource\" : \"Mary\"}\n ]\n]\n\n\nlog = xes.Log()\nfor trace in traces:\n t = xes.Trace()\n for event in trace:\n e = xes.Event()\n e.attributes = [\n xes.Attribute(type=\"string\", key=\"concept:name\", value=event[\"concept:name\"]),\n xes.Attribute(type=\"string\", key=\"org:resource\", value=event[\"org:resource\"])\n ]\n t.add_event(e)\n log.add_trace(t)\nlog.classifiers = [\n xes.Classifier(name=\"org:resource\",keys=\"org:resource\"),\n xes.Classifier(name=\"concept:name\",keys=\"concept:name\")\n]\n\nopen(\"example.xes\", \"w\").write(str(log))"} +{"package": "xesai", "pacakge-description": "No description available on PyPI."} +{"package": "xesapi", "pacakge-description": "No description available on PyPI."} +{"package": "xesking", "pacakge-description": "No description available on PyPI."} +{"package": "xesL2D5P", "pacakge-description": "No description available on PyPI."} +{"package": "xes-lib", "pacakge-description": "No description available on PyPI."} +{"package": "xes-lib-nopygame", "pacakge-description": "No description available on PyPI."} +{"package": "xesmf", "pacakge-description": "xESMF is a Python package forregridding.\nIt isPowerful: It usesESMF/ESMPyas backend and can regrid betweengeneral curvilinear gridswith allESMF regridding algorithms,\nsuch asbilinear,conservativeandnearest neighbour.Easy-to-use: It abstracts away ESMF\u2019s complicated infrastructure\nand provides a simple, high-level API, compatible withxarrayas well as basic numpy arrays.Fast: It is faster than ESMPy\u2019s original Fortran regridding engine in serial case, and also supportsdaskforout-of-core, parallel computation.Please seeonline documentation, orplay with example notebooks on Binder.For new users, I also recommend readingHow to ask for helpandHow to support xESMF."} +{"package": "xesn", "pacakge-description": "xesnEcho State Networks powered byxarrayanddask.Descriptionxesnis a python package for implementing Echo State Networks (ESNs), a\nparticular form of Recurrent Neural Network originally introduced byJaeger (2001).\nThe main purpose of the package is to enable ESNs for relatively large scale\nweather and climate applications,\nfor example as bySmith et al., (2023)andArcomano et al., (2020).\nThe package is designed to strike the balance between simplicity and\nflexibility, with a focus on implementing features that were shown to matter\nmost byPlatt et al., (2022).xesn usesxarrayto handle multi-dimensional data, relying ondaskfor parallelization and\nto handle datasets/networks that are too large for a single compute node.\nAt its core, xesn usesnumpyandcupyfor efficient CPU and GPU deployment.InstallationTo install from sourcegitclonehttps://github.com/timothyas/xesn.gitcdxesn\npipinstall-e.Note that additional dependencies can be installed to run the unit test suite::pipinstall-e.[test]pytestxesn/test/*.pyGetting StartedTo learn how to use xesn, check out thedocumentation hereGet in touchReport bugs, suggest features, or view the source codeon GitHub.License and Copyrightxesn is licensed under version 3 of the GNU Lesser General Public License.Development occurs on GitHub athttps://github.com/timothyas/xesn."} +{"package": "xesoython", "pacakge-description": "No description available on PyPI."} +{"package": "xespiano", "pacakge-description": "No description available on PyPI."} +{"package": "xespresso", "pacakge-description": "xespressoQuantum ESPRESSO Calculator for Atomic Simulation Environment (ASE).For the introduction of ASE , please visithttps://wiki.fysik.dtu.dk/ase/index.htmlFeaturesSupport all QE packages, including: pw, band, neb, dos, projwfc, pp ...Spin-polarized calculationLD(S)A+UAutomatic submit jobAutomatic check a new calculation required or notAutomatic set up \"nscf\" calculationRead and plot dos, pdos and layer resolved pdosPlot NEBAuthorXing Wangxingwang1991@gmail.comDependenciesPythonASEnumpyscipymatplotlibInstallation using pippip install --upgrade --user xespressoInstallation from sourceYou can get the source using git:gitclone--depth1https://github.com/superstar54/xespresso.gitAdd xespresso to your PYTHONPATH. On windows, you can edit the system environment variables.exportPYTHONPATH=\"/path/to/xespresso\":$PYTHONPATHexportASE_ESPRESSO_COMMAND=\"/path/to/PACKAGE.x PARALLEL -in PREFIX.PACKAGEi > PREFIX.PACKAGEo\"exportESPRESSO_PSEUDO=\"/path/to/pseudo\"ExamplesAutomatic submit jobA example of setting parameters for the queue. See example/queue.pyqueue={'nodes':4,'ntasks-per-node':20,'partition':'all','time':'23:10:00'}calc=Espresso(queue=queue)Automatic check a new calculation required or notBefore the calculation, it will first check the working directory. If the same geometry and parameters are used, try to check whether the results are available or not. Automatic check input parameters with Quantum Espresso document.calc=Espresso(label='scf/fe')Show debug information.calc=Espresso(debug=True)Add new speciesSome atoms are special:atoms with different starting_magnetizationatoms with different U valuesatoms with special basis setFor example, Fe with spin state AFM. See example/spin.pyatoms.new_array('species',np.array(atoms.get_chemical_symbols(),dtype='U20'))atoms.arrays['species'][1]='Fe1'Setting parameters with \"(i), i=1,ntyp\"Hubbard, starting_magnetization, starting_charge and so on. See example/dft+u.pyinput_ntyp={'starting_magnetization':{'Fe1':1.0,'Fe2':-1.0},'Hubbard_U':{'Fe1':3.0,'Fe2':3.0},}input_data['input_ntyp']=input_ntyp,Setting parameters for \"Hubbard_V(na,nb,k)\"Hubbard, starting_magnetization, starting_charge and so on. See example/dft+u.pyinput_data={'hubbard_v':{'(1,1,1)':4.0,'(3,3,1)':1.0},}Control parallelization levelsTo control the number of processors in each group: -ni,\n-nk, -nb, -nt, -nd) are used.calc=Espresso(pseudopotentials=pseudopotentials,package='pw',parallel='-nk 2 -nt 4 -nd 144',# parallel parameters}Non self-consistent calculationA example of nscf calculation following the above one.# start nscf calculationfromxespresso.post.nscfimportEspressoNscfnscf=EspressoNscf(calc.directory,prefix=calc.prefix,occupations='tetrahedra',kpts=(2,2,2),debug=True,)nscf.run()Calculate dos and pdosA example of calculating and plotting the pdos from the nscf calculation.fromxespresso.post.dosimportEspressoDos# dosdos=EspressoDos(parent_directory='calculations/scf/co',prefix=calc.prefix,Emin=fe-30,Emax=fe+30,DeltaE=0.01)dos.run()# pdosfromxespresso.post.projwfcimportEspressoProjwfcprojwfc=EspressoProjwfc(parent_directory='calculations/scf/co',prefix='co',DeltaE=0.01)projwfc.run()Calculate work functionfromxespresso.post.ppimportEspressoPppp=EspressoPp(calc.directory,prefix=calc.prefix,plot_num=11,fileout='potential.cube',iflag=3,output_format=6,debug=True,)pp.get_work_function()Restart from previous calculationcalc.read_results()atoms=calc.results['atoms']calc.run(atoms=atoms,restart=1)NEB calculationSee example/neb.pyfromxespresso.nebimportNEBEspressocalc=NEBEspresso(package='neb',images=images,climbing_images=[5],path_data=path_data)calc.calculate()calc.read_results()calc.plot()WorkflowOxygen evolution reaction (OER) calculationThe workflow includes four modules:OER_bulkOER_pourbaixOER_surfaceOER_siteThe workflow can handle:Generate surface slab model from bulk structureDetermine the surface adsorption siteDetermine the surface coverage(, O, OH*), Pourbaix diagramCalculate the Zero-point energyoer=OER_site(slab,label='oer/Pt-001-ontop',site_type='ontop',site=-1,height=2.0,calculator=parameters,molecule_energies=molecule_energies,)oer.run()To do lists:addqPointsSpecsandLine-of-inputfor phonon input file"} +{"package": "xesrepair", "pacakge-description": "No description available on PyPI."} +{"package": "xestore", "pacakge-description": "A simple file and document storage utility for XENONnTUsageimportxestorestore=xestore.XeStore()store.login()store.files.upload(\"a_public_file.txt\")store.files.private.upload(\"a_private_file.txt\")store.files['a_public_file'].download(PATH_TO_SAVE)doc={\"list\":[1,2,3]}store.documents.upload(doc,name=\"new_document\",**metadata)Free software: MITDocumentation:https://xestore.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand thebriggySmalls/cookiecutter-pypackageproject template."} +{"package": "xeta", "pacakge-description": "ClientThis is a test client."} +{"package": "xetcache", "pacakge-description": "XetCacheXetCache provides persistent caching of long running functions or\njupyter notebook cells.The cache can be stored on local disk together with your notebooks and\ncode (and using LFS, or the git-xet extension to store it with your git\nrepo). Or alternatively, it can be fully managed by theXetHubservice to easily share the cache with your\ncollaborators.Table of ContentsInstallSetupSetup With LocalSetup with Git StorageSetup With XetHubAuthenticationCommand LineEnvironment VariableIn PythonUsageUsage For Jupyter NotebooksUsage For Function CachingUsage For Function Call\nCachingLicenseInstallpip install xetcacheOr to install from source from GitHub:pip install git+https://github.com/xetdata/xetcache.gitSetupSetup With LocalNo additional set up needed. See Usage below.Setup with Git StorageIf using LFS, you can just directly commit and push the cache files in\nthexmemofolder.However, if using GitHub we recommend the use ofXetHub\u2019s extensions to\nGitHubfor performance and the ability to\nlazily fetch cached objects.For instance, a repository with the XetHub extension will allow you to\nlazy clone the repository withgit xet clone --lazy [repo]which will avoid fetching any large cached objects until they are\nactually needed.Setup With XetHubThe use of the fully managed XetHub service provides more powerful data\ndeduplication capabilities that allows similar objects to be stored or\nloaded, without needing to upload or download everything. We can also\ndeploy caches near your compute workloads to accelerate dataloading by\nover 10x.AuthenticationSignup onXetHuband obtain a\nusername and access token. You should write this down.There are three ways to authenticate with XetHub:Command Linexetlogin-e<email>-u<username>-p<personal_access_token>Xet login will write authentication information to~/.xetconfigEnvironment VariableEnvironment variables may be sometimes more convenient:exportXET_USER_EMAIL=<email>exportXET_USER_NAME=<username>exportXET_USER_TOKEN=<personal_access_token>In PythonFinally if in a notebook environment, or a non-persistent environment,\nwe also provide a method to authenticate directly from Python. Note that\nthis must be the first thing you run before any other operation:importpyxetpyxet.login(<username>,<personal_access_token>,<email>)UsageOptional: to cache on XetHub, you need to run:import xetcache\nxetcache.set_xet_project([give a project name here])Usage For Jupyter NotebooksFor Jupyter notebooks, run the following command to load the extensionimportxetcacheAfter which adding the following line to the top of a cell%%xetmemoinput=v1,v2output=v3,v4will cache the specified output variables (v3,v4 here) each time it is\ncalled. If called later with the same input values for v1,v2, the cached\nvalue is returned and not reevaluated. The cache is persistent across\nPython runs.By default, the output will only be cached if the cell takes longer the\n3 seconds to run. \u201calways=True\u201d can be added to the xetmemo arguments to\nignore the runime and to always cache:%%xetmemo input=v1,v2 output=v3,v4 always=TrueNote that inputs can be anything picklable including functions.A key parameter can be added to group the stored objects together.\nObjects stored with one key will not be retrievable with a different key%%xetmemoinput=v1,v2output=v3,v4always=Truekey=experiment1Usage For Function CachingTo cache the output of a function:fromxetcacheimportxetmemo@xetmemodefslowfunction(arg1,arg2):...# Stores with a key@xetmemo(key=\"hello\")defslowfunction(arg1,arg2):...By default, the output will only be cached if the cell takes longer the\n3 seconds to run. \u201calways=True\u201d can be added to the xetmemo arguments to\nignore the runtime and to always cache:# This will always cache irrespective of runtime@xetmemo(always=True)defslowfunction(arg1,arg2):...Usage For Function Call CachingTo cache a function call:defslowfn(x):..dostuff..# caches the call to slowfn with argument xxeteval(slowfn,x)# Stores with a keyxeteval(\"key\",slowfn,x)By default, the output will only be cached if the cell takes longer the\n3 seconds to run.xeteval_alwayscan be used instead to ignore the\nruntime and to always cache:# Store even if function is quick to runxeteval_always(quickfn,x)# Store with a key and to always store even the function is quick to runxeteval_always(\"key\",quickfn,x)LicenseBSD 3"} +{"package": "xe-temp", "pacakge-description": "No description available on PyPI."} +{"package": "xethereum", "pacakge-description": "xethereumsomething about ethereum."} +{"package": "xetherscan", "pacakge-description": "xetherscanEtherscan.io API wrapper, for Python"} +{"package": "xethhung12-minio", "pacakge-description": "This project is not maintained anymore. Please go forxethhung12_minio_commonxethhung12_minio_download_filexethhung12_minio_upload_fileBuild and deployrm-frdist/*\npython-mbuild\npythontwineuploaddist/*-u__token__-p{token}Behind Proxyif the client is connecting to internet though a company proxy server, use the environment variable(http_proxy) to setup the proxy.e.g.http_proxy=http://127.0.0.1:8080Usage of uploadpython-mxethhung12_minio_upload_file\\--url{url}\\--access-key{access-key}\\--secret-key{secret-key}\\--bucket{bucket}\\--local-file{localfile}\\--remote-file{remotefile}Usage of downloadpython-mxethhung12_minio_download_file\\--url{url}\\--access-key{access-key}\\--secret-key{secret-key}\\--bucket{bucket}\\--local-file{localfile}\\--remote-file{remotefile}"} +{"package": "xethhung12-minio-common", "pacakge-description": "Build and deployrm-frdist/*\npython-mbuild\npythontwineuploaddist/*-u__token__-p{token}Behind Proxyif the client is connecting to internet though a company proxy server, use the environment variable(http_proxy) to setup the proxy.e.g.http_proxy=http://127.0.0.1:8080"} +{"package": "xethhung12-minio-download-file", "pacakge-description": "Buildrm-frdist/*\npython-mbuildDeploypythontwineuploaddist/*-u__token__-p{token}Usagepython-mxethhung12_minio_download_file\\--url{url}\\--access-key{access-key}\\--secret-key{secret-key}\\--bucket{bucket}\\--local-file{localfile}\\--remote-file{remotefile}"} +{"package": "xethhung12-minio-upload-file", "pacakge-description": "Buildrm-frdist/*\npython-mbuildDeploypythontwineuploaddist/*-u__token__-p{token}Usagepython-mxethhung12_minio_upload_file\\--url{url}\\--access-key{access-key}\\--secret-key{secret-key}\\--bucket{bucket}\\--local-file{localfile}\\--remote-file{remotefile}"} +{"package": "xethhung12-tg-msg", "pacakge-description": "Build and deployrm-frdist/*\npython-mbuild\npythontwineuploaddist/*-u__token__-p{token}Usage of simple sendingpython-mxethhung12_tg_msg\\--receiver-id{receiver-id}\\--bot-token{bot-token}\\--msg{message}# --silent [if want the program close normally, eception still print out but return in normal return code]Usage of sending through STDINpython-mxethhung12_tg_msg\\--receiver-id{receiver-id}\\--bot-token{bot-token}\\--from-stdin{stdininput}# --silent [if want the program close normally, eception still print out but return in normal return code]"} +{"package": "xetrack", "pacakge-description": "Xetrackxetrack is a lightweight package to track experiments benchmarks, and monitor stractured data usingduckdbandsqlite.It is focuesed on simplicity and flexability.You create a \"Tracker\", and let it track data. You can retrive it later as pandas or connect to it as a database.Each instance of the tracker has a \"track_id\" which is a unique identifier for a single run.FeaturesSimpleEmbeddedFastPandas-likeSQL-likeObject store with deduplicationCLI for basic functionsMultiprocessing reads and writesLoguru logs integrationExperiment trackingModel monitoringInstallationpipinstallxetrackQuickstartfromxetrackimportTrackertracker=Tracker('database.db',params={'model':'resnet18'})tracker.log({\"accuracy\":0.9,\"loss\":0.1,\"epoch\":1})# All you really needtracker.latest{'accuracy':0.9,'loss':0.1,'epoch':1,'model':'resnet18','timestamp':'18-08-2023 11:02:35.162360','track_id':'cd8afc54-5992-4828-893d-a4cada28dba5'}tracker.to_df(all=True)# Retrive all the runs as dataframetimestamptrack_idmodellossepochaccuracy026-09-202312:17:00.342814398c985a-dc15-42da-88aa-6ac6cbf55794resnet180.110.9Paramsare values which are added to every future row:$tracker.set_params({'model':'resnet18','dataset':'cifar10'})$tracker.log({\"accuracy\":0.9,\"loss\":0.1,\"epoch\":2}){'accuracy':0.9,'loss':0.1,'epoch':2,'model':'resnet18','dataset':'cifar10','timestamp':'26-09-2023 12:18:40.151756','track_id':'398c985a-dc15-42da-88aa-6ac6cbf55794'}You can also set a value to an entire run withset_value(\"back in time\"):tracker.set_value('test_accuracy',0.9)# Only known at the end of the experimenttracker.to_df()timestamptrack_idmodellossepochaccuracydatasettest_accuracy026-09-202312:17:00.342814398c985a-dc15-42da-88aa-6ac6cbf55794resnet180.110.9NaN0.9226-09-202312:18:40.151756398c985a-dc15-42da-88aa-6ac6cbf55794resnet180.120.9cifar100.9Track functionsYou can track any function.The return value is logged before returnedtracker=Tracker('database.db',log_system_params=True,log_network_params=True,measurement_interval=0.1)image=tracker.track(read_image,*args,**kwargs)tracker.latest{'result':571084,'name':'read_image','time':0.30797290802001953,'error':'','disk_percent':0.6,'p_memory_percent':0.496507,'cpu':0.0,'memory_percent':32.874608,'bytes_sent':0.0078125,'bytes_recv':0.583984375}Or with a wrapper:@tracker.wrap(params={'name':'foofoo'})deffoo(a:int,b:str):returna+len(b)result=foo(1,'hello')tracker.latest{'function_name':'foo','args':\"[1, 'hello']\",'kwargs':'{}','error':'','function_time':4.0531158447265625e-06,'function_result':6,'name':'foofoo','timestamp':'26-09-2023 12:21:02.200245','track_id':'398c985a-dc15-42da-88aa-6ac6cbf55794'}Track assets (Oriented for ML models)When you attempt to track a non primitive value which is not a list or a dict - xetrack saves it as assets with deduplication and log the object hash:Tips: If you plan to log the same object many times over, after the first time you log it, just insert the hash instead for future values to save time on encoding and hashing.$tracker=Tracker('database.db',params={'model':'logistic regression'})$lr=Logisticregression().fit(X_train,y_train)$tracker.log({'accuracy':float(lr.score(X_test,y_test)),'lr':lr}){'accuracy':0.9777777777777777,'lr':'53425a65a40a49f4',# <-- this is the model hash'dataset':'iris','model':'logistic regression','timestamp':'2023-12-27 12:21:00.727834','track_id':'wisteria-turkey-4392'}$model=tracker.get('53425a65a40a49f4')# retrive an object$model.score(X_test,y_test)0.9777777777777777You can retrive the model in CLI if you need only the model in production and mind carring the rest of the file# bashxtgetdatabase.db53425a65a40a49f4model.cloudpickle# pythonimportcloudpicklewithopen(\"model.cloudpickle\",'rb')asf:model=cloudpickle.loads(f.read())# LogisticRegression()Tips and tricksTracker(Tracker.IN_MEMORY)Let you run only in memoryPandas-likeprint(tracker)_idtrack_iddatebaaccuracy048154ec7-1fe4-4896-ac66-89db54ddd12afd0bfe4f-7257-4ec3-8c6f-91fe8ae67d2016-08-202300:21:462.01.0NaN18a43000a-03a4-4822-98f8-4df671c2d410fd0bfe4f-7257-4ec3-8c6f-91fe8ae67d2016-08-202300:24:21NaNNaN1.0tracker['accuracy']# get accuracy columntracker.to_df()# get pandas dataframe of current runSQL-likeYou can filter the data using SQL-like syntax usingduckdb:The sqlite database is attached asdband the table isevents. Assts are in theassetstable.Pythontracker.conn.execute(f\"SELECT * FROM db.events WHERE accuracy > 0.8\").fetchall()Duckdb CLIduckdb\nDATTACH'database.db'ASdb(TYPEsqlite);DSELECT*FROMdb.events;\u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502timestamp\u2502track_id\u2502model\u2502epoch\u2502accuracy\u2502loss\u2502\n\u2502varchar\u2502varchar\u2502varchar\u2502int64\u2502double\u2502double\u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u25022023-12-2711:25:59.244003\u2502fierce-pudu-1649\u2502resnet18\u25021\u25020.9\u25020.1\u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518Logger integrationThis is very useful in an environment where you can use normal logs, and don't want to manage a separate logger or file.On great use-case ismodel monitoring.logs_stdout=trueprint to stdout every tracked eventlogs_path='logs'writes logs to a file$Tracker(db=Tracker.IN_MEMORY,logs_path='logs',logs_stdout=True).log({\"accuracy\":0.9})2023-12-1421:46:55.290|TRACKING|xetrack.logging:log:69!\ud83d\udcc1!{\"a\":1,\"b\":2,\"timestamp\":\"2023-12-14 21:46:55.290098\",\"track_id\":\"marvellous-stork-4885\"}$Reader.read_logs(path='logs')accuracytimestamptrack_id00.92023-12-1421:47:48.375258unnatural-polecat-1380AnalysisTo get the data of all runs in the database for analysis:Use this for further analysis and plotting.This works even while a another process is writing to the database.fromxetrackimportReaderdf=Reader('database.db').to_df()Model MonitoringHere is how we can save logs on any server and monitor them with xetrack:We want to print logs to a file orstdoutto be captured normally.We save memory by not inserting the data to the database (even though it's fine).\nLater we can read the logs and do fancy visualisation, online/offline analysis, build dashboards etc.tracker=Tracker(db=Tracker.SKIP_INSERT,logs_path='logs',logs_stdout=True)tracker.logger.monitor(\"<dict or pandas DataFrame>\")# -> write to logs in a structured way, consistent by schema, no database file neededdf=Reader.read_logs(path='logs')\"\"\"Run drift analysis and outlier detection on your logs:\"\"\"ML trackingtracker.logger.experiemnt(<modelevaluationandparams>)# -> prettily write to logsdf=Reader.read_logs(path='logs')\"\"\"Run fancy visualisation, online/offline analysis, build dashboards etc.\"\"\"CLIFor basic and repetative needs.$xtheaddatabase.db--n=2||timestamp|track_id|model|accuracy|data|params||---:|:---------------------------|:-------------------------|:---------|-----------:|:-------|:-----------------||0|2023-12-2711:36:45.859668|crouching-groundhog-5046|xgboost|0.9|mnist|1b5b2294fc521d12||1|2023-12-2711:36:45.863888|crouching-groundhog-5046|xgboost|0.9|mnist|1b5b2294fc521d12|...\n\n\n$xttaildatabase.db--n=1||timestamp|track_id|model|accuracy|data|params||---:|:---------------------------|:----------------|:---------|-----------:|:-------|:-----------------||0|2023-12-2711:37:30.627189|ebony-loon-6720|lightgbm|0.9|mnist|1b5b2294fc521d12|$xetsetaccuracy0.8--where-keyparams--where-value1b5b2294fc521d12--track-idebony-loon-6720\n\n$xtdeletedatabase.dbebony-loon-6720# delete experiments wiht a given track_id# run any other SQL in a oneliner$xtsqldatabase.db\"SELECT * FROM db.events;\"# retrive a model which was saved into a files as files using cloudpickle$xtgetdatabase.dbmodelhashoutput# If you have two databases, and you want to merge one to the other$xtcopysource.dbtarget.db"} +{"package": "xetracker", "pacakge-description": "UNKNOWN"} +{"package": "xeuclid", "pacakge-description": "xeuclidis a project of mine that\nI've been working on for the past few months.\nIt's a set of python scripts that lets you do analytic geometry inpython.\nYou can also draw TikZ diagrams usingtikz_draw.py.It's a work in progress.The following python packages are required to usexeuclid,numpyscipysympypdf2imagePillowTo usetikz_draw.pyyou have to haveLaTeXandtikzpackage installed. You might also need to installImageMagick.InstallationYou can easily installxeuclidusingpip.$pipinstallxeuclidExample UsageYou can find more examples indocs\\example_usage_files\\.fromxeuclidimport*A=col_vector([2,1])B=col_vector([-1,4])C=col_vector([-2,1])bisector1=angle_bisector(A,B,C)bisector2=angle_bisector(B,C,A)#angle bisector of angle ABC and angle BCAI=bisector1.intersection(bisector2)# intersection of bisector1 and bisector2# I is the incenter of trinagle ABCtikz=Tikz('triangle.tex',preamble=tikz_config.standalone)tikz.usepackage('ifthen')tikz.begin('document')tikz.begin('tikzpicture')tikz.draw_grid(x_range=[-5,5],y_range=[-5,5],color='Black!50')tikz.draw_axis(x_range=[-5,5],y_range=[-5,5],tick_labels=None)tikz.draw_angle(A,C,B,radius=0.3)tikz.draw_angle(C,B,A,radius=0.3)tikz.draw_angle(B,A,C,radius=0.3)tikz.draw_path(A,B,C,cycle=True)tikz.draw_path(I,A)tikz.draw_path(I,B)tikz.draw_path(I,C)tikz.draw_points(A,B,C,I)tikz.node(A,node_config=\"anchor=west\",text=r\"$A$\")tikz.node(B,node_config=\"anchor=south\",text=r\"$B$\")tikz.node(C,node_config=\"anchor=east\",text=r\"$C$\")tikz.node(I,node_config=\"anchor=north\",text=r\"$I$\")tikz.end('tikzpicture')tikz.end('document')tikz.pdf()#This will compile the TeX file using pdfLaTeX"} +{"package": "xeuledoc", "pacakge-description": "No description available on PyPI."} +{"package": "xeus-python", "pacakge-description": "No description available on PyPI."} +{"package": "xeus-python-shell", "pacakge-description": "No description available on PyPI."} +{"package": "xeus-robot", "pacakge-description": "No description available on PyPI."} +{"package": "xeval", "pacakge-description": "No description available on PyPI."} +{"package": "xevan-hash", "pacakge-description": "xevan_in_Pythonpython implementation of xevan hashing algo.\nIt is not pure python, it is c extented python due to performance.This is Enhacement from original LIMXTEC version that is customsed to work for xevan_hashes\nwith Version one block at 80 bytes and varibale block header size"} +{"package": "xev-data", "pacakge-description": "Vera Del Favero"} +{"package": "xevent", "pacakge-description": "xeventsee docs:https://ru35hub.pages.gitlab.lrz.de/xevent/"} +{"package": "xevo", "pacakge-description": "xevoThis is a simple set of classes to use for evolutionary coding in a polymorphic way. The central classes are given by \"eobj\", which implements the basic structure for an object that will be optimized by the second one \"evo\", which handles the optimization.#eobj\nEach eobj needs to at least implement:\ndefadd(a,b):\nhow to combine objects a and b\ndef randomize(s):\nreturn a new completely random version of this class\ndef mutate(s):\nreturn a sligthly mutated version of this object\ndef calcstrength(s)->float:\nhow strong is this objects version\ndef _copy(s):\ncopy the specifics of this objectyou can also override shallmaximize->bool to chance if the strength should be maximizedFinallyinit(s) should not contain any nonoptional parameters and call s.initial()There are two simple examples of this object. pion.py tries to find a fixed value (aka np.pi) and bitflip.py tries to maximize the sum of a list of booleans. This is very simple and implements a simple counter, that counts how often any state is evaluated. You can also take a look at the deep learning example below.#evo\nThis object only needs to implement two functions\ndef generation(s)->None:\nupdate the objects (stored in s.q)\ndef _copy(s) -> \"subclass of evo\":\ncopy the specifics of this objectHere there is a simple example implemented in crossevo (which is also given in the package), of a batch of object, in which 2 random objects figth against each other and the weaker one is replaced by either a combination of both objects, or by a mutation of the winning one.#erun\nRuns an experiment given an evo object and an eobj object. You can also specify the size population in the initializer.\nTo run the experiment call run(s,maxsteps=1000000,goalstrength=1000000.0), where maxsteps is the maximum number of generation calls that can be called. And by beating goalstrength the run is stopped before.\nAfter the run, you can call show_history(s,log=False) to show a strength history (with an optional logarithmic y axis (if log=True))#machine learning\nIf you take a look at the eobj deep (deep.py and deeptools.py), you find a simple optimizer object, which tries to find the perfect network setup for a keras dense network setup. So using it requires keras and tensorflow."} +{"package": "xexpr", "pacakge-description": "Xexpr ::= <Atom> | <Element>\nAtom ::= String | (singleton String)\nElement ::= (list String <Attr> (listof <Xexpr>))\nAttr ::= (dictionaryof String String)"} +{"package": "xextension", "pacakge-description": "utils for python"} +{"package": "xextract", "pacakge-description": "Extract structured data from HTML and XML documents like a boss.xextractis simple enough for writing a one-line parser, yet powerful enough to be used in a big project.FeaturesParsing of HTML and XML documentsSupportsxpathandcssselectorsSimple declarative style of parsersBuilt-in self-validation to let you know when the structure of the website has changedSpeed - under the hood the library useslxml librarywith compiled xpath selectorsTable of ContentsA little taste of itInstallationParsersStringUrlDateTimeDateElementGroupPrefixParser parametersnamecss / xpathquantattrcallbackchildrennamespacesHTML vs. XML parsingA little taste of itLet\u2019s parseThe Shawshank Redemption\u2019s IMDB page:# fetch the website>>>importrequests>>>response=requests.get('http://www.imdb.com/title/tt0111161/')# parse like a boss>>>fromxextractimportString,Group# extract title with css selector>>>String(css='h1[itemprop=\"name\"]',quant=1).parse(response.text)u'The Shawshank Redemption'# extract release year with xpath selector>>>String(xpath='//*[@id=\"titleYear\"]/a',quant=1,callback=int).parse(response.text)1994# extract structured data>>>Group(css='.cast_list tr:not(:first-child)',children=[...String(name='name',css='[itemprop=\"actor\"]',attr='_all_text',quant=1),...String(name='character',css='.character',attr='_all_text',quant=1)...]).parse(response.text)[{'name':u'Tim Robbins','character':u'Andy Dufresne'},{'name':u'Morgan Freeman','character':u\"Ellis Boyd 'Red' Redding\"},...]InstallationTo installxextract, simply run:$pipinstallxextractRequirements: six, lxml, cssselectSupported Python versions are 2.6, 2.7, 3.x.Windows users can download lxml binaryhere.ParsersStringParameters:name(optional),css / xpath(optional, default\"self::*\"),quant(optional, default\"*\"),attr(optional, default\"_text\"),callback(optional),namespaces(optional)Extract string data from the matched element(s).\nExtracted value is always unicode.By default,Stringextracts the text content of only the matched element, but not its descendants.\nTo extract and concatenate the text out of every descendant element, useattrparameter with the special value\"_all_text\":Useattrparameter to extract the data from an HTML/XML attribute.Usecallbackparameter to post-process extracted values.Example:>>>fromxextractimportString>>>String(css='span',quant=1).parse('<span>Hello <b>world</b>!</span>')u'Hello !'>>>String(css='span',quant=1,attr='class').parse('<span class=\"text-success\"></span>')u'text-success'# use special `attr` value `_all_text` to extract and concantenate text out of all descendants>>>String(css='span',quant=1,attr='_all_text').parse('<span>Hello <b>world</b>!</span>')u'Hello world!'# use special `attr` value `_name` to extract tag name of the matched element>>>String(css='span',quant=1,attr='_name').parse('<span>hello</span>')u'span'>>>String(css='span',callback=int).parse('<span>1</span><span>2</span>')[1,2]UrlParameters:name(optional),css / xpath(optional, default\"self::*\"),quant(optional, default\"*\"),attr(optional, default\"href\"),callback(optional),namespaces(optional)Behaves likeStringparser, but with two exceptions:default value forattrparameter is\"href\"if you passurlparameter toparse()method, the absolute url will be constructed and returnedIfcallbackis specified, it is calledafterthe absolute urls are constructed.Example:>>>fromxextractimportUrl,Prefix>>>content='<div id=\"main\"> <a href=\"/test\">Link</a> </div>'>>>Url(css='a',quant=1).parse(content)u'/test'>>>Url(css='a',quant=1).parse(content,url='http://github.com/Mimino666')u'http://github.com/test'# absolute url address. Told ya!>>>Prefix(css='#main',children=[...Url(css='a',quant=1)...]).parse(content,url='http://github.com/Mimino666')# you can pass url also to ancestor's parse(). It will propagate down.u'http://github.com/test'DateTimeParameters:name(optional),css / xpath(optional, default\"self::*\"),format(required),quant(optional, default\"*\"),attr(optional, default\"_text\"),callback(optional)namespaces(optional)Returns thedatetime.datetimeobject constructed out of the extracted data:datetime.strptime(extracted_data, format).formatsyntax is described in thePython documentation.Ifcallbackis specified, it is calledafterthe datetime objects are constructed.Example:>>>fromxextractimportDateTime>>>DateTime(css='span',quant=1,format='%d.%m.%Y %H:%M').parse('<span>24.12.2015 5:30</span>')datetime.datetime(2015,12,24,50,30)DateParameters:name(optional),css / xpath(optional, default\"self::*\"),format(required),quant(optional, default\"*\"),attr(optional, default\"_text\"),callback(optional)namespaces(optional)Returns thedatetime.dateobject constructed out of the extracted data:datetime.strptime(extracted_data,format).date().formatsyntax is described in thePython documentation.Ifcallbackis specified, it is calledafterthe datetime objects are constructed.Example:>>>fromxextractimportDate>>>Date(css='span',quant=1,format='%d.%m.%Y').parse('<span>24.12.2015</span>')datetime.date(2015,12,24)ElementParameters:name(optional),css / xpath(optional, default\"self::*\"),quant(optional, default\"*\"),callback(optional),namespaces(optional)Returns lxml instance (lxml.etree._Element) of the matched element(s).\nIf you use xpath expression and match the text content of the element (e.g.text()or@attr), unicode is returned.Ifcallbackis specified, it is called withlxml.etree._Elementinstance.Example:>>>fromxextractimportElement>>>Element(css='span',quant=1).parse('<span>Hello</span>')<Elementspanat0x2ac2990>>>>Element(css='span',quant=1,callback=lambdael:el.text).parse('<span>Hello</span>')u'Hello'# same as above>>>Element(xpath='//span/text()',quant=1).parse('<span>Hello</span>')u'Hello'GroupParameters:name(optional),css / xpath(optional, default\"self::*\"),children(required),quant(optional, default\"*\"),callback(optional),namespaces(optional)For each element matched by css/xpath selector returns the dictionary containing the data extracted by the parsers listed inchildrenparameter.\nAll parsers listed inchildrenparametermusthavenamespecified - this is then used as the key in dictionary.Typical use case for this parser is when you want to parse structured data, e.g. list of user profiles, where each profile contains fields like name, address, etc. UseGroupparser to group the fields of each user profile together.Ifcallbackis specified, it is called with the dictionary of parsed children values.Example:>>>fromxextractimportGroup>>>content='<ul><li id=\"id1\">michal</li> <li id=\"id2\">peter</li></ul>'>>>Group(css='li',quant=2,children=[...String(name='id',xpath='self::*',quant=1,attr='id'),...String(name='name',xpath='self::*',quant=1)...]).parse(content)[{'name':u'michal','id':u'id1'},{'name':u'peter','id':u'id2'}]PrefixParameters:css / xpath(optional, default\"self::*\"),children(required),namespaces(optional)This parser doesn\u2019t actually parse any data on its own. Instead you can use it, when many of your parsers share the same css/xpath selector prefix.Prefixparser always returns a single dictionary containing the data extracted by the parsers listed inchildrenparameter.\nAll parsers listed inchildrenparametermusthavenamespecified - this is then used as the key in dictionary.Example:# instead of...>>>String(css='#main .name').parse(...)>>>String(css='#main .date').parse(...)# ...you can use>>>fromxextractimportPrefix>>>Prefix(css='#main',children=[...String(name=\"name\",css='.name'),...String(name=\"date\",css='.date')...]).parse(...)Parser parametersnameParsers:String,Url,DateTime,Date,Element,GroupDefault value:NoneIf specified, then the extracted data will be returned in a dictionary, with thenameas the key and the data as the value.All parsers listed inchildrenparameter ofGrouporPrefixparsermusthavenamespecified.\nIf multiple children parsers have the samename, the behavior is undefined.Example:# when `name` is not specified, raw value is returned>>>String(css='span',quant=1).parse('<span>Hello!</span>')u'Hello!'# when `name` is specified, dictionary is returned with `name` as the key>>>String(name='message',css='span',quant=1).parse('<span>Hello!</span>'){'message':u'Hello!'}css / xpathParsers:String,Url,DateTime,Date,Element,Group,PrefixDefault value (xpath):\"self::*\"Use eithercssorxpathparameter (but not both) to select the elements from which to extract the data.Under the hood css selectors are translated into equivalent xpath selectors.For the children ofPrefixorGroupparsers, the elements are selected relative to the elements matched by the parent parser.Example:Prefix(xpath='//*[@id=\"profile\"]',children=[# equivalent to: //*[@id=\"profile\"]/descendant-or-self::*[@class=\"name\"]String(name='name',css='.name',quant=1),# equivalent to: //*[@id=\"profile\"]/*[@class=\"title\"]String(name='title',xpath='*[@class=\"title\"]',quant=1),# equivalent to: //*[@class=\"subtitle\"]String(name='subtitle',xpath='//*[@class=\"subtitle\"]',quant=1)])quantParsers:String,Url,DateTime,Date,Element,GroupDefault value:\"*\"quantspecifies the expected number of elements to be matched with css/xpath selector. It serves two purposes:Number of matched elements is checked against thequantparameter. If the number of elements doesn\u2019t match the expected quantity,xextract.parsers.ParsingErrorexception is raised. This way you will be notified, when the website has changed its structure.It tells the parser whether to return a single extracted value or a list of values. See the table below.Syntax forquantmimics the regular expressions.\nYou can either pass the value as a string, single integer or tuple of two integers.Depending on the value ofquant, the parser returns either a single extracted value or a list of values.Value ofquantMeaningExtracted data\"*\"(default)Zero or more elements.List of values\"+\"One or more elements.List of values\"?\"Zero or one element.Single value orNonenumExactlynumelements.You can pass either string or integer.num== 0:Nonenum== 1: Single valuenum> 1: List of values(num1, num2)Number of elements has to be betweennum1andnum2, inclusive.You can pass either a string or 2-tuple.List of valuesExample:>>>String(css='.full-name',quant=1).parse(content)# return single valueu'John Rambo'>>>String(css='.full-name',quant='1').parse(content)# same as aboveu'John Rambo'>>>String(css='.full-name',quant=(1,2)).parse(content)# return list of values[u'John Rambo']>>>String(css='.full-name',quant='1,2').parse(content)# same as above[u'John Rambo']>>>String(css='.middle-name',quant='?').parse(content)# return single value or NoneNone>>>String(css='.job-titles',quant='+').parse(content)# return list of values[u'President',u'US Senator',u'State Senator',u'Senior Lecturer in Law']>>>String(css='.friends',quant='*').parse(content)# return possibly empty list of values[]>>>String(css='.friends',quant='+').parse(content)# raise exception, when no elements are matchedxextract.parsers.ParsingError:ParserStringmatched0elements(\"+\"expected).attrParsers:String,Url,DateTime,DateDefault value:\"href\"forUrlparser.\"_text\"otherwise.Useattrparameter to specify what data to extract from the matched element.Value ofattrMeaning\"_text\"Extract the text content of the matched element.\"_all_text\"Extract and concatenate the text content of\nthe matched element and all its descendants.\"_name\"Extract tag name of the matched element.att_nameExtract the value out ofatt_nameattribute of\nthe matched element.If such attribute doesn\u2019t exist, empty string is\nreturned.Example:>>>fromxextractimportString,Url>>>content='<span class=\"name\">Barack <strong>Obama</strong> III.</span> <a href=\"/test\">Link</a>'>>>String(css='.name',quant=1).parse(content)# default attr is \"_text\"u'Barack III.'>>>String(css='.name',quant=1,attr='_text').parse(content)# same as aboveu'Barack III.'>>>String(css='.name',quant=1,attr='_all_text').parse(content)# all textu'Barack Obama III.'>>>String(css='.name',quant=1,attr='_name').parse(content)# tag nameu'span'>>>Url(css='a',quant='1').parse(content)# Url extracts href by defaultu'/test'>>>String(css='a',quant='1',attr='id').parse(content)# non-existent attributes return empty stringu''callbackParsers:String,Url,DateTime,Date,Element,GroupProvides an easy way to post-process extracted values.\nIt should be a function that takes a single argument, the extracted value, and returns the postprocessed value.Example:>>>String(css='span',callback=int).parse('<span>1</span><span>2</span>')[1,2]>>>Element(css='span',quant=1,callback=lambdael:el.text).parse('<span>Hello</span>')u'Hello'childrenParsers:Group,PrefixSpecifies the children parsers for theGroupandPrefixparsers.\nAll parsers listed inchildrenparametermusthavenamespecifiedCss/xpath selectors in the children parsers are relative to the selectors specified in the parent parser.Example:Prefix(xpath='//*[@id=\"profile\"]',children=[# equivalent to: //*[@id=\"profile\"]/descendant-or-self::*[@class=\"name\"]String(name='name',css='.name',quant=1),# equivalent to: //*[@id=\"profile\"]/*[@class=\"title\"]String(name='title',xpath='*[@class=\"title\"]',quant=1),# equivalent to: //*[@class=\"subtitle\"]String(name='subtitle',xpath='//*[@class=\"subtitle\"]',quant=1)])namespacesParsers:String,Url,DateTime,Date,Element,Group,PrefixWhen parsing XML documents containing namespace prefixes, pass the dictionary mapping namespace prefixes to namespace URIs.\nUse then full name for elements in xpath selector in the form\"prefix:element\"As for the moment, youcannot use default namespacefor parsing (seelxml docsfor more information). Just use an arbitrary prefix.Example:>>>content='''<?xml version='1.0' encoding='UTF-8'?>\n... <movie xmlns=\"http://imdb.com/ns/\">\n... <title>The Shawshank Redemption\n... 1994\n... '''>>>nsmap={'imdb':'http://imdb.com/ns/'}# use arbitrary prefix for default namespace>>>Prefix(xpath='//imdb:movie',namespaces=nsmap,children=[# pass namespaces to the outermost parser...String(name='title',xpath='imdb:title',quant=1),...String(name='year',xpath='imdb:year',quant=1)...]).parse(content){'title':u'The Shawshank Redemption','year':u'1994'}HTML vs. XML parsingTo extract data from HTML or XML document, simply callparse()method of the parser:>>>fromxextractimport*>>>parser=Prefix(...,children=[...])>>>extracted_data=parser.parse(content)contentcan be either string or unicode, containing the content of the document.Under the hoodxextactuses eitherlxml.etree.XMLParserorlxml.etree.HTMLParserto parse the document.\nTo select the parser,xextractlooks for\">>parser.parse_html(content)# force lxml.etree.HTMLParser>>>parser.parse_xml(content)# force lxml.etree.XMLParser"} +{"package": "xeye", "pacakge-description": "XeyeXeyeInstallationXeye datasets for deep learningXeye functionalitiesCreate a dataset with full terminal UI (Dataset)Other useful methodsScript exampleCreate a dataset with fast UI (FastDataset)Create a dataset with manual UI (ManualDataset)How to take pictures manuallyBuild datasets from different npz files (BuildDataset)Script exampleXeye is a package for data collection to build computer vision applications based on inferential results of deep learning models. The main reasons to use Xeye are:Create a dataset using only a laptop and its integrated camera (or alternatively an external USB camera);Create a dataset already structured like themnist;Create a dataset that can be used for building models withTensorfloworPytorch.InstallationTo install the package,pip install xeyeXeye datasets for deep learningIn theexamplefolder, you can find examples of deep learning model implementations based on datasets produced by the Xeye package (made withTensorfloworPytorchframeworks).Binary dataset: containing two types of grayscale images (with labels: 0=keyboard, 1=mouse).MultiLabel dataset: containing three types of rgb images (three types of security cameras with labels: 0=dome, 1=bullet, 2=cube)Additionally, theexamplefolder contains examples of scripts that use the Xeye package to build datasets (examples link.Xeye functionalitiesThe Xeye package includes three major approaches (classes) for creating a dataset from scratch: Dataset, FastDataset, and ManualDataset.Dataset: Uses the full terminal UI.FastDataset: Uses the constructor with all the specifications of the dataset.ManualDataset: Same as FastDataset, but every image is shot manually one at a time.Additionally, the package provides a method for combining datasets created with theBuildDatasetclass.Create a dataset with full terminal UI (Dataset)First of all, load the module datapipe from the package:importxeyethen initialize the instance like thisdata=xeye.Dataset()the execution of this method causes the starting of the user interface in theterminal--- CAMERA SETTING ---Select the index of the camera that you want to use for creating the dataset: 1the initializing method arises multiple questions that set the parameters' values--- IMAGE SETTINGS ---Num. of types of images to scan: 2Name of image type (1): keyboardName of image type (2): mouseNum. of frames to shoot for every image type: 10Single frame HEIGHT: 720Single frame WIDTH: 720num. of waiting time (in sec.) between every frame: 0Precisely the questions refer to:Select the index of the camera that you want to use for creating the dataset: Generally 0 for integrated camera, 1 for USB external camera.Num. of types of images to scan: Answer 2 if you want to create a dataset with two objects (e.g. keyboard and mouse). In general, answer with the number of object types to include in your dataset.Name of image type: Insert the name of every specific object you want to include in the dataset. Thesetupmethod creates a named folder for every image type.Num. of frames to shoot for every image type: Select the number of images you want to shoot and save them in every object folder.Single frame HEIGHT: Frame height values.Single frame WIDTH: Frame width values.Num. of waiting time (in sec.) between every frame: e.g 0.2 causes a waiting time of 0.2 seconds between every shoot.After the parameters setting, you can invoke the method to start shooting images. Datapipe module provides two different formats of images:Grayscale image with thegraymethod;Color image with thergbmethod.Let's produce a dataset based on RGB images with thergbmethod:data.rgb()In the terminal keypress [b], to make photos for the image types passed to thesetupmethod.--- START TAKING PHOTOS ---Press [b] on the keyboard to start data collection of image type [keyboard]bPress [b] on the keyboard to start data collection of image type [mouse]bOn the directory of the script, you can find the folders that contain the images produced by therbgmethod (e.g. keyboard folder and mouse folder).Images collected in the folders can be used for building datasets like themnist. The first approach to achieve this result is calling thecompress_train_testmethod:data.compress_train_test()That produces the following output in the terminal window--- DATASET SETTING ---percentage of images in the test set: 0.2In which you can select the portion of images to use in the train and test datasets (write a value between (0,1)). By doing so, the method produces a.npzfile formed by these specific tensors:Train set:X_train: Matrices/tensors of every single image in the train dataset;y_train: Classes (ordinal values) are associated with every image in the train dataset.Test set:X_test: Matrices/tensors of every single image in the test dataset;y_test: Classes (ordinal values) are associated with every image in the test dataset.(matrices for grayscale images: [Height $\\times$ Width $\\times$ 1], tensors for RGB images:[Height $\\times$ Width $\\times$ 3]).An alternative approach is represented by the use of thecompress_allmethoddata.compress_all()In this case, the images are united in a unique tensor that contains all the frames produced previously.Unique tensor:X: Matricies/tensors of every single image produced;y: Classes (ordinal values) are associated with every image produced.Finally, you can use thejust_compressmethod to create a unique tensor with all the images produced.data.just_compress()In the terminal, you have to insert the dataset\u2019s name--- DATASET SETTING ---Select a name for the compressed file: batch_testIf you pass 0, by default the dataset will be save with the namedataset_raw.npz. The dataset produced by this method can be used by the classBuildDatasetto put together more .npz files and create a dataset like themnist.Other useful methodspreview: Open the camera stream to check the framing.var_control: Print the values of the parameters set with thesetupmethod.--- PARAMETERS CONTROL ---camera index: 1num. of images types: 2labels of images types: ['keyboard', 'mouse']num. of images for types: 20Single frame HEIGHT: 720Single frame WIDTH: 720waiting time between frames: 0.0percentage of images in train dataset: 0.2Script exampleExample of a script to use theDatasetclass:importxeyedata=xeye.dataset()data.setup()data.preview()data.rgb()data.compress_train_test()data.compress_all()data.just_compress()Create a dataset with fast UI (FastDataset)TheFastDatasetclass provides a faster way to use the datapipe module. Unlike theDatasetclass, it does not have a complete terminal UI to guide you through the dataset construction process. Instead, you simply pass the parameters to the class and call the necessary methods.importxeye# define parameters valuesindex=0img_types=2label=['keyboard','mouse']num=20height=100width=100standby_time=0# percentage of images in the test setperc=0.2data=xeye.FastDataset(index=index,img_types=img_types,label=label,num=num,height=height,width=width,stand_by_time=standby_time)data.preview()data.rgb()data.compress_train_test(perc=perc)data.compress_all()data.just_compress(\"batch_test\")The parameters passed to the classFastDataset:index: Generally 0 for integrated camera, 1 for USB external camera.img_types: Numbers of object types that you want to include in your dataset.label: List of object names to include in the dataset. Thesetupmethod creates a named folder for every image type.num: Select the number of images you want to shoot and save them in every object folder.height: Frame height values.width: Frame width values.standby_time: e.g 0.2 cause a waiting time of 0.2 seconds between every shoot.For split images in the train and test dataset, pass a value between (0,1) to the perc parameter of thecompress_train_testmethodperc: the portion of images to use in the test dataset, write a value between (0,1).If you don't pass any value to thejust_compressmethod, the dataset will be saved with the namedataset_raw.npz.Create a dataset with manual UI (ManualDataset)TheManualDatasetclass is how you can build a dataset by taking pictures manually.importxeye# define parameters valuesindex=0img_types=2label=['keyboard','mouse']num=20height=100width=100standby_time=0# percentage of images in the test setperc=0.2data=xeye.ManualDataset(index=index,img_types=img_types,label=label,num=num,height=height,width=width)data.preview()data.rgb()data.compress_train_test(perc=perc)data.compress_all()data.just_compress(\"batch_test\")As you can see in the code snippet, theManualDatasetclass works like theFastDatasetclass. The only difference is the absence of thestandby_time option, which is no more necessary in this case.The parameters passed to the classManualDataset:index: Generally 0 for integrated camera, 1 for USB external camera.img_types: Numbers of object types that you want to include in your dataset.label: List of object names to include in the dataset. The constructor creates a named folder for every image type.num: Select the number of images you want to shoot and save them in every object folder.height: Frame height values.width: Frame width values.How to take pictures manuallyIn the title bar of the image window, after the caption identifying the image type, there are instructions for manually taking pictures using the ManualDataset. These instructions will be displayed as follows:Camera view for image type . Press [s] on the keyboard to save image number: .Build datasets from different npz files (BuildDataset)If you want to create a dataset that includes different types of images, but cannot shoot all image types at once (e.g., due to time constraints or location differences), you can use theBuildDatasetclass.Create datasets with thejust_compressmethod;Create different .npz files for every type of images that composes the dataset (use the same colour spaces in all datasets, RGB or grayscale);Create a new script and call theBuildDatasetclass that merges all the .npz files created before.Script exampleimportxeye# list of directory (paths for the .npz files)path=['batch_2.npz','batch_3.npz']# list of labels associated with the images inside the .npz fileslabel=[0,1]data=xeye.BuildDataset(path=path,label=label,size=None,color=True,split=True,perc=0.2)data.build()The parameters passed to the classBuildDataset:path: List of files (.npz) path you want to include in the new datasetlabel: List of ordinal integer values representing the class type of the images inside a .npz file contained in the new dataset. In the example script, the first .npz file images are associated with class 0, while the second .npz file images are associated with class 1. Remember: always start with 0.size: Tuple (height, width) for the images in the new dataset created. The default value (None) indicates that new images have the maximum height and width found in the datasets listed as dimensionscolor: Defines if the images contained in the .npz files are RGB or grayscale. A boolean value, by default, is set to True (meaning RGB images).split: Defines if you want to build a dataset split in train-test or not. A boolean value, by default, is set to True.perc: Defines the percentage of images assigned to the test dataset. A floating value between (0,1). It's set to 0.1 by default.When you want to use theBuildDatasetclass, you need to have .npz files containing images with the same types of colour spaces (all grayscale images or RGB)."} +{"package": "xfab", "pacakge-description": "No description available on PyPI."} +{"package": "xface", "pacakge-description": "\u5b89\u88c5\u4e0e\u5347\u7ea7\u4e3a\u4e86\u7b80\u5316\u5b89\u88c5\u8fc7\u7a0b\uff0c\u63a8\u8350\u4f7f\u7528 pip \u8fdb\u884c\u5b89\u88c5pipinstallxface\u5347\u7ea7 Django Cool \u5230\u65b0\u7248\u672c:pip install -U xface\u5982\u679c\u9700\u8981\u5b89\u88c5 GitHub \u4e0a\u7684\u6700\u65b0\u4ee3\u7801:pip install https://github.com/007gzs/xface/archive/master.zip\u5feb\u901f\u4f7f\u7528\u6ce8\u518c+\u8bc6\u522b:import xface\nimport cv2\n\nface_analysis = xface.FaceAnalysis()\nface_analysis.load()\nfor i in range(5):\n image = cv2.imread(\"label%d.jpg\" % i)\n faces = face_analysis.get_faces(image, max_num=1)\n if faces:\n face_analysis.register_face(\"label%d\" % i, faces[0].feature)\nfaces = face_analysis.get_faces(image)\nres = [\n {\n 'bbox': face.bbox,\n 'det_score': face.det_score,\n 'landmark': face.landmark,\n 'landmark_106': face.landmark_106,\n 'sim_face_ids': [{'face_id': face_id, 'sim': float(sim)} for face_id, sim in face.sim_face_ids or []]\n }\n for face in faces\n]\nprint(res)"} +{"package": "xfacereclib.book.FRaES2016", "pacakge-description": "Due to unfortunate communication the link to the experiments in the book chapter has not been updated. Please clickhereto download the actual package."} +{"package": "xfacereclib.extension.CSU", "pacakge-description": "FaceRecLib Wrapper classes for the CSU Face Recognition ResourcesThis satellite package to theFaceRecLibprovides wrapper classes for the CSU face recognition resources, which can be downloaded fromhttp://www.cs.colostate.edu/facerec.\nTwo algorithms are provided by the CSU toolkit (and also by this satellite package): the local region PCA (LRPCA) and the LDA-IR (also known as CohortLDA).For more information about the LRPCA and the LDA-IR algorithm, please refer to the documentation onhttp://www.cs.colostate.edu/facerec/.\nFor further information about theFaceRecLib, please readits Documentation.\nOn how to use this package in a face recognition experiment, please seehttp://pypi.python.org/pypi/xfacereclib.paper.BeFIT2012Installation InstructionsThe current package is just a set of wrapper classes for the CSU facerec2010 module, which is contained in theCSU Face Recognition Resources, where you need to download the Baseline 2011 Algorithms.\nPlease make sure that you have read installation instructions in theDocumentationof this package on how to patch the original source code to work with our algorithms, before you try to go on woth this package.NoteSince the original CSU resources are not Python3 compatible, this package only supports Python2.\nFor external dependencies of the CSU resources, please read theirREADME.TheFaceRecLiband parts of this package rely onBob, an open-source signal-processing and machine learning toolbox.\nForBobto be able to work properly, some dependent packages are required to be installed.\nPlease make sure that you have read theDependenciesfor your operating system.DocumentationFor further documentation on this package, please read theStable Versionor theLatest Versionof the documentation.For a list of tutorials on packages obBob, or information on submitting issues, asking questions and starting discussions, please visit its website."} +{"package": "xfacereclib.paper.BeFIT2012", "pacakge-description": "This package provides the source code to run the experiments published in the paperAn Open Source Framework for Standardized Comparisons of Face Recognition Algorithms.\nIt relies on theFaceRecLibto execute all face recognition experiments.\nMost of the face recognition algorithms are implemented inBob, while one of them is taken from theCSU Face Recognition Resources.NoteCurrently, this package only works in Unix-like environments and under MacOS.\nDue to limitations of the Bob library, MS Windows operating systems are not supported.\nWe are working on a port of Bob for MS Windows, but it might take a while.NoteThe experiments described in this section use theFaceRecLibin version 1.1.3,Bobin version 1.2.0 and the January 2012 release of theCSU Face Recognition Resources.\nThese versions are pin-pointed in thesetup.pyfile (see theinstall_requiressection).\nFor other versions, the results might be slightly different.InstallationThe installation of this package relies on theBuildOutsystem. By default, the command line sequence:$ python bootstrap.py\n$ bin/buildoutshould download and install most requirements, including theFaceRecLib, the Database interface packages for theBANCA databaseandthe Good, the Bad & the Ugly database, and, finally, theWrapper classes for the CSU Face Recognition Resources.\nUnfortunately, some packages must be installed manually:BobTo install the Bob toolkit, please visithttp://www.idiap.ch/software/bob/and follow the installation instructions.\nPlease verify that you have at least version 1.2.0 of Bob installed.\nIf you have installed Bob in a non-standard directory, please open thebuildout.cfgfile from the base directory and set the \u2018prefixes\u2019 directory accordingly.CSU Face Recognition ResourcesDue to the fact that the CSU toolkit needs to be patched to work with the FaceRecLib, the setup is unfortunately slightly more complicated.\nTo be able to run the experiments based on the CSU toolkit, i.e., the LDA-IR algorithm, please download the CSU Face Recognition Resources fromhttp://www.cs.colostate.edu/facerec.\nAfter unpacking the CSU toolkit, it needs to be patched.\nFor this reason, please follow the instructions:Patch the CSU toolkit:$ bin/buildout -c buildout-before-patch.cfg\n$ bin/patch_CSU.py [YOUR_CSU_SOURCE_DIRECTORY]Update thebuildout.cfgfile by modifying thesources-dir= [YOUR_CSU_SOURCE_DIRECTORY]entry to point to the base directory of the patched version of the CSU toolkit.Make sure that you update your installation byagaincalling:$ bin/buildoutNoteThe patch file is only valid for the current version of the CSU toolkit (last checked in December 2012).\nIf you have another version, please see theGetting helpsection.NoteAt Idiap, you can also use the pre-patched version of the CSU toolkit.\nJust use:$ bin/buildout -c buildout-idiap.cfginstead of downloading and patching the CSU toolkit.DatabasesOf course, we are not allowed to re-distribute the original images to run the experiments on.\nTo re-run the experiments, please make sure to have your own copy of theBANCAandthe Good, the Bad & the Uglyimages.DocumentationAfter installing you might want to create the documentation for this satellite package, which includes more detailed information on how to re-run the experiments and regenerate the scientific plots from the paper.\nTo generate and open the documentation execute:$ bin/sphinx-build docs sphinx\n$ firefox sphinx/index.htmlOf course, you can use any web browser of your choice.Getting helpIn case anything goes wrong, please feel free to open a new ticket in ourGitHub page, or send an email tomanuel.guenther@idiap.ch.Cite our paperIf you use theFaceRecLibor this package in any of your experiments, please cite the following paper:@inproceedings{Guenther_BeFIT2012,\n author = {G{\\\"u}nther, Manuel AND Wallace, Roy AND Marcel, S{\\'e}bastien},\n editor = {Fusiello, Andrea AND Murino, Vittorio AND Cucchiara, Rita},\n keywords = {Biometrics, Face Recognition, Open Source, Reproducible Research},\n month = oct,\n title = {An Open Source Framework for Standardized Comparisons of Face Recognition Algorithms},\n booktitle = {Computer Vision - ECCV 2012. Workshops and Demonstrations},\n series = {Lecture Notes in Computer Science},\n volume = {7585},\n year = {2012},\n pages = {547-556},\n publisher = {Springer Berlin},\n location = {Heidelberg},\n url = {http://publications.idiap.ch/downloads/papers/2012/Gunther_BEFIT2012_2012.pdf}\n}"} +{"package": "xfacereclib.paper.IET2014", "pacakge-description": "This package provides the source code to run the experiments published in the paperScore Calibration in Face Recognition.\nIt relies on theFaceRecLibto execute the face recognition experiments, and onBobto compute the calibration experiments.NoteCurrently, this package only works in Unix-like environments and under MacOS.\nDue to limitations of theBoblibrary, MS Windows operating systems are not supported.\nWe are working on a port ofBobfor MS Windows, but it might take a while.\nIn the meanwhile you could use ourVirtualBoximages that can be downloadedhere.InstallationThe installation of this package relies on theBuildOutsystem. By default, the command line sequence:$ ./python bootstrap.py\n$ ./bin/buildoutshould download and install all requirements, including theFaceRecLib, the database interfacesxbob.db.scface,xbob.db.mobioand all their required packages.\nThere are a few exceptions, which are not automatically downloaded:BobThe face recognition experiments rely on the open source signal-processing and machine learning toolboxBob.\nTo installBob, please visithttp://www.idiap.ch/software/boband follow the installation instructions.\nPlease verify that you have at least version 1.2.0 of Bob installed.\nIf you have installed Bob in a non-standard directory, please open the buildout.cfg file from the base directory and set theprefixesdirectory accordingly.NoteThe experiments that we report in thePaperwere generated with Bob version 1.2.1 andFaceRecLibversion 1.2.1.\nIf you use different versions of either of these packages, the results might differ slightly.\nFor example, we are aware that, due to some initialization differences, the results using Bob 1.2.0 and 1.2.1 are not identical, but similar.Image DatabasesThe experiments are run on external image databases.\nWe do not provide the images from the databases themselves.\nHence, please contact the database owners to obtain a copy of the images.\nThe two databases used in our experiments can be downloaded here:SCface [scface]:http://www.scface.orgMOBIO [mobio]:http://www.idiap.ch/dataset/mobioNoteFor the MOBIO database, you need to sign the EULA to get access to the data \u2013 the process is explained under the above MOBIO link.\nAfter signing the EULA, please download the image filesIMAGES_PNG.tar.gzand the annotation filesIMAGE_ANNOTATIONS.tar.gzand extract the archives into directories of your choice.Important!After downloading the databases, you will need to tell our software, where it can find them by changing theconfiguration files.\nIn particular, please update thescface_directoryinxfacereclib/paper/IET2014/database_scface.py, as well asmobio_image_directoryandmobio_annotation_directoryinxfacereclib/paper/IET2014/database_mobio.py.\nPlease let all other configuration parameters unchanged as this might influence the face recognition experiments and, hence, the reproducibility of the results.Getting helpIn case anything goes wrong, please feel free to open a new ticket in ourGitLabpage, or send an email tomanuel.guenther@idiap.ch.Recreating the results of thePaperAfter successfully setting up the databases, you are now able to run the face recognition and calibration experiments as explained in thePaper.The experiment configurationThe face recognition experiment are run using theFaceRecLib, but for convenience there exists a wrapper script that set up the right parametrization for the call to theFaceRecLib.\nThe configuration files that are used by theFaceRecLib, which contain all the parameters of the experiments, can be found in thexfacereclib/paper/IET2014/directory.\nParticularly, thexfacereclib/paper/IET2014/dct_mobio.pyandxfacereclib/paper/IET2014/isv_mobio.pyfiles contain the configuration for the DCT block features and the ISV algorithm as described in thePaper.\nAccordingly,Running the experimentsThis script can be found inbin/iet2014_face_recog.py.\nIt requires some command line options, which you can list using./bin/iet2014_face_recog.py--help.\nUsually, the command line options have a long version (starting with--) and a shortcut (starting with a single-), here we use only the long versions:--temp-directory: Specify a directory where temporary files will be stored (default:temp). This directory can be deleted after all experiments ran successfully.--result-directory: Specify a directory where final result files will be stored (default:results). This directory is required to evaluate the experiments.--databases: Specify a list of databases that you want your experiments to run on. Possible values arescfaceandmobio. By default, experiments on both databases are executed.--protocols: Specify a list of protocols that you want to run. Possible values arecombined,close,mediumandfarfor databasescface, andmaleandfemaleformobio. By default, all protocols are used.--combined-zt-norm: Execute the face recognition experiments on the SCface database with combined ZT-norm cohort.--verbose: Print out additional information or debug information during the execution of the experiments. The--verboseoption can be used several times, increasing the level to Warning (1), Info (2) and Debug (3). By default, only Error (0) messages are printed.--dry-run: Use this option to print the calls to theFaceRecLibwithout executing them.Additionally, you can pass options directly to theFaceRecLib, but you should do that with care.\nSimply use--to separate options to thebin/iet2014_face_recog.pyfrom options to theFaceRecLib.\nFor example, the--forceoption might be of interest.\nSee./bin/faceverify.py--helpfor a complete list of options.It is advisable to use the--dry-runoption before actually running the experiments, just to see that everything is correct.\nAlso, the Info (2) verbosity level prints useful information, e.g., by adding the--verbose--verbose(or shortly-vv) on the command line.\nA commonly used command line sequence to execute the face recognition algorithm on both databases could be:Run the experiments on the MOBIO database:$ ./bin/iet2014_face_recog.py -vv --databases mobioRun the experiments on the SCface database, using protocol-specific files for the ZT-norm:$ ./bin/iet2014_face_recog.py -vv --databases scfaceRun the experiments on the SCface database, using files from all distance conditions for the ZT-norm:$ ./bin/iet2014_face_recog.py -vv --databases scface --combined-zt-norm --protocols close medium farNoteAll output directories of the scripts will be automatically generated if they do not exist yet.WarningThe execution of the script may take a long time and require large amounts of memory \u2013 especially on the MOBIO database.\nNevertheless, the scripts are set up such that they re-use all parts of the experiments as far as this is possible.Evaluating the experimentsAfter all experiments have finished successfully, the resulting score files can be evaluated.\nFor this, thebin/iec2014_evaluate.pyscript can be used to create the Tables 3, 4, 5 and 6 of thePaper, simply by writing LaTeX-compatible files that can later be interpreted to generate the tables.Generating output filesAlso, all information are written to console (when using the-vvvoption to enable debug information), including:The\\(C^{\\mathrm{min}}_{\\mathrm{ver}}\\)of the development set, the\\(C^{\\mathrm{min}}_{\\mathrm{ver}}\\)of the evaluation set and the\\(C_{\\mathrm{ver}}\\)of the evaluation set based on the optimal threshold on the development set.The\\(C_{\\mathrm{frr}}\\)on both development and evaluation set, using the threshold defined atFAR=1%of the development set.The\\(C_{\\mathrm{ver}}\\)on the development and evaluation set, when applying threshold\\(\\theta_0=0\\)(mainly useful for calibrated scores).The\\(C_{\\mathrm{cllr}}\\)performance on the development and the evaluation set.The\\(C^{\\mathrm{min}}_{\\mathrm{cllr}}\\)performance on the development and the evaluation set.All these numbers are computed with and without ZT score normalization, and before and after score calibration.To run the script, some command line parameters can be specified, see./bin/iec2014_evaluate.py--help:--result-directory: Specify the directory where final result files are stored (default:results). This should be the same directory as passed to thebin/iec2014_execute.py`script.--databases: Specify a list of databases that you want evaluate. Possible values arescfaceandmobio. By default, both databases are evaluated.--protocols: Specify a list of protocols that you want to evaluate. Possible values arecombined,close,mediumandfarfor databasescface, andmaleandfemaleformobio. By default, all protocols are used.--combined-zt-norm: Evaluate the face recognition experiments on the SCface database with combined ZT-norm cohort.--combined-threshold: Evaluate the face recognition experiments on the SCface database by computing the threshold on the combined development set.--latex-directory: The directory, where the final score files will be placed into, by default this directory islatex.Again, the most usual way to compute the resulting tables could be:Evaluate experiments on MOBIO:$ bin/iet2014_evaluate.py -vvv --database mobioEvaluate experiments on SCface with distance-dependent ZT-norm:$ bin/iet2014_evaluate.py -vvv --database scfaceEvaluate experiments on SCface with distance-independent ZT-norm:$ bin/iet2014_evaluate.py -vvv --database scface --combined-zt-norm --protocols close medium farEvaluate experiments on SCface with distance-independent threshold (will mainly change the\\(C_{\\mathrm{ver}}\\)of the evaluation set):$ bin/iet2014_evaluate.py -vvv --database scface --combined-threshold --protocols close medium farThe experiments to compare linear calibration with categorical calibration as given in Table 7 of thePaperare run using thebin/iet2014_categorical.pyscript:$ bin/iet2014_categorical.py -vvvGenerate the LaTeX tablesFinally, the LaTeX tables can be regenerated by defining the accordant\\Resultand\\ResultAtZeroLaTeX macros and include the resulting files.\nE.g., to create Table 3 of thePaper, define:\\newcommand\\ResultIII[2]{\\\\}\n\\newcommand\\ResultII[9]{#1\\,\\% \\ResultIII}\n\\newcommand\\Result[9]{#1\\,\\% & #4\\,\\% & #2\\,\\% & #3\\,\\% & #5\\,\\% & #6\\,\\% & #9\\,\\% & #7\\,\\% & #8\\,\\% &\\ResultII}\n\\newcommand\\ResultAtZero[8]{}set up yourtabularenvironment with 10 columns and input at according places:\\input{latex/mobio_male}\n\\input{latex/mobio_female}\n\\input{latex/scface_close}\n\\input{latex/scface_medium}\n\\input{latex/scface_far}\n\\input{latex/scface_combined}Accordingly, the other tables can be generated from files:Table 4a):latex/scface_close-zt.tex,latex/scface_medium-zt.texandlatex/scface_far-zt.texTable 4b):latex/scface_close-thres.tex,latex/scface_medium-thres.texandlatex/scface_far-thres.texTables 5 and 6:latex/mobio_male.tex,latex/mobio_female.tex,latex/scface_close-zt.tex,latex/scface_medium-zt.tex,latex/scface_far-zt.texandlatex/scface_combined.tex.Table 7:latex/calibration-none.tex,latex/calibration-linear.texandlatex/calibration-categorical.texGenerate the score distribution plotsAt the end, also the score distribution plots that are shown in Figures 3 and 4 of thePapercan be regenerated.\nThese plots require the face recognition experiments to have finished, and also the categorical calibration to have run.\nAfterwards, the scriptbin/iet2014_plot.pycan be executed.\nAgain, the script has a list of command line options:--result-directory: Specify the directory where final result files are stored (default:results). This should be the same directory as passed to thebin/iec2014_execute.py`script.--figure: Specify, which figure you want to create. Possible values are 3 and 4.--output-file: Specify the file, where the plots should be written to. By default, this isFigure_3.pdforFigure_4.pdffor--figure3or--figure4, respectively.Hence, running:$ ./bin/iet2014_plot.py -vv --figure 3\n$ ./bin/iet2014_plot.py -vv --figure 4should be sufficient to generate the plots."} +{"package": "xfacereclib.paper.IET2015", "pacakge-description": "This package provides the source code to run the experiments published in the paperImpact of Eye Detection Error on Face Recognition Performance.\nIt relies on theFaceRecLibto execute the face recognition experiments, which in turn uses the face recognition algorithms and the database interface ofBob.NoteCurrently, this package only works in Unix-like environments and under MacOS.\nDue to limitations of theBoblibrary, MS Windows operating systems are not supported.\nWe are working on a port ofBobfor MS Windows, but it might take a while.\nIn the meanwhile you could use ourVirtualBoximages that can be downloadedhere.When you use this source code in a scientific publication, we would be happy if you would cite:@article{Dutta2015,\n author = \"Abhishek Dutta and Manuel G\\\"unther and Laurent El Shafey and S\\'ebastien Marcel\",\n title = \"Impact of Eye Detection Error on Face Recognition Performance\",\n year = 2015\n journal = {IET Biometrics},\n issn = {2047-4938},\n url = {http://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2014.0037},\n pdf = {http://publications.idiap.ch/downloads/papers/2015/Dutta_IETBIOMETRICS_2014.pdf}\n}InstallationThis package uses severalBoblibraries, which will be automatically installed locally using the command lines as listed below.\nHowever, in order for theBobpackages to compile, certainDependenciesneed to be installed.This packageThe installation of this package relies on theBuildOutsystem.\nBy default, the command line sequence:$ ./python bootstrap-buildout.py\n$ ./bin/buildoutshould download and install all required packages ofBobin the versions that we used to produce the results.\nOther versions of the packages might generate sightly different results.\nTo use the latest versions of allBobpackages, please remove the strict version numbers that are given in thebuildout.cfgfile in the main directory of this package.Image DatabaseThe experiments are run on an external image database.\nWe do not provide the images from the database themselves.\nHence, please contact the database owners to obtain a copy of the images.\nThe Multi-PIE database used in our experiments can be downloadedhere.NoteUnfortunately, the Multi-PIE database is not free of charge.\nIf you do not have a copy of the database yet, and you are not willing to pay for it, you cannot reproduce the results of the paper directly.\nNevertheless, you can use other databases, some of which are free of charge.\nA complete list of supported databases and their according evaluation protocols can be found in theFaceRecLibdocumentation.Important!After downloading the databases, you will need to tell our software, where it can find them by changing theconfiguration file.\nIn particular, please update theMULTIPIE_IMAGE_DIRECTORYinxfacereclib/paper/IET2015/configuration/database.py.Unpacking the AnnotationsAfter the database is set up correctly, you\u2019ll need to unpack the eye annotations that are used in the experiments.\nPlease run the script:$ ./bin/unpack_annotationsto extract the annotations in the desired directory structure.\nIf you want, you can specify another directory to unpack the annotations (see./bin/unpack_annotations.py--help), but all other functions and configurations will have their defaults set according to the default directory.Testing your InstallationAfter you have set up the database, you should be able to run our test suite:$ ./bin/nosetestsPlease make sure that all tests pass.TODO:Implement tests.Getting helpIn case anything goes wrong, please feel free to open a new ticket in ourGitHubpage, start a new discussion in ourMailing Listor send an email tomanuel.guenther@idiap.ch.Recreating the Results of thePaperAfter successfully setting up the database, you are now able to run the face recognition experiments as explained in thePaper.\nParticularly, you will be able to reproduce Figure 4, Figure 7 and Figure 13.\nBe aware that we were running more than 1000 individual face recognition experiments, each of which used a slightly different experiment configuration.The Experiment ConfigurationThe face recognition experiment are run using theFaceRecLib.\nIn total, we are testing five different face recognition algorithms, each of which uses thedefault configurationfrom theFaceRecLib:eigenfaces: a PCA is trained on pixel gray values, and the projected features are compared with Euclidean distance.fisherfaces: a combined PCA + LDA matrix is trained on pixel gray values, and the projected features are compared with Euclidean distance.gabor-jet: Gabor jets are extracted at grid locations in the image and compared with a Gabor-phase-based similarity function.lgbphs: extended local Gabor binary pattern histogram sequences are extracted from image blocks, and the histograms are compared with histogram intersection.isv: DCT features are extracted from image blocks and modeled with a Gaussian mixture model and an additional inter-session variability model, and the score is computed as a likelihood ratio.As input, all these algorithms expect images, where the face is extracted and aligned, so that the eye centers are always placed on the same location in the image.\nFor this alignment procedure, labeled eye locations must be available.\nThe main focus of this paper isnoton the face recognition algorithms themselves, but on how they perform in case that the eye locations are slightly misplaced, as it might happen in both manual and automatic annotations.Running the ExperimentsFor convenience, we have generated a wrapper script that allows to run a set of face recognition experiments in sequence \u2013 or even in parallel, see below.\nThis wrapper scriptabusesone functionality of theFaceRecLib, namely theparameter testing, which is an easy way to perform a grid search on a set of parameters.\nFor our purposes, these parameters are:Figure 4: the eye position shifts in horizontal and vertical direction, as well as the rotation angle.Figure 7: the standard deviations of the Normal distributed shifts of eye positions in horizontal and vertical direction, as well as a random seed.The according configurations are given infixed_perturbation.py(Figure 4) andrandom_perturbation.py(Figure 7).\nThere, you can find the setup as it was used to generate the according plots, but in case you want to run only a sub-set of experiments, you can reduce the parameters in each list.The experiments can be run using the./bin/parameter_test.pyscript.\nThis script has several options, the most important of which are:--configuration-file: the configuration file that contains the parameters that we want to test.\nFor our experiments, these are the two filesfixed_perturbation.py(Figure 4) andrandom_perturbation.py(Figure 7).--database: the database that should be used in the experiments, which will bemultipie-min all cases.--executable: the (pythonic) name of the face verification function that will be executed.\nSince we had to modify the default script a bit, our script needs to be specified (see below).--sub-directory: the name of a directory (will be created on need), where all experiments for the given configuration file are stored.--grid: a name of a grid configuration to run algorithms in parallel (see below).--verbose: Print out additional information or debug information during the execution of the experiments.\nThe--verboseoption can be used several times, increasing the level to Warning (1), Info (2) and Debug (3). By default, only Error (0) messages are printed.\nThe Info (aka-vv) option is recommended.--dry-run: Use this option to print the calls to theFaceRecLibwithout executing them.\nAgain, it is recommended to use this flag once, i.e., to check that everything is correct before running the experiments.Additionally, parameters can be passed directly to the./bin/faceverify.pyscript from theFaceRecLib.\nPlease use a--to separate parameters for./bin/faceverify.pyform parameters for./bin/parameter_test.py.\nUseful parameters might be the--result-directoryand the--temp-directoryoptions.\nFor a complete list of options, please check./bin/faceverify.py--help.Finally, the command lines to run the experiments for Figures 4 and 7, call:$ ./bin/parameter_test.py --configuration-file fixed_perturbation.py --database multipie-m --sub-directory fixed --executable xfacereclib.paper.IET2015.script.faceverify -- --temp-directory [YOUR_TEMP_DIRECTORY] --result-directory [YOUR_RESULT_DIRECTORY]\n\n$ ./bin/parameter_test.py --configuration-file random_perturbation.py --database multipie-m --sub-directory random --executable xfacereclib.paper.IET2015.script.faceverify -- --temp-directory [YOUR_TEMP_DIRECTORY] --result-directory [YOUR_RESULT_DIRECTORY]The last set of experiments, i.e., to regenerate Figure 13 can be run using the./bin/annotation_typesscript.\nAgain, this script has a set of options, most of which have proper default values:--image-directory: the base directory of the Multi-PIE database; needs to be specified.--annotation-directory: the base directory, where the annotations have been extracted to.--algorithms: a list of algorithms that should be tested; by default all five algorithms are run.--world-types: a list of annotation types, which should serve to train the algorithms and to enroll the models with.--probe-types: a list of annotation types, which should be probed against the enrolled models.Again, the same--verboseoption and options passed to the./bin/faceverify.pyscript exists.\nHence, the last set of experiments to be run can be started with:$ ./bin/annotation_types --image-directory [MULTIPIE_IMAGE_DIRECTORY] -vv -- --temp-directory [YOUR_TEMP_DIRECTORY] --result-directory [YOUR_RESULT_DIRECTORY]Parallel ExecutionSince the two command lines above execute more than 1000 individual face recognition algorithms, you might want to run them in parallel.\nFor this purpose, you can use the--gridoption of the./bin/parameter_test.pyscript.\nThis will trigger the usage ofGridTK, a tool originally developed to submit and monitor jobs in an SGE processing farm.\nIf you have access to such a farm, you can use the--gridsgeoption to submit the experiments to the SGE grid (you might need to set up the SGE configuration in the grid configuration filexfacereclib/paper/IET2015/configuration/grid.py, in thefacereclib/utils/grid.pyof theFaceRecLibor in theGridTKitself).On the other hand, when you have a powerful machine with lots of processing units, you can use the--gridlocaloption.\nThis will submit jobs to the \u201clocal\u201d queue, which you have to start them manually by:$ ./bin/jman --local --database [DIR]/submitted.sql3 -vv run-scheduler --parallel [NUMBER_OF_SLOTS] --die-when-finishedPlease refer to theGridTKmanual for more details.NoteWhen submitting to the either the local queue or the SGE, several job databases calledsubmitted.sql3are stored in sub-directories of thegrid_dbdirectory.\nYou can use./bin/jman--database[DIR]/submitted.sql3listto see the current status of the jobs stored in the given database.\nOf course, you can also use the default SGE tools (such asqstat) to check the statuses of the jobs.WarningFor the random experiment, please do not use more than one parallel job to preprocess the images.\nOtherwise, the random seed might be applied several times, leading to inexact results.NoteThe same--gridoption can be used for the./bin/annotation_typesscript.\nHere, only onesubmitted.sql3file is written, in the current directory.Evaluating the ExperimentsAfter all experiments have finished successfully, the resulting score files can be evaluated.\nThe figures in the paper were generated using a mix of python and R scripts, i.e., to make them look more beautiful.\nHowever, for this package we will plot the figures solely using matplotlib.\nThe./bin/plot_resultsscript can be used to create the plots similar to the ones in Figures 4, 7 and 13.\nAdditionally, it will write.csvfiles containing the exact numbers, i.e., the Figures in in thePaperrely on these files.As usual, the./bin/plot_resultshas a list of command line options, most of which have proper default values:--scores-directory: the base directory, where the score files have been produced.--experiments: a list of experiments to evaluate.\nBy default, all three experiments are evaluated.--algorithms: a list of algorithms to evaluate.\nBy default, all five algorithms are evaluated.Some more options are available, see./bin/plot_results--helpfor a complete list.\nHence, to produce all three plots from Figures 4, 7, and 13, simply call:$ ./bin/plot_results -vv --scores-directory [YOUR_RESULT_DIRECTORY]Afterward, the plots can be found in theplotsdirectory.\nFor Figure 4, they are calledHTER_fixed.pdfandAUC_fixed.pdf, while for Figure 7 they areHTER_random.pdfandAUC_random.pdf.\nThe HTER plots should be identical to the ones found in thePaper.\nThe AUC plots have a different color coding than in thePaper, but the contents are identical.\nFinally, the fileplots/ROCs.pdfcontains the ROC curves of Figure 13, except that the FAR range is slightly higher."} +{"package": "xfact", "pacakge-description": "readme"} +{"package": "xfact-lm", "pacakge-description": "readme"} +{"package": "xfactor", "pacakge-description": "No description available on PyPI."} +{"package": "xf-aes-gcm", "pacakge-description": "AES-GCM en-/decryption, with AEAD and support for Xpressfeed passwordsThis package's aim is to be able to handle general AES-GCM encryption and decryption, while still providing the constants and functionality required to inter-operate with S&P Global's Xpressfeed applications, as they use the same algorithm.In essence, this package should be capable of producing and reading the same ciphertexts as the Xpressfeed applications.InstallingFirst, ensure you are installing into a virtual environment:python3 -m venv venv\nsource ./venv/bin/activate\npip install --upgrade pipThen usepipto install this package and its dependencies:pip install -v \\\n--upgrade --force-reinstall \\\nxf-aes-gcmThere may be more recent, or beta, packages in the Test PyPI repository. To obtain one of these packages add the option--extra-index-url https://test.pypi.org/simple/to the above command.Command-line usagexf-aes-gcm[-h|--help] [-v|--version]____________ [-k KEY] [-i IV] [-t TAG_LEN] [-f [F]] [-a AAD]____________ [--no-verify] [{ENC,DEC}]Usexf-aes-gcm-hto bring up more details on these options and their default values, as well as several examples of how to use this package."} +{"package": "xfail", "pacakge-description": "XFail provides a decorator functionxfailto skip expected exceptions.\nSimilar to unittest.skipIf, butxfailcan specify which exception should be\nskipped, and raise if the decorated function is unexpectedly passed (only ifstrictisTrue).InstallSupported python versions are: 2.7, 3.4, 3.5, 3.6Can be installed from PyPI by pip:pip install xfailUsagexfail decoratorxfailaccepts two arguments,exceptionsandstrict.The first argument (exceptions) should be an Exception class to skip (Ex.Exception,AssertionError, and so on). If you want to skip multiple\nexceptions, use tuple of them, for example,@xfail((AssertionError,ValueError)).The second argumentstrictshould be a boolean. IfstrictisFalse(by default) and passed unexpectedly, raiseunittest.SkipTestexception,\nwhich will mark the test is skipped. This case is very similar to the function\nis decorated byuniteest.skipfunction and the test will be counted as\nskipped.If it isTrueand the decorated function did not raise (any of) the\nexpected exception(s),XPassFailureexception would be raised.\nIn this case, the test will be counted as fail.fromxfailimportxfail@xfail(IndexError)defget(l,index):returnl[index]l=[1,2,3]get(4)# no errorAlso supports multiple exceptions:@xfail((IndexError,ValueError))defa():'''This function passes IndexError and ValueError\n ...In test script, similar tounittest.TestCase.assertRaises:fromunittestimportTestCasefromxfailimportxfailclassMyTest(TestCase):deftest_1(self):@xfail(AssertionError)defshould_raise_error():assertFalsea()# test passesdeftest_2(self):@xfail(AssertionError,strict=True)defshould_raise_error():assertTruea()# test failes, since this function should raise AssertionError# Can be used for test function@xfail(AssertionError,strict=True)deftest_3(self)assertFalse# This test will fail@xfail(AssertionError,strict=True)deftest_3(self)assertTrueFor more exapmles, seetest_xfail.py."} +{"package": "xfaster", "pacakge-description": "DescriptionImplementation by A. Gambrel, A. Rahlin, C. Contaldi.XFaster is a fast power spectrum and likelihood estimator for CMB datasets. It\nhas most recently been used for the SPIDER B-mode polarization results, but is\nintended to be generically useful for modern CMB observatories.An accompanying paper describing the algorithm can be found here:https://arxiv.org/abs/2104.01172Documentation can be found here:https://spidercmb.github.io/xfaster/xfaster:python packagedocs:documentation on usage, file structure, etc.example:an example configuration for running xfasterTo get started, install xfaster:pip install xfaster"} +{"package": "xfastertransformer", "pacakge-description": "xFasterTransformerxFasterTransformer is an exceptionally optimized solution for large language models (LLM) on the X86 platform, which is similar to FasterTransformer on the GPU platform. xFasterTransformer is able to operate in distributed mode across multiple sockets and nodes to support inference on larger models. Additionally, it provides both C++ and Python APIs, spanning from high-level to low-level interfaces, making it easy to adopt and integrate.Table of ContentsxFasterTransformerTable of ContentsModels overviewModel support matrixDataType support listDocumentsInstallationFrom PyPIUsing DockerBuilt from sourcePrepare EnvironmentManuallyDockerHow to buildModels PreparationAPI usagePython API(PyTorch)C++ APIHow to runSingle rankMulti ranksCommand lineCodePythonC++Web DemoBenchmarkSupportQ&AModels overviewLarge Language Models (LLMs) develops very fast and are more widely used in many AI scenarios. xFasterTransformer is an optimized solution for LLM inference using the mainstream and popular LLM models on Xeon. xFasterTransformer fully leverages the hardware capabilities of Xeon platforms to achieve the high performance and high scalability of LLM inference both on single socket and multiple sockets/multiple nodes.xFasterTransformer provides a series of APIs, both of C++ and Python, for end users to integrate xFasterTransformer into their own solutions or services directly. Many kinds of example codes are also provided to demonstrate the usage. Benchmark codes and scripts are provided for users to show the performance. Web demos for popular LLM models are also provided.Model support matrixModelsFrameworkDistributionPyTorchC++ChatGLM\u2714\u2714\u2714ChatGLM2\u2714\u2714\u2714ChatGLM3\u2714\u2714\u2714Llama\u2714\u2714\u2714Llama2\u2714\u2714\u2714Baichuan\u2714\u2714\u2714QWen\u2714\u2714\u2714SecLLM(YaRN-Llama)\u2714\u2714\u2714Opt\u2714\u2714\u2714DataType support listFP16BF16INT8W8A8INT4NF4BF16_FP16BF16_INT8BF16_W8A8BF16_INT4BF16_NF4W8A8_INT8W8A8_int4W8A8_NF4DocumentsxFasterTransformer Documents andWikiprovides the following resources:An introduction to xFasterTransformer.Comprehensive API references for both high-level and low-level interfaces in C++ and PyTorch.Practical API usage examples for xFasterTransformer in both C++ and PyTorch.InstallationFrom PyPIpipinstallxfastertransformerUsing Dockerdockerpullintel/xfastertransformer:latestBuilt from sourcePrepare EnvironmentManuallyPyTorchv2.0 (When using the PyTorch API, it's required, but it's not needed when using the C++ API.)pipinstalltorch--index-urlhttps://download.pytorch.org/whl/cpuDockerBuild docker image from Dockerfiledockerbuild\\-fdockerfiles/Dockerfile\\--build-arg\"HTTP_PROXY=${http_proxy}\"\\--build-arg\"HTTPS_PROXY=${https_proxy}\"\\-tintel/xfastertransformer:dev-ubuntu22.04.Then run the docker with the command (Assume model files are in/data/directory):dockerrun-it\\--namexfastertransformer-dev\\--privileged\\--shm-size=16g\\-v\"${PWD}\":/root/xfastertransformer\\-v/data/:/data/\\-w/root/xfastertransformer\\-e\"http_proxy=$http_proxy\"\\-e\"https_proxy=$https_proxy\"\\intel/xfastertransformer:dev-ubuntu22.04Notice!!!: Please enlarge--shm-sizeifbus erroroccurred while running in the multi-ranks mode . The default docker limits the shared memory size to 64MB and our implementation uses many shared memories to achieve a better performance.How to buildUsing 'CMake'# Build xFasterTransformergitclonehttps://github.com/intel/xFasterTransformer.gitxFasterTransformercdxFasterTransformer\ngitcheckout# Please make sure torch is installed when run python examplemkdirbuild&&cdbuild\ncmake..\nmake-jUsingpython setup.py# Build xFasterTransformer library and C++ example.pythonsetup.pybuild# Install xFasterTransformer into pip environment.# Notice: Run `python setup.py build` before installation!pythonsetup.pyinstallModels PreparationxFasterTransformer supports a different model format from Huggingface, but it's compatible with FasterTransformer's format.Download the huggingface format model firstly.After that, convert the model into xFasterTransformer format by using model convert module in xfastertransformer. If output directory is not provided, converted model will be placed into${HF_DATASET_DIR}-xft.python -c 'import xfastertransformer as xft; xft.LlamaConvert().convert(\"${HF_DATASET_DIR}\",\"${OUTPUT_DIR}\")'Supported model convert list:LlamaConvertChatGLMConvertChatGLM2ConvertChatGLM3ConvertOPTConvertBaichuanConvertQwenConvertAPI usageFor more details, please see API document andexamples.Python API(PyTorch)Firstly, please install the dependencies.Python dependenciespipinstall-rrequirements.txtoneCCL (For multi ranks)Install oneCCL and setup the environment. Please refer toPrepare Environment.xFasterTransformer's Python API is similar to transformers and also supports transformers's streamer to achieve the streaming output. In the example, we use transformers to encode input prompts to token ids.importxfastertransformerfromtransformersimportAutoTokenizer,TextStreamer# Assume huggingface model dir is `/data/chatglm-6b-hf` and converted model dir is `/data/chatglm-6b-xft`.MODEL_PATH=\"/data/chatglm-6b-xft\"TOKEN_PATH=\"/data/chatglm-6b-hf\"INPUT_PROMPT=\"Once upon a time, there existed a little girl who liked to have adventures.\"tokenizer=AutoTokenizer.from_pretrained(TOKEN_PATH,use_fast=False,padding_side=\"left\",trust_remote_code=True)streamer=TextStreamer(tokenizer,skip_special_tokens=True,skip_prompt=False)input_ids=tokenizer(INPUT_PROMPT,return_tensors=\"pt\",padding=False).input_idsmodel=xfastertransformer.AutoModel.from_pretrained(MODEL_PATH,dtype=\"bf16\")generated_ids=model.generate(input_ids,max_length=200,streamer=streamer)C++ APISentencePiececan be used to tokenizer and detokenizer text.#include#include#include\"xfastertransformer.h\"// ChatGLM token ids for prompt \"Once upon a time, there existed a little girl who liked to have adventures.\"std::vectorinput({3393,955,104,163,6,173,9166,104,486,2511,172,7599,103,127,17163,7,130001,130004});// Assume converted model dir is `/data/chatglm-6b-xft`.xft::AutoModelmodel(\"/data/chatglm-6b-xft\",xft::DataType::bf16);model.config(/*max length*/100,/*num beams*/1);model.input(/*input token ids*/input,/*batch size*/1);while(!model.isDone()){std::vectornextIds=model.generate();}std::vectorresult=model.finalize();for(autoid:result){std::cout<input_ids;model.input(/*input token ids*/input_ids,/*batch size*/1);while(!model.isDone()){model.generate();}}Web DemoA web demo based onGradiois provided in repo. Now support ChatGLM, ChatGLM2 and Llama2 models.Perpare the model.Install the dependenciespipinstall-rexamples/web_demo/requirements.txtRun the script corresponding to the model. After the web server started, open the output URL in the browser to use the demo. Please specify the paths of model and tokenizer directory, and data type.transformer's tokenizer is used to encode and decode text so${TOKEN_PATH}means the huggingface model directory. This demo also support multi-rank.# Recommend preloading `libiomp5.so` to get a better performance.# `libiomp5.so` file will be in `3rdparty/mklml/lib` directory after build xFasterTransformer.LD_PRELOAD=libiomp5.sopythonexamples/web_demo/ChatGLM.py\\--dtype=bf16\\--token_path=${TOKEN_PATH}\\--model_path=${MODEL_PATH}BenchmarkBenchmark scripts are provided to get the model inference performance quickly.Prepare the model.Install the dependencies, including oneCCL and python dependencies.Enter thebenchmarkfolder and runrun_benchmark.sh. Please refer toBenchmark READMEfor more information.Notes!!!: The system and CPU configuration may be different. For the best performance, please try to modify OMP_NUM_THREADS, datatype and the memory nodes number (check the memory nodes usingnumactl -H) according to your test environment.SupportxFasterTransformer email:xft.maintainer@intel.comxFasterTransformerwechatQ&AQ: Can xFasterTransformer run on a Intel\u00ae Core\u2122 CPU?A: No. xFasterTransformer requires support for the AMX and AVX512 instruction sets, which are not available on Intel\u00ae Core\u2122 CPUs.Q: Can xFasterTransformer run on the Windows system?A: There is no native support for Windows, and all compatibility tests are only conducted on Linux, so Linux is recommended.Q: Why does the program freeze or exit with errors when running in multi-rank mode after installing the latest version of oneCCL through oneAPI?A: Please try downgrading oneAPI to version 2023.x or below, or use the provided script to install oneCCL from source code.Q: Why does running the program using two CPU sockets result in much lower performance compared to running on a single CPU socket?A: Running in this way causes the program to engage in many unnecessary cross-socket communications, significantly impacting performance. If there is a need for cross-socket deployment, consider running in a multi-rank mode with one rank on each socket.Q:The performance is normal when running in a single rank, but why is the performance very slow and the CPU utilization very low when using MPI to run multiple ranks?A:This is because the program launched through MPI readsOMP_NUM_THREADS=1, which cannot correctly retrieve the appropriate value from the environment. It is necessary to manually set the value ofOMP_NUM_THREADSbased on the actual situation.Q: Why do I still encounter errors when converting already supported models?A: Try downgradingtransformerto an appropriate version, such as the version specified in therequirements.txt. This is because different versions of Transformer may change the names of certain variables."} +{"package": "xf-auth", "pacakge-description": "No description available on PyPI."} +{"package": "xfce4_terminal_themes", "pacakge-description": "# xfce4-terminal-themesSwitch xfce4-terminal themes with ease!## Installation```bash$ pip install xfce4_terminal_themes```## UsageYou need to create a `$XDG_HOME/xfce4/terminal/themes` file.It's anatomy is:```ini[Theme Name]AnyPropertyThat = xfce4 terminal understands[Theme Name 2]FontName = Terminus 11[Theme Name 3]ColorForeground = #123456```Then, you can list themes, see the current theme, and set themes.### List themes:```sh$ ./xfce4-terminal-themes -lTheme Name 1Theme Name 2Theme Name 3```### Current theme:```sh$ ./xfce4-terminal-themes -cTheme name: Theme Name 2Font name: TerminusFont size: 11```### Set theme:```sh$ ./xfce4-terminal-themes \"Theme Name 3\"```## Contributing1. Fork it ( https://github.com/[my-github-username]/pianobar_notify/fork )2. Create your feature branch (`git checkout -b my-new-feature`)3. Commit your changes (`git commit -am 'Add some feature'`)4. Push to the branch (`git push origin my-new-feature`)5. Create a new Pull Request"} +{"package": "xfcs", "pacakge-description": "Extract metadata and data from FCS (3.0, 3.1) files.Data extraction supports file formats:Mode: List (L)Datatypes: I, F, DImplemented parameter data set options:rawchannel valuesscale values (log10, gain)channel and scale combined into one data setfluorescence compensationlog10 scaled fluorescence compensationMetadata extraction features:support for non-compliant filesmerge or separate csv filesrolling mean for any keyword with a numeric valueappend new fcs files to previously generated metadata csv fileInteractive dashboard plots using thexfcsdashboardadd-on module.InstallationUsing pip:pip install xfcsWithout pip:python setup.py installCommand Line UsageSeeUSAGEfor expanded details.To see a list of available commands and arguments, run \u2018\u2019xfcs data \u2013help\u2019\u2019 or \u2018\u2019xfcs metadata \u2013help\u2019\u2019extract data: xfcs data [options]\nextract metadata: xfcs metadata [options]RequirementsPython 3.5 or greaternumpypandasLicensexfcs is released under the BSD 2-clause license. SeeLICENSEfor details."} +{"package": "xfcsdashboard", "pacakge-description": "Create interactive plots for FCS file metadata (3.0, 3.1).Metadata plots are generated as a self contained html file.\nMultiple display options are provided to hide or show parameters, calculated mean values, and customized time range.\nBy default, all numeric parameters located will be displayed. Parameters displayed can be located on the right side of the plot.\nTo hide (or display) a parameter, click on its name.\nTo hide all except one parameter, double click on its name.InstallationUsing pip:pip install xfcsdashboardWithout pip:python setup.py installCommand Line UsageFor stand alone usage:xfcsdashboard -i Used in combination with metadata extraction in xfcs (requires xfcs installed):xfcsmeta [--options] --dashboardRequirementsPython 3.5 or greaterpandasplotlyLicensexfcsdashboard is released under the BSD 2-clause license. SeeLICENSEfor details."} +{"package": "xfdfgen", "pacakge-description": "xfdfgenxfdfgen is a Python library for creating xfdf files that can be used to populate pdf form fields.InstallationUse the package managerpipto install xfdfgen.pipinstallxfdfgenUsagefromxfdfgenimportXfdfpdf_document_name='example_document.pdf'dictionary_of_fields={'first_name':'foo','last_name':'bar'}document=Xfdf(pdf_document_name,dictionary_of_fields)output_path='example_out.xfdf'document.write_xfdf(output_path)pdf_document_name should match the name of the document containing the form fields you want to fill in.The keys of the dictionary_of_fields are the form field ids\nin the document. To find them, you can useAdobe Acrobat,pdftk,\norPDFescapeif you don't want\nto install anything.The output can be imported with various programs/libraries, such aspdftk,Foxit Reader,Adobe Acrobat,\nandpypdftk.Alternatively, you can usepdfformfieldswhich this package was created for. pdfformfields is capable\nof reading in the metadata of the pdf and\nfilling in the form for you.To view the xfdf file in a more human readable format, usedocument.pretty_print()which should output\n\n\t\n\t\n\t\t\n\t\t\tfoo\n\t\t\n\t\t\n\t\t\tbar\n\t\t\n\t\nAn example is included in the example folder.CompatibilityThis package has been tested on Windows 10 using Python 3.7LicenseApache License 2.0"} +{"package": "xfds", "pacakge-description": "Source Code:github.com/pbdtools/xfdsDocumentation:xfds.pbd.toolsDo you have FDS installed on your machine? Do you know where the FDS executable is located? Do you know what version it is? If you installed FDS and Pathfinder, you might have multiple versions of FDS on your machine, but which one do you use?xFDS leverages the power of Docker to give you acess to all the versions of FDS without having to manage the different versions of FDS yourself. Best of all, you don't have to change or install anything when FDS has a new release!Once xFDS is installed, all you have to do is navigate to your file and typexfds run. It will locate the first FDS file in the directory and run it with the latest version of FDS!~/tests/data/fds$ ls\ntest.fds\n~/tests/data/fds$ xfds run\ndocker run --rm --name test -v /tests/data/fds:/workdir openbcl/fds fds test.fdsFeaturesGenerate Parametric AnalysesFire models can often require mesh sensitivity studies, different fire sizes, multiple exhaust rates, and a number of differnt parameters. With the power of theJinjatemplating system, xFDS can help generate a variety of models from a single.fdsfile!Specify Resolution, notIJKLet xFDS calculate the number of cells so you don't have to. By setting variables at the top of your FDS file, you can use them to perform calculations. Variables are defined using theMultiMarkdown Specificationfor file metadata. Expressions between curly braces{and}are evaluated as Python code.xmax: 5\nymax: 4\nzmax: 3\nres: 0.1\n\n&MESH XB=0, {xmax}, 0, {ymax}, 0, {zmax}, IJK={xmax // res}, {ymax // res}, {zmax // res}/Will translate to:&MESH XB= 0, 5, 0, 4, 0, 3, IJK= 50, 40, 30/Want to run a coarser mesh? Just changeresto0.2and get&MESH XB= 0, 5, 0, 4, 0, 3, IJK= 25, 20, 15/Use loops to create an array of devicesCreatefor loopsby typing{% for item in list %} ... {% endfor %}.{% for x in range(1, 5) %}\n{% for y in range(1, 3) %}\n&DEVC QUANTITY='TEMPERATURE', IJK={x}, {y}, 1.8/\n{% endfor %}\n{% endfor %}Will render to the following code. Note,Python'srange()function will exclude the upper bound.&DEVC QUANTITY='TEMPERATURE', IJK=1, 1, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=1, 2, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=2, 1, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=2, 2, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=3, 1, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=3, 2, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=4, 1, 1.8/\n&DEVC QUANTITY='TEMPERATURE', IJK=4, 2, 1.8/Manage FDS RunsAuto-detect FDS file in directoryIf you're in a directory containing an FDS file, xFDS will find the FDS file without you specifying it. This is best when each FDS model has its own directory. If multiple FDS files are in the directory, only the first file found will be executed.If no FDS file is found, xFDS will put you into an interactive session with the directory mounted inside the Docker container. If no directory is specified, the current working directory will be used.Latest version of FDS always available.xFDS will always default to the latest version thanks to how the Docker images are created, but you're always welcome to use an older version of FDS if needed. Seefds-dockerfilesfor supported versions.Always know what FDS version you're using.xFDS will inject the FDS version into the container name so there's no question what version of FDS is running. xFDS will also append a globally unique ID so there's no conflicts in having multipe containers running.Runs in BackgroundFire and forget. Unless you use the interactive mode, xFDS will run your model in a container and free up the terminal for you to keep working.InstallationPrerequisitesxFDS depends on the following softwares:Docker: Needed to run fds-dockerfiles imagesPython: Needed to run pipxpipx: Needed to install xFDSOnce Docker, Python, and pipx are installed, install xFDS with the following command:pipx install xfdsFor more information about installing xFDS, seehttps://xfds.pbd.tools/installationLearn more at xfds.pbd.tools"} +{"package": "xfdtest", "pacakge-description": "one ok rockwe are the championsthis is code"} +{"package": "xfeat", "pacakge-description": "No description available on PyPI."} +{"package": "xfem", "pacakge-description": "(ngs)xfem is an Add-on library to Netgen/NGSolve which enables the use of unfitted finite element technologies known as XFEM, CutFEM, TraceFEM, Finite Cell, \u2026 . ngsxfem is an academic software. Its primary intention is to facilitate the development and validation of new numerical methods."} +{"package": "xfer", "pacakge-description": "Git plugin for transferring large files across servers.InstallationClone the repo and install with pip or setuptools:gitclonegit@github.com:bprinty/git-xfer.gitpipinstall.ConfigurationTo add a remote server that can be used bygit-xfer, either use theconfigsubcommand:gitxferconfig[]Or manually add the server as a git remote:gitremoteaddgitremoteaddserverssh://user@server.com:22/~/git-xfer.gitNote: for remote servers using a port other than 22, please use the format above in defining the remote url.git-xferuses the port specified in the url to do transfer operations.UsageTo start tracking a file with git-xfer, use:gitxferaddTo remove a file from tracking with git-xfer, use:gitxferremoveTo delete a local file and remove it from tracking withgit-xfer, use:gitxferrmTo list all the files currently tracked bygit-xfer, use:gitxferlistTo list all the files currently tracked bygit-xferon a remote, use:gitxferlistTo see the difference between locally tracked files and remotely tracked files, use:gitxferdiffTo push locally tracked files to a remote server, use:gitxferpushTo pull tracked files from a remote server, use:gitxferpullQuestions/FeedbackSubmit an issue in theGitHub issue tracker."} +{"package": "xfer-ml", "pacakge-description": "Xfer is a library that allows quick and easy transfer of knowledge stored in deep neural networks implemented in MXNet. Xfer can be used with data of arbitrary numeric format, and can be applied to the common cases of image or text data."} +{"package": "xfers", "pacakge-description": "UNKNOWN"} +{"package": "xfers-sdk", "pacakge-description": "Xfers Python LibraryThis library is the abstraction of Xfers API for access from applications written with Python.Table of ContentsAPI DocumentationRequirementsInstallationUsageAPI KeyUsing Custom HTTP ClientBalanceGet BalanceBankBank Account ValidationList Disbursement BanksPaymentVirtual AccountQRISRetail OutletE-WalletRetrieve a PaymentManaging PaymentsDisbursementsAPI DocumentationPlease checkXfers API Reference.RequirementsPython 3.7 or laterInstallationTo use the package, runpip install xfers-sdkUsageAPI Keyfromlandx_xfers_sdkimportXfersxfers=Xfers(api_key=\"test-key123\",secret_key=\"12345678\")# Then access each class from x attributebalance=xfers.Balancebalance.get()BalanceGet Balancebalance=xfers.Balancebalance.get()Usage example:fromlandx_xfers_sdkimportXfersxfers=Xfers(api_key=\"test-key123\",secret_key=\"12345678\",production=False)# Then access each class from x attributebalance=xfers.Balanceprint(balance.get())Reference:https://docs.xfers.com/reference/account-balanceBank ServiceBank Account Validationbank=xfers.Bankbank.account_validation(account_no=\"123456\",bank_short_code=\"BNI\")Reference:https://docs.xfers.com/reference/bank-account-validationList Disbursement Banksbank=xfers.Bankbank.list()Reference:https://docs.xfers.com/reference/list-disbursement-banksPaymentThere are 2 main ways to accept payments with Xfers.One time payment\nUsexfers.PaymentinstancePersistent payment method linked to one of your customers\nUsexfers.PaymentMethodinstanceReference:https://docs.xfers.com/docs/accepting-paymentsVirtual AccountCreate One Time Paymentpayment=xfers.Paymentpayment.create(type=\"virtual_bank_account\",amount=10000,expired_at=datetime.now()+timedelta(days=1),# One Dayreference_id=\"va_12345678\",bank_short_code=\"SAHABAT_SAMPOERNA\",display_name=\"Your preferred name\",description=\"Payment Description\"# suffix_no=\"12345678\")API Reference:https://docs.xfers.com/reference/create-paymentCreate Persistent Paymentpayment_method=xfers.PaymentMethodpayment_method.create(type=\"virtual_bank_accounts\",reference_id=\"12345678\",bank_short_code=\"SAHABAT_SAMPOERNA\",display_name=\"Your preferred name\",# suffix_no=\"12345678\")API Reference:https://docs.xfers.com/reference/create-payment-methodQRISCreate One Time Paymentpayment=xfers.Paymentpayment.create(type=\"qris\",amount=10000,expired_at=datetime.now()+timedelta(days=1),# One Dayreference_id=\"qris_12345678\",display_name=\"Your preferred name\",description=\"Payment Description\")API Reference:https://docs.xfers.com/reference/create-paymentCreate Persistent Paymentpayment_method=xfers.PaymentMethodpayment_method.create(type=\"qris\",reference_id=\"12345678\",display_name=\"Your preferred name\")API Reference:https://docs.xfers.com/reference/create-payment-methodRetail OutletCreate Paymentpayment=xfers.Paymentpayment.create(type=\"retail_outlet\",amount=10000,expired_at=datetime.now()+timedelta(days=1),# One Dayreference_id=\"qris_12345678\",retail_outlet_name=\"ALFAMART\",display_name=\"Your preferred name\",description=\"Payment Description\")Available Outlets:https://docs.xfers.com/docs/retail-store#available-outletsAPI Reference:https://docs.xfers.com/reference/create-paymentE-WalletCreate Paymentpayment=xfers.Paymentpayment.create(type=\"e-wallet\",amount=10000,expired_at=datetime.now()+timedelta(days=1),# One Dayreference_id=\"qris_12345678\",provider_code=\"SHOPEEPAY\",after_settlement_return_url=\"https://pay.examplessee.co.id/return-pay-here?0340450\",display_name=\"Your preferred name\",description=\"Payment Description\")List of E-Wallet:https://docs.xfers.com/docs/e-wallet#list-of-e-walletAPI Reference:https://docs.xfers.com/reference/create-paymentRetrieve a PaymentRetrieves a Payment object that was previously requested.One time paymentpayment=xfers.Paymentpayment.get(payment_id=\"va_1234567\")API Reference:https://docs.xfers.com/reference/retrieve-paymentPersistent paymenttype = The type of payment method. Currently support \"virtual_bank_accounts\" and \"qris\".payment_method=xfers.PaymentMethodpayment_method.get(type=\"virtual_bank_accounts\",payment_id=\"va_1234567\")API Reference:https://docs.xfers.com/reference/retrieve-payment-methodManaging PaymentsPersistent Payment (PaymentMethod)Receive PaymentSimulates a payment received from the customer for a given payment. Status will be changed to 'paid'.payment_method=xfers.PaymentMethodpayment_method.receive_payment(payment_method_id=\"va_123456789\",amount=90000)One Time Payment (Payment)Receive Payment [Sandbox Mode]Simulates a payment received from the customer for a given payment. Status will be changed to 'paid'.payment=xfers.Paymentpayment.receive_payment(payment_method_id=\"va_123456789\",)Receive Payment [Sandbox Mode]Simulates a payment received from the customer for a given payment. Status will be changed to 'paid'.payment=xfers.Paymentpayment.receive_payment(payment_method_id=\"va_123456789\",)Cancel PaymentCancel a payment when it is still in pending state. Status will be changed to 'cancelled'.\n(This is only available for One-off Virtual Account at the moment.)payment=xfers.Paymentpayment.cancel(payment_method_id=\"va_123456789\",)Settle Payment [Sandbox Mode]Simulates funds for a payment being made available for transfer or withdrawal. Status will be changed to 'completed'.payment=xfers.Paymentpayment.settle(payment_method_id=\"va_123456789\",)DisbursementsCreate DisbursementsCreates a Disbursement object that will send funds from your Xfers account to an intended recipient.xfers.Disbursements.create(amount=\"10000\",reference_id=\"123\",bank_shortcode=\"BCA\",bank_account_no=\"0123123123\",bank_account_holder_name=\"john doe\")Retrieve a DisbursementRetrieves a Disbursement object that was previously requested.xfers.Disbursements.get(disbursement_id=\"id\")List All DisbursementReturns a list of Disbursements.xfers.Disbursements.list(created_after=\"2022-04-15\")"} +{"package": "xfetus", "pacakge-description": "xfetus - library for synthesis of ultrasound fetal imaging (:baby: :brain: :robot:) :warning: WIP :warning:xfetus is a python-based library to syntheses fetal ultrasound images using GAN, transformers and diffusion models.\nIt also includes methods to quantify the quality of synthesis (FID, PSNR, SSIM, and visual touring tests).Installation$ pip install xfetusYou can develop locally:Generate your SSH keys as suggestedhere(orhere)Clone the repository by typing (or copying) the following line in a terminal at your selected path in your machine:cd && mkdir -p $HOME/repositories/budai4medtech && cd $HOME/repositories/budai4medtech\ngit clone git@github.com:budai4medtech/xfetus.gitReferencesPresentationGood practices in AI/ML for Ultrasound Fetal Brain Imaging SynthesisHarvey Mannering, Sofia Mi\u00f1ano, and Miguel XochicaleUniversity College LondonThe deep learning and computer vision Journal ClubUCL Centre for Advance Research Computing1st of June 2023, 15:00 GMTAbstract\nMedical image datasets for AI and ML methods must be diverse to generalise well unseen data (i.e. diagnoses, diseases, pathologies, scanners, demographics, etc).\nHowever there are few public ultrasound fetal imaging datasets due to insufficient amounts of clinical data, patient privacy, rare occurrence of abnormalities, and limited experts for data collection and validation.\nTo address such challenges in Ultrasound Medical Imaging, Miguel will discuss two proposed generative adversarial networks (GAN)-based models: diffusion-super-resolution-GAN and transformer-based-GAN, to synthesise images of fetal Ultrasound brain image planes from one public dataset.\nSimilarly, Miguel will present and discuss AI and ML workflow aligned to good ML practices by FDA, and methods for quality image assessment (e.g., visual Turing test and FID scores).\nFinally, a simple prototype in GitHub, google-colabs and guidelines to train it using Myriad cluster will be presented as well as applications for Medical Image Synthesis e.g., classification, augmentation, segmentation, registration and other downstream tasks, etc. will be discussed.\nThe resources to reproduce the work of this talk are available athttps://github.com/budai4medtech/xfetus.CitationsBibTeX to cite@misc{iskandar2023realistic,\n author={\n \tMichelle Iskandar and \n \tHarvey Mannering and \n \tZhanxiang Sun and \n \tJacqueline Matthew and \n \tHamideh Kerdegari and \n \tLaura Peralta and \n \tMiguel Xochicale},\n title={Towards Realistic Ultrasound Fetal Brain Imaging Synthesis}, \n year={2023},\n eprint={2304.03941},\n archivePrefix={arXiv},\n primaryClass={eess.IV}\n}ContributorsThanks goes to all these people (emoji key):ADD NAME SURNAME\ud83d\udd2c \ud83e\udd14Sofia Mi\u00f1ano\ud83d\udcbb\ud83d\udd2c \ud83e\udd14Zhanxiang (Sean) Sun\ud83d\udcbb\ud83d\udd2c \ud83e\udd14Harvey Mannering\ud83d\udcbb\ud83d\udd2c \ud83e\udd14Michelle Iskandar\ud83d\udcbb\ud83d\udd2c \ud83e\udd14Miguel Xochicale\ud83d\udcbb\ud83d\udcd6 \ud83d\udd27This work follows theall-contributorsspecification.Contributions of any kind welcome!"} +{"package": "xfftspy", "pacakge-description": "xfftspyInstallationpip install xfftspyUsage>>> import xfftspy\n\n# initialize XFFTS boards\n>>> cmd = xfftspy.udp_client(host='localhost')\n>>> cmd.stop()\n>>> cmd.set_synctime(100000) # synctime : 100 ms\n>>> cmd.set_usedsections([1]) # use board : 1\n>>> cmd.set_board_bandwidth(1, 2500) # bandwidth : 2500 MHz\n>>> cmd.configure() # apply settings\n>>> cmd.caladc() # calibrate ADCs\n>>> cmd.start() # start measurement\n\n# receive spectra\n>>> rcv = xfftspy.data_consumer(host='localhost')\n>>> rcv.clear_buffer()\n>>> rcv.receive_once()"} +{"package": "xfhir", "pacakge-description": "XFHIR Python SDKimportxfhirxfhir.init(client_id='xxx',client_secret='xxxx')xfhir.create({})xfhir.get(id='',resource_type='Patient')xfhir.filter(resource_type='Patient',q='')xfhir.search(q='')Connect to the XFHIR ServicefromxfhirimportXFHIRx=XFHIR(client_id='xxx',client_secret='xxxx')Create a Policy for a FHIR Resourcepatient_redact_policy=x.policy.create(effect='Redact',actions=['account-id:client-id:method:resource:path','account-id:*:Read:Patient:$',])Create the FHIR Resource on XFHIR along with its resource policiesx.create({'fhir_resource':{},'policies':[patient_redact_policy]})Full examplefromxfhirimportXFHIRx=XFHIR(client_id='xxx',client_secret='xxxx')patient_redact_policy=x.policy.create(effect='Redact',actions=['account-id:client-id:method:resource:path','account-id:*:Read:Patient:$',])x.create({'fhir_resource':{},'policies':[patient_redact_policy]})patient=x.get('Patient','identifier')The output of the patient object should be{\"id\":\"*** REDACTED **\",\"name\":\"*** REDACTED **\"}To redact only a few fields in the patient object you can create a policy that only redacts your custom fieldspatient_redact_policy=x.policy.create(effect='Redact',actions=['account-id:*:Read:Patient:$.id','account-id:*:Read:Patient:$.name','account-id:*:Read:Patient:$.contact'])"} +{"package": "xfields", "pacakge-description": "Python package for the computation of fields generated by particle ensembles in accelerators.This package is part of the Xsuite collection."} +{"package": "xfile", "pacakge-description": "No description available on PyPI."} +{"package": "xfiles", "pacakge-description": "No description available on PyPI."} +{"package": "xfilios", "pacakge-description": "XfiliosExcel and Docx FileIO handlers in the client side for Streamlit (in future Dash will also be considered) Framework. The library provides easy to use classes to encode or decode Docx and Excel at the client side. The following core features are available in the library:Convert an uploaded Docx-file into base64 encoded string to send over HTTP post request (a wrapper over python-docx package)Convert Data received from an HTTP get/post request into Downloadable Excel file (a wrapper over pandas and openpyxl)Combine multiple data source into multi-sheet Downloadable Excel file at the frontend (a wrapper using pandas ReadExcel function with openpyxl)This package is actually a wrapper over pandas and python-docx package. It is possible to extend other fileIO types like csv, text etc in further release.DocxHandlerWhen a Docx file is uploaded into streamlit, it consider the content as a file like object. The packagexfiliosprovide a class calledDocxHandlerwhich has a class method can receive a file like object and will return aDocxHandlerobject. After create a handler object it easy to convert the content into base64 encoded string to send it over a Rest API as follows:importstreamlitasstfromxfilios.docximportDocxHandlerdefdocx_handler_demo():st.title('Demo of xfilios DocxHandler')content=st.file_uploader(\"Upload Docx File\",type=\"docx\")ifcontent:handler=DocxHandler.from_file_like(content)# Now you can send the encoded string over Http post requestdocument_base_64=handler.to_base64_str()# requests.post(body={\"data\": document_base_64})st.text(\"Here is the base64 encoded document{}...\".format(document_base_64[:10]))# Or if you received a base64 encoded binary document you can create a downloadable linkdownload_link=handler.create_download_link(filename=\"demo.docx\")download_text=f\"Please Download the document back{download_link}\"st.markdown(download_text,unsafe_allow_html=True)TableHandler and ExcelHandler\nThe TableHandler and ExcelHandler can work together to achieve the same functionality likeDocxHandler. After you upload a Excel file you can use TableHandler to collect the content of the file. If you have multiple table you can load all the tables and wrap them withTableHandlerand create a list ofTableHandlerand hand it over toExcelHandler.ExcelHandlerwill finally create a downloadable Excel file where each table will an Excel sheet.importstreamlitasstfromxfilios.tableimportTableHandlerfromxfilios.excelimportExcelHandlerdefexcel_handler_demo():st.title('Demo of xfilios ExcelHandler')content=st.file_uploader(\"Upload Docx File\",type=\"xlsx\")ifcontent:# Each table handler will consist one tabletable_handler=TableHandler.from_file_like(content)# You can put multiple table handler into a list [table_handler1, table_handler2 ...]excel_handlers=ExcelHandler([table_handler])download_link=excel_handlers.create_download_link(filename=\"demo.xlsx\")download_text=f\"Please Download the File back{download_link}\"st.markdown(download_text,unsafe_allow_html=True)st.markdown(\"Here is the content of the file\")st.table(table_handler.get_data_as_dataframe())"} +{"package": "x-filter", "pacakge-description": "No description available on PyPI."} +{"package": "xfin", "pacakge-description": "xFinTarget Usersfinancial market analyst of Chinalearners of financial data analysis with pandas/NumPypeople who are interested in China financial data\nInstallationpip install xfinUpgradepip install xfin --upgrade"} +{"package": "xfinity-gateway", "pacakge-description": "Query an Xfinity GatewayThis library allows an Xfinity Gateway to be queried for connected devices. It uses therequestslibrary to scrape the web interface of the gateway.Usagefromxfinity_gatewayimportXfinityGateway# Connect to gatewaygateway=XfinityGateway('10.0.0.1')# Get list of all connected devices' MAC addressesgateway.scan_devices()# Get specific device's namegateway.get_device_name('mac address of device here')ThoughtsI have only tested on my own Xfinity-provided gateway:Model:TG1682GHardware Revision:9.0If your gateway's web interface looks like the following, this library will likely work:Please open a Github issue if you encounter any problems. Thanks!"} +{"package": "xfinity-usage", "pacakge-description": "Python/selenium script to get Xfinity bandwidth usage from Xfinity MyAccount website. Has an easily-usable\ncommand line entrypoint as well as a usable Python API, and an entrypoint to send usage to Graphite.This is a little Python script I whipped up that theselenium-pythonpackage to log in to your Xfinity account and screen-scrape the data usage. By default the usage is just printed\nto STDOUT. You can also use theXfinityUsageclass from other applications or scripts; see the\ndocstrings on the__init__andrunmethods for information. There are also options to send the data\nto a Graphite server.For the changelog, seeCHANGES.rst in the GitHub project.Development Discontinued - Maintainer WantedAs of September 2018, AT&T Fiber has become available in my area and I\u2019ve switched to that because of the much better pricing (I\u2019m getting 300Mbpssymmetricalfor the same monthly price as Xfinity 100/10). As such, I won\u2019t be able to continue maintaining this project without an Xfinity account. If anyone would like to take over maintenance, please open an Issue on GitHub and I\u2019ll contact you.RequirementsPython (tested with 2.7; should work with 3.3+ as well)seleniumPython packageOne of the supported browsers:A recent version of PhantomJS installed on your computer; this should be 2.0+, and the script is tested with 2.1.1.Google Chrome or Chromium andchromedriverFirefox andGeckodriverInstallationpip install xfinity-usageUsageCommand LineExport your Xfinity username as theXFINITY_USERenvironment\nvariable, your password as theXFINITY_PASSWORDenvironment\nvariable, and run thexfinity-usageentrypoint. Seexfinity-usage-hand the\ntop-level docstring in the script for more information.I\u2019d highly recommend not leaving your username and password hard-coded\nanywhere on your system, but the methods for securing credentials are\nvaried enough that the choice is yours.Note that this screen-scrapes their site; it\u2019s likely to break with a\nredesign.Python APISee the source of thexfinity_usage.pyscript, specifically the__init__andrunmethods of theXfinityUsageclass. As a simple example:>>>importos>>>fromxfinity_usage.xfinity_usageimportXfinityUsage>>>u=XfinityUsage(os.environ['XFINITY_USER'],os.environ['XFINITY_PASSWORD'],browser_name='chrome-headless')>>>u.run(){\n \"data_timestamp\": 1523913455,\n \"units\": \"GB\",\n \"used\": 224.0,\n \"total\": 1024.0,\n \"raw\": {\n \"courtesyUsed\": 0,\n \"courtesyRemaining\": 2,\n \"courtesyAllowed\": 2,\n \"inPaidOverage\": false,\n \"usageMonths\": [\n {\n \"policyName\": \"1 Terabyte Data Plan\",\n \"startDate\": \"10/01/2017\",\n \"endDate\": \"10/31/2017\",\n \"homeUsage\": 408.0,\n \"allowableUsage\": 1024.0,\n \"unitOfMeasure\": \"GB\",\n \"devices\": [\n {\n \"id\": \"AB:CD:EF:01:23:45\",\n \"usage\": 301.0\n },\n {\n \"id\": \"12:34:56:78:90:AB\",\n \"usage\": 107.0\n }\n ],\n \"additionalBlocksUsed\": 0.0,\n \"additionalCostPerBlock\": 10.0,\n \"additionalUnitsPerBlock\": 50.0,\n \"additionalIncluded\": 0.0,\n \"additionalUsed\": 0.0,\n \"additionalPercentUsed\": 0.0,\n \"additionalRemaining\": 0.0,\n \"billableOverage\": 0.0,\n \"overageCharges\": 0.0,\n \"overageUsed\": 0.0,\n \"currentCreditAmount\": 0,\n \"maxCreditAmount\": 0,\n \"policy\": \"limited\"\n },\n # 5 additional months removed for brevity\n {\n \"policyName\": \"1 Terabyte Data Plan\",\n \"startDate\": \"04/01/2018\",\n \"endDate\": \"04/30/2018\",\n \"homeUsage\": 224.0,\n \"allowableUsage\": 1024.0,\n \"unitOfMeasure\": \"GB\",\n \"devices\": [\n {\n \"id\": \"12:34:56:78:90:AB\",\n \"usage\": 224.0\n }\n ],\n \"additionalBlocksUsed\": 0.0,\n \"additionalCostPerBlock\": 10.0,\n \"additionalUnitsPerBlock\": 50.0,\n \"additionalIncluded\": 0.0,\n \"additionalUsed\": 0.0,\n \"additionalPercentUsed\": 0.0,\n \"additionalRemaining\": 0.0,\n \"billableOverage\": 0.0,\n \"overageCharges\": 0.0,\n \"overageUsed\": 0.0,\n \"currentCreditAmount\": 0,\n \"maxCreditAmount\": 0,\n \"policy\": \"limited\"\n }\n ]\n }\n}Note About ReliabilityIn short: xfinity\u2019s site isn\u2019t terribly reliable. Personally, I run this\nscript twice an hour via cron, so 48 times a day, every day. I usually\nsee 1-4 failures a day of all different failure modes - elements missing\nfrom the page, connection resets, blank pages, server-side error\nmessages, etc. Keep that in mind. My code could probably do more in\nterms of error handling and retries, but it\u2019s notthatimportant to\nme.RationaleComcast recently started rolling out a 1TB/month bandwidth cap in my\narea. I\u2019ve gone over my two \u201ccourtesy\u201d months, and the overage fees are\npretty insane. I work from home, and sometimes that uses a lot of\nbandwidth. I want to know when I\u2019m getting close to my limit; this month\nI\u2019m apparently at 75% and only half way through the month, and I havenoidea how that happened.It\u2019s entirely abusive and invasive that Comcast isinjecting bandwidth\nwarnings into my web\ntraffic,\nbut that\u2019s also a pretty awful way of attempting to tell a human\nsomething - especially given how much automated traffic my computer\ngenerates. Moreover,Xfinity\u2019s site has aUsage Meter(which is the source of this data), but it only shows a progress bar for\nthe month - no way to find out usage by day or hour to try and figure\nout what the cause actually was. Also, even if I visit the usage meter\nfrom my own computeron Xfinity\u2019s network, using the IP address which\nXfinity assigned to me (and is tracking usage for), I still need to log\nin to my account to view the usage. That\u2019s a complete pain and seems to\nserve only to prevent customers from keeping track of their usage, not\nto metion preventing guests or friends from checking usage. Hell,\nXfinity used to have adesktop app to track\nusagebut it\u2019s been shut down, and a\nhandyscript that used the same API as the desktop\nappno longer works as a\nresult. With all of this put together, I\u2019d say Comcast is going to great\nlengths to maximize overage fees and minimize customers\u2019 insight into\ntheir usage.In short, I want to be notified of my usage on a regular basis (I get\ndaily emails with the results of this script), and I also want to be\nable to see historical trends (I push the output to Graphite).DisclaimerI have no idea what Xfinity\u2019s terms of use for their account management website\nare, or if they claim to have an issue with automating access. They used to have\na desktop app to check usage, backed by an API (seehttps://github.com/WTFox/comcastUsage), but that\u2019s been discontinued. The fact\nthat they force me to login with my account credentials WHEN CONNECTING FROMTHEIRNETWORK, USING THE IP ADDRESSTHEYISSUED TO MY ACCOUNT just to check\nmy usage, pretty clearly shows me that Comcast cares a lot more about extracting\nthe maximum overage fees from their customers than the \u201cquality of service\u201d that\nthey claim these bandwidth limits exist for. So\u2026 use this at your own risk,\nbut it seems pretty clear (i.e. discontinuing their \u201cbandwidth meter\u201d desktop\napp) that Comcast wants to prevent users from having a clear idea of their\nsupposed bandwidth usage.LicenseThis package is licensed under theGNU AGPLv3.ContributingFor information on contributing, see.github/CONTRIBUTING.md."} +{"package": "xfit", "pacakge-description": "InstallationThis package requiresxraylibandcompwizard. On Windows, xraylib can be installed through the Anaconda interface.conda install -c conda-forge xraylib=4.0.0pip instal compwizardFor further information on how to install xraylib on other operational systems, check xraylibwiki.This module can be installed with:pip install xfitUsageThis module provides the \"Spectrum\" class. It is possible to initialize this class with a numpy nd.array or loading an *.mca or *.spt file, by giving the path.\nFor the continuum estimation algorithm, refer to theContinuum.pyfile.Test.py file provides a common *.mca file to use with the example.py script provided.Example 1import xfit\nimport numpy as np\nimport matplotlib.pyplot as plt\npath = r\"./test.mca\"\npool_file = r\"./pool.txt\"\nSpec = xfit.Spectrum(file_path=path)\nSpec.calibrate() #if no arguments are passed, it gets the parameters from the mca or spt header\nSpec.estimate_continuum(30, 11, 11, 3) #iterations, filter window, sav-gol window, sav-gol order\nSpec.fit_fano_and_noise()\nSpec.create_pool(pool_file)\nSpec.fit()\n\n#Plot ------\nfig, ax = plt.subplots()\nax.plot(Spec.energyaxis, Spec.data, color=\"black\", label=\"Data\")\nax.plot(Spec.energyaxis, Spec.continuum, color=\"green\", label=\"Continuum\")\nfor element in Spec.areas.keys():\n ax.plot(Spec.energyaxis, \n Spec.plots[element],\n label=element+\" fit result\", \n color=ElementColors[element],\n linestyle=\"--\")\nax.legend(loc=1, fancybox=1)\nax.set_yscale(\"log\")\nplt.show()0.11400000005960464 80.00951851146041 (Fano and Noise values found, respectively)Example 2import xfit\nimport numpy as np\nydata = np.arange(1024)\nfit_pool = {}\nfit_pool[\"elements\"] = {}\nfit_pool[\"elements\"][\"Cu\"] = [\"KA1\",\"KA2\",\"KB1\",\"KB3\"]\nfit_pool[\"bg\"] = 1 #Forces the use of continuum estimation for the fit\nSpec = xfit.Spectrum(array=ydata)\nSpec.calibrate(x=channels, y=energies)\nSpec.estimate_continuum(30, 11, 11, 3)\nSpec.fit_fano_and_noise()\nSpec.pool = fit_pool\nSpec.fit()\n#or simply: Spec.fit(pool=fit_pool)\n\n#Plot ------\nfig, ax = plt.subplots()\nax.plot(Spec.energyaxis, Spec.data, color=\"black\", label=\"Data\")\nax.plot(Spec.energyaxis, Spec.continuum, color=\"green\", label=\"Continuum\")\nfor element in Spec.areas.keys():\n ax.plot(Spec.energyaxis, \n Spec.plots[element],\n label=element+\" fit result\", \n color=ElementColors[element],\n linestyle=\"--\")\nax.legend(loc=1, fancybox=1)\nax.set_yscale(\"log\")\nplt.show()"} +{"package": "xfl", "pacakge-description": "UNKNOWN"} +{"package": "xflash", "pacakge-description": "UNKNOWN"} +{"package": "xFlask", "pacakge-description": "xFlask combines the extensions of Flask and it is designed to make getting started quick and easy to build Restful web service, with the ability to scale up to complex applications. It begin as a simple wrapper around Flask and its extensions to provide a simple platform to ease API development.1. FunctionalitiesFollow concepts of Model, Data Access Object (DAO), Service and ControllerEase to decouple component dependencies by using Flask-InjectorProvide a simple way to validate Value Object (VO) by using MarshmallowAdapt with Flask-Migration to easily maintain the database schemaProvide simple logging API helping to debug the application flowAdapt with Flask-Testing for testing the application components2. UsagesModelfromxflask.sqlalchemyimportColumn,Integer,Stringfromxflask.sqlalchemy.modelimportAuditModelclassUser(AuditModel):id=Column(Integer,primary_key=True)username=Column(String(50),unique=True,nullable=False)password=Column(String(50),unique=False,nullable=False)DAOfromxflask.daoimportDaofrommain.model.userimportUserclassUserDao(Dao):def__init__(self):super(UserDao,self).__init__(User)defget_by_username(self,username):returnself.query().filter_by(username=username).first()Servicefrominjectorimportinjectfromxflask.serviceimportCrudServicefrommain.dao.userimportUserDaoclassUserService(CrudService):@injectdef__init__(self,dao:UserDao):super(UserService,self).__init__(dao)defget_user(self,user_id):returnself.user_dao.get_user(user_id)Controllerfrominjectorimportinjectfromxflask.classyimportroute,JsonBodyfromxflask.controllerimportControllerfromxflask.web.responseimportResponsefrommain.controller.vo.userimportUserVofrommain.model.userimportUserfrommain.service.userimportUserServiceclassUserController(Controller):route_base='/api/user/'@injectdef__init__(self,user_service:UserService):self.user_service=user_service@route('')defget(self,user_id):user=self.user_service.get(user_id)ifuserisNone:returnResponse.not_found()returnResponse.success(user)@route('',methods=['PUT'])defupdate(self,user:JsonBody(UserVo)):self.user_service.update(User(**user))returnResponse.success()Value Object (VO)fromxflask.marshmallowimportInt,Strfromxflask.marshmallowimportvalidatefromxflask.web.voimportVoclassUserVo(Vo):id:Int(required=True)username:Str(validate=validate.Length(min=2,max=50),required=True)password:Str(validate=validate.Length(min=2,max=50),required=True)"} +{"package": "xflat", "pacakge-description": "Flatten documentsHTMLxflat turns this htmlExample titleExample headingExample body, with a class and id
line break and some text

  1. List item 1
  2. List item 2
intohtml\nhtml/head\nhtml/head/title Example title\nhtml/head/meta charset=\"utf-8\"\nhtml/body\nhtml/body/h1 Example heading class=\"main\"\nhtml/body/p Example body, with a class and id class=\"class-1 class-2\" id=\"example-body\"\nhtml/body/p/br line break and some text\nhtml/body/div\nhtml/body/div/ol\nhtml/body/div/ol/li List item 1\nhtml/body/div/ol/li List item 2\nhtml/!comment [if lt IE 7]> `An instance of a particular workflow is tracked via its `execution_id`. Therefore all events definedin a workflow must contain this field. Since it is required to have the events defined in order itwill then be easy to determine which events were successfully processed and which were not at anyparticular time in the last 7 days.The goal of the tracker is to return the state of all events in the workflow given as inputthe `workflow_id` and its `execution_id`. The state would indicate whether the event was processed or not.It will then grab the last unprocessed event and fetch all logs for its subscribers (the lambdas) that failedto process that event.For this to work, there would be a separate tracker for every workflow defined. The tracker would subscribeitself to every stream in that workflow and hence it would receive events published to that stream. The tracker itself would be a lambda function and its name would be `tracker_`. Hence it will be invoked on everysuccessful publishing of an event to the stream.The actual tracking is done via AWS CloudWatchLogs. For every workflow a CloudWatch `LogGroup` is created. And for every instance of a workflow execution, a `LogStream` would be created.Hence, when an event is published to a stream, the tracker would receive the event and extract the`execution_id`. It will create a new log stream from this execution_id if not already created. It willthen store the event in that stream. Since the lambda's name is generated from the workflow_id, it is alsoeasy to extract the log group for the log stream.For every subsequent event published to the kinesis stream, the corresponding lambda for the workflow will be invoked and it will save the event to the log stream.- Running in server mode:`xflow word_count.cfg --server`This will run xflow via server mode. On startup, the server will setup the necessary streams, lambda functions and workflows. You can then publish events to a stream or track workflow executions in a RESTful way. Following are examples how you would do this.Publishing:`curl -XPOST localhost/publish -d '{\"stream\":\"FileUploaded\", \"event\":{\"execution_id\":\"ex1\", \"message\":\"Test with ccc\"}}'`Tracking:`curl -v localhost/track/workflows/compute_word_count/executions/ex1`Installation:=============- Via pip```bash>> pip install xflow```- Via github```bash>> git clone git@github.com:dsouzajude/xFlow.git>> cd xFlow>> python setup.py install```xFlow Requirements (and roadmap):=================================- Integration with github (so we can download the lambda function from there given the link)- Monitoring around lambda functions- Centralized Logging (or ability to route logs) to log server- CI/ CD for lambda functions"} +{"package": "xflow-api", "pacakge-description": "No description available on PyPI."} +{"package": "xflowapisourcebase", "pacakge-description": "No description available on PyPI."} +{"package": "xflowapisources", "pacakge-description": "No description available on PyPI."} +{"package": "xfloweltsourcebase", "pacakge-description": "No description available on PyPI."} +{"package": "xflow-net", "pacakge-description": "XFlow Homepage|Documentation|Paper CollectionXFlowis a library built upon Python to easily write and train method for a wide range of applications related to graph flow problems. XFlow is organized task-wise, which provide datasets benchmarks, baselines and auxiliary implementation.Installationpip install xflow-netExampleimportsysimportoscurrent_script_directory=os.path.dirname(os.path.abspath(__file__))xflow_path=os.path.join(current_script_directory,'..','..','xflow')sys.path.insert(1,xflow_path)fromxflow.dataset.nximportBA,connSWfromxflow.dataset.pygimportCorafromxflow.diffusion.SIimportSIfromxflow.diffusion.ICimportICfromxflow.diffusion.LTimportLTfromxflow.seedimportrandomasseed_random,degreeasseed_degree,eigenasseed_eigenfromxflow.utilimportrun# graphs to testfn=lambda:connSW(n=1000,beta=0.1)fn.__name__='connSW'gs=[Cora,fn,BA]# diffusion models to testdf=[SI,IC,LT]# seed configurations to testse=[seed_random,seed_degree,seed_eigen]# run# configurations of IM experimentsfromxflow.method.imimportpiasim_pi,degreeasim_degree,sigmaasim_sigma,celfppasim_celfpp,greedyasim_greedyme=[im_pi]rt=run(graph=gs,diffusion=df,seeds=se,method=me,eval='im',epoch=10,budget=10,output=['animation','csv','fig'])[Result]Create your own modelsBenchmark TaskInfluence Maximizationsimulation:greedy,CELF, andCELF++,proxy:pi,sigma, degree, andeigen-centralitysketch:RISBlocking Maximizationgreedypisigmaeigen-centralitydegreeSource LocalizationNETSLEUTH(Legacy and Fast versions)Jordan CentralityLISN.Experimental ConfigurationsGraphs: Compatiable with graph objects/class byNetworkxandPytorch GeometricDiffusion Models: SupportNDLibContactFeel free toemail usif you wish your work to be listed in this repo.\nIf you notice anything unexpected, please open anissueand let us know.\nIf you have any questions or are missing a specific feature, feel freeto discuss them with us.\nWe are motivated to constantly make XFlow even better."} +{"package": "xflrpy", "pacakge-description": "Python API for XFLR5This is the python package for running scripts and interfacing withxflrpy.Note: This repository is in intial development phase.\nThere might be:Some instabilityBreaking changes without updating major versions until the first release.Any contributions/constructive criticism is welcome. Use github issues to roast me.How to UseSeeexamplesDependenciesThis package depends onmsgpackand would automatically installmsgpack-rpc-python(this may need administrator/sudo prompt):pip install msgpack-rpc-python"} +{"package": "xflsvg", "pacakge-description": "This library is part of the Pony Preservation Project. It is designed to\nsupport the development of 2D animation AI. It has three main functions:Support to creation for SVG spritemaps for XFL files. Since there\u2019s no\npublicly-known way to render Adobe\u2019s Edge format, this library assumes\nthat Adobe Animate is required to render shape objects. The XflSvgRecorder\nclass simplifies the process by exporting (1) a simplified XFL file\ncontaining a single symbol, whose frames contain all of the shapes in the\nparent XFL files, and (2) a JSON object mapping parent XFL shapes to their\nlocation in the simplified XFL file.Convert XFL files and exported SVG shapes (xflsvg files) into a tabular\ndata format. The tabular data will eventually contain ALL data necessary\nto fully recreate the original animation, and the data will be\nhierarchically structured to match the original XFL file. This is done\nusing the XflSvgRecorder class\u2019s to_json() and to_xfl() methods.Render tabular animation data. The tabular data may be exported from\nexisting xflsvg files, or they may be programmatically generated. This\nis done using the XflSvgRenderer class.This project is currently in an early stage. The xflsvg format will change\nover time as we identify exactly what XFL data is necessary to recreate\nanimations, as will the rendering code.If you\u2019re using pip to install xflsvg, you\u2019ll need to install cairocffi\nand cairosvg to use XflSvgRenderer. If you\u2019re using conda to install xflsvg,\nboth will be automatically installed. Note that pip doesn\u2019t seem to install\ncairocffi properly."} +{"package": "xfmr", "pacakge-description": "Transformer/xfmr creates a unified interface for transforming data structures\nbetween common forms used in core Python data anlytics libraries like pandas,\nscikit-learn, NumPy, SciPy, and Vaex.xfmr provides:Single API and data object that can easily output and keep track of multiple\ndata structure formats so that data can be easily passed between different\nanalytics librariesMethods for transforming data using any one of a number of diffeent libraries\non the same data objectAll xfmr wheels distributed on PyPI are BSD 3-clause licensed."} +{"package": "xfms-calculations", "pacakge-description": "Make sure you have upgraded version of pipWindowspy -m pip install --upgrade pipLinux/MAC OSpython3 -m pip install --upgrade pipCreate a project with the following structurepackaging_tutorial/\n\u251c\u2500\u2500 LICENSE\n\u251c\u2500\u2500 pyproject.toml\n\u251c\u2500\u2500 README.md\n\u251c\u2500\u2500 setup.cfg\n\u251c\u2500\u2500 src/\n\u2502 \u2514\u2500\u2500 example_package/\n\u2502 \u251c\u2500\u2500 __init__.py\n\u2502 \u2514\u2500\u2500 example.py\n\u2514\u2500\u2500 tests/\ntouch LICENSE\ntouch pyproject.toml\ntouch setup.cfg\nmkdir src/mypackage\ntouch src/mypackage/__init__.py\ntouch src/mypackage/main.py\nmkdir testspyproject.tomlThis file tells tools like pip and build how to create your project[build-system]\nrequires = [\n \"setuptools>=42\",\n \"wheel\"\n]\nbuild-backend = \"setuptools.build_meta\"build-system.requires gives a list of packages that are needed to build your package. Listing something here will only make it available during the build, not after it is installed.build-system.build-backend is the name of Python object that will be used to perform the build. If you were to use a different build system, such as flit or poetry, those would go here, and the configuration details would be completely different than the setuptools configuration described below.Setup.cfg setupUsing setup.cfg is a best practice, but you could have a dynamic setup file using setup.py[metadata]\nname = example-pkg-YOUR-USERNAME-HERE\nversion = 0.0.1\nauthor = Example Author\nauthor_email = author@example.com\ndescription = A small example package\nlong_description = file: README.md\nlong_description_content_type = text/markdown\nurl = https://github.com/pypa/sampleproject\nproject_urls =\n Bug Tracker = https://github.com/pypa/sampleproject/issues\nclassifiers =\n Programming Language :: Python :: 3\n License :: OSI Approved :: MIT License\n Operating System :: OS Independent\n\n[options]\npackage_dir =\n = src\npackages = find:\npython_requires = >=3.6\n\n[options.packages.find]\nwhere = srcRunning the buildMake sure your build tool is up to dateWindowspy -m pip install --upgrade buildLinux/MAC OSpython3 -m pip install --upgrade buildCreate the buildpy -m buildReferenceshttps://packaging.python.org/tutorials/packaging-projects/"} +{"package": "xfmt", "pacakge-description": "xfmtFormat all the things"} +{"package": "xfn", "pacakge-description": "No description available on PyPI."} +{"package": "xfnester", "pacakge-description": "UNKNOWN"} +{"package": "xf_nester", "pacakge-description": "UNKNOWN"} +{"package": "xfntr", "pacakge-description": "A GUI software to process, analyze and visualize XFNTR dataTo install the software, MAC/LInux users type:pip install xfntrWindows users type:pip install xfntr-winRequired environment: Python3.7To run the software, all users type:xfntr"} +{"package": "xfntrwin", "pacakge-description": "xfntr for windows development"} +{"package": "xfntr-win", "pacakge-description": "A GUI software to process, analyze and visualize XFNTR data"} +{"package": "xfoil", "pacakge-description": "GeneralThis is a stripped down version of XFOIL, presented in the form of a Python module. What's unique about this package\nw.r.t. many others out there allowing an interface to XFOIL, is the fact that the Python code talks directly to a\ncompiled Fortran library. This approach avoids having to read/write in-/output files to the disk and communicating with\nthe XFOIl executable. Eliminating the need for constant disk I/O operations can significantly speed up parallel\nframeworks in particular, giving this approach a clear advantage.Building and Installing the Python ModuleIf you are on a Windows machine (64bit) with Python 3.6, installing XFoil is a simple matter of running:pipinstallxfoilIf you are using a different type of machine, or a different version of Python, you will have to make sure some\nsoftware is installed on your system in order for the package to be successfully built. First of all, the module targets\nPython 3, and does NOT support Python 2. So make sure a Python 3 environment is installed and available.\nFurthermore, working compilers for C and Fortran have to be installed and on the PATH. On Windows, the build and\ninstallation have ONLY been tested with MinGW, using gcc and gfortran.Then, installing XFoil should be as simple as runningpipinstall.from the root of the downloaded repository.On Windows, you may have to force the system to use MinGW. To do so, create a file nameddistutils.cfginPYTHONPATH\\Lib\\distutilswith the following contents:[build]compiler=mingw32If you are not able to create this file for your Python environment, you can instead create a file namedsetup.cfgin\nthe root of the repo with the same contents. It is also possible to force the use of MinGW directly when invokingpipby calling:pipinstall--global-optionbuild_ext--global-option--compiler=mingw32.Using the ModuleAll XFoil operations are performed using theXFoilclass. So the first step when using this module is to create an\ninstance of this class:>>>fromxfoilimportXFoil>>>xf=XFoil()If this does not produce any errors, the installation should be functioning properly.The symmetric NACA 0012 airfoil is included as a test case. It can be loaded into the XFoil library like this:>>>fromxfoil.testimportnaca0012>>>xf.airfoil=naca0012Number of input coordinate points: 160Counterclockwise orderingMax thickness = 0.120008 at x = 0.308Max camber = 0.000000 at x = 0.033LE x,y = -0.00000 0.00000 | Chord = 1.00000TE x,y = 1.00000 0.00000 |Current airfoil nodes set from buffer airfoil nodes ( 160 )Once the airfoil has been loaded successfully it can be analyzed. Let's analyze it for a range of angles of attack, at a\nReynolds number of one million. Let's limit the maximum number of iterations to 40 (the default is 20) as well.\nFor the range of angles of attack, we will go from -20 degrees to 20 degrees with steps of 0.5 degrees:>>>xf.Re=1e6>>>xf.max_iter=40>>>a,cl,cd,cm=xf.aseq(-20,20,0.5)The XFOIL library should produce a lot of output, which should be familiar to those who have used the original XFOIL\napplication before. The final result are lists of angles of attack,a, and the corresponding lift coefficients,cl,\ndrag coefficients,cd, and moment coefficients,cm. We can now, for example, plot the lift curve for this airfoil:>>>importmatplotlib.pyplotasplt>>>plt.plot(a,cl)>>>plt.show()This should produce the following figure:Just like in the original XFOIL application, an airfoil can also analyzed for a single angle of attack, single lift\ncoefficient, or a range of lift coefficients. The commands for these operations are>>>cl,cd,cm=xf.a(10)>>>a,cd,cm=xf.cl(1)>>>a,cl,cd,cm=xf.cseq(-0.5,0.5,0.05)to analyze for an angle of attack of 10 degrees, a lift coefficient of 1.0, and for a range of lift coefficients from\n-0.5 to 0.5 with steps of 0.05.For other features and specifics, see the documentation in the Python source files."} +{"package": "xfoil-wrapper", "pacakge-description": "No description available on PyPI."} +{"package": "xfork", "pacakge-description": "Write a classic sequential program. Then convert it into a parallel one.Why?It runs faster.What if not?Don\u2019t use it.How?Before:forimageinimages:create_thumbnail(image)After:fromforkimportforkforimageinimages:fork(create_thumbnail,image)What about return values?As usual:result=fork(my_func,*args,**kwargs)It\u2019s a proxy object that behaves almost exactly like the real return value ofmy_funcexcept that\nit\u2019s lazy.How lazy?Very lazy. You can even add, multiply, etc. such proxy results without blocking which come in\nquite handy, especially in loops. Usefork.await,str,print, etc. to force evaluation\nand get the real and non-lazy value back.sizes=0forimageinimages:sizes+=fork(create_thumbnail,image)# lazy evaluationprint(sizes)# forces evaluationThreads or Processes?You don\u2019t need to bother. fork will take care of that for you.You can assist fork by decorating your functions; not decorating defaults tofork.cpu_bound:@io_bounddefcall_remote_webservice():# implementation@cpu_bounddefheavy_computation(n):# implementationException handlingOriginal (sequential) tracebacks are preserved. That should make debugging easier.\nHowever, don\u2019t try to catch exceptions. You better want to exit and see them.\nWhen you force evaluation potential exceptions will be raised.Advanced Feature: Force Specific Type of ExecutionIf you really need more control over the type of execution, usefork.processorfork.thread.\nThey work just likefork.forkbut enforce the corresponding type of background execution.importpkg_resourcesforworker_functioninpkg_resources.iter_entry_points(group='worker'):process(worker_function)Advanced Feature: Multiple Execution At OnceYou can shorten your programs by usingfork.map. It works likefork.forkbut submits\na function multiple times for each item given by an iterable.results=fork.map(create_thumbnail,images)fork.map_processandfork.map_threadwork accordingly and force a specific type of\nexecution. Use those if really necessary.\nOtherwise, just usefork.map. fork take care for you in this case again.In order to wait for the completion of a set of result proxies, usefork.await_all. If you want to\nunblock by the first unblocking result proxy, callfork.await_any.There are also blocking variants available:fork.block_map,fork.block_map_processandfork.block_map_thread; in case you need some syntactic sugar:fork.await_all(fork.map(create_thumbnail,images))# equalsfork.block_map(create_thumbnail,images)ConclusionGoodeasy to give it a try / easy way from sequential to parallel and backresults evaluate lazilysequential tracebacks are preservedit\u2019s thread-safe / cascading forks possiblecompatible with Python 2 and 3Badweird calling syntax (no syntax support)type(result) == ResultProxynot working with lambdas due to PickleErrorneeds fix:not working with coroutines (asyncio) yet (working on it)cannot fix efficiently:exception handling (force evaluation when entering and leaving try blocks)ideas are welcome :-)"} +{"package": "xform", "pacakge-description": "xform [WIP]xformis a library to transform spatial data from one space to another and\nprovides a common interface to combine different types of transforms.It was originally written fornavisto transform neurons from one brain template space to another and then\nsplit off into a separate general-purpose package.Featuresvarious supported transforms (see below)chaining of transformsa template registry that tracks available transforms and plots paths to\nget from a given source to the desired target template spaceSupported transformsCMTKwarp transformsElastixwarp transformsH5 deformation fieldsLandmark-based thin-plate spline transforms (powered bymorphops)Landmark-based least-moving square transforms (powered bymolesq)Affine transformationsInstall$ pip3 install xformAdditional dependencies:To use CMTK transforms, you need to haveCMTKinstalled and its binaries (specificallystreamxform) in a path wherexformcan find them (e.g./usr/local/bin).UsageSingle transformsAt the most basic level you can use individual transform fromxform.transforms:AffineTransformfor affine transforms using aaffine matrixCMTKtransformfor CMTK transformsElastixTransformfor Elastix transformsTPStransformorMovingLeastSquaresTransformfor landmark-based transformsH5transformfor deformation-field transforms using Hdf5 files\n(specs)A quick example that uses an affine transform to scale coordinates by a factor\nof 2:>>>importxform>>>importnumpyasnp>>># Generate the affine matrix>>>m=np.diag([2,2,2,2])>>># Create the transform>>>tr=xform.AffineTransform(m)>>># Some 3D points to transform>>>points=np.array([[1,1,1],[2,2,2],[3,3,3]])>>># Apply>>>xf=tr.xform(points)>>>xfarray([[2.,2.,2.],[4.,4.,4.],[6.,6.,6.]])>>># Transforms are invertible!>>>(-tr).xform(xf)array([[1.,1.,1.],[2.,2.,2.],[3.,3.,3.]])Transform sequencesIf you find yourself in a situation where you need to chain some transforms,\nyou can usexform.transforms.TransformSequenceto combine transforms.For example, let's say we have a CMTK transform that requires spatial data to\nbe in microns but our data is in nanometers:>>>fromxformimportCMTKtransform,AffineTransform,TransformSequence>>>importnumpyasnp>>># Initialize CMTK transform>>>cmtk=CMTKtransform('~/transform/target_source.list')>>># Create an affine transform to go from microns to nanometers>>>aff=AffineTransform(np.diag([1e3,1e3,1e3,1e3]))>>># Create a transform sequence>>>tr=TransformSequence([-aff,cmtk])>>># Apply transform>>>points=np.array([[1,1,1],[2,2,2],[3,3,3]])>>>xf=tr.xform(points)Bridging graphsWhen working with many interconnected transforms (e.g. A->B, B->C, B->D, etc.),\nyou can register the individual transforms and letxformplot the shortest\npath to get from a given source to a given target for you:>>>importxform>>>fromxformimportCMTKtransform,AffineTransform,TransformRegistry>>>importnumpyasnp>>># Create a transform registry>>>registry=TransformRegistry()>>># Generate a couple transforms>>># Note that we now provide source and target labels>>>tr1=AffineTransform(np.diag([1e3,1e3,1e3,1e3]),...source_space='A',target_space='B')>>>cmtk=CMTKtransform('~/transform/C_B.list',...source_space='B',target_space='C')>>># Register the transforms>>>registry.register_transform([tr1,cmtk])>>># Now you ask the registry for the required transforms to move between spaces>>>path,trans_seq=registry.shortest_bridging_seq(source='A',target='C')>>>patharray(['A','B','C'],dtype='>>trans_seqTransformSequencewith2transform(s)Custom transformsTODO"} +{"package": "xformer", "pacakge-description": "No description available on PyPI."} +{"package": "xformers", "pacakge-description": "XFormers: A collection of composable Transformer building blocks.XFormers aims at being able to reproduce most architectures in the Transformer-family SOTA,defined as compatible and combined building blocks as opposed to monolithic models"} +{"package": "xforms", "pacakge-description": "xformsAsync HTML forms for StarletteInstallationInstallxformsusing PIP or poetry:pipinstallxforms# orpoetryaddxformsFeaturesTODOQuick startSee example application inexamples/directory of this repository."} +{"package": "xformula", "pacakge-description": "XFormulaHighly customizable language front-end, aimed to be a base\nfor custom DSL evaluators.Developer note:I've created this library to use in many of my projects and\ndecided to publish the source code, because it may help somebody to write a DSL\ncompiler or evaluator can get benefit from Python ecosystem, within a reasonable\ntime.I couldn't write documentation because of my tight schedule in these days.\nBut I see the code as self-explanatory, feel free to read it if you're interested.In the meantime, please note thatthis project is still in development.Features:Built on top ofLark Parser ToolkitLALR(1), Earley and CYK parsing algorithms are supported by Lark;\nXFormula uses LALR(1) by defaultAutomatic EBNF grammar generator via declarative Python functions\n(The final grammar generated using the default features can be found inout/Grammar.larkfile)Modular featurization system to manipulate grammar and parser context dynamically.A ready-to-use compact dialect that supports some general purpose data types\nand basic symbols\n(Seexformula.syntax.astpackage)Seexformula.syntax.core.featurespackage andxformula.syntax.core.operations.default_operator_precedencesmodule for more\ninformation about the default behaviours.LicenseMIT"} +{"package": "xfox", "pacakge-description": "Asynchronous Low-code compiler for pythongithubHow to installpipinstallxfoxClear Exampleimportasyncioimportxfox,time#Custom Function@xfox.addfunc(xfox.funcs)asyncdeftest_func(item:str,*args,**kwargs):print(\"-----\",kwargs)@xfox.addfunc(xfox.funcs)asyncdefsomef(item:str,*args,**kwargs):returnkwargs[\"ctx\"]@xfox.addfunc(xfox.funcs)asyncdeffunction4(*args,**kwargs):return\"FOX\"@xfox.addfunc(xfox.funcs)asyncdeffunction1(item:int,type:bool,*args,**kwargs):returntype,args@xfox.addfunc(xfox.funcs)asyncdeffunction2(item:str,*args,**kwargs):awaitxfox.isempty(item)returneval(item)@xfox.addfunc(xfox.funcs)asyncdefinside(item:str,type:bool=False,*args,**kwargs):returntype@xfox.addfunc(xfox.funcs,'usefunc')asyncdeffunctest(func:xfox.AnonFunction,*args,**kwargs):return(awaitfunc.compile(),func.name)# Sync Parsingprint(asyncio.run(xfox.parse(\"\"\"// TRASH (xd) //$test_func[$test_func[sfsaf]]$function1[1;$inside[true];$sadsadsdsd[]] $onlyif[1<2;ONLYIF]$function2[1+2;dsadasd] sometext$function4[]$function1[1;$inside[fsfdfd;true];$sadsadsdsd[]]$sdasdasd[sadsadsad]sdasdsa $exec[true;print(1+231321, end='')] $exec[true;print(1+231321, end='')] $exec[true;print(1+231321, end='')]// Let/Get //$let[test;good]$get[test]// Internal Functions Test //$usefunc[$def[$print[hello!]]]$Test[]$def[$print[hello!];Test]$Test[]// While Test //$let[a;0]$while[$eval[$get[a]<=5];$let[a;$eval[$get[a]+1]]]$get[a]123 $while[True;$if[$get[a]<15;$let[a;$eval[$get[a]+1]];$break[]] $get[a]]123 $while[True;$break[]]$break[]// For Test //$for[1..5;$get[i]]$for[5;$get[i] $break[]]// Try Test //$try[ERROR $get[_];$function1[]]$try[$print[$get[_]];$function2[]]$try[$get[_];$raise[name;text]]// Import usage$import[ttest]$functiomm[] <- (custom function from ttest)//// Exit - $exit[]//// a Comment // | &s Not a Comment &s\"\"\",ctx=\"asdsdsdasds\")))Output:----- {'ctx': 'asdsdsdasds'}\n----- {'ctx': 'asdsdsdasds'}\n[LOG] hello!\n[LOG] hello!\n[LOG] Mising var item in function2\nNone\n(False, ('$sadsadsdsd[]',)) \n3 sometext\nFOX\n(True, ('$sadsadsdsd[]',))\n$sdasdasd[sadsadsad]\nsdasdsa 231322 231322 231322\n\n\n\ngood\n\n\n('', 'd489c9')\n$Test[]\n\n\n\n\n\n\n6\n123 789101112131415\n123\n\n\n\n12345\n\n\n\nERROR Mising var type in function1\n\n[ERROR] name: text\n\n\n\nHello, world!\n\n\n\n | // Not a Comment //\nPS C:\\Users\\user\\Documents\\xfox> & C:/Users/user/AppData/Local/Programs/Python/Python310/python.exe c:/Users/user/Documents/xfox/test.py\n----- {'ctx': 'asdsdsdasds'}\n----- {'ctx': 'asdsdsdasds'}\n[LOG] hello!\n[LOG] hello!\n[LOG] Mising var item in function2\nNone\n(False, ('$sadsadsdsd[]',))\n3 sometext\nFOX\n(True, ('$sadsadsdsd[]',))\n$sdasdasd[sadsadsad]\nsdasdsa 231322 231322 231322\n\n\n\ngood\n\n\n('', 'dd6fe4')\n$Test[]\n\n\n\n\n\n\n6\n123 789101112131415\n123\n\n\n\n12345\n\n\n\nERROR Mising var type in function1\n\n[ERROR] name: text\n\n// Import usage\n\nHello, world! <- (custom function from ttest)\n//\n\n\n\n | // Not a Comment //Interactive Xfox Interpreterpython-mxfoxOrxfoxStart xfox filespython-mxfox(filename).xfoxOrxfox(filename).xfoxExamplespackage for creation Discord bots (outaded)"} +{"package": "xfpip", "pacakge-description": "\u6a21\u5757\u8bf4\u660e\nxfpip \u4ec5\u7528\u4e8e\u5b66\u4e60pip\u5f00\u6e90\u5305\u7684\u5236\u4f5c\u600e\u4e48\u7528"} +{"package": "xfps", "pacakge-description": "No description available on PyPI."} +{"package": "xframe", "pacakge-description": "IntroductionThe main objective ofxFrameis to provide an easy and flexible framwork that handles details such asData storage / File accessSettings managementMultiprocessingGPU accessAllowing users to focus on the \"scientific\" part of their algorithm.xFramehas been created during our quest of writing a toolkit for fluctuation X-ray scattering.\nTo installxFramesimply callpip install xframe\n# For the fluctuation scattering toolkit use the following command instead (see next section)\npip install 'xframe[fxs]'For more information and tutorials visit the documentaiton atxframe-fxs.readthedocs.ioFluctuation X-Ray Scattering Toolkit [fxs]The projectfxscomes bundled withxFrameand provides a workflow for 3D structure determination from fluctuation X-ray scattering data.Note: No data is required to perform test reconstructions, further information as well as tutorials can be found atxframe-fxs.readthedocs.io/en/latest/fxsTo installxFrametogether with the dependencies needed byfxssimply callpip install 'xframe[fxs]'please make sure that the following libraries are installed on your system before callingpip installGNU Scientific LibraryOpenCLCitationIf you find this piece of software usefull for your scientific project consider citing the paperStill in review ... :)"} +{"package": "xframes", "pacakge-description": "The XFrames Library provides a consistent and scalable data science\nlibrary that is built on top of industry-standard open source\ntechnologies. XFrames provides the following advantages compared to other\nDataFrame implementations:A simple and well-tested Data Science library and Python based\ninterface.Powerful abstraction over underlying scalable big data and machine\nlearning frameworks: Apache Spark, Spark DataFrames and ML libraries.Dockerized container that bundles IPython notebooks, scientific\nlibraries, Apache Spark and other dependencies for painless setup.The library is extensible, allowing developers to add their own\nuseful features and functionality.How XFrames Benefits YouIf you\u2019re a data scientist, XFrames will isolate framework dependencies\nand their configuration within a single disposable, containerized\nenvironment, without compromising on any of the tools you\u2019re used to\nworking with (notebooks, dataframes, machine learning and big data\nframeworks, etc.). Once you or someone else creates a single XFrames\ncontainer, you just need to run the container and everything is\ninstalled and configured for you to work. Other members of your team\ncreate their development environments from the same configuration, so\nwhether you\u2019re working on Linux, Mac OS X, or Windows, all your team\nmembers are running data experiments in the same environment, against\nthe same dependencies, all configured the same way. Say goodbye to\npainful setup times and \u201cworks on my machine\u201d bugs.Minimum RequirementsSpark 1.6 or 2.1.Linux:Ubuntu 12.04 and aboveDocker >= 1.5 installationMac:Docker >= 1.5 installationWindowsRun in VMGetting StartedThe easiest way to get started is to download the XFrames library, build a\nDocker container that has everything you need, and run using an ipython notebook\nwithin Docker.Download LibraryClone XFrames this way:git clone https://github.com/chayden/xframes.gitBuild Docker ContainerGo to the docker directory and follow the build instructions in\nREADME.md.Review Introductory PresentationAfter starting docker container, browse tohttp://localhost:7777/tree.\nThen open info/Presentation.ipynb. If you execute the cells in this\nnotebook, then XFrames is up and running.DocumentationYou can view local documentation with the Docker container onhttp://localhost:8000.You can also view documentation athttp://xframes.readthedocs.org/Install Library On Existing Spark InstallationIf you have an existing Spark installation that you already use with\npySpark, then you can simply install the library to work with that.You can install using pip or you can get the source and either:Include the xframes directory in PYTHONPATH, orBuild an archive (see below) and install it on a different machine.Install With PipYou can also install with pip:pip install xframesUsing XFrames DirectoryIf you want to run using the source distribution, the most direct way\nis to include its xframes directory in PYTHONPATH:export PYTHONPATH=:$PYTHONPATHBuilding the LibraryIf you want to make a zip file that you can use to install XFrames on a\ndifferent machine, go to the source main directory and run:python setup.py sdist --formats=zipThis will create a file dist/xframes-.zip This file can be copied to\nthe server where you want to install xframes.Install by:unzip xframes..zip\ncd xframes.\npython setup.py installRunning XFramesXFrames uses pySpark, so you have to have Spark set up.You might have an existing Spark installation running in Cluster Mode,\nmanaged by the the Standalone, YARN, or Mesos cluster manager.\nIn this case, you need to set \u201cmaster\u201d to point to the cluster, using one\nof the configuration methods described below.Setting Up SparkIf you do not already have Spark, it is easy to set it up in local mode.Download spark fromhttp://spark.apache.org/downloads.htmlGet the tar.gz, uncompress it, and put it in some convenient directory.\nThe path to py4j is dependent on the spark version: this one works with spark 1.2.\nThen set:export SPARK_HOME=\nexport PYTHONPATH=${SPARK_HOME}/python:${SPARK_HOME}/python/lib/py4j-0.10.4-src.zipYou can test by running this program:test.py:\nfrom xframes import XFrame\nprint XFrame({'id': [1, 2, 3], 'val': ['a', 'b', 'c']})Run:$ python test.pyThis should print:+----+-----+\n| id | val |\n+----+-----+\n| 1 | a |\n| 2 | b |\n| 3 | c |\n+----+-----+\n[? rows x 2 columns]You may notice that a great deal of debug output appears on stdout.\nThis is because, by default, Spark displays log output on stdout.\nYou can change this by supplying a log4j.properties file and setting\nSPARK_CONF_DIR to the directory containing it. There is a sample\nconfig dir \u201cconf\u201d under the xframes install directory. You can copy this\nto your current directory and set:export SPARK_CONF_DIR=`pwd`/confThen when you run, you will see only the output that your program prints.Running in a IPython NotebookXFrames works especially well in an IPython notebook.\nIf you set up Spark as outline above, by setting PYTHONPATH, SPARK_HOME\nand SPARK_CONF_DIR before you launch the notebook server, then\nyou can run the same test program and get the expected results.See the bloghttp://blog.cloudera.com/blog/2014/08/how-to-use-ipython-notebook-with-apache-spark/for more information on how to set up an existing Spark installation to use with\niIPython notebook.Running in a Virtual EnvironmentXFrames works well in a virtual environment.Create a virtual environment:virtualenv venvAnd then install into it:source venv/bin/activate\npip install xframesXFrames includes support for pandas and matplotlib, which you can\ninstall if you want to use them. For exammple:pip install pandas\npip install matplotlibAfter this, make sure Spark is set up. For example:export SPARK_HOME=~/tools/spark\nexport PYTHONPATH=${SPARK_HOME}/python:${SPARK_HOME}/python/lib/py4j-0.10.4-src.zipThen test:cat <>>fromxftpdimportsftp_server>>>SFTP=sftp_server(Port=2222)>>>SFTP.level='DEBUG'>>>SFTP.start()>>>print(SFTP.Addr)10.8.2.5>>>print(SFTP.User)w7Kg0Fo4Xp6Xo9C>>>print(SFTP.Pass)k2Ea0Ko4Rz6Gz3Z>>>>>>SFTP.stop()>>>Example connecting to SFTP server[root@CentOS]# sftp -P 2222 w7Kg0Fo4Xp6Xo9C@10.8.2.5Theauthenticityofhost'[10.8.2.5]:2222 ([10.8.2.5]:2222)'can't be established.RSA key fingerprint is SHA256:khgoV/GQIShUf4KWr2ZqvpI68KMUFRsedwx4E0hWgi0.RSA key fingerprint is MD5:d2:45:1b:d8:44:66:5f:66:b9:5e:8d:33:fb:01:0b:b1.Are you sure you want to continue connecting (yes/no)? yesWarning: Permanently added '[10.8.2.5]:2222' (RSA) to the list of known hosts.w7Kg0Fo4Xp6Xo9C@10.8.2.5'spassword:\nConnectedto10.8.2.5.\nsftp>dir\nnew.pytest.py\nsftp>bye[root@CentOS]#FTP ExamplePython3.7.4(default,Sep72019,18:27:02)[Clang10.0.1(clang-1001.0.46.4)]ondarwinType\"help\",\"copyright\",\"credits\"or\"license\"formoreinformation.>>>fromxftpdimportftp_server>>>FTP=ftp_server()>>>FTP.start()[I2020-07-1521:14:48]concurrencymodel:multi-thread[I2020-07-1521:14:48]masquerade(NAT)address:None[I2020-07-1521:14:48]passiveports:None>>>print(SFTP.Addr)10.8.2.5>>>print(FTP.User)h0Dy0Yq9Ks0Dm3T>>>print(FTP.Pass)m5Sg2Yk5Mk8Fa4K>>>>>>FTP.stop()>>>"} +{"package": "xftpd-mapp-john", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xftsim", "pacakge-description": "No description available on PyPI."} +{"package": "xfunctions", "pacakge-description": "xfunctionsUsageimportxfunctinosasxfmethods:xf.sleep(t:int)xf.get_dict_by_keys(source,keys:listordict,default_none:bool=True)xf.list_strip(the_list)xf.list_remove(the_list:list,ele=None)xf.list_strip_and_remove(the_list:list,ele=None)xf.x_mix(list_in_list,i=1,target=None)xf.path_join(base_dir:str,paths)"} +{"package": "xfw", "pacakge-description": "ContentsFeaturesMissing features / bugsExamplexfw is an eXtensible Fixed-Width file handling module.Featuresfield types (integers, strings, dates) are declared independently of\nfile structure, and can be extended through subclassing. (BaseField\nsubclasses)multi-field structure declaration (FieldList class)non-homogeneous file file structure declaration (FieldListFile)checksum/hash computation helpers (ChecksumedFile subclasses)does not depend on line notion (file may not contain CR/LF chars at all\nbetween successive field sets)Missing features / bugsstring trucating is multi-byte (UTF-8, \u2026) agnostic, and will mindlessly cut\nin the middle of any entity\nIf your fields are defined in number of characters of some encoding, just use\nprovide xfw with unicode objects, and do the transcoding outside it. Seecodecsstandard module.proper interface declarationfields (IntegerField, DateTimeField) should cast by default when parsingFieldList total length should be made optional, and only used to\nauto-generate annonymous padding at record end when longer that the sum of\nindividual fields lengths.ExampleDislaimer: give file format is purely hypothetical, does not some from any spec\nI know of, should not be taken as a guideline but just as a showcase of xfw\ncapabilities.Let\u2019s assume a file composed of a general header, containing some\nconstant-value 5-char identifier, a 3-char integer giving the number of records\ncontained, and an optional 20-char comment. It is followed by records, composed\nof a header itself composed of a date (YYYYMMDD), a row type (2-char integer)\nand number of rows (2-char integer), and followed by rows. Row types all start\nwith a time (HHMMSS), followed by fields which depend on row type:type 1: a 10-char stringtype 2: a 2-char integer, 8 chars of padding, a 1-char integerTo run the following code as a doctest, run:python -m doctest README.rstDeclare all file structures:>>> import xfw\n>>> ROOT_HEADER = xfw.FieldList([\n... (xfw.StringField(5), True, 'header_id'),\n... (xfw.IntegerField(3, cast=True), True, 'block_count'),\n... (xfw.StringField(15), False, 'comment'),\n... ], 23, fixed_value_dict={\n... 'header_id': 'HEAD1',\n... })\n>>> BLOCK_HEADER = xfw.FieldList([\n... (xfw.DateTimeField('%Y%m%d', cast=True), True, 'date'),\n... (xfw.IntegerField(2, cast=True), True, 'row_type'),\n... (xfw.IntegerField(2, cast=True), True, 'row_count'),\n... ], 12)\n>>> ROW_BASE = xfw.FieldList([\n... (xfw.DateTimeField('%H%M%S', cast=True), True, 'time'),\n... ], 6)\n>>> ROW_TYPE_DICT = {\n... 1: xfw.FieldList([\n... ROW_BASE,\n... (xfw.StringField(10), True, 'description'),\n... ], 16),\n... 2: xfw.FieldList([\n... ROW_BASE,\n... (xfw.IntegerField(2, cast=True), True, 'some_value'),\n... (xfw.StringField(8), False, None), # annonymous padding\n... (xfw.IntegerField(1, cast=True), True, 'another_value'),\n... ], 17),\n... }\n>>> def blockCallback(head, item_list=None):\n... if item_list is None:\n... row_count = head['row_count']\n... else:\n... row_count = len(item_list)\n... return row_count, ROW_TYPE_DICT[head['row_type']]\n>>> FILE_STRUCTURE = xfw.ConstItemTypeFile(\n... ROOT_HEADER,\n... 'block_count',\n... xfw.FieldListFile(\n... BLOCK_HEADER,\n... blockCallback,\n... separator='\\n',\n... ),\n... separator='\\n',\n... )Parse sample file through a hash helper wrapper (SHA1):>>> from cStringIO import StringIO\n>>> sample_file = StringIO(\n... 'HEAD1002blah \\n'\n... '201112260101\\n'\n... '115500other str \\n'\n... '201112260201\\n'\n... '11550099 8'\n... )\n>>> from datetime import datetime\n>>> checksumed_wrapper = xfw.SHA1ChecksumedFile(sample_file)\n>>> parsed_file = FILE_STRUCTURE.parseStream(checksumed_wrapper)\n>>> parsed_file == \\\n... (\n... {\n... 'header_id': 'HEAD1',\n... 'block_count': 2,\n... 'comment': 'blah',\n... },\n... [\n... (\n... {\n... 'date': datetime(2011, 12, 26, 0, 0),\n... 'row_type': 1,\n... 'row_count': 1,\n... },\n... [\n... {\n... 'time': datetime(1900, 1, 1, 11, 55),\n... 'description': 'other str',\n... },\n... ]\n... ),\n... (\n... {\n... 'date': datetime(2011, 12, 26, 0, 0),\n... 'row_type': 2,\n... 'row_count': 1,\n... },\n... [\n... {\n... 'time': datetime(1900, 1, 1, 11, 55),\n... 'some_value': 99,\n... 'another_value': 8,\n... },\n... ]\n... ),\n... ],\n... )\nTrueVerify SHA1 was properly accumulated:>>> import hashlib\n>>> hashlib.sha1(sample_file.getvalue()).hexdigest() == checksumed_wrapper.getHexDigest()\nTrueGenerate a file from parsed data (as it was verified correct above):>>> generated_stream = StringIO()\n>>> FILE_STRUCTURE.generateStream(generated_stream, parsed_file)\n>>> generated_stream.getvalue() == sample_file.getvalue()\nTrueLikewise, using unicode objects and producing streams of different binary\nlength, although containing the same number of entities. Note that\nfixed-values defined in format declaration are optional (ex:header_id),\nand dependent values are automaticaly computed (ex:block_count).Generate with unicode chars fitting in single UTF-8-encoded bytes:>>> import codecs\n>>> encoded_writer = codecs.getwriter('UTF-8')\n>>> input_data = (\n... {\n... 'comment': u'Just ASCII',\n... },\n... [],\n... )\n>>> sample_file = StringIO()\n>>> FILE_STRUCTURE.generateStream(encoded_writer(sample_file), input_data)\n>>> sample_file.getvalue()\n'HEAD1000Just ASCII '\n>>> len(sample_file.getvalue())\n23Generate again, with chars needing more bytes when encoded, and demonstrating\nchecksum generation:>>> wide_input_data = (\n... {\n... 'comment': u'\\u3042\\u3044\\u3046\\u3048\\u304a\\u304b\\u304d\\u304f\\u3051\\u3053\\u3055\\u3057\\u3059\\u305b\\u305d',\n... },\n... [],\n... )\n>>> wide_sample_file = StringIO()\n>>> checksumed_wrapper = xfw.SHA1ChecksumedFile(wide_sample_file)\n>>> FILE_STRUCTURE.generateStream(encoded_writer(checksumed_wrapper), wide_input_data)\n>>> wide_sample_file.getvalue()\n'HEAD1000\\xe3\\x81\\x82\\xe3\\x81\\x84\\xe3\\x81\\x86\\xe3\\x81\\x88\\xe3\\x81\\x8a\\xe3\\x81\\x8b\\xe3\\x81\\x8d\\xe3\\x81\\x8f\\xe3\\x81\\x91\\xe3\\x81\\x93\\xe3\\x81\\x95\\xe3\\x81\\x97\\xe3\\x81\\x99\\xe3\\x81\\x9b\\xe3\\x81\\x9d'\n>>> len(wide_sample_file.getvalue())\n53\n>>> hashlib.sha1(wide_sample_file.getvalue()).hexdigest() == checksumed_wrapper.getHexDigest()\nTrueStill, both parse to their respective original data:>>> encoded_reader = codecs.getreader('UTF-8')\n>>> FILE_STRUCTURE.parseStream(encoded_reader(StringIO(sample_file.getvalue())))[0]['comment']\nu'Just ASCII'\n>>> FILE_STRUCTURE.parseStream(encoded_reader(StringIO(wide_sample_file.getvalue())))[0]['comment']\nu'\\u3042\\u3044\\u3046\\u3048\\u304a\\u304b\\u304d\\u304f\\u3051\\u3053\\u3055\\u3057\\u3059\\u305b\\u305d'"} +{"package": "xfyun-tts", "pacakge-description": "not work yet, the audio buffer returned save to a mp3 or pcm file\nand the audio player not workxfyun_ttsthis is a tts driver usingxfyunfor unittsDependentwebsocket-clientapppublicInstallationpip install xfyun_ttsUsagein the beginning,from xfyun_tts import set_app_info\nimport unitts\n\nset_app_info(appid, apikey, apisecret)\ntts = unitts.init('xfyun_tts')\n\ntts.startLoop()\nwhile True:\n\tx = input()\n\ttts.say(x)\ntts.endLoop()"} +{"package": "xga", "pacakge-description": "What is X-ray: Generate and Analyse (XGA)?XGA is a Python module designed to make it easy to analyse X-ray sources that have been observed by the XMM-Newton Space telescope. It is based around declaring different types of source and sample objects which correspond to real X-ray sources, finding all available data, and then insulating the user from the tedious generation and basic analysis of X-ray data products.XGA will generate photometric products and spectra for individual sources, or whole samples, with just a few lines of code. It is not a pipeline itself, but pipelines for complex analysis can easily be built on top of it. XGA provides an easy to use (and parallelised) Python interface with XMM's Science Analysis System (SAS), as well as with XSPEC. A major goal of this module is that you shouldn't need to leave a Python environment at any point during your analysis, as all XMM products and fit results are read into an XGA source storage structure.This module also supports more complex analyses for specific object types; the easy generation of scaling relations, the measurement of gas masses for galaxy clusters, and the PSF correction of images for instance.Installing XGAThis is a slightly more complex installation than many Python modules, but shouldn't be too difficult. If you're\nhaving issues feel free to contact me.Data Required to use XGACleaned Event ListsThis is very important- Currently, to make use of this module, youmusthave access to cleaned XMM-Newton\nevent lists, as XGA is not yet capable of producing them itself.Region FilesIt will be beneficial if you have region files available, as it will allow XGA to remove interloper sources. If you\nwish to use existing region files, then they must be in a DS9 compatible format,point sourcesmust beredandextended sourcesmust begreen.The ModuleXGA has been uploaded to PyPi, so you can simply run:pipinstallxgaAlternatively, to get the current working version from the git repository run:gitclonehttps://github.com/DavidT3/XGAcdXGA\npythonsetup.pyinstallRequired DependenciesXGA depends on two non-Python pieces of software:XMM's Science Analysis System (SAS) - Version 17.0.0, but other versions should be largely compatible with the\nsoftware. SAS version 14.0.0 however, does not support features that PSF correction of images depends on.HEASoft's XSPEC - Version 12.10.1, but other versions should be largely compatible even if I have not tested them.All required Python modules can be found in requirements.txt, and should be added to your system during the\ninstallation of XGA.Excellent installation guides forSASandHEASoftalready exist, so I won't go into that in this readme.\nXGA will not run without detecting these pieces of software installed on your system.Optional DependenciesXGA can also make use of external software for some limited tasks, but they are not required to use\nthe module as a whole:The R interpreter.Rpy2 - A Python module that provides an interface with the R language in Python.LIRA - An R fitting package.The R interpreter, Rpy2, and LIRA are all necessary only if you wish to use the LIRA scaling relation fitting function.Configuring XGA -THIS SECTION IS VERY IMPORTANTBefore XGA can be used you must fill out a configuration file (a completed example can be foundhere).Follow these steps to fill out the configuration file:Import XGA to generate the initial, incomplete, configuration file.Navigate to ~/.config/xga and open xga.cfg in a text editor. The .config directory is usually hidden, so it is\nprobably easier to navigate via the terminal.Take note of the entries that currently have /this/is/required at the beginning, without these entries the\nmodule will not function.Set the directory where you wish XGA to save the products and files it generates. I just set it to xga_output,\nso wherever I run a script that imports XGA it will create a folder called xga_output there. You could choose to use\nan absolute path and have a global XGA folder however, it would make a lot of sense.You may also set an optional parameter in the [XGA_SETUP] section, 'num_cores'. If you wish to manually limit the\nnumber of cores that XGA is allowed to use, then set this to an integer value, e.g. num_cores = 10. You can also\nset this at runtime, by importing NUM_CORES from xga and setting that to a value.The root_xmm_dir entry is the path of the parent folder containing all of your observation data.Most of the other entries tell XGA how different files are named. clean_pn_evts, for instance, gives the naming\nconvention for the cleaned PN events files that XGA generates products from.Bear in mind when filling in the file fields that XGA uses the Python string formatting convention, so anywhere\nyou see {obs_id} will be filled formatted with the ObsID of interest when XGA is actually running.The lo_en and hi_en entries can be used to tell XGA what images and exposure maps you may already have. For instance,\nif you already had 0.50-2.00keV and 2.00-10.00keV images and exposure maps, you could set lo_en = ['0.50', '2.00'] and\nhi_en = ['2.00', '10.00'].Finally, the region_file entry tells XGA where region files for each observation are stored (if they exist).Disclaimer: If region files are supplied, XGA also expects at least one image per instrument per observation.I have tried to make this part as general as possible, but I am biased by how XCS generates and stores their data\nproducts. If you are an X-ray astronomer who wishes to use this module, but it seems to be incompatible with your setup,\nplease get in touch or raise an issue.Remote Data Access:If your data lives on a remote server, and you want to use XGA on a local machine, I recommend\nsetting up an SFTP connection and mounting the server as an external volume. Then you can fill out the configuration\nfile with paths going through the mount folder - its how I use it a lot of the time.XGA's First Run After ConfigurationThe first time you import any part of XGA, it will create an 'observation census', where it will search through\nall the observations it can find (based on your entries in the configuration file), check that there are events\nlists present, and record the pointing RA and DEC.This can take a while, but will only take that long on the first\nrun. The module will check the census against your observation directory and see if it needs to be updated on\nevery run.How to use the modulePlease refer to the tutorials in the documentation, which can be foundhereProblems and QuestionsIf you encounter a bug, or would like to make a feature request, please use the GitHubissuespage, it really helps to keep track of everything.However, if you have further questions, or just want to make doubly sure I notice the issue, feel free to send\nme an email atturne540@msu.edu"} +{"package": "xgame", "pacakge-description": "QAA question-answer app."} +{"package": "xganalyzer", "pacakge-description": "xG AnalyzerPackage for xG (expected goals) statistics aggregation"} +{"package": "xgb2sql", "pacakge-description": "Project name hereSummary description here.This file will become your README and also the index of your documentation.Installpip install xgb2sqlHow to useSo easy even I could do it!fromxgb2sqlimportcoreimportxgboostasxgbfromsklearn.datasetsimportload_breast_cancerfromsklearn.model_selectionimporttrain_test_splitX,y=load_breast_cancer(return_X_y=True)X_train,X_test,y_train,y_test=train_test_split(X,y,random_state=0)woo=xgb.XGBClassifier(n_estimators=5)woo.fit(X_train,y_train)xgb.to_graphviz(woo)tree=core.xgb2sql(woo.get_booster(),'breast_cancer')print(tree)WITH booster_output AS (\n\tSELECT\n\t\tCASE\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND ((f10 < 0.591250002) OR (f10 IS NULL))\n\t\tTHEN 0.191869915\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND (f10 >= 0.591250002)\n\t\tTHEN 0\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND ((f1 < 18.9599991) OR (f1 IS NULL))\n\t\tTHEN 0.120000005\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND (f1 >= 18.9599991)\n\t\tTHEN -0.13333334\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND ((f23 < 785.799988) OR (f23 IS NULL))\n\t\t\tAND ((f21 < 23.7399998) OR (f21 IS NULL))\n\t\tTHEN 0.155555561\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND ((f23 < 785.799988) OR (f23 IS NULL))\n\t\t\tAND (f21 >= 23.7399998)\n\t\tTHEN -0.100000001\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND (f23 >= 785.799988)\n\t\t\tAND ((f1 < 14.3000002) OR (f1 IS NULL))\n\t\tTHEN 0\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND (f23 >= 785.799988)\n\t\t\tAND (f1 >= 14.3000002)\n\t\tTHEN -0.191176474\n\t\tEND AS column_0, \n\t\tCASE\n\t\t\tWHEN ((f7 < 0.0500999987) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND ((f13 < 38.6049995) OR (f13 IS NULL))\n\t\tTHEN 0.17467472\n\t\t\tWHEN ((f7 < 0.0500999987) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND (f13 >= 38.6049995)\n\t\tTHEN 0.0302315652\n\t\t\tWHEN ((f7 < 0.0500999987) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND ((f1 < 18.9599991) OR (f1 IS NULL))\n\t\tTHEN 0.113052242\n\t\t\tWHEN ((f7 < 0.0500999987) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND (f1 >= 18.9599991)\n\t\tTHEN -0.124826349\n\t\t\tWHEN (f7 >= 0.0500999987)\n\t\t\tAND ((f22 < 103.25) OR (f22 IS NULL))\n\t\t\tAND ((f21 < 25.9249992) OR (f21 IS NULL))\n\t\tTHEN 0.140555695\n\t\t\tWHEN (f7 >= 0.0500999987)\n\t\t\tAND ((f22 < 103.25) OR (f22 IS NULL))\n\t\t\tAND (f21 >= 25.9249992)\n\t\tTHEN -0.0846852511\n\t\t\tWHEN (f7 >= 0.0500999987)\n\t\t\tAND (f22 >= 103.25)\n\t\t\tAND ((f21 < 20.3549995) OR (f21 IS NULL))\n\t\tTHEN -0.01987583\n\t\t\tWHEN (f7 >= 0.0500999987)\n\t\t\tAND (f22 >= 103.25)\n\t\t\tAND (f21 >= 20.3549995)\n\t\tTHEN -0.174933031\n\t\tEND AS column_1, \n\t\tCASE\n\t\t\tWHEN ((f27 < 0.142349988) OR (f27 IS NULL))\n\t\t\tAND ((f20 < 17.6149998) OR (f20 IS NULL))\n\t\t\tAND ((f13 < 35.2600021) OR (f13 IS NULL))\n\t\tTHEN 0.159918889\n\t\t\tWHEN ((f27 < 0.142349988) OR (f27 IS NULL))\n\t\t\tAND ((f20 < 17.6149998) OR (f20 IS NULL))\n\t\t\tAND (f13 >= 35.2600021)\n\t\tTHEN 0.0472318567\n\t\t\tWHEN ((f27 < 0.142349988) OR (f27 IS NULL))\n\t\t\tAND (f20 >= 17.6149998)\n\t\t\tAND ((f29 < 0.0649200007) OR (f29 IS NULL))\n\t\tTHEN -0.0155247366\n\t\t\tWHEN ((f27 < 0.142349988) OR (f27 IS NULL))\n\t\t\tAND (f20 >= 17.6149998)\n\t\t\tAND (f29 >= 0.0649200007)\n\t\tTHEN -0.119407289\n\t\t\tWHEN (f27 >= 0.142349988)\n\t\t\tAND ((f23 < 729.549988) OR (f23 IS NULL))\n\t\t\tAND ((f4 < 0.1083) OR (f4 IS NULL))\n\t\tTHEN 0.120342232\n\t\t\tWHEN (f27 >= 0.142349988)\n\t\t\tAND ((f23 < 729.549988) OR (f23 IS NULL))\n\t\t\tAND (f4 >= 0.1083)\n\t\tTHEN -0.108723581\n\t\t\tWHEN (f27 >= 0.142349988)\n\t\t\tAND (f23 >= 729.549988)\n\t\t\tAND ((f10 < 0.241250008) OR (f10 IS NULL))\n\t\tTHEN -0.0287595335\n\t\t\tWHEN (f27 >= 0.142349988)\n\t\t\tAND (f23 >= 729.549988)\n\t\t\tAND (f10 >= 0.241250008)\n\t\tTHEN -0.163232192\n\t\tEND AS column_2, \n\t\tCASE\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND ((f10 < 0.528550029) OR (f10 IS NULL))\n\t\tTHEN 0.151598975\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND ((f20 < 16.8250008) OR (f20 IS NULL))\n\t\t\tAND (f10 >= 0.528550029)\n\t\tTHEN 0.0131686451\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND ((f1 < 18.9599991) OR (f1 IS NULL))\n\t\tTHEN 0.101920418\n\t\t\tWHEN ((f7 < 0.0489199981) OR (f7 IS NULL))\n\t\t\tAND (f20 >= 16.8250008)\n\t\t\tAND (f1 >= 18.9599991)\n\t\tTHEN -0.113945559\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND ((f23 < 785.799988) OR (f23 IS NULL))\n\t\t\tAND ((f21 < 23.7399998) OR (f21 IS NULL))\n\t\tTHEN 0.131930456\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND ((f23 < 785.799988) OR (f23 IS NULL))\n\t\t\tAND (f21 >= 23.7399998)\n\t\tTHEN -0.0824727714\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND (f23 >= 785.799988)\n\t\t\tAND ((f12 < 2.02349997) OR (f12 IS NULL))\n\t\tTHEN -0.0275684185\n\t\t\tWHEN (f7 >= 0.0489199981)\n\t\t\tAND (f23 >= 785.799988)\n\t\t\tAND (f12 >= 2.02349997)\n\t\tTHEN -0.155280709\n\t\tEND AS column_3, \n\t\tCASE\n\t\t\tWHEN ((f27 < 0.145449996) OR (f27 IS NULL))\n\t\t\tAND ((f22 < 107.599998) OR (f22 IS NULL))\n\t\t\tAND ((f13 < 46.7900009) OR (f13 IS NULL))\n\t\tTHEN 0.142997682\n\t\t\tWHEN ((f27 < 0.145449996) OR (f27 IS NULL))\n\t\t\tAND ((f22 < 107.599998) OR (f22 IS NULL))\n\t\t\tAND (f13 >= 46.7900009)\n\t\tTHEN 0.00895034242\n\t\t\tWHEN ((f27 < 0.145449996) OR (f27 IS NULL))\n\t\t\tAND (f22 >= 107.599998)\n\t\t\tAND ((f21 < 20.0849991) OR (f21 IS NULL))\n\t\tTHEN 0.12236432\n\t\t\tWHEN ((f27 < 0.145449996) OR (f27 IS NULL))\n\t\t\tAND (f22 >= 107.599998)\n\t\t\tAND (f21 >= 20.0849991)\n\t\tTHEN -0.0948726162\n\t\t\tWHEN (f27 >= 0.145449996)\n\t\t\tAND ((f23 < 710.200012) OR (f23 IS NULL))\n\t\t\tAND ((f21 < 25.0550003) OR (f21 IS NULL))\n\t\tTHEN 0.0869635344\n\t\t\tWHEN (f27 >= 0.145449996)\n\t\t\tAND ((f23 < 710.200012) OR (f23 IS NULL))\n\t\t\tAND (f21 >= 25.0550003)\n\t\tTHEN -0.0576682575\n\t\t\tWHEN (f27 >= 0.145449996)\n\t\t\tAND (f23 >= 710.200012)\n\t\t\tAND ((f6 < 0.0892650038) OR (f6 IS NULL))\n\t\tTHEN -0.0451009385\n\t\t\tWHEN (f27 >= 0.145449996)\n\t\t\tAND (f23 >= 710.200012)\n\t\t\tAND (f6 >= 0.0892650038)\n\t\tTHEN -0.147640571\n\t\tEND AS column_4\n\tFROM breast_cancer\n\tWHERE source = 'test'\n)\n\nSELECT\n 1 / ( 1 + EXP ( - (\n column_0\n\t+ column_1\n\t+ column_2\n\t+ column_3\n\t+ column_4 ) ) ) AS score\nFROM booster_outputTada!"} +{"package": "xgbatch", "pacakge-description": "No description available on PyPI."} +{"package": "xgbauto", "pacakge-description": "AutoXGBXGBoost + Optuna: no brainerauto train xgboost directly from CSV filesauto tune xgboost using optunaauto serve best xgboot model using fastapiNOTE: PRs are currently not accepted. If there are issues/problems, please create an issue.InstallationInstall using pippip install xgbautoUsageTraining a model using AutoXGB is a piece of cake. All you need is some tabular data.Parameters################################################################################## required parameters################################################################################ path to training datatrain_filename=\"data_samples/binary_classification.csv\"# path to output folder to store artifactsoutput=\"output\"################################################################################## optional parameters################################################################################ path to test data. if specified, the model will be evaluated on the test data# and test_predictions.csv will be saved to the output folder# if not specified, only OOF predictions will be saved# test_filename = \"test.csv\"test_filename=None# task: classification or regression# if not specified, the task will be inferred automatically# task = \"classification\"# task = \"regression\"task=None# an id column# if not specified, the id column will be generated automatically with the name `id`# idx = \"id\"idx=None# target columns are list of strings# if not specified, the target column be assumed to be named `target`# and the problem will be treated as one of: binary classification, multiclass classification,# or single column regression# targets = [\"target\"]# targets = [\"target1\", \"target2\"]targets=[\"income\"]# features columns are list of strings# if not specified, all columns except `id`, `targets` & `kfold` columns will be used# features = [\"col1\", \"col2\"]features=None# categorical_features are list of strings# if not specified, categorical columns will be inferred automatically# categorical_features = [\"col1\", \"col2\"]categorical_features=None# use_gpu is boolean# if not specified, GPU is not used# use_gpu = True# use_gpu = Falseuse_gpu=True# number of folds to use for cross-validation# default is 5num_folds=5# random seed for reproducibility# default is 42seed=42# number of optuna trials to run# default is 1000# num_trials = 1000num_trials=100# time_limit for optuna trials in seconds# if not specified, timeout is not set and all trials are run# time_limit = Nonetime_limit=360# if fast is set to True, the hyperparameter tuning will use only one fold# however, the model will be trained on all folds in the end# to generate OOF predictions and test predictions# default is False# fast = Falsefast=FalsePython APITo train a new model, you can run:fromxgbautoimportAutoXGB# required parameters:train_filename=\"data_samples/binary_classification.csv\"output=\"output\"# optional parameterstest_filename=Nonetask=Noneidx=Nonetargets=[\"income\"]features=Nonecategorical_features=Noneuse_gpu=Truenum_folds=5seed=42num_trials=100time_limit=360fast=False# Now its time to train the model!axgb=AutoXGB(train_filename=train_filename,output=output,test_filename=test_filename,task=task,idx=idx,targets=targets,features=features,categorical_features=categorical_features,use_gpu=use_gpu,num_folds=num_folds,seed=seed,num_trials=num_trials,time_limit=time_limit,fast=fast,)axgb.train()CLITrain the model using theautoxgb traincommand. The parameters are same as above.xgbauto train \\\n --train_filename datasets/30train.csv \\\n --output outputs/30days \\\n --test_filename datasets/30test.csv \\\n --use_gpuYou can also serve the trained model using theautoxgb servecommand.xgbautoserve--model_pathoutputs/mll--host0.0.0.0--debugTo know more about a command, run:`xgbauto --help`xgbauto train --help\n\n\nusage: xgbauto [] train [-h] --train_filename TRAIN_FILENAME [--test_filename TEST_FILENAME] --output\n OUTPUT [--task {classification,regression}] [--idx IDX] [--targets TARGETS]\n [--num_folds NUM_FOLDS] [--features FEATURES] [--use_gpu] [--fast]\n [--seed SEED] [--time_limit TIME_LIMIT]\n\noptional arguments:\n -h, --help show this help message and exit\n --train_filename TRAIN_FILENAME\n Path to training file\n --test_filename TEST_FILENAME\n Path to test file\n --output OUTPUT Path to output directory\n --task {classification,regression}\n User defined task type\n --idx IDX ID column\n --targets TARGETS Target column(s). If there are multiple targets, separate by ';'\n --num_folds NUM_FOLDS\n Number of folds to use\n --features FEATURES Features to use, separated by ';'\n --use_gpu Whether to use GPU for training\n --fast Whether to use fast mode for tuning params. Only one fold will be used if fast mode is set\n --seed SEED Random seed\n --time_limit TIME_LIMIT\n Time limit for optimization"} +{"package": "xgbert", "pacakge-description": "No description available on PyPI."} +{"package": "xgbexcel", "pacakge-description": "xgbexcelPython package that converts an XGBRegressor model to an Excel formula expression.How to startFirst, you have to install the package.pipinstallxgbexcelHow to convert XGBRegressor model to an Excel formulaLoad packagesfrom xgbexcel import XGBtoExcel\nimport numpy as np\nfrom xgboost import XGBRegressorCreate dummy dataset and fit XGBRegressor modelX_train, y_train = np.random.randint(0, 1000, (100, 2)), np.random.randint(0, 10, 100)\nmodel = XGBRegressor(n_estimators=2, max_depth=1)\nmodel.fit(X_train, y_train)Convert XGBRegressor model to an Excel formulaxgb_excel_expr = XGBtoExcel(model)\nxgb_excel_expr.expressionThe features in the Excel formula are represented using thex1,x2,x3, etc. notation, where the numbers correspond to the enumeration of the features in theXGBRegressormodel andX_train. You can manually rename the features in the Excel formula to match the desired column names in the Excel sheet. Once you have renamed the features, you can copy the expression in the Excel sheet as a formula.feature_map = {'x1': 'feature1', 'x2': 'feature2'}\nxgb_excel_expr.rename_features(feature_map)\nxgb_excel_expr.expressionSave Excel expression to a filexgb_excel_expr.save_expr('dummy.txt')EnjoyTry it yourself in the example notebook:howXGBtoExcel.ipynb"} +{"package": "xgbfir", "pacakge-description": "UNKNOWN"} +{"package": "xgbimputer", "pacakge-description": "XGBImputer - Extreme Gradient Boosting ImputerXGBImputer is an effort to implement the concepts of the MissForest algorithm proposed by Daniel J. Stekhoven and Peter B\u00fchlmann[1] in 2012, but leveraging the robustness and predictive power of the XGBoost[2] algorithm released in 2014.The package also aims to simplify the process of imputing categorical values in a scikit-learn[3] compatible way.Installation$pipinstallxgbimputerApproachGiven a 2D array X with missing values, the imputer:1 - counts the missing values in each column and arranges them in the ascending order;2 - makes an initial guess for the missing values in X using the mean for numerical columns and the mode for the categorical columns;3 - sorts the columns according to the amount of missing values, starting with the lowest amount;4 - preprocesses all categorical columns with scikit-learn's OrdinalEncoder to get a purely numerical array;5 - iterates over all columns with missing values in the order established on step 1;5.1 - selects the column in context on the iteration as the target;5.2 - one hot encodes all categorical columns other than the target;5.3 - fits the XGBoost algorithm (XGBClassifier for the categorical columns and XGBRegressor for the numeric columns) where the target column has no missing values;5.4 - predicts the missing values of the target column and replaces them on the X array;5.5 - calculates the stopping criterion (gamma) for the numerical and categorical columns identified as having missing data;6 - repeats the process described in step 5 until the stopping criterion is met; and7 - returns X with the imputed values.ExampleimportpandasaspdfromxgbimputerimportXGBImputerdf=pd.read_csv('titanic.csv')df.head()| | PassengerId | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked |\n|---:|--------------:|---------:|:---------------------------------------------|:-------|------:|--------:|--------:|---------:|--------:|--------:|:-----------|\n| 0 | 892 | 3 | Kelly, Mr. James | male | 34.5 | 0 | 0 | 330911 | 7.8292 | nan | Q |\n| 1 | 893 | 3 | Wilkes, Mrs. James (Ellen Needs) | female | 47 | 1 | 0 | 363272 | 7 | nan | S |\n| 2 | 894 | 2 | Myles, Mr. Thomas Francis | male | 62 | 0 | 0 | 240276 | 9.6875 | nan | Q |\n| 3 | 895 | 3 | Wirz, Mr. Albert | male | 27 | 0 | 0 | 315154 | 8.6625 | nan | S |\n| 4 | 896 | 3 | Hirvonen, Mrs. Alexander (Helga E Lindqvist) | female | 22 | 1 | 1 | 3101298 | 12.2875 | nan | S |df=df.drop(columns=['PassengerId','Name','Ticket'])df.info()RangeIndex: 418 entries, 0 to 417\nData columns (total 8 columns):\n# Column Non-Null Count Dtype \n--- ------ -------------- ----- \n 0 Pclass 418 non-null int64 \n 1 Sex 418 non-null object \n 2 Age 332 non-null float64\n 3 SibSp 418 non-null int64 \n 4 Parch 418 non-null int64 \n 5 Fare 417 non-null float64\n 6 Cabin 91 non-null object \n 7 Embarked 418 non-null object \ndtypes: float64(2), int64(3), object(3)\nmemory usage: 26.2+ KBdf_missing_data=pd.DataFrame(df.isna().sum().loc[df.isna().sum()>0],columns=['missing_data_count'])df_missing_data['missing_data_type']=df.dtypesdf_missing_data['missing_data_percentage']=df_missing_data['missing_data_count']/len(df)df_missing_data=df_missing_data.sort_values(by='missing_data_percentage',ascending=False)df_missing_data| | missing_data_count | missing_data_type | missing_data_percentage |\n|:------|---------------------:|:--------------------|--------------------------:|\n| Cabin | 327 | object | 0.782297 |\n| Age | 86 | float64 | 0.205742 |\n| Fare | 1 | float64 | 0.00239234 |imputer=XGBImputer(categorical_features_index=[0,1,6,7],replace_categorical_values_back=True)X=imputer.fit_transform(df)XGBImputer - Epoch: 1 | Categorical gamma: inf/274. | Numerical gamma: inf/0.0020067522\nXGBImputer - Epoch: 2 | Categorical gamma: 274./0. | Numerical gamma: 0.0020067522/0.0000494584\nXGBImputer - Epoch: 3 | Categorical gamma: 0./0. | Numerical gamma: 0.0000494584/0.\nXGBImputer - Epoch: 4 | Categorical gamma: 0./0. | Numerical gamma: 0./0.type(X)numpy.ndarraypd.DataFrame(X).head(15)| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |\n|---:|----:|:-------|--------:|----:|----:|--------:|:----------------|:----|\n| 0 | 3 | male | 34.5 | 0 | 0 | 7.8292 | C78 | Q |\n| 1 | 3 | female | 47 | 1 | 0 | 7 | C23 C25 C27 | S |\n| 2 | 2 | male | 62 | 0 | 0 | 9.6875 | C78 | Q |\n| 3 | 3 | male | 27 | 0 | 0 | 8.6625 | C31 | S |\n| 4 | 3 | female | 22 | 1 | 1 | 12.2875 | C23 C25 C27 | S |\n| 5 | 3 | male | 14 | 0 | 0 | 9.225 | C31 | S |\n| 6 | 3 | female | 30 | 0 | 0 | 7.6292 | C78 | Q |\n| 7 | 2 | male | 26 | 1 | 1 | 29 | C31 | S |\n| 8 | 3 | female | 18 | 0 | 0 | 7.2292 | B57 B59 B63 B66 | C |\n| 9 | 3 | male | 21 | 2 | 0 | 24.15 | C31 | S |\n| 10 | 3 | male | 24.7614 | 0 | 0 | 7.8958 | C31 | S |\n| 11 | 1 | male | 46 | 0 | 0 | 26 | C31 | S |\n| 12 | 1 | female | 23 | 1 | 0 | 82.2667 | B45 | S |\n| 13 | 2 | male | 63 | 1 | 0 | 26 | C31 | S |\n| 14 | 1 | female | 47 | 1 | 0 | 61.175 | E31 | S |imputer2=XGBImputer(categorical_features_index=[0,1,6,7],replace_categorical_values_back=False)X2=imputer2.fit_transform(df)XGBImputer - Epoch: 1 | Categorical gamma: inf/274. | Numerical gamma: inf/0.0020067522\nXGBImputer - Epoch: 2 | Categorical gamma: 274./0. | Numerical gamma: 0.0020067522/0.0000494584\nXGBImputer - Epoch: 3 | Categorical gamma: 0./0. | Numerical gamma: 0.0000494584/0.\nXGBImputer - Epoch: 4 | Categorical gamma: 0./0. | Numerical gamma: 0./0.pd.DataFrame(X2).head(15)| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 |\n|---:|----:|----:|--------:|----:|----:|--------:|----:|----:|\n| 0 | 2 | 1 | 34.5 | 0 | 0 | 7.8292 | 41 | 1 |\n| 1 | 2 | 0 | 47 | 1 | 0 | 7 | 28 | 2 |\n| 2 | 1 | 1 | 62 | 0 | 0 | 9.6875 | 41 | 1 |\n| 3 | 2 | 1 | 27 | 0 | 0 | 8.6625 | 30 | 2 |\n| 4 | 2 | 0 | 22 | 1 | 1 | 12.2875 | 28 | 2 |\n| 5 | 2 | 1 | 14 | 0 | 0 | 9.225 | 30 | 2 |\n| 6 | 2 | 0 | 30 | 0 | 0 | 7.6292 | 41 | 1 |\n| 7 | 1 | 1 | 26 | 1 | 1 | 29 | 30 | 2 |\n| 8 | 2 | 0 | 18 | 0 | 0 | 7.2292 | 15 | 0 |\n| 9 | 2 | 1 | 21 | 2 | 0 | 24.15 | 30 | 2 |\n| 10 | 2 | 1 | 24.7614 | 0 | 0 | 7.8958 | 30 | 2 |\n| 11 | 0 | 1 | 46 | 0 | 0 | 26 | 30 | 2 |\n| 12 | 0 | 0 | 23 | 1 | 0 | 82.2667 | 12 | 2 |\n| 13 | 1 | 1 | 63 | 1 | 0 | 26 | 30 | 2 |\n| 14 | 0 | 0 | 47 | 1 | 0 | 61.175 | 60 | 2 |LicenseLicensed under anApache-2license.References[1]Daniel J. Stekhoven and Peter B\u00fchlmann. \"MissForest\u2014non-parametric missing value imputation for mixed-type data.\"[2]XGBoost[3]scikit-learn"} +{"package": "xgbm", "pacakge-description": "No description available on PyPI."} +{"package": "xgbmagic", "pacakge-description": "UNKNOWN"} +{"package": "xgboost", "pacakge-description": "InstallationFromPyPIFor a stable version, install usingpip:pip install xgboostFor building from source, seebuild."} +{"package": "xgboost2sql", "pacakge-description": "XGBoost\u6a21\u578b\u8f6csql\u8bed\u53e5\u5de5\u5177\u5305\u73b0\u5728\u662f\u5927\u6570\u636e\u91cf\u7684\u65f6\u4ee3\uff0c\u6211\u4eec\u5f00\u53d1\u7684\u6a21\u578b\u8981\u5e94\u7528\u5728\u7279\u522b\u5927\u7684\u5f85\u9884\u6d4b\u96c6\u4e0a\uff0c\u4f7f\u7528\u5355\u673a\u7684python\uff0c\u9700\u8981\u9884\u6d4b2\u30013\u5929\uff0c\u751a\u81f3\u66f4\u4e45\uff0c\u4e2d\u9014\u5f88\u6709\u53ef\u80fd\u4e2d\u65ad\u3002\u56e0\u6b64\u9700\u8981\u901a\u8fc7\u5206\u5e03\u5f0f\u7684\u65b9\u5f0f\u6765\u9884\u6d4b\u3002\u8fd9\u4e2a\u5de5\u5177\u5305\u5c31\u662f\u5b9e\u73b0\u4e86\u5c06\u8bad\u7ec3\u597d\u7684python\u6a21\u578b\uff0c\u8f6c\u6362\u6210sql\u8bed\u53e5\u3002\u5c06\u751f\u6210\u7684sql\u8bed\u53e5\u53ef\u4ee5\u653e\u5230\u5927\u6570\u636e\u73af\u5883\u4e2d\u8fdb\u884c\u5206\u5e03\u5f0f\u6267\u884c\u9884\u6d4b\uff0c\u80fd\u6bd4\u5355\u673a\u7684python\u9884\u6d4b\u5feb\u597d\u51e0\u4e2a\u91cf\u7ea7\u601d\u60f3\u78b0\u649e\u5fae\u4fe1\u5fae\u4fe1\u516c\u4f17\u53f7\u5e72\u996d\u4eba\u9b54\u90fd\u6570\u636e\u5e72\u996d\u4eba\u4ed3\u5e93\u5730\u5740\uff1ahttps://github.com/ZhengRyan/xgboost2sql\u5fae\u4fe1\u516c\u4f17\u53f7\u6587\u7ae0\uff1ahttps://mp.weixin.qq.com/s/z3IjzMFKP7iEoag5KP6nAApipy\u5305\uff1ahttps://pypi.org/project/xgboost2sql/\u73af\u5883\u51c6\u5907\u53ef\u4ee5\u4e0d\u7528\u5355\u72ec\u521b\u5efa\u865a\u62df\u73af\u5883\uff0c\u56e0\u4e3a\u5bf9\u5305\u7684\u4f9d\u8d56\u6ca1\u6709\u7248\u672c\u8981\u6c42xgboost2sql\u5b89\u88c5pip install\uff08pip\u5b89\u88c5\uff09pipinstallxgboost2sql# to installpipinstall-Uxgboost2sql# to upgradeSource code install\uff08\u6e90\u7801\u5b89\u88c5\uff09pythonsetup.pyinstall\u8fd0\u884c\u6837\u4f8b###\u3010\u6ce8\u610f\uff1a\uff1a\uff1a\u6838\u9a8c\u5bf9\u6bd4python\u6a21\u578b\u9884\u6d4b\u51fa\u6765\u7684\u7ed3\u679c\u548csql\u8bed\u53e5\u9884\u6d4b\u51fa\u6765\u7684\u7ed3\u679c\u662f\u5426\u4e00\u81f4\u8bf7\u67e5\u770b\u6559\u7a0b\u4ee3\u7801\u3011\"https://github.com/ZhengRyan/xgboost2sql/examples/tutorial_code.ipynb\"\u5bfc\u5165\u76f8\u5173\u4f9d\u8d56importxgboostasxgbfromsklearn.datasetsimportmake_classificationfromsklearn.model_selectionimporttrain_test_splitfromxgboost2sqlimportXGBoost2Sql\u8bad\u7ec31\u4e2axgboost\u4e8c\u5206\u7c7b\u6a21\u578bX,y=make_classification(n_samples=10000,n_features=10,n_informative=3,n_redundant=2,n_repeated=0,n_classes=2,weights=[0.7,0.3],flip_y=0.1,random_state=1024)X_train,X_test,y_train,y_test=train_test_split(X,y,random_state=1024)###\u8bad\u7ec3\u6a21\u578bmodel=xgb.XGBClassifier(n_estimators=3)model.fit(X_train,y_train)#xgb.to_graphviz(model)\u4f7f\u7528xgboost2sql\u5de5\u5177\u5305\u5c06\u6a21\u578b\u8f6c\u6362\u6210\u7684sql\u8bed\u53e5xgb2sql=XGBoost2Sql()sql_str=xgb2sql.transform(model)\u5c06sql\u8bed\u53e5\u4fdd\u5b58xgb2sql.save()\u5c06sql\u8bed\u53e5\u6253\u5370\u51fa\u6765print(sql_str)selectkey,1/(1+exp(-(tree_1_score+tree_2_score+tree_3_score)+(-0.0)))asscorefrom(selectkey,--tree1casewhen(f9<-1.64164519orf9isnull)thencasewhen(f3<-4.19117069orf3isnull)thencasewhen(f2<-1.31743848orf2isnull)then-0.150000006else-0.544186056endelsecasewhen(f3<1.23432565orf3isnull)thencasewhen(f7<-2.55682254orf7isnull)then-0.200000018elsecasewhen(f5<0.154983491orf5isnull)then0.544721723elsecasewhen(f3<0.697217584orf3isnull)then-0.150000006else0.333333373endendendelsecasewhen(f5<-1.0218116orf5isnull)thencasewhen(f0<-0.60882163orf0isnull)thencasewhen(f2<0.26019755orf2isnull)then0.0666666701else-0.300000012endelse-0.520000041endelse0.333333373endendendelsecasewhen(f9<1.60392439orf9isnull)thencasewhen(f3<0.572542191orf3isnull)thencasewhen(f5<0.653370142orf5isnull)thencasewhen(f7<-0.765973091orf7isnull)thencasewhen(f3<-0.432390809orf3isnull)then0.204000011else-0.485454559endelsecasewhen(f3<-1.20459461orf3isnull)then-0.5104478else0.441509455endendelsecasewhen(f7<0.133017987orf7isnull)thencasewhen(f8<0.320554674orf8isnull)then-0.290322572else0.368339777endelsecasewhen(f8<-0.211985052orf8isnull)then0.504000008else-0.525648415endendendelsecasewhen(f7<2.22314501orf7isnull)thencasewhen(f8<-0.00532855326orf8isnull)thencasewhen(f8<-0.204920739orf8isnull)then-0.533991575else-0.200000018endelse0.428571463endelsecasewhen(f3<1.33772755orf3isnull)thencasewhen(f0<-0.975171864orf0isnull)then0.163636371else0.51818186endelse-0endendendelsecasewhen(f3<1.77943277orf3isnull)thencasewhen(f7<-0.469875157orf7isnull)thencasewhen(f3<-0.536645889orf3isnull)thencasewhen(f9<1.89841866orf9isnull)then-0else0.333333373endelsecasewhen(f4<-2.43660188orf4isnull)then0.150000006else0.551020443endendelsecasewhen(f1<-0.0788691565orf1isnull)then0.150000006else-0.375endendelsecasewhen(f4<-1.73232496orf4isnull)then-0.150000006elsecasewhen(f6<-1.6080606orf6isnull)then-0.150000006elsecasewhen(f7<-0.259483218orf7isnull)then-0.558620751else-0.300000012endendendendendendastree_1_score,--tree2casewhen(f9<-1.64164519orf9isnull)thencasewhen(f3<-4.19117069orf3isnull)thencasewhen(f0<0.942570388orf0isnull)then-0.432453066else-0.128291652endelsecasewhen(f3<1.23432565orf3isnull)thencasewhen(f7<-2.55682254orf7isnull)then-0.167702854elsecasewhen(f5<0.154983491orf5isnull)thencasewhen(f1<2.19985676orf1isnull)then0.41752997else0.115944751endelse0.115584135endendelsecasewhen(f5<-1.0218116orf5isnull)thencasewhen(f0<-0.60882163orf0isnull)then-0.119530827else-0.410788596endelse0.28256765endendendelsecasewhen(f9<1.60392439orf9isnull)thencasewhen(f3<0.460727394orf3isnull)thencasewhen(f5<0.653370142orf5isnull)thencasewhen(f7<-0.933565617orf7isnull)thencasewhen(f3<-0.572475374orf3isnull)then0.182491601else-0.377898693endelsecasewhen(f3<-1.20459461orf3isnull)then-0.392539263else0.352721155endendelsecasewhen(f7<0.207098693orf7isnull)thencasewhen(f8<0.498489976orf8isnull)then-0.193351224else0.29298231endelsecasewhen(f8<-0.117464997orf8isnull)then0.400667101else-0.402199954endendendelsecasewhen(f7<1.98268723orf7isnull)thencasewhen(f8<-0.00532855326orf8isnull)thencasewhen(f7<1.36281848orf7isnull)then-0.408002198else-0.236123681endelsecasewhen(f5<1.14038813orf5isnull)then0.404326111else-0.110877581endendelsecasewhen(f3<1.56952488orf3isnull)thencasewhen(f5<2.14646816orf5isnull)then0.409404457else0.0696995854endelse-0.32059738endendendelsecasewhen(f3<1.77943277orf3isnull)thencasewhen(f7<-0.469875157orf7isnull)thencasewhen(f3<-0.536645889orf3isnull)thencasewhen(f9<1.89841866orf9isnull)then-0else0.28256765endelse0.419863999endelsecasewhen(f3<0.444227457orf3isnull)then-0.34664312else0.0693304539endendelsecasewhen(f4<-1.10089087orf4isnull)thencasewhen(f3<2.3550868orf3isnull)then0.0147894565else-0.331404865endelse-0.421277165endendendendastree_2_score,--tree3casewhen(f9<-1.64164519orf9isnull)thencasewhen(f3<-4.19117069orf3isnull)thencasewhen(f4<-1.30126143orf4isnull)then-0.0772174299else-0.374165356endelsecasewhen(f3<1.23432565orf3isnull)thencasewhen(f7<-2.55682254orf7isnull)then-0.142005175elsecasewhen(f5<0.154983491orf5isnull)thencasewhen(f7<3.59379435orf7isnull)then0.352122813else0.132789165endelse0.0924336985endendelsecasewhen(f5<-1.0218116orf5isnull)thencasewhen(f0<-0.60882163orf0isnull)then-0.0954768136else-0.351594836endelse0.245992288endendendelsecasewhen(f9<1.60392439orf9isnull)thencasewhen(f3<0.347133756orf3isnull)thencasewhen(f5<0.661561131orf5isnull)thencasewhen(f7<-0.933565617orf7isnull)thencasewhen(f3<-0.472413659orf3isnull)then0.116336405else-0.313245147endelsecasewhen(f3<-1.5402329orf3isnull)then-0.352897167else0.311400592endendelsecasewhen(f7<0.275665522orf7isnull)thencasewhen(f8<0.403402805orf8isnull)then-0.292606086else0.220064178endelsecasewhen(f8<-0.0442957953orf8isnull)then0.350784421else-0.336107522endendendelsecasewhen(f7<1.77503061orf7isnull)thencasewhen(f8<0.196157426orf8isnull)thencasewhen(f7<1.36281848orf7isnull)then-0.3376683else-0.0711223111endelsecasewhen(f7<-0.661211252orf7isnull)then0.434363276else-0.219307661endendelsecasewhen(f3<1.37940335orf3isnull)thencasewhen(f6<1.34894884orf6isnull)then0.367155522else0.124757253endelse-0.293739736endendendelsecasewhen(f3<1.77943277orf3isnull)thencasewhen(f7<-0.469875157orf7isnull)thencasewhen(f3<-0.536645889orf3isnull)thencasewhen(f9<1.89841866orf9isnull)then-0else0.245992288endelsecasewhen(f0<1.60565615orf0isnull)then0.357973605else0.193993196endendelsecasewhen(f9<1.89456153orf9isnull)then-0.276471078else0.111896731endendelsecasewhen(f1<1.35706067orf1isnull)thencasewhen(f4<-1.10089087orf4isnull)thencasewhen(f3<2.3550868orf3isnull)then0.0119848112else-0.284813672endelse-0.376859784endelsecasewhen(f2<-0.25748384orf2isnull)then0.0723158419else-0.253415495endendendendendastree_3_scorefromdata_table)"} +{"package": "xgboost-deploy", "pacakge-description": "XGBoost Python DeploymentThis package allows users to take their XGBoost models they developed in python, and package them in a way that they can deploy the model in production using only pure python.InstallationYou can install this from pip usingpip install xgboost-deploy-python. The current version is 0.0.2.It was tested on python 3.6 and and XGBoost 0.8.1.Deployment ProcessThe typical way of moving models to production is by using thepicklelibrary to export the model file, and then loading it into the container or server that will make the predictions usingpickleagain. Both the training and deployment environments require the same package and versions of those packages instsalled for this process to work correctly.This package follows a similar process for deployment, except that it relies only on a single JSON file, and the pure python code that makes predictions, removing the dependencies ofXGBoostandpicklein deployment.Below we will step through how to use this package to take an existing model and generate the file(s) needed for deploying your model. For a more detailed walk-through, please seeexample.py, which you can run locally to create your own files and view some potential steps for validating the consistency of your trained model vs the new production version.fmapCreationIn this step we use thefmapsubmodule to create a feature map file that the module uses to accurately generate the JSON files.Afmapfile format contains one line for each feature according to the following format: Some notes about the full file format:line_numbervalues start at zero and increase incrementally.feature_namevaluescannotcontain spaces in them or the file will truncate the feature names after the first space in the JSON model filefeature_typeoptions are as follows:qfor quantitative (or cintuous) variablesintfor integer valued variablesifor binary variables, please note that this field doesnotallow null values and always expects either a 0 or a 1. Your predictor function may error and fail.Here is anfmapfile generated using theexample.pyfile:0 mean_radius q\n1 mean_texture q\n2 mean_perimeter q\n3 mean_area q\n4 mean_smoothness q\n5 mean_compactness q\n6 mean_concavity q\n7 mean_concave_points q\n8 mean_symmetry q\n9 mean_fractal_dimension q\n10 radius_error q\n11 texture_error q\n12 perimeter_error q\n13 area_error q\n14 smoothness_error q\n15 compactness_error q\n16 concavity_error q\n17 concave_points_error q\n18 symmetry_error q\n19 fractal_dimension_error q\n20 worst_radius int\n21 worst_texture int\n22 worst_perimeter int\n23 worst_area int\n24 worst_smoothness i\n25 worst_compactness i\n26 worst_concavity i\n27 worst_concave_points q\n28 worst_symmetry q\n29 worst_fractal_dimension q\n30 target iYou can either generate yourfmapfile using lists of feature names and types using thegenerate_fmapfunction or automatically from apandasDataFrame using thegenerate_fmap_from_pandaswhich extracts column names and infers feature types.JSON Model CreationTheXGBoostpackage already contains a method to generate text representations of trained models in either text or JSON formats.Once you have thefmapfile created successfully and your model trained, you can generate the JSON model file directly using the following command:model.dump_model(fout='xgb_model.json',fmap='fmap_pandas.txt',dump_format='json')This should generate a JSON file in yourfoutlocation specified that should have a list of JSON objects, each representing a tree in your model. Here's an example of a subset of one such file:[{\"nodeid\":0,\"depth\":0,\"split\":\"worst_perimeter\",\"split_condition\":110,\"yes\":1,\"no\":2,\"missing\":1,\"children\":[{\"nodeid\":1,\"depth\":1,\"split\":\"worst_concave_points\",\"split_condition\":0.160299987,\"yes\":3,\"no\":4,\"missing\":3,\"children\":[{\"nodeid\":3,\"depth\":2,\"split\":\"worst_concave_points\",\"split_condition\":0.135049999,\"yes\":7,\"no\":8,\"missing\":7,\"children\":[{\"nodeid\":7,\"leaf\":0.150075898},{\"nodeid\":8,\"leaf\":0.0300908741}]},{\"nodeid\":4,\"depth\":2,\"split\":\"mean_texture\",\"split_condition\":18.7449989,\"yes\":9,\"no\":10,\"missing\":9,\"children\":[{\"nodeid\":9,\"leaf\":-0.0510330871},{\"nodeid\":10,\"leaf\":-0.172740772}]}]},{\"nodeid\":2,\"depth\":1,\"split\":\"worst_texture\",\"split_condition\":20,\"yes\":5,\"no\":6,\"missing\":5,\"children\":[{\"nodeid\":5,\"depth\":2,\"split\":\"mean_concave_points\",\"split_condition\":0.0712649971,\"yes\":11,\"no\":12,\"missing\":11,\"children\":[{\"nodeid\":11,\"leaf\":0.099997662},{\"nodeid\":12,\"leaf\":-0.142965034}]},{\"nodeid\":6,\"depth\":2,\"split\":\"mean_concave_points\",\"split_condition\":0.0284200013,\"yes\":13,\"no\":14,\"missing\":13,\"children\":[{\"nodeid\":13,\"leaf\":-0.0510330871},{\"nodeid\":14,\"leaf\":-0.251898795}]}]}]},{...}]Model PredictionsOnce the JSON file has been created, you need to perform three more things in order to make predictions:Store the base score value used in training your XGBoost modelNote whether your problem is a classification or regression problem.Right now, this package has only been tested for thereg:linearandbinary:logisticobjectives which represent regression and classification respectively.When building a classification model, youmustuse the default base_score value of 0.5 (which ends up not adding an intercept bias to the results). If you use any other value, the production model will produce predictions thatdo not matchthe predictions from the original model.Load the JSON model file into a python list of dictionaries representing each model tree.Once you have done that, you can create your production estimator:withopen('xgb_model.json','r')asf:model_data=json.load(f)pred_type='regression'base_score=0.5# default valueestimator=ProdEstimator(model_data=model_data,pred_type=pred_type,base_score=base_score)After that, all you have to do is format your input data into python dicts and pass them in individually to the estimator'spredictfunction.If you want more detailed info for validation purposes, there is aget_leaf_valuesfunction that can return either the leaf values or final nodes selected for each tree in the model for a given input.PerformanceAs mentioned at the top, the initial test results indicate that for regression problems, there is a 100% match in predictions between original and production versions of the models up to a 0.001 error tolerance.As for speed, for 10 trees, the prediction for input with 30 features is 0.00005 seconds with 0.000008 seconds standard deviation.Obviously as the number of trees grows, the speed should decrease linearly, but it should be simple to modify this to add in parallelized tree predictions if that becomes an issue.If you are really looking for optimized deployment tools, I would check out the following compiler for ensemble decision tree models:https://github.com/dmlc/treeliteInitial Test ResultsHere is the printed output for initial testing in theexample.pyfile if you want to see it without running it yourself:Benchmark regression modeling\n=============================\n\nActual vs Prod Estimator Comparison\n188 out of 188 predictions match\nMean difference between predictions: -1.270028868389972e-08\nStd dev of difference between predictions: 9.327025899795536e-09\n\nActual Estimator Evaluation Metrics\nAUROC Score 0.9780560216858138\nAccuracy Score 0.9521276595744681\nF1 Score 0.9649805447470817\n\nProd Estimator Evaluation Metrics:\nAUROC Score 0.9780560216858138\nAccuracy Score 0.9521276595744681\nF1 Score 0.9649805447470817\n\n\nTime Benchmarks for 1 records with 30 features using 10 trees\nAverage 3.938e-05 seconds with standard deviation 2.114e-06 per 1 predictions\n\n\nBenchmark classification modeling\n=================================\n\nActual vs Prod Estimator Comparison\n188 out of 188 predictions match\nMean difference between predictions: -1.7196643532927356e-08\nStd dev of difference between predictions: 2.7826259523143417e-08\n\nActual Estimator Evaluation Metrics\nAUROC Score 0.9777333161223698\nAccuracy Score 0.9468085106382979\nF1 Score 0.9609375\n\nProd Estimator Evaluation Metrics:\nAUROC Score 0.9777333161223698\nAccuracy Score 0.9468085106382979\nF1 Score 0.9609375\n\n\nTime Benchmarks for 1 records with 30 features using 10 trees\nAverage 3.812e-05 seconds with standard deviation 1.381e-06 per 1 predictionsLicenseLicensed under an MIT license."} +{"package": "xgboost-distribution", "pacakge-description": "xgboost-distributionXGBoost for probabilistic prediction. LikeNGBoost, butfaster, and in theXGBoost scikit-learn API.Installation$pipinstallxgboost-distributionDependencies:python_requires = >=3.8\n\ninstall_requires =\n scikit-learn\n xgboost>=2.0.0UsageXGBDistributionfollows theXGBoost scikit-learn API, with an additional keyword\nargument specifying the distribution, which is fit viaMaximum Likelihood Estimation:fromsklearn.datasetsimportfetch_california_housingfromsklearn.model_selectionimporttrain_test_splitfromxgboost_distributionimportXGBDistributiondata=fetch_california_housing()X,y=data.data,data.targetX_train,X_test,y_train,y_test=train_test_split(X,y)model=XGBDistribution(distribution=\"normal\",n_estimators=500,early_stopping_rounds=10)model.fit(X_train,y_train,eval_set=[(X_test,y_test)])See thedocumentationfor all available distributions.After fitting, we can predict the parameters of the distribution:preds=model.predict(X_test)mean,std=preds.loc,preds.scaleNote that this returned anamedtupleofnumpy arraysfor each parameter of the\ndistribution (we use thescipy statsnaming conventions for the parameters, see e.g.scipy.stats.normfor the normal distribution).NGBoost performance comparisonXGBDistributionfollows the method shown in theNGBoostlibrary, using natural\ngradients to estimate the parameters of the distribution.Below, we show a performance comparison ofXGBDistributionand theNGBoostNGBRegressor, using the California Housing dataset, estimating normal distributions.\nWhile the performance of the two models is fairly similar (measured on negative\nlog-likelihood of a normal distribution and the RMSE),XGBDistributionis around15x faster(timed on both fit and predict steps):Please see theexperiments pagefor results across various datasets.Full XGBoost featuresXGBDistributionoffers the full set of XGBoost features available in theXGBoost scikit-learn API, allowing, for example, probabilistic regression\nwithmonotonic constraints:AcknowledgementsThis package would not exist without the excellent work from:NGBoost- Which demonstrated how gradient boosting with natural gradients\ncan be used to estimate parameters of distributions. Much of the gradient\ncalculations code were adapted from there.XGBoost- Which provides the gradient boosting algorithms used here, in\nparticular thesklearnAPIs were taken as a blue-print.NoteThis project has been set up using PyScaffold 4.0.1. For details and usage\ninformation on PyScaffold seehttps://pyscaffold.org/."} +{"package": "xgboost-label-encoding", "pacakge-description": "Xgboost Label Encoding (WIP)TODOs: Configuring this templateCreate a Netlify site for your repository, then turn off automatic builds in Netlify settings.Add these CI secrets:PYPI_API_TOKEN,NETLIFY_AUTH_TOKEN(Netlify user settings - personal access tokens),DEV_NETLIFY_SITE_ID,PROD_NETLIFY_SITE_ID(API ID from Netlify site settings)Set up Codecov at TODOOverviewInstallationpipinstallxgboost_label_encodingUsageDevelopmentSubmit PRs againstdevelopbranch, then make a release pull request tomaster.# Optional: set up a pyenv virtualenvpyenvvirtualenv3.9xgboost_label_encoding-3.9echo\"xgboost_label_encoding-3.9\">.python-version\npyenvversion# Install requirementspipinstall--upgradepipwheel\npipinstall-rrequirements_dev.txt# Install local packagepipinstall-e.# Install pre-commitpre-commitinstall# Run testsmaketest# Run lintmakelint# bump version before submitting a PR against master (all master commits are deployed)bump2versionpatch# possible: major / minor / patch# also ensure CHANGELOG.md updatedChangelog0.0.1First release on PyPI."} +{"package": "xgboost-launcher", "pacakge-description": "No description available on PyPI."} +{"package": "xgboostlss", "pacakge-description": "XGBoostLSS - An extension of XGBoost to probabilistic modellingWe introduce a comprehensive framework that models and predicts the full conditional distribution of univariate and multivariate targets as a function of covariates. Choosing from a wide range of continuous, discrete, and mixed discrete-continuous distributions, modelling and predicting the entire conditional distribution greatly enhances the flexibility of XGBoost, as it allows to create probabilistic forecasts from which prediction intervals and quantiles of interest can be derived.FeaturesEstimation of all distributional parameters.Normalizing Flows allow modelling of complex and multi-modal distributions.Mixture-Densities can model a diverse range of data characteristics.Multi-target regression allows modelling of multivariate responses and their dependencies.Zero-Adjusted and Zero-Inflated Distributions for modelling excess of zeros in the data.Automatic derivation of Gradients and Hessian of all distributional parameters usingPyTorch.Automated hyper-parameter search, including pruning, is done viaOptuna.The output of XGBoostLSS is explained usingSHapley Additive exPlanations.XGBoostLSS provides full compatibility with all the features and functionality of XGBoost.XGBoostLSS is available in Python.News2023-08-25: Release of v0.4.0 introduces Mixture-Densities. See therelease notesfor an overview.2023-07-19: Release of v0.3.0 introduces Normalizing Flows. See therelease notesfor an overview.2023-06-22: Release of v0.2.2. See therelease notesfor an overview.2023-06-21: XGBoostLSS now supports multi-target regression.2023-06-07: XGBoostLSS now supports Zero-Inflated and Zero-Adjusted Distributions.2023-05-26: Release of v0.2.1. See therelease notesfor an overview.2023-05-18: Release of v0.2.0. See therelease notesfor an overview.2021-12-22: XGBoostLSS now supports estimating the full predictive distribution viaExpectile Regression.2021-12-20: XGBoostLSS is initialized with suitable starting values to improve convergence of estimation.2021-12-04: XGBoostLSS now supports automatic derivation of Gradients and Hessians.2021-12-02: XGBoostLSS now supports pruning during hyperparameter optimization.2021-11-14: XGBoostLSS v0.1.0 is released!InstallationTo install XGBoostLSS, please runpipinstallxgboostlssAvailable DistributionsOur framework is built upon PyTorch and Pyro, enabling users to harness a diverse set of distributional families. XGBoostLSS currently supports thefollowing distributions.How to UsePlease visit theexample sectionfor guidance on how to use the framework.DocumentationFor more information and context, please visit thedocumentation.FeedbackWe encourage you to provide feedback on how to enhance XGBoostLSS or request the implementation of additional distributions by opening anew discussion.How to CiteIf you use XGBoostLSS in your research, please cite it as:@misc{Maerz2023,author={Alexander M\\\"arz},title={{XGBoostLSS: An Extension of XGBoost to Probabilistic Modelling}},year={2023},howpublished={\\url{https://github.com/StatMixedML/XGBoostLSS}}}Reference Paper"} +{"package": "xgboost-model", "pacakge-description": "XGBoost Model PackageThis is a XGBoost Model package. Github repository can be foundhere."} +{"package": "xgboost-model-jarushi", "pacakge-description": "XGBoost Model PackageThis is a XGBoost Model package. Github repository can be foundhere."} +{"package": "xgboost-ray", "pacakge-description": "A distributed backend for XGBoost built on top of distributed computing framework Ray."} +{"package": "xgboost_tuner", "pacakge-description": "No description available on PyPI."} +{"package": "xgboostwithwarmstart", "pacakge-description": "Seegithubfor more information."} +{"package": "xgb-rhomut", "pacakge-description": "XGBoost - $\\rho-\\mu-T$Next-generation non-linear and collapse prediction models for short to long period systems via machine learning methodsThe machine learning approach: Exterme Gradient Boosting (XGBoost)Makes predictions for a strength ratio - ductility - period relationshipsKey arguments:$R$ - strength ratio based on spectral acceleration$\\rho$ - strength ratio based on average spectral acceleration$\\mu$ - ductility$T$ - period$$\nR=\\frac{Sa(T)}{Sa_y}\n$$$$\n\\rho_2=\\frac{Sa_{avg,2}(T)}{Sa_y}\n$$$$\n\\rho_3=\\frac{Sa_{avg,3}(T)}{Sa_y}\n$$where$Sa(T)$ stands for spectral acceleration at fundamental period$Sa_y$ stands for spectral acceleration at yield$Sa_{avg,2}(T)$ stands for average spectral acceleration computed at periods\n$\u2208 [0.2T:2T]$$Sa_{avg,3}(T)$ stands for average spectral acceleration computed at periods\n$\u2208 [0.2T:3T]$Installationpip install xgb-rhomutExample predictionExample 1: Dynamic strength ratio prediction of non-collapse scenarios at a dynamic ductility level of 3.0:import xgbrhomut\nmodel = xgbrhomut.XGBPredict(im_type=\"sa_avg\", collapse=False)\nprediction = model.make_prediction(\n period=1, \n damping=0.05, \n hardening_ratio=0.02, \n ductility=4, \n dynamic_ductility=3.0\n)Example 2: Dynamic ductility prediction given a strength ratio of 3.0 (since im_type is \"sa_avg\", and collapse is False, \\rho_2 is being estimated):import xgbrhomut\nmodel = xgbrhomut.XGBPredict(im_type=\"sa_avg\", collapse=False)\nprediction = model.make_prediction(\n period=1, \n damping=0.05, \n hardening_ratio=0.02, \n ductility=4, \n strength_ratio=3.0\n)prediction:{\n \"median\": float,\n \"dispersion\": float\n}Other methodsxgbrhomut.r_mu_t.ec8.strength_ratio(mu=3, T=1, Tc=0.5)LimitationsLimitations in terms of input parameters are:$T$ \u2208 [0.01, 3.0] seconds$\\mu$ \u2208 [2.0, 8.0]$\\xi$ \u2208 [2.0, 20.0] %$a_h$ \u2208 [2.0, 7.0] %$a_c$ \u2208 [-30.0, -100.0] %$R$ \u2208 [0.5, 10.0]where$T$ stands for period$\\mu$ stands for ductility$\\xi$ stands for damping$a_h$ stands for hardening ratio$a_c$ stands for softening ratio (necessary to compute fracturing ductility, where collapse is assumed)Predictions made using the non-linear analysis resutls of 7292 unique SDOF systems amounting in total to 26,000,000 observations (collapse + non-collapse).ReferencesShahnazaryan D., O'Reilly J.G., 2023, Next-generation non-linear and collapse prediction models for short to long period systems via machine learning methods,Under Review"} +{"package": "xgbse", "pacakge-description": "hide:navigationxgbse: XGBoost Survival Embeddings\"There are two cultures in the use of statistical modeling to reach conclusions from data. One assumes that the data are generated by a given stochastic data model. The other uses algorithmic models and treats the data mechanism as unknown.\"- Leo Breiman,Statistical Modeling: The Two CulturesSurvival Analysis is a powerful statistical technique with a wide range of applications such as predictive maintenance, customer churn, credit risk, asset liquidity risk, and others.However, it has not yet seen widespread adoption in industry, with most implementations embracing one of two cultures:models with sound statistical properties, but lacking in expressivess and computational efficiencyhighly efficient and expressive models, but lacking in statistical rigorxgbseaims to unite the two cultures in a single package, adding a layer of statistical rigor to the highly expressive and computationally effcientxgboostsurvival analysis implementation.The package offers:calibrated and unbiased survival curves with confidence intervals (instead of point predictions)great predictive power, competitive to vanillaxgboostefficient, easy to use implementationexplainability through prototypesThis is a research project byLoft Data Science Team, however we invite the community to contribute. Please help by trying it out, reporting bugs, and letting us know what you think!"} +{"package": "xgbtune", "pacakge-description": "XGBTune is a library for automated XGBoost model tuning. Tuning an XGBoost\nmodel is as simple as a single function call.Get Startedfromxgbtuneimporttune_xgb_modelparams,round_count=tune_xgb_model(params,x_train,y_train)InstallXGBTune is available on PyPi and can be installed with pip:pip install xgbtuneTuning stepsThe tuning is done in the following steps:compute best roundtune max_depth and min_child_weighttune gammare-compute best roundtune subsample and colsample_bytreefine tune subsample and colsample_bytreetune alpha and lambdatune seedThis steps can be repeated several times. By default, two passes are done."} +{"package": "xgbxml", "pacakge-description": "xgbxmllxml parser for gbXML files - create and edit gbXML files with custom python Element classesDocumentation here:https://xgbxml.readthedocs.io/en/latest/"} +{"package": "xgclient", "pacakge-description": "Python xG ClientPython client forfootball (soccer) expected goals (xG) statistics API.\nIt provides a list of events with xG metric for every game of more than 80 leagues.UsageTo install the latest version ofxgclientusepip.pipinstallxgclientExample usageBasic usagefromxgclient.clientimportExpectedGoalsClientclient=ExpectedGoalsClient('Your API Key')countries=client.countries()# list of countriestournaments=client.tournaments(country_id)# list of leagues for specified countryseasons=client.seasons(league_id)# list of seasons for specified leaguefixtures=client.fixtures(season_id)# list of fixtures for specified seasonfixture=client.fixture(fixture_id)# get one fixtureCalculating xg90 (expected goals for 90 minutes) metric for every team of available seasonsimportoperatorfromxgclient.clientimportExpectedGoalsClientclient=ExpectedGoalsClient('Your API key')forcountryinclient.countries():fortournamentinclient.tournaments(country['id']):forseasoninclient.seasons(tournament['id']):print(country['name'],tournament['name'],season['name'])print('=====')season_fixtures=client.fixtures(season['id'])expected_goals={}minutes={}team_names={}forfixtureinseason_fixtures:ifnotteam_names.get(fixture['homeTeam']['id']):team_names[fixture['homeTeam']['id']]=fixture['homeTeam']['name']minutes[fixture['homeTeam']['id']]=0ifnotteam_names.get(fixture['awayTeam']['id']):team_names[fixture['awayTeam']['id']]=fixture['awayTeam']['name']minutes[fixture['awayTeam']['id']]=0fixture_duration=fixture['duration']['firstHalf']+fixture['duration']['secondHalf']minutes[fixture['homeTeam']['id']]+=fixture_durationminutes[fixture['awayTeam']['id']]+=fixture_durationforeventinfixture['events']:ifnotevent['xg']:continueifnotexpected_goals.get(event['teamId']):expected_goals[event['teamId']]=0expected_goals[event['teamId']]+=event['xg']result={}forteam_idinexpected_goals:result[team_id]=(expected_goals[team_id]/minutes[team_id])*90result=sorted(result.items(),key=operator.itemgetter(1),reverse=True)forteam_id,valueinresult:print(team_names[team_id],value)print('')Example Output:England Premier League 2016/2017\n=====\nManchester City 2.2112692731277535\nTottenham 2.052839403973515\nChelsea 1.826269731376351\nArsenal 1.799702725020647\nLiverpool 1.69972352778546\nManchester Utd 1.6932413793103451\nSouthampton 1.439378453038676\nEverton 1.3932328539823016\nBournemouth 1.2910729023383791\nStoke 1.2596034150371813\nLeicester 1.212548156301597\nWest Ham 1.2049150684931513\nCrystal Palace 1.1981870860927168\nSwansea 1.0498671831765367\nBurnley 0.9535088202866603\nWatford 0.9309592061742009\nWest Brom 0.9158252695604089\nSunderland 0.9000000000000007\nHull 0.8362012717721877\nMiddlesbrough 0.6971943443304693\n\nEngland Premier League 2017/2018\n=====\nManchester City 2.398823204419891\nLiverpool 1.871100993377485\nTottenham 1.8331631244824735\nArsenal 1.6883651452282165\nManchester Utd 1.5726460005535572\nChelsea 1.4510011061946915\nCrystal Palace 1.403015741507872\nLeicester 1.2518565517241396\nWatford 1.1562657534246574\nEverton 1.1204689655172415\nNewcastle 1.0640897755610998\nWest Ham 1.0446826051112954\nBournemouth 0.9957362637362651\nBrighton 0.9839266870313802\nSouthampton 0.9228472987872113\nStoke 0.8937382661512978\nBurnley 0.8835910224438907\nWest Brom 0.8344257316399778\nSwansea 0.7753942254303168\nHuddersfield 0.7536753318584073Pandas dataframe usage examplefromxgclient.clientimportExpectedGoalsClient,create_fixtures_dataframe,create_events_dataframe,create_fixture_oddsclient=ExpectedGoalsClient('Your API Key')season_fixtures=client.fixtures(8202)fixtures_df=create_fixtures_dataframe(season_fixtures)events_df=create_events_dataframe(season_fixtures)upcoming_odds_df=create_fixture_odds(client.upcoming_odds())"} +{"package": "xgcm", "pacakge-description": "Binder ExamplesLinkProviderDescriptionmybinder.orgBasic self-contained examplePangeo BinderMore complex examples integrated with other Pangeo tools (dask, zarr, etc.)Descriptionxgcmis a python package for working with the datasets produced by numericalGeneral Circulation Models(GCMs) and similar gridded datasets that are amenable tofinite volumeanalysis.\nIn these datasets, different variables are located at different positions with\nrespect to a volume or area element (e.g. cell center, cell face, etc.)\nxgcm solves the problem of how to interpolate and difference these variables\nfrom one position to another.xgcm consumes and producesxarraydata structures, which are coordinate and\nmetadata-rich representations of multidimensional array data. xarray is ideal\nfor analyzing GCM data in many ways, providing convenient indexing and grouping,\ncoordinate-aware data transformations, and (viadask) parallel,\nout-of-core array computation. On top of this, xgcm adds an understanding of\nthe finite volumeArakawa Gridscommonly used in ocean and atmospheric\nmodels and differential and integral operators suited to these grids.xgcm was motivated by the rapid growth in the numerical resolution of\nocean, atmosphere, and climate models. While highly parallel supercomputers can\nnow easily generate tera- and petascale datasets, common post-processing\nworkflows struggle with these volumes. Furthermore, we believe that a flexible,\nevolving, open-source, python-based framework for GCM analysis will enhance\nthe productivity of the field as a whole, accelerating the rate of discovery in\nclimate science. xgcm is part of thePangeoinitiative.Getting StartedTo learn how to install and use xgcm for your dataset, visit thexgcm documentation."} +{"package": "xgdatatools", "pacakge-description": "xgdatatoolsOriginally created by Michael Petch and was hosted on a website that was not in use anymore, This is only on github for people who want to read this file format which is abandoned by Microsoft."} +{"package": "xgeom", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-create-project-directories", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-retrieve-texts-from-dwgs", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-retrive-texts-from-dwgs", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-say-hello", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-survey-technical-requirements", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-t", "pacakge-description": "No description available on PyPI."} +{"package": "xgh-transform-coordinate", "pacakge-description": "\u751f\u6210lisp\uff0c\u7528\u4e8e\u521b\u5efa\u7528\u6237\u5750\u6807UCS"} +{"package": "xgi", "pacakge-description": "XGI is a Python package for higher-order networks.CompleXGroupInteractions (XGI) provides an ecosystem for the\nrepresentation, manipulation, and study of the\nstructure, dynamics, and functions of\ncomplex systems with group (higher-order) interactions.InstallationXGI runs on Python 3.8 or higher.To install the latest version of XGI, run the following command:$ pip install xgiTo install this package locally:Clone this repositoryNavigate to the folder on your local machineRun the following command:$ pip install -e .[\"all\"]Getting StartedTo get started, take a look at thetutorialsillustrating the library\u2019s basic functionality.Corresponding DataA number of higher-order datasets are available in theXGI-DATA repositoryand can be easily accessed with theload_xgi_data()function.ContributingIf you want to contribute to this project, please make sure to read thecontributing guidelines.\nWe expect respectful and kind interactions by all contributors and users\nas laid out in ourcode of conduct.The XGI community always welcomes contributions, no matter how small.\nWe\u2019re happy to help troubleshoot XGI issues you run into,\nassist you if you would like to add functionality or fixes to the codebase,\nor answer any questions you may have.Some concrete ways that you can get involved:Get XGI updatesby following the XGITwitteraccount, signing up for ourmailing list, or starring this repository.Spread the wordwhen you use XGI by sharing with your colleagues and friends.Request a new feature or report a bugby raising anew issue.Create a Pull Request (PR)to address anopen issueor add a feature.Join our Zulip channelto be a part of thedaily goings-on of XGI.How to CiteWe acknowledge the importance of good software to support research, and we note\nthat research becomes more valuable when it is communicated effectively. To\ndemonstrate the value of XGI, we ask that you cite XGI in your work.\nCurrently, the best way to cite XGI is to go to ourrepository pageand\nclick the \u201ccite this repository\u201d button on the right sidebar. This will generate\na citation in your preferred format, and will also integrate well with citation managers.LicenseReleased under the 3-Clause BSD license (see thelicense file)Copyright (C) 2021-2023 XGI Developers"} +{"package": "xgit", "pacakge-description": "xgitAn opinionated command line tools to make your life easier with Git and GitignoreInstallationInstall as global from pip.pip3 install xgitOr clone the repo, and install from the clone (and you may also edit as you wish).git clone https://github.com/patarapolw/xgit.git\npip3 install -e xgitUsage$ xgit -h\nAcceptable commands:\nxgit init Initialize new git along with .gitignore\nxgit commit message Commit to git with the following message\nxgit cpush message Commit and push to git with the following message\nxgit gi Generate gitignore from files in the directory\nxgit push Push changes to origin\nxgit Prompt for choices$ xgit\nWhat do you want to do?\n1. Initialize Git\n2. Commit current changes\n3. Commit current changes and push to remote\n4. Generate and commit .gitignore\n5. Push to remote\nPlease select [1-5]:Note.gitignoreis generated fromhttps://www.gitignore.io/, but this project also allows me to generate a custom.gitignorebased on/xgit/gitignore/.To learn more about my experience with Git, seehttps://github.com/patarapolw/SimpleGit"} +{"package": "xgitberg", "pacakge-description": "# Gitberg![travis status](https://img.shields.io/travis/gitenberg-dev/gitberg.svg)![PyPI version](https://img.shields.io/pypi/v/xgitberg.svg)[GITenberg](gitenberg.org) is a project to collectively curate ebooks on GitHub.[Gitberg](https://github.com/gitenberg-dev/gitberg) is a command line tool to automate tasks on books stored in git repositories.## UsageThis project provides a `gitberg` command that does the following:+ `gitberg fetch ` fetches books from PG+ `gitberg make ` makes a local git repo with extra files+ `gitberg push ` creates a repo on github and pushes to it (one per book)+ `gitberg all ` fetches, makes and pushes a range of books+ `gitberg list ` fetches, makes and pushes a range of books+ `gitberg apply ` applies an action+ `gitberg metadata ` prints the yaml metadata### Examples```gitberg list --rdf_library /Documents/gitenberg/cache/epub 181,565,576```### ConfigSome commands require a config file before they can be used.These commands will ask for config values to make a correct configuration.The config file in linux is located at `~/.config/gitberg/config.yaml`.Main config values:gh_user: gh_password: library_path: '~/data/library'rdf_library: location of your cache of the PG RDF demp## TestingTo run project tests do:python setup.py test## PackagingThis project is available as a python package. To install, usepip install xgitbergTo build this python package, use `setup.py`python setup.py sdist"} +{"package": "xGitGitlab", "pacakge-description": "GitGitLab allows you to create Gitlab projects and set them as remote source for your git checkouts.Installationsudo pip install gitgitlabUsage$ git init\n$ git touch 'readme.txt'\n$ git add readme.txt\n$ git commit -am 'initial commit'\n$ git lab create my_project -t\n Project my_project created on Gitlab\n$ git remotes\n gitlabCommand overviewgit lab listList your Gitlab projectsgit lab create Create a project on Gitlabgit lab track Set this project as remote for your local repository.git lab open Open a Gitlab project page. If is omitted, uses the project on the \u2018gitlab\u2019 remote of the repository on the current directory.Listing your projectsgit lab listlists all the projects that you own and their repository url.Creating a new projectgit lab create creates a new private project on Gitlab.git lab create \u2013trackcreates a new private project and sets it up as remote.Setting up an existing project to track the local repositorygit lab track Adds a gitlab project as remote.Obtaining helpgit lab helpOverview.git lab \u2013helpHelp for a specific command.More informationSee also theproject documentation."} +{"package": "xgit-python", "pacakge-description": "xgitGit tool based on GitPython.buildfast build viaxpip:xpip-buildsetup--all&&ls-lhdist/*or build in linux:rm-rf\"build\"\"dist\"\"*.egg-info\"pythonsetup.pychecksdistbdist_wheel--universal"} +{"package": "xglider", "pacakge-description": "xgliderGeneric tools to handle underwater gliders\u2019 dataFree software: Apache Software License 2.0Documentation:https://xglider.readthedocs.io.FeaturesTODOCreditsHistory0.0.1 (2018-05-30)First release on PyPI.Migrating/refactoring some functionalities from internal Spray glider tools."} +{"package": "x-goals", "pacakge-description": "X-Goals package. Generated with cookiercutter-pylibrary using the command line cookiecutter gh:ionelmc/cookiecutter-\npylibraryThis is V1 of X-Goals which is an alternative method to score a match.XGoals uses the weighting approach of 0.15 (corners), 0.2 (shots on) and -0.1 (cards).Cards increases by 1 for a player\u2019s first yellow card, and by 2.5 for a second yellow or a red (motivated by\nsportingindex.com weightings). Currently corners and shots on are modelled using the normal distribution, with\n95% of values lying in the range [0, 2 times the expected value]; this means the spread is set to be half the expected\nvalue (this is motivated by historical behaviour for teams over a whole season, and clearly that\u2019s not going to be\nideal as it doesn\u2019t account for the strength of the opposition properly. Don\u2019t judge too harshly as this is just\nVersion 1!). The distribution for the cards follows a Poisson distribution.Free software: Apache Software License 2.0Installationpip install x-goalsDocumentationTo use the project:Open a Jupyter notebook and paste the followingimportx_goals.appasapplicationxgoals_app=application.dash_appapplic.show_app(xgoals_app)DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append\ntoxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.1 (2018-11-12)First release on PyPI."} +{"package": "xgoogle", "pacakge-description": "No description available on PyPI."} +{"package": "xgo-pythonlib", "pacakge-description": "XGO-PythonLibXGO2 has built-in motion libraries for controlling the movement and various features of the machine dog, including battery level, firmware version, and servo angle. The motion library enables users to control translation and pose movement, as well as single servo and single-leg movement. The education library facilitates camera, screen, key, microphone, and speaker operations, as well as commonly used AI functions such as gesture recognition, face detection, emotional recognition, and age and gender recognition. The detailed instructions for use of the library are as follows.PythonLib included xgolib.py and xgoedu.pyLuwu Dynamics \u00b7 WIKIInstall instructions1 Burn the latest official image2 Run this command:pip install --upgrade xgo-pythonlib\nsudo pip install --upgrade xgo-pythonlibExamplesPerform gesture recognition on the current camera and press the \"c\" key to exit.fromxgoeduimportXGOEDUXGO_edu=XGOEDU()whileTrue:result=XGO_edu.gestureRecognition()print(result)ifXGO_edu.xgoButton(\"c\"):breakxgolib library examplefromxgolibimportXGOdog=XGO('xgomini')dog.action(1)Change Log[0.3.2] - 2024-01-29FixedUpdate xgolib.py to 1.3.9[0.3.1] - 2023-09-16FixedAdd .gitignoreGesture image flip[0.2.8] - 2023-08-22FixedMethods: display_text_on_screen()[0.2.7] - 2023-08-20AddedMethods: posenetRecognition added.FixedMethods: lcd_arc() and lcd_circle()[0.2.5] - 2023-07-19FixedMethods: Change theinitin xgolib.py to add delay to resolve some movement irregularities.[0.2.4] - 2023-07-13FixedMethods: lcd_clear() was fixed.[0.2.3] - 2023-07-04AddedMethods: cap_color_mask added.FixedCircleRecognition renamed BallRecognition and improved.[0.2.2] - 2023-07-03AddedFive Methods: SpeechRecognition SpeechSynthesis QRRecognition CircleRecognition ColorRecognitio added.[0.2.0] - 2023-06-21FixedxgoVideo and xgoVideoRecord method can be used.[0.1.9] - 2023-06-20FixedFixed the issue with the xgoTakePhoto method that was causing abnormal RGB colors in the saved photos."} +{"package": "xgorn-api", "pacakge-description": "Noid APIfromxgorn_apiimportNoidAPIapi=NoidAPI()api.api_key='your-api-key'api.bypass.ouo('https://ouo.io/4ZuwGMc')ExamplesChange endpoint to api feature.For example:/scrape/instagramapi.scrape.instagram('https://www.instagram.com/reel/CqcUdr-ppgT/?igshid=YmMyMTA2M2Y=')Change default api url.For example:api.xgorn.eu.orgapi.base_url='https://api.xgorn.eu.org'Making custom request.For example:/scrape/likee# GET request# method & endpoint: default arguments.method='get'endpoint='/scrape/likee'# url: params because it's **kwargsurl='https://likee.video/@MEKDede/video/7199606118785777185'api.make_request(method=method,endpoint=endpoint,url=url)Installationpip3installxgorn-api"} +{"package": "xgo-spider-log", "pacakge-description": "No description available on PyPI."} +{"package": "xgp", "pacakge-description": "XGP Python packageThis repository contains Python bindings to theXGP library. It is a simple wrapper that calls the XGP dynamic shared library and exposes a scikit-learn interface.DocumentationPlease refer to thePython section of the XGP website.InstallationInstallation instructions are availablehere.Quick start>>>fromsklearnimportdatasets>>>fromsklearnimportmetrics>>>fromsklearnimportmodel_selection>>>importxgp>>>X,y=datasets.load_boston(return_X_y=True)>>>X_train,X_test,y_train,y_test=model_selection.train_test_split(X,y,random_state=42)>>>model=xgp.XGPRegressor(...flavor='boosting',...loss_metric='mse',...funcs='add,sub,mul,div',...n_individuals=50,...n_generations=20,...parsimony_coefficient=0.01,...n_rounds=8,...random_state=42,...)>>>model=model.fit(X_train,y_train,eval_set=(X_test,y_test),verbose=True)>>>metrics.mean_squared_error(y_train,model.predict(X_train))# doctest: +ELLIPSIS17.794685...>>>metrics.mean_squared_error(y_test,model.predict(X_test))# doctest: +ELLIPSIS17.337693...This will also produce the following output in the shell:00:00:00--trainmse:42.06567--valmse:33.80606--round100:00:00--trainmse:24.20662--valmse:22.73832--round200:00:00--trainmse:22.06328--valmse:18.90887--round300:00:00--trainmse:20.25549--valmse:18.45531--round400:00:00--trainmse:18.86693--valmse:18.22908--round500:00:00--trainmse:17.79469--valmse:17.33769--round600:00:01--trainmse:17.62692--valmse:22.67012--round700:00:01--trainmse:17.24799--valmse:22.77802--round8"} +{"package": "xgp-reccomender", "pacakge-description": "xgp-reccomenderApp searches for avaiable Xbox Game Pass games and helps to choose what to play based on Metacritics and your ratings.Instalationpip3 install xgp-reccomenderUsagexgp-reccomenderRating games is done viarated_games. 1 is for liked games and -1 is the opposite. You can type whatever integer you want, but I reccomend to stick with -1, 1 values.OutputThe script output isgame_ranking.html. There is also simple css file written for better visualizing."} +{"package": "xgpu", "pacakge-description": "xgpuxgpuis an aggressively typed, red-squiggle-free Python binding\nofwgpu-native, autogenerated from\nthe upstream C headers.Not 'production ready'.InstallWheels are built for Mac (x86 only), Windows, and Linux for Python 3.7+:pip install xgpuMotivationWhyanotherwebgpu/wgpu_native binding whenwgpu-pyalready exists and is semi-mature?Typing:xgputakes full advantage of Python type annotations, enabling quality of life\nfeatures like IDE autocomplete for enum valuesUp to date:xgpuis 99% autogenerated from the headers, and aims to always be in sync with\nthe latestwgpu-nativereleasePerformance:xgpuis substantially faster thanwgpuConventions/Philosophyxgpuis a mostly 1-to-1 binding ofwebgpu.h(+wgpu.hfromwgpu-native).General name conventionsxgpulargely tries to maintain the names fromwebgpu.hrather than localizing\nthem into Python's conventions.Names keep their formatting fromwebgpu.hbut loseWGPUprefixes:WGPUTextureSampleType->TextureSampleTypeFields:WGPUAdapterProperties.vendorName->AdapterProperties.vendorNameMember functions:wgpuDeviceHasFeature->Device.hasFeatureEnum values:WGPUTextureUsage_CopySrc->TextureUsage.CopySrcNames invalid in Python are prefixed with \"_\":WGPUBufferUsage_None->BufferUsage._None,WGPUTextureDimension_2D->TextureDimension._2DStruct constructorswebgpu.hrequires constructing various structs, for exampleWGPUExtent3D. These can be created in two ways:# Recommended: create explicit initialized struct (note lowercase name)extents=xgpu.extent3D(width=100,height=100,depthOrArrayLayers=1)# Alternative: create 0-initialized struct and then mutate valuesextents=xgpu.Extent3D()extents.width=100extents.height=100extents.depthOrArrayLayers=1Member functionsAs a C API,webgpu.hfollows typical C convention for member functions, which is to define\nthem like:uint32_twgpuTextureGetHeight(WGPUTexturetexture)Inxgputhese become genuine member functions, e.g.,classTexture:defgetHeight(self)->intArray arguments / fieldsSomewebgpu.hfunctions and structs take arrays using the convention of passing first\nthe array item count, and then the array pointer, e.g.,voidwgpuQueueSubmit(WGPUQueuequeue,size_tcommandCount,WGPUCommandBufferconst*commands)typedefstructWGPUPipelineLayoutDescriptor{// ...size_tbindGroupLayoutCount;WGPUBindGroupLayoutconst*bindGroupLayouts;}WGPUPipelineLayoutDescriptor;These are translated to take lists:classQueue:defsubmit(self,commands:List[CommandBuffer]])defpipelineLayoutDescriptor(*,bindGroupLayouts:List[\"BindGroupLayout\"])Enums and FlagsEnums are translated intoIntEnums:mode=xgpu.AddressMode.MirrorRepeatprint(int(mode))# 2print(mode.name)# \"MirrorRepeat\"mode=xgpu.AddressMode(2)print(mode.name)# \"ClampToEdge\"Some enums are meant to be ORed together into bitflags. These can be combined\nin the natural way:usage=xgpu.BufferUsage.MapRead|xgpu.BufferUsage.CopyDstprint(usage)# prints: 9This works becauseIntEnumsinherit all the int methods include bitwise\noperations; however, this discards the type information.\nA slightly more annoying but type-safer way is:usage=xgpu.BufferUsage.MapRead.asflag()|xgpu.BufferUsage.CopyDstprint(usage)# prints: BufferUsage.MapRead | BufferUsage.CopyDstYou can also create typed flags from bare ints:usage=xgpu.BufferUsageFlags(0b1001)print(usage)# prints: BufferUsage.MapRead | BufferUsage.CopyDstYou can test for a particular flag with the pythoninoperator:has_map_read=xgpu.BufferUsage.MapReadinmybuffer.getUsage()CallbacksCallbacks must be explicitly wrapped in the appropriate callback type:defmy_adapter_cb(status:xgpu.RequestAdapterStatus,gotten:xgpu.Adapter,msg:str):print(f\"Got adapter with msg:'{msg}', status:{status.name}\")cb=xgpu.RequestAdapterCallback(my_adapter_cb)Chained structsThewebgpu.hstructure chaining convention is represented byChainedStruct, whose\nconstructor takes a list ofChainableand automatically creates the linked chain.shader_source=\"\"\"...\"\"\"shader=device.createShaderModule(nextInChain=xgpu.ChainedStruct([xgpu.shaderModuleWGSLDescriptor(code=shader_source)]),hints=[],)Byte buffers, void pointersxgpuhas two translations forvoid *:VoidPtrrepresents a pointer to\nopaque data (e.g., a window handle) whileDataPtrrepresents a pointer\nto asizeddata structure (e.g., texture data you want to upload).For example,# Note use of VoidPtr.NULL and VoidPtr.raw_castsurf_desc=xgpu.surfaceDescriptorFromWindowsHWND(hinstance=xgpu.VoidPtr.NULL,hwnd=xgpu.VoidPtr.raw_cast(self.window_handle),)# DataPtr.wrap can wrap anything supporting the 'buffer' interfacebytedata=bytearray(100)wrapped=xgpu.DataPtr.wrap(bytedata)queue.writeBuffer(buffer=some_buffer,bufferOffset=0,data=wrapped)# This includes numpy arraysmy_array=np.ones(100,dtype=np.float32)wrapped=xgpu.DataPtr.wrap(my_array)Codegen/Local BuildYou will needbunto run the codegen. Denomightwork but just go ahead and install bun. You will also need to have\nruff and cffi installed in python (pip install ruff cffi).Then:python codegen/fetch_wgpu_bins.py\nbun codegen/generate.ts\ncd xgpu\npython _build_ext.py\ncd ..\npip install ."} +{"package": "xgpy", "pacakge-description": "xgpy: a powerful python wrapper for football dataWhat is it?xgpyis a Python package that aims to aggregate multiple football data sources into a single python module.\nUsing a single function, one can retrieve data from multple places, compare and perform a more complete analysis.SourceStatusunderstat.comBetafbref.comIn Progressfantasy.premierleague.comPlannedwhoscored.comPlannedInstallationThe source code is currentlyhere.The simplest way to install the package is by pip.pip install xgpyUsagexgpyhas multiple modules, each for every source. For example, in order to get stats from understat:importxgpyfromxgpy.understatimportUnderstatPlayerplayer=UnderstatPlayer(1228)match_data=player.get_player_match_data()And that's it! Look through the documentation and call upon a number of functions.TroubleshootingThere is a known issue of pandas not installing correctly. Please make sure you have pandas\ninstalled before installing xgpy.pipinstallpandas\npipinstallxgpy"} +{"package": "xgrads", "pacakge-description": "xgrads1. IntroductionThe Grid Analysis and Display System (GrADSorOpenGrADS) is a widely used software for easy access, manipulation, and visualization of earth science data. It uses adescriptor (or control) file with a suffix.ctlto describe a raw binary 4D dataset. Thectlfile is similar to the header information of aNetCDFfile, containing all the information about dimensions, attributes, and variables except for the variable data.This python packagexgradsis designed for parse and read the.ctlfile commonly used byGrADS. Right now it can parse various kinds of.ctlfiles. However, only the commonly used raw binary 4D datasets can be read usingdaskand return as axarray.DatasetOther types of binary data, likedtypeisstationorgrib, may be supported in the future.2. How to installRequirementsxgradsis developed under the environment withxarray(=version 0.15.0),dask(=version 2.11.0),numpy(=version 1.15.4),cartopy(=version 0.17.0), andpyproj(=version 1.9.6). Older versions of these packages are not well tested.Install via pippip install xgradsInstall from githubgit clone https://github.com/miniufo/xgrads.git\ncd xgrads\npython setup.py install3. Examples3.1 Parse a.ctlfileParsing a.ctlfile is pretty simple using the following code:fromxgradsimportCtlDescriptorctl=CtlDescriptor(file='test.ctl')# print all the info in ctl fileprint(ctl)If you have already load the ASCII content in the.ctlfile, you can do it as:content=\\\"dset ^binary.dat\\n\"\\\"* this is a comment line\\n\"\\\"title 10-deg resolution model\\n\"\\\"undef -9.99e8\\n\"\\\"xdef 36 linear 0 10\\n\"\\\"ydef 19 linear -90 10\\n\"\\\"zdef 1 linear 0 1\\n\"\\\"tdef 1 linear 00z01Jan2000 1dy\\n\"\\\"vars 1\\n\"\\\"test 1 99 test variable\\n\"\\\"endvars\\n\"ctl=CtlDescriptor(content=content)# print all the infoprint(ctl)3.2 Read binary data into axarray.DatasetReading a.ctlrelated binary data file is also pretty simple using the following code:fromxgradsimportopen_CtlDatasetdset=open_CtlDataset('test.ctl')# print all the info in ctl fileprint(dset)Then you have thedsetas axarray.Dataset. This is similar toxarray.open_datasetthat usedaskto chunk (buffer) parts of the whole dataset in physical memory if the whole dataset is too large to fit in.If there are many.ctlfiles in a folder, we can also open all of them in a single call ofopen_mfdatasetas:fromxgradsimportopen_mfDatasetdset=open_mfDataset('./folder/*.ctl')# print all the info in ctl fileprint(dset)assuming that every.ctlfile has similar data structure except the time step is different. This is similar toxarray.open_mfdataset.3.3 Convert a GrADS dataset to a NetCDF datasetWith the above functionality, it is easy to convert a.ctl(GrADS) dataset to a.nc(NetCDF) dataset:fromxgradsimportopen_CtlDatasetopen_CtlDataset('input.ctl').to_netcdf('output.nc')"} +{"package": "xgram", "pacakge-description": "The telegram python api"} +{"package": "xgrid", "pacakge-description": "XGridInstallationpip install xgridTestInvokepython3 test.pyin the root folder to perform the test cases.UsageSee document for more information. Let's start with a simple kernel, the element-wise multiplication of two grid:importxgridimportnumpyasnpimportrandomxgrid.init()fvec=xgrid.grid[float,1]@xgrid.kernel()defelementwise_mul(result:fvec,a:fvec,b:fvec)->None:result[0]=a[0]*b[0]and let's define some data:a=xgrid.Grid((10000,),float)b=xgrid.Grid((10000,),float)foriinrange(10000):a[i]=random.random()b[i]=random.random()and the result:result=xgrid.Grid((10000,),float)and invoke the kernel:elementwise_mul(result,a,b)We could check the result using numpy dot:assert np.sum(result.now) == np.dot(a.now, b.now)ExamplesSolve the 2D Cavity flow withxgrid, see in examples folder."} +{"package": "xgridfit", "pacakge-description": "xgridfit-3A TrueType hinting languageXgridfit is an language for hinting TrueType fonts. It is an XML-based language, similar to (and in fact inspired by) XSLT. It has been around since before 2006, but version 3 was reborn as a (largely) Python program with Python dependencies. Xgridfit through version 2 was verbose and awkward to use. Version 3 featured a new compact syntax, and version 3.2.10 added a YAML-based language focused on describing the positions of points relative to the origin of a glyph's grid or to other points rather than issuing commands for positioning them. This language (call it Ygridfit) is simple and easy to write, but its main purpose is to supportygt, a graphical hinting tool.Documentation of the XML-based language (both full and compact syntax), is available at theGitHub development site.There is no release for the current version (3.2.18) at GitHub. Instead, install by downloading from PyPi:pip install xgridfitAlternatively, download the code from GitHub, change to the project's root directory (the one with the filepyproject.tomlin it), and type:pip install .Version 3.3.0 merges most of main() (command line) and the former compile_all (called from Ygt) into one routine (run()). This enables\nmerge-mode for Ygt.Version 3.2.18 logs certain errors rather than exiting (an improvement when a backend for Ygt).Version 3.2.17 has its own code for exporting to UFO rather than relying on ufoLib2.Version 3.2.16 adds support for deltas in the YAML notation.Version 3.2.15 fixes a bug that made a muddle of the cvar table, and removes an obnoxious message.Version 3.2.14 is revised to accommmodate the new organization of cvar data in ygt.Version 3.2.13 has small changes to maintain compatibility with ygtVersion 3.2.12 changes from fontTools.ufoLib to ufoLib2 for editing UFOs.Version 3.2.11 adds the ability to save instructions and associated data to a UFO (version 3)Version 3.2.10 supports \"min\" (minimum distance) attribute for hints and emits fewer messages when run from ygt."} +{"package": "xgrow", "pacakge-description": "No description available on PyPI."} +{"package": "xgt", "pacakge-description": "xGT is a high-performance property graph engine designed to support extremely large in-memory graphs, and thexgtlibrary is the client-side interface which controls it.DocumentationThexgtlibrary is self-documenting, and all external methods and classes have docstrings accessible throughhelp().\nA formatted version of the same is available online on the Trovares documentation site:docs.trovares.com.Extra ToolsMost users will find installing the following packages useful:PackageDescriptionjupyterFor an interactive environment to use xgt.pandasFor importing / exporting data to / from pandas frames.The \"extra\" variant ofxgtis provided to make installing these useful packages along with xgt easy. Install by doing:pip install xgt[extra]."} +{"package": "xgu", "pacakge-description": "xgu"} +{"package": "xguard", "pacakge-description": "xguardXguard is yet another guard clause library.What are Guard ClausesA guard clause is simply a check that immediately exits the function, either with a return statement or an exception. If you're used to writing functions that check to ensure everything is valid for the function to run, then you write the main function code, and then you write else statements to deal with error cases, this involves inverting your current workflow. The benefit is that your code will tend to be shorter and simpler, and less deeply indented.CreditHow to use this packageUsing this package is easy. Just import the package, create an instance of the Xguard class, and start chaining your guard clauses together.In dev mode, if you still encounter a lot of import errors, and you think you know what you are doing, try to add the xguard dir to the python path.export PYTHONPATH=/path/to/parent/directory:$PYTHONPATHHere's an example:fromxguardimportguarddefadd_ten(number:int):guard=guard.Xguard()guard.not_null(number)\\.is_type(number,int)\\.is_gt(number,0)# if we made it here, we have succeessfully used the guard clause, kudos!returnnumber+10;res:int=add_ten(5)# 120print(res)# Good Issue: Try to use the guard clauses in a factorial functionSee? Easy!For testingpython-munittestdiscovertests/Why I wrote the libraryI wrote xguard because I wanted to create something useful for other developers like myself. As someone who has written a lot of code, I know how frustrating it can be to spend time tracking down errors caused by bad inputs. I wanted to make it easier for developers to catch these issues early on and write more robust code.It was also an opporuinty for me to improve on a similar project by Adrian without wrecking his original idea. I am adding some extra features like custom error messages to make it more powerful and flexible. With custom error messages, developers can quickly understand what went wrong when a guard clause fails.Overall, my main motivation for creating xguard was to write something that I found useful and that I hope other developers will find useful as well. I believe in the power of open source software and I would love for others to contribute to the project. If you have any feedback or suggestions, please feel free to share them or even open a pull request on GitHub. Together, we can make xguard even better.DocumentationEach guard method is documented with a docstring that explains its purpose and usage, following the reST style. You can access the documentation for each method using Python's built-inhelpfunctionLicenseThis library is released under the GNU GPLv3 License. See the LICENSE file for details.AcknowledgementsThis library is based on the ideas and code of Adrian'ssimilar project. Thank you, Adrian!"} +{"package": "xh1scr", "pacakge-description": "#ENGHow to useIMPORT AsyncTok modulefromxh1scrimportAsyncTokMake task in asynchronous funcasyncdeffunc():awaitAsyncTok.run('xh1c2')status=awaitAsyncTok.status()likes=awaitAsyncTok.likes()followers=awaitAsyncTok.followers()following=awaitAsyncTok.following()nickname=awaitAsyncTok.nickname()avatar=awaitAsyncTok.getavatar()btw u can get list in runfromxh1scrimportAsyncTok\nasyncdeffunc2():awaitAsyncTok.run(['xh1c2','example','example2','and','more'])status=awaitAsyncTok.status()likes=awaitAsyncTok.likes()followers=awaitAsyncTok.followers()following=awaitAsyncTok.following()nickname=awaitAsyncTok.nickname()avatar=awaitAsyncTok.getavatar()andnowthatlibrarycanbenotasyncronousIMPORT TikTok modulefromxh1scrimportTikTokMake task in normal funcdeffunc():TikTok.run('xh1c2')status=TikTok.status()likes=TikTok.likes()followers=TikTok.followers()following=TikTok.following()nickname=TikTok.nickname()avatar=TikTok.getavatar()fromxh1scrimportTikTok\ndeffunc2():TikTok.run(['xh1c2','example','example2','and','more'])status=TikTok.status()likes=TikTok.likes()followers=TikTok.followers()following=TikTok.following()nickname=TikTok.nickname()avatar=TikTok.getavatar()#RU\u041a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c\u0414\u043b\u044f \u0440\u0430\u0431\u043e\u0442\u044b \u0441 \u043d\u0438\u043c \u043d\u0430\u0434\u043e \u0441\u0434\u0435\u043b\u0430\u0442\u044c task \u0432 \u0430\u0441\u0438\u043d\u0445\u0440\u043e\u043d\u043d\u043e\u0439 \u0444\u0443\u043d\u043a\u0446\u0438\u0438\n(\u044f \u0437\u043d\u0430\u044e \u0435\u0441\u0442\u044c \u0442\u0430\u043a\u043e\u0435 \u0436\u0435 API \u043d\u043e \u0441 \u043f\u043e\u0434\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u043e\u0439 \u0430\u0432\u0442\u043e\u0440\u0438\u0437\u0430\u0446\u0438\u0435\u0439 \u0438 \u043f\u043e\u0438\u0441\u043a\u043e\u043c \u043f\u043e id \u043d\u043e \u043f\u043b\u044e\u0441 \u043c\u043e\u0435\u0433\u043e API \u044d\u0442\u043e \u0443\u0434\u043e\u0431\u0441\u0442\u0432\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f)fromxh1scrimportTikTok\ndeffunc():TikTok.run('xh1c2')status=TikTok.status()likes=TikTok.likes()followers=TikTok.followers()following=TikTok.following()nickname=TikTok.nickname()avatar=TikTok.getavatar()\u0422\u0430\u043a \u0436\u0435 \u0432 run \u043c\u043e\u0436\u043d\u043e \u043f\u0435\u0440\u0435\u0434\u0430\u0442\u044c \u0441\u043f\u0438\u0441\u043e\u043a \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439fromxh1scrimportTikTok\ndeffunc2():TikTok.run(['xh1c2','example','example2','and','more'])status=TikTok.status()likes=TikTok.likes()followers=TikTok.followers()following=TikTok.following()nickname=TikTok.nickname()avatar=TikTok.getavatar()"} +{"package": "xhac", "pacakge-description": "MXCHIP Home Access ClientMXCHIP Home Access Client"} +{"package": "xhAStar", "pacakge-description": "A*\u5bfb\u8def\u7b97\u6cd5pip install xhAStar\u4f7f\u7528\u65b9\u6cd5importastarw,h=6,3start,goal=(0,0),(3,2)walls=[(2,1),(3,1),(4,1)]obj=astar.AStar(w,h,start,goal,walls,astar.MANHATTAN)print(obj.result)AStar\u53c2\u6570\u8bf4\u660e:w (int): \u957fh (int): \u5bbdstart (Tuple[int, int]): \u8d77\u59cb\u70b9goal (Tuple[int, int]): \u7ec8\u70b9walls (List[Tuple[int, int]]): \u5899\u58c1\u5750\u6807\u5217\u8868type (int, optional): \u5bfb\u8def\u7c7b\u578b. \u9ed8\u8ba4\u4e3a\u66fc\u54c8\u987f\u5bfb\u8def MANHATTAN."} +{"package": "xhb2beancount", "pacakge-description": "xhb2beancountHomebank to Beancount converter.InstallI recommend usingpipx.pipxinstallxhb2beancountOr just create a virtualenv and runpip install xhb2beancount.Usagexhb2beancountfile.xhb>file.beancountIf you have beancount installed you can format it with bean-format.xhb2beancountfile.xhb|bean-format-c78>file.beancountYou can customize the conversion passing a config file as an argument.xhb2beancount--configconfig.pyfile.xhbCopy thedefault config fileand edit it to suit your needs.You can also use the option--print-config-dictsto print the categories, accounts, payees and tags\nfrom your Homebank file as dictionares and copy them to your config file.xhb2beancountfile.xhb--print-config-dicts"} +{"package": "xh-cpu-usage-simulator", "pacakge-description": "A dictionary utility of self dev py libraryBuildrm-frdist\npython-mbuild# automate by following `-u {user} -p {token / password}`# api automate by following `-u __token__ -p {token / password}`python-mtwineuploaddist/*"} +{"package": "xhdata", "pacakge-description": "Overviewxhdatarequires Python(64 bit) 3.7 or greater, aims to make fetch financial data as convenient as possible.Write less, get more!Documentation:\u4e2d\u6587\u6587\u6863"} +{"package": "xh-dict-utils", "pacakge-description": "A dictionary utility of self dev py libraryBuildrm-frdist\npython-mbuild# automate by following `-u {user} -p {token / password}`# api automate by following `-u __token__ -p {token / password}`python-mtwineuploaddist/*"} +{"package": "xhd-source", "pacakge-description": "xhd_sourcepython3 -m buildpython3 -m twine upload --repository pypi dist/*"} +{"package": "xh-dual-layer-app-engine", "pacakge-description": "A dictionary utility of self dev py libraryBuildrm-frdist\npython-mbuild# automate by following `-u {user} -p {token / password}`# api automate by following `-u __token__ -p {token / password}`python-mtwineuploaddist/*"} +{"package": "xheadtail", "pacakge-description": "Collective effects for particle accelerators"} +{"package": "xheap", "pacakge-description": "It\u2019s likeheapq(blazingly fast) but object-oriented + more features.Read more here for the background story.Why?Less code.What are heaps good for anyway?When you need the smallest item of a large list\u2014fast and with no overhead.How?Let\u2019s suppose you have a heap, you can usepopto get its smallest item.fromxheapimportHeapheap=Heap(['H','D','B','A','E','C','L','J','I'])heap.pop()# returns Aheap.pop()# returns Bheap.pop()# returns Cheap.pop()# returns DHeapsortworks this way.Can I insert an item?Indeed and it\u2019s as fast as pop. Usepushfor insertion.heap=Heap(['A','D','B','H','E','C','L','J','I'])heap.push('Z')Can I remove an item from the middle of a heap?Yes, that\u2019s whatRemovalHeap.removeis supposed to do.fromxheapimportRemovalHeapheap=RemovalHeap(['A','D','B','H','E','C','L','J','I'])heap.remove('L')Can I specify the order of the heap?Just imagine two heaps of the very same set of items but you need different sorting for each heap. Or\nyou need a max-heap instead of a min-heap. That is whatOrderHeapis designed for:fromxheapimportOrderHeapitems=[date(2016,1,1),date(2016,1,2),date(2016,1,3),date(2016,1,4)]day_heap=OrderHeap(items,key=lambdadate:date.day)day_heap.peek()# returns date(2016, 1, 1)weekday_heap=OrderHeap(items,key=lambdadate:date.weekday())weekday_heap.peek()# returns date(2016, 1, 4)What about both remove+order?No problem. UseXHeap.If you wonder why there are 4 distinct heap implementations, it\u2019s a matter of speed.\nEach additional feature slows a heap down. Thus, you could always use XHeap but beware\nof the slowdown.Checking Heap InvariantA heap is just a list. So, if you tinker with it, you can check whether its invariant still holds:heap=Heap([4,3,7,6,1,2,9,8,5])heap[3]=10# I know what I am doing hereheap.check_invariant()# but better check... ooopsConclusionGooduses C implementation if available (i.e. fast)object-orientedno slowdown if you don\u2019t need more than a simple heapremoval possiblecustom orders possibleworks with Python2 and Python3Badno drawbacks discovered so far ;-)needs fix/work:item wrapper which allows duplicate itemsdecrease-key+increase-key: another missing use-case ofheapqmerge heapsideas are welcome :-)"} +{"package": "xhelpers", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xhh-cation-test", "pacakge-description": "xhh-action-test"} +{"package": "xhibit", "pacakge-description": "XHIBITExhibit your ASCII art and system specsINSTALLATIONAdd PathExample to add ~/.local/bin/ in the PATH VariablePOSIX based shell (bash,zsh,dash,....)Change bashrc to your repective shell's rcecho 'export PATH=~/.local/bin:$PATH' >> $HOME/.bashrcFish shellecho 'set PATH ~/.local/bin/ $PATH' >> $HOME/.config/fish/config.fishInstall Python Packagepip install xhibitDependenciesFor Ascii art onlypython 3.5+For Image displaykitty terminalorueberzugxorg-xdpyinfoxdotoolxorg-xpropxorg-xwininfoHow To Useusage: xhibit [-h] [-cs CS] [-rcs RCS] [-ccs CCS] [-cn CN] [-rcn RCN] [-cpu CPU] [-gpu GPU] [-img IMG] [-imb IMB] [-crop CROP]\n\noptions:\n -h, --help show this help message and exit\n -cs CS Colorscheme to display.\n -rcs RCS Randomize Colorschemes [t or f].\n -ccs CCS Give custom colorschemem of 8 colors like this \"#BF616A,#A3BE8C,#EBCB8B,#81A1C1,#B48EAD,#88C0D0,#E5E9F0,#B48EAD\".\n -cn CN Specify Character name [monalisa,egyptian,fairy,casper,dragon].\n -rcn RCN Randomize Characters [t or f].\n -cpu CPU Mention Cpu [Custom Cpu name].\n -gpu GPU Mention Gpu [Custom Gpu name].\n -img IMG Image path.\n -imb IMB Mention Image backend [kitty or ueberzug].\n -crop CROP Mention crop type [fit or fill].ASCII charactersASCII Characters availablemonalisaegyptiancasperfairydragonDefault colorschemesgruvboxdraculaExtra Colorscheme List present inside this programColorscheme listExample commandsTo Choose gruvbox Colorscheme and casperxhibit -cs gruvbox -cn casperTo Choose dracula Colorscheme and fairyxhibit -cs dracula -cn fairyTo randomize colorscheme and characterxhibit -rcs t -rcn tPick colorschemeCheckColorscheme listxhibit -cs \"Eighties.dark\" -cn dragonTo give custom user colorsYou can give custom user colors to xhibit to display text.\nMust give all the 8 colors in hex format just as shown below.\nNord Colorscheme colors are used below as example.xhibit -ccs \"#BF616A,#A3BE8C,#EBCB8B,#81A1C1,#B48EAD,#88C0D0,#E5E9F0,#B48EAD\"DOWNLOAD ALL THE THEMES AND SEE WITH FZFNote : FZF Requiredgit clone https://github.com/glowfi/xhibit-colorschemes\nmv ~/xhibit-colorschemes/themes ~/.cache\nrm -rf xhibit-colorschemes\nls ~/.cache/themes| fzf | xargs -I {} cat ~/.cache/themes/{} | xargs | tr \" \" \",\" | xargs -I {} xhibit -rcn t -ccs \"{}\"Try all colorscheme in 1 second intervalwget https://raw.githubusercontent.com/glowfi/xhibit-colorschemes/main/run.sh -O ~/.cache/xhibitCol.sh\nsh ~/.cache/xhibitCol.shImage support with ueberzug or kitty terminal.xhibit -img \"path/to/image/file\" -imb \"kitty\"\n\n or\n\nxhibit -img \"path/to/image/file\" -imb \"ueberzug\"Install ueberzug guideThe original ueberzug project has been abandoned by its original author.\nBut there are some people who are continuing its legacy.\nYou can install ueberzug by using the below commands.\nI know projects likeueberzugppexists but for now\nmy project supports onlykittyandueberzugbackend\nto display images.gitclonehttps://github.com/ueber-devel/ueberzug;cdueberzug/\npipinstall.cd..\nrm-rfueberzugImage crop fit or fillxhibit -img \"path/to/image/file\" -imb \"kitty\" -crop \"fit\"\nxhibit -img \"path/to/image/file\" -imb \"kitty\" -crop \"fill\"\n\n or\n\nxhibit -img \"path/to/image/file\" -imb \"ueberzug\" -crop \"fit\"\nxhibit -img \"path/to/image/file\" -imb \"ueberzug\" -crop \"fill\""} +{"package": "xhistogram", "pacakge-description": "For more information, including installation instructions, read the fullxhistogram documentation."} +{"package": "xhj-nameko-dependency", "pacakge-description": "\u85aa\u884c\u5bb6\u4ee3\u4ed8nameko dependencyinstallpipinstallxhj-nameko-dependencyconfig\u901a\u8fc7yaml\u6587\u4ef6\u65b9\u5f0f\u914d\u7f6enameko\u73af\u5883\u53d8\u91cf# \u516c\u79c1\u94a5\u9700\u8981\u5148base64.encode\nxhj:\n MCHNT_NUM: ${XHJ_MCHNT_NUM}\n API_BASE_URL: ${XHJ_API_BASE_URL}\n DES_KEY: ${XHJ_DES_KEY}\n PUBLIC_KEY: ${XHJ_PUBLIC_KEY}\n PRIVATE_KEY: ${XHJ_PRIVATE_KEY}How to use?fromxhjimportXHJclassTestService(Base):xhj=XHJ()@rpcdefcreate_package(self,data):returnself.xhj.call(\"remit/createpackage\",data)"} +{"package": "xhm", "pacakge-description": "UNKNOWN"} +{"package": "xhmonitor", "pacakge-description": "\u4e00\u4e2a\u6027\u80fd\u76d1\u63a7\u7684\u5e93\u5b89\u88c5\u547d\u4ee4\uff1apip install xhmonitor\u4f7f\u7528\u65b9\u6cd5\uff1afromxhmonitorimportstart_monitor,end_monitordefTestProfile():iCnt=0forxinrange(10000):iCnt+=xprint(iCnt)start_monitor()TestProfile()end_monitor()\u4f1a\u751f\u6210\u4e00\u4e2atime.txt\u548ctime.view\u6587\u672ctime.txt: \u6027\u80fd\u6d4b\u8bd5\u7684\u6587\u672c\u6587\u4ef6\uff0c\u53ef\u4ee5\u67e5\u770b\u6bcf\u4e2a\u51fd\u6570\u7684\u8fd0\u884c\u65f6\u95f4time.view\uff1a\u53ef\u4f7f\u7528kcachegrind, qcachegrind\u5de5\u5177\u6253\u5f00\u8be5\u6587\u4ef6\u53ef\u89c6\u5316\u67e5\u770b\u66f4\u8be6\u7ec6\u5185\u5bb9"} +{"package": "xhorizon", "pacakge-description": "xhorizon: Explicitly computing Penrose diagrams in general relativity.A Python package.I finally gave the package a makeover and updated to Python 3!The new documentation is still under construction\u2026but there is now an ever expanding tutorial!LinksGitHub.Documentation.PyPi.Background TheoryJC Schindler, A Aguirre.Algorithms for the explicit computation of Penrose diagrams.Class Quantum Grav 35 105019.\n(2018).arxiv:1802.02263.Getting StartedTo install:pip install xhorizonTo start using the tools, begin with thetutorialand keep an eye out forexample scripts."} +{"package": "xhostplus.blog", "pacakge-description": "This is a simple blog product for Plone 4. It\u2019s templates are\nbased upon collective.blogging, however this product does create\nit\u2019s own content types instead of using Plone\u2019s folders and\nsites to create the blog.TranslationsThis product comes with following languages:EnglishGermanFurther translations are welcome.Questions and comments tosupport@xhostplus.atChangelog1.0.1 (2013-07-16)Using getObjPositionInParent to sort blog entries in blog view\n[andreas_stocker]Setting the position of a blog entry to the very top on first save\n[andreas_stocker]1.0 (2013-01-17)Initial realease\n[andreas_stocker]"} +{"package": "xhostplus.gallery", "pacakge-description": "An image gallery product for Plone 3 and 4. It consists of a special image\ngallery folder, which can hold further image gallery folders and images, and a\nportlet. The portlet shows random images of the configured image gallery.The image gallery view is based on Plone\u2019s atct_album_view. This product\ncomes with an modified version of fancybox. It does not conflict with any\nfurther installations of fancybox.jQuery is required in order to run the gallery as it is supposed to be.TranslationsThis product comes with following languages:EnglishGermanFurther translations are welcome.Questions and comments tosupport@xhostplus.atChangelog1.8.2 - 2013-04-23Plone 4.3 compatibility\n[andreas_stocker]1.8.1 - 2012-08-17Show \u2018Next/Previous X images\u2019 instead of \u2018Next/Previous X items\u2019 in batch navigation\n[andreas_stocker]Showing batch navigation also on top of the images\n[andreas_stocker]1.8.0 - 2012-08-02Added \u2018Show images from main language\u2019 option\n[andreas_stocker]1.7.4 - 2012-07-03Plone 3 compatible again\n[andreas_stocker]1.7.3 - 2012-07-03Improved exclude uploaded images from navigation\n[andreas_stocker]1.7.2 - 2012-07-03Added Site Administrator permissions to rolemap\n[andreas_stocker]Multi-Upload can now exclude uploaded images from navigation\n[andreas_stocker]1.7.1 - 2012-01-20LinguaPlone fix\n[andreas_stocker]1.7.0 - 2011-11-02Page size configurable\n[andreas_stocker]Titles of images can be hidden\n[andreas_stocker]Cleaning filenames on multi-upload\n[andreas_stocker]1.6.5 - 2011-10-14Plone 4.1 compatible\n[andreas_stocker]1.6.4 - 2011-10-06Added xhostplus.gallery BrowserLayer\n[andreas_stocker]1.6.3 - 2011-09-28Zoomable Image works better\n[andreas_stocker]Improved Plone 3 compatibility\n[andreas_stocker]1.6.2 - 2011-07-11Slide show fixes for Plone 3\n[andreas_stocker]1.6.1 - 2011-05-02Private galleries can be selected in the gallery portlet\n[andreas_stocker]1.6.0 - 2011-04-27Added slide show\n[andreas_stocker]1.5.1 - 2011-02-08Now adding Image Gallery to default_page_types at install\n[andreas_stocker]1.5 - 2010-11-29Improved translationsAdded multiple image upload (many thanks toPlone Quick Uploadandcollective.uploadifyProjects)\n[andreas_stocker]1.0.1 - 2010-09-02Fixes in installer\n[andreas_stocker]1.0 - 2010-09-02Initial version of xhostplus.gallery\n[andreas_stocker]"} +{"package": "xhostplus.intropage", "pacakge-description": "An intro page product for Plone 3 and 4. It adds an content type, storing\nan image and a link, at which the intro page should point to.Questions and comments tosupport@xhostplus.atChangelog1.0.1 - 2011-10-06Added xhostplus.intropage BrowserLayer\n[andreas_stocker]1.0 - 2010-10-25Initial version of xhostplus.intropage\n[andreas_stocker]"} +{"package": "xhostplus.picturefolder", "pacakge-description": "A product for Plone 3 and 4 which implements a folder content type with an\noptional image field. The image is shown as thumbnail in the folder_summary_view\nof the parent folder. The picture folder itself supports all views available\nfor regular folders.TranslationsThis product comes with following languages:EnglishGermanFurther translations are welcome.Questions and comments tosupport@xhostplus.at1.0 - 2012-08-06Initial version of xhostplus.picturefolder\n[andreas_stocker]"} +{"package": "xhostplus.social", "pacakge-description": "This product adds social network buttons to each page. It supports Google+,\nTwitter, Facebook and LinkedIn. It is configurable which services are\nactivated.xhostplus.social comes with optional support for jquery.socialshareprivacy,\ndeveloped and distributed by Heise Zeitschriften Verlag GmbH & Co. KG.TranslationsThis product comes with following languages:EnglishGermanFurther translations are welcome.Questions and comments tosupport@xhostplus.atChangelog1.4.6 (2013-06-10)Improved German help text in settings for non-austrian users\n[andreas_stocker]Using canonical_object_url to determine the current page url\n[andreas_stocker]1.4.5 (2013-05-29)Do not require PasteScript for installation any more\n[andreas_stocker]1.4.4 (2013-03-25)Fixed upgrade path from 1.2 to 1.4\n[andreas_stocker]Enabled merging of JS files\n[andreas_stocker]1.4.3 (2012-02-12)Fixed JavaScript to work with IE\n[andreas_stocker]1.4.2 (2012-11-04)Fixed decode error on non-ascii hashtags\n[andreas_stocker]1.4.1 (2012-11-03)Re-added permissions for changing social attributes\n[andreas_stocker]1.4.0 (2012-11-02)Added options to enable/disable services\n[andreas_stocker]Added twitter hashtag configuration\n[andreas_stocker]Google URL shortener\n[andreas_stocker]1.2.0 (2012-05-10)Added support for LinkedIn\n[andreas_stocker]Using HTML5 compatible buttons\n[andreas_stocker]Plone 4.1 compatible\n[andreas_stocker]1.1.1 (2012-01-03)Remove quotes from cookies before adding value to a JSON string\n[andreas_stocker]1.1.0 (2011-11-09)Added support for 2-click-buttons\n[andreas_stocker]Added OpenGraph description meta tag\n[andreas_stocker]1.0.0 (2010-03-27)Initial version (not public)\n[andreas_stocker]"} +{"package": "xhostplus.textzoom", "pacakge-description": "This product provides a portlet, which allows the site visitor to resize\nthe text on the page.Questions and comments tosupport@xhostplus.atChangelog1.0.2 - 2011-10-06Added xhostplus.textzoom BrowserLayer\n[andreas_stocker]1.0.1 - 2010-12-13Setup fixes\n[andreas_stocker]1.0 - 2010-12-13Initial version of xhostplus.textzoom\n[andreas_stocker]"} +{"package": "xhostplus.videojs", "pacakge-description": "An video product for Plone 3 and 4. It provides a video content type, which\nstores WebM, H.264 and OGG Theora files (either in the ZODB or as external URL).This product uses VideoJS, falling back to Flowplayer, for playback.TranslationsThis product comes with following languages:EnglishGermanFurther translations are welcome.Questions and comments tosupport@xhostplus.atChangelog1.2.3 (2014-08-30)replaced slot body by slot main in viewvideo, added text/plain to allowable_content_types\n[eambrosch]1.2.2 (2013-07-01)Added support for youtu.be links\n[andreas_stocker]1.2.1 (2012-11-09)Uploading only one webm file is now working\n[andreas_stocker]1.2.0 (2011-10-11)Fixed fullscreen mode in VideoJS\n[andreas_stocker]Support for adding FLV files\n[andreas_stocker]1.1.0 (2011-10-09)Added support for youtube videos\n[andreas_stocker]1.0.0 (2010-03-27)Initial version (not public)\n[andreas_stocker]"} +{"package": "xhotkeys", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xhp-flow", "pacakge-description": "##ABOUT\nThis is a mini deep learning framework created by xiaohaipeng @tianjin##FeaturesDefine Dynamic Computing GraphDefine Neural Network OperatorDefine Placeholder,Linear,Sigmoid,Relu,MSEAuto-Diff ComputingAuto-Feedforward and Backward#RemainClassificationCross-EntropyCNN, RNNConnectionwechat:18651271973\nMail:307153814@qq.com"} +{"package": "xhpflow-1.0", "pacakge-description": "##ABOUT\nThis is a mini deep learning framework created by xiaohaipeng @tianjin##FeaturesDefine Dynamic Computing GraphDefine Neural Network OperatorDefine Placeholder,Linear,Sigmoid,Relu,MSEAuto-Diff ComputingAuto-Feedforward and Backward#RemainClassificationCross-EntropyCNN, RNNConnectionwechat:18651271973\nMail:307153814@qq.com"} +{"package": "xhproxies", "pacakge-description": "\u8fd4\u56de\u4ee3\u7406ip"} +{"package": "xhpubqt", "pacakge-description": "UE4\u6ed1\u52a8\u6761\u5982\u679c\u6ca1\u6709\u8bbe\u7f6e\u8303\u56f4\u4e0d\u663e\u793a\u767e\u5206\u6bd4\uff0c\u8bbe\u7f6e\u4e86\u624d\u4f1a\u663e\u793a\u5355\u673a\u9f20\u6807\u957f\u6309\u62d6\u52a8\u53ef\u4ee5\u8c03\u6574\u6570\u503c\uff0c\u4e0d\u53ef\u8d85\u8fc7\u6700\u5927\u6700\u5c0f\u503c\uff0c\u62d6\u52a8\u65f6\u4f1a\u9690\u85cf\u9f20\u6807\u7bad\u5934\u5355\u673a\u9f20\u6807\u53ef\u4ee5\u624b\u52a8\u8f93\u5165\u6570\u503c\uff0c\u624b\u52a8\u8f93\u5165\u65f6\u53ef\u8d85\u8fc7\u8bbe\u5b9a\u8303\u56f4\u65e0\u8303\u56f4\u9650\u5236\u65f6\u4f1a\u6839\u636e\u5f53\u524d\u6570\u503c\u667a\u80fd\u8c03\u6574\u5927\u5c0f"} +{"package": "xhpubs", "pacakge-description": "DescripteThis is a simple public module that helps you implement some simple function functions."} +{"package": "xhpy", "pacakge-description": "XHPyextends Python syntax such that XML document\nfragments become valid Python expressions. It is based offXHP, a similar framework for PHP.AdvantagesSimplicity: write UI logic in a simple, expressive syntax without the need for external\ntemplates or templating languages.Flexibility: use Python expressions freely within XHPy tags, and vice-versa.Security: benefit from automatic escaping of text within XHPy tags.Reusability: build reusable components by subclassing :x:element.An exampleIn bar.py:from xhpy.init import register_xhpy_module\nregister_xhpy_module('foo')\nimport fooIn foo.py:from xhpy.pylib import *\nclass :ui:foo(:x:element):\n attribute list bar\n category %flow\n def render(self):\n a =
    \n for b in self.getAttribute('bar'):\n a.appendChild(
  • {b}
    • )\n return a\nprint
    We can now run bar.py as a normal Python script:$ python bar.py\n
    • 0
    • 1
    • 2
    Congratulations! You just wrote your first snippet of XHPy.SyntaxXHPy adds some new syntax to Python. Line by line replay time!from xhpy.init import register_xhpy_moduleThis initializes XHPy and allows you to register modules to be interpreted as XHPy.register_xhpy_module('foo')Now thefoomodule infoo.pywill be interpreted as XHPy when imported.\nIffoowere a package, all of its submodules would also be registered; this is\nuseful for registering UI libraries.import fooTo actually use XHPy, however, you will probably want the core library:from xhpy.pylib import *Now you have access to all the standard HTML 4.0 elements, the:x:elementbase class\n(this is what you build custom components on top of!), and some utilities.class :ui:foo(:x:element):Making new components is easy: just subclass:x:element. For your component class to be\nregistered, it must start with:- this clearly distinguishes your components from\nordinary Python classes.attribute list barThis is an attribute declaration, meaning that:ui:fooallows bar attributes ontags. Note thelater on - like XHP, XHPy uses XML attribute syntax.category %flowThis is a category declaration -:ui:foois part of the%flowcategory. Categories are\nprimarily useful as a way of identifying elements that are similar without using\ninheritance; for example, thetag in pylib.html haschildren (pcdata | %flow)*indicating that its children must either contain text or be of the%flowcategory. (So\nwe can putinside!)def render(self):When you print an:x:element(or callstron it), therender()method is invoked; this\nis where you put your UI logic.a =
      \nfor b in self.getAttribute('bar'):\n a.appendChild(
    • {b}
      • )\nreturn aHere,is a thin wrapper around
        that allows you to construct an unordered\nlist out of a Python list. Standard HTML elements like
          and
        • are automatically\nrendered - except that, in XHPy, you can use Python expressions within tags, so that{b}is replaced by the value of b. Note the use ofgetAttribute()andappendChild():self.getAttribute('bar')fetches the value of attributebar(in this case,range(3)), whereasa.appendChild(
        • {b}
          • )adds
        • {b}
          • as a child ofa =
            .XHPy is largely based off XHP; for more details on the latter, see theXHP wiki. The syntax has been adapted for\nPython; in particular:there are no semicolons;XHPy class names may be used anywhere ordinary Python classes can;XHPy tags ignore internal whitespace, but must externally obey indentation and\nline continuation rules.More on the last point:def foo(href):\n return \n\ndef bar(href):\n return\\\n are valid, whereasdef foo(href):\n return\\\n \n is not, as it introduces an extra dedent after.How it worksWhen youimport xhpy.initXHPy installs animport hook.\nThis hook traps subsequent import statements, running them through a preprocessor\nthat parses a superset of Python. This preprocessor translates XHPy tags and class\nnames to valid Python, then executes the translated code in module scope.This is similar to how XHP works, except:with, e.g.,pythonenv, you can always use\nXHPy even without access to system-wide Python package installation directories;by default, Python compiles bytecode .pyc files from your modules, so the\npreprocessing only needs to be done once when a module is first imported."} +{"package": "xh-py-project-versioning", "pacakge-description": "A dictionary utility of self dev py libraryBuildrm-frdist\npython-mbuild# automate by following `-u {user} -p {token / password}`# api automate by following `-u __token__ -p {token / password}`python-mtwineuploaddist/*PYTHONPATH=srcpythonsrc/xh_py_project_versioning/__main__.py--project-filepyproject.toml--major-d"} +{"package": "xhs", "pacakge-description": "\ud83c\udf70xhsWarningThe primary purpose of this repository is to practice my Python skills. It is important to note that web crawling may\nbe considered illegal, and therefore, it is crucial to refrain from exerting any pressure or engaging in unauthorized\nactivities on websites.xhsis a crawling tool designed to extract data fromxiaohongshu websiteUsagexhs is available on PyPI:$python-mpipinstallxhsif you want the latest version, you can install from git:$python-mpipinstallgit+https://github.com/ReaJason/xhsBasic Usagemaybe now is more complex, Thanks@NanmiCoderPlease find in thedocument"} +{"package": "xhs-2-album", "pacakge-description": "xhs_2_albumReturn photo list and caption (markdown format) from xhs.usageimport xhs_2_album\nresult = xhs_2_album.get(status)\nresult.imgs\nresult.caphow to installpip3 install xhs_2_album"} +{"package": "x-hsky-whl-test", "pacakge-description": "Test PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xhs-spider", "pacakge-description": "Spider_XHS\u5c0f\u7ea2\u4e66\u4e2a\u4eba\u4e3b\u9875\u56fe\u7247\u548c\u89c6\u9891\u65e0\u6c34\u5370\u722c\u53d6\u6548\u679c\u56fe\u8fd0\u884c\u73af\u5883Python\u73af\u5883NodeJS\u73af\u5883\u8fd0\u884c\u65b9\u6cd5\uff1a\u628a\u4f60\u60f3\u8981\u7684id\u5168\u90e8\u653e\u5230\u5217\u8868\u91cc# \u4e3b\u9875\u5904\u7406\n\nfrom xhs_spider.home import Home\n\nhome = Home()\n\nurl_list = [\n\n 'https://www.xiaohongshu.com/user/profile/6185ce66000000001000705b',\n\n 'https://www.xiaohongshu.com/user/profile/6034d6f20000000001006fbb',\n\n]\n\nhome.main(url_list)\n\n# \u7b14\u8bb0\u5904\u7406\n\nfrom xhs_spider.note import Note\n\none_note = OneNote()\n\nurl_list = [\n\n 'https://www.xiaohongshu.com/explore/64356527000000001303282b',\n\n]\n\none_note.main(url_list)\n\n# \u641c\u7d22\u7ed3\u679c\u5904\u7406\n\nfrom xhs_spider.search import Search\n\nsearch = Search()\n\nquery = '\u4f60\u597d'\n\n# \u641c\u7d22\u7684\u6570\u91cf\uff08\u524d\u591a\u5c11\u4e2a\uff09\n\nnumber = 22\n\nsearch.main(query, number)\u65e5\u5fd723/08/08 first commit23/09/13 \u3010api\u66f4\u6539params\u589e\u52a0\u4e24\u4e2a\u5b57\u6bb5\u3011\u4fee\u590d\u56fe\u7247\u65e0\u6cd5\u4e0b\u8f7d\uff0c\u6709\u4e9b\u9875\u9762\u65e0\u6cd5\u8bbf\u95ee\u5bfc\u81f4\u62a5\u9519\u300223/09/16 \u3010\u8f83\u5927\u89c6\u9891\u51fa\u73b0\u7f16\u7801\u95ee\u9898\u3011\u4fee\u590d\u89c6\u9891\u7f16\u7801\u95ee\u9898\uff0c\u52a0\u5165\u5f02\u5e38\u5904\u7406\u300223/09/18 \u4ee3\u7801\u91cd\u6784\uff0c\u52a0\u5165\u5931\u8d25\u91cd\u8bd5\u300223/09/19 \u65b0\u589e\u4e0b\u8f7d\u641c\u7d22\u7ed3\u679c\u529f\u80fd\u6ce8\u610f\u4e8b\u9879\u672c\u9879\u76ee\u4ec5\u4f9b\u5b66\u4e60\u4e0e\u4ea4\u6d41\uff0c\u4fb5\u6743\u5fc5\u5220other\u81ea\u884c\u5c06cookies\u653e\u5230\u76ee\u5f55\u4e0bcookies.txt\u4e2d\uff0c\u53bb\u8bbe\u7f6e\u91cc\u7684\u5e94\u7528\u7a0b\u5e8f\u91cc\u627e\u6216\u8005\u7f51\u7edc\u8bf7\u6c42\u91cc\u627e\uff0c\u9700\u8981\u54ea\u4e9b\u53ef\u4ee5\u53c2\u8003cookie.txt\u6587\u4ef6\u3002\u53ef\u91c7\u7528\u4ee5\u4e0b\u65b9\u6cd5\u83b7\u53d6cookie\uff0c\u5e76\u8fd0\u884c\u5bf9\u5e94\u6587\u4ef6\u3002\u6b22\u8fcestar\uff0c\u4e0d\u65f6\u66f4\u65b0\u3002\u6709\u95ee\u9898\u53ef\u4ee5\u52a0QQ\u6216\u8005\u5fae\u4fe1\u4ea4\u6d41\uff08992822653\uff09"} +{"package": "xhtml2pdf", "pacakge-description": "XHTML2PDFRelease Notes can be found here:Release NotesAs with all open-source software, its use in production depends on many factors, so be aware that you may find issues in some cases.Big thanksto everyone who has worked on this project so far and to those who help maintain it.Aboutxhtml2pdf is a HTML to PDF converter using Python, the ReportLab Toolkit, html5lib and pypdf. It supports HTML5 and CSS 2.1 (and some of CSS 3). It is completely written in pure Python, so it is platform independent.The main benefit of this tool is that a user with web skills like HTML and CSS is able to generate PDF templates very quickly without learning new technologies.Please consider support this project usingPatreonor Bitcoins:bc1qmr0skzwx5scyvh2ql28f7gfh6l65ua250qv227DocumentationThe documentation of xhtml2pdf is available atRead the Docs.And we could use your help improving it! A good place to start isdoc/source/usage.rst.InstallationThis is a typical Python library and can be installed using pip:pip install xhtml2pdfRequirementsOnly Python 3.8+ is tested and guaranteed to work.All mandatory requirements are listed in thepyproject.tomlfile and are installed automatically using thepip install xhtml2pdfmethod.As PDF library we depend on reportlab, which needs a rendering backend to generate bitmaps and vector graphic formats.\nFor more information about this, have a look at thereportlab docs.The recommended choice is thecairo graphics librarywhich has to be installed system-wide e.g. via the OS package manager\nin combination with thePyCairoextra dependency:pip install xhtml2pdf[pycairo]Alternatively, the legacyRenderPMcan be used by installing:pip install xhtml2pdf[renderpm]AlternativesYou can tryWeasyPrint. The codebase is pretty, it has different features and it does a lot of what xhtml2pdf does.Call for testingThis project is heavily dependent on getting its test coverage up! Furthermore, parts of the codebase could do well with cleanups and refactoring.If you benefit from xhtml2pdf, perhaps look at thetest coverageand identify parts that are yet untouched.Development environmentIf you don\u2019t have it, installpip, the python package installer:sudo easy_install pipFor more information aboutpiprefer tohttp://www.pip-installer.orgWe will recommend usingvenvfor development.Create a virtual environment for the project. This can be inside the project directory, but cannot be under version control:python -m venv .venvActivate your virtual environment:source .venv/bin/activateLater to deactivate it use:deactivateThe next step will be to install/upgrade dependencies from thepyproject.tomlfile:pip install -e .[test,docs,build]Run tests to check your configuration:toxYou should have a log with the following success status:congratulations :) (75.67 seconds)Python integrationSome simple demos of how to integrate xhtml2pdf into a Python program may be found here:test/simple.pyRunning testsTwo different test suites are available to assert that xhtml2pdf works reliably:Unit tests. The unit testing framework is currently minimal, but is being\nimproved on a regular basis (contributions welcome). They should run in the\nexpected way for Python\u2019s unittest module, i.e.:toxFunctional tests. Thanks to mawe42\u2019s super cool work, a full functional\ntest suite is available attestrender/.You can run them using makemaketest# run testsmaketest-ref# generate reference data for testrendermaketest-all# Run all test using toxContactThis project is community-led! Feel free to open up issues on GitHub about new ideas to improve xhtml2pdf.HistoryThese are the major milestones and the maintainers of the project:2000-2007 Dirk Holtwick (commercial project of spirito.de)2007-2010 Dirk Holtwick (project named \u201cpisa\u201d, project released as GPL)2010-2012 Dirk Holtwick (project named \u201cxhtml2pdf\u201d, changed license to Apache)2012-2015 Chris Glass (@chrisglass)2015-2016 Benjamin Bach (@benjaoming)2016-2018 Sam Spencer (@LegoStormtroopr)2018-Current Luis Zarate (@luisza)For more history, see theRelease Notes.LicenseCopyright 2010 Dirk Holtwick, holtwick.itLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at:http://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xhtml2pdf2", "pacakge-description": "XHTML2PDFRelease Notes can be found here:Release NotesAs with all open-source software, its use in production depends on many factors, so be aware that you may find issues in some cases.Big thanksto everyone who has worked on this project so far and to those who help maintain it.Aboutxhtml2pdf is a HTML to PDF converter using Python, the ReportLab Toolkit, html5lib and pypdf. It supports HTML5 and CSS 2.1 (and some of CSS 3). It is completely written in pure Python, so it is platform independent.The main benefit of this tool is that a user with web skills like HTML and CSS is able to generate PDF templates very quickly without learning new technologies.Please consider support this project usingPatreonor Bitcoins:bc1qmr0skzwx5scyvh2ql28f7gfh6l65ua250qv227DocumentationThe documentation of xhtml2pdf is available atRead the Docs.And we could use your help improving it! A good place to start isdoc/source/usage.rst.InstallationThis is a typical Python library and can be installed using pip:pip install xhtml2pdfRequirementsOnly Python 3.7+ is tested and guaranteed to work.All additional requirements are listed in therequirements.txtfile and are installed automatically using thepip install xhtml2pdfmethod.AlternativesYou can tryWeasyPrint. The codebase is pretty, it has different features and it does a lot of what xhtml2pdf does.Call for testingThis project is heavily dependent on getting its test coverage up! Furthermore, parts of the codebase could do well with cleanups and refactoring.If you benefit from xhtml2pdf, perhaps look at thetest coverageand identify parts that are yet untouched.Development environmentIf you don\u2019t have it, installpip, the python package installer:sudo easy_install pipFor more information aboutpiprefer tohttp://www.pip-installer.orgWe will recommend usingvirtualenvfor development.Create a virtualenv for the project. This can be inside the project directory, but cannot be under version control:python -m venv xhtml2pdfenvActivate your virtualenv:source xhtml2pdfenv/bin/activateLater to deactivate it use:deactivateThe next step will be to install/upgrade dependencies from therequirements.txtfile:pip install -r requirements.txtRun tests to check your configuration:nosetests --with-coverageYou should have a log with the following success status:Ran 167 tests in 34.585s\n\nOKPython integrationSome simple demos of how to integrate xhtml2pdf into a Python program may be found here:test/simple.pyRunning testsTwo different test suites are available to assert that xhtml2pdf works reliably:Unit tests. The unit testing framework is currently minimal, but is being\nimproved on a regular basis (contributions welcome). They should run in the\nexpected way for Python\u2019s unittest module, i.e.:nosetests --with-coverage (or your personal favorite)Functional tests. Thanks to mawe42\u2019s super cool work, a full functional\ntest suite is available attestrender/.You can run them using makemaketest# run nosetestmaketest-ref# generate reference data for testrendermaketest-all# Run all test using toxContactThis project is community-led! Feel free to open up issues on GitHub about new ideas to improve xhtml2pdf.HistoryThese are the major milestones and the maintainers of the project:2000-2007, commercial project, spirito.de, written by Dirk Holtwich2007-2010 Dirk Holtwich (project named \u201cPisa\u201d, project released as GPL)2010-2012 Dirk Holtwick (project named \u201cxhtml2pdf\u201d, changed license to Apache)2012-2015 Chris Glass (@chrisglass)2015-2016 Benjamin Bach (@benjaoming)2016-2018 Sam Spencer (@LegoStormtroopr)2018-Current Luis Zarate (@luisza)For more history, see theRelease Notes.LicenseCopyright 2010 Dirk Holtwick, holtwick.itLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at:http://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xhtml2pdf-legacy", "pacakge-description": "HTML/CSS to PDF converter based on Python patched to use Pillow >= 2.7.0,<=2.8.0Aboutxhtml2pdfis a html2pdf converter using the ReportLab Toolkit,\nthe HTML5lib and pyPdf. It supports HTML 5 and CSS 2.1 (and some of CSS 3).\nIt is completely written in pure Python so it is platform independent.The main benefit of this tool that a user with Web skills like HTML and CSS\nis able to generate PDF templates very quickly without learning new\ntechnologies.RequirementsReportlab Toolkit 2.2+html5lib 0.11.1+pyPdf 1.11+ (optional)All requirements are listed inrequirements.txtfile.Development environmentPython, virtualenv and dependenciesInstall Python 2.6.x or 2.7.x. Installation steps depends on yours operating system.Install Pip, the python package installer:sudo easy_install pipFor more information aboutpiprefer tohttp://www.pip-installer.org/.I will recommend usingvirtualenvfor development. This is great to have separate environment for\neach project, keeping the dependencies for multiple projects separated:sudo pip install virtualenvFor more information aboutvirtualenvrefer tohttp://www.virtualenv.org/Create virtualenv for the project. This can be inside the project directory, but cannot be under\nversion control:virtualenv --distribute xhtml2pdfenvActivate your virtualenv:source xhtml2pdfenv/bin/activateLater to deactivate use:deactivateNext step will be to install/upgrade dependencies fromrequirements.txtfile:pip install -r requirements.txtRun tests to check you configuration:nosetests --with-coverageYou should have log with success status:Ran 35 tests in 0.322s\n\nOKPython integrationSome simple demos of how to integrate xhtml2pdf into\na Python program may be found here: test/simple.pyContributingDevelopment for this software happend on github, and the main fork is\ncurrently athttps://github.com/chrisglass/xhtml2pdfContributions are welcome in any format, but using github\u2019s pull request\nsystem is very highly preferred since it makes review and integration\nmuch easier.Running testsTwo different test suites are available to assert xhtml2pdf works reliably:Unit tests. The unit testing framework is currently minimal, but is being\nimproved on a daily basis (contributions welcome). They should run in the\nexpected way for Python\u2019s unittest module, i.e.:nosetests --with-coverage (or your personal favorite)Functional tests. Thanks to mawe42\u2019s super cool work, a full functional\ntest suite lives in testrender/.ContactIRC: #xhtml2pdf on freenodeMailing list:xhtml2pdf@googlegroups.comGoogle group:http://groups.google.com/group/xhtml2pdfMaintainer: Chris Glass LicenseCopyright 2010 Dirk Holtwick, holtwick.itLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xhtmlhook", "pacakge-description": "Extracts and imports Python code from preformatted elements in XHTML documents from remote hosts or local files. URLs can be added to the list of standard paths or modules can be imported directly using a convenience function.The import hook can also be used to import other standard file types from remote locations."} +{"package": "xhttp", "pacakge-description": "No description available on PyPI."} +{"package": "xh-utils", "pacakge-description": "XhUtilspythonsetup.pybdist_wheel--universal\ntwineuploaddist/*# pip install twinepipinstall--upgradexh_utils-ihttps://www.pypi.org/simple/\u5f69\u8272\u65e5\u5fd7\u793a\u4f8b1.\u5f69\u8272\u65e5\u5fd7fromxh_utilsimportloggerlogger.init_logger()# logger.init_logger(log_pathdir=\"./log/\",is_split_logfile=True) # \u65e5\u5fd7\u540c\u6b65\u5199\u5165\u6587\u4ef6\uff0c\u5e76\u6309\u5929\u8fdb\u884c\u6587\u4ef6\u5206\u5272\u5199\u5165logger.debug(\"debug\")logger.info(\"info\")logger.warning(\"warning\")logger.error(\"error\")logger.critical(\"critical\")"} +{"package": "xhydro", "pacakge-description": "Hydrological analysis library built with xarrayFree software: Apache-2.0Documentation:https://xhydro.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theOuranosinc/cookiecutter-pypackageproject template."} +{"package": "xi", "pacakge-description": "UNKNOWN"} +{"package": "xia2", "pacakge-description": "No description available on PyPI."} +{"package": "xia-actor", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-actor-openai", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-agent", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-agent-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-analytics", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-analytics-sql", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-api", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-api-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-broadcast", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-broadcast-fastapi", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-broadcast-listener", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-cache", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-cloudmailin", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-coder", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-compiler-jsoneditor", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-compiler-openapi", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-compiler-python", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-composer", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-diff-match-patch", "pacakge-description": "Current version is a wrap of Google\u2019s project:https://github.com/google/diff-match-patchInstallation:pipinstallxia-diff-match-patchUsageapply_patchesfunction takes a series patched files as arguments, sorted by its priorities.fromxia_diff_match_patchimportapply_patchesbase=\"Line 1\\n\"a1=\"Line 1\\nLine2\\n\"a2=\"Line 1\\n\\nCode 1\\nCode 2\\nCode 3\\n\"a3=\"Line 3\\n\"print(apply_patches(base,a1,a2,a3))"} +{"package": "xia-easy-proto", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-bigquery", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-cypher", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-firestore", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-gitlab", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-gitlab-project", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-mongodb", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-mysql", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-neo4j", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-pinecone", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-postgresql", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-redis", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-rest", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-sql", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-terraform", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-terraform-gcs", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-engine-test", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-fields", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-fields-network", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-framework", "pacakge-description": "Welcome to use XIA Framework"} +{"package": "xia-git", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-git-gitlab", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-gpt", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-gpt-openai", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xiak-diff-cover", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xia-logger", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-logger-gcp", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-logger-pubsub", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-login-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-mail", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-mail-sender", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xiami", "pacakge-description": "UNKNOWN"} +{"package": "xia-models", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-module", "pacakge-description": "Welcome to use XIA Framework"} +{"package": "xia-module-application-gh", "pacakge-description": "Welcome to use XIA Framework"} +{"package": "xia-module-gcp-project", "pacakge-description": "Welcome to use XIA Framework"} +{"package": "xia-module-pypi", "pacakge-description": "Welcome to use XIA Framework"} +{"package": "xiancipdf", "pacakge-description": "This is the homepage of our project."} +{"package": "xia-nester", "pacakge-description": "No description available on PyPI."} +{"package": "xiangcai-bark-service", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiangcheck", "pacakge-description": "# Xiangqi CheckerA simple module for checking the legality of xiangqi moves, derived from https://github.com/shaochuan/Xiangqi. Currently untested and experimental.## Get it`pip install xiangcheck`## Use itCurrently uses a move notation that has no relation to the real game. Translation coming soon.```pythonimport xiangcheckchecker = xiangcheck.Checker()# can move a soldier forward?checker.check_move((4,6),(4,5))# True# move that soldier forwardchecker.make_move((4,6),(4,5))# that old move is no longer validchecker.check_move((4,6),(4,5))# False```"} +{"package": "xiangmutest", "pacakge-description": "reStructuredText (reST) reStructuredText (reST)Why Should I Use This?Why Should I Use ThisWhy Should I Use Thisdef test(a, b, c, d):print(a+b+c+d)"} +{"package": "xiangqi", "pacakge-description": "XiangqiHow to usefromxiangqiimportEnvenv=Env(opening)# \u4e0d\u4f20\u5f00\u5c40\u72b6\u6001\u8868\u793a\u4ece\u5934\u4e0b\u8d77ob=env.reset()# \u521d\u59cb\u89c2\u5bdfwhileTrue:env.render()# \u663e\u793a\u68cb\u5c40player=# which agent are responsible for ob['cur_player']?action=player.make_decision(**ob)# agent \u7684\u51b3\u7b56ob,reward,done,info=env.step(action)ifdone:env.render()breakDesign decisionsobservation\u4ee5\u5f53\u524d\u73a9\u5bb6\u7684\u89c6\u89d2\u89c2\u5bdf\uff0c\u5305\u62ec\u5750\u6807\u7cfb\u3001\u884c\u3001\u5217\uff0c\u4ee5\u53ca\u5f53\u524d\u7684\u5408\u6cd5\u8d70\u6cd5\uff0c\u4e0a\u4e00\u6b65\u88ab\u5bf9\u624b\u5403\u6389\u7684\u5b50(\u7528\u4e8ereward shaping)action\u65b9\u68481\u4ee5\u5f53\u524d\u73a9\u5bb6\u7684\u89c6\u89d2\u884c\u52a8\uff0caction space:MultiDiscrete(9, 10, 9, 10)\u524d\u97622\u7ef4\u8868\u793a\u6e90\u4f4d\u7f6e(col, row)\uff0c\u540e\u97622\u7ef4\u8868\u793a\u76ee\u6807\u4f4d\u7f6e\u7a7a\u95f4\u5927\u5c0f8100\u65b9\u68482\n\u4efb\u4e00\u4f4d\u7f6e\u7684\u884c\uff0c\u5217\uff0c\u56db\u65b92x2\u8303\u56f4\u7684\u4f4d\u7f6e\uff0c\u7a7a\u95f4\u5927\u5c0f2550\u65b9\u68483\u5bf9\u6bcf\u4e00\u7c7b\u5b50\uff0c\u4ece\u53f3\u5230\u5de6\uff0c\u4ece\u4e0a\u5230\u4e0b\u7f16\u53f7\uff0c\u7136\u540e\u9488\u5bf9\u68cb\u5b50\u7c7b\u522b\u7f16\u7801\u6700\u5927\u53ef\u80fd\u7684\u8d70\u6cd5\u8f66\u70ae\uff1a17\uff0c\u9a6c\uff1a8\uff0c\u8c61\uff1a4\uff0c\u58eb\uff1a4\uff0c\u5175\uff1a3\uff0c\u5c06\uff1a4\u7a7a\u95f4\u5927\u5c0f119\u6ce8\u610f\uff1a\u7b56\u7565\u5e94\u8be5\u5305\u542b\u5bf9\u5bf9\u624b\u6c42\u548c\u8bf7\u6c42\u7684\u5904\u7406\uff0c\u56de\u7b54\u662f\u5426\u540c\u610f\u548cDetails\u9ed8\u8ba4\u6267\u7ea2\u8005\u5148\u4e0b\u89c2\u5bdf\u5230\u7684\u4fe1\u606f\u5305\u62ec\uff1aboard_state\uff1a\u68cb\u76d8\u72b6\u6001\uff0cFEN\u4e32\uff0c\u5b83\u5305\u542b\u4e86\u5c40\u9762\u7684\u6240\u6709\u4fe1\u606fsue_draw: \u662f\u5426\u5bf9\u624b\u5728\u6c42\u548c\uff0c\u5982\u679c\u662f\uff0c\u9700\u8981\u5bf9\u6c42\u548c\u505a\u51fa\u53cd\u5e94\uff0c\u5373\u662f\u5426\u540c\u610f\u548c\u5c40\u64cd\u4f5c\u73af\u5883\u7684\u8f93\u5165(\u5373env.step(action)\u4e2d\u7684action)\u4e3a\u4e00\u4e2a\u5b57\u7b26\u4e32\uff1a\"RESIGN\":\u8ba4\u8f93\uff0c\u8ba4\u8f93\u4f1a\u5f15\u8d77\u672c\u5c40\u7ed3\u675f\"SUE_DRAW\":\u6c42\u548c\uff0c\u4e3b\u52a8\u6c42\u548c\u53ea\u8981\u53d1\u8fd9\u4e2a\u5b57\u7b26\u4e32\uff0c\u5bf9\u624b\u9700\u8981\u56de\u590d\"yes\"\u6216\"no\"\u8868\u793a\u540c\u610f\u4e0e\u5426UCCI\u8d70\u6cd5\u4e32:\u5982\"b7b0\"\uff0c\u5373\u6e90\u4f4d\u7f6e\u548c\u76ee\u6807\u4f4d\u7f6e\u7684\u7f16\u7801\u64cd\u4f5c\u73af\u5883\u7684\u8f93\u51fa(\u5373env.step(action)\u7684\u8fd4\u56de\u503c)\u5206\u4e3a\u56db\u4e2a\u90e8\u5206\uff1aob(dict) \u89c2\u5bdf\uff0c\u5207\u6362\u5f53\u524d\u73a9\u5bb6\u540e(\u5373\u4e0b\u4e00\u4e2a\u73a9\u5bb6)\u7684\u89c2\u5bdf\uff0c\u5177\u4f53\u63cf\u8ff0\u53c2\u770b\u4e0a\u9762\uff0cdone\u4e3aTrue\u65f6\u4e3aNonereward(int) \u56de\u62a5\uff0c\u5f53\u524d\u73a9\u5bb6(\u5373\u505a\u672c\u6b21action\u7684\u73a9\u5bb6)\u7684\u56de\u62a5\uff0cdone\u4e3aFalse\u65f6\u4e3aNonedone(bool)\uff0c\u8fd9\u4e00\u5c40\u662f\u5426\u7ed3\u675finfo(str)\uff0c\u4e00\u4e9b\u9644\u52a0\u4fe1\u606f\u663e\u793a\u68cb\u5c40env.render()\uff1a\u5b57\u7b26\u754c\u9762\u4e0b\u663e\u793a\u7684\u68cb\u5c40\u3002\u68cb\u76d8\u4e0d\u4ee5\u73a9\u5bb6\u89c6\u89d2\u53d8\u5316\u7684\uff0c\u800c\u662f\u56fa\u5b9a\u7ea2\u8272\u5728\u4e0b\uff0c\u9ed1\u8272\u5728\u4e0a\u3002\u68cb\u5b50\u5728\u989c\u8272\u4e0a\u505a\u4e86\u533a\u5206\uff0c\u5728\u5b57\u5f62\u4e0a\u4e5f\u505a\u4e86\u533a\u5206\uff0c\u7ea2\u8272\u7684\u611f\u89c9\u66f4\u5e26\u4eba\u6027\u4e00\u4e9b\uff0c\u9ed1\u65b9\u6709\u70b9\u50cf\u539f\u59cb\u6587\u660e\u53e6\u5916\"\u5c06\u519b\"\uff0c\u5403\u5b50\u7b49\u4fe1\u606f\u4e5f\u4f1a\u663e\u793a\u5e38\u91cfN_ROWS=10# term: rankN_COLS=9# term: fileREWARD_WIN=1REWARD_LOSE=-1REWARD_DRAW=0REWARD_ILLEGAL=-5# illegal actionclassAction(IntEnum):ADVANCE=1# \u8fdbRETREAT=2# \u9000TRAVERSE=3# \u5e73SUE_DRAW=4# \u6c42\u548cRESIGN=5# \u8ba4\u8f93classCamp(IntEnum):BLACK=1RED=2classForce(IntEnum):SHUAI=1SHI=2XIANG=3MA=4JU=5PAO=6BING=7\u5e2e\u52a9\u51fd\u6570defdecode(board_state)# \u89e3\u7801\u68cb\u76d8\u72b6\u6001\uff0c\u6574\u6570->(Camp, Force)\u5217\u8868(\u4ece\u5de6\u5230\u53f3\uff0c\u4ece\u4e0a\u5230\u4e0b)defchinese_to_ucci(action,camp,board)# \u4e2d\u6587\u7eb5\u7ebf\u683c\u5f0f -> ucci\u683c\u5f0f\uff0c\u5982\u70ae\u4e8c\u5e73\u4e94->h7e7defucci_to_chinese(action)# \u4e0a\u9762\u51fd\u6570\u7684\u9006referenceXiangqi\u4e2d\u5f0f\u8bb0\u6cd5\u897f\u5f0f\u8bb0\u6cd5\u7740\u6cd5\u8868\u793a\u672f\u8bedUCCIUCIElo\u8ba1\u7b97\u6e90\u7801"} +{"package": "xiangqi-setup", "pacakge-description": "xiangqi-setup (and xiangqi-board)Overviewxiangqi-setupis a command line tool usingsvgutils0.3.4 to\nrenderXiangqi(Chinese chess) board setups from WXF/FEN/annoFEN/XAYfiles to SVG images.\nWith WXF files that contain move history,xiangqi-setupcan replay these moves on top of the initial setup \u2014\nall of them, none, or any custom number of moves (using the--moves COUNTargument).\nWithXAY/annoFENfiles\nit can also drawarrows, mark a field as \"good\", \"bad\" or involved in a move \u2014\nit can addannotations.The most simple way to render a given setup is:#xiangqi-setupinput.wxfoutput.svgFor filedoc/demo.wxf, the result is:(left: default board, default pieces \u2014 right: default board,euro_xiangqi_jspieces)There are a number of themes to pick from for board and pieces (independently).\nThe--helplisting below also includes the list of all themes\nand their license information.Thedefault board themeclean_alphahas been generated with command line toolxiangqi-boardthat is included with thexiangqi-setuppackage. It can be used to create\nvariations of the detault theme, e.g. to create a version with reduced spacing\nin crosses you would run:#xiangqi-board--cross-gap-px2board.{svg,ini}InstallationYou can install the latest release using pip like so:#pipinstallxiangqi-setupIf you would rather run the latest pre-release code off Gitmasterin a virtualenv, you could do:#gitclone--depth1https://github.com/hartwork/xiangqi-setup#cdxiangqi-setup/#python3-mvenvvenv#sourcevenv/bin/activate#pipinstall-e.Writing a BookFor a demo of how to usexiangqi-setupin writing a book\nplease seehttps://github.com/hartwork/xiangqi-book-example.Usage in Detailxiangqi-setup\u2014 Renders WXF/FEN/annoFEN/XAY Files to SVG Images#xiangqi-setup--helpusage: xiangqi-setup [OPTIONS] INPUT_FILE OUTPUT_FILExiangqi-setup --helpxiangqi-setup --versionGenerate razor-sharp Xiangqi (Chinese chess) setup graphicspositional arguments:INPUT_FILE location of WXF/FEN/annoFEN/XAY file to renderOUTPUT_FILE location of SVG output file to writeoptional arguments:-h, --help show this help message and exit--debug enable debugging (e.g. mark corners of the board)--version show program's version number and exittheme selection:--board THEME name of board theme to use (default: \"clean_alpha\");please check the list of available themes below--pieces THEME name of piece theme to use (default: \"retro_simple\");please check the list of available themes below--annotations THEME name of annotation theme to use (default:\"colors_alpha\"); please check the list of availablethemes belowscaling:--width-px PIXEL width of the output in pixels (default: ~248.03, i.e. 7.0cm at 90.0dpi)--width-cm CENTIMETERwidth of the output in centimeters (default: 7.0)--dpi FLOAT resolution of the output in dots per inch (default: 90.0)--scale-pieces FACTORfactor to scale pieces by (0.0 to 1.2, default: 0.9)--scale-annotations FACTORfactor to scale annotations by (0.0 to 1.2, default: 0.9)WXF format arguments:--moves COUNT how many moves to play (for a file with moves history),e.g. \"3\" would play the first move of red, the firstmove of black and the second move of red and then skipany remaining moves, \"all\" would play all moves, \"-1\"all moves but the last, \"-2\" all but the last two(default: \"0\")--annotate-last-move Add annotations \"blank_move\" and \"piece_move\" to thesource and target locations of the last moveboard themes (16 available, in alphabetic order):a4_blank_2cm_margin (license: CC0-1.0)cambaluc_remake_nolegend (license: CC0-1.0)cambaluc_remake_nolegend_nogap (license: CC0-1.0)ccbridge_3_0_beta4_default_preview_remake (license: CC0-1.0)clean_alpha (license: CC0-1.0)clean_beta (license: CC0-1.0)commons_xiangqi_board_2008 (license: public-domain)commons_xiangqi_board_2008_bw_thin (license: public-domain)dhtmlxq_2014_remake (license: CC0-1.0)latex_xq_remake (license: CC0-1.0)minimal (license: CC0-1.0)minimal_chinese (license: CC0-1.0)minimal_chinese_arabic (license: CC0-1.0)playok_2014_remake (license: CC0-1.0)western_red_wine (license: CC0-1.0)xiexie_2_5_0_remake_minimal (license: CC0-1.0)piece themes (10 available, in alphabetic order):ccbridge_3_0_beta4_default_preview_remake (license: CC0-1.0)commons_xiangqi_pieces_print_2010 (license: FDL-1.2+ / CC-BY-SA-4.0)commons_xiangqi_pieces_print_2010_bw_heavy (license: FDL-1.2+ / CC-BY-SA-4.0)euro_xiangqi_js (license: CC-BY-4.0)euro_xiangqi_js_tricolor (license: CC-BY-4.0)latex_xqlarge_2006_chinese_autotrace (license: non-commercial)latex_xqlarge_2006_chinese_potrace (license: non-commercial)playok_2014_chinese (license: CC0-1.0)playok_2014_chinese_noshadow (license: CC0-1.0)retro_simple (license: CC0-1.0)annotation themes (2 available, in alphabetic order):colors_alpha (license: CC0-1.0)gray_alpha (license: CC0-1.0)xiangqi-board\u2014 Creates Custom Board Themes#xiangqi-board--helpusage: xiangqi-board [-h] [--line-thickness-px FLOAT] [--field-width-px FLOAT][--field-height-px FLOAT] [--border-thickness-px FLOAT][--border-gap-width-px FLOAT][--border-gap-height-px FLOAT] [--cross-width-px FLOAT][--cross-thickness-px FLOAT] [--cross-gap-px FLOAT]SVG_FILE INI_FILEpositional arguments:SVG_FILEINI_FILEoptional arguments:-h, --help show this help message and exit--line-thickness-px FLOATLine thickness of square fields in pixel (default: 1)--field-width-px FLOATWidth of fields in pixel (default: 53)--field-height-px FLOATHeight of fields in pixel (default: 53)--border-thickness-px FLOATLine thickness of border in pixel (default: 2)--border-gap-width-px FLOATWidtn of gap to border in pixel (default: 40)--border-gap-height-px FLOATHeight of gap to border in pixel (default: 40)--cross-width-px FLOATWidth of starting position cross segments in pixel(default: 10)--cross-thickness-px FLOATLine thickness of starting position cross in pixel(default: 1)--cross-gap-px FLOAT Gap to starting position cross in pixel (default: 4)"} +{"package": "xiangshi", "pacakge-description": "\u76f8\u8bc6(Xiangshi)\u4e2d\u6587\u6587\u672c\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u5668Chinese Text Similarity Calculator (English README)\u5728\u7ebf\u8ba1\u7b97\u6587\u672c\u76f8\u4f3c\u5ea6\u76f8\u8bc6\u662f\u4e00\u4e2a\u4fa7\u91cd\u4e8e\u4e2d\u6587\u7684\u6587\u672c\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u5668\uff0c\u5e76\u63d0\u4f9b\uff14\u4e2a\u4f20\u7edf\u76f8\u4f3c\u5ea6\u7b97\u6cd5\uff0c\u5206\u522b\u662f\uff1a\u4f59\u5f26\u76f8\u4f3c\u5ea6\uff0cSimhash\uff0cMinhash\u4ee5\u53caJaccard(\u6770\u5361\u5fb7)\u3002\u4e0b\u8f7d\u4e0e\u5b89\u88c5Pip\u5b89\u88c5\uff1apip3installxiangshi\u56fd\u5185\u8f83\u6162\u7684\u8bdd\u53ef\u4ee5\u4f7f\u7528\u6e05\u534e\u955c\u50cf\uff1apip3install-ihttps://pypi.tuna.tsinghua.edu.cn/simplexiangshi\u65b0\u7248\u672cv4.2.0:\u5220\u9664logging\u5220\u9664file2list\uff0cdict2file\u7b49\u8f85\u52a9\u51fd\u6570\u5220\u9664Ngrams\u5220\u9664Kmeans\u589e\u52a0Jaccard\u76f8\u4f3c\u5ea6\u63d0\u5347\u4f59\u5f26\u3001Simhash\u76f8\u4f3c\u5ea6\u8ba1\u7b97\u901f\u5ea6\u6ce8\u610f\uff1av4.2.0\u6587\u672c\u76f8\u4f3c\u5ea6\u7684\u8ba1\u7b97\u7ed3\u679c\u53ef\u80fd\u548cv4.1.0\u4e0d\u4e00\u6837\uff0c\u56e0\u4e3av4.1.0\u52a0\u6743\u65b9\u5f0f\u4e0d\u540c\u3002v4.2.0\u6587\u672c\u76f8\u4f3c\u5ea6\u7684\u8f93\u5165\u5747\u4e3a\u4e24\u4e2astring\uff0c\u4e14\u4e0d\u4e0ev4.1.0\u53cd\u5411\u517c\u5bb9\u3002v4.2.0\u4e0d\u518d\u652f\u6301\u6587\u672c\u805a\u7c7b\uff08\u5982\u679c\u8fd8\u6709\u4eba\u9700\u8981\u7684\u8bdd\u8bf7\u8054\u7cfb\u6211\uff0c\u6211\u4f1a\u53e6\u5f00\u4e00\u4e2a\u5305\uff09\u4f7f\u7528\u65b9\u6cd5\u8ba1\u7b97\u6587\u672c\u76f8\u4f3c\u5ea6\u4f59\u5f26\u76f8\u4f3c\u5ea6\u793a\u4f8bimportxiangshiasxsxs.cossim(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")Simhash & Minhash & Jaccard\u76f8\u4f3c\u5ea6\u793a\u4f8bimportxiangshiasxs# Simhashxs.simhash(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")# Minhashxs.minhash(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")# Jaccardxs.jaccard(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")\u5176\u5b83\u52a0\u6743\u65b9\u6cd5\u9ed8\u8ba4\u7684\u52a0\u6743\u65b9\u6cd5\u662f\u8ba1\u7b97\u6bcf\u4e2a\u5355\u8bcd\u5728\u6587\u4e2d\u51fa\u73b0\u7684\u6570\u91cf\uff0c\u4ee5\u4e0b\u8fd8\u6709\u5176\u4ed6\u4e24\u79cd\u52a0\u6743\u65b9\u6cd5\u53ef\u4f9b\u9009\u62e9\u3002TFIDFarg=[\"\u897f\u73ed\u7259\u5931\u4e1a\u7387\u521b\u65b0\u9ad8\",\"\u6fb3\u5927\u5229\u4e9a\u5931\u4e1a\u7387\u9ad8\u8fbe5.1%\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u6211\u4ec0\u4e48\u65f6\u5019\u5f00\u901a\u4e86\u82b1\u5457\",\"\u4ece\u8fd9\u4e2a\u89d2\u5ea6\u6765\u770b\uff0c \u6211\u4eec\u4e00\u822c\u8ba4\u4e3a\uff0c\u6293\u4f4f\u4e86\u95ee\u9898\u7684\u5173\u952e\uff0c\u5176\u4ed6\u4e00\u5207\u5219\u4f1a\u8fce\u5203\u800c\u89e3\u3002\"\"\u4ece\u8fd9\u4e2a\u89d2\u5ea6\u6765\u770b\uff0c \u6bcf\u4e2a\u4eba\u90fd\u4e0d\u5f97\u4e0d\u9762\u5bf9\u8fd9\u4e9b\u95ee\u9898\u3002\"]xs.weight=\"TFIDF\"# \u5c06\u52a0\u6743\u65b9\u5f0f\u8bbe\u7f6e\u4e3aTFIDFxs.construct(arg)# \u8f93\u5165TFIDF\u6587\u672c\uff0c\u76f8\u540c\u7684\u6587\u672c\u53ea\u9700\u8c03\u7528\u8fd9\u4e2a\u51fd\u6570\u4e00\u6b21xs.cossim(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")xs.simhash(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")\u6ca1\u6709\u52a0\u6743xs.weight=\"None\"# \u5c06\u52a0\u6743\u65b9\u5f0f\u8bbe\u7f6e\u4e3aNonexs.cossim(\"\u5982\u4f55\u66f4\u6362\u82b1\u5457\u7ed1\u5b9a\u94f6\u884c\u5361\",\"\u82b1\u5457\u66f4\u6539\u7ed1\u5b9a\u94f6\u884c\u5361\")\u4fee\u6539\u9ed8\u8ba4\u51fd\u6570importxiangshiasxs#\u8ba1\u7b97Simhash\u65f6\u53d6\u524d\u591a\u5c11\u7684TFIDF\u503c\u3002\u9ed8\u8ba4\u503c\u4e3a64xs.feature=64#\u8ba1\u7b97Minhash\u65f6\u7b97\u51fa\u591a\u5c11\u4e2a\u54c8\u5e0c\u503c\u3002\u9ed8\u8ba4\u503c\u4e3a16xs.HashNums=16#\u8ba1\u7b97Minhash\u65f6\u7684\u6700\u5927\u54c8\u5e0c\u3002\u9ed8\u8ba4\u503c\u4e3a4294967311xs.prime=4294967311\u76ee\u524d\u72b6\u6001\u6301\u7eed\u7ef4\u62a4\u5e76\u4e14\u6301\u7eed\u5173\u6ce8Issues & Pull Requests\u672a\u6765\u7248\u672c\u5185\u5d4cC\u8bed\u8a00\u63d0\u901f\u4f7f\u7528BERT\u6216\u7c7b\u4f3c\u673a\u5668\u5b66\u4e60\u6a21\u578b\u5b9e\u73b0\u66f4\u7cbe\u786e\u7684\u6587\u672c\u76f8\u4f3c\u5ea6\u5176\u4ed6\u94fe\u63a5\u5728\u7ebf\u8ba1\u7b97\u6587\u672c\u8ba1\u7b97\u5668:https://kiwirafe.comEnglish Version:https://github.com/kiwirafe/xiangshi/blob/master/README(Eng).mdPyPI:https://pypi.org/project/xiangshi/Github:https://github.com/kiwirafe/xiangshi\u4e0b\u8f7d\u6570\u91cf:https://pepy.tech/project/xiangshiGitee\uff08\u4e2d\u56fd\u5f00\u6e90\uff09:https://gitee.com/kiwirafe/xiangshi\u5173\u4e8e\u7b97\u6cd5\u7684\u5176\u4ed6\u94fe\u63a5:https://github.com/kiwirafe/xiangshi/blob/master/Bibliography.md\u76f8\u8bc6\u5bd3\u610f\u540c\u662f\u5929\u6daf\u6ca6\u843d\u4eba\uff0c\u76f8\u9022\u4f55\u5fc5\u66fe\u76f8\u8bc6MIT LicenseCopyright (c) [2021] [kiwirafe]Permission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xian-py", "pacakge-description": "How to installpipinstallxian-pyWalletCreate new walletfromxian_py.walletimportWallet# Create wallet from scratchwallet=Wallet()Create wallet from existing private keyfromxian_py.walletimportWallet# Create wallet from existing private keyprivkey='ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8'wallet=Wallet(privkey)Get private key and public keyfromxian_py.walletimportWalletwallet=Wallet()# Public keyaddress=wallet.public_keyprint(f'address:{address}')# Private keyprivkey=wallet.private_keyprint(f'private key:{privkey}')Sign message with private keyfromxian_py.walletimportWalletwallet=Wallet()# Sign message with private keymessage='I will sign this message'signed=wallet.sign_msg(message)print(f'Signed message:{signed}')XianReplacesome-chain-idwith the chain ID of the network that you want to connect to. A chain ID is an ID that ensures that transactions can only be used in the network for which they were originally generated.Official chain IDs for Xian can be foundhereSubmit contractfromxian_py.walletimportWalletfromxian_py.xianimportXianwallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')xian=Xian('http://:26657','some-chain-id',wallet)# Contract codecode='''token_name = Variable() # Optional@constructdef seed():# Create a token with the information from fixtures/tokenInfotoken_name.set(\"Test Token\")@exportdef set_token_name(new_name: str):# Set the token nametoken_name.set(new_name)'''# Deploy contract on networksubmit=xian.submit_contract('con_new_token',code)print(f'success:{submit[\"success\"]}')print(f'tx_hash:{submit[\"tx_hash\"]}')Approve contract and retrieve approved amountfromxian_py.walletimportWalletfromxian_py.xianimportXianwallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')xian=Xian('http://:26657','some-chain-id',wallet)# Get approved amountapproved=xian.get_approved_amount('con_new_token')print(f'approved:{approved}')# Approve the default amountapprove=xian.approve('con_new_token')print(f'success:{approve[\"success\"]}')print(f'tx_hash:{approve[\"tx_hash\"]}')# Get approved amount againapproved=xian.get_approved_amount('con_new_token')print(f'approved:{approved}')Get token balance for an addressfromxian_py.walletimportWalletfromxian_py.xianimportXianwallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')xian=Xian('http://:26657','some-chain-id',wallet)balance=xian.get_balance('con_new_token')print(f'balance:{balance}')TransactionsSend a transaction - High level usagefromxian_py.walletimportWalletfromxian_py.xianimportXianwallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')xian=Xian('http://:26657','some-chain-id',wallet)send=xian.send_tx(contract='currency',function='transfer',kwargs={'to':'burned','amount':1000,})print(f'success:{send[\"success\"]}')print(f'tx_hash:{send[\"tx_hash\"]}')Send a transaction - Low level usagefromxian_py.walletimportWalletfromxian_py.transactionsimportget_nonce,create_tx,broadcast_txnode_url=\"http://:26657\"wallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')next_nonce=get_nonce(node_url,wallet.public_key)print(f'next nonce:{next_nonce}')tx=create_tx(contract=\"currency\",function=\"transfer\",kwargs={\"to\":\"burned\",\"amount\":100,},nonce=next_nonce,stamps=100,chain_id='some-chain-id',private_key=wallet.private_key)print(f'tx:{tx}')data=broadcast_tx(node_url,tx)print(f'success:{data[\"success\"]}')print(f'tx_hash:{data[\"tx_hash\"]}')Retrieve transaction by hashfromxian_py.walletimportWalletfromxian_py.xianimportXianwallet=Wallet('ed30796abc4ab47a97bfb37359f50a9c362c7b304a4b4ad1b3f5369ecb6f7fd8')xian=Xian('http://:26657','some-chain-id',wallet)tx=xian.get_tx('some tx hash')print(f'transaction:{tx}')"} +{"package": "xianshi", "pacakge-description": "UNKNOWN"} +{"package": "xiao11", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoai", "pacakge-description": "xiaoai\u5c0f\u7231\u97f3\u7bb1\u975e\u5b98\u65b9SDK\u3002"} +{"package": "xiaoaiai", "pacakge-description": "xiaogpthttps://user-images.githubusercontent.com/15976103/226803357-72f87a41-a15b-409e-94f5-e2d262eecd53.mp4Play ChatGPT with Xiaomi AI Speaker\u652f\u6301\u7684 AI \u7c7b\u578bGPT3ChatGPTNew Bing\u4e00\u70b9\u539f\u7406\u4e0d\u7528 root \u4f7f\u7528\u5c0f\u7231\u540c\u5b66\u548c ChatGPT \u4ea4\u4e92\u6298\u817e\u8bb0\u51c6\u5907ChatGPT id\u5c0f\u7231\u97f3\u54cd\u80fd\u6b63\u5e38\u8054\u7f51\u7684\u73af\u5883\u6216 proxypython3.8+\u4f7f\u7528pip install -U --force-reinstall xiaogpt\u53c2\u8003\u6211 fork \u7684MiService\u9879\u76ee README \u5e76\u5728\u672c\u5730 terminal \u8dd1micli list\u62ff\u5230\u4f60\u97f3\u54cd\u7684 DID \u6210\u529f\u522b\u5fd8\u4e86\u8bbe\u7f6e export MI_DID=xxx\u8fd9\u4e2a MI_DID \u7528runxiaogpt --hardware ${your_hardware} --use_chatgpt_apihardware \u4f60\u770b\u5c0f\u7231\u5c41\u80a1\u4e0a\u6709\u578b\u53f7\uff0c\u8f93\u5165\u8fdb\u6765\uff0c\u5982\u679c\u5728\u5c41\u80a1\u4e0a\u627e\u4e0d\u5230\u6216\u8005\u578b\u53f7\u4e0d\u5bf9\uff0c\u53ef\u4ee5\u7528micli mina\u627e\u5230\u578b\u53f7\u8dd1\u8d77\u6765\u4e4b\u540e\u5c31\u53ef\u4ee5\u95ee\u5c0f\u7231\u540c\u5b66\u95ee\u9898\u4e86\uff0c\u201c\u5e2e\u6211\"\u5f00\u5934\u7684\u95ee\u9898\uff0c\u4f1a\u53d1\u9001\u4e00\u4efd\u7ed9 ChatGPT \u7136\u540e\u5c0f\u7231\u540c\u5b66\u7528 tts \u56de\u7b54\u5982\u679c\u4e0a\u9762\u4e0d\u53ef\u7528\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u7528\u624b\u673a\u6293\u5305\uff0chttps://userprofile.mina.mi.com/device_profile/v2/conversation\u627e\u5230 cookie \u5229\u7528--cookie '${cookie}'cookie \u522b\u5fd8\u4e86\u7528\u5355\u5f15\u53f7\u5305\u88f9\u9ed8\u8ba4\u7528\u76ee\u524d ubus, \u5982\u679c\u4f60\u7684\u8bbe\u5907\u4e0d\u652f\u6301 ubus \u53ef\u4ee5\u4f7f\u7528--use_command\u6765\u4f7f\u7528 command \u6765 tts\u4f7f\u7528--mute_xiaoai\u9009\u9879\uff0c\u53ef\u4ee5\u5feb\u901f\u505c\u6389\u5c0f\u7231\u7684\u56de\u7b54\u4f7f\u7528--account ${account} --password ${password}\u5982\u679c\u6709\u80fd\u529b\u53ef\u4ee5\u81ea\u884c\u66ff\u6362\u5524\u9192\u8bcd\uff0c\u4e5f\u53ef\u4ee5\u53bb\u6389\u5524\u9192\u8bcd\u4f7f\u7528--use_chatgpt_api\u7684 api \u90a3\u6837\u53ef\u4ee5\u66f4\u6d41\u7545\u7684\u5bf9\u8bdd\uff0c\u901f\u5ea6\u7279\u522b\u5feb\uff0c\u8fbe\u5230\u4e86\u5bf9\u8bdd\u7684\u4f53\u9a8c,openai api, \u547d\u4ee4--use_chatgpt_api\u4f7f\u7528 gpt-3 \u7684 api \u90a3\u6837\u53ef\u4ee5\u66f4\u6d41\u7545\u7684\u5bf9\u8bdd\uff0c\u901f\u5ea6\u5feb, \u8bf7 google \u5982\u4f55\u7528openai api\u547d\u4ee4 --use_gpt3\u5982\u679c\u4f60\u9047\u5230\u4e86\u5899\u9700\u8981\u7528 Cloudflare Workers \u66ff\u6362 api_base \u8bf7\u4f7f\u7528--api_base ${url}\u6765\u66ff\u6362\u3002\u8bf7\u6ce8\u610f\uff0c\u6b64\u5904\u4f60\u8f93\u5165\u7684api\u5e94\u8be5\u662f'https://xxxx/v1'\u7684\u5b57\u6837\uff0c\u57df\u540d\u9700\u8981\u7528\u5f15\u53f7\u5305\u88f9\u53ef\u4ee5\u8ddf\u5c0f\u7231\u8bf4\u5f00\u59cb\u6301\u7eed\u5bf9\u8bdd\u81ea\u52a8\u8fdb\u5165\u6301\u7eed\u5bf9\u8bdd\u72b6\u6001\uff0c\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u72b6\u6001\u3002\u53ef\u4ee5\u4f7f\u7528--enable_edge_tts\u6765\u83b7\u53d6\u66f4\u597d\u7684 tts \u80fd\u529be.g.exportOPENAI_API_KEY=${your_api_key}xiaogpt--hardwareLX06--use_chatgpt_api# orxiaogpt--hardwareLX06--cookie${cookie}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3\u76f4\u63a5\u8f93\u5165\u8d26\u53f7\u5bc6\u7801xiaogpt--hardwareLX06--account${your_xiaomi_account}--password${your_password}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3 mute \u5c0f\u7c73\u7684\u56de\u7b54xiaogpt--hardwareLX06--mute_xiaoai--use_chatgpt_api# \u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94xiaogpt--hardwareLX06--mute_xiaoai--stream# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 gpt3 aiexportOPENAI_API_KEY=${your_api_key}xiaogpt--hardwareLX06--mute_xiaoai--use_gpt3# \u5982\u679c\u4f60\u60f3\u7528 edge-ttsxiaogpt--hardwareLX06--cookie${cookie}--use_chatgpt_api--enable_edge_tts\u4f7f\u7528 git clone \u8fd0\u884cexportOPENAI_API_KEY=${your_api_key}python3loznxiaoai.py--hardwareLX06# orpython3loznxiaoai.py--hardwareLX06--cookie${cookie}# \u5982\u679c\u4f60\u60f3\u76f4\u63a5\u8f93\u5165\u8d26\u53f7\u5bc6\u7801python3loznxiaoai.py--hardwareLX06--account${your_xiaomi_account}--password${your_password}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3 mute \u5c0f\u7c73\u7684\u56de\u7b54python3loznxiaoai.py--hardwareLX06--mute_xiaoai# \u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94python3loznxiaoai.py--hardwareLX06--mute_xiaoai--stream# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 gpt3 aiexportOPENAI_API_KEY=${your_api_key}python3loznxiaoai.py--hardwareLX06--mute_xiaoai--use_gpt3config.json\u5982\u679c\u60f3\u901a\u8fc7\u5355\u4e00\u914d\u7f6e\u6587\u4ef6\u542f\u52a8\u4e5f\u662f\u53ef\u4ee5\u7684, \u53ef\u4ee5\u901a\u8fc7--config\u53c2\u6570\u6307\u5b9a\u914d\u7f6e\u6587\u4ef6, config \u6587\u4ef6\u5fc5\u987b\u662f\u5408\u6cd5\u7684 JSON \u683c\u5f0f\n\u53c2\u6570\u4f18\u5148\u7ea7cli args > default > configpython3loznxiaoai.py--configxiao_config.json# orxiaogpt--configxiao_config.json\u6216\u8005cpxiao_config.json.examplexiao_config.json\npython3loznxiaoai.py\u82e5\u8981\u6307\u5b9a OpenAI \u7684\u6a21\u578b\u53c2\u6570\uff0c\u5982 model, temporature, top_p, \u8bf7\u5728config.json\u4e2d\u6307\u5b9a\uff1a{...\"gpt_options\":{\"temperature\":0.9,\"top_p\":0.9,}}\u5177\u4f53\u53c2\u6570\u4f5c\u7528\u8bf7\u53c2\u8003Open AI API \u6587\u6863\u3002\u914d\u7f6e\u9879\u8bf4\u660e\u53c2\u6570\u8bf4\u660e\u9ed8\u8ba4\u503chardware\u8bbe\u5907\u578b\u53f7account\u5c0f\u7231\u8d26\u6237password\u5c0f\u7231\u8d26\u6237\u5bc6\u7801openai_keyopenai\u7684apikeycookie\u5c0f\u7231\u8d26\u6237cookie \uff08\u5982\u679c\u7528\u4e0a\u9762\u5bc6\u7801\u767b\u5f55\u53ef\u4ee5\u4e0d\u586b\uff09mi_did\u8bbe\u5907diduse_command\u4f7f\u7528 MI command \u4e0e\u5c0f\u7231\u4ea4\u4e92falsemute_xiaoai\u5feb\u901f\u505c\u6389\u5c0f\u7231\u81ea\u5df1\u7684\u56de\u7b54trueverbose\u662f\u5426\u6253\u5370\u8be6\u7ec6\u65e5\u5fd7falsebot\u4f7f\u7528\u7684 bot \u7c7b\u578b\uff0c\u76ee\u524d\u652f\u6301gpt3,chatgptapi\u548cnewbingchatgptapienable_edge_tts\u4f7f\u7528Edge TTSfalseedge_tts_voiceEdge TTS \u7684\u55d3\u97f3zh-CN-XiaoxiaoNeuralprompt\u81ea\u5b9a\u4e49prompt\u8bf7\u7528100\u5b57\u4ee5\u5185\u56de\u7b54keyword\u81ea\u5b9a\u4e49\u8bf7\u6c42\u8bcd\u5217\u8868[\"\u8bf7\u95ee\"]change_prompt_keyword\u66f4\u6539\u63d0\u793a\u8bcd\u89e6\u53d1\u5217\u8868[\"\u66f4\u6539\u63d0\u793a\u8bcd\"]start_conversation\u5f00\u59cb\u6301\u7eed\u5bf9\u8bdd\u5173\u952e\u8bcd\u5f00\u59cb\u6301\u7eed\u5bf9\u8bddend_conversation\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u5173\u952e\u8bcd\u7ed3\u675f\u6301\u7eed\u5bf9\u8bddstream\u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94falseproxy\u652f\u6301 HTTP \u4ee3\u7406\uff0c\u4f20\u5165 http proxy URL\"\"gpt_optionsOpenAI API \u7684\u53c2\u6570\u5b57\u5178{}bing_cookie_pathNewBing\u4f7f\u7528\u7684cookie\u8def\u5f84\uff0c\u53c2\u8003\u8fd9\u91cc\u83b7\u53d6\u4e5f\u53ef\u901a\u8fc7\u73af\u5883\u53d8\u91cfCOOKIE_FILE\u8bbe\u7f6ebing_cookiesNewBing\u4f7f\u7528\u7684cookie\u5b57\u5178\uff0c\u53c2\u8003\u8fd9\u91cc\u83b7\u53d6\u6ce8\u610f\u8bf7\u5f00\u542f\u5c0f\u7231\u540c\u5b66\u7684\u84dd\u7259\u5982\u679c\u8981\u66f4\u6539\u63d0\u793a\u8bcd\u548c PROMPT \u5728\u4ee3\u7801\u6700\u4e0a\u9762\u81ea\u884c\u66f4\u6539\u76ee\u524d\u5df2\u77e5 LX04 \u548c L05B L05C \u53ef\u80fd\u9700\u8981\u4f7f\u7528--use_commandQA\u7528\u7834\u89e3\u4e48\uff1f\u4e0d\u7528\u4f60\u505a\u8fd9\u73a9\u610f\u4e5f\u6ca1\u7528\u554a\uff1f\u786e\u5b9e\u3002\u3002\u3002\u4f46\u662f\u633a\u597d\u73a9\u7684\uff0c\u6709\u7528\u5bf9\u4f60\u6765\u8bf4\u6ca1\u7528\uff0c\u5bf9\u6211\u4eec\u6765\u8bf4\u4e0d\u4e00\u5b9a\u5440\u60f3\u628a\u5b83\u53d8\u5f97\u66f4\u597d\uff1fPR Issue always welcome.\u8fd8\u6709\u95ee\u9898\uff1f\u63d0 Issuse \u54c8\u54c8\u89c6\u9891\u6559\u7a0bhttps://www.youtube.com/watch?v=K4YA8YwzOOADocker\u5e38\u89c4\u7528\u6cd5X86/ARM Docker Image:yihong0618/xiaogptdockerrun-eOPENAI_API_KEY=yihong0618/xiaogpt<\u547d\u4ee4\u884c\u53c2\u6570>\u5982dockerrun-eOPENAI_API_KEY=yihong0618/xiaogpt--account=--password=--hardware=--use_chatgpt_api\u4f7f\u7528\u914d\u7f6e\u6587\u4ef6xiaogpt\u7684\u914d\u7f6e\u6587\u4ef6\u53ef\u901a\u8fc7\u6307\u5b9avolume /config\uff0c\u4ee5\u53ca\u6307\u5b9a\u53c2\u6570--config\u6765\u5904\u7406\uff0c\u5982dockerrun-v:/configyihong0618/xiaogpt--config=/config/config.json\u672c\u5730\u7f16\u8bd1Docker Imagedockerbuild-txiaogpt.\u5982\u679c\u9700\u8981\u5728Apple M1/M2\u4e0a\u7f16\u8bd1x86dockerbuildxbuild--platform=linux/amd64-txiaogpt-x86.Add edge-ttsedge-tts\u63d0\u4f9b\u4e86\u7c7b\u4f3c\u5fae\u8f6ftts\u7684\u80fd\u529bhttps://github.com/rany2/edge-ttsUsage\u4f60\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570enable_edge_tts, \u6765\u542f\u7528\u5b83{\"enable_edge_tts\":true,\"edge_tts_voice\":\"zh-CN-XiaoxiaoNeural\"}\u67e5\u770b\u66f4\u591a\u8bed\u8a00\u652f\u6301, \u4ece\u4e2d\u9009\u62e9\u4e00\u4e2aedge-tts--list-voices\u5728\u5bb9\u5668\u4e2d\u4f7f\u7528edge-tts\u7531\u4e8e Edge TTS \u542f\u52a8\u4e86\u4e00\u4e2a\u672c\u5730\u7684 HTTP \u670d\u52a1\uff0c\u6240\u4ee5\u9700\u8981\u5c06\u5bb9\u5668\u7684\u7aef\u53e3\u6620\u5c04\u5230\u5bbf\u4e3b\u673a\u4e0a\uff0c\u5e76\u4e14\u6307\u5b9a\u672c\u5730\u673a\u5668\u7684 hostname:dockerrun-v:/configyihong0618/xiaogpt-p9527:9527-eXIAOGPT_HOSTNAME=--config=/config/config.json\u6ce8\u610f\u7aef\u53e3\u5fc5\u987b\u6620\u5c04\u4e3a\u4e0e\u5bb9\u5668\u5185\u4e00\u81f4\uff0cXIAOGPT_HOSTNAME \u9700\u8981\u8bbe\u7f6e\u4e3a\u5bbf\u4e3b\u673a\u7684 IP \u5730\u5740\uff0c\u5426\u5219\u5c0f\u7231\u65e0\u6cd5\u6b63\u5e38\u64ad\u653e\u8bed\u97f3\u3002\u63a8\u8350\u7684 forkMIGPT-> \u57fa\u4e8e API \u6d41\u5f0f\u5bf9\u8bdd\u7684\u4f4e\u5ef6\u8fdf\u7248MIGPTXiaoBot-> Go\u8bed\u8a00\u7248\u672c\u7684Fork, \u5e26\u652f\u6301\u4e0d\u540c\u5e73\u53f0\u7684UI\u611f\u8c22xiaomiPDM@Yonsm\u7684MiService@pjq\u7ed9\u4e86\u8fd9\u4e2a\u9879\u76ee\u975e\u5e38\u591a\u7684\u5e2e\u52a9@frostming\u91cd\u6784\u4e86\u4e00\u4e9b\u4ee3\u7801\uff0c\u652f\u6301\u4e86\u6301\u7eed\u4f1a\u8bdd\u529f\u80fd\u8d5e\u8d4f\u8c22\u8c22\u5c31\u591f\u4e86\u7f16\u8bd1\u53d1\u5e03pip install --upgrade build twine\npython -m build\ntwine upload dist/*\u53c2\u8003https://blog.csdn.net/u010214511/article/details/126909523"} +{"package": "xiaoaitts", "pacakge-description": "xiaoaitts\u5c0f\u7231\u97f3\u7bb1\u81ea\u5b9a\u4e49\u6587\u672c\u6717\u8bfb\u3002\u4e0d\u6b62\u662f TTS\u5b89\u88c5pipinstallxiaoaitts\u4f7f\u7528fromxiaoaittsimportXiaoAi# \u8f93\u5165\u5c0f\u7c73\u8d26\u6237\u540d\uff0c\u5bc6\u7801client=XiaoAi('fish','123456')# \u6717\u8bfb\u6587\u672cclient.say('\u4f60\u597d\uff0c\u6211\u662f\u5c0f\u7231')APIClass: XiaoAiXiaoAi(user, password)username\u5c0f\u7c73\u8d26\u6237\u7528\u6237\u540dpassword\u8d26\u6237\u5bc6\u7801\u4f7f\u7528\u5c0f\u7c73\u8d26\u6237\u767b\u5f55\u5c0f\u7231\u97f3\u7bb1instanceXiaoAi \u5b9e\u4f8b\u5bf9\u8c61say(text)text\u6587\u672c\u4fe1\u606f\u6717\u8bfb\u6307\u5b9a\u6587\u672c\uff0c\u8fd4\u56de\u63a5\u53e3\u8c03\u7528\u7ed3\u679cclient.say('\u4f60\u597d\uff0c\u6211\u662f\u5c0f\u7231')get_device(name=None)name\u8bbe\u5907\u540d\u79f0(\u522b\u540d)Returns: \u8bbe\u5907\u4fe1\u606f\u83b7\u53d6\u5728\u7ebf\u8bbe\u5907\u5217\u8868# \u83b7\u53d6\u6240\u6709\u5728\u7ebf\u8bbe\u5907online_devices=client.get_device()# \u83b7\u53d6\u5355\u4e2a\u8bbe\u5907\uff0c\u672a\u627e\u5230\u65f6\u8fd4\u56de nullroom_device=client.get_device('\u5367\u5ba4\u5c0f\u7231')use_device(device_id)device_id\u8bbe\u5907id\u5207\u6362\u6307\u5b9a\u8bbe\u5907\u3002xiaomitts\u5b9e\u4f8b\u5316\u540e\u9ed8\u8ba4\u4f7f\u7528get_device()\u65b9\u6cd5\u8fd4\u56de\u7684\u7b2c\u4e00\u4e2a\u8bbe\u5907\uff0c\u53ef\u4f7f\u7528\u6b64\u65b9\u6cd5\u5207\u6362\u4e3a\u6307\u5b9a\u8bbe\u5907\u3002room_device=client.get_device('\u5367\u5ba4\u5c0f\u7231')# \u4f7f\u7528\u201c\u5367\u5ba4\u5c0f\u7231\u201dclient.use_device(room_device.get('deviceID'))client.say('\u4f60\u597d\uff0c\u6211\u662f\u5367\u5ba4\u7684\u5c0f\u7231')test()\u6d4b\u8bd5\u8fde\u901a\u6027client.test()\u5a92\u4f53\u63a7\u5236set_volume(volume)volume\u97f3\u91cf\u503c\u8bbe\u7f6e\u97f3\u91cfclient.set_volume(30)get_volume()Returns: \u97f3\u91cf\u503c\u83b7\u53d6\u97f3\u91cfvolume=client.get_volume()volume_up()\u8c03\u9ad8\u97f3\u91cf\uff0c\u5e45\u5ea6 5volume_down()\u8c03\u4f4e\u97f3\u91cf\uff0c\u5e45\u5ea6 5get_status()Returns: \u72b6\u6001\u4fe1\u606f\u83b7\u53d6\u8bbe\u5907\u8fd0\u884c\u72b6\u6001play()\u7ee7\u7eed\u64ad\u653epause()\u6682\u505c\u64ad\u653eprev()\u64ad\u653e\u4e0a\u4e00\u66f2next()\u64ad\u653e\u4e0b\u4e00\u66f2set_play_loop(type=1)type0-\u5355\u66f2\u5faa\u73af 1-\u5217\u8868\u5faa\u73af 3-\u5217\u8868\u968f\u673a\u8bbe\u7f6e\u5faa\u73af\u64ad\u653eget_song_info(song_id)song_id\u6b4c\u66f2idReturns: \u6b4c\u66f2\u4fe1\u606f\u67e5\u8be2\u6b4c\u66f2\u4fe1\u606fsong_info=client.get_song_info('7519904358300484678')get_my_playlist(list_id=None)list_id\u6b4c\u5355idReturns: \u6b4c\u66f2\u4fe1\u606f\u83b7\u53d6\u7528\u6237\u81ea\u5efa\u6b4c\u5355\uff0c\u5f53\u6307\u5b9alist_id\u65f6\uff0c\u5c06\u8fd4\u56de\u76ee\u6807\u6b4c\u5355\u5185\u7684\u6b4c\u66f2\u5217\u8868# \u83b7\u53d6\u6b4c\u5355\u5217\u8868my_playlist=client.get_my_playlist()# \u83b7\u53d6\u6b4c\u5355\u5185\u7684\u6b4c\u66f2\u5217\u8868song_list=client.get_my_playlist('337361232731772372')\u53c2\u8003\u94fe\u63a5https://github.com/Yonsmhttps://github.com/vv314/xiaoai-tts"} +{"package": "xiao-asgi", "pacakge-description": "xiao asgixiao asgi is a smallASGIframework that can be used to create ASGI applications.\nIt is designed to be small in size, simple to use and have few dependencies.\nHTTP and WebSockets are both supported.Installationxiao asgi can be installed into a Python environment by runningpip install xiao-asgi.Supported Python versionsxiao asgi has been tested with the following versions of Python:3.10.03.9.7DocumentationDocstrings are included in the project and more information can be found at theWikitab (work in progress).DiscussionsHead over to theDiscussionstab to start a conversation on xiao asgi.ContributionsThis project uses theGitHub flowbranching strategy.Licensexiao asgi is open-sourced software licensed under theMITlicense."} +{"package": "xiaobaiapi", "pacakge-description": "xiaobaiapi\u4ecb\u7ecd\u8ba9\u63a5\u53e3\u6d4b\u8bd5\u8d77\u6765\u66f4\u7b80\u5355\u3001\u4eba\u6027\u5316\u3001\u66f4\u597d\u73a9\u516c\u4f17\u53f7\uff1a\u5c0f\u767d\u79d1\u6280\u4e4b\u7a97\u63a5\u53e3\u6d4b\u8bd5\u9700\u8981\u63a5\u53e3\u7684\u75db\u70b9\uff1a\u63a5\u53e3\u6587\u6863\u7684\u5bfc\u5165\uff1aswagger\u3001har\u3001curl\u63a5\u53e3\u4fe1\u606f\u5934\uff1a\u652f\u6301\u957f\u5b57\u7b26\u4e32\u63a5\u53e3\u65ad\u8a00\uff1a\u652f\u6301jsonpath\u4e0e\u6b63\u5219\u65ad\u8a00\u63a5\u53e3\u6570\u636e\uff1a\u652f\u6301jsonpath\u63d0\u53d6\u6570\u636e\u8f6f\u4ef6\u67b6\u6784python3.* + requests + jmespath + pytest + pytest-HTML\u5b89\u88c5\u6559\u7a0b\u66f4\u65b0\u4e0b\u8f7d\u6e90pip config set global.index-url https://pypi.douban.com/simple\u5b89\u88c5xiaobaiapipip install -U xiaobaiapi\u4f7f\u7528\u8bf4\u660efrom xiaobaiapi.xiaobaiapi import RequestClient\n\n\n# \u65ad\u8a00\u7684\u6848\u4f8b\nRequestClient(method='GET', url='http://127.0.0.1:8000', assertExpression='code', assertValue=200)\n\n# \u63d0\u53d6\u5668\u7684\u6848\u4f8b\uff0c\u63d0\u53d6\u7684\u503c\u5b58\u50a8\u5728r.variable\u5bf9\u8c61\u4e2d\nr = RequestClient(method='GET', url='http://127.0.0.1:8000/api/gettoken', extractorExpression='data.token', extractorVariable='token')\nprint(r.variable)\u65e5\u5fd7\u7248\u672c\u4fe1\u606f0.1\u5b8c\u6210\u5355\u4e2a\u63a5\u53e3\u65ad\u8a00\u53ca\u63d0\u53d6\u56680.1.1fix"} +{"package": "xiaobaiauto", "pacakge-description": "xiaobaiauto\u4ecb\u7ecd\u7b80\u5316\u73b0\u6709Selenium\u3001Requests\u7b49\u6846\u67b6\u5bf9\u4e8e\u9875\u9762\u53ca\u63a5\u53e3\u7684\u64cd\u4f5c\uff0c\u4e5f\u6269\u5c55\u4e86\u65e5\u5fd7\u641c\u96c6\u3001\u62a5\u544a\u751f\u6210\u3001\n\u90ae\u4ef6\u53d1\u9001\u7b49\u529f\u80fd\u7248\u672c\u8bf4\u660e\u7248\u672c\uff1a \u529f\u80fd\uff1a \u5b9e\u73b0\uff1a\n1.* \u53ea\u652f\u6301Web\u7aef \u221a\n2.* \u652f\u6301Web+API\u7aef \u221a\n3.* \u652f\u6301Web+API+Mock \u00d7\n4.* \u652f\u6301Web+API+Mock+APP \u00d7\n5.* \u652f\u6301Web+API+Mock+APP+Pref \u00d7\n\u5907\u6ce8\uff1a\u8ba1\u5212\u5c06mock\u72ec\u7acb\u6210\u5b50\u9879\u76ee\u8f6f\u4ef6\u67b6\u6784\u96c6\u6210\u4e86Selenium\u3001SMTP\u3001HTMLTestRunner\u3001logging\u3001Reuqests\u7b49\u6a21\u5757\u5b89\u88c5\u6559\u7a0bpip install xiaobaiauto\nor\npip install xiaobaiauto==\u7248\u672c\u53f7\nor\npip install -U xiaobaiauto # \u66f4\u65b0\u5230\u6700\u65b0\u7248\nor\npip install xiaobaiauto -i https://pypi.doubanio.com/simple #\u7f51\u901f\u4e00\u822c\u7684\u4f7f\u7528\u672c\u547d\u4ee4\n\n***********************************\u6ce8\u610f******************************************\n\u6b63\u786e\u5b89\u88c5\u4e4b\u540e\u82e5\u4e0d\u80fd\u6b63\u5e38\u5bfc\u5165\u672c\u5e93\uff0c\u8bf7\u5c06auto.*.pyd\u4e0eHTMLTestRunner.py\u590d\u5236\u5230\u81ea\u5df1\u7684\u9879\u76ee\u5305\u4e2d\n*********************************************************************************\u4f7f\u7528\u4ee3\u7801\u4e4b\u524d\u8bf7\u786e\u4fdd\u60a8\u7684\u7535\u8111\u4e2d\u5df2\u7ecf\u5b89\u88c5\u597d\u6d4f\u89c8\u5668\u53ca\u5bf9\u5e94\u7684\u9a71\u52a8\u5185\u5bb9chrome\u4e0echromdriver\u9a71\u52a8\u4e4b\u95f4\u5b58\u5728\u4e0d\u517c\u5bb9\u95ee\u9898\uff0c\u6240\u4ee5\u6700\u597d\u90fd\u4e0b\u8f7d\u6700\u65b0\u7248\u672c\u4e3a\u6700\u4f73\u6548\u679c\n\u9ed8\u8ba4\u4f1a\u81ea\u52a8\u5b89\u88c5\uff0c\u4e0b\u8f7d\u9ed8\u8ba4\u4e3a\u4e0e\u5f53\u524d\u5b89\u88c5chrome\u7248\u672c\u76f8\u5339\u914d\u7684\u9a71\u52a8\u6587\u4ef6\uff0c\u9ed8\u8ba4\u4e0b\u8f7d\u5230\u672c\u5730\uff0c\n\u82e5\u81ea\u5f53\u5b89\u88c5\u5931\u8d25\u53ef\u80fd\u662f\u5199\u5165\u6587\u4ef6\u6743\u9650\u53d7\u9650\uff08\u4e0b\u65b9\u4e3a\u9a71\u52a8\u4e0b\u8f7d\u5730\u5740\uff09chromedriver\u4e0b\u8f7d\u221a\u57fa\u4e8eautogenertor\u4ee3\u7801\u751f\u6210\u5668\u7684\u4f7f\u7528\u67e5\u770b\u5e2e\u52a9\u6587\u6863(\u5305\u542b\u751f\u6210\u5668\u5173\u952e\u8bcd)autogenertor -h\u521b\u5efaYAML\u683c\u5f0f\u7684\u7528\u4f8b\u6587\u4ef6autogenertor -t \u6a21\u677f\u540d\u79f0.yaml\u751f\u6210\u5355\u5143\u6d4b\u8bd5\u7528\u4f8b\u6587\u4ef6autogenertor -y yaml\u7528\u4f8b\u6587\u4ef6 -c \u4ee3\u7801\u6587\u4ef6\u540d.py\u6216\u8005autogenertorTestCase\u6587\u4ef6\u5b9e\u4f8b\uff08Pycharm\u793e\u533a\u7248 2019.3\uff0cPython3.8+\uff09import unittest\nfrom xiaobaiauto.auto import pageObject, Report, log, EmailHandler, Api, Key\n# from auto import pageObject, Report, log, EmailHandler, Api, Key # \u5e93\u6587\u4ef6\u590d\u5236\u5230\u672c\u76ee\u5f55\u4e0b\u4f7f\u7528\u672c\u884c\u4ee3\u7801\nclass MyTestCase(unittest.TestCase):\n def setUp(self):\n \"\"\"\n \u521d\u59cb\u5316\u65e5\u5fd7\n :return:\n \"\"\"\n self.logger = log()\n self.client = Api()\n self.page = pageObject()\n self.page.init(is_max=True)\n\n def test_api_xxx(self):\n headers = {'content-type': 'application/json'}\n json = {'type': 1, 'orderno': 'abcdef'}\n path = 'http://127.0.0.1:8080/api/v/1.0/'\n try:\n self.client.api(\n method='GET',\n url=path,\n json=json,\n headers=headers,\n assertText=\"\u5305\u542b\u7684\u9884\u671f\u7ed3\u679c\"\n ).json()\n self.logger.info('xxx\u63a5\u53e3\u8bf7\u6c42\u6210\u529f')\n except:\n self.logger.error('xxx\u63a5\u53e3\u8bf7\u6c42\u5931\u8d25')\n # self.logger.debug('\u8c03\u8bd5\u65e5\u5fd7\u4fe1\u606f')\n # self.logger.warning('\u8b66\u544a\u65e5\u5fd7\u4fe1\u606f')\n # self.logger.error('\u9519\u8bef\u65e5\u5fd7\u4fe1\u606f')\n\n def test_web_12306(self):\n # \u901a\u8fc7self.page \u8c03\u7528\u96c6\u6210\u65b9\u6cd5\n self.page.get(url='https://kyfw.12306.cn/otn/leftTicket/init?linktypeid=dc&fs=%E4%B8%8A%E6%B5%B7,SHH&ts=%E9%83%91%E5%B7%9E,ZZF&date=2020-02-02&flag=N,N,Y')\n #self.page.add_cookie(cookie_dict={'name': '', 'value': ''})\n #self.page.add_cookie(cookie_str='name=xiaobai; password=123456')\n chufa = self.page.xpath('//*[@id=\"fromStationText\"]')\n chufa.clear()\n chufa.send_keys('\u4e0a\u6d77')\n chufa.send_keys(Keys.ENTER)\n\n def tearDown(self):\n pass\n\nif __name__ == '__main__':\n report_file_name = 'testReport.html'\n suite = unittest.TestSuite()\n # \u6dfb\u52a0\u9700\u8981\u6267\u884c\u7684\u6d4b\u8bd5\u7528\u4f8b\n suite.addTest(MyTestCase('test_web_12306'))\n #suite.addTest(MyTestCase('test_api_xxx')) # \u4e0d\u8fd0\u884c\u5c31\u6ce8\u91ca\u6389\n fp = open(report_file_name, 'wb')\n # \u751f\u6210\u62a5\u544a\n runner = Report(\n stream=fp,\n title='\u6d4b\u8bd5',\n description='\u5907\u6ce8\u4fe1\u606f',\n tester='Tser'\n )\n runner.run(suite)\n fp.close()\n # \u5c06\u6d4b\u8bd5\u62a5\u544a\u53d1\u9001\u6307\u5b9a\u90ae\u4ef6<\u6570\u636e\u52a1\u5fc5\u4fee\u6539>\u5efa\u8bae\u4f7f\u7528QQ\u90ae\u7bb1\uff08port\u53c2\u6570\u9ed8\u8ba4\u4f7f\u7528SSL\u7aef\u53e3\uff09\n email = EmailHandler(smtp='smtp.qq.com', port=465, sender_name='qq\u53f7', sender_passwd='\u90ae\u7bb1\u6388\u6743\u7801')\n email.sendemail(\n _to=['1@qq.com', '2@qq.com'],\n _cc=['admin@163.com', 'leader@gmail.com'],\n title='\u90ae\u4ef6\u6807\u9898',\n email_content='\u90ae\u7bb1\u5185\u5bb9',\n _type='html',\n filename=[report_file_name]\n )\u8fd0\u884c\u811a\u672c\u65b9\u5f0f\u4e00 \uff08python\u547d\u4ee4\u8fd0\u884c\uff09\nstep 1 : \u6253\u5f00cmd\nstep 2 : cd \u811a\u672c\u76ee\u5f55\nstep 3 : python \u7528\u4f8b\u811a\u672c\u540d.py\n\n\u65b9\u5f0f\u4e8c \uff08\u5b9a\u65f6\u5668\u8fd0\u884c\u811a\u672c\uff09\n- \u67e5\u770b\u547d\u4ee4\u5e2e\u52a9\u6587\u6863\nautorunner -h\n\n- \u901a\u8fc7\u5b9a\u65f6\u5668\u5faa\u73af\u8fd0\u884c\u6307\u5b9a\u811a\u672c\nautorunner -t \"0 6,22 0 0 1-5\" -d \"D:\\\\Cases\" -s 1 -j \"a.py,b.py\"\n\u6216\n- \u8fd0\u884c\u5f53\u524d\u76ee\u5f55\u4e0b\u7684\u6240\u6709py\u811a\u672c\nautorunner -t \"0 6,22 0 0 1-5\" \n\n- \u6ce8\u610f\n\u65e5\u5fd7\u4e0e\u6d4b\u8bd5\u62a5\u544a\u6587\u4ef6\u9ed8\u8ba4\u5728\u547d\u4ee4\u6267\u884c\u6240\u5728\u7684\u76ee\u5f55\u4e0b\u63d0\u793aQQ\u90ae\u7bb1\u6216\u8005\u5176\u5b83\u4f01\u4e1a\u90ae\u7bb1\u5fc5\u987b\u63d0\u524d\u5f00\u542fSMTP\u670d\u52a1\u90e8\u5206\u90ae\u7bb1\u5bf9\u9891\u53d1\u53d1\u9001\u90ae\u4ef6\u8fdb\u884c\u62e6\u622a\uff0c\u6240\u4ee5\u5927\u5bb6\u5728\u4f7f\u7528\u90ae\u7bb1\u53d1\u9001\u6d88\u606f\u65f6\u8bf7\u52ff\u9891\u7e41\u5c1d\u8bd5\u70b9\u51fb\u8fd9\u91cc\u4e86\u89e3QQ\u90ae\u7bb1\u5982\u4f55\u5f00\u542fSMTP\u670d\u52a1\u66f4\u65b0\u65e5\u5fd7V2.4.0\n\u4fee\u6539\u9644\u4ef6\u4e3a\u4e2d\u6587\u540d\u79f0\u7684BUG\uff0c\u65b0\u589e\u5b9a\u65f6\u5668\u529f\u80fdautorunner\nV2.3.8\n\u4fee\u590dBUG\nV2.3.7\n\u65b0\u589e\u4e86xiaobaiauto\u4ee3\u7801\u751f\u6210\u5668autogenertor\u57fa\u4e8eyaml\u683c\u5f0f\u6587\u4ef6,\u53ef\u4ee5\u547d\u4ee4\u884c\u8fd0\u884c\uff1aautogenertor -h\nV2.3.6\n\u66f4\u65b02.3.4\u4e2d\u4e0b\u8f7d\u6587\u4ef6\u7684bug\uff08chrome\u7248\u672c\u4e0d\u5339\u914d\u65f6\u811a\u672c\u8fd0\u884c\u51fa\u9519\uff09\nV2.3.4\n\u66f4\u65b0chromedriver.exe\u4e0b\u8f7d\u65b9\u5f0f\uff0c\u90e8\u5206\u5931\u8d25\u539f\u56e0\u4e3a\u7f51\u7edc\u95ee\u9898\nV2.3.3\n\u66f4\u65b0\u81f3Py3.8\u8fdb\u884c\u7f16\u8bd1\uff0c\u6709\u6548\u89e3\u51b3\u9ad8\u7248\u672c\u4e0d\u80fd\u8c03\u7528\u5e93\u7684\u95ee\u9898\nV2.3.1\nadd_cookie()\u65b9\u6cd5\u6dfb\u52a0\u4e86cookie_str\u53c2\u6570\uff0c\u5141\u8bb8\u4f7f\u7528\u4eceF12\u76f4\u63a5\u590d\u5236\u7684cookie\u5b57\u7b26\u4e32\n\u76f4\u63a5\u8d4b\u503c\u5373\u53ef\uff0ccookie_dict\u4e0ecookie_str\u4e24\u4e2a\u53c2\u6570\u53ea\u9700\u8981\u4e00\u4e2a\u8d4b\u503c\u5373\u53ef\nV2.2.1\n\u56e02.0.0\u7248\u672c\u4e0d\u80fd\u9002\u7528\u4e8ePycharm\u793e\u533a\u7248\uff0c\u8c03\u7528\u5931\u8d25\u95ee\u9898\uff0c\u5df2\u4fee\u590d\u53c2\u4e0e\u8d21\u732e\u4f5c\u8005:@Tser\u00a9\u5c0f\u767d\u79d1\u6280"} +{"package": "xiaobaiauto2", "pacakge-description": "\u7b80\u4ecbxiaobaiauto2\u662f\u4e00\u5957\u81ea\u52a8\u5316\u6846\u67b6\uff0c\u529f\u80fd\u8986\u76d6UI\u81ea\u52a8\u5316\u4e0eAPI\u81ea\u52a8\u5316\n\u610f\u5728\u5e2e\u52a9\u5bf9\u81ea\u52a8\u5316\u6709\u66f4\u591a\u9700\u6c42\u4e14\u8fc7\u591a\u65f6\u95f4\u5199\u4ee3\u7801\u7684\u4eba\u7fa4\uff0c\u8ba9\u5927\u5bb6\u7684\u65f6\u95f4\n\u82b1\u5728\u4e1a\u52a1\u7684\u5b9e\u73b0\u4e0a\u67b6\u6784\u5f00\u59cb\u4f7f\u7528\u4e86\u89e3\u6d4b\u8bd5\u7528\u4f8b\u76ee\u5f55test\n|\n|--__init__.py\n|\n|--WebTest \n| |\n| |--conftest.py\n| |--test_WebUI.py\n|\n|--APPTest\n| |\n| |--conftest.py\n| |--test_Xiaobai_APP_Case1.py\n| |--test_Xiaobai_APP_Case2.py\n|\n|--APITest\n| |\n| |--test_cases.py\n| |--yewua.py\u4e86\u89e3\u5173\u952e\u8bcd\u5e8f\u53f7CMDkey1\u6253\u5f00\u7f51\u9875OPENURL2\u70b9\u51fbCLICK3\u8f93\u5165SENDKEY4\u5237\u65b0REFRESH5\u540e\u9000BACK6\u5173\u95edCLOSE7\u9000\u51faQUIT8\u6807\u7b7eTAG9\u5c5e\u6027ATTR10URLCURL11\u6807\u9898ITLE12\u5185\u5d4c\u9875FRAME13\u6807\u7b7e\u9875[\u5e8f\u53f7(1\u5f00\u59cb)]WINDOW14JS_\u786e\u5b9aALERT015JS_\u53d6\u6d88ALERT116JS_\u8f93\u5165\u6846ALERT217JS_\u6587\u672cALERT318\u505c\u6b62WAIT19\u811a\u672cSCRIPT20\u6dfb\u52a0cookieADDCOOKIE21\u6ed1\u5c4fSWIPE22\u622a\u5c4fDSCREENSHOT23\u5143\u7d20\u622a\u56feESCREENSHOT24\u8bc6\u522b\u9a8c\u8bc1\u7801FINDTEXT25\u5750\u6807LOCATION26\u7f51\u9875\u6e90\u7801PAGESOURCE\u4fee\u6539\u811a\u672c\u53c2\u8003test\u76ee\u5f55\u4e0b\u9762\u7684\u811a\u672c@pytest.mark.xiaobai_web\ndef test_Case1(browser):\n web_action(browser, cmd=cmd.\u6253\u5f00\u7f51\u9875, loc='', data='http://www.baidu.com')\n web_action(browser, cmd=cmd.\u8f93\u5165, loc='//*[@id=\"kw\"]', data='\u5c0f\u767d\u79d1\u6280')\n web_action(browser, cmd=cmd.\u70b9\u51fb, loc='//*[@id=\"su\"]')\n web_action(browser, cmd=cmd.wait, data=3)\n web_action(browser, cmd=cmd.\u6807\u9898, contains_assert='\u5c0f\u767d')\u5173\u952e\u8bcd\u7684\u4f7f\u7528\uff0c\u770b\u4e0a\u9762\u793a\u4f8b\u4ea6\u53ef\uff08xiaobaiauto2>0.1.5.0\uff091 \u5bfc\u5165cmd\u7c7bfrom xiaobaiauto2.xiaobaiauto2 import cmd2 cmd\u7c7b\u8c03\u7528\u5c5e\u6027cmd.\u5173\u952e\u8bcd\u82e5\u611f\u89c9\u5173\u952e\u8bcd\u4e0d\u8db3\u4ee5\u4f7f\u7528\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528\u539f\u751f\u65b9\u6cd5\uff0c\u793a\u4f8b\u5982\u4e0bbrowser.find_element(by=By.ID, value='id\u5c5e\u6027\u503c').click()\u4ee3\u7801\u6267\u884c\u4e4b\u524d\uff0c\u82e5\u60a8\u9700\u8981\u53d1\u9001\u90ae\u4ef6\uff0c\u8bf7\u5c06test_first\u65b9\u6cd5\u4e2d\u7684email\u7684\u53c2\u6570\u503c\u8fdb\u884c\u81ea\u884c\u4fee\u6539\u5373\u53ef\u5907\u6ce8\u82e5APP\u6d4b\u8bd5\u9700\u8981\u83b7\u53d6toast\u4fe1\u606f\u53ef\u4ee5\u5199\u4e00\u4e2a\u65b9\u6cd5\u6dfb\u52a0\u5230\u81ea\u5df1\u7684\u9879\u76ee\u4e2d,\u4ee3\u7801\u6837\u4f8b\u5982\u4e0b\uff1adef find_toast(self, message, timeout, poll_frequency):\n new_message = f\"//*[@text=\\'{message}\\']\"\n element = WebDriverWait(self.driver, timeout, poll_frequency).until(\n EC.presence_of_element_located((By.XPATH, new_message)))\n return element.text\u4f7f\u75281\u3001\u547d\u4ee4\u884c\u8fd0\u884c\u811a\u672cpytest --html=report.html --self-contained-html\nor\npytest --html=report.html --self-contained-html -m xiaobai_web\nor\npytest --html=report.html --self-contained-html -o log_cli=true -o log_cli_level=INFO2\u3001\u5b9a\u65f6\u4efb\u52a1\u754c\u9762\u8fd0\u884c\u811a\u672c\uff08CMD\u547d\u4ee4\uff09xiaobaiauto2Timer3.1\u3001xiaobaiauto2Api\u5c06raw\u6570\u636e\u8f6c\u6362\u6210python\u4ee3\u7801(\u7248\u672c>0.1.3.1\u53ef\u7528)xiaobaiauto2Api -h # \u5e2e\u52a9\u6587\u6863\u63d0\u793a\nxiaobaiauto2Api -f *.txt -s *.py\nxiaobaiauto2Api -f *.txt -x 2\nxiaobaiauto2Api -f *.saz -x 2\nxiaobaiauto2Api -f *.har -x 2\nxiaobaiauto2Api -f *.har -x 3\nxiaobaiauto2Api -d D:\\example3.2\u3001xiaobaiauto2 >= 0.1.4.5 \u652f\u6301c\u53c2\u6570xiaobaiauto2Api -c 1 -f 1.har,2.har\nxiaobaiauto2Api -c 1 -f 1.har,2.har -d E:\\example\nxiaobaiauto2Api -c 1 -f 1.har,2.har -d E:\\example -s 1_2_compare\nxiaobaiauto2Api -c 1 -f 1.har.2.har -d E:\\example -x 3 # \u751f\u6210*.jmx(\u542b\u63d0\u53d6\u5668\u3001\u53c2\u6570\u5316)[>=0.1.7.2]3.3\u3001xiaobaiauto2 >= 0.1.5.5 \u652f\u6301t\u53c2\u6570xiaobaiauto2Api -t api // \u751f\u6210api\u6d4b\u8bd5\u6a21\u677f\nxiaobaiauto2Api -t web // \u751f\u6210web\u6d4b\u8bd5\u6a21\u677f\nxiaobaiauto2Api -t app // \u751f\u6210app\u6d4b\u8bd5\u6a21\u677f3.4\u3001xiaobaiauto2 >= 0.1.6.3 \u652f\u6301i\u4e0ev\u53c2\u6570(\u8bf7\u770b3.6) \u4e0d\u6307\u5b9a\u7248\u672c\u9ed8\u8ba4\u5b89\u88c5\u6700\u65b0\u7248\u54e6xiaobaiauto2Api -i jdk -v 8 // \u5b89\u88c5jdk8\nxiaobaiauto2Api -i jmeter -v 5.3 // \u5b89\u88c5jmeter5.3\nxiaobaiauto2Api -i chromedriver -v 88 // \u5b89\u88c5chromedriver\u768488\u7248\u672c\nxiaobaiauto2Api -i allure -d \"D:\\Program Files\" // \u5b89\u88c5allure(\u4f1a\u6709\u4e9b\u6162\u54e6)3.5\u3001xiaobaiauto2 >= 0.1.6.5 \u652f\u6301mock\u6a21\u62df\u63a5\u53e3from xiaobaiauto2.xiaobaiauto2 import mock, MockServer\n\n@mock(uri='/login', response={\"errcode\": 200, \"msg\": \"\u767b\u5f55\u6210\u529f\", \"data\": {\"token\": \"123456\"}})\n@mock(uri='/register', response={\"errcode\": 200, \"msg\": \"\u6ce8\u518c\u6210\u529f\", \"data\": {}})\n@MockServer(uri='/index', response={\"errcode\": 200, \"msg\": \"\u9996\u9875\u6210\u529f\", \"data\": {}})\ndef run(): pass\n\nif __name__ == '__main__':\n run(port=7777)\u5bfc\u5165mock\u65b9\u6cd5from xiaobaiauto2.xiaobaiauto2 import mock, MockServer\u5b9a\u4e49mock\u63a5\u53e3\uff0cmock\u4e0eMockServer\u65e0\u533a\u522b\uff0curi\u4e3a\u63a5\u53e3\u8def\u5f84\uff0cresponse\u4e3a\u63a5\u53e3\u8fd4\u56de\u503c\uff0crun\u4e3a\u88ab\u88c5\u9970\u7684\u51fd\u6570\u540d\u79f0\u53ef\u81ea\u5b9a\u4e49@mock(uri='/login', response={\"errcode\": 200, \"msg\": \"\u767b\u5f55\u6210\u529f\", \"data\": {\"token\": \"123456\"}})\n@mock(uri='/register', response={\"errcode\": 200, \"msg\": \"\u6ce8\u518c\u6210\u529f\", \"data\": {}})\n@MockServer(uri='/index', response={\"errcode\": 200, \"msg\": \"\u9996\u9875\u6210\u529f\", \"data\": {}})\ndef run(): pass\u542f\u52a8mock\u63a5\u53e3\u670d\u52a1\uff0c run\u4e3a\u4e0a\u9762\u88ab\u88c5\u9970\u7684\u65b9\u6cd5\u540d\uff0cport\u4e3a\u76d1\u542c\u7684\u7aef\u53e3(\u9ed8\u8ba46666)if __name__ == '__main__':\n run(port=7777)jmeter\u5c1d\u8bd5\uff1fapi1: http://127.0.0.1:7777/login\napi2: http://127.0.0.1:7777/register\napi3: http://127.0.0.1:7777/index3.6\u3001xiaobaiauto2 >= 0.1.6.6 \u652f\u6301\u8f6f\u4ef6\u81ea\u52a8\u5b89\u88c5\u4e0e\u73af\u5883\u914d\u7f6e\u9ed8\u8ba4\u73af\u5883\u4e3a\u7528\u6237\u73af\u5883\uff0c\u914d\u7f6e\u7684\u662f\u7528\u6237\u73af\u5883\u53d8\u91cf\uff0c\u82e5\u8981\u914d\u7f6e\u7cfb\u7edf\u73af\u5883\u53d8\u91cf\uff0c\u8bf7\u4f7f\u7528\u7ba1\u7406\u5458\u8fd0\u884c\u5373\u53efxiaobaiauto2Api -i jdk -v 8 -d D:\\\nxiaobaiauto2Api -i jmeter -v 5.3 -d D:\\\nxiaobaiauto2Api -i chromedriver -v 88\nxiaobaiauto2Api -i jenkins -d D:\\tomcat\\webapps\nxiaobaiauto2Api -i git\nxiaobaiauto2Api -i node -v 15 -d D:\\3.7\u3001xiaobaiauto2 >= 0.1.8.3 \u652f\u6301\u8f6f\u4ef6\u81ea\u52a8\u5b89\u88c5\u4e0e\u73af\u5883\u914d\u7f6e\u7ba1\u7406\u7cfb\u7edf\u4ee3\u7406\u670d\u52a1\u5668\uff08\u67e5\u770b\u3001\u8bbe\u7f6e\u3001\u5173\u95ed\u3001\u9a8c\u8bc1\uff09xiaobaiauto2Proxy -h # \u67e5\u770b\u5e2e\u52a9\u6587\u6863\nxiaobaiauto2Proxy # \u67e5\u770b\u7cfb\u7edf\u4ee3\u7406\u662f\u5426\u5f00\u542f\nxiaobaiauto2Proxy -e 0 -p 127.0.0.1:8080 # \u5f00\u542f\u7cfb\u7edf\u4ee3\u7406\nxiaobaiauto2Proxy -e 1 # \u5173\u95ed\u7cfb\u7edf\u4ee3\u7406\nxiaobaiauto2Proxy -c 1 # \u9a8c\u8bc1\u7cfb\u7edf\u4ee3\u7406\u662f\u5426\u53ef\u75283.8\u3001xiaobaiauto2 >= 0.2 \u652f\u6301adb\u547d\u4ee4\uff0c\u63d0\u524d\u6253\u5f00APP\u5355\u8bbe\u5907\u76d1\u63a7APP\u7684\u70b9\u51fb\uff0c\u70b9\u51fb\u7684\u8def\u5f84\u81ea\u52a8\u751f\u6210XPath\u8868\u8fbe\u5f0fxiaobaiauto2App\u591a\u8bbe\u5907\u5355\u673a\u76d1\u63a7APP\u7684\u70b9\u51fb\uff0c\u70b9\u51fb\u7684\u8def\u5f84\u81ea\u52a8\u751f\u6210XPath\u8868\u8fbe\u5f0fxiaobaiauto2App -d 127.0.0.1:62001 // \u6307\u5b9a\u8bbe\u5907\u53f7\u8fdb\u884c\u76d1\u63a7\nxiaobaiauto2App -i 1 // \u6307\u5b9a\u5e8f\u53f7\u4e3a1\u7684\u8bbe\u5907\u8fdb\u884c\u76d1\u63a73.9\u3001xiaobaiauto2>=0.2.6 \u652f\u6301\u9a8c\u8bc1\u7801\u81ea\u52a8\u5316\u8bc6\u522b\u5e76\u586b\u5145from xiaobaiauto2.xiaobaiauto2 import verify_check\n\n...\n# \u9a8c\u8bc1\u7801\u56fe\u7247\u5143\u7d20\u5b9a\u4f4d\nimage_element = browser.find_element(by=By.XPATH, value='xpath\u8868\u8fbe\u5f0f')\n# \u9a8c\u8bc1\u7801\u8f93\u5165\u6846\u5143\u7d20\u5b9a\u4f4d\ninput_element = browser.find_element(by=By.XPATH, value='xpath\u8868\u8fbe\u5f0f')\nverify_check(image_element, input_element)4.0\u3001xiaobaiauto2>=0.2.9 \u652f\u6301Browser\u3001Fiddler\u3001Charles\u5bfc\u51facURL\u8f6c\u4e3arequests\u4ee3\u7801\u542f\u52a8xiaobaiauto2Copy\u670d\u52a1:xiaobaiauto2CopyBrowserF12->network->requst->copy->copy cURL(bash)Fiddler\uff08\u4e0d\u63a8\u8350\uff0c\u4f1a\u7f3a\u5c11\u8bf7\u6c42\u6570\u636e\uff09File->Export Session->Selected Session->cURL ScriptCharlesrequest->Copy cURL Request4.1\u3001xiaobaiauto2>=0.3.7 \u652f\u6301\u7b80\u5316\u7248\u7684Email\u53d1\u9001\uff0c\u65b9\u4fbf\u81ea\u52a8\u5316\u53d1\u9001\u90ae\u7bb1\u6837\u4f8b1\uff08\u6267\u884c\u5b8c\u7528\u4f8b\u6587\u4ef6\u4e4b\u540e\uff0c\u518d\u6267\u884c\u672c\u811a\u672c\uff0c\u5373\u53ef\u5b8c\u6210\u6d4b\u8bd5\u62a5\u544a\u7684\u53ca\u65f6\u53d1\u9001\uff09fromxiaobaiauto2.utils.xiaobaiauto2Emailimportxemail# \u5efa\u7acb\u8fde\u63a5\uff0cpassword\u4e3a\u6388\u6743\u7801\u4e0d\u662f\u767b\u5f55\u5bc6\u7801x=xemail(smtp_server='smtp.163.com',smtp_port=25,username='xxx@163.com',password='\u6388\u6743\u7801')# \u53d1\u9001\u90ae\u4ef6,to\u6536\u4ef6\u4eba\u53ef\u4ee5\u591a\u4eba\uff0cfiles\u9644\u4ef6\u53ef\u4ee5\u591a\u4e2a\u6587\u4ef6\uff0c\u5747\u4f7f\u7528','\u9017\u53f7\u5206\u5272x.send(to='1@163.com,2@163.com,3@163.com',subject='\u81ea\u52a8\u5316\u6d4b\u8bd5\u62a5\u544a\u6807\u9898',content='\u62a5\u544a\u5185\u5bb9',files='report.html')\u6837\u4f8b2(\u56e0\u4e3a\u53d1\u9001\u90ae\u4ef6\u88ab\u5c01\u5230teardown_module\u51fd\u6570\u4e2d\uff0c\u6240\u4ee5\u53d1\u9001\u7684\u662f\u4e0a\u4e00\u6b21\u6267\u884c\u7684\u7ed3\u679c)# filename: test_xiaobai_testcase.pyimportpytestfromxiaobaiauto2.utils.xiaobaiauto2Emailimportxemaildeftest_other():''' \u5176\u5b83\u6d4b\u8bd5\u7528\u4f8b\u4ee3\u7801 '''defteardown_module():# \u6b64\u5904\u53d1\u9001\u7684\u62a5\u544a\u662f\u4e0a\u6b21\u6d4b\u8bd5\u7684\u7ed3\u679c# \u5efa\u7acb\u8fde\u63a5\uff0cpassword\u4e3a\u6388\u6743\u7801\u4e0d\u662f\u767b\u5f55\u5bc6\u7801x=xemail(smtp_server='smtp.163.com',smtp_port=25,username='xxx@163.com',password='\u6388\u6743\u7801')# \u53d1\u9001\u90ae\u4ef6,to\u6536\u4ef6\u4eba\u53ef\u4ee5\u591a\u4eba\uff0cfiles\u9644\u4ef6\u53ef\u4ee5\u591a\u4e2a\u6587\u4ef6\uff0c\u5747\u4f7f\u7528','\u9017\u53f7\u5206\u5272x.send(to='1@163.com,2@163.com,3@163.com',subject='\u81ea\u52a8\u5316\u6d4b\u8bd5\u62a5\u544a\u6807\u9898',content='\u62a5\u544a\u5185\u5bb9',files='report.html')\u5176\u4ed6\u5e2e\u52a9163\u90ae\u7bb1\u600e\u4e48\u5f00\u542fSMTP\u53d1\u90ae\u4ef6QQ\u90ae\u7bb1\u600e\u4e48\u5f00\u542fSMTP\u53d1\u90ae\u4ef6Pytest\u5b98\u7f51\u5e2e\u52a9\u6587\u6863Android\u8c03\u8bd5\u6865(adb)\u5b98\u7f51\u5e2e\u52a9\u6587\u6863\u66f4\u65b0\u65e5\u5fd7\u7248\u672c\u529f\u80fd0.0.1\u6dfb\u52a0\u90ae\u4ef6\u53d1\u9001\uff0c\u7528\u4f8b\u6392\u5e8f\uff0cchrome\u63d0\u793a\u6846\u7981\u6b62\u7b49\u7b490.1.0.1\u6dfb\u52a0\u81ea\u52a8\u6267\u884c\u4efb\u52a1\u529f\u80fd\u53caUI\u754c\u97620.1.1fix\u7f3a\u9677\uff0ccmd\u6267\u884cxiaobaiauto2Timer0.1.2fix\u7f3a\u96770.1.3\u65b0\u589e\u9a8c\u8bc1\u7801\u8bc6\u522b,\u652f\u6301 *.png *.jpg *.jpeg \uff0c\u65b0\u589e\u90e8\u5206\u5173\u952e\u8bcd(\u6682\u5df2\u5173\u95ed)0.1.3.1fix\u7f3a\u96770.1.4.0\u65b0\u589exiaobaiauto2Api\u547d\u4ee4\u884c\u5de5\u5177\uff0c\u53ef\u4ee5\u5c06raw\u8bf7\u6c42\u6570\u636e\u8f6c\u6362\u6210python\u4ee3\u78010.1.4.1fix\u7f3a\u96770.1.4.2\u4f18\u5316\u4e0e\u65b0\u589eFiddler\u7684saz\u6587\u4ef6\u652f\u63010.1.4.3\u4f18\u5316\u4ee3\u78010.1.4.4\u4f18\u5316\u4e0e\u65b0\u589echarles\u7684har\u6587\u4ef6\u652f\u6301,\u652f\u6301\u6279\u91cf\u811a\u672c\u8f6c\u63620.1.4.5\u4f18\u5316\u4e0e\u65b0\u589e\u6bd4\u8f83\u4e24\u4e2ahar\u6587\u4ef6\u5e76\u8f6c\u4e3aPython\u4ee3\u78010.1.4.6fix\u5e76\u652f\u6301fiddler\u5bfc\u51fa\u7684har\u6587\u4ef6\u8f6c\u4e3aPython\u4ee3\u78010.1.5.0fix\u5e76\u4f18\u5316api_action0.1.5.1\u4f18\u5316xiaobaiauto2Api\u4e0eweb_action\u652f\u6301cmd\u8c03\u7528\u5173\u952e\u8bcd0.1.5.2\u65b0\u589eapiTestCase\u88c5\u9970\u56680.1.5.3\u4fee\u590dxiaobaiauto2Api\u90e8\u5206bug0.1.5.4fix0.1.5.5add \u9009\u9879-t template \u53c2\u8003xiaobaiauto2Api -h0.1.5.6fix0.1.5.7fix0.1.6.0add \u53c2\u6570\u5316\u7b26{\u53d8\u91cf}\u7cfb\u7edf\u81ea\u52a8\u8bc6\u522b\u5e76\u66ff\u6362\u4e3a\u9884\u8bbe\u503c0.1.6.1fix0.1.6.2fix0.1.6.3add -i, -v \u65b0\u589e\u547d\u4ee4\u884c\u5b89\u88c5\u8f6f\u4ef6\u652f\u6301mac\u7cfb\u7edf0.1.6.4fix0.1.6.5add mock\u6a21\u62df\u63a5\u53e30.1.6.6\u4f18\u5316 -i -v \u652f\u6301jdk jmeter chromdriver jenkins git node0.1.7.0fix0.1.7.1fix -i \u65b0\u589e\u652f\u6301allure\u4e0esvn0.1.7.2fix -x \u65b0\u589e\u652f\u6301\u8f6c\u4e3ajmeter(*.jmx)\u811a\u672c0.1.7.3fix0.1.7.5fix0.1.7.6\u4f18\u5316jmx\u6570\u636e\u683c\u5f0f0.1.7.7\u4f18\u53160.1.8.0\u4f18\u5316jmx\u6570\u636e\u683c\u5f0f0.1.8.1\u4f18\u5316jmx\u7684\u53c2\u6570\u5316\u5b9e\u73b00.1.8.2\u4f18\u5316jmx\u7684\u5b9e\u73b00.1.8.3\u65b0\u589exiaobaiauto2Proxy\u7cfb\u7edf\u4ee3\u7406\u7ba1\u7406\u6a21\u57570.1.8.5\u4f18\u5316jmx\u7684\u5b9e\u73b00.1.8.6\u4f18\u5316jmx\u7684\u5b9e\u73b00.1.8.7\u4f18\u5316jmx\u7684\u5b9e\u73b00.1.8.8\u4f18\u5316xiaobaiauto2App0.1.9\u4f18\u5316xiaobaiauto2App0.1.9.1\u4f18\u5316mac\u7684\u73af\u5883\u53d8\u91cf\u8bbe\u7f6e0.1.9.2fix0.1.9.3fix0.1.9.5fix0.1.9.6\u65b0\u589exiaobaiauto2\u5b89\u88c5\u8f6f\u4ef6tomcat0.1.9.7fix0.1.9.8fix \u652f\u6301\u4e0b\u8f7dfiddler\u4e0epostman0.1.9.9fix \u6a21\u677f\u7684\u4e0b\u8f7d\u8def\u5f84\u62a5\u9519\u95ee\u98980.2xiaobaiauto2App0.2.1\u66f4\u65b00.2.2fixed0.2.3fix\u5173\u952e\u8bcd\u4e0exiaobaiauto2App\u7684BUG0.2.5\u4f18\u5316xiaobaiauto2App\u8f93\u51fa\u4ee3\u7801\u7ed3\u67840.2.7\u65b0\u589e\u9a8c\u8bc1\u7801\u8bc6\u522bverify_check\uff0c\u5e93\u5b58\u5728\u517c\u5bb9\u95ee\u9898\uff0c\u81ea\u884c\u5b89\u88c5\u4f9d\u8d56\uff010.2.8\u65b0\u589e\u6d4f\u89c8\u5668copy->cURL(bash\u8f6crequests\u4ee3\u7801)0.2.9\u65b0\u589eFiddler/Charles->cURL(bash\u8f6crequests\u4ee3\u7801)0.3\u4f18\u5316\u4ee3\u7801\uff0c\u4fee\u590dBUG0.3.1\u4f18\u5316\u4ee3\u7801\uff0c\u4fee\u590dBUG0.3.2\u4f18\u5316\u4ee3\u78010.3.3\u4f18\u5316\u4ee3\u78010.3.5Fix BUG0.3.6\u4f18\u5316xiaobaiauto2Email\u65b0\u589e\u7b80\u5316\u7248\u90ae\u4ef6\u53d1\u90010.3.7\u4f18\u5316xiaobaiauto2Email0.5\u4f18\u5316\u8f6f\u4ef6\u5b89\u88c5\uff0cwindow\u9ed8\u8ba4\u7cfb\u7edf\u73af\u5883\u53d8\u91cf\u8bbe\u7f6e\u4e14\u7acb\u5373\u751f\u65480.5.1Fix BUG"} +{"package": "xiaobai-config", "pacakge-description": "simple_configPython\u9879\u76ee\u7684\u914d\u7f6e\u4fe1\u606f\u5de5\u5177\uff0c\u53ef\u4ee5\u4ece\u89e3\u6790\u914d\u7f6e\u6587\u4ef6\u3001\u73af\u5883\u53d8\u91cf\u3002"} +{"package": "xiaobai-id-validator", "pacakge-description": "No description available on PyPI."} +{"package": "xiaobaiinstaller", "pacakge-description": "\u5b89\u88c5pip install xiaobaiinstaller\nor\npip install -U xiaobaiinstaller\u4f7f\u7528\u6253\u5f00cmd\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff0c\u56de\u8f66\u8fd0\u884c\nxiaobaiinstaller\u5907\u6ce8- \u76ee\u524d\u652f\u6301\uff1aJMeter\u4e0eJDK\u7684\u5b89\u88c5\n- \u53ef\u4ee5\u624b\u52a8\u83b7\u53d6JMeter\u6216\u8005JDK\u7684\u7248\u672c\uff0c\u63a8\u8350\u9009\u62e9\u65b0\u7248\u672c\n- \u8f6f\u4ef6\u9ed8\u8ba4\u5b89\u88c5\u5728D:\\Program Files\u76d8\u4e0b\uff0c\u540e\u7eed\u6dfb\u52a0\u53ef\u81ea\u5b9a\u4e49\u5b89\u88c5\u5728\u5176\u5b83\u76ee\u5f55\u4e0b\n- \u540e\u7eed\u518d\u589e\u52a0\u5176\u5b83\u8f6f\u4ef6\u5b89\u88c5"} +{"package": "xiaobaisaf", "pacakge-description": "simlpe_automation_framework\u4ecb\u7ecdsimple_automation_framework(\u7b80\u79f0\uff1aSAF)\n\u4f7f\u7528\u6700\u7b80\u5355\u7684\u6a21\u5f0f\u5c31\u53ef\u4ee5\u5b9e\u73b0\u9700\u8981\u529f\u80fd\u548c\u6d4b\u8bd5\u6548\u679c\uff0c\u4e5f\u662fxiaobaiauto2\u7684\u7b80\u5316\u7248\nSAF\u7ee7\u627f\u4e86selenium\u3001requests/httpx\u3001appium\u3001loguru\u3001xiaobaiauto2\u3001\u98de\u4e66\u673a\u5668\u4eba\u3001\u9489\u9489\u673a\u5668\u4eba\u3001\u4f01\u4e1a\u5fae\u4fe1\u673a\u5668\u4eba\uff08\u6682\u65f6\u4e0d\u652f\u6301\uff09\u3001\u7985\u9053\u63d0\u5355API\u8f6f\u4ef6\u67b6\u6784xiaobaiauto2\u7684\u7b80\u5316\u7248\u7248\u672c\u6ce8\u610f\u5efa\u8bae\u4f7f\u7528Python 3.9.* \u7248\u672c\n\u5efa\u8baeselenium >=4.16.0 \u652f\u6301\u4ee3\u7801\u81ea\u52a8\u6267\u884c\u65e0\u9700\u5173\u6ce8\u6d4f\u89c8\u5668\u9a71\u52a8\u95ee\u9898\uff0c\u53ef\u4ee5\u81ea\u884c\u4e0b\u8f7d\n\u9632\u6b62\u67d0\u4e9b\u5e93\u51fa\u73b0\u4e0d\u517c\u5bb9\u95ee\u9898\uff0c\u5bfc\u81f4\u529f\u80fd\u4e0d\u53ef\u4f7f\u7528\u5b89\u88c5\u6559\u7a0bpip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple \u6ce8\uff1a\u5c06pip\u6e90\u4fee\u6539\u4e3a\u56fd\u5185\u6e90\npip install xiaobaisaf\u4f7f\u7528\u8bf4\u660e\u4f18\u5148\u4fee\u6539saf/data/config.py\u4e2d\u98de\u4e66/\u9489\u9489\u7684webhook# filename=config.pyclassfeishu(object):@staticmethoddefwebhook():return'https://open.feishu.cn/open-apis/bot/v2/hook/xxxx'classdingding(object):@staticmethoddefwebhook():return'https://oapi.dingtalk.com/robot/send?access_token=xxxxxxxx'conftest.py\uff08\u4fdd\u6301\u6b64\u6587\u4ef6\u4e0e\u7528\u4f8b\u6587\u4ef6\u5728\u540c\u76ee\u5f55\u4e0b\uff09# filename = conftest.pyfromsaf.utils.SendMsgUtilsimportrobotSendMessageimportpytest@pytest.mark.hookwrapperdefpytest_runtest_makereport(item):\"\"\":param item:\"\"\"outcome=yieldreport=outcome.get_result()ifreport.outcome=='failed':# \u8c03\u7528\u673a\u5668\u4eba\u53d1\u9001\u6267\u884c\u7ed3\u679crobotSendMessage(robot_name='feishu',msg=f'\u6d4b\u8bd5\u811a\u672c\uff1a{report.nodeid.split(\"::\")[0]}\\n\u6d4b\u8bd5\u7528\u4f8b\uff1a{report.nodeid.split(\"::\")[1]}\\n\u6d4b\u8bd5\u7ed3\u679c\uff1a{report.outcome}')# robotSendMessage(robot_name='dingding', msg=f'\u6d4b\u8bd5\u811a\u672c\uff1a{report.nodeid.split(\"::\")[0]}\\n\u6d4b\u8bd5\u7528\u4f8b\uff1a{report.nodeid.split(\"::\")[1]}\\n\u6d4b\u8bd5\u7ed3\u679c\uff1a{report.outcome}')# robotSendMessage(robot_name='feishu,dingding', msg=f'\u6d4b\u8bd5\u811a\u672c\uff1a{report.nodeid.split(\"::\")[0]}\\n\u6d4b\u8bd5\u7528\u4f8b\uff1a{report.nodeid.split(\"::\")[1]}\\n\u6d4b\u8bd5\u7ed3\u679c\uff1a{report.outcome}')\u7528\u4f8b\u6587\u4ef6# fielname = test_xiaobai_testcase.pydefsetup_module():''' \u7528\u4f8b\u811a\u672c\u6267\u884c\u4e4b\u524d\u9700\u8981\u51c6\u5907\u7684\u4fe1\u606f '''...defteardown_module():''' \u7528\u4f8b\u811a\u672c\u6267\u884c\u4e4b\u540e\u9700\u8981\u6e05\u9664\u7684\u4fe1\u606f '''defsetup_function():''' \u521d\u59cb\u5316\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u4e4b\u524d\u72b6\u6001\u4fe1\u606f '''...defteardown_function():''' \u6e05\u9664\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u4e4b\u540e\u6240\u4ea7\u751f\u7684\u4fe1\u606f '''...deftest_yewu_name_a():''' \u7528\u4f8b\u51fd\u6570\u9700\u8981\u9488\u5bf9\u4e1a\u52a1\u573a\u666f\u7684\u6d4b\u8bd5\u6b65\u9aa4\u7684\u5b9e\u73b01\u3001UI\u6d4b\u8bd5\u5c31\u662f\u5b9a\u4f4d\u9700\u8981\u64cd\u4f5c\u7684\u754c\u9762\u8282\u70b9\u7136\u540e\u6267\u884c\u64cd\u4f5c2\u3001API\u6d4b\u8bd5\u5c31\u662f\u6267\u884c\u76f8\u5173\u63a5\u53e3\u5b9e\u73b0\u63a5\u53e3\u7684\u529f\u80fd\u9700\u8981\u9488\u5bf9\u6bcf\u6b21\u7684\u7ed3\u679c\u6dfb\u52a0\u65ad\u8a00\u8fdb\u884c\u5224\u65ad\u5904\u7406'''deftest_yewu_name_b():''' \u7528\u4f8b\u51fd\u6570\u9700\u8981\u9488\u5bf9\u4e1a\u52a1\u573a\u666f\u7684\u6d4b\u8bd5\u6b65\u9aa4\u7684\u5b9e\u73b01\u3001UI\u6d4b\u8bd5\u5c31\u662f\u5b9a\u4f4d\u9700\u8981\u64cd\u4f5c\u7684\u754c\u9762\u8282\u70b9\u7136\u540e\u6267\u884c\u64cd\u4f5c2\u3001API\u6d4b\u8bd5\u5c31\u662f\u6267\u884c\u76f8\u5173\u63a5\u53e3\u5b9e\u73b0\u63a5\u53e3\u7684\u529f\u80fd\u9700\u8981\u9488\u5bf9\u6bcf\u6b21\u7684\u7ed3\u679c\u6dfb\u52a0\u65ad\u8a00\u8fdb\u884c\u5224\u65ad\u5904\u7406'''# filename = test_xiaobai_allure.py# JDK\u4e0eAllure\u5df2\u5b89\u88c5\u4e14\u914d\u7f6e\u597d\u73af\u5883\u53d8\u91cf\uff08\u82e5\u4e0d\u77e5\u9053\u53ef\u4ee5\u67e5\u770b\u516c\u4f17\u53f7\uff1a\u5c0f\u767d\u79d1\u6280\u4e4b\u7a97\uff09importpytestimportallure@allure.feature('\u4e0b\u5355')classTest_order():@allure.story('\u767b\u5f55')deftest_login(self):''' \u767b\u5f55 '''withallure.step('\u8f93\u5165\u8d26\u6237'):assertTruewithallure.step('\u8f93\u5165\u5bc6\u7801'):assertTruewithallure.step('\u70b9\u51fb\u767b\u5f55'):assertTrue@allure.story('\u641c\u7d22\u5546\u54c1')deftest_search(self):''' \u641c\u7d22\u5546\u54c1 '''withallure.step('\u641c\u7d22\u6846\u8f93\u5165\uff1a\u82f9\u679c'):assertTruewithallure.step('\u70b9\u51fb\u641c\u7d22\u6309\u94ae'):assertFalse'''# \u6267\u884c\u811a\u672cpytest test_xiaobai_allure.py --alluredir=../data# \u6253\u5f00\u62a5\u544aallure serve ../data\u6216\u8005allure generate -c -o ../report ../dataallure open ../report'''saf>1.1 \u4f7f\u7528\u7985\u9053API\uff0c\u6d4b\u8bd5\u5931\u8d25\u81ea\u52a8\u63d0\u5355\u9700\u8981\u5728\u7985\u9053\u540e\u53f0>>\u4e8c\u6b21\u5f00\u53d1>>\u5e94\u7528>>\u6dfb\u52a0\u5e94\u7528>>\u521b\u5efa\u5f00\u542f\u514d\u5bc6\u7684\u5e94\u7528\u9700\u8981\u5c06\u4e0a\u4e00\u6b65\u6240\u751f\u6210\u6570\u636e\u3010\u4ee3\u53f7\u3011\u4e0e\u3010\u5bc6\u94a5\u3011\u5199\u5165\u5230saf/data/config.py\u4e2dzenTao\u76f8\u5173\u7684\u53c2\u6570\u4f4d\u7f6e# filename = saf/data/config.pyimporthashlibimporttimeclasszenTao(object):'''\u53c2\u8003\u7985\u9053\u63a5\u53e3\u6587\u6863\uff1ahttps://www.zentao.net/book/zentaopmshelp/integration-287.html'''@staticmethoddefbaseURL():''' \u7985\u9053\u7684\u6839\u8def\u5f84 '''return'http://192.168.0.240/zentao'@staticmethoddefaccount():''' \u540e\u53f0-\u300b\u4e8c\u6b21\u5f00\u53d1-\u300b\u5e94\u7528-\u300b\u514d\u5bc6\u767b\u5f55\u7684\u8d26\u6237\u540d '''return'\u5f00\u542f\u5bc6\u94a5\u7684\u8d26\u6237\u540d\u79f0\uff0c\u4f8b\u5982\u7ba1\u7406\u5458\uff1aadmin'@staticmethoddefgetCode():''' \u540e\u53f0-\u300b\u4e8c\u6b21\u5f00\u53d1-\u300b\u5e94\u7528-\u300b\u521b\u5efa-\u300b\u4ee3\u53f7 '''return'\u590d\u5236\u751f\u6210\u5e94\u7528\u7684\u4ee3\u53f7\u5b57\u7b26\u4e32'@staticmethoddefgetKey():''' \u540e\u53f0-\u300b\u4e8c\u6b21\u5f00\u53d1-\u300b\u5e94\u7528-\u300b\u521b\u5efa-\u300b\u5bc6\u94a5 '''return'\u590d\u5236\u751f\u6210\u5e94\u7528\u7684\u5bc6\u94a5\u5b57\u7b26\u4e32'@staticmethoddefgetTime():''' \u83b7\u53d6\u65f6\u95f4\u6233 \uff0c\u9ed8\u8ba4\u5373\u53ef\uff0c\u65e0\u9700\u4fee\u6539'''returnint(time.time())@staticmethoddefgetToken():''' \u83b7\u53d6token\uff1a md5($code + $key + $time) \uff0c\u9ed8\u8ba4\u5373\u53ef\uff0c\u65e0\u9700\u4fee\u6539'''_md5=hashlib.md5(f'{zenTao.getCode()}{zenTao.getKey()}{zenTao.getTime()}'.encode('utf-8'))return_md5.hexdigest()\u7528\u4f8b\u540c\u76ee\u5f55\u4e0b\u521b\u5efaconftest.pypytest\u7684\u914d\u7f6e\u6587\u4ef6# filename = conftest.pyfromsaf.utils.BugUtilsimportaddZenTaoBUGimportpytest@pytest.mark.hookwrapperdefpytest_runtest_makereport(item,call):\"\"\":param item:\"\"\"outcome=yieldreport=outcome.get_result()ifreport.outcome=='failed':doc=item.function.__doc__doc=str(doc).replace('\\n','
            ')addZenTaoBUG(title=item.function.__name__,steps=f'{doc}\u9884\u671f\u7ed3\u679c\uff1apassed
            \u6d4b\u8bd5\u7ed3\u679c\uff1a{report.outcome}')\u7528\u4f8b\u6587\u4ef6\u6b63\u5e38\u7f16\u5199\uff0c\u6b63\u5e38\u8fd0\u884c\u5373\u53efsaf>1.0 \u62f7\u8d1dweb\u81ea\u52a8\u5316\u6a21\u677f\u5230D:\\autoProject\u76ee\u5f55\u4e0bxiaobaicmd -t web -d D:\\autoProject\nxiaobaicmd --template web --dirname D:\\autoProject\nxiaobaicmd -t api -d D:\\autoProject\nxiaobaicmd --template api --dirname D:\\autoProject\nxiaobaicmd -t app -d D:\\autoProject[\u6682\u65f6\u4e0d\u652f\u6301]saf>1.3 \u65b0\u589epytest\u53c2\u6570\u591a\u79cd\u6837\u4f8b\uff0cweb\u4e2d\u5305\u542b# filename = test_xiaobai_case_v2.pyimportpytestfromsafimportfull_load''' \u53c2\u6570\u5316 '''data2={'test_login':{'keys':'username, password, _assert','values':[('xiaobai','12345',200),('xiaohui','1234567',200)]}}data3=full_load(open('..\\\\data\\\\testCase.yaml','r').read())# \u5185\u90e8\u6570\u636e@pytest.mark.parametrize('username, password, _assert',[('xiaobai','12345',200),('xiaohui','1234567',200)])deftest_xiaobai_login1(username,password,_assert):# \u4e1a\u52a1\u5b9e\u73b0\u4ee3\u7801assert_assert==200# \u5916\u90e8\u6570\u636e@pytest.mark.parametrize(data2['test_login']['keys'],data2['test_login']['values'])deftest_xiaobai_login2(username,password,_assert):# \u4e1a\u52a1\u5b9e\u73b0\u4ee3\u7801assert_assert==200# \u5916\u90e8\u6587\u4ef6\u6570\u636e@pytest.mark.parametrize(data3['test_login']['keys'],[eval(v)forvindata3['test_login']['values']])deftest_xiaobai_login3(username,password,_assert):# \u4e1a\u52a1\u5b9e\u73b0\u4ee3\u7801assert_assert==200# filename = ..\\\\data\\\\testCase.yaml---test_login:keys:username,password,_assertvalues:-('xiaobai', '12346', 200)-('xiaohui', '123456', 200)saf>1.8 \u5de5\u5177\u4f1a\u81ea\u52a8\u5728\u5f53\u524d\u76ee\u5f55\u4e0b\u751f\u6210target\u6587\u4ef6\u5939\uff0ctarget\u76ee\u5f55\u5185\u5bb9\u4e0eweb\u6a21\u677f\u4fdd\u6301\u4e00\u81f4\uff0c\u9875\u9762\u5bf9\u8c61\u4ee3\u7801\u5728PageObjects\u76ee\u5f55\u4e0bxiaobaicmd -u https://www.baidu.com \nxiaobaicmd --url https://www.baidu.comsaf>1.9 \u57fa\u4e8eadb\u5b9e\u73b0\u76d1\u63a7Android\u8bbe\u5907\u4e2dAPP\u64cd\u4f5c\u65f6\u5b9e\u65f6\u751f\u6210XPath\u8868\u8fbe\u5f0f\u53ca\u5750\u6807\u7b49\u6570\u636exiaobaicmd -m gui # \u57fa\u4e8e\u754c\u9762\u5b9e\u65f6\u83b7\u53d6APP\u6570\u636e\nxiaobaicmd --monitor gui # \u57fa\u4e8e\u754c\u9762\u5b9e\u65f6\u83b7\u53d6APP\u6570\u636e\nxiaobaicmd -m cli # \u57fa\u4e8e\u547d\u4ee4\u5b9e\u65f6\u83b7\u53d6APP\u6570\u636e\nxiaobaicmd --monitor cli # \u57fa\u4e8e\u547d\u4ee4\u5b9e\u65f6\u83b7\u53d6APP\u6570\u636esaf>2.0 \u57fa\u7840adb\u5b9e\u73b0Android\u8bbe\u5907\u7684\u754c\u9762\u76d1\u63a7\u529f\u80fdxiaobaicmd -e [1] # \u9ed8\u8ba4\u503c\u4e3a1\uff0c\u53ef\u7701\u7565\uff1b\u8868\u793a\u6253\u5f00\u754c\u9762\u76d1\u63a7\u7b2c\u4e00\u4e2a\u8bbe\u5907\u7684\u5b9e\u65f6\u754c\u9762\nxiaobaicmd --device 1saf>2.2 \u57fa\u7840adb\u5b9e\u73b0Android\u8bbe\u5907\u7684\u7535\u91cf\u76d1\u63a7\u529f\u80fdxiaobaicmd -m power # \u754c\u9762\u76d1\u63a7\u8bbe\u5907\u7684\u7535\u91cf\u4e0e\u5185\u5b58\u4f7f\u7528\u7387\u7684\u5b9e\u65f6\u754c\u9762\nxiaobaicmd -m memory # \u754c\u9762\u76d1\u63a7\u8bbe\u5907\u7684\u7535\u91cf\u4e0e\u5185\u5b58\u4f7f\u7528\u7387\u7684\u5b9e\u65f6\u754c\u9762saf>2.3.5 \u65b0\u589e\u5b9e\u65f6\u76d1\u63a7Android\u5f53\u524dAPP\u7684CPU\u4f7f\u7528\u7387\u53caFPS\u6570\u636exiaobaicmd -m guisaf>2.3.7 \u65b0\u589e\u8bc6\u522b\u6ed1\u5757\u9a8c\u8bc1\u7801\u7834\u89e3fromsaf.utils.CaptchaUtilsimportcheckSliderfromsafimportselenium_webdriver,Bydriver=selenium_webdriver.Chrome()driver.get(\"https://www.xiaobaisoftware.com\")# \u5176\u5b83\u64cd\u4f5c...# \u5b9a\u4f4d\u76ee\u6807\u56fe\uff08\u5c0f\u56fe\uff09target_element=driver.find_element(By.XPATH,value='')# \u5b9a\u4f4d\u80cc\u666f\u56fe\uff08\u5927\u56fe\uff09background_element=driver.find_element(By.XPATH,value='')# \u5b9a\u4f4d\u6ed1\u5757\u6309\u94aebutton_element=driver.find_element(By.XPATH,value='')# \u53c2\u6570\uff1a\u6d4f\u89c8\u5668\u9a71\u52a8\u3001\u76ee\u6807\u5143\u7d20\u3001\u80cc\u666f\u5143\u7d20\u3001\u6ed1\u5757\u5143\u7d20\u3001\u5931\u8d25\u91cd\u8bd5\uff08\u975e\u5fc5\u987b\uff0c\u9ed8\u8ba4\uff1aFalse\uff09\u3001\u91cd\u8bd5\u6b21\u6570\uff08\u975e\u5fc5\u987b\uff0c\u9ed8\u8ba4\uff1a3\uff09checkSlider(driver,target_element,background_element,button_element,True,5)saf>2.3.8 \u65b0\u589e\u89e3\u6790DNS\u5e76\u5237\u65b0DNS\u7f13\u5b58\uff0c\u6570\u636e\u4fdd\u5b58HOSTS# \u6267\u884c\u811a\u672c\u4e4b\u524d\u8bf7\u4fee\u6539\u7cfb\u7edfhosts\u6587\u4ef6\u5728\u5f53\u524d\u7528\u6237\u4e0b\u6709\u53ef\u8bfb\u53ef\u5199\u7684\u6743\u9650\uff01\n# windows\u7684hosts\u6587\u4ef6\u8def\u5f84\uff1aC:\\Windows\\System32\\drivers\\etc\\hosts\n# Mac OS\u7684hosts\u6587\u4ef6\u8def\u5f84 \uff1a/private/etc/hosts\n# Linux\u7684hosts\u6587\u4ef6\u8def\u5f84 \uff1a/etc/hosts\n\n# --domains \u540e\u9762\u7684\u57df\u540d\u4f7f\u7528\u9017\u53f7\u5206\u79bb\u5373\u53ef\nxiaobaicmd --domains github.com,raw.githubusercontent.com,github.global.ssl.fastly.net,assets-cdn.github.comsaf>=2.5.0 \u65b0\u589e\u5c0f\u767d\u8f6f\u4ef6\u7ba1\u7406\u5de5\u5177\uff0c\u76ee\u524d\u652f\u6301\uff08\u5b89\u88c5\u3001\u5378\u8f7d\u3001\u66ff\u6362\u4e0d\u540c\u7248\u672c\u7684\uff09JMeter#\u547d\u4ee4\u884c\u8f93\u5165\u547d\u4ee4\u8fd0\u884c\u5373\u53ef\nxiaobaimanager\u73af\u5883\u68c0\u6d4b[\u8fd8\u672a\u5b9e\u73b0]xiaobaicmd --init\n\n\u68c0\u6d4b\u5185\u5bb9: \n1\u3001python\u7248\u672c\u53ca\u7b2c\u4e09\u65b9\u5e93\n2\u3001\u7b2c\u4e09\u65b9\u5de5\u5177\u53ca\u73af\u5883\u53c2\u4e0e\u8d21\u732eselenium\u5b98\u7f51\u6587\u6863requests\u5b98\u7f51\u6587\u6863appium\u5b98\u7f51loguru\u5b98\u65b9\u6587\u6863xiaobaiauto2\u5e2e\u52a9\u6587\u6863Allure\u5e2e\u52a9\u6587\u6863\u98de\u4e66\u673a\u5668\u4eba\u83b7\u53d6WebHook\u9489\u9489\u673a\u5668\u4eba\u83b7\u53d6WebHook163\u90ae\u7bb1\u914d\u7f6eQQ\u90ae\u7bb1\u914d\u7f6e\u66f4\u65b0\u65e5\u5fd7versioninfo1.0\u57fa\u672c\u5b9e\u73b0web\u81ea\u52a8\u5316\u6a21\u677f\u529f\u80fd1.1\u4fee\u590d\u5df2\u77e5BUG1.2\u65b0\u589eallure\u62a5\u544a\u5e93\u53ca\u5c01\u88c5\u7985\u9053\u63d0\u5355\u63a5\u53e31.3\u65b0\u589ejira\u63d0\u5355\u63a5\u53e31.4\u65b0\u589epytest\u53c2\u6570\u5316\u6837\u4f8b1.5\u4f18\u5316pytest\u6837\u4f8b\u5185\u5bb91.6\u4fee\u590d\u5df2\u77e5BUG1.7\u65b0\u589e\u57fa\u7840\u73af\u5883\u68c0\u6d4b\u529f\u80fd1.8\u65b0\u589eAPI\u81ea\u52a8\u5316\u6a21\u677f1.9\u65b0\u589exiaobaicmd -u\u547d\u4ee42.0\u65b0\u589exiaobaicmd -m\u547d\u4ee42.1\u65b0\u589exiaobaicmd --device\u547d\u4ee42.2\u4fee\u590d\u5df2\u77e5BUG2.3\u65b0\u589e\u5b9e\u65f6\u76d1\u63a7Android\u8bbe\u5907\u8017\u7535\u91cf2.3.1\u4fee\u590d\u5df2\u77e5BUG2.3.2\u4fee\u590d\u5df2\u77e5BUG2.3.3\u65b0\u589e\u5b9e\u65f6\u76d1\u63a7Android\u5f53\u524dAPP\u7684\u5185\u5b58\u4f7f\u7528\u73872.3.4\u65b0\u589exiaobaicmd -m gui\u6548\u679c\u5c55\u793a2.3.5\u65b0\u589exiaobaicmd -u \u8f6cPO\u4ee3\u7801\u65f6xpath\u7684\u8868\u8fbe\u5f0f2.3.6\u65b0\u589e\u5b9e\u65f6\u76d1\u63a7Android\u5f53\u524dAPP\u7684CPU\u4f7f\u7528\u7387\u53caFPS\u6570\u636e2.3.7\u65b0\u589e\u8bc6\u522b\u6ed1\u5757\u9a8c\u8bc1\u7801\u7834\u89e32.3.8\u4f18\u5316\u8bc6\u522b\u6ed1\u5757\u9a8c\u8bc1\u7801\u7834\u89e32.3.9\u65b0\u589e\u89e3\u6790DNS\u5e76\u5237\u65b0DNS\u7f13\u5b58\uff0c\u6570\u636e\u4fdd\u5b58HOSTS2.4\u4fee\u590d\u5df2\u77e5BUG2.4.1\u4f18\u5316DNS\u89e3\u6790\u6548\u679c2.4.2\u4f18\u5316\u81ea\u52a8\u751f\u6210\u4ee3\u78012.4.3\u4f18\u53162.4.3.1\u4f18\u53162.4.3.2\u4f18\u53162.5.0\u6dfb\u52a0xiaobaimanager\u547d\u4ee42.5.1\u4f18\u5316xiaobai"} +{"package": "xiaobanma", "pacakge-description": "#xiaobanma PackageThis is a simple package. You can useGithub-flavored Markdownto write your content."} +{"package": "xiaobo_test", "pacakge-description": "No description available on PyPI."} +{"package": "xiaochuanhttpsproxy", "pacakge-description": "https\u4ee3\u7406ip\u8fd0\u884cpython3\u7b2c\u4e09\u65b9\u5305requests\u5b89\u88c5pipinstallxiaochuanhttpsproxy\u4f7f\u7528importxiaochuanhttpsproxyxiaochuanhttpsproxy.start(2)print(xiaochuanhttpsproxy.getip())\u6bcf\u6b21\u63d0\u53d6\u7684ip\u6709\u63a5\u8fd120\u4e2a,start\u7684\u53c2\u6570\u4e3a2\u51fd\u6570\u89e3\u91ca:start() \u5f00\u59cb\u63d0\u53d6\uff0c\u53c2\u6570\u4e3a\u63d0\u53d6\u7684\u9875\u9762\u6570\uff0c\u4e00\u9875100\u4e2a\u521d\u59cbip, getip()\u83b7\u53d6\u968f\u673aipstart(1)\u7684\u8fd0\u884c\u65f6\u95f4\u5927\u6982\u4e3a2\u5206\u949f\uff0c\u4ee5\u6b64\u7c7b\u63a8\u8054\u7cfbgithub:@github,pypi:pypimail:w2239559319@outlook.com"} +{"package": "xiaochuanipproxy", "pacakge-description": "http\u4ee3\u7406ip\u63d0\u53d6\u7a0b\u5e8f\u8fd0\u884cpython3\u7b2c\u4e09\u65b9\u5305requests\u5b89\u88c5pipinstallxiaochuanipproxy\u4f7f\u7528importxiaochuanipproxyxiaochuanipproxy.start()#\u7b49\u5230\u7a0b\u5e8f\u8f93\u51fa\u63d0\u53d6\u5b8c\u6bd5\u5373\u53ef\u8c03\u7528print(xiaochuanipproxy.getip())#\u8fd4\u56de\u4e00\u4e2aip\u6bcf\u6b21\u63d0\u53d6\u7684IP\u5927\u6982\u670930\u4e2a\u63d0\u53d6\u7684\u7f51\u7ad9\u6709:\u897f\u523a\u4ee3\u7406.\u5feb\u4ee3\u7406.89\u514d\u8d39\u4ee3\u7406.5u\u4ee3\u7406.\u7c73\u6251.yqie\n\u76f8\u5e94\u7684\u51fd\u6570getxiciip(maxpage),getmipuip(),get5uip(),get98mianfeiip(maxpage),getkuaidailiip(maxpage),getyqieip\u5f00\u53d1\u8005\u7248\u672cxiaochuanipproxy\u5df2\u7ecf\u4e0a\u4f20\u81f3pypi\uff0c\u8fdb\u5165pypi\u9875\u9762"} +{"package": "xiaocui", "pacakge-description": "cui_package\u8fd9\u4e2a\u6a21\u5757\u662f\u6d4b\u8bd5\u7528\u7684"} +{"package": "xiaodnester", "pacakge-description": "UNKNOWN"} +{"package": "xiaoe-py", "pacakge-description": "No description available on PyPI."} +{"package": "xiaofeiwu", "pacakge-description": "No description available on PyPI."} +{"package": "xiaofeng_nester", "pacakge-description": "No description available on PyPI."} +{"package": "xiaofu", "pacakge-description": "No description available on PyPI."} +{"package": "xiaofufu", "pacakge-description": "No description available on PyPI."} +{"package": "xiaogang", "pacakge-description": "No description available on PyPI."} +{"package": "xiaogpt", "pacakge-description": "xiaogpthttps://user-images.githubusercontent.com/15976103/226803357-72f87a41-a15b-409e-94f5-e2d262eecd53.mp4Play ChatGPT and other LLM with Xiaomi AI Speaker\u652f\u6301\u7684 AI \u7c7b\u578bGPT3ChatGPTNew BingChatGLMGeminiBard\u901a\u4e49\u5343\u95eeWindows \u83b7\u53d6\u5c0f\u7c73\u97f3\u54cdDIDpip install miservice_forkset MI_USER=xxxxset MI_PASS=xxxmicli list\u5f97\u5230didset MI_DID=xxxx\u5982\u679c\u83b7\u53d6did\u62a5\u9519\u65f6\uff0c\u8bf7\u66f4\u6362\u4e00\u4e0b\u65e0\u7ebf\u7f51\u7edc\uff0c\u6709\u5f88\u5927\u6982\u7387\u89e3\u51b3\u95ee\u9898\u3002\u4e00\u70b9\u539f\u7406\u4e0d\u7528 root \u4f7f\u7528\u5c0f\u7231\u540c\u5b66\u548c ChatGPT \u4ea4\u4e92\u6298\u817e\u8bb0\u51c6\u5907ChatGPT id\u5c0f\u7231\u97f3\u54cd\u80fd\u6b63\u5e38\u8054\u7f51\u7684\u73af\u5883\u6216 proxypython3.8+\u4f7f\u7528pip install -U --force-reinstall xiaogpt\u53c2\u8003\u6211 fork \u7684MiService\u9879\u76ee README \u5e76\u5728\u672c\u5730 terminal \u8dd1micli list\u62ff\u5230\u4f60\u97f3\u54cd\u7684 DID \u6210\u529f\u522b\u5fd8\u4e86\u8bbe\u7f6e export MI_DID=xxx\u8fd9\u4e2a MI_DID \u7528runxiaogpt --hardware ${your_hardware} --use_chatgpt_apihardware \u4f60\u770b\u5c0f\u7231\u5c41\u80a1\u4e0a\u6709\u578b\u53f7\uff0c\u8f93\u5165\u8fdb\u6765\uff0c\u5982\u679c\u5728\u5c41\u80a1\u4e0a\u627e\u4e0d\u5230\u6216\u8005\u578b\u53f7\u4e0d\u5bf9\uff0c\u53ef\u4ee5\u7528micli mina\u627e\u5230\u578b\u53f7\u8dd1\u8d77\u6765\u4e4b\u540e\u5c31\u53ef\u4ee5\u95ee\u5c0f\u7231\u540c\u5b66\u95ee\u9898\u4e86\uff0c\u201c\u5e2e\u6211\"\u5f00\u5934\u7684\u95ee\u9898\uff0c\u4f1a\u53d1\u9001\u4e00\u4efd\u7ed9 ChatGPT \u7136\u540e\u5c0f\u7231\u540c\u5b66\u7528 tts \u56de\u7b54\u5982\u679c\u4e0a\u9762\u4e0d\u53ef\u7528\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u7528\u624b\u673a\u6293\u5305\uff0chttps://userprofile.mina.mi.com/device_profile/v2/conversation\u627e\u5230 cookie \u5229\u7528--cookie '${cookie}'cookie \u522b\u5fd8\u4e86\u7528\u5355\u5f15\u53f7\u5305\u88f9\u9ed8\u8ba4\u7528\u76ee\u524d ubus, \u5982\u679c\u4f60\u7684\u8bbe\u5907\u4e0d\u652f\u6301 ubus \u53ef\u4ee5\u4f7f\u7528--use_command\u6765\u4f7f\u7528 command \u6765 tts\u4f7f\u7528--mute_xiaoai\u9009\u9879\uff0c\u53ef\u4ee5\u5feb\u901f\u505c\u6389\u5c0f\u7231\u7684\u56de\u7b54\u4f7f\u7528--account ${account} --password ${password}\u5982\u679c\u6709\u80fd\u529b\u53ef\u4ee5\u81ea\u884c\u66ff\u6362\u5524\u9192\u8bcd\uff0c\u4e5f\u53ef\u4ee5\u53bb\u6389\u5524\u9192\u8bcd\u4f7f\u7528--use_chatgpt_api\u7684 api \u90a3\u6837\u53ef\u4ee5\u66f4\u6d41\u7545\u7684\u5bf9\u8bdd\uff0c\u901f\u5ea6\u7279\u522b\u5feb\uff0c\u8fbe\u5230\u4e86\u5bf9\u8bdd\u7684\u4f53\u9a8c,openai api, \u547d\u4ee4--use_chatgpt_api\u4f7f\u7528 gpt-3 \u7684 api \u90a3\u6837\u53ef\u4ee5\u66f4\u6d41\u7545\u7684\u5bf9\u8bdd\uff0c\u901f\u5ea6\u5feb, \u8bf7 google \u5982\u4f55\u7528openai api\u547d\u4ee4 --use_gpt3\u5982\u679c\u4f60\u9047\u5230\u4e86\u5899\u9700\u8981\u7528 Cloudflare Workers \u66ff\u6362 api_base \u8bf7\u4f7f\u7528--api_base ${url}\u6765\u66ff\u6362\u3002\u8bf7\u6ce8\u610f\uff0c\u6b64\u5904\u4f60\u8f93\u5165\u7684api\u5e94\u8be5\u662f'https://xxxx/v1'\u7684\u5b57\u6837\uff0c\u57df\u540d\u9700\u8981\u7528\u5f15\u53f7\u5305\u88f9\u53ef\u4ee5\u8ddf\u5c0f\u7231\u8bf4\u5f00\u59cb\u6301\u7eed\u5bf9\u8bdd\u81ea\u52a8\u8fdb\u5165\u6301\u7eed\u5bf9\u8bdd\u72b6\u6001\uff0c\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u72b6\u6001\u3002\u53ef\u4ee5\u4f7f\u7528--tts edge\u6765\u83b7\u53d6\u66f4\u597d\u7684 tts \u80fd\u529b\u53ef\u4ee5\u4f7f\u7528--tts openai\u6765\u83b7\u53d6 openai tts \u80fd\u529b\u53ef\u4ee5\u4f7f\u7528--use_langchain\u66ff\u4ee3--use_chatgpt_api\u6765\u8c03\u7528 LangChain\uff08\u9ed8\u8ba4 chatgpt\uff09\u670d\u52a1\uff0c\u5b9e\u73b0\u4e0a\u7f51\u68c0\u7d22\u3001\u6570\u5b66\u8fd0\u7b97..e.g.exportOPENAI_API_KEY=${your_api_key}xiaogpt--hardwareLX06--use_chatgpt_api# orxiaogpt--hardwareLX06--cookie${cookie}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3\u76f4\u63a5\u8f93\u5165\u8d26\u53f7\u5bc6\u7801xiaogpt--hardwareLX06--account${your_xiaomi_account}--password${your_password}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3 mute \u5c0f\u7c73\u7684\u56de\u7b54xiaogpt--hardwareLX06--mute_xiaoai--use_chatgpt_api# \u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94xiaogpt--hardwareLX06--mute_xiaoai--stream# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 gpt3 aiexportOPENAI_API_KEY=${your_api_key}xiaogpt--hardwareLX06--mute_xiaoai--use_gpt3# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 google \u7684 geminixiaogpt--hardwareLX06--mute_xiaoai--use_gemini--gemini_key${gemini_key}# \u5982\u679c\u4f60\u60f3\u4f7f\u7528\u963f\u91cc\u7684\u901a\u4e49\u5343\u95eexiaogpt--hardwareLX06--mute_xiaoai--use_qwen--qen_key${qwen_key}# \u5982\u679c\u4f60\u60f3\u7528 edge-ttsxiaogpt--hardwareLX06--cookie${cookie}--use_chatgpt_api--ttsedge# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 LangChain + SerpApi \u5b9e\u73b0\u4e0a\u7f51\u68c0\u7d22\u6216\u5176\u4ed6\u672c\u5730\u670d\u52a1\uff08\u76ee\u524d\u4ec5\u652f\u6301 stream \u6a21\u5f0f\uff09exportOPENAI_API_KEY=${your_api_key}exportSERPAPI_API_KEY=${your_serpapi_key}xiaogpt--hardwareLx06--use_langchain--mute_xiaoai--stream--openai_key${your_api_key}--serpapi_api_key${your_serpapi_key}\u4f7f\u7528 git clone \u8fd0\u884cexportOPENAI_API_KEY=${your_api_key}python3xiaogpt.py--hardwareLX06# orpython3xiaogpt.py--hardwareLX06--cookie${cookie}# \u5982\u679c\u4f60\u60f3\u76f4\u63a5\u8f93\u5165\u8d26\u53f7\u5bc6\u7801python3xiaogpt.py--hardwareLX06--account${your_xiaomi_account}--password${your_password}--use_chatgpt_api# \u5982\u679c\u4f60\u60f3 mute \u5c0f\u7c73\u7684\u56de\u7b54python3xiaogpt.py--hardwareLX06--mute_xiaoai# \u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94python3xiaogpt.py--hardwareLX06--mute_xiaoai--stream# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 gpt3 aiexportOPENAI_API_KEY=${your_api_key}python3xiaogpt.py--hardwareLX06--mute_xiaoai--use_gpt3# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 ChatGLM apipython3xiaogpt.py--hardwareLX06--mute_xiaoai--use_glm--glm_key${glm_key}# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 google \u7684 bardpython3xiaogpt.py--hardwareLX06--mute_xiaoai--use_bard--bard_token${bard_token}# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 google \u7684 geminipython3xiaogpt.py--hardwareLX06--mute_xiaoai--use_gemini--gemini_key${gemini_key}# \u5982\u679c\u4f60\u60f3\u4f7f\u7528\u963f\u91cc\u7684\u901a\u4e49\u5343\u95eepython3xiaogpt.py--hardwareLX06--mute_xiaoai--use_qwen--qen_key${qwen_key}# \u5982\u679c\u4f60\u60f3\u4f7f\u7528 LangChain+SerpApi \u5b9e\u73b0\u4e0a\u7f51\u68c0\u7d22\u6216\u5176\u4ed6\u672c\u5730\u670d\u52a1\uff08\u76ee\u524d\u4ec5\u652f\u6301 stream \u6a21\u5f0f\uff09exportOPENAI_API_KEY=${your_api_key}exportSERPAPI_API_KEY=${your_serpapi_key}python3xiaogpt.py--hardwareLx06--use_langchain--mute_xiaoai--stream--openai_key${your_api_key}--serpapi_api_key${your_serpapi_key}config.json\u5982\u679c\u60f3\u901a\u8fc7\u5355\u4e00\u914d\u7f6e\u6587\u4ef6\u542f\u52a8\u4e5f\u662f\u53ef\u4ee5\u7684, \u53ef\u4ee5\u901a\u8fc7--config\u53c2\u6570\u6307\u5b9a\u914d\u7f6e\u6587\u4ef6, config \u6587\u4ef6\u5fc5\u987b\u662f\u5408\u6cd5\u7684 JSON \u683c\u5f0f\n\u53c2\u6570\u4f18\u5148\u7ea7cli args > default > configpython3xiaogpt.py--configxiao_config.json# orxiaogpt--configxiao_config.json\u6216\u8005cpxiao_config.json.examplexiao_config.json\npython3xiaogpt.py\u82e5\u8981\u6307\u5b9a OpenAI \u7684\u6a21\u578b\u53c2\u6570\uff0c\u5982 model, temporature, top_p, \u8bf7\u5728config.json\u4e2d\u6307\u5b9a\uff1a{...\"gpt_options\":{\"temperature\":0.9,\"top_p\":0.9,}}\u5177\u4f53\u53c2\u6570\u4f5c\u7528\u8bf7\u53c2\u8003Open AI API \u6587\u6863\u3002\nChatGLM\u6587\u6863Bard-API\u53c2\u8003\u914d\u7f6e\u9879\u8bf4\u660e\u53c2\u6570\u8bf4\u660e\u9ed8\u8ba4\u503c\u53ef\u9009\u503chardware\u8bbe\u5907\u578b\u53f7account\u5c0f\u7231\u8d26\u6237password\u5c0f\u7231\u8d26\u6237\u5bc6\u7801openai_keyopenai\u7684apikeyserpapi_api_keyserpapi\u7684key \u53c2\u8003SerpAPIglm_keychatglm \u7684 apikeygemini_keygemini \u7684 apikey\u53c2\u8003qwen_keyqwen \u7684 apikey\u53c2\u8003bard_tokenbard \u7684 token \u53c2\u8003Bard-APIcookie\u5c0f\u7231\u8d26\u6237cookie \uff08\u5982\u679c\u7528\u4e0a\u9762\u5bc6\u7801\u767b\u5f55\u53ef\u4ee5\u4e0d\u586b\uff09mi_did\u8bbe\u5907diduse_command\u4f7f\u7528 MI command \u4e0e\u5c0f\u7231\u4ea4\u4e92falsemute_xiaoai\u5feb\u901f\u505c\u6389\u5c0f\u7231\u81ea\u5df1\u7684\u56de\u7b54trueverbose\u662f\u5426\u6253\u5370\u8be6\u7ec6\u65e5\u5fd7falsebot\u4f7f\u7528\u7684 bot \u7c7b\u578b\uff0c\u76ee\u524d\u652f\u6301gpt3,chatgptapi\u548cnewbingchatgptapitts\u4f7f\u7528\u7684 TTS \u7c7b\u578bmiedge\u3001openaitts_voiceTTS \u7684\u55d3\u97f3zh-CN-XiaoxiaoNeural(edge),alloy(openai)prompt\u81ea\u5b9a\u4e49prompt\u8bf7\u7528100\u5b57\u4ee5\u5185\u56de\u7b54keyword\u81ea\u5b9a\u4e49\u8bf7\u6c42\u8bcd\u5217\u8868[\"\u8bf7\"]change_prompt_keyword\u66f4\u6539\u63d0\u793a\u8bcd\u89e6\u53d1\u5217\u8868[\"\u66f4\u6539\u63d0\u793a\u8bcd\"]start_conversation\u5f00\u59cb\u6301\u7eed\u5bf9\u8bdd\u5173\u952e\u8bcd\u5f00\u59cb\u6301\u7eed\u5bf9\u8bddend_conversation\u7ed3\u675f\u6301\u7eed\u5bf9\u8bdd\u5173\u952e\u8bcd\u7ed3\u675f\u6301\u7eed\u5bf9\u8bddstream\u4f7f\u7528\u6d41\u5f0f\u54cd\u5e94\uff0c\u83b7\u5f97\u66f4\u5feb\u7684\u54cd\u5e94falseproxy\u652f\u6301 HTTP \u4ee3\u7406\uff0c\u4f20\u5165 http proxy URL\"\"gpt_optionsOpenAI API \u7684\u53c2\u6570\u5b57\u5178{}bing_cookie_pathNewBing\u4f7f\u7528\u7684cookie\u8def\u5f84\uff0c\u53c2\u8003\u8fd9\u91cc\u83b7\u53d6\u4e5f\u53ef\u901a\u8fc7\u73af\u5883\u53d8\u91cfCOOKIE_FILE\u8bbe\u7f6ebing_cookiesNewBing\u4f7f\u7528\u7684cookie\u5b57\u5178\uff0c\u53c2\u8003\u8fd9\u91cc\u83b7\u53d6deployment_idAzure OpenAI \u670d\u52a1\u7684 deployment ID\u53c2\u8003\u8fd9\u4e2a\u5982\u4f55\u627e\u5230deployment_idapi_base\u5982\u679c\u9700\u8981\u66ff\u6362\u9ed8\u8ba4\u7684api,\u6216\u8005\u4f7f\u7528Azure OpenAI \u670d\u52a1\u4f8b\u5982\uff1ahttps://abc-def.openai.azure.com/\u6ce8\u610f\u8bf7\u5f00\u542f\u5c0f\u7231\u540c\u5b66\u7684\u84dd\u7259\u5982\u679c\u8981\u66f4\u6539\u63d0\u793a\u8bcd\u548c PROMPT \u5728\u4ee3\u7801\u6700\u4e0a\u9762\u81ea\u884c\u66f4\u6539\u76ee\u524d\u5df2\u77e5 LX04\u3001X10A \u548c L05B L05C \u53ef\u80fd\u9700\u8981\u4f7f\u7528--use_command\uff0c\u5426\u5219\u53ef\u80fd\u4f1a\u51fa\u73b0\u7ec8\u7aef\u80fd\u8f93\u51faGPT\u7684\u56de\u590d\u4f46\u5c0f\u7231\u540c\u5b66\u4e0d\u56de\u7b54GPT\u7684\u60c5\u51b5\u3002\u8fd9\u51e0\u4e2a\u578b\u53f7\u4e5f\u53ea\u652f\u6301\u5c0f\u7231\u539f\u672c\u7684 tts.\u5728wsl\u4f7f\u7528\u65f6, \u9700\u8981\u8bbe\u7f6e\u4ee3\u7406\u4e3ahttp://wls\u7684ip:port(vpn\u7684\u4ee3\u7406\u7aef\u53e3), \u5426\u5219\u4f1a\u51fa\u73b0\u8fde\u63a5\u8d85\u65f6\u7684\u60c5\u51b5, \u8be6\u60c5\u62a5\u9519\uff1a Error communicating with OpenAIQA\u7528\u7834\u89e3\u4e48\uff1f\u4e0d\u7528\u4f60\u505a\u8fd9\u73a9\u610f\u4e5f\u6ca1\u7528\u554a\uff1f\u786e\u5b9e\u3002\u3002\u3002\u4f46\u662f\u633a\u597d\u73a9\u7684\uff0c\u6709\u7528\u5bf9\u4f60\u6765\u8bf4\u6ca1\u7528\uff0c\u5bf9\u6211\u4eec\u6765\u8bf4\u4e0d\u4e00\u5b9a\u5440\u60f3\u628a\u5b83\u53d8\u5f97\u66f4\u597d\uff1fPR Issue always welcome.\u8fd8\u6709\u95ee\u9898\uff1f\u63d0 Issue \u54c8\u54c8Exception: Errorhttps://api2.mina.mi.com/admin/v2/device_list?master=0&requestId=app_ios_xxx: Login failed@KJZH001\u8fd9\u662f\u7531\u4e8e\u5c0f\u7c73\u98ce\u63a7\u5bfc\u81f4\uff0c\u6d77\u5916\u5730\u533a\u65e0\u6cd5\u767b\u5f55\u5927\u9646\u7684\u8d26\u6237\uff0c\u8bf7\u5c1d\u8bd5cookie\u767b\u5f55\n\u65e0\u6cd5\u6293\u5305\u7684\u53ef\u4ee5\u5728\u672c\u5730\u90e8\u7f72\u5b8c\u6bd5\u9879\u76ee\u540e\u518d\u7528\u6237\u6587\u4ef6\u5939C:\\Users\\\u7528\u6237\u540d\u4e0b\u9762\u627e\u5230.mi.token\uff0c\u7136\u540e\u6254\u5230\u4f60\u65e0\u6cd5\u767b\u5f55\u7684\u670d\u52a1\u5668\u53bb\u82e5\u662flinux\u5219\u8bf7\u653e\u5230\u5f53\u524d\u7528\u6237\u7684home\u6587\u4ef6\u5939\uff0c\u6b64\u65f6\u4f60\u53ef\u4ee5\u91cd\u65b0\u6267\u884c\u5148\u524d\u7684\u547d\u4ee4\uff0c\u4e0d\u51fa\u610f\u5916\u5373\u53ef\u6b63\u5e38\u767b\u5f55\uff08\u4f46cookie\u53ef\u80fd\u4f1a\u8fc7\u4e00\u6bb5\u65f6\u95f4\u5931\u6548\uff0c\u9700\u8981\u91cd\u65b0\u83b7\u53d6\uff09\u8be6\u60c5\u8bf7\u89c1https://github.com/yihong0618/xiaogpt/issues/332\u89c6\u9891\u6559\u7a0bhttps://www.youtube.com/watch?v=K4YA8YwzOOADocker\u5e38\u89c4\u7528\u6cd5X86/ARM Docker Image:yihong0618/xiaogptdockerrun-eOPENAI_API_KEY=yihong0618/xiaogpt<\u547d\u4ee4\u884c\u53c2\u6570>\u5982dockerrun-eOPENAI_API_KEY=yihong0618/xiaogpt--account=--password=--hardware=--use_chatgpt_api\u4f7f\u7528\u914d\u7f6e\u6587\u4ef6xiaogpt\u7684\u914d\u7f6e\u6587\u4ef6\u53ef\u901a\u8fc7\u6307\u5b9avolume /config\uff0c\u4ee5\u53ca\u6307\u5b9a\u53c2\u6570--config\u6765\u5904\u7406\uff0c\u5982dockerrun-v:/configyihong0618/xiaogpt--config=/config/config.json\u672c\u5730\u7f16\u8bd1Docker Imagedockerbuild-txiaogpt.\u5982\u679c\u5728\u5b89\u88c5\u4f9d\u8d56\u65f6\u6784\u5efa\u5931\u8d25\u6216\u5b89\u88c5\u7f13\u6162\u65f6\uff0c\u53ef\u4ee5\u5728\u6784\u5efa Docker \u955c\u50cf\u65f6\u4f7f\u7528--build-arg\u53c2\u6570\u6765\u6307\u5b9a\u56fd\u5185\u6e90\u5730\u5740\uff1adockerbuild--build-argPIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple-txiaogpt.\u5982\u679c\u9700\u8981\u5728Apple M1/M2\u4e0a\u7f16\u8bd1x86dockerbuildxbuild--platform=linux/amd64-txiaogpt-x86.\u7b2c\u4e09\u65b9 TTS\u6211\u4eec\u76ee\u524d\u652f\u6301\u4e24\u79cd\u7b2c\u4e09\u65b9 TTS\uff1aedge/openaiedge-tts\u63d0\u4f9b\u4e86\u7c7b\u4f3c\u5fae\u8f6ftts\u7684\u80fd\u529bUsage\u4f60\u53ef\u4ee5\u901a\u8fc7\u53c2\u6570tts, \u6765\u542f\u7528\u5b83{\"tts\":\"edge\",\"tts_voice\":\"zh-CN-XiaoxiaoNeural\"}\u67e5\u770b\u66f4\u591a\u8bed\u8a00\u652f\u6301, \u4ece\u4e2d\u9009\u62e9\u4e00\u4e2aedge-tts--list-voices\u5728\u5bb9\u5668\u4e2d\u4f7f\u7528edge-tts\u7531\u4e8e Edge TTS \u542f\u52a8\u4e86\u4e00\u4e2a\u672c\u5730\u7684 HTTP \u670d\u52a1\uff0c\u6240\u4ee5\u9700\u8981\u5c06\u5bb9\u5668\u7684\u7aef\u53e3\u6620\u5c04\u5230\u5bbf\u4e3b\u673a\u4e0a\uff0c\u5e76\u4e14\u6307\u5b9a\u672c\u5730\u673a\u5668\u7684 hostname:dockerrun-v:/config-p9527:9527-eXIAOGPT_HOSTNAME=yihong0618/xiaogpt--config=/config/config.json\u6ce8\u610f\u7aef\u53e3\u5fc5\u987b\u6620\u5c04\u4e3a\u4e0e\u5bb9\u5668\u5185\u4e00\u81f4\uff0cXIAOGPT_HOSTNAME \u9700\u8981\u8bbe\u7f6e\u4e3a\u5bbf\u4e3b\u673a\u7684 IP \u5730\u5740\uff0c\u5426\u5219\u5c0f\u7231\u65e0\u6cd5\u6b63\u5e38\u64ad\u653e\u8bed\u97f3\u3002\u63a8\u8350\u7684 forkXiaoBot-> Go\u8bed\u8a00\u7248\u672c\u7684Fork, \u5e26\u652f\u6301\u4e0d\u540c\u5e73\u53f0\u7684UI\u611f\u8c22xiaomiPDM@Yonsm\u7684MiService@pjq\u7ed9\u4e86\u8fd9\u4e2a\u9879\u76ee\u975e\u5e38\u591a\u7684\u5e2e\u52a9@frostming\u91cd\u6784\u4e86\u4e00\u4e9b\u4ee3\u7801\uff0c\u652f\u6301\u4e86\u6301\u7eed\u4f1a\u8bdd\u529f\u80fd\u8d5e\u8d4f\u8c22\u8c22\u5c31\u591f\u4e86"} +{"package": "xiaogui", "pacakge-description": "Example Package"} +{"package": "xiaogui-ble", "pacakge-description": "xiaogui-bleSource Code:https://github.com/bluetooth-devices/xiaogui-bleBluetooth parser for xiaogui scalesInstallationInstall this via pip (or your favourite package manager):pip install xiaogui-bleUsageStart by importing it:importxiaogui_bleContributors \u2728Thanks goes to these wonderful people (emoji key):This project follows theall-contributorsspecification. Contributions of any kind welcome!CreditsThis package was created withCopierand thebrowniebroke/pypackage-templateproject template."} +{"package": "xiaoheauto", "pacakge-description": "Interface automation framework"} +{"package": "xiaohei", "pacakge-description": "=======\nXIAOHEIA Jianhua WU's projectThis package provides an easy way for setting up CI/CD tools on AWS and Azure.The XIAOHEI package works on Python versions:3.6.x and greater3.7.x and greater3.8.x and greaterPre-requisiteboto3access key & secret key of an AWS IAM user with Admin permissiongeneral AWS knowledgeAzure Credsgeneral Azure knowledgeSet up AWS EnvironmentThe quickest way to get started is to run theaws configurecommand::$ aws configure\nAWS Access Key ID: YourAwsAccessKey\nAWS Secret Access Key: YourAwsSecretKey\nDefault region name [ap-southeast-2]: ap-southeast-2\nDefault output format [None]: jsonFor more detail, follow the link athttps://github.com/aws/aws-cli/blob/develop/README.rst"} +{"package": "xiaohongshu", "pacakge-description": "\u5c0f\u7ea2\u4e66 Python SDK\u5c0f\u7ea2\u4e66Python SDKrequirementpython >= 3.6\u5b89\u88c5\u4f7f\u7528\u5b89\u88c5pypi:pipinstallxiaohongshuUsage\u4f7f\u7528\u793a\u4f8b\uff1afrom xiaohongshu.api.api import ARK\n\nark = ARK(\"xhs\", \"9a539709cafc1efc9ef05838be468a28\")\n\n# \u83b7\u53d6\u7269\u6d41\u516c\u53f8\u5217\u8868\nark.comm.get_express_list()\u63a5\u53e3\u8bf4\u660e\u516c\u5171\u63a5\u53e3\u5c01\u88c5\u5728comm\u4e2d\n\u8ba2\u5355\u76f8\u5173\u63a5\u53e3\u5c01\u88c5\u5728order\n\u5e93\u5b58\u76f8\u5173\u63a5\u53e3\u5c01\u88c5\u5728stock\n\u5546\u54c1\u76f8\u5173\u5c01\u88c5\u5728product.changelog[0.0.3] \u6dfb\u52a0\u7269\u6d41\u6a21\u5f0f\u63a5\u53e3\u7684\u8bf4\u660e\uff0c\u5b98\u65b9\u6587\u6863\u5b58\u5728\u9519\u8bef\u3002"} +{"package": "xiaohuohumax-test", "pacakge-description": "xiaohuohu-test"} +{"package": "xiaojunModule", "pacakge-description": "No description available on PyPI."} +{"package": "xiaokonglong", "pacakge-description": "No description available on PyPI."} +{"package": "xiaolanjing", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoli_nester", "pacakge-description": "UNKNOWN"} +{"package": "xiaolisensor", "pacakge-description": "xiaoli sensors sdk for python"} +{"package": "xiaolu-tool", "pacakge-description": "xiaolu-tool\u5c0f\u9e7f\u5185\u90e8\u4f7f\u7528\u7684Py\u5de5\u5177\u5305"} +{"package": "xiaomeilv", "pacakge-description": "Just a test demo"} +{"package": "xiaomi-ble", "pacakge-description": "Xiaomi BLEManage Xiaomi BLE devicesInstallationInstall this via pip (or your favourite package manager).pip install xiaomi-bleContributors \u2728Thanks goes to these wonderful people (emoji key):This project follows theall-contributorsspecification. Contributions of any kind welcome!CreditsThis package was created withCookiecutterand thebrowniebroke/cookiecutter-pypackageproject template."} +{"package": "xiaomicaiFibo-pip-fibo", "pacakge-description": "mymodule"} +{"package": "xiaomi-flashable-firmware-creator", "pacakge-description": "Xiaomi Flashable Firmware CreatorCreate flashable firmware zip from MIUI Recovery ROMs!Xiaomi Flashable Firmware Creator is a tool that generates flashable firmware-update packages from official MIUI ROMS.It supports creating untouched firmware, non-arb firmware, firmware + vendor flashable zip, and firmware-less ROMs from any local zip file or direct link of the zip file.InstallationYou can simply install this tool using Python pip.pipinstallxiaomi_flashable_firmware_creatorCLI Usagexiaomi_flashable_firmware_creator[-h](-FFIRMWARE|-NNONARB|-LFIRMWARELESS|-VVENDOR)[-oOUTPUT]Examples:Creating normal (untouched) firmware:xiaomi_flashable_firmware_creator-F[MIUIZIP]Creating non-arb firmware (without anti-rollback):xiaomi_flashable_firmware_creator-N[MIUIZIP]Creating firmware-less ROM (stock untouched ROM with just firmware removed):xiaomi_flashable_firmware_creator-L[MIUIZIP]Creating firmware + vendor flashable zip:xiaomi_flashable_firmware_creator-V[MIUIZIP]Using from other Python scriptsfromxiaomi_flashable_firmware_creator.firmware_creatorimportFlashableFirmwareCreator# initialize firmware creator object with the following parameters:# input_file: zip file to extract from. It can be a local path or a remote direct url.# process: Which mode should the tool use. This must be one of \"firmware\", \"nonarb\", \"firmwareless\" or \"vendor\".# out_dir: The output directory to store the extracted file in.firmware_creator=FlashableFirmwareCreator(input_zip,process,output_dir)# Now, you can either use auto() method to create the new zip file or do stuff at your own using firmware_creator public methods.new_zip=firmware_creator.auto()"} +{"package": "xiaomi-flashable-firmware-creator-gui", "pacakge-description": "Xiaomi Flashable Firmware Creator GUICreate flashable firmware zip from MIUI Recovery ROMs!Xiaomi Flashable Firmware Creator is a tool that generates flashable firmware-update packages from official MIUI ROMS.It supports creating untouched firmware, non-arb firmware, firmware + vendor flashable zip, and firmware-less ROMs.Features:Easy-to-use interfaceMultilanguage support (more than 25 languages!). Thanks to our community members!Screenshots:HereInstallationUsing pipYou can simply install this tool using Python pip.pipinstallxiaomi_flashable_firmware_creator_guiManual InstallationClone this repo usinggit cloneMake sure that you have Python3 installed with pip version higher than 19 on your device.Install the required packages by running the following command in cloned repo folder.pip3install.GUI Usage:Run the tool.xiaomi_flashable_firmware_creator_g"} +{"package": "xiaomi-mi-scale", "pacakge-description": "Xiaomi Mi ScaleLibraries to read weight measurements from Mi Body Composition Scales and Mi Body Fat Scales"} +{"package": "xiaomi-ndef", "pacakge-description": "Xiaomi NDEFEncode and decode NDEF message using Xiaomi NFC protocol.Usagepipinstallxiaomi-ndeffrompyndefimportNdefMessagefromxiaomi_ndefimportMiConnectData,XiaomiNfcPayload,V2NfcProtocolfromxiaomi_ndefimportndef,xiaomi,handoff,tag# ExampleNDEF_MSG_BYTES=b\"...\"# Parse ndefndef_msg=NdefMessage.parse(NDEF_MSG_BYTES)ndef_type=ndef.get_xiami_ndef_payload_type(ndef_msg)ndef_bytes=ndef.get_xiami_ndef_payload_bytes(ndef_msg,ndef_type)# Parse ndef payloadmi_connect_data=MiConnectData.parse(ndef_bytes)nfc_protocol=mi_connect_data.get_nfc_protocol()nfc_payload=mi_connect_data.to_xiaomi_nfc_payload(nfc_protocol)# Build new screen mirror recordhandoff_ndef_type,handoff_payload=xiaomi.new_handoff_screen_mirror(device_type=handoff.DeviceType.PC,bluetooth_mac=\"00:00:00:00:00:00\",enable_lyra=True)handoff_record=ndef.new_xiaomi_ndef_record(handoff_ndef_type,handoff_payload)# Build new ndef msghandoff_msg=NdefMessage(handoff_record)print(handoff_msg.to_bytes().hex())# Customize xiaomi ndefXiaomiNfcPayload(major_version=1,minor_version=11,id_hash=0,protocol=V2NfcProtocol,appData=tag.NfcTagAppData(major_version=1,minor_version=0,write_time=1666666666,flags=0,records=(tag.NfcTagDeviceRecord(device_type=tag.DeviceType.MI_SOUND_BOX,flags=0,device_number=0,attributes_map=tag.NfcTagDeviceRecord.new_attributes_map([tag.DeviceAttribute.WIFI_MAC_ADDRESS.new_pair(\"00:00:00:00:00:00\"),tag.DeviceAttribute.BLUETOOTH_MAC_ADDRESS.new_pair(\"00:00:00:00:00:01\")])),tag.NfcTagActionRecord(action=tag.Action.CUSTOM,condition=tag.Condition.AUTO,device_number=0,flags=0))))Related ProjectsPyNdefMiLinkNFCReferencePackage nameVersioncom.xiaomi.mi_connect_service3.1.453.10com.milink.service15.0.5.0.ceaac61.2919843com.xiaomi.smarthome9.1.501com.android.nfc14LicenseMIT License\n\nCopyright (c) 2024 XFY9326\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xiaoming-weather", "pacakge-description": "Xiaoming-weatherXiaoming weather provides personalized weather data strings for chinese user. Its weather data is captured fromhttp://www.weather.com.cnUsageFollowing query on terminal will provide you the weather details of the city you provided by option city code. You can get your city code in the URL by finding the city name onhttp://www.weather.com.cn. For example, China city ChongQing homepage ishttp://www.weather.com.cn/weather/101040100.shtml, the city code is 101040100.zhangyd@zhangyd-ubuntu:~$ xiaoming-weather -q 101160407\n\u5c0f\u660e\u5929\u6c14\uff1a\u4eca\u592917\u2103~24\u2103\uff0c\u660e\u5929\u9634\u8f6c\u591a\u4e91\uff0c\u6bd4\u4eca\u5929\u51c9\u4e00\u70b9\uff0c\u4f3c\u4e4e\u8981\u964d\u6e29\u4e86\u3002\n\u660e\u5929: \u9634\u8f6c\u591a\u4e91\n\u6e29\u5ea6: 10\u2103~20\u2103\n\u98ce\u529b: 3-4\u7ea7\u8f6c<3\u7ea7Helpzhangyd@zhangyd-ubuntu:~$ xiaoming-weather --help\nusage: xiaoming-weather [-h] [-q city-code]\n\nXiaoMing Weather\n\noptional arguments:\n -h, --help show this help message and exit\n -q city-code, --query city-code\n The specific city code from http://www.weather.com.cn"} +{"package": "xiaomipassive", "pacakge-description": "xiaomipassiveLYWSD02, LYWSD03MMC (custom firmware ATC) and MiFlora passive scannerInstallationgit clone https://github.com/afer92/xiaomipassive.git\ncd xiaomipassive\npip3 install .Command line toolxiaomipassivecOutput:mac: 80:EA:CA:89:xx:yy conductivity: 54 \u00b5S/cm (2023-02-26T00:42:25)\nmac: C4:7C:8D:64:xx:yyconductivity: 837 \u00b5S/cm (2023-02-26T00:42:25)\nmac: C4:7C:8D:6C:xx:yy light: 26 lux (2023-02-26T00:42:26)\n...\nA4:C1:38:09:xx:yy ATC_0990AB\n=================\nmac: A4:C1:38:09:xx:yyB rssi: -35 dBm (2023-02-26T00:42:39)\nmac: A4:C1:38:09:xx:yy temperature: 21.6 \u00b0C (2023-02-26T00:42:39)\nmac: A4:C1:38:09:xx:yy moisture: 32 % (2023-02-26T00:42:39)\nmac: A4:C1:38:09:xx:yyB battery: 93 % (2023-02-26T00:42:39)\nmac: A4:C1:38:09:xx:yy volt: 3.04 V (2023-02-26T00:42:39)class XiaomiPassiveScannerloop=asyncio.get_event_loop()scanner=XiaomiPassiveScanner(loop,callback,timeout_seconds=240)callbackFunction call at each received advertissementdefcallback(self,data):print(self.dump_result(data))Output:mac: C4:7C:8D:65:xx:yy conductivity: 376 \u00b5S/cm\nmac: 80:EA:CA:89:xx:yy light: 283 lux\nmac: 15:03:10:12:xx:yy moisture: 47.0 %\nmac: C4:7C:8D:65:xx:yy temperature: 20.8 \u00b0C\nmac: E7:2E:01:71:xx:yy battery: 18 %Functiondump_resultformat the data decoded in an advertisementDictionnarydata:{'ok':True,'mac':'C4:7C:8D:6C:xx:yy','sensor':4100,'stype':'temperature','svalue':ListContainer([123,0]),'typeCst':ListContainer([113,32,152,0]),'num':247,'tab':13,'name':'Flower care','rssi':-87,'value':12.3}timeout_secondsScan fortimeout_seconds, default=240sdevicesAftertimeout_secondsscanning, data collected for each mac addressFunctiondump_device(mac)format the data for one mac addressE7:2E:01:71:xx:yy LYWSD02\n=================\nmac: E7:2E:01:71:xx:yy rssi: -93 dBm (2023-02-24T19:34:19)\nmac: E7:2E:01:71:xx:yy moisture: 47.0 % (2023-02-24T19:32:44)\nmac: E7:2E:01:71:xx:yy temperature: 20.6 \u00b0C (2023-02-24T19:34:18)\nmac: E7:2E:01:71:xx:yy battery: 18 % (2023-02-24T19:33:37)\n\nC4:7C:8D:65:B1:1D Flower care\n=================\nmac: C4:7C:8D:65:xx:yy rssi: -81 dBm (2023-02-24T19:34:19)\nmac: C4:7C:8D:65:xx:yy light: 118 lux (2023-02-24T19:33:41)\nmac: C4:7C:8D:65:xx:yy moisture: 21 % (2023-02-24T19:33:52)\nmac: C4:7C:8D:65:xx:yy conductivity: 309 \u00b5S/cm (2023-02-24T19:34:04)\nmac: C4:7C:8D:65:xx:yy temperature: 20.7 \u00b0C (2023-02-24T19:34:15)Example#!/usr/bin/python3fromxiaomipassiveimportxiaomipassiveasxiaomiimportasynciodefmain():defcallback(self,result):print(self.dump_result(result))defget_data():loop=asyncio.get_event_loop()scanner=xiaomi.XiaomiPassiveScannermiflora_scanner=scanner(loop,callback,timeout_seconds=240)try:loop.run_until_complete(miflora_scanner.run())exceptKeyboardInterruptaserr:print(err)formac,deviceinmiflora_scanner.xdevices.items():print(device)get_data()if__name__=='__main__':exit(main())"} +{"package": "xiaomirouter", "pacakge-description": "No description available on PyPI."} +{"package": "xiaomitv", "pacakge-description": "Xiaomi TV"} +{"package": "xiaomo", "pacakge-description": "No description available on PyPI."} +{"package": "xiaomusic", "pacakge-description": "xiaomusic\u4f7f\u7528\u5c0f\u7231/\u7ea2\u7c73\u97f3\u7bb1\u64ad\u653e\u97f3\u4e50\uff0c\u97f3\u4e50\u4f7f\u7528 yt-dlp \u4e0b\u8f7d\u3002\u8fd0\u884c\u4f7f\u7528 install_dependencies.sh \u4e0b\u8f7d\u4f9d\u8d56\u4f7f\u7528 pdm \u5b89\u88c5\u73af\u5883\u53c2\u8003xiaogpt\u8bbe\u7f6e\u597d\u73af\u5883\u53d8\u91cfexportMI_USER=\"xxxxx\"exportMI_PASS=\"xxxx\"exportMI_DID=00000exportXIAOMUSIC_SEARCH='bilisearch:'\u7136\u540e\u542f\u52a8\u5373\u53ef\u3002\u9ed8\u8ba4\u76d1\u542c\u4e86\u7aef\u53e3 8090 , \u4f7f\u7528\u5176\u4ed6\u7aef\u53e3\u81ea\u884c\u4fee\u6539\u3002pdmrunxiaomusic.py\u652f\u6301\u53e3\u4ee4\u64ad\u653e\u6b4c\u66f2\u64ad\u653e\u6b4c\u66f2+\u6b4c\u540d \u6bd4\u5982\uff1a\u64ad\u653e\u6b4c\u66f2\u5468\u6770\u4f26\u6674\u5929\u4e0b\u4e00\u9996\u5355\u66f2\u5faa\u73af\u5168\u90e8\u5faa\u73af\u9690\u85cf\u73a9\u6cd5: \u5bf9\u5c0f\u7231\u540c\u5b66\u8bf4\u64ad\u653e\u6b4c\u66f2\u5c0f\u732a\u4f69\u5947\u7684\u6545\u4e8b\uff0c\u4f1a\u64ad\u653e\u5c0f\u732a\u4f69\u5947\u7684\u6545\u4e8b\u3002\u5df2\u6d4b\u8bd5\u8bbe\u5907\"L07A\": (\"5-1\", \"5-5\"), # Redmi\u5c0f\u7231\u97f3\u7bb1Play(l7a)\u652f\u6301\u97f3\u4e50\u683c\u5f0fmp3flac\u672c\u5730\u97f3\u4e50\u4f1a\u641c\u7d22 mp3 \u548c flac \u683c\u5f0f\u7684\u6587\u4ef6\uff0c\u4e0b\u8f7d\u7684\u6b4c\u66f2\u662f mp3 \u683c\u5f0f\u7684\u3002\u5728 Docker \u91cc\u4f7f\u7528dockerrun-eMI_USER=-eMI_PASS=-eMI_DID=-eMI_HARDWARE='L07A'-eXIAOMUSIC_PROXY=-eXIAOMUSIC_HOSTNAME=192.168.2.5-eXIAOMUSIC_SEARCH='bilisearch:'-p8090:8090-v./music:/app/musichanxi/xiaomusicXIAOMUSIC_SEARCH \u53ef\u4ee5\u914d\u7f6e\u4e3a 'bilisearch:' \u8868\u793a\u6b4c\u66f2\u4ece\u54d4\u54e9\u54d4\u54e9\u4e0b\u8f7d;\u914d\u7f6e\u4e3a 'ytsearch:' \u8868\u793a\u6b4c\u66f2\u4ece youtube \u4e0b\u8f7d\u3002XIAOMUSIC_PROXY \u7528\u4e8e\u914d\u7f6e\u4ee3\u7406\uff0c\u9ed8\u8ba4\u4e3a\u7a7a;\u5f53 XIAOMUSIC_SEARCH \u914d\u7f6e\u4e3a 'ytsearch:' \u65f6\u5728\u56fd\u5185\u9700\u8981\u7528\u5230\u3002MI_HARDWARE \u662f\u5c0f\u7c73\u97f3\u7bb1\u7684\u578b\u53f7\uff0c\u9ed8\u8ba4\u4e3a'L07A'\u6ce8\u610f\u7aef\u53e3\u5fc5\u987b\u6620\u5c04\u4e3a\u4e0e\u5bb9\u5668\u5185\u4e00\u81f4\uff0c XIAOMUSIC_HOSTNAME \u9700\u8981\u8bbe\u7f6e\u4e3a\u5bbf\u4e3b\u673a\u7684 IP \u5730\u5740\uff0c\u5426\u5219\u5c0f\u7231\u65e0\u6cd5\u6b63\u5e38\u64ad\u653e\u3002\u53ef\u4ee5\u628a /app/music \u76ee\u5f55\u6620\u5c04\u5230\u672c\u5730\uff0c\u7528\u4e8e\u4fdd\u5b58\u4e0b\u8f7d\u7684\u6b4c\u66f2\u3002XIAOMUSIC_PROXY \u53c2\u6570\u683c\u5f0f\u53c2\u8003 yt-dlp \u6587\u6863\u8bf4\u660e:Use the specified HTTP/HTTPS/SOCKS proxy. To\nenable SOCKS proxy, specify a proper scheme,\ne.g. socks5://user:pass@127.0.0.1:1080/.\nPass in an empty string (--proxy \"\") for\ndirect connection\u89c1https://github.com/hanxi/xiaomusic/issues/2\u548chttps://github.com/hanxi/xiaomusic/issues/11\u672c\u5730\u7f16\u8bd1Docker Imagedockerbuild-txiaomusic.docker compose \u793a\u4f8b\u4f7f\u7528\u54d4\u54e9\u54d4\u54e9\u4e0b\u8f7d\u6b4c\u66f2:version:'3'services:xiaomusic:image:hanxi/xiaomusiccontainer_name:xiaomusicrestart:unless-stoppedports:-8090:8090volumes:-./music:/app/musicenvironment:MI_USER:'\u5c0f\u7c73\u8d26\u53f7'MI_PASS:'\u5c0f\u7c73\u5bc6\u7801'MI_DID:00000MI_HARDWARE:'L07A'XIAOMUSIC_SEARCH:'bilisearch:'XIAOMUSIC_HOSTNAME:'192.168.2.5'\u4f7f\u7528 youtobe \u4e0b\u8f7d\u6b4c\u66f2:version:'3'services:xiaomusic:image:hanxi/xiaomusiccontainer_name:xiaomusicrestart:unless-stoppedports:-8090:8090volumes:-./music:/app/musicenvironment:MI_USER:'\u5c0f\u7c73\u8d26\u53f7'MI_PASS:'\u5c0f\u7c73\u5bc6\u7801'MI_DID:00000MI_HARDWARE:'L07A'XIAOMUSIC_SEARCH:'ytsearch:'XIAOMUSIC_PROXY:'http://192.168.2.5:8080'XIAOMUSIC_HOSTNAME:'192.168.2.5'\u7b80\u6613\u7684\u63a7\u5236\u9762\u677f\u6d4f\u89c8\u5668\u8fdb\u5165http://192.168.2.5:8090ip \u662f XIAOMUSIC_HOSTNAME \u8bbe\u7f6e\u76848090 \u662f\u9ed8\u8ba4\u7aef\u53e3\u611f\u8c22xiaomiPDMxiaogptMiServiceyt-dlpStar History"} +{"package": "xiaoniu-tr-free", "pacakge-description": "xiaoniu-tr-freexiaoniu translate for free -- local cache plus throttling (1.5 calls/s from 201st call on). Let's hope it lasts.Update: fix query=50980349 and source=\"text\", resort to use getInstallationpip install -U xiaoniu-tr-freeorInstall (pip or whatever) necessary requirements, e.g.pip install requests_cache langidorpip install -r requirements.txtDrop the file xiaoniu_tr.py in any folder in your PYTHONPATH (check with import sys; print(sys.path)or clone the repo (e.g.,git clone https://github.com/ffreemt/xiaoniu-tr-free.gitor downloadhttps://github.com/ffreemt/xiaoniu-tr-free/archive/master.zipand unzip) and change to the xiaoniu-tr-free folder and do apython setup.py developUsagefrom xiaoniu_tr import xiaoniu_tr\nprint(xiaoniu_tr('hello world')) # -> '\u4f60\u597d\u4e16\u754c'\nprint(xiaoniu_tr('Good morning', to_lang='de')) # ->'Guten Morgen, wow'\nprint(xiaoniu_tr('hello world', to_lang='fr')) # ->'Bonjour le monde'\nprint(xiaoniu_tr('hello world', to_lang='ja')) # ->'\u3053\u3093\u306b\u3061\u306f\u4e16\u754c'AcknowledgmentsThanks to everyone whose code was used"} +{"package": "xiaopy", "pacakge-description": "No description available on PyPI."} +{"package": "xiaopydesktop", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoranli", "pacakge-description": "A project used to setup development environment, especially the rcfiles(aka dotfiles)After pip install, the shell command \"zhijiang\" could be used, \"zhijiang info\" could be used to get help."} +{"package": "xiaoriben", "pacakge-description": "\u867d\u7136\u8bf4\u8fd9\u4e2a\u5e93\u4e0d\u662f\u5f88\u725b\u903c\uff0c\u4f46\u662f\u6211\u7684\u63cf\u8ff0\u6587\u6863\uff0c\u975e\u5e38\u725b\u903c\uff0c\u4f1a\u8ba9\u522b\u4eba\uff0c\u89c9\u5f97\u6211\u7684\u5e93\u975e\u5e38\u725b\u903c\u659c\u4f53\u52a0\u7c97this is my code"} +{"package": "xiaoshen", "pacakge-description": "\u6d4b\u8bd5\u4e00\u4e0bpypi\u7684\u53d1\u5e03"} +{"package": "xiaoshuaib", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiaoshuaibqingyun891", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiaoTangPypi", "pacakge-description": "myPypiTest\u6211\u7b80\u5355\u6d4b\u8bd5\u7684\u4f8b\u5b50"} +{"package": "xiaowei", "pacakge-description": "UNKNOWN"} +{"package": "xiaoweiahfang", "pacakge-description": "Example PackageI am a Xiao Wei or Ah Fang, a chat robot made by David Shem."} +{"package": "xiaowupkg", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoxiong", "pacakge-description": "# xiaoxiong#### \u4ecb\u7ecd\n\u5c0f\u718a\u718a#### \u8f6f\u4ef6\u67b6\u6784\n\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e#### \u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx#### \u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx#### \u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request#### \u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2 [blog.gitee.com](https://blog.gitee.com)\u4f60\u53ef\u4ee5 [https://gitee.com/explore](https://gitee.com/explore) \u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76ee[GVP](https://gitee.com/gvp) \u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518c [https://gitee.com/help](https://gitee.com/help)Gitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76ee [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)"} +{"package": "xiaoxiongfjhasj", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoyan", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoyanshitool", "pacakge-description": "UNKNOWN"} +{"package": "xiaoye", "pacakge-description": "README0706hello world!"} +{"package": "xiaoyeML", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoye-ml", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiaoyu", "pacakge-description": "No description available on PyPI."} +{"package": "xiaoyun", "pacakge-description": "No description available on PyPI."} +{"package": "xiaozezhong", "pacakge-description": "\u8096\u6cfd\u4e2d\u8096\u6cfd\u4e2d"} +{"package": "xiaozhiling", "pacakge-description": "No description available on PyPI."} +{"package": "xiaozhu", "pacakge-description": "\u4e00\u4e9b\u5b9e\u7528\u7684\u65b9\u6cd5"} +{"package": "xiaozhupeiqiSuperMath", "pacakge-description": "No description available on PyPI."} +{"package": "xia-pattern", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pattern-python", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pattern-xia", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pfcu", "pacakge-description": "XIA PFCU libraryThis library is used to control basic features of XIA PFCU equipment.\nIt is composed of a core library, an optional simulator and an optionaltangodevice server.It has been tested with PF4 model, but should work with\nother models too.It can be used with either with a direct serial line (read below\non the recommended way to setup a serial line connection) or remotely\nthrough TCP socket (either raw socket or rfc2217). In the latter case\nthe master device to which the Julabo serial line is connected must\nprovide a raw socket or rfc2217 interface.InstallationFrom within your favorite python environment type:$ pip install xia-pfcuLibraryThe core of the library consists of PFCU object.\nTo create a PFCU object you need to pass a connection object.\nA compatible connection object can be created using the companionconniolibrary which\nshould already be installed as a dependency.Here is how to connect to a PFCU through a local serial line:fromconnioimportconnection_for_urlfromxia_pfcuimportPFCUasyncdefmain():conn=connection_for_url(\"serial://dev/ttyS0\")dev=PFCU(conn)raw_status=awaitdev.raw_status()print(raw_status)status=awaitdev.status()ifstatus['shutter_enabled']:shutter_status=(awaitdev.shutter_status()).nameelse:shutter_status=\"Disabled\"print(f\"Shutter status:{shutter_status}\")# open shutterawaitdev.open_shutter()asyncio.run(main())Serial lineTo access a serial line based PFCU device it is strongly recommended you spawn\na serial to tcp bridge usingser2net,ser2sockorsocatAssuming your device is connected to/dev/ttyS0and the baudrate is set to 9600,\nhere is how you could use socat to expose your device on the machine port 5000:socat -v TCP-LISTEN:5000,reuseaddr,fork file:/dev/ttyS0,rawer,b9600,cs8,eol=10,icanon=1It might be worth considering starting socat, ser2net or ser2sock as a service usingsupervisororcircus.SimulatorA PFCU simulator is provided.Before using it, make sure everything is installed with:$ pip install xia-pfcu[simulator]Thesinstrumentsengine is used.To start a simulator you need to write a YAML config file where you define\nhow many devices you want to simulate and which properties they hold.The following example exports 1 hardware device with a minimal configuration\nusing default values:# config.ymldevices:-class:PFCUpackage:xia_pfcu.simulatortransports:-type:serialurl:/tmp/pfcu-1To start the simulator type:$ sinstruments-server -c ./config.yml --log-level=DEBUG\n2020-09-14 10:42:27,592 INFO simulator: Bootstraping server\n2020-09-14 10:42:27,592 INFO simulator: no backdoor declared\n2020-09-14 10:42:27,592 INFO simulator: Creating device PFCU ('PFCU')\n2020-09-14 10:42:27,609 INFO simulator: Created symbolic link \"/tmp/pfcu-1\" to simulator pseudo terminal '/dev/pts/3'\n2020-09-14 10:42:27,609 INFO simulator.PFCU[/tmp/pfcu-1]: listening on /tmp/pfcu-1 (baud=None)(To see the full list of options typesinstruments-server --help)You can access it as you would a real hardware. Here is an example using python\nserial library on the same machine as the simulator:$python>>>fromconnioimportconnection_for_url>>>fromxia_pfcuimportPFCU>>>conn=connection_for_url(\"serial:///tmp/pfcu-cf31\",concurrency=\"syncio\")>>>dev=PFCU(conn)>>>conn.open()>>>print(dev.status())%PFCU15OKPFCUv1.0(c)XIA1999AllRightsReservedCHANNELIN/OUT(FPanelTTLRS232)Shorted?Open?1OUTOUTOUTOUTNONO2OUTOUTOUTOUTNONO3INOUTOUTINNONO4OUTOUTOUTOUTNONORS232ControlEnabled:YESRS232ControlOnly:NOShutterModeEnabled:NOExposureDecimation:1Tango serverAtangodevice server is also provided.Make sure everything is installed with:$ pip install xia-pfcu[tango]Register a PFCU tango server in the tango database:$ tangoctl server add -s PFCU/test -d PFCU test/pfcu/1\n$ tangoctl device property write -d test/pfcu/1 -p address -v \"tcp://controls.lab.org:17890\"(the above example usestangoctl. You would need\nto install it withpip install tangoctlbefore using it. You are free to use any other\ntango tool likefandangoor Jive)Launch the server with:$ PFCU test"} +{"package": "xia-prompts", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-prompts-design-software", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-puller", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-puller-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pusher", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pusher-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-pypi", "pacakge-description": "My_pypi\u81ea\u5efa\u5305\uff0c\u7528\u4e8e\u5bfc\u5165\u4e00\u4e9b\u5e38\u89c1\u7684\u529f\u80fd\u4f9d\u7167\u6559\u7a0b\u5b98\u7f51\u4e2a\u4eba"} +{"package": "xia-sendinblue", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-service", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-service-cloudflare", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xiashan", "pacakge-description": "UNKNOWN"} +{"package": "xia-sso-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-storer", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-storer-gcs", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-synchronizer", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-token-flask", "pacakge-description": "Welcome to use X-I-A\u2019s software"} +{"package": "xia-user", "pacakge-description": "-.. image::https://img.shields.io/pypi/v/xia-user.svg?color=blue- :alt: PyPI-Server\n- :target:https://pypi.org/project/xia-user/+Introduction\n+=============================-====================================\n-X-I-A\n-====================================\n+Welcome to use X-I-A\u2019s software-Quick start\n+"} +{"package": "xiax", "pacakge-description": "xiax: eXtract or Insert artwork And sourcecode to/from XmlFree software provided by Kent Watsen (Watsen Networks)PurposeTo aid in the construction (and deconstruction) of submittablexml2rfcv2 [RFC 7749] and v3 [RFC 7991] documents.For authors : automates common steps.For reviewers : ensures correctness and facilitates validations.For copyeditors : provides safety net for making changes.+----------+ +----------+ pack +---------+\n | | prime | | ------------> | |\n | source | -----------> | primed | | ready |\n | | | | <------------ | |\n +----------+ +----------+ unpack +---------+\n | ^\n | |\n +------+\n validateInstallation`pip install xiax`Developed on Python 3.7Tested on Python 3.6, 3.5, 3.4, and 2.7.Usageusage: xiax [-h] [-v] [-d] [-f] source [destination]\n\neXtract or Insert artwork And sourcecode to/from Xml\n\npositional arguments:\n source source XML document to extract from or insert into.\n destination destination file or directory. If unspecified, then\n the current working directory is assumed.\n\noptional arguments:\n -h, --help show this help message and exit\n -v, --version show version number and exit.\n -d, --debug print verbose output to stdout.\n -f, --force allow existing files to be overwritten.\n\nExit status code: 0 on success, non-0 on error. \nDebug output goes to stdout. Error output goes to stderr.Auto-sensing Mode:The \"source\" XML file is scanned for an XML comment beginning with the\nstring \"##xiax-block-v1:\". If this string is found, then extraction\nproceeds, else insertion proceeds.Referring to the diagram above:\"insertion\" refers to both priming and packing.\"extraction\" refers only to unpacking.Insertion:Insert local file content fromandelements\ninto \"source\", saving the resulting \"packed\" XML file into as described\nbelow.The \"source\" parameter must refer to an XML file containing theelement.If the \"destination\" parameter ends with \".xml\", the argument is used\nto determined both the destination directory, as well as the draft's\nrevision number. For instance, \"./foo-03.xml\" would set the current\nworking directory to be the destination directory, and \"03\" as the\nrevision number to be used.If the \"destination\" parameter is present, but does not end with \".xml\",\nthen the argument is used only to determined the destination directory.\nThe system will try to determine the draft revision number as the next\nlogicalgit tag(see [Git Tagging] below) and, if that doesn't work,\nwill assume \"-00\". The determined revision number is placed into the\n\"source\" filename, either by replacing \"latest\" with it (if found), or\nby appending it (e.g., both \"foo.xml\" and \"foo-latest.xml\" might result\nin foo-00.xml).If the \"destination\" parameter is not provided, then the current working\ndirectory is used (same as if \"./\" had been passed).In the source XML file, theelementdocNameattribute may\ninclude the suffix \"-latest\", which will be replaced with the determined\nrevision number. This is recommended. Theelement should also\ndefined the \"xiax\" prefix (e.g.,xmlns:xiax=\"https://watsen.net/xiax\").In the source XML file, onlyandelements\nhaving axiax:src(for \"source') orxiax:gen(for \"generate\")\nattribute are processed (it is an error if both attributes appear for\nthe same element). Both attributes take a URI, but the URI must specify\na local file under the draft document's directory.Valid \"xiax:src\" attribute examples:xiax:src=\"ietf-foobar@YYYY-MM-DD.yang\"xiax:src=\"images/ex-ascii-art.txt\"xiax:src=\"file:ietf-foobar@YYYY-MM-DD.yang\"xiax:src=\"file:images/ex-ascii-art.txt\"Invalid \"src\" attribute examples:xiax:src=\"/ex-ascii-art.txt\"xiax:src=\"c:/ex-ascii-art.txt\"xiax:src=\"a/../../ex-ascii-art.txt\"xiax:src=\"file:///ex-ascii-art.txt\"xiax:src=\"file://c/ex-ascii-art.txt\"xiax:src=\"file:a/../../ex-ascii-art.txt\"Notes:Thexiax:genandxiax:valattributes have the same pattern.Any strings containing \"YYYY-MM-DD\" (either in the \"source\"\nXML file, or in the linked filename or content) will be updated\nto have the value of the current.It is an error if there is preexisting content for theorelement. A solution for inserting \"fallback\" content\nwhile preserving anxml2rfc\"src\" attribute to binary (i.e., SVG)\ncontent has yet to be defined.In addition to thexiax:srcandxiax:genattributes, an optionalxiax:val(for \"validate\") attribute may be specified, to define\nparameters for validating theandelement's\ncontent. Additionally, axiax:markersattribute may be specified\nto wrap the content with theandtags\ndescribed in RFC 8407 Section 3.2.Additionally,xiaxwill automatically fold any content containing\na line exceeding 69 characters, using the algortihm defined in\ndraft-ietf-netmod-artwork-folding. (Note: this logic isn't\nimplemented yet).The result of the insertion process is the creation of the determined\ndestination XML file in which allxiax:prefixed attrbutes in the,, andelements have been removed,\nand an XML comment beginning with the string \"##xiax-block-v1:\" is\nadded to the end of the XML file.It is an error for the destination file to already exist, unless the\n\"force\" flag is specified, in which case the destination file will be\noverwritten.The source XML file is never modified.Extraction:Extract the content ofandelements, having\nan entry in the \"xiax-block\" comment into the specified extraction\ndirectory.If the \"destination\" parameter ends with \".xml\", the argument is used\nto determined both the extraction directory, as well as the unpacked\ndraft name. Note: the \"unpacked\" (or \"primed\") XML file is extracted\nonly when the destination parameter ends with \".xml\".If the \"destination\" parameter is present, but does not end with \".xml\",\nthen the argument is used only to determined the extraction directory\n(the unpacked draft XML file will not be saved).If the \"destination\" parameter is not provided, then the current working\ndirectory is used as the extraction directory. This is the same as if\n\"./\" were passed.Onlyandelements having entries in the\n\"xiax-block\" are extracted. The extracted files are relative to the\nextraction directory. Subdirectories will be created as needed.In addition to the element's content being extracted, all the additional\nfiles used to generate and validate the content are also extracted.\nThis not only includes the files referenced by thexiax:genandxiax:valattributes, but also any additional local files files\nreferenced by those files.It is an error if any file already exists, unless the \"force\" flag is\nspecified, in which case the file will be overwritten.It is planned to implement the ability to automatically validate thexiax:srcandxiax:gencontent, but this is somewhat dependent on\ninput from users, as it may be sufficient the know that the validations\nran authomatically during \"insertion\" and that they may be manually\nrun after the extraction.The source XML file is never modified.Round-trippingIt is possible to runxiaxin a loop:# xiax -f -s packed-00.xml -d unpacked-00.xml\n # xiax -f -s unpacked-00.xml -d packed-00.xmlGit TaggingGit tags should (assuminggitis being used as the SCM) be used to\ntag milestones. In the context of authoring documents, the milestones\nare the published versions of the draft in progress.By example, assuming that draft--03 has already been published,\nwhich implies that 02, 01, and 00 were published before as well, thanget tagshould produce the following result in the working directory:# git tag\ndraft--00\ndraft--01\ndraft--02\ndraft--03Special SupportTypically the \"source\" parameter specifies anxml2rfcXML file but, in\norder to support the development of the \"generate\" and \"validate\" files,\nthese XML files MAY be passed as the \"source\" parameter instead, in which\ncasexiaxjust processes the single file.If the \"source\" parameter specifies a \"generate\" file, the \"destination\"\nparameter, if passed, will be ignored, as the generated content is sent\nto STDOUT.If the \"source\" parameter specifies a \"validate\" file, the \"destination\"\nparameter must specify the relative path to the file to be validated.Runningxiaxthis way must occur from the draft document's top-level\ndirectory (the current working directory is the document's directory)."} +{"package": "xibless", "pacakge-description": "xiblessis a library that generates Objective-C code that builds Cocoa UIs. The goal of this library\nis to replace XIBs in XCode and, if you want, get rid of XCode altogether.Withxibless, instead of designing UIs with a WYSIWYG editor, you build them in a Python script,\nsimilarly to what you do when you build Qt UIs without the Designer. For example, a script like this:result = Window(330, 110, \"Tell me your name!\")\nnameLabel = Label(result, text=\"Name:\")\nnameField = TextField(result, text=\"\")\nhelloLabel = Label(result, text=\"\")\nbutton = Button(result, title=\"Say Hello\")\n\nnameLabel.width = 45\nnameLabel.moveTo(Pack.UpperLeft)\nnameField.moveNextTo(nameLabel, Pack.Right, align=Pack.Middle)\nnameField.fill(Pack.Right)\nhelloLabel.moveNextTo(nameLabel, Pack.Below, align=Pack.Left)\nhelloLabel.fill(Pack.Right)\nbutton.moveNextTo(helloLabel, Pack.Below, align=Pack.Right)\nnameField.setAnchor(Pack.UpperLeft, growX=True)\nhelloLabel.setAnchor(Pack.UpperLeft, growX=True)\nbutton.setAnchor(Pack.UpperRight)would generate Objective-C code that build a form with a name field, a text label and a button. The\nsecond part of the script places the widgets on the form appropriately.Although xibless is written in Python, the Objective-C code it generates has no Python dependency,\nso this tool is suitable for any Cocoa developer.xiblessruns on Python 2.7 and up. This means that if you\u2019re on OS X 10.7 or newer, you can use\nthe built-in Python. Otherwise, you\u2019ll have to install a more recent version of Python.Installation and usage:Please refer to theDocumentationfor installation and usage instructions.Early Developmentxiblessis in very early development and the number of rough edges at the moment are\nincalculable. There are no error message for invalid UI scripts, so it might be very hard, for now,\nto figure out why your scripts don\u2019t work.ChangesVersion 0.5.2 \u2013 2016/01/09FixMenu.removeItem()bug resulting in un-compilable code generation.Fix compilation warnings with identifier-lessTabViewItem.Version 0.5.1 \u2013 2013/11/10Fixed a crash with UI scripts containing non-ascii textVersion 0.5.0 \u2013 2012/10/08Added VHLayout.Added Box.In View, added delegate, fixedHeight, fixedWidth and accessibilityDescription attributes as well\nas moveTo() (a more powerful version of packToCorner()) and fillAll() methods.In Segment, added image and accessibilityDescription attributes.Added SplitView.dividerStyle and added documentation for a direct split view hierarchy.Added TableView.borderType and View.focusRingType.Added Button.borderedAdded MenuItem.stateAdded TabView.tabViewType.Added TextField.usesSingleLineMode.Added margin and align arguments to layouts.Deprecated View.packToCorner().Layouts can now contain sublayouts.Allow Color() to receive values in the range of 0-255 in addition to 0.0-1.0.Don\u2019t localize strings containing only \u201c-\u201d (they\u2019re used to indicate a separator menu item).RadioButtons\u2019 height now depends on the number of rows it has.Fixed filler resizing in layouts in cases where there are other views next to the filler.Allow UI scripts to import units that are from the same folder.Replaced Button.keyEquivalent with Button.shortcut.Fixed runtemplate so that the XiblessSupport unit is compiled in the RunUI executable.Fixed a bug where we would sometimes end up with two generated item with the same varname.Always set growX/growY to False in setAnchor() for views that have a fixed width/height.The \u201ctext\u201d argument of TextField\u2019s constructor is now optional.Support sides and middle in View.setAnchor().Generated units now have a comment indicating generation time and xibless version.Moved TextField.alignment down to ControlOnly copy XiblessSupport unit when it changed, thus avoiding needless recompilation.Fixed TabView\u2019s layout deltas for cases where there\u2019s no tabs.Support shortcuts involving the \u2018+\u2019 character.Improved default margins in layouts, control heights and all other little tweaks of this sort.Version 0.4.1 \u2013 2012/08/08Added NLSTR to UI scripts namespace.Don\u2019t wrap Window.autosaveName in localization calls.Fixed a bug causing some strings not to be wrapped in localization calls.Set RadioButton\u2019s \u201cautosizesCells\u201d to True upon creation.Version 0.4.0 \u2013 2012/07/30Added Panel, SplitView, OutlineView, ListView, Toolbar, SegmentedControl, SearchField, Slider\nand NumberFormatter.Added Layouts.Added support for many, many, many new attributes, constants and types.Now generates a \u201c.h\u201d to go alongside the generated unit.Added Property and its subclasses, an easier way to add support for new attributes, even the\ncomplex ones.It\u2019s now possible to override margins in layout method calls.Added support for bindings with the newView.bind()method.Added the newdefaultsglobal variable, which can be used to bind to user defaults.Constants accessed withconstcan now be bitwise OR-ed.Generated code is now formatted to look a bit better and be easier to debug.Added new constants for menu shortcuts for special keys (arrows, enter etc.).Added support for UI script arguments.Version 0.3.1 \u2013 2012/07/20Pushed down theactionattribute fromButtontoControl.RadioButtonsis now aControlsubclass.Made window recalculate its view loop after having generated its children.Version 0.3.0 \u2013 2012/07/09Added RadioButtons, TableView, TabView, TextView, ImageView and ProgressIndicator.Added support for string localization.Added TextField.alignment and TextField.textColor.Added Button.keyEquivalent.Added canClose, canResize and canMinimize to Window.Added a Control subclass.View can now be directly instantiated in UI scripts (They\u2019re like \u201cCustom Views\u201d in IB).xibless runcan now be run on script for which the result is a View.Improved layout system.Window origin is now supplied in terms of screen proportions rather than absolute positions.Fixed \u2018id\u2019 ownerclass in main function prototype generation and added the \u201cownerimport\u201d global\nvariable in the UI script.Escape newlines in string code generation.Added documentation for Button.buttonType and Button.bezelStyle and added a demo for a button\nwith a different bezel style.Fixed the most glaring memory leaks.Fixed a bug where attributes like class-level default fonts wouldn\u2019t be generated when generating\nmore than one UI script in the same python session.Windows are not released when closed by default.Added support for circular references (a window setting one of its properties to an item that\nrequired that window before being created, for example, initialFirstResponder). We previously\ncouldn\u2019t generate code for such bindings.Made thealignargument inView.packRelativeTo()optional.Version 0.2.0 \u2013 2012/06/28Added Sphinx documentationAdded thexibless runcommand for quick UI previews.Added Combobox and Popup.Version 0.1.0 \u2013 2012/06/25Initial pre-alpha release"} +{"package": "xiblint", "pacakge-description": "Checks .xib and .storyboard files for compliance with best practices"} +{"package": "xibs", "pacakge-description": "XIBSThis repository contains the source forxibs, a prototype for Intra-Beam Scattering (IBS) modelling and computing to be later integrated intoXsuite.[!NOTE]\nThis started as a fork of M. Zampetakis' work on a simple but physics-accurateIBS implementation. The new\npackage's code is quite different from the original but is benchmarked against\nit as well as other tools to ensure the validity of results.See thedocumentationfor details.InstallingInstallation is easily done in your environment viapip:python-mpipinstallxibsLicenseThis project is licensed under theApache-2.0 License- see theLICENSEfile for details."} +{"package": "xicam", "pacakge-description": "Xi-CAMXi-cam is a graphical environment for synchrotron data analysis,\nmanagement, and visualization developed by the Advanced Light Source at\nLawrence Berkeley National Laboratory. This is a cross-platform\nopen-source Python 3 project licensed under BSD.InstallationThe latest stable Xi-CAM is available on pypipipinstallxicamFor more information, see theinstallation documentation.ResourcesDocumentation:https://xi-cam.readthedocs.io/en/latestReport an issue in Xi-CAM:New Bug Report"} +{"package": "xicam.Acquire", "pacakge-description": "Supports acquisition of data"} +{"package": "xicam.core", "pacakge-description": "===========Xi-cam.core is the fundamental package for Xi-cam.Keywords: synchrotron analysis x-ray scattering tomographyPlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: Science/ResearchClassifier: Topic :: Scientific/Engineering :: PhysicsClassifier: License :: OSI Approved :: BSD LicenseClassifier: Programming Language :: Python :: 3.6"} +{"package": "xicam.dev", "pacakge-description": "A quick-installer for Xi-cam 2 developers. Python and Git experience required. The default install location is~/Xi-cam.AttentionXi-cam 2 has not yet reached a release state. Expect some changes to API design as we continue development.RequirementsPython 3.6+PyQt5GitPython(\u2026and the Xi-cam 2 platform requirements)InstallationTo run the quick-installer:pip install -v xicam.devThis quick-installer performs the following operations:Clone essential Xi-cam 2 packages to the installation directoryInstall Xi-cam 2 dependenciesInstall Xi-cam 2 essential packages as editable sourceNote: The-vallows you to see installation progress.ConfigurationTo install to a custom directory, set a shell environment variable with the desired path:INSTALL_DIR=\"~/my/install/dir\"or, infish:set -x -g INSTALL_DIR \"~/my/install/dir\""} +{"package": "xicam.gui", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.hipies", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.ipython", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.log", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.NCEM", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.plugins", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.SAXS", "pacakge-description": "Xi-CAM SAXSXi-CAM GUI plugin that facilitates data exploration and processing for SAXS experiments.(Work in progress, release 1.0.0 will be more stable.)InstallationThe latest build of Xi-cam.SAXS is available on pypi asxicam.SAXS.DetailsIf unsure about where to install, we recommend creating an environment.\nThere are several tools that provide this, such as virtualenv or conda.For more details about setting up an environment for installation, see theXi-CAM Installation Instructionsfor your operating system.Once your environment is activated, install with the following command:pip install xicam.SAXS(this will install xicam for you as well).ResourcesFor more information about Xi-CAM, see themain Xi-CAM repository's READMERelease Notes0.3.0 - Refactoring; provides Calibration and Correlation stages."} +{"package": "xicam.threadmonitor", "pacakge-description": "No description available on PyPI."} +{"package": "xicam.XPCS", "pacakge-description": "Xi-CAM XPCSXi-CAM GUI plugin that facilitates data exploration and visualization for XPCS experiments.InstallationThe latest build of Xi-cam.XPCS is available on pypi.pip install xicam.XPCSResourcesFor more information about Xi-CAM, see themain Xi-CAM repository"} +{"package": "xickle", "pacakge-description": "UNKNOWN"} +{"package": "xicor", "pacakge-description": "xicorxi correlation method adapted for pythonWhat is xicor?xicor is an implementation of the \"xi\" correlation metric described in Chatterjee, S. (2019, September 22). A new coefficient of correlation.arxiv.org/abs/1909.10140. It is based off the R code mentioned in the paper:https://statweb.stanford.edu/~souravc/xi.RFree software: MIT licenseDocumentation:https://czbiohub.github.io/xicorInstallationThe package can be installed from PyPI usingpiphere:pip install xicorDevelopmental installTo install this code and play around with the code locally, clone this github repository and usepipto install:git clone https://github.com/czbiohub/xicor.git\ncd xicor\n\n# The \".\" means \"install *this*, the folder where I am now\"\npip install .\n# or you could install using\npython setup.py installUsagefrom xicor.xicor import Xi\nxi_obj = Xi([1, 2, 3], [1, 2, 3])\ncorrelation = xi_obj.correlation\npvals = xi_obj.pval_asymptotic(ties=False, nperm=1000)"} +{"package": "xicorpy", "pacakge-description": "Chatterjee's Xi, its Applications, and OffshootsXicorPy is a Python package implementingChatterjee's Xi, and its various offshoots. You can use the package with raw python objects, NumPy arrays, or Pandas DataFrames.Please see theDocumentationfor an introductory tutorial and a full\nuser guide.FeaturesThe package currently implements:Chatterjee's Xi from [1]Modified Xi from [2]Codependence Coefficient from [3]Feature Ordering by Conditional Independence (FOCI) for Feature Selection from [3]UsageThe package is available on PyPI. You can install using pip:pip install xicorpy.importxicorpyx=[10,8,13,9,11,14,6,4,12,7,5]y=[8.04,6.95,7.58,8.81,8.33,9.96,7.24,4.26,10.84,4.82,5.68]xi=xicorpy.compute_xi_correlation(x,y)xi,p_value=xicorpy.compute_xi_correlation(x,y,get_p_values=True)Refer to theDocsfor more details.Contributing to XiCorPyAny help with the package is greatly appreciated! Pull requests and bug reports are greatly welcome!Citations:Chatterjee (2020). \"A new coefficient of correlation\"Lin and Han (2021). \"On boosting the power of Chatterjee's rank correlation\"Azadkia and Chatterjee (2021). \"A simple measure of conditional dependence\""} +{"package": "xicorrelation", "pacakge-description": "xicorrelationpackage implements xi correlation formula proposed inhttps://arxiv.org/pdf/1909.10140.pdf.It is based off the R code mentioned in the paper:https://statweb.stanford.edu/~souravc/xi.Rand\nR packagehttps://github.com/cran/XICORSimple examplefromxicorrelationimportxicorrx=[10,8,13,9,11,14,6,4,12,7,5]y=[8.04,6.95,7.58,8.81,8.33,9.96,7.24,4.26,10.84,4.82,5.68]# API similar to spearmanr or kendalltau from scipyxi,pvalue=xicorr(x,y)print(\"xi\",xi)print(\"pvalue\",pvalue)InstallationInstallation process is simple, just:$ pip install xicorrelationChanges0.3.0Rework API do be similar to scipy.0.2.1Initial release."} +{"package": "xicsrt", "pacakge-description": "XICSRT: Photon based raytracing in PythonDocumentation:https://xicsrt.readthedocs.orgGit Repository:https://bitbucket.org/amicitas/xicsrtGit Mirror:https://github.com/PrincetonUniversity/xicsrtPurposeXICSRT is a general purpose, photon based, scientific raytracing code intended\nfor both optical and x-ray raytracing.XICSRT includes handling for x-ray Bragg reflections from crystals which allows\nmodeling of x-ray spectrometers and other x-ray systems. Care has been taken to\nallow for modeling of emission sources in real units and accurate preservation\nof photon statistics throughout. The XICSRT code has similar functionality to\nthe well knownSHADOWraytracing code, though the intention is to be a\ncomplementary tool rather than a replacement. These two projects have somewhat\ndifferent goals, and therefore different strengths.Current development is focused on x-ray raytracing for fusion science and\nhigh energy density physics (HEDP) research, in particular X-Ray Imaging Crystal\nSpectrometers for Wendelstein 7-X (W7-X), ITER and the National Ignition\nFacility (NIF).InstallationXICSRT can be simply installed usingpippip install xicsrtAlternatively it is possible to install from source usingsetuptoolspython setup.py installUsageXICSRT is run by supplying a config dictionary toxicsrt.raytrace(config).\nThe easiest way to run XICSRT is through aJupyter Notebook. A command line\ninterface is also available.To learn how format the input, and interpret the output, see the examples\nprovided in thedocumentation."} +{"package": "xicsrt-contrib", "pacakge-description": "XICSRT: Contributed ModulesGit Repository:https://bitbucket.org/amicitas/xicsrt_contribGit Mirror:https://github.com/PrincetonUniversity/xicsrt_contribPurposeA collection of community contributed modules for extension of the XICSRT\nraytracing code.The optic, source and filter objects in this repository are meant for use with\nXICSRT. These are extra objects that may be useful to an XICSRT user but have\nnot been included as built-in objects for one of the following reasons:Usage is too specific for general use.Non-standard external dependencies.Performance and stability not at production quality.Some of these objects may eventually be moved into the main repository as their\ndevelopment advances.InstallationThe XICSRT contributed modules can be simply installed usingpippip install xicsrt_contribAlternatively it is possible to install from source usingsetuptoolspython setup.py installAfter installation xicsrt should natively see all available contributed objects\nin the same way as built-in objects.UsageUse xicsrt normally; after installation the contributed objects are natively\navailable."} +{"package": "xict", "pacakge-description": "No description available on PyPI."} +{"package": "xid", "pacakge-description": "seehttps://github.com/graham/python_xidfor more info."} +{"package": "xideco", "pacakge-description": "UNKNOWN"} +{"package": "xidi-ai", "pacakge-description": "xidi tool"} +{"package": "xidpy", "pacakge-description": "xidpy"} +{"package": "xid-py", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiedaxia", "pacakge-description": "Example Package#\u5728\u6b64\u6587\u4ef6\u5185\uff0c\u53ef\u4f7f\u7528markdown\u64b0\u5199\u5bf9\u5305\u7684\u8be6\u7ec6\u4ecb\u7ecd\u548c\u8bf4\u660e\uff0c\u4fbf\u4e8e\u522b\u4eba\u719f\u6089\u548c\u4f7f\u7528\uff0c\u5728\u6b64\u4e0d\u518d\u8d58\u8ff0\n\u5404\u79cd\u81ea\u5b9a\u4e49\u5185\u5bb9"} +{"package": "xiejing-nester", "pacakge-description": "No description available on PyPI."} +{"package": "xiejun", "pacakge-description": "\u8fd9\u662f\u4e00\u4e2a\u540a\u70b8\u5929\u7684\u5de5\u5177..."} +{"package": "xieminxuan10", "pacakge-description": "\u73a9\u73a9\u800c\u5df2#\u50f5\u5c38\u66f4\u65b0"} +{"package": "xietestlib", "pacakge-description": "ggllpython"} +{"package": "xieyang", "pacakge-description": "No description available on PyPI."} +{"package": "xieyin", "pacakge-description": "Use function xieyin(sentence,pattern,accurate).Example:from xieyin import xieyin,yintostrxieyin(\u2018\u8c10\u97f3\u5b57\u7b26\u4e32\u2019,pattern=0,accurate=True)yintostr(\u2018xie yin zi fu chuan\u2019,sep=\u2019\u2019,tone=False)If you are not interested in using it as a model,you can do this:from xieyin import mainmain()"} +{"package": "xiezhi", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiezhi-ai", "pacakge-description": "xiezhi: The First One-dimensional Anomaly Detection ToolInstallpip install xiezhi-aiUsageThe inputs include data, beta, and alpha.data: The current version only supports the detection of one-dimensional data, so the data should be a list.beta and alpha are set between 0 and 1 and beta is smaller than alpha, if there are few anomalies, beta and alpha can be set close to 1;\notherwize, it should be set close to 0.5. If the number of anomalies are unknown, then both of beta and alpha should be close to 0.5.Below is the example:importxiezhiasxzdata=[1,2,3,4,5,6,7,9,10,20]# here 20 is the anomalybenign_data=xz(data,0.7,0.9)# xiezhi will return the benign data"} +{"package": "xiezhi-detect", "pacakge-description": "No description available on PyPI."} +{"package": "xiezuocat", "pacakge-description": "No description available on PyPI."} +{"package": "xifa", "pacakge-description": "XIFA: Accelerated Item Factor AnalysisWhat isxifa?xifais a python package for conductingitem factor analysis(IFA), a representative multivariate technique in psychometrics.xifais build onjax, a package for Autograd and XLA (accelerated linear algebra). Hence,xifacan run IFA on GPUs and TPUs to hugely speed up the training process. That is why we call itAccelerated IFA.To calculate a marginal maximum likelihood (MML) estimate,xifaimplements a vectorized version of Metropolis-Hastings Robbins-Monro (MH-RM) algorithm (Cai, 2010). The vectorized algorithm is designed for parallel computing with GPUs of TPUs. The vectorized algorithm includes two stages: the first stage updates the parameter estimate by a stochastic expectation-maximization (StEM) algorithm and the second stage conducts stochastic approximation (SA) to iteratively refine the estimate.For a tutorial, please see theIPIP 50 Items Example.For a large-scale application, please see theIPIP 300 Items Example (v2).Features inxifaxifasupports ordinal data IFA withgraded response model (GRM;Semejima, 1969)generalized partial credit model (GPCM;Muraki, 1992).The analysis can be eitherexploratoryorconfirmatory. In addition, the vectorized algorithm is able to handle the presence ofmissing responsesunequal category itemsFeatures in statistical inference (e.g., goodness-of-fit statistics, parameter standard errors, etc.) are still under development."} +{"package": "xignitegh", "pacakge-description": "XigniteGHPython module to get historical stock data from the XigniteGlobalHistorical APIXigniteGH is a wrapper to the XigniteGlobalHistorical API. This module implements a python interface to the API provided byXignite. A token is required.InstallTo install the package use:pipinstallxigniteghUsageimportpandasaspdfromxigniteghimportXignitexgh=Xignite(_token=\"TOKEN\",_token_userid=USERID)quotes=xgh.get_quotes(ticker=\"AAPL\",years=1)ifquotes[\"Outcome\"]==\"Success\":name=quotes[\"Security\"][\"Name\"]dividends=xgh.get_dividends(ticker=\"AAPL\",years=1)ifdividends[\"Outcome\"]==\"Success\":df=pd.json_normalize(dividends[\"CashDividends\"])The token may also be stored in the environment variableXIGNITE_TOKEN. The token userid is optional and used only with encrypted tokens."} +{"package": "xil", "pacakge-description": "XILGather and compare foreign currency exchange buy and sell rates offered by Israeli\nbanks.Banks dataThe XIL project supports the following banks:Bank and data sourceXIL moduleTestsBank name (Hebrew)Bank Leumi Le-Israelleumi:x:\u05d1\u05e0\u05e7 \u05dc\u05d0\u05d5\u05de\u05d9 \u05dc\u05d9\u05e9\u05e8\u05d0\u05dcBank Hapoalimpoalim:x:\u05d1\u05e0\u05e7 \u05d4\u05e4\u05d5\u05e2\u05dc\u05d9\u05ddMizrahi Tefahot Bankmizrahi_tefahot:x:\u05d1\u05e0\u05e7 \u05de\u05d6\u05e8\u05d7\u05d9 \u05d8\u05e4\u05d7\u05d5\u05eaIsrael Discount Bankdiscount:x:\u05d1\u05e0\u05e7 \u05d3\u05d9\u05e1\u05e7\u05d5\u05e0\u05d8 \u05dc\u05d9\u05e9\u05e8\u05d0\u05dcFirst International Bank of Israelfibi:x:\u05d4\u05d1\u05e0\u05e7 \u05d4\u05d1\u05d9\u05e0\u05dc\u05d0\u05d5\u05de\u05d9 \u05d4\u05e8\u05d0\u05e9\u05d5\u05df \u05dc\u05d9\u05e9\u05e8\u05d0\u05dcBank of Jerusalemjerusalem:x:\u05d1\u05e0\u05e7 \u05d9\u05e8\u05d5\u05e9\u05dc\u05d9\u05ddMercantile Discount Bankmercantile:x:\u05d1\u05e0\u05e7 \u05de\u05e8\u05db\u05e0\u05ea\u05d9\u05dc \u05d3\u05d9\u05e1\u05e7\u05d5\u05e0\u05d8Bank Massadmassad:x:\u05d1\u05e0\u05e7 \u05de\u05e1\u05d3One Zero Digital Bankonezero:white_check_mark:\u05d5\u05d5\u05d0\u05df \u05d6\u05d9\u05e8\u05d5 \u05d4\u05d1\u05e0\u05e7 \u05d4\u05d3\u05d9\u05d2\u05d9\u05d8\u05dc\u05d9Bank of Israelboi:x:\u05d1\u05e0\u05e7 \u05d9\u05e9\u05e8\u05d0\u05dcFor the data sources (websites and URLs) for each bank, see the docstring of the\ncorresponding XIL module.Banks that are not supported yet:Bank Yahav (\u05d1\u05e0\u05e7 \u05d9\u05d4\u05d1): no public information available.https://www.bank-yahav.co.il/investments/foreing-currency/Bank Esh Israel (\u05d1\u05e0\u05e7 \u05d0\u05e9 \u05d9\u05e9\u05e8\u05d0\u05dc): a new bank - not commercially active yet.https://www.esh.com/InstallationThe project requires Python 3.11 or above. To install the project, run:pipinstallxilContributing to the XIL projectPlease read theContribution Guide."} +{"package": "xileh", "pacakge-description": "XilehModule for optimizing pipeline with genetic algorithmsGeneral structureThe idea of this is to abstract complex processing pipelines based of thescipy.pipelinesetup,\nbut with extended data capacities going beyond a feature matrixXand potential labels / regression\ntargetsy.\nFor this end, the abstraction is based of two main components, thepipelineand thepipelinedata.\nThe pipeline consists of functions acting upon the pipeline data. Functions are added to the pipeline\nduring initialization and the pipeline is later evaluated given apipelinedataentity.SchematicWhy build something new?As with every project, the first question should be, if there is anything already available which serves the purpose...\nIf looking at libraries in two main dimensions, i.e.builting functionalityandspecificity / restrictions, we would end up with the following graph IMHO.Usually one would not want to end up in the lower left quadrant of such a split, but herexilehaims to be exactly there. I.e. provide only a very limited scope of functionality built-in, but allow for maximal freedom of customization by being as general as possible.Take for example thesklearn.Pipelinewhichxilehis motivated on. It is great to build, store and evalute all kind of machine learning piplines, but it is very specific in which type (shape) of data it can process and how it its doing it (fit/transform). Of coursesklearnas a whole has a huge bunch of functionaly implemented but then would need to have different processing steps glued together by custom code, no longer allowing for this single object describing the full pipeline.Other libraries likehydraare based of (a single) config file(s) which provide a good overview and single point of truth for the processing, but hence this again requires a quite specific format and might thus hinder rapid prototyping.So xileh deliberatly wants to:impose as little restrictions to you workflow as possible (dealing with arbitrary data objects and python functions)integrate easily with a function's based workflow during developmentprovide a single source of truth for the processingenable reuseabilty of whole pipelines by strongly motivating compositionGetting StartedInstallationClone themasterbranch, or for compatebility of storing basicmnedata entities, use themnebranchgitclonegit@github.com:bsdlab/xileh.gitFrom within the folder, install to your pip repo or just link, depeding on your liking.pipinstall.# orpipinstalldevelopPipelinedataThexileh.core.pipelinedata.xPDataimplements the pipelinedata container, which contains of three elements:A data entity, usually an array or array-like. Possible also a list of otherxPDataentities.Header information as a dictionary containing information about the whole data set used to describe the data in 1.Meta information as a dictionary containing meta data about 1., such as configuration info for the processing, aggregated measure, or per record meta data. Note that if a dictionary value has a shape property, it is assumed that it should contain a per record (i.e. 1 meta elements per value) info and is thus checked for its length upon initialization. So to provide an array which does not match the length of 1. you have to pack it into an object without shape property first.All 1.-3. are potentially extended by processing steps within the pipeline. However, processing should in general not change any entities provided during initialization, but create new copies. There might be reasons however, where a change is required (e.g. memory constraint). Overwriting is thus not restricted.Initializing a containerfromxilehimportxPData# single data container -> nothing can be addedpdata=xPData(\"somedata\",name='mycontainer')# a container which can be dynamically extended, if the data arg is of type listpdata=xPData([],name='mycontainer')# with header or meta datapdata=xPData([],name='cont1',header={'description':'some useful container'})# nested initializationpdata=xPData([xPData([1,2,3,4],name='array_1')],name='outer_container_1')#### Get and set`pytho# those getters are epdata.get_by_name('array_1')==pdata['array_1']==pdata.array_1# setting can be done accordinglypdata.get_by_name('array_1').data=np.ones(3)pdata['array_1'].data=np.ones(3)pdata.array_1.data=np.ones(3)# or overwriting whole containerstd=xPData(np.ones(3),name='new_array')pdata.get_by_name('array_1')=tdpdata['array_1']=tdpdata.array_1=tdAdd# basic way of adding a new container via get by name. Without the# create_if_missing=True, a None value would be returnednewc=pdata.get_by_name('newcont',create_if_missing=True)newc.data=np.ones(123)newc.header['description']='A few ones for important reasons'# or more concisepdata.add(np.ones,'newcont',header={'description':'A few ones for important reasons'})Deletepdata.delete_by_name('newcont')Some UtilitySimply calling the container prints some overview info reflecting the hierarchy of stored data and indicating : if it is aleaf-container.In[10]:pdata=xPData(...:[...:xPData([1,2,3,4],name='array_1'),...:xPData('string',name='string_1'),...:xPData(pd.DataFrame(),name='df1')...:],...:name='outer_container_1'...:)In[11]:pdataOut[11]:xPDataobjectat0x7f8b023b3880-withsize32outer_container_1:|array_1:list|string_1:|df1:'--------------------Only container names:In[12]:pdata.get_container_names()Out[12]:['outer_container_1','array_1','string_1','df1']Dict of containers and types:In[15]:pdata.get_containers()Out[15]:{'outer_container_1':[{'array_1':[]},{'string_1':str},{'df1':pandas.core.frame.DataFrame}]}In[14]:pdata.gc()Out[14]:{'outer_container_1':[{'array_1':[]},{'string_1':str},{'df1':pandas.core.frame.DataFrame}]}Save and loadIn[16]:pdata.save('./test_container')In[17]:fromxileh.core.pipelinedataimportfrom_containerIn[18]:newc=from_container('./test_container/')In[19]:newcOut[19]:xPDataobjectat0x7f8b024e71c0-withsize32outer_container_1:|array_1:list|string_1:|df1:'--------------------PipelinesPipelines are concatenations of functions operating onxPDataobjects. Therefore, all pipeline functions shoud follow the pattern outlined belowFunctions signaturedefadd_data_entity(pdata,name='myname',**kwargs):\"\"\"Add a simply data entity to the containerNOTE: A valid function for processing within a pipeline will have onlyone arg, which is the xPData objects that is processed, but can haveany number of kwargs, which will also be logged with the pipeline object\"\"\"pdata.add([1,2,3]*size,name)# Note, every function used in a pipeline needs to return the pdata object# --> this is to make explicit, that the function modifies the pdata objectreturnpdataInitializationpl=xPipeline('test_pipeline',log_eval=False)pl.add_steps(('add_to_data',add_data_entity),('add_to_data_2',add_data_entity,{'name':'another_test'}),)RepresentationCalling the pipeline object will list on the stepsIn[5]:plOut[5]:Pipelinename:test_pipelineSteps:->'add_to_data'->'add_to_data_2'Calling for the.stepsattribute will also show the internal list of tuples (,,)In[12]:pl.stepsOut[12]:[('add_to_data',,{}),('add_to_data_2',,{'name':'another_test'})]It is also possible to look just at a specific step by looking for its nameIn[14]:pl.get_step('add_to_data_2')Out[14]:(('add_to_data_2',,{'name':'another_test'}),1)Evaluating the pipelinePipelines use the.eval()method to process datapdata=xPData([],name='outercontainer')pl.eval(pdata)# will process the steps 'add_to_data' and 'add_to_data_2'Reuse in other modulesIf pipelines are defined on a global scope in a script or module, you can simple import it:fromxilehimportxPData,xPipelinefrommy_module.my_scriptimportmy_plaspre_pl# ================================= Functions =================================defprint_foo(pdata):fornameinpdata.get_container_names():print(f\"{name}-{pdata[name].data}\")# ================================= Pipeline ==================================pl=xPipeline('test_pipeline',log_eval=False)pl.add_steps(('print_before',print_foo),*pre_pl.steps,('print_after',print_foo))ModificationSteps can either be replaced completelyIn[17]:deffoo(pdata,k='abc'):...:returnpdata...:In[18]:pl.replace_step('add_to_data',('new_step',foo))In[19]:plOut[19]:Pipelinename:test_pipelineSteps:->'new_step'->'add_to_data_2'->'test_step'or their kwargs can be modifiedIn[20]:pl.add_steps(('test_step',foo))In[21]:pl.set_step_kwargs('test_step',k='cde')In[22]:pl.stepsOut[22]:[('add_to_data',,{}),('add_to_data_2',,{'name':'another_test'}),('test_step',,{'k':'cde'})]and of course they can be deletedIn[23]:pl.remove_step('new_step')In[24]:plOut[24]:Pipelinename:test_pipelineSteps:->'add_to_data_2'->'test_step'In[25]:pl.remove_steps(['add_to_data_2','test_step'])In[26]:plOut[26]:Pipelinename:test_pipelineSteps:->Early StoppingStopping an evaluation early can be achieved by settingearly_stopparameter\nwithin thepdata.header. This would be done in any pipeline function\nwhich you would want to trigger an early stop (e.g. you load data and nothing\nis found -> skip all processing).pdata.header['early_stop']=TrueWorking with xilehA general example of how a script could be structured is provided in this templateTemplate"} +{"package": "xilinx-language-server", "pacakge-description": "xilinx-language-serverLanguage server for xilinx:vivadovitisdocument hovercompletionReadto know more.Documentsvivado-system-level-design-entryvivado-tcl-commandsvitis-embeddedUpdateInstallvivadoandvitis, thenRunscripts/vivado.tclto updatesrc/xilinx_language_server/assets/json/vivado.jsonRunscripts/xsct.tclto updatesrc/xilinx_language_server/assets/json/xsct.jsonRelated Projectsxilinx.vim: vim filetype plugin\nfor xilinx"} +{"package": "xilinx-logicnets", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xillypy", "pacakge-description": "XillyPyA simple Xillybus interface written in Python.\nIt supports streaming as well as reading/writing bytes to an address/data interface.Usageimportxillypy# write 16 (0x10, 0b00010000) to address 2xillypy.memory_write('/dev/xillybus_mem',2,(16,))# write some bytes (.encode()) to a streaming interfacexillypy.stream_write('/dev/xillybus_write','this is my data i want to write'.encode())An example can be found inbenchmark.py.CompatibilityThe code was tested with Python 3.5 and 3.6 on a Linux Host (Ubuntu 16.04)."} +{"package": "xilnex-api", "pacakge-description": "XILNEX API test runvisithttps://developers.xilnex.com/api-reference/for API information\nsome sample module items to test run\nothers API just fill in the QUERY_URL, QUERY_METHOD, regenerates the URL request format then you are all good to go"} +{"package": "xiloudriver", "pacakge-description": "No description available on PyPI."} +{"package": "ximage", "pacakge-description": "\ud83d\udce6 Welcome to ximageDeploymentActivityPython VersionsSupported SystemsProject StatusBuild StatusLintingCode CoverageCode QualityCode ReviewLicenseCommunityCitationSlack|DocsTheximagepackage is in active development. Feel free to try it out, to report issues or to suggest changes.\u2139\ufe0f Software OverviewThe software currently enables to:label n-dimensional xarray objectsextract patches around n-dimensional labelsextract patches from n-dimensional xarray objectsJoin theDISDRODB Slack Workspaceto meet the community !\ud83d\ude80 Quick Startximageprovides an easy-to-use interface to manipulate image, videos and n-dimensional arrays with classical image processing techniques.Theximagexarray accessor provides a convenient way to labelling and extract patches in n-dimensional arrays !Image labellingmin_value_threshold=1max_value_threshold=np.infmin_area_threshold=5max_area_threshold=np.inffootprint=Nonesort_by=\"area\"sort_decreasing=Truelabel_name=\"label\"### Label xarray objectxr_obj=da.ximage.label(min_value_threshold=min_value_threshold,max_value_threshold=max_value_threshold,min_area_threshold=min_area_threshold,max_area_threshold=max_area_threshold,footprint=footprint,sort_by=sort_by,sort_decreasing=sort_decreasing,label_name=label_name,)Extract patches around labels# Output Optionsn_patches=10n_labels=Nonelabels_id=Nonehighlight_label_id=False# Patch Extraction Optionspatch_size=(100,100)centered_on=\"label_bbox\"padding=0n_patches_per_label=np.Infn_patches_per_partition=1# Tiling/Sliding Optionspartitioning_method=None# \"tiling\" / \"sliding\"n_partitions_per_label=Nonekernel_size=Nonebuffer=0stride=Noneinclude_last=Trueensure_slice_size=Truedebug=Trueverbose=Trueda_patch_gen=xr_obj.ximage.label_patches(label_name=label_name,patch_size=patch_size,variable=variable,# Output Optionsn_patches=n_patches,n_labels=n_labels,labels_id=labels_id,highlight_label_id=highlight_label_id,# Patch Extraction Optionscentered_on=centered_on,padding=padding,n_patches_per_label=n_patches_per_label,n_patches_per_partition=n_patches_per_partition,# Tiling/Sliding Optionspartitioning_method=partitioning_method,n_partitions_per_label=n_partitions_per_label,kernel_size=kernel_size,buffer=buffer,stride=stride,include_last=include_last,ensure_slice_size=ensure_slice_size,debug=debug,verbose=verbose,)Look at theTutorialsto have an overview of the software !\ud83d\udee0\ufe0f Installationpipximagecan be installed viapipon Linux, Mac, and Windows.\nOn Windows you can installWinPythonto get Python and pip\nrunning.\nThen, install theximagepackage by typing the following command in the command terminal:pipinstallximageTo install the latest development version via pip, see the\n[documentation][doc_install_link].conda [NOT YET AVAILABLE]ximagecan be installed viacondaon Linux, Mac, and Windows.\nInstall the package by typing the following command in a command terminal:condainstallximageIn case conda-forge is not set up for your system yet, see the easy to follow\ninstructions onconda-forge.\ud83d\udcad Feedback and Contributing GuidelinesIf you aim to contribute or discuss the future development of ximage,\nwe highly suggest to join theDISDRODB Slack WorkspaceFeel free to also open aGitHub Issueor aGitHub Discussionspecific to your questions or ideas.\u270d\ufe0f ContributorsGionata GhiggiSon Pham-BaCitationYou can cite theximagesoftware by:Ghiggi Gionata & Son Pham-Ba . ghiggi/ximage. Zenodo.https://doi.org/10.5281/zenodo.8131552If you want to cite a specific version, have a look at theZenodo site.\ud83d\udcda Requirements:xarraydaskdask_imageskimageLicenseThe content of this repository is released under the terms of theMITlicense."} +{"package": "ximea-py", "pacakge-description": "ximea-pyThis module provides a python interface to XIMEA cameras. It is simply a repackaging of XIMEA's python drivers available athttps://www.ximea.com/downloads/recent/XIMEA_Linux_SP.tgz(package/api/Python/v3/ximea) in order to allow for easier installation with pip, e.g. into virtual or conda environments.InstallationOn Linux, add users that will use the camera to the \"plugdev\" group:sudo usermod -aG plugdev Install with:pip install ximea-pyand use like so:import ximea.xiapi\n\nximea.xiapi.Camera()\n..."} +{"package": "ximenez", "pacakge-description": "The purpose of Ximenez is to execute an action on a set of collected\nitems. Both the action and the way items are collected, are defined by\nPython modules, which are called plug-ins. This lets you:execute a command (and retrieve its output) on a set of remote hosts\n(via SSH);perform various actions on a set of Zope servers (add an user,\nchange his/her password, remove an user, etc.);carry out any action that you are willing to write a Python plug-in\nfor.See thePlug-inssection below to know more about Ximenez built-in\nplug-ins and how to develop your own ones.UsageYou can use Ximenez with the following command-line:$ ximenez -c -a andare both plug-ins. The former gives\nXimenez a set of items on which to act, and the latter is the action\nto perform on each item of this set.Hopefully, Ximenez comes with a number of useful plug-ins , e.g.:$ ximenez -c misc.readlines -a misc.logOptional arguments are available. Seeusagefor further\ndetails.Plug-insThe main characteristic of Ximenez is that it can be extended to just\ndo what you need to do, by using plug-ins. There are two kinds of\nplug-ins: collectors and actions.Ximenez ships with a set ofbuilt-in plug-ins. You may also want to\ntake a look at theexhaustive guideto develop your own plug-ins.RequirementsXimenez should run under any OS, though some plug-ins may use\nOS-specific features or require special Python packages.Python 2.4 or above is required. This program may also work with prior\nversions of Python with minor changes.InstallationIf you haveeasy_install, then the following should do the trick:$ easy_install ximenezFor further details, see theInstallationchapter.Subversion repositoryXimenez source code lives in a Subversion repository. To checkout the\ntrunk:$ svn co https://svn.pilotsystems.net/projets/ximenez/trunk ximenezYou can alsobrowse the sourceswith the same URL.The nameIt all began in Jarrow. One of the cross beams had gone out askew on\nthe treddle.CreditsXimenez has been written by Damien Baty.Ga\u00ebl Le Mignot (Pilot Systems) and Sylvain Viollon (Infrae) have\nprovided several bug fixes.Pilot Systemshas partially sponsored the development of this\nprogram.LicenseXimenez is copyright 2006-2007 by Damien Baty.This program is free software; you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Foundation; either version 3 of the License, or (at\nyour option) any later version.This program is distributed in the hope that it will be useful, but\nWITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU\nGeneral Public License for more details.You should have received a copy of the GNU General Public License\nalong with this program. If not, see thesection about licensesof\ntheGNU web site."} +{"package": "xi-method", "pacakge-description": "Xi - Post hoc explanationsXiis a python package that implements the paper\n\"Explaining classifiers with measures of statistical association\"[1]and \"The Xi method: unlocking the mysteries of regression with Statistics\"[2]The growing size and complexity of data as well as the need of accurate predictions, forces analysts to use black-box\nmodel. While the success of those models extends statistical application, it also increases the need for\ninterpretability and ,when possible, explainability.The paper proposes an approach to the problem based on measures of statistical association.Measures of statistical association deliver information regarding the strength of the statistical dependence between the\ntarget and the feature(s) of interest, inferring this insight from the data in amodel-agnosticfashion.In this respect, we note that an important class of measures of statistical associations is represented by probabilistic\nsensitivity measures.We use these probabilistic sensitivity measures as part of the broad discourse of interpretability in statistical\nmachine learning. For brevity, we call this part the Xi-method.Briefly, the method consists in evaluating ML model predictions comparing the values of probabilistic sensitivity\nmeasures obtained in a model-agnostic fashion, i.e., directly from the data, with the same indices computed replacing\nthe true targets with the ML model forecasts.To sum up,Xihas three main advantages:Model agnostic: as long as your model outputs predictions, you can useXiwith any modelData agnostic:Xiworks with structured (tabular) and unstructured data ( text, image ).Computationally reasonableInstallationInstall from pypi:pip install xi-methodUsageThe package is quite simple and it's designed to give you post hoc explainations for your dataset and machine learning\nmodel with minimal effort.Import your data in a pandas dataframe format, splitting covariates and independent\nvariable.from xi_method.utils import load_dataset\nfrom xi_method.ximp import *\n\n# load wine quality\ndf = load_wine_quality_red_dataset()\n\nY = df.quality\ndf.drop(columns='quality', inplace=True)Create an instance ofXIClassifierorXIRegressordepending on the type of problem you are working with:xi = XIClassifier(m=20)For the classification tasks, you can specify the number of partitions in three different ways:m: number of partitions can be a dictionary or an integer. The dictionary should have covariate name as key and\nnumber of desired partition as value. If m is an integer, the desired number of partition will be applied to all\ncovariates.discrete: A list of covariates name you want to treat as categorical.obs: A dictionary mapping covariates name to number of desired observations in each partition.For regression tasks, you can only specifymas an integer.A defaultmvalue will be computed if nothing is provided by the user, as indicated in the paper.To obtain post hoc explanations, run your favorite ML model, save the predictions as numpy array\nand provide the covariates ( test set) and the predictions to the methodexplain:from sklearn.linear_model import LogisticRegression\nfrom sklearn.model_selection import train_test_split\n\nx_train, x_test, y_train, y_test = train_test_split(df.values, Y, test_size=0.3, random_state=42)\nlr = LogisticRegression(multi_class='multinomial',max_iter=100)\nlr.fit(x_train, y_train)\ny_pred = lr.predict(x_test)\n\nxi = XIClassifier(m=20)\np = xi.explain(X=x_test, y=y_pred, replicates=10, separation_measurement='L1')Objectpis a python dictionary mapping separation measurement and explanation.You can easily have access to the explanation:p.get('L1').explanationYou can choose from different separation measurement, as specified in the paper. You can specify one separation\nmeasurement or more than one, using a list.p = xi.explain(X=x_test, y=y_pred, separation_measurement=['L1','Kuiper'])Implemented separation measurement:Kullback - LeiblerKuiperL1L2HellingerYou can get a list of implemented separation measurement running:from xi_method.utils import *\nget_separation_measurement()Plot your result:plot(separation_measurement='L1', type='tabular', explain=P, k=10)References[1]E. Borgonovo, V. Ghidini, R. Hahn a, E. Plischke (2023).\nExplaining classifiers with measures of statistical association\nComputational Statistics and Data Analysis, Volume 182, June 2023, 107701[2]V. Ghidini (2023).\nThe Xi method: unlocking the mysteries of regression with Statistics"} +{"package": "ximilar-client", "pacakge-description": "Ximilar API Python ClientThis Python 3.9+ Client library is lightweight wrapper forximilar.comandvize.ai.InstallationPyPI (https://pypi.org/project/ximilar-client/):# we recommend to install ximilar-client to new virtualenv\npip install ximilar-clientManual installation with latest changes:1. Cloning the repo\ngit clone https://gitlab.com/ximilar-public/ximilar-client.git\n2. Install it with pip to your virtualenv\npip install -e ximilar-clientThis will install also urllib3, requests, tqdm and pytest library. This will not install python-opencv which is required if you want to upload local images to the Ximilar system. For more information about installing opencv on different systems we have a small page in ourdocs.You will need to install one of opencv-python or opencv-contrib-python (or headless) manually.UsageFirst you need to register viaapp.ximilar.comand obtain yourAPI TOKENfor communication with ximilar rest endpoints. You can obtain the token from theXimilar Appat your profile page.\nAfter you obtain the token, the usage is quite straightforward. First, import this package and create specific rest client (reconition/vize, tagging, colors, search, ...). In following example we will create client forXimilar Recognition Service(vize.ai). For all other Ximilar Services as Tagging, Custom Object Detection you will need to contacttech@ximilar.comfirst, so they will provide you access to the service:fromximilar.clientimportRecognitionClient,DetectionClientfromximilar.clientimportDominantColorProductClient,DominantColorGenericClientfromximilar.clientimportFashionTaggingClient,GenericTaggingClientapp_client=RecognitionClient(token=\"__API_TOKEN__\")detect_client=DetectionClient(token=\"__API_TOKEN__\")...WorkspacesWith a new version of Ximilar App you are able to work also with workspaces. Workspaces are entities where all your task, labels and images live. Each user has by default workspace with nameDefault(it will be used if you do not specify workspace when working with Image, Label, Task). However you can specify id of workspace in the constructor.client=RecognitionClient(token=\"__API_TOKEN__\",workspace='__UUID_OF_YOUR_WORKSPACE__')client=DetectionClient(token=\"__API_TOKEN__\",workspace='__UUID_OF_YOUR_WORKSPACE__')Ximilar RecognitionThis client allows you to work with Ximilar Recognition Service. With this client you are able to create classification or tagging tasks based on latest trends in machine learning and neural networks.\nAfter creating client object you can for example load your existing task and call train:task,status=client.get_task(task_id='__ID_TASK_')# Every label in the task must have at least 20 images before training.# The training can take up to several hours as we are trying to achieve really high quality# solution. This endpoint will immediately return success if your task is in training queue.task.train()# or you can list all your available taskstasks,status=client.get_all_tasks()# or you can create new classification task# each Task, Image, Label is identified by unique IDtask,status=client.create_task('__TASK_NAME__')TaskCurrently there are two types of task to create. User can select 'multi_class' (default) or 'multi_label'. See ximilar.docs for more info.# categorization/classification or multi class task means that image is assigned to exactly one label# labels are exclusive which means image can contain only 'cat' or only 'dog'classification_task,status=client.create_task('__TASK_NAME__')# tagging or multi label task means that image can have one or more labels# for example image can contain 'cat', 'dog' and 'animal' labels if there are on the picturetagging_task,status=client.create_task('__TASK_NAME__',type='multi_label')# removing task is possible through client object or task itselfclient.remove_task(task.id)task.remove()ClassifySuppose you want to use the task to predict the result on your images. Please, always try to send image bigger than 200px and lower than 600px for quality and speed:# you can send image in _file, _url or _base64 format# the _file format is intenally converted to _base64 as rgb imageresult=task.classify([{'_url':'__URL_PATH_TO_IMG__'},{'_file','__LOCAL_FILE_PATH__'},{'_base64':'__BASE64_DATA__'}])# the result is in json/dictionary format and you can access it in following way:best_label=result['records'][0]['best_label']LabelsLabels are connected to the task. Depends which task you are working with (Tagging/multi_label or Categorization/multi_class) you can create Tag or Category labels. Working with the labels are pretty simple:# getting existing labelexisting_label,status=client.get_label('__ID_LABEL__')# creating new label (CATEGORY, which is default) and attaching it to existing Categorization task (multi class)label,status=client.create_label(name='__NEW_LABEL_NAME__')task.add_label(label.id)# creating new label (TAG) for Tagging task (multi label)label,status=client.create_label(name='__NEW_LABEL_NAME__',label_type='tag')# get all labels which are connected to the tasklabels,status=task.get_labels()forlabelinlabels:print(label.id,label.name)# get label with exact name which is also connected to specific tasklabel,status=task.get_label_by_name(name='__LABEL_NAME__')# detaching (not deleting) existing label from existing tasktask.detach_label(label.id)# remove label (which also detach label from all tasks)client.remove_label(label.id)# detach image from labellabel.detach_image(image.id)# search labels which contains given substring in namelabels,status=client.get_labels_by_substring('__LABEL_NAME__')Working with training imagesImage is main entity in Ximilar system. Every image can have multiple labels (Recognition service) or multiple objects (Detection service).# getting all images of label (paginated result)images,next_page,status=label.get_training_images()whileimages:forimageinimages:print(str(image.id))ifnotnext_page:breakimages,next_page,status=label.get_training_images(next_page)# basic operationsimage,status=client.get_image(image_id=image.id)image.add_label(label.id)# detach label from imageimage.detach_label(label.id)# deleting imageclient.remove_image(image.id)Let's say you want to upload a training image and add several labels to this image:images,status=client.upload_images([{'_url':'__URL_PATH_TO_IMAGE__','labels':[label.idforlabelinlabels],\"meta_data\":{\"field\":\"key\"}},{'_file':'__LOCAL_FILE_PATH__','labels':[label.idforlabelinlabels]},{'_base64':'__BASE64_DATA__','labels':[label.idforlabelinlabels]}])# and maybe add another label to the first imageimages[0].add_label(\"__SOME_LABEL_ID__\")Upload image without resizing it (for example Custom Object Detection requires high resolution images):images,status=client.upload_images([{'_url':'__URL_PATH_TO_IMAGE__',\"noresize\":True}])Every image can have some meta data stored:image.add_meta_data({\"__KEY_1__\":\"value\",\"__KEY_2__\":{\"THIS CAB BE\":\"COMPLEX\"}})image.clear_meta_data()Every image can be marked withtestflag (for evaluation on independent test dataset only):image.set_test(True)Every image can be marked as real (default) or product. Product image should be images where is dominant one object on nice solid background. We can do more augmentations on these images.image.set_real(False)# will mark image as productXimilar FlowsThe client is able to get flow of the json or process images/records by the flow.fromximilar.clientimportFlowsClientclient=FlowsClient(\"__API_TOKEN__\")# get flowflow,_=client.get_flow(\"__FLOW_ID__\")# two way to call the flow on recordsclient.process_flow(flow.id,records)flow.proces(records)Ximilar Object DetectionXimilar Object Detection is service which will help you find exact location (Bounding Box/Object with four coordinates xmin, ymin, xmax, ymax).\nIn similar way as Ximilar Recognition, here we also have Tasks, Labels and Images. However one more entity called Object is present in Ximilar Object Detection.First you need to create/get Detection Task:client=DetectionClient(\"__API_TOKEN__\")detection_task,status=client.create_task(\"__DETECTION_TASK_NAME__\")detection_task,status=client.get_task(task.id)Second you need to create Detection Label and connect it to the task:detection_label,status=client.create_label(\"__DETECTION_LABEL_NAME__\")detection_label,status=client.get_label(\"__DETECTION_LABEL_ID__\")detection_task.add_label(detection_label.id)Lastly you need to create Objects/Bounding box annotations of some type (Label) on the images:image,status=client.get_image(\"__IMAGE_ID__\")d_object,status=client.create_object(\"__DETECTION_LABEL_ID__\",\"__IMAGE_ID__\",[xmin,ymin,xmax,ymax])d_object,status=client.get_object(d_object.id)# get all objects of imaged_objects,status=client.get_objects_of_image(\"__IMAGE_ID__\")Then you can create your task:detection_task.train()Removing entities is same as in recognition client:client.remove_task(\"__DETECTION_TASK_ID__\")client.remove_label(\"__DETECTION_LABEL_ID__\")# this will delete all objects which were created as this labelclient.remove_object(\"__DETECTION_OBJECT_ID__\")client.remove_image(\"__IMAGE_ID__\")task.remove()label.remove()object1=client.get_object(\"__DETECTION_OBJECT_ID__\")object1.remove()image.remove()Getting Detection Result:result=detection_task.detect([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])Extracting object from image:image,status=client.get_image(\"59f7240d-ca86-436b-b0cd-30f4b94705df\")object1,status=client.get_object(\"__DETECTION_OBJECT_ID__\")extracted_image_record=image.extract_object_data(object1.data)Speeding it up with Parallel ProcessingIf you are uploading/classifying thousands of images and really need to speed it up, then you can use method parallel_records_processing:# classifying images in Ximilar Custom Recognition serviceresult=client.parallel_records_processing([{\"_url\":image}forimageinimages],method=task.classify,output=True,max_workers=3)# detection images in Ximilar Custom Object Detectionresult=client.parallel_records_processing([{\"_url\":image}forimageinimages],method=task.detect,output=True,max_workers=3)# uploading imagesresult=client.parallel_records_processing([{\"_url\":image,\"labels\":[\"__LABEL_ID_1__\"]}forimageinimages],method=client.upload_images,output=True)This method works only for getting result for classification, tagging, detection, color extraction or uploading images (All methods which use json records as input).Ximilar Visual SearchService for visual fashion search. For more information see docs.ximilar.comfromximilar.client.visualimportSimilarityFashionClientclient=SimilarityFashionClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')# inserting image requires _id and product_idclient.insert([{\"_id\":\"__IMAGE_ID__\",\"product_id\":\"__PRODUCT_ID__\",\"_url\":\"__URL_PATH_TO_IMAGE__\"}])result=client.detect([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])# search in collectionresult=client.search([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])Ximilar Dominant ColorsYou can select the service for extracting dominant colors by type of your image. If the image is from Product/Fashion domain, which means that product is tipically on some solid background then usDominanColorProductClient.fromximilar.clientimportDominantColorProductClient,DominantColorGenericClientproduct_client=DominantColorProductClient(token=\"__API_TOKEN__\")generic_client=DominantColorGenericClient(token=\"__API_TOKEN__\")result=product_client.dominantcolor([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_dominant_colors'])Ximilar Generic and Fashion TaggingTagging contains two clients in similar way as DominanColors do.fromximilar.clientimportFashionTaggingClient,GenericTaggingClientfashion_client=FashionTaggingClient(token=\"__API_TOKEN__\")generic_client=GenericTaggingClient(token=\"__API_TOKEN__\")result=generic_client.tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags'])result=fashion_client.tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags'])result=fashion_client.meta_tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags_meta_simple'])Ximilar Photo and Product similarityThese two services provides visual search (similarity search) for generic (stock) photos or products (e-commerce, fashion, ...).\nWhen initializing client you need to specify bothtokenand yourcollection_idthat we created for you.fromximilar.client.searchimportSimilarityPhotosClient,SimilarityProductsClientclient=SimilarityPhotosClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')client=SimilarityProductsClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')# get random 7 items from database and return also _url if is present in itemresult=client.random(count=7,fields_to_return=['_id','_url'])# search 10 most visually similar items for item in your indexresult=client.search({'_id':'__ITEM_ID__'},k=10)# search 5 most visually similar items for external item (not in index) defined by _url fieldresult=client.search({'_url':'__URL_PATH_TO_IMAGE__'},k=5)# search visually similar items, return also _url field if present in item and# search only for items defined by filter (mongodb syntax)result=client.search({'_id':'__ITEM_ID__'},fields_to_return=['_id','_url'],filter={'meta-category-x':{'$in':['__SOME_VALUE_1__','__SOME_VALUE_2__']},'some-field':'__SOME_VALUE__'})All crud operations:# get list of items from indexresult=client.get_records([{'_id':'__ITEM_ID__'},{'_id':'__ITEM_ID__'}])# insert item tot he index with your _id, and onr of _url | _base64, and other fields (meta-info) which you can# then use when applying filter in search or random menthodsresult=client.insert([{'_id':'__ITEM_ID__','_url':'__URL_PATH_TO_IMAGE__','meta-category-x':'__CATEGORY_OF_ITEM__','meta-info-y':'__ANOTHER_META_INFO__'}])# delete item from idresult=client.remove([{'_id':'__ITEM_ID__'}])# update item in index with all additional fields and meta-inforesult=client.update([{'_id':'__ITEM_ID__','some-additional-field':'__VALUE__'}])Custom SimilarityThis service let you train your custom image similarity model.Creating entities is similar to recognition or detection service.fromximilar.client.similarityimportCustomSimilarityClientclient=CustomSimilarityClient(\"__API__TOKEN__\")tasks,_=client.get_all_tasks()task,_=client.create_task(\"__NAME__\",\"__DESCRIPTION__\")type1,_=client.create_type(\"__NAME__\",\"__DESCRIPTION__\")group,_=client.create_group(\"__NAME__\",\"__DESCRIPTION__\",type1.id)Add/Remove types to/from task:task.add_type(type1.id)task.remove_type(type1.id)Add/Remove images to/from group:group.add_images([\"__IMAGE_ID_1__\"])group.remove_images([\"__IMAGE_ID_1__\"])group.refresh()Add/Remove groups to/from group:group.add_groups([\"__GROUP_ID_1__\"])group.remove_groups([\"__GROUP_ID_1__\"])group.refresh()Set unset group as test (test flag is for evaluation dataset):group.set_test(True)# or False if unsetting from eval datasetgroup.refresh()Searching groups with name:client.get_all_groups_by_name(\"__NAME__\")ToolsIn ourtoolsfolder you can find some useful scripts for:uploader.pyfor uploading all images from specific folderdata_saver.pyfor saving entire recognition and detection workspace including imagesdata_wiper.pyfor removing entire workspace and all your data in workspacedetection_cutter.pycutting objects from images"} +{"package": "ximilar-client-new", "pacakge-description": "Ximilar API Python ClientThis Python 3.X Client library is lightweight wrapper forximilar.comandvize.ai.InstallationPyPI (https://pypi.org/project/ximilar-client/):# we recommend to install ximilar-client to new virtualenv\npip install ximilar-clientManual installation with latest changes:1. Cloning the repo\ngit clone https://gitlab.com/ximilar-public/ximilar-client.git\n2. Install it with pip to your virtualenv\npip install -e ximilar-clientThis will install also python-opencv, numpy, requests, tqdm and pytest library.UsageFirst you need to register viaapp.ximilar.comand obtain yourAPI TOKENfor communication with ximilar rest endpoints. You can obtain the token from theXimilar Appat your profile page.\nAfter you obtain the token, the usage is quite straightforward. First, import this package and create specific rest client (reconition/vize, tagging, colors, search, ...). In following example we will create client forXimilar Recognition Service(vize.ai). For all other Ximilar Services as Tagging, Custom Object Detection you will need to contacttech@ximilar.comfirst, so they will provide you access to the service:fromximilar.clientimportRecognitionClient,DetectionClientfromximilar.clientimportDominantColorProductClient,DominantColorGenericClientfromximilar.clientimportFashionTaggingClient,GenericTaggingClientapp_client=RecognitionClient(token=\"__API_TOKEN__\")detect_client=DetectionClient(token=\"__API_TOKEN__\")...WorkspacesWith a new version of Ximilar App you are able to work also with workspaces. Workspaces are entities where all your task, labels and images live. Each user has by default workspace with nameDefault(it will be used if you do not specify workspace when working with Image, Label, Task). However you can specify id of workspace in the constructor.client=RecognitionClient(token=\"__API_TOKEN__\",workspace='__UUID_OF_YOUR_WORKSPACE__')client=DetectionClient(token=\"__API_TOKEN__\",workspace='__UUID_OF_YOUR_WORKSPACE__')Ximilar RecognitionThis client allows you to work with Ximilar Recognition Service. With this client you are able to create classification or tagging tasks based on latest trends in machine learning and neural networks.\nAfter creating client object you can for example load your existing task and call train:task,status=client.get_task(task_id='__ID_TASK_')# Every label in the task must have at least 20 images before training.# The training can take up to several hours as we are trying to achieve really high quality# solution. This endpoint will immediately return success if your task is in training queue.task.train()# or you can list all your available taskstasks,status=client.get_all_tasks()# or you can create new classification task# each Task, Image, Label is identified by unique IDtask,status=client.create_task('__TASK_NAME__')TaskCurrently there are two types of task to create. User can select 'multi_class' (default) or 'multi_label'. See ximilar.docs for more info.# categorization/classification or multi class task means that image is assigned to exactly one label# labels are exclusive which means image can contain only 'cat' or only 'dog'classification_task,status=client.create_task('__TASK_NAME__')# tagging or multi label task means that image can have one or more labels# for example image can contain 'cat', 'dog' and 'animal' labels if there are on the picturetagging_task,status=client.create_task('__TASK_NAME__',type='multi_label')# removing task is possible through client object or task itselfclient.remove_task(task.id)task.remove()ClassifySuppose you want to use the task to predict the result on your images. Please, always try to send image bigger than 200px and lower than 600px for quality and speed:# you can send image in _file, _url or _base64 format# the _file format is intenally converted to _base64 as rgb imageresult=task.classify([{'_url':'__URL_PATH_TO_IMG__'},{'_file','__LOCAL_FILE_PATH__'},{'_base64':'__BASE64_DATA__'}])# the result is in json/dictionary format and you can access it in following way:best_label=result['records'][0]['best_label']LabelsLabels are connected to the task. Depends which task you are working with (Tagging/multi_label or Categorization/multi_class) you can create Tag or Category labels. Working with the labels are pretty simple:# getting existing labelexisting_label,status=client.get_label('__ID_LABEL__')# creating new label (CATEGORY, which is default) and attaching it to existing Categorization task (multi class)label,status=client.create_label(name='__NEW_LABEL_NAME__')task.add_label(label.id)# creating new label (TAG) for Tagging task (multi label)label,status=client.create_label(name='__NEW_LABEL_NAME__',label_type='tag')# get all labels which are connected to the tasklabels,status=task.get_labels()forlabelinlabels:print(label.id,label.name)# get label with exact name which is also connected to specific tasklabel,status=task.get_label_by_name(name='__LABEL_NAME__')# detaching (not deleting) existing label from existing tasktask.detach_label(label.id)# remove label (which also detach label from all tasks)client.remove_label(label.id)# detach image from labellabel.detach_image(image.id)# search labels which contains given substring in namelabels,status=client.get_labels_by_substring('__LABEL_NAME__')Working with training imagesImage is main entity in Ximilar system. Every image can have multiple labels (Recognition service) or multiple objects (Detection service).# getting all images of label (paginated result)images,next_page,status=label.get_training_images()whileimages:forimageinimages:print(str(image.id))ifnotnext_page:breakimages,next_page,status=label.get_training_images(next_page)# basic operationsimage,status=client.get_image(image_id=image.id)image.add_label(label.id)# detach label from imageimage.detach_label(label.id)# deleting imageclient.remove_image(image.id)Let's say you want to upload a training image and add several labels to this image:images,status=client.upload_images([{'_url':'__URL_PATH_TO_IMAGE__','labels':[label.idforlabelinlabels],\"meta_data\":{\"field\":\"key\"}},{'_file':'__LOCAL_FILE_PATH__','labels':[label.idforlabelinlabels]},{'_base64':'__BASE64_DATA__','labels':[label.idforlabelinlabels]}])# and maybe add another label to the first imageimages[0].add_label(\"__SOME_LABEL_ID__\")Upload image without resizing it (for example Custom Object Detection requires high resolution images):images,status=client.upload_images([{'_url':'__URL_PATH_TO_IMAGE__',\"noresize\":True}])Every image can have some meta data stored:image.add_meta_data({\"__KEY_1__\":\"value\",\"__KEY_2__\":{\"THIS CAB BE\":\"COMPLEX\"}})image.clear_meta_data()Every image can be marked withtestflag (for evaluation on independent test dataset only):image.set_test(True)Every image can be marked as real (default) or product. Product image should be images where is dominant one object on nice solid background. We can do more augmentations on these images.image.set_real(False)# will mark image as productXimilar FlowsThe client is able to get flow of the json or process images/records by the flow.fromximilar.clientimportFlowsClientclient=FlowsClient(\"__API_TOKEN__\")# get flowflow,_=client.get_flow(\"__FLOW_ID__\")# two way to call the flow on recordsclient.process_flow(flow.id,records)flow.proces(records)Ximilar Object DetectionXimilar Object Detection is service which will help you find exact location (Bounding Box/Object with four coordinates xmin, ymin, xmax, ymax).\nIn similar way as Ximilar Recognition, here we also have Tasks, Labels and Images. However one more entity called Object is present in Ximilar Object Detection.First you need to create/get Detection Task:client=DetectionClient(\"__API_TOKEN__\")detection_task,status=client.create_task(\"__DETECTION_TASK_NAME__\")detection_task,status=client.get_task(task.id)Second you need to create Detection Label and connect it to the task:detection_label,status=client.create_label(\"__DETECTION_LABEL_NAME__\")detection_label,status=client.get_label(\"__DETECTION_LABEL_ID__\")detection_task.add_label(detection_label.id)Lastly you need to create Objects/Bounding box annotations of some type (Label) on the images:image,status=client.get_image(\"__IMAGE_ID__\")d_object,status=client.create_object(\"__DETECTION_LABEL_ID__\",\"__IMAGE_ID__\",[xmin,ymin,xmax,ymax])d_object,status=client.get_object(d_object.id)# get all objects of imaged_objects,status=client.get_objects_of_image(\"__IMAGE_ID__\")Then you can create your task:detection_task.train()Removing entities is same as in recognition client:client.remove_task(\"__DETECTION_TASK_ID__\")client.remove_label(\"__DETECTION_LABEL_ID__\")# this will delete all objects which were created as this labelclient.remove_object(\"__DETECTION_OBJECT_ID__\")client.remove_image(\"__IMAGE_ID__\")task.remove()label.remove()object1=client.get_object(\"__DETECTION_OBJECT_ID__\")object1.remove()image.remove()Getting Detection Result:result=detection_task.detect([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])Extracting object from image:image,status=client.get_image(\"59f7240d-ca86-436b-b0cd-30f4b94705df\")object1,status=client.get_object(\"__DETECTION_OBJECT_ID__\")extracted_image_record=image.extract_object_data(object1.data)Speeding it up with Parallel ProcessingIf you are uploading/classifying thousands of images and really need to speed it up, then you can use method parallel_records_processing:# classifying images in Ximilar Custom Recognition serviceresult=client.parallel_records_processing([{\"_url\":image}forimageinimages],method=task.classify,output=True,max_workers=3)# detection images in Ximilar Custom Object Detectionresult=client.parallel_records_processing([{\"_url\":image}forimageinimages],method=task.detect,output=True,max_workers=3)# uploading imagesresult=client.parallel_records_processing([{\"_url\":image,\"labels\":[\"__LABEL_ID_1__\"]}forimageinimages],method=client.upload_images,output=True)This method works only for getting result for classification, tagging, detection, color extraction or uploading images (All methods which use json records as input).Ximilar Visual SearchService for visual fashion search. For more information see docs.ximilar.comfromximilar.client.visualimportSimilarityFashionClientclient=SimilarityFashionClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')# inserting image requires _id and product_idclient.insert([{\"_id\":\"__IMAGE_ID__\",\"product_id\":\"__PRODUCT_ID__\",\"_url\":\"__URL_PATH_TO_IMAGE__\"}])result=client.detect([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])# search in collectionresult=client.search([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])Ximilar Dominant ColorsYou can select the service for extracting dominant colors by type of your image. If the image is from Product/Fashion domain, which means that product is tipically on some solid background then usDominanColorProductClient.fromximilar.clientimportDominantColorProductClient,DominantColorGenericClientproduct_client=DominantColorProductClient(token=\"__API_TOKEN__\")generic_client=DominantColorGenericClient(token=\"__API_TOKEN__\")result=product_client.dominantcolor([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_dominant_colors'])Ximilar Generic and Fashion TaggingTagging contains two clients in similar way as DominanColors do.fromximilar.clientimportFashionTaggingClient,GenericTaggingClientfashion_client=FashionTaggingClient(token=\"__API_TOKEN__\")generic_client=GenericTaggingClient(token=\"__API_TOKEN__\")result=generic_client.tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags'])result=fashion_client.tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags'])result=fashion_client.meta_tags([{\"_url\":\"__URL_PATH_TO_IMAGE__\"}])print(result['records'][0]['_tags_meta_simple'])Ximilar Photo and Product similarityThese two services provides visual search (similarity search) for generic (stock) photos or products (e-commerce, fashion, ...).\nWhen initializing client you need to specify bothtokenand yourcollection_idthat we created for you.fromximilar.client.searchimportSimilarityPhotosClient,SimilarityProductsClientclient=SimilarityPhotosClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')client=SimilarityProductsClient(token='__API_TOKEN__',collection_id='__COLLECTION_ID__')# get random 7 items from database and return also _url if is present in itemresult=client.random(count=7,fields_to_return=['_id','_url'])# search 10 most visually similar items for item in your indexresult=client.search({'_id':'__ITEM_ID__'},k=10)# search 5 most visually similar items for external item (not in index) defined by _url fieldresult=client.search({'_url':'__URL_PATH_TO_IMAGE__'},k=5)# search visually similar items, return also _url field if present in item and# search only for items defined by filter (mongodb syntax)result=client.search({'_id':'__ITEM_ID__'},fields_to_return=['_id','_url'],filter={'meta-category-x':{'$in':['__SOME_VALUE_1__','__SOME_VALUE_2__']},'some-field':'__SOME_VALUE__'})All crud operations:# get list of items from indexresult=client.get_records([{'_id':'__ITEM_ID__'},{'_id':'__ITEM_ID__'}])# insert item tot he index with your _id, and onr of _url | _base64, and other fields (meta-info) which you can# then use when applying filter in search or random menthodsresult=client.insert([{'_id':'__ITEM_ID__','_url':'__URL_PATH_TO_IMAGE__','meta-category-x':'__CATEGORY_OF_ITEM__','meta-info-y':'__ANOTHER_META_INFO__'}])# delete item from idresult=client.remove([{'_id':'__ITEM_ID__'}])# update item in index with all additional fields and meta-inforesult=client.update([{'_id':'__ITEM_ID__','some-additional-field':'__VALUE__'}])Custom SimilarityThis service let you train your custom image similarity model.Creating entities is similar to recognition or detection service.fromximilar.client.similarityimportCustomSimilarityClientclient=CustomSimilarityClient(\"__API__TOKEN__\")tasks,_=client.get_all_tasks()task,_=client.create_task(\"__NAME__\",\"__DESCRIPTION__\")type1,_=client.create_type(\"__NAME__\",\"__DESCRIPTION__\")group,_=client.create_group(\"__NAME__\",\"__DESCRIPTION__\",type1.id)Add/Remove types to/from task:task.add_type(type1.id)task.remove_type(type1.id)Add/Remove images to/from group:group.add_images([\"__IMAGE_ID_1__\"])group.remove_images([\"__IMAGE_ID_1__\"])group.refresh()Add/Remove groups to/from group:group.add_groups([\"__GROUP_ID_1__\"])group.remove_groups([\"__GROUP_ID_1__\"])group.refresh()Set unset group as test (test flag is for evaluation dataset):group.set_test(True)# or False if unsetting from eval datasetgroup.refresh()Searching groups with name:client.get_all_groups_by_name(\"__NAME__\")ToolsIn ourtoolsfolder you can find some useful scripts for:uploader.pyfor uploading all images from specific folderdata_saver.pyfor saving entire recognition and detection workspace including imagesdata_wiper.pyfor removing entire workspace and all your data in workspacedetection_cutter.pycutting objects from images"} +{"package": "xiModule", "pacakge-description": "No description available on PyPI."} +{"package": "ximo-statstools", "pacakge-description": "No description available on PyPI."} +{"package": "ximu3", "pacakge-description": "Seegithubfor documentation and examples."} +{"package": "ximu3csv", "pacakge-description": "Seegithubfor documentation and examples."} +{"package": "xi-mzidentml-converter", "pacakge-description": "xi-mzidentml-converterxi-mzidentml-converter uses pyteomics (https://pyteomics.readthedocs.io/en/latest/index.html) to parse mzIdentML files (v1.2.0) and extract crosslink information. Results are written to a relational database (PostgreSQL or SQLite) using sqlalchemy.Requirements:python3.10pipenvsqlite3 or postgresql (these instruction use posrgresql)1. InstallationClone git repository :git clone https://github.com/Rappsilber-Laboratory/xi-mzidentml-converter.gitcd into the repository:cd xi-mzidentml-converterCheckout python3 branch:git checkout python32. create a postgresql role and database to usesudo su postgres\npsql\ncreate database xiview;\ncreate user xiadmin with login password 'your_password_here';\ngrant all privileges on database xiview to xiadmin;find the hba.conf file in the postgresql installation directory and add a line to allow the xiadmin role to access the database:\ne.g.sudo nano /etc/postgresql/13/main/pg_hba.confthen add the line:local xiview xiadmin md5then restart postgresql:sudo service postgresql restart3. Configure the python environment for the file parseredit the file xiSPEC_ms_parser/credentials.py to point to your postgressql database.\ne.g. so its content is:hostname = 'localhost'\nusername = 'xiadmin'\npassword = 'your_password_here'\ndatabase = 'xiview'\nport = 5432Set up the python environment:cd xiSPEC_ms_parser\npipenv install --python 3.10run create_db_schema.py to create the database tables:python create_db_schema.pyparse a test dataset:python process_dataset.py -d ~/PXD038060 -i PXD038060The argument-dis the directory to read files from and-iis the project identifier to use in the database.To run testsMake sure we have the right db user availablepsql -p 5432 -c \"create role ximzid_unittests with password 'ximzid_unittests';\"\npsql -p 5432 -c 'alter role ximzid_unittests with login;'\npsql -p 5432 -c 'alter role ximzid_unittests with createdb;'\npsql -p 5432 -c 'GRANT pg_signal_backend TO ximzid_unittests;'run the testspipenv run pytest"} +{"package": "xin", "pacakge-description": "# xina package from laozhao"} +{"package": "xin2pbn", "pacakge-description": "xin2pbn==> Deprecated, this module is moved intobridge-utilssince 2022.05.27, all features are kept$ pip uninstall xin2pbn\n$ pip install bridge-utilsxinrui bridge online url to pbn converterxinrui url looks likethis, it can be converted to standard pbn filesoutput.pbnUsagepip install xin2pbn\nxin2pbn \"url\"\nxin2pbn \"local.html\"example$ xin2pbn \"http://www.xinruibridge.com/deallog/DealLog.html?bidlog=P%3BP,1S,X,2S%3BP,P,X,P%3B3C,P,4C,P%3B5C,P,P,P%3B&playlog=W:TH,KH,AH,4H%3BE:TS,KS,AS,6C%3BN:3H,2H,9H,8H%3BS:TD,KD,AD,7D%3BN:3D,9D,2C,2D%3BS:3C,4C,TC,5C%3BN:6D,5D,QC,4D%3BS:7C,KC,AC,8C%3BN:&deal=T96.A62.J975.985%20KQ832.954.T.Q732%20AJ754.T8.K842.K4%20.KQJ73.AQ63.AJT6&vul=NS&dealer=E&contract=5C&declarer=S&wintrick=12&score=620&str=%E7%BE%A4%E7%BB%84IMP%E8%B5%9B%2020201121%20%E7%89%8C%E5%8F%B7%202/8&dealid=984602529&pbnid=344008254\"\nwrite to file output.pbn\n\n$ curl -O https://isoliu.gitlab.io/book2020/web/1-chapter2-B01-zdjs.html\n % Total % Received % Xferd Average Speed Time Time Time Current\n Dload Upload Total Spent Left Speed\n100 5054 100 5054 0 0 11512 0 --:--:-- --:--:-- --:--:-- 11512\n$ xin2pbn 1-chapter2-B01-zdjs.html\n[b'https://isoliu.gitlab.io/deallog/DealLog.html?bidlog=1D,1S,P;2D,3C,P,P;4S,P,P,X;P,P,P&playlog=E:5D,KD,2D,6D;S:3H,5H,8H,7H;N:8S,TS,AS,3D;S:4C,KC,3C,2C;W:8D,7D,2S,9D;E:8C,JC,AC,5C;W:QD,TH,5S,4D;E:6H,9H,KH,AH;N:&deal=.K5.QJT832.AK976%20KQ874.AT8.76.Q53%20JT652.7642.5.T82%20A93.QJ93.AK94.J4&vul=All&dealer=W&contract=4SX&declarer=N&wintrick=9&score=-200&str=%E9%94%A6%E6%A0%87%E8%B5%9B%20%E7%AC%AC12%E8%BD%AE%20%E7%89%8C%E5%8F%B7%204/12&dealid=653117488&pbnid=127397878', b'https://isoliu.gitlab.io/deallog/DealLog.html?bidlog=1D,1S,P;2D,3C,P,P;4S,P,P,X;P,P,P&playlog=E:5D,AD,2D,6D;S:QH,KH,AH,7H;N:KS,2S,3S,3D;N:4S,TS,AS,8D;S:3H,5H,8H,2H;N:TH,6H,JH,7C;S:9H,6C,7D,4H;S:4C,KC,3C,2C;W:AC,5C,8C,JC;W:QD,QS,TC,4D;N:&deal=.K5.QJT832.AK976%20KQ874.AT8.76.Q53%20JT652.7642.5.T82%20A93.QJ93.AK94.J4&vul=All&dealer=W&contract=4SX&declarer=N&wintrick=10&score=790&str=%E9%94%A6%E6%A0%87%E8%B5%9B%20%E7%AC%AC12%E8%BD%AE%20%E7%89%8C%E5%8F%B7%204/12&dealid=653247876&pbnid=127397878']\nwrite to file ./1-chapter2-B01-zdjs-01.pbn\nwrite to file ./1-chapter2-B01-zdjs-02.pbn\n\n$ cat 1-cha*.pbn > all.pbnsnapshotoriginal source in xinrui UIThe outputed pbn can be viewed inside bridgecomposer & pbnjviewDevelopment# docker run -it -v $PWD:/app -w /app python:3.8 bash\n# python3 -m pip install --user --upgrade twine wheel\n# python3 setup.py sdist clean\n# rm -rf dist\n# python3 setup.py sdist bdist_wheel\n# cat > ~/.pypirc\n# python3 -m twine upload --skip-existing --verbose dist/*TODOWeb interfaceconvert to js to be used by anyoneReferencehttp://www.tistis.nl/pbn/http://xinruibridge.com/http://bridgecomposer.com/"} +{"package": "xinabox-CHIP", "pacakge-description": "Python-XCHIPTemplate for python libraries"} +{"package": "xinabox-CORE", "pacakge-description": "Python-COREI2C Core for CC03/CS11/CW03, CW02, CW01, Raspberry Pi and MicrobitUsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-CORE\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-CORE"} +{"package": "xinabox-CW01-CW02-CORE", "pacakge-description": "Python CORE for CW01 and CW02MicroPython Core handling I2C communication forCW01(ESP8266) andCW02(ESP32).InstructionsUseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Python IDEmu-editorUsemu-editor(find it herehttps://codewith.mu)mu-editorneeds to recognize Product ID:0x6001and Vendor ID:0x0403- pull request submitted.In the meantime use XinaBox version of themu-editorfrom here:XinaBox mu-editor.Visual Studio Code (VSC)UseVSC(find it herehttps://code.visualstudio.com)You need a plugin, such asPymakrESPlorerUseESPlorerESPlorerThis IDE allows you to switch DTR/RTS off - see note regarding CW01 belowNote using CW01The CW01 doesn't have an \"auto resetting\" circutry on it like the CW02 has, therefore the the CW01 will be stuck in \"bootloader\" mode when inserted into your computer with a standard IP01. However if you have an old IP01 with switches, then you can bypass that by setting the A-B switch in positionAwhen programming the CW01 using mu-editor. And when loading the MicroPython using theXinaBoxUploader, the switches should be inBandDCEYou can also just use an IDE that allows you to control DTR/RTS, such as ESPlorer (see above)"} +{"package": "xinabox-OC01", "pacakge-description": "Python-OC01Insert description of xChipUsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-oc01\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-oc01Example#insert example"} +{"package": "xinabox-OC03", "pacakge-description": "Python-OC03The OC03 xChip is a low-voltage control relay module able to switch AC and DC loads. It is based on the PCA9554A and TLP241A.The optically isolated relay is controlled by a PCA9554A IO expander, which provides an control interface to the switch. The PCA9554A has several selectable I2C addresses accessible via solder pads.The TLP241A photorelay consist of a photo MOSFET optically coupled to an infrared light emitting diode which switches a AC or DC load. It provides an isolation voltage of 5000 Vrms, making it suitable for applications that require reinforced circuit insulation.UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-OC03\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-OC03ExamplefromxOC03importxOC03fromxCoreimportxCoreOC03=xOC03()# start OC03OC03.init()# sleep timeDELAY=500# infinite loopwhileTrue:# close relayOC03.writePin(True)xCore.sleep(DELAY)# open relayOC03.writePin(False)xCore.sleep(DELAY)"} +{"package": "xinabox-OC05", "pacakge-description": "Python-OC05The OC05 xChip is an 8-channel servo motor driver. It is based on the popular PCA9685 manufactured by NXP Semiconductor. It is supported by a BU33SD5 regulator to drive and accurately control up to 8 servo motors on a single module and act as system power supply. The module has 8 standard 2.54 mm (0.1\") servo headers, plus 1 standard 2.54 mm (0.1\") battery/BEC input header.UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-OC05\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-OC05ExamplefromxOC05importxOC05fromxCoreimportxCore# OC05 instanceOC05=xOC05()# configure OC05 with frequency of 60HzOC05.init(60)whileTrue:OC05.setServoPosition(1,0)# position servo to the rightxCore.sleep(50)OC05.setServoPosition(1,180)# position servo to the leftxCore.sleep(50)"} +{"package": "xinabox-SG33", "pacakge-description": "Python-SG33TODO - Insert descriptionUsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-sg33\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-sg33ExamplefromxCoreimportxCorefromxSG33importxSG33SG33=xSG33()whileTrue:ifSG33.dataAvailable()==True:SG33.getAlgorithmResults()print(SG33.getTVOC())print(SG33.getCO2())xCore.sleep(1000)"} +{"package": "xinabox-SH01", "pacakge-description": "Python-SH01Capacitive touch sensor"} +{"package": "xinabox-SL01", "pacakge-description": "Python-SL01The SL01 xChip is a UV radiation and ambient light level sensor. It is based on the VEML6075 and TSL4531. VEML6075 on the SL01 is capable of measuring UVA and UVB radiation, in turn, providing an acccurate UV Index. TSL4531 is a light sensor that is capable of measuring the luminosity (Wide Dynamic Range \u00e2\u20ac\u201d 3 lux to 220k lux) (visual brightness).UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-SL01\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-SL01ExamplefromxCoreimportxCorefromxSL01importxSL01SL01=xSL01()whileTrue:print(SL01.getUVA())print(SL01.getUVB())print(SL01.getUVIndex())print(SL01.getLUX())xCore.sleep(1000)"} +{"package": "xinabox-SL06", "pacakge-description": "Python-SL06The SL06 xChip features advanced Gesture detection, Proximity detection, Digital Ambient Light Sense (ALS) and Colour Sense (RGBC). It is based on the popular APDS9960 manufactured by Avago Technologies.UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-SL06\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-SL06ExamplefromxCoreimportxCorefromxSL06importxSL06# SL06 instanceSL06=xSL06()# configure SL06SL06.init()# enable SL06 for gesture sensingSL06.enableGestureSensor()whileTrue:ifSL06.isGestureAvailable():# check for gesturedir=SL06.getGesture()# read directionprint(dir)# print direction on consolexCore.sleep(100)"} +{"package": "xinabox-SL19", "pacakge-description": "Python-SL19The SL19 xChip is equipped to measure temperature as a function of infrared light/radiation (IR) radiating from objects in its field of view. Is is based on theMLX90614in which a IR sensitive thermopile detector chip and signal conditioning ASIC are integrated.The MLX90614 is factory calibrated in wide temperature ranges: -40-125\u00cb\u0161C for the ambient temperature and -70-380\u00cb\u0161C for the object temperature. The measured value is the average temperature of all objects in the Field Of View of the sensor. The MLX90614 offers a standard accuracy of \u00c2\u00b10.5\u00cb\u0161C around room temperatures.UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-SL19\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-SL19ExamplefromxCoreimportxCorefromxSL19importxSL19# SL19 instanceSL19=xSL19()# configure SL19SL19.init()whileTrue:tempAmbient=SL19.getAmbientTempC()# returns ambient temp in degree celciustempObject=SL19.getObjectTempC()# returns object temp in degree celcius# prints on consoleprint('Ambient: ',tempAmbient,' C')print('Object : ',tempObject,' C')xCore.sleep(2000)"} +{"package": "xinabox-SW01", "pacakge-description": "Python-SW01The SW01 xChip is equipped with a weather sensor that is capable of measuring the temperature, humidity and atmospheric pressure. It is based on the BME280 manufactured by Bosch.The humidity sensor provides an extremely fast responce time for fast context awareness application and high overall accuracy over a wide temperature range.The pressure sensor is an absolute barometric pressure sensor with extremely high accuracy and resolution.The integrated temperature sensor has been optimized for lowest noise and highest resolution. Its output is used for temperature compensation of the pressure and humidity sensors and can also be used for estimation of the ambient temperature.UsageMu-editorDownloadMu-editorCW01 and CW02UseXinaBoxUploaderand flash MicroPython to the CW01/CW02.Download Python packages from the REPL with the following code:importnetworkimportupipsta_if=network.WLAN(network.STA_IF)sta_if.active(True)sta_if.connect(\"ssid\",\"password\")upip.install(\"xinabox-SW01\")CC03, CS11 and CW03Download the .UF2 file for CC03/CS11/CW03CircuitPythonand flash it to the board.TO DOMicroBitTO DORaspberry PiRequires Python 3pip3 install xinabox-SW01ExamplefromxCoreimportxCorefromxSW01importxSW01SW01=xSW01()whileTrue:print(SW01.values())xCore.sleep(1000)"} +{"package": "xinaprocessor", "pacakge-description": "Xina Processor is an open source library for cleaning Arabic text. It includes various cleaning functions as well as modules for streaming file and folder cleaning.InstallationPIPIf you usepip, you can install xinaprocessor with:pipinstallxinaprocessorFrom sourceYou can directly clone this repo and install the library. First clone the repo with:gitclonehttps://github.com/xina-ai/xinaprocessor.gitThen cd to the directory and install the library with:pipinstall-e.DocumentationDocumentation is still in process here:https://xina-ai.github.io/xinaprocessor/Getting StartedfromxinaprocessorimportcleanersTo clean textText=\"\u0646\u0635 \u0639\u0631\u0628\u064a!\"Cleaner=cleaners.TextCleaner(text=Text)Cleaner.keep_arabic_only()To clean text File# Creating File MyData.txtFilePath=\"MyData.txt\"withopen(FilePath,\"w\")asf:f.write(\"A\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u0623\u0648\u0644\\n\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u062b\u0627\u0646\u064a!\")# Creating FileCleaner objectCleaner=cleaners.FileCleaner(filepath=FilePath)Cleaner.remove_english_text().remove_arabic_numbers().remove_punctuations()# To access the resulted dataCleanedData=Cleaner.lines# the result will look like ['\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u0623\u0648\u0644', '\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u062b\u0627\u0646\u064a']CleanedText=Cleaner.text# the result will look like '\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u0623\u0648\u0644\\n\u0627\u0644\u0633\u0637\u0631 \u0627\u0644\u062b\u0627\u0646\u064a'# To save the proccessed/cleaned text to a fileCleaner.save2file('CleanedData.txt',encoding='utf-8')To clean large text File# This Cleaner is used for large text files, the cleaned texts will be saved to CleanedFile.txt fileFilePath=\"MyData.txt\"CleanedPath=\"CleanedFile.txt\"Cleaner=cleaners.FileStreamCleaner(filepath=FilePath,savepath=CleanedPath)Cleaner.remove_hashtags().remove_honorific_signs().drop_empty_lines().clean()"} +{"package": "xin-back", "pacakge-description": "Backend demoScille Backend backbone demo."} +{"package": "xinceptio", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xinci", "pacakge-description": "# xinci \u65b0\u8bcd & \u62bd\u8bcdxinci is a Python interface for chinese words extraction & new words extraction.[https://pypi.org/project/xinci/]## RequirementsPython >= 2.7## Installation### 1. using pip```shellpip install xinci```### 2. using setup.py``` shellgit clone git@github.com:Lapis-Hong/xinci.gitcd xincipip setup.py install```## UsageThis package has two main use cases: words extraction andfind new words.### 1. command line```shellcd xincipython word_extraction.py```or```./run.sh```### 2. python package```pythonimport xinci# if you want to see logging events.import logginglogging.basicConfig(level=logging.INFO, format='%(asctime)s : %(levelname)s : %(message)s')# init default dictionary or user dic,dic = xinci.Dictionary()# load vocab, vocab is a python set.vocab = dic.load() # or dic.dictionaryprint(vocab)# add words to dicdic.add(['\u795e\u9a6c']) # or dic.add_from_file('user.dic')# remove words from dicdic.remove(['\u795e\u9a6c']) # or dic.remove_from_file('user.dic')# extract new words, xc is a setxc = xinci.extract('corpus.txt')for w in xc:print(w)# extract all words, c is a setc = xinci.extract('corpus.txt', all_words=True)for w in xc:print(w)```result```angular2html\u53d1\u73b05\u4e2a\u65b0\u8bcd\u5982\u4e0b:@\u65b0\u8bcd\t@\u8bcd\u9891\u795b\u6591\t13\u540e\u518d\t7\u4eca\u65e5\u5934\u6761\t9\u6d17\u51c0\u5207\t7\u86cb\u6db2\t9```### Notes: Iteratively add \"not seems to new words\" in result to common dic will improve a lot.## API documentation```pythonxc = xinci.extract(params)```List of available `params` and their default value:```angular2htmlcorpus_file: string, input corpus file (required)common_words_file: string, common words dic file [common.dic]min_candidate_len: int, min candidate word length [2]max_candidate_len: int, max candidate word length [5]least_cnt_threshold: int, least word count to extract [5]solid_rate_threshold: float, solid rate threshold [0.018]entropy_threshold: float, entropy threshold [1.92]all_words: bool, set True to extract all words mode [False]save_file: string, output file [None]```## ReferencesThe code is based on this java version[https://github.com/GeorgeBourne/grid]"} +{"package": "xincshi", "pacakge-description": "No description available on PyPI."} +{"package": "xincshi-hello", "pacakge-description": "No description available on PyPI."} +{"package": "xincshi-hello2", "pacakge-description": "No description available on PyPI."} +{"package": "xindata-package-test", "pacakge-description": "EnglishThis is a CSDN blogger Xin_data test project, mainly used to explain the release of custom module testing.Note: There is nothing nutritious in the package.\u4e2d\u6587\u8fd9\u662fcsdn\u535a\u4e3bXin\u5b66\u6570\u636e\u7684\u4e00\u4e2a\u6d4b\u8bd5\u9879\u76ee\uff0c\u4e3b\u8981\u662f\u7528\u4e8e\u8bb2\u89e3\u53d1\u5e03\u81ea\u5b9a\u4e49\u6a21\u5757\u6d4b\u8bd5\u3002\n\u6ce8\uff1a\u5305\u4e2d\u6ca1\u6709\u4ec0\u4e48\u6709\u8425\u517b\u7684\u4e1c\u897f\u3002"} +{"package": "xindi-lib", "pacakge-description": "xindi-liballows you to manage subnets of a network.from xindi import ManagedNetworkYou can start with a dictionaryinput_data = dict()\ninput_data['managed_network'] = '10.0.0.0/26'\nmanaged_network = ManagedNetwork(indict=input_data)or with JSONinput_data = '{\"managed_network\": \"10.0.0.0/26\"}'\nmanaged_network = ManagedNetwork(injson=input_data)assign new subnets of the needed sizemy_first_net = dict(\n usecase='first network', \n owner='Wolfgang Wangerin', \n department='ITA'\n )\nmanaged_network.next_free_subnet(27, my_first_net)or free an existing subnetmanaged_network.free('10.0.0.0/27')list all assigned subnets:managed_network.assigned_networks()and export the configurationoutdict = managed_network.export()\noutjson = managed_network.exportJson()It is now up to you to set up an API or Webfrontend and use this library. Let me know, if you use this in an FOSS project, because I may have a usecase for it."} +{"package": "xinet", "pacakge-description": "xinetDiscover and create anything interesting!PyPIProvide PyPI support.pipinstallxinethelpViewQt for Python"} +{"package": "xinetzone", "pacakge-description": "\u4e0a\u5584\u82e5\u6c34\u7f51\u9875\u7248\u672c\uff1axinetzone\u3002"} +{"package": "xinference", "pacakge-description": "Xorbits Inference: Model Serving Made Easy \ud83e\udd16English |\u4e2d\u6587\u4ecb\u7ecd|\u65e5\u672c\u8a9eXorbits Inference(Xinference) is a powerful and versatile library designed to serve language,\nspeech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy\nand serve your or state-of-the-art built-in models using just a single command. Whether you are a\nresearcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full\npotential of cutting-edge AI models.\ud83d\udc49 Join our Slack community!\ud83d\udd25 Hot TopicsFramework EnhancementsSupport speech recognition model:#929Metrics support:#906Docker image:#855Support multimodal:#829Auto recover:#694Function calling API:#701, here's example:https://github.com/xorbitsai/inference/blob/main/examples/FunctionCall.ipynbSupport rerank model:#672New ModelsBuilt-in support forYi-VL:#946Built-in support forWhisper:#929Built-in support forOrion-chat:#933Built-in support forInternLM2-chat:#829Built-in support forqwen-vl:#829Built-in support forphi-2:#828IntegrationsDify: an LLMOps platform that enables developers (and even non-developers) to quickly build useful applications based on large language models, ensuring they are visual, operable, and improvable.Chatbox: a desktop client for multiple cutting-edge LLM models, available on Windows, Mac and Linux.Key Features\ud83c\udf1fModel Serving Made Easy: Simplify the process of serving large language, speech\nrecognition, and multimodal models. You can set up and deploy your models\nfor experimentation and production with a single command.\u26a1\ufe0fState-of-the-Art Models: Experiment with cutting-edge built-in models using a single\ncommand. Inference provides access to state-of-the-art open-source models!\ud83d\udda5Heterogeneous Hardware Utilization: Make the most of your hardware resources withggml. Xorbits Inference intelligently utilizes heterogeneous\nhardware, including GPUs and CPUs, to accelerate your model inference tasks.\u2699\ufe0fFlexible API and Interfaces: Offer multiple interfaces for interacting\nwith your models, supporting OpenAI compatible RESTful API (including Function Calling API), RPC, CLI\nand WebUI for seamless model management and interaction.\ud83c\udf10Distributed Deployment: Excel in distributed deployment scenarios,\nallowing the seamless distribution of model inference across multiple devices or machines.\ud83d\udd0cBuilt-in Integration with Third-Party Libraries: Xorbits Inference seamlessly integrates\nwith popular third-party libraries includingLangChain,LlamaIndex,Dify, andChatbox.Why XinferenceFeatureXinferenceFastChatOpenLLMRayLLMOpenAI-Compatible RESTful API\u2705\u2705\u2705\u2705vLLM Integrations\u2705\u2705\u2705\u2705More Inference Engines (GGML, TensorRT)\u2705\u274c\u2705\u2705More Platforms (CPU, Metal)\u2705\u2705\u274c\u274cMulti-node Cluster Deployment\u2705\u274c\u274c\u2705Image Models (Text-to-Image)\u2705\u2705\u274c\u274cText Embedding Models\u2705\u274c\u274c\u274cMultimodal Models\u2705\u274c\u274c\u274cAudio Models\u2705\u274c\u274c\u274cMore OpenAI Functionalities (Function Calling)\u2705\u274c\u274c\u274cGetting StartedPlease give us a star before you begin, and you'll receive instant notifications for every new release on GitHub!DocsBuilt-in ModelsCustom ModelsDeployment DocsExamples and TutorialsJupyter NotebookThe lightest way to experience Xinference is to try ourJuypter Notebook on Google Colab.DockerNvidia GPU users can start Xinference server usingXinference Docker Image. Prior to executing the installation command, ensure that bothDockerandCUDAare set up on your system.dockerrun--namexinference-d-p9997:9997-eXINFERENCE_HOME=/data-v:/data--gpusallxprobe/xinference:latestxinference-local-H0.0.0.0Quick StartInstall Xinference by using pip as follows. (For more options, seeInstallation page.)pipinstall\"xinference[all]\"To start a local instance of Xinference, run the following command:$xinference-localOnce Xinference is running, there are multiple ways you can try it: via the web UI, via cURL,\nvia the command line, or via the Xinference\u2019s python client. Check out ourdocsfor the guide.Getting involvedPlatformPurposeGithub IssuesReporting bugs and filing feature requests.SlackCollaborating with other Xorbits users.TwitterStaying up-to-date on new features.Contributors"} +{"package": "xinference-client", "pacakge-description": "Xinference Restful ClientXinference provides a restful client for managing and accessing models programmatically.Installpipinstallxinference-clientUsagefromxinference_clientimportRESTfulClientasClientclient=Client(\"http://localhost:9997\")model_uid=client.launch_model(model_name=\"chatglm2\")model=client.get_model(model_uid)chat_history=[]prompt=\"What is the largest animal?\"model.chat(prompt,chat_history=chat_history,generate_config={\"max_tokens\":1024})Result:{\"id\":\"chatcmpl-8d76b65a-bad0-42ef-912d-4a0533d90d61\",\"model\":\"56f69622-1e73-11ee-a3bd-9af9f16816c6\",\"object\":\"chat.completion\",\"created\":1688919187,\"choices\":[{\"index\":0,\"message\":{\"role\":\"assistant\",\"content\":\"The largest animal that has been scientifically measured is the blue whale, which has a maximum length of around 23 meters (75 feet) for adult animals and can weigh up to 150,000 pounds (68,000 kg). However, it is important to note that this is just an estimate and that the largest animal known to science may be larger still. Some scientists believe that the largest animals may not have a clear \\\"size\\\" in the same way that humans do, as their size can vary depending on the environment and the stage of their life.\"},\"finish_reason\":\"None\"}],\"usage\":{\"prompt_tokens\":-1,\"completion_tokens\":-1,\"total_tokens\":-1}}"} +{"package": "xinfernce", "pacakge-description": "No description available on PyPI."} +{"package": "xin-first", "pacakge-description": "No description available on PyPI."} +{"package": "xingapi", "pacakge-description": "xingapi for python usersInstallationpip install xingapieBest xingAPI com guide\uc774\ubca0\uc2a4\ud2b8 xingAPI \uac00\uc774\ub4dc(\ub9c1\ud06c)Requirementspython 32bit environmentxingAPI installationDevCenter installationDownload res filesUsage1. Session1) \uae30\ubcf8\uc0ac\uc6a9\ubc95importxingapiasxasession=xa.Session()session.login(id='\uc544\uc774\ub514',pw='\ube44\ubc00\ubc88\ud638',cert='\uacf5\uc778\uc778\uc99d\ube44\ubc00\ubc88\ud638')2) account.txt\ub97c \ud65c\uc6a9\ud558\ub294\ubc95account.txt\ub97c \uc544\ub798\uc640\uac19\uc774 \uc0dd\uc131\ud558\uc5ec \ud604\uc7ac\ud130\ubbf8\ub110\uc704\uce58\uc5d0 \ub450\uace0\uc544\uc774\ub514\n\ube44\ubc00\ubc88\ud638\n\uacf5\uc778\uc778\uc99d\ube44\ubc00\ubc88\ud638\uc544\ub798\uc2a4\ud06c\ub9bd\ud2b8\ub97c \uc2e4\ud589importxingapiasxawithopen('account.txt')asf:id,pw,cert=f.read().split()session=xa.Session()session.login(id,pw,cert)2. Query \uc0ac\uc6a9\ubc951) \uae30\ubcf8\uc801\uc778 \uc0ac\uc6a9\uc608\uc2dc\uc0bc\uc131\uc804\uc790(005930)\uc758 \uc8fc\uc2dd \ubd84\ubcc4 \uc8fc\uac00 \uc870\ud68c('t1302)\ub97c \uc608\ub85c \ub4e4\uc5b4\ubcf4\uaca0\ub2e4query=xa.Query('t1302')data=query(shcode='005930',cnt=900)xa.Query \uc624\ube0c\uc81d\ud2b8 \uc0dd\uc131\uc2dc trcode\ub97c \uc785\ub825\n\uc624\ube0c\uc81d\ud2b8\ub97c \ub2e4\uc2dc__call__\ud560 \ub54c, \ud544\ub4dc\uc774\ub984\uacfc, \ud544\ub4dc\uac12\uc744 keyword=value \ud398\uc5b4\ub85c \uc804\ub2ec\ud55c\ub2e4\n\ubc18\ud658\ub41c \ub370\uc774\ud130\ub294 { \ube14\ub85d\uc774\ub9841 : \ube14\ub85d\ub370\uc774\ud1301, \ube14\ub85d\uc774\ub9842 : \ube14\ub85d\ub370\uc774\ud1302 } \uc758dict\ud615\ud0dc\ub85c\n\ubc18\ud658\ub418\uace0, \ube14\ub85d\ub370\uc774\ud130\ub294pandas.DataFrame\uc624\ube0c\uc81d\ud2b8\uc774\ub2e4.2) \ud55c\uc904\ub85c\ub3c4 \uac00\ub2a5df=xa.Query('t1302')(shcode='005930',cnt=900)['t1302OutBlock1']3) \uc870\ud68c/\uc5f0\uc18d\uc870\ud68cquery=xa.Query('t1302')data1=query.call(shcode='005930',cnt=100).datadata2=query.nextcall(cts_time=data1['t1302OutBlock']['\uc2dc\uac04CTS'][0]).dataquery=xa.Query('t1302')data3=query.call(shcode='005930',cnt=100).datadata4=query.nextcall(shcode='005930',cnt=100,cts_time=cts_time=data1['t1302OutBlock']['\uc2dc\uac04CTS'][0]).dataDevCenter\uc5d0\uc11c TR \ud655\uc778\ucc3d\uc744 \uc0ac\uc6a9\ud558\uba74 \uc870\ud68c\ubc84\ud2bc/\ub2e4\uc74c\uc870\ud68c\ubc84\ud2bc\uc774 \uc788\ub2e4xa.Query.call(**input_kwargs)\ud568\uc218\ub294 \uc870\ud68c\ubc84\ud2bc\uc5d0 \ud574\ub2f9\ud558\uba70, \uc624\ube0c\uc81d\ud2b8 \uc790\uc2e0\uc744 \ubc18\ud658\ud55c\ub2e4.xa.Query.nextcall(**input_kwargs)\ud568\uc218\ub294 \ub2e4\uc74c\uc870\ud68c\ubc84\ud2bc\uc5d0 \ud574\ub2f9\ud558\uba70, \uc5ed\uc2dc \uc624\ube0c\uc81d\ud2b8 \uc790\uc2e0\uc744 \ubc18\ud658\ud55c\ub2e4.nextcall(\ub2e4\uc74c\uc870\ud68c)\uc758 \uacbd\uc6b0data3\ucc98\ub7fc call(\uc870\ud68c)\uc5d0 \uc0ac\uc6a9\ud55c \ud0a4\uac12\uacfc \ud568\uaed8 \uc0ac\uc6a9\ud574\ub3c4 \ub418\uc9c0\ub9cc,\ncall(\uc870\ud68c)\ub97c \ud55c \uacbd\uc6b0\uc5d4data2\ucc98\ub7fc \ub2e4\uc74c\uc870\ud68c \uc5d0\uc0ac\uc6a9\ud560 \uc0c8\ub85c\uc6b4 \ud0a4\uac12\ub9cc \uc785\ub825\ud574\ub3c4 \ub3d9\uc791\ud55c\ub2e4.4) \uc5f0\uc18d\uc870\ud68c (\uc790\ub3d9 \ub05d\uae4c\uc9c0)query=xa.Query('t1302')data=query.call(shcode='005930',cnt=100).next(keypairs={'time':'cts_time'})\uc704\uc5d0\uc11c \uc0ac\uc6a9\ud55ccall(\uc870\ud68c),nextcall(\uc5f0\uc18d\uc870\ud68c)\ub97c \uc870\ud569\ud55cnext\ud568\uc218\ub97c \uc774\uc6a9\ud558\uba74query.isnext\uac00 False\uac00 \ub420\ub54c\uae4c\uc9c0 \uc2a4\uc2a4\ub85c \ubc18\ubcf5\ud55c\ub2e4.\n\uc5ec\uae30\uc11c keypairs\ub780 InBlock\uc5d0 \ub2e4\uc2dc \ub123\uc5b4\uc904 \ud544\ub4dc\uc774\ub984\uacfc, OutBlock\uc5d0\uc11c \uac00\uc838\uc62c \ud544\ub4dc \uac12\uc758 \ud544\ub4dc\uc774\ub984\uc744 \uc774\uc57c\uae30\ud55c\ub2e4. \uc608\ub97c\ub4e4\uc5b4t1302\uc758 \uacbd\uc6b0 InBlock\uc758timekey \uc5d0 OutBlock\uc758cts_time\uc758 value\ub97c \uac00\uc838\uc640\uc57c\ud558\ubbc0\ub85c keypairs={'time':'cts_time'} \ub85c\uc804\ub2ec\ud55c\ub2e4.5) \uc5f0\uc18d\uc870\ud68c (\uc790\ub3d9 \uc8fc\uc5b4\uc9c4 \ud69f\uc218\ub9cc\ud07c\ub9cc)query=xa.Query('t1302')data=query.call(shcode='005930',cnt=100).next(keypairs={'time':'cts_time'},total=5)total\uc744 \uba85\uc2dc\ud574\uc8fc\uba74 \ub2e4\uc74c\uc870\ud68c\uc758 \ubc18\ubcf5\ud68c\uc218\ub97c \uba87\ubc88\uae4c\uc9c0 \ud560 \uac83\uc778\uc9c0 \uc815\ud574\uc900\ub2e4.\n\uacfc\uac70 \ub370\uc774\ud130\uac00 \uc591\uc774 \ub108\ubb34 \ub9ce\uc740 \uacbd\uc6b0, dataframe\uac1d\uccb4 \uc548\uc5d0 \ub2f4\uc9c0 \ubabb\ud558\uace0 Out of memory\uac00 \ubc1c\uc0dd\n\ud560 \uc218 \uc788\uc73c\ubbc0\ub85c \uadf8\ub7f0\uacbd\uc6b0 \uc720\uc6a9\ud558\uac8c \uc0ac\uc6a9\uac00\ub2a5\ud558\ub2e4.Real \uc0ac\uc6a9\ubc954. App \uc0ac\uc6a9\ubc95\ub85c\uadf8\uc778 \ubc29\ubc95app=xa.App('../account.txt')app=xa.App('\uc544\uc774\ub514','\ud328\uc2a4\uc6cc\ub4dc','\uacf5\uc778\uc778\uc99d\ud328\uc2a4\uc6cc\ub4dc')app=xa.App(id='\uc544\uc774\ub514',pw='\ud328\uc2a4\uc6cc\ub4dc',cert='\uacf5\uc778\uc778\uc99d\ud328\uc2a4\uc6cc\ub4dc')\uc885\ubaa9\ucf54\ub4dc\uc870\ud68c\uc885\ubaa9\ucf54\ub4dc \uc804\uccb4(\ucf54\uc2a4\ud53c+\ucf54\uc2a4\ub2e5) \ub9ac\uc2a4\ud2b8\ub85c \ubc1b\uc544\uc624\uae30app.\uc885\ubaa9\ucf54\ub4dc.\uc804\uccb4\uc885\ubaa9\ucf54\ub4dc \ucf54\uc2a4\ud53c \ub9ac\uc2a4\ud2b8\ub85c \ubc1b\uc544\uc624\uae30app.\uc885\ubaa9\ucf54\ub4dc.\ucf54\uc2a4\ud53c\uc885\ubaa9\ucf54\ub4dc \ud22c\uc790\uc8fc\uc758 \ub9ac\uc2a4\ud2b8\ub85c \ubc1b\uc544\uc624\uae30app.\uc885\ubaa9\ucf54\ub4dc.\ud22c\uc790\uc8fc\uc758\uc885\ubaa9\uba85\uc73c\ub85c \ucf54\ub4dc \uac80\uc0c9\ud558\uae30app.\uc885\ubaa9\ucf54\ub4dc.\uc885\ubaa9\uba85\uc73c\ub85c\uac80\uc0c9('\uc0bc\uc131\uc804\uc790')\uc885\ubaa9\ucf54\ub4dc\ub85c \uc885\ubaa9\uba85 \uac80\uc0c9\ud558\uae30app.\uc885\ubaa9\ucf54\ub4dc.\uc885\ubaa9\ucf54\ub4dc\ub85c\uac80\uc0c9('005930')\uac04\ud3b8\uac80\uc0c9app.\uc885\ubaa9\ucf54\ub4dc('\uc0bc\uc131\uc804\uc790')app.\uc885\ubaa9\ucf54\ub4dc('005930')\uc885\ubaa9\uc815\ubcf4\uc870\ud68c\uc77c/\uc6d4/\uc8fc\ubd09\uc870\ud68c# \uc77c\ubd09 500\uac1c \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('005930').\uc77c\ubd09(500)# \uc8fc\ubd09 100\uac1c \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('005930').\uc8fc\ubd09(100)# \uc6d4\ubd09 \ub05d\uae4c\uc9c0(\uac00\ub2a5\ud55c\ub370\uc774\ud130) \uc804\ubd80 \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('005930').\uc6d4\ubd09()# \uc77c\ubd09 \ub05d\uae4c\uc9c0(\ub370\uc774\ud130 \ud5c8\uc6a9\ub418\ub294 \ub370\uae4c\uc9c0) \uc870\ud68c\uc77c/\uc6d4/\uc8fc\ubd09\uc758 \uacbd\uc6b0 request \ud55c\ubc88\uc5d0 300\uac1c\uc529 \uc694\uccad\ud558\ubbc0\ub85c 300\uac1c \ub2e8\uc704\ub85c \ub04a\uc5b4\uc11c \uc694\uccad\ud558\uba74 \ud6a8\uc728\uc801\uc774\ub2e4\n\uc77c/\uc6d4/\uc8fc\ubd09\uc740 \ub3d9\uc791\ubc29\uc2dd\uc774 \uac19\uc9c0\ub9cc \ubd84\ubd09\uc740 \ub3d9\uc791\ubc29\uc2dd\uc774 \ub2e4\ub984\ubd84\ubd09\uc870\ud68c (30\ucd08/1\ubd84/3\ubd84/5\ubd84/10\ubd84/30\ubd84/60\ubd84 \uac00\ub2a5)app.\uc885\ubaa9\uc815\ubcf4('005930').\ubd84\ubd09()# 30\ucd08\ubd09app.\uc885\ubaa9\uc815\ubcf4('005930').\ubd84\ubd09(1)# 1\ubd84\ubd09app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ubd84\ubd09(2)# 3\ubd84\ubd09app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ubd84\ubd09(5)# 30\ubd84\ubd09\uccb4\uacb0\uc870\ud68c# \ub2f9\uc77c\uccb4\uacb0\uc870\ud68c (\uc804\uc77c: \uad6c\ubd84=1)app.\uc885\ubaa9\uc815\ubcf4('005930').\uccb4\uacb0(\uad6c\ubd84=0)# 9\uc2dc30\ubd84\uc5d0\uc11c 10\uc2dc30\ubd84\uae4c\uc9c0 \ub370\uc774\ud130app.\uc885\ubaa9\uc815\ubcf4('005930').\uccb4\uacb0(\uc885\ub8cc\uc2dc\uac04='103000',\uac1c\uc218=1000)\ud638\uac00\uc870\ud68c (30\ucd08/1\ubd84/3\ubd84/5\ubd84/10\ubd84/30\ubd84/60\ubd84 \uac00\ub2a5)app.\uc885\ubaa9\uc815\ubcf4('005930').\ud638\uac00()# 30\ucd08\ubd09app.\uc885\ubaa9\uc815\ubcf4('005930').\ud638\uac00(1)# 1\ubd84\ubd09app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ud638\uac00(2)# 3\ubd84\ubd09app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ud638\uac00(5)# 30\ubd84\ubd09\ud14c\ub9c8app.\uc885\ubaa9\uc815\ubcf4('005930').\ud14c\ub9c8# 30\ucd08\ubd09\uc2e0\ud638\uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\uc2e0\ud638\uc870\ud68c(30)\ub9e4\ubb3c\ub300app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ub9e4\ubb3c\ub300()# \ub2f9\uc77capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ub9e4\ubb3c\ub300(2)# \uc804\uc77capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ub9e4\ubb3c\ub300(3)# \ub2f9\uc77c+\uc804\uc77c\ubd84\ubcc4/\uc77c\ubcc4 \uccb4\uacb0\uac15\ub3c4app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ubd84\ubcc4\uccb4\uacb0\uac15\ub3c4()# \ub2f9\uc77c, 380\uac1c \uc774\ud558app.\uc885\ubaa9\uc815\ubcf4('005930').\uc77c\ubcc4\uccb4\uacb0\uac15\ub3c4(2500)# 2500\uac1c, \uc57d 10\ub144\uce58\ud2f1\ucc28\ud2b8/\ubd84\ucc28\ud2b8# \uc624\ub298\ub0a0\uc9dc\uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ud2f1\ucc28\ud2b8(N\ud2f1=1)# \uc624\ub298\ub0a0\uc9dc 1\ud2f1\ucc28\ud2b8app.\uc885\ubaa9\uc815\ubcf4('005930').\ubd84\ucc28\ud2b8(N\ubd84=3)# \uc624\ub298\ub0a0\uc9dc 3\ubd84\ucc28\ud2b8# \uae30\uac04\uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ud2f1\ucc28\ud2b8(N\ud2f1=10,\uc2dc\uc791\uc77c='20200503')# 10\ud2f1 '20200503'\ubd80\ud130 \uc624\ub298\uae4c\uc9c0 \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\ubd84\ucc28\ud2b8(\uc2dc\uc791\uc77c='20200501',\uc885\ub8cc\uc77c='20200504')# 1\ubd84\ubd09 \uc2dc\uc791\uc77c\ubd80\ud130 \uc885\ub8cc\uc77c\uae4c\uc9c0\uc870\ud68c\uc77c\ucc28\ud2b8/\uc8fc\ucc28\ud2b8/\ubd09\ucc28\ud2b8app.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\uc77c\ucc28\ud2b8(\uc2dc\uc791\uc77c='20200503')# \uc77c\ucc28\ud2b8 '20200503'\ubd80\ud130 \uc624\ub298\uae4c\uc9c0 \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\uc8fc\ucc28\ud2b8(\uc2dc\uc791\uc77c='20190101',\uc885\ub8cc\uc77c='20191231')# \uc8fc\ucc28\ud2b8 2019\ub144\ub3c4 \uc870\ud68capp.\uc885\ubaa9\uc815\ubcf4('\uc0bc\uc131\uc804\uc790').\uc6d4\ucc28\ud2b8(\uc2dc\uc791\uc77c='20000101',\uc885\ub8cc\uc77c='20191231')# \uc6d4\ucc28\ud2b8 2000\ub144\ubd80\ud130 2019\ub144\uae4c\uc9c0 \uc870\ud68c"} +{"package": "xingchen", "pacakge-description": "\u901a\u4e49\u661f\u5c18(https://tongyi.aliyun.com/xingchen) Python SDK"} +{"package": "xinge", "pacakge-description": "xinge-api-python\u6982\u8ff0\u6b22\u8fce\u4f7f\u7528\u4fe1\u9e3d ServerSDK - Python \u7248\u672c\u5c01\u88c5\u7684\u5f00\u53d1\u5305\uff0c\u5177\u6709\u6700\u65b0\u7248\u672c\u7684\u4fe1\u9e3d API \u529f\u80fd\u3002\u517c\u5bb9\u7248\u672cPython 3.7\u9700\u8981\u4f7f\u7528\u5230 requests\u279c~pipinstallrequests\u5982\u9700\u8fd0\u884c\u6d4b\u8bd5\u7528\u4f8b\uff0c\u9700\u8981\u5b89\u88c5 unittestpip install unittest2\u5f15\u7528 SDKpipinstallxinge\u4ee3\u7801\u793a\u4f8bfromxinge_pushimportXinge,Messagexinge=Xinge('app id','secret key')message=Message(title=\"some title\",content=\"some content\")xinge.push_account(platform=\"android\",account=\"some account\",message=message)ret_code,error_msg=xinge.push_account(platform=\"android\",account=\"some account\",message=message)ifret_code:print\"push failed! retcode:{}, msg:{}\".format(ret_code,error_msg)else:print\"push successfully!\"Publishpython3setup.pysdistbdist_wheel\npython3-mtwineuploaddist/*"} +{"package": "xingenester", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xinge_push", "pacakge-description": "Xinge Push API for Python(http://xg.qq.com).\nYou can download the lastest version here:http://xg.qq.com/xg/ctr_index/downloadInstallationTo install xinge_push, simply:$ sudo pip install xinge_pushor alternatively install via easy_install:$ sudo easy_install xinge_pushor from source:$ sudo python setup.py install"} +{"package": "xingkacky", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xingkong", "pacakge-description": "\u83b7\u53d6\u4fe1\u606f\u7ec4\u4ef6\u6a21\u5757"} +{"package": "xingpackage", "pacakge-description": "new121120231211\u65b0\u5efa\u5e93"} +{"package": "xingpdf", "pacakge-description": "This is the homepage of our project."} +{"package": "xing-plus", "pacakge-description": "xing plus supports more easy api for eBEST INVESTMENT"} +{"package": "xingpypitest", "pacakge-description": "xingpypitestfor testing pypi\u6d4b\u8bd5PyPI"} +{"package": "xingtest", "pacakge-description": "No description available on PyPI."} +{"package": "xing-tick-crawler", "pacakge-description": "xing-tick-crawler\ubc18\ub4dc\uc2dc python 32bit\ub97c \uc0ac\uc6a9\uc124\uce58pipinstallxing-tick-crawler\uc0ac\uc6a9\uc608\uc2dc1. config.py \ud30c\uc77c \uc0dd\uc131 \ubc0f \uc124\uc815config={\"id\":\"my_id\",# xing api \uc544\uc774\ub514\"password\":\"my_password\",# xing api \ud328\uc2a4\uc6cc\ub4dc\"cert_password\":\"my_cert_password\",# \uacf5\ub3d9\uc778\uc99d\uc11c \ube44\ubc00\ubc88\ud638}RES_FOLDER_PATH=\"C:/eBEST/xingAPI/Res\"# xing_tick_crawler Res \ud30c\uc77c \ud3f4\ub354 \uc704\uce58TICKER_DATA_FOLDER_PATH=\".\"# tick \ub370\uc774\ud130 \uc800\uc7a5\ud560 \uc704\uce582. main.py \uc0dd\uc131 \ubc0f \uc2e4\ud589\ud544\uc694\uc5c6\ub294 \ub370\uc774\ud130 off \ud558\uace0, \uc2e4\ud589\"\"\"\ud06c\ub864\ub7ec 1 \uad6c\ub3c5\uc635\uc158 (\uae30\ubcf8\uac12 All True)- STOCK_VI_ON_OFF- KOSPI_ORDER_BOOK- KOSPI_AFTER_MARKET_ORDER_BOOK- KOSPI_AFTER_MARKET_TICK- KOSPI_BROKER_INFO- STOCK_FUTURES_ORDER_BOOK- STOCK_FUTURES_TICK\ud06c\ub864\ub7ec 2 \uad6c\ub3c5\uc635\uc158 (\uae30\ubcf8\uac12 All True)- KOSDAQ_ORDER_BOOK- KOSDAQ_AFTER_MARKET_ORDER_BOOK- KOSDAQ_AFTER_MARKET_TICK- KOSDAQ_BROKER_INFO\"\"\"fromxing_tick_crawler.crawlerimportcrawler_1,crawler_2,crawl_kospi_tick,crawl_kosdaq_tickfromdatetimeimportdatetimefrommultiprocessingimportProcess,get_contextfrommultiprocessing.queuesimportQueueif__name__==\"__main__\":crawler_1_subs_option={# \uc8fc\uc2dd VI \uc815\ubcf4 off'STOCK_VI_ON_OFF':False,}crawler_2_subs_option={}queue=Queue(ctx=get_context())p1=Process(target=crawl_kospi_tick,args=(queue,))p2=Process(target=crawl_kosdaq_tick,args=(queue,))p3=Process(target=crawler_1,args=(queue,),kwargs=crawler_1_subs_option)p4=Process(target=crawler_2,args=(queue,),kwargs=crawler_2_subs_option)p1.start()p2.start()p3.start()p4.start()whileTrue:tick=queue.get()waiting_tasks=queue.qsize()tick_type,tick_data=tickprint(f\"\\r{datetime.now()}waiting tasks :{'%6d'%waiting_tasks}\",end='')print(tick_type,tick_data)\uad6c\ud604 Real \ubaa9\ub85d\uc8fc\uc2dd\uc2dc\uc7a5\ucf54\uc2a4\ud53c \ud638\uac00\ucf54\uc2a4\ud53c \uccb4\uacb0\ucf54\uc2a4\ub2e5 \ud638\uac00\ucf54\uc2a4\ub2e5 \uccb4\uacb0\uc8fc\uc2ddVI \ubc1c\ub3d9\ud574\uc81c\ucf54\uc2a4\ud53c \uc2dc\uac04\uc678\ub2e8\uc77c\uac00 \ud638\uac00\ucf54\uc2a4\ud53c \uc2dc\uac04\uc678\ub2e8\uc77c\uac00 \uccb4\uacb0\ucf54\uc2a4\ub2e5 \uc2dc\uac04\uc678\ub2e8\uc77c\uac00 \ud638\uac00\ucf54\uc2a4\ub2e5 \uc2dc\uac04\uc678\ub2e8\uc77c\uac00 \uccb4\uacb0\ucf54\uc2a4\ud53c \uac70\ub798\uc6d0\ucf54\uc2a4\ub2e5 \uac70\ub798\uc6d0\ucf54\uc2a4\ud53c \ud504\ub85c\uadf8\ub7a8\ub9e4\ub9e4 \uc885\ubaa9\ubcc4\ucf54\uc2a4\ub2e5 \ud504\ub85c\uadf8\ub7a8\ub9e4\ub9e4 \uc885\ubaa9\ubcc4\uc120\ubb3c\uc635\uc158\uc2dc\uc7a5\uc8fc\uc2dd\uc120\ubb3c \ud638\uac00\uc8fc\uc2dd\uc120\ubb3c \uccb4\uacb0\uc8fc\uc2dd\uc120\ubb3c \uac00\uaca9\uc81c\ud55c\ud3ed\ud655\ub300\ucf54\uc2a4\ud53c200 \uc120\ubb3c\ud638\uac00\ucf54\uc2a4\ud53c200 \uc120\ubb3c\uccb4\uacb0\ucf54\uc2a4\ud53c200 \uc635\uc158\uccb4\uacb0\ucf54\uc2a4\ud53c200 \uc635\uc158\ud638\uac00\ucf54\uc2a4\ud53c200 \uc635\uc158\uac00\uaca9\uc81c\ud55c\ud3ed\ud655\ub300"} +{"package": "xingu", "pacakge-description": "Xingu for automated ML model trainingXingu is a framework of a few classes that helps on full industrialization of\nyour machine learning training and deployment pipelines. Just write your\nDataProvider class, mostly in a declarative way, that completely controls\nyour training and deployment pipeline.Notebooks are useful in EDA time, but when the modeling is ready to become\na product, use Xingu proposed classes to organize interactions with DB\n(queries), data cleanup, feature engineering, hyper-parameters optimization,\ntraining algorithm, general and custom metrics computation, estimation\npost-processing.Don\u2019t save a pickle at the end of your EDA, let Xingu organize a versioned\ninventory of saved models (PKLs) linked and associated to commit hashes and\nbranches of your code.Don\u2019t save metrics manually and in an informal way. Metrics are first class\ncitizens, so use Xingu to write methods that compute metrics and let it\nstore metrics in an organized database that can be queried and compared.Don\u2019t make ad-hoc plots to understand your data. Plots are important assets\nto measure the quality of your model, so use Xingu to write methods that\nformaly generate versioned plots.Do not worry or even write code that loads pre-req models, use Xingu pre-req\narchitecture to load pre-req models for you and package them together.Don\u2019t save ad-hoc hypermaters after optimizations. Let Xingu store and manage\nthose for you in a way that can be reused in future trains.Don\u2019t change your code if you want different functionality. Use Xingu\nenvironment variables or command line parameters to strategize your trains.Don\u2019t manually copy PKLs to production environments on S3 or other object\nstorage. Use Xingu\u2019s deployment tools to automate the deployment step.Don\u2019t write database integration code. Just provide your queries and Xingu\nwill give you the data. Xingu will also maintain a local cache of your data\nso you won\u2019t hammer your database across multiple retrains. Do the same with\nstatic data files with parquet, CSV, on local filesystem or object storage.Xingu can run anyware, from your laptop, with a plain SQLite database, to\nlarge scale cloud-powered training pipelines with GitOps, Jenkins, Docker\netc. Xingu\u2019s database is used only to cellect training information, it isn\u00b4t\nrequired later when model is used to predict.Installpipinstallhttps://github.com/avibrazil/xinguorpipinstallxinguUse to Train a ModelCheck your project has the necessary files and folders:$find\ndataproviders/\ndataproviders/my_dataprovider.py\nestimators/\nestimators/myrandomestimator.py\nmodels/\ndata/\nplots/Train with DataProvidersid_of_my_dataprovider1andid_of_my_dataprovider2, both defined indataproviders/my_dataprovider.py:$xingu\\--dpsid_of_my_dataprovider1,id_of_my_dataprovider2\\--databasesathena\"awsathena+rest://athena.us...\"\\--query-cache-pathdata\\--trained-models-pathmodels\\--debugUse the APISee theproof of concept notebookwith vairous usage scenarios:POC 1. Train some ModelsPOC 2. Use Pre-Trained Models for Batch PredictPOC 3. Assess Metrics and create Comparative ReportsPOC 4. Check and report how Metrics evolvedPOC 5. Play with Xingu barebonesPOC 6. Play with theConfigManagerPOC 7. Xingu Estimators in the Command LinePOC 8. Deploy Xingu Data and Estimators between environments (laptop, staging, production etc)Procedures defined by XinguXingu classes do all the heavy lifting while you focus on your machine learning\ncode only.ClassCoachis responsible of coordinating the training process of one or\nmultiple models. You control parallelism via command line or environment\nvariables.ClassModelimplements a standard pipelines for train, train with hyperparam\noptimization, load and save pickles, database access etc. These pipelines are\nis fully controlled by your DataProvider or the environment.ClassDataProvideris a base class that is constantly queried by theModelto determine how theModelshould operate. Your should create a class derived\nfromDataProviderand reimplement whatever you want to change. This will\ncompletely change behaviour ofModeloperation in a way that you\u00b4ll get a\ncompletelly different model.It is yourDataProviderthat defines the source of training data as SQL\nqueries or URLs of parquets, CSVs, JSONsIt is yourDataProviderthat defines how multi-source data should be\nintegratedIt is yourDataProviderthat defines how data should be split into train\nand test setsYourDataProviderdefines whichEstimatorclass to useYourDataProviderdefines how theEstimatorshould be initialized and\noptimizedYourDataProviderdefines which metrics should be computed, how to\ncompute them and against which datasetYourDataProviderdefines which plots should be created and against\nwhich datasetSee below when and how each method of yourDataProviderwill be called\nbyxingu.ModelClassEstimatoris another base class (that you can reimplement) to contain\nestimator-specific affairs. There will be anEstimator-derived class for an\nXGBoostRegressor, other for a CatBoostClassifier, other for a\nSciKit-Learn-specific algorithm, including hyperparam optimization logic and\nlibraries. A concreteEstimatorclass can and should be reused across multiple\ndifferent models.The hierarchical diagrams below expose complete Xingu pipelines with all their\nsteps. Steps marked with \ud83d\udcab are were you put your code. All the rest is Xingu\nboilerplate code ready to use.Coach.team_train():Train various Models, all possible in parallel.Coach.team_train_parallel()(background, parallelism controled byPARALLEL_TRAIN_MAX_WORKERS):Coach.team_load()(for pre-req models not trained in this session)Per DataProvider requested to be trained:Coach.team_train_member()(background):Model.fit()calls:\ud83d\udcabDataProvider.get_dataset_sources_for_train()return dict of queries and/or URLsModel.data_sources_to_data(sources)\ud83d\udcabDataProvider.clean_data_for_train(dict of DataFrames)\ud83d\udcabDataProvider.feature_engineering_for_train(DataFrame)\ud83d\udcabDataProvider.last_pre_process_for_train(DataFrame)\ud83d\udcabDataProvider.data_split_for_train(DataFrame)return tuple of dataframesModel.hyperparam_optimize()(decide origin of hyperparam)\ud83d\udcabDataProvider.get_estimator_features_list()\ud83d\udcabDataProvider.get_target()\ud83d\udcabDataProvider.get_estimator_optimization_search_space()\ud83d\udcabDataProvider.get_estimator_hyperparameters()\ud83d\udcabEstimator.hyperparam_optimize()(SKOpt, GridSearch et all)\ud83d\udcabEstimator.hyperparam_exchange()\ud83d\udcabDataProvider.post_process_after_hyperparam_optimize()\ud83d\udcabEstimator.fit()\ud83d\udcabDataProvider.post_process_after_train()Coach.post_train_parallel()(background, only ifPOST_PROCESS=true):Per trained Model (parallelism controled byPARALLEL_POST_PROCESS_MAX_WORKERS):Model.save()(PKL save in background)Model.trainsets_save()(save the train datasets, background)Model.trainsets_predict():Model.predict_proba()orModel.predict()(seebelow)\ud83d\udcabDataProvider.pre_process_for_trainsets_metrics()Model.compute_and_save_metrics(channel=trainsets)(seebelow)\ud83d\udcabDataProvider.post_process_after_trainsets_metrics()Coach.single_batch_predict()(seebelow)Coach.team_batch_predict():Load from storage and use various pre-trained Models to estimate data from a pre-defined SQL query.\nThe batch predict SQL query is defined into the DataProvider and this process will query the database\nto get it.Coach.team_load()(for all requested DPs and their pre-reqs)Per loaded model:Coach.single_batch_predict()(background)Model.batch_predict()\ud83d\udcabDataProvider.get_dataset_sources_for_batch_predict()Model.data_sources_to_data()\ud83d\udcabDataProvider.clean_data_for_batch_predict()\ud83d\udcabDataProvider.feature_engineering_for_batch_predict()\ud83d\udcabDataProvider.last_pre_process_for_batch_predict()Model.predict_proba()orModel.predict()(seebelow)Model.compute_and_save_metrics(channel=batch_predict)(seebelow)Model.save_batch_predict_estimations()Model.predict()andModel.predict_proba():Model.generic_predict()\ud83d\udcabDataProvider.pre_process_for_predict()orDataProvider.pre_process_for_predict_proba()\ud83d\udcabDataProvider.get_estimator_features_list()\ud83d\udcabEstimator.predict()orEstimator.predict_proba()\ud83d\udcabDataProvider.post_process_after_predict()orDataProvider.post_process_after_predict_proba()Model.compute_and_save_metrics():Sub-system to compute various metrics, graphics and transformations over\na facet of the data.This is executed right after a Model was trained and also during a batch predict.Predicted data is computed beforeModel.compute_and_save_metrics()is called.\nByModel.trainsets_predict()andModel.batch_predict().Model.save_model_metrics()calls:Model.compute_model_metrics()calls:Model.compute_trainsets_model_metrics()calls:AllModel.compute_trainsets_model_metrics_{NAME}()All \ud83d\udcabDataProvider.compute_trainsets_model_metrics_{NAME}()Model.compute_batch_model_metrics()calls:AllModel.compute_batch_model_metrics_{NAME}()All \ud83d\udcabDataProvider.compute_batch_model_metrics_{NAME}()Model.compute_global_model_metrics()calls:AllModel.compute_global_model_metrics_{NAME}()All \ud83d\udcabDataProvider.compute_global_model_metrics_{NAME}()Model.render_model_plots()calls:Model.render_trainsets_model_plots()calls:AllModel.render_trainsets_model_plots_{NAME}()All \ud83d\udcabDataProvider.render_trainsets_model_plots_{NAME}()Model.render_batch_model_plots()calls:AllModel.render_batch_model_plots_{NAME}()All \ud83d\udcabDataProvider.render_batch_model_plots_{NAME}()Model.render_global_model_plots()calls:AllModel.render_global_model_plots_{NAME}()All \ud83d\udcabDataProvider.render_global_model_plots_{NAME}()Model.save_estimation_metrics()calls:Model.compute_estimation_metrics()calls:AllModel.compute_estimation_metrics_{NAME}()All \ud83d\udcabDataProvider.compute_estimation_metrics_{NAME}()"} +{"package": "xingxing", "pacakge-description": "No description available on PyPI."} +{"package": "xingyun", "pacakge-description": "XingYun \uff08\u884c\u96f2\uff09XingYun is a package that helps store data , code and log to cloud and manage them. Tastes better if consumed together withEgorovSystem.Installationpip install xingyunBefore use, better to set upEgorovSystemand set values for the following entries:aws_access,xingyun-getid,xingyun-GlobalDataManager.ExampleBelow is an example for usage. For more advanced usage seedoc.project 1# project_1.pyfromxingyunimportGlobalDataManager,Logger,make_hook_loggerlogger=Logger()G=GlobalDataManager(\"test/1\",[make_hook_logger(logger)])# ----- save data -----G.set(\"a\",114514,force_timestamp=0)G.set(\"a\",1919810)# ----- load data -----assertG.get(\"a\")==1919810assertG.get(\"a\",time_stamp=0)=114514# ----- save log -----G.log(\"\u54fc\u54fc\u54fc\u554a\u554a\u554a\u554a\u554a\")# stdout: \u54fc\u54fc\u54fc\u554a\u554a\u554a\u554a\u554aassertG.get(\"_log\").endswith(\"\u54fc\u54fc\u54fc\u554a\u554a\u554a\u554a\u554a\")# ----- save code -----G.log_code()assertG.get(\"_code\").get(\"project_1.py\")==open(\"project_1.py\",\"r\").read()project 2# project_2.pyfromxingyunimportGlobalDataManager,Logger,make_hook_loggerlogger=Logger()# share data between multiple runs by initializing with the same name.G=GlobalDataManager(\"test/1\")# ----- load data from another run -----assertG.get(\"a\")==1919810assertG.get(\"a\",time_stamp=0)=114514"} +{"package": "xingyunlib", "pacakge-description": "xingyunlib[toc]\u5f00\u53d1\u8005\uff1a\u4e25\u5b50\u6631|\u5d14\u8f69\u5b87v1.2.20201004#v1.2.xx\u4ee5\u540e\u5168\u662f\u6b63\u5f0f\u7248##hack-20201004:\u4fee\u590dxesuser\u6545\u969c\u7248\u6743\u6240\u6709\uff0c\u4fb5\u6743\u5fc5\u7a76\u5185\u7f6e\u51fd\u6570 \u5bfc\u5165\u65b9\u5f0f\uff1afromxingyunlibimport*\u52a0\u5bc6\u51fd\u6570md=md5(\"111\")#\u4f5c\u7528\uff1a\u7528MD5\u52a0\u5bc6\"111\"\uff0c\u8fd4\u56de\u4e00\u4e2a\u5b57\u7b26\u4e32s1=sha1(\"111\")#\u4f5c\u7528\uff1a\u7528sha1\u52a0\u5bc6\"111\"\uff0c\u8fd4\u56de\u4e00\u4e2a\u5b57\u7b26\u4e32s256=sha256(\"111\")#\u4f5c\u7528\uff1a\u7528sha1\u52a0\u5bc6\"111\"\uff0c\u8fd4\u56de\u4e00\u4e2a\u5b57\u7b26\u4e32\u989c\u8272\u7c7bcolor=colorX(\u989c\u8272,\u4f20\u8fdb\u53bb\u7684\u989c\u8272\u7c7b\u578b)#\u7c7b\u578b\u652f\u6301\"rgb\",\"hsv\",\"hex\"#\u793a\u4f8b\uff1acolor=colorX((100,100,100),\"rgb\")color.color\u8fd4\u56de\u989c\u8272z=color.colorcolor_to(to_color,change=False)\u8fd4\u56de\u4e00\u4e2a\u8981\u8f6c\u6362\u7684\u989c\u8272to_color:\u8f6c\u6362\u7684\u989c\u8272\uff0c\u7c7b\u578b\u652f\u6301\"rgb\",\"hsv\",\"hex\"change\uff1a\u662f\u5426\u66f4\u6539\u539f\u6765\u7684\u989c\u8272color=colorX((255,255,255),\"rgb\")#\u5b9e\u4f8b\u5316rgbcolor.color_to(\"hex\",True)#\u66f4\u6539\u8fdb\u5236\u4e3a16\u8fdb\u5236print(color.color)#\u6253\u5370\u51facolor.colorall\uff08\u4e00\u6b21\u6027\u5bfc\u5165\u6269\u5c55\uff01\u53ef\u80fd\u51fa\u73b0\u8986\u76d6\u73b0\u8c61\uff01\uff09\u4f7f\u7528\u65b9\u5f0ffromxingyunlib.allimport*#\u6216\u8005importxingyunlib.allasxingyunlibprint_format\uff08print\u683c\u5f0f\u5316\u6269\u5c55\uff09\u5f00\u53d1\u8005\uff1a\u4e25\u5b50\u6631\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.print_formatimport*print()print(*str,t=0,sepr=\" \",end=\"\\n\")\u6211\u4eec\u6765\u9010\u4e2a\u8bb2\u89e3\u4ed6\u4eec\u7684\u7528\u6cd5\u9996\u5148\u6765\u770bt\u53c2\u6570\uff1a\nt=\u6bcf\u4e2a\u5b57\u505c\u7559\u7684\u65f6\u95f4(\u9ed8\u8ba4\u4e3a\u4e0d\u505c\u7559)\n\u6bd4\u5982\u8bf4\uff0c\u8981\u6bcf\u4e2a\u5b57\u505c\u75591\u79d2\uff0c\u8f93\u51fa\"nice\"\u7684\u4ee3\u7801\u5982\u4e0b\uff1aprint(\"nice\",t=1)\u7136\u540e\u6211\u4eec\u6765\u770bend\u53c2\u6570\n\u8fd9\u4e2aend\u53c2\u6570\u5176\u5b9e\u548c\u539f\u6765print\u7684end\u53c2\u6570\u662f\u540c\u6837\u7684\u4f5c\u7528\n\u9ed8\u8ba4\u662f\"\\n\"(\u6362\u884c\u7b26)\u6700\u540e\u6211\u4eec\u770bsepr\u53c2\u6570\uff0c\u8fd9\u4e2a\u53c2\u6570\u4e5f\u662f\u548c\u539f\u6765print\u7684sepr\u662f\u540c\u6837\u7684\u4f5c\u7528\n\u6211\u4eec\u6765\u770b\u4e00\u4e2a\u4f8b\u5b50\uff1aprint(\"ni\",\"e\",sepr=\"c\")\u6700\u540e\u8f93\u51fa\u7684\u5c31\u662f\u201cnice\u201d\u6211\u4eec\u6765\u770b\u5927\u5bb6\u8fd9\u4e2a\u5f88\u5173\u5fc3\u7684\u53d8\u8272\u7b80\u6d01\u65b9\u5f0f\n\u6211\u4eec\u5728\u53d8\u8272\u5177\u4f53\u652f\u6301\u8fd9\u4e9b\u989c\u8272\uff1a\n\u7ea2\u3001\u767d\u3001\u7eff\u3001\u84dd\u3001\u9ec4\u3001\u9752\u3001\u7d2b\n\u7528\u6cd5\u5982\u4e0b\uff08\u6ce8\u610f\u662f\u4e24\u4e2a\u659c\u6760\uff09\uff1a\n'\\'+\u989c\u8272\uff08\u5b57\u7684\u989c\u8272\u53d8\u5316\uff09\n'\\l'+\u989c\u8272\uff08\u5b57\u7684\u989c\u8272\u53d8\u5316,\u4eae\u8272\uff09\n'\\b'+\u989c\u8272\uff08\u5b57\u7684\u80cc\u666f\u53d8\u5316\uff09\n'\\bl'+\u989c\u8272\uff08\u5b57\u7684\u80cc\u666f\u53d8\u5316,\u4eae\u8272\uff09\n'\\'(\u53bb\u9664\u6240\u6709\u7684\u53d8\u8272\u6548\u679c)clear_os()clear_os()\u6e05\u9664\u5c4f\u5e55\u4e0a\u7684\u6240\u6709\u6587\u5b57xes\u66f4\u6539\uff08\u53bb\u9664xeslib\u91cc\u9762\u6240\u6709\u7684print\uff09\u6700\u65b0\u7248\u672c\u7684xingyunlib\u589e\u52a0\u4e86xeslib\u7684\u5185\u5bb9\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.xesimportxeslib\u91cc\u9762\u7684\u5e93\u540d\u66f4\u6539\uff1a\u628axeslib\u91cc\u9762\u6240\u6709\u7684print\u90fd\u53bb\u4e86\u4fee\u6539AIspeak.speak\u51fd\u6570fromxingyunlib.xesimportAIspeakxes.AIspeak.speak(\"hello python!\",\"file.mp3\")\"\"\"\u672c\u7a0b\u5e8f\u4f5c\u7528\uff1a\u5c06hello python\uff01\u4fdd\u5b58\u5230file.mp3\u97f3\u9891\u6587\u4ef6\u91cc\u9762\uff0c\u5e76\u4e14\u4e0d\u64ad\u653e\"\"\"xes.AIspeak.speak(\"hello python!\")\"\"\"\u672c\u7a0b\u5e8f\u4f5c\u7528\uff1a\u64ad\u653ehello python\uff01\u8fd9\u6bb5\u97f3\u9891\"\"\"xesapp\uff08\u83b7\u53d6\u5b66\u800c\u601d\u7ad9\u4e0a\u67d0\u4e2a\u4f5c\u54c1\u7684\u6570\u636e\uff01\u5df2\u4fee\u590d\uff01\uff09\u5f00\u53d1\u8005\uff1a\u4e25\u5b50\u6631|\u5d14\u8f69\u8bed\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.xesappimport*xesapp(url)=xesapp(url)\u6784\u5efa\u4e00\u4e2a\u8fd0\u884c\u5bf9\u8c61\nurl\u4e3a\u5b66\u800c\u601d\u91cc\u9762\u7684py\u4f5c\u54c1\u7f51\u5740\u63a5\u4e0b\u6765\u8bb2\u8fd9\u4e2a\u7c7b\u7684\u65b9\u6cd5\uff1aget_hot()\u8fd4\u56de\u4f5c\u54c1\u7684\u70ed\u5ea6print(xesapp.get_hot())get_cover()\u8fd4\u56de\u4f5c\u54c1\u5c01\u9762\u7684urlprint(xesapp.get_cover())load_cover(filename)\u4e0b\u8f7d\u4f5c\u54c1\u5c01\u9762\u5230filenamexesapp.load_cover(\"\")get_view()\u8fd4\u56de\u4f5c\u54c1\u7684\u89c2\u770b\u4eba\u6570print(xesapp.get_view())get_hot()\u8fd4\u56de\u4f5c\u54c1\u7684\u70ed\u5ea6print(xesapp.get_hot())get_like()\u8fd4\u56de\u4f5c\u54c1\u7684\u70b9\u8d5e\u6570print(xesapp.get_like())get_unlike()\u8fd4\u56de\u4f5c\u54c1\u7684\u70b9\u8e29\u6570print(xesapp.get_unlike())load_file(cache = \"\")\u9ed8\u8ba4\u4e0b\u8f7d\u4f5c\u54c1\u6e90\u6587\u4ef6\u5230\u5de5\u4f5c\u76ee\u5f55\n\u5982\u679ccache\u4e0d\u4e3a\u7a7a\u62e9\u4e0b\u8f7d\u5230\u8fd9\u4e2a\u6587\u4ef6\u5939xesapp.load_file()is_like()\u5224\u65ad\u5728\u7a0b\u5e8f\u8fd0\u884c\u8fd9\u4e2a\u4f5c\u54c1\u6709\u6ca1\u6709\u4eba\u70b9\u8d5e\n\u8fd4\u56de\u4e00\u4e2abool\u503c\nTrue\uff1a\u70b9\u8d5e\u4e86\nFalse\uff1a\u70b9\u8e29\u4e86\nNone\uff1a\u6ca1\u6709\u70b9\u8d5e\u4e5f\u6ca1\u6709\u70b9\u8e29ifxesapp.is_like==True:print(\"\u70b9\u8d5e\u4e86\")elifxesapp.is_like==False:print(\"\u70b9\u8e29\u4e86\")else:print(\"\u4ec0\u4e48\u90fd\u6ca1\u70b9\")run_app()\u8fd0\u884c\u8fd9\u4e2a\u4f5c\u54c1exec(xesapp.run_app())get_published()\u83b7\u53d6\u4f5c\u54c1\u7b2c\u4e00\u6b21\u4fdd\u5b58\u65f6\u95f4print(xesapp.get_published())get_modified()\u83b7\u53d6\u4f5c\u54c1\u6700\u540e\u4e00\u6b21\u66f4\u65b0\u65f6\u95f4print(xesapp.get_modified())is_hidden_code()\u83b7\u53d6\u4f5c\u54c1\u662f\u5426\u9690\u85cf\u4ee3\u7801ifxesapp.is_hidden_code():print(\"\u4f5c\u54c1\u7684\u4ee3\u7801\u9690\u85cf\u4e86\")else:print(\"\u4f5c\u54c1\u7684\u4ee3\u7801\u6ca1\u6709\u9690\u85cf\")get_description()\u83b7\u53d6\u4f5c\u54c1\u7684\u8bf4\u660eprint(xesapp.get_description())get_comments()\u83b7\u53d6\u4f5c\u54c1\u4e00\u5171\u6709\u591a\u5c11\u4eba\u8bc4\u8bbaprint(xesapp.get_comments())is_comments()\u83b7\u53d6\u4ece\u8fd9\u4e2a\u4f5c\u54c1\u521d\u59cb\u5316\u5230\u73b0\u5728\u662f\u5426\u6709\u4eba\u8bc4\u8bbaifxesapp.is_comments():print(\"\u8bc4\u8bba\u4e86\")else:print(\"\u6ca1\u6709\u8bc4\u8bba\")cmt(url)\u8fd9\u4e2a\u662f\u4e00\u4e2a\u83b7\u53d6\u8bc4\u8bba\u7684apidta_dic#\u83b7\u53d6\u4e00\u4e2a\u5305\u542b\u6240\u6709\u8bc4\u8bba\u7684\u5217\u8868a=cmt(\"http://code.xueersi.com/home/project/detail?lang=code&pid=9785566&version=offline&form=python&langType=python\")print(a.dta_dic)#\u8f93\u51fa\"\"\"\uff08\u7565\uff09\"\"\"fmt\uff08\uff09#\u8fd4\u56de\u4e00\u4e2a\u5b57\u7b26\u4e32\uff08\u8bc4\u8bba\u7684\u5b57\u7b26\u683c\u5f0f\u5316\uff09a=cmt(\"http://code.xueersi.com/home/project/detail?lang=code&pid=9785566&version=offline&form=python&langType=python\")print(a.fmt())#\u90e8\u5206\u8f93\u51fa\"\"\"[2020-10-17 20:52:11]\u4e00\u7ef4\u56de\u590d\u4e25\u5b50\u6631:\u5feb\u70b9=-=\u4e0d\u53d6\u5173\u5c31pen\u4f60[2020-10-17 20:51:31]\u4e00\u7ef4\u56de\u590d\u4e25\u5b50\u6631:\u6709\u65f6\u5173\u6ce8\u6211\u8fd9\u4e2a\u4eba\uff0c\u5e76\u4e0d\u662f\u592a\u597d\u7684\u9009\u62e9\u53d6\u5173\u6211\u5427\uff0c\u6709\u4e8b\u8bf7\u52a0qq\uff1a3456198711\u5fae\u4fe1\uff1ahuiyu431249891[2020-10-17 18:34:35]\u4fca\u7fd4\u56de\u590d\u4e25\u5b50\u6631:\u4f5c\u8005\u662f\u559c\u6b22\u4e92\u5173\u5417\uff1f\u5c45\u7136\u5173\u6ce8\u6211\u8fd9\u6837\u7684\u8682\u8681\uff0c\u592a\u611f\u52a8\u4e86[2020-10-15 21:56:11]\u9648\u5955\u7ff0\u56de\u590d\u4e25\u5b50\u6631:\u8003\u8651\u5408\u4f5c\u561b[2020-10-10 19:29:26]\u831c\u5e7b\u56de\u590d\u4e25\u5b50\u6631:\u4f5c\u8005\u5728\u5417[2020-10-10 19:10:42]\u848b\u72c4\u7481\u56de\u590d\u4e25\u5b50\u6631:\u4e92\u5173.......(\u7565)\"\"\"sorted\uff08by=\u201clikes\u201d,reverse=True\uff09#\u8bbe\u7f6e\u6392\u5e8fa=cmt(\"http://code.xueersi.com/home/project/detail?lang=code&pid=9785566&version=offline&form=python&langType=python\")a.sorted(by=\"likes\",reverse=True)#reverse\u4e3a \u4ece\u9ad8\u5230\u4f4e\u6392\u5217print(a.fmt())\"\"\"[2020-10-15 21:56:11]\u9648\u5955\u7ff0\u56de\u590d\u4e25\u5b50\u6631:\u8003\u8651\u5408\u4f5c\u561b[2020-10-17 20:52:11]\u4e00\u7ef4\u56de\u590d\u4e25\u5b50\u6631:\u5feb\u70b9=-=\u4e0d\u53d6\u5173\u5c31pen\u4f60[2020-10-17 18:34:35]\u4fca\u7fd4\u56de\u590d\u4e25\u5b50\u6631:\u4f5c\u8005\u662f\u559c\u6b22\u4e92\u5173\u5417\uff1f\u5c45\u7136\u5173\u6ce8\u6211\u8fd9\u6837\u7684\u8682\u8681\uff0c\u592a\u611f\u52a8\u4e86[2020-10-01 20:51:57]\u738b\u738e\u73f0\u56de\u590d\u4e25\u5b50\u6631:\u554a\u8fd9...\uff08\u7565\uff09\"\"\"xesuser\uff08\u83b7\u53d6\u5b66\u800c\u601d\u7ad9\u4e0a\u67d0\u4e2a\u7528\u6237\u7684\u6570\u636e\uff01\u5df2\u4fee\u590d\uff01\uff09\u6ce8\u610f\uff01\uff01\u5343\u4e07\u4e00\u5b9a\u4e0d\u8981\u8d85\u9ad8\u9891\u7387\u8bf7\u6c42\uff0c\u5426\u5219\u4f1a\u62a5\u9519\uff01\uff01\uff01\u4f5c\u8005\uff1a\u4e25\u5b50\u6631\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.xesuserimport*get_user_id(\"\u4f5c\u54c1\u7f51\u5740\")user_id=get_user_id(\"\u4f5c\u54c1\u7f51\u5740\")#\u672c\u4f5c\u54c1\u6700\u91cd\u8981\u7684\u51fd\u6570\uff0c\u8fd9\u4e2a\u83b7\u53d6\u4f5c\u54c1\u7f51\u5740\u7684\u4f5c\u8005\u7684user_idget__fans(user_id)fans_info=get_fans(user_id)#\u8fd9\u4e2auser_id\u4ece\u4e0a\u9762\u62ff#\u83b7\u53d6\u8fd9\u4e2a\u4eba\u7c89\u4e1d\u7684\u5927\u90e8\u5206\u4fe1\u606f\uff0c\u8fd4\u56de\u4e00\u4e2a\u5217\u8868#\u6bcf\u9879\u662f\u4e00\u4e2a\u5b57\u5178\uff1afans_info[x][\"realname\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u540d\u5b57fans_info[x][\"avatar_path\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u5934\u50cf\u7684urlfans_info[x][\"fans\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u7c89\u4e1d\u6570\u91cffans_info[x][\"follows\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u5173\u6ce8\u6570\u91cfget_follows(user_id)follows_info=get_follows(user_id)#\u5927\u4f53\u548cget_fans\u4e00\u6837#\u83b7\u53d6\u8fd9\u4e2a\u4eba\u7c89\u4e1d\u7684\u5927\u90e8\u5206\u4fe1\u606f\uff0c\u8fd4\u56de\u4e00\u4e2a\u5217\u8868#\u6bcf\u9879\u662f\u4e00\u4e2a\u5b57\u5178\uff1afollows_info[x][\"realname\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u540d\u5b57follows_info[x][\"avatar_path\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u5934\u50cf\u7684urlfollows_info[x][\"fans\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u7c89\u4e1d\u6570\u91cffollows_info[x][\"follows\"]#:\u83b7\u53d6\u7b2cx\u9879\u4ed6\u7684\u5173\u6ce8\u6570\u91cfget_info(user_id)user_info=get_info(user_id)#\u83b7\u53d6\u8fd9\u4e2a\u4eba\u7684\u5927\u90e8\u5206\u4fe1\u606f\uff0c\u8fd4\u56de\u4e00\u4e2a\u5b57\u5178user_info[\"name\"]#:\u8fd4\u56de\u8fd9\u4e2a\u4eba\u7684\u540d\u5b57user_info[\"slogan\"]#:\u8fd4\u56de\u8fd9\u4e2a\u4eba\u7684\u53e3\u53f7(\u540d\u5b57\u4e0b\u9762\u90a3\u6bb5)user_info[\"fans\"]#:\u8fd4\u56de\u8fd9\u4e2a\u4eba\u7684\u7c89\u4e1d\u6570\u91cfuser_info[\"follows\"]#:\u8fd4\u56de\u8fd9\u4e2a\u4eba\u7684\u5173\u6ce8\u6570\u91cfuser_info[\"icon\"]#:\u8fd4\u56de\u8fd9\u4e2a\u4eba\u7684\u5934\u50cfurluser(user_id)user=user(user_id)#\u8fd9\u4e2a\u5176\u5b9e\u5927\u90e8\u5206\u90fd\u662f\u524d\u9762\u7684\u5185\u5bb9\uff0c\u4e0d\u8fc7\u524d\u9762\u7684\u52a0\u8f7d\u6bd4\u8f83\u6162\uff0c\u8fd9\u4e2a\u9002\u7528\u9700\u8981\u6570\u636e\u6bd4\u8f83\u591a\u7684\u7a0b\u5e8fuser.works#\uff1a\u83b7\u53d6\u53d1\u5e03\u7684\u4f5c\u54c1\u603b\u6570#user.work_info#\uff1a\u83b7\u53d6\u53d1\u5e03\u7684\u4f5c\u54c1\u7684\u4fe1\u606f\uff0c\u8fd4\u56de\u4e00\u4e2a\u5217\u8868\uff0c\u5217\u8868\u7684\u6bcf\u9879\u90fd\u662f\u5b57\u5178user.work_num#\uff1a\u83b7\u53d6\u4e00\u5171\u6709\u591a\u5c11\u4e2a\u4f5c\u54c1\uff08\u66fe\u7ecf\u53d1\u8fc7\u7684\u4e5f\u7b97\uff09user.fans#\uff1a\u83b7\u53d6\u7c89\u4e1d\u603b\u6570#user.fans_info#\uff1a\u83b7\u53d6\u7c89\u4e1d\u4fe1\u606f\uff08\u548cget_fans\u8fd4\u56de\u4e00\u6837\u7684\u4fe1\u606f\uff09user.follows#\uff1a\u83b7\u53d6\u5173\u6ce8\u603b\u6570#user.follows_info#\uff1a\u83b7\u53d6\u5173\u6ce8\u4fe1\u606f\uff08\u548cget_follows\u8fd4\u56de\u4e00\u6837\u7684\u4fe1\u606f\uff09user.like_num#\uff1a\u83b7\u53d6\u70b9\u8d5e\u603b\u6570user.view_num#\uff1a\u83b7\u53d6\u6d4f\u89c8\u603b\u6570user.favorites#\uff1a\u83b7\u53d6\u6536\u85cf\u603b\u6570xesapi\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.xesapiimport*get_api(url)\u8fd4\u56deurl\u8fd9\u4e2aapi\u4e0a\u7684\u6570\u636e\u793a\u4f8b->http://code.xueersi.com/api/index/works/modulesprint(get_api(\"http://code.xueersi.com/api/index/works/modules\"))\"\"\"==\u8f93\u51fa=={'stat': 1, 'status': 1, 'msg': '\u64cd\u4f5c\u6210\u529f', 'data': [{'title': '\u53ef\u591a\u63a8\u8350', 'simple_title': '\u63a8\u8350', 'lines': 2, 'projects': [{'id': 11584188, 'name': '\u5706\u5708\u6218\u4e89', 'category': 1, 'type': 'normal', 'user_id': 9686613, 'thumbnail': 'https://rescode.xesimg.com/hufu-code/common/mit/32f6766530dc287c1c8ab00c634e352b.png', 'published': 1, 'published_at': '2020-11-18 19:42:53', 'modified_at': '2020-11-18 19:42:53', 'likes': 4, 'views': 333, 'comments': 0, 'version': '3.0', 'source': 'xes_live', 'deleted_at': None, 'original_id': 2, 'created_at': '2020-11-17 20:46:43', 'updated_at': '2020-11-20 21:25:02', 'weight': 1, 'adapter': '', 'hidden_code': 2, 'source_code_views': 3, 'removed': 0, 'first_frame': 'https://rescode.xesimg.com/hufu-code/common/mit/32f6766530dc287c1c8ab00c634e352b.png', 'unlikes': 5, 'project_id': 11584188, 'works_id': 11584188, 'lang': 'scratch', 'popular_score': 12.13, 'username': '\u51af\u5609\u777f', 'user_avatar': 'https://oot.xesimg.com/user/h/cc1e41a2dc511b8108a05b8f0dc8cf69.jpg', 'project_type': 'scratch', 'topic_id': 'CS_11584188'}, {'id': 11027485, 'name': '\u4e95\u5b57\u68cb\u5c0f\u6e38\u620f(\u53cc\u4eba)', 'category': 1, 'type': 'normal', 'user_id': 7818569, 'thumbnail':...(\u7565)\"\"\"get_page(page,lang=\"\",tag=\"\",type=\"popular\")page\uff1a\u9875\u7801lang\uff1a\u8bed\u8a00tag\uff1a\u6807\u7b7etype\uff1a\u722c\u53d6\u9875\u9762\u7c7b\u578b\uff08\u9ed8\u8ba4\u4e3apopular\uff09print(get_page(1,\"cpp\"))'''==\u8f93\u51fa=={'page': '1', 'per_page': '35', 'total': 7000, 'data': [{'id': 10443775, 'name': '\u6559\u4f60\u5982\u4f55\u9ed1\u7535\u8111', 'category': 1, 'type': 'normal', 'user_id': 8730932, 'thumbnail': 'https://livefile.xesimg.com/programme/assets/b33adba6678f5e477f65d0f36d5581eb.jpg', 'la...(\u7565)'''page_all_tags\u8fd9\u4e2a\u662f\u4e00\u4e2a\u5e38\u91cf(\u5c31\u662f\u4e0a\u9762\u90a3\u4e2atag\u53ef\u4ee5\u53d6\u5f97\u91cf)print(page_all_tags)\"\"\"==\u8f93\u51fa=={'all_tags': ['\u6e38\u620f', '\u52a8\u753b', '\u6545\u4e8b', '\u6a21\u62df', '\u827a\u672f', '\u6559\u7a0b', '\u7b97\u6cd5', '\u6d77\u9f9f', '\u6c99\u76d2\u4e13\u533a', '\u5176\u4ed6'], 'tips': '1\u3001\u4e3a\u4ec0\u4e48\u8981\u7ed9\u4f5c\u54c1\u6253\u5206\u7c7b\u6807\u7b7e\uff1fn\u4e3a\u4f60\u7684\u4f5c\u54c1\u9009\u62e9\u5206\u7c7b\uff0c\u66f4\u6709\u5229\u4e8e\u5176\u4ed6\u5c0f\u670b\u53cb\u7cbe\u51c6\u7684\u627e\u5230\u4f60\u7684\u4f5c\u54c1\uff0c\u8fd9\u6837\uff0c\u4f60\u7684\u4f5c\u54c1\u88ab\u522b\u4eba\u770b\u5230\u7684\u673a\u7387\u4f1a\u66f4\u5927\u54e6\u3002n\u4e00\u5b9a\u8981\u51c6\u786e\u7684\u9009\u62e9\u5206\u7c7b\uff0c\u4e0d\u8981\u968f\u4fbf\u9009\u62e9\u4e0d\u6216\u8005\u4e0d\u9009\u5466\uff01nn2\u3001\u5982\u4f55\u4e3a\u81ea\u5df1\u7684\u4f5c\u54c1\u9009\u62e9\u5206\u7c7b\uff1fn\u8981\u60f3\u51c6\u786e\u7684\u9009\u62e9\u5206\u7c7b\uff0c\u9996\u5148\u8981\u5148\u77e5\u9053\u6bcf\u4e2a\u5206\u7c7b\u4ee3\u8868\u4ec0\u4e48\u610f\u601d\uff0c\u4e00\u8d77\u6765\u4e86\u89e3\u4e00\u4e0b\u5427\uff01n\u6e38\u620f\uff1a\u5c04\u51fb\uff0c\u5192\u9669\uff0c\u8dd1\u9177\uff0c\u6362\u88c5\u7b49\u7b49\u8fd9\u4e9b\u90fd\u7b97\u4f5c\u6e38\u620f\u3002n\u52a8\u753b\uff1a\u7528\u7f16\u7a0b\u5b9e\u73b0\u52a8\u753b\u6548\u679c\u7684\u4f5c\u54c1\u3002n\u6545\u4e8b\uff1a\u7528\u7f16\u7a0b\u8868\u8fbe\u4e00\u4e2a\u5947\u5999\u7684\u6545\u4e8b\uff0c\u6bd4\u5982\u5199\u5c0f\u8bf4\u3002n\u6a21\u62df\uff1a\u89c6\u9891\u8f6f\u4ef6\u6a21\u62df\u5668\uff0c\u97f3\u4e50\u8f6f\u4ef6\u6a21\u62df\u5668\uff0c\u6d4f\u89c8\u5668\u6a21\u62df\u5668\uff0c\u751a\u81f3\u505a\u4e2a\u6a21\u62df\u7684\u7cfb\u7edf\u3002n\u827a\u672f\uff1a\u7f8e\u672f\uff0c\u97f3\u4e50\u7b49\u7b49\u7c7b\u578b\u7684\u4f5c\u54c1\u90fd\u53ef\u4ee5\u3002n\u6559\u7a0b\uff1a\u5982\u679c\u4f60\u662f\u5927\u725b\uff0c\u5c31\u5feb\u505a\u4f5c\u54c1\u6559\u522b\u4eba\u548c\u4f60\u4e00\u6837\u4f18\u79c0\u5427\uff01n\u7b97\u6cd5\uff1a\u7b97\u6cd5\u662f\u89e3\u51b3\u4e00\u4e2a\u95ee\u9898\u7684\u65b9\u6cd5\uff0cC++\u7528\u6237\u8bf7\u770b\u8fd9\u91cc\u3002n\u6d77\u9f9f\uff1a\u6d77\u9f9f\u753b\u56fe\u662fpython\u8bed\u8a00\u4e2d\u4e13\u95e8\u7528\u6237\u753b\u56fe\u7684\u65b9\u6cd5\u5466\uff01n\u6c99\u76d2\u4e13\u533a\uff1aMC\uff1fmini\uff1f\u4e3a\u4ec0\u4e48\u4e0d\u81ea\u5df1\u521b\u4f5c\u4e00\u4e2a\u7c7b\u4f3c\u7684\u4f5c\u54c1\u5462\uff1fn\u5176\u4ed6\uff1a\u5982\u679c\u6ca1\u60f3\u597d\u81ea\u5df1\u4f5c\u54c1\u7684\u5206\u7c7b\uff0c\u5c31\u9009\u8fd9\u4e2a\u5427\u3002'}\"\"\"pygame_extend\uff08pygame\u6269\u5c55\uff09\u5bfc\u5165\u65b9\u5f0f\uff1afromxingyunlib.pygame_extendimport*(\u8fd9\u6837\u987a\u4fbf\u5bfc\u5165pygame\u548csys\u6b38\u563f\u563f)\uff01\u6ca1\u5199\u5b8c\u6559\u7a0b\u7b49\u9700\u6c42\u591a\u4e86\u5728\u8bf4\u628a\uff01tkinter_extend\uff08tkinter\u6269\u5c55\uff09\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.tkinter_extendimport*\u4f5c\u8005\uff1a\u4e25\u5b50\u6631inpu_box(class)#\u521b\u5efa(\u5c31\u5f53button\u63a7\u4ef6\u7528)\uff1aa=inpu_box(tk,\u51fd\u6570\u540d,**\u6309\u94ae\u7684\u914d\u7f6e)#\u6253\u5305\uff1aa.pack(**pack\u7684\u914d\u7f6e)#\u914d\u7f6e\uff1aa.config_entry(**\u6587\u672c\u6846\u7684\u914d\u7f6e)a.config_button(**\u6309\u94ae\u7684\u914d\u7f6e)#\u5176\u5b9e\u4f60\u57fa\u672c\u53ef\u4ee5\u5f53\u505aEntry\u6765\u7528\uff0c\u9664\u4e86\u521d\u59cb\u5316\u8bed\u53e5\u8fd8\u6709\u914d\u7f6e\u4ee5\u5916\u57fa\u672c\u90fd\u662f\u4e00\u6837\u7684#\uff08\u5269\u4e0b\u7684\u6559\u7a0b\u8fd8\u6ca1\u5199\u5b8c\uff09jitter()\u4f5c\u7528\uff1a\u6296\u52a8\u7a97\u53e3\uff08\u9700\u8981\u5728\u7a97\u53e3\u52a0\u8f7d\u5b8c\u6bd5\u540e\u4f7f\u7528\uff0c\u5426\u5219\u53ef\u80fd\u4f1a\u51fa\u73b0\u9b3c\u755c\uff09fromtkinterimport*root=Tk()a=Text(root)a.pack(fill=BOTH)jitter(root)root.mainloop()center()\u4f5c\u7528\uff1a\u5c06\u7a97\u53e3\u5c45\u4e2dfromtkinterimport*root=Tk()a=Text(root)a.pack(fill=BOTH)jitter(root)root.mainloop()dsfAdmin\uff08\u81ea\u52a8\u5b89\u88c5\u7b2c\u4e09\u65b9\u5e93\uff09\u5f00\u53d1\u8005|\u4e25\u5b50\u6631(\u6682\u65f6\u53ea\u652f\u6301windows)\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.dsfAdminimport*get_pakages()\u4f5c\u7528\uff1a\u83b7\u53d6\u5df2\u5b89\u88c5\u6bcf\u4e2a\u5305\u7684\u7248\u672cforxinrange(len(get_pakages())):print(\"\u5e93\"+x[0].center(19,\" \"),\"\u7248\u672c\"+x[1].center(10,\" \"))find_pakages(pakages,ver=None)\u4f5c\u7528\uff1a\u83b7\u53d6\u65f6\u5426\u5b89\u88c5pakage\u8fd9\u4e2a\u5e93\uff0cver\u4ee3\u8868\u7248\u672c\uff0c\u9ed8\u8ba4\u4e0d\u8fdb\u884c\u7248\u672c\u76d1\u6d4biffind_pakages(\"xingyunlib\"):print(\"\u4f60\u6709\u5b89\u88c5xingyunlib\u5e93\uff01\")else:print(\"\u4f60\u6ca1\u6709\u5b89\u88c5xingyunlib\u5e93\uff01\")upgrade_pakages(pakage)\u4f5c\u7528\uff1a\u66f4\u65b0pakage\u8fd9\u4e2a\u5e93upgrade_pakages(\u201cxingyunlib\u201d)install_pakages(pakage)\u4f5c\u7528\uff1a\u5b89\u88c5\u8fd9\u4e2a\u5e93,\u5e38\u548cfind_pakages\u4e00\u8d77\u7528ifnotfind_pakages(\"alsolib\"):install_pakages(\"alsolib\")#\u6ce8\u610f\u8fd9\u4e2a\uff0c\u8fd9\u4e2a\u975e\u5e38\u91cd\u8981\u7684,\u53ef\u4ee5\u5728\u6ca1\u5b89\u88c5\u7b2c\u4e09\u65b9\u5e93\u7684\u65f6\u5019\u81ea\u52a8\u4e0b\u8f7d\u5e93dump_pip_list(filename)\u4f5c\u7528\uff1a\u5c06\u5e93\u7684list\u4fdd\u5b58\u5230\u8fd9\u4e2a\u6587\u4ef6\u91cc\u9762load_pip_list(filename)\u4f5c\u7528\uff1a\u5c06\u8fd9\u4e2a\u6587\u4ef6\u91cc\u9762\u7684\u5e93\u5bfc\u51fa\u5230\u6b63\u5728\u4f7f\u7528\u7684\u7f16\u8bd1\u5668dump_pip_list(\"pip_pakages\")#\u540c\u76ee\u5f55\u4f1a\u51fa\u73b0\u4e00\u4e2a\u2018pip_pakages.pip\u2019\u6587\u4ef6# |\u628a\u8fd9\u4e2a\u6587\u4ef6\u79fb\u5230\u53e6\u4e00\u53f0\u7535\u8111# vload_pip_list(\"pip_pakages\")#\u7136\u540e\u8fd9\u4e2a\u7a0b\u5e8f\u5c31\u4f1a\u81ea\u52a8\u5b89\u88c5\u5728\u7b2c\u4e00\u53f0\u7535\u8111\u4e0a\u6240\u6709\u7684\u7b2c\u4e09\u65b9\u5e93\u4e86image\uff08pillow\u53cawordcloud\u6269\u5c55\uff09\u5f00\u53d1\u8005|\u4e25\u5b50\u6631\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.imageimport*resize(filename,XY)\u4f5c\u7528\uff1a\u5c06filename\u8fd9\u4e2a\u6587\u4ef6\u53d8\u6210XY\u5927\u7684\u6587\u4ef6resive(\"img1.png\",(100,100))#\u5c06img1.png\u53d8\u6210100x100\u7684\u7f29\u7565\u56fecloud(text,font_path,savafile=None,image=None,background_color=\"white\",color=True)\uff08\u8fd9\u4e2a\u51fd\u6570\u8981\u5b89\u88c5numpy\u548cwordcloud\u5e93\uff09\u4f5c\u7528\uff1atext\u4e3a\u5217\u8868\uff0cfont_path\u4e3a\u5b57\u4f53\u6587\u4ef6\u7684\u4f4d\u7f6esavafile\u4e3a\u4fdd\u5b58\u7684\u6587\u4ef6\u540d\uff0cimage\u4e3a\u6a21\u677f\u56fe\u7247\u7684\u540d\u5b57background_color\u4e3a\u80cc\u666f\u989c\u8272 color\u4e3a\u662f\u5426\u6839\u636e\u6a21\u677f\u56fe\u7247\u7684\u989c\u8272\u4e0a\u8272\uff08\u5728\u6709\u6a21\u677f\u7684\u60c5\u51b5\u4e0b\uff09importostext=\"ahuidgayugwuydgatywefuwfdytafayuofdwtyfauyfatyfautfatyfatyufduyoawfgtydfeutoaftyaf\".split(\"a\")cloud(text,\"(\u4f60\u7684\u5b57\u4f53\u6587\u4ef6)\",\"all.png\")os.startfile(\"all.png\")add_text(img, text, **args)\u8fd9\u4e2a**args\u5305\u62ec\u4ee5\u4e0b\u5185\u5bb9font=\uff08\u201d\u5b57\u4f53\u6587\u4ef6.ttf\u201d\uff0c\u5b57\u53f7\uff09XY=\uff08x\u5750\u6807\uff0cy\u5750\u6807\uff09#\u8fd9\u4e2a\u5750\u6807\u4ee5\u56fe\u7247\u5de6\u4e0a\u89d2\u4e3a0\uff0c0\uff08\u539f\u70b9\uff09fillColor=\u989c\u8272\uff08\u5efa\u8bae\u4f7f\u752816\u8fdb\u5236\u989c\u8272\uff09show_img=True#\u8bbe\u7f6e\u662f\u5426\u5728\u4fee\u6539\u5b8c\u6210\u540e\u663e\u793a\u56fe\u7247\uff0c\u9ed8\u8ba4\u4e3aFalsechange_img=\"newimgname.png\"#\u8bbe\u7f6e\u8f93\u51fa\u7684\u56fe\u7247\u6587\u4ef6\u540dadd_text(\"\u539f\u56fe.png\",\"\u5e7f\u544a\",font=font,XY=XY,fillColor=fillColor,show_img=show_img,change_img=change_img)user\uff08\u81ea\u5b9a\u4e49\u7528\u6237\u7c7b\uff09\u5f00\u53d1\u8005|\u4e25\u5b50\u6631\u5bfc\u5165\u65b9\u5f0ffromxingyunlib.userimport*\u521d\u59cb\u5316\uff1auser_login(filename=None)filename:\u4e4b\u524d\u7684\u4fdd\u5b58\u6570\u636e\u7684\u6587\u4ef6\u540d\uff0c\u5982\u679c\u6ca1\u6709\u4fdd\u5b58\u8fc7\u8bf7\u4e0d\u8981\u5199filenameuser=user_login()#\u5bfc\u5165\u4e4b\u524d\u7684\u6570\u636euser=user_login(\"<\u6570\u636e\u6587\u4ef6\u540d\u79f0>\")\u6ce8\u518c\uff1auser.registered(name,key,flag=True,filename=None)name:\u6ce8\u518c\u7684\u540d\u5b57key:\u5bc6\u7801flag\u8bbe\u7f6e\u4e3aTrue:\u5982\u679c\u5df2\u7ecf\u5bfc\u5165\u6570\u636e\u5219\u8fd4\u56deFalse(\u5982\u679c\u5df2\u7ecf\u6ce8\u518c\u8fc7\u4e86\u5c31\u4e0d\u8ba9\u4f60\u6ce8\u518c)\u5426\u5219\u8fd4\u56deTrue(\u6ce8\u518c\u6210\u529f\uff09flag\u8bbe\u7f6e\u4e3aFalse\uff1a\u90fd\u53ef\u4ee5\u6ce8\u518cfilename\uff1a\u4fdd\u5b58\u6570\u636e\u6587\u4ef6\u7684\u540d\u79f0type=user.registered(input(\"\u8bf7\u8f93\u5165\u4f60\u7684\u540d\u5b57\uff1a\"),input(\"\u8bf7\u8f93\u5165\u4f60\u7684\u5bc6\u7801\uff1a\"),flag=True,filename=\"data\")iftype==True:print(\"\u6ce8\u518c\u6210\u529f\uff01\")else:print(\"\u6ce8\u518c\u5931\u8d25\uff01\")user.login(name,key)name:\u6ce8\u518c\u65f6\u7684\u540d\u79f0key:\u5bc6\u7801\u8fd4\u56de\u4e00\u4e2abool\u503c\uff0c\u4e3aTrue\u6216FalseTrue\uff1a\u9a8c\u8bc1\u5bc6\u7801\u6b63\u786e False\uff1a\u9a8c\u8bc1\u5931\u8d25type=user.login(input(\"\u8bf7\u8f93\u5165\u4f60\u7684\u540d\u5b57\uff1a\"),input(\"\u8bf7\u8f93\u5165\u4f60\u7684\u5bc6\u7801\uff1a\"))iftype==True:print(\"\u6ce8\u518c\u6210\u529f\uff01\")else:print(\"\u6ce8\u518c\u5931\u8d25\uff01\")user.load(filename)\u5bfc\u5165\u4fdd\u5b58\u7684\u6570\u636e\uff0cfilename\u4e3a\u6587\u4ef6\u540db=user_login()b.load(\"\u4f60\u4fdd\u5b58\u7684\u6587\u4ef6\u540d\")mail\u5bfc\u5165\u65b9\u5f0ffromxingyunlibimportmail\u7528\u6cd5\uff1amail.send(to,title,txt)mail.send(\"3161399620@qq.com\",\"hello python\",\"hello world!\")to:\u53d1\u9001\u7ed9\u7684\u90ae\u7bb1title:\u6807\u9898txt:\u53d1\u9001\u7684\u6587\u672cerr\uff08\u81ea\u5b9a\u4e49\u629b\u51fa\u9519\u8bef\uff09\u5bfc\u5165\u65b9\u5f0ffromxingyunlibimporterr\u5f53\u4f60\u6709\u4e00\u4e9b\u7a0b\u5e8f\u60f3\u5728\u7279\u5b9a\u7684\u60c5\u51b5\u7ec8\u6b62\u600e\u4e48\u529e\uff1f\u8bd5\u8bd5\u4e0b\u9762\u7684\u7a0b\u5e8ferr(txt)fromxingyunlibimporterra=input(\"\u8bf7\u8f93\u51651\uff1a\")ifa!=\"1\":#\u5982\u679c\u975e1err.err(\"\u4f60\u6ca1\u6709\u8f93\u51651\u3002\u3002\u3002\")else:...#\u7a0b\u5e8f\u81ea\u7136\u9000\u51fahttp_spider\uff08\u722c\u866b\uff09\u5bfc\u5165\u65b9\u5f0ffromxingyunlibimporthttp_spiderload_requests(str,between,line)\u9ed8\u8ba4\u503c\uff1abetween=\":\" ; line=\"\\n\"between\uff1a\u5206\u9694\u7b26line\uff1a\u6362\u884c\u7b26\u8fd9\u4e2a\u6982\u5ff5\u6709\u70b9\u96be\u7406\u89e3\uff0c\u5177\u4f53\u770b\u4e0b\u9762\u793a\u4f8b\uff0c\u80fd\u4e0d\u80fd\u542c\u61c2\u7531\u5929\u547dfromxingyunlibimporthttp_spiderheader=http_spider.load_requests(\"\"\"Accept: application/json, text/plain, */*Accept-Encoding: gzip, deflateAccept-Language: zh-CN,zh;q=0.9,en;q=0.8User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.116 Safari/537.36\"\"\",\": \",\"\\n\")#\u90a3\u6bb5\u5b57\u7b26\u4e32\u662f\u4ece\u6d4f\u89c8\u5668\u590d\u5236\u51fa\u6765\u7684print(header)\"\"\"----------\u8f93\u51fa\uff1a{'Accept': 'application/json, text/plain, */*', 'Accept-Encoding': 'gzip, deflate', 'Accept-Language': 'zh-CN,zh;q=0.9,en;q=0.8', 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.116 Safari/537.36'}\"\"\"\u4e3b\u8981\u4f5c\u7528\u662f\u81ea\u52a8\u5206\u6790\u4ece\u6d4f\u89c8\u5668\u590d\u5236\u51fa\u6765\u7684headersspider(*args,**kwargs)\u8fd9\u4e2a\u51fd\u6570\u5c31\u660e\u663e\u5f88\u6c34\uff0c\u5b8c\u5168\u662f\u51d1\u6570\u7528\u7684\uff0c\u4e0d\u8fc7\u5bf9\u4e8e\u4e00\u4e9b\u65b0\u624b\u6765\u8bf4\u8fd8\u662f\u6709\u70b9\u7528\u7684\u5176\u5b9e\u5c31\u662frequests\u7684\u53d8\u4f53\uff0c\u589e\u52a0\u4e86\u4e00\u4e2a\u5224\u65ad\u662f\u5426\u72b6\u6001\u7801\u662f\u542610x\uff0c40x\uff0c50x\u7684\u529f\u80fd\u800c\u5df2fromxingyunlibimporthttp_spiderprint(http_spider.spider(\"http://code.xueersi.com/api/compilers/6?id=6\").text)#\u7565\u53bb\u8f93\u51fa\u7ed3\u679cua_list\u8bdd\u4e0d\u591a\u8bf4\uff0c\u4e0a\u4ee3\u7801fromxingyunlibimporthttp_spiderprint(http_spider.ua_list)\"\"\"\u8f93\u51fa\uff1a['Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1)', 'Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0)', 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1)', 'Mozilla/4.0 (compatible; MSIE 9.0; Windows NT 6.1)', 'Mozilla/5.0 (compatible; rv:1.9.1) Gecko/20090702 Firefox/3.5', 'Mozilla/5.0 (compatible; rv:1.9.2) Gecko/20100101 Firefox/3.6', 'Mozilla/5.0 (compatible; rv:2.0) Gecko/20110101 Firefox/4.0', 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0.2) Gecko/20100101 Firefox/6.0.2', 'Mozilla/5.0 (compatible) AppleWebKit/534.21 (KHTML, like Gecko) Chrome/11.0.682.0 Safari/534.21', 'Opera/9.80 (compatible; U) Presto/2.7.39 Version/11.00', 'Mozilla/5.0 (compatible; U) AppleWebKit/533.1 (KHTML, like Gecko) Maxthon/3.0.8.2 Safari/533.1', 'Mozilla/5.0 (Linux; U; Android 2.2) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1 ', 'Mozilla/5.0 (iPhone; U; CPU OS 4_2_1 like Mac OS X) AppleWebKit/532.9 (KHTML, like Gecko) Version/5.0.3 Mobile/8B5097d Safari/6531.22.7', 'Mozilla/5.0 (iPad; U; CPU OS 4_2_1 like Mac OS X) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/4.0.2 Mobile/8C148 Safari/6533.18.5', 'Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_7) AppleWebKit/534.16+ (KHTML, like Gecko) Version/5.0.3 Safari/533.19.4']\"\"\"\u8fd9\u662f\u4e00\u4e2a\u5217\u8868\uff0c\u91cc\u9762\u6709\u5f88\u591a\u7b14\u8005\u641c\u96c6\u7684ua\uff0c\uff08\u622a\u81f32020-9-19\uff09\u6536\u5f55\u4e8615\u4e2aua\uff0c\u8db3\u591f\u4f60\u7528\u4e86get_xes_url(url)\u722c\u53d6\u4e00\u4e2axes\u7684\u9875\u9762fromxingyunlibimporthttp_spiderprint(http_spider.get_xes_url(\"http://code.xueersi.com/api/compilers/6?id=6\"))#\u7565\u53bb\u8f93\u51fa\u7ed3\u679cdata\uff08\u4fdd\u5b58\u6570\u636e\uff09\u6570\u636e\u7c7b\u65b9\u6cd52020-10-1\u4f5c\u8005\uff1a\u4e25\u5b50\u6631\u5bfc\u5165\u65b9\u5f0ffromxingyunlibimportdataData\u521d\u59cb\u5316\u65b9\u6cd5\uff1adta=data.Data(filename,find=False)\"\"\"filename:\u6587\u4ef6\u540d\uff0c\u82e5\u6ca1\u6709\u5219\u521b\u5efafind:\u641c\u7d22\u6a21\u5f0f\uff0c\u82e5\u6ca1\u6709filename\u5219\u62a5\u9519\"\"\"\u8f93\u5165\u6570\u636e\uff1achange_data(data)dta=data.Data(filename,find=False)#\u7565\"\"\"data\u53c2\u6570\u652f\u6301\u7684\u6570\u636e:list,bool,tutle,str,set,dict,int,float\"\"\"dta.change_data(\"\u52a0\u6cb9\uff01\")eval_data()\u628a\u4ece\u6587\u4ef6\u4e2d\u4fdd\u5b58\u7684\u6570\u636e\u8f6c\u6362\u6210\u53ef\u6267\u884c\u5185\u5bb9\"\"\"fruit.txt\u5185\u5bb9\uff1a[\"apple\",\"orange\"]\"\"\"dta=data.Data(\"fruit.txt\",find=False)dta.eval_data()forxindta.data:print(f\"fruit:{x}\")\"\"\"\u8f93\u51fa\u7ed3\u679c\uff1afruit:applefruit:orange\"\"\"save()\u4fdd\u5b58\u7ed3\u679c\u5230\u6587\u4ef6\u4e2ddta=data.Data(\"great\",find=False)dta.change_data([\"hhc\",\"hhv\"])dta.save()\"\"\"great\u5185\u5bb9:[\"hhc\",\"hhv\"]\"\"\""} +{"package": "xingyunlib-user-bin", "pacakge-description": "No description available on PyPI."} +{"package": "xingzuoxy", "pacakge-description": "Get constellation Info From juhe API"} +{"package": "xini", "pacakge-description": "xini - eXtract pyproject.toml configs to INIpyproject.tomlis a fantastic idea. I want all my tool configurations\nin my pyproject.toml file. Not all my tools support apyproject.tomlconfiguration option though, but why wait?xinipulls configurations from apyproject.tomlfile for:pytestflake8coveragepylintAnd generates the appropriate ini-config files.Install... pip install xiniHow Does It Work?Write tool configuration in thepyproject.tomlunder the appropriate \"[tool.toolname]\"\nsection. This becomes the standard location for your configurations.\nKeeppyproject.tomlin source control as normal.Runxiniin the root project directory where thepyproject.tomlfile exits.\n(xinidoes not search forpyproject.tomlfiles anywhere but the current directory.)xinigenerates standard named ini-config files in the current directory\n(e.g. .flake8, .coveragerc, etc.). Tools that use old-style ini file formats can then\nrun using the generated config file.No need to maintain these ini-config files in source\ncontrol.Make config changes inpyproject.tomland runxinito regnerate ini-config files.The FutureIt is my sincere hope that there is no future for this project. I wish\nall tool developers to build support forpyproject.tomlas a configuration\noption so a tool likexiniis unnecessary."} +{"package": "xinject", "pacakge-description": "IntroductionDocumentationInstallQuick StartLicensingIntroductionMain focus is an easy way to create lazy universally injectable dependencies;\nin less magical way. It also leans more on the side of making it easier to get\nthe dependency you need anywhere in the codebase.py-xinject allows you to easily inject lazily created universal dependencies into whatever code that needs them,\nin an easy to understand and self-documenting way.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiInstall# via pippipinstallxinject# via poetrypoetryaddxinjectQuick Start# This is the \"my_resources.py\" file/module.importboto3fromxinjectimportDependencyPerThreadclassS3(DependencyPerThread):def__init__(self,**kwargs):# Keeping this simple; a more complex version# may store the `kwargs` and lazily create the s3 resource# only when it's asked for (via a `@property or some such).self.resource=boto3.resource('s3',**kwargs)To use this resource in codebase, you can do this:# This is the \"my_functions.py\" file/modulefrom.my_resourcesimportS3defdownload_file(file_name,dest_path):# Get dependencys3_resource=S3.grab().resources3_resource.Bucket('my-bucket').download_file(file_name,dest_path)Inject a different version of the resource:from.my_resourcesimportS3from.my_functionsimportdownload_fileus_west_s3_resource=S3(region_name='us-west-2')defget_s3_file_from_us_west(file,dest_path):# Can use Dependencies as a context-manager,# inject `use_west_s3_resource` inside `with`:withus_west_s3_resource:download_file(file,dest_path)# Can also use Dependencies as a function decorator,# inject `use_west_s3_resource` whenever this method is called.@us_west_s3_resourcedefget_s3_file_from_us_west(file,dest_path):download_file(file,dest_path)LicensingThis library is licensed under the MIT-0 License. See the LICENSE file."} +{"package": "xinjingru", "pacakge-description": "No description available on PyPI."} +{"package": "xinlan-tools", "pacakge-description": "xinlan-toolspython\u5f00\u53d1\u7684\u5c0f\u5de5\u5177\u96c6\u3002\u6587\u4ef6\u52a0\u5bc6\u547d\u4ee4\u683c\u5f0f\uff1atoolsencrypt[--numbern]\u53c2\u6570\uff1afile_or_dir\u5fc5\u5e26\u53c2\u6570\uff0c\u9700\u8981\u52a0\u5bc6\u7684\u6587\u4ef6\u6216\u6240\u5728\u8def\u5f84--number\u53ef\u9009\u53c2\u6570\uff0c\u52a0\u5bc6\u4e2d\u4f7f\u7528\u7684\u5b57\u8282\u6570\uff0c\u9ed8\u8ba4\u4e3a10\u6587\u4ef6\u52a0\u5bc6\u548c\u89e3\u5bc6\u547d\u4ee4\u4e00\u81f4\uff0c\u8fd0\u884c\u7b2c\u4e00\u6b21\u662f\u52a0\u5bc6\uff0c\u8fd0\u884c\u7b2c\u4e8c\u6b21\u662f\u89e3\u5bc6\u56fe\u7247\u683c\u5f0f\u8f6c\u6362\u652f\u6301 png\u548cjpg\u4e4b\u95f4\u76f8\u4e92\u8f6c\u6362\n\u547d\u4ee4\u683c\u5f0f\uff1atoolsconvertsourcetarget\u53c2\u6570\uff1asource\u5fc5\u5e26\u53c2\u6570\uff0c\u9700\u8981\u8f6c\u6362\u7684\u56fe\u7247\u6587\u4ef6\u540dtarget\u5fc5\u5e26\u53c2\u6570\uff0c\u9700\u8f6c\u6362\u6210\u7684\u56fe\u7247\u6587\u4ef6\u540d"} +{"package": "xinmokk", "pacakge-description": "UNKNOWN"} +{"package": "xinnester", "pacakge-description": "UNKNOWN"} +{"package": "xin-optimisation", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xinp", "pacakge-description": "No description available on PyPI."} +{"package": "xinput", "pacakge-description": "Enable/disable xinput devices (for example, a touchpad) from terminal or using the API.PrerequisitesPython 2.6.8+, 2.7.+, 3.3.+InstallationLatest stable version from PyPI.$ pip install xinputLatest stable version from bitbucket.$ pip install -e hg+https://bitbucket.org/barseghyanartur/xinput@stable#egg=xinputLatest stable version from github.$ pip install -e git+https://github.com/barseghyanartur/xinput@stable#egg=xinputUsage examplesFirst argument represents device state (0 for disable and 1 for enable). Second argument represents device name.By default we operate withSynaptics TouchPadbut it\u2019s possible to have custom device names.After installation you should be able to disable/enable touchpad by typing \u201cdisable-touchpad\u201d or \u201cenable-touchpad\u201d\ncommands in your terminal.Command-lineTo enable Synaptics TouchPad, type in terminal:$ xinput-manage 1 Synaptic TouchPadTo disable Genius Optical Mouse, type in terminal:$ xinput-manage 0 Genius Optical MouseThere are also shortcuts for enabling/disabling the touchpad.Type the following in terminal to disable the touchpad:$ disable-touchpadType the following in terminal to enable the touchpad:$ enable-touchpadProgrammatically>>> from xinput import operate_xinput_device, MODE_ENABLE, DEVICE_NAME_SYNAPTIC, MODE_DISABLE\n>>> operate_xinput_device(MODE_DISABLE, DEVICE_NAME_SYNAPTIC)\n>>> operate_xinput_device(MODE_ENABLE, DEVICE_NAME_SYNAPTIC)LicenseGPL 2.0/LGPL 2.1SupportFor any issues contact me at the e-mail given in theAuthorsection.AuthorArtur Barseghyan "} +{"package": "xinput-gui", "pacakge-description": "xinput-guiA simple GUI for Xorg's Xinput tool.xinput allows you to edit properties of devices like keyboards, mice, and touchpads. This GUI wraps around the xinput command to make editing them faster and more user-friendly.Installationxinput-gui depends on Python 3.5+, GTK+ 3.20+, PyGObject, and xinput.Arch LinuxAvailable as a package on the AUR:xinput-guiInstall it withmakepkgor your preferred AUR helper.GentooAvailable as a Gentoo package thanks to@filalex77:app-misc/xinput-guiTo install it, run the following commands:eselect-repository enable bright\nemerge --sync\nemerge xinput-guipipAvailable on PyPI:xinput-guiInstall it with pip:pip install --user xinput-gui.Manual installClone this repo and run./setup.py install --user.UsageJust runxinput-gui. Selecting a device will list all of it's properties. When editing them, changes will be applied immediately.Contributingxinput-gui is written in Python 3. The GUI uses GTK+ 3 and was made using the Glade interface designer.Please feel free to open issues with bugs, feature requests, or any other discussion you find necessary.Pull requests are always welcome, but please make sure that there's an open issue for the bug you're fixing/feature you're adding first. Pull requests that are submitted that haven't already been discussed likely won't be or will take a while to be accepted. This is the kind of tool that can easily become bloated/difficult to use/get out of scope, so I do want to be fairly careful about what features are added.<3"} +{"package": "xinqing", "pacakge-description": "A class describes a person."} +{"package": "xinsongyan", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xinsonha", "pacakge-description": "No description available on PyPI."} +{"package": "xinspect", "pacakge-description": "Tools for static and dynamic code introspection.Helps with writing doctestsdef func(a=1, b=2, c=3):\n \"\"\"\n Example:\n >>> from this.module import * # import contextual namespace\n >>> import xinspect\n >>> globals().update(xinspect.get_func_kwargs(func)) # populates globals with default kwarg value\n >>> print(a + b + c)\n 6\n \"\"\"Helps with code that generates code>>> import ubelt as ub\n>>> source = ub.codeblock(\n>>> '''\n>>> p = os.path.dirname(join('a', 'b'))\n>>> glob.glob(p)\n>>> ''')\n>>> # Generate a list of lines to fix the name errors\n>>> lines = autogen_imports(source=source)\n>>> print(lines)\n['import glob', 'from os.path import join', 'import os']See Also:https://github.com/Erotemic/xdev"} +{"package": "xinstall", "pacakge-description": "xinstall: Easy Cross-platform Installation and Configuration of AppsInstall xinstall:::bash\npip3 install -U xinstallUsageRunxinstall -hfor the help doc.Below is an example of install SpaceVim and configure it.xinstall svim -icIn casexinstallis not on the search path,\nyou can usepython3 -m xinstall.maininstead.\nFor example,\nto check the help doc.python3 -m xinstall.main -hsudo Permissionxinstall has 3 levels ofsudopermission.(L1) Non-root user runningxinstall subcmd -ic: nosudopermission(L2) Non-root user runningxinstall --sudo subcmd -ic:sudois called when necessary(L3) Non-root user runningsudo xinstall subcmd -ic: root permission everywhere(L3) root user runningxinstall subcmd -ic: root permission everywhereThe suggested way is to runxinstal --sudo subcmd -icusing non-root user ifsudopermission is required.sudo xinstall subcmd -icmight have side effect as some tools are installed to the local user directory,\nin which casesudo xinstall subcmd -icinstalls the tool into/root/which might not what you wwant.ProxySome tools used by xinstall respect environment variableshttp_proxyandhttps_proxy.\nExporting those 2 evironment variable will make most part of xinstall work if proxy is required.export http_proxy=http://server_ip:port\nexport https_proxy=http://server_ip:port"} +{"package": "xint", "pacakge-description": "atomDiscover and create anything interesting!\u6df7\u5408 MXNet\uff0cPyTorch\uff0cTensrFlow \u7684\u5e93\u3002PyPIProvide PyPI support.pipinstallxintHelpViewxintin GitHub."} +{"package": "xintegrator", "pacakge-description": "No description available on PyPI."} +{"package": "xinterp", "pacakge-description": "xinterpThis package enables exact round to even datetime64 interpolation.InstallationClone the repository, enter the folder and:pip install -e .Usageimportnumpyasnpfromxinterpimportinterp_intlikexp=np.array([0,10,20])fp=np.array([0,1000,2000],dtype=\"datetime64[s]\")x=np.array([-5,0,5,10,15,20,25])nat=np.datetime64(\"NaT\")f=interp_intlike(x,xp,fp,left=nat,right=nat)f_expected=np.array([nat,0,500,1000,1500,2000,nat],dtype=\"datetime64[s]\")assertnp.array_equal(f,f_expected,equal_nan=True)assertf.dtype==f_expected.dtype"} +{"package": "xintesis", "pacakge-description": "XintesisSimple Python Flask based REST API builderRequire:python >= 3.6flask_restplus >= 0.11.0flask_cors >= 3.0.7flask_jwt_extended >= 3.10.0jinja2 >= 2.10.1click >= 7.0selenium-requests >= 1.3Install using:pip install xintesisorpython setup.py installTo build a new API project structure with sample package and project use command:python -m xintesis create-api "} +{"package": "xintian", "pacakge-description": "No description available on PyPI."} +{"package": "xintool", "pacakge-description": "xintoolpython3 open source toools"} +{"package": "xinUtil", "pacakge-description": "UNKNOWN"} +{"package": "xin-util", "pacakge-description": "Xin-utilSimple self-use great functionsInstallationUse the package managerpipto install utilities.pipinstall-ihttps://test.pypi.org/simple/xin-utilUsage# regular utilitiesfromxin_util.PrettyPrintDictimportpretty_print_dictfromxin_util.CreateDIYdictFromDataFrameimportCreateDIYdictFromDataFramefromxin_util.ReadWritePicklefileimportread_pickle,save_picklefromxin_util.DownloadFromS3importS3_download_folder,S3_upload_folderfromxin_util.BarPlotsimportplot_stacked_barfromxin_util.ZipAndUnzipimportzip,unzipfromxin_util.AccessSQLimportgetDBData,create# TimeSeriesfromxin_util.TimeSeriesFeatureEngineerimportTimeSeries,create_average_feature# NLP relatedfromxin_util.TextProcessimporttext_tokensfromxin_util.ResamplingDataimportup_resamplefromxin_util.Scoresimportsingle_label_f_score,single_label_included_score,multiple_label_included_scorefromxin_util.TFIDFpredictimporttf_idf_classifyfromxin_util.EmbeddingCNNpredictimportConvolution_Network_classifyfromxin_util.EmbeddingRNNpredictimportRecurrent_Network_classifyfromxin_util.FASTTEXTpredictimportfasttext_classifyfromxin_util.NBpredictimportNaive_Bayes_classifyfromxin_util.ONEHOTNNpredictimportOnehot_Network_classifyfromxin_util.LatentDirichletAllocationClassimportMyLDA# Model training time predictionfrommodel_trainingtime_prediction.layer_level_utilsimportget_train_datafrommodel_trainingtime_prediction.random_network_genimportgen_nnfrommodel_trainingtime_prediction.train_time_predictimportprediction_modelDocumentationPrettyPrintDictCreateDIYdictFromDataFrameReadWritePicklefileDownloadFromS3ZipAndUnzipTimeSeriesFeatureEngineerTextProcessResamplingDataScoresTFIDFpredictEmbeddingCNNpredictEmbeddingRNNpredictFASTTEXTpredictNBpredictONEHOTNNpredictLatentDirichletAllocationClassAccessSQLContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT"} +{"package": "xinv", "pacakge-description": "xinvA CLI tool for generating customized invoices. The content is hardcoded in\na configuration file but can be overridden with command options.Created specifically for personal needs, so probably not suitable for others.\nThe tool officially supports and is distributed only for macOS. Very likely,\nit works also on other Unix-like systems but no quality checks are done\nfor them.Usage$xinv\nUsage:xinv[OPTIONS]COMMAND[ARGS]...\n\nOptions:--helpShowthismessageandexit.\n\nCommands:createinitContributingRunning TestsBesides Python packages required for testing, extra tools have to be installed\nin your system in order to successfully run regression tests.\nPlease follow the instructions below.macOSbrewinstallwkhtmltopdfimagemagickpoppler"} +{"package": "xinvert", "pacakge-description": "xinvert1. IntroductionResearches on meteorology and oceanography usually encounterinversion problemsthat need to be solved numerically. One of the classical inversion problem is to solve Poisson equation for a streamfunction $\\psi$ given the vertical component of vorticity $\\zeta$ and proper boundary conditions.$$\\nabla^2\\psi=\\zeta$$Nowadaysxarraybecomes a popular data structure commonly used inBig Data Geoscience. Since the whole 4D data, as well as the coordinate information, are all combined intoxarray, solving the inversion problem become quite straightforward and the only input would be just onexarray.DataArrayof vorticity. Inversion on the spherical earth, like some meteorological problems, could utilize the spherical harmonics likewindspharm, which would be more efficient using FFT than SOR used here. However, in the case of ocean, SOR method is definitely a better choice in the presence of irregular land/sea mask.More importantly, this could be generalized into a numerical solver for elliptical equation usingSORmethod, with spatially-varying coefficients. Various popular inversion problems in geofluid dynamics will be illustrated as examples.One problem with SOR is that the speed of iteration usingexplicit loops in Pythonwill bee-x-t-r-e-m-e-l-y ... s-l-o-w! A very suitable solution here is to usenumba. We may try our best to speed things up using more hardwares (possibly GPU).Classical problems include Gill-Matsuno model, Stommel-Munk model, QG omega model, PV inversion model, Swayer-Eliassen balance model... A complete list of the classical inversion problems can be found atthis notebook.Whyxinvert?Thinking and coding in equations:User APIs are very close to the equations: unknowns are on the LHS of=, whereas the known forcings are on its RHS;Genearlize all the steady-state problems:All the known steady-state problems in geophysical fluid dynamics can be easily adapted to fit the solvers;Very short parameter list:Passing a singlexarrayforcing is enough for the inversion. Coordinates information is already encapsulated.Flexible model parameters:Model paramters can be either a constant, or varying with a specific dimension (like Coriolis $f$), or fully varying with space and time, due to the use ofxarray's broadcasting capability;Parallel inverting:The use ofxarray, and thusdaskallow parallel inverting, which is almost transparent to the user;Pure Python code for C-code speed:The use ofnumbaallow pure python code in this package but native speed;2. How to installRequirementsxinvertis developed under the environment withxarray(=version 0.15.0),dask(=version 2.11.0),numpy(=version 1.15.4), andnumba(=version 0.51.2). Older versions of these packages are not well tested.Install via pippipinstallxinvertInstall from githubgitclonehttps://github.com/miniufo/xinvert.gitcdxinvert\npythonsetup.pyinstall3. Examples:This is a list of the problems that can be solved byxinvert:GalleryGalleryinvert Poisson equation forhorizontal streamfunctioninvert Poisson equation foroverturning streamfunctioninvert geostrophic equation forbalanced massinvert Eliassen model foroverturning streamfunctioninvert PV balance equation forsteady reference stateinvert Gill-Matsuno model forwind and mass fieldsinvert Stommel-Munk model forwind-driven ocean circulationinvert Fofonoff model forinviscid/adiabatic steady stateinvert Bretherton model forsteady flow over topographyinvert Omega equation forQG vertical velocity4 Animate the convergence of iterationOne can see the whole convergence process of SOR iteration as:fromxinvertimportanimate_iteration# output has 1 more dimension (iter) than input, which could be animated over.# Here 40 frames and loop 1 per frame (final state is after 40 iterations) is used.psi=animate_iteration(invert_Poisson,vor,iParams=iParams,loop_per_frame=1,max_frames=40)See the animation at the top."} +{"package": "xinxu131813", "pacakge-description": "this is a nb lib"} +{"package": "xinyujaychou-nester", "pacakge-description": "No description available on PyPI."} +{"package": "xio", "pacakge-description": "### About xioXio is a Python micro framework for quickly write simple microservices REST based Web applications and APIs.Xio is builded on concept of resources, app , node and network- resources:The main concept is that everything is resource, a resource is a feature which match an uri and we can interact wich- app:An app is a root resource used as container for all resources it contain- nodeA node is a app gateway, an app (and so a resource) which provide unique checkpoint for resources deliveryNodes could be linked beetween for create network- networkA network is a container of nodes and define rules for decentralized backbone of resources### RequirementsYou need Python >= 2.7### Installation```pip install xio```### UsageBasic app creation```mkdir myfirstappcd myfirstappvi app.py```Here is an minimalist example of what app.py look like```#-*- coding: utf-8 -*--import xioapp = xio.app(__name__)@app.bind('www')def _(req):return 'Hello World'if __name__=='__main__':app.main()```start server```./app.py run```"} +{"package": "xion", "pacakge-description": "Xion is a JSON interface to Xfconf, using a slightly modified xfconf-query\nbin. Backup and restore Xfce settings in VCS-friendly files.This can be useful to synchronise custom keybinds across several Xfce\ninstallations.Usage`bash # Export custom commands to JSON. $ xion-exfce4-keyboard-shortcuts/commands/custom commands.json # Import them on another machine. $ xion-icommands.json # Want to clear existing commands to keep only those in commands.json? $ xion-icommands.json-r`More info withxion \u2013help.FeaturesExport channel settings, filtering on user-provided root, to JSON files.Import channel settings from those JSON files.Imported settings are immediately applied to your session.Replace entire channel setting trees, or just update with provided values.JSON files have a predictable formatting for easy versioning.ContextXion comes from the need to share parts of the Xfce settings between several\ncomputers.> Why don\u2019t you just version the Xfconf XML files?I got frustrated with the way Xfconf stored settings on disk: its XML files have\nunpredictable tag sorting and some volatile values, and Xfconf does not read\nthose settings unless you log back in, and this is if you don\u2019t overwrite them\nin the process. This makes diffing modifications cumbersome, especially when\ntrying to share parts of my settings in a Git repository. I needed a way to dump\nand restore only some parts of my settings.Xfconf is the daemon storing and providing most Xfce configuration values,\ncalled properties. Sadly, it is not possible to manipulate these values without\nbuilding against libxfconf, which itself uses Glib, which I simply don\u2019t know\nand don\u2019t want to use, either as a C program or using FFI. The lazy way is to\nuse xion-query, a modified build of the xfconf-query CLI tool.> Why don\u2019t you just use xfconf-query?It simply does not have a very machine-readable interface, so Xion uses a\nmodified build to work smoothly, removing some output aimed at humans and adding\nvalue types to its output. I tried to make it easy to get xion-query.Installation### Get xion-queryGo to my [Xfconf fork](https://github.com/Dece/xfconf/releases/) to get a build\nor find instructions on how to build it.If you want to build it manually, checkout the tags named \u201cxion-\u201d. It\nis possible to build xion-query with Docker if you don\u2019t want to mess around\nfinding the various dependencies.Once you have your build, name itxion-query, make it executable and place it\nsomewhere in your path, e.g. in/usr/local/bin/.### Get xionXion is available on PyPI:`bash # Installsystem-wide.$ sudo pip3 install xion # Install for your user. $ pip3 install xion--user`"} +{"package": "xiongmao", "pacakge-description": "xiongmaoFor a more tidy PandasBinding pandas methods to the dataframe class can make for more compact, more pythonic code with fewer edits required to make a change."} +{"package": "xiongmao-DelOro", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiongxiong", "pacakge-description": "Bearer token decoder for Python (>= 2.7 and 3).InstallationUsingpip:pip install xiongxiongXiongxiongClassThe classmustbe instantiated with the private key and, optionally,\nthe hashing algorithm (defaults tosha1).For example:fromxiongxiongimportXiongxiongxiongxiong=Xiongxiong(privateKey,'md5')n.b., An exception will be thrown if the specified hashing algorithm is\nnot supported. If you are using Python greater than 2.7.9 or 3.2, you\nwill have access to all the algorithms supported by your platform\u2019s\ninstance of OpenSSL; otherwise you are limited to MD5, SHA1, SHA224,\nSHA256, SHA384 and SHA512.Obviously, the private key and hashing algorithm must match those used\nby a token\u2019s encoder in order to successfully decode it.xiongxiong(accessToken)xiongxiong(basicLogin, basicPassword)An instantiation of theXiongxiongclass is callable and will decode\nthe seed data, expiration and validate from the bearer token/basic\nauthentication pair, returning aTokenobject (see below).TokenObjectThe decodedTokenis built, called by the above function, in such a\nway that its properties are read-only. (The factory function shouldn\u2019t\nbe invoked directly and has been designed to be a private module\nfunction, insofar as Python allows.) It nonetheless has the following\nmembers:.dataThe original seed data, which will be split into a list by:characters, wherever possible (a string, otherwise)..expirationThe expiration time (datetime.datetime).validThe validity of the token/basic pair (Boolean).For example, continuing from the above:fromdatetimeimportdatetimetokenData=xiongxiong(someBearerToken)iftokenData.valid:expiresIn=tokenData.expiration-datetime.now()print('Token expires in%dseconds.'%expiresIn.seconds)print('Contents:%s'%tokenData.data)The validity property (valid) will returnfalseif the token\ncan\u2019t be authenticated, otherwise it will test whether the token has\npassed its best before date."} +{"package": "xiot", "pacakge-description": "No description available on PyPI."} +{"package": "xipctl", "pacakge-description": "No description available on PyPI."} +{"package": "xiplot", "pacakge-description": "\u03c7iplot\u03c7iplot, pronounced like \"kaiplot\"[^1], is a web-first visualisation platform for multidimensional data, implemented in thexiplotPython package.[^1]: Pronouncing \u03c7iplot like \"xaiplot\" is also recognised.Description\u03c7iplot is built on top of thedashframework. The goal of the \u03c7iplot is to explore new insights from the collected data and to make data exploring user-friendly and intuitive.\n\u03c7iplot can be used without installation with theWASM-based browser version.You can find more details in theuser guideand in the paper:Tanaka, A., Tyree, J., Bj\u00f6rklund, A., M\u00e4kel\u00e4, J., Puolam\u00e4ki, K. (2023).\u03c7iplot: Web-First Visualisation Platform for Multidimensional Data.Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, Lecture Notes in Computer Science, pp. 335-339.DOI: 10.1007/978-3-031-43430-3_26For a quick demonstration, seethe videoor try theWASM version.ScreenshotInstallation freeYou can try out the installation free WASM version of \u03c7iplot atedahelsinki.fi/xiplot. Note that all data processing happens locally inyourbrowser nothing is sent to a server.Please refer to thewasmbranch for more information on how the WASM version is implementedInstallation\u03c7iplot can also be installed locally with:pip install xiplot.\nTo start the local server runxiplotin a terminal (with same Python environment venv/conda/... in the PATH).Or to use the latest, in-development, version clone this repository.\nTo install the dependencies runpip install -e .orpip install -r requirements.txt.\nTo start the local server runpython -m xiplot.For more options runxiplot --help.FundingThexiplotapplication was created byAkihiro TanakaandJuniper Tyreeas part of their summer internships in Kai Puolam\u00e4ki'sExploratory Data Analysis groupat the University of Helsinki.Akihiro's internpship was paid for by the Academy of Finland (decision 346376) with funding associated with the VILMA Centre of Excellence. Juniper's internship was paid for by \"Future Makers Funding Program 2018 of the Technology Industries of Finland Centennial Foundation, and the Jane and Aatos Erkko Foundation\", with funding associated with the Atmospheric AI programme of the Finnish Center for Artificial Intelligence.LicenseThemainbranch of thexiplotrepository is licensed under the MIT License (LICENSE-MITorhttp://opensource.org/licenses/MIT).ContributionUnless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you shall be licensed as described above, without any additional terms or conditions."} +{"package": "xiplot-filetypes", "pacakge-description": "\u03c7iplotplugin for additional file typesThis plugin adds support for additional file types (besidecsvandjson) to\u03c7iplot.\nCurrently, this plugin adds support forfeatherandparquet.\nNote that in theWASM versiononly support forparquetis added.InstallationIn non-WASM\u03c7iplotthis plugin should be automatically installed.\nOtherwise you can usepip install xiplot_filetypesin the same Python environment.In theWASM versionyou can install the plugin by going to the \"Plugin\" tab and selectingxiplot_filetypes."} +{"package": "xiPy", "pacakge-description": "The official pythonic library for the next-gen Xively platform."} +{"package": "xir", "pacakge-description": "# Python3 XIR Langauge Bindings## InstallationFrom this directory execute the following command to install globally on your system. If you would prefer to install locally you can also use the\u2013userflag from pip. For more info seepip3 install \u2013help.` sudo pip3 install . `"} +{"package": "xirasol", "pacakge-description": "placegolder for xirasol."} +{"package": "xircuits", "pacakge-description": "Docs\u2022Install\u2022Tutorials\u2022Developer Guides\u2022Contribute\u2022Blog\u2022DiscordComponent Libraries\u2022Project TemplatesXircuits is a Jupyterlab-based extension that enables visual, low-code, training workflows. It allows anyone to easily create executable python code in seconds.FeaturesRich Xircuits Canvas InterfaceUnreal Engine-like Chain Component InterfaceCustom Nodes and PortsSmart Link and Type Check LogicComponent TooltipsDynamic PortsCode GenerationXircuits generates executable python scripts from the canvas. As they're very customizable, you can perform DevOps automation like actions. Consider this Xircuits template which trains an mnist classifier.You can run the code generated python script in Xircuits, but you can also take the same script to train 3 types of models in one go using bash script:TrainModel.py --epoch 5 --model \"resnet50\"\nTrainModel.py --epoch 5 --model \"vgg16\"\nTrainModel.py --epoch 5 --model \"mobilenet\"Famous Python Library SupportXircuits is built on top of the shoulders of giants. Perform ML and DL using Tensorflow or Pytorch, accelerate your big data processing via Spark, or perform autoML using Pycaret. We're constantly updating our Xircuits library, so stay tuned for more!Didn't find what you're looking for? Creating Xircuits components is very easy! If it's in python - it can be made into a component. Your creativity is the limit, create components that are easily extendable!Effortless CollaborationCreated a cool Xircuits workflow? Just pass the .xircuits file to your fellow data scientist, they will be able to load your Xircuits canvas instantly.Created a cool component library? All your colleagues need to do is to drop your component library folder in theirs and they can immediately use your components.And many more.InstallationYou will need python 3.8+ to install Xircuits. We recommend installing in a virtual environment.$ pip install xircuitsYou will also need to install the component library before using them. For example, if you would like to use the Pytorch components, install them by:$ xircuits install pytorchFor the list of available libraries, you can checkhere.Download Examples$ xircuits examplesLaunch$ xircuitsDevelopmentCreating workflows and components in Xircuits is easy. We've provided extensive guides for you in ourdocumentation. Here are a few quick links to get you started:Tutorials:Your First Xircuits Worflow|Running a Xircuits Project TemplateComponent Development:Creating a Xircuits Component|Creating a Xircuits Component LibraryAdvanced:Xircuits Core DevelopmentUse CasesGPT Agent Toolkit | BabyAGIDiscord BotsPySparkAutoMLAnomaly DetectionNLPDevelopers DiscordHave any questions? Feel free to chat with the devs at ourDiscord!"} +{"package": "xiren", "pacakge-description": "UNKNOWN"} +{"package": "xirion", "pacakge-description": "No description available on PyPI."} +{"package": "xirr", "pacakge-description": "xirrIrregular internal rate of return (xirr) and net present value (npv) calculations.Based onhttps://stackoverflow.com/questions/8919718/financial-python-library-that-has-xirr-and-xnpv-functionwith some handling for special cases fromhttps://github.com/RayDeCampo/java-xirr/See theDocumentation."} +{"package": "xiRT", "pacakge-description": "A python package for multi-dimensional retention time prediction for linear and crosslinked\npeptides using a (Siamese) deep neural network architecture.OverviewDescriptionInstallationoverviewxiRT is a deep learning tool to predict the separation behavior (i.e. retention times) of linear\nand crosslinked peptides from single to multiple fractionation dimensions including RP (typically\ndirectly coupled to the mass spectrometer). xiRT was developed to predict retention times from a\nmulti-dimensional separation from the combination of SCX / hSAX / RP chromatography.\nHowever, xiRT supports all available chromatographic and other peptide separation\nmethodsxiRT requires the columns shown in the table below. Importantly, the xiRT framework requires that\nCSM are sorted such that in the Peptide1 - Peptide2, Peptide1 is the longer or lexicographically\nlarger one for crosslinked RT predictions. The sorting is done internally and may result in swapped\npeptide sequences in the output tables.DescriptionxiRT is meant to be used to generate additional information about CSMs for machine learning-based\nrescoring frameworks but the usage can be extended to spectral libraries, targeted acquisitions etc.\nTherefore xiRT offers several training / prediction modes that need to be configured\ndepending on the use case. At the moment training, prediction, crossvalidation are the supported\nmodes.training: trains xiRT on the input CSMs (using 10% for validation) and stores a trained modelprediction: use a pretrained model and predict RTs for the input CSMscrossvalidation: load/train a model and predict RTs for all data points without using them\nin the training process. Requires the training of several models during CVNote: all modes can be supplemented by using a pretrained model (\"transfer learning\") when not\nenough training data is available to achieve robust prediction performance.This readme only gives a brief overview about xiRTs functions and parameters. Please refer\nto thedocumentationfor more details and examples.Installation and UsagexiRT is a python package that comes with a executable python file. To run xiRT follow the steps\nbelow.RequirementsxiRT requires a running python installation on windows/mac/linux. All further requirements\nare managed during the installation process via pip or conda. xiRT was tested using python >3.7 with\nTensorFlow 1.4 and python >3.8 and TensorFlow >2.0. A GPU is not mandatory to run xiRT, however\nit can greatly decrease runtime. Further system requirements depend on the data sets to be used.InstallationTo install xiRT simply run the command below. We recommend to use an isolated python environment,\nfor example by using pipenvorconda. Installation should finish within minutes.Using pipenv:pipenv shellpip install xirtOptional: To enable CUDA support, using aconda environmentis the easiest solution.Conda will take care of the CUDA libraries and other dependencies. Note, xiRT runs either on CPUs\nor GPUs. To use a GPU specify CuDNNGRU/CuDNNLSTM as type in the LSTM settings, to use a CPU set the\ntype to GRU/LSTM.conda create --name xirt_env python=3.8conda activate xirt_envpip install xirtHint:\nThe plotting functionality for the network is not enabled per default because\npydot and graphviz sometimes make trouble when they are installed via pip. If on linux,\nsimply usesudo apt-get install graphviz, on windows download latest graphviz package fromhere, unzip the content of the file and thebindirectory path to the windows PATH variable. These two packages allow the visualization\nof the neural network architecture. xiRT will function also without this functionality.Older versions of TensorFlow will require the separate installation of tensorflow-gpu. We recommend\nto install tensorflow in conda, especially if GPU usage is desired.General UsageThis section explains the general usage of xiRT via the command line. A minimal working example\nin a quick-start guide fashion is availablehere.The command line interface (CLI) requires three inputs:input PSM/CSM fileaYAMLfile to configure the neural network architectureanother YAML file to configure the general training / prediction behaviour, called setup-configConfigs are either available viagithub.\nAlternatively, up-to-date configs can be generated from the xiRT package itself:xirt -p learning_params.yamlxirt -s xirt_params.yamlTo use these two parameter files in xiRT and store the results in a directory calledout_dir,run the following command:xirt -i psms.csv -o out_dir -x xirt_params.yaml -l learning_params.yamlTo adapt the xiRT parameters to your needs, edits to the YAML config file are needed. The configuration file\nis used to determine the prediction task (rp, scx, hsax, ...) but also to set important network parameters\n(number of neurons, layers, regularization). While the default network configuration offers suitable\nparameters for most situations, the prediction tasks need further adjustments. The adjustments\nneed to account for the type and number of prediction tasks. Please visit thedocumentationto\nget more information about viable configurations.Once xirt is running, the progress is logged to the terminal as well as a dedicated log file.\nThis log file summarizes the training steps and contains important information\n(settings, file paths, metrics). Further output files and quality control plots are then stored in\nthe specified output (-o) directory.\nFind a description for the fileshereinput formatshort nameexplicit column namedescriptionExamplepeptide sequence 1Peptide1First peptide sequence for crosslinksPEPRTIDERpeptide sequence 2Peptide2Second peptide sequence for crosslinks, or emptyELRVISfasta description 1Fasta1FASTA header / description of protein 1SUCD_ECOLI Succinate--CoA ligase [ADP-forming]fasta description 2Fasta2FASTA header / description of protein 2SUCC_ECOLI Succinate--CoA ligase [ADP-forming]PSMIDPSMIDA unique identifier for the identification1link site 1LinkPos1Crosslink position in the first peptide (0-based)3link site 2LinkPos2Crosslink position in the second peptide (0-based2scorescoreSingle score from the search engine17.12unique idPSMIDA unique index for each entry in the result table0TTisTTBinary column which is True for any TTTrueTDisTDBinary column which is True for any TDTrueDDisDDBinary column which is True for any DDTruefdrfdrEstimated false discovery rate0.01The first four columns should be self explanatory, if not check thesample input.\nThe fifth column (\"PSMID\") is a unique(!) integer that can be used as to retrieve CSMs/PSMs. In addition,\ndepending on the number retention time domains that should be learned/predicted the RT columns\nneed to be present. The column names need to match the configuration in the network parameter yaml.\nNote that xiRT swaps the sequences such that peptide1 is longer than peptide 2. In order to\nkeep track of this process all columns that follow the convention 1 and 2 are swapped.\nMake sure to only have such paired columns and not single columns ending with 1/2.xiRT configThis file determines the network architecture and training behaviour used in xiRT. Please see\nthedocumentationfor a\ndetailed example. For crosslinks the most important parameter sections to adapt are theoutputand\nthepredictionssection. Here the parameters must be adapted for the used chromatography\ndimensions and modelling choices. See also the providedexamples.Setup configThis file determines the input data to be used and gives some training procedure options. Please see\nthedocumentationfor\na detailed example.ContributorsSven GieseLudwig SinnCitationIf you consider xiRT helpful for your work please cite our manuscript.Currently, in preparation.RappsilberLabThe Rappsilber applies and develops crosslinking chemistry methods, workflows and software.\nVisit the lab page to learn more about the developedsoftware.xiSUITExiVIEW: Graham, M. J.; Combe, C.; Kolbowski, L.; Rappsilber, J. bioRxiv 2019.xiNET: Combe, C. W.; Fischer, L.; Rappsilber, J. Mol. Cell. Proteomics 2015.xiSPEC: Kolbowski, L.; Combe, C.; Rappsilber, J. Nucleic Acids Res. 2018, 46 (W1), W473\u2013W478.xiSEARCH: Mendes, M. L.; Fischer, L.; Chen, Z. A.; Barbon, M.; O\u2019Reilly, F. J.; Giese, S. H.; Bohlke\u2010Schneider, M.; Belsom, A.; Dau, T.; Combe, C. W.; Graham, M.; Eisele, M. R.; Baumeister, W.; Speck, C.; Rappsilber, J. Mol. Syst. Biol. 2019, 15 (9), e8994."} +{"package": "xirvik-tools", "pacakge-description": "Something here"} +{"package": "xi.sdk.resellers", "pacakge-description": "xi.sdk.resellersFor Resellers. Who are looking to Innovate with Ingram Micro's API SolutionsAutomate your eCommerce with our offering of APIs and Webhooks to create a seamless experience for your customers.Requirements.Python 3.7+Installation & Usagepip installIf you want to install from PyPI:pipinstallxi.sdk.resellersIf the python package is hosted on a repository, you can install directly using:pipinstallgit+https://github.com/ingrammicro-xvantage/xi-sdk-resellers-python.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/ingrammicro-xvantage/xi-sdk-resellers-python.git)Then import the package:importxi.sdk.resellersSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importxi.sdk.resellersTestsExecutepytestto run the tests.Getting StartedPlease follow theinstallation procedureand then run the following:importxi.sdk.resellersfromxi.sdk.resellers.restimportApiExceptionfrompprintimportpprint# Defining the host is optional and defaults to https://api.ingrammicro.com:443# See configuration.py for a list of all supported configuration parameters.configuration=xi.sdk.resellers.Configuration(host=\"https://api.ingrammicro.com:443\")# Enter a context with an instance of the API clientwithxi.sdk.resellers.ApiClient(configuration)asapi_client:# Create an instance of the API classapi_instance=xi.sdk.resellers.AccesstokenApi(api_client)grant_type='client_credentials'# str | Keep grant_type as client_credentials only.client_id='client_id_example'# str |client_secret='client_secret_example'# str |try:# Accesstokenapi_response=api_instance.get_accesstoken(grant_type,client_id,client_secret)print(\"The response of AccesstokenApi->get_accesstoken:\\n\")pprint(api_response)exceptApiExceptionase:print(\"Exception when calling AccesstokenApi->get_accesstoken:%s\\n\"%e)Documentation for API EndpointsAll URIs are relative tohttps://api.ingrammicro.com:443ClassMethodHTTP requestDescriptionAccesstokenApiget_accesstokenGET/oauth/oauth20/tokenAccesstokenDealsApiget_resellers_v6_dealsdetailsGET/resellers/v6/deals/{dealId}Deals DetailsDealsApiget_resellers_v6_dealssearchGET/resellers/v6/deals/searchDeals SearchFreightEstimateApipost_freightestimatePOST/resellers/v6/freightestimateFreight EstimateInvoicesApiget_invoicedetails_v6_1GET/resellers/v6.1/invoices/{invoiceNumber}Get Invoice Details v6.1InvoicesApiget_resellers_v6_invoicesearchGET/resellers/v6/invoicesSearch your invoiceOrderStatusApiresellers_v1_webhooks_orderstatusevent_postPOST/resellers/v1/webhooks/orderstatuseventOrder StatusOrdersApidelete_ordercancelDELETE/resellers/v6/orders/{OrderNumber}Cancel your OrderOrdersApiget_orderdetails_v6_1GET/resellers/v6.1/orders/{ordernumber}Get Order Details v6.1OrdersApiget_resellers_v6_ordersearchGET/resellers/v6/orders/searchSearch your OrdersOrdersApipost_createorder_v6POST/resellers/v6/ordersCreate your OrderOrdersApiput_ordermodifyPUT/resellers/v6/orders/{orderNumber}Modify your OrderProductCatalogApiget_reseller_v6_productdetailGET/resellers/v6/catalog/details/{ingramPartNumber}Product DetailsProductCatalogApiget_reseller_v6_productsearchGET/resellers/v6/catalogSearch ProductsProductCatalogApipost_priceandavailabilityPOST/resellers/v6/catalog/priceandavailabilityPrice and AvailabilityQuoteToOrderApipost_quote_to_order_v6POST/resellers/v6/q2o/ordersQuote To OrderQuotesApiget_quotessearch_v6GET/resellers/v6/quotes/searchQuote SearchQuotesApiget_reseller_v6_validate_quoteGET/resellers/v6/q2o/validatequoteValidate QuoteQuotesApiget_resellers_v6_quotesGET/resellers/v6/quotes/{quoteNumber}Get Quote DetailsRenewalsApiget_resellers_v6_renewalsdetailsGET/resellers/v6/renewals/{renewalId}Renewals DetailsRenewalsApipost_renewalssearchPOST/resellers/v6/renewals/searchRenewals SearchReturnsApiget_resellers_v6_returnsdetailsGET/resellers/v6/returns/{caseRequestNumber}Returns DetailsReturnsApiget_resellers_v6_returnssearchGET/resellers/v6/returns/searchReturns SearchReturnsApipost_returnscreatePOST/resellers/v6/returns/createReturns CreateStockUpdateApiresellers_v1_webhooks_availabilityupdate_postPOST/resellers/v1/webhooks/availabilityupdateStock UpdateDocumentation For ModelsAccesstokenResponseAvailabilityAsyncNotificationRequestAvailabilityAsyncNotificationRequestResourceInnerAvailabilityAsyncNotificationRequestResourceInnerLinksInnerDealsDetailsResponseDealsDetailsResponseProductsInnerDealsSearchResponseDealsSearchResponseDealsInnerErrorErrorResponseErrorResponseDTOErrorResponseErrorsInnerErrorResponseErrorsInnerFieldsInnerFieldsFreightRequestFreightRequestLinesInnerFreightRequestShipToAddressInnerFreightResponseFreightResponseFreightEstimateResponseFreightResponseFreightEstimateResponseDistributionInnerFreightResponseFreightEstimateResponseDistributionInnerCarrierListInnerFreightResponseFreightEstimateResponseLinesInnerGetAccesstoken400ResponseGetAccesstoken500ResponseGetAccesstoken500ResponseFaultGetAccesstoken500ResponseFaultDetailGetResellerV6ValidateQuote400ResponseGetResellerV6ValidateQuote400ResponseFieldsInnerGetResellerV6ValidateQuote500ResponseInvoiceDetailsv61ResponseInvoiceDetailsv61ResponseBillToInfoInvoiceDetailsv61ResponseFxRateInfoInvoiceDetailsv61ResponseLinesInnerInvoiceDetailsv61ResponseLinesInnerSerialNumbersInnerInvoiceDetailsv61ResponsePaymentTermsInfoInvoiceDetailsv61ResponseShipToInfoInvoiceDetailsv61ResponseSummaryInvoiceDetailsv61ResponseSummaryForeignFxTotalsInvoiceDetailsv61ResponseSummaryLinesInvoiceDetailsv61ResponseSummaryMiscChargesInnerInvoiceDetailsv61ResponseSummaryTotalsInvoiceSearchResponseInvoiceSearchResponseInvoicesInnerOrderCreateRequestOrderCreateRequestAdditionalAttributesInnerOrderCreateRequestEndUserInfoOrderCreateRequestLinesInnerOrderCreateRequestLinesInnerAdditionalAttributesInnerOrderCreateRequestLinesInnerEndUserInfoInnerOrderCreateRequestLinesInnerWarrantyInfoInnerOrderCreateRequestLinesInnerWarrantyInfoInnerSerialInfoInnerOrderCreateRequestResellerInfoOrderCreateRequestShipToInfoOrderCreateRequestShipmentDetailsOrderCreateRequestVmfOrderCreateResponseOrderCreateResponseEndUserInfoOrderCreateResponseOrdersInnerOrderCreateResponseOrdersInnerAdditionalAttributesInnerOrderCreateResponseOrdersInnerLinesInnerOrderCreateResponseOrdersInnerLinesInnerAdditionalAttributesInnerOrderCreateResponseOrdersInnerLinesInnerShipmentDetailsInnerOrderCreateResponseOrdersInnerLinksInnerOrderCreateResponseOrdersInnerMiscellaneousChargesInnerOrderCreateResponseOrdersInnerRejectedLineItemsInnerOrderCreateResponseShipToInfoOrderDetailB2BOrderDetailB2BAdditionalAttributesInnerOrderDetailB2BBillToInfoOrderDetailB2BEndUserInfoOrderDetailB2BLinesInnerOrderDetailB2BLinesInnerAdditionalAttributesInnerOrderDetailB2BLinesInnerEstimatedDatesInnerOrderDetailB2BLinesInnerEstimatedDatesInnerDeliveryOrderDetailB2BLinesInnerEstimatedDatesInnerDeliveryDeliveryDateRangeOrderDetailB2BLinesInnerEstimatedDatesInnerShipOrderDetailB2BLinesInnerEstimatedDatesInnerShipShipDateRangeOrderDetailB2BLinesInnerLinksInnerOrderDetailB2BLinesInnerMultipleShipmentsInnerOrderDetailB2BLinesInnerScheduleLinesInnerOrderDetailB2BLinesInnerServiceContractInfoOrderDetailB2BLinesInnerServiceContractInfoContractInfoOrderDetailB2BLinesInnerServiceContractInfoLicenseInfoOrderDetailB2BLinesInnerServiceContractInfoSubscriptionsOrderDetailB2BLinesInnerShipmentDetailsInnerOrderDetailB2BLinesInnerShipmentDetailsInnerCarrierDetailsInnerOrderDetailB2BLinesInnerShipmentDetailsInnerCarrierDetailsInnerTrackingDetailsInnerOrderDetailB2BLinesInnerShipmentDetailsInnerCarrierDetailsInnerTrackingDetailsInnerSerialNumbersInnerOrderDetailB2BMiscellaneousChargesInnerOrderDetailB2BShipToInfoOrderModifyRequestOrderModifyRequestAdditionalAttributesInnerOrderModifyRequestLinesInnerOrderModifyRequestShipToInfoOrderModifyResponseOrderModifyResponseLinesInnerOrderModifyResponseLinesInnerAdditionalAttributesInnerOrderModifyResponseLinesInnerShipmentDetailsOrderModifyResponseRejectedLineItemsInnerOrderModifyResponseShipToInfoOrderSearchResponseOrderSearchResponseOrdersInnerOrderSearchResponseOrdersInnerLinksOrderSearchResponseOrdersInnerSubOrdersInnerOrderSearchResponseOrdersInnerSubOrdersInnerLinksInnerOrderStatusAsyncNotificationRequestOrderStatusAsyncNotificationRequestResourceInnerOrderStatusAsyncNotificationRequestResourceInnerLinesInnerOrderStatusAsyncNotificationRequestResourceInnerLinesInnerSerialNumberDetailsInnerOrderStatusAsyncNotificationRequestResourceInnerLinesInnerShipmentDetailsInnerOrderStatusAsyncNotificationRequestResourceInnerLinesInnerShipmentDetailsInnerPackageDetailsInnerOrderStatusAsyncNotificationRequestResourceInnerLinksInnerPostQuoteToOrderV6400ResponsePostQuoteToOrderV6400ResponseFieldsInnerPostRenewalssearch400ResponsePriceAndAvailabilityRequestPriceAndAvailabilityRequestAdditionalAttributesInnerPriceAndAvailabilityRequestAvailabilityByWarehouseInnerPriceAndAvailabilityRequestProductsInnerPriceAndAvailabilityRequestProductsInnerAdditionalAttributesInnerPriceAndAvailabilityResponseInnerPriceAndAvailabilityResponseInnerAvailabilityPriceAndAvailabilityResponseInnerAvailabilityAvailabilityByWarehouseInnerPriceAndAvailabilityResponseInnerAvailabilityAvailabilityByWarehouseInnerBackOrderInfoInnerPriceAndAvailabilityResponseInnerDiscountsInnerPriceAndAvailabilityResponseInnerDiscountsInnerQuantityDiscountsInnerPriceAndAvailabilityResponseInnerDiscountsInnerSpecialPricingInnerPriceAndAvailabilityResponseInnerPricingPriceAndAvailabilityResponseInnerReserveInventoryDetailsInnerPriceAndAvailabilityResponseInnerServiceFeesInnerProductDetailResponseProductDetailResponseAdditionalInformationProductDetailResponseAdditionalInformationProductWeightInnerProductDetailResponseCiscoFieldsProductDetailResponseIndicatorsProductDetailResponseTechnicalSpecificationsInnerProductSearchResponseProductSearchResponseCatalogInnerProductSearchResponseCatalogInnerLinksInnerQuoteDetailsResponseQuoteDetailsResponseAdditionalAttributesInnerQuoteDetailsResponseEndUserInfoQuoteDetailsResponseProductsInnerQuoteDetailsResponseProductsInnerPriceQuoteDetailsResponseResellerInfoQuoteSearchResponseQuoteSearchResponseQuotesInnerQuoteSearchResponseQuotesInnerLinksQuoteToOrderDetailsDTOQuoteToOrderDetailsDTOAdditionalAttributesInnerQuoteToOrderDetailsDTOEndUserInfoQuoteToOrderDetailsDTOLinesInnerQuoteToOrderDetailsDTOLinesInnerVmfAdditionalAttributesLinesInnerQuoteToOrderDetailsDTOShipToInfoQuoteToOrderDetailsDTOVmfadditionalAttributesInnerQuoteToOrderResponseRenewalsDetailsResponseRenewalsDetailsResponseAdditionalAttributesInnerRenewalsDetailsResponseEndUserInfoRenewalsDetailsResponseProductsInnerRenewalsDetailsResponseReferenceNumberRenewalsSearchRequestRenewalsSearchRequestDateTypeRenewalsSearchRequestDateTypeEndDateRenewalsSearchRequestDateTypeExpirationDateRenewalsSearchRequestDateTypeInvoiceDateRenewalsSearchRequestDateTypeStartDateRenewalsSearchRequestStatusRenewalsSearchRequestStatusOpporutinyStatusRenewalsSearchResponseRenewalsSearchResponseRenewalsInnerRenewalsSearchResponseRenewalsInnerLinksInnerReturnsCreateRequestReturnsCreateRequestListInnerReturnsCreateRequestListInnerShipFromInfoInnerReturnsCreateResponseReturnsCreateResponseReturnsClaimsInnerReturnsDetailsResponseReturnsDetailsResponseProductsInnerReturnsSearchResponseReturnsSearchResponseReturnsClaimsInnerReturnsSearchResponseReturnsClaimsInnerLinksInnerValidateQuoteResponseValidateQuoteResponseLinesInnerValidateQuoteResponseVmfAdditionalAttributesInnerDocumentation For AuthorizationAuthentication schemes defined for the API:applicationType: OAuthFlow: applicationAuthorization URL:Scopes:write: allows modifying resourcesread: allows reading resourcesdescription:Author-Ingram Micro XvantageContactFor any inquiries or support, please feel free to contact us at:Email:xi_support@ingrammicro.com"} +{"package": "xisf", "pacakge-description": "xisfXISF Encoder/Decoder (seehttps://pixinsight.com/xisf/).This implementation is not endorsed nor related with PixInsight development team.Copyright (C) 2021-2022 Sergio D\u00edaz, sergiodiaz.euThis program is free software: you can redistribute it and/or modify it\nunder the terms of the GNU General Public License as published by the\nFree Software Foundation, version 3 of the License.This program is distributed in the hope that it will be useful, but WITHOUT\nANY WARRANTY; without even the implied warranty of MERCHANTABILITY or\nFITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for\nmore details.You should have received a copy of the GNU General Public License along with\nthis program. If not, seehttp://www.gnu.org/licenses/.XISF ObjectsclassXISF()Implements an baseline XISF Decoder and a simple baseline Encoder.\nIt parses metadata from Image and Metadata XISF core elements. Image data is returned as a numpy ndarray\n(using the \"channels-last\" convention by default).What's supported:Monolithic XISF files onlyXISF data blocks with attachment, inline or embedded block locationsPlanar pixel storage models,however it assumes 2D images only(with multiple channels)UInt8/16/32 and Float32/64 pixel sample formatsGrayscale and RGB color spacesDecoding:multiple Image core elements from a monolithic XISF fileSupport all standard compression codecs defined in this specification for decompression\n(zlib/lz4[hc]/zstd + byte shuffling)Encoding:Single image core element with an attached data blockSupport all standard compression codecs defined in this specification for decompression\n(zlib/lz4[hc]/zstd + byte shuffling)\"Atomic\" properties only (scalar types, String, TimePoint)Metadata and FITSKeyword core elementsWhat's not supported (at least by now):Read pixel data in the normal pixel storage modelsRead pixel data in the planar pixel storage models other than 2D imagesComplex, Vector, Matrix and Table propertiesAny other not explicitly supported core elements (Resolution, Thumbnail, ICCProfile, etc.)Usage example:from xisf import XISF\nimport matplotlib.pyplot as plt\nxisf = XISF(\"file.xisf\")\nfile_meta = xisf.get_file_metadata() \nfile_meta\nims_meta = xisf.get_images_metadata()\nims_meta\nim_data = xisf.read_image(0)\nplt.imshow(im_data)\nplt.show()\nXISF.write(\n \"output.xisf\", im_data, \n creator_app=\"My script v1.0\", image_metadata=ims_meta[0], xisf_metadata=file_meta, \n codec='lz4hc', shuffle=True\n)If the file is not huge and it contains only an image (or you're interested just in one of the\nimages inside the file), there is a convenience method for reading the data and the metadata:from xisf import XISF\nimport matplotlib.pyplot as plt \nim_data = XISF.read(\"file.xisf\")\nplt.imshow(im_data)\nplt.show()The XISF format specification is available athttps://pixinsight.com/doc/docs/XISF-1.0-spec/XISF-1.0-spec.html__init__def__init__(fname)Opens a XISF file and extract its metadata. To get the metadata and the images, see get_file_metadata(),\nget_images_metadata() and read_image().Arguments:fname- filenameReturns:XISF object.get_images_metadatadefget_images_metadata()Provides the metadata of all image blocks contained in the XISF File, extracted from\nthe header (core elements). To get the actual image data, see read_image().It outputs a dictionary m_i for each image, with the following structure:m_i = { \n 'geometry': (width, height, channels), # only 2D images (with multiple channels) are supported\n 'location': (pos, size), # used internally in read_image()\n 'dtype': np.dtype('...'), # derived from sampleFormat argument\n 'compression': (codec, uncompressed_size, item_size), # optional\n 'key': 'value', # other attributes are simply copied \n ..., \n 'FITSKeywords': { : fits_keyword_values_list, ... }, \n 'XISFProperties': { : property_dict, ... }\n}\n\nwhere:\n\nfits_keyword_values_list = [ {'value': , 'comment': }, ...]\nproperty_dict = {'id': , 'type': , 'value': property_value, ...}Returns:list [ m_0, m_1, ..., m_{n-1} ] where m_i is a dict as described above.get_file_metadatadefget_file_metadata()Provides the metadata from the header of the XISF File ( core elements).Returns:dictionary with one entry per property: { : property_dict, ... }\nwhere:property_dict = {'id': , 'type': , 'value': property_value, ...}get_metadata_xmldefget_metadata_xml()Returns the complete XML header as a xml.etree.ElementTree.Element object.Returns:xml.etree.ElementTree.Element- complete XML XISF headerread_imagedefread_image(n=0,data_format='channels_last')Extracts an image from a XISF object.Arguments:n- index of the image to extract in the list returned by get_images_metadata()data_format- channels axis can be 'channels_first' or 'channels_last' (as used in\nkeras/tensorflow, pyplot's imshow, etc.), 0 by default.Returns:Numpy ndarray with the image data, in the requested format (channels_first or channels_last).read@staticmethoddefread(fname,n=0,image_metadata={},xisf_metadata={})Convenience method for reading a file containing a single image.Arguments:fnamestring- filenamenint, optional- index of the image to extract (in the list returned by get_images_metadata()). Defaults to 0.image_metadatadict, optional- dictionary that will be updated with the metadata of the image.xisf_metadatadict, optional- dictionary that will be updated with the metadata of the file.Returns:[np.ndarray]- Numpy ndarray with the image data, in the requested format (channels_first or channels_last).write@staticmethoddefwrite(fname,im_data,creator_app=None,image_metadata={},xisf_metadata={},codec=None,shuffle=False,level=None)Writes an image (numpy array) to a XISF file. Compression may be requested but it only\nwill be used if it actually reduces the data size.Arguments:fname- filename (will overwrite if existing)im_data- numpy ndarray with the image datacreator_app- string for XISF:CreatorApplication file property (defaults to python version in None provided)image_metadata- dict with the same structure described for m_i in get_images_metadata().\nOnly 'FITSKeywords' and 'XISFProperties' keys are actually written, the rest are derived from im_data.xisf_metadata- file metadata, dict with the same structure returned by get_file_metadata()codec- compression codec ('zlib', 'lz4', 'lz4hc' or 'zstd'), or None to disable compressionshuffle- whether to apply byte-shuffling before compression (ignored if codec is None). Recommended\nfor 'lz4' ,'lz4hc' and 'zstd' compression algorithms.level- for zlib, 1..9 (default: 6); for lz4hc, 1..12 (default: 9); for zstd, 1..22 (default: 3).\nHigher means more compression.Returns:bytes_written- the total number of bytes written into the output file.codec- The codec actually used, i.e., None if compression did not reduce the data block size so\ncompression was not finally used."} +{"package": "xissue", "pacakge-description": "Twine is a utility for publishing Python packages on PyPI.It provides build system independent uploads of source and binary distribution artifacts for both new and existing projects."} +{"package": "xist", "pacakge-description": "No description available on PyPI."} +{"package": "xit", "pacakge-description": "This repository is a namespace for a group of related projects. Also, it is\nthe base library for this namespace.NoteThe project is currently in development and is not ready for production\nuse.InstallDevelopment Stage:CheckADR-4about how to usepoetryto manage how to evolve projects on\ndevelopment stages.This section is under constructionProduction Stage:This section is under constructionAfter installation tasks:Each of our projects should have abacklog-0001document with task to\nexecute after a project is installed. This document must be located in thedocs/source/backlogdirectory."} +{"package": "xit2md", "pacakge-description": "xit2md[x]it!is a plain-text file format for todos and check lists. xit2md converts a checklist in [x]it! format to markdown task lists. Markdown task lists are available in many markdown dialects including GitHub Flavored Markdown.Installationpip install xit2mdUsageOn the Console# convert [x]it! file to markdown file$xit2mdin.xit>out.md# fetch [x]it! file from the web and convert to markdown$curl\"https://myserver.com/example.xit\"|xit2mdAs a Library>>>fromxit2mdimportxit2md_text>>>xit=\"\"\"Named Group...[ ] Open...[x] Checked...[@] Ongoing...[~] Obsolete...[?] In Question...\"\"\">>>print(xit2md_text(xit,heading_level=2))## Named Group- [ ] Open- [x] Checked- [ ] Ongoing- [x] ~Obsolete~- [ ] In Question"} +{"package": "xit-books", "pacakge-description": "Documentation manager and generator based on \u2018Sphinx\u2019.NoteThe project is currently in development and is not ready for production\nuse.InstallDevelopment Stage:CheckADR-4on base namespace project about how to usepoetryto manage how to evolve projects on development stages.This section is under constructionProduction Stage:This section is under constructionAfter installation tasks:Each of our projects should have abacklog-0001document with task to\nexecute after a project is installed. This document must be located in thedocs/source/backlogdirectory.DocumentationNotethat because the purpose of this project is to be a documentation\nmanager, it will be usualy installed in other projects as a development\ndependency.This section is under construction"} +{"package": "xiter", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiTest", "pacakge-description": "No description available on PyPI."} +{"package": "xitorch", "pacakge-description": "xitorch: differentiable scientific computing libraryxitorchis a PyTorch-based library of differentiable functions and functionals that\ncan be widely used in scientific computing applications as well as deep learning.The documentation can be found at:https://xitorch.readthedocs.io/ExampleFinding root of a function:importtorchfromxitorch.optimizeimportrootfinderdeffunc1(y,A):# example functionreturntorch.tanh(A@y+0.1)+y/2.0# set up the parameters and the initial guessA=torch.tensor([[1.1,0.4],[0.3,0.8]]).requires_grad_()y0=torch.zeros((2,1))# zeros as the initial guess# finding a rootyroot=rootfinder(func1,y0,params=(A,))# calculate the derivativesdydA,=torch.autograd.grad(yroot.sum(),(A,),create_graph=True)grad2A,=torch.autograd.grad(dydA.sum(),(A,),create_graph=True)Moduleslinalg: Linear algebra and sparse linear algebra moduleoptimize: Optimization and root finder moduleintegrate: Quadrature and integration moduleinterpolate: InterpolationRequirementspython >=3.8.1,<3.12pytorch 1.13.1 or higher (installhere)Getting startedAfter fulfilling all the requirements, type the commands below to installxitorchpython -m pip install xitorchOr to install from GitHub:python -m pip install git+https://github.com/xitorch/xitorch.gitFinally, if you want to make an editable install from source:git clone https://github.com/xitorch/xitorch.git\ncd xitorch\npython -m pip install -e .Note that the last option is only available perPEP 660, so you will requirepip >= 23.1Used inDifferentiable Quantum Chemistry (DQC):https://dqc.readthedocs.io/GalleryNeural mirror design (example 01):Initial velocity optimization in molecular dynamics (example 02):"} +{"package": "xitroo-api", "pacakge-description": "Unofficial Xitroo ApiAn API for xitroo.com, Xitroo is a temporarily email service website that offers unlimited emails for free,\nUnfortunately they don't have an API so i made my own Unofficial Xitroo Api and decided to share it with you guys, It can be used for websites that require to email verify to sign up and much more.Installingpip install xitroo-apiUsage>>> from xitroo import Api\n\nApi.GenerateEmail(length=18, domain=\"com\")\n\nApi.FetchEmail(xitroo_email=\"email here\", subject=\"subject here\")\n\n-----------------------------------------------------------------\n\nGenerateEmail arguments:\n\n1 - length: is the amount of characters in the random string, it can be set to any number default is 18 characters. \n2 - domain: xitroo has multiple domains such as [.com, .fr, .net, .org] you can chosse anyone you want or you can set it to \"random\".\n\nFetchEmail arguments:\n\n1 - xitroo_email: Its the email generated from [Api.GenerateEmail(length=21, domain=\"random\")]\n2 - Subject: its from what site you used the email on, Its the subject of the email received.\n3 - Timeout: How long to wait for the email to be received, The default is 30 secends it can be set to any amount of timeExample One>>> from xitroo import Api\n\nemail = Api.GenerateEmail(length=21, domain=\"random\")\nprint(email)\n>>> thisisanexample@xitroo.com\n\n#use this email on whatever site you want, for this example im using it on instagram\n\n#you need to grab the subject that instagram uses in there emails and place it in the function below,\nIt dosent have to be the full subject just a part of it \n\nBody = Api.FetchEmail(xitroo_email=email, subject=\"your instagram code is\")\nprint(Body)\n>>> your instagram code is 762354\n\n# you can use regex to grab the code only from the Body, For example\n\ncode = re.findall('your instagram code is (.*?)', str(Body))[0]\nprint(code)\n>>> 762354Example TwoOn this Example we are getting a link to verify\n\n>>> from xitroo import Api\n\nemail = Api.GenerateEmail(length=18, domain=\"fr\")\nprint(email)\n>>> thisisanexample@xitroo.fr\n\n#use this email on whatever site you want\n\n#you need to grab the subject of the email that the website sent and place it in the function below,\nIt dosent have to be the full subject just a part of it \n\nBody = Api.FetchEmail(xitroo_email=email, subject=\"verify your account\", timeout=15)\nprint(Body)\n>>> Thanks for registering please click the link below to comlpte registration\n https://example.com/verify-user-account \n\n# you can use regex to grab the link only from the Body, For example\n\nlink = re.findall('registration\\n(.*?)', str(Body))[0]\nprint(link)\n>>> https://example.com/verify-user-account\n\nto verify the account with a link you got two options either you use selenium and open the link with chromedriver\nor send a request to that link#Contact me on discord: Flex#8629"} +{"package": "xits2", "pacakge-description": "No description available on PyPI."} +{"package": "xiu", "pacakge-description": "Usage:data"} +{"package": "xiudb-Peiiii", "pacakge-description": "Unlike a database, this one doesn\u2019t store records, but store objects directly .\nHome-page:https://github.com/Peiiii/xiudbAuthor: Wang Pei\nAuthor-email:1535376447@qq.comLicense: UNKNOWN\nDescription: UNKNOWN\nPlatform: UNKNOWN\nClassifier: Programming Language :: Python :: 3\nClassifier: License :: OSI Approved :: MIT License\nClassifier: Operating System :: OS Independent"} +{"package": "xiuxian1.0", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xiva-hub-client", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xivapyi", "pacakge-description": "xivapyiAn async python3 wrapper around the XIVAPI for Final Fantasy XIV.WARNINGThis project is still in very early development, and will not be ready until the v1.0 release.\nPlease refrain from using xivapyi for now. Thanks for reading.Installationxivapyi requires python 3.6 or greater.To get started:pipinstallxivapyiContributingThis library uses Poetry for dependency management. You can read more about ithere.Licensexivapyi is licensed under theBSD 3-Clause License."} +{"package": "xivelymqtt", "pacakge-description": "This project tries to implement a client library based on Python for Xively IoT platform. Using MQTT is expected to increase response time and save costly communication bandwidth"} +{"package": "xively-mqtt", "pacakge-description": "This project tries to implement a client library based on Python for Xively IoT platform. Using MQTT is expected to increase response time and save costly communication bandwidth"} +{"package": "xively-python", "pacakge-description": "This is the official pythonic wrapper library for the Xively V2 API."} +{"package": "xiver-gpt", "pacakge-description": "Xiver GPTThe module we use to work with gptBasic usageWith default configfromxiver_gptimportXiverGPTprint(XiverGPT().create_response('Hello! How are u?'))With another model or providerfromxiver_gptimportXiverGPTimportg4fprint(XiverGPTg4f_model=g4f.Model.your_model,g4f_provider=g4f.Provider.your_provider,).create_reT(sponse('Hello! How are u?'))AttentionAt the moment the initialization of the XiverGPT class object can be quite\nlong due to the selection of a suitable provider.\nIn the future the initialization time will be reduced many times!Installation$pipinstallxiver_gptInstallation from sourceDependencies:poetry$gitclonehttps://github.com/xiver/xiver-gpt.git;cdxiver_gpt-master\n$poetryinstall\n$poetryrunbuild;cddist\n$pipinstall$(ls-Art|tail-n1)"} +{"package": "xivo-client-sim", "pacakge-description": "Dependenciesgevent >= 0.13.0pip install geventInstallation notes on Debian squeezeYou need the following packages to install gevent (more precisely, greenlet,\non which gevent depends) on a plain Debian squeeze:build-essential python-dev libevent-dev"} +{"package": "xivo-test-helpers", "pacakge-description": "UNKNOWN"} +{"package": "xiwal", "pacakge-description": "No description available on PyPI."} +{"package": "xixi", "pacakge-description": "No description available on PyPI."} +{"package": "xixiang", "pacakge-description": "XiXiang \u7199\u9999\u70b9\u9910\u652f\u6301 Python 3.5+ \u7684\u7199\u9999\u70b9\u9910\u975e\u5b98\u65b9\u5e93\u80cc\u666f\u56e0\u4e3a\u6211\u53f8\u70b9\u9910\u7684\u4eba\u6bd4\u8f83\u591a\uff0c\u60f3\u7740\u52a0\u4e00\u4e2a\u70b9\u9910\u670d\u52a1\u505a\u707e\u5907\uff0c\u4e8e\u662f\u5c31\u9664\u4e86\u7f8e\u9910\u6211\u4eec\u8fd8\u5f97\u652f\u6301\u7199\u9999\u70b9\u9910\u3002\u5b89\u88c5pipinstallxixiang\u4ee3\u7801\u8c03\u7528importxixiangtry:client=xixiang.XiXiang.login(\"1881881888\",\"hunter2\")menus=client.get_menus()shops=client.get_businesses(menus[0])dishes=client.get_items(shops[0],menus[0])ifany(dishfordishindishesifdish.menu_name==\"\u9999\u9165\u9e21\u817f\"):print(\"\u4eca\u5929\u6709\u9999\u9165\u9e21\u817f :happy:\")else:print(\"\u4eca\u5929\u6ca1\u6709\u9999\u9165\u9e21\u817f :sad:\")exceptxixiang.XiXiangErrorasex:print(\"Error:{}\".format(ex))\u8d21\u732e\u4e0d\u8bba\u662f\u4efb\u4f55\u7591\u95ee\u3001\u60f3\u8981\u7684\u529f\u80fd\u8fd8\u662f\u60f3\u5403\u7684\u5957\u9910\u90fd\u6b22\u8fce\u76f4\u63a5\u63d0 issue\u5047\u5982\u4f60\u4eec\u516c\u53f8\u662f\u7528\u7f8e\u9910\u70b9\u9910\u7684\uff0c\u9694\u58c1\u4e5f\u6709\u7f8e\u9910\u7684\u5e93\u5662~:wink: \u6b22\u8fce\u5404\u79cd PR\u534f\u8bae\u5bbd\u677e\u7684MIT\u534f\u8bae\uff1a\u2714 \u652f\u6301\u5404\u79cd\u6539\u5199\u2714 \u652f\u6301\u4f60\u628a\u4ee3\u7801\u4f5c\u8005\u90fd\u6539\u6210\u81ea\u5df1\u2716 \u4e0d\u652f\u6301\u6bcf\u5929\u4e2d\u5348\u514d\u8d39\u5403\u897f\u8d1d\u839c\u9762\u6751\u2716 \u4e5f\u4e0d\u652f\u6301\u70b9\u5927\u7f8a\u817f\u3001\u638c\u4e2d\u5b9d"} +{"package": "xixibao", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xixihaha159", "pacakge-description": "No description available on PyPI."} +{"package": "xixo", "pacakge-description": "lilo"} +{"package": "xixur999calculator", "pacakge-description": "This is a very simple calInstagram: @thebitccSnapchat: @zanderthebitccChange Log0.0.1 (3/1/2021)First Release"} +{"package": "xix-utils", "pacakge-description": "Xix utils began as an attemp at designing atemplating / content-publshing framework which is now only those remains - xix.utils.\nxix_utils is simply \u201cyet more batteries for python.\u201d Generalized\nconcepts and resulting POCs abstracted from other projects become modules under\nxix.utils. Known unstable modules should signal warnings at runtime.Tested on Python 2.4 and 2.5.Subversion trunk:svn cohttp://svn.xix.python-hosting.com/trunkXixInstallation:python setup.py installNote to Developers: Please run unit tests and provide feedback. To run suite:python runtests.py"} +{"package": "xiyang-morch-pkg", "pacakge-description": "Fuzhou Xiyang network technology company, face morph project."} +{"package": "xiyang-morph-pkg", "pacakge-description": "Fuzhou Xiyang network technology company, face morph project.install:pip install xiyang-morph-pkginstall relation packagesdlib >= 19.9.0\nnumpy >= 1.13.1\nscipy >= 0.18.0\nopencv-contrib-python>=4.2.0.34import packagefrom xiyang_morph import morphparam 1: str_img_pathparam 2: dist_img_pathparam 3\uff1aresult img save pathmorph.morph(\"../../imgs/test6.jpg\", \"../../imgs/test7.jpg\", \"../img/result.jpg\")"} +{"package": "xiyang-porch-pkg", "pacakge-description": "Fuzhou Xiyang network technology company, face morph project."} +{"package": "xiyuhaochi", "pacakge-description": "UNKNOWN"} +{"package": "xiyusullos_nester", "pacakge-description": "No description available on PyPI."} +{"package": "xjam", "pacakge-description": "This program identifies and generates stacking sequences of high-symmetric honeycomb lattice layered materials via the Joining and Arrangement of Multilayers (JAM) notation by mapping a string of characters to the structure of a polytype using only its chemical symbols.Installing JAMYou can install and uninstall with:# install\npip3 install xjam\n\n# invoque as:\nx.jam\n\n# uninstall\npip3 uninstall xjamor# install\ngit clone https://github.com/fortizchi/xjam\ncd xjam\npython3 setup.py install --record files.txt\n\n# invoque as:\nx.jam\n\n# uninstall\nxargs rm -rf < files.txtThe JAM.inp fileThe user must create a JAM.inp file to control the options when running the JAM algorithm.\nThe JAM.inp file includes the following variables:-option: INT, type of material (PL, BPL, BU, BBU)\n-num_layers: INT, number of layers to stack\n-atom_list: CHAR, list of the chemical symbols of the elements in the material\n-latticep: FLOAT, the lattice constant used to scale all lattice vectors\n-z_vacuum: FLOAT, the vacuum space\n-buckling: FLOAT, the distortion out of the plane\n-distance: FLOAT, the interlayer distanceRunning JAMx.jam"} +{"package": "xj-behavior", "pacakge-description": "xj-behavior\u4ecb\u7ecd\u884c\u4e3a\u6a21\u5757\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-captcha", "pacakge-description": "xj_captcha\u4ecb\u7ecd\u77ed\u4fe1\u6a21\u5757\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u522b\u6ce8\u610f\uff1a\u7531\u4e8e\u7248\u672c\u517c\u5bb9\u95ee\u9898 \u66f4\u65b0\u5b8c\u77ed\u4fe1\u6a21\u5757\u540e \u9700\u624b\u52a8\u5c06 pyOpenSSL \u66f4\u65b0\u5230\u6700\u65b0\u7248\u672c \u547d\u4ee4\uff1a\npip install --upgrade pyOpenSSL\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-comment", "pacakge-description": "xj-comment\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-common", "pacakge-description": "xj-comment\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xjd", "pacakge-description": "xjdTable of ContentsInstallationLicenseInstallationpip install xjdLicensexjdis distributed under the terms of theMITlicense."} +{"package": "xj-database", "pacakge-description": "xj_database\u4ecb\u7ecd\u6570\u636e\u5e93\u7ba1\u7406\u7cfb\u7edf\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-dictionary", "pacakge-description": "Xj-Dictionary Module\u5b57\u5178\u6a21\u5757Part 1. Introduce\u4ecb\u7ecd\u672c\u6a21\u5757\u4f7f\u7528M\u5de5\u7a0b\u5316\u5f00\u53d1\u6587\u6863\uff08MB 311-2022\uff09\u6807\u51c6\u7f16\u5199\u672c\u6a21\u5757\u91c7\u7528MSA\u8bbe\u8ba1\u6a21\u5f0f\uff08MB 422-2022\uff09Install\u5b89\u88c5\u4f9d\u8d56# \u6ce8\uff1a\u4f7f\u7528pip install django-simple-api\u4f1a\u5b89\u88c5\u4e0d\u4e0apipinstallgit+https://e.coding.net/aber/github/django-simple-api.git@setup.py/settings.pyINSTALLED_APPS=[...,\"django_simple_api\",'apps.dictionary.apps.DictionaryConfig',]MIDDLEWARE=[...,\"django_simple_api.middleware.SimpleApiMiddleware\",]/main/urls.pyfromdjango.urlsimportinclude,re_pathurlpatterns=[...,re_path(r'(api/)?dictionary/?',include('apps.dictionary.urls')),]urlpatterns+=[path(\"docs/\",include(\"django_simple_api.urls\"))]Part 2. API DocumentAPI \u63a5\u53e3\u6587\u6863Chapter 3. Detail Design\u8be6\u7ec6\u8bbe\u8ba13.7 Dictionary \u914d\u7f6e\u7c7b\u6ce8\uff1a\u914d\u7f6e\u4e0d\u5efa\u8bae\u4ece\u63a5\u53e3\u4e2d\u6dfb\u52a0\uff0c\u524d\u671f\u8bbe\u8ba1\u4e3a\u4ece\u540e\u53f0\u6dfb\u52a01\u3001\u914d\u7f6e\u6dfb\u52a0(dictionary_configure)\u5730\u5740\u6807\u51c6\t/api/dictionary_configure/\t\tPOST\n\u7b80\u5199\t/api/config/\t\tPOST\u53c2\u6570\u53c2\u6570\u540d\u8bcd\u7c7b\u578b\u5fc5\u987b\u9ed8\u8ba4\u8bf4\u660egroup\u5206\u7ec4string\u5426default-key\u952estring\u662fvalue\u503cstring\u662fdescription\u8bf4\u660estring\u54262\u3001\u914d\u7f6e\u67e5\u627e (dictionary_configure)\u5730\u5740/api/dictionary_configure/\t\tGET\n/api/dictionary_configure//\t\tGET\u53c2\u6570\u53c2\u6570\u540d\u8bcd\u7c7b\u578b\u5fc5\u987b\u9ed8\u8ba4\u8bf4\u660egroup\u5206\u7ec4string\u5426default\u4e0d\u4f20\u5219\u4e3a\u9ed8\u8ba4\u5206\u7ec4\u8fd4\u56de\u53c2\u6570\u8bf4\u660e\u8fd4\u56de\u53c2\u6570\u540d\u79f0\u7c7b\u578b\u8bf4\u660ekey\u952estring\u662fvalue\u503cstring\u662fdescription\u8bf4\u660estring\u5426\u8fd4\u56de\u793a\u4f8b\uff08/api/\uff09{\"err\":0,\"msg\":\"200 OK\",\"data\":{\"logo\":}}2\u3001\u914d\u7f6e\u5217\u8868 (dictionary_list)\u5730\u5740/api/dictionary_configure_list/\t\tGET\u53c2\u6570\u53c2\u6570\u540d\u8bcd\u7c7b\u578b\u5fc5\u987b\u9ed8\u8ba4\u8bf4\u660egroup\u5206\u7ec4string\u5426default\u4e0d\u4f20\u5219\u4e3a\u9ed8\u8ba4\u5206\u7ec4\u8fd4\u56de\u53c2\u6570\u8bf4\u660e\u8fd4\u56de\u53c2\u6570\u540d\u79f0\u7c7b\u578b\u8bf4\u660ekey\u952estring\u662fvalue\u503cstring\u662fdescription\u8bf4\u660estring\u5426\u8fd4\u56de\u793a\u4f8b\uff08/api/\uff09{\"err\":0,\"msg\":\"200 OK\",\"data\":{\"logo\":}}SQLCREATETABLE`dictionary_configure`(`id`bigint(20)NOTNULLAUTO_INCREMENT,`group`varchar(128)NOTNULL,`key`varchar(128)NOTNULL,`value`longtextNOTNULL,`description`varchar(255)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,UNIQUEKEY`dictionary_configure_group_key_d0e0a692_uniq`(`group`,`key`)USINGBTREE,KEY`dictionary_configure_group_09d9ee65`(`group`)USINGBTREE,KEY`dictionary_configure_key_52d53a3c`(`key`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=4DEFAULTCHARSET=utf8ROW_FORMAT=DYNAMIC;"} +{"package": "xj-enroll", "pacakge-description": "xj-enroll\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xjenza-gen", "pacakge-description": "xjenza-genThis tool is a Python-based utility designed to automate the process of creating\nand compiling LaTeX documents.PrerequisitesTo run this tool successfully, you will need:Python 3.6 or later (I'll assume you have this already)LaTeX distribution installed (e.g., TeX Live, MiKTeX)biberbibliography toolmacOSIf you don't have a package manager installed, I recommend installingHomebrew.brewinstallbibertexliveUbuntusudoapt-getinstallbibertexlive-fullUsageTo get started, installxjenza-genusingpiporpipx(recommended):[!NOTE]\nmacOS users that want to givepipxa try should install it usingbrew install pipx.\nUbuntu users can install it usingpip install --user pipx.pipinstallxjenza-genQuick StartIt's very easy to get started withxjenza-gen. Simply run the following\ncommand:xjenza-gennew[article-name]You will be prompted to enter the title, author, and some other basic information about\nyour article.xjenza-genwill then create new directory calledarticle-nameunder your\ncurrent directory with the following structure:article-name/\n\u251c\u2500\u2500 packages/\n\u2502 \u251c\u2500\u2500 logo.pdf\n\u2502 \u251c\u2500\u2500 xjenza-preamble.tex\n\u2502 \u2514\u2500\u2500 xjenza.sty\n\u251c\u2500\u2500 figs/\n\u251c\u2500\u2500 bibliography.bib\n\u251c\u2500\u2500 article-name.texand populatearticle-name.texwith the information you provided. This file is the main LaTeX file you will be working with, following the template foundhere.AcknowledgementsWilliam Hicklin for thexjenza LaTeX templateMalta Chamber of Scientists"} +{"package": "xj-equipment", "pacakge-description": "xj-equipment\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xjet", "pacakge-description": "Python SDK for xJet Connect APIAuthors@xJetLabs(forked from)@nik-1xInstallationpipinstallxjetIf requiresnaclpackage, install itmanually:pipinstallpynaclWebhook analogwhileTrue:res=httpx.get('https://api.xjet.io/v1/account.events',params={'timeout':10},headers={'X-API-Key':api_key,},timeout=11,)print(res.json)time.sleep(3)Usage/ExamplesLive exampleInitializationfromxjetimportJetAPI# api_key: str# private_key: strapi=JetAPI(api_key=\"API_KEY\",private_key=\"PRIVATE_KEY\",network='mainnet'# mainnet / testnet)Infoawaitxjet.currencies()# Shows all saved xJetSwap currenciesAccountawaitapi.me()# get API Application information.# {'id': , 'name: , 'service_wallet': }awaitapi.balance()# get balance# {# 'balances': [# {'currency': , 'amount': ,# 'values': {'byn': 0.0, 'cny': 0.0, 'eur': 0.0, 'gbp': 0.0, 'kzt': 0.0, 'rub': 0.0, 'uah': 0.0, 'usd': 0.0}}],# 'timestamp': # }awaitapi.submit_deposit()# check for deposit# {'success': }# ton_address: str# currency: str# amount: floatawaitapi.withdraw(ton_address,currency,amount)# check for deposit# limit: int# offset: intawaitxjet.operations(limit,offset)# operationsCheque# currency: str# amount: float# expires: [int, None]# description: [str, None]# activates_count: [int, None]# groups_id: [int, None]# personal_id: [int, None]# password: [str, None]awaitapi.cheque_create(currency,amount,expires,description,activates_count,groups_id,personal_id,password)# create cheque# {'cheque_id': , 'external_link': 'https://t.me/xJetSwapBot?start=c_'}awaitapi.cheque_status(cheque_id)# get cheque status# {# 'id': ,# 'issuer_id': ,# 'amount': ,# 'activates_count': ,# 'activates: ,# 'locked_value': ,# 'currency': ,# 'expires': ,# 'description': ,# 'status': 'activated/canceled/expired/active',# 'password': ,# 'groups_id': ,# 'personal_id': ,# 'is_for_premium': # }awaitapi.cheque_list()# get cheques on account# list of cheque_statusawaitapi.cheque_cancel(cheque_id)# delete cheque# returns cheque_statusInvoice# currency: str# amount: float# description: [str, None]# max_payments: [int, None]awaitapi.invoice_create(currency,amount,description,max_payments)# create invoice# {'invoice_id': , 'external_link': 'https://t.me/xJetSwapBot?start=inv_'}awaitapi.invoice_status(invoice_status)# get invoice status# {# 'id': ,# 'description': ,# 'currency': ,# 'amount': ,# 'max_amount': None,# 'min_amount': None,# 'payments': [{'telegram_id': , 'amount': , 'comment': [str | None}, ... ],# 'max_payments': 1,# 'after_pay': [],# 'created': '2023-04-20T22:55:24.313000'# }awaitapi.invoice_list()# get invoices on account# list of invoice_status# NFT methodsawaitapi.nft_list()awaitapi.nft_transfer(nft_address,to_address)LicenseGNUv3"} +{"package": "xj-excel", "pacakge-description": "SKY-EXCEL Moduleexcel\u5de5\u5177\u6a21\u5757Part 1. Introduce\u4ecb\u7ecd\u5982\u679c\u4f60\u4e0d\u5e0c\u671b\u6bcf\u4e00\u6b21\u9700\u8981\u628a\u63a5\u53e3\u8fd4\u56de\u7684\u5b57\u5178\u6570\u636e\u5bfc\u51fa\u6210excel\u8868\u683c\u800c\u53bb\u8bbe\u8ba1\u8868\u5934\u3001\u5408\u5e76\u5355\u5143\u683c\uff0c\u800c\u8fdb\u884c\u4e00\u6b21\u4e00\u6b21\u91cd\u590d\u5927\u91cf\u7684\u7f16\u7a0b\u6d3b\u52a8\u3002\u90a3\u4e48\u4f60\u53ef\u4ee5\u5c1d\u8bd5\u4e00\u4e0b\u8fd9\u4e2a\u6a21\u5757\u3002sky-excel\u628a\u8868\u5934\u8bbe\u8ba1\u4e0e\u5355\u5143\u683c\u8bbe\u8ba1\u8026\u5408\u5230\u4e00\u8d77\uff0c\u4f60\u53ea\u9700\u8981\u521b\u5efa\u4e00\u4e2aexcel\u6a21\u677f\u5373\u53ef\uff0c\u7136\u540e\u8fdb\u884c\u914d\u7f6e\u5bf9\u5e94\u8f93\u5165\u7684\u5b57\u6bb5\u5c31\u53ef\u4ee5\u5b9e\u73b0\uff0c\u628a\u63a5\u53e3\u7684\u6570\u636e\u5bfc\u51fa\u5355\u5143\u683c\u3002\u8fd9\u4e2a\u6a21\u5757\u4ec5\u4ec5\u505a\u4e86\u4e00\u4ef6\u4e8b\u60c5\uff0c\u5c31\u662f\u628a\u4f60\u5199\u597d\u7684\u8868\u5934\u7248\u672c\u6284\u5199\u4e00\u822c\uff0c\u628a\u5b57\u5178\u6570\u636e\u6309\u7167\u952e\u503c\u5bf9\u5339\u914d\u586b\u5145\u8fdb\u53bb\u5373\u53ef\u3002Part 2. API DocumentAPI 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----------------------------DROPTABLEIFEXISTS`location_boundary`;CREATETABLE`location_boundary`(`id`int(11)NOTNULLAUTO_INCREMENT,`boundary_list`textCHARACTERSETutf8COLLATEutf8_unicode_ciNOTNULLCOMMENT'\u8fb9\u754c\u7ebf\u5217\u8868',`name`varchar(30)CHARACTERSETutf8COLLATEutf8_unicode_ciNOTNULLCOMMENT'\u540d\u79f0',`created_at`timestamp(0)NOTNULLDEFAULTCURRENT_TIMESTAMP(0)ONUPDATECURRENT_TIMESTAMP(0),PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=5CHARACTERSET=utf8COLLATE=utf8_unicode_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for location_location-- ----------------------------DROPTABLEIFEXISTS`location_location`;CREATETABLE`location_location`(`id`int(10)NOTNULLAUTO_INCREMENT,`name`varchar(50)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULLCOMMENT'\u7ad9\u540d',`region_code`bigint(18)NULLDEFAULTNULLCOMMENT'\u533a\u7ad9\u53f7',`address`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULLCOMMENT'\u7ad9\u5740',`longitude`decimal(10,6)NULLDEFAULTNULLCOMMENT'\u7ecf\u5ea6',`latitude`decimal(10,6)NULLDEFAULTNULLCOMMENT'\u7eac\u5ea6',`group_id`int(11)NOTNULLDEFAULT0COMMENT'\u5206\u7ec4ID',`user_id`int(11)NOTNULLDEFAULT0COMMENT'\u7528\u6237ID',`by_user_id`int(11)NOTNULLDEFAULT0COMMENT'\u586b\u62a5\u7528\u6237ID',`updated_at`timestamp(0)NULLDEFAULTCURRENT_TIMESTAMP(0)ONUPDATECURRENT_TIMESTAMP(0),`created_at`timestamp(0)NULLDEFAULTCURRENT_TIMESTAMP(0),`is_delete`tinyint(2)NOTNULLCOMMENT'\u662f\u5426\u5220\u9664',PRIMARYKEY(`id`)USINGBTREE,INDEX`code`(`region_code`)USINGBTREE,INDEX`lng`(`longitude`)USINGBTREE,INDEX`lat`(`latitude`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=231CHARACTERSET=utf8COLLATE=utf8_general_ciCOMMENT='\u6c14\u8c61\u7ad9\u4fe1\u606f'ROW_FORMAT=Compact;-- 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PyPI."} +{"package": "xj-migrate", "pacakge-description": "xj_migrate\u4ecb\u7ecd\u8fc1\u79fb\u6a21\u5757\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xjobs", "pacakge-description": "No description available on PyPI."} +{"package": "xj_palindrome", "pacakge-description": "No description available on PyPI."} +{"package": "xjpath", "pacakge-description": "No description available on PyPI."} +{"package": "xj-payment", "pacakge-description": "xj_payment\u4ecb\u7ecd\u652f\u4ed8\u6a21\u5757\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bpip install --upgrade -ihttps://pypi.org/simplexj_payment\u4f7f\u7528\u8bf4\u660e\u7279\u522b\u6ce8\u610f\uff1a\u7531\u4e8e\u7248\u672c\u517c\u5bb9\u95ee\u9898 \u66f4\u65b0\u5b8c\u652f\u4ed8\u6a21\u5757\u540e \u9700\u624b\u52a8\u5c06 pyOpenSSL \u66f4\u65b0\u5230\u6700\u65b0\u7248\u672c \u547d\u4ee4\uff1a\npip install --upgrade pyOpenSSL\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-push", "pacakge-description": "xj_push\u4ecb\u7ecd\u63a8\u9001\u6a21\u5757\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-python", "pacakge-description": "No description available on PyPI."} +{"package": "xj-recycle", "pacakge-description": "xj-recycle\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/"} +{"package": "xj-resource", "pacakge-description": "\u6a21\u5757\u4ecb\u7ecd1.\u8d44\u6e90\u4e0a\u4f201.\u6587\u4ef6\u4e0a\u4f202.\u56fe\u7247\u4e0a\u4f20SQLCREATETABLE`resource_file`(`id`int(11)NOTNULLAUTO_INCREMENT,`user_id`int(11)NOTNULLDEFAULT'0'COMMENT'\u7528\u6237ID',`title`varchar(50)COLLATEutf8_unicode_ciNOTNULLDEFAULT'',`url`varchar(255)COLLATEutf8_unicode_ciNOTNULLDEFAULT''COMMENT'\u4fdd\u5b58\u8def\u5f84',`filename`varchar(80)COLLATEutf8_unicode_ciNOTNULLDEFAULT''COMMENT'\u6587\u4ef6\u540d\u79f0',`format`varchar(10)COLLATEutf8_unicode_ciNOTNULLCOMMENT'\u6587\u4ef6\u540e\u7f00',`thumb`varchar(255)COLLATEutf8_unicode_ciDEFAULT''COMMENT'\u7f29\u7565\u56fe\u4f4d\u7f6e',`md5`varchar(255)COLLATEutf8_unicode_ciNOTNULLDEFAULT'',`snapshot`jsonDEFAULTNULLCOMMENT'\u6587\u4ef6\u5feb\u7167',`created_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMP,`updated_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP,PRIMARYKEY(`id`))ENGINE=InnoDBAUTO_INCREMENT=5DEFAULTCHARSET=utf8COLLATE=utf8_unicode_ciCOMMENT='\u6587\u4ef6\u4e0a\u4f20\u8868';CREATETABLE`resource_file_map`(`id`int(11)NOTNULLAUTO_INCREMENT,`file_id`int(11)NOTNULLCOMMENT'\u56fe\u7247ID',`source_id`int(11)NOTNULLCOMMENT'\u6765\u6e90\u8868 \u5173\u8054ID',`source_table`varchar(255)COLLATEutf8_unicode_ciNOTNULLCOMMENT'\u6765\u6e90\u8868\u8868\u660e',`price`int(10)NOTNULL,`created_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMP,`updated_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP,PRIMARYKEY(`id`),KEY`image_id`(`file_id`))ENGINE=InnoDBDEFAULTCHARSET=utf8COLLATE=utf8_unicode_ci;CREATETABLE`resource_image`(`id`int(11)NOTNULLAUTO_INCREMENT,`user_id`int(11)NOTNULLDEFAULT'0'COMMENT'\u7528\u6237ID',`title`varchar(50)COLLATEutf8_unicode_ciNOTNULLDEFAULT'',`url`varchar(255)COLLATEutf8_unicode_ciNOTNULLDEFAULT''COMMENT'\u4fdd\u5b58\u8def\u5f84',`filename`varchar(80)COLLATEutf8_unicode_ciNOTNULLDEFAULT''COMMENT'\u6587\u4ef6\u540d\u79f0',`format`varchar(10)COLLATEutf8_unicode_ciNOTNULLDEFAULT''COMMENT'\u6587\u4ef6\u540e\u7f00',`thumb`varchar(255)COLLATEutf8_unicode_ciDEFAULT''COMMENT'\u7f29\u7565\u56fe\u4f4d\u7f6e',`md5`varchar(255)COLLATEutf8_unicode_ciNOTNULLDEFAULT'',`snapshot`jsonDEFAULTNULLCOMMENT'\u6587\u4ef6\u5feb\u7167',`created_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMP,`updated_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP,PRIMARYKEY(`id`))ENGINE=InnoDBAUTO_INCREMENT=17DEFAULTCHARSET=utf8COLLATE=utf8_unicode_ciCOMMENT='\u6587\u4ef6\u4e0a\u4f20\u8868';CREATETABLE`resource_image_map`(`id`int(11)NOTNULLAUTO_INCREMENT,`image_id`int(11)NOTNULLCOMMENT'\u56fe\u7247ID',`source_id`int(11)NOTNULLCOMMENT'\u6765\u6e90\u8868 \u5173\u8054ID',`source_table`varchar(255)COLLATEutf8_unicode_ciNOTNULLCOMMENT'\u6765\u6e90\u8868\u8868\u660e',`price`int(10)NOTNULL,`created_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMP,`updated_at`timestampNOTNULLDEFAULTCURRENT_TIMESTAMPONUPDATECURRENT_TIMESTAMP,PRIMARYKEY(`id`),KEY`image_id`(`image_id`))ENGINE=InnoDBDEFAULTCHARSET=utf8COLLATE=utf8_unicode_ci;\u914d\u7f6eSTATIC_URL='/static/'STATICFILES_DIRS=(os.path.join(BASE_DIR,'static'),)xj-resource\u4f9d\u8d56\u65e0\u914d\u7f6esettings.pySTATIC_URL='/static/'# \u914d\u7f6e\u6d4f\u89c8\u5668\u8bbf\u95ee\u9759\u6001\u8d44\u6e90\u7684\u201c\u6839\u8def\u5f84\u201dMEDIA_URL=\"/media/\"MEDIA_ROOT=os.path.join(BASE_DIR,\"media\")STATIC_ROOT=os.path.join(BASE_DIR,\"static\")# \u4e0d\u8981\u548c STATICFILES_DIRS \u76f8\u540c\uff0c\u4f1a\u51b2\u7a81\u7684 \u90e8\u7f72django\u9879\u76ee\u9700\u8981\u7528\u5230STATIC_ROOT# \u6ce8\u610f\uff1aSTATIC_ROOT \u548c STATICFILES_DIRS \u4e0d\u662f\u540c\u4e00\u4e2a\u4e1c\u897f\uff0c\u53ea\u6709\u5728\u8fd9\u91cc\u624d\u662f\u771f\u7684 /static/# \u516c\u5171\u7684\u9759\u6001\u6587\u4ef6\u7684\u6587\u4ef6\u5939STATICFILES_DIRS=[os.path.join(BASE_DIR,\"resource\"),# os.path.join(BASE_DIR, \"media\")# os.path.join(BASE_DIR, \"static\")]===================="} +{"package": "xj-role", "pacakge-description": "Xj-User Module\u7528\u6237\u6a21\u5757Part 1. Introduce\u4ecb\u7ecdPart 2. API DocumentAPI \u63a5\u53e3\u6587\u6863Part 3. Normal FormNF \u8303\u5f0f\u8bbe\u8ba1\uff0c\u5173\u7cfb\u6a21\u5f0f\u8bbe\u8ba1\u8bc4\u4f30\u5206\u6790"} +{"package": "xj-ruoyi", "pacakge-description": "Xj-User Module\u7528\u6237\u6a21\u5757Part 1. Introduce\u4ecb\u7ecdPart 2. API DocumentAPI \u63a5\u53e3\u6587\u6863Part 3. Normal FormNF \u8303\u5f0f\u8bbe\u8ba1\uff0c\u5173\u7cfb\u6a21\u5f0f\u8bbe\u8ba1\u8bc4\u4f30\u5206\u6790"} +{"package": "xjskypdf", "pacakge-description": "This is only one!"} +{"package": "xjson", "pacakge-description": "# xjsonxjson \u662f\u4e00\u4e2a\u80fd\u8ba9\u4f60\u7528xpath \u8bed\u6cd5\u6765\u89e3\u6790\u7684json\u7684\u5de5\u5177##Overview\u5728\u5904\u7406json\u7684\u65f6\u5019\uff0c\u5982\u679cjson\n\u5217\u8868\u6709\u5f88\u591a\u5143\u7d20\u7684\u8bdd\uff0c\u9700\u8981\u4e00\u4e2a\u4e2a\u8fed\u4ee3\u53bb\u5904\u7406\u3002\u7136\u800c\u5728xpath\n\u5374\u4e0d\u662f\u8fd9\u6837\u7684\uff0cxpath \u53ef\u4ee5\u628a\u8def\u5f84\u4e0b\u7684\u90fd\u63d0\u53d6\u51fa\u6765\uff0c\u8fd9\u6837\u5c31\u80fd\u628a\u63d0\u53d6\n\u53d8\u6210\u4e00\u884c\uff0c\u65b9\u4fbf\u5199\u5728\u914d\u7f6e\u6587\u4ef6\u4e2d\u3002 xjson\n\u505a\u7684\u5c31\u662f\u8fd9\u4e48\u4e00\u4ef6\u4e8b\u3002\u8ba9\u4f60\u80fd\u591f\u4ee5xpath\u7684\u5f62\u5f0f\u89e3\u6790json\u3002{\n \"success\":true,\n \"message\":\"\u64cd\u4f5c\u6210\u529f\uff01\",\n \"result\":[\n {\n \"firstCategoryList\":[\n {\n \"name\":\"\u5de5\u5177\",\n \"id\":\"2\"\n }\n ],\n \"secondCategoryList\":[\n {\n \"name\":\"\u94bb\u524a\u7c7b\u7535\u52a8\u5de5\u5177\",\n \"id\":\"142\",\n \"list\":[\n {\n \"name\":\"\u624b\u7535\u94bb\",\n \"id\":\"925\"\n },\n {\n \"name\":\"\u78c1\u5ea7\u94bb\",\n \"id\":\"928\"\n }\n ]\n },\n {\n \"name\":\"\u78e8\u524a\u7c7b\u7535\u52a8\u5de5\u5177\",\n \"id\":\"143\",\n \"list\":[\n {\n \"name\":\"\u89d2\u5411\u78e8\u5149\u673a\",\n \"id\":\"936\"\n },\n {\n \"name\":\"\u78e8\u5177\u7535\u78e8\",\n \"id\":\"937\"\n }\n ]\n }\n ]\n }\n ]\n}\u5982\u679c\u7528json\uff0c\u9700\u8981\u628a\u4e09\u7ea7\u5206\u7c7b\u63d0\u53d6\u51fa\u6765\u7684\u8bdd\uff0c\u4f60\u9700\u8981\u5199\u6210for result in json_content[\"result\"]:\n for second_category in result[\"secondCategoryList\"]:\n for third_category in second_category[\"list\"]:\n print third_category[\"name\"]\u4e0d\u4ec5\u6df7\u4e71\uff0c\u800c\u4e14\u9700\u8981\u65f6\u523b\u6ce8\u610f\u5404\u5c42\u5d4c\u5957\u4e4b\u95f4\u7684\u5173\u7cfb\uff0c\u800c\u5728 xjson\n\u4e2d\uff0c\u4f60\u53ea\u9700\u8981\u6309\u7167\u5c42\u6b21\u5173\u7cfb\u5199\u6210result/secondCategoryList/list/name\u5c31\u53ef\u4ee5\u628a\u4e09\u7ea7\u5206\u7c7b\u5168\u90e8\u63d0\u53d6\u51fa\u6765\u4e86\u3002\n\u800c\u4e14\u8fd9\u6837\u505a\u7684\u8bdd\uff0c\u653e\u5728\u914d\u7f6e\u6587\u4ef6\u4e2d\uff0c\u901a\u8fc7\u914d\u7f6e\u6765\u63d0\u53d6json\u662f\u975e\u5e38\u65b9\u4fbf\u7684\u3002Requirementspython2.7"} +{"package": "xjsonrpc", "pacakge-description": "pjrpc upstream status:bernhardkaindl/xjsonrpc status:xjsonrpcis an extensibleJSON-RPCclient/server library with an intuitive interface\nthat can be easily extended and integrated in your project without writing a lot of boilerplate code.It was forked fromhttps://github.com/dapper91/pjrpcto make fast progress in\nthe area of the rabbitmq/aio_pika backend with fixes and improved code examples.Features:framework agnosticintuitive apiextendabilitysynchronous and asynchronous client backendsynchronous and asynchronous server supportpopular frameworks integrationbuiltin parameter validationpytest integrationopenapi schema generation supportweb ui support (SwaggerUI, RapiDoc, ReDoc)InstallationYou can install xjsonrpc with pip:$pipinstallxjsonrpcExtra requirementsaiohttpaio_pikaflaskjsonschemakombupydanticrequestshttpxopenapi-ui-bundlesstarlettedjangoDocumentationDocumentation is available atRead the Docs.QuickstartClient requestsxjsonrpcclient interface is very simple and intuitive. Methods may be called by name, using proxy object\nor by sending handmadexjsonrpc.common.Requestclass object. Notification requests can be made usingxjsonrpc.client.AbstractClient.notifymethod or by sending axjsonrpc.common.Requestobject without id.importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')response:xjsonrpc.Response=client.send(xjsonrpc.Request('sum',params=[1,2],id=1))print(f\"1 + 2 ={response.result}\")result=client('sum',a=1,b=2)print(f\"1 + 2 ={result}\")result=client.proxy.sum(1,2)print(f\"1 + 2 ={result}\")client.notify('tick')Asynchronous client api looks pretty much the same:importxjsonrpcfromxjsonrpc.client.backendimportaiohttpasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')response=awaitclient.send(xjsonrpc.Request('sum',params=[1,2],id=1))print(f\"1 + 2 ={response.result}\")result=awaitclient('sum',a=1,b=2)print(f\"1 + 2 ={result}\")result=awaitclient.proxy.sum(1,2)print(f\"1 + 2 ={result}\")awaitclient.notify('tick')Batch requestsBatch requests also supported. You can buildxjsonrpc.common.BatchRequestrequest by your hand and then send it to the\nserver. The result is axjsonrpc.common.BatchResponseinstance you can iterate over to get all the results or get\neach one by index:importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')batch_response=awaitclient.batch.send(xjsonrpc.BatchRequest(xjsonrpc.Request('sum',[2,2],id=1),xjsonrpc.Request('sub',[2,2],id=2),xjsonrpc.Request('div',[2,2],id=3),xjsonrpc.Request('mult',[2,2],id=4),))print(f\"2 + 2 ={batch_response[0].result}\")print(f\"2 - 2 ={batch_response[1].result}\")print(f\"2 / 2 ={batch_response[2].result}\")print(f\"2 * 2 ={batch_response[3].result}\")There are also several alternative approaches which are a syntactic sugar for the first one (note that the result\nis not axjsonrpc.common.BatchResponseobject anymore but a tuple of \u201cplain\u201d method invocation results):using chain call notation:result=awaitclient.batch('sum',2,2)('sub',2,2)('div',2,2)('mult',2,2).call()print(f\"2 + 2 ={result[0]}\")print(f\"2 - 2 ={result[1]}\")print(f\"2 / 2 ={result[2]}\")print(f\"2 * 2 ={result[3]}\")using subscription operator:result=awaitclient.batch[('sum',2,2),('sub',2,2),('div',2,2),('mult',2,2),]print(f\"2 + 2 ={result[0]}\")print(f\"2 - 2 ={result[1]}\")print(f\"2 / 2 ={result[2]}\")print(f\"2 * 2 ={result[3]}\")using proxy chain call:result=awaitclient.batch.proxy.sum(2,2).sub(2,2).div(2,2).mult(2,2).call()print(f\"2 + 2 ={result[0]}\")print(f\"2 - 2 ={result[1]}\")print(f\"2 / 2 ={result[2]}\")print(f\"2 * 2 ={result[3]}\")Which one to use is up to you but be aware that if any of the requests returns an error the result of the other ones\nwill be lost. In such case the first approach can be used to iterate over all the responses and get the results of\nthe succeeded ones like this:importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')batch_response=client.batch.send(xjsonrpc.BatchRequest(xjsonrpc.Request('sum',[2,2],id=1),xjsonrpc.Request('sub',[2,2],id=2),xjsonrpc.Request('div',[2,2],id=3),xjsonrpc.Request('mult',[2,2],id=4),))forresponseinbatch_response:ifresponse.is_success:print(response.result)else:print(response.error)Batch notifications:importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')client.batch.notify('tick').notify('tack').notify('tick').notify('tack').call()Serverxjsonrpcsupports popular backend frameworks likeaiohttp,flaskand message brokers likekombuandaio_pika.Running of aiohttp based JSON-RPC server is a very simple process. Just define methods, add them to the\nregistry and run the server:importuuidfromaiohttpimportwebimportxjsonrpc.serverfromxjsonrpc.server.integrationimportaiohttpmethods=xjsonrpc.server.MethodRegistry()@methods.add(context='request')asyncdefadd_user(request:web.Request,user:dict):user_id=uuid.uuid4().hexrequest.app['users'][user_id]=userreturn{'id':user_id,**user}jsonrpc_app=aiohttp.Application('/api/v1')jsonrpc_app.dispatcher.add_methods(methods)jsonrpc_app.app['users']={}if__name__==\"__main__\":web.run_app(jsonrpc_app.app,host='localhost',port=8080)Parameter validationVery often besides dumb method parameters validation it is necessary to implement more \u201cdeep\u201d validation and provide\ncomprehensive errors description to clients. Fortunatelyxjsonrpchas builtin parameter validation based onpydanticlibrary which uses python type annotation for validation.\nLook at the following example: all you need to annotate method parameters (or describe more complex types beforehand if\nnecessary).xjsonrpcwill be validating method parameters and returning informative errors to clients.importenumimportuuidfromtypingimportListimportpydanticfromaiohttpimportwebimportxjsonrpc.serverfromxjsonrpc.server.validatorsimportpydanticasvalidatorsfromxjsonrpc.server.integrationimportaiohttpmethods=xjsonrpc.server.MethodRegistry()validator=validators.PydanticValidator()classContactType(enum.Enum):PHONE='phone'EMAIL='email'classContact(pydantic.BaseModel):type:ContactTypevalue:strclassUser(pydantic.BaseModel):name:strsurname:strage:intcontacts:List[Contact]@methods.add(context='request')@validator.validateasyncdefadd_user(request:web.Request,user:User):user_id=uuid.uuid4()request.app['users'][user_id]=userreturn{'id':user_id,**user.dict()}classJSONEncoder(xjsonrpc.server.JSONEncoder):defdefault(self,o):ifisinstance(o,uuid.UUID):returno.hexifisinstance(o,enum.Enum):returno.valuereturnsuper().default(o)jsonrpc_app=aiohttp.Application('/api/v1',json_encoder=JSONEncoder)jsonrpc_app.dispatcher.add_methods(methods)jsonrpc_app.app['users']={}if__name__==\"__main__\":web.run_app(jsonrpc_app.app,host='localhost',port=8080)Error handlingxjsonrpcimplements all the errors listed inprotocol specificationwhich can be found inxjsonrpc.common.exceptionsmodule so that error handling is very simple and \u201cpythonic-way\u201d:importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclient=xjsonrpc_client.Client('http://localhost/api/v1')try:result=client.proxy.sum(1,2)exceptxjsonrpc.MethodNotFoundase:print(e)Default error list can be easily extended. All you need to create an error class inherited fromxjsonrpc.exc.JsonRpcErrorand define an error code and a description message.xjsonrpcwill be automatically\ndeserializing custom errors for you:importxjsonrpcfromxjsonrpc.client.backendimportrequestsasxjsonrpc_clientclassUserNotFound(xjsonrpc.exc.JsonRpcError):code=1message='user not found'client=xjsonrpc_client.Client('http://localhost/api/v1')try:result=client.proxy.get_user(user_id=1)exceptUserNotFoundase:print(e)On the server side everything is also pretty straightforward:importuuidimportflaskimportxjsonrpcfromxjsonrpc.serverimportMethodRegistryfromxjsonrpc.server.integrationimportflaskasintegrationapp=flask.Flask(__name__)methods=xjsonrpc.server.MethodRegistry()classUserNotFound(xjsonrpc.exc.JsonRpcError):code=1message='user not found'@methods.adddefadd_user(user:dict):user_id=uuid.uuid4().hexflask.current_app.users[user_id]=userreturn{'id':user_id,**user}@methods.adddefget_user(self,user_id:str):user=flask.current_app.users.get(user_id)ifnotuser:raiseUserNotFound(data=user_id)returnuserjson_rpc=integration.JsonRPC('/api/v1')json_rpc.dispatcher.add_methods(methods)app.users={}json_rpc.init_app(app)if__name__==\"__main__\":app.run(port=80)Open API specificationxjsonrpchas built-inOpenAPIandOpenRPCspecification generation support and integrated web UI as an extra dependency. Three UI types are supported:SwaggerUI (https://swagger.io/tools/swagger-ui/)RapiDoc (https://mrin9.github.io/RapiDoc/)ReDoc (https://github.com/Redocly/redoc)Web UI extra dependency can be installed using the following code:$pipinstallxjsonrpc[openapi-ui-bundles]The following example illustrates how to configure OpenAPI specification generation\nand Swagger UI web tool with basic auth:importuuidfromtypingimportAny,Optionalimportflaskimportflask_httpauthimportpydanticimportflask_corsfromwerkzeugimportsecurityimportxjsonrpc.server.specs.extractors.pydanticfromxjsonrpc.server.integrationimportflaskasintegrationfromxjsonrpc.server.validatorsimportpydanticasvalidatorsfromxjsonrpc.server.specsimportextractors,openapiasspecsapp=flask.Flask('myapp')flask_cors.CORS(app,resources={\"/myapp/api/v1/*\":{\"origins\":\"*\"}})methods=xjsonrpc.server.MethodRegistry()validator=validators.PydanticValidator()auth=flask_httpauth.HTTPBasicAuth()credentials={\"admin\":security.generate_password_hash(\"admin\")}@auth.verify_passworddefverify_password(username:str,password:str)->Optional[str]:ifusernameincredentialsandsecurity.check_password_hash(credentials.get(username),password):returnusernameclassAuthenticatedJsonRPC(integration.JsonRPC):@auth.login_requireddef_rpc_handle(self,dispatcher:xjsonrpc.server.Dispatcher)->flask.Response:returnsuper()._rpc_handle(dispatcher)classJSONEncoder(xjsonrpc.JSONEncoder):defdefault(self,o:Any)->Any:ifisinstance(o,pydantic.BaseModel):returno.dict()ifisinstance(o,uuid.UUID):returnstr(o)returnsuper().default(o)classUserIn(pydantic.BaseModel):\"\"\"\n User registration data.\n \"\"\"name:strsurname:strage:intclassUserOut(UserIn):\"\"\"\n Registered user data.\n \"\"\"id:uuid.UUIDclassAlreadyExistsError(xjsonrpc.exc.JsonRpcError):\"\"\"\n User already registered error.\n \"\"\"code=2001message=\"user already exists\"classNotFoundError(xjsonrpc.exc.JsonRpcError):\"\"\"\n User not found error.\n \"\"\"code=2002message=\"user not found\"@specs.annotate(tags=['users'],errors=[AlreadyExistsError],examples=[specs.MethodExample(summary=\"Simple example\",params=dict(user={'name':'John','surname':'Doe','age':25,},),result={'id':'c47726c6-a232-45f1-944f-60b98966ff1b','name':'John','surname':'Doe','age':25,},),],)@methods.add@validator.validatedefadd_user(user:UserIn)->UserOut:\"\"\"\n Creates a user.\n\n :param object user: user data\n :return object: registered user\n :raise AlreadyExistsError: user already exists\n \"\"\"forexisting_userinflask.current_app.users_db.values():ifuser.name==existing_user.name:raiseAlreadyExistsError()user_id=uuid.uuid4().hexflask.current_app.users_db[user_id]=userreturnUserOut(id=user_id,**user.dict())@specs.annotate(tags=['users'],errors=[NotFoundError],examples=[specs.MethodExample(summary='Simple example',params=dict(user_id='c47726c6-a232-45f1-944f-60b98966ff1b',),result={'id':'c47726c6-a232-45f1-944f-60b98966ff1b','name':'John','surname':'Doe','age':25,},),],)@methods.add@validator.validatedefget_user(user_id:uuid.UUID)->UserOut:\"\"\"\n Returns a user.\n\n :param object user_id: user id\n :return object: registered user\n :raise NotFoundError: user not found\n \"\"\"user=flask.current_app.users_db.get(user_id.hex)ifnotuser:raiseNotFoundError()returnUserOut(id=user_id,**user.dict())@specs.annotate(tags=['users'],errors=[NotFoundError],examples=[specs.MethodExample(summary='Simple example',params=dict(user_id='c47726c6-a232-45f1-944f-60b98966ff1b',),result=None,),],)@methods.add@validator.validatedefdelete_user(user_id:uuid.UUID)->None:\"\"\"\n Deletes a user.\n\n :param object user_id: user id\n :raise NotFoundError: user not found\n \"\"\"user=flask.current_app.users_db.pop(user_id.hex,None)ifnotuser:raiseNotFoundError()json_rpc=AuthenticatedJsonRPC('/api/v1',json_encoder=JSONEncoder,spec=specs.OpenAPI(info=specs.Info(version=\"1.0.0\",title=\"User storage\"),servers=[specs.Server(url='http://127.0.0.1:8080',),],security_schemes=dict(basicAuth=specs.SecurityScheme(type=specs.SecuritySchemeType.HTTP,scheme='basic',),),security=[dict(basicAuth=[]),],schema_extractor=extractors.pydantic.PydanticSchemaExtractor(),ui=specs.SwaggerUI(),# ui=specs.RapiDoc(),# ui=specs.ReDoc(),),)json_rpc.dispatcher.add_methods(methods)app.users_db={}myapp=flask.Blueprint('myapp',__name__,url_prefix='/myapp')json_rpc.init_app(myapp)app.register_blueprint(myapp)if__name__==\"__main__\":app.run(port=8080)Specification is available onhttp://localhost:8080/myapp/api/v1/openapi.jsonWeb UI is running onhttp://localhost:8080/myapp/api/v1/ui/Swagger UI:RapiDoc:Redoc:"} +{"package": "xj-task", "pacakge-description": "xj-task\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee 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----------------------------DROPTABLEIFEXISTS`thread`;CREATETABLE`thread`(`id`bigint(20)NOTNULLAUTO_INCREMENT,`is_deleted`tinyint(1)NOTNULL,`title`varchar(200)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`content`longtextCHARACTERSETutf8COLLATEutf8_general_ciNULL,`ip`char(39)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`has_enroll`tinyint(1)NOTNULL,`has_fee`tinyint(1)NOTNULL,`has_comment`tinyint(1)NOTNULL,`cover`varchar(1024)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`video`varchar(1024)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`photos`jsonNULL,`files`jsonNULL,`create_time`datetime(6)NOTNULL,`update_time`datetime(6)NOTNULL,`logs`jsonNULL,`auth_id`int(11)NOTNULL,`category_id`int(11)NOTNULL,`classify_id`int(11)NULLDEFAULTNULL,`show_id`int(11)NULLDEFAULTNULL,`user_id`bigint(20)NOTNULL,`author`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`is_original`tinyint(1)NOTNULL,`price`decimal(32,8)NULLDEFAULTNULL,`more`jsonNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_thread_auth_id_4ba1b73f_fk_eh_thread_auth_id`(`auth_id`)USINGBTREE,INDEX`eh_thread_category_id_83d71a7b_fk_eh_thread_category_id`(`category_id`)USINGBTREE,INDEX`eh_thread_classify_id_6d669669_fk_eh_thread_classify_id`(`classify_id`)USINGBTREE,INDEX`eh_thread_show_id_bd20d39c_fk_eh_thread_show_id`(`show_id`)USINGBTREE,INDEX`eh_thread_title_91293eff`(`title`)USINGBTREE,INDEX`eh_thread_user_id_9f31dde5`(`user_id`)USINGBTREE,INDEX`eh_thread_price_e356e61e`(`price`)USINGBTREE,CONSTRAINT`eh_thread_auth_id_4ba1b73f_fk_eh_thread_auth_id`FOREIGNKEY(`auth_id`)REFERENCES`thread_auth`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_thread_category_id_83d71a7b_fk_eh_thread_category_id`FOREIGNKEY(`category_id`)REFERENCES`thread_category`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_thread_classify_id_6d669669_fk_eh_thread_classify_id`FOREIGNKEY(`classify_id`)REFERENCES`thread_classify`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_thread_show_id_bd20d39c_fk_eh_thread_show_id`FOREIGNKEY(`show_id`)REFERENCES`thread_show`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=86CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_auth-- ----------------------------DROPTABLEIFEXISTS`thread_auth`;CREATETABLE`thread_auth`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(50)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=2CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_category-- ----------------------------DROPTABLEIFEXISTS`thread_category`;CREATETABLE`thread_category`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(50)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`description`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=2CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_classify-- 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----------------------------DROPTABLEIFEXISTS`thread_extend_data`;CREATETABLE`thread_extend_data`(`id`int(11)NOTNULLAUTO_INCREMENT,`field_1`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`field_2`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_3`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_4`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_5`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_6`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_7`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_8`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_9`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_10`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_11`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_12`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_13`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_14`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_15`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_16`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_17`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_18`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_19`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`field_20`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`thread_id`bigint(20)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_thread_extend_data_thread_id_89eebd4a_fk_eh_thread_id`(`thread_id`)USINGBTREE,CONSTRAINT`eh_thread_extend_data_thread_id_89eebd4a_fk_eh_thread_id`FOREIGNKEY(`thread_id`)REFERENCES`thread`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_extend_field-- ----------------------------DROPTABLEIFEXISTS`thread_extend_field`;CREATETABLE`thread_extend_field`(`id`int(11)NOTNULLAUTO_INCREMENT,`field`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`value`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`type`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`unit`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`classify_id`int(11)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,UNIQUEINDEX`eh_thread_extend_field_classify_id_field_537821d6_uniq`(`classify_id`,`field`)USINGBTREE,CONSTRAINT`eh_thread_extend_fie_classify_id_b341a273_fk_eh_thread`FOREIGNKEY(`classify_id`)REFERENCES`thread_classify`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_image_auth-- ----------------------------DROPTABLEIFEXISTS`thread_image_auth`;CREATETABLE`thread_image_auth`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_resource-- ----------------------------DROPTABLEIFEXISTS`thread_resource`;CREATETABLE`thread_resource`(`id`bigint(20)NOTNULL,`name`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`url`varchar(1024)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`filename`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`filetype`smallint(6)NULLDEFAULTNULL,`format`varchar(50)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`price`decimal(32,8)NULLDEFAULTNULL,`snapshot`jsonNULL,`logs`jsonNULL,`image_auth_id`int(11)NULLDEFAULTNULL,`user_id`bigint(20)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_thread_resource_user_id_647f8542_fk_mz_user_id`(`user_id`)USINGBTREE,INDEX`eh_thread_resource_image_auth_id_2662cb84_fk_eh_thread`(`image_auth_id`)USINGBTREE,INDEX`eh_thread_resource_price_9bc424eb`(`price`)USINGBTREE,CONSTRAINT`eh_thread_resource_image_auth_id_2662cb84_fk_eh_thread`FOREIGNKEY(`image_auth_id`)REFERENCES`thread_image_auth`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBCHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_show-- ----------------------------DROPTABLEIFEXISTS`thread_show`;CREATETABLE`thread_show`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(50)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`config`jsonNULL,`description`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULLCOMMENT' ',PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=2CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_statistic-- ----------------------------DROPTABLEIFEXISTS`thread_statistic`;CREATETABLE`thread_statistic`(`id`bigint(20)NOTNULLAUTO_INCREMENT,`flag_classifies`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`flag_weights`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`weight`doubleNOTNULL,`views`int(11)NOTNULL,`plays`int(11)NOTNULL,`comments`int(11)NOTNULL,`likes`int(11)NOTNULL,`favorite`int(11)NOTNULL,`shares`int(11)NOTNULL,`thread_id_id`bigint(20)NULLDEFAULTNULL,PRIMARYKEY(`id`)USINGBTREE,UNIQUEINDEX`thread_id_id`(`thread_id_id`)USINGBTREE,INDEX`eh_thread_statistic_weight_3752b28a`(`weight`)USINGBTREE,CONSTRAINT`eh_thread_statistic_thread_id_id_7763ffcc_fk_eh_thread_id`FOREIGNKEY(`thread_id_id`)REFERENCES`thread`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=44CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_tag-- ----------------------------DROPTABLEIFEXISTS`thread_tag`;CREATETABLE`thread_tag`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_tag_mapping-- ----------------------------DROPTABLEIFEXISTS`thread_tag_mapping`;CREATETABLE`thread_tag_mapping`(`id`int(11)NOTNULLAUTO_INCREMENT,`tag_id`int(11)NOTNULL,`thread_id`bigint(20)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_thread_tag_mapping_tag_id_0e339c9b_fk_eh_thread_tag_id`(`tag_id`)USINGBTREE,INDEX`eh_thread_tag_mapping_thread_id_eceb96e8_fk_eh_thread_id`(`thread_id`)USINGBTREE,CONSTRAINT`eh_thread_tag_mapping_tag_id_0e339c9b_fk_eh_thread_tag_id`FOREIGNKEY(`tag_id`)REFERENCES`thread_tag`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_thread_tag_mapping_thread_id_eceb96e8_fk_eh_thread_id`FOREIGNKEY(`thread_id`)REFERENCES`thread`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_to_resource-- ----------------------------DROPTABLEIFEXISTS`thread_to_resource`;CREATETABLE`thread_to_resource`(`id`int(11)NOTNULLAUTO_INCREMENT,`resource_id`bigint(20)NOTNULL,`thread_id`bigint(20)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_thread_to_resourc_resource_id_ab2eab84_fk_eh_thread`(`resource_id`)USINGBTREE,INDEX`eh_thread_to_resource_thread_id_9d5d277d_fk_eh_thread_id`(`thread_id`)USINGBTREE,CONSTRAINT`eh_thread_to_resourc_resource_id_ab2eab84_fk_eh_thread`FOREIGNKEY(`resource_id`)REFERENCES`thread_resource`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_thread_to_resource_thread_id_9d5d277d_fk_eh_thread_id`FOREIGNKEY(`thread_id`)REFERENCES`thread`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_transact-- ----------------------------DROPTABLEIFEXISTS`thread_transact`;CREATETABLE`thread_transact`(`id`bigint(20)NOTNULLAUTO_INCREMENT,`amount`decimal(32,2)NOTNULL,`balance`decimal(32,2)NOTNULL,`create_time`datetime(6)NOTNULL,`remark`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,`snapshot`jsonNULL,`currency_id`int(11)NOTNULL,`pay_mode_id`int(11)NOTNULL,`thread_id`bigint(20)NOTNULL,`user_id`bigint(20)NOTNULL,PRIMARYKEY(`id`)USINGBTREE,INDEX`eh_transact_currency_id_a6ec55bb_fk_eh_transact_currency_id`(`currency_id`)USINGBTREE,INDEX`eh_transact_pay_mode_id_3ca69012_fk_eh_transact_paymode_id`(`pay_mode_id`)USINGBTREE,INDEX`eh_transact_thread_id_f492b164_fk_eh_thread_id`(`thread_id`)USINGBTREE,INDEX`eh_transact_user_id_7723fcf3_fk_mz_user_id`(`user_id`)USINGBTREE,INDEX`eh_transact_amount_a5ca65d2`(`amount`)USINGBTREE,INDEX`eh_transact_balance_18c9a594`(`balance`)USINGBTREE,CONSTRAINT`eh_transact_currency_id_a6ec55bb_fk_eh_transact_currency_id`FOREIGNKEY(`currency_id`)REFERENCES`thread_transact_currency`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_transact_pay_mode_id_3ca69012_fk_eh_transact_paymode_id`FOREIGNKEY(`pay_mode_id`)REFERENCES`thread_transact_paymode`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_transact_thread_id_f492b164_fk_eh_thread_id`FOREIGNKEY(`thread_id`)REFERENCES`thread`(`id`)ONDELETERESTRICTONUPDATERESTRICT,CONSTRAINT`eh_transact_user_id_7723fcf3_fk_mz_user_id`FOREIGNKEY(`user_id`)REFERENCES`del_mz_user_v3`(`id`)ONDELETERESTRICTONUPDATERESTRICT)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_transact_currency-- ----------------------------DROPTABLEIFEXISTS`thread_transact_currency`;CREATETABLE`thread_transact_currency`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNOTNULL,`is_virtual`tinyint(1)NOTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;-- ------------------------------ Table structure for thread_transact_paymode-- ----------------------------DROPTABLEIFEXISTS`thread_transact_paymode`;CREATETABLE`thread_transact_paymode`(`id`int(11)NOTNULLAUTO_INCREMENT,`value`varchar(255)CHARACTERSETutf8COLLATEutf8_general_ciNULLDEFAULTNULL,PRIMARYKEY(`id`)USINGBTREE)ENGINE=InnoDBAUTO_INCREMENT=1CHARACTERSET=utf8COLLATE=utf8_general_ciROW_FORMAT=Dynamic;SETFOREIGN_KEY_CHECKS=1;\u4f7f\u75281.\u5728API\u4e2d\u6709\u90e8\u5206\u8026\u5408\uff0c\u9700\u8981\u8c03\u7528\u7528\u6237\u4fe1\u606f\u7684\u9700\u8981\u4f7f\u7528\uff1afrom.utils.custom_authentication_wrapperimportauthentication_wrapper@authentication_wrapperfun.....# \u6216\u8005fromapps.user.utils.custom_authorizationimportCustomAuthenticationclassShowListAPIView(APIView):\"\"\"get:\u5c55\u793a\u7c7b\u578b\u5217\u8868\"\"\"authentication_classes=(CustomAuthentication,)defget(self,request,*args,**kwargs):res=t.thread_show(request)returnres\u5bcc\u6587\u672c\u7f16\u8f91\u5668\u7684\u4f7f\u7528\uff1a\u5bcc\u6587\u672c\u7f16\u8f91\u5668\uff0c\u5728web\u5f00\u53d1\u4e2d\u53ef\u4ee5\u8bf4\u662f\u4e0d\u53ef\u7f3a\u5c11\u7684\u3002django\u5e76\u6ca1\u6709\u81ea\u5e26\u5bcc\u6587\u672c\u7f16\u8f91\u5668\uff0c\u56e0\u6b64\u6211\u4eec\u9700\u8981\u81ea\u5df1\u96c6\u6210\uff0c\u5728\u8fd9\u91cc\u63a8\u8350\u5927\u5bb6\u4f7f\u7528DjangoUeditor\uff0c\u56e0\u4e3aDjangoUeditor\u5c01\u88c5\u4e86\u6211\u4eec\u9700\u8981\u7684\u4e00\u4e9b\u529f\u80fd\u5982\u6587\u4ef6\u4e0a\u4f20\u3001\u5728\u540e\u53f0\u548c\u524d\u53f0\u4e00\u8d77\u4f7f\u7528\u7b49\uff0c\u975e\u5e38\u65b9\u4fbf\u3002\u4e00\u3001\u4e0b\u8f7dDjangoUeditor:\u200b 1.python3:https://github.com/twz915/DjangoUeditor3/(\u76f4\u63a5\u4e0b\u8f7dzip)\n\u200b 2.python2:https://github.com/zhangfisher/DjangoUeditor(\u76f4\u63a5\u4e0b\u8f7dzip,\u6216pip install DjangoUeditor)\u4e8c\u3001 \u65b0\u5efadjango\u9879\u76ee:\u200b 1. \u5728\u9879\u76ee\u7684\u6839\u76ee\u5f55\u65b0\u5efaextra_apps\u6587\u4ef6\u5939\u5e76\u5c06\u6211\u4eec\u4e0b\u8f7d\u597d\u7684zip\u6587\u4ef6\u89e3\u538b\u6253\u5f00\u540e\u627e\u5230 DjangoUeditor\u5c06DjangoUeditor\u76f4\u63a5\u62f7\u8d1d\u5230\u6211\u4eec\u9879\u76ee\u7684extra_apps\u4e2d\n\u200b 2.\u5728settings.py\u6587\u4ef6\u4e2d\u6dfb\u52a0\u4e24\u884c\u4ee3\u7801\uff1a\u5982\u4e0b\n\u200b sys.path.insert(0, os.path.join(BASE_DIR, 'apps'))\n\u200b sys.path.insert(0, os.path.join(BASE_DIR, 'extra_apps'))\n\u200b 3.\u53d8\u6210\u84dd\u8272\u6587\u4ef6\u5939\u540e\u5c31\u53ef\u4ee5\u5728settings.py \u7684INSTALLED_APPS\u4e2d\u5f15\u5165DjangoUeditor\nPS\uff1a\u6ce8\u610f\u5982\u679c\u53cd\u5411\u4ee3\u7406\u8bbf\u95ee\u9700\u8981\u518d\u6b21\u6267\u884c\u4e00\u6b21\uff0c\u9632\u6b62\u6837\u5f0f\u5931\u6548\u3002 python mananger.py collectstatic\u4e09\u3001\u5f02\u5e38\u5904\u7406\uff1a\u62a5\u9519\uff1aModuleNotFoundError: No module named 'django.utils.six' \u7684\u89e3\u51b3\u529e\u6cd5\u62a5\u9519\u539f\u56e0\uff1a\u5728python\u9ad8\u7248\u672c\uff0c\u7531\u4e8e\u7f3a\u5c11six.py\uff0c\u4f1a\u5bfc\u81f4DjangoUeditor\u6a21\u5757\u65e0\u6cd5\u627e\u5230'django.utils.six'\u6a21\u5757\u89e3\u51b3\u529e\u6cd5\uff1a\u5982\u679c\u662f\u865a\u62df\u673a\uff0c\u5c06venv/Lib/site-packages/six.py\u6587\u4ef6\u62f7\u8d1d\u5230venv/Lib/site-packages/django/utils/six.py\u5373\u53ef\u89e3\u51b3\u7248\u672c\u5dee\u522b\uff1av2\u4fdd\u6301\u539f\u6709\u63a5\u53e3\uff0c\u4f46\u662f\u652f\u6301\u6269\u5c55\u5b57\u6bb5\u914d\u7f6e\uff0c\u6269\u5c55\u5b57\u6bb5\u589e\u5220\u6539\u67e5\u3002\u4f46\u662f\u8fd8\u6ca1\u6709\u505a\u6761\u4ef6\u641c\u7d22xj-thread\u4ecb\u7ecd{\u4ee5\u4e0b\u662f Gitee \u5e73\u53f0\u8bf4\u660e\uff0c\u60a8\u53ef\u4ee5\u66ff\u6362\u6b64\u7b80\u4ecbGitee \u662f OSCHINA \u63a8\u51fa\u7684\u57fa\u4e8e Git \u7684\u4ee3\u7801\u6258\u7ba1\u5e73\u53f0\uff08\u540c\u65f6\u652f\u6301 SVN\uff09\u3002\u4e13\u4e3a\u5f00\u53d1\u8005\u63d0\u4f9b\u7a33\u5b9a\u3001\u9ad8\u6548\u3001\u5b89\u5168\u7684\u4e91\u7aef\u8f6f\u4ef6\u5f00\u53d1\u534f\u4f5c\u5e73\u53f0\n\u65e0\u8bba\u662f\u4e2a\u4eba\u3001\u56e2\u961f\u3001\u6216\u662f\u4f01\u4e1a\uff0c\u90fd\u80fd\u591f\u7528 Gitee \u5b9e\u73b0\u4ee3\u7801\u6258\u7ba1\u3001\u9879\u76ee\u7ba1\u7406\u3001\u534f\u4f5c\u5f00\u53d1\u3002\u4f01\u4e1a\u9879\u76ee\u8bf7\u770bhttps://gitee.com/enterprises}\u8f6f\u4ef6\u67b6\u6784\u8f6f\u4ef6\u67b6\u6784\u8bf4\u660e\u5b89\u88c5\u6559\u7a0bxxxxxxxxxxxx\u4f7f\u7528\u8bf4\u660exxxxxxxxxxxx\u53c2\u4e0e\u8d21\u732eFork \u672c\u4ed3\u5e93\u65b0\u5efa Feat_xxx \u5206\u652f\u63d0\u4ea4\u4ee3\u7801\u65b0\u5efa Pull Request\u7279\u6280\u4f7f\u7528 Readme_XXX.md \u6765\u652f\u6301\u4e0d\u540c\u7684\u8bed\u8a00\uff0c\u4f8b\u5982 Readme_en.md, Readme_zh.mdGitee \u5b98\u65b9\u535a\u5ba2blog.gitee.com\u4f60\u53ef\u4ee5https://gitee.com/explore\u8fd9\u4e2a\u5730\u5740\u6765\u4e86\u89e3 Gitee \u4e0a\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGVP\u5168\u79f0\u662f Gitee \u6700\u6709\u4ef7\u503c\u5f00\u6e90\u9879\u76ee\uff0c\u662f\u7efc\u5408\u8bc4\u5b9a\u51fa\u7684\u4f18\u79c0\u5f00\u6e90\u9879\u76eeGitee \u5b98\u65b9\u63d0\u4f9b\u7684\u4f7f\u7528\u624b\u518chttps://gitee.com/helpGitee \u5c01\u9762\u4eba\u7269\u662f\u4e00\u6863\u7528\u6765\u5c55\u793a Gitee \u4f1a\u5458\u98ce\u91c7\u7684\u680f\u76eehttps://gitee.com/gitee-stars/remotes/origin/master"} +{"package": "xjtlu", "pacakge-description": "XJTLU"} +{"package": "xj-tools", "pacakge-description": "\u6a21\u5757\u4ecb\u7ecd1.\u7528\u6237\u9a8c\u8bc1\u5668\u88c5\u9970\u56682.\u6a21\u578bcurd\u64cd\u4f5c\u52a9\u624b\u51fd\u65703.\u8868\u5355\u9a8c\u8bc1\u56684.\u8fd4\u56de\u534f\u8bae"} +{"package": "xju", "pacakge-description": "Various modules implemented to some broad principles:fine-grained static typingpure context managementuseful functionality that is hard to use incorrectly100% test coverage(see the bottom of this readme for release history)xju.newtype- static and dynamic distinct int, float and str typesunlike typing.NewType the new types are compatible with isinstance, so you\ncan actually use them to do real stuff, like implement overloaded methodsseexju/newtype.py.testfor sample codexju.cmc- context managementunlike python standard library e.g. open(), these are \u201cpure\u201d context managers: resources\nare never acquired until __enter__xju.cmc.cmclass- provides context management for class attributes that are context managersmanaging multiple resource attributes is clumsy with ExitStack, this module implements\n__enter__ and __exit__ automatically to ensure correct ordering and cleanup on exceptionsseexju/cmc/cmclass.py.testfor sample codexju.cmc.Dict- dictionary that is a context manager for its (context manager) valuesseexju/cmc/Dict.py.testfor sample codexju.cmc.Opt- context manager for its optional (context manager) valueseexju/cmc/Opt.py.testfor sample codexju.cmc.async_cmclass- provides async context management for class attributes that are async / sync context managersmanaging multiple resource attributes is clumsy with AsyncExitStack, this module implements\n__aenter__ and __aexit__ automatically to ensure correct ordering and cleanup on exceptionsseexju/cmc/async_cmclass.py.testfor sample codexju.cmc.AsyncDict- dictionary that is a async context manager for its (async context manager) valuesseexju/cmc/AsyncDict.py.testfor sample codexju.cmc.AsyncOpt- async context manager for its optional (async context manager) valueseexju/cmc/AsyncOpt.py.testfor sample codexju.cmc.io- pure context management for e.g. file reading and writing, non-blocking iosee unit tests for sample code:\n*FileLock.py.test*FileMode.py.test*FilePosition.py.test*FileReader.py.test*FileWriter.py.test*UnixStreamListener.py.test*UnixStreamSocket.py.test*Pipe.py.testxju.cmc.tstoretime-based storage, organised as files covering time-rangesseexju/cmc/tstore.py.testfor sample codexju.cmc.perflogtime-based json-format record storage built on xju.cmc.tstorexju.cmc.Thread/Mutex/Lock/Conditionthreading primitives that encourage correct designseexju/cmc/ThreadMutexLockCondition.py.testfor sample codexju.cmc.AsyncTask/Mutex/Lock/Conditionasyncio Task/Mutex/Lock/Condition context managersseexju/cmc/Task.py.testfor sample codexju.cmc.AsyncServiceQueueasyncio thread-safe service queue, allows any thread to queue a coroutine on an event loop\nso it is executed by a task in that event loopseexju/cmc/AsyncServiceQueue.py.testfor sample codexju.pqjquery-like html inspection and modificationseexju/pq.py.testfor sample codexju.assert_assert functions that capture term values e.g. x and y in Assert(x)==yseexju/assert_.py.testfor sample codexju.cmdwrapper for subprocess.Popen that captures very common usage without the option-and-flag-warren of subprocessseexju/cmd.py.testfor sample codexju.json_codecencoding/decoding type-hinted dict/list/int/bool/None/float/str/Enum and classes to and from jsondesigned to fit well with type checkingbuilt in support for xju.newtype described abovegenerates json schema equivalent schemas for typesgenerates typescript code (types, type-guards and dynamic casts) equivalentsextensible with custom encodingsseexju/json_codec.py.testfor full sample codexju.jsonschemarepresents JSON schemas as straight-foward, easy-to-read python data structures, because life\u2019s too short for jsonschema.orgseexju/jsonschema.py.testfor sample codexju.patchminimal, simple, direct patching(/stub/mock) utility, unlike mock-warren. Because one shouldn\u2019t need a degree to read and write a unit testseexju/patch.py.testfor sample codexju.timetype-safe time and duration classesseexju/time.py.testfor sample codexju.xnException wrapping to provide human readable context gatheringseexju/xn.py.testfor sample codeRelease History2.0.2 add xju.cmc.delay_cancellation2.0.2 add bytes support to xju.json_codec2.0.2 use class name as xn exception message where exception message is empty2.0.1 add python 3.12 support2.0.0 add xju.time.async_sleep_until()2.0.0 add xju.json_codec_mypy_plugin, avoids type: ignore against json_codec.codec()2.0.0 xn first line -> first parabreaking changexn.in_function_context now uses first paragraph of docstring\nnot just first line (paragraph ends at empty line); paragraph\nlines are stripped and joined by single space2.0.0 add xju.newtype.Bool1.4.1 fix type hints on xju.cmc.async_cmclass and xju.cmc.cmclass1.4.0 add Enum support to xju.json_codec1.3.0 add xju.cmc.AsyncDict, like xju.cmc.Dict but async1.3.0 xju.cmc.AsyncOpt/Opt async context manager that holds an optional async context manager1.3.0 xju.cmc.Opt context manager that holds an optional context manager1.3.0 python xju.cmc add async_cmclass, like xju.cmc.cmclass; handles both async and non-async attrs1.3.0 strip leading whitespace from doc strings, for compatibility with code formatters like black1.2.13 xju.newtype Literals now handle more than one value, e.g. Literal[\u2018fred\u2019,\u2019jock\u2019]1.2.13 xju.newtype eq/neq now follows python \u201cyou can compare apples to oranges\u201d, rely on mypy \u2013strict-equality (which for what it\u2019s worth is broken at mypy 1.3.0)1.2.13 now compatible with mypy \u2013strict-equality1.2.13 add xju.cmc.AsyncTask/Mutex/Condition/Lock (thread equivalents for asyncio); note Task deprecated, use AsyncTask1.2.13 add custom encoding facility to xju.json_codec1.2.13 add typescript aliases to json_codec generated code for xju.newtype Str/Int/Float1.2.12 fixes typescript null v object handling1.2.12 adds typescript aliases for NewStr, NewInt, NewFloat1.2.11 adds typescript \u2013strict support and fixes typescript code generation bugs1.2.11 xju.json_codec supports Literal[int] and Literal[bool]1.2.11 xju.json_codec supports generic classes1.2.10 xju.json_codec supports typing.NewType str/int/bool/float1.2.9 xju.json_codec generates typescript equivalents1.2.9 xju.json_codec adds codec() convenience method1.2.9 xju.json_codec uses kw_args to construct classes1.2.8 xju.json_codec supports string type-hints (for foward definitions)1.2.8 xju.json_codec adds typing.Self support (for recursive types)1.2.8 xju.json_codec requires python 3.11, tested with mypy 1.1.1"} +{"package": "xj-user", "pacakge-description": "Xj-User Module\u7528\u6237\u6a21\u5757Part 1. Introduce\u4ecb\u7ecdPart 2. API DocumentAPI \u63a5\u53e3\u6587\u6863Part 3. Normal FormNF \u8303\u5f0f\u8bbe\u8ba1\uff0c\u5173\u7cfb\u6a21\u5f0f\u8bbe\u8ba1\u8bc4\u4f30\u5206\u6790"} +{"package": "xjx7773", "pacakge-description": "#face_sdk_detect_landmark\n\u8fd9\u4e2a\u662fface_sdk_detect_landmark\u7684\u6a21\u5757\uff0c\u7b2c\u4e00\u6ce2\u5c1d\u8bd5\u3002"} +{"package": "xk6-output-plugin-py", "pacakge-description": "xk6-output-plugin-pyPython plugin SDK forxk6-output-plugin.Documentationpippipinstallxk6-output-plugin-pypoetrypoetryaddxk6-output-plugin-pyExampleimportdatetimeimportloggingfromxk6_output_plugin_py.outputimportserve,Output,Info,MetricType,ValueTypeclassExample(Output):defInit(self,params):logging.info(\"init\")returnInfo(description=\"example-py plugin\")defStart(self):logging.info(\"start\")defStop(self):logging.info(\"stop\")defAddMetrics(self,metrics):logging.info(\"metrics\")formetricinmetrics:logging.info(metric.name,extra={\"metric.type\":MetricType.Name(metric.type),\"metric.contains\":ValueType.Name(metric.contains),},)defAddSamples(self,samples):logging.info(\"samples\")forsampleinsamples:t=datetime.datetime.fromtimestamp(sample.time/1000.0,tz=datetime.timezone.utc)logging.info(sample.metric,extra={\"sample.time\":t,\"sample.value\":sample.value},)if__name__==\"__main__\":serve(Example())Output/\\ |\u203e\u203e| /\u203e\u203e/ /\u203e\u203e/ \n /\\ / \\ | |/ / / / \n / \\/ \\ | ( / \u203e\u203e\\ \n / \\ | |\\ \\ | (\u203e) | \n / __________ \\ |__| \\__\\ \\_____/ .io\n\nINFO[0000] init plugin=example.py\nINFO[0000] start plugin=example.py\n execution: local\n script: script.js\n output: example-py plugin\n\n scenarios: (100.00%) 1 scenario, 1 max VUs, 10m30s max duration (incl. graceful stop):\n * default: 1 iterations for each of 1 VUs (maxDuration: 10m0s, gracefulStop: 30s)\n\nINFO[0001] metrics plugin=example.py\nINFO[0001] http_reqs metric.contains=DEFAULT metric.type=COUNTER plugin=example.py\nINFO[0001] http_req_duration metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_blocked metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_connecting metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_tls_handshaking metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_sending metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_waiting metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_receiving metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0001] http_req_failed metric.contains=DEFAULT metric.type=RATE plugin=example.py\nINFO[0001] samples plugin=example.py\nINFO[0001] http_reqs plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=1\nINFO[0001] http_req_duration plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=124.175733\nINFO[0001] http_req_blocked plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=142.170447\nINFO[0001] http_req_connecting plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=124.043583\nINFO[0001] http_req_tls_handshaking plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=0\nINFO[0001] http_req_sending plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=0.091421\nINFO[0001] http_req_waiting plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=124.004817\nINFO[0001] http_req_receiving plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=0.079495\nINFO[0001] http_req_failed plugin=example.py sample.time=\"2023-06-23T07:14:09.985000+00:00\" sample.value=0\nINFO[0001] http_reqs plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=1\nINFO[0001] http_req_duration plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=127.37244\nINFO[0001] http_req_blocked plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=249.034715\nINFO[0001] http_req_connecting plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=123.502855\nINFO[0001] http_req_tls_handshaking plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=125.451159\nINFO[0001] http_req_sending plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=0.083551\nINFO[0001] http_req_waiting plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=127.117785\nINFO[0001] http_req_receiving plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=0.171104\nINFO[0001] http_req_failed plugin=example.py sample.time=\"2023-06-23T07:14:10.362000+00:00\" sample.value=0\nINFO[0002] metrics plugin=example.py\nINFO[0002] vus metric.contains=DEFAULT metric.type=GAUGE plugin=example.py\nINFO[0002] vus_max metric.contains=DEFAULT metric.type=GAUGE plugin=example.py\nINFO[0002] data_sent metric.contains=DATA metric.type=COUNTER plugin=example.py\nINFO[0002] data_received metric.contains=DATA metric.type=COUNTER plugin=example.py\nINFO[0002] iteration_duration metric.contains=TIME metric.type=TREND plugin=example.py\nINFO[0002] iterations metric.contains=DEFAULT metric.type=COUNTER plugin=example.py\nINFO[0002] samples plugin=example.py\nINFO[0002] vus plugin=example.py sample.time=\"2023-06-23T07:14:10.718000+00:00\" sample.value=1\nINFO[0002] vus_max plugin=example.py sample.time=\"2023-06-23T07:14:10.718000+00:00\" sample.value=1\nINFO[0002] data_sent plugin=example.py sample.time=\"2023-06-23T07:14:11.363000+00:00\" sample.value=542\nINFO[0002] data_received plugin=example.py sample.time=\"2023-06-23T07:14:11.363000+00:00\" sample.value=17310\nINFO[0002] iteration_duration plugin=example.py sample.time=\"2023-06-23T07:14:11.363000+00:00\" sample.value=1643.740944\nINFO[0002] iterations plugin=example.py sample.time=\"2023-06-23T07:14:11.363000+00:00\" sample.value=1\nINFO[0002] stop plugin=example.py\n\n data_received..................: 17 kB 11 kB/s\n data_sent......................: 542 B 330 B/s\n http_req_blocked...............: avg=195.6ms min=142.17ms med=195.6ms max=249.03ms p(90)=238.34ms p(95)=243.69ms\n http_req_connecting............: avg=123.77ms min=123.5ms med=123.77ms max=124.04ms p(90)=123.98ms p(95)=124.01ms\n \u2713 http_req_duration..............: avg=125.77ms min=124.17ms med=125.77ms max=127.37ms p(90)=127.05ms p(95)=127.21ms\n { expected_response:true }...: avg=125.77ms min=124.17ms med=125.77ms max=127.37ms p(90)=127.05ms p(95)=127.21ms\n \u2713 http_req_failed................: 0.00% \u2713 0 \u2717 2 \n http_req_receiving.............: avg=125.29\u00b5s min=79.49\u00b5s med=125.29\u00b5s max=171.1\u00b5s p(90)=161.94\u00b5s p(95)=166.52\u00b5s\n http_req_sending...............: avg=87.48\u00b5s min=83.55\u00b5s med=87.48\u00b5s max=91.42\u00b5s p(90)=90.63\u00b5s p(95)=91.02\u00b5s \n http_req_tls_handshaking.......: avg=62.72ms min=0s med=62.72ms max=125.45ms p(90)=112.9ms p(95)=119.17ms\n http_req_waiting...............: avg=125.56ms min=124ms med=125.56ms max=127.11ms p(90)=126.8ms p(95)=126.96ms\n http_reqs......................: 2 1.21664/s\n iteration_duration.............: avg=1.64s min=1.64s med=1.64s max=1.64s p(90)=1.64s p(95)=1.64s \n iterations.....................: 1 0.60832/s\n vus............................: 1 min=1 max=1\n vus_max........................: 1 min=1 max=1\n\n\nrunning (00m01.6s), 0/1 VUs, 1 complete and 0 interrupted iterations\ndefault \u2713 [======================================] 1 VUs 00m01.6s/10m0s 1/1 iters, 1 per VU"} +{"package": "xkammd", "pacakge-description": "#Hello"} +{"package": "xkammdmmd", "pacakge-description": "#Hello"} +{"package": "xkbcommon", "pacakge-description": "Python bindings forlibxkbcommonusingcffi.Example usage:>>> from xkbcommon import xkb\n>>> ctx = xkb.Context()\n>>> keymap = ctx.keymap_new_from_names()\n>>> state = keymap.state_new()\n>>> state.led_name_is_active(\"Caps Lock\")\nFalse\n>>> capslock = 66\n>>> str(state.update_key(capslock, xkb.XKB_KEY_DOWN))\n'StateComponent.XKB_STATE_MODS_DEPRESSED|XKB_STATE_MODS_LOCKED|XKB_STATE_MODS_EFFECTIVE|XKB_STATE_LEDS'\n>>> str(state.update_key(capslock, xkb.XKB_KEY_UP))\n'StateComponent.XKB_STATE_MODS_DEPRESSED'\n>>> state.led_name_is_active(\"Caps Lock\")\nTrueVersion numberingFrom release 0.5 onwards, the version numbering of this package will\nrelate to releases oflibxkbcommonas follows:If the Python package version is major.minor[.patch] then it requires\nat least release major.minor.0 of libxkbcommon to build and run, and\nshould work with any subsequent release. The patch version of the\nPython package is unrelated to the patch version of libxkbcommon."} +{"package": "xkbgroup", "pacakge-description": "========xkbgroup========.. image:: https://img.shields.io/badge/python-3.2+-blue.svg.. image:: https://img.shields.io/pypi/v/xkbgroup.svg:target: https://pypi.python.org/pypi/xkbgroup.. image:: https://img.shields.io/badge/license-MIT-blue.svg:target: https://github.com/hcpl/xkbgroup/blob/master/LICENSEUse this library to change the keyboard layout through XKB extension (subsystem)of the X server system. Both library and command line script included... contents:: **Table of Contents**Dependencies------------* Python 3.2+* ``libX11.so.6`` shared library which you must have by default if you useX serverInstallation------------>From PyPI package xkbgroup__++++++++++++++++++++++++++++__ https://pypi.python.org/pypi/xkbgroup.. code-block:: shpip install xkbgroupLibrary usage-------------.. code-block:: sh# Assume we have the following configuration$ setxkbmap -layout us,ru,ua,fr# Change layout once before calling python$ python.. code-block:: python>>> from xkbgroup import XKeyboard>>> xkb = XKeyboard()>>> xkb.groups_count4>>> xkb.group_num1>>> xkb.group_num = 2>>> xkb.group_num2>>> xkb.group_num -= 2>>> xkb.group_num0>>> xkb.groups_names['English (US)', 'Russian', 'Ukrainian', 'French']>>> xkb.group_name'English (US)'>>> xkb.group_name = 'Ukrainian'>>> xkb.group_name'Ukrainian'>>> xkb.group_num2>>> xkb.groups_symbols['us', 'ru', 'ua', 'fr']>>> xkb.group_symbol'ua'>>> xkb.group_symbol = 'fr'>>> xkb.group_symbol'fr'>>> xkb.groups_variants['', '', '', '']>>> xkb.group_variant''>>> xkb.group_num -= 3>>> xkb.group_variant''>>> xkb.group_num0>>> xkb.group_dataGroupData(num=0, name='English (US)', symbol='us', variant='')>>> xkb.groups_data[GroupData(num=0, name='English (US)', symbol='us', variant=''), GroupData(num=1, name='Russian', symbol='ru', variant=''), GroupData(num=2, name='Ukrainian', symbol='ua', variant=''), GroupData(num=3, name='French', symbol='fr', variant='')]>>> xkb.format('{num} => {symbol}')'0 => us'>>> xkb.group_num = 1>>> xkb.format('{num} => {symbol}')'1 => ru'>>> xkb.group_num = 3>>> xkb.format('{num}: {symbol} - {name} \"{variant}\"')'3: fr - French \"\"'>>> xkb.format('{count}')'4'>>> xkb.format('{names}')\"['English (US)', 'Russian', 'Ukrainian', 'French']\">>> xkb.format('{names::}')'English (US)RussianUkrainianFrench'>>> xkb.format('{names:: - }')'English (US) - Russian - Ukrainian - French'>>> xkb.format('{symbols:: - }')'us - ru - ua - fr'>>> xkb.format('{symbols:s: - }')'us - ru - ua - fr'>>> xkb.format('{all_data}')\"[GroupData(num=0, name='English (US)', symbol='us', variant=''), GroupData(num=1, name='Russian', symbol='ru', variant=''), GroupData(num=2, name='Ukrainian', symbol='ua', variant=''), GroupData(num=3, name='French', symbol='fr', variant='')]\">>> xkb.format('{all_data:{{num}}}')\"['0', '1', '2', '3']\">>> xkb.format('{all_data:/* {{name}} */}')\"['/* English (US) */', '/* Russian */', '/* Ukrainian */', '/* French */']\">>> xkb.format('{all_data:{{symbol}}:\\n}')'us\\nru\\nua\\nfr'>>> print(xkb.format('{all_data:{{symbol}}:\\n}'))usruuafr>>> print(xkb.format('{all_data:{{num}}\\\\: {{symbol}} - {{name}} - \"{{variant}}\":\\n}'))0: us - English (US) - \"\"1: ru - Russian - \"\"2: ua - Ukrainian - \"\"3: fr - French - \"\">>>Command line features mapping-----------------------------+----------+-------------------------------------+--------------------------------------+| Category | Library | Command line |+==========+=====================================+======================================+| Get | ``xkb.group_num`` | ``xkbgroup get num`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_name`` | ``xkbgroup get name`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_symbol`` | ``xkbgroup get symbol`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_variant`` | ``xkbgroup get variant`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_data`` | ``xkbgroup get current_data`` || +-------------------------------------+--------------------------------------+| | ``xkb.groups_count`` | ``xkbgroup get count`` || +-------------------------------------+--------------------------------------+| | ``xkb.groups_names`` | ``xkbgroup get names`` || +-------------------------------------+--------------------------------------+| | ``xkb.groups_symbols`` | ``xkbgroup get symbols`` || +-------------------------------------+--------------------------------------+| | ``xkb.groups_variants`` | ``xkbgroup get variants`` || +-------------------------------------+--------------------------------------+| | ``xkb.groups_data`` | ``xkbgroup get all_data`` |+----------+-------------------------------------+--------------------------------------+| Set | ``xkb.group_num = 2`` | ``xkbgroup set num 2`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_name = 'English (US)'`` | ``xkbgroup set name 'English (US)'`` || +-------------------------------------+--------------------------------------+| | ``xkb.group_symbol = 'fr'`` | ``xkbgroup set symbol fr`` |+----------+-------------------------------------+--------------------------------------+| Format | ``xkb.format('{format_str}')`` | ``xkbgroup format '{format_str}'`` |+----------+-------------------------------------+--------------------------------------+Naming convention-----------------Throughout the whole XKB subsystem the `so-called groups represent actualkeyboard layouts`__. This library follows the same convention and names of theAPI methods start with ``group_`` or ``groups_``.__ https://wiki.archlinux.org/index.php/X_KeyBoard_extension#Keycode_translationClasses-------These all reside in ``xkbgroup/core.py``:* ``XKeyboard`` \u2014 the main class:- ``__init__(self, auto_open=True, non_symbols=None)``:+ ``auto_open`` \u2014 if ``True`` then automatically call ``open_display()``on initialization.+ ``non_symbols`` \u2014 either iterable of string non-symbol names or None touse the default set of non-symbol names.- ``open_display()`` \u2014 establishes connection with X server and preparesobjects necessary to retrieve and send data.- ``close_display()`` \u2014 closes connection with X server and cleans upobjects created on ``open_display()``.- ``group_*`` \u2014 properties for accessing current group data:+ ``group_num`` \u2014 get/set current group number(e.g. ``0``, ``2``, ``3``).+ ``group_name`` \u2014 get/set current group full name(e.g. ``English (US)``, ``Russian``, ``French``).+ ``group_symbol`` \u2014 get/set current group symbol(e.g. ``us``, ``ru``, ``fr``).+ ``group_variant`` \u2014 get (only) current group variant(e.g. ``\u2006``, ``dos``, ``latin9``).+ ``group_data`` \u2014 get (only) all data about the current group.In fact, assembles all previous ``group_*`` values.- ``groups_*`` \u2014 properties for querying info about all groups set by``setxkbmap``:+ ``groups_count`` \u2014 get number of all groups.+ ``groups_names`` \u2014 get names of all groups.+ ``groups_symbols`` \u2014 get symbols of all groups.+ ``groups_variants`` \u2014 get variants of all groups.+ ``groups_data`` \u2014 get all data about all groupsby assembling all previous ``groups_*`` values.- ``format()`` \u2014 obtain a formatted output, see ``_for details.* ``X11Error`` \u2014 an exception class, raised for errors on X server issues.Helper files------------There are also complementary files:* ``generate_bindings.sh`` \u2014 a shell script which generates Python bindingsto X server structures, functions and ``#define`` definitions by:- converting X11 C headers using ``h2xml`` and ``xml2py``;- creating ``ctypes`` references to functions from ``libX11.so.6`` using``xml2py``.* ``xkbgroup/xkb.py`` \u2014 the output of the above script, usable for Xlibdevelopment under Python."} +{"package": "xkb-indicator", "pacakge-description": "https://raw.githubusercontent.com/abo-abo/xkb-indicator/master/README.org"} +{"package": "xkbregistry", "pacakge-description": "Python bindings forlibxkbregistryusingcffi.libxkbregistryis part oflibxkbcommonbut is commonly packaged\nseparately in distributions.Example usage:>>> from xkbregistry import rxkb\n>>> ctx = rxkb.Context()\n>>> ctx.models[\"pc101\"].description\n'Generic 101-key PC'\n>>> ctx.layouts[\"us\"]\nrxkb.Layout('us')\n>>> ctx.layouts[\"us\"].description\n'English (US)'\n>>> ctx.layouts[\"us(intl)\"].description\n'English (US, intl., with dead keys)'\n>>> ctx.option_groups[0].description\n'Switching to another layout'Version numberingFrom release 1.0 onwards, the version numbering of this package will\nrelate to releases oflibxkbcommonas follows:If the Python package version is major.minor[.patch] then it requires\nat least release major.minor.0 of libxkbcommon and/or libxkbregistry\nto build and run, and should work with any subsequent release. The\npatch version of the Python package is unrelated to the patch version\nof libxkbcommon."} +{"package": "xkcc537", "pacakge-description": "No description available on PyPI."} +{"package": "xkcc537211", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd", "pacakge-description": "A Python interface to xkcd.comBy Ben Rosser, released under MIT License (see LICENSE for full text).This is a Python library for accessing and retrieving links to comics\nfrom the xkcd webcomic by Randall Munroe. It is NOT endorsed or made by\nhim, it\u2019s an entirely independent project.It makes use of the JSON interface to Randall\u2019s site to retrieve comic\ndata. Both Python 2 and Python 3 are supported, and there are no\ndependencies beyond the Python standard library, so xkcd\u2019s footprint\nshould be very light.There is support for accessing specific comics, the latest comic, or a\nrandom comic. Comic metadata can be queried and the comics themselves\ncan be downloaded onto your local system. The goal is simply to provide\na relatively Pythonic wrapper around the xkcd API for any Python program\nor library that wants to access information about xkcd comics, for one\nreason or another.The xkcd module, as of version 2.4.0, also supports getting information\non What If articles from whatif.xkcd.com. This information is generated\nby scraping the What If archive page with a HTML parser.Full API documentation is availablehere.Changelog:Version 2.4.2:Switched to using HTTPS URLs for all xkcd queries.Version 2.4.1:Routines that take comic/article numbers (e.g. xkcd.getComic()) now\nalso can take strings containing cardinal numbers.Version 2.4.0:Added preliminary What If support; routines for querying basic data\nabout What If articles now exist.Comic.download() will create its default directory (~/Downloads) if\nit does not already exist, rather than simply failing.All prints to standard output are now wrapped in \u201csilent\u201d options\nthat now default to True (this affects xkcd.getComic and\nComic.download); if silent is set, output won\u2019t be printed.Significantly improved documentation for all available functions and\nclasses.Version 2.3.3:Made pypandoc conversion optional; long_description will be MD\nformatted if it cannot be imported (and rST-formatted if it can).Version 2.3.2:Fixed distutils URL to point at TC01/python-xkcd, not TC01/xkcd.Started using pypandoc to dynamically turn README.md into a RST\nlong-description.Version 2.3:Fixed ASCII bug in Python 2.xCreated Sphinx documentation and uploaded it to pythonhosted.orgVersion 2.2:Fixed very silly bug with xkcd.getComic()Added a getExplanation() which returns an explainxkcd link for a\nComic().Added support for Python 3!Version 2.1:Fixed bugs with Comic.download() functionAdded optional parameter to Comic.download() to change name of output\nfileAdded more information to long_description textCredits:Ben Rosserrosser.bjr@gmail.com: DeveloperContributions from (github users, unless indicated otherwise):@KyuTanya Sandoval (@tsando)"} +{"package": "xkcd1172", "pacakge-description": "xkcd1172Rapidly increases CPU temperature when holding down the spacebar.https://xkcd.com/1172Installation$pip3installxkcd1172RequirementsXorg (Wayland works if you are focused on an Xwayland window)SpacebarCPUBuilding$gitclonehttps://git.dawidpotocki.com/dawid/xkcd1172\n$cdxkcd1172\n\n$python3-mbuild\n$pip3installdist/xkcd1172--py3-none-any.whlRunning standalone$xkcd1172Autostart$xkcd1172-a# Add to XDG autostart$xkcd1172-r# Remove from XDG autostartRunning as a libraryimportxkcd1172xkcd1172.start_daemon_thread()"} +{"package": "xkcd2347", "pacakge-description": "xkcd2347xkcd2347 is a small utility that uses theDependencyGraphManifestConnectionresource in the GitHub GraphQL API to walk the software dependencies in\nprojects. The utility got its strange name from this XKCD comic:Installpip install xkcd2347Use$ xkcd2347 --depth 2 edsu/xkcd2347\ndiskcache: https://github.com/wikifactory/dircache\npyyaml: https://github.com/yaml/pyyaml\nrequests: https://github.com/psf/requests\n alabaster: https://github.com/bitprophet/alabaster\n codecov: https://github.com/webknjaz/codecov-python\n detox: https://github.com/tox-dev/detox\n flake8: https://github.com/PyCQA/flake8\n httpbin: https://github.com/postmanlabs/httpbin\n more-itertools: https://github.com/more-itertools/more-itertools\n pysocks: https://github.com/Anorov/PySocks\n pytest: https://github.com/pytest-dev/pytest\n pytest-cov: https://github.com/pytest-dev/pytest-cov\n pytest-httpbin: https://github.com/kevin1024/pytest-httpbin\n pytest-mock: https://github.com/pytest-dev/pytest-mock\n pytest-xdist: https://github.com/pytest-dev/pytest-xdist\n readme-renderer: https://github.com/pypa/readme_renderer\n sphinx: https://github.com/sphinx-doc/sphinx\n tox: https://github.com/tox-dev/tox\n apipkg: https://github.com/pytest-dev/apipkg\n appdirs: https://github.com/ActiveState/appdirs\n atomicwrites: https://github.com/untitaker/python-atomicwrites\n attrs: https://github.com/python-attrs/attrs\n babel: https://github.com/python-babel/babel\n bleach: https://github.com/mozilla/bleach\n blinker: https://github.com/jek/blinker\n brotlipy: https://github.com/python-hyper/brotlipy\n certifi: https://github.com/certifi/python-certifi\n cffi: https://github.com/chevah/python-cffi\n chardet: https://github.com/chardet/chardet\n click: https://github.com/pallets/click\n configparser: https://github.com/mdsitton/configparser-3.2.0r3\n contextlib2: https://github.com/jazzband/contextlib2\n coverage: https://github.com/nedbat/coveragepy\n decorator: https://github.com/micheles/decorator\n distlib: \n dnspython: https://github.com/rthalley/dnspython\n entrypoints: \n enum34: https://github.com/certik/enum34\n eventlet: https://github.com/eventlet/eventlet\n execnet: https://github.com/pytest-dev/execnet\n filelock: https://github.com/benediktschmitt/py-filelock\n flask: https://github.com/pallets/flask\n funcsigs: https://github.com/aliles/funcsigs\n functools32: https://github.com/michilu/python-functools32\n greenlet: https://github.com/python-greenlet/greenlet\n idna: https://github.com/kjd/idna\n imagesize: https://github.com/shibukawa/imagesize_py\n importlib-metadata: \n importlib-resources: \n itsdangerous: https://github.com/pallets/itsdangerous\n jinja2: https://github.com/pallets/jinja\n markupsafe: https://github.com/pallets/markupsafe\n mccabe: https://github.com/PyCQA/mccabe\n mock: https://github.com/calvinchengx/python-mock\n monotonic: https://github.com/atdt/monotonic\n pathlib2: https://github.com/mcmtroffaes/pathlib2\n pluggy: https://github.com/pytest-dev/pluggy\n py: https://github.com/pytest-dev/py\n pycodestyle: https://github.com/PyCQA/pycodestyle\n pycparser: https://github.com/eliben/pycparser\n pyflakes: https://github.com/PyCQA/pyflakes\n pygments: https://github.com/pygments/pygments\n pytest-forked: https://github.com/pytest-dev/pytest-forked\n pytz: https://github.com/stub42/pytz\n raven: https://github.com/getsentry/raven-python\n scandir: https://github.com/benhoyt/scandir\n singledispatch: https://github.com/ambv/singledispatch\n six: https://github.com/benjaminp/six\n snowballstemmer: https://github.com/snowballstem/snowball\n toml: https://github.com/uiri/toml\n typing: https://github.com/python/typing\n urllib3: https://github.com/urllib3/urllib3\n virtualenv: https://github.com/cheshire/virtualenv\n webencodings: https://github.com/gsnedders/python-webencodings\n werkzeug: https://github.com/pallets/werkzeug\n zipp: https://github.com/jaraco/zippxkcd2347 will cache results in~/.xkcd2347/cachebut you can ignore the cache to get more recent results by using the--flushcommand line option.If you give set--level 0then xkcd2347 will try to find all the dependencies\nas far down as they go. It does take care to not get caught in circular\ndependencies.Use as a Libraryimportxkcd2347gh=xkcd2347.GitHub(key=\"yourkeyhere\")fordepingh.get_dependencies('docnow','twarc'):print(dep['packageName'])DevelopPut your GitHub token in a .env file:GITHUB_TOKEN=YOUR_TOKEN_HEREAnd then run the tests!python setup.py test"} +{"package": "xkcd936", "pacakge-description": "xkcd936Convert cumbersome strings into memorable phrases.Installationpip install xkcd936Usagefrom xkcd936 import visualize\nmemorable_str = visualize('k2dhE4hd@!Y')AboutThis generator performs an MD5 hash of the input. The resulting bits are used\nto choose a grammatical template:article adj adj animaladj article adj animalThe dictionary can be upgraded to include patterns like:verb article adj nounarticle adj adj nounarticle adv adj nounadv verb article nounand a word for each slot.The total space is around 43 bits. This may not sound like much, but it\ndoesn't matter.Software doesn't just run on the computer -- it also runs in each of your\nusers' heads. For many problems with user-facing software, \"adding more bits\"\nis the wrong solution. The right solution often involves tapping into the\nuser's natural cognitive and social capabilities.LicenseReleased under MIT license."} +{"package": "xkcd-bot", "pacakge-description": "xkcd-botmasterdevelopA telegram bot that sends out new XKCD comics for subscribed users.Further InformationChangelogLicense (GPLv3)GitlabGithubProgstatsPyPi"} +{"package": "xkcd-cli", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd-cli-viewer", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd-comicdb", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd-comics", "pacakge-description": "xkcdThis is a script for downloading all the xkcd comicsHow to use the scriptclone the repo$gitclonehttps://xkcd.com/brayo-pip/xkcd.gitRun this code to install all the dependencies$cdxkcd$pip3install-rrequirements.txtThen run the script.$pythonxkcd/download.pyHow this script is better than most of the other scriptsI can't say for sure that this is the best script for downloading xkcd comics there is,\nbut I can say it's one of the fastest. The script uses persistent http connections which I haven't yet seen in another xkcd script.\nThe script skips previously downloaded comics and skips non-image comics such as js-scripts, it however highlights you of this and provides you with a link should you wish to visit the site yourself and see the 'interactive comic'.Other technical featuresThe script maintains a continuity file so that it can 'recall' the last comic it downloaded.\nIt does updates the continuity file every 10 comics, I didn't want to update too often as this could be a bottleneck.\nThe continuity file is also updated during this 'sleep' session.The script also has an amateur network congestion control, simply sleeps for 0.5 seconds for every 10 comics downloaded.This may be necessary once I introduce multi-threading.Upcoming featuresI wish to introduce multi-threading so as to be able to fully utilize the a user's bandwidth. Requesting multiple comics simultaneously and writing them to disk/SSD simultaneously."} +{"package": "xkcd-dl", "pacakge-description": ".. figure:: https://raw.githubusercontent.com/prodicus/xkcd-dl/master/assets/logo.png:alt: logo|PyPI version| |License|Download each and every `xkcd `__ comic uploaded! Like ever!:Author: Tasdik RahmanIf you have found my little bits of software of any use to you, you can help me pay my internet bills :)|Paypal badge| |Instamojo|Some of my projects are also on `Gratipay `__.. contents:::backlinks: none.. sectnum::Features=========- Can download all the xkcd's uploaded till date(1603 as I am writingthis!).- Download individual xkcd's and store them- Download ranges of xkcd's and store them- Download the latest issue xkcd- Download the meta text inside each xkcd and store it- No duplicacy in your XKCD database.- Stores each xkcd in a separate file named as the ``title`` of thexkcd at your home directory- Writes a ``description.txt`` for each xkcd. Storing meta-data like- ``date-publised``- url value- a small description of that xkcd- The alt text on the comic- written in uncomplicated ``python``.Demo====.. figure:: https://raw.githubusercontent.com/prodicus/xkcd-dl/master/assets/usage.gif:alt: UsageUsageEach Comic is stored in it's own individual folder with a``description.txt`` placed in it. It contains meta-data like -``img-link`` - ``title`` - ``date-published`` - ``alt``Here's a little example for the same.. figure:: https://raw.githubusercontent.com/prodicus/xkcd-dl/master/assets/directory_struc.jpg:alt: xkcd\\_archive Structurexkcd\\_archive StructureUsage=====When running for the first time, do a ``xkcd-dl --update-db``.. code:: bash$ xkcd-dl --update-dbXKCD link database updatedStored it in 'xkcd_dict.json'. You can start downloading your XKCD's!Run 'xkcd-dl --help' for more options$``--help``----------.. code:: bash$ xkcd-dl --helpusage: xkcd-dl [-h] [-u] [-l] [-d XKCD_NUM | -a][-r [DOWNLOAD_RANGE [DOWNLOAD_RANGE ...]]] [-v] [-P PATH][-s XKCD_NUM]Run `xkcd-dl --update-db` if running for the first time.optional arguments:-h, --help show this help message and exit-u, --update-db Update the database-l, --download-latestDownload most recent comic-d XKCD_NUM, --download XKCD_NUMDownload specified comic by number-a, --download-all Download all comics-r [DOWNLOAD_RANGE [DOWNLOAD_RANGE ...]], --download-range [DOWNLOAD_RANGE [DOWNLOAD_RANGE ...]]Download specified range-v, --version show program's version number and exit-P PATH, --path PATH set path-s XKCD_NUM, --show XKCD_NUMShow specified comic by number``--download-latest``---------------------This downloads the last uploaded xkcd comic and stores under the homedirectory of the user with a brief description.. code:: bash$ xkcd-dl --download-latestDownloading xkcd from 'http://imgs.xkcd.com/comics/flashlights.png' and storing it under '/home/tasdik/xkcd_archive/1603'$If it has been downloaded, will not do anythingThis command will work even if you have not run --update-db yet.``--download=XKCDNUMBER``-------------------------Downloads the particular ``XKCDNUMBER``\\ (given that it exists and hasnot been downloaded already) and stores it in the home directory.. code:: bash$ xkcd-dl --download=143Downloading xkcd from 'http://xkcd.com/143/' and storing it under '/home/tasdik/xkcd_archive/143'$ xkcd-dl --download=1603Downloading xkcd from 'http://xkcd.com/1603/' and storing it under '/home/tasdik/xkcd_archive/1603'xkcd number '1603' has already been downloaded!$``--download-range ``--------------------Will take two number parameters and download all the xkcd's betweenthe two, inclusive... code:: bash$ xkcd-dl --download-range 32 36Downloading xkcd from 'http://xkcd.com/32/' and storing it under '/home/tasdik/xkcd_archive/32'Downloading xkcd from 'http://xkcd.com/33/' and storing it under '/home/tasdik/xkcd_archive/33'Downloading xkcd from 'http://xkcd.com/34/' and storing it under '/home/tasdik/xkcd_archive/34'Downloading xkcd from 'http://xkcd.com/35/' and storing it under '/home/tasdik/xkcd_archive/35'Downloading xkcd from 'http://xkcd.com/36/' and storing it under '/home/tasdik/xkcd_archive/36'``--download-all``------------------As the name suggests, will download all the xkcd's uploaded till dateand store them under the home directory of the user... code:: bash$ xkcd-dl --download-allDownloading all xkcd's Till date!!Downloading xkcd from 'http://xkcd.com/1466' and storing it under '/home/tasdik/xkcd_archive/1466'Downloading xkcd from 'http://xkcd.com/381' and storing it under '/home/tasdik/xkcd_archive/381'Downloading xkcd from 'http://xkcd.com/198' and storing it under '/home/tasdik/xkcd_archive/198'Downloading xkcd from 'http://xkcd.com/512' and storing it under '/home/tasdik/xkcd_archive/512'Downloading xkcd from 'http://xkcd.com/842' and storing it under '/home/tasdik/xkcd_archive/842'Downloading xkcd from 'http://xkcd.com/920' and storing it under '/home/tasdik/xkcd_archive/920'........``--path=PATH``---------------To use a custom directory to store your xkcd_archive, you can append--path=./any/path/here to the end of any download method. Absolute and relativepaths work, but the directory must already exist... code:: bash$ xkcd-dl --download=3 --path=comicDownloading xkcd from 'http://xkcd.com/3/' and storing it under '/home/tasdik/comic/xkcd_archive/3'$ xkcd-dl --download-range 54 56 --path=/home/tasdik/xkcdDownloading xkcd from 'http://xkcd.com/54/' and storing it under '/home/tasdik/xkcd/xkcd_archive/54'Downloading xkcd from 'http://xkcd.com/55/' and storing it under '/home/tasdik/xkcd/xkcd_archive/55'Downloading xkcd from 'http://xkcd.com/56/' and storing it under '/home/tasdik/xkcd/xkcd_archive/56'``--show XKCD_NUM``-------------------Opens the specified comic. Downloads it, if not downloaded already. Prints the alt text and metadata to stdout... code:: bash$ xkcd-dl --show 32Downloading xkcd from 'http://xkcd.com/32/' and storing it under '/home/bk/Documents/xkcd-dl/xkcd_dl/xkcd_archive/32'title : Pillardate-publised: 2006-1-1url: http://xkcd.com/32/alt: A comic by my brother Doug, redrawn and rewritten by me$ xkcd-dl -s 1000Downloading xkcd from 'http://xkcd.com/1000/' and storing it under '/home/bk/Documents/xkcd-dl/xkcd_dl/xkcd_archive/1000'xkcd number '1000' has already been downloaded!title : 1000 Comicsdate-publised: 2012-1-6url: http://xkcd.com/1000/alt: Thank you for making me feel less alone.Installation============Option 1: installing through `pip `__ (Suggested way)-------------------------------------------------------------------------------------------`pypi package link `__``$ pip3 install xkcd-dl``If you are behind a proxy``$ pip3 --proxy [username:password@]domain_name:port install xkcd-dl``**Note:** If you get ``command not found`` then``$ sudo apt-get install python3-pip`` should fix thatOption 2: installing from source--------------------------------.. code:: bash$ git clone https://github.com/prodicus/xkcd-dl.git$ cd xkcd-dl/$ pip3 install -r requirements.txt$ python3 setup.py installUpgrading---------.. code:: bash$ pip3 install -U xkcd-dlUninstalling------------``$ pip3 uninstall xkcd-dl``For ``Arch`` distributions--------------------------Here is the ``AUR`` link for you- `Arch package `__Contributing============**I hacked this up in one night, so its a little messy up there.** Feel free to contribute.1. Fork it.2. Create your feature branch(``git checkout -b my-new-awesome-feature``)3. Commit your changes (``git commit -am 'Added feature'``)4. Push to the branch (``git push origin my-new-awesome-feature``)5. Create new Pull RequestContributors------------Big shout out to- `Ian C `__ for fixing issue `#2 `__ which stopped the download if a title of a comic had a special character in it and `BlitzKraft `__ for pointing it out.- `BlitzKraft `__ for adding the feature to download the `alt-text` from the the xkcd **and** major clean ups!- `Braden Best `__ for pointing out the issues when installing from source apart from his valuable input.To-do------ [x] add ``xkcd-dl --download-latest``- [x] add ``xkcd-dl --download=XKCDNUMBER``- [x] add ``xkcd-dl --download-all``- [x] add ``xkcd-dl download-range ``- [x] add path setting with ``[--path=/path/to/directory]`` option- [x] add exclude list to easily recognize and ignore dynamic comicsi.e. comics without a default image.- [x] Remove redundant code in ``download_xkcd_number()``,``download_latest()`` and ``download_all()`` (**Refactoring!!**)- [x] Adding support to open a particular xkcd at the CLI itself.Implemented using `xdg-open`. Opens using your default image viewer.Known Issues------------- There have been issues when installed from source if you are using``python 2.*`` as discussed in`#5 `__.So using ``python3.*`` is suggested.- If you get ``command not found`` when installing, it may mean thatyou don't have ``pip3`` installed.``$ sudo apt-get install python3-pip`` should fix that. To check yourversion of pip- Dynamic comics have to be added manually using the excludeList.. code:: bash$ pip3 --versionpip 1.5.6 from /usr/lib/python3/dist-packages (python 3.4)$Bugs----Please report the bugs at the `issuetracker `__**OR**You can tweet me at `@tasdikrahman `__ if you can't get it to work. In fact, you should tweet me anyway.Changelog=========- ``0.1.2``:bug: fixed relative import error in setup.pyadded support for gif files when renaming downloaded image (#38)Motivation==========``xkcd-dl`` is inspired by an awesome package called `youtube-dl `__ written by `Daniel Bolton `__ (Much respect!)How about you get to download all of the xkcd which have been uploadedtill date? This does just that!Now I don't know about you, but I just love reading ``xkcd``'s! Had a boring Sunday night looming over, thought why not create something like ``youtube-dl`` but for downloading ``xkcd``'s!And hence `xkcd-dl `__Cheers to a crazy night!Legal stuff===========Built with \u2665 by `Tasdik Rahman `__ `(@tasdikrahman) `__ and `others `__ released under `MIT License `__You can find a copy of the License at http://prodicus.mit-license.org/.. |PyPI version| image:: https://badge.fury.io/py/xkcd-dl.svg:target: https://badge.fury.io/py/xkcd-dl.. |License| image:: https://img.shields.io/pypi/l/xkcd-dl.svg:target: https://img.shields.io/pypi/l/xkcd-dl.svg.. |Paypal badge| image:: https://tuxtricks.files.wordpress.com/2016/12/donate.png:target: https://www.paypal.me/tasdikrahman.. |Instamojo| image:: https://www.instamojo.com/blog/wp-content/uploads/2017/01/instamojo-91.png:target: https://www.instamojo.com/@tasdikrahman"} +{"package": "xkcd-get", "pacakge-description": "No description available on PyPI."} +{"package": "xkcdhermit", "pacakge-description": "No description available on PyPI."} +{"package": "xkcdpass", "pacakge-description": "xkcdpassA flexible and scriptable password generator which generates strong passphrases, inspired byXKCD 936:$ xkcdpass\n> correct horse battery stapleInstallxkcdpasscan be easily installed using pip:pip install xkcdpassor manually:python setup.py installSourceThe latest development version can be found on github:https://github.com/redacted/XKCD-password-generatorContributions welcome and gratefully appreciated!RequirementsPython 2 (version 2.7 or later), or Python 3 (version 3.4 or later). Running module unit tests on Python 2 requiresmockto be installed.Runningxkcdpassxkcdpasscan be called with no arguments:$ xkcdpass\n> pinball previous deprive militancy bereaved numericwhich returns a single password, using the default dictionary and default settings. Or you can mix whatever arguments you want:$ xkcdpass --count=5 --acrostic='chaos' --delimiter='|' --min=5 --max=6 --valid-chars='[a-z]'\n> collar|highly|asset|ovoid|sultan\n> caper|hangup|addle|oboist|scroll\n> couple|honcho|abbot|obtain|simple\n> cutler|hotly|aortae|outset|stool\n> cradle|helot|axial|ordure|shalewhich returns--count=55 passwords to choose from--acrostic='chaos'the first letters of which spell \u2018chaos\u2019--delimiter='|'joined using \u2018|\u2019--min=5--max=6with words between 5 and 6 characters long--valid-chars='[a-z]'using only lower-case letters (via regex).A concise overview of the availablexkcdpassoptions can be accessed via:xkcdpass --help\n\nUsage: xkcdpass [options]\n\nOptions:\n -h, --help\n show this help message and exit\n -w WORDFILE, --wordfile=WORDFILE\n Specify that the file WORDFILE contains the list of\n valid words from which to generate passphrases. Multiple\n wordfiles can be provided, separated by commas.\n Provided wordfiles: eff-long (default), eff-short,\n eff-special, legacy, spa-mich (Spanish), fin-kotus (Finnish)\n ita-wiki (Italian), ger-anlx (German), nor-nb (Norwegian),\n fr-freelang (French), pt-ipublicis / pt-l33t-ipublicis (Portuguese)\n swe-short (Swedish)\n --min=MIN_LENGTH\n Minimum length of words to make password\n --max=MAX_LENGTH\n Maximum length of words to make password\n -n NUMWORDS, --numwords=NUMWORDS\n Number of words to make password\n -i, --interactive\n Interactively select a password\n -v VALID_CHARS, --valid-chars=VALID_CHARS\n Valid chars, using regexp style (e.g. '[a-z]')\n -V, --verbose\n Report various metrics for given options, including word list entropy\n -a ACROSTIC, --acrostic=ACROSTIC\n Acrostic to constrain word choices\n -c COUNT, --count=COUNT\n number of passwords to generate\n -d DELIM, --delimiter=DELIM\n separator character between words\n -R, --random-delimiters\n use randomised delimiters\n -D DELIMITERS, --valid-delimiters=DELIMETERS\n delimeters to choose from, used with -\n -s SEP, --separator SEP\n Separate generated passphrases with SEP.\n -C CASE, --case CASE\n Choose the method for setting the case of each word in\n the passphrase. Choices: ['alternating', 'upper',\n 'lower', 'random', 'capitalize', 'as-is'] (default: 'lower').\n --allow-weak-rng\n Allow fallback to weak RNG if the system does not\n support cryptographically secure RNG. Only use this if\n you know what you are doing.Word listsSeveral word lists are provided with the package. The default,eff-long, was specifically designed by the EFF forpassphrase generationand is licensed underCC BY 3.0. As it was originally intended for use with Diceware ensure that the number of words in your passphrase is at least six when using it. Two shorter variants of that list,eff-shortandeff-special, are also included. Please refer to the EFF documentation linked above for more information.The original word list fromxkcdpassversions earlier than 1.10.0 is also provided as a convenience, and is available underlegacy. This word list is derived mechanically from12Dictsby Alan Beale. It is the understanding of the author ofxkcdpassthat purely mechanical transformation does not imbue copyright in the resulting work. The documentation for the 12Dicts project athttp://wordlist.aspell.net/12dicts/contains the following dedication:The 12dicts lists were compiled by Alan Beale. I explicitly release them to the public domain, but request acknowledgment of their use.Note that the generator can be used with any word file of the correct format: a file containing one \u2018word\u2019 per line.Additional languagesSpanish: a modifed version of archive.umich.edu in the/linguisticsdirectory. It includes ~80k words. Less than 5 char. and latin-like words were deleted using regex. This list is public domain, seehere.Finnish: a modified version of the Institute for the Languages of FinlandXML word list. Profanities and expressions containing spaces were removed using regex. The resulting list contains ~93k words. The list is published under GNU LGPL, EUPL 1.1 and CC-BY 3.0 licenses.Italian: generated from dumps of the Italian-language Wikipedia, which is released under the Creative Commons Attribution-Share-Alike 3.0 licence.German (ger-anlx): based onthis GPL v3 list. Single and double character words have been removed.German (eff_large_de_sample.wordlist): based onthis public domain dictionary. Converted to UTF-8 and randomly sampled to reduce file size.Norwegian: a modified version ofNorsk Ordbank in Norwegian Bokm\u00e5l 2005, 2018-06-28 update, which is released under theCC-BY 4.0 license. Regex has been used to alter the list for cleanup and removal of words with impractical characters. The resulting list contains ~137k words.French: One cleaned version ofthis list(public domain), and one filtered to remove potentially offensive words.Portuguese: Converted variant of the LibreOffice / Firefox Portuguese dictionary (fromthis link. GPL and BSD licenced.Swedish: a modified version ofMartin Lindhe\u2019s Swedish word list(MIT license). Modifications also released under MIT license.Additional language word lists are always welcome!Using xkcdpass as an imported moduleThe built-in functionality ofxkcdpasscan be extended by importing the module into python scripts. An example of this usage is provided inexample_import.py, which randomly capitalises the letters in a generated password.example_json.pydemonstrates integration of xkcdpass into a Django project, generating password suggestions as JSON to be consumed by a Javascript front-end.A simple use of import:from xkcdpass import xkcd_password as xp\n\n# create a wordlist from the default wordfile\n# use words between 5 and 8 letters long\nwordfile = xp.locate_wordfile()\nmywords = xp.generate_wordlist(wordfile=wordfile, min_length=5, max_length=8)\n\n# create a password with the acrostic \"face\"\nprint(xp.generate_xkcdpassword(mywords, acrostic=\"face\"))When used as an imported module,generate_wordlist()takes the following args (defaults shown):wordfile=None,\nmin_length=5,\nmax_length=9,\nvalid_chars='.'Whilegenerate_xkcdpassword()takes:wordlist,\nnumwords=6,\ninteractive=False,\nacrostic=False,\ndelimiter=\" \"Insecure random number generatorsxkcdpassuses crytographically strong random number generators where possible (provided byrandom.SystemRandom()on most modern operating systems). From version 1.7.0 falling back to an insecure RNG must be explicitly enabled, either by using a new command line variable before running the script:xkcdpass --allow-weak-rngor setting the appropriate environment variable:export XKCDPASS_ALLOW_WEAKRNG=1Changelog1.19.8Enablespython -m xkcdpassusage1.19.7Adds Swedish wordlist, improvements to test suite, improvements to setup.py (excludes examples from install)1.19.6Fixes randomly failing unit test1.19.5Adds \u201cas-is\u201d option for case1.19.4Makes randomised delimiters behavior consistent with fixed delimeters1.19.3Restore a randomly sampled version of eff_large_de wordlist1.19.2Reduction in install size1.19.1Improvements to help text, handle rare case where arguments lead to empty wordlist1.19.0Initial support for multiple wordfiles1.18.2fixes for README1.18.0Added randomised delimiters1.17.6Bugfixes1.17.5Bugfixes1.17.4Improvements to French dictionary1.17.3Updated license and supported versions1.17.2Compatibility fix for 2.x/3.x1.17.1Fix issue with README and unicode encoding1.17.0Add French, Norwegian, and Portuguese dictionaries. Bugfixes and improvements to tests (WIP).1.16.5Adds title case option for\u2013caseLicenseThis is free software: you may copy, modify, and/or distribute this work under the terms of the BSD 3-Clause license.\nSee the fileLICENSE.BSDfor details."} +{"package": "xkcd-pass", "pacakge-description": "xkcd-passA flexible and scriptable password generator which generates strong passphrases, inspired byXKCD 936.$ xkcd-pass\n> DenotePetroleumMournfulStoreroom47Whilst this password generator is inspired byXKCD 936, its defaults have been configured in a way which gives this tool the most compatibility out of the box with the majority of services we use passwords for today. The defaults that we have set are:Phrase containing 4 words between 5 and 9 characters (The default wordfileeff-longonly contains words between 5 and 9 characters).The first letter of each word is capitalized.The passphrase is ended with two random digits.This allows the password generator to provide passwords by default which will be strong, easy to remember, difficult to brute-force and still pass the usual requirements of at least one upper-case letter, one lower-case letter and at least 1 digit.Some of the base code that I started with for this project come fromredacted/xkcd-password-generator. Whilst that package was great, the reason for taking this project separately and adapting it is for the below reasons:To neaten up the codebase to make it easier for other contributors to help develop it further.To provide the project with an active maintainer meaning bugs and potential new features can be released more promptly.To neaten up the output so it is much easier to use with our scripts and programs.To provide it with more compatibility for more services by adding the random digit generator to the end of the password.To have a thoroughly tested codebase giving users the ability to trust that the package will work as expected.SupportFor support using this bot, please join ourofficial support serveronDiscord.Installxkcd-passcan easily be installed with the following command:pip install xkcd-passor manually by:python setup.py installSourceThe source code can be foundhere.Contributions welcome and gratefully appreciated!RequirementsPython 3 (Version 3.6 or later).Runningxkcd_passxkcd-passcan be called with no arguments with an output using the default wordfile and settings.$ xkcd-pass\n> HeadscarfSuddenDumping93The default settings return a single password made up of 4 words each having its first letter capitalized with two random digits afterwards.It can also be called with a mixture of multiple arguments for example:$ xkcd-pass -d _ -c 5 --min 5 --max 7 --padding-digits-num 4\n> Crisped_Harsh_Relearn_Chemist9839\n> Brittle_Deacon_Banker_Amigo4544\n> Ambush_Emptier_Antsy_Walrus2442\n> Donated_Either_Stardom_Duress8549\n> Ether_Prevail_Virtual_Tiger3393This will return:-d _words joined by_.-c 55 passwords to choose from.--min 5 --max 7words between 5 and 7 characters long.--padding-digits-num 44 digits on the end of the password.A full overview of the available options can be accessed by running following command:xkcd-pass --helpBash-Completionxkcd-passalso supports bash-completion. To set this up you need to add the below to your.bashrcfile:eval \"$(register-python-argcomplete xkcd-pass)\"This will then take effect the next time you login. To enable bash-completion immediately, you can run:source .bashrcWord ListsSeveral word lists are provided with the package. The default, eff-long, was specifically designed by the EFF forpassphrase generationand is licensed underCC BY 3.0. As it was originally intended for use with Diceware ensure that the number of words in your passphrase is at least six when using it. Two shorter variants of that list, eff-short and eff-special, are also included. Please refer to the EFF documentation linked above for more information.Note thatxkcd-passcan be used with any word file of the correct format: a file containing one word per line.ChangelogVersion 1.0.0Initial ReleaseVersion 1.0.1Fixed license display on PyPI.Fixed links to license files on PyPI.Version 1.0.2Fix interactive usage.Fix issue where wrong wordfile wasn't being recognized.Add 100% test coverage.Version 1.0.5Fix typo in static import causing wordfile error.Version 1.0.6Change package name toxkcd_pass.Version 1.0.7Change command-line package toxkcd-pass.Version 1.0.9Fix issues with README.md badges after rename.Update--helpforMIN_LENGTHandMAX_LENGTH.Update number of words in password to 4 by default.Restructured tests into individual files to neaten up codebase.Added static type annotations to the codebase.Added support forzulintto run various code linters easily.Version 1.1.0Add support for bash-completion forxkcd-pass.Update github links to correct names in PyPi metadata.Add tool to prep dev environment.Add documentation for contributing and development.Add support for correct entropy for padded digits.Version 1.1.1Add docs for official discord support server.Update link to source code in docs to correct typo.Fix an issue in contributing logs to add an extra step needed.Fixed issue with codecov badge in docs.Update example docs to use correct defaults.Fixed issue with prep-dev-environment script.Version 1.1.2Fix dependency issues.Add more PyPi classifiers.Make CI run tests on multiple Python versions.Version 1.1.3Rename the GitHub repository toxkcd-pass-pythonfromxkcd-password-gen.LicenseThis project is released under theGNU GENERAL PUBLIC LICENSE v3. However the original code fromredacted/xkcd-password-generatoris licensed under theBSD 3-Clause license.ContributingAnybody is welcome to contribute to this project. I just ask that you check out our contributing guidelinesherefirst."} +{"package": "xkcdpassword", "pacakge-description": "xkcdpassword\n=A simple, pure Python, Xkcd-style password generator.e.g: \u201ccorrect horse battery staple\u201dWhen invoked, this package will generate a short list of unique words, perhaps to a specified number, and then return them on sys.std.out. The user can also specify to remove spaces so the output can be easily copy-pasted or piped. The word list is customizable (words.txt), and already curated for length.### PrerequisitesPython 2.7\nPyperclip### Installingsudo pip install xkcdpassword### Using$ xkcdpassword->correct horse battery staple$ xkcdpassword -ns->correcthorsebatterystaple$ xkcdpassword 3->correct horse battery$ xkcdpassword -ns 6->correcthorsebatterystaplethingexplainer$ xkcdpassword -h-> Syntax help### AuthorsDoug Walter-dougwritescode@gmail.com### LicenseThis project is licensed under the MIT License - see the [LICENSE.txt](LICENSE.txt) file for details## AcknowledgmentsRandall Patrick Munroe, the ruler of the geek pantheon."} +{"package": "xkcd-phrase", "pacakge-description": "xkcd-phraseA flexible and scriptable password generator which generates strong passphrases, inspired byXKCD 936.$ xkcd-phrase\nMove Barbed Unplug HuskinessThis password generator is inspired byXKCD 936and the version provided byAdam BirdsWith the original code fromredacted/xkcd-password-generator.. The defaults have been configured in a way to give this tool the most compatibility out of the box with passphrase requirements and the flexibility to adjust for site specific requirements. The defaults provide:A phrase containing 4 words between 4 and 9 characters (The default wordfileeff-longonly contains words between 4 and 9 characters).The first letter of each word is capitalized.A seperator for human readability.This allows the phrase generator to provide phrases by default which will be strong, easy to remember, difficult to brute-force and still pass the usual requirements of at least one upper-case letter, one lower-case letter and a special character.Installxkcd-phrasecan easily be installed with the following command:pip install xkcd-phraseor manually by:python -m pip install SourceThe source code can be foundhere.RequirementsPython 3 (Version 3.8 or later).Runningxkcd_phrasexkcd-phrasecan be called with no arguments with an output using the default wordfile and settings.$ xkcd-phrase\n> Spiffy Deceit Unease PushoverThe default settings return a single phrase made up of 4 words each having: its first letter capitalized and spaces between the words for readability.It can also be called with a mixture of multiple arguments for example:$ xkcd-phrase -d _ -c 5 --min 5 --max 7 --numeric-char-num 4 --numeric-char-append\nCause_Resale_Moody_Arise6814\nSuggest_Bundle_Cruelly_Suggest4674\nSleeve_Resort_Plastic_Drool5351\nHazily_Skimmed_Islamic_Gigolo6475\nSalvage_Sphinx_Tightly_Banter9381This will return:-d _words joined by_.-c 55 passwords to choose from.--min 5 --max 7words between 5 and 7 characters long.--numeric-char-num 4Include 4 numerical characters in the passphrase.--numeric-char-appendInclude the numerics on the end of the passphrase.$ xkcd-phrase -V -n 6 --numeric-char-num 2 --special-char-num 2\nThe total possible number of symbol choices in the phrase is\n77 possible symbols comprising:\n 52 alphabetic characters\n 10 numeric characters\n 15 special characters\n\nThe phrase length is 53 with the entropy of the phrase is calculated as:\n log2(possible_symb (77) ^ phrase_len (53)) = 332.14\n\nThe phrase is: I)licit0y Dugout Reproduce Overfed De:al Sque3zeThis will return:-Vverbose output explaining the entropy of the passphrase.-n 6Use 6 words in the phrase.--numeric-char-num 2Include 2 numerical characters in the passphrase.--special-char-num 2Include 2 special characters in the passphrase..Note the default behaviour to substitute the numeric and special characters randonly into words.As an aide memoire, you can choose an acrostic for example:$ xkcd-phrase -a queen\n> Quadrant Uncover Enforced Excretion NachoA full overview of the available options can be accessed by running following command:xkcd-phrase --helpBash-Completionxkcd-phrasealso supports bash-completion. To set this up you need to add the below to your.bashrcfile:eval \"$(register-python-argcomplete xkcd-phrase)\"This will then take effect the next time you login. To enable bash-completion immediately, you can run:source .bashrcWord ListsSeveral word lists are provided with the package. The default, eff-long, was specifically designed by the EFF forpassphrase generationand is licensed underCC BY 3.0. As it was originally intended for use with Diceware ensure that the number of words in your passphrase is at least six when using it. Two shorter variants of that list, eff-short and eff-special, are also included. Please refer to the EFF documentation linked above for more information.Note thatxkcd-phrasecan be used with any word file of the correct format: a file containing one word per line.ChangelogVersion 1.0.0Initial ReleaseLicenseThis project is released under theGNU GENERAL PUBLIC LICENSE v3. However the original code fromredacted/xkcd-password-generatoris licensed under theBSD 3-Clause license.ContributingContributions welcome and gratefully appreciated!"} +{"package": "xkcd-probability", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd.py", "pacakge-description": "RequirementsThis module requires the following modules:beautifulsoup4requestsInstallationPython 3.8 or higher is required.To install the stable version, do the following:# Unix / macOSpython3-mpipinstall\"xkcd.py\"# Windowspy-mpipinstall\"xkcd.py\"To install the development version, do the following:$gitclonehttps://github.com/Infiniticity/xkcd.pyLinksxkcdDocumentation"} +{"package": "xkcd-python", "pacakge-description": "xkcd-pythonxkcd-python is an API wrapper for xkcd.com written in python.InstallationUse the package managerpipto install xkcd-python.pipinstall-Uxkcd-pythonUsageNormal usagefromxkcd_pythonimportClient#creates the clientclient=Client()# returns the comic by idclient.get(1)# returns a random comicclient.random()# returns the latest comicclient.latest_comic()Async usagefromxkcd_pythonimportClientimportasyncioclient=Client()asyncdefmain():tasks=(client.get(x)forxinrange(1,20))returnawaitasyncio.gather(*tasks)asyncio.run(main)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT"} +{"package": "xkcdrand", "pacakge-description": "No description available on PyPI."} +{"package": "xkcdrandom", "pacakge-description": "xkcdrandomTable of ContentsAboutInstallationUsageLicenseAboutA random number generator made in accordance withhttps://xkcd.com/221/.This is really just a test project to help me understand Python packaging and distribution withHatchInstallationpip install xkcdrandomUsageimport xkcdrandom\n\nnum = xkcdrandom.get_random_number()Licensexkcdrandomis distributed under the terms of theMITlicense."} +{"package": "xkcd-scrape", "pacakge-description": "XKCD Scrapexkcd-scrapeis a Python module to dump the XKCD.com archive and get comic info using BS4. Honestly, it's a very basic module with one premise - easily get information about comics.ExamplesBasic usage:fromxkcdscrapeimportxkcd# Load the archive of comics into a variable# Allows to get the publication date by passing into getComicInfo and getRandomComicarchive=xkcd.parseArchive()# Get info about latest comicinfo=xkcd.getComicInfo(archive=archive)# w/ dateinfo=xkcd.getComicInfo()# w/o date# Get info about specific comic# The comic can either be an int (2000), a str (\"2000\"|\"/2000/\"), or a link (\"https://xkcd.com/2000\")info=xkcd.getComicInfo(2000,archive)# w/ dateinfo=xkcd.getComicInfo(2000)# w/o date# Get info about a random comic# Passing the second paramenter as True makes the module only fetch comics that are present in the archiveinfo=xkcd.getRandomComic(archive,True)# w/ dateinfo=xkcd.getRandomComic()# w/o date# Dump archive to filexkcd.dumpToFile(archive,\"dump.json\")# Get info using the archive dump.info=xkcd.getComicInfo(\"dump.json\")# latestinfo=xkcd.getComicInfo(\"dump.json\",2000)# specificinfo=xkcd.getRandomComic(\"dump.json\",True)# random# Get latest entry from the RSS feed# Currently VERY raw, just returns the first tag as a stringlastentry=xkcd.getLastRSS()ThegetComicInfofunction (also called inside ofgetRandomComic) returns a dict with following keys:# xkcd.getComicInfo(2000, archive){'date':'2018-5-30','num':'2000','link':'https://xkcd.com/2000/','name':'xkcd Phone 2000','image':'https://imgs.xkcd.com/comics/xkcd_phone_2000.png','title':'Our retina display features hundreds of pixels per inch in the central fovea region.'}As you can see, it returns the following list of keys:num- comic numberlink- hyperlink to comicname- the name of the comicdate- YYYY-MM-DD formatted date of when the comic was posted (not returned if archive is None)image- hyperlink to image used in the comictitle- title (hover) text of the comicArchiveTheXKCD archiveis where we get the list of comics, as well as their names and date of posting. This is the only place where we can get the date of posting, so it's required if you need the date.The archive is a dict containing various dicts with keys of/num/. Example:{...,\"/2000/\":{\"date\":\"2018-5-30\",\"name\":\"xkcd Phone 2000\"},...}TestsTests can be run from the project's shell after installing and activating the venv usingpoetry run pytest.\nUse Python's includedunittestmodule for creating tests (examples are intests/).TODOImprove RSS feed outputAPI and homepage (on one domain?)"} +{"package": "xkcd-wallpaper", "pacakge-description": "No description available on PyPI."} +{"package": "xkcd-wrapper", "pacakge-description": "xkcd-wrapperA Python wrapper for thexkcd webcomicAPI.Retrieves xkcd comic data and metadata as python objects.Asynchronous (async) and synchronous implementations.InstallationAt the command line, withpip,synchronous implementation:$pipinstallxkcd-wrapper[sync]async implementation:$pipinstallxkcd-wrapper[async]Usagesynchronous:>>>importxkcd_wrapper>>>client=xkcd_wrapper.Client()>>>specific_comic=client.get(100)# Comic object with comic 100 data>>>latest_comic=client.get_latest()# Comic object containing data of the latest xkcd comic>>>random_comic=client.get_random()# Comic object of a random comic>>>specific_comicxkcd_wrapper.Comic(100)>>>specific_comic.image_url'https://imgs.xkcd.com/comics/family_circus.jpg'async:>>>importxkcd_wrapper,asyncio>>>async_client=xkcd_wrapper.AsyncClient()>>>asyncdefasync_call():...responses=awaitasyncio.gather(...async_client.get(100),# Comic object with comic 100 data...async_client.get_latest(),# Comic object containing data of the latest xkcd comic...async_client.get_random()# Comic object of a random comic...)...print(...responses[0],# async_client.get(100) output...responses[0].image_url,...sep='\\n'...)>>>asyncio.run(async_call())xkcd_wrapper.Comic(100)'https://imgs.xkcd.com/comics/family_circus.jpg'DocumentationCheck the documentation for more details:https://xkcd-wrapper.readthedocs.io/en/latestHistory1.0.2 (01-11-2022)Support Python 3.10Update dependencies1.0.1 (28-02-2021)Deprecate Python 3.5Support Python 3.9Update dependencies1.0.0 (06-09-2020)Reworked xkcd API response json decodingReworkedComicClientandAsyncClientcan now retrieve comic images0.2.2 (13-08-2020)Fixed failing to importxkcd_wrapperif either onlyrequestsoraiohttpwere installed0.2.1 (11-08-2020)Separate dependencies\n(you can now use the async implementation without having to install the sync dependencies and vice versa)0.2.0 (08-08-2020)Async implementation (AsyncClient)0.1.0 (23-04-2020)First release on PyPIClientandComicclasses"} +{"package": "xkci-cli", "pacakge-description": "No description available on PyPI."} +{"package": "xkey", "pacakge-description": "xKeyxKey provides a set of Novation SysEx utilities. It was intended to allow easy encoding\nand decoding of SysEx firmware updates from Novation.Although this project was designed to support FLKey and Launchkey devices, others\nNovation firmware updates may be compatible with these utilities. However only software\nfor these devices has been tested so far.This project was generated by reverse engineering the software update process used by\nNovation FLKey MIDI keyboards. As a result of this, the exact use and terminology used\nby Novation may differ from that reflected in this project.:warning:Tampering with firmware updates may break your device!Firmware updates encoded and decoded using this utility may result in an unusable and\nunrecoverable device. This tool is provided with no warranty or guarantees.InstallationxKey can be installed directly from PyPi. xKey currently has no external runtime\ndependencies as it only utilises functions exposed by the Python standard library.pipinstallxkeyExample UsageDecode an input SysEx format firmware update into binary$ xkey decode launchkeymk3-firmware-217.syx \n2023-04-22 17:50:58,705 - [INFO] Reading SysEx from launchkeymk3-firmware-217.syx\n2023-04-22 17:50:58,712 - [INFO] SysEx file appears to be for Novation launchkey-mk3\n2023-04-22 17:50:58,712 - [INFO] SysEx file appears to contain build 000217\n2023-04-22 17:50:58,712 - [INFO] Encoded file size 96788-bytes (CRC32 0x49ca849c)\n2023-04-22 17:50:58,821 - [INFO] Writing decoded SysEx to launchkeymk3-firmware-217.syx.binEncode an input binary format firmware update into SysEx$ xkey encode launchkeymk3-firmware-217.syx.bin --model launchkey-mk3 --build 217\n2023-04-22 17:52:07,454 - [INFO] Starting encoding of SysEx for launchkey-mk3, build 000217\n2023-04-22 17:52:07,454 - [INFO] Reading binary from launchkeymk3-firmware-217.syx.bin\n2023-04-22 17:52:07,613 - [INFO] Input binary file size 96788-bytes (CRC32 0x49ca849c)\n2023-04-22 17:52:07,613 - [INFO] Writing encoded SysEx to launchkeymk3-firmware-217.syx.bin.syx"} +{"package": "xkeysnail", "pacakge-description": "xkeysnailis yet another keyboard remapping tool for X environment.\nIt\u2019s likexmodmapbut allows more flexible remappings.Has high-level and flexible remapping mechanisms, such asper-application keybindings can be definedmultiple stroke keybindings can be definedsuch asCtrl+x Ctrl+ctoCtrl+qnot only key remapping but arbitrary commands defined by\nPython can be bound to a keyRuns in low-level layer (evdevanduinput), makingremapping work in almost all the places"} +{"package": "xkiller", "pacakge-description": "py-xkillerA daemon that is intended for use in a \u201cNo X sessions\u201d challenge.Essentially, every so often, the daemon:Checks if the system time is past the time stored athttp://time.kaashif.co.uk/endIf it is, quit - the challenge is overChecks if there are any daemons with the binary name \u201cX\u201d or \u201cXorg\u201d\nand kills them.Installing$ pip3 install xkillerRunning$ xkiller(it will daemonize itself)You may want to run it as root, so it can actually kill sessions\nstarted by display managers etc.If run as root, /var/run/xkiller.pid will be the PIDfile, if not,\n/tmp/xkiller.pid is the PIDfile. Also, you can specify a PIDfile like\nso:$ xkiller /home/kaashif/mypidfile.pid"} +{"package": "xkivy", "pacakge-description": "XKivyA kivy and kivymd extension module for easy accessibility, creation of new widgets and also adding more functionality.This module containing new advanced widgets that are readily available to suit your needs.You may use this module with kivymd module for the best experience.This module was built to incorporate new widgets to kivy and kivymd ,to provide flexibility with widgets ,to add functionality and to fix some problems with kivymd.Getting StartedYou can get this module to run on your machine through installing it with pip.Using Pippython -m pip install xkivyPrerequisitesThere is only the need of kivy and kivymd for this module to be running.kivymd >= 1.2.0\nkivy >= 2.0.0InstallingInstalling is simple, through downloading the necessary files and then install or through pip.Using Pippip install xkivyDownloading and then installing\nThrough Gitgit clone https://github.com/digreatbrian/xkivy.git\ncd xkivy\npython setup.py installorgit clone https://github.com/digreatbrian/xkivy.git\ncd xkivy\npip install .Or Through tar.gz filepip install xkivy-1.0.1.tar.gzDeploymentTo use this module, you just have to do the same procedure when creating a kivy/kivymd App.Examplefrom kivy.app import App\n from xkivy.uix.button import XRectangularButton as XButton\n\n class TestApp(App):\n def build(self):\n return XButton(text='Test Button') \n\n app=TestApp() \n app.run()ContributingPlease readCONTRIBUTING.mdfor details on our code of conduct, and the process for submitting pull requests to us.AuthorsBrian Musakwa-Initial work-digreatbrianSee also the list ofcontributorswho participated in this project.WidgetsTo see the flexible widgets that xkivy has ,please followUIX-WIDGETSLicenseThis project is licensed under the MIT License - see theLICENSEfile for detailsAcknowledgmentsI hereby thank everyone who has contributed to this software."} +{"package": "xklb", "pacakge-description": "library (media toolkit)A wise philosopher once told me: \"the future isautotainment\".Manage and curate large media libraries. An index for your archive.\nPrimary usage is local filesystem but also supports some virtual constructs like\ntracking online video playlists (eg. YouTube subscriptions) and scheduling browser tabs.InstallLinux recommended butWindows setup instructionsavailable.pip install xklbShould also work on Mac OS.External dependenciesRequired:ffmpegSome features work better with:mpv,firefox,fishGetting startedLocal media1. Extract MetadataFor thirty terabytes of video the initial scan takes about four hours to complete.\nAfter that, subsequent scans of the path (or any subpaths) are much quicker--only\nnew files will be read byffprobe.library fsadd tv.db ./video/folder/2. Watch / Listen from local fileslibrary watch tv.db # the default post-action is to do nothing\nlibrary watch tv.db --post-action delete # delete file after playing\nlibrary listen finalists.db -k ask_keep # ask whether to keep file after playingTo stop playing press Ctrl+C in either the terminal or mpvOnline media1. Download MetadataDownload playlist and channel metadata. Break free of the YouTube algo~library tubeadd educational.db https://www.youtube.com/c/BranchEducation/videosAnd you can always add more later--even from different websites.library tubeadd maker.db https://vimeo.com/terburgTo prevent mistakes the default configuration is to download metadata for only\nthe most recent 20,000 videos per playlist/channel.library tubeadd maker.db --extractor-config playlistend=1000Be aware that there are some YouTube Channels which have many items--for example\nthe TEDx channel has about 180,000 videos. Some channels even have upwards of\ntwo million videos. More than you could likely watch in one sitting--maybe even one lifetime.\nOn a high-speed connection (>500 Mbps), it can take up to five hours to download\nthe metadata for 180,000 videos.TIP! If you often copy and paste many URLs you can paste line-delimited text as arguments via a subshell. For example, infishshell withcb:library tubeadd my.db (cb)Or in BASH:library tubeadd my.db $(xclip -selection c)1a. Get new videos for saved playlistsTubeupdate will go through the list of added playlists and fetch metadata for\nany videos not previously seen.library tubeupdate tube.db2. Watch / Listen from websiteslibrary watch maker.dbTo stop playing press Ctrl+C in either the terminal or mpvList all subcommands$ library\nxk media library subcommands (v2.5.007)\n\nCreate database subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 fsadd \u2502 Add local media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 tubeadd \u2502 Add online video media (yt-dlp) \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 webadd \u2502 Add open-directory media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 galleryadd \u2502 Add online gallery media (gallery-dl) \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 tabsadd \u2502 Create a tabs database; Add URLs \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 links-add \u2502 Create a link-scraping database \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 siteadd \u2502 Auto-scrape website data to SQLITE \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 redditadd \u2502 Create a reddit database; Add subreddits \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 pushshift \u2502 Convert pushshift data to reddit.db format (stdin) \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 hnadd \u2502 Create / Update a Hacker News database \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 substack \u2502 Backup substack articles \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 tildes \u2502 Backup tildes comments and topics \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 places-import \u2502 Import places of interest (POIs) \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nUpdate database subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 fsupdate \u2502 Update local media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 tubeupdate \u2502 Update online video media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 webupdate \u2502 Update open-directory media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 galleryupdate \u2502 Update online gallery media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 links-update \u2502 Update a link-scraping database \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 redditupdate \u2502 Update reddit media \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nPlayback subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 watch \u2502 Watch / Listen \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 now \u2502 Show what is currently playing \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 next \u2502 Play next file and optionally delete current file \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 stop \u2502 Stop all playback \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 pause \u2502 Pause all playback \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 open-links \u2502 Open links from link dbs \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 surf \u2502 Auto-load browser tabs in a streaming way (stdin) \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nMedia database subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 tabs \u2502 Open your tabs for the day \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 block \u2502 Block a channel \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 playlists \u2502 List stored playlists \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 download \u2502 Download media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 download-status \u2502 Show download status \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 redownload \u2502 Re-download deleted/lost media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 history \u2502 Show some playback statistics \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 search \u2502 Search captions / subtitles \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nText subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 cluster-sort \u2502 Sort text and images by similarity \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 extract-links \u2502 Extract inner links from lists of web links \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 extract-text \u2502 Extract human text from lists of web links \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 markdown-links \u2502 Extract titles from lists of web links \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nFile subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 eda \u2502 Exploratory Data Analysis on table-like files \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 mcda \u2502 Multi-criteria Ranking for Decision Support \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 incremental-diff \u2502 Diff large table-like files in chunks \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 media-check \u2502 Check video and audio files for corruption via ffmpeg \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 sample-hash \u2502 Calculate a hash based on small file segments \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 sample-compare \u2502 Compare files using sample-hash and other shortcuts \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nFolder subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 merge-folders \u2502 Merge two or more file trees \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 relmv \u2502 Move files preserving parent folder hierarchy \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 mv-list \u2502 Find specific folders to move to different disks \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 scatter \u2502 Scatter files between folders or disks \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nMulti-database subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 merge-dbs \u2502 Merge SQLITE databases \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 copy-play-counts \u2502 Copy play history \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nFilesystem Database subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 christen \u2502 Clean filenames \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 disk-usage \u2502 Show disk usage \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 mount-stats \u2502 Show some relative mount stats \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 big-dirs \u2502 Show large folders \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 search-db \u2502 Search a SQLITE database \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 optimize \u2502 Re-optimize database \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nSingle database enrichment subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 dedupe-db \u2502 Dedupe SQLITE tables \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 dedupe-media \u2502 Dedupe similar media \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 merge-online-local \u2502 Merge online and local data \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 mpv-watchlater \u2502 Import mpv watchlater files to history \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 reddit-selftext \u2502 Copy selftext links to media table \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n\nMisc subcommands:\n\u256d\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 export-text \u2502 Export HTML files from SQLite databases \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 process-audio \u2502 Shrink audio by converting to Opus format \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 dedupe-czkawka \u2502 Process czkawka diff output \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 nouns \u2502 Unstructured text -> compound nouns (stdin) \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256fExamplesWatch online media on your PCwget https://github.com/chapmanjacobd/library/raw/main/example_dbs/mealtime.tw.db\nlibrary watch mealtime.tw.db --random --duration 30mListen to online media on a chromecast groupwget https://github.com/chapmanjacobd/library/raw/main/example_dbs/music.tl.db\nlibrary listen music.tl.db -ct \"House speakers\" --randomHook into HackerNewswget https://github.com/chapmanjacobd/hn_mining/raw/main/hackernews_only_direct.tw.db\nlibrary watch hackernews_only_direct.tw.db --random --ignore-errorsOrganize via separate databaseslibrary fsadd --audio audiobooks.db ./audiobooks/\nlibrary fsadd --audio podcasts.db ./podcasts/ ./another/more/secret/podcasts_folder/\n\n# merge later if you want\nlibrary merge-dbs --pk path -t playlists,media both.db audiobooks.db podcasts.db\n\n# or split\nlibrary merge-dbs --pk path -t playlists,media audiobooks.db both.db -w 'path like \"%/audiobooks/%\"'\nlibrary merge-dbs --pk path -t playlists,media podcasts.db both.db -w 'path like \"%/podcasts%\"'GuidesMusic alarm clockvia termux crontabWake up to your own music30 7 * * * library listen ./audio.dbWake up to your own musiconly when you arenothome(computer on local IP)30 7 * * * timeout 0.4 nc -z 192.168.1.12 22 || library listen --randomWake up to your own music on your Chromecast speaker grouponly when you are home30 7 * * * ssh 192.168.1.12 library listen --cast --cast-to \"Bedroom pair\"Browser TabsVisit websites on a scheduletabsis a way to organize your visits to URLs that you want to remember every once in a while.The main benefit of tabs is that you can have a large amount of tabs saved (say 500 monthly tabs) and only the smallest\namount of tabs to satisfy that goal (500/30) tabs will open each day. 17 tabs per day seems manageable--500 all at once does not.The use-case of tabs are websites that you know are going to change: subreddits, games,\nor tools that you want to use for a few minutes daily, weekly, monthly, quarterly, or yearly.1. Add your websiteslibrary tabsadd tabs.db --frequency monthly --category fun \\\n https://old.reddit.com/r/Showerthoughts/top/?sort=top&t=month \\\n https://old.reddit.com/r/RedditDayOf/top/?sort=top&t=month2. Add library tabs to cronlibrary tabs is meant to runonce per day. Here is how you would configure it withcrontab:45 9 * * * DISPLAY=:0 library tabs /home/my/tabs.dbOr withsystemd:tee ~/.config/systemd/user/tabs.service\n[Unit]\nDescription=xklb daily browser tabs\n\n[Service]\nType=simple\nRemainAfterExit=no\nEnvironment=\"DISPLAY=:0\"\nExecStart=\"/usr/bin/fish\" \"-c\" \"lb tabs /home/xk/lb/tabs.db\"\n\ntee ~/.config/systemd/user/tabs.timer\n[Unit]\nDescription=xklb daily browser tabs timer\n\n[Timer]\nPersistent=yes\nOnCalendar=*-*-* 9:58\n\n[Install]\nWantedBy=timers.target\n\nsystemctl --user daemon-reload\nsystemctl --user enable --now tabs.serviceYou can also invoke tabs manually:library tabs tabs.db -L 1 # open one tabIncremental surfing. \ud83d\udcc8\ud83c\udfc4 totally rad!Find large foldersCurate with library big-dirsIf you are looking for candidate folders for curation (ie. you need space but don't want to buy another hard drive).\nThe big-dirs subcommand was written for that purpose:$ library big-dirs fs/d.dbYou may filter by folder depth (similar to QDirStat or WizTree)$ library big-dirs --depth=3 audio.dbThere is also an flag to prioritize folders which have many files which have been deleted (for example you delete songs you don't like--now you can see who wrote those songs and delete all their other songs...)$ library big-dirs --sort-groups-by deleted audio.dbRecently, this functionality has also been integrated into watch/listen subcommands so you could just do this:$ library watch --big-dirs ./my.db\n$ lb wt -B # shorthand equivalentBackfill dataBackfill missing YouTube videos from the Internet Archiveforbaseinhttps://youtu.be/ http://youtu.be/ http://youtube.com/watch?v=https://youtube.com/watch?v=https://m.youtube.com/watch?v=http://www.youtube.com/watch?v=https://www.youtube.com/watch?v=sqlite3 video.db\"update or ignore mediaset path = replace(path, '$base', 'https://web.archive.org/web/2oe_/http://wayback-fakeurl.archive.org/yt/'), time_deleted = 0where time_deleted > 0and (path = webpath or path not in (select webpath from media))and path like '$base%'\"endBackfill reddit databases with pushshift datahttps://github.com/chapmanjacobd/reddit_mining/forreddit_dbin~/lb/reddit/*.dbsetsubreddits(sqlite-utils$reddit_db'select path from playlists'--tsv --no-headers|grep old.reddit.com|sed's|https://old.reddit.com/r/\\(.*\\)/|\\1|'|sed's|https://old.reddit.com/user/\\(.*\\)/|u_\\1|'|tr -d\"\\r\")~/github/xk/reddit_mining/links/forsubredditin$subredditsifnottest-e\"$subreddit.csv\"echo\"octosql -o csv \\\"select path,score,'https://old.reddit.com/r/$subreddit/' as playlist_path from `../reddit_links.parquet` where lower(playlist_path) = '$subreddit' order by score desc \\\" >$subreddit.csv\"endend|parallel -j8forsubredditin$subredditssqlite-utils upsert --pk path --alter --csv --detect-types$reddit_dbmedia$subreddit.csvendlibrary tubeadd --safe --ignore-errors --force$reddit_db(sqlite-utils --raw-lines$reddit_db'select path from media')endDatasetteExplore `library` databases in your browserpip install datasette\ndatasette tv.dbPipe tomnamerRename poorly named filespip install mnamer\nmnamer --movie-directory ~/d/70_Now_Watching/ --episode-directory ~/d/70_Now_Watching/ \\\n --no-overwrite -b (library watch -p fd -s 'path : McCloud')\nlibrary fsadd ~/d/70_Now_Watching/Pipe tolowcharts$ library watch -p f -col time_created | lowcharts timehist -w 80Matches: 445183.\nEach \u220e represents a count of 1896\n[2022-04-13 03:16:05] [151689] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-04-19 07:59:37] [ 16093] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-04-25 12:43:09] [ 12019] \u220e\u220e\u220e\u220e\u220e\u220e\n[2022-05-01 17:26:41] [ 48817] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-05-07 22:10:14] [ 36259] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-05-14 02:53:46] [ 3942] \u220e\u220e\n[2022-05-20 07:37:18] [ 2371] \u220e\n[2022-05-26 12:20:50] [ 517]\n[2022-06-01 17:04:23] [ 4845] \u220e\u220e\n[2022-06-07 21:47:55] [ 2340] \u220e\n[2022-06-14 02:31:27] [ 563]\n[2022-06-20 07:14:59] [ 13836] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-06-26 11:58:32] [ 1905] \u220e\n[2022-07-02 16:42:04] [ 1269]\n[2022-07-08 21:25:36] [ 3062] \u220e\n[2022-07-15 02:09:08] [ 9192] \u220e\u220e\u220e\u220e\n[2022-07-21 06:52:41] [ 11955] \u220e\u220e\u220e\u220e\u220e\u220e\n[2022-07-27 11:36:13] [ 50938] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-08-02 16:19:45] [ 70973] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n[2022-08-08 21:03:17] [ 2598] \u220eBTW, for some cols like time_deleted you'll need to specify a where clause so they aren't filtered out:$ library watch -p f -col time_deleted -w time_deleted'>'0 | lowcharts timehist -w 80UsageCreate database subcommandsfsaddAdd local media$ library fsadd -h\nusage: library fsadd [(--video) | --audio | --image | --text | --filesystem] DATABASE PATH ...\n\nThe default database type is video:\n library fsadd tv.db ./tv/\n library fsadd --video tv.db ./tv/ # equivalent\n\nYou can also create audio databases. Both audio and video use ffmpeg to read metadata:\n library fsadd --audio audio.db ./music/\n\nImage uses ExifTool:\n library fsadd --image image.db ./photos/\n\nText will try to read files and save the contents into a searchable database:\n library fsadd --text text.db ./documents_and_books/\n\nCreate a text database and scan with OCR and speech-recognition:\n library fsadd --text --ocr --speech-recognition ocr.db ./receipts_and_messages/\n\nCreate a video database and read internal/external subtitle files into a searchable database:\n library fsadd --scan-subtitles tv.search.db ./tv/ ./movies/\n\nDecode media to check for corruption (slow):\n library fsadd --check-corrupt\n # See media-check command for full options\n\nNormally only relevant filetypes are included. You can scan all files with this flag:\n library fsadd --scan-all-files mixed.db ./tv-and-maybe-audio-only-files/\n # I use that with this to keep my folders organized:\n library watch -w 'video_count=0 and audio_count>=1' -pf mixed.db | parallel mv {} ~/d/82_Audiobooks/\n\nRemove path roots with --force\n library fsadd audio.db /mnt/d/Youtube/\n [/mnt/d/Youtube] Path does not exist\n\n library fsadd --force audio.db /mnt/d/Youtube/\n [/mnt/d/Youtube] Path does not exist\n [/mnt/d/Youtube] Building file list...\n [/mnt/d/Youtube] Marking 28932 orphaned metadata records as deleted\n\nIf you run out of RAM, for example scanning large VR videos, you can lower the number of threads via --io-multiplier\n\n library fsadd vr.db --delete-unplayable --check-corrupt --full-scan-if-corrupt 15% --delete-corrupt 20% ./vr/ --io-multiplier 0.2\n\nMove files on import\n\n library fsadd audio.db --move ~/library/ ./added_folder/\n This will run destination paths through `library christen` and move files relative to the added folder roottubeaddAdd online video media (yt-dlp)$ library tubeadd -h\nusage: library tubeadd [--safe] [--extra] [--subs] [--auto-subs] DATABASE URLS ...\n\nCreate a dl database / add links to an existing database\n\n library tubeadd dl.db https://www.youdl.com/c/BranchEducation/videos\n\nAdd links from a line-delimited file\n\n cat ./my_yt_subscriptions.txt | library tubeadd reddit.db -\n\nAdd metadata to links already in a database table\n\n library tubeadd --force reddit.db (sqlite-utils --raw-lines reddit.db 'select path from media')\n\nFetch extra metadata:\n\n By default tubeadd will quickly add media at the expense of less metadata.\n If you plan on using `library download` then it doesn't make sense to use `--extra`.\n Downloading will add the extra metadata automatically to the database.\n You can always fetch more metadata later via tubeupdate:\n library tubeupdate tw.db --extrawebaddAdd open-directory media$ library webadd -h\nusage: library web-add [(--filesystem) | --video | --audio | --image | --text] DATABASE URL ...\n\nScan open directories\n\nlibrary download open_dir.db --fs --prefix ~/d/dump/video/ --relative -vv -s factory -pgalleryaddAdd online gallery media (gallery-dl)$ library galleryadd -h\nusage: library galleryadd DATABASE URLS\n\nAdd gallery_dl URLs to download later or periodically update\n\nIf you have many URLs use stdin\n\n cat ./my-favorite-manhwa.txt | library galleryadd your.db --insert-only -tabsaddCreate a tabs database; Add URLs$ library tabsadd -h\nusage: library tabsadd [--frequency daily weekly (monthly) quarterly yearly] [--no-sanitize] DATABASE URLS ...\n\nAdding one URL:\n\n library tabsadd -f daily tabs.db https://wiby.me/surprise/\n\n Depending on your shell you may need to escape the URL (add quotes)\n\n If you use Fish shell know that you can enable features to make pasting easier:\n set -U fish_features stderr-nocaret qmark-noglob regex-easyesc ampersand-nobg-in-token\n\n Also I recommend turning Ctrl+Backspace into a super-backspace for repeating similar commands with long args:\n echo 'bind \\b backward-kill-bigword' >> ~/.config/fish/config.fish\n\nImporting from a line-delimitated file:\n\n library tabsadd -f yearly -c reddit tabs.db (cat ~/mc/yearly-subreddit.cron)links-addCreate a link-scraping database$ library links-add -h\nusage: library links-add DATABASE PATH ... [--case-sensitive] [--cookies-from-browser BROWSER[+KEYRING][:PROFILE][::CONTAINER]] [--selenium] [--manual] [--scroll] [--auto-pager] [--poke] [--chrome] [--local-html] [--file FILE]\n\nDatabase version of extract-links\n\nYou can fine-tune what links get saved with --path/text/before/after-include/exclude.\n\n library links-add --path-include /video/\n\nDefaults to stop fetching\n\n After encountering ten pages with no new links:\n library links-add --stop-pages-no-new 10\n\n Some websites don't give an error when you try to access pages which don't exist.\n To compensate for this the script will only continue fetching pages until there are both no new nor known links for four pages:\n library links-add --stop-pages-no-match 4\n\nBackfill fixed number of pages\n\n You can disable automatic stopping by any of the following:\n\n - Set `--backfill-pages` to the desired number of pages for the first run\n - Set `--fixed-pages` to _always_ fetch the desired number of pages\n\n If the website is supported by --auto-pager data is fetched twice when using page iteration.\n As such, page iteration (--max-pages, --fixed-pages, etc) is disabled when using `--auto-pager`.\n\n You can set unset --fixed-pages for all the playlists in your database by running this command:\n sqlite your.db \"UPDATE playlists SET extractor_config = json_replace(extractor_config, '$.fixed_pages', null)\"\n\nTo use \"&p=1\" instead of \"&page=1\"\n\n library links-add --page-key p\n\n By default the script will attempt to modify each given URL with \"&page=1\".\n\nSingle page\n\n If `--fixed-pages` is 1 and --start-page is not set then the URL will not be modified.\n\n library links-add --fixed-pages=1\n Loading page https://site/path\n\n library links-add --fixed-pages=1 --page-start 99\n Loading page https://site/path?page=99\n\nReverse chronological paging\n\n library links-add --max-pages 10\n library links-add --fixed-pages (overrides --max-pages and --stop-known but you can still stop early via --stop-link ie. 429 page)\n\nChronological paging\n\n library links-add --page-start 100 --page-step 1\n\n library links-add --page-start 100 --page-step=-1 --fixed-pages=5 # go backwards\n\n # TODO: store previous page id (max of sliding window)\n\nJump pages\n\n Some pages don't count page numbers but instead count items like messages or forum posts. You can iterate through like this:\n\n library links-add --page-key start --page-start 0 --page-step 50\n\n which translates to\n &start=0 first page\n &start=50 second page\n &start=100 third page\n\nPage folders\n\n Some websites use paths instead of query parameters. In this case make sure the URL provided includes that information with a matching --page-key\n\n library links-add --page-key page https://website/page/1/\n library links-add --page-key article https://website/article/1/\n\nImport links from args\n\n library links-add --no-extract links.db (cb)\n\nImport lines from stdin\n\n cb | lb linksdb example_dbs/links.db --skip-extract -\n\nOther Examples\n\n library links-add links.db https://video/site/ --path-include /video/\n\n library links-add links.db https://loginsite/ --path-include /article/ --cookies-from-browser firefox\n library links-add links.db https://loginsite/ --path-include /article/ --cookies-from-browser chrome\n\n library links-add --path-include viewtopic.php --cookies-from-browser firefox \\\n --page-key start --page-start 0 --page-step 50 --fixed-pages 14 --stop-pages-no-match 1 \\\n plab.db https://plab/forum/tracker.php?o=(string replace ' ' \\n -- 1 4 7 10 15)&s=2&tm=-1&f=(string replace ' ' \\n -- 1670 1768 60 1671 1644 1672 1111 508 555 1112 1718 1143 1717 1851 1713 1712 1775 1674 902 1675 36 1830 1803 1831 1741 1676 1677 1780 1110 1124 1784 1769 1793 1797 1804 1819 1825 1836 1842 1846 1857 1861 1867 1451 1788 1789 1792 1798 1805 1820 1826 1837 1843 1847 1856 1862 1868 284 1853 1823 1800 1801 1719 997 1818 1849 1711 1791 1762)siteaddAuto-scrape website data to SQLITE$ library siteadd -h\nusage: library site-add DATABASE PATH ... [--auto-pager] [--poke] [--local-html] [--file FILE]\n\nExtract data from website requests to a database\n\n library siteadd jobs.st.db --poke https://hk.jobsdb.com/hk/search-jobs/python/\n\nRun with `-vv` to see and interact with the browserredditaddCreate a reddit database; Add subreddits$ library redditadd -h\nusage: library redditadd [--lookback N_DAYS] [--praw-site bot1] DATABASE URLS ...\n\nFetch data for redditors and reddits:\n\n library redditadd interesting.db https://old.reddit.com/r/coolgithubprojects/ https://old.reddit.com/user/Diastro\n\nIf you have a file with a list of subreddits you can do this:\n\n library redditadd 96_Weird_History.db --subreddits (cat ~/mc/96_Weird_History-reddit.txt)\n\nLikewise for redditors:\n\n library redditadd shadow_banned.db --redditors (cat ~/mc/shadow_banned.txt)\n\nNote that reddit's API is limited to 1000 posts and it usually doesn't go back very far historically.\nAlso, it may be the case that reddit's API (praw) will stop working in the near future. For both of these problems\nmy suggestion is to use pushshift data.\nYou can find more info here: https://github.com/chapmanjacobd/reddit_mining#how-was-this-madepushshiftConvert pushshift data to reddit.db format (stdin)$ library pushshift -h\nusage: library pushshift DATABASE < stdin\n\nDownload data (about 600GB jsonl.zst; 6TB uncompressed)\n\n wget -e robots=off -r -k -A zst https://files.pushshift.io/reddit/submissions/\n\nLoad data from files via unzstd\n\n unzstd --memory=2048MB --stdout RS_2005-07.zst | library pushshift pushshift.db\n\nOr multiple (output is about 1.5TB SQLITE fts-searchable):\n\n for f in psaw/files.pushshift.io/reddit/submissions/*.zst\n echo \"unzstd --memory=2048MB --stdout $f | library pushshift (basename $f).db\"\n library optimize (basename $f).db\n end | parallel -j5hnaddCreate / Update a Hacker News database$ library hnadd -h\nusage: library hnadd [--oldest] DATABASE\n\nFetch latest stories first:\n\n library hnadd hn.db -v\n Fetching 154873 items (33212696 to 33367569)\n Saving comment 33367568\n Saving comment 33367543\n Saving comment 33367564\n ...\n\nFetch oldest stories first:\n\n library hnadd --oldest hn.dbsubstackBackup substack articles$ library substack -h\nusage: library substack DATABASE PATH ...\n\nBackup substack articlestildesBackup tildes comments and topics$ library tildes -h\nusage: library tildes DATABASE USER\n\nBackup tildes.net user comments and topics\n\n library tildes tildes.net.db xk3\n\nWithout cookies you are limited to the first page. You can use cookies like this:\n https://github.com/rotemdan/ExportCookies\n library tildes tildes.net.db xk3 --cookies ~/Downloads/cookies-tildes-net.txtplaces-importImport places of interest (POIs)$ library places-import -h\nusage: library places-import DATABASE PATH ...\n\nLoad POIs from Google Maps Google TakeoutUpdate database subcommandsfsupdateUpdate local media$ library fsupdate -h\nusage: library fsupdate DATABASE\n\nUpdate each path previously saved:\n\n library fsupdate video.dbtubeupdateUpdate online video media$ library tubeupdate -h\nusage: library tubeupdate [--audio | --video] DATABASE\n\nFetch the latest videos for every playlist saved in your database\n\n library tubeupdate educational.db\n\nFetch extra metadata:\n\n By default tubeupdate will quickly add media.\n You can run with --extra to fetch more details: (best resolution width, height, subtitle tags, etc)\n\n library tubeupdate educational.db --extra https://www.youtube.com/channel/UCBsEUcR-ezAuxB2WlfeENvA/videos\n\nRemove duplicate playlists:\n\n lb dedupe-db video.db playlists --bk extractor_playlist_idwebupdateUpdate open-directory media$ library webupdate -h\nusage: library web-update DATABASE\n\nUpdate saved open directoriesgalleryupdateUpdate online gallery media$ library galleryupdate -h\nusage: library galleryupdate DATABASE URLS\n\nCheck previously saved gallery_dl URLs for new contentlinks-updateUpdate a link-scraping database$ library links-update -h\nusage: library links-update DATABASE\n\nFetch new links from each path previously saved\n\n library links-update links.dbredditupdateUpdate reddit media$ library redditupdate -h\nusage: library redditupdate [--audio | --video] [--lookback N_DAYS] [--praw-site bot1] DATABASE\n\nFetch the latest posts for every subreddit/redditor saved in your database\n\n library redditupdate edu_subreddits.dbPlayback subcommandswatchWatch / Listen$ library watch -h\nusage: library watch DATABASE [optional args]\n\nControl playback:\n To stop playback press Ctrl-C in either the terminal or mpv\n\n Create global shortcuts in your desktop environment by sending commands to mpv_socket:\n echo 'playlist-next force' | socat - /tmp/mpv_socket\n\nOverride the default player (mpv):\n library does a lot of things to try to automatically use your preferred media player\n but if it doesn't guess right you can make it explicit:\n library watch --player \"vlc --vlc-opts\"\n\nCast to chromecast groups:\n library watch --cast --cast-to \"Office pair\"\n library watch -ct \"Office pair\" # equivalent\n If you don't know the exact name of your chromecast group run `catt scan`\n\nPlay media in order (similarly named episodes):\n library watch --play-in-order\n library watch -O # equivalent\n\n The default sort value is 'natural_ps' which means media will be sorted by parent path\n and then stem in a natural way (using the integer values within the path). But there are many other options:\n\n Options:\n\n - reverse: reverse the sort order\n - compat: treat characters like '\u2466' as '7'\n\n Algorithms:\n\n - natural: parse numbers as integers\n - os: sort similar to the OS File Explorer sorts. To improve non-alphanumeric sorting on Mac OS X and Linux it is necessary to install pyicu (perhaps via python3-icu -- https://gitlab.pyicu.org/main/pyicu#installing-pyicu)\n - path: use natsort \"path\" algorithm (https://natsort.readthedocs.io/en/stable/api.html#the-ns-enum)\n - human: use system locale\n - ignorecase: treat all case as equal\n - lowercase: sort lowercase first\n - signed: sort with an understanding of negative numbers\n - python: sort like default python\n\n Values:\n\n - path\n - parent\n - stem\n - title (or any other column value)\n - ps: parent, stem\n - pts: parent, title, stem\n\n Use this format: algorithm, value, algorithm_value, or option_algorithm_value.\n For example:\n\n - library watch -O human\n - library watch -O title\n - library watch -O human_title\n - library watch -O reverse_compat_human_title\n\n - library watch -O path # path algorithm and parent, stem values (path_ps)\n - library watch -O path_path # path algorithm and path values\n\n Also, if you are using --random you need to fetch sibling media to play the media in order:\n\n - library watch --random --fetch-siblings each -O # get the first result per directory\n - library watch --random --fetch-siblings if-audiobook -O # get the first result per directory if 'audiobook' is in the path\n - library watch --random --fetch-siblings always -O # get 2,000 results per directory\n\n If searching by a specific subpath it may be preferable to just sort by path instead\n library watch d/planet.earth.2024/ -u path\n\n library watch --related # Similar to -O but uses fts to find similar content\n library watch -R # equivalent\n library watch -RR # above, plus ignores most filters\n\n library watch --cluster # cluster-sort to put similar-named paths closer together\n library watch -C # equivalent\n\n library watch --big-dirs # Recommended to use with --duration or --depth filters; see `lb big-dirs -h` for more info\n library watch -B # equivalent\n\n All of these options can be used together but it will be a bit slow and the results might be mid-tier\n as multiple different algorithms create a muddied signal (too many cooks in the kitchen):\n library watch -RRCO\n\n You can even sort the items within each cluster by auto-MCDA ~LOL~\n library watch -B --sort-groups-by 'mcda median_size,-deleted'\n library watch -C --sort-groups-by 'mcda median_size,-deleted'\n\nFilter media by file siblings of parent directory:\n library watch --sibling # only include files which have more than or equal to one sibling\n library watch --solo # only include files which are alone by themselves\n\n `--sibling` is just a shortcut for `--lower 2`; `--solo` is `--upper 1`\n library watch --sibling --solo # you will always get zero records here\n library watch --lower 2 --upper 1 # equivalent\n\n You can be more specific via the `--upper` and `--lower` flags\n library watch --lower 3 # only include files which have three or more siblings\n library watch --upper 3 # only include files which have fewer than three siblings\n library watch --lower 3 --upper 3 # only include files which are three siblings inclusive\n library watch --lower 12 --upper 25 -O # on my machine this launches My Mister 2018\n\nPlay recent partially-watched videos (requires mpv history):\n library watch --partial # play newest first\n\n library watch --partial old # play oldest first\n library watch -P o # equivalent\n\n library watch -P p # sort by percent remaining\n library watch -P t # sort by time remaining\n library watch -P s # skip partially watched (only show unseen)\n\n The default time used is \"last-viewed\" (ie. the most recent time you closed the video)\n If you want to use the \"first-viewed\" time (ie. the very first time you opened the video)\n library watch -P f # use watch_later file creation time instead of modified time\n\n You can combine most of these options, though some will be overridden by others.\n library watch -P fo # this means \"show the oldest videos using the time I first opened them\"\n library watch -P pt # weighted remaining (percent * time remaining)\n\nPrint instead of play:\n library watch --print --limit 10 # print the next 10 files\n library watch -p -L 10 # print the next 10 files\n library watch -p # this will print _all_ the media. be cautious about `-p` on an unfiltered set\n\n Printing modes\n library watch -p # print as a table\n library watch -p a # print an aggregate report\n library watch -p b # print a big-dirs report (see library bigdirs -h for more info)\n library watch -p f # print fields (defaults to path; use --cols to change)\n # -- useful for piping paths to utilities like xargs or GNU Parallel\n\n library watch -p d # mark deleted\n library watch -p w # mark watched\n\n Some printing modes can be combined\n library watch -p df # print files for piping into another program and mark them as deleted within the db\n library watch -p bf # print fields from big-dirs report\n\n Check if you have downloaded something before\n library watch -u duration -p -s 'title'\n\n Print an aggregate report of deleted media\n library watch -w time_deleted!=0 -p=a\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 duration \u2502 size \u2502 count \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Aggregate \u2502 14 days, 23 \u2502 50.6 GB \u2502 29058 \u2502\n \u2502 \u2502 hours and 42 \u2502 \u2502 \u2502\n \u2502 \u2502 minutes \u2502 \u2502 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n Total duration: 14 days, 23 hours and 42 minutes\n\n Print an aggregate report of media that has no duration information (ie. online or corrupt local media)\n library watch -w 'duration is null' -p=a\n\n Print a list of filenames which have below 1280px resolution\n library watch -w 'width<1280' -p=f\n\n Print media you have partially viewed with mpv\n library watch --partial -p\n library watch -P -p # equivalent\n library watch -P -p f --cols path,progress,duration # print CSV of partially watched files\n library watch --partial -pa # print an aggregate report of partially watched files\n\n View how much time you have watched\n library watch -w play_count'>'0 -p=a\n\n See how much video you have\n library watch video.db -p=a\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 hours \u2502 size \u2502 count \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Aggregate \u2502 145769 \u2502 37.6 TB \u2502 439939 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n Total duration: 16 years, 7 months, 19 days, 17 hours and 25 minutes\n\n View all the columns\n library watch -p -L 1 --cols '*'\n\n Open ipython with all of your media\n library watch -vv -p --cols '*'\n ipdb> len(media)\n 462219\n\nSet the play queue size:\n By default the play queue is 120--long enough that you likely have not noticed\n but short enough that the program is snappy.\n\n If you want everything in your play queue you can use the aid of infinity.\n Pick your poison (these all do effectively the same thing):\n library watch -L inf\n library watch -l inf\n library watch --queue inf\n library watch -L 999999999999\n\n You may also want to restrict the play queue.\n For example, when you only want 1000 random files:\n library watch -u random -L 1000\n\nOffset the play queue:\n You can also offset the queue. For example if you want to skip one or ten media:\n library watch --skip 10 # offset ten from the top of an ordered query\n\nRepeat\n library watch # listen to 120 random songs (DEFAULT_PLAY_QUEUE)\n library watch --limit 5 # listen to FIVE songs\n library watch -l inf -u random # listen to random songs indefinitely\n library watch -s infinite # listen to songs from the band infinite\n\nConstrain media by search:\n Audio files have many tags to readily search through so metadata like artist,\n album, and even mood are included in search.\n Video files have less consistent metadata and so only paths are included in search.\n library watch --include happy # only matches will be included\n library watch -s happy # equivalent\n library watch --exclude sad # matches will be excluded\n library watch -E sad # equivalent\n\n Search only the path column\n library watch -O -s 'path : mad max'\n library watch -O -s 'path : \"mad max\"' # add \"quotes\" to be more strict\n\n Double spaces are parsed as one space\n library watch -s ' ost' # will match OST and not ghost\n library watch -s toy story # will match '/folder/toy/something/story.mp3'\n library watch -s 'toy story' # will match more strictly '/folder/toy story.mp3'\n\n You can search without -s but it must directly follow the database due to how argparse works\n library watch ./your.db searching for something\n\nConstrain media by arbitrary SQL expressions:\n library watch --where audio_count = 2 # media which have two audio tracks\n library watch -w \"language = 'eng'\" # media which have an English language tag\n (this could be audio _or_ subtitle)\n library watch -w subtitle_count=0 # media that doesn't have subtitles\n\nConstrain media to duration (in minutes):\n library watch --duration 20\n library watch -d 6 # 6 mins \u00b110 percent (ie. between 5 and 7 mins)\n library watch -d-6 # less than 6 mins\n library watch -d+6 # more than 6 mins\n\n Duration can be specified multiple times:\n library watch -d+5 -d-7 # should be similar to -d 6\n\n If you want exact time use `where`\n library watch --where 'duration=6*60'\n\nConstrain media to file size (in megabytes):\n library watch --size 20\n library watch -S 6 # 6 MB \u00b110 percent (ie. between 5 and 7 MB)\n library watch -S-6 # less than 6 MB\n library watch -S+6 # more than 6 MB\n\nConstrain media by time_created / time_last_played / time_deleted / time_modified:\n library watch --created-within '3 days'\n library watch --created-before '3 years'\n\nConstrain media by throughput:\n Bitrate information is not explicitly saved.\n You can use file size and duration as a proxy for throughput:\n library watch -w 'size/duration<50000'\n\nConstrain media to portrait orientation video:\n library watch --portrait\n library watch -w 'width 0 desc' # play media that has at least one subtitle first\n\n Prioritize large-sized media\n library watch --sort 'ntile(10000) over (order by size/duration) desc'\n library watch -u 'ntile(100) over (order by size) desc'\n\n Sort by count of media with the same-X column (default DESC: most common to least common value)\n library watch -u same-duration\n library watch -u same-title\n library watch -u same-size\n library watch -u same-width, same-height ASC, same-fps\n library watch -u same-time_uploaded same-view_count same-upvote_ratio\n\n No media found when using --random\n In addition to -u/--sort random, there is also the -r/--random flag.\n If you have a large database it should be faster than -u random but it comes with a caveat:\n This flag randomizes via rowid at an earlier stage to boost performance.\n It is possible that you see \"No media found\" or a smaller amount of media than correct.\n You can bypass this by setting --limit. For example:\n library watch -B --folder-size=+12GiB --folder-size=-100GiB -r -pa\n path count size duration avg_duration avg_size\n --------- ------- -------- ------------------------------ -------------- ----------\n Aggregate 10000 752.5 GB 4 months, 15 days and 10 hours 20 minutes 75.3 MB\n (17 seconds)\n library watch -B --folder-size=+12GiB --folder-size=-100GiB -r -pa -l inf\n path count size duration avg_duration avg_size\n --------- ------- ------- --------------------------------------- -------------- ----------\n Aggregate 140868 10.6 TB 5 years, 2 months, 28 days and 14 hours 20 minutes 75.3 MB\n (30 seconds)\n\nPost-actions -- choose what to do after playing:\n library watch --post-action keep # do nothing after playing (default)\n library watch -k delete # delete file after playing\n library watch -k softdelete # mark deleted after playing\n\n library watch -k ask_keep # ask whether to keep after playing\n library watch -k ask_delete # ask whether to delete after playing\n\n library watch -k move # move to \"keep\" dir after playing\n library watch -k ask_move # ask whether to move to \"keep\" folder\n The default location of the keep folder is ./keep/ (relative to the played media file)\n You can change this by explicitly setting an *absolute* `keep-dir` path:\n library watch -k ask_move --keep-dir /home/my/music/keep/\n\n library watch -k ask_move_or_delete # ask after each whether to move to \"keep\" folder or delete\n\n You can also bind keys in mpv to different exit codes. For example in input.conf:\n ; quit 5\n\n And if you run something like:\n library watch --cmd5 ~/bin/process_audio.py\n library watch --cmd5 echo # this will effectively do nothing except skip the normal post-actions via mpv shortcut\n\n When semicolon is pressed in mpv (it will exit with error code 5) then the applicable player-exit-code command\n will start with the media file as the first argument; in this case `~/bin/process_audio.py $path`.\n The command will be daemonized if library exits before it completes.\n\n To prevent confusion, normal post-actions will be skipped if the exit-code is greater than 4.\n Exit-codes 0, 1, 2, 3, and 4: the external post-action will run after normal post-actions. Be careful of conflicting player-exit-code command and post-action behavior when using these!\n\nExperimental options:\n Duration to play (in seconds) while changing the channel\n library watch --interdimensional-cable 40\n library watch -4dtv 40\n\n Playback multiple files at once\n library watch --multiple-playback # one per display; or two if only one display detected\n library watch --multiple-playback 4 # play four media at once, divide by available screens\n library watch -m 4 --screen-name eDP # play four media at once on specific screen\n library watch -m 4 --loop --crop # play four cropped videos on a loop\n library watch -m 4 --hstack # use hstack styleopen-linksOpen links from link dbs$ library open-links -h\nusage: library open-links DATABASE [search] [--title] [--title-prefix TITLE_PREFIX]\n\nOpen links from a links db\n\n wget https://github.com/chapmanjacobd/library/raw/main/example_dbs/music.korea.ln.db\n library open-links music.korea.ln.db\n\nOnly open links once\n\n library open-links ln.db -w 'time_modified=0'\n\nPrint a preview instead of opening tabs\n\n library open-links ln.db -p\n library open-links ln.db --cols time_modified -p\n\nDelete rows\n\n Make sure you have the right search query\n library open-links ln.db \"query\" -p -L inf\n library open-links ln.db \"query\" -pa # view total\n\n library open-links ln.db \"query\" -pd # mark as deleted\n\nCustom search engine\n\n library open-links ln.db --title --prefix 'https://duckduckgo.com/?q='\n\nSkip local media\n\n library open-links dl.db --online\n library open-links dl.db -w 'path like \"http%\"' # equivalentsurfAuto-load browser tabs in a streaming way (stdin)$ library surf -h\nusage: library surf [--count COUNT] [--target-hosts TARGET_HOSTS] < stdin\n\nStreaming tab loader: press ctrl+c to stop.\n\nOpen tabs from a line-delimited file:\n\n cat tabs.txt | library surf -n 5\n\nYou will likely want to use this setting in `about:config`\n\n browser.tabs.loadDivertedInBackground = True\n\nIf you prefer GUI, check out https://unli.xyz/tabsender/Media database subcommandstabsOpen your tabs for the day$ library tabs -h\nusage: library tabs DATABASE\n\nTabs is meant to run **once per day**. Here is how you would configure it with `crontab`:\n\n 45 9 * * * DISPLAY=:0 library tabs /home/my/tabs.db\n\nIf things aren't working you can use `at` to simulate a similar environment as `cron`\n\n echo 'fish -c \"export DISPLAY=:0 && library tabs /full/path/to/tabs.db\"' | at NOW\n\nYou can also invoke tabs manually:\n\n library tabs -L 1 # open one tab\n\nPrint URLs\n\n library tabs -w \"frequency='yearly'\" -p\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 frequency \u2502 time_valid \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 https://old.reddit.com/r/Autonomia/top/?sort=top&t=year \u2502 yearly \u2502 Dec 31 1970 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 https://old.reddit.com/r/Cyberpunk/top/?sort=top&t=year \u2502 yearly \u2502 Dec 31 1970 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 https://old.reddit.com/r/ExperiencedDevs/top/?sort=top&t=year \u2502 yearly \u2502 Dec 31 1970 \u2502\n\n ...\n\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nView how many yearly tabs you have:\n\n library tabs -w \"frequency='yearly'\" -p a\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 count \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Aggregate \u2502 134 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nDelete URLs\n\n library tb -p -s cyber\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 frequency \u2502 time_valid \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 https://old.reddit.com/r/cyberDeck/to \u2502 yearly \u2502 Dec 31 1970 \u2502\n \u2502 p/?sort=top&t=year \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 https://old.reddit.com/r/Cyberpunk/to \u2502 yearly \u2502 Aug 29 2023 \u2502\n \u2502 p/?sort=top&t=year \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 https://www.reddit.com/r/cyberDeck/ \u2502 yearly \u2502 Sep 05 2023 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n library tb -p -w \"path='https://www.reddit.com/r/cyberDeck/'\" --delete\n Removed 1 metadata records\n library tb -p -s cyber\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 path \u2502 frequency \u2502 time_valid \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 https://old.reddit.com/r/cyberDeck/to \u2502 yearly \u2502 Dec 31 1970 \u2502\n \u2502 p/?sort=top&t=year \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 https://old.reddit.com/r/Cyberpunk/to \u2502 yearly \u2502 Aug 29 2023 \u2502\n \u2502 p/?sort=top&t=year \u2502 \u2502 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255bblockBlock a channel$ library block -h\nusage: library block DATABASE URLS ...\n\nBlocklist specific URLs (eg. YouTube channels, etc)\n\n library block dl.db https://annoyingwebsite/etc/\n\nOr URL substrings\n\n library block dl.db \"%fastcompany.com%\"\n\nBlock videos from the playlist uploader\n\n library block dl.db --match-column playlist_path 'https://youtube.com/playlist?list=PLVoczRgDnXDLWV1UJ_tO70VT_ON0tuEdm'\n\nOr other columns\n\n library block dl.db --match-column title \"% bitcoin%\"\n library block dl.db --force --match-column uploader Zeducation\n\nDisplay subdomains (similar to `lb download-status`)\n\n library block audio.db\n subdomain count new_links tried percent_tried successful percent_successful failed percent_failed\n ------------------- ------- ----------- ------- --------------- ------------ -------------------- -------- ----------------\n dts.podtrac.com 5244 602 4642 88.52% 690 14.86% 3952 85.14%\n soundcloud.com 16948 11931 5017 29.60% 920 18.34% 4097 81.66%\n twitter.com 945 841 104 11.01% 5 4.81% 99 95.19%\n v.redd.it 9530 6805 2725 28.59% 225 8.26% 2500 91.74%\n vimeo.com 865 795 70 8.09% 65 92.86% 5 7.14%\n www.youtube.com 210435 140952 69483 33.02% 66017 95.01% 3467 4.99%\n youtu.be 60061 51911 8150 13.57% 7736 94.92% 414 5.08%\n youtube.com 5976 5337 639 10.69% 599 93.74% 40 6.26%\n\nFind some words to block based on frequency / recency of downloaded media\n\n library watch dl.db -u time_downloaded desc -L 10000 -pf | lb nouns | sort | uniq -c | sort -g\n ...\n 183 ArchiveOrg\n 187 Documentary\n 237 PBS\n 243 BBC\n ...playlistsList stored playlists$ library playlists -h\nusage: library playlists DATABASE [--delete ...]\n\nList of Playlists\n\n library playlists\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 extractor_key \u2502 title \u2502 path \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Youtube \u2502 Highlights of Life \u2502 https://www.youtube.com/playlist?list=PL7gXS9DcOm5-O0Fc1z79M72BsrHByda3n \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nSearch playlists\n\n library playlists audio.db badfinger\n path extractor_key title count\n ---------------------------------------------------------- --------------- ------------------------------ -------\n https://music.youtube.com/channel/UCyJzUJ95hXeBVfO8zOA0GZQ ydl_Youtube Uploads from Badfinger - Topic 226\n\nAggregate Report of Videos in each Playlist\n\n library playlists -p a\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 extractor_key \u2502 title \u2502 path \u2502 duration \u2502 count \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Youtube \u2502 Highlights of Life \u2502 https://www.youtube.com/playlist?list=PL7gXS9DcOm5-O0Fc1z79M72BsrHByda3n \u2502 53.28 minutes \u2502 15 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n 1 playlist\n Total duration: 53.28 minutes\n\nPrint only playlist urls:\n Useful for piping to other utilities like xargs or GNU Parallel.\n library playlists -p f\n https://www.youtube.com/playlist?list=PL7gXS9DcOm5-O0Fc1z79M72BsrHByda3n\n\nRemove a playlist/channel and all linked videos:\n library playlists --remove https://vimeo.com/canal180downloadDownload media$ library download -h\nusage: library download [--prefix /mnt/d/] [--safe] [--subs] [--auto-subs] [--small] DATABASE --video | --audio | --photos\n\nFiles will be saved to //. If prefix is not specified the current working directory will be used\n\nBy default things will download in a random order\n\n library download dl.db --prefix ~/output/path/root/\n\nLimit downloads to a specified playlist URLs or substring (TODO: https://github.com/chapmanjacobd/library/issues/31)\n\n library download dl.db https://www.youtube.com/c/BlenderFoundation/videos\n\nLimit downloads to a specified video URLs or substring\n\n library download dl.db --include https://www.youtube.com/watch?v=YE7VzlLtp-4\n library download dl.db -s https://www.youtube.com/watch?v=YE7VzlLtp-4 # equivalent\n\nMaximizing the variety of subdomains\n\n library download photos.db --photos --image --sort \"ROW_NUMBER() OVER ( PARTITION BY SUBSTR(m.path, INSTR(m.path, '//') + 2, INSTR( SUBSTR(m.path, INSTR(m.path, '//') + 2), '/') - 1) )\"\n\nPrint list of queued up downloads\n\n library download --print\n\nPrint list of saved playlists\n\n library playlists dl.db -p a\n\nPrint download queue groups\n\n library download-status audio.db\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 extractor_key \u2502 duration \u2502 never_downloaded \u2502 errors \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Soundcloud \u2502 \u2502 10 \u2502 0 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 10 days, 4 hours \u2502 1 \u2502 2555 \u2502\n \u2502 \u2502 and 20 minutes \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 7.68 minutes \u2502 99 \u2502 1 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255bdownload-statusShow download status$ library download-status -h\nusage: library download-status DATABASE\n\nPrint download queue groups\n\n library download-status video.db\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 extractor_key \u2502 duration \u2502 never_downloaded \u2502 errors \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Youtube \u2502 3 hours and 2.07 \u2502 76 \u2502 0 \u2502\n \u2502 \u2502 minutes \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Dailymotion \u2502 \u2502 53 \u2502 0 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 1 day, 18 hours \u2502 30 \u2502 0 \u2502\n \u2502 \u2502 and 6 minutes \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Dailymotion \u2502 \u2502 186 \u2502 198 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 1 hour and 52.18 \u2502 1 \u2502 0 \u2502\n \u2502 \u2502 minutes \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Vimeo \u2502 \u2502 253 \u2502 49 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 2 years, 4 \u2502 51676 \u2502 197 \u2502\n \u2502 \u2502 months, 15 days \u2502 \u2502 \u2502\n \u2502 \u2502 and 6 hours \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Youtube \u2502 4 months, 23 \u2502 2686 \u2502 7 \u2502\n \u2502 \u2502 days, 19 hours \u2502 \u2502 \u2502\n \u2502 \u2502 and 33 minutes \u2502 \u2502 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nSimulate --safe flag\n\n library download-status video.db --saferedownloadRe-download deleted/lost media$ library redownload -h\nusage: library redownload DATABASE\n\nIf you have previously downloaded YouTube or other online media, but your\nhard drive failed or you accidentally deleted something, and if that media\nis still accessible from the same URL, this script can help to redownload\neverything that was scanned-as-deleted between two timestamps.\n\nList deletions:\n\n library redownload news.db\n Deletions:\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 time_deleted \u2502 count \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 2023-01-26T00:31:26 \u2502 120 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-01-26T19:54:42 \u2502 18 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-01-26T20:45:24 \u2502 26 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n Showing most recent 3 deletions. Use -l to change this limit\n\nMark videos as candidates for download via specific deletion timestamp:\n\n library redownload city.db 2023-01-26T19:54:42\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 size \u2502 time_created \u2502 time_modified \u2502 time_downloaded \u2502 width \u2502 height \u2502 fps \u2502 duration \u2502 path \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 697.7 MB \u2502 Apr 13 2022 \u2502 Mar 11 2022 \u2502 Oct 19 \u2502 1920 \u2502 1080 \u2502 30 \u2502 21.22 minutes \u2502 /mnt/d/76_CityVideos/PRAIA DE BARRA DE JANGADA CANDEIAS JABOAT\u00c3O \u2502\n \u2502 \u2502 \u2502 \u2502 \u2502 \u2502 \u2502 \u2502 \u2502 RECIFE PE BRASIL AVENIDA BERNARDO VIEIRA DE MELO-4Lx3hheMPmg.mp4\n ...\n\n...or between two timestamps inclusive:\n\n library redownload city.db 2023-01-26T19:54:42 2023-01-26T20:45:24historyShow some playback statistics$ library history -h\nusage: library history [--frequency daily weekly (monthly) yearly] [--limit LIMIT] DATABASE [(all) watching watched created modified deleted]\n\nExplore history through different facets\n\n library history video.db watched\n Finished watching:\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 time_period \u2502 duration_sum \u2502 duration_avg \u2502 size_sum \u2502 size_avg \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 2022-11 \u2502 4 days, 16 hours and 20 minutes \u2502 55.23 minutes \u2502 26.3 GB \u2502 215.9 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2022-12 \u2502 23 hours and 20.03 minutes \u2502 35.88 minutes \u2502 8.3 GB \u2502 213.8 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-01 \u2502 17 hours and 3.32 minutes \u2502 15.27 minutes \u2502 14.3 GB \u2502 214.1 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-02 \u2502 4 days, 5 hours and 60 minutes \u2502 23.17 minutes \u2502 148.3 GB \u2502 561.6 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-03 \u2502 2 days, 18 hours and 18 minutes \u2502 11.20 minutes \u2502 118.1 GB \u2502 332.8 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-05 \u2502 5 days, 5 hours and 4 minutes \u2502 45.75 minutes \u2502 152.9 GB \u2502 932.1 MB \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nlibrary history video.db created --frequency yearly\n Created media:\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 time_period \u2502 duration_sum \u2502 duration_avg \u2502 size_sum \u2502 size_avg \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 2005 \u2502 9.78 minutes \u2502 1.95 minutes \u2502 16.9 MB \u2502 3.4 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2006 \u2502 7 hours and 10.67 minutes \u2502 5 minutes \u2502 891.1 MB \u2502 10.4 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2007 \u2502 1 day, 17 hours and 33 minutes \u2502 8.55 minutes \u2502 5.9 GB \u2502 20.3 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2008 \u2502 5 days, 16 hours and 10 minutes \u2502 17.02 minutes \u2502 20.7 GB \u2502 43.1 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2009 \u2502 24 days, 2 hours and 56 minutes \u2502 33.68 minutes \u2502 108.4 GB \u2502 105.2 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2010 \u2502 1 month, 1 days and 1 minutes \u2502 35.52 minutes \u2502 124.2 GB \u2502 95.7 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2011 \u2502 2 months, 14 days, 1 hour and 22 minutes \u2502 55.93 minutes \u2502 222.0 GB \u2502 114.9 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2012 \u2502 2 months, 22 days, 19 hours and 17 minutes \u2502 45.50 minutes \u2502 343.6 GB \u2502 129.6 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2013 \u2502 3 months, 11 days, 21 hours and 48 minutes \u2502 42.72 minutes \u2502 461.1 GB \u2502 131.7 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2014 \u2502 3 months, 7 days, 10 hours and 22 minutes \u2502 46.80 minutes \u2502 529.6 GB \u2502 173.1 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2015 \u2502 2 months, 21 days, 23 hours and 36 minutes \u2502 36.73 minutes \u2502 452.7 GB \u2502 139.2 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2016 \u2502 3 months, 26 days, 7 hours and 59 minutes \u2502 39.48 minutes \u2502 603.4 GB \u2502 139.9 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2017 \u2502 3 months, 10 days, 2 hours and 19 minutes \u2502 31.78 minutes \u2502 543.5 GB \u2502 117.5 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2018 \u2502 3 months, 21 days, 20 hours and 56 minutes \u2502 30.98 minutes \u2502 607.5 GB \u2502 114.8 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2019 \u2502 5 months, 23 days, 2 hours and 30 minutes \u2502 35.77 minutes \u2502 919.7 GB \u2502 129.7 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2020 \u2502 7 months, 16 days, 10 hours and 58 minutes \u2502 26.15 minutes \u2502 1.2 TB \u2502 93.9 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2021 \u2502 7 months, 21 days, 9 hours and 40 minutes \u2502 39.93 minutes \u2502 1.3 TB \u2502 149.9 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2022 \u2502 17 years, 3 months, 0 days and 21 hours \u2502 19.62 minutes \u2502 35.8 TB \u2502 77.5 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023 \u2502 15 years, 3 months, 24 days and 1 hours \u2502 17.57 minutes \u2502 27.6 TB \u2502 60.2 MB \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 title_path \u2502 duration \u2502 time_created \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 [Eng Sub] TVB Drama | The King Of Snooker \u684c\u7403\u5929\u738b 07/20 | Adam Cheng | 2009 #Chinesedrama \u2502 43.85 minutes \u2502 yesterday \u2502\n \u2502 https://www.youtube.com/watch?v=zntYD1yLrG8 \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 [Eng Sub] TVB Drama | The King Of Snooker \u684c\u7403\u5929\u738b 08/20 | Adam Cheng | 2009 #Chinesedrama \u2502 43.63 minutes \u2502 yesterday \u2502\n \u2502 https://www.youtube.com/watch?v=zQnSfoWrh-4 \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 [Eng Sub] TVB Drama | The King Of Snooker \u684c\u7403\u5929\u738b 06/20 | Adam Cheng | 2009 #Chinesedrama \u2502 43.60 minutes \u2502 yesterday \u2502\n \u2502 https://www.youtube.com/watch?v=Qiax1kFyGWU \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 [Eng Sub] TVB Drama | The King Of Snooker \u684c\u7403\u5929\u738b 04/20 | Adam Cheng | 2009 #Chinesedrama \u2502 43.45 minutes \u2502 yesterday \u2502\n \u2502 https://www.youtube.com/watch?v=NT9C3PRrlTA \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 [Eng Sub] TVB Drama | The King Of Snooker \u684c\u7403\u5929\u738b 02/20 | Adam Cheng | 2009 #Chinesedrama \u2502 43.63 minutes \u2502 yesterday \u2502\n \u2502 https://www.youtube.com/watch?v=MjpCiTawlTE \u2502 \u2502 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\nView download stats\n\n library history video.db --freqency daily downloaded\n Downloaded media:\n day total_duration avg_duration total_size avg_size count\n ---------- -------------------------------------- ------------------------ ------------ ---------- -------\n 2023-08-11 1 month, 7 days and 8 hours 17 minutes 192.2 GB 58.3 MB 3296\n 2023-08-12 18 days and 15 hours 17 minutes 89.7 GB 56.4 MB 1590\n 2023-08-14 13 days and 1 hours 22 minutes 111.2 GB 127.2 MB 874\n 2023-08-15 13 days and 6 hours 17 minutes 140.0 GB 126.7 MB 1105\n 2023-08-17 2 months, 8 days and 8 hours 19 minutes 380.4 GB 72.6 MB 5243\n 2023-08-18 2 months, 30 days and 18 hours 17 minutes 501.9 GB 63.3 MB 7926\n 2023-08-19 2 months, 6 days and 19 hours 19 minutes 578.1 GB 110.6 MB 5229\n 2023-08-20 3 days and 9 hours 6 minutes and 57 seconds 14.5 GB 20.7 MB 700\n 2023-08-21 4 days and 3 hours 12 minutes 18.0 GB 36.3 MB 495\n 2023-08-22 10 days and 8 hours 17 minutes 82.1 GB 91.7 MB 895\n 2023-08-23 19 days and 9 hours 22 minutes 93.7 GB 74.7 MB 1254\n\n See also: library history video.db --freqency daily downloaded --hide-deleted\n\nView deleted stats\n\n library history video.db deleted\n Deleted media:\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 time_period \u2502 duration_sum \u2502 duration_avg \u2502 size_sum \u2502 size_avg \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 2023-04 \u2502 1 year, 10 months, 3 days and 8 hours \u2502 4.47 minutes \u2502 1.6 TB \u2502 7.4 MB \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2023-05 \u2502 9 months, 26 days, 20 hours and 34 minutes \u2502 30.35 minutes \u2502 1.1 TB \u2502 73.7 MB \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 title_path \u2502 duration \u2502 subtitle_count \u2502 time_deleted \u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 Terminus (1987) \u2502 1 hour and \u2502 0 \u2502 yesterday \u2502\n \u2502 /mnt/d/70_Now_Watching/Terminus_1987.mp4 \u2502 15.55 minutes \u2502 \u2502 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 Commodore 64 Longplay [062] The Transformers (EU) /mnt/d/71_Mealtime_Videos/Youtube/World_of_Longplays/Com \u2502 24.77 minutes \u2502 2 \u2502 yesterday \u2502\n \u2502 modore_64_Longplay_062_The_Transformers_EU_[1RRX7Kykb38].webm \u2502 \u2502 \u2502 \u2502\n ...searchSearch captions / subtitles$ library search -h\nusage: library search DATABASE QUERY\n\nSearch text databases and subtitles\n\n library search fts.db boil\n 7 captions\n /mnt/d/70_Now_Watching/DidubeTheLastStop-720p.mp4\n 33:46 I brought a real stainless steel boiler\n 33:59 The world is using only stainless boilers nowadays\n 34:02 The boiler is old and authentic\n 34:30 - This boiler? - Yes\n 34:44 I am not forcing you to buy this boiler\u2026\n 34:52 Who will give her a one liter stainless steel boiler for one Lari?\n 34:54 Glass boilers cost two\n\nSearch and open file\n\n library search fts.db 'two words' --openText subcommandscluster-sortSort text and images by similarity$ library cluster-sort -h\nusage: library cluster-sort [input_path | stdin] [output_path | stdout]\n\nGroup lines of text into sorted output\n\n echo 'red apple\n broccoli\n yellow\n green\n orange apple\n red apple' | library cluster-sort\n\n orange apple\n red apple\n red apple\n broccoli\n green\n yellow\n\nShow the groupings\n\n echo 'red apple\n broccoli\n yellow\n green\n orange apple\n red apple' | library cluster-sort --print-groups\n\n [\n {'grouped_paths': ['orange apple', 'red apple', 'red apple']},\n {'grouped_paths': ['broccoli', 'green', 'yellow']}\n ]\n\nAuto-sort images into directories\n\n echo 'image1.jpg\n image2.jpg\n image3.jpg' | library cluster-sort --image --move-groupsextract-linksExtract inner links from lists of web links$ library extract-links -h\nusage: library extract-links PATH ... [--case-sensitive] [--scroll] [--download] [--verbose] [--local-html] [--file FILE] [--path-include ...] [--text-include ...] [--after-include ...] [--before-include ...] [--path-exclude ...] [--text-exclude ...] [--after-exclude ...] [--before-exclude ...]\n\nExtract links from within local HTML fragments, files, or remote pages; filtering on link text and nearby plain-text\n\n library links https://en.wikipedia.org/wiki/List_of_bacon_dishes --path-include https://en.wikipedia.org/wiki/ --after-include famous\n https://en.wikipedia.org/wiki/Omelette\n\nRead from local clipboard and filter out links based on nearby plain text:\n\n library links --local-html (cb -t text/html | psub) --after-exclude paranormal spooky horror podcast tech fantasy supernatural lecture sport\n # note: the equivalent BASH-ism is <(xclip -selection clipboard -t text/html)\n\nRun with `-vv` to see the browserextract-textExtract human text from lists of web links$ library extract-text -h\nusage: library extract-text PATH ... [--skip-links]\n\nSorting suggestions\n\n lb extract-text --skip-links --local-file (cb -t text/html | psub) | lb cs --groups | jq -r '.[] | .grouped_paths | \"\\n\" + join(\"\\n\")'File subcommandsedaExploratory Data Analysis on table-like files$ library eda -h\nusage: library eda PATH ... [--table TABLE] [--start-row START_ROW] [--end-row END_ROW] [--repl]\n\nPerform Exploratory Data Analysis (EDA) on one or more files\n\nOnly 20,000 rows per file are loaded for performance purposes. Set `--end-row inf` to read all the rows and/or run out of RAM.mcdaMulti-criteria Ranking for Decision Support$ library mcda -h\nusage: library mcda PATH ... [--table TABLE] [--start-row START_ROW] [--end-row END_ROW]\n\nPerform Multiple Criteria Decision Analysis (MCDA) on one or more files\n\nOnly 20,000 rows per file are loaded for performance purposes. Set `--end-row inf` to read all the rows and/or run out of RAM.\n\n$ library mcda ~/storage.csv --minimize price --ignore warranty\n\n ### Goals\n #### Maximize\n - size\n #### Minimize\n - price\n\n | | price | size | warranty | TOPSIS | MABAC | SPOTIS | BORDA |\n |----|---------|--------|------------|----------|------------|----------|---------|\n | 0 | 359 | 36 | 5 | 0.769153 | 0.348907 | 0.230847 | 7.65109 |\n | 1 | 453 | 40 | 2 | 0.419921 | 0.0124531 | 0.567301 | 8.00032 |\n | 2 | 519 | 44 | 2 | 0.230847 | -0.189399 | 0.769153 | 8.1894 |\n\n$ library mcda ~/storage.csv --ignore warranty\n\n ### Goals\n #### Maximize\n - price\n - size\n\n | | price | size | warranty | TOPSIS | MABAC | SPOTIS | BORDA |\n |----|---------|--------|------------|----------|-----------|----------|---------|\n | 2 | 519 | 44 | 2 | 1 | 0.536587 | 0 | 7.46341 |\n | 1 | 453 | 40 | 2 | 0.580079 | 0.103888 | 0.432699 | 7.88333 |\n | 0 | 359 | 36 | 5 | 0 | -0.463413 | 1 | 8.46341 |\n\n$ library mcda ~/storage.csv --minimize price --ignore warranty\n\n ### Goals\n #### Maximize\n - size\n #### Minimize\n - price\n\n | | price | size | warranty | TOPSIS | MABAC | SPOTIS | BORDA |\n |----|---------|--------|------------|----------|------------|----------|---------|\n | 0 | 359 | 36 | 5 | 0.769153 | 0.348907 | 0.230847 | 7.65109 |\n | 1 | 453 | 40 | 2 | 0.419921 | 0.0124531 | 0.567301 | 8.00032 |\n | 2 | 519 | 44 | 2 | 0.230847 | -0.189399 | 0.769153 | 8.1894 |incremental-diffDiff large table-like files in chunks$ library incremental-diff -h\nusage: library incremental-diff PATH1 PATH2 [--join-keys JOIN_KEYS] [--table1 TABLE1] [--table2 TABLE2] [--table1-index TABLE1_INDEX] [--table2-index TABLE2_INDEX] [--start-row START_ROW] [--batch-size BATCH_SIZE]\n\nSee data differences in an incremental way to quickly see how two different files differ.\n\nData (PATH1, PATH2) can be two different files of different file formats (CSV, Excel) or it could even be the same file with different tables.\n\nIf files are unsorted you may need to use `--join-keys id,name` to specify ID columns. Rows that have the same ID will then be compared. If you are comparing SQLITE files you may be able to use `--sort id,name` to achieve the same effect.\n\nTo diff everything at once run with `--batch-size inf`media-checkCheck video and audio files for corruption via ffmpeg$ library media-check -h\nusage: library media-check [--chunk-size SECONDS] [--gap SECONDS OR 0.0-1.0*DURATION] [--delete-corrupt >0-100] [--full-scan] [--audio-scan] PATH ...\n\nDefaults to decode 0.5 second per 10% of each file\n\n library media-check ./video.mp4\n\nDecode all the frames of each file to evaluate how corrupt it is (very slow; about 150 seconds for an hour-long file)\n\n library media-check --full-scan ./video.mp4\n\nDecode all the packets of each file to evaluate how corrupt it is (about one second of each file but only accurate for formats where 1 packet == 1 frame)\n\n library media-check --full-scan --gap 0 ./video.mp4\n\nDecode all audio of each file to evaluate how corrupt it is (about four seconds per file)\n\n library media-check --full-scan --audio ./video.mp4\n\nDecode at least one frame at the start and end of each file to evaluate how corrupt it is (takes about one second per file)\n\n library media-check --chunk-size 5% --gap 99.9% ./video.mp4\n\nDecode 3s every 5% of a file to evaluate how corrupt it is (takes about three seconds per file)\n\n library media-check --chunk-size 3 --gap 5% ./video.mp4\n\nDelete the file if 20 percent or more of checks fail\n\n library media-check --delete-corrupt 20% ./video.mp4\n\nTo scan a large folder use `fsadd`. I recommend something like this two-stage approach:\n\n library fsadd --delete-unplayable --check-corrupt --chunk-size 5% tmp.db ./video/ ./folders/\n library media-check (library fs tmp.db -w 'corruption>15' -pf) --full-scan --delete-corrupt 25%\n\nThe above can now be done in one command via `--full-scan-if-corrupt`:\n\n library fsadd --delete-unplayable --check-corrupt --chunk-size 5% tmp.db ./video/ ./folders/ --full-scan-if-corrupt 15% --delete-corrupt 25%\n\nCorruption stats\n\n library fs tmp.db -w 'corruption>15' -pa\n path count duration avg_duration size avg_size\n --------- ------- ------------------- -------------- --------- ----------\n Aggregate 907 15 days and 9 hours 24 minutes 130.6 GiB 147.4 MiB\n\nCorruption graph\n\n sqlite --raw-lines tmp.db 'select corruption from media' | lowcharts hist --min 10 --intervals 10\n\n Samples = 931; Min = 10.0; Max = 100.0\n Average = 39.1; Variance = 1053.103; STD = 32.452\n each \u220e represents a count of 6\n [ 10.0 .. 19.0] [561] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n [ 19.0 .. 28.0] [ 69] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n [ 28.0 .. 37.0] [ 33] \u220e\u220e\u220e\u220e\u220e\n [ 37.0 .. 46.0] [ 18] \u220e\u220e\u220e\n [ 46.0 .. 55.0] [ 14] \u220e\u220e\n [ 55.0 .. 64.0] [ 12] \u220e\u220e\n [ 64.0 .. 73.0] [ 15] \u220e\u220e\n [ 73.0 .. 82.0] [ 18] \u220e\u220e\u220e\n [ 82.0 .. 91.0] [ 50] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\n [ 91.0 .. 100.0] [141] \u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220e\u220esample-hashCalculate a hash based on small file segments$ library sample-hash -h\nusage: library sample-hash [--threads 10] [--chunk-size BYTES] [--gap BYTES OR 0.0-1.0*FILESIZE] PATH ...\n\nCalculate hashes for large files by reading only small segments of each file\n\n library sample-hash ./my_file.mkv\n\nThe threads flag seems to be faster for rotational media but slower on SSDssample-compareCompare files using sample-hash and other shortcuts$ library sample-compare -h\nusage: library sample-hash [--threads 10] [--chunk-size BYTES] [--gap BYTES OR 0.0-1.0*FILESIZE] PATH ...\n\nConvenience subcommand to compare multiple files using sample-hashFolder subcommandsmerge-foldersMerge two or more file trees$ library merge-folders -h\nusage: library merge-folders [--replace] [--skip] [--simulate] SOURCES ... DESTINATION\n\nMerge multiple folders with the same file tree into a single folder.\n\nhttps://github.com/chapmanjacobd/journal/blob/main/programming/linux/misconceptions.md#mv-src-vs-mv-src\n\nTrumps are new or replaced files from an earlier source which now conflict with a later source.\nIf you only have one source then the count of trumps will always be zero.\nThe count of conflicts also includes trumps.relmvMove files preserving parent folder hierarchy$ library relmv -h\nusage: library relmv [--dry-run] SOURCE ... DEST\n\nMove files/folders without losing hierarchy metadata\n\nMove fresh music to your phone every Sunday:\n\n # move last week music back to their source folders\n library relmv /mnt/d/80_Now_Listening/ /mnt/d/\n\n # move new music for this week\n library relmv (\n library listen audio.db --local-media-only --where 'play_count=0' --random -L 600 -p f\n ) /mnt/d/80_Now_Listening/mv-listFind specific folders to move to different disks$ library mv-list -h\nusage: library mv-list [--limit LIMIT] [--lower LOWER] [--upper UPPER] MOUNT_POINT DATABASE\n\nFree up space on a specific disk. Find candidates for moving data to a different mount point\n\n\nThe program takes a mount point and a xklb database file. If you don't have a database file you can create one like this:\n\n library fsadd --filesystem d.db ~/d/\n\nBut this should definitely also work with xklb audio and video databases:\n\n library mv-list /mnt/d/ video.db\n\nThe program will print a table with a sorted list of folders which are good candidates for moving.\nCandidates are determined by how many files are in the folder (so you don't spend hours waiting for folders with millions of tiny files to copy over).\nThe default is 4 to 4000--but it can be adjusted via the --lower and --upper flags.\n\n ...\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 4.0 GB \u2502 7 \u2502 /mnt/d/71_Mealtime_Videos/unsorted/Miguel_4K/ \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 5.7 GB \u2502 10 \u2502 /mnt/d/71_Mealtime_Videos/unsorted/Bollywood_Premium/ \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 2.3 GB \u2502 4 \u2502 /mnt/d/71_Mealtime_Videos/chief_wiggum/ \u2502\n 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\u2588\u2588\u2551\u2588\u2588\u2551\u2591\u255a\u2588\u2588\u2588\u2551\u2588\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u2591\u2591\u2591\u2588\u2588\u2551\u2591\u2591\u2591\u2588\u2588\u2551\u2591\u2591\u2588\u2588\u2551\u255a\u2588\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u255a\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u2591\u2591\u2591\u2588\u2588\u2551\u2591\u2591\u2591\u2588\u2588\u2551\u255a\u2588\u2588\u2588\u2588\u2588\u2554\u255d\u2588\u2588\u2551\u2591\u255a\u2588\u2588\u2588\u2551\u2588\u2588\u2588\u2588\u2588\u2588\u2554\u255d\n \u255a\u2550\u255d\u255a\u2550\u255d\u2591\u2591\u255a\u2550\u2550\u255d\u255a\u2550\u2550\u2550\u2550\u2550\u255d\u2591\u2591\u2591\u2591\u255a\u2550\u255d\u2591\u2591\u2591\u255a\u2550\u255d\u2591\u2591\u255a\u2550\u255d\u2591\u255a\u2550\u2550\u2550\u2550\u2550\u255d\u2591\u2591\u255a\u2550\u2550\u2550\u2550\u255d\u2591\u2591\u2591\u2591\u255a\u2550\u255d\u2591\u2591\u2591\u255a\u2550\u255d\u2591\u255a\u2550\u2550\u2550\u2550\u255d\u2591\u255a\u2550\u255d\u2591\u2591\u255a\u2550\u2550\u255d\u255a\u2550\u2550\u2550\u2550\u2550\u255d\u2591\n\n Type \"done\" when finished\n Type \"more\" to see more files\n Paste a folder (and press enter) to toggle selection\n Type \"*\" to select all files in the most recently printed table\n\nThen it will give you a prompt:\n\n Paste a path:\n\nWherein you can copy and paste paths you want to move from the table and the program will keep track for you.\n\n Paste a path: /mnt/d/75_MovieQueue/720p/s11/\n 26 selected paths: 162.1 GB ; future free space: 486.9 GB\n\nYou can also press the up arrow or paste it again to remove it from the list:\n\n Paste a path: /mnt/d/75_MovieQueue/720p/s11/\n 25 selected paths: 159.9 GB ; future free space: 484.7 GB\n\nAfter you are done selecting folders you can press ctrl-d and it will save the list to a tmp file:\n\n Paste a path: done\n\n Folder list saved to /tmp/tmp7x_75l8. You may want to use the following command to move files to an EMPTY folder target:\n\n rsync -a --info=progress2 --no-inc-recursive --remove-source-files --files-from=/tmp/tmp7x_75l8 -r --relative -vv --dry-run / jim:/free/real/estate/scatterScatter files between folders or disks$ library scatter -h\nusage: library scatter [--limit LIMIT] [--policy POLICY] [--sort SORT] --targets TARGETS DATABASE RELATIVE_PATH ...\n\nBalance files across filesystem folder trees or multiple devices (mostly useful for mergerfs)\n\nScatter filesystem folder trees (without mountpoints; limited functionality; good for balancing fs inodes)\n\n library scatter scatter.db /test/{0,1,2,3,4,5,6,7,8,9}\n\nReduce number of files per folder (creates more folders)\n\n library scatter scatter.db --max-files-per-folder 16000 /test/{0,1,2,3,4,5,6,7,8,9}\n\nMulti-device re-bin: balance by size\n\n library scatter -m /mnt/d1:/mnt/d2:/mnt/d3:/mnt/d4/:/mnt/d5:/mnt/d6:/mnt/d7 fs.db subfolder/of/mergerfs/mnt\n Current path distribution:\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 mount \u2502 file_count \u2502 total_size \u2502 median_size \u2502 time_created \u2502 time_modified \u2502 time_downloaded\u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 /mnt/d1 \u2502 12793 \u2502 169.5 GB \u2502 4.5 MB \u2502 Jan 27 \u2502 Jul 19 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d2 \u2502 13226 \u2502 177.9 GB \u2502 4.7 MB \u2502 Jan 27 \u2502 Jul 19 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d3 \u2502 1 \u2502 717.6 kB \u2502 717.6 kB \u2502 Jan 31 \u2502 Jul 18 2022 \u2502 yesterday \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d4 \u2502 82 \u2502 1.5 GB \u2502 12.5 MB \u2502 Jan 31 \u2502 Apr 22 2022 \u2502 yesterday \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n\n Simulated path distribution:\n 5845 files should be moved\n 20257 files should not be moved\n \u2552\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2564\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2555\n \u2502 mount \u2502 file_count \u2502 total_size \u2502 median_size \u2502 time_created \u2502 time_modified \u2502 time_downloaded\u2502\n \u255e\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2561\n \u2502 /mnt/d1 \u2502 9989 \u2502 46.0 GB \u2502 2.4 MB \u2502 Jan 27 \u2502 Jul 19 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d2 \u2502 10185 \u2502 46.0 GB \u2502 2.4 MB \u2502 Jan 27 \u2502 Jul 19 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d3 \u2502 1186 \u2502 53.6 GB \u2502 30.8 MB \u2502 Jan 27 \u2502 Apr 07 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d4 \u2502 1216 \u2502 49.5 GB \u2502 29.5 MB \u2502 Jan 27 \u2502 Apr 07 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d5 \u2502 1146 \u2502 53.0 GB \u2502 30.9 MB \u2502 Jan 27 \u2502 Apr 07 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d6 \u2502 1198 \u2502 48.8 GB \u2502 30.6 MB \u2502 Jan 27 \u2502 Apr 07 2022 \u2502 Jan 31 \u2502\n \u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n \u2502 /mnt/d7 \u2502 1182 \u2502 52.0 GB \u2502 30.9 MB \u2502 Jan 27 \u2502 Apr 07 2022 \u2502 Jan 31 \u2502\n \u2558\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2567\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255b\n ### Move 1182 files to /mnt/d7 with this command: ###\n rsync -aE --xattrs --info=progress2 --remove-source-files --files-from=/tmp/tmpmr1628ij / /mnt/d7\n ### Move 1198 files to /mnt/d6 with this command: ###\n rsync -aE --xattrs --info=progress2 --remove-source-files --files-from=/tmp/tmp9yd75f6j / /mnt/d6\n ### Move 1146 files to /mnt/d5 with this command: ###\n rsync -aE --xattrs --info=progress2 --remove-source-files --files-from=/tmp/tmpfrj141jj / /mnt/d5\n ### Move 1185 files to /mnt/d3 with this command: ###\n rsync -aE --xattrs --info=progress2 --remove-source-files --files-from=/tmp/tmpqh2euc8n / /mnt/d3\n ### Move 1134 files to /mnt/d4 with this command: ###\n rsync -aE --xattrs --info=progress2 --remove-source-files --files-from=/tmp/tmphzb0gj92 / /mnt/d4\n\nMulti-device re-bin: balance device inodes for specific subfolder\n\n library scatter -m /mnt/d1:/mnt/d2 fs.db subfolder --group count --sort 'size desc'\n\nMulti-device re-bin: only consider the most recent 100 files\n\n library scatter -m /mnt/d1:/mnt/d2 -l 100 -s 'time_modified desc' fs.db /\n\nMulti-device re-bin: empty out a disk (/mnt/d2) into many other disks (/mnt/d1, /mnt/d3, and /mnt/d4)\n\n library scatter fs.db -m /mnt/d1:/mnt/d3:/mnt/d4 /mnt/d2Multi-database subcommandsmerge-dbsMerge SQLITE databases$ library merge-dbs -h\nusage: library merge-dbs DEST_DB SOURCE_DB ... [--only-target-columns] [--only-new-rows] [--upsert] [--pk PK ...] [--table TABLE ...]\n\nMerge-DBs will insert new rows from source dbs to target db, table by table. If primary key(s) are provided,\nand there is an existing row with the same PK, the default action is to delete the existing row and insert the new row\nreplacing all existing fields.\n\nUpsert mode will update each matching PK row such that if a source row has a NULL field and\nthe destination row has a value then the value will be preserved instead of changed to the source row's NULL value.\n\nIgnore mode (--only-new-rows) will insert only rows which don't already exist in the destination db\n\nTest first by using temp databases as the destination db.\nTry out different modes / flags until you are satisfied with the behavior of the program\n\n library merge-dbs --pk path (mktemp --suffix .db) tv.db movies.db\n\nMerge database data and tables\n\n library merge-dbs --upsert --pk path video.db tv.db movies.db\n library merge-dbs --only-target-columns --only-new-rows --table media,playlists --pk path --skip-column id audio-fts.db audio.db\n\n library merge-dbs --pk id --only-tables subreddits reddit/81_New_Music.db audio.db\n library merge-dbs --only-new-rows --pk subreddit,path --only-tables reddit_posts reddit/81_New_Music.db audio.db -v\n\n To skip copying primary-keys from the source table(s) use --business-keys instead of --primary-keys\n\n Split DBs using --where\n\n library merge-dbs --pk path specific-site.db big.db -v --only-new-rows -t media,playlists -w 'path like \"https://specific-site%\"'copy-play-countsCopy play history$ library copy-play-counts -h\nusage: library copy-play-counts DEST_DB SOURCE_DB ... [--source-prefix x] [--target-prefix y]\n\nCopy play count information between databases\n\n library copy-play-counts audio.db phone.db --source-prefix /storage/6E7B-7DCE/d --target-prefix /mnt/dFilesystem Database subcommandschristenClean filenames$ library christen -h\nusage: library christen DATABASE [--run]\n\nRename files to be somewhat normalized\n\nDefault mode is dry-run\n\n library christen fs.db\n\nTo actually do stuff use the run flag\n\n library christen audio.db --run\n\nYou can optionally replace all the spaces in your filenames with dots\n\n library christen --dot-space video.dbdisk-usageShow disk usage$ library disk-usage -h\nusage: library disk-usage DATABASE [--sort-groups-by size | count] [--depth DEPTH] [PATH / SUBSTRING SEARCH]\n\nOnly include files smaller than 1kib\n\n library disk-usage du.db --size=-1Ki\n lb du du.db -S-1Ki\n | path | size | count |\n |---------------------------------------|-----------|---------|\n | /home/xk/github/xk/lb/__pycache__/ | 620 Bytes | 1 |\n | /home/xk/github/xk/lb/.github/ | 1.7 kB | 4 |\n | /home/xk/github/xk/lb/__pypackages__/ | 1.4 MB | 3519 |\n | /home/xk/github/xk/lb/xklb/ | 4.4 kB | 12 |\n | /home/xk/github/xk/lb/tests/ | 3.2 kB | 9 |\n | /home/xk/github/xk/lb/.git/ | 782.4 kB | 2276 |\n | /home/xk/github/xk/lb/.pytest_cache/ | 1.5 kB | 5 |\n | /home/xk/github/xk/lb/.ruff_cache/ | 19.5 kB | 100 |\n | /home/xk/github/xk/lb/.gitattributes | 119 Bytes | |\n | /home/xk/github/xk/lb/.mypy_cache/ | 280 Bytes | 4 |\n | /home/xk/github/xk/lb/.pdm-python | 15 Bytes | |\n\nOnly include files with a specific depth\n\n library disk-usage du.db --depth 19\n lb du du.db -d 19\n | path | size |\n |---------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------|\n | /home/xk/github/xk/lb/__pypackages__/3.11/lib/jedi/third_party/typeshed/third_party/2and3/requests/packages/urllib3/packages/ssl_match_hostname/__init__.pyi | 88 Bytes |\n | /home/xk/github/xk/lb/__pypackages__/3.11/lib/jedi/third_party/typeshed/third_party/2and3/requests/packages/urllib3/packages/ssl_match_hostname/_implementation.pyi | 81 Bytes |big-dirsShow large folders$ library big-dirs -h\nusage: library big-dirs DATABASE [--limit (4000)] [--depth (0)] [--sort-groups-by deleted | played] [--size=+5MB]\n\nSee what folders take up space\n\n library big-dirs video.db\n library big-dirs audio.db\n library big-dirs fs.db\n\nlb big-dirs video.db --folder-size=+10G --lower 400 --upper 14000\n\nlb big-dirs video.db --depth 5\nlb big-dirs video.db --depth 7\n\nYou can even sort by auto-MCDA ~LOL~\n\nlb big-dirs video.db -u 'mcda median_size,-deleted'search-dbSearch a SQLITE database$ library search-db -h\nusage: library search-db DATABASE TABLE SEARCH ... [--delete]\n\nSearch all columns in a SQLITE table. If the table does not exist, uses the table which startswith (if only one match)optimizeRe-optimize database$ library optimize -h\nusage: library optimize DATABASE [--force]\n\nOptimize library databases\n\nThe force flag is usually unnecessary and it can take much longerSingle database enrichment subcommandsdedupe-dbDedupe SQLITE tables$ library dedupe-db -h\nusage: library dedupe-dbs DATABASE TABLE --bk BUSINESS_KEYS [--pk PRIMARY_KEYS] [--only-columns COLUMNS]\n\nDedupe your database (not to be confused with the dedupe subcommand)\n\nIt should not need to be said but *backup* your database before trying this tool!\n\nDedupe-DB will help remove duplicate rows based on non-primary-key business keys\n\n library dedupe-db ./video.db media --bk path\n\nBy default all non-primary and non-business key columns will be upserted unless --only-columns is provided\nIf --primary-keys is not provided table metadata primary keys will be used\nIf your duplicate rows contain exactly the same data in all the columns you can run with --skip-upsert to save a lot of timededupe-mediaDedupe similar media$ library dedupe-media -h\nusage: library [--audio | --id | --title | --filesystem] [--only-soft-delete] [--limit LIMIT] DATABASE\n\nDedupe your files (not to be confused with the dedupe-db subcommand)\n\nlibrary dedupe video.db / httpmerge-online-localMerge online and local data$ library merge-online-local -h\nusage: library merge-online-local DATABASE\n\nIf you have previously downloaded YouTube or other online media, you can dedupe\nyour database and combine the online and local media records as long as your\nfiles have the youtube-dl / yt-dlp id in the filename.mpv-watchlaterImport mpv watchlater files to history$ library mpv-watchlater -h\nusage: library mpv-watchlater DATABASE [--watch-later-directory ~/.config/mpv/watch_later/]\n\nExtract timestamps from MPV to the history tablereddit-selftextCopy selftext links to media table$ library reddit-selftext -h\nusage: library reddit-selftext DATABASE\n\nExtract URLs from reddit selftext from the reddit_posts table to the media tableMisc subcommandsexport-textExport HTML files from SQLite databases$ library export-text -h\nusage: library export-text DATABASE\n\nGenerate HTML files from SQLite databasesprocess-audioShrink audio by converting to Opus format$ library process-audio -h\nusage: library process-audio PATH ... [--always-split] [--split-longer-than DURATION] [--min-split-segment SECONDS] [--dry-run]\n\nConvert audio to Opus. Optionally split up long tracks into multiple files.\n\n fd -tf -eDTS -eAAC -eWAV -eAIF -eAIFF -eFLAC -eAIFF -eM4A -eMP3 -eOGG -eMP4 -eWMA -j4 -x library process-audio\n\nUse --always-split to _always_ split files if silence is detected\n\n library process-audio --always-split audiobook.m4a\n\nUse --split-longer-than to _only_ detect silence for files in excess of a specific duration\n\n library process-audio --split-longer-than 36mins audiobook.m4b audiobook2.mp3Chicken mode////////////////////////\n ////////////////////////|\n //////////////////////// |\n ////////////////////////| |\n | _\\/_ | _\\/_ | |\n | )o(> | <)o( | |\n | _/ <\\ | /> \\_ | | just kidding :-)\n | (_____) | (_____) | |_\n | ~~~oOo~~~ | ~~~0oO~~~ |/__|\n _|====\\_=====|=====_/====|_ ||\n |_|\\_________ O _________/|_|||\n ||//////////|_|\\\\\\\\\\\\\\\\\\\\|| ||\n || || |\\_\\\\ || ||\n ||/|| \\\\_\\\\ ||/||\n ||/|| \\)_\\) ||/||\n || || \\ O / || ||\n || \\ / || LGB\n\n \\________/======\n / ( || ) \\\\You can expand all by running this in your browser console:(()=>{constreadmeDiv=document.getElementById(\"readme\");constdetailsElements=readmeDiv.getElementsByTagName(\"details\");for(leti=0;i/must be provided, as shown in the example below:importmlflowimportmlflow.pyfuncclassMod(mlflow.pyfunc.PythonModel):defpredict(self,ctx,inp):return7exp_name=\"myexp\"mlflow.create_experiment(exp_name,artifact_location=\"oss://mlflow-test/\")mlflow.set_experiment(exp_name)mlflow.pyfunc.log_model('model_test',python_model=Mod())In the example provided above, thelog_modeloperation creates three entries in the OSS storageoss://mlflow-test/$RUN_ID/artifacts/model_test/, the MLmodel file\nand the conda.yaml file associated with the model."} +{"package": "xknx", "pacakge-description": "XKNX - An asynchronous KNX library written in PythonDocumentationSee documentation at:https://xknx.io/HelpWe need your help for testing and improving XKNX. For questions, feature requests, bug reports either open anissue, join theXKNX chat on Discordor write anemail.DevelopmentYou will need at least Python 3.9 in order to use XKNX.Setting up your local environment:Install requirements:pip install -r requirements/testing.txtInstall pre-commit hook:pre-commit installTestingTo run all tests, linters, formatters and type checker calltoxRunning only unit tests is possible withpytestRunning specific unit tests can be invoked by:pytest -vv test/management_tests/procedures_test.py -k test_nm_individual_address_serial_number_write_failHome-AssistantXKNX is the underlying library for the KNX integration inHome Assistant.Example\"\"\"Example for switching a light on and off.\"\"\"importasynciofromxknximportXKNXfromxknx.devicesimportLightasyncdefmain():\"\"\"Connect to KNX/IP bus, switch on light, wait 2 seconds and switch it off again.\"\"\"asyncwithXKNX()asxknx:light=Light(xknx,name='TestLight',group_address_switch='1/0/9')awaitlight.set_on()awaitasyncio.sleep(2)awaitlight.set_off()asyncio.run(main())AttributionsMany thanks toWeinzierl Engineering GmbHandMDT technologies GmbHfor providing us each an IP Secure Router to support testing and development of xknx."} +{"package": "xknxproject", "pacakge-description": "(X)KNX ProjectExtracts KNX projects and parses the underlying XML.This project aims to provide a library that can be used to extract and parse KNX project files and read out useful information including the group addresses, devices, their descriptions and possibly more.DocumentationCurrently, xknxproject supports extracting (password protected) ETS 4, 5 and 6 projects and can obtain the following information:Areas, Lines, Devices and their individual address and channelsCommunicationObjectInstance references for their devices (GA assignments)Group Addresses and their DPT type if setThe application programs communication objects, their respective flags and the DPT TypeLocation information of devices (in which rooms they are)Functions assigned to roomsCaution: Loading a middle-sized project with this tool takes about 1.5 seconds. For bigger projects this might as well be >3s.Not all supported languages are included in project / application data. If the configured language is not found, the default language will be used - which is manufacturer / product dependent.Installationpip install xknxprojectUsage\"\"\"Extract and parse a KNX project file.\"\"\"fromxknxproject.modelsimportKNXProjectfromxknxprojectimportXKNXProjknxproj:XKNXProj=XKNXProj(path=\"path/to/your/file.knxproj\",password=\"password\",# optionallanguage=\"de-DE\",# optional)project:KNXProject=knxproj.parse()The resultingKNXProjectis a typed dictionary and can be used just like a dictionary, or can be exported as JSON.\nYou can find an example file (exported JSON) in our test suite underhttps://github.com/XKNX/xknxproject/tree/main/test/resources/stubsThe full type definition can be found here:https://github.com/XKNX/xknxproject/blob/main/xknxproject/models/knxproject.py"} +{"package": "xkpa", "pacakge-description": "UNKNOWN"} +{"package": "xkpassgen", "pacakge-description": "xkpassgen is now xkcd_passThis package has been renamed. Usepip install xkcd_passinstead.New package:https://pypi.org/project/xkcd_pass/"} +{"package": "xktools", "pacakge-description": "\"\"\"\n##\u672c\u6a21\u5757\u9700\u8981\u5916\u90e8\u4f9d\u8d56\u7684\u5e93\npip install xlrd \u8bfb\u6570\u636e\uff0c\u52a0\u5feb\u901f\u5ea6\npip install openpyxl \u8bfb\u6570\u636e\u548c\u5199\u6570\u636e\uff0c\u4e3b\u8981\u7528\u4e8e\u6587\u4ef6\u4fdd\u5b58\npip install pymysql MySQL\u6570\u636e\u5e93\u652f\u6301\uff1b\u5982\u679c\u53ea\u662f\u672c\u5730SQLite\u4e0d\u9700\u8981\npip install xktools\n\"\"\"\n\"\"\"\n##\u5b9e\u73b0\u76ee\u6807\uff1a\n\u81ea\u52a8\u5bf9Excel\u8868\u683c\u8fdb\u884c\u6570\u636e\u5e93\u5bfc\u5165\u548c\u5bfc\u51fa\uff0c\u6570\u636e\u52a0\u5de5\u3001Excel\u6c47\u603b\u3001\u5206\u53d1\uff0c\u4e3b\u8981\u5b9e\u73b0\u81ea\u52a8\u5bf9\u5e94\u5b57\u6bb5\u3002\n##\u5b9e\u73b0\u601d\u8def\uff1a\n\u4e3a\u4e86\u4fbf\u4e8e\u5904\u7406\u6570\u636e\uff0c\u628aExcel\u5206\u4e3a\u57fa\u7840\u8868\u548c\u6c47\u603b\u8868\u3002\u901a\u8fc7\u6570\u636e\u5e93\u5bf9\u57fa\u7840\u8868\u8fdb\u884c\u5904\u7406\uff0c\u6c47\u603b\u901a\u8fc7Excel\u81ea\u8eab\u529f\u80fd\u5b9e\u73b0\uff0c\u7b80\u5316\u5bf9Excel\u7684\u5904\u7406\u3002\n\u57fa\u7840\u8868\uff0c\u683c\u5f0f\u4e3a\u7b2c\u4e00\u884c\u6570\u636e\u7c7b\u578b\uff08\u6587\u672c\u3001\u6570\u5b57\u3001\u5927\u6587\u672c\uff09\uff0c\u7b2c\u4e8c\u884c\u4e3a\u5b57\u6bb5\u540d\u79f0\u3010\u53ef\u4ee5\u81ea\u5b9a\u4e49\uff0c\u9700\u8981\u8bbe\u7f6e\u5b57\u6bb5\u7c7b\u578b\u548c\u5b57\u6bb5\u540d\u79f0\u3011\u3002\n\u6570\u636e\u6c47\u603b\uff0c\u57fa\u4e8e\u57fa\u7840\u8868\u91c7\u7528Excel\u7684\u6c47\u603b\u529f\u80fd\uff0c\u901a\u8fc7\u6a21\u7248\u63d0\u524d\u8bbe\u7f6e\u597d\u6570\u636e\u6c47\u603b\uff0c\u53ea\u66f4\u65b0\u57fa\u7840\u8868\u5373\u53ef\uff0c\u4e5f\u53ef\u4ee5\u5728\u6570\u636e\u5e93\u4e2d\u6c47\u603b\u597d\uff0c\u76f4\u63a5\u5bfc\u51fa\u7ed3\u679c\u3002\n\u6839\u636eExcel\u8bbe\u7f6e\uff0c\u81ea\u52a8\u751f\u6210\u521b\u5efa\u8868\u3001\u63d2\u5165\u6570\u636e\u3001\u8bfb\u53d6\u6570\u636e\u7684SQL\uff0c\u5bfc\u5165\u6570\u636e\u5e93SQLite\uff08MySQL\uff09\uff0c\u811a\u672c\u81ea\u52a8\u6839\u636e\u5b57\u6bb5\u6240\u5728\u7684\u4f4d\u7f6e\u5b9a\u4f4d\u3002\n\u5230\u5982\u6570\u636e\u5e93\u4e4b\u540e\uff0c\u5728\u6570\u636e\u5e93\u4e2d\u5b58\u653e\uff0c\u52a0\u5de5\uff0c\u53ef\u4ee5\u6839\u636e\u6a21\u7248\u5bfc\u51fa\u5230Excel\uff0c\u4e0d\u53d7\u5b57\u6bb5\u6240\u5728\u884c\u5217\u9650\u5236\u3002\n\u53ef\u4ee5\u5b9e\u73b0\u5bf9Excel\u6c47\u603b\u5408\u5e76\u3001\u5206\u53d1\u62c6\u5206\u3002\n\u4e0d\u540c\u4eba\u4e4b\u95f4\uff0c\u786e\u5b9a\u660e\u786e\u7684\u5bf9\u5e94\u683c\u5f0f\uff0c\u4e0d\u8bba\u662f\u5982\u4f55\u66f4\u65b0\u8868\u683c\u5f0f\uff0c\u53ea\u8981\u5b57\u6bb5\u5217\u540d\u79f0\u4e0d\u53d8\uff0c\u5c31\u53ef\u4ee5\u8fdb\u884c\u5bf9\u5e94.Excel\u4e4b\u95f4\u53ea\u4f20\u9012\u57fa\u7840\u8868\n\u5176\u4ed6\u7684\u8868\uff0c\u91c7\u7528\u81ea\u52a8\u6c47\u603b\u7684\u6a21\u5f0f\u3002\u4e3a\u4e86\u7b80\u5316\uff0c\u91c7\u7528SQLite\u8fdb\u884c\u6570\u636e\u4ea4\u6362\n\"\"\""} +{"package": "xk-user", "pacakge-description": "eds sdk for python"} +{"package": "xk-utils", "pacakge-description": "xk-utilsxk-utils\u5b58\u653e\u661f\u77ff\u516c\u7528\u6a21\u5757\uff0c\u5305\u62ec\u90ae\u4ef6\u6a21\u5757, \u65e5\u5fd7\u6a21\u5757\u7b49\u6253\u5305python3-mpipinstall--upgradebuild\npython3-mbuild\u53d1\u5e03pipinstall--upgradetwine\npython3-mtwineupload--repositorypypidist/*\u5b89\u88c5pipinstallxk-utils\u4f7f\u75281\u3001\u53d1\u9001\u90ae\u4ef6fromxk_utils.mailimportMailProducerredis_config={'host':'127.0.0.1','port':6379,'password':'****','db':99}# \u5b9a\u4e49\u90ae\u4ef6key\uff0c \u5728\u670d\u52a1\u7aef\u9700\u8981\u914d\u7f6e\u76f8\u5173\u6536\u4ef6\u4eba\uff0c \u90ae\u4ef6\u6807\u9898m=MailProducer(key='log',**redis_config)m.send(f'<\u90ae\u4ef6\u5185\u5bb9>')2\u3001\u8bb0\u5f55\u65e5\u5fd7# \u8bb0\u5f55\u6587\u4ef6\u65e5\u5fd7importosfromxk_utils.loggerimportget_loggerlogger=get_logger('log','werkzeug',write_file=True,file_path=os.path.join(os.path.dirname(__file__),'log'))logger.info(\"\u8bb0\u5f55\u6587\u4ef6\")# \u8bb0\u5f55\u53ef\u4ee5\u53d1\u9001\u90ae\u4ef6\u7684\u65e5\u5fd7logger=get_logger('log','celery',send_mail=True,host='127.0.0.1',port=6379,password='****',db=99)logger.info('\u8fd9\u662f\u4e00\u6761\u6b63\u5e38\u65e5\u5fd7\uff0c \u4e0d\u53d1\u9001\u90ae\u4ef6')logger.error('\u8fd9\u662f\u4e00\u6761\u9519\u8bef\u65e5\u5fd7\uff0c \u53d1\u9001\u90ae\u4ef6\uff0c \u90ae\u4ef6\u8054\u7cfb\u4eba\u3001\u6807\u9898\uff0c\u8bf7\u5728\u670d\u52a1\u5668\u7aef\u914d\u7f6e\uff0c key=')"} +{"package": "xkwformat", "pacakge-description": "No description available on PyPI."} +{"package": "xkwpy", "pacakge-description": "No description available on PyPI."} +{"package": "xkye", "pacakge-description": "IntroducingXkye-Pythonstandard library to provide objective query builder forxkyelanguage. You can easily query the entities from the xkye file using this library. It provides a more convenient and idiomatic way to write and manipulate queries.InstallationInstall library with pypi:$pip3installxkyeUsagefromxkyeimportIOasio#initiate the xkye with iox=io(filename.xky)#read the contents of the filex.read()#get the output of any of the entity from teh xky file\n#to get the value of the entityx.get(\"entityname\")#to get the value of the entity in the given clutchx.get(\"entityname\",\"clutchname\")#to get the value of the entity in the given cluth's spanx.get(\"entityname\",\"clutchname\",clutchspan)#to get the span count of the given clusterx.getSpan(\"clustername\")ExamplesPlease use theexamplesdirectory to see some complex examples using xkye-pyhton library. For details about xkye syntax and format, use the officalXkye-langdocumentation.DocumentationDocumentation is available atxkye-python.readthedocs.io.Version matrixXkye versionXkye-Python Library version>= 1.0.0>= 1.0.0Upcoming features on or before v2.0.0Ability to get the span limit of the given cluster (Completed)Ability to add entity, clutch and subclutchContribution GuideWant to hack on Xkye-Python? Awesome! We haveContribution-Guideon our official repo. If you are not familiar with making a pull request using GitHub and/or git, please readthis guide. If you\u2019re looking for ways to contribute, please look at ourissue tracker.LicenseXkye-python is open-source standard python library for xkye language that is released under the MIT License. For details on the license, see theLICENSEfile.If you like this library, help me to develop it by buying a cup of coffee"} +{"package": "xl", "pacakge-description": "xlParsing google resultsTo install:pip install xl"} +{"package": "xl2csv", "pacakge-description": "Excel to CSV ConverterA tool to convert an Excel file consisting of multiple worksheets to individual CSV files."} +{"package": "xl2dict", "pacakge-description": "Introductionxl2dict is a python module to convert spreadsheets in to python dictionary. The input is a spreadsheet (xls or xlsx)\nand the output is a list of dictionaries. The first row in the spreadsheet is treated as the header rows and each of the\ncells in the first row assumes the keys in the output python dictionary. This python module will also enable the user\nto seamlessly search for a data row in the speadsheet by specifying keyword / keywords . All the data rows containing\nthe specified keyword in any of their cells will be returned. This behavior is extremely useful in implementing\ndata driven and keyword driven tests and also in implementing object repositories for most opensource test automation\ntools.This module will also enable the users to write data in to spreadsheet rows matching a\nspecified keyword / keywords, a feature that can be used to store dynamic data between dependent tests.InstallationTo install xl2dict, type the following command in the command line$pipinstallxl2dictQuickstart1. convert_sheet_to_dict()This method will convert excel sheets to dict. The input is path to the excel file or a sheet object.\nif file_path is None, sheet object must be provded. This method will convert only the first sheet.\nIf you need to convert multiple sheets, please use the method fetch_data_by_column_by_sheet_name_multiple() and\nfetch_data_by_column_by_index_multiple().If you need to filter data by a specific keyword, specify the dict in\nfilter_variables_dict like {column name : keyword} . Any rows that matches the keyword in the specified column\nwill be returned. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.convert_sheet_to_dict(file_path=\"Users/xyz/Desktop/myexcel.xls\", sheet=\"First Sheet\",\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})2. fetch_data_by_column_by_sheet_name()This method will convert the specified sheet in the excel file to dict. The input is path to the excel file .\nIf sheet_name is not provided, this method will convert only the first sheet.\nIf you need to convert multiple sheets, please use the method fetch_data_by_column_by_sheet_name_multiple() or\nfetch_data_by_column_by_sheet_index_multiple(). If you need to filter data by a specific keyword,\nspecify the dict in filter_variables_dict like {column name : keyword} . Any rows that matches the keyword in\nthe specified column will be returned. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.fetch_data_by_column_by_sheet_name(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_name=\"First Sheet\",\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})3. fetch_data_by_column_by_sheet_index()This method will convert the specified sheet in the excel file to dict. The input is path to the excel file .\nIf sheet_index is not provided, this method will convert only the first sheet.\nIf you need to convert multiple sheets, please use the method fetch_data_by_column_by_sheet_name_multiple() or\nfetch_data_by_column_by_sheet_index_multiple(). If you need to filter data by a specific keyword,\nspecify the dict in filter_variables_dict like {column name : keyword} . Any rows that matches the keyword in\nthe specified column will be returned. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.fetch_data_by_column_by_sheet_index(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_index=1,\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})4. fetch_data_by_column_by_sheet_name_multiple()This method will convert multiple sheets in the excel file to dict. The input is path to the excel file .\nIf sheet_names is not provided, this method will convert ALL the sheets.If you need to filter data by a specific\nkeyword / keywords, specify the dict in filter_variables_dict like {column name : keyword} .\nAny rows that matches the keyword in the specified column will be returned. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.fetch_data_by_column_by_sheet_name_multiple(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_names=[\"First Sheet\",\"Some other sheet\"],\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})5. fetch_data_by_column_by_sheet_index_multiple()This method will convert multiple sheets in the excel file to dict. The input is path to the excel file .\nIf sheet_indices is not provided, this method will convert ALL the sheets.If you need to filter data by a\nspecific keyword / keywords, specify the dict in filter_variables_dict like {column name : keyword} .\nAny rows that matches the keyword in the specified column will be returned. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.fetch_data_by_column_by_sheet_index_multiple(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_indices=[0,1,4,7],\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})6. fetch_matching_data_row_indices()This method will fetch all the rows matching the specified filter. The input is path to the excel file .\nIf sheet_name_index is not provided, this method will search the first sheet sheet. If you need to filter data\nby a specific keyword / keywords, specify the dict in filter_variables_dict like {column name : keyword} .\nAll the row indices that matches the keyword in the specified column will be returned. Multiple keywords can be\nspecified.Usage example:myxlobject= XlToDict()\nmyxlobject.fetch_matching_data_row_indices(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_name_index=\"First Sheet\",\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})\n\nmyxlobject.fetch_matching_data_row_indices(file_path=\"Users/xyz/Desktop/myexcel.xls\",\n sheet_name_index=5,\n filter_variables_dict={\"User Type\" : \"Admin\", \"Environment\" : \"Dev\"})7. write_data_to_column()This method will write data in to the specified column of all the rows matching the specified filter. The input\nis path to the excel file .If sheet_name is not provided, this method will write data in to the specified column\nin the first sheet sheet. If you need to write data in to rows by a specific keyword / keywords, specify the\ndict in filter_variables_dict like {column name : keyword} .The specified data will be written in the specified\ncolumn in all rows that matches the keyword. Multiple keywords can be specified.Usage example:myxlobject= XlToDict()\nmyxlobject.write_data_to_column(file_path=\"Users/xyz/Desktop/myexcel.xls\",column_name=\"Workorder Number\",\n data=\"999999999\", sheet_name=\"First Sheet\",\n filter_variables_dict={\"Test Case\" : \"Create Work Order\", \"Environment\" : \"Dev\"})"} +{"package": "xl2py", "pacakge-description": "An Excel (XL) 2 Python (Py) structure retriever for optimization. Convert the I/O of XL files into Python.DescriptionConvert an XL structure to Py and use any optimization algorithm of your willNow, with object-oriented formulasThe current project makes use of the XL COM interface (win32com library) to:Read an objective function cellRecursively build its dependent structure as of its formulaThe XL structure is represented in Py as a dict() objectThe structure is referenced to as:dictobj[Workbook number as int][Worksheet number as int][Row as int][Column as int]Whereby it handles:multi-XL workbook/worksheet referencessingle worksheet multirange retrievalXL cell formulas are translated toobject orientedcalculation blocks (no moreevalsas of this update).The calculation structure is determinded by cell-dependency trees, which have been already stored during the conversion (2)Handling of circular referencesOngoing development: A simple evolutionary algorithm that runs based off the abovementioned structure.FeaturesConversion LibraryThe following XL functions can be currently handled by xl2py.\nxl2py is capable of undertakingsingle-cells,arraysandarray/matrix operationsStandard operators: +, -, /, *, ^Logical operators: <, >, <=, >=, <>, =IFAVERAGESTDEV.PTRANSPOSEABSMMULTIFERRORSUMCOUNTSQRTTackled in the latest updateNo moreevals-> formulas are object oriented (Calculation-, Formula- and Reference- and Numeric-Blocks)by-operand handlingOver the latest update development, by-operand handling of formulas took place of RPN (reverse-polish notation). For additional details, viz. github repositoryOn the wayObject serializationCVS outputsA conceptual example with corresponding XL file. (reach me for further assistance)InstructionsInstallationpipinstallxl2py==version_noExample: I/O object creationimportxl2pyBuilder=xl2py.builder()# creates a xl2py builder object# place the path of your XL filepath=r'C:\\\\User\\\\DEFAULT\\\\WHATEVER\\\\...'# define your XL file password (if it exists)pwd='password'# opens up a XL COM interface and attach it to the Builder objectBuilder.connect_com(path,pwd)# declare your input cell/range referencesinputs=xl2py.xlref(,\\,)# inputs include other inputs to the xlref objectinputs+=xl2py.xlref(,,)# output must be a single cell referenceoutput=xl2py.xlref(,,)# Now you are all set. You shall translate the XL structure to python.Builder.set_structure(inputs,output)# If you want to change the input cell/range values...# vals must be of the shape of the inputs# and must be parsed as a list of lists or numpy arraysBuilder.set_input_values(vals)# grab the output (objective fun) value as numpy arrayoutput_val=Builder.get_output_value()# Grab the new output valueYou can find me @ Gabriel S. Gusm\u00e3o https://www.researchgate.net/profile/Gabriel_Gusmaohttps://github.com/gusmaogabriels"} +{"package": "xl2roefact", "pacakge-description": "RENware Software Systemsxl2roefactPentru accesul la toate link-urile din acest document vizitatisite-ul dedicat:https://invoicetoroefact.renware.eu/acestui sistem.FacilitatiAceasta componenta este \"totul despre crearea de facturi electronice\" din formatul Excel office (xlsx). Aplicatia poate genera factura in format JSON, XML, PDF si o poate incarca in sistemulRO E-Fact[^ld_roefact].Aceasta componenta ofera urmatoarele facilitati (acestea fiind obiectivele fundamentale ale componentei):transformarea facturilor din Excel in formatulXMLcerut de catre sistemul ANAF RO E-Fact pentru incarcareincarcarea acestorain sistemul ANAF RO E-Fact[^ld_roefact]transformarea facturilor din Excel intr-un formatJSONintermediar, independent de platforma si care permite integrarea acestora cu alte sisteme (standardREST)generarea facturii in format PDFpentru transmiterea acesteia catre client, semnarea electronica, tiparirea si arhivarea acesteia in format fizic (in general manipularea facturii in format\"human readable\")Componenta ofera doua instrumente pentru realizarea si indeplinirea acestor obiective:xl2roefactoaplicatie de tip linie de comanda(disponibila pentru sistemele de operare Windows, Linux si MacOS)xl2roefact PyPioblioteca standard Pythonutilizabila pentru dezvoltari proprii in scopul extinderii altor sisteme existente (custom development)Instalarea aplicatiei xl2roefactPachetele de instalare suntdisponibile aici.\nPachetele disponibile contin in numele lor versiunea de aplicatie utilizata si sistemul de operare pentru care sunt disponibile:MSIpachet instalare pentruWindowsDEBpachet instalare pentruLinux Debian(verificati disponibilitatea pentru varianta sistemului de operare folosit de dvs)EXEexecutabilWindows in format \"portabil\" (un singur fisier)NOTA 1:pentru echivalent utilizareportabila pentru Linuxse va instala biblioteca Python (vezi sectiuneaxl2roefact PyPi library) dupa care devine utilizabil scriptul Python \"ca orice alta comanda Linux\"NOTA 2:pachetulMSIpentruWindowseste disponibil in orice variante / versiuni al sistemului. Optiunile pentruLinuxsunt mult mai flexibile si astfel celelalte pot lipsi insa pot fi disponibile graruit, la cerere.Configurarea aplicatiei xl2roefactParametrii de configurare a plicatiei se gasesc in fisierulconfig_settings.py. Acestia sunt sub elaborati in limbaj Python prin utilizarea conventiilor de constante conform recomandarilor PEP (numele capitatlizat) si sunt acompaniti de linii de explicatii privind aplicabilitatea lor.Configurare aplicatiei se poate face interactiv si din aplicatie. Pentru a obtine help referitor la detaliile comenzi se va folosixl2roefactsettings--helpComenzile aplicatieiInterfata aplicatie este realizata utilizind conventiile si practicile uzuale pentru aplicatii tip linie de comanda consola. Pentru informatii privind comenzile se poate folosi optiunea dehelp, dispobilia atit la nivelul general:xl2roefact--helpcit si la nivel detaliat pentru fiecare comandaxl2roefact[COMMAND]--helpLista comenzilor:about- Afiseaza informatii despre aceatsa aplicatie (copyright, scop, etc)settings_ Afiseaza parametrii de configurare a aplicatiei.Vezi sectiunea de configurare a aplicatieixl2json- Transforma fisierul (fisierele) Excel in forma JSON pentru utilizare ulterioara ca forma de date standardizat pentru schimbul de informatii cu alte sisteme electroniceComenzile detaliate:::: mkdocs-typer\n:module: xl2roefact.app_cli\n:command: app_cli\n:prog_name: xl2roefact\n:depth: 2Practici si regului referitoare la continutul facturilor din ExcelAcest capitol se refera la modul in care este \"tratat\" continutul fisierului Excel cu factura, mai exact la modalitatea in care informatia facturii este cautata, identificata si gasita in scopul de a fi salvata in oricare din formatele de \"factura electronica / E-Fact\".Utilizarea sablonului de factura Excel ce este livrat impreuna cu aplicatiaESTE O VARIANTA DE LUCRU RECOMANDATA, dar nu obligatorie. Chiar si in cazul utilizarii acestuia, prin modificarea \"structurii\" acestuia, informatia poate ajungenerecognoscibila / neidentificabilatotal sau partial daca nu sunt urmate regulile expuse.In general trebuie facuta diferenta intre datele facturii si modul in care aceasta va fi tiparita (va aparea la tiparire / previzualizare).Mai exactcontinutul informationalal facturii nu trebuie nici confundat si nici mixat cuformatul de afisare al acesteia(layout). Pentru acesta din urma se recomanda a fi folosite cu precadereregulile de formataredin Excel si nu cele stocare a datelor. Un exemplu este un numar zecimal oarecare unde:una este valoarea introdusa intr-o celula (de ex cu 3 zecimale) sialta este valoarea afisata (cu 2 zecimale) - aceasta din urma trebuie obtinuta prin formatarea celulei respective de a afisa 2 zecimale prin rotunjire insa valoarea efectiva trebuie sa fie cea originala cu 3 zecimale, lucru (diferenta) care se poate vedea la editarea continutului celulei.Tutorial utilizare aplicatieOrganizarea informatieiAplicatiaxl2roefact\"promoveaza\" structurarea informatiei procesate astfel incit sa fie evitata situatia\"de aglomerare\" a directorului curent cu fisierece trebuiesc identificate si izolate in situatia in care se facprocesari in masa(pe mai multe fisiere / facturi sursa).Astfel, aplicatia se asteapa ca fisierele Excel sursa (adica facturile de procesat) sa fie copiate in directorulinvoice_files/de unde vor fi citite si tot aici vor fi create fisierele rezultate (JSON, XML, etc). Acest director este relativ la directorul curent de unde este lansata aplicatia si considerat\"implicit\"cu acest nume dar daca se doreste un alt director acest lucru poate fi facut folosind parametrul--files-directory(sau prescurtat-d) la lansarea aplicatiei astfel:xl2roefact-d\"calea si numele directorului dorit\"!!! note \"Nota\"\nGhilimelele sunt necesare numai daca numele si calea (path) contin caracterul spatiu.Exemple:pentru stabilirea directorului curent ca sursa pentru fisierele factura Excel:xl2roefact-d./procesarea tuturor facturilor facturilor din lunaiunie, copiate intr-un director dedicat sub directorul curent:xl2roefact-d./facturi_iunie/Exemplu de procesare a unei facturise creaza directorul recomandat pentru stocarea facturilor in Excel:mdinvoice_filesse copiaza facturafactura_A.xlsxin acest director apoi se revine in directorul anterior daca acesta a fost schimbat pentru efectuarea copieriise lanseaza aplicatia:xl2roefactxl2jsonIn urma acestor operatii, in directorulinvoice_filesvor rezulta:invoice_files/\n factura_A.xlsx # fisierul Excel original\n factura_A.json # fisierul JSON rezultat in urma procesariifactura_A.xlsxca fiind fisierul Excel original cu facturafactura_A.jsonacesta fiind fisierul format JSON rezultat in urma procesarii si ce poate fi folosit pentru interschimbarea electronica a informatiei intre sistemeAspecte tehnice referitoare la formatul fisierului JSON aferent facturiiAcest fisier este cel generat de catre aplicatie in urma executiei acesteia cu comandaxl2json. Formatul JSON are urmatoarra structura de baza:{\"Invoice\":{...},\"meta_info\":{...},\"excel_original_data\":{...}}Cheile de la primul nivel contin:Invoice- datele efective ale facturiimeta_infoinformatii referitoare la procesarea facturii si mapa de conversie a cheiiInvoicedin formatulJSONin formatulXMLcerut de sistemulRO E-Factharta de ajutor in conversia formatului JSON in formatul XML acceptat de sistemul RO E-Fact (cheiemeta_info.map_JSONkeys_XMLtags) si definititiile XML aferente (cheiemeta_info.invoice_XML_schemes)alte informatii despre fisierul Excel prelucrat (numele, worksheet cu factura, data si ora procesarii, CRC pentru verificare, etc)excel_original_data- informatiile originale din fisierul Excel, asa cum au fost ele identificate si gasite precum si locatia (adresele celulelor). Aceste informatii sunt utile in cazul in care exista neclaritati in urma procesuluicde conversie pentru \"a intelege\" de unde si cum arata informatiile originale din fisierul ExcelPentru detalii suplimentare despre formatul JSON trebyie consultata componenta referitoare labibliotecaxl2roefactdestinata dezvoltarii software.Descarcare (download) aplicatie xl2roefact CLIPachet instalare aplicatie WindowsPachet instalare script PythonDate identificarepart number (p/n):0000-0095-xl2roefactproducator si copyright: RENWare Software Systemsauthor: Petre Iordanescu (petre.iordanescu@gmail.com)LicenseNote[^ld_roefact]: Toate interactiunile cu sistemulANAF RO E-Factnecesita oconexiune la internetsi un set decredentiale ANAF RO E-Fact ale companieipentru care se incarca factura. In lipsa acestora, fisierulXMLgenerat de aplicatie poate fi incarcat ulterior (de ex de catre departmentul contabilitate)"} +{"package": "xl2sitemap", "pacakge-description": "Excel to Sitemap (xl2sitemap)Xl2sitemapis a command line tool to generate sitemaps using data in an excel sheet. Xl2sitemap reads data from an excel sheet and converts the data intoSEO friendlysitemaps that can be submitted to search engines directly after uploading.Generates a .xml fileGenerates a .xml.gz file (compressed)Gives you flexibility with the number of urls in a single fileNew Features!Ability to create multiple sitemaps based on classifiers. Classifiers are nothing but different groups for which it is ideal to create different sitemaps. This makes it easier forindexation problem debuggingas mentioned on the blogXML Sitemapsby MozYou can also:Add attributes such as priority, changefreq, lastmod to your urlsetsRequirementsDillinger uses a number of open source projects to work properly:Python 3- Python 3 and aboveA well structured excel file with appropriate column names as mentioned belowStructuring your excel sheetThe columnurlis acompulsory columnin your excel sheet. This contains the urls of your websiteTheclassifiercolumn is an optional column. This contains the classifier based on which the sitemap file will be split into multiple files. If you are including this column in your excel sheet, make sure you use the-cflagThelastmodcolumn is an optional column. This contains the last modified date of the corresponding url in DD/MM/YYYY format. If you are including this column in your excel sheet, make sure you use the-lflagThechangefreqcolumn is an optional column. This contains the last change frequency of the corresponding url. If you are including this column in your excel sheet, make sure you use the-fflagTheprioritycolumn is an optional column. This contains the priority of the corresponding url. If you are including this column in your excel sheet, make sure you use the-pflagInstallationInstallation of xl2sitemap requires running the following command form your command line utilitypip install xl2sitemapRunning from command lineRunning xl2sitemap with the basic default configuration requires running the following commandxl2sitemap example-input.xlsxTheexample-input.xlsxcan be any excel sheet with the appropriate columns in itOther options that can be enabled areFlagUsage-fWill addtag in your sitemap-pWill addtag in your sitemap-lWill addtag in your sitemap-cWill split sitemap into multiple files based on the classifier column-m 50000Will add a maximum of 50,000 urls only in a single sitemap. If urls are greater than 50,000 then multiple files will be generatedExamplexl2sitemap example-input.xlsx -m 40000 -p -f -lThis will generate sitemaps with 40,000 urls in each file with,,attributes for each.DevelopmentWant to contribute? Great!\nOpen your favorite Terminal and run these commands.git clone https://github.com/antiproblemist/excel-to-sitemap.gitLicenseBSD 3-ClauseAuthorFollow the author onLinkedinFree Software, Hell Yeah!"} +{"package": "xl2times", "pacakge-description": "No description available on PyPI."} +{"package": "xl3335currency", "pacakge-description": "MGGY-8411-HW1This package is for currency convertion and calculation.Installtion$ pip install xl3335currencyAUDUSD_returnDefine the AUDUSD_return class - each instance will store one row from the dataframe.GBPEUR_returnDefine the GBPEUR_return class - each instance will store one row from the dataframe.USDCAD_returnDefine the USDCAD_return class - each instance will store one row from the dataframe.portfolioThis class defies a nobject for keeping track of our current investments/profits for each currency pair."} +{"package": "xlab", "pacakge-description": "xLab is an experiment execution tool that automates tasks in research-oriented projects. It provides a simple interface that can be integrated to project executables with minimum modifications. xLab enables the following functionalities:Maintaining a folder structure for runs.Caching results saved after each run.Accessing cached results from a Python dictionary of arguments.Installationpip install xlabQuickstartRunxlab project initon the root directory of your project.Wrap the code of your executables within awithclause such that it resembles the following pattern:# Import libraries...importxlab.experimentasexp# ...parser=get_parser()withexp.setup(parser)assetup:args=setup.argsdir=setup.dir# Use args to run experiment and# dir as a directory to save results# ...Call your program either directly from the terminal or indirectly through another script.If you executable could be run on the terminal before using xLab, now you can continue running the program in the same way as before, but now with results cached and automatically saved in a folder structure.You can also run the executable within a Python script by using the following code structure:# Import libraries...importxlab.experimentasexp# ...e=exp.Experiment(executable,required_args,command)print(e.args)# Prints all arguments (both required and optional)# Modify e.args as you wish...e.run()"} +{"package": "xlab-util", "pacakge-description": "No description available on PyPI."} +{"package": "xladybug", "pacakge-description": "Debugger toolX|linkedinDebug your code with advance python module, get time of execution, parameters, returns and many more.Import:from xladybug import debugUsage for functions:@debug\ndef function():\n #your_codeUsage for variables:x = 10\ndebug(x)Usage for debugging:debug('here!')"} +{"package": "xl-aliyun-fc2", "pacakge-description": "OverviewThe SDK of this version is dependent on the third-party HTTP libraryrequests.Running environmentPython 3.6+InstallationInstall the official release version through PIP (taking Linux as an example):$pipinstallxl-aliyun-fc2You can also install the unzipped installer package directly:$sudopythonsetup.pyinstallGetting started# -*- coding: utf-8 -*-importfc2importzipfileimportbase64# To know the endpoint and access key id/secret info, please refer to:# https://help.aliyun.com/document_detail/52984.htmlclient=fc2.Client(endpoint='',accessKeyID='',accessKeySecret='')# Create service.client.create_service('demo')zipFileBase64=''withopen('file.zip','rb')asf:content=f.read()zipFileBase64=base64.b64encode(content).decode()# Create function.client.create_function('demo',{'functionName':'test_func','runtime':'python3','handler':'index.handler','code':{'zipFile':zipFileBase64},'environmentVariables':{'testKey':'testValue'}})# Invoke function synchronously.client.invoke_function('demo','test_func')More resourcesAliyun FunctionCompute docsContacting usLinksLicenseMIT"} +{"package": "xlambda-helper", "pacakge-description": "X-Lambda Helper (Python version)A Python library to help handle warm-up requests generated byX-Lambda.X-LambdapredictsAWS Lambdademand and keeps a fleet of containers warm to mitigate cold-start latency. Warm invocations sent by X-Lambda are received by a Lambda function, which needs to respond accordingly.ThisX-Lambda Helperproject helps to handle warm invocations in Python functions.RequirementsPython 3.6+AWS accountQuick startInstall X-Lambda Helper:pip install xlambda_helper.Decorate yourLambda handlerfollowing the example below:Deploy your code in AWS Lambda.Usage exampleimportxlambda_helper@xlambda_helper.warm()defhandler(event,context):# Your original code goes herex_men=[{'Charles':'Professor Xavier'},{'Logan':'Wolverine'},{'Jean':'Phoenix'},{'Scott':'Cyclops'}]returnx_menAboutX-Lambda Helper will be executed every time your handler is invoked by AWS Lambda. It will check whether the invocation is a warming request coming from X-Lambda. If not, it will run your handler code normally. If yes, it will short-circuit to return a default answer and will not execute the handler function.When handling warm requests, X-Lambda Helper will automatically adjust your function behavior:Check whether it was a cold startSleep for a period of time, if neededDefer to your original handler function, if invocation is not a warm request"} +{"package": "xlandsat", "pacakge-description": "Analyze Landsat remote sensing images using xarrayDocumentation(latest)\u2022Contributing(how you can help)\u2022CompGeoLabAboutxlandsatis Python library for loading and analyzing Landsat scenes\ndownloaded fromUSGS EarthExplorerwith\nthe power ofxarray.\nWe take care of reading the metadata from the*_MTL.txtfiles provided by\nEarthExplorer and organizing the bands into a singlexarray.Datasetdata\nstructure for easier manipulation, processing, and visualization.ExampleHere's a quick example of loading and plotting thisLandsat 9 scene from the city of Manaus, Brazil,\nwhich is where the Solim\u00f5es (brown water) and Negro (black water) rivers merge\nto form the Amazon river:importxlandsatasxlsimportmatplotlib.pyplotasplt# Download a sample Landsat 9 scene in EarthExplorer formatpath_to_scene_file=xls.datasets.fetch_manaus()# Load the data from the file into an xarray.Datasetscene=xls.load_scene(path_to_scene_file)# Make an RGB composite as an xarray.DataArrayrgb=xls.composite(scene,rescale_to=[0.02,0.2])# Plot the composite using xarray's plotting machineryrgb.plot.imshow()# Annotate the plot with the rich metadata xlandsat adds to the sceneplt.title(f\"{rgb.attrs['title']}\\n{rgb.attrs['long_name']}\")plt.axis(\"scaled\")plt.show()Project goalsLoading single scenes in the EarthExplorer format.Provide some calculation, like composites, but leave most of the rest to the\nuser and xarray.Our goal isnotto provide a solution for large-scale data processing.\nInstead, our target is smaller scale analysis done on individual computers.For cloud-based data processing, see thePangeo Project.For other satellites and more powerful features, useSatpy.Project statusxlandsat is ready for use but still changing.This means that we sometimes break backwards compatibility as we try to\nimprove the software based on user experience, new ideas, better design\ndecisions, etc. Please keep that in mind before you update xlandsat to a newer\nversion.We welcome feedback and ideas!This is a great time to bring new ideas on\nhow we can improve the project.\nSubmitissues on GitHub.LicenseThis is free software: you can redistribute it and/or modify it under the terms\nof theMIT License. A copy of this license is provided inLICENSE.txt."} +{"package": "xlang", "pacakge-description": "xlangThis is a python util package."} +{"package": "xlart", "pacakge-description": "Excel art generator"} +{"package": "xlatti", "pacakge-description": "No description available on PyPI."} +{"package": "xlavir", "pacakge-description": "xlavir - Informative Excel reports from viral sequencing Nextflow analysisExcel report from viral sequencing data analysis output from thenf-core/viralreconorCFIA-NCFAD/nf-virontusNextflowpipelines.UsageCreate an Excel report from a Nextflow pipeline run:# e.g. run nf-core/viralrecon Nextflow pipeline against SARS-CoV-2 samples# sequenced by Illumina using the ARTIC V4.1 protocolnextflowrunnf-core/viralrecon\\-profiledocker\\--inputsamplesheet.csv\\--platformillumina\\--protocolamplicon\\--genome'MN908947.3'\\--primer_setartic\\--primer_set_version'4.1'\\--skip_assembly\\--outdirviralrecon-results# create Excel report from Nextflow pipeline runxlavirviralrecon-resultsxlavir-report-viralrecon-results.xlsxSeeexample reportfrom test data intests/data/tools.FeaturesCollect sample results from anf-core/viralreconorCFIA-NCFAD/nf-virontusinto an Excel reportSamtoolsread mapping stats (flagstat)Mosdepthread mapping coverage informationVariant calling information (SnpEffandSnpSiftresults, VCF file\ninformation) from the following variant callersBcftoolsiVarMedakaNanopolishClair3Consensus sequencesQA/QC of sample analysis results (basic PASS/FAIL based on minimum genome\ncoverage and depth)Nextflowworkflow execution informationPrepend worksheets from other Excel documents into the report (e.g. cover\npage/sheet, sample sheet, lab results)Add custom images into worksheets with custom names and descriptions (e.g.\nphylogenetic tree figure PNG)LicenseDistributed under the terms of theMITlicense, \"xlavir\" is free and open\nsource software.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template."} +{"package": "xlayers", "pacakge-description": "xlayers: Python implementation of MITgcm\u2019s layer packagexlayers allows you to transform your data from a regular vertical grid (like depth) to a vertical grid defined based on contours of some variable (like density). xlayers uses FORTRAN code from the layers package of the MITgcm, which was written by Ryan Abernathey.We recommend using this package on xarrays, but it can also be applied to numpy\narrays. Thisexamplemay be helpful in getting started.Why a new vertical regridding package?xlayers has many advantages over other similar tools. It conserves the total quantity of the input variable in the water column: this is particularly important when performing volume or heat budgets in density space. xlayers outputs the thickness-weighted variable in density space, which makes thickness-weighted averaging easier. This output is mapped in a smooth and sensible way. xlayers is also very fast and parallelizable.Installationxlayers can be installed from PyPI with pip:python-mpipinstallxlayersIt is also available fromconda-forgefor conda installations:condainstall-cconda-forgexlayersTo install xlayers from source repository, the fortran-compiler package is required. The easiest way to install the fortran-compiler is viaconda:condainstall-cconda-forgefortran-compilerunsetLDFLAGSOnce the compiler is installed, now we can install xlayers from Github:gitclonehttps://github.com/cspencerjones/xlayers.gitcdxlayerspythonsetup.pyinstallFeaturesxlayers isproperty conserving, meaning that the total amount of your variable in the water column will not change when it is transformed into the new coordinate system.xlayers acheives this using binning: it bins the variable onto a much finer vertical grid, estimates the depth of the new coordinate surfaces, and adds up these bins in the new space.InputsThis package expects your initial coordinate system to be on a structured grid. i.e. it will not take density as an initial vertical variable, but depth is ok.Before runninglayers_xarray, you must runfinegridto define some of the binning parameters needed.finegridtakes 2 inputs (which should both be numpy arrays): the vertical depth of the gridcells, and the vertical distance between the centers of the grid cells. The second variable should be loneger by 1 than the first, because it includes the distance between the cell center of the top cell and the sea surface, and the distance between the cell center of the bottom cell and the domain bottom.The first two inputs tolayers_xarrayshould be on the same gridpoints.data_inis the variable to be remapped andtheta_inis the variable that defines the location of the new coordinate system.OutputsThe output oflayers_xarrayisthickness weighted, i.e. if the input variable is salinity, the output variable is the salinity in each layermultiplied by the depth of the layer. In order to get an output that has the same units as the input, divide by the thickness of the layer (which you can get by inputting an array of ones intolayers_xarrayinstead of you input variabledata_in).Get in touchReport bugs, suggest features or view the source codeon GitHub."} +{"package": "xlaz", "pacakge-description": "xlaz"} +{"package": "xl-bert", "pacakge-description": "DocumentationThis is the repository of the xl_bert package. This library helps you find sentence embedding for your sentence using SOTA language models such as Bert and XLNET.This library takes in an input seven paramters :\n\n**sentence_list,model_name,model_dir,token_model_dir,n_layers,strategy,max_len**. Each parameter has been explained below.\n\n**sentence_list** : List of sentences you want to get embedding of. \n\n**model_name** : Name of model which you want to use, currently can be 'bert' or 'xlnet'.\n\n**model_dir** : Directory path of pretrained/finetuned Bert/XLNet language model. Default is 'xlnet-base-cased'. Pretrained language models can be seen from here:\n\n\n`_\n\n\n**token_model_dir** : Directory path of tokenizer. Default is 'xlnet-base-cased'\n\n\n**n_layers** : Number of layers you want to use to get sentence embedding.Default is 1\n\n**Strategy** : This is where it gets interesting. Strategy is categorised in four choices.\n\n 'avg': We average each layer individually and then average n_layers.\n 'cat': We concatenate each layer individually, then we concatenate n_layers\n 'avgcat': We average each layer individually and then concat n_layers\n 'catavg': We concat each individual layer and then average n_layers. \n\n**max_len** : Maximum length of sentence you want. Default 50================\nInstallationpip install xl_bertUsage with Bert as well as XLNetget_sentence_embedding(['I am playing','let me dance'],model_name='xlnet',model_dir='xlnet- \nlarge-cased',token_model_dir='xlnet-large-cased',n_layers=2,strategy='avg',max_len=50)ContributionPackage author and current maintainer is Shivam Panwar (panwar.shivam199@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed, especially since this package is very much in its infancy.Created by Shivam Panwar (panwar.shivam199@gmail.com)"} +{"package": "xlb_nester", "pacakge-description": "UNKNOWN"} +{"package": "xlbridge", "pacakge-description": "XlBridge Python User LibraryXlBridge enables writing Excel user-defined formulas (UDFs) in C#, Python (or any programming language that\nsupports gRPC and protobufs).The XlBridge Python User Library provides the functionality to expose Python formulas to the XlBridge Excel add-in.The XlBridge Excel add-in is non-free software, seehttps://xlbridge.qaplix.sefor pricing and trial version availability."} +{"package": "xlcalculator", "pacakge-description": "Excel Calculatorxlcalculator is a Python library that reads MS Excel files and, to the extent\nof supported functions, can translate the Excel functions into Python code and\nsubsequently evaluate the generated Python code. Essentially doing the Excel\ncalculations without the need for Excel.xlcalculator is a modernization of thekoala2library.xlcalculatorcurrently supports:Loading an Excel file into a Python compatible stateSaving Python compatible stateLoading Python compatible stateIgnore worksheetsExtracting sub-portions of a model. \u201cfocussing\u201d on provided cell addresses\nor defined namesEvaluatingIndividual cellsDefined Names (a \u201cnamed cell\u201d or range)RangesShared formulasnot an Array FormulaOperands (+, -, /, *, ==, <>, <=, >=)on cells onlySet cell valueGet cell valueParsing a dict into the Model objectCode is in examples\\third_party_datastructureFunctions are at the bottom of this READMELNPython Math.log() differs from Excel LN. Currently returning\nMath.log()VLOOKUP\n- Exact match onlyYEARFRAC\n- Basis 1, Actual/actual, is only within 3 decimal placesNot currently supported:Array Formulas or CSE Formulas (not a shared formula):https://stackoverflow.com/questions/1256359/what-is-the-difference-between-a-shared-formula-and-an-array-formulaorhttps://support.office.com/en-us/article/guidelines-and-examples-of-array-formulas-7d94a64e-3ff3-4686-9372-ecfd5caa57c7#ID0EAAEAAA=Office_2013_-_Office_2019)Functions required to complete testing as per Microsoft Office Help\nwebsite for SQRT and LNEXPDBRun testsSetup your environment:virtualenv -p 3.10 ve\nve/bin/pip install -e .[test]From the root xlcalculator directory:ve/bin/py.test -rw -s --tb=nativeOr simply usetox:toxRun ExampleFrom the examples/common_use_case directory:python use_case_01.pyAdding/Registering Excel FunctionsExcel function support can be easily added.Fundamental function support is found in the xlfunctions directory. The\nfunctions are thematically organised in modules.Excel functions can be added by any code using thexlfunctions.xl.register()decorator. Here is a simple example:fromxlcalculator.xlfunctionsimportxl@xl.register()@xl.validate_argsdefADDONE(num:xl.Number):returnnum+1The@xl.validate_argsdecorator will ensure that the annotated arguments are\nconverted and validated. For example, even if you pass in a string, it is\nconverted to a number (in typical Excel fashion):>>>ADDONE(1):2>>>ADDONE('1'):2If you would like to contribute functions, please create a pull request. All\nnew functions should be accompanied by sufficient tests to cover the\nfunctionality. Tests need to be written for both the Python implementation of\nthe function (tests/xlfunctions) and a comparison with Excel\n(tests/xlfunctions_vs_excel).Excel number precisionExcel number precision is a complex discussion.It has been discussed in aWikipedia\npage.The fundamentals come down to floating point numbers and a contention between\nhow they are represented in memory Vs how they are stored on disk Vs how they\nare presented on screen. AMicrosoft\narticleexplains the contention.This project is attempting to take care while reading numbers from the Excel\nfile to try and remove a variety of representation errors.Further work will be required to keep numbers in-line with Excel throughout\ndifferent transformations.From what I can determine this requires a low-level implementation of a\nnumeric datatype (C or C++, Cython??) to replicate its behaviour. Python\nbuilt-in numeric types don\u2019t replicate behaviours appropriately.Unit testing Excel formulas directly from the workbook.If you are interested in unit testing formulas in your workbook, you can useFlyingKoala. An example on how can\nbe foundhere.TODODo not treat ranges as a granular AST node it instead as an operation \u201c:\u201d of\ntwo cell references to create the range. That will make implementing\nfeatures likeA1:OFFSET(...)easy to implement.Support for alternative range evaluation: by ref (pointer), by expr (lazy\neval) and current eval mode.Pointers would allow easy implementations of functions like OFFSET().Lazy evals will allow efficient implementation of IF() since execution\nof true and false expressions can be delayed until it is decided which\nexpression is needed.Implement array functions. It is really not that hard once a proper\nRangeData class has been implemented on which one can easily act with scalar\nfunctions.Improve testingRefactor model and evaluator to use pass-by-object-reference for values of\ncells which then get \u201cused\u201d/referenced by ranges, defined names and formulasHandle multi-file addressesImprove integration with pyopenxl for reading and writing filesexample of\nproblem spaceSupported FunctionsCompatibilityFunctionxlcalculatorPyCelformulasKoalaFLOORDate and TimeFunctionxlcalculatorPyCelformulasKoalaDATEDATEDIFDATEVALUEDAYDAYSEDATEEOMONTHHOURISOWEEKNUMMINUTEMONTHNOWSECONDTIMETIMEVALUETODAYWEEKDAYYEARYEARFRACEngineeringFunctionxlcalculatorPyCelformulasKoalaBIN2DECBIN2HEXBIN2OCTDEC2BINDEC2HEXDEC2OCTHEX2BINHEX2DECHEX2OCTOCT2BINOCT2DECOCT2HEXFinancialFunctionxlcalculatorPyCelformulasKoalaIRRNPVPMTPVSLNVDBXIRRXNPVInformationFunctionxlcalculatorPyCelformulasKoalaISBLANKISERRISERRORISEVENISNAISNUMBERISODDISTEXTNALogicalFunctionxlcalculatorPyCelformulasKoalaANDFALSEIFIFERRORIFSNOTORSWITCHTRUEXORLookup and referenceFunctionxlcalculatorPyCelformulasKoalaCHOOSECOLUMNCOLUMNSHLOOKUPINDEXINDIRECTLOOKUPMATCHOFFSETROWROWSVLOOKUPMath and TrigonometryFunctionxlcalculatorPyCelformulasKoalaABSACOSACOSHACOTACOTHARABICASINASINHATANATAN2ATANHCEILINGCEILING.MATHCEILING.PRECISECOSCOSHCOTCOTHCSCCSCHDECIMALDEGREESEVENEXPFACTFACTDOUBLEFLOOR.MATHFLOOR.PRECISEGCDINTISO.CEILINGLCMLNLOGLOG10MODMROUNDODDPIPOWERRADIANSRANDRANDBETWEENROMANROUNDROUNDDOWNROUNDUPSECSECHSIGNSINSINHSQRTSQRTPISUMSUMIFSUMIFSSUMPRODUCTTANTANHTRUNCStatisticalFunctionxlcalculatorPyCelformulasKoalaAVERAGEAVERAGEAAVERAGEIFAVERAGEIFSCOUNTCOUNTACOUNTBLANKCOUNTIFCOUNTIFSLARGELINESTMAXMAXAMAXIFSMINMINAMINIFSSMALLTextFunctionxlcalculatorPyCelformulasKoalaCONCATCONCATENATEEXACTFINDLEFTLENLOWERMIDREPLACERIGHTTRIMUPPERVALUECHANGES0.5.0 (2023-02-06)Added support for Python 3.10, dropped 3.8.Upgraded requirements.txt to latest versions.yearfrac==0.4.4was incompatible with latest setuptools.openpyxlhad API changes that were addressed and tests fixed.0.4.2 (2021-05-17)Make sure that decimal rounding is only set in context and not system wide.0.4.1 (2021-05-14)Fixed cross-sheet references.0.4.0 (2021-05-13)Passignore_hiddenfromread_and_parse_archive()toparse_archive()Add Excel tests forIF().AddNOT()function.ImplementedBIN2OCT(),BIN2DEC(),BIN2HEX(),OCT2BIN(),OCT2DEC(),OCT2HEX(),DEC2BIN(),DEC2OCT(),DEC2HEX(),HEX2BIN(),HEX2OCT(),HEX2DEC().Drop Python 3.7 support.0.3.0 (2021-05-13)Add support for cross-sheet references.Make*IF()functions case insensitive to properly adhere to Excel specs.Support for Python 3.9.0.2.13 (2020-12-02)Add functions:FALSE(),TRUE(),ATAN2(),ACOS(),DEGREES(),ARCCOSH(),ASIN(),ASINH(),ATAN(),CEILING(),COS(),RADIANS(),COSH(),EXP(),EVEN(),FACT(),FACTDOUBLE(),INT(),LOG(),LOG10().RAND(),RANDBETWRRN(),SIGN(),SIN(),SQRTPI(),TAN()0.2.12 (2020-11-28)Add functions:PV(),XIRR(),ISEVEN(),ISODD(),ISNUMBER(),ISERROR(),FLOOR(),ISERR()Bugfix unary operator needed to be right associated to handle cases of\ndouble use eg; double-negative.. \u20134 == 40.2.11 (2020-11-16)Add functions:DAY(),YEAR(),MONTH(),NOW(),WEEKDAY()EDATE(),EOMONTH(),DAYS(),ISOWEEKNUM(),DATEDIF()FIND(),LEFT(),LEN(),LOWER(),REPLACE(),TRIM()UPPER(),EXACT()0.2.10 (2020-10-30)Support CONCATENATEUpdate setup.py classifiers, licence and keywords0.2.9 (2020-09-26)Bugfix ModelCompiler.read_and_parse_dict() where a dict being parsed into a\nModel through ModelCompiler was triggering AttributeError on calling\nxlcalculator.xlfunctions.xl. It\u2019s a leftover from moving xlfunctions into\nxlcalculator. There has been a test included.0.2.8 (2020-09-22)Fix implementation ofISNA()andNA().ImpementMATCH().0.2.7 (2020-09-22)Add functions:ISBLANK(),ISNA(),ISTEXT(),NA()0.2.6 (2020-09-21)AddCOUNTIIF()andCOUNTIFS()function support.0.2.5 (2020-09-21)AddSUMIFS()support.0.2.4 (2020-09-09)Updated README with supported functions.Fix bug in ModelCompiler extract method where a defined name cell was being\noverwritten with the cell from one of the terms contained within the formula.\nAdded a test for this.Move version of yearfrac to 0.4.4. That project has removed a dependency\non the package six.0.2.3 (2020-08-18)In-boarded xlfunctions.Bugfix COUNTA.Now supports 256 arguments.Updated README. Includes words on xlfunction.Changed licence from GPL-3 style to MIT Style.0.2.2 (2020-05-28)Make dependency resolution part of the execution.AST eval\u2019ing takes care of depedency resolution.Provide cycle detection with reporting.Implemented a specific evaluation context. That makes cache control,\nnamespace customization and data encapsulation much easier.Add more tokenizer tests to increase coverage.0.2.1 (2020-05-28)Use a less intrusive way to patchopenpyxl. Instead of permanently\npatching the reader to support cached formula values,mockis used to\nonly patch the reader while reading the workbook.This way the patches do not interfere with other packages not expecting\nthese new classes.0.2.0 (2020-05-28)Support for delayed node evaluation by wrapping them into expressions. The\nfunction will eval the expression when needed.Support for native Excel data types.Enable and update Excel file based function tests that are now working\nproperly.Flake8 source code.0.1.0 (2020-05-25)Refactoredxlcalculatortypes to be more compact.Reimplemented evaluation engine to not generate Python code anymore, but\nbuild a proper AST from the AST nodes. Each AST node supports aneval()function that knows how to compute a result.This removes a lot of complexities around trying to determine the evaluation\ncontext at code creation time and encoding the context as part of the\ngenerated code.Removal of all special function handling.Use of newxlfunctionsimplementation.Use Openpyxl to load the Excel files. This provides shared formula support\nfor free.0.0.1b (2020-05-03)Initial release."} +{"package": "xlcocotools", "pacakge-description": "pip install xlcocotools\u5b98\u65b9\u539f\u9879\u76ee\uff1acocodataset/cocoapi: COCO API\u6211\u7684\u4fee\u6539\uff1a\u589e\u52a0\"prt\"\u53c2\u6570\uff0c\u53ef\u4ee5\u9009\u62e9\u662f\u5426\u8f93\u51fa\u4e2d\u95f4\u7ed3\u679c\u517c\u5bb9win\u3001linux\u7684\u5b89\u88c5"} +{"package": "xlcompare", "pacakge-description": "xlcompareCompare two Excel files (old vs new) where each row has auniqueID (identifier). Ideal for comparing requirements, bill of materials, invoices, exported databases, etc. Generates differences Excel file showing changes from old to new (red strikeout for deletions, blue for insertions). Supports both.xlsand.xlsxformats as inputs.Easy To UseGenerate differences Excel filediff.xlsxwith:xlcompareold.xlsnew.xlsFeaturesSupports both.xlsand.xlsxfile formats for input filesGenerates output Excel file containing differences (default:diff.xlsx)Output is autofiltered to show differences at a glanceChanges in each cell are marked with red strikeout for deletions, blue for insertionsDeleted rows will be at the bottom in red strikeoutPure Python (usesxlrd,pylightxl,XlsxWriterpackages)Excel File Format AssumptionsFirst row is assumed to contain column headingsColumns that are common between the two files will be compared (others are ignored)Column containing unique IDs is labeled \"ID\" (can override with the--idoption)Limitations:Only compares first sheet of each Excel fileCompares cells as textPython 3.6 or laterInstallationpython -m pip install xlcompareUsageusage:xlcompare[-h][--idID][--outfileOUTFILE][--colwidthmaxCOLWIDTHMAX]oldfilenewfile\n\nComparesExcel.xlsor.xlsxfiles(firstsheetonly)withheadersanduniquerowIDs;generatesdiff.xlsx.\n\npositionalarguments:oldfileoldExcelfilenewfilenewExcelfile\n\noptionalarguments:-h,--helpshowthishelpmessageandexit--idIDIDcolumnheading(default:ID)--outfileOUTFILE,-oOUTFILEoutput.xlsxfileofdifferences(default:diff.xlsx)--colwidthmaxCOLWIDTHMAXmaximumcolumnwidthinoutputfile(default:50)Examplesxlcompareold.xlsnew.xls# Generates diff.xlsxxlcompareold.xlsnew.xlsx# Generates diff.xlsxxlcompareold.xlsxnew.xls# Generates diff.xlsxxlcompareold.xlsnew.xls-omydiff.xlsx# Generates mydiff.xlsxxlcompareold.xlsxnew.xls--idMYID# Uses \"MYID\" as the ID column"} +{"package": "xlcompose", "pacakge-description": "No description available on PyPI."} +{"package": "xlcrf", "pacakge-description": "xlcrfUn tool (libreria Python + script) per creare file utili per la\nraccolta dati (con validazione dell'input) a partire da una descrizione\ndella struttura del dataset desiderato (mediante un file.xlsx).UtilizzoLo strumento si pu\u00f2 utilizzare via webquioppure da linea di comando, come segue:xlcrf file_struttura.xlsxQuesto produrr\u00e0file_struttura_CRF.xlsx.File di strutturaPer indicazioni su come compilarlo segui le istruzioniqui."} +{"package": "xlcsv", "pacakge-description": "xlcsvA Python micropackage for consuming Excel as CSV.Build CSVStringIOfrom Excel files.importxlcsvbuffer=xlcsv.to_csv_buffer(\"my-file.xlsx\")Read Excel files without Excel using aDataFramelibrary.# ...importpandasaspddf=pd.read_csv(buffer)importpolarsaspldf=pl.read_csv(buffer)ContributingSeeCONTRIBUTING.md."} +{"package": "xldata", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xldeploy-py", "pacakge-description": "Python SDK forXL-Deploy.Usageimportxldeployconfig=xldeploy.Config(protocol=\"http\",host=\"localhost\",port=\"4516\",context_path=\"deployit\",username=\"admin\",password=\"admin\")# If you are using urlconfig=xldeploy.Config.initialize(url=\"http://localhost:4516/deployit\",username=\"admin\",password=\"admin\")# If you are using proxiesconfig=xldeploy.Config(protocol=\"http\",host=\"localhost\",port=\"4516\",context_path=\"deployit\",username=\"admin\",password=\"admin\",proxy_host=\"localhost\",proxy_port=8080,proxy_username=\"proxyUsername\",proxy_password=\"proxyPassword\")# orconfig=xldeploy.Config()client=xldeploy.Client(config)# repositoryrepository=client.repositoryprint(repository.exists(\"Applications/EC2/1.0/ec2\"))print(repository.exists(\"Applications/EC2/1.0/wrong\"))ci=repository.read(\"Applications/EC2/1.0/ec2\")print(ci.amiId)# deploymentdeployment=client.deploymentdeploymentRef=deployment.prepare_initial(\"Applications/NIApp/1.0\",\"Environments/awsEnv\")depl=deployment.prepare_auto_deployeds(deploymentRef)task=deployment.create_task(depl)task.start()print(task.task_id)# Deployfile## Apply Deployfile script.importrefromosimportpathdeployfile=client.deployfiledeploy_file=open('deploy_file_path','rb').read()file_names=re.findall('upload\\([\\'|\"](.*)[\\'|\"]\\)',deploy_file.decode(\"utf-8\"))files_to_upload=[path.abspath(path.join(path.abspath(path.join(file_path,\"..\")),name))fornameinfile_names]deployfile.apply('deploy_file_path',files_to_upload)## POST of multiple multipart-encoded binary filesBasedonPython[requests](https://pypi.python.org/pypi/requests)module,see[docs](http://docs.python-requests.org/en/master/user/advanced/#advanced)## Generate Deployfile script.deployfile=client.deployfiledeployfile.generate([Environments/directory1,Environments/directory1])Installing from the PyPi repository$ pip install xldeploy-pyInstalling package directly from source$ cd xldeploy-py\n$ pip install --editable ."} +{"package": "xldiff", "pacakge-description": "XL DiffA dead-simple command line diffing of datasets stored in Excel\nformat (.xlsx).Usagepython -m xldiff file_left.xlsx file_right.xlsxIf the datasets match then the program will exit successfully\nand produce no output. If they do not match then the first\nnon-matching row from the \"left\" and the \"right\" versions will\nbe printed and the program will terminate with a non-zero\nexit code.OK, but what's it for?Mostly to make it easier to verify\nthat data has been moved successfully from one system to another\nor that a new \"version\" of a dataset has actually changed."} +{"package": "xl-distributions", "pacakge-description": "No description available on PyPI."} +{"package": "xl_dlframe", "pacakge-description": "It\u2019s just an empty package, which is used to excercise packaging my code."} +{"package": "xld-logchecker", "pacakge-description": "XLD LogcheckerThis is a fork ofhttps://github.com/puddly/xld_logsigner, to be used within our\ndownstream applications, removing unnecessary functionality that we do not need.Based heavily onbarrybingo/xld_sign.\nThis is a complete disassembly of the XLD log signing algorithm, re-implemented in\nPython 3.5+.Usageusage: xld.py [-h] (--verify | --sign) FILE\n\nVerifies and resigns XLD logs\n\npositional arguments:\n FILE path to the log file\n\noptional arguments:\n -h, --help show this help message and exit\n --verify verify a log\n --sign sign or fix an existing logOverviewThe final code isn't pretty, but it is simple enough to describe the algorithm.The log is encoded as UTF-8 and hashed with a SHA-256 variant that uses a different IV.The digest is converted to hex and the string\\nVersion=0001is appended onto the end.The versioned hex-digest is then passed through an unidentified scrambling function that operates on pairs of bytes (open an issue if you recognize it).The resulting bytestring is then encoded using a 65-character lookup table with a strange mapping."} +{"package": "xld-py-cli", "pacakge-description": "Python CLI forXL Deploy.\nFor more information, see thedocumentation.Usage$ xld --url URL --username USERNAME --password PASSWORD apply FILENAME\n\n$ xld --url URL --username USERNAME --password PASSWORD generate DIRECTORIES\n\n$ xld --url URL --username USERNAME --password PASSWORD deploy VERSION ENVIRONMENTAdd\u2013debugto see the stacktrace$ xld \u2013url URL \u2013username USERNAME \u2013password PASSWORD apply FILENAME \u2013debug$ xld \u2013url URL \u2013username USERNAME \u2013password PASSWORD generate DIRECTORIES \u2013debug$ xld \u2013url URL \u2013username USERNAME \u2013password PASSWORD deploy VERSION ENVIRONMENT \u2013debugInstallation$ pip install xld-py-cliTestingOn xl-deploy base folder$ ./gradle pytest"} +{"package": "xleaf", "pacakge-description": "xleafLeaf and canopy radiative transfer modeling tools built on PROSPECT-D and SAIL.Introduction\ud83c\udf33xleafis a python package for running leaf and canopy simulation models using PROSAIL. It provides python bindings to the PROSPECT-D & 4SAILFortran code.\ud83c\udf3f It includes sensible defaults that make it easy to get up and running quickly, and clear code documentation in the form of docstrings and type hints.\ud83d\udcda All credit for the fundamental modeling code and for the underlying science belongs to the original researchers.xleafis mostly a wrapper. Please cite their most recent research:@article{feret2017prospect,\n title={PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle},\n author={Feret, J-B and Gitelson, AA and Noble, SD and Jacquemoud, S},\n journal={Remote Sensing of Environment},\n volume={193},\n pages={204--215},\n year={2017},\n publisher={Elsevier}\n}\ud83e\uddd9 Shout out to my man JB.Installpip install xleaf\ud83d\udda5\ufe0f Depending on your OS, you may need a FORTRAN compiler. So on ubuntu you could runsudo apt install gcc. On macos you'd runbrew install gcc.Leaf and canopy simulationsimportxleafimportmatplotlib.pyplotasplt# run with off-the-shelf defaultsleaf=xleaf.simulate_leaf()# or specify detailed parameterscanopy=xleaf.simulate_canopy(chl=40,# ug/cm2car=8,# ug/cm2antho=0.5,# ug/cm2ewt=0.01,# cmlma=0.009,# g/cm2N=1.5,# unitlesslai=3.0,# m2/m2lidf=30,# degreessoil_dryness=0.75,# %solar_zenith=35,# degreessolar_azimuth=120,# degreesview_zenith=0,# degreesview_azimuth=60,# degreeshot_spot=0.01,# unitless)# and plot them togetherplt.plot(xleaf.wavelengths,leaf,label='leaf')plt.plot(xleaf.wavelengths,canopy,label='canopy')plt.legend()\ud83d\udcc4 The definitions and expected range of values for each parameter are described in thexleafdocstrings.Random forests\ud83d\udccaxleafprovides classes for generating random parameters within the global range of expected values. These classes have a.sample()method for generating an appropriate random value based on a literature review.importxleafimportmatplotlib.pyplotasplt# generate 5 random leaf spectra from global defaultsforidxinrange(5):chl=xleaf.ChlorophyllSampler.sample()car=xleaf.CarotenoidSampler.sample()antho=xleaf.AnthocyaninSampler.sample()ewt=xleaf.EWTSampler.sample()lma=xleaf.LMASampler.sample()N=xleaf.NSampler.sample()leaf=xleaf.simulate_leaf(chl,car,antho,ewt,lma,N)plt.plot(xleaf.wavelengths,leaf,label=f\"leaf{idx+1}\")plt.legend()\ud83e\uddea Or experiment by setting the range of values yourself:importxleafimportmatplotlib.pyplotaspltMyLAISampler=xleaf.UniformSampler(min=2,max=6)MyVZASampler=xleaf.NormalSampler(mean=0,stdv=3,min=-10,max=10)# generate 5 random canopy spectra just varying LAI/VZAforidxinrange(5):lai=MyLAISampler.sample()vza=MyVZASampler.sample()canopy=xleaf.simulate_canopy(lai=lai,view_zenith=vza)plt.plot(xleaf.wavelengths,canopy,label=f\"lai:{lai:0.2f}, vza:{vza:0.2f}\")plt.legend()\u26a1 These parameters don't always vary independently. Try to exercise caution when constructing parameter estimates to ensure biological realism.Developed byChristopher Anderson[^1] [^2][^1]:Planet Labs PBC, San Francisco[^2]:Center for Conservation Biology, Stanford University"} +{"package": "xleap", "pacakge-description": "No description available on PyPI."} +{"package": "xleapp", "pacakge-description": "xLEAPPDevelopment build. Please be cauious using on real cases.Framework for Logs, Events, And Plists Parser (LEAPP)This framework is a complete rewrite of the excellent tool iLEAPP.Details of iLEAPP can be found in thisblog postxLEAPP is the framework created to merge several tools together. More information about the rewrite is given in by talk (YouTube) at Black Hills Info Security's Wild West Hackin' Fest (WWHF): Deadwood in 2021.FeaturesProvides a centralized and modular frameworkProvides a simplified way to write plugins (artifacts) for each different supported platform.Parses iOS, macOS, Android, Chromebook, warranty returns, and Windows artifacts depending on the plugins installed.Other DocumentationArtifact CreationPre-requisitesThis project requires you to have Python >= 3.9PluginsHere is a list of plugins that need to be completed. Plugin package suffixed with \"non-free\" use licenses that may not conform with MIT licenses and are seperated out.xleapp-ios [Github] [PyPI]xleapp-ios-non-free [Github]xleapp-androidxleapp-android-non-freexleapp-chromexleapp-chrome-non-freexleapp-returnsxleapp-returns-non-freexleapp-vehiclesxleapp-vehicles-non-freexleapp-windowsxleapp-windows-non-freeInstallationWindowsPythonPS>py-3-mpipinstallxleappPS>py-3-mpipinstallxleapp-PIPXPS>py-3-mpipinstallpipxPS>pipxinstallxleappPS>pipxinjectxleappxleapp-LinuxPython$python3-mpipinstallxleapp\n$python3-mpipinstallxleapp-PIPX$python3-mpipinstallpipx\n$pipxinstallxleapp\n$pipxinjectxleappxleapp-Installation from Github and Development InformationWindowsLinuxVS Code configuration filesThere are severalconfiguration filesthat I have been using for VS Code.Compile to executableNOTE:This may not work at this time with this alpha version.To compile to an executable so you can run this on a system without python installed.To create xleapp.exe, run:pyinstaller--onefilexleapp.specTo create xleappGUI.exe, run:pyinstaller--onefile--noconsolexleappGUI.specUsageCLI$xleapp-h\nusage:xleapp[-h][-I][-R][-A][-C][-V][-oOUTPUT_FOLDER][-iINPUT_PATH][--artifacts[ARTIFACTS...]][-p][-l][--gui][--version]xLEAPP:Logs,Events,andPlistsParser.\n\noptionalarguments:-h,--helpshowthishelpmessageandexit-Iparseiosartifacts-RparseWarrantReturns/UserGeneratedArchivesartifacts-Aparseandroidartifacts-CparseChromebookartifacts-Vparsevehicleartifacts-oOUTPUT_FOLDER,--output_folderOUTPUT_FOLDEROutputfolderpath-iINPUT_PATH,--input_pathINPUT_PATHPathtoinputfile/folder--artifact[ARTIFACT...]Filteredlistofartifactstorun.Allowed:core,-p,--artifact_pathsTextfilelistofartifactpaths-l,--artifact_tableTextfilewithtableofartifacts--guiRunsxLEAPPintographicalmode--versionshowprogram's version number and exitGUIThis needs work and may not work properly!$xleapp--guiHelp$xleapp.py--helpThe GUI will open in another window.AcknowledgementsThis tool is the result of a collaborative effort of many people in the DFIR community.This product includes software developed by Sarah Edwards (Station X Labs, LLC, @iamevltwin, mac4n6.com) and other contributors as part of APOLLO (Apple Pattern of Life Lazy Output'er)."} +{"package": "xleapp-ios", "pacakge-description": "xLEAPP iOS ArtifactsProvides iOS artifacts supported underMIT license.This is not a standalone package. xLEAPP is required to be installed. See xLEAPP project documentation for information on using this plugins."} +{"package": "xlearn", "pacakge-description": "No description available on PyPI."} +{"package": "xlearning", "pacakge-description": "# XLearning\nX Learning."} +{"package": "xlearntestbyamshoreline", "pacakge-description": "No description available on PyPI."} +{"package": "xleb", "pacakge-description": "No description available on PyPI."} +{"package": "xled", "pacakge-description": "XLED - unofficial control of Twinkly - Smart Decoration LED lightsXLED is a python library and command line interface (CLI) to controlTwinkly- Smart Decoration LED lights for Christmas.Official materials says:Twinkly is a LED light device that you can control via smartphone. It\nallows you to play with colouful and animated effects, or create new ones.\nDecoration lights, not suitable for household illumination.Since itsKickstarter projectin 2016 many products were introduced with\nvarying properties and features. Most notably products released since September\n2019 are identified as Generation II. Older products are since then referred as\nGeneration I.Library and CLI are free software available under MIT license.InstallationBoth library and CLI tool are supported on Linux, primarily Fedora.First make sure that you havepip installed. E.g. for Fedora:$ sudo dnf install python3-pip python3-wheelYou might want tocreate and activate a virtual environment. E.g.:$ mkdir -p ~/.virtualenvs\n$ python3 -m venv ~/.virtualenvs/xled\n$ source ~/.virtualenvs/xled/bin/activateInstallxled from PyPI:$ python3 -m pip install --upgrade xledUsageIf you have installed the project into virtual environment, activate it first. E.g.$ source ~/.virtualenvs/xled/bin/activateUse of the library:>>>importxled>>>discovered_device=xled.discover.discover()>>>discovered_device.id'Twinkly_33AAFF'>>>control=xled.ControlInterface(discovered_device.ip_address,discovered_device.hw_address)>>>control.set_mode('movie')>>>control.get_mode()['mode']'movie'>>>control.get_device_info()['number_of_led']210Documentation for the library can be found online.Use of the CLI:$xledonLooking for any device...\nWorking on device: Twinkly_33AAFF\nTurned on.For more commands and options seexled \u2013help.Why?My first Twinkly was 105 LEDs starter light set. That was the latest available\nmodel in 2017: TW105S-EU. As of December 2017 there are only two ways to\ncontrol lights: mobile app on Android or iOS or hardware button on the cord.Android application didn\u2019t work as advertised on my Xiaomi Redmi 3S phone. On\nfirst start it connected and disconnected in very fast pace (like every 1-2\nseconds) to the hardware. I wasn\u2019t able to control anything at all. Later I\nwanted to connect it to my local WiFi network. But popup dialog that shouldn\u2019t\nhave appear never did so.Public API waspromised around Christmas 2016for next season. Later update\nfrom October 2016 it seemsAPI won\u2019t be available any time soon:API for external control are on our dev check list, we definitely need some\nfeedback from the community to understand which could be a proper core set\nto start with.It turned out that application uses HTTP to control lights. I ended up with\ncapturing network traffic anddocumented this private API. In the end I\u2019m\nable to configure the device pretty easilly.As of 2020 Twinkly devices can be controlled by Amazon Alexa and Google\nAssistant as well. Mobile application now requires an account to operate lights\neven locally. No sign of public API for local devices though. Therefore with my\nsecond device - Twinkly 210 RGB+W Wall I keep improving this library and CLI\ndocumentation to be able to operate my devices locally and not rely on\navailability of manufacturer\u2019s servers.ReferencesUnofficial documentation of private protocol and API isavailable online.There are other projects that might be more suitable for your needs:Twinkly integration in Home AssistantSmartThings:Twinkly integration in SmartThings by StevenJonSmithTwinkly integration in SmartThings by Dameon87TwinklyTree Bindingfor openHABTwinkly HomeKit Hub for Mongoose OSusingTwinkly library for Mongoose OSTwinklyWPF- .net 5 GUI and API libraryioBroker.twinkly- twinkly adapter for ioBroker to communicate with the Twinkly lightsTwinkly.vb for HomeSeerthingzi-logic-twinkly- Twinkly lights integration for node redPython class to interact with generation I device and IDA Pro loader of firmware binary inTwinkly Twinkly Little Star by F-Secure LABS.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.7.0 (2021-11-28)Major changes:Add realtime UDP protocol including unit testsAdd several missing rest calls in ControlInterfaceUnit test all methods in ControlInterfaceOther bugfixes and improvements:Provide a short guide how to install packages from PyPIProvidepython_requiresin setup.pyAdd project URLs to metadataCorrected import of security, and removed some old commentsMake encrypt_wifi_password work also with python3More flexible parameters to set_mqtt_configEnable options in set_network_mode_ap and _stationEnable relative values in set_brightnessMake firmware_update compatible with Generation IIFix error inpython setup.py install(fix #82)Use generic Exception in discover moduleOn Python 2.7 ignore VCR deprecation warningOn Python 2.7 ignore cryptography deprecation warningFix dependencies for python 2.7Don\u2019t debug log reapped devicesTime format as hardcoded value instead of locale specificRaise an exception with a error message firmware update failedGet MAC address from gestalt API callAlways UTF-8 decode response from JOINED event in discoveryLog instead of print in discovery interface and return on unknown eventIf hw_address wasn\u2019t possible to resolve don\u2019t use None as a peerConfigure all loggers used by CLI with cli_log.basic_config()Make response assertions less strictReformat setup py so tox tests passDocumentation updates:Update example in README to use reflect change in APIAdd Gitter badgeUpdate of xled and xled-docs should be done hand in handRemove Enhancement section from Contributing as there is no such thingWrite down support for OS, devices, python and guide to CLIRewrite README fileFix documentation for set_led_movie_configChanges in CI/CD:Run linters as GitHub actionUse generic python3 in black pre-commit configConfigure pytest to collect tests only from tests/Use GitHub action for PyPI publishUpdate URL for CI from Travis to GitHub actionsOne more place to update supported python versionsMake Travis environment python againRemove non-deploy section from travis.ymlFix typo in travis.yml dep installIgnore Flake8 error on Sphinx configuration fileRun pytest directly from ToxAdd bug report template for GitHub issues and reference itSwitch to token authentication for deployment to pypi through TravisChanges in dependencies and python versions:Add 3.10 to supported Python versionsUpdate coverage from 4.4.2 to 5.5Update pip from 20.2.3 to 21.1Update travis.yaml: remove python 3.5 and add 3.8 and 3.9Add 3.9 to supported Python versionsDrop Python 3.5 supportDrop compatibility code for Python version 3.4Add Python 3.8 as a supported languageUpdate pip from 19.0.3 to 20.2.3Update sphinx from 1.6.5 to 3.0.40.6.1 (2020-01-17)Make tests with tox pass again so release can be automatically deployed:Add Black reformatter to tox linter envsTox config: new linters env to run Flake8Tox config update: Flake8 against tests/ and setup.py as wellMake xled.compat pass Flake8 for F821 undefined namesRefactor beacon processing of seen/new peer into separate methodsReformat test_control test with blackMake tox install test-only requiresUse conditional deployment to pypi with travis only from master0.6.0 (2020-01-15)Drop support for python 3.4Explicitly specify Linux as only operating systemAutomatically refresh token if expiredAdd brightness managementCheck response is OK before trying to decode JSON from bodyUse id instead of name in discoveryDevice class representing the deviceGet network status in control interfaceUse response from alive device to check if we reached discover timeoutProvide generator xdiscover() to return all or specific devicesSupport timeout for discoveryWhen agent stops stop ping task and processing responsesProvide close() for UDPClient and use it on DiscoveryInterface.stop()Do not continue receiving more data if UDP recv timeoutsOther bugfixes and improvements:Fix assertionsExpose HighControlInterface on package levelIf ApplicationError is raised, store value of response attributeAllow disable/enable of brightness without value changeUpdate wheel from 0.30.0 to 0.33.1Update pip from 9.0.1 to 19.0.3Add python 3.6 and 3.7 to Travis config0.5.0 (2018-12-09)CLI to update firmwareExample of library call and CLI usageOption to select device by hostname in CLI and ping in discoveryNew HighControlInterface() to aggregate and abstract low-level callsCLI and HighControlInterface way to set static single colorOther bugfixes and improvements:Fix typo in CLI error messagePrint message before discovery on CLIRefactor: join consecutive strings on same linePrint better message after device has been discovered over CLIRegenerate documentation index of a packageFix typo in control.set_mode() documentationReturn named tuple in discover.discover()Use discovery and named tuple in example of library useDo not assert return value in ControlInterface.set_led_movie_full()Return ApplicationResponse for ControlInterface.set_led_movie_config()Return ApplicationResponse for control.ControlInterface.led_reset()Remove unneeded debug message from DiscoveryInterface.__init__()0.4.0 (2018-12-03)Support Python 3.6 and 3.7 including tests and documentationPython 3 support with pyzmq >= 17.0 and Tornado 5Remove redundant udplibOther Python 3 compatibility:In Python 3+ import Mapping from collections.abcPython 3 compatible encoding of discovered IP and HW address and nameMake xled.security.xor_strings() compatible with Python 2 and 3Treat PING_MESSAGE as bytes to simplify handling Python 2 and 3Other bugfixes and improvements:Remove mention of PyPy from docs as it wasn\u2019t ever tested on itImprove robustness with sending messages from agent to interfaceEscape display of binary challenge in debug log of xled.authIgnore (usually own) PING_MESSAGE on network when handling responses0.3.1 (2018-11-27)Update changelog for version 0.3.0Update description in setup.py to refer to CLIFix JSON payload sent to server for firmware update.0.3.0 (2018-11-27)CLI interfaceDiscovery interface - currently works only on Python 2Add support for API led/movie/full and corresponding CLI upload-movieNew Authentication mechanism - use sessionRename authentication module from long challenge_response_auth to authChange interface of ApplicationResponse to collections.MappingPython files reformatted with BlackOther bugfixes and improvements:Really show ApplicationResponse status in repr() when availableCatch JSONDecodeError in Python 3.5+ in ApplicationResponseNew shortcut method ok() of ApplicationResponseMake ApplicationResponse\u2019s attribute status_code @propertyImprove error reporting during parsing of ApplicationResponseIf repr() of ApplicationResponse is called parse response firstCheck status of underlying requests\u2019 Response if requestedAccept requests\u2019 response as attribute to class ApplicationResponseMove generate_challenge to security moduleUnit tests for control interfaceRun unit tests on supported python versions with tox and TravisConfiguration for pre-commit-hooksInitial pyup configurationDon\u2019t run Tox on Travis on Python 3.3Update coverage0.2.1 (2018-01-02)Add missing MANIFEST.inConfigure Travis for automatic deployment to PyPI0.2.0 (2018-01-02)First Python control interface.0.1.0 (2017-12-17)Low level control interface."} +{"package": "xleditor", "pacakge-description": "xleditor\u6253\u5f00\u5e76\u5728\u539f\u6709\u57fa\u7840\u4e0a\u7f16\u8f91 xls / xlsx \u6587\u6863Useage:# pip install xlrd\n# pip install xlutils\n\nimport xleditor\n\nbook = xleditor.open_workbook('old.xls')\nsheet = book.get_sheet_by_index(0)\n\nprint sheet.get_value(3, 0)\nsheet.write(0, 5, 'hello world')\n\nbook.save('new.xls')"} +{"package": "xled-plus", "pacakge-description": "XLED Plus provides addons to the XLED package. Whereas XLED provides a\npython interface to Twinkly led lights, XLED Plus provides classes and\nfunctions to make it easier to produce various effects on the lights\nentirely from python: still or animated, simple or advanced,\nprerecorded or created in real time."} +{"package": "xler8r-lite", "pacakge-description": "XLER8R PatternsXLER8R Patterns are designed to fast track most commonly used architectures, while XLER8R Lite supports provisioning\nfor static web hosting infrastructure only, XLER8R premium provides support for building serverless APIs, container based\napplications, organizational hierarchy setup, sso setup, management account and member account setup and many more.\nReach out toinfo@cre8ivelogix.comto find out more about premium version of XLER8Rhttps://xler8r.comCreate a CDK projectTo try out XLER8R Lite by itself you can create a new CDK project by running the following commandscdkinitapp--languagetypescriptThis will create a bare bone CDK project.Adding WA-CDK Lite dependencyOpen CDK project in your favorite IDE, goto package.json file and add the WA-CDK-Lite dependency{\"dependencies\":{\"@cre8ivelogix/xler8r-lite\":\"CURRENT_VERSION\"}}Install DependenciesOnce package.json file is updated, you can install the dependencies by running the following commandsnpminstallUsing Well Architected CDK constructsNow that you have all the constructs available from XLER8R Lite,\nuse them just like any other class in typescript.For example in the following code snippet we are using WaBucket from AWS-CDK-Lite packagenewX8Website(this,\"TestWebSite\",{waDomainName:'example.com',});The Bucket created using WaBucket by default satisfies various security and compliance requirements,\ncheckout WaBucket class documentation for details.Well Architected CDK Version UpdatesThe version of all CDK packages are fixed to the same version. If an\nupgrade is desired, please make sure that all CDK packages are upgraded\nto the same version at the same time. Different versions of CDK mixed\nin the project may cause type incompatibilities.Useful commandsnpm run buildcompile typescript to jsnpm run watchwatch for changes and compilenpm run testperform the jest unit testsnpm run build-testbuilds and runs unit testsnpm run doc-gengenerate documentationnpm run prettyruns prettier on source code"} +{"package": "xlerai", "pacakge-description": "XlerAI Python API libraryThe XlerAI Python library provides convenient access to the XlerAI REST API from any Python 3.7+\napplication. The library wraps theopenai python library,\npoints it atapi.xler.ai/v1for you, and extends their library further with additional functionality.DocumentationThe REST API documentation can be foundon docs.xler.ai.InstallationpipinstallxleraiUsageThe full API of this library can be found inapi.md.importosfromxleraiimportXlerAIclient=XlerAI(# This is the default and can be omittedapi_key=os.environ.get(\"OPENAI_API_KEY\"),)chat_completion=client.chat.completions.create(messages=[{\"role\":\"user\",\"content\":\"Say this is a test\",}],model=\"gpt-3.5-turbo\",)While you can provide anapi_keykeyword argument,\nwe recommend usingpython-dotenvto addOPENAI_API_KEY=\"My API Key\"to your.envfile\nso that your API Key is not stored in source control.Async usageSimply importAsyncXlerAIinstead ofXlerAIand useawaitwith each API call:importosimportasynciofromxleraiimportAsyncXlerAIclient=AsyncXlerAI(# This is the default and can be omittedapi_key=os.environ.get(\"OPENAI_API_KEY\"),)asyncdefmain()->None:chat_completion=awaitclient.chat.completions.create(messages=[{\"role\":\"user\",\"content\":\"Say this is a test\",}],model=\"gpt-3.5-turbo\",)asyncio.run(main())Functionality between the synchronous and asynchronous clients is otherwise identical.Streaming ResponsesWe provide support for streaming responses using Server Side Events (SSE).fromxleraiimportXlerAIclient=XlerAI()stream=client.chat.completions.create(model=\"gpt-4\",messages=[{\"role\":\"user\",\"content\":\"Say this is a test\"}],stream=True,)forchunkinstream:print(chunk.choices[0].delta.contentor\"\",end=\"\")The async client uses the exact same interface.fromxleraiimportAsyncXlerAIclient=AsyncXlerAI()asyncdefmain():stream=awaitclient.chat.completions.create(model=\"gpt-4\",messages=[{\"role\":\"user\",\"content\":\"Say this is a test\"}],stream=True,)asyncforchunkinstream:print(chunk.choices[0].delta.contentor\"\",end=\"\")asyncio.run(main())RequirementsPython 3.7 or higher."} +{"package": "xless", "pacakge-description": "xlessxlessis a python script that allows display excel files directly on linux command line.[kai@admin~]$xlesstest.xlsx-s1-g-HNone-N+------+----------+---------+------+----------+----------+|index|0|1|2|3|4|+------+----------+---------+------+----------+----------+|0|Bat25|KIT|chr4|55598212|55598236||1|Bat-26|MSH2|chr2|47641560|47641586||2|MONO-27|MAP4K3|chr2|39564894|39564921||3|NR-21|SLC7A8|chr14|23652347|23652367||4|NR-24|ZNF2|chr2|95849362|95849384||5|MSI-01|NAV1|chr1|201754411|201754427||6|MSI-03|FAM161A|chr2|62063094|62063110||7|MSI-04|RGPD4|chr2|108479623|108479640||8|MSI-06|ATP6V0E1|chr5|172421761|172421775||9|MSI-07|GPR126|chr6|142691951|142691967||10|MSI-08|ELFN1|chr7|1787520|1787536||11|MSI-09|GTF2IP1|chr7|74608741|74608753||12|MSI-11|GUCY1A2|chr11|106695515|106695526||13|MSI-12|BLOC1S6|chr15|45897772|45897785||14|MSI-13|SMG1|chr16|18882660|18882674||15|MSI-14|RNF112|chr17|19314918|19314935||16|HSPH1-T17|HSPH1|chr13|31722621|31722637||17|EWSR1|EWSR1|chr22|29696469|29696484|+------+----------+---------+------+----------+----------+Installxlessrequires only thepandasandopenpyxllibrary and no other dependencies.Installxlessviapip:pip3 install xlessor simply clone from Github:gitclonehttps://github.com/ZKai0801/xless.gitcpxless/xless/usr/local/bin/Usage[kai@admin~]$xless-h\nusage:xless[-h][-HHEADER][-s[SHEET[SHEET...]]][-g][-N][-FFIELD_SEPARATOR][-v]excel\n\nDisplayexceldirectlyonthescreen\n\npositionalarguments:excelInputexcel,oruse'-'toreadfromstdin\n\noptionalarguments:-h,--helpshowthishelpmessageandexit-HHEADER,--headerHEADERRow(0-indexed)touseforthecolumnlabelsoftheparsedDataFrame;UseNoneifthereisnoheader.-s[SHEET[SHEET...]],--sheet[SHEET[SHEET...]]0-indexedsheetposition,orsheetname.set'all'todisplayallsheets-g,--show_gridShowinggridforcells-N,--show_indexShowingindexforrows-FFIELD_SEPARATOR,--field_separatorFIELD_SEPARATORUsethisfortheinputfieldseparator.Ifthisisspecified,thentheinputfilewillbetreatedasaplain-txtfile-v,--versionshowprogram'sversionnumberandexitThe input file could be inxlsx,tsvorcsvformat. All files will be automatically parsed and output as tab-delimited that could be easily processed by other tools likeawk. Files in other format will not be parsed by the xless."} +{"package": "xlf-merge", "pacakge-description": "xlf-mergeTool to merge XLF translation files.\nAnd it can also find dupes in XLF files.InstallationUsing PIPpipinstallxlf-mergeUsing package Debian/Archlinux packageGo tohttps://repository.salamek.cz/to see how to setup access to my public repository, then just do:debianaptupdate&&aptinstallxlf-mergearchlinuxpacman-Syxlf-mergeUsageMergingxlf-mergemerge--method='source/id'Merge files by source:xlf-mergemergemessages.cs.xlf.oldmessages.xlfmessages.cs.xlf--method='source'Merge files by id:xlf-mergemergemessages.cs.xlf.oldmessages.xlfmessages.cs.xlf--method='id'Finding dupesxlf-merge dupes --method='source/id/target'Finding dupes by source:xlf-merge dupes messages.cs.xlf --method='source'Finding dupes by id:xlf-merge dupes messages.cs.xlf --method='id'Finding dupes by target:xlf-merge dupes messages.cs.xlf --method='target'"} +{"package": "xlform", "pacakge-description": "xlform\u4e00\u4e2a\u4eff django form \u7684\u8868\u5355\u9a8c\u8bc1\u5e93InstallationpipinstallxlformExamplefromxlform.formsimportFormfromxlform.fieldsimport*classNF(Form):a=CharField(max_length=4,min_length=2,empty_value='123')b=CharField(max_length=4,min_length=2,required=False,empty_value='222')phone=PhoneField(max_length=11)email=EmailField()reg=RegexField(regex='^1[3456789]\\d{9}$')uuid=UUIDField(required=False)boolean=BooleanField(required=False)integer=IntegerField(max_value=11)ft=FloatField(max_value=12)dc=DecimalField(max_digits=3,decimal_places=1,required=False)data={# 'a': '12','b':'123','phone':'16666666666','email':'16666666666@qq.com','reg':'16666666666','uuid':'998a281c-e257-11e8-b428-8c85904e5604','boolean':0,'integer':'11','ft':'11.1111','dc':11.0}nf=NF(data)ifnf.is_valid():print(nf.cleaned_data)else:print(nf.errors)"} +{"package": "xl-formulas", "pacakge-description": "xlFormulasHelper class to write Excel-style formula strings to worksheets when saving from a Pandas dataframe.Default initialization assumes the worksheet will be saved with an index and header row (the first real 'data' cell would be B2) but an index and header parameter are available to ensure alignment.Pass in mathematical operators with strings, limited support currently for Excel built-in functions. If a value is not a column name in df.columns it is passed in as it is, whether that means it's an operator or builtin function.The.formula()method returns a list of strings beginning with '=' and containing the row index for the Excel formulaInstallation:pip install xl-formulasBasic usage:import pandas as pd\nfrom xlFormulas import ExcelFormulas\n\ndf = pd.read_excel('sample_data.xlsx')\n\n# Pass in Pandas dataframe to intialize ExcelFormulas helper\nef = ExcelFormulas(df)\n\n# Returns a column like \"=B2+C2\" in df['C']\ndf['C'] = ef.formula('A + B')\n\n# Makes a \"=(B2 + C2)/(C2 - D2)\" column in df['D']\ndf['D'] = ef.formula(f'{ef.paren('A + B')} / {ef.paren('B - C')}'\n\n# Use Excel built-in functions (Still pretty buggy)\n# This would get a column of \"=SUM(B2,C2,5)\" in df['E']\ndf['E'] = ef.formula(ef.builtin('SUM', 'A', 'B', 'C'))"} +{"package": "xlfparser", "pacakge-description": "xlfparserPython wrapper for C++ Excel formula parserhttps://github.com/pyxll/xlfparser."} +{"package": "xlframe", "pacakge-description": "No description available on PyPI."} +{"package": "xlfunctions", "pacakge-description": "XLFunctionsA collection of classes which implement functions as used in Microsoft\nExcel. The intent is to be a definitive library to support evaluating Excel\ncalculations.There are a number of solutions being developed in the Python universe which\nare writing their own implementations of the same functions. Often those\nimplementations are simply wrapping pandas, numpy or scipy. Although\npotentially fit for purpose in those solutions, the calculated result may not\nnecessarily agree with Excel.There are also a handful of libraries to be found which have attempted a\nuniversal Python implementation of Excel functions however as they aren\u2019t\nbeing actively used by a library they appear to be abandoned reasonably\nrapidly. xlfunctions is being used byxlcalcualtor(an attempted\nre-write ofKoala2and, in turn,FlyingKoala).Excel occasionally does unusual things while calculating which may not always\nalign with what is accepted outside the realms of Excel. With this in mind it\nis common that numpy, scipy or pandas libraries may not calculate a result\nwhich agrees with Excel. This is especially true of Excel\u2019s date\nhandling. This library attempts to take care to return results as close as\npossible to what Excel would expect.If you want to align perfectly with\nExcel, please read the discussion on Excel number precision (below)Supported FunctionsABSAVERAGECHOOSECONCATCOUNTCOUNTADATEIRRLNPython Math.log() differs from Excel LN. Currently returning Math.log()MAXMIDMINMODNPVPMTPOWERRIGHTROUNDROUNDDOWNROUNDUPSLNSQRTSUMSUMPRODUCTTODAYVLOOKUPExact match onlyXNPVYEARFRACBasis 1, Actual/actual, is only within 3 decimal placesRun TestsSetup your environment:virtualenv -p 3.7 ve\nve/bin/pip install -e .[test]From the root xlfunctions directory:ve/bin/python -m unittest discover -p \"test_*.py\"Or simply run tox:toxAdding/Registering Excel FunctionsExcel functions can be added by any code using the thexlfunctions.xl.register()decorator. Here is a simple example:fromxlfunctionsimportxl@xl.register()@xl.validate_argsdefADDONE(num:xl.Number):returnnum+1Thev@xl.alidate_argsdecorator will ensure that the annotated arguments are\nconverted and validated. For example, even if you pass in a string, it is\nconverted to a number (in typical Excel fashion):>>>ADDONE(1):2>>>ADDONE('1'):2If you would like to contribute functions, please create a pull request. All\nnew functions should be accompanied by sufficient tests to cover the\nfunctionality.Excel number precisionExcel number precision is a complex discussion.It has been discussed in aWikipedia\npage.The fundamentals come down to floating point numbers and a contention between\nhow they are represented in memory Vs how they are stored on disk Vs how they\nare presented on screen. AMicrosoft\narticleexplains the contention.This project is attempting to take care while reading numbers from the Excel\nfile to try and remove a variety of representation errors.Further work will be required to keep numbers in-line with Excel throughout\ndifferent transformations.From what I can determine this requires a low-level implementation of a\nnumeric datatype (C or C++, Cython??) to replicate its behaviour. Python\nbuilt-in numeric types don\u2019t replicate appropriate behaviours.CHANGES0.2.2 (2020-05-28)Implement a few more operators for the Excel Number type.0.2.1 (2020-05-28)Fix an error message to refer to the righ type.Added a test to ensure SUM() works with arrays containing Excel data types.0.2.0 (2020-05-28)Support for delayed argument execution by introducing expressions that can\nbe evaluated when needed. This is required to support efficient logical\noperator implementations. For example, when an \u201cif\u201d-condition is true, the\nfalse value does not need to be computed.Implemented all Excel types.Better control of logic differences between Python and Excel. (Compare\nwith None and blank handling, for example.)Tight control of type casting with very situation-specific edge case\nhandling. (For example, when a string representing a boolean will evaluate\nas a boolean and when not. For example,int(bool(\u2018False\u2019)) == 0in Excel\nbutAND(\u2018False\u2019, True) == True.Make date/time its own type.Moved errors back into their own module.Moved criteria parsing into its own module.Made function signature validation and conversion much more consistent\nallowing a lot less error handling and data conversion in the function\nbody.0.1.0 (2020-05-25)Complete rewrite of library.Introduced a function registry that can be used to extend the function\nlibrary in third party software.Removed excessive use of static methods and converted all Excel functions\nto simple Python functions (with some decorators).Organized functions into categories based on Microsoft documentation.Proper argument validation and conversion where supported.Many functions are now much more flexible with their types and more\ncorrectly mimic Excel behavior.Use ofdateutilandyearfraclibraries to do complicated date\ncalculations instead of implementing it from scratch.Achieved 100% test coverage.0.0.3b (2020-05-11)Initial release."} +{"package": "xlgcid", "pacakge-description": "xlgcidXunLei GCID hash algorithm, inspired fromhttps://binux.blog/2012/03/hash_algorithm_of_xunlei/.Usagefromxlgcidimportget_file_gcid_digestprint(get_file_gcid_digest('a.txt').hex())"} +{"package": "xlhelper", "pacakge-description": "UNKNOWN"} +{"package": "xl-helper", "pacakge-description": "This tool helps with installation and upgrade of XL Deploy and plugins"} +{"package": "xlib", "pacakge-description": "Homepage|Releases|ChangelogCopyrightThe main part of the code isCopyright (C) 2000-2002 Peter LiljenbergSome contributed code is copyrighted bythe contributors,\nin these cases that is indicated in the source files in question.The Python X Library is released under LGPL v2.1 or later (since 2016),\nsee the file LICENSE for details. 0.15rc1 and before were released under\nGPL v2.RequirementsThe Python X Library requires Python 2.7 or newer. It has been tested to\nvarious extents with Python 2.7 and 3.3 through 3.6.InstallationThe Python Xlib uses the standard setuptools package, to install run\nthis command:python setup.py installSee the command help for details:python setup.py install-h.Alternatively, you can run programs from the distribution directory, or\nchange the module path in programs.There\u2019s a simple example program, implemented twice using both the\nhigh-level interface and the low-level protocol.IntroductionThe Python X Library is intended to be a fully functional X client\nlibrary for Python programs. It is written entirely in Python, in\ncontrast to earlier X libraries for Python (the ancient X extension and\nthe newer plxlib) which were interfaces to the C Xlib.This is possible to do since X client programs communicate with the X\nserver via the X protocol. The communication takes place over TCP/IP,\nUnix sockets, DECnet or any other streaming network protocol. The C Xlib\nis merely an interface to this protocol, providing functions suitable\nfor a C environment.There are three advantages of implementing a pure Python library:Integration: The library can make use of the wonderful object system\nin Python, providing an easy-to-use class hierarchy.Portability: The library will be usable on (almost) any computer\nwhich have Python installed. A C interface could be problematic to\nport to non-Unix systems, such as MS Windows or OpenVMS.Maintainability: It is much easier to develop and debug native Python\nmodules than modules written in C.DocumentationThe reference manual is not finished by far, but is probably still useful. It\ncan bebrowsed online.There are also someexample programsand, of course,the standard X11 documentationapplies.Project statusThe low-level protocol is complete, implementing client-side X11R6. The\nhigh-level object oriented interface is also fully functional. It is\npossible to write client applications with the library. Currently, the\nonly real application using Python Xlib is the window manager PLWM,\nstarting with version 2.0.There is a resource database implementation, ICCCM support and a\nframework for adding X extension code. Several extensions have been\nimplemented; (RECORD, SHAPE, Xinerama, Composite, RANDR, and XTEST)\npatches for additions are very welcome.There are most likely still bugs, but the library is at least stable\nenough to run PLWM. A continuously bigger part of the library is covered\nby regression tests, improving stability.The documentation is still quite rudimentary, but should be of some help\nfor people programming with the Xlib. X beginners should first find some\ngeneral texts on X. A very good starting point ishttp://www.rahul.net/kenton/xsites.htmlSee the file TODO for a detailed list of what is missing, approximately\nordered by importance."} +{"package": "x-lib", "pacakge-description": "Framework to handle simplify development application with,\nflask, consulate and sql alchemy together"} +{"package": "xlibris", "pacakge-description": "xlibris=====A DOI based PDF management system."} +{"package": "xlibs", "pacakge-description": "No description available on PyPI."} +{"package": "xlib-screenfilter", "pacakge-description": "No description available on PyPI."} +{"package": "xliee-sentry-telegram", "pacakge-description": "Plugin for Sentry which allows sending notification viaTelegrammessenger.Presented plugin tested with Sentry 23.8.0.dev0DISCLAIMER: Sentry API is under development andis not frozen.How will it look likeInstallationInstall this packagepipinstallxliee-sentry-telegramRestart your Sentry instance.Go to your Sentry web interface. OpenSettingspage of one of your projects.OnIntegrations(orLegacy Integrations) page, findTelegram Notifications Python3plugin and enable it.Configure plugin onConfigure pluginpage.SeeTelegram\u2019s documentationto know how to createBotAPI Token.Done!"} +{"package": "xliff-ai-translator", "pacakge-description": "XLIFF AI TranslatorXLIFF AI Translator is an AI-powered tool designed to translate XLIFF files, enhancing content accessibility across different languages. This application utilizes advanced machine learning models to offer precise and context-aware translations, ensuring seamless localization of digital content.FeaturesAutomated Translation: Efficiently translates XLIFF files from one language to another, supporting multiple languages.AI Integration: Employs cutting-edge AI translation models for accurate file translation.Customizable Workflow: Adaptable to specific translation needs and preferences.Batch Processing Capability: Allows translation of multiple text at once, optimizing productivity.User-Oriented Design: Simple and accessible, suitable for both technical and non-technical users.InstallationUsing pipTo install XLIFF AI Translator, execute the following command:pip install xliff-ai-translatorThis command installs the latest version along with its dependencies.Installing from SourceAlternatively, install from source with these commands:git clone https://github.com/sutasrof/xliff-ai-translator.git\ncd xliff-ai-translator\npip install .These steps clone the repository and install the package with its required dependencies.UsageRun XLIFF AI Translator from the command line. Here's a basic example:xliff-ai-translator source.xliff destination.xliff target_language_codeReplacesource.xliffwith your original file path,destination.xlifffor the translated file path, andtarget_language_codewith the desired language code (e.g., 'en' for English, 'fr' for French, etc.)."} +{"package": "xline", "pacakge-description": "No description available on PyPI."} +{"package": "xlines", "pacakge-description": "PACKAGE: xlinesxlines:Python3 commandline utility.Essential software developer toolsFeatures:Count lines in specific file objects provided as parametersAlternatively provide a parent directory (project directory):xlines sums all lines of text in all objects in subdirs.outputs filename plus number of linesExclusion list of File extensions not countedUser customizable"} +{"package": "xlingual-papers-recommender", "pacakge-description": "What is it?Component of a papers recommender system in a cross-lingual and multidisciplinary scope.Result of the Coursework of MBA in Data Science and Analytics - USP / ESALQ - 2020-2022.Designed to be customizable in many ways:sentence-transformer modelthe maximum number of candidate articles for the evaluation of semantic similarityaccepts any type of document that has bibliographic referencesDependencessentence-transformercelerymongoengineModelThe algorithm adopted is a combination of recommender systems graph based and content based filtering with semantic similarityThe identification of the relationship between scientific articles is made during the document's entry into the system through the common bibliographic references. Subsequently, the documents are ranked by semantic similarity and recorded in a database.The recommendation system works in two steps: creating links between articles via common citations and assigning a similarity coefficient for a selection of these linked articles.The system itself does not establish which articles should be recommended.The recommendation system client defines which articles to present as a recommendation depending on the criticality of the use case.Installationpip install -U xlingual_papers_recommenderConfigurationsexport DATABASE_CONNECT_URL=mongodb://my_user:my_password@127.0.0.1:27017/my_dbexport CELERY_BROKER_URL=\"amqp://guest@0.0.0.0:5672//\"export CELERY_RESULT_BACKEND_URL=\"rpc://\"export MODELS_PATH=sentence_transformers_modelsexport DEFAULT_MODEL=paraphrase-xlm-r-multilingual-v1CeleryStart servicecelery -A xlingual_papers_recommender.core.tasks worker -l info -Q default,low_priority,high_priority --pool=solo --autoscale 8,4 --loglevel=DEBUGClean queuecelery worker -Q low_priority,default,high_priority --purgeUsageRegister new paperxlingual_papers_recommender receive_paper [--skip_update SKIP_UPDATE] source_file_path log_file_pathpositional arguments:\nsource_file_path /path/document.json\nlog_file_path /path/registered.jsonloptional arguments:\n-h, --help show this help message and exit\n--skip_update SKIP_UPDATE\nif it is already registered, skip_update do not updateExamples of source_file_path:docs\n\u2514\u2500\u2500 examples\n \u251c\u2500\u2500 document1.json\n \u251c\u2500\u2500 document2.json\n \u251c\u2500\u2500 document3.json\n \u251c\u2500\u2500 document4.json\n \u251c\u2500\u2500 document5.json\n \u251c\u2500\u2500 document51.json\n \u251c\u2500\u2500 document6.json\n \u251c\u2500\u2500 document6_2.json\n \u251c\u2500\u2500 document7.json\n \u2514\u2500\u2500 document7_2.jsonReferences attributes:pub_yearvolnumsupplpagesurnameorganization_authordoijournalpaper_titlesourceissnthesis_datethesis_locthesis_countrythesis_degreethesis_orgconf_dateconf_locconf_countryconf_nameconf_orgpublisher_locpublisher_countrypublisher_nameeditionsource_person_author_surnamesource_organization_authorGet paper recommendationsusage: xlingual_papers_recommender get_connected_papers [-h] [--min_score MIN_SCORE] pidpositional arguments:pid pidoptional arguments:-h, --help show this help message and exit--min_score MIN_SCOREmin_scoreLoad papers data from datasetsRegister partsusage: xlingual_papers_recommender_ds_loader register_paper_part [-h] [--skip_update SKIP_UPDATE] [--pids_selection_file_path PIDS_SELECTION_FILE_PATH]{abstracts,references,keywords,paper_titles,articles} input_csv_file_path output_file_pathpositional arguments:{abstracts,references,keywords,paper_titles,articles}part_nameinput_csv_file_path CSV file with papers part dataoutput_file_path jsonl output file pathoptional arguments:-h, --help show this help message and exit--skip_update SKIP_UPDATETrue to skip if paper is already registered--pids_selection_file_path PIDS_SELECTION_FILE_PATHSelected papers ID file path (CSV file path which has \"pid\" column)Register articlesExample:xlingual_papers_recommender_ds_loader register_paper_part articles articles.csv articles.jsonlRequired columnspidmain_langurisubject_areaspub_yeardoi (optional)network_collection (optional)Register abstractsExample:xlingual_papers_recommender_ds_loader register_paper_part abstracts /inputs/abstracts.csv /outputs/abstracts.jsonlColumnspidlangoriginaltext (padronizado)Same forpaper_titlesandkeywordsdatasets.Register referencesExample:xlingual_papers_recommender_ds_loader register_paper_part references /inputs/references.csv /outputs/references.jsonlColumnspub_yearvolnumsupplpagesurnameorganization_authordoijournalpaper_titlesourceissnthesis_datethesis_locthesis_countrythesis_degreethesis_orgconf_dateconf_locconf_countryconf_nameconf_orgpublisher_locpublisher_countrypublisher_nameeditionsource_person_author_surnamesource_organization_authorMerge papers partsusage: xlingual_papers_recommender_ds_loader merge_parts [-h] [--split_into_n_papers SPLIT_INTO_N_PAPERS] [--create_paper CREATE_PAPER]\n input_csv_file_path output_file_path\n\npositional arguments:\n input_csv_file_path Selected papers ID file path (CSV file path which has \"pid\" column)\n output_file_path jsonl output file path\n\noptional arguments:\n -h, --help show this help message and exit\n --split_into_n_papers SPLIT_INTO_N_PAPERS\n True to create one register for each abstract\n --create_paper CREATE_PAPER\n True to register papersExample:xlingual_papers_recommender_ds_loader merge_parts pids.csv output.jsonlRegister papers from loaded datasetsusage: xlingual_papers_recommender_ds_loader register_paper [-h] [--skip_update SKIP_UPDATE] input_csv_file_path output_file_path\n\npositional arguments:\n input_csv_file_path Selected papers ID file path (CSV file path which has \"pid\" column)\n output_file_path jsonl output file path\n\noptional arguments:\n -h, --help show this help message and exit\n --skip_update SKIP_UPDATE\n True to skip if paper is already registeredExample:xlingual_papers_recommender_ds_loader register_paper pids.csv output.jsonlGenerate reports from papers, sources and connectionsusage: xlingual_papers_recommender_reports all [-h] reports_path\n\npositional arguments:\n reports_path /path\n\noptional arguments:\n -h, --help show this help message and exitExample:xlingual_papers_recommender_reports all /reports"} +{"package": "xlinjietool", "pacakge-description": 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"xlinjietool\u6253\u9020\u96c6\u6210\u5de5\u5177\u5e93\u603b\u89c8amazon(\u4e9a\u9a6c\u900a\u89e3\u6790)db(\u6570\u636e\u5e93)headers(header\u5934\u89e3\u6790)amazon(\u4e9a\u9a6c\u900a\u89e3\u6790)\u5404\u4e2a\u7ad9\u70b9\u65e5\u671f\u89e3\u6790\u7ad9\u70b9\u94fe\u63a5\u7ec4\u88c5db(\u6570\u636e\u5e93)esredismysqlheaders(header\u5934\u89e3\u6790)\u628aweb\u590d\u5236\u7684headers\u89e3\u6790\u6210\u4e3ajson\u65f6\u95f4\u76f8\u5173fromxlj.CommimportTimeprint(Time.timestamp_to_time())print(Time.timestamp_to_time(16563153))print(Time.timestamp_to_time(1656315389))print(Time.timestamp_to_time('1656315389'))print(Time.now_timestamp())print(Time.now_timestamp(10))2022-06-2715:37:492022-06-2715:35:002022-06-2715:36:292022-06-2715:36:2916563154693531656315469"} +{"package": "xllabelme", "pacakge-description": "labelmeImage Polygonal Annotation with PythonInstallation|Usage|Tutorial|Examples|Youtube FAQDescriptionLabelme is a graphical image annotation tool inspired byhttp://labelme.csail.mit.edu.It is written in Python and uses Qt for its graphical interface.VOC dataset example of instance segmentation.Other examples (semantic segmentation, bbox detection, and classification).Various primitives (polygon, rectangle, circle, line, and point).FeaturesImage annotation for polygon, rectangle, circle, line and point. (tutorial)Image flag annotation for classification and cleaning. (#166)Video annotation. (video annotation)GUI customization (predefined labels / flags, auto-saving, label validation, etc). (#144)Exporting VOC-format dataset for semantic/instance segmentation. (semantic segmentation,instance segmentation)Exporting COCO-format dataset for instance segmentation. (instance segmentation)RequirementsUbuntu / macOS / WindowsPython3PyQt5 / PySide2InstallationThere are options:Platform agnostic installation:Anaconda,DockerPlatform specific installation:Ubuntu,macOS,WindowsPre-build binaries fromthe release sectionAnacondaYou need installAnaconda, then run below:# python3condacreate--name=labelmepython=3sourceactivatelabelme# conda install -c conda-forge pyside2# conda install pyqt# pip install pyqt5 # pyqt5 can be installed via pip on python3pipinstalllabelme# or you can install everything by conda command# conda install labelme -c conda-forgeDockerYou need installdocker, then run below:# on macOSsocatTCP-LISTEN:6000,reuseaddr,forkUNIX-CLIENT:\\\"$DISPLAY\\\"&dockerrun-it-v/tmp/.X11-unix:/tmp/.X11-unix-eDISPLAY=docker.for.mac.host.internal:0-v$(pwd):/root/workdirwkentaro/labelme# on Linuxxhost+\ndockerrun-it-v/tmp/.X11-unix:/tmp/.X11-unix-eDISPLAY=:0-v$(pwd):/root/workdirwkentaro/labelmeUbuntusudoapt-getinstalllabelme# orsudopip3installlabelme# or install standalone executable from:# https://github.com/wkentaro/labelme/releasesmacOSbrewinstallpyqt# maybe pyqt5pipinstalllabelme# orbrewinstallwkentaro/labelme/labelme# command line interface# brew install --cask wkentaro/labelme/labelme # app# or install standalone executable/app from:# https://github.com/wkentaro/labelme/releasesWindowsInstallAnaconda, then in an Anaconda Prompt run:condacreate--name=labelmepython=3condaactivatelabelme\npipinstalllabelme# or install standalone executable/app from:# https://github.com/wkentaro/labelme/releasesUsageRunlabelme --helpfor detail.The annotations are saved as aJSONfile.labelme# just open gui# tutorial (single image example)cdexamples/tutorial\nlabelmeapc2016_obj3.jpg# specify image filelabelmeapc2016_obj3.jpg-Oapc2016_obj3.json# close window after the savelabelmeapc2016_obj3.jpg--nodata# not include image data but relative image path in JSON filelabelmeapc2016_obj3.jpg\\--labelshighland_6539_self_stick_notes,mead_index_cards,kong_air_dog_squeakair_tennis_ball# specify label list# semantic segmentation examplecdexamples/semantic_segmentation\nlabelmedata_annotated/# Open directory to annotate all images in itlabelmedata_annotated/--labelslabels.txt# specify label list with a fileFor more advanced usage, please refer to the examples:Tutorial (Single Image Example)Semantic Segmentation ExampleInstance Segmentation ExampleVideo Annotation ExampleCommand Line Arguments--outputspecifies the location that annotations will be written to. If the location ends with .json, a single annotation will be written to this file. Only one image can be annotated if a location is specified with .json. If the location does not end with .json, the program will assume it is a directory. Annotations will be stored in this directory with a name that corresponds to the image that the annotation was made on.The first time you run labelme, it will create a config file in~/.labelmerc. You can edit this file and the changes will be applied the next time that you launch labelme. If you would prefer to use a config file from another location, you can specify this file with the--configflag.Without the--nosortlabelsflag, the program will list labels in alphabetical order. When the program is run with this flag, it will display labels in the order that they are provided.Flags are assigned to an entire image.ExampleLabels are assigned to a single polygon.ExampleFAQHow to convert JSON file to numpy array?Seeexamples/tutorial.How to load label PNG file?Seeexamples/tutorial.How to get annotations for semantic segmentation?Seeexamples/semantic_segmentation.How to get annotations for instance segmentation?Seeexamples/instance_segmentation.Developinggitclonehttps://github.com/wkentaro/labelme.gitcdlabelme# Install anaconda3 and labelmecurl-Lhttps://github.com/wkentaro/dotfiles/raw/main/local/bin/install_anaconda3.sh|bash-s.source.anaconda3/bin/activate\npipinstall-e.How to build standalone executableBelow shows how to build the standalone executable on macOS, Linux and Windows.# Setup condacondacreate--namelabelmepython=3.9\ncondaactivatelabelme# Build the standalone executablepipinstall.\npipinstallpyinstaller\npyinstallerlabelme.spec\ndist/labelme--versionHow to contributeMake sure below test passes on your environment.See.github/workflows/ci.ymlfor more detail.pipinstall-rrequirements-dev.txt\n\nflake8.\nblack--line-length79--checklabelme/MPLBACKEND='agg'pytest-vsxtests/AcknowledgementThis repo is the fork ofmpitid/pylabelme."} +{"package": "xllib", "pacakge-description": "ComposerA Composer of Tables.pipinstallcomposerUsageSeeColab Notebookfor demo.ToDoCT.drop()method for dropping columns/rowsCT.iloc[1:3, 2:5]select/modify cell/row/columns[^1][^1]: Refer tolink1andlink2for potential implementation."} +{"package": "xl-link", "pacakge-description": "# XLLink for PandasQuick-start: https://0hughman0.github.io/xl_link/quickstart.htmlInstallation: `pip install xl_link`XLLink aims to provide a powerfull interface between Pandas DataFrames, and Excel spreadsheets.XLLink tweaks the DataFrame.to_excel method to return its own XLMap object.This XLMap stores all the information about the location of the written DataFrame within the spreadsheet.By allowing you to use Pandas indexing methods, i.e. loc, iloc, at and iat. XLLink remains intuitive to use. But instead of returning a DataFrame, Series, or scalar, XLMap will instead return the XLRange, or XLCell corresponding to the location of the result within your spreadsheet.Additionally XLMaps offer a wrapper around excel engines (currently supporting xlsxwriter and openpyxl) to make creating charts in excel far more intuitive. Providing a DataFrame.plot like interface for excel charts.## Chart democreating a complex chart is as easy as:>>> f = XLDataFrame(index=('Breakfast', 'Lunch', 'Dinner', 'Midnight Snack'),\n data={'Mon': (15, 20, 12, 3),\n 'Tues': (5, 16, 3, 0),\n 'Weds': (3, 22, 2, 8),\n 'Thur': (6, 7, 1, 9)})\n>>> xlmap = f.to_excel('Chart.xlsx', sheet_name=\"XLLinked\", engine='openpyxl')\n>>> xl_linked_chart = xlmap.create_chart('bar', title=\"With xl_link\", x_axis_name=\"Meal\", y_axis_name=\"Calories\", subtype='col')\n>>> xlmap.sheet.add_chart(xl_linked_chart, 'F1')\n>>> xlmap.writer.save()Producing this chart:![multi bar chart](https://raw.githubusercontent.com/0Hughman0/xl_link/master/examples/BarExample.png)## Formatting demoApplying conditional formatting to a table is as easy as:>>> import numpy as np\n>>> xy_data = XLDataFrame(data={'Y1': np.random.rand(10) * 10,\n 'Y2': np.random.rand(10) * 10})\n>>> xlmap = xy_data.to_excel(\"ConditionalFormatting.xlsx\", engine='xlsxwriter')\n>>> xlmap.sheet.conditional_format(xlmap.data.range, # position of data within spreadsheet\n {'type': '3_color_scale',\n 'min_type': 'num', 'min_value': xlmap.f.min().min(), 'min_color': 'green',\n 'mid_type': 'num', 'mid_value': xlmap.f.mean().mean(), 'mid_color': 'yellow',\n 'max_type': 'num', 'max_value': xlmap.f.max().max(), 'max_color': 'red'})\n>>> xlmap.writer.save()![conditional formatting](https://raw.githubusercontent.com/0Hughman0/xl_link/master/examples/ConditionalFormattingExample.png)Check out the examples folder for more examples!This package uses the utility functions from XlsxWriter under the BSD license found here:https://github.com/jmcnamara/XlsxWriter## Compatibilitypandas >= 0.19Xlsxwriter >= 0.9openpyxl >= 2.4latest tested versions:pandas==0.23.4XlsxWriter==1.0.7- (potential issue with stock chart, using openpyxl recommend if desired)openpyxl==2.5.5Copyright (c) 2018 0Hughman0Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \u201cSoftware\u201d), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \u201cAS IS\u201d, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."} +{"package": "xllm", "pacakge-description": "\ud83e\udd96 X\u2014LLM: Cutting Edge & Easy LLM FinetuningCutting Edge & Easy LLM Finetuning using the most advanced methods (QLoRA, DeepSpeed, GPTQ, Flash Attention 2, FSDP,\netc)Developed\nbyBoris Zubarev|CV|LinkedIn|bobazooba@gmail.comWhy you should use X\u2014LLM \ud83e\ude84Are you usingLarge Language Models (LLMs)for your work and want to train them more efficiently with advanced\nmethods? Wish to focus on the data and improvements rather than repetitive and time-consuming coding for LLM training?X\u2014LLMis your solution. It's a user-friendly library that streamlines training optimization, so you canfocus on\nenhancing your models and data. Equipped withcutting-edge training techniques, X\u2014LLM is engineered for efficiency\nby engineers who understand your needs.X\u2014LLMis ideal whether you'regearing up for productionor need afast prototyping tool.FeaturesHassle-free training for Large Language ModelsSeamless integration of new data and data processingEffortless expansion of the librarySpeed up your training, while simultaneously reducing model sizesEach checkpoint is saved to the \ud83e\udd17 HuggingFace HubEasy-to-use integration with your existing projectCustomize almost any part of your training with easeTrack your training progress usingW&BSupported many \ud83e\udd17 Transformers models\nlikeYi-34B,Mistal AI,Llama 2,Zephyr,OpenChat,Falcon,Phi,Qwen,MPTand many moreBenefit from cutting-edge advancements in LLM training optimizationQLoRA and fusingFlash Attention 2Gradient checkpointingbitsandbytesGPTQ (including post-training quantization)DeepSpeedFSDPAnd many moreQuickstart \ud83e\udd96InstallationX\u2014LLMis tested on Python 3.8+, PyTorch 2.0.1+ and CUDA 11.8.pipinstallxllmVersion which includedeepspeed,flash-attnandauto-gptq:pipinstall\"xllm[train]\"Defaultxllmversion recommended for local development,xllm[train]recommended for training.Training recommended environmentCUDA version:11.8Docker:huggingface/transformers-pytorch-gpu:latestFast prototyping \u26a1fromxllmimportConfigfromxllm.datasetsimportGeneralDatasetfromxllm.experimentsimportExperiment# Init Config which controls the internal logic of xllm# QLoRA exampleconfig=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",apply_lora=True,load_in_4bit=True,)# Prepare the datatrain_data=[\"Hello!\"]*100train_dataset=GeneralDataset.from_list(data=train_data)# Build Experiment from Config: init tokenizer and model, apply LoRA and so onexperiment=Experiment(config=config,train_dataset=train_dataset)experiment.build()# Run Experiment (training)experiment.run()# # [Optional] Fuse LoRA layers# experiment.fuse_lora()# [Optional] Or push LoRA weights to HuggingFace Hubexperiment.push_to_hub(repo_id=\"YOUR_NAME/MODEL_NAME\")HowConfigcontrolsxllmMore about configLoRASimpleconfig=Config(model_name_or_path=\"openchat/openchat_3.5\",apply_lora=True,)Advancedconfig=Config(model_name_or_path=\"openchat/openchat_3.5\",apply_lora=True,lora_rank=8,lora_alpha=32,lora_dropout=0.05,raw_lora_target_modules=\"all\",# Names of modules to apply LoRA. A comma-separated string, for example: \"k,q,v\" or \"all\".)QLoRATo train theQLoRAmodel, we need to load the backbone model usingbitsandbyteslibrary and int4 (or int8) weights.Simpleconfig=Config(model_name_or_path=\"01-ai/Yi-34B\",apply_lora=True,load_in_4bit=True,prepare_model_for_kbit_training=True,)Advancedconfig=Config(model_name_or_path=\"01-ai/Yi-34B\",apply_lora=True,load_in_4bit=True,prepare_model_for_kbit_training=True,llm_int8_threshold=6.0,llm_int8_has_fp16_weight=True,bnb_4bit_use_double_quant=True,bnb_4bit_quant_type=\"nf4\",)Push checkpoints to the HuggingFace HubBefore that, you must log in toHuggingface Hubor add anAPI Tokento the environment variables.config=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",push_to_hub=True,hub_private_repo=True,hub_model_id=\"BobaZooba/AntModel-7B-XLLM-Demo-LoRA\",save_steps=25,)Checkpoints will be saved locally and in Huggingface Hub eachsave_stepsIf you train a model withLoRA, then onlyLoRAweights will be savedReport to W&BBefore that, you must log in toW&Bor add anAPI Tokento the environment variables.config=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",report_to_wandb=True,logging_steps=5,wandb_project=\"xllm-demo\",)Gradient checkpointingThis will help to useless GPU memoryduring training, that is, you will be able to learn more than without this\ntechnique. The disadvantages of this technique is slowing down the forward step, that is,slowing down training.You will be training larger models (for example 7B in colab), but at the expense of training speed.config=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",use_gradient_checkpointing=True,)Flash Attention 2This speeds up training and GPU memory consumption, but it does not work with all models and GPUs. You also need to\ninstallflash-attnfor this. This can be done using:pip install \"xllm[train]\"config=Config(model_name_or_path=\"meta-llama/Llama-2-7b-hf\",use_flash_attention_2=True,)Recommended setupRecommendationsIncredibly effective method is LoRA (apply_lora). It allows for a tremendous reduction in training costs\nand, moreover, helps very effectively combat catastrophic forgetting.Then, I advise usingload_in_4bitandprepare_model_for_kbit_trainingtogether. This also significantly reduces\nmemory consumption.Lastly, I would recommend applyuse_gradient_checkpointing. This method also greatly reduces memory consumption, but\nat the expense of slowing down training.If your project allows, I suggest enablingpush_to_hubandhub_private_repo, also specifying the model name\ninhub_model_idandsave_steps. Example: \"BobaZooba/SupaDupaLlama-7B-LoRA\". During training, every checkpoint of\nyour model will be saved in the HuggingFace Hub. If you specifiedapply_lora, then only the LoRA weights will be\nsaved, which you can later easily fuse with the main model, for example, usingxllm.If your GPU allows it adduse_flash_attention_2I also recommend usingreport_to_wandb, also specifyingwandb_project(the project name in W&B)\nandwandb_entity(user or organization name in W&B).Note that forpush_to_hub, you need to log in to the HuggingFace Hub beforehand or specify the\ntoken (HUGGING_FACE_HUB_TOKEN) in the .env file. Similarly, when usingreport_to_wandb, you will need to log in to\nW&B. You can either specify the token (WANDB_API_KEY) in the .env file or you will be prompted to enter the token on\nthe command line.FeaturesQLoRAGradient checkpointingFlash Attention 2Stabilize trainingPush checkpoints to HuggingFace HubW&B reportconfig=Config(model_name_or_path=\"meta-llama/Llama-2-7b-hf\",tokenizer_padding_side=\"right\",# good for llama2warmup_steps=1000,max_steps=10000,logging_steps=1,save_steps=1000,per_device_train_batch_size=2,gradient_accumulation_steps=2,max_length=2048,stabilize=True,use_flash_attention_2=True,apply_lora=True,load_in_4bit=True,prepare_model_for_kbit_training=True,use_gradient_checkpointing=True,push_to_hub=False,hub_private_repo=True,hub_model_id=\"BobaZooba/SupaDupaLlama-7B-LoRA\",report_to_wandb=False,wandb_project=\"xllm-demo\",wandb_entity=\"bobazooba\",)FuseThis operation is only for models with a LoRA adapter.You can explicitly specify to fuse the model after training.config=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",apply_lora=True,fuse_after_training=True,)Even when you are using QLoRaconfig=Config(model_name_or_path=\"HuggingFaceH4/zephyr-7b-beta\",apply_lora=True,load_in_4bit=True,prepare_model_for_kbit_training=True,fuse_after_training=True,)Or you can fuse the model yourself after training.experiment.fuse_lora()DeepSpeedDeepSpeedis needed for training models onmultiple GPUs.DeepSpeedallows you\ntoefficiently manage the resources of several GPUs during training. For example, you\ncandistribute the gradients and the state of the optimizer to several GPUs, rather than storing a complete set of\ngradients and the state of the optimizer on each GPU. Starting training usingDeepSpeedcan only happen from\nthecommand line.train.pyfromxllmimportConfigfromxllm.datasetsimportGeneralDatasetfromxllm.cliimportcli_run_trainif__name__=='__main__':train_data=[\"Hello!\"]*100train_dataset=GeneralDataset.from_list(data=train_data)cli_run_train(config_cls=Config,train_dataset=train_dataset)Run train (in thenum_gpusparameter, specify as many GPUs as you have)deepspeed--num_gpus=8train.py--deepspeed_stage2You also can pass other parametersdeepspeed--num_gpus=8train.py\\--deepspeed_stage2\\--apply_loraTrue\\--stabilizeTrue\\--use_gradient_checkpointingTrueNotebooksNameCommentLinkX\u2014LLM PrototypingIn this notebook you will learn the basics of the libraryLlama2 & Mistral AI efficient fine-tuning7B model training in colab using QLoRA, bnb int4, gradient checkpointing and X\u2014LLMProduction solution \ud83d\ude80X\u2014LLMenables not only to prototype models, but also facilitates the development of production-ready solutions through\nbuilt-in capabilities and customization.UsingX\u2014LLMto train a model is easy and involves these few steps:Prepare\u2014 Get the data and the model ready by downloading and preparing them. Saves data locally\ntoconfig.train_local_path_to_dataandconfig.eval_local_path_to_dataif you are using eval datasetTrain\u2014 Use the data prepared in the previous step to train the modelFuse\u2014 If you used LoRA during the training, fuse LoRAQuantize\u2014 Optimize your model's memory usage by quantizing itRemember, these tasks inX\u2014LLMstart from the command line. So, when you're all set to go, launching your full project\nwill look something like this:Example how to run your projectDownloading and preparing data and modelpython3MY_PROJECT/cli/prepare.py\\--dataset_keyMY_DATASET\\--model_name_or_pathmistralai/Mistral-7B-v0.1\\--path_to_env_file./.envRun train using DeepSpeed on multiple GPUsdeepspeed--num_gpus=8MY_PROJECT/cli/train.py\\--use_gradient_checkpointingTrue\\--deepspeed_stage2\\--stabilizeTrue\\--model_name_or_pathmistralai/Mistral-7B-v0.1\\--use_flash_attention_2False\\--load_in_4bitTrue\\--apply_loraTrue\\--raw_lora_target_modulesall\\--per_device_train_batch_size8\\--warmup_steps1000\\--save_total_limit0\\--push_to_hubTrue\\--hub_model_idMY_HF_HUB_NAME/LORA_MODEL_NAME\\--hub_private_repoTrue\\--report_to_wandbTrue\\--path_to_env_file./.envFuse LoRApython3MY_PROJECT/cli/fuse.py\\--model_name_or_pathmistralai/Mistral-7B-v0.1\\--lora_hub_model_idMY_HF_HUB_NAME/LORA_MODEL_NAME\\--hub_model_idMY_HF_HUB_NAME/MODEL_NAME\\--hub_private_repoTrue\\--force_fp16True\\--fused_model_local_path./fused_model/\\--path_to_env_file./.env[Optional] GPTQ quantization of the trained model with fused LoRApython3MY_PROJECT/cli/quantize.py\\--model_name_or_path./fused_model/\\--apply_loraFalse\\--stabilizeFalse\\--quantization_max_samples128\\--quantized_model_path./quantized_model/\\--prepare_model_for_kbit_trainingFalse\\--quantized_hub_model_idMY_HF_HUB_NAME/MODEL_NAME_GPTQ\\--quantized_hub_private_repoTrue\\--path_to_env_file./.envRight now, theX\u2014LLMlibrary lets you use only theSODA dataset. We've\nset it up this way for demo purposes, but we're planning to add more datasets soon. You'll need to figure out how to\ndownload and handle your dataset. Simply put, you take care of your data, andX\u2014LLMhandles the rest. We've done it\nthis\nway on purpose, to give you plenty of room to get creative and customize to your heart's content.You can customize your dataset in detail, adding additional fields. All of this will enable you to implement virtually\nany task in the areas ofSupervised LearningandOffline Reinforcement Learning.At the same time, you always have an easy way to submit data for language modeling.ExamplefromxllmimportConfigfromxllm.datasetsimportGeneralDatasetfromxllm.cliimportcli_run_trainif__name__=='__main__':train_data=[\"Hello!\"]*100train_dataset=GeneralDataset.from_list(data=train_data)cli_run_train(config_cls=Config,train_dataset=train_dataset)Build your own projectTo set up your own project usingX\u2014LLM, you need to do two things:Implement your dataset (figure out how to download and handle it)AddX\u2014LLM's command-line tools into your projectOnce that's done, your project will be good to go, and you can start running the steps you need (like prepare, train,\nand so on).To get a handle on building your project withX\u2014LLM, check out the materials below.Useful materialsGuide: here, we go into detail about everything the library can\ndoDemo project: here's a step-by-step example of how to useX\u2014LLMand fit\nit\ninto your own projectWeatherGPT: this repository features an example of how to utilize the xllm library. Included is a solution for a common type of assessment given to LLM engineers, who typically earn between $120,000 to $140,000 annuallyShurale: project with the finetuned 7B Mistal modelConfig \ud83d\udd27TheX\u2014LLMlibrary uses a single config setup for all steps like preparing, training and the other steps. It's\ndesigned in a way that\nlets you easily understand the available features and what you can adjust.Confighas control almost over every\nsingle part of each step. Thanks to the config, you can pick your dataset, set your collator, manage the type of\nquantization during training, decide if you want to use LoRA, if you need to push a checkpoint to theHuggingFace Hub,\nand a\nlot more.Config path:src.xllm.core.config.ConfigOrfromxllmimportConfigUseful materialsImportant config fields for different stepsHow do I choose the methods for training?Detailed description of all config fieldsCustomization options \ud83d\udee0You have the flexibility to tweak many aspects of your model's training: data, how data is processed, trainer, config,\nhow the model is loaded, what happens before and after training, and so much more.We've got ready-to-use components for every part of thexllmpipeline. You can entirely switch out some components\nlike the dataset, collator, trainer, and experiment.\nFor some components like experiment and config, you have the option to just build on what's already there.Useful materialsHow to implement datasetHow to add CLI tools to your projectHow to implement collatorHow to implement trainerHow to implement experimentHow to extend configProjects using X\u2014LLM \ud83c\udfc6Building something cool withX\u2014LLM? Kindly reach out to me\natbobazooba@gmail.com. I'd love to hear from you.Hall of FameWrite to us so that we can add your project.Shurale7B-v1Shurale7B-v1-GPTQBadgeConsider adding a badge to your model card.[](https://github.com/BobaZooba/xllm)Testing \ud83e\uddeaAt the moment, we don't have Continuous Integration tests that utilize a GPU. However, we might develop these kinds of\ntests in the future. It's important to note, though, that this would require investing time into their development, as\nwell as funding for machine maintenance.Future Work \ud83d\udd2eAdd more teststAdd RunPod deploy functionAddDPOcomponentsAdd Callbacks toExperimentGPU CI using RunPodSolve DeepSpeed + push_to_hub checkpoints bugMake DeepSpeed Stage 3 + bitsandbytes works correcAdd multipackingAdd adaptive batch sizeFix caching in CIAdd sequence bucketingAdd more datasetsMaybe addtensor_parallelTale QuestTale Questis my personal project which was built usingxllmandShurale. It's an interactive text-based game\ninTelegramwith dynamic AI characters, offering infinite scenariosYou will get into exciting journeys and complete fascinating quests. Chat\nwithGeorge Orwell,Tech Entrepreneur,Young Wizard,Noir Detective,Femme Fataleand many moreTry it now:https://t.me/talequestbotPlease support me here"} +{"package": "xlm", "pacakge-description": "No description available on PyPI."} +{"package": "xlmg", "pacakge-description": "No description available on PyPI."} +{"package": "xlmhg", "pacakge-description": "masterdevelopThis is an efficient Python/Cython implementation of the semiparametricXL-mHG testfor enrichment in ranked lists. The XL-mHG test is an extension\nof the nonparametricmHG test, which was developed byDr. Zohar\nYakhiniand colleagues.Installation$pipinstallxlmhgGetting startedThexlmhgpackage provides two functions (one simple and more more advanced)\nfor performing XL-mHG tests. These functions are documented in theUser Manual. Here\u2019s a quick example using the \u201csimple\u201d test function:importxlmhgstat,cutoff,pval=xlmhg.xlmhg_test(v,X,L)Where:vis the ranked list of 0\u2019s and 1\u2019s, represented by a NumPy array of\nintegers,XandLare the XL-mHG parameters, and the return values have\nthe following meanings:stat: The XL-mHG test statisticcutoff: The cutoff at which XL-mHG test statistic was attainedpval: The XL-mHG p-valueDocumentationPlease refer to theXL-mHG User Manual(hosted on ReadTheDocs).Citing XL-mHGIf you use the XL-mHG test in your research, please citeEden et al. (PLoS\nComput Biol, 2007)andWagner (PLoS One, 2015).Copyright and LicenseCopyright (c) 2015-2019 Florian WagnerRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n* Redistributions of source code must retain the above copyright notice, this\nlist of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright notice,\nthis list of conditions and the following disclaimer in the documentation\nand/or other materials provided with the distribution.\n\n* Neither the name of the copyright holder nor the names of its\ncontributors may be used to endorse or promote products derived from\nthis software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE."} +{"package": "xlmhglite", "pacakge-description": "XL-mHG LiteUseful links:Documentation|Source code|Bug reports|||||xlmhgis an efficient Python/Cython implementation of the semiparametricXL-mHG testfor enrichment in ranked lists. The XL-mHG test is an extension\nof the nonparametricmHG test, which was developed byDr. Zohar\nYakhiniand colleagues.xlmhgliteis a fork of the originalxlmhgpackage (which is unfortunately no longer being maintained).\nThis fork was updated to support modern Python versions (Python >=3.8), fix bugs in the original implementation,\nand reduce the mandatory dependencies of the project to a minimum.\nTo that end, the plotting functionality ofxlmhgis not part of the corexlmhglitepackage, instead being an optional requirement.InstallationTo install the core (\u201clite\u201d) version ofxlmhglite:\n.. code-block:: bash$ pip install xlmhgliteTo install the complete version ofxlmhglite(including the plotting functionality):\n.. code-block:: bash$ pip install xlmhglite[\u2018all\u2019]Getting startedThexlmhglitepackage provides two functions (one simple and more more advanced)\nfor performing XL-mHG tests. These functions are documented in theUser Manual. Here\u2019s a quick example using the \u201csimple\u201d test function:importxlmhglitestat,cutoff,pval=xlmhglite.xlmhg_test(v,X,L)Where:vis the ranked list of 0\u2019s and 1\u2019s, represented by a NumPy array of\nintegers,XandLare the XL-mHG parameters, and the return values have\nthe following meanings:stat: The XL-mHG test statisticcutoff: The cutoff at which XL-mHG test statistic was attainedpval: The XL-mHG p-valueXL-mHG Lite DocumentationPlease refer to theXL-mHG User Manual.Citing XL-mHGIf you use the XL-mHG test in your research, please citeEden et al. (PLoS\nComput Biol, 2007)andWagner (PLoS One, 2015).Copyright and LicenseCopyright (c) 2015-2019 Florian WagnerRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n* Redistributions of source code must retain the above copyright notice, this\nlist of conditions and the following disclaimer.\n\n* Redistributions in binary form must reproduce the above copyright notice,\nthis list of conditions and the following disclaimer in the documentation\nand/or other materials provided with the distribution.\n\n* Neither the name of the copyright holder nor the names of its\ncontributors may be used to endorse or promote products derived from\nthis software without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.History1.1.0 (2023-06-11)This version improves clarity of warning messages and addresses some additional bugs.\nMoreover, the project has been transitioned to use pyproject.toml and setup.cfg, and old code was cleaned up for better maintainability.ChangedWarning messages regarding failed import of the cython module were made more informative.Transitioned the project to use pyproject.toml and setup.cfg, and cleaned up legacy code from setup.py.FixedFixed bug where calculating enrichment scores using the pure Python implementation would raise an AttributeError.Fixed bug where the pure Python implementation would raise an ImportError if numba is not already installed on the system.1.0.1 (2023-06-11)Minor patch addressing installation issues.1.0.0 (2023-06-10)First stable release."} +{"package": "xlms-tools", "pacakge-description": "xlms-toolsDescriptionxlms-tools is a set of command line tools to apply crosslinking mass spectrometry (XL-MS) data to protein structure models.Setting up xlms-toolsxlms-tools can be installed directly from PyPI, as follows:$pipinstallxlms-toolsOr alternatively, by downloading or cloning this repository, and running the following from the project directory:$pipinstalldist/xlms_tools-1.0.3-py3-none-any.whlUsing xlms-toolsCurrently, xlms-tools can be run in two modes. The first is to score how well a protein structure model agrees with XL-MS data, which is specified as a list crosslinks and monolinks derived from a XL-MS experiment. The second mode is to compute the depths of individual residues in protein structures.To score how well a protein structure agrees with XL-MS dataFirst, format crosslinks and monolinks into a text file with the following format:98|A|147|A5.1#72|A|161|A4.3# crosslinks: ||| 72|A|180|A2.7#35|A1.9#137|A5.3# monolinks: | 97|A2.6#where each line corresponds to either a crosslink or a monolink. Optionally, a numerical value can be appended at the end of each line, corresponding to the occupancy of each individual monolink or crosslink. For a detailed discussion on occupancy, please refer to the paper.Score protein structure model/s:\nTo compute the crosslink (XLP) and monolink probability (MP) scores of one or more protein structures, execute the following in the command line:$xlms-tools-mscore-l[listofcrosslinksand/ormonolinks][PDBfile/s]--name[nameofrun]Example files can be found in the tests/ directory. You can navigate to the tests/ directory and run the scoring, as follows:$xlms-tools-mscore-lxlms_data_qtv.txtmodel_1.pdb--namewithoccupancy_m1#score model_1.pdb$xlms-tools-mscore-lxlms_data_qtv.txtmodel_*pdb--namewithoccupancy_all#score all modelsThe outputs include (a) a tab-separated (.tsv) file containing the scores, which can be viewed using a spreadsheet editor, as well as (b) a ChimeraX command (.cxc) file, which can be executed by double-clicking the .cxc file (given a working installation of ChimeraX). In the ChimeraX visualization, crosslinks and monolinks are color-coded: blue means that the spanning distance of the crosslink, or the residue depth of the monolinked residue, are well within the cutoff, red stands for a maximum distance violation (for crosslinks) or a maximum depth violation (for monolinks), while yellow is within the cutoff, but approaching it. The distance cutoffs are currently only defined for BS3/DSS, but will be expanded in future releases.link typeblueyellowredany monolinkdepth \u2264 6.25\u00c5-depth > 6.25\u00c5BS3 or DSS crosslinkCA-CA distance \u2264 21\u00c521\u00c5 < CA-CA distance \u2264 33\u00c5CA-CA distance > 33\u00c5To compute residue depths in a protein structureRun the following command:$xlms-tools-mdepth[PDBfile/s]Example files can be found in the tests/ directory. You can navigate to the tests/ directory and run the depth computations, as follows:$xlms-tools-mdepthmodel_1.pdb#compute residue depths for model_1.pdb$xlms-tools-mdepthmodel_*pdb#compute residue depths for all modelsEach line of the output file (.depth file) corresponds to one residue# format: :\t\tA:26LYS4.317777777777779A:27LEU4.608300983124843\nA:28VAL5.739574753218949\nA:29VAL8.684474490011493\nA:30ALA8.926983412282244\nA:31THR8.0268463237516\nA:32ASP6.0348264453008715\nA:33THR4.487608873498731\nA:34ALA4.371281572999748\nA:35PHE5.2527378512712275\nA:36VAL5.226420625104608\nA:37PRO6.844806528409208\n...APIxlms_tools.depth.computedepth(biopdbstruct)Computes the depth of each residue in a Biopython PDB structureParameters:biopdbstruct: an instance of theBio.PDB structure classReturns:depths: dictionary containing residue depths, with key-value pairs in the format chainid:residue#-residue_depthresidues: dictionary containing residue names, with key-value pairs in the format chainid:residue#-residue_nameExample usage:fromBio.PDBimportPDBParser\nfromxlms_tools.depthimportcomputedepthparser=PDBParser()biopdbstruct=parser.get_structure('test','tests/bigmodel.pdb')depths,residues=computedepth(biopdbstruct)xlms_tools.score.linkmetrics(biopdbstruct,link,depths,linkweight=1.0,linker='BS3/DSS')Computes the score and CA-CA distance/residue depth in a Biopython PDB structure for a given crosslink or monolink.Parameters:biopdbstruct: an instance of theBio.PDB structure classlink: a tuple defining either a monolink (residue#, chainid), or a crosslink (residue#_1, chainid_1, residue#_2, chainid_2)depths: dictionary of residue depths (fromxlms_tools.depth.computedepth(biopdbstruct))linkweight: for quantitative XL-MS data, a measure of relative abundance or occupancy. If unspecified, default weight is 1.0linker: crosslinking reagent used (if unspecified, default is BS3/DSS)Returns:score: monolink probability (MP) score for a monolink, crosslink probability (XLP) score for a crosslinkmonolinkdepth: depth of the monolinked residuecrosslinkdistance: CA-CA distance of crosslinkExample usage:fromBio.PDBimportPDBParser\nfromxlms_tools.depthimportcomputedepth\nfromxlms_tools.scoreimportlinkmetricsparser=PDBParser()biopdbstruct=parser.get_structure('test','tests/bigmodel.pdb')depths,residues=computedepth(biopdbstruct)# compute monolink scorempscore,mpdepth=linkmetrics(biopdbstruct,(1,'A'),depths)# computed crosslink scorexlpscore,distance=linkmetrics(biopdbstruct,(1049,'B',1409,'B'),depths)CitationsWhen using xlms-tools, please cite:\nManalastas-Cantos, K., Adoni, K. R., Pfeifer, M., M\u00e4rtens, B., Gr\u00fcnewald, K., Thalassinos, K., & Topf, M. (2024). Modeling flexible protein structure with AlphaFold2 and cross-linking mass spectrometry. Molecular & Cellular Proteomics.https://doi.org/10.1016/j.mcpro.2024.100724"} +{"package": "xl_nester", "pacakge-description": "UNKNOWN"} +{"package": "xlnet-tensorflow", "pacakge-description": "XLNet for TensorFlowThis is a fork of the originalXLNet repositorythat adds package configuration so that it can be easily installed and used.\nThe purpose is to remove the need of cloning the repository and modifying it\nlocally which can be quite dirty for common tasks (e.g. training a new classifier).\nA lot of code can be shared (e.g.modeling.py,classifier_utils.py) and this\nfork is exactly for that.All the credit goes tozihangdai/xlnet.Please refer to the official repository for details on how to use the modules\ncontained in this package. Useful information can also be found\nin theXLNet paper.Release NotesSeptember 5, 2019: Initial version -v1.0.1;September 7, 2019: version -v1.1.October 25, 2019: version -v1.1.1."} +{"package": "xloaderx", "pacakge-description": "No description available on PyPI."} +{"package": "xlocal", "pacakge-description": "This module provides execution locals aka \u201cxlocal\u201d objects which implement\na more restricted variant of \u201cthread locals\u201d. An execution local allows to\nmanage attributes on a per-execution basis in a manner similar to how real\nlocals work:Invoked functions cannot change the binding for the invoking functionexistence of a binding is local to a code block (and everything it calls)Attribute bindings for an xlocal objects will not leak outside a\ncontext-managed code block and they will not leak to other threads of\ngreenlets. By contrast, both process-globals and so called \u201cthread\nlocals\u201d do not implement the above properties.Let\u2019s look at a basic example:# content of example.py\n\nfrom xlocal import xlocal\n\nxcurrent = xlocal()\n\ndef output():\n print \"hello world\", xcurrent.x\n\nif __name__ == \"__main__\":\n with xcurrent(x=1):\n output()If we execute this module, theoutput()function will see\naxcurrent.x==1binding:$ python example.py\nhello world 1Here is what happens in detail:xcurrent(x=1)returns a context manager which\nsets/resets thexattribute on thexcurrentobject. While remaining\nin the same thread/greenlet, all code triggered by the with-body (in this case\njust theoutput()function) can accessxcurrent.x. Outside the with-\nbodyxcurrent.xwould raise an AttributeError. It is also not allowed\nto directly setxcurrentattributes; you always have to explicitely mark their\nlife-cycle with a with-statement. This means that invoked code:cannot rebind xlocal state of its invoking functions (no side effects, yay!)xlocal state does not leak outside the with-context (lifecylcle control)Another module may now reuse the example code:# content of example_call.py\nimport example\n\nwith example.xcurrent(x=3):\n example.output()which when running \u2026:$ python example_call.py\nhello world 3will cause theexample.output()function to print thexcurrent.xbinding\nas defined at the invokingwith xcurrent(x=3)statement.Other threads or greenlets will never see thisxcurrent.xbinding; they may even\nset and read their own distincitxcurrent.xobject. This means that all\nthreads/greenlets can concurrently call into a function which will always\nsee the execution specificxattribute.Usage in frameworks and libraries invoking \u201chandlers\u201dWhen invoking plugin code or handler code to perform work, you may not\nwant to pass around all state that might ever be needed. Instead of using\na global or thread local you can safely pass around such state in\nexecution locals. Here is a pseudo example:xcurrent = xlocal()\n\ndef with_xlocal(func, **kwargs):\n with xcurrent(**kwargs):\n func()\n\ndef handle_request(request):\n func = gethandler(request) # some user code\n spawn(with_xlocal(func, request=request))handle_requestwill run a user-provided handler function in a newly\nspawned execution unit (for example spawn might map tothreading.Thread(...).start()or togevent.spawn(...)). The\ngenericwith_xlocalhelper wraps the execution of the handler\nfunction so that it will see axcurrent.requestbinding. Multiple\nspawns may execute concurrently andxcurrent.requestwill\ncarry the execution-specific request object in each of them.Issues worth notingIf a method memorizes an attribute of an execution local, for\nexample the abovexcurrent.request, then it will keep a reference to\nthe exact request object, not the per-execution one. If you want to\nkeep a per-execution local, you can do it this way for example:Class Renderer:\n @property\n def request(self):\n return xcurrent.requestthis means that Renderer instances will have an execution-localself.requestobject even if the life-cycle of the instance crosses\nexecution units.Another issue is that if you spawn new execution units, they will not\nimplicitely inherit execution locals. Instead you have to wrap\nyour spawning function to explicitely set execution locals, similar to\nwhat we did in the above \u201cinvoking handlers\u201d section.Copyright / inspirationThis code is based on discussions with Armin Ronacher and others\nin response to atweet of mine. It extracts and refines some ideas found in Armin\u2019s \u201cwerzeug.local\u201d module\nand friends.copyright:2012 by Holger Krekel, partially Armin Ronacherlicense:BSD, see LICENSE for more details."} +{"package": "xlocale", "pacakge-description": "This package exposes part of the xlocale-family of C functions to Python. This\nis particularly useful to set the locale per-thread.Normally you use thelocale.setlocalefunction to change the locale for the entire process:import locale\n\nlocale.setlocale(locale.LC_ALL, 'nl_NL')This may not be desirable for webservers or other applications that use\nmultiple threads. To change the locale for just the current thread you\ndo this:import xlocale\n\nloc = xlocale.Locale(xlocale.LC_ALL_MASK, 'nl_NL')\nloc.use()Creating a locale objectxlocale.Locale([mask[, locale[, base]])Create a new locale object. The new locale is created by taken\na base locale and changing one or more locale categories. If\nno base is given the C locale will be used.maskis a bitmask build from theLC_*_MASKconstants. Normally you\nwill want to useLC_ALL_MASKto change the locale completely.localeis a string with the locale name. If not provided the C locale\nwill be used.xlocale.Locale.current_locale()Return a Locale instance for the currently locale.Locale instancesLocale.use()Switch the locale for the current thread.Locale.name(mask)Return the name for a locale category.maskis a bitmask of locale\ncategories, and the name for the first configured category will be returned.This method is not available on all platforms, and will raise an exception\non unsupported platforms.Locale.lconv()Return information describing how numbers and currency values must be\ndisplayed in the current locale. This is an object with the following\nattributes:decimal_pointThe decimal point character, except for currency\nvalues, cannot be an empty string.thousands_sepThe separator between groups of digits before the\ndecimal point, except for currency values.groupingThe sizes of the groups of digits, except for currency\nThis is a list of integers representing group size\nfrom low order digit groups to high order (right to\nleft). The list may be terminated with 0 or CHAR_MAX.\nIf the list is terminated with 0 the last group size\nbefore the 0 is repeated to account for all the\ndigits. If the list isterminated with CHAR_MAX, no\nmore grouping is performed.int_curr_symbolThe standardized international currency symbol.currency_symbolThe local currency symbol.mon_decimal_pointThe decimal point character for currency values.mon_thousands_sepThe separator for digit groups in currency values.mon_groupingLike grouping but for currency values.positive_signThe character used to denote nonnegative currency\nvalues, usually the empty string.negative_signThe character used to denote negative currency values,\nusually a minus sign.int_frac_digitsThe number of digits after the decimal point in an\ninternational-style currency value.frac_digitsThe number of digits after the decimal point in the\nlocale style for currency values.p_cs_precedesTrue if the currency symbol precedes the currency\nvalue for nonnegative values, False if it follows.p_sep_by_spaceTrue if a space is inserted between the currency\nsymbol and the currency value for nonnegative values,\nFalse otherwise.n_cs_precedesLike p_cs_precedes but for negative values.n_sep_by_spaceLike p_sep_by_space but for negative values.p_sign_posnThe location of the positive_sign with respect to a\nnonnegative quantity and the currency_symbol, coded as\nfollows:0 - Parentheses around the entire string.1 - Before the string.2 - After the string.3 - Just before currency_symbol.4 - Just after currency_symbol.n_sign_posnLike p_sign_posn but for negative currency values.int_p_cs_precedesSame as p_cs_precedes, but for internationally\nmonetary quantities.\nformatted monetary quantities.int_n_cs_precedesSame as n_cs_precedes, but for internationally\nmonetary quantities.\nformatted monetary quantities.int_p_sep_by_spaceSame as p_sep_by_space, but for internationally\nformatted monetary quantities.int_n_sep_by_spaceSame as n_sep_by_space, but for internationally\nformatted monetary quantities.int_p_sign_posnSame as p_sign_posn, but for internationally formatted\nmonetary quantities.int_n_sign_posnSame as n_sign_posn, but for internationally formatted\nmonetary quantities.ConstantsConstantDescriptionLC_COLLATE_MASKCollationLC_CTYPE_MASKCharacter typeLC_MESSAGES_MASKMessagesLC_MONETARY_MASKMonetaryLC_NUMERIC_MASKNumericLC_TIME_MASKTimeLC_ALL_MASKCombination of all of the above.Changelog1.3.4 - February 25, 2018More Python 3 compilation fixes.1.3.3 - February 25, 2018Python 3 has no PyInt.1.3.2 - February 25, 2018Fix handling of exceptions raised when creating a Locale: they are now\ncorrectly seen as being raised in the constructor.1.3.1 - February 23, 2018Add Python 3 support.Add manylinux support.1.2 - November 15, 2014No longer return the current locale from Locale.use(). This created\nunsolvable double free problems.1.1 - October 10, 2014Fix a memory handling error in Locale.use() which could result in a segfault\nwhen using a locale instance multiple times.1.0 - August 27, 2014First release"} +{"package": "xlock", "pacakge-description": "No description available on PyPI."} +{"package": "xlocust-bigquery", "pacakge-description": "No description available on PyPI."} +{"package": "xlog", "pacakge-description": "No description available on PyPI."} +{"package": "xloger", "pacakge-description": "No description available on PyPI."} +{"package": "xlogger", "pacakge-description": "Something about xloggerI'm a python starter, when I learn the logging section,\nI thought that writing the logging format is so 'non-python',\nand I have to write the same 'anti-human' codes every where.\nLogs are important and should be used more. And in more simple way.So I checked StackOverflow for some inspiration, and I actually learned some.Here is the module I made, in fact, it's the first one I wrote that should be\nshared at pypi I thought.Hope you guys enjoy it:)Usagejust copy the code, it have no dependencies. this is the way recommended,\nbecause you can make your own logger customized easily by setting some variables.or if you want to installpip3 install xloggerthen add lines to your code:fromxloggerimportxloggerlogger=xlogger.get_my_logger(__name__)and then just use logger as usual.Main references'How can I color Python logging output?'https://stackoverflow.com/questions/384076/how-can-i-color-python-logging-outputThankSergey Pleshakov - my code base on your code."} +{"package": "xlogger-lob", "pacakge-description": "No description available on PyPI."} +{"package": "xlogging", "pacakge-description": "No description available on PyPI."} +{"package": "xlogin", "pacakge-description": "UNKNOWN"} +{"package": "xlogit", "pacakge-description": "Examples|Docs|Installation|API Reference|Contributing|ContactQuick startThe following example usesxlogitto estimate a mixed logit model for choices of electricity supplier (See the data here). The parameters are:X: 2-D array of input data (in long format) with choice situations as rows, and variables as columnsy: 1-D array of choices (in long format)varnames: List of variable names that matches the number and order of the columns inXalts: 1-D array of alternative indexes or an alternatives listids: 1-D array of the ids of the choice situationspanels: 1-D array of ids for panel formationrandvars: dictionary of variables and their mixing distributions (\"n\"normal,\"ln\"lognormal,\"t\"triangular,\"u\"uniform,\"tn\"truncated normal)The current version ofxlogitonly supports input data in long format.# Read data from CSV fileimportpandasaspddf=pd.read_csv(\"examples/data/electricity_long.csv\")# Fit the model with xlogitfromxlogitimportMixedLogitvarnames=['pf','cl','loc','wk','tod','seas']model=MixedLogit()model.fit(X=df[varnames],y=df['choice'],varnames=varnames,ids=df['chid'],panels=df['id'],alts=df['alt'],n_draws=600,randvars={'pf':'n','cl':'n','loc':'n','wk':'n','tod':'n','seas':'n'})model.summary()GPU processing enabled.\nOptimization terminated successfully.\n Current function value: 3888.413414\n Iterations: 46\n Function evaluations: 51\n Gradient evaluations: 51\nEstimation time= 2.6 seconds\n----------------------------------------------------------------------\nCoefficient Estimate Std.Err. z-val P>|z|\n----------------------------------------------------------------------\npf -0.9996286 0.0331488 -30.1557541 9.98e-100 ***\ncl -0.2355334 0.0220401 -10.6865870 1.97e-22 ***\nloc 2.2307891 0.1164263 19.1605300 5.64e-56 ***\nwk 1.6251657 0.0918755 17.6887855 6.85e-50 ***\ntod -9.6067367 0.3112721 -30.8628296 2.36e-102 ***\nseas -9.7892800 0.2913063 -33.6047603 2.81e-112 ***\nsd.pf 0.2357813 0.0181892 12.9627201 7.25e-31 ***\nsd.cl 0.4025377 0.0220183 18.2819903 2.43e-52 ***\nsd.loc 1.9262893 0.1187850 16.2166103 7.67e-44 ***\nsd.wk -1.2192931 0.0944581 -12.9083017 1.17e-30 ***\nsd.tod 2.3354462 0.1741859 13.4077786 1.37e-32 ***\nsd.seas -1.4200913 0.2095869 -6.7756668 3.1e-10 ***\n----------------------------------------------------------------------\nSignificance: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nLog-Likelihood= -3888.413\nAIC= 7800.827\nBIC= 7847.493For more examples ofxlogitseethis Jupyter Notebook in Google Colab.Google Colab provides GPU resources for free, which will significantly speed up your model estimation usingxlogit.Quick installInstallxlogitusingpipas follows:pipinstallxlogitHintTo enable GPU processing, you must install theCuPy Python library. Whenxlogitdetects that CuPy is properly installed, it switches to GPU processing without any additional setup. If you use Google Colab, CuPy is usually installed by default.For additional installation details check xlogit installation instructions at:https://xlogit.readthedocs.io/en/latest/install.htmlNo GPU? No problemxlogitcan also be used without a GPU. However, if you need to speed up your model estimation, there are several low cost and even free options to access cloud GPU resources. For instance:Google Colaboffers free GPU resources with no setup required, as the service can be accessed using a web browser. Using xlogit in Google Colab is very easy as it runs out of the box without having to to install CUDA or CuPy, which are installed by default. For examples of xlogit running in Google Colabsee this link.Amazon Sagemaker Studio Laboffers Python runtime environments with free GPUs.Google Cloud platformoffers GPU processing at less than $1 USD per hour for NVIDIA Tesla K80 GPU with 4,992 CUDA cores.Amazon Sagemakeroffers virtual machine instances with the same TESLA K80 GPU at a similar price range of less than $1 USD per hour.BenchmarkAs shown in the plots below,xlogitis significantly faster than existing estimation packages. Also,xlogitprovides convenient scaling when the number of random draws increases. These results were obtained using a modest and low-cost NVIDIA GTX 1060 graphics card. More sophisticated graphics cards are expected to provide even faster estimation times. For additional details about this benchmark and for replication instructions checkhttps://xlogit.readthedocs.io/en/latest/benchmark.html.NotesThe current version allows estimation of:Mixed Logitwith several types of mixing distributions (normal, lognormal, triangular, uniform, and truncated normal)Mixed Logitwith panel dataMixed Logitwith unbalanced panel dataMixed Logitwith Halton drawsMultinomial LogitmodelsConditional logitmodelsHandling of unbalanced availability of choice alternatives for all of the supported modelsPost-estimation tools for prediction and specification testingInclusion of sample weights for all of the supported modelsContributorsThe following contributors have tremendously helped in the enhancement and expansion ofxlogit\u2019s features.@crforsytheJohn Helveston (@jhelvy)ContactIf you have any questions, ideas to improvexlogit, or want to report a bug,chat with us on gitteror open anew issue in xlogit\u2019s GitHub repository.CitingxlogitPlease citexlogitas follows:Arteaga, C., Park, J., Beeramoole, P. B., & Paz, A. (2022). xlogit: An open-source Python package for GPU-accelerated estimation of Mixed Logit models. Journal of Choice Modelling, 42, 100339.https://doi.org/10.1016/j.jocm.2021.100339Or using BibTex as follows:@article{xlogit,\n title = {xlogit: An open-source Python package for GPU-accelerated estimation of Mixed Logit models},\n author = {Cristian Arteaga and JeeWoong Park and Prithvi Bhat Beeramoole and Alexander Paz},\n journal = {Journal of Choice Modelling},\n volume = {42},\n pages = {100339},\n year = {2022},\n issn = {1755-5345},\n doi = {https://doi.org/10.1016/j.jocm.2021.100339},\n}"} +{"package": "xlogs", "pacakge-description": "python-xlogslogging toolkitinstallpip install xlogsUsage1. Use as decoratorfromxlogsimportlogif__name__=='__main__':# config_file: the logging config template, use the default if None@log(log_dir='./logs',config_file=None)defdivision():pass2. Load from ini config filefromxlogsimportLogConfigimportloggingif__name__=='__main__':LogConfig(config_file='/xxx.ini',log_file='/xxx/')logging.info('Default load to root')info=logging.getLogger('root')info.info('write msg to test.log')info=logging.getLogger('test')info.info('write msg to message.log')info=logging.getLogger('info')info.info('write msg to info.log')error=logging.getLogger('error')error.error('write msg to error.log')# reload a new config fileLogConfig(config_file='/yyy.ini',log_file='/yyy/').reset()logging.getLogger().info(\"info with new logger\")3. config with argsfromxlogsimportget_loggerif__name__=='__main__':logger=get_logger(debug=True,logfile='/message.log')logger.info(\"info oooooo\")logger.debug(\"debug ggggg\")logger.error(\"err rrrr\")"} +{"package": "xlOil", "pacakge-description": "xlOilxlOil provides framework for interacting with Excel in different programming\nlanguages. It gives a way to write functions in a language and have them\nappear in Excel as worksheet functions or macros or have them control GUI elements.\nFor example, the Python bindings can replace VBA in almost all use cases\nand even provide functionality not available from VBA.xlOil is designed to have very low overheads when calling your worksheet\nfunctions.xlOil supports different languages via plugins. The languages currently\nsupported are:C++PythonSQLIn addition there isxlOil_Utilswhich contains some handy tools which Microsoft\nnever quite got around to adding.The latest stable documentation is here:https://xloil.readthedocs.io/en/stable.xlOil featuresPythonConcise syntax to declare an Excel functionOptional type checking of function parametersSupports keyword argumentsChoice of globally declared functions or code modules limited to a single workbook\nlike VBA workbook-level functionsTight integration withnumpy- very low overheads for array functionsUnderstands python tuples, lists, dictionarys andpandasdataframesAsync functionsRTD functions and on-the-fly RTD server creationMacro type functions which write to ranges on the sheetAccess to the Excel Application object and the full Excel object modelDrive Excel through COM automationHook Excel eventsPass any python object back to Excel and back into another functionSimple add-in deploymentTwo-way connection toJupyternotebooks: run worksheet functions inJupyterand query variables\nin thejupyterkernelCreate Ribbon toolbars and Custom Task PanesReturnmatplotlibplots and images from worksheet functionsC++Safe and convenient wrappers around most things in the C-APIConcise syntax to declare Excel functions: registration is automaticDeal with Excel variants, Ranges, Arrays and strings in a natural C++ fashionObject cache allows returning opaque objects to Excel and passing them back to other functionsSimplified RTD server creationRTD-based background calculationCreate Ribbon toolbars and Custom Task PanesSQLCreate tables from Excel ranges and arraysQuery and join them with the full sqlite3 SQL syntaxUtils: very fast functions to:Sort on multiple columnsSplit and join stringsMake arrays from blocksSupporting other languagesYou can use xlOil as an end-user of these plugins or you can use it to write\nyou own language bindings (and ideally add them to the repo)."} +{"package": "xloop", "pacakge-description": "IntroductionDocumentationInstallQuick StartLicensingIntroductionThis library is intended to house general for/iterator looping generators/utilities.Only one so far isxloop, seexloop docs.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiInstall# via pippipinstallxloop# via poetrypoetryaddxloopQuick Startfromxloopimportxloopargs=[None,\"hello\",2,[3,4],['A',[\"inner\",\"list\"]]]output=list(xloop(*args))assertoutput==[\"hello\",2,3,4,'A',[\"inner\",\"list\"]]LicensingThis library is licensed under the MIT-0 License. See the LICENSE file."} +{"package": "xlpandas", "pacakge-description": "xlPandasRead and write Excel xlsx using pandas/openpyxl without destroying formatting.Sometimes you have a nicely formatted worksheet, but you'd like to work with it\nusingpandas, or perhaps you want to write\ndata to an Excel template.Pandas can read and write Excel files usingxlrd, but treats them like csvs.\nxlPandas usesopenpyxlto access data\nwhile preserving template formatting, macros, and other worksheet attributes.Installpip install xlpandasExampleimportxlpandasasxpd# Read excel filedf=xpd.read_file('template.xlsx',skiprows=2)print(df.columns)# Modify dataframedf['new_column']=True# Access openpyxl worksheetsheet=df.to_sheet()sheet.cell(1,1).value='title'# From openpyxl worksheetdf=xpd.xlDataFrame(sheet)# Write filedf.to_file('out.xlsx')"} +{"package": "xlparser", "pacakge-description": "xlparser\u5b89\u88c5\u4f7f\u7528\u547d\u4ee4\u884c\u793a\u4f8bpython \u8c03\u7528\u793a\u4f8b\u8f6c\u4efb\u4f55\u7c7b\u578b\u7684\u6587\u4ef6\u4fdd\u5b58\u4efb\u4f55\u7c7b\u578b\u7684\u6587\u4ef6Csv \u6587\u4ef6\u5904\u7406Zip \u6587\u4ef6\u5904\u7406RequiredEnglishxlparser\u5c06 excel(xlsx/xls/csv) \u8f6c\u5230\u5176\u4ed6\u7684\u683c\u5f0f(csv, xlsx, json).Warning: \u5982\u679c\u4f60\u9047\u5230\u95ee\u9898\uff0c\u6700\u597d\u5728issue \u63d0\u4ea4\u660e\u786e\u7684\u62a5\u9519\u4fe1\u606f\u3002\u5b89\u88c5pip install xlparser\u5982\u679c\u60f3\u8fc7\u6ee4\u5b57\u6bb5\uff0c\u7ed3\u5408xcut\u4f7f\u7528\u66f4\u65b9\u4fbfpip install xcut\u4f7f\u7528$ xlparser -h\nxlparser [options] INFILE [OUTFILE]\\n\n options:\\n\n -h For help.\\n\u547d\u4ee4\u884c\u793a\u4f8b\u5c06 xlsx \u8f6c\u6210 csv$ xlparser source.xlsx new.csv\u5c06 csv \u8f6c\u6210 xlsx$ xlparser source.csv new.xlsx\u5c06 csv \u8f6c\u6210 json$ xlparser source.csv new.json\u5c06 xlsx \u8f6c\u6210 csv(\u6807\u51c6\u8f93\u51fa)$ xlparser source.xlsx | head \n\n$ xlparser src.xlsx | tee test.csv\nname, score\n\"\u674e\u96f7,\u97e9\u6885\",15\n\u5c0f\u82b1,16xcut \u547d\u4ee4\u7ed3\u5408$ xlparser src.xlsx | xcut --from-csv -f name \nname\n\"\u674e\u96f7,\u97e9\u6885\"\n\u5c0f\u82b1\n\n$ xlparser src.xlsx | xcut --from-csv -f score,name\nscore,name\n15,\"\u674e\u96f7,\u97e9\u6885\"\n16,\u5c0f\u82b1python \u8c03\u7528\u793a\u4f8b\u8f6c\u4efb\u4f55\u7c7b\u578b\u7684\u6587\u4ef6parseany type of file to rows:>>> from xlparser import parse, saveCsv\n>>> rows = parse('some.xlsx')\n>>> list(rows)\n[['foo', 'bar'], ['\u770b', '\u6211', '\u53d8']]Theparsefunction supports the following file formats: .csv, .xls, .xlsx .\u4fdd\u5b58\u4efb\u4f55\u7c7b\u578b\u7684\u6587\u4ef6Save rows to csv>>> from xlparser import parse, saveCsv\n>>> rows = [['foo', 'bar'], ['\u770b', '\u6211', '\u53d8']]\n>>> saveCsv(rows, 'test.csv')Save rows to xlsx>>> saveXlsx(rows, 'test.xlsx')Csv \u6587\u4ef6\u5904\u7406>>> from xlparser import *\n\n>>> rows = [('foo','bar'), ('\u770b','\u6211','\u53d8')]\n>>> saveCsv(rows, 'test.csv')\n\n>>> list(parseCsv('test.csv'))\n[['foo', 'bar'], ['\u770b', '\u6211', '\u53d8']]Zip \u6587\u4ef6\u5904\u7406>>> from xlparser import loadZip\n>>> zf = loadZip('test.xlsx')\n>>> print(zf.filelist)\n......\n>>> zf.extract('xl/media/image1.png', '/tmp')\n>>> os.rename('/tmp/'+'xl/media/image1.png', './image1.png')Requiredpython>=3.5xlrd: required by xlsopenpyxl>=2.5.4: required by xlsx"} +{"package": "xlpie", "pacakge-description": "xlpie"} +{"package": "xlpkg", "pacakge-description": "No description available on PyPI."} +{"package": "xlpo", "pacakge-description": "** WARNING: project under active development, do not use in production **DescriptionSimple command line utilities to convert xls/xlsx files to gettext PO files and back.FeaturesTODOHistoryDevelopment versionTODO"} +{"package": "xlprocess", "pacakge-description": "No description available on PyPI."} +{"package": "xlpus", "pacakge-description": "No description available on PyPI."} +{"package": "xlpython", "pacakge-description": "UNKNOWN"} +{"package": "xlr8", "pacakge-description": "XLR8 BOMBER 3.0\ud83d\udca3 \ud83d\udcf1 \ud83d\udc80A Superfast SMS & Call bomber for Linux And Termux !DisclaimerThis tool is for educational purposes only !Don't use this to take revengeI will not be responsible for any misuseAboutUnlimited Usage !Cross PlatformSupports newest Android alsoNo balance will be deducted to send SMS/callsWorking ApisNo missing SMS issues, all messages will be sent.Working with all Operators/CarriersTested On :Kali LinuxTermuxUbuntuParrot Sec OSKali nethunterAlpine linuxTermux Issue:Termux App is no longer recieving updates on playstoredue to recently introduced Google Play policyDON'T WORRYWe have a solution for that !You can download the latest termux app and install itFrom hereLinkUsageUpdate the packagesTermuxpkgup-yKali Linux/Parrot OSaptupdate-y&&aptupgrade-yInstall some dependenciesapt-getinstallgitwgetpython3-yClone the repositorygitclonehttps://github.com/anubhavanonymous/XLR8_BOMBERGo to the Xlr8 directorycdXLR8_BOMBERRun the scriptpython3xlr8.pyVersion3.0 CI aplhaFeaturesSms,Call & Whatsapp BombingSend anonymous msgNoteThis bomber only works in India !!LicenceApache 2.0 \u00a9 Anubhav KashyapScreenshots (Termux)Contact UsIf you have any feedback or queriesmail us at: anubhavkashyap@pm.meTelegram ChannelJoin the Official Telegram channel of XLR8All updates of Xlr8 will be posted here !Change Log0.0.1 (19/04/2020)First Release"} +{"package": "xlrd", "pacakge-description": "xlrd is a library for reading data and formatting information from Excel\nfiles in the historical.xlsformat.WarningThis library will no longer read anything other than.xlsfiles. For\nalternatives that read newer file formats, please seehttp://www.python-excel.org/.The following are also not supported but will safely and reliably be ignored:Charts, Macros, Pictures, any other embedded object,includingembedded worksheets.VBA modulesFormulas, but results of formula calculations are extracted.CommentsHyperlinksAutofilters, advanced filters, pivot tables, conditional formatting, data validationPassword-protected files are not supported and cannot be read by this library.Quick start:importxlrdbook=xlrd.open_workbook(\"myfile.xls\")print(\"The number of worksheets is{0}\".format(book.nsheets))print(\"Worksheet name(s):{0}\".format(book.sheet_names()))sh=book.sheet_by_index(0)print(\"{0}{1}{2}\".format(sh.name,sh.nrows,sh.ncols))print(\"Cell D30 is{0}\".format(sh.cell_value(rowx=29,colx=3)))forrxinrange(sh.nrows):print(sh.row(rx))From the command line, this will show the first, second and last rows of each sheet in each file:pythonPYDIR/scripts/runxlrd.py3rows*blah*.xls"} +{"package": "xlrd2", "pacakge-description": "xlrd2xlrd2 is an effort to extendxlrd project, which is no longer mintained by its developers.\nThe main goal is to make it suitable for extracting necessary information from malicious xls documents.Xlrd Purpose: Provide a library for developers to use to extract data from Microsoft Excel (tm) spreadsheet files. It is not an end-user tool.Versions of Python supported: 2.7, 3.4+.Installation:Installing using pippip install xlrd2Installing the latest developmentUsing pippip install -U https://github.com/DissectMalware/xlrd2/archive/master.zipOr download the latest versionwget https://github.com/DissectMalware/xlrd2/archive/master.zipExtract the zip file and go to the extracted directorypython setup.py install --userQuick start:importxlrd2book=xlrd2.open_workbook(\"myfile.xls\")print(\"The number of worksheets is{0}\".format(book.nsheets))print(\"Worksheet name(s):{0}\".format(book.sheet_names()))sh=book.sheet_by_index(0)print(\"{0}{1}{2}\".format(sh.name,sh.nrows,sh.ncols))print(\"Cell D30 is{0}\".format(sh.cell_value(rowx=29,colx=3)))forrxinrange(sh.nrows):print(sh.row(rx))Another quick start: This will show the first, second and last rows of each sheet in each file:python PYDIR/scripts/runxlrd2.py 3rows *blah*.xlsXlrd Acknowledgements:This package started life as a translation from C into Python of parts of a utility called \"xlreader\" developed by David Giffin. \"This product includes software developed by David Giffindavid@giffin.org.\"OpenOffice.org has truly excellent documentation of the Microsoft Excel file formats and Compound Document file format, authored by Daniel Rentz. Seehttp://sc.openoffice.orgU+5F20 U+654F: over a decade of inspiration, support, and interesting decoding opportunities.Ksenia Marasanova: sample Macintosh and non-Latin1 files, alpha testingBackporting to Python 2.1 was partially funded by Journyx - provider of timesheet and project accounting solutions (http://journyx.com/).Provision of formatting information in version 0.6.1 was funded by Simplistix Ltd (http://www.simplistix.co.uk/)"} +{"package": "xlrd3", "pacakge-description": "xlrd3A fork of original archivedxlrdproject.\nThis fork aims to fix bugs that existing inxlrdand improve it features.\nAs the name of this fork implies, python2 support is dropped.At version 1.0.0, xlrd3 on pair with xlrd version 1.2.0 with following bugs fixed:MemoryError:on_demandwithmmapstill causes somexlsto be read the whole file into memory.on_demandnot supported forxlsxParsing comments failed forxlsxon Windows platform.When to use xlrd3If you just need toreadand deal with bothxlsxandxls, usexlrd3.\nThen if you want to export your data to other excel files, useOpenPyXLorxlsxWriter.\nIf you need toeditxlsx(read and write) and are sure thatxlsnever appear in your workflow, you are advised to useOpenPyXLinstead.Purpose: Provide a library for developers to use to extract data from Microsoft Excel (tm) spreadsheet files. It is not an end-user tool.Original Author: John MachinLicence: BSD-style (see licences.py)Versions of Python supported: 3.6+.Outside scope: xlrd3 will safely and reliably ignore any of these if present in the file:Charts, Macros, Pictures, any other embedded object. WARNING: currently this includes embedded worksheets.VBA modulesFormulas (results of formula calculations are extracted, of course).CommentsHyperlinksAutofilters, advanced filters, pivot tables, conditional formatting, data validationHandling password-protected (encrypted) files.Installation:$pip install xlrd3Quick start:importxlrd3asxlrdbook=xlrd.open_workbook(\"myfile.xls\")print(\"The number of worksheets is{0}\".format(book.nsheets))print(\"Worksheet name(s):{0}\".format(book.sheet_names()))sh=book.sheet_by_index(0)print(\"{0}{1}{2}\".format(sh.name,sh.nrows,sh.ncols))print(\"Cell D30 is{0}\".format(sh.cell_value(rowx=29,colx=3)))forrxinrange(sh.nrows):print(sh.row(rx))Another quick start: This will show the first, second and last rows of each sheet in each file:python PYDIR/scripts/runxlrd.py 3rows *blah*.xlsAcknowledgements:This package started life as a translation from C into Python of parts of a utility called \"xlreader\" developed by David Giffin. \"This product includes software developed by David Giffindavid@giffin.org.\"OpenOffice.org has truly excellent documentation of the Microsoft Excel file formats and Compound Document file format, authored by Daniel Rentz. Seehttp://sc.openoffice.orgU+5F20 U+654F: over a decade of inspiration, support, and interesting decoding opportunities.Ksenia Marasanova: sample Macintosh and non-Latin1 files, alpha testingBackporting to Python 2.1 was partially funded by Journyx - provider of timesheet and project accounting solutions (http://journyx.com/).Provision of formatting information in version 0.6.1 was funded by Simplistix Ltd (http://www.simplistix.co.uk/)"} +{"package": "xlrd3k", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlrd-compdoc-commented", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.7, 3.4+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlrd-demo", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.7, 3.4+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlrdformulas", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlrd-ignore-writeaccess-corruption", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.7, 3.4+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlrdinc", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.7, 3.4+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlrd-no-sector-corruption-check", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.7, 3.4+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlrd-with-formulas", "pacakge-description": "Extract data from Excel spreadsheets (.xls and .xlsx, versions 2.0 onwards) on any platform. Pure Python (2.6, 2.7, 3.3+). Strong support for Excel dates. Unicode-aware."} +{"package": "xlref", "pacakge-description": "About xlrefxlrefis an useful library to capture by a simple reference (e.g.,A1(RD):..:RD) a table with non-empty cells from Excel-sheets when\nits exact position is not known beforehand.This code was inspired by thexleashmodule of thepandalonelibrary. The reason of\ndeveloping a similar tool was to have a smaller library to install and\nimprove the performances of reading.xlsxfiles.InstallationTo install it use (with root privileges):$pipinstallxlrefOr download the last git version and use (with root privileges):$pythonsetup.pyinstallTutorialA typical example iscapturinga table with a \u201cheader\u201d row and\nconvert into a dictionary. The code below shows how to do it:>>> import xlref as xl\n>>> _ref = 'excel.xlsx#ref!A1(RD):RD[%s]'\n>>> ref = xl.Ref(_ref % '\"dict\"')\n>>> ref.range # Captured range.\nB2:C28\n>>> values = ref.values; values # Captured values.\n{...}\n>>> values['st-cell-move']\n'#D5(RU):H1(DL)'You can notice from the code above that all the values of the\ndictionary are references. To parse it recursively, there are two\noptions:add the \u201crecursive\u201d filter before the \u201cdict\u201d:>>> values = xl.Ref(_ref % '\"recursive\", \"dict\"').values\n>>> values['st-cell-move'].tolist()\n[[1.0, 2.0, 3.0],\n [4.0, 5.0, 6.0],\n [7.0, 8.0, 9.0]]apply a filter onto dictionary\u2019 values using the extra\nfunctionality of the \u201cdict\u201d filter:>>> values = xl.Ref(_ref % '{\"fun\": \"dict\", \"value\":\"ref\"}').values\n>>> values['st-cell-move'].tolist()\n[[1.0, 2.0, 3.0],\n [4.0, 5.0, 6.0],\n [7.0, 8.0, 9.0]]You have also the possibility to define and use your custom filters as\nfollows:>>> import numpy as np\n>>> xl.FILTERS['my-filter'] = lambda parent, x: np.sum(x)\n>>> xl.Ref('#D5(RU):H1(DL)[\"my-filter\"]', ref).values\n45.0An alternative way is to use directly the methods of the filtered\nresults as follows:>>> xl.Ref('#D5(RU):H1(DL)[\"sum\"]', ref).values\n45.0"} +{"package": "xl-reports", "pacakge-description": "XL ReportsGenerate Excel reports!Create an Excel template fileDefine a report configurationFetch your dataGenerate reportReport Configuration SchemaReport configuration is defined as array/list of objects/dicts.\"cell\": Worksheet cell coordinates to insert data, example:\"B2\"\"range\": Worksheet coordinate range to insert data. Range start coordinate is required and end coordinate is optional. examples:\"B2:\"or\"B2:C5\"\"data_key\": Key to use when fetching values from the data dictionary to insert into the worksheet. example:data[\"report_date\"]\"sheet\": Worksheet name.Example configuration[\n {\n \"cell\": \"B2\",\n \"data_key\": \"account\",\n \"sheet\": \"my_sheet\"\n },\n {\n \"cell\": \"B4\",\n \"data_key\": \"report_date\",\n \"sheet\": \"my_sheet\"\n },\n {\n \"range\": \"A8\",\n \"data_key\": \"report_data\",\n \"sheet\": \"my_sheet\"\n }\n]Example data[{\n \"account\": \"Engineering\",\n \"report_date\": str(date.today()),\n \"report_data\": [\n [23.43, 11.96, 9.66],\n [6.99, 65.87, 45.33],\n ]\n}]"} +{"package": "xlrp", "pacakge-description": "XLRP\u4f7f\u7528\u624b\u518cxlrp\u662f\u7528\u4e8e\u751f\u6210excel\u62a5\u544a\u7684python\u5e93\uff0c\u53ef\u4ee5\u5728\u4e0d\u7834\u574f\u5f53\u524d\u4ee3\u7801\u7ed3\u6784\u7684\u57fa\u7840\u4e0a\uff0c\u6dfb\u52a0\u6d4b\u8bd5\u7528\u4f8b\u5206\u7c7b\uff0c\u751f\u6210\u62a5\u544a\uff0c\u53ef\u5e94\u7528\u5927\u90e8\u5206\u6570\u636e\u9a71\u52a8\u573a\u666f\u5b89\u88c5\u548c\u5bfc\u5165pip install xlrp # \u5b89\u88c5\n\nfrom XLRP import xlrp\u7528\u4f8b\u5206\u7c7b\u5bf9\u4e8e\u7c7b\u3001\u65b9\u6cd5\u7684\u5f62\u5f0f\uff0c\u901a\u5e38\u4e00\u4e2a\u65b9\u6cd5\u4ee3\u8868\u4e00\u4e2a\u7528\u4f8b\uff0c\u6240\u4ee5\uff0c\u5728\u65b9\u6cd5\u4e0a\u53ef\u4ee5\u4f7f\u7528\u88c5\u9970\u5668\u7684\u5f62\u5f0f\uff0c\u5bf9\u4e8e\u5e38\u89c1excel\u9a71\u52a8\uff0c\u5355\u51fd\u6570\u7684\u5f62\u5f0f\uff0c\u53ef\u4ee5\u4f7f\u7528with\u7684\u5f62\u5f0f\u8fdb\u884c\u5206\u7c7b# \u88c5\u9970\u5668\u5f62\u5f0f\n\n@xlrp.SysName(\"\u6d4b\u8bd5\u6a21\u5757\")\nclass ExcelTest:\n @xlrp.ModelName('\u6a21\u57571')\n @xlrp.StepName(\"\u6b65\u9aa41\")\n def xl_pr(self, a, b):\n print(a, b)\n\n# with\u5f62\u5f0f\n@xlrp.SysName(\"\u7cfb\u7edf\u540d\u79f0\")\ndef excel_data():\n with xlrp.ModelName(\"\u6a21\u57571\"):\n with xlrp.StepName(\"\u7528\u4f8b1):\n print(123)\u5355\u51fd\u6570\u7528\u4f8b\u8fd0\u884c\u5bf9\u4e8e\u5355\u4e2a\u7528\u4f8b\u7684\u5f62\u5f0f\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528run\u65b9\u6cd5\u8fdb\u884c\u8fd0\u884c\uff0c\u5e76\u53ef\u4ee5\u5411\u5176\u4e2d\u4f20\u5165\u4e00\u4e2a\u5217\u8868\u4f5c\u4e3a\u53c2\u6570\uff0c\u5217\u8868\u4e2d\u4e00\u4e2a\u5143\u7d20\u4ee3\u8868\u4e00\u4e2a\u7528\u4f8bdef pr(a, b):\n print(a + b)\n\n# Runner\u53ef\u4ee5\u63a5\u53d7\u4e00\u4e2a\u5e03\u5c14\u503c\u53c2\u6570\uff0c\u7528\u6765\u786e\u5b9a\u662f\u5426\u7acb\u5373\u663e\u793a\u521b\u5efa\u7684\u56fe\u50cf\nrunner = Runner()\nrunner.run(excel_data, [(1, 3), (4, 5), (6, 7)])\u8fd0\u884c\u7c7b\u5bf9\u4e8e\u7c7b\u7684\u5f62\u5f0f\uff0c\u5bf9\u65b9\u6cd5\u7684\u547d\u540d\u505a\u4e86\u4e00\u5b9a\u7684\u89c4\u5b9a\uff0c\u7c7b\u4e2d\u7684\u65b9\u6cd5\uff0c\u5fc5\u987b\u662f\u4ee5\"xl\"\u5f00\u5934\u7684\uff0c\u624d\u4f1a\u4f5c\u4e3axlrp\u7684\u7528\u4f8b\u8fd0\u884c@xlrp.SysName(\"\u6d4b\u8bd5\")\nClass ExcelData:\n @xlrp.ModelName(\"\u6a21\u57571\")\n @xlrp.StepName(\"\u7528\u4f8b1\")\n def xl_pr():\n print(123)\n \n @xlrp.ModelName(\"\u6a21\u57572\")\n @xlrp.StepName(\"\u7528\u4f8b2\")\n def xl_pr2():\n print(456)\n\n# \u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u8fd9\u91cc\u4f20\u5165\u7684\u662f\u7c7b\u7684\u5b9e\u4f8b\u5bf9\u8c61\nrunner = Runner().run_class(ExcelData())\u6587\u4ef6\u5939\u7528\u4f8b\u6536\u96c6\u5728\u9700\u8981\u8fd0\u884c\u6574\u4e2a\u6587\u4ef6\u5939\u4e2d\u7684\u7528\u4f8b\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528run_discover\u7684\u65b9\u5f0f\uff0crun_class\u6709\u4e24\u4e2a\u5fc5\u586b\u53c2\u6570\u662f\u7b2c\u4e00\u4e2astart_dir\uff0c\u4e3a\u7528\u4f8b\u5b58\u653e\u7684\u6587\u4ef6\u5939\uff1b\u7b2c\u4e8c\u662fsys_name\uff0c\u6211\u4eec\u4f7f\u7528run_discover\u7701\u7565@SysName\u88c5\u9970\u5668\u3002\u4e24\u4e2a\u53ef\u9009\u53c2\u6570\uff0c\u7b2c\u4e00\u4e2apatten\uff0c\u6587\u4ef6\u5f62\u5f0f\uff0c\u9ed8\u8ba4'xl*.py'\uff0c\u5373xl\u5f00\u5934\u7684py\u6587\u4ef6\uff1b\u7b2c\u4e8c\u4e2a\u4e3acls_start_mark\uff0c\u53ef\u4ee5\u6807\u8bb0\u7c7b\u540d\u662f\u4ee5\u4ec0\u4e48\u5f00\u5934\uff0c\u9ed8\u8ba4'Xl'\u7528\u4f8b\u5728\u6536\u96c6\u7684\u65f6\u5019\uff0c\u9996\u5148\u662f\u6839\u636e\u6587\u4ef6\u540d\u8fdb\u884c\u6392\u5e8f\uff0c\u5b58\u653e\u5728\u5f85\u8fd0\u884c\u5217\u8868\u4e2d\u4f9d\u6b21\u8fd0\u884c\uff0crun_discover\u53ea\u80fd\u6536\u96c6class\u7c7b\uff0c\u6240\u4ee5\u8bf7\u5c3d\u91cf\u5728\u6587\u4ef6\u4e2d\u4f7f\u7528class\u5305\u88f9\u7528\u4f8b# xl_test.py\n\nfrom XLRP.xlrp import *\n\n\n@xl_ddt\nclass XlTest:\n @ModelName(\"\u767b\u5f55\u6a21\u5757\")\n def xl_01_login(self):\n with StepName(\"\u767b\u5f55\"):\n print('\u9a6c\u5e08\u5085\u6210\u529f\u767b\u5f55\u4e86\uff01\uff01\uff01')\n with StepName(\"\u767b\u51fa\"):\n print('\u9a6c\u5e08\u5085\u5012\u4e0b\u4e86\uff01\uff01\uff01')\n\n @xl_data([('\u5546\u54c1\u7ec4\u54081', '\u5546\u54c11', '\u5546\u54c12'), ('\u5546\u54c1\u7ec4\u54082', '\u5546\u54c13',), ('\u5546\u54c1\u7ec4\u54083', '\u5546\u54c16',)])\n @ModelName(\"\u8d2d\u4e70\u6a21\u5757\")\n def xl_02_buysomething(self, step, *args):\n with StepName(step):\n print('\u9009\u62e9\u5546\u54c1<\u677e\u679c\u5f39\u6296\u95ea\u7535\u97ad>', args)\n # with StepName(step):\n # print('\u9a6c\u5e08\u5085\u9009\u62e9\u4e86\u4ed8\u6b3e')\n\n @xl_data([('\u6570\u5b661', 1, 2), ('\u6570\u5b662', 3, 5), ('\u6570\u5b663', 4, 0)])\n @ModelName(\"\u6570\u5b66\u9898\")\n def xl_03_compute(self, step, a, b):\n with StepName(step):\n print(\"\u9a6c\u5e08\u5085\u5f00\u59cb\u505a\u6570\u5b66\u9898\")\n print(a / b)\n\n @ModelName(\"\u7edf\u8ba1\u6a21\u5757\")\n def xl_04_count(self):\n with StepName('\u4e0d\u8bb2\u6b66\u5fb7'):\n print(\"\u6211\u4ed8\u94b1\u4e86\uff0c\u5e74\u8f7b\u4eba\u4e0d\u8bb2\u6b66\u5fb7\uff01\uff01\uff01\")\n\n def xl_05_age(self):\n with ModelName('\u8ba1\u7b97\u9a6c\u5e08\u5085\u5e74\u9f84'):\n with StepName(\"\u5148\u6253\u5012\u9a6c\u5e08\u5085\"):\n print('\u6765\u9a97\u3001\u6765\u2026\u2026\u5077\u88ad')\n with StepName(\"\u9a6c\u5e08\u5085\u81ea\u66dd\u5e74\u9f84\"):\n print('\u5077\u88ad\u6211\u8fd920\u591a\u5c81\u7684\u7a0b\u5e8f\u5458')\n\n @ModelName(\"\u677e\u679c\u5f39\u6296\u95ea\u7535\u97ad\")\n def xl_06_flash(self):\n @StepName(\"\u4e00\u97ad\")\n def xl_one():\n print(\"\u677e\u679c\")\n xl_one()\n\n @StepName(\"\u4e24\u97ad\")\n def xl_two():\n print('\u5f39~')\n return False\n xl_two()\n\n@ModelName(\"\u9a6c\u5e08\u5085\u6253\u4e0d\u8fc7\")\n@StepName(\"\u6253\u4e0d\u8fc7\u4e5f\u8981\u6253\")\ndef ma_sifu(a, b):\n print(f'\u9a6c\u5e08\u5085\u6253\u4e86{a}\u548c{b}')# run.py\n\nfrom XLRP.xlrp import *\n\n\nif __name__ == '__main__':\n runner = Runner()\n runner.run_discover('./', '\u6d4b\u8bd5\u7cfb\u7edf', 'xl_test.py').save_default()\u7c7b\u65b9\u6cd5\u53c2\u6570\u5316\u6211\u4eec\u5df2\u7ecf\u77e5\u9053\u5728run\u7684\u65b9\u6cd5\u4e2d\uff0c\u662f\u53ef\u4ee5\u4f20\u5165\u51fd\u6570\u540d\u548c\u53c2\u6570\u6765\u8fdb\u884c\u53c2\u6570\u5316\u8bbe\u7f6e\u7684\uff0c\u4f46\u662f\u5bf9\u4e8e\u7c7b\u6765\u8bf4\uff0c\u5219\u4e0d\u80fd\u8fd9\u4e48\u8fdb\u884c\u5904\u7406\uff0c\u6240\u4ee5\uff0cxlrp\u81ea\u5e26\u4e86\u53c2\u6570\u5316\u7684\u88c5\u9970\u5668\uff0c\u4e3a\u4e86\u65b9\u4fbf\u8bb0\u5fc6\uff0c\u5219\u5ef6\u7528\u5927\u5bb6\u719f\u6089\u7684ddt\uff0c\u4f46\u4e3a\u4e86\u533a\u5206\uff0c\u8fd9\u91cc\u4e3axl_ddt\uff0c\u867d\u7136\u540d\u5b57\u76f8\u540c\uff0c\u4f46\u662f\u4ed6\u4eec\u7684\u5185\u90e8\u903b\u8f91\u662f\u6709\u533a\u522b\u7684@SysName(\"\u6d4b\u8bd5\u6a21\u5757\")\n@xl_ddt\nclass ExcelTest:\n @ModelName('\u6a21\u57571')\n @xl_data([(1, 2, '\u6b65\u9aa41'), (2, 3, '\u6b65\u9aa42'), (5, 5, '\u6b65\u9aa43')])\n def xl_pr(self, a, b, step):\n with StepName(step):\n assert a == b\n\n @xl_data([(1, 2, '\u6b65\u9aa41'), (2, 3, '\u6b65\u9aa42'), (5, 5, '\u6b65\u9aa43')])\n @ModelName('\u6a21\u57572')\n def xl_pr2(self, a, b, step):\n with StepName(step):\n assert a > b/a\n\n @ModelName(\"\u6a21\u57573\")\n @StepName(\"\u6b65\u9aa4\")\n def xl_pr3(self):\n print(123)\n\n @ModelName(\"\u6a21\u57574\")\n @StepName(\"\u6b65\u9aa4\")\n def xl_pr4(self):\n print(666)\u901a\u8fc7\u4e0a\u8ff0\u7684\u4f8b\u5b50\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4ed6\u7684\u4f7f\u7528\u65b9\u6cd5\uff0c\u548c\u5e38\u7528\u7684ddt\u533a\u522b\u5e76\u4e0d\u662f\u5f88\u5927\uff0c\u800c\u6211\u4eec\u4f5c\u4e3a\u7c7b\u65b9\u5f0f\u8fd0\u884c\uff0c\u5176\u5b9exl_ddt\u7684\u610f\u4e49\u5e76\u4e0d\u5927\uff0c\u4f46\u662f\u4e3a\u4e86\u8ba9run_class\u7684\u65b9\u6cd5\u66f4\u5c0f\u66f4\u6613\u7ef4\u62a4\uff0c\u8fd8\u662f\u9009\u62e9\u91cd\u65b0\u8bbe\u7f6e\u4e00\u4e2axl_ddt\u6765\u6355\u83b7\u5f53\u524d\u7c7bxl_data\u548crun\u7684\u53c2\u6570\u5316\u76f8\u4f3c\uff0c\u4e5f\u662f\u4f20\u5165\u4e00\u4e2a\u5217\u8868\uff0c\u5217\u8868\u4e2d\u6bcf\u4e2a\u5143\u7d20\u4ee3\u8868\u4e00\u4e2a\u7528\u4f8b\u7684\u53c2\u6570\uff0c\u4e09\u4e2a\u53c2\u6570\u4f1a\u751f\u6210\u4e09\u4e2a\u7528\u4f8b\uff0c\u6ce8\u610f\u4e8b\u9879xlrp\u5728\u6536\u96c6\u53c2\u6570\u6784\u9020\u7528\u4f8b\u7684\u65f6\u5019\uff0c\u662f\u5728\u539f\u6709\u7684\u65b9\u6cd5\u4e0a\uff0c\u5c3e\u90e8\u52a0\u4e0a\u4e86\"_\u6570\u5b57\"\u7684\u5f62\u5f0f\uff0c\u7c7b\u4e2d\u7528\u4f8b\u7684\u8fd0\u884c\u987a\u5e8f\uff0c\u4e5f\u662f\u4f9d\u636e\u7528\u4f8b\u540d\u79f0\u6765\u8fdb\u884c\u7684\u4fdd\u5b58\u56fe\u50cf\u5728\u6211\u4eec\u8fd0\u884c\u7528\u4f8b\u4e4b\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u9009\u62e9\u5c06\u56fe\u7247\u5b58\u5728excel\u4e2d@xlrp.SysName(\"\u7cfb\u7edf1\")\ndef single(a, b):\n with xlrp.ModelName(\"\u6a21\u5757\")\uff1a\n with xlrp.StepName(\"\u7528\u4f8b\"):\n print(a, b)\n\n@xlrp.SysName(\"\u6d4b\u8bd5\")\nClass ExcelData:\n @xlrp.ModelName(\"\u6a21\u57571\")\n @xlrp.StepName(\"\u7528\u4f8b1\")\n def xl_pr():\n print(123)\n \n @xlrp.ModelName(\"\u6a21\u57572\")\n @xlrp.StepName(\"\u7528\u4f8b2\")\n def xl_pr2():\n print(456)\n\n# plot_save_excel\u6709\u4e24\u4e2a\u53c2\u6570\uff1a\n# file_path: \u9700\u8981\u4fdd\u5b58\u8fdb\u5165\u7684excel\u6587\u4ef6\n# width_list: \u56fe\u7247\u7684\u5927\u5c0f\uff0c\u9ed8\u8ba4\u662f(700, 700, 700)\n# width_list \u7684\u56fe\u50cf\u5927\u5c0f\uff0c\u9ed8\u8ba4\u7b2c\u4e09\u4e2a\u53c2\u6570\uff0c\u4f1a\u5728\u539f\u57fa\u7840\u4e0aX2\uff0c\u4e3a\u4fdd\u8bc1\u56fe\u50cf\u7f8e\u89c2\uff0c\u8bf7\u4fdd\u6301\u4e09\u4e2a\u6570\u5b57\u4e00\u81f4\nrunner = Runner()\nrunner.run(single).plot_save_excel('./test.xlsx')\nrunner.run_class(ExcelData()).plot_save_excel('./test.xlsx')\u9ed8\u8ba4\u4fdd\u5b58(\u751f\u6210\u62a5\u544a)\u9ed8\u8ba4\u751f\u6210\uff0c\u4f1a\u751f\u6210\u4e00\u4e2a.xlrp_cache\u6587\u4ef6\u5939\u4ee5\u53calog\u3001plot\u3001report\u4e09\u4e2a\u5b50\u6587\u4ef6\u5939\uff0c\u5b58\u653e\u5728\u5f53\u524d\u8c03\u7528\u6587\u4ef6\u540c\u7ea7\u76ee\u5f55\u4e0b\uff0cexcel\u6587\u4ef6\u5305\u542b\u4e24\u4e2asheet\u9875\u9762\uff0c\u4e00\u4e2a\u662f\u4f7f\u7528xlrp\u8fd0\u884c\u7684\u6240\u6709\u7528\u4f8b\u4ee5\u53ca\u4ed6\u4eec\u7684\u8fd0\u884c\u7ed3\u679c\uff0c\u7b2c\u4e8c\u4e2asheet\u4e3a\u7edf\u8ba1\u56fe\u6807\uff0c\u4e00\u4e2a\u997c\u56fe\u3001\u4e00\u4e2a\u67f1\u72b6\u56fe\u3001\u4e00\u4e2a\u6298\u7ebf\u56fe\uff0c\u5206\u522b\u4ee3\u8868\uff0c\u7cfb\u7edf\u7528\u4f8b\u8fd0\u884c\u603b\u901a\u8fc7\u7387\u3001\u7cfb\u7edf\u6a21\u5757\u7528\u4f8b\u901a\u8fc7\u7387\u3001\u7cfb\u7edf\u6a21\u5757\u53ca\u6a21\u5757\u7528\u4f8b\u8fd0\u884c\u8017\u65f6runner = Runner()\nrunner.run(single).save_default()\nrunner.run_class(ExcelTest()).save_default()\u591a\u8fdb\u7a0b\u8fd0\u884c\u5728\u591a\u8fdb\u7a0b\u8fd0\u884c\u7684\u65f6\u5019\uff0c\u4e3a\u4e86\u4f7f\u6587\u4ef6\u80fd\u6b63\u5e38\u4fdd\u5b58\uff0c\u4e0d\u81f3\u4e8e\u8986\u76d6\uff0c\u5728Runner\u8fd0\u884c\u7c7b\u4e2d\uff0c\u589e\u52a0\u4e86file_mark\u53c2\u6570\uff0c\u6b64\u53c2\u6570\u4e3a\u8bbe\u7f6e\u6587\u4ef6\u7684\u547d\u540d\u89c4\u5219\uff0c\u81ea\u5b9a\u4e49\u7684\u65b9\u5f0f\u80fd\u8ba9\u81ea\u5df1\u66f4\u597d\u7406\u89e3\u6587\u4ef6\u7684\u4f4d\u7f6e\u7b49\u4fe1\u606f\uff0c\u76f8\u6bd4\u5176\u4ed6ID\u7c7b\u7684\u4e0d\u660e\u610f\u4e49\u7684\u6807\u8bc6\u66f4\u6709\u8fa8\u8bc6\u6027\u4f7f\u7528\u8fdb\u7a0b\u6c60\u7684\u65b9\u5f0f\u6dfb\u52a0\u591a\u4e2a\u8fdb\u7a0b\u8fd0\u884c\u7528\u4f8b\uff1afrom XLRP.xlrp import *\nfrom multiprocessing import Process, Pool\n\n\n@SysName(\"\u6d4b\u8bd5\u6a21\u5757\")\n@xl_ddt\nclass ExcelTest:\n @ModelName('\u6a21\u57571')\n @xl_data([(1, 2, '\u6b65\u9aa41'), (2, 3, '\u6b65\u9aa42'), (5, 5, '\u6b65\u9aa43')])\n def xl_pr(self, a, b, step):\n with StepName(step):\n assert a == b\n\n @xl_data([(1, 2, '\u6b65\u9aa41'), (2, 3, '\u6b65\u9aa42'), (5, 5, '\u6b65\u9aa43')])\n @ModelName('\u6a21\u57572')\n def xl_pr2(self, a, b, step):\n with StepName(step):\n assert a > b/a\n\n @ModelName(\"\u6a21\u57573\")\n @StepName(\"\u6b65\u9aa4\")\n def xl_pr3(self):\n print(1/ 0)\n\n @ModelName(\"\u6a21\u57574\")\n @StepName(\"\u6b65\u9aa4\")\n def xl_pr4(self):\n print(666)\n\n @ModelName(\"\u6a21\u57575\")\n @StepName(\"\u6b65\u9aa4\")\n def xl_pr5(self):\n return False\n\ndef run(mark):\n runner = Runner(file_mark=mark)\n runner.run_class(ExcelTest()).save_default()\n \n\nif __name__ == '__main__':\n file_names = ['\u6d4b\u8bd51', '\u6d4b\u8bd52', '\u6d4b\u8bd53', '\u6d4b\u8bd54']\n pool = Pool(4)\n for task in file_names:\n pool.apply_async(run, (task, ))\n pool.close()\n pool.join()\u4f7f\u7528\u4e8b\u9879\u4f7f\u7528xlrp\u9700\u8981\u7cfb\u7edf\u3001\u6a21\u5757\u3001\u6b65\u9aa4\u90fd\u5b58\u5728\uff0c\u7f3a\u5c11\u67d0\u4e00\u4e2a\u5219\u4e0d\u80fd\u5b8c\u6574\u6784\u6210\u6d4b\u8bd5\u7cfb\u7edf\u62a5\u544a\u3002\u4e00\u4e2a\u9875\u9762\u4e2d\uff0c\u5982\u679c\u4f7f\u7528\u591a\u4e2aSysName\u88c5\u9970\u5668\uff0c\u7cfb\u7edf\u751f\u6210\u7684\u62a5\u544a\u4f1a\u53d6\u7528\u6700\u540e\u4e00\u6b21\u8d4b\u503c\u7684\u7cfb\u7edf\u540d\u79f0\uff0c\u8fd9\u662f\u56e0\u4e3axlrp\u672a\u5efa\u8bbe\u6587\u4ef6\u7528\u4f8b\u6536\u96c6\u529f\u80fd\uff0c\u9ed8\u8ba4\u4ee5class\u4f5c\u4e3a\u5927\u8303\u7574\u3002\u6bcf\u4e2a\u6b65\u9aa4\u7684\u547d\u540d\u5e94\u8be5\u4e0d\u540c\uff0c\u5426\u5219\u53ef\u80fd\u4f1a\u8986\u76d6\u6570\u636e\uff0cxlrp\u7684step\u7528\u4f8b\u547d\u540d\u90fd\u638c\u63e1\u5728\u7528\u6237\u624b\u4e0a\uff0c\u7ed9\u4e88step\u4e0d\u540c\u540d\u5b57\uff0c\u5373\u89c6\u4e3a\u4e0d\u540c\u7528\u4f8b\uff0cxlrp\u4ee5\u7528\u6237\u547d\u540dstep\u7528\u4f8b\u4e3a\u51c6\uff0c\u800c\u4e0d\u4ee5\u53c2\u6570\u5316\u7684\u51fd\u6570\u6216\u8005\u8fd0\u884c\u6b21\u6570\u51b3\u5b9a\uff0c\u6240\u4ee5\u5728\u53c2\u6570\u5316\u7684\u65f6\u5019\uff0c\u4f20\u5165step\u540d\u79f0\u4e5f\u8bb8\u662f\u4e00\u4e2a\u597d\u4e3b\u610fxlrp\u53ef\u4ee5\u6dfb\u52a0file_mark\u6807\u8bb0\u591a\u8fdb\u7a0b\uff0c\u4f46\u5e76\u4e0d\u652f\u6301\u591a\u7ebf\u7a0b\u7684\u64cd\u4f5c\uff0c\u8fd9\u662f\u7531\u4e8e\u8d44\u6e90\u548c\u5171\u4eab\u53d8\u91cf\u5360\u7528\u7684\u95ee\u9898\uff0c\u9501\u7684\u673a\u5236\u4e5f\u4f1a\u4f7f\u5f97\u591a\u7ebf\u7a0b\u53d8\u5f97\u201c\u4e0d\u591a\u7ebf\u7a0b\u201d\uff0c\u6240\u4ee5\u5982\u679c\u9700\u8981\u8fdb\u884c\u5e76\u53d1\u6027\u64cd\u4f5c\uff0c\u5e94\u4f7f\u7528\u8fdb\u7a0b\u5f62\u5f0f\uff0c\u5e76\u4f7f\u7528Runner\u7c7b\u4e2d\u7684file_mark\uff0c\u7ed9\u5b9a\u6bcf\u4e2a\u8fdb\u7a0b\u7684\u6587\u4ef6\u540d\u79f0\uff0c\u4fdd\u8bc1\u6587\u4ef6\u72ec\u7acb\u4e0d\u81f3\u4e8e\u88ab\u8986\u76d6\uff0c\u800c\u7528\u6237\u624b\u52a8\u8bbe\u7f6e\u6587\u4ef6\u6807\u8bb0\u7684\u65b9\u5f0f\uff0c\u4e5f\u4f1a\u8ba9\u7528\u6237\u66f4\u5bb9\u6613\u5206\u6e05\u6587\u4ef6\u6307\u5411xlrp\u6709run\u548crun_class\u7684\u8fd0\u884c\u65b9\u5f0f\uff0c\u5982\u679c\u662fclass\u5305\u62ec\u591a\u4e2a\u65b9\u6cd5\u7684\u7528\u4f8b\u7cfb\u7edf\uff0c\u4f7f\u7528run_class\u7684\u65b9\u5f0f\u66f4\u52a0\u4fbf\u6377\uff0crun\u5728\u8fd0\u884c\u5355\u4e2a\u51fd\u6570\u7684\u65f6\u5019\uff0c\u53ef\u4ee5\u4f7f\u7528\u8fd9\u79cd\u65b9\u5f0f\uff0c\u4f46\u662f\u5c3d\u91cf\u4e0d\u8981\u5728\u540c\u6587\u4ef6\u4e2d\u8fdb\u884c\u6df7\u7528\uff0c\u4ed6\u4eec\u5c5e\u4e8e\u4e0d\u540c\u7684\u8fd0\u884c\u65b9\u5f0f\uff0c\u5728\u6570\u636e\u65b9\u9762\uff0c\u53ef\u80fd\u4f1a\u9020\u6210\u51b2\u7a81run_class\u7684\u8fd0\u884c\u662f\u6309\u7167\u7528\u4f8b\u540d\u79f0\u6765\u51b3\u5b9a\u987a\u5e8f\u7684\uff0c\u6240\u4ee5\uff0c\u4f7f\u7528\u7528\u4f8b\u540d\u79f0\u6765\u5408\u7406\u5904\u7406\u8fd0\u884c\u987a\u5e8f\uff0c\u4f46\u8fd9\u91cc\u9700\u8981\u6ce8\u610f\u5224\u65ad\u7684\u662f\u5b57\u7b26\u4e32\u5f62\u5f0f\uff0c\u5982 xl_12_test \u5176\u5b9e\u662f\u6bd4 xl_5_test \u8981\u63d0\u524d\u7684\uff0c\u6240\u4ee5\uff0c\u4ee50\u7684\u65b9\u5f0f\u8fdb\u884c\u8865\u4f4d\u64cd\u4f5c\uff0c\u6ee1\u5341\u8fdb\u4e00\u662f\u6bd4\u8f83\u597d\u7684\u65b9\u5f0f xl_0009_test, xl_0010_test"} +{"package": "xlrw", "pacakge-description": "# xlrw\nxlrw is a Python library to read/write Excel files\nsupport 2010 xlsx/xlsm/xltx/xltm 97-2003 xls/xls/xlt/xlt"} +{"package": "xls", "pacakge-description": "Extract data from XLS Spreadsheets.This uses the js-xls library and PyV8."} +{"package": "xls2csv", "pacakge-description": "No description available on PyPI."} +{"package": "xls2db", "pacakge-description": "xls2db is a python program that takes an excel spreadsheet following a certain\nschema into an sqlite database that can be opened using python\u2019s sqlite3 module.\nIt can also be used as a module.Why??Because fuck you, that\u2019s why.But seriously: I was getting sick of doing data entry for this toy project of\nmine using cursor.execute()\u2019s, so I figured I\u2019d try entering the data into an\nexcel spreadsheet, converting it into the db, and then manipulating it from\nthere. Crazy, I know.Usage:As a script:xls2db infile.xls outfile.dbAs a module:from xls2db import xls2db\nxls2db(\"infile.xls\", \"outfile.db\")For more, visit ."} +{"package": "xls2json", "pacakge-description": "xls2jsonxls2json[--perentry][--persheet]xls_input[output_path='output']Take XLS file and write to JSON file(s) (single, one for every row, and/or one for every workbook sheet).RequirementsxlrdInstallationpip3installxls2jsonTODOcompatibility with json2xls"} +{"package": "xls2moodle", "pacakge-description": "xls2moodleScript to convert multiple choice questions from xls to moodle's xml format. The xml format\ncan then be used to import the questions into moodle quizes. Please note, that this repository\nand the code was intended to be used for german tables / quizes. Adaptions are possible, but\nsome columns (in the input) are hard-coded at the moment.To install the package and make use of the tkinter GUI (thanks @euvbonk), you can usepip install xls2moodleinputThe script requires two arguments as commandline options (see MoodleXML usage):course namelocation of tabular excel file with questionsoutputxml format, ready for import in moodlequestion formatPlease refer to the template_advanced.xlsx to get an ideao on the file format.\nMandatory columns:Aussage1 - possible answer 1Aussage2 - possible answer 2Aussage3 - possible answer 3Aussage4 - possible answer 4WAHR - contains index of correct answer(s), 1-basedFALSCH - contains index of wrong answer(s), 1-basedThemenblock - contains a topic name (this should be the same for similar questions)Hauptfrage - Question textOptional columns:Anwendung - boolean, filter to include (1) or exclude (0) questionsFurther columns are ignored.templatesThe script reads templates (xml_templates-folder) that were previously exported from moodle.\nIf the format changes in the future, this process needs to be repeated. In the meantime, do\nnot touch any of the xml templates.known issueslatex equation code supported (?)reading of data with special encoding (utf-8) currently not possible with the latest pandas versionContributorsBenjamin Furtw\u00e4nglerSven Gieseeuvbonk"} +{"package": "xls2txt", "pacakge-description": "No description available on PyPI."} +{"package": "xls2xlsx", "pacakge-description": "Convert xls file to xlsxFree software: MIT licenseDocumentation:https://xls2xlsx.readthedocs.io.FeaturesConvert.xlsfiles to.xlsxusing xlrd and openpyxl.Convert.htmand.mhtfiles containing tables or excel contents to.xlsxusing beautifulsoup4 and openpyxl.We attempt to support anything that the underlying packages used will support. For example, the following are supported for both input types:Multiple worksheetsText, Numbers, Dates/Times, UnicodeFonts, text color, bold, italic, underline, double underline, strikeoutSolid and Pattern Fills with colorBorders: Solid, Hair, Thin, Thick, Double, Dashed, Dotted; with colorAlignment: Horizontal, Vertical, Rotated, Indent, Shrink To FitNumber Formats, including unicode currency symbolsHidden Rows and ColumnsMerged CellsHyperlinks (only 1 per cell)CommentsThese features are additionally supported by the.xlsinput format:Freeze panesThese features are additional supported by the.htmand.mhtinput formats:ImagesNot supported by either format:Conditional Formatting (the current stylings are preserved)Formulas (the calculated values are preserved)Charts (the image of the chart is handled by.htmand.mhtinput formats)Drawings (the image of the drawing is handled by.htmand.mhtinput formats)Pivot tables (the current data is preserved)Text boxes (converted to an image by.htmand.mhtinput formats)Shapes and Clip Art (converted to an image by.htmand.mhtinput formats)Autofilter (the current filtered out rows are preserved)Rich text in cells (openpyxl doesn\u2019t support this: only styles applied to the entire cell are preserved)Named RangesMacros (VBA)InstallationTo install xls2xlsx, run this command in your terminal:$pipinstallxls2xlsxThis is the preferred method to install xls2xlsx, as it will always install the most recent stable release.UsageTo use xls2xlsx from the command line:$xls2xlsx[-v]file.xls...This will createfile.xlsxin the current folder.file.xlscan be any.xls,.htm, or.mhtfile and can also be a URL. The-vflag will print the input and output filename.To use xls2xlsx in a project:fromxls2xlsximportXLS2XLSXx2x=XLS2XLSX(\"spreadsheet.xls\")x2x.to_xlsx(\"spreadsheet.xlsx\")Alternatively:fromxls2xlsximportXLS2XLSXx2x=XLS2XLSX(\"spreadsheet.xls\")wb=x2x.to_xlsx()The xls2xlsx.to_xlsx method returns the filename given. If no filename is provided, the method returns the openpyxl workbook.The input file can be in any of the following formats:Excel 97-2003 workbook (.xls)Web page (.htm,.html), optionally including a _Files folderSingle file web page (.mht,.mhtml)The input specified can also be any of the following:A filename / pathnameA urlA file-like object (opened in Binary mode for.xlsand either Binary or Text mode otherwise)The contents of a.xlsfile as abytesobjectThe contents of a.htmor.mhtfile as astrobjectNote: The file format is determined by examining the file contents,notby looking at the file extension.DependenciesPython >= 3.6 is required.These packages are also required:xlrd, openpyxl, requests, beautifulsoup4, Pillow,python-dateutil,cssutils, webcolors,currency-symbols,fonttools, PyYAML.Implementation NotesThe.htmand.mhtinput format conversion uses ImageFont from Pillow to measure the size (width and height) of cell contents. The first time you use it, it will look for font files in standard places on your system and create a Font Name to filename mapping. If the proper font files are not found on your system corresponding to the fonts used in the input file, then as a backup, an estimation algorithm is used.If passed a.mhtfile (or url), the temporary folder name specified in the file will be used to unpack the contents for processing, then this folder will be removed when done.CreditsDevelopment LeadJoe Cool ContributorsNone yet. Why not be the first?AcknowledgementsA portion of the code is based on the work of John Ricco (johnricco226@gmail.com), Apr 4, 2017:https://johnricco.github.io/2017/04/04/python-html/This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.0 (2023-01-05)Modernize for more recent pythons and more recent packages. Drop support for Python 3.6. Fix issues #11, #14, #16. Add feature #12.0.1.5 (2020-11-03)Fix issues #1, #3, #50.1.4 (2020-11-02)Fix issue #40.1.3 (2020-10-15)Fix issue #2 - cli not working0.1.0 (2020-09-13)First release on PyPI."} +{"package": "xlsapi", "pacakge-description": "Make \u201cExcel databases\u201d accessible as REST API."} +{"package": "xlsb2xlsx", "pacakge-description": "xlsb2xlsxPurposeAn alternative tosofficethat specifically converts.xlsbfiles to.xlsxfiles.How to usexlsb2xlsxTo convert all.xlsbfiles in a directory, run:python -m xlsb2xlsx /filepathTo convert all.xlsbfiles in a directoryrecursively, run:python -m xlsb2xlsx /filepath --recursiveORpython -m xlsb2xlsx /filepath -rThe--recursiveflag specifies whether files in nested directories are also converted.Fine PrintThis wrapper is built on top of theAspose.Cells projectwhich is proprietary.As a result of being built on top of Aspose.Cells,each converted.xlsxfile will contain an additional sheet namedEvaluation Warningat the end of the.xlsxfile after the conversion is complete. This additional sheet reminds the user that they are using a free version of Aspose's software which should be used for \"Evaluation Only\". The copyrights of Aspose.Cells belong to Apose Pty Ltd and this wrapper exists only for additional ease of use."} +{"package": "xls-cli", "pacakge-description": "A simple tool to open and explore a xls file using ascii characters simulated sheet in terminal"} +{"package": "xlsclone", "pacakge-description": "baangt-CloneXLSThis package was mainly made to use inbaangt.It's functionality is to Clone aexcel file(xls/xlsx)and a new sheet is made inside cloned file which is used to\nstore the change logs.This package contains two main classes. First isCloneXls& second isChangeLog.CloneXlsupdate_or_make_cloneis the main method of this class. On the first run it will create a clone file and if the file\nalready exist it will callChangeLogclass.ChangeLogThis class is used to check the changes between source and cloned file and update those changes inside cloned file.\nTheir are few helpful functionalities like ignore_headers & ignore_sheets these both parameters takes a list.\nHeaders and sheets present in this lists will be ignored for change log and will not be updated from source.xlsxChangeLogis the main method of this class which will trigger all the other methods like checking for changes,\nupdating change log sheet, updating whole clone file from source(except ignored data). AIt will write all the\nchanges inChange Logsworksheet. This data will containDate & time, \"Sheet Name\", \"Header Name\", \"Row Number\", \"Old Value\", \"New Value\"."} +{"package": "xlsconv", "pacakge-description": "xlsform-converter (xlsconv)xlsform-converter converts surveys defined via theXLSForm standardintoDjango modelsand configuration. This makes it possible to re-use the powerful form building tools provided by theOpen Data Kit ecosystem, while leveraging Django's robust support for relational databases likePostgreSQL.xlsform-converter is designed to facilitate the rapid development of offline-capable data collection apps via thewq framework. The ultimate goal is to provide full compatibility with the form authoring tools provided byODKandKoboToolbox(etc.). Note that this is not the same as full XForm compatibility: the client and server components of wq (wq.appandwq.db) use a JSON-basedREST APIto exchange data and are not directly compatible with their ODK Analogues (ODK Collect and ODK Aggregate, respectively).For the database itself, the key distinction from other XLSForm tools (including those powered by Django, like KoboToolbox) is that xlsform-converter converts the xlsform fields directly into a Django model definition, rather than representing the entire XForm standard within Django. This means that each row in an XLSForm \"survey\" tab is mapped to (usually) a single column in a simple relational database table. Repeat questions are handled by creating a second model with aForeignKeyto the parent survey model.For a more thorough comparison of XLSForm tools, seehttps://wq.io/overview/survey123-vs-kobotoolbox-vs-wq.xlsform-converter also supports a couple of additional \"constraints\" that are not part of the XLSForm standard:wq:ForeignKey('app.ModelName'): Create a foreign key to an existing Django model (presumably not defined in the spreadsheet). This is effectively a more relational version ofselect_one_external.wq:initial(3): Very similar torepeat_count, but only set for new records.wq:length(5): Text field maximum length (similar to astring-lengthconstraint)Included Templatesxlsform-converter uses ASTs and templates to generate the following Django/wq project files from a given XLSForm (for example,this file).Django Appsmodels.pyadmin.py(for use withdjango.contrib.admin)wizard.py(for use withDjango Data Wizard)rest.py(for use withwq.db.rest)serializers.py(for use withwq.db.rest)UsageIf you are using wq, you may be interested inwq.create, which uses xlsconv internally for thewq addformcommand. Otherwise, you can use xlsconv directly with the following command-line API:# Recommended: create virtual environment# python3 -m venv venv# . venv/bin/activate# Install xlsconvpipinstallxlsconv# Use the default models.py templatexls2djangomy-odk-survey.xls>myapp/models.py# Use the rest.py template (or admin.py, or serializers.py)xls2djangomy-odk-survey.xlsrest>myapp/models.py"} +{"package": "xlscrap", "pacakge-description": "WARNING : DON'T EXPECT SOMETHING USEFULL FROM THIS TOOL AT THIS STAGE !!xlscrapxlscrap is aMIT-licensedpackage to ease Excel files mass data extractionSee thedocumentation.RationaleHave you ever feel the pain of extracting data from a lot of Excel files ?When you have hundreds or thousands file that look similar\nbut differ in slighty annoying details.When data cells coordinates can't be used because they changeWhen you have to spot dozens or hundreds fields with different strategies.When the same field moves in different sheet position or nameWhen the same field label changesWhen the data cell is on the right of the label or below the labelWhen you need to check that the collected data is correct.xlscrap helps you to scrap data out of your Excel files.Quickstart>>>importxlscrap>>>s=xlscrap.Scrapper()>>>s.field('name')>>>s.field('age')>>>s.field('address')>>>s.table('pets',fields=['name','breed','age'])>>>s.scrap('excel-files/*.xls*')lookingfor4fieldsin5filesinexcel-files/*.xls*,file1/5,found4/4fieldsindiana.xlsxfile2/5,found4/4fieldsinbob.xlsfile3/5,found3/4fieldsinrichard.odsfile4/5,found0/4fieldsinalien.xlsfile5/5,found4/4fieldsinmaria.xlsm>>>s.result[{'name':'Diana','age':47,'address':'44 rue du Louvre\\n75000 Paris\\nFrance''pets':[]},...]TODOset gitlab URL in setup.pyclone gitlab/githubcomplete quickstart in README"} +{"package": "xlscript", "pacakge-description": "No description available on PyPI."} +{"package": "xlseries", "pacakge-description": "A python package to scrapetime\nseriesfromanyexcel\nfile and return them turned intopandasdata frames.InstallationIf you want to install in developer mode,clone the repositoryand follow these instructions:If you are using Anaconda as your python distributionconda create-nxlseries python=2Create new environmentcd project_directorysource activate xlseriesActivate the environmentpip install-e.Install the package in developer modepip install-rrequirements.txtInstall dependenciesdeactivateDeactivate when you are doneIf you are using a standard python installationcd project_directoryvirtualenv venvCreate new environmentsource venv/bin/activateActivate the environmentpip install-rrequirements.txtInstall dependenciesdeactivateDeactivate when you are doneIf you just want to use it:pip install xlseriesin your environment, instead of cloning and pip\ninstalling in developer mode.Quick startfromxlseriesimportXlSeriesxl=XlSeries(\"path_to_excel_file\"oropenpyxl.Workbookinstance)dfs=xl.get_data_frames(\"path_to_json_parameters\"orparameters_dictionary)With the test case number 1:fromxlseriesimportXlSeriesfromxlseries.utils.path_findersimportget_orig_cases_path,get_param_cases_path# this will only work if you clone the repo with all the test filespath_to_excel_file=get_orig_cases_path(1)path_to_json_parameters=get_param_cases_path(1)xl=XlSeries(path_to_excel_file)dfs=series.get_data_frames(path_to_json_parameters)or passing only the critical parameters as a dictionary:parameters_dictionary={\"headers_coord\":[\"B1\",\"C1\"],\"data_starts\":2,\"frequency\":\"M\",\"time_header_coord\":\"A1\"}dfs=xl.get_data_frames(parameters_dictionary)you can specify what worksheet you want to scrape (otherwise the first\none will be used):dfs=xl.get_data_frames(parameters_dictionary,ws_name=\"my_worksheet\")you can ask an XlSeries object for a template dictionary of the critical\nparameters you need to fill:>>>params=xl.critical_params_template()>>>params{'data_starts':2,'frequency':'M','headers_coord':['B1','C1','E1-G1'],'time_header_coord':'A1'}>>>params[\"headers_coord\"]=[\"B1\",\"C1\"]>>>dfs=xl.get_data_frames(params,ws_name=\"my_worksheet\")if this doesn\u2019t work and you want to see exactly where the scraping is\nfailing, you may want to fill out all the parameters and try again to\nsee where the exception is raised:>>>params=xl.complete_params_template()>>>params{'alignment':u'vertical','blank_rows':False,'continuity':True,'data_ends':None,'data_starts':2,'frequency':'M','headers_coord':['B1','C1','E1-G1'],'missing_value':[None,'-','...','.',''],'missings':False,'series_names':None,'time_alignment':0,'time_composed':False,'time_header_coord':'A1','time_multicolumn':False}>>>params[\"headers_coord\"]=[\"B1\",\"C1\"]>>>params[\"data_ends\"]=256>>>params[\"missings\"]=True>>>dfs=xl.get_data_frames(params,ws_name=\"my_worksheet\")Excel file: Up to this development point the excel file should\nnot be morecomplicatedthan the7 test cases:Parameters: Together with the excel file, some parameters about\nthe series must be provided. These could be passed to\nget_data_frames() as a path to aJSON fileor as apython\ndictionary.xlseriesuse about 14 parameters to characterize the\ntime series of a spreadsheet, but only 4 of them arecriticalmost\nof the time: the rest can be guessed by the package. The only\ndifference between specifying more or less parameters than the 4\ncritical is the total time thatxlserieswill need to complete\nthe task (more parameters, less time). Go to theparameterssection for a more detailed\nexplanation about how to use them, and when you need to specify more\nthan the basic 4 (headers_coord,data_starts,frequencyandtime_header_coord).Take a look to thisipython notebook\ntemplateto get started!.If you want to dig inside the test cases and get an idea of how far is\ngoingxlseriesat the moment, check out thisipython notebook with\nthe 7 test cases.For more details go to the official repository on github:https://github.com/abenassi/xlseries"} +{"package": "xlserver", "pacakge-description": "Read your .xls and .xlsx files.ContentsInstallHow it works?Install$: pip xlserver\n$: python setup.py installHow it works?$: xlserver -p 8000Accesshttp://localhost:8000"} +{"package": "xlsext", "pacakge-description": "xlsextExcel ExtensionsInstallationpip install xlsext"} +{"package": "xlsfile-shaw1236", "pacakge-description": "-- Prerequisite modules\n-pandas@0.25.3\n-openpyxl3.0.1\n-xlrd@1.2.0-- Install xlsfile\npip install xlsfile --user-- How to use xlsfile?from xlsfile import xlsfileCsv file testingprint(\"Test csv file\")\ncontents = xlsfile.readcsv(\"test2.csv\")\nxlsfile.writecsv(\"test3.csv\", contents)input = {}\ninput[\"name\"] = [\"Test1\", \"Test2\", \"Test3\"]\ninput[\"email\"] = [\"test1@gmail.com\", \"test2@yahoo.com\", \"test3@gmail.com\"]\ninput[\"name\"].append(\"Test4\")\ninput[\"email\"].append(\"test@yahoo.com\")filename = \"testfamily.xlsx\"Excel file testprint(\"\\nExcel file test\")\nxlsfile.write(filename, input)\ncontents = xlsfile.read(filename)\nprint(contents)Excel to csvprint(\"\\nExcel to csv\")\nxlsfile.xls2csv(filename, filename.replace(\".xlsx\", \".csv\"))csv to Excelprint(\"\\ncsv to Excel\")\nxlsfile.csv2xls(filename.replace(\".xlsx\", \".csv\"), \"testfamily2.xlsx\")\ncontents = xlsfile.read(\"testfamily2.xlsx\")\nprint(contents)"} +{"package": "xlsform-filler-data", "pacakge-description": "XLSform filler dataA commandline tool for creating dummy/test data from XLSform surveys.Installationpip install xlsform-filler-dataUsageTo create a dummy dataset, with a default number of rows(100) from a XLSform source:xlsform-filler-data /To specify the number of rows to create, use the-rflag. Example:xlsform-filler-data / -r 200To specify the output path and filename, pass the-oflag. Example:xlsform-filler-data / -o <./myfile.xlsx>RoadmapAs of version0.1.1the tool does not properly randomise multiple choice questions; omits some variables such as 'start' and 'end'; does not maintain the order of the variables; and does not incorporate constraints or cascading choice lists. These limitations will be adddressed in future releases."} +{"package": "xlsimport", "pacakge-description": "InstallationPackage installed as usually, with commandpip install xlsimportpackage requiresxlrdanddateutils.UsageXlsimport provide only API for now, no demo nor default setup. But it\u2019s simple to start using it.First, you need to create descendant ofxlsimport.models.Formatclass, for example:class SubjectFormat(Format):\n cells = (\n {'name': 'Name', 'parsers': (TextCellToStringParser,)},\n {'name': 'Hours', 'parsers': (TextCellToIntParser, NumberCellToIntParser,)},\n {'name': 'Short name', 'parsers': (TextCellToStringParser,)},\n )\n\n def to_python(self, data_row):\n return {\n 'name': data_row[0],\n 'short_name': re.sub(r'[0-9-]+', '', data_row[2]),\n 'hours': data_row[1],\n }In this codeNamecolumn may contains only text cells and they are represented as strings.\nSecond columnHoursmay contains text cells or number cells. They are represented as integers. Note that parsers\napplied with respect to order.If you want to skip column, giveparsersthe valuexlsimport.models.dummy_parsers.\nIf cell must be empty there isblank_parsersvalue for that case.Next you should make class that knows how to handle data (craate or update records).\nYou also might want to place it into class like Django command.Here\u2019s my example:...\n\nclass Command(BaseCommand):\n\n ...\n\n def handle(self, *args, **options):\n source_filename = args[0]\n source_file = open(source_filename, 'r')\n descriptor, name = tempfile.mkstemp()\n os.fdopen(descriptor, 'wb').write(source_file.read())\n doc = xlrd.open_workbook(name, formatting_info=True)\n format_doc = SubjectFormat(doc)\n\n for index, parsed_row in enumerate(format_doc):\n process_row(index, parsed_row)process_rowhere is a function that takes dictionary fromto_pythonmethod above.Tip. I created agistwith nice example of linuxdialogusage."} +{"package": "xlsjzxku", "pacakge-description": "No description available on PyPI."} +{"package": "xlsmloader", "pacakge-description": "xlsmloaderPre-requisitesPython 3 installed.How to install"} +{"package": "xlson", "pacakge-description": "xlsonPython package for transforming Excel files to JSON files and manipulating themInstallationTo install the package from PyPI type:pip install xlsonOr from the repo:pip install git+https://github.com/loven-doo/xlson.gitFor 'dev' branch version:pip install git+https://github.com/loven-doo/xlson.git@devPackage referencexlson.prepare_xlxlson.handlers.XLSonHandler"} +{"package": "xlsOperator", "pacakge-description": "No description available on PyPI."} +{"package": "xlsql", "pacakge-description": "Introductionxlsqlis a simple command-line tool that converts an Excel.xlsxspreadsheet into asqlite3database.InstallationTo install this utility usingpipyou can simplypip install xlsqlUsageTo view command help, you can always runxlsql --help.Usage: xlsql [OPTIONS] SPREADSHEET\n\nConvert an Excel spreadsheet into a SQLite database.\n\nArgs:\n spreadsheet (str): The path to the Excel spreadsheet.\n\nOptions:\n --column, -c: A column (or columns) to extract. Can be specified multiple times.\n --database: The name of the database to create. (default: database.db)\n --force: Overwrite an existing database.\n --sheet, -s: A sheet (or sheets) to extract. Can be specified multiple times.\n --verbose, -v: Show verbose output.\n --version, -V: Show the xlsql version number.\n\nExamples:\n xlsql ~/Documents/Example.xlsx\n # Creates: ~/Documents/example.db with all data included in the database.\n\n xlsql ~/Documents/Example.xlsx --verbose\n # Creates: ~/Documents/example.db, displaying verbose output while running.\n\n xlsql ~/Documents/Example.xlsx --database /tmp/example.db\n # Creates /tmp/example.db with all data included from the Excel sheet.\n\n xlsql ~/Documents/Example.xlsx --database /tmp/example.db --force\n # Overwrites the existing db with fresh content from the sheet!\n\n xlsql example.xlsx -c name -c id -c address -s people\n # Only select the name, id, and address columns from the people sheet.ContributingTo contribute to this project, please fork the repo and make your changes there. Submit a PR back to this repo for review.Be sure to install the dev dependencies, such aspre-commitandblack."} +{"package": "xlsrch", "pacakge-description": "xlsrch======tools for development..... in anad laboInstallation------------::pip install xlsrchUsage-----::python -m xlsrch... edit config file: xlsrch_conf.yaml... invoke againpython -m xlsrch... the result will print out on STD-OUT and out.txt on defaultnot yet edit^^^^^^^^^^^^--------------| any questions to:| dais.cns@gmail.com"} +{"package": "xls-reader", "pacakge-description": "No description available on PyPI."} +{"package": "xls-report", "pacakge-description": "xls_reportDatabase report generation in xls-format according to the xml descriptionExample:#!/usr/bin/python3importsqlite3fromxls_reportimportXLSReportconnect=sqlite3.connect(\"chinook.sqlite\")cursor=connect.cursor()report=XLSReport({'cursor':cursor,'xml':'test_xls.xml','callback_url':'http://localhost','callback_token':'12345','callback_frequency':20,'parameters':{'title0':'Invoices','customer':'','title1':'Albums','title2':'Money','title3':'Sales','title4':'Customers','artist':''}})report.to_file('test.xls')cursor.close()connect.close()test.xls:{{title0}}font:boldTrue;alignment:horizcentre;borders:left1,top1,bottom1,right1;font:boldTrue;borders:left1,top1,bottom1,right1;font:boldTrue;alignment:horizcentre;LastnameFirstnameAmountDiscountTotalSELECTb.LastName,b.FirstName,round(sum(a.Total),2),round(sum(a.Total)/50,2)FROMInvoiceASaJOINCustomerASbON(b.CustomerId=a.CustomerId)WHEREb.LastNameLIKE'%{{customer}}%'GROUPBYb.LastName,b.FirstNameORDERBYb.LastName,b.FirstName;C{{cs}}-D{{cs}}Total:SUM(E2:E{{ds}}){{title1}}ArtistAlbumSELECTb.nameasArtist,a.TitleasAlbumFROMAlbumaJOINArtistbON(b.ArtistId=a.ArtistId)WHEREArtistLIKE'%{{artist}}%'ORDERBYArtist,Title;{{title2}}ReportbysomegenresMediaGenreAmountDiscountChargedSELECTd.NameASMedia,round(sum(a.Quantity*a.UnitPrice),2)ASMoney,round(sum(a.Quantity*a.UnitPrice/50),2)ASDiscountFROMInvoiceLineASaJOINTrackASbON(b.TrackId=a.TrackId)JOINGenreAScON(c.GenreId=b.GenreId)JOINMediaTypeasdON(d.MediaTypeId=b.MediaTypeId)WHEREc.Name='Latin'GROUPBYd.Name,c.NameORDERBYd.Name,c.NameLatinC{{cs}}-D{{cs}}SELECTround(sum(a.Quantity*a.UnitPrice),2)ASMoney,round(sum(a.Quantity*a.UnitPrice/50),2)ASDiscountFROMInvoiceLineASaJOINTrackASbON(b.TrackId=a.TrackId)JOINGenreAScON(c.GenreId=b.GenreId)JOINMediaTypeasdON(d.MediaTypeId=b.MediaTypeId)WHEREc.Name='World'GROUPBYd.Name,c.NameORDERBYd.Name,c.NameWorldC{{cs}}-D{{cs}}Subtotal:INDIRECT(\"E\"&({{ss}}+3))+INDIRECT(\"E\"&({{ss}}+4))Total:INDIRECT(\"E\"&({{cs}}-5))+INDIRECT(\"E\"&({{cs}}-1)){{title3}}MediaGenreAmountDiscountChargedSELECTd.NameASMedia,c.NameasGenre,round(sum(a.Quantity*a.UnitPrice),2)ASMoney,round(sum(a.Quantity*a.UnitPrice/50),2)ASDiscount,round(sum(a.Quantity*a.UnitPrice),2)-round(sum(a.Quantity*a.UnitPrice/50),2)ASChargedFROMInvoiceLineASaJOINTrackASbON(b.TrackId=a.TrackId)JOINGenreAScON(c.GenreId=b.GenreId)JOINMediaTypeasdON(d.MediaTypeId=b.MediaTypeId)GROUPBYd.Name,c.NameORDERBYd.Name,c.Name{{title4}}CustomerMediaGenreAmountDiscountChargedSELECTf.LastName||''||f.FirstNameASCustomer,d.NameASMedia,c.NameasGenre,round(sum(a.Quantity*a.UnitPrice),2)ASMoney,round(sum(a.Quantity*a.UnitPrice/50),2)ASDiscount,round(sum(a.Quantity*a.UnitPrice),2)-round(sum(a.Quantity*a.UnitPrice/50),2)ASChargedFROMInvoiceLineASaJOINTrackASbON(b.TrackId=a.TrackId)JOINGenreAScON(c.GenreId=b.GenreId)JOINMediaTypeasdON(d.MediaTypeId=b.MediaTypeId)JOINInvoiceaseON(e.InvoiceId=a.InvoiceId)JOINCustomerasfON(f.CustomerId=e.CustomerId)WHEREf.LastNameLIKE'%%'GROUPBYCustomer,d.Name,c.NameORDERBYCustomer,d.Name,c.NamePlaylistPlaylistAlbumTrackMillisecondsBytesPriceSELECTDISTINCTb.NameASPlaylist,d.TitleASAlbum,c.NameASTrack,c.Milliseconds,c.Bytes,c.UnitPriceASPriceFROMPlaylistTrackasaJOINPlaylistasbON(b.PlaylistId=a.PlaylistId)JOINTrackascON(c.TrackId=a.TrackId)JOINAlbumasdON(d.AlbumId=c.AlbumId)ORDERBYb.Name,d.Title,c.NameSee directory test. TODO: normal documentation."} +{"package": "xLSTM", "pacakge-description": "xLSTMfromxLSTMimportLSTMLSTM(len_dictionary=50_000,hidden_size=1024,nlayers=12).generate_text()"} +{"package": "xlsToCsv", "pacakge-description": "This script converts excel files to CSV"} +{"package": "xls-to-csv", "pacakge-description": "XLS to CSV converter.\nVery fast, extremely light and easy to use.Installation:pip install xlstocsvComplementary package to xlsx2csv(https://github.com/xevo/xls2csv) - great tool, but does not work with .xls filesxlstocsvworks only with xls file (for legacy systems and 'legacy' clients :))Dependencies:\n- python > 2.7\n- pandas,\n- xlrdUsage:xlstocsv /path/to/xls_or_xlsx_file/# spits CSV lines on CLI\nUsage:xlstocsv /path/to/xls_or_xlsx_file/ /path/to/file.csv# writes in a CSV file"} +{"package": "xlstools", "pacakge-description": "xls-toolsExcel and Excel-like toolsxlrd_likeA minimal interface for accessing excel-type files using thexlrdAPI:XlrdLike: workbook equivalent.sheet_names()- return list of sheet names.sheet_by_name()- return an XlSheetLike given by name.sheet_by_index()- return an XlSheetLike given by index.sheets()- return a list of XlSheetLikes-- requires initializing every sheetXlSheetLike: worksheet equivalent.name- the name of the sheet according to the workbook.nrows- int number of rows, 0-indexed.ncols- int number of columns, 0-indexed.row(n)- return a list of XlCellLike corresponding to the nth (0-indexed) row, or IndexError.col(k)- return a list of XlCellLike corresponding to the kth (0-indexed) column, or IndexError.cell(n,k)- return the nth row, kth cell, or IndexError.get_rows()- row iterator.row_dict(n)- return a dict of row n, using row 0 (headers) as keys and XlCellLike as valuesXlCellLike: cell equivalent.ctype- int, as indicated inxlrd.value- native valuexlrdctypes are as follows:from xlrd.biffh import (\n XL_CELL_EMPTY, # 0\n XL_CELL_TEXT, # 1\n XL_CELL_NUMBER, # 2\n XL_CELL_DATE, # 3\n XL_CELL_BOOLEAN,# 4\n # XL_CELL_ERROR, # 5\n # XL_CELL_BLANK, # 6 - for use in debugging, gathering stats, etc\n)To use:>>> from xls_tools import open_xl\n>>> xl = open_xl(filename)\n>>>Google sheetsAlso provides an xlrd-like interface for accessing google sheets. Can also write to google sheets.\nFor this you need credentials for Google's service API. See:Obtaining a service account$pythonsetup.pyinstallxls_tools[gsheet]xl_reader and xl_sheetModerately clever sheets for auto-detecting tabular data in spreadsheets, and manipulating it.\n\"Clever\" enough to get in trouble perhaps."} +{"package": "xlstotxt", "pacakge-description": "No description available on PyPI."} +{"package": "xlstpl", "pacakge-description": "xlstplA python module to generate xls files from a xls template.How it worksxlstpl uses xlrd to read and use xlwt to write .xls files, uses jinja2 as its template engine.When xlstpl reads a .xls file, it creates a tree for each worksheet.Then, it translates the tree to a jinja2 template with custom tags.When the template is rendered, jinja2 extensions of cumtom tags call corresponding tree nodes to write the .xls file.Syntaxxlstpl uses jinja2 as its template engine, follows thesyntax of jinja2 template.Each worksheet is translated to a jinja2 template with custom tags....\n...\n{% row 45 %}\n{% cell 46 %}{% endcell %}\n{% cell 47 %}{% endcell %}\n{% cell 48 %}{{address}} {%xv v%}{% endcell %}\n{% cell 49 %}{% endcell %}\n{% cell 50 %}{% endcell %}\n{% cell 51 %}{% endcell %}\n{% cell 52 %}{% endcell %}\n{% cell 53 %}{% endcell %}\n{% row 54 %}\n{% cell 55 %}{% endcell %}\n{% cell 56 %}{% sec 0 %}{{name}}{% endsec %}{% sec 1 %}{{address}}{% endsec %}{% endcell %}\n...\n...\n{% for item in items %}\n{% row 64 %}\n{% cell 65 %}{% endcell %}\n{% cell 66 %}{% endcell %}\n{% cell 67 %}{% endcell %}\n{% cell 68 %}{% endcell %}\n{% cell 69 %}{% endcell %}\n{% cell 70 %}{% endcell %}\n{% cell 71 %}{% endcell %}\n{% cell 72 %}{% endcell %}\n{% endfor %}\n...\n...xlstpl added 4 custom tags: row, cell, sec, and xv.row, cell, sec are used internally, used for row, cell and rich text.xv is used to define a variable.When a cell contains only a xv tag, this cell will be set to the type of the object returned from the variable evaluation.For example, if a cell contains only {%xv amt %}, and amt is a number, then this cell will be set to Number type, displaying with the style set on the cell.If there is another tag, it is equivalent to {{amt}}, will be converted to a string.InstalltionpipinstallxlstplHow to useSeeexamples.Notesxlrdxlrd does not extract print settings.This repodoes.xlwtxlwt always sets the default font to 'Arial'. (Excel measures column width units based on the default font).This repodoes not."} +{"package": "xl-sudoku-solver", "pacakge-description": "XL-Sudoku-SolverInstallpip install xl-sudoku-solverUsageCmd:problem1.txt:\n9x37xxxx1\nxxx6xx5xx\nx4xxx1xxx\nxxx36x2xx\n8xxxxxxx4\nxx6x97xxx\nxxx5xxx2x\nxx7xx3xxx\n3xxxx28x9$ xl-sudoku-solver --time -f problem1.txt\n+-----------+-----------+-----------+\n| 9 ! 5 ! 3 | 7 ! 2 ! 4 | 6 ! 8 ! 1 |\n| 7 ! 8 ! 1 | 6 ! 3 ! 9 | 5 ! 4 ! 2 |\n| 6 ! 4 ! 2 | 8 ! 5 ! 1 | 9 ! 3 ! 7 |\n+-----------+-----------+-----------+\n| 1 ! 7 ! 4 | 3 ! 6 ! 8 | 2 ! 9 ! 5 |\n| 8 ! 3 ! 9 | 2 ! 1 ! 5 | 7 ! 6 ! 4 |\n| 5 ! 2 ! 6 | 4 ! 9 ! 7 | 3 ! 1 ! 8 |\n+-----------+-----------+-----------+\n| 4 ! 9 ! 8 | 5 ! 7 ! 6 | 1 ! 2 ! 3 |\n| 2 ! 1 ! 7 | 9 ! 8 ! 3 | 4 ! 5 ! 6 |\n| 3 ! 6 ! 5 | 1 ! 4 ! 2 | 8 ! 7 ! 9 |\n+-----------+-----------+-----------+\nCost: 0.171875s"} +{"package": "xls-updater", "pacakge-description": "xls_updaterConvert legacy xls data to newer xlsx format.\ud83d\udcadBased on the kind comment made by JackypengyuUsageUsage: python -m xls_updater [OPTIONS] SRC_FILE_PATH\n\n Convert an xls file to xlsx.\n\nOptions:\n --version Show the version and exit.\n --help Show this message and exit.DevelopmentPlease seeCONTRIBUTING.mdLicenseThis project is published under the MIT license.If you do find it useful, please consider contributing your changes back upstream."} +{"package": "xls-writer", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx", "pacakge-description": "UNKNOWN"} +{"package": "xlsx2csv", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx2dfs", "pacakge-description": "xlsx2dfsEasy loading from and writing to excel sheets to/from pandas DataFrames (and list of sheet_names).Installationpipinstallxlsx2dfsUsagefromxlsx2dfsimportxlsx2dfs,withNames,dfs2xlsx# xlsx file pathfpath=\"test.xlsx\"# read from it:dfs,sheet_names=xlsx2dfs(fpath)# write to itout_fpath=\"out_test.xlsx\"dfs2xlsx(dfs,sheet_names=[\"sheet1\",\"sheet2\",\"sheet3\"],out_fpath=out_fpath)# or using `withNames` which allows alternate input of sheet_name and corresponding df# `withNames(\"sheet1\", dfs[0], \"sheet2\" dfs[1], \"sheet3\", dfs[2])` returns# ([dfs[0], dfs[1], dfs[2]], [\"sheet1\", \"sheet2\", \"sheet3\"])# thus (dfs, sheet_names). Using asterisk we can integrate them into the argument list# of `dfs2xlsx`.dfs2xlsx(*withNames(\"sheet1\",dfs[0],\"sheet2\"dfs[1],\"sheet3\",dfs[2]),out_fpath)# This makes especially sense when you have different data frames as results in your script# and you want to save few lines of code which would be needed to bind them# together into a list and name them.# Instead, you can do the naming and binding to a list using `*withNames().# This also enhances readability and is intuitive.# e.g.dfs2xlsx(*withNames(\"Temperatures\",temperatures_df,\"Prediction\",prediction_df,\"Original Data\",orig_df),\"/path/to/output/file.xlsx\")document the version:Linux:$ pip freeze | grep xlsx2dfsWindows:c:\\> pip freeze | findstr xlsx2dfs"} +{"package": "xlsx2html", "pacakge-description": "xlsx2htmlA simple export from xlsx format to html tables with keep cell formattingInstallpipinstallxlsx2htmlUsageSimple usagefromxlsx2htmlimportxlsx2htmlout_stream=xlsx2html('path/to/example.xlsx')out_stream.seek(0)print(out_stream.read())or pass filepathfromxlsx2htmlimportxlsx2htmlxlsx2html('path/to/example.xlsx','path/to/output.html')or use file like objectsimportiofromxlsx2htmlimportxlsx2html# must be binary modexlsx_file=open('path/to/example.xlsx','rb')out_file=io.StringIO()xlsx2html(xlsx_file,out_file,locale='en')out_file.seek(0)result_html=out_file.read()or from shellpython-mxlsx2htmlpath/to/example.xlsxpath/to/output.html"} +{"package": "xlsx2html-bugfix", "pacakge-description": "xlsx2htmlA simple export from xlsx format to html tables with keep cell formattingInstallpipinstallxlsx2htmlUsageSimple usagefromxlsx2htmlimportxlsx2htmlout_stream=xlsx2html('path/to/example.xlsx')out_stream.seek(0)print(out_stream.read())or pass filepathfromxlsx2htmlimportxlsx2htmlxlsx2html('path/to/example.xlsx','path/to/output.html')or use file like objectsimportiofromxlsx2htmlimportxlsx2html# must be binary modexlsx_file=open('path/to/example.xlsx','rb')out_file=io.StringIO()xlsx2html(xlsx_file,out_file,locale='en')out_file.seek(0)result_html=out_file.read()or from shellpython-mxlsx2htmlpath/to/example.xlsxpath/to/output.html"} +{"package": "xlsx2json", "pacakge-description": "UNKNOWN"} +{"package": "xlsx2pandas", "pacakge-description": "\ud83d\ude80xlsx2pandas (PandasXcelerator)Part of aProjectText Suite. xlsx2pandas (PandasXcelerator) is a Python library for extraction of tables in Excel sheets into a pandas DataFrames.\ud83c\udf1fFeaturesTODO: features\ud83d\udce5 InstallationTo installxlsx2pandas, use the following pip command:pip3installgit+https://github.com/Flagro/xlsx2pandas.git\ud83d\udcd8UsageRunxlsx2pandasfrom the bin folder with these arguments:path: Path to the file or directory to process.--sheet: (Optional) Comma-separated list of excel workbooks's sheets.\ud83d\udda5\ufe0f Example Commandxlsx2pandas'path/to/file'--sheetSheet1,Sheet2\ud83e\udd1dCollaboration & IssuesOpen for collaboration; check theissues pagefor discussions.Here's how you can contribute:Fork the Project.Create your Feature Branch (git checkout -b feature/AmazingFeature).Commit your Changes (git commit -m 'Add some AmazingFeature').Push to the Branch (git push origin feature/AmazingFeature).Open a Pull Request."} +{"package": "xlsx2pdf", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx2sqlite", "pacakge-description": "Generate a Sqlite3 database from a Office Open XML file.\nRead thexlsx2sqlite documentation.UsageFirst create a .INI config file that you will pass as an argument to thexlsx2sqlitecommand line tool. This will serve as a model to import data\nfrom the .xlsx file.The INI file must contains this section:PATHSOptional sections, see below:EXCLUDEExample of a configuration:[PATHS]; declare the paths of the files to be read.root_path=baserootpath/xlsx_file=%(root_path)s/exampletoimport.xlsxdb_file=%(root_path)s/databasename.dbdb_url=sqlite:///%(db_file)ssql_views=%(root_path)s/views; declare to import a worksheet like this :; name of the worksheet to import[SheetName1]; comma-separated list of the columns to importcolumns=Col1,Col2,Col3; composite primary key is supported:primary_key=Col1,Col2[SheetName2]; valid model keywords are:columns=Col1,Col2primary_key=idunique=Col2not_null=Col2; add if the row with the header is not the first row of the worksheetheader=2Optional \u201cexclude\u201d section, use if you don\u2019t want to import some section of the ini file,\nthis is useful in example for co-exist with some other configuration file.[EXCLUDE]sections=SECTION1,section2,etc.; use a list of comma-separated values.InstallationInstall the release from PyPI:$pipinstallxlsx2sqliteInstalling from source, a virtualenv is recommended:$pipinstall--editable.Requirementsxlsx2sqliteis powered byClickandTablib.Compatibilityxlsx2sqliteis compatible with Python 3.7+.LicenceGPLv3Authorsxlsx2sqlitewas written byErik Mascheri."} +{"package": "xlsx2xlsm", "pacakge-description": "xlsx2xlsmPython change Microsoft Word 2007+ (.xlsx) files to .xlsmInstallationpip install xlsx2xlsmExample>>>fromxlsx2xlsmimportxlsx2xlsm>>>xlsx2xlsm(\"1.xlsx\")# or you have bin file path>>>xlsx2xlsm(\"1.xlsx\",\"vbaProject.bin\")"} +{"package": "xlsxcessive", "pacakge-description": "XlsXcessive provides a Python API for writing Excel/OOXML compatible .xlsx\nspreadsheets. It generates the XML and usesopenpackto wrap it up into an OOXML compatible ZIP file.Creating a WorkbookThe starting point for generating an .xlsx file is a workbook:from xlsxcessive.workbook import Workbook\n\nworkbook = Workbook()Adding WorksheetsThe workbook alone isn\u2019t very useful. Multiple worksheets can be added to the\nworkbook and contain the cells with data, formulas, etc. Worksheets are created\nfrom the workbook and require a name:sheet1 = workbook.new_sheet('Sheet 1')Working With CellsAdd some cells to the worksheet:sheet1.cell('A1', value='Hello, world')\nsheet1.cell('B1', value=7)\nsheet1.cell('C1', value=3.14)\nsheet1.cell('D1', value=decimal.Decimal(\"19.99\"))Strings, integers, floats and decimals are supported.Add cells via row index and column index:sheet1.cell(coords=(0, 4), value=\"Added via row/col index\")This form of addressing is useful when iterating over data\nstructures to populate a sheet with cells.Calculations With FormulasCells can also contain formulas. Formulas are created with a string representing\nthe formula code. You can optionally supply a precalcuated value and asharedboolean flag to share the formula across a number of\ncells. The first cell to reference a shared formula as its value is the master\ncell for the formula. Other cells may also reference the formula:formula = sheet1.formula('B1 + C1', shared=True)\nsheet1.cell('C2', formula) # master\nsheet1.cell('D2', formula) # shared, references the master formulaCells With StyleThe library contains basic support for styling cells. The first thing to do is\ncreate a style format. Style formats are shared on a stylesheet on the\nworkbook:bigfont = workbook.stylesheet.new_format()\nbigfont.font(size=24, bold=True)Apply the format to cells:sheet1.cell('A2', 'HI', format=bigfont)Other supported style transformations include cell alignment and borders:col_header = workbook.stylesheet.new_format()\ncol_header.align('center')\ncol_header.border(bottom='medium')Adjusting Column WidthIt is possible to adjust column widths on a sheet. The column width is specified\nby either number or index:# these are the same column\nsheet1.col(index=0, width=10)\nsheet1.col(number=1, width=10)TODO: Referencing columns by letters.Merging CellsCells can be merged together. The left-most cell in the merge range should\ncontain the data:from xlsxcessive.worksheet import Cell\na3 = sheet1.cell('A3', 'This is a lot of text to fit in a tiny cell')\na3.merge(Cell('D3'))Save Your WorkYou can save the generated OOXML data to a local file or to an output file\nstream:# local file\nsave(workbook, 'financials.xlsx')\n\n# stream\nsave(workbook, 'financials.xlsx', stream=sys.stdout)FutureThis is certainly a work in progress. The focus is going to be on improving the\nfeatures that can be written out in the .xlsx file. That means more data types,\nstyles, metadata, etc. I also want to improve the validation of data before it\nis written in an incorrect manner and Excel complains about it. I don\u2019t think\nthis library will ever be crafted to read .xlsx files. That\u2019s a job for another\nlibrary that can hate its life."} +{"package": "xlsxColumnRow", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlsxcompare", "pacakge-description": "# xlsx_compare\nForked from XLSXwriterA package that extracts some test helper functions from XLSXwriter for external use. The script provies the ability to compare the equivalency of two Excel documents."} +{"package": "xlsx-csv", "pacakge-description": "A Fast XLSX to CSV ConverterInstallationpipinstallxlsx_csvUsageimportxlsx_csvxlsx_csv.xlsx2csv(\"path/to/xlsx.file\",\"SheetName\")It will create a \"path/to/xlsx.csv\" file."} +{"package": "xlsxCsvConverterrr", "pacakge-description": "xlsxCsvConverterrrfromconverter.converterimportxlsx_to_csv,csv_to_xlsxxlsx_to_csv('input_file','output_file')# input_file - xlsx file, output_file - path to save csv filecsv_to_xlsx('input_file','output_file')# input_file - csv file, output_file - path to save xlsx file# Functions return True if file had been saved"} +{"package": "xlsxdiff", "pacakge-description": "All test data for merger courtesy ofhttp://www.identitygenerator.com/"} +{"package": "xlsxdocument", "pacakge-description": "This is a wrapper foropenpyxlwhich makes creating XLSX documents with\nthe purpose of exporting data less boring:from xlsxdocument import XLSXDocument\n\ndef xlsx_export(request):\n some_data = Bla.objects.all()\n\n xlsx = XLSXDocument()\n xlsx.table_from_queryset(Bla.objects.all())\n return xlsx.to_response('bla.xlsx')Adding in additional cells at the end is also possible:xlsx = XLSXDocument()\nxlsx.table_from_queryset(\n Bla.objects.all(),\n additional=[(\n 'Full URL',\n lambda instance: 'http://example.com%s' % (\n instance.get_absolute_url(),\n ),\n )],\n)You can also easily add the facility to export rows to Django\u2019s\nadministration interface:from django.contrib import admin\nfrom django.utils.translation import gettext_lazy as _\n\nfrom xlsxdocument import export_selected\n\nfrom app import models\n\n\nclass AttendanceAdmin(admin.ModelAdmin):\n list_filter = ('event',)\n actions = (export_selected,)\n\n\nadmin.site.register(models.Event)\nadmin.site.register(models.Attendance, AttendanceAdmin)If you require additional columns withexport_selecteduse this\nsnippet instead:from xlsxdocument import create_export_selected\n\nclass AttendanceAdmin(...):\n actions = [\n create_export_selected(\n additional=[\n # ... see above\n ]\n )\n ]"} +{"package": "xlsxecute", "pacakge-description": "xlsxecuteThis tool will take an Excel model (.xlsx), update any parameters as defined via command line arguments or in the parameters file and calculate all cells, resulting in an Excel spreadsheet resembling the original, but with all formula cells replaced by the calculated values.Parameters that define how to update cells in your spreadsheet can be provided in three ways:\nJSON file, CSV file, or command line argumentsIf both a config file and command line arguments are provided, the command line argumentsConfig file formattingOnly one config file can be provided at a time. The config file can either beCommand line arguments:Command line arguments take the form of:-f\"Sheet name.Cell1=Replacement value string\"-f\"Sheet name.Cell2=Replacement_value_float\"Note: Quotation marks are not required if there no space in the parameter string.Example:xlsxecute -f \"Variables.C2=red\" -f Variables.C3=0.8 sample.xlsxJSON:{\"Sheet name.Cell1\":\"Replacement value string\",\"Sheet name.Cell2\":Replacement_value_float}Example: params.json{\"Variables.C2\":\"red\",\"Variables.C3\":0.8}CSV:Sheet name.Cell1,Replacement value string\nSheet name.Cell2,Replacement value floatExample: params.csvVariables.C2,red\nVariables.C3,0.8NOTE: Do NOT include a header row in the CSVExecutable usage:usage: xlsxecute [-h] [--output_dir OUTPUT_DIR] [--run_dir RUN_DIR] [--param {sheet}.{cell}={new_value}] source_file [parameter_file]\n\npositional arguments:\n source_file Excel (xlsx) file that contains the model\n parameter_file Path to json or csv parameter file\n\noptional arguments:\n -h, --help show this help message and exit\n --output_dir OUTPUT_DIR\n Optional output location. (Default: output)\n --run_dir RUN_DIR Optional directory to store intermediate files. (Default: runs)\n --param {sheet}.{cell}={new_value}, -p {sheet}.{cell}={new_value}"} +{"package": "xlsx-evaluate", "pacakge-description": "Calculate XLSX formulasxlsx_evaluate- python library to convert excel functions in python code without the need for Excel itself within the scope of supported features.This library is forkxlcalculator. Use this library.SummaryCurrently supportsSupported FunctionsAdding/Registering Excel FunctionsExcel number precisionTestInstallation# pippipinstallxlsx-evaluate# poetrypoetryaddxlsx-evaluateExampleinput_dict={'B4':0.95,'B2':1000,\"B19\":0.001,'B20':4,'B22':1,'B23':2,'B24':3,'B25':'=B2*B4','B26':5,'B27':6,'B28':'=B19 * B20 * B22','C22':'=SUM(B22:B28)',\"D1\":\"abc\",\"D2\":\"bca\",\"D3\":\"=CONCATENATE(D1, D2)\",}fromxlsx_evaluateimportModelCompilerfromxlsx_evaluateimportEvaluatorcompiler=ModelCompiler()my_model=compiler.read_and_parse_dict(input_dict)evaluator=Evaluator(my_model)forformulainmy_model.formulae:print(f'Formula{formula}evaluates to{evaluator.evaluate(formula)}')# cells need a sheet and Sheet1 is default.evaluator.set_cell_value('Sheet1!B22',100)print('Formula B28 now evaluates to',evaluator.evaluate('Sheet1!B28'))print('Formula C22 now evaluates to',evaluator.evaluate('Sheet1!C22'))print('Formula D3 now evaluates to',evaluator.evaluate(\"Sheet1!D3\"))TODODo not treat ranges as a granular AST node it instead as an operation \":\" of\ntwo cell references to create the range. That will make implementing\nfeatures likeA1:OFFSET(...)easy to implement.Support for alternative range evaluation: by ref (pointer), by expr (lazy\neval) and current eval mode.Pointers would allow easy implementations of functions like OFFSET().Lazy evals will allow efficient implementation of IF() since execution\nof true and false expressions can be delayed until it is decided which\nexpression is needed.Implement array functions. It is really not that hard once a proper\nRangeData class has been implemented on which one can easily act with scalar\nfunctions.Improve testingRefactor model and evaluator to use pass-by-object-reference for values of\ncells which then get \"used\"/referenced by ranges, defined names and formulasHandle multi-file addressesImprove integration with pyopenxl for reading and writing filesexample of\nproblem space"} +{"package": "xlsx-from-json", "pacakge-description": "xlsx_from_jsonCreates xlsx from json viaopenpyxl.UsageCreate .json file with following structure:{\"rows\":[{\"cells\":[{\"value\":\"Sample text\",// merge 5x2 cell range\"width\":5,\"height\":2,// openpyxl style: https://openpyxl.readthedocs.io/en/2.5/styles.html\"style\":{\"font\":{\"name\":\"Times New Roman\",\"size\":12},\"border\":{\"bottom\":{// openpyxl border styles: // https://openpyxl.readthedocs.io/en/stable/_modules/openpyxl/styles/borders.html\"border_style\":\"medium\",\"color\":\"FFFFFFFF\"}}}}],// move row by 2x1\"skip_columns\":2,\"skip_rows\":1,// change row height\"row_height\":10}],\"start_column\":1,\"start_row\":1,// change column widths\"column_widths\":[{// column_number or column_letter\"column_number\":1,\"width\":10}],// set number format (e.g. 1.234 -> 1.23)\"number_format\":\"0.00\",// apply style to all cells\"default_style\":{\"font\":{\"bold\":true}}}Create openpyxl workbook viaxlsx_from_jsonfunction:importjsonfromxlsx_from_jsonimportxlsx_from_jsonwithopen(\"data.json\",encoding=\"utf-8\")asf:json_data=json.load(f)wb=xlsx_from_json(json_data)Created workbook will have values:sheet=wb.activeassertsheet.cell(row=2,cell=3).value==\"Sample text\"The same true for the styles (cell ctyle + default style):sheet=wb.activeassertsheet.cell(row=2,cell=3).font.name==\"Times New Roman\"assertsheet.cell(row=2,cell=3).font.bold==TrueNow you can use workbook according to openpyxlguide."} +{"package": "xlsxgen", "pacakge-description": "xlsxgenpip install \u3067 xlsxgen\u306e\u30e2\u30b8\u30e5\u30fc\u30eb\u3092\u843d\u3068\u3057\u3066\u3001python\u30b3\u30fc\u30c9\u3092\u4ee5\u4e0b\u306e\u901a\u308a\u8a18\u8ff0\u3059\u308b\u3002\u30b9\u30d4\u30fc\u30c9\u91cd\u8996\u306e\u5834\u5408\u306f\u30e1\u30bd\u30c3\u30c9(process_bytes)\u3092\u30b3\u30e1\u30f3\u30c8\u89e3\u9664\u3059\u308b\u30e1\u30e2\u30ea\u5bb9\u91cf\u3092\u6291\u3048\u305f\u3044\u5834\u5408\u306f\u30e1\u30bd\u30c3\u30c9(process_bytes_zlib)\u3068\u3001zlip\u306e\u5727\u7e2e\u51e6\u7406\u306e\u7b87\u6240\u3092\u30b3\u30e1\u30f3\u30c8\u89e3\u9664\u3059\u308b\u4f7f\u3044\u65b9importpandasaspdimportzipfileimportxlsxgenimportresourceimporttimeimportioimportzlib# \u958b\u59cbstart_time=time.perf_counter()file_name='tenpo_shohin_pattern3.xlsx'excel_sheet='sheet1'withopen(file_name,'rb')asfile_obj:withzipfile.ZipFile(file_obj,'r')aszip_ref:# \u30a8\u30af\u30bb\u30eb\u30d5\u30a1\u30a4\u30eb\u3092\u5c55\u958b\u3057\u3066\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u53d6\u5f97s_list=[f'xl/worksheets/{excel_sheet}.xml']sheet_list=[iforiinzip_ref.namelist()ifiins_list]solve_bytes='xl/sharedStrings.xml'bytes_obj=zip_ref.read([iforiinzip_ref.namelist()ifiinsheet_list][0])bytes_solve_obj=zip_ref.read(solve_bytes)generator=xlsxgen.DataGenerator()# \u30b9\u30d4\u30fc\u30c9\u91cd\u8996\u306e\u30b1\u30fc\u30b9(\u30e1\u30e2\u30ea\u5bb9\u91cf\u306f\u5927\u304d\u304f\u6d88\u8cbb\u3059\u308b)generator.process_bytes(10000,bytes_obj,bytes_solve_obj)# \u30e1\u30e2\u30ea\u5bb9\u91cf\u3092\u6291\u3048\u305f\u3044\u30b1\u30fc\u30b9(\u30b9\u30d4\u30fc\u30c9\u306f\u5c11\u3057\u9045\u3044)# bytes_obj = zlib.compress(bytes_obj)# bytes_solve_obj = zlib.compress(bytes_solve_obj)# generator.process_bytes_zlib(10000, bytes_obj, bytes_solve_obj)whileTrue:csv_data=generator.generate_data_chunk()ifcsv_data==\"finish\":print(csv_data)breakifcsv_data:print(csv_data)#df = pd.read_csv(io.StringIO(csv_data), header=None)#print(df)memory_info=resource.getrusage(resource.RUSAGE_SELF).ru_maxrssprint(f\"Max RSS:{memory_info/1024/1024}MB\")end_time=time.perf_counter()# \u7d4c\u904e\u6642\u9593\u3092\u51fa\u529b(\u79d2)elapsed_time=end_time-start_timeprint(elapsed_time)"} +{"package": "xlsxgrep", "pacakge-description": "Owerviewxlsxgrepis a CLI tool to search text in XLSX, XLS, CSV, TSV and ODS files. It works similarly to Unix/GNU Linuxgrep.FeaturesGrep compatible: xlsxgrep tries to be compatible with Unix/Linux grep, where it makes sense.\nSome of grep options are supported (such as-r,-ior-c).Search many XLSX, XLS, CSV, TSV and ODS files at once, even recursively in directories.Regular expressions: Python regex.Supported file types: csv, ods, tsv, xls, xlsxUsage:usage: xlsxgrep [-h] [-V] [-P] [-F] [-i] [-w] [-c] [-r] [-H] [-N] [-l] [-L] [-S SEPARATOR] [-Z]\n pattern path [path ...]\n\npositional arguments:\n pattern use PATTERN as the pattern to search for.\n path file or folder location\n\noptional arguments:\n -h, --help show this help message and exit\n -V, --version display version information and exit.\n -P, --python-regex PATTERN is a Python regular expression. This is the default.\n -F, --fixed-strings interpret PATTERN as fixed strings, not regular expressions.\n -i, --ignore-case ignore case distinctions.\n -w, --word-regexp force PATTERN to match only whole words.\n -c, --count print only a count of matches per file.\n -r, --recursive search directories recursively.\n -H, --with-filename print the file name for each match.\n -N, --with-sheetname print the sheet name for each match.\n -l, --files-with-match\n print only names of FILEs with match pattern.\n -L, --files-without-match\n print only names of FILEs with no match pattern.\n -S SEPARATOR, --separator SEPARATOR\n define custom list separator for output, the default is TAB\n -Z, --null output a zero byte (the ASCII NUL character) instead of the usual newline.Examples:xlsxgrep-i\"foo\"foobar.xlsxxlsxgrep-c-H\"(?i)foo|bar\"/folderInstallationpipinstallxlsxgrep"} +{"package": "xlsxhelper", "pacakge-description": "xlsxhelperExcel file manipulation toolset.NoticeThe library is based on library openpyxl, so only xlsx (new excel format) files are supported.Help Functionsget_workbookget_worksheetget_merged_range_stringparse_colsparse_rowsget_cellsset_cells_dataload_data_from_workbookget_merged_rangescopy_cellsmerge_rangesTest Passed With Pythons2.73.43.53.63.73.83.93.103.11Releasesv0.3.2 2023/09/10Fix unit test problem.v0.3.1 2022/01/10Fix license file missing problem.Add set_cells_data function.v0.3.0 2020/07/19Add workbook and worksheet create support.v0.2.1 2019/08/31Fix load_data_from_workbook get raw function statement problem.Fix worksheet.merged_cell_ranges deprecating problem, use worksheet.merged_cells.ranges instead."} +{"package": "xlsx-import-tools", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx-lib-infomoto", "pacakge-description": "No description available on PyPI."} +{"package": "xlsxlite", "pacakge-description": "XLSXLiteThis is a lightweight XLSX writer with emphasis on minimizing memory usage. It's also really fast.fromxlsxlite.writerimportXLSXBookbook=XLSXBook()sheet1=book.add_sheet(\"People\")sheet1.append_row(\"Name\",\"Email\",\"Age\")sheet1.append_row(\"Jim\",\"jim@acme.com\",45)book.finalize(to_file=\"simple.xlsx\")BenchmarksThebenchmarking testwrites\nrows with 10 cells of random string data to a single sheet workbook. The table below gives the times in seconds (lower is better)\nto write a spreadsheet with the given number of rows, and includesxlxswriterandopenpyxlfor comparison.Implementation100,000 rows1,000,000 rowsopenpyxl43.5469.1openpyxl + lxml21.1226.3xlsxwriter17.2186.2xlsxlite1.919.2LimitationsThis library is for projects which need to generate large spreadsheets, quickly, for the purposes of data exchange, and\nso it intentionally only supports a tiny subset of SpreadsheetML specification:No styling or themesOnly strings, numbers, booleans and dates are supported cell typesIf you need to do anything fancier then take a look atxlxswriterandopenpyxl.DevelopmentTo run all tests:py.test xlsxlite -s"} +{"package": "xlsxmetadata", "pacakge-description": "# xlsxmetadataReally lightweight lib for peeking into xlsx column/row size before you try to open the file with something else### setup```pip install xlsxmetadata```### reading from file...```pythonfrom xlsxmetadata.metadata import get_dimensions, get_sheet_namesmy_big_file = '/path/to/my/real_big_file.xlsx'sheet_names = get_sheet_names(my_big_file)print(sheet_names)>>> {'test_sheet': 1}dimensions = get_dimensions('/path/to/my/real_big_workbook.xlsx', 'test_sheet')print(dimensions['end_column'])>>> 16834print(dimensions['end_row'])>>> 1200000```### reading from flask form...```pythonfrom io import BytesIOfrom xlsxmetadata.metadata import get_dimensions, get_sheet_namesmy_big_file = request.files.get('my_big_file')sheet_names = get_sheet_names(BytesIO(my_big_file.read()))print(sheet_names)>>> {'test_sheet': 1}# you will probably have to reset the read-headmy_big_file.seek(0)dimensions = get_dimensions(BytesIO(my_big_file.read()), 'test_sheet')print(dimensions['end_column'])>>> 16834print(dimensions['end_row'])>>> 1200000```This information is stored as metadata in the first few bytes of `.xlsx` files. For some reason no other libraries (xlrd, openpyxl) seem to give the users access to this data directly."} +{"package": "xlsxopera", "pacakge-description": "xlsxoperaWorking on xlsx (Microsoft Excel) files. Convert to list, dict, get headers, cell values, positions and more.Developed by voidayan (c) 2022InstallInstall package from pip:pip3 install xlsxoperaNote: Required packages is openpyxlHow to workCreate an objectfromxlsxoperaimportNotebook# Load file to operate and sheet namenotebook=Notebook(\"file-to-path.xlsx\",\"sheet_name\")# Or load file to operate without sheet name. Default will be active spreadsheet.notebook=Notebook(\"file-to-path.xlsx\")Get rows in list of lists:# Get all rows (from 1 to last)rows_in_spreadsheet=notebook.list_rows()# Get rows (for e.g, from 9 to 13)rows_in_spreadsheet=notebook.list_rows(start=9,end=13)"} +{"package": "xlsx-parser", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx-provider-plugin", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlsx-ptable", "pacakge-description": "xlsx_ptable python\u5305\u4ecb\u7ecdxlsx_ptable Python Package\u662f\u4e00\u4e2a\u57fa\u4e8e\u7528\u6237log\u6587\u4ef6\uff0c\u5e76\u6839\u636e\u914d\u7f6e\u6587\u4ef6\u751f\u6210excel\u8868\u683c\u7684python\u5e93\u3002\u5b83\u53ef\u4ee5\u5e2e\u52a9\u4f60\u751f\u6210\u4f18\u96c5\u7684Excel\u8868\u683c\u3002\u5b89\u88c5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5My Python Package\uff1apython-mpipinstallxlsx_ptable\u7528\u6cd5\u4ee5\u4e0b\u662f\u5982\u4f55\u4f7f\u7528My Python Package\u7684\u4e00\u4e9b\u57fa\u672c\u793a\u4f8b\uff1a\u5047\u8bbe\u7528\u6237user_log.txt\u6587\u4ef6\u4e3a:%tab1: (X1@1), (X2@a), (Y@sample y1), (Z@sample z1)\n.............\n%tab1: (X1@2), (X2@), (Y@sample y2), (Z@sample z2)\n.............\n%tab1: (X1@3), (Z@sample z3)\n%tab1: (X1@4), (X2@c), (Y@sample y3), (Z@sample z4)\n%tab1: (X1@4), (X2@d), (Y@sample y4),\n%tab1: (X1@5), (X2@e), (Y@sample y5), (Z@sample 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\u8bb0\u5f55;Sample\u66f4\u591asample\uff0c\u8bf7\u8bbf\u95eexlsx_ptable\u3002\u8d21\u732e\u6b22\u8fce\u4efb\u4f55\u5f62\u5f0f\u7684\u8d21\u732e\uff01\u8bf7\u9605\u8bfb\u6211\u4eec\u7684\u8d21\u732e\u6307\u5357\u4e86\u89e3\u5982\u4f55\u5f00\u59cb\u3002\u8bb8\u53ef\u6839\u636eMIT\u8bb8\u53ef\u8bc1\u53d1\u5e03\u3002\u95ee\u9898\u548c\u5efa\u8bae\u5982\u679c\u4f60\u6709\u4efb\u4f55\u95ee\u9898\u6216\u5efa\u8bae\uff0c\u8bf7\u901a\u8fc7\u90ae\u7bb1gu.peng@intelllif.com\u8054\u7cfb\u6216\u8005\n\u8bf7\u5728\u6b64\u63d0\u51faIssue\u3002"} +{"package": "xlsxq", "pacakge-description": "xlsxqxlsxq is a lightweight and flexible command-line .xlsx processor.UsageThis is a beta version and specifications are subject to change.# Show help message and exit.xlsxq-h# List worksheets.xlsxqsheetlist--infileinfile.xlsx--outputjson# Show range values.xlsxqrangeshow--infileinfile.xlsx--sheet'Sheet1'--range'A1:B3'--outputjson# Show range values in tab-delimited format.xlsxqrangeshow--infileinfile.xlsx--sheet'Sheet1'--range'A1:B3'--outputtsvRequirementsPython 3.8+Installationpipinstall-UxlsxqTODOWrite docs"} +{"package": "xlsxr", "pacakge-description": "xlsx-readerPython3 library optimised for reading very large Excel XLSX files, including those with hundreds of columns as well as rows.Simple examplefrom xlsxr import Workbook\n\nworkbook = Workbook(filename=\"myworkbook.xlsx\", convert_values=True)\n\nfor sheet in workbook.sheets:\n print(\"Sheet \", sheet.name)\n for row in sheet.rows:\n print(row)ConversionsBy default, everything is a string, and all dates and datetimes will appear in ISO 8601 format (YYYY-mm-dd or YYYY-mm-ddTHH:MM:SS). If you supply the optionconvert_valuesto the Worksheet constructor, the library will convert numbers to ints or floats, and dates to datetime.datetime or datetime.date objects. There is no attempt to handle standalone times.Empty cells appear as the empty string ''.xlsxr.workbook.Workbook classConstructorThe xlsxr.Workbook class constructor takes the following keyword arguments:ArgumentDescriptionfilenamePath to an Excel file on the local filesystem.streamA file-like object (byte stream)urlThe URL of a remote Excel fileconvert_valuesIf True, convert numbers and dates from strings to Python values (default is False)fill_mergedIf True, repeat values to fill merged areas (default is False)You may specify only one offilename,stream,orurl.PropertiesPropertyDescriptionsheetsA list of xlsxr.sheet.Sheet objectsstylesA list of xlsxr.style.Style objectsxlsxr.sheet.Sheet classPropertiesProperty | Description\nworkbook | The parent Workbook objet\nname | The name of the sheet\nsheet_id | The internal identifier of the sheet\nstate | The state of the sheet (normally 'visible' or 'hidden')\nrelation_id | ??\ncols | A list of metadata for each column.\nrows | A list of the data rows in the sheet (parsed on demand).\nmerges | A list of merges in the sheet (parsed on demand).Each row is a list of scalar values. The will all be strings or None unless you specified theconvert_valuesoption for the Workbook.Merges appear as strings defining ranges, e.g. \"A1:C3\".ColumnsColumns are represented as dict objects with the following properties:KeyDescriptioncollapsedTrue if the column is collapsed.hiddenTrue if the column is hiddenmin??max??styleA key into thestylesproperty of the workbook.xlsxr.style.Style classPropertiesPropertyDescriptionnumber_formats??cell_style_formats??cell_formats??cell_styles??LicenseThis is free and unencumbered software released into the public domain. See UNLICENSE.md for details."} +{"package": "xlsxreader", "pacakge-description": "PyPi module that reads .xlsx files\nreturns a delimted python tempfile of worksheet in positon 1 in a given .xlsx workbook"} +{"package": "xlsxreporter", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx-split", "pacakge-description": "xlsx-splitCreate new file for every row in excel sheet, with support of header and footer replication.Installpip install xlsx-splitInstalled Commandsxlsx-splitCommand HelpsE:\\xlsx-split>xlsx-split --help\n Usage: xlsx-split [OPTIONS] WORKBOOK\n\n Options:\n -h, --header TEXT Header row number list.\n -f, --footer TEXT Footer row number list.\n -c, --cols TEXT Column number list.\n -r, --rows TEXT Content row number list.\n -t, --test TEXT Conditions that a good row must matchs. Format\n like COL_LETTER:REGEX, e.g. A:\\d+ means the\n value of A column must be an Integer.\n -s, --sheet TEXT Sheet name. Default to Current Active Sheet\n -w, --workspace TEXT Where new files saved. Default to\n \"{FILENAME_ROOT}\"\n -p, --filename-pattern TEXT Default to\n \"{FILENAME_ROOT}-{ROW}.{FILENAME_EXT}\"\n --help Show this message and exit.Noticeheader/footer/rows obeys ROWS-RULE.cols obeys COLS-RULE.test obeys TEST-RULE\u3002filename-pattern obeys FILENAME-RULE\u3002ROWS-RULE1 == [1]1,2,3 == [1,2,3]1-3 == [1,2,3]1-3,5 == [1,2,3,5]3- == [3,4,5,6....] # From the third row to the sheet.max_rowsCOLS-RULEA == [1]A,B,C == [1,2,3]A-C == [1,2,3]A-C,E == [1,2,3,5]C- == [3,4,5,6....] # From column C to the sheet.max_colsTEST-RULECan provide multiple tests.The final result is the result of LOGIC AND of all tests result.Test format: Column:TestRegex, e.g. A:\\d+ means the Column A must contain digits.FILENAME-RULEfilename-pattern is a python string format template.Available variablesFILEPATH Source file's full path, e.g. c:\\a\\b.xlsxDIRNAME Source file's direct folder path, e.g. c:\\aFILENAME Source file's filename, e.g. b.xlsxFILENAME_ROOT Source file's filename without ext, e.g. bFILENAME_EXT Source file's file ext, e.g. .xlsxROW Index of current row\uff0c\u59821,2,3...A..Z,AA... The value of the cell [ROW, COLUMN]. A or Z or ZZ is the column.Releases0.1.2Fix parse_rows & parse_cols problem.Document changes.0.1.1Document changes.0.1.0First release"} +{"package": "xlsx-streaming", "pacakge-description": "xlsx_streaminglibrary lets you stream data from your database to an xlsx document. The xlsx document can hence be streamed over HTTP without the need to store it in memory on the server. Database queries are made by batch, making it safe to export even very large tables.The full documentation can be found onreadthedocs.Bug reports, patches and suggestions welcome! Just open anissueor send apull request.Running the testsAs simple as:python setup.py test"} +{"package": "xlsxstyler", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx-template", "pacakge-description": "No description available on PyPI."} +{"package": "xlsxtmpl", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlsxToCsv", "pacakge-description": "excelToCSVThexlsxToCsvpackage contains the ability to convert .xlsx file to a .csv file that is more consumable by many other packages/programs/scripts.The source code for this package is available athttps://github.com/willmichel81/excelToCSV.The importable name of the package is excelToCSVImport into your code>>> from excelToCSV import excelToCSVTest to make sure package is connecting>>> pip install xlsxToCsv>>> python>>> from excelToCSV import excelToCSV>>> test = excelToCSV(C:/complete/path/to/file/example.txt)>>> print(test)If you have succesfully installed xlsxToCsv then you should get the following results from the above code\"('C:/complete/path/to/file/', '.txt')\"Short SummeryTakes user specified range data (ex. A1:A16) data from sheet(s)(ex. \"MAIN\") in side of .xlsx and then converts data to json dict and/or csv."} +{"package": "xlsx-to-dict", "pacakge-description": "XLSX to DICTConvert xlsx file to dict python object"} +{"package": "xlsx_to_handontable", "pacakge-description": "# xlsx_to_handontablexlsx to handontableconfiguration+sample# INSTALLpip install xlsx_to_handontable# USAGEfrom xlsx_to_handontable import xlsx_to_configs_samples\nfrom yaml_dump import yaml_dump\np = \u20180.xlsx\u2019\nconfigs, samples = xlsx_to_configs_samples(p)\nprint(yaml_dump(configs))\nprint(\u2018-\u2019 * 20)\nprint(yaml_dump(samples))# History## 0.1.0 (2017-01-13)\n- First release on PyPI."} +{"package": "xlsx-to-json", "pacakge-description": "No description available on PyPI."} +{"package": "xlsxToJsonTranslate", "pacakge-description": "xlsxToJsonTranslateSimple tool to convert xlsx file to a json object. Build for i18n angular appsUsagexlsxToJsonTranslate-i-o-l-kFormat of xlsx fileInformationKeyfrenViolation - Ajoutrgpd.violation.journey.add.titleAjout d'une violation de donn\u00e9es personnellesAdding a violation of personal dataViolation - Ajoutrgpd.violation.journey.add.step-date.still-aliveLa violation est-elle toujours en cours ?The violation is it ongoing?Violation - Ajoutrgpd.violation.journey.add.step-date.determined-periodLa violation s'est \u00e9tendue sur une p\u00e9riode d\u00e9termin\u00e9eThe violation was extended over a fixed periodViolation - Ajoutrgpd.violation.journey.add.step-date.date-start-violationDate approximative de la violationApproximate date of the violationViolation - Ajoutrgpd.violation.journey.add.step-date.date-know-violationDate et heure de prise de connaissance de la violationDate and time of becoming aware of the breachViolation - Ajoutrgpd.violation.journey.add.step-date.comments-datesCommentaires sur les datesComments on datesViolation - Ajoutrgpd.violation.journey.add.step-date.discovery-circumstancesDans quelles circonstances avez-vous d\u00e9couvert la violation ?Under what circumstances did you discover the violation?Output formatfr.json{\"rgpd\":{\"violation\":{\"journey\":{\"add\":{\"title\":\"Ajout d'une violation de donn\u00e9es personnelles\",\"step-date\":{\"still-alive\":\"La violation est-elle toujours en cours ?\",\"determined-period\":\"La violation s'est \u00e9tendue sur une p\u00e9riode d\u00e9termin\u00e9e\",\"date-start-violation\":\"Date approximative de la violation\",\"date-know-violation\":\"Date et heure de prise de connaissance de la violation\",\"comments-dates\":\"Commentaires sur les dates\",\"discovery-circumstances\":\"Dans quelles circonstances avez-vous d\u00e9couvert la violation ?\"}}}}}}en.json{\"rgpd\":{\"violation\":{\"journey\":{\"add\":{\"title\":\"Adding a violation of personal data\",\"step-date\":{\"still-alive\":\"The violation is it ongoing?\",\"determined-period\":\"The violation was extended over a fixed period\",\"date-start-violation\":\"Approximate date of the violation\",\"date-know-violation\":\"Date and time of becoming aware of the breach\",\"comments-dates\":\"Comments on dates\",\"discovery-circumstances\":\"Under what circumstances did you discover the violation?\"}}}}}}"} +{"package": "xlsxtools", "pacakge-description": "xlsxtoolsUtility functions for writing and manipulating Excel files:write_dataframe_to_excel() : write a Pandas DataFrame to an Excel file, optionally calling\nauto_size_excel_column_widths() and filter_and_freeze_excel()auto_size_excel_column_widths() : Reformat an Excel file, adjusting the column widths to fit their contentsfilter_and_freeze_excel() : Clean up an Excel file by setting a filter on the first row,\nsplitting & freezing the panesReleases1.0, 2021-10-26Initial releaseLicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or\ndistribute this software, either in source code form or as a compiled\nbinary, for any purpose, commercial or non-commercial, and by any\nmeans."} +{"package": "xlsxtpl", "pacakge-description": "Usexltpl.xlsxtplA python module to generate xlsx files from a xlsx template.How it worksxlsxtpl uses openpyxl to read and write .xlsx files, uses jinja2 as its template engine.When xlsxtpl reads a .xlsx file, it creates a tree for each worksheet.Then, it translates the tree to a jinja2 template with custom tags.When the template is rendered, jinja2 extensions of cumtom tags call corresponding tree nodes to write the .xlsx file.Syntaxxlsxtpl uses jinja2 as its template engine, follows thesyntax of jinja2 template.Each worksheet is translated to a jinja2 template with custom tags....\n...\n{% row 45 %}\n{% cell 46 %}{% endcell %}\n{% cell 47 %}{% endcell %}\n{% cell 48 %}{{address}} {%xv v%}{% endcell %}\n{% cell 49 %}{% endcell %}\n{% cell 50 %}{% endcell %}\n{% cell 51 %}{% endcell %}\n{% cell 52 %}{% endcell %}\n{% cell 53 %}{% endcell %}\n{% row 54 %}\n{% cell 55 %}{% endcell %}\n{% cell 56 %}{% sec 0 %}{{name}}{% endsec %}{% sec 1 %}{{address}}{% endsec %}{% endcell %}\n...\n...\n{% for item in items %}\n{% row 64 %}\n{% cell 65 %}{% endcell %}\n{% cell 66 %}{% endcell %}\n{% cell 67 %}{% endcell %}\n{% cell 68 %}{% endcell %}\n{% cell 69 %}{% endcell %}\n{% cell 70 %}{% endcell %}\n{% cell 71 %}{% endcell %}\n{% cell 72 %}{% endcell %}\n{% endfor %}\n...\n...xlsxtpl added 4 custom tags: row, cell, sec, and xv.row, cell, sec are used internally, used for row, cell and rich text.xv is used to define a variable.When a cell contains only a xv tag, this cell will be set to the type of the object returned from the variable evaluation.For example, if a cell contains only {%xv amt %}, and amt is a number, then this cell will be set to Number type, displaying with the style set on the cell.If there is another tag, it is equivalent to {{amt}}, will be converted to a string.InstalltionpipinstallxlsxtplHow to useSeeexamples.NotesRich textOpenpyxl does not preserve the rich text it read.\nA temporary workaround for rich text is provided inthis repo(2.6).\nFor now, xlsxtpl uses this repo to support rich text reading and writing."} +{"package": "xlsxutility", "pacakge-description": "Xlsx filetype utility functionsautofit_columns: Autofit all columns from dataframe written to xlsxfile with xlsxwriterdefautofit_columns(dataframe,worksheet,padding=1.1,index=True):\"\"\":param dataframe: Base dataframe written to xlsx workbook:param worksheet: Sheet in xlsx workbook to be formatted:param padding: Optional, padding amount:param index: Optional, Index true/false in dataframe. Defaults true, use false for non-indexed dataframe outputs.:return: formatted worksheet\"\"\"Example Callimportpandasaspdimportnumpyasnpfromxlsxutilityimportautofit_columnsdf=pd.DataFrame(np.array([[1,2,3],[4,5,6],[7,8,9]]),columns=['a','b','c'])writer=pd.excelwriter(\"some_path\",engine='xlsxwriter')df.to_excel(writer)autofit_columns(df,writer.sheets['Sheet1'],index=False)align_cells: Horizontally or vertically align all cells in given dataframe.Note - If using in conjunction with autofit_columns this must be called first, or the default width (1) will overwrite.defalign_cells(dataframe,workbook,worksheet,align='center'):\"\"\":param dataframe: Reference Dataset, Pandas Dataframe:type dataframe: Pandas Dataframe:param workbook: Xlsxwriter workbook:param worksheet: Xlsxwriter worksheet (must be within workbook):param align (optional):Defaults to horizontal center. Alignment types Horizontal: (left / center/ right / fill / justify / center_across / distributed) or Vertical: (top, vcenter, bottom, vjustify, vdistributed)\"\"\"Example Callimportpandasaspdimportnumpyasnpfromxlsxutilityimportalign_cellsdf=pd.DataFrame(np.array([[1,2,3],[4,5,6],[7,8,9]]),columns=['a','b','c'])writer=pd.excelwriter(\"some_path\",sheet_name='Example',engine='xlsxwriter')df.to_excel(writer)align_cells(df,writer,writer.sheets['Example'],'center')"} +{"package": "xlsxutils", "pacakge-description": "No description available on PyPI."} +{"package": "xlsx-validator", "pacakge-description": "No description available on PyPI."} +{"package": "xlsxviewer", "pacakge-description": "xlsxviewerxlsx viewer"} +{"package": "xlsxwriter-celldsl", "pacakge-description": "XlsxWriter-CellDSLWhat is this?XlsxWriter-CellDSLis a complementary Python module for the\nexcellentXlsxWriterlibrary that provides a DSL (domain specific language)\nto perform common operations in worksheets without having to specify absolute coordinates and keep track of them,\ninstead opting to use primarily relative movement of an imaginary \"cursor\" within the spreadsheet, among other things.The issue with absolute coordinatesIf you've ever written code that generates structures that have a dynamic layout in Excel, you may have noticed that, in\norder to make sure writes happen in correct cells, you have to carry data that have been used to figure out the size of\nthose structures and then sum up those size data with some offsets in order to get the coordinate that you then pass\nintowritefunction.This is really painful to do in more complex cases where many structures are present within a worksheet since you have\nto keep track of the sizes of each structure and drag this information across every module that's related to the\nworksheet.If you want to then refactor the code or move structures around, you'll have to rewrite the coordinate calculations for\nevery structure downstream, which is extremely error-prone. Moreover, if you then refactor writing some structures into\nfunctions, you will have to pass into the function some kind ofinitialcoordinates, which is information that's\nunlikely to be relevant for the structure itself. To put it simply, a structure doesn't care where it is located and\nthus, keeping track of absolute coordinates is a very error-prone and redundant activity.To put it another way, in many cases writing a structure into an Excel sheet is not a random access operation for which\nabsolute coordinates would be more appropriate for. Writes do not occur to arbitrary cells, in fact, more often than not\nwrites occur in some kind of sequential order, with known spacing and local positioning, but not necessarily known\nglobal positioning.Not only that, but even writingandreading an Excel sheet follows this principle: at any given moment the operator\ncares more about nearby cells than distant ones. Mirroring this mode of operation is what relative coordinates are best\nsuited for. This module implements a number of utilities that allow the developer to have an imaginary \"cursor\"\nplaced somewhere in the worksheet and operations occur wherever this cursor is, followed by moving the cursor with arrow\nkeys into the next position.Features and usesMoveOp: Move the cursor around using relative coordinates.AtCellOp: Perform an absolute coordinate jump if no other movement option suffices.FormatDict: Construct formats by treating them as a composition of smaller formats instead of raw dictionaries with\nrepeated key-value pairs.FormatHandler: Delegate keeping track of added formats to XlsxWriter-CellDSL and remove the need to distribute\nreferences to added formats between generating functions.SaveOp,LoadOp: Give current position a name and then jump back to it later or use it to retrieve the absolute\ncoordinates of some point of interest after the script has finished execution.StackSaveOp,StackLoadOp: A structure composed of substructures would want to take advantage ofSaveOpcapabilities without having to generate a name for it.WriteOp,MergeWriteOp,WriteRichOp: Perform common writing actions to current cell, only focusing on data, and\nthe cell format.ImposeFormatOp,OverrideFormatOp,DrawBoxBorderOp: Deferred execution of operations allows additional formatting\nto be applied to writing actions after they occur which would ordinarily require changing the arguments of the first\nwriting function call.SectionBeginOp,SectionEndOp: Errors are inevitable and though deferred execution makes debugging more difficult,\nthis needn't be the case if you annotate segments with names.AddChartOp: Add charts to the worksheet and utilize the flexibility of named ranges in an environment which does not\nallow named ranges withRefArrayOp.Exceptions provide a lot of useful information to track down the line that causes it.Several short forms of common operations improve conciseness of code.Deferred execution of operations allows taking advantage ofconstant_memorymode in XlsxWriter easily, without\nhaving to contend with write-to-stream limitations such as ensuring the writes occurs in left-to-right, top-to-bottom\norder only, thus providing the performance ofconstant_memorymode, but flexibility of regular mode.Deferred execution allows introspection into the action chain and modifying it out-of-order.Upon execution, history of operations can be saved and used in scripts further down.Avoid more bugs by preventing overwriting data over non-emtpy cells withoverwrites_okattribute.DocumentationRead the full documentationhere.Usage examplefromxlsxwriterimportWorkbook# Various operationsimportxlsxwriter_celldsl.opsasops# The entry point to the libraryfromxlsxwriter_celldslimportcell_dsl_context# A factory of objects needed for the context managerfromxlsxwriter_celldsl.utilsimportWorkbookPair# A number of basic formatsfromxlsxwriter_celldsl.formatsimportFormatsNamespaceasF# Useful functions to assist in printing sequencesfromxlsxwriter_celldsl.utilsimportrow_chain,col_chain,segmentwb=Workbook('out.xlsx')wb_pair=WorkbookPair.from_wb(wb)ws_triplet=wb_pair.add_worksheet(\"TestSheet1\")withcell_dsl_context(ws_triplet)asE:# ExecutorHelper (as E here) is a special preprocessor object that keeps track of operations# to be done and performs some preprocessing on them# See the docs for `ExecutorHelper.commit`E.commit([# xlsxwriter_celldsl.ops exports both command classes and basic instances of those classes.# ExecutorHelper.commit uses instances.# All commands are immutable objects, however, they are cached and reused# so few new instances are created.ops.Write.with_data(\"Hello, world, at A1, using left aligned Liberation Sans 10 (default font)!\").with_format(F.default_font),ops.Move.c(3),# Move three columns to the right\"Wow, short form of ops.Write.with_data('this string'), at D1, three columns away from A1!\",11,# Short form of ops.Move, refer to ExecutorHelper.commit to see how this worksF.default_font_bold,\"Wow, I'm at B3 now, written in bold\",2,[[[\"However deeply I'm nested, I will be reached anyway, at B4\"]]],6,# Rich string short form, several formats within a single text cellF.default_font,\"A single cell, but two parts, first half normal \",F.default_font_bold,\"but second half bold! For as long as we stay at C4...\",# Adding a format to the end will allow to set the cell format, here enabling the text wrap.F.wrapped,6,\"Oops, D4 now\",# Saving current position as \"see you later\"ops.Save.at(\"see you later\"),# Absolute coordinate jumpops.AtCell.r(49).c(1),\"Jumping all the way to B50\",# Jumping to some previously saved positionops.Load.at(\"see you later\"),6,\"We've gone back to D4, moved right and now it's E4\",3333,ops.Save.at(\"Bottom Right Corner\"),# Reversing movement back in timeops.BacktrackCell.rewind(1),# Drawing a box using bordersops.DrawBoxBorder.bottom_right(\"Bottom Right Corner\"),33,# Two formats may be \"merged\" together using OR operator# In this case, we add \"wrapped\" trait to default fontF.default_font|F.wrapped,\"And now, we're inside a 5x5 box, starting at E4, but this is G6.\"\"Even though this operation precedes the next one, the next one affect this cell\"\", thus we are inside a smaller box that only encloses G6.\",ops.DrawBoxBorder,ops.AtCell.r(10).c(0),# Sections allow you to document your code segments by giving them names# and also assist in debugging as you will be shown the name stack# up until the line that causes the exceptionops.SectionBegin.with_name(\"Multiplication table\"),[# col_chain / row_chain write data sequentially from an iterable# row_chain prints it in a row, but the actual position of the cursor doesn't change!\"A sequence from 1 to 9, horizontally\",6,row_chain([f\"*{v}\"forvinrange(1,10)]),1,# col_chain prints it in a column\"A sequence from 1 to 9, vertically\",2,col_chain([f\"{v}*\"forvinrange(1,10)]),6,# Nothing stops you from chaining chainscol_chain([row_chain([ops.Write.with_data(a*b)forbinrange(1,10)])forainrange(1,10)]),# Every SectionBegin must be matched with a SectionEndops.SectionEnd,# ...however you can skip that by using utils.segment to implicitly add SectionBegin and SectionEnd to# a piece of codesegment(\"Empty segment\",[])]])Changelog0.6.0Exceptions coming from XlsxWriter are now also captured and provide debug info.Deprecatedtop_leftandright_bottommethods in Range-d commands, now they usewith_top_leftandwith_right_bottomto be consistent with other similar methods.AddedSetPrintAreacommand.Moved exceptions toerrorssubmodule.cell_dsl_contextis now a proper classCellDSLContext.SectionBeginOpis no longer affected by coordinates of where they occur, thus preventing unexpected behavior where\nan inner section started sooner than the outer section because the inner section started at some previous coordinate.WriteRichcan now accept a cell format. The short form also supports it by placing the cell format as the last\nfragment in the chain. This removes the restriction of following a format with a format or string since now not doing\nso will merely mark the end of the short form.Added an alias forSetColWidth--SetColumnWidth, to make it consistent with the other ops.WriteRichOpandImposeFormatOp/OverrideFormatOpare now implemented: they affect the cell format of the op.0.5.0Charts can now be combined.A suite of WriteOp variations for writing data with known types likeWriteNumberandWriteDatetime.BREAKING CHANGE: Operation instances and classes have been separated: the classes are now inops.classesmodule.\nRegular instances are still importable fromops, so unless your code creates its own instances of operations, you\nneedn't change anything.0.4.0AddAddConditionalFormatOpandAddImageOpWrite the format section in the docsNew default format traits inFormatsNamespace0.3.0Addoverwrites_okDocs!Removed dummy_cell_dsl_contextComplete overhaul toAddChartOp, removing the string function name interface0.2.0AddSectionBeginOpandSectionEndOpImprovement to error reporting: now they provide some contextRemove format data from repr of commandsSeparateCellDSLErrorintoMovementCellDSLErrorandExecutionCellDSLErrorRaise exceptions on various error that may occur from XlsxWriter side (use proper exceptions instead of return codes)"} +{"package": "xlsxwriter-tables", "pacakge-description": "xlsxwriter-tablesEasily export nested data to ExcelThis class is intended to be used withXlsxWriter. It serves several purposes:Co-location of column info and data-generation logicEasily specify deeply nested data as the source for column dataReference column headers dynamically in column formulasTheexample.pyfile shows basic usage;excel_table.pyis also thoroughly documented. I intend to document more examples of usage in the future.APISample data``` py\nserialized_data = [\n {\n 'alpha': {\n 'oscar': True,\n 'papa': {\n 'romeo': State(\n name='Alabama', \n statehood_granted=date(1819, 12, 14),\n symbols={\n 'bird': 'Yellowhammer',\n 'flower': 'Camellia',\n },\n ),\n 'sierra': State(\n name='Georgia', \n statehood_granted=date(1788, 1, 2),\n symbols={\n 'bird': 'Brown Thrasher',\n 'flower': 'Cherokee Rose',\n },\n ),\n }\n },\n 'bravo': 22,\n 'charlie': 4,\n },\n {\n 'alpha': {\n 'oscar': False,\n 'papa': {\n 'romeo': State(\n name='Minnesota', \n statehood_granted=date(1858, 5, 11),\n symbols={\n 'bird': 'Common Loon',\n 'flower': 'Ladys Slipper',\n },\n ),\n 'sierra': State(\n name='Wisconsin', \n statehood_granted=date(1848, 5, 29),\n symbols={\n 'bird': 'Robin',\n 'flower': 'Wood Violet',\n },\n ),\n }\n },\n 'bravo': 32,\n 'charlie': 30,\n },\n {\n 'alpha': {\n 'oscar': None,\n 'papa': {\n 'romeo': State(\n name='Maryland', \n statehood_granted=date(1776, 7, 4),\n symbols={\n 'bird': 'Baltimore Oriole',\n 'flower': 'Black-Eyed Susan',\n },\n ),\n 'sierra': State(\n name='Virginia', \n statehood_granted=date(1788, 6, 25),\n symbols={\n 'bird': 'Cardinal',\n 'flower': 'Flowering Dogwood',\n },\n ),\n }\n },\n 'bravo': 7,\n 'charlie': 10,\n },\n]\n```Given the sample data above, we can generate an Excel table for export using XlsxWriter with the following code:excel_table=ExcelTable(data=serialized_data,columns=dict(oscar='alpha.oscar',state_name='alpha.papa.romeo.name',statehood_granted='alpha.papa.romeo.statehood_granted',state_bird='alpha.papa.romeo.symbols.bird',state_flower='alpha.papa.romeo.symbols.flower',other_states_bird='alpha.papa.sierra.symbols.bird',bravo=None,charlie=None,average_bravo_charlie=dict(header='Avg of Bravo/Charlie',data_accessor=lambdaitem:None,formula='=AVERAGE({bravo},{charlie})',),))Co-location of Column and Data Accessor CodeOne advantage to this approach is that everything pertaining to a single column isin one place! The alternative approach force columns to be specified in one place, and data generated in another. This means that to make a change to a column or columns, you have to change it in multiple places. As the size of your tables grow, it becomes more difficult to maintain.With this style, columns are defined with the logic used to generate the data in each rowfor that column. If columns need to be reordered, headers renamed, or additional info updated, there is only one place that these changes need to be made.EasilyFlattenNested Data Into RowThe next advantage is that it provides a concise, readable style for accessing nested data by chaining properties together (dot-syntax is the default, but custom separators can be specified). This makes it much easier to spot inconsistencies across multiple columns, and identify why a cell is showing up blank or generating an AttributeError.Unbreakable Formula ReferencesWith XlsxWriter, column formulas can be defined with references to other columns in the table (formula='=SUM([@Qty] * [@Price]). Hard-coding column headers is a bad idea, however, as this is subject to break if the referenced column header changes. In this case, it can be difficult to notice that a formula broke, especially in large Excel tables.xlsxwriter-tablessolves this by using the columns' keys to generate dynamic references to each column in column formulas. This approach will fail at runtime if the keys change, alerting you that a change needs to be made.Nesting Classes and DictsThe class is flexible enough to handle both class instances and dicts. Classes can be nested inside of dicts (romeois an instance ofStatein the example). Likewise, dicts can be properties of class instances (symbols, adict, is a property of eachStateinstance). The same syntax is used to access nested values of both classes and dicts.Field Separator SyntaxThe default field separator is the dot (.), but custom characters can be specified. For instance, to assimilate Django's ORM-style \"dunder\" syntax for querying fields, useseparator='__'. Columns would then use this like so:...separator='__',columns=dict(oscar='alpha__oscar',state_name='alpha__papa__romeo__name',...Specifyingcolumn=NoneIn the simplest cases where the column key is also the top-level attribute that is desired, and the column key is the desired column header, set the column's value toNone.For example, these column definitions will generate the header, 'Bravo', and access data on each item usingitem.bravo(class) oritem['bravo'](dict):bravo=None,bravo={},bravo=(),AttributeErrors and KeyErrorsBy default, if attributes or keys cannot be found, they fail gracefully - meaning they return the valueNone, and cell values for those fields are blank. This is useful for cases where the shape of each itemis not expectedto conform perfectly to the column schema.For debugging purposes, or in other cases where the datais expectedto be uniform, you can setraise_attribute_errors=True:excel_table=ExcelTable(...raise_attribute_errors=True,columns=dict(alpha_quebec='alpha.quebec',...))This will result in:Other ExceptionsAny other error is printed to the cell in which it occurred, to help diagnose.Column Header TextTheheaderattribute defaults to the title-cased dictionary key, unless a header is explicitly provided. For example:THISCOLUMNBECOMESTHISHEADER-------------------------------------------------------------------oscar=...,-->'Oscar'state_name=...,-->'State Name'average_bravo_charlie=dict(-->'Avg of Bravo/Charlie'header='Avg of Bravo/Charlie',...)Additional Column AttributesColumn attributes can be supplied in each column's dictionary, following XlsxWriter's docs. With the exception offormula, these attributes simply get passed through to XlsxWriter.Column FormulasFormulas can be specified per XlsxWriter's docs. To dynamically reference the calculated column header of another column in a formula, use curly braces and the column's kwarg.For instance, the following code foraverage_bravo_charlie...bravo=None,charlie=None,average_bravo_charlie=dict(...formula='=AVERAGE({bravo},{charlie})',),...will generate this column formula:'=AVERAGE([@[Bravo]], [@[Charlie]])This means that changing the header text in a referenced column willnotbreak the formula! Further, changing the column's kwargwillbreak the formula if it is not also updated. However, it will raise an error at runtime, rather than failing silently in the Excel file.Saving to ExcelTo save the data to an Excel file, use XlsxWriter'sworksheet.add_table()method as usual.The ExcelTable class automatically calculates the top, left, bottom, and right coordinates of the table based on the size of the data. These values are available inexcel_table.coordinatesas a tuple, making it easy to spread them into theadd_table()call.importxlsxwriterworkbook=xlsxwriter.Workbook('example.xlsx')worksheet=workbook.add_worksheet()excel_table=ExcelTable(...)worksheet.add_table(*excel_table.coordinates,{'columns':excel_table.columns,'data':excel_table.data,'total_row':excel_table.include_total_row,...})workbook.close()"} +{"package": "xlsx-xargs", "pacakge-description": "xlsx-xargs\u7c7b\u4f3cxargs\u547d\u4ee4\uff0c\u904d\u5386\u4f9d\u636e\u662fexcel\u8868\u5355\u4e2d\u7684\u6bcf\u4e00\u884c\u3002\u547d\u4ee4\u53c2\u6570\uff0c\u5141\u8bb8\u88abstring.format\u66ff\u6362\uff0c\u66ff\u6362\u5185\u5bb9\u4e3a\u6307\u5b9a\u5355\u5143\u683c\u503c\u3002\u547d\u4ee4\u8bf4\u660eE:\\xlsx-xargs>python xlsx_xargs.py --help\n Usage: xlsx_xargs.py [OPTIONS] [COMMANDS]...\n\n \u7c7b\u4f3cxargs\u547d\u4ee4\uff0c\u904d\u5386\u4f9d\u636e\u662fexcel\u8868\u5355\u4e2d\u7684\u6bcf\u4e00\u884c\u3002\u547d\u4ee4\u53c2\u6570\uff0c\u5141\u8bb8\u88abstring.format\u66ff\u6362\uff0c\u66ff\u6362\u5185\u5bb9\u4e3a\u6307\u5b9a\u5355\u5143\u683c\u503c\u3002\n\n \u6ce8\u610f\uff1a\n\n COMMANDS\u524d\u52a0\u4e24\u4e2a\u51cf\u53f7\uff0c\u53ef\u8868\u793a\u51cf\u53f7\u540e\u5747\u4e3aCOMMANDS\u53c2\u6570\u3002 xlsx-xargs [OPTIONS] -- [COMMANDS]...\n\n Options:\n -f, --file TEXT Excel\u6587\u4ef6\u8def\u5f84\u3002 [required]\n -s, --sheet TEXT \u8868\u5355\u9875\u540d\u79f0\u3002\u9ed8\u8ba4\u4e3a\u5f53\u524d\u9875\u3002\n -r, --rows TEXT \u6307\u5b9a\u9700\u8981\u5904\u7406\u7684\u884c\u3002\u9ed8\u8ba4\u4e3a\u6240\u6709\u884c\u3002\n -t, --test TEXT \u4f7f\u7528\u6b63\u5219\u5bf9\u884c\u8fdb\u884c\u8fc7\u6ee4\uff0c\u53ea\u5904\u7406\u5339\u914d\u7684\u884c\u3002\u5141\u8bb8\u4f7f\u7528\u591a\u4e2a\u8868\u8fbe\u5f0f\uff0c\u591a\u4e2a\u8868\u8fbe\u5f0f\u4e4b\u95f4\u6c42\u4e0e\u3002\n --help Show this message and exit.\u6ce8\u610f\u4e8b\u9879rows \u8981\u9075\u4ecerows\u89c4\u5219\u3002tests \u8981\u9075\u4ecetest\u89c4\u5219\u3002COMMANDS \u524d\u52a0--\uff0c\u53ef\u4ee5\u9632\u6b62\u53c2\u6570\u51b2\u7a81\u95ee\u9898\u3002rows\u89c4\u52191 == [1]1,2,3 == [1,2,3]1-3 == [1,2,3]1-3,5 == [1,2,3,5]3- == [3,4,5,6....] # \u4ece\u7b2c3\u884c\u5f00\u59cb\uff0c\u76f4\u5230\u6700\u540e\u4e00\u884c\u3002test\u89c4\u5219\u6bcf\u4e2atest\u90fd\u662f\u7531\uff08\u5217\u540d+\":\"+\u6b63\u5219\uff09\u7ec4\u6210\uff0c\u5982\uff08A:\\d+\uff09\u3002\u53ef\u4ee5\u7531\u591a\u4e2atest\u7ec4\u6210\u3002\u591a\u4e2atest\u6c42\u201c\u4e0e\u201d\u4e3a\u6700\u540e\u7ed3\u679c\u3002"} +{"package": "xltable", "pacakge-description": "Documentation here:https://xltable.readthedocs.org/en/latestxltable is an API for writing tabular data and charts to Excel. It is not a replacement for other Excel writing\npackages such as xlsxwriter, xlwt or pywin32. Instead it uses those packages as a back end to write the Excel files\n(or to write to Excel directly in the case of pywin32) and provides a higer level abstraction that allows the\nprogrammer to deal with tables of data rather than worry about writing individual cells.The main feature that makes xltable more useful than just writing the Excel files directly is that it can\nhandle tables with formulas that relate to cells in the workbook without having to know in advance where\nthose tables will be placed on a worksheet. Only when all the tables have been added to the workbook and\nthe workbook is being written are formulas resolved to their final cell addresses.Tables of data are constructed using pandas.DataFrame objects. These can contain formulas relating to columns or\ncells in the same table or other tables in the same workbook.As well as writing tables to Excel, xltable can also write charts using tables as source data.Integrating xltable into Excel can be done using PyXLL,https://www.pyxll.com.\nPyXLL embeds a Python interpreter within Excel and makes it possible to use Excel as a front end user interface\nto Python code. For example, you could configure a custom ribbon control for users to run Python reports and have\nthe results written back to Excel.Example:from xltable import *\nimport pandas as pa\n\n# create a dataframe with three columns where the last is the sum of the first two\ndataframe = pa.DataFrame({\n \"col_1\": [1, 2, 3],\n \"col_2\": [4, 5, 6],\n \"col_3\": Cell(\"col_1\") + Cell(\"col_2\"),\n}, columns=[\"col_1\", \"col_2\", \"col_3\"])\n\n# create the named xlwriter Table instance\ntable = Table(\"table\", dataframe)\n\n# create the Workbook and Worksheet objects and add table to the sheet\nsheet = Worksheet(\"Sheet1\")\nsheet.add_table(table)\n\nworkbook = Workbook(\"example.xlsx\")\nworkbook.add_sheet(sheet)\n\n# write the workbook to the file (requires xlsxwriter)\nworkbook.to_xlsx()"} +{"package": "xl-tables", "pacakge-description": "Use descriptors to get and set Excel table values.Examplesimportxl_tablesasxlimportdatetimeclassMyTable(xl.Table):label_first=xl.Constant('First Name',(1,1))# Constants initialize their value on Table creationfirst_name=xl.Cell((1,2))label_last=xl.Constant('Last Name',(2,1))last_name=xl.Cell(2,2)label_now=xl.Constant('Now',(3,1))now=xl.DateTime(3,2)label_today=xl.Constant('Today',(4,1))today=xl.Date(4,2)label_time=xl.Constant('Time',(5,1))time=xl.Time(5,2)header=xl.Constant(['Data 1','Data 2','Data 3'],rows=7,row_length=3)array_item=xl.RangeItem('A8:C10')# Contiguous Range is preferablearray=xl.Range('A8:C10')# array_item = xl.RowItem(8, 9, 10, row_length=3)# array = xl.Row(8, 9, 10, row_length=3)tbl=MyTable()tbl.first_name='John'tbl.last_name='Doe'tbl.now=datetime.datetime.now()tbl.today=datetime.datetime.today()tbl.time=datetime.time(20,1,1)# datetime.datetime.now().time()tbl.array=[(1,2,3),(4,5,6),(7,8,9)]# Make a border around the cells in the tabletbl.array_item.Borders(xl.xlEdgeTop).LineStyle=xl.xlDoubletext='{lbl1}={opt1}\\n'\\'{lbl2}={opt2}\\n'\\'{lbl3}={now}\\n'\\'{lbl4}={today}\\n'\\'{lbl5}={time}\\n'\\'\\n'\\'{header}\\n'\\'{arr}\\n'.format(lbl1=tbl.label_first,opt1=tbl.first_name,lbl2=tbl.label_last,opt2=tbl.last_name,lbl3=tbl.label_now,now=tbl.now,lbl4=tbl.label_today,today=tbl.today,lbl5=tbl.label_time,time=tbl.time,header=tbl.get_row_text(tbl.header,delimiter=', '),arr=tbl.get_table_text(tbl.array,delimiter=', '))withopen('person_text.txt','w')asf:f.write(text)print('===== Manual Text =====')print(text)print('===== End =====')# Short function provided for thistxt=tbl.get_table_text(tbl.array,header=tbl.header,head={tbl.label_first:tbl.first_name,tbl.label_last:tbl.last_name,tbl.label_now:tbl.now,tbl.label_today:tbl.today,tbl.label_time:tbl.time})print('===== Get Table Text =====')print(txt)print('===== End =====')tbl.save('person.txt')# 'person.txt' or '.tsv' will save every cell separated by '\\t'tbl.save('person.csv')# 'person.csv' will save every cell separated by ','tbl.save('person.xlsx')"} +{"package": "xl-tensorflow", "pacakge-description": "Tensorflow(>=2.1.0) models and some tools for training and deploying"} +{"package": "xltmpl", "pacakge-description": "\u529f\u80fd\u672c\u6a21\u5757\u57fa\u4e8eopenpyxl\uff0c\u901a\u8fc7\u81ea\u5b9a\u4e49xls/xlsx\u6a21\u677f\uff0c\u5411\u6a21\u677f\u5199\u5165\u6570\u636e\uff0c\u4ece\u800c\u4fdd\u7559\u8868\u683c\u6837\u5f0f\uff0c\u9002\u5408\u56fa\u5b9a\u683c\u5f0f\u62a5\u8868\u5bfc\u51fa\u3002\u5b89\u88c5pip install xltmpl==1.0.6\u5feb\u901f\u5f00\u59cb\u7b2c\u4e00\u6b65\u3001\u5047\u8bbe\u4e00\u4e2axls/xlsx\u6a21\u677f\u7684Sheet1\u8bbe\u7f6e\u5982\u4e0b\uff1aABCDE1nameagesex2{{}}{{}}{{}}3\u7b2c\u4e00\u884c\u662f\u8868\u5934\u7b2c\u4e8c\u884c\u5168\u90e8\u586b\u5145{{}}\uff0c\u7136\u540e\u8bbe\u7f6e{{}}\u5355\u5143\u683c\u7684\u683c\u5f0f(\u5982\u5b57\u4f53\u3001\u5b57\u53f7\u3001\u6587\u672c\u989c\u8272\u3001\u8fb9\u6846\u3001\u80cc\u666f\u7b49\u7b49)\uff0c\u540e\u9762\u7684\u5355\u5143\u683c\u6837\u5f0f\u90fd\u4f7f\u7528\u8be5\u884c\u7684\u6837\u5f0f\u7b2c\u4e8c\u6b65\uff1a\u5f80Excel\u5199\u5165\u6570\u636e\uff0c\u53ef\u4ee5\u5f88\u65b9\u4fbf\u7684\u5199\u5165\u591a\u79cd\u6570\u636e\u7c7b\u578b# -*- coding: utf-8 -*-\"\"\"\u6f14\u793axltmpl\u6309\u6a21\u677f\u5bfc\u51fa\u6570\u636e\"\"\"importpandasaspdfromxltmpl.xltmplimportXlTemplatexlpath_tmpl='xlsx_template.xlsx'# xls format is allowedxlpath_save='save.xlsx'# \u6307\u5b9a\u6a21\u677f\u4f4d\u7f6e\uff0c\u4ee5\u53ca\u5199\u5165\u6570\u636e\u540e\u7684\u65b0\u8868\u4f4d\u7f6e\uff0c\u7136\u540e\u5411Excel\u6a21\u677f\u5199\u5165\u6570\u636ewithXlTemplate(tmpl_path=xlpath_tmpl,xlpath_save=xlpath_save,place_holder='{{}}')astmpl:# \u5f80Sheet1\u6dfb\u52a0\u4e00\u884c\u6570\u636erow=['apple','orange','banana']tmpl.append_row('Sheet1',row)# \u5f80\u7b2c\u4e00\u4e2aSheet\u5929\u673a\u591a\u884c\u6570\u636erows=[['Jason','M',23],['Rose','F',19]]tmpl.append_rows(1,rows)# \u5f80\u7b2c\u4e8c\u4e2aSheet\u6dfb\u52a0\u4e00\u6761\u8bb0\u5f55\uff0c\u5176\u4e2dheader_row\u6307\u5b9a\u8868\u5934\u4f4d\u7f6e\uff0cstyle_row\u6307\u5b9a\u6837\u5f0f\u5728\u7b2c\u51e0\u884c# \u6dfb\u52a0record\u65f6\uff0cExcel\u4e2d\u6709\u7684\u5b57\u6bb5\u81ea\u52a8\u653e\u5230Sheet\u5bf9\u5e94\u7684\u5217\uff0c\u4e0d\u5b58\u5728\u7684\u5b57\u6bb5\u81ea\u52a8\u820d\u5f03record={'name':'Micheal','age':14,'sex':'M','other':'\u8fd9\u4e2a\u5b57\u6bb5Sheet\u4e2d\u4e0d\u5b58\u5728\uff0c\u4e0d\u4f1a\u5199\u5165Excel'}tmpl.append_dict(2,record,header_row=1,style_row=2)# \u5f80\u7b2c\u4e09\u4e2aSheet\u6dfb\u52a0\u4e00\u4e2adataframedata={'Name':['Jason','Rose','Micheal'],'Age':[23,19,14],}df=pd.DataFrame(data)tmpl.append_dataframe(3,df)\u5173\u4e8eExcel\u6a21\u677fxltmpl\u652f\u6301xls\u548cxlsx\u8868\u5934\u53ef\u4ee5\u4e0d\u5728\u7b2c\u4e00\u884c\uff0c\u4e0d\u5728\u7b2c\u4e00\u884c\u65f6\uff0c\u8ffd\u52a0\u6570\u636e\u9700\u6307\u5b9aheader_row\u53c2\u6570\u6a21\u677f\u6700\u540e\u4e00\u884c\u5168\u90e8\u586b\u5145{{}}"} +{"package": "xltojson", "pacakge-description": "xltojsonThis Python Package provides the functionality to translate excel data to JSON object.Excel provides a very intuitive way of organising data using its rich customizations provided by its functions.Nowadays, many software applications uses JSON (JavaScript Object Notation) to transfer data. If data is in excel format, it can be a cumbersome task to manually translate data to JSON.Excel File FormatEach spreadsheet is translated to a python dictionary with key same as the spreadsheet name. The spreadsheet with name \"Main\" encloses all the other spreadsheet data.Following is a simple code snippet using which a user can translate file containing excel data to a JSON file.Usage:from xltojson import parse\n parse.translate_excel_to_json(input_excel_file_path, output_json_file_path):peace_symbol:"} +{"package": "xl-tool", "pacakge-description": "Function for io, image preprocess and others"} +{"package": "xltools", "pacakge-description": "Author:Limodou About XltoolsXltools is used to read and write excel via excel template."} +{"package": "xltoy", "pacakge-description": "XLtoy:The ultimate toolkit for Microsoft Excel modelers and model-ops.The nameXLtoyit's a word pun that starts fromexel to pyconcept, but thepseem superfluous here andxlto(p)ybecame\nXLtoy, more funny.DescriptionExcel is a good instrument to do analysis activities, model design, reporting and so on, his intuitiveness is the\nmain reason why it is so diffused all around the world. On the other hand, its great diffusion sees it involved in other\nphases of deploy process. Generally, when excel cross the frontier in processes that involve IT departments it does not perform\nvery well, i mean: change management, error handling, big data, parallel execution, cross platform, deploy on cloud and so on.\nMuch of this work is entrusted to the IT department, which works to address these shortcomings.XLtoy framework come to help this side, it can read, parse, diff, validate, manage changes and run out of the box complicated\nmodels written using Microsoft Excel. Not all features are ready up to now, but the development plan is show below.This tool is useful for users that write, share, maintain and deploy models written in Excel.It can:Read data and formulas and store they in standard formats like json or YAML.Parse formulas and identify interdependencies between equations.Many kind of model are well handled by XLtoy like:validation modelsrule based modelsfinancial modelsforecasting modelsIn a collaborative environment, for example, a change management tools, can save a lot of time and money.\nNo less, dev-ops (od mod-ops) than need an instrument to identify uniquely model, data, and changes on each delivery.\nModel differ can identify precisely which and where are the differences using syntactic or semantic algorithm.\nTopological analisys can help to identify interdependencies between formulas.How it worksAnalyze an entire workbook, is too difficult, and often useless, this approach force to write unpredictable an inefficient\nalgorithms and doesn't work because often we are interested only in a subset of an entire workbook. So main idea, is to\nidentify a subset of areas of interest, defined asworking areasand focus XLtoy only on these.\nWorking areas are Named range defined by user, they follow some pattern and address algotithms. So with minimum changes\nto an existent sheet, the parser can handle it and produce useful information.\nIf you can apply somesimplerulesyou are ready to go!\nAll other operations are doneout of the boxusing command line in order to promote automations and compatibility with\nall platforms.InstallationIt's strongly suggested to use virtualenv:>pip3 install virtualenv\n>python3 -m venv XLtoy_pyenv\n>source XLtoy_pyenv/bin/activate>pip install xltoy\n\n# Or from source:\n\n>git clone https://github.com/glaucouri/XLtoy.git\n>cd XLtoy/\n>python setup.py installAll features now are accessible viaxltoycli command.$ xltoy --help\n\nUsage: xltoy [OPTIONS] COMMAND [ARGS]...\n\nOptions:\n --help Show this message and exit.\n\nCommands:\n collect\n diffDocumentation$ xltoy collect --help\nUsage: xltoy collect [OPTIONS] FILENAME\n\nOptions:\n --timeit Print out how many times it takes for the task\n --yaml Print out the yaml hierarchical view\n --json Print out the json hierarchical view\n --gml_graph PATH save to a file the topology of models in gml format\n --data Collect only data, it will ignore formulas\n -v, --verbose verbose output (repeat for increased verbosity)\n --add_fingerprint Enable fingerprint metadata informations, under section\n xltoy\n\n --parsed Parse formulas and use this version instead of excel\n syntax\n\n --tag TEXT Add a tag attribute to fingerprint eg: --tag v1.0\n --description TEXT Add a description attribute to fingerprint eg:\n --description model 2020Q1\n\n --help Show this message and exit.\n\n$ xltoy diff --help\nUsage: xltoy diff [OPTIONS] FILENAME1 FILENAME2\n\nOptions:\n --timeit Print out how many times it takes for the task\n --data Collect only data, it will ignore formulas\n --relative Areas are handled as relative, each starts from row1,col1\n -v, --verbose verbose output (repeat for increased verbosity)\n --nofingerprint Ignore fingerprint metadata, under section xltoy\n --parsed Parse formulas and use this version instead of excel syntax\n --json Print out in json format instead of default YAML\n --help Show this message and exit.Follow tutorials to a deep dive into all featuresworking rulesHow to manage working areas and how works the parserTutorial1How to manage valuesTutorial2How to manage models and formulasFramework descriptionsThe XLtoy Framework is composed of many subpackages, all of them are reachable via cli sub command.xltoy.collector: It read an excel workbook and extract all needed information, following rules described here.\nThis means equations, named or anonymous exogenous data and parameters.\nResult can be represented as hierarchical yaml or json. This functionality solve problem related\ntochange management,versioning,model governanceanddiffoperation.xltoy.parser: It can parse all collected equation in order to understand for each all the dependencies,\nand transliterate each in a readable and working python code.\nAll relations between formulas are stored in a dependency graph in a key:value structure\nusing the mnemonic name for each equation. This data structure allow us to do a topological analysis of entire\nsystem of equationsTime lineThe framework will be finished in some steps, i want to share the release plane because\nwith the release of first version i will need feedback, use cases and tester.Version 0.1: first working version:it defineworking rulesfully testes with py3.6 to py3.8collector can read data,formulas and can show an entire workbook as yaml or json.diffworks with data and formulas too, it can compare 2 workbook or a representation of it yaml\nor json.with fingerprint option model can be marked (like a md5 for a file)Version 0.2: parser feature:parser can understand excel formula (probably not all syntax)in memory graph representation with all relation between equations.can find all predecessors and successors of a given equation.models can be exported as graph or python code.execution of python version can be done in a notebook or a stand alone env.Version 0.3: executor feature:data can be stored as pandas DataFramemodels can be binded to external data. Binding feature. and can be run on huge data set.Version 0.4: big data feature:model can be distributed on a spark cluster and executed in order to work on big data"} +{"package": "xltpl", "pacakge-description": "xltplA python module to generate xls/x files from a xls/x template.How it worksWhen xltpl reads a xls/x file, it creates a tree for each worksheet.And, each tree is translated to a jinja2 template with custom tags.When the template is rendered, jinja2 extensions of cumtom tags call corresponding tree nodes to write the xls/x file.How to installpipinstallxltplHow to useTo use xltpl, you need to be familiar with thesyntax of jinja2 template.Get a pre-written xls/x file as the template.Insert variables in the cells, such as :{{name}}Insert control statements in the notes(comments) of cells, use beforerow, beforecell or aftercell to seperate them :beforerow{% for item in items %}beforerow{% endfor %}Insert control statements in the cells (v0.9) :{%- for row in rows %}\n{% set outer_loop = loop %}{% for row in rows %}\nCell\n{{outer_loop.index}}{{loop.index}}\n{%+ endfor%}{%+ endfor%}Run the codefromxltpl.writerximportBookWriterwriter=BookWriter('tpl.xlsx')person_info={'name':u'Hello Wizard'}items=['1','1','1','1','1','1','1','1',]person_info['items']=itemspayloads=[person_info]writer.render_book(payloads)writer.save('result.xlsx')SupportedMergedCellNon-string value for a cell (use{% xv variable %}to specify a variable)For xlsxImage (use{% img variable %})DataValidationAutoFilterRelatedpydocxtplA python module to generate docx files from a docx template.django-excel-exportA Django library for exporting data in xlsx, xls, docx format, utilizing xltpl and pydocxtpl, with admin integration.Demo projectLive demo(User name: admin\nPassword: admin)xltpl for nodejsCodeSandbox examples:browsernodexltpl for javaNotesxlrdxlrd does not extract print settings.This repodoes.xlwtxlwt always sets the default font to 'Arial'.Excel measures column width units based on the default font.This repodoes not."} +{"package": "xlttools", "pacakge-description": "xlttoolsThis is a tool library of x1aolata.v0.02"} +{"package": "xlum", "pacakge-description": "xlum-pythonPython importer for theXLUM data exchange and archive formatSystem requirementslxmlhttps://pypi.org/project/lxml/pandashttps://pandas.pydata.org/urllib3https://urllib3.readthedocs.io/en/stable/openpyxlhttps://openpyxl.readthedocs.io/en/stable/Access to GitHub for XSD schema validationInstallation$pipinstallxlumUsageimportxlummeta_obj=xlum.from_xlum(file_name=\"\")Citing@Article{gchron-2022-27,\n AUTHOR = {Kreutzer, S. and Grehl, S. and H\\\"ohne, M. and Simmank, O. and Dornich, K. and Adamiec, G. and Burow, C. and Roberts, H. and Duller, G.},\n TITLE = {XLUM: an open data format for exchange and long-term data preservation of luminescence data},\n JOURNAL = {Geochronology Discussions},\n VOLUME = {2022},\n YEAR = {2022},\n PAGES = {1--22},\n URL = {https://gchron.copernicus.org/preprints/gchron-2022-27/},\n DOI = {10.5194/gchron-2022-27}\n}FundingThe development of the XLUM-format as format basis for reference data was supported by the European Union\u2019s Horizon 2020 research and innovation programme under the Marie Sk\u0142odowska-Curie grant agreement No 844457CREDit)."} +{"package": "xlumina", "pacakge-description": "\u2728 XLuminA \u2728XLuminA, a highly-efficient, auto-differentiating discovery framework for super-resolution microscopyXLuminA: An Auto-differentiating Discovery Framework for Super-Resolution MicroscopyCarla Rodr\u00edguez, S\u00f6ren Arlt, Leonhard M\u00f6ckl and Mario Krenn\ud83d\udcbb Installation:XLuminA can be installed withpip install xluminaThis will installJAX and jaxlib(the version of JAX used in this project is v0.4.13),Optax(the version of Optax used in this project is v0.1.7), andSciPy(the version of SciPy used in this project is v1.10.1).GPU compatibility:The package automatically installs the CPU version of JAX. To installJAX with NVIDIA GPU support(Note: wheels only available on linux), use:# CUDA 12 installation\npip install --upgrade \"jax[cuda12_pip]\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html\n\n# CUDA 11 installation\npip install --upgrade \"jax[cuda11_pip]\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html\ud83d\udc7e Features:XLuminA allows for the simulation, in a (very) fast and efficient way, of classical light propagation through optics hardware configurations,and enables the optimization and automated discovery of new setup designs.The simulator contains many features:\u2726 Light sources (of any wavelength and power) using both scalar or vectorial optical fields.\u2726 Phase masks (e.g., spatial light modulators (SLMs), polarizers and general variable retarders (LCDs)).\u2726 Amplitude masks (e.g., circles, triangles and squares).\u2726 Beam splitters.\u2726 The light propagation methods available in XLuminA are:Fast-Fourier-transform (FFT) based numerical integration of the Rayleigh-Sommerfeld diffraction integral.Chirped z-transform. This algorithm is an accelerated version of the Rayleigh-Sommerfeld method, which allows for arbitrary selection and sampling of the region of interest.Propagation throughhigh NA objective lensesis availale to replicate strong focusing conditions in polarized light.\ud83d\udcdd Example of usage:Examples of some experiments that can be reproduced with XLuminA are:Optical telescope (or 4f-correlator),Polarization-based beam shaping as used inSTED (stimulated emission depletion) microscopy,Thesharp focus of a radially polarized light beam.The code for each of these optical setups is provided in the Jupyter notebook ofexamples.ipynb.\ud83d\ude80 Testing XLuminA's efficiency:We evaluated our framework by conducting several tests - seeFigure 1. The experiments were run on an Intel CPU Xeon Gold 6130 and Nvidia GPU Quadro RTX 6000.(1) Average execution time (in seconds) over 100 runs, within a computational window size of $2048\\times 2048$, for scalar and vectorial field propagation using Rayleigh-Sommerfeld (RS, VRS) and Chirped z-transform (CZT, VCZT) inDiffractioand XLuminA. Times for XLuminA reflect the run with pre-compiled jitted functions. The Python files corresponding to light propagation algorithms testing arescalar_diffractio.pyandvectorial_diffractio.pyfor Diffractio, andscalar_xlumina.pyandvectorial_xlumina.pyfor XLuminA.(2) we compare the gradient evaluation times of numerical (using SciPy'sBFGS optimizer)vsanalytical differentiation (using JAX'sADAM optimizer) when optimizing using XLuminA's optical simulator...(3) and its convergence time:The Jupyter notebook used for running these simulations is provided astest_diffractio_vs_xlumina.ipynb.The Python files corresponding to numerical/autodiff evaluations arenumerical_methods_evaluation_diffractio.py,numerical_methods_evaluation_xlumina.pyandautodiff_evaluation_xlumina.pyIf you want to run the comparison test of the propagation functions, you need to installDiffractio- The version of Diffractio used in this project is v0.1.1.\ud83e\udd16\ud83d\udd0e Discovery of new optical setups:With XLuminA we were able to re-discover three foundational optics experiments:\u27a4 Optical telescope (or 4f-correlator),\u27a4 Polarization-based beam shaping as used inSTED (stimulated emission depletion) microscopy,\u27a4 Thesharp focus of a radially polarized light beam.The Python files used for the discovery of these optical setups, as detailed inour paper, are organized in pairs ofoptical_tableandoptimizeras follows:Experiment name\ud83d\udd2c Optical table\ud83e\udd16 Optimizer\ud83d\udcc4 File for dataOptical telescopefour_f_optical_table.pyfour_f_optimizer.pyGenerate_synthetic_data.pyPolarization-based STEDvsted_optical_table.pyvsted_optimizer.pyN/ASharp focussharp_focus_optical_table.pysharp_focus_optimizer.pyN/A\u2605 The large-scale setup functions are defined inxl_optical_table.pyandxl_optimizer.py.\ud83d\udc40 Overview:In this section we list the available functions in different files and a brief description:Inwave_optics.py: module for scalar optical fields.ClassFunctionsDescriptionScalarLightClass for scalar optical fields defined in the XY plane: complex amplitude $U(r) = A(r)*e^{-ikz}$..drawPlots intensity and phase..apply_circular_maskApply a circular mask of variable radius..apply_triangular_maskApply a triangular mask of variable size..apply_rectangular_maskApply a rectangular mask of variable size..apply_annular_apertureApply annular aperture of variable size..RS_propagationRayleigh-Sommerfelddiffraction integral in z-direction (z>0 and z<0)..get_RS_minimum_zGiven a quality factor, determines the minimum (trustworthy) distance forRS_propagation..CZTChirped z-transform- efficient diffraction using the Bluestein method.LightSourceClass for scalar optical fields defined in the XY plane - defines light source beams..gaussian_beamGaussian beam..plane_wavePlane wave.Invectorized_optics.py: module for vectorized optical fields.ClassFunctionsDescriptionVectorizedLightClass for vectorized optical fields defined in the XY plane: $\\vec{E} = (E_x, E_y, E_z)$.drawPlots intensity, phase and amplitude..draw_intensity_profilePlots intensity profile..VRS_propagationVectorial Rayleigh-Sommerfelddiffraction integral in z-direction (z>0 and z<0)..get_VRS_minimum_zGiven a quality factor, determines the minimum (trustworthy) distance forVRS_propagation..VCZTVectorized Chirped z-transform- efficient diffraction using the Bluestein method.PolarizedLightSourceClass for polarized optical fields defined in the XY plane - defines light source beams..gaussian_beamGaussian beam..plane_wavePlane wave.Inoptical_elements.py: shelf with all the optical elements available.FunctionDescriptionScalar light devices-phase_scalar_SLMPhase mask for the spatial light modulator available for scalar fields.SLMSpatial light modulator: applies a phase mask to incident scalar field.Jones matrices-jones_LPJones matrix of alinear polarizerjones_general_retarderJones matrix of ageneral retarder.jones_sSLMJones matrix of thesuperSLM.jones_LCDJones matrix of liquid crystal display (LCD).Polarization-based devices-sSLMsuper-Spatial Light Modulator: adds phase mask (pixel-wise) to $E_x$ and $E_y$ independently.LCDLiquid crystal device: builds any linear wave-plate.linear_polarizerLinear polarizer.BSSingle-side coated dielectric beam splitter.high_NA_objective_lensHigh NA objective lens (only forVectorizedLight).VCZT_objective_lensPropagation through high NA objective lens (only forVectorizedLight).General elements-lensTransparent lens of variable size and focal length.circular_maskCircular mask of variable size.triangular_maskTriangular mask of variable size and orientation.rectangular_maskRectangular mask of variable size and orientation.annular_apertureAnnular aperture of variable size.forked_gratingForked grating of variable size, orientation, and topological charge.Pre-built optical setups-building_blockBasic building unit. Consists of asSLM, andLCDlinked viaVRS_propagation.xl_setupOptical table with the large set-up (Fig.6aofour paper).vSTEDOptical table with the vectorial-based STED setup (Fig.3aofour paper).sharp_focusOptical table with the sharp focus of a radially polarized light beam setup (Fig.4aofour paper).general_setupOptical table with the general setup for large-scale discovery (Fig.5aofour paper).Intoolbox.py: file with useful functions.FunctionDescriptionBasic operations-spaceBuilds the space where light is placed.wrap_phaseWraps any phase mask into $[-\\pi, \\pi]$ range.is_conserving_energyComputes the total intensity from the light source and compares is with the propagated light -Ref.delta_kroneckerKronecker delta.build_LCD_cellBuilds the cell forLCD.draw_sSLMPlots the two phase masks ofsSLM.moving_avgCompute the moving average of a dataset.rotate_maskRotates the (X, Y) frame w.r.t. given point.profileDetermines the profile of a given input without using interpolation.spot_sizeComputes the spot size as $\\pi (FWHM_x \\cdot FWHM_y) /\\lambda^2$.compute_fwhmComputes FWHM in 2D.Inloss_functions.py: file with loss functions.FunctionDescriptionvMSE_IntensityParallel computation of Mean Squared Error (Intensity) for a given electric field component $E_x$, $E_y$ or $E_z$.MSE_IntensityMean Squared Error (Intensity) for a given electric field component $E_x$, $E_y$ or $E_z$.vMSE_PhaseParallel computation of Mean Squared Error (Phase) for a given electric field component $E_x$, $E_y$ or $E_z$.MSE_PhaseMean Squared Error (Phase) for a given electric field component $E_x$, $E_y$ or $E_z$.vMSE_AmplitudeParallel computation of Mean Squared Error (Amplitude) for a given electric field component $E_x$, $E_y$ or $E_z$.MSE_AmplitudeMean Squared Error (Amplitude) for a given electric field component $E_x$, $E_y$ or $E_z$.mean_batch_MSE_IntensityBatch-basedMSE_Intensity.small_areaFraction of intensity comprised inside the area of a mask.small_area_STEDFraction of intensity comprised inside the area of a mask - STED version.\u26a0\ufe0f Considerations when using XLuminA:By default, JAX usesfloat32precision. If necessary, enablejax.config.update(\"jax_enable_x64\", True)at the beginning of the file.Basic units are microns (um) and radians. Other units (centimeters, millimeters, nanometers, and degrees) are available at__init.py__.IMPORTANT- RAYLEIGH-SOMMERFELD PROPAGATION:FFT-based diffraction calculation algorithmscan be innacurate depending on the computational window size (sampling).Before propagating light, one should check which is the minimum distance available for the simulation to be accurate.You can use the following functions:get_RS_minimum_z, forScalarLightclass, andget_VRS_minimum_z, forVectorizedLightclass.\ud83d\udcbb Development:Some functionalities of XLuminA\u2019s optics simulator (e.g., optical propagation algorithms, planar lens or amplitude masks) are inspired in an open-source NumPy-based Python module for diffraction and interferometry simulation,Diffractio, although we have rewritten and modified these approaches to combine them with JAX just-in-time (jit) functionality. On top of that, we developed completely new functions (e.g., beam splitters, LCDs or propagation through high NA objective lens with CZT methods, to name a few) which significantly expand the software capabilities.Clone repository:git clone https://github.com/artificial-scientist-lab/XLuminA.git\ud83d\udcdd How to cite XLuminA:If you use this software, please cite as:@misc{rodr\u00edguez2023xlumina,\n title={XLuminA: An Auto-differentiating Discovery Framework for Super-Resolution Microscopy}, \n author={Carla Rodr\u00edguez and S\u00f6ren Arlt and Leonhard M\u00f6ckl and Mario Krenn}, \n year={2023}, \n eprint={2310.08408}, \n archivePrefix={arXiv}, \n primaryClass={physics.optics} \n}"} +{"package": "xl-url-convert", "pacakge-description": "No description available on PyPI."} +{"package": "xlutil", "pacakge-description": "xlutilExcel Utilities library created by Santo K Thomas"} +{"package": "xlutils", "pacakge-description": "xlutilsThis package provides a collection of utilities for working with Excel\nfiles. Since these utilities may require either or both of the xlrd\nand xlwt packages, they are collected together here, separate from either\npackage.Currently available are:xlutils.copyTools for copying xlrd.Book objects to xlwt.Workbook objects.xlutils.displayUtility functions for displaying information about xlrd-related\nobjects in a user-friendly and safe fashion.xlutils.filterA mini framework for splitting and filtering Excel files into new\nExcel files.xlutils.marginsTools for finding how much of an Excel file contains useful data.xlutils.saveTools for serializing xlrd.Book objects back to Excel files.xlutils.stylesTools for working with formatting information expressed in styles.InstallationDo the following in your virtualenv:pip install xlutilsDocumentationThe latest documentation can also be found at:http://xlutils.readthedocs.org/en/latest/Problems?Try the following in this order:Read the sourceAsk a question onhttp://groups.google.com/group/python-excel/LicensingCopyright (c) 2008-2015 Simplistix Ltd.\nSee docs/license.txt for details."} +{"package": "xlutils3", "pacakge-description": "UNKNOWN"} +{"package": "xlwang-package", "pacakge-description": "\u9352\u6735\u7d94\u7ed7\ue0ff\u7af4\u6d93\u7335ython\u9356\u2013\u6769\u6b10\u69f8\u7ed7\ue0ff\u7af4\u6d93\ue044\u5bd8"} +{"package": "xlwings", "pacakge-description": "xlwings (Open Source)xlwings is aBSD-licensedPython library that makes it easy to call Python from Excel and vice versa:Scripting: Automate/interact with Excel from Python using a syntax that is close to VBA.Macros: Replace your messy VBA macros with clean and powerful Python code.UDFs: Write User Defined Functions (UDFs) in Python (Windows only).Numpy arraysandPandas Series/DataFramesare fully supported. xlwings-powered workbooks are easy to distribute and work\nonWindowsandmacOS.xlwings includes all files in the xlwings package except theprofolder, i.e., thexlwings.prosubpackage.xlwings PROxlwings PRO offers additional functionality on top of xlwings (Open Source), including:xlwings Server: No local Python installation required, supports Excel on the web and Google Sheets in addition to Excel on Windows and macOS. Integrates with VBA, Office Scripts and Office.js and supports custom functions on all platforms.xlwings Reports: the flexible, template-based reporting systemxlwings Reader: A faster and more feature-rich alternative forpandas.read_excel()(no Excel installation required)Easy deployment via 1-click installer and embedded codeSee thefull list of PRO featuresxlwings PRO issource availableand dual-licensed under one of the following licenses:PolyForm Noncommercial License 1.0.0(noncommercial use is free)xlwings PRO License(commercial use requires apaid plan)License KeyTo use xlwings PRO, you need to install a license key on a Terminal/Command Prompt like so (alternatively, set the env varXLWINGS_LICENSE_KEY:xlwings license update -k YOUR_LICENSE_KEYSeethe docsfor more details.License key for noncommercial purpose:To use xlwings PRO for free in a noncommercial context, use the following license key:noncommercial.License key for commercial purpose:To try xlwings PRO for free in a commercial context, request a trial license key:https://www.xlwings.org/trialTo use xlwings PRO in a commercial context beyond the trial, you need to enroll in a paid plan (they include additional services like support and the ability to create one-click installers):https://www.xlwings.org/pricingxlwings PRO licenses are developer licenses, are verified offline (i.e., no telemetry/license server involved) and allow royalty-free deployments to unlimited internal and external end-users and servers for a hassle-free management. Deployments use deploy keys that don\u2019t expire but instead are bound to a specific version of xlwings.LinksHomepage:https://www.xlwings.orgQuickstart:https://docs.xlwings.org/en/stable/quickstart.htmlDocumentation:https://docs.xlwings.orgBook (O\u2019Reilly, 2021):https://www.xlwings.org/bookVideo Course:https://training.xlwings.org/p/xlwingsSource Code:https://github.com/xlwings/xlwingsxltrail (Version control for Excel files):https://www.xltrail.com"} +{"package": "xlwombat", "pacakge-description": "No description available on PyPI."} +{"package": "xlwrap", "pacakge-description": "No description available on PyPI."} +{"package": "xlwt", "pacakge-description": "xlwtThis is a library for developers to use to generate\nspreadsheet files compatible with Microsoft Excel versions 95 to 2003.The package itself is pure Python with no dependencies on modules or packages\noutside the standard Python distribution.Please read this before using this package:https://groups.google.com/d/msg/python-excel/P6TjJgFVjMI/g8d0eWxTBQAJInstallationDo the following in your virtualenv:pip install xlwtQuick startimportxlwtfromdatetimeimportdatetimestyle0=xlwt.easyxf('font: name Times New Roman, color-index red, bold on',num_format_str='#,##0.00')style1=xlwt.easyxf(num_format_str='D-MMM-YY')wb=xlwt.Workbook()ws=wb.add_sheet('A Test Sheet')ws.write(0,0,1234.56,style0)ws.write(1,0,datetime.now(),style1)ws.write(2,0,1)ws.write(2,1,1)ws.write(2,2,xlwt.Formula(\"A3+B3\"))wb.save('example.xls')DocumentationDocumentation can be found in thedocsdirectory of the xlwt package.\nIf these aren\u2019t sufficient, please consult the code in the\nexamples directory and the source code itself.The latest documentation can also be found at:https://xlwt.readthedocs.org/en/latest/Problems?Try the following in this order:Read the sourceAsk a question onhttps://groups.google.com/group/python-excel/Acknowledgementsxlwt is a fork of the pyExcelerator package, which was developed by\nRoman V. Kiseliov. This product includes software developed by\nRoman V. Kiseliov .xlwt uses ANTLR v 2.7.7 to generate its formula compiler."} +{"package": "xlwt3k", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xlwt-fix", "pacakge-description": "xlwtThis is a library for developers to use to generate\nspreadsheet files compatible with Microsoft Excel versions 95 to 2003.The package itself is pure Python with no dependencies on modules or packages\noutside the standard Python distribution.Please read this before using this package:https://groups.google.com/d/msg/python-excel/P6TjJgFVjMI/g8d0eWxTBQAJInstallationDo the following in your virtualenv:pip install xlwtQuick startimportxlwtfromdatetimeimportdatetimestyle0=xlwt.easyxf('font: name Times New Roman, color-index red, bold on',num_format_str='#,##0.00')style1=xlwt.easyxf(num_format_str='D-MMM-YY')wb=xlwt.Workbook()ws=wb.add_sheet('A Test Sheet')ws.write(0,0,1234.56,style0)ws.write(1,0,datetime.now(),style1)ws.write(2,0,1)ws.write(2,1,1)ws.write(2,2,xlwt.Formula(\"A3+B3\"))wb.save('example.xls')DocumentationDocumentation can be found in thedocsdirectory of the xlwt package.\nIf these aren\u2019t sufficient, please consult the code in the\nexamples directory and the source code itself.The latest documentation can also be found at:https://xlwt.readthedocs.io/en/latest/Problems?Try the following in this order:Read the sourceAsk a question onhttps://groups.google.com/group/python-excel/Acknowledgementsxlwt is a fork of the pyExcelerator package, which was developed by\nRoman V. Kiseliov. This product includes software developed by\nRoman V. Kiseliov .xlwt uses ANTLR v 2.7.7 to generate its formula compiler."} +{"package": "xlwt-fixed-bitmap", "pacakge-description": "# xlwt-fixed"} +{"package": "xlwt-future", "pacakge-description": "Py2.6+ and Py3.3+ fork of xlwt.xlwt is a library for generating spreadsheet files that are compatible\nwith Excel 97/2000/XP/2003, OpenOffice.org Calc, and Gnumeric. xlwt has\nfull support for Unicode. Excel spreadsheets can be generated on any\nplatform without needing Excel or a COM server. The only requirement is\nPython 2.6, 2.7, or 3.3."} +{"package": "xlxlxl181_nester", "pacakge-description": "UNKNOWN"} +{"package": "xlxnester", "pacakge-description": "No description available on PyPI."} +{"package": "xlyy-toolkit", "pacakge-description": "\u8fd9\u662fNatsuriTsukine\u7684\u4e00\u4e2a\u5de5\u5177\u5305"} +{"package": "xm2xl", "pacakge-description": "xm2xlFlatten Xmind file into xlsx sheetInstallationpip install xm2xlUsageUsage : xm2xl \n \n Flags\n -s, --sheet=SHEET : Sheet to read data from\n Default: ''\n -o, --outputfile=OUTPUTFILE : Name of the output file\n Default: ''"} +{"package": "xmacro", "pacakge-description": "xmacroxmacrois a simple tool to define and parse XML macro. it's inspired byros/xacrowhich is an XML macro language desiged forurdf.xmacrolooks like a simplified version ofros/xacro, it's simpler, but it works well both forurdfandsdf. in addition it's flexible, and also easy to use.xmacrois independent of ROS, you could install it bypip.XML namespace isn't used inxmacro, there are some reserved tags:xmacro_include,xmacro_define_value,xmacro_define_block,xmacro_block.it provides python api so that we could parse xml file in ROS2 launch file.xmacro4sdf:xmacrowith some specific functions forsdf(pre-defined common macro,xmacro_includepath parser formodel://).xmacro4urdf:xmacrowith some specific functions forurdf(pre-defined common macro,xmacro_includepath parser forpackage://).UsageInstallation# install by pippipinstallxmacro# install from source codegitclonehttps://github.com/gezp/xmacro.gitcdxmacro&&sudopython3setup.pyinstallexamples# some examples in folder test/xmacroxmacrotest_xmacro_block.xml.xmacro>test_xmacro_block.xmlXMLMacro FeaturesValue macroBlock macroMath expressionsIncludePython APIValue macroValue macro are named values that can be inserted anywhere into the XML documentexceptblock.xmacro definitiongenerated xmlBlock macroDefine block macros with the macro tag, then specify the macro name and a list of parameters. The list of parameters should be whitespace separated.The usage of block macros is to definewhich will be replaced with correspondingblock.xmacro definition${m}${m*(y*y+z*z)/12}00${m*(x*x+z*z)/12}0${m*(x*x+z*z)/12}000.02000generated xml000.020000.20.0008333333333333335000.00216666666666666700.002166666666666667only support simple parameters (string and number), and block parameters isn't supported.it's supported to use otherxmacro_blockinxmacro_define_blockwhich is recursive definition (the max nesting level is 5).condition blocka example here (you could find more examples intest/xmacro/test_xmacro_condition.xml.xmacro)000.02000theconditioncan beTrue,False,1,0, we can also use math expression to define condition, but operatorisn't supported in math expression.ifconditionisFalseor0, thexmacro_blockwou't be loaded.conditionis reserved attribute of, soconditioncan't be used asparamsof.Math expressionswithin dollared-braces${xxxx}, you can also write simple math expressions.refer to examples ofValue macroandBlock macroit's implemented by callingeval()in python, so it's unsafe for some cases.Including other xmacro filesYou can include other xmacro files by using thetag.it will include the xmcaro definition with tagand macros with tag.The uri forfilemeans to open the file directly.it try to open the file with relative pathsimple_car/model.sdf.xmacro.you can also try to open file with absolute path/simple_car/model.sdf.xmacrowith urifile:///simple_car/model.sdf.xmacro.supports to include recursively.Python APIyou can usexmacroin python easilyfromxmacro.xmacroimportXMLMacroxmacro=XMLMacro()#case1 parse from filexmacro.set_xml_file(inputfile)xmacro.generate()xmacro.to_file(outputfile)#case2 parse from xml stringxmacro.set_xml_string(xml_str)xmacro.generate()xmacro.to_file(outputfile)#case3 generate to stringxmacro.set_xml_file(inputfile)xmacro.generate()xmacro.to_string()#case4 custom macro valuexmacro.set_xml_file(inputfile)# use custom dictionary to overwrite global macro value defined by kv={\"rplidar_a2_h\":0.8}xmacro.generate(kv)xmacro.to_file(outputfile)XMLMacro4sdf Featurespre-defined common.sdf.xmacroexamples# some examples in folder test/sdfxmacro4sdfmodel.sdf.xmacro>model.sdfXMLMacro4urdf Featurespre-defined common.urdf.xmacroexamples# some examples in folder test/urdfxmacro4urdfrobot.urdf.xmacro>robot.urdfMaintainer and Licensemaintainer : Zhenpeng Ge,zhenpeng.ge@qq.comxmacrois provided under MIT License."} +{"package": "x-maes", "pacakge-description": "No description available on PyPI."} +{"package": "x-magical", "pacakge-description": "x-magicalx-magicalis a benchmark extension ofMAGICALspecifically geared towardscross-embodiment imitation. The tasks still provide the Demo/Test structure that allows one to evaluate how well imitation or reward learning techniques can generalize the demonstrator's intent to substantially different deployment settings, but there's an added axis of variation focusing on how well these techniques can adapt to systematic embodiment gaps between the demonstrator and the learner. This is a challenging problem, as different embodiments are likely to use unique and suitable strategies that allow them to make progress on a task.Embodiments in anx-magicaltask must still learn the same set of general skills like 2D perception and manipulation, but they are specifically designed such that they solve the task in different ways due to differences in their end-effector, shapes, dynamics, etc. For example, in the sweeping task, some agents can sweep all debris in one motion while others need to sweep them one at a time. These differences in execution speeds and state-action trajectories pose challenges for current LfD techniques, and the ability to generalize across embodiments is precisely what this benchmark evaluates.x-magicalis under active development - stay tuned for more tasks and embodiments!Tasks, Embodiments and VariantsEach task inx-magicalcan be instantiated with a particularembodiment, which changes the nature of the robotic agent. Additionally, the task can be instantiated in a particularvariant, which changes one or more semantic aspects the environment. Both axes of variation are meant to evaluate combinatorial generalization. We list the task-embodiment pairings below, with a picture of the initial state of theDemovariant:TaskDescriptionSweepToTop: The agent must sweep all three debris to the goal zone shaded in pink.Embodiments:Gripper,Shortstick,MediumStick,Longstick.Variants: all exceptJitter.Here is a description (source) of what each variant modifies:VariantDescriptionDemoThe default variant with no randomization,i.e.the same initial state acrossreset().JitterThe rotations and orientations of all objects, and the size of goal regions, are jittered by up to 5% of the maximum range.LayoutPositions and rotations of all objects are completely randomized. The definition of what constitutes an \"object\" is task-dependent,i.e.some tasks might not randomize the pose of the robotic agent, just the pushable shapes.ColorThe color of blocks and goal regions is randomized, subject to task-specific constraints.ShapeThe shape of pushable blocks is randomized, again subject to task-specific constraints.DynamicsThe mass and friction of objects are randomized.AllAll applicable randomizations are applied.Usagex-magicalenvironments are available in the Gym registry and can be constructed via string specifiers that take on the form-----v0, where:task: The name of the desired task. See above for the full list of available tasks.embodiment: The embodiment to use for the robotic agent. See above for the list of supported embodiments per task.observation_space: Whether to use pixel or state-based observations. All environments support pixel observations but they may not necessarily provide state-based observation spaces.view_mode: Whether to use an allocentric or egocentric agent view.variant: The variant of the task to use. See above for the full list of variants.For example, here's a short code snippet that illustrates this usage:importgymimportxmagical# This must be called before making any Gym envs.xmagical.register_envs()# List all available environments.print(xmagical.ALL_REGISTERED_ENVS)# Create a demo variant for the SweepToTop task with a gripper agent.env=gym.make('SweepToTop-Gripper-Pixels-Allo-Demo-v0')obs=env.reset()print(obs.shape)# (384, 384, 3)env.render(mode='human')env.close()# Now create a test variant of this task with a shortstick agent,# an egocentric view and a state-based observation space.env=gym.make('SweepToTop-Shortstick-State-Ego-TestLayout-v0')init_obs=env.reset()print(init_obs.shape)# (16,)env.close()Installationx-magicalrequires Python 3.8 or higher. We recommend using anAnacondaenvironment for installation. You can create one with the following:condacreate-nxmagicalpython=3.8\ncondaactivatexmagicalInstalling PyPI releasepipinstallx-magicalInstalling from sourceClone the repository and install in editable mode:gitclonehttps://github.com/kevinzakka/x-magical.gitcdx-magical\npipinstall-rrequirements.txt\npipinstall-e.ContributingIf you'd like to contribute to this project, you should install the extra development dependencies as follows:pipinstall-e.[dev]AcknowledgmentsA big thank you to Sam Toyer, the developer ofMAGICAL, for the valuable help and discussions he provided during the development of this benchmark. Please consider citing MAGICAL if you find this repository useful:@inproceedings{toyer2020magical,\n author ={Sam Toyer and Rohin Shah and Andrew Critch and Stuart Russell},\n title ={The{MAGICAL}Benchmark for Robust Imitation},\n booktitle ={Advances in Neural Information Processing Systems},\n year ={2020}}Additionally, we'd like to thank Brent Yi for fruitful technical discussions and various debugging sessions."} +{"package": "xm-ai", "pacakge-description": "No description available on PyPI."} +{"package": "xmail", "pacakge-description": "No description available on PyPI."} +{"package": "xmailer", "pacakge-description": "No description available on PyPI."} +{"package": "xmailx", "pacakge-description": "welcome to my package"} +{"package": "xmaios-bot", "pacakge-description": "No description available on PyPI."} +{"package": "xmake", "pacakge-description": "====xmake====.. image:: https://img.shields.io/pypi/v/xmake.svg:target: https://pypi.python.org/pypi/xmake.. image:: https://img.shields.io/travis/andreycizov/python-xmake.svg:target: https://travis-ci.org/andreycizov/python-xmake.. image:: https://readthedocs.org/projects/xmake/badge/?version=latest:target: https://xmake.readthedocs.io/en/latest/?badge=latest:alt: Documentation Status.. image:: https://pyup.io/repos/github/andreycizov/python-xmake/shield.svg:target: https://pyup.io/repos/github/andreycizov/python-xmake/:alt: Updates.. image:: https://codecov.io/gh/andreycizov/python-xmake/coverage.svg?branch=master:target: https://codecov.io/gh/andreycizov/python-xmake/?branch=masterMotivation----------A reasonably simple DSL for executing jobs with automated parallelisation.Includes________- Docker bindings.Example_______see examples for now.. code-block:: pythonAuthor------Andrey Cizov (acizov@gmail.com), 2018"} +{"package": "x-man", "pacakge-description": "XmanXmanis a HTTP proxy recording & replaying requests.It acts as an extensible \"Man in the middle\" server, which can:forward requests to other addressreturn cached results immediately without need to proxyingrecord incoming requests to a file, restore responses from theretransform requests & responses on the fly (eg. replace path with regex)throttle requests when clients are making them too frequentlyWithxmanyou can setup a mock server imitating a real server:Configure it to forward to a real server. Enable recording requests and replaying responses.Make some typical requests. Request-response entries will be recorded to a file.You can turn off a real server now. Responses are returned from cache.Usexmanwith recorded data to setup lighweight HTTP service mocks anywhere.Installationpip3installx-manPython 3.6 (or newer) is required.QuickstartConfigure listening on SSL port 8443, forwarding requests tohttps://127.0.0.1:8000with caching.\nWhen the same request comes, cached response will be returned.$xmanhttps://127.0.0.1:8000--listen-port8443--listen-ssl=true--replay=true[2020-09-05 19:39:55] [INFO ] CACHE: loaded request-response pairs record_file=tape.json loaded=17 conflicts=0[2020-09-05 19:39:55] [INFO ] Listening on HTTPS port 8443... ssl=True addr= port=8443 destination=https://127.0.0.1:8000Run in dockerYou can runxmanin docker and pass your custom arguments at the end.That command just prints out the help:dockerrun--rm-it--network=hostigrek5151/xman:latestBasic forwarding all requests with rudimentary caching:dockerrun--rm-it--network=hostigrek5151/xman:latest\\http://127.0.0.1:8000--listen-port8443--listen-ssl=true--replay=trueFor more customization create your ownext.pyextension file (example in section below) and run:dockerrun--rm-it--network=host-v`pwd`/ext.py:/ext.pyigrek5151/xman:latest\\--config=/ext.pyIf you want to keep recorded requests & responses outside container, mounttape.jsonas well:touchtape.json\ndockerrun--rm-it--network=host-v`pwd`/ext.py:/ext.py-v`pwd`/tape.json:/src/tape.jsonigrek5151/xman:latest\\--config=/ext.py--record=true--replay=trueExtensionsIf you need more customization, you can specify extension file, where you can implement your custom behaviour or even processing logic.\nIn order to do that you must create Python script and pass its filename by parameter:xman --config ext.py.In extension file you can specify request / response mappers or custom comparator deciding which requests should be treated as the same. Using that you can achieve custom behaviour for some particular type of requests.Implement your function in place of one of the following functions:transform_request(request: HttpRequest) -> HttpRequest- Transforms each incoming Request before further processing (caching, forwarding).transform_response(request: HttpRequest, response: HttpResponse) -> HttpResponse- Transforms each Response before sending it.immediate_responder(request: HttpRequest) -> Optional[HttpResponse]- Returns immediate response for matched request instead of proxying it further or searching in cachecan_be_cached(request: HttpRequest, response: HttpResponse) -> bool- Indicates whether particular request with response could be saved in cache.cache_request_traits(request: HttpRequest) -> Tuple- Gets tuple denoting request uniqueness. Requests with same results are treated as the same when caching.override_config(config: Config)- Overrides default parameters in config.Extensions exampleext.pyfromtypingimportTuple,Optionalfromnuclear.sublogimportlogfromxman.cacheimportsorted_dict_traitfromxman.configimportConfigfromxman.requestimportHttpRequestfromxman.responseimportHttpResponsefromxman.transformimportreplace_request_pathdeftransform_request(request:HttpRequest)->HttpRequest:\"\"\"Transforms each incoming Request before further processing (caching, forwarding).\"\"\"returnreplace_request_path(request,r'^/some/path/(.+?)(/[a-z]+)(/.*)',r'\\3')defimmediate_responder(request:HttpRequest)->Optional[HttpResponse]:\"\"\"Returns immediate response for matched request instead of proxying it further or searching in cache\"\"\"ifrequest.path.startswith('/some/api'):returnHttpResponse(status_code=200,headers={'Content-Type':'application/json'},content=''.encode())returnNonedeftransform_response(request:HttpRequest,response:HttpResponse)->HttpResponse:\"\"\"Transforms each Response before sending it.\"\"\"ifrequest.path.startswith('/some/api'):log.debug('Found Ya',path=request.path)response=response.set_content('{\"payload\": \"anythingyouwish\"}\"')returnresponsedefcan_be_cached(request:HttpRequest,response:HttpResponse)->bool:\"\"\"Indicates whether particular request with response could be saved in cache.\"\"\"returnresponse.status_code==200defcache_request_traits(request:HttpRequest)->Tuple:\"\"\"Gets tuple denoting request uniqueness. Requests with same results are treated as the same when caching.\"\"\"ifrequest.path.endswith('/some/path'):returnrequest.method,request.path,sorted_dict_trait(request.headers)returnrequest.method,request.path,request.contentdefoverride_config(config:Config):\"\"\"Overrides default parameters in config.\"\"\"# config.listen_port = 8080# config.listen_ssl = True# config.dst_url = 'http://127.0.0.1:8000'# config.record = False# config.record_file = 'tape.json'# config.replay = False# config.replay_throttle = False# config.replay_clear_cache = False# config.replay_clear_cache_seconds = 60# config.allow_chunking = True# config.proxy_timeout = 10config.verbose=0UsageSee help by typingxman:xman v0.1.2 (nuclear v1.1.9) - HTTP proxy recording & replaying requestsUsage:xman [OPTIONS] [DST_URL]Arguments:[DST_URL] - destination base urlDefault: http://127.0.0.1:8000Options:--version - Print version information and exit-h, --help [SUBCOMMANDS...] - Display this help and exit--listen-port LISTEN_PORT - listen port for incoming requestsDefault: 8080--listen-ssl LISTEN_SSL - enable https on listening sideDefault: True--record RECORD - enable recording requests & responsesDefault: False--record-file RECORD_FILE - filename with recorded requestsDefault: tape.json--replay REPLAY - return cached results if foundDefault: False--replay-throttle REPLAY_THROTTLE - throttle response if too many requests are madeDefault: False--replay-clear-cache REPLAY_CLEAR_CACHE - enable clearing cache periodicallyDefault: False--replay-clear-cache-seconds REPLAY_CLEAR_CACHE_SECONDS - clearing cache interval in secondsDefault: 60--allow-chunking ALLOW_CHUNKING - enable sending response in chunksDefault: True--config CONFIG - load extensions from Python file-v, --verbose - show more details in output"} +{"package": "xmanage", "pacakge-description": "xmanage"} +{"package": "xmanager", "pacakge-description": "XManager: A framework for managing machine learning experiments \ud83e\uddd1\u200d\ud83d\udd2cXManager is a platform for packaging, running and keeping track of machine\nlearning experiments. It currently enables one to launch experiments locally or\nonGoogle Cloud Platform (GCP). Interaction with\nexperiments is done via XManager's APIs through Pythonlaunch scripts. Check\noutthese slidesfor a more detailed introduction.To get started, installXManager, itsprerequisitesif needed and followthe\ntutorialor a codelab\n(Colab Notebook/Jupyter Notebook)\nto create and run a launch script.SeeCONTRIBUTING.mdfor guidance on contributions.Install XManagerpipinstallgit+https://github.com/deepmind/xmanager.gitOr, alternatively,a PyPI projectis also\navailable.pipinstallxmanagerOn Debian-based systems, XManager and all its dependencies can be installed and\nset up by cloning this repository and then runningcdxmanager/setup_scripts&&chmod+xsetup_all.sh&&../setup_all.shPrerequisitesThe codebase assumes Python 3.9+.Install Docker (optional)If you usexmanager.xm.PythonDockerto run XManager experiments,\nyou need to install Docker.Followthe stepsto install Docker.And if you are a Linux user, followthe stepsto enable sudoless Docker.Install Bazel (optional)If you usexmanager.xm_local.BazelContainerorxmanager.xm_local.BazelBinaryto run XManager experiments, you need to install Bazel.Followthe stepsto\ninstall Bazel.Create a GCP project (optional)If you usexm_local.Vertex(Vertex AI)\nto run XManager experiments, you need to have a GCP project in order to be able\nto access Vertex AI to run jobs.Createa GCP project.Installgcloud.Associate your Google Account (Gmail account) with your GCP project by\nrunning:exportGCP_PROJECT=\ngcloudauthlogin\ngcloudauthapplication-defaultlogin\ngcloudconfigsetproject$GCP_PROJECTSet upgcloudto work with Docker by running:gcloudauthconfigure-dockerEnable Google Cloud Platform APIs.EnableIAM.Enablethe 'Cloud AI Platfrom'.Enablethe 'Container Registry'.Create a staging bucket in us-central1 if you do not already have one. This\nbucket should be used to save experiment artifacts like TensorFlow log files,\nwhich can be read by TensorBoard. This bucket may also be used to stage files\nto build your Docker image if you build your images remotely.exportGOOGLE_CLOUD_BUCKET_NAME=\ngsutilmb-lus-central1gs://$GOOGLE_CLOUD_BUCKET_NAMEAddGOOGLE_CLOUD_BUCKET_NAMEto the environment variables or your .bashrc:exportGOOGLE_CLOUD_BUCKET_NAME=Writing XManager launch scriptsA snippet for the impatient \ud83d\ude42# Contains core primitives and APIs.fromxmanagerimportxm# Implementation of those core concepts for what we call 'the local backend',# which means all executables are sent for execution from this machine,# independently of whether they are actually executed on our machine or on GCP.fromxmanagerimportxm_local## Creates an experiment context and saves its metadata to the database, which we# can reuse later via `xm_local.list_experiments`, for example. Note that# `experiment` has tracking properties such as `id`.withxm_local.create_experiment(experiment_title='cifar10')asexperiment:# Packaging prepares a given *executable spec* for running with a concrete# *executor spec*: depending on the combination, that may involve building# steps and / or copying the results somewhere. For example, a# `xm.python_container` designed to run on `Kubernetes` will be built via#`docker build`, and the new image will be uploaded to the container registry.# But for our simple case where we have a prebuilt Linux binary designed to# run locally only some validations are performed -- for example, that the# file exists.## `executable` contains all the necessary information needed to launch the# packaged blob via `.add`, see below.[executable]=experiment.package([xm.binary(# What we are going to run.path='/home/user/project/a.out',# Where we are going to run it.executor_spec=xm_local.Local.Spec(),)])## Let's find out which `batch_size` is best -- presumably our jobs write the# results somewhere.forbatch_sizein[64,1024]:# `add` creates a new *experiment unit*, which is usually a collection of# semantically united jobs, and sends them for execution. To pass an actual# collection one may want to use `JobGroup`s (more about it later in the# documentation), but for our purposes we are going to pass just one job.experiment.add(xm.Job(# The `a.out` we packaged earlier.executable=executable,# We are using the default settings here, but executors have plenty of# arguments available to control execution.executor=xm_local.Local(),# Time to pass the batch size as a command-line argument!args={'batch_size':batch_size},# We can also pass environment variables.env_vars={'HEAPPROFILE':'/tmp/a_out.hprof'},))## The context will wait for locally run things (but not for remote things such# as jobs sent to GCP, although they can be explicitly awaited via# `wait_for_completion`).The basic structure of an XManager launch script can be summarized by these\nsteps:Create an experiment and acquire its context.fromxmanagerimportxmfromxmanagerimportxm_localwithxm_local.create_experiment(experiment_title='cifar10')asexperiment:Define specifications of executables you want to run.spec=xm.PythonContainer(path='/path/to/python/folder',entrypoint=xm.ModuleName('cifar10'),)Package your executables.[executable]=experiment.package([xm.Packageable(executable_spec=spec,executor_spec=xm_local.Vertex.Spec(),),])Define your hyperparameters.importitertoolsbatch_sizes=[64,1024]learning_rates=[0.1,0.001]trials=list(dict([('batch_size',bs),('learning_rate',lr)])for(bs,lr)initertools.product(batch_sizes,learning_rates))Define resource requirements for each job.requirements=xm.JobRequirements(T4=1)For each trial, add a job / job groups to launch them.forhyperparametersintrials:experiment.add(xm.Job(executable=executable,executor=xm_local.Vertex(requirements=requirements),args=hyperparameters,))Now we should be readyto runthe launch script.To learn more about differentexecutablesandexecutorsfollow'Components'.Run XManagerxmanagerlaunch./xmanager/examples/cifar10_tensorflow/launcher.pyIn order to run multi-job experiments, the--xm_wrap_late_bindingsflag might\nbe required:xmanagerlaunch./xmanager/examples/cifar10_tensorflow/launcher.py----xm_wrap_late_bindingsComponentsExecutable specificationsXManager executable specifications define what should be packaged in the form of\nbinaries, source files, and other input dependencies required for job execution.\nExecutable specifications are reusable and generally platform-independent.Seeexecutable_specs.mdfor details on each executable specification.NameDescriptionxmanager.xm.ContainerA pre-built.tarimage.xmanager.xm.BazelContainerABazeltarget producing a.tarimage.xmanager.xm.BinaryA pre-built binary.xmanager.xm.BazelBinaryABazeltarget producing a self-contained binary.xmanager.xm.PythonContainerA directory with Python modules to be packaged as a Docker container.ExecutorsXManager executors define a platform where the job runs and resource\nrequirements for the job.Each executor also has a specification which describes how an executable\nspecification should be prepared and packaged.Seeexecutors.mdfor details on each executor.NameDescriptionxmanager.xm_local.LocalRuns a binary or a container locally.xmanager.xm_local.VertexRuns a container onVertex AI.xmanager.xm_local.KubernetesRuns a container on Kubernetes.Job / JobGroupAJobrepresents a single executable on a particular executor, while aJobGroupunites a group ofJobs providing a gang scheduling concept:Jobs inside them are scheduled / descheduled simultaneously. SameJobandJobGroupinstances can beadded multiple times.JobA Job accepts an executable and an executor along with hyperparameters which can\neither be command-line arguments or environment variables.Command-line arguments can be passed in list form,[arg1, arg2, arg3]:binaryarg1arg2arg3They can also be passed in dictionary form,{key1: value1, key2: value2}:binary--key1=value1--key2=value2Environment variables are always passed inDict[str, str]form:exportKEY=VALUEJobs are defined like this:[executable]=xm.Package(...)executor=xm_local.Vertex(...)xm.Job(executable=executable,executor=executor,args={'batch_size':64,},env_vars={'NCCL_DEBUG':'INFO',},)JobGroupA JobGroup accepts jobs in a kwargs form. The keyword can be any valid Python\nidentifier. For example, you can call your jobs 'agent' and 'observer'.agent_job=xm.Job(...)observer_job=xm.Job(...)xm.JobGroup(agent=agent_job,observer=observer_job)"} +{"package": "xmanual", "pacakge-description": "xmanual"} +{"package": "xmap-coordinates", "pacakge-description": "Reserved Python package"} +{"package": "xmapper", "pacakge-description": "xmapper is a XML format convert tool.Seehttps://github.com/xxh840912/xmapper"} +{"package": "xmark", "pacakge-description": "No description available on PyPI."} +{"package": "xmars", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xmas", "pacakge-description": "Table of ContentsHOW?Merry Christmas.Hope you can have such a pleasant night, just as the cat sat on the wall near the Christmas tree, gazing at the picturesque starry night, of course, next to your lover.HOW?> pip install xmas\n\n> xmas name"} +{"package": "xmasclock", "pacakge-description": "# Xmas Clock: Christmas countdown timer :santa: :thumbsup:## Sample Usage :christmas_tree:`bash $ xmasclock.py days days until xmas: 114 $ $ xmasclock.py seconds seconds until xmas: 9869129 `## Installation`bash # easy peasy, pip3 can be used as well $ pip install xmasclock `"} +{"package": "xmask", "pacakge-description": "Configuration of tracking simulations for the LHC and other accelerator"} +{"package": "xmastree", "pacakge-description": "===============================xmastree===============================merry xmas**install**pip install xmastreeorpython setup.py install**usage**python\uff1aIn [1]: __import__('xmastree').XmasTree().show()*/ \\/ \\/ \\/ @\\/ @ \\/ ! $\\/ ^\\/# ! \\/^ \\/ \\/! # $ \\/ $ \\/^ \\/ % ! \\/&@# ^@ ! \\/ # \\/@ & $ #% \\/___________________\\| |shell\uff1aashin@hasee:~> xmastree*/ \\/ \\/ \\/ \\/ ! \\/ %$ \\/ ^ & \\/ @ \\/ #^ \\/ $! \\/ % \\/ \\/$ \\/ # % \\/ & ! \\/ % # \\/ @& %# @ \\/___________________\\| |ashin@hasee:~> xmastree -H 10 -C 140*/ \\/ \\/ $\\/ %\\/ \\/% \\/ ! \\/_________\\| |"} +{"package": "xmatch", "pacakge-description": "xmatchis used to cross match a sky position to a series of catalog, at once.$cross_matchxmatch.cfg--lonlat0.00.0or as a python modulefromastropy.coordinatesimportSkyCoordimportxmatchref=SkyCoord(0,0,unit=\"deg\",frame=\"galactic\")cat_list=xmatch.parse_config('xmatch.cfg')['cat_fits']result=xmatch.xmatch(ref,cat_list)FeaturesGalactic and equatorial system supportedOutput infits,csv,txtorhtmlfor the central point source photometryInstallationInstallxmatchusing pip :$pipinstallxmatchor by running setuptools onsource$pythonsetup.pyinstallContributeIssues TrackerSource CodeSupportIf you are having issues, please let us know.LicenseThis project is licensed under the LGPL+3.0 license."} +{"package": "xmath", "pacakge-description": "No description available on PyPI."} +{"package": "xmatrix", "pacakge-description": "XmatrixA python package to calculate Matrix math problems.python version: 3.6 and above.Usageinstallpip3installxmatrix--upgradeAdd import in your filefromxmatriximport*create a matrixMatrix(\"row;row...\") or Matrix([[1,2,3],[4,5,6],[7,8,9]])xm(\"row;row...\") or xm([[1,2,3],[4,5,6],[7,8,9]])my_matrix=Matrix(\"1,2;3,4\")my_matrix_also_equal_to=xm(\"1,2;3,4\")#result:[1,2][3,4]we also support bigger matrixmy_matrix=xm(\"1,2,3;4,5,6;7,8,9\")#result:[1,2,3][4,5,6][7,8,9]simple calculatemy_matrix=xm(\"1,2;3,4\")my_matrix2=xm(\"4,6;2,9\")print(my_matrix+my_matrix2)#result:[5,8][5,13]print(my_matrix-my_matrix2)#result:[-3,-4][1,-5]print(my_matrix*my_matrix2)#result:[8,24][20,54]print(my_matrix*87)#result:[87,174][261,348]print(my_matrix**7)#result:[30853,44966][67449,98302]print(my_matrix==my_matrix2)#result:FalseTranspose Matrixmy_matrix=xm(\"1,2,3;4,5,6;7,8,9\")print(my_matrix)#result:[1,2,3][4,5,6][7,8,9]print(my_matrix.transpose)print(my_matrix.tp)#result:[1,4,7][2,5,8][3,6,9]my_matrix2=xm(\"1,2,3,4;5,6,7,8;9,10,11,12;13.1,14.2,15.3,16.4\")print(my_matrix2)#result:[1,2,3,4][5,6,7,8][9,10,11,12][13.1,14.2,15.3,16.4]print(my_matrix2.tp)#result:[1,5,9,13.1][2,6,10,14.2][3,7,11,15.3][4,8,12,16.4]Inversemy_matrix=xm(\"1,2;3,4\")print(my_matrix)#result:[1,2][3,4]print(my_matrix.inverse)print(my_matrix.iv)#result:[-2,1][1.5,-0.5]#special use by '**' power operator:print(my_matrix**-1)#result:[-2,1][1.5,-0.5]my_matrix2=xm(\"1,2,3;4,5,6;7,8,9\")print(my_matrix2)#result:[1,2,3][4,5,6][7,8,9]print(my_matrix2.iv)#result:#The determinant is zero, can't be inverse.#Nonemy_matrix3=xm(\"1,1,1;1,2,3;1,4,5\")print(my_matrix3)#result:[1,1,1][1,2,3][1,4,5]print(my_matrix3.inverse)#result:[1,0.5,-0.5][1,-2,1][-1,1.5,-0.5]my_matrix4=xm(\"1,1,2,1;1,1,0,0;1,1,0,1;1,0,1,0\")print(my_matrix4)#result:[1,1,2,1][1,1,0,0][1,1,0,1][1,0,1,0]print(my_matrix4.iv)#result:[-0.5,0,0.5,1][0.5,1,-0.5,-1][0.5,0,-0.5,0][0,-1,1,0]#and more...get the matrix by listmy_matrix=xm(\"1,2,3;4,5,6;7,8,9\")print(my_matrix.raw)#result:[[1,2,3],[4,5,6],[7,8,9]]get identity Matrixi=IdentityMatrix(3)i_also_equal_to=ixm(3)#result:print(i)[1,0,0][0,1,0][0,0,1]Gaussian elimination Row Reduced Echelon Formmy_matrix=xm('1,-3,2,8;-1,4,-2,-9;-3,9,4,6')#resultprint(my_matrix)[1,-3,2,8][-1,4,-2,-9][-3,9,4,6]# Row Reduced Echelon Form (rref)print(my_matrix.rref)[1,0,0,-1][0,1,0,-1][0,0,1,3]"} +{"package": "xm-aws-eks", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xm.booking", "pacakge-description": "xm.bookingThis is a package for booking hours on a content type. It also\nhandles estimates of duration or size. It is a spin-off from\neXtremeManagement. Quite likely some more code needs to move between\nthose two.xm.booking is intended to be useful without eXtremeManagement. But\nfor now the bookings from Products.eXtremeManagement.content.Bookings\nare used. In place of that we want to make a nice and small Zope 3\ncontent object. Of course this needs migration code in\neXtremeManagement.Conversely, eXtremeManagement depends on xm.booking, so if you change\nthis package, please also run the eXtremeManagement tests. If unsure,\nplease contact the eXtremeManagement authors or mailing list. Seehttp://plone.org/products/extreme-management-tool/The code is hosted athttps://github.com/zestsoftware/xm.bookingHistory of xm.booking2.2 (2012-09-12)Moved to github.\n[maurits]2.1 (2011-02-03)Added missing return statement in the size_estimate indexer.\nYou may want to recatalog the Stories to fix their size_estimate.\n[maurits]2.0 (2010-09-24)Made booking table compatible with both Plone 3 and 4, by using\neither poi_niceName (Plone 3, Poi 1.2) or @@pas_member (Plone4).\n[maurits]Explicitly load the permissions.zcml file from\nProducts.eXtremeManagement, otherwise you might get a\nComponentLookupError on zope startup.\n[maurits]Added z3c.autoinclude.plugin target plone.\n[maurits]Use plone.indexer instead of the deprecated\nregisterIndexableAttribute which no longer works in Plone 4. Added\ndependency on plone.indexer for this, so using Plone 3.3 is\nrecommended (might still work on earlier versions).\n[maurits]1.1 (2010-05-01)Avoid renaming bookings that were added via the tracker at the\nmoment you edit them.\nFixeshttp://plone.org/products/extreme-management-tool/issues/184[maurits]1.0 (2009-05-05)Protect the booking table with the eXtremeManagement: View Details\npermission. [maurits+mike]0.9 (2009-01-25)Nothing changed yet.0.8 (2009-01-07)Nothing changed yet.0.7 (2008-10-06)Fixed error where a day=DateTime() default argument in a method defintion\nwould get stuck with the DateTime() of the moment when the site was last\nstarted, sigh. KSS-added bookings all got that date. Fixeshttp://plone.org/products/extreme-management-tool/issues/80. [reinout]0.6 (2008-09-16)Added optional argument \u2018description\u2019 to create_booking. [maurits]Showing booking\u2019s description as \u2018structure\u2019 as it is handled as\nwebintelligent text in Products.eXtremeManagement\u2019s views now. [reinout]0.5 (2008-03-04)No history recorded.0.4 (2008-03-04)No history recorded.0.3 (2008-02-25)No history recorded."} +{"package": "xmc", "pacakge-description": ""} +{"package": "xmca", "pacakge-description": "xMCA | Maximum Covariance Analysis in PythonThe aim of this package is to provide a flexible tool for the climate science community to performMaximum Covariance Analysis (MCA)in a simple and consistent way. Given the huge popularity ofxarrayin the climate science community,xmcasupportsxarray.DataArrayas well asnumpy.ndarrayas input formats.Mode 2 of complex rotated Maximum Covariance Analysis showing the shared dynamics of SST and continental precipitation associated to ENSO between 1980 and 2020.:beginner: What is MCA?MCA maximises the temporal covariance between two different\ndata fields and is closely related to Principal Component Analysis (PCA) / Empirical\nOrthogonal Function analysis (EOF analysis). While EOF analysis maximises the variance within a single data\nfield, MCA allows to extract the dominant co-varying patterns between two different data\nfields. When the two input fields are the same, MCA reduces to standard EOF analysis.For the mathematical understanding please have a look at e.g.Bretherton et al.or thelecture materialwritten by C. Bretherton.:star: New in release 1.4.xMuch faster and more memory-efficient algorithmSignificance testing of individual modes viaRule N(Overland & Preisendorfer 1982)Bootstrapping/permutation schemes + block-wise approach for autocorrelated dataIterative permutation (Winkler et al. 2020)Period parameter ofsolvemethod provides more flexibility to exponential extension, making complex MCA more stableFixed missing coslat weighting when saving a model (Issue 25):pushpin: Core FeaturesStandardRotatedComplexComplex RotatedEOF analysis:heavy_check_mark::heavy_check_mark::heavy_check_mark::heavy_check_mark:MCA:heavy_check_mark::heavy_check_mark::heavy_check_mark::heavy_check_mark:*click on check marks for reference**Complex rotated MCA is also available as a pre-print onarXiv.:wrench: InstallationInstallation is simply done viapip install xmcaIf you have problems during the installation please consult the documentation or raise an issue here on Github.:newspaper: DocumentationA tutorial to get you started as well as the full API can be found in thedocumentation.:zap: QuickstartImport the packagefromxmca.arrayimportMCA# use with np.ndarrayfromxmca.xarrayimportxMCA# use with xr.DataArrayAs an example, we take North American surface temperatures shipped withxarray.Note: only works withxr.DataArray, notxr.Dataset.importxarrayasxr# only needed to obtain test data# split data arbitrarily into west and east coastdata=xr.tutorial.open_dataset('air_temperature').airwest=data.sel(lon=slice(200,260))east=data.sel(lon=slice(260,360))PCA / EOF analysisConstruct a model with only one field and solve it to perform standard PCA /\nEOF analysis.pca=xMCA(west)# PCA of west coastpca.solve(complexify=False)# True for complex PCAsvals=pca.singular_values()# singular vales = eigenvalues for PCAexpvar=pca.explained_variance()# explained variancepcs=pca.pcs()# Principal component scores (PCs)eofs=pca.eofs()# spatial patterns (EOFs)Obtaining aVarimax/Promax-rotatedsolution can be achieved by rotating\nthe model choosing the number of EOFs to be rotated (n_rot) as well as the\nPromax parameter (power). Here,power=1equals a Varimax-rotated solution.pca.rotate(n_rot=10,power=1)expvar_rot=pca.explained_variance()# explained variancepcs_rot=pca.pcs()# Principal component scores (PCs)eofs_rot=pca.eofs()# spatial patterns (EOFs)MCASame as for PCA / EOF analysis, but with two input fields instead of\none.mca=xMCA(west,east)# MCA of field A and Bmca.solve(complexify=False)# True for complex MCAeigenvalues=mca.singular_values()# singular valespcs=mca.pcs()# expansion coefficient (PCs)eofs=mca.eofs()# spatial patterns (EOFs)Significance analysisA simple way of estimating the significance of the obtained modes is by\nrunning Monte Carlo simulations based on uncorrelated Gaussian white\nnoise known asRule N(Overland and Preisendorfer 1982). Here we create 200 of such synthetic data sets and compare the synthetic with the real singular spectrum to assess significance.surr=mca.rule_n(200)median=surr.median('run')q99=surr.quantile(.99,dim='run')q01=surr.quantile(.01,dim='run')cutoff=np.sum((svals-q99>0)).values# first 8 modes significantfig=plt.figure(figsize=(10,4))ax=fig.add_subplot(111)svals.plot(ax=ax,yscale='log',label='true')median.plot(ax=ax,yscale='log',color='.5',label='rule N')q99.plot(ax=ax,yscale='log',color='.5',ls=':')q01.plot(ax=ax,yscale='log',color='.5',ls=':')ax.axvline(cutoff+0.5,ls=':')ax.set_xlim(-2,200)ax.set_ylim(1e-1,2.5e4)ax.set_title('Significance based on Rule N')ax.legend()The first 8 modes are significant according to rule N using 200 synthetic runs.Saving/loading an analysismca.save_analysis('my_analysis')# this will save the data and a respective# info file. The files will be stored in a# special directorymca2=xMCA()# create a new, empty instancemca2.load_analysis('my_analysis/info.xmca')# analysis can be# loaded via specifying the path to the# info file created earlierQuickly inspect your results visuallyThe package provides a method to plot individual modes.mca2.set_field_names('West','East')pkwargs={'orientation':'vertical'}mca2.plot(mode=1,**pkwargs)Result of default plot method after performing MCA on T2m of North American west and east coast showing mode 1.You may want to modify the plot for some better optics:fromcartopy.crsimportEqualEarth# for different map projections# map projections for \"left\" and \"right\" fieldprojections={'left':EqualEarth(),'right':EqualEarth()}pkwargs={\"figsize\":(8,5),\"orientation\":'vertical','cmap_eof':'BrBG',# colormap amplitude\"projection\":projections,}mca2.plot(mode=3,**pkwargs)You can save the plot to your local disk as a.pngfile viaskwargs={'dpi':200}mca2.save_plot(mode=3,plot_kwargs=pkwargs,save_kwargs=skwargs):bookmark: Please citeI am just starting my career as a scientist. Feedback on my scientific work is therefore important to me in order to assess which of my work advances the scientific community. As such, if you use the package for your own research and find it helpful, I would appreciate feedback here onGithub, viaemail, or as acitation:Niclas Rieger, 2021: nicrie/xmca: version x.y.z. doi:10.5281/zenodo.4749830.:muscle: CreditsKudos to the developers and contributors of the following Github projects which I initially used myself and used as an inspiration:ajdawson/eofsYefee/xMCAAnd of course credits to the developers of the extremely useful packagesxarraycartopy"} +{"package": "xmcda", "pacakge-description": "Read, write and manipulate XMCDA objectsThis package enables the manipulating MCDA objects, as defined in the standard data interexchange formatXMCDAXMCDA is a data standard which allows to represent MultiCriteria Decision Analysis (MCDA) data elements in XML according to a clearly defined grammar, designed by theDecision Deck Consortium."} +{"package": "xm.charting", "pacakge-description": "IntroductionChangelog0.5 (2012-09-12)Moved to github:https://github.com/zestsoftware/xm.charting[maurits]0.4 (2010-09-24)Added z3c.autoinclude.plugin target plone.\n[maurits]0.3 (2009-01-07)Style changes by Mirella.0.2 (2008-09-16)Small fixes.0.1 (2008-09-16)Initial release"} +{"package": "xmchat", "pacakge-description": "# xmchat[![Build Status](https://travis-ci.org/haomingw/xmchat.svg?branch=master)](https://travis-ci.org/haomingw/xmchat)chatbot"} +{"package": "xmco-cert-commons", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmcortex", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmd", "pacakge-description": "No description available on PyPI."} +{"package": "xmdaikz", "pacakge-description": "No description available on PyPI."} +{"package": "xmds", "pacakge-description": "xMDSPython library of variants of multi-dimensional scalingCreated byBaihan Lin, Columbia University"} +{"package": "xmds2tools", "pacakge-description": "xmds2-toolsTools to read .hdf5 and .xsil files generated usingXMDS2and functions to implement Bessel transformations and Bessel quadrature integrationThese tools were built to work with the output files generated by XMDS2 but can be used for other purposes.The functionreader.ReadH5reads anyHDF5 fileand returns the contents as a Python dictionary. Likewise,reader.WriteH5takes a Python dictionary and saves the contents as an HDF5 file.XMDS2 simulations generate a text file with extension.xsilas well as the HDF5 data. The functionreader.ParseXSILreads the XML data from the text file and returns a dictionary with simulation parameters including global variables, command line variables, and variables derived from global and command line variables. If the Bessel transform is used on an axis a variable called\"axis name\"Outeris added where\"axis name\"is the name of the axis defined in XMDS and the value of the variable is the outer radius of the interval defining the grid.Thebessel.pymodule is based onNumerical calculation of dipolar-quantum-droplet stationary statesand implements Bessel quadrature integration and numerical radial derivative in cylindrical coordinates.ExamplesTheexamples/folder contains Python scripts demonstrating the use of thereaderandbesselmodules to analyse the output of some of the XMDS2 examples. Thebesselmodule is also used for quadrature integration and compared to the trapezium method.None of the examples or any of the XMDS2 source code is reproduced here and the user is instead refered to theXMDS2 websiteexamples/groundstate_workedexamples.pycorresponds to the continuous renormalisation groundstate example.examples/bc_groundstate.pycorresponds to the imaginary time evolution example using DCT and Bessel transform in the XMDS directoryexamples/bessel_cosine_groundstate.xmdsexamples/bessel_integration.pycompares convergence when integrating using the trapezium method and by Bessel quadratureInstallationInstall fromPyPIpython -m pip install xmds2toolsBuild from sourcepython -m pip install --upgrade pip setuptoolspython -m pip install buildgit clone https://github.com/CSChisholm/xmds2-toolscd xmds2-toolspython -m buildAcknowledgementsThese functions were written and tested during the PhD project of C. S. Chisholm atICFO - The Institute of Photonic Sciencesunder the supervision of Prof. Dr. Leticia Tarruell and with support from Dr. Ram\u00f3n Ramos.Thanks to Prof. P. B. Blakie, Dr. M. T. Johnsson, and Prof. M. J. Davis for advice.ReferencesG. R. Dennis, J. J. Hope, and M. T. Johnsson,XMDS2: Fast, scalable simulation of coupled stochastic partial differential equations. Computer Physics Communications184(1), 201-208 (2013).A.-C. Lee, D. Baillie, and P. B. Blakie,Numerical calculation of dipolar-quantum-droplet stationary states. Physical Review Research3, 013283 (2021)."} +{"package": "xmelange", "pacakge-description": "XMelangePython library for working with xml, xsd, wsdl and soap web servicesInstallation$ pip install xmelangeRun from command lineComplex TypesComplex types allow elements in their content (viaand)\nComplex types also can carry attributes (via).Simple TypesSimple types cannot have element content.\nSimple types cannot carry attributes."} +{"package": "xmem", "pacakge-description": "XmemSimple to use, extensible key-based storage module.Built around python dictionary.How to installpipinstallxmemSamplefromxmemimportMemoryEngine# for json based storagefromxmem.templatesimportJsonTemplate# or for pickle based storagefromxmem.templatesimportPickleTemplate# or Registry storage [Windows]fromxmem.templatesimportRegistryTemplate# instantiate memory using save :path and :template instance# path may be str, or pathlib.Path objectmemory=MemoryEngine('data',JsonTemplate())# optional: register save to python script exit eventmemory.save_atexit()CRUDCreate, UpdateCreate and update is handled using same functions.put,putallIf key doesnt exist it would be created, else the value updated.# add or update memory using :put# method :put may be chainedmemory\\.put('One',1)\\.put('Two',2)# or by using :putallmemory.putall({'three':3,'Four':4})Read# read from memory using :gettwo=memory.get('Two')# output: 2Delete# delete keys using :deletememory.delete('Two','Four')# or clear the whole memory using :clearmemory.clear()Method :delete takes one or more keys as parametersCreate a templateA template has two methods that need to be overwriddendefsave(self,data:dict):...defload(self)->dict:..."} +{"package": "xmemx", "pacakge-description": "UNKNOWN"} +{"package": "xmen", "pacakge-description": "\u2716\ufe0fMENxMEN is an extensible toolkit for Cross-lingual (x)MedicalEntityNormalization.\nThrough its compatibility with theBigBIO (BigScience Biomedical)framework, it can be used out-of-the box to run experiments with many open biomedical datasets. It can also be easily integrated with existing Named Entity Recognition (NER) pipelines.InstallationxMEN is available throughPyPi:pip install xmenDevelopmentWe usePoetryfor building, testing and dependency management (seepyproject.toml).\ud83d\ude80 Getting StartedA very simple pipeline highlighting the main components of xMEN can be found innotebooks/00_Getting_Started.ipynb\ud83c\udf93 ExamplesFor more advanced use cases, check out theexamplesfolder.\ud83d\udcc2 Data LoadingUsually, BigBIO-compatible datasets can just be loaded from the Hugging Face Hub:fromdatasetsimportload_datasetdataset=load_dataset(\"distemist\",\"distemist_linking_bigbio_kb\")Integration with NER ToolsTo use xMEN with existing NER pipelines, you can also create a dataset at runtime.spaCyfromxmen.dataimportfrom_spacydocs=...# list of spaCy docs with entity spansdataset=from_spacy(docs)for an example, see:examples/02_spaCy_German.ipynbSpanMarkerfromspan_markerimportSpanMarkerModelsentences=...# list of sentencesmodel=SpanMarkerModel.from_pretrained(...)preds=model.predict(sentences)fromxmen.dataimportfrom_spansdataset=from_spans(preds,sentences)\ud83d\udd27 Configuration and CLIxMEN provides a convenient command line interface to prepare entity linking pipelines by creating target dictionaries and pre-computing indices to link to concepts in them.Runxmen helpto get an overview of the available commands.Configuration is done through.yamlfiles. For examples, see the/examples/conffolder.\ud83d\udcd5 Creating DictionariesRunxmen dictto create dictionaries to link against. Although the most common use case is to create subsets of the UMLS, it also supports passing custom parser scripts for non-UMLS dictionaries.Note: Creating UMLS subsets requires a local installation of theUMLS metathesaurus(not only MRCONSO.RRF). In the examples, we assume that the environment variable$UMLS_HOMEpoints to the installation path. You can either set this variable, or replace the path with your local installation.UMLS SubsetsExample configuration forMedmentions:name:medmentionsdict:umls:lang:-enmeta_path:${oc.env:UMLS_HOME}/2017AA/METAversion:2017AAsemantic_types:-T005-T007-T017-T022-T031-T033-T037-T038-T058-T062-T074-T082-T091-T092-T097-T098-T103-T168-T170-T201-T204sabs:-CPT-FMA-GO-HGNC-HPO-ICD10-ICD10CM-ICD9CM-MDR-MSH-MTH-NCBI-NCI-NDDF-NDFRT-OMIM-RXNORM-SNOMEDCT_USRunningxmen --dict examples/conf/medmentions.yamlcreates a.jsonlfile from the described UMLS subset.Using Custom DictionariesParsing scripts for custom dictionaries can be provided with the--codeoption (examples can be found in thedictsfolder).Example configuration forDisTEMIST:name:distemistdict:custom:lang:-esdistemist_path:local_files/dictionary_distemist.tsvRunningxmen dict examples/conf/distemist.yaml --code examples/dicts/distemist.pycreates a.jsonlfile from the custom DisTEMIST gazetteer (which you can download fromZenodoand put into any folder, e.g.,local_files).\ud83d\udd0e Candidate GenerationThexmen indexcommand is used to compute term indices from a dictionary created through thedictcommand.\nIf an index already exists, you will be prompted to overwrite the existing file (or pass--overwrite).xMEN provides implementations of different neural and non-neural candidate generatorsTF-IDF Weighted Character N-gramsBased on the implementation fromscispaCy.Runxmen index my_config.yaml --ngramorxmen index my_config.yaml --allto create the index.To use the linker at runtime, pass the index folder as an argument:fromxmen.linkersimportTFIDFNGramLinkerngram_linker=TFIDFNGramLinker(index_base_path=\"/path/to/my/index/ngram\",k=100)predictions=ngram_linker.predict_batch(dataset)SapBERTDense Retrieval based onSapBERTembeddings.YAML file (optional, if you want to configure another Transformer model):linker:candidate_generation:sapbert:model_name:cambridgeltl/SapBERT-UMLS-2020AB-all-lang-from-XLMRRunxmen index my_config.yaml --sapbertorxmen index my_config.yaml --allto create theFAISSindex.To use the linker at runtime, pass the index folder as an argument. To make predictions on a batch of documents, you have to pass a batch size, as the SapBERT linker runs on the GPU by default:fromxmen.linkersimportSapBERTLinkersapbert_linker=SapBERTLinker(index_base_path=\"/path/to/my/index/sapbert\",k=1000)predictions=sapbert_linker.predict_batch(dataset,batch_size=128)If you have loaded a yaml-config as a dictionary-like object, you may also just pass it as kwargs:sapbert_linker=SapBERTLinker(**config)By default, SapBERT assumes a CUDA device is available. If you want to disable cuda, passcuda=Falseto the constructor.EnsembleDifferent candidate generators often work well for different kinds of entity mentions, and it can be helpful to combine their predictions.In xMEN, this can be easily achieved with anEnsembleLinker:fromxmen.linkersimportEnsembleLinkerensemble_linker=EnsembleLinker()ensemble_linker.add_linker('sapbert',sapbert_linker,k=10)ensemble_linker.add_linker('ngram',ngram_linker,k=10)or (as a shortcut for the combination ofTFIDFNGramLinkerandSapBERTLinker):fromxmen.linkersimportdefault_ensembleensemble_linker=default_ensemble(\"/path/to/my/index/\")You can callpredict_batchon theEnsembleLinkerjust as with any other linker.Sometimes, you want to compare the ensemble performance to individual linkers and already have the candidate lists. To avoid recomputation, you can use thereuse_predsargument:prediction=ensemble_linker.predict_batch(dataset,128,100,reuse_preds={'sapbert':predictions_sap,'ngram':predictions_ngram'})\ud83c\udf00 Entity RankersCross-encoder Re-rankerWhen labelled training data is available, a trainable re-ranker can improve ranking of candidate lists a lot.To train a cross-encoder model, first create a dataset of mention / candidate pairs:fromxmen.reranking.cross_encoderimportCrossEncoderReranker,CrossEncoderTrainingArgsfromxmenimportload_kb# Load a KB from a pre-computed dictionary (jsonl) to obtain synonyms for concept encodingkb=load_kb('path/to/my/dictionary.jsonl')# Obtain prediction from candidate generator (see above)candidates=linker.predict_batch(dataset)ce_dataset=CrossEncoderReranker.prepare_data(candidates,dataset,kb)Then you can use this dataset to train a supervised reranking model:# Number of epochs to trainn_epochs=10# Any BERT model, potentially language-specificcross_encoder_model='bert-base-multilingual-cased'args=CrossEncoderTrainingArgs(n_epochs,cross_encoder_model)rr=CrossEncoderReranker()# Fit the modelrr.fit(args,ce_dataset['train'].dataset,ce_dataset['validation'].dataset)# Predict on test setprediction=rr.rerank_batch(candidates['test'],ce_dataset['test'])Note on Memory UsageIn most examples and benchmarks, we use 64 candidates as a batch size for the cross-encoder, which usually fit into 48GB of GPU memory.\nIf you encounter memory issues, you can try reducing this number and/or using a smaller BERT model. See:Issue #22Pre-trained Cross-encodersWe provide pre-trained models, based on automatically translated versions of MedMentions (seenotebooks/01_Translation.ipynb).Instead of fitting the cross-encoder model, you can just load a pre-trained model, e.g., for French:rr=CrossEncoderReranker.load('phlobo/xmen-fr-ce-medmentions',device=0)Models are available on the Hugging Face Hub:https://huggingface.co/models?library=xmen\ud83d\udca1 Pre- and Post-processingWe support various optional components for transforming input data and result sets inxmen.data:SamplingAbbrevation expansionFiltering by UMLS semantic groupsFiltering by UMLS semantic typesReplacement of retired CUIS\ud83d\udcca EvaluationxMEN provides implementations of common entity linking metrics (e.g., a wrapper forneleval) and utilities for error analysis.fromxmen.evaluationimportevaluate,error_analysis# Runs the evaluationeval_results=evaluate(ground_truth,predictions)# Performs error analysiserror_dataframe=error_analysis(ground_truth,predictions))CitationIf you use xMEN in your work, please cite the following paper:Florian Borchert, Ignacio Llorca, Roland Roller, Bert Arnrich, and Matthieu-P Schapranow.xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization.\narXiv preprint arXiv:2310.11275 (2023).http://arxiv.org/abs/2310.11275.BibTeX:@article{borchert2023xmen,title={{xMEN}: A Modular Toolkit for Cross-Lingual Medical Entity Normalization},author={Florian Borchert and Ignacio Llorca and Roland Roller and Bert Arnrich and Matthieu-P. Schapranow},year={2023},url={https://arxiv.org/abs/2310.11275},journal={arXiv preprint arXiv:2310.11275}}"} +{"package": "x-menu", "pacakge-description": "No description available on PyPI."} +{"package": "xmenu-keras-retinanet", "pacakge-description": "No description available on PyPI."} +{"package": "xmesh", "pacakge-description": "This is the MXOS meta tool,mdevwritten by Snow Yang.https://www.mxchip.comInstallationUsing pip:pip3 install mdev(Usepip3 uninstall mdevto uninstall it.)Basic UsageBuilddemos/helloworldand flash APP image into EMC3080.mdev build -m emc3080 demos/helloworld -f APPAdditional Commandsmdev has multiple sub-commands.For a list of available commands, runmdev -h. Get help on a\ncommand withmdev -h."} +{"package": "x-Metaformer", "pacakge-description": "\ud83e\udd5e x-MetaformerA PyTorch implementation of\"MetaFormer Baselines\"with optional extensions.We support various self-supervised pretraining approaches such asBarlowTwins,MoCoV3orVICReg(seex_metaformer.pretraining).SetupSimply run:pip install x-metaformerExampleimporttorchfromx_metaformerimportCAFormer,ConvFormermy_metaformer=CAFormer(in_channels=3,depths=(3,3,9,3),dims=(64,128,320,512),multi_query_attention=False,# share keys and values across query headsuse_seqpool=True,# use sequence pooling vom CCTinit_kernel_size=3,init_stride=2,drop_path_rate=0.4,norm='ln',# ln, bn, rms (layernorm, batchnorm, rmsnorm)use_grn_mlp=True,# use global response norm in mlpsuse_dual_patchnorm=False,# norm on both sides for the patch embeddinguse_pos_emb=True,# use 2d sinusodial positional embeddingshead_dim=32,num_heads=4,attn_dropout=0.1,proj_dropout=0.1,patchmasking_prob=0.05,# replace 5% of the initial tokens with a tokenscale_value=1.0,# scale attention logits by this valuetrainable_scale=False,# if scale can be trainednum_mem_vecs=0,# additional memory vectors (in the attention layers)sparse_topk=0,# sparsify - keep only top k values (in the attention layers)l2=False,# l2 norm on tokens (in the attention layers)improve_locality=False,# remove attention on own tokenuse_starreglu=False# use gated StarReLU)x=torch.randn(64,3,64,64)# B C H Wout=my_metaformer(x,return_embeddings=False)# returns average pooled tokens"} +{"package": "xmeve", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xm-file", "pacakge-description": "xm_fileLibrary for reading and unpacking Fasttracker II moduleshttps://en.wikipedia.org/wiki/XM_(file_format).DocumentationThe original specxm.txtis included as part of the repoXMFile APIproperty.headerModule header informationproperty.patternsList of patterns (including pattern data)property.instrumentsList of instruments (including samples and sample data)Examplesfromxm_fileimportXMFilexm_file=XMFile(\"example.xm\")info=f\"\"\"Module name:{xm_file.header.module_name}Length:{xm_file.header.song_length}Channels:{xm_file.header.no_channels}Patterns:{xm_file.header.no_channels}Instruments:{xm_file.header.no_instruments}BPM:{xm_file.header.bpm}Tempo:{xm_file.header.tempo}\"\"\"print(info)"} +{"package": "xmflask", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xm.globalissues", "pacakge-description": "eXtremeManagement has a content type called \u2018Poi Task\u2019 that provides a way to link a\ntask to a story.xm.globalissues changes the way issues are being found when adding a\nPoi Task, so issues are found globally in the instance.Setup>>> self.setRoles(['Manager'])\n>>> workflow = self.portal.portal_workflowWe need to install Poi and eXtremeManagement:>>> ignore = self.portal.portal_quickinstaller.installProducts(['Poi', 'eXtremeManagement'])We create a project, an iteration, and a story. Note that in our\nmodel, issues correspond to tasks:>>> projectfolder = \\\n... self.portal[self.portal.invokeFactory('Folder', 'folder')]\n>>> project = projectfolder[projectfolder.invokeFactory('Project', 'project')]\n>>> iteration1 = project[project.invokeFactory('Iteration', 'iteration1')]\n>>> story1 = iteration1[iteration1.invokeFactory('Story', 'story1')]Remember that a story has to be estimated and marked as so, so that\nwe\u2019re able to add any tasks to it. Therefore, right now, we shouldn\u2019t\nbe able to add any tasks. An image is allowed, though.>>> def list_addable(context):\n... allowed = context.getAllowedTypes()\n... addable = context.getAddableTypesInMenu(allowed)\n... return u', '.join(ad.Title() for ad in addable)\n>>> list_addable(story1)\nu'File, Image'>>> story1.setRoughEstimate(1.5)\n>>> workflow.doActionFor(story1, 'estimate')\n>>> list_addable(story1)\nu'File, Image, Issue Tracker Task, Task'Let\u2019s create an issue tracker in the project with two issues in it:>>> tracker = project[project.invokeFactory('PoiTracker', 'tracker')]\n>>> myissue = tracker[tracker.invokeFactory('PoiIssue', '1')]\n>>> yourissue = tracker[tracker.invokeFactory('PoiIssue', '2')]Poi TasksIn our story, we can now add two different types of tasks, the normal\n\u201cTask\u201d type and the \u201cPoi Task\u201d type. The \u201cPoi Task\u201d is what we\u2019re\ninterested in, so let\u2019s create one and connect it with one of our\nissues:>>> task = story1[story1.invokeFactory('PoiTask', 'task')]\n>>> task.setIssues([myissue])\n>>> task.getIssues()\n[]\n>>> story1.manage_delObjects(['task'])Poi Tasks have a vocabulary methodvocabulary_issuesthat\u2019ll return\na DisplayList of issues that can be referred to. Note that this list\nonly includes open issues:>>> task.vocabulary_issues() # doctest: +ELLIPSIS\n\n>>> myissue.isValid = True\n>>> workflow.doActionFor(myissue, 'post')\n>>> workflow.doActionFor(myissue, 'resolve-unconfirmed')\n>>> task.vocabulary_issues() # doctest: +ELLIPSIS\n\n>>> workflow.doActionFor(myissue, 'open-resolved')\n>>> task.vocabulary_issues() # doctest: +ELLIPSIS\nMass-creating Poi TasksThe@@xm-poiview allows us to create tasks by tags. We use theadd_tasks_from_tagsmethod for this.>>> from Products.statusmessages.interfaces import IStatusMessage\n>>> storyview = story1.restrictedTraverse('@@xm-poi')\n>>> def show_message():\n... for msg in [msg.message for msg in\n... IStatusMessage(storyview.request).showStatusMessages()]:\n... print msgFinding issues globallyThanks to xm.globalissues, issues that live outside our project are also\nconsidered:>>> folder = self.folder\n>>> tracker2 = folder[folder.invokeFactory('PoiTracker', 'tracker2')]\n>>> other_issue = tracker2[tracker2.invokeFactory('PoiIssue', 'other-issue')]\n>>> other_issue.setSubject(['yourtag'])\n>>> other_issue.reindexObject()\n>>> storyview.add_tasks_from_tags(['yourtag'])\n>>> show_message() # doctest: +NORMALIZE_WHITESPACE\nAdded tasks for issues: other-issue.Changelog1.0 (2009-02-20)Initial release"} +{"package": "xm-gnpu-v100", "pacakge-description": "xm-toolTable of ContentsInstallationLicenseInstallationpip install xm-toolLicensexm-toolis distributed under the terms of theMITlicense."} +{"package": "xmgrace_parser", "pacakge-description": "UNKNOWN"} +{"package": "xm.hitcounter", "pacakge-description": "xm.hitcounter Package Readme=========================Overview--------Easy and efficient plone hit counterChangelog for xm.hitcounter(name of developer listed in brackets)xm.hitcounter - 0.0.1 Unreleased- Initial package structure.[zopeskel]"} +{"package": "xmh-utils", "pacakge-description": "No description available on PyPI."} +{"package": "xmi", "pacakge-description": "I used the followinfg link for referencehttps://medium.com/analytics-vidhya/how-to-create-a-python-library-7d5aea80cc3fLegendStatus Indicators:Complete the documentationTasks that are currently being worked on.Set up the repositoryLibrary Development ProgressXmiManager is currently able to read the following entities from the JSON FileEntity NameStatusStructuralModelStructuralPointConnectionStructuralCurveMemberStructuralSurfaceMemberStructuralMaterialStructuralCrossSectionStructuralUnit"} +{"package": "xmi2conll", "pacakge-description": "xmi2conll CLISimple CLI to convert any annotated document in UIMA CAS XMI to CONLL format (IOB schema support).Installation:Start by create and activate a new environnement with virtualenv :virtualenv--python=/usr/bin/python3.8venvsourcevenv/bin/activatethen choose:Easy way (use pip):pipinstallxmi2conllDev install:gitclonehttps://github.com/Lucaterre/xmi2conll\npipinstall-rrequirements.txtUsage:with pip install run:x2c--helpor with dev install run:pythonx2c.py--helpUsage: x2c.py [OPTIONS] INPUT_XMI TYPESYSTEM\n\n XMI to CONLL Converter CLI \u00a9 2022 - @Lucaterre\n\n INPUT_XMI (str): XMI file path or directory path that contains XMI for batch\n processing.\n\n TYPESYSTEM (str): Typesystem.xml path.\n\nOptions:\n -o, --output TEXT output path that contains new conll, \n if it not specify ./output/ is auto created.\n [default: ./output/]\n -tn, --type_name_annotations TEXT\n type name of the annotations [default: de.t\n udarmstadt.ukp.dkpro.core.api.ner.type.Named\n Entity]\n -s, --conll_separator TEXT Defines a separator in CONLL between mention\n and label; only 'space' or 'tab' are accepted [default:\n space]\n -h, --header BOOLEAN show or hide title of CLI [default: True]\n --help Show this message and exit.Citation:@misc{xmi2conll-cli,\n author = \"Lucas Terriel\",\n title = {xmi2conll, a cli to convert any annotated document in UIMA CAS XMI to CONLL format (IOB schema support)},\n howpublished = {\\url{https://github.com/Lucaterre/xmi2conll}},\n year = {2022}\n}License:This tool is distributed under MIT license."} +{"package": "xmi2odoo", "pacakge-description": "With this command you can create Odoo modules from a UML description in XMI file or UML file generated by ArgoUML."} +{"package": "xmi2oerp", "pacakge-description": "With this command you can create OpenERP modules from a UML description in XMI file or UML file generated by ArgoUML."} +{"package": "xmidas", "pacakge-description": "Software for analysis of imaging and spectrosocpy data collected at NSLS-II,\nBrookhaven National LaboratoryFree software: 3-clause BSD licenseDocumentation:https://nsls-ii.github.io/xmidas/."} +{"package": "xmimsim", "pacakge-description": "XMIMSIMXMIMSIM (the python package) is a front-end to XMI-MSIM, XRF open-source simulation software, for running in python.InstallationMacOSOn mac, acquire XMIMSIM throughhomebrew. To install donotuse the brewsci/science tapbrew tap tschoonj/tap\nbrew cask install tschoonj/tap/xmi-msimLinux/WindowsFollow the instructionshere.PythonInstall the python utility withpip install xmimsimGetting startedThe examples folder contains the following example:import xmimsim as xmiThere is only one class currently in xmimsim, so one could just as easily usefrom xmimsim import model.From there, the parameters can be defined as a dictionary:parameters = {'n_photons_interval' : 1,'n_photons_line' : 100000,'n_interactions_trajectory' : 1,\n 'reference_layer' : 2,'d_sample_source' : 100,'area_detector' : 0.5,\n 'collimator_height' : 0,'collimator_diameter' : 0,'d_source_slit' : 100,\n 'slit_size_x' : 0.001,'slit_size_y' : 0.001,'detector_type' : 'SiLi',\n 'detector_live_time' : 1500,'detector_pulse_width' : 1e-05,'detector_nchannels' : 2048,\n 'detector_gain' : 0.0182138,'detector_zero' : 0,'detector_fano' : 0.12,'detector_noise' : 0.1}to be injected into the code. The model is initialized with:xm = xmi.model()from there the model,xm, can be added to, e.g.:xm.set_parameters(**parameters)\nxm.add_source(\n energy = 13.5,\n horizontal_intensity = '1e+012',\n vertical_intensity = '1e+009',\n gaussian=0.14)All these classes return self, so one can actually do this all with one line, i.e.xm.set_parameters(**parameters).add_source(....)The beampath layers are added:xm.add_excitation_path_layer(atomic_numbers=[4], masses=[100], density=1.85, thickness=0.02)\nxm.add_detector_path_layer(atomic_numbers=[4], masses=[100], density=1.85, thickness=0.0025)\nxm.add_crystal_layer(atomic_numbers=[14], masses=[100], density=2.33, thickness=0.35)Which behave like regular analyte layers:xm.add_layer(symbols=['N','O','Ar'],masses=[70,29,1],density=.00122,thickness=3)\nxm.add_layer(symbols=['As','Fe'],masses=[50,50],density=7.31,thickness=0.01)Orientations are defined:xm.sample_orientation(rthetaphi=[1,270+65,0])\nxm.detector_orientation(rthetaphi=[1,135,0])\nxm.detector_window(xyz=[0,5.6,0])The filename is defined for this, although this is not strictly necessary:xm.set_filename('xmsi_testfile')And the calculation is run, discarding the massive xmso in favor of the csv file (default):xm.calculate(M_lines=False, auger_cascade=True,radiative_cascade=False)We can print out the number of photons from each of the following bands.print(xm.count_photons(**{'k_a_Fe':[6.098,6.744],'k_b_Fe':[6.7801,7.340],'k_a_As':[10.196,10.890],'k_b_As':[11.472,11.999]}))xm.get_spectrum()also returns a plottable spectrum from the xmi file.If you simply copy the blocks of code together into one file and run it it should give you an output.Changelog0.0.1Initial Release0.0.2Fixed windows command, but it requires some changing of environment variables to make it run.Fixed some header issues with the readmeCleaned up example.py file0.1.0Fixing the windows problem broke *nix versions. Fixed.0.1.1Added default of no collimator or detector offsetFixed a minor bug in the code (should not change any answers) with element arrays normalizations0.1.2Fixed Readme document type so PyPI handles it correctly0.1.3Allowed larger numbers of interaction counts (greater than 1) in get_spectrum() methodContributingThanks toTom Schoonjansfor creating XMI-MSIM. Special thanks to thevaporypackage, which some of the inspiration for this code comes from (also a python interface for a third-party utility).Report problems to my gmail: nsgeorgescuNGeorgescu :https://github.com/NGeorgescuGithub :https://github.com/NGeorgescu/xmimsim.git"} +{"package": "xmind2case", "pacakge-description": "XMind2TestCaseXMind2TestCase\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9ad8\u6548\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\uff01\u4e00\u3001\u80cc\u666f\u8f6f\u4ef6\u6d4b\u8bd5\u8fc7\u7a0b\u4e2d\uff0c\u6700\u91cd\u8981\u3001\u6700\u6838\u5fc3\u5c31\u662f\u6d4b\u8bd5\u7528\u4f8b\u7684\u8bbe\u8ba1\uff0c\u4e5f\u662f\u6d4b\u8bd5\u7ae5\u978b\u3001\u6d4b\u8bd5\u56e2\u961f\u65e5\u5e38\u6295\u5165\u6700\u591a\u65f6\u95f4\u7684\u5de5\u4f5c\u5185\u5bb9\u4e4b\u4e00\u3002\u7136\u800c\uff0c\u4f20\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u8fc7\u7a0b\u6709\u5f88\u591a\u75db\u70b9\uff1a1\u3001\u4f7f\u7528Excel\u8868\u683c\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\uff0c\u867d\u7136\u6210\u672c\u4f4e\uff0c\u4f46\u7248\u672c\u7ba1\u7406\u9ebb\u70e6\uff0c\u7ef4\u62a4\u66f4\u65b0\u8017\u65f6\uff0c\u7528\u4f8b\u8bc4\u5ba1\u7e41\u7410\uff0c\u8fc7\u7a0b\u62a5\u8868\u7edf\u8ba1\u96be...2\u3001\u4f7f\u7528TestLink\u3001TestCenter\u3001Redmine\u7b49\u4f20\u7edf\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u867d\u7136\u6d4b\u8bd5\u7528\u4f8b\u7684\u6267\u884c\u3001\u7ba1\u7406\u3001\u7edf\u8ba1\u6bd4\u8f83\u65b9\u4fbf\uff0c\u4f46\u4f9d\u7136\u5b58\u5728\u7f16\u5199\u7528\u4f8b\u6548\u7387\u4e0d\u9ad8\u3001\u601d\u8def\u4e0d\u591f\u53d1\u6563\u3001\u5728\u4ea7\u54c1\u5feb\u901f\u8fed\u4ee3\u8fc7\u7a0b\u4e2d\u6bd4\u8f83\u8017\u65f6\u7b49\u95ee\u9898...3\u3001\u516c\u53f8\u81ea\u7814\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u8fd9\u662f\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff0c\u4f46\u5bf9\u4e8e\u5927\u90e8\u5206\u5c0f\u516c\u53f8\u3001\u5c0f\u56e2\u961f\u6765\u8bf4\uff0c\u4e00\u65b9\u9762\u7814\u53d1\u7ef4\u62a4\u6210\u672c\u9ad8\uff0c\u53e6\u4e00\u65b9\u9762\u5bf9\u6280\u672f\u8981\u6709\u4e00\u5b9a\u8981\u6c42...4\u3001...\u57fa\u4e8e\u8fd9\u4e9b\u60c5\u51b5\uff0c\u73b0\u5728\u8d8a\u6765\u8d8a\u591a\u516c\u53f8\u9009\u62e9\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fd9\u79cd\u9ad8\u6548\u7684\u751f\u4ea7\u529b\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\uff0c\u7279\u522b\u662f\u654f\u6377\u5f00\u53d1\u56e2\u961f\u3002\u4e8b\u5b9e\u4e0a\u4e5f\u8bc1\u660e\uff0c\u601d\u7ef4\u5bfc\u56fe\u5176\u53d1\u6563\u6027\u601d\u7ef4\u3001\u56fe\u5f62\u5316\u601d\u7ef4\u7684\u7279\u70b9\uff0c\u8ddf\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65f6\u6240\u9700\u7684\u601d\u7ef4\u975e\u5e38\u543b\u5408\uff0c\u6240\u4ee5\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\u6781\u5927\u63d0\u5347\u4e86\u6211\u4eec\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u6548\u7387\uff0c\u4e5f\u975e\u5e38\u65b9\u4fbf\u6d4b\u8bd5\u7528\u4f8b\u8bc4\u5ba1\u3002\u4f46\u662f\u4e0e\u6b64\u540c\u65f6\uff0c\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u8fc7\u7a0b\u4e2d\u4e5f\u5e26\u6765\u4e0d\u5c11\u95ee\u9898\uff1a1\u3001\u6d4b\u8bd5\u7528\u4f8b\u96be\u4ee5\u91cf\u5316\u7ba1\u7406\u3001\u6267\u884c\u60c5\u51b5\u96be\u4ee5\u7edf\u8ba1\uff1b2\u3001\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u4e0eBUG\u7ba1\u7406\u7cfb\u7edf\u96be\u4ee5\u6253\u901a\uff1b3\u3001\u56e2\u961f\u6210\u5458\u7528\u601d\u7ef4\u5bfc\u56fe\u8bbe\u8ba1\u7528\u4f8b\u7684\u98ce\u683c\u5404\u5f02\uff0c\u6c9f\u901a\u6210\u672c\u5de8\u5927\uff1b4\u3001...\u7efc\u5408\u4ee5\u4e0a\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u53d1\u73b0\u4e0d\u540c\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65b9\u5f0f\uff0c\u5404\u6709\u5404\u4e2a\u7684\u4f18\u52a3\u3002\u90a3\u4e48\u95ee\u9898\u6765\u4e86\uff0c\u6211\u4eec\u80fd\u4e0d\u80fd\u5c06\u5b83\u4eec\u5404\u81ea\u4f18\u70b9\u5408\u5728\u4e00\u8d77\u5462\uff1f\u8fd9\u6837\u4e0d\u5c31\u53ef\u4ee5\u63d0\u5347\u6211\u4eec\u7684\u6548\u7387\u4e86\uff01\u4e8e\u662f\uff0c\u8fd9\u65f6\u5019XMind2TestCase\u5c31\u5e94\u8fd0\u800c\u751f\u4e86\uff0c\u8be5\u5de5\u5177\u57fa\u4e8e Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py 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\u624b\u52a8\uff09\uff1b\n2\u3001\u652f\u6301\u5bfc\u51fa\u6587\u4ef6\u4e2d\u6587\u663e\u793a\uff1b\n3\u3001\u589e\u52a0\u547d\u4ee4\u8fd0\u884c\u6307\u5f15\uff1b\n4\u3001\u4fee\u590d\u670d\u52a1\u5668\u8fdc\u7a0b\u90e8\u7f72\u65e0\u6cd5\u8bbf\u95ee\u95ee\u9898\uff1b\n5\u3001\u53d6\u6d88\u6d4b\u8bd5\u7528\u4f8b\u5173\u952e\u5b57\u9ed8\u8ba4\u8bbe\u7f6e\uff1b\n\n\u5907\u6ce8\uff1aXMind2Testcase\u9488\u5bf9XMind\u7ecf\u5178\u7cfb\u5217\u7248\u672c\uff0c\u6682\u4e0d\u652f\u6301XMind 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2Excel", "pacakge-description": "xmind2Excelxmind2Excel \u662f\u7528\u6765\u5c06xmind\u8f6c\u4e3axmind\u7684\u901a\u7528\u5de5\u5177\u6700\u8fd1\u66f4\u65b0\u521d\u59cb\u53d1\u5e03...\n\n\n############################\nLast update time: 2018-11-13 \nBy\uff1a 8034.com\u4f7f\u7528\u8bf4\u660e\uff1a1\uff09 \u5b89\u88c5\uff1a\npip install xmind2Excel\n2\uff09 \u6267\u884c\nPython -c \"from xmind2Excel.main import Main; Main()\" \n3\uff09 \u6309\u6a21\u677fxmind\u683c\u5f0f\u8981\u6c42\uff0c\u7f16\u5199\u7528\u4f8b\n4\uff09 \u8fd0\u884c\u5de5\u5177\uff0c\u628axmind\u8f6c\u5316\u4e3axls\u3001xlsx\u683c\u5f0f\u7684\u6587\u4ef6\n\n\u6ce8\uff1a \u4e3a\u65b9\u4fbf\u540e\u671f\u64cd\u4f5c\u65b9\u4fbf \n\u53ef\u4ee5 \u628a\u4e0a\u9762\u7684 \u8fd0\u884c\u547d\u4ee4\u653e\u5230bat\u6216shell\u6587\u4ef6\u4e2d\uff0c\u4e0b\u6b21\u76f4\u63a5\u53cc\u51fb\u8fd0\u884c########################################################\u6e90\u7801\u6253\u5305## \u6253\u5305 \u68c0\u67e5\npython setup.py check \n## \u6253\u5305 \u751f\u6210\npython setup.py sdist\n## \u4e0a\u4f20\ntwine upload dist/*\n## \u4f7f\u7528\npip install xxmind \n## \u66f4\u65b0\npip install --upgrade xxmind\n## \u5378\u8f7d\npip uninstall -y xxmind########################################################MANIFEST.ininclude pat1 pat2 ... #include all files matching any of the listed patterns\nexclude pat1 pat2 ... #exclude all files matching any of the listed patterns\nrecursive-include dir pat1 pat2 ... #include all files under dir matching any of the listed patterns\nrecursive-exclude dir pat1 pat2 ... #exclude all files under dir matching any of the listed patterns\nglobal-include pat1 pat2 ... #include all files anywhere in the source tree matching \u2014 & any of the listed patterns\nglobal-exclude pat1 pat2 ... #exclude all files anywhere in the source tree matching \u2014 & any of the listed patterns\nprune dir #exclude all files under dir\ngraft dir #include all files under dir"} +{"package": "xmind2json", "pacakge-description": "xmind2json is fork from xmindparser(https://github.com/tobyqin/xmindparser), a tool to help you convert xmind file to programmable data type, e.g. json, xml.\nNow support XMind 8.Quikly Start\u279c pip3 install xmind2json\nCollecting xmind2json\nInstalling collected packages: xmind2json\nSuccessfully installed xmind2json-1.0.11\n\n\u279c xmind2json /Documents/test.xmind\nGenerated: /Documents/test.jsonChange Log1.1.0Fork from github.com/tobyqin/xmindparser.Support xmind 8 file type.Default convert to json type file.Output json file can contain non-ASCII characters."} +{"package": "xmind2testcase", "pacakge-description": 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\u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py pypi\u4e94\u3001CHANGELOGv1.0.0\n1\u3001XMind\u7528\u4f8b\u6a21\u677f\u5b9a\u4e49\u548c\u89e3\u6790\uff1b\n2\u3001XMind\u7528\u4f8b\u8f6c\u6362\u4e3aTestLink\u7528\u4f8b\u6587\u4ef6\uff1b\n\nv1.1.0\n1\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u6362\u4e3a\u7985\u9053\u7528\u4f8b\u6587\u4ef6\uff1b\n2\u3001\u6dfb\u52a0\u4e00\u952e\u4e0a\u4f20PYPI\u529f\u80fd\uff1b\n\nv1.2.0\n1\u3001\u6dfb\u52a0Web\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8f6c\u6362\uff1b\n2\u3001\u6dfb\u52a0\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.3.0\n1\u3001XMind\u4e2d\u652f\u6301\u6807\u8bc6\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\uff1b\n2\u3001TestCase\u3001TestSuite\u4e2d\u6dfb\u52a0\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u6570\u636e\uff1b\n3\u3001\u5b8c\u5584\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.5.0\n1\u3001\u652f\u6301\u901a\u8fc7\u6807\u7b7e\u8bbe\u7f6e\u7528\u4f8b\u7c7b\u578b\uff08\u81ea\u52a8 or \u624b\u52a8\uff09\uff1b\n2\u3001\u652f\u6301\u5bfc\u51fa\u6587\u4ef6\u4e2d\u6587\u663e\u793a\uff1b\n3\u3001\u589e\u52a0\u547d\u4ee4\u8fd0\u884c\u6307\u5f15\uff1b\n4\u3001\u4fee\u590d\u670d\u52a1\u5668\u8fdc\u7a0b\u90e8\u7f72\u65e0\u6cd5\u8bbf\u95ee\u95ee\u9898\uff1b\n5\u3001\u53d6\u6d88\u6d4b\u8bd5\u7528\u4f8b\u5173\u952e\u5b57\u9ed8\u8ba4\u8bbe\u7f6e\uff1b\n\n\u5907\u6ce8\uff1aXMind2Testcase\u9488\u5bf9XMind\u7ecf\u5178\u7cfb\u5217\u7248\u672c\uff0c\u6682\u4e0d\u652f\u6301XMind Zen\u7248\u672c\uff01\u516d\u3001\u81f4\u8c22XMind2TestCase\u5de5\u5177\u7684\u4ea7\u751f\uff0c\u53d7\u76ca\u4e8e\u4ee5\u4e0b\u56db\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u5e76\u5728\u6b64\u57fa\u7840\u4e0a\u6269\u5c55\u3001\u4f18\u5316\uff0c\u53d7\u76ca\u532a\u6d45\uff0c\u611f\u6069\uff011\u3001XMind\uff1aXMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7ad9\u5f0f\u89e3\u51b3\u65b9\u6848(Python\u5b9e\u73b0)\uff012\u3001xmind2testlink\uff1a\u8df5\u884c\u4e86XMind\u901a\u7528\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\u8bbe\u8ba1\u601d\u8def\uff0c\u540c\u65f6\u63d0\u4f9b\u4e86Web\u8f6c\u6362\u5de5\u5177\uff013\u3001TestLink\uff1a\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u6d41\u7a0b\u548c\u6587\u6863\uff1b4\u3001\u7985\u9053\u5f00\u6e90\u7248(ZenTao)\uff1a\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u9879\u76ee\u7ba1\u7406\u6d41\u7a0b\u3001\u6587\u6863\u548c\u7528\u6237\u4ea4\u6d41\u91ca\u7591\u7fa4\uff1b\u5f97\u76ca\u4e8e\u5f00\u6e90\uff0c\u4e5f\u5c06\u575a\u6301\u5f00\u6e90\uff0c\u5e76\u4e3a\u52aa\u529b\u5f00\u6e90\u8d21\u732e\u81ea\u5df1\u7684\u70b9\u6ef4\u4e4b\u529b\u3002\u540e\u7eed\uff0c\u5c06\u7ee7\u7eed\u6839\u636e\u5b9e\u9645\u9879\u76ee\u9700\u8981\uff0c\u5b9a\u671f\u8fdb\u884c\u66f4\u65b0\u7ef4\u62a4\uff0c\n\u6b22\u8fce\u5927\u4f19\u7684\u4f7f\u7528\u548c\u610f\u89c1\u53cd\u9988\uff0c\u8c22\u8c22\uff01\uff08\u5982\u679c\u672c\u9879\u76ee\u5bf9\u4f60\u6709\u5e2e\u52a9\u7684\u8bdd\uff0c\u4e5f\u6b22\u8fcestar\uff09LICENSEMIT License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase2021", "pacakge-description": "XMind2TestCaseXMind2TestCase\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9ad8\u6548\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\uff01LICENSEMIT License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase4sunny", "pacakge-description": "XMind2TestCaseXMind2TestCase\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9ad8\u6548\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\uff01\u4e00\u3001\u80cc\u666f\u8f6f\u4ef6\u6d4b\u8bd5\u8fc7\u7a0b\u4e2d\uff0c\u6700\u91cd\u8981\u3001\u6700\u6838\u5fc3\u5c31\u662f\u6d4b\u8bd5\u7528\u4f8b\u7684\u8bbe\u8ba1\uff0c\u4e5f\u662f\u6d4b\u8bd5\u7ae5\u978b\u3001\u6d4b\u8bd5\u56e2\u961f\u65e5\u5e38\u6295\u5165\u6700\u591a\u65f6\u95f4\u7684\u5de5\u4f5c\u5185\u5bb9\u4e4b\u4e00\u3002\u7136\u800c\uff0c\u4f20\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u8fc7\u7a0b\u6709\u5f88\u591a\u75db\u70b9\uff1a1\u3001\u4f7f\u7528Excel\u8868\u683c\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\uff0c\u867d\u7136\u6210\u672c\u4f4e\uff0c\u4f46\u7248\u672c\u7ba1\u7406\u9ebb\u70e6\uff0c\u7ef4\u62a4\u66f4\u65b0\u8017\u65f6\uff0c\u7528\u4f8b\u8bc4\u5ba1\u7e41\u7410\uff0c\u8fc7\u7a0b\u62a5\u8868\u7edf\u8ba1\u96be...2\u3001\u4f7f\u7528TestLink\u3001TestCenter\u3001Redmine\u7b49\u4f20\u7edf\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u867d\u7136\u6d4b\u8bd5\u7528\u4f8b\u7684\u6267\u884c\u3001\u7ba1\u7406\u3001\u7edf\u8ba1\u6bd4\u8f83\u65b9\u4fbf\uff0c\u4f46\u4f9d\u7136\u5b58\u5728\u7f16\u5199\u7528\u4f8b\u6548\u7387\u4e0d\u9ad8\u3001\u601d\u8def\u4e0d\u591f\u53d1\u6563\u3001\u5728\u4ea7\u54c1\u5feb\u901f\u8fed\u4ee3\u8fc7\u7a0b\u4e2d\u6bd4\u8f83\u8017\u65f6\u7b49\u95ee\u9898...3\u3001\u516c\u53f8\u81ea\u7814\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u8fd9\u662f\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff0c\u4f46\u5bf9\u4e8e\u5927\u90e8\u5206\u5c0f\u516c\u53f8\u3001\u5c0f\u56e2\u961f\u6765\u8bf4\uff0c\u4e00\u65b9\u9762\u7814\u53d1\u7ef4\u62a4\u6210\u672c\u9ad8\uff0c\u53e6\u4e00\u65b9\u9762\u5bf9\u6280\u672f\u8981\u6709\u4e00\u5b9a\u8981\u6c42...4\u3001...\u57fa\u4e8e\u8fd9\u4e9b\u60c5\u51b5\uff0c\u73b0\u5728\u8d8a\u6765\u8d8a\u591a\u516c\u53f8\u9009\u62e9\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fd9\u79cd\u9ad8\u6548\u7684\u751f\u4ea7\u529b\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\uff0c\u7279\u522b\u662f\u654f\u6377\u5f00\u53d1\u56e2\u961f\u3002\u4e8b\u5b9e\u4e0a\u4e5f\u8bc1\u660e\uff0c\u601d\u7ef4\u5bfc\u56fe\u5176\u53d1\u6563\u6027\u601d\u7ef4\u3001\u56fe\u5f62\u5316\u601d\u7ef4\u7684\u7279\u70b9\uff0c\u8ddf\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65f6\u6240\u9700\u7684\u601d\u7ef4\u975e\u5e38\u543b\u5408\uff0c\u6240\u4ee5\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\u6781\u5927\u63d0\u5347\u4e86\u6211\u4eec\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u6548\u7387\uff0c\u4e5f\u975e\u5e38\u65b9\u4fbf\u6d4b\u8bd5\u7528\u4f8b\u8bc4\u5ba1\u3002\u4f46\u662f\u4e0e\u6b64\u540c\u65f6\uff0c\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u8fc7\u7a0b\u4e2d\u4e5f\u5e26\u6765\u4e0d\u5c11\u95ee\u9898\uff1a1\u3001\u6d4b\u8bd5\u7528\u4f8b\u96be\u4ee5\u91cf\u5316\u7ba1\u7406\u3001\u6267\u884c\u60c5\u51b5\u96be\u4ee5\u7edf\u8ba1\uff1b2\u3001\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u4e0eBUG\u7ba1\u7406\u7cfb\u7edf\u96be\u4ee5\u6253\u901a\uff1b3\u3001\u56e2\u961f\u6210\u5458\u7528\u601d\u7ef4\u5bfc\u56fe\u8bbe\u8ba1\u7528\u4f8b\u7684\u98ce\u683c\u5404\u5f02\uff0c\u6c9f\u901a\u6210\u672c\u5de8\u5927\uff1b4\u3001...\u7efc\u5408\u4ee5\u4e0a\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u53d1\u73b0\u4e0d\u540c\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65b9\u5f0f\uff0c\u5404\u6709\u5404\u4e2a\u7684\u4f18\u52a3\u3002\u90a3\u4e48\u95ee\u9898\u6765\u4e86\uff0c\u6211\u4eec\u80fd\u4e0d\u80fd\u5c06\u5b83\u4eec\u5404\u81ea\u4f18\u70b9\u5408\u5728\u4e00\u8d77\u5462\uff1f\u8fd9\u6837\u4e0d\u5c31\u53ef\u4ee5\u63d0\u5347\u6211\u4eec\u7684\u6548\u7387\u4e86\uff01\u4e8e\u662f\uff0c\u8fd9\u65f6\u5019XMind2TestCase\u5c31\u5e94\u8fd0\u800c\u751f\u4e86\uff0c\u8be5\u5de5\u5177\u57fa\u4e8e Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase4sunny\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase4sunny\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py pypi\u4e94\u3001CHANGELOGv1.0.0\n1\u3001XMind\u7528\u4f8b\u6a21\u677f\u5b9a\u4e49\u548c\u89e3\u6790\uff1b\n2\u3001XMind\u7528\u4f8b\u8f6c\u6362\u4e3aTestLink\u7528\u4f8b\u6587\u4ef6\uff1b\n\nv1.1.0\n1\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u6362\u4e3a\u7985\u9053\u7528\u4f8b\u6587\u4ef6\uff1b\n2\u3001\u6dfb\u52a0\u4e00\u952e\u4e0a\u4f20PYPI\u529f\u80fd\uff1b\n\nv1.2.0\n1\u3001\u6dfb\u52a0Web\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8f6c\u6362\uff1b\n2\u3001\u6dfb\u52a0\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.3.0\n1\u3001XMind\u4e2d\u652f\u6301\u6807\u8bc6\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\uff1b\n2\u3001TestCase\u3001TestSuite\u4e2d\u6dfb\u52a0\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u6570\u636e\uff1b\n3\u3001\u5b8c\u5584\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.5.0\n1\u3001\u652f\u6301\u901a\u8fc7\u6807\u7b7e\u8bbe\u7f6e\u7528\u4f8b\u7c7b\u578b\uff08\u81ea\u52a8 or \u624b\u52a8\uff09\uff1b\n2\u3001\u652f\u6301\u5bfc\u51fa\u6587\u4ef6\u4e2d\u6587\u663e\u793a\uff1b\n3\u3001\u589e\u52a0\u547d\u4ee4\u8fd0\u884c\u6307\u5f15\uff1b\n4\u3001\u4fee\u590d\u670d\u52a1\u5668\u8fdc\u7a0b\u90e8\u7f72\u65e0\u6cd5\u8bbf\u95ee\u95ee\u9898\uff1b\n5\u3001\u53d6\u6d88\u6d4b\u8bd5\u7528\u4f8b\u5173\u952e\u5b57\u9ed8\u8ba4\u8bbe\u7f6e\uff1b\n\n\u5907\u6ce8\uff1aXMind2Testcase\u9488\u5bf9XMind\u7ecf\u5178\u7cfb\u5217\u7248\u672c\uff0c\u6682\u4e0d\u652f\u6301XMind 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase-adaptation", "pacakge-description": 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase-interchen", "pacakge-description": 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py pypi\u4e94\u3001CHANGELOGv1.0.0\n1\u3001XMind\u7528\u4f8b\u6a21\u677f\u5b9a\u4e49\u548c\u89e3\u6790\uff1b\n2\u3001XMind\u7528\u4f8b\u8f6c\u6362\u4e3aTestLink\u7528\u4f8b\u6587\u4ef6\uff1b\n\nv1.1.0\n1\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u6362\u4e3a\u7985\u9053\u7528\u4f8b\u6587\u4ef6\uff1b\n2\u3001\u6dfb\u52a0\u4e00\u952e\u4e0a\u4f20PYPI\u529f\u80fd\uff1b\n\nv1.2.0\n1\u3001\u6dfb\u52a0Web\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8f6c\u6362\uff1b\n2\u3001\u6dfb\u52a0\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.3.0\n1\u3001XMind\u4e2d\u652f\u6301\u6807\u8bc6\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\uff1b\n2\u3001TestCase\u3001TestSuite\u4e2d\u6dfb\u52a0\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u6570\u636e\uff1b\n3\u3001\u5b8c\u5584\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.3.2\n1\u3001\u5bfc\u51fa xlsx \u683c\u5f0f\u7684\u7985\u9053\u7528\u4f8b\n\nv1.3.3\n1\u3001install required \u6dfb\u52a0 openpyxl\u516d\u3001\u81f4\u8c22XMind2TestCase\u5de5\u5177\u7684\u4ea7\u751f\uff0c\u53d7\u76ca\u4e8e\u4ee5\u4e0b\u56db\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u5e76\u5728\u6b64\u57fa\u7840\u4e0a\u6269\u5c55\u3001\u4f18\u5316\uff0c\u53d7\u76ca\u532a\u6d45\uff0c\u611f\u6069\uff011\u3001XMind\uff1aXMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7ad9\u5f0f\u89e3\u51b3\u65b9\u6848(Python\u5b9e\u73b0)\uff012\u3001xmind2testlink\uff1a\u8df5\u884c\u4e86XMind\u901a\u7528\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\u8bbe\u8ba1\u601d\u8def\uff0c\u540c\u65f6\u63d0\u4f9b\u4e86Web\u8f6c\u6362\u5de5\u5177\uff013\u3001TestLink\uff1a\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u6d41\u7a0b\u548c\u6587\u6863\uff1b4\u3001\u7985\u9053\u5f00\u6e90\u7248(ZenTao)\uff1a\u63d0\u4f9b\u4e86\u5b8c\u6574\u7684\u9879\u76ee\u7ba1\u7406\u6d41\u7a0b\u3001\u6587\u6863\u548c\u7528\u6237\u4ea4\u6d41\u91ca\u7591\u7fa4\uff1b\u5f97\u76ca\u4e8e\u5f00\u6e90\uff0c\u4e5f\u5c06\u575a\u6301\u5f00\u6e90\uff0c\u5e76\u4e3a\u52aa\u529b\u5f00\u6e90\u8d21\u732e\u81ea\u5df1\u7684\u70b9\u6ef4\u4e4b\u529b\u3002\u540e\u7eed\uff0c\u5c06\u7ee7\u7eed\u6839\u636e\u5b9e\u9645\u9879\u76ee\u9700\u8981\uff0c\u5b9a\u671f\u8fdb\u884c\u66f4\u65b0\u7ef4\u62a4\uff0c\n\u6b22\u8fce\u5927\u4f19\u7684\u4f7f\u7528\u548c\u610f\u89c1\u53cd\u9988\uff0c\u8c22\u8c22\uff01\uff08\u5982\u679c\u672c\u9879\u76ee\u5bf9\u4f60\u6709\u5e2e\u52a9\u7684\u8bdd\uff0c\u4e5f\u6b22\u8fcestar\uff09LICENSEMIT License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase-kd", "pacakge-description": 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcasepro", "pacakge-description": "XMind2TestCasePro1. \u533a\u522bxmind2testcase\u4e0exmind2testcasepro\u7684\u533a\u522b\uff1a\u652f\u6301\u65b0\u7248\u672c\u7684xmind\u6587\u4ef6\u7684\u89e3\u6790\uff0c\u540c\u65f6\u652f\u6301\u65e7\u7248\u672c\u7684xmind\u6587\u4ef6\u7684\u89e3\u6790\u7528\u4f8b\u7684\u5c55\u793a\u66f4\u52a0\u4e30\u5bcc\uff0c\u66f4\u52a0\u7cbe\u7ec6\u3002\u5728\u4fdd\u6301testcase 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\u4f7f\u7528\u793a\u4f8b4.1 \u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcasepro4.2 \u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcasepro4.3 \u547d\u4ee4\u884cUsage:\n xmind2testcasepro [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcasepro /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcasepro /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcasepro /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcasepro /path/to/testcase.xmind -json => output testcase.json4.4 Web\u9875\u9762Usage:\n xmind2testcasepro [webtool] [port_num]\n\nExample:\n xmind2testcasepro webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcasepro webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80004.5 API\u8c03\u7528view samples.py5. 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\u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002"} +{"package": "xmind2testcase-wzc", "pacakge-description": "XMind2TestCaseXMind2TestCase\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9ad8\u6548\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\uff01\u4e00\u3001\u80cc\u666f\u8f6f\u4ef6\u6d4b\u8bd5\u8fc7\u7a0b\u4e2d\uff0c\u6700\u91cd\u8981\u3001\u6700\u6838\u5fc3\u5c31\u662f\u6d4b\u8bd5\u7528\u4f8b\u7684\u8bbe\u8ba1\uff0c\u4e5f\u662f\u6d4b\u8bd5\u7ae5\u978b\u3001\u6d4b\u8bd5\u56e2\u961f\u65e5\u5e38\u6295\u5165\u6700\u591a\u65f6\u95f4\u7684\u5de5\u4f5c\u5185\u5bb9\u4e4b\u4e00\u3002\u7136\u800c\uff0c\u4f20\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u8fc7\u7a0b\u6709\u5f88\u591a\u75db\u70b9\uff1a1\u3001\u4f7f\u7528Excel\u8868\u683c\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\uff0c\u867d\u7136\u6210\u672c\u4f4e\uff0c\u4f46\u7248\u672c\u7ba1\u7406\u9ebb\u70e6\uff0c\u7ef4\u62a4\u66f4\u65b0\u8017\u65f6\uff0c\u7528\u4f8b\u8bc4\u5ba1\u7e41\u7410\uff0c\u8fc7\u7a0b\u62a5\u8868\u7edf\u8ba1\u96be...2\u3001\u4f7f\u7528TestLink\u3001TestCenter\u3001Redmine\u7b49\u4f20\u7edf\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u867d\u7136\u6d4b\u8bd5\u7528\u4f8b\u7684\u6267\u884c\u3001\u7ba1\u7406\u3001\u7edf\u8ba1\u6bd4\u8f83\u65b9\u4fbf\uff0c\u4f46\u4f9d\u7136\u5b58\u5728\u7f16\u5199\u7528\u4f8b\u6548\u7387\u4e0d\u9ad8\u3001\u601d\u8def\u4e0d\u591f\u53d1\u6563\u3001\u5728\u4ea7\u54c1\u5feb\u901f\u8fed\u4ee3\u8fc7\u7a0b\u4e2d\u6bd4\u8f83\u8017\u65f6\u7b49\u95ee\u9898...3\u3001\u516c\u53f8\u81ea\u7814\u6d4b\u8bd5\u7ba1\u7406\u5de5\u5177\uff0c\u8fd9\u662f\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff0c\u4f46\u5bf9\u4e8e\u5927\u90e8\u5206\u5c0f\u516c\u53f8\u3001\u5c0f\u56e2\u961f\u6765\u8bf4\uff0c\u4e00\u65b9\u9762\u7814\u53d1\u7ef4\u62a4\u6210\u672c\u9ad8\uff0c\u53e6\u4e00\u65b9\u9762\u5bf9\u6280\u672f\u8981\u6709\u4e00\u5b9a\u8981\u6c42...4\u3001...\u57fa\u4e8e\u8fd9\u4e9b\u60c5\u51b5\uff0c\u73b0\u5728\u8d8a\u6765\u8d8a\u591a\u516c\u53f8\u9009\u62e9\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fd9\u79cd\u9ad8\u6548\u7684\u751f\u4ea7\u529b\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\uff0c\u7279\u522b\u662f\u654f\u6377\u5f00\u53d1\u56e2\u961f\u3002\u4e8b\u5b9e\u4e0a\u4e5f\u8bc1\u660e\uff0c\u601d\u7ef4\u5bfc\u56fe\u5176\u53d1\u6563\u6027\u601d\u7ef4\u3001\u56fe\u5f62\u5316\u601d\u7ef4\u7684\u7279\u70b9\uff0c\u8ddf\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65f6\u6240\u9700\u7684\u601d\u7ef4\u975e\u5e38\u543b\u5408\uff0c\u6240\u4ee5\u5728\u5b9e\u9645\u5de5\u4f5c\u4e2d\u6781\u5927\u63d0\u5347\u4e86\u6211\u4eec\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u6548\u7387\uff0c\u4e5f\u975e\u5e38\u65b9\u4fbf\u6d4b\u8bd5\u7528\u4f8b\u8bc4\u5ba1\u3002\u4f46\u662f\u4e0e\u6b64\u540c\u65f6\uff0c\u4f7f\u7528\u601d\u7ef4\u5bfc\u56fe\u8fdb\u884c\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u8fc7\u7a0b\u4e2d\u4e5f\u5e26\u6765\u4e0d\u5c11\u95ee\u9898\uff1a1\u3001\u6d4b\u8bd5\u7528\u4f8b\u96be\u4ee5\u91cf\u5316\u7ba1\u7406\u3001\u6267\u884c\u60c5\u51b5\u96be\u4ee5\u7edf\u8ba1\uff1b2\u3001\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u4e0eBUG\u7ba1\u7406\u7cfb\u7edf\u96be\u4ee5\u6253\u901a\uff1b3\u3001\u56e2\u961f\u6210\u5458\u7528\u601d\u7ef4\u5bfc\u56fe\u8bbe\u8ba1\u7528\u4f8b\u7684\u98ce\u683c\u5404\u5f02\uff0c\u6c9f\u901a\u6210\u672c\u5de8\u5927\uff1b4\u3001...\u7efc\u5408\u4ee5\u4e0a\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u53d1\u73b0\u4e0d\u540c\u7684\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u65b9\u5f0f\uff0c\u5404\u6709\u5404\u4e2a\u7684\u4f18\u52a3\u3002\u90a3\u4e48\u95ee\u9898\u6765\u4e86\uff0c\u6211\u4eec\u80fd\u4e0d\u80fd\u5c06\u5b83\u4eec\u5404\u81ea\u4f18\u70b9\u5408\u5728\u4e00\u8d77\u5462\uff1f\u8fd9\u6837\u4e0d\u5c31\u53ef\u4ee5\u63d0\u5347\u6211\u4eec\u7684\u6548\u7387\u4e86\uff01\u4e8e\u662f\uff0c\u8fd9\u65f6\u5019XMind2TestCase\u5c31\u5e94\u8fd0\u800c\u751f\u4e86\uff0c\u8be5\u5de5\u5177\u57fa\u4e8e Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py pypi\npip install 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase-xls", "pacakge-description": 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c2\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n }\n ]\n },\n ...\n ]\n },\n ...\n ]\n }\n }\n]\u5177\u4f53\u53c2\u8003\uff1axmind_testcase_demo.json\u56db\u3001\u81ea\u52a8\u5316\u53d1\u5e03\uff1a\u4e00\u952e\u6253 Tag \u5e76\u4e0a\u4f20\u81f3 PYPI\u6bcf\u6b21\u5728 __ about __.py \u66f4\u65b0\u7248\u672c\u53f7\u540e\uff0c\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u66f4\u65b0\u6253\u5305\u4e0a\u4f20\u81f3PYPI\uff0c\u540c\u65f6\u6839\u636e\u5176\u7248\u672c\u53f7\u81ea\u52a8\u6253 Tag \u5e76\u63a8\u9001\u5230\u4ed3\u5e93\uff1apython3 setup.py pypi\u4e94\u3001CHANGELOGv1.0.0\n1\u3001XMind\u7528\u4f8b\u6a21\u677f\u5b9a\u4e49\u548c\u89e3\u6790\uff1b\n2\u3001XMind\u7528\u4f8b\u8f6c\u6362\u4e3aTestLink\u7528\u4f8b\u6587\u4ef6\uff1b\n\nv1.1.0\n1\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u6362\u4e3a\u7985\u9053\u7528\u4f8b\u6587\u4ef6\uff1b\n2\u3001\u6dfb\u52a0\u4e00\u952e\u4e0a\u4f20PYPI\u529f\u80fd\uff1b\n\nv1.2.0\n1\u3001\u6dfb\u52a0Web\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8f6c\u6362\uff1b\n2\u3001\u6dfb\u52a0\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.3.0\n1\u3001XMind\u4e2d\u652f\u6301\u6807\u8bc6\u6d4b\u8bd5\u7528\u4f8b\u6267\u884c\u7ed3\u679c\uff1b\n2\u3001TestCase\u3001TestSuite\u4e2d\u6dfb\u52a0\u7528\u4f8b\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u6570\u636e\uff1b\n3\u3001\u5b8c\u5584\u7528\u6237\u4f7f\u7528\u6307\u5357\uff1b\n\nv1.5.0\n1\u3001\u652f\u6301\u901a\u8fc7\u6807\u7b7e\u8bbe\u7f6e\u7528\u4f8b\u7c7b\u578b\uff08\u81ea\u52a8 or \u624b\u52a8\uff09\uff1b\n2\u3001\u652f\u6301\u5bfc\u51fa\u6587\u4ef6\u4e2d\u6587\u663e\u793a\uff1b\n3\u3001\u589e\u52a0\u547d\u4ee4\u8fd0\u884c\u6307\u5f15\uff1b\n4\u3001\u4fee\u590d\u670d\u52a1\u5668\u8fdc\u7a0b\u90e8\u7f72\u65e0\u6cd5\u8bbf\u95ee\u95ee\u9898\uff1b\n5\u3001\u53d6\u6d88\u6d4b\u8bd5\u7528\u4f8b\u5173\u952e\u5b57\u9ed8\u8ba4\u8bbe\u7f6e\uff1b\n\n\u5907\u6ce8\uff1aXMind2Testcase\u9488\u5bf9XMind\u7ecf\u5178\u7cfb\u5217\u7248\u672c\uff0c\u6682\u4e0d\u652f\u6301XMind 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testcase-yys", "pacakge-description": "No description available on PyPI."} +{"package": "xmind2testcasezen", "pacakge-description": "XMind2TestCaseZenXMind2TestCaseZen\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u4e00\u4e2a\u9ad8\u6548\u6d4b\u8bd5\u7528\u4f8b\u8bbe\u8ba1\u7684\u89e3\u51b3\u65b9\u6848\uff01\u4e00\u3001\u533a\u522bxmind2testcase\u4e0exmind2testcaseZen\u7684\u533a\u522b\uff1a\u652f\u6301\u65b0\u7248\u672c\u7684xmind\u6587\u4ef6\u7684\u89e3\u6790\uff0c\u540c\u65f6\u652f\u6301\u65e7\u7248\u672c\u7684xmind\u6587\u4ef6\u7684\u89e3\u6790\u4f8b\u7684\u5c55\u793a\u66f4\u52a0\u4e30\u5bcc\uff0c\u66f4\u52a0\u7cbe\u7ec6\u3002\u5728\u4fdd\u6301testcase 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c \u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002 \u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c \u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCaseZen\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3 \uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e94\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u516d\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcasezen\u4e03\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcasezen\u516b\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcasezen [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcasezen /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcasezen /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcasezen /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcasezen /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcasezen [webtool] [port_num]\n\nExample:\n xmind2testcasezen webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcasezen webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcasezen.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcasezen.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcasezen.services import gen_testcase_to_json_file\nfrom xmind2testcasezen.services import gen_testsuite_to_json_file\nfrom xmind2testcasezen.services import get_testcase_list\nfrom xmind2testcasezen.services import get_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = gen_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = gen_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcasezen.services import get_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcasezen.services import get_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002 \u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCaseZen\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2testlink", "pacakge-description": "Documentationxmind2testlink is a tool to help you convert xmind file to testlink recognized xml files,\nthen you can import it into testlink as test suite and test cases.For more detail, please go to:https://github.com/tobyqin/xmind2testlinkChange Log2.0.9Fix unit test and flake8 issues.2.0.8Enhancement - parse callout as preconditions for XmindZen.\nAuto determine rule v1 or v2 by checking descendants of the 3rd level nodes(which is v1 testcase level) have priority marker or not.2.0.7Bug fix - convert execution type to 1 by default.2.0.6Support XmindZen file type, since comments feature is removed in xmind zen, so we cannot createpreconditionsfrom XmindZen.2.0.5Bug fix - failed to parse priority maker, thanks @nancy301513.2.0.4Bug fix - failed to parse comment node.2.0.3Bug fix - root suite should not have a title.2.0.1Bug fix - web app should not cache the connector.\nBug fix - combination title parts incorrectly under some conditions.2.0.0Upgrade to v2.0, support convert more flexible xmind files.1.1.7Keep line breaks and html tag for text fields, such as test suite summary, test case steps.1.1.4Fix potential failure if test action node is empty.1.1.1Fix potential failure if the node is a image.1.1.0Handle unicode in xmind.1.0.0The baby version."} +{"package": "xmind2xls", "pacakge-description": 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\u548c excel \u7ed3\u5408\u8d77\u6765\u3002\u5728\u63d0\u5347\u6548\u7387\u7684\u540c\u65f6\uff0c\u517c\u987e\u5230\u5b9e\u7528\u7684\u6548\u679c\u6211\u7684\u8bbe\u8ba1\u601d\u8def\u662f\u8fd9\u6837\u7684\uff1a\u4e09\u3001\u73af\u5883\u642d\u5efa1\u3001\u5b89\u88c5pythonhttps://jingyan.baidu.com/article/25648fc19f61829191fd00d4.html2\u3001\u8fd0\u884c\u547d\u4ee4\u884c\u5b89\u88c5xmind2xlspip3 install xmind2xls\u56db\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u65b0\u5efa\u6a21\u72482\u3001\u7f16\u8f91\u6a21\u72483\u3001\u8fd0\u884c\u547d\u4ee4\u884cxmind2xls [path_to_xmind_file] [-xlsx]4\u3001\u5728\u6a21\u7248\u540c\u76ee\u5f55\u4e0b\u67e5\u770bexcel\u7ed3\u679c\u4e94\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2xls\u516d\u3001\u81f4\u8c22XMind2Xls\u5de5\u5177\u7684\u4ea7\u751f\uff0c\u53d7\u76ca\u4e8e\u4ee5\u4e0b\u4e24\u4e2a\u5f00\u6e90\u9879\u76ee\uff0c\u5e76\u5728\u6b64\u57fa\u7840\u4e0a\u6269\u5c55\u3001\u4f18\u5316\u30021\u3001XMind\uff1aXMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7ad9\u5f0f\u89e3\u51b3\u65b9\u6848(Python\u5b9e\u73b0)\uff012\u3001xmind2testcase\uff1a\u8df5\u884c\u4e86XMind\u901a\u7528\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\u8bbe\u8ba1\u601d\u8def\uff0c\u540c\u65f6\u63d0\u4f9b\u4e86Web\u8f6c\u6362\u5de5\u5177\uff01\u4e03\u3001\u6301\u7eed\u96c6\u6210\u90e8\u7f72\u4e3a\u4e86\u5e94\u5bf9\u540e\u671f\u9879\u76ee\u7684\u7ef4\u62a4\u548c\u6301\u7eed\u4f18\u5316\uff0c\u672c\u9879\u76ee\u5f15\u5165\u4e86travis+github\u7684\u6301\u7eed\u96c6\u6210\u90e8\u7f72\u6a21\u5f0f\n\u6bcf\u6b21\u672c\u5730\u4ee3\u7801\u6253\u4e0atag\u63a8\u9001\u5230github\u4ed3\u5e93\u540e\uff0ctravis\u4f1a\u81ea\u52a8\u89e6\u53d1\u6784\u5efa\u3001\u6d4b\u8bd5\u3001\u90e8\u7f72\u5230pypi\u7b49\u64cd\u4f5c\n\u6b22\u8fce\u6709\u5fd7\u4e8e\u6301\u7eed\u6539\u8fdb\u6d4b\u8bd5\u6d41\u7a0b\u548c\u63d0\u9ad8\u6548\u7387\u7684\u5c0f\u4f19\u4f34\u4e3a\u672c\u9879\u76ee\u6dfb\u7816\u52a0\u74e6LICENSEMIT License\nCopyright (c) 2019 taoyu\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xmind2zantao", "pacakge-description": "Xmind2Zantao\u4f7f\u7528\u8bf4\u660ehttps://github.com/lileixuan/xmind2zantao/blob/main/xmind2zantao_web/static/guide/index.md\u90e8\u7f72\u5b89\u88c5\u8f6f\u4ef6\u5305\uff1apipinstallxmind2zantao\u5feb\u901f\u542f\u52a8web\u670d\u52a1gunicornxmind2zantao_web.application:app-eZANTAO_DEFAULT_EXECUTION_TYPE='\u529f\u80fd\u6d4b\u8bd5'-papplication.pid-b0.0.0.0:8000-w4-D\u73af\u5883\u53d8\u91cf\uff1a`ZANTAO_DEFAULT_EXECUTION_TYPE` \u5982\u679c\u6307\u5b9a\u4e86\u503c\uff0c\u5f53\u7528\u4f8b\u7c7b\u578b\u4e3a\u7a7a\u7684\u65f6\u5019\u4f1a\u53ea\u7528\u8be5\u503c\u66ff\u6362\u3002\u6253\u5f00\u6d4f\u89c8\u5668\uff0c\u8f93\u5165\u4e0a\u9762\u6307\u5b9aIP\u5730\u5740\u548c\u7aef\u53e3\u6765\u4f7f\u7528\u3002\u542f\u7528\u7985\u9053\u8f85\u52a9\u529f\u80fd\u542f\u7528\u7985\u9053\u8f85\u52a9\u529f\u80fd\u540e\uff0c\u5c06\u4f1a\u5f00\u542f\u767b\u5f55\u9a8c\u8bc1\u529f\u80fd\u3002\u7528\u6237\u53ef\u4f7f\u7528\u7985\u9053\u8d26\u6237\u767b\u5f55\uff0c\u8f85\u52a9\u529f\u80fd\u7684\u6743\u9650\u548c\u767b\u5f55\u8d26\u6237\u4e00\u81f4\u3002\u542f\u52a8\u670d\u52a1\u65f6\u6307\u5b9a\u76f8\u5e94\u7684\u73af\u5883\u53d8\u91cf\u5373\u53efgunicornxmind2zantao_web.application:app-eZANTAO_DEFAULT_EXECUTION_TYPE='\u529f\u80fd\u6d4b\u8bd5'-eZANTAO_BASE_URL='http://127.0.0.1/zentao'-eZANTAO_PRODUCT_ID=1,3-papplication.pid-b0.0.0.0:8000-w4-D\u9700\u8981\u7684\u73af\u5883\u53d8\u91cf\u5982\u4e0b\uff1a# \u7985\u9053\u5730\u5740ZANTAO_BASE_URL='http://127.0.0.1/zentao'# \u4ea7\u54c1ID\u5217\u8868\uff0c\u9017\u53f7\u5206\u5272\u3002\u5982\u679c\u914d\u7f6e\u4e86\uff0c\u5c06\u53ea\u80fd\u770b\u5230\u914d\u7f6e\u7684\u4ea7\u54c1\u3002ZANTAO_PRODUCT_ID=1,3\u83b7\u53d6\u4ea7\u54c1ID\uff1a\u611f\u8c22\u53c2\u8003\uff1axmind2testlin xmindparser"} +{"package": "xmindconvertestlink", "pacakge-description": "No description available on PyPI."} +{"package": "xmindparser", "pacakge-description": "Documentationxmindparser is a tool to help you convert xmind file to programmable data type, e.g. json, xml.Detail usage:https://github.com/tobyqin/xmindparserChange Log1.0.9Support and test with Python 3.91.0.8Handle empty title name for xmind zen in some cases.1.0.6Keep empty topic title as null but not \u201c[Blank]\u201d1.0.5Support xmind zen file type.1.0.4Support parse label feature.1.0.2Rename config key names.1.0.1Support parse xmind to xml file type.1.0.0Support parse xmind to dict data type with Python.Support parse xmind to json file type."} +{"package": "xmindparserpro", "pacakge-description": "\u57fa\u4e8exmindparser\uff0c\u5728json\u548cdict\u8fd4\u56de\u5185\u589e\u52a0\u4e86\u8282\u70b9\u5173\u7cfb\u7ed3\u6784"} +{"package": "xmindruntestcase", "pacakge-description": 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Python \u5b9e\u73b0\uff0c\u901a\u8fc7\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\uff0c\n\u7136\u540e\u4f7f\u7528XMind\u8fd9\u6b3e\u5e7f\u4e3a\u6d41\u4f20\u4e14\u5f00\u6e90\u7684\u601d\u7ef4\u5bfc\u56fe\u5de5\u5177\u8fdb\u884c\u7528\u4f8b\u8bbe\u8ba1\u3002\n\u5176\u4e2d\u5236\u5b9a\u6d4b\u8bd5\u7528\u4f8b\u901a\u7528\u6a21\u677f\u662f\u4e00\u4e2a\u975e\u5e38\u6838\u5fc3\u7684\u6b65\u9aa4\uff08\u5177\u4f53\u8bf7\u770b\u4f7f\u7528\u6307\u5357\uff09\uff0c\u6709\u4e86\u901a\u7528\u7684\u6d4b\u8bd5\u7528\u4f8b\u6a21\u677f\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u5728 XMind \u6587\u4ef6\u4e0a\u89e3\u6790\u5e76\u63d0\u53d6\u51fa\u6d4b\u8bd5\u7528\u4f8b\u6240\u9700\u7684\u57fa\u672c\u4fe1\u606f\uff0c\n\u7136\u540e\u5408\u6210\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6240\u9700\u7684\u7528\u4f8b\u5bfc\u5165\u6587\u4ef6\u3002\u8fd9\u6837\u5c31\u5c06XMind \u8bbe\u8ba1\u6d4b\u8bd5\u7528\u4f8b\u7684\u4fbf\u5229\u4e0e\u5e38\u89c1\u6d4b\u8bd5\u7528\u4f8b\u7cfb\u7edf\u7684\u9ad8\u6548\u7ba1\u7406\u7ed3\u5408\u8d77\u6765\u4e86\uff01\u5f53\u524dXMind2TestCase\u5df2\u5b9e\u73b0\u4ece XMind \u6587\u4ef6\u5230 TestLink \u548c Zentao(\u7985\u9053) \u4e24\u5927\u5e38\u89c1\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u7684\u6d4b\u8bd5\u7528\u4f8b\u8f6c\u6362\uff0c\u540c\u65f6\u4e5f\u63d0\u4f9b XMind \u6587\u4ef6\u89e3\u6790\u540e\u7684\u4e24\u79cd\u6570\u636e\u63a5\u53e3\n\uff08TestSuites\u3001TestCases\u4e24\u79cd\u7ea7\u522b\u7684JSON\u6570\u636e\uff09\uff0c\u65b9\u4fbf\u5feb\u901f\u4e0e\u5176\u4ed6\u6d4b\u8bd5\u7528\u4f8b\u7ba1\u7406\u7cfb\u7edf\u6253\u901a\u3002\u4e8c\u3001\u4f7f\u7528\u793a\u4f8b1\u3001Web\u5de5\u5177\u793a\u4f8b2\u3001\u8f6c\u6362\u540e\u7528\u4f8b\u9884\u89c83\u3001TestLink\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b4\u3001\u7985\u9053\uff08ZenTao\uff09\u5bfc\u5165\u7ed3\u679c\u793a\u4f8b\u4e09\u3001\u5b89\u88c5\u65b9\u5f0fpip3 install xmind2testcase\npip3 install xmindtotestcase\u56db\u3001\u7248\u672c\u5347\u7ea7pip3 install -U xmind2testcase\u4e94\u3001\u4f7f\u7528\u65b9\u5f0f1\u3001\u547d\u4ee4\u884c\u8c03\u7528Usage:\n xmind2testcase [path_to_xmind_file] [-csv] [-xml] [-json]\n\nExample:\n xmind2testcase /path/to/testcase.xmind => output testcase.csv\u3001testcase.xml\u3001testcase.json\n xmind2testcase /path/to/testcase.xmind -csv => output testcase.csv\n xmind2testcase /path/to/testcase.xmind -xml => output testcase.xml\n xmind2testcase /path/to/testcase.xmind -json => output testcase.json2\u3001\u4f7f\u7528Web\u754c\u9762Usage:\n xmind2testcase [webtool] [port_num]\n\nExample:\n xmind2testcase webtool => launch the web testcase convertion tool locally -> 127.0.0.1:5001\n xmind2testcase webtool 8000 => launch the web testcase convertion tool locally -> 127.0.0.1:80003\u3001API\u8c03\u7528import json\nimport xmind\nfrom xmind2testcase.zentao import xmind_to_zentao_csv_file\nfrom xmind2testcase.testlink import xmind_to_testlink_xml_file\nfrom xmind2testcase.utils import xmind_testcase_to_json_file\nfrom xmind2testcase.utils import xmind_testsuite_to_json_file\nfrom xmind2testcase.utils import get_xmind_testcase_list\nfrom xmind2testcase.utils import get_xmind_testsuite_list\n\n\ndef main():\n xmind_file = 'docs/xmind_testcase_template.xmind'\n print('Start to convert XMind file: %s' % xmind_file)\n\n zentao_csv_file = xmind_to_zentao_csv_file(xmind_file)\n print('Convert XMind file to zentao csv file successfully: %s' % zentao_csv_file)\n\n testlink_xml_file = xmind_to_testlink_xml_file(xmind_file)\n print('Convert XMind file to testlink xml file successfully: %s' % testlink_xml_file)\n\n testsuite_json_file = xmind_testsuite_to_json_file(xmind_file)\n print('Convert XMind file to testsuite json file successfully: %s' % testsuite_json_file)\n\n testcase_json_file = xmind_testcase_to_json_file(xmind_file)\n print('Convert XMind file to testcase json file successfully: %s' % testcase_json_file)\n\n testsuites = get_xmind_testsuite_list(xmind_file)\n print('Convert XMind to testsuits dict data:\\n%s' % json.dumps(testsuites, indent=2, separators=(',', ': '), ensure_ascii=False))\n\n testcases = get_xmind_testcase_list(xmind_file)\n print('Convert Xmind to testcases dict data:\\n%s' % json.dumps(testcases, indent=4, separators=(',', ': ')))\n\n workbook = xmind.load(xmind_file)\n print('Convert XMind to Json data:\\n%s' % json.dumps(workbook.getData(), indent=2, separators=(',', ': '), ensure_ascii=False))\n\n print('Finished conversion, Congratulations!')\n\n\nif __name__ == '__main__':\n main()4\u3001XMind\u7528\u4f8b\u6587\u4ef6\u8f6c\u4e3aJSON\u6570\u636e\uff081\uff09\u8f6c\u4e3aTestCase JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testcase_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestcases = get_xmind_testcase_list(xmind_file)\nprint(testcases)\n\n\nOutput:\n\n[\n { # \u6d4b\u8bd5\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6807\u9898\n \"version\": 1, # \u7528\u4f8b\u7248\u672c\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\", # \u7528\u4f8b\u6458\u8981\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", # \u524d\u7f6e\u6761\u4ef6\n \"execution_type\": 1, # \u7528\u4f8b\u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\u30012\uff1a\u81ea\u52a8\uff09\n \"importance\": 1, # \u4f18\u5148\u7ea7\uff081\uff1a\u9ad8\u30012\uff1a\u4e2d\u30013\uff1a\u4f4e\uff09\n \"estimated_exec_duration\": 3, # \u9884\u8ba1\u6267\u884c\u65f6\u95f4\uff08\u5206\u949f\uff09\n \"status\": 7, # \u7528\u4f8b\u72b6\u6001\uff081\uff1a\u8349\u7a3f\u30012\uff1a\u5f85\u8bc4\u5ba1\u30013\uff1a\u8bc4\u5ba1\u4e2d\u30014\uff1a\u91cd\u505a\u30015\u3001\u5e9f\u5f03\u30016\uff1afeature\u30017\uff1a\u7ec8\u7a3f\uff09\n \"steps\": [ # \u6d4b\u8bd5\u6b65\u9aa4\u5217\u8868\n {\n \"step_number\": 1, # \u7f16\u53f7\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", # \u6b65\u9aa4\u5185\u5bb9\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", # \u9884\u671f\u7ed3\u679c\n \"execution_type\": 1 # \u6267\u884c\u7c7b\u578b\uff081\uff1a\u624b\u52a8\uff0c2\uff1a\u81ea\u52a8\uff09\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\" # \u6d4b\u8bd5\u96c6\uff08\u6a21\u5757\u540d\uff09\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\", \n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\", \n \"execution_type\": 1, \n \"importance\": 1, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 3, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 4, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 3, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [\n {\n \"step_number\": 1, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\", \n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\", \n \"execution_type\": 1\n }, \n {\n \"step_number\": 2, \n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\", \n \"expectedresults\": \"\", \n \"execution_type\": 1\n }\n ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }, \n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"version\": 1, \n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\", \n \"preconditions\": \"\u65e0\", \n \"execution_type\": 1, \n \"importance\": 2, \n \"estimated_exec_duration\": 3, \n \"status\": 7, \n \"steps\": [ ], \n \"product\": \"\u6211\u662f\u4ea7\u54c1\u540d\", \n \"suite\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\"\n }\n]\u6d4b\u8bd5\u7528\u4f8b\u6570\u636e\u589e\u52a0\u6267\u884c\u7ed3\u679c\u5b57\u6bb5\uff1aresult\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u8be6\u60c5\u67e5\u770b\u4f7f\u7528\u6307\u5357\uff0c\u53c2\u8003\u793a\u4f8b\uff1atestcase json\uff082\uff09\u8f6c\u4e3aTestSuite JSON\u6570\u636efrom xmind2testcase.utils import get_xmind_testsuite_list\nxmind_file = 'docs/xmind_testcase_demo.xmind'\ntestsuites = get_xmind_testsuite_list(xmind_file)\nprint(testsuites)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03\uff08Sheet)\u5217\u8868\n \"name\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4ea7\u54c1\u540d\u79f0\n \"details\": null, # \u4ea7\u54c1\u6458\u8981\n \"testcase_list\": [], # \u7528\u4f8b\u5217\u8868\n \"sub_suites\": [ # \u7528\u4f8b\u96c6\u5217\u8868\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u7528\u4f8b\u96c61\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": null, # \u7528\u4f8b\u96c6\u6458\u8981\n \"testcase_list\": [ # \u7528\u4f8b\u5217\u8868\n { # \u5177\u4f53\u7528\u4f8b\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c2\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b2\",\n \"preconditions\": \"\u524d\u7f6e\u6761\u4ef6\",\n \"execution_type\": 1,\n \"importance\": 1,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u9884\u671f\u7ed3\u679c2\u53ef\u4ee5\u4e3a\u7a7a\uff09\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 3,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c3\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 4,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa44\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c4\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u6d4b\u8bd5\u6b65\u9aa4\u548c\u9884\u671f\u7ed3\u679c\u53ef\u4ee5\u90fd\u4e3a\u7a7a\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": [] # \u7528\u4f8b\u96c6\u4e2d\u53ef\u4ee5\u5305\u542b\u5b50\u7528\u4f8b\u96c6\uff08\u76ee\u524d\u53ea\u8981\u4ea7\u54c1\u7c7b\u522b\u4e0b\u6709\u7528\u4f8b\u96c6\uff09\n },\n {\n \"name\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c62)\", # \u7528\u4f8b\u96c62\u540d\u79f0\uff08\u6a21\u5757\u540d\uff09\n \"details\": \"\u6d4b\u8bd5\u96c6\u6458\u8981\uff08\u8be6\u60c5\uff09\",\n \"testcase_list\": [\n {\n \"name\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u6b65\u9aa42\uff08\u4f18\u5148\u7ea7\u9ed8\u8ba4\u4e3a\u4e2d\uff09\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 3,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": [\n {\n \"step_number\": 1,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"expectedresults\": \"\u9884\u671f\u7ed3\u679c1\",\n \"execution_type\": 1\n },\n {\n \"step_number\": 2,\n \"actions\": \"\u6d4b\u8bd5\u6b65\u9aa43\",\n \"expectedresults\": \"\",\n \"execution_type\": 1\n }\n ]\n },\n {\n \"name\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"version\": 1,\n \"summary\": \"\u6d4b\u8bd5\u7528\u4f8b3\uff08\u524d\u7f6e\u6761\u4ef6\u9ed8\u8ba4\u4e3a\u7a7a\uff09 \u65e0\u8bbe\u7f6e\u4f18\u5148\u7ea7\uff0c\u8fd9\u91cc\u52a0\u5165\u7528\u4f8b\u6807\u9898\",\n \"preconditions\": \"\u65e0\",\n \"execution_type\": 1,\n \"importance\": 2,\n \"estimated_exec_duration\": 3,\n \"status\": 7,\n \"steps\": []\n }\n ],\n \"sub_suites\": []\n }\n ]\n }\n]TestSuite\u589e\u52a0\u6267\u884c\u7ed3\u679c\u7edf\u8ba1\u5b57\u6bb5\uff1astatistics\uff0c\u793a\u4f8b\u5982\u4e0b\uff1a\u53c2\u8003\u793a\u4f8b\uff1atestsuite json\uff083\uff09XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\u4ee5\u4e0a\uff081\uff09TestCase\u6570\u636e\u3001\uff082\uff09TestSuite\u6570\u636e\u7684\u83b7\u53d6\uff0c\u5176\u5b9e\u662f\u57fa\u4e8e**XMind**\u8fd9\u4e2a\u5de5\u5177\uff0c\u5bf9XMind\u6587\u4ef6\u8fdb\u884c\u89e3\u6790\u548c\u6570\u636e\u63d0\u53d6\uff0c\u7136\u540e\u8f6c\u6362\u800c\u6765\u3002\n\u8fd9\u4e2a\u5de5\u5177\u662f\u5728\u8bbe\u8ba1XMind2TestCase\u65f6\uff0c\u9488\u5bf9XMind\u5355\u72ec\u62bd\u53d6\u51fa\u6765\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86XMind\u601d\u7ef4\u5bfc\u56fe\u521b\u5efa\u3001\u89e3\u6790\u3001\u66f4\u65b0\u7684\u4e00\u7cfb\u5217\u65b9\u6cd5\u3002\u4f7f\u7528\u5b83\u53ef\u4ee5\u76f4\u63a5\u5c06XMind\u6587\u4ef6\u8f6c\u6362\u4e3aJSON\u6570\u636e\uff1aimport xmind\nxmind_file = 'docs/xmind_testcase_demo.xmind'\nworkbook = xmind.load(xmind_file)\ndata = workbook.getData()\nprint(data)\n\n\nOutput:\n\n[\n { # XMind\u753b\u5e03(sheet)\u5217\u8868\n \"id\": \"7hmnj6ahp0lonp4k2hodfok24f\", # \u753b\u5e03ID\n \"title\": \"\u753b\u5e03 1\", # \u753b\u5e03\u540d\u79f0\n \"topic\": { # \u4e2d\u5fc3\u4e3b\u9898\n \"id\": \"7c8av5gt8qfbac641lth4g1p67\", # \u4e3b\u9898ID\n \"link\": null, # \u4e3b\u9898\u4e0a\u7684\u8d85\u94fe\u63a5\u4fe1\u606f\n \"title\": \"\u6211\u662f\u4ea7\u54c1\u540d\", # \u4e3b\u9898\u540d\u79f0\n \"note\": null, # \u4e3b\u9898\u4e0a\u7684\u5907\u6ce8\u4fe1\u606f\n \"label\": null, # \u4e3b\u9898\u4e0a\u6807\u7b7e\u4fe1\u606f\n \"comment\": null, # \u4e3b\u9898\u4e0a\u7684\u6279\u6ce8\uff08\u8bc4\u8bba\uff09\u4fe1\u606f\n \"markers\": [], # \u4e3b\u9898\u4e0a\u7684\u56fe\u6807\u4fe1\u606f\n \"topics\": [ # \u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"2rj4ek3nn4sk0lc4pje3gvgv9k\",\n \"link\": null,\n \"title\": \"\u6211\u662f\u6a21\u5757\u540d(\u6d4b\u8bd5\u96c61)\", # \u5b50\u4e3b\u98981\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [ # \u5b50\u4e3b\u9898\u4e0b\u7684\u5b50\u4e3b\u9898\u5217\u8868\n {\n \"id\": \"3hjj43s7rv66uncr1srl3qsboi\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u7528\u4f8b1\",\n \"note\": \"\u524d\u7f6e\u6761\u4ef6\\n\",\n \"label\": \"\u624b\u52a8\uff08\u6267\u884c\u65b9\u5f0f\u9ed8\u8ba4\u4e3a\u624b\u52a8\uff09\",\n \"comment\": null,\n \"markers\": [\n \"priority-1\"\n ],\n \"topics\": [\n {\n \"id\": \"3djn37j1fdc6081de319slf035\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa41\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"7v0f1152popou38ndaaamt49l5\",\n \"link\": null,\n \"title\": \"\u9884\u671f\u7ed3\u679c1\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": []\n }\n ]\n },\n {\n \"id\": \"2srtqqjp818clkk1drm233lank\",\n \"link\": null,\n \"title\": \"\u6d4b\u8bd5\u6b65\u9aa42\",\n \"note\": null,\n \"label\": null,\n \"comment\": null,\n \"markers\": [],\n \"topics\": [\n {\n \"id\": \"4jlbo280urmid3qkd01j7h8jnq\",\n \"link\": null,\n \"title\": 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License\n\nCopyright (c) 2019 Devin https://zhangchuzhao.site\nCopyright (c) 2017 Toby Qin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xminds", "pacakge-description": "See ourreadthedocsfor the Python Data Science library documentation.See theAPI Documentationfor the Crossing Minds universal recommendation API documentation.Our tools are licensed under the MIT License."} +{"package": "xmind-sdk", "pacakge-description": "XMind SDK for python=====**XMind SDK for python** to help Python developers to easily work with XMind files and build XMind extensions.Install XMind SDK for python---Clone the repository to a local working directory> `git clone https://github.com/xmindltd/xmind-sdk-python.git`Now there will be a directory named `xmind-sdk-python` under the current directory. Change to the directory `xmind-sdk-python` and install **XMind SDK for python**.> `python setup.py install`*It is highly recommended to install __XMind SDK for python__ under an isolated python environment using [virtualenv](https://pypi.python.org/pypi/virtualenv)*Usage----Open an existing XMind file or create a new XMind file and place it into a given path> `import xmind`>> `workbook = xmind.load(/path/to/file/) # Requires '.xmind' extension`Save XMind file to a path.If the path is not given then the API will save to the path set in the workbook> `xmind.save(workbook)`or:> `xmind.save(workbook, /save/file/to/path)`UML diagram----Diagram![click](https://raw.githubusercontent.com/andrii-z4i/xmind-sdk-python/master/docs/Xmind-Sdk.png \"Diagram\")Tests---From root directory run> `python test.py`Get coverage report---Install coverage package> `pip install coverage`Run tests under coverage> `coverage run --source=xmind.core test.py`Check coverage report> `coverage report`or> `coverage html -d coverage_html`to have rich visualisationLICENSE---The MIT License (MIT)Copyright (c) 2013 XMind, LtdPermission is hereby granted, free of charge, to any person obtaining a copy ofthis software and associated documentation files (the \"Software\"), to deal inthe Software without restriction, including without limitation the rights touse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies ofthe Software, and to permit persons to whom the Software is furnished to do so,subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESSFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS ORCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHERIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR INCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."} +{"package": "xmind-sdk-python-fileobj", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmind-sdk-python-upload-file", "pacakge-description": "XMind SDK for python=====**XMind SDK for python** to help Python developers to easily work with XMind files and build XMind extensions.Install XMind SDK for python---Clone the repository to a local working directory> `git clone https://github.com/xmindltd/xmind-sdk-python.git`Now there will be a directory named `xmind-sdk-python` under the current directory. Change to the directory `xmind-sdk-python` and install **XMind SDK for python**.> `python setup.py install`*It is highly recommended to install __XMind SDK for python__ under an isolated python environment using [virtualenv](https://pypi.python.org/pypi/virtualenv)*Usage----Open an existing XMind file or create a new XMind file and place it into a given path> `import xmind`>> `workbook = xmind.load(/path/to/file/) # Requires '.xmind' extension`> `workbook = xmind.load(file_object)` # support '.xmind' file uploadsSave XMind file to a path.If the path is not given then the API will save to the path set in the workbook> `xmind.save(workbook)`or:> `xmind.save(workbook, /save/file/to/path)`Tests---From root directory run> `python test.py`Get coverage report---Install coverage package> `pip install coverage`Run tests under coverage> `coverage run --source=xmind.core test.py`Check coverage report> `coverage report`or> `coverage html -d coverage_html`to have rich visualisationLICENSE---The MIT License (MIT)Copyright (c) 2013 XMind, LtdPermission is hereby granted, free of charge, to any person obtaining a copy ofthis software and associated documentation files (the \"Software\"), to deal inthe Software without restriction, including without limitation the rights touse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies ofthe Software, and to permit persons to whom the Software is furnished to do so,subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESSFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS ORCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHERIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR INCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."} +{"package": "xmind-switch", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmind-switch2", "pacakge-description": "No description available on PyPI."} +{"package": "xmind-to-testlink", "pacakge-description": "XmindToTestlink is a tool to help you convert xmindzen file to testlink recognized xml files,\nthen you can import it into testlink as test suite , test cases and requirement.For more detail, please go to:https://github.com/DancePerth/XmindToTestlink"} +{"package": "xminigrid", "pacakge-description": "XLand-MiniGridMeta-Reinforcement Learning in JAX\ud83e\udd73XLand-MiniGrid wasacceptedtoIntrinsically Motivated Open-ended Learningworkshop at NeurIPS 2023.We look forward to seeing everyone at the poster session!XLand-MiniGridis a suite of tools, grid-world environments and benchmarks for meta-reinforcement learning research inspired by\nthe diversity and depth ofXLandand the simplicity and minimalism ofMiniGrid. Despite the similarities,\nXLand-MiniGrid is written in JAX from scratch and designed to be highly scalable, democratizing large-scale experimentation\nwith limited resources. Ever wanted to reproduce aDeepMind AdAagent? Now you can and not in months, but days!Features\ud83d\udd2e System of rules and goals that can be combined in arbitrary ways to produce\ndiverse task distributions\ud83d\udd27 Simple to extend and modify, comes with example environments ported from the originalMiniGrid\ud83e\ude84 Fully compatible with all JAX transformations, can run on CPU, GPU and TPU\ud83d\udcc8 Easily scales to $2^{16}$ parallel environments and millions of steps per second on a single GPU\ud83d\udd25 Multi-GPU PPO baselines in thePureJaxRLstyle, which can achieve1 trillionenvironment steps under two daysHow cool is that? For more details, take a look at thetechnical paperorexamples, which will walk you through the basics and training your own adaptive agents in minutes!Installation \ud83c\udf81\u26a0\ufe0f XLand-MiniGrid is currently in alpha stage, so expect breaking changes! \u26a0\ufe0fThe latest release of XLand-MiniGrid can be installed directly from PyPI:pip install xminigrid\n# or, from github directly\npip install \"xminigrid @ git+https://github.com/corl-team/xland-minigrid.git\"Alternatively, if you want to install the latest development version from the GitHub and run provided algorithms or scripts,\ninstall the source as follows:git clone git@github.com:corl-team/xland-minigrid.git\ncd xland-minigrid\n# additional dependencies for baselines\npip install -e \".[dev,benchmark]\"Note that the installation of JAX may differ depending on your hardware accelerator!\nWe advise users to explicitly install the correct JAX version (see theofficial installation guide).Basic Usage \ud83d\udd79\ufe0fMost users who are familiar with other popular JAX-based environments\n(such asgymnaxorjumnaji),\nwill find that the interface is very similar.\nOn the high level, current API combinesdm_envand gymnax interfaces.importjaximportxminigridfromxminigrid.wrappersimportGymAutoResetWrapperkey=jax.random.PRNGKey(0)reset_key,ruleset_key=jax.random.split(key)# to list available benchmarks: xminigrid.registered_benchmarks()benchmark=xminigrid.load_benchmark(name=\"trivial-1m\")# choosing ruleset, see section on rules and goalsruleset=benchmark.sample_ruleset(ruleset_key)# to list available environments: xminigrid.registered_environments()env,env_params=xminigrid.make(\"XLand-MiniGrid-R9-25x25\")env_params=env_params.replace(ruleset=ruleset)# auto-reset wrapperenv=GymAutoResetWrapper(env)# fully jit-compatible step and reset methodstimestep=jax.jit(env.reset)(env_params,reset_key)timestep=jax.jit(env.step)(env_params,timestep,action=0)# optionally render the stateenv.render(env_params,timestep)Similar to gymnasium or jumanji, users can register new environment\nvariations withregisterfor convenient further usage withmake.timestepis a dataclass containingstep_type,reward,discount,observation, as well as the internal environmentstate.For a bit more advanced introduction see providedwalkthrough notebook.On environment interfaceCurrently, there are a lot of new JAX-based environments appearing, each offering its own variant of API. Initially, we tried to reuse Jumaji, but it turned out\nthat its designis not suitable for meta learning. The Gymnax design appeared to be more appropriate, but unfortunately it is not actively supported and\noften departs from the idea that parameters should only be contained inenv_params. Furthermore, splittingtimestepinto multiple entities seems suboptimal to us, as it complicates many things, such as envpool or dm_env\nstyle auto reset, where the reset occurs on the next step (we need access to done of previous step).Therefore, we decided that we would make a minimal interface that would cover just our needs without the\ngoal of making it generic. The core of our library is interface independent, and we plan\nto switch to the new one when/if a better design becomes available\n(e.g. when stable GymnasiumFuncEnvis released).Rules and Goals \ud83d\udd2eIn XLand-MiniGrid, the system of rules and goals is the cornerstone of the\nemergent complexity and diversity. In the original MiniGrid\nsome environments have dynamic goals, but the dynamics are never changed.\nTo train and evaluate highly adaptive agents, we need to be able to change\nthe dynamics in non-trivial ways.Rulesare the functions that can change the environment state in some deterministic\nway according to the given conditions.Goalsare similar to rules, except they do\nnot change the state, they only test conditions. Every task should be described with a goal, rules and initial objects. We call theserulesets.\nCurrently, we support only one goal per task.To illustrate, we provide visualization for specific ruleset. To solve this task, agent should take blue pyramid and put it near the purple square to transform both\nobjects into red circle. To complete the goal, red circle should be placed near\ngreen circle. However, placing purple square near yellow circle will make it unsolvable in this trial. Initial objects positions will be randomized on each reset.For more advanced introduction, see corresponding section in the providedwalkthrough notebook.Benchmarks \ud83c\udfb2While composing rules and goals by hand is flexible, it can quickly become cumbersome.\nBesides, it's hard to express efficiently in a JAX-compatible way due to the high number of heterogeneous computationsTo avoid significant overhead during training and facilitate reliable comparisons between agents,\nwe pre-sampled several benchmarks with up tothree million unique tasks, following the procedure used to train DeepMind\nAdA agent from the original XLand. These benchmarks differ in the generation configs, producing distributions with\nvarying levels of diversity and average difficulty of the tasks. They can be used for different purposes, for example\nthetrivial-1mbenchmark can be used to debug your agents, allowing very quick iterations. However, we would caution\nagainst treating benchmarks as a progression from simple to complex. They are just different \ud83e\udd37.Pre-sampled benchmarks are hosted onHuggingFaceand will be downloaded and cached on the first use:importjax.randomimportxminigridfromxminigrid.benchmarksimportBenchmark# downloading to path specified by XLAND_MINIGRID_DATA,# ~/.xland_minigrid by defaultbenchmark:Benchmark=xminigrid.load_benchmark(name=\"trivial-1m\")# reusing cached on the second usebenchmark:Benchmark=xminigrid.load_benchmark(name=\"trivial-1m\")# users can sample or get specific rulesetsbenchmark.sample_ruleset(jax.random.PRNGKey(0))benchmark.get_ruleset(ruleset_id=benchmark.num_rulesets()-1)# or split them for train & testtrain,test=benchmark.shuffle(key=jax.random.PRNGKey(0)).split(prop=0.8)We also provide thescriptused to generate these benchmarks. Users can use it for their own purposes:python scripts/ruleset_generator.py --helpIn depth description of all available benchmarks is providedin the technical paper(Section 3).P.S.Be aware, that benchmarks can change, as we are currently testing and balancing them!Environments \ud83c\udf0dWe provide environments from two domains.XLandis our main focus for meta-learning. For this domain we provide single\nenvironment and numerous registered variants with different grid layouts and sizes. All of them can be combined\nwith arbitrary rulesets.To demonstrate the generality of our library we also port majority of\nnon-language based tasks from originalMiniGrid. Similarly, some environments come with multiple registered variants.\nHowever, we have no current plans to actively develop and support them (but that may change).NameDomainVisualizationGoalXLand-MiniGridXLandspecified by the provided rulesetMiniGrid-EmptyMiniGridgo to the green goalMiniGrid-EmptyRandomMiniGridgo the green goal from different starting positionsMiniGrid-FourRoomsMiniGridgo the green goal, but goal and starting positions are randomizedMiniGrid-LockedRoomMiniGridfind the key to unlock the door, go to the green goalMiniGrid-MemoryMiniGridremember the initial object and choose it at the end of the corridorMiniGrid-PlaygroundMiniGridgoal is not specifiedMiniGrid-UnlockMiniGridunlock the door with the keyMiniGrid-UnlockPickUpMiniGridunlock the door and pick up the object in another roomMiniGrid-BlockedUnlockPickUpMiniGridunlock the door blocked by the object and pick up the object in another roomMiniGrid-DoorKeyMiniGridunlock the door and go to the green goalUsers can get all registered environments withxminigrid.registered_environments(). We also provide manual control to easily explore the environments:python -m xminigrid.manual_control --env-id=\"MiniGrid-Empty-8x8\"Baselines \ud83d\ude80In addition to the environments, we provide high-qualityalmostsingle-file\nimplementations of recurrent PPO baselines in the style ofPureJaxRL. With the help of magicaljax.pmaptransformation\nthey can scale to multiple accelerators, achieving impressive FPS of millions during training.Agents can be trained from the terminal and default arguments can be overwritten from the command line or from the yaml config:# for meta learning\npython training/train_meta_task.py \\\n --config-path='some-path/config.yaml' \\\n --env_id='XLand-MiniGrid-R1-9x9'\n\n# for minigrid envs\npython training/train_singe_task.py \\\n --config-path='some-path/config.yaml' \\ \n --env_id='XLand-MiniGrid-R1-9x9'For the source code and hyperparameters available see/trainingor runpython training/train_meta_task.py --help.\nFurthermore, we provide standalone implementations that can be trained in Colab:xland,minigrid.P.S.Do not expect that provided baselines will solve the hardest environments or benchmarks\navailable. How much fun would that be \ud83e\udd14? However, we hope that they will\nhelp to get started quickly!Contributing \ud83d\udd28We welcome anyone interested in helping out! Please take a look at ourcontribution guidefor further instructions and open an issue if something is not clear.See Also \ud83d\udd0eA lot of other work is going in a similar direction, transforming RL through JAX. Many of them have inspired us,\nand we encourage users to check them out as well.Brax- fully differentiable physics engine used for research and development of robotics.Gymnax- implements classic environments including classic control, bsuite, MinAtar and simplistic meta learning tasks.Jumanji- a diverse set of environments ranging from simple games to NP-hard combinatorial problems.Pgx- JAX implementations of classic board games, such as Chess, Go and Shogi.JaxMARL- multi-agent RL in JAX with wide range of commonly used environments.Let's build together!Citation \ud83d\ude4f@inproceedings{nikulin2023xlandminigrid,title={{XL}and-MiniGrid: Scalable Meta-Reinforcement Learning Environments in {JAX}},author={Alexander Nikulin and Vladislav Kurenkov and Ilya Zisman and Viacheslav Sinii and Artem Agarkov and Sergey Kolesnikov},booktitle={Intrinsically-Motivated and Open-Ended Learning Workshop, NeurIPS2023},year={2023},url={https://openreview.net/forum?id=xALDC4aHGz}}"} +{"package": "xmip", "pacakge-description": "Science is not immune to racism. Academia is an elitist system with numerous gatekeepers that has mostly allowed a very limited spectrum of people to pursue a career. I believe we need to change that.Open source development and reproducible science are a great way to democratize the means for scientific analysis.But you can't git clone software if you are being murdered by the police for being Black!Free access to software and hollow diversity statements are hardly enough to crush the systemic and institutionalized racism in our society and academia.If you are using this package, I ask you to go beyond just speaking out and donateheretoData for Black LivesandBlack Lives Matter Action.I explicitly welcome suggestions regarding the wording of this statement and for additional organizations to support. Please raise anissuefor suggestions.xmip (formerly cmip6_preprocessing)This package facilitates the cleaning, organization and interactive analysis of Model Intercomparison Projects (MIPs) within thePangeosoftware stack.Are you interested in CMIP6 data, but find that is is not quiteanalysis ready? Do you just want to run a simple (or complicated) analysis on various models and end up having to write logic for each seperate case, because various datasets still require fixes to names, coordinates, etc.? Then this package is for you.Developed during thecmip6-hackathonthis package provides utility functions that play nicely withintake-esm.We currently support the following functionsPreprocessing CMIP6 data (Please check out thetutorialfor some examples using thepangeo cloud). The preprocessig includes:\na. Fix inconsistent naming of dimensions and coordinates\nb. Fix inconsistent values,shape and dataset location of coordinates\nc. Homogenize longitude conventions\nd. Fix inconsistent unitsCreating large scale ocean basin masks for arbitrary model outputThe following issues are under development:Reconstruct/find grid metricsArrange different variables on their respective staggered grid, so they can work seamlessly withxgcmCheck out this recent Earthcubenotebook(cite via doi:10.1002/essoar.10504241.1) for a high level demo ofxmipandxgcm.InstallationInstallxmipvia pip:pip install xmipor conda:conda install -c conda-forge xmipTo install the newest main from github you can use pip aswell:pip install git+pip install git+https://github.com/jbusecke/xmip.git"} +{"package": "xmiparser", "pacakge-description": "An API for files in the XML formatXMIdefined byOMGto store UML.This is the standalone version of the xmiparser. It was formerly part of\ntheArchGenXMLcode generator.ContentsChangelog1.5 (2010-09-04)1.4 (2009-03-29)DownloadChangelog1.5 (2010-09-04)Re-added sample .zargo file from the past, the tests run again.\n[moldy]Replaced buggy odict implementation by the ordereddict implementation\navailable in Python 2.7.\n[moldy]Removed DeprecationWarning about the sets module.\n[vincentfretin]By default search in current directory for profile.\n[jensens]1.4 (2009-03-29)Search profiles in directories configured with ArgoUML (read the ~/.argouml/argo.user.properties file)\nYou don\u2019t need to specify the -p option with archgenxml anymore.\n[vincentfretin]Download"} +{"package": "xmipp-metadata", "pacakge-description": "Xmipp Metadata HandlerThis package implements a Xmipp Metadata handling functionality with image binary accession in Python.Included functionalitiesXmippMetadataclass: Reading and writing of Xmipp Metadata files (.xmd)ImageHandlerclass: Reading and writing of image binaries stored in the metadata. It support the following formats:MRC files (reading and writing) for stacks and volumes (.mrcs and .mrc)Spider files (reading and writing) for stacks and volumes (.stk and .vol)EM files (reading and writing) for stack and images (.ems and .em)"} +{"package": "xmipy", "pacakge-description": "xmipyxmipyis an extension tobmipyincluding an implementation of the abstract methods.\nThe extended interface is required to couple certain hydrological kernels, particularly MODFLOW 6. Currently it is a joint development of the USGS and Deltares. Theimod_coupleruses it, for example, to couple Modflow 6 and MetaSWAP.xmipycan be installed by runningpip install xmipyContributingIn order to develop onxmipylocally, execute the following line inside your virtual environmentpipinstall-e\".[tests, lint, docs]\""} +{"package": "xmi-reader", "pacakge-description": "NETDATA, AWSTAPE and HET File Python LibraryOpen and extract (unload) XMI/AWS/HET mainframe files.InstallationYou can install thexmilibrary from PyPI using:python3 -m pip install xmi-readerHow to UseThe most simple way to use this library is to import this module and usexmi.open_file()to open an XMI, AWS, or HET file::importxmixmi_obj=xmi.open_file(\"/path/to/file.xmi\")het_obj=xmi.open_file(\"/path/to/file.het\")aws_obj=xmi.open_file(\"/path/to/file.aws\")To list all datasets and dataset members::forfinhet_obj.get_files():ifhet_obj.is_pds(f):forminhet_obj.get_members(f):print(\"{}({})\".format(f,m))else:print(f)Print JSON metatdata::print(xmi_obj.get_json())print(het_obj.get_json(text=True))# Adds plaintext files to json outputprint(aws_obj.get_json(indent=6))# Increases the json indentSilently extract all files/folders to/tmp/xmi_files/::aws_obj.set_output_folder(\"/tmp/xmi_files/\")aws_obj.set_quiet(True)aws_obj.extract_all()Print detailed file information::xmi_obj.print_details()xmi_obj.print_xmit()# Same output as previous, print_xmit() is an alias to print_details()het_obj.print_tape()# print_tape() is an alias to print_details()aws_obj.print_tape(human=True)# Converts size to human readablePrint message:ifxmi_obj.has_message():print(xmi_obj.get_message())# or justprint(xmi_obj.get_message())# Prints 'None' if no messageIf you you're having problems with the library or want to see whats happening\nbehind the scenes you can enable debugging:importloggingimportxmixmi_obj=xmi.XMIT(filename=\"/path/to/file.xmi\",loglevel=logging.DEBUG)xmi_obj.open()More InformationDocumentationInstallationAPIXMI File formatAWS/HET File formatIEBCOPY File formatIssuesPull requests"} +{"package": "xmisc", "pacakge-description": "Xiaobei\u2019s miscellaneous classes and functionsExample: \u201cHello World\u201d in Xmiscfromxmisc.graphicsimporthelloworldhelloworld.demo()Run this script or paste it into a Python console.Download and InstallGitHub PyPI Dependenciesnose setuptools>=33.1.1 numpy>=1.11.3 pandas>=0.19.2 tabulate>=0.7.5 matplotlib>=2.0.0 LicenseCode and documentation are available according to the GNU LGPL License."} +{"package": "xmitgcm", "pacakge-description": "xmitgcm is a python package for readingMITgcmbinary MDS files intoxarraydata structures. By storing data indaskarrays, xmitgcm enables\nparallel,out-of-coreanalysis of MITgcm output data.LinksHTML documentation:https://xmitgcm.readthedocs.orgIssue tracker:https://github.com/MITgcm/xmitgcm/issuesSource code:https://github.com/MITgcm/xmitgcmInstallationRequirementsxmitgcm is compatible with python >=3.7. It requiresxarray(>= version 0.11.0) anddask(>= version 1.0).\nThese packages are most reliably installed via thecondaenvironment management\nsystem, which is part of theAnacondapython distribution. Assuming you have\nconda available on your system, the dependencies can be installed with the\ncommand:conda install xarray daskIf you are using earlier versions of these packages, you should update before\ninstalling xmitgcm.Installation via pipIf you just want to use xmitgcm, the easiest way is to install via pip:pip install xmitgcmThis will automatically install the latest release frompypi.Installation from githubxmitgcm is under active development. To obtain the latest development version,\nyou may clone thesource repositoryand install it:git clone https://github.com/MITgcm/xmitgcm.git\ncd xmitgcm\npython setup.py installUsers are encouraged toforkxmitgcm and submitissuesandpull requests.Quick StartFirst make sure you understand what anxarrayDataset object is. Then find\nsome MITgcm MDS data. If you don\u2019t have any data of your own, you can download\nthe xmitgcmtest repositoriesTo download the some test data, run the shell commands:$ curl -L -J -O https://ndownloader.figshare.com/files/6494718\n$ tar -xvzf global_oce_latlon.tar.gzThis will create a directory calledglobal_oce_latlonwhich we will use\nfor the rest of these examples. If you have your own data, replace this with\nthe path to your mitgcm files.To open MITgcm MDS data as an xarray.Dataset, do the following in python:from xmitgcm import open_mdsdataset\ndata_dir = './global_oce_latlon'\nds = open_mdsdataset(data_dir)data_dir, should be the path (absolute or relative) to an\nMITgcm run directory. xmitgcm will automatically scan this directory and\ntry to determine the file prefixes and iteration numbers to read. In some\nconfigurations, theopen_mdsdatasetfunction may work without further\nkeyword arguments. In most cases, you will have to specify further details.Consult theonline documentationfor\nmore details."} +{"package": "xmixers", "pacakge-description": "Xmixers: A collection of SOTA efficient token/channel mixers"} +{"package": "xmjson", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xml2ajson", "pacakge-description": "xml To jsonuse\uff1a\npip install xml2ajson\nfrom xml2ajson import getFromXmlDirgetFromXmlDir(your xml directory)"} +{"package": "xml2csv", "pacakge-description": "UNKNOWN"} +{"package": "xml2data", "pacakge-description": "xml2data is a library for converting xml into native data, according to css-selector like template.RequirementsPython 2.7Examplethe following convertsa webpagecontaining some app information:import xml2data\ntemplate = \"\"\"{\n 'apps': [div#main-container div.section:first-child div.goods-container div.goods @ {\n 'name': div.top span.name,\n 'url': div.top span.name a $[href],\n 'description': div.goods div.bottom\n }],\n 'author': div#main-container div.section div.text p a:first-child $text,\n 'twitter': div#main-container div.section div.text p a:nth-child(2) $[href]\n}\"\"\"\ndata = xml2data.urlload('http://hp.vector.co.jp/authors/VA038583/', template)results:data == {\n 'apps': [{\n 'name': 'copipex',\n 'url': './down/copipex023.zip',\n 'description': '<\u30b3\u30d4\u30fc\u21d2\u8cbc\u4ed8\u3051> \u304c <\u30de\u30a6\u30b9\u3067\u7bc4\u56f2\u9078\u629e\u21d2\u30af\u30ea\u30c3\u30af> \u3067\u53ef\u80fd\u306b'\n }, {\n 'name': 'gummi',\n 'url': './gummi.html',\n 'description': '\u30a6\u30a3\u30f3\u30c9\u30a6\u306e\u4efb\u610f\u306e\u90e8\u5206\u3092\u5225\u7a93\u306b\u8868\u793a\u3002\u64cd\u4f5c\u3082\u53ef\u80fd'\n }, {\n 'name': 'PAWSE',\n 'url': './down/pawse032.zip',\n 'description': 'Pause\u30ad\u30fc\u3067\u3001\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u4e00\u6642\u505c\u6b62\u3001\u5b9f\u884c\u901f\u5ea6\u306e\u5236\u9650\u304c\u53ef\u80fd\u306b'\n }, {\n 'name': 'onAir',\n 'url': './onair.html',\n 'description': '\u73fe\u5728\u653e\u9001\u4e2d\u306e\u30c6\u30ec\u30d3\u756a\u7d44\u306e\u30bf\u30a4\u30c8\u30eb\u3092\u4e00\u89a7\u8868\u793a'\n }],\n 'author': 'slay',\n 'twitter': 'http://twitter.com/slaypni'\n}"} +{"package": "xml2ddl", "pacakge-description": "XML to DDL is a set of Python programs that converts an XML representation of a database into a set of SQL (or DDL commands - Data Definition Language) commands.\nAlso, you can download the XML metadata directly from your existing database.\nOther tools exist to examine the difference between two XML schemas and output a sequence of SQL statements\nto change from one to the other (normally via ALTER statements).\nThere is also a tool to create HTML documentation from the XML.\nXML to DDL supports PostgreSQL, MySQL, Oracle and Firebird databases."} +{"package": "xml2df", "pacakge-description": "xml2dfConvert XML file to a pandas dataframe. This package flattens the XML structure and creates a list of dictionaries that is then transformed to a dataframe.requirement: pandasThe code is available in the xml2df.py\nRunning the file will allow you to process the example.xml file:def main():\ndocument = ET.parse(\"example.xml\")# batched elements is a list containing all the nodes who's children are of the same instance\n\nbatched_elements = [\"publish_date\", \"author_details\"]\n\ndf_result = xml2df(document, \"book\", batched_elements)\nprint(df_result.head(5))The file contains several functions to process your XML file. Please find the descriptions below:xml2df function:This function runs the xml_flatten function to supply us with a flat structure result, the result of the xml_flatten function is then\n modified to join all existing lists to strings. If you do not need this final modification, please consider using the xml_flatten\n function instead which takes the same arguments.\nxml_document: the xml document to be processed\nroot_node: specify the root node to begin drilldown\nbatched_elements: as described in info allows you to identify batched nodes. For batched nodes, the xml.text is requested for all its\n child nodes. If any child nodes have their own children, this function will iter over all children and get their texts as well.\n Please note that when a the children have their own child node, they will ALSO be treated as a regular node and get their own values\n in a separate column.\n example:\n \n \n 2020\n 05\n 11\n \n \n 2020\n 05\n 11\n \n \n John Doe\n \n \n To keep the subinstances of publication date as a whole, \"publication_date\" must be added to the batched_elements list\n leave empty if you don't need this\nunique_results: default set to True, set to False if you need to get all results and not only unique results (applies set function)\njoin_separator: default set to \";\". modify this if you want the lists to be joined with any other separatorxml_flatten function:This function, given the root node, will drill down the elements and flatten the xml.\nxml_document: the xml document to be processed\nroot_node: specify the root node to begin drilldown\nbatched_elements: as described in info allows you to identify batched nodes. For batched nodes, the xml.text is requested for all its\n child nodes. If any child nodes have their own children, this function will iter over all children and get their texts as well.\n Please note that when a the children have their own child node, they will ALSO be treated as a regular node and get their own values\n in a separate columnget_flat_children function:This function will simply iterate over every node until there are no child nodes found. At this point the function will\n create a dictionary that saves the value of the node text along with the full attribute (name=value).\n format is then {\"nodeparent_nodechild\": \"attribute_name=attribute_value|node_text\"}. \n Please note that only attributes belonging to the leaves (nodes without children) is retrieved. in case of batched \n elements the attributes of the batch node are retrieved.\nbatched_elements: please refer to the full explanation in xml2df function.\nresult_dict: dictionary to aggregates the results.\nroot: initially, the value supplied will be used to start the drilldown. when this function calls itself, the root will be changed\n to its children.\nprev_root: default set to empty string. do not modify unless you want all column names to start with a given string.\nattribute_separator: default set to \"|\". This separator is used to explicitly distinguish attributes from values in the final string.\nbatch_result_separator: default set to \" - \". This value can be modified to change the join string on the batched results."} +{"package": "xml2dictionary", "pacakge-description": "xml2dictionaryxml2dictionary is a package that converts any xml to json (dict)RequirementsPython 3.8PipenvInstallationpipinstallxml2dictionaryUsageExamplefromxml2dictionaryimportxml2dictionary\nwithopen('tests/sample.xml','r')asf:m=f.read()result=xml2dictionary(m)OrderedDict([('breakfast_menu',OrderedDict([('food',[OrderedDict([('name','Belgian Waffles'),('price','$5.95'),('description','Two of our famous Belgian Waffles with plenty of real maple syrup'),('calories','650')]),OrderedDict([('name','Strawberry Belgian Waffles'),('price','$7.95'),('description','Light Belgian waffles covered with strawberries and whipped cream'),('calories','900')]),OrderedDict([('name','Berry-Berry Belgian Waffles'),('price','$8.95'),('description','Light Belgian waffles covered with an assortment of fresh berries and whipped cream'),('calories','900')]),OrderedDict([('name','French Toast'),('price','$4.50'),('description','Thick slices made from our homemade sourdough bread'),('calories','600')]),OrderedDict([('name','Homestyle Breakfast'),('price','$6.95'),('description','Two eggs, bacon or sausage, toast, and our ever-popular hash browns'),('calories','950')])])]))])Functionsparse-parsesxmlstringtodictionary\nclear_signs-clearsparsedxmlfrompropswith`sign`,shifts`shift`,escapes`scape`json_to_xml-convertsjsontoxml\nxml2json-usesparse&clear_signs"} +{"package": "xml2dictnitrate", "pacakge-description": "# XML2DictXML2Dict is an open source python library, which used for converting python dict and XML type.XML2Dict is licensed under the [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0.html)XML2Dict is inspired from Chen Zheng\u2019s [xml2dict](http://github.com/nkchenz/xml2dict/tree)## ExamplePlease see source test case## AttentionXML2Dict do not test for all cases now, if you find any bug please issue an report.## Thanks\nFixed parse error when tag has empty content [snwilhelm](https://gist.github.com/1209773)Fix MANIFEST.in syntax to avoid creating broken distributions; bump version to 0.2.2 [slinkp](https://github.com/mcspring/XML2Dict/pull/2)## AboutXML2Dict is written by [Sprint Mc](https://github.com/mcspring).And you can follow me on [Twitter](http://twitter.com/mcspring)!"} +{"package": "xml2epub", "pacakge-description": "xml2epubBatch convert multiple web pages, html files or images into one e-book.Features:Automatically generate cover: If thetext in html is one ofCOVER_TITLE_LIST,\nthen the cover will be added automatically, otherwise the default cover will be generated. We will randomly generate the cover image with a similar \"O'Reilly\" style.Automatically obtain the core content of the article: we filter the obtained html string and retain the core content. SeeSUPPORTED_TAGSfor a list of tags reserved in html.ToCHow to installBasic UsageAPITipsFAQHow to installxml2epubis available on pypihttps://pypi.org/project/xml2epub/$ pip install xml2epubBasic Usageimportxml2epub## create an empty eBookbook=xml2epub.Epub(\"My New E-book Name\")## create chapters by url#### custom your own cover imagechapter0=xml2epub.create_chapter_from_string(\"https://cdn.jsdelivr.net/gh/dfface/img0@master/2022/02-10-0R7kll.png\",title='cover',strict=False)#### create chapter objectschapter1=xml2epub.create_chapter_from_url(\"https://dev.to/devteam/top-7-featured-dev-posts-from-the-past-week-h6h\")chapter2=xml2epub.create_chapter_from_url(\"https://dev.to/ks1912/getting-started-with-docker-34g6\")## add chapters to your eBookbook.add_chapter(chapter0)book.add_chapter(chapter1)book.add_chapter(chapter2)## generate epub filebook.create_epub(\"Your Output Directory\")After waiting for a while, if no error is reported, the following \"My New E-book Name.epub\" file will be generated in \"Your Output Directory\":For moreexamples, see:examplesdirectory.If we cannot infer the cover image from html string, we will generate one. The randomly generated cover image is a similar \"O'Reilly\" style:APIcreate_chapter_from_file(file_name, url=None, title=None, strict=True, local=False): Create a Chapter object from an html or xhtml file.file_name (string): The filename containing the html or xhtml content of the created chapter.url (Option[string]): The url used to infer the chapter title. It is recommended to bring theurlparameter, which helps to identify relative links in the web page.title (Option[string]): The chapter name of the chapter, if None, the content of the title tag obtained from the web file will be used as the chapter name.strict (Option[boolean]): Whether to perform strict page cleaning, which will remove inline styles, insignificant attributes, etc., generally True.local (Option[boolean]): Whether to use local resources, which means that all images and css files in html have been saved locally, and the resources will be copied directly using the file path in html instead of getting them from the Internet.create_chapter_from_url(url, title=None, strict=True, local=False): Create a Chapter object by extracting webpage from given url.url (string): website link. It is recommended to bring theurlparameter, which helps to identify relative links in the web page.title (Option[string]): The chapter name of the chapter, if None, the content of the title tag obtained from the web file will be used as the chapter name.strict (Option[boolean]): Whether to perform strict page cleaning, which will remove inline styles, insignificant attributes, etc., generally True. When False, you can enter an image link and specify title, which is helpful for custom cover image.local (Option[boolean]): Whether to use local resources, which means that all images and css files in html have been saved locally, and the resources will be copied directly using the file path in html instead of getting them from the Internet.create_chapter_from_string(html_string, url=None, title=None, strict=True, local=False): Create a Chapter object from a string. The principle of the above two methods is to first obtain the html or xml string, and then call this method.html_string (string):htmlorxhtmlstring orimageurl (withstrict=False) orimagepath (withstrict=Falseandlocal=True). When it is an image, if there is notitlefield or thetitlefield is any one ofCOVER_TITLE_LIST, such ascover, then the image will be used as the cover.url (Option[string]): The url used to infer the chapter title. It is recommended to bring theurlparameter, which helps to identify relative links in the web page.title (Option[string]): The chapter name of the chapter, if None, the content of the title tag obtained from the web file will be used as the chapter name.strict (Option[boolean]): Whether to perform strict page cleaning, which will remove inline styles, insignificant attributes, etc., generally True.local (Option[boolean]): Whether to use local resources, which means that all images and css files in html have been saved locally, and the resources will be copied directly using the file path in html instead of getting them from the Internet.Epub(title, creator='dfface', language='en', rights='', publisher='dfface', epub_dir=None): Constructor method to create Epub object.Mainly used to add book information and all chapters and generate epub file.title (str): Thetitleof the epub.creator (Option[str]): Theauthorof the epub.language (Option[str]): Thelanguageof the epub.rights (Option[str]): Thecopyrightof the epub.publisher (Option[str]): Thepublisherof the epub.epub_dir(Option[str]): The path of intermediate file, the system's temporary file path is used by default, or you can specify it yourself.Epub objectadd_chapter(chapter_object): Add Chapter object to Epub.chapter_object (Chapter object): Use the three methods of creating a chapter object to get the object.Epub objectcreate_epub(output_directory, epub_name=None): Create an epub file from the Epub object.output_directory (str): Directory to output the epub file to.epub_name (Option[str]): The file name of your epub. This should not contain .epub at the end. If this argument is not provided, defaults to the title of the epub.html_clean(input_string, help_url=None, tag_clean_list=constants.TAG_DELETE_LIST, class_list=constants.CLASS_INCLUDE_LIST, tag_dictionary=constants.SUPPORTED_TAGS): The internal defaultcleanmethod we expose for easy customization.input_string (str): A string representing HTML / XML.help_url (Option[str]): current chapter's url, which helps to identify relative links in the web page.tag_dictionary (Option[dict]): defines all tags and their classes that need to be saved, you can see what the default values are inSUPPORTED_TAGS.tag_clean_list (Option[list]): defines all tags that need to be deleted. Note that the entire tag and its sub-tags will be deleted directly here. You can see what the default values are inTAG_DELETE_LIST.class_list (Option[list]): defines all tags containing the content of the class that need to be deleted, that is, as long as the class attribute of any tag contains the content in this list, then the entire tag will be deleted including its sub-tags. You can see what the default values are inCLASS_INCLUDE_LIST.TipsIf you want to add a cover image yourself, use thecreate_chapter_from_stringmethod, then assignhtml_stringto the image URL (e.g.https://www.xxx.com/xxx.png) and keep thestrict=Falseparameter. Or assignhtml_stringto the local image file path (e.g../xxx.png) and keep thelocal=Trueandstrict=Falseparameters. And it's better to add atitle='Cover'parameter.If you want to clean the web content yourself, first use the crawler to get the html string, then use the exposedhtml_cleanmethod (it is recommended to add the values oftag_clean_list,class_clean_listandurl) and assign the output to thecreate_chapter_from_stringmethodhtml_stringparameter while keepingstrict=False.No matter which method, when usingcreate_chapter_*andstrict=False, it is recommended to bring theurlparameter, which helps to identify relative links in the web page.Whenever you use thehtml_cleanmethod, it is recommended to include thehelp_urlparameter, which helps to identify relative links in web pages.After generating the epub, it is better to usecalibreto convert theepubto a more standards-compliantepub/mobi/azw3to solve the problem that the epub cannot be read in some software. And if the generated epub has style problems, you can also use calibre to edit the ebook andadjust the styleto suit your reading habits.If the images and CSS files in your html are local resources, please set thelocalparameter increate_chapter_*toTrue, then the program will automatically copy the local resources instead of getting them from the Internet.FAQThe generated epub has no content?When generating an epub by URL, you need to ensure that the web page corresponding to the URL is a static web page, and you can access all the content without logging in. If the epub you generate is empty when opened, then you may have encountered a website that requires login to access. At this time, you can try to obtain the html string corresponding to the URL, and then use thecreate_chapter_from_stringmethod to generate the epub. That is to say, you need to use a certain crawler technology.The generated epub contains content I don't want?Although we do some filtering when cleaning the html string, this is not guaranteed to work in all cases. In this case, I recommend that you filter the html string yourself before usingcreate_chapter_from_stringmethod.Want to generate epub directly from html string without sanitizing content?Set the parameterstrictofcreate_chapter_from_stringtoFalse, which means that it will not be cleaned up internally.If you choose to get the html string yourself and clean it up yourself, you can follow these steps:Use crawler technology to obtain html strings, such asrequests.get(url).text.Use thehtml_cleanmethod we expose to clean up the string, e.g.html_clean(html_string, tag_clean_list=['sidebar']). Or you can write your own methods to sanitize strings, all just to get clean strings, whatever you want.Using thecreate_chapter_from_string(html_string, strict=False)method to generate the Chapter object, pay special attention to the parameterstrictto be set to False, which means that our internal cleaning strategy will be skipped.After that, you can generate epub according to the basic usage. Seevuepress2epub.pyas an example."} +{"package": "xml2html", "pacakge-description": "xml2htmlsimple html generator for xml filesFree software: MIT licenseDocumentation:https://xml2html.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-03-23)First release on PyPI."} +{"package": "xml2js", "pacakge-description": "No description available on PyPI."} +{"package": "xml2json", "pacakge-description": "UNKNOWN"} +{"package": "xml2obj", "pacakge-description": "UNKNOWN"} +{"package": "xml2pandas", "pacakge-description": "xml2pandasCreator: Chase KellyLast Updated: 7/2019This package is intended to turn 2-D data in.xmlformat into a pandas DataFrame.Use:from xml2pandas import ReadXMLxml = ReadXML('/path/to/file.xml')xml()- preserving call for inevitable keywords and optionsxml(detect=True)will convert numeric columdf = xml.df"} +{"package": "xml2py", "pacakge-description": "xml2py is hosted athttps://github.com/pwexler/xml2py"} +{"package": "xml2pytorch", "pacakge-description": "xml2pytorchUsing xml to define pytorch neural networksWhat can it DoWith xml2pytorch, you can easily define neural networks in xml, and then declare them in pytorch.RNN and LSTM are not supported currently.InstallationEnvironmentOS independent. Python3. (Not tested on Python2, but it should work.)Install requirementstorch>=0.4.1\nnumpy>=1.15.1Installing by pip3pip3 install xml2pytorchQuick StartHow to declare the CNN defined by a xml fileimport torch\nimport xml2pytorch as xm\n\n# declare the net defined in .xml\nnet = xm.convertXML(xml_filename) \n\n# input a random tensor\nx = torch.randn(1, 3, 32, 32)\ny = net(x)\nprint(y)How to define a simple CNN in xml<graph>\n\t<net>\n\t\t<layer>\n\t\t\t<net_style>Conv2d</net_style>\n\t\t\t<in_channels>3</in_channels>\n\t\t\t<out_channels>6</out_channels>\n\t\t\t<kernel_size>5</kernel_size>\n\t\t</layer>\t\n\t\t<layer>\n\t\t\t<net_style>ELU</net_style>\n\t\t</layer>\t\n\t\t<layer>\n\t\t\t<net_style>MaxPool2d</net_style>\n\t\t\t<kernel_size>2</kernel_size>\n\t\t\t<stride>2</stride>\n\t\t\t<activation>logsigmoid</activation>\n\t\t</layer>\n\t\t<layer>\n\t\t\t<net_style>Conv2d</net_style>\n\t\t\t<in_channels>6</in_channels>\n\t\t\t<out_channels>16</out_channels>\n\t\t\t<kernel_size>5</kernel_size>\n\t\t\t<activation>relu</activation>\n\t\t</layer>\t\n\t\t<layer>\n\t\t\t<net_style>MaxPool2d</net_style>\n\t\t\t<kernel_size>2</kernel_size>\n\t\t\t<stride>2</stride>\n\t\t\t<activation>relu</activation>\n\t\t</layer>\n\t\t<layer>\n\t\t\t<net_style>reshape</net_style>\n\t\t\t<dimensions>[-1, 16*5*5]</dimensions>\n\t\t</layer>\n\t\t<layer>\n\t\t\t<net_style>Linear</net_style>\n\t\t\t<in_features>400</in_features> \n\t\t\t<out_features>120</out_features>\n\t\t\t<activation>tanh</activation>\n\t\t</layer>\n\t\t<layer>\n\t\t\t<net_style>Linear</net_style>\n\t\t\t<in_features>120</in_features> \n\t\t\t<out_features>84</out_features>\n\t\t\t<activation>sigmoid</activation>\n\t\t</layer>\n\t\t<layer>\n\t\t\t<net_style>Linear</net_style>\n\t\t\t<in_features>84</in_features>\n\t\t\t<out_features>10</out_features>\n\t\t\t<activation>softmax</activation>\n\t\t</layer>\n\t</net>\n</graph>"} +{"package": "xml2rfc", "pacakge-description": "Generate RFCs and IETF drafts from document source in XML according to the IETF xml2rfc v2 and v3 vocabulariesChangelogInstallationUsageContributingGetting StartedGit Cloning TipsDocker Dev EnvironmentRelease ProcedureIntroductionTheIETFuses a specific format for the standards and other documents it publishes asRFCs, and for the draft documents which are produced when developing documents for publications. There exists a number of different tools to facilitate the formatting of drafts and RFCs according to the existing rules, and this tool,xml2rfc, is one of them. It takes as input an xml file that contains the text and meta-information about author names etc., and transforms it into suitably formatted output. The input xml file should follow the grammars inRFC7749(for v2 documents)orRFC7991(for v3 documents). Note that the grammar for v3 is still being refined, and changes will eventually be captured in thebis draft for 7991. Changes not yet captured can be seen in the xml2rfc sourcev3.rng, or in thedocumentation xml2rfc produceswith its--docflag.xml2rfcprovides a variety of output formats. See the command line help for a full list of formats. It also provides conversion from v2 to v3, and can run thepreptoolon its input.InstallationInstallation of the python package is done as usual withpip install xml2rfc, using appropriate switches.Installation of support libraries for the PDF-formatterIn order to generate PDFs,xml2rfcuses theWeasyPrintmodule, which depends on external libraries that must be installed as native packages on your platform, separately from thexml2rfcinstall.First, install thePango, and other required libraries on your system. See installation instructions on theWeasyPrint Docs.Next, install WeasyPrint python modules using pip.pipinstall'weasyprint>=53.0,!=57.0,!=60.0'Finally, install the fullNoto FontandRoboto Monopackages:Download the full font file from:https://noto-website-2.storage.googleapis.com/pkgs/Noto-unhinted.zipFollow the installation instructions athttps://www.google.com/get/noto/help/install/Go tohttps://fonts.google.com/specimen/Roboto+Mono, and download the\nfont. Follow the installation instructions above, as applied to this download.Go tohttps://fonts.google.com/noto/specimen/Noto+Sans+Math, and\ndownload the font. Follow the installation instructions above, as\napplied to this download.With these installed and available toxml2rfc, the--pdfswitch will be enabled.Usagexml2rfcaccepts a single XML document as input and outputs to one or more conversion formats.Basic Usagexml2rfcSOURCE[options]FORMATS...Runxml2rfc --helpfor a full listing of command-line options.Getting StartedThis project is following the standardGit Feature Workflowdevelopment model. Learn about all the various steps of the development workflow, from creating a fork to submitting a pull request, in theContributingguide.Make sure to read theStyleguidessection to ensure a cohesive code format across the project.You can submit bug reports, enhancements and new feature requests in thediscussionsarea. Accepted tickets will be converted to issues.Git Cloning TipsAs outlined in theContributingguide, you will first want to create a fork of the xml2rfc project in your personal GitHub account before cloning it.For example(replaceUSERNAMEwith your GitHub username):gitclonehttps://github.com/USERNAME/xml2rfc.gitDocker Dev EnvironmentRun./run.shcommand to build and start a docker development environment.\nThe initial build may take time because it downloads all required fonts as well../run.sh"} +{"package": "xml2xlsx", "pacakge-description": "Creatingxlsxfiles fromxmltemplate usingopenpyxl.TargetThis project is intended to createxlsxfiles fromxmlapi toopenpyxl, supposedly generated by other tamplate engines (i.e. django,\njinja).This is a merely an xml parser translating mostly linearly to worksheet, rows\nand finally cells of the Excel workbook.ExampleAn xml file like this one<workbook><worksheettitle=\"test\"><row><cell>This</cell><cell>is</cell><cell>aTEST</cell></row><row><cell>Nice,isn'tit?</cell></row></worksheet></workbook>can be parsed to create a neat Excel workbook with two rows of data in one\nworksheet. Parsing can be done using command line (provided that you have your\nsystem paths set correctly:xml2xlsx<input.xml>output.xmlor as a library callfromxml2xlsximportxml2xlsxtemplate='<sheet title=\"test\"></sheet>'f=open('test.xlsx','wb')f.write(xml2xlsx(template))f.close()This is mainly intended (and was developed for this purpose) to parse files\ngenerated by other templating engines, like django template system. One can\ngenerate an excel workbook from template like this:{%foreinlist%}<row><cell>{{e.name}}</cell></row>{%endfor%}FeaturesBasic features of the library include creating multiple, named sheets within one\nworkbook and creating rows of cells in these sheets. However, there are more\npossibiliteis to create complex excel based reports.Cell typeEach cell can be specified to use one of the types:string (default)numberdateType is defined intypecell attribute. The cell value is converted\nappropriately to the type specified. If you insert a number in the cell value\nand do not specifytype=\"number\"attribute, you will find Excel complaining\nabout storing nubers as text.Since there are more date formats than countries, you have to be aware of\ncurrent locale. The simplest way to be i18n compatible is to specify date format\nindate-fmtattribute and pass compatible (possibily non localized) date\nin the cell value, as in the following example...<row><celltype=\"date\"date-fmt=\"%Y-%m-%d\">2016-10-01</cell></row><row><celltype=\"date\"date-fmt=\"%d.%m.%Y\">01.10.2016</cell></row>...Generated excel file will have two rows with the same date (1st of October 2016)\nwith date formatted according to Excel defaults (and current locale).WarningExcel tries to be very smart and converts date-like text to date format.\nPlease usetype=\"date\"anddate-fmtattribute always if you pass\ndates to cells.ColumnsColumns can be tackled only in a limited way, i.e. only column widths can be\nchanged. Column properties are defined incolumnstag as one or more child\nof thesheettag. It is possible to specify a range of columns usingstartandendatrributes. For example:...<sheettitle=\"test\"><columnsstart=\"A\"end=\"D\"width=\"123\"/><row><cell>Test</cell></row></sheet>...Formulasxml2xlscan effectively create cells with formulas in them. The only\nlimitation (as withopenpyxl) is using English names of the functions.For example:...<row><cell>=SUM(A1:A5)</cell></row>...Cell referencingThe parser can store positions of the cell in a dictionary-like structure. It\nthen can be referenced to create complex formulas. Each value of the cell is\npreprocessed using string format with stored values. This means that these\nvalues can be referenced using{and}brackets.Current row and columnThere are two basic values that can always be used, i.e.rowandcolwhich return current row number and column name.<workbook><sheet><row><cell>{col}{row}</cell></row></sheet></workbook>...would create a workbook with a text \u201cA1\u201d included in theA1cell of the\nworksheet. Using template languages, you can create more complicated\nconstructs, like (using django template system):...{%foreinlist%}<row><celltype=\"date\"date-fmt=\"%Y-%m-%d\">{{e|date:\"Y-m-d\"}}</cell><cell>=TEXT(A{row},\"ddd\")</cell></row>{%endfor%}...would create a list of rows with a date in the first column and weekday names\nfor these dates in the second column (providedlistcontext variable\ncontains a list of dates).Specified cellIt is also possible to store cell possible to store names of specified cells in\na pseudo-variable (as in a dictionary). One has to useref-idattribute of\nthecelltag and then reuse the value of this attribute in the remainder of\nthe xml input. This is very useful in formulas. A simple example would be\nreferencing another cell in a formula like this:...<row><cellref-id=\"mycell\">Thisisjustatest</cell></row>...<row><cell>={mycell}</cell></row>...which would create an excel formula referencing a cell with \u201cthis is just a\ntest\u201d text, whatever this cell address was.WarningUsing the same identifier inref-idattribute for two different cellsoverwritesthe cell reference, i.e. the last cell in the xml template\nwould be referenced.A more complex example using django template engine to create summaries can\nlook like this:...{%foreinlist%}<row><cellref-id=\"{% if forloop.first %}start{% elsif forloop.last %}end{% endif %}\">{{e}}</cell></row>{%endfor%}<row><cell>Summary</cell><cell>=SUM({start}:{end})</cell></row>...List of cellsReferencing a single cell can be harsh when dealing with complex reports.\nEspecially when creating summaries of irregularly sheet-distributed data.xml2xlsxcan append a cell to a variable-like list, as inref-idattribute, to reuse it as a comma concatenated value. Instead ofref-id, one\nhas to useref-appendattribute.This is a simple example to demonstrate the feature:...\n<sheet>\n <row>\n <cell ref-append=\"mylist\">1</cell>\n <cell ref-append=\"mylist\">2</cell>\n </row>\n <row><cell ref-append=\"mylist\">3</cell></row>\n <row><cell>=SUM({mylist})</cell></row>\n</sheet>This will generate an Excel sheet withA3cell containing formula to sumA1,B1andA2cells (=SUM(A1, B1, A2)).Referencing limitationsIt is perfectly possible to reference a cell in another sheet with bothref-idandref-append. However, there is a limitation to that. Sincexml2xslxis a linear parser, you are only allowed to reference already\nparsed elements. This means, you have to create sheets in a proper order (sheets\nreferencing other sheets must be createdafterreferenced cells are parsed).The following examplewill not work:...<sheettitle=\"one\"><row><cell>{mycell}</cell></row></sheet><sheettitle=\"two\"><row><cellref-id=\"mycell\">XYZ</cell></row></sheet>...However, it is possible to make this exmaple workandretain the same\nworksheet ordering usingindexattribute:...<sheettitle=\"two\"><row><cellref-id=\"mycell\">XYZ</cell></row></sheet><sheettitle=\"one\"index=\"0\"><row><cell>{mycell}</cell></row></sheet>...Cell formattingThe cell format can be specified using various attributes of the cell tag. Only\nfont formatting can be specifed for now.Font formatA font format is specified in infontattribute. It is a semicolon separated\ndict like list of font formats as specified infontclass ofopenpyxllibrary.An example to create a cell with bold 10px font:...\n<cell font=\"bold: True; size: 10px;\">Cell formatted</cell>\n...Planned featuresHere is the (probably incomplete) wishlist for the projectGlobal font and cell stylesRow widths and column heightsHorizontal and vertical cell mergingXML validation with XSD to quickly raise an error if parsing wrong xmlXML Schema ReferenceParsed xml should be enclosed in aworkbooktag. Eachworkbooktag can\nhave multiplesheet. The hierarchy continues torowandcelltags.Here is a complete list of available attributes of these tags.workbookNo attributes for now.sheetAttribute:titleUsage:Specifies the worksheet titleAttribute:indexUsage:Specifies the worksheet index. This is relative to already created indexes.\nAn index of 0 creates sheet at the beginning of the sheets collection.rowNo attributes for nowcolumnsAttribute:startUsage:Specifies the starting column for the column range (in a letter format).Attribute:endUsage:Specifies the ending column for the column range (in a letter format).Default:Same asstartattributeAttribute:widthUsage:Specifies the width for all columns in the range. It is in px format.cellAttribute:typeUsage:Specifies the resulting type of the excel cell.Type:One ofunicode,date,numberDefault:unicodeAttribute:date-fmtUsage:Specifies the format of the date parsed as instrftime and strptimefunctions ofdatetimestandard python library.Remarks:Parsed only iftype=\"date\".Attribute:fontUsage:Sepcifies font formatting for a single cell.Type:List of semicolon separated dict-like values in form ofkey: value; key: value;Remarks:Key and values are arguments ofFontclas inopenpyxl.Release History0.2Added documentationAdded cell referencing with inter-sheet possibilityChangedsheettitle attribute fromnametotitleAdded possibility to set index for a sheet"} +{"package": "xml4h", "pacakge-description": "xml4his an MIT licensed library for Python to make it easier to work with XML.This library exists because Python is awesome, XML is everywhere, and combining\nthe two should be a pleasure but often is not. Withxml4h, it can be easy.As of version 1.0xml4hsupports Python versions 2.7 and 3.5+.Featuresxml4his a simplification layer over existing Python XML processing libraries\nsuch aslxml,ElementTreeand theminidom. It provides:a rich pythonic API to traverse and manipulate the XML DOM.a document builder to simply and safely construct complex documents with\nminimal code.a writer that serialises XML documents with the structure and format that you\nexpect, unlike the machine- but not human-friendly output you tend to get\nfrom other libraries.Thexml4habstraction layer also offers some other benefits, beyond a nice\nAPI and tool set:A common interface to different underlying XML libraries, so code written\nagainstxml4hneed not be rewritten if you switch implementations.You can easily move betweenxml4hand the underlying implementation: parse\nyour document using the fastest implementation, manipulate the DOM with\nhuman-friendly code usingxml4h, then get back to the underlying\nimplementation if you need to.InstallationInstallxml4hwith pip:$ pip install xml4hOr install the tarball manually with:$ python setup.py installLinksGitHub for source code and issues:https://github.com/jmurty/xml4hReadTheDocs for documentation:https://xml4h.readthedocs.orgInstall from the Python Package Index:https://pypi.python.org/pypi/xml4hIntroductionWithxml4hyou can easily parse XML files and access their data.Let\u2019s start with an example XML document:$ cat tests/data/monty_python_films.xml\n<MontyPythonFilms source=\"http://en.wikipedia.org/wiki/Monty_Python\">\n <Film year=\"1971\">\n <Title>And Now for Something Completely Different\n \n A collection of sketches from the first and second TV series of\n Monty Python's Flying Circus purposely re-enacted and shot for film.\n \n \n \n Monty Python and the Holy Grail\n \n King Arthur and his knights embark on a low-budget search for\n the Holy Grail, encountering humorous obstacles along the way.\n Some of these turned into standalone sketches.\n \n \n \n Monty Python's Life of Brian\n \n Brian is born on the first Christmas, in the stable next to\n Jesus'. He spends his life being mistaken for a messiah.\n \n \n <... more Film elements here ...>\nWithxml4hyou can parse the XML file and use \u201cmagical\u201d element and attribute\nlookups to read data:>>> import xml4h\n>>> doc = xml4h.parse('tests/data/monty_python_films.xml')\n\n>>> for film in doc.MontyPythonFilms.Film[:3]:\n... print(film['year'] + ' : ' + film.Title.text)\n1971 : And Now for Something Completely Different\n1974 : Monty Python and the Holy Grail\n1979 : Monty Python's Life of BrianYou can also use more explicit (non-magical) methods to traverse the DOM:>>> for film in doc.child('MontyPythonFilms').children('Film')[:3]:\n... print(film.attributes['year'] + ' : ' + film.children.first.text)\n1971 : And Now for Something Completely Different\n1974 : Monty Python and the Holy Grail\n1979 : Monty Python's Life of BrianThexml4hbuilder makes programmatic document creation simple, with a\nmethod-chaining feature that allows for expressive but sparse code that mirrors\nthe document itself. Here is the code to build part of the above XML document:>>> b = (xml4h.build('MontyPythonFilms')\n... .attributes({'source': 'http://en.wikipedia.org/wiki/Monty_Python'})\n... .element('Film')\n... .attributes({'year': 1971})\n... .element('Title')\n... .text('And Now for Something Completely Different')\n... .up()\n... .elem('Description').t(\n... \"A collection of sketches from the first and second TV\"\n... \" series of Monty Python's Flying Circus purposely\"\n... \" re-enacted and shot for film.\"\n... ).up()\n... .up()\n... )\n\n>>> # A builder object can be re-used, and has short method aliases\n>>> b = (b.e('Film')\n... .attrs(year=1974)\n... .e('Title').t('Monty Python and the Holy Grail').up()\n... .e('Description').t(\n... \"King Arthur and his knights embark on a low-budget search\"\n... \" for the Holy Grail, encountering humorous obstacles along\"\n... \" the way. Some of these turned into standalone sketches.\"\n... ).up()\n... .up()\n... )Pretty-print your XML document withxml4h\u2019s writer implementation with\nmethods to write content to a stream or get the content as text with flexible\nformatting options:>>> print(b.xml_doc(indent=4, newline=True)) # doctest: +ELLIPSIS\n\n\n \n And Now for Something Completely Different\n A collection of sketches from ...\n \n \n Monty Python and the Holy Grail\n King Arthur and his knights embark ...\n \n\nWhy usexml4h?Python has three popular libraries for working with XML, none of which are\nparticularly easy to use:xml.dom.minidomis a light-weight, moderately-featured implementation of the W3C DOM\nthat is included in the standard library. Unfortunately the W3C DOM API is\nverbose, clumsy, and not very pythonic, and theminidomdoes not support\nXPath expressions.xml.etree.ElementTreeis a fast hierarchical data container that is included in the standard\nlibrary and can be used to represent XML, mostly. The API is fairly pythonic\nand supports some basic XPath features, but it lacks some DOM traversal\nniceties you might expect (e.g. to get an element\u2019s parent) and when using it\nyou often feel like your working with something subtly different from XML,\nbecause you are.lxmlis a fast, full-featured XML library with an API\nbased on ElementTree but extended. It is your best choice for doing serious\nwork with XML in Python but it is not included in the standard library, it\ncan be difficult to install, and it gives you the same it\u2019s-XML-but-not-quite\nfeeling as its ElementTree forebear.Given these three options it can be difficult to choose which library to use,\nespecially if you\u2019re new to XML processing in Python and haven\u2019t already\nused (struggled with) any of them.In the past your best bet would have been to go withlxmlfor the most\nflexibility, even though it might be overkill, because at least then you\nwouldn\u2019t have to rewrite your code if you later find you need XPath support or\npowerful DOM traversal methods.This is wherexml4hcomes in. It provides an abstraction layer over\nthe existing XML libraries, taking advantage of their power while offering an\nimproved API and tool set.Development Status: betaCurrentlyxml4hincludes adapter implementations for three of the main XML\nprocessing Python libraries.If you havelxmlavailable (highly recommended) it will use that, otherwise\nit will fall back to use the(c)ElementTreethen theminidomlibraries.History1.0Add support for Python 3 (3.5+)Dropped support for Python versions before 2.7.Fix node namespace prefix values for lxml adapter.Improve builder\u2019sup()method to accept and distinguish between a count\nof parents to step up, or the name of a target ancestor node.Addxml()andxml_doc()methods to document builder to more easily\nget string content from it, without resorting to the write methods.Thewrite()andwrite_doc()methods no longer send output tosys.stdoutby default. The user must explicitly provide a target writer\nobject, and hopefully be more mindful of the need to set up encoding correctly\nwhen providing a text stream object.Handling of redundant Element namespace prefixes is now more consistent: we\nalways strip the prefix when the element has anxmlnsattribute defining\nthe same namespace URI.0.2.0Add adapter for the(c)ElementTreelibrary versions included as standard\nwith Python 2.7+.Improved \u201cmagical\u201d node traversal to work with lowercase tag names without\nalways needing a trailing underscore. See also improved docs.Fixes for: potential errors ASCII-encoding nodes as strings; default XPath\nnamespace from document node; lookup precedence of xmlns attributes.0.1.0Initial alpha release with support forlxmlandminidomlibraries."} +{"package": "xmla", "pacakge-description": "olap.xmlaThis package is meant for accessing xmla datasources - seehttp://en.wikipedia.org/wiki/XML_for_AnalysisBuilingIn this directory, run:python setup.py buildTestingTests are done against the Mondrian, SSAS, icCube XMLA providers. The\ntestsDiscover module tests behavior with different XMLA providers with\nthe Discover command while testsExecute does the same with the Execute\ncommand. Note that you likely need to modify the sources if you want to\ntest yourself since they contain specifics (namely the location of the\nservices and names of the data sources).SampleHere is an example how to use it:import olap.xmla.xmla as xmla\n\np = xmla.XMLAProvider()\n# mondrian\nc = p.connect(location=\"http://localhost:8080/mondrian/xmla\")\n# to analysis services (if iis proxies requests at /olap/msmdpump.dll)\n# you will need a valid kerberos principal of course\n# c = p.connect(location=\"https://my-as-server/olap/msmdpump.dll\",\n# sslverify=\"/path/to/my/as-servers-ca-cert.pem\")\n# to icCube\n# c = p.connect(location=\"http://localhost:8282/icCube/xmla\", username=\"demo\",\n# password=\"demo\")\n\n# getting info about provided data\nprint c.getDatasources()\nprint c.getMDSchemaCubes()\n# for ssas a catalog is needed, so the call would be like\n# get a catalogname from a call to c.getDBSchemaCatalogs()\n# c.getMDSchemaCubes(properties={\"Catalog\":\"a catalogname\"})\n\n# execute a MDX (working against the foodmart sample catalog of mondrian)\ncmd= \"\"\"select {[Measures].ALLMEMBERS} * {[Time].[1997].[Q2].children} on columns,\n[Gender].[Gender].ALLMEMBERS on rows\nfrom [Sales]\n\"\"\"\n\nres = c.Execute(cmd, Catalog=\"FoodMart\")\n#return only the Value property from the cells\nres.getSlice(properties=\"Value\")\n# or two props\nres.getSlice(properties=[\"Value\", \"FmtValue\"])\n\n# to return some subcube from the result you can\n# return all\nres.getSlice()\n# carve out the 4th column\nres.getSlice(Axis0=3)\n# same as above, SlicerAxis is ignored\nres.getSlice(Axis0=3, SlicerAxis=0)\n# return the data sliced at the 2nd and 3rd row\nres.getSlice(Axis1=[1,2])\n# return the data sliced at the 2nd and 3rd row and at the 4th column\nres.getSlice(Axis0=3, Axis1=[1,2])Using the procedural interface:import olap.xmla.xmla as xmla\n\np = xmla.XMLAProvider()\nc = p.connect(location=\"http://localhost:8080/mondrian/xmla\")\ns = p.getOLAPSource()\n\n# import olap.interfaces as oi\n# oi.IOLAPSource.providedBy(s) == True\n\ns.getCatalogs()\ns.getCatalog(\"FoodMart\").getCubes()\ns.getCatalog(\"FoodMart\").getCube(\"HR\").getDimensions()\ns.getCatalog(\"FoodMart\").getCube(\"HR\").getDimension(\"[Department]\").\\\ngetMembers()\ns.getCatalog(\"FoodMart\").getCube(\"HR\").getDimension(\"[Department]\").\\\ngetMember(\"[Department].[14]\")\n\ncmd= \"\"\"select {[Measures].ALLMEMBERS} * {[Time].[1997].[Q2].children} on columns,\n[Gender].[Gender].ALLMEMBERS on rows\nfrom [Sales]\n\"\"\"\nres=s.getCatalog(\"FoodMart\").query(cmd)\nres.getSlice()NoteThe contained vs.wsdl originates from the following package:http://www.microsoft.com/en-us/download/confirmation.aspx?id=9388and\nwas subsequently modified (which parameters go in the soap header) to\nwork with the suds package.olap.xmlaCHANGES0.7.2now relies on requests 1.2.3fixed race condition in kerberos auth0.7.1kerberos-auth was sent twice0.7works now with requests 0.14- and 1.-series of requestsselection of cell properties failed0.6dependency on kerberos and s4u2p is now optionaladded optional kerberos-sspi package for kerberos on windows through sspi via pywin320.5as_userandspnare no longer ignored in the kerberos authenticationimplemented the procedural interface from olap.interfacesfixed problem when no sliceraxis info is returnedparameterpropertyof getSlice now spellsproperties0.4keywordkerberosis gone. kerberos auth need is detected automaticallyBeginSessionandEndSessionprovide XMLA Sessionsupportchanges to work with icCube XMLA provider0.3changed keyworddoKerberosin XMLProvider.connect tokerberosaddedsslverifykeyword to XMLProvider.connect defaulting toTrue.\nThis will be handed to requests get method, so you can point it to your certificate bundle file.0.2removed dependencies on specific versions in setup.py"} +{"package": "xmlable", "pacakge-description": "XMLableAn easy xml/xsd generator and parser for python dataclasses!@xmlify@dataclassclassConfig:date:strnumber_of_cores:intcodes:list[int]show_logs:boolwrite_xsd(THIS_DIR/\"config.xsd\",Config)write_xml_template(THIS_DIR/\"config_xml_template.xml\",Config)original=Config(date=\"31/02/2023\",number_of_cores=48,codes=[101,345,42,67],show_logs=False,)write_xml_value(THIS_DIR/\"config_xml_example.xml\",original)read_config:Config=parse_file(Config,THIS_DIR/\"config_xml_example.xml\")assertread_config==originalSee more inexamplesCapabilitiesTypesCurrently supports the types:int,float,str,dict,tuple,set,list,None# as well as unions!int|float|NoneAnd dataclasses that have been@xmlify-ed.These can be combined for types such as:@xmlify@dataclassclassComplex:a:dict[tuple[int,str],list[tuple[dict[int,float|str],set[bool]]]]c1=Complex(a={(3,\"hello\"):[({3:0.4},{True,False}),({2:\"str\"},{False})]})Custom ClassesThe xmlify interface can be implemented by adding methods described inxmlifyOnce the classis_xmlifiedit can be used just as if generated by@xmlifyfromxmlable._xobjectimportXObjectfromxmlable._userimportIXmlifyfromxmlable._manualimportmanual_xmlify@manual_xmlifyclassMyClass(IXmlify):defget_xobject()->XObject:classXMyClass(XObject):defxsd_out(self,name:str,attribs:dict[str,str]={},add_ns:dict[str,str]={})->_Element:passdefxml_temp(self,name:str)->_Element:passdefxml_out(self,name:str,val:Any,ctx:XErrorCtx)->_Element:passdefxml_in(self,obj:ObjectifiedElement,ctx:XErrorCtx)->Any:passreturnXMyClass()# must be an instance of XMyClass, not the classdefxsd_forward(add_ns:dict[str,str])->_Element:passdefxsd_dependencies()->set[type]:return{MyClass}See theuser define examplefor implementation.LimitationsUnions of Generic TypesGenerating xsd works, parsing works, however generating an xml template can fail\nif they type is not determinable at runtime.Values do not have type arguments carried with themMany types are indistinguishable in pythonFor example:@xmlify@dataclassclassGenericUnion:u:dict[int,float]|dict[int,str]GenericUnion(u={})# which variant in the xml should {} have??named_In this case an error is raisedTo Developgitclone# this project# Can use hatch to build, runhatchruncheck:test# run tests/hatchruncheck:lint# check formattinghatchruncheck:typecheck# mypy for src/ and all exampleshatchrunauto:examplegen# regenerate the example codehatchrunauto:lint# format code# Alternatively can just create a normal envpython3.11-mvenv.venvsource.venv/bin/activate# activate virtual environmentpipinstall-e.# install this project in the venvpipinstall-e.[dev]# install optional dev dependencies (mypy, black and pytest)black.# to reformatmypy# type checkpytest# to run testsHatchis used for build, test and pypi publish.To ImproveFuzzing(As a fun weekend project) generate arbitrary python data types with values, and dataclasses.\nThen@xmlifyall and validate as in the current testsEtree vs ObjectifyCurrently using objectify for parsing and etree for construction, I want to move parsing to useetreepreviously used objectify for quick prototype."} +{"package": "xmlabox", "pacakge-description": "No description available on PyPI."} +{"package": "xmlai", "pacakge-description": "xmlaiLightweight prompting library built for Python"} +{"package": "xml-analyser", "pacakge-description": "xml-analyserA tool showing various statistics about element usage in an arbitrary XML file.Usage:xml-analyser example.xmlIfexample.xmllooks like this:ThishastextMoretextherexml-analyzer example.xmloutputs this:{\"example\":{\"count\":1,\"parent_counts\":{},\"attr_counts\":{},\"child_counts\":{\"foo\":2}},\"foo\":{\"count\":2,\"parent_counts\":{\"example\":2},\"attr_counts\":{},\"child_counts\":{\"bar\":2,\"baz\":1}},\"bar\":{\"count\":2,\"parent_counts\":{\"foo\":2},\"attr_counts\":{\"a\":2,\"b\":2,\"c\":1},\"child_counts\":{\"baz\":2}},\"baz\":{\"count\":3,\"parent_counts\":{\"bar\":2,\"foo\":1},\"attr_counts\":{\"d\":1},\"child_counts\":{},\"count_with_text\":2,\"max_text_length\":14}}Truncating the XML insteadThe--truncateoption works differently: the XML file passed to this tool will be truncated, by finding any elements with more than two child elements of the same type and truncating to just those two elements.This can reduce a large XML file to something that's easier to understand.Given an example document like this one:ThishastextThishastextThishastextThishastextMoretexthereMoretexthereThe following command:xml-analyser example.xml --truncateWill return the following:ThishastextThishastextMoretexthere"} +{"package": "xml-analyzer", "pacakge-description": "xml-analyzer is likely a typo for xml-analyserUsepip install xml-analyserinstead.The package you want:https://pypi.org/project/xml-analyser/"} +{"package": "xml-api", "pacakge-description": "XML API\u4ecb\u7ecd\u8be5\u6846\u67b6\u53ef\u4ee5\u4f7f\u7528xml\u7f16\u5199\u8bf7\u6c42\uff0c\u652f\u6301http\u548ctcp\u534f\u8bae\u3002\u4f9d\u8d56python 3.6+\nrequests 2.25.0+\nselenium 3.141.0+ (\u53ef\u9009)\nPyMySQL 0.9.3+ (\u53ef\u9009)\ncx-Oracle 8.3.0+ (\u53ef\u9009)\u7248\u672cv0.0.1 2023-03-311\u3001\u9879\u76ee\u521d\u59cb\u5316v0.0.2 2023-04-121\u3001\u79fb\u690d\u4e86config\u3001db\u7b49\u6a21\u5757v0.0.6 2023-04-201\u3001\u589e\u52a0\u4e86selenium\u7684\u652f\u6301\n2\u3001\u589e\u52a0\u4e86\u5916\u90e8\u6a21\u5757\u5bfc\u5165\u9650\u5236"} +{"package": "xmlApiParse", "pacakge-description": "No description available on PyPI."} +{"package": "xml-archive-to-pdf", "pacakge-description": "Transformation d\u2019un fichier xml de typeunistra:archiveen fichier pdfInstallationpipinstallxml-archive-to-pdfUsagexml-archive-to-pdf-itests/data/pathfinder_1.xml-o/tmp/pathfinder_1.pdf--logotests/data/logo.png--fonttests/data/CustomFontDocumentationStructuration d\u2019un fichier xml de typeunistra:archiveL\u2019objectif est de pouvoir g\u00e9n\u00e9rer simplement un fichier pdf en se basant sur un fichier xml conforme \u00e0 la normeunistra:archive.\nEn amont, il faudra s\u2019assurer que le fichier xml soit valid\u00e9 par un sch\u00e9ma xsd et qu\u2019il contient toutes les informations n\u00e9cessaires \u00e0 la fabrication du pdf.On aura principalement :Des blocs s\u00e9par\u00e9s par des titresDes cl\u00e9s avec un intitul\u00e9 parlant dans l\u2019attribut nameDes valeursUne mise en forme de tableau dans l\u2019attribut styleConcernant le rendu des \u00e9l\u00e9ments dans le pdf :Lorsque l\u2019on met l\u2019attributstyle=\u201dtable\u201d, l\u2019ensemble du bloc est affich\u00e9 comme un tableau.\nLe premier \u00e9l\u00e9ment permet de d\u00e9finir le nom des colonnes. Tous les \u00e9l\u00e9ments suivants doivent avoir les m\u00eames colonnes.\nCelui-ci doit \u00eatre structur\u00e9 de la m\u00eame mani\u00e8re que l\u2019exemple ci-dessous.En dehors des tableaux, lorsqu\u2019un tag poss\u00e8de des enfants, c\u2019est que c\u2019est un titre. Sinon, c\u2019est un ensemble cl\u00e9-valeur.Il y 6 niveaux d\u2019indentation maximum et les tableaux ne sont pas indent\u00e9sPour les labels, si l\u2019attribut name est rempli, on l\u2019utilise. S\u2019il est absent, on utilise le nom du tag et s\u2019il est vide, on met un blanc.Exemple d\u2019un fichier xmlSombre-cr\u00e2ne20Barbare3Pr\u00eatrecombattant1Moinecimeterre\u00e0deuxmains37feu\u00e9pique1000tr\u00e8sbonnearc\u00e0distance82glacesimple100mauvaise\u00e9p\u00e9e\u00e0unemain53terrerare500moyenneronronsanglierL\u00e9gende de l\u2019exempleattributsname : intitul\u00e9 parlant qui servira de label/titre \u00e0 la place du nom du tagstyle : style d\u2019un bloctable: affichage sous forme d\u2019un tableau. Le tableau se redimensionne automatiquement en fonction du nombre de colonnes.\nAttention n\u00e9anmoins \u00e0 ne pas utiliser trop de colonnes ou des \u00e9l\u00e9ments trop gros, car le rendu pourrait ne pas correspondre vos attentes.title: permet de forcer l\u2019affichage sous forme de titre. Ca peut \u00eatre utile dans le cas o\u00f9 on veut afficher un tag vide comme un titre et\nnon pas comme une cl\u00e9/valeur.R\u00e9sultatFichier pdf de l\u2019exempleAutres\u2013logo : le param\u00e8tre logo est optionnel et permet de rajouter un logo sur le document en haut \u00e0 droite\u2013font : le param\u00e8tre font est optionnel et permet de remplacer la font par d\u00e9faut par une autre font\nAttention, le dossier qui contiendra la font doit obligatoirement avoir les 4 fichiers suivants:CustomFont-BoldOblique.ttfCustomFont-Bold.ttfCustomFont-Oblique.ttfCustomFont.ttf"} +{"package": "xmlarrangement-android", "pacakge-description": "# XmlArrangement - Android* XML Arrangement Rules Generator for Android CodeStyle---## Before```xml```## After```xml```## How to use?### 1) Create a file to describe your desired order: (empty lines are ignored)```txtxmlns:androidxmlns:.*android:idandroid:nameandroid:layout_widthandroid:layout_heightandroid:minWidthandroid:minHeightandroid:.*.*```See [example.txt](example.txt)### 2) Run:```user@machine:~$ xmlarrangement-android my-order.txt > rules.xml```### 3) Install:* Android Studio **>** Preferences **>** CodeStyle **>** Scheme **>** Manage **>** Export* Open exported file and rename your scheme, e.g. ``* Find the line ``* You should see a structure like this:```xml...```* Replace the content inside `` with the content of `rules.xml`* Copy new file to Android Studio codestyle path:* **Mac**: ~/Library/Preferences/AndroidStudioX.X/config/codestyles/* **Linux**: ~/.AndroidStudioX.X/config/codestyles/* **Windows**: %USERPROFILE%\\\\.AndroidStudioX.X\\config\\codeStyles* Restart AndroidStudio, go to Preferences **>** CodeStyle **>** Scheme and apply `NewScheme`.## Installation- Simple, using PyPI:```user@machine:~$ [sudo] pip install xmlarrangement-android```- or download the source and:```user@machine:~$ [sudo] python setup.py install```## References* [Formatting xml layout files for Android](https://medium.com/@VeraKern/formatting-xml-layout-files-for-android-47aec62722fc#.bt8shn2qx)"} +{"package": "xmlasdict", "pacakge-description": "python library to read xml DOM trees as dicts (with iter and gettattribute behaviour)Started on 2022-02-01SetupStart using this project in a virtual environment$virtualenvvenv$sourcevenv/Scripts/activate$pipinstall-rrequirements.txtInitialize to grab dependencies$makeinit# install dependencies$makeinit-dev# includes the previous + adds dependencies for developersBuild Docs$makedocuDevelopersRun Tests$maketest# to run all tests$PYTEST_LOGCONF=debug-logconf.ymlpythontests/test_demo.py# to run a specific test with specific loggingCheck the code-style and syntax (flake8)$makecheck"} +{"package": "xmlbegone", "pacakge-description": "UNKNOWN"} +{"package": "xml-boiler", "pacakge-description": "Automatically transform between XML namespaces, possibly doing a chain of file format conversions"} +{"package": "xml-browser", "pacakge-description": "xml_browser.py- Edit XML documents as a directory structureNoteThis is a demo version. I\u2019m publishing it early, so I can get feedback from you. If some people find this utility useful, I\u2019ll keep developing (hopefully with some help :)). Otherwise, it will just stay here as a fun idea of mine that I will maybe play around with. As this is a demo version, it lacks quite some features I\u2019m willing to add some day (you can find the list below). Please open an issue if you notice any misconception - I\u2019d like to eliminate them as soon as possible.xml_browser converts arbitrary XML documents to a directory structure. This enables user to browse and edit XML in a simple and (as the author hopes) intuitive way.This utility was written in Python 3, but is intended to be portable. It was just quickly tested under Python 2, so it may be not working in older versions.Table of contentsWhy?How to use it?ThemakedirObtaining data from directory treeEditingTheassemblePlanned featuresLicenseWhy?The main target is editing XML from within shell scripts. Representing XML as a directory structure makes it easy to do editing with basic shell tools. Also, some advantage of this approach is that operating on a directory structure makes shell code more comprehensive. For example, if script doessedonroot,0/some_element,1/0-textthen you probably suspect what is going on.xml_browser is easy to get and run in volatile environment. You could just setup virtualenv and install xml_browser with pip, or even just get the script via http. No need to preinstall anything or download precompiled binaries. xml_browser is pure Python utility and has no external dependencies.How to use it?ThemakedirTake following XML as an example:\n \n This is a xml_browser demo.\n yup\n tail\n \n \nLet\u2019s say above is the content ofexample.xmlfile. To create a directory structure based on this file, run:xml_browser.py makedir < example.xmlxml_browser reads data from standard input - that way it is easy to pipe results of a command (e.g.curl) directly, without doing too much of a shell magic, like process substitution.By running the command, we\u2019ll get following dirtree:documentRoot,0\n\u251c\u2500\u2500 a,0\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 0-attributes\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 0-text\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 b,0\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u251c\u2500\u2500 0-tail\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u251c\u2500\u2500 0-text\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u251c\u2500\u2500 .tail.ws\n\u2502\u00a0\u00a0 \u2502\u00a0\u00a0 \u2514\u2500\u2500 .text.ws\n\u2502\u00a0\u00a0 \u251c\u2500\u2500 .tail.ws\n\u2502\u00a0\u00a0 \u2514\u2500\u2500 .text.ws\n\u251c\u2500\u2500 .text.ws\n\u2514\u2500\u2500 z,1\n \u2514\u2500\u2500 .tail.ws\n\n3 directories, 10 filesYou can notice directories corresponding with every element fromexample.xmland some files inside them.\nAll directories have suffixes that are appended to element names as an ordering information. This way we know, thatelement goes before. We will discuss ordering in detail later.What about files, why do their names start with0-? The answer is simple - no valid XML tag can start with a number, so it will not clash with any tag name (textas a tag name is not that unusual). Tags cannot start with hyphen (-) either, but if it was the first character of a filename, then you\u2019d need to use--in almost every shell command to parse it correctly. Also,0-is rather easy to type.0-attributesholds information about element attributes in a propfile format, e.g:a=1\nb= 2Note that there are no quotes. Leading and trailing whitespaces of a value are taken litteraly (no stripping!). Attribute names can have leading and trailing whitespaces but - in contrary to values - they will be stripped. So, following line of0-attributes:\" attribute_name = value \"will evaluate to\"attribute_name\"and\" value \"respectively.0-textcontains stripped text of element with a newline appended at the end.0-tailis almost the same thing, but a tail is a text that goes rightafterelement. It\u2019s stripped in the same way.When you edit0-tailor0-textand assemble directory tree to a XML document you can see that leading and trailing whitespaces are preserved. It is possible thanks to.text.wsand.tail.wsfiles. They consist of whitespaces and axcharacter somewhere between them. Thisxserves as a substitution mark - it will be replaced with stripped text from0-text/0-tail. Usually we don\u2019t need to manipulate whitespaces, so they are kept in hidden files.Obtaining data from directory treeMoving around manually doesn\u2019t need explaining, I believe. Let\u2019s focus a bit on usage in shell scripts.For automated tasksfind,grepand globbing are your friends.The simplest case is when you know the structure of your XML:text_of_b=$(cat documentRoot,0/a,*/b,0/0-text)The * is used here just to show, that we can do that this way. Tag names cannot contain commas, so it is used to separate tag name from ordering. Note that * is specified after a comma, so onlyatag will be matched. if the pattern wasa*, then names likealaskawould match as well.What if we want to find everyfooelement in the whole document? Let\u2019s try tofinda way:find root,0 -type d -name \"foo,*\"What if we want to find everyfooelement with abarargument having valuebaz?:find root,0 -type d -name \"foo,*\" -exec grep -q 'bar=baz' {}/0-attributes -printLet\u2019s expand above case and call a compound command for every match:find root,0 -type d -name \"foo,*\" -exec grep -q 'bar=baz' {}/0-attributes -print | \\\nwhile read -r match; do\n cat $match/0-text\n # we could do that in -exec in find or with xargs, but I'm too lazy to come up with a more complex example.\n # that would fit for a loop. But you see, you can run lots of commands here for every hit!\ndoneWhat if we want to make above the right way?:find root,0 -type d -name \"foo,*\" -exec grep -q 'bar=baz' {}/0-attributes -print0 | \\\nwhile IFS= read -r -d '' match; do\n cat \"$match/0-text\"\ndoneWe could do this withoutfindtoo, but I consider this less readable - and we need to play around withIFS:IFS=$'\\n'\nfor match in $(grep -lR 'bar=baz' root,0/* | grep 'foo,[^/]*/0-attributes'); do\n cat \"$(dirname \"$match\")/0-text\" 2> /dev/null\ndoneThese examples are rather lengthy, but not that hard to construct. xml_browser is intended to be used in shell, so using somefind,grepand some loops is not improper.EditingEditing data is similar to reading it. You can usesedorawkin commands above, so let\u2019s focus on xml_browser specific thing - node ordering.Consider following:\n \n \n \n \n \n \n Some tail text\nAs you already know, we\u2019ll get following subdirectories insidereallySimple,0directory:a,0 a,1 b,2 a,3 c,4 c,5Easy. But how to add a node? It\u2019s obvious how to append a node at the end (e.g.mkdir new,6, you may want to move0-tailto the new last element). But how to insert it between some existing nodes? Time for some theory.Numbers at the time of assembling directory structure into a XML document are used solely for ordering, so it does not matter if you have, let\u2019s say,a,0,a,1,over,2or something likea,-100,a,4.5andover,9000- the result will be exactly the same. You can specify any float.But bash sucks at floats!- you might say. That\u2019s true. You can append more commas and numbers to the dirname. So to insertmiddleelement betweena,3andc,4, do:mkdir middle,3,1You need to know, that ordering operates on tuples of floats. Tuple fora,0is(0.0,), formiddle,3,1it\u2019s(3.0, 1.0), so if you create a directory namedfoo,3,-3the tuple will be(3.0,-3.0)and the element will be placed betweena,3andmiddle,3,1- that\u2019s how tuple ordering work, element by element.xml_browser\u2019smakedirwill always generate subsequent integers starting from 0, so it is possible to access elements easily, as the names are predictable. So if you need to read and manipulate data/nodes, do the reading part first, before you will alter ordering.TheassembleWhen you\u2019re done editting, you can assemble the directory tree to a XML document. Just call:xml_browser.py assemble documentRoot > result.xmlLike withmakedir, result is written on standard output, so you can pipe it to any command or redirect to a file.Planned featuresSupport for namespaces - ElementTree doesn\u2019t handle them correctly.Fancy formatting/generating optionsOptions for creating dirtree - creation mode, handling already existing tree.Waiting for your suggestions!LicenseMIT (c) Adrian W\u0142osiak 2016"} +{"package": "xmlbuilder", "pacakge-description": "XMLBuilder is tiny library build on top of ElementTree.TreeBuilder tomake xml files creation more pythonomic. `XMLBuilder` use `with`statement and attribute access to define xml document structure.Only 2.5+ python versions are supported.from __future__ import with_statement # only for python 2.5from xmlbuilder import XMLBuilderx = XMLBuilder('root')x.some_tagx.some_tag_with_data('text', a='12')with x.some_tree(a='1'):with x.data:x.mmmfor i in range(10):x.node(val=str(i))etree_node = ~x # <= return xml.etree.ElementTree objectprint str(x) # <= string objectwill result:textThere some fields, which allow xml output customization:formatted = produce formatted xml. default = Truetabstep = tab string, used for formatting. default = ' ' * 4encoding = xml document encoding. default = 'utf-8'xml_header = add xml header()to begining of the document. default = Truebuilder = builder class, used for create dcument. Default =xml.etree.ElementTree.TreeBuilderOptions can be readed byx = XMLBuilder('root')print x[option_name]and changed byx[option_name] = new_valLook at xmlbuilder/test.py for UT and more examples.Happy xml'ing."} +{"package": "xml-builder", "pacakge-description": "No description available on PyPI."} +{"package": "xml-cleaner", "pacakge-description": "XML cleanerWord and sentence tokenization in Python.[![PyPI version](https://badge.fury.io/py/xml-cleaner.svg)](https://badge.fury.io/py/xml-cleaner)\n[![Build Status](https://travis-ci.org/JonathanRaiman/xml_cleaner.svg?branch=master)](https://travis-ci.org/JonathanRaiman/xml_cleaner)\n![Jonathan Raiman, author](https://img.shields.io/badge/Author-Jonathan%20Raiman%20-blue.svg)[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.md)UsageUse this package to split up strings according to sentence and word boundaries.\nFor instance, to simply break up strings into tokens:`tokenize(\"Joeywas a greatsailor.\")#=> [\"Joey \", \"was \", \"a \", \"great \", \"sailor \",\".\"]`To also detect sentence boundaries:`sent_tokenize(\"Catsat mat. Cat's namedCool.\",keep_whitespace=True) #=>[[\"Cat\", \"sat \", \"mat\", \". \"], [\"Cat \", \"'s \", \"named \", \"Cool\",\".\"]]`sent_tokenizecan keep the whitespace as-is with the flagskeep_whitespace=Trueandnormalize_ascii=False.Installation` pip3 install xml_cleaner `TestingRunnose2."} +{"package": "xmlclone-pdesign", "pacakge-description": "\u8bf4\u660e\u8bbe\u8ba1\u6a21\u5f0f&\u5e38\u7528\u7b97\u6cd5\u7684Python\u5b9e\u73b0\uff0c\u672c\u6587\u73af\u5883\u5982\u4e0b:$cat/proc/version\nLinuxversion5.15.90.1-microsoft-standard-WSL2(oe-user@oe-host)(x86_64-msft-linux-gcc(GCC)9.3.0,GNUld(GNUBinutils)2.34.0.20200220)#1 SMP Fri Jan 27 02:56:13 UTC 2023$conda--version\nconda23.7.4\n\n$condacreate-nvpdesignpython=3.12-y\n$condaactivatevpdesign\n\n$python--version\nPython3.12.0\n\n$make--version\nGNUMake4.3\nBuiltforx86_64-pc-linux-gnu\nCopyright(C)1988-2020FreeSoftwareFoundation,Inc.\nLicenseGPLv3+:GNUGPLversion3orlater\nThisisfreesoftware:youarefreetochangeandredistributeit.\nThereisNOWARRANTY,totheextentpermittedbylaw.Demo\u4f7f\u7528# \u5b89\u88c5pipinstallxmlclone-pdesign# \u6d4b\u8bd5maketest\u9879\u76ee\u73af\u5883# \u521b\u5efa\u5e76\u6fc0\u6d3b\u865a\u62df\u73af\u5883condacreate-nvpdesignpython=3.12-y\ncondaactivatevpdesign# \u5b89\u88c5\u4f9d\u8d56pipinstall-rrequirements.txt# \u6d4b\u8bd5maketest# \u6253\u5305\u53d1\u5e03makerelease\u5176\u5b83\u914d\u7f6ereadthedocs\u767b\u5f55readthedocs\u5bfc\u5165\u672c\u9879\u76ee\u8fdb\u884c\u7f16\u8bd1\u5373\u53efpypi\u5f53\u9700\u8981\u53d1\u5e03\u7248\u672c\u65f6\uff0c\u901a\u8fc7git tag -a [version]\u7684\u65b9\u5f0f\u521b\u5efa\u7248\u672c\u5e76git push --tags\u63a8\u9001\u5230git\u901a\u8fc7make release\u5373\u53ef\u53d1\u5e03\u5230pypi\u53c2\u8003\u94fe\u63a5shields.io"} +{"package": "xmlcls", "pacakge-description": "No description available on PyPI."} +{"package": "xmlcmd", "pacakge-description": "xmlcmd is a proof of concept experiment in augmenting standard POSIX commands\nwith superpowers, such as outputting xml.Sadly it is more sleight of hand than any real magic.To begin with, a directory which is first on thePATHmust be created\n(e.g. ~/bin). This should not be on the path whichwhereisuses, so if\nthings go wrong you can always do$(whereis cmd)to execute affected\ncommands.The idea is to put symlinks to xmlcmd (which is created in the normalpython setup.py installinstallation) into this directory for a number of commands.\nWhen these commands are run with an \u2013xml option, the _{cmd} module will be\nimported from the xmlcmd package and themain()function run with two\narguments: the original list of command line arguments (typically corresponding\nto sys.argv) minus the--xml, and the full path to the \u2018original\u2019 file\nwhich would have been run if the--xmloption had not been specified.This is similar to the waybusyboxworks to implement a whole range of\nUNIX commands from a single binary, by using argv[0] to determine the required\naction. This allows the relevant logic to be factored out into a single place.ben$ sudo pip install xmlcmd\n...\nben$ ln -s $(which xmlcmd) ~/bin/ls\nben$ ls --xml\nPlans:Add a few more commands (currently only supports ls and ps)Put a bunch of actually helpful XML output things into the xmlcmd\npackage to simplify creation of additional command helpersA more usefulxpathcommand than the perl program of that name\non my OS X and Ubuntu installsBen Bass 2011"} +{"package": "xmlcoll", "pacakge-description": "xmlcoll is a python package for working with collections of items.\nThe items have heterogeneous data stored aspropertiesin a dictionary with keys given by a\nname and optional tags. The package API has routines to write data to and\nretrieve data fromXMLand to validate that\nXML against a schema.InstallationInstall fromPyPIwith pip by\ntyping in your favorite terminal:$ pip install xmlcollUsageTo get familiar with xmlcoll, please see the tutorial Jupyternotebook.AuthorsBradley S. Meyer DocumentationThe project documentation is available athttps://xmlcoll.readthedocs.io.ContributeIssue Tracker:https://github.com/mbradle/xmlcoll/issues/Source Code:https://github.com/mbradle/xmlcoll/LicenseThe project is licensed under the GNU Public License v3 (or later)."} +{"package": "xmlComparator", "pacakge-description": "features include:order of child nodes are irrelevantauto handling of namespacepromises: not match reported <=> nonmatch exists; match reported <=> match indeed; reported nonmatch is relevantdoes not support:report accurate nonmatched attributes - nonmatched nodes will be reported in this caseif two nodes have different attributes, their texts will not be compared"} +{"package": "xml_compare", "pacakge-description": "The xml_compare library allows to easily test two XML trees if theyhave the same content. This is especially valuable when unit testingXML based systems.If the trees differ, xml_compare tries to give a good indication onthe nature and location of difference.It should work with any etree implementation, but it has been developedwith lxml.It was inspired by the xml_compare method of formencode_ (http://formencode.org/module-formencode.doctest_xml_compare.html#xml_compare )"} +{"package": "xmlconfig", "pacakge-description": "UNKNOWN"} +{"package": "xmlcord", "pacakge-description": "No description available on PyPI."} +{"package": "xmlcurses", "pacakge-description": "An interface for python\u2019s curses library using XML files to describe windows and their contents"} +{"package": "xml-dataclasses", "pacakge-description": "XML dataclassesXML dataclasses on PyPIThis library maps XML to and from Python dataclasses. It build on normal dataclasses from the standard library and useslxmlfor parsing/generating XML.It's currently in alpha. It isn't ready for production if you aren't willing to do your own evaluation/quality assurance.Requires Python 3.7 or higher.FeaturesConvert XML documents to well-defined dataclasses, which work with Mypy or IDE auto-completionXML dataclasses are dataclassesFull control of parsing and generating XML vialxmlLoading and dumping of attributes, child elements, and text contentRequired and optional attributes/child elementsLists of child elements are supported, as are unions and lists or unionsInheritance does work, but has the same limitations as dataclasses. Inheriting from base classes with required fields and declaring optional fields doesn't work due to field order. This isn't recommendedNamespace support is decent as long as correctly declared. I've tried on several real-world examples, although they were known to be valid.lxmldoes a great job at expanding namespace information when loading and simplifying it when savingPost-load validation hookxml_validateFields not required in the constructor are ignored by this library (viaignored()orinit=False)LimitationsWhitespace and comments aren't supported in the data model. They must be stripped when loading the XMLSo far, I haven't found any examples where XML can't be mapped to a dataclass, but it's likely possible given how complex XML isNo typing/type conversions. Since XML is untyped, only string values are currently allowed. Type conversions are tricky to implement in a type-safe and extensible manner.Dataclasses must be written by hand, no tools are provided to generate these from, DTDs, XML schema definitions, or RELAX NG schemasSecurityThe caveats concerning untrusted content are roughly the same as withlxml, since that does the parsing. This is good, sincelxml's behaviour to XML attacks are well-understood. This library recursively resolves data structures, which may have memory implications for unbounded payloads. Because loading is driven from the dataclass definitions, it shouldn't be possible to execute arbitrary Python code (not a guarantee, see license). If you must deal with untrusted content, a workaround is touselxmlto validateuntrusted content with a strict schema, which you may already be doing.PatternsDefining attributesAttributes can be eitherstrorOptional[str]. Using any other type won't work. Attributes can be renamed or have their namespace modified via therenamefunction. It can be used either on its own, or with an existing field definition:@xml_dataclassclassFoo:__ns__=Nonerequired:stroptional:Optional[str]=Nonerenamed_with_default:str=rename(default=None,name=\"renamed-with-default\")namespaced:str=rename(ns=\"http://www.w3.org/XML/1998/namespace\")existing_field:str=rename(field(...),name=\"existing-field\")For now, you can work around this limitation with properties that do the conversion, and perform post-load validation.By default, unknown attributes raise an error. This can be disabled by passingOptionstoloadwithignore_unknown_attributes.Defining textLike attributes, text can be eitherstrorOptional[str]. You must declare text content with thetextfunction. Similar torename, this function can use an existing field definition, or take thedefaultargument. Text cannot be renamed or namespaced. Every class can only have one field defining text content. If a class has text content, it cannot have any children.@xml_dataclassclassFoo:__ns__=Nonevalue:str=text()@xml_dataclassclassFoo:__ns__=Nonecontent:Optional[str]=text(default=None)@xml_dataclassclassFoo:__ns__=Noneuuid:str=text(field(default_factory=lambda:str(uuid4())))Defining children/child elementsChildren must ultimately be other XML dataclasses. However, they can also beOptional,List, andUniontypes:Optionalmust be at the top level. Valid:Optional[List[XmlDataclass]]. Invalid:List[Optional[XmlDataclass]]Next,Listshould be defined (if multiple child elements are allowed). Valid:List[Union[XmlDataclass1, XmlDataclass2]]. Invalid:Union[List[XmlDataclass1], XmlDataclass2]Finally, ifOptionalorListwere used, a union type should be the inner-most (again, if needed)If a class has children, it cannot have text content.Children can be renamed via therenamefunction. However, attempting to set a namespace is invalid, since the namespace is provided by the child type's XML dataclass. Also, unions of XML dataclasses must have the same namespace (you can use different fields with renaming if they have different namespaces, since the XML names will be resolved as a combination of namespace and name).By default, unknown children raise an error. This can be disabled by passingOptionstoloadwithignore_unknown_children.Defining post-load validationSimply implement an instance method calledxml_validatewith no parameters, and no return value (if you're using type hints):defxml_validate(self)->None:passIf defined, theloadfunction will call it after all values have been loaded and assigned to the XML dataclass. You can validate the fields you want inside this method. Return values are ignored; instead raise and catch exceptions.Ignored fieldsFields not required in the constructor are ignored by this library (new in version 0.0.6). This is useful if you want to populate a field via post-load validation.You can simply setinit=False, although you may also want to exclude the field from comparisons. Theignoredfunction does this, and can also be used.The name doesn't matter, but it might be useful to use the_prefix as a convention.Example (fully type hinted)(This is a simplified real world example - the container can also include optionallinkschild elements.)fromdataclassesimportdataclassfromtypingimportListfromlxmlimportetree# type: ignorefromxml_dataclassesimportxml_dataclass,rename,load,dump,NsMap,XmlDataclassCONTAINER_NS=\"urn:oasis:names:tc:opendocument:xmlns:container\"@xml_dataclass@dataclassclassRootFile:__ns__=CONTAINER_NSfull_path:str=rename(name=\"full-path\")media_type:str=rename(name=\"media-type\")@xml_dataclass@dataclassclassRootFiles:__ns__=CONTAINER_NSrootfile:List[RootFile]# see Gotchas, this workaround is required for type hinting@xml_dataclass@dataclassclassContainer(XmlDataclass):__ns__=CONTAINER_NSversion:strrootfiles:RootFiles# WARNING: this is an incomplete implementation of an OPF containerdefxml_validate(self)->None:ifself.version!=\"1.0\":raiseValueError(f\"Unknown container version '{self.version}'\")if__name__==\"__main__\":nsmap:NsMap={None:CONTAINER_NS}# see Gotchas, stripping whitespace and comments is highly recommendedparser=etree.XMLParser(remove_blank_text=True,remove_comments=True)lxml_el_in=etree.parse(\"container.xml\",parser).getroot()container=load(Container,lxml_el_in,\"container\")lxml_el_out=dump(container,\"container\",nsmap)print(etree.tostring(lxml_el_out,encoding=\"unicode\",pretty_print=True))GotchasType hintingThis can be a real pain to get right. Unfortunately, if you need this, you may have to resort to:@xml_dataclass@dataclassclassChild:__ns__=Nonepass@xml_dataclass@dataclassclassParent(XmlDataclass):__ns__=Nonechildren:ChildIt's important that@dataclassbe thelastdecorator, i.e. the closest to the class definition (and so the first to be applied). Luckily, only the root class you intend to pass toload/dumphas to inherit fromXmlDataclass, but all classes should have the@dataclassdecorator applied.Whitespace and commentsIf you are able to, it is strongly recommended you strip whitespace and comments from the input vialxml:parser=etree.XMLParser(remove_blank_text=True,remove_comments=True)By default,lxmlpreserves whitespace. This can cause a problem when checking if elements have no text. The library does attempt to strip these; literally via Python'sstrip(). Butlxmlis likely faster and more robust.Similarly, comments are included by default, and because loading is strict, they will be considered as nodes that the dataclass has not declared. It is recommended to omit them during parsing.Optional vs requiredOn dataclasses, optional fields also usually have a default value to be useful. But this isn't required;Optionalis just a type hint to sayNoneis allowed. This would occur e.g. if an element has no children.For loading XML dataclasses, whether or not a field is required is determined by if it has adefault/default_factorydefined. If so, and it's missing, that default is used. Otherwise, an error is raised.For dumping, the default isn't considered. Instead, if a value is marked asOptionaland the value isNone, it isn't written.This makes sense in many cases, but possibly not every case.Changelog[0.0.9] - 2022-02-10Fix issue passing options when loading children - thankstim-lansen![0.0.7] and [0.0.8] - 2021-04-08Warn if comments are found/don't treat comments as child elements in error messagesAllow lenient loading of undeclared attributes or children[0.0.6] - 2020-03-25Allow ignored fields viainit=falseor theignoredfunction[0.0.5] - 2020-02-18Fixed type hinting for consumers. While the library passed mypy validation, it was hard to get XML dataclasses in a codebase to pass mypy validation[0.0.4] - 2020-02-16Improved type resolving. This lead to easier field definitions, asattrandchildare no longer needed because the type of the field is inferred[0.0.3] - 2020-02-16Added support for union types on childrenDevelopmentThis project usespre-committo run some linting hooks when committing. When you first clone the repo, please run:pre-commit installYou may also run the hooks at any time:pre-commit run --all-filesDependencies are managed viapoetry. To install all dependencies, use:poetry installThis will also install development dependencies such asblack,isort,pylint,mypy, andpytest. Pre-defined tasks make it easy to run these, for examplepoetry run task lint- this runsblack,isort,mypy, andpylintpoetry run task test- this runspytestwith coverageFor a full list of tasks, seepoetry run task --list.LicenseThis library is licensed under the Mozilla Public License Version 2.0. For more information, seeLICENSE."} +{"package": "xmldataset", "pacakge-description": "XML Dataset: simple xml parsingFree software: BSD licenseDocumentation:https://xmldataset.readthedocs.ioHistory0.1.0 (2014-08-17)First release on PyPI.0.1.1 (2014-08-17)Minor updates to supporting documents0.1.2 (2014-08-17)Minor updates to supporting documents0.1.3 (2014-08-17)Minor updates to supporting documents0.1.4 (2014-08-27)Added default option to profile markup, allows a default value to be\nbe set in the event that the context is missing from the XML, usage\ndefault: Results in a string of \u2018\u2019 for missing entries\ndefault:Missing Results in a string of \u2018Missing\u2019 for missing entries0.1.5 (2014-09-08)Added an option of __DATASET_PROCESSING__ which allows datasets\nto be processed against a function, usage\n__DATASET_PROCESSING__ = dataset:processThe process needs to be parsed as an object parameter as per the\nexisting dataset process functionality0.1.6 (2014-09-24)Updated the default option so that it works with nested defaultsIf there is a level in the XML structure that is not\ntraversed but contains defaults, we may still want these\ndefault values to be reflected in the dataset. The parser\nnow understands the optional syntax -__ALWAYS_FOLLOW__ entryTo allow the parser to follow the profile entry and set defaults0.1.7 (2015-06-02)Added an option for parse_using_profile of global_valuesWhen supplied as a dictionary, all entries in the dictionary\nare merged into new datasets. For example -parse_using_profile(xml, profile, global_values = { \u2018location\u2019 : \u2018Chorleywood\u2019})1.0.0 (2016-06-18)First official release, revamped documentation1.0.1 (2016-10-14)Tidied up core for main execution example (use python -m xmldataset to use the inbuilt example)Added use of pandas to quick startAdded 3.4 to tox.ini, updated .travis.yml to include 3.4 and current1.0.2 (2020-05-30)Added 3.7, 3.8 to tox.ini, updated .travis.yml to include 3.7 and 3.8, removed 2.6 and 3.3 (no longer supported)Implemented fix for duplicate results, thanks @davidmarcanoCode passed through black for standardisation1.0.3 (2020-05-30)Documentation, awesome badge1.0.4 (2020-05-30)History update"} +{"package": "xml-default-dict", "pacakge-description": "No description available on PyPI."} +{"package": "xmldestroyer", "pacakge-description": "This library does a bottom-up transformation of XML documents, extracting the\nparts that are relevant for the task at hand, and either returning it as a\npython generator, or serializing it to disk as XML (again!), JSON or text.One design goal is to be able to process gigabyte-sized documents with constant\nmemory footprint.Inspired by the Haskell librariesScrap Your Boilerplate,uniplateandgeniplate.Example, get the texts from all

            tags in a document:from xmldestroyer import xd\nimport sys\n\ndef p(text, _attrs, _children, _parents):\n return text\n\ninfile, outfile = sys.args\n\nxd(infile, outfile, p=p)This outputs a text file with the text from all

            tags, one per line.Works with python 2.7, 3.3, 3.4 and 3.5."} +{"package": "xmldict", "pacakge-description": "Convert xml to python dictionaries, and vice-versa.Installationpip install xmldictOn most of the systems, you will need thesudopermissions if you are doing a system wide\ninstall.sudo pip install xmldictExmaple::# Converting xml to dictionary\n>>> xmldict.xml_to_dict(\u2018\u2019\u2019\n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \n\u2026 \u2018\u2019\u2019)\n{\u2018root\u2019: {\u2018persons\u2019: {\u2018person\u2019: [{\u2018name\u2019: {\u2018last\u2019: \u2018bar\u2019, \u2018first\u2019: \u2018foo\u2019}}, {\u2018name\u2019: {\u2018last\u2019: \u2018bar\u2019, \u2018first\u2019: \u2018baz\u2019}}]}}}::# Converting dictionary to xml\n>>> xmldict.dict_to_xml({\u2018root\u2019: {\u2018persons\u2019: {\u2018person\u2019: [{\u2018name\u2019: {\u2018last\u2019: \u2018bar\u2019, \u2018first\u2019: \u2018foo\u2019}}, {\u2018name\u2019: {\u2018last\u2019: \u2018bar\u2019, \u2018first\u2019: \u2018baz\u2019}}]}}})\n\u2018barfoobarbaz\u2019Convert xml to python dictionaries."} +{"package": "xmldict_translate", "pacakge-description": "Utils for converting strings between \u201cxml\u201d and \u201cdict\u201d formatsThis package contains functions:xml2dict(xml-string) -> dictionary\ndict2xml(dictionary) -> xml-stringNow support python2.7 and python3.3"} +{"package": "xmldiff", "pacakge-description": "xmldiffxmldiffis a library and a command-line utility for making diffs out of XML.\nThis may seem like something that doesn\u2019t need a dedicated utility,\nbut change detection in hierarchical data is very different from change detection in flat data.\nXML type formats are also not only used for computer readable data,\nit is also often used as a format for hierarchical data that can be rendered into human readable formats.\nA traditional diff on such a format would tell you line by line the differences,\nbut this would not be be readable by a human.xmldiffprovides tools to make human readable diffs in those situations.Full documentation is onxmldiff.readthedocs.ioxmldiffis still under rapid development,\nand no guarantees are done that the output of one version will be the same as the output of any previous version.Quick usagexmldiffis both a command-line tool and a Python library.\nTo use it from the command-line, just runxmldiffwith two input files:$ xmldiff file1.xml file2.xmlThere is also a command to patch a file with the output from thexmldiffcommand:$ xmlpatch file.diff file1.xmlThere is a simple API for usingxmldiffas a library:from lxml import etree\nfrom xmldiff import main, formatting\n\ndiff = main.diff_files('file1.xml', 'file2.xml',\n formatter=formatting.XMLFormatter())There is also a methoddiff_trees()that take two lxml trees,\nand a methoddiff_texts()that will take strings containing XML.\nSimilarly, there ispatch_file()patch_text()andpatch_tree():result = main.patch_file('file.diff', 'file1.xml')Changes fromxmldiff0.6/1.xA complete, ground up, pure-Python rewriteEasier to maintain, the code is less complex and more Pythonic,\nand uses more custom classes instead of just nesting lists and dicts.Fixes the problems with certain large files and solves the memory leaks.A nice, easy to use Python API for using it as a library.Adds support for showing the diffs in different formats,\nmainly one where differences are marked up in the XML,\nuseful for making human readable diffs.These formats can show text differences in a semantically meaningful way.An output format compatible with 0.6/1.x is also available.2.0 is currently significantly slower thanxmldiff0.6/1.x,\nbut this will change in the future.\nCurrently we make no effort to makexmldiff2.0 fast,\nwe concentrate on making it correct and usable.ContributorsLennart Regebro,regebro@gmail.com(main author)Stephan Richter,srichter@shoobx.comAlbertas Agejevas,alga@shoobx.comGreg Kempe,greg@laws.africaFilip Demski,glamhoth@protonmail.comThe diff algorithm is based on \u201cChange Detection in Hierarchically Structured Information\u201d,\nand the text diff is using Google\u2019sdiff_match_patchalgorithm.Changes2.6.3 (2023-05-21)And there was a namespace bug in the patch as well. #1182.6.2 (2023-05-21)Solved an error in the xmlformatter when using default namespaces. #892.6.1 (2023-04-05)#108: Fixed an error that happens if using namespaces like ns0 or ns1.2.6 (2023-04-03)AddedInsertNamespaceandDeleteNamespaceactions for better handling\nof changing namespaces. Should improve any \u201cUnknown namespace prefix\u201d\nerrors. Changing the URI of a a namespace prefix is not supported, and will\nraise an error.2.6b1 (2023-01-12)Used geometric mean for the node_ratio, for better handling of simple nodes.Added an experimental \u2013best-match method that is slower, but generate\nsmaller diffs when you have many nodes that are similar.The -F argument now also affects the \u2013fast-match stage.2.5 (2023-01-11)Make it possible to adjust the attributes considered when comparing nodes.Python versions 3.7 to 3.11 are now supported.Improved node matching method, that puts more emphasis similarities than\ndifferences when weighing attributes vs children.Added a parameter to return error code 1 when there are differences between the filesAdded a parameter for ignoring attributes in comparison.Solved a bug in xmlpatch in certain namespace situations.Added a \u2013diff-encoding parameter to xmlpatch, to support diff-files that are\nnot in your system default encoding.2.4 (2019-10-09)Added an option to pass pairs of (element, attr) as unique\nattributes for tree matching. Exposed this option on the command\nline, too.2.3 (2019-02-27)Added a simplexmlpatchcommand and API.Multiple updates to documentation and code style2.2 (2018-10-12)A workaround for dealing with top level comments and the xml formatter2.1 (2018-10-03)Changed the substitution unicode character area to use the Private Use Area\nin BMP(0), to support narrow Python buildsAdded \u2013unique-attributes argument.2.1b1 (2018-10-01)Added options for faster node comparisons. The \u201cmiddle\u201d option is now\ndefault, it had very few changes in matches, but is much faster.Implemented a Fast Match algorithm for even faster diffing.Speed improvements through cachingFixed a bug where MoveNode actions sometimes was in the wrong orderAdded an InsertComment action, as comments require different handling,\nso it\u2019s easier to deal with them this way. You can still use DeleteNode and\nUpdateTextIn for them with no special handling.When renaming tags the XMLFormatter will mark them with \u201cdiff:rename\u201d\ninstead of making a new tag and deleting the old.Tags will now be moved first, and updated and renamed later, as the new\ntag name or attributes might not be valid in the old location.2.0 (2018-09-25)A complete, bottom-up, pure-python rewriteNew easy API100% test coverageNew output formats:A new default output format with new actionsA format intended to be parseable by anyone parsing the old format.XML with changes marked though tags and attributesxmldiff 2.0 is significantly slower than xmldiff 0.6 or 1.0,\nthe emphasis so far is on correctness, not speed."} +{"package": "xml_diff", "pacakge-description": "Compares the text inside two XML documents and marks up the differences withandtags.This is the result of about 7 years of trying to get this right and coded simply. I\u2019ve used code like this in one form or another to compare bill text on GovTrack.us .The comparison is completely blind to the structure of the two XML documents. It does a word-by-word comparison on the text content only, and then it goes back into the original documents and wraps changed text in newandwrapper elements.The documents are then concatenated to form a new document and the new document is printed on standard output. Or use this as a library and callcompareyourself with twolxml.etree.Elementnodes (the roots of your documents).The script is written in Python 3.ExampleComparing these two documents:\n Here is some bold text.\nand:\n Here is some italic content that shows how xml_diff works.\nYields:\n \n Here is some bold text.\n \n \n Here is some italic content that shows how xml_diff works.\n \nOn Ubuntu, get dependencies with:apt-get install python3-lxml libxml2-dev libxslt1-devFor really fast comparisons, get Google\u2019s Diff Match Patch library , as re-written and sped-up by @leutloff and then turned into a Python extension module by me :pip3 install diff_match_patch_pythonOr if you can\u2019t install that for any reason, use the pure-Python library:pip3 install diff-match-patchThis is also at . xml_diff will use whichever is installed.Finally, install this module:pip3 install xml_diffThen call the module from the command line:python3 -m xml_diff --tags del,ins doc1.xml doc2.xml > changes.xmlOr use the module from Python:import lxml.etree\nfrom xml_diff import compare\n\ndom1 = lxml.etree.parse(\"doc1.xml\").getroot()\ndom2 = lxml.etree.parse(\"doc2.xml\").getroot()\ncomparison = compare(dom1, dom2)The two DOMs are modified in-place.Optional ArgumentsThecomparefunction takes other optional keyword arguments:mergeis a boolean (default false) that indicates whether the comparison function should perform a merge. If true,dom1will contain not justnodes but alsonodes and, similarly,dom2will contain not justnodes but alsonodes. Although the two DOMs will now contain the same semantic information about changes, and the same text content, each preserves their original structure \u2014 since the comparison is only over text and not structure. The newins/delnodes contain content from the other document (including whole subtrees), and so there\u2019s no guarantee that the final documents will conform to any particular structural schema after this operation.word_separator_regex(defaultr\"\\s+|[^\\s\\w]\") is a regular expression for how to separate words. The default splits on one or more spaces in a row and single instances of non-word characters.differis a function that takes two arguments(text1, text2)and returns an iterator over difference operations given as tuples of the form(operation, text_length), whereoperationis one of\"=\"(no change in text),\"+\"(text inserted intotext2), or\"-\"(text deleted fromtext1). (See xml_diff/__init__.py\u2019sdefault_differfunction for how the default differ works.)tagsis a two-tuple of tag names to use for deleted and inserted content. The default is('del', 'ins').make_tag_funcis a function that takes one argument, which is either\"ins\"or\"del\", and returns a newlxml.etree.Elementto be inserted into the DOM to wrap changed content. If given, thetagsargument is ignored."} +{"package": "xmldiff-real", "pacakge-description": "Xmldiff is a utility for extracting differences between twoxml files. It returns a set of primitives to apply on source tree to obtainthe destination tree..The implementation is based on _Change detection in hierarchically structured- information_, by S. Chawathe, A. Rajaraman, H. Garcia-Molina and J. Widom,- Stanford University, 1996"} +{"package": "xmldiffs", "pacakge-description": "xmldiffsCompare two XML files, with some customized options."} +{"package": "xmldirector.bookalope", "pacakge-description": "xmldirector.bookalopeIntegration ofPlone (https://www.plone.org)XML Director (https://www.xml-director.info)Bookalope (https://bookalope.net)This Plone 4/5 add-on allows to generate Ebook formats (EPUB, EPUB3, Mobi) and\nother formats (ICML, PDF, DOCX) from content stored in XML Director.RequirementsPlone 4.3 (tested)Plone 5.0 (experimental, in progress)XML Director (xmldirector.plonecore)ConfigurationInstallxmldirector.bookalopethrough the Plone add-on installer\nand configure your Bookalope API key and choose if you are running against\nBookalope\u2019s production or beta environment.APIThere is only one public API method in order to interact with Bookalope\nfrom XML Director code (seexmldirector/bookalope/browser/api.py):convert_bookalope(context, source, cover=None, formats=[], title=u'', author=u'', prefix=None, storage_path='result')context- a XML DirectorConnectorinstancesource- source path of the DOCX file inside the directory configured for the given\nConnectorcontexte.g.src/index.docxcover- source path of cover page imageformats- a list of formats to be generated (supported: epub, epub3, docx, pdf, icml, mobi)title- title used for the ebookauthor- author name of the publicationprefix- generated files will be stored underresult/.storage_path- subpath used to store the generated ebook filesLicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.bookalopeBugtrackerSeehttps://github.com/xml-director/xmldirector.bookalope/issuesAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.5.0 (2018/08/18)improved compatibility with Plone 5.0improved error handling0.3.2 (2016/06/27)updated to latest Bookalope API changes0.3.1 (2016/04/06)cleanup and minor improvements0.3.0 (2016/04/06)added new Bookalope UI0.2.0 (2016/04/05)major cleanupvarious fixesadded REST API endpoint \u2018xmldirector-convert-bookalope\u20190.1.0 (2016/04/04)initial release"} +{"package": "xmldirector.connector", "pacakge-description": "xmldirector.connectorxmldirector.connectorintegrates Plone 5 withlocal filesystemWebDAV-backed backendAWS S3remote servers over SFTP/SSHxmldirector.connectorprovides aConnectorcontent-type that\nmounts a particular storage into Plone.No support for indexing and search mounted content.RequirementsPlone 5.2 with Python 3.6 or higher (tested)Supported backends:eXist-dbBase-XOwnCloudAlfrescoMarklogic ServerAWS S3Cloud federation servicesOtixo.comStoragemadeeasy.comConfigurationGoto the Plone control panel and click on theXML-DirectorConnectorconfiglet and\nconfigure the your serviceExistDBwebdav://localhost:6080/existdb/webdav/dbusername and password required to access your XML database over WebDAVBaseXwebdav://localhost:8984/webdavusername and password required to access your XML database over WebDAVOwncloudwebdav://hostname:port/remote.php/webdavusername and password required to access your Owncloud instance over WebDAVAlfrescowebdav://hostname:port/webdavusername and password required to access your Alfresco instance over WebDAVLocal filesystemfile:///path/to/some/directoryno support for credentials, the referenced filesystem must be readable (and writable)AWS S3s3://bucketnameenter your AWS access key as username and the AWS secret key as password\n(You need to install the Python packagefs-s3fsthrough buildout).SSH/SFTPssh://hostname.comorsftp://hostname.com(You need to install the Python packagefs.sshfsthrough buildout).API notesThe implementation ofxmldirector.connectoris heavily backed by the PyFilesystem 2 API.\nEveryConnectorinstance in Plone gives you access to the mounted storage through thehandle = connector.get_handle()call which is instance offs.base.FS. Checkhttps://docs.pyfilesystem.orgfor details.Compatiblity with rcloneAn alternative to using native drivers under the hood, usingrclone(https://rclone.org/) is meanwhile perhaps the better solution.rcloneis an\napplication (a commandline utility) to interact with up to 40 different storage\nsystems out of the box.rclonealso allows you to mount different storages\ndirectly into your filesystem (tested on Linux but supposed to work on Mac and\nWindows too). So for example, you can mount your Dropbox and Google Drive\nstorages into your local filesystem under/mnt/dropboxand/mnt/driveand\npoint your connector instances tofile:///mnt/dropboxandfile:///mnt/drive. So any interaction would happen through the filesystem\ndriver of Pyfilesystem. The underlying communication with the Dropbox or Google\nDrive API would be handled byrcloneunder the hood.SecurityThe mounted storage gives you access to all contents inside the mounted\nsubtree. The mounted filesystem is sandboxed\n(https://docs.pyfilesystem.org/en/latest/concepts.html#sandboxing). So you can\nnot escape and access content outside the mounted storage.Available driversConnectivity with other backend is accomplished through dedicated driverse that implementation\nthe API layer between PyFilesystem 2 and the related backend.\nSeehttps://www.pyfilesystem.org/page/index-of-filesystems/for all available drivers.LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://bitbucket.org/onkopedia/xmldirector.connectorBugtrackerSeehttps://bitbucket.org/onkopedia/xmldirector.connectorAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.5.0 (2021-02-09)added support for referencing another connector instance for using\ntheir connector configuration0.4.0 (2021-01-26)updates JS resourcesminor tweaks0.3.1 (2020-11-24)uninstall profile addedfix for mod_dav issue when sorting entries (issue #64)0.3.0 (2020-11-04)minor cleanupremoved Python 2 supportremoved defusedxml dependency0.2.9 (2020-05-04)added @@connector-zip-export functionality0.2.8 (2020-03-01)fix for content-disposition header0.2.5 (2020-02-05)removed Python 3 support0.2.4 (2019-07-24)Python 3 fix0.2.3 (2019-07-20)fixed redirection upon remove0.2.2 (2019-07-20)import fix for nested zip filesupdated to fs 2.4.80.2.1 (2019-03-04)restored Python 2.7 compatibilityTravis tests for Python 2.70.2 (2019-02-20)various fixesvarious XML related backports0.1 (2018-12-14)initial release"} +{"package": "xmldirector.crex", "pacakge-description": "xmldirector.crexIntegration ofPlone (https://www.plone.org)XML Director (https://www.xml-director.info)C-REX (http://www.c-rex.net/app/).This module providesa generic support for the C-Rex (www.c-rex.net) conversion servicea REST API for the integration of XML Director with third-party toolsRequirementsPlone 4.3 (tested)Plone 5.0 (tested)XML Director 2.0 (xmldirector.plonecore)LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.crexBugtrackerSeehttps://github.com/xml-director/xmldirector.crex/issuesAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.3.0 (2016/08/18)Plone 5.0 compatibilityimproved error handling0.2.0 (2016/04/07)cleanupnew user interfaces0.1.0 (2015/12/03)initial release"} +{"package": "xmldirector.demo", "pacakge-description": "xmldirector.plonecore demo packageChangelog0.1.1 (2015-04-11)initial release0.1.0 (2015-02-09)initial release"} +{"package": "xmldirector.dita", "pacakge-description": "xmldirector.ditaDITA conversion support for XML DirectorThis module packages theDITA Open ToolkitXMLMind DITA Converteras Python module.APIThe module provides the following API:result = xmldirector.dita.converter.dita2html(ditamap, output_dir_or_file, converter)ditamap- path to DITA map fileoutput_dir_or_file- output directory (DITA) or output filename (DITAC)converter- name of the converter to be used (ditafor DITA OT orditacforXMLMind Dita converter)output_filename = xmldirector.dita.html2dita.html2dita(html_filename, infotype, output_filename)html_filename- name of HTML input fileoutput_filename- name of generated DITA file (a temporary file will be generated if omitted)infotype- DITA content type (topic, task, reference, concept)Commandline usageYou can start a DITA conversion from the commandline:> bin/dita2html -d some.ditamap -o output_directory -c dita|ditac-d- path to DITA map file-o- name of output directory (for DITA-OT) or the HTML output file\n(XMLMind DITAC)-c- name of the converter to be used (ditafor DITA OT orditacforXMLMind Dita converter)You can convert a HTML file to DITA through the commandline:bin/html2dita -h\nusage: html2dita [-h] [-i HTML_FILENAME] [-f topic] [-o None]\n\noptional arguments:\n -h, --help show this help message and exit\n -i HTML_FILENAME, --html-filename HTML_FILENAME\n Input HTML filename\n -f topic, --infotype topic\n DITA type (topic, concept, reference, task)\n -o None, --output-filename None\n Output DITA filenameLicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.ditaBugtrackerSeehttps://github.com/xml-director/xmldirector.dita/issuesAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.1.0 (2016/06/22)HTML -> DITA conversion using Saxon or LXML0.0.12 (2016/06/21)tidy HTML document internally0.0.11 (2016/06/21)added html2dita()0.0.10 (2016/06/21)updated to DITA OT 2.3.1updated to DITAC 2.6.10.0.1 (03/01/2016)initial release"} +{"package": "xmldirector.dropbox", "pacakge-description": "xmldirector.dropboxIntegration ofPlone (https://www.plone.org)XML Director (https://www.xml-director.info)DropboxRequirementsPlone 4.3 (tested)Plone 5.0 (tested)XML Director 2.0 (xmldirector.plonecore)UsageFirst you need to register your own App as Dropbox developer\nonhttps://dropbox.com/developer. Your application must be configured\nfor full dropbox access. The application key and application secret\nmust be configured globally inside your Plone site setup -> XML Director\nDropbox setting.AConnectorinstance must be authorized with Dropbox (seeDropboxtab/action).The connection URL for aConnectorconnected to Dropbox must bedropbox://dropbox.com/.LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.dropboxBugtrackerSeehttps://github.com/xml-director/xmldirector.dropboxAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog1.0.0 (2016-08-18)compatibility with Plone 5.0improved error handling0.9.0 (2016-07-27)initial release"} +{"package": "xmldirector.facebook", "pacakge-description": "xmldirector.facebookIntegration ofPlone (https://www.plone.org)FacebookRequirementsPlone 4.3 (tested)Plone 5.0 (tested)XML Director 2.0 (xmldirector.plonecore)UsageFirst you need to register your own App as Facebook developer.\nonhttps://apps.facebook.com/. Your application must be configured\nfor full facebook access. The application key and application secret\nmust be configured globally inside your Plone site setup -> XML Director\nFacebook setting.AConnectorinstance must be authorized with Facebook (seeFacebooktab/action).The connection URL for aConnectorconnected to Facebook must befacebook://facebook.com/.LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.facebookBugtrackerSeehttps://github.com/xml-director/xmldirector.facebook/issuesAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.2.0 (2016-08-18)Plone 5.0 compatibilityimproved error handling0.1.0 (2016-04-10)initial release"} +{"package": "xmldirector.plonecore", "pacakge-description": "xmldirector.plonecoreNoteThis moduleisa solution for mounting XML databases like eXist-db or\nBaseX into Plone through their WebDAV portisa solution for construction Dexterity content-types programmatically\nor through-the-web with XML related fields where the content is stored\nin BaseX or eXist-dbisan _experimental_ solution for mounting general WebDAV\nservices into Ploneis nota replacement for the ZODBxmldirector.plonecoreis the technical foundation of the XML-Director\nproject (www.xml-director.info). The goal of the XML-Director project is\nbuilding an enterprise-level XML content management system on top of the CMS\nPlone (www.plone.org) with support for XML databases like eXis-db or Base-X.\nHowever the underlaying implementation can also be used to mount arbitrary\nbackend through WebDAV into Plone.xmldirector.plonecoreintegrates Plone 4.3 or 5.1 with\neXist-db or Base-X or providing the following features:mounts an arbitary eXist-db or Base-X collection into PloneACE editor integrationZIP export from eXist-db or Base-XZIP import into eXist-db or Base-Xpluggable view mechanism for configuring custom views for XML database\ncontent by filename and view namecreate, rename or delete collections through the webextensible architecture through Plone Dexterity behaviorssupport for XQuery scripts called through the RESTXQ layer of eXist-db\n(allows you to call XQuery scripts and return the output format (JSON,\nHTML, XML) depending on your application requirements)dedicated per-connector logging facilitysmall and extensibleexperimental support for mounting arbitrary WebDAV service into PloneXMLText- a field for storing XML content in BaseX or eXist-dbXPathField- for retrieving parts of XML content stored within aXMLTextfield through an XPath expression (e.g. for extracting\nand displaying metadata from XML content)XMLBinaryandXMLImagefields for storing binary data and images\nin BaseX or eXist-db. The functionality is identical with the standard\nDexterity file and image fields (except for the different storage layer)The primary usecase forxmldirector.plonecoreis the integration of XML document\ncollections into Plone using eXist-db or Base-X as storage layer.xmldirector.plonecoreis\nnot storage layer for Plone content in the first place although it could be\nused in some way for storing primary Plone content (or parts of the content)\ninside eXist-db or Base-X. There is no build-in support for mapping metadata as stored in\nXML documents to Plone metadata or vice versa. However this could be\nimplemented easily in application specific code build on top ofxmldirector.plonecore. The design goal ofxmldirector.plonecoreis to provide the basic\nfunctionality for integrating Plone with eXist-db or Base-X without implementing any\nfurther specific application requirements. Additional functionality can be\nadded through Dexterity behaviors, supplementary browser views, event lifecycle\nsubscribers and related technology.RequirementsPlone 4.3 (tested)Plone 5.0 (tested)Plone 5.1 (tested)Supported backends:eXist-db 2.2 and 3.0Base-X >= 8.2OwnCloudAlfrescoMarklogic ServerDropbox (via dropdav.com (Dropbox to WebDAV bridge, paid SaaS) or via xmldirector.dropbox)AWS S3Cloud federation servicesOtixo.comStoragemadeeasy.comexperimental support for the following backends/protocols (don\u2019t\nuse XML Director with these protocols/backends in production):FTP (working in general, open issues with the connection pool)SFTP (working in general, open issues with the connection pool)NoteYou need to pinfs=0.5.4in your buildout configurationConfigurationGoto the Plone control panel and click on theXML-DirectorCoreconfiglet and\nconfigure the your serviceExistDBhttp://localhost:6080/existdb/webdav/dbusername and password required to access your XML database over WebDAVBaseXhttp://localhost:8984/webdavusername and password required to access your XML database over WebDAVOwncloudhttp://hostname:port/remote.php/webdavusername and password required to access your Owncloud instance over WebDAVAlfrescohttp://hostname:port/webdavusername and password required to access your Alfresco instance over WebDAVDropbox (via dropdav.com SaaS)https://dav.dropdav.comusername and password required of your dropdav.com accountDropbox (via xmldirector.dropbox)dropbox://dropbox.comaccess to Dropbox must be authenticated using OAuth\n(see xmldirector.dropbox documentation)SME (storagemadeeasy.com)https://webdaveu.storagemadeeasy.com(EU)https://webdav.storagemadeeasy.com(US)username and password required of your storagemadeeasy.com accountOtixo.comhttps://otixo.comusername and password required of your otixo.com accountLocal filesystemfile:///path/to/some/directoryno support for credentials, the referenced filesystem must be readable (and writable)AWS S3s3://bucketnameenter your AWS access key as username and the AWS secret key as passwordyou need to install thebotomodule (either usingpipor using zc.buildout)FTPftp://hostname/path/to/directoryusername and password that are necessary to access the configured directory path\nthrough FTPSFTPsftp://hostname/path/to/directoryusername and password that are necessary to access the configured directory path\nthrough SFTP. Username and password can be omitted in case the XML Director server (your\nPlone instance) has access using SSH keys (without passphrase) to the remote SFTP\nservice. The handling of username + password vs. SSH authentication using SSH keys is\ncurrently under investigation and might change in a further release.Protocol/ServiceNative support3rd-party SaaS support (e.g. Otixo.com, storagemadeeasy.com)Local filesystemYesNoWebDAVYesYesExistDB 2.2/3.0YesYesBaseX 8.3YesYesAmazon AWS S3YesYesAlfrescoYesYesOwncloudYesYesDropbox(experimental)YesSFTP(experimental)YesFTP(experimental)YesUsing xmldirector.plonecoreThe package provides a new content-typesConnectorthat will include\neXist-db or Base-X into Plone - either from the top-level collection of your eXist-db/Base-X\ndatabase or from a subcollection. You can browse and traverse into\nsubcollections, view single documents or edit text-ish content through the web\n(using the build-in ACE editor integration).All connection settings (URL, username and password can be overriden on\nthe connector level) in order to ignore the Plone site-wide eXist-db\nsettings).NoteThis module provides a generic integration of arbitrary\nWebDAV services like OwnCloud, BaseX (over WebDAV) or even other Plone\nserves (exposed through the Plone WebDAV source port) with Plone.\nThis integration is highly experimental and not the primary purpose\nofxmldirector.plonecore. Use the functionality at your own risk.\nIn order to use this module together with WebDAV services other than the\nXML database eXist-db: you have to set the emulation mode towebdavinside the eXist-db control panel of PloneDexterity fieldsxmldirector.plonecorecomes with the following Dexterity fields that\ncan be either used programmatically in your own field schema or through-the-web.XMLTextTheXMLTextcan be used to storevalidXML content. The field is rendered\nwithout Plone using the ACE editor. You can perform a client-side XML validation\nwithin the edit mode of a document by clicking on theValidate XMLbutton.\nA document with invalid XML content can not be submitted or saved. Invalid XML\nwill be rejected with an error message through the edit form.XMLXPathTheXMLXPathfield can be used to reference anXMLTextfield in order\nto display a part of the XML content using an XPath expression.ExampleAnXMLPathfield with field namemyxmlmight contain the following XML\ncontent:\n\n \n This is a text\n \n ....\nIn order to extract and display the text within a dedicated Dexterity field\nyou can use the following extended expression:field=<fieldname>,xpath=<xpath expression>In this case you would use:field=myxml,xpath=/doc/metadata/title/text()Note that the current syntax is very rigid and does not allow any whitespace\ncharacters expect within the <xpath expression>.XMLBinary, XMLImageSame as file and image field in Plone but with BaseX or eXist-db as\nstorage layer.LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://bitbucket.org/onkopedia/xmldirector.plonecoreBugtrackerSeehttps://bitbucket.org/onkopedia/xmldirector.plonecoreTravis-CIAll releases and code changes to XML Director are automatically tested against\nvarious combinations of Plone and backend versions. The current test setup\nconsists of 14 different combinations against the most common databases and\nservices. Seehttps://github.com/xml-director/xmldirector.plonecore/blob/master/.travis.ymlfor testing details. A complete test run consists of over 1400 single tests.Seehttps://travis-ci.org/xml-director/xmldirector.plonecoreCreditsThe development ofxmldirector.plonecorewas funded as part of a customer project\nby Deutsche Gesellschaft f\u00fcr H\u00e4matologie und medizinische Onkologie (DGHO).AuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog2.1.1 (2017-07-23)fixed JS issue in rename action2.1.0 (2017-04-04)compatibility with Plone 5.12.0.4 (2017-01-10)pinned fs==0.5.42.0.3 (2016-12-05)minor bug fixes2.0.2 (2016-08-26)added explicit setContext() to BaseWrapper class for setting a custom\nconnector class2.0.0 (2016-08-18)full compatibility with Plone 5.0 (limited to Plone 5.1 alpha)replaced DataTables.net with agGridmajor UI changesupdated to latest ACE versionswitch to Dropzone.js for multi-file uploads1.6.1 (2016-04-08)improved unicode filename handling across driversPEP8 fixes1.6.0 (2016-03-18)experimental native Dropbox support (requires installed \u2018dropbox\u2019 SDK for\nPython using \u2018pip install dropbox\u2019 or by adding \u2018dropbox\u2019 as dependency\ninside your buildout) - not ready for productionworkaround for sporadic open() failures with Exist-DB:\nopen() will be tried up to three times (with a slight delay between\ncalls in order to give the backend a chance to recover in between)support for latest plone.api releases (which minor monkey patch)move restapi permission checks to ZCML configurationupdated to ACE 1.2.3updated to DataTables 1.10.11support for latest plone.api release1.5.0 (2016-02-17)huge internal renaming: renamed all webdav_* variables\nto connector_*adjusted tests to Marc Logic Server1.4.2 (2016-02-02)fix in restapi in the context of local fs tests1.4.1 (2016-01-18)pass query string down to redirection call within __call__()1.4.0 (2016-01-11)new REST API1.3.0 (2015-12-20)added \u2018create_if_not_existing\u2019 parameter to webdav_handle() methodadded ensuredir() to wrapper base class1.3.0b1 (2015-10-15)support for OSFS (local filesystem), S3individual per-connector URL configurationsupport for multi-file uploadsunicode fixes in the context of testing federated cloud solutionsmassive amount of smaller internal and UI fixeslots of testing with different storage backendsupdated tests1.2.0 (2015-09-29)refactored zip export functionalitynew supported WebDAV storage backends:AlfrescoOwncloudDropbox (via dropdav.com SaaS)1.1.1 (2015-08-25)updated selenium version pinbetter encapsulation of the DataTables Javascript initialization\ncode in local.jsfixed integration bug in Plone 5.01.1.0 (2015-08-21)some CSS styles fine-tuningadded optionaldirsparameter to ZIP export API for\nexporting only a subset of the export directory structureadded control panel functionality for installing Exist-DB\nspecific RESTXQ script (e.g. all-locks.xql which is needed\nby the lockmanager introspection control panel for getting\nhold of all locks).ZIP import now works inside the given subdirectory and no longer\nonly on the top level directory of the connectordelete actions for collections and collection itemsdelete actions now ask for confirmationmassive speedup of ZIP import by reducing and caching WebDAV operationsusing Datatables.net for collections and collection itemsZIP export/import is now more robust with directories or filenames\ncontaining non-ascii charactersimproved Plone 5.0 integration1.0.4 (2015-07-22)updated ACeditor to version 1.2.01.0.3 (2015-07-22)using DataTables.net for connector logging view instead of TableUtils JS1.0.2 (2015-06-12)updated Saxon 6.0.6HEadded get_last_user(), get_last_date() to logger API for\ngetting hold of the username performing the last logger entry1.0.0 (2015-05-30)using defusedxml module for protecting XML Director against\nmalicious data and XML related security attacksadded support for \u2018force_default_view\u2019 URL parameter\nto enforce redirection to the default anonymous viewsupport for logging HTML messages0.4.2 (2015-04-11)updated lxml, cssselect dependencies to newest versionsanalyzed XSD parsing slowness and logging/warning long-running\nXSD parsingfirst serious take on Plone 5.0 compatibility on the UI level\n(backend tests have been always passing but we had serious\nUI issues until 5.0 beta 1 and there are still issues). Plone 5\nbeta support is work-in-progress and not fully completed.0.4.1 (2015-04-07)added entry_by_uuid() to PersistentLogAdapter APIfixed unicode issues with uploaded binaries/images with non-ascii\nfilenamesadded \u2018version_suffix\u2019 parameter to parser_folder() of validator registryJavascript cleanup0.4.0 (2015-02-18)added @@transformer-registery viewadded @@transformer-registery-view viewupdated xmldirector.demo to use Transformer registryadded (optional) debug option for debugging Transformer steps (input and\noutput data of a step is written to disk)added more testssupport for XSLT2+3 transformations by integrating Saxon 9.6 HE0.3.6 (2015-02-06)re-added Dexterity testsadded validator registry for XML schemas, DTDs, Schematron files\nand RelaxNG schemasadded @@validator-registry viewadded unified validation API based on registered validation filesdocumented validator registry0.3.5 (2015-01-30)rewritten persistent logger internals: now uses an OOBTree\nfor holding all logging entries instead of a persistent list\nin order to support filtering of log entries by min-max\nvalueslogger table now uses a paginated view with searchable columnswebdav password setting is no longer required (empty password allowed)fixed Webdav authentication issue with empty passwordsmoved demo related code into a dedicated package xmldirector.demo0.3.4 (2015-01-13)default view handler accept a custom request/filename\nargument in order to override the name of downloaded filefixed bug in view registry with BrowserView as view handleradded PersistentLoggerAdapter for adopting arbitrary\npersistent objects for persistent logging through a Zope\nannotation0.3.3 (2015-01-05)running the tests should not leave any testing directory\ntraces within the XML databasesalmost 100% test coverage for the core functionalitymore testsadded documentation on content-types0.3.2 (2014-12-30)SHA256 calculation for xml content now generated in\na more stable way (but possibly much slower way)API for service-side XML validationadded Docker supportadded XSLT registryadded Shakespeare XML data for XMLDocument demo content-typeadded \u2018test_all.sh\u2019 script for running tests against BaseX\nand eXist-db Docker containers0.3.1 (2014-12-12)addedTest connectionbutton to controlpanelmoved test content type into a dedicated profiledemocontentMoved metadata handling from JSON to XML on the storage\nlayer in order to let the underlaying database index\nthe .metadata.xml files as well0.3.0 (2014-12-11)renamed zopyx.existdb to xmldirector.plonecoreexperimental Dexterity support with four new fields:XMLText - for XML contentXMLXPath - for referencing XMLText parts through an XPath\nexpressionXMLImage and XMLBinary - same as image and file fields in Dexterity\nbut with eXist-db as storage layerremovedemulationconfiguration optionadded plone.app.dexterity as dependencyupgraded to ACE editor V 1.1.8added progressbar for zip_upload()added support for importing a single file through the\nZIP import form into the current subdirectory0.2.11 (2014-11-08)updated documentation0.2.10 (2014-11-08)bugfix release0.2.9 (2014-11-01)support for overriding credentials locally0.2.8 (2014-11-01)minor fix for mounting Plone sites over WebDAV into another Plone site0.2.7 (2014-11-01)experimental support for BaseX XML database through the WebDAV API.\nLimitations: REMOVE operations over WebDAV do not seem to work\nagainst BaseX 7.90.2.6 (2014-11-01)more tests0.2.5 (2014-10-30)experimental traversal support for accessing WebDAV resources by path\nusing (un)restrictedTraverse()minor URL fixesmore tests0.2.4 (2014-10-22)configuration option for default view for authenticated site visitors0.2.3 (2014-10-13)fix in saving ACE editor content0.2.2 (2014-10-12)typo in page template0.2.1 (2014-10-12)added support for renaming a collection through the web0.2.0 (2014-10-02)various minor bug fixesadded basic tests0.1.17 (2014-09-25)fixed action links0.1.16 (2014-09-25)Connector is no longer a folderish object0.1.15 (2014-09-22)removed indexing support completely (leaving a specific\nindexing functionality to policy packages using zopyx.existdb)0.1.14 (2014-09-15)fixed subpath handling in create/remove collections0.1.13 (2014-09-07)support for removing collections TTW0.1.12 (2014-09-05)support for creating new collections TTW0.1.11 (2014-08-21)action \u201cClear log\u201d added0.1.10 (2014-08-05)log() got a new \u2018details\u2019 parameter for adding extensive logging information0.1.9 (2014-08-01)human readable timestamps0.1.8 (2014-07-31)minor visual changes0.1.7 (2014-07-29)rewritten code exist-db browser code (dealing the correct\nway with paths, filenames etc.)0.1.6 (2014-07-29)fixed improper view prefix in directory browser0.1.5 (2014-07-13)minor fixes and cleanup0.1.4 (2014-07-12)made webservice query API aware of all output formats (xml, html, json)timezone handling: using environment variable TZ for converting eXist-db UTC\ntimestamps to the TZ timezone (or UTC as default) for display purposes with\nPlone0.1.3 (2014-07-07)added webservice API interfacevarious bug fixes0.1.2 (2014-06-30)various bug fixes0.1.0 (2014-06-20)initial release"} +{"package": "xmldirector.twitter", "pacakge-description": "xmldirector.twitterIntegration ofPlone (https://www.plone.org)TwitterRequirementsPlone 4.3 (tested)Plone 5.0 (tested)XML Director 2.0 (xmldirector.plonecore)UsageFirst you need to register your own App as Twitter developer.\nonhttps://apps.twitter.com/. Your application must be configured\nfor full twitter access. The application key and application secret\nmust be configured globally inside your Plone site setup -> XML Director\nTwitter setting.AConnectorinstance must be authorized with Twitter (seeTwittertab/action).The connection URL for aConnectorconnected to Twitter must betwitter://twitter.com/.LicenseThis package is published under the GNU Public License V2 (GPL 2)Source codeSeehttps://github.com/xml-director/xmldirector.twitterBugtrackerSeehttps://github.com/xml-director/xmldirector.twitter/issuesAuthorAndreas Jung/ZOPYXHundskapfklinge 33D-72074 Tuebingen, Germanyinfo@zopyx.comwww.zopyx.comChangelog0.2.0 (2016-08-19)fixes for Plone 5internal cleanup0.1.0 (2016-04-10)initial release"} +{"package": "xmldsig", "pacakge-description": "A XML Signature (XMLDSig) is a syntax to provide digital signatures of an XML file. Support for these signatures is provided by, for instance, the libxmlsec C library. A Python wrapper for this library is available as pyXMLSec. However, this wrapper only provides access to the low-level API functions and does not achieve a Pythonic API.This xmldsig module is a convenience wrapper for pyXMLSec. It has been built initially to be used for signing and validating messages from the Dutch iDEAL payment processing system, but has been extended for general use. The module is inspired by the code examples of pyXMLSec and the module made by Philippe Lagadec. However, his module lacks the ability to specify the key format, which is required to load certificates as named keys. This module has been made to mimic large parts of Lagadec\u2019s API to ensure an easy transition.See the documentation athttps://github.com/AntagonistHQ/xmldsigfor more information."} +{"package": "xmldt", "pacakge-description": "xmldt - a Python module to process XML/HTML files in natural waySynopsispydt file.xml > proc.py\n\nfrom xmldt import XmlDtpydt scriptpydtis used to bootstrap the processing taskxmldtvariables and functionsclass proc(XmlDt): # or HtmlDt for HTML\n\n\nproc(strip=True, # _flags dictionary\n empty=False # keep spaces\n ns_strip= ???\n\nproc(filename=\"x.xml\")__defaul__(s,ele)__pcdata__(s,text)__comment__(s,txt)__end__(s,result)__join__(s,ele)@XmlDt.dt_tag(\"id-id\")\\ndef id_id(s, e):....toxml functiontoxml(\"foo\", {}) == \"<foo/>\"\n toxml(\"foo\", {\"a\": \"b\"}) == \"<foo a=\\\"b\\\"/>\"\n toxml(\"foo\", {}, \"bar\") == \"<foo>bar</foo>\"\n toxml(\"foo\", {}, {\"a\": \"b\", \"c\": \"d\"}) == \"<foo><a>b</a><c>d</c></foo>\"\n toxml(\"foo\", {}, [\"a\", \"b\"]) == \"<foo>a</foo><foo>b</foo>\"\n toxml(\"foo\", {\"a\": \"b\"}, [\"a\", \"b\"]) == \"<foo a=\\\"b\\\">a</foo><foo a=\\\"b\\\">b</foo>\"\n toxml(\"foo\", {}, [\"a\", \"b\"], [\"c\"]) == \"<foo><item>a</item><item>b</item><item>c</item></foo>\"Function Class Elementele = Element(\"tag\", {}, \"contents\")\n ele.xml \"<tag>contents</tag>\"\n ele.toxml(v={\"a\":\"b\"}) \"<tag a='b'>contents</tag>\"\n ele.tag ele.tag=\"val\" or ele.q\n ele.contents ele.c = \"\"\".... \"\"\" or ele.c\n ele[\"att\"] : value or None ele.attrs or ele.velement functions and methodsele.parent : element or Noneele.parent.tag : tag-nameele[\"root\"]ele[\"gparent\"]ele.in_context(\"tag1\")ele._dt(DT)self functions and methodss._pathor s.dt_paths._parentor s.dt_parent = s._path[-1]s._gparentor s.dt_gparent = s._path[-2]s._rootor s.dt_root = s._path[0]types_types = { 'table' : 'list', 'tr' : 'list', 'td' : 'list' }Valid types arezerolistmapmmap"} +{"package": "xmle", "pacakge-description": "# xmle\nAn extension to xml.etree.ElementTree.Element to handle xml snippetsThis library aids in generating neatly formatted HTML output from a\nvariety of object types.Check out some examples in theExample.ipynbnotebook."} +{"package": "xmlego", "pacakge-description": "XMLegoinspired by Odoo templatingXML + Lego: Build template with extensions"} +{"package": "xmlenc", "pacakge-description": "UNKNOWN"} +{"package": "xml-encoder", "pacakge-description": "XML EncoderExamplesEncoding a fileimportxml_encoderpath_in='/foo/bar.xml'path_out='/foo/bar.exml'xml_encoder.encode(path_in,path_out)Decoding a fileimportxml_encoderpath_in='/foo/bar.exml'path_out='/foo/bar.xml'xml_encoder.decode(path_in,path_out)ContactIf you have any questions or concerns, please reach out to me (John Carter) atjfcarter2358@gmail.com"} +{"package": "xmler", "pacakge-description": "Long description and usage instructions can be found athttps://github.com/iDev0urer/xmler"} +{"package": "xmlexicon", "pacakge-description": "Package for transforming a .csv file containing a Ancient Greek - Old Church Slavonic-Latin dictionary into TEI XML. At this moment this package works for that particular .csv file.As a bonus there is a visualization tool: you can see the average count of old church slavonic equivalents and look into part of speech distribution.Made as a part of an international project \"Epifanii Slavinetskii\u2019s Greek\u2013Slavonic\u2013Latin Lexicon in the East Slavic and European Language Space of the 16th\u2013early 18th Century\"."} +{"package": "xmlExtkwd", "pacakge-description": "No description available on PyPI."} +{"package": "xml_extractor", "pacakge-description": "# Example PackageThis is a simple example package. You can use\n[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)\nto write your content."} +{"package": "xml.Ext.Top20kwd", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmlfetch", "pacakge-description": "Xmlfetch - Pythonic & Simple XML GeneratorSee LICENSE for licensing notes.This piece of software comes handy when the necessity of generating XML code from\nscratch occurs,for example,being you in writing configuration options list for\napplications you use,or others you are coding on your own.Depending on the time and fortune,and the amount of volunteering for this\nproject,updated versions may\nbe available in the future."} +{"package": "xml-flatten", "pacakge-description": "DescriptionThis package accepts a nested xml as input parameter and provides a flatten structure as output. The output data is a list, which has xpath of all the data points from the xml.Installationpip install xml-flattenUsage examplexml file : nested_xml_sample.xml<?xml version=\"1.0\"?>\n<?xml-stylesheet href=\"catalog.xsl\" type=\"text/xsl\"?>\n<!DOCTYPE catalog SYSTEM \"catalog.dtd\">\n<catalog>\n <product description=\"Cardigan Sweater\" product_image=\"cardigan.jpg\">\n <catalog_item gender=\"Men's\">\n <item_number>QWZ5671</item_number>\n <price>39.95</price>\n <size description=\"Medium\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n </size>\n <size description=\"Large\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n </size>\n\t\t <Manufacturer description=\"raw\">\n\t\t\t<name>M1</name>\n\t\t\t<address>\n\t\t\t\t<line1>jsdf</line1>\n\t\t\t\t<line2>sdfgdhh</line2>\n\t\t\t\t\t<child6>dfgdfg</child6>\n\t\t\t\t\t\t<child7>fdghfyuk</child7>\n\t\t\t\t\t\t\t<child8>\n\t\t\t\t\t\t\t\t<child9>fdghfyuk</child9>\n\t\t\t\t\t\t\t\t<child91>fdghfyuk</child91>\n\t\t\t\t\t\t\t</child8>\n\t\t\t\t<pin>23423</pin>\n\t\t\t</address>\n\t\t </Manufacturer>\n </catalog_item>\n <catalog_item gender=\"Women's\">\n <item_number>RRX9856</item_number>\n <price>42.50</price>\n <size description=\"Small\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"navy_cardigan.jpg\">Navy</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n </size>\n <size description=\"Medium\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"navy_cardigan.jpg\">Navy</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n <size description=\"Large\">\n <color_swatch image=\"navy_cardigan.jpg\">Navy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n <size description=\"Extra Large\">\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n </catalog_item>\n </product>\n <product description=\"Formal Shirt\" product_image=\"FormalShirt.jpg\">\n <catalog_item gender=\"Men's\">\n <item_number>QWZ5671</item_number>\n <price>49.95</price>\n <size description=\"Large\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n </size>\n <size description=\"XLarge\">\n <color_swatch image=\"red_cardigan.jpg\">Blue</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Black</color_swatch>\n </size>\n </catalog_item>\n <catalog_item gender=\"Women's\">\n <item_number>RRX9856</item_number>\n <price>40.50</price>\n <size description=\"Medium\">\n <color_swatch image=\"red_cardigan.jpg\">Red</color_swatch>\n <color_swatch image=\"navy_cardigan.jpg\">Navy</color_swatch>\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n <size description=\"Large\">\n <color_swatch image=\"navy_cardigan.jpg\">Navy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n <size description=\"Extra Large\">\n <color_swatch image=\"burgundy_cardigan.jpg\">Burgundy</color_swatch>\n <color_swatch image=\"black_cardigan.jpg\">Black</color_swatch>\n </size>\n </catalog_item>\n </product>\n</catalog>flatten_xml.pyfrom xml.etree import ElementTree\nfrom xml_flatten import xml_flatten\n\ntree = ElementTree.parse(\"./nested_xml_sample.xml\")\nroot = tree.getroot()\n\nfor i in root:\n res=xml_flatten.rec(i,1,\"root\")\n for i in xml_flatten.xml_flat:\n print(i)output['root', {'product': ' '}, {'description': 'Cardigan Sweater', 'product_image': 'cardigan.jpg'}]\n['root>product', {'catalog_item': ' '}, {'gender': \"Men's\"}]\n['root>product>catalog_item', {'item_number': 'QWZ5671'}, '']\n['root>product>catalog_item', {'price': '39.95'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Medium'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'Manufacturer': ''}, {'description': 'raw'}]\n['root>product>catalog_item>Manufacturer', {'name': 'M1'}, '']\n['root>product>catalog_item>Manufacturer', {'address': ''}, '']\n['root>product>catalog_item>Manufacturer>address', {'line1': 'jsdf'}, '']\n['root>product>catalog_item>Manufacturer>address', {'line2': 'sdfgdhh'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child6': 'dfgdfg'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child7': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child8': ''}, '']\n['root>product>catalog_item>Manufacturer>address>child8', {'child9': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address>child8', {'child91': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address', {'pin': '23423'}, '']\n['root>product', {'catalog_item': ' '}, {'gender': \"Women's\"}]\n['root>product>catalog_item', {'item_number': 'RRX9856'}, '']\n['root>product>catalog_item', {'price': '42.50'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Small'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Medium'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Extra Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root', {'product': ' '}, {'description': 'Cardigan Sweater', 'product_image': 'cardigan.jpg'}]\n['root>product', {'catalog_item': ' '}, {'gender': \"Men's\"}]\n['root>product>catalog_item', {'item_number': 'QWZ5671'}, '']\n['root>product>catalog_item', {'price': '39.95'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Medium'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'Manufacturer': ''}, {'description': 'raw'}]\n['root>product>catalog_item>Manufacturer', {'name': 'M1'}, '']\n['root>product>catalog_item>Manufacturer', {'address': ''}, '']\n['root>product>catalog_item>Manufacturer>address', {'line1': 'jsdf'}, '']\n['root>product>catalog_item>Manufacturer>address', {'line2': 'sdfgdhh'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child6': 'dfgdfg'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child7': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address', {'child8': ''}, '']\n['root>product>catalog_item>Manufacturer>address>child8', {'child9': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address>child8', {'child91': 'fdghfyuk'}, '']\n['root>product>catalog_item>Manufacturer>address', {'pin': '23423'}, '']\n['root>product', {'catalog_item': ' '}, {'gender': \"Women's\"}]\n['root>product>catalog_item', {'item_number': 'RRX9856'}, '']\n['root>product>catalog_item', {'price': '42.50'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Small'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Medium'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Extra Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root', {'product': ' '}, {'description': 'Formal Shirt', 'product_image': 'FormalShirt.jpg'}]\n['root>product', {'catalog_item': ' '}, {'gender': \"Men's\"}]\n['root>product>catalog_item', {'item_number': 'QWZ5671'}, '']\n['root>product>catalog_item', {'price': '49.95'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'XLarge'}]\n['root>product>catalog_item>size', {'color_swatch': 'Blue'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product', {'catalog_item': ' '}, {'gender': \"Women's\"}]\n['root>product>catalog_item', {'item_number': 'RRX9856'}, '']\n['root>product>catalog_item', {'price': '40.50'}, '']\n['root>product>catalog_item', {'size': ' '}, {'description': 'Medium'}]\n['root>product>catalog_item>size', {'color_swatch': 'Red'}, {'image': 'red_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Navy'}, {'image': 'navy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]\n['root>product>catalog_item', {'size': ' '}, {'description': 'Extra Large'}]\n['root>product>catalog_item>size', {'color_swatch': 'Burgundy'}, {'image': 'burgundy_cardigan.jpg'}]\n['root>product>catalog_item>size', {'color_swatch': 'Black'}, {'image': 'black_cardigan.jpg'}]"} +{"package": "xmlformatter", "pacakge-description": "xmlformatterxmlformatteris an Open Source Python package, which provides formatting of XML documents.It is the replacement for the Python 2 package XmlFormatter, which has been removed from PyPi completely (see Notes). xmlformatter differs from others formatters byhandling whitespaces by a distinct set of formatting rules- formatting element content by a object style and mixed content by a text style. You may find xmlformatter useful for corrections and presentations. In addition xmlformatter comes with a wrapper script named xmlformat.Formatting Rulesxmlformatter treats the element content from the following example as a object. The elements are associated with containers, like complex, or properties names, like real and imaginary. Text nodes are associated with property values, like 4.4E+12. Leading and trailing whitespaces are meaningless in this scenario like sequences of whitespaces. Leading and trailing whitespaces will be remove, sequences of whitespaces will be collapsed.<complex>\n <real> 4.4E+12</real>\n <imaginary>5.4E-11\n </imaginary>\n</complex>The element content from the example above can be formatted by xmlformat:$ xmlformat ele.xmlThe following output shows the formatted XML document. xmlformatter has removed leading and trailing whitespaces from the text nodes and has indented the child elements equal. This formatting style is called object style.<complex>\n <real>4.4E+12</real>\n <imaginary>5.4E-11</imaginary>\n</complex>xmlformatter treats the mixed content from the following example as a literal text with some markup. The outer element enclose poem encloses the text. The inline element em gives a text snippet a special meaning. Leading and trailing whitespaces enclosed by inline elements are misplaced. They will be adopted by the previous or following text node. Note: xmlformatter may insert a text node if necessary. Even sequences of whitespaces will be collapsed:<poem> Es<em> war</em> einmal und <em>ist </em>nicht mehr...</poem>The following output shows the formatted XML document. xmlfromatter has removed leading and trailing whitespaces and has collapsed sequences of whitespaces. This formatting style is called text style.<poem>Es <em>war</em> einmal und <em>ist</em> nicht mehr...</poem>Both styles are used while formatting a XML document. The formatting rules are:A: Surrounding whitespaces are removed from element content.B: Leading whitespaces are removed from element content.C: Trailing whitespaces are removed from element content.D: Leading whitespaces of inline elements are put to preceding text (or inserted) if necessary within mixed content.E: Trailing whitespaces of inline elements are put to following text (or inserted) if necessary within mixed content.F: Sequences of whitespaces (n>2) are replaced by a single blank \u201c \u201c within element and mixed content.G: Linebreak and whitespace are used to indent elements within elements content.The following example shows the described whitespaces by their labels within a XML document:<root>AAAA\nAAAA<number>BBBB4.4E+12CCC</number>AAAA\nAAAA<poem>BBBBEs<em>DDDDwar</em> einmal und <em>istEEEE</em>nicht mehrF\nFFFFein <strong>riesengro\u00dfer</strong><em>DDDDTeddyb\u00e4r</em>,F\nder a\u00dfFFFFdie <em>MilchEEEE</em>und trank das BrotFFFF\nund als er starb da <strong>war erEEEE</strong><em>tot</em>.CCCC</poem>AAAA\n</root>The following output shows the formatted XML document:<root>\n <number>4.4E+12</number>\n <poem>Es <em>war</em> einmal und <em>ist</em> nicht mehr ein <strong>riesengro\u00dfer</strong> <em>Teddyb\u00e4r</em>, der a\u00df die <em>Milch</em>und trank das Brot und als er starb da <strong>war er</strong> <em>tot</em>.</poem>\n</root>Classclass xmlformatter.Formatter(compress ::= False, selfclose ::= False, indent ::= 2, indent_char ::= \" \", inline ::= True, encoding_input ::= None, encoding_output ::= None, preserve ::= [ ], blanks ::= False)The Formatter class can be used to format XML documents in scripts. By default all parts of the XML document will formatted. All descendants of elements listed by preserve are left unformatted. Setting the boolean property compress to True suppresses the indenting given by the indent and indent_char properties. Without a value given to encoding_input xmlformatter trys to determine the encoding from the XML document. On failure it use UTF-8 as default. encoding_output advises xmlformatter to encode the output explicit by the given value. Otherwise xmlformatter use the inpurt encoding. Setting the boolean property inline to False suppresses inline formatting. By default element content will be formatted everywhere - also within mixed content. The following example shows the usage of the xmlfromatter class:import xmlformatter\n\nformatter = xmlformatter.Formatter(indent=\"1\", indent_char=\"\\t\", encoding_output=\"ISO-8859-1\", preserve=[\"literal\"])\nformatter.format_file(\"/home/pa/doc.xml\")The example formats the XML document in /home/pa/doc.xml, preserving the element literal, indenting by the tab character and output in ISO-8859-1 encoding.Memberscompress ::= FalseMinify the XML document.selfclose ::= FalseCollapse<element></element>to<element/>.correct ::= TrueApply formatting rules to whitespaces.indent ::= 2Indent a child element in element content n-times by indent_char.indent_char ::= \" \"Indent a child element by this string.input_encoding ::= NoneAssume the XML document encoded by a not None value.output_encoding ::= NoneEncode the formatted XML document by a not None value.preserve ::= [ ]Skip formatting for all elements listed in preserve and all their descendants.blanks ::= FalseKeep blank lines. Multiple lines are collapsed into one.eof_newline ::= FalseAdd a single newline character at the end of each fileMethodsformat_file(path)Format a XML document given by a path.format_string(xmldoc)Format a XML document given by a string.Cmdxmlformat [--preserve \"pre,literal\"] [--blanks] [--compress] [--selfclose] [--indent num] [--indent-char char]\n [--overwrite] [--outfile file] [--encoding enc] [--outencoding enc] [--disable-inlineformatting]\n [--dispable-correction] [--help] < --infile file | file | - >xmlformat can read from STDIN, like:$ cat /home/pa/doc.xml | xmlformat -Use \u2013overwrite for inplace edits, seehttps://pre-commit.com/NotesRemove XmlFormatter before installing xmlformatter:$ pip uninstall XmlFormatterAfter reinstallation replace the string \u201cformatter.formatter\u201d by \u201cformatter\u201d, \u201cpreserving\u201d by \u201cpreserve\u201d and \u201cindentChar\u201d by \u201cindent_char\u201d inside your scripts carefully. To reach compatibility with XmlFormatter call xmlformat with \u2013disable-inlineformatting or use inline=False in your scripts."} +{"package": "xml-from-seq", "pacakge-description": "xml_from_seqGenerate XML from a Python data structure.ExamplesTheXML()function renders a Python list or tuple to an XML element. The first item is the\nelement name, the second item\u00a0\u2013 if it's a dict \u2013\u00a0is the attributes, and the rest of the items\nare either text or nested elements.fromxml_from_seqimportXMLitem=['item',{'attr1':123,'attr2':'other value'},'This is the content of the item.']assertXML(item)=='<item attr1=\"123\" attr2=\"other value\">This is the content of the item.</item>'item=['item','This is some content of the item.'['sub','This is the content of a subelement.']]print(XML(item))<item>Thisissomecontentoftheitem.<sub>Thisisthecontentofasubelement.</sub></item>If an element is False or None it will be omitted. If a element's name isNoneits contents will\nappear in its place. If an attribute's value isNoneit will be omitted.If an element's name is a list or tuple, it will be inserted into the XML as-is \u2013\u00a0so you can\ninclude already-rendered XML by double-bracketing it:print(XML([['<foo>123</foo>']]))<foo>123</foo>If an element's tag name isxml_from_seq.CDATA, that element's content will be rendered unescaped\nin a<![CDATA[...]]>section.Indentation and line breaksIf the first item in an element (not counting an attribute dict) isxml_from_seq.INLINE, that\nelement's contents won't be indented on separate lines from the element's start and end tags.fromxml_from_seqimportINLINE,XMLitem=['item','This is some content of the item.'['sub',INLINE,'This is the content of a subelement.']]print(XML(item))<item>Thisissomecontentoftheitem.<sub>Thisisthecontentofasubelement.</sub></item>You can pass an integerindentparameter to theXML()function to indent the output XML by\nthat many tabs."} +{"package": "xmlfuse", "pacakge-description": "xmlfuseGiven two XML documents having the same text, fuses the markup together to create the output XML document.Installationpip install xmlfuseBuilding and testing:If you prefer to build from sources, follow these steps:make venv\nmakeAPIimportlxml.etreeasetfromxmlfuse.fuseimportfusexml1=et.fromstring('<span>Hello, <i>world!</i></span>')xml2=et.fromstring('<span><b>Hello</b>, world!</span>')xml=fuze(xml1,xml2)assertet.tostring(xml)==b'<span><b>Hello</b>, <i>world!</i></span>'Input documents must have exactly the same textError is raised if text differs. Whitespace does matter!Example:xml1=et.fromstring('<span>Hello</span>')xml2=et.fromstring('<span>Good bye</span>')xml=fuze(xml1,xml2)# expect RuntimeError raisedConflicting markupConflicting markup. Sometimes it is not possible to merge two markups, because tags intersect. In such a case one has a choice:a. Raise an exception and let caller handle the problem\nb. Resolve by segmenting one of the markupsWe treat first document asmaster, and second asslave. Master markup is never segmented. If there is a\nconflict between master and slave markups (and ifauto_segmentflag isTrue),fuse()will segment slave to make markup consistent.Example:xml1=et.fromstring('<span>Hel<i>lo, world!</i></span>')xml2=et.fromstring('<span><b>Hello</b>, world!</span>')xml=fuze(xml1,xml2)assertet.tostring(xml)==b'<span><b>Hel<i>lo</i></b></i>, <i>world!</i></span>'Setauto_segmentflag toFalseto prevent segmentation. Error will be raised instead, if conflict detected.AmbiguitiesWhen master ans slave markups wrap the same text, there is a nesting ambuguity - which tag should be inner?We resolve this by consistently trying to putslavemarkup inside themaster. This behavior can be changed\nby setting the flagprefer_slave_innerto false.Example:xml1=et.fromstring('<span><i>Hello</i>, world!</span>')xml2=et.fromstring('<span><b>Hello</b>, world!</span>')xml=fuze(xml1,xml2,prefer_slave_inner=True)assertet.tostring(xml)==b'<span><b><i>Hello</i></b>, world!</span>'xml=fuze(xml1,xml2,prefer_slave_inner=False)assertet.tostring(xml)==b'<span><i><b>Hello</b></i>, world!</span>'Slave top-level tag is droppedNote that top-level tag from slave is not merged. It is just dropped. If you want it to be merged into the output,\nsetstrip_slave_top_tag=False.fuse() signaturefuse(xml1,xml2,*,prefer_slave_inner=True,auto_segment=True,strip_slave_top_tag=True)Where:xml1is the master XML document (LXML Element object, seehttp://lxml.de)xml2is the slave XML documentprefer_slave_innercontrols ambigiuty resolutionauto_segmentallows slave smarkup segmentation in case of conflicting markupstrip_slave_top_tagallowsfuseto ignore top-level tag from the slave XMLReturns fused XML document"} +{"package": "xml-generator-seobaeksol", "pacakge-description": "XML GeneratorComprehensive XML generator for PythonTable of ContentsInstallationUsageContributingLicenseInstallationpipinstallxml-generator-seobaeksolUsageImportfromxml_generator.typesimportXmlNodeComprehensive parsingParse Comprehensive format into an XmlNode object.node=XmlNode.parse({\"name\":\"node\",\"attributes\":{\"attr1\":\"value1\",\"attr2\":\"value2\"},\"body\":[{\"name\":\"child1\",\"attributes\":{\"attr1\":\"value1\"}},{\"name\":\"child2\",\"attributes\":{\"attr2\":\"value2\"}},],})Create a XmlNode with a querynode=XmlNode.from_query('node@attr1=\"value1\"@attr2=\"value2\"')Create a XmlNode with a extended queryextend_query={\"root\":[\"NoValueNode\",{\"SHORT-NAME\":\"node\",},{\"ELEMENTS@type=string\":[\"element@hint=id\",\"element@unit=m\",{\"element@unit=m@min=0@max=100@init=50\":\"100\"},],},]}Searching a specific nodeReturn the first XmlNode with the given query. Query can be a name with attributes.parent=node.find(\"node\")child1=node.find(\"child1@attr1\")child2=node.find(\"child2\")SerializationUsing theto_xml()function that return the XmlNode as an XML string.withopen('sample.xml','w',encoding='utf-8')asf:f.write(node.to_xml())Using theto_extend_query()function that return the extended query object as an XML string.extended_query_obj=root.to_extended_query()DeserializationUseXmlParserclass for reading a xml file that returnXmlNodebyclose()method.\nIt is sub-class ofxml.etree.ElementTree.XMLParserbuilt-in python class.fromxml_generator.typesimportXmlParserparser=XmlParser()withopen(file=\"xml_generator/tests/samples/complex.xml\",mode=\"r\",encoding=\"utf-8\")asf:original_xml=f.read()parser.feed(original_xml)root=parser.close()xml_string=root.to_xml(declaration=True,declaration_tag='<?xml version=\"1.0\" encoding=\"UTF-8\"?>\\n')ContributingComing soon.Testingpython-munittestdiscover-sxml_generator/tests-p\"test*.py\"Buildingpython.\\setup.pysdistbdist_wheelDeploymenttwineuploaddist/*LicenseLicense :: OSI Approved :: MIT License"} +{"package": "xmlhelpy", "pacakge-description": "xmlhelpyxmlhelpyis a wrapper library based onClick. Its main goal is to easily provide\nthexmlhelpinterface to any Python CLI tool. This interface can be used to\nobtain a machine readable XML representation of tools and their parameters. The\nXML representation can be used, for example, to generate GUIs on top of any\ntool that provides it.Installationxmlhelpy can be installed usingpip, note that Python version>=3.8is\nrequired to install the latest version:pipinstallxmlhelpyWhen installing xmlhelpy from source for development, it is recommended to\ninstall it in editable mode and to install all additional development\ndependencies as defined inpyproject.toml:pipinstall-e.[dev]Performing the development installation inside a virtual environment is\nrecommended, seeVirtualenvfor more information.UsageQuickstartIn essence, xmlhelpy works very similarly to Click, as the following example\ntaken from the Click documentation shows:importclickimportxmlhelpy@xmlhelpy.command()@xmlhelpy.argument(\"count\",description=\"Number of greetings.\",param_type=xmlhelpy.Integer,)@xmlhelpy.option(\"name\",description=\"Your name.\",default=\"me\",)defhello(count,name):\"\"\"Simple program that greets NAME for a total of COUNT times.A slightly modified example taken from Click.\"\"\"forxinrange(count):click.echo(f\"Hello{name}!\")if__name__==\"__main__\":hello()And when running it, assuming the code above was saved ashello.py:$pythonhello.py2Hellome!\nHellome!The main functionality xmlhelpy provides on top of the usual Click\nfunctionality is the--xmlhelpoption:$pythonhello.py--xmlhelp<?xml version='1.0' encoding='UTF-8'?><programname=\"hello\"description=\"Simple program that greets NAME for a total of COUNT times.\"><paramdescription=\"Number of greetings.\"type=\"long\"name=\"arg0\"positional=\"true\"required=\"true\"/><paramdescription=\"Your name.\"type=\"string\"name=\"name\"default=\"me\"/></program>With this option, a machine readable representation of thehellocommand and\nits parameters can be obtained without writing any additional code.The rest of this documentation focuses on the specific functionality that\nxmlhelpy provides. Please refer to theClickdocumentation for more general\nusage.Builtin optionsBesides the usual--helpoption that Click provides, xmlhelpy provides the\nfollowing:--xmlhelp: Prints a machine readable representation of a command or\nenvironment and their parameters.--version: Prints the version of a group, command or environment, if\nspecified.--commands: Prints a list of all subcommands a group contains.Commandsxmlhelpy provides three different command types:groups, regularcommandsandenvironments.Similar to Click, groups can be used to easily group related commands into\nmultiple subcommands. Environments, on the other hand, are commands that are\nmeant to wrap other commands, e.g. ansshtool to execute another command on\na remote machine. Environments are almost identical to regular commands, with\nthe exception that they also contain the required--env-execoption, which\nspecifies one or more command strings to be executed inside the environment.The following code shows an example of each command type:@xmlhelpy.group(name=None,version=None,cls=xmlhelpy.Group,)defmy_group():\"\"\"My group.\"\"\"@my_group.command(name=None,version=None,description=None,example=None,cls=xmlhelpy.Command,)defmy_command():\"\"\"My command.\"\"\"@my_group.environment(name=None,version=None,description=None,example=None,cls=xmlhelpy.Environment,)defmy_environment(env_exec):\"\"\"My environment.\"\"\"All command types provide the following parameters:name: The name of the command, which defaults to the name of the function\nwith underscores replaced by dashes.version: The version of the command. Subcommands can override the version\nof their parent groups, otherwise it is inherited.cls: A custom command class to customize the command behaviour.Commands and environments additionally provide the following parameters:description: The description of the command to be shown in the xmlhelp.\nDefaults to the first line of the docstring of the function.example: An example parametrization of using the command.ParametersSimilar to Click, xmlhelpy providesargumentandoptionparameters.\nArguments are required, positional parameters, while options are always given\nby their name.The following code shows an example of each parameter type:@xmlhelpy.command()@xmlhelpy.argument(\"arg\",description=\"\",nargs=1,param_type=xmlhelpy.String,required=True,default=None,exclude_from_xml=False,)@xmlhelpy.option(\"opt\",description=\"\",nargs=1,param_type=xmlhelpy.String,required=False,default=None,exclude_from_xml=False,char=None,var_name=None,is_flag=False,requires=None,excludes=None,)defmy_command(**kwargs):passBoth parameter types provide the following parameters:name: The name of the parameter, which will also be used for the variable\nname, with dashes replaced by underscores. The names of options have to be\ngiven as--<name> <value>.description: The description of the parameter.nargs: The number of arguments (separated by spaces) to expect. If larger\nthan1, the variable in the decorated function will be a tuple. For\narguments,-1can be specified for a single argument to allow for an\nunlimited number of values.param_type: The type of the parameter, either as class or instance.required: Whether the parameter is required or not. Defaults toTruefor\narguments.default: The default value to take if the parameter is not given.exclude_from_xml: Flag indicating whether the parameter should be excluded\nfrom the xmlhelp output.Options additionally provide the following parameters:char: A shorthand for an option consisting of a single ASCII letter, which\nhas to be given as-<char> <value>.var_name: A custom variable name to use in the decorated function instead\nof the parameter name.is_flag: Whether the option is a flag. Flags do not require a value. They\nalways use boolean types andFalseas default value. Additionally, their\ntype is specified asflagin the xmlhelp.requires: A list of option names which should be required when using this\noption.excludes: A list of option names which should be excluded when using this\noption.Parameter typesxmlhelpy wraps most of the parameter types that also exist in Click. All types\ncan be specified for both arguments and options. Types can either be given as\nclasses or as instances.The following code shows an example of the different parameter types:@xmlhelpy.command()@xmlhelpy.argument(\"string\",param_type=xmlhelpy.String)@xmlhelpy.argument(\"tokenlist\",param_type=xmlhelpy.TokenList(separator=\",\"))@xmlhelpy.argument(\"bool\",param_type=xmlhelpy.Bool)@xmlhelpy.argument(\"long\",param_type=xmlhelpy.Integer)@xmlhelpy.argument(\"long_range\",param_type=xmlhelpy.IntRange(min=None,max=None))@xmlhelpy.argument(\"real\",param_type=xmlhelpy.Float)@xmlhelpy.argument(\"real_range\",param_type=xmlhelpy.FloatRange(min=None,max=None))@xmlhelpy.argument(\"choice\",param_type=xmlhelpy.Choice([\"a\",\"b\"],case_sensitive=False))@xmlhelpy.argument(\"path\",param_type=xmlhelpy.Path(path_type=None,exists=False))defmy_command(**kwargs):passThe provided types can be used for the following cases:String: For simple string values.TokenList: For string values that should be converted to a list according\nto a given separator.Bool: For simple boolean values.Integer: For simple integer values.IntRange: For integer values in a certain range.Float: For simple float values.FloatRange: For float values in a certain range.Choice: For string values that can be selected from a specific list, either\ncase sensitive or insensitive.Path: For path values that can optionally be checked for whether they\nactually exist. The given path type can optionally be set to eitherfileordirectory, which sets the type in the xmlhelp accordingly and is also\nrelevant for the check mentioned above."} +{"package": "xmlib-to-git", "pacakge-description": "XML Rollbasase To GITApp that changes an XML Rollbase application into a git repository.Featuresxml conversiongit history relative to the creation date of the XML filegit pushbranch creation for each customer when-cparameter is setRequiresseerequirement.txtInstallationpip install xmlib-to-gitUsage$xmlib-to-git\\-f<xml-file>\\-o<local-repo>\\[-g<remote-repo]\\[-c<customer-id]\\[-v]"} +{"package": "xmlightning", "pacakge-description": "xmlightningxmlightning is a simple,Flask-like way of creating XML parsersInstallationTo install xmlightning through pippip install xmlightningGetting StartedFor a basic hello world, take the following two fileshello_world.xml<root>\n <foo>Hello World</foo>\n </root>hello_world.pyfrom xmlightning import Lightning\n\n\n parser = Lightning()\n\n @parser.route(\"./foo\")\n def hello_world(element):\n print(\"hello_world\")\n\n parser.parse(\"test.xml\")BreakdownAfter the Lightning class gets imported in your project, to use it you must instantiate it.After the Lightning class was instantiated, the example uses the decorator, \"route\".Route DecoratorThe route decorator takes in one argument, path, which is a string.\nPath refers to any valid XPATH string.Note that the route decorator requires the function it is used on to take in one argument: element.The type of element can be imported through the followingThrough xmlfrom xml.etree.ElementTree import ElementOr through xmlightningfrom xmlightning import ElementNext, the hello_world.xml file is parsed.\nWhenever the parser encounters a path that matches a route, the function of that route is executed.Finally, the string from the function is printed to the screenhello_world"} +{"package": "xmlist", "pacakge-description": "xmlistxmlistis a module for generating XML, which it represents by lists and tuples.using xmlistxml = xmlist.serialize(['html',\n ('xmlns', 'http://www.w3.org/1999/xhtml'),\n ['head', ['title', 'Hello, world!']],\n ['body',\n ['h1', 'Hello, world!'],\n ['p', 'xmlist is a module for generating XML']]])hacking on xmlist[assuming the setup_requires and test_requires are already installed withpip --user]virtualenv --python=python2.7 --system-site-packages env27 ;\nenv27/bin/pip2 install --editable .testing xmlistenv27/bin/python -B setup.py -q test"} +{"package": "xmlJoiner", "pacakge-description": "xmlJoinerJoin two or more PARC Telemetry files downloaded from ESA EDDS.InstallationTo install the reader you can use the command:$python3-mpipinstallxmlJoinerUsageTo join all the XML filesmyxml_01.xmlrandmyxml_02.xmlin a single file calledmyxml.xmlyou can use the command:$xmlJoinmyxml01.xmlmyxml_02.xml-omyxml.xmlYou can join also directly all the files in a folder:$xmlJoin-fmyfolder-omyfolder.xmlN.B.:be careful the file are sorted alphabetically. if they are numered the file #10 is befre the file #2. Please check the order using the command$xmlJoin-fmyfolder--show-listand change the file names if it is necessary.You can use it also as library:fromxmlJoinerimportxmlJoinxmlJoin(fileList,\"joined.xml\",verbose=True)"} +{"package": "xmljson", "pacakge-description": "This library is not actively maintained. Alternatives arexmltodictanduntangle.\nUse only if you need to parse using specific XML to JSONconventions.xmljson converts XML into Python dictionary structures (trees, like in JSON) and vice-versa.AboutXML can be converted to a data structure (such as JSON) and back. For example:<employees>\n <person>\n <name value=\"Alice\"/>\n </person>\n <person>\n <name value=\"Bob\"/>\n </person>\n</employees>can be converted into this data structure (which also a valid JSON object):{\n \"employees\": [{\n \"person\": {\n \"name\": {\n \"@value\": \"Alice\"\n }\n }\n }, {\n \"person\": {\n \"name\": {\n \"@value\": \"Bob\"\n }\n }\n }]\n}This uses theBadgerFishconvention that prefixes attributes with@.\nThe conventions supported by this library are:Abdera: Use\"attributes\"for attributes,\"children\"for nodesBadgerFish: Use\"$\"for text content,@to prefix attributesCobra: Use\"attributes\"for sorted attributes (even when empty),\"children\"for nodes, values are stringsGData: Use\"$t\"for text content, attributes added as-isParker: Use tail nodes for text content, ignore attributesYahooUse\"content\"for text content, attributes added as-isConvert data to XMLTo convert from a data structure to XML using the BadgerFish convention:>>> from xmljson import badgerfish as bf\n>>> bf.etree({'p': {'@id': 'main', '$': 'Hello', 'b': 'bold'}})This returns anarrayofetree.Elementstructures. In this case, the\nresult is identical to:>>> from xml.etree.ElementTree import fromstring\n>>> [fromstring('<p id=\"main\">Hello<b>bold</b></p>')]The result can be inserted into any existing rootetree.Element:>>> from xml.etree.ElementTree import Element, tostring\n>>> result = bf.etree({'p': {'@id': 'main'}}, root=Element('root'))\n>>> tostring(result)\n'<root><p id=\"main\"/></root>'This includeslxml.htmlas well:>>> from lxml.html import Element, tostring\n>>> result = bf.etree({'p': {'@id': 'main'}}, root=Element('html'))\n>>> tostring(result, doctype='<!DOCTYPE html>')\n'<!DOCTYPE html>\\n<html><p id=\"main\"></p></html>'For ease of use, strings are treated as node text. For example, both the\nfollowing are the same:>>> bf.etree({'p': {'$': 'paragraph text'}})\n>>> bf.etree({'p': 'paragraph text'})By default, non-string values are converted to strings using Python\u2019sstr,\nexcept for booleans \u2013 which are converted intotrueandfalse(lower\ncase). Override this behaviour usingxml_fromstring:>>> tostring(bf.etree({'x': 1.23, 'y': True}, root=Element('root')))\n'<root><y>true</y><x>1.23</x></root>'\n>>> from xmljson import BadgerFish # import the class\n>>> bf_str = BadgerFish(xml_tostring=str) # convert using str()\n>>> tostring(bf_str.etree({'x': 1.23, 'y': True}, root=Element('root')))\n'<root><y>True</y><x>1.23</x></root>'If the data contains invalid XML keys, these can be dropped viainvalid_tags='drop'in the constructor:>>> bf_drop = BadgerFish(invalid_tags='drop')\n>>> data = bf_drop.etree({'$': '1', 'x': '1'}, root=Element('root')) # Drops invalid <$> tag\n>>> tostring(data)\n'<root>1<x>1</x></root>'Convert XML to dataTo convert from XML to a data structure using the BadgerFish convention:>>> bf.data(fromstring('<p id=\"main\">Hello<b>bold</b></p>'))\n{\"p\": {\"$\": \"Hello\", \"@id\": \"main\", \"b\": {\"$\": \"bold\"}}}To convert this to JSON, use:>>> from json import dumps\n>>> dumps(bf.data(fromstring('<p id=\"main\">Hello<b>bold</b></p>')))\n'{\"p\": {\"b\": {\"$\": \"bold\"}, \"@id\": \"main\", \"$\": \"Hello\"}}'To preserve the order of attributes and children, specify thedict_typeasOrderedDict(or any other dictionary-like type) in the constructor:>>> from collections import OrderedDict\n>>> from xmljson import BadgerFish # import the class\n>>> bf = BadgerFish(dict_type=OrderedDict) # pick dict classBy default, values are parsed into boolean, int or float where possible (except\nin the Yahoo method). Override this behaviour usingxml_fromstring:>>> dumps(bf.data(fromstring('<x>1</x>')))\n'{\"x\": {\"$\": 1}}'\n>>> bf_str = BadgerFish(xml_fromstring=False) # Keep XML values as strings\n>>> dumps(bf_str.data(fromstring('<x>1</x>')))\n'{\"x\": {\"$\": \"1\"}}'\n>>> bf_str = BadgerFish(xml_fromstring=repr) # Custom string parser\n'{\"x\": {\"$\": \"\\'1\\'\"}}'xml_fromstringcan be any custom function that takes a string and returns a\nvalue. In the example below, only the integer1is converted to an integer.\nEverything else is retained as a float:>>> def convert_only_int(val):\n... return int(val) if val.isdigit() else val\n>>> bf_int = BadgerFish(xml_fromstring=convert_only_int)\n>>> dumps(bf_int.data(fromstring('<p><x>1</x><y>2.5</y><z>NaN</z></p>')))\n'{\"p\": {\"x\": {\"$\": 1}, \"y\": {\"$\": \"2.5\"}, \"z\": {\"$\": \"NaN\"}}}'ConventionsTo use a different conversion method, replaceBadgerFishwith one of the\nother classes. Currently, these are supported:>>> from xmljson import abdera # == xmljson.Abdera()\n>>> from xmljson import badgerfish # == xmljson.BadgerFish()\n>>> from xmljson import cobra # == xmljson.Cobra()\n>>> from xmljson import gdata # == xmljson.GData()\n>>> from xmljson import parker # == xmljson.Parker()\n>>> from xmljson import yahoo # == xmljson.Yahoo()OptionsConventions may support additional options.TheParkerconvention absorbs the root element by default.parker.data(preserve_root=True)preserves the root instance:>>> from xmljson import parker, Parker\n>>> from xml.etree.ElementTree import fromstring\n>>> from json import dumps\n>>> dumps(parker.data(fromstring('<x><a>1</a><b>2</b></x>')))\n'{\"a\": 1, \"b\": 2}'\n>>> dumps(parker.data(fromstring('<x><a>1</a><b>2</b></x>'), preserve_root=True))\n'{\"x\": {\"a\": 1, \"b\": 2}}'InstallationThis is a pure-Python package built for Python 2.7+ and Python 3.0+. To set up:pip install xmljsonSimple CLI utilityAfter installation, you can benefit from using this package as simple CLI utility. By now only XML to JSON conversion supported. Example:$ python -m xmljson -h\nusage: xmljson [-h] [-o OUT_FILE]\n [-d {abdera,badgerfish,cobra,gdata,parker,xmldata,yahoo}]\n [in_file]\n\npositional arguments:\nin_file defaults to stdin\n\noptional arguments:\n-h, --help show this help message and exit\n-o OUT_FILE, --out_file OUT_FILE\n defaults to stdout\n-d {abdera,badgerfish,...}, --dialect {...}\n defaults to parker\n\n$ python -m xmljson -d parker tests/mydata.xml\n{\n \"foo\": \"spam\",\n \"bar\": 42\n}This is a typical UNIX filter program: it reads file (orstdin), processes it in some way (convert XML to JSON in this case), then prints it tostdout(or file). Example with pipe:$ some-xml-producer | python -m xmljson | some-json-processorThere is alsopip\u2019sconsole_scriptentry-point, you can call this utility asxml2json:$ xml2json -d abdera mydata.xmlRoadmapTest cases for UnicodeSupport for namespaces and namespace prefixesSupport XML commentsHistory0.2.1 (25 Apr 2020)Bugfix: Don\u2019t strip whitespace in xml text values (@imoore76)Bugfix: Yahoo convention should convert<x>0</x>into{x: 0}. Empty elements become''not{}Suggest alternate libraries in documentation0.2.0 (21 Nov 2018)xmljsoncommand line script converts from XML to JSON (@tribals)invalid_tags='drop'in the constructor drops invalid XML tags in.etree()(@Zurga)Bugfix: Parker converts{'x': null}to<x></x>instead of<x>None</x>(@jorndoe #29)0.1.9 (1 Aug 2017)Bugfix and test cases for multiple nested children inAbderaconventionThanks to @mukultaneja0.1.8 (9 May 2017)AddAbderaandCobraconventionsAddParker.data(preserve_root=True)option to preserve root element in\nParker convention.Thanks to @dagwieers0.1.6 (18 Feb 2016)Addxml_fromstring=andxml_tostring=parameters to constructor to\ncustomise string conversion from and to XML.0.1.5 (23 Sep 2015)Add theYahooXML to JSON conversion method.0.1.4 (20 Sep 2015)FixGData.etree()conversion of attributes. (They were ignored. They\nshould be added as-is.)0.1.3 (20 Sep 2015)Simplify{'p':{'$':'text'}}to{'p': 'text'}in BadgerFish and GData\nconventions.Add test cases for.etree()\u2013 mainly from theMDN JXON article.dict_type/list_typedo not need to inherit fromdict/list0.1.2 (18 Sep 2015)Always use thedict_typeclass to create dictionaries (which defaults toOrderedDictto preserve order of keys)Update documentation, test casesRemove support for Python 2.6 (since we needcollections.Counter)Make theTravis CI buildpass0.1.1 (18 Sep 2015)Converttrue,falseand numeric values from strings to Python typesxmljson.parker.data()is compliant with Parker convention (bugs resolved)0.1.0 (15 Sep 2015)Two-way conversions via BadgerFish, GData and Parker conventions.First release on PyPI."} +{"package": "xmljson-adv", "pacakge-description": "This library is not actively maintained. Alternatives arexmltodictanduntangle.\nUse only if you need to parse using specific XML to JSONconventions.xmljson converts XML into Python dictionary structures (trees, like in JSON) and vice-versa.AboutXML can be converted to a data structure (such as JSON) and back. For example:<employees>\n <person>\n <name value=\"Alice\"/>\n </person>\n <person>\n <name value=\"Bob\"/>\n </person>\n</employees>can be converted into this data structure (which also a valid JSON object):{\n \"employees\": [{\n \"person\": {\n \"name\": {\n \"@value\": \"Alice\"\n }\n }\n }, {\n \"person\": {\n \"name\": {\n \"@value\": \"Bob\"\n }\n }\n }]\n}This uses theBadgerFishconvention that prefixes attributes with@.\nThe conventions supported by this library are:Abdera: Use\"attributes\"for attributes,\"children\"for nodesBadgerFish: Use\"$\"for text content,@to prefix attributesCobra: Use\"attributes\"for sorted attributes (even when empty),\"children\"for nodes, values are stringsGData: Use\"$t\"for text content, attributes added as-isParker: Use tail nodes for text content, ignore attributesYahooUse\"content\"for text content, attributes added as-isConvert data to XMLTo convert from a data structure to XML using the BadgerFish convention:>>> from xmljson import badgerfish as bf\n>>> bf.etree({'p': {'@id': 'main', '$': 'Hello', 'b': 'bold'}})This returns anarrayofetree.Elementstructures. In this case, the\nresult is identical to:>>> from xml.etree.ElementTree import fromstring\n>>> [fromstring('<p id=\"main\">Hello<b>bold</b></p>')]The result can be inserted into any existing rootetree.Element:>>> from xml.etree.ElementTree import Element, tostring\n>>> result = bf.etree({'p': {'@id': 'main'}}, root=Element('root'))\n>>> tostring(result)\n'<root><p id=\"main\"/></root>'This includeslxml.htmlas well:>>> from lxml.html import Element, tostring\n>>> result = bf.etree({'p': {'@id': 'main'}}, root=Element('html'))\n>>> tostring(result, doctype='<!DOCTYPE html>')\n'<!DOCTYPE html>\\n<html><p id=\"main\"></p></html>'For ease of use, strings are treated as node text. For example, both the\nfollowing are the same:>>> bf.etree({'p': {'$': 'paragraph text'}})\n>>> bf.etree({'p': 'paragraph text'})By default, non-string values are converted to strings using Python\u2019sstr,\nexcept for booleans \u2013 which are converted intotrueandfalse(lower\ncase). Override this behaviour usingxml_fromstring:>>> tostring(bf.etree({'x': 1.23, 'y': True}, root=Element('root')))\n'<root><y>true</y><x>1.23</x></root>'\n>>> from xmljson import BadgerFish # import the class\n>>> bf_str = BadgerFish(xml_tostring=str) # convert using str()\n>>> tostring(bf_str.etree({'x': 1.23, 'y': True}, root=Element('root')))\n'<root><y>True</y><x>1.23</x></root>'If the data contains invalid XML keys, these can be dropped viainvalid_tags='drop'in the constructor:>>> bf_drop = BadgerFish(invalid_tags='drop')\n>>> data = bf_drop.etree({'$': '1', 'x': '1'}, root=Element('root')) # Drops invalid <$> tag\n>>> tostring(data)\n'<root>1<x>1</x></root>'Convert XML to dataTo convert from XML to a data structure using the BadgerFish convention:>>> bf.data(fromstring('<p id=\"main\">Hello<b>bold</b></p>'))\n{\"p\": {\"$\": \"Hello\", \"@id\": \"main\", \"b\": {\"$\": \"bold\"}}}To convert this to JSON, use:>>> from json import dumps\n>>> dumps(bf.data(fromstring('<p id=\"main\">Hello<b>bold</b></p>')))\n'{\"p\": {\"b\": {\"$\": \"bold\"}, \"@id\": \"main\", \"$\": \"Hello\"}}'To preserve the order of attributes and children, specify thedict_typeasOrderedDict(or any other dictionary-like type) in the constructor:>>> from collections import OrderedDict\n>>> from xmljson import BadgerFish # import the class\n>>> bf = BadgerFish(dict_type=OrderedDict) # pick dict classBy default, values are parsed into boolean, int or float where possible (except\nin the Yahoo method). Override this behaviour usingxml_fromstring:>>> dumps(bf.data(fromstring('<x>1</x>')))\n'{\"x\": {\"$\": 1}}'\n>>> bf_str = BadgerFish(xml_fromstring=False) # Keep XML values as strings\n>>> dumps(bf_str.data(fromstring('<x>1</x>')))\n'{\"x\": {\"$\": \"1\"}}'\n>>> bf_str = BadgerFish(xml_fromstring=repr) # Custom string parser\n'{\"x\": {\"$\": \"\\'1\\'\"}}'xml_fromstringcan be any custom function that takes a string and returns a\nvalue. In the example below, only the integer1is converted to an integer.\nEverything else is retained as a float:>>> def convert_only_int(val):\n... return int(val) if val.isdigit() else val\n>>> bf_int = BadgerFish(xml_fromstring=convert_only_int)\n>>> dumps(bf_int.data(fromstring('<p><x>1</x><y>2.5</y><z>NaN</z></p>')))\n'{\"p\": {\"x\": {\"$\": 1}, \"y\": {\"$\": \"2.5\"}, \"z\": {\"$\": \"NaN\"}}}'ConventionsTo use a different conversion method, replaceBadgerFishwith one of the\nother classes. Currently, these are supported:>>> from xmljson import abdera # == xmljson.Abdera()\n>>> from xmljson import badgerfish # == xmljson.BadgerFish()\n>>> from xmljson import cobra # == xmljson.Cobra()\n>>> from xmljson import gdata # == xmljson.GData()\n>>> from xmljson import parker # == xmljson.Parker()\n>>> from xmljson import yahoo # == xmljson.Yahoo()OptionsConventions may support additional options.TheParkerconvention absorbs the root element by default.parker.data(preserve_root=True)preserves the root instance:>>> from xmljson import parker, Parker\n>>> from xml.etree.ElementTree import fromstring\n>>> from json import dumps\n>>> dumps(parker.data(fromstring('<x><a>1</a><b>2</b></x>')))\n'{\"a\": 1, \"b\": 2}'\n>>> dumps(parker.data(fromstring('<x><a>1</a><b>2</b></x>'), preserve_root=True))\n'{\"x\": {\"a\": 1, \"b\": 2}}'InstallationThis is a pure-Python package built for Python 2.7+ and Python 3.0+. To set up:pip install xmljsonSimple CLI utilityAfter installation, you can benefit from using this package as simple CLI utility. By now only XML to JSON conversion supported. Example:$ python -m xmljson -h\nusage: xmljson [-h] [-o OUT_FILE]\n [-d {abdera,badgerfish,cobra,gdata,parker,xmldata,yahoo}]\n [in_file]\n\npositional arguments:\nin_file defaults to stdin\n\noptional arguments:\n-h, --help show this help message and exit\n-o OUT_FILE, --out_file OUT_FILE\n defaults to stdout\n-d {abdera,badgerfish,...}, --dialect {...}\n defaults to parker\n\n$ python -m xmljson -d parker tests/mydata.xml\n{\n \"foo\": \"spam\",\n \"bar\": 42\n}This is a typical UNIX filter program: it reads file (orstdin), processes it in some way (convert XML to JSON in this case), then prints it tostdout(or file). Example with pipe:$ some-xml-producer | python -m xmljson | some-json-processorThere is alsopip\u2019sconsole_scriptentry-point, you can call this utility asxml2json:$ xml2json -d abdera mydata.xmlRoadmapTest cases for UnicodeSupport for namespaces and namespace prefixesSupport XML commentsHistory0.2.0 (21 Nov 2018)xmljsoncommand line script converts from XML to JSON (@tribals)invalid_tags='drop'in the constructor drops invalid XML tags in.etree()(@Zurga)Bugfix: Parker converts{\u2018x\u2019: null}to<x></x>instead of<x>None</x>(@jorndoe #29)0.1.9 (1 Aug 2017)Bugfix and test cases for multiple nested children inAbderaconventionThanks to @mukultaneja0.1.8 (9 May 2017)AddAbderaandCobraconventionsAddParker.data(preserve_root=True)option to preserve root element in\nParker convention.Thanks to @dagwieers0.1.6 (18 Feb 2016)Addxml_fromstring=andxml_tostring=parameters to constructor to\ncustomise string conversion from and to XML.0.1.5 (23 Sep 2015)Add theYahooXML to JSON conversion method.0.1.4 (20 Sep 2015)FixGData.etree()conversion of attributes. (They were ignored. They\nshould be added as-is.)0.1.3 (20 Sep 2015)Simplify{'p':{'$':'text'}}to{'p': 'text'}in BadgerFish and GData\nconventions.Add test cases for.etree()\u2013 mainly from theMDN JXON article.dict_type/list_typedo not need to inherit fromdict/list0.1.2 (18 Sep 2015)Always use thedict_typeclass to create dictionaries (which defaults toOrderedDictto preserve order of keys)Update documentation, test casesRemove support for Python 2.6 (since we needcollections.Counter)Make theTravis CI buildpass0.1.1 (18 Sep 2015)Converttrue,falseand numeric values from strings to Python typesxmljson.parker.data()is compliant with Parker convention (bugs resolved)0.1.0 (15 Sep 2015)Two-way conversions via BadgerFish, GData and Parker conventions.First release on PyPI."} +{"package": "xml-json-serializer2", "pacakge-description": "No description available on PyPI."} +{"package": "xml-json-yaml-convert", "pacakge-description": "BRANCHSTATUSmaindevelopxml_json_yaml_convertBase level XML, JSON, YAML conversion toolWritten By: Benjamin P. TrachtenbergContact Information:e_ben_75-python@yahoo.comIf you have any questions e-mail meLinkedIn:Ben TrachtenbergDocker Hub:Docker HubPyPi Page forxml_json_yaml_convertRequirementsrequirementsrequirements-devInstallationFrom source \"setup.py install\"From pip \"pip install xml-json-yaml-convert\"LanguagesPythonAboutThis is a library for a simple conversion between XML, YAML, and JSON"} +{"package": "xmlmanip", "pacakge-description": "from xmlmanip import XMLSchema, SearchableListstring = \"\"\"\n<breakfast_menu>\n<food tag=\"waffles\">\n <name>Belgian Waffles</name>\n <price>$5.95</price>\n <description>\n Two of our famous Belgian Waffles with plenty of real maple syrup\n </description>\n <calories>650</calories>\n</food>\n<food tag=\"waffles\">\n <name >Strawberry Belgian Waffles</name>\n <price>$7.95</price>\n <description>\n Light Belgian waffles covered with strawberries and whipped cream\n </description>\n <calories>900</calories>\n</food>\n<food tag=\"waffles\">\n <name>Berry-Berry Belgian Waffles</name>\n <price>$8.95</price>\n <description>\n Belgian waffles covered with assorted fresh berries and whipped cream\n </description>\n <calories>900</calories>\n</food>\n<food tag=\"toast\">\n <name>French Toast</name>\n <price>$4.50</price>\n <description>\n Thick slices made from our homemade sourdough bread\n </description>\n <calories>600</calories>\n</food>\n<food tag=\"classic\">\n <name>Homestyle Breakfast</name>\n <price>$6.95</price>\n <description>\n Two eggs, bacon or sausage, toast, and our ever-popular hash browns\n </description>\n <calories>950</calories>\n</food>\n</breakfast_menu>\n\"\"\"You can import your XML string to convert it to a dict. (dict conversion\nhandled byhttps://github.com/martinblech/xmltodict).schema = XMLSchema(string)\nschemaXMLSchema([('breakfast_menu',\n OrderedDict([('food',\n [OrderedDict([('@tag', 'waffles'),\n ('name', 'Belgian Waffles'),\n ('price', '$5.95'),\n ('description',\n 'Two of our famous Belgian Waffles with plenty of real maple syrup'),\n ('calories', '650')]),\n OrderedDict([('@tag', 'waffles'),\n ('name', 'Strawberry Belgian Waffles'),\n ('price', '$7.95'),\n ('description',\n 'Light Belgian waffles covered with strawberries and whipped cream'),\n ('calories', '900')]),\n OrderedDict([('@tag', 'waffles'),\n ('name',\n 'Berry-Berry Belgian Waffles'),\n ('price', '$8.95'),\n ('description',\n 'Belgian waffles covered with assorted fresh berries and whipped cream'),\n ('calories', '900')]),\n OrderedDict([('@tag', 'toast'),\n ('name', 'French Toast'),\n ('price', '$4.50'),\n ('description',\n 'Thick slices made from our homemade sourdough bread'),\n ('calories', '600')]),\n OrderedDict([('@tag', 'classic'),\n ('name', 'Homestyle Breakfast'),\n ('price', '$6.95'),\n ('description',\n 'Two eggs, bacon or sausage, toast, and our ever-popular hash browns'),\n ('calories', '950')])])]))])Use .search() to search for data of interest.schema.search(name=\"Homestyle Breakfast\")[SchemaInnerDict([('@tag', 'classic'),\n ('name', 'Homestyle Breakfast'),\n ('price', '$6.95'),\n ('description',\n 'Two eggs, bacon or sausage, toast, and our ever-popular hash browns'),\n ('calories', '950')])]TheSearchAbleListclass will also allow you to easily search\nthrough lists of dicts.example_list = [{\"thing\": 1, \"other_thing\": 2}, {\"thing\": 2, \"other_thing\": 2}]\nsearchable_list = SearchableList(example_list)\nprint(searchable_list.search(thing__ne=2)) # thing != 2\nprint(searchable_list.search(other_thing=2))[{'thing': 1, 'other_thing': 2}]\n[{'thing': 1, 'other_thing': 2}, {'thing': 2, 'other_thing': 2}]Use .locate() if you are interested in the \u201cpath\u201d to your data of\ninterest and .retrieve() to get an object from its \u201cpath.\u201dschema.locate(name=\"Homestyle Breakfast\")['__breakfast_menu__food__4__name']schema.retrieve('__breakfast_menu__food__4__name')'Homestyle Breakfast'schema.retrieve('__breakfast_menu__food__4')SchemaInnerDict([('@tag', 'classic'),\n ('name', 'Homestyle Breakfast'),\n ('price', '$6.95'),\n ('description',\n 'Two eggs, bacon or sausage, toast, and our ever-popular hash browns'),\n ('calories', '950')])You have access to all of the standard comparison methods.paths = schema.locate(name__contains=\"Waffles\")\npaths['__breakfast_menu__food__0__name',\n '__breakfast_menu__food__1__name',\n '__breakfast_menu__food__2__name']schema.search(name__contains=\"Waffles\")[SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Belgian Waffles'),\n ('price', '$5.95'),\n ('description',\n 'Two of our famous Belgian Waffles with plenty of real maple syrup'),\n ('calories', '650')]),\n SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Berry-Berry Belgian Waffles'),\n ('price', '$8.95'),\n ('description',\n 'Belgian waffles covered with assorted fresh berries and whipped cream'),\n ('calories', '900')]),\n SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Strawberry Belgian Waffles'),\n ('price', '$7.95'),\n ('description',\n 'Light Belgian waffles covered with strawberries and whipped cream'),\n ('calories', '900')])]schema.search(calories__lt=\"700\")[SchemaInnerDict([('@tag', 'toast'),\n ('name', 'French Toast'),\n ('price', '$4.50'),\n ('description',\n 'Thick slices made from our homemade sourdough bread'),\n ('calories', '600')]),\n SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Belgian Waffles'),\n ('price', '$5.95'),\n ('description',\n 'Two of our famous Belgian Waffles with plenty of real maple syrup'),\n ('calories', '650')])]Warning, all types are compared as strings, which may have undesirable results.schema.search(calories__lt=\"700\") == schema.search(calories__lt=\"70\")TrueSome attributes cannot be accessed via keyword arguements,\nunfortunately.schema.search(@tag__ne=\"waffles\")File \"<ipython-input-13-da95e3095c41>\", line 1\n schema.search(@tag__ne=\"waffles\")\n ^\nSyntaxError: invalid syntaxYou will need to pass the desired attribute and comparison method as\nstrings in this case.schema.search('@tag', 'waffles') # default comparison is __eq__[SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Belgian Waffles'),\n ('price', '$5.95'),\n ('description',\n 'Two of our famous Belgian Waffles with plenty of real maple syrup'),\n ('calories', '650')]),\n SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Strawberry Belgian Waffles'),\n ('price', '$7.95'),\n ('description',\n 'Light Belgian waffles covered with strawberries and whipped cream'),\n ('calories', '900')]),\n SchemaInnerDict([('@tag', 'waffles'),\n ('name', 'Berry-Berry Belgian Waffles'),\n ('price', '$8.95'),\n ('description',\n 'Belgian waffles covered with assorted fresh berries and whipped cream'),\n ('calories', '900')])]schema.search('@tag', 'waffles', comparison='ne')[SchemaInnerDict([('@tag', 'classic'),\n ('name', 'Homestyle Breakfast'),\n ('price', '$6.95'),\n ('description',\n 'Two eggs, bacon or sausage, toast, and our ever-popular hash browns'),\n ('calories', '950')]),\n SchemaInnerDict([('@tag', 'toast'),\n ('name', 'French Toast'),\n ('price', '$4.50'),\n ('description',\n 'Thick slices made from our homemade sourdough bread'),\n ('calories', '600')])]"} +{"package": "xml_marshaller", "pacakge-description": "IntroductionThis module allows one to marshal simple Python data types into a\ncustom XML format. The Marshaller and Unmarshaller classes can be\nsubclassed in order to implement marshalling into a different XML DTD.\nOriginal Authors are XML-SIG (xml-sig@python.org).Fully compatible with PyXML implementation, enables namespace support\nfor XML Input/Output.Implemented with lxmlInstallationpython setup.py installTestingpython setup.py testUsageFor simple serialisation and unserialisation:>>> from xml_marshaller import xml_marshaller\n>>> xml_marshaller.dumps(['item1', {'key1': 1, 'key2': 'string'}])\n'<marshal><list id=\"i2\"><string>item1</string><dictionary id=\"i3\"><string>key1</string><int>1</int><string>key2</string><string>string</string></dictionary></list></marshal>'\n>>> xml_marshaller.loads(xml_marshaller.dumps(['item1', {'key1': 1, 'key2': 'string'}]))\n['item1', {'key2': 'string', 'key1': 1}]Can works with file like objects:>>> from xml_marshaller import xml_marshaller\n>>> from StringIO import StringIO\n>>> file_like_object = StringIO()\n>>> xml_marshaller.dump('Hello World !', file_like_object)\n>>> file_like_object.seek(0)\n>>> file_like_object.read()\n'<marshal><string>Hello World !</string></marshal>'\n>>> file_like_object.seek(0)\n>>> xml_marshaller.load(file_like_object)\n'Hello World !'xml_marshaller can also output xml with qualified names:>>> from xml_marshaller import xml_marshaller\n>>> xml_marshaller.dumps_ns('Hello World !')\n'<marshal:marshal xmlns:marshal=\"http://www.erp5.org/namespaces/marshaller\"><marshal:string>Hello World !</marshal:string></marshal:marshal>'You can also use your own URI:>>> from xml_marshaller.xml_marshaller import Marshaller\n>>> marshaller = Marshaller(namespace_uri='http://my-custom-namespace-uri/namespace')\n>>> marshaller.dumps('Hello World !')\n'<marshal:marshal xmlns:marshal=\"http://my-custom-namespace-uri/namespace\"><marshal:string>Hello World !</marshal:string></marshal:marshal>'History1.0.2 (2019-02-25)Python 2 fixups.1.0.1 (2018-11-12)Fix changelog.1.0 (2018-11-12)Stop distinguish unicode and bytes and always return \u2018str\u20190.10 (2018-09-12)Add support for Python 30.9.7 (2010-10-30)Enhance egg folder structure\n[nicolas Delaby]Improve tests\n[nicolas Delaby]add XSD Schema\n[nicolas Delaby]0.9.6 (2010-10-12)[fix] Support boolean transformation\n[Nicolas Delaby]0.9.5 (2010-09-01)[fix] Formatting of documentation\n[Lukasz Nowak]0.9.4 (2010-09-01)[fix] Instances are now correctly unmarshalled.\n[Cedric de Saint Martin]"} +{"package": "xmlmerge", "pacakge-description": "xmlmergeXMLMerge is simple tool to merge multiple xml files.How to InstallpipinstallxmlmergeUsage$xmlmergefile1.xmlfile2.xml>file3.xml$xmlmergetests/*.xml>combine.xmlHow end file looks like<products><productid=\"9999\"><a>1234</a><b>1234</b></product><productid=\"5678\"><a>1234</a><b>1234</b></product></products>ContactContact Kiran Kumar Kotarikirankotari@live.comwith any suggestions or comments. If you find any bugs please fix them and send me a pull request."} +{"package": "xml-miner", "pacakge-description": "XML/TRXML SelectorDescriptionThis package provides two scripts:mine-xmlandmine-trxml.mine-xmlselects tags from xml/mxml files, and save the\nselected values to file.mine-trxmlselects fields from trxml/mtrxml files, and save\nthe selected values to file.StatusRequirementsPython 3.6+Installationpip install xml-selectorUsageUse xml selector scriptThe xml selector supports:one or more tagnames:selector could be one tagnamenameor comma separated tagnameslangskill,compskill,softskillsmultiple sources:e.g. select from xml dir, xml files, mxml file, or directly from\nannotation serverexamples:#select from xml directory\nmine-xml --source tests/xmls/ --selector name --output_file name.tsv\nmine-xml --source tests/xmls/ --selector langskill,compskill,softskill --output_file skill.tsv --with_field_name\n\n#select from xml file or mxml file\nmine-xml --source tests/sample.mxml --selector experience --output_file experience.tsv\n\n#select directly from annotation server\nmine-xml --source localhost:50249 --selector name --output_file name.tsv --query \"set Data2018\"Use trxml selector scriptThe trxml selector supports:one or more selectors:selector can be one field:name.0.nameor comma separated fields:name.0.name,address.0.addresssingle or multi item:can select field from one item, e.g.experienceitem.3.experienceor select field value of all item, e.g.experienceitem.experience(orexperienceitem.*.experience)multiple sources:e.g. select from trxml dir, trxml files, or mtrxml fileexamples:# one selector, single item\nmine-trxml --source tests/trxmls/ --selector name.0.name --output_file name.tsv\n\n# one selector, multiple item\nmine-trxml --source tests/sample.mxml --selector experienceitem.experience --output_file experience.tsv\n\n# more selectors, single item\nmine-trxml --source tests/trxmls/ --selector name.0.name,address.0.address,phone.0.phone --output_file personal.tsv\n\n# more selectors, multiple item\nmine-trxml --source tests/sample.mxml --itemgroup experienceitem --fields experience,experiencedate --output_file experience.tsv\nmine-trxml --source tests/sample.mxml --selector experienceitem.*.experience,experienceitem.*.experiencedate --output_file experience.tsv\nmine-trxml --source tests/sample.mxml --selector experienceitem.experience,experienceitem.experiencedate --output_file experience.tsvDevelopmentTo install package and its dependencies, run the following from project\nroot directory:python setup.py installTo work the code and develop the package, run the following from project\nroot directory:python setup.py developTo run unit tests, execute the following from the project root\ndirectory:python setup.py testselector and output details:mine-xml:input: documents, selector(s), outputoutput:default (parameterwith_field_namenot set):filename, field_valuee.g. select all names with selectornamefilenamevaluexxxxChao Liparameterwith_field_nameset:filename, field_value, field_namee.g. select skills with selectorcompskill,langskill,otherskillfilenamevaluefieldxxxxjavacompskillxxxxdutchlangskillmine-trxmlinput:documents, selector(s), output,documents, itemgroup, fields, outputsingle selector:single item (name.0.name): filename fieldfilenamename.0.namexxxxChao Limulti items (skill.*.skill): filename item_index fieldfilenameitem_indexfieldxxxx0javaxxxx1dutchmultiple selectorssingle item: filename, field1, field2 \u2026each selector points to a field of a specific item with a digital\nindex, e.g.name.0.lastname,name.0.firstname,address.0.countryfilenamename.0.lastnamename.0.firstnameaddress.0.countryxxxxLiChaoChinaxxxxLeeRichardUSAmulti items: filename, item_index, field1, field2 \u2026each selector points to a field from all items in an itemgroup, e.g.skill.skill,skill.type,skill.datefilenameskillskilltypedatexxxx0javacompskill2001-2005xxxx1dutchlangskill2002-0.0.5 (2019-10-14)bug fix: ElementTree xpath find will return a None if value is an empty string, restore to empty string0.0.4 (2019-09-11)bug fix: reading always use utf8, and not continue reading if failed on encoding of one document0.0.3 (2019-08-11)expand miner.py module to generate matched phrases per doc0.0.2 (2019-08-09)added support for CI0.0.1 (2019-08-09)make two script: mine-xml and mine-trxml0.0.0 (2019-08-06)Add the first version of the mine_xml and mine_trxml"} +{"package": "xmlmodel", "pacakge-description": "XMLModel allows you to expressively define an XML document, using native python classes, you can then access the elements of the XML through a tree of native python objects."} +{"package": "xml_models", "pacakge-description": "Django REST Model was written in a Test Driven Development style. For example usages\nplease refer to xml_models_test.pyFor XPath processing, the py-dom-xpath library is included, but this is a fairly slow\npure python library. While it works perfectly well, Django REST Model was written\noriginally to work with LXML, which is a much faster library, and provides better\nnamespace support. If Django REST Model appears slow, try switching to LXML and\nhopefully you\u2019ll experience significant speed improvements."} +{"package": "xml_models2", "pacakge-description": "[![Build Status](https://travis-ci.org/alephnullplex/xml_models2.svg?branch=master)](https://travis-ci.org/alephnullplex/xml_models2)[![Coverage Status](https://coveralls.io/repos/alephnullplex/xml_models2/badge.svg?branch=master)](https://coveralls.io/r/alephnullplex/xml_models2?branch=master)[Read The Docs](http://xml-models2.readthedocs.org/en/latest/)# XmlModels2XmlModels allows you to define Models similar in nature to Django models that are backed by XML endpoints rather than adatabase. Using a familiar declarative definition, the fields map to values in the XML document by means of XPathexpressions. With support for querying external REST APIs using a django-esque approach, we have strived to makewriting and using xml backed models as close to django database models as we can, within the limitations of theavailable API calls.# InstallationThe simplest approach is to to use `pip install xml_models2`# A simple exampleJust to get started, this is an example of taking an XML representation of an Address that might be returned from aGET request to an external REST api.<Address id=\"2\"><number>22</number><street>Acacia Avenue</street><city>Maiden</city><country>England</country><postcode>IM6 66B</postcode></Address>class Address(xml_models.Model):id=xml_models.IntField(xpath=\"/Address/@id\")number = xml_models.IntField(xpath=\"/Address/number\")street = xml_models.CharField(xpath=\"/Address/street\")city = xml_models.CharField(xpath=\"/Address/city\")country = xml_models.CharField(xpath=\"/Address/country\")postcode = xml_models.CharField(xpath=\"/Address/postcode\")finders = {(id,): 'http://adresses/%s'}This example would be used as follows:->>> address = Address.objects.get(id=2)>>> print \"address is %s, %s\" % (address.number, address.street)\"22, Acacia Avenue\"# HeritageThis project is a fork of [Django REST Models](http://djangorestmodel.sourceforge.net/)"} +{"package": "xml-models-redux", "pacakge-description": "Django REST Model was written in a Test Driven Development style. For example usages\nplease refer to xml_models_test.pyFor XPath processing, the py-dom-xpath library is included, but this is a fairly slow\npure python library. While it works perfectly well, Django REST Model was written\noriginally to work with LXML, which is a much faster library, and provides better\nnamespace support. If Django REST Model appears slow, try switching to LXML and\nhopefully you\u2019ll experience significant speed improvements."} +{"package": "xmlmp", "pacakge-description": "xmlmp is a small Python package (and a couple of simple scripts using it), that\nfacilitates the authoring of unix man-pages (the ugly groff things), using XML.\nIt defines the xmlmp 1.0 DTD, and provides filters that convert documents\ncomplying with it to either unix man-pages, or HTML documents."} +{"package": "xmlobj", "pacakge-description": "Descriptionxmlobj is simple utility to map xml file to python objectxmlobj also allows you to add functionality to mapped object by adding mixin classA Simple Examplefrom pathlib import Path\n\nfrom PIL import Image, ImageDraw\n\nfrom xmlobj import get_xml_obj\n\n\nclass DrawBoxesMixin:\n def draw_box(self, image) -> Image.Image:\n p1 = (self.object.bndbox.xmin, self.object.bndbox.ymin)\n p2 = (self.object.bndbox.xmax, self.object.bndbox.ymax)\n img_draw = ImageDraw.Draw(image)\n img_draw.text(p1, self.object.name, align=\"left\")\n img_draw.rectangle([p1, p2])\n return image\n\n\nif __name__ == \"__main__\":\n pascal_annotation = Path(\"samples/000027.xml\")\n img_file = \"samples/000027.jpg\"\n img = Image.open(img_file)\n obj = get_xml_obj(pascal_annotation, mixin_clsasses=[DrawBoxesMixin])\n rendered_img = obj.draw_box(img.copy())\n rendered_img.show()Save xmlimport xml.etree.cElementTree as ET\n\nfrom xmlobj import get_xml_obj\n\nif __name__ == \"__main__\":\n obj = get_xml_obj(\"samples/books.xml\")\n root = obj.to_xml()\n tree = ET.ElementTree(root)\n ET.indent(tree, space=\"\\t\", level=0)\n tree.write(\"my_xml_books.xml\")LimitationsTag lowercaseOriginal:<CD>\n <TITLE>Empire Burlesque\n Bob Dylan\n USA\n Output:\n Empire Burlesque\n Bob Dylan\n USA\nAttribute propertiesOriginal:\n Gambardella, Matthew\n XML Developer's Guide\n Computer\n 44.95\n 2000-10-01\n An in-depth look at creating applications\n with XML.\n \n Output:\n bk101\n Gambardella, Matthew\n XML Developer's Guide\n Computer\n 44.95\n 2000-10-01\n An in-depth look at creating applications\n with XML.\nInstallationpip install xmlobj"} +{"package": "xmlobject", "pacakge-description": "xmlobject lets you access your XML document with beautiful and easy to read Python syntax so that you don\u2019t need to deal with lxml, minidom or sax."} +{"package": "xmlobjects", "pacakge-description": "UNKNOWN"} +{"package": "xml-objects", "pacakge-description": "Makes managing XML a lot easier by making an XML document look like nested Python objects.## InstallingInstall via `pip`:pip install xml-objects## UsageSee [sample.xml](sample.xml) for the structure used in these examples. Taken unashamedly from Microsoft's [Sample XML](https://msdn.microsoft.com/en-us/library/ms762271.aspx). The results of the code below can be seen by running [`xml_node.py`](xml_node.py) directly.```pythonxml = XMLNode.from_file('sample.xml')print(xml.book.price)for book in xml.book:print(f\"{book.title.value}, {book.author.value}, {book.price.value}\")```Which will output:```PS [34] master -> python .\\xml_node.py['44.95', '5.95', '5.95', '5.95', '5.95', '4.95', '4.95', '4.95', '6.95', '36.95', '36.95', '49.95']XML Developer's Guide, Gambardella, Matthew, 44.95Midnight Rain, Ralls, Kim, 5.95Maeve Ascendant, Corets, Eva, 5.95Oberon's Legacy, Corets, Eva, 5.95The Sundered Grail, Corets, Eva, 5.95Lover Birds, Randall, Cynthia, 4.95Splish Splash, Thurman, Paula, 4.95Creepy Crawlies, Knorr, Stefan, 4.95Paradox Lost, Kress, Peter, 6.95Microsoft .NET: The Programming Bible, O'Brien, Tim, 36.95MSXML3: A Comprehensive Guide, O'Brien, Tim, 36.95Visual Studio 7: A Comprehensive Guide, Galos, Mike, 49.95```## Future Ideas- Script to drop into a shell with the functionality of XMLNode. Optionally, with an argument to pre-load an XML file.- The `__str__` method should probably print out available child-nodes for ease of exploration.- Open from URL?## ContributingI'd love to have people contribute. Feel free to open a pull request and we'll talk about it!## Code of ConductSee the [Code of Conduct](CODE_OF_CONDUCT.md).Keywords: data xml interface update modify investigatePlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Intended Audience :: DevelopersClassifier: Topic :: Text Processing :: Markup :: XMLClassifier: License :: OSI Approved :: MIT LicenseClassifier: Programming Language :: Python :: 3Classifier: Programming Language :: Python :: 3.6Description-Content-Type: text/markdown"} +{"package": "xml_orm", "pacakge-description": "This library is inspired by Django object to relation layer. XML document schemas are represented by Python classes with fields corresponding to nested elements and attributes. Document namespaces and encodings are stored as class Meta information. Object instances are transparently loaded from XML documents, with validation on load and save operations. Object-oriented approach allows reusing of schema elements by inheritance and overriding of XML elements and attributes represented by Python class members. XML namespaces, serialization an de-serialization to different encodings and optional schema validation are supported, along with most common XSD types to Python objects mapping. XSD inspection utility is provided for conversion of existing XSD schemas to Python objects (very much work in progress, but usable for simple schemas). Documentation is work in progress, mostly in Russian. For reference see source of test.py which showcases all current features."} +{"package": "xml-overrider", "pacakge-description": "# xml_overrider\nSimple way to override XML values based on based on xpaths.Changelog0.1.2 - 2017-08-08Fix packaging0.1.1 - 2017-08-08Minor fixes0.1.0 - 2017-08-07Initial release (testing)"} +{"package": "xml-parser", "pacakge-description": "UNKNOWN"} +{"package": "xmlparsing", "pacakge-description": "XMLParsing is an easy-to-use Python 3 parser for compiling, transforming, encoding and decoding XML files and text.XMLParsing installation:Run this in your command prompt/shellpip install xmlparsingXMLParsing convert dictionary:xmlparsing.dict2xmlINPUT:importxmlparsingmyDict={\"numbers\":[1,2,3],\"letters\":[\"a\",\"b\",\"c\"],\"text\":\"Lorem ipsum dolor sit amet\"}print(xmlparsing.dict2xml(myDict,title=\"all\"))OUTPUT:123abcLoremipsumdolorsitametIn the above, you can see that the \"title\" attribute in xmlparsing.dict2xml is what defines the tag that your entire document will be inside.XMLParsing convert JSON file:xmlparsing.jsonfil2xmlINPUT:importxmlparsingprint(xmlparsing.jsonfile2xml('myStorage.json')The file \"myStorage.json\":{\"numbers\":[1,2,3],\"letters\":[\"a\",\"b\",\"c\"],\"text\":\"Lorem ipsum dolor sit amet\"}OUTPUT:123abcLoremipsumdolorsitametXMLParsing format XML:xmlparsing.formatxmlINPUT:importxmlparsingprint(xmlparsing.formatxml(' 1 2 3 a b c Lorem ipsum dolor sit amet '))OUTPUT:123abcLoremipsumdolorsitametThe code above cleans up XML.XMLParsing convert XML to dictionary:xmlparsing.xml2dictINPUT:importxmlparsingprint(xmlparsing.xml2dict('''123abcLorem ipsum dolor sit amet'''))OUTPUT:{'all':{'numbers':{'item':[{'@i':'0','#text':'1'},{'@i':'1','#text':'2'},{'@i':'2','#text':'3'}]},'letters':{'item':[{'@i':'0','#text':'a'},{'@i':'1','#text':'b'},{'@i':'2','#text':'c'}]},'text':'Lorem ipsum dolor sit amet'}}XMLParsing convert XML to JSON:xmlparsing.xml2jsonINPUT:importxmlparsingprint(xmlparsing.xml2json('''123abcLorem ipsum dolor sit amet'''))OUTPUT:{\"all\":{\"letters\":{\"item\":[{\"#text\":\"a\",\"@i\":\"0\"},{\"#text\":\"b\",\"@i\":\"1\"},{\"#text\":\"c\",\"@i\":\"2\"}]},\"numbers\":{\"item\":[{\"#text\":\"1\",\"@i\":\"0\"},{\"#text\":\"2\",\"@i\":\"1\"},{\"#text\":\"3\",\"@i\":\"2\"}]},\"text\":\"Lorem ipsum dolor sit amet\"}}THE END!Enjoy using XMLParsing!"} +{"package": "xmlpatcher", "pacakge-description": "XML PatcherA convenient library for patching XML files with XPath.Usage example:fromxmlpatcherimportXMLDocumentfromxmlpatcher.patchesimportSetValue,Removedocument=XMLDocument(\"./example.xml\")document.patch(SetValue(\"/Book/@color\",\"red\"),Remove(\"/Book/Page[1]\"))document.save()The above code will transform this file:WelcomeGoodbyeInto this:Goodbye"} +{"package": "xmlplain", "pacakge-description": "xmlplainXML as plain object utility moduleSynopsysThis module is a set of utility functions for parsing self-contained\nXML input into plain list/dict/string types and emitting to/reading\nfrom XML or YAML formats.The motivating usage was to dump XML to YAML, manually edit\nfiles as YAML, and emit XML output back.Though this module can be used more simply to dump compatible plain\nlist/dict/string objects into XML or YAML for textual storage.An XML file content when read to object and written back to XML has\nall it's document strcuture and content preserved w.r.t. to\nelements start/end and text content.\nThough XML comments, document type specifications, external\nentity definitions are discarded if present on input. External system\nentities (i.e. inclusion of external files) are not supported\nand generate an input error.The input XML is just syntactically validated and does not validate\nagainst any DTD or schema specification as the underlying backend\nis the core xml.sax module.The only and optional destructive transformation on the document\ncontent is astrip_spaceoption on reading (resp.prettyoption\non writing) which can affect non-leaf text content (stripping\nleading and trailing spaces).The XML namespaces are ignored as there is no actual schema validation,\nhence element, attribute names and namespaces URIs attributes\nare passed and preserved as-is.Note that there are alternative modules with nearly the same\nfunctionality, but none of them provide all of:simple plain objects (dict, list, strings) dumped to/reloaded from XMLpreservation of semi-structured XML documents (tags duplicates,\nmixed text and tags) on inputmanagement of human-editable form through YAML bridgeUsageIn order to convert a XML file to a YAML representation, for instance given\nthetests/example-1.xmlfile:Thisisanexampleforxmlobjdocumentation.documentexampleElt1Elt2Elt3Elt4Execute the following python code:importxmlplain# Read to plain objectwithopen(\"tests/example-1.xml\")asinf:root=xmlplain.xml_to_obj(inf,strip_space=True,fold_dict=True)# Output plain YAMLwithopen(\"example-1.yml\",\"w\")asoutf:xmlplain.obj_to_yaml(root,outf)This will output the YAML representation inexample-1.yml:example:doc:'Thisisanexampleforxmlobjdocumentation.'content:'@version':betakind:documentclass:examplestructured:''elements:-item:Elt 1-doc:Elt 2-item:Elt 3-doc:Elt 4One can then read the emitted YAML representation and generate\nagain an XML output with:importxmlplain# Read the YAML filewithopen(\"example-1.yml\")asinf:root=xmlplain.obj_from_yaml(inf)# Output back XMLwithopen(\"example-1.new.xml\",\"w\")asoutf:xmlplain.xml_from_obj(root,outf,pretty=True)This will output back the following XML (there may be some\nindentation and/or short empty elements differences w.r.t. the\noriginal):Thisisanexampleforxmlobjdocumentation.documentexampleElt1Elt2Elt3Elt4For a detailled usage, read the API documentation with:pydoc xmlplainOr get to the online documentation at:https://guillon.github.io/xmlplainInstallThe module is compatible withpython 2.6/2.7andpython 3.x.For a local installation (installs to$HOME/.local) do:pip install --user xmlplainThis will install the last release and its dependencies in your user environment.Optionally install at system level with:sudo pip install xlmplainSourcesDownload this module archives from the releases at:https://github.com/guillon/xmlplain/releasesOr clone the source git repository at:https://github.com/guillon/xmlplainInstallation from sourcesInstall first modules dependencies with:pip install --user setuptools PyYAML ordereddictEither copy thexmlplain.pyfile somewhere or install it\nwithsetup.py.For a user local installation (installs to$HOME/.local) do:./setup.py install --userDevelopmentThis module is delivered as part of a source tree with tests, in order\nto run tests, do for instance:make -j16 checkWith python coverage installed, one may check coverage of changes with:make -j16 coverage\nfirefox tests/coverage/html/index.htmlWhen check target pass and newly added code is covered,\nplease submit a pull request tohttps://github.com/guillon/xmlplainDocumentationThe documentation is generated withsphinxas is:make doc\nfirefox html/index.htmlThe online documentation is hosted at:https://guillon.github.io/xmlplainReleaseThe release process relies on the virtualenv tool, python2 and python3\nbeing installed on the release host.The release builds, tests, do coverage checks on both python2 and python3\nthen generates documentation and uploadable archives for PyPi.Before Bumping a release be sure to update the__version__string\ninxmlplain.pyand commit it (no check is done against the version\nin the release target).Then Proceed as follow to prepare the release:make -j16 releaseWhen all this passes locally, commit all and push to githubnext/masterbranch in order to have travis checks running.\nVerify travis status before proceeding further, for instance\nfrom the travis command line with:travis branchesOnce all is passed, and themake -j16 releasetarget has been re-executed,\nupload doc to github and packages to PyPI with:make release-uploadAt this point the package version should be available onhttps://pypi.org/project/xmlplainand the doc updated onhttps://guillon.github.io/xmlplainOne should check the proper installation on PyPi with:make -j16 release-checkWhich will restart a release check, this time downloading from PyPI instead of using\nthe local sources.After all is done, one should manually update the github with:Apply a tagvx.y.zmatching the new release version and push it to githubGo to github and finalize the tag promotion into a release with and at least upload\nalso on in the github release the source archivexmlplain-x.y.x.tar.gzavailable\non the just uploaded PyPi files:https://pypi.org/project/xmlplain/#filesOptionally add some information and publish the releaseLicenseThis is free and unencumbered software released into the public domain."} +{"package": "xmlplot", "pacakge-description": "### xmlplot"} +{"package": "xmlpolymerase", "pacakge-description": "Overviewxmlpolymerase is a simple powerful serializer and deserializer for\npython-structures into XML. Possible structures are string, int, float, bool,\nlist and dict.The primary function of a polymerase is the polymerization of new DNA or RNA\nagainst an existing DNA or RNA template in the processes of replication and\ntranscription.(Cite: Wikipeadiahttp://en.wikipedia.org/wiki/Polymerase)UsageThis is a pure python module. The API is pretty simple, for more read the\ndocstrings, an exampkle follows:>>> from odict import OrderedDict\n>>> teststructure = OrderedDict()\n>>> teststructure['one'] = 'Eins'\n>>> teststructure['two'] = 'Zwei'\n>>> teststructure['three'] = 'Drei'\n>>> teststructure['four'] = [True, 2, '3-2', 42.23]\n>>> domnode = serialize(structure, nodename='object')\n>>> print domnode.toprettyxml()\n\n \n Eins\n \n \n Zwei\n \n \n Drei\n \n \n \n True\n \n \n 2\n \n \n 3-2\n \n \n 42.23\n \n \n\n>>> structure = deserialze(domnode)\nOrderedDict([('one', 'Eins'), ('two', 'Zwei'), ('three', 'Drei'), ('four', [True, 2, '3-2', 23.42])])Thanksto Nicola Larosa and Michael Foord for the OrderedDict implementation, which is\nused and copied (unmodified) into this package inodict.pyhere. The code\nwas published under a BSD-License. For details please read the contents of the\nfile.LicenseAll code exceptodict.pyis under the GNU General Public License GPL 2.0 or\nlater.Copyright and AuthorsCopyright, BlueDynamics Alliance, Austriaauthor: Jens Klein Feedback, Bugreports, \u2026If you like to give the author feedback about this product just write a mail\nto .If you have access to theplone.orgcollectiveyou might want to commit\nbug-fixes direct to trunk or do enhancements on a branch. Anyway, the author\nwould be happy to get a short mail about those changes.\u2013 Jens Klein "} +{"package": "xml-preferences", "pacakge-description": "Module xml_preferencesxml_preferences uses a scheme to create a hierarchy of objects that\nrepresent the data stored in an XML files. CHanges to the objects can\nlater to saved back into an XML file.The inspiration for this module is to store preferences for applications.Classesclass xml_preferences.XmlPreferences__init__( scheme )Theschemeis an instance of xml_preferences.Scheme.load( filename )Reads the preferences from thefilenameand returns the resulting\ntree of xml_preferences.PreferencesNode objects.In case of an error xml_preferences.ParseError is raise.loadString( text )Reads the preferences from the stringtextand returns the resulting\ntree of xml_preferences.PreferencesNode objects.In case of an error xml_preferences.ParseError is raise.save( data_node )Write the xml_preferences.PreferencesNodedata_nodehierarchy\ninto the file used to load() the preferences.saveAs( data_node, filename )Write the xml_preferences.PreferencesNodedata_nodehierarchy\nintofileaname.saveToString( data_node )Write the xml_preferences.PreferencesNodedata_nodehierarchy\ninto a string and return the string.saveToFile( data_node, f )Write the xml_preferences.PreferencesNodedata_nodehierarchy\ninto the file objectf.class xml_preferences.Scheme__init__( document_root )Thedocument_rootis an instance of xml_preferences.SchemeNode\nand represent the top level XML document element.dumpScheme( f )Write a dump of the scheme into the file objectf.This is useful for debugging issues with scheme design.class xml_preferences.SchemeNode__init__( factory, element_name, all_attribute_info=None, element_plurality=False, key_attribute=None, collection_name=None, store_as=None, default=True, default_attributes=None )TheSchemeNoderepresents on XML element with the nameelement_name.Any attributes that element has are listed inall_attribute_info, which is a tuple/list of names or name,type pairs.\nFor example:all_attribute_info=(\u2018description\u2019, (\u2018count\u2019, int))TheSchemeNodecan represent an in three ways:The element will only appear once.The element haselement_pluralityset to True and can appear many times and will be stored as a list of elements in its parent.The element has akey_attributeand can appear many times and will be stored as a dictionary in its parent.Thecollection_namedefaults to the element_name. Thecollection_nameis passed to the parent\nsetChildNodeList or setChildNodeMap functions.store_asdefaults to theelement_nameand is used to name the python variable that this node is store in its in parent object.Whendefaultis True and there is not XML that matches this SchemeNode a default value will be stored in the parent object.When the node is defaulted the attributes of the node can be set from a dictionary pass asdefault_attributes.dumpScheme( f, indent=0 )Write a dump of the scheme into the file objectf.This is useful for debugging issues with scheme design.addSchemeChild( scheme_node )\n__lshift__( scheme_node )Addscheme_nodeas a child element of this SchemeNode.\nThe << operator is useful in making the scheme definition readable.class xml_preferences.PreferencesNodeFor typical use all the set and get functions provide all the necessary features.\nThat can be overriden to create special behaviour. It is assumed that all\nattribures are initised to a suitable value in __init__.__init__()Derive fromPreferencesNodeto initialise the variables used to hold the parsed XML preferences.finaliseNode( self )Called after all attributes and child nodes have been set on this node.Use this call to default any missing preferences.setAttr( self, name, value )Called to save the value of an attribute. The default implemention is:setattr( self, name, value )setChildNode( self, name, node )Called to save the value of singleton child element. The default implemention is:setattr( self, name, node )setChildNodeList( self, collection_name, node )Called to save the value of the next element to added to a list. The default implemention is:getattr( self, collection_name ).append( node )setChildNodeMap( self, collection_name, key, node )Called to save the value of the next element into a dict using thekey. The default implemention is:getattr( self, collection_name )[ key ] = nodegetAttr( self, name )Called to get the value of thenameattribute. The default implemention is:return getattr( self, name )getChildNode( self, name )Called to get the value of thenamechild node. The default implemention is:return getattr( self, name )getChildNodeList( self, collection_name )Called to get a list of values of thecollection_namechild nodes, which are assumed to be stored in a list. The default implemention is:return getattr( self, name )getChildNodeMap( self, collection_name )Called to get a list value of thecollection_namechild nodes, which are assumed to be stored in a dict. The default implemention is:return getattr( self, name ).values()dumpNode( self, f, indent=0 )Write a dump of the PreferencesNode hierarchy into file objectf.Setindentto the number of spaces to indent the dumped text.Useful when debugging.ExampleSee test_xml_preferences.py for example use."} +{"package": "xmlprops", "pacakge-description": "xmlprops provides mechanism for to access and manipulate XML based properties.OverviewXMLProps provides means to access properties that are stored in XML (file or string) - Java XML style.There are two main classes xmlprops provides:XMLPropsFile: file based XML that containing propertiesXMLPropsStr: string base XML that containing propertiesBoth classes inherit fromdictclass.\nBoth classes provide similar methods to allow stractured access to the properties.Both classes inherit same base class that provides access and manipulation\nmethods that used by XMLProps family.A property is represented by key value XML entries.Key: property path. string names separated by, usually, \u2018.\u2019 (dot). Key examples:\u2018factory_name\u2019\u2018arizona.capitol\u2019\u2018texas.dallas.mayor\u2019The property name is the last element in property path (similar to basename in path methods)\nThe property hierarchy is the path to it.\nValue: property value. string representing the value assignment to propertyThe get dict function \u2018[]\u2019 was enhanced to include hierarchical get.\nOn the item a.b.c; get will try to get c, a.c, and a.b.c.\nThe last one available, wins.Functionsget(key, key_sep=None)Similar toget()\u201cdict\u201d function \u2018[]\u2019 but in addition adds hierarchical relations.get()looks for thekeyin it loaded properties.Assuming key is property path, the following order of search will be done (key is \u2018a.b.c.\u2019):First lookup c,Then lookup \u2018a.c\u2019And lastly look for \u2018a.b.c.\u2019The last found match wins.set(key, value)Sets dictionarykeywithvalueget_keys(prefix, keys, key_sep=None)Return a dictionary forprefixand list ofkeysget_match(key_prefix=None, key_suffix=None, key_sep=None, value_sep = None, decrypt=False)ReturnsOrderedDictwith all keys matching the criteria.\nLook forkeyforkey_prefixandkey_suffixEach found key is loaded into a dictionary\nThekeyin the returned dictionary is stripped of its prefix.\nThe function returns newly created dictionary\nIf you want the prefix to end with \u2018.\u2019 delimiter; use \u2018prefix.\u2019 as key_prefix.\nIfvalue_sepis provided, it is used to separate the value of the element into a list.\nIfdecrypt, encrypted fields with ending with _encrypted will be decryptedget_re(key_re=None, value_sep = None, decrypt=False)The function looks for a keys that fits regular expression.key_reis string of a Pythonic regular expression\nIf value_sep provided, it is used to separate the value of the element into a list.\nReturnsdictobject.get_contain(key_value=None, ignore_case=False, exact_match=False, value_sep = None, decrypt=False)The function looks for a keys that that haskey_valuein them.Parameters:1.key_value: exact match ofkeyor Pythonic regular expression\n1.ignore_case: if set will ignore the case where finding a match\n2.exact: if set, will take only keys that equals key_value (with considerations to case)\n3. Ifvalue_sepis provided, it is used to separate the value of the element into a list.XMLPropsFile.writes(props_file=None)Writes loaded and possibly updated props into property filewrites()will either write a new property file of override existing one with it loaded properties.props_file: a path to property file. If none provided, the file loaded will be overwritten.\nReturns: None\nRaises: XMLPropsWriteFileErrorXMLPropsStr.writes()Writes loaded and possibly updated props into property stringwrites()will either write a new property file of override existing one with it loaded properties.props_file: a path to property file. If none provided, the file loaded will be overwritten.\nReturns: XML formatted string withentry,name and *valuepopulated from the objectExamples of usefromxmlpropsimportXMLPropsStrfromxmlpropsimportXMLPropsFile## Define example stringprops_xml_01='''\n\n\n MySql\n BF\n shared\n db1\n 10\n 1\n userdb\n passworddb\n hostdb\n hw_host\n portdb1\n databasedb1\n portdb2\n databasedb2\n 1\n 2\n\n'''##Load XML from stringxmlprops=XMLPropsStr(props=props_xml_01)print(xmlprops)## prints {'db1.charset': 'utf8', 'db1.use_unicode': 'True', 'init_active': '1', 'product': 'MySql', 'db1.host': 'hostdb', 'service_mode': 'BF', 'db1.port': 'portdb', 'exposure': 'shared', 'db1.password': 'passworddb', 'db1.database': 'databasedb', 'max_active': '10', 'db1.user': 'userdb', 'db1.priority': '2', 'makers': 'db1'}xmlprops.get_match(key_prefix='db2.')['port']## returns 'portdb2'xmlprops.get_match(key_prefix='db1.')['port']##returns 'portdb1'xmlprops.get_match(key_prefix='db1.port')['']##returns 'portdb1'xmlprops.get_match(key_prefix='db2.')## returns OrderedDict([('port', 'portdb2'), ('database', 'databasedb2')])##Next statement examplifies that last value for key \"priority\" was loadedxmlprops.get_match(key_prefix='db1.')['priority']## returns '2'## Next statements examplify priority in evaluating keys when using \"get\" functionxmlprops.get('db1.host')## returns 'hostdb' - since key 'db1.host' is evaluated after key 'host'xmlprops.get('db1.max_active')## returns '10' - key 'max_active' is evaluated first, then 'db1.max_active' is evaluated and is not foundxmlprops.get('db2.max_active')## returns '10' - key 'max_active' is evaluated first, then 'db2.max_active' is evaluated and is not foundxmlprops.set('new_key','new_key_value')## Add new key/valuexmlprops.get_contain('host')## returns {'host': 'hw_host', 'db1.host': 'hostdb'}xmlprops.get_contain(key_value='host',exact_match=True)## returns {'host': 'hw_host'}xmlprops.get_contain('db1.host')## retuns {'db1.host': 'hostdb'}xmlprops.get_contain('db.\\.port')## returns {'db2.port': 'portdb2', 'db1.port': 'portdb1'}Additional resourcesDocumentation is in the \u201cdocs\u201d directory and online at the design and use of xmlprops.exampleandtestsdirectory shows ways to use xmlprops . Both directories are available to view and download as part of source code\non GitHub.GitHub_linkDocs are updated rigorously. If you find any problems in the docs, or think they\nshould be clarified in any way, please take 30 seconds to fill out a ticket in\ngithub or send us email atsupport@acrisel.comTo get more help or to provide suggestions you can send as email to:arnon@acrisel.comuri@acrisel.com"} +{"package": "xmlproxy", "pacakge-description": "xmlproxyimportxml.etree.ElementTreeasetr=et.Element('root')s=et.SubElement(r,'tagname')s.text='123'# use xmlproxy:classRoot(et.Element):tagname=text_property('tagname')r=Root('root')r.abc='123'forgot tag name and enjoy type hit!"} +{"package": "x-mlps", "pacakge-description": "X-MLPsAn MLP model that provides a flexible foundation to implement, mix-and-match, and test various state-of-the-art MLP building blocks and architectures.\nBuilt on JAX and Haiku.Installationpipinstallx-mlpsNote: X-MLPs will not install JAX for you (seeherefor install instructions).Getting StartedTheXMLPclass provides the foundation from which all MLP architectures are built on, and is the primary class you use.\nAdditionally, X-MLPs relies heavily on factory functions to customize and instantiate the building blocks that make up a particularXMLPinstance.\nFortunately, this library provides several SOTA MLP blocks out-of-the-box as factory functions.\nFor example, to implement the ResMLP architecture, you can implement the follow model function:importhaikuashkimportjaxfromeinopsimportrearrangefromx_mlpsimportXMLP,Affine,resmlp_block_factorydefcreate_model(patch_size:int,dim:int,depth:int,num_classes:int=10):defmodel_fn(x:jnp.ndarray,is_training:bool)->jnp.ndarray:# Reformat input image into a sequence of patchesx=rearrange(x,\"(h p1) (w p2) c -> (h w) (p1 p2 c)\",p1=patch_size,p2=patch_size)returnXMLP(num_patches=x.shape[-2],dim=dim,depth=depth,block=resmlp_block_factory,# Normalization following the stack of ResMLP blocksnormalization=lambdanum_patches,dim,depth,**kwargs:Affine(dim,**kwargs),num_classes=num_classes,)(x,is_training=is_training)# NOTE: Operating directly on batched data is supported as well.returnhk.vmap(model_fn,in_axes=(0,None))model=create_model(patch_size=4,dim=384,depth=12)model_fn=hk.transform(model)rng=jax.random.PRNGKey(0)params=model_fn.init(rng,jnp.ones((1,32,32,3)),False)It's important to note theXMLPmoduledoes notreformat input data for you (e.g., to a sequence of patches).\nAs such, you must reformat data manually before feeding it to anXMLPmodule.\nTheeinopslibrary, which is installed by X-MLPs, provides functions that can help here (e.g.,rearrange).Note: Like the core Haiku modules, all modules implemented in X-MLPs support batched data and being vectorized viavmap.X-MLPs Architecture DetailsX-MLPs uses a layered approach to construct arbitrary MLP networks. There are three core modules used to create a network's structure:XSublayer- bottom level module which wraps arbitrary feedforward functionality.XBlock- mid level module consisting of one or moreXSublayermodules.XMLP- top level module which represents a generic MLP network, and is composed of a stack of repeatedXBlockmodules.To support user-defined modules, each of the above modules support passing arbitrary keyword arguments to child modules.\nThis is accomplished by prepending arguments with one or more predefined prefixes (including user defined prefixes).\nBuilt-in prefixes include:\"block_\" - arguments fed directly to theXBlockmodule.\"sublayers_\" - arguments fed to allXSublayers in eachXBlock.\"sublayers{i}_\" - arguments fed to the i-thXSublayerin eachXBlock(where 1 <= i <= # of sublayers).\"ff_\" - arguments fed to the feedforward module in aXSublayer.Prefixes must be combined in order when passing them to theXMLPmodule (e.g., \"block_sublayer1_ff_\").XSublayerTheXSublayermodule is a flexible sublayer wrapper module providing skip connections and pre/post-normalization to an arbitrary child module (specifically, arbitrary feedforward modules e.g.,XChannelFeedForward).\nChild module instances are not passed directly, rather a factory function which creates the child module is instead.\nThis ensures that individual sublayers can be configured automatically based on depth.XBlockTheXBlockmodule is a generic MLP block. It is composed of one or moreXSublayermodules, passed as factory functions.XMLPAt the top level is theXMLPmodule, which represents a generic MLP network.\nNXBlockmodules are stacked together to form a network, created via a common factory function.Built-in MLP ArchitecturesThe following architectures have been implemented in the form ofXBlocks and have corresponding factory functions.ResMLP -resmlp_block_factoryMLP-Mixer -mlpmixer_block_factorygMLP -gmlp_block_factoryS\u00b2-MLP -s2mlp_block_factoryFNet -fft_block_factoryImportantly, the components that make up these blocks are part of the public API, and thus can be easily mixed and\nmatched. Additionally, several component variations have been made based on combining ideas from current research.\nThis includes:fftlinear_block_factory- an FNet block variation: combines a 1D FFT for patch mixing plus a linear layer.create_shift1d_op- A 1D shift operation inspired by S\u00b2-MLP, making it appropriate for sequence data.create_multishift1d_op- Likecreate_shift1d_op, but supports multiple shifts of varying sizes.See their respective docstrings for more information.LICENSESeeLICENSE.Citations@article{Touvron2021ResMLPFN,title={ResMLP: Feedforward networks for image classification with data-efficient training},author={Hugo Touvron and Piotr Bojanowski and Mathilde Caron and Matthieu Cord and Alaaeldin El-Nouby and Edouard Grave and Gautier Izacard and Armand Joulin and Gabriel Synnaeve and Jakob Verbeek and Herv'e J'egou},journal={ArXiv},year={2021},volume={abs/2105.03404}}@article{Tolstikhin2021MLPMixerAA,title={MLP-Mixer: An all-MLP Architecture for Vision},author={Ilya O. Tolstikhin and Neil Houlsby and Alexander Kolesnikov and Lucas Beyer and Xiaohua Zhai and Thomas Unterthiner and Jessica Yung and Daniel Keysers and Jakob Uszkoreit and Mario Lucic and Alexey Dosovitskiy},journal={ArXiv},year={2021},volume={abs/2105.01601}}@article{Liu2021PayAT,title={Pay Attention to MLPs},author={Hanxiao Liu and Zihang Dai and David R. So and Quoc V. Le},journal={ArXiv},year={2021},volume={abs/2105.08050}}@article{Yu2021S2MLPSM,title={S2-MLP: Spatial-Shift MLP Architecture for Vision},author={Tan Yu and Xu Li and Yunfeng Cai and Mingming Sun and Ping Li},journal={ArXiv},year={2021},volume={abs/2106.07477}}@article{Touvron2021GoingDW,title={Going deeper with Image Transformers},author={Hugo Touvron and Matthieu Cord and Alexandre Sablayrolles and Gabriel Synnaeve and Herv'e J'egou},journal={ArXiv},year={2021},volume={abs/2103.17239}}@inproceedings{Huang2016DeepNW,title={Deep Networks with Stochastic Depth},author={Gao Huang and Yu Sun and Zhuang Liu and Daniel Sedra and Kilian Q. Weinberger},booktitle={ECCV},year={2016}}@article{LeeThorp2021FNetMT,title={FNet: Mixing Tokens with Fourier Transforms},author={James P Lee-Thorp and Joshua Ainslie and Ilya Eckstein and Santiago Onta{\\~n}{\\'o}n},journal={ArXiv},year={2021},volume={abs/2105.03824}}"} +{"package": "xmlpumpkin", "pacakge-description": "Parse XMLs fromCaboChaand provides simple tree accessors.UsageExpected usages are focused on chunk surfaces and dependency links:>>> aisansan = xmlpumpkin.parse_to_tree(\n... u'\u611b\u71e6\u3005\u3068\u3053\u306e\u8eab\u306b\u964d\u3063\u3066\u5fc3\u5bc6\u304b\u306a\u3046\u308c\u3057\u3044\u6d99\u3092\u6d41\u3057\u305f\u308a\u3057\u3066'\n... )\n>>> len(aisansan.chunks)\n8\n>>> print(aisansan.root.surface)\n\u6d41\u3057\u305f\u308a\u3057\u3066\n>>> print(aisansan.root.func_surface)\n\u3066\n>>> for dep in aisansan.root.linked:\n... print(dep.surface)\n...\n\u964d\u3063\u3066\n\u6d99\u3092You need CaboCha in your path, or shortly with prepared XML:>>> tree = xmlpumpkin.Tree(xml_as_unicode)Should you need an easy interface from Python to CaboCha:>>> from xmlpumpkin import cabocha\n>>> print(cabocha.txttree(\n... u'\u611b\u71e6\u3005\u3068\u3053\u306e\u8eab\u306b\u964d\u3063\u3066\u5fc3\u5bc6\u304b\u306a\u3046\u308c\u3057\u3044\u6d99\u3092\u6d41\u3057\u305f\u308a\u3057\u3066'\n... ))\n \u611b\u71e6\u3005\u3068-----D\n \u3053\u306e-D |\n \u8eab\u306b-D\n \u964d\u3063\u3066-------D\n \u5fc3\u5bc6\u304b\u306a---D |\n \u3046\u308c\u3057\u3044-D |\n \u6d99\u3092-D\n \u6d41\u3057\u305f\u308a\u3057\u3066\nEOS\n>>> print(cabocha.as_xml(\n... u'\u611b\u71e6\u3005\u3068\u3053\u306e\u8eab\u306b\u964d\u3063\u3066\u5fc3\u5bc6\u304b\u306a\u3046\u308c\u3057\u3044\u6d99\u3092\u6d41\u3057\u305f\u308a\u3057\u3066'\n... ))\n\n ...\nAll I/Os are unicodes!\nIf encodings other than UTF-8 is preferred, directly modify following constants:>>> import xmlpumpkin.runner\n>>> xmlpumpkin.runner.CABOCHA_ENCODING = 'SJIS'\n>>>\n>>> import xmlpumpkin.tree\n>>> xmlpumpkin.tree.XML_ENCODING = 'SJIS'PropertiesNot enough but a few properties are provided viaTreeandChunkobjects.class xmlpumpkin.Tree(cabocha_xml)chunks - tuple of chunksroot - root (not depending on any chunks) Chunk objectchunk_by_id(chunk_id) - get Chunk object by its id generated by CaboCha_element - origin XML as lxml Element objectclass xmlpumpkin.Chunk(element, parent)id - chunk idlink_to_id - its depending chunk idlinked_from_ids - tuple of chunk id depending to this chunkfunc_id - functional token id of this chunkdep - its depending Chunk objectlinked - list of all Chunk objects depending to this chunksurface - surface of this chunkfunc_surface - surface of this chunk\u2019s functional token_tokens() - its containing tokens as lxml Element objects"} +{"package": "xmlpydict", "pacakge-description": "xmlpydict \ud83d\udcd1Requirementspython 3.7+InstallationTo install xmlpydict, using pip:pipinstallxmlpydictQuickstart>>>fromxmlpydictimportparse>>>parse(\"\"){'package':{'xmlpydict':{'@language':'python'}}}>>>parse(\"Hello!\"){'person':{'@name':'Matthew','#text':'Hello!'}}GoalsCreate a consistent parsing strategy between XML and Python dictionaries. xmlpydict takes a more laid-back approach to enforce the syntax of XML. However, still ensures fast speeds by using finite automata.Featuresxmlpydict allows for multiple root elements.\nThe root object is treated as the Python object.xmlpydict supports the followingCDataSection: CDATA Sections are stored as {'#text': CData}.Comments: Comments are tokenized for corectness, but have no effect in what is returned.Element Tags: Allows for duplicate attributes, however only the latest defined will be taken.Characters: Similar to CDATA text is stored as {'#text': Char} , however this text is stripped.dict.get(key[, default]) will not cause exceptions# Empty tags are containers>>>fromxmlpydictimportparse>>>parse(\"\"){'a':{}}>>>parse(\"\"){'a':{}}>>>parse(\"\").get('href')None>>>parse(\"\"){}Attribute prefixing# Change prefix from default \"@\" with keyword argument attr_prefix>>>fromxmlpydictimportparse>>>parse('

            ',attr_prefix=\"$\"){\"p\":{\"$width\":\"10\",\"$height\":\"5\"}}Exceptions# Grammar and structure of the xml_content is checked while parsing>>>fromxmlpydictimportparse>>>parse(\"\")Exception:notwellformed(violationatpos=5)UnsupportedProlog / Enforcing Document Type Definition and Element Type DeclarationsEntity ReferencingNamespaces"} +{"package": "xmlpylighter", "pacakge-description": "xmlpylighter is a tiny web page to pretty print and compare xml filesusageLaunching$ xmlpylighterthat\u2019s all.xmlpylighter will start a small server\n(by default, serving tohttp://localhost:8080)Just go to your browser, paste one or two xml text and submitinstallation(don\u2019t hesitate to install inside a virtualenv)$ pip install xmlpylighterproject dependenciesbottlepygmentslxmlVersion Historyv0.1first versionserve simple http pagepretty print and highlight one or two xmlshow diff if two xml are provided"} +{"package": "xml-python", "pacakge-description": "A library for making Python objects from XML."} +{"package": "xmlrecords", "pacakge-description": "XML Recordsxmlrecordsis a user-friendly wrapper oflxmlpackage for extraction of tabular data from XML files.This data provider sends all his data in... XML. You know nothing about XML, except that it looks kind of weird and you woulddefinitelynever use it for tabular data. How could you just transform all this XML nightmare into a sensible tabular format, like a DataFrame? Don't worry: you are in the right place!InstallationpipinstallxmlrecordsThe package requirespython 3.7+and one external dependencylxml.UsageBasic exampleUsually, you only need to specify path to table rows; optionally, you can specify paths to any extra data you'd like to add to your table:# XML objectxml_bytes=b\"\"\"\\Virtual Shore2020-02-02T05:12:22Sunny Night2017112.34Babel-17196310\"\"\"# Transform XML to records (= a list of key-value pairs)importxmlrecordsrecords=xmlrecords.parse(xml=xml_bytes,records_path=['Shelf','Book'],# The rows are XML nodes with the repeating tag meta_paths=[['Library','Name'],['Shelf','Timestamp']],# Add additional \"meta\" nodes)forrinrecords:print(r)# Output:# {'Name': 'Virtual Shore', 'Timestamp': '2020-02-02T05:12:22', 'Title': 'Sunny Night', 'alive': 'no', 'name': 'Mysterious Mark', 'Year': '2017', 'Price': '112.34'}# {'Name': 'Virtual Shore', 'Timestamp': '2020-02-02T05:12:22', 'Title': 'Babel-17', 'alive': 'yes', 'name': 'Samuel R. Delany', 'Year': '1963', 'Price': '10'}# Validate record keysxmlrecords.validate(records,expected_keys=['Name','Timestamp','Title','alive','name','Year','Price'],)With PandasYou can easily transform records to a pandas DataFrame:importpandasaspddf=pd.DataFrame(records)With SQLYou can use records directly with INSERT statements if your SQL database isPEP 249 compliant. Most SQL databases are.SQLite is an exception. There, you'll have to transform records (= a list of dictionaries) into a list of lists:importsqlite3withsqlite3.connect('maindev.db')asconn:c=conn.cursor()c.execute(\"\"\"\\CREATE TABLE BOOKS (LIBRARY_NAME TEXT,SHELF_TIMESTAMP TEXT,TITLE TEXT,AUTHOR_ALIVE TEXT,AUTHOR_NAME TEXT,YEAR INT,PRICE FLOAT,PRIMARY KEY (TITLE, AUTHOR_NAME))\"\"\")c.executemany(\"\"\"INSERT INTO BOOKS VALUES (?,?,?,?,?,?,?)\"\"\",[list(x.values())forxinrecords],)conn.commit()FAQWhy notxmltodict?xmltodictcan convert arbitrary XML to a python dict. However, it is 2-3 times slower thanxmlrecordsand does not support some features specific for tablular data.Why notxmlorlxml?xmlrecordsuseslxmlunder the hood. Usingxmlorlxmldirectly is a viable option too - in case this package doesn't cover your particular use case."} +{"package": "xmlrepr", "pacakge-description": "Overviewxmlreprmodule is used to have a nice representations for objects in xml format.\nso, instead of having representation like this<__main__.Foo object at 0x00000001>,\nyou can simply try this. This package also could be used for complex representations:\n \n \n \n \n \n \n \n \n 2\n \n \n \n \n \n \n \ninstallingthere are two other basic releases:0.0.60.0.7simple introductionfunctionparametersdocumentationstatusreprarg1, level=None, props=None, children=Noneseereprat0.0.7Deprecatedxmlreprname, props:dict=None, children:list=Nonerecursively builds xml representationsRecommendedxmlrepr(name, props=None, children=None)nameThe name of the xml tag. string value. e.g.propsDictionary represents properties of the tag.e.g.ifbool(props)gives False(it's None by default), no property will get displayed.e.g.Keys and values of props could be string or any object.if value in props is boolean value(True or False), will just display the key if True and omit them if False.e.g.if the key and value strings has'\\n'in them, will got replaced byr'\\n'.(this is a current fix to a bug)childrenA list of objects that are ready to be represented in xml format.UsageIn__str__or__repr__, just make call to this function and return the result.(no need for__xml__and its 'level' parameter)Why is it Recommended ?(And why is repr deprecated ?)xmlrepr module is intended to asmuch simpleas it could be. Having__xml__method and 'level' parameter wasn't a good thing.\nUsing__repr__and__str__instead of__xml__. Depending on recursion istead of 'level' parameter. making it easier for developers.xmlrepr function came toreplacerepr withless codeand dependencies. for example stop usingglobals()['__builtins__']['repr']thing.xmlrepr function isdeveloper friendly.xmlrepr hasfixed bugsthat are still in repr function.ExamplesLet's see some examples to understand the module easily.fromxmlreprimportxmlreprinput=xmlrepr('input',dict(name='text',type='text',value='welcome',required=True))span=xmlrepr('span')p=xmlrepr('p',0,[span])a=xmlrepr('a',dict(href='\\n'),[p])print(xmlrepr('form',None,[input,a,\"some text\\nand lines\"]))Output:
            \n \n \n

            \n \n

            \n             \n some text \n and lines\n
            Play around the code above to make sure you understand it.Source CodeHere is howxmlreprfunction is implemented.defxmlrepr(name,props=None,children=None):props=' '+' '.join('%s=\"%s\"'%(key.replace('\\n',r'\\n'),value.replace('\\n',r'\\n'))ifvalue!=Trueelsekeyforkey,valueinprops.items()ifvalue!=False)ifpropselse''ifchildren:# regular tag -> recursionreturn\"<{name}{props}>\\n{indent}{inners}\\n\".format(name=name,props=props,indent=' '*4,inners='\\n'.join(str(child)forchildinchildren).replace('\\n','\\n'))else:# self-closing tag -> stop recursionreturn\"<%s%s/>\"%(name,props)"} +{"package": "xmlrfc2md", "pacakge-description": "No description available on PyPI."} +{"package": "xmlrpc2", "pacakge-description": "xmlrpc2======="} +{"package": "xmlrpcauth", "pacakge-description": "DEPRECATED, the xmlrpclib module of the standard library already supports this:xmlrpclib.ServerProxy('http[s]://user:pass@host')"} +{"package": "xmlrpccomp", "pacakge-description": "xmlrpc compxmlrpc python2 and python3Usageserverfrom xmlrpccomp import RpcServer\n>>> def hello():\n... return 'hello'\n... \n>>> server = RpcServer(('localhost', 5000))\n>>> server.register_function(hello, 'hello')\n>>> server.serve_forever()client>>> from xmlrpccomp import RpcClient\n>>> client = RpcClient('http://localhost:5000')\n>>> client.hello()\n'hello'"} +{"package": "xmlrpcdo", "pacakge-description": "xmlrpcdo is a simple, self-explaining XML-RPC request fiddler"} +{"package": "xmlrpclib", "pacakge-description": "This kit contains a Python implementation for\nUserland\u2019s XML-RPC protocol. It also includes\nserver frameworks for SocketServer and Medusa."} +{"package": "xmlrpclibex", "pacakge-description": "A Python xmlrpc client library with proxy and timeout support.Installation$pipinstallxmlrpclibexOr$pythonsetup.pyinstallUsageA basic examplefromxmlrpclibeximportxmlrpclibexsp=xmlrpclibex.ServerProxy(uri,timeout=30,proxy={'host':'your proxy address','port':'your proxy port','is_socks':True,'socks_type':'v5'})The timeout and proxy parametersThis module subclasses the ServerProxy class from the xmlrpclib module (or\nthe xmlrpc.client module in case of Python3), and adds two parameters\ntimeout and proxy.timeout: seconds waiting for the socket operations.proxy: a dict specifies the proxy settings (supports HTTP proxy and socks\nproxy). The dict supports the following keys:host: the address of the proxy server (IP or DNS)port: the port of the proxy server. default: 8080 for http\nproxy, and 1080 for socks proxyusername: username to authenticate to the server. default Nonepassword: password to authenticate to the server, only relevant when\nusername is set. default Noneis_socks: whether the proxy is a socks proxy, default Falsesocks_type: string, \u2018v4\u2019, \u2018v5\u2019, \u2018http\u2019 (http connect tunnel), only\nrelevant when is_socks is True. default \u2018v5\u2019NoteSometimes, access HTTPS over HTTP Proxy (through CONNECT tunnel) may report\nerrors, recommend using SOCKS proxy.LicenseCopyright 2015 benhengxLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xmlrpclib-to", "pacakge-description": "No description available on PyPI."} +{"package": "xmlrpcssl", "pacakge-description": "xmlrpcsslxmlprcsslis a Python library that provides secure communication (TLS) beetween clients and servers through xmlrpc protocol. It supports plugable handlers to provide user authentication. For now, it has as an example a ldap based authentication handler.Server configuration>>>fromxmlrpcsslimportSecureAuthenticatedXMLRPCServer>>>fromxmlrpcssl.handlersimportLdapVerifyingRequestHandler>>>fromdatetimeimportdatetime>>>keySsl='/tmp/server.key'>>>crtSsl='/tmp/server.crt'>>>tcpPort=433>>>serverIp='10.0.0.1'>>>ldapHost='ldapHost'# User must have access granted to this host in ldap>>>ldapServer='ldapServer'# ip or name of ldap server>>>gidNumber=111# User must be in this group in order to be authenticated>>>isMasterUser=False# True if the user has write permissions in the ldap server>>>baseUsrLoginDn='o=Organization,c=US'# user base DN to perform login in# the ldap server>>>baseSearchDn='o=Organization,c=US'# search base DN to perform a search in# the ldap server base>>>RequestHandler=LdapVerifyingRequestHandler# a handler that inherits from# BaseRequestHandler and performs user authentication>>>optArgs={'isMasterUser':isMasterUser,'baseUsrLoginDn':baseUsrLoginDn,...'ldapServer':ldapServer,'gidNumber':gidNumber,'baseSearchDn':baseSearchDn,...'host':ldapHost,'RequestHandler':RequestHandler}>>>serverSSL=SecureAuthenticatedXMLRPCServer((serverIp,tcpPort),keySsl,crtSsl,**optArgs)>>>deftest():...# toy test function...returndatetime.now().strftime(\"%H:%M:%S\")>>>serverSSL.register_function(test)>>>serverSSL.serve_forever()Client configuration>>>fromxmlrpclibimportServerProxy>>>userName='ldapUser'>>>password='ldapUserPassword'>>>tcpPort=433>>>serverIp='10.0.0.1'>>>clientXml=ServerProxy('https://'+userName+':'+password+'@'+serverIp+':'+str(tcpPort))>>>response=clientXml.test()>>>printresponseInstallationTo install xmlrpcssl, simply run:$ pip install xmlrpcsslxmlrpcssl is compatible with Python 2.6+Documentationhttps://xmlrpcssl.readthedocs.ioSource CodeFeel free to fork, evaluate and contribute to this project.Source:https://github.com/jonDel/xmlrpcsslLicenseGPLv3 licensed.Creditshttp://code.activestate.com/recipes/496786-simple-xml-rpc-server-over-httpsandhttps://github.com/nosmo/python-xmlrpcsslfor inspiration"} +{"package": "xmlrpcutils", "pacakge-description": "xmlrpcutilsxmlrpc server simplify.Installpip install xmlrpcutilsTestServerfrom xmlrpcutils.server import SimpleXmlRpcServer\nfrom xmlrpcutils.service import ServiceBase\n\nclass SayHelloService(ServiceBase):\n\n def hello(self, name):\n return f\"Hello {name}, how are you!\"\n\nclass TestServer(SimpleXmlRpcServer):\n \n def register_services(self):\n super().register_services()\n SayHelloService(namespace=\"debug\").register_to(self.server)\n\napp = TestServer()\napp_ctrl = app.get_controller()\n\nif __name__ == \"__main__\":\n app_ctrl()Start test serverpython test_server.py startRemote call with TestServerIn [9]: from xmlrpc.client import ServerProxy\n\nIn [10]: server = ServerProxy('http://127.0.0.1:8381')\n\nIn [11]: server.system.listMethods()\nOut[11]:\n['debug.counter',\n 'debug.echo',\n 'debug.false',\n 'debug.hello',\n 'debug.hostname',\n 'debug.null',\n 'debug.ping',\n 'debug.sleep',\n 'debug.sum',\n 'debug.timestamp',\n 'debug.true',\n 'debug.uname',\n 'debug.urandom',\n 'debug.uuid4',\n 'system.listMethods',\n 'system.methodHelp',\n 'system.methodSignature',\n 'system.multicall']\n\nIn [12]: server.debug.hello('zencore')\nOut[12]: 'Hello zencore, how are you!'Use apikey auth mechanism.Addapikeysin the server's config fileapikeys:\n HyuTMsNzcSZYmwlVDdacERde9azdTKT8:\n appid: test01\n other-app-info: xxx\n SEEpVkus5b86aHxS6UMSCFLxkIhYMMZF:\n appid: test02\n other-app-info: xxxAddapikeyheader at the client sideIn [93]: from xmlrpc.client import ServerProxy\n ...: service = ServerProxy(\"http://127.0.0.1:8911\", headers=[(\"apikey\", \"HyuTMsNzcSZYmwlVDdacERde9azdTKT8\")])\n ...: result = service.debug.ping()\n ...: print(result)\npongEnable server http-keepalivekeepalive:\n enable: true\n timeout: 5\n max: 60Http-keepalive is not enabled by default, add keepalive.enable=true to enable it.Enable server response headerserver-tokens: trueThe response header Server is hide by default, add server-tokens=true to show it.Enable methodSignaturedef myfunc1(arg1:int, arg2:str, arg3:list) -> str:\n passAdd returns and args typing to enable methodSignature.Multiple signatures can NOT be auto detected.def myfunc2(arg1, arg2, arg3=None):\n \"\"\"\n @methodSignature: [\"str\", \"int\", \"str\"]\n @methodSignature: [\"str\", \"int\", \"str\", \"list\"]\n \"\"\"\n passUse doc string @methodSignature: to enable methodSignature.Use doc string @methodSignature many times for multiple signatures.def myfunc3(args, arg1, arg2, arg3):\n pass\nmyfunc3._methodSignature = [\"str\", \"int\", \"str\", \"list\"]\n\ndef myfunc4(args, arg1, arg2, arg3=None):\n pass\nmyfunc4._methodSignature = [\n [\"str\", \"int\", \"str],\n [\"str\", \"int\", \"str\", \"list\"],\n]Use extra attr to enable methodSignature.NotePython3.7 or older does not support using parameterheadersin ServerProxy. Therefore, you need to use the client of a higher version when the server requires APIKEY-HEADER verification. Or customize a transport for ServerProxy.Releasesv0.1.1First release.v0.1.2Fix license_files missing problem.v0.1.3Fix DebugService init method problem, add super().init() calling.v0.2.0Don't force to use gevent.Allow non-namespace services.v0.3.1Remove all gevent things.Add apikey auth mechanism. Use headers parameter to provide apikey at then client side.v0.3.2Fix get_ignore_methods name.v0.4.0Add server-tokens option, allow user hide/show response header Server. Default to hide the Server header.Add keepalive options, allow user to enable http-keepalive function.v0.4.2Doc update.v0.4.3Doc fix.Add methodSignature support.v0.4.4Fix methodSignature respose data type. It should be [[...], [...]] type or const string \"signatures not supported\"."} +{"package": "xmlrunner", "pacakge-description": "UNKNOWN"} +{"package": "xml-safe-mod", "pacakge-description": "xml-safe-modA small utility for safely making updates to XML configuration files.It aims to give a safer alternative to using sed when updating XML configuration files, both by avoiding leaking secrets and by making the updates themselves safe and atomic.Usage# In-place updateecho'{\"secret1\": \"password1\"}'|xml-safe-mod--src/etc/daemon/config.xml--in-place--setsecret1./xpath/expression# Use a template file to generate another fileecho'{\"secret1\": \"password1\"}'|xml-safe-mod--src/etc/daemon/config.xml.in--dest/etc/daemon/config.xml--ownerdaemon--groupdaemon--perms600--setsecret1./xpath/expressionIt would support theElementTree subset of XPath."} +{"package": "xmlschema", "pacakge-description": "Thexmlschemalibrary is an implementation ofXML Schemafor Python (supports Python 3.8+).This library arises from the needs of a solid Python layer for processing XML\nSchema based files forMaX (Materials design at the Exascale)European project.\nA significant problem is the encoding and the decoding of the XML data files\nproduced by different simulation software.\nAnother important requirement is the XML data validation, in order to put the\nproduced data under control. The lack of a suitable alternative for Python in\nthe schema-based decoding of XML data has led to build this library. Obviously\nthis library can be useful for other cases related to XML Schema based processing,\nnot only for the original scope.The fullxmlschema documentation is available on \u201cRead the Docs\u201d.FeaturesThis library includes the following features:Full XSD 1.0 and XSD 1.1 supportBuilding of XML schema objects from XSD filesValidation of XML instances against XSD schemasDecoding of XML data into Python data and to JSONEncoding of Python data and JSON to XMLData decoding and encoding ruled by converter classesAn XPath based API for finding schema\u2019s elements and attributesSupport of XSD validation modesstrict/lax/skipXML attacks protection using an XMLParser that forbids entitiesAccess control on resources addressed by an URL or filesystem pathDownloading XSD files from a remote URL and storing them for offline useXML data bindings based on DataElement classStatic code generation with Jinja2 templatesInstallationYou can install the library withpipin a Python 3.7+ environment:pip install xmlschemaThe library uses the Python\u2019s ElementTree XML library and requireselementpathadditional package.\nThe base schemas of the XSD standards are included in the package for working\noffline and to speed-up the building of schema instances.UsageImport the library and then create a schema instance using the path of\nthe file containing the schema as argument:>>>importxmlschema>>>my_schema=xmlschema.XMLSchema('tests/test_cases/examples/vehicles/vehicles.xsd')NoteFor XSD 1.1 schemas use the classXMLSchema11, because the default classXMLSchemais an alias of the XSD 1.0 validator classXMLSchema10.The schema can be used to validate XML documents:>>>my_schema.is_valid('tests/test_cases/examples/vehicles/vehicles.xml')True>>>my_schema.is_valid('tests/test_cases/examples/vehicles/vehicles-1_error.xml')False>>>my_schema.validate('tests/test_cases/examples/vehicles/vehicles-1_error.xml')Traceback (most recent call last):File\"\", line1, inFile\"/home/brunato/Development/projects/xmlschema/xmlschema/validators/xsdbase.py\", line393, invalidateraiseerrorxmlschema.validators.exceptions.XMLSchemaValidationError:failed validating with XsdGroup(model='sequence').Reason: character data between child elements not allowed!Schema:\n \n Instance:\n NOT ALLOWED CHARACTER DATA\n \n \n Using a schema you can also decode the XML documents to nested dictionaries, with\nvalues that match to the data types declared by the schema:>>>importxmlschema>>>frompprintimportpprint>>>xs=xmlschema.XMLSchema('tests/test_cases/examples/collection/collection.xsd')>>>pprint(xs.to_dict('tests/test_cases/examples/collection/collection.xml')){'@xsi:schemaLocation': 'http://example.com/ns/collection collection.xsd',\n 'object': [{'@available': True,\n '@id': 'b0836217462',\n 'author': {'@id': 'PAR',\n 'born': '1841-02-25',\n 'dead': '1919-12-03',\n 'name': 'Pierre-Auguste Renoir',\n 'qualification': 'painter'},\n 'estimation': Decimal('10000.00'),\n 'position': 1,\n 'title': 'The Umbrellas',\n 'year': '1886'},\n {'@available': True,\n '@id': 'b0836217463',\n 'author': {'@id': 'JM',\n 'born': '1893-04-20',\n 'dead': '1983-12-25',\n 'name': 'Joan Mir\u00f3',\n 'qualification': 'painter, sculptor and ceramicist'},\n 'position': 2,\n 'title': None,\n 'year': '1925'}]}AuthorsDavide Brunato and others who have contributed with code or with sample cases.LicenseThis software is distributed under the terms of the MIT License.\nSee the file \u2018LICENSE\u2019 in the root directory of the present\ndistribution, orhttp://opensource.org/licenses/MIT."} +{"package": "xmlscomparator", "pacakge-description": "No description available on PyPI."} +{"package": "xmlsec", "pacakge-description": "Python bindings for theXML Security Library.DocumentationA documentation forxmlseccan be found atxmlsec.readthedocs.io.UsageCheck theexamplessection in the documentation to see various examples of signing and verifying using the library.Requirementslibxml2 >= 2.9.1libxmlsec1 >= 1.2.18Installxmlsecis available on PyPI:pipinstallxmlsecDepending on your OS, you may need to install the required native\nlibraries first:Linux (Debian)apt-getinstallpkg-configlibxml2-devlibxmlsec1-devlibxmlsec1-opensslNote: There is no required version of LibXML2 for Ubuntu Precise,\nso you need to download and install it manually.wgethttp://xmlsoft.org/sources/libxml2-2.9.1.tar.gztar-xvflibxml2-2.9.1.tar.gzcdlibxml2-2.9.1./configure&&make&&makeinstallLinux (CentOS)yuminstalllibxml2-develxmlsec1-develxmlsec1-openssl-devellibtool-ltdl-develLinux (Fedora)dnfinstalllibxml2-develxmlsec1-develxmlsec1-openssl-devellibtool-ltdl-develMacbrewinstalllibxml2libxmlsec1pkg-configAlpineapkaddbuild-baselibressllibffi-devlibressl-devlibxslt-devlibxml2-devxmlsec-devxmlsecTroubleshootingMacIf you get any fatal errors about missing.hfiles, update yourC_INCLUDE_PATHenvironment variable to include the appropriate\nfiles from thelibxml2andlibxmlsec1libraries.WindowsStarting with 1.3.7, prebuilt wheels are available for Windows,\nso runningpip install xmlsecshould suffice. If you want\nto build from source:Configure build environment, seewiki.python.orgfor more details.Install from source dist:pipinstallxmlsec--no-binary=xmlsecBuilding from sourceClone thexmlsecsource code repository to your local computer.gitclonehttps://github.com/mehcode/python-xmlsec.gitChange into thepython-xmlsecroot directory.cd/path/to/xmlsecInstall the project and all its dependencies usingpip.pipinstall.ContributingSetting up your environmentFollow steps 1 and 2 of themanual installation instructions.Initialize a virtual environment to develop in.\nThis is done so as to ensure every contributor is working with\nclose-to-identicial versions of packages.mkvirtualenvxmlsecThemkvirtualenvcommand is available fromvirtualenvwrapperpackage which can be installed by followinglink.Activate the created virtual environment:workonxmlsecInstallxmlsecin development mode with testing enabled.\nThis will download all dependencies required for running the unit tests.pipinstall-rrequirements-test.txtpipinstall-e\".\"Running the test suiteSet up your environment.Run the unit tests.pytesttestsTests configurationEnv variablePYXMLSEC_TEST_ITERATIONSspecifies number of\ntest iterations to detect memory leaks.Reporting an issuePlease attach the output of following information:version ofxmlsecversion oflibxmlsec1version oflibxml2output from the commandpkg-config--cflagsxmlsec1LicenseUnless otherwise noted, all files contained within this project are licensed under the MIT opensource license.\nSee the includedLICENSEfile or visitopensource.orgfor more information."} +{"package": "xmlsec-aop", "pacakge-description": "UNKNOWN"} +{"package": "xmlsecurity", "pacakge-description": "UNKNOWN"} +{"package": "xml-serializer", "pacakge-description": "XML SerializerAllows you to convert XML to python dict (with python objects) using a schema.ExamplesWe have next xml data (profiles.xml)And we want to turn it into{\"payload\":{\"my_profile\":{\"record\":{\"id\":1,\"nickname\":\"eff1c\",\"admin\":True,\"posts\":{\"topic\":\"something\",\"post\":[{\"name\":\"test post\",\"description\":\"It's my test post.\"},{\"name\":\"python xml_serializer\",\"description\":\"It's very useful module!\",},],},}}}}We will write next schemafromxml_serializerimportTag,TagAttrfromxml_serializer.converter_typesimportInteger,String,Booleanprofiles_schema={Tag(\"payload\"):{Tag(\"MyProfile\",\"my_profile\"):{Tag(\"record\"):{TagAttr(\"id\"):Integer(nullable=False),TagAttr(\"nickname\"):String(nullable=False),TagAttr(\"admin\"):Boolean(),Tag(\"posts\"):{TagAttr(\"topic\"):String(nullable=False),Tag(\"post\"):[{TagAttr(\"name\"):String(),TagAttr(\"description\"):String()}]}}}}Get etree element (tag)fromxml.etreeimportElementTreeasetreetree=etree.parse(\"profiles.xml\")root=tree.getroot()# you can use root tag or find any elsemain_tag=root.find(\"payload\")And call the method to pass them tofromxml_serializerimportxml_serializeresponse=xml_serialize(profiles_schema,main_tag)SchemaTag/TagAttrIn order to serialize data, you need to describe the scheme of its structure.To do this, we create a python dict with Tag/TagAttr object keys.The value for Tag is a set of TagAttr-s or Tag.\nI think it's clear that TagAttr is an attribute of the current tag, and Tag is actually a nested tag.fromxml_serializerimportTag,TagAttrfromxml_serializer.converter_typesimportStringschema={Tag(\"posts\"):{TagAttr(\"topic\"):String(nullable=False),Tag(\"post\"):[{TagAttr(\"name\"):String(),TagAttr(\"description\"):String()}]}}Both Tag and TagAttr have 2 parameters: field_name and name.field_name- it is name in xml.name- it is our custom name with which the object will return to us after serialization (by default- field_name).Field data typesTo convert TagAttr values, we use data types:String,Integer,Float,Boolean,NestedType.String,Integer,Float,Booleanare similar to common data types (as in python).\nAll of them have thenullableparameter (Trueby default).When set toFalse, if the tag does not have this attribute in the input data, an error will be raisedNestedTypeIt is a data type that allows you to intercept serialization in the middle of a schema and\nprocess the resulting data according to your needs.In order to use it, we have to describe the nested schema separately\nand create a function that will process the data received from it.NestedType has 2 attributes for it:schemaanddata_handling_functionfromxml_serializerimportTag,TagAttrfromxml_serializer.converter_typesimportBoolean,String,NestedTypeposts_schema={Tag(\"post\",\"posts\"):[{TagAttr(\"name\"):String(),TagAttr(\"description\"):String()}]}defget_post_names(data):posts=data[\"posts\"]return[post[\"name\"]forpostinposts]schema_with_nesting={Tag(\"record\"):{TagAttr(\"admin\"):Boolean(),Tag(\"posts\",\"post_names\"):NestedType(posts_schema,get_post_names)}}In this example, we return only a list of post-s names to the posts tag, discarding all the information we don't need.\nThis way, NestedType allows you to modify the output data schema without unnecessary iterations.Custom typeYou can create your own field data types. UseAbstractTypefor it.fromxml_serializer.abstract_typeimportAbstractTypeclassBoolean(AbstractType):defconvert_method(self,value):returnTrueifvalue.lower()==\"true\"elseFalse"} +{"package": "xmlsession", "pacakge-description": "No description available on PyPI."} +{"package": "xmlsig", "pacakge-description": "XML Signature created with cryptography and lxml"} +{"package": "xml-sitemap-writer", "pacakge-description": "py-xml-sitemap-writerPython3 package for writing largeXML sitemapswith no external dependencies.pip install xml-sitemap-writerUsageThis package is meant togenerate sitemaps with hundred of thousands of URLsinmemory-efficient wayby\nmaking use ofiterators to populate sitemapwith URLs.fromtypingimportIteratorfromxml_sitemap_writerimportXMLSitemapdefget_products_for_sitemap()->Iterator[str]:\"\"\"Replace the logic below with a query from your database.\"\"\"foridxinrange(1,1000001):yieldf\"/product/{idx}.html\"# URLs should be relative to what you provide as \"root_url\" belowwithXMLSitemap(path='/your/web/root',root_url='https://your.site.io')assitemap:sitemap.add_section('products')sitemap.add_urls(get_products_for_sitemap())sitemap.xmlandsitemap-00N.xml.gzfiles will be generated once this code runs:https://your.site.io/sitemap-products-001.xml.gzhttps://your.site.io/sitemap-products-002.xml.gz...And gzipped sub-sitemaps with up to 15.000 URLs each:https://your.site.io/product/1.htmlhttps://your.site.io/product/2.htmlhttps://your.site.io/product/3.html...For easier discovery of your sitemap add its URL to/robots.txtfile:Sitemap: https://your.site.io/sitemap.xml"} +{"package": "xmlsq", "pacakge-description": "The utilityxmlsqperforms simple and full XPath 1.0 queries on an XML document.>>> import xmlsq\n>>> xml = r\"helloworld\"\n>>> xmlsq.get_text(xml, \"//b\")\n'hello'\n>>> xmlsq.get_text(xml, \"//b[2]\")\n'world'\n>>> xmlsq.full_query(xml, \"//b\")\n'hello\\nworld\\n'\n>>> xmlsq.get_text(xml, \"//b/@foo\")\n'baz'\n>>> xmlsq.full_query(xml, \"//b/@foo\")\n'foo=\"baz\"\\n'\n>>> xmlsq.full_query(xml, \"/a\", xmlsq.Opts.RAW)\n'helloworld'\n>>> xmlsq.count(xml, \"//b\")\n2\n>>> xmlsq.count(xml, \"//notthere\")\n0\n>>> xmlsq.count(xml, \"//e\")\n1\n>>> xmlsq.full_query(xml, \"2+3.5\")\n'5.500000'xmlsq.get_text()extracts the text value of thefirstnode found selected by the query.xmlsq.full_query()outputs the result of the full XPath 1.0 query as a string.xmlsq.count()computes the integer value ofcount(query).Forxmlsq.get_text()andxmlsq.count()the querymustevaluate to a node.xmlsq.full_query()accepts any valid XPath 1.0 expression and returns the result as a string.For full details of all available methods and options, please see thedocumentation.System requirementsWindows platform with Python 3.\nRequires the Windows native librarydiXmlsq.dllto be installed on your system, available fromhttps://www.cryptosys.net/xmlsq/.AcknowledgmentThis software is based on the pugixml library (https://pugixml.org). Pugixml is Copyright (C) 2006-2019 Arseny Kapoulkine.ContactFor more information or to make suggestions, please contact us athttps://cryptosys.net/contact/David IrelandDI Management Services Pty LtdAustralia5 June 2020"} +{"package": "xmlsquash", "pacakge-description": "UNKNOWN"} +{"package": "xmlstarlet", "pacakge-description": "XMLStarlet CFFIXMLStarlet Toolkit: Python CFFI bindingsFree software: MIT licenseDocumentation (this package):https://xmlstarlet.readthedocs.io.Original XMLStarlet Documentation:http://xmlstar.sourceforge.net/doc/UG/FeaturesSupports all XMLStarlet commands from Python, justimport xmlstarlet:edit(*args): Edit/Update XML document(s)select(*args): Select data or query XML document(s) (XPATH, etc)transform(*args): Transform XML document(s) using XSLTvalidate(*args): Validate XML document(s) (well-formed/DTD/XSD/RelaxNG)format(*args): Format XML document(s)elements(*args): Display element structure of XML documentcanonicalize(*args): XML canonicalizationlistdir(*args): List directory as XML (NOTsupported on Windows)escape(*args): Escape special XML charactersunescape(*args): Unescape special XML characterspyx(*args): Convert XML into PYX format (based on ESIS - ISO 8879)depyx(*args): Convert PYX into XMLFor some examples, have a look attests/test_xmlstarlet.py.CreditsKudos to XMLStarlet and its maintainers and users (original sources onSourceForge)!This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.Binary wheels built via GitHub Actions bycibuildwheelHistory1.6.8 (2022-04-30)Added Python 3.10 support.Fixed issue #199 (pending confirmation) - upgraded libxml2 and libxslt versions to fix CVEsUpgraded development and build-time dependencies.Now using latestcibuildwheel2.5.0, which supports more architectures and builds.Started to improve the documentation - added better usage examples.Formatting and linting fixes1.6.7 (2020-12-24)Fixed MacOS binary wheel builds1.6.6 (2020-10-04)Simplified and automated building source and binary wheels for Linux, MacOS, and Windows via GitHub actions +cibuildwheel.Improved documentation and local development workflow.Fixes issue #51 (previously closed as \u201chard to fix\u201d, but now reopened).Completely rewritten native Windows build process, based on libxslt.Windows port does not supportls(and converselylistdir()).1.6.5 (2020-09-29)No changes from previous release except up-to-date dependencies and some build fixes.Fixes issue #118 (awaiting confirmation).1.6.3 (2019-10-29)First working release on PyPI, based on xmlstarlet-1.6.1 source tarball.1.6.2 (2019-10-28)Second (failed) release on PyPI, based on XMLStarlet master branch.1.6.1 (2019-10-23)First (incomplete) release on PyPI, based on XMLStarlet master branch."} +{"package": "xmlstore", "pacakge-description": "### xmlstore"} +{"package": "xml-stream", "pacakge-description": "xml_streamA simple XML file and string reader that is able to read big XML files and strings by using streams (iterators),\nwith an option to convert to dictionariesDescriptionxml_streamcomprises two helper functions:read_xml_fileWhen given a path to a file and the name of the tag that holds the relevant data, it returns an iterator\nof the data asxml.etree.ElementTree.Elementobject by default, or as dicts whento_dictargument isTrueread_xml_stringWhen given an XML string and the name of the tag that holds the relevant data, it returns an iterator\nof the data asxml.etree.ElementTree.Elementobject by default, or as dicts whento_dictargument isTrueMain DependenciesPython +3.6Getting StartedInstall the packagepipinstallxml_streamImport theread_xml_fileand theread_xml_stringclasses and use accordinglyfromxml_streamimportread_xml_file,read_xml_stringxml_string=\"\"\"MarketingJohn DoeJane DoePeter DoeCustomer ServiceMary DoeHarry DoePaul Doe\"\"\"file_path='...'# path to your XML file# For XML strings, use read_xml_string which returns an iteratorforelementinread_xml_string(xml_string,records_tag='staff'):# returns the element as xml.etree.ElementTree.Element by default# ...do something with the elementprint(element)# Note that if a tag is namespaced with say _prefix:tag_ and domain is _xmlns:prefix=\"https://example\",# the records_tag from that tag will be '{https://example}tag'forelement_as_dictinread_xml_string(xml_string,records_tag='staff',to_dict=True):# returns the element as dictionary# ...do something with the element dictionaryprint(element_as_dict)# will print\"\"\"{'operations_department': {'employees': [[{'team': 'Marketing','location': {'name': 'head office','address': 'Kampala, Uganda'},'first_name': 'John','last_name': 'Doe','_value': 'John Doe'},{'team': 'Marketing','location': {'name': 'head office','address': 'Kampala, Uganda'},'first_name': 'Jane','last_name': 'Doe','_value': 'Jane Doe'},{'team': 'Marketing','location': {'name': 'head office','address': 'Kampala, Uganda'},'first_name': 'Peter','last_name': 'Doe','_value': 'Peter Doe'}, ],[{'team': 'Customer Service','location': {'name': 'Kampala branch','address': 'Kampala, Uganda'},'first_name': 'Mary','last_name': 'Doe','_value': 'Mary Doe'},{'team': 'Customer Service','location': {'name': 'Kampala branch','address': 'Kampala, Uganda'},'first_name': 'Harry','last_name': 'Doe','_value': 'Harry Doe'},{'team': 'Customer Service','location': {'name': 'Kampala branch','address': 'Kampala, Uganda'},'first_name': 'Paul','last_name': 'Doe','_value': 'Paul Doe'}],]}}\"\"\"# For XML files (even really large ones), use read_xml_file which also returns an iteratorforelementinread_xml_file(file_path,records_tag='staff'):# returns the element as xml.etree.ElementTree.Element by default# ...do something with the elementprint(element)forelement_as_dictinread_xml_file(file_path,records_tag='staff',to_dict=True):# returns the element as dictionary# ...do something with the element dictionaryprint(element_as_dict)# see the print output for read_xml_stringHow to testClone the repo and enter its root foldergitclonehttps://github.com/sopherapps/xml_stream.git&&cdxml_streamCreate a virtual environment and activate itvirtualenv-p/usr/bin/python3.6env&&sourceenv/bin/activateInstall the dependenciespipinstall-rrequirements.txtDownload a huge xml file for test purposes and save it in the/testfolder ashuge_mock.xmlwgethttp://aiweb.cs.washington.edu/research/projects/xmltk/xmldata/data/SwissProt/SwissProt.xml&&mvSwissProt.xmltest/huge_mock.xmlRun the test commandpython-munittestAcknowledgementsThisStack Overflow Answerabout converting XML to dict was very helpful.ThisReal Python tutorial on publishing packageswas very helpfulLicenseCopyright (c) 2020Martin AhinduraLicensed under theMIT License"} +{"package": "xml-subsetter", "pacakge-description": "Xml Subsetterdecimate data while keeping others intactbefore#bulk.xmlsomemetadatathingthingthingthinge0e1e2e3ahyahyahahyahyahahyahyahe4e5e6e7e8e9e10...e99subset_head(\"bulk.xml\", target_file='/tmp/small.xml', data_tag='e',ratio=0.05)after#small.xmlsomemetadatathingthingthingthinge0e1e2e3ahyahyahahyahyahahyahyahe4"} +{"package": "xmltag", "pacakge-description": "No description available on PyPI."} +{"package": "xml-template", "pacakge-description": "Introduction to XML::Template (name suggestions welcome)XML::Template is a templating system; there are already many others, so if\nyou do not like it, look into a different one (its design is inspired by\nat least Template Toolkit and Kid, probably also including elements from\nothers). XML::Template is (like Kid or TAL) designed to guarantee that your\noutput is well-formed XML, which is a good step on the road to give you\nvalid XHTML.You can get the latest version of XML::Template with bzr; get bzr from your\nfavourite distribution and do \u201cbzr get http://bzr.sesse.net/xml-template/\u201d\nto check out the code and this documentation."} +{"package": "xml-thunder", "pacakge-description": "XML ThunderInstallationpip install xml_thunderUsageXML Thunder provides a class called 'Lightning'.\nThe Lightning class's primary purpose is used for creating an XML parser.\nThe Lightning class provides the following methods:__init__(self)Initializes an empty private dictionary__repr__(self)Returns the string of the private dictionary__str__(self)Returns the string of the private dictionary__contains__(self, route: String)Returns a bool if the route is in the keys of the private dictionary__getitem__(self, route: String)Returns None or a Callable from the private dictionary__setitem__(self, route: String, function: Callable)Maps a route to the functionReturns None__delitem__(self, route: String)Deletes the specified routeReturns None__len__(self)Returns the length of a private dictionary__bool__(self)Returns True if the private dictionary is emptyget_all_routes(self)Returns all registered routes in the private dictionaryroute(self, path: String)Creates a route for the provided 'path''path' is any valid xPathNote that this method is a decorator and should be used as suchparse(self, xml_like_document: String | FileObject)The entrypoint for parsing xml strings/filesReturns None"} +{"package": "xml-to-acts", "pacakge-description": "No description available on PyPI."} +{"package": "xmltocd", "pacakge-description": "xml-to-chain-dictAn effective, powerful, fast and simple XML Python parsing tool.online tutorial\uff1ahttp://101.34.219.31:8001/\u6ce8\uff1a0.2.2.2 \u7248\u672c\uff08\u5305\u542b\uff09\u4e4b\u524d\u7684\u4ee3\u7801\u4e3a\u6d4b\u8bd5\u7248\uff0c\u4e0d\u7a33\u5b9a\uff1b\n0.2.3.1 \u7248\u672c\uff08\u5305\u542b\uff09\u5f80\u540e\u7684\u4ee3\u7801\u4e3a\u6b63\u5f0f\u7248\uff0c\u63d0\u4f9b\u7a33\u5b9a\u7684\u89e3\u6790\u5f15\u64ce\u3002\n0.2.3.2\uff1a\u4fee\u590d\u4f7f\u7528 tag \u641c\u7d22\u65f6\u53cc\u500d\u7ed3\u679c\u7684 BUG\uff1b\u4fee\u590d\u65b0\u589e\u5c5e\u6027\u65f6\u6574\u578b\u8d4b\u503c\u95ee\u9898\u3002\u82e5\u60a8\u6709\u610f\u53c2\u4e0e\u672c\u5de5\u5177\u7684\u5f00\u53d1\uff0c\u8bf7\u76f4\u63a5\u8054\u7cfb\uff1ajiyangj@foxmail.com\uff0c\u671f\u5f85\u60a8\u7684\u610f\u89c1\u3002"} +{"package": "xmlTodataframe", "pacakge-description": "No description available on PyPI."} +{"package": "xml-to-df", "pacakge-description": "XML to Pandas DataframeFlattens out nested xml to individual columns in dataframeSample input.xml\n\n Everyday Italian\n Giada De Laurentiis\n 2005\n 30.00\n \n 1\n 5\n 2\n \n \n \n Harry Potter\n J K. Rowling\n \n Praveen\n Pathan\n india\n india1\n \n 2005\n 29.99\n \n \n \n \n \n \n Learning XML\n Erik T. Ray\n 2003\n 39.95\n \ndf = xml_to_df.convert_xml_to_df(\"input.xml\")df.head()Output dataframebook_categorybook_title_langbook_titlebook_authorbook_yearbook_pricebook_values_value_idbook_values_valuebook_title_languagebook_cricketers_cricketer1book_cricketers_cricketer2book_cricketers_countryCOOKINGenEveryday ItalianGiada De Laurentiis200530.00[300, 100, 200][1, 5, 2]NaNNaNNaNNaNCHILDRENenHarry PotterJ K. Rowling200529.99NaNNaNhelloPraveenPathan[india, india1]WEBenLearning XMLErik T. Ray200339.95NaNNaNNaNNaNNaNNaN"} +{"package": "xmltodict", "pacakge-description": "xmltodictxmltodictis a Python module that makes working with XML feel like you are working withJSON, as in this\"spec\":>>>print(json.dumps(xmltodict.parse(\"\"\"... ... ... elements... more elements... ... ... element as well... ... ... \"\"\"),indent=4)){\"mydocument\":{\"@has\":\"an attribute\",\"and\":{\"many\":[\"elements\",\"more elements\"]},\"plus\":{\"@a\":\"complex\",\"#text\":\"element as well\"}}}Namespace supportBy default,xmltodictdoes no XML namespace processing (it just treats namespace declarations as regular node attributes), but passingprocess_namespaces=Truewill make it expand namespaces for you:>>>xml=\"\"\"... ... 1... 2... 3... ... \"\"\">>>xmltodict.parse(xml,process_namespaces=True)=={...'http://defaultns.com/:root':{...'http://defaultns.com/:x':'1',...'http://a.com/:y':'2',...'http://b.com/:z':'3',...}...}TrueIt also lets you collapse certain namespaces to shorthand prefixes, or skip them altogether:>>>namespaces={...'http://defaultns.com/':None,# skip this namespace...'http://a.com/':'ns_a',# collapse \"http://a.com/\" -> \"ns_a\"...}>>>xmltodict.parse(xml,process_namespaces=True,namespaces=namespaces)=={...'root':{...'x':'1',...'ns_a:y':'2',...'http://b.com/:z':'3',...},...}TrueStreaming modexmltodictis very fast (Expat-based) and has a streaming mode with a small memory footprint, suitable for big XML dumps likeDiscogsorWikipedia:>>>defhandle_artist(_,artist):...print(artist['name'])...returnTrue>>>>>>xmltodict.parse(GzipFile('discogs_artists.xml.gz'),...item_depth=2,item_callback=handle_artist)APerfectCircleFant\u00f4masKingCrimsonChrisPotter...It can also be used from the command line to pipe objects to a script like this:importsys,marshalwhileTrue:_,article=marshal.load(sys.stdin)print(article['title'])$bunzip2enwiki-pages-articles.xml.bz2|xmltodict.py2|myscript.py\nAccessibleComputing\nAnarchism\nAfghanistanHistory\nAfghanistanGeography\nAfghanistanPeople\nAfghanistanCommunications\nAutism\n...Or just cache the dicts so you don't have to parse that big XML file again. You do this only once:$bunzip2enwiki-pages-articles.xml.bz2|xmltodict.py2|gzip>enwiki.dicts.gzAnd you reuse the dicts with every script that needs them:$gunzipenwiki.dicts.gz|script1.py\n$gunzipenwiki.dicts.gz|script2.py\n...RoundtrippingYou can also convert in the other direction, using theunparse()method:>>>mydict={...'response':{...'status':'good',...'last_updated':'2014-02-16T23:10:12Z',...}...}>>>print(unparse(mydict,pretty=True))good2014-02-16T23:10:12ZText values for nodes can be specified with thecdata_keykey in the python dict, while node properties can be specified with theattr_prefixprefixed to the key name in the python dict. The default value forattr_prefixis@and the default value forcdata_keyis#text.>>>importxmltodict>>>>>>mydict={...'text':{...'@color':'red',...'@stroke':'2',...'#text':'This is a test'...}...}>>>print(xmltodict.unparse(mydict,pretty=True))ThisisatestLists that are specified under a key in a dictionary use the key as a tag for each item. But if a list does have a parent key, for example if a list exists inside another list, it does not have a tag to use and the items are converted to a string as shown in the example below. To give tags to nested lists, use theexpand_iterkeyword argument to provide a tag as demonstrated below. Note that usingexpand_iterwill break roundtripping.>>>mydict={...\"line\":{...\"points\":[...[1,5],...[2,6],...]...}...}>>>print(xmltodict.unparse(mydict,pretty=True))[1,5][2,6]>>>print(xmltodict.unparse(mydict,pretty=True,expand_iter=\"coord\"))1526Ok, how do I get it?Using pypiYou just need to$pipinstallxmltodictRPM-based distro (Fedora, RHEL, \u2026)There is anofficial Fedora package for xmltodict.$sudoyuminstallpython-xmltodictArch LinuxThere is anofficial Arch Linux package for xmltodict.$sudopacman-Spython-xmltodictDebian-based distro (Debian, Ubuntu, \u2026)There is anofficial Debian package for xmltodict.$sudoaptinstallpython-xmltodictFreeBSDThere is anofficial FreeBSD port for xmltodict.$pkginstallpy36-xmltodictopenSUSE/SLE (SLE 15, Leap 15, Tumbleweed)There is anofficial openSUSE package for xmltodict.# Python2$zypperinpython2-xmltodict# Python3$zypperinpython3-xmltodict"} +{"package": "xml-to-dict", "pacakge-description": "xml_to_dictA simple Python XML to Dictionary parser.The package is based onthis answerfrom Stack Overflow. It parses entities as well as attributes followingthis XML-to-JSON \"specification\".I just added thefrom_nestfunction, which lets you retrieve a value from the nested dictionaries.Installpip3installxml_to_dict--userUsagefromxml_to_dictimportXMLtoDictsample_xml=('''''''Ezequiel''33''San Isidro''''''Bel\u00e9n''30''San Isidro''''''')parser=XMLtoDict()print(parser.parse(sample_xml))# {'response': {'results': {'user': [{'name': 'Ezequiel', 'age': '33', 'city': 'San Isidro'}, {'name': 'Bel\u00e9n', 'age': '30', 'city': 'San Isidro'}]}}}print(parser.value_from_nest('.*ser',sample_xml))# [{'name': 'Ezequiel', 'age': '33', 'city': 'San Isidro'}, {'name': 'Bel\u00e9n', 'age': '30', 'city': 'San Isidro'}]ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Fork the ProjectCreate your Feature BranchCommit your ChangesPush to the BranchOpen a Pull RequestLicenseDistributed under the MIT License. SeeLICENSEfor more information."} +{"package": "xmltodict3", "pacakge-description": "An open-source library that is used for converting XML to a python dictionary.This library:can work with namespacecan transform XML value into python object (integer, boolean, datetime & custom transformers) using the \"type\" attributeInstallation:pip install xmltodict3orpip install git+https://github.com/dart-neitro/xmltodict3Example 1 (Simple case):>>> from xmltodict3 import XmlTextToDict\n>>> text = \"\"\"\n... \n... \n... data\n... \n... \n... \"\"\"\n>>> result = XmlTextToDict(text, ignore_namespace=True).get_dict()\n>>> print(result)\n{'schema': {'root': {'@attr': 'attr_value', '#text': 'data'}}}Example 2 (with transformers):>>> from xmltodict3 import XmlTextToDict\n>>> import xmltodict3.transformers as transformers\n>>> text = \"\"\"\n... \n... \n... \n... 123\n... \n... \n... \n... \"\"\"\n>>> transformer_list = transformers.DefaultTransformerList\n>>> pull_transformers = transformers.PullTransformers(*transformer_list)\n>>> pull_transformers.set_removing_types(True)\n>>> xml_to_dict = XmlTextToDict(text)\n>>> xml_to_dict.use_pull_transformers(pull_transformers)\n>>> result = xml_to_dict.get_dict()\n>>> print(result)\n{'root': {'values': {'int_value': 123}}}More examples"} +{"package": "xmltodictest", "pacakge-description": "https://github.com/renzon"} +{"package": "xmltojson", "pacakge-description": "xmltojsonPython library and cli tool for converting XML to JSONInstall$ poetry add xmltojson$ pip install xmltojsonUsageCommand line:Converting an XML file and sending the output to STDOUT$ xmltojson Send output to a file$ xmltojson -o xmltojson can also read from STDIN$ echo 'John' | xmltojson --stdinLibrary:[1]: import xmltojson\n[2]: with open('/path/to/file', 'r') as f:\n...: my_xml = f.read()\n[3]: xmltojson.parse(my_xml)\n'{\"name\": \"John\"}'"} +{"package": "xmltool", "pacakge-description": "xmltool is a python package to manipulate XML files. It\u2019s very useful to update some XML files with the python syntax without using the DOM.Read the documentation"} +{"package": "xmltools", "pacakge-description": "No description available on PyPI."} +{"package": "xmltopy", "pacakge-description": "UNKNOWN"} +{"package": "xmltotabular", "pacakge-description": "xmltotabularPython library for converting XML to tabular data.Current StatusThis library is under periodic development. It is useful as it stands (seesul-cidr/patent_data_extractorfor thede factoreference implementation), but there is still much to be done before a1.0release. Please get in touch if this project could be useful to you, and especially if you'd be interesting in contributing (I would welcome help with documentation and examples for a robust test suite, for example).DevelopmentWith a working version of Python >= 3.6 and Pipenv:Install dependencies.(note that aPipfile.lockis not included in this repository -- this library should work with any dependency versions which satisfy what is listed in thePipfileandsetup.py, and any necessary pinning should be specified in both)$pipenvinstall--devInstall pre-commit hooks.$pipenvrunpre-commitinstallTestingLinting and formatting.$pipenvrunpre-commitrun--all-filesTests$pipenvrunpytestCoverageTo collect coverage execution data, use:$pipenvruncoveragerun-mpytestand to get a report on the data, use:$pipenvruncoveragereport-mor$pipenvruncoveragehtmlto create an HTML report inhtmlcov/."} +{"package": "xmltoxsd", "pacakge-description": "XMLtoXSD LibraryThexmltoxsdlibrary is a Python tool designed to convert XML documents into XSD (XML Schema Definition) schemas automatically. It simplifies the process of generating XSD schemas from XML files, making it easier for developers to validate their XML data.FeaturesAutomatic Type Inference: Automatically determines the data types for XML elements and attributes.Support for Complex XML Structures: Handles nested elements and attributes with ease.CustomizableminOccursAttribute: Allows users to specify default values forminOccursattribute in the generated XSD.InstallationInstallxmltoxsdusing pip:pipinstallxmltoxsdQuick StartHere's how to quickly get started with xmltoxsd:from xmltoxsd import XSDGenerator\n\ngenerator = XSDGenerator()\nxsd_schema = generator.generate_xsd(\"path/to/your/xml_file.xml\")\nprint(xsd_schema)UsageTo generate an XSD schema from an XML file:with open(\"output.xsd\", \"w\") as f:\n f.write(xsd_schema)ContributingWe welcome contributions to the xmltoxsd library. Please read our CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.LicenseThis project is licensed under the MIT License - see the LICENSE file for details.SupportIf you have any questions or encounter issues using the library, please open an issue on my GitHub repository."} +{"package": "xmltramp", "pacakge-description": "No description available on PyPI."} +{"package": "xmltramp2", "pacakge-description": "# xmltramp2[![Build Status](https://travis-ci.org/tBaxter/xmltramp2.svg?branch=master)](https://travis-ci.org/tBaxter/xmltramp2)[xmltramp](http://www.aaronsw.com/2002/xmltramp/) was originally created by Aaron Swartzfor simple-yet-powerful parsing of RSS and other xml files.It is a simple, fast, lightweight alternative to more heavyweight parsers such as BeautifulSoup or ElementTree. It won't do all they do, but what it does do it does simply and easily.It has been substantially rewritten for subsequent python versions,including Python3 compatibility. Tests are included.## InstallationThe easiest way is via pip:`pip install xmltramp2`Usage is unchanged from older versions of xmltramp, other than you now import from a package:`from xmltramp2 import xmltramp`## UsageEveryone's got their data in XML these days. You need to read it. You've looked at the other XML APIs and they all contain miles of crud that's only necessary when parsing the most arcane documents. Wouldn't it be nice to have an easy-to-use API for the normal XML documents you deal with? That's xmltramp:```>>> sample_xml = \"\"\"John Polk and John PalfreyJohn PolkJohn PalfreyBuffy\"\"\">>> import xmltramp>>> doc = xmltramp.Namespace(\"http://example.org/bar\")>>> bbc = xmltramp.Namespace(\"http://example.org/bbc\")>>> dc = xmltramp.Namespace(\"http://purl.org/dc/elements/1.1/\")>>> d = xmltramp.parse(sample_xml)>>> d...>>> d('version')'2.7182818284590451'>>> d(version='2.0')>>> d('version')'2.0'>>> d._dir[..., ..., ..., ...]>>> d._name(u'http://example.org/bar', u'doc')>>> d[0] # First child....>>> d.author # First author....>>> str(d.author)'John Polk and John Palfrey'>>> d[dc.creator] # First dc:creator....>>> d[dc.creator:] # All creators.[..., ...]>>> d[dc.creator] = \"Me!!!\">>> str(d[dc.creator])'Me!!!'>>> d[bbc.show](bbc.station)'4'>>> d[bbc.show](bbc.station, '5')>>> d[bbc.show](bbc.station)'5'```## CreditsMost thanks go to Aaron Swartz, both for writing this in the first place, and just in general, for all he did.Additional thanks to Kristian Glass, for helping get this over the Python3 hump, and for tests."} +{"package": "xmltranslate", "pacakge-description": "UNKNOWN"} +{"package": "xmltread", "pacakge-description": "xmltreadxmltrampwas originally created by Aaron Swartz\nfor simple-yet-powerful parsing of RSS and other xml files.It is a small, fast alternative to heavyweight parsers like BeautifulSoup and ElementTree.It has been mildly rewritten for python 3 compatibility, including bringing the packaging up to date so it can once again be installed via pip.\nSadly, python modules can no longer be built from a single source file, but the tweaked original xmltramp lives inside of xmltread.from xmltread import xmltrampworks, so you don't need to replace xmltramp with xmltread in your code.Installationvia pip:pip install xmltreadUsageEveryone's got their data in XML these days. You need to read it. You've looked at the other XML APIs and they all contain miles of crud that's only necessary when parsing the most arcane documents. Wouldn't it be nice to have an easy-to-use API for the normal XML documents you deal with? That's xmltramp:>>> sample_xml = \"\"\"\n John Polk and John Palfrey\n John Polk\n John Palfrey\n Buffy\n\"\"\"\n\n>>> import xmltramp\n>>> doc = xmltramp.Namespace(\"http://example.org/bar\")\n>>> bbc = xmltramp.Namespace(\"http://example.org/bbc\")\n>>> dc = xmltramp.Namespace(\"http://purl.org/dc/elements/1.1/\")\n>>> d = xmltramp.parse(sample_xml)\n>>> d\n...\n>>> d('version')\n'2.7182818284590451'\n>>> d(version='2.0')\n>>> d('version')\n'2.0'\n>>> d._dir\n[..., ..., ..., ...]\n>>> d._name\n('http://example.org/bar', 'doc')\n>>> d[0] # First child.\n...\n>>> d.author # First author.\n...\n>>> str(d.author)\n'John Polk and John Palfrey'\n>>> d[dc.creator] # First dc:creator.\n...\n>>> d[dc.creator:] # All creators.\n[..., ...]\n>>> d[dc.creator] = \"Me!!!\"\n>>> str(d[dc.creator])\n'Me!!!'\n>>> d[bbc.show](bbc.station)\n'4'\n>>> d[bbc.show](bbc.station, '5')\n>>> d[bbc.show](bbc.station)\n'5'CreditsBased on the original by Aaron Swartz."} +{"package": "xmltree2xml", "pacakge-description": "xmltree2xmlxmltree2xml convert a compile xmltree from android to classic xmlUsageusage: xmltree2xml [-h] [-n] [-r RESOURCES] [-o OUTPUT_DIR] [-f] file [file ...]\n\nconvert android xmltree to classic xml.\n\npositional arguments:\n file xmltree file.\n\noptions:\n -h, --help show this help message and exit\n -n, --no-header do not add an xml header.\n -r RESOURCES, --resources RESOURCES\n resource file for replace every hexa reference to human redable reference.\n -o OUTPUT_DIR, --output-dir OUTPUT_DIR\n output directory.\n -f, --rename-file rename output file with resource name.Input file syntaxthe android xml compile look like thisE: list (line=16)\n A: name=\"carrier_config_list\" (Raw: \"carrier_config_list\")\n E: pbundle_as_map (line=17)\n E: string-array (line=19)\n A: name=\"mccmnc\" (Raw: \"mccmnc\")\n E: item (line=20)\n A: value=\"TEST\" (Raw: \"TEST\")\n E: pbundle_as_map (line=24)\n E: string-array (line=26)\n A: name=\"mccmnc\" (Raw: \"mccmnc\")\n E: item (line=28)\n A: value=20601\n E: item (line=30)\n A: value=20810\n E: item (line=31)\n A: value=20826\n E: string (line=33)\n A: name=\"feature_flag_name\" (Raw: \"feature_flag_name\")\n T: 'vvm_carrier_flag_el_telecom'\n E: int (line=34)\n A: name=\"vvm_port_number_int\" (Raw: \"vvm_port_number_int\")\n A: value=5499\n E: string (line=37)\n A: name=\"vvm_destination_number_string\" (Raw: \"vvm_destination_number_string\")\n T: '8860'\n E: string (line=38)\n A: name=\"vvm_type_string\" (Raw: \"vvm_type_string\")\n T: 'vvm_type_omtp_1_3'\n E: pbundle_as_map (line=41)\n E: string-array (line=43)\n A: name=\"mccmnc\" (Raw: \"mccmnc\")and output look like thisvvm_carrier_flag_el_telecom8860vvm_type_omtp_1_3Resource fileWith resource file the reference@0x7f08013fhas converted to real value@drawable/ic_shortcut_add_contact.# dump resource file with android sdkaapt2dumpresourceYOUR_APK>resourcefile.txt#xmltree2xmlxmltree2xml-rresourcefile.txtLR.xmltreeWithoutwithLicenseMIT"} +{"package": "xmltreewalker", "pacakge-description": "XmlTreeWalker works in conjunction with expat. It can be used forfiltering and content modification of XML documents by employing various\nOperators and having them activate based on specified Filter rules.Uses include content extraction, suppression and rewriting."} +{"package": "xmlui", "pacakge-description": "\u501f\u9274\u4e86html\u7684\u65b9\u5f0f\uff0c\u901a\u8fc7xml\u63cf\u8ff0UI\u7ed3\u6784"} +{"package": "xmlunittest", "pacakge-description": "Anyone uses XML, for RSS, for configuration files, for\u2026 well, we all use XML\nfor our own reasons (folk says one can not simply uses XML, but still\u2026).So, your code generates XML, and everything is fine. As you follow best\npractices (if you don\u2019t, I think you should), you have written some good\nunit-tests, where you compare code\u2019s result with an expected result. I mean you\ncompare string with string. One day, something bad might happen.XML is not a simple string, it is a structured document. One can not simply\ncompare two XML string and expect everything to be fine: attributes\u2019s order can\nchange unexpectedly, elements can be optional, and no one can explain simply\nhow spaces and tabs works in XML formatting.Here comes XML unittest TestCase: if you want to use the built-in unittest\npackage (or if it is a requirement), and you are not afraid of using xpath\nexpression withlxml, this library is made for you.You will be able to test your XML document, and use the power of xpath and\nvarious schema languages to write tests that matter.LinksDistribution:https://pypi.python.org/pypi/xmlunittestDocumentation:http://python-xmlunittest.readthedocs.org/en/latest/Source:https://github.com/Exirel/python-xmlunittestHow toExtendsxmlunittest.XmlTestCaseWrite your tests, using the function or method that generate XML documentUsexmlunittest.XmlTestCase\u2018s assertion methods to validateKeep your tests readableExample:fromxmlunittestimportXmlTestCaseclassCustomTestCase(XmlTestCase):deftest_my_custom_test(self):# In a real case, data come from a call to your function/method.data=\"\"\"\n \n \n \n \n \"\"\"# Everything starts with `assertXmlDocument`root=self.assertXmlDocument(data)# Check namespaceself.assertXmlNamespace(root,'ns','uri')# Checkself.assertXpathsUniqueValue(root,('./leaf/@id',))self.assertXpathValues(root,'./leaf/@active',('on','off'))"} +{"package": "xmlunittestbetter", "pacakge-description": "Python XML-Unittest===================[![Build Status](https://travis-ci.org/richardasaurus/python-xmlunittest-better.png?branch=master)](https://travis-ci.org/richardasaurus/python-xmlunittest-better)[![Downloads](https://pypip.in/d/xmlunittestbetter/badge.png)](https://crate.io/packages/xmlunittestbetter/)This is a spork of [https://github.com/Exirel/python-xmlunittest](https://github.com/Exirel/python-xmlunittest).With wider lxml support and Python 2.7, 3.4 & 3.4 support.Examples======- Extend xmlunittest.XmlTestCase- Write your tests, using the function or method that generate XML document- Use xmlunittest.XmlTestCase\u2018s assertion methods to validate- Keep your test readableExample:```from xmlunittest import XmlTestCaseclass CustomTestCase(XmlTestCase):def test_my_custom_test(self):# In a real case, data come from a call to your function/method.data = \"\"\"\"\"\"# Everything starts with `assert_xml_document`root = self.assert_xml_document(data)# Check namespaceself.assert_xml_namespace(root, 'ns', 'uri')# Checkself.assert_xpaths_unique_value(root, ('./leaf@id', ))self.assert_xpath_values(root, './leaf@active', ('on', 'off'))```Running the tests======To run the unit tests for this package::```pip install toxtox```"} +{"package": "xmlutil", "pacakge-description": "Programming Language :: Python\nProgramming Language :: Python :: 2\nProgramming Language :: Python :: 2.7\nProgramming Language :: Python :: 3\nProgramming Language :: Python :: 3.3\nProgramming Language :: Python :: 3.4\nProgramming Language :: Python :: 3.5\nProgramming Language :: Python :: 3.6\nProgramming Language :: Python :: 3.7\nTopic :: Software Development :: Libraries :: Python Modules\nDescription: Convenience wrappers for working with XML data\nPlatform: UNKNOWN\nClassifier: Development Status :: 3 - Alpha\nClassifier: Intended Audience :: Developers"} +{"package": "xmlutils", "pacakge-description": "No description available on PyPI."} +{"package": "xml-utils", "pacakge-description": "XML utils for the curator core project.Quick start1. Add \u201cxml_utils\u201d to your INSTALLED_APPS settingINSTALLED_APPS=[...'xml_utils',]"} +{"package": "xmlv", "pacakge-description": "No description available on PyPI."} +{"package": "xml-validators", "pacakge-description": "No description available on PyPI."} +{"package": "xmlvirshparser", "pacakge-description": "UNKNOWN"} +{"package": "xmlwalk", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmlwitch", "pacakge-description": "xmlwitch offers Pythonic XML generation through context generators in a\nminimalist implementation with less than 100 lines of code. BSD-licensed.Usageimport xmlwitch\nxml = xmlwitch.Builder(version='1.0', encoding='utf-8')\nwith xml.feed(xmlns='http://www.w3.org/2005/Atom'):\n xml.title('Example Feed')\n xml.updated('2003-12-13T18:30:02Z')\n with xml.author:\n xml.name('John Doe')\n xml.id('urn:uuid:60a76c80-d399-11d9-b93C-0003939e0af6')\n with xml.entry:\n xml.title('Atom-Powered Robots Run Amok')\n xml.id('urn:uuid:1225c695-cfb8-4ebb-aaaa-80da344efa6a')\n xml.updated('2003-12-13T18:30:02Z')\n xml.summary('Some text.')\nprint(xml)Setup$ pip install xmlwitch # or\n$ easy_install xmlwitch # or\n$ cd xmlwitch-0.3; python setup.py installLinksDevelopment repositoryAuthor\u2019s website"} +{"package": "xmlx", "pacakge-description": "XMLX - a simple and compact XML parser.XMLX = XML eXtrasTo initialize an element object from a string:>>>xmlx.Element('hello!')..If you prefer dictionaries, simply usexmlx.elemdict(text):>>>xmlx.elemdict('hello!'){'?':{},'@':'hello!','*':'hello!'}?is the element\u2019s attributes,@is its content (JS innerHTML), and*is its text (JS outerHTML).See help(xmlx) for further documentation."} +{"package": "xml-xls-loader", "pacakge-description": "Python module to load a MS xml xls into a pandas DataFrameUsagefromxml_xls_loaderimportxmlxls_to_pddat=xmlxls_to_pd(attachment,header=3,skip_footer=4)"} +{"package": "xmlxnat", "pacakge-description": "No description available on PyPI."} +{"package": "xmm", "pacakge-description": "A command-line package manager for thexonotic-map-repositoryproject.Used with the unofficial Xonotic map repository,xonotic.co, by default.The JSON provides rich metadata about map packages which makes it easier\nto discern differences between them.For information about what data is available checkJSON\nStructure. ## RequirementsDebian/UbuntuIf you do not already havepipandsetuptoolsfor Python 3:sudo apt install python3-pip python3-setuptoolsInstallationpip3 install xmm --useror for development:git clone https://github.com:z/xonotic-map-manager.git\ncd xonotic-map-manager\npython3 setup.py developUsageusage: xmm [-h] [--version] [-S [SERVER]] [-T [TARGET]] [-R [REPOSITORY]]\n {search,install,remove,discover,list,show,export,servers,repos,update,hello}\n ...\n\nXonotic Map Manager is a tool to help manage Xonotic maps\n\npositional arguments:\n {search,install,remove,discover,list,show,export,servers,repos,update,hello}\n search search for maps based on bsp names\n install install a map from the repository, or specify a URL.\n remove remove based on pk3 name\n discover discover packages in a target directory\n list list locally installed packages\n show show details of remote or locally installed packages\n export export locally managed packages to a file\n servers subcommands on servers described in servers.json\n repos subcommands on repos described in sources.json\n update update sources json\n hello hello is an example plugin\n\noptional arguments:\n -h, --help show this help message and exit\n --version show program's version number and exit\n -S [SERVER], --server [SERVER]\n target server as defined in servers.json\n -T [TARGET], --target [TARGET]\n target directory\n -R [REPOSITORY], --repository [REPOSITORY]\n repository to use (defaults to all available)DocumentationDocumentation is hosted onreadthedocs.io.ContributingContributions to this project are welcome, please readCONTRIBUTING.md.LicenseCopyright (c) 2016 Tyler Mulligan (z@xnz.me) and contributors.Distributed under the MIT license. See the LICENSE file for more\ndetails.0.8.0 / 2016-12-22AddedMulti-repo supportCreated documentation with sphinx, hosted at readthedocs.ioIntegrated tests and CI with travisarg completion forbashandzshviaargcomplete-Lflag on thexmm showsubcommand to explicitly indicate\nshowing map details from a locally installed map. Otherwise, the\nsource_collection cache is used for all information.-Rflag to specify a single repository if using many--versionflagexportcommand supports two more formats, shasums, maplist\n(bsps), or repo JSON (#7)serverscommand added with subcommandlistreposcommand added with subcommandlist--highlight,-Hflags become--colorUser-configurable LoggingChangedComplete overhaul of code base exposing a Python APINo longer using pickle, storing data inJSONConfiguration updates, seeUpgrading"} +{"package": "xmminiappcli", "pacakge-description": "xmminiappcli"} +{"package": "xmmsclient", "pacakge-description": "Xmms2 python native client. It allows you to build applications for xmms2 which is a musical player written in C."} +{"package": "xmmspy", "pacakge-description": "xmmspy is a wrapper for all but one xmms_remotefunction. (xmms_remote_playlist). It\u2019s written with boost::python,\nexposing an included C++ XMMSRemote class to Python."} +{"package": "xmm-tools", "pacakge-description": "No description available on PyPI."} +{"package": "xmnlp", "pacakge-description": "xmnlp: \u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u5f00\u6e90\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\u5305XMNLP: An out-of-the-box Chinese Natural Language Processing Toolkit\u529f\u80fd\u6982\u89c8\u4e2d\u6587\u8bcd\u6cd5\u5206\u6790 (RoBERTa + CRF finetune)\u5206\u8bcd\u8bcd\u6027\u6807\u6ce8\u547d\u540d\u4f53\u8bc6\u522b\u652f\u6301\u81ea\u5b9a\u4e49\u5b57\u5178\u4e2d\u6587\u62fc\u5199\u68c0\u67e5 (Detector + Corrector SpellCheck)\u6587\u672c\u6458\u8981 & \u5173\u952e\u8bcd\u63d0\u53d6 (Textrank)\u60c5\u611f\u5206\u6790 (RoBERTa finetune)\u6587\u672c\u8f6c\u62fc\u97f3 (Trie)\u6c49\u5b57\u504f\u65c1\u90e8\u9996 (HashMap)\u53e5\u5b50\u8868\u5f81\u53ca\u76f8\u4f3c\u5ea6\u8ba1\u7b97Outline\u4e00. \u5b89\u88c5\u6a21\u578b\u4e0b\u8f7d\u914d\u7f6e\u6a21\u578b\u4e8c. \u4f7f\u7528\u6587\u6863\u9ed8\u8ba4\u5206\u8bcd\uff1aseg\u5feb\u901f\u5206\u8bcd\uff1afast_seg\u6df1\u5ea6\u5206\u8bcd\uff1adeep_seg\u8bcd\u6027\u6807\u6ce8\uff1atag\u5feb\u901f\u8bcd\u6027\u6807\u6ce8\uff1afast_tag\u6df1\u5ea6\u8bcd\u6027\u6807\u6ce8\uff1adeep_tag\u5206\u8bcd&\u8bcd\u6027\u6807\u6ce8\u81ea\u5b9a\u4e49\u5b57\u5178\u547d\u540d\u4f53\u8bc6\u522b\uff1aner\u5173\u952e\u8bcd\u63d0\u53d6\uff1akeyword\u5173\u952e\u8bed\u53e5\u63d0\u53d6\uff1akeyphrase\u60c5\u611f\u8bc6\u522b\uff1asentiment\u62fc\u97f3\u63d0\u53d6\uff1apinyin\u90e8\u9996\u63d0\u53d6\uff1aradical\u6587\u672c\u7ea0\u9519\uff1achecker\u53e5\u5b50\u8868\u5f81\u53ca\u76f8\u4f3c\u5ea6\u8ba1\u7b97\uff1asentence_vector\u5e76\u884c\u5904\u7406\u4e09. \u66f4\u591a\u8d21\u732e\u8005\u5b66\u672f\u5f15\u7528\u9700\u6c42\u5b9a\u5236\u4ea4\u6d41\u7fa4RefrenceLicense\u4e00. \u5b89\u88c5\u5b89\u88c5\u6700\u65b0\u7248 xmnlppipinstall-Uxmnlp\u56fd\u5185\u7528\u6237\u53ef\u4ee5\u52a0\u4e00\u4e0b index-urlpipinstall-ihttps://pypi.tuna.tsinghua.edu.cn/simple-Uxmnlp\u5b89\u88c5\u5b8c\u5305\u4e4b\u540e\uff0c\u8fd8\u9700\u8981\u4e0b\u8f7d\u6a21\u578b\u6743\u91cd\u624d\u53ef\u6b63\u5e38\u4f7f\u7528\u6a21\u578b\u4e0b\u8f7d\u8bf7\u4e0b\u8f7d xmnlp \u5bf9\u5e94\u7248\u672c\u7684\u6a21\u578b\uff0c\u5982\u679c\u4e0d\u6e05\u695a xmnlp \u7684\u7248\u672c\uff0c\u53ef\u4ee5\u6267\u884cpython -c 'import xmnlp; print(xmnlp.__version__)'\u67e5\u770b\u7248\u672c\u6a21\u578b\u540d\u79f0\u9002\u7528\u7248\u672c\u4e0b\u8f7d\u5730\u5740xmnlp-onnx-models-v5.zipv0.5.0, v0.5.1, v0.5.2, v0.5.3\u98de\u4e66[IGHI] |\u767e\u5ea6\u7f51\u76d8[l9id]xmnlp-onnx-models-v4.zipv0.4.0\u98de\u4e66[DKLa] |\u767e\u5ea6\u7f51\u76d8[j1qi]xmnlp-onnx-models-v3.zipv0.3.2, v0.3.3\u98de\u4e66[o4bA] |\u767e\u5ea6\u7f51\u76d8[9g7e]\u914d\u7f6e\u6a21\u578b\u4e0b\u8f7d\u6a21\u578b\u540e\u9700\u8981\u8bbe\u7f6e\u6a21\u578b\u8def\u5f84 xmnlp \u624d\u53ef\u4ee5\u6b63\u5e38\u8fd0\u884c\u3002\u63d0\u4f9b\u4e24\u79cd\u914d\u7f6e\u65b9\u5f0f\u65b9\u5f0f 1\uff1a\u914d\u7f6e\u73af\u5883\u53d8\u91cf\uff08\u63a8\u8350\uff09\u4e0b\u8f7d\u597d\u7684\u6a21\u578b\u89e3\u538b\u540e\uff0c\u53ef\u4ee5\u8bbe\u7f6e\u73af\u5883\u53d8\u91cf\u6307\u5b9a\u6a21\u578b\u5730\u5740\u3002\u4ee5 Linux \u7cfb\u7edf\u4e3a\u4f8b\uff0c\u8bbe\u7f6e\u5982\u4e0bexportXMNLP_MODEL=/path/to/xmnlp-models\u65b9\u5f0f 2\uff1a\u901a\u8fc7\u51fd\u6570\u8bbe\u7f6e\u5728\u8c03\u7528 xmnlp \u524d\u8bbe\u7f6e\u6a21\u578b\u5730\u5740\uff0c\u5982\u4e0bimportxmnlpxmnlp.set_model('/path/to/xmnlp-models')* \u4e0a\u8ff0/path/to/\u53ea\u662f\u5360\u4f4d\u7528\u7684\uff0c\u914d\u7f6e\u65f6\u8bf7\u66ff\u6362\u6210\u6a21\u578b\u771f\u5b9e\u7684\u76ee\u5f55\u5730\u5740\u3002\u4e8c. \u4f7f\u7528\u6587\u6863xmnlp.seg(text: str) -> List[str]\u4e2d\u6587\u5206\u8bcd\uff08\u9ed8\u8ba4\uff09\uff0c\u57fa\u4e8e\u9006\u5411\u6700\u5927\u5339\u914d\u6765\u5206\u8bcd\uff0c\u91c7\u7528 RoBERTa + CRF \u6765\u8fdb\u884c\u65b0\u8bcd\u8bc6\u522b\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u5217\u8868\uff0c\u5206\u8bcd\u540e\u7684\u7ed3\u679c\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.seg(text))['xmnlp','\u662f','\u4e00\u6b3e','\u5f00\u7bb1','\u5373\u7528','\u7684','\u8f7b\u91cf\u7ea7','\u4e2d\u6587','\u81ea\u7136\u8bed\u8a00','\u5904\u7406','\u5de5\u5177','\ud83d\udd27','\u3002']xmnlp.fast_seg(text: str) -> List[str]\u57fa\u4e8e\u9006\u5411\u6700\u5927\u5339\u914d\u6765\u5206\u8bcd\uff0c\u4e0d\u5305\u542b\u65b0\u8bcd\u8bc6\u522b\uff0c\u901f\u5ea6\u8f83\u5feb\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u5217\u8868\uff0c\u5206\u8bcd\u540e\u7684\u7ed3\u679c\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.seg(text))['xmnlp','\u662f','\u4e00\u6b3e','\u5f00\u7bb1','\u5373','\u7528','\u7684','\u8f7b\u91cf\u7ea7','\u4e2d\u6587','\u81ea\u7136\u8bed\u8a00','\u5904\u7406','\u5de5\u5177','\ud83d\udd27','\u3002']xmnlp.deep_seg(text: str) -> List[str]\u57fa\u4e8e RoBERTa + CRF \u6a21\u578b\uff0c\u901f\u5ea6\u8f83\u6162\u3002\u5f53\u524d\u6df1\u5ea6\u63a5\u53e3\u53ea\u652f\u6301\u7b80\u4f53\u4e2d\u6587\uff0c\u4e0d\u652f\u6301\u7e41\u4f53\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u5217\u8868\uff0c\u5206\u8bcd\u540e\u7684\u7ed3\u679c\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.deep_seg(text))['xmnlp','\u662f','\u4e00\u6b3e','\u5f00\u7bb1','\u5373\u7528','\u7684','\u8f7b','\u91cf\u7ea7','\u4e2d\u6587','\u81ea\u7136','\u8bed\u8a00','\u5904\u7406','\u5de5\u5177','\ud83d\udd27','\u3002']xmnlp.tag(text: str) -> List[Tuple(str, str)]\u8bcd\u6027\u6807\u6ce8\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u8bcd\u548c\u8bcd\u6027\u5143\u7ec4\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.tag(text))[('xmnlp','eng'),('\u662f','v'),('\u4e00\u6b3e','m'),('\u5f00\u7bb1','n'),('\u5373\u7528','v'),('\u7684','u'),('\u8f7b\u91cf\u7ea7','b'),('\u4e2d\u6587','nz'),('\u81ea\u7136\u8bed\u8a00','l'),('\u5904\u7406','v'),('\u5de5\u5177','n'),('\ud83d\udd27','x'),('\u3002','x')]xmnlp.fast_tag(text: str) -> List[Tuple(str, str)]\u57fa\u4e8e\u9006\u5411\u6700\u5927\u5339\u914d\uff0c\u4e0d\u5305\u542b\u65b0\u8bcd\u8bc6\u522b\uff0c\u901f\u5ea6\u8f83\u5feb\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u8bcd\u548c\u8bcd\u6027\u5143\u7ec4\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.fast_tag(text))[('xmnlp','eng'),('\u662f','v'),('\u4e00\u6b3e','m'),('\u5f00\u7bb1','n'),('\u5373','v'),('\u7528','p'),('\u7684','uj'),('\u8f7b\u91cf\u7ea7','b'),('\u4e2d\u6587','nz'),('\u81ea\u7136\u8bed\u8a00','l'),('\u5904\u7406','v'),('\u5de5\u5177','n'),('\ud83d\udd27','x'),('\u3002','x')]xmnlp.deep_tag(text: str) -> List[Tuple(str, str)]\u57fa\u4e8e RoBERTa + CRF \u6a21\u578b\uff0c\u901f\u5ea6\u8f83\u6162\u3002\u5f53\u524d\u6df1\u5ea6\u63a5\u53e3\u53ea\u652f\u6301\u7b80\u4f53\u4e2d\u6587\uff0c\u4e0d\u652f\u6301\u7e41\u4f53\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u8bcd\u548c\u8bcd\u6027\u5143\u7ec4\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"xmnlp \u662f\u4e00\u6b3e\u5f00\u7bb1\u5373\u7528\u7684\u8f7b\u91cf\u7ea7\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5de5\u5177\ud83d\udd27\u3002\"\"\">>>print(xmnlp.deep_tag(text))[('xmnlp','x'),('\u662f','v'),('\u4e00\u6b3e','m'),('\u5f00\u7bb1','v'),('\u5373\u7528','v'),('\u7684','u'),('\u8f7b','nz'),('\u91cf\u7ea7','b'),('\u4e2d\u6587','nz'),('\u81ea\u7136','n'),('\u8bed\u8a00','n'),('\u5904\u7406','v'),('\u5de5\u5177','n'),('\ud83d\udd27','w'),('\u3002','w')]\u5206\u8bcd&\u8bcd\u6027\u6807\u6ce8\u81ea\u5b9a\u4e49\u5b57\u5178\u652f\u6301\u7528\u6237\u81ea\u5b9a\u4e49\u5b57\u5178\uff0c\u5b57\u5178\u683c\u5f0f\u4e3a\u8bcd1 \u8bcd\u60271\n\u8bcd2 \u8bcd\u60272\u4e5f\u517c\u5bb9 jieba \u5206\u8bcd\u7684\u5b57\u5178\u683c\u5f0f\u8bcd1 \u8bcd\u98911 \u8bcd\u60271\n\u8bcd2 \u8bcd\u98912 \u8bcd\u60272\u6ce8\uff1a\u4e0a\u8ff0\u884c\u5185\u7684\u95f4\u9694\u7b26\u4e3a\u7a7a\u683c\u4f7f\u7528\u793a\u4f8b\uff1afromxmnlp.lexical.tokenizationimportTokenization# \u5b9a\u4e49 tokenizer# detect_new_word \u5b9a\u4e49\u662f\u5426\u8bc6\u522b\u65b0\u8bcd\uff0c\u9ed8\u8ba4 True\uff0c \u8bbe\u4e3a False \u65f6\u901f\u5ea6\u4f1a\u66f4\u5febtokenizer=Tokenization(user_dict_path,detect_new_word=True)# \u5206\u8bcdtokenizer.seg(texts)# \u8bcd\u6027\u6807\u6ce8tokenizer.tag(texts)xmnlp.ner(text: str) -> List[Tuple(str, str, int, int)]\u547d\u540d\u4f53\u8bc6\u522b\uff0c\u652f\u6301\u8bc6\u522b\u7684\u5b9e\u4f53\u7c7b\u578b\u4e3a\uff1aTIME\uff1a\u65f6\u95f4LOCATION\uff1a\u5730\u70b9PERSON\uff1a\u4eba\u7269JOB\uff1a\u804c\u4e1aORGANIZAIRION\uff1a\u673a\u6784\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u5b9e\u4f53\u3001\u5b9e\u4f53\u7c7b\u578b\u3001\u5b9e\u4f53\u8d77\u59cb\u4f4d\u7f6e\u548c\u5b9e\u4f53\u7ed3\u5c3e\u4f4d\u7f6e\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\u73b0\u4efb\u7f8e\u56fd\u603b\u7edf\u662f\u62dc\u767b\u3002\">>>print(xmnlp.ner(text))[('\u7f8e\u56fd','LOCATION',2,4),('\u603b\u7edf','JOB',4,6),('\u62dc\u767b','PERSON',7,9)]xmnlp.keyword(text: str, k: int = 10, stopword: bool = True, allowPOS: Optional[List[str]] = None) -> List[Tuple[str, float]]\u4ece\u6587\u672c\u4e2d\u63d0\u53d6\u5173\u952e\u8bcd\uff0c\u57fa\u4e8e Textrank \u7b97\u6cd5\u3002\u53c2\u6570\uff1atext\uff1a\u6587\u672c\u8f93\u5165k\uff1a\u8fd4\u56de\u5173\u952e\u8bcd\u7684\u4e2a\u6570stopword\uff1a\u662f\u5426\u53bb\u9664\u505c\u7528\u8bcdallowPOS\uff1a\u914d\u7f6e\u5141\u8bb8\u7684\u8bcd\u6027\u7ed3\u679c\u8fd4\u56de\uff1a\u7531\u5173\u952e\u8bcd\u548c\u6743\u91cd\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"\u81ea\u7136\u8bed\u8a00\u5904\u7406: \u662f\u4eba\u5de5\u667a\u80fd\u548c\u8bed\u8a00\u5b66\u9886\u57df\u7684\u5206\u652f\u5b66\u79d1\u3002...: \u5728\u8fd9\u6b64\u9886\u57df\u4e2d\u63a2\u8ba8\u5982\u4f55\u5904\u7406\u53ca\u8fd0\u7528\u81ea\u7136\u8bed\u8a00\uff1b\u81ea\u7136\u8bed\u8a00\u8ba4\u77e5\u5219\u662f\u6307\u8ba9\u7535\u8111\u201c\u61c2\u201d\u4eba\u7c7b\u7684...: \u8bed\u8a00\u3002...: \u81ea\u7136\u8bed\u8a00\u751f\u6210\u7cfb\u7edf\u628a\u8ba1\u7b97\u673a\u6570\u636e\u8f6c\u5316\u4e3a\u81ea\u7136\u8bed\u8a00\u3002\u81ea\u7136\u8bed\u8a00\u7406\u89e3\u7cfb\u7edf\u628a\u81ea\u7136\u8bed\u8a00\u8f6c\u5316...: \u4e3a\u8ba1\u7b97\u673a\u7a0b\u5e8f\u66f4\u6613\u4e8e\u5904\u7406\u7684\u5f62\u5f0f\u3002\"\"\">>>print(xmnlp.keyword(text))[('\u81ea\u7136\u8bed\u8a00',2.3000579596585897),('\u8bed\u8a00',1.4734141257937314),('\u8ba1\u7b97\u673a',1.3747500999598312),('\u8f6c\u5316',1.2687686226652466),('\u7cfb\u7edf',1.1171384775870152),('\u9886\u57df',1.0970728069617324),('\u4eba\u7c7b',1.0192131829490039),('\u751f\u6210',1.0075197087342542),('\u8ba4\u77e5',0.9327188339671753),('\u6307',0.9218423928455112)]xmnlp.keyphrase(text: str, k: int = 10, stopword: bool = False) -> List[str]\u4ece\u6587\u672c\u4e2d\u63d0\u53d6\u5173\u952e\u53e5\uff0c\u57fa\u4e8e Textrank \u7b97\u6cd5\u3002\u53c2\u6570\uff1atext\uff1a\u6587\u672c\u8f93\u5165k\uff1a\u8fd4\u56de\u5173\u952e\u8bcd\u7684\u4e2a\u6570stopword\uff1a\u662f\u5426\u53bb\u9664\u505c\u7528\u8bcd\u7ed3\u679c\u8fd4\u56de\uff1a\u7531\u5173\u952e\u8bcd\u548c\u6743\u91cd\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\"\"\u81ea\u7136\u8bed\u8a00\u5904\u7406: \u662f\u4eba\u5de5\u667a\u80fd\u548c\u8bed\u8a00\u5b66\u9886\u57df\u7684\u5206\u652f\u5b66\u79d1\u3002...: \u5728\u8fd9\u6b64\u9886\u57df\u4e2d\u63a2\u8ba8\u5982\u4f55\u5904\u7406\u53ca\u8fd0\u7528\u81ea\u7136\u8bed\u8a00\uff1b\u81ea\u7136\u8bed\u8a00\u8ba4\u77e5\u5219\u662f\u6307\u8ba9\u7535\u8111\u201c\u61c2\u201d\u4eba\u7c7b\u7684...: \u8bed\u8a00\u3002...: \u81ea\u7136\u8bed\u8a00\u751f\u6210\u7cfb\u7edf\u628a\u8ba1\u7b97\u673a\u6570\u636e\u8f6c\u5316\u4e3a\u81ea\u7136\u8bed\u8a00\u3002\u81ea\u7136\u8bed\u8a00\u7406\u89e3\u7cfb\u7edf\u628a\u81ea\u7136\u8bed\u8a00\u8f6c\u5316...: \u4e3a\u8ba1\u7b97\u673a\u7a0b\u5e8f\u66f4\u6613\u4e8e\u5904\u7406\u7684\u5f62\u5f0f\u3002\"\"\">>>print(xmnlp.keyphrase(text,k=2))['\u81ea\u7136\u8bed\u8a00\u7406\u89e3\u7cfb\u7edf\u628a\u81ea\u7136\u8bed\u8a00\u8f6c\u5316\u4e3a\u8ba1\u7b97\u673a\u7a0b\u5e8f\u66f4\u6613\u4e8e\u5904\u7406\u7684\u5f62\u5f0f','\u81ea\u7136\u8bed\u8a00\u751f\u6210\u7cfb\u7edf\u628a\u8ba1\u7b97\u673a\u6570\u636e\u8f6c\u5316\u4e3a\u81ea\u7136\u8bed\u8a00']xmnlp.sentiment(text: str) -> Tuple[float, float]\u60c5\u611f\u8bc6\u522b\uff0c\u57fa\u4e8e\u7535\u5546\u8bc4\u8bba\u8bed\u6599\u8bad\u7ec3\uff0c\u9002\u7528\u4e8e\u7535\u5546\u573a\u666f\u4e0b\u7684\u60c5\u611f\u8bc6\u522b\u3002\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u5143\u7ec4\uff0c\u683c\u5f0f\u4e3a\uff1a[\u8d1f\u5411\u60c5\u611f\u6982\u7387\uff0c\u6b63\u5411\u60c5\u611f\u6982\u7387]\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\u8fd9\u672c\u4e66\u771f\u4e0d\u9519\uff0c\u4e0b\u6b21\u8fd8\u8981\u4e70\">>>print(xmnlp.sentiment(text))(0.02727833203971386,0.9727216958999634)xmnlp.pinyin(text: str) -> List[str]\u6587\u672c\u8f6c\u62fc\u97f3\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u62fc\u97f3\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\u81ea\u7136\u8bed\u8a00\u5904\u7406\">>>print(xmnlp.pinyin(text))['Zi','ran','yu','yan','chu','li']xmnlp.radical(text: str) -> List[str]\u63d0\u53d6\u6587\u672c\u90e8\u9996\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672c\u7ed3\u679c\u8fd4\u56de\uff1a\u90e8\u9996\u7ec4\u6210\u7684\u5217\u8868\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\u81ea\u7136\u8bed\u8a00\u5904\u7406\">>>print(xmnlp.radical(text))['\u81ea','\u706c','\u8ba0','\u8a00','\u5902','\u738b']xmnlp.checker(text: str, suggest: bool = True, k: int = 5, max_k: int = 200) -> Union[ List[Tuple[int, str]], Dict[Tuple[int, str], List[Tuple[str, float]]]]:\u6587\u672c\u7ea0\u9519\u53c2\u6570\uff1atext\uff1a\u8f93\u5165\u6587\u672csuggest\uff1a\u662f\u5426\u8fd4\u56de\u5efa\u8bae\u8bcdk\uff1a\u8fd4\u56de\u5efa\u8bae\u8bcd\u7684\u4e2a\u6570max_k\uff1a\u62fc\u97f3\u641c\u7d22\u6700\u5927\u6b21\u6570\uff08\u5efa\u8bae\u4fdd\u6301\u9ed8\u8ba4\u503c\uff09\u7ed3\u679c\u8fd4\u56de\uff1asuggest \u4e3a False \u65f6\u8fd4\u56de (\u9519\u8bcd\u4e0b\u6807\uff0c\u9519\u8bcd) \u5217\u8868\uff1bsuggest \u4e3a True \u65f6\u8fd4\u56de\u5b57\u5178\uff0c\u5b57\u5178\u952e\u4e3a(\u9519\u8bcd\u4e0b\u6807\uff0c\u9519\u8bcd) \u5217\u8868\uff0c\u503c\u4e3a\u5efa\u8bae\u8bcd\u4ee5\u53ca\u6743\u91cd\u5217\u8868\u3002\u793a\u4f8b\uff1a>>>importxmnlp>>>text=\"\u4e0d\u80fd\u9002\u5e94\u4f53\u80b2\u4e13\u4e1a\u9009\u62d4\u4eba\u6750\u7684\u8981\u6c42\">>>print(xmnlp.checker(text)){(11,'\u6750'):[('\u624d',1.58528071641922),('\u6750',1.0009655653266236),('\u88c1',1.0000178480604518),('\u5458',0.35814568400382996),('\u58eb',0.011077565141022205)]}xmnlp.sv.SentenceVector(model_dir: Optional[str] = None, genre: str = '\u901a\u7528', max_length: int = 512)SentenceVector \u521d\u59cb\u5316\u51fd\u6570model_dir: \u6a21\u578b\u4fdd\u5b58\u5730\u5740\uff0c\u9ed8\u8ba4\u52a0\u8f7d xmnlp \u63d0\u4f9b\u7684\u6a21\u578b\u6743\u91cdgenre: \u5185\u5bb9\u7c7b\u578b\uff0c\u76ee\u524d\u652f\u6301 ['\u901a\u7528', '\u91d1\u878d', '\u56fd\u9645'] \u4e09\u79cdmax_length: \u8f93\u5165\u6587\u672c\u7684\u6700\u5927\u957f\u5ea6\uff0c\u9ed8\u8ba4 512\u4ee5\u4e0b\u662f SentenceVector \u7684\u4e09\u4e2a\u6210\u5458\u51fd\u6570xmnlp.sv.SentenceVector.transform(self, text: str) -> np.ndarrayxmnlp.sv.SentenceVector.similarity(self, x: Union[str, np.ndarray], y: Union[str, np.ndarray]) -> floatxmnlp.sv.SentenceVector.most_similar(self, query: str, docs: List[str], k: int = 1, **kwargs) -> List[Tuple[str, float]]query: \u67e5\u8be2\u5185\u5bb9docs: \u6587\u6863\u5217\u8868k: \u8fd4\u56de topk \u76f8\u4f3c\u6587\u672ckwargs: KDTree \u7684\u53c2\u6570\uff0c\u8be6\u89c1sklearn.neighbors.KDTree\u4f7f\u7528\u793a\u4f8bimportnumpyasnpfromxmnlp.svimportSentenceVectorquery='\u6211\u60f3\u4e70\u624b\u673a'docs=['\u6211\u60f3\u4e70\u82f9\u679c\u624b\u673a','\u6211\u559c\u6b22\u5403\u82f9\u679c']sv=SentenceVector(genre='\u901a\u7528')fordocindocs:print('doc:',doc)print('similarity:',sv.similarity(query,doc))print('most similar doc:',sv.most_similar(query,docs))print('query representation shape:',sv.transform(query).shape)\u8f93\u51fadoc: \u6211\u60f3\u4e70\u82f9\u679c\u624b\u673a\nsimilarity: 0.68668646\ndoc: \u6211\u559c\u6b22\u5403\u82f9\u679c\nsimilarity: 0.3020076\nmost similar doc: [('\u6211\u60f3\u4e70\u82f9\u679c\u624b\u673a', 16.255546509314417)]\nquery representation shape: (312,)\u5e76\u884c\u5904\u7406\u65b0\u7248\u672c\u4e0d\u518d\u63d0\u4f9b\u5bf9\u5e94\u7684\u5e76\u884c\u5904\u7406\u63a5\u53e3\uff0c\u9700\u8981\u4f7f\u7528xmnlp.utils.parallel_handler\u6765\u5b9a\u4e49\u5e76\u884c\u5904\u7406\u63a5\u53e3\u3002\u63a5\u53e3\u5982\u4e0b\uff1axmnlp.utils.parallel_handler(callback:Callable,texts:List[str],n_jobs:int=2,**kwargs)->Generator[List[Any],None,None]\u4f7f\u7528\u793a\u4f8b\uff1afromfunctoolsimportpartialimportxmnlpfromxmnlp.utilsimportparallel_handlerseg_parallel=partial(parallel_handler,xmnlp.seg)print(seg_parallel(texts))\u4e09. \u66f4\u591a\u5173\u4e8e\u8d21\u732e\u8005\u671f\u5f85\u66f4\u591a\u5c0f\u4f19\u4f34\u7684 contributions\uff0c\u4e00\u8d77\u6253\u9020\u4e00\u6b3e\u7b80\u5355\u6613\u7528\u7684\u4e2d\u6587 NLP \u5de5\u5177\u5b66\u672f\u5f15\u7528 Citation@misc{xmnlp,title={XMNLP:ALightweightChineseNaturalLanguageProcessingToolkit},author={XianmingLi},year={2018},publisher={GitHub},howpublished={\\url{https://github.com/SeanLee97/xmnlp}},}\u9700\u6c42\u5b9a\u5236\u672c\u4eba\u81f4\u529b\u4e8e NLP \u7814\u7a76\u548c\u843d\u5730\uff0c\u65b9\u5411\u5305\u62ec\uff1a\u4fe1\u606f\u62bd\u53d6\uff0c\u60c5\u611f\u5206\u7c7b\u7b49\u3002\u5176\u4ed6 NLP \u843d\u5730\u9700\u6c42\u53ef\u4ee5\u8054\u7cfbxmlee97@gmail.com\uff08\u6b64\u4e3a\u6709\u507f\u670d\u52a1\uff0cxmnlp \u76f8\u5173\u7684 bug \u76f4\u63a5\u63d0 issue\uff09\u4ea4\u6d41\u7fa4\u641c\u7d22\u516c\u4f17\u53f7xmnlp-ai\u5173\u6ce8\uff0c\u83dc\u5355\u9009\u62e9 \u201c\u4ea4\u6d41\u7fa4\u201d \u5165\u7fa4\u3002Reference\u672c\u9879\u76ee\u91c7\u7528\u7684\u6570\u636e\u4e3b\u8981\u6709\uff1a\u8bcd\u6cd5\u5206\u6790\uff0c\u6587\u672c\u7ea0\u9519\uff1a\u4eba\u6c11\u65e5\u62a5\u8bed\u6599\u60c5\u611f\u8bc6\u522b\uff1aChineseNlpCorpusLicenseApache 2.0\u5927\u90e8\u5206\u6a21\u578b\u57fa\u4e8eLangML\u642d\u5efa"} +{"package": "xmo", "pacakge-description": "\ud83d\udce6 setup.py (for humans)This repo exists to providean example setup.pyfile, that can be used\nto bootstrap your next Python project. It includes some advanced\npatterns and best practices forsetup.py, as well as some\ncommented\u2013out nice\u2013to\u2013haves.For example, thissetup.pyprovides a$ python setup.py uploadcommand, which creates auniversal wheel(andsdist) and uploads\nyour package toPyPiusingTwine, without the need for an annoyingsetup.cfgfile. It also creates/uploads a new git tag, automatically.In short,setup.pyfiles can be daunting to approach, when first\nstarting out \u2014 even Guido has been heard saying, \"everyone cargo cults\nthems\". It's true \u2014 so, I want this repo to be the best place to\ncopy\u2013paste from :)Check out the example!Installationcdyour_project# Download the setup.py file:# download with wgetwgethttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py-Osetup.py# download with curlcurl-Ohttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.pyTo DoTests via$ setup.py test(if it's concise).Pull requests are encouraged!More ResourcesWhat is setup.py?on Stack OverflowOfficial Python Packaging User GuideThe Hitchhiker's Guide to PackagingCookiecutter template for a Python packageLicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or\ndistribute this software, either in source code form or as a compiled\nbinary, for any purpose, commercial or non-commercial, and by any means."} +{"package": "xmoai", "pacakge-description": "xMOAI \ud83d\uddff: Multiobjective Optimization in Explainable Artificial IntelligencexMOAI is an open-source package implementing Explainable Artificial Intelligence (XAI) using Multiobjective Optimization (MOO). It is capable of generating\na large number of counterfactuals in datasets with several attributes - most of them immutable or very constrained. It supports both regression or classification\nproblems. For classification problems, it does support both problems with trained machine learning models exposing the predicted class probabilities or only\nthe predicted class. It was tested throughly with trained models in scikit-learn, XGBoost, LightGBM and Tensorflow. In practice, it works with any model that exposes\nan output similar to scikit-learn or Tensorflowpredictmethods.Usageimportnumpyasnpfromxmoai.setup.configureimportgenerate_counterfactuals_classification_probafromsklearn.ensembleimportRandomForestClassifierfromsklearn.datasetsimportload_irisfromsklearn.model_selectionimporttrain_test_split# seedrandom_state=0# getting a datasetX,y=load_iris(return_X_y=True)X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=random_state)# training a machine learning modelclf=RandomForestClassifier(max_depth=2,random_state=random_state)clf.fit(X_train,y_train)# getting an individual (X_original), its original prediction (y_original) and# the desired output (y_desired)index=0X_original=X_test[0,:].reshape(1,-1)y_original=clf.predict(X_original)y_original_proba=clf.predict_proba(X_original)y_desired=1print(f'The original prediction was{y_original}with probabilities{y_original_proba}')print(f'We will attempt to generate counterfactuals where the outcome is{y_desired}.')# generating counterfactualsimmutable_column_indexes=[2]# let's say we can't change the last columncategorical_columns={}# there are no categorical columnsinteger_columns=[]# there are no columns that only accept integer valuesy_acceptable_range=[0.5,1.0]# we will only accept counterfactuals with the predicted prob. in this rangeupper_bounds=np.array(X_train.max(axis=0)*0.8)# this is the maximum allowed number per columnlower_bounds=np.array(X_train.min(axis=0)*0.8)# this is the minimum allowed number per column.# you may change the bounds depending on the needs specific to the individual being trained.# running the counterfactual generation algorithmfront,X_generated,algorithms=generate_counterfactuals_classification_proba(clf,X_original,y_desired,immutable_column_indexes,y_acceptable_range,upper_bounds,lower_bounds,categorical_columns,integer_columns,n_gen=20,pop_size=30,max_changed_vars=3,verbose=False,seed=random_state)FeaturesThe documentation as well as the code are part of an ongoing research. Currently, it does support:Regression problemsClassification problems (probability or single class as outputs)On the variables, it does support:Decimal and integer variables as values (such as counts, quantities, etc.)Ordinally encoded categorical variables (categories encoded as integers)Setting the upper and lower bounds per variableSetting which columns are immutableSetting which categories are bound to be modified (xMOAI is able to understand only the categories 1, 5, 7 and 15 are allowed categories instead of treating it as a numerical range)Setting the target desired (for regression problems, you can inform the value you want to have as an output; for classification problems, the desired class)Setting the \"allowed output range\" (for regression problems, you can inform what values are acceptable as outputs instead of a single value. As an example, for a housing prices dataset you may want to find a counterfactual with an output of $100000.00. However, anything between $99000.00 and $105000.00 could also be good prices for your problem. For a classification problem, it is the percentage of certainity of the predicted class considering your problem).It does not support at the present moment:One-hot encoded categoriesModels available in hosted servers (i.e. with a REST API endpoint)Multiple allowed intervals for a single attribute (e.g. for a single column, instead of a range of -10 to +20, two ranges of -10 to 0 and +10 to +20).ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.PaperPreprint available inhttps://doi.org/10.13140/RG.2.2.30680.52480LicenseMIT"} +{"package": "xmobar-wttr", "pacakge-description": "xmobar_wttris a command-line program which fetches weather info\nfromwttr.inand applies direct formatting to be used by xmobar.\nDifferent from already available plugins, it can easily be configured\nto use any kind of combination of numbers, icons, and colors. It\nimplements a custom syntax with which a single line in thexmobar_wttr.ymlconfiguration file translates to an xmobar field entry.In thecommandslist of yourxmobarrc, add something along the lines\nofRun Com \"xmobar_wttr\" [\"-c\", \"~/.config/xmobar/xmobar_wttr.yml\"] \"wttr\" 9000PrerequisitesThis program mainly uses following python3 modulesrequestspyyamlFurthermore, the program uses weather icons fromhttps://github.com/erikflowers/weather-icons. Install them\ndirectly from the website, using an AUR helper such asyay -S ttf-weather-iconsor by other means.Installpip install xmobar-wttrFor installing from source, clone the repository, and runcd xmobar_wttr\npython setup.py install --useror create a virtual environment withpipenv install\npipenv install -e .To activate the virtual environment runpipenv shellor start every command withpipenv run.Usageusage: xmobar_wttr [-h] [-c ] [-l ] [-f ] [-o ] [-s
            ] [-p [ ...]] [-v]\n\noptional arguments:\n -h, --help show this help message and exit\n -c , --config \n\t\t\tPath to the config file\n -l , --location \n\t\t\tLocation for which to pull information.\n -f , --format \n\t\t\tFormat template for xmobarrc\n -o , --output \n\t\t\tPath to the output file\n -s
            , --section
            \n\t\t\tSection in the yaml file to be parsed\n -p [ ...], --pars [ ...]\n\t\t\tSelect parameters to be fetched from wttr.in\n\t\t\texcluded parameters are not available in xmobar template format\n -v, --verbose Run program in verbose modeConfigurationxmobar_wttrworks with both command-line arguments as well as YAML\nconfiguration files (the first takes precedence over the latter). To\nset your desired defaults edit the configuration filexmobar_wttr.ymland place it in either~/.config/xmobar_wttr/xmobar_wttr.yml~/.config/xmobar/xmobar_wttr.yml~/.xmobar_wttr/xmobar_wttr.yml~/.xmobar_wttr.ymlNotationFields are separated by%.Each field should have a parameter entry prefixed by an exclamation\nmark!, e.g.!h.Units can be placed using.uFonts can be selected usingwhereNis the xmobar font\nindex, e.g.<2:weather condition>formats toweather conditionAnalogously colors can be used using{#dedede:...}.Notation*Description%[!par]parameter value%g[!par]render parameter only as icon%G[!par]prefix icon to parameter value.uappend units of previous parameterFormat mapResult<2:\u2026>\u2026{#dedede:\u2026}\u2026\\\u2026\\x\u2026Example:'%g!x %!t(%!f)<1:\u200a>.u {#46d9ff:%G}<1:\u200a>!h'could format to something like\uf00c 3(1)\u200a\u00b0C \uf07a\u200a81and renders in xmobar as"} +{"package": "xmod", "pacakge-description": "\ud83c\udf31 Turn any object into a module \ud83c\udf31Callable modules! Indexable modules!?Ever wanted to call a module directly, or index it? Or just sick of seeingfrom foo import fooin your examples?Give your module the awesome power of an object, or maybe just save a\nlittle typing, withxmod.xmodis a tiny library that lets a module to do things that normally\nonly a class could do - handy for modules that \"just do one thing\".Example: Make a module callable like a function!# In your_module.py\nimport xmod\n\n@xmod\ndef a_function():\n return 'HERE!!'\n\n\n# Test at the command line\n>>> import your_module\n>>> your_module()\nHERE!!Example: Make a module look like a list!?!# In your_module.py\nimport xmod\n\nxmod(list(), __name__)\n\n# Test at the command line\n>>> import your_module\n>>> assert your_module == []\n>>> your_module.extend(range(3))\n>>> print(your_module)\n[0, 1, 2]API Documentation"} +{"package": "xmodal", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmode", "pacakge-description": "No description available on PyPI."} +{"package": "xmodel", "pacakge-description": "Json Modeling LibraryProvides easy way to map dict to/from Full-Fledged 'JsonModel' object.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiGetting Started???+ warning \"Alpha Software!\"\nThis is pre-release Alpha software, based on another code base and\nthe needed changes to make a final release version are not yet\ncompleted. Everything is subject to change!poetryinstallxmodelorpipinstallxmodelVery basic example:fromxmodelimportJsonModelclassMyModel(JsonModel):some_attr:strjson_dict_input={'some_attr':'a-value'}obj=MyModel(json_dict_input)assertobj.some_attr=='a-value'json_dict=obj.api.json()assertjson_dict==json_dict_input"} +{"package": "xmodel-rest", "pacakge-description": "Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiGetting Startedwarning \"Alpha Software!\"This is pre-release Alpha software, based on another code base and\nthe needed changes to make a final release version are not yet\ncompleted. Everything is subject to change; and documentation needs\nto be written.poetryinstallxmodel-restorpipinstallxmodel-rest"} +{"package": "xmodels", "pacakge-description": "=======xmodels=======.. image:: https://secure.travis-ci.org/berndca/xmodels.png?branch=master:target: https://secure.travis-ci.org/berndca/xmodels:alt: Build Status.. image:: https://coveralls.io/repos/berndca/xmodels/badge.png:target: https://coveralls.io/r/berndca/xmodels:alt: Coverage**For more information, please see our documentation:** http://xmodels.readthedocs.org/en/latest/Overview========xmodels is a Python library to convert XML documents and Python dictionariesincluding collections.OrderedDict to and from instances of Python datastructures and validate them against a schema.The conversions between XML and Python dict/collections.OrderedDict areperformed by `xmltodict `_.It supports XML specific schema features like ordered sets of element type****, selection from a set of element type**** and namespaces.=======History=======0.1.0 (2014-11-02)==================* First release on PyPI."} +{"package": "xmodem", "pacakge-description": "XMODEM protocol implementationDocumentation available athttp://packages.python.org/xmodem/Python Package Index (PyPI) page is available athttps://pypi.python.org/pypi/xmodemUsageCreate a function to get and put character data (to a serial line for\nexample):>>> import serial\n>>> from xmodem import XMODEM\n>>> ser = serial.Serial('/dev/ttyUSB0', timeout=0) # or whatever port you need\n>>> def getc(size, timeout=1):\n... return ser.read(size) or None\n...\n>>> def putc(data, timeout=1):\n... return ser.write(data) # note that this ignores the timeout\n...\n>>> modem = XMODEM(getc, putc)Now, to upload a file, use thesendmethod:>>> stream = open('/etc/fstab', 'rb')\n>>> modem.send(stream)To download a file, use therecvmethod:>>> stream = open('output', 'wb')\n>>> modem.recv(stream)For more information, take a look at thedocumentation.Changes0.4.7:bugfix: stall on some kinds of error inrecv(),PR #56.bugfix: sequence number miscalculation insend(),PR #52.enhancement: callback function added forrecv(),PR #53.bugfix: receiving empty file and stall condition inrecv(),PR #50.bugfix: callback is now called for some kinds of errors\nand some CLI fixes,8a798e8b.bugfix: remove DepreactionWarning forlogging.warn(),PR #49.0.4.6:bugfix: Abort send on EOT in startup-sequenceIssue #34.enhancement: Include LICENSE file in the source distribution.0.4.5:bugfix: Remove bogusassert Falsecode inrecv()that resulted inAssertionErrorintroduced in version 0.4.0 commit-id9b03fc20,PR #29.0.4.4:bugfix: Large file transfers insend()were more likely to fail for\nsmall values ofretry: This value should be the maximum failures per\nblock transfer as documented, but was improperly implemented as the number\nof failures allowed for the total duration of the transfer,PR #21.bugfix:send(retry=n)andrecv(retry=n)should retryntimes\nas documented, was retryingn - 1.0.4.3:bugfix:putc()callback was called in series, 3 times for each part of\nxmodem block header, data, and checksum during block transfer. Now all\nthree data blocks are sent by singleputc()call. This resolves issues\nwhen integrating with microcontrollers or equipment sensitive to timing\nissues at stream boundaries,PR #19.0.4.2:bugfix: documentation files missing from the release tarballIssue #16.0.4.1bugfix: re-transmit insend()onNAKor timeout, previously\nre-transmissions (wrongly) occurred only on garbage bytes.PR #12.0.4.0enhancement: support for python 3PR #8.bugfix: CRC failures in XMODEM.recv() were not renegotiated correctlyPR #11."} +{"package": "xmodits-py", "pacakge-description": "XMODITS python librarySupported formats:Impulse Tracker .ITExtended Module .XMScream Tracker .S3MAmiga Pro Tracker .MODOpen ModPlug Tracker .MPTM (Identical to Impulse Tracker sample-wise)Unreal Music Container .UMX (Containing the above formats)How to useimportxmoditsfile=\"~/Downloads/music.xm\"folder=\"~/Music/samples/\"# Rip samples to folderxmodits.dump(file,folder)Required ArgumentsArgumentMeaningPathPath to a tracker moduleDestinationDestination folder for ripped samplesAdditional ArgumentsArgumentDefinitionwith_folderCreate a new folder for ripped samples.e.g.When set toTrue,\"drums.it\"will create\"drums_it\"in the destination folder and place those samples there.index_paddingSet padding.e.g.\"01 - kick.wav\"-->\"1 - kick.wav\"index_onlyOnly name samples with a number.e.g.\"09 - HiHat.wav\"-->\"09.wav\"index_rawPreserves the internal sample indexingupperName samples in upper caselowerName samples in lower casestrictEnabled by default.Will reject files that don't match the following file extensions:[it, xm, s3m, mod, umx, mptm]ExceptionsThey are pretty much self explanitory.ExceptionMeaningSampleExtractionA sample could not be extractedPartialExtractionNot all of the samples could be extractedTotalExtractionNone of the samples could be extractedUnsupportedFormatA module format was recognized, but its type is not supportedInvalidModuleThe file is not a valid tracker moduleEmptyModuleThe tracker module is valid but it has no samplesUnrecognizedFileExtensionThe file extension was not recognizedNoFormatFoundCould not determine a valid formatAdditional ExamplesDump samples without namesimportxmoditstracker=\"mods/music.xm\"folder=\"samples/\"xmodits.dump(tracker,folder,index_only=True)This produces the following output in folder\"samples\":01.wav\n02.wav\n03.wav\n04.wav\n...\n15 - vocal.wavDump samples without padding the index:importxmoditstracker=\"mods/music.xm\"folder=\"samples/\"xmodits.dump(tracker,folder,index_padding=0# or 1, both have the same effect)Output:1 - hihat.wav\n2 - kick.wav\n3 - snare.wav\n4 - toms.wav\n...\n15 - vocal.wavSamples stored in tracker modules can have an arbitary index. If you prefer to use this index, include the parameter:index_raw=TrueIf you're dumping from multiple modules to the same folder, you're guaranteed to have collisions.You should include the parameter:with_folder=Truedevelopment:https://docs.python.org/3/library/venv.htmlCreate a python virtual environment in this directory:python -m venv devactivate virtual environment:source ./dev/bin/activateinstallmaturin (crates.io)or frompipirun test library:maturin developLicenseThe xmodits python library is licensed under the LGPLv3"} +{"package": "xmodmap-toggle", "pacakge-description": "No description available on PyPI."} +{"package": "xmonitor", "pacakge-description": "xmonitor"} +{"package": "xmos-ai-tools", "pacakge-description": "DocumentationClickherefor documentation on using xmos-ai-tools to deploy AI models on xcore."} +{"package": "xmos-ai-tools-beta", "pacakge-description": "XMOS AI ToolsUsageUsing xformerfromxmos_ai_toolsimportxformerasxfxf.convert(\"source model path\",\"converted model path\",params=None)whereparamsis a dictionary of compiler flags and paramters and their values.For example:fromxmos_ai_toolsimportxformerasxfxf.convert(\"example_int8_model.tflite\",\"xcore_optimised_example_int8_model.tflite\",{\"mlir-disable-threading\":None,\"xcore-reduce-memory\":None,})To see all available parameters, callfromxmos_ai_toolsimportxformerasxfxf.print_help()This will print all options available to pass to xformer. To see hidden options, runprint_help(show_hidden=True)Using the xcore tflm host interpreterfrom xmos_ai_tools import xcore_tflm_host_interpreter as xtflm\n\nie = xtflm.XTFLMInterpreter(model_content=xformed_model)\nie.set_input_tensor(0, input_tensor)\nie.invoke()\nxformer_outputs = []\nfor i in range(num_of_outputs):\n xformer_outputs.append(ie.get_output_tensor(i))"} +{"package": "xmovie", "pacakge-description": "No description available on PyPI."} +{"package": "xmp", "pacakge-description": "No description available on PyPI."} +{"package": "xmp2jsonforybigta", "pacakge-description": "No description available on PyPI."} +{"package": "xmpdf", "pacakge-description": "xmpdfExtracts email metadata and text body from a PDF containing emails.Installationpip install xmpdfUsagefrom xmpdf import Xmpdf\n\nems = Xmpdf(pdf_file)\n# print summary info about emails in PDF file\nprint(ems.info())\n# process emails\nfor m in ems.emails:\n process(m)OS DependenciesIf you encounter errors installing xmpdf, please check the OS-level\ndependencies of thepdftotextpackage to ensure you have the required libraries installed, as xmpdf utilizes\nthis package.NotesAssumes an email ends when a new email beginsWorks best with a standard email header (i.e., From:, To:, Sent:, Subject:)The initial development of this package was funded in part by The Mellon Foundation\u2019s \u201cEmail Archives: Building Capacity and Community\u201d program."} +{"package": "xm.portlets", "pacakge-description": "This module provide the portlet used in Plone witheXtremeManagement"} +{"package": "xmpp2", "pacakge-description": "An XMPP client"} +{"package": "xmpp-backends", "pacakge-description": "A small python library providing a common interface for communicating with\nthe administration interfaces of various Jabber/XMPP servers."} +{"package": "xmppcat", "pacakge-description": "A unix command line program that works likecatbut sends its output through XMPP.Helpusage: xmppcat [-h] [-V] [-c CONFIG] [-H HOST] [-P PORT] [-u USER] [-p PWD]\n [-q] [-d] [-v]\n recipient [file]\n\nCLI application that works like cat but sends its output through xmpp\n\npositional arguments:\nrecipient The XMPP jid to send the message to\nfile The file to read. If not specified it will be read\n from STDIN\n\noptional arguments:\n-h, --help show this help message and exit\n-V, --version show program's version number and exit\n-c CONFIG, --config CONFIG\n Use a different configuration file\n-H HOST, --host HOST XMPP host (xmppcat will try to auto detect it with DNS\n or JID parsing)\n-P PORT, --port PORT XMPP port\n-u USER, --user USER XMPP username (JID)\n-p PWD, --pass PWD XMPP password\n\noutput arguments:\n-q, --quiet Suppress any non-error output\n-d, --debug Enable debugging output\n-v, --verbose Show additional connection informationsConfiguration fileThe program requires several arguments to be specified in order to be able to connect and authenticate to a XMPP server.\nTo simplify this process you can save this options in a configuration file, either globally in/etc/xmppcat.confor locally in$HOME/.xmppcat.conf.This is an example of a configuration file for xmppcat:[DEFAULT]\nuser = myuser@jabber.org/xmppcat\npass = mypassword\nhost = jabber.org # can be autodetected by dnspython\nport = 5222 # also autodetectableExample usageecho \"Hello world!\" | xmppcat recipient@jabber.org\nxmppcat recipient@jabber.org file.txtLICENSECopyright (c) 2012 Massimiliano Torromeoxmppcat is free software released under the terms of the BSD license.See the LICENSE file provided with the source distribution for full details.ContactsMassimiliano Torromeo "} +{"package": "xmpp-client", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xmppgcm", "pacakge-description": "Version 0.2.3OtherCode simplification.Version 0.2.2ImprovementsUnit tests implemented.Some sentences changed to be compatible with Python 3.OtherAdded standard requirements.txt."} +{"package": "xmpp-http-upload", "pacakge-description": "This provides a Flask-based HTTP service which can be used withmod_http_upload_external.ConfigurationThe configuration file is specified using the environment variableXMPP_HTTP_UPLOAD_CONFIG. It must contain the full path to the configuration\nfile.The configuration file must contain the following keys:SECRET_KEYAbytesobject which is the shared secret between the Prosody module\nand this service. See themod_http_upload_external documentationfor details.DATA_ROOTPath to the directory where the service stores the uploaded files.NON_ATTACHMENT_MIME_TYPESA list of string globs which specify the content types which arenotsent\nas attachment. Defaults to the empty list if not given.Example use:NON_ATTACHMENT_MIME_TYPES = [\n \"image/*\",\n \"video/*\",\n \"audio/*\",\n \"text/plain\",\n]Everything which does not match any of the entries here will be sent withContent-Disposition:attachmentin order to prevent funny attacks.It is not recommended to add things liketext/htmlor*to this\nlist.ENABLE_CORSAllow cross-origin access to all endpoints unconditionally. This is needed\nto allow web clients to use the upload feature.Issues, Bugs, LimitationsThis servicedoes not handle any kind of quota.The format in which the files are stored isnotcompatible withmod_http_upload\u2013 so you\u2019ll lose all uploaded files when switching.This blindly trusts the clients Content-Type. I don\u2019t think this is a major issue, because we also tell the browser to blindly trust the clients MIME type. This, in addition with forcing all but a white list of MIME types to be downloaded instead of shown inline, should provide safety against any type of XSS attacks.I have no idea about web security. The headers I set may be subtly wrong and circumvent all security measures I intend this to have. Please double-check for yourself and report if you find anything amiss.Example Installation instructionsExample instructions for debian based systems, if you don\u2019t use debian check your distributions repositories for the correct python3 flask package name.\nYou probably also want to use something else thenapt-geton non debian based distributions.In this example we will install the flask http server and proxy requests from an already installed and configured webserver (nginx) to the flask http server.\nIt is also possible to run the python script withwsgiwhich should yield in better performance.I assume your webserver useswww-dataas service account. If you have a different user update the systemd service and the permissions for the data directory.Clone and install:git clone https://github.com/horazont/xmpp-http-upload\nsudo mv xmpp-http-upload /opt/xmpp-http-upload\ncd /opt/xmpp-http-upload\ncopy config.example.py config.py\nsudo apt-get install python3-flaskEditconfig.pyand changeSECRET_KEY. Be sure to only change between''.Create the upload directory:sudo mkdir /var/lib/xmpp-http-upload\nsudo chown www-data.www-data /var/lib/xmpp-http-uploadEnable systemd service:sudo copy contrib/xmpp-http-upload.service /etc/systemd/system\nsudo systemctl enable xmpp-http-upload.service\nsudo systemctl start xmpp-http-upload.serviceConfigure your webserver:As final step you need to point your external webserver to your xmpp-http-upload flask app.\nCheck thecontribdirectory, there is an example for nginx there."} +{"package": "xmpplib", "pacakge-description": "xmpplib is a lightweight and useful XMPP/Jabber client."} +{"package": "xmpp_logging_handler", "pacakge-description": "Usage example, assumes gmail.com account.from xmpp_logging_handler import XMPPHandler\nimport logging\nlogger = logging.getLogger()\nmyHandler = XMPPHandler('SENDING_USER', 'SENDING_PASSWORD', ['raymond@thisislevelup.com',],)\nlogger.addHandler(myHandler)\nlogging.error('Its broken')"} +{"package": "xmppony", "pacakge-description": "xmppony is an XMPP library released under GNU GPLv3. It\u2019s a fork of xmpppy\n(CVS trunk as of 2008-03-25), which was in turn a fork of jabber.py.xmpppy was written by Alexey Nezhdanov under GNU GPLv2+.http://xmpppy.sourceforge.net/jabber.py was written by Matthew Allum under GNU LGPL.http://jabberpy.sourceforge.net/"} +{"package": "xmpppy", "pacakge-description": "Python 2/3 implementation of XMPP (RFC3920, RFC3921).Documentation:http://xmpppy.sf.net/Source Code:https://github.com/xmpppy/xmpppyStatus:AboutThis library has been written to be compliant withRFC3920andRFC3921.InstallationUsingpip, you can install the package with:pip install xmpppy --upgradeUsageAs a libraryRegularly, the module is used as a library, like:jabberid = \"foobar@xmpp.domain.tld\"\npassword = \"secret\"\nreceiver = \"bazqux@xmpp.domain.tld\"\nmessage = \"hello world\"\n\njid = xmpp.protocol.JID(jabberid)\nconnection = xmpp.Client(server=jid.getDomain(), debug=debug)\nconnection.connect()\nconnection.auth(user=jid.getNode(), password=password, resource=jid.getResource())\nconnection.send(xmpp.protocol.Message(to=receiver, body=message))Command line interfaceThe package also installs a command line program calledxmpp-message.\nIts synopsis is:xmpp-message --debug \\\n --jabberid foobar@xmpp.domain.tld --password secret \\\n --receiver bazqux@xmpp.domain.tld --message 'hello world'You can also put your credentials into an~/.xsendfile, like:JID=foobar@xmpp.domain.tld\nPASSWORD=secretand then invokexmpp-messageomitting the--jabberidand--passwordoptions, like:xmpp-message --receiver bazqux@xmpp.domain.tld --message 'hello world'DocumentationThe canonical documentation is hosted athttps://xmpppy.github.io/andhttp://xmpppy.sourceforge.net/.For learning about how to use this module, please have a look at these spots\nwithin the code base.Thexmpp-messageprogram, located atxmpp/cli.py, for sending a single XMPP message.The other programs within thedoc/examplesdirectory.The docstrings within the library itself.SupportIf you have any questions about xmpppy usage or you have found a bug or want\nto share some ideas - you are welcome to join us on theissue trackeror on thexmpppy-devel mailing list.Other projectshttps://github.com/poezio/slixmpphttps://github.com/horazont/aioxmpphttps://github.com/Jajcus/pyxmpp2https://github.com/fritzy/SleekXMPPhttps://dev.gajim.org/gajim/python-nbxmpphttps://github.com/xmpppy/xmpppy/files/4346179/xmpp_libs.xlsx"} +{"package": "xmppwb", "pacakge-description": "Note that xmppwb is currently in early development and may contain bugs.A bot that bridges XMPP (chats and MUCs) with webhooks, thus making it possible\nto interact with services outside the XMPP world. This can be used to connect\nXMPP to other chat services that provide a webhook API (for exampleRocket.ChatorMattermost).InstallationUsageConfigurationIntegrating with Rocket.ChatIntegrating with MattermostLicenseInstallationNote: Python 3.5 is required. It will not work with Python 3.4 as xmppwb uses specific syntax that was introduced with Python 3.5.xmppwbrequiresPython 3.5+and can be installed using pip3:$pip3install--upgradexmppwbwhich will automatically install the dependencies (aiohttp,pyyamlandslixmpp).UsageThis bridge is meant to run on the same server as the application you are\nbridging with, as it currently uses HTTP for incoming webhooks.To run the bridge:$xmppwb--configconfigfile.confor:$python3-mxmppwb--configconfigfile.confSynopsis:$xmppwb-cCONFIG[-h][-v][-lLOGFILE][-d][--version]See alsoxmppwb--help.ConfigurationPlease seeCONFIGURATION.rstfor detailed documentation. A simple config file looks like this (theneed to be changed):xmpp:# This JID must exist.jid:password:\"\"# Define all MUCs that should be available to the bridges defined later.mucs:-jid:nickname:# password: \"\"incoming_webhook_listener:bind_address:\"127.0.0.1\"port:5000bridges:-xmpp_endpoints:-muc:outgoing_webhooks:-url:incoming_webhooks:-token:Note that the password is stored in cleartext, so take precautions such as\nrestricting file permissions. It is recommended to use a dedicated JID for\nthis bridge.The terminologyincomingandoutgoingin the config file refers to\nwebhooks from the perspective of this bridge. The webhooks must also be defined\non the other end (Rocket.Chat and Mattermost provide a UI for this, for\nexample). Anoutgoing webhook in Rocket.Chatmust be set up in theincoming webhooks section in this bridgeand vice versa.Integrating with Rocket.ChatAn example config for bridging XMPP withRocket.Chatis provided inrocketchat.example.conf.\nIt is recommended to copy it and fill out all.To create the corresponding webhooks in RocketChat, go toAdministration->Integrationsand create a new incoming webhook.\nHere you can select the channel that you want to bridge with.After saving, a webhook URL will be generated. Copy it and fill it into\ntheplaceholder in the config\nfile.Now create an outgoing webhook. The URL is of the formhttp://{bind_adress}:{port}/and depends on your settings in theincoming_webhook_listenersection. It defaults tohttp://127.0.0.1:5000/.Copy the token and fill it into theplaceholder.After having filled out all other placeholders, the bridge is ready to run\n(seeusage).Integrating with MattermostAn example config for bridging XMPP withMattermostis provided inmattermost.example.conf.\nIt is recommended to copy it and fill out all.To create the corresponding webhooks in Mattermost, go toAccount Settings->Integrationsand create a new incoming webhook.\nHere you can select the channel that you want to bridge with.After saving, a webhook URL will be generated. Copy it and fill it into\ntheplaceholder in the config\nfile.Now create an outgoing webhook. The callback URL is of the formhttp://{bind_adress}:{port}/and depends on your settings in theincoming_webhook_listenersection. It defaults tohttp://127.0.0.1:5000/.After saving, copy the token and fill it into theplaceholder.After having filled out all other placeholders, the bridge is ready to run\n(seeusage).Licensexmppwb is released under the MIT license. Please readLICENSEfor details."} +{"package": "xmppxmlrpc", "pacakge-description": "No description available on PyPI."} +{"package": "xmppy", "pacakge-description": "No description available on PyPI."} +{"package": "xm-program", "pacakge-description": "No description available on PyPI."} +{"package": "xmp-tool", "pacakge-description": "This is a simple command line utility to read/write single value\nfields in XMP files using thepython-xmp-toolkit.InstallationA simple install from pip:$pipinstallxmp-toolNote:python-xmp-toolkitdepends onExempiwhich needs to bebuilt for XMP to be installed properly.Use your systems package manager to installExempi, on Mac OS X with\nhomebrew:$brewinstallexempiOn a Debian based Linux system do:# apt-get install libexempi-devUsage:$xmp-tool-husage:xmp-tool[-h][--valueVALUE][--no-sidecar][field]file[file...]ReadorwriteXMPfieldsinafilepositionalarguments:fieldThefieldtoread/write.IfnofieldspecifiedentireXMPdocumentprinted.fileAfiletoworkonoptionalarguments:-h,--helpshowthishelpmessageandexit--valueVALUEAvaluetowritetothefieldspecified--no-sidecarNeverwritetosidecarfiles.Reading a field:$xmp-toolformattest.jpgtest.jpg:format=image/jpegReading the entire XMP contents of a file:$xmp-tooltest.jpgtest.jpg:None=lto01Writing a field:# First try to read the field when there's no data in it$xmp-toolPhysicalMediumtest.jpgtest.jpeg:ERRORREADINGFIELD\"PhysicalMedium\"# Then try to add the data and then read the field$xmp-toolPhysicalMedium--valuelto01test.jpg$xmp-toolPhysicalMediumtest.jpgtest.jpg:PhysicalMedium=lto01"} +{"package": "xmptools", "pacakge-description": "XMP ToolsThis package provides basic XMP support forRDFLib,\nincluding parsing, modification, and serialization. XMP is Adobe's metadata format, based on\nRDF. Trivially, XMP metadata is RDF serialized asRDF/XML,\n\"wrapped\" within a special XML element.Adobe's XMP documentationcan be found hereandhere.Unit tests with incomplete coverage are provided, as well as somedocumentationand examples.The parser and the serializer are implemented as RDFLib plugins. Because of limited\nextensibility of RDFLib, we have copied some methods from RDFLib and modified them. The plugins\nregister themselves asformat=\"xmp\". Normally, you do not have to know this, as we provide\nconvenience functionality for reading and writing XMP (see below).Future plansMake the embedded metadata support more \"robust\". Writing of embedded metadata is not in the\nplans, at least for now.ContactAuthor: Ora Lassilaora@somanyaircraft.comCopyright (c) 2021-2022 Ora Lassila andSo Many Aircraft"} +{"package": "xmpush-python", "pacakge-description": "# xmpush-python\nApython3library forked from [Xiaomi push python SDK](https://dev.mi.com/mipush/downpage/python.html)\nThe main purpose is to support distribute this SDK via PyPI.## Latest changes\n- Initial version and no changes at all.## Install`bash pip installxmpush-python`or download from [here](https://github.com/ULHI-xin/xmpush-python/releases/download/0.0.2/xmpush-python-1.0.3.tar.gz)\nthen run`bash pip installxmpush-python-1.0.3.tar.gz(Supposexmpush-python-1.0.3.tar.gzis the local file downloaded) `## Licence\nApache 2.0\nThe original SDK by Xiaomi is developed underApache Software Licenseand it\u2019s not modified.\nI cannot find any license declaration in the original copy of code."} +{"package": "xmq", "pacakge-description": "xmq"} +{"package": "xmq-python", "pacakge-description": "Message Queue Client for Python\u751f\u6210\u5b89\u88c5\u5305\u53c2\u8003https://packaging.python.org/tutorials/packaging-projects/\u5347\u7ea7\u5b89\u88c5\u5fc5\u8981\u5de5\u5177python3-mpipinstall--upgradebuildpython3-mpipinstall--user--upgradetwine\u751f\u6210\u5b89\u88c5\u5305python3-mbuild\u4e0a\u4f20\u5b89\u88c5\u5305python3-mtwineupload--repository-urlhttps://<\u79c1\u6709\u955c\u50cf\u5730\u5740>dist/*\u9ed8\u8ba4\u4e0a\u4f20\u5230https://pypi.orgpython3-mtwineuploaddist/*\u4f7f\u7528\u5b89\u88c5\u5305installpip3installxmq-python\u53d1\u9001\u6d88\u606ffromxmq_python.producerimportProducerproducer=Producer(mq_type='AMQO',host='',port=0,access_key='',access_secret='',timeout=None,max_message_size=None,username='',password='',virtual_host='',instance_id='')producer.start()producer.Publish('order','demand',{\"id\":123,\"name\":\"neil\"})producer.stop()\u63a5\u6536\u6d88\u606ffromxmq_python.consumerimportConsumerimporttimedefcallback(message):print(\"Got message: \",message)returnTrueconsumer=Consumer(mq_type='AMQO',consumer_group_name='',host='',port=0,access_key='',access_secret='',timeout=None,max_message_size='',username='',password='',virtual_host='',instance_id='')consumer.Register(\"order\",\"demand\",callback)consumer.start()time.sleep(100)consumer.stop()"} +{"package": "xmqt", "pacakge-description": "No description available on PyPI."} +{"package": "xmr", "pacakge-description": "hihi so i made this package becausetagokok"} +{"package": "xmr-haystack", "pacakge-description": "xmr-haystackDescriptionThis program takes a Monero wallet file, scans the blockchain, and outputs transactions in which\nyour one-time public outputs (stealth addresses) were used as decoys.InstallationA Python 3 environment is required to run this application. Given that you have a working Python 3\nenvironment, all you need to do to install this application is run the following command:$ pip3 install xmr-haystackIf you are on Linux or MacOS and you would prefer to build from the source code, then the following\ncommands will allow you to do so:$ git clone https://github.com/jeffro256/xmr-haystack.git\n$ cd xmr-haystack\n$ pip3 install .If you are Windows and would prefer to build from the source code, then follow these steps:Download the unzip source code fromGithub.Open 'cmd' from the Start MenuNaviagte to newly unzipped directory in cmdType$ pip3 install .Usagepython3 -m xmr-haystack [-h] [-a ADDR] [-p PORT] [-l LOGIN] [-s HEIGHT] [-q | -Q] [-i CACHE_IN] [-o CACHE_OUT] [-n] \n [-c CLI_EXE_FILE] wallet file\n\nAmerica's favorite stealth address scanner\u2122\n\npositional arguments:\n wallet file path to wallet file\n\noptional arguments:\n -h, --help show this help message and exit\n -a ADDR, --daemon-addr ADDR\n daemon address (e.g. node.xmr.to)\n -p PORT, --daemon-port PORT\n daemon port (e.g. 18081)\n -l LOGIN, --daemon-login LOGIN\n monerod RPC login in the form of [username]:[password]\n -s HEIGHT, --scan-height HEIGHT\n rescan blockchain from specified height. defaults to wallet restore height\n -q, --quiet use this flag if you would like a simpler output\n -Q, --extra-quiet use this flag if you would like a BARE BONES output\n -i CACHE_IN, --cache-input CACHE_IN\n path to input cache file\n -o CACHE_OUT, --cache-output CACHE_OUT\n path to output cache file\n -n, --no-cache do not read from cache file and do not save to cache file\n -c CLI_EXE_FILE, --wallet-cli-path CLI_EXE_FILE\n path to monero-wallet-cli executable. Helpful if executable is not in PATHExample$ python -m xmr-haystack Documents/mywallet/mywallet\n\n...\nYour stealth address: 58ddd530a2148ca67f914823bab3e5b30f10be16b5a17ca194a022e279fb9258\n [2019-10-28 14:49:50]: Pubkey was created. Transaction(hash=f889ab737e12a88f249762e15fdcf2e0fa5a3f2d124d63860c029e57a61d33b6, height=1954776, ins=22, outs=2)\n [2019-10-28 17:20:56]: Used as a decoy. Transaction(hash=41662618c3fe6556a1b69128be7ff731565fb5d3003d03296587bc3d9985e01b, height=1954856, ins=11, outs=2)\n [2019-10-28 20:46:02]: Used as a decoy. Transaction(hash=ce3d73fd5f47ed3205d5f4d3a5246a7d3adf09ab6fb9238ac8f5d0c3976874d3, height=1954958, ins=11, outs=2)\n [2019-10-29 01:06:24]: Used as a decoy. Transaction(hash=76be4fa1b0089e2dec7332adf0230294e9c94ec4e32be44d65830ba2f0ecb1c3, height=1955092, ins=814, outs=2)\n [2019-10-29 07:03:25]: Used as a decoy. Transaction(hash=28277d27a738543257414e3f5f4b71eed5d3551fa815c22a66c7183cf38ebcd1, height=1955280, ins=22, outs=2)\n [2019-10-29 12:39:36]: Used as a decoy. Transaction(hash=1e3e89a8be3af614ce06324d1c61c16ed4cf84fcbf39095be84cbe3875fd0644, height=1955443, ins=11, outs=2)\n [2019-10-29 16:27:17]: Used as a decoy. Transaction(hash=1e2e63f61222809178476a7dcb7b2b5aaba060b23cfc95c9c797bfb3d233b92f, height=1955566, ins=187, outs=2)\n [2020-07-15 00:26:23]: Pubkey was spent. Transaction(hash=a6cbb9f76f9b37247c9f3fb160dccdf5d627b92702a09c488815cf8bcd9baf70, height=2142546, ins=11, outs=2)\n...DisclaimerWhile this program works, it is still inveryearly dev stages. Use this program at your own risk;\nI take no responsibility for any lost funds or privacy, etc, etc. That said, I really hope you find\nthis code useful and I would really appreciate any feedback. :)Donate89tQx7bUmQDMdkgUjk5ZSfVpV3yGKZ6udWe4XGbBNE27iyxoYoWif8nHCLnvqjodaLENVGgBpWSFE2XGyjNKLT1bB8efQh5"} +{"package": "xmrig-auto-throttler", "pacakge-description": "xmrig auto throttlerThis program automatically throttles xmrig when you start using your computer and stops throttling when you become idle again. It does so by defining two profiles, which are two config.json's, one for the minimum load situation, one for the maximum load situation.InstallationArch Linux (or other arch-derivatives like Manjaro, etc...)sudopacman-Sxprintidle\npip3installxmrig-auto-throttlerUbuntu (or other Debian based distros)sudoapt-getinstallxprintidle\npip3installxmrig-auto-throttlerWindowsComing soonDonatePlease consider a donation if you find this program useful."} +{"package": "x-mroy-0", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1045", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1046", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1047", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1048", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1050", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1051", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-1052", "pacakge-description": "No description available on PyPI."} +{"package": "x-mroy-202", "pacakge-description": "No description available on PyPI."} +{"package": "xmrto-wrapper", "pacakge-description": "XMR.to wrapperInteract with XMR.to.This is built according to the XMR.toAPI documentation.Withhttps://test.xmr.toyou can pay testnet BTC with stagenet XMR (including lightning payments).How toGet helpxmrto_wrapper -hGeneral usageCreate an order for an amount inBTC:# Create an order for 0.001 BTC:\n xmrto_wrapper create-order --destination 3K1jSVxYqzqj7c9oLKXC7uJnwgACuTEZrY --btc-amount 0.001\n # Result:\n {\"uuid\": \"xmrto-p4XtrP\", \"state\": \"TO_BE_CREATED\", \"btc_dest_address\": \"3K1jSVxYqzqj7c9oLKXC7uJnwgACuTEZrY\", \"btc_amount\": \"0.001\", \"uses_lightning\": false}\n # If XMR.to is fast enough with the order processing, the result can also be:\n {\"uuid\": \"xmrto-LAYDkk\", \"state\": \"UNPAID\", \"btc_dest_address\": \"3K1jSVxYqzqj7c9oLKXC7uJnwgACuTEZrY\", \"btc_amount\": \"0.001\", \"uses_lightning\": false, \"receiving_subaddress\": \"86hZP8Qddg2KXyvjLPTRs9a7C5zwAgC21RcwGtEjD3RPCzfbu4aKBeYgqFgpcsNNCcP5iGuswbMKRFXLHiSu45sWMuRYrxc\", \"incoming_amount_total\": \"0.1373\", \"remaining_amount_incoming\": \"0.1373\", \"incoming_price_btc\": \"0.00728332\", \"btc_amount_partial\": \"0\", \"seconds_till_timeout\": 2697, \"created_at\": \"2020-05-01T18:47:57Z\"}--btcis the equivalent of--btc-amountand can be used interchangeably.It's possible to give the amount inXMR, where--xmris the equivalent of--xmr-amount(They can be used interchangeably).# Create an order for 1 XMR:\n xmrto_wrapper create-order --destination 3K1jSVxYqzqj7c9oLKXC7uJnwgACuTEZrY --xmr-amount 1\n # Result:\n {\"uuid\": \"xmrto-JSSqo3\", \"state\": \"TO_BE_CREATED\", \"btc_dest_address\": \"3K1jSVxYqzqj7c9oLKXC7uJnwgACuTEZrY\", \"btc_amount\": \"0.00722172\", \"uses_lightning\": false}Use--followto keep tracking the order.Prior tov0.1there used to be a separate sub command:--create-and-track-order.--followprovides the same behaviour.Track an existing order:xmrto_wrapper track-order --secret-key xmrto-ebmA9q--secretand--keyare the equivalents of--secret-keyand can be used interchangeably.Use--followto keep tracking the order.Confirm an underpaid order (for an underpaid order):xmrto_wrapper confirm-partial-payment --secret-key xmrto-ebmA9q--secretand--keyare the equivalents of--secret-keyand can be used interchangeably.Use--followto keep tracking the order.Get the recent price for an amount inBTC:xmrto_wrapper check-price --btc-amount 0.01--btcis the equivalent of--btc-amountand can be used interchangeably.It's possible to give the amount inXMR, where--xmris the equivalent of--xmr-amount(They can be used interchangeably).xmrto_wrapper check-price --xmr-amount 1Use--followto keep tracking the order.The API used is--api v3by default, so no need to actually set that parameter.The URL used is--url https://xmr.toby default, so no need to actually set that parameter.There also is--url https://test.xmr.tofor stagenet XMR.Oftenhttps://test.xmr.tohas some new features available for testing.More infoxmrto_wrapper.py --versionxmrto_wrapper.py --logoThe option--debugshows debug information.See:xmrto_wrapper --help.xmrto_wrapper create-order --help...When importing as modulefrom xmrto_wrapper import xmrto_wrapperenvironment variables are considered:cli optionenvironment variable--urlXMRTO_URL--apiAPI_VERSION--destinationDESTINATION_ADDRESS--btc-amount,--btcBTC_AMOUNT--xmr-amount,--xmrXMR_AMOUNT--secret-key,--secret,--keySECRET_KEY--invoiceLN_INVOICErequirements.txt vs. setup.pyAccording to these sources:python documentationstackoverflow - second answer by jonathan HansonI try to stick to:requirements.txtlists the necessary packages to make a deployment work.setup.pydeclares the loosest possible dependency versions.Creatingrequirements.txtYou won't ever need this probably - This is helpful when developing.pip-toolsis used to createrequirements.txt.There isrequirements.inwhere dependencies are set and pinned.To create therequirements.txt, runupdate_requirements.shwhich basically just callspip-compile.Note:There also isbuild_requirements.txtwhich only containspip-tools. I found, when working with virtual environments, it is necessary to installpip-toolsinside the virtual environment as well. Otherwisepip-syncwould install outside the virtual environment.A development environment can be created like this:# Create a virtual environment 'venv'.python-mvenvvenv# Activate the virtual environment 'venv'../venv/bin/activate# Install 'pip-tools'.pipinstall--upgrade-rbuild_requirements.txt# Install dependencies.pip-syncrequirements.txt...python-mxmrto_wrapper.xmrto_wrappercreate-order--urlhttps://test.xmr.to--apiv3--destination=\"tb1qkw6npn7ann5nw9f7l94qkqhh8pdtnsuxlw3v8q\"--btc0.5--follow...# Deactivate the virtual environment 'venv'.deactivateUse as modulemodule_example.pyshows how to import as module.ExecutableIf installed usingpip, a system executable will be installed as well.\nThis way, you can just use the tool like every executable on your system.xmrto_wrapper --helpIf you would like to donate - Thanks:86Avv8siJc1fG85FmNaUNK4iGMXUHLGBY2QwR3zybFMELXrNA34ioEahrupu16v6mZb2hqp2f89YH78oTvyKaha4QRVk2Rb"} +{"package": "xms-client", "pacakge-description": "XMS is the controller of distributed storage system # noqa: E501You can use XMS to manage you XSKY storage cluster"} +{"package": "xmscore", "pacakge-description": "No description available on PyPI."} +{"package": "xmsextractor", "pacakge-description": "No description available on PyPI."} +{"package": "xmsg", "pacakge-description": "TODO"} +{"package": "x-msgpack", "pacakge-description": "x_msgpackSeparate\"msgpack\"module in\"micropython-mpy-env\"package into a single\"x_msgpak\" module, for general Python project. See theMessagePacksection for more detail."} +{"package": "xmsgrid", "pacakge-description": "No description available on PyPI."} +{"package": "xmsgs-tools", "pacakge-description": "_ ___ ___ __ ___ ___ __ _ ___ | |_ ___ ___ | |___\\ \\/ / '_ ` _ \\/ __|/ _` / __|_____| __/ _ \\ / _ \\| / __|> <| | | | | \\__ \\ (_| \\__ \\_____| || (_) | (_) | \\__ \\/_/\\_\\_| |_| |_|___/\\__, |___/ \\__\\___/ \\___/|_|___/|___/Little python helpers for parsing through Xilinx build outputs.### WORK IN PROGRESSThere are some blatant problems:- unhandled exceptions on some message types- duplicated messages reported- etc### InstallThis is pure python, no dependancies. Only tested on linux (debian wheezy).Using pypi:pip install xmsgs-toolsOr, locally,python setup.py install### UsageDo ``xmsgsprint -h`` or ``xmsgsdiff -h`` for usage. Examples:bnewbold@ent$ xmsgsprint test/run_a/xst.xmsgs -t severe -fHDLCompiler:413: Result of 32-bit expression is truncated to fit in 2-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 4-bit target.HDLCompiler:413: Result of 9-bit expression is truncated to fit in 8-bit target.HDLCompiler:413: Result of 9-bit expression is truncated to fit in 8-bit target.HDLCompiler:413: Result of 9-bit expression is truncated to fit in 8-bit target.HDLCompiler:413: Result of 3-bit expression is truncated to fit in 2-bit target.HDLCompiler:413: Result of 9-bit expression is truncated to fit in 8-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 2-bit target.HDLCompiler:413: Result of 3-bit expression is truncated to fit in 2-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 9-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 12-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 4-bit target.HDLCompiler:413: Result of 32-bit expression is truncated to fit in 5-bit target.=== Summary ==================================================================Severe Warnings: 13bnewbold@ent$ xmsgsdiff test/run_a test/run_b --by-file -i 2261 2677 37 647 -s \"*main*\" -t warning--- +Xst:0: Value \", final ratio i...=== Summary ==================================================================Warnings: 153 (+2, -0)### Example Raw .xmsgsDetected unknown constraint/property "x_interface_info". This constraint/property is not supported by the current software release and will be ignored."/home/bnewbold/leaf/twl/dds/hdl/block_design/ip/block_design_axi_gpio_0_0/synth/block_design_axi_gpio_0_0.vhd" line 167: Output port <gpio_io_o> of the instance <U0> is unconnected or connected to loadless signal.### Notes'fulltext' is not a unique identifier; many warning texts are repeatedSee also, XReport GUI tool.### TODO- Are message numbers unique across tools? If not, need more sophisticated filtering.- Collapse redundant warnings (eg, every bit on on the same port)"} +{"package": "xmsinterp", "pacakge-description": "No description available on PyPI."} +{"package": "xm-slurm", "pacakge-description": "No description available on PyPI."} +{"package": "xms_sdk", "pacakge-description": "UNKNOWN"} +{"package": "xm.theme", "pacakge-description": "1.3 (2012-09-12)Moved to github:https://github.com/zestsoftware/xm.theme[maurits]Let the plone.contentviews viewlet work in both Plone 3 and 4,\nwithout AttributeError in Plone 4 for prepareObjectTabs.\n[maurits]1.2 (2010-09-24)Added z3c.autoinclude.plugin target plone.\n[maurits]1.1 (2010-05-01)Show Plone Site title in the header when you are not in a project,\ninstead of showing hardcoded \u2018Extreme Management\u2019.\nFixeshttp://plone.org/products/extreme-management-tool/issues/203[maurits]cleaned up the other css files [mirella]cleaned up IEfixes [mirella]cleaned up forms.css.dtml [mirella]cleaned up columns.css [mirella]finished cleaning up authoring.css [mirella]started with cleaning up authoring.css [mirella]cleaned up public.css and base.css [mirella]more css code clean up [mirella]started with cleaning up css code [mirella]added german translation [jensens]Fix z-index for kupu-fulleditor-zoomed on #portal-top and\n.documentContent. [laurens]1.0.1 (2009-03-22)Add-iteration css updated for planned iterations view [jladage]1.0 (2009-03-15)removed cachesettings.xml because it contains site specifice configuration.\nIt\u2019s now located in project.setup [jladage]added title to my projects menuadded mockup folder for design proposals [laurens]moved two xm.theme specefic classes from extreme.css to xm.theme\u2019s main.css [laurens]removed two images from eXtremeManagement that weren\u2019t being used [laurens]disabled .myProject in print.css [laurens]Ticket #148 - Removed \u2018my project\u2019 link. [simon]Ticket #147 - Overrode path_bar template to remove \u2018Home\u2019. [simon]Fixed KSSUnicodeError in the fullname viewlet when you have a\nnon-ascii name. [maurits]Added Products.eXtremeManagement>=2.0alpha3 to our dependencies in\nsetup.py.http://plone.org/products/extreme-management-tool/issues/157shows we need at least that version. [maurits]1.0rc2 (2009-02-25)Added cachesettings.xml to store our xm rules.1.0rc1 (2009-01-25)Added extra viewlet for the my project stub in portaltop. [jladage]Fixed issue 100, insert list of projects on DOM load. [reinout +\nmark]Fixed issue 135, Titles of portlets are now not transformed to\ncapitalized. [jladage]Fixed issue 126, When adding a project the header was not displayed.\n[jladage]1.0beta2 (2009-01-15)Style and portlet cleanup by laurens and jladage. [laurens, jladage]1.0beta1 (2009-01-09)Overrode the login portlet template, added a footer to the Login portlet. [simon]0.9 (2009-01-07)Also show Documents as attachments. [mark]Remove the viewlets which showed the iterations grouped by\nstate since there is a porlet to do this. [mark]The username is not rendered on each page but on DOM load. This allows for\ncaching based on roles instead of each user.[jladage]Images are moved to a skins folder, so they get cached properly using the\nHTTPCache. [jladage]The username in the personal_bar now links to the author page instead of the\ndashboard. [jladage]Added \u2018Iterations:\u2019 in front of the open/current/closed iterations list and\nshow it only if we have iterations in the project. [fredvd]Moved the employees_overview page to Products.eXtremeManagement.\n[maurits]Made the employees overview page much much faster. The billable\npercentages are not quite the same as from the bookings per month\npages they point to, but that is for another day. [maurits]Protecting the big employees overview page with the Manage Portal\npermission now. [maurits]0.8 (2008-09-16)Added locales/en to work around i18n bug: with e.g. Dutch and\nEnglish as allowed languages, Dutch as site default, English as\nbrowser language (the only one or not), you would get Dutch for all\ntranslations in the xm.theme domain, even though the rest of the UI\nis in English\u2026 [maurits]Fixed the livesearch.js customization to work with Plone 3.1.x We have to drop\nsupport for Plone 3.0.x for this one, because jquery.js is not available.\n[jladage]0.7.3 (2008-08-01)Use gradient image in booking-per-month table heading. [mirella]\n(Moved from Products.eXtremeManagement trunk by Maurits.)Made gradient images bigger in height for layout reasons. [mirella]Fixed name typo in css. [mirella]Placed the gradient images in bottom in the used classes. [mirella]Added translations and description for employees overview. [mirella]Added odd color and padding to employees overview. [mirella]Started HISTORY.txt (merged from 0.7.2). [maurits]0.7 (2008-05-15)No history recorded.0.6 (2008-03-31)No history recorded.0.5 (2008-03-03)No history recorded.0.4 (2008-02-27)No history recorded.0.3 (2008-02-26)No history recorded.0.2 (2008-02-25)No history recorded."} +{"package": "xm.tracker", "pacakge-description": "IntroductionThis package provides a user interface to track time based on the concepts of\ngtimelog. When starting your working day you start a timer. Each time that you\nchange to a different tasks you log an entry of what you were working on.In eXtreme Management we book our hours on tasks. This tracker allows you to\nselect a number of tasks from the list of tasks that are assigned to you.\nThe selected tasks are shown in the time tracker.History of xm.tracker1.0.8 (2014-06-16)Do not use kukit-devel.js in the tracker. It is nice for debugging\nwhen you are developing on the tracker, but not in production. I\nupdated to Firefox 30 and Firebug 2.0 today and the tracker gave a\njavascript error for kukit-devel.js:TypeError: 'log' called on an object that does not implement interface Console.It did work\nwhen I actually enabled Firebug. Bonus: now it works on Safari too.\n[maurits]1.0.7 (2014-03-31)Never cache the tracker view. It always needs to be fresh.\n[maurits]1.0.6 (2012-09-12)Moved to github:https://github.com/zestsoftware/xm.tracker[maurits]1.0.5 (2011-05-03)Removed base2 library from head section. [jladage]Fixed translation of invalid time message.\n[maurits]1.0.4 (2010-09-24)Explicitly load the permissions.zcml file from\nProducts.eXtremeManagement, otherwise you can get a\nComponentLookupError on zope startup.\n[maurits]Added z3c.autoinclude.plugin target plone.\n[maurits]For entries, always round up to the nearest minute.\n[maurits]1.0.3 (2010-05-03)Fixed rounding error: hours in entries were counted twice (2:15\ntracked in the timer would mean 2 hours plus (2*60 + 15 = 135)\nminutes = 4 hours, 15 minutes tracked.\n[maurits]1.0.2 (2010-05-01)Round booked time up to multiple of 15 minutes. Round tracked time\nup to complete minutes.\nFixeshttp://plone.org/products/extreme-management-tool/issues/175[maurits]Specify egenix-mx-base as dependency in setup.py. It is\neasy_installable now. When this is not pulled in automatically you\ncan run into seemingly unrelated problems, certainly when you do not\nstart the instance on the foreground; not all zcml will be loaded.\nHaving it as an official dependency should work fine now, and if it\nfails it is at least explicit about what fails.\n[maurits]added german translation. [jensens]1.0.2 (2009-05-05)Nothing changed yet.1.0.1 (2009-05-05)Added div #task_selection_form_content to unassigned_task_select.pt\nto provide styling for the unassigned tasks form. [laurens]1.0 (2009-03-15)select tasks button is now placed inside track time toolbar\n[laurens]1.0rc1 (2009-01-25)Tooltip now displays total booked and total tracked. [jladage]0.6 (2009-01-15)I made changes and didn\u2019t publish them in the history file. :) [laurens]0.5 (2009-01-09)Fix buttons on the \u2018select task for unassigned entry\u2019 form. [mark]Reinstate class on \u2018book to task\u2019 button which triggers the\nKSS. [reinout, mark]0.4 (2009-01-07)Moved \u201ceXtremeManagement: View Tracker\u201d permission to\nProducts.eXtremeManagement as we do not actually use that permission\nin the xm.tracker package. [maurits]Display a warning in a task when it is orphaned (removed, in the\nwrong state). [maurits]CSS changes to the tracker interface to visually distinguish tasks with and\nwithout bookings. [simon]Added project-grouping of tasks in the tracker view. [simon]Moved timer display to a separate viewlet. And added kss-refreshing of that\nviewlet in two places so that the timer (and especially the tooltip showing\nthe booked hours) gets updated on stopping the timer, on editing the time of\nan entry and on adding entries. [reinout]Fixedhttp://plone.org/products/extreme-management-tool/issues/79by\nnot using unicode in one small place. [reinout]Added KSS and template changes to allow the \u2018seconds\u2019 part of the tracker\ntimer to be individually styled. (This relates to kss.plugin.timer r72297.)\n[simon]0.3 (2008-09-18)Show the total hours booked plus tracked today as a tooltip on the\ntimer. [maurits+simon]Do not store the portal_url in the task_url; copying a Data.fs from\nproduction to a development machine would give you a url to the\ntasks on the production site, which is not handy and can be\ndangerous. After this change you need to remove existing tracker\ntasks and add them again unfortunately. [maurits+simon]Bug fix: when the tracker pointed to a task with a Discussion Item\n(comment) in it you would get: \u2018TypeError: a float is required\u2019.\n[maurits]0.2 (2008-09-17)Bug fix: a booking for 75 minutes would get stored as 1 hour and\n75 minutes instead of 1 hour and 15 minutes. [maurits]0.1.1 (2008-09-16)Removed egenix-mx-base from the install_requires of setup.py as it\nis not easy_installable. Improved docs/INSTALL.txt to explain about\nhow to install mx.DateTime. [maurits]0.1 (2008-09-16)First version. [maurits, reinout, jladage, simon]xm.tracker InstallationTo install xm.tracker into the global Python environment (or a workingenv),\nusing a traditional Zope 2 instance, you can do this:When you\u2019re reading this you have probably already runeasy_install xm.tracker. Find out how to install setuptools\n(and EasyInstall) here:http://peak.telecommunity.com/DevCenter/EasyInstallYou may need to manually install mxBase from Egenix; this is needed\nas we use mx.DateTime. It was previously not easy_installable, but\nnow this works fine so we have install it automatically as we have\nspecified it in the install_requires. Alternatively, get it here:http://www.egenix.com/products/python/mxBase/Your operating system may have a package already that you can\ninstall. On Ubuntu it is python2.4-egenix-mxdatetime.If you are using Zope 2.9 (not 2.10), getpythonproductsand install it\nvia:python setup.py install --home /path/to/instanceinto your Zope instance.Create a file calledxm.tracker-configure.zcmlin the/path/to/instance/etc/package-includesdirectory. The file\nshould only contain this:Alternatively, if you are using zc.buildout and the plone.recipe.zope2instance\nrecipe to manage your project, you can do this:Addxm.trackerto the list of eggs to install, e.g.:[buildout]\n...\neggs =\n ...\n xm.trackerTell the plone.recipe.zope2instance recipe to install a ZCML slug:[instance]\nrecipe = plone.recipe.zope2instance\n...\nzcml =\n xm.trackerYou may need to install mxBase from Egenix manually if the\ndependency fails to install automatically. On Linux/Max you can\nuse a buildout recipe:[buildout]\n# mx-base has to be the first part\nparts =\n mx-base\n ...\n\n...\n\n[mx-base]\nrecipe = collective.recipe.mxbaseOn Windows we have seen this fail. In that case, you can get an\ninstaller here:http://www.egenix.com/products/python/mxBase/Your operating system may have a package already that you can\ninstall instead. On Ubuntu it is python2.4-egenix-mxdatetime.Re-run buildout, e.g. with:$ ./bin/buildoutYou can skip the ZCML slug if you are going to explicitly include the package\nfrom another package\u2019s configure.zcml file.Products.eXtremeManagementdoes this."} +{"package": "xmtraining", "pacakge-description": "khkjhsadkhakjh"} +{"package": "xmu", "pacakge-description": "xmu is a Python utility used to read and write XML for Axiell EMu, a collections management system used in museums, galleries, and similar institutions.Install with:pip install xmuLearn more:GitHub repsositoryDocumentation"} +{"package": "xmutant", "pacakge-description": "This package provides a byte-code based mutation analysis framework for Python. It computes the mutation score (The quality score) of your doctests. Bytecode based mutation analysis ensures that invalid mutants are completely avoided (unlike source code based mutants), and also that trivial redundant and equivalent mutants (that can be distinguished by compiler) are already removed. It uses coverage analysis to ensure that only covered mutants that have a chance to be detected are run. It also includes randomized evaluation of equivalent mutants (use -a to set the number of attempts to be made).Compatibility-------------It was tested on Python 3.6To run------python xmutant.py -a Mutation Operators (on bytecode)--------------------------------- modify constants- replace boolean comparators (< <= == != > >=)- replace arithmetic operators (+ - * / // ./. ** % << >> ^)- remove unary negation and invert- invert unary signs- swap 'and' and 'or' in boolean expressions- swap inplace 'and' and 'or' in assignments- swap 'jump if * or pop' and 'jump if * and pop'- swap 'pop if true' and 'pop if false'"} +{"package": "xmuznlwtyr", "pacakge-description": "Xmuznlwtyr=================This API SDK was automatically generated by [APIMATIC Code Generator](https://apimatic.io/).This SDK uses the Requests library and will work for Python ```2 >=2.7.9``` and Python ```3 >=3.4```.How to configure:=================The generated code might need to be configured with your API credentials.To do that, open the file \"Configuration.py\" and edit its contents.How to resolve dependencies:===========================The generated code uses Python packages named requests, jsonpickle and dateutil.You can resolve these dependencies using pip ( https://pip.pypa.io/en/stable/ ).1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r requirements.txt```Note: You will need internet access for this step.How to test:=============You can test the generated SDK and the server with automatically generated testcases. unittest is used as the testing framework and nose is used as the testrunner. You can run the tests as follows:1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r test-requirements.txt```3. Invoke ```nosetests```How to use:===========After having resolved the dependencies, you can easily use the SDK following these steps.1. Create a \"xmuznlwtyr_test.py\" file in the root directory.2. Use any controller as follows:```pythonfrom __future__ import print_functionfrom xmuznlwtyr.xmuznlwtyr_client import XmuznlwtyrClientapi_client = XmuznlwtyrClient()controller = api_client.clientresponse = controller.get_basic_auth_test()print(response)```"} +{"package": "xMySQL", "pacakge-description": "No description available on PyPI."} +{"package": "xmyu", "pacakge-description": "No description available on PyPI."} +{"package": "xmz-env", "pacakge-description": "just for fun"} +{"package": "xn", "pacakge-description": "UNKNOWN"} +{"package": "xnat", "pacakge-description": "A new XNAT client that exposes XNAT objects/functions as python\nobjects/functions. The aim is to abstract as much of the REST API\naway as possible and make xnatpy feel like native Python code. This\nreduces the need for the user to know the details of the REST API.\nLow level functionality can still be accessed via the connection object\nwhich hasget,head,put,post,deletemethods for more\ndirectly calling the REST API.DisclaimerThis is NOT pyxnat, but a new module which uses a\ndifferent philosophy for the user interface. Pyxnat is located at:https://pythonhosted.org/pyxnat/Getting startedTo install just use the setup.py normally:python setup.py installor install directly using pip:pip install xnatTo get started, create a connection and start querying:>>> import xnat\n>>> session = xnat.connect('https://central.xnat.org', user=\"\", password=\"\")\n>>> session.projects['Sample_DICOM'].subjectswhen using IPython most functionality can be figured out by looking at the\navailable attributes/methods of the returned objects.CredentialsTo store credentials this module uses the .netrc file. This file contains login\ninformation and should be accessible ONLY by the user (if not, the module with\nthrow an error to let you know the file is unsafe).DocumentationThe official documentation can be found atxnat.readthedocs.orgThis documentation is a stub, but shows the classes and methods available.StatusCurrently we have basic support for almost all data on XNAT servers. Also it is\npossible to import data via the import service (upload a zip file). There is\nalso some support for working with the prearchive (reading, moving, deleting and\narchiving).Any function not exposed by the object-oriented API of xnatpy, but exposed in the\nXNAT REST API can be called via the generic get/put/post methods in the session\nobject.There is at the moment still a lack of proper tests in the code base and the documentation\nis somewhat sparse, this is a known limitation and can hopefully be addressed in the future."} +{"package": "xnat4tests", "pacakge-description": "Xnat4Tests runs a basic XNAT repository instance in a single Docker to be\nused for quick demonstrations on your workstation or integrated within test suites for\ntools that use XNAT\u2019s REST API.The XNAT container service plugin is installed by default and is configured to use\nthe same Docker host as the XNAT instance.Thehome/logs,home/work,build,archive,prearchivedirectories are\nmounted in from the host system from the$HOME/.xnat4tests/xnat_root/defaultdirectory\nby default. This can be useful for debugging and can be used to replicate the environment\nunder which containers run in within XNAT\u2019s container service.In addition to thestart_xnat,stop_xnatandrestart_xnatfunctions, which control the life-cycle of\nthe XNAT instance, there is also aconnectfunction that returns an XnatPy connection object to the test instanceInstallationDocker needs to be installed on your system, seeGet Dockerfor details.Xnat4Tests is available on PyPI so can be installed with$pip3installxnat4testsor include in your package\u2019stest_requiresif you are writing Python tests.UsageCommand line interfaceA test XNAT instance can be launched using the CLI with$xnat4testsstartThis will spin up an empty XNAT instance that can be accessed using the default admin\nuser account user=\u2019admin\u2019/password=\u2019admin\u2019. To add some sample data to play with you\ncan use theadd-datacommand$xnat4testsstart$xnat4testsadd-data'dummydicom'or in a single line$xnat4testsstart--with-data'dummydicom'By default, xnat4tests will create a configuration file at$HOME/.xnat4tests/configs/default.yaml.\nThe config file can be adapted to modify the names of the Docker images/containers used, the ports\nthe containers run on, and which directories are mounted into the container. Multiple\nconfigurations can be used concurrently by saving the config file to a new location and\npassing it to the base command, i.e.$xnat4tests--config/path/to/my/repo/xnat4tests-config.yamlstartTo stop or restart the running container you can usexnat4tests stopandxnat4tests restartcommands, respectively.Python APIIf you are developing Python applications you will typically want to use the API to\nlaunch the XNAT instance using thexnat4tests.start_xnatfunction. An XnatPy connection\nsession object can be accessed usingxnat4tests.connectand the instanced stopped\nafterwards usingstop_xnat.# Import xnat4tests functionsfromxnat4testsimportstart_xnat,stop_xnat,connect,Configconfig=Config.load(\"default\")# Launch the instance (NB: it takes quite while for an XNAT instance to start). If an existing# container with the reserved name is already running it is returned insteadstart_xnat(config)# Connect to the XNAT instance using XnatPy and run some testswithconnect(config)aslogin:PROJECT='MY_TEST_PROJECT'SUBJECT='MYSUBJECT'SESSION='MYSESSION'login.put(f'/data/archive/projects/MY_TEST_PROJECT')# Create subjectxsubject=login.classes.SubjectData(label=SUBJECT,parent=login.projects[PROJECT])# Create sessionlogin.classes.MrSessionData(label=SESSION,parent=xsubject)assert[p.nameforpin(config.xnat_root_dir/\"archive\").iterdir()]==[PROJECT]# Remove the container after you are done (not strictly necessary). To avoid# having to wait for XNAT to restart each time before you run your tests, you can# skip this line and start_xnat will attempt to use the instance that is already# runningstop_xnat(config)Alternatively, if you are using Pytest then you can set up the connection as\na fixture in yourconftest.py, e.g.importtempfilefrompathlibimportPathfromxnat4testsimportstart_xnat,stop_xnat,connect,Config@pytest.fixture(scope=\"session\")defxnat_config():tmp_dir=Path(tempfile.mkdtemp())returnConfig(xnat_root_dir=tmp_dir,xnat_port=9999,docker_image=\"myrepo_xnat4tests\",docker_container=\"myrepo_xnat4tests\",build_args={\"xnat_version\":\"1.8.5\",\"xnat_cs_plugin_version\":\"3.2.0\",},)@pytest.fixture(scope=\"session\")defxnat_uri(xnat_config):xnat4tests.start_xnat(xnat_config)xnat4tests.add_data(\"dummydicom\")yieldxnat_config.xnat_urixnat4tests.stop_xnat(xnat_config)"} +{"package": "xnat-access", "pacakge-description": "XNAT AccessThin XNAT REST API wrapper for Python 3 requests.Installationpip3install--userxnat-accessUsagefromxnat_accessimportXNATClientxnat=XNATClient('https://example.com/xnat','USERNAME','PASSWORD')url='projects/PROJECT/subjects/SUBJECT/experiments/EXPERIMENT/scans'scans=xnat.get_result(url)print(scans)# all functions# --------------------# xnat.get_request# xnat.get_json# xnat.get_result# xnat.get_file# xnat.download_file# xnat.put_request# xnat.upload_file# xnat.delete_request# xnat.open_session# xnat.close_session# xnat.session_is_open"} +{"package": "xnatbidsfns", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xnat-browser", "pacakge-description": "Browse a XNAT server from the terminal usingTextualandxnatpy.browsexnat-browser browse http://localhostqueryxnat-browser query http://localhost"} +{"package": "xnatclient", "pacakge-description": "XNAT Python clientPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: MIT licenseDocumentation:https://xnatclient.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-09-27)First release on PyPI."} +{"package": "xnat-dicom-cache", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xnatio", "pacakge-description": "# xnatio\nxnatio, which runs inside the of jupyter notebook, is a program designed for gathering and presenting useful summary statistics from the [XNAT](https://xnat.org) database. My vision for the project is that it will be highly customizable, allowing users to interface with data of any xsi:type\u2013even if xnatio does not understand what that data represents. There will also be a range of pre-selected queries to generate useful information.I am completing this project during my employment as a summer student in the Neuroinformatics Research Group at Washington University in St. Louis."} +{"package": "xnatjsession", "pacakge-description": "XNAT JSESSIONUtility functions for XNAT JSESSION"} +{"package": "xnat-nott", "pacakge-description": "XNAT helper functionsSimple set of XNAT helper functions targeted at Nottingham applications. These\nfunctions were originally built in to various XNAT applications where they\nacquired fixes and code aimed to work around XNAT oddities. It seemed best to\nmerge these into a combined set of helpers that can be re-used in different projectsTo doCould make functions into an object but might reduce flexibility"} +{"package": "xnatpytools", "pacakge-description": "XnatPy ToolsCollection of XPython tools for working with XNATFree software: MIT licenseDocumentation:https://xnatpytools.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-12-23)First release on PyPI."} +{"package": "xnattagger", "pacakge-description": "No description available on PyPI."} +{"package": "xnatum", "pacakge-description": "No description available on PyPI."} +{"package": "xnatuploader", "pacakge-description": "xnatuploaderA command-line tool for uploading batches of DICOMS to an XNAT server, building\non thexnatutilslibrary.UsageInitialising the spreadsheetScanning for filesUploading filesInterrupting and restartingFinding filesPath matchingXNAT hierarchy mappingMatching exampleChecking the spreadsheetInstallationTask SchedulerUpgradingUsagexnatuploader uses a 'two pass' approach to uploading files to an XNAT server.\nThe first pass scans a directory for files to upload, builds a list of\nthe files and their associated metadata and saves the list as a spreadsheet.\nThe second pass reads the spreadsheet and uploads the files to XNAT.On the second pass, the status of each file upload - whether it was successful,\nand any error messages if the upload failed - is written back to the spreadsheet.The second pass can be re-run using the updated spreadsheet - files which have\nbeen successfully uploaded already will be skipped, and files which were not\nuploaded on earlier runs will be re-attempted.The details of how xnatuploader gets metadata for each file are configured\nusing the spreadsheet: xnatuploader can write out a pre-initialised spreadsheet\nbefore you run the first pass.WindowsFrom the Start menu, select the Anaconda prompt. Once the Anaconda prompt is\nopened, you'll need to activate the conda environment in which xnatuploader\nwas installed:conda activate xnatuploaderInitialisationxnatuploader is run by typing commands at the Anaconda prompt or terminal:Initialising the spreadsheetxnatuploader init --spreadsheet spreadsheet.xlsxThis initialises a spreadsheet with a single worksheet with default\nconfiguration values. Details of the configuration are in thesection on finding files.Scanning for filesxnatuploader scan --spreadsheet spreadsheet.xlsx --dir data_filesThis scans the directorydata_filesfor DICOMs and builds a list of files\nand metadata, which is stored in the spreadsheet as a new worksheet named\n'Files'.Uploading filesxnatuploader upload --spreadsheet spreadsheet.xlsx --dir data_files --project Test001 --server https://xnat.institution.edu/This command will prompt you for your username and password on the XNAT server,\nread all the files from the spreadsheet and attempt to upload them.The files will be uploaded to the project specified, using XNAT's hierarchy:Subject (research participant or patient)Session (experiment or visit)Dataset (a scan)A Session can have multiple datasets, and a dataset will typically have many\nindividual DICOM files.The subject, session and dataset are based on the metadata values are extracted\nin the scanning pass. See theFinding filessection below for more details and\nconfiguration instructions.The upload command needs to know both the URL of the XNAT server and a project\nID on the server to which the scans will be added. The project must already\nexist, and you must have the right access level to add scans to it.You can also configure the XNAT URL and project ID in the spreadsheet - see\nthe screenshot below for an example. If you specify an XNAT server or project\nID as options on the command line, these values will be used in preference to\nthe values in the spreadsheet.Interrupting and restartingWhen a file can't be uploaded due to a network error, or the integrity check for\nthe upload fails, this error will be recorded in the spreadsheet and a warning\nwill be printed to the command line. If you re-run the upload, the program will\ntry to re-upload those files which didn't successfully upload on earlier runs.While uploading is in progress, two progress bars will be shown on the command\nline. One shows the progress at a high level, with a step for every dataset in\nthe upload (note that a single patient may have more than one dataset). The\nsecond progress bar shows a step for every file in the current dataset.You can interrupt the upload by pressing Ctrl-C. If you do this, the program\nwill prompt you to confirm whether you really want to stop. If you confirm,\nthe current progress will be written back to the spreadsheet, and all files\nwhich haven't yet been uploaded will have a status written to indicate that\nthe upload was interrupted. If you re-run the upload with the same spreadsheet,\nit will continue from where it was interrupted.Finding filesWhenxnatupload scanis run, it scans the specified directory for files to\nupload. The scan looks for files at every level of the subdirectories within\nthe directory, and tries to match values in the filepaths which can be used\nto determine how the files should be uploaded to XNAT.Here's an example of a directory structure with scans for two patients.\nThe top-level directories have the naming convention SURNAME^GIVENNAME-ID.\nInside each patient's directory is a directory named for the date of their\nvisit in YYYYMMDD format, and inside those is one or more directories for\neach type of scan they recieved on the visit. These directories contain\nthe actual DICOM files for the scan.Doe^John-0001/20200312/Chest CT/scan0000.dcm\nDoe^John-0001/20200312/Chest CT/scan0001.dcm\nDoe^John-0001/20200312/Chest CT/scan0002.dcm\nRoe^Jane-0342/20190115/Head CT/scan0000.dcm\nRoe^Jane-0342/20190115/Head CT/scan0001.dcm\nRoe^Jane-0342/20190115/Head CT/scan0002.dcm\nRoe^Jane-0342/20190115/Head CT/scan0003.dcm\nRoe^Jane-0342/20200623/Head CT/scan0000.dcm\nRoe^Jane-0342/20200623/Head CT/scan0001.dcm\nRoe^Jane-0342/20200623/Head CT/scan0002.dcm\nRoe^Jane-0342/20200623/Neck CT/scan0000.dcm\nRoe^Jane-0342/20200623/Neck CT/scan0001.dcm\nRoe^Jane-0342/20200623/Neck CT/scan0002.dcm\nRoe^Jane-0342/20200623/Neck CT/scan0003.dcmTo transform these filepaths into XNAT hierarchy values, we need to tell\nxnatuploader to get the ID from the top-level directory and the scan type from\nthe name of the directories containing the DICOM files (\"Chest CT\", \"Head CT\"\nand so on).We also need to get the session date. This could be done using the second\nlevel of directories, but it's safer to get it from the DICOM\nmetadata, which will have a value StudyDate with the date of the scan.Here is a configuration worksheet which will get the correct XNAT values\nfrom this directory layout.Configuration for inferring the XNAT values is in two sections, \"Paths\" and\n\"Mappings\", which correspond to two steps:\"Paths\" tells the script how to matching patterns against the filepath to create values\"Mappings\" assigns those values, or DICOM metadata values, to the XNAT hierarchyPath matchingThe \"Paths\" section of the config is one or more lists of patterns to be matched\nagainst paths. Each set of patterns starts with a label - in the example above,\nthe label is \"Nested\". Each cell to the right of the label will be matched\nagainst one or more directory names in each of the filepaths, from left to\nrightIf all matches are successful, that path will be marked as a row\nto be uploaded in the spreadsheet, and the values captured from the path will\nbe assigned to the XNAT hierarchy values according to the \"Mappings\" section\nof the config worksheet.The parts of the patterns in curly brackets like{SubjectName}are used to\ncapture values. Patterns which are in all caps, such as{YYYY}or{II},\nwill only match numbers with the specified number of digits. All other\npatterns, for example{SubjectName}, will match any sequence of characters.There are two special patterns,*and**.*matches a single directory\nwith any name, and**matches one or more directories with any name.**lets you construct a pattern which will match files which might be nested at\ndifferent levels for different patients.Note: if one set of patterns isn't flexible enough to match all the ways in\nwhich scans are stored in the directory, you can add extra patterns as new\nrows in the spreadsheet. Each set of patterns needs a unique label.\nSets of patterns will be matched in order from the top, and the first one\nwhich succeeds will be used.XNAT hierarchy mappingThe \"Mapping\" section tells the script how to build the three XNAT hierarchy\nvalues, Subject, Session and Dataset, based on values captured from the paths\nand/or metadata fields read from the DICOM files. In the example, we're setting\nthe Subject to theIDvalue, the Session to theStudyDatevalues extracted\nfrom the DICOMs, and the Dataset to theDirectoryvalue.Matching exampleHere's a step-by-step illustration of how the set of patterns in the example\nis matched against a filepath:Doe^John-0001/20200312/Chest CT/scan0000.dcm{SubjectName}-{ID}matchesDoe^John-0001, setting the valuesSubjectNameto \"Doe^John\" andIDto \"0001\"**matches20200312, and does not set any values{Directory}matchesChest CTand sets the valueDirectoryto \"Chest CT\"{filename}.dcmmatchesscan0000.dcmand sets the valuefilenameto \"0001\"The XNAT hierarchy values are then built according to the rules in the\n\"Mapping\" section:Subjectis set to the value stored inID:0001Sessionis set to the value extracted from the DICOM metadata fieldStudyDateDatasetis set to the value stored inDirectory:Chest CTNote that not every value captured from the path needs to be used in \"Mapping\",\nasSubjectNameandfilenameare ignored.The filename for the purposes of uploading will be automatically generated from\nthe path itself.Checking the spreadsheetBy default, all files which match a pattern are marked as selected for upload\nin the spreadsheet. Before uploading, you can edit the spreadsheet to\ndeselect files or groups of files which shouldn't be uploaded.By default, files for which no match succeeds won't be written to the\nspreadsheet. You can run a scan with the--unmatchedflag, which will\nwrite a row for every file whether or not the match succeeds:xnatuploader scan --spreadsheet spreadsheet.xlsx --dir data_files --unmatchedThis can be useful for figuring out why files aren't matching patterns.InstallationIf you're on Windows, you'll need to installAnaconda, which will install the Python programming language and environment manager\non your PC.Open the Anaconda prompt via the Start menu.If you're on a Mac or Linux, you can also install Conda using the relevant\ninstaller, and just use a terminal for the rest of the installation instructions.conda create -n xnatuploaderThis will create a separate Python environment in which we'll install\nxnatuploader. Answer 'Y' when it prompts you to proceed.conda activate xnatuploaderThis activates the Python environment you've just createdpip install xnatuploaderThis will download and install the latest version of xnatuploader. To check that\neverything has worked after the upload and installation has finished, type the\nfollowing:xnatuploader --helpYou should get a message like the following:usage: XNAT batch uploader [-h] [--dir DIR] [--spreadsheet SPREADSHEET]\n [--server SERVER] [--project PROJECT]\n [--loglevel LOGLEVEL] [--debug] [--logdir LOGDIR]\n [--test] [--unmatched] [--overwrite]\n {init,scan,upload,help}\n\npositional arguments:\n {init,scan,upload,help}\n Operation\n\noptional arguments:\n -h, --help show this help message and exit\n --dir DIR Base directory to scan for files\n --spreadsheet SPREADSHEET\n File list spreadsheet\n --server SERVER XNAT server\n --project PROJECT XNAT project ID\n --loglevel LOGLEVEL Logging level\n --debug Debug mode: only attempt to match 10 patterns and\n generates a lot of debug messages\n --logdir LOGDIR Directory to write logs to\n --test Test mode: don't upload, just log what will be\n uploaded\n --unmatched Whether to include unmatched files in list\n --overwrite Whether to overwrite files which have already been\n uploadedTask schedulerxnatuploader can be run by the Windows Task Scheduler if it's wrapped in the\nfollowing batch file (replace USER_NAME with your own)call C:\\Users\\USER_NAME\\Anaconda3\\Scripts\\activate.bat\ncall conda activate xnatuploader\ncall xnatuploader upload --spreadsheet spreadsheet.xlsx --dir dirNote that this will only work if the underlying xnat library can authenticate\nusing credentials stored in a _netrc or .netrc file. Seethe xnatpy documentationfor instructions on how to set this up.Alternately, if you run xnatuploader manually and authenticate, it will keep\nan authentication token on your machine for a time period (controlled by the\npolicy of your XNAT server, typically 72 hours). Once you've authenticated\nmanually, a task scheduler job should work until the token expires.UpgradingTo get the latest version of xnatuploader, type the following (at the Anaconda\nprompt or terminal):pip install --upgrade xnatuploader"} +{"package": "xnatutils", "pacakge-description": "Xnat-utils is a collection of scripts for conveniently up/downloading and\nlisting data on/from XNAT based on theXnatPy package.Optional DependenciesThe following converters are required for automatic conversions of downloaded images (using the\n\u2018\u2013convert_to\u2019 and \u2018\u2013converter\u2019 options)dcm2niix (https://github.com/rordenlab/dcm2niix)MRtrix 3 (http://mrtrix.readthedocs.io/en/latest/)InstallationInstall Python (>=3.4)While many systems (particularly in research contexts) will already have Python 3 installed (note that Python 2\nis not sufficient), if your workstation doesn\u2019t here are some basic instructions on how to install it.macOSmacOS ships with it\u2019s own, slightly modified, version of Python, which it uses\nin some applications/services. For the most part it is okay for general use\nbut in some cases, such as withxnat-utils, the modifications can cause\nproblems. To avoid these I recommend installing an unmodified version of Python\nfor use in your scientific programs using Homebrew (http://brew.sh). To do this\nfirst install Homebrew:/usr/bin/ruby -e \"$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)\"then install Python with:brew install python3If everything has gone well, when you type:which python3it should come back with:/usr/local/bin/python3If it doesn\u2019t or your run into any problems follow the instructions you receive\nwhen you run:brew doctorNote that these instructions are just recommendations so you don\u2019t have to\nfollow all of them, just the ones that are likely to be related to your\nproblem.WindowsDownload the version of Python for Windows using the most appropriate installer\nfor Python (>=3.4), herehttps://www.python.org/downloads/windows/.Linux/UnixPython3 is most likely already installed but if it isn\u2019t it is best to install\nit using your package manager.Install pipPip is probably already be installed by default with your Python package so\ncheck whether it is installed first:pip3 --versionNoting that it should be in /usr/local/bin if you are using Homebrew on macOS.If pip is not installed you can install it by downloading the following script,https://bootstrap.pypa.io/get-pip.pyand:python3 Install XnatUtils packageThe XnatUtils source code can be downloaded (or cloned using git) fromhttps://github.com/MonashBI/xnatutils.git. To install itcdto to the directory you have downloaded and run:pip3 install xnatutilsIf you get permission denied errors you may need to usesudo,\nor if you don\u2019t have admin access then you can install it in your\nuser directory with the--userflag.:pip3 install --user xnatutilsI have had some difficulty with the installation ofprogressbar2as there is a\nconflict with theprogressbarpackage (they both produce packages calledprogressbar). In this case it is probably a good idea to install xnat-utils\nin a virtual environment (https://virtualenv.readthedocs.io/en/latest/).AuthenticationThe first time you use one of the utilities you will be prompted for the address\nof the server would like to connect to, in addition to your username and\npassword. By default a alias token for these credentials will be stored in\na ~/.netrc file with the following format (with permissions set to 600 on the file):machine \nuser \npassword If you don\u2019t want these credentials stored, then pass the \u2018\u2013no_netrc\u2019\n(or \u2018-n\u2019) option.If you have saved your credentials in the ~/.netrc file, subsequent calls won\u2019t require\nyou to provide the server address or username/password until the token\nexpires (if you don\u2019t want deal with expiring tokens you can just save your username/password\nin the ~/.netrc file instead, however, please be careful with important passwords). To reset\nthe saved credentials provide--serveroption again with the full server address\nincluding the protocol (e.g. \u2018https://\u2019) or edit the ~/.netrc file directly.To connect to an additional XNAT server, provide the new server address via the--serveroption.\nCredentials for this server will be saved alongside the credentials for your previously saved\nservers. If the--serveroption is not provided the first server in the file will be used. To\nused the save credentials for a secondary server you only need to provide as of the secondary server\naddress to--serverto distinguish it from the other saved servers. For example given the following\nsaved credentials in a ~/.netrc file:machine xnat.myuni.edu\nuser myusername\npassword mypassword\nmachine xnat-dev.myuni.edu\nuser mydevusername\npassword mydevpasswordthen:$ xnat-ls -s dev MYPROJECTwill be enough to select the development server from the saved credentials list.UsageSix commands will be installedxnat-get - download scans and resourcesxnat-put - upload scans and resources (requires write privileges to project)xnat-ls - list projects/subjects/sessions/scansxnat-rename - renames an XNAT sessionxnat-varget - retrieve a metadata field (including \u201ccustom variables\u201d)xnat-varput - set a metadata field (including \u201ccustom variables\u201d)Please see the help for each tool by passing it the \u2018-h\u2019 or \u2018\u2013help\u2019 option.Help on Regular ExpressionsThe regular expression syntax used byxnat-getandxnat-lsis fully defined\nhere,https://docs.python.org/2/library/re.html. However, for most basic use\ncases you will probably only need to use the \u2018.\u2019 and \u2018*\u2019 operators.\u2018.\u2019 matches any character so the pattern:MRH060_00._MR01will matchMRH060_001_MR01\nMRH060_002_MR01\nMRH060_003_MR01\nMRH060_004_MR01\nMRH060_005_MR01\nMRH060_006_MR01\nMRH060_007_MR01\nMRH060_008_MR01\nMRH060_009_MR01The \u2018*\u2019 matches 0 or more repeats of the previous character, which is most\nuseful in conjunction with the \u2018.\u2019 character to match string of wildcard\ncharacters, e.g.:MRH060.*will match all subjects/sessions in the MRH060 project.Note, that when using regular expressions that use \u2018*\u2019 on the command line you\nwill need to enclose them in single quotes to avoid the default wilcard file search, e.g.:$ xnat-ls 'MRH099.*'Probably the only other syntax that will prove useful is the\n\u2018(option1|option2|\u2026)\u2019. For example:MRH060_00(1|2|3)_MR01will matchMRH060_001_MR01\nMRH060_002_MR01\nMRH060_003_MR01For more advanced syntax please refer to the numerous tutorials on regular\nexpressions online."} +{"package": "xnbs", "pacakge-description": "nlitDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nnlit--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallnlitnbdev# activate conda environment$condaactivatenlit# make sure the nlit package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the nlit package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/nlit.gitor fromconda$condainstall-cdsm-72nlitor frompypi$pipinstallnlitDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find\npackage manager specific guidelines oncondaandpypirespectively."} +{"package": "xnbtd", "pacakge-description": "xNBTDxNBTD est une application de gestion pour entreprise de livraison.\nElle facilite la gestion des tourn\u00e9es et des plannings.ExigencesPython 3.xDjango 3.xUn serveur web pour h\u00e9berger l'applicationInstallationPour installer xNBTD, suivez ces \u00e9tapes (pour les syst\u00e8mes Linux) :Cr\u00e9ez le r\u00e9pertoire :mkdir /opt/eldertekAcc\u00e9dez au r\u00e9pertoire :cd /opt/eldertekClonez le d\u00e9p\u00f4t :git clone https://github.com/eldertek/xnbtd && cd xnbtdInstallez Poetry :make install-poetryInstallez xnbtd :make installVoil\u00e0 ! Vous devez maintenant d\u00e9ployer l'application.Vous devez ensuite la d\u00e9ployer, voir ci-dessous.D\u00e9ploiementPour d\u00e9ployer xNBTD dans un environnement de production, suivez ces \u00e9tapes :Installez un serveur web pr\u00eat pour la production, tel que Nginx ou Apache.Configurez le serveur web pour servir l'application Django.Utilisez un gestionnaire de processus, tel que Gunicorn ou uWSGI, pour ex\u00e9cuter l'application Django.ContributionNous accueillons les contributions \u00e0 xNBTD ! Si vous souhaitez contribuer, veuillez suivre ces \u00e9tapes :Fork le d\u00e9p\u00f4tCr\u00e9ez une nouvelle branche pour vos modificationsEffectuez vos modifications et poussez-les vers votre forkSoumettez une pull request pour examenSupportSi vous avez besoin d'aide avec xNBTD, veuillez ouvrir une issue sur le d\u00e9p\u00f4t. Nous ferons de notre mieux pour vous aider.Droits d'auteur (c) 2023 Andr\u00e9 Th\u00e9o LAURET - Tous droits r\u00e9serv\u00e9s"} +{"package": "xncml", "pacakge-description": "# xncml![Read the Docs](https://img.shields.io/readthedocs/xncml)\n![PyPI](https://img.shields.io/pypi/v/xncml)Tools for opening and manipulating NcML (NetCDF Markup Language) files with/for xarray.These tools allow you to modify NcML by:Adding or removing global attributesAdding or removing variable attributesRemoving variables and dimensionsand read NcML files intoxarray.Datasetobjects:`python import xncml ds =xncml.open_ncml(\"large_ensemble.ncml\")`See [documentation] for more information.## Installationxncml can be installed from PyPI with pip:`bash pip install xncml `[documentation]:https://xncml.readthedocs.io"} +{"package": "xnd", "pacakge-description": "OverviewThexndmodule implements a container type that maps most Python values\nrelevant for scientific computing directly to typed memory.Whenever possible, a single, pointer-free memory block is used.xndsupports ragged arrays, categorical types, indexing, slicing, aligned\nmemory blocks and type inference.Operations like indexing and slicing return zero-copy typed views on the data.Importing PEP-3118 buffers is supported.Linkshttps://github.com/plures/http://ndtypes.readthedocs.io/en/latest/http://xnd.readthedocs.io/en/latest/"} +{"package": "xndzkteste", "pacakge-description": "UNKNOWN"} +{"package": "xnemogcm", "pacakge-description": "xnemogcmInterface to open NEMO ocean global circulation model output dataset and create a xgcm grid.\nNEMO 3.6, 4.0, and 4.2.0 are tested and supported. Any version between 3.6 and 4.2.0 should work,\nbut in case of trouble,please open an issue.UsagefrompathlibimportPathfromxnemogcmimportopen_nemo_and_domain_cfgds=open_nemo_and_domain_cfg(nemo_files='/path/to/output/files',domcfg_files='/path/to/domain_cfg/mesh_mask/files')# Interface with xgcmfromxnemogcmimportget_metricsimportxgcmgrid=xgcm.Grid(ds,metrics=get_metrics(ds),periodic=False)See theexampledirectory for some jupyter notebook examples.\nxnemocgm is able to process xarray.Datasets (e.g. they could be retrieved from a remote server),\nand can get information of the variables grid points with multiple options\n(seeexample/open_process_files.ipynb.Notexnemogcmis capable or recombining the domain_cfg and mesh_mask files output\nby multiple processors,\nthe recombining tool from the NEMO toolbox is thus not needed here, see\ntheexample/recombing_mesh_mask_domain_cfg.ipynbInstallationInstallation via pip:pip3installxnemogcmInstallation via conda:condainstall-cconda-forgexnemogcmRequirements for devWe usepoetryto set up a virtual environment containing all\nneeded packages to run xnemogcm and the tests.\nTo install all the dependencies, typepoetry install --with test,devafter cloning the directory. This will create a new virtual environment.\nTypingpoetry shellin the package directory will activate the virtual environment.About test dataTest data are based on the GYRE configuration, and produced by another repository:rcaneill/xnemogcm_test_data.\nTesting is built in a way that it is quite easy to add other nemo version to test.About notebooks examplesSources for the notebooks are located insrc_example. This is where to add / modify the\nexamples. A github action is set to automatically build the notebook according to\nthe latest version of the code, and publish them toexamplewhen commiting to master branch.What's newv0.4.2 (2023-08-07)Allow additional dimension names occurring when variables on inner grid are diagnosed, e.g.x_grid_U_innerorx_grid_U.Add coordinates into the DataArraysAdd some standard names and units in domcfgv0.4.1 (2023-03-29)Allow to open files if time bounds are missingMinor bug correction for nemo 3.6Add nemo 3.6 and 4.2.0 test dataUpdate code to support nemo 3.6 and 4.2.0v0.4.0 (2022-12-08)Optimize speedAdd option to decode grid type from attributesShift from pipenv and setupy.py to poetryRefactor data test to allow testing of multiple version of NEMOv0.3.4 (2021-06-15)Adding some exampleBug fixesAdd option to compute extra scale factorsv0.3.2 - v0.3.3 (2021-05-05)By default adds the lat/lon/depth variables of domcfg as coordinatesv0.3.1 (2021-05-04)Minor bug fix when mergingbetter squeezing of time in domcfg + nemo v3.6 compatibilityv0.3.0 (2021-04-13)Cleaning the backendRemoving the saving options (that were useless and confusing)Minor bug fixesTested with realistic regional configurationv0.2.3 (2021-03-15)Support for surface only filesReshaping the data files for the tests (dev)"} +{"package": "xnester", "pacakge-description": "No description available on PyPI."} +{"package": "xnesterx", "pacakge-description": "UNKNOWN"} +{"package": "xnet", "pacakge-description": "Xnet - Just like Xmas, but on your networks!xnetis a framework and a collection of command-line\ntools utilizing microthreads (from the python library gevent).All tools developed in Xnet have a common set of command-line parameters for parallelization and other functionality, which is provided by the framework. Try the\u2013helpoption for each tool for more details. Reading the source code of some existing tool should suffice to produce new tools under the same flag.Current list of tools:xnet (meta-tool)tcpstatenetcatsresolviprangeiissnsslinfowebgetxnet install instructionsDebian 6Development packages are needed to build a newer gevent\nthan what debian ships with.$ sudo apt-get install gcc\n$ sudo apt-get install libevent-dev\n$ sudo apt-get install python-dev\n$ sudo apt-get install python-pip\n$ sudo apt-get install python-opensslOptionally, if you want to contain xnet in a local directory\ninstead of making a system installation:$ sudo apt-get install python-virtualenv\n$ virtualenv pyenv && cd pyenv && . bin/activateFinally, install gevent and xnet:$ pip install gevent==0.13.8\n$ pip install xnetDebian 7The same procedure as for Debian 6 but we can use the python-gevent\npackage right away instead of compiling our own.$ sudo apt-get install python-pip\n$ sudo apt-get install python-openssl\n$ sudo apt-get install python-geventOptionally, if you want to contain xnet in a local directory\ninstead of making a system installation:$ sudo apt-get install python-virtualenv\n$ virtualenv pyenv && cd pyenv && . bin/activateFinally, install xnet:$ pip install xnetBacktrack 5R2$ sudo apt-get install python-dev\n$ sudo apt-get install python-openssl\n$ sudo apt-get install python-pip\n$ sudo apt-get install libevent-devOptionally, if you want to contain xnet in a local directory\ninstead of making a system installation:$ sudo apt-get install python-virtualenv\n$ virtualenv pyenv && cd pyenv && . bin/activateFinally, install gevent and xnet:$ pip install gevent==0.13.8\n$ pip install xnetOSXGevent 0.13.8 misbehaves under OSX, but the development release 1.0rc2 works.\nThis must be compiled so Xcode is a requirement. The list below may be incomplete.Optional if you want to contain xnet in a local directory\ninstead of making a system installation.$ sudo port install py-virtualenv\n$ virtualenv pyenv && cd pyenv && . bin/activateAnd then gevent.$ pip install cython -e git://github.com/surfly/gevent.git@1.0rc2#egg=gevent"} +{"package": "x-net-django-color-field", "pacakge-description": "X-Net Django Color FieldA color field for Django models and forms.Installationpip install x_net_django_color_fieldAddx_net_django_color_fieldto INSTALLED_APPSUsageConsider the following model using aColorFieldfromdjango.dbimportmodelsfromx_net_django_color_field.modelsimportColorFieldclassCustomModel(models.Model):color=ColorField(verbose_name=\"Color\")Consider the following form using aColorFieldfromdjango.formsimportformsfromx_net_django_color_field.formsimportColorFieldclassCustomForm(forms.Form):color=ColorField(label=\"Color\")"} +{"package": "x-net-django-email-template", "pacakge-description": "X-Net Django Email TemplateThis is the default email template that we use in ourcompanyfor sending emails with django (registration, password forgot, eg.)Installationpip installx_net_django_email_templateAddx_net_django_email_templateto INSTALLED_APPSUsageWhen extends the default.html you can overwrite the blocks:{% extends \"email/default.html\" %}\n\n{% load html_email i18n %}\n\n{% block title %}Title{% endblock %}\n{% block header_title %}Header title{% endblock %}\n\n{% block main %}

            This is an example of text.

            Click me{% endblock %}\n\n{% block footer %}

            {% trans \"This is an automatically generated email, please do not reply to this message.\" %}

            {% endblock %}TemplatetagsWith thefull_statictemplate tag you can insert absolute urls in the email template.{% load html_email %}CompatibilityYou can inline css to this HTML template with theX-Net Email Inliner.\nWe have test this HTML template with the following email client:Apple Mail 13Outlook 2007Outlook 2010Outlook 2013Outlook 2013 with 120 DPIOutlook 2016 (macOS)Outlook 2016Outlook 2016 with 120 DPIOutlook 2019Outlook 2019 with 120 DPIOutlook Office 365ThunderbirdGmail AppSamsung MailMail/iOSOutlook AndroidOutlook iOSOffice 365 (Browser)Gmail (Browser)GMX.de (Browser)"} +{"package": "x-net-email-css-inliner", "pacakge-description": "X-Net Email CSS InlinerTheX-Net Email CSS Inlineris a HTML email inliner inspired by theZURB CSS inliner.Inlining is the process of prepping an HTML email for delivery to email clients\nSome email clients strip out your email's styles unless they are written inline\nwith style tags. Here's what the inliner does:Inlining CSS:All of your CSS is embedded directly into the HTML as style attributes on each tag.CSS inside a@mediablock can't be inlined, so it's put in a
            XPLANT

            It makes good things for you

          • Home in red
          • Things in green
          • About in blue

          This page has ben generated with python'sxplant.html.html5_plant.

          Enjoy pure pythonic1:1 python -> xmltranslation.


          Did you ever had hard times with learningHTML template language?

          It's a crude way to mix HTML with any logics like iterators, classes, conditions.


          You know what? You already have all of it (and much more) inpython!

          HTML templates is a blind alley. HTML does not miss server-side scripting.

          The python miss a good HTML generator not vice versa.

          "} +{"package": "xp-last", "pacakge-description": "No description available on PyPI."} +{"package": "xplat", "pacakge-description": "Xplat (splat) provides a consistent api for common functions that are\nnot standard across platforms.APIget_username():from xplat import xplat\nxplat.get_username()"} +{"package": "xplay", "pacakge-description": "No description available on PyPI."} +{"package": "xplenty", "pacakge-description": "Xplenty Python WrapperThe Xplenty PY is a python artifact that provides a simple wrapper for theXplenty REST API. To use it, create an XplentyClient object and call its methods to access the Xplenty API. This page describes the available XplentyClient methods.InstallationVia pip:pipinstallxplentyCreate an Xplenty Client ObjectPass your account ID and API key to the XplentyClient constructor.fromxplentyimportXplentyClientaccount_id=\"MyAccountID\"api_key=\"V4eyfgNqYcSasXGhzNxS\"client=XplentyClient(account_id,api_key)Create a ClusterThis method creates a new cluster. A cluster is a group of machines (\"nodes\") allocated to your account. The number of nodes in the cluster is determined by the \"nodes\" value that you supply to the call. While the cluster is active, only your account's users can run jobs on the cluster.\nYou will need to provide an active cluster when starting a new job. Save the cluster ID value returned in the response \"id\" field. You will use the value to refer to this cluster in subsequent API calls.cluster_type=\"production\"nodes=2name=\"New Cluster #199999\"description=\"New Cluster's Description\"terminate_on_idle=Falsetime_to_idle=3600cluster=client.create_cluster(cluster_type,nodes,name,description,terminate_on_idle,time_to_idle)printcluster.idList All ClustersThis method returns the list of clusters that were created by users in your account.\nYou can use this information to monitor and display your clusters and their statuses.clusters=client.clustersprint\"Number of clusters:\",len(clusters)forclusterinclusters:printcluster.id,cluster.name,cluster.created_atGet Cluster InformationThis method returns the details of the cluster with the given ID.id=85cluster=client.get_cluster(id)printcluster.nameTerminate a ClusterThis method deactivates the given cluster, releasing its resources and terminating its runtime period. Use this method when all of the cluster's jobs are completed and it's no longer needed. The method returns the given cluster's details, including a status of \"pending_terminate\".id=85cluster=client.terminate_cluster(id)printcluster.statusRun a JobThis method creates a new job and triggers it to run. The job performs the series of data processing tasks that are defined in the job's package. Unless the job encounters an error or is terminated by the user, it will run until it completes its tasks on all of the input data. Save the job ID value returned in the response \"id\" field. You will use the value to refer to this job in subsequent API calls.cluster_id=83package_id=782variables={}variables['OUTPUTPATH']=\"test/job_vars.csv\"variables['Date']=\"09-10-2012\"job=client.add_job(cluster_id,package_id,variables)printjob.idList All JobsThis method returns information for all the jobs that have been created under your account.jobs=client.jobsforjobinjobs:printjob.id,job.progress,job.statusGet Job InformationThis method retrieves information for a job, according to the given job ID.job_id=235job=client.get_job(job_id)printjob.statusTerminate a JobThis method terminates an active job. Usually it's unnecessary to request to terminate a job, because normally the job will end when its tasks are completed. You may want to actively terminate a job if you need its cluster resources for a more urgent job, or if the job is taking too long to complete.job_id=235job=client.stop_job(job_id)printjob.statusList All PackagesThis method returns the list of packages that were created by users in your account.\nYou can use this information to display your packages and their properties.packages=client.packagesprint\"Number of packages:\",len(packages)forpackageinpackages:printpackage.id,package.name,package.created_atGet Package InformationThis method returns the details of the package with the given ID.id=85package=client.get_package(id)printpackage.nameContributingFork itCreate your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create new Pull RequestLicenseReleased under theMIT license."} +{"package": "xplenty3", "pacakge-description": "## Xplenty Python 3 WrapperUpdated the Python 2 [xplenty.py](https://github.com/xplenty/xplenty.py) using[`2to3`](https://docs.python.org/2/library/2to3.html)The Xplenty PY is a python artifact that provides a simple wrapper for the [Xplenty REST API](https://github.com/xplenty/xplenty-api-doc). To use it, create an XplentyClient object and call its methods to access the Xplenty API. This page describes the available XplentyClient methods.### InstallationVia pip:```bashpip install xplenty```### Create an Xplenty Client ObjectPass your account ID and API key to the XplentyClient constructor.```pythonfrom xplenty import XplentyClientaccount_id =\"MyAccountID\"api_key = \"V4eyfgNqYcSasXGhzNxS\"client = XplentyClient(account_id,api_key)```### Create a ClusterThis method creates a new cluster. A cluster is a group of machines (\"nodes\") allocated to your account. The number of nodes in the cluster is determined by the \"nodes\" value that you supply to the call. While the cluster is active, only your account's users can run jobs on the cluster.You will need to provide an active cluster when starting a new job. Save the cluster ID value returned in the response \"id\" field. You will use the value to refer to this cluster in subsequent API calls.```pythoncluster_type = \"production\"nodes = 2name =\"New Cluster #199999\"description =\"New Cluster's Description\"terminate_on_idle = Falsetime_to_idle = 3600cluster = client.create_cluster(cluster_type, nodes, name, description, terminate_on_idle, time_to_idle)print cluster.id```### List All ClustersThis method returns the list of clusters that were created by users in your account.You can use this information to monitor and display your clusters and their statuses.```pythonclusters = client.clustersprint \"Number of clusters:\",len(clusters)for cluster in clusters:print cluster.id, cluster.name, cluster.created_at```### Get Cluster InformationThis method returns the details of the cluster with the given ID.```pythonid = 85cluster = client.get_cluster(id)print cluster.name```### Terminate a ClusterThis method deactivates the given cluster, releasing its resources and terminating its runtime period. Use this method when all of the cluster's jobs are completed and it's no longer needed. The method returns the given cluster's details, including a status of \"pending_terminate\".```pythonid = 85cluster = client.terminate_cluster(id)print cluster.status```### Run a JobThis method creates a new job and triggers it to run. The job performs the series of data processing tasks that are defined in the job's package. Unless the job encounters an error or is terminated by the user, it will run until it completes its tasks on all of the input data. Save the job ID value returned in the response \"id\" field. You will use the value to refer to this job in subsequent API calls.```pythoncluster_id = 83package_id = 782variables = {}variables['OUTPUTPATH']=\"test/job_vars.csv\"variables['Date']=\"09-10-2012\"job = client.add_job(cluster_id, package_id, variables)print job.id```### List All JobsThis method returns information for all the jobs that have been created under your account.```pythonjobs = client.jobsfor job in jobs:print job.id , job.progress , job.status```### Get Job InformationThis method retrieves information for a job, according to the given job ID.```pythonjob_id = 235job = client.get_job(job_id)print job.status```### Terminate a JobThis method terminates an active job. Usually it's unnecessary to request to terminate a job, because normally the job will end when its tasks are completed. You may want to actively terminate a job if you need its cluster resources for a more urgent job, or if the job is taking too long to complete.```pythonjob_id = 235job = client.stop_job(job_id)print job.status```### List All PackagesThis method returns the list of packages that were created by users in your account.You can use this information to display your packages and their properties.```pythonpackages = client.packagesprint \"Number of packages:\",len(packages)for package in packages:print package.id, package.name, package.created_at```### Get Package InformationThis method returns the details of the package with the given ID.```pythonid = 85package = client.get_package(id)print package.name```## Contributing1. Fork it2. Create your feature branch (`git checkout -b my-new-feature`)3. Commit your changes (`git commit -am 'Add some feature'`)4. Push to the branch (`git push origin my-new-feature`)5. Create new Pull Request## LicenseReleased under the [MIT license](http://www.opensource.org/licenses/mit-license.php)."} +{"package": "xplinter", "pacakge-description": "XplinterAn easy-to-use XML shredder"} +{"package": "xplogger", "pacakge-description": "xploggerLogging utility for ML experimentsWhyPeople use different tools for logging experimental results -Tensorboard,Wandbetc to name a few. Working with different collaborators, I will have to switch my logging tool with each new project. So I made this simple tool that provides a common interface to logging results to different loggers.Installationpip install \"xplogger[all]\"If you want to use only the filesystem logger, usepip install \"xplogger\"Install from sourcegit clone git@github.com:shagunsodhani/xplogger.gitcd xploggerpip install \".[all]\"Alternatively,pip install \"git+https://git@github.com/shagunsodhani/xplogger.git@master#egg=xplogger[all]\"If you want to use only the filesystem logger, usepip install .orpip install \"git+https://git@github.com/shagunsodhani/xplogger.git@master#egg=xplogger\".Documentationhttps://shagunsodhani.github.io/xploggerUseMake alogbook_config:import xplogger.logbook\nlogbook_config = xplogger.logbook.make_config(\n logger_dir = ,\n wandb_config = ,\n tensorboard_config = ,\n mlflow_config = )The API formake_configcan be accessedhere.Make aLogBookinstance:logbook = xplogger.logbook.LogBook(config = logbook_config)Use thelogbookinstance:log = {\n \"epoch\": 1,\n \"loss\": 0.1,\n \"accuracy\": 0.2\n}\nlogbook.write_metric(log)The API forwrite_metriccan be accessedhere.NoteIf you are writing to wandb, thelogmust have a key calledstep. If yourlogalready captures thestepbut as a different key (sayepoch), you can pass thewandb_key_mapargument (set as{epoch: step}). For more details, refer the documentationhere.If you are writing to mlflow, thelogmust have a key calledstep. If yourlogalready captures thestepbut as a different key (sayepoch), you can pass themlflow_key_mapargument (set as{epoch: step}). For more details, refer the documentationhere.If you are writing to tensorboard, thelogmust have a key calledmain_tagortagwhich acts as the data Identifier and another key calledglobal_step. These keys are describedhere. If yourlogalready captures these values but as different key (saymodeformain_tagandepochforglobal_step), you can pass thetensorboard_key_mapargument (set as{mode: main_tag, epoch: global_step}). For more details, refer the documentationhere.Dev Setuppip install -e \".[dev]\"Install pre-commit hookspre-commit installThe code is linted using:blackflake8mypyisortTests can be run locally usingnoxAcknowledgementsConfig forcircleci,pre-commit,mypyetc are borrowed/modified fromHydra"} +{"package": "xploitv", "pacakge-description": "XPLOITVDisclaimerThis tool has been developed with a totally didactic purpose.I am not responsible for the misuse of the same or for the damages caused to third parties.Furthermore, this tool has no affinity or relationship with Xploitv or any of its developers.InstallationTo install the tool, the easiest way is to use the pip command:python-mpipinstallxploitvHack the world!To see all the functionalities that the application offers, run the command:xploitv --helpusage: xploitv [-h] [-v] [--version] [-t THREADS] [-x FORMAT] [-i ID | -w FILE]\n\n\noptional arguments:\n-h, --help show this help message and exit\n\ninformation:\n-v Verbosity (Default: -vv)\n--version Print the version\n\nperformance:\n-t THREADS, --threads THREADS\n Define the number of threads\n\noutput:\n-x FORMAT, --extension FORMAT\n Output extension (csv,txt)\n\ngrabber (one required):\n-i ID, --id ID Grab all the accounts linked to an identifier\n-w FILE, --wordlist FILE\n Grab all the accounts linked to identifiers in a wordlistTo get all the accounts associated with an identifier, run the command:xploitv -i ____ ___ .__ .__ __\n\\ \\/ /_____ | | ____ |__|/ |____ __\n \\ /\\____ \\| | / _ \\| \\ __\\ \\/ /\n / \\| |_> > |_( <_> ) || | \\ /\n/___/\\ \\ __/|____/\\____/|__||__| \\_/\n \\_/__|\n\n [[ An automated Xploitv grabber ]]\n\n[18:51:48] Let's hack this world!\n[18:51:49] Grabbing accounts from 123456\n ...WordlistsThe true potential of this program comes from its ability to run usingwordlists. Furthermore, this method of execution is carried out using concurrency techniques, that you can customize using the-tparameter:xploitv -w -t 50Output and verbosityAre you wondering how you can save your results? Easy.Xploitv displays the results on the screen. You can customize the verbosity level using the-vparameter:xploitv -i -vvv____ ___ .__ .__ __\n\\ \\/ /_____ | | ____ |__|/ |____ __\n \\ /\\____ \\| | / _ \\| \\ __\\ \\/ /\n / \\| |_> > |_( <_> ) || | \\ /\n/___/\\ \\ __/|____/\\____/|__||__| \\_/\n \\_/__|\n\n [[ An automated Xploitv grabber ]]\n\n[19:03:30] Let's hack this world!\n[19:03:31] Grabbing accounts from 123456\n[19:03:31] Account from code 123456\nUsername: 'xxxx@gmail.com'\nPassword: 'xxxx'\n[19:03:31] Account from code 123456\nUsername: 'xxxx@msn.com'\nPassword: 'xxxx'To save the result, you can add the-xparameter that allows you to store the output intxtorcsvformat.xploitv -i -x csv____ ___ .__ .__ __\n\\ \\/ /_____ | | ____ |__|/ |____ __\n \\ /\\____ \\| | / _ \\| \\ __\\ \\/ /\n / \\| |_> > |_( <_> ) || | \\ /\n/___/\\ \\ __/|____/\\____/|__||__| \\_/\n \\_/__|\n\n [[ An automated Xploitv grabber ]]\n\n[19:07:17] Let's hack this world!\n[19:07:17] Grabbing accounts from 123456\n[19:07:17] Setting the output format to 'csv'\n[19:07:17] Results stored in ./dump.csvUninstallEasy to install. Easy to uninstall. To do this, just run the command:pip uninstall xploitvSupport the developer!Everything I do and publish can be used for free whenever I receive my corresponding merit.Anyway, if you want to help me in a more direct way, you can leave me a tip by clicking on this badge:"} +{"package": "xplordb", "pacakge-description": "xplordbMineral Exploration Database template/ system for Postgres/PostGIS and QGIS.The project incorporates import scripts, data storage, validation, reporting, 3D drill trace generation and more. psql, pgAdmin and QGIS are the suggested database and GIS front-end programs.The xplordb database template also comes with a pythonxplordbpackage.Installationxplordbpackage can be installed with pip :pip install xplordbInstall xplordb schemafromxplordb.import_ddlimportImportDDLimport_ddl=ImportDDL(db='xplordb',user='postgres',password='postgres',host='localhost',port=5432)import_ddl.import_xplordb_schema(import_data=False,full_db=False)xplordb schema installation can only be done on existing databaseCreate xplordb databasefromxplordb.create_dbimportCreateDatabasecreate_db=CreateDatabase(connection_db='postgres',user='postgres',password='postgres',host='localhost',port=5432)create_db.create_db(db='xplordb',import_data=False,full_db=False)connection database is needed for new database creationAvailable options are :import_data: Import sample datafull_db: Import not mandatory tablesxplordb APIWith xplordb package you can data to an xplordb database.Here are some examples of API use.Create mandatory Person and Datasetfromxplordb.sqlalchemy.baseimportcreate_sessionfromxplordb.datamodel.personimportPersonfromxplordb.datamodel.datasetimportDatasetfromxplordb.import_dataimportImportDatasession=create_session(database='xplordb',host='localhost',port=5432,user='postgres',password='postgres')import_data=ImportData(session)import_data.import_persons_array([Person(trigram=\"xdb\",full_name=\"default\")])import_data.import_datasets_array([Dataset(name=\"default\",loaded_by=\"xdb\")])session.commit()Create a collarfromxplordb.sqlalchemy.baseimportcreate_sessionfromxplordb.datamodel.collarimportCollarfromxplordb.import_dataimportImportDatasession=create_session(database='xplordb',host='localhost',port=5432,user='postgres',password='postgres')import_data=ImportData(session)import_data.import_collars_array([Collar(hole_id=\"collar\",data_set='default',loaded_by='xdb',x=100.0,y=100.0,z=0.0,srid=3857)])session.commit()We assume that person and dataset are already available in xplordb databaseAdd survey to collarfromxplordb.sqlalchemy.baseimportcreate_sessionfromxplordb.datamodel.surveyimportSurveyfromxplordb.import_dataimportImportDatasession=create_session(database='xplordb',host='localhost',port=5432,user='postgres',password='postgres')import_data=ImportData(session)import_data.import_surveys_array([Survey('collar','default','xdb',dip=0.0,azimuth=45.0,depth=0.0),Survey('collar','default','xdb',dip=0.1,azimuth=44.5,depth=100.0),Survey('collar','default','xdb',dip=0.0,azimuth=45.0,depth=200.0)])session.commit()We assume that person dataset and collar are already available in xplordb databaseUse sqlalchemy session for new queryxplordbmodule provides sqlalchemy table description that can be used to interact with xplordb database without usingImportDataclass :ref.person:xplordb.sqlalchemy.ref.person.XplordbPersonTableref.dataset:xplordb.sqlalchemy.ref.dataset.XplordbDatasetTabledh.collar:xplordb.sqlalchemy.dh.collar.XplordbCollarTabledh.survey:xplordb.sqlalchemy.dh.survey.XplordbSurveyTableref.lithology:xplordb.sqlalchemy.ref.lithcode.XplordbLithCodeTabledf.lith:xplordb.sqlalchemy.df.lith.XplordbLithTableExample to get all survey for a collar list:fromxplordb.sqlalchemy.baseimportcreate_sessionfromxplordb.sqlalchemy.dh.surveyimportXplordbSurveyTablesession=create_session(database='xplordb',host='localhost',port=5432,user='postgres',password='postgres')collars_id=['HOLE_1','HOLE_2']surveys=session.query(XplordbSurveyTable).filter(XplordbSurveyTable.hole_id.in_(collars_id)).all()"} +{"package": "xplore", "pacakge-description": "xplorexplore is a python package built with Pandas for data scientist or analysts, AI/ML engineers or researchers for exploring features of a dataset in one line of code for quick analysis before data wrangling and feature extraction. You can also choose to generate a more detailed report on the exploration of your dataset upon request.Getting startedInstall the packagepipinstallxploreImport the package into your codefromxplore.dataimportxploreAssign the read/open command to the file path or URL of your structured dataset to a variable namedata=Explore your dataset using the xplore() methodxplore(data)Testing xploreNavigate to the test.py file after installing the package and run the code in that file to see and understand how xplore works.Sample Output------------------------------------Thefist5entriesofyourdatasetare:rankcountry_fullcountry_abrvtotal_points...three_year_ago_avgthree_year_ago_weightedconfederationrank_date01GermanyGER0.0...0.00.0UEFA1993-08-0812ItalyITA0.0...0.00.0UEFA1993-08-0823SwitzerlandSUI0.0...0.00.0UEFA1993-08-0834SwedenSWE0.0...0.00.0UEFA1993-08-0845ArgentinaARG0.0...0.00.0CONMEBOL1993-08-08[5rowsx16columns]------------------------------------Thelast5entriesofyourdatasetare:rankcountry_fullcountry_abrvtotal_points...three_year_ago_avgthree_year_ago_weightedconfederationrank_date57788206AnguillaAIA0.0...0.00.0CONCACAF2018-06-0757789206BahamasBAH0.0...0.00.0CONCACAF2018-06-0757790206EritreaERI0.0...0.00.0CAF2018-06-0757791206SomaliaSOM0.0...0.00.0CAF2018-06-0757792206TongaTGA0.0...0.00.0OFC2018-06-07[5rowsx16columns]------------------------------------Statsonyourdataset:------------------------------------TheValuetypesofeachcolumnare:rankint64country_fullobjectcountry_abrvobjecttotal_pointsfloat64previous_pointsint64rank_changeint64cur_year_avgfloat64cur_year_avg_weightedfloat64last_year_avgfloat64last_year_avg_weightedfloat64two_year_ago_avgfloat64two_year_ago_weightedfloat64three_year_ago_avgfloat64three_year_ago_weightedfloat64confederationobjectrank_dateobjectdtype:object------------------------------------InfoonyourDataset:------------------------------------Theshapeofyourdatasetintheorderofrowsandcolumnsis:(57793,16)------------------------------------Thefeaturesofyourdatasetare:Index(['rank','country_full','country_abrv','total_points','previous_points','rank_change','cur_year_avg','cur_year_avg_weighted','last_year_avg','last_year_avg_weighted','two_year_ago_avg','two_year_ago_weighted','three_year_ago_avg','three_year_ago_weighted','confederation','rank_date'],dtype='object')------------------------------------Thetotalnumberofnullvaluesfromindividualcolumnsofyourdatasetare:rank0country_full0country_abrv0total_points0previous_points0rank_change0cur_year_avg0cur_year_avg_weighted0last_year_avg0last_year_avg_weighted0two_year_ago_avg0two_year_ago_weighted0three_year_ago_avg0three_year_ago_weighted0confederation0rank_date0dtype:int64------------------------------------Thenumberofrowsinyourdatasetare:57793------------------------------------Thevaluesinyourdatasetare:[[1'Germany''GER'...0.0'UEFA''1993-08-08'][2'Italy''ITA'...0.0'UEFA''1993-08-08'][3'Switzerland''SUI'...0.0'UEFA''1993-08-08']...[206'Eritrea''ERI'...0.0'CAF''2018-06-07'][206'Somalia''SOM'...0.0'CAF''2018-06-07'][206'Tonga''TGA'...0.0'OFC''2018-06-07']]------------------------------------Doyouwanttogenerateadetailedreportontheexplorationofyourdataset?[y/n]:Contributing to xploreFork and clone this repo if you have any contributions you want to make.\nPush your commits to a new branch and send a PR when done.\nI'll review your code and merge your PR as soon as possible.Maintainers:Jerry Buaba|Labaran Mohammed|Benjamin Acquaah"} +{"package": "xplorts", "pacakge-description": "Explore time series datasetsxplorts(\"explore-tee-ess\") is a collection of Python tools to make standalone HTML documents containing interactive charts. It is particularly aimed at showing time series data (hence the \"ts\") with annual, quarterly or monthly periodicity, such as that published by national statistical institutes by way of national accounts, productivity, or labour markets series.Once created, the HTML documents can be used with any web browser. They do not need an\nactive internet connection.Installationpip install xplortsForxplorts.utils.ukons_lprod_to_csvetc., you also needopenpyxl:pip install openpyxlDemoTo see an interactive sample data explorer, tryExplore UK output per hour worked.Source: Office for National Statistics licensed under the Open Government Licence v.3.0Steps to make explorer for ONS labour productivity dataDownloadOutput per hour worked, UKfrom the ONS web site.Open aTerminalwindow (Macintosh) orCommand promptwindow (Windows).Extract productivity, gross value added and labour data using the utility scriptukons_lprod_to_csv.py. The extracted time series will go into a fileoutputperhourworked.csvin the folder next to the originalExceldataset.In the command shell or terminal window:python xplorts/utils/ukons_lprod_to_csv.py outputperhourworked.xlsx --quarterly --sectionNote: For older versions of Pandas you will have to open the Excel file, save it as.xls, and use that rather than the original.xlsxformat.Run the moduledblprodto create a stand-aloneHTMLlabour productivity dashboard in the fileoutputperhourworked.html.In the command shell or terminal window:python -m xplorts.dblprod outputperhourworked.csv -d date -b industry -p lprod -g gva -l labourUse the explorer in any web browser.FeaturesThe labour productivity explorer demonstrates these features:A grouped multi-line chart shows a set of related lines for one split level at a time, like time series for productivity, gross value added, and hours worked for a particular industry.A time series components chart shows a set of stacked bars in combination with a totals line, for one split level at a time, like cumulative growth time series for gross value added, hours worked (sign reversed), and productivity for a particular industry.A snapshot growth components chart shows a set of stacked bars in combination with markers showing total growth, as a function of a categorical factor, like growth for gross value added and hours worked (sign reversed) by industry, along with growth in productivity, for a selectable time period.A heatmap chart shows data values as a function of a categorical split variable across time.Drop-down list and slider widgets provide interactive selection of a categorical split level or snapshot time period to show. Static screenshots are shown here, but check out the interactive sample data explorer at the link above.Hover tool displays data values at the cursor location.Chart tools include box zoom, wheel zoom, pan, and save to file.Time periods can be represented on a chart axis as nested categories like (year, quarter).A categorical chart axis can represent time periods or levels of a split factor.Usingxplortsin PythonImportImport the package into your code:import xplortsPackage documentationTo show the docstring for the package:xplorts?To show the docstring for a particular module, likeslideselect:xplorts.slideselect?ModulesModuleDescriptionbaseMiscellaneous helper functions and classes.diffMulti-tab revisions display for two vintages of a dataset.dutilsMiscellaneous data manipulation helpers.dashboardMulti-tab dashboard showing levels, growth components, and growth heatmaps.dblprodModify a Bokeh Figure by adding charts to show labour productivity levels or growth components.ghostbokehDefine an abstract base class to a build pseudo-subclass of a Bokeh class.growthcompsGrowth of time series and their contribution to growth of derived series.heatmapFunctions to create a heatmap of data values as a function of horizontal and vertical categorical variables.linesLine charts to show several time series with a split factor.scatterScatter charts to show one or more categorical series with a split factor.slideselectClass combining select and slider widgets, with support for javascript linking to other objects.snapcompSnapshot growth components chart, with a categorical vertical axis showing levels of a split factor, horizontal stacked bars showing growth components, and markers showing overall growth for each stack of bars.stacksHorizontal or vertical stacked bar chart showing several data series with a split factor.tscompGrowth components chart, with a categorical vertical axis showing levels of a split factor, horizontal stacked bars showing growth components, and a line showing overall growth.Usingxplortson the command lineInstall (once, possibly within a particular virtual environment)Open aTerminalwindow (Macintosh) orCommand promptwindow (Windows)Activate virtual environment, if relevantOn Windows:activate my_envOn Mac:conda activate my_envExecute anxplortsmodule entry pointxp-dashboard ...Or tellpythonexplicitly to run anxplortsmodulepython -m xplorts.dashboard ...Getting help about command line optionsPass the option-hto anyxplortsscript to get help. For example:xp-dashboard -hOrpython -m xplorts.dblprod -husage: dblprod.py [-h] [-b BY] [-d DATE] [-p LPROD] [-v GVA] [-l LABOUR]\n [-g ARGS] [-t SAVE] [-s]\n datafile\n\nCreate interactive visualiser for labour productivity levels with a split\nfactor\n\npositional arguments:\n datafile File (CSV) with data series and split factor\n\noptional arguments:\n -h, --help Show this help message and exit\n -b BY, --by BY Factor variable for splits\n -d DATE, --date DATE Date variable\n -p LPROD, --lprod LPROD\n Productivity variable\n -v GVA, --gva GVA Gross value added (GVA) variable\n -l LABOUR, --labour LABOUR\n Labour variable (e.g. jobs or hours worked)\n -g ARGS, --args ARGS Keyword arguments. YAML mapping of mappings. The\n keys 'lines', 'growth_series' and 'growth_snapshot'\n can provide keyword arguments to pass to\n `prod_ts_lines`, `prod_ts_growth` and\n `prod_growth_snapshot`, respectively.\n -t SAVE, --save SAVE Interactive .html to save, if different from the\n datafile base\n -s, --show Show interactive .htmlxplortsscriptsScriptEntry pointDescriptiondashboardxp-dashboardMulti-tab dashboard showing levels, growth components, and growth heatmaps.dblprodxp-dblprodCreate a labour productivity dashboard, with three charts including:a lines chart showing levels of labour productivity, gross value added, and labour,a time series growth components chart showing cumulative growth in labour productivity, gross value added, and labour, anda snapshot growth components chart showing period-on-period growth in labour productivity, gross value added, and labour.diffxp-diff Multi-tab revisions display for two vintages of a dataset, showing revisions in levels, growths, and cumulative growth.heatmapxp-heatmapCreate a heatmap of values as a function of two categorical variables.linesxp-linesCreate a line chart showing several time series with a split factor. Widgets select one split factor category at a time.scatterxp-scatterCreate scatter chart showing one or more time series with a split factor. Widgets select one split factor category at a time.snapcompxp-snapcompCreate a snapshot growth components chart, with a categorical vertical axis showing levels of a split factor, horizontal stacked bars showing growth components, and a line showing overall growth. A widget selects one time period at a time.stacksxp-stacksCreate stacked bar chart showing several data series with a split factor. Widgets select one split factor at a time (or one time period at a time if the split factor is plotted as a chart axis).tscompxp-tscompCreate a time series growth components chart, with time periods along the horizontal axis, vertical stacked bars showing growth components, and a line showing overall growth. Widgets select one split factor category at a time.utils.ukons_lcli_to_csvExtract data from ONSlabour costs and labour income dataset, in a format suitable for use withxplortscharts.utils.ukons_lprod_to_csvExtract data from ONS labour productivity datasets such asOutput per hour worked, UK, in a format suitable for use withxplortscharts.utils.ukons_psp_to_csvExtract data from ONS datasetPublic service productivity estimates: total public service, in a format suitable for use withxplortscharts."} +{"package": "xplot", "pacakge-description": "No description available on PyPI."} +{"package": "xplotter", "pacakge-description": ":bar_chart: Gathering insights from data in a complete EDA process components :chart_with_upwards_trend:Table of contentAbout xplotterPackage structureFeaturesInstalling the packageExamplesInsights moduleUsage around the worldContributionSocial MediaAbout xplotterThe definition is clear:xplotteris a python library created for making the Exploratory Data Analysis process so much easier! Withxplotter, data scientists and data analysts can use a vast number of functions for plotting, customizing and extracting insights from data with very few lines of code. The exploratory process is a key step on every data science and business inteligence project and it's very important to understand your data before take any action. The use cases are almost infinity!Why use xplotter?Use functions for plotting graphs and extracting information from your data in an easy wayYou can explore your data fasterVisualize some beautiful charts with few lines of codeSave your images in a local repositoryImprove analytics by analysing trends and distributions of your dataRich documentation to explorePackage structureAfter viewing some of benefits of usingxplotterin a data project, it's also important to see how the package was built and how it's organized. At the moment, there are two modules on the xplotter package folder and they are explained on the table below:ModuleDescriptionFunctions/MethodsLines of Code (approx)formatterAuxiliar functions for formatting charts3~150insightsFunctions for exploring data in a wide range of possibilities14~1800FeaturesThe features of xplotter package are built into useful and well-documented functions that can be used in any step of data exploration process. There will be a specific session of usage examples in this documentations but, just be clear, you can use xplotter for a simple formatting step like customizing the border axis in a matplotlib graph...fromxplotter.formatterimportformat_spinesfig,ax=plt.subplots(figsize=(10,7))format_spines(ax,right_border=False)...or even plot a simple and customized countplot with labels already written inside the bars...fromxplotter.insightsimportplot_countplotplot_countplot(df=df,col='cat_column')At this moment, all the features available in the xplotter package are:ModuleFunction/ClassShort Descriptionformatterformat_spinesModify borders and axis colors of matplotlib figureformatterAnnotateBarsMakes the process of labeling data points in a bar chart easierformattermake_autopctHelps labeling data in a pie or donut chartinsightssave_figEasy way for saving figures created inside or outside xplotterinsightsplot_donutchartCreates a custom donut chart for a specific categorical columninsightsplot_pie_chartCreates a custom pie chart for a specific categorical columninsightsplot_double_donut_chartCreates a \"double\" custom donut chart for two columns of a given datasetinsightsplot_countplotCreates a simple countplot using a dataset and a column nameinsightsplot_pct_countplotCreates a percentage countplot (grouped bar chart) using a dataset and a column nameinsightsplot_distplotCreates a custom distribution plot based on a numeric columninsightsplot_aggregationPlots a custom aggregate chart into a bar styleinsightsplot_cat_aggreg_reportA rich and complete report using count, aggregation and distribution functionsinsightsdata_overviewExtract useful information of a given dataset to offers an overview from the datainsightsplot_corr_matrixA beautiful and customized correlation matrix for a dataset and a target columninsightsplot_multiple_distplotsPlots custom distribution charts for multiple columns at once using the col_list parameterinsightsplot_multiple_dist_scatterplotPlots a rich graph that joins a distribution and a scatterplotinsightsplot_multiple_countplotsPlots multiple formatted countplot based on a list of columns of a given datasetinsightsplot_evolutionplotPlots an evolution plot in a line chartInstalling the packageThe last version ofxplotterpackage are published and available onPyPI repository:pushpin:Note:as a good practice for every Python project, the creation of avirtual environmentis needed to get a full control of dependencies and third part packages on your code. By this way, the code below can be used for creating a new venv on your OS.# Creating and activating venv on Linux$python-mvenv/\n$source//bin/activate# Creating and activating venv on Windows$python-mvenv/\n$//Scripts/activateWith the new venv active, all you need is execute the code below using pip for installing xplotter package (upgrading pip is optional):$pipinstall--upgradepip\n$pipinstallxplotterThe xplotter package is built in a layer above some other python packages like matplotlib, seaborn and pandas. Because of that, when installing xplotter, the pip utility will also install all dependencies linked to xplotter. The output expected on cmd or terminal are something like:Installing collected packages: six, pytz, python-dateutil, pyparsing, numpy, kiwisolver, cycler, scipy, pandas, matplotlib, seaborn, xplotter\nSuccessfully installed cycler-0.10.0 kiwisolver-1.3.1 matplotlib-3.2.1 numpy-1.20.2 pandas-1.1.5 pyparsing-2.4.7 python-dateutil-2.8.1 pytz-2021.1 scipy-1.6.3 seaborn-0.11.1 six-1.15.0 xplotter-0.0.3ExamplesIn this session, you will see some usage examples of xplotter on real problems using data. After installing the package, it's important to know how to use it and how to extract the real power of it.Insights ModuleAs you could see by this time, the insights module from xplotter have a lot of functions that can deliver something like \"charts as a code\". It's just a funy way to describe how the components and the tools inside this module can make life of a data explorer easier. To ilustrate that, the code below reads the titanic dataset directly from seaborn and plots a custom donut chart forsurvivedfeature.fromxplotter.insightsimportplot_donut_chartimportseabornassnstitanic=seaborn.load_dataset('titanic')plot_donut_chart(df=titanic,col='survived')This outputs the following figure:Another example uses the iris dataset also read from seabornload_dataset()function. In this case, we can use theplot_distplot()xplotter funcion for visualize the distribution of sepal_length feature for each species in a fast and direct way:iris=seaborn.load_dataset('iris')plot_distplot(df=iris,col='sepal_length',hue='species')Let's see the beautiful distribution plot the function above generated for you:There are much more you can do using insights module from xplotter package. It's a hole world to be explore and a bunch of business questions that can be answeared through visualization charts easy plotted through those already coded functions. In the next topic, this documentation will share with you some of real world implementations using xplotter.Usage Around the WorldFor being easy and simple, xplotter can have alot of applications. One of the most famous one is the notebookTitanic Dataset Explorationposted on Kaggle byThiago Panini. This well written notebook uses the insight module for plotting beautiful charts and building a really complete Exploratory Data Analysis proccess and, by now, it achieve abronze medalwith 32 upvotes by Kaggle's community and a incredible mark of more than 1,600 views!ContributionThe xplotter python package is an open source implementation and the more people use it, the more happy the developers will be. So if you want to contribute with xplotter, please feel free to follow the best practices for implementing coding on this github repository through creating new branches, making merge requests and pointig out whenever you think there is a new topic to explore or a bug to be fixed.Thank you very much for reaching this and it will be a pleasure to have you as xplotter user or developer.Social MediaFollow me on LinkedIn:https://www.linkedin.com/in/thiago-panini/See my other Python packages:https://github.com/ThiagoPanini"} +{"package": "xPlotUtil", "pacakge-description": "No description available on PyPI."} +{"package": "xplt", "pacakge-description": "XpltA plotting library forXsuiteand simmilar accelerator physics codes.UsagepipinstallxpltRead the docs athttps://eltos.github.io/xpltDeveloper installationgitclonegit@github.com:eltos/xplt.gitcdxplt\npipinstall-e.\npipinstallpre-commit\npre-commitinstall\ngitconfigcore.autocrlfinput"} +{"package": "xplug", "pacakge-description": "This Package make your life easy! enjoy."} +{"package": "xply", "pacakge-description": "xplyAn exploit development framework for Python 3About\u2022Setup\u2022Contributing\u2022LicenseAboutThis is a ground-up rewrite of the greatpwnlibfor Python 2. There were a\nnumber of attempts to portpwnlibto Python 3, but they all appear abandoned.\nIn addition, they still had a bunch of issues with the changes in Python 3,\nespecially when it comes to the handling of binary data.xplydoes not have nearly the range of features thatpwnlibhas (although\nmore will be added over time), but was written from the ground up with Python 3\nin mind.SetupYou can installxplyusingpip:pipinstallxplyxplyrequires at least Python 3.7 (forfrom __future__ import annotations).ContributingContributions are always welcome! If you encounter a bug or have a feature request, pleaseopen an issueon GitHub. Feel free to create apull requestfor your improvements.Licensexply is licensed under the MIT license, as found in the LICENSE file.\u00a9 2019 Tobias Holl (@TobiasHoll)"} +{"package": "xpm", "pacakge-description": "UNKNOWN"} +{"package": "xpmir-rust", "pacakge-description": "Experimaestro Information Retrieval (rust library)This package contains implementations in Rust of several key components of the Experimaestro IR library:Sparse indexing: given a list of (term/impact) for each document, build/query an efficient structure"} +{"package": "xpoint", "pacakge-description": "No description available on PyPI."} +{"package": "xpol", "pacakge-description": "A code to compute angular power spectra based on cross-correlation between maps and covariance matrices.This is the generalisation to polarisation ofTristram M. et al., 2005 MNRAS 358 833Install PythonThe easiest way to installXpolis viapippipinstallxpol[--user]If you plan to develop the code, it is better to clone the repositorygitclonehttps://gitlab.in2p3.fr/tristram/Xpol.git/where/to/cloneand install the python librarypipinstall-e/where/to/cloneThe -e option allow the developer to make changes within the Xpol directory without having\nto reinstall at every changes. If you plan to just use the code and do not develop it, you can\nremove the -e option.You can find a example of the module usage in test/script_xpol.pyInstall CThe code is in C, fully MPI parallelized in CPU and memory (using spherical transform by s2hat).Librairies needed are :HEALPix (http://healpix.jpl.nasa.gov/)cfitsio (http://heasarc.gsfc.nasa.gov/fitsio/fitsio.html)s2hat (http://www.apc.univ-paris7.fr/APC_CS/Recherche/Adamis/MIDAS09/software/s2hat/s2hat.html)In addition you will need some BLAS/LAPACK optimized routines (MKL, NAG, \u2026)Equationswiki is hereUsageYou can use the python class (Xpol) to compute spectra based on a data.importxpolbinning=xpol.Bins(lmins,lmaxs)xp=xpol.Xpol(mask,bins=binning)pcl,cl=xp.get_spectra(dT)see the fileexamples/script_xpol.pyfor more detailed usage.For intensive computation and simulation you can alternatively use the MPI C version with a parameter file detailedhereReferencesXpolhave been used to derive power spectra for:ArcheopsCMB power spectra [Tristram+2005, A&A 436 785]Dust power spectra [Ponthieu+2005, A&A 444 327]Planck:CMB power spectra [Planck 2015 results. XI, Couchot+2015]Dust power spectra [Planck Intermediate Paper XXX]CIB power spectra [Planck 2013 results. XXX]SZ power spectra [Planck 2013 results. XXI, Planck 2015 results XXII]SZ-CIB cross-power spectra [Planck 2015 results. XXIII]And many others !"} +{"package": "xpore", "pacakge-description": "xPore is a Python package for identification and quantification of differential RNA modifications from direct RNA sequencing.InstallationxPore requiresPython3.\nTo install the latest release with PyPI (recommended), run$pipinstallxporeDocumentationPlease refer to our xPore documentation (https://xpore.readthedocs.io) for additional information, a quick start guide, and details on the data processing and output file format.xPore is described in details inPratanwanich et al.Nat Biotechnol(2021)Release HistoryThe current release is xPore v2.1.Please refer to the github release history for previous releases:https://github.com/GoekeLab/xpore/releasesCiting xPoreIf you use xPore in your research, please citePloy N. Pratanwanich, et al. Identification of differential RNA modifications from nanopore direct RNA sequencing with xPore.Nat Biotechnol(2021),https://doi.org/10.1038/s41587-021-00949-w.Getting HelpWe appreciate your feedback and questions! You can report any error or suggestion related to xPore as anissue on github. If you have questions related to the manuscript, data, or any general comment or suggestion please use theDiscussions.Thank you!ContactxPore is maintained byPloy N. Pratanwanich,Yuk Kei WanandJonathan Goekefrom the Genome Institute of Singapore, A*STAR."} +{"package": "xport", "pacakge-description": "Read and write SAS Transport files (*.xpt).SAS uses a handful of archaic file formats: XPORT/XPT, CPORT, SAS7BDAT.\nIf someone publishes their data in one of those formats, this Python\npackage will help you convert the data into a more useful format. If\nsomeone, like the FDA, asks you for an XPT file, this package can write\nit for you.What\u2019s it for?XPORT is the binary file format used by a bunch ofUnited States\ngovernment agenciesfor publishing data sets. It made a lot of sense\nif you were trying to read data files on your IBM mainframe back in\n1988.The officialSAS specification for XPORTis relatively\nstraightforward. The hardest part is converting IBM-format floating\npoint to IEEE-format, which the specification explains in detail.There was anupdate to the XPT specificationfor SAS v8 and above.\nThis modulehas not yet been updatedto work with the new version.\nHowever, if you\u2019re using SAS v8+, you\u2019re probably not using XPT\nformat. The changes to the format appear to be trivial changes to the\nmetadata, but this module\u2019s current error-checking will raise aValueError. If you\u2019d like an update for v8, please let me know bysubmitting an issue.InstallationThis project requires Python v3.7+. Grab the latest stable version from\nPyPI.$python-mpipinstall--upgradexportReading XPTThis module follows the common pattern of providingloadandloadsfunctions for reading data from a SAS file format.importxport.v56withopen('example.xpt','rb')asf:library=xport.v56.load(f)The XPT decoders,xport.loadandxport.loads, return axport.Library, which is a mapping (dict-like) ofxport.Dataset``s.The ``xport.Dataset`is a subclass ofpandas.DataFramewith SAS metadata attributes (name, label, etc.).\nThe columns of axport.Datasetarexport.Variabletypes, which\nare subclasses ofpandas.Serieswith SAS metadata (name, label,\nformat, etc.).If you\u2019re not familiar withPandas\u2019s dataframes, it\u2019s easy to think\nof them as a dictionary of columns, mapping variable names to variable\ndata.The SAS Transport (XPORT) format only supports two kinds of data. Each\nvalue is either numeric or character, soxport.loaddecodes the\nvalues as eitherstrorfloat.Note that since XPT files are in an unusual binary format, you should\nopen them using mode'rb'.You can also use thexportmodule as a command-line tool to convert\nan XPT file to CSV (comma-separated values) file. Thexportexecutable is a friendly alias forpython-mxport. Caution: if this command-line does not work with the lastest version, it should be working with version 2.0.2. To get this version, we can either download the files from thislinkor simply type the following command line your bash terminal:pip installxport==2.0.2.$xportexample.xpt>example.csvWriting XPTThexportpackage follows the common pattern of providingdumpanddumpsfunctions for writing data to a SAS file format.importxportimportxport.v56ds=xport.Dataset()withopen('example.xpt','wb')asf:xport.v56.dump(ds,f)Because thexport.Datasetis an extension ofpandas.DataFrame,\nyou can create datasets in a variety of ways, converting easily from a\ndataframe to a dataset.importpandasaspdimportxportimportxport.v56df=pandas.DataFrame({'NUMBERS':[1,2],'TEXT':['a','b']})ds=xport.Dataset(df,name='MAX8CHRS',label='Up to 40!')withopen('example.xpt','wb')asf:xport.v56.dump(ds,f)SAS Transport v5 restricts variable names to 8 characters (with a\nstrange preference for uppercase) and labels to 40 characters. If you\nwant the relative comfort of SAS Transport v8\u2019s limit of 246 characters,\npleasemake an enhancement request.It\u2019s likely that most people will be usingPandasdataframes for the\nbulk of their analysis work, and will want to convert to XPT at the\nvery end of their process.importpandasaspdimportxportimportxport.v56df=pd.DataFrame({'alpha':[10,20,30],'beta':['x','y','z'],})...# Analysis work ...ds=xport.Dataset(df,name='DATA',label='Wonderful data')# SAS variable names are limited to 8 characters. As with Pandas# dataframes, you must change the name on the dataset rather than# the column directly.ds=ds.rename(columns={k:k.upper()[:8]forkinds})# Other SAS metadata can be set on the columns themselves.fork,vinds.items():v.label=k.title()ifv.dtype=='object':v.format='$CHAR20.'else:v.format='10.2'# Libraries can have multiple datasets.library=xport.Library({'DATA':ds})withopen('example.xpt','wb')asf:xport.v56.dump(library,f)Feature requestsI\u2019m happy to fix bugs, improve the interface, or make the module\nfaster. Justsubmit an issueand I\u2019ll take a look. If you work for\na corporation or well-funded non-profit, please consider asponsorship.ThanksCurrent and past sponsors include:ContributingThis project is configured to be developed in a Conda environment.$gitclonegit@github.com:selik/xport.git$cdxport$makeinstall# Install into a Conda environment$condaactivatexport# Activate the Conda environment$makeinstall-html# Build the docs websiteAuthorsOriginal version byJack Cushman, 2012.Major revisions byMichael Selik, 2016 and 2020.Minor revisions byAlfred Chan, 2020.Minor revisions byDerek Croote, 2021.Change Logv0.1.0, 2012-05-02Initial release.v0.2.0, 2016-03-22Major revision.v0.2.0, 2016-03-23Add numpy and pandas converters.v1.0.0, 2016-10-21Revise API to the pattern of from/to v2.0.0, 2016-10-21Reader yields regular tuples, not namedtuplesv3.0.0, 2020-04-20Revise API to the load/dump pattern.\nEnable specifying dataset name, variable names, labels, and formats.v3.1.0, 2020-04-20Allowdumps(dataframe)instead of requiring aDataset.v3.2.2, 2020-09-03Fix a bug that incorrectly displays a - (dash) when it\u2019s a null for numeric field.v3.3.0, 2021-12-25Enable reading Transport Version 8/9 files. Merry Christmas!v3.4.0, 2021-12-25Add support for special missing values, like.A, that extendfloat.v3.5.0, 2021-12-31Enable writing Transport Version 8 files. Happy New Year!v3.5.1, 2022-02-01Fix issues with writingDataset.labelandVariable.label.v3.6.0, 2022-02-02Add beta support for changing the text encoding for data and metadata.v3.6.1, 2022-02-15Fix issue with v8 format when the dataset has no long labels."} +{"package": "xportage", "pacakge-description": "XPortageTODO"} +{"package": "xports", "pacakge-description": "No description available on PyPI."} +{"package": "xpos", "pacakge-description": "xposDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nxpos--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallxposnbdev# activate conda environment$condaactivatexpos# make sure the xpos package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the xpos package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/xpos.gitor fromconda$condainstall-cdsm-72xposor frompypi$pipinstallxposDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find\npackage manager specific guidelines oncondaandpypirespectively."} +{"package": "xpose", "pacakge-description": ":card_file_box: xpos\u00e9Black boxes machine learning xpos\u00e9"} +{"package": "xpose-generator", "pacakge-description": "# xpose-generatorThis simple script is something I did rather quickly to generate the website weneeded to create in the context of the [presentations done in third year of CSengineering at ESIPE][1].It is very simple: it takes the information describe in `a`, a text filecontaining meta-information, and every markdown file it finds in `content`, andgenerates the proper html tree in `build`.## Installation / Upgradepip install -U xpose-generatorOnce this is done, you can call `xposegen`, in the directory of your choice,where there is a [`a`][2] file, and a `content/` directory.## How to write content:Write the `a` file required by ESIPE's integration system, following theinstructions [here][2].Simply write a .md file in `content/`, write a line `Title: My Title Here` ontop of the file, and then write your content. Note: For presentation purpose,don't write `h1` tags, aka `#`, in markdown.Here be samples (and dragons):Title: This is my test pageNavOrder: 1## Hello, worldHello, world. I am writing some stuff in markdown.[This is a link to another page, with header][hello.html#title]*note*: if you have many pages, set the `Order: ` property,so the pages will be in that order on the navigation menu.If you have images, etc... Just put it in `content/` with everything else.So you have (approximately, you may have more files in `content/`...) thisstructure:[paul@styx:xpose] master \u00b1 tree.\u251c\u2500\u2500 a\u2514\u2500\u2500 content\u2514\u2500\u2500 index.mdTo have more information about how to write markdown, check [github's guide tomarkdown][3]. This will give you the basis. To know more about the supportedsyntax, see the documentation of [python-markdown][4]. The following extensionsare used: [extra][5], [admonition][6], [codehilite][7], [headerid][8],[sane_lists][9]# ContributingPlease, feel free to clone the repository, make your stuff, and eventually makea pull request to merge what you did? That would be nice.Also, even if you don't want to merge your code, an email will be appreciated.## TODO* Support subdirectory use in `content/`* Add support for custom css* do not hard-code everything; add support for cli args, or conffile* Decrease every header if a `# title` is detected.* Use the generated `h1` title as page's title, and strip it from final HTML.* Add `next` and `prev` buttons on every page, linking to the next page inNavOrder.[1]: http://www-igm.univ-mlv.fr/~dr/xall.php[2]: http://www-igm.univ-mlv.fr/~dr/XPOSE/modalites.html[3]: https://help.github.com/articles/markdown-basics[4]: http://pythonhosted.org//Markdown[5]: http://pythonhosted.org//Markdown/extensions/extra.html[6]: http://pythonhosted.org//Markdown/extensions/admonition.html[7]: http://pythonhosted.org//Markdown/extensions/code_hilite.html[8]: http://pythonhosted.org//Markdown/extensions/header_id.html[9]: http://pythonhosted.org//Markdown/extensions/sane_lists.html"} +{"package": "xpost", "pacakge-description": "xpost - Python CLI for Twitter Operationsxpost is a command-line interface (CLI) Python package for interacting with Twitter. It allows users to tweet, add users, store API credentials securely, and delete tweets.FeaturesTweeting: Effortlessly post tweets from the command line.Credential Storage: Securely encrypt and store your Twitter API credentials using the robustPBKDF2HMACalgorithms, ensuring security.Tweet Deletion: Conveniently delete tweets with a simple command.InstallationInstall xpost using pip:pipinstallxpostVerify the installation by checking the versio:xpost--versionUsageAdding user Authentication CredentialsSecurely store your Twitter API credentials:$x-configadd_user\nEnterausernametoencryptyourAPIs:usrDarwin\nSetapasswordtosecureyourencryptedAPIs:\nConfirmyourpassword:\nEnterCLIENT_ID:client_id\nEnterCLIENT_SECRET:client_secret\nEnterAPI_KEY:api_key\nEnterAPI_KEY_SECRET:apiKey\nEnterBEARER_TOKEN:bTokn\nEnterACCESS_TOKEN:aTokn\nEnterACCESS_TOKEN_SECRET:aTokn_secret\nSavingyourencrypteddata...\n-Credentialsencryptedandstoredsuccessfully.\nSavingcompleted.Datastoredat:~/.tweet\n\nUsercredentialssuccessfullyadded.Viewing Stored CredentialsCheck your encrypted credentials:$ls~/.tweetOr view decrypted credentials:>>>importxpostasx>>>x.show_credentials()EnteryourusernametodecryptyourAPIs:test_usrEnteryourpasswordtodecryptyourAPIs:{'CLIENT_ID':'client_id','CLIENT_SECRET':'client_secret','API_KEY':'api_key','API_KEY_SECRET':'apiKey','BEARER_TOKEN':'bTokn','ACCESS_TOKEN':'aTokn','ACCESS_TOKEN_SECRET':'aTokn_secret'}Reset your APIsPermanently delete all stored credentials:To reset your APIs$x-configreset\nDoyouwanttodeletealldata?[Y/n]:Y\nWARNING:Thiswillpermanentlydeletealldata,includingproductionAPIkeys.Confirmwith'Y'orcancelwith'N':Y\nProcessingdeletion....\n\nAlluserfilesin~/.tweethavebeensuccessfullydeleted.\nDatadeletionsuccessfull.Command Usage ExamplesUse thexcommand to perform tweeting operations. Below are examples of how to use the command:Posting a TweetTo post a tweet directly message or from a text file:$x--post\"Your message to be tweeted\"$x--post\"path/to/text/file.txt\"Important: The username and password you provide are used for decrypting your encrypted API credentials.$x--post\"Hello, X!\"EnteryourusernametodecryptyoursavedAPIs:test_usr\nEnteryourpasswordtodecryptyoursavedAPIs:\nINFO:root:Tweetsuccessfullyposted.TweetID:1728786247492247770Twitterpost:\nHello,X!\n\nINFO:root:Tweetinfosavedtothedatabase.\nTweetURL:https://twitter.com/eulerDavinci/status/1728786247492247770Deleting a TweetRemove a tweet by its ID:$x--delete$x--delete1728786247492247770EnteryourusernametodecryptyoursavedAPIs:test_usr\nEnteryourpasswordtodecryptyoursavedAPIs:\nINFO:root:Tweetdeletedsuccessfullyfromtwitter.com\nINFO:root:TweetwithID1728786247492247770removedfromdatabase.\nTweetsuccessfullydeleted.Licensexpost is released under the MIT License. See theLICENSEfile for more details.ContributionsContributions are welcome from anyone, even if you are new to open source. If you are new and looking for some way to contribute, a good place to start is documentation and docstring.Please note that all participants in this project are expected to follow our Code of Conduct. By participating in this project you agree to abide by its terms. SeeCODE OF CONDUCTSSupportFor support, please open an issue on the GitHub repository.TestsTo ensure the functionality ofxpost, you can run the following test commands. These commands test various functionalities of the xpost package.First, import the necessary functions fromxpost:fromxpostimport*Testing Configuration CommandsUse these functions to test configuration-related operations:Adding a User: Adds a new user and stores their credentials.add_user()Resets all stored credentials.reset_credentials()Display the stored credentials.show_credentials()Testing Tweet OperationsTo test tweeting functionalities, use these functions:Posts a new tweet.post_tweet()Deletes an existing tweet.delete_tweet()Feedback and Feature RequestsYour feedback is incredibly valuable to us! For any feedback or feature requests, please reach out via email. We appreciate your input in enhancing xpost.Please note,xpostis intentionally designed with a focus on basic features. This is to minimize distractions often associated with social media platforms, allowing users to concentrate on meaningful content creation. Our goal is to facilitate a simplified and efficient tweeting experience, enabling users to reflect on their past posts in the future."} +{"package": "xPostgreSQL", "pacakge-description": "No description available on PyPI."} +{"package": "xpotato", "pacakge-description": "POTATO: exPlainable infOrmation exTrAcTion framewOrkPOTATO is a human-in-the-loop XAI framework for extracting and evaluating interpretable graph features for any classification problem in Natural Language Processing.Built systemsTo get started with rule-systems we provide rule-based features prebuilt with POTATO on different datasets (e.g. our paperOffensive text detection on English Twitter with deep learning models and rule-based systemsfor the HASOC2021 shared task). If you are interested in that, you can go underfeatures/for more info!Install and Quick StartCheck out our quick demonstration (~2 min) video about the tool:https://youtu.be/PkQ71wUSeNUThere is a longer version with a detailed method description and presented background research (~1 hour):https://youtu.be/6R_V1WfIjsUSetupThe tool is heavily dependent upon thetuw-nlprepository. You can install tuw-nlp with pip:pip install tuw-nlpThen follow theinstructionsto setup the package.Then install POTATO from pip:pip install xpotatoOr you can install it from source:pip install -e .UsagePOTATO is an IE tool that works on graphs, currently we support three types of graphs: AMR, UD andFourlang.In the README we provide examples with fourlang semantic graphs. Make sure to follow the instructions in thetuw_nlprepo to be able to build fourlang graphs.If you are interested in AMR graphs, you can go to thehasocfolder To get started with rule-systems prebuilt with POTATO on the HASOC dataset (we also presented a paper namedOffensive text detection on English Twitter with deep learning models and rule-based systemsfor the HASOC2021 shared task).We also provide experiments on theCrowdTruthmedical relation extraction datasets with UD graphs, go to thecrowdtruthfolder for more info!POTATO can also handle unlabeled, or partially labeled data, seeadvancedmode to get to know more.To see complete working examples go under thenotebooks/folder to see experiments on HASOC and on the Semeval relation extraction dataset.First import packages from potato:fromxpotato.dataset.datasetimportDatasetfromxpotato.models.trainerimportGraphTrainerFirst we demonstrate POTATO's capabilities with a few sentences manually picked from the dataset.Note that we replaced the two entitites in question withXXXandYYY.sentences=[(\"Governments and industries in nations around the world are pouring XXX into YYY.\",\"Entity-Destination(e1,e2)\"),(\"The scientists poured XXX into pint YYY.\",\"Entity-Destination(e1,e2)\"),(\"The suspect pushed the XXX into a deep YYY.\",\"Entity-Destination(e1,e2)\"),(\"The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.\",\"Other\"),(\"The entity1 to buy papers is pushed into the next entity2.\",\"Entity-Destination(e1,e2)\"),(\"An unnamed XXX was pushed into the YYY.\",\"Entity-Destination(e1,e2)\"),(\"Since then, numerous independent feature XXX have journeyed into YYY.\",\"Other\"),(\"For some reason, the XXX was blinded from his own YYY about the incommensurability of time.\",\"Other\"),(\"Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.\",\"Other\"),(\"Olympics have already poured one XXX into the YYY.\",\"Entity-Destination(e1,e2)\"),(\"After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.\",\"Entity-Destination(e1,e2)\"),(\"I placed the XXX in a natural YYY, at the base of a part of the fallen arch.\",\"Entity-Destination(e1,e2)\"),(\"The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.\",\"Other\"),(\"The XXX leaked from every conceivable YYY.\",\"Other\"),(\"The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.\",\"Entity-Destination(e1,e2)\"),(\"The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.\",\"Other\"),(\"Gaza XXX recover from three YYY of war.\",\"Other\"),(\"This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.\",\"Other\")]Initialize the dataset and also provide a label encoding. Then parse the sentences into graphs. Currently we provide three types of graphs:ud,fourlang,amr. Also provide the language you want to parse, currently we support English (en) and German (de).dataset=Dataset(sentences,label_vocab={\"Other\":0,\"Entity-Destination(e1,e2)\":1},lang=\"en\")dataset.set_graphs(dataset.parse_graphs(graph_format=\"ud\"))Check the dataset:df=dataset.to_dataframe()We can also check any of the graphs:Check any of the graphs parsedfromxpotato.models.utilsimportto_dotfromgraphvizimportSourceSource(to_dot(df.iloc[0].graph))RulesIf the dataset is prepared and the graphs are parsed, we can write rules to match labels. We can write rules either manually or extract\nthem automatically (POTATO also provides a frontend that tries to do both).The simplest rule would be just a node in the graph:# The syntax of the rules is List[List[rules that we want to match], List[rules that shouldn't be in the matched graphs], Label of the rule]rule_to_match=[[[\"(u_1 / into)\"],[],\"Entity-Destination(e1,e2)\"]]Init the rule matcher:fromxpotato.graph_extractor.extractimportFeatureEvaluatorevaluator=FeatureEvaluator()Match the rules in the dataset:#match single featuredf=dataset.to_dataframe()evaluator.match_features(df,rule_to_match)SentencePredicted labelMatched rule0Governments and industries in nations around the world are pouring XXX into YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']1The scientists poured XXX into pint YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']2The suspect pushed the XXX into a deep YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']3The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']4The entity1 to buy papers is pushed into the next entity2.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']5An unnamed XXX was pushed into the YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']6Since then, numerous independent feature XXX have journeyed into YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']7For some reason, the XXX was blinded from his own YYY about the incommensurability of time.8Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.9Olympics have already poured one XXX into the YYY.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']10After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.11I placed the XXX in a natural YYY, at the base of a part of the fallen arch.12The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.13The XXX leaked from every conceivable YYY.14The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.Entity-Destination(e1,e2)[['(u_1 / into)'], [], 'Entity-Destination(e1,e2)']15The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.16Gaza XXX recover from three YYY of war.17This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.You can see in the dataset that the rules only matched the instances where the \"into\" node was present.One of the core features of our tool is that we are also able to match subgraphs. To describe a graph, we use thePENMANnotation.E.g. the string(u_1 / into :1 (u_3 / pour))would describe a graph with two nodes (\"into\" and \"pour\") and a single directed edge with the label \"1\" between them.#match a simple graph featureevaluator.match_features(df,[[[\"(u_1 / into :1 (u_2 / pour) :2 (u_3 / YYY))\"],[],\"Entity-Destination(e1,e2)\"]])Describing a subgraph with the string \"(u_1 / into :1 (u_2 / pour) :2 (u_3 / YYY))\" will return only three examples instead of 9 (when we only had a single node as a feature)SentencePredicted labelMatched rule0Governments and industries in nations around the world are pouring XXX into YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / pour) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']1The scientists poured XXX into pint YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / pour) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']2The suspect pushed the XXX into a deep YYY.3The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.4The entity1 to buy papers is pushed into the next entity2.5An unnamed XXX was pushed into the YYY.6Since then, numerous independent feature XXX have journeyed into YYY.7For some reason, the XXX was blinded from his own YYY about the incommensurability of time.8Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.9Olympics have already poured one XXX into the YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / pour) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']10After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.11I placed the XXX in a natural YYY, at the base of a part of the fallen arch.12The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.13The XXX leaked from every conceivable YYY.14The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.15The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.16Gaza XXX recover from three YYY of war.17This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.We can also add negated features that we don't want to match (e.g. this won't match the first row where 'pour' is present):#match a simple graph featureevaluator.match_features(df,[[[\"(u_1 / into :2 (u_3 / YYY))\"],[\"(u_2 / pour)\"],\"Entity-Destination(e1,e2)\"]])SentencePredicted labelMatched rule0Governments and industries in nations around the world are pouring XXX into YYY.1The scientists poured XXX into pint YYY.2The suspect pushed the XXX into a deep YYY.Entity-Destination(e1,e2)[['(u_1 / into :2 (u_3 / YYY))'], ['(u_2 / pour)'], 'Entity-Destination(e1,e2)']3The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.Entity-Destination(e1,e2)[['(u_1 / into :2 (u_3 / YYY))'], ['(u_2 / pour)'], 'Entity-Destination(e1,e2)']4The entity1 to buy papers is pushed into the next entity2.5An unnamed XXX was pushed into the YYY.Entity-Destination(e1,e2)[['(u_1 / into :2 (u_3 / YYY))'], ['(u_2 / pour)'], 'Entity-Destination(e1,e2)']6Since then, numerous independent feature XXX have journeyed into YYY.Entity-Destination(e1,e2)[['(u_1 / into :2 (u_3 / YYY))'], ['(u_2 / pour)'], 'Entity-Destination(e1,e2)']7For some reason, the XXX was blinded from his own YYY about the incommensurability of time.8Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.9Olympics have already poured one XXX into the YYY.10After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.11I placed the XXX in a natural YYY, at the base of a part of the fallen arch.12The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.13The XXX leaked from every conceivable YYY.14The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.15The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.16Gaza XXX recover from three YYY of war.17This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.If we don't want to specify nodes, regex can also be used in place of the node and edge-names:#regex can be used to match any node (this will match instances where 'into' is connected to any node with '1' edge)evaluator.match_features(df,[[[\"(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))\"],[],\"Entity-Destination(e1,e2)\"]])SentencePredicted labelMatched rule0Governments and industries in nations around the world are pouring XXX into YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']1The scientists poured XXX into pint YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']2The suspect pushed the XXX into a deep YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']3The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']4The entity1 to buy papers is pushed into the next entity2.5An unnamed XXX was pushed into the YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']6Since then, numerous independent feature XXX have journeyed into YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']7For some reason, the XXX was blinded from his own YYY about the incommensurability of time.8Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.9Olympics have already poured one XXX into the YYY.Entity-Destination(e1,e2)[['(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))'], [], 'Entity-Destination(e1,e2)']10After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.11I placed the XXX in a natural YYY, at the base of a part of the fallen arch.12The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.13The XXX leaked from every conceivable YYY.14The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.15The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.16Gaza XXX recover from three YYY of war.17This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.We can also train regex rules from a training data, this will automatically replace regex '.*' with nodes that are\n'good enough' statistically based on the provided dataframe.evaluator.train_feature(\"Entity-Destination(e1,e2)\",\"(u_1 / into :1 (u_2 / .*) :2 (u_3 / YYY))\",df)This returns '(u_1 / into :1 (u_2 / push|pour) :2 (u_3 / YYY))' (replaced '.*' withpushandpour)Learning rulesTo extract rules automatically, train the dataset with graph features and rank them based on relevancy:df=dataset.to_dataframe()trainer=GraphTrainer(df)#extract featuresfeatures=trainer.prepare_and_train()fromxpotato.dataset.utilsimportsave_dataframefromsklearn.model_selectionimporttrain_test_splittrain,val=train_test_split(df,test_size=0.2,random_state=1234)#save train and validation, this is important for the frontend to worksave_dataframe(train,'train.tsv')save_dataframe(val,'val.tsv')importjson#also save the ranked featureswithopen(\"features.json\",\"w+\")asf:json.dump(features,f)You can also save the parsed graphs for evaluation or for caching:importpicklewithopen(\"graphs.pickle\",\"wb\")asf:pickle.dump(val.graph,f)FrontendIf the DataFrame is ready with the parsed graphs, the UI can be started to inspect the extracted rules and modify them. The frontend is a streamlit app, the simplest way of starting it is (the training and the validation dataset must be provided):streamlit run frontend/app.py -- -t notebooks/train.tsv -v notebooks/val.tsv -g udit can be also started with the extracted features:streamlit run frontend/app.py -- -t notebooks/train.tsv -v notebooks/val.tsv -g ud -sr notebooks/features.jsonif you already used the UI and extracted the features manually and you want to load it, you can run:streamlit run frontend/app.py -- -t notebooks/train.tsv -v notebooks/val.tsv -g ud -sr notebooks/features.json -hr notebooks/manual_features.jsonAdvanced modeIf labels are not or just partially provided, the frontend can be started also inadvancedmode, where the user canannotatea few examples at the start, then the system gradually offers rules based on the provided examples.Dataset without labels can be initialized with:sentences=[(\"Governments and industries in nations around the world are pouring XXX into YYY.\",\"\"),(\"The scientists poured XXX into pint YYY.\",\"\"),(\"The suspect pushed the XXX into a deep YYY.\",\"\"),(\"The Nepalese government sets up a XXX to inquire into the alleged YYY of diplomatic passports.\",\"\"),(\"The entity1 to buy papers is pushed into the next entity2.\",\"\"),(\"An unnamed XXX was pushed into the YYY.\",\"\"),(\"Since then, numerous independent feature XXX have journeyed into YYY.\",\"\"),(\"For some reason, the XXX was blinded from his own YYY about the incommensurability of time.\",\"\"),(\"Sparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.\",\"\"),(\"Olympics have already poured one XXX into the YYY.\",\"\"),(\"After wrapping him in a light blanket, they placed the XXX in the YYY his father had carved for him.\",\"\"),(\"I placed the XXX in a natural YYY, at the base of a part of the fallen arch.\",\"\"),(\"The XXX was delivered from the YYY of Lincoln Memorial on August 28, 1963 as part of his famous March on Washington.\",\"\"),(\"The XXX leaked from every conceivable YYY.\",\"\"),(\"The scientists placed the XXX in a tiny YYY which gets channelled into cancer cells, and is then unpacked with a laser impulse.\",\"\"),(\"The level surface closest to the MSS, known as the XXX, departs from an YYY by about 100 m in each direction.\",\"\"),(\"Gaza XXX recover from three YYY of war.\",\"\"),(\"This latest XXX from the animation YYY at Pixar is beautiful, masterly, inspired - and delivers a powerful ecological message.\",\"\")]Then, the frontend can be started:streamlit run frontend/app.py -- -t notebooks/unsupervised_dataset.tsv -g ud -m advancedOnce the frontend starts up and you define the labels, you are faced with the annotation interface. You can search elements by clicking on the appropriate column name and applying the desired filter. You can annotate instances by checking the checkbox at the beginning of the line. You can check multiple checkboxs at a time. Once you've selected the utterances you want to annotate, click on theAnnotatebutton. The annotated samples will appear in the lower table. You can clear the annotation of certain elements by selecting them in the second table and clickingClear annotation.Once you have some annotated data, you can train rules by clicking theTrain!button. It is recommended to set theRank features based on accuracyto True, if you have just a few samples. You will get a similar interface as in supervised mode, you can generate rule suggestions, and write your own rules as usual. Once you are satisfied with the rules, select each of them and clickannotate based on selected. This process might take a while if you are working with large data. You should get all the rule matches marked in the first and the second tables. You can order the tables by each column, so it's easier to check. You will have to manually accept the annotations generated this way for them to appear in the second table.You can read about the use of the advanced mode in thedocsEvaluateIf you have the features ready and you want to evaluate them on a test set, you can run:pythonscripts/evaluate.py-tud-fnotebooks/features.json-dnotebooks/val.tsvThe result will be acsvfile with the labels and the matched rules.ServiceIf you are ready with the extracted features and want to use our package in production for inference (generating predictions for sentences), we also provide a REST API built on POTATO (based onfastapi).First install FastAPI andUvicornpipinstallfastapi\npipinstall\"uvicorn[standard]\"To start the service, you should setlanguage,graph_typeand thefeaturesfor the service. This can be done through enviroment variables.Example:exportFEATURE_PATH=/home/adaamko/projects/POTATO/features/semeval/test_features.jsonexportGRAPH_FORMAT=udexportLANG=enThen, start the REST API:pythonservices/main.pyIt will start a service running onlocalhoston port8000(it will also initialize the correct models).Then you can use any client to make post requests:curl-XPOSTlocalhost:8000-H'Content-Type: application/json'-d'{\"text\":\"The suspect pushed the XXX into a deep YYY.\\nSparky Anderson is making progress in his XXX from YYY and could return to managing the Detroit Tigers within a week.\"}'The answer will be a list with the predicted labels (if none of the rules match, it will return \"NONE\"):[\"Entity-Destination(e1,e2)\",\"NONE\"]The streamlit frontend also has an inference mode, where the implemented rule-system can be used for inference. It can be started with:streamlitrunfrontend/app.py---hrfeatures/semeval/test_features.json-minferenceContributingWe welcome all contributions! Please fork this repository and create a branch for your modifications. We suggest getting in touch with us first, by opening an issue or by writing an email to Adam Kovacs or Gabor Recski atfirstname.lastname@tuwien.ac.atCitingIf you use the library, please cite ourpaperpublished in CIKM 2022:@inproceedings{Kovacs:2022,author={Kov\\'{a}cs, \\'{A}d\\'{a}m and G\\'{e}mes, Kinga and Ikl\\'{o}di, Eszter and Recski, G\\'{a}bor},title={POTATO: ExPlainable InfOrmation ExTrAcTion FramewOrk},year={2022},isbn={9781450392365},publisher={Association for Computing Machinery},address={New York, NY, USA},url={https://doi.org/10.1145/3511808.3557196},doi={10.1145/3511808.3557196},booktitle={Proceedings of the 31st ACM International Conference on Information & Knowledge Management},pages={4897\u20134901},numpages={5},keywords={explainability, explainable, hitl},location={Atlanta, GA, USA},series={CIKM '22}}LicenseMIT license"} +{"package": "xpprint", "pacakge-description": "No description available on PyPI."} +{"package": "xpra", "pacakge-description": "Xpra is a multi platform persistent remote display server and client for forwarding applications and desktop screens. Also known as \u2018screen for X11\u2019."} +{"package": "xprec", "pacakge-description": "Library for double-double arithmetic calculationExtension module for numpy providing theddoubledata type.Loading this module registers an additional scalar data typeddoublewith\nnumpy implementing double-double arithmetic. You can use use the data type\nby passingdtype=xprec.ddoubleto numpy functions.Thexprec.linalgmodule provides some linear algebra subroutines, in\nparticular QR, RRQR, SVD and truncated SVD.Installation$ pip install xprecQuickstartimport numpy as np\nx = np.linspace(0, np.pi)\n\n# import double-double precision data type\nfrom xprec import ddouble\nx = x.astype(ddouble)\ny = x * x + 1\nz = np.sin(x)\n\n# do some linalg\nimport xprec.linalg\nA = np.vander(np.linspace(-1, 1, 80, dtype=ddouble), 150)\nU, s, VT = xprec.linalg.svd(A)Trouble shootingiccYou may suffer from a long runtime when xprec is built with icc. If you encounter this problem, please try the following:CFLAGS=\"-fp-model=precise\" pip install xprecLicenceThe xprec library is\nCopyright (C) 2021 Markus Wallerberger.\nLicensed under the MIT license (see LICENSE.txt).Contains code from the QD library, which is\nCopyright (C) 2012 Yozo Hida, Xiaoye S. Li, David H. Bailey.\nReleased under a modified BSD license (see QD-LICENSE.txt)."} +{"package": "xpress", "pacakge-description": "FICO\u00ae Xpress Python interfaceCreate and solve Mathematical Optimization problems like the following:min x1^2 + 2 x2\ns.t. x1 + 3 x2 >= 4\n -10 <= x1 <= 10\n x1 in Z\n x2 >= 0with just a few lines of code:importxpressasxpx1=xp.var(vartype=xp.integer,name='x1',lb=-10,ub=10)x2=xp.var(name='x2')p=xp.problem(x1,x2,# variables of the problemx1**2+2*x2,# single expression is taken as the objective functionx1+3*x2>=4,# one or more constraintsname='myexample')# problem name (optional)p.optimize()print(\"solution:{0}={1};{2}={3}\".format(x1.name,p.getSolution(x1),x2.name,p.getSolution(x2)))With thexpressmodule, one can create and solve optimization problems using the Python\u00ae programming language and theFICO XpressOptimizer library. The module allows forCreating, handling, solving, and querying optimization problems;Using Python numerical libraries such as NumPy to create optimization problems;Setting and getting the value of parameters (controls and attributes) of a problem; andUsing Python functions as callbacks for the Xpress Optimizer and the Xpress Nonlinear solver.The Xpress Python interface allows for creating, handling, and solving all problems that can be solved with the FICO-Xpress library: Linear Programming (LP), Quadratic Programming (QP), Second-Order Conic Programming (SOCP), and their mixed-integer extensions: MILP, MIQP, MIQCQP, MISOCP, together with general nonlinear and mixed-integer nonlinear.InstallationThe Xpress Python interface can be downloaded fromPyPIand fromAnaconda. Runpip install xpressto install from PyPI, andconda install -c fico-xpress xpressto install from the Conda repository.The downloaded package contains: a folder with several examples of usages of the module, with varying degrees of difficulty; a directorylicensecontaining theXpress Community License; and a directorydocwith the manual in PDF version---the full HTML documentation for the Xpress Optimizer's library, including the Python interface with its example, is also available at theFICO Xpress Optimization Helppage.If you do not have any FICO Xpress license, the community license will be recognized by the module and no further action is needed. If you do have a license, for instance located in/users/johndoe/xpauth.xpr, make sure to set the global environment variableXPRESSto point to the folder containing thexpauth.xprfile, i.e.XPRESS=/user/johndoe.LicensingThe Xpress software is governed by theXpress Shrinkwrap License Agreement. When downloading the package, you accept the license terms. A copy of the Xpress Shrinkwrap License is stored in the fileLICENSE.txtin thedist-infodirectory of the Xpress module.This package includes the community license of Xpress, see thelicensing options overviewfor more details.Miscellaneous\"Python\" is a registered trademark of the Python Software Foundation. \"FICO\" is a registered trademark of Fair Isaac Corporation in the United States and may be a registered trademark of Fair Isaac Corporation in other countries. Other product and company names herein may be trademarks of their respective owners.Copyright (C) Fair Isaac 1983-2024"} +{"package": "xpresscli", "pacakge-description": "Example UsageAssumptions:The filecli.tomlexists in the current working directory; otherwise the user must specify the path to the\nconfiguration file and pass it to theClientconstructor.The filecli.tomlcontains the complete CLI description consisting of:general description of the CLI handler;detailed description of each client command;details about how each command is routed;First, we will work out the JSON schema for the client definition.{\"client\":{\"prog\":\"sff\",\"description\":\"The EMDB-SFF Read/Write Toolkit (sfftk-rw)\",\"options\":[{\"name\":[\"-V\",\"--version\"],\"help\":\"Show the version and exit\",\"action\":\"store_true\"},{\"name\":[\"-c\",\"--config-file\"],\"help\":\"The path to the configuration file\",\"type\":\"str\",\"required\":false},{\"name\":[\"-v\",\"--verbose\"],\"help\":\"Show more information about the analysis\",\"action\":\"store_true\"}]},\"config_file\":{\"format\":\"ini\",\"filename\":\"sfftk.conf\",\"location\":\"user\",\"create\":true},\"commands\":[{\"name\":\"convert\",\"description\":\"Perform EMDB-SFF file format interconversions\",\"manager\":\"sfftkrw.sffrw.handle_convert\",\"groups\":{\"output\":{\"required\":true,\"mutually_exclusive\":true}},\"options\":[{\"name\":[\"from_file\"],\"nargs\":\"*\",\"help\":\"file to convert from\",\"validator\":\"sfftkrw.validators.FileExists\"},{\"name\":[\"-D\",\"--details\"],\"help\":\"populate the
          ...
          in the XML file\"},{\"name\":[\"-R\",\"--primary-descriptor\"],\"help\":\"populate the ... in the XML file\",\"validator\":\"sfftkrw.validators.PrimaryDescriptor\"},{\"name\":[\"-x\",\"--exclude-geometry\"],\"help\":\"exclude geometry data from the SFF file\",\"action\":\"store_true\"},{\"name\":[\"--json-indent\"],\"help\":\"indentation level for JSON output\",\"type\":\"int\",\"default\":4},{\"name\":[\"--json-sort-keys\"],\"help\":\"sort keys for JSON output\",\"action\":\"store_true\"},{\"name\":[\"-o', '--output\"],\"help\":\"output file name\",\"group\":\"output\"},{\"name\":[\"-f\",\"--format\"],\"help\":\"output file format\",\"choices\":[\"sff\",\"xml\",\"json\"],\"group\":\"output\"}]},{\"name\":\"view\",\"description\":\"View EMDB-SFF files\",\"manager\":\"sfftkrw.sffrw.handle_view\",\"options\":[{\"name\":[\"from_file\"],\"nargs\":\"*\",\"help\":\"file to view\",\"validator\":\"sfftkrw.validators.FileExists\"},{\"name\":[\"--sff-version\"],\"help\":\"display the SFF version\",\"action\":\"store_true\"}]}]}TOML is a much better way to capture the client description because it can accommodate coments and is far more compact (no extraneous braces). The equivalent TOML file is:[client]prog=\"sff\"description=\"The EMDB-SFF Read/Write Toolkit (sfftk-rw)\"[[client.options]]name=[\"-V\",\"--version\"]help=\"Show the version and exit\"action=\"store_true\"[[client.options]]name=[\"-c\",\"--config-file\"]help=\"The path to the configuration file\"type=\"str\"required=false[[client.options]]name=[\"-v\",\"--verbose\"]help=\"Show more information about the analysis\"action=\"store_true\"[config_file]format=\"ini\"filename=\"sfftk.conf\"location=\"user\"create=true[[commands]]name=\"convert\"description=\"Perform EMDB-SFF file format interconversions\"manager=\"sfftkrw.sffrw.handle_convert\"[commands.groups.output]required=truemutually_exclusive=true[[commands.options]]name=[\"from_file\"]nargs=\"*\"help=\"file to convert from\"validator=\"sfftkrw.validators.FileExists\"[[commands.options]]name=[\"-D\",\"--details\"]help=\"populate the
          ...
          in the XML file\"[[commands.options]]name=[\"-R\",\"--primary-descriptor\"]help=\"populate the ... in the XML file\"validator=\"sfftkrw.validators.PrimaryDescriptor\"[[commands.options]]name=[\"-x\",\"--exclude-geometry\"]help=\"exclude geometry data from the SFF file\"action=\"store_true\"[[commands.options]]name=[\"--json-indent\"]help=\"indentation level for JSON output\"type=\"int\"default=4[[commands.options]]name=[\"--json-sort-keys\"]help=\"sort keys for JSON output\"action=\"store_true\"[[commands.options]]name=[\"-o\",\"--output\"]help=\"output file name\"group=\"output\"[[commands.options]]name=[\"-f\",\"--format\"]help=\"output file format\"choices=[\"sff\",\"xml\",\"json\"]group=\"output\"[[commands]]name=\"view\"description=\"View EMDB-SFF files\"manager=\"sfftkrw.sffrw.handle_view\"[[commands.options]]name=[\"from_file\"]nargs=\"*\"help=\"file to view\"validator=\"sfftkrw.validators.FileExists\"[[commands.options]]name=[\"--sff-version\"]help=\"display the SFF version\"action=\"store_true\"importsysfromclientimportClientdefmain():\"\"\"Entry point for the application script\"\"\"withClient()ascli:exit_status=cli.execute()returnexit_statusif__name__==\"__main__\":sys.exit(main())"} +{"package": "xpressinsight", "pacakge-description": "FICO\u00aeXpress Insight Python PackageThe 'xpressinsight' Python package can be used to develop Python\u00aebased web applications for Xpress Insight.DocumentationFICO Xpress Insight 4 Python Package Reference ManualFICO Xpress Insight 4 Developers Guide For PythonFICO Xpress Insight 5 Python Package Reference ManualFICO Xpress Insight 5 Developers Guide For PythonRelease Notesv 1.9.0 (Insight 5.9.0)New functionAppBase.initialize_entitiesfor initializing selected app entities to their default values.Add support for calling app interface & other standard functions from multiple threads.Theattach_statusproperty now holds the status of the last attachment operation invoked from the current thread;\npreviously it referred to the last attachment operation from any thread.Theattach_statusproperty is no longer read-only.The internal work folder is now calledxpressinsightinstead ofinsight.The following changes only affect test mode:The execution mode work folder is now a sub-folderwork_dirwithin the application folder.Thexpressinsightwork folder is now created as a sub-folder of the execution mode work folder.Resolved issues when attachment filenames end.properties.v 1.8.0 (Insight 5.8.0)New functionget_scenario_dataallows reading entities from other apps and scenarios.Introducexi.types.Columnclass which can be used in place ofxi.Columnin app definitions. There is currently no\nplan to removexi.Column.Attempt to capture entity data after an execution mode that ended abnormally (exception raised orsys.exitcalled).v 1.7.1 (Insight 5.7.0)New functionget_solution_databasereturns the location and credentials of the DMP solution's database.Enabled functionsget_app_attach,get_scen_attachandput_scen_attachto write/read the attachment to/from a\nfolder other than the work directory or a local filename different from attachment name.Enabled functionsget_attach_by_tag,get_attachs_by_tagandget_attach_filenames_by_tagto write the\nattachments to a folder other than the work directory.Fixed an issue with theInsightDmpContext.solution_token_expiry_timevalue in non-UTC timezones.Removed support for Python 3.7. This version supports only Python 3.8 - 3.11.v 1.6.0 (Insight 5.6.0)Resolved an error when a script declares multiple app classes with a shared superclass.Added attributedefaultto thexi.Columnclass.Use of the old syntax for annotating entities (e.g.xi.Scalarinstead ofxi.types.Scalar) will cause a warning\nmessage when the app is built or executed in Python 3.11. This syntax has been deprecated and will not be usable\nat all in Python 3.12+.New functionget_insight_contextreturns information about the Insight server and the DMP solution.Python 3.11 support.Pandas 2.0 support.v 1.5.0 (Insight 5.5.0)Allow an Index entity to be referenced multiple times within a single Series or DataFrame -\ne.g.Distance: xi.types.Series(index=['City', 'City'], dtype=xi.real).Supportmultiprocessingpackage.v 1.4.1 (Insight 4.59.6)Resolve issue building apps with Xpress 9.2 and apprunner 1.4.Update dependencies to require Pandas v1 with xpressinsight 1.4.v 1.4.0 (Insight 5.4.0 and 4.59.2)New syntax for annotating entities,xi.types.Scalar/Param/Index/Series/DataFrameinstead\nofxi.Scalar/Param/Index/Series/DataFrame.The new syntax is compatible with forward annotations (from __future__ import annotations).The old syntax will continue to work in Python 3.7-3.10 but will not be usable in Python 3.11+,\nso we recommend existing apps are migrated from the old to the new syntax.When the new syntax is used, entities may also be declared in a parent class of the Insight\napplication class.v 1.3.0 (Insight 5.3.0 and 4.59.0)Support for Insight 5 custom progress notifications:Added functionssend_progress_update,get_messagesandput_messagesto Insight application interface\n(AppInterface).Added thesend_progressattribute theExecMode,ExecModeLoad, andExecModeRundecorators.Added theupdate_progressattribute to the entity type annotations.RHEL 8 support.Python 3.10 supportAt time of writing the \u2018default\u2019 Anaconda channel does not have all the dependencies required by thexpressinsightpackage for this Python version. We recommend conda users to stick with Python 3.9, or use a\ndifferent distribution of Python 3.10 until this is resolved.Fixed an issue that caused a failure if the path to the temporary directory contained a space.v 1.2.3 (Insight 5.2.1 and 4.58.0)Added thethreadsattribute to theExecMode,ExecModeLoad, andExecModeRundecorators.v 1.2.2Fixed an issue that could cause a type check exception when the user created\nempty (null) fields in a DataFrame column in the Insight UI.v 1.2.1Added test mode functionsadd_item_infoandclear_item_infosto Insight application interface.Added functionscenario_parent_pathto Insight application interface.AddedRepositoryPathclass for building and parsing of repository paths.v 1.2.0Added scenario types property (scen_types) to application configuration (AppConfig).Added repository functionsget_item_infoandget_item_infosto Insight application interface (AppInterface).v 1.1.3Performance improvements.Python 3.9 support.v 1.1.2Fixed an exception that could occur when an empty MultiIndex DataFrame has been assigned to an Insight entity.Updated documentation describing how to set up Anaconda.v 1.1.1Improve error message when Insight cannot start Python because of security restrictions.Update documentation and update VDL version number in examples.v 1.1.0Additional factory functioncreate_appinitializes and configures standard test environment.Some performance issues with executing a Python based scenario have been addressed.Maximum length of a string in an Index, Series, or DataFrame has been changed from 1,000,000 bytes to 250,000 characters.Default name of the temporary Insight working directory has been changed from \"insight\" to \"work_dir/insight\".v 1.0.2The functionsupdateandreset_progresshave been added to the Insight Python interface.Changed Python standard output to unbuffered mode to improve responsiveness of output messages.LicensingThe Xpress software is governed by theXpress Shrinkwrap License Agreement.\nWhen downloading or using the package, you accept the license terms. After installation, a copy of the Xpress Shrinkwrap\nLicense will be stored in theLICENSE.txtfile in thesite-packages/xpressinsight-*.dist-infodirectory.\nIn Anaconda, a copy of the license file will be stored in thepkgs/xpressinsight-*/info/licensesdirectory.\"Python\" is a registered trademark of the Python Software Foundation.\n\"FICO\" is a registered trademark of Fair Isaac Corporation in the United States\nand may be a registered trademark of Fair Isaac Corporation in other countries.\nOther product and company names herein may be trademarks of their respective owners.\u00a9 Copyright 2012-2024 Fair Isaac Corporation. All rights reserved."} +{"package": "xpression", "pacakge-description": "xpress - Build expressions, serialize them as JSON, and evaluate them in Pythonxpress is inspired by JsonLogic but aims to terser at the cost of reduced features. It ONLY supports logical operators.Virtuesxpress follows similar principles as JsonLogicTerse(er).Readable. As close to infix expressions as possibleConsistent. 3-tuple expressions[\"operand\", \"operator\", \"operand\"]joined byANDand/orORSecure. We nevereval()Flexible. Easy to add new operators, easy to build complex structuresLimitationsOnly logical operators are supported.Unary operators are not supported.ExamplesSimplexpress.evaluate([1,\"==\",1])# TrueThis is a simple rule, equivalent to 1 == 1. A few things about the format:The operator is always at the 2nd position(index: 1) in the expression 3-tuple. There is only one operator per expression.The operands are either a literal, a variable or an array of literals and/or variables.Each value can be a string, number, boolean, array (non-associative), or nullCompoundHere we\u2019re beginning to nest rules.xpress.evaluate([[3,\">\",1],\"and\",[1,\"<\",3]])# TrueIn an infix language (like Python) this could be written as:((3>1)and(1<3))Data-DrivenObviously these rules aren\u2019t very interesting if they can only take static literal data. Typically xpress will be called with a rule object and a data object. You can use the var operator to get attributes of the data object. Here\u2019s a complex rule that mixes literals and data. The pie isn\u2019t ready to eat unless it\u2019s cooler than 110 degrees, and filled with apples.rules=[[\"var:temp\",\"<\",110],\"and\",[\"var:pie.filling\",\"==\",\"apple\"]]data={\"temp\":100,\"pie\":{\"filling\":\"apple\"}};xpress.evaluate(rules,data);# TrueAlways and NeverSometimes the rule you want to process is \u201cAlways\u201d or \u201cNever.\u201d If the first parameter passed to jsonLogic is a non-object, non-associative-array, it is returned immediately.# Alwaysxpress.evaluate(True,data_will_be_ignored)# True# Neverxpress.evaluate(False,i_wasnt_even_supposed_to_be_here)# FalseSupported OperationsAccessing DatavarLogical and Boolean Operators=====!=!==orandNumeric Operators>,>=,Item:returnItem(item_id=item_id,name=name)app=App(routes=[Path(\"/items/{item_id}\",get=read_item,)])Run the application:uvicornexample:appNavigate tohttp://127.0.0.1:8000/items/123?name=foobarbazin your browser.\nYou will get the following JSON response:{\"item_id\":123,\"name\":\"foobarbaz\"}Now navigate tohttp://127.0.0.1:8000/docsto poke around the interactiveSwagger UIdocumentation:For more examples, tutorials and reference materials, see ourdocumentation.Inspiration and relationship to other frameworksXpresso is mainly inspired by FastAPI.\nFastAPI pioneered several ideas that are core to Xpresso's approach:Leverage Pydantic for JSON parsing, validation and schema generation.Leverage Starlette for routing and other low level web framework functionality.Provide a simple but powerful dependency injection system.Use that dependency injection system to provide extraction of request bodies, forms, query parameters, etc.Xpresso takes these ideas and refines them by:Decoupling the dependency injection system from the request/response cycle, leading to an overall much more flexible and powerful dependency injection system, packaged up as the standalonedilibrary.Decoupling the framework from Pydantic by usingAnnotated(PEP 593) instead of default values (param: FromQuery[str]instead ofparam: str = Query(...)).Middleware on Routersso that you can use generic ASGI middleware in a routing-aware manner (for example, installing profiling middleware on only some paths without using regex matching).Support forlifespans on any Router or mounted App(this silently fails in FastAPI and Starlette)dependency injection into the application lifespanand support formultiple dependency scopes.Formalizing the framework for extracting parameters and bodies from requests into theBinder APIso that 3rd party extensions can do anything the framework does.Support forcustomizing parameter and form serialization.Better performance by implementingdependency resolution in Rust,executing dependencies concurrentlyandcontrolling threading of sync dependencies on a per-dependency basis.Current stateThis project is under active development.\nIt should not be considered \"stable\" or ready to be used in production.\nIt is however ready for experimentation and learning!What is implemented and mostly stable?Extraction and OpenAPI documentation of parameters (query, headers, etc.) and request bodies (including multipart requests).Parameter serialization.Routing, including applications, routers and routes.Dependency injection and testing utilities (dependency overrides).Most of this APIs will begenerallystable going forward, although some minor aspects like argument names will probably change at some point.What is not implemented or unstable?Low-level API for binders (stuff inxpresso.binders): this is public, but should be considered experimental and is likely to change. The high level APIs (FromPath[str]andAnnotated[str, PathParam(...)]) are likely to be stable.Security dependencies and OpenAPI integration. This part used to exist, but needed some work. It is planned for the future, but we need to think about the scope of these features and the API.See this release on GitHub:v0.46.0"} +{"package": "xpring", "pacakge-description": "The Xpring SDK for Python.Installpipinstallxpring[py]APIWalletConstructYou can construct aWalletfrom its seed.\nIf you do not have your own wallet yet, you cangenerate one with some free\nXRP on the testnet.importxpringseed='sEdSKaCy2JT7JaM7v95H9SxkhP9wS2r'wallet=xpring.Wallet.from_seed(seed)print(wallet.private_key.hex())# b4c4e046826bd26190d09715fc31f4e6a728204eadd112905b08b14b7f15c4f3print(wallet.public_key.hex())# ed01fa53fa5a7e77798f882ece20b1abc00bb358a9e55a202d0d0676bd0ce37a63print(wallet.account_id.hex())# d28b177e48d9a8d057e70f7e464b498367281b98print(wallet.address)# rLUEXYuLiQptky37CqLcm9USQpPiz5rkpDSign / VerifyAWalletcan sign and verify arbitrary bytes, but you\u2019ll generally\nwant to leave these low-level responsibilities to theClient.message=bytes.fromhex('DEADBEEF')signature=wallet.sign(message)wallet.verify(message,signature)# TrueClientClientis the gateway to the XRP Ledger.\nIt is constructed with the URL of the gRPC service of arippledserver.\nIf you are running the server yourself,\nyou need to configure the[port_grpc]stanza in your configuration file.\nIn theexampleconfiguration file, it iscommentedout.# url = 'main.xrp.xpring.io:50051' # Mainneturl='test.xrp.xpring.io:50051'# Testnetclient=xpring.Client.from_url(url)Account>>>client.get_account(wallet.address)account_data{account{value{address:\"rDuKotkyx18D5WqWCA4mVhRWK2YLqDFKaY\"}}balance{value{xrp_amount{drops:999999820}}}sequence:{value:10}flags{}owner_count{}previous_transaction_id{value:b\"...\"}previous_transaction_ledger_sequence{value:4845872}}ledger_index:4869818Fee>>>client.get_fee()current_ledger_size:6fee{base_fee{drops:10}median_fee{drops:5000}minimum_fee{drops:10}open_ledger_fee{drops:10}}expected_ledger_size:25ledger_current_index:4869844levels{median_level:128000minimum_level:256open_ledger_level:256reference_level:256}max_queue_size:2000Submit>>>unsigned_transaction={...'Account':'rDuKotkyx18D5WqWCA4mVhRWK2YLqDFKaY',...'Amount':'10',...'Destination':'rNJDvXkaBRwJYdeEcx9pchE2SecMkH3FLz',...'Fee':'10',...'Flags':0x80000000,...'Sequence':9,...'TransactionType':'Payment'...}>>>signed_transaction=wallet.sign_transaction(unsigned_transaction)>>>client.submit(signed_transaction)engine_result{result_type:RESULT_TYPE_TESresult:\"tesSUCCESS\"}engine_result_message:\"The transaction was applied. Only final in a validated ledger.\"hash:b\"...\">>>client.submit(signed_transaction)engine_result{result_type:RESULT_TYPE_TEFresult:\"tefPAST_SEQ\"}engine_result_code:-190engine_result_message:\"This sequence number has already passed.\"hash:b\"...\"Transaction>>>txid=bytes.fromhex(signed_transaction['hash'])>>>client.get_transaction(txid)transaction{account{value{address:\"rDuKotkyx18D5WqWCA4mVhRWK2YLqDFKaY\"}}fee{drops:10}sequence{value:10}payment{amount{value{xrp_amount{drops:10}}}destination{value{address:\"rNJDvXkaBRwJYdeEcx9pchE2SecMkH3FLz\"}}}signing_public_key{value:b\"...\"}transaction_signature{value:b\"...\"}flags{value:2147483648}}ledger_index:5124377hash:b\"...\"validated:truemeta{transaction_index:1transaction_result{result_type:RESULT_TYPE_TESresult:\"tesSUCCESS\"}affected_nodes{ledger_entry_type:LEDGER_ENTRY_TYPE_ACCOUNT_ROOTledger_index:b\"...\"modified_node{final_fields{account_root{account{value{address:\"rNJDvXkaBRwJYdeEcx9pchE2SecMkH3FLz\"}}balance{value{xrp_amount{drops:1000000100}}}sequence{value:1}flags{}owner_count{}}}previous_fields{account_root{balance{value{xrp_amount{drops:1000000090}}}}}previous_transaction_id{value:b\"...\"}previous_transaction_ledger_sequence{value:4845872}}}affected_nodes{ledger_entry_type:LEDGER_ENTRY_TYPE_ACCOUNT_ROOTledger_index:b\"...\"modified_node{final_fields{account_root{account{value{address:\"rDuKotkyx18D5WqWCA4mVhRWK2YLqDFKaY\"}}balance{value{xrp_amount{drops:999999800}}}sequence{value:11}flags{}owner_count{}}}previous_fields{account_root{balance{value{xrp_amount{drops:999999820}}}sequence{value:10}}}previous_transaction_id{value:b\"...\"}previous_transaction_ledger_sequence{value:4845872}}}delivered_amount{value{xrp_amount{drops:10}}}}date{value:636581642}"} +{"package": "xprint", "pacakge-description": "xprintDevelopment EnvironmentWindows 10Python 3.7.0Installation$ pip3 install xprintUsageImport:import xprint as xp\n\n# xp.init()Base:xp.wr()xp.fi()Usage:xp.success()xp.error()xp.value()xp.step()xp.job()xp.about_t()xp.about_to()xp.getting()..."} +{"package": "xprintidle", "pacakge-description": "# python-xprintidle\nA cffi wrapper around xprintidle.This uses a modified version of xprintidle.c fromhttps://github.com/pmaia/xprintidle-plus- I\u2019m fairly sure I\u2019ve satisfied the GPL but not 100% sure. Please let me know if there\u2019s an issue!Usage/docs coming soon.For now:` import xprintidle print xprintidle.idle_time() `## RequireslibX11libXssa c compiler and python dev headers## Installationpip install xprintidle"} +{"package": "xprintlog", "pacakge-description": "xprintlog\u65e0\u4fb5\u5165\u5e2e\u52a9\u4f60\u66ff\u6362\u5c06\u51fd\u6570\u5185\u90e8\u7684print\u51fd\u6570\u66ff\u6362\u4e3alogging\u5b89\u88c5pipinstallxprintlog\u4f7f\u7528\u76f4\u63a5\u4f7f\u7528\u88c5\u9970\u5668\u8fdb\u884c\u88c5\u9970# test.pyimportxprintlogasxprint@xprint.xprint()deftest():print(111)test()#[.\\test.py:6 - test][DEBUG] - 111\u4f7f\u7528\u7c7b\u4f3c\u4e8elogging\u7684\u65b9\u5f0f\uff0c\u8fdb\u884c\u7b49\u7ea7\u8bbe\u7f6eimportxprintlogasxprint@xprint.xprint(print_level=xprint.INFO,level=xprint.DEBUG)deftest():print(111)test()# [.\\test.py:7 - test][INFO] - 111@xprint.xprint(print_level=xprint.DEBUG,level=xprint.INFO)deftest1():print(111)test1()# \u8fd9\u91cc\u6ca1\u6709\u8f93\u51fa\u652f\u6301\u51fd\u6570\u5d4c\u5957\uff0c\u4e14\u51fd\u6570\u95f4\u4e92\u4e0d\u5f71\u54cdimportxprintlogasxprint@xprint.xprint(print_level=xprint.INFO,level=xprint.DEBUG)deftest():print(111)@xprint.xprint(print_level=xprint.DEBUG,level=xprint.INFO)deftest1():print(111)test()test1()# [.\\test.py:7 - test][INFO] - 111"} +{"package": "xprize-data", "pacakge-description": "No description available on PyPI."} +{"package": "xprizo-sdk-py", "pacakge-description": "Xprizo api endpoints # noqa: E501"} +{"package": "xproc", "pacakge-description": "xprocInstallpipinstall-UxprocSupport commandsxproc memorxproc memoryxprocmemTIMEKERNELUSERMemFreeMemTotal21:19:371345876kB13143712kB10079620kB24624680kB21:19:381345964kB13143796kB10079612kB24624680kB21:19:391345964kB13143804kB10079612kB24624680kB21:19:401345964kB13143808kB10079644kB24624680kB21:19:411345964kB13143808kB10079580kB24624680kBxprocmem-e\"Active,Inactive,Active(anon),Inactive(anon),Active(file),Inactive(file)\"TIMEActiveInactiveActive(anon)Inactive(anon)Active(file)Inactive(file)21:21:194397264kB8727816kB173164kB128kB4224100kB8727688kB21:21:214397404kB8727816kB173300kB128kB4224104kB8727688kB21:21:234397404kB8727816kB173300kB128kB4224104kB8727688kB21:21:254397404kB8727816kB173300kB128kB4224104kB8727688kB21:21:274397404kB8727816kB173300kB128kB4224104kB8727688kBxproc vmstatxprocvmstat15TIMEallocstall_movableallocstall_normalcompact_failcompact_free_scannedcompact_isolatedcompact_migrate_scannedcompact_stallcompact_success10:15:01409085501083447544343462565610:15:02409085501083447544343462565610:15:03409085501083447544343462565610:15:04409085501083447544343462565610:15:054090855010834475443434625656xproc loadxprocload13TIMELOAD_1_MINLOAD_5_MINLOAD_15_MINNR_RUNNINGNR_TOTALLAST_PID14:28:340.070.180.151316207310214:28:350.070.180.151316207310214:28:360.070.180.1513162073102"} +{"package": "xprocrustes", "pacakge-description": "xprocrustesPython library of Procrustes alignment algorithmsCreated byBaihan Lin, Columbia University"} +{"package": "xprod-call-router", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-crm", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-crypta-util", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-datacloud", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-data-schema", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-dev-utils", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-input-checker", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-input-pipeline", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-key-manager", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-logging", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-ml-utils", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-partners-data", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-pykikimr", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-short-links", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-sms", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprod-yt-pipeline", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xprofile", "pacakge-description": "A tool to manage and automatically apply xrandr configurations.xprofileis compatible with and tested on python versions:2.62.73.23.33.4installationA universal installation method is to use pip (the pip package is availablehere):$ pip install --upgrade xprofileBefore installingxprofilewith pip see if a package for your Operating\nSystem exists.To installxprofilefor arch linux you can use theAUR package:# This is an example using yaourt\n$ yaourt -S xprofileusageOncexprofilehas been installed you can execute the following command to get\nsome help:$ xprofile --help\nusage: xprofile [-h] [--verbose] [--config CONFIG] [--version]\n {list,current,generate,activate} ...\n\nA tool to manage and automatically apply xrandr configurations.\n\noptional arguments:\n -h, --help show this help message and exit\n --verbose output more verbosely\n --config CONFIG config file to read profiles from\n --version show program's version number and exit\n\nsubcommands:\n The following commands are available\n\n {list,current,generate,activate}\n list list all available xrandr profiles\n current get information about the current active profile\n generate generate a new profile and print to stdout\n activate activate the given profile or automatically select oneTo get detailed help for a specific subcommand use:$ xprofile [subcommand] --helpOr refer to thexprofile(1) andxprofilerc(5) man pages.licensexprofileis licensed under GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007The GNU General Public License is a free, copyleft license for software and\nother kinds of works.For the full license information refer to theLICENSEfile in the github\nrepository."} +{"package": "xprompt", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xprompt-client", "pacakge-description": "XPrompt clientclient for XPromptExampleimport xprmopt\napi_key_response = xprompt.login(user_email='..', password='..')\n\nxprompt.api_key = api_key_response['access_token']\nxprompt.openai_api_key = \"\"\n\n\nprompt = \"\"\"tell me a joke\"\"\"\n\nr = xprompt.OpenAIChatCompletion.create(model=\"gpt-3.5-turbo\", messages=[{\"role\": \"user\", \"content\": prompt}], temperature=0)\nprint(r)Publish clientupdate the xprompt-common version inpyproject.tomlbump version inpyproject.tomlpoetry buildpoetry publishgit tag -a v0.1.0 -m \"version 0.1.0\"Test out the client publishedcreate a new venvinstall the clientpip install xpromptrun the example above"} +{"package": "xprompt-common", "pacakge-description": "XPrompt commonxprompt client and server shared componentspublish common libbump version inpyproject.tomlpoetry buildpoetry publishgit tag -a v0.1.0 -m \"version 0.1.0\""} +{"package": "xps", "pacakge-description": "X-ray photoelectron spectroscopy (XPS)FutureDocmuentation (priority)Add database of inelastic mean free path (IMFP) of common materialsX-ray Photonelectron SpectroscopyExampleAn example analyzing a Ge peak fit within CasaXPS.import xps\n\n# Shortcut for the XPS machine at Dalhousie\n# xps_mach = 'Dalhousie'\n# mach = xps.MACH_PARAM[xps_mach]\nmach = {\n 'coef' : [0.9033, -4.0724, 5.0677, 1.1066],\n 'scale' : 0.01,\n 'work_func' : 4.6,\n}\nhv = xps.PHOTON_ENERGY['Al']\n\n# Pass energy [eV], found from XPS operator\npe = 30\n\nsfwagner_Ge = xps.sf.Ge['3d']['area']\n\ndata = xps.parser.CasaXPS('Ge_example.csv')\n\n# Labels defined by user in CasaXPS fits\npk_lbl = 'Ge 3d'\nbe = data.binding_energy(pk_lbl)\narea = data.area(pk_lbl)\n\nke = xps.kinetic_energy(be, hv, mach['work_func'])\n\nt_fn = xps.transmission(ke, pe, mach['coef'], mach['scale'])\nt_fn_wagner = 1/ke # Proportional to 1/KE\n\nsf_mach = xps.sf_machine(sfwagner_Ge, t_fn, t_fn_wagner)\n\npk_corr = xps.peak_correction(area, sf_mach)\n\n# NOTE Use the xps.XPSPeak(...) helper for convienence\n# analyzed_Ge = xps.XPSPeak(pk_lbl, be, area, sfwagner_Ge, hv, pe, mach)\n\n# NOTE Returns pandas.DataFrame with all parameters calculated.\n# The user can also query parameters individually\n# df = analyzed_Ge.get_data()Matrix Factor correctionsIf using multple elements within a matrix (e.g. an alloy), you can utilize thexps.matrix_factorfunction. You require the inelastic mean free path\nof electron scattering (imfp) of both species in bulk and the density, as\nwell as theimfpof the matrix at the measured kinetic energies of both\nelements. For example, if you have two corrected peaks:pk_Mn_corr, andpk_Ge_corr. Theimfpcan be calculated using the TPP-2M equation for\ninelastic mean free path, found in the following reference:S. Tanuma, C. J. Powel, D. R. Penn,Surf. Interf. Anal., Vol 21, 165 (1994)import xps\n# pk_Mn_corr and pk_Ge_corr calculated as in the example above\n\n# a is the kinetic energy used to determine imfp of Ge in Bulk\nimfp_matrix_a = 21.17\nimfp_Ge_a = 29.84\nrho_Ge_a = 5.32\n\n# b is the kinetic energy used to determine imfp of Mn in Bulk\nimfp_matrix_b = 14.17\nimfp_Mn_b = 14.87\nrho_Mn_b = 7.43\n\nmat_fact = xps.matrix_factor(imfp_Ge_a, imfp_Mn_b,\n mfp_matrix_a, mfp_matrix_b,\n rho_Ge_a, rho_Mn_b)\nrelative_pk_Ge_corr = (pk_Ge_corr/pk_Mn_corr)*mat_fact\n\n# NOTE because Mn is used as the normalizing component we can use its\n# corrected peak value directly, all other elements require the matrix\n# factor correction\nprint('Ratios of Mn and Ge in MnGe matrix')\nprint('Mn : {:0.4e}'.format(pk_Mn_corr))\nprint('Ge : {:0.4e}'.format(relative_pk_Ge_corr))sfwagner.{db,py}: Empirically derived set of atomic sensitivity factors for XPSThe data in Appendix 5 is reproduced and provided here for non-profit use with\npermission of the publisher John Wiley & Sons Ltd.\"Practical Surface Analysis by Auger and X-ray Photoelectron Spectroscopy\",\nD. Briggs and M. P. Seah,\nAppendix 5, p511-514,\nPublished by J. Wiley and Sons in 1983, ISBN 0-471-26279Copyright (c) 1983 by John Wiley & Sons Ltd.The original set of data first appeared in the following resource:\nC. D. Wagner, L. E. Davis, M. V. Zeller, J. A. Taylor, R. M. Raymond and L. H. Gale,\nSurf. Interface Anal., 3. 211 (1981)Any use of this data must include the citations above in any work.Electron Inelastic Mean Free Path (IMFP)Electron IMFP can be calculated from using the Tanuma, Powel, Penn modified\n(TPP-2M) equation derived from equations (3), (4b,c,d,e) and (8) in the\nfollowing reference:S. Tanuma, C. J. Powel, D. R. Penn,Surf. Interf. Anal., Vol 21, 165 (1994)For convienence the IMFP TPP-2M equation is located inxps.scatterand\ncan be used as such:from xps import scatter\n\n# Mn example\nkinetic_energy = 1000 # Can be calculated from xps.kinetic_energy\n\nrho = 7.43 # [g/cc]\nNv = 7 # valence electrons\nM = 53.938 # atomic mass\nbandgap_energy = 0 # [eV]\n\n# Return SI units [m]\nimfp_Mn = scatter.imfp_TPP2M(kinetic_energy, rho, M, Nv,\n bandgap_energy, 'SI')The value here can be used in thexps.matrix_factorcalculations\noutlined above."} +{"package": "xp-scenery-organizer", "pacakge-description": "X-Plane 11 Scenery Organizer"} +{"package": "xps-crypto", "pacakge-description": "No description available on PyPI."} +{"package": "xpsd", "pacakge-description": "No description available on PyPI."} +{"package": "xpsfshg", "pacakge-description": "WhatsApp-Analyzer Package"} +{"package": "xpsieve", "pacakge-description": "No description available on PyPI."} +{"package": "xpsych", "pacakge-description": "xpsychPython library of theory-of-minds simulationsCreated byBaihan Lin, Columbia University"} +{"package": "xpt", "pacakge-description": "No description available on PyPI."} +{"package": "xpt2046-circuitpython", "pacakge-description": "skip to docsxpt2046-circuitpythonA CircuitPython (or Adafruit-Blinka) library which reads values from an XPT2046 chip, commonly found on cheap microcontroller TFT displays.installationThis project is available on PyPi:pip3installxpt2046-circuitpythonOr, to install it manually:gitclonehttps://github.com/humeman/xpt2046-circuitpythoncdxpt2046-circuitpython\npip3install.If you're using this on regular Linux rather than CircuitPython, make sure you alsoinstall Adafruit Blinka.usageBe sure to enable SPI insudo raspi-configbefore proceeding.sample wiringTFTBoardGPIOPin #T_CLKSPI0 SCLKGPIO1123T_CSGPIO631T_DINSPI0 MOSIGPIO1019T_DOSPI0 MISOGPIO921T_IRQGPIO2215examplesThe most basic read example is:importxpt2046_circuitpythonimporttimeimportbusioimportdigitaliofromboardimportSCK,MOSI,MISO,D6,D22# Pin configT_CS_PIN=D6T_IRQ_PIN=D22# Set up SPI bus using hardware SPIspi=busio.SPI(clock=SCK,MOSI=MOSI,MISO=MISO)# Create touch controllertouch=xpt2046.Touch(spi,cs=digitalio.DigitalInOut(T_CS_PIN),interrupt=digitalio.DigitalInOut(T_IRQ_PIN))# Check if we have an interrupt signaliftouch.is_pressed():# Get the coordinates for this touchprint(touch.get_coordinates())Some more examples:read.py: A simple program which continuously prints coordinates when the screen is pressedadafruit-ili.py: A simple drawing program for an ILI9341 display controlled by the Adafruit display library"} +{"package": "xpt2csv", "pacakge-description": "No description available on PyPI."} +{"package": "xpt2csv-cli", "pacakge-description": "No description available on PyPI."} +{"package": "xptcleaner", "pacakge-description": "xptcleanerxptcleaner package provides functions for creating json file for vocabulary mappings and for Standardizing SEND xpt files (SAS v5 Transport format) using CDISC controlled terminologies.InstallationUsing pipProbably the easiest way: from your conda, virtualenv or just base installation do:pip install xptcleanerIf you are running on a machine without admin rights, and you want to install against your base installation you can do:pip install xptcleaner --userUsing source archive or using wheel fileYou can choose to install xptcleaner using source archive or using wheel file.Using source archive:\nUsing the below shell command to install the xptcleaner package, assume that the source archive is under 'dist' sub folder. Replace {version} with the correct version number, e.g. 1.0.0.$ py -m pip install ./dist/xptcleaner-{version}.tar.gzUsing wheel:\nUsing the below shell command to install the xptcleaner package, assume that the wheel file is under 'dist' sub folder. Replace {version} with the correct version number, e.g. 1.0.0.$ py -m pip install ./dist/xptcleaner-{version}-py3-none-any.whlThe following required python packages will be installed during the xptcleaner package installation:* pandas\n\n* pyreadstatFunctionsgen_vocab(in_file, out_path)Create json file for vocabulary mappings.\n Keys are synonyms and values are the CDISC Controlled Terminology Submission values.\n Vocabularies are defined by column values from the tab-delimited files.\n \n Parameters\n ----------\n in_file : str\n List of tab-delimited files with synonyms and preferred terms.\n out_path : str\n output json filename.standardize_file(input_xpt_dir, output_xpt_dir, json_file)Standardizes SEND xpt files using CDISC controlled terminologies.\n Here is the list of CDISC codelist supported.\n - Sex\n - Strain/Substrain\n - Species\n - SEND Severity\n - Route of Administration Response\n - Standardized Disposition Term\n - Specimen\n - Non-Neoplastic Finding Type\n - SEND Control Type\n\t\n Parameters\n ----------\n input_xpt_dir : str\n input folder name with xpt files under the folder.\n output_xpt_dir : str\n output folder name for writing the cleaned xpt files.\n json_file : str\n json filename used for mapping.How to usexptcleaner can be used from python script and from R script.Use xptcleaner from python script# xptcleaner and module xptclean importimportxptcleanerfromxptcleanerimportxptclean#input CDISC and Extensible CT files.infile1=\"{path to CT file}/SEND_Terminology_EXTENSIBLE.txt\"infile2=\"{path to CT file}/SEND Terminology_2021_12_17.txt\"#output JSON filejsonfile=\"{path to CT file to be created}/SENDct.json\"#Call the gen_vocab function with the input and output filesxptclean.gen_vocab([infile1,infile2],jsonfile)#Call the standardize_file function to clean the xpt filerawXptFolder=\"{path to xpt files}/96298/\"cleanXptFolder=\"{path to cleaned xpt files}/96298/\"xptclean.standardize_file(rawXptFolder,cleanXptFolder,jsonfile)Use xptcleaner from R scriptxptcleaner is integrated with sendigR package. refer to installation and usage onsendigR."} +{"package": "xpt-convert", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xpto", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xptools", "pacakge-description": "xptoolsAnalysis tools for experimental sciences to display images, detect particles (cells, bubbles, crystals), moving fronts and analyze their shape, size and distibution.Installationxptools is on PyPI so you can install it straight from pip with the commandpip install xptoolsAlternatively, you can clone the repository to your local computer and install from sourcegit clone https://github.com/hlgirard/xptools\ncd xptools\npip install .Scriptsanalyze_front - This scipt takes a directory containing video files. For each file, it asks the user to select a region of interest\nand processes the selected area with a minimum threshold to find the largest area. It then plots the height of this area as\na function of time.analyze_front --plotly --scale 60 --framerate 30 moviedirectory/analyze_bubbles - This script takes a movie (or directory of movies) showing bubbles on a surface (bright on dark). It uses a watershed segmentation algorithm to identify the bubbles and characterize their size. It then plots the bubble density and mean size as a function of time.analyze_bubbles --plotly --scale 60 bubble_movie.avianalyze_crystals - This script takes a directory containing pictures of droplets containing crystals (under cross polarization). It uses a thresholding algorithm to segment the crystals, count them and measure their size.analyze_crystals --plotly --key funct_key.txt imagedirectory/display_image_matrix - Arranges all the images in a directory as a matrix and saves the resulting imagedisplay_image_matrix --lines 10 --compress imagedirectory/UtilitiesSeveral utilities are included in the submodule utils including:select_roi:select_rectangle - Prompts the user to make a rectangular selection on the passed image and returns the coordinates of the selection.videotools:open_video - Opens a video file as a list of np.arrays each containing one frame of the video.videotools:determine_threshold - Determines the threshold to use for a video based on the minimum threshold algorithm.videotools:obtain_cropping_boxes - Prompts the user to select the region of interest for each video file. Returns a dataframe containing the coordinates of the selected area for each file.imagetools:open_all_images - Opens all the images in a folder and returns a list of cv2 images.Example usageimportpandasaspdfromxptools.utilsimportvideotoolsvideo_list=['Film1.avi','Film2.avi']dict_crop=videotools.obtain_cropping_boxes(video_list)forkey,valindict_crop:stack=videotools.open_video(key)(minRow,minCol,maxRow,maxCol)=valstack=[img[minRow:maxRow,minCol:maxCol]forimginstack]process(stack)NotebooksSegmentationBroadSpectrum.ipynb - Tests different image segmentation techniques to determine which is most appropriateSegmentationFocused.ipynb - Implements a specific analysis and plots the resulting size and number distributions for the particlesWatershed_Segmentation.ipynb - Implements Watershed segmentation.CreditsCode for display_image_matrix adapted fromhttps://gist.github.com/pgorczak/95230f53d3f140e4939c#file-imgmatrix-pyLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details."} +{"package": "xpublish", "pacakge-description": "XpublishPublish Xarray Datasets to the webA quick exampleServerside: Publish a Xarray Dataset through a rest APIds.rest.serve(host=\"0.0.0.0\",port=9000)Client-side: Connect to a published datasetThe published datasets can be accessed from various kinds of client applications, e.g., from within Python using Zarr and fsspec.importxarrayasxrimportzarrfromfsspec.implementations.httpimportHTTPFileSystemfs=HTTPFileSystem()http_map=fs.get_mapper(\"http://0.0.0.0:9000/zarr/\")# open as a zarr groupzg=zarr.open_consolidated(http_map,mode=\"r\")# or open as another Xarray Datasetds=xr.open_zarr(http_map,consolidated=True)Or to explore other access methods, openhttp://0.0.0.0:9000/docsin a browser.Why?Xpublish lets you serve/share/publish Xarray Datasets via a web application.The data and/or metadata in the Xarray Datasets can be exposed in various forms throughpluggable REST API endpoints.\nEfficient, on-demand delivery of large datasets may be enabled with Dask on the server-side.Xpublish'splugin ecosystemhas capabilities including:publish on-demand or derived data productsturning xarray objects into streaming services (e.g. OPeNDAP)How?Under the hood, Xpublish is using a web app (FastAPI) that is exposing a\nREST-like API with builtin and/or user-defined endpoints.For example, Xpublish provides by default a minimal Zarr compatible REST-like API with the following endpoints:zarr/.zmetadata: returns Zarr-formatted metadata keys as json strings.zarr/var/0.0.0: returns a variable data chunk as a binary string.Futher endpoints can be added by installing or writing plugins."} +{"package": "xpublish-edr", "pacakge-description": "xpublish-edrXpublishrouters for theOGC EDR API.Documentation and codeURLs for the docs and code.InstallationForcondausers you cancondainstall--channelconda-forgexpublish_edror, if you are apipuserspipinstallxpublish_edrExampleimportxarrayasxrimportxpublishfromxpublish.routersimportbase_router,zarr_routerfromxpublish_edr.cf_edr_routerimportcf_edr_routerds=xr.open_dataset(\"dataset.nc\")rest=xpublish.Rest(datasets,routers=[(base_router,{\"tags\":[\"info\"]}),(cf_edr_router,{\"tags\":[\"edr\"],\"prefix\":\"/edr\"}),(zarr_router,{\"tags\":[\"zarr\"],\"prefix\":\"/zarr\"}),],)Get in touchReport bugs, suggest features or view the source code onGitHub.License and copyrightxpublish-edr is licensed under BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause).Development occurs on GitHub athttps://github.com/gulfofmaine/xpublish-edr/issues."} +{"package": "xpublish-host", "pacakge-description": "xpublish-hostA collection of tools and standards for deployingxpublishinstances.Why?With ~50 netCDF-based datasets to be published throughxpublish, Axiom needed a standard way to configure each of these deployments. We could have created single repository and defined each individualxpublishdeployment, we could have created individual repositories for each dataset, or we could have done something in the middle. We decided to abstract out the parts common to each deployment and put it here intoxpublish-host. This prevents the re-implementation of things like authentication (tbd), logging, metrics, and allows data engineers to focus on the data and not the deployment.GoalsStandardize the configuration of anxpublishdeployment (plugins, ports, cache, dask clusters, etc.) using config files and environmental variables, not python code.Standardize on a core set ofFastAPIobservability middleware (metrics, monitoring, etc.),Provide a plugin to definexpublishdatasets via configuration (DatasetsConfigPlugin).Provide a set of commonloaderfunctions for use as an argument in aDatasetsConfigto standardize common access patterns (xarray.open_mfdatasetis currently supported).Provide a pre-built Docker image to run an opinionated and performantxpublishinstance usinggunicorn.Thoughtsxpublish-hostmakes no assumptions about the datasets you want to publish throughxpublishand only requires the path to an importable python function that returns the object you want to be passed in as an argument toxpublish.Rest. This allowsxpublish-hostto support datasets in addition toxarray.Datasetin the future, such as Parquet files.As a compliment toxpublish-host, Axiom maintain a private repository of server and dataset YAML files that are compatible withxpublish-hostand theDatasetsConfigPlugin. On deploy we mount these files into thexpublish-hostcontainer and they represent the only customizations required to get a workingxpublish-hostinstance going.InstallationMost users will not need to installxpublish_hostdirectly as a library but instead will use the Docker image to deploy anxpublishinstance. If you want to use thexpublish_hosttools and config objects directly in python code, you can of course install it:Forcondausers you cancondainstall--channelconda-forgexpublish_hostor, if you are apipuserpipinstallxpublish_hostor, if you are usingdockerdockerrun--rm-p9000:9000axiom/xpublish-host:latestBatteries IncludedHost ConfigurationA top-level configuration for running anxpublish-hostinstance.The configuration is managed usingPydanticBaseSettingsandGoodConffor loading configuration from files.Thexpublish-hostconfiguration can be set in a few waysEnvironmental variables- prefixed withXPUB_, they map directly to thepydanticsettings classes,Environment files- Load environmental variables from a file. UsesXPUB_ENV_FILESto control the location of this file if it is defined. See thePydanticdocsfor more information,Configuration files (JSON and YAML)-GoodConfbasedconfiguration files. When using thexpublish_host.app.servehelper this file can be set by definingXPUB_CONFIG_FILE.Python arguments (API only)- When usingxpublish-hostas a library you can use the args/kwargs of each configuration object to control yourxpublishinstance.The best way to get familiar with which configuration options are available (until the documentation catches up) is to look at the actually configuration classes inxpublish_host/config.pyand the tests intests/test_config.pyandtests/utils.pyA feature-full configuration is as follows, which includes the defaults for each field.# These are passed into the `xpublish.Rest.serve` method to control how the# server is run. These are ignored if running through `gunicorn` in production mode# or using the Docker image. See the `CLI` section below for more details.publish_host:\"0.0.0.0\"publish_port:9000log_level:debug# Dask cluster configuration.# The `args` and `kwargs` arguments are passed directly into the `module`# Omitting cluster_config or setting to null will not use a cluster.cluster_config:module:dask.distributed.LocalClusterargs:[]kwargs:processes:truen_workers:2threads_per_worker:1memory_limit:1GiBhost:\"0.0.0.0\"scheduler_port:0# random portdashboard_address:0.0.0.0:0# random portworker_dashboard_address:0.0.0.0:0# random port# Should xpublish discover and load plugins?plugins_load_defaults:true# Define any additional plugins. This is where you can override# default plugins. These will replace any auto-discovered plugins.# The keys here (zarr, dconfig) are not important and are not used internallyplugins_config:zarr:module:xpublish.plugins.included.zarr.ZarrPlugindconfig:module:xpublish_host.plugins.DatasetsConfigPluginkwargs:# Define all of the datasets to load into the xpublish instance.datasets_config_file:datasets.yamldatasets_config:# The keys here (dataset_id_1) are not important and are not used internally# but it is good practice to make them equal to the dataset's id fielddataset_id_1:# The ID is used as the \"key\" of the dataset in `xpublish.Rest`# i.e. xpublish.Rest({ [dataset.id]: [loader_function_return] })id:dataset_idtitle:Dataset Titledescription:Dataset Description# Path to an importable python function that returns the dataset you want# to pass into `xpublish.Rest`loader:[python module path]# Arguments passed into the `loader` functionargs:-[loader arg1]-[loader arg2]# Keyword arguments passed into the `loader` function. See the `examples`# directory for more details on how this can be used.kwargs:keyword1:'keyword1'keyword2:false# After N seconds, invalidate the dataset and call the `loader` method againinvalidate_after:10# If true, defers the initial loading of the dataset until the first request# for the dataset comes in. Speeds up server load times but slows down the# first request (per-process) to each datasetskip_initial_load:true# Keyword arguments to pass into `xpublish.Rest` as app_kws# i.e. xpublish.Rest(..., app_kws=app_config)app_config:docs_url:/apiopenapi_url:/api.json# Keyword arguments to pass into `xpublish.Rest` as cache_kws# i.e. xpublish.Rest(..., cache_kws=cache_config)cache_config:available_bytes:1e11Metricsxpublish-hostprovides aprometheuscompatible metrics endpoint. The docker image supports multi-process metric generation throughgunicorn. By default the metrics endpoint is available at/metrics.The default labels formatxpublish-hostmetrics are:[XPUB_METRICS_PREFIX_NAME]_[metric_name]{app_name=\"[XPUB_METRICS_APP_NAME]\",environment=\"[XPUB_METRICS_ENVIRONMENT]\"}The metrics endpoint can be configured using environmental variables:XPUB_METRICS_APP_NAME(default:xpublish)XPUB_METRICS_PREFIX_NAME(default:xpublish_host)XPUB_METRICS_ENDPOINT(default:/metrics)XPUB_METRICS_ENVIRONMENT(default:development)XPUB_METRICS_DISABLE- disabled the metrics endpoint by setting this to any valueHealthA health check endpoint is available at/healthto be used by various health checkers (docker, load balancers, etc.). You can disable the heath check endpoint by settings the environmental variableXPUB_HEALTH_DISABLEto any value. To change the endpoint, setXPUB_HEALTH_ENDPOINTto the new value, i.e.export XPUB_HEALTH_ENDPOINT=\"/amiworking\"DatasetsConfigPluginThis plugin is designed to load datasets intoxpublishfrom a mapping ofDatatsetConfigobjects. It can get the mapping directory from the plugin arguments or from ayamlfile.TheDatasetsConfigPluginplugin can take two parameters:datasets_config: dict[str, DatasetConfig]datasets_config_file: Path- File path to a YAML file defining the abovedatasets_configobject.Define datasets from anxpublish-hostconfiguration file:plugins_config:dconfig:module:xpublish_host.plugins.DatasetsConfigPluginkwargs:datasets_config:simple:id:statictitle:Staticdescription:Static dataset that is never reloadedloader:xpublish_host.examples.datasets.simpleOr from axpublish-hostconfiguration file referencing an external datasets configuration file# datasets.yamldatasets_config:simple:id:statictitle:Staticdescription:Static dataset that is never reloadedloader:xpublish_host.examples.datasets.simpleplugins_config:dconfig:module:xpublish_host.plugins.DatasetsConfigPluginkwargs:datasets_config_file:datasets.yamlYou can also mix and match between in-line configurations and file-based dataset configurations. Always be sure theidfield is unique for each defined dataset or they will overwrite each other, with config file definitions taking precedence.plugins_config:dconfig:module:xpublish_host.plugins.DatasetsConfigPluginkwargs:datasets_config_file:datasets.yamldatasets_config:simple_again:id:simple_againtitle:Simpledescription:Simple Datasetloader:xpublish_host.examples.datasets.simpleDatasetConfigTheDatasetConfigobject is a way to store information about how to load a dataset you want published throughxpublish. It supports dynamically loading datasets on request rather than requiring them to be loaded whenxpublishis started. It allows mixing together static datasets that do not change and dynamic datasets that you may want to reload periodically onto onexpublishinstance.Theloaderparameter should be a path to a python module that will return the dataset you want served throughxpublish. Theargsandkwargsparameters are passed into that function whenxpublishneeds to load or reload your dataset.Here is an example of how to configure anxpublishinstance that will serve astaticdataset that is loaded once on server start and adynamicdataset that is not reloaded on server start. It is loaded for the first time on first request and then reloaded every 10 seconds. It isn't reloaded on a schedule, it is reloaded on-request if the dataset has not been accessed afterinvalidate_afterseconds has elapsed.datasets_config:simple:id:statictitle:Staticdescription:Static dataset that is never reloadedloader:xpublish_host.examples.datasets.simpledynamic:id:dynamictitle:Dynamicdescription:Dynamic dataset re-loaded on request periodicallyloader:xpublish_host.examples.datasets.simpleskip_initial_load:trueinvalidate_after:10You can run the above config file and take a look at what is produced. There are (2) datasets:staticanddynamic. If you watch the logs and keep refreshing access to thedynamicdataset, it will re-load the dataset every10seconds.$xpublish-host-cxpublish_host/examples/dynamic.yaml\n\nINFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)INFO:127.0.0.1:42808-\"GET /datasets HTTP/1.1\"200OK# The static dataset is already loadedINFO:127.0.0.1:41938-\"GET /datasets/static/ HTTP/1.1\"200OK# The dynamic dataset is loaded on first accessINFO:xpublish_host.plugins:Loadingdataset:dynamic\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK# Subsequent access to dynamic before [invalidate_after] seconds uses# the already loaded datasetINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK# Eventually [invalidate_after] seconds elapses and the dynamic# dataset is reloaded when the request is madeINFO:xpublish_host.plugins:Loadingdataset:dynamic\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK\nINFO:127.0.0.1:41938-\"GET /datasets/dynamic/ HTTP/1.1\"200OK# The static dataset is never reloadedINFO:127.0.0.1:41938-\"GET /datasets/static/ HTTP/1.1\"200OK# This works when accessing datasets through other plugins as well (i.e. ZarrPlugin)INFO:xpublish_host.plugins:Loadingdataset:dynamic\nINFO:127.0.0.1:48092-\"GET /datasets/dynamic/zarr/.zmetadata HTTP/1.1\"200OK\nINFO:127.0.0.1:48092-\"GET /datasets/dynamic/zarr/.zmetadata HTTP/1.1\"200OKLoadersxpublish_host.loaders.mfdataset.load_mfdatasetA loader function to utilizexarray.open_mfdatasetto open a path of netCDF files. Common loading patterns have been abstracted into keyword arguments to standardize the function as much as possible.defload_mfdataset(root_path:str|Path,# root folder pathfile_glob:str,# a file glob to loadopen_mfdataset_kwargs:t.Dict={},# any kwargs to pass directly to xarray.open_mfdatasetfile_limit:int|None=None,# limit the number of files to load, from the end after sorting ASCskip_head_files:int|None=0,# skip this number of files from the beginning of the file listskip_tail_files:int|None=0,# skip this number of files from the end of the file listcomputes:list[str]|None=None,# A list of variable names to call .compute() on to they are evaluated (useful for coordinates)chunks:dict[str,int]|None=None,# A dictionary of chunks to use for the datasetaxes:dict[str,str]|None=None,# A dictionary of axes mapping using the keys t, x, y, and zsort_by:dict[str,str]|None=None,# The field to sort the resulting dataset by (usually the time axis)isel:dict[str,slice]|None=None,# a list of isel slices to take after loading the datasetsel:dict[str,slice]|None=None,# a list of sel slices to take after loading the datasetrechunk:bool=False,# if we should re-chunk the data applying all sorting and slicingattrs_file_idx:int=-1,# the index into the file list to extract metadata fromcombine_by_coords:list[str|Path]=None,# a list of files to combine_by_coords with, useful for adding in grid definitions**kwargs)->xr.Dataset:Yeah, that is a lot. An Example may be better.# Select the last 24 indexes of ocean_time and the first Depth index# from the last 5 netCDF files found in a directory,# after sorting by the filename. Drop un-needed variables# and use a Dask cluster to load the files if one is available.# Compute the h and mask variables into memory so they are# not dask arrays, and finally, sort the resulting xarray# dataset by ocean_time and then Depth.datasets_config:sfbofs_latest:id:sfbofs_latesttitle:Last 24 hours of SFBOFS surface datadescription:Last 24 hours of SFBOFS surface dataloader:xpublish_host.loaders.mfdataset.load_mfdatasetkwargs:root_path:data/sfbofs/file_glob:\"**/*.nc\"file_limit:5axes:t:ocean_timez:Depthx:Longitudey:Latitudecomputes:-h-maskchunks:ocean_time:24Depth:1nx:277ny:165sort_by:-ocean_time-Depthisel:Depth:[0,1,null]ocean_time:[-24,null,null]open_mfdataset_kwargs:parallel:truedrop_variables:-forecast_reference_time-forecast_hourRunningThere are two main ways to runxpublish-host, one is suited for Development (xpublishby default usesuvicorn.run) and one suited for Production (xpublish-hostusesgunicorn). See theUvicorndocsfor more information.DevelopmentAPITo configure and deploy anxpublishinstance while pulling settings from a yaml file and environmental variables you can use theservefunction.Load config from a file>>>fromxpublish_host.appimportserve>>>serve('xpublish_host/examples/example.yaml')INFO:goodconf:Loadingconfigfromxpublish_host/examples/example.yaml...INFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)pythonLoad environmental variables from a custom .env file>>>importos>>>os.environ['XPUB_ENV_FILES']='xpublish_host/examples/example.env'>>>fromxpublish_host.appimportserve>>>serve()INFO:goodconf:Noconfigfilespecified.Loadingwithenvironmentvariables....INFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)pythonSet the default location to load a configuration file from>>>importos>>>os.environ['XPUB_CONFIG_FILE']='xpublish_host/examples/example.yaml'>>>fromxpublish_host.appimportserve>>>serve()INFO:goodconf:Loadingconfigfromxpublish_host/examples/example.yaml...INFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)pythonRestConfigYou can also use theRestConfigobjects directly to serve datasets through the API while mixing in configuration file as needed. If you using the API in this way without using a config file or environmental variables it is better to use thexpublishAPI directly instead.fromxpublish_host.configimportRestConfig,PluginConfigfromxpublish_host.pluginsimportDatasetsConfigPluginpc=PluginConfig(module=DatasetsConfigPlugin,kwargs=dict(datasets_config=dict(simple=dict(id='simple',title='title',description='description',loader='xpublish_host.examples.datasets.simple',),kwargs=dict(id='kwargs',title='title',description='description',loader='xpublish_host.examples.datasets.kwargs',args=('temperature',),kwargs=dict(values=[0,1,2,3,4,5,6,7,8])))))rc=RestConfig(load=True,plugins_config={'dconfig':pc})rest=rc.setup()# This returns an `xpublish.Rest` instancerest.serve(host='0.0.0.0',port=9000,log_level='debug',)DatasetConfigIf you are serving a single dataset there is a helper methodserveon theDatasetConfigobject.fromxpublish_host.pluginsimportDatasetConfigdc=DatasetConfig(id='id',title='title',description='description',loader='xpublish_host.examples.datasets.simple',)# Keyword arguments are passed into RestConfig and can include all of the# top level configuration options.dc.serve(host='0.0.0.0',port=9000,log_level='debug',)CLI (dev)When developing locally or in a non-production environment you can use helper CLI methods to run anxpublishserver and optionally pass in the path to a configuration file. Use the providedxpublish-hostcommand (when installed throughsetuptools) orpython xpublish_host/app.py, they are the same thing!Pass in a config file argument$xpublish-host-cxpublish_host/examples/example.yaml\n\nINFO:goodconf:Loadingconfigfromxpublish_host/examples/example.yaml\n...\nINFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)Pull config file from an environmental variable$XPUB_CONFIG_FILE=xpublish_host/examples/example.yamlxpublish-host\n\nINFO:goodconf:Loadingconfigfromxpublish_host/examples/example.yaml\n...\nINFO:Uvicornrunningonhttp://0.0.0.0:9000(PressCTRL+Ctoquit)Either way,xpublishwill be running on port 9000 with (2) datasets:simpleandkwargs. You can access the instance athttp://[host]:9000/datasets/.ProductionTo getxpublishto play nicely with async loops and processes being run bygunicornanddask, there is a custom worker class (xpublish_host.app.XpdWorker) and agunicornconfig file (xpublish_host/gunicorn.conf.py) that must be used. These are loaded automatically if you are using the provided Docker image.If you define acluster_configobject when running usinggunicorn, one cluster is spun up in the parent process and the scheduler_address for that cluster is passed to each worker process. If you really want one cluster per process, you will have to implement it yourself and send a PR ;). Better integration withLocalClusterwould be nice, but the way it is done now allows a \"bring your own\" cluster configuration as well if you are managingdaskclusters outside of the scope of this project.Note:when usinggunicornthe host and port configurations can only be passed in using the-b/--bindarguments or in the configuration file. If set in any environmental variables they will be ignored!CLI (prod)You can rungunicornmanually (locally) to test how things will run inside of the Docker image.XPUB_CONFIG_FILE=xpublish_host/examples/example.yamlgunicornxpublish_host.app:app-cxpublish_host/gunicorn.conf.pyIf you would like the metrics endpoint (/metrics) to function correctly when running throughgunicorn, you need to create a temporary directory for metrics and pass it in as thePROMETHEUS_MULTIPROC_DIRdirectory. This is handled automatically in the provided Docker image.mkdir-p/tmp/xpub_metricsPROMETHEUS_MULTIPROC_DIR=/tmp/xpub_metricsXPUB_CONFIG_FILE=xpublish_host/examples/example.yamlgunicornxpublish_host.app:app-cxpublish_host/gunicorn.conf.pyEither way,xpublishwill be running on port 9000 with (2) datasets:simpleandkwargs. You can access the instance athttp://[host]:9000/datasets/. Metrics are available athttp://[host]:9000/metricsDockerThe Docker image by default loads anxpublish-hostconfiguration file from/xpd/config.yaml, a datasets configuration object from/xpd/datasets.yaml, and an environmental variable file from/xpd/.env. You can change the location of those files by setting the env variablesXPUB_CONFIG_FILE,XPUBDC_CONFIG_FILE, andXPUB_ENV_FILESrespectively.# Using default config pathdockerrun--rm-p9000:9000-v\"$(pwd)/xpublish_host/examples/example.yaml:/xpd/config.yaml\"axiom/xpublish-host:latest# Using ENV variablesdockerrun--rm-p9000:9000-e\"XPUB_CONFIG_FILE=/xpd/xpublish_host/examples/example.yaml\"axiom/xpublish-host:latestEither way,xpublishwill be running on port 9000 with (2) datasets:simpleandkwargs. You can access the instance athttp://[host]:9000/datasets/."} +{"package": "xpublish-intake", "pacakge-description": "xpublish-intakeAnxpublishplugin for serving intake catalogsWhy?As data access services are moved from custom APIs intoxpublishplugins, data users need a way to discover these new plugins as they become available without changing their analysis code. One way to standardize dataset access for those that can be loaded viaintakeis to provide anintakecatalog of the plugins endpoints.IdeasThis plugin currently supports thexpublish.plugins.included.zarr.ZarrPluginplugin (which isintakecompatible). In the future it would be nice if this library did not have to understand each and every plugin that isintakecompatible and left it up to the plugin authors to addintakecatalog support into their access services where applicable. This library could provide a mixin forxpublishplugins to use to register their endpoints in a standard way to then be advertised in anintakecatalog.InstallationForcondausers you cancondainstall--channelconda-forgexpublish_intakeor, if you are apipuserpipinstallxpublish_intakeSetupTheintakeplugin will be automatically discoverd byxpublishif you have the library installed. This will work for most users if you don't need to customize the endpoints.If you specify your plugins manually you will need to addIntakePluginto thepluginsargument ofxpublish.Restor register theIntakePluginexplicitly.fromxpublish_intake.pluginsimportIntakePlugin# Included in the `plugins` maprest=Rest(...plugins={...'intake':IntakePlugin()})# Registered explicitlyrest=Rest(...)rest.register_plugin(IntakePlugin())UsageTheintakeplugin is by default configured withapp_router_prefix='/intake'which creates the/intake.yamlroute for the rootintakecatalog containing all datasets in anxpublish.Restinstance. By default that route is available athttp://.../intake.yaml.dataset_router_prefix=''which creates an/datasets/[name]/catalog.yamlrouter for all datasets in thexpublish.Restinstance. By default those route are available athttp://.../datasets/[name]/catalog.yaml.Get in touchReport bugs, suggest features or view the source code onGitHub.License and copyrightxpublish_intakeis licensed under the MIT License.Development occurs on GitHub athttps://github.com/axiom-data-science/xpublish-intake."} +{"package": "xpublish-intake-provider", "pacakge-description": "Xpublish-Intake-ProviderXpublish-Intake-Provider allows serving datasets with Xpublish specified by Intake catalogs.InstallationForcondausers you cancondainstall--channelconda-forgexpublish_intake_provideror, if you are apipuserspipinstallxpublish_intake_providerExampleCurrently this package includes one plugin which can load an\nIntake catalog and serve it's datasets via/datasets/{dataset_id}.You can register the plugin multiple times in order to serve\nmultiple catalogs as long as each gets its own name.fromxpublish_intake_providerimportIntakeDatasetProviderPluginrest=xpublish.Rest({})rest.register_plugin(IntakeDatasetProviderPlugin(name=\"gfs-datasets\",uri=\"https://raw.githubusercontent.com/axiom-data-science/mc-goods/main/mc_goods/gfs-1-4deg.yaml\"))rest.register_plugin(IntakeDatasetProviderPlugin(name=\"gomofs-datasets\",uri=\"https://raw.githubusercontent.com/axiom-data-science/mc-goods/main/mc_goods/gomofs.yaml\"))Get in touchReport bugs, suggest features or view the source code onGitHub.License and copyrightxpublish_intake_provider is licensed under BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause).Development occurs on GitHub athttps://github.com/ioos/xpublish_intake_provider."} +{"package": "xpublish-opendap", "pacakge-description": "xpublish_opendapOpenDAP endpoint plugin for Xpublish.InstallationForcondausers you cancondainstall--channelconda-forgexpublish-opendapor, if you are apipuserspipinstallxpublish-opendapOnce it's installed, the plugin will register itself with Xpublish and OpenDAP endpoints will be included for each dataset on the server.Get in touchReport bugs, suggest features or view the source code onGitHub.License and copyrightxpublish_opendap is licensed under BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause).Development occurs on GitHub athttps://github.com/xpublish-community/xpublish_opendap."} +{"package": "xpublish-wms", "pacakge-description": "xpublish-wmsXpublishrouters for theOGC WMS API.InstallationForcondausers you cancondainstall--channelconda-forgexpublish_wmsor, if you are apipuserspipinstallxpublish_wmsOnce it's installed, the plugin will register itself with Xpublish and WMS endpoints will be included for each dataset on the server.Dataset RequirementsAt this time, only a subset of xarray datasets will work out of the box with this plugin. To be compatible, a dataset must contain CF compliant coordinate variables forlat,lon,time, andvertical.timeandverticalare optional.Currently the following grid/model types are supported:Regularly spaced lat/lon grids (Tested with GFS, GFS Wave models)Curvilinear grids (Tested with ROMS models CBOFS, DBOFS, TBOFS, WCOFS, GOMOFS, and CIOFS models)FVCOM grids (Tested with LOOFS, LSOFS, LMHOFS, and NGOFS2 models)SELFE grids (Tested with CREOFS model)2d Non Dimensional grids (Tested with RTOFS, HRRR-Conus models)Supporting new grid/model typesIf you have a dataset that is not supported, you can add support by creating a newxpublish_wms.Gridsubclass and registering it with thexpublish_wms.register_grid_implfunction. See thexpublish_wms.gridsmodule for examples.Get in touchReport bugs, suggest features or view the source code onGitHub.License and copyrightxpublish-wms is licensed under BSD 3-Clause \"New\" or \"Revised\" License (BSD-3-Clause).Development occurs on GitHub athttps://github.com/xpublish-community/xpublish-wms.SupportWork on this plugin is sponsored by:IOOS(github) funds work on this plugin via the\"Reaching for the Cloud: Architecting a Cloud-Native Service-Based Ecosystem for DMAC\"project being led byRPS Ocean Science."} +{"package": "xpubsub", "pacakge-description": "xpubsubA basic pubsub module for communications within an app.This project is an excercise to help me develop skills relating to:writing a Python modulepublishing modules on pypiusing:gitpytestpyenvpoetrymypytoxYou would probably be better off usingPyPubSubInterfacefromxpubsubimportPubSubpub=PubSub()HashOrList=Union[Hashable,list[Hashable]]pub.add(topic_list:HashOrList,callback:Callable):pub.remove(topic_list:HashOrList,callback:Callable):pub.send(topic_list:HashOrList,message:Any):Example: example.pyfromxpubsubimportPubSubpub=PubSub()defhello(topic,message):print(topic,message)defgoodbye(topic,msg):print(\"\ud83d\ude2d\",topic,msg)pub.add(\"hi\",hello)pub.add([\"SHTF!\",\"go away\"],goodbye)pub.send(\"hi\",\"\ud83d\udc4b\ud83d\ude0d\")pub.send(\"SHTF!\",\"Head For The Hills!\")pub.send(\"go away\",\"its over\")pub.remove(\"go away\",goodbye)pub.send(\"go away\",\"nothing happens\")# this does nothing!Outputhi \ud83d\udc4b\ud83d\ude0d\n\ud83d\ude2d SHTF! Head For The Hills!\n\ud83d\ude2d go away its over"} +{"package": "xpuls-fastapi-utils", "pacakge-description": "\ud83e\uddf0 FastAPI utils by xpuls-labsThis is a thin wrapper around FastAPI to centralize telemetry, logs, config management and other itemsThis also maintains the reusable utilities and hooks that can be shared across projectsHow to install?pipinstallxpuls-fastapi-utils"} +{"package": "xpuls-mlmonitor", "pacakge-description": "Welcome to xpuls.ai \ud83d\udc4bMLMonitor - Automatic Instrumentation for ML FrameworksWebsite|Docs|Blog|Twitter|CommunityRoadmap \ud83d\ude80FrameworkStatusLangchain\u2705LLamaIndexPlannedPyTorchPlannedSKLearnPlannedTransformersPlannedStable DiffusionNext\ud83d\udca1 If support of any framework/feature is useful for you, please feel free to reach out to us viaDiscordor Github Discussions\ud83d\udd17 InstallationInstall from PyPIpipinstallxpuls-mlmonitor\ud83e\udde9 Usage Examplefromxpuls.mlmonitor.langchain.instrumentimportLangchainTelemetryimportos# Enable this for advance tracking with our xpuls-ml platformos.environ[\"XPULSAI_TRACING_ENABLED\"]=\"true\"# Add default labels that will be added to all captured metricsdefault_labels={\"service\":\"ml-project-service\",\"k8s_cluster\":\"app0\",\"namespace\":\"dev\",\"agent_name\":\"fallback_value\"}# Enable the auto-telemetryLangchainTelemetry(default_labels=default_labels,xpuls_host_url=\"http://app.xpuls.ai\"# Optional param, required when XPULSAI_TRACING is enabled).auto_instrument()## [Optional] Override labels for scope of decorator [Useful if you have multiple scopes where you need to override the default label values]@TelemetryOverrideLabels(agent_name=\"chat_agent_alpha\")defget_response_using_agent_alpha(prompt,query):agent=initialize_agent(llm=chat_model,verbose=True,agent=CONVERSATIONAL_REACT_DESCRIPTION,memory=memory)res=agent.run(f\"{prompt}.\\nQuery:{query}\")\u2139\ufe0f Complete Usage GuidesLangchain Framework+Grafana Template\ud83e\uddfe LicenseThis project is licensed under the Apache License 2.0. See the LICENSE file for more details.\ud83d\udce2 ContributingWe welcome contributions to MLMonitor! If you're interested in contributing.If you encounter any issues or have feature requests, please file an issue on our GitHub repository.\ud83d\udcac Get in touch\ud83d\udc49Join our Discord community!\ud83d\udc26 Follow the latest from xpuls.ai team on Twitter@xpulsai"} +{"package": "xpuls-ml-sdk", "pacakge-description": "Welcome to xpuls.ai \ud83d\udc4bxpuls-ml-sdkWebsite|Docs|Articles|Twitter|CommunityRoadmap \ud83d\ude80FrameworkStatusLangchain\u2705LLamaIndexPlannedPyTorchPlannedSKLearnPlannedTransformersPlannedStable DiffusionNext\ud83d\udca1 If support of any framework/feature is useful for you, please feel free to reach out to us viaDiscordor Github Discussions\ud83d\udd17 InstallationInstall from PyPIpipinstallxpuls-ml-sdk\ud83e\udde9 Usage Examplefromxpuls.mlmonitor.langchain.instrumentimportLangchainTelemetryimportosimportxpulsfromxpuls.prompt_hubimportPromptClient# Enable this for advance tracking with our xpuls-ml platformxpuls.host_url=\"https://api.xpuls.ai\"xpuls.api_key=\"********************\"# Get from https://platform.xpuls.aixpuls.adv_tracing_enabled=\"true\"# Enable this for automated insights and log tracing via xpulsAI platform# Add default labels that will be added to all captured metricsdefault_labels={\"service\":\"ml-project-service\",\"k8s_cluster\":\"app0\",\"namespace\":\"dev\",\"agent_name\":\"fallback_value\"}# Enable the auto-telemetryLangchainTelemetry(default_labels=default_labels,).auto_instrument()prompt_client=PromptClient(prompt_id=\"clrfm4v70jnlb1kph240\",# Get prompt_id from the platformenvironment_name=\"dev\"# Deployed environment name)## [Optional] Override labels for scope of decorator [Useful if you have multiple scopes where you need to override the default label values]@TelemetryOverrideLabels(agent_name=\"chat_agent_alpha\")@MapXpulsProject(project_slug=\"defaultoPIt9USSR\")# Get Project Slug from platformdefget_response_using_agent_alpha(prompt,query):agent=initialize_agent(llm=chat_model,verbose=True,agent=CONVERSATIONAL_REACT_DESCRIPTION,memory=memory)data=prompt_client.get_prompt({\"variable-1\":\"I'm the first variable\"})# Substitute any variables in promptres=agent.run(data)# Pass the entire `XPPrompt` object to run or invoke method\u2139\ufe0f Complete Usage GuidesLangchain Framework+Grafana Template\ud83e\uddfe LicenseThis project is licensed under the Apache License 2.0. See the LICENSE file for more details.\ud83d\udce2 ContributingWe welcome contributions to xpuls-ml-sdk! If you're interested in contributing.If you encounter any issues or have feature requests, please file an issue on our GitHub repository.\ud83d\udcac Get in touch\ud83d\udc49Join our Discord community!\ud83d\udc26 Follow the latest from xpuls.ai team on Twitter@xpulsai\ud83d\udcee Write to us athello@xpuls.ai"} +{"package": "xput", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xputer", "pacakge-description": "No description available on PyPI."} +{"package": "xput-pkg-hacked-toad", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xpx-chain", "pacakge-description": "ProximaX Sirius Blockchain Python SDK is a Python library for interacting with the Sirius Blockchain."} +{"package": "xpxhg", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xpxp1", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xpxp2", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xp-xscreensaver", "pacakge-description": "No description available on PyPI."} +{"package": "xpy", "pacakge-description": "This is an \u201ceXtended\u201d Python console, which really just means a Python console\ndone just the way that I like it. Primarily, this means enhanced readline\nhistory support, and X clipboard utilities.Python readline history is now stored in git, by default under a repository\nnamed ~/.pyhistMultiple instances of the console will have their histories union-merged\nunder the shared git repo. This means no more clobbering of readline\nhistory.X Clipboard helper called Clip, e.g., Clip.run(), Clip.read_to_history(),\nClip.write_from_history(), etc. are available and made visible to the xpy\nconsole.The fancy, colorized, full-stack exception traceback display may help you to\nanalyze code issues.The xpy console can be inserted into code usingimport xpy; xpy.xpy_start_console()This will break into an interactive console local to the current frame. It\nis not a debugger, but it is an ordinary interactive Python console. Any\ncode runs within the scope of the frame where the command is run.Script commands include xpy (autogenerated, slower startup), xpy2, and xpy3\nfor starting an interactive console. It can also be started with python -m\nxpy or python3 -m xpy. The console is exited with Ctrl-D.Tab completion that works within the local console frame."} +{"package": "x-py", "pacakge-description": "\u57fa\u4e8e Tornado \u7684\u793a\u4f8b\u7a0b\u5e8f\u8bbe\u7f6e\u914d\u7f6e\u6587\u4ef6` cp app.example.yaml cp app.yaml `\u5b89\u88c5\u7b2c\u4e09\u65b9\u5e93\u547d\u4ee4` pip install pyyaml sqlalchemymysql-connector`\u542f\u52a8\u7a0b\u5e8f\u547d\u4ee4` python app.py ``\u542f\u52a8\u6210\u529f\u540e\uff0c\u8bbf\u95ee\u5730\u5740http://localhost:8000\u6267\u884c\u6d4b\u8bd5\u547d\u4ee4python tests/test_all.pycoverage run tests/test.py"} +{"package": "xpyb", "pacakge-description": "No description available on PyPI."} +{"package": "xpybutil", "pacakge-description": "See README"} +{"package": "xpycommon", "pacakge-description": "xpycommonIntroductionCurrently, xpycommon is neither an open source software or the GNU defined free software."} +{"package": "xpydf", "pacakge-description": "xpdf-pythonPython wrapper around the pdftotext functionality of xpdf.Usagefromxpydf.pdf_loaderimportPdfLoaderloader=PdfLoader(\"foo.pdf\")pdf_text=loader.extract_strings()pdf_images=loader.extract_images()"} +{"package": "xpyenv", "pacakge-description": "UNKNOWN"} +{"package": "x-py-libs", "pacakge-description": "self python libs"} +{"package": "xpylog", "pacakge-description": "NAMExpylog - an xconsole-like syslog monitor on X11SYNOPSISxpylogDESCRIPTIONThis manual page documentsxpylog, a realtime syslog monitor on X Window\nSystem.xpylogis a xconsole-like simple monotoring application with\nseveral additional features.OPTIONSNoneREQUIREMENTSxpylogobtains the syslog messages viajournalctlcommand in systemd.INSTALLATION$pip3installxpylogAVAILABILITYThe latest version ofxpylogis available at PyPI\n(https://pypi.org/project/xpylog/) .SEE ALSOxpywm(1), xconsole(1), journalctl(1), systemd(1)AUTHORHiroyuki Ohsaki "} +{"package": "xpymon", "pacakge-description": "NAMExpymon - A versatile WiFi/network/battery/CPU/video system monitor on LinuxSYNOPSISxpywmDESCRIPTIONThis manual page documentsxpymon, a minimal but versatile system monitor\non Linux.xpymonis designed to work withxpywm, a simple but\nextensible X11 window manager written in Python\n(https://pypi.org/project/xpywm/). However,xpymoncan be used\nindependently and be combined with other window managers.xpymonconsumes the minimum amount of the desktop; i.e., the height of the\nstatsu monitor window is just eight pixels.OPTIONS-TRun in test mode.CUSTOMIZATIONOn startup,xpymonloads per-user RC script (~/.xpymonrc) if it exists.\nThe RC script is any valid Python script. You can change the behavior ofxpymonusing the RC file.An example~/.xpymonrcfile is as follows.# blink status monitor when the remaining battery capacity is less than 10%globalBATTERY_WARN_THRESHBATTERY_WARN_THRESH=.1REQUIREMENTSThe implementation ofxpymonheavily depends on the Linux kernel (/proc\nand /sys pseudo filesystems) and its standard utilities such as ip (iproute2),\nifconfig (net-tools), and iwconfig (wireless-tools).INSTALLATION$sudoaptinstalliproute2net-toolswireless-tools$pip3installxpymonAVAILABILITYThe latest version ofxpymonis available at PyPI\n(https://pypi.org/project/xpymon/) .SEE ALSOxpywm(1), ip(8), iwconfig(8), ifconfig(8), xrandr(1), zdump(8), proc(5)AUTHORHiroyuki Ohsaki "} +{"package": "xpynfo", "pacakge-description": "This is a simple CLI tool to dump X window info in a tree format.Current version is a proof-of-concept. The API will potentially change drastically.FeaturesUsestheanytreepackageto tidy outputUsesthexcffibpackageforXinteraction viaXCBPython bindingsProvides access toXGetWindowAttributesinfoXGetGeometryinfoXListPropertiesinfowith properties filled out viaxcb_get_propertycallsSystem DependenciesThe core features depend onlibxcb.Thexcffibdocsalso mentionlibxcb-render. I suspect the full list ofxcbcomponents is actually necessary, but I haven\u2019t checked from a fresh install yet.Here\u2019s a good way to discover dependencies in the RPM world. You should be able to replacednfwithyumon older systems.$sudodnfinstall-ydnf-utils--allowerasing#ForafullXCBinstall,usethisasthefirstlineinstead#UNLISTED_DEPS=($(eval\"echo 'xcb-'{'proto','util-*'}{'','-devel'}\"));$UNLISTED_DEPS=($(eval\"echo xcb-util-renderutil{,-devel}\"));\\DEPS=($(\\repoquery--requires--resolvepython2-xcffib\\|awk-F':''\\\n /^[^:]*:[^:]*$/{ \\\n gsub(\"-[0-9]+$\", \"\", $1); \\\n print $1; \\\n }'\\|sort-u\\));\\FULL_DEPS=(\"${UNLISTED_DEPS[@]}\"\"${DEPS[@]}\"\"${DEPS[@]/%/-devel}\")eval sudo dnf install \\\n --skip-broken \\$(printf\"'%s' \"\"${FULL_DEPS[@]}\")Package xcb-util-renderutil-0.3.9-10.fc28.x86_64 is already installed, skipping.\nPackage xcb-util-renderutil-devel-0.3.9-10.fc28.x86_64 is already installed, skipping.\nPackage libxcb-1.13-1.fc28.x86_64 is already installed, skipping.\nPackage libxcb-1.13-1.fc28.i686 is already installed, skipping.\nPackage python2-2.7.15-1.fc28.x86_64 is already installed, skipping.\nPackage python2-cffi-1.11.2-1.fc28.x86_64 is already installed, skipping.\nPackage python2-six-1.11.0-3.fc28.noarch is already installed, skipping.\nPackage libxcb-devel-1.13-1.fc28.x86_64 is already installed, skipping.\nPackage python2-devel-2.7.15-1.fc28.x86_64 is already installed, skipping.\nNo match for argument: python2-cffi-devel\nNo match for argument: python2-six-devel\nDependencies resolved.\nNothing to do.\nComplete!#Or,foranevensimplerfullinstall,$sudodnfinstall'libxcb*''xcb*'I have no idea how to do this in other ecosystems. It should be possible inthe Debian worldorthe Arch worldwith some tweaking.Installation$pipinstall--userxpynfoUsage$exportPATH=~/.local/bin:$PATH$whichxpynfo~/.local/bin/xpynfo$xpynfo--versionxpynfo $xpynfo--help< dumps all the help >$xpynfo\\--recurse\\--use-names\\--styleAsciiStyle\\--max-depth1\\--properties\\$(xprop|awk'/WM_CLIENT_LEADER/{ print strtonum($NF); }')#Note:youhavetoclickawindowtopopulatexprop106954753: Sublime Text\n| Properties:\n| WM_CLASS: ['sublime_text', 'Sublime_text']\n| WM_CLIENT_LEADER: 106954753\n| WM_CLIENT_MACHINE: gxc-fedora-28.wotw\n| WM_COMMAND: sublime_text\n| WM_ICON_NAME: sublime_text\n| WM_LOCALE_NAME: en_US.UTF-8\n| WM_NAME: Sublime Text\n| WM_NORMAL_HINTS: \n| WM_PROTOCOLS: ['WM_DELETE_WINDOW', 'WM_TAKE_FOCUS', '_NET_WM_PING']\n| _NET_WM_ICON_NAME: sublime_text\n| _NET_WM_NAME: Sublime Text\n| _NET_WM_PID: 637\n| _NET_WM_USER_TIME_WINDOW: 106954754\n+-- 106954754(Very Basic) Documentationusage: xpynfo [-h] [-V] [-r] [-d MAX_DEPTH] [-a] [-g] [-p] [-n]\n [-s {AsciiStyle,ContRoundStyle,ContStyle,DoubleStyle}]\n [window_id]\n\nA tool to examine various pieces of X info. Without options the command simply\nprints the window id.\n\npositional arguments:\n window_id Specify the window ID; default is the screen's root\n window\n\noptional arguments:\n -h, --help show this help message and exit\n -V, --version Displays the package version and exits\n\nScope Control:\n Options to control the scope of the calls xpynfo makes\n\n -r, --recurse Also query children of the given ID recursively\n -d MAX_DEPTH, --max-depth MAX_DEPTH\n Limit the depth of recursion\n\nX Calls:\n Options to add X information\n\n -a, --attributes Add XWindowAttributes info to output\n -g, --geometry Add XGetGeometry info to output\n -p, --properties Add XListProperties combined with parsed XGetProperty\n info to output\n\nStyle:\n Options to tweak output look\n\n -n, --use-names Add _NET_WM_NAME or WM_NAME (when available) to output\n -s {AsciiStyle,ContRoundStyle,ContStyle,DoubleStyle}, --style {AsciiStyle,ContRoundStyle,ContStyle,DoubleStyle}\n Set the anytree rendering style"} +{"package": "xpypact", "pacakge-description": "ContentsDescriptionImplemented functionalityInstallationExamplesContributingReferencesNoteThis document is in progress.DescriptionThe module loads FISPACT JSON output files and converts to Polars dataframes\nwith minor data normalization.\nThis allows efficient data extraction and aggregation.\nMultiple JSON files can be combined using simple additional identification for different\nFISPACT runs. So far we use just two-dimensional identification by material\nand case. The case usually identifies certain neutron flux.Implemented functionalityexport to DuckDBexport to parquet filesNoteCurrently available FISPACT v.5 API uses rather old python version (3.6).\nThat prevents direct use of their API in our package (>=3.10).\nCheck if own python integration with FISPACT is reasonable and feasible.\nOr provide own FISPACT python binding.InstallationFrom PyPIpip install xpypactAs dependencypoetry add xpypactFrom sourcepip install htpps://github.com/MC-kit/xpypact.gitExamplesfrom xpypact import FullDataCollector, Inventory\n\ndef get_material_id(p: Path) -> int:\n ...\n\ndef get_case_id(p: Path) -> int:\n ...\n\njsons = [path1, path2, ...]\nmaterial_ids = {p: get_material_id(p) for p in jsons }\ncase_ids = {c: get_case_id(p) for p in jsons }\n\ncollector = FullDataCollector()\n\nif sequential_load:\n for json in jsons:\n inventory = Inventory.from_json(json)\n collector.append(inventory, material_id=material_ids[json], case_id=case_ids[json])\n\nelse: # multithreading is allowed for collector as well\n\n task_list = ... # list of tuples[directory, case_id, tasks_sequence]\n threads = 16 # whatever\n\n def _find_path(arg) -> tuple[int, int, Path]:\n _case, path, inventory = arg\n json_path: Path = (Path(path) / inventory).with_suffix(\".json\")\n if not json_path.exists():\n msg = f\"Cannot find file {json_path}\"\n raise FindPathError(msg)\n try:\n material_id = int(inventory[_LEN_INVENTORY:])\n case_str = json_path.parent.parts[-1]\n case_id = int(case_str[_LEN_CASE:])\n except (ValueError, IndexError) as x:\n msg = f\"Cannot define material_id and case_id from {json_path}\"\n raise FindPathError(msg) from x\n if case_id != _case:\n msg = f\"Contradicting values of case_id in case path and database: {case_id} != {_case}\"\n raise FindPathError(msg)\n return material_id, case_id, json_path\n\n with futures.ThreadPoolExecutor(max_workers=threads) as executor:\n mcp_futures = [\n executor.submit(_find_path, arg)\n for arg in (\n (task_case[0], task_case[1], task)\n for task_case in task_list\n for task in task_case[2].split(\",\")\n if task.startswith(\"inventory-\")\n )\n ]\n\n mips = [x.result() for x in futures.as_completed(mcp_futures)]\n mips.sort(key=lambda x: x[0:2]) # sort by material_id, case_id\n\n def _load_json(arg) -> None:\n collector, material_id, case_id, json_path = arg\n collector.append(from_json(json_path.read_text(encoding=\"utf8\")), material_id, case_id)\n\n with futures.ThreadPoolExecutor(max_workers=threads) as executor:\n executor.map(_load_json, ((collector, *mip) for mip in mips))\n\n\ncollected = collector.get_result()\n\n# save to parquet files\n\ncollected.save_to_parquets(Path.cwd() / \"parquets\")\n\n# or use DuckDB database\n\nimport from xpypact.dao save\nimport duckdb as db\n\ncon = db.connect()\nsave(con, collected)\n\ngamma_from_db = con.sql(\n \"\"\"\n select\n g, rate\n from timestep_gamma\n where material_id = 1 and case_id = 54 and time_step_number = 7\n order by g\n \"\"\",\n).fetchall()ContributingJust follow ordinary practice:Commit messageConventional commitsReferencesNoteadd references to FISPACT, pypact and used tools: poetry etc"} +{"package": "xpystac", "pacakge-description": "xpystacxpystac provides the glue that allowsxarray.open_datasetto accept pystac objects.The goal is that as long as this library is in your env, you should never need to think about it.ExampleSearch collection of COGs:importpystac_clientimportxarrayasxrcatalog=pystac_client.Client.open(\"https://earth-search.aws.element84.com/v1\",)search=catalog.search(intersects=dict(type=\"Point\",coordinates=[-105.78,35.79]),collections=['sentinel-2-l2a'],datetime=\"2022-04-01/2022-05-01\",)xr.open_dataset(search,engine=\"stac\")Here are a few examples from thePlanetary Computer Docsimportplanetary_computerimportpystac_clientimportxarrayasxrcatalog=pystac_client.Client.open(\"https://planetarycomputer.microsoft.com/api/stac/v1\",modifier=planetary_computer.sign_inplace,)Read from a reference file:collection=catalog.get_collection(\"nasa-nex-gddp-cmip6\")asset=collection.assets[\"ACCESS-CM2.historical\"]xr.open_dataset(asset)ref:https://planetarycomputer.microsoft.com/dataset/nasa-nex-gddp-cmip6#Example-NotebookRead from a zarr file:collection=catalog.get_collection(\"daymet-daily-hi\")asset=collection.assets[\"zarr-abfs\"]xr.open_dataset(asset)ref:https://planetarycomputer.microsoft.com/docs/quickstarts/reading-zarr-data/Installpipinstallgit+https://github.com/stac-utils/xpystacHow it worksWhen you callxarray.open_dataset(object, engine=\"stac\")this library maps thatopencall to the correct library.\nDepending on thetypeofobjectthat might be a stacking library (eitherodc-stacorstackstac)\nor back toxarray.open_datasetitself but with the engine and other options pulled from the pystac object.Prior ArtThis work is inspired byhttps://github.com/TomAugspurger/staccontainersand the discussion inhttps://github.com/stac-utils/pystac/issues/846"} +{"package": "xpyth", "pacakge-description": "No description available on PyPI."} +{"package": "xpython", "pacakge-description": "xPythonprovides a python-like syntax and converters to any language.In other words - you write code on xPython and then convert it to\nPython, JavaScript, Java, Swift, PHP and other languages.Quick startReadQuick Starton GitHub."} +{"package": "x-python", "pacakge-description": "x-pythonThis is a CPython bytecode interpreter written Python.You can use this to:Learn about how the internals of CPython works since this models thatExperiment with additional opcodes, or ways to change the run-time environmentUse as a sandboxed environment for trying pieces of executionHave one Python program that runs multiple versions of Python bytecode.Use in a dynamic fuzzer or in coholic execution for analysisThe ability to run simple Python bytecode as far back as 2.4 from\nPython 3.10 or Python 3.10 from a Python 2.7 interpreter (assuming no\nfancy async features of newer runtimes) I find pretty neat.Also, idea of the sandboxed environment in a debugger I find\ninteresting. (Note: currently environments are not sandboxed that\nwell, but I am working towards that, and it is a bit challenging.)Since there is a separate execution, and traceback stack,\ninside a debugger you can try things out in the middle of a debug\nsession without effecting the real execution. On the other hand if a\nsequence of executions works out, it is possible to copy this (under\ncertain circumstances) back into CPython\u2019s execution stack.I have hooked intrepan3kinto this interpreter so you have a pdb/gdb like debugger also with\nthe ability to step bytecode instructions.To experiment with faster ways to support trace callbacks such as\nthose used in a debugger, added is an instruction to\nsupport fast breakpoints and breakpointing on a particular instruction\nthat doesn\u2019t happen to be on a line boundary. I believe this could\ncould and should be ported back to CPython and there would be benefit.\n(Python 3.8 supports the ability to save additional frame information which\nis where the original opcode is stored. It just needs theBRKPTopcode)Although this is far in the future, suppose you to add a race\ndetector? It might be easier to prototype it in Python here. (This\nassumes the interpreter supports threading well, I suspect it doesn\u2019t)Another unexplored avenue implied above is mixing interpretation and\ndirect CPython execution. In fact, there are bugs so this happens\nright now, but it will be turned into a feature. Some functions or\nclasses you may want to not run under a slow interpreter while others\nyou do want to run under the interpreter.Examples:What to know instructions get run when you write some simple code?\nTry this:$ xpython -vc \"x, y = 2, 3; x **= y\"\nINFO:xpython.vm:L. 1 @ 0: LOAD_CONST (2, 3)\nINFO:xpython.vm: @ 2: UNPACK_SEQUENCE 2\nINFO:xpython.vm: @ 4: STORE_NAME (2) x\nINFO:xpython.vm: @ 6: STORE_NAME (3) y\nINFO:xpython.vm:L. 1 @ 8: LOAD_NAME x\nINFO:xpython.vm: @ 10: LOAD_NAME y\nINFO:xpython.vm: @ 12: INPLACE_POWER (2, 3)\nINFO:xpython.vm: @ 14: STORE_NAME (8) x\nINFO:xpython.vm: @ 16: LOAD_CONST None\nINFO:xpython.vm: @ 18: RETURN_VALUE (None)Option-cis the same as Python\u2019s flag (program passed in as string)\nand-vis also analogus Python\u2019s flag. Here, it shows the bytecode\ninstructions run.Note that the disassembly above in the dynamic trace above gives a\nlittle more than what you\u2019d see from a static disassembler from\nPython\u2019sdismodule. In particular, theSTORE_NAMEinstructions show thevaluethat is store, e.g. \u201c2\u201d at instruction\noffset 4 into namex. SimilarlyINPLACE_POWERshows the operands, 2 and 3, which is how the value\n8 is derived as the operand of the next instruction,STORE_NAME.Want more like the execution stack stack and block stack in addition? Add anotherv:$ xpython -vvc \"x, y = 2, 3; x **= y\"\n\nDEBUG:xpython.vm:make_frame: code= at 0x7f8018507db0, file \"\", line 1>, callargs={}, f_globals=(, 140188140947488), f_locals=(, 93856967704000)\nDEBUG:xpython.vm:':1 @-1>\nDEBUG:xpython.vm: frame.stack: []\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm:L. 1 @ 0: LOAD_CONST (2, 3) in :1\nDEBUG:xpython.vm: frame.stack: [(2, 3)]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 2: UNPACK_SEQUENCE 2 in :1\nDEBUG:xpython.vm: frame.stack: [3, 2]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 4: STORE_NAME (2) x in :1\nDEBUG:xpython.vm: frame.stack: [3]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 6: STORE_NAME (3) y in :1\nDEBUG:xpython.vm: frame.stack: []\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm:L. 1 @ 8: LOAD_NAME x in :1\nDEBUG:xpython.vm: frame.stack: [2]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 10: LOAD_NAME y in :1\nDEBUG:xpython.vm: frame.stack: [2, 3]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 12: INPLACE_POWER (2, 3) in :1\nDEBUG:xpython.vm: frame.stack: [8]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 14: STORE_NAME (8) x in :1\nDEBUG:xpython.vm: frame.stack: []\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 16: LOAD_CONST None in :1\nDEBUG:xpython.vm: frame.stack: [None]\nDEBUG:xpython.vm: blocks : []\nINFO:xpython.vm: @ 18: RETURN_VALUE (None) in :1Want to see this colorized in a terminal? Use this viatrepan-xpy-x:Suppose you have Python 2.4 bytecode (or some other bytecode) for\nthis, but you are running Python 3.7?$ xpython -v test/examples/assign-2.4.pyc\nINFO:xpython.vm:L. 1 @ 0: LOAD_CONST (2, 3)\nINFO:xpython.vm: @ 3: UNPACK_SEQUENCE 2\nINFO:xpython.vm: @ 6: STORE_NAME (2) x\nINFO:xpython.vm: @ 9: STORE_NAME (3) y\nINFO:xpython.vm:L. 2 @ 12: LOAD_NAME x\nINFO:xpython.vm: @ 15: LOAD_NAME y\nINFO:xpython.vm: @ 18: INPLACE_POWER (2, 3)\nINFO:xpython.vm: @ 19: STORE_NAME (8) x\nINFO:xpython.vm: @ 22: LOAD_CONST None\nINFO:xpython.vm: @ 25: RETURN_VALUE (None)Not much has changed here, other then the fact that that in after 3.6 instructions are two bytes instead of 1- or 3-byte instructions.The above examples show straight-line code, so you see all of the instructions. But don\u2019t confuse this with a disassembler likepydisasmfromxdis.\nThe below example, with conditional branching example makes this more clear:$ xpython -vc \"x = 6 if __name__ != '__main__' else 10\"\nINFO:xpython.vm:L. 1 @ 0: LOAD_NAME __name__\nINFO:xpython.vm: @ 2: LOAD_CONST __main__\nINFO:xpython.vm: @ 4: COMPARE_OP ('__main__', '__main__') !=\nINFO:xpython.vm: @ 6: POP_JUMP_IF_FALSE 12\n ^^ Note jump below\nINFO:xpython.vm: @ 12: LOAD_CONST 10\nINFO:xpython.vm: @ 14: STORE_NAME (10) x\nINFO:xpython.vm: @ 16: LOAD_CONST None\nINFO:xpython.vm: @ 18: RETURN_VALUE (None)Want even more status and control? Seetrepan-xpy.Status:Currently bytecode from Python versions 3.10 to 3.2, and 2.7 to 2.4 are\nsupported. The most recent versions of Python don\u2019t have all opcodes\nimplemented. This is only one of many interests I have, so support may\nbe shoddy. I use funding to help me direct where my attention goes in\nfixing problems, which are vast in this project.Byterun, from which this was based on, is awesome. But it cheats in\nsubtle ways.Want to write a very small interpreter using CPython?# get code somehow\nexec(code)This cheats in kind of a gross way, but this the kind of cheating goes\non inByterunin a more subtle way. As in the example above which\nrelies on built-in functionexecto do all of the work,Byterunrelies on various similar sorts of built-in functions to support\nopcode interpretation. In fact, if the code you wereinterpretingwas the above,Byterunwould use its built-in function for running\ncode inside theexecfunction call, so all of the bytecode that gets\nrun inside code insidecodewould not seen for interpretation.Also, built-in functions likeexec, and other built-in modules have\nan effect in the interpreter namespace. So the two namespaces then\nget intermingled.One example of this that has been noted is forimport. Seehttps://github.com/nedbat/byterun/issues/26. But there are others\ncases as well. While we haven\u2019t addressed theimportissue\nmentioned in issue 26, we have addressed similar kinds of issues like\nthis.Some built-in functions and theinpsectmodule require built-in\ntypes like cell, traceback, or frame objects, and they can\u2019t use the\ncorresponding interpreter classes. Here is an example of this inByterun: class__init__functions don\u2019t get traced into, because\nthe built-in function__build_class__is relied on. And__build_class__needs a native function, not an\ninterpreter-traceable function. Seehttps://github.com/nedbat/byterun/pull/20.AlsoByterunis loose in accepting bytecode opcodes that is invalid\nfor particular Python but may be valid for another. I suppose this is\nokay since you don\u2019t expect invalid opcodes appearing in valid\nbytecode. It can however accidentally or erronously appear code that\nhas been obtained via some sort of extraction process, when the\nextraction process isn\u2019t accruate.In contrast toByterun,x-pythonis more stringent what opcodes it\naccepts.Byterun needs the kind of overhaul we have here to be able to scale to\nsupport bytecode for more Pythons, and to be able to run bytecode\nacross different versions of Python. Specifically, you can\u2019t rely on\nPython\u2019sdismodule if\nyou expect to run a bytecode other than the bytecode that the\ninterpreter is running, or run newer \u201cwordcode\u201d bytecode on a\n\u201cbyte\u201d-oriented byteocde, or vice versa.In contrast,x-pythonthere is a clear distinction between the\nversion being interpreted and the version of Python that is\nrunning. There is tighter control of opcodes and an opcode\u2019s\nimplementation is kept for each Python version. So we\u2019ll warn early\nwhen something is invalid. You can run bytecode back to Python 2.4\nusing Python 3.10 (largely), which is amazing give that 3.10\u2019s native\nbyte code is 2 bytes per instruction while 2.4\u2019s is 1 or 3 bytes per\ninstruction.The \u201clargely\u201d part is, as mentioned above, because the interpreter has\nalways made use of Python builtins and libraries, and for the most\npart these haven\u2019t changed very much. Often, since many of the\nunderlying builtins are the same, the interpreter can (and does) make\nuse interpreter internals. For example, built-in functions likerange()are supported this way.So interpreting bytecode from a newer Python release than the release\nthe Python interpreter is using, is often doable too. Even though\nPython 2.7 doesn\u2019t support keyword-only arguments or format strings,\nit can still interpret bytecode created from using these constructs.That\u2019s possible here because these specific features are more\nsyntactic sugar rather than extensions to the runtime. For example,\nformat strings basically map down to using theformat()function\nwhich is available on 2.7.But new features like asynchronous I/O and concurrency primitives are not\nin the older versions. So those need to be simulated, and that too is a\npossibility if there is interest or support.You can run many of the tests that Python uses to test itself, and I\ndo! And most of those work. Right now this program works best on Python up to\n3.4 when life in Python was much simpler. It runs over 300 in Python\u2019s\ntest suite for itself without problems. For Python 3.6 the number\ndrops down to about 237; Python 3.9 is worse still.HistoryThis is a fork ofByterun.which is a pure-Python implementation of\na Python bytecode execution virtual machine. Ned Batchelder started\nit (based on work from Paul Swartz) to get a better understanding of\nbytecodes so he could fix branch coverage bugs in coverage.py."} +{"package": "xpython-utils", "pacakge-description": "\u4e00\u4e9b\u5de5\u5177"} +{"package": "xpyth-parser", "pacakge-description": "Parse XPATH 3.1 using PyparsingXPath (XML Path Language) is a query language for selecting nodes from an XML document.\nIn addition, XPath is used to compute values (e.g., strings, numbers, or Boolean values) from the content of an XML document.\nXPath is maintained by the World Wide Web Consortium (W3C).Pyparsingis a parsing module used to construct grammar in Python.\nXPyth-parser uses Pyparsing to parse XPath strings, and offers an additional abstraction layer.StatusThis library is an attempt to create a parser which can be used both to query XML documents,\nas well as calculation tasks.\nThe original plan was to support both options. However, XPath 3.1 is not widely used, so use cases are sparse.\nParsing XPath 3.1 on a grammar level should still be supported, but not all information may be available when using\nthe abstraction layer. Most importantly, there will beXPath functionsmissing.Dealing with dynamic contexts (i.e., parsing XML as Parser.xml will be done using LXML for now).\nIn a way, XPyth-parser is at the present moment a fancy wrapper around LXML, in order to support some XPath 2.0+ functionality.AlternativesFor most use cases, there will be (better) alternatives to this project.LXMLis Pythonic binding\nfor the C libraries libxml2 and libxslt. If only XPath 1.0 is needed, LXML will be a better solution.Requirementsxpyth-parser depends on LXML, PyParsing. For parsing dates we use Isodate.GoalsThis project started out with a specific goal:\nto parseXBRL formulatests.\nThese tests are heavily reliant onXBRL specific XPath 2.0 functions.\nBecause of this, the author of this library is focussing on correctly interpreting these functions.Examplesfrom xpyth_parser.parse import Parser \ncount = Parser(\"count(1,2,3)\").run()\nprint(count) -> 3This will give a wrapper class which contains the resolved syntax tree in count.XPath and the answer in count.resolved_answerParsing onlyIt is also possible to only parse the string, but not try to resolve the static and dynamic contextcount = Parser(\"count(1,2,3), no_resolve=True\")count.xpathwill be the full syntax tree, instead of having functions processed and contexts applied.count.run()will resolve the expression as if no_resolve=False. contexts might need to be passed to the object beforehand."} +{"package": "xpytk", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xpyutils", "pacakge-description": "Extra Python Utilities\ud83d\udee0\ufe0f Ongoing project of extra Python utilities including implementation of lazy property,\ncollections of common regular expressions, ...Lazy PropertyA simple use oflazy_property:fromxpyutilsimportlazy_propertyimportrandomrandom.seed(42)classPerson:def__init__(self,name:str)->None:self._name=name@propertydefname(self)->str:\"\"\"Name of the person.\"\"\"returnself._name@lazy_propertydeflucky_number(self)->int:\"\"\"Lucky number.\"\"\"returnrandom.randint(0,100)@lazy_property.require_presence()defage(self)->int:\"\"\"Age.\"\"\"returnrandom.randint(20,30)person=Person('Isaac')print(person.lucky_number)# 81print(person.lucky_number)# it is still 81try:person.ageexceptExceptionase:print(e)# property 'age' is not present yet"} +{"package": "xpywm", "pacakge-description": "NAMExpywm - A simple but extensible X11 window manager written in Python.SYNOPSISxpywmDESCRIPTIONThis manual page documentsxpywm, a simple but extensible X11 window manager\nwritten in Python.xpywmis a Python version ofpwm(http://www.lsnl.jp/~ohsaki/software/pwm/), an X11 window manager written in\nPerl.Development ofpwmwas motivated by perlwm (http://perlwm.sourceforge.net/),\nwhich is a window manager written entirely in Perl. The idea of implementing\nX11 window manager in a light-weight language is great since it allows you to\nfully customize the behavior of the window manager with a little programming.\nSimilarly to perlwm,pwmis built based on X11::Protocol module developed by\nStephen McCamant.xpywmis ported frompwm.xpywmuses python3-xlib module for\ncommunication with the X11 display server.The notable features ofxpywmare its simplicity, compactness, and\nprogrammable cascaded/tiled window placement algorithms.xpywmis simple in a sense that it is entirely written in Python, and it\nrequires only python3-xlib module from PyPI.xpywmis written with less\nthan 1,000 lines of code. If you are familiar with X11 protocol and basics of\nPython programming, you can easily read and understand the source code ofxpywm.xpywmis compact since it provides minimal window decorations.xpywmhas\nno pop-up menus, graphical icons, and window animations.xpywmis designed\nto consume the minimum amount of screen space for letting users and\napplications to use as wide screen space as possible. For instance,xpywmdraws the window titleinsidethe window, rather than outside the window,\nwhich saves dozen-pixel lines around the window.xpywmsupports two types of window placement algorithms: programmed mode and\ntiled mode.In the programmed mode, you can specify rules for inferring appropriate window\ngeometries. By default, Emacs is placed at the top-left corner of the screen\nwith 50% window width and 100% window height. Firefox, chromium, mupdf, xdvi,\nLibreOffice, tgif and Mathematica are placed next to the Emacs with 50% window\nwidth and 100% window height. The terminal window is placed at the\nbottom-right corner with 50% window width and 70% window height. If there\nexist more than two terminal windows, the size of each terminal window is\nshrunk to 1/4 of the screen, and placed in a non-overlapping way.In the titled mode, all windows are placed in a titled fashion so that any\nwindow will have the same window width and height, and that any window will\nnot overlap with others, as like tile-based window managers. Moreover,xpywmtries to allocate larger area for Emacs; i.e., if there are three\nwindows, say, Emacs and two terminals, Emacs will occupy the half of the\nscreen, and each terminal will have the quarter of the screen.OPTIONSNoneINSTALLATION$pip3installxpywmCUSTOMIZATIONOn startup,xpywmloads per-user RC script (~/.xpywmrc) if it exists.\nThe RC script is any valid Python script. You can change the appearance and\nthe behavior ofxpywmusing the RC file.Since Python is one of interpreters, you can easily customize the behavior ofxpywmby directly modifying its variables, functions, and methods. For\ninstance, if you want to change the appearance of window frames, override\nvariables. If you want to change the keyboard binding, modify the dictionary\nKEYBOARD_HANDLER. The key of the dictionary is the name of an X11 keysym\nstring. The value of the dictionary is self explanatory: modifier is the mask\nof keyboard modifiers and callback is the reference to the callback function.An example~/.xpywmrcfile is as follows.# specify the title fontglobalTITLE_FONTTITLE_FONT='-hiro-fixed-medium-r-normal--8-80-75-75-c-80-iso646.1991-irv'# add key binding: Alt + Ctrl + 6 to access your serverKEYBOARD_HANDLER['6']={'modifier':X.Mod1Mask|X.ControlMask,'command':'ssh -f your_server urxvt &'}# add key binding: Alt + Ctrl + F12 to execute your shell scriptKEYBOARD_HANDLER['F12']={'modifier':X.ShiftMask,'command':'/path/to/your/script.sh'}BINDINGSMod1 + Button1Move the current active window while dragging with pressing Mod1 + Button1.Mod1 + Button3Resize the current active window while dragging with pressing Mod1 + Button3.Ctrl + Mod1 + iFocus the next window. Available windows are circulated in the order of\ntop-left, bottom-left, top-right, and bottom-right.Ctrl + Mod1 + mRaise or lower the current active window.Ctrl + Mod1 + 'Toggle the maximization of the current active window.Ctrl + Mod1 + ;Toggle the vertical maximization of the current active window.Ctrl + Mod1 + ,Layout all available windows in the programmed mode.Ctrl + Mod1 + .Layout all available windows in the tiled mode.Ctrl + Mod1 + zDestroy the current active window.Ctrl + Mod1 + yToggle the current active window between the first and the second virtual screens.Ctrl + Mod1 + [Switch to the previous virtual screen.Ctrl + Mod1 + ]Switch to the next virtual screen.Ctrl + Mod1 + 1Run a command \"(unset STY; urxvt) &\" via os.system() function.Ctrl + Mod1 + 2Run a command \"pidof emacs || emacs &\" via os.system() function.Ctrl + Mod1 + 3Run a command \"pidof firefox || firefox &\" via os.system() function.Mod1 + F1 -- Mod1 + F4Switch to the virtual screen 1--4, respectively.Shift + F7Enable the external video output through HDMI or DP port.Ctrl + Mod1 + DeleteRestart xpywm.Ctrl + Mod1 + =Terminate xpywm.AVAILABILITYThe latest version ofxpywmis available at PyPI\n(https://pypi.org/project/xpywm/) .SEE ALSOtwm(1), perlwm(1), pwm(1), xpymon(1), xpylog(1)AUTHORHiroyuki Ohsaki "} +{"package": "xpz_first", "pacakge-description": "UNKNOWN"} +{"package": "xq", "pacakge-description": "Apply XPath expressions to XML, likejqdoes for JSONPath and JSON.InstallationInstall withpip:pip install xqOr download the repo and install viasetuptools:python setup.py installUsageExtract download URLs from an RSS feed:http get 'http://br-rss.jeffbr13.net/rss/channels/1/' | xq '//item/enclosure/@url'Extract all links from an HTML page footer:http get 'http://br-rss.jeffbr13.net/ | xq '//footer//a/@href'TestRununittestin the root directory to autodetect and run tests:python -m unittestBuildIncrementxq.VERSIONand run the following two commands\nto create asource distribution,\ncreate auniversal wheel,\nandupload to PyPIpython setup.py sdist\npython setup.py bdist_wheel --universal\ntwine upload dist/*See Alsojqhq"} +{"package": "xqa", "pacakge-description": "No description available on PyPI."} +{"package": "xq-common", "pacakge-description": "No description available on PyPI."} +{"package": "xqlpdemo", "pacakge-description": "xqlpdemoThis is my first python package for adding two number"} +{"package": "xqrcode", "pacakge-description": "xqrcodeA simply QR-code decoder, from URL or a file.Installationpip3 install xqrcodeUsageimportxqrcoderesults=xqrcode.decode_from_url(url='image-url')or:importxqrcoderesults=xqrcode.decode_from_file(path_to_file='/path/to/file')"} +{"package": "xq-rpc", "pacakge-description": "No description available on PyPI."} +{"package": "xqt", "pacakge-description": "Wrapper system to handle differences between Python Qt ports."} +{"package": "xquant", "pacakge-description": "Event-driven backtest frame for Chinese equity/futures market."} +{"package": "xquantipy", "pacakge-description": "No description available on PyPI."} +{"package": "xquant-python", "pacakge-description": "No description available on PyPI."} +{"package": "xquery", "pacakge-description": "XQueryA package to easily run queries at SQL Server and BigQuery.Allows sending queries and receiving data in form of pandas DataFrame from SQL Server and BigQuery.How to useSQL SERVERfromxqueryimportXQueryserver_name='ENTER_SERV_NAME'database_name='ENTER_DB_NAME'sql_xq=XQuery()sql_xq.set_connection_sql_server(server_name=server_name,database_name=database_name)df=sql_xq.pull_query('SELECT 1 AS d')print(df)sql_xq.session.close_connection()BIGQUERYfromxqueryimportXQueryfromsrc.XQuery.configimportBQ_CLIENT_SECRET_FILE# edit path to your filebq_xq=XQuery()bq_xq.set_connection_big_query(BQ_CLIENT_SECRET_FILE)df=bq_xq.pull_query('SELECT 1 AS d')print(df)bq_xq.session.close_connection()"} +{"package": "xqute", "pacakge-description": "xquteA job management system for pythonFeaturesWritten in asyncPlugin systemScheduler adaptorJob retrying/pipeline halting when failedInstallationpip install xquteA toy exampleimportasynciofromxquteimportXquteasyncdefmain():# 3 jobs allowed to run at the same timexqute=Xqute(scheduler_forks=3)for_inrange(10):awaitxqute.put('sleep 1')awaitxqute.run_until_complete()if__name__=='__main__':asyncio.run(main())APIhttps://pwwang.github.io/xqute/UsageXqute objectAn xqute is initialized by:xqute=Xqute(...)Available arguments are:scheduler: The scheduler class or nameplugins: The plugins to enable/disable for this sessionjob_metadir: The job meta directory (Default:./.xqute/)job_error_strategy: The strategy when there is error happenedjob_num_retries: Max number of retries when job_error_strategy is retryjob_submission_batch: The number of consumers to submit jobsscheduler_forks: Max number of job forks**scheduler_opts: Additional keyword arguments for schedulerNote that the producer must be initialized in an event loop.To push a job into the queue:awaitxqute.put(['echo',1])Using SGE schedulerxqute=Xqute('sge',scheduler_forks=100,qsub='path to qsub',qdel='path to qdel',qstat='path to qstat',sge_q='1-day',# or qsub_q='1-day'...)Keyword-arguments with names starting withsge_will be interpreted asqsuboptions.listortupleoption values will be expanded. For example:sge_l=['h_vmem=2G', 'gpu=1']will be expanded in wrapped script like this:# ...#$ -l h_vmem=2G#$ -l gpu=1# ...Using Slurm schedulerxqute=Xqute('slurm',scheduler_forks=100,sbatch='path to sbatch',scancel='path to scancel',squeue='path to squeue',sbatch_partition='1-day',# or slurm_partition='1-day'sbatch_time='01:00:00',...)Using ssh schedulerxqute=Xqute('ssh',scheduler_forks=100,ssh='path to ssh',ssh_servers={\"server1\":{\"user\":...,\"port\":22,\"keyfile\":...,# How long to keep the ssh connection alive\"ctrl_persist\":600,# Where to store the control socket\"ctrl_dir\":\"/tmp\",},...}...)SSH servers must share the same filesystem and using keyfile authentication.PluginsTo write a plugin forxqute, you will need to implement the following hooks:on_init(scheduler): Right after scheduler object is initializedon_shutdown(scheduler, sig): When scheduler is shutting downon_job_init(scheduler, job): When the job is initializedon_job_queued(scheduler, job): When the job is queuedon_job_submitted(scheduler, job): When the job is submittedon_job_started(scheduler, job): When the job is started (when status changed to running)on_job_polling(scheduler, job): When job status is being polledon_job_killing(scheduler, job): When the job is being killedon_job_killed(scheduler, job): When the job is killedon_job_failed(scheduler, job): When the job is failedon_job_succeeded(scheduler, job): When the job is succeededNote that all hooks are corotines excepton_initandon_shutdown, that means you should also implement them as corotines (sync implementations are allowed but will be warned).To implement a hook, you have to fetch the plugin manager:fromsimplugimportSimplugpm=Simplug('xqute')# orfromxquteimportsimplugaspmand then use the decoratorpm.impl:@pm.impldefon_init(scheduler):...Implementing a schedulerCurrently there are only 2 builtin schedulers:localandsge.One can implement a scheduler by subclassing theSchedulerabstract class. There are three abstract methods that have to be implemented in the subclass:fromxquteimportScheduerclassMyScheduler(Scheduler):name='my'job_class:MyJobasyncdefsubmit_job(self,job):\"\"\"How to submit a job, return a unique id in the scheduler system(the pid for local scheduler for example)\"\"\"asyncdefkill_job(self,job):\"\"\"How to kill a job\"\"\"asyncdefjob_is_running(self,job):\"\"\"Check if a job is running\"\"\"As you may see, we may also need to implement a job class beforeMyScheduler. The only abstract method to be implemented iswrap_cmd:fromxquteimportJobclassMyJob(Job):asyncdefwrap_cmd(self,scheduler):...You have to use the trap command in the wrapped script to update job status, return code and clear the job id file."} +{"package": "xq-webapi", "pacakge-description": "No description available on PyPI."} +{"package": "xqys", "pacakge-description": "No description available on PyPI."} +{"package": "xr", "pacakge-description": "XR: Regular expressions for people not just machinesxr: Regular expressions for people.Full reference manual on website.Release v1.0Xr is an graceful, easy, thoughtful, extensible and testable regular expression library for Python built to be read and written by actual people.Xr makes it easy to build and reuse libraries of well test regular expression subcomponents. Try xr just once and you'll never again copy-and-paste a regular expression.Awesome featuresXr supports modern programming practicesOptimizationComposabilityUnittesting supportXr is tested against Python 2.7 & 3.4-3.8 and PyPyGetting startedXr is distributed on pypi so installation is as easy as running pip:pip install xrHello WorldAll good introductions to a programming language start with \"Hello World.\" Xr is no different. In this tutorial you will learn how to recognize the string \"Hello World\" in a regular expression built with the xr library.>>> from xr import Text\n>>> hello_world = Text('Hello World')\n>>> hello_world.match_exact('Hello World')\n\n>>> hello_world.match_exact('Goodbye World')\n(None)Notice we return a re.Pattern object when we match, and None if we don't. This matches the behaivor of Python's built in re library. Xr composes regular expression source strings for you and feeds these to the re library where all of the heavy lifting of the actual regular expression matching takes place.Our Hello World program is pretty good, but it doesn't cover all of the important Hello World use cases: Some programmers become a enthuisastic about learning how to use a new library and show this ethusiasticaly with an exclamation point. We of course want to accomodate enthusiasm so we should allow for an optional exclamation point at the end of the regular expression>>> hello.world.match_exact('Hello World!')\n(None)\n>>> hello_world = Text('Hello World') + Text('!').optional()\n>>> hello_world.match_exact('Hello World!')\nSo far so good, but what if our programmer is really really enthusiastic? What if we encounter two, three or more exclamation marks? Enthusiasm is good and we want to welcome it all!!!>>> hello.world.match_exact('Hello World!!!!!!!!!!')\n(None)\n>>> hello_world = Text('Hello World') + Text('!').many()\n>>> hello_world.match_exact('Hello World!!!!!!!!!!')\nXr supports operator overloading, letting us make our example a little bit simpiler. Because the underlying regular expression object implements both__add__and__radd__so were able to simplify expressions likeText('a') + Text('b')If one side of a + expression is axr.RE object, our library is smart enough to do what makes sense if the other side is just a string. In this case we can reduce the code volume a little bit by writing:>>> hello_world = \"Hello World\" + Text('!').many()So far we've accommodated enthusiastic programmers, but only English speaking enthusiastic programmers. The majority of the world's population does not speak English natively. Far more people are thinking \"N\u01d0 h\u01ceo sh\u00ecji\u00e8\" than they do \"Hello World\" when become excited about learning how to use a new library.Before we can accomodate a new lanugae, we should refactor our code a little bit. One of the powerful features of the xr library is that you build your regular expressions in plain python. This makes available all of the features and convienences of writing in a programming language, like variable names for subcomponents.>>> verbiage = \"Hello World\"\n>>> punctuation = \"!\".many()\n>>> hello_world = verbiage + punctuationNow that this code is refactored we can modify our program to recognize Chinesse. When reading this code keep in mind that for operators to work between xr expressions at least one side of the operator must be a xr.RE subclass. We have to write something likeText('a') | 'b' | 'c' | 'd'or'a' | 'b' | Text('c') | 'd'. We cannot write this:'a' | 'b' | 'c' | 'd'.>>> verbiage = Text(\"Hello World\") | \"\u4f60\u597d\u4e16\u754c\"While we are at this, lets add a few more languages. Most of the world's potential enthusiastic programmers don't speak English or Mandarin when they feel very very enthusiastic.>>> verbiage = Text(\"Hello World\") | \"\u4f60\u597d\u4e16\u754c\" | \"Hola Mundo\" | \"\u041f\u0440\u0438\u0432\u0435\u0442 \u043c\u0438\u0440\";When creating regular expresions it can be easy to forget that youre actually describing your regular expressions ina n abstract syntax tree in the python language. Remember that xr expressions are composiable - you can build your tree programatically.>>> from functools import reduce # For python 3 users \n>>> verbiage = [\"Hello World\",\n... \"\u4f60\u597d\u4e16\u754c\",\n... \"Hola Mundo\",\n... \"\u041f\u0440\u0438\u0432\u0435\u0442 \u043c\u0438\u0440\",\n... \"\u0645\u0631\u062d\u0628\u0627 \u0628\u0627\u0644\u0639\u0627\u0644\u0645\"]\n>>> verbiage = reduce(lambda x,y: x|y, map(Text, verbiage))\n>>> punctuation = \"!\".many()\n>>> hello_world = verbiage + punctuation\n>>> hello_world.match('\u4f60\u597d\u4e16\u754c!!!')\n\n>>> hello_world.match('Hola Mundo')\n< re.Match object;span=(0, 10), match='Hola Mundo'>\n>>> hello_world.match('Hello World')\nOur Hello World is now far more inclusive, but what about multilingual programmers? Lets modify our Hello World program to accept multiple utterances of Hello World in any language.In addition to concatenation, regular expressions support or operators - Text(\"a\") | Text(\"b\") matches both the strings \"a\" and \"b\".>>> hello_worlds = hello_world + (Text(\" \").many(1) + hello_world).many()"} +{"package": "xradar", "pacakge-description": "xradarXradar includes all the tools to get your weather radar into the xarray data model.Free software: MIT licenseDocumentation:https://docs.openradarscience.org/projects/xradarAboutAt a developer meeting held in the course of the ERAD2022 conference in Locarno, Switzerland, future plans and cross-package collaboration of theopenradarsciencecommunity were intensively discussed.The consensus was that a close collaboration that benefits the entire community can only be maximized through joint projects. So the idea of a common software project whose only task is to read and write radar data was born. The data import should include as many available data formats as possible, but the data export should be limited to the recognized standards, such asODIM_H5andCfRadial.As memory representation an xarray based data model was chosen, which is internally adapted to the forthcoming standard CfRadial2.1/FM301. FM301 is enforced by theJoint Expert Team on Operational Weather Radar (JET-OWR). Information on FM301 is available at WMO asWMO CF Extensions.Any software package that uses xarray in any way will then be able to directly use the described data model and thus quickly and easily import and export radar data. Another advantage is the easy connection to already existingopen source radar processing software.StatusXradar is considered stable for the implemented readers and writers which have been ported from wradlib. It will remain in beta status until the standard is finalized and the API as well as data model will move into stable/production status.FeaturesImport/Export CfRadial1 dataImport/Export CfRadial2 dataImport/Export ODIM_H5 dataImport GAMIC HDF5Import Rainbow5Import Iris/SigmetImport Furuno SCN/SCNXGeoreferencing (AEQD)Angle ReindexingHistory0.4.3 (2024-02-24)MNT: address black style changes, update pre-commit-config.yaml ({pull}152) by@kmuehlbauer.FIX: use len(unique) to estimate unique entry for odim range ({pull}151) by@martinpaule.0.4.2 (2023-11-02)FIX: Fix handling of sweep_mode attributes ({pull}143) by@mgrover1FIX: explicitely check for \"False\" in get_crs() {pull}142) by@kmuehlbauer.0.4.1 (2023-10-26)FIX: Add history to cfradial1 output, and fix minor error in CfRadial1_Export.ipynb notebook({pull}132) by@syedhamidaliFIX: fix readthedocs build for python 3.12 ({pull}140) by@kmuehlbauer.FIX: align coordinates in backends, pin python >3.9,<=3.12 in environment.yml ({pull}139) by@kmuehlbauerFIX: prevent integer overflow when calculating azimuth in FURUNO scn files ({issue}137) by@giacant, ({pull}138) by@kmuehlbauer0.4.0 (2023-09-27)ENH: Add cfradial1 exporter ({issue}124) by@syedhamidali, ({pull}126) by@syedhamidaliFIX: use datastore._group instead of variable[\"sweep_number\"] ({issue}121) by@aladinor, ({pull}123) by@kmuehlbauerMIN: use \"crs_wkt\" instead of deprecated \"spatial_ref\" when adding CRS ({pull}127) by@kmuehlbauerFIX: always read nodata and undetect attributes from ODIM file ({pull}125) by@egoudenMIN: usecmweathercolormaps in xradar ({pull}128) by@kmuehlbauer.0.3.0 (2023-07-11)ENH: Add new examples using radar data on AWS s3 bucket ({pull}102) by@aladinorFIX: Correct DB_DBTE8/DB_DBZE8 and DB_DBTE16/DB_DBZE16 decoding for iris-backend ({pull}110) by@kmuehlbauerFIX: Cast boolean string to int in rainbow dictionary ({pull}113) by@egoudenMNT: switch to mamba-org/setup-micromamba, split CI tests ({issue}115), ({pull}116) by@kmuehlbauerFIX: time interpolation ({pull}117) by@kmuehlbauerFIX: robustangle_resretrieval inextract_angle_parameters({issue}112), ({pull}118) by@kmuehlbauerFIX: robust radar identifier into_odim()({pull}120) by@kmuehlbauer0.2.0 (2023-03-24)ENH: switch to add optional how attributes in ODIM format writer ({pull}97) by@egoudenFIX: add keyword argument for mandatory source attribute in ODIM format writer ({pull}96) by@egoudenFIX: check for dim0 if not given, only swap_dims if needed ({issue}92), ({pull}94) by@kmuehlbauerFIX+ENH: need array copy before overwriting and make compression available in to_odim ({pull}95) by@kmuehlbauer0.1.0 (2023-02-23)Add an example on reading multiple sweeps into a single object ({pull}69) by@mgrover1ENH: add spatial_ref with pyproj when georeferencing, add/adapt methods/tests ({issue}38), ({pull}87) by@kmuehlbauerDocs/docstring updates, PULL_REQUEST_TEMPLATE.md ({pull}89) by@kmuehlbauerFinalize release 0.1.0, add testpypi upload on push to main ({pull}91) by@kmuehlbauer0.0.13 (2023-02-09)FIX: only skip setting cf-attributes if both gain and offset are unused ({pull}85) by@kmuehlbauer0.0.12 (2023-02-09)ENH: add IRISDB_VELCdecoding and tests ({issue}78), ({pull}83) by@kmuehlbauerFIX: furuno backend inconsistencies ({issue}77), ({pull}82) by@kmuehlbauerFIX: ODIM_H5 backend inconsistencies ({issue}80), ({pull}81) by@kmuehlbauer0.0.11 (2023-02-06)fix_Undetect/_FillValuein odim writer ({pull}71) by@kmuehlbauerport more backend tests from wradlib ({pull}73) by@kmuehlbauer0.0.10 (2023-02-01)add WRN110 scn format to Furuno reader ({pull}65) by@kmuehlbauerAdapt to new build process, pyproject.toml only, userufffor linting ({pull}67) by@kmuehlbauer0.0.9 (2022-12-11)add ODIM_H5 exporter ({pull}39) by@kmuehlbauerfetch radar data from open-radar-data ({pull}44) by@kmuehlbaueralign readers with CfRadial2, add CfRadial2 exporter ({pull}45), ({pull}49), ({pull}53), ({pull}56), ({pull}57) and ({pull}58) by@kmuehlbaueradd georeference accessor, update examples ({pull}60), ({pull}61) by@mgrover1refactored and partly reimplemented angle reindexing ({issue}55), ({pull}62) by@kmuehlbauer0.0.8 (2022-09-28)add GAMIC HDF5 importer ({pull}29) by@kmuehlbaueradd Furuno SCN/SCNX importer ({pull}30) by@kmuehlbaueradd Rainbow5 importer ({pull}32) by@kmuehlbaueradd Iris/Sigmet importer ({pull}33) by@kmuehlbaueradd georeferencing (AEQD) ({pull}28) by@mgrover10.0.7 (2022-09-21)Add zenodo badges to README.md ({pull}22) by@mgrover1Fix version on RTD ({pull}23) by@kmuehlbauerAdd minimal documentation for Datamodel ({pull}24) by@kmuehlbauer0.0.6 (2022-09-19)Improve installation and contribution guide, update README.md with more badges, add version and date of release to docs, update install process ({pull}19) by@kmuehlbauerAdd minimal documentation for CfRadial1 and ODIM_H5 importers ({pull}20) by@kmuehlbauerAdd accessors.py submodule, add accessors showcase ({pull}21) by@kmuehlbauer0.0.5 (2022-09-14)Data Model, CfRadial1 Backend ({pull}13) by@kmuehlbauerODIM_H5 Backend ({pull}14) by@kmuehlbauer0.0.4 (2022-09-01)Setting up CI workflow and build,@mgrover1and@kmuehlbauer0.0.1 (2022-09-01)First release on PyPI."} +{"package": "xradarsat2", "pacakge-description": "xsarradarSat2 Level 1 python reader for efficient xarray/dask based processorInstallconda install -c conda-forge xradarsat2>>>importxradarsat2>>>folder_path=\"/level1/root/directory\">>>xradarsat2.rs2_reader(folder_path)DataTree('None', parent=None)\u251c\u2500\u2500 DataTree('orbitAndAttitude')\u2502 Dimensions: (timeStamp: 7)\u2502 Coordinates:\u2502 * timeStamp (timeStamp) datetime64[ns] 2010-10-15T21:01:32.370461 ... 2010...\u2502 Data variables:\u2502 yaw (timeStamp) float64 3.756 3.773 3.785 3.792 3.807 3.82 3.83\u2502 roll (timeStamp) float64 -29.8 -29.8 -29.8 -29.8 -29.8 -29.8 -29.8\u2502 pitch (timeStamp) float64 0.002605 0.002862 ... -0.001594 -0.001443\u2502 xPosition (timeStamp) float64 -5.072e+06 -5.076e+06 ... -5.087e+06\u2502 yPosition (timeStamp) float64 4.643e+06 4.676e+06 ... 4.799e+06 4.828e+06\u2502 zPosition (timeStamp) float64 2.033e+06 1.944e+06 ... 1.584e+06 1.494e+06\u2502 xVelocity (timeStamp) float64 -425.7 -352.1 -278.6 ... -131.8 -58.51 14.65\u2502 yVelocity (timeStamp) float64 2.642e+03 2.58e+03 ... 2.324e+03 2.259e+03\u2502 zVelocity (timeStamp) float64 -7.063e+03 -7.09e+03 ... -7.207e+03\u2502 Attributes:\u2502 attitudeDataSource: Downlink\u2502 attitudeOffsetsApplied: true\u2502 Description: Attitude Information Data Store. Orbit Informati...\u251c\u2500\u2500 DataTree('geolocationGrid')\u2502 Dimensions: (line: 11, pixel: 11)\u2502 Coordinates:\u2502 * line (line) int64 0 1007 2015 3023 4031 5039 6046 7054 8062 9070 10078\u2502 * pixel (pixel) int64 0 1043 2086 3129 4172 ... 6258 7301 8344 9387 10431\u2502 Data variables:\u2502 latitude (line, pixel) float64 17.97 17.89 17.8 ... 12.77 12.67 12.57\u2502 longitude (line, pixel) float64 130.4 130.9 131.4 ... 133.3 133.8 134.3\u2502 height (line, pixel) float64 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\u2502 Attributes: (12/13)\u2502 productFormat: GeoTIFF\u2502 outputMediaInterleaving: BSQ\u2502 rasterAttributes_dataType: Magnitude Detected\u2502 rasterAttributes_bitsPerSample_dataStream: Magnitude\u2502 rasterAttributes_bitsPerSample_value: 16\u2502 rasterAttributes_numberOfSamplesPerLine: 10432\u2502 ... ...\u2502 rasterAttributes_sampledPixelSpacing_units: m\u2502 rasterAttributes_sampledPixelSpacing_value: 50.0\u2502 rasterAttributes_sampledLineSpacing_units: m\u2502 rasterAttributes_sampledLineSpacing_value: 50.0\u2502 rasterAttributes_lineTimeOrdering: Increasing\u2502 rasterAttributes_pixelTimeOrdering: Decreasing\u251c\u2500\u2500 DataTree('imageGenerationParameters')\u2502 \u251c\u2500\u2500 DataTree('doppler')\u2502 \u2502 \u251c\u2500\u2500 DataTree('dopplerCentroid')\u2502 \u2502 \u2502 Dimensions: (timeOfDopplerCentroidEstimate: 5,\u2502 \u2502 \u2502 n-Coefficients: 5)\u2502 \u2502 \u2502 Coordinates:\u2502 \u2502 \u2502 * timeOfDopplerCentroidEstimate (timeOfDopplerCentroidEstimate) datetime64[ns] ...\u2502 \u2502 \u2502 * n-Coefficients (n-Coefficients) int64 0 1 2 3 4\u2502 \u2502 \u2502 Data variables:\u2502 \u2502 \u2502 dopplerAmbiguity (timeOfDopplerCentroidEstimate) int64 0 ...\u2502 \u2502 \u2502 dopplerAmbiguityConfidence (timeOfDopplerCentroidEstimate) float64 ...\u2502 \u2502 \u2502 dopplerCentroidReferenceTime (timeOfDopplerCentroidEstimate) float64 ...\u2502 \u2502 \u2502 dopplerCentroidPolynomialPeriod (timeOfDopplerCentroidEstimate) float64 ...\u2502 \u2502 \u2502 dopplerCentroidCoefficients (timeOfDopplerCentroidEstimate, n-Coefficients) float64 ...\u2502 \u2502 \u2502 dopplerCentroidConfidence (timeOfDopplerCentroidEstimate) float64 ...\u2502 \u2502 \u2502 Attributes:\u2502 \u2502 \u2502 Description: Doppler Centroid Data Store\u2502 \u2502 \u2514\u2500\u2500 DataTree('dopplerRateValues')\u2502 \u2502 Dimensions: (dopplerRateReferenceTime: 1,\u2502 \u2502 n-RateValuesCoefficients: 3)\u2502 \u2502 Coordinates:\u2502 \u2502 * dopplerRateReferenceTime (dopplerRateReferenceTime) float64 0.005568\u2502 \u2502 * n-RateValuesCoefficients (n-RateValuesCoefficients) int64 0 1 2\u2502 \u2502 Data variables:\u2502 \u2502 dopplerRateValues (dopplerRateReferenceTime, n-RateValuesCoefficients) float64 ...\u2502 \u2502 Attributes:\u2502 \u2502 Description: Doppler Rate Values Data Store.\u2502 \u2514\u2500\u2500 DataTree('chirp')\u2502 Dimensions: (pole: 1, n-amplitudeCoefficients: 4,\u2502 n-phaseCoefficients: 4)\u2502 Coordinates:\u2502 * pole (pole) = 0.11.2) usingrally env create --name example --from-sysenvcommand. An expected\nsystem variables are the same as native docker client supports.Check that Rally can access the dockerFirst of all try to executerally env checkcommand. It checks all\nplatforms of the environment to be available. If it does not show any errors\nfor communicating with docker, go and execute any task against docker.\nIf is fails, try to execute the command again with--detailedflag.Also, you can userally env infocommand for the same purpose. Unlikerally env checkit will not only check the platforms, but print some\ninformation about them. In case of docker platform, it will print the similar\ntodocker --versiondata.Execute a workload against dockerHere is a simple workload:---version:2title:Simple task with only one workloadsubtasks:-title:a subtask with one workloaddescription:This workload should run a container from \"ubuntu\"image and execute simple command.scenario:Docker.run_container:image_name:\"ubuntu\"command:\"echo'Helloworld!'\"runner:constant:times:10concurrency:2sla:failure_rate:max:0This task will downloadubuntuimage first, if it does not present in the\nsystem. Then, it will run 10 containers from the image with 2 concurrency and\nexecute a simple command. The output of the command will be saved as\nTextArea and will be available via json and html reports.See plugin references for the full list of available plugins for docker\nplatform to combine workloads.Known issuesThis package works fine, but you need to install the proper version of Docker\nclient which suits your Docker API version."} +{"package": "xrally-kubernetes", "pacakge-description": "xrally-kubernetesxRally plugins forKubernetesplatform.Getting startedFirst of all, you need to create rally env for Kubernetes. There are two main\nways to communicate to Kubernetes cluster - specifying auth-token or\ncertifications. Choose what is suitable for your case and use one of the\nfollowing samples.To create env using certifications, use specsamples/platforms/cert-spec.yaml:rally env create --name kubernetes --spec samples/platforms/cert-spec.yamlFor using Kubernetes token authentication, you need to get API key and usesamples/platforms/apikey-spec.yamlspec to create env:rally env create --name kubernetes --spec samples/platforms/apikey-spec.yamlFor initializationRally environmentto communicate to existing Kubernetes\ncluster you can also use system environment variables instead of making\nspecification json/yaml file. See the list of available options:As like regular kubernetes client (kubectl) Rally can read kubeconfig file.\nCallrally env create --name kubernetes-created --from-sys-envand Rally\nwith check$HOME/.kube/configfile to the available configuration. Also,\nyou can specifyKUBECONFIGvariable with a path different to the default$HOME/.kube/config.Despite the fact thatkubectldoesn't support specifying Kubernetes\ncredentials via separated system environment variables per separate option\n(auth_url, api_key, etc) like other platforms support (OpenStack, Docker,\netc), Rally team provides this way. Checkexisting@kubernetes plugin documentationfor the list of all available variables. Here is a simple example of this feature:#theURLtotheKuberneteshost.export KUBERNETES_HOST=\"https://example.com:3030\"#apathtoafilecontainingTLScertificatetousewhenconnectingtotheKuberneteshost.export KUBERNETES_CERT_AUTH=\"~/.kube/cert_auth_file\"#clientAPIkeytouseastokenwhenconnectingtotheKuberneteshost.export KUBERNETES_API_KEY=\"foo\"#clientAPIkeyprefixtouseintokenwhenconnectingtotheKuberneteshost.export KUBERNETES_API_KEY_PREFIX=\"bar\"#finallycreateaRallyenvironmentrally env create --name my-kubernetes --from-sysenvCheck env availbility by the following command:rally env checkWhere the tasks and bugs are tracked ?!The primary tracking system isIssues at GitHub.For Rally framework related issues look atLaunchpad."} +{"package": "xr-analytics", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "x-rand", "pacakge-description": "x_randRandomization package foredXcoursesFeaturesUsers can:Randomize mathematical problems on edXRandomize multiple choice problems on edXRandomize checkbox problems on edXAPI DocumentationThefull api documentationfor x_rand2 can be foundhere.CompatibilityFor Compatibility purposes, x_rand has multiple x_rand packages. All github documentation refers to the most recent version of x_rand which is x_rand2All versions API documentation can be found in the links below:x_rand:https://connor-makowski.github.io/x_rand/x_rand/x_rand.htmlx_rand2:https://connor-makowski.github.io/x_rand/x_rand2/x_rand.htmlInstallation For use in edXUpload thepython_lib.zipfile to your edX course.WARNING: This will overwrite your currentpython_lib.zipif you already have it.NOTE: If you already have apython_lib.zip, you can add the x_rand.py file frompython_libdirectly to yourpython_libfolder, re-zip it and re-upload it.Installation For testing and admin useMake sure you have Python 3.x.x (or higher) installed on your system. You can download it frompython.pip install x_randExample Random mathematical problemInitialize anx_randvariable with the current student AID:Note you should always set a randomupseed(integer) for each problemx=x_rand(anonymous_student_id, upseed=28)Input data:data=[\n ['a','b'],\n [1,2],\n [2,4]\n]To use the variables in edX problems, you have to create relevant variables and make them global:To do this use theglobals().update()functionThen randomly select a row out of that dataglobals().update(x.select_random(data))Note: Column headers from your data are now available to be called as variables globally. If the first row of data was selected:print (a)\n> 1\nprint (b)\n> 2These can be called into edX scripts as$aand$brespectively. An exampleBlank Advanced Problemscript is below:\n\n\n\nEnter your answer below.\n\n\n\nExample Random multiple choice or checkbox problemInitialize anx_randvariable with the current student AID:Note you should always set a randomupseed(integer) for each problemx=x_rand(anonymous_student_id, upseed=99)Input data:data = [\n [\"text\", \"correct\"],\n [\"A\", \"True\"],\n [\"B\", \"True\"],\n [\"1\", \"False\"],\n [\"2\", \"False\"],\n [\"3\", \"False\"],\n [\"4\", \"False\"]\n]To use the variables in edX problems, you have to create relevant variables and make them global:To do this use a theglobals().update()functionRandomly select four (n_total=4) answers where one (n_true=1) answer is true (specified as thecorrectcolumn bycorrect_indicator='correct'):globals().update(x.choices_random(data, correct_indicator='correct', n_true=1, n_total=4))Note: You can now call each of your column headers in the order in which they were randomly selected from00ton_total-1:print (text_00, correct_00)\n> 2, False\nprint (text_01, correct_01)\n> A, True\nprint (text_02, correct_02)\n> 3, False\nprint (text_03, correct_03)\n> 1, False\nprint (text_04, correct_04)\n> NameError: name 'text_04' is not definedThese can be called into edX scripts as$text_XXand$correct__XXrespectively. Similarly, all columns added can be called asmycol_XX. An exampleBlank Advanced Problemscript is below:\n\n\n\nSelect all that apply.\n\n$text_00\n$text_01\n$text_02\n$text_03\nNone of the above\n\n\nExample Fingerprinting problemThis can be used to identify students that post exam problems to outside websites.While not guaranteed to be unique, large enough lists with sufficient numbers of selected values can almost guarantee a unique result per student.To fingerprint a problem.Initialize anx_randvariable with the current student AID:Note you should always set a randomupseed(integer) for each problemx=x_rand(anonymous_student_id, upseed=100)Input data:females = [\n [\"female\"],\n [\"Jenny\"],\n [\"Carla\"],\n [\"Mary\"],\n [\"Jin\"],\n [\"Marta\"],\n [\"Sadef\"]\n]\nmales = [\n [\"male\"],\n [\"Carter\"],\n [\"John\"],\n [\"Jose\"],\n [\"Luke\"],\n [\"Adam\"],\n [\"Ahmed\"]\n]To use the variables in edX problems, you have to create relevant variables and make them global:To do this, use a simpleglobals().update()functionRandomly select and shuffle four (n_total=4) female names and four (n_total=4) male names:globals().update(x.fingerprint(females, n_total=4))\nglobals().update(x.fingerprint(males, n_total=4))Note: You can now call each of your column headers in the order in which they were randomly selected from00ton_total-1:print (female_00, male_03)\n> Jenny CarterThese can be called into edX scripts as$female_XXand$male_XXrespectively. Similarly, all columns added can be called asmycol_XX. An exampleBlank Advanced Problemscript is below:\n \n\n\nSelect a response below\n\n No\n Yes\n \n\nRecreating Student dataSee./examplesexamples on how to recreate student data on your local machine."} +{"package": "xrandom", "pacakge-description": "xrandomRandom something.Installation$ pip3 install xrandomUsagexrandom.salt()first, last = xrandom.fake_name()salt = random.salt()salt, hint = random.salt(hint=True)..."} +{"package": "xrandr-extend", "pacakge-description": "xrandr-extendExtend a HIDPI screen to a normal DPI external display. This command line tool\nimplements various solutions described in theHIDPI Arch Linux wiki\npage.Free software: GNU General Public License v3Installationpipinstallxrandr-extend--useror alternatively usepipx:pipxinstallxrandr-extendConfigurationpython-mxrandr_extend.configThis creates a file~/.config/xrandr-extend.cfgwhich looks like this:[provider:modesetting]primary=eDP-1hdmi=HDMI-1vga=DP-1[provider:intel]primary=eDP1hdmi=HDMI1vga=DP1[resolutions]primary=3200, 1800hdmi=1920, 1080vga=1920, 1200# [scaling]# primary = 1.0# hdmi = 2.0# vga = 2.0# [rotation]# primary = left# hdmi = left# vga = rightThe first few sections have the name in the format[provider:display_driver].\nRunxrandr --listprovidersto find what your system has. The values in this\nsection should be given asprofile = monitor_name, as in the output ofxrandr --listmonitorscommand. You may even remove existing sections and\nadd more sections for yourdisplay driver.Each line in the[resolutions]section signifies aresolution profilein\nthe formatprofile = [width_in_pixels, height_in_pixels]. Theprofileprimaryshould contain the resolution of your built-in display. You may edit\nor remove the remaining valueshdmiandvga.The[scaling]section contains the scale factors, which if uncommented,\noverrides the scale factor computed from the resolutions.The[rotation]section specifies the directions to rotate the output contents\nsimilarly toxrandr --rotate.Quick referenceusage: xrandr-extend [-h] [-p PRI_RES PRI_RES] [-e EXT_RES EXT_RES][-x EXT_SCALE] [-m] [-n] [-o] [-s] [-d]profileExtend a HIDPI screen to a normal DPI external displaypositional arguments:profile Use preset external resolution profiles (available:['hdmi', 'vga']).optional arguments:-h, --help show this help message and exit-p PRI_RES PRI_RES, --pri-res PRI_RES PRI_RESModify preset resolution of primary display (default:3200, 1800)-e EXT_RES EXT_RES, --ext-res EXT_RES EXT_RESModify preset resolution of external display (defaultbased on profile)-x EXT_SCALE, --ext-scale EXT_SCALESets the scale factor of external display (DPI ofprimary display / DPI of external display), overridingscale factor estimation from resolutions-m, --mirror Mirror the external display-n, --pan Pan the position of external display-o, --only Extend and use only external display-s, --pos Set the position of external display explicitly-d, --dry-run Preview command without executing itExamples--------#Built-inoptionsoruser-configuredoptionsareusedwhenonlythedisplay#profileismentioned$xrandr-extend--dry-runvga$xrandr-extendvga$xrandr-extendhdmi#Otheroptionstoextendthedisplay$xrandr-extend--panhdmi$xrandr-extend--onlyhdmi$xrandr-extend-e1024768-nvga# Pan with custom external resolution$xrandr-extend-x2.0hdmi# Custom scale factorCreditsThis package was created withCookiecutterand theashwinvis/cookiecutter-pypackageproject template.History0.3.0 (2021-12-22)New option-ror--rotateto orient the external display0.2.0 (2019-07-15)New optional option-xor--ext-scalefor the scaling factor (PR #4, #5)0.1.1 (2019-05-16)Correct commandxrandr_extend->xrandr-extend0.1.0 (2019-05-16)Flicker correctionUse cookiecutter to generate src layout0.0.3Deploy to PyPIReorganize as a package and allow for configurationUsepkg_resourcesto finddefault.cfg0.0.2Simpler defaults which uses only scaling factorsParse args only inside__main__and do not run any commands during dry runLess bugs"} +{"package": "xrandrl", "pacakge-description": "No description available on PyPI."} +{"package": "xrandr-manager", "pacakge-description": "xrandr-managerAboutManage display on Linux.Requirexrandr(pacman -S xorg-xrandr)Installationpipinstallxrandr-managerUsageSet all display.xrandr-managerSet mirror display.xrandr-manager--mirrorOnly main display.xrandr-manager--offSelect main display from prompt.xrandr-manager--promptShow help.xrandr-manager--help"} +{"package": "xrandroll", "pacakge-description": "XRandRollNone of the existing display configuration tools does what I think is \"the right thing\".\nSo I went and wrote one.The Right ThingDon't start from a stored config, use xrandr to read the systems' current stateAllow creating \"profiles\" that will get applied smartly (not there yet)Generate a xrandr invocation to reflect the desired configurationAllow per-monitor scalingAllow arbitrary monitor positioningImplement \"scale everything so all the pixels are the same size\"To try:If you have PySide2:python -m xrandrollin the folder where you cloned it (of course deps are a problem,\nthis is experimental code, if you can't figure it out it's probably better for you \ud83d\ude0a).TODO:Implement other thingsForget about it forever"} +{"package": "xray", "pacakge-description": "xray has been renamed to xarray!We issued this final release of xray\nv0.7.0, which is identical to xarray v0.7.0, to ease this transition. You\ncan find xarray on PyPI athttps://pypi.python.org/pypi/xarray/.xarray(formerlyxray) is an open source project and Python package\nthat aims to bring the labeled data power ofpandasto the physical sciences,\nby providing N-dimensional variants of the core pandas data structures.Our goal is to provide a pandas-like and pandas-compatible toolkit for\nanalytics on multi-dimensional arrays, rather than the tabular data for which\npandas excels. Our approach adopts theCommon Data Modelfor self-\ndescribing scientific data in widespread use in the Earth sciences:xarray.Datasetis an in-memory representation of a netCDF file.Important linksHTML documentation:http://xarray.pydata.orgIssue tracker:http://github.com/pydata/xarray/issuesSource code:http://github.com/pydata/xarraySciPy2015 talk:https://www.youtube.com/watch?v=X0pAhJgySxk"} +{"package": "x-ray", "pacakge-description": "x-ray is a Python library for finding bad redactions in PDF documents.Why?At Free Law Project, we collect millions of PDFs. An ongoing problem\nis that people fail to properly redact things. Instead of doing it the right\nway, they just draw a black rectangle or a black highlight on top of black\ntext and call it a day. Well, when that happens you just select the text under\nthe rectangle, and you can read it again. Not great.After witnessing this problem for years, we decided it would be good to figure\nout how common it is, so, with some help, we built this simple tool. You give\nthe tool the path to a PDF. It tells you if it has worthless redactions in it.What next?Right now,x-rayworks pretty well and we are using it to analyze documents\nin our collections. It could be better though. Bad redactions take many forms.\nSee the issues tab for other examples we don't yet support. We'd love your\nhelp solving some of tougher cases.InstallationWith poetry, do:poetry add x-rayWith pip, that'd be:pip install x-rayUsageYou can easily use this on the command line. Once installed, just:%xraypath/to/your/file.pdf{\"1\":[{\"bbox\":[58.550079345703125,72.19873046875,75.65007781982422,739.3987426757812],\"text\":\"The Ring travels by way of Cirith Ungol\"}]}Or if you have the file on a server somewhere, give it a URL. If it starts\nwithhttps://, it will be interpreted as a PDF to download:%xrayhttps://free.law/pdf/congressional-testimony-michael-lissner-free-law-project-hearing-on-ethics-and-transparency-2021-10-26.pdf{}A fun trick you can do is to make a file with one URL per line, call iturls.txt. Then you can run this to check each URL:xargs-n1xrayis possible but you have to manually ensure that the dependencies are all\ninstalled! The first command installs xrayutilities in the systems default\ndirectories, whereas in the second command you can manually specify the\ninstallation path.By default the installation procedure tries to enable OpenMP support\n(recommended). It is disabled silently if OpenMP is not available. It can also\nbe disabled by using the--without-openmpoption for the installation:python setup.py build_ext --without-openmp installRequirementsThe following requirements are needed for installing and usingxrayutilities:Python (>= 3.6)h5pyscipy (version >= 0.18.0)numpy (version >= 1.9)lmfit (>= 1.0.1)matplotlib (optional, version >= 3.1.0)mayavi (optional, only used optionally inCrystal.show_unitcell)When building from source you also might need:C-compiler (preferential with OpenMP support)Python dev headerssetuptoolspytest (optional - only if you want to run the test environment)sphinx (optional - only when you want to build the documentation)numpydoc (optional - only when you want to build the documentation)rst2pdf (optional - only when you want to build the documentation)sphinx_rtd_theme (optional - only when you want to build the documentation)svglib (optional - only when you want to build the pdf documentation)refer to your operating system documentation to find out how to install\nthose packages. On Microsoft Windows refer to the Documentation for the\neasiest way of the installation (Anaconda, Python(x,y), or WinPython).Python-2.7 and Python-3.X compatibilityThe current development is for Python3 (version >=3.6) only. xrayutilities up\nto version 1.5.x can be used with Python-2.7 as well. Python 3.3 to 3.5 was\nsupported up to 1.6.0.The Python package configurationThe following steps should only be necessary when using non-default\ninstallation locations to ensure the Python module is found by the Python\ninterpreter. In this case the module is installed under/lib[64]/python?.?/site-packageson Unix systems and/Lib/site-packageson Windows systems.If you have installed the Python package in a directory unknown to your Python\ndistribution, you have to tell Python where to look for the Package. There are\nseveral ways how to do this:add the directory where the package is installed to yourPYTHONPATHenvironment variable.add the path to sys.path in the.pythonrcfile placed in your home\ndirectoryimport sys\nsys.path.append(\"path to the xrayutilities package\")simply apply the previous method in every script where you want to\nuse the xrayutilities package before importing the packageimport sys\nsys.path.append(\"path to the xrayutilities package\")\nimport xrayutilitiesObtaining the source codeThe sources are hosted on sourceforge in git repository.\nUsegit clone https://github.com/dkriegner/xrayutilities.gitto clone the git repository. If you would like to have commit rights\ncontact one of the administrators.Updateif you already installed xrayutilities you can update it by navigating into\nits source folder and obtain the new sources by ::git pullor download the new tarball from sourceforge\n(https://sf.net/projects/xrayutilities) if any code changed during the update you\nneed to reinstall the Python package. Thats easiest achieved bypip install .In case you are not certain about the installation location it can be determined bypython -c \"import xrayutilities as xu; print xu.__file__\"\n /usr/local/lib64/python3.6/site-packages/xrayutilities/__init__.pycif the output is e.g.:/usr/local/lib64/python3.6/site-packages/xrayutilities/init.pyyou previously installed xrayutilities in/usr/local, which should be used\nagain as install path. Use ::pip install --prefix= .to install the updated package.DocumentationDocumentation for xrayutilities is found on the webpagehttps://xrayutilities.sourceforge.ioThe API-documentation can also be browsed bypydoc -p PORTin any web-browser, after the installation is finished."} +{"package": "xrayvisim", "pacakge-description": "XRAYVISION is an open-source Python library for Fourier or synthesis imaging of X-Rays. The most\ncommon usage of this technique is radio interferometry however there have been a number of solar\nX-ray missions which also use this technique but obtain the visibilities via a different method.InstallationRequirements: Python3.6+, SunPy0.8+As XRAYVISION is still a work in progress it has not been release to PyPI yet. The recommended way\nto install XRAYVISION is via pip from git.pipinstallgit+https://github.com/sunpy/xrayvision.gitUsagefromastropyimportunitsasufromxrayvision.visibilityimportRHESSIVisibilityfromxrayvisionimportSAMPLE_RHESSI_VISIBILITIESrhessi_vis=RHESSIVisibility.from_fits_file(SAMPLE_RHESSI_VISIBILITIES)rhessi_map=rhessi_vis.to_map(shape=(65,65),pixel_size=[4.,4.]*u.arcsec)rhessi_map.peek()Getting HelpContributingWhen you are interacting with the SunPy community you are asked to\nfollow ourCode of Conduct."} +{"package": "xray-vision", "pacakge-description": "xray-visionDomain specific plotting and GUI widgets for X-ray scienceConda RecipesInstall the most recent tagged build:conda install xray-vision -c lightsource2-tagInstall the most recent development build:conda install xray-vision -c lightsource2-devFind the tagged recipehereand the dev recipehere"} +{"package": "xRBM", "pacakge-description": "# xRBM Library\nImplementation of Restricted Boltzmann Machine (RBM) and its variants in TensorflowNote: xRBM is not released yet. Use at your own risk!## Feedback, Bugs, and Questions\nFor any questions, feedback, and bug reports, please use the [Github Issues](https://github.com/omimo/xRBM/issues).## Credits\nCreated by [Omid Alemi](https://omid.al/projects/)## License\nThis code is available under the [MIT license](http://opensource.org/licenses/MIT)."} +{"package": "xrcalc", "pacakge-description": "Microapp xarray calculator"} +{"package": "xrcat", "pacakge-description": "xrcatThis is a small package for getting resources from Xresources. It can be used as a python module or as a CLI tool.UsageIn the command line:$ xrcat \"dwm.background\"\n#1d2021As a python module:from xrcat import xrcat\n\n# Load current resources into xrcat\nxrcat.updateResources()\n\n# Get the resource\nprint(xrcat.getResource(\"dwm.background\"))\n# Output: '#1d2021'Wildcardsxrcat also supports wildcards matching. This means that if you for example wantdwm.backgroundand the value is None, xrcat will match it to*.background. Matches are prioritized based on length so for the example above*.backgroundwill be choosen instead of*backgroundeven though both are matches. This behavior is implemented to ensure that program specific resources are selected before general resources.ContributingI am very new to making packages, so if you know anything that needs polishing or fixing, I am all ears. All help appreciated!LicenseThis project is under the GNU General Public License v3 (GPLv3) - See LICENSE for details"} +{"package": "xrcon", "pacakge-description": "Darkplaces and Quakes rcon[1]protocol and client implementation.\nWorks with such games likeXonotic,Nexuiz,Warsowand other games with\nQuakes rcon.FeaturesSupport old Quake rcon and new Darkplaces secure rcon protocols.Support both IPv4 and IPv6 connections.Bundled console client.Well tested, test coverage near 100%.Works with python 2.7, 3.3+.Installationexecutepip install xrconor runpip install-egit+https://github.com/bacher09/xrcon#egg=xrconto install development version from githubUsageUsing as library:from xrcon.client import XRcon\nrcon = XRcon('server', 26000, 'password')\nrcon.connect() # create socket\ntry:\n data = rcon.execute('status') # on python3 data would be bytes type\nfinally:\n rcon.close()For more info readXRcondocstrings.Using console client:$ xrcon -s yourserver:26001 -p password commandIf you want use IPv6 address it should be put inside square brackets.\nFor example:$ xrcon -s [1080:0:0:0:8:800:200C:417A]:26002 -p password status\n$ xrcon -s [1080:0:0:0:8:800:200C:417B] -p password statusIf port is omitted then by default would be used port 26000.\nYou may also change type of rcon, by default would be used secure time based\nrcon protocol. This protocol works only in Darkplaces based games.\nFor instance:$ xrcon -s warsowserver:44400 -p password -t 0 status0 means old (unsecure) quakes rcon, 1 means secure time base rcon, and 2 is\nsecure challenge based rcon protocol.You may also create ini configuration file in your home directory.xrcon.ini.\nFor example:[DEFAULT]\nserver = someserver:26000\npassword = secret\ntype = 1\ntimeout = 0.9\n\n[other]\nserver = someserver:26001\n\n[another]\nserver = otherserver\npassword = otherpassword\ntype = 0\ntimeout = 1.2Then if you wants execute command on this servers just do:$ xrcon status # for DEFAULT server\n$ xrcon -n other status # for other server\n$ xrcon -n another status # for another serverAlso, there is another one CLI utility \u2014xping. It can be used to measurerttfor server or client. It also supports other games too, so you can measure\nping for Warsow, Quake 3, Urban Terror and some other games.\nHere\u2019s an example:$ xping -c 4 pub.regulars.win\nXPING pub.regulars.win (89.163.144.234) port: 26000\n89.163.144.234 port=26000 time=39.36 ms\n89.163.144.234 port=26000 time=39.63 ms\n89.163.144.234 port=26000 time=39.83 ms\n89.163.144.234 port=26000 time=39.87 ms\n\n--- pub.regulars.win ping statistics ---\n4 packets transmitted, 4 received, 0.0% packet loss\nrtt min/avg/max/mdev = 39.357/39.672/39.870/0.204 msAlso, you can ping clients too, this might be helpful for server admins for\nchecking client networking. First, you need to determine client host and\nport. You can do this viarcon statuscommand. Let\u2019s suppose that status\ncommand returned172.16.254.2:33045address, then xping command will be\nlook like this:xping-p33045 172.16.254.2. Note, that this might not work\nfor some clients because of firewalls and NATs.Here\u2019s few other examples:$ xping -p 26005 mars.regulars.win # stop it with Ctrl-C\n$ xping -p 44400 -t qfusion 212.83.185.75 # ping warsow server\n$ xping -p 27960 -t q3 144.76.158.173 # ping urban terror serverFor more info about CLI options checkxping--help.In some cases results of xping might be inaccurate. For example, if you\nexperience packet duplication or reordering. All currently supported\ngaming protocols have no way to identify concrete response for probe.\nBecause of this, there is no way to determine if application received original\nor duplicated response. It can affect result even more, if duplicated packet\nwill arrive some time later, so application can process it as response for\nnew probe. In some cases application might detect packet duplication.LicenseLGPL[1]remote console, for more info readthis."} +{"package": "xrd", "pacakge-description": "Compatible with XRD 1.0 (execpt XRD Signature and XRDS)http://docs.oasis-open.org/xrd/xrd/v1.0/xrd-1.0.htmlOutstanding issues:support ds:Signaturesupport XRDSparsing of Expires date stamp from XMLmore tests are neededBasic usage:from xrd import XRD, Link\n\nlnk = Link(rel='http://spec.example.net/photo/1.0',\n type='image/jpeg',\n href='http://photos.example.com/gpburdell.jpg')\nlnk.titles.append(('User Photo', 'en'))\nlnk.titles.append(('Benutzerfoto', 'de'))\nlnk.properties.append(('http://spec.example.net/created/1.0', '1970-01-01'))\n\nxrd = XRD(subject=http://example.com/gpburdell)\nxrd.properties.append('http://spec.example.net/type/person')\nxrd.links.append(lnk)\n\nxrd.to_xml()"} +{"package": "xrdconfig", "pacakge-description": "xrdconfigSimple command line tool for checking XrootD configuration files and comparing\nthem. Requires Python 3.8 or later and XrootD 5.0.0 or later."} +{"package": "xrdfit", "pacakge-description": "Introductionxrdfit is a Python package for fitting the diffraction peaks in synchrotron X-ray diffraction (SXRD) and XRD spectra. It is designed to be an easy to use tool for quick analysis of spectra. Features are included for automating fitting over many spectra to enable tracking of peaks as they shift throughout an experiment. xrdfit uses the Python module lmfit for the underlying fitting. xrdfit is designed to be accessible for all researchers who need to process SXRD spectra and so does not require a detailed knowledge of programming or fitting.InstallationTo install as a Python module, typepython -m pip install xrdfitfrom the root directory.\nFor developers, you should install in linked .egg mode usingpython -m pip install -e .If you are using a Python virtual environment, you should activate this first before using the above commands.DocumentationDocumentation including an API reference is provided at:https://xrdfit.readthedocs.io/en/latest/The majority of the documentation is provided as example driven interactive Jupyter notebooks. These are included along with the source code in the \"tutorial notebooks\" folder.\nIf this package was downloaded from pip, the source can be found on GitHub:https://github.com/LightForm-group/xrdfitTry it outYou can try outxrdfitdirectly in your browser with Binder by clickinghere.Note thatTutorial Notebook 4will not run correctly in Binder as it requires the download of asupplementary datasetwhich is not included in the source repository due to its size.CompatibilityThe latest version of xrdfit was tested with Python version 3.10. The minimum required Python version is 3.7.Required librariesThis module uses the Python libraries:NumPymatplotlibpandasdilltqdmSciPylmfitThe following libraries are required to use the tutorial documentation workbooks:Jupyter"} +{"package": "xrd-image-util", "pacakge-description": "xrd-image-utilUtility package for handling XRD image data.Aboutxrd-image-utilaims to provide (i) a lightweight interface for Bluesky data handling, (ii) an arsenal of tools for analyzing XRD image data, and (iii) options for exporting XRD image data. In its current form,xrd-image-utilis tailored for data gathering at APS beamline 6-ID-B.PrerequisitesPython 3.8+Anaconda installations of Python are recommendedGetting StartedThe package can be installed via PyPI with the following shell command:pip install xrd-image-utilExecutionThe package can be imported in-line with the following line of code (the alias ofxiuis not required):import xrdimageutil as xiuLicenseSeeLICENSE.txtfor more information.AuthorHenry Smith- Co-op Student Technical at Argonne National LaboratorySupportReport bugs hereEmail author atsmithh@anl.gov"} +{"package": "xrdmon", "pacakge-description": "UNKNOWN"} +{"package": "xrdownloader", "pacakge-description": "XploitsR | XRDownloader is a module for faster downloading of files.\nIt supports all HTTP protocols and also supports auto resume failed downloads.\nHas a progress-bar to show download statistics also.Installation:pipinstallxrdownloaderLatest development release on GitHubPull and installpipinstall-egit+https://github.com/XploitsR/XRDownloader.git@master#egg=XRDownloaderUsage:# import xrdownloader moduleimportxrdownloader# XRDownloader returns the response from ongoing downloadsxr=xrdownloader.XRDownloader()# To download single file, just put in the urldownload(\"your-file-url\")# To download multiple files, add [] and seperate the links with ,download([\"link-1\",\"link-2\",\"link-3\",\"and so on..\"])# You can also specify a file that contains your linksdownload(\"your-file\")# example: download(\"myLinks.txt\")Examples:single file downloadimportxrdownloaderxr=xrdownloader.XRDownloader()response=xr.download(\"https://xploitsr.tk/assets/csxp_img/logo/icon.png\")print(response)multiple file downloadimportxrdownloaderxr=xrdownloader.XRDownloader()response=xr.download([\"https://www.somesite.co/file-1.pdf\",\"https://www.somesite.co/file-2.pdf\"])print(response)file that contains links of files to downloadimportxrdownloaderxr=xrdownloader.XRDownloader()response=xr.download(\"xploitsr-links.txt\")print(response)All links you typed since day one of using xrdownloader is saved in a file named:allXlinks.txtin every directory you used xrdownloader moduleScreenshot:"} +{"package": "xrdpattern", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xrdphase", "pacakge-description": "Python package for doing science.Free software: 3-clause BSD licenseDocumentation: (COMING SOON!)https://gwbischof.github.io/xrdphase.FeaturesTODO"} +{"package": "xrdPlanner", "pacakge-description": "xrdPlannerA tool to project X-ray diffraction cones on a detector screen at different geometries (tilt, rotation, offset) and X-ray energiesMain application is to visualize the maximum achievable resolution at a given geometry.Is able to project diffraction cones for standard samples or directly from cif files.Can turn out valuable when planning beamtimes at synchrotron facilities (e.g.DanMAX).Helps in deciding on the geometry of an experiment.Meant to run standalone but is readilyinsertableas a widget into an existing PyQt6 GUI.The math used is not meant to bring people to the moon but to provide a quick and simple preview.This is not meant to accurately simulate a diffraction experiment, the step sizes are integer values in mm or degrees.The module building code is designed forDectrisPILATUS3/EIGER2orSACLAMPCCD Detectors (central hole geometry) but one-module systems like theBrukerPhoton IIandRayonixMX-HSare possible as well.It usespython3,numpy,pyqt6,pyqtgraph,pyFAIandDans_Diffraction.Short how-to:pip install xrdPlanner.TypexrdPlannerin a terminal and hit enter.Choose a detector and a model from theDetectormenu.Pick a reference from theReferencemenu to plot its contours (pyFAI).Drop a .cif file onto the window to draw its contours (Dans_Diffraction), click a contour to get a hkl tooltip.Use the units from theUnitsmenu you are the most comfortable with.Hover over the grey line at the top to show the sliders. Click it to make it stay open.Drag the sliders to change energy and geometry.Customisation:Edit thesettings.jsonfile and thedetector_db.jsonfiles.UseSettings->Edit filesto edit thecurrent settingsorDetector dbfile.Reload the settings file to see the difference.geodetermines the startup defaults.plocustomises the general layout and visuals.thmmakes it look the way you want.lmtsets the limiting values of the geometry/energy sliders.Check thesettings file documentation.Add all the missing detectors to thedetector_db.json, see thedetector db entries.ConventionsThe geometry is defined with the center of rotation at the sample position, such that the radius of the rotation circle is equal to the sample to detector distance (SDD). That is, the rotation moves the detector along the goniometer circle, keeping the point of normal incidence (PONI) at the same position relative to the detector surface. At 0\u00b0 the detector is vertical and at 90\u00b0 the detector is horizontal with the detector normal pointing down.\nThe tilt angle is defined relative to the detector face and such that the PONI shifts along the detector face, keeping the SDD fixed. The detector face is thus always tangential to the goniometer circle. The $tilt$ can intuitively be described as a rolling motion along the goniometer circle and is considered a convenience function as it is eqivalent to a combination of $rotation$ and $y_{offset}$. Consequently, the vertical shift of the PONI position ($\\Delta y_{PONI}$) on the detector face is equal to the arclength of a section on the goniometer circle with an angular span equal to the tilt angle.\n$$\\Delta y_{PONI} = SDD \\cdot tilt$$\nThe vertical shift of the point of beam incidence (POBI) in the detector reference frame ($\\Delta y_{POBI}$) can be described by the side length of the right-angle triangle spanned by the goniometer origin, the PONI, and the POBI, subtracted from the vertical shift of the PONI.\n$$\\Delta y_{POBI} = SDD \\cdot \\left( tilt - tan \\left( rotation + tilt \\right) \\right)$$pyFAIuses three rotations, $rot1$, $rot2$, and $rot3$, and three translations, $dist$, $poni1$, and $poni2$, to define the detector position. xrdPlanner uses the same translations ($SDD$, $y_{offset}$, and $x_{offset}$), but only one of the rotations ($rot2$). Apart from the change in sign, the pyFAI $rot2$ and xrdPlanner $rotation$ are equivalent, however, the $tilt$ in pyFAI convention is described by a combination of $rot2$ and shift of $poni1$:\n$$rot2 = -\\left( rotation + tilt\\right)$$\ncombined with\n$$\\Delta poni1 = SDD \\cdot tilt + y_{offset}$$\nAdditionally, pyFAI places the origin at the lower left corner of the detector, whereas xrdPlanner uses the center of the detector as origin, so one must account for translational shifts corresponding to half the width and height of the detector.PolarisationThe polarisation value indicated in xrdPlanner is the apparent scattering intensity, i.e. for P=0.2 only 20 % of the nominal intensity is observed, such that $I_{ij}^{obs}=P_{ij}\\cdot I_0$. (Omitting solid angle).\nThe polarisation valuePfor the $ij^{th}$ pixel is defined as[1]:P_{ij} = 1 - [p (\\vec{v}_{ij} \\cdot \\vec{e}_x)^2+(1-p) (\\vec{v}_{ij} \\cdot \\vec{e}_y)^2] \\qquad$1.0$horizontal polarisation$0.5$random polarisation$0.0$vertical polarisationwherepis the polarisation factor, $\\vec{v}_{ij}$ is the normalised vector coordinate of the $ij^{th}$ pixel, and $\\vec{e}_x$ and $\\vec{e}_y$ are the horizontal and vertical basis vectors.NB:The polarisation factor differs from the pyFAI convention, which goes from -1 to 1 rather than from 0 to 1.Use pre-set beamline settings files:Download a settings file from here (e.g. settings/DanMAX.json).Use the import settings function from the GUI to import.You can switch between all imported settings.Use the export window to customise and export your settings.Known bugs and limitations:On Windows: Switching Dark/Light mode requires restart to change the window frame color.As of now, there is no consistency check performed on the imported .json file.The projections fail at a combined angle (rotation + tilt) of 90 degrees and beyond.If the program crashes (libc++abi) when opening the export window (on a Mac) please update PyQt6 to the latest version.After the update:Sometimes I might change the name of a parameter and you will get a warning message upon startup looking something like this:WARNING: \"conic_ref_min_int\" is not a valid key! Either that key is no longer in use or its name got changed and is now reset to the default value. The settings file is updated and the warning should no longer appear after restart. Apart from this, your edited settings file will not be altered after updating.Added new keys:conic_ref_cif_kev: this key sets the energy at which Dans_Dffraction calculates the intensities from a cif, increasing the value allows for higher resolution reference conics. However, the calculation will get slower.useponi_markerandponi_sizeto adjust the poni marker style and size, the color is picked from the colormap.slider_label_xxxx(ener, dist, rota, voff, hoff, tilt, bsdx) accept any string to customise the labels for the sliders.Latest updates:2023-11-28 Update: Added hotkeys to toggle between units/colormaps/overlays.2023-11-28 Update: Added polarisation and solid angle correction factor overlays.2023-11-12 Update: Added a new window to export settings to a file.2023-11-12 Update: Added the option to limit the available detectors for a settings file.2023-11-12 Update: Upon crash the program will start using the default settings.2023-09-26 Update: Added a PONI marker.2023-09-26 Update: Added the option to add custom labels to the sliders.2023-09-26 Update: Added the option to automatically find a reasonable window size (set plot_size to 0).2023-09-26 Bugfix: Fixed a bug that prevented the beamstop menu from updating upon changing the available beamstop list.2023-09-26 Bugfix: Fixed a bug in the calculation of the beamcenter for the combination of rotation and tilt.Older updates2023-08-29 Update: Added a feature to import and switch between settings files.2023-08-22 Bugfix: Fixed missing symbols and the slider bar on Linux.2023-08-22 Update: Added a beamstop, define distance to sample with a slider and pick a size from the menu.2023-08-15 Bugfix: Fixed several bugs with regard to the save/load of the settings file (Again).2023-08-15 Update: Changed the way themes / styles and customisation works internally.2023-07-14 Update: Added a keyplo.conic_ref_cif_kevto edit the energy for the cif intensity calculation.2023-07-14 Bugfix: Fixed a bug in the calculation of the conics, sections close to 90 deg. would sometimes not be drawn.2023-06-30 Update: Reference hkl intensity determines linewidth (irel).2023-06-30 Bugfix: Reference lines stay after settings reload.2023-06-23 Bugfix: Fixed several bugs with regard to the reloading of the settings file.2023-06-21 Update: Settings files accessible from menu, changes can be applied on the fly.2023-06-14 Update: Big speed update.2023-06-01 Update: countourpy was dropped, the conics are now calculated directly instead of being evaluated on a grid.2023-05-25 Update: Dans_Diffraction is used in favour of gemmi as it allows the direct calculation of intensities from the cif.2023-04-26 Update: A hkl tooltip is shown on click on a contour (only for cif contours).2023-04-25 Bugfix: Segmented contours are now drawn properly.2023-04-20 Bugfix: Confined slider window mobility to main window area.2023-04-10 Bugfix: Main window aspect ratio on Windows (menu bar within window).2023-04-10 Bugfix: Label size could not be adjusted.2023-04-10 Bugfix: Large angle (2-Theta > 90) contour label positions.2023-04-09 Update: Drop a cif file onto the window to draw its contours (usesDans_Diffraction).2023-04-05 Update: Uses pyqt6, pyqtgraph and contourpy, dropped matplotlib backend.2023-03-23 Update: Settings are saved to (if doesn't exist) or loaded from (if exists) a 'settings.json' file.2023-03-23 Update: Added horizontal offset support and slider.2022-06-07 Update: Added functionality to plot Standard (LaB6, CeO2, ...) contours (needspyFAI).2022-04-28 Update: Changed contour line generation to accept a list of 2-theta values as input.2022-04-27 Update: Added support forSACLAMPCCD Detectors (central hole geometry).2022-04-25 Bugfix: Calculation of the beamcenter (rotation and tilt).ExamplesA PILATUS3 300K detector and a Rubrene sample.A rotated EIGER2 9M detector and a Rubrene sample (darkmode).The export window with options to select and build up the available detecor / beamstop bank and review/change parameters.HotkeysKeyAction#Display unitst2-Thetadd-spacingqq-spaces$sin(\\theta)/\\lambda$#Toggle OverlaypShow polarisationaShow solid anglehHighlight / Transparency#Cycle colormapscNextShift + cPreviousSettings file documentationgeo - startup defaultsdet_type = 'EIGER2' # [str] Pilatus3 / Eiger2 / etc.\n # -> Detector menu entry\ndet_size = '4M' # [str] 300K 1M 2M 6M / 1M 4M 9M 16M\n # -> Detector submenu entry\nener = 21 # [keV] Beam energy\ndist = 75 # [mm] Detector distance\nyoff = 0 # [mm] Detector offset (vertical)\nxoff = 0 # [mm] Detector offset (horizontal)\nrota = 25 # [deg] Detector rotation\ntilt = 0 # [deg] Detector tilt\nbssz = 'None' # [mm] Current beamstop size (or 'None')\nbsdx = 40 # [mm] Beamstop distance\nunit = 1 # [0-3] Contour legend\n # 0: 2-Theta\n # 1: d-spacing\n # 2: q-space\n # 3: sin(theta)/lambda\nreference = 'None' # [str] Plot reference contours\n # pick from pyFAI\ndarkmode = False # [bool] Darkmode\ncolormap = 'viridis' # [cmap] Contour colormap\nbs_list = [1.5, # [list] Available beamstop sizes\n 2.0,\n 2.5,\n 3.0,\n 5.0]plo - plot settings# - geometry contour section - \nconic_tth_min = 5 # [int] Minimum 2-theta contour line\nconic_tth_max = 100 # [int] Maximum 2-theta contour line\nconic_tth_num = 15 # [int] Number of contour lines\nbeamcenter_marker = 'o' # [marker] Beamcenter marker\nbeamcenter_size = 6 # [int] Beamcenter size\nponi_marker = 'x' # [marker] Poni marker\nponi_size = 8 # [int] Poni size\nconic_linewidth = 2.0 # [float] Contour linewidth\nconic_label_size = 14 # [int] Contour label size\n\n# - reference contour section - \nconic_ref_linewidth = 2.0 # [float] Reference contour linewidth\nconic_ref_num = 100 # [int] Number of reference contours\nconic_ref_cif_int = 0.01 # [float] Minimum display intensity (cif)\nconic_ref_cif_kev = 10.0 # [float] Energy [keV] for intensity calculation\nconic_ref_cif_irel = True # [bool] Linewidth relative to intensity\nconic_ref_cif_lw_min = 0.1 # [float] Minimum linewidth when using irel\nconic_ref_cif_lw_mult = 3.0 # [float] Linewidth multiplier when using irel\nconic_hkl_show_int = False # [bool] Show intensity in hkl tooltip\nconic_hkl_label_size = 14 # [int] Font size of hkl tooltip\n\n# - module section - \ndet_module_alpha = 0.20 # [float] Detector module alpha\ndet_module_width = 1 # [int] Detector module border width\n\n# - general section - \nconic_steps = 100 # [int] Conic resolution\nplot_size = 0 # [int] Plot size, px (0 for auto)\nplot_size_fixed = True # [bool] Fix window size\nunit_label_size = 16 # [int] Label size, px\npolarisation_fac = 0.99 # [float] Horizontal polarisation factor\nshow_polarisation = False # [bool] Show polarisation overlay\nshow_solidangle = False # [bool] Show solid angle overlay\noverlay_resolution = 300 # [int] Overlay resolution\noverlay_toggle_warn = True # [bool] Overlay warn color threshold\n\n# - slider section - \nslider_margin = 12 # [int] Slider frame top margin\nslider_border_width = 1 # [int] Slider frame border width\nslider_border_radius = 1 # [int] Slider frame border radius (px)\nslider_label_size = 14 # [int] Slider frame label size\nslider_column_width = 75 # [int] Slider label column width\nenable_slider_ener = True # [bool] Show energy slider\nenable_slider_dist = True # [bool] Show distance slider\nenable_slider_rota = True # [bool] Show rotation slider\nenable_slider_yoff = True # [bool] Show vertical offset slider\nenable_slider_xoff = True # [bool] Show horizontal offset slider\nenable_slider_tilt = True # [bool] Show tilt slider\nenable_slider_bsdx = True # [bool] Show beamstop distance slider\n\n# - slider labels - \nslider_label_ener = 'Energy\\n[keV]' # [str] Label for energy slider\nslider_label_dist = 'Distance\\n[mm]' # [str] Label for distance slider\nslider_label_rota = 'Rotation\\n[\\u02da]' # [str] Label for rotation slider\nslider_label_voff = 'Vertical\\noffset\\n[mm]' # [str] Label for vertical offset slider\nslider_label_hoff = 'Horizontal\\noffset\\n[mm]' # [str] Label for horizontal offset slider\nslider_label_tilt = 'Tilt\\n[\\u02da]' # [str] Label for tilt slider\nslider_label_bsdx = 'Beamstop\\ndistance\\n[mm]' # [str] Label for beamstop distance slider\n \n# - update/reset - \nupdate_settings = True # [bool] Update settings file after load\nupdate_det_bank = True # [bool] Update detector bank after load\nreset_settings = False # [bool] Reset settings file\nreset_det_bank = False # [bool] Reset detector bank\n\n# - debug/testing -\nset_debug = False # [bool] Debug modethm - themecolor_dark = '#404040' # [color] Global dark color\ncolor_light = '#EEEEEE' # [color] Global light color\n\n# light mode\nlight_conic_label_fill = '#FFFFFF' # [color] Contour label fill color\nlight_conic_ref_color = '#DCDCDC' # [color] Reference contour color\nlight_beamstop_color = '#FF000080' # [color] Beamstop color\nlight_beamstop_edge_color = '#FF0000' # [color] Beamstop edge color\nlight_det_module_color = '#404040' # [color] Detector module border color\nlight_det_module_fill = '#404040' # [color] Detector module background color\nlight_plot_bg_color = '#FFFFFF' # [color] Plot background color\nlight_unit_label_color = '#808080' # [color] Label color\nlight_unit_label_fill = '#FFFFFF' # [color] Label fill color\nlight_slider_border_color = '#808080' # [color] Slider frame border color\nlight_slider_bg_color = '#AAC0C0C0' # [color] Slider frame background color\nlight_slider_bg_hover = '#C0C0C0' # [color] Slider frame hover color\nlight_slider_label_color = '#000000' # [color] Slider frame label color\n\n# dark mode\ndark_conic_label_fill = '#000000' # [color] Contour label fill color\ndark_conic_ref_color = '#505050' # [color] Reference contour color\ndark_beamstop_color = '#FF000080' # [color] Beamstop color\ndark_beamstop_edge_color = '#FF0000' # [color] Beamstop edge color\ndark_det_module_color = '#EEEEEE' # [color] Detector module border color\ndark_det_module_fill = '#EEEEEE' # [color] Detector module background color\ndark_plot_bg_color = '#000000' # [color] Plot background color\ndark_unit_label_color = '#C0C0C0' # [color] Label color\ndark_unit_label_fill = '#000000' # [color] Label fill color\ndark_slider_border_color = '#202020' # [color] Slider frame border color\ndark_slider_bg_color = '#AA303030' # [color] Slider frame background color\ndark_slider_bg_hover = '#303030' # [color] Slider frame hover color\ndark_slider_label_color = '#C0C0C0' # [color] Slider frame label colorlmt - limits# energy [keV]\nener_min = 5 # [int] Energy minimum [keV]\nener_max = 100 # [int] Energy maximum [keV]\nener_stp = 1 # [int] Energy step size [keV]\n\n# distance [mm]\ndist_min = 40 # [int] Distance minimum [mm]\ndist_max = 1000 # [int] Distance maximum [mm]\ndist_stp = 1 # [int] Distance step size [mm]\n\n# X-offset [mm]\nxoff_min = -150 # [int] Horizontal offset minimum [mm]\nxoff_max = 150 # [int] Horizontal offset maximum [mm]\nxoff_stp = 1 # [int] Horizontal offset step size [mm]\n\n# Y-offset [mm]\nyoff_min = -250 # [int] Vertical offset minimum [mm]\nyoff_max = 250 # [int] Vertical offset maximum [mm]\nyoff_stp = 1 # [int] Vertical offset step size [mm]\n\n# rotation [deg]\nrota_min = -45 # [int] Rotation minimum [deg]\nrota_max = 45 # [int] Rotation maximum [deg]\nrota_stp = 1 # [int] Rotation step size [deg]\n\n# tilt [deg]\ntilt_min = -40 # [int] Tilt minimum [deg]\ntilt_max = 40 # [int] Tilt maximum [deg]\ntilt_stp = 1 # [int] Tilt step size [deg]\n\nbsdx_min = 5 # [int] Beamstop distance minimum [mm]\nbsdx_max = 1000 # [int] Beamstop distance maximum [mm]\nbsdx_stp = 1 # [int] Beamstop distance step size [mm]Detector db entriesThe detector_db.json is stored as a dictionarykey: detector name e.g. PILATUS3value: dictionary {Entry:Value,}, see table belowEntryValueHinthms83.8[mm] Module size (horizontal)vms33.5[mm] Module size (vertical)pxs172e-3[mm] Pixel sizehgp7[pix] Gap between modules (horizontal)vgp17[pix] Gap between modules (vertical)cbh0[mm] Central beam holeThe size Entry is a dictionary {key:value,}key: detector size / type, e.g. 300Kvalue: list [hmn, vmn]hmn: [int] Number of modules (horizontal)vmn: [int] Number of modules (vertical)Example of the PILATUS3 entry\"PILATUS3\": {\n \"hms\": 83.8,\n \"vms\": 33.5,\n \"pxs\": 0.172,\n \"hgp\": 7,\n \"vgp\": 17,\n \"cbh\": 0,\n \"size\": {\n \"300K\": [1, 3],\n \"1M\": [2, 5],\n \"2M\": [3, 8],\n \"6M\": [5,12]\n }\n},Example code for adding xrdPlanner as a widget into an existing GUIxrdPlanner uses its own menu bar, setting the GUI as the parent for xrdPlanner makes it add its menus to the parents menu bar, and likely more in the future.import sys\nfrom PyQt6 import QtWidgets\nfrom xrdPlanner.classes import MainWindow as xrdPlanner\n\nclass MainWindow(QtWidgets.QMainWindow):\n def __init__(self):\n super().__init__()\n # make layout and widget\n layout = QtWidgets.QGridLayout()\n central_widget = QtWidgets.QWidget()\n central_widget.setLayout(layout)\n self.setCentralWidget(central_widget)\n # add xrdPlanner to layout\n xrdPlanner_as_widget = xrdPlanner(parent=self)\n layout.addWidget(xrdPlanner_as_widget)\n\nif __name__ == '__main__':\n app = QtWidgets.QApplication(sys.argv)\n window = MainWindow()\n window.show()\n app.exec()I hope this turns out to be useful for someone!"} +{"package": "xrd-simulator", "pacakge-description": "Simulate X-ray Diffraction from Polycrystals in 3D.TheX-RayDiffractionSIMULATORpackage defines polycrystals as a mesh of tetrahedral single crystals\nand simulates diffraction as collected by a 2D discretized detector array while the sample is rocked\naround an arbitrary rotation axis.xrd_simulatorwas originally developed with the hope to answer questions about measurement optimization in\nscanning x-ray diffraction experiments. However,xrd_simulatorcan simulate a wide range of experimental\ndiffraction setups. The essential idea is that the sample and beam topology can be arbitrarily specified,\nand their interaction simulated as the sample is rocked. This means that standard \u201cnon-powder\u201d experiments\nsuch asscanning-3dxrdand full-field3dxrd(or HEDM if you like) can be simulated as well as more advanced\nmeasurement sequences such as helical scans for instance. It is also possible to simulatepowder likescenarios using orientation density functions as input.IntroductionBefore reading all the boring documentation (which is hosted here) let\u2019s dive into some end to end\nexamples to get us started on a good flavour.Thexrd_simulatoris built around four python objects which reflect a diffraction experiment:Abeamof x-rays (using thexrd_simulator.beammodule)A 2D areadetector(using thexrd_simulator.detectormodule)A 3Dpolycrystalsample (using thexrd_simulator.polycrystalmodule)A rigid body samplemotion(using thexrd_simulator.motionmodule)Once these objects are defined it is possible to let thedetectorcollect scattering of thepolycrystalas the sample undergoes the prescribed rigid bodymotionwhile being illuminated by the xraybeam.Let\u2019s go ahead and build ourselves some x-rays:importnumpyasnpfromxrd_simulator.beamimportBeam# The beam of xrays is represented as a convex polyhedron# We specify the vertices in a numpy array.beam_vertices=np.array([[-1e6,-500.,-500.],[-1e6,500.,-500.],[-1e6,500.,500.],[-1e6,-500.,500.],[1e6,-500.,-500.],[1e6,500.,-500.],[1e6,500.,500.],[1e6,-500.,500.]])beam=Beam(beam_vertices,xray_propagation_direction=np.array([1.,0.,0.]),wavelength=0.28523,polarization_vector=np.array([0.,1.,0.]))We will also need to define a detector:fromxrd_simulator.detectorimportDetector# The detector plane is defined by it's corner coordinates det_corner_0,det_corner_1,det_corner_2detector=Detector(pixel_size_z=75.0,pixel_size_y=55.0,det_corner_0=np.array([142938.3,-38400.,-38400.]),det_corner_1=np.array([142938.3,38400.,-38400.]),det_corner_2=np.array([142938.3,-38400.,38400.]))Next we go ahead and produce a sample, to do this we need to first define a mesh that\ndescribes the topology of the sample, in this example we make the sample shaped as a ball:fromxrd_simulator.meshimportTetraMesh# xrd_simulator supports several ways to generate a mesh, here we# generate meshed solid sphere using a level set.mesh=TetraMesh.generate_mesh_from_levelset(level_set=lambdax:np.linalg.norm(x)-768.0,bounding_radius=769.0,max_cell_circumradius=450.)Every element in the sample is composed of some material, or \u201cphase\u201d, we define the present phases\nin a list ofxrd_simulator.phase.Phaseobjects, in this example only a single phase is present:fromxrd_simulator.phaseimportPhasequartz=Phase(unit_cell=[4.926,4.926,5.4189,90.,90.,120.],sgname='P3221',# (Quartz)path_to_cif_file=None# phases can be defined from crystalographic information files)The polycrystal sample can now be created. In this example the crystal elements have random orientations\nand the strain is uniformly zero in the sample:fromscipy.spatial.transformimportRotationasRfromxrd_simulator.polycrystalimportPolycrystalorientation=R.random(mesh.number_of_elements).as_matrix()polycrystal=Polycrystal(mesh,orientation,strain=np.zeros((3,3)),phases=quartz,element_phase_map=None)We may save the polycrystal to disc by using the builtinsave()command aspolycrystal.save('my_polycrystal',save_mesh_as_xdmf=True)We can visualize the sample by loading the .xdmf file into your favorite 3D rendering program.\nInparaviewthe sampled colored by one of its Euler angles looks like this:We can now define some motion of the sample over which to integrate the diffraction signal:fromxrd_simulator.motionimportRigidBodyMotionmotion=RigidBodyMotion(rotation_axis=np.array([0,1/np.sqrt(2),-1/np.sqrt(2)]),rotation_angle=np.radians(1.0),translation=np.array([123,-153.3,3.42]))Now that we have an experimental setup we may collect diffraction by letting the beam and detector\ninteract with the sample:polycrystal.diffract(beam,detector,motion)diffraction_pattern=detector.render(frames_to_render=0,lorentz=False,polarization=False,structure_factor=False,method=\"project\")The resulting rendered detector frame will look something like the below. Note that the positions of the diffraction spots may vary as the crystal orientations were randomly generated!:importmatplotlib.pyplotaspltfig,ax=plt.subplots(1,1)ax.imshow(diffraction_pattern,cmap='gray')plt.show()To compute several frames simply change the motion and collect the diffraction again. The sample may be moved before\neach computation using the same or another motion.polycrystal.transform(motion,time=1.0)polycrystal.diffract(beam,detector,motion)Many more options for experimental setups and intensity rendering exist, have fun experimenting!\nThe above example code can be found as asingle .py file here.InstallationAnaconda installation (Linux and Macos)xrd_simulatoris distributed on theconda-forge channeland the preferred way to install\nthe xrd_simulator package is viaAnaconda:conda install -c conda-forge xrd_simulator\nconda create -n xrd_simulator\nconda activate xrd_simulatorThis is meant to work across OS-systems and requires anAnacondainstallation.(The conda-forge feedstock ofxrd_simulatorcan be found here.)Anaconda installation (Windows)To install with anaconda on windows you must make sure that external dependencies ofpygalmeshare preinstalled\non your system. Documentation on installing these packagecan be found elsewhere.Pip InstallationPip installation is possible, however, external dependencies ofpygalmeshmust the be preinstalled\non your system. Installation of these will be OS dependent and documentationcan be found elsewhere.:pip install xrd-simulatorSource installationNaturally one may also install from the sources:git clone https://github.com/FABLE-3DXRD/xrd_simulator.git\ncd xrd_simulator\npython setup.py installThis will then again require thepygalmeshdependencies to be resolved beforehand.Creditsxrd_simulatormakes good use of xfab and pygalmesh. The source code of these repos can be found here:https://github.com/FABLE-3DXRD/xfabhttps://github.com/nschloe/pygalmesh"} +{"package": "xrdsum", "pacakge-description": "xrdsumXrootDplugin for calculating checksums and storing them\nin extended attributes. Currently supports ADLER32 checksum and HDFS as backend.\nBorrows heavily fromcephsum plugin.This plugin is designed to easily accommodate new checksum types and backends.\nAdditional dependencies for backends are defined as optional dependencies for\nthe package (see usage instructions).Usagexrdsum requires Python version >=3.8. To install, run:pipinstallxrdsum[hdfs]xrdsum--help\nUsage:xrdsum[OPTIONS]COMMAND[ARGS]...Callbacktogivethe--verboseand--debugoptionstoallcommands\n\nOptions:-v,--verboseVerboseoutput-d,--debugDebugoutput-l,--log-fileTEXTLogfile--install-completionInstallcompletionforthecurrentshell.--show-completionShowcompletionforthecurrentshell,tocopyitorcustomizetheinstallation.--helpShowthismessageandexit.\n\nCommands:getGetthechecksumofafile.verifyCheckifafilehasthecorrectchecksum.Example:/usr/bin/time-vxrdsum--verbose--debugget/xrootd/dteam/user/jwalder/file_1GB_020--read-size128xrootd config# ensure cksum adler32 is included in the tpc directive, in order to calculate by default on transfer\nofs.tpc cksum adler32 fcreds ?gsi =X509_USER_PROXY autorm xfr 40 pgm /etc/xrootd/xrdcp-tpc.sh\n\n# add this line to trigger external checksum calculation. Would be overwritten by other xrootd.chksum lines\nxrootd.chksum max 50 adler32 /etc/xrootd/xrdsum.shwith/etc/xrootd/xrdcp-tpc.shcontaining:#!/bin/sh# from https://github.com/snafus/cephsum/blob/master/scripts/xrdcp-tpc.sh#Original code#/usr/bin/xrdcp --server -f $1 root://$XRDXROOTD_PROXY/$2# Get the last two variables as SRC and DST, all others are assumed as additional argumentsOTHERARGS=\"${@:1:$#-2}\"DSTFILE=\"${@:$#:1}\"SRCFILE=\"${@:$#-1:1}\"/usr/bin/xrdcp$OTHERARGS--server-f$SRCFILEroot://$XRDXROOTD_PROXY/$DSTFILEand with/etc/xrootd/xrdsum.shcontaining:#!/usr/bin/env bashRESULT=$(xrdsumget--store-result--chunk-size64--verbose--storage-catalog/etc/xrootd/storage.xml\"$1\")ECODE=$?# XRootD expects return on stdout - checksum followed by a new lineprintf\"%s\\n\"\"$RESULT\"exit\"$ECODE\"Conda installation examplewgethttps://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh\nbashMiniconda3-latest-Linux-x86_64.sh-b-p/miniconda\nrm-fMiniconda3-latest-Linux-x86_64.shexportPATH=\"/miniconda/bin:$PATH\"condainit\ncondaupdate-yconda\ncondainstallpython=3.10\npipinstallxrdsum[hdfs]"} +{"package": "xrdtools", "pacakge-description": "xrdtoolsThe xrdtools package can be used to read .xrdml files (Panalytical XPert X-ray diffraction).\nNot all feature of file format may be supported at the current development state.For more information please visithttp://xrdtools.readthedocs.org/en/latest/orhttps://github.com/paruch-group/xrdtools.DevelopmentCurrently, I do not have the time to develop this package any further.\nTherefore, patches are very sporadic.In case anyone wants to take over the maintenance, please contact me\n@bziegler."} +{"package": "xrdump", "pacakge-description": "Replacement for ncdump using xarray."} +{"package": "xrd-viewer", "pacakge-description": "xrd-viewerSimple analysis tool for NeXus data files measured at the SIXS beamline at synchrotron Soleil.Written in Python with Qt5 GuiInstallationPlease install thepython3-pyqt5package of your distribution and then runpip install xrd-viewerthen start the program by runningxrd-viewerUsageOnce you opened the program, you will be greeted by the default interface with an logo on the top plot and an empty plot on the bottom.The (optional) first step is toload a mask fileviaFile > Load Mask...After file selection a preview of the mask file is presented on the upper plot. The program adds an automatic correction of the borders of the detector chips to the mask (hard coded factor of 0.4 will change in the future). The mask can not be unloaded. So please restart the program for a empty mask.ThenFile > Open...thefolder of the measurements. It will list all measurement files in the list on the left. There you can select one or multiple files to analyse. If you select mutiple, only one can be visualized on the top plot. The name of this file is visible in the window title bar of the program.After selection of the measurement file theanalysis ploton the bottom gets updated. You can select which attributes to assign to each axis. The possible attributes are exctracted from the measurement file. There are two special attributes added:xpad_imageandslices. Thexpad_imagecorresponds to the region of interest (see below) andslicescorresponds to the scan frame in the measurement (slider on the top of the upper plot).\nThe typical setting isomegavsxpad_image.Theregion of interest(ROI) can be selected in the upper plot window. Click theEdit regions...button to open the extended region editor. By default it has two regions. The first region is the background region and all regions afterwards are ROIs. By default the second region (= the first ROI) is the active region. The active region is displayed as red rectangle and can be manipulated by moving the edges to the desired positions. The region editor can also be used to refine the region (values are in pixels). A new ROI can be added byNew Regionbutton.Tips for analysis of measurementsIf the background region should not be applied. You can move it to the upper left corner with an width and length of 1. (In this corner is typically a shadow in the measurements, so zero counts.)You can move the cursor in the bottom plot my draging the mouse. The upper plot gets updated. This also sets the focus on the frame slider, so you can move the cursor by pressing left and right.Typically the first frames of a measurement are corrupted, you can set an value in the bottom input box to ignore them.After selecting a measurementFile > Save Graph...becomes enabled. You can save the current analysis plot as image in*.JPG,*.PNGor*.PDFformat (the cursor and indicator will be removed) or as plain text*.TXTfor further analysis. The plain text file will have some metadata about the measurement file, the mask file and the selected regions."} +{"package": "xrd-xy-parser", "pacakge-description": "xrd-xy-parserxrd-xy-parser is parser of xy file from X-ray diffraction.Python ver >= 3.10installationpipinstallxrd-xy-parserorpip3installxrd-xy-parserhow to usefromxrd_xy_parserimportxyif__name__==\"__main__\":try:header,body,footer=xy.readstr(\"examples/example.xy\")print(\"header:{}\\n\"\"body:{}\\n\"\"footer:{}\\n\".format(header,body,footer))'''header:<301.15K>Wavelength = 1.54059body:array([[30. , 1. ],[30.01, 1. ],[30.02, 3. ],...,[49.97, 3. ],[49.98, 1. ],[49.99, 0. ]])footer:\"\"'''exceptxy.ParseErrorase:print(e)getting 2\u03b8,Intensity column# 2\u03b8 columnprint(body[:,0])# array([30. , 30.01, 30.02, ..., 49.97, 49.98, 49.99])# Intensity columnprint(body[:,1])# array([1., 1., 3., ..., 3., 1., 0.])or read2xytry:xy=read2xy(\"examples/example.xy\")print(xy)# x:array([30. , 30.01, 30.02, ..., 49.97, 49.98,])# y:array([1., 1., 3., ..., 3., 1., 0.])exceptxy.ParseErrorase:print(e)functionxy.read(str)xy.read(Pathlib.Path)xy.read(TextIOBase)read xy data fromstr,PathorTextIOBase,return tuple (header, body, footer).xy.read2xy(str)xy.read2xy(Pathlib.Path)xy.read2xy(TextIOBase)read xy data fromstr,PathorTextIOBase,return xrdXY object.classxrdXYattributex: np.ndarrayy: np.ndarrayxy file structurexy file is not explicitly specified.xy file consists fromheader,body,footerparts.headerincludes some infomation,bodyis float list.footeris empty or consists from\\s,\\t,\\r\\n,\\n.<301.15K> \\\\header\nWavelength = 1.54059 \\\\header\n26.78\t11598.00 \\\\body\n26.8\t10786.00\n26.82\t5768.00\n26.84\t1149.00\n26.86\t255.00\n26.88\t74.00\n26.9\t52.00\n26.92\t30.00\n26.94\t19.00 \\\\body\n\\\\ footer"} +{"package": "xre", "pacakge-description": "xreBuild regex like legos.One to two paragraph statement about your product and what it does.InstallationOS X & Linux:Clone the repository:gitclonehttps://github.com/polyrand/setDNS.gitRun:chmod+xsetdns.py\n./setdns.pyDevelopment setupDependency management is done with pip-tools + venv (stdlib).Framework requirements are in requirements/main.in (main.txt are the pinned ones). Development and documentation requirements are in requirements/dev.in (main.txt are the pinned ones)DocumentationDocumentation is written in markdown using mkdocs. In order to work on it, run:mkdocsserveNow it will be available atlocalhost:8000.Usage exampleA few motivating and useful examples of how your product can be used. Spice this up with code blocks and potentially more screenshots.Release History0.2.1CHANGE: Update docs (module code remains unchanged)0.2.0CHANGE: RemovesetDefaultXYZ()ADD: Addinit()0.1.1FIX: Crash when callingbaz()(Thanks @GenerousContributorName!)0.1.0The first proper releaseCHANGE: Renamefoo()tobar()0.0.1Work in progressMetaRicardo Ander-Egg Aguilar \u2013@ricardoanderegg\u2013ricardoanderegg.comgithub.com/polyrandlinkedin.com/in/ricardoandereggDistributed under the XYZ license. SeeLICENSEfor more information.ContributingFork it (https://github.com/polyrand/yourproject/fork)Create your feature branch (git checkout -b feature/fooBar)Commit your changes (git commit -am 'Add some fooBar')Push to the branch (git push origin feature/fooBar)Create a new Pull Request"} +{"package": "xrea", "pacakge-description": "This package is simple implementation of XREA API(https://apidoc.xrea.com) wrapper with Python 3.\u201cXREA\u201d is the web hosting service in Japan.Short description in Japanese\u3053\u306ePython\u30d1\u30c3\u30b1\u30fc\u30b8\u306fXREA API(https://apidoc.xrea.com)\u306e\u30e9\u30c3\u30d1\u30fc\u3067\u3059\u3002\nPython3\u7cfb(3.4\u4ee5\u964d)\u3067\u4f7f\u3048\u307e\u3059\u3002Supported servicesXREA(https://www.xrea.com)CoreServer(https://www.coreserver.jp)Requirementsworks withPython 3.4+requestsInstallationvia pipenv$pipenvinstallxreavia pip$pipinstallxreavia setup.py$pythonsetup.pyinstallExamplesInit:>>>fromxreaimportXrea# for CoreServer: from xrea import CoreServer......account=\"foo\"# your account...server_name=\"z123456.xrea.com\"# your server...api_secret_key=\"zajxTrzkHBGkRRfvWs5w397jZFqQKC8L\"# your api_secret_key>>>xrea=Xrea(account=account,server_name=server_name,api_secret_key=api_secret_key)# for CoreServer\n# xrea = CoreServer(account=account, server_name=server_name, api_secret_key=api_secret_key)Call site/list without optional params:>>>response=xrea.site.list()>>>pprint(response.result){'1': {'domain': 'blank',\n 'ip': '11.22.33.44,\n 'no': 1,\n 'nodir': 0,\n 'phpver': 'php71',\n 'redirect_url': '',\n 'ssl_info': [],\n 'ssl_status': 0},\n '2': {'domain': 'abcde.example.info',\n 'ip': '11.22.33.44',\n 'no': 2,\n 'nodir': 0,\n 'phpver': 'php71',\n 'redirect_url': '',\n 'ssl_info': [],\n 'ssl_status': 1}}Call log/log_list with optional params:>>>response2=xrea.log.log_list(type='analog')>>>pprint(response2.result){'abcde.example.info': [{'filedate': '2018-01-14',\n 'filename': 'abcde.example.info.html'},\n {'filedate': '2018-01-13',\n 'filename': 'abcde.example.info.1.html'}]}Call aaa/bbb (not valid)>>>response3=xrea.aaa.bbb(foo='12345')xrea.error.XreaApiResponseError: [status: 404, error: 100002]page_name:\u6b63\u3057\u304f\u3042\u308a\u307e\u305b\u3093AuthorNAKAMORI Ryosuke-https://github.com/tpdnLicenceBSD-2-Clause"} +{"package": "xrecsys", "pacakge-description": "No description available on PyPI."} +{"package": "xregi", "pacakge-description": "This is a python package for registering x-ray images and CT scans. It is based on thexReg, a C++ library for medical image registration, andsynthex, a python package for synthetic x-ray imaging.Third-party librariesBefore you start, please make sure you have all the dependencies installed. The following libraries are required:Total SegmentatorxRegSyntheXInstall TotalSegmentatortotal segmentator can be installed through pippipinstallTotalSegmentatorInstall xRegxReg is a C++ library for medical image registration. It is used as the backend of xregi. To install xReg, please follow the instructions in theREADME.md of xregOn other environments, such as Windows, MacOS and Ubuntu\uff0cyou may need to install xreg aside according to your system. The detailed information can be found at theBuildingsection in the README.md of xreg.Install SyntheXSynthex will be installed along with xregi. If you want to install it separately, here is the installation for SyntheX:gitclonehttps://github.com/arcadelab/SyntheX.gitcd/SyntheX\ncondainstall.Xregi Installation GuideInstall through pipOn ubuntu 20.04, simply install this package using pippipinstallxregiInstall from sourceOn ubuntu 20.04, download the source code and install it under xregi pathgitclonehttps://github.com/shez12/xregi\ngitcheckoutmasterFetch the source data and example images fromhereor#download data.zipwget--load-cookies/tmp/cookies.txt\"https://docs.google.com/uc?export=download&confirm=$(wget--quiet--save-cookies/tmp/cookies.txt--keep-session-cookies--no-check-certificate'https://docs.google.com/uc?export=download&id=1wjrxNE6B0pX3IooGxwC_cjf4n8MhxU1p'-O-|sed-rn's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=1wjrxNE6B0pX3IooGxwC_cjf4n8MhxU1p\"-Odata.zip&&rm-rf/tmp/cookies.txt#unzip data.zipcdDownloads/\nunzipdata.zipUsageBefore using xregi, you need to move the data folder to xregi directory.mvdataxregi/xregi supports command line interactions and API. To use the API,importxregireg_=Registration2D3D().load()reg_.solve()...ContributorsJiaming (Jeremy) Zhang, MSE in Robotics, Johns Hopkins UniversityZhangcong She, MSE in Mechanical Engineering, Johns Hopkins UniversityBenjamin D. Killeen, PhD in Computer Science, Johns Hopkins University"} +{"package": "xregistration", "pacakge-description": "robust-registrationRobust astrometric registration and cross-match of astronomical catalogsThis code does robust (Bayesian) cross-matches of catalogs with potentially large astrometric errors.\nThe algorithm is described inTian et al. (2019).Thexregistrationmodule includes code that implements a catalog cross-match with astrometric errors. The algorithm uses a Bayesian approach to handle objects that do not\nexist in both catalogs. This version of the algorithm implements the \"ring\" algorithm, which subsets all pairs within an initial search radiusRinto overlapping rings. This approach allows it to find shifts that are much larger than the positional uncertainties in the catalogs. It is particularly appropriate for catalogs from Hubble Space Telescope and other small field telescopes that have potentially large astrometric errors. The code in thexregistration/estimation.pymodule also uses a simple annealing schedule for the astrometric uncertainty, the \u03c3 value, to improve convergence in the iteration.The Jupyter notebook demonstrates using the robust registration algorithm to cross-match catalogs with rotation and shift. The first part of this notebook tests the algorithm on simulated HST/ACS/WFC catalogs. The second part demonstrates the cross-registration of a real HST image with a large shift (from the HLA catalog) to the Gaia DR2 catalog of the same field. We also compare the robust estimation results with the results from the method of least-squares (Budav\u00e1ri & Lubow 2012).InstallationInstall this code using pip:pip install xregistrationReferencesTian, F., Budav\u00e1ri, T., Basu, A., Lubow, S.H., & White, R.L. (2019) Robust Registration of Astronomy Catalogs with Applications to the Hubble Space Telescope.The Astronomical Journal158, 191. doi:10.3847/1538-3881/ab3f38.Budav\u00e1ri, T., & Lubow, S.H. (2012) Catalog Matching with Astrometric Correction and its Application to the Hubble Legacy Archive.The Astrophysical Journal761, 188. doi:10.1088/0004-637X/761/2/188ModuleDescriptionxregistrationRobust cross-match moduledemo_robust_registration.ipynbJupyter notebook demo script"} +{"package": "xreload", "pacakge-description": "xreloadThis is Pypi-packaged version of Guido van Rossum originalxreload.pyscript:http://svn.python.org/projects/sandbox/trunk/xreload/It also re-use some changes to this code made on theplone.reloadpackage:https://github.com/plone/plone.reload/blob/master/plone/reload/xreload.pyLicenseNeither Guido's original code norplone.reloadcode has any specific license,\nso none is provided with this package.Usagefrom xreload import xreload\nxreload(sys.modules[__name__], new_annotations={'RELOADING': True})DevelopmentReleasing a new versionWith a valid~/.pypirc:edit version insetup.pypython setup.py sdisttwine upload dist/*git tag $version && git push && git push --tags"} +{"package": "xrely-lib-client", "pacakge-description": "client library for xrely platform. For more information please visit https://www.xrely.com"} +{"package": "xremap", "pacakge-description": "xremap-pythonGenerate an xremap config with a Python DSL.Installation$pipinstallxremapThis will installxremap-pythoncommand.Usage$xremap-pythonexample/config.py>config.yml\n$sudoxremapconfig.ymlLicenseThe gem is available as open source under the terms of theMIT License."} +{"package": "xremotebot", "pacakge-description": "UNKNOWN"} +{"package": "xremovebg", "pacakge-description": "Install Librarypypi$ pip3 install xremovebggithub$pipinstallgit+https://github.com/krypton-byte/removebgLibraryfromremovebgimportRemoveBgrb=RemoveBg()res=rb.upload('images.png')res.save('saved.png')Run server$python-mremovebg-p8000Command Linewithout session$python-mremovebg--file=3.jpg--json2>/dev/null{\"url\":\"https://o.remove.bg/downloads/47b11d7f-3157-4dea-88ba-a47632c348a2/3-removebg-preview.png\",\"filename\":\"3-removebg-preview.png\",\"width\":500,\"height\":500,\"foreground_type\":\"product\",\"rated\":false}save session$python-mremovebg--file=3.jpg--save-session=session--json2>/dev/null{\"url\":\"https://o.remove.bg/downloads/47b11d7f-3157-4dea-88ba-a47632c348a2/3-removebg-preview.png\",\"filename\":\"3-removebg-preview.png\",\"width\":500,\"height\":500,\"foreground_type\":\"product\",\"rated\":false}load session$python-mremovebg--file=3.jpg--load-session=session--json2>/dev/null{\"url\":\"https://o.remove.bg/downloads/47b11d7f-3157-4dea-88ba-a47632c348a2/3-removebg-preview.png\",\"filename\":\"3-removebg-preview.png\",\"width\":500,\"height\":500,\"foreground_type\":\"product\",\"rated\":false}get histories removebg$python-mremovebg--get-histories--json2>/dev/null[{\"url\":\"https://o.remove.bg/downloads/47b11d7f-3157-4dea-88ba-a47632c348a2/3-removebg-preview.png\",\"filename\":\"3-removebg-preview.png\",\"width\":500,\"height\":500,\"foreground_type\":\"product\",\"rated\":false}]"} +{"package": "xrenner", "pacakge-description": "No description available on PyPI."} +{"package": "xrennerjsonnlp", "pacakge-description": "Xrenner to JSON-NLP(C) 2019 byDamir Cavar,Oren Baldinger, Maanvitha Gongalla, Anurag Kumar, Murali Kammili, Boli FangBrought to you by theNLP-Lab.org!IntroductionXrennerwrapper forJSON-NLP.Xrennerspecializes in coreference and anaphora resolution, in a more highly annotated manner\nthan just a coreference chain.Required Dependency ParseXrenner requires aDependency ParseinCoNLL-Uformat.\nThis can come fromCoreNLP, or another parser that provides universal dependencies in [CoNNL-U] format.\nThere are two ways to accomplish this:CoreNLP ServerTheXrennerPipelineclass will take care of the details, however it requires an availableCoreNLPserver.\nThe easiest way to create one is withDocker:docker pull nlpbox/corenlp\ndocker run -p 9000:9000 -ti nlpbox/corenlpTo test this, open a new tab,wget -q --post-data \"Although they didn't like it, they accepted the offer.\" 'localhost:9000/?properties={\"annotators\":\"depparse\",\"outputFormat\":\"conll\"}' -O /dev/stdoutYou then need to create a.envfile in the root of the project, follow the example insample_env.\nThe default entry that corresponds to theDockercommand above is:CORENLP_SERVER=http://localhost:9000Provide your own CoNLL-UUse theXrennerPipeline.process_conllfunction, with your conll data passed as a string via\ntheconllargument.You may find thepyjsonnlp.conversion.to_conllufunction helpful for convertingJSON-NLP,\nmaybe fromspaCy, toCoNLL-U.MicroserviceTheJSON-NLPrepository provides a Microservice class, with a pre-built implementation ofFlask. To run it, execute:python xrennerjsonnlp/server.pySinceserver.pyextends theFlaskapp, a WSGI file would contain:from xrennerjsonnlp.server import app as applicationText is provided to the microservice with thetextparameter, via eitherGETorPOST. If you passurlas a parameter, the microservice will scrape that url and process the text of the website.Here is an exampleGETcall:http://localhost:5000?text=John went to the store. He bought some milk.Theprocess_conllendpoint mentioned above is available at the/process_conllURI. Instead of passingtext, passconll. A POST operation will be easier than GET\nin this situation."} +{"package": "xreq", "pacakge-description": "Example PackageThis is a simple example package. You can useGithub-flavored Markdownto write your content."} +{"package": "xrequests", "pacakge-description": "PyRequests:0.0.1>AdvancedCustomRequestModule|Usedinallmyprojects\"},conversation_id=None,parent_id=None)# You can start a custom conversationresponse=chatbot.ask(\"Prompt\",conversation_id=None,parent_id=None)# You can specify custom conversation and parent ids. Otherwise it uses the saved conversation (yes. conversations are automatically saved)print(response)# {# \"message\": message,# \"conversation_id\": self.conversation_id,# \"parent_id\": self.parent_id,# }Awesome ChatGPTMy listIf you have a cool project you want added to the list, open an issue.DisclaimersThis is not an official OpenAI product. This is a personal project and is not affiliated with OpenAI in any way. Don't sue meCreditsrawandahmad698- Reverse engineering Auth0FlorianREGAZ- TLS clientPyRo1121- LintingHarry-Jing- Async supportUkenn2112- Documentationaliferouss19- LogoAll other contributors"} +{"package": "xrfeitoria", "pacakge-description": "IntroductionXRFeitoria is a rendering toolbox for generating synthetic data photorealistic with ground-truth annotations.\nIt is a part of theOpenXRLabproject.https://github.com/openxrlab/xrfeitoria/assets/35397764/1e83bcd4-ae00-4c20-8188-3fe73f7c9c01Major FeaturesSupport rendering photorealistic images with ground-truth annotations.Support multiple engine backends, includingUnreal EngineandBlender.Support assets/camera management, including import, place, export, and delete.Support a CLI tool to render images from a mesh file.InstallationpipinstallxrfeitoriaRequirementsPython >= 3.8(optional)Unreal Engine >= 5.1WindowsLinuxMacOS(optional)Blender >= 3.0WindowsLinuxMacOSGet-StartedCLIxf-render--help# render a mesh filexf-render{mesh_file}# for examplewgethttps://graphics.stanford.edu/~mdfisher/Data/Meshes/bunny.obj\nxf-renderbunny.objhttps://github.com/openxrlab/xrfeitoria/assets/35397764/430a7264-9337-4327-838d-08e9a354c277https://github.com/openxrlab/xrfeitoria/assets/35397764/9c029eb7-a8be-4d11-890e-b2499ff22caaDocumentationThe reference documentation is available onreadthedocs.TutorialsThere are severaltutorials.\nYou can read themhere.Sample codesThere are severalsamples.\nPlease follow the instructionshere.Use plugins under developmentDetails can be foundhere.If you want to publish plugins of your own, you can use the following command:# install xrfeitoria firstcdxrfeitoriapipinstall.# for instance, build plugins for Blender, UE 5.1, UE 5.2, and UE 5.3 on Windows.# using powershell where backtick(`) is the line continuation character.python-mxrfeitoria.utils.publish_plugins`-u\"C:/Program Files/Epic Games/UE_5.1/Engine/Binaries/Win64/UnrealEditor-Cmd.exe\"`-u\"C:/Program Files/Epic Games/UE_5.2/Engine/Binaries/Win64/UnrealEditor-Cmd.exe\"`-u\"C:/Program Files/Epic Games/UE_5.3/Engine/Binaries/Win64/UnrealEditor-Cmd.exe\"Frequently Asked QuestionsPlease refer toFAQ.:rocket: Amazing Projects Using XRFeitoriaProjectTeaserEngineSynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and ModelingUnreal Engine / BlenderZolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh ReconstructionBlenderSHERF: Generalizable Human NeRF from a Single ImageBlenderMatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and BeyondUnreal EngineHumanLiff: Layer-wise 3D Human Generation with Diffusion ModelBlenderPrimDiffusion: Volumetric Primitives Diffusion for 3D Human GenerationBlenderLicenseThe license of our codebase is Apache-2.0. Note that this license only applies to code in our library, the dependencies of which are separate and individually licensed. We would like to pay tribute to open-source implementations to which we rely on. Please be aware that using the content of dependencies may affect the license of our codebase. Refer toLICENSEto view the full license.CitationIf you find this project useful in your research, please consider cite:@misc{xrfeitoria,title={OpenXRLab Synthetic Data Rendering Toolbox},author={XRFeitoria Contributors},howpublished={\\url{https://github.com/openxrlab/xrfeitoria}},year={2023}}Projects in OpenXRLabXRPrimer: OpenXRLab foundational library for XR-related algorithms.XRSLAM: OpenXRLab Visual-inertial SLAM Toolbox and Benchmark.XRSfM: OpenXRLab Structure-from-Motion Toolbox and Benchmark.XRLocalization: OpenXRLab Visual Localization Toolbox and Server.XRMoCap: OpenXRLab Multi-view Motion Capture Toolbox and Benchmark.XRMoGen: OpenXRLab Human Motion Generation Toolbox and Benchmark.XRNeRF: OpenXRLab Neural Radiance Field (NeRF) Toolbox and Benchmark.XRFeitoria: OpenXRLab Synthetic Data Rendering Toolbox."} +{"package": "xrff2csv", "pacakge-description": "A Python tool that converts XRFF files to CSV format.ContactIf you have any questions or comments about xrff2csv, please feel free to contact me via:E-mail:rso@randalolson.comor Twitter:https://twitter.com/randal_olsonThis project is hosted athttps://github.com/rhiever/xrff2csv"} +{"package": "xrfgui", "pacakge-description": "No description available on PyPI."} +{"package": "xrft", "pacakge-description": "xrftis an open-source Python package for\ntaking the discrete Fourier transform (DFT) onxarrayanddaskarrays.It is:Powerful: It keeps the metadata and coordinates of the original xarray dataset and provides a clean work flow of DFT.Easy-to-use: It uses the native arguments ofnumpy FFTand provides a simple, high-level API.Fast: It uses thedask API of FFTandmap_blocksto allow parallelization of DFT.Please cite thedoiif you find this\npackage useful in order to support its continuous development.Get in touchReport bugs, suggest features or view the source codeon GitHub."} +{"package": "xrf-tomo", "pacakge-description": "XRF Tomography ReconstructionInstallationThe software is expected to work with Python version 3.7-3.9. Create conda environment\nwith the preferable python version:$ conda create -n xrf-tomo-env python=3.8 -c conda-forge\n$ conda activate xrf-tomo-envtomopyandxraylib(dependency of PyXRF) are not available from PyPI and need\nto be installed fromconda-forge:$ conda install tomopy pyxrf -c conda-forgesvmbiris an optional dependency. Installsvmbirseparately if needed. Instructions\nare slightly different depending on OS. Linux:$ pip install svmbirOSX:$ ln -sf /usr/local/bin/gcc-10 /usr/local/bin/gcc\n$ CC=gcc pip install --no-binary svmbir svmbirWindows:$ CC=gcc pip install svmbirFinally install this package. From PyPI:$ pip install xrf-tomoFrom source (develop install). Clone the repository in the appropriate directory and\nthen install withpip:$ git clone https://github.com/NSLS-II-SRX/xrf-tomo\n$ cd xrf-tomo\n$ pip install -e .Using the packageActivate the environment:$ conda activate xrf-tomo-envIn IPython environment or a script import necessary or all functions from the package, e.g.from xrf_tomo import *"} +{"package": "xri", "pacakge-description": "XRIXRI is a small Python library for efficient and RFC-correct representation of URIs and IRIs.\nIt is currently work-in-progress and, as such, is not recommended for production environments.The generic syntax for URIs is defined inRFC 3986.\nThis is extended in the IRI specification,RFC 3987, to support extended characters outside of the ASCII range.\nTheURIandIRItypes defined in this library implement those definitions and store their constituent parts asbytesorstrvalues respectively.Creating a URI or IRITo get started, simply pass a string value into theURIorIRIconstructor.\nThese can both accept eitherbytesorstrvalues, and will encode or decode UTF-8 values as required.>>> from xri import URI\n>>> uri = URI(\"http://alice@example.com/a/b/c?q=x#z\")\n>>> uri\n\n>>> uri.scheme = \"https\"\n>>> print(uri)\nhttps://alice@example.com/a/b/c?q=x#zComponent partsEachURIorIRIobject is fully mutable, allowing any component parts to be get, set, or deleted.\nThe following component parts are available:URI/IRIobject.scheme(None or string).authority(None orAuthorityobject).userinfo(None or string).host(string).port(None, string or int).path(Pathobject - can be used as an iterable of segment strings).query(None orQueryobject).fragment(None or string)(The type \"string\" here refers tobytesorbytearrayforURIobjects, andstrforIRIobjects.)Percent encoding and decodingEach of theURIandIRIclasses has class methods calledpct_encodeandpct_decode.\nThese operate slightly differently, depending on the base class, as a slightly different set of characters are kept \"safe\" during encoding.>>>URI.pct_encode(\"abc/def\")'abc%2Fdef'>>>URI.pct_encode(\"abc/def\",safe=\"/\")'abc/def'>>>URI.pct_encode(\"20% of $125 is $25\")'20%25%20of%20%24125%20is%20%2425'>>>URI.pct_encode(\"20% of \u00a3125 is \u00a325\")# '\u00a3' is encoded with UTF-8'20%25%20of%20%C2%A3125%20is%20%C2%A325'>>>IRI.pct_encode(\"20% of \u00a3125 is \u00a325\")# '\u00a3' is safe within an IRI'20%25%20of%20\u00a3125%20is%20\u00a325'>>>URI.pct_decode('20%25%20of%20%C2%A3125%20is%20%C2%A325')# str in, str out (using UTF-8)'20% of \u00a3125 is \u00a325'>>>URI.pct_decode(b'20%25%20of%20%C2%A3125%20is%20%C2%A325')# bytes in, bytes out (no UTF-8)b'20% of\\xc2\\xa3125 is\\xc2\\xa325'Safe characters (passed in via thesafeargument) can only be drawn from the set below.\nOther characters passed to this argument will give aValueError.! # $ & ' ( ) * + , / : ; = ? @ [ ]Advantages over built-inurllib.parsemoduleCorrect handling of character encodingsRFC 3986 specifies that extended characters (beyond the ASCII range) are not supported directly within URIs.\nWhen used, these should always be encoded with UTF-8 before percent encoding.\nIRIs (defined in RFC 3987) do however allow such characters.urllib.parsedoes not enforce this behaviour according to the RFCs, and does not support UTF-8 encoded bytes as input values.>>>urlparse(\"https://example.com/\u00e4\").path'/\u00e4'>>>urlparse(\"https://example.com/\u00e4\".encode(\"utf-8\")).pathUnicodeDecodeError:'ascii'codeccan't decode byte 0xc3 in position 20: ordinal not in range(128)Conversely,xrihandles these scenarios correctly according to the RFCs.>>>URI(\"https://example.com/\u00e4\").pathURI.Path(b'/%C3%A4')>>>URI(\"https://example.com/\u00e4\".encode(\"utf-8\")).pathURI.Path(b'/%C3%A4')>>>IRI(\"https://example.com/\u00e4\").pathIRI.Path('/\u00e4')>>>IRI(\"https://example.com/\u00e4\".encode(\"utf-8\")).pathIRI.Path('/\u00e4')Optional components may be emptyOptional URI components, such asqueryandfragmentare allowed to be present but empty,according to RFC 3986.\nAs such, there is a semantic difference between an empty component and a missing component.\nWhen composed, this will be denoted by the absence or presence of a marker character ('?'in the case of the query component).Theurlparsefunction does not distinguish between empty and missing components;\nboth are treated as \"missing\".>>>urlparse(\"https://example.com/a\").geturl()'https://example.com/a'>>>urlparse(\"https://example.com/a?\").geturl()'https://example.com/a'xri, on the other hand, correctly distinguishes between these cases:>>>str(URI(\"https://example.com/a\"))'https://example.com/a'>>>str(URI(\"https://example.com/a?\"))'https://example.com/a?'"} +{"package": "xripl", "pacakge-description": "XRIPLXRIPL (C22023): X-Ray Radiographic Image Processing LibraryPawel M. Kozlowski 2018-10-19XRIPL (read as \"zripple\") is a library of tools for processing x-ray\nradiographs and extracting contours of interest within the image using\ncomputer vision techniques. Features include spatial calibration, denoising,\nbackground and attenuation correction through pseudo-flatfielding, watershed\nsegmentation, contour processing, and visualization. The details of the XRIPL\nanalysis pipeline are published in the Proceedings of the 23rd Topical\nConference on High-Temperature Plasma Diagnostics Proceedings [1].[1] P. M. Kozlowski, Y. Kim, B. M. Haines, H. F. Robey, T. J. Murphy,\nH. M. Johns, and T. S. Perry. Use of Computer Vision for analysis of image\ndata sets from high temperature plasma experiments. Review of Scientific\nInstruments 92, 033532 (2021)https://doi.org/10.1063/5.0040285InstallationOfficial releases of XRIPLare published to pypi.org and can simply be pip installed like so:pip install xriplMore detailed installation instructions can be foundhere.LicenseXRIPL is released under a3-clause BSD license.Citing XRIPLIf you use XRIPL in your work, please follow the best practices for citing\nXRIPL which can be foundhere.AcknowledgementsDevelopment of Fiducia was supported by the U.S. Department of Energy, and\nthe NNSA."} +{"package": "xrit", "pacakge-description": "xRIT Parser Toolkit======================A toolkit to parse / dump HRIT / LRIT files.### xritparseParses xRIT file Header and print in a human readable format.```Usage:xritparse [-hi] filen.lrit [file2.lrit]-h Print Structured Header Record-i Print Image Data Record```##### Example:```# xritparse DCSdat363042229684.lritParsing file DCSdat363042229684.lritPrimary Header:File Type Code: DCSHeader Length: 89Data Field Length: 1617088NOAA Specific HeaderSignature: NOAAProduct ID: DCSProduct SubId: NoneParameter: 11500Compression: Not CompressedAnnotation RecordFilename: DCSdat363042229684.lritTimestamp RecordDateTime: 2016-12-28 04:22:00DCS Filename:Filename: pL-16363042229-A.dcs```### xritdumpDumps the data section of a HRIT/LRIT file.PS: This does not convert or process anything. It just saves the data section.```Usage:xritdump filename.lrit output.bin```### xritcatReads the data section of a HRIT/LRIT file and prints to stdout.```Usage:xritcat filename.lrit```## Python LibraryThis also can be used as a python library by importing `xrit`. The documentation is still WIP. Please us the module executables as a reference.## InstallingThe package is available at `pip`. Just run:```sudo pip install xrit```"} +{"package": "xrmap", "pacakge-description": "Plot xarrays lat-lon datasets using folium"} +{"package": "xrmath", "pacakge-description": "No description available on PyPI."} +{"package": "xrmocap", "pacakge-description": "IntroductionEnglish |\u7b80\u4f53\u4e2d\u6587XRMoCap is an open-source PyTorch-based codebase for the use of multi-view motion capture. It is a part of theOpenXRLabproject.If you are interested in single-view motion capture, please refer tommhuman3dfor more details.https://user-images.githubusercontent.com/26729379/187710195-ba4660ce-c736-4820-8450-104f82e5cc99.mp4A detailed introduction can be found inintroduction.md.Major FeaturesSupport popular multi-view motion capture methods for single person and multiple peopleXRMoCap reimplements SOTA multi-view motion capture methods, ranging from single person to multiple people. It supports an arbitrary number of calibrated cameras greater than 2, and provides effective strategies to automatically select cameras.Support keypoint-based and parametric human model-based multi-view motion capture algorithmsXRMoCap supports two mainstream motion representations, keypoints3d and SMPL(-X) model, and provides tools for conversion and optimization between them.Integrate optimization-based and learning-based methods into one modular frameworkXRMoCap decomposes the framework into several components, based on which optimization-based and learning-based methods are integrated into one framework. Users can easily prototype a customized multi-view mocap pipeline by choosing different components in configs.News2022-12-21: XRMoCapv0.7.0is released. Major updates include:Addmview_mperson_end2end_estimatorfor learning-based methodAdd SMPLX support and allow smpl_data initiation inmview_sperson_smpl_estimatorAdd multiple optimizers, detailed joint weights and priors, grad clipping for better SMPLify resultsAddmediapipe_estimatorfor human keypoints2d perception2022-10-14: XRMoCapv0.6.0is released. Major updates include:Add4D Association Graph, the first Python implementation to reproduce this algorithmAdd Multi-view multi-person top-down smpl estimationAdd reprojection error point selector2022-09-01: XRMoCapv0.5.0is released. Major updates include:SupportHuMMan Mocaptoolchain for multi-view single person SMPL estimationReproduceMvP, a deep-learning-based SOTA for multi-view multi-human 3D pose estimationReproduceMVPose (single frame)andMVPose (temporal tracking and filtering), two optimization-based methods for multi-view multi-human 3D pose estimationSupport SMPLify, SMPLifyX, SMPLifyD and SMPLifyXDBenchmarkMore details can be found inbenchmark.md.Supported methods:(click to collapse)SMPLify(ECCV'2016)SMPLify-X(CVPR'2019)MVPose (Single frame)(CVPR'2019)MVPose (Temporal tracking and filtering)(T-PAMI'2021)Shape-aware 3D Pose Optimization(ICCV'2019)MvP(NeurIPS'2021)HuMMan MoCap(ECCV'2022)4D Association Graph(CVPR'2020)Supported datasets:(click to collapse)Campus(CVPR'2014)Shelf(CVPR'2014)CMU Panoptic(ICCV'2015)4D Association(CVPR'2020)Getting StartedPlease seegetting_started.mdfor the basic usage of XRMoCap.LicenseThe license of our codebase is Apache-2.0. Note that this license only applies to code in our library, the dependencies of which are separate and individually licensed. We would like to pay tribute to open-source implementations to which we rely on. Please be aware that using the content of dependencies may affect the license of our codebase. Refer toLICENSEto view the full license.CitationIf you find this project useful in your research, please consider cite:@misc{xrmocap,title={OpenXRLab Multi-view Motion Capture Toolbox and Benchmark},author={XRMoCap Contributors},howpublished={\\url{https://github.com/openxrlab/xrmocap}},year={2022}}ContributingWe appreciate all contributions to improve XRMoCap. Please refer toCONTRIBUTING.mdfor the contributing guideline.AcknowledgementXRMoCap is an open source project that is contributed by researchers and engineers from both the academia and the industry.\nWe appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.\nWe wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models.Projects in OpenXRLabXRPrimer: OpenXRLab foundational library for XR-related algorithms.XRSLAM: OpenXRLab Visual-inertial SLAM Toolbox and Benchmark.XRSfM: OpenXRLab Structure-from-Motion Toolbox and Benchmark.XRLocalization: OpenXRLab Visual Localization Toolbox and Server.XRMoCap: OpenXRLab Multi-view Motion Capture Toolbox and Benchmark.XRMoGen: OpenXRLab Human Motion Generation Toolbox and Benchmark.XRNeRF: OpenXRLab Neural Radiance Field (NeRF) Toolbox and Benchmark."} +{"package": "xrmreader", "pacakge-description": "Reading and preprocessing x-ray projection data in Zeiss .txrm formatThis package extends thedxchange readerto read the Zeiss proprietary data format .txrm to python lists or arrays. In particular, the import of metadata from the file headers is extended to access information needed for reconstructing x-ray projection data, e.g. acquired on Zeiss x-ray microscopes. Further, the package contains some simple functions to preprocess x-ray projections in preparation for reconstruction. These include flat field correction, revision of detector shifts, downsampling, conversion into line integral domain and truncation correction.For installation, please runcondainstall-cconda-forgedxchange\npipinstallxrmreaderThis example code usespyconradfor visualization.importxrmreaderimportpyconrad.autoinitfromedu.stanford.rsl.conrad.data.numericimportNumericGridprojection_data=r'your_file.txrm'metadata=xrmreader.read_metadata(projection_data)print(metadata)# load raw dataraw_projections=xrmreader.read_txrm(projection_data)NumericGrid.from_numpy(raw_projections).show('Raw projections')# preprocess data in individual stepsprojections=xrmreader.read_txrm(projection_data)projections=xrmreader.divide_by_reference(projections,metadata['reference'])projections=xrmreader.revert_shifts(projections,metadata['x-shifts'],metadata['y-shifts'])projections=xrmreader.downsample(projections,spatial_factor=2)projections=xrmreader.negative_logarithm(projections)projections=xrmreader.truncation_correction(projections)NumericGrid.from_numpy(projections).show('Preprocessed projections version 1')# load and preprocess data in one step (this does the same thing as the individual steps above, but needs less memory)preprocessed_projections=xrmreader.read_and_preprocess_txrm(projection_data)NumericGrid.from_numpy(preprocessed_projections).show('Preprocessed projections version 2')CopyrightAs the reading functionality is modified from the dxchange project by De Carlo et al.\n(https://github.com/data-exchange/dxchange), we reproduce their copyright notice.Copyright (c) 2016, UChicago Argonne, LLC. All rights reserved.Copyright 2016. UChicago Argonne, LLC. This software was produced\nunder U.S. Government contract DE-AC02-06CH11357 for Argonne National\nLaboratory (ANL), which is operated by UChicago Argonne, LLC for the\nU.S. Department of Energy. The U.S. Government has rights to use,\nreproduce, and distribute this software. NEITHER THE GOVERNMENT NOR\nUChicago Argonne, LLC MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR\nASSUMES ANY LIABILITY FOR THE USE OF THIS SOFTWARE. If software is\nmodified to produce derivative works, such modified software should\nbe clearly marked, so as not to confuse it with the version available\nfrom ANL.Additionally, redistribution and use in source and binary forms, with\nor without modification, are permitted provided that the following\nconditions are met:Redistributions of source code must retain the above copyright\nnotice, this list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright\nnotice, this list of conditions and the following disclaimer in\nthe documentation and/or other materials provided with the\ndistribution.Neither the name of UChicago Argonne, LLC, Argonne National\nLaboratory, ANL, the U.S. Government, nor the names of its\ncontributors may be used to endorse or promote products derived\nfrom this software without specific prior written permission.THIS SOFTWARE IS PROVIDED BY UChicago Argonne, LLC AND CONTRIBUTORS\n\"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\nLIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS\nFOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL UChicago\nArgonne, LLC OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,\nINCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,\nBUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;\nLOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT\nLIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN\nANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE\nPOSSIBILITY OF SUCH DAMAGE.For the rest of the code, this applies.Copyright (c) 2021 Mareike ThiesPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xrnn", "pacakge-description": "EXtremely Rapid Neural Networks (xrnn)Is a Python machine learning framework for building layers and neural networks\nby exposing an easy-to-use interface for building neural networks as a series of layers, similar toKeras, while being as lightweight, fast, compatible and extendable as possible.Table of ContentsThe advantages of this package over existing machine learning frameworksInstallationExamplesFeaturesBuilding from SourceCurrent Design LimitationsProject StatusLicenseThe advantages of this package over existing machine learning frameworksWorks on any Python version 3.6(released in 2016)and above.Requires only one dependency, which is Numpy(you most likely already have it).Lightweight in terms of size.Very fast startup time, which is the main version behind developing this project, meaning that importing the package,\nbuilding a network and straiting training takes less than a second (compared toTensorflowfor example which can take more than 10 seconds).High performance even on weak hardware, reached 72% validation accuracy on MNIST dataset using a CNN on a 2 core 2.7 GHZ cpu (i7-7500U) in 25 seconds.Memory efficient, uses less RAM than Tensorflow(~25% less)for a full CNN training/inference pipeline.Compatibility, there's no OS specific code (OS and hardware independent), so the package can pretty much be built and run on any platform that has python >= 3.6 and any C/C++ compiler that has come out in the last 20 years.InstallationSimply run the following command:pip install xrnnNotethat the pre-built wheels are only provided for windows at the moment, if you want to install the package on other platforms\nseeBuilding From Source.ExamplesThis example will show how to build a CNN for classification, add layers to it, train it on dummy data, validate it and\nuse it for inference.importnumpyasnp# Create a dummy dataset, which contains 1000 images, where each image is 28 pixels in height and width and has 3 channels.number_of_sample=1000height=28width=28channels=3number_of_classes=9# How many classes are in the dataset, for e.g. cat, car, dog, etc.x_dummy=np.random.random((number_of_sample,height,width,channels))y_dummy=np.random.randint(number_of_classes,size=(number_of_sample,))# Build the network.batch_size=64# How many samples are in each batch (slice) of the data.epochs=2# How many full iterations over the dataset to train the network for.fromxrnn.modelimportModel# The neural network blueprint (houses the layers)fromxrnn.layersimportConv2D,BatchNormalization,Flatten,Dense,MaxPooling2Dfromxrnn.activationsimportReLU,Softmaxfromxrnn.lossesimportCategoricalCrossentropy# This loss is used for classification problems.fromxrnn.optimizersimportAdammodel=Model()model.add(Conv2D(16,3,2,'same'))model.add(ReLU())model.add(BatchNormalization())model.add(MaxPooling2D(2,2,'same'))model.add(Flatten())model.add(Dense(100))model.add(ReLU())model.add(Dense(9))# The output layer, has the same number of neurons as the number of unique classes in the dataset.model.add(Softmax())model.set(Adam(),CategoricalCrossentropy())model.train(x_dummy,y_dummy,epochs=epochs,batch_size=batch_size,validation_split=0.1)# Use 10% of the data for validation.x_dummy_predict=np.random.random((batch_size,height,width,channels))prediction=model.inference(x_dummy_predict)# Same as model.predict(x_dummy_predict).And that's it! You've built, trained and validated a convolutional neural network in just a few lines. It's true that the data is random\ntherefor the model isn't going to learn, but this demonstrates how to use the package, just replace 'x_dummy' and 'y_dummy' with\nactual data and see how the magic happens!Featuresxrnn.layers: Implements Conv2D, Dropout, Dense, Max/AvgPool2D, Flatten and BatchNormalization layers.xrnn.optimizers: Implements Adam, SGD (with momentum support), RMSprop and Adagrad optimizers.xrnn.losees: Implements BinaryCrossentropy, CategoricalCrossentropy and MeanSquaredError (MSE) loss functions.xrnn.activations: Implements ReLU, LeakyReLU, Softmax, Sigmoid and Tanh activation functions.xrnn.models: Implements theModelclass, which is similar to KerasSequentialmodel.\nand can be used to build, train, validate and use (inference) a neural network.For more information on how to use each feature (like theModelclass), look at said feature docstring (for examplehelp(Conv2D.forward)).\nNonetheless, if you are acquainted with Keras, it's pretty easy to get started with this package because it hasalmostthe same interface as Keras, the only notable difference is that kerasmodel.fitis equivalent tomodel.trainin this package.Building From SourceIf you want to use the package on platform that doesn't have a pre-built wheel (which is only available for windows atm) follow these steps:clone the GitHub repository.navigate to the source tree where the .py and .cpp files reside.Open the terminal.Create a new folder calledlib.Compile the source files viag++ -shared -o lib/c_layers layers_f.cpp layers_d.cpp -Ofast -fopenmp -fPICNavigate pack to the main directory (where pyproject.toml and setup.py reside).Runpython -m build -w. If you don't havebuildinstalled, runpip install buildbefore running the previous command.Runpip install dist/THE_WHEEL_NAME.whlAnd that's it! You can check the installation by running the following commandpip listand checking to see ofxrnnis in there.You can ignore any warnings raised during the build process is long as it's successful.A notefor compiling on windows: If you want to compile the package on windows (for some reason since pre-built wheels are already provided)\nand you are using MSVC compiler, the C source files (layer_f and layers_d) must have the .cpp extension, so they are treated as C++ source files\nbecause for some reason, compiling them as C source files (happens when they have .c extension) with openmp support doesn't work, but renaming the\nfiles to have .cpp extension (so they are treated as C++ source files) magically solves the problem, even when the source code is unchanged.\nAnywayit's strongly recommendedto useTDM-GCCon windows (which was used to build the windows wheel) because it doesn't have this problem and results\nin a faster executable (~15% faster). So the whole reason for having the files as C++ source files is for compatibility with Microsoft's compiler,\notherwise they would've been writen directly in C with no support when they are treated as C++ files (preprocessor directives and extern \"C\") because\nthe code for the layers is written in C, so it can be called from Python using ctypes.Current Design LimitationsThe current design philosophy is compatibility, being able to port/build this package on any OS or hardware, so only\nnative Python/C code is used with no dependence on any third party libraries (except for numpy), this is great for\ncompatibility but not so for performance, because the usage of optimized libraries likeEigen,Intel's oneDNNorcudais prohibited, which in turn makes this machine learning framework unusable for large datasets and big models.Project StatusThis project is completed and currently no hold. I might be picking it up and the future and adding the following features to it:Add Support for Cuda.Optimize CPU performance to match the mature frameworks like Pytorch and Tensorflow.Add support for automatic differentiation to make building custom layers easier.Add more layer implementation, mainly recurrent, attention and other convolution (transpose, separable) layers.Add support for multiple inputs/outputs to the layers and models.While keeping with the core vision of the project, which is to make as easy to install, compatible with all platforms and extendable as possibleLicenseThis project is licensed under theMIT license."} +{"package": "xrocket", "pacakge-description": "xRocketxRocket Python SDK.DescriptionPay and Trading xRocket API.Getting StartedDependencieshttpxInstallingpip install xrocketUsing PayAPIimportasynciofromxrocketimportPayAPIasyncdefmain():api=PayAPI(api_key='your api key here')cheque=awaitapi.cheque_create(currency='BOLT',amount=1,enable_captcha=False)awaitapi.cheque_delete(cheque['data']['id'])invoice=awaitapi.invoice_create(currency='BOLT',amount=1)awaitapi.invoice_delete(invoice_id=invoice['data']['id'])awaitapi.transfer(user_id=6037851294,currency='TONCOIN',amount=0.1)awaitapi.withdrawal(network='TON',currency='TONCOIN',amount=0.1,address='EQAsl59qOy9C2XL5452lGbHU9bI3l4lhRaopeNZ82NRK8nlA')asyncio.run(main())Using TradeAPIimportasynciofromxrocketimportTradeAPIasyncdefmain():api=TradeAPI(api_key='your api key here')balance=awaitapi.balance()print(balance)awaitapi.order_execute(pair='BOLT-TONCOIN',order_type='BUY',execute_type='LIMIT',rate=0.02,amount=5,currency='BOLT')price=awaitapi.rates_crypto_in_fiat(crypto='BOLT',fiat='USD')print(f\"1 BOLT ={price['data']['rate']}USD\")asyncio.run(main())Authors@shibdev@VladPavlyVersion History0.2.1Added testnet support0.2.0Additions0.1.0Initial versionLicenseThis project is licensed under the MIT License - see the LICENSE.md file for detailsDonateIf you like the library, I will be glad to accept donations.TON: EQCgphx8rTI0PukwmgpVqiPgqguTujhQscg2h7jgc4U0t347Acknowledgmentsxrocket-pay-docsxrocket-trade-docs"} +{"package": "xroms", "pacakge-description": "xromsxromscontains functions for commonly used scripts for working with ROMS output in xarray.There are functions to...help read in model output with automatically-calculated z coordinatescalculate many derived variables with correct grid metrics in one line including:horizontal speedkinetic energyeddy kinetic energyvertical shearvertical vorticityhorizontal divergencenormalized surface divergenceErtel potential vorticitydensity as calculated in ROMSpotential densitybuoyancy$N^2$ (buoyancy frequency/vertical buoyancy gradient)$M^2$ (horizontal buoyancy gradient)useful functions including:derivatives in all dimensions, accounting for curvilinear grids and sigma layersgrid metrics (i.e., grid lengths, areas, and volumes)subset horizontal grid such that the staggered grids are consistenteasily change horizontal and vertical grids usingxgcmgrid objectseasily reorder to dimensional conventionslice along a fixed valuewrapper for interpolation in longitude/latitude and for fixed depthsmixed-layer depthDemonstrations:selecting data in many different waysinterpolationchanging time samplingcalculating climatologiesvarious calculationsprovide/track attributes and coordinates through functionswrapscf-xarrayto generalize coordinate and dimension calling.ability to automatically choose colormaps for plotting withxarraywrapsxcmoceanfor thisInstallationYou need to havecondainstalled for these installation instructions. You'll have best results if you use the channelconda-forge, which you can prioritize withconda config --add channels conda-forge --force.Install, the easy wayPyPI:pip install xromsconda-forge:mamba install -c conda-forge xromsCreate environment if neededAs a first step, you can create an environment for this package with conda if you want. If you do this, you'll need to git clone the package first as below. Note thatmambaandcondacan be used interchangeably, butmambais faster for installation.mamba env create -f environment.ymlYou can choose to install with conda the optional dependencies for full functionality:conda install --file requirements-opt.txtand to install optional dependencyxcmocean:pip install git+git://github.com/pangeo-data/xcmoceanThen choose one of the following to installxromsfrom GitHub:Clonexromsinto a particular directory then install so that it is editable (-e)git clone git@github.com:xoceanmodel/xroms.git\ncd xroms\npip install -e .Directly installxromsfrom githubpip install git+git://github.com/xoceanmodel/xroms"} +{"package": "xron", "pacakge-description": "Xron (\u02c8kair\u0251n) is a methylation basecaller that could identify m6A methylation modification from ONT direct RNA sequencing.Using a deep learning CNN+RNN+CTC structure to establish end-to-end basecalling for the nanopore sequencer.The name is inherited fromChironBuilt withPyTorchand python 3.8+m6A-aware RNA basecall one-liner:xron call -i -o -m models/ENEYFT --boostnanoTable of contentsTable of contentsInstallInstall from SourceInstall from PypiBasecallSegmentation using NHMMPrepare chunk datasetRealign the signal using NHMM.TrainingInstallFor either installation method, recommend to create a vritual environment first using conda or venv, take conda for examplecondacreate--nameYOUR_VIRTUAL_ENVIRONMENTpython=3.8\ncondaactivateYOUR_VIRTUAL_ENVIRONMENTThen you can install from our pypi repository or install the newest version from github repository.InstallpipinstallxronXron requires at least PyTorch 1.11.0 to be installed. If you have not yet installed PyTorch, install it via guide fromofficial repository.BasecallBefore running basecall using Xron, you need to download the models from our AWS s3 bucket by runningxron initxroninitThis will automatically download the models and put them into themodelsfolder.\nWe provided sample code in xron-samples folder to achieve m6A-aware basecall and identify m6A site.\nTo run xron on raw fast5 files:xron call -i ${INPUT_FAST5} -o ${OUTPUT} -m models/ENEYFT --fast5 --beam 50 --chunk_len 2000Segmentation using NHMMPrepare chunk datasetXron also include a non-homegeneous HMM (NHMM) for signal re-sqquigle. To use it:\nFirstly we need to extract the chunk and basecalled sequence usingpreparemodulexronprepare-i${FAST5_FOLDER}-o${CHUNK_FOLDER}--extract_seq--basecallerguppy--reference${REFERENCE}--moderna_meth--extract_kmer-k5--chunk_len4000--write_correctionReplace the FAST5_FOLDER, CHUNK_FOLDER and REFERENCE with your basecalled fast5 file folder, your output folder and the path to the reference genome fasta file.Realign the signal using NHMM.Then run the NHMM to realign (\"resquiggle\") the signal.xronrelabel-i${CHUNK_FOLDER}-m${MODEL}--device$DEVICEThis will generate a paths.py file under CHUNK_FOLDER which gives the kmer segmentation of the chunks.TrainingTo train a new Xron model using your own dataset, you need to prepare your own training dataset, the dataset should includes a signal file (chunks.npy), labelled sequences (seqs.npy) and sequence length for each read (seq_lens.npy), and then run the xron supervised training modulexrontrain-ichunks.npy--seqseqs.npy--seq_lenseq_lens.npy--model_folderOUTPUT_MODEL_FOLDERTraining Xron model from scratch is hard, I would recommend to fine-tune our model by specify --load flag, for example we can finetune the provided ENEYFT model (model trained using cross-linked ENE dataset and finetuned on Yeast dataset):xrontrain-ichunks.npy--seqseqs.npy--seq_lenseq_lens.npy--model_foldermodels/ENEYFT--load"} +{"package": "xrootd", "pacakge-description": "XRootD: eXtended ROOT DaemonTheXRootDproject provides a high-performance,\nfault-tolerant, and secure solution for handling massive amounts of data\ndistributed across multiple storage resources, such as disk servers, tape\nlibraries, and remote sites. It enables efficient data access and movement in a\ntransparent and uniform manner, regardless of the underlying storage technology\nor location. It was initially developed by the High Energy Physics (HEP)\ncommunity to meet the data storage and access requirements of the BaBar\nexperiment at SLAC and later extended to meet the needs of experiments at the\nLarge Hadron Collider (LHC) at CERN. XRootD is the core technology powering theEOSdistributed filesystem, which is the storage\nsolution used by LHC experiments and the storage backend forCERNBox. XRootD is also used as the core\ntechnology for global CDN deployments across multiple science domains.XRootD is based on a scalable architecture that supports multi-protocol\ncommunications. XRootD provides a set of plugins and tools that allows the user\nto configure it freely to deploy data access clusters of any size, and which can\ninclude sophisticated features such as erasure coded files, various methods of\nauthentication and authorization, as well as integration with other storage\nsystems likeceph.DocumentationGeneral documentation such as configuration reference guides, and user manuals\ncan be found on the XRootD website athttp://xrootd.org/docs.html.Supported Operating SystemsXRootD is officially supported on the following platforms:RedHat Enterprise Linux 7 or later and their derivativesDebian 11 and Ubuntu 22.04 or latermacOS 11 (Big Sur) or laterSupport for other operating systems is provided on a best-effort basis\nand by contributions from the community.Installation InstructionsXRootD is available via official channels in most operating systems.\nInstallation via your system's package manager should be preferred.In RPM-based distributions, like CentOS, Alma, Rocky, Fedora, etc, one can\nsearch and install XRootD packages with$sudoyuminstallxrootdor$sudodnfinstallxrootdIn RHEL-based distributions, it will be necessary to first install the EPEL\nrelease repository withyum install epel-releaseordnf install epel-release.If you would like to use our official repository for XRootD RPMs, you can enable\nit on RHEL-based distributions with$sudocurl-Lhttps://cern.ch/xrootd/xrootd.repo-o/etc/yum.repos.d/xrootd.repoand on Fedora with$sudocurl-Lhttps://cern.ch/xrootd/xrootd-fedora.repo-o/etc/yum.repos.d/xrootd.repoOn Debian 11 or later, and Ubuntu 22.04 or later, XRootD can be installed via apt$sudoaptinstallxrootd-clientxrootd-serverpython3-xrootdOn macOS, XRootD is available via Homebrew$brewinstallxrootdXRootD can also be installed with conda, as it is also available in conda-forge:$condaconfig--addchannelsconda-forge\n$condaconfig--setchannel_prioritystrict\n$condainstallxrootdFinally, it is possible to install the XRootD python bindings from PyPI using pip:$pipinstallxrootdFor detailed instructions on how to build and install XRootD from source code,\nplease seedocs/INSTALL.mdin the main repository on GitHub.User Support and Bug ReportsBugs should be reported usingGitHub issues.\nYou can open a new ticket by clickinghere.For general questions about XRootD, please send a message to our user mailing\nlist atxrootd-l@slac.stanford.eduor open a newdiscussionon GitHub. Please check XRootD's contact page athttp://xrootd.org/contact.htmlfor further information.ContributingUser contributions can be submitted via pull request on GitHub. We recommend\nthat you create your own fork of XRootD on GitHub and use it to submit your\npatches. For more detailed instructions on how to contribute, please refer to\nthe filedocs/CONTRIBUTING.md."} +{"package": "xrootdfs", "pacakge-description": "Package name changed to xrootdpyfs (http://pypi.python.org/pypi/xrootdpyfs) due to naming conflict XRootD FUSE."} +{"package": "xrootdlib", "pacakge-description": "Thexrootdliboffers building blocks and basic tools to work with the XRootD data access middleware.\nIt is meant to facilitate auxiliary work, such as monitoring, accounting and orchestration."} +{"package": "xrootdpyfs", "pacakge-description": "XRootDPyFS is a PyFilesystem interface to XRootD.XRootD protocol aims at giving high performance, scalable fault tolerant access\nto data repositories of many kinds. The XRootDPyFS adds a high-level interface\non top of the existing Python interface (pyxrootd) and makes it easy to e.g.\ncopy a directory in parallel or recursively remove a directory.Further documentation is available onhttps://xrootdpyfs.readthedocs.io/.Getting startedIf you just want to try out the library, the easiest is to use Docker.Build the image:$dockerbuild--platformlinux/amd64-txrootd.Run the container and launchxrootd:$dockerrun--platformlinux/amd64-hxrootdpyfs-itxrootdbashYou will see the logs in the stdout. Next, in another shell, connect the container\nand fire up an ipython shell:$dockerps# find the container id$dockerexec-itbash[xrootdpyfs@xrootdpyfs code]$ipythonQuick examplesHere is a quick example of a file listing with the xrootd PyFilesystem\nintegration:>>> from xrootdpyfs import XRootDPyFS\n>>> fs = XRootDPyFS(\"root://localhost//tmp/\")\n>>> fs.listdir(\"xrootdpyfs\")\n['test.txt']Or, alternatively using the PyFilesystem opener (note the firstimport xrootdpyfsis required to ensure the XRootDPyFS opener is registered):>>> import xrootdpyfs\n>>> from fs.opener import open_fs\n>>> fs = open_fs(\"root://localhost//tmp/\")\n>>> fs.listdir(\"xrootdpyfs\")\n['test.txt']Reading files:>>> f = fs.open(\"xrootdpyfs/test.txt\")\n>>> f.read()\nb'Hello XRootD!\\n'\n>>> f.close()Reading files using thereadtext()method:>>> fs.readtext(\"xrootdpyfs/test.txt\")\nb'Hello XRootD!\\n'Writing files:>>> f = fs.open(\"xrootdpyfs/hello.txt\", \"w+\")\n>>> f.write(\"World\")\n>>> f.close()Writing files using thewritetext()method:>>> fs.writetext(\"xrootdpyfs/test.txt\", \"World\")DevelopmentThe easiest way to develop is to build the Docker image and mount\nthe source code as a volume to test any code modification with a\nrunning XRootD server:$dockerbuild--platformlinux/amd64-txrootd--progress=plain.$dockerrun--platformlinux/amd64-hxrootdpyfs-it-v:/codexrootdbash[xrootdpyfs@xrootdpyfs code]$xrootdIn another shell:$dockerps# find the container id$dockerexec-itbash[xrootdpyfs@xrootdpyfs code]$python-mpytest-vvvtestsIf you want to test a specific version of xrootd, run:$dockerbuild--platformlinux/amd64--build-argxrootd_version=4.12.7-txrootd--progress=plain.DocumentationDocumentation is available at or can be\nbuild using Sphinx:pip install Sphinx\npython setup.py build_sphinxTestingRunning the tests are most easily done using docker:$dockerbuild--platformlinux/amd64-txrootd.&&dockerrun--platformlinux/amd64-hxrootdpyfs-itxrootd"} +{"package": "xrosfs", "pacakge-description": "Mount a Running Docker Container File Sytem via FUSE.No requirement to install additional agents to container side. it\u2019s\nonly required to have permitted todocker execcommand.Docker containerxros-over-sshfsthat mount other containers file system automatically by XrosFS with\nautofs and sshfs is released.RequirementsDocker Host SidePython 3.5 or laterFUSE 2.6 (or later)Permitted to execute$ docker execDocker Container SideShell (ashorbash) and some commands(test,stat,ddbase64etc.) (Usually, they are already installed plain\nimage of alpine, debian etc.)InstallationpipinstallxrosfsUsageMount/ofcontainer1to~/mnt.$xrosfscontainer1:/~/mntIn above step, xrosfs connect tocontainer1asrootuser. Passuser@container1:/to xrosfs, if you want to connect as other users.Known IssuesCan\u2019t access to file that had\\nincluded filename.Bad response time in operates.Some operations methods are not full implemented\nyet(flush(fsync)utimensetc.).LicenseCopyright (c) 2018 hankei6kmLicensed under the MIT License. See LICENSE.txt in the project root."} +{"package": "xrotor", "pacakge-description": "GeneralThis is a stripped down version of XROTOR. All the modification, design, and graphical functionality has\nbeen removed. The only main menu options that are available in this stripped down version are:OPER, which allows for the calculation of performance characteristics at given operating conditions;BEND, which allows for the calculation of structural loads and deformations;NOIS, which allows for the calculation of the acoustic signature;LOAD, which loads a propeller definition file from the disk;SAVE, which saves a propeller definition file to the disk; andDISP, which displays the current propeller characteristics data onscreen.Building and Installing the Python ModuleTo successfully build and install the Python module a few prerequisites have to be present on your system. First of all,\na working installation of Python is required, of course. The module targets Python 3, and does NOT support Python 2.\nFurthermore, working compilers for C and Fortran have to be installed and on the PATH. On Windows, the build and\ninstallation have ONLY been tested with MinGW, using gcc and gfortran.Then, installing XRotor should be as simple as running:pipinstallxrotorOr, from the root of the downloaded repository:pipinstall.On Windows, you may have to force the system to use MinGW. To do so, create a file nameddistutils.cfginPYTHONPATH\\Lib\\distutilswith the following contents:[build]compiler=mingw32If you are not able to create this file for your Python environment, it is also possible to force the use of MinGW\ndirectly when invokingpipby calling:pipinstall--global-optionbuild_ext--global-option--compiler=mingw32xrotorUsing the ModuleAll XRotor operations are performed using theXRotorclass. So the first step when using this module is to create an\ninstance of this class:>>>fromxrotorimportXRotor>>>xr=XRotor()If this does not produce any errors, the installtion should be functioning properly.\nA test case is installed along with the module. To run it in XRotor, execute the following commands in the same python\nconsole:>>>fromxrotor.modelimportCase>>>fromxrotor.testimportcase>>>xr.case=Case.from_dict(case)>>>xr.operate(1,2000)Iter dGmax @Imax gGrms Av Aw Be rlx1 0.397E-01 1 0.167E-02 0.1553 0.1750 9.966 0.20002 0.225E-01 1 0.103E-02 0.1553 0.1764 9.966 0.20003 0.154E-01 1 0.733E-03 0.1553 0.1776 9.966 0.20004 0.116E-01 1 0.559E-03 0.1553 0.1824 9.966 1.00005 0.514E-03 29 0.224E-04 0.1553 0.1825 9.966 0.20006 0.412E-03 29 0.179E-04 0.1553 0.1825 9.966 1.00007 0.227E-05 29 0.742E-07 0.1553 0.1825 9.966 0.2000These commands initialize a sample propeller definition in XRotor and operate it at a fixed RPM of 2000 rev/min. The\noutput from the last function should be familiar to anyone who has used the original XRotor console application before:\nit is the convergence history of the OPER command. The familiar solution results can also be printed to the screen with\nthe following command:>>>xr.print_case()===========================================================================Free Tip Potential Formulation Solution:Wake adv. ratio: 0.18252no. blades : 2 radius(m) : 0.8300 adv. ratio: 0.15532thrust(n) : 481. power(w) : 0.219E+05 torque(n-m): 105.Efficiency : 0.5929 speed(m/s) : 27.000 rpm : 2000.000Eff induced: 0.8510 Eff ideal : 0.8993 Tcoef : 0.4981Tnacel(n) : 0.0132 hub rad.(m): 0.0600 disp. rad. : 0.0000Tvisc(n) : -15.5982 Pvisc(w) : 0.615E+04rho(kg/m3) : 1.22500 Vsound(m/s): 340.000 mu(kg/m-s) : 0.1789E-04---------------------------------------------------------------------------Sigma: NaNCt: 0.04658 Cp: 0.03833 j: 0.48795Tc: 0.49815 Pc: 0.84023 adv: 0.15532i r/r c/r beta(deg) cl Cd rEx10^6 Mach effi effp na.u/u1 0.081 0.1458 59.81 0.433 0.0934 0.25 0.090 3.944 0.555 0.0002 0.108 0.1475 56.04 0.501 0.0799 0.28 0.097 1.343 0.691 0.0003 0.149 0.1500 50.09 0.602 0.0720 0.32 0.110 1.036 0.782 0.0004 0.196 0.1527 43.42 0.642 0.0687 0.38 0.127 0.953 0.808 0.0005 0.244 0.1558 36.98 0.624 0.0620 0.44 0.147 0.933 0.816 0.0006 0.292 0.1594 31.45 0.581 0.0559 0.52 0.169 0.933 0.811 0.0007 0.341 0.1634 27.32 0.544 0.0521 0.60 0.191 0.928 0.800 0.0008 0.388 0.1672 24.38 0.521 0.0495 0.69 0.214 0.914 0.789 0.0009 0.435 0.1697 22.20 0.506 0.0474 0.77 0.236 0.896 0.781 0.00010 0.481 0.1699 20.38 0.494 0.0459 0.85 0.258 0.882 0.772 0.00011 0.526 0.1679 18.76 0.484 0.0450 0.91 0.280 0.875 0.761 0.00012 0.569 0.1639 17.37 0.476 0.0444 0.95 0.301 0.871 0.749 0.00013 0.611 0.1583 16.20 0.471 0.0440 0.99 0.322 0.867 0.738 0.00014 0.652 0.1515 15.24 0.470 0.0438 1.00 0.342 0.864 0.729 0.00015 0.690 0.1438 14.45 0.471 0.0436 1.00 0.361 0.860 0.722 0.00016 0.727 0.1356 13.78 0.475 0.0436 0.99 0.380 0.856 0.715 0.00017 0.762 0.1271 13.22 0.479 0.0438 0.98 0.397 0.853 0.709 0.00018 0.794 0.1188 12.73 0.483 0.0441 0.95 0.414 0.849 0.702 0.00019 0.825 0.1106 12.29 0.486 0.0447 0.92 0.429 0.846 0.694 0.00020 0.853 0.1029 11.91 0.487 0.0455 0.88 0.443 0.843 0.685 0.00021 0.879 0.0958 11.57 0.485 0.0466 0.84 0.456 0.838 0.673 0.00022 0.903 0.0892 11.26 0.479 0.0481 0.81 0.468 0.832 0.660 0.00023 0.924 0.0834 10.99 0.468 0.0501 0.77 0.479 0.824 0.642 0.00024 0.943 0.0782 10.74 0.450 0.0529 0.74 0.488 0.813 0.618 0.00025 0.959 0.0738 10.53 0.423 0.0570 0.71 0.496 0.796 0.585 0.00026 0.972 0.0701 10.35 0.385 0.0635 0.68 0.503 0.775 0.537 0.00027 0.983 0.0672 10.20 0.335 0.0740 0.66 0.509 0.747 0.467 0.00028 0.991 0.0651 10.08 0.270 0.0913 0.65 0.513 0.713 0.365 0.00029 0.997 0.0636 10.01 0.193 0.1177 0.63 0.516 0.675 0.236 0.00030 0.999 0.0629 9.97 0.125 0.1467 0.63 0.518 0.642 0.123 0.000If the module is working as it should, the output should match the output shown above.At the time of writing, the only the two operating modes available are fixed RPM and fixed thrust with fixed blade pitch.\nBoth can be invoked by calling theoperatemember function on an instance of theXRotorclass. The first argument\nto this function specifies which mode is used: 1 for fixed RPM, as was demonstrated above; 2 for fixed thrust at fixed\nblade pitch. The second argument to the function specifies the value for the RPM/thrust.See the documentation for more detailed explanation of how to use the API."} +{"package": "xround", "pacakge-description": "UNKNOWN"} +{"package": "xroute-env", "pacakge-description": "xroute_envRL environment for detailed routing.QuickstartInstallationTo interact with the xroute environment, you need to download the simulator first:Operating SystemDownload LinkUbuntu 22.04DownloadThen, put the simulator in thethird_party/openroadfolder.Launch Algorithm BackendDQNPPOLaunch SimulatorRun the following command to get launch script:cdexamples\npython3init.py[start_port][worker_num]start_port: the listen port number of the first worker instance.worker_num: the number of worker instances."} +{"package": "xrouter", "pacakge-description": "No description available on PyPI."} +{"package": "xrpa", "pacakge-description": "xrpaWhat is this?by: axinerxrpaThis is a xrpa.InstallationThis package can be installed using pip (Python3):pip install xrpaCopyrightCopyright (c) 2022 axinerPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE."} +{"package": "xrpatcher", "pacakge-description": "XRPatcher - A ML-Oriented Generic Patcher forxarrayData StructuresInstallation|ExamplesJ. Emmanuel JohnsonQuentin FebvreAboutThis is a lightweight package to create patchitemsfrom xarray data structures.\nThis makes it more compatible with machine learning datasets and dataloaders like PyTorch or TensorFlow.\nThe user simply needs to define the patch dimensions and the stride dimensions and you are good to go!\nIt also reconstructs (or unpatchifies) from arbitrary patches which allows for more robust inference procedures, e.g. to account for border effects from CNN models.\u23e9 ExamplesQuick ExampleimportxarrayasxrfromxrpatcherimportXRDAPatcher# load demo datasetdata=xr.tutorial.load_dataset(\"eraint_uvz\")# extract demo dataarraydata=data.u[...,:240,:360]# Instantiate the patching logic for trainingpatches=dict(longitude=30,latitude=30)train_patcher=XRDAPatcher(da=data,patches=patches,strides=patches,# No Overlapcheck_full_scan=True# check no extra dimensions)# Instantiate the patching logic for testingpatches=dict(longitude=30,latitude=30)strides=dict(longitude=5,latitude=5)test_patcher=XRDAPatcher(da=data,patches=patches,strides=strides,# Overlapcheck_full_scan=True# check no extra dimensions)Extended ExampleExample 1: Patching Crash CourseWe have an extended example where we demonstrate some of the ways to do the reconstruction!Example 2: PyTorch IntegrationWe have an extended example where we demonstrate some nifty PyTorch Integration.\ud83d\udee0\ufe0f InstallationpipWe can directly install it via pip from thepipinstall\"git+https://github.com/jejjohnson/xrpatcher.git\"CloningWe can also clone the git repositorygitclonehttps://github.com/jejjohnson/xrpatcher.gitcdxrpatcherConda Environment (RECOMMENDED)We use conda/mamba as our package manager. To install from the provided environment files\nrun the following command.mambaenvcreate-nenvironment.yamlpoetryThe easiest way to get started is to simply use the poetry package which installs all necessary dev packages as wellpoetryinstallpipWe can also install viapipas wellpipinstall.InspirationThere are a few other packages that gave us inspiration for this.xbatcherPatchExtractor (scikit-learn)"} +{"package": "xrpattern", "pacakge-description": "Reserved Python package"} +{"package": "xrpc", "pacakge-description": "MotivationNoneIncludesAutomated pythontypingmodule deserialization of primitives3 modes of message passingUDP-based protocolscreative logging customisationeasy daemon creationsExamplesee examples for nowAuthorAndrey Cizov (acizov@gmail.com), 2018"} +{"package": "xrpi-test-12.10.16", "pacakge-description": "UNKNOWN"} +{"package": "xrpl-dex-sdk", "pacakge-description": "XRPL Decentralized Exchange SDKThis Python SDK provides aCCXT-compatible APIfor interacting with theXRPL decentralized exchange.A TypeScript version of this SDK is availablehere.InstallationThis package requiresPython v3.8(or newer) and thePippackage installer.From PyPIAdd the SDK as a dependency to your project:$ pip install xrpl_dex_sdkImport the SDK into your script:importxrpl_dex_sdkFrom SourceMake sure you havePoetryinstalled on your system.NOTE: If you use VSCode, it should automatically show a prompt to select the virtual environment created by Poetry (./.venv). You will now have auto-formatting withblack, linting withflake8, type-checking withmypy, and vscode testing configs.Clone the repo and install dependencies:$ git clone https://github.com/AktaryTech/xrpl-dex-sdk-python.git\n$ cd xrpl-dex-sdk-python\n$ poetry installUsageTo use the SDK, import it into your script and initialize it:fromxrpl_dex_sdkimportSDK,SDKParams,constantssdk=SDK(SDKParams.from_dict({\"network\":constants.TESTNET,\"generate_wallet\":True,}))Currencies, MarketSymbols, and ID FormattingCurrency codes, market symbols (aka pairs), and Order/Trade IDs are strings that follow the following formats:TypeFormatExampleCurrencyCode[Currency]+[IssuerAddress]USD+rhub8VRN55s94qWKDv6jmDy1pUykJzF3wqMarketSymbol[BaseCurrency]/[QuoteCurrency]XRP/USD+rhub8VRN55s94qWKDv6jmDy1pUykJzF3wqOrderId, TradeId[AccountAddress]/[Sequence]rpkeJcxB2y5BeAFyycuWwdTTcR3og2a3SR:30419065ExamplesPlacing an OrderThe following example places an Order to buy 20 TST tokens, issued by the account atrP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd, at a price of 1.5 XRP each:fromxrpl_dex_sdkimportSDK,SDKParams,constants,modelssdk=SDK(SDKParams(network=constants.TESTNET,generate_wallet=True,))create_order_result=awaitsdk.create_order(symbol=\"TST+rP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd/XRP\",side=models.OrderSide.Buy,type=models.OrderType.Limit,amount=20,price=1.5,)order=awaitsdk.fetch_order(create_order_result.id)print(order)Outputs the newly created Order object:{\n ...,\n \"status\": \"open\",\n \"symbol\": \"TST+rP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd/XRP\",\n \"type\": \"limit\",\n \"timeInForce\": \"GTC\",\n \"side\": \"buy\",\n \"amount\": \"20\",\n \"price\": \"1.5\",\n \"average\": \"0\",\n \"filled\": \"0\",\n \"remaining\": \"20\",\n \"cost\": \"0\",\n \"trades\": [],\n \"info\": {\n // ... raw response from XRPL server\n }\n}Fetching an Order BookThe following example retrieves the latest order book for the market pairTST+rP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd/XRP:fromxrpl_dex_sdkimportSDK,SDKParams,constants,modelssdk=SDK(SDKParams(network=constants.TESTNET,generate_wallet=True,))order_book=awaitsdk.fetch_order_book(symbol=\"TST+rP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd/XRP\",limit=5)print(order_book)Outputs an object like the following:{\"symbol\":\"TST+rP9jPyP5kyvFRb6ZiRghAGw5u8SGAmU4bd/XRP\",\"bids\":[[\"0.0030627837459923\",\"93.030522464522\"],[\"0.00302447007930511\",\"1\"]],\"asks\":[[\"331.133829801611\",\"0.3\"]],\"info\":{// ... raw response from XRPL server}}MethodsFor full SDK documentation, loaddocs/_build/html/index.htmlin your browser. Rundocs/build.shto re-generate documentation.Further ReadingCCXT (CryptoCurrency eXchange Trading Library)General DocumentationUnified APIXRPL LedgerGeneral DocumentationDecentralized ExchangedEX TutorialContributingPull requests, issues and comments are welcome! Make sure to add tests for new features and bug fixes.ContactFor questions, suggestions, etc, you can reach the maintainer atinfo@aktarytech.com.LicenseThe software is distributed under the MIT license. SeeLICENSEfor details.Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this library by you, as defined in the MIT license, shall be licensed as above, without any additional terms or conditions.DisclaimerTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.CopyrightCopyright \u00a9 2022 Ripple Labs, Inc."} +{"package": "xrpld-netgen", "pacakge-description": "No description available on PyPI."} +{"package": "xrpld-publisher", "pacakge-description": "No description available on PyPI."} +{"package": "xrpl-helpers", "pacakge-description": "No description available on PyPI."} +{"package": "xrpl-plugin", "pacakge-description": "Python Pluginspipinstallxrpl-plugin\nplugin-buildpath/to/plugin.py# edit rippled.cfg to include the plugin.xrplugin in a [plugins] stanza# run rippled with the `plugin` branch and submit plugin transactions to it"} +{"package": "xrpl-py", "pacakge-description": "xrpl-pyA pure Python implementation for interacting with theXRP Ledger.Thexrpl-pylibrary simplifies the hardest parts of XRP Ledger interaction, like serialization and transaction signing. It also provides native Python methods and models forXRP Ledger transactionsand core serverAPI(rippled) objects.As an example, this is how you would use this library to send a payment on testnet:fromxrpl.accountimportget_balancefromxrpl.clientsimportJsonRpcClientfromxrpl.modelsimportPayment,Txfromxrpl.transactionimportsubmit_and_waitfromxrpl.walletimportgenerate_faucet_wallet# Create a client to connect to the test networkclient=JsonRpcClient(\"https://s.altnet.rippletest.net:51234\")# Create two wallets to send money between on the test networkwallet1=generate_faucet_wallet(client,debug=True)wallet2=generate_faucet_wallet(client,debug=True)# Both balances should be zero since nothing has been sent yetprint(\"Balances of wallets before Payment tx\")print(get_balance(wallet1.address,client))print(get_balance(wallet2.address,client))# Create a Payment transaction from wallet1 to wallet2payment_tx=Payment(account=wallet1.address,amount=\"1000\",destination=wallet2.address,)# Submit the payment to the network and wait to see a response# Behind the scenes, this fills in fields which can be looked up automatically like the fee.# It also signs the transaction with wallet1 to prove you own the account you're paying from.payment_response=submit_and_wait(payment_tx,client,wallet1)print(\"Transaction was submitted\")# Create a \"Tx\" request to look up the transaction on the ledgertx_response=client.request(Tx(transaction=payment_response.result[\"hash\"]))# Check whether the transaction was actually validated on ledgerprint(\"Validated:\",tx_response.result[\"validated\"])# Check balances after 1000 drops (.001 XRP) was sent from wallet1 to wallet2print(\"Balances of wallets after Payment tx:\")print(get_balance(wallet1.address,client))print(get_balance(wallet2.address,client))Installation and supported versionsThexrpl-pylibrary is available onPyPI. Install withpip:pip3 install xrpl-pyThe library supportsPython 3.7and later.FeaturesUsexrpl-pyto build Python applications that leverage theXRP Ledger. The library helps with all aspects of interacting with the XRP Ledger, including:Key and wallet managementSerializationTransaction Signingxrpl-pyalso provides:A network client \u2014 Seexrpl.clientsfor more information.Methods for inspecting accounts \u2014 SeeXRPL Account Methodsfor more information.Codecs for encoding and decoding addresses and other objects \u2014 SeeCore Codecsfor more information.\u27a1\ufe0f Reference DocumentationSee the completexrpl-pyreference documentation on Read the Docs.UsageThe following sections describe some of the most commonly used modules in thexrpl-pylibrary and provide sample code.Network clientUse thexrpl.clientslibrary to create a network client for connecting to the XRP Ledger.fromxrpl.clientsimportJsonRpcClientJSON_RPC_URL=\"https://s.altnet.rippletest.net:51234\"client=JsonRpcClient(JSON_RPC_URL)Manage keys and walletsxrpl.walletUse thexrpl.walletmodule to create a wallet from a given seed or or via aTestnet faucet.To create a wallet from a seed (in this case, the value generated usingxrpl.keypairs):wallet_from_seed=xrpl.wallet.Wallet.from_seed(seed)print(wallet_from_seed)# pub_key: ED46949E414A3D6D758D347BAEC9340DC78F7397FEE893132AAF5D56E4D7DE77B0# priv_key: -HIDDEN-# address: rG5ZvYsK5BPi9f1Nb8mhFGDTNMJhEhufn6To create a wallet from a Testnet faucet:test_wallet=generate_faucet_wallet(client)test_account=test_wallet.addressprint(\"Classic address:\",test_account)# Classic address: rEQB2hhp3rg7sHj6L8YyR4GG47Cb7pfcuwxrpl.core.keypairsUse thexrpl.core.keypairsmodule to generate seeds and derive keypairs and addresses from those seed values.Here's an example of how to generate aseedvalue and derive anXRP Ledger \"classic\" addressfrom that seed.fromxrpl.coreimportkeypairsseed=keypairs.generate_seed()public,private=keypairs.derive_keypair(seed)test_account=keypairs.derive_classic_address(public)print(\"Here's the public key:\")print(public)print(\"Here's the private key:\")print(private)print(\"Store this in a secure place!\")# Here's the public key:# ED3CC1BBD0952A60088E89FA502921895FC81FBD79CAE9109A8FE2D23659AD5D56# Here's the private key:# EDE65EE7882847EF5345A43BFB8E6F5EEC60F45461696C384639B99B26AAA7A5CD# Store this in a secure place!Note:You can usexrpl.core.keypairs.signto sign transactions butxrpl-pyalso provides explicit methods for safely signing and submitting transactions. SeeTransaction SigningandXRPL Transaction Methodsfor more information.Serialize and sign transactionsTo securely submit transactions to the XRP Ledger, you need to first serialize data from JSON and other formats into theXRP Ledger's canonical format, then toauthorize the transactionby digitallysigning itwith the account's private key. Thexrpl-pylibrary provides several methods to simplify this process.Use thexrpl.transactionmodule to sign and submit transactions. The module offers three ways to do this:sign_and_submit\u2014 Signs a transaction locally, then submits it to the XRP Ledger. This method does not implementreliable transaction submissionbest practices, so only use it for development or testing purposes.sign\u2014 Signs a transaction locally. This methoddoes notsubmit the transaction to the XRP Ledger.submit_and_wait\u2014 An implementation of thereliable transaction submission guidelines, this method submits a signed transaction to the XRP Ledger and then verifies that it has been included in a validated ledger (or has failed to do so). Use this method to submit transactions for production purposes.fromxrpl.models.transactionsimportPaymentfromxrpl.transactionimportsign,submit_and_waitfromxrpl.ledgerimportget_latest_validated_ledger_sequencefromxrpl.accountimportget_next_valid_seq_numbercurrent_validated_ledger=get_latest_validated_ledger_sequence(client)# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\",last_ledger_sequence=current_validated_ledger+20,sequence=get_next_valid_seq_number(test_wallet.address,client),fee=\"10\",)# sign the transactionmy_tx_payment_signed=sign(my_tx_payment,test_wallet)# submit the transactiontx_response=submit_and_wait(my_tx_payment_signed,client)Get fee from the XRP LedgerIn most cases, you can specify the minimumtransaction costof\"10\"for thefeefield unless you have a strong reason not to. But if you want to get thecurrent load-balanced transaction costfrom the network, you can use theget_feefunction:fromxrpl.ledgerimportget_feefee=get_fee(client)print(fee)# 10Auto-filled fieldsThexrpl-pylibrary automatically populates thefee,sequenceandlast_ledger_sequencefields when you create transactions. In the example above, you could omit those fields and let the library fill them in for you.fromxrpl.models.transactionsimportPaymentfromxrpl.transactionimportsubmit_and_wait,autofill_and_sign# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\")# sign the transaction with the autofill method# (this will auto-populate the fee, sequence, and last_ledger_sequence)my_tx_payment_signed=autofill_and_sign(my_tx_payment,client,test_wallet)print(my_tx_payment_signed)# Payment(# account='rMPUKmzmDWEX1tQhzQ8oGFNfAEhnWNFwz',# transaction_type=,# fee='10',# sequence=16034065,# account_txn_id=None,# flags=0,# last_ledger_sequence=10268600,# memos=None,# signers=None,# source_tag=None,# signing_pub_key='EDD9540FA398915F0BCBD6E65579C03BE5424836CB68B7EB1D6573F2382156B444',# txn_signature='938FB22AE7FE76CF26FD11F8F97668E175DFAABD2977BCA397233117E7E1C4A1E39681091CC4D6DF21403682803AB54CC21DC4FA2F6848811DEE10FFEF74D809',# amount='2200000',# destination='rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe',# destination_tag=None,# invoice_id=None,# paths=None,# send_max=None,# deliver_min=None# )# submit the transactiontx_response=submit_and_wait(my_tx_payment_signed,client)Subscribe to ledger updatesYou can sendsubscribeandunsubscriberequests only using the WebSocket network client. These request methods allow you to be alerted of certain situations as they occur, such as when a new ledger is declared.fromxrpl.clientsimportWebsocketClienturl=\"wss://s.altnet.rippletest.net/\"fromxrpl.modelsimportSubscribe,StreamParameterreq=Subscribe(streams=[StreamParameter.LEDGER])# NOTE: this code will run forever without a timeout, until the process is killedwithWebsocketClient(url)asclient:client.send(req)formessageinclient:print(message)# {'result': {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': '7CD50477F23FF158B430772D8E82A961376A7B40E13C695AA849811EDF66C5C0', 'ledger_index': 18183504, 'ledger_time': 676412962, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'validated_ledgers': '17469391-18183504'}, 'status': 'success', 'type': 'response'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'BAA743DABD168BD434804416C8087B7BDEF7E6D7EAD412B9102281DD83B10D00', 'ledger_index': 18183505, 'ledger_time': 676412970, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183505'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'D8227DAF8F745AE3F907B251D40B4081E019D013ABC23B68C0B1431DBADA1A46', 'ledger_index': 18183506, 'ledger_time': 676412971, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183506'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'CFC412B6DDB9A402662832A781C23F0F2E842EAE6CFC539FEEB287318092C0DE', 'ledger_index': 18183507, 'ledger_time': 676412972, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183507'}Asynchronous CodeThis library supports Python'sasynciopackage, which is used to run asynchronous code. All the async code is inxrpl.asyncioIf you are writing asynchronous code, please note that you will not be able to use any synchronous sugar functions, due to how event loops are handled. However, every synchronous method has a corresponding asynchronous method that you can use.This sample code is the asynchronous equivalent of the above section on submitting a transaction.importasynciofromxrpl.models.transactionsimportPaymentfromxrpl.asyncio.transactionimportsign,submit_and_waitfromxrpl.asyncio.ledgerimportget_latest_validated_ledger_sequencefromxrpl.asyncio.accountimportget_next_valid_seq_numberfromxrpl.asyncio.clientsimportAsyncJsonRpcClientasync_client=AsyncJsonRpcClient(JSON_RPC_URL)asyncdefsubmit_sample_transaction():current_validated_ledger=awaitget_latest_validated_ledger_sequence(async_client)# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\",last_ledger_sequence=current_validated_ledger+20,sequence=awaitget_next_valid_seq_number(test_wallet.address,async_client),fee=\"10\",)# sign and submit the transactiontx_response=awaitsubmit_and_wait(my_tx_payment_signed,async_client,test_wallet)asyncio.run(submit_sample_transaction())Encode addressesUsexrpl.core.addresscodecto encode and decode addresses into and from the\"classic\" and X-address formats.# convert classic address to x-addressfromxrpl.coreimportaddresscodectestnet_xaddress=(addresscodec.classic_address_to_xaddress(\"rMPUKmzmDWEX1tQhzQ8oGFNfAEhnWNFwz\",tag=0,is_test_network=True,))print(testnet_xaddress)# T7QDemmxnuN7a52A62nx2fxGPWcRahLCf3qaswfrsNW9LpsMigratingIf you're currently usingxrpl-pyversion 1, you can usethis guide to migrate to v2.ContributingIf you want to contribute to this project, seeCONTRIBUTING.md.Mailing ListsWe have a low-traffic mailing list for announcements of newxrpl-pyreleases. (About 1 email per week)Subscribe to xrpl-announceIf you're using the XRP Ledger in production, you should run arippled serverand subscribe to the ripple-server mailing list as well.Subscribe to ripple-serverCode SamplesFor samples of common use cases, see theXRPL.org Code Samplespage.You can also browse those samplesdirectly on GitHub.Report an issueExperienced an issue? Report ithere.LicenseThexrpl-pylibrary is licensed under the ISC License. SeeLICENSEfor more information."} +{"package": "xrpl-py-23", "pacakge-description": "xrpl-pyA pure Python implementation for interacting with the XRP Ledger, thexrpl-pylibrary simplifies the hardest parts of XRP Ledger interaction, like serialization and transaction signing, by providing native Python methods and models forXRP Ledger transactionsand core serverAPI(rippled) objects.# create a network clientfromxrpl.clientsimportJsonRpcClientclient=JsonRpcClient(\"https://s.altnet.rippletest.net:51234\")# create a wallet on the testnetfromxrpl.walletimportgenerate_faucet_wallettest_wallet=generate_faucet_wallet(client)print(test_wallet)public_key:ED3CC1BBD0952A60088E89FA502921895FC81FBD79CAE9109A8FE2D23659AD5D56private_key:-HIDDEN-classic_address:rBtXmAdEYcno9LWRnAGfT9qBxCeDvuVRZo# look up account infofromxrpl.models.requests.account_infoimportAccountInfoacct_info=AccountInfo(account=\"rBtXmAdEYcno9LWRnAGfT9qBxCeDvuVRZo\",ledger_index=\"current\",queue=True,strict=True,)response=client.request(acct_info)result=response.resultimportjsonprint(json.dumps(result[\"account_data\"],indent=4,sort_keys=True))# {# \"Account\": \"rBtXmAdEYcno9LWRnAGfT9qBxCeDvuVRZo\",# \"Balance\": \"1000000000\",# \"Flags\": 0,# \"LedgerEntryType\": \"AccountRoot\",# \"OwnerCount\": 0,# \"PreviousTxnID\": \"73CD4A37537A992270AAC8472F6681F44E400CBDE04EC8983C34B519F56AB107\",# \"PreviousTxnLgrSeq\": 16233962,# \"Sequence\": 16233962,# \"index\": \"FD66EC588B52712DCE74831DCB08B24157DC3198C29A0116AA64D310A58512D7\"# }Installation and supported versionsThexrpl-pylibrary is available onPyPI. Install withpip:pip3 install xrpl-pyThe library supportsPython 3.7and later.FeaturesUsexrpl-pyto build Python applications that leverage theXRP Ledger. The library helps with all aspects of interacting with the XRP Ledger, including:Key and wallet managementSerializationTransaction Signingxrpl-pyalso provides:A network client \u2014 Seexrpl.clientsfor more information.Methods for inspecting accounts \u2014 SeeXRPL Account Methodsfor more information.Codecs for encoding and decoding addresses and other objects \u2014 SeeCore Codecsfor more information.\u27a1\ufe0f Reference DocumentationSee the completexrpl-pyreference documentation on Read the Docs.UsageThe following sections describe some of the most commonly used modules in thexrpl-pylibrary and provide sample code.Network clientUse thexrpl.clientslibrary to create a network client for connecting to the XRP Ledger.fromxrpl.clientsimportJsonRpcClientJSON_RPC_URL=\"https://s.altnet.rippletest.net:51234\"client=JsonRpcClient(JSON_RPC_URL)Manage keys and walletsxrpl.walletUse thexrpl.walletmodule to create a wallet from a given seed or or via aTestnet faucet.To create a wallet from a seed (in this case, the value generated usingxrpl.keypairs):wallet_from_seed=xrpl.wallet.Wallet(seed,0)print(wallet_from_seed)# pub_key: ED46949E414A3D6D758D347BAEC9340DC78F7397FEE893132AAF5D56E4D7DE77B0# priv_key: -HIDDEN-# classic_address: rG5ZvYsK5BPi9f1Nb8mhFGDTNMJhEhufn6To create a wallet from a Testnet faucet:test_wallet=generate_faucet_wallet(client)test_account=test_wallet.classic_addressprint(\"Classic address:\",test_account)# Classic address: rEQB2hhp3rg7sHj6L8YyR4GG47Cb7pfcuwxrpl.core.keypairsUse thexrpl.core.keypairsmodule to generate seeds and derive keypairs and addresses from those seed values.Here's an example of how to generate aseedvalue and derive anXRP Ledger \"classic\" addressfrom that seed.fromxrpl.coreimportkeypairsseed=keypairs.generate_seed()public,private=keypairs.derive_keypair(seed)test_account=keypairs.derive_classic_address(public)print(\"Here's the public key:\")print(public)print(\"Here's the private key:\")print(private)print(\"Store this in a secure place!\")# Here's the public key:# ED3CC1BBD0952A60088E89FA502921895FC81FBD79CAE9109A8FE2D23659AD5D56# Here's the private key:# EDE65EE7882847EF5345A43BFB8E6F5EEC60F45461696C384639B99B26AAA7A5CD# Store this in a secure place!Note:You can usexrpl.core.keypairs.signto sign transactions butxrpl-pyalso provides explicit methods for safely signing and submitting transactions. SeeTransaction SigningandXRPL Transaction Methodsfor more information.Serialize and sign transactionsTo securely submit transactions to the XRP Ledger, you need to first serialize data from JSON and other formats into theXRP Ledger's canonical format, then toauthorize the transactionby digitallysigning itwith the account's private key. Thexrpl-pylibrary provides several methods to simplify this process.Use thexrpl.transactionmodule to sign and submit transactions. The module offers three ways to do this:sign_and_submit\u2014 Signs a transaction locally, then submits it to the XRP Ledger. This method does not implementreliable transaction submissionbest practices, so only use it for development or testing purposes.sign\u2014 Signs a transaction locally. This methoddoes notsubmit the transaction to the XRP Ledger.send_reliable_submission\u2014 An implementation of thereliable transaction submission guidelines, this method submits a signed transaction to the XRP Ledger and then verifies that it has been included in a validated ledger (or has failed to do so). Use this method to submit transactions for production purposes.fromxrpl.models.transactionsimportPaymentfromxrpl.transactionimportsign,send_reliable_submissionfromxrpl.ledgerimportget_latest_validated_ledger_sequencefromxrpl.accountimportget_next_valid_seq_numbercurrent_validated_ledger=get_latest_validated_ledger_sequence(client)test_wallet.sequence=get_next_valid_seq_number(test_wallet.classic_address,client)# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.classic_address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\",last_ledger_sequence=current_validated_ledger+20,sequence=test_wallet.sequence,fee=\"10\",)# sign the transactionmy_tx_payment_signed=sign(my_tx_payment,test_wallet)# submit the transactiontx_response=send_reliable_submission(my_tx_payment_signed,client)Get fee from the XRP LedgerIn most cases, you can specify the minimumtransaction costof\"10\"for thefeefield unless you have a strong reason not to. But if you want to get thecurrent load-balanced transaction costfrom the network, you can use theget_feefunction:fromxrpl.ledgerimportget_feefee=get_fee(client)print(fee)# 10Auto-filled fieldsThexrpl-pylibrary automatically populates thefee,sequenceandlast_ledger_sequencefields when you create transactions. In the example above, you could omit those fields and let the library fill them in for you.fromxrpl.models.transactionsimportPaymentfromxrpl.transactionimportsend_reliable_submission,autofill_and_sign# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.classic_address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\")# sign the transaction with the autofill method# (this will auto-populate the fee, sequence, and last_ledger_sequence)my_tx_payment_signed=autofill_and_sign(my_tx_payment,test_wallet,client)print(my_tx_payment_signed)# Payment(# account='rMPUKmzmDWEX1tQhzQ8oGFNfAEhnWNFwz',# transaction_type=,# fee='10',# sequence=16034065,# account_txn_id=None,# flags=0,# last_ledger_sequence=10268600,# memos=None,# signers=None,# source_tag=None,# signing_pub_key='EDD9540FA398915F0BCBD6E65579C03BE5424836CB68B7EB1D6573F2382156B444',# txn_signature='938FB22AE7FE76CF26FD11F8F97668E175DFAABD2977BCA397233117E7E1C4A1E39681091CC4D6DF21403682803AB54CC21DC4FA2F6848811DEE10FFEF74D809',# amount='2200000',# destination='rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe',# destination_tag=None,# invoice_id=None,# paths=None,# send_max=None,# deliver_min=None# )# submit the transactiontx_response=send_reliable_submission(my_tx_payment_signed,client)Subscribe to ledger updatesYou can sendsubscribeandunsubscriberequests only using the WebSocket network client. These request methods allow you to be alerted of certain situations as they occur, such as when a new ledger is declared.fromxrpl.clientsimportWebsocketClienturl=\"wss://s.altnet.rippletest.net/\"fromxrpl.models.requestsimportSubscribe,StreamParameterreq=Subscribe(streams=[StreamParameter.LEDGER])# NOTE: this code will run forever without a timeout, until the process is killedwithWebsocketClient(url)asclient:client.send(req)formessageinclient:print(message)# {'result': {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': '7CD50477F23FF158B430772D8E82A961376A7B40E13C695AA849811EDF66C5C0', 'ledger_index': 18183504, 'ledger_time': 676412962, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'validated_ledgers': '17469391-18183504'}, 'status': 'success', 'type': 'response'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'BAA743DABD168BD434804416C8087B7BDEF7E6D7EAD412B9102281DD83B10D00', 'ledger_index': 18183505, 'ledger_time': 676412970, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183505'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'D8227DAF8F745AE3F907B251D40B4081E019D013ABC23B68C0B1431DBADA1A46', 'ledger_index': 18183506, 'ledger_time': 676412971, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183506'}# {'fee_base': 10, 'fee_ref': 10, 'ledger_hash': 'CFC412B6DDB9A402662832A781C23F0F2E842EAE6CFC539FEEB287318092C0DE', 'ledger_index': 18183507, 'ledger_time': 676412972, 'reserve_base': 20000000, 'reserve_inc': 5000000, 'txn_count': 0, 'type': 'ledgerClosed', 'validated_ledgers': '17469391-18183507'}Asynchronous CodeThis library supports Python'sasynciopackage, which is used to run asynchronous code. All the async code is inxrpl.asyncioIf you are writing asynchronous code, please note that you will not be able to use any synchronous sugar functions, due to how event loops are handled. However, every synchronous method has a corresponding asynchronous method that you can use.This sample code is the asynchronous equivalent of the above section on submitting a transaction.importasynciofromxrpl.models.transactionsimportPaymentfromxrpl.asyncio.transactionimportsign,send_reliable_submissionfromxrpl.asyncio.ledgerimportget_latest_validated_ledger_sequencefromxrpl.asyncio.accountimportget_next_valid_seq_numberfromxrpl.asyncio.clientsimportAsyncJsonRpcClientasync_client=AsyncJsonRpcClient(JSON_RPC_URL)asyncdefsubmit_sample_transaction():current_validated_ledger=awaitget_latest_validated_ledger_sequence(async_client)test_wallet.sequence=awaitget_next_valid_seq_number(test_wallet.classic_address,async_client)# prepare the transaction# the amount is expressed in drops, not XRP# see https://xrpl.org/basic-data-types.html#specifying-currency-amountsmy_tx_payment=Payment(account=test_wallet.classic_address,amount=\"2200000\",destination=\"rPT1Sjq2YGrBMTttX4GZHjKu9dyfzbpAYe\",last_ledger_sequence=current_validated_ledger+20,sequence=test_wallet.sequence,fee=\"10\",)# sign the transactionmy_tx_payment_signed=awaitsign(my_tx_payment,test_wallet)# submit the transactiontx_response=awaitsend_reliable_submission(my_tx_payment_signed,async_client)asyncio.run(submit_sample_transaction())Encode addressesUsexrpl.core.addresscodecto encode and decode addresses into and from the\"classic\" and X-address formats.# convert classic address to x-addressfromxrpl.coreimportaddresscodectestnet_xaddress=(addresscodec.classic_address_to_xaddress(\"rMPUKmzmDWEX1tQhzQ8oGFNfAEhnWNFwz\",tag=0,is_test_network=True,))print(testnet_xaddress)# T7QDemmxnuN7a52A62nx2fxGPWcRahLCf3qaswfrsNW9LpsContributingIf you want to contribute to this project, seeCONTRIBUTING.md.Mailing ListsWe have a low-traffic mailing list for announcements of newxrpl.jsreleases. (About 1 email per week)Subscribe to xrpl-announceIf you're using the XRP Ledger in production, you should run arippled serverand subscribe to the ripple-server mailing list as well.Subscribe to ripple-serverReport an issueExperienced an issue? Report ithere.LicenseThexrpl-pylibrary is licensed under the ISC License. SeeLICENSEfor more information."} +{"package": "xrpl-sidechain-cli", "pacakge-description": "xrpl-sidechain-cliInstallpipinstallxrpl-sidechain-cliNOTE: if you're looking at the repo before it's published, this won't work. Instead, you'll do this:gitclonehttps://github.com/xpring-eng/sidechain-cli.gitcdsidechain-cli# install poetrycurl-sSLhttps://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py|python-\npoetryinstall\npoetryshellInstall rippled and the xbridge witness.rippled:https://xrpl.org/install-rippled.htmlwitness:https://github.com/seelabs/xbridge_witnessGet startedexportXCHAIN_CONFIG_DIR={filepathwhereyouwantyourconfigfilesstored}exportRIPPLED_EXE={rippledexefilepath}exportWITNESSD_EXE={witnessdexefilepath}./scripts/tutorial.shTo stop the servers:sidechain-cliserverstop--allUse Commandssidechain-cli--helpEach subcommand also has a--helpflag, to tell you what fields you'll need."} +{"package": "xrpl-websocket", "pacakge-description": "XRPL WebsocketWebsocket client for rippled with reconnecting feature, support both python 2 and 3InstallationVia pip:pipinstallxrpl_websocketExamplesShort-lived connectionSimple example to send a payload and wait for responseimportjsonfromxrpl_websocketimportClientif__name__==\"__main__\":# create instanceclient=Client()# connect to the websocketclient.connect(nowait=False)# send server info commandresp=client.send(command='server_info')print(\"Server Info:\")print(json.dumps(resp,indent=4))# close the connectionclient.disconnect()More advanced: Custom classYou can also write your own class for the connection, if you want to handle the nitty-gritty details yourself.classExample(Client):def__init__(self):super(self.__class__,self).__init__(log_level=logging.ERROR,server=\"wss://xrpl.ws\")# connect to the websocketself.connect()defon_transaction(self,data):print(json.dumps(data,indent=4))defon_ledger(self,data):print('on_ledger')defon_open(self,connection):print(\"Connection is open\")print(\"Subscribe to ledger transactions\")self.subscribe_transactions()defon_close(self):print(\"on_close\")defsubscribe_transactions(self):self.send({'command':'subscribe','streams':['transactions']})"} +{"package": "xrp-price-aggregate", "pacakge-description": "xrp-price-aggregateBased onXRPL-Labs/XRP-Price-AggregatorUsagepip install xrp-price-aggregateRun directly as a module or import and provide aggregation count (how many\nrounds) along with delay between each round.# run xrp_price_aggregate.__main__ and also beautify the results\npython -m xrp_price_aggregate | python -m json.tool\n{\n \"raw_results_named\": {\n \"hitbtc\": [\n \"0.72235\"\n ],\n ...\n },\n \"raw_results\": [\n \"0.72110\",\n \"0.72236\",\n \"0.72202\",\n ...\n ],\n \"raw_median\": \"0.72219\",\n \"raw_stdev\": \"0.00071\",\n \"filtered_results\": [\n \"0.72236\",\n \"0.72202\",\n \"0.72240\",\n ...\n ],\n \"filtered_median\": \"0.72236\",\n \"filtered_mean\": \"0.72219\"\n}>>># await it yourself>>>importasyncio>>>importxrp_price_aggregate>>>asyncio.run(xrp_price_aggregate.as_awaitable_json())'{\"raw_results_named\": {\"hitbtc\": [\"0.711729\"], \"binance\": [\"0.7131\"], \"bitrue\": [\"0.71292\"], \"bitfinex\": [\"0.7122\"], \"ftx\": [\"0.712675\", \"0.7126\"], \"kraken\": [\"0.71223\"], \"cex\": [\"0.71334\", \"0.7135\"], \"bitstamp\": [\"0.71328\"]}, \"raw_results\": [\"0.7131\", \"0.7122\", \"0.71328\", \"0.71334\", \"0.7135\", \"0.712675\", \"0.7126\", \"0.711729\", \"0.71223\", \"0.71292\"], \"raw_median\": \"0.7127975\", \"raw_stdev\": \"0.0005759840275563203497399309551\", \"filtered_results\": [\"0.71310\", \"0.71328\", \"0.71334\", \"0.71268\", \"0.71260\", \"0.71223\", \"0.71292\"], \"filtered_median\": \"0.71292\", \"filtered_mean\": \"0.71288\"}'>>># synchronous is the default case>>>importxrp_price_aggregate>>>xrp_price_aggregate.as_json()'{\"raw_results_named\": {\"cex\": [\"0.72039\", \"0.72136\"], \"hitbtc\": [\"0.72122\"], \"kraken\": [\"0.72132\"], \"bitfinex\": [\"0.72145\"], \"bitstamp\": [\"0.72047\"], \"bitrue\": [\"0.72122\"], \"binance\": [\"0.72150\"], \"ftx\": [\"0.72078\", \"0.72155\"]}, \"raw_results\": [\"0.72150\", \"0.72145\", \"0.72047\", \"0.72039\", \"0.72136\", \"0.72078\", \"0.72155\", \"0.72122\", \"0.72132\", \"0.72122\"], \"raw_median\": \"0.72127\", \"raw_stdev\": \"0.00043\", \"filtered_results\": [\"0.72150\", \"0.72145\", \"0.72136\", \"0.72155\", \"0.72122\", \"0.72132\", \"0.72122\"], \"filtered_median\": \"0.72136\", \"filtered_mean\": \"0.72137\"}'>>>xrp_price_aggregate.as_dict(count=3,delay=2){'raw_results_named':{'binance':[Decimal('0.721'),Decimal('0.7213'),Decimal('0.7211')],'ftx':[Decimal('0.7208'),Decimal('0.720975'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.7208'),Decimal('0.720975')],'bitfinex':[Decimal('0.7215'),Decimal('0.7215'),Decimal('0.72141')],'hitbtc':[Decimal('0.720796'),Decimal('0.720796'),Decimal('0.720796')],'bitstamp':[Decimal('0.72047'),Decimal('0.72047'),Decimal('0.72047')],'bitrue':[Decimal('0.72081'),Decimal('0.72094'),Decimal('0.72111')],'kraken':[Decimal('0.72132'),Decimal('0.72132'),Decimal('0.72132')],'cex':[Decimal('0.72039'),Decimal('0.72136'),Decimal('0.72039'),Decimal('0.72136'),Decimal('0.72039'),Decimal('0.72136')]},'raw_results':[Decimal('0.721'),Decimal('0.7215'),Decimal('0.72047'),Decimal('0.72039'),Decimal('0.72136'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72081'),Decimal('0.7213'),Decimal('0.7215'),Decimal('0.72047'),Decimal('0.72039'),Decimal('0.72136'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72094'),Decimal('0.7211'),Decimal('0.72141'),Decimal('0.72047'),Decimal('0.72039'),Decimal('0.72136'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72111')],'raw_median':Decimal('0.720975'),'raw_stdev':Decimal('0.0003566360729171225136133563969'),'filtered_results':[Decimal('0.721'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72081'),Decimal('0.7213'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72094'),Decimal('0.7211'),Decimal('0.7208'),Decimal('0.720975'),Decimal('0.720796'),Decimal('0.72132'),Decimal('0.72111')],'filtered_median':Decimal('0.720975'),'filtered_mean':Decimal('0.7209962777777777777777777778')}Note on JupyterWhen running in Jupyter notebooks, be sure to usenest_asyncioimportnest_asyncioimportxrp_price_aggregatenest_asyncio.apply()agg_results=xrp_price_aggregate.as_dict(count=6,delay=3)Public Colab Example Notebook,\nbackup of the.ipynbas a Gist"} +{"package": "xrprimer", "pacakge-description": "IntroductionEnglish |\u7b80\u4f53\u4e2d\u6587XRPrimer is a fundational library for XR-related algorithms.\nThe XRPrimer provides reusable data structures, efficient operaters and extensible interfaces both in C++ and Python.Major FeaturesVarious camera models and conversion tools (Pinhole, Fisheye, Omni etc.)Basic 3D operations (Triangulation, Projection etc.)Multi-camera extrinsic calibration toolsRendering and visualization toolsOperation SystemsIt currently supports the following systems.LinuxiOSInstallationPythonIf using xrprimer in a Python project, it can be installed by:pipinstallxrprimerIf you want to use the latest updates of xrprimer, please refer toPython Installationfor detailed installation.C++If using xrprimer in a C++ project, please refer toC++ Installationfor compilation and test.Getting startedUse XRPrimer in Python projectsThe below code is supposed to run successfully upon you finish the installation.python-c\"import xrprimer; print(xrprimer.__version__)\"Use XRPrimer in C++ projectsAn example is given below to show how to link xrprimer in C++ projects. More details can be foundhere.cmake_minimum_required(VERSION3.16)project(sample)#setpathforfindXRPrimerpackage(configmode)set(XRPrimer_DIR\"/lib/cmake\")find_package(XRPrimerREQUIRED)add_executable(samplesample.cpp)target_link_libraries(sampleXRPrimer::xrprimer)FAQIf you face some installation issues, you may first refer to thisFrequently Asked Questions.LicenseThe license of our codebase is Apache-2.0. Note that this license only applies to code in our library, the dependencies of which are separate and individually licensed. We would like to pay tribute to open-source implementations to which we rely on. Please be aware that using the content of dependencies may affect the license of our codebase. Refer toLICENSEto view the full license.CitationIf you find this project useful in your research, please consider cite:@misc{xrprimer,title={OpenXRLab Foundational Library for XR-related Algorithms},author={XRPrimer Contributors},howpublished={\\url{https://github.com/openxrlab/xrprimer}},year={2022}}ContributingWe appreciate all contributions to improve XRPrimer. Please refer toCONTRIBUTING.mdfor the contributing guideline.AcknowledgementXRPrimer is an open source project that is contributed by researchers and engineers from both the academia and the industry.\nWe appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.\nWe wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new models.Projects in OpenXRLabXRPrimer: OpenXRLab foundational library for XR-related algorithms.XRSLAM: OpenXRLab Visual-inertial SLAM Toolbox and Benchmark.XRSfM: OpenXRLab Structure-from-Motion Toolbox and Benchmark.XRLocalization: OpenXRLab Visual Localization Toolbox and Server.XRMoCap: OpenXRLab Multi-view Motion Capture Toolbox and Benchmark.XRMoGen: OpenXRLab Human Motion Generation Toolbox and Benchmark.XRNeRF: OpenXRLab Neural Radiance Field (NeRF) Toolbox and Benchmark."} +{"package": "xrptipbotPy", "pacakge-description": "No description available on PyPI."} +{"package": "xrpy", "pacakge-description": "No description available on PyPI."} +{"package": "xrqwpgfaey", "pacakge-description": "Xrqwpgfaey=================This API SDK was automatically generated by [APIMATIC Code Generator](https://apimatic.io/).This SDK uses the Requests library and will work for Python ```2 >=2.7.9``` and Python ```3 >=3.4```.How to configure:=================The generated code might need to be configured with your API credentials.To do that, open the file \"Configuration.py\" and edit its contents.How to resolve dependencies:===========================The generated code uses Python packages named requests, jsonpickle and dateutil.You can resolve these dependencies using pip ( https://pip.pypa.io/en/stable/ ).1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r requirements.txt```Note: You will need internet access for this step.How to test:=============You can test the generated SDK and the server with automatically generated testcases. unittest is used as the testing framework and nose is used as the testrunner. You can run the tests as follows:1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r test-requirements.txt```3. Invoke ```nosetests```How to use:===========After having resolved the dependencies, you can easily use the SDK following these steps.1. Create a \"xrqwpgfaey_test.py\" file in the root directory.2. Use any controller as follows:```pythonfrom __future__ import print_functionfrom xrqwpgfaey.xrqwpgfaey_client import XrqwpgfaeyClientapi_client = XrqwpgfaeyClient()controller = api_client.clientresponse = controller.get_basic_auth_test()print(response)```"} +{"package": "xrrloader", "pacakge-description": "No description available on PyPI."} +{"package": "xrscipy", "pacakge-description": "scipy for xarrayxr-scipy is a thin wrapper of scipy for thexarrayeco-system. You can read the documentationhere.Many scipy functions, such asscipy.integrate.trapezoidrequires coordinate array as an argument.\nxr-scipy wraps these functions to use native coordinate objects of xarray and returns an xarray object with the computed data.\nThis enables more xarray-oriented data analysis with scipy.Other usage/options are kept almost the same as the original scipy function.Exampleimportxarrayasxrimportnumpyasnpimportxrscipy.integrateIn[1]:da=xr.DataArray([0,3,2,4,6],coords={'x':np.linspace(0,1,5)})In[2]:daOut[2]:array([0,3,2,4,6])Coordinates:*x(x)float640.00.250.50.751.0In[3]:xrscipy.integrate.cumulative_trapezoid(da,coord='x')Out[3]:array([0.,0.375,1.,1.75,3.])Coordinates:*x(x)float640.00.250.50.751.0Installationpip install xrscipy"} +{"package": "xrsdkit", "pacakge-description": "No description available on PyPI."} +{"package": "xrsigproc", "pacakge-description": "Apply convolution to signals using various kernels to filter signals into large and small scale components."} +{"package": "xrsmtp", "pacakge-description": "XRSmtpXploitsR | XRSmtp is a module for fetching the details of any SMTP provider for your development or personal use.Usage# import the xrsmtp module\nimport xrsmtp\n\n#XRSmtp returns an a list which can be accessed with only 0 and 1 index\nxr = xrsmtp.XRSmtp()\n\n# For SSL\nsmtp_server = xr.smtp_portSSL(\"your-smtp-providers-name\")[0] #example: Gmail\nsmtp_port = xr.smtp_portSSL(\"your-smtp-providers-name\")[1] #example: Gmail\n\n\n# For TLS\nsmtp_server = xr.smtp_portTLS(\"your-smtp-providers-name\")[0] #example: Gmail\nsmtp_port = xr.smtp_portTLS(\"your-smtp-providers-name\")[1] #example: Gmail\n\n\n# [0] is used to retrieve the smtp server from the returned list\n# [1] is used to retrieve the smtp server's port from the returned list\n\n\n# You can list all possible smtp provider names XRsmtp module has using\nsmtp_listAll()\n\nexample: \n smtps = xr.smtp_listAll()\n print(\"SMTP provider names \", smtps)"} +{"package": "xrsrv", "pacakge-description": "XRSRV - eXeRcise SeRVer library: backend for physical exercise apps and utilities"} +{"package": "xrst", "pacakge-description": "Extract Sphinx RST FilesInstallThis installs the most recent testing version of xrst:pip install xrst\npip uninstall -y xrst\npip install --index-url https://test.pypi.org/simple/ xrstDocumentationhttps://xrst.readthedocs.ioGit Repositoryhttps://github.com/bradbell/xrst"} +{"package": "xrt", "pacakge-description": "Package xrt is a python software library for ray tracing and wave propagation\nin x-ray regime. It is primarily meant for modeling synchrotron sources,\nbeamlines and beamline elements. Includes a GUI for creating a beamline and\ninteractively viewing it in 3D.Features of xrtRays and waves. Classical ray tracing and wave propagation via Kirchhoff\nintegrals, also freely intermixed. No further approximations, such as thin\nlens or paraxial. The optical surfaces may have figure errors, analytical or\nmeasured. In wave propagation, partially coherent radiation is treated by\nincoherent addition of coherently diffracted fields generated per electron.\nPropagation of _individual_ coherent source modes is possible as waves,\nhybrid waves (i.e. partially as rays and then as waves) and only rays.Publication quality graphics. 1D and 2D position histograms aresimultaneouslycoded by hue and brightness. Typically, colors represent\nenergy and brightness represents beam intensity. The user may select other\nquantities to be encoded by colors: angular and positional distributions,\nvarious polarization properties, beam categories, number of reflections,\nincidence angle etc. Brightness can also encode partial flux for a selected\npolarization and incident or absorbed power. Publication quality plots are\nprovided by matplotlib with image formats PNG, PostScript, PDF and SVG.Unlimited number of rays. The colored histograms arecumulative. The\naccumulation can be stopped and resumed.Parallel execution. xrt can be run in parallel in several threads or\nprocesses (can be opted), which accelerates the execution on multi-core\ncomputers. Alternatively, xrt can use the power of GPUs via OpenCL for\nrunning special tasks such as the calculation of an undulator source or\nperforming wave propagation.Scripting in Python. xrt can be run within Python scripts to generate a\nseries of images under changing geometrical or physical parameters. The image\nbrightness and 1D histograms can be normalized to the global maximum\nthroughout the series.Synchrotron sources. Bending magnet, wiggler, undulator and elliptic\nundulator are calculated internally within xrt. Please look the section\n\u201cComparison of synchrotron source codes\u201d for the comparison other popular\ncodes. If the photon source is one of the synchrotron sources, the total flux\nin the beam is reported not just in number of rays but in physical units of\nph/s. The total power or absorbed power can be opted instead of flux and is\nreported in W. The power density can be visualized by isolines. The magnetic\ngap of undulators can be tapered. Undulators can be calculated in near field.\nCustom magnetic field is also possible. Undulators can be calculated on GPU,\nwith a high gain in computation speed, which is important for tapering and\nnear field calculations.Shapes. There are several predefined shapes of optical elements implemented\nas python classes. The python inheritance mechanism simplifies creation of\nother shapes: the user specifies methods for surface height and surface\nnormal. The surface and the normal are defined either in local Cartesian\ncoordinates or in user-defined parametric coordinates. Parametric\nrepresentation enables closed shapes such as capillaries or wave guides. It\nalso enables exact solutions for complex shapes (e.g. a logarithmic spiral or\nan ellipsoid) without any expansion. The methods of finding the intersections\nof rays with the surface are very robust and can cope with pathological cases\nsuch as sharp surface kinks. Notice that the search for intersection points\ndoes not involve any approximation and has only numerical inaccuracy which is\nset by default as 1 fm. Any surface can be combined with a (differently and\nvariably oriented) crystal structure and/or (variable) grating vector.\nSurfaces can be faceted.Energy dispersive elements. Implemented are crystals in dynamical\ndiffraction, gratings (also with efficiency calculations), Fresnel zone\nplates, Bragg-Fresnel optics and multilayers in dynamical diffraction.\nCrystals can work in Bragg or Laue cases, in reflection or in transmission.\nThe two-field polarization phenomena are fully preserved, also within the\nDarwin diffraction plateau, thus enabling the ray tracing of crystal-based\nphase retarders.Materials. The material properties are incorporated using three different\ntabulations of the scattering factors, with differently wide and differently\ndense energy meshes. Refractive index and absorption coefficient are\ncalculated from the scattering factors. Two-surface bodies, such as plates or\nrefractive lenses, are treated with both refraction and absorption.Multiple reflections. xrt can trace multiple reflections in a single\noptical element. This is useful, for example in \u2018whispering gallery\u2019 optics\nor in Montel or Wolter mirrors.Non-sequential optics. xrt can trace non-sequential optics where different\nparts of the incoming beam meet different surfaces. Examples of such optics\nare poly-capillaries and Wolter mirrors.Singular optics. xrt correctly propagates vortex beams, which can be used\nfor studying the creation of vortex beams by transmissive or reflective\noptics.Global coordinate system. The optical elements are positioned in a global\ncoordinate system. This is convenient for modeling a real synchrotron\nbeamline. The coordinates in this system can be directly taken from a CAD\nlibrary. The optical surfaces are defined in their local systems for the\nuser\u2019s convenience.Beam categories. xrt discriminates rays by several categories:good,out,overanddead. This distinction simplifies the adjustment of\nentrance and exit slits. An alarm is triggered if the fraction of dead rays\nexceeds a specified level.Portability. xrt runs on Windows and Unix-like platforms, wherever you can\nrun python.Examples. xrt comes with many examples; see the galleries, the links are at\nthe top bar.xrtQook \u2013 a GUI for creating scriptsThe main interface to xrt is through a python script. Many examples of such\nscripts can be found in the supplied folders \u2018examples\u2019 and \u2018tests\u2019. The script\nimports the modules of xrt, instantiates beamline parts, such as synchrotron or\ngeometric sources, various optical elements, apertures and screens, specifies\nrequired materials for reflection, refraction or diffraction, defines plots and\nsets job parameters.The Qt tool xrtQook takes these ingredients as GUI elements and prepares a\nready to use script that can be run within the tool itself or in an external\nPython context. xrtQook has a parallelly updated help panel that provides a\ncomplete list of parameters for the used objects. xrtQook writes/reads the\nrecipes of beamlines into/from xml files.xrtGlow \u2013 an interactive 3D beamline viewerThe beamline created in xrtQook can be interactively viewed in an OpenGL based\nwidget xrtGlow. It visualizes beams, footprints, surfaces, apertures and\nscreens. The brightness represents intensity and the color represents an\nauxiliary user-selected distribution, typically energy. A virtual screen can be\nput at any position and dragged by mouse with simultaneous observation of the\nbeam distribution on it.The primary purpose of xrtGlow is to demonstrate the alignment correctness\ngiven the fact that xrtQook can automatically calculate several positional and\nangular parameters.Dependenciesnumpy, scipy and matplotlib are required. If you use OpenCL for calculations on\nGPU or CPU, you need AMD/NVIDIA drivers,Intel CPU only OpenCL runtime(these are search key words), pytools and pyopencl. PyQt4 or PyQt5 are needed\nfor xrtQook. Spyder (as library of Spyder IDE) is highly recommended for nicer\nview of xrtQook. OpenGL is required for xrtGlow.Get xrtxrt is available as source distribution frompypi.python.organd fromGitHub. The distribution archive also includes tests\nand examples. The complete documentation is available online atRead the Docsand offline aszip file at GitHub.Get helpFor getting help and/or reporting a bug please useGitHub xrt Issues."} +{"package": "xrtc", "pacakge-description": "XRTC APIXRTC is the next generation ultra-low latency TCP streaming protocol. It is 30-50x faster than\nLL-HLS and RTMP, and it is 2-5x faster than WebRTC. Unlike UDP-based WebRTC, XRTC uses a pure\nTCP/HTTP for ease of cross-firewall deployment and security.This is an SDK for XRTC API in Python. The SDK implements the following convenience features:non-async context manager with requests package, error managementasync context manager with asyncio/aiohttp for handling parallel HTTP requests, error managementlogin and connection configurations loading from .env file or from the environmentconfigurations, serialized and deserialized request bodies and response data models and parser with PydanticTo start using XRTC, please obtain your free API token atXRTC web siteThis project is maintained byDelta Cygni Labs Ltdwith the headquarters in Tampere,\nFinland.InstallationInstallation from Pypi:pip install xrtcUpdate from Pypi if you have already installed the package:pip install xrtc --upgradeInstallation from source (advanced users only):pip install .Installation from source if you want the package to be editable (advanced users only):pip install . -eLogin credentials and connection URLsLogin credentials you can provide as arguments to the contexts or specify\nin a dotenv file (by defaultxrtc.env) placed to the work directory.Example ofxrtc.envfile content:# XRTC credentials\nACCOUNT_ID=AC0987654321012345\nAPI_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxUsage examplesSee more onGitHub, examples directory.Simple set and get:from xrtc import XRTC\n\n# Get your free account and API key from https://xrtc.org\nwith XRTC(account_id=\"AC0987654321012345\", api_key=\"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\") as xrtc:\n # Upload an item\n xrtc.set_item(items=[{\"portalid\": \"exampleportal\", \"payload\": \"examplepayload\"}])\n\n # Download items and iterate through them\n for item in xrtc.get_item(portals=[{\"portalid\": \"exampleportal\"}]):\n print(item.dict())The same example with the async context manager:from xrtc import AXRTC\n\nasync def main():\n \"\"\"Async function that enables the use of async context manager.\"\"\"\n\n # Get your free account and API key from https://xrtc.org\n async with AXRTC(account_id=\"AC0987654321012345\", api_key=\"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\") as xrtc:\n # Upload an item\n await xrtc.set_item(items=[{\"portalid\": \"exampleportal\", \"payload\": \"examplepayload\"}])\n\n # Download items and iterate through them\n async for item in xrtc.get_item(portals=[{\"portalid\": \"exampleportal\"}]):\n print(item.dict())\n\n\nAXRTC.run(main())A more sophisticated example for continuous setting and getting with XRTC and async context manager.\nMeasures end-to-end latency in ms. Note different get item modes (watch, probe) as well as cutoff\nparameter to discard the items from previous runs. Two set of credentials are used for setting\nand getting: theaccountidis the same, but theapikeyare different (request them twice fromXRTC web site), and the credentials are loaded from the respective\ndotenv files.import asyncio\nfrom time import time\nimport json\n\nfrom xrtc import AXRTC\n\n\nclass LatencyTest:\n def __init__(self):\n self.test_running = True\n\n async def setting(self):\n \"\"\"Set time co-routine.\"\"\"\n async with AXRTC(env_file_credentials=\"xrtc_set.env\") as xrtc:\n # Keep uploading items\n for counter in range(0, 100):\n payload = json.dumps({\"time\": str(time())})\n await xrtc.set_item(items=[{\"portalid\": \"latency\", \"payload\": payload}])\n await asyncio.sleep(0.1)\n\n # Uploading finished, sleep to let all items arrive\n await asyncio.sleep(1)\n self.test_running = False\n\n async def getting(self):\n \"\"\"Get time co-routine.\"\"\"\n mean = 0\n iteration = 0\n async with AXRTC(env_file_credentials=\"xrtc_get.env\") as xrtc:\n # Keep polling for items\n while self.test_running:\n # mode=\"watch\" means wait until there is fresh item. Compare to mode=\"probe\"\n # cutoff=500 discards the items older than 500ms, e.g. from the previous run\n # iterate through the items (a single request may bring several items)\n async for item in xrtc.get_item(\n portals=[{\"portalid\": \"latency\"}], mode=\"stream\", cutoff=500\n ):\n received_time = json.loads(item.payload)[\"time\"]\n latency = round((time() - float(received_time)) * 1000, 1)\n\n # Recurring sample mean\n mean = round(1 / (iteration + 1) * (mean * iteration + latency), 1)\n iteration += 1\n\n print(f\"{iteration = }: {latency = } ms, {mean = } ms\")\n\n async def execute(self):\n \"\"\"Launch parallel setting and getting tasks.\"\"\"\n await asyncio.gather(self.setting(), self.getting())\n\n\nlatency_test = LatencyTest()\nasyncio.run(latency_test.execute())"} +{"package": "xrtpy", "pacakge-description": "# XRTpy[![License](https://img.shields.io/badge/License-BSD%202\u2013Clause-blue.svg)](./LICENSE)\n[![GitHub Actions \u2014 CI](https://github.com/HinodeXRT/xrtpy/workflows/CI/badge.svg)](https://github.com/HinodeXRT/xrtpy/actions?query=workflow%3ACI+branch%3Amain)\n[![Read the Docs Status](https://readthedocs.org/projects/xrtpy/badge/?version=latest&logo=twitter)](http://xrtpy.readthedocs.io/en/latest/?badge=latest)\n[![astropy](http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat&logo=astropy)](http://www.astropy.org/)XRTpy is a Python package being developed for the analysis of observations\nmade by the X-Ray Telescope (XRT) on theHinodespacecraft.## AcknowledgementsThe development of XRTpy is supported by NASA contract NNM07AB07C to the\nSmithsonian Astrophysical Observatory."} +{"package": "xrtr", "pacakge-description": "A generic string router based on a Radix Tree structure, (partially) Cython optimized for speed.Documentationhttps://xrtr.readthedocs.io/en/latest/Inspirationxrtris highly inspired inRouter, byshiyanhui.Licensexrtris a free software distributed under theMITlicense, the same license asRouter\u2019s license.To DoThere is a LOT of room for improvement (specially when migrating the code to C and Cythonandthe fact this is my first project with Cython);Fix test coverage (and why is it not covering method declarations, as an example);There is a lot of fixes to be done regarding Cython, distribution, naming conventions and so on;Add Windows buildsusing AppVeyor;Changelogv0.2.1 on 2018-10-09Fixed bug where theno_conflictflag where not being propagated to theadd_methodif a \u201cnon-conflicting method\u201d was the first node being created in that tree.v0.2.0 on 2018-10-03Addmethod_forfunction.v0.1.4 on 2018-10-03Addsentinelobject.v0.1.3 on 2018-09-21Add testing for repeated variables.v0.1.2 on 2018-09-14Minor tweaks and improvements (search optimizations).v0.1.1 on 2018-09-11Minor tweaks and improvements.v0.1.0 on 2018-08-22First release on PyPI."} +{"package": "xrt-spec-dl", "pacakge-description": "xrt_spec_dlsimple tool to ddownload XRT time slicesFree software: GNU General Public License v3Documentation:https://xrt-spec-dl.readthedocs.io.FeaturesTODOCredits"} +{"package": "xruletest", "pacakge-description": "No description available on PyPI."} +{"package": "xrumaplib", "pacakge-description": "No description available on PyPI."} +{"package": "xrunner", "pacakge-description": "UNKNOWN"} +{"package": "xrview", "pacakge-description": "xrviewVisualizing xarray data with bokeh.Documentation:https://xrview.readthedocs.ioFeaturesPlot xarray Datasets and DataArrays in a few lines of codeVisualize large timeseries data setsInstallationxrview can be installed viapip:$pipinstallxrvieworconda:$condainstall-cphausamannxrviewCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.1 (Oct 19, 2020)Bug fixesFixed tooltip rendering for datetime axis.0.2.0 (Sep 8, 2020)Breaking changesDropped compatibility with Python 2.7 and 3.5 and bokeh versions < 2.20.1.0 (Sep 8, 2020)First official releaseLast release compatible with Python 2.7/3.5"} +{"package": "xrviz", "pacakge-description": "# XrViz[![Anaconda-Server Badge](https://anaconda.org/conda-forge/xrviz/badges/installer/conda.svg)](https://conda.anaconda.org/conda-forge)\n[![PyPI version](https://badge.fury.io/py/xrviz.svg)](https://badge.fury.io/py/xrviz)\n[![Build Status](https://travis-ci.org/intake/xrviz.svg?branch=master)](https://travis-ci.org/intake/xrviz)\n[![Documentation Status](https://readthedocs.org/projects/xrviz/badge/?version=latest)](https://xrviz.readthedocs.io/en/latest/?badge=latest)\n[![Gitter](https://badges.gitter.im/ESIP_GUI/community.svg)](https://gitter.im/ESIP_GUI/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)XrViz is an interactive graphical user interface(GUI) for visually browsing Xarrays.\nYou can view data arrays along various dimensions, examine data values, change\ncolor maps, extract series, display geographic data on maps and much more.\nIt is built on [Xarray](http://xarray.pydata.org),\n[HvPlot](https://hvplot.pyviz.org) and [Panel](https://panel.pyviz.org/).\nIt can be used with [Intake](http://intake.readthedocs.io/)\nto ease the process of investigating and loading datasets.Documentation is available at [Read the Docs](https://xrviz.readthedocs.io).\nTry it out on binder: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intake/xrviz/master?filepath=examples%2Fgreat_lakes.ipynb)
          ### InstallationRecommended method using conda:` conda install-cconda-forgexrviz `You can also install using pip:` pip install xrviz `### Usage\nYou can view the example dashboard by running following in command line (this will open a tab in your browser):` python-c\"import xrviz;xrviz.example()\"`"} +{"package": "xrx-mysql-utils", "pacakge-description": "xrx-mysql-utils"} +{"package": "xrx-redis-file-transporter", "pacakge-description": "xrx-redis-file-transporter"} +{"package": "xrx-text-utils", "pacakge-description": "xrx-text-utils"} +{"package": "xrypt-xethhung12", "pacakge-description": "Installationpipinstall-Uxrypt-xethhung12Usagefromxrypt_xethhung12.rsa_encryptionimportgen_key_pair,read_public_key_from_pem_str,read_private_key_from_pem_str\nfromxrypt_xethhung12.rsa_formatimportpub_key_to_pem,pri_key_to_pem\nfromxrypt_xethhung12.xrypt.xryptimportDeEnCryptor,Signer,Verifierif__name__=='__main__':# Generate key pairs_pub,s_pri=gen_key_pair()r_pub,r_pri=gen_key_pair()# encrypt and decryptdata_encrypted=DeEnCryptor(s_pub,s_pri).encryptToContainer(r_pub,\"helloworld\")data=DeEnCryptor(r_pub,r_pri).decryptContainer(s_pub,data_encrypted)print(data)# sign and verifysigned_data=Signer(s_pri).sign(\"helloworld\")print(Verifier(s_pub).verify(signed_data))# To pem format stringprint(pub_key_to_pem(s_pub))print(pri_key_to_pem(s_pri))reloaded_s_pub_key=read_public_key_from_pem_str(pub_key_to_pem(s_pub))reloaded_s_pri_key=read_private_key_from_pem_str(pri_key_to_pem(s_pri))reloaded_r_pub_key=read_public_key_from_pem_str(pub_key_to_pem(r_pub))reloaded_r_pri_key=read_private_key_from_pem_str(pri_key_to_pem(r_pri))# encrypt and decrypt - againdata_encrypted=DeEnCryptor(reloaded_s_pub_key,reloaded_s_pri_key).encryptToContainer(reloaded_r_pub_key,\"helloworld\")data=DeEnCryptor(reloaded_r_pub_key,reloaded_r_pri_key).decryptContainer(reloaded_s_pub_key,data_encrypted)print(data)# sign and verify - againsigned_data=Signer(reloaded_s_pri_key).sign(\"helloworld\")print(Verifier(reloaded_s_pub_key).verify(signed_data))ScriptsGenerate rsa key pairpri={pri}pub={pub}opensslgenrsa-out$pri4096opensslrsa-in$pri-outformPEM-pubout-out$pubBuildrm-frdist\npython3-mbuildBuild and Deployrm-frdist\npython3-mbuild\ntwineuploaddist/*-u__token__-p$pwdUpdate version devpython3-mxh_py_project_versioning--patchUpdate versionpython3-mxh_py_project_versioning--patch-d"} +{"package": "xrzz", "pacakge-description": "XRZZHTTP RequestDescriptionJust a simple module for HTTP Request \n\n supports : {\n\n \t 1: GET,\n \t 2: POST \n\n }TodoAccept Cookies\nPersistent Connection to server\nAuto Encode url \nproxy support\nAuto Redirect facility\nPUT; PATCH; TRACE; CONNECT\noptimization neededSupportsGET, POSTInstallationtill now it doesn't need any external modules\n\npip install xrzzUsageimport xrzz\n\na = xrzz.http(\"get\", \n\t\turl=\"https://httpbin.org/get\", \n\t\theaders={\"user-agent\": \"Xrzz/v1\"},\n\t\ttls=True)\nprint(a.body())\n\n\n# output (Bytes)\n\n\t\tb'{\\n\"args\": {},\\n\"headers\": {\\n\"Host\": \"httpbin.org\",\\n \"User-Agent\": \"Xrzz/v1\", \\n\n\t\t\"X-Amzn-Trace-Id\": \"Root=1-606b416e-79346cf934ed2d6f4aa2cbf7\"\\n },\\n \"origin\": \"45.103.157.9\", \\n \n\t\t\"url\": \"https://httpbin.org/get\"\\n}\\n'\n\n\t\tUsually it returns in bytes \n\n# output (decoded)\n\n\t\t{\n\t\t \"args\": {},\n\t\t \"headers\": {\n\t\t \"Host\": \"httpbin.org\",\n\t\t \"User-Agent\": \"Xrzz/v1\",\n\t\t \"X-Amzn-Trace-Id\": \"Root=1-606b416e-79346cf934ed2d6f4aa2cbf7\"\n\t\t },\n\t\t \"origin\": \"45.103.157.9\",\n\t\t \"url\": \"https://httpbin.org/get\"\n\t\t}\n\n\nprint(a.head() \n\n# output (dict)\n\n\t\t{\n\t\t\t'Date': 'Mon, 05 Apr 2021 17:06:13 GMT', \n\t\t\t'Content-Type': 'application/json', \n\t\t\t'Content-Length': '242', \n\t\t\t'Connection': 'close', \n\t\t\t'Server': 'gunicorn/19.9.0', \n\t\t\t'Access-Control-Allow-Origin': '*', \n\t\t\t'Access-Control-Allow-Credentials': 'true'\n\t\t}Whats newPOST METHODVersionv0.1.3"} +{"package": "xs", "pacakge-description": "No description available on PyPI."} +{"package": "xs1-api-client", "pacakge-description": "xs1-api-clientA python 3.5+ library for accessing actuator and sensor data on the the\nEZcontrol\u00ae XS1 Gateway using its HTTP API.Build StatusMasterBetaDevHome AssistantThe initial goal of this library was to be able to integrate the EZcontrol\u00ae XS1 Gateway withHome Assistant.\nYou can find the related integration documentation here:XS1 Home Assistant component documentationNote:\nxs1-api-client was designed to have reusable device objects, meaning device objects can be updated.\nWhen a user changes the order of devices within the XS1 gateway, their ids don\u2019t change but their numbers (orders) do.\nThis causes the \u201cdevice object\u201d <-> device id association to get messed up. Since there is no way for us to know\nabout this change, it\u2019s impossible for us to tell that the device number we use for an already created device object\ndoes not correspond to the correct device anymore without fetching all devices again, which requires the recreation\nof all device objects.TL;DR:Do not change the order of the devices in the XS1 Gatewayif you can avoid it, and if you do,\nrestart the service that relies on xs1-api-client to force a re-fetch of all devices.How to useInstallationpip installxs1-api-clientUsageFor a basic example have a look at the [example.py] file. If you need\nmore info have a look at the [documentation] which should help.Basic ExampleCreate the API ObjectThe basic way of creating an API object is by providing connection info\ndirectly when creating it:fromxs1_api_clientimportapiasxs1apifromxs1_api_clientimportapi_constants# Create an api object with private configurationapi=xs1api.XS1(host='192.168.2.20',user=\"Username\",password=\"Password\")This will automatically try to connect to the gateway with the given credentials and retrieve basic\ngateway information which you can output like this:print(\"Gateway Hostname: \"+api.get_gateway_name())print(\"Gateway MAC: \"+api.get_gateway_mac())print(\"Gateway Hardware Version: \"+api.get_gateway_hardware_version())print(\"Gateway Bootloader Version: \"+api.get_gateway_bootloader_version())print(\"Gateway Firmware Version: \"+api.get_gateway_firmware_version())print(\"Gateway uptime: \"+str(api.get_gateway_uptime())+\" seconds\")You can also specify a custom port and enable SSL:api=xs1api.XS1(host='192.168.2.20',port=1234,ssl=True,user=\"Username\",password=\"Password\")Now that you have a connection to your gateway we can retrieve its\nconfiguration and set or retrieve values of configured actuators and sensors or even modify their configuration.DevicesAll devices that you have configured in your XS1 are implemented using\ntheXS1Devicebase class which can be found at/device/__init__.py.\nThis class provides basic functionality for every device like getting\ntheid,name,typeand other values.Retrieve ActuatorsTo retrieve a list of all 64 actuators use the following call:actuators=api.get_all_actuators()This will return a list ofXS1Actuatorobjects which is another base\nclass for all actuators. You can use something like this to print all\nyour actuators:foractuatorinactuators:print(\"Actuator \"+str(actuator.id())+\": \"+actuator.name()+\" (\"+str(actuator.type())+\")\")There is also an integrated__str__method to print out most of the useful properties just like this:foractuatorinactuators:print(actuator)You can also filter the elements byenabledanddisabledstate using:enabled_actuators=api.get_all_actuators(True)Retrieve a single actuator simply by using:actuator_1=api.get_actuator(1)Retrieve an Actuator ValueTo retrieve the current value of an actuator just call:current_value=actuator.value()Set a new Actuator valueTo set a new value to this actuator use:actuator.set_value(100)This will send the required request to the XS1 and set thenew_valueproperty to your value. Most of the time this value is set\ninstantaneously is in sync with thevalueproperty. However if this\nvalue is different from the standardvaluethe XS1 gateway is still\ntrying to update the value on the remote device. For some devices this\ncan take up to a couple of minutes (f.ex. FHT 80B heating).Updating Actuator InformationCurrently there isno callbackwhen the value is finally updated soyou have to update the device information manuallyif you want to\nget an update on its current state:actuator.update()After that the usual methods likeactuator.value()will respond with\nthe updated state.Executing Actuator FunctionsIf you have defined function presets for a device you can get a list of\nall functions using:functions=actuator.get_functions()and print them like this:forfunctioninfunctions:print(function)to execute one of the functions type:function.execute()This will (like set_value) update the device state immediately with the\ngateways response. Remember though that there can be a delay for sending\nthis value to the actual remote device like mentioned above.Retrieve a List of SensorsTo retrieve a list of all 64 sensors use the following call:sensors=api.get_all_sensors()Just like with actuators you can filter the elements byenabledanddisabledstate using:enabled_sensors=api.get_all_sensors(True)This will return a list ofXS1Sensorobjects which is the base\nclass for all sensors.You can print basic information about them like this:forsensorinsensors:print(\"Sensor \"+str(sensor.id())+\": \"+sensor.name()+\" (\"+str(sensor.value())+\")\")Just like mentioned above you can also use:forsensorinsensors:print(sensor)or:sensor_1=api.get_sensor(1)to retrieve a specific sensor.Updating Sensor InformationJust like with actuators there is no automatic updates for sensors\neither. To get a state update from the XS1 gateway for your sensor\nobject call:sensor.update()After that the complete state of this sensor is updated.Disabled DevicesThe XS1 allows up to 64 actuator and 64 sensor configurations. These 128\ndevice configurations are accessible via the HTTP API at any time - even\nwhen there is nothing configured for a specific device id/number.To check if a device has been configured (and enabled) in the XS1 web interface call:device.enabled()for both actuators and sensors alike.Get a device configurationSince version 2.0 it is possible to get and set device configurations on the XS1 using this library.Please have a look at theexample_config.pyfile to get an idea of how to retrieve a device configuration.Modify a device configurationBefore you proceedEvery configuration change will write to the internal flash memory of the XS1.\nPlease keep in mind that that the use flash memory can and will probably degrade when written too often.Copy a device configurationThere is a very detailed example in this project calledexample_config_copy_actuator.pythat will show you\nhow to copy a device configuration and also explains most of the important configuration parameters you will have\nto use to set a custom configuration. Keep in mind though that the configuration parameters can vary between device\ntypes and systems.ContributingGithub is for social coding: if you want to write code, I encourage contributions through pull requests from forks\nof this repository. Create Github tickets for bugs and new features and comment on the ones that you are interested in.Licensexs1-api-client by Markus Ressel\nCopyright (C) 2017 Markus Ressel\n\nThis program is free software: you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or\n(at your option) any later version.\n\nThis program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\nGNU General Public License for more details.\n\nYou should have received a copy of the GNU General Public License\nalong with this program. If not, see ."} +{"package": "xs3d", "pacakge-description": "xs3d: Compute cross sectional area for 3D image objectsimportxs3d# let binary image be a boolean numpy array# in fortran order that is 500 x 500 x 500 voxels# containing a shape, which may have multiple# connected components, representing e.g. a neuronbinary_image=np.load(...)# a point inside the shape (must be integer)vertex=np.array([200,121,78])# normal vector defining sectioning plane# it doesn't have to be a unit vector# vector can be of arbitrary orientation# This vector is given in voxel space,# not physical space (i.e. divide by anisotropy)!normal=np.array([0.01,0.033,0.9])# voxel dimensions in e.g. nanometersresolution=np.array([32,32,40])# cross sectional area returned as a floatarea=xs3d.cross_sectional_area(binary_image,vertex,normal,resolution)# optionally return a bitfield that tells you if the section# plane touched the image border, indicating a possible# underestimate of the area if the image is a cutout of# a larger scene.# if the bitfield is > 0, then some edge contact is made# the bitfield order is -x+x-y+y-z+z00# where - means left edge (0), and + means right edge (size-1)# and 0 means unusedarea,contact_warning=xs3d.cross_sectional_area(binary_image,vertex,normal,resolution,return_contact=True)# Returns the cross section as a float32 3d image# where each voxel represents its contribution# to the cross sectional areaimage=xs3d.cross_section(binary_image,vertex,normal,resolution,)# Get a slice of a 3d image in any orientation.# Note: result may be reflected or transposed# compared with what you might expect.image2d=xs3d.slice(labels,vertex,normal,anisotropy)Installationpip install xs3dCross Section CalculationWhen using skeletons (one dimensional stick figure representations) to create electrophysiological compartment simulations of neurons, some additional information is required for accuracy. The caliber of the neurite changes over the length of the cell.Previously, the radius from the current skeleton vertex to the nearest background voxel was used, but this was often an underestimate as it is sensitive to noise and divots in a shape.A superior measure would be the cross sectional area using a section plane that is orthogonal to the direction of travel along the neurite. This library provides that missing capability.How Does it Work?The algorithm roughly works as follows.Label voxels that are intercepted by the sectioning plane.Label the connected components of those voxels.Filter out all components except the region of interest.Compute the polygon formed by the intersection of the plane with the 8 corners and 12 edges of each voxel.Add up the area contributed by each polygon so formed in the component of interest."} +{"package": "xsampleproject", "pacakge-description": "A sample project that exists as an aid to thePython Packaging User Guide\u2019sTutorial on Packaging and Distributing\nProjects.This projects does not aim to cover best practices for Python project\ndevelopment as a whole. For example, it does not provide guidance or tool\nrecommendations for version control, documentation, or testing.The source for this project is available here.Most of the configuration for a Python project is done in thesetup.pyfile, an example of which is included in this project. You should edit this\nfile accordingly to adapt this sample project to your needs.This is the README file for the project.The file should use UTF-8 encoding and be written usingreStructuredText. It\nwill be used to generate the project webpage on PyPI and will be displayed as\nthe project homepage on common code-hosting services, and should be written for\nthat purpose.Typical contents for this file would include an overview of the project, basic\nusage examples, etc. Generally, including the project changelog in here is not\na good idea, although a simple \u201cWhat\u2019s New\u201d section for the most recent version\nmay be appropriate."} +{"package": "xsampletests", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xsamtools", "pacakge-description": "xsamtoolsxsamtools makes thesamtoolstooling fromhtslibandbcftoolsavailable through pypi packaging. These tools have been lightly\nmodified to allow merges on VCF streams without an index.Installationpip install xsamtoolsInstallation requires a C toolchain. Typically Ubuntu/Debian systems should have the following packages installed:libbz2-devliblzma-devlibcurl4-openssl-devlibncurses5-devlibcurl4-openssl-devmay be omitted at the cost of some cloud support features in htslib.UsageAfter successful installation, the following executables are available:samtools:htsfilebgziptabixbcftoolsxsamtools:merge_vcfs.pyxsamtools also provides Python tooling to create named (FIFO) pipes to Google Storage objects:from xsamtools import pipes\n\nreader = pipes.BlobReaderProcess(\"bucket-name\", \"read-key\")\nprint(\"reader path\", reader.filepath) # local FIFO filepath\n\nwriter_key = pipes.BlobWriterProcess(\"bucket-name\", \"writ-key\")\nprint(\"writer path\", writer.filepath) # local FIFO filepathThese streams appear as either readable or writable files on the filesystem. Such objects are not seekable.A utility method is also provided to merge VCFs from GS objects:from xsamtools import vcf\n\nvcf.combine(\"src-bucket-name\", [\"first-src-vcf-key\", \"second-src-vcf-key\"], \"dst-bucket-name\", \"dst-vcf-key\")There is no formal limit on the number of VCF keys. Care should be taken that the VCF objects provided are aligned by\nchromosome or the merge will fail.DockerA Docker image with xsamtools installed is published athttps://hub.docker.com/r/xbrianh/xsamtools"} +{"package": "xsanio-server", "pacakge-description": "UNKNOWN"} +{"package": "xsanta", "pacakge-description": "xsantaSecret Santa sender / receiver generatorInstallationpip install xsantaExampleIn python:>>> from secret import santa\n>>> invited = [\n... 'Iron Man', 'Captain America', 'Thanos', 'Hulk',\n... 'Black Widow', 'Thor', 'Loki', 'Wanda Maximoff',\n... ]\n>>> excluded = [\n... ('Iron Man', 'Captain America'),\n... ('Thor', 'Loki'),\n... ('Black Widow', 'Hulk'),\n... ]\n>>> santa.run(invited, excluded)\nThor \ud83c\udf81 >> Thanos \ud83c\udf81 >> Loki \ud83c\udf81 >> Hulk \ud83c\udf81 >> Iron Man \ud83c\udf81 >> Thor\nCaptain America \ud83c\udf81 >> Black Widow \ud83c\udf81 >> Wanda Maximoff \ud83c\udf81 >> Captain AmericaIn command line:python santa.py \"['Iron Man', 'Captain America', 'Thanos']\" --emoji=False\nCaptain America >> Thanos >> Iron Man >> Captain America"} +{"package": "xs-api", "pacakge-description": "No description available on PyPI."} +{"package": "xsar", "pacakge-description": "Python xarray library to use Level-1 GRD Synthetic Aperture Radar products"} +{"package": "xsarsea", "pacakge-description": "xsarsea aims at computing geophysical parameters (such as wind, waves or currents) from radar quantities"} +{"package": "xsarslc", "pacakge-description": "xsarslcFunctions for Sentinel-1 SLC productsthe main feature of this library is the SAR processor:graph TD;\n A[level-1 SLC] -->| SAR processor | B(level-1B XSP);This is a Work In Progress Library.Disclaimer: no warranty on the quality of output product at this stage.installationpipinstallgit+https://github.com/umr-lops/xsar_slcusageimportxsarslc"} +{"package": "xs-authserver", "pacakge-description": "A component of a School Server likeXS,XSCEorDXS.xs-authserverimplements a seamless web authentication service using XO\nlaptop registration capabilities. It is heavily inspired by the Moodle OLPC-XS\nauthentication plugin.Continuous integration statusPyPI status"} +{"package": "xsbe", "pacakge-description": "XSBE - XML Schema By ExampleXSBE is a novel library intended forrapid developmentof XML related python code.It takes the approach of using lightly annotated example XML documents to act as a schema. Using these schemas it can\nthen transform an XML document into a more friendly data structures built of dictionaries and lists such as you might\nexpect through parsing json or yaml.Copyright 2020 Philip CoulingPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."} +{"package": "xsc", "pacakge-description": "nlitDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nnlit--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallnlitnbdev# activate conda environment$condaactivatenlit# make sure the nlit package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the nlit package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/nlit.gitor fromconda$condainstall-cdsm-72nlitor frompypi$pipinstallnlitDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find\npackage manager specific guidelines oncondaandpypirespectively."} +{"package": "xscaffold", "pacakge-description": "No description available on PyPI."} +{"package": "x-scaffold", "pacakge-description": "No description available on PyPI."} +{"package": "xscale", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xscaler", "pacakge-description": "No description available on PyPI."} +{"package": "xscanner", "pacakge-description": "No description available on PyPI."} +{"package": "xscen", "pacakge-description": "VersionsDocumentation and SupportOpen SourceCoding StandardsDevelopment StatusA climate change scenario-building analysis framework, built with Intake-esm catalogs and xarray-based packages such as xclim and xESMF.For documentation concerningxscen, see:https://xscen.readthedocs.io/en/latest/FeaturesSupports workflows with YAML configuration files for better transparency, reproducibility, and long-term backups.Intake-esm-based catalog to find and manage climate data.Climate dataset extraction, subsetting, and temporal aggregation.Calculate missing variables throughintake-esm\u2019sDerivedVariableRegistry.Regridding powered byxESMF.Bias adjustment tools provided byxclim.InstallationPlease refer to theinstallation docs.AcknowledgmentsThis package was created withCookiecutterand theOuranosinc/cookiecutter-pypackageproject template."} +{"package": "xsconnect", "pacakge-description": "Generate pin assignment constraints for a given combination of XESS peripheral + motherboard + daughterboard.Free software: MIT licenseDocumentation:https://xesscorp.github.com/xsconnect.FeaturesAutomates the tedious process of creating FPGA pin assignments for a given combination\nof XESS FPGA board (e.g. XuLA2), motherboard (e.g. StickIt!) and\nperipheral board (e.g. StickIt! Audio I/O).Command-line version,xsconn, for batch-file operations.GUI version,gxsconn, for even easier interactive use.History0.1.4 (2016-11-04)Added support for StickIt! Rotary Encoder V2.0.Added support for StickIt! SmallButtons V1.0.Added support for StickIt! AudioIO V2.0.Added support for StickIt! QuadDAC V1.0.Added support for Logic Pod Mini V1.0.Added support for CAT Board.0.1.3 (2015-09-12)Replaced explicit scripts with entrypoints.0.1.2 (2015-07-14)Added definition file for the StickIt! Grove board.Removed travis testing requirement.0.1.1 (2015-06-01)Added generic peripheral device for getting FPGA pin assignments\nfor each connector pin of the StickIt! Board.0.1.0 (2015-05-25)First release on PyPI."} +{"package": "xsCorePy", "pacakge-description": "1.\u6dfb\u52a0\u65e5\u671f\u5de5\u5177\u7c7b 2.\u6dfb\u52a0json\u5de5\u5177\u7c7b"} +{"package": "xscrapers", "pacakge-description": "XSCRAPERSTheXSCRAPERSpackage provides an OOP interface to some simple webscraping techniques.A base use case can be to load some pages toBeautifulsoup Elements.\nThis package allows to load the URLs concurrently using multiple threads, which allows to safe an enormous amount of time.importxscrapers.webscraperaswsURLS=[\"https://www.google.com/\",\"https://www.amazon.com/\",\"https://www.youtube.com/\",]PARSER=\"html.parser\"web_scraper=ws.Webscraper(PARSER,verbose=True)web_scraper.load(URLS)web_scraper.parse()Note that herein, the data scraped is stored in thedataattribute of the webscraper.\nThe URLs parsed are stored in theurlattribute.Downloading the Firefox GeckodriverLinuxSeethis linkfor a good explanation.\nIn short, the steps are:Download the geckodriver from themozilla GitHub release page, note to change theXfor the version you want to downloadwgethttps://github.com/mozilla/geckodriver/releases/download/vX.XX.X/geckodriver-vX.XX.X-linux64.tar.gzExtract the file withtar-xvzf geckodriver*Make it executablechmod+x geckodriverIn the last step, the driver can be added to thePATHenvironment variable, moved to theusr/local/binfolder, or can be given as full path to theWebdriverclass asexe_pathargumentexportPATH=$PATH:/path-to-extracted-file/sudomv geckodriver /usr/local/bin/"} +{"package": "xscreenfilter", "pacakge-description": "No description available on PyPI."} +{"package": "xscreensaver-config", "pacakge-description": "xscreensaver_configPython parser for .xscreensaver config fileInstallationpip install xscreensaver-configfrom xscreensaver_config.ConfigParser import ConfigParser\nconfig = ConfigParser('/home/user/.xscreensaver')\n# Read config as dict\nprint(config.read())\n...\n\n# Update config\nconfig.update({'mode': 'one'})\n\n# Save config\nconfig.save()"} +{"package": "xsdata", "pacakge-description": "Naive XML Bindings for pythonxsData is a complete data binding library for python allowing developers to access and\nuse XML and JSON documents as simple objects rather than using DOM.The code generator supports XML schemas, DTD, WSDL definitions, XML & JSON documents. It\nproduces simple dataclasses with type hints and simple binding metadata.The included XML and JSON parser/serializer are highly optimized and adaptable, with\nmultiple handlers and configuration properties.xsData is constantly tested against theW3C XML Schema 1.1 test suite.Getting started$# Install all dependencies$pipinstallxsdata[cli,lxml,soap]$# Generate models$xsdatatests/fixtures/primer/order.xsd--packagetests.fixtures.primer>>># Parse XML>>>frompathlibimportPath>>>fromtests.fixtures.primerimportPurchaseOrder>>>fromxsdata.formats.dataclass.parsersimportXmlParser>>>>>>xml_string=Path(\"tests/fixtures/primer/sample.xml\").read_text()>>>parser=XmlParser()>>>order=parser.from_string(xml_string,PurchaseOrder)>>>order.bill_toUsaddress(name='Robert Smith',street='8 Oak Avenue',city='Old Town',state='PA',zip=Decimal('95819'),country='US')Check thedocumentationfor more \u2728\u2728\u2728FeaturesGenerate code from:XML Schemas 1.0 & 1.1WSDL 1.1 definitions with SOAP 1.1 bindingsDTD external definitionsDirectly from XML and JSON DocumentsExtensive configuration to customize outputPluggable code writer for custom output formatsDefault Output:Pure python dataclasses with metadataType hints with support for forward references and unionsEnumerations and inner classesSupport namespace qualified elements and attributesData Binding:XML and JSON parser, serializerPyCode serializerHandlers and Writers based on lxml and native xml pythonSupport wildcard elements and attributesSupport xinclude statements and unknown propertiesCustomize behaviour through configChangelog: 24.2.1 (2024-02-19)Fixed FieldInfo type errors (#949)Fixed private package names (#950)Changelog: 24.2 (2024-02-17)Added Dict encoder/decoder (#921)Deprecated Serializer config pretty_print/pretty_print_indentation\n(#942)Fixed lxml event writer to respect the encoding configuration\n(#940)Migrated documentation to mkdocs with markdownRefactored project docstrings"} +{"package": "xsdata-attrs", "pacakge-description": "xsdata powered by attrs!xsData is a complete data binding library for python allowing developers to access and\nuse XML and JSON documents as simple objects rather than using DOM.Now powered by attrs!Install$# Install with cli support$pipinstallxsdata-attrs[cli]Generate Models$# Generate models$xsdatahttp://rss.cnn.com/rss/edition.rss--outputattrsParsing document edition.rss\nAnalyzer input: 9 main and 0 inner classes\nAnalyzer output: 9 main and 0 inner classes\nGenerating package: init\nGenerating package: generated.rss...@attr.sclassRss:classMeta:name=\"rss\"version:Optional[float]=attr.ib(default=None,metadata={\"type\":\"Attribute\",})channel:Optional[Channel]=attr.ib(default=None,metadata={\"type\":\"Element\",})...XML Parsing>>>fromxsdata_attrs.bindingsimportXmlParser>>>fromurllib.requestimporturlopen>>>fromgenerated.rssimportRss>>>>>>parser=XmlParser()>>>withurlopen(\"http://rss.cnn.com/rss/edition.rss\")asrq:...result=parser.parse(rq,Rss)...>>>result.channel.item[2].title'Vatican indicts 10 people, including a Cardinal, over an international financial scandal'>>>result.channel.item[2].pub_date'Sat, 03 Jul 2021 16:37:14 GMT'>>>result.channel.item[2].link'https://www.cnn.com/2021/07/03/europe/vatican-financial-scandal-intl/index.html'Changelog: 23.8 (2023-08-12)Removed python 3.6 and 3.7 supportAdded official support for 3.11 and 3.12Set xsdata minimum version v23.5This project is still alive :)"} +{"package": "xsdata-ech", "pacakge-description": "eCH xsdata dataclassesProvidesxsdatadataclasses for swiss\ne-government standards defined byeCH.! JSON deserialization might return wrong classes, if they have the same structure.TestsRun the testspip install .[test]\ntoxReleasingBump versionpip install .[dev]\nbump2version {major|minor|patch}Update definitionsGenerate filespip install .[dev]\nxsdata generate xxx.xsdThen move the files and fix the imports.\nHistory0.2.0 (19.02.2024)0.1.0 (18.06.2023)Initial release.The MIT License (MIT)Copyright \u00a9 2023 Seantis GmbHPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \u201cSoftware\u201d), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies\nof the Software, and to permit persons to whom the Software is furnished to do\nso, subject to the following conditions:The above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \u201cAS IS\u201d, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\nTHE SOFTWARE."} +{"package": "xsdata-plantuml", "pacakge-description": "xsDataPlantUML pluginGeneratePlantUMLclass diagrams from xml\nschemas, wsdl definitions and directly from xml documents.Usage$pipinstallxsdata-plantuml$xsdatasamples/order.xsd--outputplantuml--packagesamples@startuml\n\nclass Items {\n +item : item[]\n}\nItems +-- item\nclass item {\n +productName : string\n +quantity : positiveInteger\n +USPrice : decimal\n +comment : string\n +shipDate : date\n +partNum : string\n}\nclass PurchaseOrderType {\n +shipTo : USAddress\n +billTo : USAddress\n +comment : string\n +items : Items\n +orderDate : date\n}\nclass USAddress {\n +name : string\n +street : string\n +city : string\n +state : string\n +zip : decimal\n +country : NMTOKEN\n}\nclass comment {\n +@value : string\n}\nclass purchaseOrder {\n}\npurchaseOrder *- PurchaseOrderType\n\n@enduml"} +{"package": "xsdata-pydantic", "pacakge-description": "xsdata powered by pydantic!xsData is a complete data binding library for python allowing developers to access and\nuse XML and JSON documents as simple objects rather than using DOM.Now powered by pydantic!Install$# Install with cli support$pipinstallxsdata-pydantic[cli]Generate Models$# Generate models$xsdatahttp://rss.cnn.com/rss/edition.rss--outputpydanticParsing document edition.rss\nAnalyzer input: 9 main and 0 inner classes\nAnalyzer output: 9 main and 0 inner classes\nGenerating package: init\nGenerating package: generated.rssfromdataclassesimportfieldfrompydantic.dataclassesimportdataclass@dataclassclassRss:classMeta:name=\"rss\"version:Optional[float]=field(default=None,metadata={\"type\":\"Attribute\",})channel:Optional[Channel]=field(default=None,metadata={\"type\":\"Element\",})...XML Parsing>>>fromxsdata_pydantic.bindingsimportXmlParser>>>fromurllib.requestimporturlopen>>>fromgenerated.rssimportRss>>>>>>parser=XmlParser()>>>withurlopen(\"http://rss.cnn.com/rss/edition.rss\")asrq:...result=parser.parse(rq,Rss)...>>>result.channel.item[2].title\"'A total lack of discipline': Clarissa Ward visits abandoned Russian foxholes\">>>result.channel.item[2].pub_date'Fri, 08 Apr 2022 22:56:33 GMT'>>>result.channel.item[2].link'https://www.cnn.com/videos/world/2022/04/08/ukraine-chernihiv-visit-ward-pkg-tsr-vpx.cnn'Changelog: 22.10 (2022-10-02)Initial Release"} +{"package": "xsdb", "pacakge-description": "UNKNOWN"} +{"package": "xsd-to-django-model", "pacakge-description": "No description available on PyPI."} +{"package": "xsd-to-vol", "pacakge-description": "xsd-to-volConvert XML Schema Definition files to voluptuous schemas.Binary file usageBasic usage:xml-to-vol-ischema.xsd-oschema.pyBasic pipe usage:catschema.xsd|xml-to-vol>schema.pyPipe through black formatter:catschema.xsd|xsd-to-vol|black->schema.pyAdvanced piping example with curl:curl-shttps://api-test.geofox.de/gti/public/geofoxThinInterfacePublic.xsd2>&1|xsd-to-vol|black->schema.pyYou can also mix input/output files and stdin/stdout.Library usageYou can also use thexml_to_volmethod to convert your schema:fromxsd_to_volimportxsd_to_volwithopen(\"schema.xsd\",'r')asschema_file:xsd=schema_file.read()print(xsd_to_vol(xsd))To DoWhile the generation should work for most xsd files, there are some features I'd\nlike to have in future versions:Only include used imports: Currently all possible voluptuous requirements\nare imported. The required imports can be determined.Tests: Gather different xsd schemas and build pytests to test the generation.Automatic code formatting: Run black over the code (without piping).Contributions are welcome!If you want to contribute to this, please read theContribution guidelines"} +{"package": "xsd-validator", "pacakge-description": "xsd_validatorValidates an XML file against XSDs, supports XSD version 1.1. Requires Java Runtime (version 8 or better).APIAssert thatmy.xmlis valid according to schemaschema.xsd:fromxsd_validatorimportXsdValidatorvalidator=XsdValidator('schema.xsd')validator.assert_valid('my.xml')A more complex schema may be split between several files, for example:schema.xsd,schema-aux.xsdandxml.xsd.\nJust pass them all to theXsdValidator:fromxsd_validatorimportXsdValidatorvalidator=XsdValidator('schema.xsd','schema-aux.xsd','xml.xsd')validator.assert_valid('my.xml')Sometimes you need to get all problems discovered. You can loop through the errors like this:fromxsd_validatorimportXsdValidatorvalidator=XsdValidator('schema.xsd','schema-aux.xsd','xml.xsd')forerrinvalidator('my.xml'):print(err)CLIYou can usexsd_validatormodule as an executable, like this:python-mxsd_validatorFor example:python-mxsd_validatorschema.xsdmy.xmlHelp:python-mxsd_validator-husage:xsd_validator[-h]xsd[xsd...]xml\n\nValidateanXMLfileagainsdXSDschema(supportsXSDversion1.1)positionalarguments:xsdXSDfilesxmlXMLfiletocheck\n\noptionalarguments:-h,--helpshowthishelpmessageandexit"} +{"package": "xsearch", "pacakge-description": "About The ProjectUse Python to search, export and analyse the search results of a long list of keywords.Built WithSeleniumA package to automate web browser interaction from Python.Getting StartedPrerequisitesPythonPython 3ChromeDownload GoogleChrome, and check the version through 'Help > About Google Chrome'.ChromeDriverDownload a driver to interface with the Chrome browser. Make sure it\u2019s consistent with Chrome version.link1link2link3InstallationIf you havepipon your system, you can simply install or upgrade the Python bindings:pip install searchAlternately, you can download the source code fromPyPI(e.g. xsearch-0.0.8.tar.gz), unarchive it, and run:python setup.py installUsageSearch Engines Supportedgoogle.comorgoogle.com.hkbaidu.combing.comorcn.bing.comsogou.comweixin.sogou.comCodeimportxsearchxsearch.search()Example\u8bf7\u8f93\u5165\u5bfc\u5165\u6587\u4ef6\u540d\uff0c\u652f\u6301txt/xlsxinput.txt\u8bf7\u8f93\u5165\u6307\u5b9a\u7ad9\u70b9\uff0c\u5982\u6709\u591a\u4e2a\u7528\u9017\u53f7\u5206\u9694\uff0c\u5982\u65e0\u8bf7\u76f4\u63a5\u56de\u8f66zhihu.com, 36kr.com\u8bf7\u8f93\u5165\u6307\u5b9a\u6587\u4ef6\u7c7b\u578b\uff0c\u5982\u6709\u591a\u4e2a\u7528\u9017\u53f7\u5206\u9694\uff0c\u5982\u65e0\u8bf7\u76f4\u63a5\u56de\u8f66\u8bf7\u8f93\u5165\u5bfc\u51fa\u6587\u4ef6\u540d\uff0c\u652f\u6301csv/jsonoutput.csv\u8bf7\u8f93\u5165\u9700\u8981\u63d0\u53d6\u7684\u5173\u952e\u8bcd\u7c7b\u578b\uff0c\u5982\u6709\u591a\u4e2a\u7528\u9017\u53f7\u5206\u9694\uff0c\u5982\u65e0\u8bf7\u76f4\u63a5\u56de\u8f66n,a,v\u8bf7\u8f93\u5165\u641c\u7d22\u57df\u540dgoogle.comLicenseThe project is under theMITlicense."} +{"package": "xsec", "pacakge-description": "xsec is a tool for fast evaluation of cross-sections, taking advantage\nof the power and flexibility of Gaussian process regression.For more information, please visit the GitHub repository\nathttps://github.com/jeriek/xsec."} +{"package": "xsect", "pacakge-description": "XSectAboutThis package contains tools for calculating structural member cross sectional\nproperties in Python. In addition, it contains a SQLite database of standard\ncross sectional properties for which data can be acquired via query functions\nor instantiated directly into a newCrossSectionobject.Calculable cross sectional properties include:Cross sectional areaCentroidSecond moment of the area (moment of inertia)Radius of gyrationSection modulusPrincipal anglesValues about the principal axes for the above propertiesComposite sections that consist of multiple shapes are also supported, such as those shown below. Here, the shapes shown in blue are added to the cross section, while those shown in red are subtracted cutouts.InstallationThe package may be installed viapipby running the below command:pip install xsectExamples UsagesThe following sections outline some possible uses for this package.Quick Access to PropertiesWhether you are performing quick calculations, perhaps through the use of\na Jupyter notebook, or a more complex calculation, you can useXSectto\nreduce the amount of input required for calculations. Rather than turning\nto references to lookup and manually input properties for members, you\ncan create cross sections simply by passing the name of the member into\nthe appropriate initializer. For example:>>> xsect.CrossSection.from_aisc('L8x8x1-1/8')\nCrossSection(name='L8X8X1-1/8', area=16.8, ...)If a property is not contained in the database, you can rapidly calculate\nthe properties given a series of (x, y) boundary points or use one of the\nbuilt-in cross section summary functions to calculate the properties\nfor a specific shape. For example:>>> odict = xsect.cruciform_summary(8, 8, 1.125)\n>>> odict\n{'area': 66.9375,\n 'x': 0.0,\n 'y': 0.0,\n 'width': 16.0,\n 'height': 16.0,\n 'inertia_x': 781.0517578125,\n 'inertia_y': 781.0517578125,\n 'inertia_j': 1562.103515625,\n 'inertia_xy': 0.0,\n 'inertia_z': 781.0517578125,\n 'gyradius_x': 3.415900115553699,\n 'gyradius_y': 3.415900115553699,\n 'gyradius_z': 3.415900115553699,\n 'elast_sect_mod_x': 97.6314697265625,\n 'elast_sect_mod_y': 97.6314697265625,\n 'elast_sect_mod_z': 97.6314697265625}This can be used to quickly generate a cross section by unwrapping the\ndictionary within theCrossSectioninitializer:>>> xsect.CrossSection('4L8x8x1.125', **odict)\nCrossSection(name='4L8x8x1.125', area=66.9375, ...)Design OptimizationIf you are creating a Python application for analyzing and optimizing\nstructures, you could useXSectto pull various cross sections from the\nstandard sections database to perform analysis via an iterative scheme.\nYou could also calculate some required properties for the member and use\na database filter to acquire the lightest cross section of a particular shape\ngiven that criteria. For example, if you were designing a member for a known\nmaximum tensile force, you could calculate its required cross sectional area\nand perform a filter similar to the below to get the lightest member:>>> xsect.filter_aisc([\"type='L'\", 'area>28'], order=['unit_weight'])\n type name T_F unit_weight area d\n0 L L12X12X1-1/4 F 96.4 28.4 12.0\n1 L L12X12X1-3/8 F 105.0 31.1 12.0This returns a data frame of all \"L\" shape sections with areas greater\nthan 28 in ascending order of unit weight. The first row is, naturally,\nthe lightest member available meeting those conditions.Likewise, if you are designing a brand new cross section, you could use\none of the provided shape functions or create your own custom function\nto generate its boundary points, then calculate the requisite properties\nfor your design.Database SourcesThe properties contained in the SQLite database are acquired from the following\nsources:AISC ShapesThe database includes steel shapes from the American Institute of Steel\nConstruction (AISC), which were taken from the below publicly available\nlocations. For variable descriptions, please consult the README included\nwith their data.AISC Shapes Database v15.0"} +{"package": "xsection", "pacakge-description": "xsection"} +{"package": "xsectron", "pacakge-description": "cross_sectionA cross section calculation handbook for studentsThis work is licensed under aCreative Commons Attribution-NonCommercial 4.0 International License.The python codes in this repository are licensed under MIT license.What are the goals of this handbook?Unified notation systemDerivation of cross section, tree-level and a bit loopElectromagnetism and weak interaction coveredReference of textbooks for each stepReference of literatures for final numerical resultsComparison to latest experiment resultsFocus on simplified theoryPython codes providedThe short-term plan: process to coverneutrino - leptonneutrino - quark & nucleusWIMP - nucleondark photon - electronaxion - electronHow to generate the handbookinsidenotefolder, runlatexmk -C && latexmk --lualatex main.tex --shell-escapeCredit of template usageThe template used in LaTex codes is modified based onPhysics Book Template, published at Overleaf underCreative Commons CC BY 4.0 license, byCharles Averill.0.0.0 / 2023-09-13Bump to v0.0.0 by @dachengx inhttps://github.com/dachengx/cross_section/pull/1New Contributors@dachengx made their first contribution inhttps://github.com/dachengx/cross_section/pull/1"} +{"package": "xseed-maxbox", "pacakge-description": "xseed-minicampus-python-script"} +{"package": "xseed-max-box-creation", "pacakge-description": "xseed-minicampus-python-script"} +{"package": "xseed-minicampus-creation", "pacakge-description": "xseed-minicampus-python-script"} +{"package": "xseer", "pacakge-description": "XSeerDeep learning for fast, accurate denoising of astronomical spectra.OverviewRequirementsXSeer is designed for use with Python 3 only. It has three requirements:Tensorflow 2.xAstropyNumpyTODO:Two functionsrewrite fits/write new fitsdisplay plot"} +{"package": "xseis2", "pacakge-description": "No description available on PyPI."} +{"package": "xsellco-api", "pacakge-description": "XSELLCO-API Python WrapperThis project provides a Python wrapper for interacting with theRepricer.com(aka Xsellco) API, simplifying the integration of Repricer.com's API features into Python applications. It offers both synchronous and asynchronous support to accommodate different programming needs, thanks in part to thehttpx library. Detailed API documentation can be found ateDesk Developers.Getting StartedThese instructions will give you a copy of the project up and running on\nyour local machine for development and testing purposes. See deployment\nfor notes on deploying the project on a live system.Installingpip install xsellco_apiFor Developing:Clone the repository and installrequirements-dev.txt:UsageThe library provides both synchronous (sync) and asynchronous (async_) interfaces for interacting with the Repricer.com API. Below are examples of how to use each interface:Synchronous Usagefromxsellco_api.syncimportRepricersrepricer=Repricers(user_name='your_username',password='your_password')repricer_data=repricer.get_report()print(repricer_data)# list of dictionaries# or# All classes support context manager usagewithRepricers(user_name='your_username',password='your_password')asrepricer:repricer_data=repricer.get_report()print(repricer_data)# list of dictionariesAsynchronous Usageimportasynciofromxsellco_api.async_importAsyncRepricersasyncdefmain():asyncwithAsyncRepricers(user_name='your_username',password='your_password')asrepricer:repricer_data=awaitrepricer.get_report()print(repricer_data)asyncio.run(main())Deprecation NoticePlease note that the xsellco_api.api module is deprecated and will be removed in future versions. Users are encouraged to switch to the sync or async_ modules for continued support.License"} +{"package": "xsendfile", "pacakge-description": "This WSGI application allows you to tell your Web server (e.g., Apache, Nginx)\nwhich file on disk to serve in response to a HTTP request. You can use this\nwithin your Web application to control access to static files or customize the\nHTTP response headers which otherwise would be set by the Web server, for\nexample.For more information, please read the documentation on:http://pythonhosted.org/xsendfile/"} +{"package": "xsendfile_middleware", "pacakge-description": "WSGI Middleware to Support X-Accel-RedirectDescriptionNginxhas a mechanism whereby, by returning anX-Accel-Redirectheader,\na web app may convince nginx to serve a static file directly.PEP 333defines a mechanism whereby an app server (or middleware)\ncan offer to serve files directly by providingwsgi.file_wrapperin theenviron.\nThis package provides a piece of WSGI middleware to take advantage of those\ntwo mechanisms.Despite the name of the package, currently this middleware only works\nwith nginx\u2019sX-Accel-Redirectmechanism. (It would probably be\nstraightforward to generalize it so that it worksX-Sendfile, but\nat the moment, I have no need for that.)Download & SourceThe source repository is ongithub.\nYou may submit bug reports and pull requests there.It is also available viaPyPI.UsageThe middleware isxsendfile_middleware.xsendfile_middleware.\nYou can call it directly, e.g.:from xsendfile_middleware import xsendfile_middleware\n\ndef main(**settings):\n \"\"\" Construct and return a filtered app.\n \"\"\"\n def my_app(environ, start_response):\n # ...\n return app_iter\n\n # wrap middleware around app\n return xsendfile_middleware(my_app)There is also a suitable entry point provided so that you can instantiate\nthe middleware from aPasteDeploy.inifile, e.g.:[app:myapp]\nuse = egg:MyEgg\n\n[pipeline:main]\npipeline = egg:xsendfile_middleware myappConfigurationX_REDIRECT_MAPOnce you have the middleware in place, the only configuration needed\n(or possible) is to set anX_REDIRECT_MAPkey in the WSGI environ.\nHow you do that depends on how you\u2019ve got things set up. If you are\nrunning your app underuwsgi, for example, then you can use something\nlike the following in yournginxconfig:location /app {\n uwsgi_pass 127.0.0.1:6543;\n include uwsgi_params;\n\n uwsgi_param X_REDIRECT_MAP /path/to/files/=/_redir_/;\n}\n\nlocation /_redir_/ {\n internal;\n alias /path/to/files/;\n}In this configuration, if your app returns an app_iter which is\nan instance of the file wrapper provided by the middleware, and\nthat wrapper wraps file at,e.g.,/path/to/files/dir/file.data,\nthe middleware will set anX-Accel-Redirect:/_redir_/dir/file.dataheader in the response. (This, hopefully, will cause nginx to send\nthe desired file directly to the client.)The format ofX_REDIRECT_MAPis a comma-separated list of\n\u201c/prefix/=/base_uri/\u201d mappings. As a short-cut, \u201c/prefix/\u201d\n(with no equals sign) means the same as \u201c/prefix/=/prefix/\u201d (anX-Accel-Redirectheader containing the original file name will be\nsent for matching paths.) The entries in the map are checked in\norder; the first matching entry wins. If none of the entries match,\nthen the middleware will pass the response on up the chain unmolested.Warning:\nThe parsing ofX_REDIRECT_MAPis rather simplistic. Things will\nprobably not go well if you try to include commas, equal signs,\nor any non-ASCII characters in either theprefixorbase_uri.\nAlso, do not include any extraneous white space inX_REDIRECT_MAP.AuthorThis package was written byJeff Dairiki.Changes0.1.1 (2016-10-28)(Release 0.1 does not exist. It had corrupt rST in its PKG-INFO\ncausing the README on PyPI not to be formatted.)No changes (other than test configuration) from 0.1a3. This package\nhas been used in production for years now \u2014 might as well drop the\n\u201calpha\u201d designation.TestingDrop support for python 3.2. Now tested under pythons 2.6, 2.7,\n3.3, 3.4, 3.5, pypy and pypy3.0.1a3 (2015-05-08)Brown bag. The previous release was unusable do to this bug:Make sure not to include unicode strings in the headers passed tostart_response.0.1a2 (2015-05-08)Py3k, pypy compatibility: the tests now run under python 2.6, 2.7,\n3.2, 3.3, 3.4, pypy and pypy3.0.1a1 (2013-12-11)Initial Release"} +{"package": "xsensing-client", "pacakge-description": "\u672c\u4ed3\u5e93\u662fXsensing\u7edf\u4e00AI\u63a5\u53e3\u5ba2\u6237\u7aef(Unified Artificial Intelligence Interface Client, UAIC)\u4ee3\u7801\u548c\u4f7f\u7528\u8bf4\u660e\u3002\u672c\u4ed3\u5e93\u63d0\u4f9b\u5ba2\u6237\u7aef\u3001API\u30021 About UAICXsensing\u7684\u7edf\u4e00AI\u63a5\u53e3(Unified Artificial Intelligence Interface, UAII)\u5206\u4e3a\u670d\u52a1\u7aefUAIS\u548c\u5ba2\u6237\u7aefUAIC\u3002\u670d\u52a1\u7aefUAIS\u8fd0\u884c\u5728GPU\u670d\u52a1\u5668\u4e0a\uff0c\u7edf\u4e00\u8c03\u5ea6\u4e0d\u540c\u7b97\u6cd5\u6a21\u5757\u3001\u7ba1\u7406\u6a21\u578b\u5e93\uff0c\u6267\u884cAI\u8ba1\u7b97\u4efb\u52a1\uff1b\u5ba2\u6237\u7aefUAIC\u8fd0\u884c\u5728\u5e94\u7528\u670d\u52a1\u5668\u4e0a\uff0c\u901a\u8fc7Socket\u4e0eUAIS\u901a\u8baf\uff0c\u53ef\u8fdc\u7a0b\u67e5\u770bUAIS\u8fd0\u884c\u60c5\u51b5\uff1b\u81ea\u5b9a\u4e49\u5904\u7406\u6d41\u7a0b\u3001\u7ba1\u9053\u548c\u6a21\u5757\uff1b\u7ba1\u7406UAIS\uff1b\u83b7\u53d6UAIS\u7684\u8f93\u51fa\u30022 Getting Started2.1 \u5b89\u88c5\u6e90\u7801\u5b89\u88c5gitclonehttps://github.com/zhangzhengde0225/xsensing_client.gitcdxsensing_clientpythonsetup.pyinstallpip\u5b89\u88c5pipinstallxsensing_client2.2 \u6837\u4f8bClient Examples\uff0c\u4e0b\u9762\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u5ba2\u6237\u7aef\u4ee3\u7801\u3002importxsensing_clientuaic=xsensing_client.UAIC(url='http://127.0.0.1:5000')# \u8fde\u63a5\u5230UAIS\u670d\u52a1\u5668uaic.ps()# \u67e5\u770b\u670d\u52a1\u5668\u6d41\u3001\u7ba1\u9053\u548c\u6a21\u5757\u7684\u72b6\u6001uaic.stop(stream=None,pipeline=None,module=None)# \u505c\u6b62\u6d41\uff0c\u65e0\u53c2\u6570\u65f6\uff0c\u505c\u6b62\u5168\u90e8\uff1b\u6307\u5b9a\u6d41\u65f6\u505c\u6b62\u6307\u5b9a\u7684\u6d41\uff1b\u6307\u5b9a\u7ba1\u9053\u6216\u6a21\u5757\u65f6\uff0c\u505c\u6b62\u4e0e\u4e4b\u76f8\u5173\u7684\u6240\u6709\u6d41uaic.get_cfg()# \u4ece\u670d\u52a1\u5668\u8bfb\u53d6\u5404\u6d41\u3001\u7ba1\u9053\u3001\u6a21\u5757\u7684\u9ed8\u8ba4\u914d\u7f6e\u6587\u4ef6\uff0c\u4fdd\u5b58\u5230\u672c\u5730\u3002uaic.configure(config_file='config.py')# \u4e0a\u4f20\u670d\u52a1\u7aef\u7684\u6d41\u3001\u7ba1\u9053\u548c\u6a21\u5757\u914d\u7f6e\u6587\u4ef6\uff0c\u66f4\u65b0\u670d\u52a1\u7aef\u914d\u7f6e\u3002uaic.start(stream=None)# \u542f\u52a8\u6d41\uff0c\u65e0\u53c2\u6570\u662f\u542f\u52a8\u6240\u6709\u6d41\uff1b\u6307\u5b9a\u6d41\u65f6\u542f\u52a8\u6307\u5b9a\u7684\u6d41\uff1b\u542f\u52a8\u6d41\u7684\u540c\u65f6\u8c03\u8d77\u6240\u6709\u76f8\u5173\u7ba1\u9053\u548c\u6a21\u5757\u3002uaic.scan(pipeline=None)# \u7aa5\u89c6\u6307\u5b9a\u7ba1\u9053\u7684\u8f93\u51fa\u30023 \u8be6\u7ec6\u6587\u6863\u5ba2\u6237\u7aef\u6587\u6863"} +{"package": "xsentinels", "pacakge-description": "OverviewVarious objects that allow for sentinel-like singletons for various purposes, including:Ones pre-defined in this library:DefaultNullAlso, Easily create your own custom singletons/sentinels types.\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiInstall# via pippipinstallxsentinels# via poetrypoetryaddxsentinelsQuick StartfromxsentinelsimportDefaultimportosdefmy_func(my_param=Default):ifmy_paramisDefault:# Resolve default value for parameter, otherwise None.my_param=os.environ.get('MY_PARAM',None)...LicensingThis library is licensed under the MIT-0 License. See the LICENSE file."} +{"package": "xseof", "pacakge-description": "xseofOverviewI/O library for the ESA EOF files.This package provides a set of \u201cdataclasses\u201d, comapible with thexsdataPython library, to access and make I/O operation on the XML files\nin the ESA Earth Observation Ground Segment File Format (EOF)[1].In particular, this package supports all the XML based orbit and attitude\nproducts described in[1].Project linksHome Page:https://github.com/avalentino/xseofDownload:https://pypi.org/project/xseofInstallationStandard installation viapip:$ pip install xseofInstallation viaconda:$ conda install -c avalentino xseofTestingMove to the the source directory root and run the following command:$ python3 -m pytestBasic usageLoad a generic orbit file:>>> import xseof\n>>> orbit = xseof.load(\n \"MA1_TEST_AUX_ORBRES_20210610T045753_20210610T065853_0001.EOF\")Access and print loaded data:>>> import pprint\n>>> orbit.earth_observation_header.fixed_header.notes = \"\"\n>>> pprint.pprint(orbit.earth_observation_header.fixed_header)\nFixedHeaderType(\n file_name='MA1_TEST_AUX_ORBRES_20210610T045753_20210610T065853_0001',\n file_description='FOS Orbit File',\n notes='',\n mission='MetOpSGA1',\n file_class='TEST',\n file_type='AUX_ORBRES',\n validity_period=ValidityPeriodType(\n validity_start='UTC=2021-06-10T04:57:53',\n validity_stop='UTC=2021-06-10T05:02:23'),\n file_version='0001',\n eoffs_version='3.0',\n source=SourceType(system='System Identification as per Ground '\n 'Segment File Format Standard '\n '(PE-TN-ESA-GS-0001)',\n creator='Creator Identification as per '\n 'Ground Segment File Format Standard '\n '(PE-TN-ESA-GS-0001)',\n creator_version='Creator Version '\n 'Identification as per '\n 'Ground Segment File Format '\n 'Standard '\n '(PE-TN-ESA-GS-0001)',\n creation_date='UTC=2022-06-23T10:06:43'))\n\n>>> print(orbit.data_block.list_of_osvs.count)\n10\n>>> pprint.pprint(orbit.data_block.list_of_osvs.osv[0])\nOsvType(tai='TAI=2021-06-10T04:57:17.817060',\n utc='UTC=2021-06-10T04:57:52.817060',\n ut1='UT1=2021-06-10T04:57:53.117059',\n absolute_orbit=999,\n x=PositionComponentType(value=Decimal('-1606749.988'), unit='m'),\n y=PositionComponentType(value=Decimal('-5677008.966'), unit='m'),\n z=PositionComponentType(value=Decimal('-4135675.595'), unit='m'),\n vx=VelocityComponentType(value=Decimal('-2876.652288'), unit='m/s'),\n vy=VelocityComponentType(value=Decimal('-3541.028256'), unit='m/s'),\n vz=VelocityComponentType(value=Decimal('5985.303441'), unit='m/s'),\n quality='0000000000000')Load an EOF file of a specific type:>>> from xseof import int_attref\n>>> quaternions = int_attref.load(\n \"MA1_TEST_INT_ATTREF_20210610T045753_20210610T065853_0001.EOF\")Load data form string:>>> from xseof import aux_orbres\n>>> filename = \"MA1_TEST_AUX_ORBRES_20210610T045753_20210610T065853_0001.EOF\"\n>>> with open(filename) as fd:\n... data = fd.read()\n>>> orbit = aux_orbres.from_string(data)LicanseCopyright 2022 Antonio ValentinoLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d);\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific langua[1](1,2)https://eop-cfi.esa.int/Repo/PUBLIC/DOCUMENTATION/SYSTEM_SUPPORT_DOCS/PE-TN-ESA-GS-0001%20EO%20GS%20File%20Format%20Standard%203.0%20signed.pdfVersion historyxseof v1.1.1 (27/12/2022)Improve robustness in EOF files detection.Improve support for element-tree imputs.xseof v1.1.0 (23/12/2022)Fix loading of Sentine-1 orbit form string.Newstrictoption (default:False) to enforce strict XML namespaces\nchecking inxseof.loadandxseof.from_string.Improve docstrings to clarify thatlxmlis needed to use anElementTreeas source for thexseof.loadandxseof.*.loadfunctions.\nA dedicated unit test has been added also.Test coverage improved.xseof v1.0.0 (20/11/2022)Initial release."} +{"package": "xsequence", "pacakge-description": "No description available on PyPI."} +{"package": "xsera", "pacakge-description": "Test version 1.1.2"} +{"package": "xserializer", "pacakge-description": "No description available on PyPI."} +{"package": "xserver", "pacakge-description": "No description available on PyPI."} +{"package": "xserverpy", "pacakge-description": "# Xserverpy[![Build Status](https://travis-ci.org/oarrabi/xserverpy.svg?branch=master)](https://travis-ci.org/oarrabi/xserverpy) [![Coverage Status](https://coveralls.io/repos/oarrabi/xserverpy/badge.svg?branch=master&service=github)](https://coveralls.io/github/oarrabi/xserverpy?branch=master)[![PyPI version](https://badge.fury.io/py/xserverpy.svg)](http://badge.fury.io/py/xserverpy)Xserverpy makes it possible to use Xcode bots from the command line.
          ![Preview](https://raw.githubusercontent.com/oarrabi/xserverpy/master/assets/preview.gif)# Use cases- Running Xcode server tasks, like new integration (ie. Build project) or list bots, without the need to install or run Xcode.- Build Xcode bots from another CI tool like Jenkins (see [Future milestones and improvements](#future-milestones-and-improvements).- You love ASCII progress bars (or Nikola Tesla's inventions)# Installation## Using brew (recommended)brew tap oarrabi/tapbrew install xserverpy## Using pippip install xserverpy# Usage## Authentication and Host informationAll of xserverpy command accept authentication and Xcode server host/port as flags. For example, in order to list all the bots you would run:xserverpy bots --host HOST --port PORT --user USER --pass PASSTo reduce duplication in calling consequent or future commands, you can run `init` subcommand to store these configuration on your machine.xserverpy init --host HOST --port PORT --user USER --pass PASSNow that you stored them, you can call all of xcserverpy subcommands without passing these stored arguments:xserverpy botsxserverpy integrations listxserverpy init flags:--host HOST Xcode server host--port PORT Xcode server host port, default 443--user USER Username to use for authentication--password PASSWORD Password to use for authentication--local Store configuration file in the local directoryNote:- Running `init` sotres a configuration file at `~/.xserverpy`.- Using `init --local` stores the configuration in the current directory## BotsList all bots [Demo](http://showterm.io/1e0d25570e5c65ab57cd0)xserverpy bots # pass host/user info or load from stored## IntegrationsList integrations per bot [Demo](http://showterm.io/5899725079c80c3026d9d)xserverpy integrations list --bot ---Integrate (build project) [Demo](http://showterm.io/bb69e715ba165d147edf5)xserverpy integrations new --bot ---Integrate and wait [Demo](http://showterm.io/4b61beb417fe4a5b1ba25)xserverpy integrations new --bot --wait---Show running integrations [Demo](http://showterm.io/eae3a3cabf806cc9fd84d)xserverpy integrations running---Cancel integrations (build project) [Demo](http://showterm.io/9bbb138149c147ca1c103)xserverpy integrations cancel --id ## Note on integrate and waitWhen using `xserverpy integrations new --wait`, xserverpy keeps polling Xcode server for updates on the running integrations. The default interval is .5s, you can control the behavior and the format of the progress using the following flags:--interval INTERVAL Interval to poll the server for updates, default .5s--no-tty Force non tty progress reporting# Future milestones and improvements- Create Jenkins plugin to embed Xcode server tasks in Jenkins- Implement show all pending integrations- Improve code coverage# AuthorOmar Abdelhafith[nsomar](http://nsomar.com), [nsomar medium](https://medium.com/@nsomar), [@ifnottrue](https://twitter.com/ifnottrue)"} +{"package": "xsession-manager", "pacakge-description": "xsession-managerSave and restore windows for X11 desktop environment like Gnome, and many other features.This project was written inBashoriginally. But now I'm completely rewriting it inPythonwhich obviously makes it way more flexible, extensible.If you are a Gnome 3 user and also want to use these similar features on Wayland, please giveAnother Window Session Managera try, it's a Gnome extension, much more faster thanxsm, and much more native experience on Gnome.InstallInstall dependenciesFedoradnfinstallpython3-develpython3-tkinterwmctrlInstallxsession-managervia PyPipip3installxsession-managerInstall xsession-manager via source codeMethod-1: Using pip.This method install xsession-manager in~/.local/lib/python3.9/site-packagesif you are a normal user, in/usr/local/lib/python3.9/site-packagesif you are root.cdthe_root_of_source_code\npipinstall.Method-2: Using setup.pyThis method install xsession-manager in/usr/local/lib/python3.9/site-packages.cdthe_root_of_source_code\nsudopython3setup.pyinstallCommon usageSave running windows as a X sessionSave all running GUI windows toxsession-defaultxsm-sSpecify a session name like,my-session-name, restore it later on by runningxsm -s my-session-name. This feature should be very helpful when you have multiple tasks to do and each task needs different GUI apps.xsm-smy-session-nameNote:It will save some window states, which include Always on Top and Always on Visible Workspace and will be used when executingxsm -rorxsm -ma.Close running windows except those apps with mutiple windows. It's better to leave them to the user to close by hand, some apps like JetBrain's IDEs may have their own session.xsm-cClose running windows include those apps with mutiple windows.xsm-c-imRestore the saved X sessionRestore all GUI apps using the saved session namedxsession-defaultxsm-rRestoregnome-system-monitorusing the saved session namedmy-session-namexsm-rmy-session-name-ignome-system-monitorMove running windows to their Workspaces according to the saved X sessionxsm-maList saved X sessionsxsm-lView the details of a saved X sessionsxsm-txsession-defaultFull usage:usage: xsm [-h] [-s [SAVE]] [-c [CLOSE_ALL ...]] [-im] [-r [RESTORE]] [-ri RESTORING_INTERVAL] [-pr [PR]] [-l] [-t [DETAIL]]\n [-x EXCLUDE [EXCLUDE ...]] [-i INCLUDE [INCLUDE ...]] [-ma [MOVE_AUTOMATICALLY]] [--version] [-v] [-vv]\n\noptions:\n -h, --help show this help message and exit\n -s [SAVE], --save [SAVE]\n Save the current session. Save to the default session if not specified a session name.\n -c [CLOSE_ALL ...], --close-all [CLOSE_ALL ...]\n Close the windows gracefully. Close all windows if only -c/--close-all present. Or close one or more\n apps if arguments provided, which supports , , or exactly the\n same as -x. For example: `xsm -c gedit 23475 0x03e00004`\n -im, --including-apps-with-multiple-windows\n Close the windows gracefully including apps with multiple windows\n -r [RESTORE], --restore [RESTORE]\n Restore a session gracefully. Restore the default session if not specified a session name.\n -ri RESTORING_INTERVAL, --restoring-interval RESTORING_INTERVAL\n Specify the interval between restoring applications, in seconds. The default is 2 seconds.\n -pr [PR] Pop up a dialog to ask user whether to restore a X session.\n -l, --list List the sessions.\n -t [DETAIL], --detail [DETAIL]\n Check out the details of a session.\n -x EXCLUDE [EXCLUDE ...], --exclude EXCLUDE [EXCLUDE ...]\n Exclude apps from the operation according to , , or . Require\n at least one value\n -i INCLUDE [INCLUDE ...], --include INCLUDE [INCLUDE ...]\n Include apps from the operation according to , , or . Require\n at least one value\n -ma [MOVE_AUTOMATICALLY], --move-automatically [MOVE_AUTOMATICALLY]\n Auto move windows to specified workspaces according to a saved session. The default session is\n `xsession-default`\n --version show program's version number and exit\n -v, --verbose Print debugging information\n -vv Print more debugging information, could contain sensitive infoIf you want to restore the previous X session automatically after loginHere is a solution. If you are using Fedora, create a file namedauto-restore-working-state.desktopand theExecshould be:xsm-prThen put this file into~/.config/autostart.For example:[Desktop Entry]\nName=Auto Restore saved X Windows\nComment=\nIcon=\nExec=xsm -pr\nTerminal=false\nType=Application\nX-GNOME-Autostart-Delay=20NOTE: You can also usexsession-managerinstead ofxsm.Todo:TODO"} +{"package": "xsessionp", "pacakge-description": "xsessionpOverviewA declarative window instantiation utility for x11 sessions, heavily inspired by tmuxp.InstallationFrompypi.org$ pip install xsessionpFrom source code$gitclonehttps://github.com/crashvb/xsessionp\n$cdxsessionp\n$virtualenvenv\n$sourceenv/bin/activate\n$python-mpipinstall--editable.[dev]UsageTL;DRDefine a configuration file(s) declaring the desired end state:# ~/.xsessionp/example.yml---desktop:0environment:xsp:makes_life_easywindows:-command:-/usr/bin/xed---new-windowcopy_environment:falsefocus:truedimensions:926x656hints:name:^Unsaved Document.*position:166,492-command:-/usr/bin/gnome-terminal----tmuxdesktop:0environment:GNOME_TERMINAL_SCREEN:\"\"dimensions:1174x710hints:name:^Terminal$class:^\\['gnome-terminal-server', 'Gnome-terminal'\\]$position:213,134shell:truestart_directory:/tmpA configuration can be instantiated using theloadcommand:$xsploadexample\nLoading:/home/user/.xsessionp/example.ymlCommandsThis packages makes available thexsessionpcommand, and the shorterxspalias.A listing of commands is available by executing:xsp --help. Command-specific usage is available by executing--helpafter the command (e.g.:xsp ls --help).close-windowCloses a managed window(s).$xspclose-window--target/home/user/.xsessionp/example.yml:window[0]:262512556\nClosedwindow:119537674learnCapture metadata from a graphically selected window. Intended to assist with developing workspace configurations.$xsplearn\n---\nwindows:\n-command:-nemo-/home/userdesktop:0dimensions:1667x918environment:-DBUS_SESSION_BUS_ADDRESS=unix:path/run/user/1000/bushints:name:^Home$position:1717,264list-windowsLists managed windows in a given format.$xsplist-windows\nIDXSP:NAMEDESKTOPPOSITIONDIMENSIONSNAME119537674/tmp/tmpqf3bcpzt/xclock.yml:window[0]:2625125560[25,49][300,300]xclock138412043/tmp/tmpqf3bcpzt/xclock.yml:window[1]:2625127110[25,399][300,40]xclockloadLoads an xsessionp workspace for each instance of CONFIG specified.$xsploadexample\nLoading:/home/user/.xsessionp/example.ymllsLists xsessionp workspace(s) discovered within each default configuration directory.$xspls\nexample\n$xspls--qualified\n/home/user/.xsessionp/example.ymlreposition-windowAligns the current position of a managed window(s) to match the embedded metadata.$xspreposition-window-t/tmp/tmpqf3bcpzt/xclock.yml:window[0]:262512556\nRepositionedwindow:119537674testPerform basic acceptance tests by launching two xclock instances on the current desktop$xsptest...\nLoading:/tmp/tmpqf3bcpzt/xclock.ymlversion$xspversion\nx.y.zConfigurationAny key defined at the root level (globals) will propagate to all windows as the default value for that key.\nGlobals can be overridden in individual window configurations (locals), or omitted by added a key with a \"no_\" prefix (e.g.: no_dimensions).\nKeys with ano_prefix have a higher precedence then those without.command (type:list,str)Command used to launch the window. Provided asargstosubprocess.Popen.copy_environment (type:bool, default:True)If true, the environment of xsessionp will be used as the base for launched windows. Otherwise, and empty environment will be used instead. This does not affect values declared viaenvironment.desktop (type:int)The X11 desktop to be assigned to the launched window. If not provided, desktop assignment is not performed, and defaults to the behavior of the underlying window manager.dimensions (type:str)The dimensions (geometry) to assigned to the launched window. Values should take the form of{width}x{height}or{width},{height}. If not provided, no sizing is performed.disabled (type:bool, default:False)If true, the window will not be selected when the configuration is loaded. This is intended to allow complex window configuration(s) to remain inline without needing to comment them.environment (typeDict[str, str])Key value pairs to be provided via the environment of the launched window. These values have precedence over the \"base\" environment; seecopy_environment.focus (type:bool, default:False)If true, the window will be activated after all windows have been launched. If more than one window contains this value, the value is ignored.hint_method (type:enum, values:AND,OR)Boolean method by whichhintsare evaluated.hints (type:Dict[str, str])Distinguishing characteristics of the launched window that can be used to identify (guess) amongst otherwise ambiguous deltas.Deterministically identifying the X11 window(s) that are created when a process is launched is difficult. Often theWM_PIDatom is missing, or doesn't align with the PID of the process that was invoked, for various reasons.\nAs such, a listing of X11 windows is captured bothbeforeandafterthe process is executed, and the difference (delta) is used to guess the correct window. If the size of the delta is equal to 1, then it is assumed to correspond to the executed process.\nIf the size of the delta is greater than 1, then these hints are used to restrict which window is selected.Common hints include:class,name,state, andtype. Hint values are compiled into regular expression patterns prior to evaluating.name (type:str, default:generated)Name (xsp:name) use to select windows when the configuration is loaded, and to identify the window when executing commands.position (type:str)The position to assigned to the launched window. Values should take the form of{x},{y}or{x}x{y}. If not provided, no positioning is performed.search_delay (type:float, default:0)The amount of time, in seconds, to wait before searching for launched windows. Seehintsfor an explanation of the methodology.shell (type:bool, default:False)If true,commandwill be executed via a shell. Provided asshelltosubprocess.Popen.snapped (type:bool, default:False)If true, supporting window managers will be instructed tosnap, rather than tile, the launched window.start_directory (type:str, default:/)The working directory of the launched window. Provided ascwdtosubprocess.Popen.start_timeout (type:int, default:3)The maximum amount of time, in seconds, to wait for launched windows to be visible, prior to sizing and positioning.tile (type:str)Mode to use when tiling the launched window. Tiling occurs after window sizing and positioning. If not specified, no tiling is performed.Supported Tiling ModesLinux Mint Cinnamon:BOTTOM,LEFT,LEFT_BOTTOM,LEFT_TOP,MAXIMIZE,NONE,RIGHT,RIGHT_BOTTOM,RIGHT_TOP,TOPEnvironment VariablesVariableDefault ValueDescriptionXSESSIONP_CONFIGDIR~/.xsessionpxsessionp configuration directory.DevelopmentSource Control"} +{"package": "xsettings", "pacakge-description": "IntroductionDocumentationInstallQuick StartLicensingIntroductionHelps document and centralizing settings in a python project/library.Facilitates looking up BaseSettings fromretrievers, such as an environmental variable retriever.Converts and standardizes any retrieved values to the type-hint on the setting attribute (such as bool, int, datetime, etc).Interface to provide own custom retrievers, to grab settings/configuration from wherever you want.Retrievers can be stacked, so multiple ones can be consulted when retrieving a setting.Seexsettings docs.Documentation\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiInstall# via pippipinstallxsettings# via poetrypoetryaddxsettingsQuick StartfromxsettingsimportEnvVarSettings,SettingsFieldfromxsettings.errorsimportSettingsValueErrorfromtypingimportOptionalimportdataclassesimportos# Used to showcase looking up env-vars automatically:os.environ['app_version']='1.2.3'# Used to showcase complex setting types:@dataclasses.dataclassclassDBConfig:@classmethoddeffrom_dict(cls,values:dict):returnDBConfig(**values)user:strhost:strpassword:str# Some defined settings:classMySettings(EnvVarSettings):app_env:str='dev'app_version:strapi_endpoint_url:strsome_number:int# For Full Customization, allocate SettingsField,# In this case an alternate setting lookup-name# if you want the attribute name to differ from lookup name:token:Optional[str]=SettingsField(name='API_TOKEN')# Or if you wanted a custom-converter for a more complex obj:db_config:DBConfig=SettingsField(converter=DBConfig.from_dict)# BaseSettings subclasses are singleton-like dependencies that are# also injectables and lazily-created on first-use.# YOu can use a special `BaseSettings.grab()` class-method to# get the current settings object.## So you can grab the current MySettings object lazily via# its `grab` class method:MySettings.grab().some_number=3assertMySettings.grab().some_number==3# You can also use a proxy-object, it will lookup and use# the current settings object each time its used:my_settings=MySettings.proxy()# Here I showcase setting a dict here and using the converter# I defined on the SettingsField to convert it for me:my_settings.db_config={'user':'my-user','password':'my-password','host':'my-host'}expected=DBConfig(user='my-user',password='my-password',host='my-host')# The dict gets converted automatically to the DBConfig obj:assertMySettings.grab().db_config==expected# If you set a setting with the same/exact type as# it's type-hint, then it won't call the converter:my_settings.db_config=expected# It's the same exact object-instance still (ie: not changed/converted):assertmy_settings.db_configisexpected# Will use the default value of `dev` (default value on class)# since it was not set to anything else and there is no env-var for it:assertmy_settings.app_env=='dev'# EnvVarSettings (superclass) is configured to use the EnvVar retriever,# and so it will find this in the environmental vars since it was not# explicitly set to anything on settings object:assertmy_settings.app_version=='1.2.3'# Any BaseSettings subclass can use dependency-injection:assertmy_settings.tokenisNonewithMySettings(token='my-token'):assertmy_settings.token=='my-token'# Parent is still consulted for any settings unset on child but set on parent:assertmy_settings.db_config==expected# Can set settings like you expect,# this will go into the child created in above `with` statement:my_settings.app_env='prod'assertmy_settings.app_env=='prod'# After `with` child is not the current settings object anymore,# reverts back to what it was before:assertmy_settings.tokenisNonetry:# If a setting is undefined and required (ie: not-optional),# and it was not set to anything nor is there a default or an env-var for it;# BaseSettings will raise an exception when getting it:print(my_settings.api_endpoint_url)exceptSettingsValueErrorase:assertTrueelse:assertFalsetry:# `SettingsValueError` inherits from both AttributeError and ValueError,# as the error could be due to either aspect; so you can also do an except# for either standard error:print(my_settings.api_endpoint_url)exceptValueErrorase:assertTrueelse:assertFalseLicensingThis library is licensed under the MIT-0 License. See the LICENSE file."} +{"package": "xs-ext", "pacakge-description": "\u6682\u65e0"} +{"package": "xsf_nester", "pacakge-description": "UNKNOWN"} +{"package": "xsforms", "pacakge-description": "UNKNOWN"} +{"package": "xsge-gui", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides a simple toolkit for adding GUIs to a SGE game\nas well as support for modal dialog boxes."} +{"package": "xsge-lighting", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides a simple interface for lighting."} +{"package": "xsge-particle", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides particle effects for the SGE."} +{"package": "xsge-path", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides paths for the SGE. Paths are used to make\nobjects move in a certain way."} +{"package": "xsge-physics", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides an easy-to-use framework for collision physics.\nThis is especially useful for platformers, though it can also be useful\nfor other types of games."} +{"package": "xsget", "pacakge-description": "xsgetConsole tools to download online novel and convert to text file.InstallationStable version From PyPI usingpipx:pipx install xsget playwrightplaywright installStable version From PyPI usingpip:python3 -m pip install xsget playwrightplaywright installLatest development version from GitHub:python3 -m pip install -e git+https://github.com/kianmeng/xsget.gitplaywright installxsgetxsget -husage: xsget [-l CSS_PATH] [-p URL_PARAM] [-g [FILENAME] | -c [FILENAME]] [-r][-t] [-b] [-bs SESSION] [-bd DELAY] [-q] [-d] [-h] [-V]URLxsget is a console app that crawl and download online novel.website: https://github.com/kianmeng/xsgetchangelog: https://github.com/kianmeng/xsget/blob/master/CHANGELOG.md\"issues: https://github.com/kianmeng/xsget/issues\"positional arguments:URL set url of the index page to crawloptional arguments:-l CSS_PATH, --link-css-path CSS_PATHset css path of the link to a chapter (default: 'a')-p URL_PARAM, -url-param-as-filename URL_PARAMuse url param key as filename (default: '')-g [FILENAME], --generate-config-file [FILENAME]generate config file from options (default: 'xsget.toml')-c [FILENAME], --config-file [FILENAME]load config from file (default: 'xsget.toml')-r, --refreshrefresh the index page-t, --testshow extracted urls without crawling-b, --browsercrawl by actual browser (default: 'False')-bs SESSION, --browser-session SESSIONset the number of browser session (default: 2)-bd DELAY, --browser-delay DELAYset the second to wait for page to load in browser (default: 0)-q, --quietsuppress all logging-d, --debugshow debugging log and stacktrace-h, --helpshow this help message and exit-V, --versionshow program's version number and exitexamples:xsget http://localhostxsget http://localhost/page[1-100].htmlxsget -g -l \"a\" -p \"id\" http://localhostxstxtxstxt -husage: xstxt [-pt CSS_PATH] [-pb CSS_PATH] [-la LANGUAGE] [-ps SEPARATOR][-rh REGEX REGEX] [-rt REGEX REGEX] [-bt TITLE] [-ba AUTHOR][-ic INDENT_CHARS] [-fw] [-oi] [-ow] [-i GLOB_PATTERN][-e GLOB_PATTERN] [-l TOTAL_FILES] [-w WIDTH] [-o FILENAME][-od OUTPUT_DIR] [-y] [-p] [-g [FILENAME] | -c [FILENAME]] [-m][-q] [-d] [-h] [-V]xstxt is a console app that extract content from HTML to text file.website: https://github.com/kianmeng/xsgetchangelog: https://github.com/kianmeng/xsget/blob/master/CHANGELOG.md\"issues: https://github.com/kianmeng/xsget/issues\"optional arguments:-pt CSS_PATH, --title-css-path CSS_PATHset css path of chapter title (default: 'title')-pb CSS_PATH, --body-css-path CSS_PATHset css path of chapter body (default: 'body')-la LANGUAGE, --language LANGUAGElanguage of the ebook (default: 'zh')-ps SEPARATOR, --paragraph-separator SEPARATORset paragraph separator (default: '\\n\\n')-rh REGEX REGEX, --html-replace REGEX REGEXset regex to replace word or pharase in html file-rt REGEX REGEX, --txt-replace REGEX REGEXset regex to replace word or pharase in txt file-bt TITLE, --book-title TITLEset title of the novel (default: '\u4e0d\u8be6')-ba AUTHOR, --book-author AUTHORset author of the novel (default: '\u4e0d\u8be6')-ic INDENT_CHARS, --indent-chars INDENT_CHARSset indent characters for a paragraph (default: '')-fw, --fullwidthconvert ASCII character to from halfwidth to fullwidth (default: 'False')-oi, --output-individual-fileconvert each html file into own txt file-ow, --overwriteoverwrite output file-i GLOB_PATTERN, --input GLOB_PATTERNset glob pattern of html files to process (default: '['./*.html']')-e GLOB_PATTERN, --exclude GLOB_PATTERNset glob pattern of html files to exclude (default: '[]')-l TOTAL_FILES, --limit TOTAL_FILESset number of html files to process (default: '3')-w WIDTH, --width WIDTHset the line width for wrapping (default: 0, 0 to disable)-o FILENAME, --output FILENAMEset output txt file name (default: 'book.txt')-od OUTPUT_DIR, --output-dir OUTPUT_DIRset output directory (default: 'output')-y, --yesyes to prompt-p, --purgeremove extracted files specified by --output-folder option (default: 'False')-g [FILENAME], --generate-config-file [FILENAME]generate config file from options (default: 'xstxt.toml')-c [FILENAME], --config-file [FILENAME]load config from file (default: 'xstxt.toml')-m, --monitormonitor config file changes and re-run when needed-q, --quietsuppress all logging-d, --debugshow debugging log and stacktrace-h, --helpshow this help message and exit-V, --versionshow program's version number and exitexamples:xstxt --input *.htmlxstxt --output-individual-file --input *.htmlxstxt --config --monitorCopyright and LicenseCopyright (C) 2021,2022,2023,2024 Kian-Meng AngThis program is free software: you can redistribute it and/or modify it under\nthe terms of the GNU Affero General Public License as published by the Free\nSoftware Foundation, either version 3 of the License, or (at your option) any\nlater version.This program is distributed in the hope that it will be useful, but WITHOUT ANY\nWARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A\nPARTICULAR PURPOSE. See the GNU Affero General Public License for more details.You should have received a copy of the GNU Affero General Public License along\nwith this program. If not, seehttps://www.gnu.org/licenses/."} +{"package": "xsge-tiled", "pacakge-description": "xSGE is a collection of higher-level extensions for the SGE which\nenhance the core functionality in an implementation-independent way.\nLike the SGE itself, they are distribted under the terms of the GNU\nLesser General Public License.This extension provides support for loading the JSON format of theTiled Map Editor. This allows you to use\nTiled to edit your game\u2019s world (e.g. levels), rather than building a\nlevel editor yourself."} +{"package": "xshape", "pacakge-description": "xshapeTools for working with shapefiles, topographies, and polygons in xarrayFree software: MIT licenseDocumentation:https://xshape.readthedocs.io.FeaturesRead a shapefile and obtain an xarray DataArray of field recordsDraw shapefile boundaries on gridded dataPlot xarray DataArray data indexed by shapefile records as a choroplethUsageGetting records for fields in a shapefileIn[1]:importxshapeIn[2]:fields,polygons=xshape.parse_shapefile(...:'tests/data/shapefiles/CA_counties/CA_counties',...:encoding='latin1')In[3]:fieldsOut[3]:Dimensions:(shape:58)Coordinates:*shape(shape)int640123456789101112131415161718...Datavariables:STATEFP(shape)0)].copy()...:ca['fips']=df['STATE']*1000+df['COUNTY']...:da=ca.set_index(['fips'])['POPESTIMATE2016'].to_xarray()...:da.coords['GEOID']=('fips',),list(map('{:05}'.format,da.fips.values))...:da=da.swap_dims({'fips':'GEOID'})In[9]:da.xshape.plot(...:'tests/data/shapefiles/CA_counties/CA_counties',...:encoding='latin1',...:cmap='YlGnBu');...:We can also combine the information from the fields with the data contained in the DataArray:In[10]:land_area=(....:fields....:.set_coords('GEOID')....:.swap_dims({'shape':'GEOID'})....:.ALAND.astype(float))In[11]:np.log(da/land_area).xshape.plot(....:'tests/data/shapefiles/CA_counties/CA_counties',....:encoding='latin1',....:cmap='YlGnBu');....:TODOUse shapefiles to reshape gridded/pixel dataHistory0.1.0 (2018-01-13)First release on PyPI."} +{"package": "xshell", "pacakge-description": "xshellRunxshell.embed(), you can do anything, in the Interactive Console.Installation$ pip3 install xshellUsageWrite this anywhere.xshell.embed('Are you ready?')"} +{"package": "xshg", "pacakge-description": "No description available on PyPI."} +{"package": "xshinnosuke", "pacakge-description": "XShinnosuke : Deep Learning FrameworkDescriptionsXShinnosuke(short asXS) is a high-level neural network framework which supports for bothDynamic GraphandStatic Graph, and has almost the same API toKerasandPytorchwithslightly differences.It was written by Python only, and dedicated to realize experimentations quickly.Here are some features of XS:Based onCupy(GPU version)/Numpyandnativeto Python.Withoutany other3rd-partydeep learning library.Keras and Pytorch style API, easy to start up.Supports commonly used layers such as:Dense, Conv2D, MaxPooling2D, LSTM, SimpleRNN, etc, and commonly used function:conv2d, max_pool2d, relu, etc.Sequentialin Pytorch and Keras,Modelin Keras andModulein Pytorch,all of them are supportedby XS.Training and inference supports for bothdynamic graphandstatic graph.Autogradis supported .XS is compatible with:Python 3.x (3.7 is recommended)==> C++ version1. API docs2. NotebookGetting startedCompared with Pytorch and KerasResNet18(5 Epochs, 32 Batch_size)XS_static_graph(cpu)XS_dynamic_graph(cpu)Pytorch(cpu)Keras(cpu)Speed(Ratio - seconds)1x-65.050.98x- 66.332.67x- 24.391.8x- 35.97Memory(Ratio - GB)1x-0.470.47x- 0.220.55x- 0.260.96x- 0.45ResNet18(5 Epochs, 32 Batch_size)XS_static_graph(gpu)XS_dynamic_graph(gpu)Pytorch(gpu)Keras(gpu)Speed(Ratio - seconds)1x-9.641.02x- 9.453.47x- 2.781.07x- 9.04Memory(Ratio - GB)1x-0.481.02x- 0.494.4x- 2.114.21x- 2.02XS holds the best memory usage!1. Static GraphThe core networks of XS is a model, which provide a way to combine layers. There are two model types:Sequential(a linear stack of layers) andFunctional(build a graph for layers).ForSequentialmodel:fromxs.nn.modelsimportSequentialmodel=Sequential()Using.add()to connect layers:fromxs.layersimportDensemodel.add(Dense(out_features=500,activation='relu',input_shape=(784,)))# must be specify input_shape if current layer is the first layer of modelmodel.add(Dense(out_features=10))Once you have constructed your model, you should configure it with.compile()before training or inference:model.compile(loss='cross_entropy',optimizer='sgd')If your labels areone-hotencoded vectors/matrix, you shall specify loss assparse_crossentropy, otherwise usecrossentropyinstead.Useprint(model)to see details of model:***************************************************************************Layer(type)OutputShapeParamConnectedto###########################################################################dense0(Dense)(None,500)392500---------------------------------------------------------------------------dense1(Dense)(None,10)5010dense0---------------------------------------------------------------------------***************************************************************************Totalparams:397510Trainableparams:397510Non-trainableparams:0Start training your network byfit():# trainX and trainy are ndarrayshistory=model.fit(trainX,trainy,batch_size=128,epochs=5)Once completing training your model, you can save or load your model bysave()/load(), respectively.model.save(save_path)model.load(model_path)Evaluate your model performance byevaluate():# testX and testy are Cupy/Numpy ndarrayaccuracy,loss=model.evaluate(testX,testy,batch_size=128)Inference throughpredict():predict=model.predict(testX)ForFunctionalmodel:fromxs.nn.modelsimportModelfromxs.layersimportInput,Conv2D,MaxPooling2D,Flatten,DenseX_input=Input(input_shape=(1,28,28))# (channels, height, width)X=Conv2D(8,(2,2),activation='relu')(X_input)X=MaxPooling2D((2,2))(X)X=Flatten()(X)X=Dense(10)(X)model=Model(inputs=X_input,outputs=X)model.compile(optimizer='sgd',loss='cross_entropy')model.fit(trainX,trainy,batch_size=256,epochs=80)Pass inputs and outputs layer toModel(), thencompileandfitmodel asSequentialmodel.2. Dynamic GraphFirst design your own network, make sure your network is inherited fromModuleandoverridethe__init__()andforward()function:fromxs.nn.modelsimportModulefromxs.layersimportConv2D,ReLU,Flatten,Denseimportxs.nn.functionalasFclassMyNet(Module):def__init__(self):super().__init__()self.conv1=Conv2D(out_channels=8,kernel_size=3)# don't need to specify in_channels, which is simple than Pytorchself.relu=ReLU(inplace=True)self.flat=Flatten()self.fc=Dense(10)defforward(self,x,*args):x=self.conv1(x)x=self.relu(x)x=F.max_pool2d(x,kernel_size=2)x=self.flat(x)x=self.fc(x)returnxThen manually set the training/ testing flow:fromxs.nn.optimizersimportSGDfromxs.utils.dataimportDataSet,DataLoaderimportxs.nnasnnimportnumpyasnp# random generate dataX=np.random.randn(100,3,12,12)Y=np.random.randint(0,10,(100,))# generate training dataloadertrain_dataset=DataSet(X,Y)train_loader=DataLoader(dataset=train_dataset,batch_size=10,shuffle=True)# initialize netnet=MyNet()# specify optimizer and critetionoptimizer=SGD(net.parameters(),lr=0.1)critetion=nn.CrossEntropyLoss()# start trainingEPOCH=5forepochinrange(EPOCH):forx,yintrain_loader:optimizer.zero_grad()out=net(x)loss=critetion(out,y)loss.backward()optimizer.step()train_acc=critetion.calc_acc(out,y)print(f'epoch ->{epoch}, train_acc:{train_acc}, train_loss:{loss.item()}')Building an image classification model, a question answering system or any other model is just as convenient and fast~AutogradXS autograd supports for basic operators such as:+, -, *, \\, **, etcand some common functions:matmul(), mean(), sum(), log(), view(), etc.fromxs.nnimportTensora=Tensor(5,requires_grad=True)b=Tensor(10,requires_grad=True)c=Tensor(3,requires_grad=True)x=(a+b)*cy=x**2print('x: ',x)# x: Variable(45.0, requires_grad=True, grad_fn=)print('y: ',y)# y: Variable(2025.0, requires_grad=True, grad_fn=)x.retain_grad()y.backward()print('x grad:',x.grad)# x grad: 90.0print('c grad:',c.grad)# c grad: 1350.0print('b grad:',b.grad)# b grad: 270.0print('a grad:',a.grad)# a grad: 270.0Here are examples ofautograd.InstallationBefore installing XS, please install the followingdependencies:NumpyCupy (Optional)Then you can install XS by using pip:$ pip install xshinnosukeSupportsfunctionaladmmmmreluflattenconv2dmax_pool2davg_pool2dreshapesigmoidtanhsoftmaxdropout2dbatch_normgroupnorm2dlayernormpad_2dembeddingTwo basic class:- Layer:DenseFlattenConv2DMaxPooling2DAvgPooling2DChannelMaxPoolingChannelAvgPoolingActivationInputDropoutBatchNormalizationLayerNormalizationGroupNormalizationTimeDistributedSimpleRNNLSTMEmbeddingZeroPadding2DAddMultiplyMatmulLogNegativeExpSumAbsMeanPow- Tenosr:ParameterOptimizersSGDMomentumRMSpropAdaGradAdaDeltaAdamWaiting for implemented moreObjectivesMSELossMAELossBCELossSparseCrossEntropyCrossEntropyLossActivationsReLUSigmoidTanhSoftmaxInitializationsZerosOnesUniformLecunUniformGlorotUniformHeUniformNormalLecunNormalGlorotNormalHeNormalOrthogonalRegularizeswaiting for implement.Preprocessto_categorical (convert inputs to one-hot vector/matrix)pad_sequences (pad sequences to the same length)ContactEmail:eleven_1111@outlook.com"} +{"package": "xshl-target", "pacakge-description": "Python Library for XSHL TargetJSON Schemaimportjsonfromxshl.targetimportTarget,Referencet=Reference([\"project:[\\\"mcode-cc\\\",\\\"xshl\\\"]@pypi.org/xshl-target/#https://xshl.org/schemas/1.1/definitions/target.json\",\"https://github.com/mcode-cc/py-xshl-target\",\"https://en.wikipedia.org/wiki/Object_database\",\"https://translate.yandex.ru?value.lang=en-ru&value.text=Targets\",\"https://en.wikipedia.org/wiki/Object_database\"],unique=True)t.insert(0,Target(\"https://github.com/mcode-cc/py-xshl-target\"))t.append(Target(**{\"@id\":\"https://xshl.org/schemas/1.1/definitions/target.json\",\"@type\":\"/xshl-target/\",\"base\":\"pypi.org\",\"entity\":[\"mcode-cc\",\"xshl\"],\"spot\":\"project\"}))print(json.dumps(t.dictionaries,ensure_ascii=False,sort_keys=True,indent=4))[{\"@id\":\"https://xshl.org/schemas/1.1/definitions/target.json\",\"@type\":\"/xshl-target/\",\"base\":\"pypi.org\",\"entity\":[\"mcode-cc\",\"xshl\"],\"spot\":\"project\"},{\"@type\":\"/mcode-cc/py-xshl-target\",\"base\":\"github.com\",\"spot\":\"https\"},{\"@type\":\"/wiki/Object_database\",\"base\":\"en.wikipedia.org\",\"spot\":\"https\"},{\"@context\":{\"value\":{\"lang\":\"en-ru\",\"text\":\"Targets\"}},\"base\":\"translate.yandex.ru\",\"spot\":\"https\"}]"} +{"package": "xsiftx", "pacakge-description": "UNKNOWN"} +{"package": "xsigma", "pacakge-description": "Introduction:Documentation:Win32:install doxygeninstall perlinstall graphvizUnix:sudo apt install doxygensudo apt install graphvizsudo apt install html"} +{"package": "xsim", "pacakge-description": "xSimManage MTN / MCI Account"} +{"package": "xsj-distributions", "pacakge-description": "No description available on PyPI."} +{"package": "xskillscore", "pacakge-description": "Metrics for verifying forecasts"} +{"package": "xSlack", "pacakge-description": "Slack cross-team channels"} +{"package": "xslcoverage", "pacakge-description": "With XSL Coverage you can trace the calls of your XSL stylesheetsand compute their coverage. Currently it works only with Saxon with the\nhelp of Tracer plugin provided by the package."} +{"package": "xslearn", "pacakge-description": "xslearnxslearn is a machine learning toolkit implemented by Python. (keep updating...)model examples(below are implemented models)- linear_modelPerceptronLogistic Regression- neighborsKNeighborsClassifier- naive_bayesNaiveBayesGaussianNaiveBayes- svmSVC- treeDecisionTreeClassifierID3C4.5CartDecisionTreeRegressor- ensembleBoostingAdaboostClassifierBaggingBaggingClassifierBaggingRegressorRandomForestClassifierRandomForestRegressor"} +{"package": "xslha", "pacakge-description": "xSLHAxSLHAis apythonparser for files written in the SLHA format. It is optimised for fast reading of a large sample of files.InstallationThe package can be installed viapip install xslhaand is loaded in python byimport xslhaReading a single spectrum fileReading a spectrum filefileand stroing the information in a class objectspcis done via the commandspc=xslha.read(file)One has afterwards access to the different information by using theValuecommand, e.gprint(\"tan(beta): \",spc.Value('MINPAR',[3]))\nprint(\"T_u(3,3): \",spc.Value('TU',[3,3]))\nprint(\"m_h [GeV]: \",spc.Value('MASS',[25]))\nprint(\"Gamma(h) [GeV]: \",spc.Value('WIDTH',25))\nprint(\"BR(h->W^+W^-): \",spc.Value('BR',[25,[-13,13]]))\nprint(\"Sigma(pp->N1 N1,Q=8TeV): \",spc.Value('XSECTION',[8000,(2212,2212),(1000021,1000021)]))produces the following outputtan(beta): 16.870458\nT_u(3,3): 954.867627\nm_h [GeV]: 117.758677\nGamma(h) [GeV]: 0.00324670136\nBR(h->W^+W^-): 0.000265688227\nSigma(pp->N1 N1,Q=8TeV): [[(0, 2, 0, 0, 0, 0), 0.00496483158]]Thus, the conventions are:for information given in the different SLHA blocks is returned by using using the name of the block as input as well as the numbers in the block as listthe widths of particles are returned via the keywordWIDHTand the pdg of the particlefor branching ratios, the keywordBRis used together with a nested list which states the pdg of the decay particle as well as of the final statesfor cross-sections the keywordXSECTIONis used together with a nested list which states the center-of-mass energy and the pdgs of the initial/final states. The result is a list containing all calculated cross-sections for the given options for the renormalisation scheme, the QED & QCD order, etc. (see the SLHA recommendations for details).Another possibility to access the information in the spectrum file is to look at the different dictionariesspc.blocks\nspc.widths\nspc.br\nspc.xsctionswhich contain all informationReading all spectrum files from a directoryIn order to read several spectrum files located in a directorydir, one can make use of the commandlist_spc=xslha.read_dir(dir)This generates a listlist_spcwhere each entry corresponds to one spectrum. Thus, one can for instance use[[x.Value('MINPAR',[1]),x.Value('MASS',[25])] for x in list_spc]to extract the input for a 2D-scatter plot.Fast read-in of many filesReading many spectrum files can be time consuming. However, many of the information which is given in a SLHA file is often not needed for a current study. Therefore, one can speed up the reading by extracting first all relevant information. This generates smaller files which are faster to read in. This can be done via the optional argumententriesforread_dir:list_spc_fast=xslha.read_dir(\"/home/$USER/Documents/spc1000\",entries=[\"# m0\",\"# m12\",\"# hh_1\"])`entriesdefines a list of strings which can be used to extract the necessary lines from the SLHA file by usinggrep. The speed improvement can be easily an order of magnitude if only some entries from a SLHA file are actually needed.SpeedThe impact of this optimisation for reading 1000 files is as follows:%%time\nlist_spc=xslha.read_dir(\"/home/$USER/Documents/spc1000\")\n\nCPU times: user 5.05 s, sys: 105 ms, total: 5.15 s\nWall time: 5.51 scompared to%%time\nlist_spc_fast=xslha.read_dir(\"/home/$USER/Documents/spc1000\",entries=[\"# m0\",\"# m12\",\"# hh_1\"])\n\nCPU times: user 147 ms, sys: 132 ms, total: 280 ms\nWall time: 917 msOne can also compares this with other available python parser:pylha:%%time\nall_spc=[]\nfor filename in os.listdir(\"/home/$USER/Documents/spc1000/\"): \n with open(\"~/Documents/spc1000/\"+filename) as f:\n input=f.read()\n all_spc.append(pylha.load(input))\n\nCPU times: user 21.5 s, sys: 174 ms, total: 21.7 s\nWall time: 21.7 spyslha{%%time\nall_spc=[]\nfor filename in os.listdir(\"/home/$USER/Documents/spc1000/\"): \n all_spc.append(pyslha.read((\"/home/$USER/Documents/spc1000/\"+filename)))\n\nCPU times: user 13.3 s, sys: 152 ms, total: 13.5 s\nWall time: 13.5 sReading spectra stored in one fileAnother common approach for saving spectrum files is to produce one huge file in which the different spectra are separated by a keyword.xSLHAcan read such files by setting the optional argumentseparatorforread:list_spc=xslha.read(file,separator=keyword)In order to speed up the reading of many spectra also in this case, it is possible to define the entries as well which are need:list_spc=xslha.read(file,separator=keyword,entries=list)In this casexSLHAwill produce first a smaller spectrum file usingcatandgrep. For instance, in order to read efficiently files produced withSSP, one can use:list_spc=xslha.read(\"SpectrumFiles.spc\",separator=\"ENDOFPARAMETERFILE\",entries=[\"# m0\", \"# m12\", \"# hh_1\"])Special blocksThere are some programs which use blocks that are not supported by the official SLHA conventions:HiggsBoundsexpects the effective coupling ratios in blocksHIGGSBOUNDSINPUTHIGGSCOUPLINGSBOSONSandHIGGSBOUNDSINPUTHIGGSCOUPLINGSFERMIONSwhich are differently order compared to other blocks (first the numerical entries are stated before the PDGs of the involved particles follow)SPhenoversion generated bySARAHcan calculate one-loop corrections to the decays. The results are given in the blocksDECAY1Lwhich appear in parallel toDECAYcontaining the standard calculation.xSLHAwill distinguish these cases when reading the file and offer the two following options forValuesin addtion:spc.Values('WIDTH1L',1000022)\nspc.Values('BR1L',[1000023,[25,1000022]])Writing filesFiles in the SLHA format can be written viaxslha.write(blocks,file)where it might be the best to use ordered dictionaries to define the blocks and the values in the blocks. For instanceimport collections\nout_blocks=collections.OrderedDict([\n ('MODSEL',collections.OrderedDict([('1', 1), ('2', 2),('6',0)])),\n ('MINPAR',collections.OrderedDict([('1', 1000.),('2', 2000),('3',10),('4',1),('5',0)]))\n])\nxslha.write(out_blocks,\"/home/$USER/Documents/LH.in\")"} +{"package": "xs-lib", "pacakge-description": "personal python liblegacy python lib seexsthunder/python-lib: useful python pieces of codecode and releasecode atxsthunder/xs_lib at masterupdatexs_lib/version.py at master\u00b7 xsthunder/xs_libmerge to releae and travis will deploy to pipTODOFeaturesFull test with traivis to make sure things are on rail.xs_lib.ismain.main(__name__, main)to define entrancexs_lib.common.IN_TRAVISandxs_lib.common.IN_JUPYTERto tell current state, also allow bash env setting totrueorfalseto overwrite.xs_lib.common.CLI_TESTis read from bash env to control cli.Install and RunInstall viaxs-lib \u00b7 PyPIpip install xs-libUse in Codeuse for singleipynbfileexport theipynbfileimportxs_lib.commonascommon# this will choose con tqdmforiincommon.tqdm(range(3)):print(i)nbe=common.NBExporter()nbe('./pdb.ipynb',to='./')use for projcetclonexsthunder/jupyter_dev_templateUse in clinb2py --helpoptional pakage tqdmconda install tqdmUsage suggestionadd#test_exportto top of the code cell which will be exported to test and standard file.add#exportto top ot the code cell which will be exported to standard file.useSure 1.4.7 - Documentation \u2014 sure 1.4.7 documentationfor#test_export.DevelopmentEnvironment Setupbash./config/create-env.shfor condadepsnot alldepsare necessary. only ipython are set in thesetup.py/deps.xs_lib.commonsupports dynamic import. feel free to import.to import other modules, please install corresponding deps first or you may come across import error.It's recommanded to install all packages listed increate-env.shcode structuresRefdeployment - How can I use setuptools to generate a console_scripts entry point which callspython -m mypackage? - Stack OverflowPackaging Python Projects \u2014 Python Packaging User Guidenotebook2scriptfromcourse-v3/nbs/dl2 at master \u00b7 fastai/course-v3"} +{"package": "xslide", "pacakge-description": "xslideTool for creating presentations.Accepts content specified in:markdowngrot- graphviz syntax overlay for generating graphsplain python stringsxplantsyntax (can build arbitrary html code)Outputs:statichtmlBasic usage:importxslideslide=xslide.XSlide(\"Title of example from README\")slide.markdown(\"\"\"\n# xslide\n\n- Can accept a `markdown`\n- Can draw graphs in `grot` (`graphviz` overlay)\n- Can use HTML in `xplant`\n\nAuthor: [Michal Kaczmarczyk](mailto:michal.s.kaczmarczyk@gmail.com),\n\n\"\"\")slide.next(\"Header of the next slide\")slide.markdown(\"This one contains a graph:\")withslide.make_graph(\"this_dot_name\",html_style=\"max-width: 55%;\")asg:stage_1=g.node(\"Stage 1\",shape=\"box3d\")stage_2=g.node(\"Stage\\n2\",shape=\"circle\",penwidth=\"3.1\")g.edge(stage_1,stage_2,penwidth=\"2.6\")sink=g.node(\"This\\nsinks\\nall\")fornin[\"alfa\",\"beta\",\"gamma\",\"delta\"]:ifn==\"gamma\":g.edge(stage_2,n,sink,penwidth=\"2.6\",color=\"#314289\")else:g.edge(stage_2,n,sink,color=\"#aabbcc\",style=\"dashed\")slide.flush()# makes a breakslide.markdown(\"\"\"\n*Markdown* with `nice_code` formatting. This example generates such a files:\n\n\\`\\`\\`\n >$ tree XSLIDE/examples/output/readme_example\n XSLIDE/examples/output/readme_example\n |-- index.html\n |-- readme_example_01.html\n |-- readme_example_01.html_this_dot_name.dot\n |-- readme_example_01.html_this_dot_name.dot.svg\n |-- readme_example_02.html\n |-- serve.py\n `-- xslide.css\n\\`\\`\\`\n\"\"\")# don't forget to:slide.store()Result can be seen in gitlab in:examples/output/readme_example/index.html"} +{"package": "xslots", "pacakge-description": "xslotsExample usage: Crack an n-digit codefromdatetimeimporttimedeltaimporttimefromxslotsimportSlotsslots=Slots(4,0,9,0)password=\"939614\"start=time.time()whileTrue:print(slots)s=\"\".join(str(slots)))ifs==password:end=time.time()print(f\"Hacked code{s}in{timedelta(seconds=end-start)}\")breakslots.increase()"} +{"package": "xslproxy", "pacakge-description": "Xsl transforming reverse proxy based ontwistedandlxmlInstallationpython3 -m pip install xslproxyUsageUsage: twist [options] plugin [plugin_options] xslproxy [options]\nOptions:\n --backend= Url to backend, no trailing slash [default: http://localhost]\n --help Display this help and exit.\n --listen= Listen port (strports syntax) [default: tcp:8080]\n --path= [default: A directory with xsl files]\n --version Display Twisted version and exit.Requests to one of the proxy endpoints will be forwarded to the backend. When a\nsuccessful result is returned from the backend, content is transformed using\nthe specified XSL stylesheets and sent to the client. The following proxy\nendpoints are available:/transform/{XSLPARAMS}All stylesheets and parameters specified in XSLPARAMS are applied and to the\nbackend response and the result is returned to the client withContent-Typeheader set toapplication/xml,text/htmlortext/plainaccording to themethodspecified in theelement of the last stylesheet in the chain.TheXSLPARAMSpath segement takes the followingkey=valuepairs. Each\npair separated by the ampersand (&) character:xsl[]Relative path to a stylesheet on the server (without.xslor.xsltextension). This parameter can be specified multiple times.xa[stylesheet-key]Stylesheet alias. Relative path to a stylesheet on the server (without.xslor.xslt. This parameter is usefull if the same stylesheet should\nbe applied multiple times with different parameters.xp[stylesheet-key][param-key]XPath parameter with the nameparam-keyfor the stylesheet specified instylesheet-key. The latter need to match one of the values specified viaxsl[]parameter.sp[stylesheet-key][param-key]String parameter with the nameparam-keyfor the stylesheet specified instylesheet-key. The latter need to match one of the values specified viaxsl[]parameter.LicenseThe software is subject to theAGPLv3or later license."} +{"package": "xslxObject", "pacakge-description": "xslxObjectObject approach to xslx files"} +{"package": "xsmc", "pacakge-description": "No description available on PyPI."} +{"package": "xsmiles", "pacakge-description": "XSMILES visualizations in Jupyter LabA Custom Jupyter Lab Widget to visualize SMILES-based and atom-based scores.Please CiteIf you use XSMILES, the use cases, its code, or the generated explanations, please cite our article:Article in preparation, a preprint should appear mid September!Heberle, H., Zhao, L., Schmidt, S., Wolf, T., & Heinrich, J. (2022). XSMILES: interactive visualization for molecules, SMILES and XAI scores. Article in preparation.@article{Heberle2022XSMILES,author={Heberle, Henry and Zhao, Linlin and Schmidt, Sebastian and Wolf, Thomas and Heinrich, Julian},doi={},journal={Article in preparation},month={},number={},pages={},title={{XSMILES: interactive visualization for molecules, SMILES and XAI scores}},volume={},year={2022}}Availability and examplesXSMILES main pageTBD Demo websiteHOW TO use XSMILES (JupyterLab notebook)More examples with JupyterLabTBD PiPY repositoryKNIME component? Check the main pageExample Notebook with a how-toTo use XSMILES with Jupyter Lab you need to install the package with pipand have internet connectionwhile using it.RDKit MinimalLib is downloaded by your browser.Please check this notebook to seehow to usethe tool:NotebookNote that it is only being tested withJupyter Lab. A reason for you to use Lab is the space available for visualizations, which is much better than in regular Jupyter notebooks. We also had problems with the installation with Jupyter notebooks.InstallationQuick example - create conda environment and installs xsmilescondacreate--namexsmiles_envpython=3.7-cconda-forge# create conda env with python 3.7condaactivatexsmiles_env# activate the created envcondainstall-cconda-forgejupyterlab# install jupyter labpipinstallxsmiles# if xsmiles is not in pip yet, try pip install xsmiles-0.2.2-py2.py3-none-any.whl# Download the most up to date whl from this repository's releases)jupyterlabexamples/xsmiles_examples.ipynb# run a notebook with jupyter labUninstallpip uninstall xsmilesrm -r /share/jupyter/labextensions/xsmilesjupyter labextension listDevelopmentPlease check theDEVELOPMENT.mdfile."} +{"package": "xsm-parser", "pacakge-description": "Executable State Model ParserParses an *.xsm file (Executable State Model) to yield an abstract syntax tree using python named tuplesWhy you need thisYou need to process an *.xsm file in preparation for populating a database or some other purposeInstallationCreate or use a python 3.11+ environment. Then% pip install xsm-parserAt this point you can invoke the parser via the command line or from your python script.From your python scriptYou need this import statement at a minimum:from xsm-parser.parser import StateModelParserYou then specify a path as shown:result = StateModelParser.parse_file(file_input=path_to_file, debug=False)Check the code inparser.pyto verify I haven't changed these parameters on you wihtout updating the readme.In either case,resultwill be a list of parsed scrall statements. You may find the header of thevisitor.pyfile helpful in interpreting these results.From the command lineThis is not the intended usage scenario, but may be helpful for testing or exploration. Since the parser\nmay generate some diagnostic info you may want to create a fresh working directory and cd into it\nfirst. From there...% xsm cabin.xsmThe .xsm extension is not necessary, but the file must contain xsm text. See this repository's wiki for\nmore about the xsm language. The grammar is defined in thestate_model.pegfile. (if the link breaks after I do some update to the code,\njust browse through the code looking for the state_model.peg file, and let me know so I can fix it)You can also specify a debug option like this:% xsm cabin.xsm -DThis will create a diagnostics folder in your current working directory and deposit a couple of PDFs defining\nthe parse of both the state model grammar:state_model_tree.pdfand your supplied text:state_model.pdf.You should also see a file namedxsm-parser.login a diagnostics directory within your working directory"} +{"package": "xsmpy", "pacakge-description": "xsmredis stream for python and rustpython installpip install xsmpy"} +{"package": "xsms", "pacakge-description": "A simple SMS client written in Python + Tkinter which uses the em73xx\nlibrary. Originally written for my Thinkpad X250 (which uses this chip)\nit was mainly written for use with xmobar - with a text-mode summary so\nyou can quickly see any unread messages, and a lightweight GUI to read\nand send messages.TODOclean-up the UI, make it match the xmonad style I have (using ttk\nstyle in xsms/style.py)reply, mark as [un]read, delete/archive functionalityInstallEither retrieve from pypi using pip:$ pip install xsmsor clone this repo, and install usingsetup.py:$ git clone https://github.com/smcl/xsms\n$ cd xsms\n$ python setup.py installUsingOnce xsms is installed you can either launch it standalone \u2026$ python -m xsms --device=/dev/ttyACM0\u2026 or add it to xmobarrc, like the below (which takes advantage of the\nability to specify the font via tags to easily get some icons from Font\nAwesome):-- assumes you have Font Awesome installed and used here:\n-- additionalFonts = [\"xft:FontAwesome-10\"],\nRun Com \"/usr/bin/python\" [ \"-m\", \"xsms\", \"-d\", \"/dev/ttyACM0\", \"-p\", \"1234\", \"-r\", \"\uf003\", \"-u\", \"\uf0e0 %d\" ] \"xsms\" 600,This will result in an xmobar entry like the below:xsms-xmobar.png\u2026 and if you want to be able to click the icon to raise the GUI, you\ncan:template = \"%StdinReader% }{ ... stuff ... %xsms% ... \"xsms-inbox.pngFor a quick reference of the switches and parameters supported, invokepython-mxms--help:$ python -m xsms --help\nusage: __main__.py [-h] [-d DEVICE] [-g] [-p PIN] [-r READ_FORMAT]\n [-u UNREAD_FORMAT]\n\nxsms - an sms client for linux systems with an em73xx modem\n\noptional arguments:\n -h, --help show this help message and exit\n -d DEVICE, --device DEVICE\n -g, --gui\n -p PIN, --pin PIN\n -r READ_FORMAT, --read_format READ_FORMAT\n -u UNREAD_FORMAT, --unread_format UNREAD_FORMATProblemsIf you\u2019ve having a problem like the below\u2026$ python -m xsms --device /dev/ttyACM0 --pin 1234\nTraceback (most recent call last):\n File \"/usr/lib/python2.7/runpy.py\", line 174, in _run_module_as_main\n \"__main__\", fname, loader, pkg_name)\n File \"/usr/lib/python2.7/runpy.py\", line 72, in _run_code\n exec code in run_globals\n File \"/home/sean/dev/py/xsms/xsms/__main__.py\", line 63, in \n modem = Modem(args.device, pin=args.pin)\n File \"/usr/local/lib/python2.7/dist-packages/em73xx-0.5-py2.7.egg/em73xx/modem.py\", line 23, in __init__\nmodule>\n self.device = serial.Serial(dev, bps, timeout=1)\n File \"/usr/lib/python2.7/dist-packages/serial/serialutil.py\", line 182, in __init__\n self.open()\n File \"/usr/lib/python2.7/dist-packages/serial/serialposix.py\", line 247, in open\n raise SerialException(msg.errno, \"could not open port {}: {}\".format(self._port, msg))\nserial.serialutil.SerialException: [Errno 16] could not open port /dev/ttyACM0: [Errno 16] Device or resource busy: '/dev/ttyACM0'\u2026 then it\u2019s possible that the ModemManager service is accessing the\ndevice already. It\u2019s not currently possible to use em73xx together with\nthe modem. You can kill it off and retry:$ sudo systemctl stop ModemManager\n$ python -m xsms --device /dev/ttyACM0 --pin 1234\n5"} +{"package": "xsmtplib", "pacakge-description": "An extension of standard smtplib, which supports proxy tunneling.Package works on Python 2.7+ and Python 3.5+.UsingPySocks.InstallationYou can installxsmtplibfromPyPIby running:pip install xsmtplibOr you can just download tarball / clone the repository and run:python setup.py installAlternatively, include justxsmtplib.pyin your project.Usagexsmtplibextends standard python smtplib, so it can be used instead without any compatibility issues.Connection to SMTP server via proxy can be done during instance initialization:from xsmtplib import SMTP\n\nserver = SMTP(host=\"smtp.example.com\", proxy_host=\"proxy.example.com\")\nserver.sendmail(\"user@example.com\", \"admin@example.com\", \"I have an issue. Please help!\")\nserver.quit()Alternatively, you can connect to SMTP server manually when you need to:from xsmtplib import SMTP\n\nserver = SMTP(timeout=30)\nserver.set_debuglevel(1)\nserver.connect_proxy(proxy_host=\"proxy.example.com\", host=\"smtp.example.com\")\nserver.helo(\"user@example.com\")\nserver.sendmail(\"user@example.com\", \"admin@example.com\", \"I have an issue. Please help!\")\ns.quit()Known issuesSMTPS (SSL SMTP) and LMTP connections via proxy are not supported yet.LicenseSeeLICENSEfile for more details."} +{"package": "xsnippet-cli", "pacakge-description": "xsnippet-cliis a simple command line interface for interacting withxsnippetservice. By means this script, you can easily post and receive\nsnippets directly from your terminal.UsageIt\u2019s very easy to use. You can paste the snippet this way$ xsnippet /path/to/fileor this way$ cat /path/to/file | xsnippetAs you can see the last method posts a some command output. It\u2019s very usefull\nto post the last few lines from logfile this way$ tail -n 5 nginx.log | xsnippetIt\u2019s important to note that you can specify a snippet language or tags.\nThats can be done by the following command$ cat setup.py | xsnippet -l python -t setuptools testIf you want to receive snippet just do the following command$ xsnippet -r snippet_idInstallation$ (sudo) pip install xsnippet-clior$ (sudo) easy_install xsnippet-clior$ wget http://git.io/xsnippet-cli.zip -O xsnippet-cli.zip\n$ unzip xsnippet-cli.zip && cd xsnippet-cli-master\n$ (sudo) python ./setup.py installMetaAuthor: Igor Kalnitsky License: BSD License"} +{"package": "xsnumpy", "pacakge-description": "No description available on PyPI."} +{"package": "xso", "pacakge-description": "xarray-simlab-odeThexsoframework for building and solving models based on ordinary differential equations (ODEs), an extension ofxarray-simlab.Xarray-simlab provides a generic framework for building computational models in a modular fashion and anxarrayextension for setting and running simulations using xarray'sDatasetstructure.Xarray-simlab-ode (XSO) extends the framework with a set of variables, processes and a solver backend, suited towards ODE-based models. It is designed for flexible, interactive and reproducible modeling workflows.Installation$pipinstallxsoIn a nutshellA highly simplified model based on ordinary differential equations is shown below.Create new model components by writing compact Python classes:importxso@xso.componentclassVariable:var=xso.variable(description='basic state variable',attrs={'units':'\u00b5M'})@xso.componentclassLinearGrowth:var_ext=xso.variable(foreign=True,flux='growth',description='external state variable')rate=xso.parameter(description='linear growth rate',attrs={'units':'$d^{-1}$'})@xso.fluxdefgrowth(self,var_ext,rate):returnvar_ext*rateCreate a new model just by providing a dictionary of model components:model=xso.create({'Var':Variable,'Growth':LinearGrowth},time_unit='d')Create an input xarray.Dataset, run the model and get an output xarray.Dataset:importnumpyasnpinput_ds=xso.setup(solver='solve_ivp',model=model,time=np.arange(1,10,.1),input_vars={'Var':{'value_label':'X','value_init':1},'Growth':{'var_ext':'X','rate':1.},})withmodel:output_ds=input_ds.xsimlab.run()4.Perform model setup, pre-processing, run, post-processing and visualization in a functional style, using method chaining:withmodel:batchout_ds=(input_ds.xsimlab.update_vars(input_vars={'Growth':{'rate':('batch',[0.9,1.0,1.1,1.2])}}).xsimlab.run(parallel=True,batch_dim='batch').swap_dims({'batch':'Growth__rate'}).Var__var_value.plot.line(x='time'))DocumentationDocumentation is hosted on ReadTheDocs:https://xarray-simlab-ode.readthedocs.ioContributingThe package is in the early stages of development, and contributions are very welcome. See GitHub Issues for specific issues, or raise your own.\nCode contributions can be made via Pull Requests on GitHub.\nCheck out the contributing guidelines for more specific information.Licensexarray-simlab-ode was created by Benjamin Post.\nIt is licensed under the terms of the BSD 3-Clause license.CreditsXarray-simlab-ode is an extension ofxarray-simlab, created by Beno\u00eet Bovy."} +{"package": "xsocs", "pacakge-description": "The X-ray Strain Orientation Calculation Software (X-SOCS) is a user-friendly software,\ndeveloped for automatic analysis of 5D sets of data recorded during continuous mapping measurements.\nX-SOCS aims at retrieving strain and tilt maps of nanostructures, films, surfaces or even embedded structures.DocumentationInstallationX-SOCS runs on Linux, Windows and macOS withPython>=3.7 and can be installed with:pip install xsocs[gui]or with conda:conda install -c conda-forge xsocsSeeHow to install XSocsfor details.Using XSOCSOnce installed, you can run X-SOCS from the console with either:xsocsOr:python -m xsocsSeeUsing X-Socs documentationand\nthevideo tutorials.LicenseThe source code of X-SOCS is licensed under theMIT license."} +{"package": "xsome", "pacakge-description": "UNKNOWN"} +{"package": "xson", "pacakge-description": "XML Encoding for JSONXSONis a Python package that supports the serialization of Python objects to\nXML documents according to theJSONxspecification (draft), as well as the\ndeserialization of JSONx documents to Python objects. The implementation aims at\nbeing API and CLI-compatible with Python\u2019s standardJSONpackage.RequirementsPython>= 3.5InstallTo useXSONin another project, it can be added tosetup.cfgas an install\nrequirement (if usingsetuptoolswith declarative config):[options]install_requires=xsonTo installXSONmanually, e.g., into a virtual environment, usepip:pip install xsonThe above approaches install the latest release ofXSONfromPyPI.\nAlternatively, for the development version, clone the project and perform a\nlocal install:pip install .UsageAPIExample:>>> import xson\n>>> out = xson.dumps({'foo': 42, 'bar': [3.14, 'baz', True, None]}, indent=4)\n>>> print(out) #doctest: +NORMALIZE_WHITESPACE\n\n\n 42\n \n 3.14\n baz\n true\n \n \n\n>>> dct = xson.loads(out)\n>>> print(dct)\n{'foo': 42, 'bar': [3.14, 'baz', True, None]}CLIA command line tool is available to validate, pretty-print, or convert between\nJSONx and JSON objects:xson-tool --helpor:python -m xson.tool --helpCopyright and LicensingLicensed under the BSD 3-ClauseLicense."} +{"package": "xsorted", "pacakge-description": "xsortedLikesortedbut using external sorting so that large data sets can be sorted, for example:>>> from random import random\n>>> from six.moves import xrange\n>>> from xsorted import xsorted\n>>> nums = (random() for _ in xrange(pow(10, 7)))\n>>> for x in xsorted(nums): passThe only restriction is that the items must be pickleable (or you can provide your own serializer for externalizing\npartitions of items).MotivationIt is sometimes necessary to sort a dataset without having to load the entire set into memory. For example, if you\nwant to group a very large csv file by one of it\u2019s columns. There are several ways in which this can be achieved, a\ncommon solution is to use the unix commandsort. However unixsortdoes not offer the flexibility of the python\ncsv module.xsortedattempts to generalize external sorting of any python iterable in a similar way in whichsortedgeneralises the sorting of any iterable.Installation$ pip install xsortedUsageJust likesorted\u2026>>> from xsorted import xsorted\n>>> ''.join(xsorted('qwertyuiopasdfghjklzxcvbnm'))\n'abcdefghijklmnopqrstuvwxyz'Withreverse\u2026>>> ''.join(xsorted('qwertyuiopasdfghjklzxcvbnm', reverse=True))\n'zyxwvutsrqponmlkjihgfedcba'And a customkey\u2026>>> list(xsorted(('qwerty', 'uiop', 'asdfg', 'hjkl', 'zxcv', 'bnm'), key=lambda x: x[1]))\n['uiop', 'hjkl', 'bnm', 'asdfg', 'qwerty', 'zxcv']The implementation details ofxsortedcan be customized using the factoryxsorter(in order to provide\nthe same interface assortedthe partition_size is treated as an implementation detail):>>> from xsorted import xsorter\n>>> xsorted_custom = xsorter(partition_size=4)\n>>> ''.join(xsorted_custom('qwertyuiopasdfghjklzxcvbnm'))\n'abcdefghijklmnopqrstuvwxyz'"} +{"package": "xsource", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xspace", "pacakge-description": "xspacePython library of virtual spaces for RL agent trainingsCreated byBaihan Lin, Columbia University"} +{"package": "xspear.btas2015", "pacakge-description": "Vulnerability of Speaker Verification under Realistic AttacksThis package is an extension to thebob.bio.spearpackage.It contains functionality to run speaker recognition experiments on theAVspoofdatabase.It is an extension to thebob.bio.spearpackage, which provides the basic scripts.For further information aboutbob.bio.spear, please readits Documentation.InstallationTo install this package \u2013 alone or together with otherPackages of Bob\u2013 please read theInstallation Instructions.\nForBobto be able to work properly, some dependent packages are required to be installed.\nPlease make sure that you have read theDependenciesfor your operating system.DocumentationFor further documentation on this package, please read theStable Versionor theLatest Versionof the documentation.\nFor a list of tutorials on this or the other packages ofBob, or information on submitting issues, asking questions and starting discussions, please visit its website."} +{"package": "xspear.fast_plda", "pacakge-description": "Toolchain for fast and scalable PLDA====================================This package contains scripts that run the fast and scalable PLDA [1] and two-stage PLDA [2]. The package uses the framework of Bob `Spear` for handling the protocol, the toolchain and doing the post-processing (whitening and length-normalization).If you use this package and/or its results, please you must cite the following publications:[1] The original Fast PLDA paper published at S+SSPR 2014::@inproceedings{Sizov2014,author = {Sizov, A and Lee, K.A. and Kinnunen, T.},title = {Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication},booktitle = {Proc. S+SSPR},year = {2014},url = {to appear},}[2] Two-stage PLDA applied for anti-spoofing:@article{Sizov2015,title={Joint Speaker Verification and Anti-Spoofing in the i-Vector Space},author={Sizov, A. and Khoury, E. and Kinnunen, T. and Wu, Z. and Marcel, S.},journal={Information Forensics and Security, {IEEE} Transactions on},volume={10},number={4},pages={821-832},year={2015},publisher={IEEE}}[3] The Spear paper published at ICASSP 2014::@inproceedings{Khoury2014,author = {Khoury, E. and El Shafey, L. and Marcel, S.},title = {Spear: An open source toolbox for speaker recognition based on {B}ob},booktitle = {IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)},year = {2014},url = {http://publications.idiap.ch/downloads/papers/2014/Khoury_ICASSP_2014.pdf},}Installation------------Just download this package and decompress it locally::$ wget http://pypi.python.org/packages/source/x/xspear.fast_plda/xspear.fast_plda-1.1.1.zip$ unzip xspear.fast_plda-1.1.1.zip$ cd xspear.fast_plda-1.1.1Use buildout to bootstrap and have a working environment ready forexperiments::$ python bootstrap.py$ ./bin/buildoutThis also requires that bob (== 1.2) is installed.Example of use--------------To reproduce our spoofing experiments you need to download the data$ wget http://www.idiap.ch/resource/biometric/data/TIFS2015.zip$ unzip TIFS2015.zipand modify necessary directories for the scripts/TIFS2015/reproduce_* shell scripts.For more details and options, please use --help option for the executable files in the bin/ directory:$ bin/ivec_whitening_lnorm.py --help.. _Spear: https://pypi.python.org/pypi/bob.spear/"} +{"package": "xspfclean", "pacakge-description": "XSPF Playlist files cleanerRemoves not found and empty entries from an xspf playlistInstallation:pip install xspfcleanUsage:xspfclean [-h] playlist"} +{"package": "xspf-fixup", "pacakge-description": "$ xspf_fixupA simple command line program to fix playlist (.xspffiles) with broken links.RefrencesSource code in GithubPackage from Python package index (PyPI)RequirementsPython 3.6+InstallationFrom the Python package index (PyPI)Run:$pip3installxspf_fixupFrom sourceDownload fromGithubStanding inside the folder, run:$pip3install-rrequirements.txtFor install the dependencies and then run:$pip3install.Usageuser@host:~/tmp/xspf_fixup/examples$xspf_fixup--help\nUsage:xspf_fixup[OPTIONS][FILES]...Asimplecommandlineprogramtofixplaylist(.xspffiles)withbrokenlinks.Formoreinfo:(https://github.com/jbokser/xspf_fixup).\n\nOptions:-v,--versionShowversionandexit.-s,--showShow.xspffileinfoandexit.-o,--overwriteOverwritethe.xspffile.-r,--reportMakeareportinmarkdownforeach.xspffile.-h,--helpShowthismessageandexit.\nuser@host:~/tmp/xspf_fixup/examples$xspf_fixup-o./test.xspfTitleDurationLocationResult\n---------------------------------------------------------------1RocklandAgus03:01videos/RocklandAgus.mp4Fixed2HonkyTonkWay04:06videos/HonkyTonkWay.mp4Fixed3ForgeAheadAgos03:24videos/ForgeAheadAgos.mp4Fixed\n\nTrackscount:.....3(Fixed:3)Totalduration:...10:32\n\nuser@host:~/tmp/xspf_fixup/examples$user@host:~/tmp/xspf_fixup/examples$to_xspf-h\nUsage:to_xspf[OPTIONS]Asimplecommandlineprogramtogenerateaplaylist(.xspffile)withalistoffiles.Example:$lsexamples/videos/*.mp4|to_xspf.py>file.xspfFormoreinfo:(https://github.com/jbokser/xspf_fixup).\n\nOptions:-v,--versionShowversionandexit.-i,--input-fileFILENAMEInputtextfile(orstdin).-h,--helpShowthismessageandexit.\nuser@host:~/tmp/xspf_fixup/examples$lsvideos/*.mp4|to_xspf>files.xspf\nFile'videos/Forge Ahead Agos.mp4':Ok\nFile'videos/Honky Tonk Way.mp4':Ok\nFile'videos/Rockland Agus.mp4':Ok\n\nuser@host:~/tmp/xspf_fixup/examples$Why? (The rationale behind this)Mainly used bymeto fix the.xspffiles thatLuis \"la cosa muerta\" Musagave me.AuthorJuan S. Bokserjuan.bokser@gmail.com"} +{"package": "xspf-lib", "pacakge-description": "Library to work with xspf.RequirementsPython 3.8 or higherInstallingInstall and update viapip:pip install -U xspf-libExampleGenerating new playlist.>>> import xspf_lib as xspf\n>>> killer_queen = xspf.Track(location=\"file:///home/music/killer_queen.mp3\",\n title=\"Killer Queen\",\n creator=\"Queen\",\n album=\"Sheer Heart Attack\",\n trackNum=2,\n duration=177000,\n annotation=\"#2 in GB 1975\",\n info=\"https://ru.wikipedia.org/wiki/Killer_Queen\",\n image=\"file:///home/images/killer_queen_cover.png\")\n>>> anbtd = xspf.Track()\n>>> anbtd.location = [\"https://freemusic.example.com/loc.ogg\",\n \"file:///home/music/anbtd.mp3\"]\n>>> anbtd.title = \"Another One Bites the Dust\"\n>>> anbtd.creator = \"Queen\"\n>>> anbtd.identifier = [\"id1.group\"]\n>>> anbtd.link = [xspf.Link(\"link.namespace\", \"link.uri.info\")]\n>>> anbtd.meta = [xspf.Meta(\"meta.namespace\", \"METADATA_INFO\")]\n>>> playlist = xspf.Playlist(title=\"Some Tracks\",\n creator=\"myself\",\n annotation=\"I did this only for examples!.\",\n trackList=[killer_queen, anbtd])\n>>> print(playlist.xml_string())\nSome TracksmyselfI did this only for examples!.2020-02-03T14:29:59.199202+03:00file:///home/music/killer_queen.mp3Killer QueenQueen#2 in GB 1975https://ru.wikipedia.org/wiki/Killer_Queenfile:///home/images/killer_queen_cover.pngSheer Heart Attack2177000https://freemusic.example.com/loc.oggfile:///home/music/anbtd.mp3id1.groupAnother One Bites the DustQueenlink.uri.infoMETADATA_INFO\n>>> playlist.write(\"some_tracks.xspf\")Parsing from file.>>> from xspf_lib import Playlist\n>>> playlist = Playlist.parse(\"some_tracks.xspf\")LicenseThe license of the project is MIT License - seeLICENSEfile for details."} +{"package": "xspharm", "pacakge-description": "xspharm: Xarray Interface for Spherical Harmonic TransformOverviewxspharmis an xarray-compatible library that facilitates spherical harmonic transforms. It leverages the computational efficiency ofpyspharmand the convenience ofxarraydata structures to provide an intuitive interface for processing geospatial data on a spherical domain.Quick StartTo installxspharm, run this command in your terminal:$pipinstallxspharmThis is the preferred method to install xspharm, as it will always install the most recent stable release.fromxspharmimportxspharmxsp=xspharm(grid_ds,grid_type='regular')# convert u anv v to streamfunction and velocity potentialsfvp_ds=xsp.uv2sfvp(u_ds,v_ds,ntrunc=24)# tri_truncate the fields (can be xarray DataArray or Dataset in same spatial coordinates with grid_ds)trunc_ds=xsp.truncate(field_ds,ntrunc=42)DocumentationDocumentationavailable athttps://xspharm.readthedocs.io.xspharmprovides a suite of methods to manipulate and transform geospatial datasets:truncate: Reduces the resolution of a data variable or an entire dataset to a specified spherical harmonic wavenumber.exp_taper: Applies tapering to mitigate the Gibbs phenomenon in spherical harmonic coefficients.uv2sfvp: Transforms zonal (u) and meridional (v) wind components into streamfunction (sf) and velocity potential (vp).uv2vordiv: Converts zonal (u) and meridional (v) wind components to vorticity and divergence fields.uv2absvor: Changes zonal (u) and meridional (v) wind components to absolute vorticity.sf2uv: Derives rotational wind components from a given streamfunction.vp2uv: Obtains divergent wind components from velocity potential.sfvp2uv: Integrates streamfunction and velocity potential to produce zonal (u) and meridional (v) wind components.AcknowledgmentsSpecial thanks toJeff Whitakerfor sharing thepyspharmlibrary, which forms the foundation of this package\u2019s capabilities; and toAndrew Dawsonfor inspiring with thewindspharmlibrary.LicenseDistributed under the BSD License.History0.1.2 (2023-11-04)Fix bugs and documentation0.1.1 (2023-11-03)Update documentation0.1.0 (2023-11-02)First release on PyPI."} +{"package": "xspider.coop", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xspike", "pacakge-description": "\u5b89\u88c5pipinstallxspike\u5b89\u88c5 Redis\u5728\u7ec8\u7aef\u4e2d\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\u540e\uff0c\u6839\u636e\u63d0\u793a\u5b89\u88c5 Redis \u5e76\u542f\u52a8 Redis \u6570\u636e\u7ef4\u62a4\u670d\u52a1\uff1axspikeGPU \u81ea\u52a8\u9009\u62e9\u3001\u6392\u961fimportxspikeasxqueuer=x.GPUQueuer()# Start the queuerqueuer.start()# Your code here# Stop the queuerqueuer.close()\u6279\u91cf\u542f\u52a8\u5b9e\u9a8c\u5c06\u5b9e\u9a8c\u542f\u52a8\u547d\u4ee4\u653e\u5728\u9879\u76ee\u76ee\u5f55\u4e0b\u7684 exp_plans/exp_demo/xxx.sh \u6587\u4ef6\u4e2d\uff0c\u6bcf\u6761\u547d\u4ee4\u4e4b\u95f4\u7528\u6362\u884c\u5206\u5272\uff0c\u793a\u4f8b\u5982\u4e0b\uff1aCUDA_VISIBLE_DEVICES=0pythonrun.py\\'lr=5e-2'\\'max_epochs=1'\\'lora_rank=512'\\'lora_alpha=1024'CUDA_VISIBLE_DEVICES=0pythonrun.py\\'lr=5e-3'\\'max_epochs=1'\\'lora_rank=1024'\\'lora_alpha=2018'# \u5176\u4ed6\u5b9e\u9a8c\u547d\u4ee4......\u5e76\u5728\u9879\u76ee\u76ee\u5f55\u4e0b\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1axx"} +{"package": "xspline", "pacakge-description": "XSplineAdvanced spline package that provides b-spline bases, their derivatives and integrals.InstallationQuickstart"} +{"package": "xsprofile", "pacakge-description": "xsprofileXSProfile is a Python package for handling and analysing time-series of geospatial cross-sections and profiles."} +{"package": "xspy", "pacakge-description": "welcome to my package"} +{"package": "xsrfprobe", "pacakge-description": "XSRFProbeThe Prime Cross Site Request Forgery Audit & Exploitation Toolkit.About:XSRFProbeis an advancedCross Site Request Forgery(CSRF/XSRF) Audit and Exploitation Toolkit. Equipped with a powerful crawling engine and numerous systematic checks, it is able to detect most cases of CSRF vulnerabilities, their related bypasses and futher generate (maliciously) exploitable proof of concepts with each found vulnerability. For more info on how XSRFProbe works, seeXSRFProbe Internalsonwiki.XSRFProbe Wiki\u2022Getting Started\u2022General Usage\u2022Advanced Usage\u2022XSRFProbe Internals\u2022GallerySome Features:Performsseveral types of checksbefore declaring an endpoint as vulnerable.Can detect several types of Anti-CSRF tokens in POST requests.Works with a powerful crawler which features continuous crawling and scanning.Out of the box support for custom cookie values and generic headers.AccurateToken-Strength DetectionandAnalysisusing various algorithms.Can generate both normal as well as maliciously exploitable CSRF proof of concepts.Welldocumented codeandhighly generalised automated workflow.The user is incontrol of everythingwhatever the scanner does.Has a user-friendly interaction environment with full verbose support.Detailed logging system of errors, vulnerabilities, tokens and other stuffs.Gallery:Lets see some real-world scenarios of XSRFProbe in action:Usage:For the full usage info, please take a look at the wiki's \u2014General UsageandAdvanced Usage.Installing via Pypi:XSRFProbe can be easily installed via a single command:pip install xsrfprobeInstalling manually:For the basics, the first step is to install the tool:python3 setup.py installNow, the tool can be fired up via:xsrfprobe --helpAfter testing XSRFProbe on a site, an output folder is created in your present working directory asxsrfprobe-output. Under this folder you can view the detailed logs and information collected during the scans.Version and License:XSRFProbev2.3release is aStage 5 Production-Ready (Stable)release and the work is licensed under theGNU General Public License (GPLv3).Warnings:Do not use this tool on a live site!It is because this tool is designed to perform all kinds of form submissions automatically which can sabotage the site. Sometimes you may screw up the database and most probably perform a DoS on the site as well.Test on a disposable/dummy setup/site!Disclaimer:Usage of XSRFProbe for testing websites without prior mutual consistency can be considered as an illegal activity. It is the final user's responsibility to obey all applicable local, state and federal laws. The author assumes no liability and is not exclusively responsible for any misuse or damage caused by this program.Author's Words:This project is basedentirely upon my own research and my own experience with web applicationson Cross-Site Request Forgery attacks. You can try going through the source code which is highly documented to help you understand how this toolkit was built. Usefulpull requests,ideas and issuesare highly welcome. If you wish to see what how XSRFProbe is being developed, check out theDevelopment Board.Copyright \u00a9@0xInfection"} +{"package": "xss-catcher", "pacakge-description": "See website for more info."} +{"package": "xssd", "pacakge-description": "Bug Reports and DevelopmentPlease report any problems tothe GitLab issuesDescriptionThis module provides a way to validate data from many different file formats with a condensed\nXML Schema (XSD) subset. Errors are returned using a mirror-tree pattern instead of an exception\nbased invalidation.Based on xsd and xml validation, this is an attempt to provide those functions\nwithout requiring xml and to allow errors to be fed into machine readable mechanisms.Synopsefrom xssd import Validatorval = Validator( definition )\nerr = val.validate( data )print err or \u201cAll is well!\u201dDefinitionsAn example definition for registering a user on a website:definition={'root':[{'name : 'username', 'type' : 'token' },{'name : 'password', 'type' : 'password' },{'name : 'confirm', 'type' : 'confirm' },{'name : 'firstName', 'type' : 'rname' },{'name : 'familyName', 'type' : 'name', 'minOccurs' : 0 },{'name : 'nickName', 'type' : 'name', 'minOccurs' : 0 },{'name : 'emailAddress', 'type' : 'email', 'minOccurs' : 1, 'maxOccurs' : 3 },[{'name':'aim','type':'index'},{'name':'msn','type':'email'},{'name':'jabber','type':'email'},{'name':'irc','type':'string'},],],'simpleTypes':{'confirm':{'base':'id','match':'/input/password'},'rname':{'base':'name','minLength':1},'password':{'base':'id','minLength':6},},'complexTypes':{},}DataAnd this is an example of the data that would validate against it:data={'username':'abcdef','password':'1234567','confirm':'1234567','firstName':'test','familyName':'user','nickName':'foobar','emailAddress':['foo@bar.com','some@other.or','great@nice.con'],'msn':'foo@msn.com',}We are asking for a username, a password typed twice, some real names, a nick name, between 1 and 3 email addresses and at least one instant message account, foo is an extra string of information to show that the level is arbitary. bellow the definition and all options are explained.Errors and ResultsThe first result you get is a structure the second is a boolean, the boolean explains the total stuctures pass or fail status.The structure that is returned is almost a mirror structure of the input:errors={'input':{'username':NO_ERROR,'password':NO_ERROR,'confirm':NO_ERROR,'firstName':NO_ERROR,'familyName':NO_ERROR,'nickName':NO_ERROR,'emailAddress':NO_ERROR,}},Simple TypesA simple type is a definition which will validate data directly, it will never validate lists or dictionaries.Each simpleType is defined as an item in the definition\u2019s \u2018simpleTypes\u2019 list.base - The name of another simple type to first test the value against.fixed - The value should match this exactly.pattern - Should be a regular expresion reference which matchs the value.minLength - The minimum length of a string value.maxLength - The maximum length of a string value.match - An XPath link to another data node it should match.notMatch - An XPath link to another data node it should NOT match.enumeration - An array reference of possible values of which value should be one.custom - Should contain a CODE reference which will be called upon to validate the value.minInclusive - The minimum value of a number value inclusive, i.e greater than or eq to (>=).maxInclusive - The maximum value of a number value inclusive, i.e less than of eq to (<=).minExclusive - The minimum value of a number value exlusive, i.e more than (>).maxExclusive - The maximum value of a number value exlusive, i.e less than (<).fractionDigits - The maximum number of digits on a fractional number.Complex TypesA complex type is a definition which will validate a dictionary. The optional very first structure, \u2018root\u2019 is a complex definition and follows the same syntax as all complex types. Each complex type is a list of data which should all occur in the hash, when a list entry is a hash it equates to one named entry in the hash data and has the following options:name - Required name of the entry in the hash data.minOccurs - The minimum number of the named that this data should have in it.maxOccurs - The maximum number of the named that this data should have in it.type - The type definition which validates the contents of the data.Where the list entry is an array, it will toggle the combine mode and allow further list entries With in it this allows for parts of the sturcture to be optional only if different parts of the stucture exist.Inbuilt TypesBy default these types are available to all definitions as base types.string - /^.*$/integer - /^[-]{0,1}d+$/index - /^d+$/double - /^[0-9-.]*$/token - /^w+$/boolean - /^1|0|true|false$/email - /^.+@.+..+$/date - /^dddd-dd-dd$/ + datetime\u2018time\u2019 - /^dd:dd$/ + datetimedatetime - /^(dddd-dd-dd)?[T ]?(dd:dd)?$/ + valid_date methodpercentage - minInclusive == 0 + maxInclusive == 100 + doubleTestingThe test suite provides the full supported schema and tests against itself to ensure sanity."} +{"package": "xssh", "pacakge-description": "SSH Multiplexer to allow parallel ssh command execution across multiple hosts."} +{"package": "xss-hmm-detect", "pacakge-description": "SVM XSS DETECT PackageThis is a simple example package for detecting XSS payload using SVM. You can uselinkto see project details. Our team is from Northeastern University Cybersecurity major."} +{"package": "xsskiller", "pacakge-description": "XSSKillerHerramienta automatizada que escanea los parametros de las URLS para verificar si es vulnerable XSS reflejadoInstalacionpip3installxsskillerUsoPara su mejor uso podrias usar el menu de ayudaBuscar XSS en el parametro de un URLBuscar XSS en una archivo de texto que contenga URL'sPodemos usar XSSKiller con otras herramientas usando las tuberiasBuscar texto reflejado"} +{"package": "xss-scan", "pacakge-description": "No description available on PyPI."} +{"package": "xss-scanner", "pacakge-description": "No description available on PyPI."} +{"package": "xss-svm-detect", "pacakge-description": "SVM XSS DETECT PackageThis is a simple example package for detecting XSS payload using SVM. You can uselinkto see project details. Our team is from Northeastern University Cybersecurity major."} +{"package": "xssterminal", "pacakge-description": "ExampleXSSTerminalDescriptionIts a tool for developing advanced xss payloads through multiple trials and errors. Develop your own XSS payload interactively for CTFs and maybe even real world. Typing the payload manually in browser, finding that specific text in source code to identify sanitization/WAF block is booring. This is the upgrade you need :muscle:FeaturesEasy to view response and sending requests in loop without lot of hassle.Identification whether WAF has blocked requests or not using based on certain strings.Saving of sessions and rerunning in future.Go version is archived but works.Installationpip install xssterminalpython3 setup.py installUsageusage: XSSTerminal [-h] [-u BASE_URL] [-p PAYLOAD] [-e ERROR_STRING | -s MATCH_STRING | -b BLIND_STRING] [-m {GET,POST}] [-o OUTPUT] [-r RESUME]\n\nXSS Terminal\n\noptional arguments:\n -h, --help show this help message and exit\n -u BASE_URL, --base-url BASE_URL\n Base URL\n -p PAYLOAD, --payload PAYLOAD\n Starting payload\n -e ERROR_STRING, --error-string ERROR_STRING\n Error string\n -s MATCH_STRING, --match-string MATCH_STRING\n Match string\n -b BLIND_STRING, --blind-string BLIND_STRING\n Blind error string\n -m {GET,POST}, --method {GET,POST}\n HTTP Method (Default get)\n -o OUTPUT, --output OUTPUT\n Output file name\n -r RESUME, --resume RESUME\n Filename to resume XSST session\n --banner Print banner and exit\n\nFor advanced usage with explanation:XSSTerminal Usage/ExplanationExampleUsing one GET parameter:./XSSTerminal.py -u https://baseurl.com/?v= -p 'hello.com\\'>
          z\nz\n
          description fields1.1.2 First usable public release"} +{"package": "xstatic-vis", "pacakge-description": "UNKNOWN"} +{"package": "xstatix", "pacakge-description": "STATiX (Space and Time Algorithm for Transients in X-rays)The Space and Time Algorithm for Transients in X-rays (STATiX) builds upon\ntools from the image and signal processing fields and in particular the\nMulti-Scale Variance Stabilisation Transform\n(Zhang et al. 2008;Starck et al. 2009)\nto provide a complete detection analysis pipeline optimised for finding\ntransient sources on X-ray imaging observations. Unlike standard source\ndetection codes, STATiX operates on 3-dimensional data cubes with 2-spatial\nand one temporal dimensions. It is therefore sensitive to short and faint\nX-ray flares that may be hidden in the background once the data cube is\ncollapsed in time to produce 2-dimensional images. Although the algorithm\nis motivated by transient source searches, it also provides a competitive tool\nfor the detection of the general, typically less variable, X-ray source\npopulation present in X-ray observations. See Ruiz et al. 2023 (in preparation)\nfor a detailed explanation of the algorithm.STATiX is distributed as a Python package. The current implementation\nonly allows the processing of data for the XMM-Newton EPIC-pn camera. In the near\nfuture we will extend the code for all XMM-Newton cameras. Upgrading the code\nfor other X-ray imaging missions is possible, but beyond our current capabilities.InstallationSTATix needs the following software and libraries for a correct installation:C/C++ compiler and makeCMakeCFITSIO(>V3.31)pkg-configIn Ubuntu (and other Debian based Linux distributions) these dependencies can be installed viaapt:sudo apt install gcc make cmake libcfitsio* pkg-configOnce these prerequisites are installed, STATiX can be easily installed usingpip:pip install xstatixAlthough the STATiX source detection pipeline does not need any additional software, some of its side functions related with XMM-Newton data manipulation need a working installation ofSAS. If all the initial data products are already available (images, data cubes, exposure maps, etc) SAS is not needed. Otherwise these products will be generated during running time if SAS is available. All SAS-related functions are in thexmmsasmodule.ExamplesWe provideJupyter notebooks and scriptswith examples on how to use STATiX\nwith XMM-Newton data."} +{"package": "xstatstests", "pacakge-description": "Statistical tests on xarray objects"} +{"package": "xstavka-parse-package", "pacakge-description": "##\u041f\u0430\u043a\u0435\u0442 \u0434\u043b\u044f \u0440\u0430\u0437\u0431\u043e\u0440\u0430 \u0442\u0430\u0431\u043b\u0438\u0446 \u0441\u043e \u0441\u0442\u0430\u0432\u043a\u0430\u043c\u0438 \u0441 \u0441\u0430\u0439\u0442\u0430https://1xstavka.ru/\u041f\u0440\u0438 \u0438\u0437\u043c\u0435\u043d\u0435\u043d\u0438\u0438 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u0441\u0430\u0439\u0442\u0430 \u043c\u043e\u0436\u0435\u0442 \u0441\u0442\u0430\u0442\u044c \u043d\u0435 \u0430\u043a\u0442\u0443\u0430\u043b\u044c\u043d\u044b\u043c*\u0414\u0430\u043d\u043d\u044b\u0435 \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u044e\u0442\u0441\u044f \u0432 html, \u0437\u0430\u0442\u0435\u043c \u043f\u0430\u0440\u0441\u044f\u0442\u0441\u044f \u0432 json##\u041f\u0440\u0438\u043c\u0435\u0440 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044ffrom xstavka_parse_package.parse import parse_list\nif __name__ == '__main__':\n url_list = [\n r'https://1xstavka.ru/line/Volleyball/',\n r'https://1xstavka.ru/line/Football/',\n r'https://1xstavka.ru/line/Tennis/',\n r'https://1xstavka.ru/line/Ice-Hockey/',\n ]\n parse_list(url_list)##\u0423\u0441\u0442\u0430\u043d\u043e\u0432\u043a\u0430pip install xstavka_parse_package\u041b\u0438\u0446\u0435\u043d\u0437\u0438\u044f\u041b\u0438\u0446\u0435\u043d\u0437\u0438\u044f MIT"} +{"package": "xsterminal", "pacakge-description": "No description available on PyPI."} +{"package": "xsthunder-python-lib", "pacakge-description": "personal python liblegacy python lib seexsthunder/python-lib-old: useful python pieces of codeTODO[x] fix three version replicates, inrebuild.cmd,x_lib.__init__,setup.py[x] create github repo[x] ex_command\u80fd\u7528\uff0c\u9ed8\u8ba4\u76ee\u5f55\u5c31\u5728jupyter\u76ee\u5f55\u4e0b\u3002\u5373\u5916\u90e8\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528x_lib.common.ex_command[x] save_and_export_notebook\u4f7f\u7528\u4e86./\u5c31\u662f\u672c\u76ee\u5f55\u4e0b\u8981\u6c42\u4e00\u5b9a\u6709script\uff1b\uff1b\u89e3\u51b3\u65b9\u6cd5\u662f\u901a\u8fc7import\u800c\u4e0d\u662fex_command\u7684\u65b9\u5f0f\u4fdd\u5b58\u6587\u4ef6[x] save_and_export_notebook\u4f7f\u7528\u4e86\u652f\u6301\u591a\u7ea7\u76ee\u5f55FeaturesFull test with traivis to make sure things are on rail.list of function seedocInstall and RunInstall viaxsthunder-python-lib \u00b7 PyPIpip install xsthunder-python-liborpip install xsthunder-python-lib --userUse in Codeuse for singleipynbfileexport theipynbfilenbe=common.NBExporter()nbe('./pdb.ipynb',to='./')use for projcetclonexsthunder/jupyter_dev_templateDevelopmentEnvironment Setupfor condadepsnot alldepsare necessary. only ipython are set in thesetup.py/deps.x_lib.commonsupports dynamic import. feel free to import.to import other modules, please install corresponding deps first or you may come across error.It's recommanded to install all packages listed increate-env.shRefdeployment - How can I use setuptools to generate a console_scripts entry point which callspython -m mypackage? - Stack OverflowPackaging Python Projects \u2014 Python Packaging User Guidenotebook2scriptfromcourse-v3/nbs/dl2 at master \u00b7 fastai/course-v3"} +{"package": "xstr", "pacakge-description": "xstrNew python3 strings just dropped.Installationpip3installxstrfromxstrimportustrfromxtrimportdstrfromxstrimporthstrorimportxstrorimporthstr# import dstr# import ustrHypenString -- hstr()fromxstrimporthstrx=hstr('hello new world and all who inhabit it.')print(x)# hello-new-world-and-all-who-inhabit-it.print(x.original())# hello new world and all who inhabit it.outputhello-new-world-and-all-who-inhabit-it.hello new world and all who inhabit it.DotString -- dstr()fromxstrimportdstrx=dstr('hello new world and all who inhabit it.')print(x)# hello.new.world.and.all.who.inhabit.it.print(x.original())# hello new world and all who inhabit it.outputhello.new.world.and.all.who.inhabit.it.hello new world and all who inhabit it.UnderlineString -- ustr()fromxstrimportustrx=ustr('hello new world and all who inhabit it.')print(x)# hello_new_world_and_all_who_inhabit_it.print(x.original())# hello new world and all who inhabit it.outputhello_new_world_and_all_who_inhabit_it.hello new world and all who inhabit it."} +{"package": "xs-transformers", "pacakge-description": "No description available on PyPI."} +{"package": "xstr-donaldguiles", "pacakge-description": "xstrNew python3 strings just dropped.Installationcd\nhttps://github.com/Donny-GUI/xstr.gitfromxstrimportustrfromxtrimportdstrfromxstrimporthstrorimportxstrorimporthstr# import dstr# import ustrHypenString -- hstr()fromxstrimporthstrx=hstr('hello new world and all who inhabit it.')print(x)# hello-new-world-and-all-who-inhabit-it.print(x.original())# hello new world and all who inhabit it.outputhello-new-world-and-all-who-inhabit-it.hello new world and all who inhabit it.DotString -- dstr()fromxstrimportdstrx=dstr('hello new world and all who inhabit it.')print(x)# hello.new.world.and.all.who.inhabit.it.print(x.original())# hello new world and all who inhabit it.outputhello.new.world.and.all.who.inhabit.it.hello new world and all who inhabit it.UnderlineString -- ustr()fromxstrimportustrx=ustr('hello new world and all who inhabit it.')print(x)# hello_new_world_and_all_who_inhabit_it.print(x.original())# hello new world and all who inhabit it.outputhello_new_world_and_all_who_inhabit_it.hello new world and all who inhabit it."} +{"package": "xstream", "pacakge-description": "XSTREAM combines the X25519 Elliptic Curve Diffie-Hellman functionwith HKDF and the STREAM construction for streaming authenticatedencryption. The result is an easy-to-use public key cryptosystem."} +{"package": "xstrip-auth", "pacakge-description": "xstrip-authCryptographically strong pseudorandom key generator based on the XStrip AlgorithmInstallingViaPyPI:pipinstallxstrip_authUsageGenerate a 256-bit key for usefromxstrip_authimportXStripKeyConstructkey=\"#P@$$W0R9\"construct=XStripKeyConstruct(key)# Creating a 16Bit key for use from the key under a md5 hash implementationconstruct.generateKey(hf='md5')# Prints# [md5](16): 'ec1a93e0f8d41d75ffb77914e7a31cbf'# Create a 256bit key for use from the key under the sha256 hash implementationconstruct.generateKey(hf='sha256')# Prints# [sha256](32): 'd6b05d17e2e15152c478825ca6e7adafd0045b0c7fd92850ead98bad0cced9a4'APIClass:XStripKey(hash, salt[, iterations][, hf])hash: The key, final content to be encapsulated by the instancesalt: The salt used to intensify the operationiterations: Number of iterations undergone to generate thehash. Default:100000hf: Hash function used for the operation. Default:'sha256'Encapsulate a generated key within an interfacing instance for managing the inherent contentTheXStripKeyclass is defined and exposed publicly by the module:fromxstrip_authimportXStripKeykey=XStripKey(bytes.fromhex('d4d64d71c71ed5365ddde126ca8e6a17301e5f9601a15119e53c2f91def21f11'),bytes.fromhex('422f487975c57bb648f3'))print(key.verify(\"#P@$$W0R9\"))# Prints# TrueXStripKey::hex(getter)Shows the encapsulated key in byte hex formatXStripKey::hf(getter)Returns the hash function of the keyXStripKey::salt(getter)Returns the salt of the key in bytesXStripKey::iterations(getter)Returns the number of iterations used in encoding the keyXStripKey::verify(key[, encoder])key: encoder: Returns: Verify whether or not the specifiedkeymatches the inherent key of theselfinstanceencoderis defined by any transformers that was used used in generating the construct else, this falls back to anoopfunction that returns its parameters\nReturns a boolean for the condition resultXStripKey::matchExec(key, fn[, *args][, encoder])key: fn: *args: encoder: Returns: Execute thefnfunction if thekeymatches the inherent key of theselfinstance by checkingself.verify(key,encoder)\nfn is called by arguments defined inargs(if-any)encoderis defined by any transformers that was used used in generating the construct else, this falls back to anoopfunction that returns its parameters\nReturns the return content of the functionfndeffn(value):print(\"Password Matches, arg:%d\"%value)key.matchExec(\"#P@$$W0R9\",fn,10)# Prints# Password Matches, arg: 10XStripKey::mismatchExec(key, fn[, *args][, encoder])key: fn: *args: encoder: Returns: Execute thefnfunction if thekeydoes not match the inherent key of theselfinstance by checkingself.verify(key,encoder)\nfn is called by arguments defined inargs(if-any)encoderis defined by any transformers that was used used in generating the construct else, this falls back to anoopfunction that returns its parameters\nReturns the return content of the functionfndeffn(value):print(\"Password Matches, arg:%d\"%value)key.mismatchExec(\"something\",fn,19)# Prints# Password Matches, arg: 19XStripKey::codes()Returns the octal representation of each character in a listXStripKey::export()Exports the entire key construct in base64 encoding parsable byXStripKey.parse()print(key.export())# Prints# b'MTAwMDAwOjQyMmY0ODc5NzVjNTdiYjY0OGYzL2Q0Z...OGU2YTE3MzAxZTVmOTYwMWExNTExOWU1M2MyZjkxZGVmMjFmMTE='XStripKey.parse(content)fn: The exported construct to be parsed\nReturns: Parse the base64 exported data fromXStripKey::exportprint(XStripKey.parse(key.export()))print(key==XStripKey.parse(key.export()))# Prints# [sha256](32): 'd4d64d71c71ed5365ddde126ca8e6a17301e5f9601a15119e53c2f91def21f11'# TrueClass:XStripKeyConstruct(key[, iterations])key: The key to be constructed oniterations: The number of times the kdf should apply the hash function to the key in the transformative processClass to generate series of hashed keys for a single key\nMaking the product pseudorandomly secure for every use of the same keyTheXStripKeyclass is defined and exposed publicly by the module:fromxstrip_authimportXStripKeyConstructXStripKey::generateKey([hf][, salt][, encoder])hf: The hash function to process the key on. Default:'sha256'salt: The hash to be used on the key when randomising the data. Default:py:os/randomencoder: The middleware transformative function. Default:noopReturns: Generates a special key for the encapsulated key under special conditions making the product completely random and untied to the operation\nHence, generating cryptographically secure keys everytime this method is calledencoderis defined by any transformers that was used used in generating the construct else, this falls back to anoopfunction that returns its parametersconstruct=XStripKeyConstruct(\"t0y$t0ry\")construct.generateKey()# [sha256](32): '5e53edcff3bc4dc5e06b243dd206e4dbba1be625361bd2db3c9599edec217f01'construct.generateKey()# [sha256](32): '907d183f27a75c23830906063494ff073942e3f74d21605f7b19b16a7d94df06'construct.generateKey('md5')# [md5](16): 'd38518dccec4a4ef1767c01e48095a2c'construct.generateKey('sha1')# [sha1](20): '42f405740cd7a35a283b44c1ee0bbf0c9812015b'DevelopmentBuildingFeel free to clone, use in adherance to thelicenseand perhaps send pull requestsgitclonehttps://github.com/miraclx/xstrip-auth.gitcdxstrip-auth# hack on codepip3install.--userLicenseApache 2.0\u00a9Miraculous Owonubi(@miraclx) "} +{"package": "xstrle", "pacakge-description": "\u5185\u542bxssoft\u5236\u4f5cturtle\u56fe\u5f62\u65b9\u6cd5"} +{"package": "xstruct", "pacakge-description": "xstructThis module provides a solution to serialize, deserialize and represent\npacked binary data in a declarative manner. It is built on top and\nextends the capabilities of the standardstructmodule while\npresenting an higher-level object oriented interface similar to that of\nthe familiar@dataclassdecorator. It has optional support for\nembedded BSON data structures.Now available onPyPIandGitHubInstallationThe following command should work on most systems:$pipinstallxstructUsageThis module provides a class decorator with an interface similar todataclasses.dataclass.Basic usagefromxstructimportstruct,UInt16,Big@struct(endianess=Big)classUDPHeader:src_port:UInt16dst_port:UInt16length:UInt16checksum:UInt16xstructprovides pseudo-types for common signed and unsigned integer\nsizes, IEEE-754 floating point numbers, NUL terminated strings and\noptionally BSON documents.Struct objects can be created by decoding binary data from abytes-like object...>>>UDPHeader.unpack(b\"\\x00\\x001\\x00\\x00\\x00{\\x00\\x00\\x00L\\x00\\x00\\x00\\x00\")UDPHeader(src_port=8241,dst_port=123,length=76,checksum=0)...or through the generated constructor, and can be serialized back to\nbinary data.>>>UDPHeader(src_port=8241,dst_port=123,length=76,checksum=0).pack()b'\\x00\\x001\\x00\\x00\\x00{\\x00\\x00\\x00L\\x00\\x00\\x00\\x00'Optional membersDefault values can be specified for members at the tail end of a struct.fromxstructimportstruct,Int32,Little@struct(endianess=Little)classSecondsOptional:member1:Int32member2:Int32=0If a buffer ends prematurely during decoding, default values are used in\nplace of missing struct members.>>>SecondsOptional.decode(b\"*\\0\\0\\0\")SecondsOptional(member1=42,member2=0)Members with a default value can also be omitted when creating a struct\nthrough the generated constructor.>>>SecondsOptional(42)SecondsOptional(member1=42,member2=0)Struct inclusionStructs can include other structsfromxstructimportstruct,Int32,Int64,CString,Big@struct(endianess=Big)classHeader:src:Int32msg_type:Int32upd_time:Int64@struct(endianess=Big)classMessage:header:Headermsg:CStringEncoding and decodingMessagewill work as expected.Struct endianessThe endianess of the numeric members of the struct can optionally be\nselected by providing theendianessargument to thestructdecorator. Valid options areLittle,BigandNative. When left\nunspecified, endianess defaults toNative.Future workAs of now, this library is fairly complete and in an usable state.\nFuture work could add support for:Decoding network addresses (IPv4, IPv6, MAC) to stringsPascal stringsArraysFixed width embedded binary payloadsTail end paddingDecoding total struct size from/to designated member"} +{"package": "xs-turtle", "pacakge-description": "\ud83d\udce6 setup.py (for humans)This repo exists to providean example setup.pyfile, that can be used\nto bootstrap your next Python project. It includes some advanced\npatterns and best practices forsetup.py, as well as some\ncommented\u2013out nice\u2013to\u2013haves.For example, thissetup.pyprovides a$ python setup.py uploadcommand, which creates auniversal wheel(andsdist) and uploads\nyour package toPyPiusingTwine, without the need for an annoyingsetup.cfgfile. It also creates/uploads a new git tag, automatically.In short,setup.pyfiles can be daunting to approach, when first\nstarting out \u2014 even Guido has been heard saying, \"everyone cargo cults\nthems\". It's true \u2014 so, I want this repo to be the best place to\ncopy\u2013paste from :)Check out the example!Installationcdyour_project# Download the setup.py file:# download with wgetwgethttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py-Osetup.py# download with curlcurl-Ohttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.pyTo DoTests via$ setup.py test(if it's concise).Pull requests are encouraged!More ResourcesWhat is setup.py?on Stack OverflowOfficial Python Packaging User GuideThe Hitchhiker's Guide to PackagingCookiecutter template for a Python packageLicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or\ndistribute this software, either in source code form or as a compiled\nbinary, for any purpose, commercial or non-commercial, and by any means."} +{"package": "xsugar", "pacakge-description": "xsugar Experimental Scripting FrameworkOften in my Ph.D. I found myself doing the same thing over and over again: writing a script to execute an experiment, and writing a script to parse, analyze, and plot the data. These scripts would always be saving data and figures to roughly the same place, and the general process carried out was the same. I came to realize if the data is numerical and tabular, and the experimental design relies on a finite number of conditions, much of this process can (and should) be automated. This package is my attempt to do that.FeaturesFull factorial experiment generation for N factorsAutomation of data parsing, saving, with support for arbitrary numerical datasetsIntelligent data plotting and figure generationDocumentationDocumentation can be found ongithub.ioGetting StartedInstalling the python moduleSoon, this software should be pip-installable, and the following should work:pip install xsugarSimple ExampleIn this experiment we gonig change two factors: the wavelength of an optical source and the temperature. We are going to measure the intensity (which I've just fudged to be a sinewave).from xsugar import Experiment\nimport numpy as np\nimport pandas as pd\n\nwavelength = [500, 600, 700]\ntemperature = [25, 35]\nsampling_frequency = 10000\nmeasurement_time = 0.01\n\ndef measure_output(cond):\n time = np.arange(0, 1 / cond['sampling_frequency'], cond['measurement_time'])\n data = np.sin(time)\n data = pd.DataFrame({'Time (ms)': time, 'Current (nA)': data})\n return data\n\nexp = Experiment(name='REFL1', kind='photocurrent', base_path='/home/jordan/experimental_directory/', measure_func=measure_output, wavelength=wavelength, temperature=temperaturesampling_frequency=sampling_frequency)\nexp.Execute()\nexp.plot()Terminology and ArchitectureThis module is designed to runexperiments, which consist of a number experimentalconditionsin which the experimenter manipulates zero or morefactors. These conditions also have associatedmetadata.In this module I use the termfactorsto refer to an experimental variable that is deliberately manipulated by the experimenter1. Each unique combination of factors used in an experiment I refer to as acondition. If you wish to run replicates with identical factors, the replicate number is considered (for the purposes of this module) a factor, and part of an experimental condition. Each experimentalconditionalso has a set ofmetadataassociated with it. This might be unique to the condition (i.e. with the time and date the experiment was run), or it might be common to all conditions (i.e. the sampling frequency used to aquire data).Each experiment is assumed to have a uniquename, which should not contain any hyphens (-) or tildes (~). All other characters are permitted. This name should be unique to the experiment and easy to recall (i.e. CVDDOP1 or HIPPONEURON1). The experiment may also have an optionalidentifier(i.e. 1), where many similar experiments are being done. Experiments are assumed to also have akind, which is just an additional way of categorizing experiments.All experimental data exists inside a singlebase directory. Inside thisbase directory, this module will create (if it does not already exist) a folder calleddata/, and a folder calledfigures/. Inside each of these folders, there will be subfolders for each experimentalkind, and within those folders, folders with each unique experimentalname, where the data or figures will be stored.Each experiment involves the measurement of some quantity, via ameasurement function. This function should take as a single argument, a dictionary which contains the full experimental condition (the levels of all the factors, plus any associated metadata), and it should return the measured data, which should be in the form of a scalar, a numpy array, or a pandas DataFrame. The data returned by a measurement function will be saved in a filename that combines the factors and their current levels with the experimental name using tildes and underscores (i.e. if the name is \"TEST1\", kind is \"photocurrent\", and the factors are wavelength, which is currently at a value of 2, and temperature, at a value of 25, the filename will be TEST1wavelength-2temperature-25.csv, and will be saved in the \"photocurrent\" directory within the base directory.).After the data is measured, you may want to extract a quantity from each of your datasets (for example, the mean value of measured photocurrent). You can do this withquantity functions. These functions should take two arguments: the data and the experimental condition. They may also take any number of additional keyword arguments as desired, for example, to parameterize curve fitting. These quantity functions can be used directly or passed in as an argument to the plotting / analysis methods. When extracting desired quantities, you can take the average result (along a given factor), or representative result. These quantities may be scalars, or they may transform the data (such as extracting a power spectral density).Finally, you may want to generate figures from the raw data, or from the derived quantities. Plotting the raw data is the default behavior, but if you supply a quantity function to the plotting function, it will generate a set of plot families for that derived quantity. If the derived quantity is a dataset itself, the plotter will just generate one plot for condition. If the derived quantity is a scalar, the behavior is more complex.If the derived quantity is a scalar (for example full-width-half-max for a curve fitting procedure on a dataset) the default method of figure generation is to combinatorially generate a set of all possible plot families. For example, if two factors are involved, there will be two plots. One plot will have factor 1 on the x-axis, and several curves which correspond to different levels of factor 2. The other plot will have factor 2 on the x-axis, and different curves which correspond to varying levels of factor 1.If there are three factors, this procedure is repeated. First factor 1 is placed on the x-axis, and the number of figures generated this will be the number of levels of factor 2 plus the number of levels of factor 3. Then factor 2 will be placed on the x-axis, and so on. This plotting scheme is designed to work with N factors, each of which have any number of levels. This can generate a large number of plots, so plots with a given x-axis can be excluded or included specifically with arguments to the plotting function.1I decided not to use \"variable\" because of how overloaded it is in the context of programming."} +{"package": "xsuite", "pacakge-description": "Integrated suite for particle accelerator simulations"} +{"package": "xsum", "pacakge-description": "Fast Exact Summation Using Small and Large Superaccumulators (XSUM)In applications like optimization or finding the sample mean of data, it is\ndesirable to use higher accuracy than a simple summation. Where in a simple\nsummation, rounding happens after each addition.\nAn exact summation is a way to achieve higher accuracy results.XSUMis a library for performing exact summation using\nsuper-accumulators. It provides methods for exactly summing a set of\nfloating-point numbers, where using a simple summation and the rounding which\nhappens after each addition could be an important factor in many applications.This library is an easy to use header-only cross-platform C++11 implementation\nand also contains Python bindings (please see the example).The main algorithm is taken from the original C libraryFUNCTIONS FOR EXACT SUMMATIONdescribed\nin the paper\"Fast Exact Summation Using Small and Large Superaccumulators,\"byRadford M. Neal.The code is rewritten in C++ and amended with more functionalities with the goal\nof ease of use. The provided Python bindings provide theexact summationinterface in a Python code.The C++ code also includes extra summation functionalities, (parallel reduction\non multi-core architectures) which are especially useful in high-performance\nmessage passing libraries (likeOpenMPIandMPICH). Where binding a user-defined global summation\noperation to anophandle can subsequently be used inMPI_Reduce,MPI_Allreduce,MPI_Reduce_scatter,andMPI_Scanor a similar calls.NOTE:To see or use or reproduce the results of the original\nimplementation reported in the paperFast Exact Summation Using Small and Large Superaccumulators, by Radford M.\nNeal, please refer toFUNCTIONS FOR EXACT SUMMATION.UsageXSUMlibrary presents two objects, or super-accumulatorsxsum_small_accumulatorandxsum_large_accumulator. It also provides methods\nfor summing floating-point numbers and rounding to the nearest floating-point\nnumber.A small superaccumulator uses sixty-seven 64-bit chunks, each with 32-bit\noverlap with the next one. This accumulator is the preferred method for summing\na moderate number of terms. A large superaccumulator uses 4096 64-bit chunks and\nis suitable for big summations. A small superaccumulator is also a component of\nthe large superaccumulator [1].XSUMlibrary provides two interfaces to use superaccumulators. The first\none is a function interface, which takes input and produces output, and in the\nsecond one, supperaccumulators are represented as classes (xsum_smallandxsum_large.)C++xsum_small_accumulatorandxsum_large_accumulator, both have a default\nconstructor, thus they do not need to be initialized. Addition operation is\nsimply axsum_add,// A small superaccumulatorxsum_small_accumulatorsacc;// Adding values to the small accumulator saccxsum_add(&sacc,1.0);xsum_add(&sacc,2.0);// Large superaccumulatorxsum_large_accumulatorlacc;// Adding values to the large accumulator laccxsum_add(&lacc,1.0e-3);xsum_add(&lacc,2.0e-3);orxsum_small, andxsum_largeobjects can simply be used as,// A small superaccumulatorxsum_smallsacc;// Adding values to the small accumulator saccsacc.add(1.0);sacc.add(2.0);// Large superaccumulatorxsum_largelacc;// Adding values to the large accumulator lacclacc.add(1.0e-3);lacc.add(2.0e-3);One can also add a vector of numbers to a superaccumulator.// A small superaccumulatorxsum_small_accumulatorsacc;// Adding a vector of numbersdoublevec[]={1.234e88,-93.3e-23,994.33,1334.3,457.34,-1.234e88,93.3e-23,-994.33,-1334.3,-457.34};xsum_add(&sacc,vec,10);std::vectorv={1.234e88,-93.3e-23,994.33,1334.3,457.34,-1.234e88,93.3e-23,-994.33,-1334.3,-457.34};xsum_add(&sacc,v);the same withxsum_small, andxsum_largeobjects as,// A small superaccumulatorxsum_smallsacc;// Adding a vector of numbersdoublevec[]={1.234e88,-93.3e-23,994.33,1334.3,457.34,-1.234e88,93.3e-23,-994.33,-1334.3,-457.34};sacc.add(vec,10);std::vectorv={1.234e88,-93.3e-23,994.33,1334.3,457.34,-1.234e88,93.3e-23,-994.33,-1334.3,-457.34};sacc.add(v);The squared norm of a vector (sum of squares of elements) and the dot product of\ntwo vectors (sum of products of corresponding elements) can be added to a\nsuperaccumulator usingxsum_add_sqnormandxsum_add_dotrespectively.For exmaple,// A small superaccumulatorxsum_small_accumulatorsacc;// Adding a vector of numbersdoublevec1[]={1.e-2,2.,3.};doublevec2[]={1.e-3,2.,3.};// Add dot product of vectors to a small superaccumulatorxsum_add_dot(&sacc,vec1,vec2,3);withxsum_small, andxsum_largeobjects as,// A small superaccumulatorxsum_smallsacc;// Adding a vector of numbersdoublevec1[]={1.e-2,2.,3.};doublevec2[]={1.e-3,2.,3.};// Add dot product of vectors to a small superaccumulatorsacc.add_dot(vec1,vec2,3);When it is needed, one can simply use thexsum_initto reinitilize the\nsuperaccumulator.xsum_small_accumulatorsacc;xsum_add(&sacc,1.0e-2);...// Reinitilize the small accumulatorxsum_init(&sacc);...or withxsum_smallobject as,xsum_smallsacc;sacc.add(1.0e-2);...// Reinitilize the small accumulatorsacc.init();...The superaccumulator can be rounded as,xsum_small_accumulatorsacc;xsum_add(&sacc,1.0e-15);....doubles=xsum_round(&sacc);where,xsum_roundis used to round the superaccumulator to the nearest\nfloating-point number.Withxsum_small, andxsum_largeobjects we do as,xsum_smallsacc;sacc.add(1.0e-15);....doubles=sacc.round();where,roundis used to round the superaccumulator to the nearest\nfloating-point number.Twosmallsuperaccumulators can be added together.xsum_addcan be used to\nadd the second superaccumulator to the first one without doing any rounding. Twolargesuperaccumulator can also be added in the same way. In the case of the\ntwo large superaccumulators, the second one internally will be rounded to a\nsmall superaccumulator and then the addition is done.// Small superaccumulatorsxsum_small_accumulatorsacc1;xsum_small_accumulatorsacc2;xsum_add(&sacc1,1.0);xsum_add(&sacc2,2.0);xsum_add(&sacc1,&sacc2);// Large superaccumulatorsxsum_large_accumulatorlacc1;xsum_large_accumulatorlacc2;xsum_add(&lacc1,1.0);xsum_add(&lacc2,2.0);xsum_add(&lacc1,&lacc2);or as,// Small superaccumulatorsxsum_smallsacc1;xsum_smallsacc2;sacc1.add(1.0);sacc2.add(2.0);// Add a small accumulator sacc2 to the first accumulator sacc1sacc1.add(sacc2);// Large superaccumulatorsxsum_largelacc1;xsum_largelacc2;lacc1.add(1.0);lacc2.add(2.0);// Add a large accumulator lacc2 to the first accumulator lacc1lacc1.add(lacc2);Asmallsuperaccumulator can also be added to alargeone,// Small superaccumulatorxsum_small_accumulatorsacc;xsum_add(&sacc,1.0e-10);...// Large superaccumulatorxsum_large_accumulatorlacc;xsum_add(&lacc,2.0e-3);...// Addition of a small superaccumulator to a large onexsum_add(&lacc,&sacc);Withxsum_small, andxsum_largeobjects we do as,// Small superaccumulatorxsum_smallsacc;sacc.add(1.0e-10);...// Large superaccumulatorxsum_largelacc;lacc.add(2.0e-3);...// Addition of a small superaccumulator to a large onelacc.add(sacc);The large superaccumulator can be rounded to a small one as,xsum_large_accumulatorlacc;xsum_small_accumulatorsacc=xsum_round_to_small(&lacc);or as,xsum_largelacc;xsum_small_accumulatorsacc=lacc.round_to_small();ExampleTwo simple examples on how to use the library:#include#include#include\"xsum/xsum.hpp\"usingnamespacexsum;intmain(){// Large superaccumulatorxsum_large_accumulatorlacc;doubleconsta=0.7209e-5;doubles=0;for(inti=0;i<10000;++i){xsum_add(&lacc,a);s+=a;}std::cout<#include#include\"xsum/xsum.hpp\"usingnamespacexsum;intmain(){// Large superaccumulatorxsum_largelacc;doubleconsta=0.7209e-5;doubles=0;for(inti=0;i<10000;++i){lacc.add(a);s+=a;}std::cout<#include#include#include\"xsum/myxsum.hpp\"#include\"xsum/xsum.hpp\"usingnamespacexsum;intmain(){// Initialize the MPI environmentMPI_Init(NULL,NULL);// Get the number of processesintworld_size;MPI_Comm_size(MPI_COMM_WORLD,&world_size);// Get the rank of the processintworld_rank;MPI_Comm_rank(MPI_COMM_WORLD,&world_rank);// Create the MPI data type of the superaccumulatorMPI_Datatypeacc_mpi=create_mpi_type();// Create the XSUM user-opMPI_OpXSUM=create_XSUM();doubleconsta=0.239e-3;doubles(0);xsum_large_accumulatorlacc;for(inti=0;i<1000;++i){s+=a;xsum_add(&lacc,a);}MPI_Allreduce(MPI_IN_PLACE,&s,1,MPI_DOUBLE,MPI_SUM,MPI_COMM_WORLD);MPI_Allreduce(MPI_IN_PLACE,&lacc,1,acc_mpi,XSUM,MPI_COMM_WORLD);if(world_rank==0){std::cout<<\"Rank = \"<>>edges=[(0,1),(1,0)]>>>permuted_edges,permutation_statistics=xswap.permute_edge_list(edges,allow_self_loops=True,allow_antiparallel=True,multiplier=10)>>>permuted_edges[(0,0),(1,1)]>>>permutation_statistics{'swap_attempts':20,'same_edge':10,'self_loop':0,'duplicate':1,'undir_duplicate':0,'excluded':0}Computing degree-sequence based prior probabilities of edges existing>>>edges=[(0,1),(1,0)]>>>prior_prob_df=xswap.prior.compute_xswap_priors(edges,n_permutations=10000,shape=(2,2),allow_self_loops=True,allow_antiparallel=True)>>>prior_prob_dfsource_idtarget_idedgesource_degreetarget_degreexswap_prior000False110.5101True110.5210True110.5311False110.5Choice of parametersBipartite networksBipartite networks should be indexed using the bi-adjacency matrix, meaning that the edge(0, 0)is from source node 0 to target node 0, and is not a self-loop.\nMoreover, bipartite networks should be permuted usingallow_self_loops=Falseandallow_antiparallel=True.Directed and undirected networksFor non-bipartite networks, the decisions ofallow_self_loopsandallow_antiparallelare not always the same.\nFor undirected networks, setallow_antiparallel=False, as otherwise the edges (1, 0) and (0, 1), which represent the same edge, will be treated as separate.\nAntiparallel edges may or may not be allowed for directed networks, depending on context.\nSimilarly, self-loops may or may not be allowed for directed or undirected networks, depending on the specific network being permuted.LibrariesThe XSwap library includes Roaring Bitmaps (https://github.com/RoaringBitmap/CRoaring), available under the Apache 2.0 license (https://github.com/RoaringBitmap/CRoaring/blob/LICENSE).AcknowledgmentsDevelopment of this project has largely taken place in theGreene Labat the University of Pennsylvania. However, as an open source project under thehetioorganization, this repository is grateful for its community of maintainers, contributors, and users.This work is funded in part by the Gordon and Betty Moore Foundation\u2019s Data-Driven Discovery Initiative through Grants GBMF4552 to Casey Greene, GBMF4560 to Blair Sullivan, and the National Institutes of Health\u2019s National Human Genome Research Institute R01 HG010067."} +{"package": "xswem", "pacakge-description": "XSWEMA simple and explainable deep learning model for NLP implemented in TensorFlow.Based on SWEM-max as proposed by Shen et al. inBaseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms, 2018.This package is currently in development. The purpose of this package is to make it easy to train and explain SWEM-max.You can find demos of the functionality we have implemented in thenotebooksdirectory of the package. Each notebook has a badge that allows you to run it yourself in Google Colab. We will add more notebooks as new functionality is added.For a demo of how to train a basic SWEM-max model seetrain_xswem.ipynb.Local ExplanationsWe are currently implementing some methods we have developed for local explanations.local_explain_most_salient_wordsSo far we have only implemented the local_explain_most_salient_words method. This method extracts the words the model has learnt as most salient from a given input sentence. Below we show an example of this method using a sample from theag_newsdataset. This method is explained in more detail in thelocal_explain_most_salient_words.ipynbnotebook.Global ExplanationsWe have implemented the global explainability method proposed in section 4.1.1 of the original paper. You can see a demo of this method in the notebookglobal_explain_embedding_components.ipynb.How to installThis package is hosted onPyPIand can be installed using pip.pip install xswem"} +{"package": "xswitch", "pacakge-description": "No description available on PyPI."} +{"package": "xswizard", "pacakge-description": "UNKNOWN"} +{"package": "xsync", "pacakge-description": "XsyncA set of tools to create hybrid sync/async interfaces.CPython versions 3.7 through 3.11-dev and PyPy versions 3.7 through 3.9 are officially supported.Windows, MacOS, and Linux are all supported.What doesXsyncdo?Xsyncallows developers to create dynamic interfaces which can be run in sync or async contexts.In simple terms, it makes this possible:result=my_function()result=awaitmy_function()How neat is that?!UsageThe above behaviour can be achieved with theas_hybriddecorator:@xsync.as_hybrid()defmy_function():...This setsmy_functionup as a \"hybrid callable\", which is capable of being run both synchronously and asynchronously.\nHowever, we also need to set an async implementation formy_functionfor it to work.\nWe can do this using theset_async_impldecorator:@xsync.set_async_impl(my_function)asyncdefmy_async_function():...Doing this tellsXsyncto run this function instead ofmy_functionwhen awaiting:my_function()# runs as normalawaitmy_function()# calls `my_async_function` insteadDon't worry,my_async_functioncan still be run directly, as you'd expect.It also works on methods, class methods, and static methods:classMyClass:@xsync.as_hybrid()defmy_method(self):...@xsync.set_async_impl(my_method)asyncdefmy_async_method(self):...@classmethod@xsync.as_hybrid()defmy_class_method(cls):...@classmethod@xsync.set_async_impl(my_class_method)asyncdefmy_async_class_method(cls):...@staticmethod@xsync.as_hybrid()defmy_static_method(cls):...@staticmethod@xsync.set_async_impl(my_static_method)asyncdefmy_async_static_method(cls):...The above is the newer (and better) of two available implementations.View the old implementationThe above behaviour can be achieved with themaybe_asyncdecorator:@xsync.maybe_async()defmy_function():...This setsmy_functionup as a \"hybrid callable\", which is capable of being run both synchronously and asynchronously.\nHowever, we also need to set an async implementation formy_functionfor it to work.\nWe can do this by creating another function of the same name, but with an_async_prefix:asyncdef_async_my_function():...Xsyncsearches for a function with the name of the original function prefixed by_async_at runtime, and runs this instead when awaiting:my_function()# runs as normalawaitmy_function()# calls `_async_my_function` insteadIt also works on methods and class methods:classMyClass:@xsync.maybe_async()defmy_method(self):...asyncdef_async_my_method(self):...@classmethod@xsync.maybe_async()defmy_class_method(cls):...@classmethodasyncdef_async_my_class_method(cls):...This implementation does not work with static methods.ContributingContributions are very much welcome! To get started:Familiarise yourself with thecode of conductHave a look at thecontributing guideLicenseTheXsyncmodule for Python is licensed under theBSD 3-Clause License."} +{"package": "xsynth", "pacakge-description": "XSynthXSynth is a command line tool for synthesing applications. It is a key\ncomponent of the QuickDev system. As a stand-alone application it is\na pre-processor for multiple languages include python, javascript\nand html.I have been using bits and pieces of this for over two decades. This\nis a very early release of code that I am origanizing and documenting\nfor use by others."} +{"package": "xsystem", "pacakge-description": "Regex-learnerThis project provides a tool/library implementing an automated regular expression building mechanism.This project takes inspiration on the paper from Ilyas, et al [1]Ilyas, Andrew, M. F. da Trindade, Joana, Castro Fernandez, Raul and Madden, Samuel. 2018. \"Extracting Syntactical Patterns from Databases.\"This repository contains code and examples to assist in the exeuction of regular expression learning from the columns of data.This is a basic readme. It will be completed as the prototype grows.Examples of usageExample of learning a date pattern from 100 examples of randomly sampled dates in the format DD-MM-YYYY.fromxsystemimportXTructurefromfakerimportFakerfake=Faker()x=XTructure()# Create basic XTructure classfor_inrange(100):d=fake.date(pattern=r\"%d-%m-%Y\")# Create example of data - date in the format DD-MM-YYYYx.learn_new_word(d)# Add example to XSystem and learn new featuresprint(str(x))# ([0312][0-9])(-)([01][891652073])(-)([21][09][078912][0-9])Similary, the tool can be used directly from the command line using theregex-learnerCLI provided by the installation of the package.The tool has several options, as described by the help message:> regex-learner -h\nusage: regex-learner [-h] [-i INPUT] [-o OUTPUT] [--max-branch MAX_BRANCH] [--alpha ALPHA] [--branch-threshold BRANCH_THRESHOLD]\n\nA simple tool to learn human readable a regular expression from examples\n\noptions:\n -h, --help show this help message and exit\n -i INPUT, --input INPUT\n Path to the input source, defaults to stdin\n -o OUTPUT, --output OUTPUT\n Path to the output file, defaults to stdout\n --max-branch MAX_BRANCH\n Maximum number of branches allowed, defaults to 8\n --alpha ALPHA Weight for fitting tuples, defaults to 1/5\n --branch-threshold BRANCH_THRESHOLD\n Branching threshold, defaults to 0.85, relative to the fitting score alphaAssuming a data file containing the examples to learn from is calledEXAMPLE_FILE, and assuming one is interested in a very simple regular expression, the tool can be used as follows:catEXAMPLE_FILE|regex-learner--max-branch2NoteNote that this project is not based on the actual implementation of the paper as presented in [2]ReferencesIlyas, Andrew, et al. \"Extracting syntactical patterns from databases.\" 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE, 2018.https://github.com/mitdbg/XSystem"} +{"package": "xt", "pacakge-description": "[![Build Status](https://travis-ci.org/mapbox/xt.svg?branch=master)](https://travis-ci.org/mapbox/xt) [![Coverage Status](https://coveralls.io/repos/github/mapbox/xt/badge.svg?branch=master)](https://coveralls.io/github/mapbox/xt?branch=master)Automatically convert a stream of tile coordinates to another formatz/x/y | z-x-y==>[x, y, z][x, y, z]==>z/x/y|z-x-y|z?x?y -d ?Installation` pip install xt `Or to develop:` git@github.com:mapbox/xt.git && cd xt && pip install-e'.[test]'`ExamplesTile URL to [mercantile](https://github.com/mapbox/mercantile)[x, y, z]` \u00bb echohttps://map.s/17/20971/5051.png| xt [20971, 50651, 17] `mercantile toz/x/y` \u00bb echo '[0, 0, 0]' | xt 0/0/0 `mercantile toz-x-y` \u00bb echo '[100, 100, 100]' | xt-d-100-100-100`roundtripping` \u00bb pbpaste | xt | xt-d- | xt | xt | xt | xt-d| xt | xt 17/20972/50653 `Using mercantile to generate tile urls from a parent tile:` \u00bb echo '[0, 0, 0]' | mercantile children--depth2 | xt | awk '{print\"https://map.s/\"$NF\".png\"}'https://map.s/2/0/0.pnghttps://map.s/2/1/0.pnghttps://map.s/2/1/1.pnghttps://map.s/2/0/1.pnghttps://map.s/2/2/0.pnghttps://map.s/2/3/0.pnghttps://map.s/2/3/1.pnghttps://map.s/2/2/1.pnghttps://map.s/2/2/2.pnghttps://map.s/2/3/2.pnghttps://map.s/2/3/3.pnghttps://map.s/2/2/3.pnghttps://map.s/2/0/2.pnghttps://map.s/2/1/2.pnghttps://map.s/2/1/3.pnghttps://map.s/2/0/3.png`"} +{"package": "xtab", "pacakge-description": "xtab.pyis a Python module and command-line program that\nrearranges data from a normalized format to a crosstabulated format. It takes data\nin this form:StationDateValueWQ-012006-05-234.5WQ-022006-05-233.7WQ-032006-05-236.8WQ-012006-06-159.7WQ-022006-05-155.1WQ-032006-06-157.2WQ-012006-07-1910WQ-022006-07-196.1WQ-032006-07-198.8and rearranges it into this form:Station2006-05-232006-06-152006-07-19WQ-014.53.76.8WQ-029.75.17.2WQ-03106.18.8Input and output are both text (CSV) files.A summary of its capability and usage is shown below. Full documentation\nis available athttp://xtab.osdn.io/.CapabilitiesYou can use the xtab program to:Rearrange data exported from a database to better suit its\nsubsequent usage in statistical, modeling, graphics, or other\nsoftware, or for easier visual review and table preparation.Convert a single file (table) of data to a SQLite database.Check for multiple rows of data in a text file with the same\nkey values.NotesMultiple data values can be crosstabbed, in which case the output\nwill contain multiple sets of similar columns.Either one or two rows of headers can be produced in the output file.\nOne row is the default, and is most suitable when the output file will\nbe further processed by other software. Two rows facilitate readability\nwhen the output contains multiple sets of similar columns.The xtab program does not carry out any summarization or\ncalculation on the data values, and therefore there should be\nno more than one data value to be placed in each cell of the output\ntable. More than one value per cell is regarded as an error, and in\nsuch cases only one of the multiple values will be put in the cell.Error messages can be logged to either the console or a file. If no\nerror logging option is specified, then if there are multiple values\nto be put in a cell (the most likely data error), a single message\nwill be printed on the console indicating that at least one error of\nthis type has occurred. If an error logging option is specified,\nthen the SQL for all individual cases where there are multiple values\nper cell will be logged.The SQL commands used to extract data from the input file for each\noutput table cell can be logged to a file.As an intermediate step in the crostabbing process, data are converted\nto a SQLite table. By default, this table is created in memory.\nHowever, it can optionally be created on disk, and preserved so that\nit is available after the crosstabulation is completed.There are no inherent limits to the number of rows or columns in the\ninput or output files. (So the output may exceed the limits of some\nother software.)Input and output file names, and column names in the input file that\nare to be used for row headings, column headings, and cell values are\nall required as command-line arguments. If any required arguments are\nmissing, an exception will be raised, whatever the error logging option.Data rows are sorted alphanumerically by the row headers and column\nheaders are sorted alphanumerically in the output."} +{"package": "xtable", "pacakge-description": "doc on github.ioxtableprint console tables. xtable serves as both a class and a command line tool.installationuse the classcommand linefrom CSV, preformatted table, JSON list to console table, JSON, markdown and more.convert table data to MarkdownInstallation`pip install xtable`run it through xtableorpython -mxtable`below is a simple introduction for some basic usage.use the classfrom xtable import xtable\n\ndata = [\n [1,2,3,4,5],\n [11,52,3,4,5],\n [11,None,3,4,5],\n [11,None,3,None,5],\n ]\nhdr = ['c1','c2','c3','c4','c5']\n\nxt = xtable(data=data,header=hdr)print(xt)// result :c1 c2 c3 c4 c5\n--------------\n1 2 3 4 5\n11 52 3 4 5\n11 3 4 5\n11 3 5# test/t2.csv\n'''\nh1,h2,h3\n\"asd\",\"sdfsadf\",1\n\"c\",\"cc\",233\n'''\n\nxt = xtable.init_from_csv(\"test/t2.csv\")print(xt)// result :h1 h2 h3\n---------------\nasd sdfsadf 1\nc cc 233data = [\n {\"h1\":\"v1\",\"h2\":\"v2\",\"h3\":\"v3\"},\n {\"h1\":\"v11\",\"h2\":\"v22\",\"h3\":\"v33\"},\n {\"h1\":\"v11111\",\"h2\":\"v22222\",\"h3\":\"v34444\"},\n ]\nxt = xtable.init_from_list(data)print(xt)// result :h1 h2 h3\n--------------------\nv1 v2 v3\nv11 v22 v33\nv11111 v22222 v34444// all of them support \"xheader\".data = [\n {\"h1\":\"v1\",\"h2\":\"v2\",\"h3\":\"v3\"},\n {\"h1\":\"v11\",\"h2\":\"v22\",\"h3\":\"v33\"},\n {\"h1\":\"v11111\",\"h2\":\"v22222\",\"h3\":\"v34444\"},\n ]\nxt = xtable.init_from_list(data, xheader=[\"h1\",\"h3\"])print(xt)\n\nxt2 = xtable.init_from_list(data, xheader=\"h2,h3\")print(xt2)h1 h3\n-------------\nv1 v3\nv11 v33\nv11111 v34444\n\nh2 h3\n-------------\nv2 v3\nv22 v33\nv22222 v34444// output json/yaml/csv/htmldata = [\n {\"h1\":\"v1\",\"h2\":\"v2\",\"h3\":\"v3\"},\n {\"h1\":\"v11\",\"h2\":\"v22\",\"h3\":\"v33\"},\n {\"h1\":\"v11111\",\"h2\":\"v22222\",\"h3\":\"v34444\"},\n ]\nxt = xtable.init_from_list(data, xheader=[\"h1\",\"h3\"])print(xt.csv())print(xt.yaml())print(xt.json())print(xt.html())// result- h1: v1\n h3: v3\n- h1: v11\n h3: v33\n- h1: v11111\n h3: v34444\n\n[\n {\n \"h1\": \"v1\",\n \"h3\": \"v3\"\n },\n {\n \"h1\": \"v11\",\n \"h3\": \"v33\"\n },\n {\n \"h1\": \"v11111\",\n \"h3\": \"v34444\"\n }\n]\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nuse the command line[yonghang@mtp xtable]$ cat test/t1.txt \na b c\n121 1212 12\n12 332 2323\n[yonghang@mtp xtable]$ cat test/t1.txt | xtable \na b c\n-------------\n121 1212 12\n12 332 2323\n[yonghang@mtp xtable]$ \n[yonghang@mtp xtable]$ cat test/t2.csv \nh1,h2,h3\n\"asd\",\"sdfsadf\",1\n\"c\",\"cc\",233\n[yonghang@mtp xtable]$ \n[yonghang@mtp xtable]$ cat test/t2.csv | xtable -b\",\"\nh1 h2 h3\n-------------------\n\"asd\" \"sdfsadf\" 1\n\"c\" \"cc\" 233[yonghang@mtp xtable]$ cat test/t3.json | qic\n[\n {\"userId\": 1,\"firstName\": \"Krish\",\"lastName\": \"Lee\",\"phoneNumber\": \"123456\",\"emailAddress\": \"krish.lee@learningcontainer.com\"\n },\n {\"userId\": 2,\"firstName\": \"racks\",\"lastName\": \"jacson\",\"phoneNumber\": \"123456\",\"emailAddress\": \"racks.jacson@learningcontainer.com\"\n },\n {\"userId\": 3,\"firstName\": \"denial\",\"lastName\": \"roast\",\"phoneNumber\": \"33333333\",\"emailAddress\": \"denial.roast@learningcontainer.com\"\n },\n {\"userId\": 4,\"firstName\": \"devid\",\"lastName\": \"neo\",\"phoneNumber\": \"222222222\",\"emailAddress\": \"devid.neo@learningcontainer.com\"\n },\n {\"userId\": 5,\"firstName\": \"jone\",\"lastName\": \"mac\",\"phoneNumber\": \"111111111\",\"emailAddress\": \"jone.mac@learningcontainer.com\"\n }\n]\n\n[yonghang@mtp xtable]$ cat test/t3.json | xtable\nuserId firstName lastName phoneNumber emailAddress\n------------------------------------------------------------------------\n1 Krish Lee 123456 krish.lee@learningcontainer.com\n2 racks jacson 123456 racks.jacson@learningcontainer.com\n3 denial roast 33333333 denial.roast@learningcontainer.com\n4 devid neo 222222222 devid.neo@learningcontainer.com\n5 jone mac 111111111 jone.mac@learningcontainer.compivot[yonghang@mtp xtable]$ cat test/t3.json | xtable -v\nuserId : 1\nfirstName : Krish\nlastName : Lee\nphoneNumber : 123456\nemailAddress : krish.lee@learningcontainer.com\n--\nuserId : 2\nfirstName : racks\nlastName : jacson\nphoneNumber : 123456\nemailAddress : racks.jacson@learningcontainer.com\n--\nuserId : 3\nfirstName : denial\nlastName : roast\nphoneNumber : 33333333\nemailAddress : denial.roast@learningcontainer.com\n--\nuserId : 4\nfirstName : devid\nlastName : neo\nphoneNumber : 222222222\nemailAddress : devid.neo@learningcontainer.com\n--\nuserId : 5\nfirstName : jone\nlastName : mac\nphoneNumber : 111111111\nemailAddress : jone.mac@learningcontainer.comif we look at the source code, we know class xtable support .pivot() as well,iftype(js) islist:\n xt = xtable.init_from_json(js,args.header)\n if args.pivot :print(xt.pivot())\n else :print(xt)when header has space...some command output is already a table, only not that decent, eg. as below. xtable will help a little bit.-ctold xtable thatcontainer idis together while-ttold xtable the input stream is already in \"table\" format.[yonghang@mtp xtable]$ sudo podman ps --all\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\neeb5db3c4f9a docker.io/library/nginx:latest nginx -g daemon o... About a minute ago Exited (0) About a minute ago romantic_hamilton\n5ef267563b44 docker.io/library/httpd:latest httpd-foreground 55 seconds ago Exited (0) 6 seconds ago sad_lamarr\n[yonghang@mtp xtable]$ \n[yonghang@mtp xtable]$ \n[yonghang@mtp xtable]$ sudo podman ps --all | xtable -c \"CONTAINER ID\" -t\nCONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES\n----------------------------------------------------------------------------------------------------------------------------------------\neeb5db3c4f9a docker.io/library/nginx:latest nginx -g daemon o... About a minute ago Exited (0) About a minute ago romantic_hamilto\n5ef267563b44 docker.io/library/httpd:latest httpd-foreground About a minute ago Exited (0) 28 seconds ago sad_lamar\n[yonghang@mtp xtable]$ \n[yonghang@mtp xtable]$ sudo podman ps --all | xtable -c \"CONTAINER ID\" -tv\nCONTAINER ID : eeb5db3c4f9a\nIMAGE : docker.io/library/nginx:latest\nCOMMAND : nginx -g daemon o...\nCREATED : About a minute ago\nSTATUS : Exited (0) About a minute ago\nPORTS : \nNAMES : romantic_hamilto\n--\nCONTAINER ID : 5ef267563b44\nIMAGE : docker.io/library/httpd:latest\nCOMMAND : httpd-foreground\nCREATED : About a minute ago\nSTATUS : Exited (0) 32 seconds ago\nPORTS : \nNAMES : sad_lamarxtable take care of lines[yonghang@W5202860 test]$ cat sql.json | qic\n[\n {\"name\": \"sql example 1\",\"query\": \"SELECT QUARTER, REGION, SUM(SALES)\\n FROM SALESTABLE\\n GROUP BY CUBE (QUARTER, REGION)\"\n },\n {\"name\": \"sql example 2\",\"query\": \"select name, cast(text as varchar(8000)) \\nfrom SYSIBM.SYSVIEWS \\n where name='your table name' \"\n },\n {\"name\": \"sql example 3\",\"query\": \"select Id, max(V1),max(V2),max(V3) from \\n (\\n select ID,Value V1,'' V2,'' V3 from A where Code=1 \\n union all \\n select ID,'' V1, Value V2,'' V3 from A where Code=2 \\n union all \\n select ID,'' V1, '' V2,Value V3 from A where Code=3 \\n) AG\\n group by ID\"\n }\n]\n\n[yonghang@W5202860 test]$ \n[yonghang@W5202860 test]$ cat sql.json | xtable\nname query\n-------------------------------------------------------------------\nsql example 1 SELECT QUARTER, REGION, SUM(SALES)\n FROM SALESTABLE\n GROUP BY CUBE (QUARTER, REGION)\nsql example 2 select name, cast(text as varchar(8000))\n from SYSIBM.SYSVIEWS\n where name='your table name'\nsql example 3 select Id, max(V1),max(V2),max(V3) from\n (\n select ID,Value V1,'' V2,'' V3 from A where Code=1\n union all\n select ID,'' V1, Value V2,'' V3 from A where Code=2\n union all\n select ID,'' V1, '' V2,Value V3 from A where Code=3\n ) AG\n group by IDmarkdownyonghang@air xtable % cat test/t2.csv\nh1,h2,h3\n\"asd\",\"sdfsadf\",1\n\"c\",\"cc\",233\n\nyonghang@air xtable % cat test/t2.csv | xtable -F md\n| h1,h2,h3 |\n| ----------------- |\n| \"asd\",\"sdfsadf\",1 |\n| \"c\",\"cc\",233 |\nyonghang@air xtable %\nyonghang@air xtable % cat test/t1.txt\na b c\n121 1212 12\n12 332 2323\nyonghang@air xtable % cat test/t1.txt | xtable -F md\n| a | b | c |\n| ---- | ---- | ---- |\n| 121 | 1212 | 12 |\n| 12 | 332 | 2323 |\nyonghang@air xtable %\nyonghang@air xtable % cat test/t3.json | qic\n[\n {\n \"userId\": 1,\n \"firstName\": \"Krish\",\n \"lastName\": \"Lee\",\n \"phoneNumber\": \"123456\",\n \"emailAddress\": \"krish.lee@learningcontainer.com\"\n },\n {\n \"userId\": 2,\n \"firstName\": \"racks\",\n \"lastName\": \"jacson\",\n \"phoneNumber\": \"123456\",\n \"emailAddress\": \"racks.jacson@learningcontainer.com\"\n },\n {\n \"userId\": 3,\n \"firstName\": \"denial\",\n \"lastName\": \"roast\",\n \"phoneNumber\": \"33333333\",\n \"emailAddress\": \"denial.roast@learningcontainer.com\"\n },\n {\n \"userId\": 4,\n \"firstName\": \"devid\",\n \"lastName\": \"neo\",\n \"phoneNumber\": \"222222222\",\n \"emailAddress\": \"devid.neo@learningcontainer.com\"\n },\n {\n \"userId\": 5,\n \"firstName\": \"jone\",\n \"lastName\": \"mac\",\n \"phoneNumber\": \"111111111\",\n \"emailAddress\": \"jone.mac@learningcontainer.com\"\n }\n]\n\nyonghang@air xtable %\nyonghang@air xtable % cat test/t3.json | xtable -F md\n| userId | firstName | lastName | phoneNumber | emailAddress |\n| ------ | --------- | -------- | ----------- | ---------------------------------- |\n| 1 | Krish | Lee | 123456 | krish.lee@learningcontainer.com |\n| 2 | racks | jacson | 123456 | racks.jacson@learningcontainer.com |\n| 3 | denial | roast | 33333333 | denial.roast@learningcontainer.com |\n| 4 | devid | neo | 222222222 | devid.neo@learningcontainer.com |\n| 5 | jone | mac | 111111111 | jone.mac@learningcontainer.com |\nyonghang@air xtable %"} +{"package": "xtag", "pacakge-description": "xtagA python model for easily wrapping strings into html/xml tags.A longer description of your project goes here\u2026NoteThis project has been set up using PyScaffold 4.1.1. For details and usage\ninformation on PyScaffold seehttps://pyscaffold.org/."} +{"package": "x-tagger", "pacakge-description": "No description available on PyPI."} +{"package": "xtal", "pacakge-description": "No description available on PyPI."} +{"package": "xtal2png", "pacakge-description": "\u26a0\ufe0f Manuscript and results using a generative model coming soon \u26a0\ufe0fxtal2pngEncode/decode a crystal structure to/from a grayscale PNG image for direct use with image-based machine learning models such asGoogle's Imagen.The latest advances in machine learning are often in natural language such as with LSTMs and transformers or image processing such as with GANs, VAEs, and guided diffusion models. Encoding/decoding crystal structures via grayscale PNG images is akin to making/reading a QR code for crystal structures. This allows you, as a materials informatics practitioner, to get streamlined results for new state-of-the-art image-based machine learning models applied to crystal structure. Let's take Google's text-to-image diffusion model,Imagen(unofficial), whichcan also be used as an image-to-image model. Rather than dig into the code spending hours, days, or weeks modifying, debugging, and playing GitHub phone tag with the developers before you can (maybe) get preliminary results,xtal2pnglets you get those results using the default instructions on the repository.After getting preliminary results, you get to decide whether it's worth it to you to take on the higher-cost/higher-expertise task of modifying the codebase and using a more customized approach. Or, you can stick with the results ofxtal2png. It's up to you!Getting StartedInstallationcondacreate-nxtal2png-cconda-forgextal2pngm3gnet\ncondaactivatextal2pngNOTE:m3gnetis an optional dependency that performs surrogate DFT relaxation.ExampleHere, we use the top-levelXtalConverterclass with and without optional relaxation viam3gnet.# example_structures is a list of `pymatgen.core.structure.Structure` objects>>>fromxtal2pngimportXtalConverter,example_structures>>>>>>xc=XtalConverter(relax_on_decode=False)>>>data=xc.xtal2png(example_structures,show=True,save=True)>>>decoded_structures=xc.png2xtal(data,save=False)>>>len(decoded_structures)2>>xc=XtalConverter(relax_on_decode=True)>>data=xc.xtal2png(example_structures,show=True,save=True)>>relaxed_decoded_structures=xc.png2xtal(data,save=False)>>len(relaxed_decoded_structures)2Outputprint(example_structures[0],decoded_structures[0],relaxed_decoded_structures[0])OriginalStructureSummaryLatticeabc:5.03378811.52302110.74117angles:90.090.090.0volume:623.0356027127609A:5.0337880.03.0823061808931787e-16B:1.8530431062799525e-1511.5230217.055815392078867e-16C:0.00.010.74117PeriodicSite:Zn2+(0.9120,5.7699,9.1255)[0.1812,0.5007,0.8496]PeriodicSite:Zn2+(4.1218,5.7531,1.6156)[0.8188,0.4993,0.1504]...DecodedStructureSummaryLatticeabc:5.025098039215686511.53333333333333110.8angles:90.090.090.0volume:625.9262117647058A:5.02509803921568650.00.0B:0.011.5333333333333310.0C:0.00.010.8PeriodicSite:Zn(0.9016,5.7780,3.8012)[0.1794,0.5010,0.3520]PeriodicSite:Zn(4.1235,5.7554,6.9988)[0.8206,0.4990,0.6480]...Relaxed DecodedStructureSummaryLatticeabc:5.02683430738121411.57885461368523710.724087971087924angles:90.090.090.0volume:624.1953646135236A:5.0268343073812140.00.0B:0.011.5788546136852370.0C:0.00.010.724087971087924PeriodicSite:Zn(0.9050,5.7978,3.7547)[0.1800,0.5007,0.3501]PeriodicSite:Zn(4.1218,5.7810,6.9693)[0.8200,0.4993,0.6499]...The before and after structures match within an expected tolerance; note the round-off error due to encoding numerical data as RGB images which has a coarse resolution of approximately1/255 = 0.00392. Note also that the decoded version lacks charge states. The QR-code-like intermediate PNG image is also provided in original size and a scaled version for a better viewing experience:64x64 pixelsScaled for Better Viewing (tool credit)LegendAdditional examples can be found inthe docs.Limitations and Design ConsiderationsThere are some limitations and design considerations forxtal2png. Here, we cover round-off error, image dimensions, contextual features, and customization.Round-offWhile the round-off\nerror is a necessary evil for encoding to aPNG file format, the unrounded NumPy arrays\ncan be used directly instead if supported by the image model of interest viastructures_to_arraysandarrays_to_structures.Image dimensionsWe choose a\n$64\\times64$ representation by default which supports up to 52 sites within a unit cell.\nThe maximum number of sitesmax_sitescan be adjusted which changes the size of the\nrepresentation. A square representation is used for greater compatibility with the\ncommon limitation of image-based models supporting only square image arrays. The choice\nof the default sidelength as a base-2 number (i.e. $2^6$) reflects common conventions of\nlow-resolution images for image-based machine learning tasks.Contextual featuresWhile the\ndistance matrix does not directly contribute to the reconstruction in the current\nimplementation ofxtal2png, it serves a number of purposes. First, similar to the unit\ncell volume and space group information, it can provide additional guidance to the\nalgorithm. A corresponding example would be the role of background vs. foreground in\nclassification of wolves vs. huskies; oftentimes classification algorithms will pay\nattention to the background (such as presence of snow) in predicting the animal class.\nLikewise, providing contextual information such as volume, space group, and a distance\nmatrix is additional information that can help the models to capture the essence of\nparticular crystal structures. In a future implementation, we plan to reconstruct\nEuclidean coordinates from the distance matrices and homogenize (e.g. via weighted\naveraging) the explicit fractional coordinates with the reconstructed coordinates.CustomizationSee thedocsfor the full list of customizable parameters thatXtalConvertertakes.InstallationPyPI (pip) installationCreate and activate a newcondaenvironment namedxtal2png(-n) withpython==3.9.*or your preferred Python version, then installxtal2pngviapip.condacreate-nxtal2pngpython==3.9.*\ncondaactivatextal2png\npipinstallxtal2pngEditable installationIn order to set up the necessary environment:clone and enter the repository via:gitclonehttps://github.com/sparks-baird/xtal2png.gitcdxtal2pngcreate and activate a new conda environment (optional, but recommended)condaenvcreate--namextal2pngpython==3.9.*\ncondaactivatextal2pngperform an editable (-e) installation in the current directory (.):pipinstall-e.NOTE:Some changes, e.g. insetup.cfg, might require you to runpip install -e .again.Optional and needed only once aftergit clone:install severalpre-commitgit hooks with:pre-commitinstall# You might also want to run `pre-commit autoupdate`and checkout the configuration under.pre-commit-config.yaml.\nThe-n, --no-verifyflag ofgit commitcan be used to deactivate pre-commit hooks temporarily.installnbstripoutgit hooks to remove the output cells of committed notebooks with:nbstripout--install--attributesnotebooks/.gitattributesThis is useful to avoid large diffs due to plots in your notebooks.\nA simplenbstripout --uninstallwill revert these changes.Then take a look into thescriptsandnotebooksfolders.Command Line Interface (CLI)Make sure to install the package first per the installation instructions above. Here is\nhow to access the help for the CLI and a few examples to get you started.HelpYou can see the usage information of thextal2pngCLI script via:xtal2png--helpUsage:xtal2png[OPTIONS]xtal2pngcommandlineinterface.\n\nOptions:--versionShowversion.-p,--pathPATHCrystallographicinformationfile(CIF)filepath(extensionmustbe.cifor.CIF)orpathtodirectorycontaining.ciffilesorprocessedPNGfilepathorpathtodirectorycontainingprocessed.pngfiles(extensionmustbe.pngor.PNG).AssumesCIFsif--encodeflagisused.AssumesPNGsif--decodeflagisused.-s,--save-dirPATHEncodeCIFfilesasPNGimages.--encodeEncodeCIFfilesasPNGimages.--decodeDecodePNGimagestoCIFfiles.-v,--verboseTEXTSetlogleveltoINFO.-vv,--very-verboseTEXTSetlogleveltoINFO.--helpShowthismessageandexit.ExamplesTo encode a single CIF file located atsrc/xtal2png/utils/Zn2B2PbO6.cifas a PNG and save the PNG to thetmpdirectory:xtal2png--encode--pathsrc/xtal2png/utils/Zn2B2PbO6.cif--save-dirtmpTo encode all CIF files contained in thesrc/xtal2png/utilsdirectory as a PNG and\nsave corresponding PNGs to thetmpdirectory:xtal2png--encode--pathsrc/xtal2png/utils--save-dirtmpTo decode a single structure-encoded PNG file located atdata/preprocessed/Zn8B8Pb4O24,volume=623,uid=b62a.pngas a CIF file and save the CIF\nfile to thetmpdirectory:xtal2png--decode--pathdata/preprocessed/Zn8B8Pb4O24,volume=623,uid=b62a.png--save-dirtmpTo decode all structure-encoded PNG file contained in thedata/preprocesseddirectory as CIFs and save the CIFs to thetmpdirectory:xtal2png--decode--pathdata/preprocessed--save-dirtmpNote that the save directory (e.g.tmp) including any parents (e.g.ab/cd/tmp) will\nbe created automatically if the directory does not already exist.Project Organization\u251c\u2500\u2500 AUTHORS.md <- List of developers and maintainers.\n\u251c\u2500\u2500 CHANGELOG.md <- Changelog to keep track of new features and fixes.\n\u251c\u2500\u2500 CONTRIBUTING.md <- Guidelines for contributing to this project.\n\u251c\u2500\u2500 Dockerfile <- Build a docker container with `docker build .`.\n\u251c\u2500\u2500 LICENSE.txt <- License as chosen on the command-line.\n\u251c\u2500\u2500 README.md <- The top-level README for developers.\n\u251c\u2500\u2500 configs <- Directory for configurations of model & application.\n\u251c\u2500\u2500 data\n\u2502 \u251c\u2500\u2500 external <- Data from third party sources.\n\u2502 \u251c\u2500\u2500 interim <- Intermediate data that has been transformed.\n\u2502 \u251c\u2500\u2500 preprocessed <- The final, canonical data sets for modeling.\n\u2502 \u2514\u2500\u2500 raw <- The original, immutable data dump.\n\u251c\u2500\u2500 docs <- Directory for Sphinx documentation in rst or md.\n\u251c\u2500\u2500 environment.yml <- The conda environment file for reproducibility.\n\u251c\u2500\u2500 models <- Trained and serialized models, model predictions,\n\u2502 or model summaries.\n\u251c\u2500\u2500 notebooks <- Jupyter notebooks. Naming convention is a number (for\n\u2502 ordering), the creator's initials and a description,\n\u2502 e.g. `1.0-fw-initial-data-exploration`.\n\u251c\u2500\u2500 pyproject.toml <- Build configuration. Don't change! Use `pip install -e .`\n\u2502 to install for development or to build `tox -e build`.\n\u251c\u2500\u2500 references <- Data dictionaries, manuals, and all other materials.\n\u251c\u2500\u2500 reports <- Generated analysis as HTML, PDF, LaTeX, etc.\n\u2502 \u2514\u2500\u2500 figures <- Generated plots and figures for reports.\n\u251c\u2500\u2500 scripts <- Analysis and production scripts which import the\n\u2502 actual PYTHON_PKG, e.g. train_model.\n\u251c\u2500\u2500 setup.cfg <- Declarative configuration of your project.\n\u251c\u2500\u2500 setup.py <- [DEPRECATED] Use `python setup.py develop` to install for\n\u2502 development or `python setup.py bdist_wheel` to build.\n\u251c\u2500\u2500 src\n\u2502 \u2514\u2500\u2500 xtal2png <- Actual Python package where the main functionality goes.\n\u251c\u2500\u2500 tests <- Unit tests which can be run with `pytest`.\n\u251c\u2500\u2500 .coveragerc <- Configuration for coverage reports of unit tests.\n\u251c\u2500\u2500 .isort.cfg <- Configuration for git hook that sorts imports.\n\u2514\u2500\u2500 .pre-commit-config.yaml <- Configuration of pre-commit git hooks.Note on PyScaffoldThis project has been set up usingPyScaffold4.2.1 and thedsproject extension0.7.1.To create the same starting point for this repository, as of 2022-06-01 on Windows you will need the development versions of PyScaffold and extensions, however this will not be necessary once certain bugfixes have been introduced in the next stable releases:pipinstallgit+https://github.com/pyscaffold/pyscaffold.gitgit+https://github.com/pyscaffold/pyscaffoldext-dsproject.gitgit+https://github.com/pyscaffold/pyscaffoldext-markdown.gitThe followingpyscaffoldcommand creates a starting point for this repository:putupxtal2png--github-actions--markdown--dsprojAlternatively, you can edit a file interactively and update and uncomment relevant lines, which saves some of the additional setup:putup--interactivextal2pngAttributions@michaeldalversonfor iterating through various representations during extensive work with crystal GANs. The base representation forxtal2png(see#output) closely follows a recent iteration (2022-06-13), taking the first layer ($1\\times64\\times64$) of the $4\\times64\\times64$ representation and replacing a buffer column/row of zeros with unit cell volume."} +{"package": "xtal-cartographer", "pacakge-description": "Install Models with:cartographer-install -m phos -o site_packagesExample Usage:cartographer -i PDB.mtz -o PDB.map -intensity FWT -phase PHWTusage: cartographer [-h] [-m M] -i I -o O [-r [R]] [-intensity [INTENSITY]] [-phase [PHASE]]\n\noptions:\n -h, --help show this help message and exit\n -m M, -model_path M Path to model\n -i I, -input I Input mtz path\n -o O, -output O Output map path \n -r [R], -resolution [R] Resolution cutoff to apply to mtz\n -intensity [INTENSITY] Name of intensity column in MTZ\n -phase [PHASE] Name of phase column in MTZusage: cartographer-install [-h] -m {phos,sugar,base} [-o {site_packages,ccp4}] [--all] [--reinstall]\n\nCartographer Install\n\noptions:\n -h, --help show this help message and exit\n -m {phos,sugar,base}, --model {phos,sugar,base}\n -o {site_packages,ccp4}, --output {site_packages,ccp4}\n --all\n --reinstall"} +{"package": "xtalpi", "pacakge-description": "XtalpiFeaturesTODOHistory0.0.1 (2020-10-28)First release on PyPI."} +{"package": "xtalpi-pandas", "pacakge-description": "No description available on PyPI."} +{"package": "xtalx", "pacakge-description": "xtalxThis package provides a library for interfacing with the XtalX pressure and\ndensity/viscosity sensors. Python version 3 is required. The easiest way to\ninstall the xtalx module is using pip:python3 -m pip install xtalxNote that you may wish to use sudo to install xtalx for all users on your\nsystem:sudo python3 -m pip install xtalxYou may also install the package from the source using:make installor:sudo make installxtalx_p_discoverThe xtalx package includes the xtalx_p_discover binary which can be used to\nlist all XtalX pressure sensors that are attached to the system and their\ncorresponding firmware versions:~$ xtalx_p_discover\n******************\nSensor SN: XTI-7-1000035\n git SHA1: 61be0469c1162b755d02fd9156a2754bebf24f59.dirty\n Version: 0x0107xtalx_p_testThe xtalx package includes a simple test binary that will connect to an XtalX\npressure sensor and continuously print the current pressure and temperature\nreading:~$ xtalx_p_test\nXtalX(XTI-7-1000035): 23.973375 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.973375 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.973375 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.963872 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.963872 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.954370 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.954370 PSI, 23.947930 C\nXtalX(XTI-7-1000035): 23.973375 PSI, 23.947930 C\n...Terminate the program by pressing Ctrl-C.xtalx_z_discoverThe xtalx packages includes the xtalx_z_discover binary which can be used to\nlist all XtalX density/viscosity sensors that are attached to the system and\ntheir corresponding firmware version:~% xtalx_z_discover\n******************\n Product: XtalX TCSC\nSensor SN: TCSC-1-2000045\n git SHA1: b50b8e4a406f0b8585f50c1f9aa7c95145d4810d\n Version: 0x0101xtalx_z_get_infoThe xtalx package includes the xtalx_z_get_info binary that can be used to get\na bit more detailed information about a sensor:~% xtalx_z_get_info\n[1691531122175214000] I: Controlling sensor TCSC-1-2000045 with firmware 0x101 (b50b8e4a406f0b8585f50c1f9aa7c95145d4810d).\n*************************************\n Serial Num: TCSC-1-2000045\n Git SHA1: b50b8e4a406f0b8585f50c1f9aa7c95145d4810d\n FW Version: 0x0101\n HCLK: 80000000\n DCLK: 2500000\n ACLK: 1250000\n HSE: 10 MHz\n Max cmd len: 16384\n # resets: 1\n Drive Type: DriveType.INTERNAL_DRIVE\n Reset Reason: ResetReason.POWER_ON_RESET\n Reset CSR: 0x0C004400\n Reset SR1: 0x00000000\nMax sweep freqs: 1024\n-----------------------\nElectrical calibration:\n Calibration Date: 1683682186 (Tue May 9 19:29:46 2023)\n R Source: 10037.000000\n R Feedback: 149850.000000\n DAC-to-V: 2.208075 + -0.000256*x\n ADC-to-V: 1.674066 + 0.000204*x\n Nominal VDDA: 3.35\n-----------------------\nTuning fork calibration:\n Calibration Date: 1683682197 (Tue May 9 19:29:57 2023)\nCal DAC Amplitude: 975 (0.25V)xtalx_z_gl_track_modeThe xtalx package includes the xtalx_z_gl_track_mode binary that is the core\ntool for use with the density/viscosity sensor. It features a GUI instead of\ncommand-line output. To execute it:~% xtalx_z_gl_track_modextalx_z_cli_track_modeThe xtalx package includes the xtalx_z_cli_track_mode binary that is similar\nto the GUI track mode tool but only prints log messages to the console and\nwrite measurements to the .csv files. This allows it to be run on a headless\nsystem. To execute it:~% xtalx_z_cli_track_modeWindows useOn Windows, the binaries are all launched via the command line just like on\nLinux and macOS, however Windows can\u2019t automatically find them. In order to\nlaunch them, you need to execute them using their full Python path as follows:python3 -m xtalx.tools.p_sensor.discover\npython3 -m xtalx.tools.p_sensor.xtalx_test_yield\npython3 -m xtalx.tools.z_sensor.discover\npython3 -m xtalx.tools.z_sensor.get_info\npython3 -m xtalx.tools.z_sensor.gl_track_modeOn Windows, it is also common to have the Python interpreter installed under\nthe name \u201cpy\u201d or \u201cpy3\u201d, so if \u201cpython3\u201d does not work for you it is recommended\nto try one of the shorter command names. If the Python interpreter cannot be\nfound, it may not be installed at all so should be installed via the Microsoft\nStore (it is a free, open-source install)."} +{"package": "xtapi", "pacakge-description": "No description available on PyPI."} +{"package": "xtarfile", "pacakge-description": "OverviewWrapper around tarfile to add support for more compression formats.UsageFirst, install the library with the tarfile compression formats you wish to support.\nThe example below shows an install for zstandard tarfile support.pipinstallxtarfile[zstd]You can now use the xtarfile module in the same way as the standard library tarfile module:importxtarfileastarfilewithtarfile.open('some-archive','w:zstd')asarchive:archive.add('a-file.txt')withtarfile.open('some-archive','r:zstd')asarchive:archive.extractall()Alternatively, detecting the correct compression module based on the file extensions is also supported:importxtarfileastarfilewithtarfile.open('some-archive.tar.zstd','w')asarchive:archive.add('a-file.txt')withtarfile.open('some-archive.tar.zstd','r')asarchive:archive.extractall()DevelopmentInstall the project\u2019s dependencies withpip install .[zstd].Run the tests viapython3 setup.py test."} +{"package": "xtas", "pacakge-description": "xtasDistributed text analysis suite based on Celery.Copyright University of Amsterdam, Netherlands eScience Center and\ncontributors, distributed under the Apache License (seeAUTHORS.txt,LICENSE.txt). Parts of xtas use GPL-licensed software, such as the\nStanford NLP tools, and datasets that may incur additional restrictions.\nCheck the documentation for individual functions.QuickstartInstall:pip install xtasStart worker:python -m xtas.worker --loglevel=infoStart web frontend:python -m xtas.webserverFor full documentation, please visithttp://nlesc.github.io/xtas/."} +{"package": "xtb", "pacakge-description": "This repository hosts the Python API for the extended tight binding (xtb) program.The idea of this project is to provide thextbAPI for Pythonwithoutrequiring an additionalxtbinstallation.InstallationDepending on what you plan to do withxtb-pythonthere are two recommended\nways to install.If you plan to use this project in your workflows, follow the\nConda Installation section.If you plan to develop on this project, proceed\nwith the Build from Source section.For more details visit thedocumentation.Conda InstallationInstallingxtb-pythonfrom theconda-forgechannel can be achieved by addingconda-forgeto your channels with:conda config --add channels conda-forgeOnce theconda-forgechannel has been enabled,xtb-pythoncan be installed with:conda install xtb-pythonIt is possible to list all of the versions ofxtb-pythonavailable on your platform with:conda search xtb-python --channel conda-forgeBuild from SourceThe project is build with meson, the exact dependencies are defined by thextbproject, in summary it requires a Fortran and a C compiler as well as a\nlinear algebra backend. Make yourself familiar with buildingxtbfirst!Additionally this project requires a development version of Python installed.\nAlso ensure that you have thenumpyandcffipackages installed,\nconfigure the build of the extension with.All steps to build the project are automated usingpip install .To pass options to the meson build of xtb use--config-settingsetup-args=\"-Dxtb-6.5.1:la_backend=openblas\"to set for example the linear algebra backend to OpenBLAS.ContributingContributions to this open source project are very welcome. Before starting,\nreview ourcontributing guidelinesfirst, please.Licensextb-pythonis free software: you can redistribute it and/or modify it under\nthe terms of the GNU Lesser General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or\n(at your option) any later version.xtb-pythonis distributed in the hope that it will be useful,\nbut without any warranty; without even the implied warranty of\nmerchantability or fitness for a particular purpose. See the\nGNU Lesser General Public License for more details."} +{"package": "xtb-bot-api", "pacakge-description": "This is a bot api for the xtb currently contribute to the project at my github profilehttps://github.com/AnthonyAniobi/XTB_API[Github](https://github.com/AnthonyAniobi/XTB_API)profile` Github = profile `"} +{"package": "xtb-broker", "pacakge-description": "XTB broker models, methods and tools"} +{"package": "xtbclient", "pacakge-description": "XTBClientX-Trade Brokers (XTB) trading platform client, supporting both asynchronous and synchronous clients with typed classes.A python library supporting both asyncio and \"normal\" clients for X-Trade Brokers (XTB) trading using websockets.It will use eitherwebsocketsif using theasync XTB clientorwebsocket-clientif using thesync XTB clientSource codeAvailable ongithub.comInstallingTo install the client(s) just runpip install xtb-client.\nOr, better yet, using poetry runpoetry add xtb-client.Getting startedBoth clients support context manager notation -withorasync withstatement.Async clientIf you call the API too quicky the server may disconnect you so I've added somesleepcalls to simulate waiting a bit.importasyncioimportdatetimeimportloggingimportsysfromXTBClient.clientimportXTBAsyncClientfromXTBClient.models.modelsimportConnectionMode,Period,Transaction,TradeOperation,TradeTypefromXTBClient.models.requestsimportChartLastInfoRecord,ChartRangeRecordlogging.basicConfig(level=logging.DEBUG,stream=sys.stdout)asyncdefasync_client_test(user,password):logger=logging.getLogger(\"async client\")asyncwithXTBAsyncClient(user,password,mode=ConnectionMode.DEMO)asclient:start=datetime.datetime.now()future=start.replace(year=start.year+1)start=start.replace(year=start.year-1)transaction=Transaction(cmd=TradeOperation.Buy,custom_comment=\"Testing custom comment\",expiration=future,offset=0,order=0,price=1.12,sl=0.0,symbol=\"EURUSD\",tp=0.0,type=TradeType.Open,volume=1)id=awaitclient.trade_transaction(transaction)logger.info(f\"Initiated transaction:{id}\")status=awaitclient.transaction_status(id)logger.info(f\"Trade transaction status:{status}\")chart_info=awaitclient.get_chart_last_request(ChartLastInfoRecord(Period.PERIOD_M5,datetime.datetime.now(),\"EURPLN\"))logger.info(f\"Last chart info:{chart_info}\")chart_info=awaitclient.get_chart_range_request(ChartRangeRecord(Period.PERIOD_M5,datetime.datetime.utcnow(),datetime.datetime.now(),\"EURPLN\",ticks=5))logger.info(f\"Chart range info:{chart_info}\")trades=awaitclient.get_trades(False)logger.info(f\"All trades:{trades}\")trades=awaitclient.get_trades_history(start=start,end=datetime.datetime.now())logger.info(f\"All trades history:{trades}\")awaitasyncio.sleep(1)eurpln=awaitclient.get_symbol(\"EURPLN\")logger.info(f\"EURO -> PLN:{eurpln}\")current_user=awaitclient.get_current_user_data()logger.info(f\"Current user:{current_user}\")calendars=awaitclient.get_calendar()logger.info(f\"All calendars:{calendars}\")awaitasyncio.sleep(1)symbols=awaitclient.get_all_symbols()logger.info(f\"All symbols:{symbols}\")asyncio.get_event_loop().run_until_complete(async_client_test(\"user\",\"password\"))Sync (normal) clientIf you call the API too quicky the server may disconnect you so I've added somesleepcalls to simulate waiting a bit.importdatetimeimportloggingimportsysimporttimefromXTBClient.models.modelsimportConnectionMode,Period,Transaction,TradeOperation,TradeTypefromXTBClient.models.requestsimportChartLastInfoRecord,ChartRangeRecordfromXTBClient.client.xtbimportXTBSyncClientlogging.basicConfig(level=logging.DEBUG,stream=sys.stdout)defsync_client_test(user,password):logger=logging.getLogger(\"sync client\")withXTBSyncClient(user,password,mode=ConnectionMode.DEMO,proxy=None)asclient:start=datetime.datetime.now()future=start.replace(year=start.year+1)start=start.replace(year=start.year-1)transaction=Transaction(cmd=TradeOperation.Buy,custom_comment=\"Testing custom comment\",expiration=future,offset=0,order=0,price=1.12,sl=0.0,symbol=\"EURUSD\",tp=0.0,type=TradeType.Open,volume=1)id=client.trade_transaction(transaction)logger.info(f\"Initiated transaction:{id}\")status=client.transaction_status(id)logger.info(f\"Trade transaction status:{status}\")chart_info=client.get_chart_last_request(ChartLastInfoRecord(Period.PERIOD_M5,datetime.datetime.now(),\"EURPLN\"))logger.info(f\"Last chart info:{chart_info}\")chart_info=client.get_chart_range_request(ChartRangeRecord(Period.PERIOD_M5,datetime.datetime.utcnow(),datetime.datetime.now(),\"EURPLN\",ticks=5))logger.info(f\"Chart range info:{chart_info}\")trades=client.get_trades(False)logger.info(f\"All trades:{trades}\")trades=client.get_trades_history(start=start,end=datetime.datetime.now())logger.info(f\"All trades history:{trades}\")time.sleep(1)eurpln=client.get_symbol(\"EURPLN\")logger.info(f\"EURO -> PLN:{eurpln}\")current_user=client.get_current_user_data()logger.info(f\"Current user:{current_user}\")calendars=client.get_calendar()logger.info(f\"All calendars:{calendars}\")time.sleep(1)symbols=client.get_all_symbols()logger.info(f\"All symbols:{symbols}\")sync_client_test(\"user\",\"password\")API and usageSince this is Python you can browse through the code to find out what methods are available and how to use them.\nAll methods and classes should have typing hints so you can tell what each method expects as parameters.All return types from the XTB API is typed, there's no dictionaries with unknown key/value pairs or anything similar.Working on the codeThis project uses poetry for dependency management as well as for it's publishing functionality.\nTo get started all you need to do is:open a command promptclone the repositorybrowse to the newly cloned repository in the already opened command promptrunpoetry installWork in progressStreaming operations likegetCandlesand others are missingAdd missingnormalAPI methodsMore unit tests could be addedBetter documentationAdded library to PyPi repository"} +{"package": "xtbf", "pacakge-description": "No description available on PyPI."} +{"package": "xtb-trading", "pacakge-description": "Trade on xtb automatically"} +{"package": "xtbugdemo", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtcalc", "pacakge-description": "Simple calculatorUsage in codefrom xtcalc import tool\n\n# Add 5 + 34\na1 = xt.add(5, 34)\n\n# Subtract 12 - 5\na2 = xt.subtract(12, 5)\n\n# Divide 15 / 5\na3 = xt.divide(15, 5)\n\n# Multiply 45 * 23\na4 = xt.multiply(45, 23)\n\n# A random number, for example from 1 to 50\na5 = xt.rnd(1,50)\n\nprint(a1, a2, a3, a4, a5)Syntax and descriptionSyntaxDescriptionExampleaddAdd 5 + 34xt.add(5, 34)subtractSubtract 12 - 5xt.subtract(12, 5)divideDivide 15 / 5xt.divide(15, 5)multiplyMultiply 45 * 23xt.multiply(45, 23)rndRandom from 1 to 50xt.rnd(1, 50)"} +{"package": "xtce-generator", "pacakge-description": "xtce_generatorA tool to generate xtce files from a sqlite database. This database is assumed to have been generated byjucier.\nWe follow the XTCE specifications described onXTCE Verison 1.2as per OMG document number:formal/18-10-04. You may find this documenthere.XTCE Patterns, Conventions and CaveatsNotes For DevelopersDependenciessix==1.15.0PyYAML~=5.3.1setuptools~=50.3.2flake8twineNOTE:If you have issues running venv for python3.6 on Ubuntu 16, you should be able to fix it with this:sudo apt install python3.6-venv python3.6-devHow to useBe sure to run this from a virtual environment:python xtce_generator.py --sqlite_path /home/vagrant/auto-yamcs/juicer/newdb --log_level ['DEBUG', 'INFO', `WARNING`, `ERROR`, `CRITICAL`, `SILENT`] --config_yaml /home/vagrant/xtce_generator/src/xtce_generator/config.yaml --spacesystem ocpocAfter xtce_generator is done, you should have a file with the name of space_system_name.xml. In our case this isocpoc.xmlsince we passedocpocas our root spacesystem.\nPlease beware that you may pass in any name for your spacesystem; this depends on your working context. It could be a vehicle name, machine architecture or the name of a space mission itself!Using The XMLThe auto-generated xtce file,ocpoc.xmlin our case, is ready for use for any ground system that is xtce-compliant. For now we useyamcs. Here is an example demonstrating such use:Copy your xtce to your yamcs project:cp ~/xtce_generator/src/ocpoc.xml /home/vagrant/yamcs-cfs/src/main/yamcs/mdbBe sure to add this file to youryamcsinstance file:...\nmdb:\n # Configuration of the active loaders\n # Valid loaders are: sheet, xtce or fully qualified name of the class\n - type: \"xtce\"\n spec: \"mdb/cfs-ccsds.xml\"\n - type: \"xtce\"\n spec: \"mdb/CFE_EVS.xml\"\n - type: \"xtce\"\n spec: \"mdb/ocpoc.xml\"Then all you do is run yamcs!mvn yamcs:runXTCE ComplianceIn the future we will strive to be 100% xtce compliant. However, given that we useyamcsas our ground system, if there are quirks yamcs has we will be adhering to those quirks. For more info on this, you may gohere.XTCE Data StructuresOur xtce data structures are generated withgenerateDS 2.36.2. There is a quirk with this tool where it will be nameSpaceSystemobjects toSpaceSystemTypeafter generating the python code the xtce schema. This is very easy to fix.Go to theexportmethod of yourSpaceSystemType.\nChange it fromdef export(self, outfile, level, namespaceprefix_='', namespacedef_='', name_='SpaceSystemType', pretty_print=True):todef export(self, outfile, level, namespaceprefix_='', namespacedef_='', name_='SpaceSystem', pretty_print=True):After renaming that parameter, you are good to go!\n**NOTE: **Beware that if you do not change this,yamcswillnotrun.XTCE Patterns and ConventionsWhile we strive for 100% XTCE compliance, we lean towards YAMCS's version of XTCE, which isalmostfully XTCE compliant. Below are the specifications of the patterns, naming conventions and overall structure we follow to generate our XTCE files.NamespacesAs the XTCE standard mandates, our namespaces are enclosed with thetag. More specfically, we have aBaseTypenamespace. This namespace hasallof the necessary base types that a SpaceSystem may use. Please note that we use the termsNamespaceandSpaceSysteminterchangeably. A base type is something that is notusuallyuser-defined, but is rather machine-defined. Below is a table with examples of base types that may be part of ourBaseTypenamespace.NameDescriptionSize in bitsEncodingEndiannessuint1_LEAn unsigned integer.1unsignedLittle Endianuint16_BEAn unsigned integer.16unsignedBig endianchar160_LEA string with 160 bits, or 20 characters.160UTF-8Little EndianOur naming conventions for base types willalwaysbe [type][number_of_bits][under_score][Endianness] just lke you see in the table above.Please note that these base types are nearly identical to what you'd find in a programming language like C. That is because that is what they are meant to represent. Our goal is to auto-generate our XTCE files by extracting data(structs, variables, etc) from binary and executable files. Our reasons for this approach are simple; writing XTCE files by hand is error-prone and time consuming. At the moment the tool chain that will allow us to do this isalmostdone. One of those tools isjuicer, which extracts DWARF data from ELF files, such as executable binary files.DefaultRateInStream\n \n \n \n \n \n \n \n \n \n \n \nThis xtce xml node allows users to specify the min/max rate a container packet is supposed to be received by the ground station.\nAt the moment onlyminimumValueis supported as that is what YAMCS supports(Yamcs 5.7.9, build c654828f93607440ffee33c5bed72a98af775cd8) at the time of writing.ParameterTypesOur parameter types arealwaysdefined under. The naming of our parameter types follows the convention shown in the table above.ArgumentTypesOur argument types, as per XTCE design and standard, arealwaysdefined under. The naming of our arguments types follows the convention shown in the table above.User-defined TypesEnumeratedParameterType,AggregateParamterType,AggregateArgumentTypeandEnumeratedArgumentTypetypes are what we consider user-defined types. This means that these types arenotpart of theBaseTypenamespace.EnumeratedParameterTypeandAggregateParamterTypetypes arealwaysdefined on.AggregateArgumentTypeandEnumeratedArgumentTypearealwaysdefined on.AggregateArgumentTypemembers are flattened. This won't affect much of anything since the outcome is the same as if they were bundled inside an AAggregate.ArraysArrays Inside Structures(*AggregateType)Standalone( that is it does not appear inside a structure) arrays arenotsupportedThe following is the example of a structure(AggregateParamterType) using an array:\n \n \n \n \n \n \n \n Here we have a structure calledCFE_ES_MemPoolStats_t(notice the naming convention explained above). It has an array called BlockStats which points to an array in BaseType namespace.The way arrays are constructed was heavily inspired byDWARF4andXTCEstandards.Base types(Intrinsic types)The types shown above such as uint16_LE are what is known as a base type. These are the types that represent things like int, float, char, etc in code. As mentioned above thesewillalways be part of theBaseTypenamespace. Below is a table with all of our base types. Please note that this table is subject as we have not fully standarized our xtce format yet.\nThe endianness cells marked with a \"*\" at the end areexclusivelydescribingjustbit ordering and NOT byte-ordering.\nAs you see on the table this just applies to the types that are 8 bits or less as byte-ordering is irrelevant for these.\nWe considerbitordering for all of our types for the rare case where there is an architecture that takes into count bit ordering.NameDescriptionSize in bitsEncodingEndiannessuint1_BEAn unsigned integer.1unsignedBig Endian*uint1_LEAn unsigned integer.1unsignedBig Endian*uint2_BEAn unsigned integer.2unsignedBig Endian*uint2_LEAn unsigned integer.2unsignedLittle Endian*int2_BEA signed integer.2signedBig Endian*int2_LEA signed integer.2signedLittle Endian*uint3_BEAn unsigned integer.3unsignedBig Endian*uint3_LEAn unsigned integer.3unsignedLittle Endian*int3_BEA signed integer.3signedBig Endian*int3_LEA signed integer.3signedLittle Endian*uint4_BEAn unsigned integer.4unsignedBig Endian*uint4_LEAn unsigned integer.4unsignedLittle Endian*int4_BEA signed integer.4signedBig Endian*int4_LEA signed integer.4signedLittle Endian*uint5_BEAn unsigned integer.5unsignedBig Endian*uint5_LEAn unsigned integer.5unsignedLittle Endian*int5_BEA signed integer.5signedBig Endian*int5_LEA signed integer.5signedLittle Endian*uint6_BEAn unsigned integer.6unsignedBig Endian*uint6_LEAn unsigned integer.6unsignedLittle Endian*int6_BEA signed integer.6signedBig Endian*int6_LEA signed integer.6signedLittle Endian*uint7_BEAn unsigned integer.7unsignedBig Endian*uint7_LEAn unsigned integer.7unsignedLittle Endian*int7_BEA signed integer.7signedBig Endian*int7_LEA signed integer.7signedLittle Endian*uint8_BEAn unsigned integer.8unsignedBig Endian*uint8_LEAn unsigned integer.8unsignedLittle Endian*int8_BEA signed integer.8signedBig Endian*int8_LEA signed integer.8signedLittle Endian*uint9_BEAn unsigned integer.9unsignedBig Endianuint9_LEAn unsigned integer.9unsignedLittle Endianint9_BEA signed integer.9signedBig Endianint9_LEA signed integer.9signedLittle Endianuint10_BEAn unsigned integer.10unsignedBig Endianuint10_LEAn unsigned integer.10unsignedLittle Endianint10_BEA signed integer.10signedBig Endianint10_LEA signed integer.10signedLittle Endianuint11_BEAn unsigned integer.11unsignedBig Endianuint11_LEAn unsigned integer.11unsignedLittle Endianint11_BEA signed integer.11signedBig Endianint11_LEA signed integer.11signedLittle Endianuint12_BEAn unsigned integer.12unsignedBig Endianuint12_LEAn unsigned integer.12unsignedLittle Endianint12_BEA signed integer.12signedBig Endianint12_LEA signed integer.12signedLittle Endianuin13_BEAn unsigned integer.13unsignedBig Endianuint13_LEAn unsigned integer.13unsignedLittle Endianint13_BEA signed integer.13signedBig Endianint13_LEA signed integer.13signedLittle Endianuint14_BEAn unsigned integer.14unsignedBig Endianuint14_LEAn unsigned integer.14unsignedLittle Endianint14_BEA signed integer.14signedBig Endianint14_LEA signed integer.14signedLittle Endianuint15_BEAn unsigned integer.15unsignedBig Endianuint15_LEAn unsigned integer.15unsignedLittle Endianint15_BEA signed integer.15signedBig Endianint15_LEA signed integer.15signedLittle Endianuint16_BEAn unsigned integer.16unsignedBig Endianuint16_LEAn unsigned integer.16unsignedLittle Endianint16_BEA signed integer.16signedBig Endianint16_LEA signed integer.16signedLittle Endianuint17_BEAn unsigned integer.17unsignedBig Endianuint17_LEAn unsigned integer.17unsignedLittle Endianint17_BEA signed integer.17signedBig Endianint17_LEA signed integer.17signedLittle Endianuint18_BEAn unsigned integer.18unsignedBig Endianuint18_LEAn unsigned integer.18unsignedLittle Endianint18_BEA signed integer.18signedBig Endianint18_LEA signed integer.18signedLittle Endianuint19_BEAn unsigned integer.19unsignedBig Endianuint19_LEAn unsigned integer.19unsignedLittle Endianint19_BEA signed integer.19signedBig Endianint19_LEA signed integer.19signedLittle 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integer.61unsignedLittle Endianint61_BEA signed integer.61signedBig Endianint61_LEA signed integer.61signedLittle Endianuint62_BEAn unsigned integer.62unsignedBig Endianuint62_LEAn unsigned integer.62unsignedLittle Endianint62_BEA signed integer.62signedBig Endianint62_LEA signed integer.62signedLittle Endianuint63_BEAn unsigned integer.63unsignedBig Endianuint63_LEAn unsigned integer.63unsignedLittle Endianint63_BEA signed integer.63signedBig Endianint63_LEA signed integer.63signedLittle Endianuint64_BEAn unsigned integer.64unsignedBig Endianuint64_LEAn unsigned integer.64unsignedLittle Endianint64_BEA signed integer.64signedBig Endianint64_LEA signed integer.64signedLittle Endianfloat32_LEA signed floating point number.32signedLittle Endianfloat32_BEA signed floating point number.32signedBig Endianfloat64_LEA signed floating point number.64signedLittle Endianfloat64_BEA signed floating point number.64signedBig Endianboolean8_LEA boolean. \"1\" means TRUE; \"0\" FALSE.8N/ALittle EndianCaveatsThe namestringis special. Any type in the database with the type name ofstringis assumed to be a string\nand parsed as such by the XTCE tool. This means donotdo things like this in code:struct string\n{\n char buffer[64];\n};unsignedis assumed to be the same asunsigned intas perc++ standards.YAMCS-XTCE QuirksOur xtce flavor adheres to yamcs. In the future, we'll try our best to design our toolchain in such a way we can\nbe 100% compliant withxtce, but at the moment we adhere to yamcs-flavored xtceonly. As a result of this, we will\nneed to deal with any quirks this yamcs-flavored xtce standard may have. Below are a list of quirks we've discovered\nso far:It seems that yamcs has issues processing anyParamterentries that have a '#' in the name.Notes For DevelopersThis project can also be used as a library and devs can obtain it from Pypi(particularly useful to parse XTCE files):pip install xtce-generatorMakesureyou havelxml>=4.6installed. Otherwise some of the parse methods will not work properly onxtcemodule.TestingAll testing of this tool is done withauto-yamcsDocumentation updated on April 5, 2022"} +{"package": "xtcocotools", "pacakge-description": "No description available on PyPI."} +{"package": "xt-cvdata", "pacakge-description": "xt-cvdataDescriptionThis repo contains utilities for building and working with computer vision datasets, developed byXtract AI.So far, APIs for the following open-source datasets are included:COCO 2017 (detection and segmentation):xt_cvdata.apis.COCOOpen Images V5 (detection and segmentation):xt_cvdata.apis.OpenImagesVisual Object Tagging Tool (VoTT) CSV output (detection):xt_cvdata.apis.VoTTCSVMore to come.InstallationFrom PyPI:pipinstallxt-cvdataFrom source:gitclonehttps://github.com/XtractTech/xt-cvdata.git\npipinstall./xt-cvdataUsageSee specific help on a dataset class usinghelp. E.g.,help(xt_cvdata.apis.COCO).Building a datasetfromxt_cvdata.apisimportCOCO,OpenImages# Build an object populated with the COCO image list, categories, and annotationscoco=COCO('/nasty/data/common/COCO_2017')print(coco)print(coco.class_distribution)# Same for Open Imagesoi=OpenImages('/nasty/data/common/open_images_v5')print(oi)print(coco.class_distribution)# Get just the person classescoco.subset(['person'])oi.subset(['Person']).rename({'Person':'person'})# Merge and buildmerged=coco.merge(oi)merged.build('./data/new_dataset_dir')This package follows pytorch chaining rules, meaning that methods operating on an object modify it in-place, but also return the modified object. The exception is themerge()method which does not modify in-place and returns a new merged object. Hence, the above operations can also be completed using:fromxt_cvdata.apisimportCOCO,OpenImagesmerged=(COCO('/nasty/data/common/COCO_2017').subset(['person']).merge(OpenImages('/nasty/data/common/COCO_2017').subset(['Person']).rename({'Person':'person'})))merged.build('./data/new_dataset_dir')In practice, somewhere between the two approaches will probably be most readable.The current set of dataset operations are:analyze: recalculate dataset statistics (e.g., class distributions, train/val split)verify_schema: check if class attributes follow required schemasubset: remove all but a subset of classes from the datasetrename: rename/combine dataset classessample: sample a specified number of images from the train and validation setssplit: define the proportion of data in the validation setmerge: merge two datasets together, returning merged datasetbuild: create the currently defined dataset using either symlinks or by copying imagesImplementing a new dataset typeNew dataset types should inherit from the basext_cvdata.Builderclass. See theBuilder,COCOandOpenImagesclasses as a guide. Specifically, the class initializer should defineinfo,licenses,categories,annotations, andimagesattributes such thatself.verify_schema()runs without error. This ensures that all of the methods defined in theBuilderclass will operate correctly on the inheriting class.Data Sources[descriptions and links to data]Dependencies/Licensing[list of dependencies and their licenses, including data]References[list of references]"} +{"package": "xtd", "pacakge-description": "UNKNOWN"} +{"package": "xtdb", "pacakge-description": "XTDB Python: A Python ORM forXTDBCheck outthe documentationfor a more complete documentation of the package.InstallationYou can install this project using pip:$pipinstallxtdbUsageThe following examples assume you have set theXTDB_URIvariable in your environment.\nTo start experimenting, you could use the following setup using Docker:$dockerrun-p3000:3000-djuxt/xtdb-standalone-rocksdb:1.21.0\n$exportXTDB_URI=http://localhost:3000/_xtdbUsing the ClientTheXTDBClientsupports the fullHTTP API spec.>>>importos>>>fromxtdb.sessionimportXTDBClient,Operation>>>>>>client=XTDBClient(os.environ[\"XTDB_URI\"])>>>client.submit_tx([Operation.put({\"xt/id\":\"123\",\"name\":\"fred\"})])>>>>>>client.query('{:query {:find [(pull ?e [*])] :where [[ ?e :name \"fred\" ]]}}')[[{'name':'fred','xt/id':'123'}]]>>>>>>client.get_entity(\"123\"){'name':'fred','xt/id':'123'}Take a look at the spec to see the full range of functionality that maps directly to the client.Using the Datalog moduleThedatalogmodule also provides a layer to construct queries with more easily.\nGiven the data fromthe cities examplehas been seeded:>>>fromxtdb.datalogimportFind,Where>>>>>>query=Find(\"(pull Country [*])\")&Find(\"City\")&(Where(\"City\",\"City/country\",\"Country\")&Where(\"City\",\"City/name\",'\"Rome\"'))>>>str(query){:query{:find[(pullCountry[*])City]:where[[City:City/countryCountry][City:City/name\"Rome\"]]}}>>>>>>client.query(query)[[{'type':'Country','Country/name':'Italy','xt/id':'c095839f-031f-46ad-85e1-097f634ba4f0'},'33aa7fa6-b752-4982-a772-d2dbaeda58ae']]To see more datalog query examples, check out theunit tests.Using the ORM and SessionBelow is an example of how to use the ORM functionality.importosfromdataclassesimportdataclassfromxtdb.ormimportBasefromxtdb.queryimportQueryfromxtdb.sessionimportXTDBSession@dataclassclassTestEntity(Base):name:str@dataclassclassSecondEntity(Base):age:inttest_entity:TestEntitysession=XTDBSession(os.environ[\"XTDB_URI\"])entity=TestEntity(name=\"test\")withsession:session.put(entity)query=Query(TestEntity).where(TestEntity,name=\"test\")result=session.query(query)result[0].dict()# {\"TestEntity/name\": \"test\", \"type\": \"TestEntity\", \"xt/id\": \"fe2a3ee0-9254-41dc-91cc-74ad9e2a16db\"}To see more examples, check out theexamples directory.\nDon't hesitate to add your own examples!Using the CLI for queryingThis package also comes with an easy CLI tool to query XTDB.\nAgain, set theXTDB_URIvariable in your environment first and you will be able to query XTDB as follows:$echo'{:query {:find [(pull ?e [*])] :where [[ ?e :name \"fred\" ]]}}'|python-mxtdb[[{\"name\":\"fred\",\"xt/id\":\"123\"}]]To use a query from a file, run:$catquery.txt{:query{:find[(pull?e[*])]:where[[?e:name\"fred\"]]}}$\n$python-mxtdb>> from xtea import *\n>>> key = \" \"*16 # Never use this\n>>> text = \"This is a text. \"*8\n>>> x = new(key, mode=MODE_OFB, IV=\"12345678\")\n>>> c = x.encrypt(text)\n>>> text == x.decrypt(c)\nTrueResourcesPyPi:https://pypi.org/project/xteaDocs:http://xtea.readthedocs.io/Source code:https://github.com/varbin/xteaIssue tracker:https://github.com/varbin/xtea/issuesChangelogVersion 0.7.1, former 0.6.1 / 0.7.0; Jun 16, 2018Improved testsPEP8-style formattingUnittests: Counter, modes (but not results of them!), test vectors[BREAKING CHANGE] Counter class is now in xtea.counterPython 3.3 is not tested anymore on Travis CI[BREAKING CHANGE] CFB mode is now correctly implemented.\nBy settingpartition_sizeit is possible to set the\ninternal partition size (in bits) as per PEP-272.Python 3: An optional C extension improves speed upto a factor of 10.[BREAKING CHANGE]block_sizeandkey_sizeis now in bytes.Skipped 0.7.0 with(unreleased) Version 0.6.0; Oct 16, 2016Python 3 does work now[BREAKING CHANGE] counters cannot return numbers any more, they must return bytestrings now[BREAKING CHANGE] Cipher objects remember state, so two consecutive calls to XTEACipher.encrypt should not return the sameimproved documentation(unreleased) Version 0.5.0; Oct 15, 2016Removed CBCMACVersion 0.4.1; Jul 30, 2015Fixed installerVersion 0.4.0; Jul 12, 2014Buggless & PEP compliant CTRCTR mode works with strings nowraises DeprecatedWarning if a number is returnedCBCMAC class added (use static method CBCMAC.new(args) to create)Version 0.3.2; Jul 11, 2014Minor FixesVersion 0.3.1; Jul 11, 2014Minor FixesFixed that the length of data will not be checkedVersion 0.3.0; Jul 11, 2014Added CFB modeFully working with PEP 272Raising NotImplementedError only on PGP-CFB (OpenPGP) modeWheel support and changelog (0.2.1)(unreleased) Version 0.2.1 - dev; Jul 10, 2014Added better wheel support for uploading (just for me) with a setup.cfgAdded this file (auto uploading on pypi/warehouse and github)(upload.py for github)Version 0.2.0; Jul 9, 2014Added a test feature; warning in CTRRaises warning on CTR, added a handler that CTR will not crash anymore ;)Version 0.1.1; Jul 9, 2014Module raises a NotImplementedError on CFBMinor changesVersion 0.1; Jun 22, 2014Initial releaseSupports all mode except CFBBuggy CTR ( \u201c\u00c3\u0178\u201d = \u201c\\xc3\\x9f\u201d )Working with PEP 272, default mode is ECB"} +{"package": "xtea3", "pacakge-description": "As the packagexteais now compatible with both major Python versions, 2 and 3,\ntwo different package versions are not required anymore.All non utility members of thextea3namespace will remain in place,\nbut are internally used from thexteapackage instead,\nwhich will be automatically installed with this updated version."} +{"package": "xtea4", "pacakge-description": "This is an XTEA-Cipher implementation in Python (eXtended Tiny Encryption Algorithm).XTEA is a blockcipher with 8 bytes blocksize and 16 bytes Keysize (128-Bit).\nThe algorithm is secure at 2014 with the recommend 64 rounds (32 cycles). This\nimplementation supports following modes of operation:\nECB, CBC, CFB, OFB, CTRExample:>>> from xtea4 import *\n>>> key = \" \"*16 # Never use this\n>>> text = \"This is a text. \"*8\n>>> x = new(key, mode=MODE_OFB, IV=\"12345678\")\n>>> c = x.encrypt(text)\n>>> text == x.decrypt(c)\nTrueNoteI do NOT guarantee that this implementation (or the base cipher) is secure. If you find bugs, please report them athttps://github.com/tgates42/xtea/issues.Changelog(dev) Version 0.6.1; \u2026Improved testsPEP8-style formattingUnittests: Counter, modes (but not results of them!), test vectors[BREAKING CHANGE] Counter class is now in xtea4.counter(unreleased) Version 0.6.0; Oct 16, 2016Python 3 does work now[BREAKING CHANGE] counters cannot return numbers any more, they must return bytestrings now[BREAKING CHANGE] Cipher objects remember state, so two consecutive calls to XTEACipher.encrypt should not return the sameimproved documentation(unreleased) Version 0.5.0; Oct 15, 2016Removed CBCMACVersion 0.4.1; Jul 30, 2015Fixed installerVersion 0.4.0; Jul 12, 2014Buggless & PEP compliant CTRCTR mode works with strings nowraises DeprecatedWarning if a number is returnedCBCMAC class added (use static method CBCMAC.new(args) to create)Version 0.3.2; Jul 11, 2014Minor FixesVersion 0.3.1; Jul 11, 2014Minor FixesFixed that the length of data will not be checkedVersion 0.3.0; Jul 11, 2014Added CFB modeFully working with PEP 272Raising NotImplementedError only on PGP-CFB (OpenPGP) modeWheel support and changelog (0.2.1)Version 0.2.1 - dev; Jul 10, 2014Never released\u2026Added better wheel support for uploading (just for me) with a setup.cfgAdded this file (auto uploading on pypi/warehouse and github)(upload.py for github)Version 0.2.0; Jul 9, 2014Added a test feature; warning in CTRAdded a test featureRaises warning on CTR, added a handler that CTR will not crash anymore ;)Version 0.1.1; Jul 9, 2014[0.1.1] NotImplementedError on CFBModule raises a NotImplementedError on CFBMinor changesVersion 0.1; Jun 22, 2014[0.1] Initial releaseSupports all mode except CFBBuggy CTR ( \u201c\u00df\u201d = \u201c\\xc3\\x9f\u201d )Working with PEP 272, default mode is ECB"} +{"package": "xtelligent-serial", "pacakge-description": "Serialization + JSONSynopsisThis library is intended to serialize objects to and from Python primitives. That is,\nobjects will be represented as dict, list, int, float, bool, str, and None. The resulting\nprimitives may be easily serialized to JSON usingpython.jsonor this library.Because the library focuses on representation with native primitives, it could be useful\nfor serialization to other formats.UsageThe library usesdecoratorsto mark methods in charge of serialization. There's aserializerdecorator that associates a function with serializing a specific type, and\nthere's a correspondingdeserializer:@serializer(datetime)defdthandler(dt:datetime):returndt.isoformat()@deserializer(datetime)defstr2dt(datestr:str):returndatetime.fromisoformat(datestr)Finally, the library implements aserializationdecorator to make a class in charge of\nserializing itself. Please see theexampleto illustrate.Thextelligent_serial.jsonnamespace includes two convenience methods for reading and writing to\nand from JSON. Thefrom_jsonandto_jsonfunctions are documentedhere. The\nfunctions serialize types that your code supports with the serialization decorators.AutomaticdataclasssupportPython'sdataclasswith thefrozenoption creates the rough equivalent of aNamedTuple, but you\nmay still add methods and properties. Immutability is a great practice for creating testable,\nreadable code. A frozendataclassdoes not acquire the \"infinite state machine\" behaviors common\nto object-oriented class design. It is beyond the scope of this document to create full justification\nof immutability, and there is an abundance of material on this subject. It is obvious that a frozendataclassmaps very well to JSON documents. The consistent structure ofdataclasstypes make it\nstraightforward for this library to support these classes automatically, without decorators. The only\ncaveat is that all member attribute types must be supported by decorators, or they must also be\nprimitive ordataclasstypes. Again, please see theexampleto illustrate.DocumentationAPI ReferenceExampleGeneral example:Source CodeExample of use with attrs third party library:Source CodeRoadmapIntegration withjson.JSONDecoderandjson.JSONEncoder. For now, this module is an alternative\nto thejsonmodule.Serialization convenience methods on the decorators.Support for automatic deserialization. Right now, it is required to pass a parameter indicating\nthe type to deserialize to.Research automatic support for NamedTuple."} +{"package": "xtellixClient", "pacakge-description": "Python Client to Connect Solve-Hub xtellix Optimization ServerDraft Version 0.0.1This is a simple example usage of how to initialize the Optimization Engine Server and Perform Optimization on your objective functions.The remaining documents is in two (2) parts:Section A: Initializing Server; andSection B: Running the Optimization Loop.SECTION APREREQUISITES: INSTALL KEY LIBRARIES & INITIALIZE SERVERInstall xtellixClient using pip commandhttps://pypi.org/project/xtellixClient-0.0.1/Read more atGithubpip install xtellixClientSTEP 1A: IMPORT XTELLIX CLIENT LIBRARIESImport the xtellixClient moduleimportxtellixClient.xtellixClientasxmSTEP 1B: IMPORT OTHER KEY LIBRARIESimportmathimportnumpyasnpfromtqdmimporttrangeimporttimeSTEP 2: OBJECTIVE FUNCTIONDefine your cost or objective functionHere we define the Griewank function as en example. More infomation about the Griewank benchmark function can be found on theweb.defgriewank_function(x,dim):\"\"\"Griewank's function \tmultimodal, symmetric, inseparable \"\"\"sumPart=0prodPart=1foriinrange(dim):sumPart+=x[i]**2prodPart*=math.cos(float(x[i])/math.sqrt(i+1))return1+(float(sumPart)/4000.0)-float(prodPart)OPTIONAL STEP 2B: COST FUNCTION WRAPPERS FOR THE OBJECTIVE FUNCTIONTo make it easier to dynamically call other benchmark functions without changing much of the code, we recommend defining a general purpose wrapper to be called during the optimization processdefcost_function(newSuggestions,dim):\"\"\"Generic function wrapper for the cost function \"\"\"returngriewank_function(newSuggestions,dim)STEP 3: INITIALIZE CONNECTION TO THE OPTIMIZATION SERVERConnect to your unique optimization server using your provided credentials:server_endpoint, andclient_secret_token. These are two are used to established a secured successful connection before you can begin any optimization project. Watch for server connection errors and contact the support team for assistance#set server_endpoint and client_secret_token as variablessever_endpoint=\"http://127.0.0.1:5057\"client_secret=1234567890#Initialize connection and watch for errorsxm.connect(sever_endpoint,client_secret)STEP 4: INITIALIZE THE OPTIMIZATION ENGINELet's begin by setting up all the initial parameters for the objective function, then the optimization enginea. Initial parameters for the Cost Functionubound=600#upper bound of the Griewank functionlbound=-600#lower bound of the Griewank functiondim=100#problem dimensionb. Optimization Engine SettingsinitMetric=30000000#largest possible cost function value - arbitrary very large/low number for minimization/maximization problems respectivelymaxIter=dim*200# maximum number of iterations. We recommend 100 to 200 times the dimension of the problem. and 10 - 50 times for intensive CPU problemsmaxSamples=8# maximum number of default stochastic samplingiseedId=0#Seed value for random number generatorminOrMax=True### True for MINIMIZATION | False for MAXIMIZATIONc. Prepare the initial parameter valuex0=np.ones([dim])*lboundd. Compute the first objective functionfobj=cost_function(x0,dim)initMetric=fobj#Optional: use the first value as initial metricprint(\"Initial Objective Function Value = \",fobj)e. Initialize Optimization Enginexm.initializeOptimizer(initMetric,ubound,lbound,dim,maxIter,maxSamples,x0,iseedId,minOrMax)SECTION BTHE OPTIMIZATION LOOP: SOLVING YOUR OPTIMIZATION PROBLEM3 SIMPLE STEPS: GET -> COMPUTE -> UPDATESolving the optimizatin problem (here: Griewank function) is done in the following three (3) steps:a. Get new suggested parameters from the optimization servernewSuggestions=xm.getParameters()b. Compute new cost function based on the new parametersfobj=cost_function(newSuggestions,dim)c. Send new cost function value to the optimization serverxm.updateObjectiveFunctionValue(fobj)d. Repeat the whole process until optimization is achievedThe whole process can be summarized below:The Optimization Loop with comments#OPtional Step: Use TQDM Library for nice progress barwithtrange(maxIter)ast:foriint:##a: Get parameters from Optimization EnginenewSuggestions=xm.getParameters()##b: Compute new cost function value based on the parametersfobj=cost_function(newSuggestions,dim)##c: Send new cost function value to optimization serverxm.updateObjectiveFunctionValue(fobj)##Optional step: Check the progress of the optmizationobj,pareato,_,svrit=xm.getProgress()###Optional step: Update the progress bart.set_description('Function Eval%i'%i)t.set_postfix(current=obj,best=pareato)The Optimization Loop WITHOUT commentsWe see the simplicity of the process without the commentsforiinrange(maxIter):newSuggestions=xm.getParameters()fobj=cost_function(newSuggestions,dim)xm.updateObjectiveFunctionValue(fobj)GET FINAL PARAMETERS FROM SERVERGet the optimized parametersx0=xm.getParameters()Or Get the optimized parameter (force download a fresh copy from the server)x0=xm.getParameters(False)Calculate the final objective function valuefobj=cost_function(x0,dim)Print final objective function value and optimized parametersprint(fobj)print(x0)The full code for the above exampleimportxtellixClient.xtellixClientasxmimportmathimportnumpyasnpfromtqdmimporttrangedefgriewank_function(x,dim):\"\"\"Griewank's function \tmultimodal, symmetric, inseparable \"\"\"sumPart=0prodPart=1foriinrange(dim):sumPart+=x[i]**2prodPart*=math.cos(float(x[i])/math.sqrt(i+1))return1+(float(sumPart)/4000.0)-float(prodPart)defcost_function(newSuggestions,dim):\"\"\"Generic function wrapper for the cost function \"\"\"returngriewank_function(newSuggestions,dim)#set server_endpoint and client_secret_token as variablessever_endpoint=\"http://127.0.0.1:5057\"client_secret=1234567890#Initialize connection and watch for errorsxm.connect(sever_endpoint,client_secret)ubound=600lbound=-600dim=100initMetric=30000000maxIter=dim*200maxSamples=8iseedId=0minOrMax=True## True for MINIMIZATION | False for MAXIMIZATIONx0=np.ones([dim])*lboundfobj=cost_function(x0,dim)print(\"Initial Objective Function Value = \",fobj)xm.initializeOptimizer(initMetric,ubound,lbound,dim,maxIter,maxSamples,x0,iseedId,minOrMax)##OPTIMIZATION LOOPforiinrange(maxIter):newSuggestions=xm.getParameters()fobj=cost_function(newSuggestions,dim)xm.updateObjectiveFunctionValue(fobj)##Optional step: Check the progress of the optmizationobj,pareato,feval,_=xm.getProgress()print(\"Feval = \",feval,\" Best Objective = \",pareato,\" Current Objective = \",obj)x0=xm.getParameters(False)fobj=cost_function(x0,dim)print(fobj)print(x0)"} +{"package": "xtellixClient-0.0.1", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtellixClient-0.0.2", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtelnet", "pacakge-description": "xtelnetThis is an easy to use telnet module to interact with a remote system smoothly over this protocol!Why should I use xtelnet?Easy to use and stableSimple Authentication mechanismCompatible with almost all servers when it comes to authentication and executing the commandsAvailable Command line toolThread-safe: if the session is shared among threads to execute commands, the commands will be executed one by oneSupports running multiple sessions concurrentlyCan connect simultaneously and run in parallel the same command on: single or some or all connected hostsAllow reconnect after closing the connectionAllow escape ANSI charactersGrab bannersAvailable \"ping\" function to use if you want to keep the connection openSupports SOCKS 4 / 5 proxiesSupports SSLInstall :pip install xtelnetorpip3 install xtelnetUsage on a script :importxtelnett=xtelnet.session()\nip='192.168.0.32'#just an examplet.connect(ip, username='root',password='toor',p=23,timeout=5)\noutput1=t.execute('echo ala_is_king')print(output1)\noutput2=t.execute('cd / && ls')print(output2)\nt.cwd('/')#change working directoryt.switch_terminal('tclsh')#change terminal type where the prompt will get changed as well (just and example of command to do it on some routers)t.switch_terminal('tclquit')\nt.close()#close the connection but keep the connection string to do reconnect latert.reconnect()#reconnect to the host with the previous parameterst.ping()#send new line to the host to keep the connectio opent.destroy()#close the connection and remove the connection string totally, after this you can't do \"reconnect\"t.destroy()#close the connection and remove the connection string totally, after this you can't do \"reconnect\"t.connect('114.35.81.134',proxy_type=5,proxy_host='localhost',proxy_port=9150,proxy_username='user',proxy_password='pass')#use SOCKS5 proxy to connect, set 'proxy_type' to 4 to use SOCKS4To start a manual interactive session after login, just do:importxtelnett=xtelnet.session()\nip='192.168.0.32'#just an examplet.connect(ip, username='root',password='toor',p=23,timeout=5)\nt.interact()The multi_session helps you in controlling multiple telnet sessions in parallel:importxtelnett=xtelnet.multi_session()\nip1='192.168.0.32'#just an exampleip2='192.168.0.4'ip3='192.168.0.10'ip4='192.168.0.11'ip5='192.168.0.12'host1=xtelnet.dict_host(ip1, username='root',password='toor',p=23,timeout=5)\nhost2=xtelnet.dict_host(ip2, username='root',password='toor',p=23,timeout=5)\nhost3=xtelnet.dict_host(ip3, username='root',password='toor',p=23,timeout=5)\nhost4=xtelnet.dict_host(ip4, username='root',password='toor',p=23,timeout=5)\nhost5=xtelnet.dict_host(ip5, username='root',password='toor',p=23,timeout=5)\nt.connect([host1,host2,host3,host4,host5])print(t.sessions)#to see the connected hostsc=t.all_execute('echo \"ala is king\"')#execute this command on all hostsprint(c)#print outputc=t.some_execute([ip1,ip2],'echo \"ala is king\"')#execute this command on some hostsprint(c)\nc=t.host_execute(ip1,'echo \"ala is king\"')#execute this command on this hostprint(c)\nt.disconnect_host(ip1)#to disconnect of this hostt.disconnect_some([ip2,ip3])#to disconnect of those hostst.disconnect_all()#to disconnect of all hostst.destroy()#disconnect from all hostsUsage from command line :xtelnet host [options...]options:-username : set a username (required if username is needed to access)-password : set a password (required if password is needed to access)-port : (23 by default) set port-timeout : (5 by default) set timeout--add-command : a command to execute after login and disable shell--set-newline : (\"\\n\" by default) set a new line indecator(\"\\n\" or \"\\r\\n\")--no-shell : (enabled by default if no commands are specified) disable shell after authentication--read-retries : times to retry reading the response if it takes too long--help : get this help messageexamples:xtelnet 127.0.0.1 -username root -password root --add-command \"echo ala\" --add-command \"dir\"xtelnet 127.0.0.1 -username root -password root -port 2323 -timeout 5xtelnet 127.0.0.1 -username root -password root -port 2323 -timeout 5 --no-shellXtelnet can be used to grab banners:importxtelnettelnet_banner=xtelnet.get_banner(\"localhost\",p=23)#suppose you have telnet server running on that porthttp_banner=xtelnet.get_banner(\"www.google.com\",p=80,payload=\"GET / HTTP/1.1\\r\\nHost:www.google.com\\r\\n\\r\\n\")#we send a http request as a payload to get the responsessh_banner=xtelnet.get_banner(\"localhost\",p=22)Xtelnet can escape all ANSI characters :importxtelnetescaped_string=xtelnet.escape_ansi( unescaped_string )"} +{"package": "xTemplate", "pacakge-description": "No description available on PyPI."} +{"package": "xtempmail", "pacakge-description": "Temporary MailTempmail client fortempmail.plusInstallation$pipinstallgit+https://github.com/krypton-byte/xtempmailFeatureCustom Name/MailReply/send Message(support attachment file)Read Message (support Download attachment file)Delete messageDestroy InboxLock InboxUnlock InboxGenerate Secret InboxAsynchronousSynchronousExampleexample/main.pyUsage SyncfromxtempmailimportEmail,extensionimportloggingfromxtempmail.mailimportEmailMessage,EMAILlog=logging.getLogger('xtempmail')log.setLevel(logging.INFO)app=Email(name='krypton',ext=ext=EMAIL.MAILTO_PLUS))@app.on.message()defbaca(data:EmailMessage):print(f\"\\tFrom:{data.from_mail}\\n\\tSubject:{data.subject}\\n\\tBody:{data.text}\\n\\tReply -> Delete\")ok=[]foriindata.attachments:# -> Forward attachmentok.append((i.name,i.download()))ifdata.from_is_local:data.from_mail.send_message(data.subject,data.text,multiply_file=ok)# -> Forward messagedata.delete()#delete message@app.on.message(lambdamsg:msg.attachments)defget_message_media(data:EmailMessage):print(f'Attachment:{[i.nameforiindata.attachments]}')@app.on.message(lambdax:x.from_mail.__str__().endswith('@gmail.com'))defgetGmailMessage(data:EmailMessage):print(f'Gmail:{data.from_mail}')if__name__=='__main__':try:app.listen_new_message(1)exceptKeyboardInterrupt:app.destroy()#destroy inboxUsage Asyncimportasyncioimportloggingfromxtempmail.aiomailimportEMAIL,EmailMessage,Emaillog=logging.getLogger('xtempmail')log.setLevel(logging.INFO)app=Email(name='krypton',ext=EMAIL.MAILTO_PLUS)@app.on.message()asyncdefbaca(data:EmailMessage):print(f\"\\tFrom:{data.from_mail}\\n\\tSubject:{data.subject}\\n\\tBody:{data.text}\\n\\tReply -> Delete\")ok=[]foriindata.attachments:# -> Forward attachmenok.append((i.name,awaiti.download()))ifdata.from_is_local:awaitdata.from_mail.send_message(data.subject,data.text,multiply_file=ok)# -> Forward messageawaitdata.delete()#delete message@app.on.message(lambdamsg:msg.attachments)asyncdefget_message_media(data:EmailMessage):print(f'Attachment:{[i.nameforiindata.attachments]}')@app.on.message(lambdax:x.from_mail.__str__().endswith('@gmail.com'))asyncdefgetGmailMessage(data:EmailMessage):print(f'Gmail:{data.from_mail}')if__name__=='__main__':try:loop=asyncio.new_event_loop()loop.run_until_complete(app.listen())exceptException:asyncio.run(app.destroy())Demo"} +{"package": "xtendcms", "pacakge-description": "=====\nXtendCMSXtendCMS is a admin styling app for the wagtail cms system.Quick startAdd \"xtendcms\" to your INSTALLED_APPS setting like this::INSTALLED_APPS = [\n...\n'xtendcms',\n]Runpython manage.py migrateto create the XtendCMS models."} +{"package": "xtenors", "pacakge-description": "xtenorsTable of ContentsInstallationOverviewExamplesPerformanceLicenseInstallationpip install xtenorsOverviewExamplesPerformanceLicensextenorsis distributed under the terms of theMITlicense."} +{"package": "xtensor", "pacakge-description": "UNKNOWN"} +{"package": "xtensor-python", "pacakge-description": "UNKNOWN"} +{"package": "xtensors", "pacakge-description": "xtensorsis a named tensor utility library.InstallationInstall withpip:pip install xtensorsDocumentationDocumentaion is available onhttps://xtensors.readthedocs.io/en/latest"} +{"package": "xter", "pacakge-description": "No description available on PyPI."} +{"package": "xterm", "pacakge-description": "made bymat"} +{"package": "xterm256-colors", "pacakge-description": "xterm256-colorsEasily colorize text printed to an xterm-256color terminal emulatorfromxterm256_colorsimportFore256,Back256print(Fore256.CHARTREUSE1('Hello,'),Back256.HOTPINK('World!'))Installationpipinstallxterm256-colors"} +{"package": "xterm256-converter", "pacakge-description": "No description available on PyPI."} +{"package": "xtermcolor", "pacakge-description": "UNKNOWN"} +{"package": "xtermutil", "pacakge-description": "No description available on PyPI."} +{"package": "xtest", "pacakge-description": "pyrex interface to XTest including faking multi-key presses such as Control-Shift-sversion 1.21 adds fakeRelativeMotionEvent and the missing flush calls"} +{"package": "xtesting", "pacakge-description": "Xtesting have leveraged on Functest efforts to provide a reference testing\nframework:Requirements Management:https://wiki.opnfv.org/display/functest/Requirements+managementDocker Slicing:http://testresults.opnfv.org/functest/dockerslicing/Functest Framework:http://testresults.opnfv.org/functest/framework/Xtesting aims at allowing a smooth integration of new Functest Kubernetes\ntestcases.But, more generally, it eases building any CI/CD toolchain for other\ndomains than testing Virtualized Infrastructure Managers (VIM) such asOpenStack.To learn more about Xtesting:Documentation:http://xtesting.readthedocs.io/en/latest/Gerrit:https://gerrit.opnfv.org/gerrit/#/q/project:functest-xtestingGet in touch viaemail."} +{"package": "xtesting-db-populate", "pacakge-description": "xtesting-db-populateScript to populate xtesting-db with project, tests cases and pods.This application read local xtesting files and variables to populate\ntest databases.Installpip install xtesting-db-populateRequirementsTo create projects and populate tests cases,testcases.yamlfile\nisMandatoryTo get the testapi url, theMandatoryvariableTEST_DB_URLmust\nbe set with the value of the test api url\n(https://testapi.test/api/v1/)If you want to set pods,One ofthe two may be set:an environment variableNODE_NAMEmust be set to the pod value\n(pod1)a filepods.yamlthat should be like:---pods:-pod1-pod2Usage!\ue0b0~/D/v/a/v/xtesting_project\ue0b0\ue0a0\ue0b0testing-db-populate\n\ud83c\udfafgettestapiurl[success]\ud83d\udce4readpods.yaml[success]\ud83e\udd16populatepod\"pod1\"[skipped]\ud83e\udd16populatepod\"pod2\"[skipped]\ud83d\udce4readtestcases.yaml[success]\ud83d\udce6populateproject\"project1\"[skipped]\ud83d\udccbpopulatecase\"test 1\"[skipped]\ud83d\udccbpopulatecase\"test 2\"[skipped]\ud83d\udccbpopulatecase\"test 3\"[skipped]\ud83d\udccbpopulatecase\"test 4\"[skipped]To specify the folder where is store testcases.yaml et pods.yaml add\nthe folder path as argument. As an example if they are ontestsfolder:!\ue0b0~/D/v/a/v/xtesting_project\ue0b0\ue0a0\ue0b0testing-db-populatetests\n\ud83c\udfafgettestapiurl[success]\ud83d\udce4readpods.yaml[success]\ud83e\udd16populatepod\"pod1\"[skipped]\ud83e\udd16populatepod\"pod2\"[skipped]\ud83d\udce4readtestcases.yaml[success]\ud83d\udce6populateproject\"project1\"[skipped]\ud83d\udccbpopulatecase\"test 1\"[skipped]\ud83d\udccbpopulatecase\"test 2\"[skipped]\ud83d\udccbpopulatecase\"test 3\"[skipped]\ud83d\udccbpopulatecase\"test 4\"[skipped]"} +{"package": "xtestlib", "pacakge-description": "X's Test Library"} +{"package": "xtestrunner", "pacakge-description": "Modern style test report based on unittest framework.\u57fa\u4e8eunittest\u6846\u67b6\u73b0\u4ee3\u98ce\u683c\u6d4b\u8bd5\u62a5\u544a\u3002\u7279\u70b9\u7b80\u6d01\u3001\u7f8e\u89c2\u5177\u6709\u73b0\u4ee3\u98ce\u683c\u7684\u6d4b\u8bd5\u62a5\u544a\u3002\u652f\u6301HTML/XML\u4e0d\u540c\u683c\u5f0f\u3002\u652f\u6301\u5355\u5143\u3001Web UI\u3001API\u5404\u79cd\u7c7b\u578b\u7684\u6d4b\u8bd5\u3002\u96c6\u6210\u90ae\u4ef6/\u9489\u9489/\u4f01\u5fae/\u98de\u4e66\u53d1\u9001\u6d88\u606f\u3002\u652f\u6301\u7528\u4f8b\u9519\u8bef/\u5931\u8d25\u91cd\u8dd1\u3002\u652f\u6301\u6807\u7b7e\u9ed1\u3001\u767d\u540d\u5355\u3002\u9488\u5bf9Selenium\u8fd0\u884c\u5931\u8d25/\u9519\u8bef\u81ea\u52a8\u622a\u56fe\uff08HTML\u683c\u5f0f\uff09\u3002\u652f\u6301\u591a\u8bed\u8a00en\u3001zh-CN\uff08HTML\u683c\u5f0f\uff09\u3002ReportInstall>pipinstallXTestRunnerIf you want to keep up with the latest version, you can install with github repository url:>pipinstall-Ugit+https://github.com/SeldomQA/XTestRunner.git@masterdemo\u67e5\u770b\u66f4\u591a\u4f7f\u7528\u4f8b\u5b50\u3002unittest\u6d4b\u8bd5importunittestfromXTestRunnerimportHTMLTestRunnerclassTestDemo(unittest.TestCase):\"\"\"\u6d4b\u8bd5\u7528\u4f8b\u8bf4\u660e\"\"\"deftest_success(self):\"\"\"\u6267\u884c\u6210\u529f\"\"\"self.assertEqual(2+3,5)@unittest.skip(\"skip case\")deftest_skip(self):\"\"\"\u8df3\u8fc7\u7528\u4f8b\"\"\"passdeftest_fail(self):\"\"\"\u5931\u8d25\u7528\u4f8b\"\"\"self.assertEqual(5,6)deftest_error(self):\"\"\"\u9519\u8bef\u7528\u4f8b\"\"\"self.assertEqual(a,6)if__name__=='__main__':suit=unittest.TestSuite()suit.addTests([TestDemo(\"test_success\"),TestDemo(\"test_skip\"),TestDemo(\"test_fail\"),TestDemo(\"test_error\")])with(open('./result.html','wb'))asfp:runner=HTMLTestRunner(stream=fp,title='test report',description='describe: ... ',language='en',rerun=3)runner.run(suit)Document\u66f4\u591a\u4f8b\u5b50\uff0c\u8bf7\u9605\u8bfb\u4e2d\u6587\u6587\u6863\u611f\u8c22\u611f\u8c22\u4ece\u4ee5\u4e0b\u9879\u76ee\u4e2d\u5f97\u5230\u601d\u8def\u548c\u5e2e\u52a9\u3002HTMLTestRunnerHTMLTestRunner_cnTheme style"} +{"package": "xtest-sapnwrfc", "pacakge-description": "PyRFCAsynchronous, non-blockingSAP NetWeawer RFC SDKbindings for Python.FeaturesSupported platformsRequirementsSAP NW RFC SDK 7.50.11DockerWindowsmacOSDownload and installationGetting startedCall ABAP Function Module from PythonCall Python function from ABAPSPJ articlesHow to obtain supportContributingLicenseFeaturesClient and Server bindingsAutomatic conversion between Python and ABAP datatypesStateless and stateful connections (multiple function calls in the same ABAP session / same context)Sequential and parallel calls, using one or more clientsThroughput monitoringSupported platformsAllplatforms supported by SAP NWRFC SDKare supported by build from source installation (build instructions)In addition, pre-built wheels are provided for Windows, Darwin and Ubuntu Linux, attached to PyRFC GitHubreleaseDocker containers:SAP fundamental-tools/dockerLinux wheels supported by build from source installation onlyPre-builtportable Linux wheelsare not supported, neither issues related to portable Linux wheelsmust notbe distributed with embedded SAP NWRFC SDK binaries, only private use permittedRequirementsSAP NW RFC SDK 7.50.11seeSAP Note 3274546for a list of bug fixes and enhancements made with this patch releaseUsing the latest version is recommended as SAP NWRFC SDK is fully backwards compatible, from today S4, down to R/3 release 4.6C.Can be downloaded from SAP Software Download Center of the SAP Support Portal, like described athttps://support.sap.com/nwrfcsdk.If you are lacking the required authorization for downloading software from the SAP Service Marketplace, please follow the instructions ofSAP Note 1037575for requesting this authorization.DockerDocker container examples for Linux, Intel and ARM based Darwin:SAP/fundamental-tools/docker. SAP NWRFC SDK libraries are not included.WindowsVisual C++ Redistributable Package for Visual Studio 2013is required for runtime, seeSAP Note 2573790 - Installation, Support and Availability of the SAP NetWeaver RFC Library 7.50Build toolchain for Python 3 requiresMicrosoft C++ Build Tools, the latest version recommendedBuild toolchain for Python 2 requiresMicrosoft Visual C++ 9.0Due to achange introduced with Python 3.8 for Windows, PATH directories are no longer searched for DLL. The SAP NWRFC SDK lib path is no longer required on PATH, for Python >= 3.8.macOSRemote paths must be set in SAP NWRFC SDK for macOS:documentationWhen the PyRFC is started for the first time, the popups may come-up for each NWRFC SDK library, to confirm the usage. If SAP NW RFC SDK is installed in admin folder, the app shall be first time started with admin privileges, eg.sudo -EDownload and installationpipinstallpyrfcCython must be installed upfront because the build from source is standard installation method on Linux.Build from source can be requested also on other platforms:pipinstallpyrfc--no-binary:all:# orPYRFC_BUILD_CYTHON=yespipinstallpyrfc--no-binary:all:Alternative build from source installation:gitclonehttps://github.com/SAP/PyRFC.gitcdPyRFC\npython-mpipinstall.# orpython-mbuild--wheel--sdist--outdirdist\npipinstall--upgrade--no-index--find-links=distpyrfcSee also thepyrfc documentation,\ncomplementingSAP NWRFC SDKdocumentation, especiallySAP NWRFC SDK 7.50 Programming Guide.Getting startedNote:The package must beinstalledbefore use.Call ABAP Function Module from PythonIn order to call remote enabled ABAP function module (ABAP RFM), first a connection must be opened.frompyrfcimportConnectionconn=Connection(ashost='10.0.0.1',sysnr='00',client='100',user='me',passwd='secret')Connection parameters are documented insapnwrfc.inifile, located in theSAP NWRFC SDKdemofolder. Check also section4.1.2 Using sapnwrfc.iniofSAP NWRFC SDK 7.50 Programming Guide.Using an open connection, remote function modules (RFM) can be invoked. More info inpyrfc documentation.# ABAP variables are mapped to Python variablesresult=conn.call('STFC_CONNECTION',REQUTEXT=u'Hello SAP!')print(result){u'ECHOTEXT':u'Hello SAP!',u'RESPTEXT':u'SAP R/3 Rel. 702 Sysid: ABC Date: 20121001 Time: 134524 Logon_Data: 100/ME/E'}# ABAP structures are mapped to Python dictionariesIMPORTSTRUCT={\"RFCFLOAT\":1.23456789,\"RFCCHAR1\":\"A\"}# ABAP tables are mapped to Python lists, of dictionaries representing ABAP tables' rowsIMPORTTABLE=[]result=conn.call(\"STFC_STRUCTURE\",IMPORTSTRUCT=IMPORTSTRUCT,RFCTABLE=IMPORTTABLE)printresult[\"ECHOSTRUCT\"]{\"RFCFLOAT\":1.23456789,\"RFCCHAR1\":\"A\"...}printresult[\"RFCTABLE\"][{\"RFCFLOAT\":1.23456789,\"RFCCHAR1\":\"A\"...}]Finally, the connection is closed automatically when the instance is deleted by the garbage collector. As this may take some time, we may either call the close() method explicitly or use the connection as a context manager:withConnection(user='me',...)asconn:conn.call(...)# connection automatically closed hereAlternatively, connection parameters can be provided as a dictionary:defget_connection(conn_params):\"\"\"Get connection\"\"\"print'Connecting ...',conn_params['ashost']returnConnection(**conn_param)frompyrfcimportConnectionabap_system={'user':'me','passwd':'secret','ashost':'10.0.0.1','saprouter':'/H/111.22.33.44/S/3299/W/e5ngxs/H/555.66.777.888/H/','sysnr':'00','client':'100','trace':'3',#optional, in case you want to trace'lang':'EN'}conn=get_connection(**abap_system)Connecting...10.0.0.1conn.aliveTrueSee also pyrfc documentation forClient ScenarioCall Python function from ABAP# create server for ABAP system ABCserver=Server({\"dest\":\"gateway\"},{\"dest\":\"MME\"},{\"port\":8081,\"server_log\":False})# expose python function my_stfc_connection as ABAP function STFC_CONNECTION, to be called from ABAP systemserver.add_function(\"STFC_CONNECTION\",my_stfc_connection)# start serverserver.start()# get server attributesprint(\"Server attributes\",server.get_server_attributes())# stop serverinput(\"Press Enter to stop servers...\")server.stop()print(\"Server stoped\")See also pyrfc documentation forServer Scenarioand server examplesource code.SPJ articlesHighly recommended reading about RFC communication and SAP NW RFC Library, published in the SAP Professional Journal (SPJ)Part I RFC Client ProgrammingPart II RFC Server ProgrammingPart III Advanced TopicsHow to obtain supportIf you encounter an issue or have a feature request, you can create aticket.Check out theSAP Community(search for \"pyrfc\") and stackoverflow (use the tagpyrfc), to discuss code-related problems and questions.ContributingWe appreciate contributions from the community toPyRFC!\nSeeCONTRIBUTING.mdfor more details on our philosophy around extending this module.LicenseCopyright (c) 2018 SAP SE or an SAP affiliate company. All rights reserved. This file is licensed under the Apache Software License, v. 2 except as noted otherwise in theLICENSE file."} +{"package": "xtestx", "pacakge-description": "No description available on PyPI."} +{"package": "xtex2svg", "pacakge-description": "Project Page :rod2ik/xtex2svgThis project is part of other mkdocs-related projects.If you're interested, please consider having a look at this page for a more complete list of all our mkdocs-related projects:https://eskool.gitlab.io/mkhack3rs/Initial Influences and History :For All newer Credits: Rodrigo Schwencke atrod2ik/xtex2svg3Initially inspired by Ryan Marcus atRyanMarcus/tex2svgLicences:Rodrigo Schwencke :GPLv3+"} +{"package": "xtfixdemo", "pacakge-description": "No description available on PyPI."} +{"package": "xt-FlaskAPIDocs", "pacakge-description": "flask-api-docsInterface automation document based on flashInstallationIt is possible to install the tool with pip:pip install xt-FlaskAPIDocsUsageSample usage:fromflaskimportFlaskfromflask_api_demo.test.HelloWorldimportHelloWorldfromflask_docsimportBluePrint,Docsapp=Flask(__name__)a=BluePrint('hello',__name__)a.add_url_rule('/hello','hello',HelloWorld().hello_world,methods=['GET'],args={\"test1\":'str',\"test2\":'int'})a.add_url_rule('/bye','bye',HelloWorld().bye_world,methods=['GET'],args={\"test1\":'str',\"test2\":'int'})app.register_blueprint(a)Docs(app,hide_docs=True)"} +{"package": "xtgen", "pacakge-description": "XTGenCommand line tool for generating ML training apps with research data sets and models"} +{"package": "xtgeo", "pacakge-description": "IntroductionXTGeo is a LGPL licensed Python library with C backend to support\nmanipulation of (oil industry) subsurface reservoir modelling. Typical\nusers are geoscientist and reservoir engineers working with\nreservoir modelling, in relation with RMS. XTGeo is developed in Equinor.Detailed documentation forXTGeo at ReadtheDocsFeature summaryPython 3.8+ supportFocus on high speed, using numpy and pandas with C backendRegular surfaces, i.e. 2D maps with regular sampling and rotation3D grids (corner-point), supporting several formats such as\nRMS and EclipseSupport of seismic cubes, usingsegyioas backend for SEGY formatSupport of well data, line and polygons (still somewhat immature)Operations between the data types listed above; e.g. slice a surface\nwith a seismic cubeOptional integration with ROXAR API python for several data types\n(see note later)Linux is main development platform, but Windows and MacOS (64 bit) are supported\nand PYPI wheels for all three platforms are provided.InstallationFor Linux, Windows and MacOS 64bit, PYPI installation is enabled:pip install xtgeoFor detailed installation instructions (implies C compiling), see\nthe documentation.Getting startedimportxtgeo# create an instance of a surface, read from filemysurf=xtgeo.surface_from_file(\"myfile.gri\")# Irap binary as defaultprint(f\"Mean is{mysurf.values.mean()}\")# change date so all values less than 2000 becomes 2000# The values attribute gives the Numpy arraymysurface.values[mysurface.values<2000]=2000# export the modified surface:mysurface.to_file(\"newfile.gri\")Note on RMS Roxar API integrationThe following applies to the part of the XTGeo API that is\nconnected to Roxar API (RMS):RMS is neither an open source software nor a free software and\nany use of it needs a software license agreement in place."} +{"package": "xtgeoviz", "pacakge-description": "xtgeovizUtility functions for plotting xtgeo objects.Installxtgeoviz is available from PyPI.pipinstallxtgeovizUsageimportxtgeoviz.plotasxtgplotimportxtgeosurf=xtgeo.surface_from_file(\"somemap.gri\")xtgplot.quickplot(surf)DocumentationThe documentation can be found athttps://equinor.github.io/xtgeoviz.Developing & ContributingAll contributions are welcome. Please see theContributing documentfor more details and instructions for getting started.LicenseThis software is released under the LGPLv3 license."} +{"package": "xt-githooks", "pacakge-description": "githooks"} +{"package": "xthematic", "pacakge-description": "xthematic=========modify, save and load terminal colors in a convenient manner.Quick Demo~~~~~~~~~~A demo youtube video is available below that showcases the following:- set colors from the terminal through hex codes:- save the current colors as a theme with some name- activate a theme in the terminal|xthematic demo gif|Installation~~~~~~~~~~~~python 3.6+ and pip are required... code:: bashpip install xthematicDevelopment version'''''''''''''''''''.. code:: bashgit clone https://github.com/taesko/xthematic.git && cd xthematicpip install --user .Logging setup (optional)''''''''''''''''''''''''Logs are written to /var/log/xthematic.log if this file doesn't exist orcan't be created because of permissions a warning is printed when theapp is invoked. Backups logs are written to$XDG_CONFIG_HOME/xthematic/logs. You need to create the/var/log/xthematic.log file with r/w permissions if you want to avoidthis... code:: bashsudo touch /var/log/xthematic.logsudo chown username: /var/log/xthematic.logBasic Usage~~~~~~~~~~~Complete help can be found at ``xthematic --help``.The single executable ``xthematic`` is split into 3 subcommands -``view``, ``color`` and ``theme``xthematic view^^^^^^^^^^^^^^View colors in various formats through the terminal.Takes a variable number of arguments in a colorview format and prints aline with specific text, foreground and background colors.the colorview format is made out of 3 fields seperated by ':' and fieldscan be left empty to specify default values.``{foreground_hex}:{background_hex}:{string}``Note - '#' can be omitted at the start of hex codes.e.g. ``FF0000:00FF00:\"Hello World\"`` - print \"Hello World\" with red textand green background. \\`FF0000::\"Hello World\"' - print \"Hello World\"with red text and default background.xthematic color^^^^^^^^^^^^^^^View or set terminal colors.Takes two arguments - ``color_id`` and ``color``\\ (optional). The firstmust be an integer between 0 and 16 while the second a valid hex code(the '#' can be omitted)If only color_id is supplied the respectful terminal color is printed.If both arguments are supplied that terminal color is set to the hexvalue until the terminal session is closed.xthematic theme^^^^^^^^^^^^^^^Activate, save and deactivate themes.Takes a single argument - a name of a theme. Without any other optionalarguments prints the colors of the theme to the terminal. If a themename is not given it prints the current terminal colors.Use the -a, -s, -d feature switches to activate, save or deactivatethemes.Documentation~~~~~~~~~~~~~Man or info pages are not written the most complete documentation is:``xthematic --help``License~~~~~~~This project is licensed under the MIT License - see the`LICENSE `__file for details.Authors~~~~~~~- Antonio TodorovAcknowledgements~~~~~~~~~~~~~~~~- the `pywal `__ project forinspiration and example of code printing escape sequences which waspart of the earliest version... |xthematic demo gif| image:: https://img.youtube.com/vi/w0SPD3lVWHE/0.jpg:target: https://www.youtube.com/watch?v=w0SPD3lVWHE"} +{"package": "xtheme", "pacakge-description": "XTHEMETheme manager for people who are tired of writing tons of config files.\nInspired bybudRich/mondo.Installgitclonehttps://github.com/rtnx/xthemecdxtheme\npipinstall--user.ThemesTheme files are intomlformat. There's no requirements for them,\nthey are there for you to set variable that will be used later in generators.GeneratorsGenerators include:template.jinja2 - template for config file using variables from theme.config.toml - configuration file.pre-apply.sh - script executed before applying themepost-apply.sh - script executed after applying theme.config.toml:[config]name='i3'target='/home/rtgnx/.i3/config'# target file to which template is rendered"} +{"package": "x-thonny", "pacakge-description": "Thonny is a simple Python IDE with features useful for learning programming. Seehttps://thonny.orgfor more info."} +{"package": "xthread", "pacakge-description": "Threading for human.FeaturesSome of main features:Support pause/unpauseSupport termination thread non-preemtivelyInstallationYou can install xthread from PyPi$pipinstallxthreadUsageimporttimefromxthreadimportThreaddeftarget(executor):print(\"Running...\")time.sleep(1)thread=Thread(target)# Running...# Running...thread.pause()thread.unpause()# Running...# Running...thread.stop()"} +{"package": "xtick", "pacakge-description": "xtickVisualization for intraday data"} +{"package": "xtictoc", "pacakge-description": "Xtictoc (Tic-Tac-Toe) GameWelcome to Xtictoc, a simple console-based Tic-Tac-Toe (XO) game in Python.InstallationYou can install the game usingpip:pipinstallxtictocHow to PlayTo start the game, open a terminal and run:xtictocFollow the prompts to make your moves and enjoy playing Tic-Tac-Toe against a bot opponent.DevelopmentIf you'd like to contribute to the development of this game or explore the source code, feel free to check out the GitHub repository.LicenseThis game is licensed under the MIT License - see the LICENSE file for details."} +{"package": "xtiff", "pacakge-description": "xtiffA tiny Python library for writing multi-channel TIFF stacks.The aim of this library is to provide an easy way to write multi-channel image stacks for external visualization and\nanalysis. It acts as an interface to the populartifffilepackage and supportsxarrayDataArrays as well asnumpy-compatible data structures.To maximize compatibility with third-party software, the images are written in standard-compliant fashion, with minimal\nmetadata and in TZCYX channel order. In particular, a minimal (but customizable) subset of the OME-TIFF standard is\nsupported, enabling the naming of channels.RequirementsThis package requires Python 3.8 or newer.Using virtual environments is strongly recommended.InstallationInstall xtiff and its dependencies with:pip install xtiffUsageThe package provides the following main function for writing TIFF files:to_tiff(img, file, image_name=None, image_date=None, channel_names=None, description=None,\n profile=TiffProfile.OME_TIFF, big_endian=None, big_tiff=None, big_tiff_threshold=4261412864,\n compression_type=None, compression_level=0, pixel_size=None, pixel_depth=None,\n interleaved=True, software='xtiff', ome_xml_fun=get_ome_xml, **ome_xml_kwargs)\n\n\nimg: The image to write, as xarray DataArray or numpy-compatible data structure.\n Supported shapes:\n - (y, x),\n - (c, y, x)\n - (z, c, y, x)\n - (t, z, c, y, x)\n - (t, z, c, y, x, s)\n Supported data types:\n - any numpy data type when using TiffProfile.TIFF\n - uint8, uint16, float32 when using TiffProfile.IMAGEJ (uint8 for RGB images)\n - bool, int8, int16, int32, uint8, uint16, uint32, float32, float64 when using TiffProfile.OME_TIFF\n\nfile: File target supported by tifffile TiffWriter, e.g. path to file (str, pathlib.Path) or binary stream.\n\nimage_name: Image name for OME-TIFF images. If True, the image name is determined using the DataArray name or\n the file name (in that order); if False, the image name is not set. If None, defaults to the behavior for True\n for named DataArrays and when the file path is provided, and to the behavior of False otherwise. Only relevant\n when writing OME-TIFF files, any value other than None or False will raise a warning for other TIFF profiles.\n\nimage_date: Date and time of image creation in '%Y:%m:%d %H:%M:%S' format or as datetime object. Defaults to\n the current date and time if None. Note: this does not determine the OME-XML AcquisitionDate element value.\n\nchannel_names: A list of channel names. If True, channel names are determined using the DataArray channel\n coordinate; if False, channel names are not set. If None, defaults to the behavior for True for DataArrays when\n writing multi-channel OME-TIFFs, and to the behavior for False otherwise. Only relevant when writing\n multi-channel OME-TIFF files, any value other than None or False will raise a warning for other TIFF profiles.\n\ndescription: TIFF description tag. Will default to the OME-XML header when writing OME-TIFF files. Any value\n other than None will raise a warning in this case.\n\nprofile: TIFF specification of the written file.\n Supported TIFF profiles:\n - TIFF (no restrictions apply)\n - ImageJ (undocumented file format that is supported by the ImageJ software)\n - OME-TIFF (Open Microscopy Environment TIFF standard-compliant file format with minimal OME-XML header)\n\nbig_endian: If true, stores data in big endian format, otherwise uses little endian byte order. If None, the\n byte order is set to True for the ImageJ TIFF profile and defaults to the system default otherwise.\n\nbig_tiff: If True, enables support for writing files larger than 4GB. Not supported for TiffProfile.IMAGEJ.\n\nbig_tiff_threshold: Threshold for enabling BigTIFF support when big_tiff is set to None, in bytes. Defaults\n to 4GB, minus 32MB for metadata.\n\ncompression_type: Compression algorithm, see tifffile.TIFF.COMPRESSION() for available values. Compression is\n not supported for TiffProfile.IMAGEJ. Note: Compression prevents from memory-mapping images and should therefore\n be avoided when images are compressed externally, e.g. when they are stored in compressed archives.\n\ncompression_level: Compression level, between 0 and 9. Compression is not supported for TiffProfile.IMAGEJ.\n Note: Compression prevents from memory-mapping images and should therefore be avoided when images are compressed\n externally, e.g. when they are stored in compressed archives.\n\npixel_size: Planar (x/y) size of one pixel, in micrometer.\n\npixel_depth: Depth (z size) of one pixel, in micrometer. Only relevant when writing OME-TIFF files, any value\n other than None will raise a warning for other TIFF profiles.\n\ninterleaved: If True, OME-TIFF images are saved as interleaved (this only affects OME-XML metadata). Always\n True for RGB(A) images (i.e., S=3 or 4) - a warning will be raised if explicitly set to False for RGB(A) images.\n\nsoftware: Name of the software used to create the file. Must be 7-bit ASCII. Saved with the first page only.\n\nome_xml_fun: Function that will be used for generating the OME-XML header. See the default implementation for\n reference of the required signature. Only relevant when writing OME-TIFF files, ignored otherwise.\n\nome_xml_kwargs: Optional arguments that are passed to the ome_xml_fun function. Only relevant when writing\n OME-TIFF files, will raise a warning if provided for other TIFF profiles.In addition,get_ome_xml()is provided as the default OME-XML-generating function.FAQWhat metadata is included in the written images?In general, written metadata is kept at a minimum and only information that can be inferred from the raw image data is\nincluded (image dimensions, data type, number of channels, channel names for xarrays). Additional metadata natively supported by the\ntifffile package can be specified using function parameters. For OME-TIFF files, the OME-XML \"Description\" tag contents\ncan be further refined by specifying custom OME-XML-generating functions.Why should I care about TIFF? I use Zarr/NetCDF/whatever.That's good! TIFF is an old and complex file format, has many disadvantages and is impractical for storing large images.\nHowever, it also remains one of the most widely used scientific image formats and is (at least partially) supported by\nmany popular tools, such as ImageJ. With xtiff, you can continue to store your images in your favorite file format,\nwhile having the opportunity to easily convert them to a format that can be read by (almost) any tool.Why can't I use the tifffile package directly?Of course you can! Christoph Gohlke'stifffilepackage provides a very powerful and\nfeature-complete interface for writing TIFF files and is the backend for xtiff. Essentially, the xtiff package is just a\nwrapper for tifffile. While you can in principle write any image directly with tifffile, in many cases, the flexibility\nof the TIFF format can be daunting. The xtiff package reduces the configuration burden and metadata to an essential\nminimum.AuthorsCreated and maintained by Jonas Windhagerjonas.windhager@uzh.chContributingContributingChangelogChangelogLicenseMIT"} +{"package": "xtify", "pacakge-description": "AboutPython library for using theXtifyweb service API for mobile push notifications.RequirementsTested using Python 2.7, it will probably work on older versions. For versions\nof Python 2.5 or earlier``simplejson`` will need to be installed.FunctionalityAs of version 0.1 only the Xtify Push API 2.0 is implemented. Mostly because it\nwas the only one I needed, at least for now\u2026.Available Classes:\nPushNotification, PushContent, PushAction, PushRichContentUsage Examples>>> import xtify\n>>> pushNotif = xtify.PushNotification(appKey='myAppKey', apiKey='myApiKey)\n>>> pushNotif.sendAll=True\n>>> pushNotif.content.subject='greetings earthling'\n>>> pushNotif.content.message='take me to your leader'\n>>> pushNotif.push()>>> import xtify\n>>> pushContent = xtify.PushContent(\n subject='greetings earthling', message='take me to your leader')\n>>> pushNotif = xtify.pushNotification(\n appKey='myAppKey', apiKey='myApiKey', sendall=True, content=pushContent)\n>>> pushNotif.push()"} +{"package": "xtime", "pacakge-description": "xtimeInstallationpip3installxtimeUsageimportxtimetime_string=xtime.timestamp_to_string(seconds,f='%Y-%m-%d%H:%M:%S')"} +{"package": "xtimeout", "pacakge-description": "`\u4e2d\u6587 `__=======================Check function with timeout for tracing or handle it====================================================Feature=======- Check a function call is timeout or not.- The timeout callback and function call are on the same thread.- Multi-thread support. Nest call support.Usage=====.. code:: pythondef on_timeout(start_time: float):\"\"\":param start_time:\"\"\"traceback.print_stack()pdb.set_trace()raise Exception(\"time_out\")# time unit is millisecond@pymonitor.check_time(10, on_timeout)def function_1():passdef function_2():with pymonitor.check_context(20, on_timeout):# do somethingwith pymonitor.check_context(10, on_timeout):# do somethingImplementation Comparison=========================Here are some comparisons of the other implementations.- Use ``signal`` module and emit a signal- Only works in main thread.- Not good for nest call becauseof one signal correspond onehandler.If you need nest support you need to enter the timeout functioncontinuallyand call ``alarm``. The cost depend on your accuracy.- Support Linux only.- Start new thread for work and join it with a time, if it had timeout,handle with it (eg. terminate it)- Can\u2019t inject the function call.- Overhead from threading.- Use ``sys.settrace`` keep tracing for each- A huge cost for that."} +{"package": "xtimetracker", "pacakge-description": "xtimetrackerSimple time tracking from the command line.Overviewxtimetrackerhelps you manage your projects and track your time. It is a command line tool (x) with a simple set of commands and options.It was born as a forkof theWatson projectand it maintains compatibility with its JSON file format. It aspires to be a simple, maintained, and extendable (using plugins) time tracking software.InstallingYou can install it usingpiplike this:$pipinstallxtimetrackerUsageStart tracking your activity via:$xstartresearch+experiment-alphaWith this command, you have started a newframefor theresearchproject with theexperiment-alphatag.Now stop tracking via:$xstopStopping project research [experiment-alpha], started 30 minutes ago and stopped just now. (id: 5c57b13)You can view a log of your latest working sessions using thelogcommand:$xlogTuesday 26 January 2020 (8m 32s)ffb2a4c 13:00 to 13:08 08m 32s research [experiment-alpha]Please note that, as the report command, thelogcommand comes with projects, tags and dates filtering.To list all available commands use:$xhelpLicenseCopyright (C) 2020 David AlfonsoThis work is licensed under multiple licenses.All original source code is licensed under GPL-3.0-or-later.All code borrowed fromthe Watson project _ is licensed under the MIT license.SPDX-License-Identifier: GPL-3.0-or-later AND MITFor more accurate information, you can check the individual files."} +{"package": "xtip", "pacakge-description": "XtipA semi-clone of tanin47'stipbut for X11 (i.e. Linux).Alpha stage, anything may change at any time.Customised in python (but it's very easy to run shell commands from python if\nyou prefer another language).Installation and setupInstall the core dependencies:zenity,dmenu,xclipe.g. on Debian-based OS:sudo apt install zenity xclip suckless-toolsInstall xtip from pypi, e.g.pip3 install xtipBind a hotkey to run thextipcommand using your preferred method.I usesxhkd, but I think most\ndesktop environments have a hotkey binding system.Optionally install dependencies for any individual commands that you want to use:GoogleTranslate requires the python googtrans libraryEmacsclient requires emacs (obviously)Writing your own commandsFor most customisation of commands you should probably just write your own\n(because it only takes a few lines of python). You can write new commands in~/.config/xtip/custom_commands.py.To do so: write a new class derived fromCommandand decorate it with@command, for example:from typing import Optional\nfrom subprocess import run\n\nfrom xtip.commands import Command, command\n\n\n@command\nclass Emacsclient(Command):\n unique_name = \"Open in emacsclient\"\n\n def run(self, text: str) -> Optional[str]:\n # TODO(david): Figure out a way to get the absolute path... maybe by\n # guessing from a few possible prefixes?\n run([\"emacsclient\", \"-c\", \"-n\", text])\n\n # Return text from here to output it to the screen and clipboard\n return None\n\n def accepts(self, text: str) -> bool:\n # TODO: only accept things that look like valid paths?\n Return TrueTODO: Do we need both inheritence and a decorator? Probably not!TODOWrite some testsCI buildsTry to display useful outputs in dmenu completion (e.g. converted datetimes)Something better than dmenu? Better mouse support, popup at cursor.Figure out how to construct an absolute path from a relative one"} +{"package": "xtkinter", "pacakge-description": "xtkinter\u4ecb\u7ecdxtkinter\u662f\u57fa\u4e8etkinter\u7684python Ui\u7a97\u53e3\u8bbe\u8ba1\u6a21\u5757\uff0c\u662ftkinter\u5e93\u7684\u6269\u5c55\uff0c\u6dfb\u52a0\u4e86\u66f4\u7075\u6d3b\u7684\u81ea\u5b9a\u4e49\u7a97\u53e3\u8bbe\u8ba1\u4ee5\u53ca\u4e3b\u9898\u6837\u5f0f\u7684\u53ef\u89c6\u5316\u4fee\u6539\u5b89\u88c5\u6559\u7a0b\u53ef\u4f7f\u7528pip install xtkinter \u4e0b\u8f7d\u5b89\u88c5\u6700\u65b0\u8be5\u6a21\u5757\u5728gitee\u5e73\u53f0\u4e0a\u4e0b\u8f7d\u6e90\u4ee3\u7801git clonehttps://gitee.com/yuhypython/xtkinter.git\u6848\u4f8b\u7528xtkinter\u7684\u81ea\u5b9a\u4e49\u7a97\u53e3\u529f\u80fd\u5f00\u53d1\u7684\u7a97\u53e3\uff0c\u8be5\u6848\u4f8b\u6a21\u4eff\u7f51\u7edc\u4e0a\u4e00\u4e2a\u7528PyQt\u8bbe\u8ba1\u7684UI\u6846\u67b6\uff0c\u7528xtkinter\u6a21\u5757\u4e5f\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u6bd4\u8f83\u7f8e\u89c2\u7684\u754c\u9762\uff0c\u800c\u4e14\u4ee3\u7801\u91cf\u5f88\u5c11\uff0c\u975e\u5e38\u7b80\u5355\u6613\u7528\u3002\u8be5\u6848\u4f8b\u662fxtkinter\u57fa\u4e8e\u672c\u8eab\u5f00\u53d1\u7684\u4e3b\u9898\u521b\u5efa\u5668themeCreator, \u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6253\u5f00\uff0c\u5e76\u5bf9\u73b0\u6709\u4e3b\u9898\u4fee\u6539\u6216\u521b\u5efa\u65b0\u7684\u4e3b\u9898\uff0c\u8be6\u89c1\u4f7f\u7528\u8bf4\u660efrom xtkinter.xtkthemes import themeCreator as thcthc.themeCreator()\u8c03\u7528themeCreator()\u65b9\u6cd5\u5c31\u4f1a\u6253\u5f00\u5982\u4e0b\u7684\u754c\u9762\uff0c\u8be5\u754c\u9762\u4e5f\u57fa\u4e8extkinter\u6a21\u5757\u81ea\u8eab\u5f00\u53d1\u7684\u4f7f\u7528\u8bf4\u660e\u4ecb\u7ecd\uff1a xtkinter\u4e3b\u8981\u5206\u4e3a\u4e24\u90e8\u5206\uff0c\u4e00\u90e8\u5206\u662f\u66f4\u52a0\u7075\u6d3b\u7684\u81ea\u5b9a\u4e49\u7a97\u53e3\uff1b \u53e6\u4e00\u90e8\u5206\u5c31\u662f\u4e3b\u9898\u521b\u5efa\u5668themeCreator.\u7b2c\u4e00\u7ae0\uff1axtkinter \u7684\u81ea\u5b9a\u4e49\u7a97\u53e31. \u4e3b\u7a97\u53e3\u7684\u81ea\u5b9a\u4e49\u8bbe\u8ba1 xtk_tk\n\n \u9996\u5148\u662f\u5bfc\u5165\u6a21\u5757 from xtkinter.windows import xtk_tk as xtk\n\n \u8bf4\u660e\uff1a \u5bf9\u4e8e\u7a97\u53e3\u7684\u8bbe\u8ba1\uff0c\u56e0\u4e3a\u539f\u6709\u7684tkinter\u7a97\u53e3\u7684\u6807\u9898\u680f\u53ca\u7a97\u53e3\u5916\u5f62\u65e0\u6cd5\u66f4\u591a\u7684\u4fee\u6539\uff0c\u6240\u4ee5\u5728xtkinter\u4e2d\u53bb\u6389\u4e86\u539f\u6709\u7684tkinter\u6807\u9898 \n \u680f\uff0c\u7136\u540e\u91cd\u65b0\u521b\u5efa\u6807\u9898\u680f\uff0c\u53ef\u4ee5\u968f\u610f\u8bbe\u7f6e\u3002\u6240\u4ee5\u5728\u4f7f\u7528\u4e2d\u5982\u679c\u9700\u8981\u4f20\u7edf\u7684tkinter\u6807\u9898\u680f\uff0c\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528tkinter.Tk() \n \u6216 \u4f7f\u7528\u5c01\u88c5\u540extk.Tk()\uff0c\u90fd\u662f\u5728\u8c03\u7528\u539ftkinter\u7684\u7a97\u53e3\uff1b\u5982\u679c\u60f3\u81ea\u5b9a\u4e49\u7a97\u53e3\u5219\u4f7f\u7528xtk\u4e0b\u7684\u4e09\u4e2a\u7a97\u53e3\u5bf9\u8c61\u3002\n \n \u5728\u8be5\u6a21\u5757\u4e0b\u6709\u4e09\u4e2a\u7a97\u53e3\u5bf9\u8c61\uff1a \n CanvasRoundedWindow \uff1a\u81ea\u5b9a\u4e49\u5706\u89d2\u5f62\u7a97\u53e3\n \u4f7f\u7528 \n root = xtk.CanvasRoundedWindow() \n \n root.mainloop()\n \u5c31\u53ef\u4ee5\u8c03\u7528\u4e00\u4e2a\u7b80\u5355\u7684\u5706\u89d2\u5f62\u7a97\u53e3\n\n \u800c\u5bf9\u7a97\u53e3\u7684\u8bbe\u7f6e\u662f\u901a\u8fc7\u5bf9\u8c61\u7684\u5c5e\u6027\u6765\u8c03\u6574\u7684\uff0c \u4ee5\u4e0b\u662fCanvasRoundedWindow\u5bf9\u8c61\u7684\u5c5e\u6027\n \n icon : \u6807\u9898\u7684\u56fe\u6807\uff0c\u662fstr\u7c7b\u578b\uff0c\u4e3a\u56fe\u7247\u7684\u5730\u5740,\n title: \u6807\u9898\u7684\u5185\u5bb9\uff0cstr\u7c7b\u578b,\n title_height : \u6807\u9898\u680f\u7684\u9ad8\u5ea6 int,\n title_frame_bg:\u6807\u9898\u680f\u7684\u80cc\u666f\u8272,\n main_frame_bg:\u7a97\u53e3\u4e3b\u6846\u67b6\u7684\u80cc\u666f\u8272,\n inner_bd: \u7a97\u53e3\u5185\u8fb9\u6846\u7684\u5bbd\u5ea6,\n win_width:\u7a97\u53e3\u7684\u5bbd\u5ea6,\n win_height:\u7a97\u53e3\u7684\u9ad8\u5ea6,\n win_transparent_color: \u7a97\u4f53\u7684\u900f\u660e\u8272\uff0c\u5373tkinter\u4e2d-transparentcolor\u7684\u5c5e\u6027\n win_bg: \u7a97\u4f53\u7684\u80cc\u666f\u8272, \u4e00\u822c\u548ctitle_frame_bg\u7684\u503c\u76f8\u540c,\n win_outline_color: \u7a97\u4f53\u7684\u5916\u8fb9\u6846\u7684\u989c\u8272,\n win_outline_width: \u7a97\u4f53\u7684\u5916\u8fb9\u6846\u7684\u5bbd\u5ea6,\n radii:\u7a97\u4f53\u5706\u89d2\u7684\u5927\u5c0f, \u6b64\u5c5e\u6027\u503c\u4e3a0\u65f6\uff0c\u7a97\u4f53\u4e3a\u65b9\u89d2\uff0c\u548cCornerWindow\u4e00\u6837\u90fd\u80fd\u505a\u6210\u65b9\u89d2\u7a97\u53e3,\n \n \u4e3e\u4f8b\uff1a\n root = xtk.CanvasRoundedWindow(icon='xxx/image.png', title='\u6d4b\u8bd5', title_height=28, \n title_frame_bg='#21252b', main_frame_bg='#ffffff', inner_bd=2, \n win_width=1200, win_height=800, win_transparent_color='#21253b',\n win_bg='#21252b',win_outline_color='#bbbbbb', win_outline_width=2, \n radii=10)\n \n root.mainloop()\n \u6b64\u5916\u8be5\u5bf9\u8c61\u8fd8\u5305\u62ec\u4e24\u4e2a\u6846\u67b6\uff0croot.title_frame \u6807\u9898\u6846\u67b6 \u548c root.main_frame \u7a97\u53e3\u4e3b\u6846\u67b6 \n\n CornerWindow\uff1a \u81ea\u5b9a\u4e49\u65b9\u89d2\u5f62\u7a97\u53e3\uff0c\u4e0e CanvasRoundedWindow\u5bf9\u8c61\u7684\u4f7f\u7528\u65b9\u6cd5\u76f8\u540c \n\n\n2. \u7f6e\u9876\u7a97\u53e3\u7684\u81ea\u5b9a\u4e49\u8bbe\u8ba1 xtk_toplevel\n \n \u8fd9\u4e2a\u548cxtk_tk\u76f8\u540c\uff0c\u540c\u6837\u6709CanvasRoundedWindow \u548c CornerWindow \u4e24\u4e2a\u5bf9\u8c61\uff0c\u4f7f\u7528\u65b9\u6cd5\u540c\u4e0a\n\n3. \u7a97\u4f53\u5185\u7a97\u53e3\u7684\u81ea\u5b9a\u4e49\u8bbe\u8ba1 xtk_inner_window\n\n xtk_inner_window \u662f\u5728\u4e3b\u7a97\u4f53\u5185\u7684\u7a97\u53e3\uff0c\u540c\u6837\u4e5f\u6709CanvasRoundedInnerWindow \u548c CornerInnerWindow \u4e24\u4e2a\u5bf9\u8c61\uff0c\u4f7f\u7528\u65b9\u6cd5\u540c\u4e0a\n\n ![\u8f93\u5165\u56fe\u7247\u8bf4\u660e](assets/3.png)\u7b2c\u4e8c\u7ae0\uff1a\u4e3b\u9898\u521b\u5efa\u5668themeCreator\u7684\u4f7f\u7528xtkinter\u4e2d\u63d0\u4f9b\u4e86\u4e00\u4e2a\u53ef\u89c6\u5316\u7684\u4fee\u6539\u4e3b\u9898\u6837\u5f0f\u7684\u529f\u80fd\uff0c\u5982\u4e0b\u56fe\uff1a\n\n ![\u8f93\u5165\u56fe\u7247\u8bf4\u660e](assets/1.png)\n\n \u5728\u8fd9\u91cc\u9762\u53ef\u4ee5\u65b0\u5efa\u6216\u4fee\u6539\u4e3b\u9898\uff0c\u8fd9\u91cc\u9762\u53ea\u6d89\u53ca\u56fe\u5f62\u5316\u4e3b\u9898\uff0c\u5373\u63a7\u4ef6\u7684\u6574\u4f53\u5916\u89c2\u90fd\u662f\u7531\u56fe\u7247\u7ec4\u6210\u7684\uff0c\u6240\u4ee5\u9664\u4e86\u4e00\u4e9b\u989c\u8272\u5c5e\u6027\u5916\uff0c\u5c31\u662f\u56fe\u7247\uff0c\u6bd4\u5982: \u6309\u94ae\u7684\u5404\u79cd\u5916\u89c2\uff0c\u4f60\u53ef\u4ee5\u81ea\u5df1\u4e0a\u4f20\u56fe\u7247\uff0c\u4e5f\u53ef\u4ee5\u7528\u81ea\u5b9a\u4e49\u751f\u6210\u56fe\u7247\uff0c\u7136\u540e\u4fdd\u5b58\u3002 \n\n \u6700\u540e\u4f7f\u7528xtkinter\u4e2d\u7684\u6837\u5f0f\u6a21\u5757\u5f15\u7528\u4f60\u4fee\u6539\u6216\u521b\u5efa\u7684\u4e3b\u9898\uff0c\u6bd4\u5982\uff1a\u4f60\u521b\u5efa\u4e86\u4e00\u4e2aaaaa\u7684\u4e3b\u9898\uff0c\u5c31\u53ef\u4ee5\u7528\u4e0b\u9762\u7684\u4ee3\u7801\u8bbe\u5b9a\u3002\n\n from xtkinter.xtkthemes.xtk_themes import ThemedStyle\n\n style = ThemedStyle()\n style.set_theme('xttk')"} +{"package": "xtl", "pacakge-description": "No description available on PyPI."} +{"package": "xtlearn", "pacakge-description": "PackagextlearnSome classes to be used in sklearn pipelines with pandas dataframes"} +{"package": "xtlib", "pacakge-description": "XTlib: Experiment Tools LibraryXTlib is an API and command line tool for scaling and managing Machine Learning (ML) experiments.XTLib enables you to efficiently organize and scale your ML experiments.\nOur tools offer an incremental approach to adoption, so you can immediately realize benefits to your research from using XTlib.XTlib Key FeaturesXTlib scales your ML experiments across multiple cloud compute services:Local machine and VM's, Philly, Azure Batch, and Azure Machine Learning (AML)XTlib provides a consistent storage model across services:Workspaces, experiments, jobs, and runsBlob sharesXTLib also offers several experiment-related tools to expand your ML projects:Composable Tensorboard views (live and post-training)Hyperparameter searchingRun and job reportsAd-hoc plottingXTLib provides an experiment store to track, compare, plot, rerun, and share your Machine Learning (ML) experiments.The store consists of user-defined workspaces. Each workspace contains a set of user-run experiments.XTlib supports flexible storage capabilities: local (folder-based) and Azure Storage services (cloud-based).XTLib also uses scalable cloud compute resources, so you can run multiple experiments in parallel and on larger computers, as needed. With this feature, you can scale experiments from your local machine, to multiple VM's under your control, to compute services like Azure Batch and Azure ML.For more information, run: xt --help,or see our documentation.ContributingCheckCONTRIBUTINGpage.Microsoft Open Source Code of ConductThis project has adopted theMicrosoft Open Source Code of Conduct.\nFor more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.LicenseThis project is licensed under the terms of the MIT license. SeeLICENSE.txtfor additional details."} +{"package": "xtl-read-assistant", "pacakge-description": "xtl-read-assistantx as a third language reading assistant toolPre-installation of libicuFor Linux/OSXE.g.Ubuntu:sudo apt install libicu-devCentos:yum install libicuOSX:brew install icu4cFor WindowsDownload and install the pyicu and pycld2 whl packages for your OS version fromhttps://www.lfd.uci.edu/~gohlke/pythonlibs/#pyicuandhttps://www.lfd.uci.edu/~gohlke/pythonlibs/#pycld2Installationpip install xtl-read-assistantValidate installationpython -c \"import xtl_read_assistant; print(xtl_read_assistant.__version__)\"\n# 0.0.2 or other version infoPatchpyppeteer/connection.pyThe pyppeteer package does not work too well with websockets 7+. Either downgrade the websockets to 6 or manually perform the following patch.Change site-packages\\pyppeteer\\connection.pyline 44to:# self._url, max_size=None, loop=self._loop) self._url, max_size=None, loop=self._loop, ping_interval=None, ping_timeout=None)UsageRunread-assist.exe; Copy text to the clipboard (ctrl-c); Activate hotkey (ctrl-alt-g)The translated text is stored in the clipboard.default setup: --mother-lang=zh --second-lang=en --third-lang=deread-assistctrl-alt-g: to activate clipboard translationctrl-alt-x: to exitother setup exmaple: --mother-lang=zh --second-lang=en --third-lang=frread-assist --third-lang=fr"} +{"package": "xtls", "pacakge-description": "This is a security placeholder package.\nIf you want to claim this name for legitimate purposes,\nplease contact us atsecurity@yandex-team.ruorpypi-security@yandex-team.ru"} +{"package": "xtlsapi", "pacakge-description": "xtlsapiPython library to communicate with xray coreInstall it from PyPIpipinstallxtlsapiUsagefromxtlsapiimportXrayClient,utils,exceptionsxray_client=XrayClient('1.2.3.4',1234)user_id=utils.generate_random_user_id()user_email=utils.generate_random_email()inbound_tag='inbound-tag'# Get statsprint(utils.human_readable_bytes(xray_client.get_client_download_traffic('user-email@mail.com')))print(utils.human_readable_bytes(xray_client.get_client_upload_traffic('user-email@mail.com')))print(utils.human_readable_bytes(xray_client.get_inbound_download_traffic(inbound_tag)))print(utils.human_readable_bytes(xray_client.get_inbound_upload_traffic(inbound_tag)))# Add & Remove clientuser=xray_client.add_client(inbound_tag,user_id,user_email)ifuser:print(user)xray_client.remove_client(inbound_tag,user_email)# restart loggerxray_client.restart_logger()DevelopmentRead theCONTRIBUTING.mdfile."} +{"package": "xtmigrations", "pacakge-description": "XTMigrationsA fast and easy to use database migration tool for Postgresql, written in Python.\nThis tool helps you keep track of changes in your database.Let's assume you have anemployeestable with the fieldsidandfirst_name.You would create a new \"migration\" as follows:$migratenewmyfirstmigration\nMigrationfilegeneratedscripts/20221012_234403_996058_my_first_migration.sqlYou would edit the filescripts/20221012_234403_996058_my_first_migration.sqlas follows:# Autogenerated: scripts/20221012_234403_996058_my_first_migration.sql\n\n@Up\n# Your Up migration goes here (this section describes the database changes you want to apply)\nCREATE TABLE employees (id BIGSERIAL, first_name VARCHAR(100));\n\n@Down\n# Your Down migration goes here (this section is to \"undo\" the change in the \"Up\" section above)\nDROP TABLE employees;To apply your changes you would just run$ migrate up\n$ migrate status # to show your changes\n----------------------------------------------- - --------------------\n| Name | Status |\n----------------------------------------------- - --------------------\n| init | Applied |\n| 20221012_234403_996058_my_first_migration | Applied. |\n----------------------------------------------- - --------------------On your next software release, you decide that you want to add anemailfield, you would just do the following$migratenewaddingemailfield\nMigrationfilegeneratedscripts/20221012_234936_024571_adding_email_field.sqlYou just edit the filescripts/20221012_234936_024571_adding_email_field.sql# Autogenerated: scripts/20221012_234936_024571_adding_email_field.sql\n\n@Up\n# Your Up migration goes here\nALTER TABLE employees ADD COLUMN email VARCHAR(255) DEFAULT NULL;\n\n@Down\n# Your Down migration goes here\nALTER TABLE employees DROP COLUMN email;Before applying the change, you can check the state of your database:$ migrate status\n----------------------------------------------- - --------------------\n| Name | Status |\n----------------------------------------------- - --------------------\n| init | Applied |\n| 20221012_234403_996058_my_first_migration | Applied |\n| 20221012_234936_024571_adding_email_field | Pending... |\n----------------------------------------------- - --------------------You then apply the new change$ migrate upIf for some reason, you decide to remove the change, you canundothe migration$ migrate downYou can also undo multiple migrations. For example, if you want to undo 2 migrations, you would simply run$ migrate down 2InstallationViapip(python 3+ supported)$ pip install xtmigrationsIf you have virtualenv, make sure to run source ~/is your migrations folder. This will create a new / directory structure.For this example, let's assume we call it \"migrations\" and it will generate a migrations/ folder. We will run$ migrate init migrationsNow go inside migrations/ folder$ cd migrationsConfigure config/db.cnf with your database settingsOnce it is configured, try to run the following command to make sure that xtmigrations is able to connect to your database.migrate statusTo create a new migration, run the following (no quotes needed)$ migrate new my first featureThis will create a new migration script (SQL file) under scripts/ folder.Make sure to edit the new sql file. There is a @Up and a @Down section.Keep in mind that your SQL inside @Down section shouldundothe database change defined in the @Up section.Apply the migration$ migrate upTo unapply a migration, run the following:$ migrate downEnvironment-specific migrations and seed data.In some scenarios, we want to prepopulate seed our application with seed data depending on the environmentUse the following command to create an environment-specific migration (Noting that your config/db.cnf is where you define your current environment)In our example, let's say we want to create a migration for ourdevenvironment and ourintegrationenvironment. We would run the following$ migrate new -e dev seed data for development\n\n$ migrate new -e integration seed data for integration testingLet's assume our current environment isdev(defined in config/db.cnf). To see all migrations for all environment, you can run:$ migrate status -aTo see all the migrations that will be applied for a particular environment (e.g. integration environment), you can run$ migrate status -e integrationNote that runningmigrate upwill only run the migration scripts for your current environmentUsagemigrate init | status [-a | -e] | new [-e ] | up [<number>] | down [<number>] | help | versionNote: can be 0 which means \"all\" (migrate down 0 would undo all of the migrations).LicenseCopyright \u00a9 Nejmatek Inc 2022Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.For any question, contact me atstartechm@proton.meIf you are looking for support, go toNejmatek.com"} +{"package": "xtml", "pacakge-description": "Cross-Training for Machine Learning"} +{"package": "xt-models", "pacakge-description": "xt-modelsDescriptionThis repo contains common models and utilities for working with ML tasks, developed byXtract AI.More to come.InstallationFrom PyPi:pipinstallxt-modelsFrom source:gitclonehttps://github.com/XtractTech/xt-models.git\npipinstall./xt-modelsUsageGrabbing a segmentation modelfromxt_models.modelsimportModelBuilder,SegmentationModulefromtorchimportnndeep_sup_scale=0.4fc_dim=2048n_class=2net_encoder=ModelBuilder.build_encoder(arch=\"resnet50dilated\",fc_dim=fc_dim,weights=\"/nasty/scratch/common/smart_objects/model/ade20k/encoder_epoch_20.pth\")net_decoder=ModelBuilder.build_decoder(arch=\"ppm_deepsup\",fc_dim=fc_dim,num_class=150,weights=\"/nasty/scratch/common/smart_objects/model/ade20k/decoder_epoch_20.pth\")in_channels=net_decoder.conv_last[-1].in_channelsnet_decoder.conv_last[-1]=nn.Conv2d(in_channels,n_class,kernel_size=(1,1),stride=(1,1))net_decoder.conv_last_deepsup=nn.Conv2d(in_channels,n_class,1,1,0)model=SegmentationModule(net_encoder,net_decoder,deep_sup_scale)Grabbing a detection modelfrom xt_models.models import Model\nimport torch\n\n# Load a fine-tuned model for inference\nmodel_name = \"yolov5x\"\nmodel = Model(model_name,nc=15)\ndevice = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\nweights = \"/nasty/scratch/common/smart_objects/model/veh_detection/yolov5_ft/best_state_dict.pt\"\nckpt = torch.load(weights, map_location=device)\nmodel.load_state_dict(ckpt['model_state_dict'])\n\n# Load pre-trained COCO model for finetuning/inference\nmodel_name = \"yolov5x\"\nmodel = Model(model_name,nc=80)\ndevice = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')\nweights = \"/nasty/scratch/common/smart_objects/model/veh_detection/yolov5_pretrain/yolov5x_state_dict.pt\"\nckpt = torch.load(weights, map_location=device)\nmodel.load_state_dict(ckpt['model_state_dict'])\n# Fine-tuning number of classes\nn_class = 15\nmodel.nc = n_classImplementing a new modelIf you are having to always copy and paste the same model code for different projects, simply add the model code to themodelsdirectory, and import it in themodels/__init__.pyfile.Data Sources[descriptions and links to data]Dependencies/Licensing[list of dependencies and their licenses, including data]References[list of references]"} +{"package": "xtn", "pacakge-description": "xtn RepositoryOn GithubSample codeimport xtn\n\n# reads the data in the file (without comments) into a dict with key value pairs, the values can be dict, list, str\nwith open(r'path/to/file.xtn', 'r') as f:\n data = xtn.load(f)\n\n# reads the file including comments into XtnObject\nwith open(r'path/to/file.xtn', 'r') as f:\n obj = xtn.XtnObject.load(f)\n\n# writes the XtnObject with any changes back to a file with canonical indentation\nwith open(r'path/to/file.xtn', 'w') as f:\n obj.dump(f)"} +{"package": "xt-nlp", "pacakge-description": "xt-nlpDescriptionThis repo contains common NLP pre/post processing functions, loss functions, metrics, and helper functions.InstallationFrom PyPI:pipinstallxt-nlpFrom source:gitclonehttps://github.com/XtractTech/xt-nlp.git\npipinstall./xt-nlpUsageSee specific help on a class or function usinghelp. E.g.,help(SESLoss).Defining SES Metrics and Lossfromxt_nlp.metricsimportSESF1fromxt_nlp.metricsimportSESLosseval_metrics={'f1':SESF1(threshold=0.8)}loss_fn=SESLoss()Read BRAT annotations for sequence extraction into data loaderfromxt_nlp.utilsimportget_brat_examples,split_examples,get_features,build_ses_dataloader# tokenizer =# max_sequence_length =# doc_stride =# class_dict = Dictionary mapping classname ==> list of classes to group into this class# classes =# batch_size =# workers =examples=get_brat_examples(datadir='./data/datadir',classes=classes)train_examples,val_examples=split_examples(examples,train_prop=.9,seed=4000)train_features=get_features(examples=train_examples,tokenizer=tokenizer,all_ans_types=classes,max_seq_len=max_sequence_length,doc_stride=doc_stride,mode='train')train_loader=build_ses_dataloader(train_features,classes,class_dict,batch_size=batch_size,workers=workers,max_seq_length=max_sequence_length,shuffle=True)"} +{"package": "xton", "pacakge-description": "No description available on PyPI."} +{"package": "x-to-nwb", "pacakge-description": "Converting ABF/DAT files to NWBThe scriptx-to-nwballows to convert ABF/DAT files to NeurodataWithoutBorders v2 files.For programmatic use the functionconvertis designed as public interface.fromx_to_nwbimportconverthelp(convert)ABF specialitiesAs of 9/2018 PClamp/Clampex does not record all required amplifier settings.\nFor gathering these please see themcc_get_settings.pyscript in the ipfx\nrepository which gathers all amplifier settings from all active amplifiers and\nwrites them to a file in JSON output.In case you don't have a JSON settings file pass--no-searchSettingsFileto avoid warnings.By default all AD and DA channels are outputted into the NWB file. You can\nselect to only export some AD channels withx-to-nwb--includeChannelABCD2018_03_20_0000.abfOr to discard some AD channels usex-to-nwb--discardChannelABCD2018_03_20_0000.abfRequired input filesABF files acquired with Clampex/pCLAMP.If custom waveforms are used for the stimulus protocol, the source ATF files are required as well.ExamplesConvert a single filex-to-nwb2018_03_20_0000.abfConvert a single file with overwrite and use a directory for finding custom waveformsSome acquired data might use custom wave forms for defining the stimulus\nprotocols. These custom waveforms are stored in external files and don't reside\nin the ABF files. We therefore allow the user to pass a directory where\nthese files should be searched. Currently only custom waveforms in ATF (Axon\nText format) are supported.x-to-nwb--overwrite--protocolDirprotocols2018_03_20_0000.abfConvert a folder with ABF filesThe following command converts all ABF files which reside insomeFolderto a single NWB file.x-to-nwb--fileType\".abf\"--overwritesomeFolderDisabling compressionThe following command disables compression of the HDF5 datasets (intended for debugging purposes).x-to-nwb--no-compression2018_03_20_0000.abfDAT specialitiesRequired input filesDAT files acquired with Patchmaster version 2x90.ExamplesConvert a single file creating one NWB file per Groupx-to-nwbH18.28.015.11.12.datConvert a single file creating one NWB file with all Groupsx-to-nwb--multipleGroupsPerFileH18.28.015.11.12.datOutputting DAT/ABF metadata files for debugging purposesx-to-nwb--outputMetadata*.dat*.abf"} +{"package": "xTool", "pacakge-description": "code fromairflow-mastermiscutilsDBUtils-1.2"} +{"package": "xtoolbox", "pacakge-description": "XToolBox\u6587\u6863\u6682\u672a\u5b8c\u5584\u5b89\u88c5# \u5b89\u88c5python-mpipinstallxtoolbox# \u5347\u7ea7python-mpipinstall--upgradextoolbox# \u5378\u8f7dpython-mpipuninstallxtoolbox"} +{"package": "xToolkit", "pacakge-description": "1 \u4ec0\u4e48\u662fxToolkit\u5e93\u5e93xToolkit\u7684\u4e2d\u6587\u540d\u5b57\u53eb\uff38\u5de5\u5177\u96c6\uff0e\u662fpython\u5185\u7f6e\u5e93\u7684\u4e00\u4e2a\u6269\u5c55\u5e93.\u628apython\u7684datetime,string,list,dist\uff0cxthread\u7b49\u6570\u636e\u7ed3\u6784\u8fdb\u884c\u4e86\u7cfb\u7edf\u5e93\u529f\u80fd\u7684\u6269\u5c55\u3002\u5b89\u88c5\u65b9\u6cd5(\u5229\u7528\u963f\u91cc\u4e91\u7684pypi\u6e90\u5b89\u88c5\u4f1a\u6bd4\u9ed8\u8ba4\u7684pypi\u5feb\u5f88\u591a)\uff1apipinstallxToolkit-ihttps://mirrors.aliyun.com/pypi/simple/\u5907\u7528\u5b89\u88c5\u65b9\u6cd5(\u7531\u4e8e\u56fd\u5185\u51e0\u4e2a\u6e90\u540c\u6b65pypi\u6e90\u7684\u9891\u7387\u90fd\u4e0d\u540c,\u5982\u679c\u8fd9\u4e2a\u9891\u7387\u6162\u4e86\uff0c\u5c31\u6362\u5176\u4ed6\u7684):# \u8c46\u74e3\u6e90pipinstallxToolkit-ihttp://pypi.douban.com/simple--trusted-hostpypi.douban.com\u5347\u7ea7\u65b9\u6cd5\uff08\u5229\u7528\u963f\u91cc\u4e91\u7684pypi\u6e90\u5b89\u88c5\u4f1a\u6bd4\u9ed8\u8ba4\u7684pypi\u5feb\u5f88\uff09pip install --upgrade xToolkit -i https://mirrors.aliyun.com/pypi/simple/\u5bfc\u5165\u65b9\u6cd5\uff1afromxToolkitimportxstring,xdatetime,xthreading,xlise,xfile\u672c\u5e93\u4f7f\u7528\u5230\u4e86\u7b2c\u4e09\u5e93 python-dateutil\uff0cjieba\uff0cnumpy\uff0cpandas\uff0cemoji\uff0c\u5728\u5b89\u88c5\u672c\u5e93\u7684\u65f6\u5019\u4f1a\u81ea\u52a8\u5b89\u88c5\uff0c\u4e0d\u8fc7\u5176\u4e2d\u6709\u51e0\u4e2a\u5e93\u6bd4\u8f83\u5927\uff0c\u53ef\u4ee5\u63d0\u524d\u5b89\u88c5\u597d\uff0c\u8fd9\u6837\u53ef\u4ee5\u907f\u514d\u5b89\u88c5\u7b2c\u4e09\u65b9\u5e93\u7684\u65f6\u5019\u5b89\u88c5\u51fa\u9519\u30022 \u9002\u7528\u5bf9\u8c61\u9002\u7528\u5bf9\u8c61\uff1apython\u5de5\u7a0b\u5e08\u4f5c\u8005\uff1a\u718a\u5229\u5b8f\u90ae\u7bb1\uff1axionglihong@163.com\u6709\u4efb\u4f55\u610f\u89c1\u6b22\u8fce\u53d1\u9001\u90ae\u4ef6\uff0c\u6211\u4eec\u4e00\u8d77\u6253\u9020\u4e00\u4e2a\u597d\u7528\u7684python\u5185\u7f6e\u5e93\u7684\u6269\u5c55\u5e93\u64cd\u4f5c\u6587\u6863CSDN\u5730\u5740\uff1ahttps://blog.csdn.net/qq_22409661/article/details/1085314853 \u600e\u4e48\u4f7f\u7528xToolkit\u5462\uff1f3.1 \u65f6\u95f4\u6a21\u5757 xdatetime\u6a21\u57573.1.1 \u5224\u65ad\u65f6\u95f4\u683c\u5f0f\u65f6\u5206\u662f\u5426\u6b63\u786e\u652f\u6301\u5224\u65ad\u7684\u7c7b\u578b\u5305\u62ec date,datetime,time,int,float,str \u5176\u4ed6\u7c7b\u578b\u9ed8\u8ba4\u4e3aFalsexdatetime.shape(\"2020-03-23 00:00:00\")>>Truexdatetime.shape(25251425)>>Truexdatetime.shape(253698.25)>>Truexdatetime.shape(\"2020-03-\")>>Falsexdatetime.shape(\"english\")>>Falsexdatetime.shape(\"\u6211\u662f\u4e00\u4e2a\u5175\")>>Falsexdatetime.shape(\"258741\")>>Truexdatetime.shape(\"2020/03/20T10:09:06.252525+0800\")>>Truexdatetime.shape(datetime.datetime(2020,9,29,8,12))>>Truexdatetime.shape(datetime.date(2020,9,29))>>Truexdatetime.shape(datetime.time(8,9,29))>>True3.1.2 get\u65b9\u6cd5\u521b\u5efa\u5bf9\u8c61\u5229\u7528get\u65b9\u6cd5\u53ef\u4ee5\u521b\u5efa\u65f6\u95f4\u5bf9\u8c61\uff0c\u5e76\u4e14\u521b\u5efa\u7684\u65b9\u6cd5\u8fd8\u6bd4\u8f83\u591a\uff0c\u53ef\u4ee5\u4f20\u5165\u65f6\u95f4\u6233\uff0c\u65f6\u95f4\u5b57\u7b26\u4e32\uff0cdatetime\u5bf9\u8c61\uff0cdate\u5bf9\u8c61\u7b49# \u65f6\u95f4\u6233\u65b9\u6cd5xdatetime.get(98787987)>>1973-02-17T17:06:27+08:00# \u5b57\u7b26\u4e32\u65b9\u5f0fxdatetime.get(\"1988-07-20\")>>1988-07-20T00:00:00xdatetime.get(\"2020-09-22-10-06-14\")>>2020-09-22T10:06:14# datetime\u5bf9\u8c61xdatetime.get((datetime(2020,3,23,21,56,12))>>2020-03-23T21:56:12# date\u5bf9\u8c61\u7b49xdatetime.get(date(2020,3,23))>>2020-03-23T00:00:003.1.3 \u83b7\u53d6\u65f6\u95f4\u6233\u83b7\u53d6\u5f53\u524d\u65f6\u95f4\u6233# \u6b64\u65b9\u6cd5\u83b7\u53d6\u7684\u65f6\u95f4\u6233\u6ca1\u6709\u5fae\u5999\u90e8\u5206\uff0c\u5982\u679c\u9700\u8981\u83b7\u53d6\u5fae\u5999\u90e8\u5206\uff0c\u7528time.time()xdatetime.get().timestamp>>1585833834.0\u83b7\u53d6\u6307\u5b9a\u65f6\u95f4\u7684\u65f6\u95f4\u6233xdatetime.get(\"2020-04-02 21:26:54\").timestamp>>1585834014.03.1.4 \u83b7\u53d6\u5e74\u6708\u65e5\u65f6\u5206\u79d2\u83b7\u53d6\u65e5\u671f\u65f6\u95f4\u5143\u7d20\uff0c\u5e74\u6708\u65e5\u65f6\u5206\u79d2\uff0c\u5fae\u5999# \u5e74xdatetime.get().year>>2020# \u6708xdatetime.get().month>>4# \u65e5xdatetime.get().day>>2# \u65f6xdatetime.get().hour>>21# \u5206xdatetime.get().minute>>37# \u79d2xdatetime.get().second>>48# \u5fae\u5999xdatetime.get().microsecond>>70815# \u661f\u671fxdatetime.get().weekday# \u8fd4\u56de\u6570\u5b57 1-7\u4ee3\u8868\u5468\u4e00\u5230\u5468\u65e5>>5# \u5468xdatetime.get().weed# \u8fd4\u56de\u6574\u6570\u4ee3\u8868\u5f53\u524d\u662f\u672c\u5e74\u7b2c\u591a\u5c11\u4e2a\u5468>>35# \u5b63xdatetime.get().quarter# \u8fd4\u56de\u6574\u6570\u4ee3\u8868\u5f53\u524d\u662f\u672c\u5e74\u7b2c\u51e0\u4e2a\u5b63\u5ea6>>33.1.5 \u65f6\u95f4\u63a8\u79fbshift\u65b9\u6cd5\u83b7\u53d6\u67d0\u4e2a\u65f6\u95f4\u4e4b\u524d\u6216\u4e4b\u540e\u7684\u65f6\u95f4,\u5173\u952e\u5b57\u53c2\u6570\uff1ayears, months, days, hours\uff0cminutes\uff0cseconds\uff0cmicroseconds\uff0c weeks# \u4e00\u5e74\u4ee5\u524dxdatetime.get().shift(years=-1)>>2019-04-03T21:10:49.095790+08:00# \u4e00\u5e74\u4ee5\u540exdatetime.get().shift(years=1)>>2021-04-03T21:10:49.095790+08:00# \u4e00\u4e2a\u6708\u4e4b\u540exdatetime.get().shift(months=1)>>2020-05-03T21:12:17.332790+08:00# \u4e00\u5929\u4ee5\u540exdatetime.get().shift(days=1)>>2020-04-04T21:14:30.914443+08:00#\u4e00\u4e2a\u5c0f\u65f6\u4ee5\u540exdatetime.get().shift(hours=1)>>2020-04-03T22:14:08.301192+08:00# \u4e00\u5206\u949f\u4ee5\u540exdatetime.get().shift(minutes=1)>>2020-04-03T21:17:27.956196+08:00#\u4e00\u79d2\u949f\u4ee5\u540exdatetime.get().shift(seconds=1)>>2020-04-03T21:16:45.380686+08:00#\u4e00\u6beb\u79d2\u4ee5\u540exdatetime.get().shift(microseconds=1)>>2020-04-03T21:16:58.252929+08:00#\u4e00\u5468\u4ee5\u540exdatetime.get().shift(weeks=1)>>2020-04-10T21:17:11.827210+08:003.1.6 \u65f6\u95f4\u66ff\u6362\u66ff\u6362datetime\u5bf9\u8c61\uff0c\u5e74\u6708\u65e5\u65f6\u5206\u79d2\u67d0\u4e00\u90e8\u5206\uff0c\u8fd4\u56de\u4e00\u4e2a\u88ab\u66ff\u6362\u540e\u7684datetime\u5bf9\u8c61\uff0c\u539f\u5bf9\u8c61\u4e0d\u53d8\u5173\u952e\u5b57\u53c2\u6570\uff1ayear, month, day, hour\uff0cminute\uff0csecond\uff0cmicrosecond# \u628a\u5e74\u66ff\u6362\u4f1a\u62102018xdatetime.get().replace(year=2018)>>2018-04-03T21:23:42.819295+08:00# \u628a\u6708\u66ff\u6362\u4f1a\u621010xdatetime.get().replace(month=10)>>2018-10-03T21:23:42.819295+08:00# \u628a\u65e5\u66ff\u6362\u4f1a\u62107xdatetime.get().replace(day=7)>>2018-04-07T21:23:42.819295+08:00# \u628a\u65f6\u66ff\u6362\u4f1a\u621022xdatetime.get().replace(hour=22)>>2018-04-03T22:23:42.819295+08:00# \u628a\u5206\u66ff\u6362\u4f1a\u621021xdatetime.get().replace(minute=21)>>2018-04-03T21:21:42.819295+08:00# \u628a\u79d2\u66ff\u6362\u4f1a\u621021xdatetime.get().replace(second=21)>>2018-04-03T21:23:21.819295+08:003.1.7 \u65f6\u95f4\u6269\u5c55\u90e8\u52063.1.7.1 \u4e8c\u4e2a\u65f6\u95f4\u7684\u5dee\u503c\u8ba1\u7b97\u4e8c\u4e2a\u65f6\u95f4\u7684\u5dee\u503c\uff0c\u8fd4\u56de\u503c\u4e3a\u79d2\u6570,\u4f20\u5165\u7684\u4e8c\u4e2a\u65f6\u95f4\u683c\u5f0f\u5305\u62ec\uff0c\u65f6\u95f4\u5b57\u7b26\u4e32\uff0cdatetime\uff0c\u65f6\u95f4\u6233\u7b49xdatetime.get(\"2020-04-28 10:52:52\",\"1988-07-20 17:31:12\").how>>1002648100xdatetime.get(\"2020-04-28\",\"1988-07-20 17:31:12\").how>>1002608928xdatetime.get(\"1975-04-28 14:14:55\",\"1988-07-20 17:31:12\").how>>-4174965773.1.7.2 \u5f00\u59cb\u4e0e\u7ed3\u675f\u65f6\u95f4\u8fd4\u56de \u6307\u5b9a\u65f6\u95f4\u4e2d\uff0c\u5e74\uff0c\u6708\uff0c\u5468\u7684\u5f00\u59cb\u65f6\u95f4\u548c\u7ed3\u675f\u65f6\u95f4\u7c7b\u578bgenre Y->\u5e74\uff0cM->\u6708\uff0cW->\u5468\u7b2c\u4e00\u4e2a\u53c2\u6570\uff1a\u5e74\u7b2c\u4e8c\u4e2a\u53c2\u6570\uff1a\u5e74\u6708\u7c7b\u578b\u4e2d\uff0c\u4ee3\u8868\u6708\uff0c\u5468\u7c7b\u578b\u4ee3\u8868\u5468\u6570# \u5e74(\u5f53genre\u4e3a\u5e74\u65f6\uff0c\u6708\u5931\u6548)xdatetime.get(2020,0,genre=\"Y\").begin_end>>['2020-01-01','2020-12-01']xdatetime.get(2021,0,genre=\"Y\").begin_end>>['2021-01-01','2021-12-01']# \u6708xdatetime.get(2020,8,genre=\"M\").begin_end>>['2020-08-01','2020-08-31']xdatetime.get(2021,5,genre=\"M\").begin_end>>['2021-05-01','2021-05-31']# \u5468xdatetime.get(2020,35,genre=\"W\").begin_end>>['2020-08-24','2020-08-30']xdatetime.get(2021,45,genre=\"W\").begin_end>>['2021-11-08','2021-11-14']# \u5b63xdatetime.get(2020,1,genre=\"Q\").begin_end>>['2020-01-01','2020-03-31']xdatetime.get(2021,2,genre=\"Q\").begin_end>>['2021-04-01','2021-06-30']xdatetime.get(2020,3,genre=\"Q\").begin_end>>['2020-07-01','2020-09-30']xdatetime.get(2021,4,genre=\"Q\").begin_end>>['2021-10-01','2021-12-31']3.1.7.3 \u65f6\u95f4\u662f\u5426\u5728\u6307\u5b9a\u65f6\u95f4\u533a\u95f4\u4e2d\u8ba1\u7b97\u65f6\u95f4\u662f\u5426\u5728\u6307\u5b9a\u7684\u65f6\u95f4\u533a\u95f4\u5185\uff0c\u8fd4\u56de\u503c\u4e3abool\u578b\u9700\u8981\u4f20\u5165\u4e8c\u4e2a\u53c2\u6570\uff0c\u7b2c\u4e00\u4e2a\u4e3a\u9700\u8981\u9a8c\u8bc1\u7684\u5b57\u7b26\u4e32\uff0c\u7b2c\u4e8c\u4e2a\u662f\u4e00\u4e2a\u65f6\u95f4\u5217\u8868\uff0c\u91cc\u9762\u5305\u542b\u4e8c\u4e2a\u65f6\u95f4\uff0c\u5f00\u59cb\u65f6\u95f4\u548c\u7ed3\u675f\u65f6\u95f4xdatetime.get(\"2027-04-01\",[\"1988-04-14\",\"2020-05-14\"]).middle>>Falsexdatetime.get(\"2020-04-15\",[\"2020-04-14\",\"2020-05-14 12:12:14\"]).middle>>True3.2 \u5b57\u7b26\u4e32\u6a21\u5757xstring3.2.1 \u5b57\u7b26\u4e32\u683c\u5f0f\u6548\u9a8c\u8fdb\u884c\u5b57\u7b26\u4e32\u683c\u5f0f\u6548\u9a8c\uff0c\u5305\u62ec\u8f66\u724c\u683c\u5f0f\uff0c\u8eab\u4efd\u8bc1\u53f7\u7801\uff0c\u6574\u5f62\u6216\u6d6e\u70b9\u578b\uff0c\u65f6\u95f4\u5b57\u7b26\u4e32\uff0cURL\u5730\u5740\uff0c\u624b\u673a\u53f7\uff0c\u94f6\u884c\u5361\uff0c\u7528\u6237\u59d3\u540d\uff0c\u5bc6\u7801\uff0c\u90ae\u7bb1\uff0c\u5de5\u53f7\u3002# \u8f66\u724c\u53f7xstring.check(\"\u9102A96288\").is_car_number>>True# \u8eab\u4efd\u8bc1\u53f7\u7801# \u63d0\u4f9b\u4e2d\u56fd\u5927\u9646\u8eab\u4efd\u8bc1\u9a8c\u8bc1\uff0c\u6682\u65f6\u53ea\u652f\u6301\u6548\u9a8c18\u4f4d\u8eab\u4efd\u8bc1xstring.check(\"110101199003072316\").is_identity_card>>True# \u6574\u5f62\u6216\u6d6e\u70b9\u578bxstring.check(\"12.5\").is_int_or_float>>True# \u65f6\u95f4\u5b57\u7b26\u4e32xstring.check(\"1988-07-20\").is_datetime_string>>True# URL\u5730\u5740xstring.check(\"https://wwww.baidu.com\").is_url>>True# \u624b\u673a\u53f7xstring.check(\"15172383635\").is_phone>>True# \u94f6\u884c\u5361xstring.check(\"6222600260001072444\").is_bank_number>>True# \u7528\u6237\u59d3\u540d# \u59d3\u540d\u8981\u6c42\u4e3a2-4\u4e2a\u4e2d\u6587xstring.check(\"\u718a\u5229\u5b8f\").is_user_name>>True# \u5bc6\u7801# \u5305\u542b6-18\u4f4d\u5b57\u7b26\uff0c\u5fc5\u987b\u5305\u542b\u5b57\u6bcd\u4e0e\u6570\u5b57\uff0c\u53ef\u4ee5\u5305\u542b\u7279\u6b8a\u5b57\u7b26xstring.check(\"xlh123456\").is_user_password>>True# \u90ae\u7bb1# \u7b2c\u4e00\u79cd\uff1a\u53ea\u5141\u8bb8\u82f1\u6587\u5b57\u6bcd\u3001\u6570\u5b57\u3001\u4e0b\u5212\u7ebf\u3001\u82f1\u6587\u53e5\u53f7\u3001\u4ee5\u53ca\u4e2d\u5212\u7ebf\u7ec4\u6210# \u7b2c\u4e8c\u79cd\uff1a\u540d\u79f0\u5141\u8bb8\u6c49\u5b57\u3001\u5b57\u6bcd\u3001\u6570\u5b57\uff0c\u57df\u540d\u53ea\u5141\u8bb8\u82f1\u6587\u57df\u540dxstring.check(\"xionglihong@163.com\").is_mailbox>>True# \u5de5\u53f7# \u5de5\u53f7\u683c\u5f0f\u4e3a 4\u4e2a\u5927\u5199\u5b57\u6bcd+8\u4f4d\u6570\u5b57xstring.check(\"HBBZ00000001\").is_job>>True3.2.2 \u5b57\u7b26\u4e32\u5904\u74063.2.2.1 \u8eab\u4efd\u8bc1\u53f7\u7801\u5904\u7406\u8fdb\u884c\u5b57\u7b26\u4e32\u5904\u7406\uff0c\u6bd4\u5982\u4ece\u8eab\u4efd\u8bc1\u63d0\u53d6\u751f\u65e5\u53f7\u7801\uff0c\u6027\u522b\u7b49\u64cd\u4f5cxstring.dispose(\"11010119900307053X\").get_identity_card(True)>>{'code':'0000','msg':'\u8eab\u4efd\u8bc1\u683c\u5f0f\u6b63\u786e','data':{'age':'31','birthday':'1990-03-07','gender':'\u7537'}}3.2.2.2 split \u591a\u6807\u7b7e\u5206\u5272# \u4e3b\u8981\u89e3\u51b3\u4e86\u7cfb\u7edf\u6a21\u5757split\u53ea\u80fd\u7528\u4e00\u4e2a\u5206\u9694\u7b26xstring.dispose(\"abc,\u6211\u7684-\u4ed6\u7684,1245*ss\").split([\",\",\"-\",\"*\"])>>['abc','\u6211\u7684','\u4ed6\u7684','1245','ss']3.2.2.3 strip\u591a\u5b57\u7b26\u4e32\u8fc7\u6ee4# \u5982\u679c\u4e0d\u4f20\u8fc7\u6ee4\u53c2\u6570\uff0c\u9ed8\u8ba4\u53bb\u6389\u6240\u6709\u7a7a\u683cxstring.dispose(\" \u9102 A9 62 --8 8---__ \").strip()>>\u9102A962--88---__xstring.dispose(\" \u9102 A9 62 --8 8---__ \").strip([\" \",\"-\",\"_\"])>>\u9102A962883.2.2.4 \u628a\u5b57\u7b26\u4e32\u8f6c\u6362\u4e3aemoji\u8868\u60c5xstring.dispose('Python is :thumbs_up:').string_to_emoji()>>Pythonis\ud83d\udc4d3.2.2.5 emoji\u8868\u60c5\u8f6c\u5b57\u7b26\u4e32xstring.dispose('Python is \ud83d\udc4d').emoji_to_string()>>Pythonis:thumbs_up:3.2.2.6 \u4e2d\u6587\u5206\u8bcd# \u5206\u8bcd\u5bf9\u8c61 \u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b\u6d77\u519b\u5de5\u7a0b\u5927\u5b66# \u5168\u6a21\u5f0f\uff1a\u628a\u6587\u672c\u4e2d\u6240\u6709\u53ef\u80fd\u7684\u8bcd\u8bed\u90fd\u626b\u63cf\u51fa\u6765\uff0c\u6709\u5197\u4f59 cut_all=True# ['\u4e2d\u56fd', '\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b', '\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b\u6d77\u519b', '\u56fd\u4eba', '\u4eba\u6c11', '\u4eba\u6c11\u89e3\u653e\u519b', '\u89e3\u653e', '\u89e3\u653e\u519b', '\u6d77\u519b', '\u6d77\u519b\u5de5\u7a0b\u5927\u5b66', '\u519b\u5de5', '\u5de5\u7a0b', '\u5927\u5b66']# \u7cbe\u786e\u6a21\u5f0f\uff1a\u628a\u6587\u672c\u7cbe\u786e\u7684\u5207\u5206\u5f00\uff0c\u4e0d\u5b58\u5728\u5197\u4f59\u5355\u8bcd cut_all=False# ['\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b', '\u6d77\u519b\u5de5\u7a0b\u5927\u5b66']# \u9ed8\u8ba4\u4e3a\u7cbe\u786e\u6a21\u5f0f# \u7cbe\u786e\u6a21\u5f0fxstring.dispose('\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b\u6d77\u519b\u5de5\u7a0b\u5927\u5b66').part(cut_all=False)>>['\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b','\u6d77\u519b\u5de5\u7a0b\u5927\u5b66']# \u5168\u6a21\u5f0fxstring.dispose('\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b\u6d77\u519b\u5de5\u7a0b\u5927\u5b66').part(cut_all=True)>>['\u4e2d\u56fd','\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b','\u4e2d\u56fd\u4eba\u6c11\u89e3\u653e\u519b\u6d77\u519b','\u56fd\u4eba','\u4eba\u6c11','\u4eba\u6c11\u89e3\u653e\u519b','\u89e3\u653e','\u89e3\u653e\u519b','\u6d77\u519b','\u6d77\u519b\u5de5\u7a0b\u5927\u5b66','\u519b\u5de5','\u5de5\u7a0b','\u5927\u5b66']3.2.2.7 \u91d1\u989d\u4eba\u6027\u5316# \u91d1\u989d\u4eba\u6027\u5316,\u4fdd\u7559\u4e8c\u4f4d\u5c0f\u6570xstring.dispose(3.0).humanized_amount()xstring.dispose(\"3.0\").humanized_amount()xstring.dispose(37787841.902).humanized_amount()xstring.dispose(\"37787841.9882\").humanized_amount()xstring.dispose(378978989).humanized_amount()xstring.dispose(\"378978989\").humanized_amount()>>3.00>>3.00>>37,787,841.90>>37,787,841.99>>378,978,989.00>>378,978,989.003.2.3 \u5b57\u7b26\u4e32\u9ad8\u7ea7\u683c\u5f0f\u6821\u9a8c\u672c\u6a21\u5757\u4e3b\u8981\u7528\u4e8e\u9879\u76ee\u4e2d\u5165\u53c2\u6a21\u5757\u5bf9\u7528\u6237\u8f93\u5165\u7684\u53c2\u6570\u8fdb\u884c\u6821\u9a8c\uff0c\u6821\u9a8c\u6210\u529f\u8fd4\u56de\u7528\u6237\u8f93\u5165\u7684\u503c\uff0c\u6821\u9a8c\u5931\u8d25\u8fd4\u56deFlash# \u53c2\u6570\u6821\u9a8cclassParameterVerifyData(object):\"\"\"\u53c2\u6570\u6821\u9a8c\"\"\"def__call__(self,request,parameter,**kwargs):\"\"\"is_blank \u5982\u679c\u4e3aTrue\u4ee3\u8868\u5982\u679c\u7528\u6237\u4f20\u503c\uff0c\u5c31\u8fdb\u884c\u6821\u9a8c\uff0c\u5982\u679c\u4f20\u7a7a\uff0c\u503c\u5c31\u4e3a\u7a7a\"\"\"method=kwargs[\"method\"]ifkwargs.get(\"method\")else\"POST\"# \u53c2\u6570ifmethod==\"POST\":parameter=request.POST.get(parameter,None)else:parameter=request.GET.get(parameter,None)returnxstring.formative(parameter,**kwargs)# \u53c2\u6570\u6821\u9a8cParameterVerify=ParameterVerifyData()ParameterVerify\u4ece\u672c\u8d28\u4e0a\u8c03\u7528xstring.formative(parameter, **kwargs)# \u67e5\u8be2\u8ba2\u5355\u5217\u8868@staticmethoddefselect_order_list(request):\"\"\"\u67e5\u8be2\u8ba2\u5355\u5217\u8868\"\"\"# \u53c2\u6570\u6821\u9a8cparameter={\"rests_license\":ParameterVerify(request,\"rests_license\",rule=\"is_url_list\"),\"limit\":ParameterVerify(request,\"limit\",rule=\"is_int\"),\"shopping_sign\":ParameterVerify(request,\"shopping_sign\",rule=\"casual\"),# \u5546\u5e97\u6807\u8bc6\"title\":ParameterVerify(request,\"title\",rule=\"casual\"),\"distribution\":ParameterVerify(request,\"distribution\",rule=\"is_choices\",choices=[\"\u5feb\u9012\",\"\u7ebf\u4e0b\u53d6\u8d27\"]),\"phoenix\":ParameterVerify(request,\"cn123451\",regular=\"cn\\d{6}(?!\\d)\"),# \u5fae\u9cef\u53f7}forkey,iteminparameter.items():ifitemisFalse:returnGlobalReturn(code=10001,msg=\"{}\u4e3a{}\uff0c\u683c\u5f0f\u9519\u8bef\".format(key,item))returnGlobalReturn(**OperationOrderForm().select_order_list(request=request,**parameter))\u652f\u6301\u7684\u6821\u9a8c\u7c7b\u578b\u4e3a\uff1a\u6821\u9a8c\u7c7b\u578b\u5173\u952e\u5b57\u8bf4\u660eis_car_number\u8f66\u724c\u53f7is_identity_card\u8eab\u4efd\u8bc1is_int_or_float\u6574\u5f62\u6216\u6d6e\u70b9\u578bis_int\u6574\u5f62is_datetime_string\u65f6\u95f4\u5b57\u7b26\u4e32is_urlurl\u5730\u5740is_phone\u624b\u673a\u53f7is_bank_number\u94f6\u884c\u5361is_user_name\u7528\u6237\u59d3\u540dis_user_password\u5bc6\u7801is_mailbox\u90ae\u7bb1is_jsonjsonis_choices\u679a\u4e3e\u683c\u5f0fis_job\u5de5\u53f7is_ip_addressip\u5730\u5740is_phoenix\u5fae\u9cef\u53f7is_verification_code\u9a8c\u8bc1\u7801is_version\u7248\u672c\u53f7is_contact_information\u7535\u8bdd\u53f7\u7801\u5305\u62ec\u4e2d\u56fd\u5927\u9646\u7684\u624b\u673a\u53f7\u7801\u548c\u56fa\u5b9a\u7535\u8bdd\u53f7\u7801is_longitude\u7ecf\u5ea6\u7ecf\u5ea6\u7684\u8303\u56f4\u5728-180\u5230180\u4e4b\u95f4is_latitude\u7eac\u5ea6\u7eac\u5ea6\u7684\u8303\u56f4\u5728-90\u523090\u4e4b\u95f4is_longitude_latitude\u7ecf\u7eac\u5ea6\u7ecf\u5ea6\u7684\u8303\u56f4\u5728-180\u5230180\u4e4b\u95f4\uff0c\u5176\u4e2d\u7eac\u5ea6\u7684\u8303\u56f4\u5728-90\u523090\u4e4b\u95f4is_latitude_longitude\u7eac\u7ecf\u5ea6\u5176\u4e2d\u7eac\u5ea6\u7684\u8303\u56f4\u5728-90\u523090\u4e4b\u95f4\uff0c\u7ecf\u5ea6\u7684\u8303\u56f4\u5728-180\u5230180\u4e4b\u95f4is_car_number_list\u8f66\u724c\u53f7\u5217\u8868\u5217\u8868\u7684\u6bcf\u4e00\u4e2a\u503c\u4e3a\u8f66\u724c\u53f7\uff0c\u4ee5\u4e0b\u540c\u7406is_identity_card_list\u8eab\u4efd\u8bc1\u5217\u8868is_int_or_float_list\u6574\u5f62\u6216\u6d6e\u70b9\u578b\u5217\u8868is_int_list\u6574\u5f62\u5217\u8868is_datetime_string_list\u65f6\u95f4\u5b57\u7b26\u4e32\u5217\u8868is_url_listurl\u5730\u5740\u5217\u8868is_phone_list\u624b\u673a\u53f7\u5217\u8868is_bank_number_list\u94f6\u884c\u5361\u5217\u8868is_user_name_list\u7528\u6237\u59d3\u540d\u5217\u8868is_user_password_list\u5bc6\u7801\u5217\u8868is_mailbox_list\u90ae\u7bb1\u5217\u8868is_json_listjson\u5217\u8868is_ip_address_listip\u5730\u5740\u5217\u8868is_longitude_latitude_list\u7ecf\u7eac\u5ea6\u5217\u8868is_phoenix_list\u5fae\u9cef\u53f7\u5217\u8868is_verification_code_list\u9a8c\u8bc1\u7801\u5217\u8868is_version_list\u7248\u672c\u53f7\u5217\u8868is_contact_information_list\u7535\u8bdd\u53f7\u7801\u5217\u8868is_casual_list\u4efb\u610f\u5217\u8868\u5217\u8868\u91cc\u9762\u7684\u503c\u4e0d\u8fdb\u884c\u6821\u9a8c\uff0c\u53ea\u80fd\u786e\u4fdd\u6574\u4f53\u662f\u4e00\u4e2a\u5217\u8868\u53c2\u6570\u8bf4\u660e xstring.formative(parameter, **kwargs)\uff1aparameter \u4e3a\u9700\u8981\u6821\u9a8c\u7684\u53c2\u6570\u540d\u79f0is_blank \u662f\u5426\u53ef\u4ee5\u4e3a\u7a7a\uff0c\u5982\u679c\u53ef\u4ee5\u4e3a\u7a7a\uff0c\u4e0d\u8fdb\u884c\u89c4\u5219\u6821\u9a8c\uff0c\u76f4\u63a5\u8fd4\u56de\u7a7a\u5b57\u7b26\u4e32\uff0c\u5982\u679c\u7528\u6237\u4f20\u4e86\uff0c\u5c31\u8fdb\u884c\u89c4\u5219\u6821\u9a8crule \u4e3a\u6b63\u5219\u6807\u8bc6\uff0c\u5982\u679crule\u4e3ais_choices\uff0c\u5fc5\u987b\u4f20choices\uff0cchoices\u4e3a\u679a\u4e3e\u503c\uff0cchoices\u7684\u7c7b\u578b\u4e3a\u5217\u8868regular \u4e3a\u81ea\u5b9a\u4e49\u6b63\u5219\u8868\u8fbe\u5f0f\uff0c\u5982\u679c\u4f20\u5165\u81ea\u5b9a\u4e49\u6b63\u5219\u8868\u8fbe\u5f0f\u5c31\u4f7f\u7528\u7528\u6237\u7684\u6b63\u5219\u8868\u8fbe\u5f0f3.3 \u591a\u7ebf\u7a0b\u6a21\u5757xthread3.3.1 \u591a\u7ebf\u7a0b\u6a21\u5757\u628a\u591a\u4e2a\u51fd\u6570\u653e\u5165\u591a\u7ebf\u7a0b\u6a21\u5757# \u51fd\u6570\u4e00deffunction_1(a,b,c):time.sleep(1)returna*2,b*2,c*2# \u51fd\u6570\u4e8cdeffunction_2(a,b):time.sleep(1)returna*2,b*2# \u51fd\u6570\u4e09deffunction_3(a):time.sleep(1)returna*2# \u51fd\u6570\u56dbdeffunction_4():time.sleep(1)return0st=time.time()result=xthreading([function_1,1,1,1],[function_2,2,2],[function_3,2],[function_4])print(result[0])print(result[1])print(result[2])print(result[3])et=time.time()print(\"\u8fd0\u884c\u65f6\u95f4\uff1a{}\".format(et-st))>>(2,2,2)>>(4,4)>>4>>0>>\u8fd0\u884c\u65f6\u95f4\uff1a1.0010571479797363# \u4ece\u4e0a\u9762\u7684\u8fd0\u884c\u65f6\u95f4\u53ef\u4ee5\u770b\u51fa\uff0c\u5982\u679c\u5355\u7ebf\u7a0b\u6267\u884c\u5e94\u8be5\u662f4\u79d2\u4ee5\u4e0a\uff0c\u7ed3\u679c\u4e3a1\u79d2,\u8bf4\u660e\u8fd0\u884c\u65f6\u662f\u591a\u7ebf\u7a0b\u8fd0\u884c3.4 \u5217\u8868\u6a21\u5757xlist3.4.1 \u503c\u7684\u9891\u7387# \u8ba1\u7b97\u5217\u8868\u4e2d\u503c\u7684\u9891\u7387xlise.basics([\"\u6b66\u6c49\",\"\u6b66\u660c\",\"\u6b66\u6c49\",\"\u65e0\u804a\",\"\u4e94\u83f1\",\"\u6b66\u660c\"]).values_count()>>{'\u6b66\u660c':2,'\u6b66\u6c49':2,'\u4e94\u83f1':1,'\u65e0\u804a':1}3.4.2 \u5b57\u5178\u5217\u8868\u503c\u66ff\u6362# 1.\u5b57\u5178\u578b\u5217\u8868\u7684\u503c\u6574\u4f53\u66ff\u6362# 2.\u8981\u6c42\u4f20\u5165\u53c2\u6570\u683c\u5f0f\u4e3a [{\"id\": None, \"name\": \"wuhan\"}, {\"id\": 5, \"name\": \"\u4e2d\u56fd\"}, {\"id\": 25, \"name\": \"\u4e0a\u53f7\"}, {\"id\": 5, \"name\": \"\u6d4b\u8bd5\"}]# 3.\u8fd9\u79cd\u5f62\u72b6\u7684\u53c2\u6570\u5373\u53ef\uff0c\u6bd4\u5982\u53ef\u4ee5\u4f20\u5165 django \u7684 QuerySet \u7b49# 4.\u53c2\u6570\uff1a# 1.\u9700\u8981\u66ff\u6362\u7684\u5bf9\u8c61# 2.kwargs[\"rules\"] \u8981\u6c42\u5143\u7956\uff0c\u6bd4\u5982 ((None, ''), (45, 47)))value=[{\"id\":None,\"name\":\"wuhan\"},{\"id\":5,\"name\":\"\u4e2d\u56fd\"},{\"id\":25,\"name\":\"\u4e0a\u53f7\"},{\"id\":5,\"name\":\"\u6d4b\u8bd5\"}]xlise.basics(value).dict_to_value(rules=((None,''),(\"\u4e2d\u56fd\",\"china\")))>>[{'id':'','name':'wuhan'},{'id':5.0,'name':'china'},{'id':25.0,'name':'\u4e0a\u53f7'},{'id':5.0,'name':'\u6d4b\u8bd5'}]3.5 \u6587\u4ef6\u6a21\u5757xfile3.5.1 excel\u8f6cdict\u5bfc\u5165\u7684excel\u8868\u683c\u7684\u683c\u5f0f\u662f\u8fd9\u6837\u7684\uff1a3.5.1.1 \u57fa\u672c\u7528\u6cd5# excel\u8f6cdict# 1.\u4f20\u6765\u7684\u6587\u4ef6\u53ef\u4ee5\u662f\u6587\u4ef6\u8def\u5f84\uff0c\u4e5f\u53ef\u4ee5\u662f\u4e8c\u8fdb\u5236\u6587\u4ef6# 2.\u4f20\u6765\u7684\u53ef\u4ee5\u662f\u4e8c\u8fdb\u5236\u6587\u4ef6\uff0c\u8fd9\u91cc\u4ee5django\u63a5\u6536\u524d\u7aef\u4f20\u6765\u6587\u4ef6\u4e3a\u4f8b\uff1a# \u63a5\u6536\u7528 request.FILES.get(\"fileName\", None) \u4f20\u5165 my_file \u5373\u53ef# kwargs\u63a5\u6536\u7684\u53c2\u6570\u6709:# sheet\u7d22\u5f15\uff0c0\u4ee3\u8868\u7b2c\u4e00\u4e2a\u8868\uff0c1\u4ee3\u8868\u7b2c\u4e8c\u4e2a\u8868\uff0c\u9ed8\u8ba40# max\u8868\u683c\u6700\u5927\u7684\u884c\u6570\uff0c\u9ed8\u8ba42000\u884c# min\u8868\u683c\u6700\u5c0f\u7684\u884c\u6570\uff0c\u9ed8\u8ba41\u884c# title \u8868\u5934(\u7528\u4e8e\u8868\u5934\u6821\u9a8c)# \u8868\u5934\u4e3a\u9009\u586b,\u5982\u679c\u4e0d\u586b\uff0c\u4e0d\u8fdb\u884c\u8868\u5934\u6821\u9a8cxfile.read(\"./result/t_excel.xls\").excel_to_dict()>>[{'\u7f16\u53f7':1,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1},{'\u7f16\u53f7':2,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1},{'\u7f16\u53f7':3,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1},{'\u7f16\u53f7':4,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1},{'\u7f16\u53f7':5,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1},{'\u7f16\u53f7':6,'\u65f6\u95f4':'1988-07-21 00:00:00','\u5e74\u9f84':1,'\u5206\u6570':63.2,'\u603b\u5206':1}]3.5.1.2 \u6821\u9a8c\u8868\u5934\u518d\u8fdb\u884c\u8bfb\u53d6\u9519\u8bef\u7684\u8868\u5934\u662f\u8fd9\u6837\u7684\uff1axfile.read(\"./result/t_excel.xls\").excel_to_dict(title=[\"\u7f16\u53f7\",\"\u65f6\u95f4\",\"\u5e74\u9f84\",\"\u5206\u6570\",\"\u603b\u5206\"])>>{'code':'0001','data':{'data':None},'msg':'\u8868\u5934\u7b2c 3 \u5217\u9519\u8bef\uff0c\u9519\u8bef\u503c\u4e3a \u5e74\u9f841 \u5e94\u8be5\u4e3a \u5e74\u9f84'}3.6 \u5927\u6742\u70e9\u6a21\u5757xfile3.6.1 \u7ecf\u7eac\u5ea6\u8ba1\u7b97\u4e8c\u70b9\u8ddd\u79bb# \u53c2\u6570\u683c\u5f0f\uff1a\uff08\u7eac\u5ea6\uff0c\u7ecf\u5ea6\uff09,(3.6546879, 4.5879546), (6.5879546, 5.1123654)xhotchpotch.distance_hav((3.6546879,4.5879546),(6.5879546,5.1123654))>>331293.85661410464 \u5347\u7ea7\u65e5\u5fd72019\u5e7405\u5e7410\u65e5 V0.0.10xToolkit \u4e0a\u7ebf\u5566\u65b0\u589e\u83b7\u53d6\u5f53\u524d\u65f6\u95f4\u529f\u80fd2019\u5e7405\u5e7416\u65e5 V0.0.12\u65b0\u589e\u683c\u5f0f\u5316\u65f6\u95f4format\u529f\u80fd\uff0c\u66f4\u4eba\u6027\u5316\u7684\u8f93\u51fa\u65f6\u95f4\u683c\u5f0f\u65b0\u589e\u63a8\u79fb\u65f6\u95f4\u529f\u80fd\u65b0\u589e\u66ff\u6362\u65f6\u95f4\u529f\u80fd\u65b0\u589e\u5224\u65ad\u65f6\u95f4\u683c\u5f0f\u662f\u5426\u6b63\u786e\u529f\u80fd\u65b0\u589e\u83b7\u53d6\u65f6\u95f4\u533a\u95f4\u529f\u80fd2019\u5e7406\u670811\u65e5 V0.0.21\u65b0\u589e\u5b57\u7b26\u4e32\u6548\u9a8c\u529f\u80fd2019\u5e7408\u670820\u65e5 v0.0.25\u65b0\u589e\u4e2d\u56fd\u5c45\u6c11\u8eab\u4efd\u8bc1\u6548\u9a8c\u529f\u80fd\u65b0\u589e\u4e2d\u56fd\u5927\u9646\u624b\u673a\u53f7\u7801\u6548\u9a8c\u529f\u80fd\u65b0\u589e\u6570\u5b57\u6548\u9a8c\u529f\u80fd2019\u5e7409\u670802\u65e5 v0.0.30\u65b0\u589e\u6d6e\u70b9\u6570\uff0c\u94f6\u884c\u5361\u6548\u9a8c2020\u5e7405\u670828\u65e5 v0.0.43\u65b0\u589e\u5b57\u7b26\u4e32 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\u6821\u9a8c2023\u5e7411\u670822\u65e5 V0.0.88\u53c2\u6570\u6821\u9a8c\u52a0\u5165\uff0c\u4e3a\u7a7a\u6821\u9a8c\u5e76\u8bbe\u7f6e\u9ed8\u8ba4\u503c2023\u5e7411\u670822\u65e5 V0.0.89\u52a0\u5165\u590d\u6838\u6821\u9a8c\u91cc\u9762\u7684\u4e00\u4e9b\u7279\u6b8a\u60c5\u51b5\u5f00\u53d1\u8ba1\u5212\uff1a\u65e0"} +{"package": "xtools", "pacakge-description": "xtoolsxtoolsis a Python wrapper aroundXTools\u2019 API.Note this project is not affiliated with nor endorsed by XTools.Installpip install xtoolsRequirementsPython 3.8+.UsageRead the docs."} +{"package": "xtopology", "pacakge-description": "xtopologyPython library of topological data analysisCreated byBaihan Lin, Columbia University"} +{"package": "xtor", "pacakge-description": "xtorxtor is a simple tool for managing Tor instances.InstallationLinuxsudo apt-get install torsudo apt-get install obfs4proxyWindowsDownload and install Tor Expert Bundlehttps://archive.torproject.org/tor-package-archive/torbrowser/12.5a6/tor-expert-bundle-12.5a6-windows-x86_64.tar.gzhttps://archive.torproject.org/tor-package-archive/torbrowser/12.5a6/tor-expert-bundle-12.5a6-windows-i686.tar.gzThen install the python package:pip install xtorUsagefromxtorimportTortor=Tor.startTor(port=9052,control_port=9053,host=\"127.0.0.1\",password=\"passw0rd\",init_msg_handler=print,path=\"/usr/bin/tor\",# optional, primarily for windows)withtor:print(tor.ip)print(tor.client.get(\"https://api.ipify.org\").text)# connect to an existing tor instancetor=Tor(port=9052,control_port=9053,host=\"127.0.0.1\",password=\"passw0rd\",)withtor:print(tor.ip)print(tor.client.get(\"https://api.ipify.org\").text)tor.new_identity(wait=True)# get a new identity and wait for it to be ready (new ip)print(tor.ip)CLIxtor--help"} +{"package": "xtorch", "pacakge-description": "EasyTorchEnglish|\u7b80\u4f53\u4e2d\u6587"} +{"package": "xtoy", "pacakge-description": "No description available on PyPI."} +{"package": "xtp-job-control", "pacakge-description": "XTP_JOB_CONTROLA python library to create, managed and executed worflows for thextp votca package. Seedocumentation"} +{"package": "xtprod", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtproductions", "pacakge-description": "the Arsenaaaaaaaaaaaaaaaaaaal"} +{"package": "xtproductjson", "pacakge-description": "No description available on PyPI."} +{"package": "xtpwrapper", "pacakge-description": "===========XTP-Wrapper (Chinese Stock Market Quote and Trade Python API)===========Chinese Stock Market Quote and Trade API by dealer, Python Wrapper C++ Interface.|travis| |appveyor| |codacy| |pypi| |status| |pyversion|Version: v1.1.18.13Platform: Linux 64bit, Windows 64bit, MacOSPython Requirement: x86-64Install=======Before you install xtpwrapper package, you need to make sure you havealready install cython package.>>>pip install cython --upgrade>>>pip install xtpwrapper --upgradeDonate [\u6350\u52a9]============|alipay| |wechat|Contact=======Email: 365504029@qq.com.. |travis| image:: https://travis-ci.org/nooperpudd/xtpwrapper.svg?branch=master:target: https://travis-ci.org/nooperpudd/xtpwrapper.. |appveyor| image:: https://ci.appveyor.com/api/projects/status/cbpvidl5hoocmic3/branch/master?svg=true:target: https://ci.appveyor.com/project/nooperpudd/xtpwrapper/branch/master.. |codacy| image:: https://api.codacy.com/project/badge/Grade/2dd3feb2897c425c9ec725c8be170695:target: https://www.codacy.com/app/nooperpudd/xtpwrapper?utm_source=github.com&utm_medium=referral&utm_content=nooperpudd/xtpwrapper&utm_campaign=Badge_Grade.. |pypi| image:: https://img.shields.io/pypi/v/xtpwrapper.svg:target: https://pypi.python.org/pypi/xtpwrapper.. |status| image:: https://img.shields.io/pypi/status/xtpwrapper.svg:target: https://pypi.python.org/pypi/xtpwrapper.. |pyversion| image:: https://img.shields.io/pypi/pyversions/xtpwrapper.svg:target: https://pypi.python.org/pypi/xtpwrapper.. |alipay| image:: img/alipay.png.. |wechat| image:: img/wechat.jpg"} +{"package": "xt-py", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtPyapollos", "pacakge-description": "\u57fa\u4e8ePyapollos \u4fee\u6539\u7684\u963f\u6ce2\u7f57\u4f9d\u8d56\u4e09\u65b9\u5e93\u4fee\u6539get_value\u65b9\u6cd5\uff0c\u652f\u6301\u4e00\u6b21\u6027\u83b7\u53d6\u914d\u7f6e\u5185\u5bb9 [whole=True]"} +{"package": "xtr", "pacakge-description": "xallDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nbnx--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallbnxnbdev# activate conda environment$condaactivatebnx# make sure the bnx package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the bnx package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/bnx.gitor fromconda$condainstall-cdsm-72bnxor frompypi$pipinstallbnxDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find\npackage manager specific guidelines oncondaandpypirespectively."} +{"package": "xtra", "pacakge-description": "trprogram Package To print \"Hello World\"pip install trakosBy :TrakosTelegram Channelhttps://t.me/trprogram"} +{"package": "xtrace", "pacakge-description": "This module printsfunction traceto stdout from the moment it is called:import xtrace\nxtrace.start()\n...\nxtrace.stop()It is also possible to callxtraceas module from the command line:python -m xtrace <script.py> [param] ...or use as a standalone script:python xtrace.py <script.py> [param] ...The output format is inspired by Xdebug function traces and will likely to\nmerge with ithttp://xdebug.org/docs/execution_traceto be compatible with\nPHP inspection tools. But I didn\u2019t have enough time to polish it, so feel\nfree to send a patch if you know how to bring them closer.This code is released into public domain. Enjoy!History0.5 - fix major crash when function in executed script tried to read\nvariables in its global scope0.4 - added beep function which beeps in DEBUG mode when excited0.3 - fix AttributeError when running from console (issue #2)0.2 - added version info, support running from command line, moved main\nfunctions into a class to isolate used variables in local namespace0.1 - initial releaseCreditsAmaury Forgeot d\u2019Arc, for valuable insight into Python internalsDebuggingTo see various internal events thatxtraceproduces on top of standard\ndata provided by Python, enable DEBUG option:import xtrace\nxtrace.DEBUG = TrueThis will callbeepfunctiton for every interesting event. Feel free to\noverride it (monkeypatch) with your own to filter messages, forward, etc.Known Python BugsPython bugs affecting trace output in unexpected way:http://bugs.python.org/issue15005(Python 2, Linux only)captured stdout from subprocess call becomes corrupted\nunder a trace function that prints to the screen"} +{"package": "xtraceback", "pacakge-description": "XTraceback is an extended Python traceback formatter with support for variable\nexpansion and syntax highlighting.ExamplesAs a context manager - the stdlib traceback module is monkey patched:>>> import sys\n>>> import traceback\n>>> import xtraceback\n>>>\n>>> def some_func():\n... some_var = 2*2\n... raise Exception(\"exc\")\n>>>\n>>> with xtraceback.StdlibCompat():\n... try:\n... some_func()\n... except:\n... traceback.print_exc(file=sys.stdout) #doctest: +ELLIPSIS +REPORT_NDIFF\nTraceback (most recent call last):\n File \"<doctest README.rst[...]>\", line 3, in <module>\n 1 with xtraceback.StdlibCompat():\n 2 try:\n--> 3 some_func()\n g:some_func = <function some_func at 0x...>\n g:sys = <module 'sys' (built-in)>\n g:traceback = <module 'traceback' from='<stdlib>/traceback.pyc'>\n g:xtraceback = <package 'xtraceback' from='xtraceback'>\n 4 except:\n 5 traceback.print_exc(file=sys.stdout) #doctest: +ELLIPSIS +REPORT_NDIFF\n File \"<doctest README.rst[...]>\", line 3, in some_func\n 1 def some_func():\n 2 some_var = 2*2\n--> 3 raise Exception(\"exc\")\n some_var = 4\nException: excAs a sys.excepthook:>>> xtraceback.compat.install_sys_excepthook()\n>>> print sys.excepthook #doctest: +ELLIPSIS\n<bound method StdlibCompat.print_exception of <xtraceback.stdlibcompat.StdlibCompat object at 0x...>>\n>>> raise Exception(\"exc\") #doctest: +ELLIPSIS\nTraceback (most recent call last):\n File \"<stdlib>/doctest.py\", line 1231, in __run\n compileflags, 1) in test.globs\n File \"<doctest README.rst[...]>\", line 1, in <module>\n raise Exception(\"exc\") #doctest: +ELLIPSIS\nException: excBy itself:>>> try:\n... raise Exception(\"exc\")\n... except:\n... print xtraceback.XTraceback(*sys.exc_info(), color=False) #doctest: +ELLIPSIS\nTraceback (most recent call last):\n File \"<doctest README.rst[...]>\", line 2, in <module>\n 1 try:\n--> 2 raise Exception(\"exc\")\n g:some_func = <function some_func at 0x...>\n g:sys = <module 'sys' (built-in)>\n g:traceback = <module 'traceback' from='<stdlib>/traceback.pyc'>\n g:xtraceback = <package 'xtraceback' from='xtraceback'>\n 3 except:\n 4 print xtraceback.XTraceback(*sys.exc_info(), color=False) #doctest: +ELLIPSIS\nException: exc\n<BLANKLINE>In a sitecustomize module:import xtraceback\nxtraceback.compat.install()ConfigurationFor options and their defaults seextraceback.XTraceback\u2019s constructor. When\nusing stdlib compat thextraceback.StdlibCompatclass has adefaultsdictionary which should be updated with your overrides - the default instance\nexists at xtraceback.compat:xtraceback.compat.defaults.update(option=value[, ...])InstallationThe package is on PyPI:pip install xtracebackSyntax highlighting depends on the pygments library:pip install pygmentsNose pluginThe nose plugin is enabled with the\u2013with-xtracebackflag. Seenosetests \u2013helpfor other options."} +{"package": "xtracer", "pacakge-description": "X-TracerMulti Tracing ToolExample 1 for python3 file or python3 consoleip_trace()Example>>fromxtracerimportTracer>>trace=Tracer()>>ip_info=trace.ip_trace('142.250.185.78')>>print(ip_info)IP:142.250.185.78Country:Germanycountrycode:DEregion:HERegionName:HesseCity:FrankfurtamMainzipcode:60313timezone:Europe/BerlinISP:GoogleLLCorg:GoogleLLCas:AS15169GoogleLLClatitude:50.1109longitude:8.68213>>.mac_trace()Example>>fromxtracerimportTracer>>trace=Tracer()>>mac_info=trace.mac_trace('00:11:22:33:44:55')>>print(mac_info)Mac:00:11:22:33:44:55MacVendor:CIMSYSIncPrivate:No>>Example 2 for terminal/cmd~$ python3 -m xtracer=========================__ _______ |\\ \\/ /_ _| |> < | | |/_/\\_\\ |_| ||X-Tracer By: Anikin Luke |-------------------------|Your Ip: 142.250.185.78=========================|[1] ==> (IP Tracer)[2] ==> (MAC Tracer)[0] ==> (Exit)=========================Select~>Installationpython3 -m pip install xtracerorpip3 install xtracerX-Traceronly supports python3InfoNumber of tracers: 2Tracers list:ip_trace('<target_ip>')mac_trace('<target_mac>')"} +{"package": "xtrack", "pacakge-description": "Tracking library for particle accelerators"} +{"package": "xtract", "pacakge-description": "Code:https://rolln.de/knoppo/xtractDocumentation:https://docs.rolln.de/knoppo/xtract/masterCoverage:https://coverage.rolln.de/knoppo/xtract/masterPython library providing an API to unpack/decompress and pack/compress directories and files.\nIt\u2019s a wrapper around the supported archive and compression formats.Supported Archives:Archives arealwaysunpacked to a new directory!rarapplication/rarapplication/x-rarzipapplication/zipapplication/x-ziptarno compression (See usage examples below for an example of adding compression)application/tarapplication/x-tarSupported Compressions:gzapplication/gzipapplication/x-gzipxzapplication/xzapplication/x-xzbz2application/bzipapplication/x-bzipInstallationpipinstallxtractSee thequickstart documentationfor more detailed installation instructions.Usage ExamplesThe convenience functionxtractcan be used to unpack/decompress anything:>>>fromxtractimportxtract>>>xtract('my-directory.tar.gz')'/home/<user>/my-directory.tar'Use theallswitch to loop untilFileTypeNotSupportedis raised:>>>xtract('my-directory.tar.gz',all=True)'/home/<user>/my-directory'Compress a file:>>>fromxtractimportbz2>>>bz2('my-file.txt',delete_source=True)'/home/<user>/my-file.txt.bz2'Every function returns the destination (if successful) to chain them:This creates an intermediate.tarfile! Usedelete_source=Trueto delete it afterwards.>>>fromxtractimporttar,gzip>>>gzip(>>>tar('my-directory',['file1.txt','file2.txt']),>>>delete_source=True>>>)'/home/<user>/my-directory.tar.gz'See themanualfor more examples.LicenseCopyright (c) 2017 Mathias StelzerThis program is free software: you can redistribute it and/or modify\nit under the terms of the GNU General Public License as published by\nthe Free Software Foundation, either version 3 of the License, or\n(at your option) any later version.This program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\nGNU General Public License for more details.You should have received a copy of the GNU General Public License\nalong with this program. If not, see <http://www.gnu.org/licenses/>."} +{"package": "xtracthub", "pacakge-description": "No description available on PyPI."} +{"package": "xtractmime", "pacakge-description": "xtractmimextractmimeis aBSD-licensedPython 3.7+ implementation of theMIME Sniffing\nStandard.Install fromPyPI:pip install xtractmimeBasic usageBelow mentioned are some simple examples of usingxtractmime.extract_mime:>>>fromxtractmimeimportextract_mime>>>extract_mime(b'Sample text content')b'text/plain'>>>extract_mime(b'',content_types=(b'text/html',))b'text/html'Additional functionality to check if a MIME type belongs to a specific MIME type group using\nmethods included inxtractmime.mimegroups:>>>fromxtractmime.mimegroupsimportis_html_mime_type,is_image_mime_type>>>mime_type=b'text/html'>>>is_html_mime_type(mime_type)True>>>is_image_mime_type(mime_type)FalseAPI Referencefunctionxtractmime.extract_mime(*args, **kwargs) -> Optional[bytes]Parameters:body: bytescontent_types: Optional[Tuple[bytes]] = Nonehttp_origin: bool = Trueno_sniff: bool = Falseextra_types: Optional[Tuple[Tuple[bytes, bytes, Optional[Set[bytes]], bytes], ...]] = Nonesupported_types: Set[bytes] = NoneReturn theMIME type essence(e.g.text/html) matching the input data, orNoneif no match can be found.Thebodyparameter is the byte sequence of which MIME type is to be determined.xtractmimeonly considers the first few\nbytes of thebodyand the specific number of bytes read is defined in thextractmime.RESOURCE_HEADER_BUFFER_LENGTHconstant.content_typesis a tuple of MIME types given in the resource metadata. For example, for resources retrieved via HTTP, users should pass the list of MIME types mentioned in theContent-Typeheader.http_originindicates if the resource has been retrieved via HTTP (True, default) or not (False).no_sniffis a flag which isTrueif the user agent does not wish to\nperform sniffing on the resource andFalse(by default) otherwise. Users may want to set\nthis parameter toTrueif theX-Content-Type-Optionsresponse header is set tonosniff. For more info, seehere.extra_typesis a tuple of patterns to support detecting additional MIME types. Each entry in the tuple should follow the format(Byte Pattern, Pattern Mask, Leading Bytes, MIME type):Byte Patternis a byte sequence to compare with the first few bytes (xtractmime.RESOURCE_HEADER_BUFFER_LENGTH) of thebody.Pattern Maskis a byte sequence that indicates the significance ofByte Patternbytes:b\"\\xff\"indicates the matching byte is strictly significant,b\"\\xdf\"indicates that the byte is significant in an ASCII case-insensitive way, andb\"\\x00\"indicates that the byte is not significant.Leading Bytesis a set of bytes to be ignored while matching the leading bytes in the content.MIME typeshould be returned if the pattern matches.Sampleextra_types:extra_types=((b'test',b'\\xff\\xff\\xff\\xff',None,b'text/test'),...)NOTEBe careful while using theextra_typesargument, as it may introduce some privilege escalation vulnerabilities forxtractmime. For more info, seehere.Optionalsupported_typesis a set of allMIME types supported the by user agent. Ifsupported_typesis not\nspecified, all MIME types are assumed to be supported. Using this parameter can improve the performance ofxtractmime.functionxtractmime.is_binary_data(input_bytes: bytes) -> boolReturnTrueif the provided byte sequence contains any binary data bytes, elseFalseMIME type group functionsThe following functions returnTrueif a given MIME type belongs to a certainMIME type group, orFalseotherwise:xtractmime.mimegroups.is_archive_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_audio_video_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_font_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_html_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_image_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_javascript_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_json_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_scriptable_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_xml_mime_type(mime_type: bytes) -> bool\nxtractmime.mimegroups.is_zip_mime_type(mime_type: bytes) -> boolExample>>>fromxtractmime.mimegroupsimportis_html_mime_type,is_image_mime_type,is_zip_mime_type>>>mime_type=b'text/html'>>>is_html_mime_type(mime_type)True>>>is_image_mime_type(mime_type)False>>>is_zip_mime_type(mime_type)FalseChangelogSee thechangelog"} +{"package": "xtracto", "pacakge-description": "Xtracto Web Development FrameworkeXtensible, Configurable, and Reusable Automation Component Tool and Organizerfor html through pypxXtracto is a lightweight web development framework designed to simplify the process of creating dynamic web pages using Python.This module is a parser for pypx (custom markup language) to htmlreadpypx.mdto understand the custom markup languageFeaturesParser Class:Easily parse and transform content using theParserclass.Automatic Server Setup:Use theAppclass for hassle-free server setup with FastAPI and Uvicorn.Testing Support:Conduct tests on your content or files using theTestsclass.It is recommended that you use python 3.9 (as of 3rd january 2024) for best compatibilityInstallationpip install xtractoUsage1. Parser ClassInitialize theParserclass with the content or file path:Example with contentfromxtractoimportParsercontent=\"Your content here\"parser=Parser(content=content)Example with a file pathfromxtractoimportParserfile_path=\"path/to/your/file.pypx\"parser=Parser(path=file_path)2. Automatic Server SetupUse theAppclass for automatic server setup:fromxtractoimportAppapp=App()3. CompilationCompile non-dynamic pages to HTML:ExamplefromxtractoimportParserparser=Parser()parser.compile(start_path_for_map=\"/\")Configurationproject root is determined using the presence ofxtracto.config.pyit must be present otherwise will raise error.Paths in the pypx files are relative to the project root.Paths in the config file are relative to the project root.The config file can be empty.Customize project-specific configurations in thextracto.config.pyfile. Update the following parameters:modules_dir: Directory for modules (default: \"xtractocomponents\").pages_dir: Directory for pages (default: \"xtractopages\").strip_imports: Whether to strip imports (default: True).raise_value_errors_while_importing: Whether to raise value errors during imports (default: True)."} +{"package": "xtractor", "pacakge-description": "No description available on PyPI."} +{"package": "xtractr", "pacakge-description": "xTractrPurposexTractr is a repository of all extraction-related functions that I've had to use for varying projects - generalized to be able to be useful across any range of tasks. Some of the extraction mechanisms are genuinely involved and are useful, others are simply 2 line functions meant to more clearly represent abstractions provided by packages and services like Python-Docx, Selenium, and AWS. The goal of xTractr is to make a variety of disparate 'extraction-related' tasks much more human-readable and simpler to reference in an IDE with autocomplete than having to lookup a method everytime you want to do something.Future WorkRight now, xTractr is kind of barebones - I plan on diversifying some of its functionality and continuing to experiment with effective ways to communicate the purpose of varying packages. Let me know if there's a type of job that I missed as I expand its scope."} +{"package": "xtract-sdk", "pacakge-description": "Xtract SDK v0.0.5Packaging: Creating file group objects for downstream data packaging.Here we have a number of data elements that need to be defined.Group: a collection of files and extractor to be executed on the collection of files. Groups need not have mutually exclusive\nsets of files. A group is also intitialized with an empty metadata dictionary.from xtract_sdk.packagers import Group, Family, FamilyBatchgroup1 = Group(files=[{'path': 12388550508, 'mdata': {}}], parser='image'}group2 = Group(files=[{'path': 14546663235, 'mdata': {}}], parser='image'}Family: a collection of groups such that all files in the group are mutually exclusive. This grouping is useful for\nparallelizing the download and extraction of separate groups that may contain the same files. You can easily add Group\nobjects to a family as follows:fam = Family()fam.add_group(group1)fam.add_group(group2)FamilyBatch: If the number of groups in a family is generally small, you may want to batch the families to increase application\nperformance. In order to do this, you may add any number of families to a FamilyBatch that enables users to iterate\nover families. The family_batch can be directly read by the downloader that will batch-fetch all files therein.fam_batch=FamilyBatch()fam_batch.add_family(fam)Downloaders: coming soon!"} +{"package": "xtracture", "pacakge-description": "Xtracture: Open Source Document Content Extractuion LibraryXtracture is an open source library designed to efficiently extract arbitrary elements from documents.FeaturesNatural language rule creation using LLMsSwitchable OCR engines for optimized perfomance and accuracyprerequirementsOpenAI API Key (for LLM rule creation)Installationpip install -U xtractureUsageUse Google Cloud Vision APIGoogle CLoud Vision Credentials must be correctly configured.seeexamples/google_cloud_vision_example.py.Use TesseractTesseract must be installed beforehand.seeexamples/tesseract_example.py.Use only GPT ExtractorYou can input OCR-processed text file.\nseeexamples/lambda_example.py.LicenseXtracture is released under the MIT License."} +{"package": "xtradict", "pacakge-description": "Extended dict class for python, instead of using dict['index'], you can use dict.index, to use it, use strg(**dict) or default kwargs"} +{"package": "x-trading", "pacakge-description": "No description available on PyPI."} +{"package": "xtra-ez", "pacakge-description": "No description available on PyPI."} +{"package": "xtrain", "pacakge-description": "XTRAIN: a tiny library for trainingFlaxmodels.Design goals:Help avoiding boiler-plate codeMinimal functionality and dependencyAgnostic to hardware configuration (e.g. GPU->TPU)General workflowStep 1: define your modelclass MyFlaxModule(nn.Module):\n def __call__(self, x):\n ...Step 2: define loss functiondef my_loss_func(**kwargs):\n model_out = kwargs[\"preds\"]\n labels = kwargs[\"labels\"]\n loss = ....\n return lossStep 3: create an iterator that supplies training datamy_data = itertools.cycle(\n zip(sequence_of_inputs, sequence_of_labels)\n)Step 4: train# create and initialize a Trainer object\ntrainer = xtrain.Trainer(\n model = MyFlaxModule(),\n losses = my_loss_func,\n)\ntrainer.initialize(my_data, tx=my_optax_optimizer)\n\ntrain_iter = trainer.train(my_data) # returns a python iterator\n\n# iterate the train_iter trains the model\nfor step in range(train_steps):\n avg_loss = next(train_iter)\n if step // 1000 == 0:\n print(avg_loss)\n trainer.reset()Full documentationhttps://jiyuuchc.github.io/xtrain/"} +{"package": "xtraining", "pacakge-description": "This is a simple example package."} +{"package": "xtralien", "pacakge-description": "pyxtralienThis module is a simple interface to Ossila's Source Measure Unit.DescriptionXtralien is an open-source project from the Engineers atOssilato allow control of their equipment easily and Pythonically.\nIt is based on CLOI, the Command Language for Ossila Instruments.InstallationUsingpip:pipinstallxtralienIf you want to control the equipment using USB you will also need to installpySerial.UsageBelow is a simple example of taking a measurement using the library.importtimefromxtralienimportDevicecom_port='com5'channel='smu1'# Connect to the Source Measure Unit using USBwithDevice(com_port)asSMU:# Turn on SMU 1SMU[channel].set.enabled(1,response=0)# Set voltage, measure voltage and currentvoltage,current=SMU[channel].oneshot(set_v)[0]# Print measured voltage and currentprint(f'V:{voltage}V; I:{current}A')# Reset output voltage and turn off SMU 1SMU[channel].set.voltage(0,response=0)time.sleep(0.1)SMU[channel].set.enabled(False,response=0)For more documentation examples see ourprogramming guide."} +{"package": "xtransfer", "pacakge-description": "#\u00a0xtransferA cli utility to rule file transfers (well\u2026 between local FS, SFTP and S3)\u2026Under heavy construction\u2026"} +{"package": "x-transformers", "pacakge-description": "No description available on PyPI."} +{"package": "xtream", "pacakge-description": "READ MEHISTORY"} +{"package": "xtream-diamonds", "pacakge-description": "No description available on PyPI."} +{"package": "xtree", "pacakge-description": "xtree can easily convert an archive or a directory populated by a lot of\nnested subdirectories into a flat tree structure, or the other way round.This is particularly useful to move files scattered across a lot of\nsubdirectories into a single directory, or to move files grouped by a\ncommon pattern into corresponding subdirectories."} +{"package": "xtremcache", "pacakge-description": "xtremcachextremcacheis a Python package dedicated to handle generic file and directories caching on Windows or Linux.\nThe goal of this module is to be able to cache a file or directory with a unique identifier of your choice and later uncache to a specific location.\nThe directory where the cached files are located is local.\nThe concurrent access (reading and writing) on chached archives is handle by a small data base located in the local data directory.Installationxtremcacheis available onPyPi.TestsTests are written followingunittestframework. Some dependencies are needed (test-requirements.txt). If you want to run tests, enter the following command at the root level of the package:python-munittestdiscover-stests# All testspython-munittestdiscover-stests/unit# Unit testspython-munittestdiscover-stests/integration# Integration testsUsageCache and uncache exampleCreate CacheManager with optional data location and the maximum size in Mo of this cache directory.Cache a directory with unique id to find it lather.Uncache with unique id to a specifique directory.Python:fromxtremcache.cachemanagerimportCacheManagercache_manager=CacheManager(cache_dir='/tmp/xtremcache',max_size=20_000_000)cache_manager.cache(id='UUID',path='/tmp/dir_to_cache')cache_manager.uncache(id='UUID',path='/tmp/destination_dir')Shell:xtremcacheconfigsetcache_dir'/tmp/xtremcache'--local\nxtremcacheconfigsetmax_size'20m'--local\nxtremcachecache--id'UUID''/tmp/dir_to_cache'xtremcacheuncache--id'UUID''/tmp/destination_dir'Override cached exampleCreate CacheManager with data location and the maximum size in Mo of this cache directoryCache a directory with unique id to find it latherOverride last unique id to a new directoryPython:fromxtremcache.cachemanagerimportCacheManagercache_manager=CacheManager(cache_dir='/tmp/xtremcache',max_size=20_000_000)cache_manager.cache(id='UUID',path='/tmp/dir_to_cache')cache_manager.cache(id='UUID',path='/tmp/new_dir_to_cache',force=True)Shell:xtremcacheconfigsetcache_dir'/tmp/xtremcache'--local\nxtremcacheconfigsetmax_size'20m'--local\nxtremcachecache--id'UUID''/tmp/dir_to_cache'xtremcachecache--force--id'UUID''/tmp/new_dir_to_cache'Cache and clean exampleCreate CacheManager with data location and the maximum size in Mo of this cache directoryCache a directory with unique id to find it latherRemove chached filePython:fromxtremcache.cachemanagerimportCacheManagercache_manager=CacheManager(cache_dir='/tmp/xtremcache',max_size='20m')cache_manager.cache(id='UUID',path='/tmp/dir_to_cache')cache_manager.remove(id='UUID')Shell:xtremcacheconfigsetcache_dir'/tmp/xtremcache'--local\nxtremcacheconfigsetmax_size'20m'--local\nxtremcachecache--id'UUID''/tmp/dir_to_cache'xtremcacheremove--id'UUID'Cache and clean all exampleCreate CacheManager with data location and the maximum size in Mo of this cache directoryCache a directory with unique id to find it latherRemove all chached filesPython:fromxtremcache.cachemanagerimportCacheManagercache_manager=CacheManager(cache_dir='/tmp/xtremcache',max_size='20m')cache_manager.cache(id='UUID',path='/tmp/dir_to_cache')cache_manager.remove()Shell:xtremcacheconfigsetcache_dir'/tmp/xtremcache'--local\nxtremcacheconfigsetmax_size'20m'--local\nxtremcachecache--id'UUID''/tmp/dir_to_cache'xtremcacheremove"} +{"package": "xtreme-calculator-sdk", "pacakge-description": "No description available on PyPI."} +{"package": "xtreme-distributions", "pacakge-description": "No description available on PyPI."} +{"package": "xtreme-vision", "pacakge-description": "Xtreme-VisionGo to PyPI page>HereThis is the Official Repository of Xtreme-Vision. Xtreme-Vision is a High Level Python Library which is built with simplicity in mind for Computer Vision Tasks, such as Object-Detection, Human-Pose-Estimation, Segmentation Tasks, it provides the support of a list of state-of-the-art algorithms, You can Start Detecting with Pretrained Weights as well as You can train the Models On Custom Dataset and with Xtreme-Vision you have the Power to detect/segment only the Objects of your interestCurrently, It Provides the Solution for the following Tasks:Object DetectionPose EstimationObject SegmentationHuman Part SegmentationFor Detection with pre-trained models it provides:RetinaNetCenterNetYOLOv4TinyYOLOv4Mask-RCNNDeepLabv3+ (Ade20k)CDCL (Cross Domain Complementary Learning)For Custom Training It Provides:YOLOv4TinyYOLOv4RetinaNet with (resnet50, resnet101, resnet152)If You Like this Project, Sponser it hereDependencies:tensorflow >= 2.3.0kerasopencv-pythonnumpypillowmatplotlibpandasscikit-learnscikit-imageimgauglabelme2cocoprogressbar2scipyh5pyconfigobjGet Started:!pipinstallxtreme-visionFor More Tutorials of Xtreme-Vision, ClickHereYOLOv4ExampleImage Object DetectionUsingYOLOv4fromxtreme_vision.DetectionimportObject_Detectionmodel=Object_Detection()model.Use_YOLOv4()model.Detect_From_Image(input_path='kite.jpg',output_path='./output.jpg')fromPILimportImageImage.open('output.jpg')"} +{"package": "xtrf-api", "pacakge-description": "XTRF Home Portal API enables you to perform operations on Projects, Quotes, Customers, Vendors etc. as a XTRF Home Portal user. <br>The documentation is generated from OpenAPI specification 3.0 available <a href="/home-api/openapi.json">here</a> <br> The API client/consumer code may be easily generated in 60+ programming languages using an open source code generator available at the time of writing this documentation at <a href='https://editor.swagger.io/'>https://editor.swagger.io/</a> Thank you for using XTRF Application Programming interface (XTRF API). By using the API you agree to the terms below. If you disagree with any of these terms, XTRF does not grant you a license to use the XTRF API. XTRF reserves the right to update and change these terms from time to time without a prior notice of API users. You can always find the most recent version of these terms here: # noqa: E501"} +{"package": "xtrip-auth", "pacakge-description": "xtrip-auth"} +{"package": "xtrm-drest", "pacakge-description": "Dynamic RESTDynamic API extensions for Django REST FrameworkSeehttp://dynamic-rest.readthedocs.orgfor full documentation.Table of ContentsOverviewMaintainersRequirementsInstallationDemoFeaturesLinked relationshipsSideloaded relationshipsEmbedded relationshipsInclusionsExclusionsFilteringOrderingDirectory panelOptimizationsSettingsCompatibility tableContributingLicenseOverviewDynamic REST (or DREST) extends the popularDjango REST Framework(or DRF) with API features that\nempower simple RESTful APIs with the flexibility of a graph query language.DREST classes can be used as a drop-in replacement for DRF classes, which offer the following features on top of the standard DRF kit:Linked relationshipsSideloaded relationshipsEmbedded relationshipsInclusionsExclusionsFilteringSortingDirectory panel for your Browsable APIOptimizationsDREST was initially written to complementEmber Data,\nbut it can be used to provide fast and flexible CRUD operations to any consumer that supports JSON over HTTP.MaintainersAnthony LeontievRyo ChijiiwaRequirementsPython (2.7, 3.3, 3.4, 3.5)Django (1.8, 1.9, 1.10, 1.11)Django REST Framework (3.1, 3.2, 3.3, 3.4, 3.5, 3.6)InstallationInstall usingpip:pipinstalldynamic-rest(or adddynamic-resttorequirements.txtorsetup.py)Addrest_frameworkandxtrm_dresttoINSTALLED_APPSinsettings.py:INSTALLED_APPS=(...'rest_framework','xtrm_drest')If you want to use theDirectory panel, replace DRF's browsable API renderer with DREST's\nin your settings:REST_FRAMEWORK={'DEFAULT_RENDERER_CLASSES':['rest_framework.renderers.JSONRenderer','xtrm_drest.renderers.DynamicBrowsableAPIRenderer',],}DemoThis repository comes with atestspackage that also serves as a demo application.\nThis application is hosted athttps://dynamic-rest.herokuapp.combut can also be run locally:Clone this repository:gitclonegit@github.com:AltSchool/dynamic-rest.gitcddynamic-restFrom within the repository root, start the demo server:makeserveVisitlocalhost:9002in your browser.To load sample fixture data, runmake fixturesand restart the server.FeaturesTo understand the DREST API features, let us consider a demo model with a corresponding viewset, serializer, and route.\nThis will look very familiar to anybody who has worked with DRF:# The related LocationSerializer and GroupSerializer are omitted for brevity# The ModelclassUser(models.Model):name=models.TextField()location=models.ForeignKey('Location')groups=models.ManyToManyField('Group')# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\")location=DynamicRelationField('LocationSerializer')groups=DynamicRelationField('GroupSerializer',many=True)# The ViewSetclassUserViewSet(DynamicModelViewSet):serializer_class=UserSerializerqueryset=User.objects.all()# The Routerrouter=DynamicRouter()router.register('/users',UserViewSet)Linked relationshipsOne of the key features of the DREST serializer layer is the ability to represent relationships in different ways, depending on the request context (external requirements) and the code context (internal requirements).By default, a \"has-one\" (or \"belongs-to\") relationship will be represented as the value of the related object's ID.\nA \"has-many\" relationship will be represented as a list of all related object IDs.When a relationship is represented in this way, DREST automatically includes relationship links for any has-many relationships in the API response that represents the object:-->\n GET /users/1/\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2],\n \"links\": {\n \"groups\": \"/users/1/groups\"\n }\n }\n }An API consumer can navigate to these relationship endpoints in order to obtain information about the related records. DREST will automatically create\nthe relationship endpoints -- no additional code is required:-->\n GET /users/1/groups\n<--\n 200 OK\n {\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2,\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3,\n }]\n }Sideloaded relationshipsUsing linked relationships provides your API consumers with a \"lazy-loading\" mechanism for traversing through a graph of data. The consumer can first load the primary resource and then load related resources later.In some situations, it can be more efficient to load relationships eagerly, in such a way that both the primary records and their related data are loaded simultaneously. In Django, this can be accomplished by usingprefetch_relatedorselect_related.In DREST, the requirement to eagerly load (or \"sideload\") relationships can be expressed with theinclude[]query parameter.For example, in order to fetch a user and sideload their groups:--> \n GET /users/1/?include[]=groups.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2]\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3\n }]\n }The \"user\" portion of the response looks nearly identical to the first example; the user is returned top-level, and the groups are represented by their IDs. However, instead of including a link to the groups endpoint, the group data is present within the respones itself, under a top-level \"groups\" key.Note that each group itself contains relationships to \"location\", which are linked in this case.With DREST, it is possible to sideload as many relationships as you'd like, as deep as you'd like.For example, to obtain the user with groups, locations, and groups' locations all sideloaded in the same response:--> \n GET /users/1/?include[]=groups.location.*&include[]=location.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2]\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2,\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3,\n }],\n \"locations\": [{\n \"id\": 1,\n \"name\": \"New York\"\n }, {\n \"id\": 2,\n \"name\": \"New Jersey\"\n }, {\n \"id\": 3,\n \"name\": \"California\"\n }]\n }Embedded relationshipsIf you want your relationships loaded eagerly but don't want them sideloaded in the top-level, you can instruct your serializer to embed relationships instead.In that case, the demo serializer above would look like this:# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\")location=DynamicRelationField('LocationSerializer',embed=True)groups=DynamicRelationField('GroupSerializer',embed=True,many=True)... and the call above would return a response with relationships embedded in place of the usual ID representation:--> \n GET /users/1/?include[]=groups.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3\n }]\n }\n }In DREST, sideloading is the default because it can produce much smaller payloads in circumstances where related objects are referenced more than once in the response.For example, if you requested a list of 10 users along with their groups, and those users all happened to be in the same groups, the embedded variant would represent each group 10 times. The sideloaded variant would only represent a particular group once, regardless of the number of times that group is referenced.InclusionsYou can use theinclude[]feature not only to sideload relationships, but also to load basic fields that are marked \"deferred\".In DREST, any field or relationship can be marked deferred, which indicates to the framework that the field should only be returned when requested byinclude[]. This could be a good option for fields with large values that are not always relevant in a general context.For example, a user might have a \"personal_statement\" field that we would want to defer. At the serializer layer, that would look like this:# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\",\"personal_statement\")deferred_fields=(\"personal_statement\",)location=DynamicRelationField('LocationSerializer')groups=DynamicRelationField('GroupSerializer',many=True)This field will only be returned if requested:-->\n GET /users/1/?include[]=personal_statement\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2],\n \"personal_statement\": \"Hello, my name is John and I like........\",\n \"links\": {\n \"groups\": \"/users/1/groups\"\n }\n }\n }Note thatinclude[]=personal_statementdoes not have a.following the field name as in the previous examples for embedding and sideloading relationships. This allows us to differentiate between cases where we have a deferred relationship and want to include the relationship IDs as opposed to including and also sideloading the relationship.For example, if the user had a deferred \"events\" relationship, passinginclude[]=eventswould return an \"events\" field populated by event IDs, passinginclude[]=events.would sideload or embed the events themselves, and by default, only a link to the events would be returned. This can be useful for large has-many relationships.ExclusionsJust as deferred fields can be included on demand with theinclude[]feature, fields that are not deferred can be excluded with theexclude[]feature. Likeinclude[],exclude[]also supports multiple values and dot notation to allow you to exclude fields on sideloaded relationships.For example, if we want to fetch a user with his groups, but ignore the groups' location and user's location, we could make a request like this:-->\n GET /users/1/?include[]=groups.*&exclude[]=groups.location&exclude[]=location\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"groups\": [1, 2],\n \"links\": {\n \"location\": \"/users/1/location\"\n }\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"links\": {\n \"location\": \"/groups/1/location\"\n }\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"links\": {\n \"location\": \"/groups/2/location\"\n }\n }]\n }exclude[]supports the wildcard value:*, which means \"don't return anything\".\nWhy is that useful?include[]overridesexclude[], soexclude[]=*can be combined withinclude[]to return only a single value or set of values from a resource.For example, to obtain only the user's name:-->\n GET /users/1/?exclude[]=*&include[]=name\n<--\n 200 OK\n {\n \"user\": {\n \"name\": \"John\",\n \"links\": {\n \"location\": \"/users/1/location\",\n \"groups\": \"/users/1/groups\"\n }\n }\n }Note thatlinkswill always be returned for relationships that are deferred.FilteringTired of writing custom filters for all of your fields? DREST has your back with thefilter{}feature.You can filter a user by his name (exact match):-->\n GET /users/?filter{name}=John\n<--\n 200 OK\n ...... or a partial match:--> \n GET /users/?filter{name.icontains}=jo\n<--\n 200 OK\n ...... or one of several names:-->\n GET /users/?filter{name.in}=John&filter{name.in}=Joe\n<--\n 200 OK... or a relationship ID:-->\n GET /users/?filter{groups}=1\n<--\n 200 OK... or lack thereof:-->\n GET /users/?filter{-groups}=1\n<--\n 200 OK... or a relationship field:-->\n GET /users/?filter{groups.name}=Home\n<--\n 200 OK... or multiple criteria:-->\n GET /users/?filter{groups.name}=Home&filter{name}=John\n<--\n 200 OK... or combine it withinclude[]to filter the sideloaded data (get all the users and only sideload certain groups):-->\n GET /users/?include[]=groups.*&filter{groups|name.icontains}=h\n<--\n 200 OKThe sky is the limit! DREST supports just about every basic filtering scenario and operator that you can use in Django:inicontainsistartswithrangeltgt\n...See thefull list here.OrderingYou can use thesort[]feature to order your response by one or more fields. Dot notation is supported for sorting by nested properties:-->\n GET /users/?sort[]=name&sort[]=groups.name\n<--\n 200 OK\n ...For descending order, simply add a-sign. To sort by name in descending order for example-->\n GET /users/?sort[]=-name\n<--\n 200 OK\n ...Directory panelWe love the DRF browsable API, but wish that it included a directory that would let you see your entire list of endpoints at a glance from any page.\nDREST adds that in:OptimizationsSupporting nested sideloading and filtering is expensive and can lead to very poor query performance if implemented naively.\nDREST uses Django'sPrefetchobject to prevent N+1 query situations and guarantee that your API is performant.\nWe also optimize the serializer layer to ensure that the conversion of model objects into JSON is as fast as possible.How fast is it? Here are somebenchmarksthat compare DREST response time to DRF response time. DREST out-performs DRF on every benchmark:Linear benchmark: rendering a flat listQuadratic benchmark: rendering a list of listsCubic benchmark: rendering a list of lists of listsSettingsDREST is configurable, and all settings should be nested under a single block in yoursettings.pyfile.\nHere are ourdefaults:xtrm_drest={# DEBUG: enable/disable internal debugging'DEBUG':False,# ENABLE_BROWSABLE_API: enable/disable the browsable API.# It can be useful to disable it in production.'ENABLE_BROWSABLE_API':True,# ENABLE_LINKS: enable/disable relationship links'ENABLE_LINKS':True,# ENABLE_SERIALIZER_CACHE: enable/disable caching of related serializers'ENABLE_SERIALIZER_CACHE':True,# ENABLE_SERIALIZER_OPTIMIZATIONS: enable/disable representation speedups'ENABLE_SERIALIZER_OPTIMIZATIONS':True,# DEFER_MANY_RELATIONS: automatically defer many-relations, unless# `deferred=False` is explicitly set on the field.'DEFER_MANY_RELATIONS':False,# MAX_PAGE_SIZE: global setting for max page size.# Can be overriden at the viewset level.'MAX_PAGE_SIZE':None,# PAGE_QUERY_PARAM: global setting for the pagination query parameter.# Can be overriden at the viewset level.'PAGE_QUERY_PARAM':'page',# PAGE_SIZE: global setting for page size.# Can be overriden at the viewset level.'PAGE_SIZE':None,# PAGE_SIZE_QUERY_PARAM: global setting for the page size query parameter.# Can be overriden at the viewset level.'PAGE_SIZE_QUERY_PARAM':'per_page',# ADDITIONAL_PRIMARY_RESOURCE_PREFIX: String to prefix additional# instances of the primary resource when sideloading.'ADDITIONAL_PRIMARY_RESOURCE_PREFIX':'+',# Enables host-relative links. Only compatible with resources registered# through the dynamic router. If a resource doesn't have a canonical# path registered, links will default back to being resource-relative urls'ENABLE_HOST_RELATIVE_LINKS':True}Compatibility tableNot all versions of Python, Django, and DRF are compatible. Here are the combinations you can use reliably with DREST (all tested by our tox configuration):PythonDjangoDRFOK2.71.83.1YES2.71.83.2YES2.71.83.3YES2.71.83.4YES2.71.93.1NO12.71.93.2YES2.71.93.3YES2.71.93.4YES2.71.103.2NO32.71.103.3NO32.71.103.4YES2.71.103.5YES2.71.103.6YES2.71.113.4YES2.71.113.5YES2.71.113.6YES3.31.83.1YES3.31.83.2YES3.31.83.3YES3.31.83.4YES3.31.9x.xNO23.31.10x.xNO43.31.11x.xNO53.41.83.1YES3.41.83.2YES3.41.83.3YES3.41.83.4YES3.41.93.1NO13.41.93.2YES3.41.93.3YES3.41.93.4YES3.41.103.2NO33.41.103.3NO33.41.103.4YES3.41.103.5YES3.41.103.6YES3.41.113.3NO33.41.113.4YES3.41.113.5YES3.51.83.1YES3.51.83.2YES3.51.83.3YES3.51.83.4YES3.51.93.1NO13.51.93.2YES3.51.93.3YES3.51.93.4YES3.51.103.2NO33.51.103.3NO33.51.103.4YES3.51.103.5YES3.51.103.6YES3.51.113.4YES3.51.113.5YES3.51.113.6YES1: Django 1.9 is not compatible with DRF 3.12: Django 1.9 is not compatible with Python 3.33: Django 1.10 is only compatible with DRF 3.4+4: Django 1.10 requires Python 2.7, 3.4, 3.55: Django 1.11 requires Python 2.7, 3.4, 3.5, 3.6ContributingSeeContributing.LicenseSeeLicense.#CreditsThis is a fork from AltSchool\nDRF 3.8 fixes was implemented by jgissend10drf-writable-nested-\nThe writable nested part was from drf-writable-nested implemented\nby beda-software"} +{"package": "xtrm-library", "pacakge-description": "Dynamic RESTDynamic API extensions for Django REST FrameworkSeehttp://dynamic-rest.readthedocs.orgfor full documentation.Table of ContentsOverviewMaintainersRequirementsInstallationDemoFeaturesLinked relationshipsSideloaded relationshipsEmbedded relationshipsInclusionsExclusionsFilteringOrderingDirectory panelOptimizationsSettingsCompatibility tableContributingLicenseOverviewDynamic REST (or DREST) extends the popularDjango REST Framework(or DRF) with API features that\nempower simple RESTful APIs with the flexibility of a graph query language.DREST classes can be used as a drop-in replacement for DRF classes, which offer the following features on top of the standard DRF kit:Linked relationshipsSideloaded relationshipsEmbedded relationshipsInclusionsExclusionsFilteringSortingDirectory panel for your Browsable APIOptimizationsDREST was initially written to complementEmber Data,\nbut it can be used to provide fast and flexible CRUD operations to any consumer that supports JSON over HTTP.MaintainersAnthony LeontievRyo ChijiiwaRequirementsPython (2.7, 3.3, 3.4, 3.5)Django (1.8, 1.9, 1.10, 1.11)Django REST Framework (3.1, 3.2, 3.3, 3.4, 3.5, 3.6)InstallationInstall usingpip:pipinstalldynamic-rest(or adddynamic-resttorequirements.txtorsetup.py)Addrest_frameworkandxtrm_dresttoINSTALLED_APPSinsettings.py:INSTALLED_APPS=(...'rest_framework','xtrm_drest')If you want to use theDirectory panel, replace DRF's browsable API renderer with DREST's\nin your settings:REST_FRAMEWORK={'DEFAULT_RENDERER_CLASSES':['rest_framework.renderers.JSONRenderer','xtrm_drest.renderers.DynamicBrowsableAPIRenderer',],}DemoThis repository comes with atestspackage that also serves as a demo application.\nThis application is hosted athttps://dynamic-rest.herokuapp.combut can also be run locally:Clone this repository:gitclonegit@github.com:AltSchool/dynamic-rest.gitcddynamic-restFrom within the repository root, start the demo server:makeserveVisitlocalhost:9002in your browser.To load sample fixture data, runmake fixturesand restart the server.FeaturesTo understand the DREST API features, let us consider a demo model with a corresponding viewset, serializer, and route.\nThis will look very familiar to anybody who has worked with DRF:# The related LocationSerializer and GroupSerializer are omitted for brevity# The ModelclassUser(models.Model):name=models.TextField()location=models.ForeignKey('Location')groups=models.ManyToManyField('Group')# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\")location=DynamicRelationField('LocationSerializer')groups=DynamicRelationField('GroupSerializer',many=True)# The ViewSetclassUserViewSet(DynamicModelViewSet):serializer_class=UserSerializerqueryset=User.objects.all()# The Routerrouter=DynamicRouter()router.register('/users',UserViewSet)Linked relationshipsOne of the key features of the DREST serializer layer is the ability to represent relationships in different ways, depending on the request context (external requirements) and the code context (internal requirements).By default, a \"has-one\" (or \"belongs-to\") relationship will be represented as the value of the related object's ID.\nA \"has-many\" relationship will be represented as a list of all related object IDs.When a relationship is represented in this way, DREST automatically includes relationship links for any has-many relationships in the API response that represents the object:-->\n GET /users/1/\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2],\n \"links\": {\n \"groups\": \"/users/1/groups\"\n }\n }\n }An API consumer can navigate to these relationship endpoints in order to obtain information about the related records. DREST will automatically create\nthe relationship endpoints -- no additional code is required:-->\n GET /users/1/groups\n<--\n 200 OK\n {\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2,\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3,\n }]\n }Sideloaded relationshipsUsing linked relationships provides your API consumers with a \"lazy-loading\" mechanism for traversing through a graph of data. The consumer can first load the primary resource and then load related resources later.In some situations, it can be more efficient to load relationships eagerly, in such a way that both the primary records and their related data are loaded simultaneously. In Django, this can be accomplished by usingprefetch_relatedorselect_related.In DREST, the requirement to eagerly load (or \"sideload\") relationships can be expressed with theinclude[]query parameter.For example, in order to fetch a user and sideload their groups:--> \n GET /users/1/?include[]=groups.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2]\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3\n }]\n }The \"user\" portion of the response looks nearly identical to the first example; the user is returned top-level, and the groups are represented by their IDs. However, instead of including a link to the groups endpoint, the group data is present within the respones itself, under a top-level \"groups\" key.Note that each group itself contains relationships to \"location\", which are linked in this case.With DREST, it is possible to sideload as many relationships as you'd like, as deep as you'd like.For example, to obtain the user with groups, locations, and groups' locations all sideloaded in the same response:--> \n GET /users/1/?include[]=groups.location.*&include[]=location.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2]\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2,\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3,\n }],\n \"locations\": [{\n \"id\": 1,\n \"name\": \"New York\"\n }, {\n \"id\": 2,\n \"name\": \"New Jersey\"\n }, {\n \"id\": 3,\n \"name\": \"California\"\n }]\n }Embedded relationshipsIf you want your relationships loaded eagerly but don't want them sideloaded in the top-level, you can instruct your serializer to embed relationships instead.In that case, the demo serializer above would look like this:# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\")location=DynamicRelationField('LocationSerializer',embed=True)groups=DynamicRelationField('GroupSerializer',embed=True,many=True)... and the call above would return a response with relationships embedded in place of the usual ID representation:--> \n GET /users/1/?include[]=groups.*\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"location\": 2\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"location\": 3\n }]\n }\n }In DREST, sideloading is the default because it can produce much smaller payloads in circumstances where related objects are referenced more than once in the response.For example, if you requested a list of 10 users along with their groups, and those users all happened to be in the same groups, the embedded variant would represent each group 10 times. The sideloaded variant would only represent a particular group once, regardless of the number of times that group is referenced.InclusionsYou can use theinclude[]feature not only to sideload relationships, but also to load basic fields that are marked \"deferred\".In DREST, any field or relationship can be marked deferred, which indicates to the framework that the field should only be returned when requested byinclude[]. This could be a good option for fields with large values that are not always relevant in a general context.For example, a user might have a \"personal_statement\" field that we would want to defer. At the serializer layer, that would look like this:# The SerializerclassUserSerializer(DynamicModelSerializer):classMeta:model=Username='user'fields=(\"id\",\"name\",\"location\",\"groups\",\"personal_statement\")deferred_fields=(\"personal_statement\",)location=DynamicRelationField('LocationSerializer')groups=DynamicRelationField('GroupSerializer',many=True)This field will only be returned if requested:-->\n GET /users/1/?include[]=personal_statement\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"location\": 1,\n \"groups\": [1, 2],\n \"personal_statement\": \"Hello, my name is John and I like........\",\n \"links\": {\n \"groups\": \"/users/1/groups\"\n }\n }\n }Note thatinclude[]=personal_statementdoes not have a.following the field name as in the previous examples for embedding and sideloading relationships. This allows us to differentiate between cases where we have a deferred relationship and want to include the relationship IDs as opposed to including and also sideloading the relationship.For example, if the user had a deferred \"events\" relationship, passinginclude[]=eventswould return an \"events\" field populated by event IDs, passinginclude[]=events.would sideload or embed the events themselves, and by default, only a link to the events would be returned. This can be useful for large has-many relationships.ExclusionsJust as deferred fields can be included on demand with theinclude[]feature, fields that are not deferred can be excluded with theexclude[]feature. Likeinclude[],exclude[]also supports multiple values and dot notation to allow you to exclude fields on sideloaded relationships.For example, if we want to fetch a user with his groups, but ignore the groups' location and user's location, we could make a request like this:-->\n GET /users/1/?include[]=groups.*&exclude[]=groups.location&exclude[]=location\n<--\n 200 OK\n {\n \"user\": {\n \"id\": 1,\n \"name\": \"John\",\n \"groups\": [1, 2],\n \"links\": {\n \"location\": \"/users/1/location\"\n }\n },\n \"groups\": [{\n \"id\": 1,\n \"name\": \"Family\",\n \"links\": {\n \"location\": \"/groups/1/location\"\n }\n }, {\n \"id\": 2,\n \"name\": \"Work\",\n \"links\": {\n \"location\": \"/groups/2/location\"\n }\n }]\n }exclude[]supports the wildcard value:*, which means \"don't return anything\".\nWhy is that useful?include[]overridesexclude[], soexclude[]=*can be combined withinclude[]to return only a single value or set of values from a resource.For example, to obtain only the user's name:-->\n GET /users/1/?exclude[]=*&include[]=name\n<--\n 200 OK\n {\n \"user\": {\n \"name\": \"John\",\n \"links\": {\n \"location\": \"/users/1/location\",\n \"groups\": \"/users/1/groups\"\n }\n }\n }Note thatlinkswill always be returned for relationships that are deferred.FilteringTired of writing custom filters for all of your fields? DREST has your back with thefilter{}feature.You can filter a user by his name (exact match):-->\n GET /users/?filter{name}=John\n<--\n 200 OK\n ...... or a partial match:--> \n GET /users/?filter{name.icontains}=jo\n<--\n 200 OK\n ...... or one of several names:-->\n GET /users/?filter{name.in}=John&filter{name.in}=Joe\n<--\n 200 OK... or a relationship ID:-->\n GET /users/?filter{groups}=1\n<--\n 200 OK... or lack thereof:-->\n GET /users/?filter{-groups}=1\n<--\n 200 OK... or a relationship field:-->\n GET /users/?filter{groups.name}=Home\n<--\n 200 OK... or multiple criteria:-->\n GET /users/?filter{groups.name}=Home&filter{name}=John\n<--\n 200 OK... or combine it withinclude[]to filter the sideloaded data (get all the users and only sideload certain groups):-->\n GET /users/?include[]=groups.*&filter{groups|name.icontains}=h\n<--\n 200 OKThe sky is the limit! DREST supports just about every basic filtering scenario and operator that you can use in Django:inicontainsistartswithrangeltgt\n...See thefull list here.OrderingYou can use thesort[]feature to order your response by one or more fields. Dot notation is supported for sorting by nested properties:-->\n GET /users/?sort[]=name&sort[]=groups.name\n<--\n 200 OK\n ...For descending order, simply add a-sign. To sort by name in descending order for example-->\n GET /users/?sort[]=-name\n<--\n 200 OK\n ...Directory panelWe love the DRF browsable API, but wish that it included a directory that would let you see your entire list of endpoints at a glance from any page.\nDREST adds that in:OptimizationsSupporting nested sideloading and filtering is expensive and can lead to very poor query performance if implemented naively.\nDREST uses Django'sPrefetchobject to prevent N+1 query situations and guarantee that your API is performant.\nWe also optimize the serializer layer to ensure that the conversion of model objects into JSON is as fast as possible.How fast is it? Here are somebenchmarksthat compare DREST response time to DRF response time. DREST out-performs DRF on every benchmark:Linear benchmark: rendering a flat listQuadratic benchmark: rendering a list of listsCubic benchmark: rendering a list of lists of listsSettingsDREST is configurable, and all settings should be nested under a single block in yoursettings.pyfile.\nHere are ourdefaults:xtrm_drest={# DEBUG: enable/disable internal debugging'DEBUG':False,# ENABLE_BROWSABLE_API: enable/disable the browsable API.# It can be useful to disable it in production.'ENABLE_BROWSABLE_API':True,# ENABLE_LINKS: enable/disable relationship links'ENABLE_LINKS':True,# ENABLE_SERIALIZER_CACHE: enable/disable caching of related serializers'ENABLE_SERIALIZER_CACHE':True,# ENABLE_SERIALIZER_OPTIMIZATIONS: enable/disable representation speedups'ENABLE_SERIALIZER_OPTIMIZATIONS':True,# DEFER_MANY_RELATIONS: automatically defer many-relations, unless# `deferred=False` is explicitly set on the field.'DEFER_MANY_RELATIONS':False,# MAX_PAGE_SIZE: global setting for max page size.# Can be overriden at the viewset level.'MAX_PAGE_SIZE':None,# PAGE_QUERY_PARAM: global setting for the pagination query parameter.# Can be overriden at the viewset level.'PAGE_QUERY_PARAM':'page',# PAGE_SIZE: global setting for page size.# Can be overriden at the viewset level.'PAGE_SIZE':None,# PAGE_SIZE_QUERY_PARAM: global setting for the page size query parameter.# Can be overriden at the viewset level.'PAGE_SIZE_QUERY_PARAM':'per_page',# ADDITIONAL_PRIMARY_RESOURCE_PREFIX: String to prefix additional# instances of the primary resource when sideloading.'ADDITIONAL_PRIMARY_RESOURCE_PREFIX':'+',# Enables host-relative links. Only compatible with resources registered# through the dynamic router. If a resource doesn't have a canonical# path registered, links will default back to being resource-relative urls'ENABLE_HOST_RELATIVE_LINKS':True}Compatibility tableNot all versions of Python, Django, and DRF are compatible. Here are the combinations you can use reliably with DREST (all tested by our tox configuration):PythonDjangoDRFOK2.71.83.1YES2.71.83.2YES2.71.83.3YES2.71.83.4YES2.71.93.1NO12.71.93.2YES2.71.93.3YES2.71.93.4YES2.71.103.2NO32.71.103.3NO32.71.103.4YES2.71.103.5YES2.71.103.6YES2.71.113.4YES2.71.113.5YES2.71.113.6YES3.31.83.1YES3.31.83.2YES3.31.83.3YES3.31.83.4YES3.31.9x.xNO23.31.10x.xNO43.31.11x.xNO53.41.83.1YES3.41.83.2YES3.41.83.3YES3.41.83.4YES3.41.93.1NO13.41.93.2YES3.41.93.3YES3.41.93.4YES3.41.103.2NO33.41.103.3NO33.41.103.4YES3.41.103.5YES3.41.103.6YES3.41.113.3NO33.41.113.4YES3.41.113.5YES3.51.83.1YES3.51.83.2YES3.51.83.3YES3.51.83.4YES3.51.93.1NO13.51.93.2YES3.51.93.3YES3.51.93.4YES3.51.103.2NO33.51.103.3NO33.51.103.4YES3.51.103.5YES3.51.103.6YES3.51.113.4YES3.51.113.5YES3.51.113.6YES1: Django 1.9 is not compatible with DRF 3.12: Django 1.9 is not compatible with Python 3.33: Django 1.10 is only compatible with DRF 3.4+4: Django 1.10 requires Python 2.7, 3.4, 3.55: Django 1.11 requires Python 2.7, 3.4, 3.5, 3.6ContributingSeeContributing.LicenseSeeLicense.#CreditsThis is a fork from AltSchool\nDRF 3.8 fixes was implemented by jgissend10drf-writable-nested-\nThe writable nested part was from drf-writable-nested implemented\nby beda-software"} +{"package": "xtrmth", "pacakge-description": "# XTRMTHAll your math.\n####One Library.All you functions.\n####One Import.## The days of endlessly searching through documentation are over.\nXTRMTH uses easy-to-understand syntax, and won\u2019t force memorization of every edge-case.## No more strange, inadequate errors.\nAll edge-cases* have a detailed, concice, error message. More broad errors will use formatted strings to show exactly where and how you messed up.{Documentation to be added in version 2.0.0, along with xtrmth variables (xmv.py).}*personally found or reported"} +{"package": "xtrude", "pacakge-description": "An xarray extension for 3D terrain visualization"} +{"package": "xtsautorun", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xtsjspider", "pacakge-description": "No description available on PyPI."} +{"package": "xtssort", "pacakge-description": "xtssortThis is the ten method of list sorting.installpip install xtssortfromxtssortimport*# Bubble_sortingBubble_sorting(lt=list,Positive_or_reverse_order=2or1)# selectionSortselectionSort(arr=list)# insertionSortinsertionSort(arr=list)# shellSortshellSort(arr=list)# mergeSortmergeSort(arr=list)# quickSortquickSort(arr=list,left=,right=)# heapSortheapSort(arr=list)# countingSortcountingSort(arr=list,maxValue=)# bucket_sortbucket_sort(arr=list,max_num=)# radix_sortradix_sort(data=list)"} +{"package": "xt-st-common", "pacakge-description": "XT-STREAMLIT - 1.1.1This repo contains all of the common Streamlit code used by the Exploration Toolkit and CMR's Discovery Program.xt-st-common- Common Framework for XT's Streamlit appsGetting Started UserTODO: Installation guide and pointer to API docsGetting Started DeveloperTODO: Poetry primerThis project recommends usingpoethepoetas a tool for running tasks. Seepypoetry.tomlIn your base python environmentpipinstallpipx# Pipx is a tool for installing python tools globallypipxinstallpoethepoet# Installs poe as a global toolpoe--help# Will show all the available tasks defined for this project"} +{"package": "xtsv", "pacakge-description": "xtsv \u2013 A generic TSV-style format based intermodular communication framework and REST API implemented in Pythoninter-module communication via a TSV-style formatprocessing can be started or stopped at any modulemodule dependency checks before processingeasy to add new modulesmultiple alternative modules for some taskseasy to use command-line interfaceconvenient REST API with simple web frontendPython library APICan be turned into a docker image and runnable docker formIf a bug is found please leave feedback with the exact details.Citing and Licensextsvis licensed under the LGPL 3.0 license. The submodules have their\nown license.If you use this library, please cite the following paper:Indig, Bal\u00e1zs, B\u00e1lint Sass, and Iv\u00e1n Mittelholcz. \"The xtsv Framework and the Twelve Virtues of Pipelines.\" Proceedings of The 12th Language Resources and Evaluation Conference. 2020.@inproceedings{indig-etal-2020-xtsv,\n title = \"The xtsv Framework and the Twelve Virtues of Pipelines\",\n author = \"Indig, Bal{\\'a}zs and\n Sass, B{\\'a}lint and\n Mittelholcz, Iv{\\'a}n\",\n booktitle = \"Proceedings of The 12th Language Resources and Evaluation Conference\",\n month = may,\n year = \"2020\",\n address = \"Marseille, France\",\n publisher = \"European Language Resources Association\",\n url = \"https://www.aclweb.org/anthology/2020.lrec-1.871\",\n pages = \"7044--7052\",\n abstract = \"We present xtsv, an abstract framework for building NLP pipelines. It covers several kinds of functionalities which can be implemented at an abstract level. We survey these features and argue that all are desired in a modern pipeline. The framework has a simple yet powerful internal communication format which is essentially tsv (tab separated values) with header plus some additional features. We put emphasis on the capabilities of the presented framework, for example its ability to allow new modules to be easily integrated or replaced, or the variety of its usage options. When a module is put into xtsv, all functionalities of the system are immediately available for that module, and the module can be be a part of an xtsv pipeline. The design also allows convenient investigation and manual correction of the data flow from one module to another. We demonstrate the power of our framework with a successful application: a concrete NLP pipeline for Hungarian called e-magyar text processing system (emtsv) which integrates Hungarian NLP tools in xtsv. All the advantages of the pipeline come from the inherent properties of the xtsv framework.\",\n language = \"English\",\n ISBN = \"979-10-95546-34-4\",\n}RequirementsPython 3.5 <=[Optional, if required by any module] PyJNIus and OpenJDK 11 JDKAPI documentationModuleError: The exception thrown when something bad happened to the\nmodules (e.g. the module could not be found or the ordering of the modules is\nnot feasible because of the required and supplied fields)HeaderError: The exception thrown when the input could not satisfy the\nrequired fields in its headerjnius_config: Set JAVA VM options and CLASSPATH for thePyJNIus librarybuild_pipeline(inp_data, used_tools, available_tools, presets, conll_comments=False) -> iterator_on_output_lines:\nBuild the current pipeline from the input data (stream, iterable or string),\nthe list of the elements of the desired pipeline chosen from the available\ntools and presets returning an output iteratorpipeline_rest_api(name, available_tools, presets, conll_comments, singleton_store=None, form_title, doc_link) -> app:\nCreate a Flask application with the REST API and web frontend on the\navailable initialised tools and presets with the desired name. Run with a\nwsgi server or Flask's built-in server with withapp.run()(seeREST API\nsection)singleton_store_factory() -> singleton: Singletons can be used for\ninitialisation of modules (eg. when the application is restarted frequently\nand not all modules are used between restarts)process(stream, initialised_app, conll_comments=False) -> iterator_on_output_lines:\nA low-level API to run a specific member of the pipeline on a specific\ninput stream, returning an output iteratorparser_skeleton(...) -> argparse.ArgumentParser(...): A CLI argument\nparser skeleton can be further customized when neededadd_bool_arg(parser, name, help_text, default=False, has_negative_variant=True):\nA helper function to easily add BOOL arguments to the ArgumentParser classTo be defined by the actual pipeline:tools: The list of tools (seeconfigurationfor details)presets: The dictionary of shorthands for tasks which are defined as list\nof tools to be run in a pipeline (seeconfigurationfor details)Data formatThe input and output can be one of the following:Free form text fileTSV file with fixed column order and without header (like CoNLL-U)TSV file with arbitrary column order where the columns are identified by\nthe TSV header (main format ofxtsv)The TSV files are formatted as follows (closely resembling the CoNLL-U,\nvertical format):The first line is theheader(when the column order is not fixed,\ntherefore the next module identifies columns by their names)Columns are separated by TAB charactersOne token per line (one column), the other columns contain the information\n(stem, POS-tag, etc.) of that individual tokenSentences are separated by emtpy linesIf allowed by settings, zero or more comment lines (e.g. lines starting\nwith hashtag and space) immediately precede the sentencesThe fields (represented by TSV columns) are identified by the header in the\nfirst line of the input. Each module can (but does not necessarily have to)\ndefine:A set of source fields which is required to present in the inputA list of target fields which are to be generated to the output in orderNewly generated fields are started from the right of the rightmost\ncolumn, the existing columnsshouldnot be modified at allThe following types of modules can be defined by their input and output\nformat requirements:Tokeniser: No source fields, no header, has target fields, free-format\ntext as input, TSV+header outputInternal module: Has source fields, has header, has target fields,\nTSV+header input, TSV+header outputFinalizer: Has source fields, no header, no target fields, TSV+header\ninput, free-format text as outputFixed-order TSV importer: No source fields, no header, has target\nfields, Fixed-order TSV w/o header as input, TSV+header outputFixed-order TSV processor: No source fields, no header, no target\nfields, Fixed-order TSV w/o header as input, Fixed-order TSV w/o header as\noutputCreating a module that can be used withxtsvWe strive to be a welcoming open source community.\nIn agreement with the license, everybody is free to create a new compatible module without asking for permission.The following requirements apply for a new module:It must provide (at least) the mandatory API (seeemDummyfor a well-documented\nexample)It must conform to the (to be defined) field-name conventions and the\nformat conventionsIt must have an LGPL 3.0 compatible license\n(as all modules communicate through the thin xtsv API, there is no restriction or obligation to commit for the module license.This is not legal advice!)The following technical steps are needed to insert the new module into the pipeline:Add the new module package as a requirement to the requirements.txt of the pipeline's main repository (e.g.emtsv)Insert the configuration inconfig.py:# Setup the tuple:# module name,# class,# friendly name,# args (tuple),# kwargs (dict)em_dummy=('emdummy','EmDummy','EXAMPLE (The friendly name of DummyTagger used in REST API form)',('Params','goes','here'),{'source_fields':{'Source field names'},'target_fields':['Target field names'],'other':'kwargs as needed',})Add the new module totoolslist inconfig.py, optionally also topresetsdictionarytools=[...,(em_dummy,('dummy-tagger','emDummy')),]Update README.md with the short description of the newly added module and add neccessary documentaion (e.g. extra installation instructions)Test, commit and push (create a pull request if you want to include your module in other's pipeline)InstallationCan be installed as pip package:pip3 install xtsvOr by using the git repository as submodule for another git repositoryUsageHere we present the usage scenarios.To extend the toolchain with new modules,just add new modules toconfig.py.Some examples of the realised applications:emtsvemmorphpyHunTag3Command-line interfaceMultiple modules at once (not necessarily starting with raw text):echo\"Input text.\"|python3./main.pymodules,separated,by,comasModulesglued togetherone by one with thestandard *nix pipelineswhere users can interact with the databetween the modules:echo\"Input text.\"|\\python3main.pymodule|\\python3main.pyseparated|\\python3main.pyby|\\python3main.pycomasIndependently from the other options,xtsvcan also be used with input or\noutput streams redirected or with string input (this applies to the runnable\ndocker form as well):python3./main.pymodules,separated,by,comas-iinput.txt-ooutput.txt\npython3./main.pymodules,separated,by,comas--text\"Input text.\"Docker imageWith the appropriate Dockerfilextsvcan be used as follows:Runnable docker form (CLI usage of docker image):catinput.txt|dockerrun-ixtsv-dockertask,separated,by,comas>output.txtAs service through Rest API (docker container)dockerrun--rm-p5000:5000-itxtsv-docker# REST API listening on http://0.0.0.0:5000REST APIServer:Docker image (see above)Any wsgi server (uwsgi,gunicorn,waitress, etc.) can be configured\nto run with a prepared wsgi file .Debug server (Flask)only for development (single threaded, one request\nat a time):When the server outputs a message like* Running onthen it is ready to\naccept requests onhttp://127.0.0.1:5000. (We do not recommend using\nthis method in production as it is built atop of Flask debug server! Please\nconsider using the Docker image for REST API in production!)Any wsgi server (uwsgi,gunicorn,waitress, etc.) can be configured\nto run with a prepared wsgi file .Docker image (see above)Client:Web fronted provided byxtsvFrom Python (the URL contains the tools to be run separated by/):>>>importrequests>>># With input file>>>r=requests.post('http://127.0.0.1:5000/tools/separated/by/slashes',files={'file':open('input.file',encoding='UTF-8')})>>>print(r.text)...>>># With input text>>>r=requests.post('http://127.0.0.1:5000/tools/separated/by/slashes',data={'text':'Input text.'})>>>print(r.text)...>>># CoNLL style comments can be enabled per request (disabled by default):>>>r=requests.post('http://127.0.0.1:5000/tools/separated/by/slashes',files={'file':open('input.file',encoding='UTF-8')},data={'conll_comments':True})>>>print(r.text)...The server checks whether the module order is feasible, and returns an\nerror message if there are any problems.As Python LibraryInstall xtsv package or make sure the main pipeline's installation is in thePYTHONPATHenvironment variable.import xtsvExample:importsysfromxtsvimportbuild_pipeline,parser_skeleton,jnius_config,process,pipeline_rest_api,singleton_store_factory# Imports end here. Must do only once per Python sessionargparser=parser_skeleton(description='An example pipeline for xtsv')opts=argparser.parse_args()jnius_config.classpath_show_warning=opts.verbose# False to suppress warning# Set input from any stream, iterator or raw string in any acceptable formatifopts.input_textisnotNone:# Raw, or processed TSV input list and output file...# input_data = ['A kutya', 'elment s\u00e9t\u00e1lni.'] # Raw text line by line# Processed data: header and the token POS-tag pairs line by line# input_data = [['form', 'xpostag'], ['A', '[/Det|Art.Def]'], ['kutya', '[/N][Nom]'], ['elment', '[/V][Pst.NDef.3Sg]'], ['s\u00e9t\u00e1lni', '[/V][Inf]'], ['.', '.']]input_data=opts.input_textelse:# Set input from any stream or iterable and output stream...input_data=opts.input_stream# Set output iterator: e.g. output_iterator = open('output.txt', 'w', encoding='UTF-8') # Fileoutput_iterator=opts.output_stream# Select a predefined task to do or provide your own list of pipeline elements# i.e. set the tagger name as in the _tools dictionary in the config.py_ e.g. used_tools = ['dummy']used_tools=['tools','in','a','list']presets=[]# The relevant part of config.py# from emdummy import EmDummyem_dummy=('emdummy','EmDummy','EXAMPLE (The friendly name of EmDummy used in REST API form)',('Params','goes','here'),{'source_fields':{'form'},# Source field names'target_fields':{'star'}})# Target field namestools=[(em_dummy,('dummy','dummy-tagger','emDummy'))]# Run the pipeline on input and write result to the output...# You can enable or disable CoNLL-U style comments here (default: disabled)output_iterator.writelines(build_pipeline(input_data,used_tools,tools,presets,opts.conllu_comments,opts.output_header))# Alternative: Run specific tool for input streams (still in emtsv format).# Useful for training a module (see Huntag3 for details):# e.g. output_iterator.writelines(process(input_data, EmDummy(*em_dummy[3], **em_dummy[4])))output_iterator.writelines(process(sys.stdin,Module('with','params')))# Or process individual tokens further... WARNING: The header will be the# first item in the iterator!fortokinbuild_pipeline(input_data,used_tools,tools,presets,opts.conllu_comments,opts.output_header):iflen(tok)>1:# Empty line (='\\n') means end of sentenceform,xpostag,*rest=tok.strip().split('\\t')# Split to the expected columns# Alternative2: Run REST API debug serverapp=pipeline_rest_api(name='TEST',available_tools=tools,presets=presets,conll_comments=opts.conllu_comments,singleton_store=singleton_store_factory(),form_title='TEST TITLE',doc_link='https://github.com/dlt-rilmta/xtsv',output_header=opts.output_header)# And run the Flask debug server separatelyapp.run()"} +{"package": "xtsv-word", "pacakge-description": "xtsv-wordThis module provides a special dataclass-like structure to handle tokens inxtsvformat. It is meant to be used withinxtsvmodules to make the processing of token attributes (xtsvfields) more comfortable and transparent.It allows for each token to be represented by aWordobject which is initialised simply by passing the token in itsxtsvrepresentation (i.e. a list of strings, one for each field in the input stream) to aWordFactoryobject. This factory object keeps track of the input and target fields of thextsvmodule, and assigns the items of the list representing the token inxtsvto the respectiveWordobject attributes which are identified by the name of the corresponding field (i.e. thextsvcolumn header).Both the input and the target fields can be accessed as attributes of aWordobject, i.e. they can be both retrieved and modified. (The usual use case is to only read input field attributes and to specify target field attributes. However, theWordobject does not prevent a user from modifying input field values. This is discouraged but not ruled out byxtsv.) When thextsvmodule is done processing a token, theWordobject is simply converted into a list which contains the original input fields followed by the target fields, as expected byxtsv.Disclaimer: This is not an official extension of thextsvmodule.Suggested usageInstallxtsv-wordfrompip:python3 -m pip install xtsv-wordor build locally:makeFor example, assuming that the internal app object defined in thextsvmodulemyXtsvModuleis calledInternalApp, the input stream contains the fields['form', 'wsafter']andmyXtsvModulehas a single target field:['syllables']:CreateWordFactoryobject:# myXtsvModule.py\n\nfrom xtsv_word import WordFactory\n\nclass InternalApp:\n\t...\n\tdef prepare_fields(self, field_names):\n\t\tself.wf = WordFactory(field_names, self.target_fields)\n\t\t# self.target_fields is normally set in InternalApp.__init__()UseWordobject:class InternalApp:\n\t...\n\tdef process_sentence(self, sen, field_values):\n\t\treturn_sen = []\n\t\tfor tok in sen:\n\t\t\t# Get Word object from factory\n\t\t\tword = self.wf.get_word(tok)\n\n\t\t\t# process token by getting and setting its attributes, e.g.:\n\t\t\tword.syllables = split_syllables(word.form)\n\t\t\t...\n\t\t\t# alternatively access attributes as dict keys:\n\t\t\tword['syllables'] = '-'.join(word['syllables'])\n\n\t\t\t# convert Word object to list of fields for xtsv output stream\n\t\t\treturn_sen.append(list(word))\n\n\t\t...\n\t\treturn return_senSee docstrings for further details."} +{"package": "xtt", "pacakge-description": "# xtt-python[![PyPI version](https://badge.fury.io/py/xtt.svg)](https://badge.fury.io/py/xtt)[![Build Status](https://travis-ci.org/xaptum/xtt-python.svg?branch=master)](https://travis-ci.org/xaptum/xtt-python)A Python module (`xtt`) that encapsulates the [XTT TrustedTransit](https://github.com/xaptum/xtt) protocol for securing Internetof Things (IoT) devices.## Installation``` bashpip install xtt```The package is published to PyPI for Python 2.7 and 3.3+ for Linux andOS X. `pip` installs all dependencies, including `xtt` itself.## Quick-Start``` pythonimport socketimport xtt# In these examples, we assume the id, certs, and keys needed to run# an XTT client handshake are available as files.# Load root certificate, used to authenticate the serverroot_id = xtt.CertificateRootId.from_file(\"root_id.bin\")root_pubkey = xtt.ED25519PublicKey.from_file(\"root_pub.bin\")# Load the server idserver_id = xtt.Identity.from_file(\"server_id.bin\")# Load the DAA group informationgroup_basename = b'BASENAME'group_gpk = xtt.LRSWGroupPublicKey.from_file(\"daa_gpk.bin\")group_id = xtt.GroupId(hashlib.sha256(group_gpk.data).digest())group_cred = xtt.LRSWCredential.from_file(\"daa_cred.bin\")group_secretkey = xtt.LRSWPrivateKey.from_file(\"daa_secretkey.bin\")group_ctx = xtt.ClientLRSWGroupContext(group_id, group_secretkey,group_cred, group_basename)sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM, 0)sock.connect(('192.0.2.1', 4443))xtt_sock = xtt.XTTClientSocket(sock,version = xtt.Version.ONE,suite_spec = xtt.SuiteSpec.XTT_X25519_LRSW_ED25519_CHACHA20POLY1305_SHA512,group_ctx, server_id, root_id, root_pubkey)xtt_sock.start()my_identity = xtt_sock.identitymy_public_key = xtt_sock.longterm_public_keymy_private_key = xtt_sock.longterm_private_key```## ContributingPlease submit bugs, questions, suggestions, or (ideally) contributionsas issues and pull requests on GitHub.## LicenseCopyright 2018 Xaptum, Inc.Licensed under the Apache License, Version 2.0 (the \"License\"); you may notuse this work except in compliance with the License. You may obtain a copy ofthe License from the LICENSE.txt file or at[http://www.apache.org/licenses/LICENSE-2.0](http://www.apache.org/licenses/LICENSE-2.0)Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an \"AS IS\" BASIS, WITHOUTWARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See theLicense for the specific language governing permissions and limitations underthe License."} +{"package": "xt-TimeUtils", "pacakge-description": "This is a tool for processing time.InstallationIt is possible to install the tool with pip:pip install xt-TimeUtilsFeatureTime processing module based ondatetimeandarrowConfigurationThe script itself is currently configuration free.DependenciesarrowdatetimeUsageSample usage:fromxtdate_utils.xtdate_utilsimportTimeUtilsstr_to_datetime=TimeUtils.str_to_datetime('2021-01-01','%Y-%m-%d')ChangesVersion 0.1.3Add two new interfaces(get_after_day,get_before_day)Version 0.1.4Fix the error of importerrorVersion 0.2.0 2021-02-24Fix the error of 'get_last_cycle_list' interfaceInterface 'get_last_cycle_list' add configuration itemis_process, It is used to control the time period. The default time period is the(week + 1)parameter.Version 0.2.1 2021-04-06Initial versionAddIterCycleGearClass, it supports cycle configurable. Three configuration options have been added:day\u3001week\u3001iter.Addupdate_iteration_periodto update_iteration_periodparameter.LicenseThe script is released under the MIT License.The MIT License is registered with and approved by the Open Source Initiative."} +{"package": "xt-training", "pacakge-description": "xt-trainingDescriptionThis repo contains utilities for training deep learning models in pytorch, developed byXtract AI.InstallationFrom PyPI:pipinstallxt-trainingFrom source:gitclonehttps://github.com/XtractTech/xt-training.git\npipinstall./xt-trainingUsageSee specific help on a class or function usinghelp. E.g.,help(Runner).Training a modelUsing xt-training (High Level)First, you must define a config file with the necessary items.\nTo generate a template config file, run:python-mxt_trainingtemplatepath/to/save/dirTo generate template files for nni, add the--nniflagInstructions for defining a valid config file can be seen at the top of the config file.After defining a valid config file, you can train your model by running:python-mxt_trainingtrainpath/to/config.py/path/to/save_dirYou can test the model by runningpython-mxt_trainingtestpath/to/config.py/path/to/save_dirUsing functional train (Middle Level)As of version >=2.0.0, xt-training has functional calls for the train and test functions\nThis is useful if you want to run other code after training, or want any values/metrics returned after training.\nThis can be called like so:fromxt_training.utilsimportfunctional# model =# train_loader =# optimizer =# scheduler =# loss_fn =# metrics =# epochs =# save_dir =defon_exit(test_loaders,runner,save_dir,model):# Do what you want after training.# As of version >=2.0.0. whatever gets returned here will get returned from the functional callreturnrunner,modelrunner,model=functional.train(save_dir,train_loader,model,optimizer,epochs,loss_fn,val_loader=None,test_loaders=None,scheduler=scheduler,is_batch_scheduler=False,# Whether or not to run scheduler.step() every epoch or every stepeval_metrics=metrics,tokenizer=None,on_exit=train_exit,use_nni=False)# Do something after with runner and/or model...A similar functional call exists for test.Using Runner (Low Level)If you want a little more control and want to define the trianing code yourself, you can utilize the Runner like so:fromxt_trainingimportRunner,metricsfromtorch.utils.tensorboardimportSummaryWriter# Here, define class instances for the required objects# model =# optimizer =# scheduler =# loss_fn =# Define metrics - each of these will be printed for each iteration# Either per-batch or running-average values can be printedbatch_metrics={'eps':metrics.EPS(),'acc':metrics.Accuracy(),'kappa':metrics.Kappa(),'cm':metrics.ConfusionMatrix()}# Define tensorboard writerwriter=SummaryWriter()# Create runnerrunner=Runner(model=model,loss_fn=loss_fn,optimizer=optimizer,scheduler=scheduler,batch_metrics=batch_metrics,device='cuda:0',writer=writer)# Define dataset and loaders# dataset =# train_loader =# val_loader =# Trainmodel.train()runner(train_loader)batch_metrics['cm'].print()# Evaluatemodel.eval()runner(val_loader)batch_metrics['cm'].print()# Print training and evaluation historyprint(runner)Scoring a modelimporttorchfromxt_trainingimportRunner# Here, define the model# model =# model.load_state_dict(torch.load(<checkpoint file>))# Create runner# (alternatively, can use a fully-specified training runner as in the example above)runner=Runner(model=model,device='cuda:0')# Define dataset and loaders# dataset =# test_loader =# Scoremodel.eval()y_pred,y=runner(test_loader,return_preds=True)"} +{"package": "xtts-api-server", "pacakge-description": "A simple FastAPI Server to run XTTSv2This project is inspired bysilero-api-serverand utilizesXTTSv2.This server was created forSillyTavernbut you can use it for your needsFeel free to make PRs or use the code for your own needsThere's agoogle collab versionyou can use it if your computer is weak.If you want to get a high-quality voice clone, I advise you to usewebui for fine-tuning xttsIf you are looking for an option for normal XTTS use look herehttps://github.com/daswer123/xtts-webuiChangelogYou can keep track of all changes on therelease pageTODOMake it possible to change generation parameters through the generation request and through a different endpointInstallationSimple installation :pipinstallxtts-api-serverThis will install all the necessary dependencies, including aCPU support onlyversion of PyTorchI recommend that you install theGPU versionto improve processing speed ( up to 3 times faster )Windowspython-mvenvvenv\nvenv\\Scripts\\activate\npipinstallxtts-api-server\npipinstalltorch==2.1.1+cu118torchaudio==2.1.1+cu118--index-urlhttps://download.pytorch.org/whl/cu118Linuxpython-mvenvvenvsourcevenv\\bin\\activate\npipinstallxtts-api-server\npipinstalltorch==2.1.1+cu118torchaudio==2.1.1+cu118--index-urlhttps://download.pytorch.org/whl/cu118Manual# Clone REPOgitclonehttps://github.com/daswer123/xtts-api-servercdxtts-api-server# Create virtual envpython-mvenvvenv\nvenv/scripts/activateorsourcevenv/bin/activate# Install depspipinstall-rrequirements.txt\npipinstalltorch==2.1.1+cu118torchaudio==2.1.1+cu118--index-urlhttps://download.pytorch.org/whl/cu118# Launch serverpython-mxtts_api_serverUse Docker image with Docker ComposeA Dockerfile is provided to build a Docker image, and a docker-compose.yml file is provided to run the server with Docker Compose as a service.You can build the image with the following command:mkdirxtts-api-servercdxtts-api-server\ndockerrun-ddaswer123/xtts-api-serverORcddocker\ndockercomposebuildThen you can run the server with the following command:dockercomposeup# or with -d to run in backgroundStarting Serverpython -m xtts_api_serverwill run on default ip and port (localhost:8020)Use the--deepspeedflag to process the result fast ( 2-3x acceleration )usage: xtts_api_server [-h] [-hs HOST] [-p PORT] [-sf SPEAKER_FOLDER] [-o OUTPUT] [-t TUNNEL_URL] [-ms MODEL_SOURCE] [--listen] [--use-cache] [--lowvram] [--deepspeed] [--streaming-mode] [--stream-play-sync]\n\nRun XTTSv2 within a FastAPI application\n\noptions:\n -h, --help show this help message and exit\n -hs HOST, --host HOST\n -p PORT, --port PORT\n -d DEVICE, --device DEVICE `cpu` or `cuda`, you can specify which video card to use, for example, `cuda:0`\n -sf SPEAKER_FOLDER, --speaker-folder The folder where you get the samples for tts\n -o OUTPUT, --output Output folder\n -mf MODELS_FOLDERS, --model-folder Folder where models for XTTS will be stored, finetuned models should be stored in this folder\n -t TUNNEL_URL, --tunnel URL of tunnel used (e.g: ngrok, localtunnel)\n -ms MODEL_SOURCE, --model-source [\"api\",\"apiManual\",\"local\"]\n -v MODEL_VERSION, --version You can download the official model or your own model, official version you can find [here](https://huggingface.co/coqui/XTTS-v2/tree/main) the model version name is the same as the branch name [v2.0.2,v2.0.3, main] etc. Or you can load your model, just put model in models folder\n --listen Allows the server to be used outside the local computer, similar to -hs 0.0.0.0\n --use-cache Enables caching of results, your results will be saved and if there will be a repeated request, you will get a file instead of generation\n --lowvram The mode in which the model will be stored in RAM and when the processing will move to VRAM, the difference in speed is small\n --deepspeed allows you to speed up processing by several times, automatically downloads the necessary libraries\n --streaming-mode Enables streaming mode, currently has certain limitations, as described below.\n --streaming-mode-improve Enables streaming mode, includes an improved streaming mode that consumes 2gb more VRAM and uses a better tokenizer and more context.\n --stream-play-sync Additional flag for streaming mod that allows you to play all audio one at a time without interruptionYou can specify the path to the file as text, then the path counts and the file will be voicedYou can load your own model, for this you need to create a folder in models and load the model with configs, note in the folder should be 3 filesconfig.jsonvocab.jsonmodel.pthIf you want your host to listen, use -hs 0.0.0.0 or use --listenThe -t or --tunnel flag is needed so that when you get speakers via get you get the correct link to hear the preview. More infohereModel-source defines in which format you want to use xtts:local- loads version 2.0.2 by default, but you can specify the version via the -v flag, model saves into the models folder and usesXttsConfigandinference.apiManual- loads version 2.0.2 by default, but you can specify the version via the -v flag, model saves into the models folder and uses thetts_to_filefunction from the TTS apiapi- will load the latest version of the model. The -v flag won't work.All versions of the XTTSv2 model can be foundherethe model version name is the same as the branch name [v2.0.2,v2.0.3, main] etc.The first time you run or generate, you may need to confirm that you agree to use XTTS.About Streaming modeStreaming mode allows you to get audio and play it back almost immediately. However, it has a number of limitations.You can see how this mode workshereandhereNow, about the limitationsCan only be used on a local computerPlaying audio from the your pcDoes not work endpointtts_to_fileonlytts_to_audioand it returns 1 second of silence.You can specify the version of the XTTS model by using the-vflag.Improved streaming mode is suitable for complex languages such as Chinese, Japanese, Hindi or if you want the language engine to take more information into account when processing speech.--stream-play-syncflag - Allows you to play all messages in queue order, useful if you use group chats. In SillyTavern you need to turn off streaming to work correctlyAPI DocsAPI Docs can be accessed fromhttp://localhost:8020/docsHow to add speakerBy default thespeakersfolder should appear in the folder, you need to put there the wav file with the voice sample, you can also create a folder and put there several voice samples, this will give more accurate resultsSelecting FolderYou can change the folders for speakers and the folder for output via the API.Note on creating samples for quality voice cloningThe following post is a quote by userMaterial1276 from redditSome suggestions on making good samplesKeep them about 7-9 seconds long. Longer isn't necessarily better.Make sure the audio is down sampled to a Mono, 22050Hz 16 Bit wav file. You will slow down processing by a large % and it seems cause poor quality results otherwise (based on a few tests). 24000Hz is the quality it outputs at anyway!Using the latest version of Audacity, select your clip and Tracks > Resample to 22050Hz, then Tracks > Mix > Stereo to Mono. and then File > Export Audio, saving it as a WAV of 22050HzIf you need to do any audio cleaning, do it before you compress it down to the above settings (Mono, 22050Hz, 16 Bit).Ensure the clip you use doesn't have background noises or music on e.g. lots of movies have quiet music when many of the actors are talking. Bad quality audio will have hiss that needs clearing up. The AI will pick this up, even if we don't, and to some degree, use it in the simulated voice to some extent, so clean audio is key!Try make your clip one of nice flowing speech, like the included example files. No big pauses, gaps or other sounds. Preferably one that the person you are trying to copy will show a little vocal range. Example files are inhereMake sure the clip doesn't start or end with breathy sounds (breathing in/out etc).Using AI generated audio clips may introduce unwanted sounds as its already a copy/simulation of a voice, though, this would need testing.CreditThanks to the authorKolja Beigelfor the repositoryRealtimeTTS, I took some of its code for my project.Thankserew123for the note about creating samples and the code to download the modelsThankslendotfor helping to fix the multiprocessing bug and adding code to use multiple samples for speakers"} +{"package": "xtuner", "pacakge-description": "\ud83d\udc4b join us on\ud83d\udd0d Explore our models onEnglish |\u7b80\u4f53\u4e2d\u6587\ud83c\udf89 News[2024/02]SupportGemmamodels![2024/02]SupportQwen1.5models![2024/01]SupportInternLM2models! The latest VLMLLaVA-Internlm2-7B/20Bmodels are released, with impressive performance![2024/01]SupportDeepSeek-MoEmodels! 20GB GPU memory is enough for QLoRA fine-tuning, and 4x80GB for full-parameter fine-tuning. Clickherefor details![2023/12]\ud83d\udd25 Support multi-modal VLM pretraining and fine-tuning withLLaVA-v1.5architecture! Clickherefor details![2023/12]\ud83d\udd25 SupportMixtral 8x7Bmodels! Clickherefor details![2023/11]SupportChatGLM3-6Bmodel![2023/10]SupportMSAgent-Benchdataset, and the fine-tuned LLMs can be applied byLagent![2023/10]Optimize the data processing to accommodatesystemcontext. More information can be found onDocs![2023/09]SupportInternLM-20Bmodels![2023/09]SupportBaichuan2models![2023/08]XTuner is released, with multiple fine-tuned adapters onHuggingFace.\ud83d\udcd6 IntroductionXTuner is an efficient, flexible and full-featured toolkit for fine-tuning large models.EfficientSupport LLM, VLM pre-training / fine-tuning on almost all GPUs. XTuner is capable of fine-tuning 7B LLM on a single 8GB GPU, as well as multi-node fine-tuning of models exceeding 70B.Automatically dispatch high-performance operators such as FlashAttention and Triton kernels to increase training throughput.Compatible withDeepSpeed\ud83d\ude80, easily utilizing a variety of ZeRO optimization techniques.FlexibleSupport various LLMs (InternLM,Mixtral-8x7B,Llama2,ChatGLM,Qwen,Baichuan, ...).Support VLM (LLaVA). The performance ofLLaVA-InternLM2-20Bis outstanding.Well-designed data pipeline, accommodating datasets in any format, including but not limited to open-source and custom formats.Support various training algorithms (QLoRA,LoRA, full-parameter fune-tune), allowing users to choose the most suitable solution for their requirements.Full-featuredSupport continuous pre-training, instruction fine-tuning, and agent fine-tuning.Support chatting with large models with pre-defined templates.The output models can seamlessly integrate with deployment and server toolkit (LMDeploy), and large-scale evaluation toolkit (OpenCompass,VLMEvalKit).\ud83c\udf1f DemosReady-to-use models and datasets from XTuner APIQLoRA Fine-tunePlugin-based ChatExamples of Plugin-based Chat \ud83d\udd25\ud83d\udd25\ud83d\udd25\ud83d\udd25 SupportsModelsSFT DatasetsData PipelinesAlgorithmsInternLM2InternLMLlamaLlama2ChatGLM2ChatGLM3QwenBaichuanBaichuan2Mixtral 8x7BDeepSeek MoEGemma...MSAgent-BenchMOSS-003-SFT\ud83d\udd27Alpaca en/zhWizardLMoasst1Open-PlatypusCode AlpacaColorist\ud83c\udfa8Arxiv GenTitleChinese LawOpenOrcaMedical Dialogue...Incremental Pre-trainingSingle-turn Conversation SFTMulti-turn Conversation SFTQLoRALoRAFull parameter fine-tune\ud83d\udee0\ufe0f Quick StartInstallationIt is recommended to build a Python-3.10 virtual environment using condacondacreate--namextuner-envpython=3.10-y\ncondaactivatextuner-envInstall XTuner via pippipinstall-Uxtuneror with DeepSpeed integrationpipinstall-U'xtuner[deepspeed]'Install XTuner from sourcegitclonehttps://github.com/InternLM/xtuner.gitcdxtuner\npipinstall-e'.[all]'Fine-tuneXTuner supports the efficient fine-tune (e.g., QLoRA) for LLMs. Dataset prepare guides can be found ondataset_prepare.md.Step 0, prepare the config. XTuner provides many ready-to-use configs and we can view all configs byxtunerlist-cfgOr, if the provided configs cannot meet the requirements, please copy the provided config to the specified directory and make specific modifications byxtunercopy-cfg${CONFIG_NAME}${SAVE_PATH}vi${SAVE_PATH}/${CONFIG_NAME}_copy.pyStep 1, start fine-tuning.xtunertrain${CONFIG_NAME_OR_PATH}For example, we can start the QLoRA fine-tuning of InternLM2-Chat-7B with oasst1 dataset by# On a single GPUxtunertraininternlm2_chat_7b_qlora_oasst1_e3--deepspeeddeepspeed_zero2# On multiple GPUs(DIST)NPROC_PER_NODE=${GPU_NUM}xtunertraininternlm2_chat_7b_qlora_oasst1_e3--deepspeeddeepspeed_zero2(SLURM)srun${SRUN_ARGS}xtunertraininternlm2_chat_7b_qlora_oasst1_e3--launcherslurm--deepspeeddeepspeed_zero2--deepspeedmeans usingDeepSpeed\ud83d\ude80 to optimize the training. XTuner comes with several integrated strategies including ZeRO-1, ZeRO-2, and ZeRO-3. If you wish to disable this feature, simply remove this argument.For more examples, please seefinetune.md.Step 2, convert the saved PTH model (if using DeepSpeed, it will be a directory) to HuggingFace model, byxtunerconvertpth_to_hf${CONFIG_NAME_OR_PATH}${PTH}${SAVE_PATH}ChatXTuner provides tools to chat with pretrained / fine-tuned LLMs.xtunerchat${NAME_OR_PATH_TO_LLM}--adapter{NAME_OR_PATH_TO_ADAPTER}[optionalarguments]For example, we can start the chat withInternLM2-Chat-7B with adapter trained from oasst1 dataset:xtunerchatinternlm/internlm2-chat-7b--adapterxtuner/internlm2-chat-7b-qlora-oasst1--prompt-templateinternlm2_chatLLaVA-InternLM2-7B:xtunerchatinternlm/internlm2-chat-7b--visual-encoderopenai/clip-vit-large-patch14-336--llavaxtuner/llava-internlm2-7b--prompt-templateinternlm2_chat--image$IMAGE_PATHFor more examples, please seechat.md.DeploymentStep 0, merge the HuggingFace adapter to pretrained LLM, byxtunerconvertmerge\\${NAME_OR_PATH_TO_LLM}\\${NAME_OR_PATH_TO_ADAPTER}\\${SAVE_PATH}\\--max-shard-size2GBStep 1, deploy fine-tuned LLM with any other framework, such asLMDeploy\ud83d\ude80.pipinstalllmdeploy\npython-mlmdeploy.pytorch.chat${NAME_OR_PATH_TO_LLM}\\--max_new_tokens256\\--temperture0.8\\--top_p0.95\\--seed0\ud83d\udd25 Seeking efficient inference with less GPU memory? Try 4-bit quantization fromLMDeploy! For more details, seehere.EvaluationWe recommend usingOpenCompass, a comprehensive and systematic LLM evaluation library, which currently supports 50+ datasets with about 300,000 questions.\ud83e\udd1d ContributingWe appreciate all contributions to XTuner. Please refer toCONTRIBUTING.mdfor the contributing guideline.\ud83c\udf96\ufe0f AcknowledgementLlama 2QLoRALMDeployLLaVA\ud83d\udd8a\ufe0f Citation@misc{2023xtuner,title={XTuner: A Toolkit for Efficiently Fine-tuning LLM},author={XTuner Contributors},howpublished={\\url{https://github.com/InternLM/xtuner}},year={2023}}LicenseThis project is released under theApache License 2.0. Please also adhere to the Licenses of models and datasets being used."} +{"package": "xtuning", "pacakge-description": "No description available on PyPI."} +{"package": "xtuples", "pacakge-description": "xtuplesTable of ContentsInstallationOverviewPerformanceLicenseInstallationpip install xtuplesOverviewimporttypingimportxtuplesasxtxtuples (xt) provides:#1: xt.iTuple: a bunch of (primarily) itertools / functools boilerplate, wrapped into a tuple subclass.#2: xt.nTuple.decorate: a decorator to inject .pipe(), .partial(), and a dict of any user defined methods, into a NamedTuple.iTupleThe idea with #1 is to facilitate a functional style of programming, utilising method chaining to mimic the function pipelines seen in languages like f#.For instance, a naive way to get all the squared primes under x, might be:defprimes_under(x):return(xt.iTuple.range(x).filter(lambdav:v>1).fold(lambdaprimes,v:(primes.append(v)ifnotprimes.any(lambdaprime:v%prime==0)elseprimes),initial=xt.iTuple()))sq_primes_under_10=primes_under(10).map(lambdav:v**2)iTuple has type annotations for a reasonable range of overloads of common methods, such that mypy should, without requiring explicit annotations, be able to track types through methods like zip(), map(), filter(), and so on.See ./tests/test_mypy.py for particular examples.nTupleThe idea with #2 is to ease method re-use between, and interface definitions on, NamedTuples, where rather than inheriting methods, we inject them in (on top of a type signature stub).For instance, we can share the function f between NamedTuples A and B, as so:classHas_X(typing.Protocol):x:intdeff(self:Has_X)->int:returnself.x+1@xt.nTuple.decorate(f=f)classA(typing.NamedTuple):x:inty:floatdeff(self:A)->int:...# type: ignore[empty-body]@xt.nTuple.decorate(f=f)classB(typing.NamedTuple):x:inty:floatdeff(self:B)->int:...# type: ignore[empty-body]Annoyingly, we have to set mypy to ignore the empty body, but we still get type checking on the implementation (at f).JAXWorth highlighting is the compatibility this promotes withJAX, an auto-grad / machine learning framework from the Google Brain / Deepmind folks.Because both iTuple and nTuple are kinds of tuple, JAX can take derivatives of / through without any further work (TODO: have a jax.register function on iTuple, so we don't need to call .pipe(tuple)).Furthermore, because both iTuple and nTuple are immutable, generally very little refactoring is required for an xtuples code-base to be compliant with the (somewhat opinionated) functional purity requirements of the JAX jit compiler.xt.fxtuples also exposes:#3: xt.f: a module of sister methods to those in xt.iTuple, designed to provide / be used as arguments for their bound iTuple cousins.For instance, instead of:cum_sq_primes_under_10=(iTuple.range(10).map(primes_under).map(lambdait:it.map(lambdav:v**2)))We can write:cum_sq_primes_under_10=(iTuple.range(10).map(primes_under).map(xt.f.map(lambdav:v**2)))Ie. it simply saves us from writing out quite so many lambdas.PerformancePerformance using xtuples is generally not worse than a canonical equivalent implementation, and can sometimes be significantly better.iTupleFor instance, as iTuple is simply a subclass of the built-in tuple, it has very similar performance characteristics.CreationCreation is slightly slower than for an equivalent length list:%timeitxtuples.iTuple.range(10**2)%timeitlist(range(10**2))1.56 \u00b5s \u00b1 9.4 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n588 ns \u00b1 11.3 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)%timeitxtuples.iTuple.range(10**3)%timeitlist(range(10**3))11.9 \u00b5s \u00b1 128 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n7.97 \u00b5s \u00b1 60.2 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)%timeitxtuples.iTuple.range(10**4)%timeitlist(range(10**4))132 \u00b5s \u00b1 1.51 \u00b5s per loop (mean \u00b1 std. dev. of 7 runs, 10,000 loops each)\n89.6 \u00b5s \u00b1 817 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000 loops each)%timeitxtuples.iTuple.range(10**6)%timeitlist(range(10**6))40.9 ms \u00b1 1.12 ms per loop (mean \u00b1 std. dev. of 7 runs, 10 loops each)\n24.5 ms \u00b1 424 \u00b5s per loop (mean \u00b1 std. dev. of 7 runs, 10 loops each)MemoryWhereas memory usage (comparable for small sizes), gets increasingly more efficient with size:memory={}foriinrange(5):memory[i]=dict(iTuple=asizeof(xtuples.iTuple.range(10**i)),list=asizeof(list(range(10**i))),)memory{0: {'iTuple': 160, 'list': 88},\n 1: {'iTuple': 232, 'list': 448},\n 2: {'iTuple': 952, 'list': 4048},\n 3: {'iTuple': 8152, 'list': 40048},\n 4: {'iTuple': 80152, 'list': 400048}}ex_iTuple=xtuples.iTuple.range(100)ex_list=list(range(100))ex_range=range(100)Iteration & IndexingIteration is very similar:%timeitforxinex_iTuple:pass%timeitforxinex_list:pass764 ns \u00b1 4.57 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n721 ns \u00b1 24.1 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)And whilst elementwise indexing is clearly slower:%timeitforiinrange(100):ex_iTuple[i]%timeitforiinrange(100):ex_list[i]18.6 \u00b5s \u00b1 240 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n2.84 \u00b5s \u00b1 75.3 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)And so is slice indexing:%timeitex_iTuple[10:20]%timeitex_list[10:20]667 ns \u00b1 10.3 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n93.9 ns \u00b1 0.998 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)It is worth noting that per element indexing is not all that common using xtuples (as the canonical implementation is much more likely to use .map() and co).Function applicationElementwise function application with .map() ismuchfaster than the equivalent loop or list comprehension:add_2=functools.partial(operator.add,2)deff_loop_map(f,l):res=[]forvinl:res.append(f(v))returnres%timeitex_iTuple.map(add_2)%timeitf_loop_map(add_2,ex_list)%timeit[add_2(x)forxinex_list]%timeitlist(map(add_2,ex_list))5.57 \u00b5s \u00b1 104 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n8.33 s \u00b1 248 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)\n5.96 s \u00b1 181 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)\n5.12 s \u00b1 609 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)As is elementwise filtering:deff_loop_filter(f):res=[]foriinex_list:iff(i):res.append(i)returnresf=lambdax:x%2==0%timeitex_iTuple.filter(f)%timeitf_loop_filter(f)%timeit[vforvinex_listiff(v)]15.2 \u00b5s \u00b1 41.6 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n6.68 s \u00b1 139 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)\n7.13 s \u00b1 113 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)And, so are both fold and cumulative fold:deff_loop_fold():acc=0foriinex_list:acc=operator.add(acc,i)returnacc%timeitex_iTuple.fold(operator.add)%timeitf_loop_fold()3.11 \u00b5s \u00b1 48.5 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n4.87 s \u00b1 89.8 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)So, as mentioned below, the answer to the poor .append() performance is just to use .foldcum() instead:deff_loop_foldcum():res=[]acc=0foriinex_list:acc=operator.add(acc,i)res.append(acc)returnres%timeitex_iTuple.foldcum(operator.add)%timeitf_loop_foldcum()5.91 \u00b5s \u00b1 19 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n15.2 s \u00b1 1.67 s per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)AppendAppending ismuchslower, which is clearly to some extent a 'gotcha'.%timeitex_iTuple.append(1)%timeitex_list.append(1)1.56 \u00b5s \u00b1 22.9 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n69.3 ns \u00b1 6.18 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)Having said that, the canonical xtuples implementation is much more likely to use .map() .foldcum() or similar than .append().And, as we've already seen, .map() and .foldcum() aremuchfaster than the for-loop & append() implementations (so just do that instead - I personally also find it much more readable).Prepend / ExtendPrepending to the tuple ismuchfaster than with the list, though the relevant comparison is probably a deque (given that list is not at all optimised for left-append):%timeitex_iTuple.prepend(1)%timeitex_list.insert(0,1)1.44 \u00b5s \u00b1 11 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n109 ms \u00b1 10.2 ms per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)Extend is somewhat slower (but is nowhere near as bad as append):%timeitxtuples.iTuple.range(100).extend([1])%timeitxtuples.iTuple.range(100).extend(list(range(100)))%timeitlist(range(100)).extend([1])%timeitlist(range(100)).extend(list(range(100)))3.93 \u00b5s \u00b1 32.3 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n5.58 \u00b5s \u00b1 43.4 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n769 ns \u00b1 8.37 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n1.48 \u00b5s \u00b1 19 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)And flatten ismuchfaster:ex_iTuple_nested=ex_iTuple.map(lambdav:[v])ex_list_nested=[[v]forvinex_list]deff_loop_flatten(l):forvinl:yield fromv%timeitex_iTuple_nested.flatten()%timeitlist(f_loop_flatten(ex_list_nested))%timeitlist(itertools.chain(*ex_list_nested))5.38 \u00b5s \u00b1 81.1 ns per loop (mean \u00b1 std. dev. of 7 runs, 100,000 loops each)\n29.5 s \u00b1 1.14 s per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)\n1min 19s \u00b1 14.9 s per loop (mean \u00b1 std. dev. of 7 runs, 1 loop each)SummaryOverall, iTuple performance and memory usage is comparable - if not better - than a raw list.The one clear weakness is .append() - however, the canonical xtuples implementation would use .map() .foldcum() etc. instead (which are actuallyfasterthan the equivalent .append() implementation).Named TuplenTuple doesnot(in comparison to iTuple) define a base class for us to sub-class.Rather, it provides a decorator - nTuple.decorate - that adds .pipe() .partial() and a dict of user defined methods to a given NamedTuple.As such, performance is essentially just that of built-in NamedTuples (ie. generally very strong).@xtuples.nTuple.decorate(update_x=lambdaself,x:self._replace(x=x),update_s=lambdaself,s:self._replace(s=s),)classExample(typing.NamedTuple):x:ints:strclassExample_Cls:x:ints:strdef__init__(self,x,s):self.x=xself.s=s@dataclasses.dataclass(frozen=True,eq=True)classExample_DC:x:ints:strex_nTuple=Example(1,\"a\")ex_dict=dict(x=1,s=\"a\")ex_cls=Example_Cls(1,\"a\")ex_dc=Example_DC(1,\"a\")NOTE, re-registering: ExampleFor instance, NamedTuples are significantly more memory efficient than any of the possible alternatives:dict(nTuple=asizeof(ex_nTuple),dict=asizeof(ex_dict),cls=asizeof(ex_cls),dataclass=asizeof(ex_dc),){'nTuple': 144, 'dict': 432, 'cls': 352, 'dataclass': 352}%timeitExample(1,\"a\")%timeitdict(x=1,s=\"a\")%timeitExample_Cls(1,\"a\")%timeitExample_DC(1,\"a\")257 ns \u00b1 8.92 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n111 ns \u00b1 1.53 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n209 ns \u00b1 2.58 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n443 ns \u00b1 3.05 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)Whilst providing comparable (if not slightly faster) field access times:%timeitex_nTuple.x%timeitex_nTuple[0]%timeitex_dict[\"x\"]%timeitex_cls.x%timeitex_dc.x27.7 ns \u00b1 0.303 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n25.1 ns \u00b1 0.0815 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n29.7 ns \u00b1 0.181 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n30.3 ns \u00b1 0.492 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n34.9 ns \u00b1 0.125 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)Writes are, however, slower - the price we pay for immutability (but are still notably faster than the frozen dataclass equivalent):%timeitex_dict[\"x\"]=1%timeitex_cls.x=1%timeitex_nTuple._replace(x=1)&timeitex_nTuple.update_x(x)%timeitex_nTuple.update(x=1)%timeitdataclasses.replace(ex_dc,x=1)32.4 ns \u00b1 0.467 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n43.8 ns \u00b1 0.524 ns per loop (mean \u00b1 std. dev. of 7 runs, 10,000,000 loops each)\n735 ns \u00b1 5.93 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n1.03 \u00b5s \u00b1 3.35 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)\n1.28 \u00b5s \u00b1 4.37 ns per loop (mean \u00b1 std. dev. of 7 runs, 1,000,000 loops each)Like frozen dataclasses, NamedTuples are conveniently hashable (in comparison to dicts, for instance, which aren't), and do so based on value (versus standard classes which use object ids by default):dict(nTuple=hash(ex_nTuple)==hash(Example(1,\"a\")),cls=hash(ex_cls)==hash(Example_Cls(1,\"a\")),dataclass=hash(ex_dc)==hash(Example_DC(1,\"a\")),){'nTuple': True, 'cls': False, 'dataclass': True}This is particularly useful in combination with iTuple, which is also hashable (making combinations of the two recursively hashable):@xtuples.nTuple.decorateclassExample_Nested(typing.NamedTuple):x:ints:strit:xtuples.iTuplehash(Example_Nested(1,\"s\",xtuples.iTuple()))==hash(Example_Nested(1,\"s\",xtuples.iTuple()))TrueFinally, sorting is both provided by default (again, in comparison to dicts and classes), and works as one would expect (ie. by the first field, then the second field, etc.):xtuples.iTuple([Example(2,\"a\"),Example(1,\"b\"),Example(1,\"a\"),]).sort()iTuple(Example(x=1, s='a'), Example(x=1, s='b'), Example(x=2, s='a'))Licensextuplesis distributed under the terms of theMITlicense."} +{"package": "xturing", "pacakge-description": "Build, customize and control your own personal LLMsxTuringprovides fast, efficient and simple fine-tuning of LLMs, such as LLaMA, GPT-J, Galactica, and more.\nBy providing an easy-to-use interface for fine-tuning LLMs to your own data and application, xTuring makes it\nsimple to build, customize and control LLMs. The entire process can be done inside your computer or in your\nprivate cloud, ensuring data privacy and security.WithxTuringyou can,Ingest data from different sources and preprocess them to a format LLMs can understandScale from single to multiple GPUs for faster fine-tuningLeverage memory-efficient methods (i.e. INT4, LoRA fine-tuning) to reduce hardware costs by up to 90%Explore different fine-tuning methods and benchmark them to find the best performing modelEvaluate fine-tuned models on well-defined metrics for in-depth analysis\ud83c\udf1f What's new?We are excited to announce the latest enhancements to ourxTuringlibrary:LLaMA 2integration- You can use and fine-tune theLLaMA 2model in different configurations:off-the-shelf,off-the-shelf with INT8 precision,LoRA fine-tuning,LoRA fine-tuning with INT8 precisionandLoRA fine-tuning with INT4 precisionusing theGenericModelwrapper and/or you can use theLlama2class fromxturing.modelsto test and finetune the model.fromxturing.modelsimportLlama2model=Llama2()## orfromxturing.modelsimportBaseModelmodel=BaseModel.create('llama2')Evaluation- Now you can evaluate anyCausal Language Modelon any dataset. The metrics currently supported isperplexity.# Make the necessary importsfromxturing.datasetsimportInstructionDatasetfromxturing.modelsimportBaseModel# Load the desired datasetdataset=InstructionDataset('../llama/alpaca_data')# Load the desired modelmodel=BaseModel.create('gpt2')# Run the Evaluation of the model on the datasetresult=model.evaluate(dataset)# Print the resultprint(f\"Perplexity of the evalution:{result}\")INT4Precision- You can now use and fine-tune any LLM withINT4 PrecisionusingGenericLoraKbitModel.# Make the necessary importsfromxturing.datasetsimportInstructionDatasetfromxturing.modelsimportGenericLoraKbitModel# Load the desired datasetdataset=InstructionDataset('../llama/alpaca_data')# Load the desired model for INT4 bit fine-tuningmodel=GenericLoraKbitModel('tiiuae/falcon-7b')# Run the fine-tuningmodel.finetune(dataset)CPU inference- Now you can use just your CPU for inference of any LLM.CAUTION : The inference process may be sluggish because CPUs lack the required computational capacity for efficient inference.Batch integration- By tweaking the 'batch_size' in the .generate() and .evaluate() functions, you can expedite results. Using a 'batch_size' greater than 1 typically enhances processing efficiency.# Make the necessary importsfromxturing.datasetsimportInstructionDatasetfromxturing.modelsimportGenericLoraKbitModel# Load the desired datasetdataset=InstructionDataset('../llama/alpaca_data')# Load the desired model for INT4 bit fine-tuningmodel=GenericLoraKbitModel('tiiuae/falcon-7b')# Generate outputs on desired promptsoutputs=model.generate(dataset=dataset,batch_size=10)An exploration of theLlama LoRA INT4 working exampleis recommended for an understanding of its application.For an extended insight, consider examining theGenericModel working exampleavailable in the repository.\u2699\ufe0f Installationpipinstallxturing\ud83d\ude80 Quickstartfromxturing.datasetsimportInstructionDatasetfromxturing.modelsimportBaseModel# Load the datasetinstruction_dataset=InstructionDataset(\"./alpaca_data\")# Initialize the modelmodel=BaseModel.create(\"llama_lora\")# Finetune the modelmodel.finetune(dataset=instruction_dataset)# Perform inferenceoutput=model.generate(texts=[\"Why LLM models are becoming so important?\"])print(\"Generated output by the model:{}\".format(output))You can find the data folderhere.CLI playground$xturingchat-m\"<path-to-model-folder>\"UI playgroundfromxturing.datasetsimportInstructionDatasetfromxturing.modelsimportBaseModelfromxturing.uiimportPlaygrounddataset=InstructionDataset(\"./alpaca_data\")model=BaseModel.create(\"<model_name>\")model.finetune(dataset=dataset)model.save(\"llama_lora_finetuned\")Playground().launch()## launches localhost UI\ud83d\udcda TutorialsPreparing your datasetCerebras-GPT fine-tuning with LoRA and INT8Cerebras-GPT fine-tuning with LoRALLaMA fine-tuning with LoRA and INT8LLaMA fine-tuning with LoRALLaMA fine-tuningGPT-J fine-tuning with LoRA and INT8GPT-J fine-tuning with LoRAGPT-2 fine-tuning with LoRA\ud83d\udcca PerformanceHere is a comparison for the performance of different fine-tuning techniques on the LLaMA 7B model. We use theAlpaca datasetfor fine-tuning. The dataset contains 52K instructions.Hardware:4xA100 40GB GPU, 335GB CPU RAMFine-tuning parameters:{'maximum sequence length':512,'batch size':1,}LLaMA-7BDeepSpeed + CPU OffloadingLoRA + DeepSpeedLoRA + DeepSpeed + CPU OffloadingGPU33.5 GB23.7 GB21.9 GBCPU190 GB10.2 GB14.9 GBTime/epoch21 hours20 mins20 minsContribute to this by submitting your performance results on other GPUs by creating an issue with your hardware specifications, memory consumption and time per epoch.\ud83d\udcce Fine-tuned model checkpointsWe have already fine-tuned some models that you can use as your base or start playing with.\nHere is how you would load them:fromxturing.modelsimportBaseModelmodel=BaseModel.load(\"x/distilgpt2_lora_finetuned_alpaca\")modeldatasetPathDistilGPT-2 LoRAalpacax/distilgpt2_lora_finetuned_alpacaLLaMA LoRAalpacax/llama_lora_finetuned_alpacaSupported ModelsBelow is a list of all the supported models viaBaseModelclass ofxTuringand their corresponding keys to load them.ModelKeyBloombloomCerebrascerebrasDistilGPT-2distilgpt2Falcon-7BfalconGalacticagalacticaGPT-JgptjGPT-2gpt2LlaMAllamaLlaMA2llama2OPT-1.3BoptThe above mentioned are the base variants of the LLMs. Below are the templates to get theirLoRA,INT8,INT8 + LoRAandINT4 + LoRAversions.VersionTemplateLoRA<model_key>_loraINT8<model_key>_int8INT8 + LoRA<model_key>_lora_int8** In order to load any model'sINT4+LoRAversion, you will need to make use ofGenericLoraKbitModelclass fromxturing.models. Below is how to use it:model=GenericLoraKbitModel('<model_path>')Themodel_pathcan be replaced with you local directory or any HuggingFace library model likefacebook/opt-1.3b.\ud83d\udcc8 RoadmapSupport forLLaMA,GPT-J,GPT-2,OPT,Cerebras-GPT,GalacticaandBloommodelsDataset generation using self-instructionLow-precision LoRA fine-tuning and unsupervised fine-tuningINT8 low-precision fine-tuning supportOpenAI, Cohere and AI21 Studio model APIs for dataset generationAdded fine-tuned checkpoints for some models to the hubINT4 LLaMA LoRA fine-tuning demoINT4 LLaMA LoRA fine-tuning with INT4 generationSupport for aGeneric modelwrapperSupport forFalcon-7BmodelINT4 low-precision fine-tuning supportEvaluation of LLM modelsINT3, INT2, INT1 low-precision fine-tuning supportSupport for Stable Diffusion\ud83e\udd1d Help and SupportIf you have any questions, you can create an issue on this repository.You can also join ourDiscord serverand start a discussion in the#xturingchannel.\ud83d\udcdd LicenseThis project is licensed under the Apache License 2.0 - see theLICENSEfile for details.\ud83c\udf0e ContributingAs an open source project in a rapidly evolving field, we welcome contributions of all kinds, including new features and better documentation. Please read ourcontributing guideto learn how you can get involved."} +{"package": "xtweet", "pacakge-description": "xtweetxtweetes una biblioteca que te permite interactuar de manera eficiente con la API de Twitter. Con ella, puedes obtener informaci\u00f3n detallada sobre tweets y medios de manera r\u00e1pida y sencilla.UsoLa claseTweetrepresenta un tweet de Twitter y proporciona propiedades para acceder a la informaci\u00f3n del tweet.fromxtweetimportTweettweet=Tweet(url)PropiedadesLa clase Tweet proporciona las siguientes propiedades para acceder a la informaci\u00f3n del tweet:date: Fecha de publicaci\u00f3n del tweet.text: Texto del tweet.thumbnail_url: URL de la miniatura de la primera imagen incluida en el tweet, si est\u00e1 disponible.likes: N\u00famero de me gusta del tweet.replies: N\u00famero de respuestas al tweet.retweets: N\u00famero de retweets del tweet.tweet_id: ID del tweet.user_name: Nombre del usuario que public\u00f3 el tweet.user_screen_name: Nombre de pantalla del usuario que public\u00f3 el tweet.La claseMediarepresenta los medios incluidos en un tweet y proporciona m\u00e9todos para descargar im\u00e1genes y videos.fromxtweetimportMediamedia=Media(url)M\u00e9todosLa claseMediaproporciona los siguientes m\u00e9todos para descargar im\u00e1genes y videos:download_photo(fp, name_file): Descarga todas las im\u00e1genes incluidas en el tweet y las guarda en el directorio especificado por el argumentofpcon un nombre de archivo que incluye un \u00edndice para distinguir entre las diferentes im\u00e1genes. El argumento opcionalname_fileespecifica el nombre base del archivo.download_video(fp, name_file): Descarga todos los videos incluidos en el tweet y los guarda en el directorio especificado por el argumentofpcon un nombre de archivo que incluye un \u00edndice para distinguir entre los diferentes videos. El argumento opcionalname_fileespecifica el nombre base del archivo."} +{"package": "xtwine", "pacakge-description": "TWINE: A Lightweight Block Cipher for Multiple PlatformsThis repository is an implementation ofTWINE: A Lightweight Block Cipher for Multiple Platformspaper introduced by Tomoyasu Suzaki, Kazuhiko Minematsu, Sumio Morioka, and Eita Kobayashi.InstallationInstall by pip from PyPI:pip3installtwineOr install latest version from github:python3-mpipinstall-Ugit+https://github.com/amoallim15/TWINE.gitUsageThis repository contains a command line tool that can be used to ecnrypt plaintext samples using either of the supported 80 bits or 128 bits sized keys.Example 1:xtwine\"hello world\"-k\"<o8~I{?3Uz\"The output:Encryption Key: \"<o8~I{?3Uz\"\nabb90d4c0a8f67632cec7c01ee409ea1Example 2:xtwine\"01bbed92bccc2104b7e12141f1413ad6\"-d-k\"4ejqxfDL3#\"The output:Decryption Key: \"4ejqxfDL3#\"\nhello worldExample 3:xtwine\"1 plus 1 equals 2\"The output:Encryption Key: \"8_D]H[!^M*\"\n0315a70682ac625cdced6a7ff834d629c2b70de4e2d1fc7bExample 4:xtwine\"1 plus 1 equals 2\"-z128The output:Encryption Key: \"oti,D:H6[5WX|8jS\"\n7f9c4394decc4c59c94be30b49db5ef66943a2938416382fExample 5:fromxtwineimportTwinetwine=Twine(key_size=0x50)# If the key param is not specified# it will generate a key automatically.ciphertext=twine.encrypt(\"hello world\")print(ciphertext)# > \"abb90d4c0a8f67632cec7c01ee409ea1\"plaintext=twine.decrypt(ciphertext)print(plaintext)# > \"hello world\"Release History1.0.2hotfix: from xtwine import Twine1.0.1read/write from/to stdin/stdout.AboutAli MoallimContributingBug reports and pull requests are welcome on GitHub athttps://github.com/amoallim15/xtwine.\nI'm also available for questions, feel free to get in touch.LicenseThis code is licensed underMIT."} +{"package": "xtyle", "pacakge-description": "XtylePython (JSX-Toolkit) DocumentationIntroductionWelcome to the Xtyle! This tool allows you to work with JSX components.It ispowered by.Python:py-mini-racer,css-html-js-minify, andlibsassJavaScript:babel, andprettierInstallpipinstall\"xtyle\"Install for Developmentpipinstall\"xtyle[debug]\"Example (JSX)importxtylecode_js=xtyle.jsx(\"const App = () => <div>Hello World</div>\")print(code_js)Example (SCSS)importxtylecode_css=xtyle.scss(\"$color: red; body { color: $color; }\")print(code_css)Get Server and Learn More...Example (Client)importxtyleengine=xtyle.client(\"http://localhost:3000\")engine.component(name=\"kebab-case-name\",code=\"TypeScript Code\",props=\"TypeScript Code\",style=\"SASS/SCSS Code\",docs=\"TypeScript Code\",)engine.plugin(name=\"myPlugin\",components=[dict(name=\"kebab-case-name\",code=\"TypeScript Code\",props=\"TypeScript Code\",style=\"SASS/SCSS Code\",docs=\"TypeScript Code\",)],install=dict(init=\"export default list\",store=\"export default dict\",globals=\"export default dict\",directives=\"export default dict\",),)Example (Client-Extended)importxtyleengine=xtyle.client(\"http://localhost:3000\")defcreate_component(name):return{\"name\":name,\"code\":\"\\nexport default function Component(props: Props ={}) {\\nreturn (\\n<div x-html {...props} class={[$NAME, props.class]}>\\n{props.children}\\n</div>\\n);\\n}\\n\",\"style\":\"\\n$color: red;\\n.#{$NAME} { color: $color; }\\n\",\"props\":\"\\ntype Props = {\\nclass?: string | string[] | object;\\nstyle?: string | string[] | object;\\nchildren?: any;\\n};\\n\\nexport default Props;\\n\",\"docs\":\"\\n/**\\n* Component - This is a my component.\\n*/\\n\",}one_component=create_component(\"alert\")example_components=[create_component(\"alert\"),create_component(\"custom-button\"),]plugin_name=\"myPlugin\"install_code={\"init\":\"\"\"export default [() => console.log(\"Plugin INIT\")]\"\"\"}# Componentdemo_component=engine.component(**one_component)# Plugindemo_plugin=engine.plugin(plugin_name,example_components,install_code)print(demo_component)print(\"\\n\\n\")print(demo_plugin)Browser Usage<!-- Babel & Prettier --><scriptsrc=\"https://cdn.jsdelivr.net/gh/hlop3z/xtyle-python@main/src/xtyle/babel.min.js\"></script><scriptsrc=\"https://cdn.jsdelivr.net/gh/hlop3z/xtyle-python@main/src/xtyle/prettier-full.min.js\"></script>"} +{"package": "xtypes", "pacakge-description": "No description available on PyPI."} +{"package": "xtyping", "pacakge-description": "xtypingInstall:pip install xtypingWhat is xtyping?xtyping (short for extended typing) lets you import all your friends fromtypingas well astyping_extensionstyping|typing_extensions; xtyping 'exports' everything intyping.__all__andtyping_extensions.__all__Common type aliasesWhy not usetyping_extensions?Don't have to import bothtypingandtyping_extensions; BOOMInstead of writing:from typing import Optional\nfrom typing_extensions import TypedDictyou can write:from xtyping import Optional, TypedDict\n# or\nimport xtyping as xt\nTypedDict = xt.TypedDict\nOptional = xt.Optionalimportxtypingasxtfrom_typing=[\" ~ \".join((f\"xt.{el}\",f\"typing.{el}\",str(getattr(xt,el))))forelinxt.__all_typing__]from_typing_extensions=[\" ~ \".join((f\"xt.{el}\",f\"typing_extensions.{el}\",str(getattr(xt,el))))forelinxt.__all_typing__]from_xtyping_shed=[\" ~ \".join((f\"xt.{el}\",f\"xtyping.shed.{el}\",str(getattr(xt,el))))forelinxt.__all_shed__]print(\"\\n\".join([\"-------------\",\"from `typing`\",\"-------------\",*from_typing,\"\\n\",\"------------------------\",\"from `typing_extensions`\",\"------------------------\",*from_typing_extensions,\"\\n\",\"-------------------\",\"from `xtyping.shed`\",\"-------------------\",*from_xtyping_shed,\"\\n\",]))-------------\nfrom `typing`\n-------------\nxt.AbstractSet ~ typing.AbstractSet ~ typing.AbstractSet\nxt.Any ~ typing.Any ~ typing.Any\nxt.AnyStr ~ typing.AnyStr ~ ~AnyStr\nxt.AsyncContextManager ~ typing.AsyncContextManager ~ typing.AbstractAsyncContextManager\nxt.AsyncGenerator ~ typing.AsyncGenerator ~ typing.AsyncGenerator\nxt.AsyncIterable ~ typing.AsyncIterable ~ typing.AsyncIterable\nxt.AsyncIterator ~ typing.AsyncIterator ~ typing.AsyncIterator\nxt.Awaitable ~ typing.Awaitable ~ typing.Awaitable\nxt.ByteString ~ typing.ByteString ~ typing.ByteString\nxt.Callable ~ typing.Callable ~ typing.Callable\nxt.ChainMap ~ typing.ChainMap ~ typing.ChainMap\nxt.ClassVar ~ typing.ClassVar ~ typing.ClassVar\nxt.Collection ~ typing.Collection ~ typing.Collection\nxt.Container ~ typing.Container ~ typing.Container\nxt.ContextManager ~ typing.ContextManager ~ typing.AbstractContextManager\nxt.Coroutine ~ typing.Coroutine ~ typing.Coroutine\nxt.Counter ~ typing.Counter ~ typing.Counter\nxt.DefaultDict ~ typing.DefaultDict ~ typing.DefaultDict\nxt.Deque ~ typing.Deque ~ typing.Deque\nxt.Dict ~ typing.Dict ~ typing.Dict\nxt.FrozenSet ~ typing.FrozenSet ~ typing.FrozenSet\nxt.Generator ~ typing.Generator ~ typing.Generator\nxt.Generic ~ typing.Generic ~ <class 'typing.Generic'>\nxt.Hashable ~ typing.Hashable ~ typing.Hashable\nxt.IO ~ typing.IO ~ <class 'typing.IO'>\nxt.ItemsView ~ typing.ItemsView ~ typing.ItemsView\nxt.Iterable ~ typing.Iterable ~ typing.Iterable\nxt.Iterator ~ typing.Iterator ~ typing.Iterator\nxt.KeysView ~ typing.KeysView ~ typing.KeysView\nxt.List ~ typing.List ~ typing.List\nxt.Mapping ~ typing.Mapping ~ typing.Mapping\nxt.MappingView ~ typing.MappingView ~ typing.MappingView\nxt.MutableMapping ~ typing.MutableMapping ~ typing.MutableMapping\nxt.MutableSequence ~ typing.MutableSequence ~ typing.MutableSequence\nxt.MutableSet ~ typing.MutableSet ~ typing.MutableSet\nxt.NamedTuple ~ typing.NamedTuple ~ <class 'typing.NamedTuple'>\nxt.NewType ~ typing.NewType ~ <function NewType at 0x7fd2e534f790>\nxt.Optional ~ typing.Optional ~ typing.Optional\nxt.Reversible ~ typing.Reversible ~ typing.Reversible\nxt.Sequence ~ typing.Sequence ~ typing.Sequence\nxt.Set ~ typing.Set ~ typing.Set\nxt.Sized ~ typing.Sized ~ typing.Sized\nxt.SupportsAbs ~ typing.SupportsAbs ~ <class 'typing.SupportsAbs'>\nxt.SupportsBytes ~ typing.SupportsBytes ~ <class 'typing.SupportsBytes'>\nxt.SupportsComplex ~ typing.SupportsComplex ~ <class 'typing.SupportsComplex'>\nxt.SupportsFloat ~ typing.SupportsFloat ~ <class 'typing.SupportsFloat'>\nxt.SupportsInt ~ typing.SupportsInt ~ <class 'typing.SupportsInt'>\nxt.SupportsRound ~ typing.SupportsRound ~ <class 'typing.SupportsRound'>\nxt.TYPE_CHECKING ~ typing.TYPE_CHECKING ~ False\nxt.Text ~ typing.Text ~ <class 'str'>\nxt.Tuple ~ typing.Tuple ~ typing.Tuple\nxt.Type ~ typing.Type ~ typing.Type\nxt.TypeVar ~ typing.TypeVar ~ <class 'typing.TypeVar'>\nxt.Union ~ typing.Union ~ typing.Union\nxt.ValuesView ~ typing.ValuesView ~ typing.ValuesView\nxt.cast ~ typing.cast ~ <function cast at 0x7fd2e53435e0>\nxt.get_type_hints ~ typing.get_type_hints ~ <function get_type_hints at 0x7fd2dc7531f0>\nxt.no_type_check ~ typing.no_type_check ~ <function no_type_check at 0x7fd2e53438b0>\nxt.no_type_check_decorator ~ typing.no_type_check_decorator ~ <function no_type_check_decorator at 0x7fd2e5343940>\nxt.overload ~ typing.overload ~ <function overload at 0x7fd2dc721a60>\n\n\n------------------------\nfrom `typing_extensions`\n------------------------\nxt.AbstractSet ~ typing_extensions.AbstractSet ~ typing.AbstractSet\nxt.Any ~ typing_extensions.Any ~ typing.Any\nxt.AnyStr ~ typing_extensions.AnyStr ~ ~AnyStr\nxt.AsyncContextManager ~ typing_extensions.AsyncContextManager ~ typing.AbstractAsyncContextManager\nxt.AsyncGenerator ~ typing_extensions.AsyncGenerator ~ typing.AsyncGenerator\nxt.AsyncIterable ~ typing_extensions.AsyncIterable ~ typing.AsyncIterable\nxt.AsyncIterator ~ typing_extensions.AsyncIterator ~ typing.AsyncIterator\nxt.Awaitable ~ typing_extensions.Awaitable ~ typing.Awaitable\nxt.ByteString ~ typing_extensions.ByteString ~ typing.ByteString\nxt.Callable ~ typing_extensions.Callable ~ typing.Callable\nxt.ChainMap ~ typing_extensions.ChainMap ~ typing.ChainMap\nxt.ClassVar ~ typing_extensions.ClassVar ~ typing.ClassVar\nxt.Collection ~ typing_extensions.Collection ~ typing.Collection\nxt.Container ~ typing_extensions.Container ~ typing.Container\nxt.ContextManager ~ typing_extensions.ContextManager ~ typing.AbstractContextManager\nxt.Coroutine ~ typing_extensions.Coroutine ~ typing.Coroutine\nxt.Counter ~ typing_extensions.Counter ~ typing.Counter\nxt.DefaultDict ~ typing_extensions.DefaultDict ~ typing.DefaultDict\nxt.Deque ~ typing_extensions.Deque ~ typing.Deque\nxt.Dict ~ typing_extensions.Dict ~ typing.Dict\nxt.FrozenSet ~ typing_extensions.FrozenSet ~ typing.FrozenSet\nxt.Generator ~ typing_extensions.Generator ~ typing.Generator\nxt.Generic ~ typing_extensions.Generic ~ <class 'typing.Generic'>\nxt.Hashable ~ typing_extensions.Hashable ~ typing.Hashable\nxt.IO ~ typing_extensions.IO ~ <class 'typing.IO'>\nxt.ItemsView ~ typing_extensions.ItemsView ~ typing.ItemsView\nxt.Iterable ~ typing_extensions.Iterable ~ typing.Iterable\nxt.Iterator ~ typing_extensions.Iterator ~ typing.Iterator\nxt.KeysView ~ typing_extensions.KeysView ~ typing.KeysView\nxt.List ~ typing_extensions.List ~ typing.List\nxt.Mapping ~ typing_extensions.Mapping ~ typing.Mapping\nxt.MappingView ~ typing_extensions.MappingView ~ typing.MappingView\nxt.MutableMapping ~ typing_extensions.MutableMapping ~ typing.MutableMapping\nxt.MutableSequence ~ typing_extensions.MutableSequence ~ typing.MutableSequence\nxt.MutableSet ~ typing_extensions.MutableSet ~ typing.MutableSet\nxt.NamedTuple ~ typing_extensions.NamedTuple ~ <class 'typing.NamedTuple'>\nxt.NewType ~ typing_extensions.NewType ~ <function NewType at 0x7fd2e534f790>\nxt.Optional ~ typing_extensions.Optional ~ typing.Optional\nxt.Reversible ~ typing_extensions.Reversible ~ typing.Reversible\nxt.Sequence ~ typing_extensions.Sequence ~ typing.Sequence\nxt.Set ~ typing_extensions.Set ~ typing.Set\nxt.Sized ~ typing_extensions.Sized ~ typing.Sized\nxt.SupportsAbs ~ typing_extensions.SupportsAbs ~ <class 'typing.SupportsAbs'>\nxt.SupportsBytes ~ typing_extensions.SupportsBytes ~ <class 'typing.SupportsBytes'>\nxt.SupportsComplex ~ typing_extensions.SupportsComplex ~ <class 'typing.SupportsComplex'>\nxt.SupportsFloat ~ typing_extensions.SupportsFloat ~ <class 'typing.SupportsFloat'>\nxt.SupportsInt ~ typing_extensions.SupportsInt ~ <class 'typing.SupportsInt'>\nxt.SupportsRound ~ typing_extensions.SupportsRound ~ <class 'typing.SupportsRound'>\nxt.TYPE_CHECKING ~ typing_extensions.TYPE_CHECKING ~ False\nxt.Text ~ typing_extensions.Text ~ <class 'str'>\nxt.Tuple ~ typing_extensions.Tuple ~ typing.Tuple\nxt.Type ~ typing_extensions.Type ~ typing.Type\nxt.TypeVar ~ typing_extensions.TypeVar ~ <class 'typing.TypeVar'>\nxt.Union ~ typing_extensions.Union ~ typing.Union\nxt.ValuesView ~ typing_extensions.ValuesView ~ typing.ValuesView\nxt.cast ~ typing_extensions.cast ~ <function cast at 0x7fd2e53435e0>\nxt.get_type_hints ~ typing_extensions.get_type_hints ~ <function get_type_hints at 0x7fd2dc7531f0>\nxt.no_type_check ~ typing_extensions.no_type_check ~ <function no_type_check at 0x7fd2e53438b0>\nxt.no_type_check_decorator ~ typing_extensions.no_type_check_decorator ~ <function no_type_check_decorator at 0x7fd2e5343940>\nxt.overload ~ typing_extensions.overload ~ <function overload at 0x7fd2dc721a60>\n\n\n-------------------\nfrom `xtyping.shed`\n-------------------\nxt.AF ~ xtyping.shed.AF ~ ~AF\nxt.AFn ~ xtyping.shed.AFn ~ ~AFn\nxt.AnyAsyncCallable ~ xtyping.shed.AnyAsyncCallable ~ typing.Callable[..., typing.Awaitable[typing.Any]]\nxt.AnyCallable ~ xtyping.shed.AnyCallable ~ typing.Callable[..., typing.Any]\nxt.AnyFunction ~ xtyping.shed.AnyFunction ~ typing.Union[typing.Callable[..., ~R], typing.Callable[..., typing.Awaitable[~R]]]\nxt.AnyIterable ~ xtyping.shed.AnyIterable ~ typing.Union[typing.Iterable[~T], typing.AsyncIterable[~T]]\nxt.AnyIterator ~ xtyping.shed.AnyIterator ~ typing.Union[typing.Iterator[~T], typing.AsyncIterator[~T]]\nxt.ArrShape ~ xtyping.shed.ArrShape ~ typing.Tuple[int, ...]\nxt.ArrayShape ~ xtyping.shed.ArrayShape ~ typing.Tuple[int, ...]\nxt.AsyncFn ~ xtyping.shed.AsyncFn ~ ~AsyncFn\nxt.AsyncFuncType ~ xtyping.shed.AsyncFuncType ~ typing.Callable[..., typing.Awaitable[typing.Any]]\nxt.Bytes ~ xtyping.shed.Bytes ~ typing.Union[bytes, bytearray]\nxt.BytesPath ~ xtyping.shed.BytesPath ~ typing.Union[bytes, os.PathLike]\nxt.CmdArgs ~ xtyping.shed.CmdArgs ~ typing.Union[bytes, str, typing.Sequence[str], typing.Sequence[typing.Union[str, pathlib.Path, os.PathLike]]]\nxt.CmdArgsType ~ xtyping.shed.CmdArgsType ~ typing.Union[bytes, str, typing.Sequence[str], typing.Sequence[typing.Union[str, pathlib.Path, os.PathLike]]]\nxt.D ~ xtyping.shed.D ~ typing.Dict\nxt.DT ~ xtyping.shed.DT ~ ~DT\nxt.DictAny ~ xtyping.shed.DictAny ~ typing.Dict[typing.Any, typing.Any]\nxt.DictAnyAny ~ xtyping.shed.DictAnyAny ~ typing.Dict[typing.Any, typing.Any]\nxt.DictFloat ~ xtyping.shed.DictFloat ~ typing.Dict[float, float]\nxt.DictFloatFloat ~ xtyping.shed.DictFloatFloat ~ typing.Dict[float, float]\nxt.DictInt ~ xtyping.shed.DictInt ~ typing.Dict[int, int]\nxt.DictIntInt ~ xtyping.shed.DictIntInt ~ typing.Dict[int, int]\nxt.DictNumber ~ xtyping.shed.DictNumber ~ typing.Dict[typing.Union[float, int], typing.Union[float, int]]\nxt.DictNumberNumber ~ xtyping.shed.DictNumberNumber ~ typing.Dict[typing.Union[float, int], typing.Union[float, int]]\nxt.DictStr ~ xtyping.shed.DictStr ~ typing.Dict[str, str]\nxt.DictStrAny ~ xtyping.shed.DictStrAny ~ typing.Dict[str, typing.Any]\nxt.DictStrInt ~ xtyping.shed.DictStrInt ~ typing.Dict[str, int]\nxt.DictStrStr ~ xtyping.shed.DictStrStr ~ typing.Dict[str, str]\nxt.El ~ xtyping.shed.El ~ ~El\nxt.Element ~ xtyping.shed.Element ~ ~Element\nxt.Enum ~ xtyping.shed.Enum ~ <enum 'Enum'>\nxt.EnvMap ~ xtyping.shed.EnvMap ~ typing.Union[typing.Mapping[bytes, typing.Union[bytes, str]], typing.Mapping[str, typing.Union[bytes, str]]]\nxt.EnvType ~ xtyping.shed.EnvType ~ typing.Union[typing.Mapping[bytes, typing.Union[bytes, str]], typing.Mapping[str, typing.Union[bytes, str]]]\nxt.F ~ xtyping.shed.F ~ ~F\nxt.FALSE ~ xtyping.shed.FALSE ~ typing.Literal[False]\nxt.FN ~ xtyping.shed.FN ~ ~FN\nxt.Flint ~ xtyping.shed.Flint ~ typing.Union[float, int]\nxt.Fn ~ xtyping.shed.Fn ~ ~Fn\nxt.FsPath ~ xtyping.shed.FsPath ~ typing.Union[str, pathlib.Path, os.PathLike]\nxt.FsPathLike ~ xtyping.shed.FsPathLike ~ <class 'os.PathLike'>\nxt.FuncType ~ xtyping.shed.FuncType ~ typing.Callable[..., typing.Any]\nxt.HrTime ~ xtyping.shed.HrTime ~ typing.Tuple[int, int]\nxt.IntStr ~ xtyping.shed.IntStr ~ typing.Union[int, str]\nxt.IterableAny ~ xtyping.shed.IterableAny ~ typing.Iterable[typing.Any]\nxt.IterableFloat ~ xtyping.shed.IterableFloat ~ typing.Iterable[float]\nxt.IterableInt ~ xtyping.shed.IterableInt ~ typing.Iterable[int]\nxt.IterableNumber ~ xtyping.shed.IterableNumber ~ typing.Iterable[typing.Union[float, int]]\nxt.IterableStr ~ xtyping.shed.IterableStr ~ typing.Iterable[str]\nxt.IterableT ~ xtyping.shed.IterableT ~ typing.Iterable[~T]\nxt.Json ~ xtyping.shed.Json ~ typing.Union[typing.Dict[str, ForwardRef('Json')], typing.List[ForwardRef('Json')], str, int, float, bool, NoneType]\nxt.JsonArrT ~ xtyping.shed.JsonArrT ~ typing.List[typing.Any]\nxt.JsonDictT ~ xtyping.shed.JsonDictT ~ typing.Dict[str, typing.Any]\nxt.JsonListT ~ xtyping.shed.JsonListT ~ typing.List[typing.Any]\nxt.JsonObjT ~ xtyping.shed.JsonObjT ~ typing.Dict[str, typing.Any]\nxt.JsonPrimitive ~ xtyping.shed.JsonPrimitive ~ typing.Union[NoneType, bool, int, float, str]\nxt.JsonT ~ xtyping.shed.JsonT ~ typing.Union[typing.Dict[str, ForwardRef('JsonT')], typing.List[ForwardRef('JsonT')], str, int, float, bool, NoneType]\nxt.KT ~ xtyping.shed.KT ~ ~KT\nxt.KT_co ~ xtyping.shed.KT_co ~ +KT_co\nxt.KT_contra ~ xtyping.shed.KT_contra ~ -KT_contra\nxt.KeyT ~ xtyping.shed.KeyT ~ ~KeyT\nxt.KeyType ~ xtyping.shed.KeyType ~ ~KeyType\nxt.L ~ xtyping.shed.L ~ typing.Literal\nxt.ListAny ~ xtyping.shed.ListAny ~ typing.List[typing.Any]\nxt.ListFloat ~ xtyping.shed.ListFloat ~ typing.List[float]\nxt.ListInt ~ xtyping.shed.ListInt ~ typing.List[int]\nxt.ListListStr ~ xtyping.shed.ListListStr ~ typing.List[typing.List[str]]\nxt.ListNumber ~ xtyping.shed.ListNumber ~ typing.List[typing.Union[float, int]]\nxt.ListStr ~ xtyping.shed.ListStr ~ typing.List[str]\nxt.ListT ~ xtyping.shed.ListT ~ typing.List[~T]\nxt.Lit ~ xtyping.shed.Lit ~ typing.Literal\nxt.Ls ~ xtyping.shed.Ls ~ typing.List\nxt.N ~ xtyping.shed.N ~ ~N\nxt.NoneBytes ~ xtyping.shed.NoneBytes ~ typing.Union[bytes, NoneType]\nxt.NoneStr ~ xtyping.shed.NoneStr ~ typing.Union[str, NoneType]\nxt.NoneStrBytes ~ xtyping.shed.NoneStrBytes ~ typing.Union[str, bytes, NoneType]\nxt.NoneType ~ xtyping.shed.NoneType ~ <class 'NoneType'>\nxt.Null ~ xtyping.shed.Null ~ <class 'NoneType'>\nxt.Number ~ xtyping.shed.Number ~ typing.Union[float, int]\nxt.ONE ~ xtyping.shed.ONE ~ typing.Literal[True]\nxt.OpenBinaryMode ~ xtyping.shed.OpenBinaryMode ~ typing.Union[typing.Literal['rb+', 'r+b', '+rb', 'br+', 'b+r', '+br', 'wb+', 'w+b', '+wb', 'bw+', 'b+w', '+bw', 'ab+', 'a+b', '+ab', 'ba+', 'b+a', '+ba', 'xb+', 'x+b', '+xb', 'bx+', 'b+x', '+bx'], typing.Literal['rb', 'br', 'rbU', 'rUb', 'Urb', 'brU', 'bUr', 'Ubr'], typing.Literal['wb', 'bw', 'ab', 'ba', 'xb', 'bx']]\nxt.OpenBinaryModeReading ~ xtyping.shed.OpenBinaryModeReading ~ typing.Literal['rb', 'br', 'rbU', 'rUb', 'Urb', 'brU', 'bUr', 'Ubr']\nxt.OpenBinaryModeUpdating ~ xtyping.shed.OpenBinaryModeUpdating ~ typing.Literal['rb+', 'r+b', '+rb', 'br+', 'b+r', '+br', 'wb+', 'w+b', '+wb', 'bw+', 'b+w', '+bw', 'ab+', 'a+b', '+ab', 'ba+', 'b+a', '+ba', 'xb+', 'x+b', '+xb', 'bx+', 'b+x', '+bx']\nxt.OpenBinaryModeWriting ~ xtyping.shed.OpenBinaryModeWriting ~ typing.Literal['wb', 'bw', 'ab', 'ba', 'xb', 'bx']\nxt.OpenTextMode ~ xtyping.shed.OpenTextMode ~ typing.Union[typing.Literal['r+', '+r', 'rt+', 'r+t', '+rt', 'tr+', 't+r', '+tr', 'w+', '+w', 'wt+', 'w+t', '+wt', 'tw+', 't+w', '+tw', 'a+', '+a', 'at+', 'a+t', '+at', 'ta+', 't+a', '+ta', 'x+', '+x', 'xt+', 'x+t', '+xt', 'tx+', 't+x', '+tx'], typing.Literal['w', 'wt', 'tw', 'a', 'at', 'ta', 'x', 'xt', 'tx'], typing.Literal['r', 'rt', 'tr', 'U', 'rU', 'Ur', 'rtU', 'rUt', 'Urt', 'trU', 'tUr', 'Utr']]\nxt.OpenTextModeReading ~ xtyping.shed.OpenTextModeReading ~ typing.Literal['r', 'rt', 'tr', 'U', 'rU', 'Ur', 'rtU', 'rUt', 'Urt', 'trU', 'tUr', 'Utr']\nxt.OpenTextModeUpdating ~ xtyping.shed.OpenTextModeUpdating ~ typing.Literal['r+', '+r', 'rt+', 'r+t', '+rt', 'tr+', 't+r', '+tr', 'w+', '+w', 'wt+', 'w+t', '+wt', 'tw+', 't+w', '+tw', 'a+', '+a', 'at+', 'a+t', '+at', 'ta+', 't+a', '+ta', 'x+', '+x', 'xt+', 'x+t', '+xt', 'tx+', 't+x', '+tx']\nxt.OpenTextModeWriting ~ xtyping.shed.OpenTextModeWriting ~ typing.Literal['w', 'wt', 'tw', 'a', 'at', 'ta', 'x', 'xt', 'tx']\nxt.Opt ~ xtyping.shed.Opt ~ typing.Optional\nxt.OptFloat ~ xtyping.shed.OptFloat ~ typing.Union[float, NoneType]\nxt.OptInt ~ xtyping.shed.OptInt ~ typing.Union[int, NoneType]\nxt.OptStr ~ xtyping.shed.OptStr ~ typing.Union[str, NoneType]\nxt.OptionalFloat ~ xtyping.shed.OptionalFloat ~ typing.Union[float, NoneType]\nxt.OptionalInt ~ xtyping.shed.OptionalInt ~ typing.Union[int, NoneType]\nxt.OptionalStr ~ xtyping.shed.OptionalStr ~ typing.Union[str, NoneType]\nxt.P ~ xtyping.shed.P ~ ~P\nxt.PT ~ xtyping.shed.PT ~ ~PT\nxt.Path ~ xtyping.shed.Path ~ <class 'pathlib.Path'>\nxt.PathLike ~ xtyping.shed.PathLike ~ <class 'os.PathLike'>\nxt.R ~ xtyping.shed.R ~ ~R\nxt.RT ~ xtyping.shed.RT ~ ~RT\nxt.ReturnT ~ xtyping.shed.ReturnT ~ ~ReturnT\nxt.ReturnType ~ xtyping.shed.ReturnType ~ ~ReturnType\nxt.STDIN ~ xtyping.shed.STDIN ~ typing.Union[bytes, str, NoneType]\nxt.STDIO ~ xtyping.shed.STDIO ~ typing.Union[NoneType, int, bytes, typing.IO[typing.Any]]\nxt.Self ~ xtyping.shed.Self ~ ~Self\nxt.Seq ~ xtyping.shed.Seq ~ typing.Sequence\nxt.SetAny ~ xtyping.shed.SetAny ~ typing.Set[typing.Any]\nxt.SetFloat ~ xtyping.shed.SetFloat ~ typing.Set[float]\nxt.SetInt ~ xtyping.shed.SetInt ~ typing.Set[int]\nxt.SetNumber ~ xtyping.shed.SetNumber ~ typing.Set[typing.Union[float, int]]\nxt.SetStr ~ xtyping.shed.SetStr ~ typing.Set[str]\nxt.SetT ~ xtyping.shed.SetT ~ typing.Set[~T]\nxt.ShapeType ~ xtyping.shed.ShapeType ~ typing.Tuple[int, ...]\nxt.StrBytes ~ xtyping.shed.StrBytes ~ typing.Union[str, bytes]\nxt.StrEnum ~ xtyping.shed.StrEnum ~ <enum 'StrEnum'>\nxt.StrIntFloat ~ xtyping.shed.StrIntFloat ~ typing.Union[str, float, int]\nxt.StrOrBytesPath ~ xtyping.shed.StrOrBytesPath ~ typing.Union[str, bytes, os.PathLike]\nxt.StrPath ~ xtyping.shed.StrPath ~ typing.Union[str, os.PathLike]\nxt.StringEnum ~ xtyping.shed.StringEnum ~ <enum 'StringEnum'>\nxt.T ~ xtyping.shed.T ~ ~T\nxt.TRUE ~ xtyping.shed.TRUE ~ typing.Literal[True]\nxt.T_ParamSpec ~ xtyping.shed.T_ParamSpec ~ ~T_ParamSpec\nxt.T_Retval ~ xtyping.shed.T_Retval ~ ~T_Retval\nxt.T_co ~ xtyping.shed.T_co ~ +T_co\nxt.T_contra ~ xtyping.shed.T_contra ~ -T_contra\nxt.TupleStrStr ~ xtyping.shed.TupleStrStr ~ typing.Tuple[str, str]\nxt.TupleStrs ~ xtyping.shed.TupleStrs ~ typing.Tuple[str, ...]\nxt.Txt ~ xtyping.shed.Txt ~ typing.Union[bytes, str]\nxt.U ~ xtyping.shed.U ~ typing.Union\nxt.VT ~ xtyping.shed.VT ~ ~VT\nxt.VT_co ~ xtyping.shed.VT_co ~ +VT_co\nxt.VT_contra ~ xtyping.shed.VT_contra ~ -VT_contra\nxt.V_co ~ xtyping.shed.V_co ~ +V_co\nxt.ValT ~ xtyping.shed.ValT ~ ~ValT\nxt.ValType ~ xtyping.shed.ValType ~ ~ValType\nxt.ZERO ~ xtyping.shed.ZERO ~ typing.Literal[False]\nxt._DT ~ xtyping.shed._DT ~ ~_DT\nxt._KT ~ xtyping.shed._KT ~ ~_KT\nxt._KT_co ~ xtyping.shed._KT_co ~ +_KT_co\nxt._KT_contra ~ xtyping.shed._KT_contra ~ -_KT_contra\nxt._R ~ xtyping.shed._R ~ ~_R\nxt._RT ~ xtyping.shed._RT ~ ~_RT\nxt._T ~ xtyping.shed._T ~ ~_T\nxt._T_co ~ xtyping.shed._T_co ~ +_T_co\nxt._T_contra ~ xtyping.shed._T_contra ~ -_T_contra\nxt._VT ~ xtyping.shed._VT ~ ~_VT\nxt._VT_co ~ xtyping.shed._VT_co ~ +_VT_co\nxt._VT_contra ~ xtyping.shed._VT_contra ~ -_VT_contra\nxt._V_co ~ xtyping.shed._V_co ~ +_V_co\nxt.__all_shed__ ~ xtyping.shed.__all_shed__ ~ ('AF', 'AFn', 'AnyAsyncCallable', 'AnyCallable', 'AnyFunction', 'AnyIterable', 'AnyIterator', 'ArrShape', 'ArrayShape', 'AsyncFn', 'AsyncFuncType', 'Bytes', 'BytesPath', 'CmdArgs', 'CmdArgsType', 'D', 'DT', 'DictAny', 'DictAnyAny', 'DictFloat', 'DictFloatFloat', 'DictInt', 'DictIntInt', 'DictNumber', 'DictNumberNumber', 'DictStr', 'DictStrAny', 'DictStrInt', 'DictStrStr', 'El', 'Element', 'Enum', 'EnvMap', 'EnvType', 'F', 'FALSE', 'FN', 'Flint', 'Fn', 'FsPath', 'FsPathLike', 'FuncType', 'HrTime', 'IntStr', 'IterableAny', 'IterableFloat', 'IterableInt', 'IterableNumber', 'IterableStr', 'IterableT', 'Json', 'JsonArrT', 'JsonDictT', 'JsonListT', 'JsonObjT', 'JsonPrimitive', 'JsonT', 'KT', 'KT_co', 'KT_contra', 'KeyT', 'KeyType', 'L', 'ListAny', 'ListFloat', 'ListInt', 'ListListStr', 'ListNumber', 'ListStr', 'ListT', 'Lit', 'Ls', 'N', 'NoneBytes', 'NoneStr', 'NoneStrBytes', 'NoneType', 'Null', 'Number', 'ONE', 'OpenBinaryMode', 'OpenBinaryModeReading', 'OpenBinaryModeUpdating', 'OpenBinaryModeWriting', 'OpenTextMode', 'OpenTextModeReading', 'OpenTextModeUpdating', 'OpenTextModeWriting', 'Opt', 'OptFloat', 'OptInt', 'OptStr', 'OptionalFloat', 'OptionalInt', 'OptionalStr', 'P', 'PT', 'Path', 'PathLike', 'R', 'RT', 'ReturnT', 'ReturnType', 'STDIN', 'STDIO', 'Self', 'Seq', 'SetAny', 'SetFloat', 'SetInt', 'SetNumber', 'SetStr', 'SetT', 'ShapeType', 'StrBytes', 'StrEnum', 'StrIntFloat', 'StrOrBytesPath', 'StrPath', 'StringEnum', 'T', 'TRUE', 'T_ParamSpec', 'T_Retval', 'T_co', 'T_contra', 'TupleStrStr', 'TupleStrs', 'Txt', 'U', 'VT', 'VT_co', 'VT_contra', 'V_co', 'ValT', 'ValType', 'ZERO', '_DT', '_KT', '_KT_co', '_KT_contra', '_R', '_RT', '_T', '_T_co', '_T_contra', '_VT', '_VT_co', '_VT_contra', '_V_co', '__all_shed__', '__all_typing__', '__all_typing_extensions__', '__all_typing_extensions_future__', 'null')\nxt.__all_typing__ ~ xtyping.shed.__all_typing__ ~ ('AbstractSet', 'Any', 'AnyStr', 'AsyncContextManager', 'AsyncGenerator', 'AsyncIterable', 'AsyncIterator', 'Awaitable', 'ByteString', 'Callable', 'ChainMap', 'ClassVar', 'Collection', 'Container', 'ContextManager', 'Coroutine', 'Counter', 'DefaultDict', 'Deque', 'Dict', 'FrozenSet', 'Generator', 'Generic', 'Hashable', 'IO', 'ItemsView', 'Iterable', 'Iterator', 'KeysView', 'List', 'Mapping', 'MappingView', 'MutableMapping', 'MutableSequence', 'MutableSet', 'NamedTuple', 'NewType', 'Optional', 'Reversible', 'Sequence', 'Set', 'Sized', 'SupportsAbs', 'SupportsBytes', 'SupportsComplex', 'SupportsFloat', 'SupportsInt', 'SupportsRound', 'TYPE_CHECKING', 'Text', 'Tuple', 'Type', 'TypeVar', 'Union', 'ValuesView', 'cast', 'get_type_hints', 'no_type_check', 'no_type_check_decorator', 'overload')\nxt.__all_typing_extensions__ ~ xtyping.shed.__all_typing_extensions__ ~ ('Annotated', 'AsyncContextManager', 'AsyncGenerator', 'AsyncIterable', 'AsyncIterator', 'Awaitable', 'ChainMap', 'ClassVar', 'Concatenate', 'ContextManager', 'Coroutine', 'Counter', 'DefaultDict', 'Deque', 'Final', 'IntVar', 'Literal', 'NewType', 'NoReturn', 'OrderedDict', 'ParamSpec', 'ParamSpecArgs', 'ParamSpecKwargs', 'Protocol', 'SupportsIndex', 'TYPE_CHECKING', 'Text', 'Type', 'TypeAlias', 'TypeGuard', 'TypedDict', 'final', 'get_args', 'get_origin', 'get_type_hints', 'overload', 'runtime', 'runtime_checkable')\nxt.__all_typing_extensions_future__ ~ xtyping.shed.__all_typing_extensions_future__ ~ ('LiteralString', 'Never', 'NotRequired', 'Required', 'Self', 'TypeVarTuple', 'Unpack', 'assert_never', 'assert_type', 'clear_overloads', 'dataclass_transform', 'get_overloads', 'is_typeddict', 'reveal_type')\nxt.null ~ xtyping.shed.null ~ <class 'NoneType'>"} +{"package": "xu", "pacakge-description": "xuCollection of handy random generators.classesobjectsfunctionsintegerbooleanpicknumbercharstringrandomExamplesfromxuimportstringprint(string(10).lower)print(string(10).upper)print(string(10).digit)print(string(10).alpha)print(string(10).latin)print(string(10).list(2))eoqsalszaj\nFCVYJZIDMY\n6712277415\noTrbOHkUbd\nNcrW4STecT\n['euZY9gFrzx', '0AEepSNvAO']fromxuimportbooleanforitinboolean.matrix(2,4):print(it)[False, True]\n[True, False]\n[True, True]\n[False, False]fromxuimportpickdata=[1,2,3,4]print(pick(data))data='1234'print(pick(data,2))3\n['2', '3']fromxuimportintegerprint(integer(9)*5)print()forrowininteger(9)**5:print(row)print()forrowininteger(9)**(5,3):print(row)[4, 9, 1, 3, 5]\n\n[4, 2, 0, 8, 8]\n[0, 3, 9, 4, 2]\n[5, 1, 1, 8, 2]\n[1, 5, 3, 5, 6]\n[6, 1, 1, 0, 2]\n\n[1, 1, 6, 1, 8]\n[4, 0, 2, 3, 9]\n[1, 5, 7, 2, 4]"} +{"package": "xu2net", "pacakge-description": "U2-Net: U Square NetThis is the official repo for our paperU2-Net(U square net)published in Pattern Recognition 2020:U2-Net: Going Deeper with Nested U-Structure for Salient Object DetectionXuebin Qin,Zichen Zhang,Chenyang Huang,Masood Dehghan,Osmar R. ZaianeandMartin JagersandContact: xuebin[at]ualberta[dot]caUpdates !!!(2021-Aug-24)We played a bit more about fusing the orignal image and the generated portraits to composite different styles. You can(1) Download this repo bygit clone https://github.com/NathanUA/U-2-Net.git(2) Download the u2net_portrait.pth fromGoogleDriveorBaidu Pan(\u63d0\u53d6\u7801\uff1achgd)model and put it into the directory:./saved_models/u2net_portrait/,(3) run the code by commandpython u2net_portrait_composite.py -s 20 -a 0.5,where-sindicates the sigma of gaussian function for blurring the orignal image and-adenotes the alpha weights of the orignal image when fusing them.(2021-July-16)A newbackground removal webappdeveloped by \u0418\u0437\u0430\u0442\u043e\u043f \u0412\u0430\u0441\u0438\u043b\u0438\u0439.(2021-May-26)ThankDang Quoc Quyfor hisArt Transfer APPbuilt upon U2-Net.(2021-May-5)ThankAK391for sharing hisGradio Web Demo of U2-Net.(2021-Apr-29)ThanksJonathan Benavides Vallejofor releasing his AppLensOCR: Extract Text & Image, which uses U2-Net for extracting the image foreground.(2021-Apr-18)ThanksAndrea Scuderifor releasing his AppClipping Camera, which is an U2-Net driven realtime camera app and \"is able to detect relevant object from the scene and clip them to apply fancy filters\".(2021-Mar-17)Dennis Bappertre-trained the U2-Net model forhuman portrait matting. The results look very promising and he also provided the details of the training process and data generation(and augmentation) strategy, which are inspiring.(2021-Mar-11)Dr. Tim developed avideo version rembgfor removing video backgrounds using U2-Net. The awesome demo results can be found onYouTube.(2021-Mar-02)We found some other interesting applications of our U2-Net includingMOJO CUT,Real-Time Background Removal on Iphone,Video Background Removal,Another Online Portrait Generation Demo on AWS,AI Scissor.(2021-Feb-15)We just released an online demohttp://profu.aifor the portrait generation. Please feel free to give it a try and provide any suggestions or comments.(2021-Feb-06)Recently, some people asked the problem of using U2-Net for human segmentation, so we trained another example model for human segemntation based onSupervisely Person Dataset.(1) To run the human segmentation model, please first downlowd theu2net_human_seg.pthmodel weights into./saved_models/u2net_human_seg/.(2) Prepare the to-be-segmented images into the corresponding directory, e.g../test_data/test_human_images/.(3) Run the inference by command:python u2net_human_seg_test.pyand the results will be output into the corresponding dirctory, e.g../test_data/u2net_test_human_images_results/Notes: Due to the labeling accuracy of the Supervisely Person Dataset, the human segmentation model (u2net_human_seg.pth) here won't give you hair-level accuracy. But it should be more robust than u2net trained with DUTS-TR dataset on general human segmentation task. It can be used for human portrait segmentation, human body segmentation, etc.(2020-Dec-28)Some interesting applications and useful tools based on U2-Net:(1)Xiaolong Liudeveloped several very interesting applications based on U2-Net includingHuman Portrait Drawing(As far as I know, Xiaolong is the first one who uses U2-Net for portrait generation),image mattingandso on.(2)Vladimir Seregindeveloped an interesting tool,NN based lineart, for comparing the portrait results of U2-Net and that of another popular model,ArtLine, developed byVijish Madhavan.(3)Daniel Gatisbuilt a python tool,Rembg, for image backgrounds removal based on U2-Net. I think this tool will greatly facilitate the application of U2-Net in different fields.(2020-Nov-21)Recently, we found an interesting application of U2-Net forhuman portrait drawing. Therefore, we trained another model for this task based on theAPDrawingGAN dataset.Usage for portrait generationClone this repo to localgit clone https://github.com/NathanUA/U-2-Net.gitDownload the u2net_portrait.pth fromGoogleDriveorBaidu Pan(\u63d0\u53d6\u7801\uff1achgd)model and put it into the directory:./saved_models/u2net_portrait/.Run on the testing set.(1) Download the train and test set fromAPDrawingGAN. These images and their ground truth are stitched side-by-side (512x1024). You need to split each of these images into two 512x512 images and put them into./test_data/test_portrait_images/portrait_im/. You can also download the split testing set onGoogleDrive.(2) Running the inference with commandpython u2net_portrait_test.pywill ouptut the results into./test_data/test_portrait_images/portrait_results.Run on your own dataset.(1) Prepare your images and put them into./test_data/test_portrait_images/your_portrait_im/.To obtain enough details of the protrait, human head region in the input image should be close to or larger than 512x512. The head background should be relatively clear.(2) Run the prediction by commandpython u2net_portrait_demo.pywill outputs the results to./test_data/test_portrait_images/your_portrait_results/.(3) The difference betweenpython u2net_portrait_demo.pyandpython u2net_portrait_test.pyis that we added a simpleface detectionstep before the portrait generation inu2net_portrait_demo.py. Because the testing set of APDrawingGAN are normalized and cropped to 512x512 for including only heads of humans, while our own dataset may varies with different resolutions and contents. Therefore, the codepython u2net_portrait_demo.pywill detect the biggest face from the given image and then crop, pad and resize the ROI to 512x512 for feeding to the network. The following figure shows how to take your own photos for generating high quality portraits.(2020-Sep-13)Our U2-Net based model is the6thinMICCAI 2020 Thyroid Nodule Segmentation Challenge.(2020-May-18)The official paper of ourU2-Net (U square net)(PDF in elsevier(free until July 5 2020),PDF in arxiv) is now available. If you are not able to access that, please feel free to drop me an email.(2020-May-16)We fixed the upsampling issue of the network. Now, the model should be able to handlearbitrary input size. (Tips: This modification is to facilitate the retraining of U2-Net on your own datasets. When using our pre-trained model on SOD datasets, please keep the input size as 320x320 to guarantee the performance.)(2020-May-16)We highly appreciateCyril Diagnefor building this fantastic AR project:AR Copy and Pasteusing ourU2-Net(Qinet al, PR 2020) andBASNet(Qinet al, CVPR 2019). Thedemo videoin twitter has achieved over5Mviews, which is phenomenal and shows us more application possibilities of SOD.U2-Net Results (176.3 MB)Our previous work:BASNet (CVPR 2019)Required librariesPython 3.6numpy 1.15.2scikit-image 0.14.0python-opencv\nPIL 5.2.0PyTorch 0.4.0torchvision 0.2.1globUsage for salient object detectionClone this repogit clone https://github.com/NathanUA/U-2-Net.gitDownload the pre-trained model u2net.pth (176.3 MB) fromGoogleDriveorBaidu Pan \u63d0\u53d6\u7801: pf9kor u2netp.pth (4.7 MB) fromGoogleDriveorBaidu Pan \u63d0\u53d6\u7801: 8xsiand put it into the dirctory './saved_models/u2net/' and './saved_models/u2netp/'Cd to the directory 'U-2-Net', run the train or inference process by command:python u2net_train.pyorpython u2net_test.pyrespectively. The 'model_name' in both files can be changed to 'u2net' or 'u2netp' for using different models.We also provide the predicted saliency maps (u2net results,u2netp results) for datasets SOD, ECSSD, DUT-OMRON, PASCAL-S, HKU-IS and DUTS-TE.U2-Net ArchitectureQuantitative ComparisonQualitative ComparisonCitation@InProceedings{Qin_2020_PR,\ntitle = {U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection},\nauthor = {Qin, Xuebin and Zhang, Zichen and Huang, Chenyang and Dehghan, Masood and Zaiane, Osmar and Jagersand, Martin},\njournal = {Pattern Recognition},\nvolume = {106},\npages = {107404},\nyear = {2020}\n}"} +{"package": "xuance", "pacakge-description": "No description available on PyPI."} +{"package": "xuantie-qemu", "pacakge-description": "No description available on PyPI."} +{"package": "xuanzoupdf", "pacakge-description": "This is the homepage of our project"} +{"package": "xuanzouword", "pacakge-description": "Hello XuanZouWord"} +{"package": "xuanzouword2", "pacakge-description": "Hello XuanZouWord"} +{"package": "xubib", "pacakge-description": "bibbib is a special library, which aims to organize and standardize bib files, so as to facilitate relevant personnel to read and find the information in the files.The following modules are available. These contain some functions, that can be used by your own codebase.bibcopy.PythonList - \u5982\u4f55\u5982\u4f55\u3002bibcopy.qiyuhanshu - \u5982\u4f55\u5982We build and maintain bib, so if we encounter bugs in the process of using it, we can provide relevant information to937207118@qq.com.See thestorehousefor guidelines and code references for using bib.[Compatibility]bib 1.0.6 supports Python3.[Installing Bib]We provide complete source code, so you can download all the relevant information of bib.Instructions are as follows\uff1apip install TestThen in py file, through instruction\uff1afrom fb inmport bibcopyIn this way, you can use the functions described above.[Contributing]Are you a developer? Do you want to integrate bib into your project and contribute back? Great! Just do it and if you have any questions, please contact me throughit."} +{"package": "xubotest", "pacakge-description": "UNKNOWN"} +{"package": "xuchangxin", "pacakge-description": "No description available on PyPI."} +{"package": "xuderong", "pacakge-description": "No description available on PyPI."} +{"package": "xudo", "pacakge-description": "A quality of life tool to help bring up docker containers, access docker logs, generate jooq, run tests and moreInstallationpip3 install xudoorpython3 setup.py installto install with local filesChange/Users/ostralyan/devto the absolute path of where the hbng folder is stored:echo '/Users/ostralyan/dev' >~/.xudo_profileUsagexudo logs [api | changelog | migrations]- This will follow the logs of the chosen containerxudo pull- Pulls the Elastic Search and MySQL contianersxudo build[-c-m-s-a-x]- Deletes the corresponding process(es) and the image(s) and builds the container from scratch-c: Changelog-m: Migrations-s: Sql-a: Api-x: Api no cachexudo test (be | app | admin | core | it)- Runs the backend, frontend or integration testsbe: Backendit: Integration Testsxudo watch- Watches hbngxudo clean- Removes all dangling containersxudo prune- Prompts to removeall stopped containersall networks not used by at least one containerall dangling imagesall build cachexudo-h|--help- Shows the help screenxudo--version- Shows the versionPushing to Pypicd /path/to/xudo-clirm -rf dist/python setup.py sdist bdist_wheeltwine upload dist/*"} +{"package": "xudoku", "pacakge-description": "xudoku - Solve sudoku using an 'exact cover' algorithmThis is the sudoku code from @moygit's project 'exact_cover_np'.The package is maintained by me, @jwg4.I separated the code for the 'exact cover' algorithm (now available athttps://github.com/jwg4/exact_cover) from the sudoku code and created this package. At that package you can find more info about the exact cover algorithm, which can be used for lots of combinatoric problems.How to use the package>>> import xudoku\n>>> s = xudoku.Sudoku(9)\n>>> s.read(\"tests/files/insight.csv\")\n>>> sol = s.solve()\n>>> sol._sudo.tolist()\n[[1, 3, 5, 2, 9, 7, 8, 6, 4], [9, 8, 2, 4, 1, 6, 7, 5, 3], [7, 6, 4, 3, 8, 5, 1, 9, 2], [2, 1, 8, 7, 3, 9, 6, 4, 5], [5, 9, 7, 8, 6, 4, 2, 3, 1], [6, 4, 3, 1, 5, 2, 9, 7, 8], [4, 2, 6, 5, 7, 1, 3, 8, 9], [3, 5, 9, 6, 2, 8, 4, 1, 7], [8, 7, 1, 9, 4, 3, 5, 2, 6]]\n>>> s._hardness\n'Easy'Currently the puzzle data can only be read from CSV. You could useio.StringIO, which turns a string into a file-like object, if you want to generate your sudoku puzzle in code."} +{"package": "xud-wizard", "pacakge-description": "xud-wizardA wrapper program for xud-docker."} +{"package": "xueanquan", "pacakge-description": "No description available on PyPI."} +{"package": "xuebadb", "pacakge-description": "xuebadbTravis CI Status:xuebadbis a python package that allows users to conveniently connect to and query from various database systems using a unified API. Currently, it supports connecting toMySQLandSQL Serverdatabase systems. The queries return Pandas dataframes which can then be cleaned up and analysed using one of the modules in the package.Requirements:In order to be able to use the package, you would have to install the following:Python packages:pyodbcmysql-connectorpandasnumpymissingnomatplotlibMicrosoft ODBC Driver 17Package structure:xuebadb --> package-- dbgeneric --> sub-package-- db_interface --> module-- mysql_interface -->module-- odbc_interface --> module-- dfanalysis --> sub-package-- cleanup --> module-- stats --> module"} +{"package": "xuefei", "pacakge-description": "\u522b\u89c9\u5f97\u81ea\u5df1\u5389\u5bb3"} +{"package": "xuelang-1", "pacakge-description": "No description available on PyPI."} +{"package": "xueqiu", "pacakge-description": "xueqiua humanize XueQiu API wrappers.Installation1.First, you need to install some basic components.git-scmpython3nodejs(needsnodecommand in the PATH variable)2.And then, installGoogle Chrome BrowserandChrome Driver.>copychromedriver.exe%LOCALAPPDATA%\\Programs\\Python\\Python37-32\\3.Finally, installxueqiuviapip.$pipinstallxueqiu# OR git+https://github.com/1dot75cm/xueqiu@master$pipinstallgit+https://github.com/1dot75cm/browsercookie@master\n$python3-mxueqiu\nxueqiux.y.z-AhumanizeXueQiuAPIwrappers.\n\n:copyright:(c)2019by1dot75cm.\n:license:MIT,seeLICENSEformoredetails.enjoy!!!Quick startExample:>>>news=xueqiu.news()# watch the news>>>news{'list':[<xueqiu.Post\u4e3a\u4f55\u4ef7\u503c\u6295\u8d44\u957f\u671f\u6709\u6548[https://xueqiu.com/8291461932/120351059]>,<xueqiu.Post\u97ec\u8574\u8d44\u672cCEO\u6e29\u6653\u4e1c\u6012\u65a5\u8d3e\u8dc3\u4ead\uff1a\u600e\u5c31\u4e00\u4e2a[https://xueqiu.com/2095268812/120483699]>,<xueqiu.Post\u589e\u6301\u4e0e\u56de\u8d2d20190122-201901[https://xueqiu.com/9206540776/120458648]>,<xueqiu.Post\u533b\u836f\u7814\u53d1\u5916\u5305\u4e3a\u4ec0\u4e48\u8fd9\u4e48\u7ea2?(\u4e0a)[https://xueqiu.com/1472391509/120481662]>,<xueqiu.Post\u533b\u836f\u5927\u8d5b\u9053\u4e4b\u5927\u5206\u5b50\u751f\u7269\u836f\uff08\u4e0b\uff09[https://xueqiu.com/1472391509/120482094]>,<xueqiu.Post\u589e\u5f3a\u578b\u6307\u6570\u57fa\u91d1\uff0c\u5230\u5e95\u201c\u5f3a\u201d\u5728\u54ea\u91cc\uff1f[https://xueqiu.com/8082119199/120480761]>,<xueqiu.Post\u4ef7\u503c\u6295\u8d44\u4e0d\u9700\u8981\u6982\u7387\u601d\u7ef4\u5417\uff1f\u2014\u4e0e\u8463\u5b9d\u73cd\u5148\u751f[https://xueqiu.com/3555476733/120245234]>,<xueqiu.Post\u9093\u6653\u5cf0\u7684\u6295\u8d44\u89c2[https://xueqiu.com/7649503965/120430145]>,<xueqiu.Post\u590d\u5229\u65e0\u654c\uff1a\u4e70\u5165\u4e00\u53ea\u80a1\u7968\u770b\u8fd9\u56db\u70b9[https://xueqiu.com/1876906471/120479202]>,<xueqiu.Post\u518d\u8bba\u5b89\u5168\u8fb9\u9645[https://xueqiu.com/4465952737/120453192]>],'next_max_id':20323343}>>>p=news['list'][0]>>>\"{}{}\u8d5e{}\u8bc4\u8bba{}\u8f6c\u53d1{}{}\".format(p.title,p.user.name,p.like_count,p.reply_count,p.retweet_count,p.target)'\u4e3a\u4f55\u4ef7\u503c\u6295\u8d44\u957f\u671f\u6709\u6548 \u623f\u6768\u51ef\u7684\u6295\u8d44\u4e16\u754c \u8d5e9 \u8bc4\u8bba11 \u8f6c\u53d19 https://xueqiu.com/8291461932/120351059'>>>p.user.get_posts()# get user's article>>>p.user.posts{'count':622,'page':1,'maxpage':63,'list':[<xueqiu.Post[https://xueqiu.com/8291461932/120497097]>,<xueqiu.Post[https://xueqiu.com/8291461932/120491351]>,<xueqiu.Post[https://xueqiu.com/8291461932/120487476]>,<xueqiu.Post[https://xueqiu.com/8291461932/120487448]>,<xueqiu.Post[https://xueqiu.com/8291461932/120486037]>,<xueqiu.Post\u817e\u8baf\u6e38\u620f\u5e1d\u56fd\u7684\u62a4\u57ce\u6cb3\u8fd8\u5728\u5417\uff1f[https://xueqiu.com/8291461932/120485596]>,<xueqiu.Post[https://xueqiu.com/8291461932/120473933]>,<xueqiu.Post[https://xueqiu.com/8291461932/120434054]>,<xueqiu.Post[https://xueqiu.com/8291461932/120434037]>,<xueqiu.Post[https://xueqiu.com/8291461932/120434020]>]}>>>p.user.posts['list'][0].text# content'\u56de\u590d@A8\u5929\u9053\u916c\u52e4: \u8fd9\u4e2a\u95ee\u9898\u5e94\u8be5\u653e\u5728\u4e70\u4e4b\u524d\u3002//@A8\u5929\u9053\u916c\u52e4:\u56de\u590d@\u623f\u6768\u51ef\u7684\u6295\u8d44\u4e16\u754c:\u5047\u5982\u82b1\u65d7\u94f6\u884c\u505a\u5047\u8d26\uff0c\u8042\u592b\u8fd8\u4f1a\u4e0d\u4f1a\u6301\u6709\uff1f'>>>p.user.posts['list'][0].like()# like this (need login)APIUser classA user class that contains user-related methods.User object attributes:id- user id.profile- user's profile url.name- user name.city- city, for example '\u4e0a\u6d77'.description- user description.friends_count- the number of user's friends.followers_count- the number of user's fans.posts_count- the number of user's post.stocks_count- the number of stocks.friends- use to saveUserobject for friends.followers- use the saveUserobject for fans.posts- use the savePostobject for post.articles- use the savePostobject for user's article.favorites- use the savePostobject for favorite articles.stocks- use the saveStockobject for favorite stocks.hot_stocks- use the saveStockobject for the current hot stocks.User object methods:get_friends(page: int = 1)- get your friends and save toself.friends.get_followers(page: int = 1)- get your fans and save toself.followers.get_posts(page: int = 1, count: int = 10)- get your posts and save toself.posts.get_articles(page: int = 1, count: int = 10)- get your articles and save toself.articles.get_favorites(page: int = 1, count: int = 20)- get your favorite posts and save toself.favorites.get_stocks(mkt: int = 1, count: int = 1000)- get your stocks and save toself.stocks.get_hot_stocks(mkt: int = 10, time_range: str = \"hour\", count: int = 10)- get hottest stocks.:parammkt: (optional) market type, default is10.value: \u5168\u740310\u6caa\u6df112\u6e2f\u80a113\u7f8e\u80a111:paramtime_range: (optional) hottest stocks by time range, default ishour.value:hour,day:paramcount: (optional) the number of results, default is10.send_verification_code(phone: int)- send verification code to your phone.Note: only 5 times a day.login(uid: str = '', passwd: str = '', login_type: str = 'phone')- user login by password or verification code. If the cookie cache exists, load it first and return. Otherwise, login and save the cookie to file (Linux~/.xueqiu/cookieor Windows).:paramuid: your username or phone number.:parampasswd: your password or verification code.:paramlogin_type: (optional) login type, default isphone.value:password,phoneload_cookie()- load cookies from local file or browser(chrome or firefox). You can login your account on the chrome browser, then executeload_cookie(), and now login successfully.Example:>>>u=User(2478797769)>>>u.name\"\u7ea2\u5229\u57fa\u91d1\">>>u.get_posts()>>>u.posts['list'][0].title'\u3010\u4f60\u4e86\u89e3\u7ea2\u5229\u57fa\u91d1\u5417\u3011\u7ea2\u5229\u57fa\u91d1\uff08501029\uff09\u70ed\u95ee\u5feb\u7b54\uff01\uff0812.31\uff09'>>>u.get_favorites()>>>u.favorites['list'][0].title'2018\u5e74A\u80a1\u5927\u6570\u636e\u76d8\u70b9\uff1a30\u5f20\u56fe\u5c3d\u89c8\u5e02\u573a\u70ed\u70b9'Post classA post class that contains post-related methods.Post object attributes:id- post id.user- post authors. aUserclass object.created_at- created time. aArrowclass object.target- post url.view_count- view count.reply_count- reply count.retweet_count- retweet count.fav_count- favorites count.like_count- like count.title- post title.text- post content.full_text- the full content of the article.comments- use the saveCommentobject for post.Post object methods:get_content()- get article content and save toself.full_text.get_comments(page: int = 1, count: int = 20, asc: str = 'false')- get article comments and save toself.comments.like()- like the article. (require login)unlike()- unlike the article. (require login)favorite()- favorite the article. (require login)unfavorite()- unfavorite the article. (require login)Example:>>>p=Post('2478797769/78869335')>>>p.user.name\"\u7ea2\u5229\u57fa\u91d1\">>>p.created_at.format(\"YYYY-MM-DD\")\"2016-12-13\">>>p.title'\u3010\u4f60\u4e86\u89e3\u7ea2\u5229\u57fa\u91d1\u5417\u3011\u7ea2\u5229\u57fa\u91d1\uff08501029\uff09\u70ed\u95ee\u5feb\u7b54\uff01\uff0812.31\uff09'>>>p.target\"https://xueqiu.com/2478797769/78869335\">>>p.get_content()>>>p.full_text'\u76ee\u5f55\uff1a\\n\u4e00\u3001\\n\u534e\u5b9d\u6807\u666e\u4e2d\u56fdA\u80a1\u7ea2\u5229\u673a\u4f1a\u6307\u6570\u8bc1\u5238\u6295\u8d44\u57fa\u91d1\\n......'>>>p.get_comments()>>>p.comments['list'][-1].text'\u4e3a\u4ec0\u4e48\u6210\u4efd\u80a1\u4e2d\u6709\u5f88\u591a\u6b21\u65b0\u80a1\uff1f\u767e\u601d\u4e0d\u5f97\u5176\u89e3'Comment classA comment class that contains comment-related methods.Comment object attributes:id- comment id.user- comment authors. aUserclass object.post- comment on an article. aPostclass object.created_at- created time. aArrowclass object.like_count- like count.text- comment content.Comment object methods:like()- like the comment. (require login)unlike()- unlike the comment. (require login)Example:>>>p=Post('2478797769/78869335')>>>p.get_comments()>>>c=p.comments['list'][0]>>>c.user.name'\u7ea2\u5229\u57fa\u91d1'>>>c.text'\u56de\u590d@\u5b59\u6d69\u4e91: \u600e\u4e48\u53ef\u80fd....2018\u5e74\u8dcc\u5e45\u4e3a24.54%\uff0c\u8f83\u4e3b\u6d41\u6307\u6570\u8dcc\u5e45\u8f83\u5c0f\u3002\u4e0d\u77e5\u9053\u60a850%\u591a\u662f\u54ea\u513f\u770b\u6765\u7684\u5462'Selector classTheSelectorclass implements a stock filter.Selector object attributes:market- market string, default isSH.value:SH,HK,USqueries- include default parameters with selector.Selector object methods:url()- return a selector url string.help(range: str = \"base\", show: str = \"text\")- show selector parameters.:paramrange: (optional) parameters range, default isbase.\nvalue:SH: industries, areas, base, ball, quota, finan_rate, stock_data,\nprofit_sheet, balance_sheet, cash_sheetHK: industries, base, ball, quotaUS: industries, base, ball, quota, grow,\nprofit_sheet, balance_sheet, cash_sheet:paramshow: (optional) output help or return generator, default istext.value:text,keysscope(exchange: str = '', indcode: str = '', areacode: str = '')- set stock selector scope.:paramexchange: (optional) set A-share exchange market, default isNone.value:SH,SZorNone:paramindcode: (optional) set industry code, default isNone. please seeself.help('industries'):paramareacode: (optional) set area code, default isNone. please seeself.help('areas')param(*args, **kwargs)- set stock selector paramters.:param*args: (optional) set parameters key, default value isALL.\nfor example, theself.param('pb', 'mc')will be setpb=ALL&mc=ALLparams.:param**kwargs: (optional) set parameters key and value.\nfor example, theself.param('pettm'=0_30)will be setpettm=0_30param.orderby(key: str = 'symbol')- stock selector results are sorted by field.:paramkey: the results are sorted by thekey, default issymbol.\nthe key parameters can be viewed throughself.help('base').order(ord: str = 'desc')- set stock selector results are sorted.:paramord: the ascending and descending order, default isdesc.value:asc,descpage(page: int = 1)- set stock selector results page number.count(size: int = 10)- the number of stock selector results.run()- sends a stock screener request and return[Stock class]list.Example:>>>s=Selector(\"SH\")# scope \u6df1\u5e02\uff0c\u623f\u5730\u4ea7\uff0c\u6d59\u6c5f\u5730\u533a# param \u7b5b\u9009\u603b\u5e02\u503c\uff0c18\u5e743\u5b63\u5ea6ROE 0-30%# orderby \u6309\u5e02\u503c\u6392\u5e8f# order \u5347\u5e8f\u6392\u5217# page \u7b2c2\u9875# count \u6bcf\u98752\u4e2a>>>result=s.scope('SZ','K70','CN330000').param('mc',roediluted_20180930='0_30').orderby('mc').order('asc').page(2).count(2).run()>>>result['list'][<xueqiu.Stock\u8363\u5b89\u5730\u4ea7[SZ000517]>,<xueqiu.Stock\u6ee8\u6c5f\u96c6\u56e2[SZ002244]>]Stock classA stock class that contains stock-related methods.Stock object attributes:basesymbol- stock symbol.code- stock code.name- stock name.current- current price.current_year_percent- current year return.percent- change rate.chg- change amount.open- price today.last_close- last close.high- highest.low- lowest.avg_price- average price.volume- trading volume.amount- amount.turnover_rate- turnover rate.amplitude- amplitude.market_capital- market capital.float_market_capital- float market capital.total_shares- total shares.float_shares- float shares.currency- currency unit.exchange- stock exchange.issue_date- launch date. aArrowclass object.extendlimit_up- stock limit up.limit_down- stock limit down.high52w- the highest of the fifty-two weeks.low52w- the lowest of the fifty-two weeks.volume_ratio- volume ratio.pe_lyr- pe lyr.pe_ttm- pe ttm.pe_forecast- pe forecast.pb- price/book value ratio.eps- earnings per share.bps- net asset value per share.dividend- stock dividend.dividend_yield- stock dividend yield.profit- net profit.profit_forecast- profit forecast.profit_four- profit last four quarters.otherstime- current time. aArrowclass object.posts- used to the savePostobject for stock.followers- used to the saveUserobject for stock's fans.prousers- used to the saveUserobject for stock's professional users.popstocks- pop stocks.industries- industry stocks.history- stock history.Stock object methods:refresh(dt: dict = {})- get current stock data and updateself.time.get_posts(page: int = 1, count: int = 20, sort: str = \"time\", source: str = \"all\")- get stock posts and save toself.posts.:parampage: (optional) page number, default is1.:paramcount: (optional) the number of results, default is20.:paramsort: (optional) order type, default istime.value:time\u6700\u65b0,reply\u8bc4\u8bba,relevance\u9ed8\u8ba4:paramsource: (optional) source of the results, default isall.value:all,user\u8ba8\u8bba,news\u65b0\u95fb,notice\u516c\u544a,trans\u4ea4\u6613get_followers(page: int = 1, count: int = 15)- get stock fans and save toself.followers.:parampage: (optional) page number, default is1.:paramcount: (optional) the number of results, default is15.get_prousers(count: int = 5)- get stock professional users and save toself.prousers.get_popstocks(count: int = 8)- get pop stocks and save toself.popstocks.get_industry_stocks(count: int = 8)- get industry stocks and save toself.industries.get_histories(begin: str = '-1m', end: str = arrow.now(), period: str = 'day')- get stock history data and save toself.history.:parambegin: the start date of the results.value: -1w -2w -1m -3m -6m -1y -2y -3y -5y cyear issue or YYYY-MM-DD:paramend: (optional) the end date of the results, default isnow.:paramperiod: (optional) set date period, default isday.value: day week month quarter year 120m 60m 30m 15m 5m 1mincome(quarter: str = 'all', count: int = 12, lang: str = 'cn')- get stock income sheet.balance(quarter: str = 'all', count: int = 12, lang: str = 'cn')- get stock balance sheet.cash_flow(quarter: str = 'all', count: int = 12, lang: str = 'cn')- get stock cash flow sheet.Example:>>>s=Stock(\"SH601318\")>>>s.symbol\"SH601318\">>>s.name\"\u4e2d\u56fd\u5e73\u5b89\">>>s.market_capital1119664786363.0>>>s.issue_date.format(\"YYYY-MM-DD\")\"2007-02-28\">>>s.refresh()# update stock data>>>s.get_posts(){'count':188745,'page':1,'maxpage':100,'list':[<xueqiu.Post[https://xueqiu.com/1566609429/120543602]>,<xueqiu.Post[https://xueqiu.com/1083048635/120542397]>,<xueqiu.Post[https://xueqiu.com/6376335219/120542355]>,<xueqiu.Post[https://xueqiu.com/8335420516/120542213]>,<xueqiu.Post[https://xueqiu.com/2706248223/120542082]>,<xueqiu.Post[https://xueqiu.com/4298761680/120542015]>,<xueqiu.Post[https://xueqiu.com/2856403580/120541995]>,<xueqiu.Post[https://xueqiu.com/6122867052/120541786]>,<xueqiu.Post[https://xueqiu.com/1083048635/120541288]>,<xueqiu.Post[https://xueqiu.com/9598902646/120541255]>]}>>>s.get_popstocks()>>>s.popstocks[<xueqiu.Stock\u62db\u5546\u94f6\u884c[SH600036]>,<xueqiu.Stock\u5174\u4e1a\u94f6\u884c[SH601166]>,<xueqiu.Stock\u6c11\u751f\u94f6\u884c[SH600016]>,<xueqiu.Stock\u8d35\u5dde\u8305\u53f0[SH600519]>,<xueqiu.Stock\u82cf\u5b81\u6613\u8d2d[SZ002024]>,<xueqiu.Stock\u4e07\u79d1A[SZ000002]>,<xueqiu.Stock\u817e\u8baf\u63a7\u80a1[00700]>,<xueqiu.Stock\u4e2d\u7eff[02988]>]>>>s.get_industry_stocks()>>>s.industries{'industryname':'\u975e\u94f6\u91d1\u878d','list':[<xueqiu.Stock\u4e5d\u9f0e\u6295\u8d44[SH600053]>,<xueqiu.Stock\u534e\u6797\u8bc1\u5238[SZ002945]>,<xueqiu.Stock\u7231\u5efa\u96c6\u56e2[SH600643]>,<xueqiu.Stock\u4e2d\u822a\u8d44\u672c[SH600705]>,<xueqiu.Stock\u534e\u94c1\u79d1\u6280[SH603300]>,<xueqiu.Stock\u6c11\u751f\u63a7\u80a1[SZ000416]>,<xueqiu.Stock\u718a\u732b\u91d1\u63a7[SH600599]>,<xueqiu.Stock\u5b8f\u6e90\u8bc1\u5238[SZ000562]>]}>>>s.get_histories('2019-01-07','2019-01-11')>>>s.history.iloc[:,0:8]datevolumeopenhighlowclosechgpercentturnoverrate2019-01-077659300757.0957.1755.9056.30-0.29-0.510.702019-01-085599209256.0556.0955.2055.80-0.50-0.890.512019-01-098191461356.2057.6055.9656.951.152.060.752019-01-106732822356.8757.8256.5557.500.550.970.612019-01-114575697358.0058.2957.5058.070.570.990.42>>>s.history.iloc[:,8:17]datema5ma10ma20ma30pepbpspcfmarket_capital2019-01-0755.97056.88559.252060.714310.0731.9491.0519723.5360001.029178e+122019-01-0855.91056.63158.892060.48639.9841.9321.0426293.5045971.020037e+122019-01-0956.26456.50158.630560.278010.1901.9721.0641173.5768241.041060e+122019-01-1056.62856.43058.397060.091010.2881.9911.0743943.6113681.051114e+122019-01-1156.92456.50758.177559.901010.3902.0111.0850443.6471671.061534e+12>>>s.get_histories('-1w')>>>s.history.iloc[:,0:8]datevolumeopenhighlowclosechgpercentturnoverrate2019-01-244494061859.6160.5259.2260.430.941.580.412019-01-256724591160.5061.7860.4361.290.861.420.622019-01-285816488461.8062.4161.2061.520.230.380.532019-01-293951929461.3861.9060.9861.650.130.210.362019-01-303100032360.8861.8660.7861.25-0.40-0.650.27>>>s.get_histories('-1y')>>>s.history[['pe','pb','ps']].describe()pepbpscount243.000000243.000000243.000000mean11.8405882.2739961.217041std1.3574890.2152170.110052min9.7289001.9110001.03104425%10.8494502.1432001.15055450%11.5049002.2373001.19770075%12.6286002.3452001.251150max15.5967002.9354001.559700>>>s.income()[['\u51c0\u5229\u6da6','\u8425\u4e1a\u603b\u6536\u5165']]report_name\u51c0\u5229\u6da6\u8425\u4e1a\u603b\u6536\u51652018Q38.948900e+107.504560e+112018Q26.477000e+105.348140e+112018Q12.895100e+103.104520e+112017Q49.997800e+108.908820e+11...>>>s.balance()[['\u8d44\u4ea7\u5408\u8ba1','\u8d1f\u503a\u5408\u8ba1']]report_name\u8d44\u4ea7\u5408\u8ba1\u8d1f\u503a\u5408\u8ba12018Q36.910935e+126.260499e+122018Q26.851431e+126.216339e+122018Q16.725766e+126.108353e+122017Q46.493075e+125.905158e+12...>>>s.cash_flow()['\u7ecf\u8425\u6d3b\u52a8\u73b0\u91d1\u6d41\u91cf\u51c0\u989d']report_name\u7ecf\u8425\u6d3b\u52a8\u73b0\u91d1\u6d41\u91cf\u51c0\u989d2018Q31.775950e+112018Q21.616070e+112018Q11.398670e+112017Q41.212830e+11...Fund classA fund class that contains fund-related methods.Fund object attributes:fund_nav- fund net value.fund_nav_guess- estimate value.fund_nav_premium- fund nav premium rate.fund_history- fund history.fund_stocks- component stocks.fund_weight- stocks weight.Fund object methods:get_fund_stocks(year: str = \"\", mouth: str = \"12\")- get fund's stocks from\u5929\u5929\u57fa\u91d1.get_fund_nav()- get fund nav.get_fund_histories(page: int = 1, size: int = 90)- get history fund nav.calc_premium()- calculate fund premium.refresh_all()- refresh all of the fund stock objects.Example:>>>f=Fund('501301')>>>f.symbol\"SH501301\">>>f.fund_nav['2019-01-29',1.1311,1.1311,'-0.47%']>>>f.get_fund_stocks()>>>f.fund_stocksstocksweight0\u4e2d\u56fd\u79fb\u52a8[00941]0.10821\u5de5\u5546\u94f6\u884c[01398]0.09752\u817e\u8baf\u63a7\u80a1[00700]0.09703\u5efa\u8bbe\u94f6\u884c[00939]0.09324\u4e2d\u56fd\u5e73\u5b89[02318]0.09225\u4e2d\u56fd\u94f6\u884c[03988]0.06426\u4e2d\u56fd\u6d77\u6d0b\u77f3\u6cb9[00883]0.05227\u4e2d\u56fd\u77f3\u5316[00386]0.03438\u4e2d\u56fd\u4eba\u5bff[02628]0.02979\u62db\u5546\u94f6\u884c[03968]0.0267>>>list(f.fund_stocks.weight)[0.1082,0.0975,0.097,0.0932,0.0922,0.0642,0.0522,0.0343,0.0297,0.0267]>>>f.get_fund_histories('2019-01-07','2019-01-11')>>>f.fund_historydatenavcnavpercent2019-01-071.07431.07430.702019-01-081.06791.0679-0.602019-01-091.09491.09492.532019-01-101.09441.0944-0.052019-01-111.09641.09640.18>>>f.get_fund_histories('-1w')datenavcnavpercent2019-01-251.14131.14132.022019-01-281.13641.1364-0.432019-01-291.13111.1311-0.472019-01-301.13791.13790.602019-01-311.14751.14750.84get_all_funds functionExample:>>>df=get_all_funds()>>>df.groupby(by='type').count()typecodenameETF-\u573a\u5185171171QDII171171QDII-ETF1010QDII-\u6307\u65708383\u4fdd\u672c\u578b5252\u503a\u5238\u578b16131613\u503a\u5238\u6307\u65706969\u5176\u4ed6\u521b\u65b022\u5206\u7ea7\u6760\u6746132132\u56fa\u5b9a\u6536\u76ca132132\u5b9a\u5f00\u503a\u5238657657\u6df7\u5408-FOF4040\u6df7\u5408\u578b31673167\u7406\u8d22\u578b116116\u8054\u63a5\u57fa\u91d1194194\u80a1\u7968\u578b373373\u80a1\u7968\u6307\u6570462462\u8d27\u5e01\u578b665665>>>df[df['code'].str.contains('^510')].head()codenametype7319510010\u4ea4\u94f6\u4e0a\u8bc1180\u6cbb\u7406ETFETF-\u573a\u51857320510020\u535a\u65f6\u4e0a\u8bc1\u8d85\u5927\u76d8ETFETF-\u573a\u51857321510030\u534e\u5b9d\u4e0a\u8bc1180\u4ef7\u503cETFETF-\u573a\u51857322510050\u534e\u590f\u4e0a\u8bc150ETFETF-\u573a\u51857323510060\u5de5\u94f6\u4e0a\u8bc1\u592e\u4f0150ETFETF-\u573a\u5185>>>df[df['name'].str.contains('\u6052\u751f')].head()codenametype54000071\u534e\u590f\u6052\u751fETF\u8054\u63a5AQDII-\u6307\u657058000075\u534e\u590f\u6052\u751fETF\u8054\u63a5\u73b0\u6c47QDII-\u6307\u657059000076\u534e\u590f\u6052\u751fETF\u8054\u63a5\u73b0\u949eQDII-\u6307\u6570761000948\u534e\u590f\u6caa\u6e2f\u901a\u6052\u751fETF\u8054\u63a5AQDII-\u6307\u6570919001149\u6c47\u4e30\u664b\u4fe1\u6052\u751f\u9f99\u5934\u6307\u6570C\u80a1\u7968\u6307\u6570get_all_funds_ranking functionExample:>>>df=get_all_funds_ranking(fund_type='fof')# \u5f00\u653e\u5f0f\u57fa\u91d1\u6392\u884c>>>df.head()[['code','name','issue_date','nav','current_year']]codenameissue_datenavcurrent_year0005220\u6d77\u5bcc\u901a\u805a\u4f18\u7cbe\u9009\u6df7\u5408(FOF)2017-11-060.82770.0507811006306\u6cf0\u8fbe\u5b8f\u5229\u6cf0\u548c\u5e73\u8861\u517b\u8001(FOF)2018-10-251.00990.0205132006042\u4e0a\u6295\u6469\u6839\u5c1a\u777f\u6df7\u5408(FOF)2018-08-150.99310.0116133005222\u6cf0\u8fbe\u5b8f\u5229\u5168\u80fd\u6df7\u5408(FOF)C2017-11-020.98030.0156444005221\u6cf0\u8fbe\u5b8f\u5229\u5168\u80fd\u6df7\u5408(FOF)A2017-11-020.98500.015883>>>df=get_all_funds_ranking(fund_type='ct')# \u573a\u5185\u57fa\u91d1\u6392\u884c>>>df.tail()[['code','name','issue_date','nav','-1year','current_year']]codenameissue_datenav-1yearcurrent_year419150197\u56fd\u6cf0\u56fd\u8bc1\u6709\u8272\u91d1\u5c5e\u884c\u4e1a\u5206\u7ea7B2015-03-300.3411-0.715443-0.038349420150294\u5357\u65b9\u4e2d\u8bc1\u9ad8\u94c1\u4ea7\u4e1a\u6307\u6570\u5206\u7ea7B2015-06-100.4018-0.543043-0.057697421150308\u5bcc\u56fd\u4e2d\u8bc1\u4f53\u80b2\u4ea7\u4e1a\u6307\u6570\u5206\u7ea7B2015-06-250.8470-0.663614-0.055753422150264\u534e\u5b9d\u4e2d\u8bc11000\u6307\u6570\u5206\u7ea7B2015-06-040.3436-0.6616960.031840423512590\u6d66\u94f6\u5b89\u76db\u4e2d\u8bc1\u9ad8\u80a1\u606fETF2019-01-291.0032NaNNaNget_economic functionExample:>>>get_economic()# \u83b7\u53d6\u7ecf\u6d4e\u6307\u6807{'\u4e2d\u56fd\u4eba\u6c11\u94f6\u884c\u5229\u7387':'1083','\u4e2d\u56fd\u5b63\u5ea6\u56fd\u5185\u751f\u4ea7\u603b\u503c(GDP)\u5e74\u7387':'461','\u4e2d\u56fd\u89c4\u6a21\u4ee5\u4e0a\u5de5\u4e1a\u589e\u52a0\u503c\u5e74\u7387':'462','\u4e2d\u56fd\u5b98\u65b9\u5236\u9020\u4e1a\u91c7\u8d2d\u7ecf\u7406\u4eba\u6307\u6570(PMI)':'594','\u4e2d\u56fd\u8d22\u65b0\u5236\u9020\u4e1a\u91c7\u8d2d\u7ecf\u7406\u4eba\u6307\u6570(PMI)':'753','\u4e2d\u56fd\u5931\u4e1a\u7387':'1793','\u4e2d\u56fd\u8d38\u6613\u5e10 (\u7f8e\u5143)':'466','\u4e2d\u56fd\u53f0\u6e7e\u5229\u7387\u51b3\u8bae':'1117',......>>>get_economic(search='\u7f8e\u56fd')# \u83b7\u53d6\u7ecf\u6d4e\u6307\u6807 - \u7f8e\u56fd{'\u7f8e\u56fd\u5931\u4e1a\u7387':'300','\u7f8e\u56fd\u603b\u7edf\u9009\u4e3e':'371','\u7f8e\u56fdADP\u5c31\u4e1a\u4eba\u6570':'1','\u7f8e\u56fdISM\u5236\u9020\u4e1aPMI':'173','\u7f8e\u56fd\u96f6\u552e\u9500\u552e\u6708\u7387':'256','\u7f8e\u56fd\u8425\u5efa\u8bb8\u53ef\u603b\u6570':'25','\u7f8e\u56fdISM\u975e\u5236\u9020\u4e1aPMI':'176','\u7f8e\u56fd\u6838\u5fc3\u96f6\u552e\u9500\u552e\u6708\u7387':'63',......>>>df=get_economic('\u4e2d\u56fd\u8d22\u65b0\u5236\u9020\u4e1a\u91c7\u8d2d\u7ecf\u7406\u4eba\u6307\u6570(PMI)')# \u83b7\u53d6\u8d22\u65b0PMI>>>df.tail()dateactualactual_stateforecastrevised2018-09-3050.0down50.5NaN2018-11-0150.1up49.9NaN2018-12-0350.2up50.1NaN2019-01-0249.7down50.3NaN2019-02-0148.3down49.5NaN>>>df.to_excel('output.xls')# \u5bfc\u51faexcelget_economic_of_china functionExample:>>>get_economic_of_china(search='\u603b\u4eba\u53e3')[{'id':'A01050201','name':'\u6c11\u65cf\u81ea\u6cbb\u5730\u65b9\u603b\u4eba\u53e3\u6570'},{'id':'A030301','name':'\u5e74\u672b\u603b\u4eba\u53e3'},{'id':'A030501','name':'\u4eba\u53e3\u666e\u67e5\u603b\u4eba\u53e3'},{'id':'A030508','name':'\u4eba\u53e3\u666e\u67e50-14\u5c81\u4eba\u53e3\u5360\u603b\u4eba\u53e3\u6bd4\u91cd'},......>>>df=get_economic_of_china('A030101,A030102,A030103',time_period='1949-')>>>df.to_period('A').tail()\u5e74\u672b\u603b\u4eba\u53e3\u7537\u6027\u4eba\u53e3\u5973\u6027\u4eba\u53e3195358796.030468.028328.0195257482.029833.027649.0195156300.029231.027069.0195055196.028669.026527.0194954167.028145.026022.0>>>get_economic_of_china(category='month',search='\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570')[{'id':'A01010101','name':'\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570(\u4e0a\u5e74\u540c\u6708=100)'},{'id':'A01010102','name':'\u98df\u54c1\u70df\u9152\u7c7b\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570(\u4e0a\u5e74\u540c\u6708=100)'},{'id':'A01010103','name':'\u8863\u7740\u7c7b\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570(\u4e0a\u5e74\u540c\u6708=100)'},{'id':'A01010104','name':'\u5c45\u4f4f\u7c7b\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570(\u4e0a\u5e74\u540c\u6708=100)'},......>>>get_economic_of_china(\"A01010101\",category='month').to_period('M')\u5c45\u6c11\u6d88\u8d39\u4ef7\u683c\u6307\u6570(\u4e0a\u5e74\u540c\u6708=100)2018-12101.8606982018-11102.1750412018-10102.5431512018-09102.472394......>>>get_economic_of_china(category='month_by_state',search='region')[{'id':'110000','name':'\u5317\u4eac\u5e02'},{'id':'120000','name':'\u5929\u6d25\u5e02'},{'id':'130000','name':'\u6cb3\u5317\u7701'},{'id':'140000','name':'\u5c71\u897f\u7701'},......>>>get_economic_of_china(\"A03010101\",region='210000,130000',category='month_by_state').to_period('M')\u8fbd\u5b81\u7701\u6cb3\u5317\u77012018-12333.6381.02018-11311.0398.32018-10274.3429.22018-09273.5456.2......get_data_invest functionExample:>>>get_data_invest(query='BABA')[['941155','\u963f\u91cc\u5df4\u5df4','BABA','\u7ebd\u7ea6'],['940993','Baba Farid Sugar Mills Ltd','BABA','\u5df4\u57fa\u65af\u5766\u5361\u62c9\u5947'],['986306','\u963f\u91cc\u5df4\u5df4','BABAUSD','\u745e\u58eb'],['987353','Baba Arts Ltd','BART','\u5b5f\u4e70BSE'],>>>get_data_invest('941155','-1y').head()datecloseopenhighlowvol2018-03-05181.60179.41181.95177.0715656661.02018-03-06187.37185.19188.01184.8217856088.02018-03-07189.05184.37189.07184.3213728910.02018-03-08187.18189.05190.23186.5714331400.02018-03-09190.55189.64190.70188.0114208356.0get_data_yahoo functionExample:>>>get_data_yahoo('BABA','-1y').head()DateHighLowOpenCloseVolumeAdjClose2018-02-22190.740005187.770004190.199997188.75000012282800188.7500002018-02-23193.404999189.949997190.179993193.28999316937300193.2899932018-02-26195.149994190.649994194.460007194.19000219463100194.1900022018-02-27193.567001187.210007192.589996188.25999523218500188.2599952018-02-28188.240005185.000000187.250000186.13999919367600186.139999get_quota_yahoo functionExample:>>>get_quote_yahoo('BABA')[['marketCap','price']]marketCappriceBABA458608476160176.92get_stock_margin functionExample:>>>get_stock_margin()[['\u6536\u76d8-\u6caa\u6df1300','\u6da8\u8dcc\u5e45','\u878d\u8d44\u4f59\u989d','\u878d\u8d44\u51c0\u4e70\u5165\u989d']]tdate\u6536\u76d8-\u6caa\u6df1300\u6da8\u8dcc\u5e45\u878d\u8d44\u4f59\u989d\u878d\u8d44\u51c0\u4e70\u5165\u989d2019-02-213442.7056-0.26714675177047759637512306462019-02-203451.92730.35816674801924695045336292892019-02-193439.6078-0.17810474348561766159982805112019-02-183445.74483.2060377374873371505113256902...>>>get_stock_margin(mkt_type='sh')[['\u6536\u76d8-\u6caa\u6df1300','\u6da8\u8dcc\u5e45','\u878d\u8d44\u4f59\u989d','\u878d\u8d44\u51c0\u4e70\u5165\u989d']]tdate\u6536\u76d8-\u6caa\u6df1300\u6da8\u8dcc\u5e45\u878d\u8d44\u4f59\u989d\u878d\u8d44\u51c0\u4e70\u5165\u989d2019-02-222804.22621.90511646195485962927200504702019-02-212751.8012-0.34107045923480915920499902782019-02-202761.21890.20223945718481888119920748912019-02-192755.64590.0468094551927439903286343033...>>>get_stock_margin(code='601318')[['\u6536\u76d8-\u6caa\u6df1300','\u6da8\u8dcc\u5e45','\u878d\u8d44\u4f59\u989d','\u878d\u8d44\u51c0\u4e70\u5165\u989d']]tdate\u6536\u76d8-\u6caa\u6df1300\u6da8\u8dcc\u5e45\u878d\u8d44\u4f59\u989d\u878d\u8d44\u51c0\u4e70\u5165\u989d2019-02-2267.022.492719272743520-1596418912019-02-2165.39-0.743819432385411-500541602019-02-2065.880.304519482439571123740392019-02-1965.680.597319470065532169750461get_hsgt_history functionExample:>>>shgt=get_hsgt_history(mkt_type='shgt',begin='-1m')# \u6caa\u80a1\u901a(\u5317) \u8fd11\u6708>>>shgt[['\u5f53\u65e5\u8d44\u91d1\u6d41\u5165','\u5f53\u65e5\u4f59\u989d','\u5f53\u65e5\u6210\u4ea4\u51c0\u4e70\u989d','\u9886\u6da8\u80a1','\u6307\u6570','\u6da8\u8dcc\u5e45']]DetailDate\u5f53\u65e5\u8d44\u91d1\u6d41\u5165\u5f53\u65e5\u4f59\u989d\u5f53\u65e5\u6210\u4ea4\u51c0\u4e70\u989d\u9886\u6da8\u80a1\u6307\u6570\u6da8\u8dcc\u5e452019-02-223965.0048035.003589.82\u534e\u5b89\u8bc1\u52382804.230.0190532019-02-211718.5650281.441473.51\u8c6b\u5149\u91d1\u94c52751.80-0.0034122019-02-203228.5748771.432933.49\u9f0e\u7acb\u80a1\u4efd2761.220.0020212019-02-191418.1150581.891259.40\u5b8f\u56fe\u9ad8\u79d12755.650.000468...>>>hksh=get_hsgt_history(mkt_type='hksh',begin='-1m')# \u6e2f\u80a1\u901a(\u6caa) \u8fd11\u6708>>>hksh[['\u5f53\u65e5\u8d44\u91d1\u6d41\u5165','\u5f53\u65e5\u4f59\u989d','\u5f53\u65e5\u6210\u4ea4\u51c0\u4e70\u989d','\u9886\u6da8\u80a1','\u6307\u6570','\u6da8\u8dcc\u5e45']]DetailDate\u5f53\u65e5\u8d44\u91d1\u6d41\u5165\u5f53\u65e5\u4f59\u989d\u5f53\u65e5\u6210\u4ea4\u51c0\u4e70\u989d\u9886\u6da8\u80a1\u6307\u6570\u6da8\u8dcc\u5e452019-02-2279841202186.64\u534e\u8679\u534a\u5bfc\u4f5328816.300.0065102019-02-21-58142581-1122.04\u5357\u4eac\u718a\u732b28629.920.0040642019-02-20-59942599-1166.03\u4e2d\u56fd\u71c3\u6c1428514.050.0101292019-02-19-74142741-1223.02\u5609\u91cc\u7269\u6d4128228.13-0.004194...get_hsgt_top10 functionExample:>>>get_hsgt_top10(mkt_type='shgt',date='2019-02-22')# \u6caa\u80a1\u901a\u6210\u4ea4\u989dtop10RankCodeNameCloseChangePercentHGTJMEHGTMRJEHGTMCJEHGTCJJE1601318\u4e2d\u56fd\u5e73\u5b8967.022.492735334611173867553138532942011240049512600030\u4e2d\u4fe1\u8bc1\u523822.4310.0049-2072734533191159305263893838455053133600519\u8d35\u5dde\u8305\u53f0726.010.79972541560434482395181940834756423229934600036\u62db\u5546\u94f6\u884c30.631.828534614656840232337156176803458500174...get_hsgt_holding functionExample:>>>hold=get_hsgt_holding(mkt_type='north',date='2019-02-22')# \u5317\u5411\u6301\u80a1>>>hold[['\u4ee3\u7801','\u540d\u79f0','\u6301\u80a1\u5e02\u503c','\u6301\u80a1\u6570\u91cf','\u6301\u80a1\u5360A\u80a1\u6bd4\u4f8b']]HDDATE\u4ee3\u7801\u540d\u79f0\u6301\u80a1\u5e02\u503c\u6301\u80a1\u6570\u91cf\u6301\u80a1\u5360A\u80a1\u6bd4\u4f8b2019-02-22600519\u8d35\u5dde\u8305\u53f08.517306e+101173166449.182019-02-22601318\u4e2d\u56fd\u5e73\u5b895.141756e+107671973216.852019-02-22000333\u7f8e\u7684\u96c6\u56e24.714754e+10103371052215.522019-02-22600276\u6052\u745e\u533b\u836f3.194746e+1048186219512.95...>>>hold=get_hsgt_holding(code='601318',date='2019-02-22')# \u4e2a\u80a1\u6301\u80a1\uff0c\u6700\u591a\u8fd11\u6708\u6570\u636e>>>hold[['\u4ee3\u7801','\u540d\u79f0','\u6301\u80a1\u5e02\u503c','\u6301\u80a1\u6570\u91cf','\u6301\u80a1\u5360A\u80a1\u6bd4\u4f8b']]HDDATE\u4ee3\u7801\u540d\u79f0\u6301\u80a1\u5e02\u503c\u6301\u80a1\u6570\u91cf\u6301\u80a1\u5360A\u80a1\u6bd4\u4f8b2019-02-22601318\u4e2d\u56fd\u5e73\u5b895.141756e+107671973216.852019-02-21601318\u4e2d\u56fd\u5e73\u5b894.981185e+107617656286.802019-02-20601318\u4e2d\u56fd\u5e73\u5b894.991939e+107577320516.802019-02-19601318\u4e2d\u56fd\u5e73\u5b894.943077e+107526000926.72...BaiduIndex classExample:>>>BaiduIndex.cookie=\"cookie string\"# OR load cookie from browsers>>>idx=BaiduIndex()>>>idx.search('\u80a1\u7968,\u57fa\u91d1',begin='-3m',area='\u4e0a\u6d77').tail()date\u80a1\u7968\u57fa\u91d12019-02-1817227782019-02-1921178372019-02-2018797822019-02-2119337602019-02-222097779>>>idx.search('\u80a1\u7968,\u57fa\u91d1',begin='-2q',index='feed',area='\u5e7f\u5dde').head()date\u80a1\u7968\u57fa\u91d12018-08-23221807168382018-08-24196099113392018-08-25185960163462018-08-26137134122062018-08-2718002828195>>>idx.region_distribution('\u80a1\u7968','-6w')# \u5730\u57df\u5206\u5e03{'\u80a1\u7968':{'city':{'514':1000,'57':962,'138':677,'94':663,....},'prov':{'913':1000,'917':693,'916':555,'911':498,....},'period':'2019-01-23|2019-02-22'}}>>>idx.social_attribute('\u80a1\u7968','-15d')# \u4eba\u7fa4\u5c5e\u6027{'\u80a1\u7968':{'age':{'1':'2','2':'11','3':'45','4':'32','5':'10'},'sex':{'F':'23','M':'77'}}}search functionsearch(query: str = \"\", query_type: str = \"stock\", symbol: str = \"\", count: int = 10, page: int = 1, sort: str = \"time\", source: str = \"user\")- Sends a search request.:paramquery: query string.:paramquery_type: (optional) type of the query request, default isstock.value: stock, post, user:paramsymbol: (optional) the stock symbol.:paramcount: (optional) the number of results, default is20.:parampage: (optional) page number, default is1.:paramsort: (optional) order type, default istime.value: time\u6700\u65b0, reply\u8bc4\u8bba, relevance\u9ed8\u8ba4:paramsource: (optional) source of the results, default isuser.value: all, user\u8ba8\u8bba, news\u65b0\u95fb, notice\u516c\u544a, trans\u4ea4\u6613:return: a list of :class:Object <instance_id>objects. Object class: Stock, Post or User:rtype: list([ins1, ins2, ...])news functionnews(category: int = -1, count: int = 10, max_id: int = -1)- Get news.:paramcategory: (optional) type of the news, default is-1.value: \u5934\u6761-1, \u4eca\u65e5\u8bdd\u98980, \u76f4\u64ad6, \u6caa\u6df1105, \u6e2f\u80a1102, \u7f8e\u80a1101, \u57fa\u91d1104, \u79c1\u52df113, \u623f\u4ea7111, \u6c7d\u8f66114, \u4fdd\u9669110:paramcount: (optional) the number of results, default is10.:parammax_id: (optional) the max id of news, default is-1.:return: a list of :class:Post <instance_id>objects.:rtype: list([post1, post2, ...])utils moduleThis module contains some utils.get_cookies()- load cookies from local file, browser and selenium. return aLWPCookieJarclass object.get_session()- get the requests session.clean_html(tree: str)- clean html.check_symbol(code: str)- check stock symbol.exrate(date: str = \"\", code: str = \"USD\")- get the monetary exchange rate by date.code:{'USD':'\u7f8e\u5143','EUR':'\u6b27\u5143','JPY':'\u65e5\u5143','HKD':'\u6e2f\u5143','GBP':'\u82f1\u9551','AUD':'\u6fb3\u5927\u5229\u4e9a\u5143','NZD':'\u65b0\u897f\u5170\u5143','SGD':'\u65b0\u52a0\u5761\u5143','CHF':'\u745e\u58eb\u6cd5\u90ce','CAD':'\u52a0\u62ff\u5927\u5143','MYR':'\u9a6c\u6765\u897f\u4e9a\u6797\u5409\u7279','RUB':'\u4fc4\u7f57\u65af\u5362\u5e03','ZAR':'\u5357\u975e\u5170\u7279','KRW':'\u97e9\u5143','AED':'\u963f\u8054\u914b\u8fea\u62c9\u59c6','SAR':'\u6c99\u7279\u91cc\u4e9a\u5c14','HUF':'\u5308\u7259\u5229\u798f\u6797','PLN':'\u6ce2\u5170\u5179\u7f57\u63d0','DKK':'\u4e39\u9ea6\u514b\u6717','SEK':'\u745e\u5178\u514b\u6717','NOK':'\u632a\u5a01\u514b\u6717','TRY':'\u571f\u8033\u5176\u91cc\u62c9','MXN':'\u58a8\u897f\u54e5\u6bd4\u7d22','THB':'\u6cf0\u94e2'}exusd(date: str = \"\")- only forUSD.exhkd(date: str = \"\")- only forHKD.Example:>>>CJ=get_cookies()>>>sess=get_session()>>>clean_html(\"<span>hello.</span>\")hello.>>>check_symbol(601318)\"SH601318\">>>exrate(\"2019-01-10\",\"EUR\")[7.8765,7.8443]>>>exusd(date=\"2019-01-10\")[6.816,6.8526]>>>exhkd(\"2019-01-10\")[0.86959,0.87419]"} +{"package": "xueqiudanjuan", "pacakge-description": "WarningThis package only for personal use under the rules of XueQiu.\nPlease obey the rules of XueQiu, and do not take the bad influence for the XueQiu website.General InformationThis is a Python package designed by BugMakerH, which is used for getting the data on the XueQiu website.\nYou can import this package using:importxueqiudanjuanHow to use this packagehello.pyhello()This function is nothing but a test for checking whether the package works well.stocks.pyStockThis is a class to get data about stocks.\nYou can create a Stock class using:st=stocks.Stock()This means to create a Stock object.\nAnd, you can use 'get_realtime_quotec()' to get the real price of a specified stock. Like this:st.get_realtime_quotec(\"SH000001\")Update documentation0.0.11Deleted the function 'get_realtime_quotec_prize' in the class 'Stock'.0.0.10Update the import in '__init__'.0.0.9Updated the test of stocks.py in '__main__'.Added the import of all the files in '__init__'.0.0.8Updated the url of long description.0.0.7Updated the url of long description.0.0.6Added the Github URL of the package.Remove the stock's code from the '__init__' function to the 'get_realtime_quotec' function.0.0.5Updated nothing, cuz I deleted the version 0.0.4 by mistake.0.0.4Created the README file and added the README file to the package.Linked the package's long description to the README file.0.0.3Created the class engine and the class stocks.Finished the first version of the class engine.Added a function of the class stocks, which is called 'get_realtime_quotec' to get the realtime price of the specified stocks.Added a test of the class stocks in the '__main__'.0.0.2Updated nothing, but a joke.0.0.1Added a test for the package, which added a file called \"hello.py\" with a function called \"hello\"."} +{"package": "xuerui-stat", "pacakge-description": "xuerui-statAn open-source Python package for using statistical tools and methods.Source codehttps://github.com/Xuerui-Yang/xuerui-statInstallationpip install xuerui-statTools and methodsDataManagerDescriptionIt is a tool to manage data files. Once a data file is imported, the tool would move it to a specified data directory automatically. And when importing data, the tool can search files in the data directory.Examplefromxuerui_statimportDataManagerdm=DataManager(enable=True)This command defines a class to name the tool. For the first use, users should use the command 'set_dir(yourpath)' with your prefered path to set your data directory, for example,dm.set_dir('/home/xuerui/Documents/Data/')Once it is done, the directory path is printed like this:Data directory: '/home/xuerui/Documents/Data/'The parameter 'enable' for the class can be set as True or False. When it is True, the data file imported by the command below would be moved to the data directory automatically.df=dm.import_data('/home/xuerui/Documents/PythonProjects/FactorAnalysis/example.csv')Otherwise users can manually move the files using the such command:dm.addto_dir('/home/xuerui/Documents/example.csv')The moved data files are renamed by adding the script names, in order to identify them. For example, 'example.csv' is imported in 'my_example.py' using the above command. So it would be moved to the data directory and renamed as 'MyExample_example.csv'.Users can also check the contents under the data directory usingdm.list_dir()DecisionTree, PlotTree, RandomForestDescriptionThese commands give users tools for data mining by using tree relevant methods.ExampleAs above, the following commands import the data which is to be analyse.fromxuerui_statimport*dm=DataManager(enable=False)data=dm.import_data(\"/home/xuerui/Documents/PythonProjects/test.csv\")The decision tree method can be applied to the data by specifying the name of category.dt=DecisionTree(data,'Cat')dt.train()t=dt.treeprint(t)pt=PlotTree(dt)pt.tree_structure_plot()dt.test()pt.confusion_matrix_plot()The tree and confusion matrix can be plotted via the 'PlotTree' module.Furthermore, the random forest can also be used as follows:rf=RandomForest(data,'Cat')rf.train(num_tree=300,max_depth=0,min_gini=0)print(rf.oob_error)dt.test()print(dt.confusion_matrix)"} +{"package": "xuexitong-fileloads", "pacakge-description": "chaoxingxuexitong-fileloads\u4e0b\u8f7d\u5b66\u4e60\u901a\u8bfe\u4ef6\u89c6\u9891\u89c9\u5f97\u8f93\u5165\u592a\u591a\u9ebb\u70e6\u53ef\u4ee5\u8d70\u6781\u7b80\u901a\u9053\uff0c\u6b64\u65f6\u8bb0\u5f97\u81f3\u5c11\u6539\u4e2a\u57fa\u672c\u76ee\u5f55\u548c\u94fe\u63a5\uff0c\u5176\u4ed6\u53c2\u6570\u81ea\u5b9a\u4e49\uff0c\u4e0d\u6539\u6309\u9ed8\u8ba4\u53c2\u6570\u3002\u4f7f\u7528\u65b9\u6cd5\u4ee3\u7801\u91cc\u5199\u4e86\u4e0d\u5c11\u53ea\u8fd0\u884c\u4ee3\u78012\u5373\u53ef\uff0c\u4ee3\u7801\u5df2\u4f5c\u4e3a\u6a21\u5757\u5bfc\u5165\u5927\u81f4\u6d41\u7a0b\u4f9d\u6b21\uff1amode_op \u6a21\u5f0f\u9009\u62e99\u81ea\u5b9a\u4e49\uff0c\u4e2d\u95f4\u503c\u4ec5\u7b2c\u4e00\u6b21\u5faa\u73af\u6781\u7b80,0\u6781\u7b80.loop_op \u63092\u81ea\u52a8\u5faa\u73af1\u624b\u52a8\u5355\u6b21.file_class \u8f93\u5165\u5faa\u73af\u4e0b\u8f7d\u7c7b\u578b3\u5168\u90e82pdf1mp4\u4e0d\u4e0b\u8f7d0,start_inPage\u7ae0\u8282\u5185\u9875\u9762\u8ddf\u7740\u63d0\u793a\u5373\u53ef"} +{"package": "xugrid", "pacakge-description": "This is a work in progress.See documentation.Xarray extension to work with 2D unstructured grids, for data and topology\nstored according toUGRID conventions.Processing structured data with xarray is convenient and efficient. The goal of\nXugrid is to extend this ease to unstructured grids.importmatplotlib.pyplotaspltimportxugrid# Get some sample data as a xugrid UgridDataArrayuda=xugrid.data.elevation_nl()# Get a cross-sectionsection_y=475_000.0section=uda.ugrid.sel(y=section_y)# Plot unstructured grid and cross sectionfig,(ax0,ax1)=plt.subplots(figsize=(22.6,10),ncols=2)uda.ugrid.plot(ax=ax0,vmin=-20,vmax=90,cmap=\"terrain\")ax0.axhline(y=section_y,color=\"red\")section.plot(ax=ax1,x=\"mesh2d_face_x\")InstallationInstall via conda from the conda-forge channel:conda install -c conda-forge xugridOr from the Python Package Index:pip install xugridDocumentation"} +{"package": "xuhalin-test", "pacakge-description": "test"} +{"package": "xuino", "pacakge-description": "UNKNOWN"} +{"package": "xujian", "pacakge-description": "UNKNOWN"} +{"package": "xuk", "pacakge-description": "metafidxuk\u062e\u0648\u06a9 \u0628\u0631\u0627\u06cc \u0645\u062f\u0644-\u0633\u0627\u0632\u06cc\u0650 \u0627\u0628\u0632\u0627\u0631\u06cc\u0650 \u0645\u0627\u0644\u06cc \u062a\u0648\u0633\u0639\u0647 \u062f\u0627\u062f\u0647 \u0645\u06cc\u200c\u0634\u0647.\u0631\u0627\u0647\u0646\u0645\u0627\u06cc\u0650 \u062e\u0648\u06a9 \u0631\u0648 \u062f\u0631\u0627\u06cc\u0646 \u0635\u0641\u062d\u0647\u0628\u062e\u0648\u0646\u06cc\u062f.installputhon-mpipinstallxuk\u0645\u062f\u0644\u200c\u0647\u0627\u06cc\u0650 \u06a9\u0646\u0648\u0646\u06cc \u0628\u0647 \u0634\u0631\u062d\u0650 \u0632\u06cc\u0631 \u0627\u0633\u062a.\u0627\u062e\u062a\u06cc\u0627\u0631\u0650 \u0645\u0639\u0627\u0645\u0644\u0647\u0642\u06cc\u0645\u062a-\u06af\u0630\u0627\u0631\u06ccblack-scholes-merton\u0627\u0633\u062a\u0631\u0627\u062a\u0698\u0647\u0627\u06cc\u0650 \u0645\u0639\u0627\u0645\u0644\u0627\u062a\u06cccovered-callmarried-putbull-call-spreadbear-call-spreadbull-put-spreadbear-put-spread\u062f\u0631\u0622\u0645\u062f\u0650-\u062b\u0627\u0628\u062a\u0628\u0627\u0632\u062f\u0647 \u062a\u0627 \u0633\u0631\u0631\u0633\u06cc\u062fcoupon-bondzero-coupon-bond\u062a\u062d\u0644\u06cc\u0644\u0650 \u062a\u06a9\u0646\u06cc\u06a9\u06cc\u0631\u0648\u0646\u062fdow"} +{"package": "xuleipdf", "pacakge-description": "This is the homepage of our project."} +{"package": "xulpymoney", "pacakge-description": "Project web page is inhttps://github.com/turulomio/xulpymoney/"} +{"package": "xumm-sdk-py", "pacakge-description": "XUMM SDK (Python)Interact with the XUMM SDK from Python environments.\u26a0\ufe0f Please note: The XUMM SDK (XUMM API in general) is for BACKEND USE only. Please DO NOT use your API credentials in a FRONTEND environment.To implement the XUMM SDK (or XUMM API directly) in your own web project, make sure your frontend calls your own backend, where the follow up communication with the XUMM SDK (or XUMM API) will take place. Your XUMM credentials should never be publicly available.Getting StartedUsagePayloadsApp StorageHelper MethodsDevelopmentGetting StartedInstallationVia pip:pip3installxumm-sdk-pyUsageimportxummsdk=xumm.XummSdk()# Or with manually provided credentials (instead of using dotenv):sdk=xumm.XummSdk('XUMM_APIKEY','XUMM_APISECRET')After constructing the SDK, you can call the methods:sdk.*for the helper methods (see below)sdk.payload.*to get/update/create payloads for users to signsdk.storage.*for your XUMM app storage (to store meta info for headless applications)The SDK will look in your environment or dotenv file (.env) for theXUMM_APIKEYandXUMM_APISECRETvalues. A sample dotenv can be foundhere. Alternatively you can provide your XUMM API Key & Secret by passing them to the XummSdk constructor.NOTE: If both your environment and the SDK constructor contain credentials, the values provided to the constructor will be used.PayloadsIntroPayloads are the primary reason for the XUMM API (thus this SDK) to exist. TheXUMM API Docs explain 'Payloads'like this:An XRPL transaction \"template\" can be posted to the XUMM API. Your transaction tample to sign (so: your \"sign request\") will be persisted at the XUMM API backend. We now call it a aPayload. XUMM app user(s) can open the Payload (sign request) by scanning a QR code, opening deeplink or receiving push notification and resolve (reject or sign) on their own device.A payload can contain an XRPL transaction template. Some properties may be omitted, as they will be added by the XUMM app when a user signs a transaction. A simple payload may look like this:payload={'txjson':{'TransactionType':'Payment','Destination':'rwiETSee2wMz3SBnAG8hkMsCgvGy9LWbZ1','Amount':'1337'}}As you can see the payload looks like a regular XRPL transaction, wrapped in antxjsonobject, omitting the mandatoryAccount,FeeandSequenceproperties. They will be added containing the correct values when the payload is signed by an app user.Optionally (besidestxjson) a payload can contain these properties (PY definition):optionsto define payload options like a return URL, expiration, etc.custom_metato add metadata, user insruction, your own unique ID, ...user_tokento push the payload to a user (afterobtaining a user specific token)A more complex payloadcould look like this. Areference for payload options & custom metacan be found in theAPI Docs.Instead of providing atxjsontransaction, a transaction formatted as HEX blob (string) can be provided in atxblobproperty.sdk.payload.getsdk.payload.get(payload:Union[str,CreatedPayload]):->XummPayloadTo get payload details, status and if resolved & signed: results (transaction, transaction hash, etc.) you canget()a payload.Note! Please don't usepolling! The XUMM API offers Webhooks (configure your Webhook endpoint in theDeveloper Console) or usea subscriptionto receive live payload updates (for non-SDK users:Webhooks).You canget()a payload by:Payload UUIDpayload=sdk.payload.get('aaaaaaaa-bbbb-cccc-dddd-1234567890ab')Passing a created Payload object (see:sdk.payload.create)new_payload:xumm_types.created_payload={txjson:{...}}created=sdk.payload.create(new_payload)payload=sdk.payload.get(created)sdk.payload.get('aaaaaaaa-bbbb-cccc-dddd-1234567890ab')sdk.payload.createsdk.payload.create(payload:create_payload):->Union[CreatedPayload,None]To create a payload, atxjsonXRPL transaction can be provided. Alternatively, a transaction formatted as HEX blob (string) can be provided in atxblobproperty.See theintrofor more information about payloads.Take a look at theDeveloper Docs for more information about payloads.The response (see:Developer Docs) of asdk.payload.create()operation, a<CreatedPayload>json object, looks like this:{\"uuid\":\"1289e9ae-7d5d-4d5f-b89c-18633112ce09\",\"next\":{\"always\":\"https://xumm.app/sign/1289e9ae-7d5d-4d5f-b89c-18633112ce09\",\"no_push_msg_received\":\"https://xumm.app/sign/1289e9ae-7d5d-4d5f-b89c-18633112ce09/qr\"},\"refs\":{\"qr_png\":\"https://xumm.app/sign/1289e9ae-7d5d-4d5f-b89c-18633112ce09_q.png\",\"qr_matrix\":\"https://xumm.app/sign/1289e9ae-7d5d-4d5f-b89c-18633112ce09_q.json\",\"qr_uri_quality_opts\":[\"m\",\"q\",\"h\"],\"websocket_status\":\"wss://xumm.app/sign/1289e9ae-7d5d-4d5f-b89c-18633112ce09\"},\"pushed\":true}Thenext.alwaysURL is the URL to send the end user to, to scan a QR code or automatically open the XUMM app (if on mobile). If auser_tokenhas been provided as part of the payload data provided tosdk.payload.create(), you can see if the payload has been pushed to the end user. A button \"didn't receive a push notification\" could then take the user to thenext.no_push_msg_receivedURL.Alternatively user routing / instruction flows can be custom built using the QR information provided in therefsobject, and a subscription for live status updates (opened, signed, etc.) using a WebSocket client can be setup by conneting to therefs.websocket_statusURL.Please note: this SDK already offers subscriptions. There's no need to setup your own WebSocket client, seePayload subscriptions: live updates.There's more information about thepayload workflowand apayload lifecyclein the Developer Docs.sdk.payload.cancelsdk.payload.cancel(payload:Union[str,XummPayload,CreatedPayload]):->Union[DeletedPayload,None]To cancel a payload, provide a payload UUID (string), a<XummPayload>(by performing asdk.payload.get()first) or a<CreatedPayload>(by using the response of asdk.payload.create()call). By cancelling an existing payload, the payload will be marked as expired and can no longer be opened by users.Please note:if a user already opened the payload in XUMM APP, the payload cannot be cancelled: the user may still be resolving the payload in the XUMM App, and should have a chance to complete that process.A response (generic API typeshere) looks like:response.result.cancelled# boolresponse.result.reason# XummCancelReasonresponse.meta# XummPayloadMetaresponse.custom_meta# XummCustomMetaPayload subscriptions: live updatesTo subscribe to live payload status updates, the XUMM SDK can setup a WebSocket connection and monitor live status events. Emitted events include:The payload is opened by a XUMM App user (webpage)The payload is opened by a XUMM App user (in the app)Payload expiration updates (remaining time in seconds)The payload was resolved by rejectingThe payload was resolved by accepting (signing)More information about the status update events & sample event datacan be found in the Developer Docs.Status updates can be processed by providing acallback functionto thesdk.payload.subscribe()method. Alternatively, the (by thesdk.payload_subscribe()method) returned raw websocket can be used to listen for WebSocketonmessageevents.The subscription will be closed by either:Returning non-void in thecallback functionpassed to thesdk.payload.subscribe()methodManually calling<PayloadSubscription>.resolve()on the object returned by thesdk.payload.subscribe()methodsdk.payload.subscribesdk.payload.subscribe(payload:Union[str,XummPayload,CreatedPayload],callback:on_payload_event):->PayloadSubscriptionIf a callback function is not provided, the subscription will stay active until the<PayloadSubscription>.resolve()method is called manually, eg. based on handling<PayloadSubscription>.websocket.onmessageevents.When a callback function is provided, for every paylaod specific event the callback function will be called with<SubscriptionCallbackParams>. The<SubscriptionCallbackParams>.dataproperty contains parsed JSON containing event information. Either by calling<SubscriptionCallbackParams>.resolve()or by returning a non-void value in thecallback functionthe subscription will be ended, and the<PayloadSubscription>.resolvedpromise will resolve with the value returned or passed to the<SubscriptionCallbackParams>.resolve()method.Resolving (by returning non-void in the callback or callingresolve()manually) closes the WebSocket client the XUMM SDK sets up 'under the hood'.The<PayloadSubscription>object looks like this:response.payload# XummPayloadresponse.resolved# Union[CallbackPromise, None]response.resolve# CallbackPromiseresponse.websocket# WSClientExamples:Async process after returning data in the callback functionAwait based on returning data in the callback functionAwait based on resolving a callback eventAwait based on resolving without using a callback functionsdk.payload.create_subscribesdk.payload.create_and_subscribe(payload:CreatePayload,callback:on_payload_event):->PayloadAndSubscriptionThe<PayloadAndSubscription>object is basically a<PayloadSubscription>object with the created payload results in thecreatedproperty:All information that applies onsdk.payload.create()andsdk.payload.create_and_subscribe()applies. Differences are:The input for asdk.payload.create_and_subscribe()call isn't a payload UUID / existing payload, but a paykiad to create.The response object also contains (<PayloadAndSubscription>.created) the response obtained when creating the payloadApp StorageApp Storage allows you to store a JSON object at the XUMM API platform, containing max 60KB of data.\nYour XUMM APP storage is stored at the XUMM API backend, meaning it persists until you overwrite or delete it.This data is private, and accessible only with your own API credentials. This private JSON data can be used to store credentials / config / bootstrap info / ... for your headless application (eg. POS device).storage_set=awaitsdk.storage.set({'name':'Wietse','age':32,'male':True})print(storage_set)# Truestorage_get=sdk.storage.get()print(storage_get.data)# { 'name': 'Wietse', 'age': 32, 'male': True }storage_delete=sdk.storage.delete()print(storage_delete)# Truestorage_get_after_delete=sdk.storage.get()print(storage_get_after_delete.data)# NoneHelper methodssdk.ping()Thepingmethod allows you to verify API access (valid credentials) and returns some info on your XUMM APP:pong=sdk.ping()Returns<ApplicationDetails>:pong.quota# {}pong.application.name# 'My XUMM APP'pong.application.uuidv4# '00000000-1111-2222-3333-aaaaaaaaaaaa'pong.application.webhookurl# ''pong.application.disabled# 0pong.call.uuidv4# 'bbbbbbbb-cccc-dddd-eeee-111111111111'sdk.get_curated_assets()Theget_curated_assetsmethod allows you to get the list of trusted issuers and IOU's. This is the same list used to\npopulate the \"Add Asset\" button at the XUMM home screan.curated_assets=sdk.get_curated_assets()Returns<CuratedAssetsResponse>:curated_assets.issuers# [ 'Bitstamp', 'GateHub' ]curated_assets.currencies# [ 'USD', 'BTC', 'EUR', 'ETH' ]curated_assets.details.Bitstamp# {}curated_assets.details.GateHub# {}sdk.get_kyc_status()Theget_kyc_statusreturn the KYC status of a user based on a user_token, issued after the\nuser signed a Sign Request (from your app) before (see Payloads - Intro).If a user token specified is invalid, revoked, expired, etc. the method will always\nreturnNONE, just like when a user didn't go through KYC. You cannot distinct a non-KYC'd user\nfrom an invalid token.Alternatively, KYC status can be retrieved for an XPRL account address: the address selected in\nXUMM when the session KYC was initiated by.kyc_status=sdk.get_kyc_status('00000000-0000-0000-0000-000000000000')... or using an account address:kyc_status=sdk.get_kyc_status('rwu1dgaUq8DCj3ZLFXzRbc1Aco5xLykMMQ')Returns<str of PossibleKycStatuses>.Notes on KYC informationOnce an account has successfully completed the XUMM KYC flow, the KYC flag will be applied to the account even if the identity document used to KYC expired. The flag shows that the account wasonceKYC'd by a real person with a real identity document.Please note that the KYC flag provided by XUMM can't be seen as a \"all good, let's go ahead\" flag: it should be used asone of the data pointsto determine if an account can be trusted. There are situations where the KYC flag is stillTrue, but an account can no longer be trusted. Eg. when account keys are compromised and the account is now controlled by a 3rd party. While unlikely, depending on the level of trust required for your application you may want to mitigate against these kinds of fraud.sdk.get_transaction()Theget_transactionmethod allows you to get the transaction outcome (mainnet)\nlive from the XRP ledger, as fetched for you by the XUMM backend.Note: it's best to retrieve these resultsyourselfinstead of relying on the XUMM platform to get live XRPL transaction information! You can use thexrpl-pypackage to do this:tx_info=sdk.get_transaction(tx_hash)Returns:<XrplTransaction>.sdk.verify_user_tokens() / sdk.verify_user_tokens()Theverify_user_tokens(or single token:verify_user_token) method allows you to verify one or more User Tokens obtained from previous sign requests. This allows you to detect if you will be able to push your next Sign Request to specific users.some_token='691d5ae8-968b-44c8-8835-f25da1214f35'token_validity=sdk.verify_user_tokens([some_token,'b12b59a8-83c8-4bc0-8acb-1d1d743871f1','51313be2-5887-4ae8-9fda-765775a59e51'])ifsdk.verify_user_token(some_token).active:# Push, use `user_token` in payloadelse:# QR or Redirect (deeplink) flowReturns:<UserTokenValidity or [UserTokenValidity]>.DevelopmentInstall requirmentspipinstall-e\".[develop]\"BuildPlease note: at least Python version3.6+is required!To build the code, runpython setup.py install.DebuggingThe XUMM SDK will emit debugging info when invoked with a debug environment variable configured like:DEBUG=xumm-sdk*You'll see the XUMM SDK debug messages if you invoke your script instead of this:python3 main.pyExample:DEBUG=xumm-sdk* python3 main.pyLint & testLint the code using:python3-mflake8For running tests:python3test.pytests/"} +{"package": "xumx-slicq-v2", "pacakge-description": "xumx-sliCQ-V2xumx-sliCQ-V2 is a PyTorch neural network for music demixing, trained only onMUSDB18-HQ.It demixes a musical mixture into stems (vocals/drums/bass/other) by masking the magnitude spectrogram. The code is based onOpen-Unmix (UMX)with some key differences:Spectral transform: sliced Constant-Q Transform (sliCQT) with the Bark scale vs. STFTNeural network architecture: convolutional denoising autoencoder (CDAE) vs. dense + Bi-LSTMAll targets are trained together with combined loss functions likeCrossNet-Open-Unmix (X-UMX)xumx-sliCQ-V2 scores a total SDR of 4.4 dB with 60 MB* of pretrained weights for all targetson the MUSDB18-HQ test set.The realtime model scores 4.07 dB and is light and fast!It takes an average of 2 seconds to demix a song with a GPU and 11 seconds with a CPU using PyTorch.\u2020The provided ONNX model optimizes the performance further, taking 7 seconds on the CPU.Both variants beat the 3.6 dB score of the originalxumx-sliCQ(28 MB) with the improvementsdescribed here. It also brings the performance closer to the 4.64 dB and 5.54 dB scored by UMX and X-UMX (137 MB) respectively.\u2021Some of the code in this repo is vendored from different external sources:xumx_slicq_v2.norbertfromhttps://github.com/yoyololicon/norbertandcadenzafromhttps://github.com/claritychallenge/clarity/tree/main/recipes/cad1*: Pretrained weights for xumx-sliCQ-V2 are stored in this repo with Git LFS:offline,realtime\u2020: See theinference section belowfor measurements\u2021: UMX and X-UMX were independently re-evaluated as part of xumx-sliCQ:1,2Key conceptsBark-scale sliCQT to better represent musical signals with a nonuniform time-frequency resolution compared to the fixed resolution STFT:Convolutional network applied to ragged sliCQT (time-frequency blocks with different frame rates):UsagePrerequisitesYou need Python + pip >= 3.8 or Docker. To use your GPU, you need the NVIDIA CUDA Toolkit and an NVIDIA CUDA-capable GPU. For Docker + GPU, you also need thenvidia-docker 2.0 runtime. For your own training, tuning, and evaluation, you need theMUSDB18-HQ dataset.Podman supportMake these changes to use Podman instead of Docker:Build command:buildah bud -t \"xumx-slicq-v2\" .Run gpu string:--gpus=all --ipc=host(compared to--gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864which may result in OCI permission errors around setting ulimits)InstallIf you want to use Docker (recommended), git clone the source code and build the container:$ git clone https://github.com/sevagh/xumx-sliCQ -b v2\n$ cd ./xumx-sliCQ\n$ docker build -t \"xumx-slicq-v2\" .The container is based on theNVIDIA PyTorch NGC Containerto include features and optimizations for to NVIDIA GPUs, such as automaticTF32 for Ampere+,bfloat16 support for Ampere+, and more.To dynamically update the source code in the container while you develop new features, you can volume mount the local checkout of xumx-sliCQ to:/xumx-sliCQ-V2. If not, the container will use a frozen copy of the source code when you built the image.If you want to use pip, the project isavailable on PyPI.org:# regular case\n$ pip install xumx-slicq-v2\n\n# for ONNX CPU inference\n$ pip install xumx-slicq-v2[onnxruntime-cpu]\n\n# for ONNX CUDA inference\n$ pip install xumx-slicq-v2[onnxruntime-cuda]\n\n# for musdb + museval\n$ pip install xumx-slicq-v2[musdb]\n\n# for all development/training dependencies (needs CUDA GPU)\n$ pip install xumx-slicq-v2[devel]List of all scriptsScriptDescriptionDeviceFor end usersxumx_slicq_v2.inferenceDemix mixed songsCPUorCUDA GPUFor developersxumx_slicq_v2.evaluationEvaluate pretrained networksCPUxumx_slicq_v2.trainingTrain the networkCUDA GPUxumx_slicq_v2.optunaOptuna hyperparam tuningCUDA GPUxumx_slicq_v2.slicqfinderRandom sliCQT param searchCPUorCUDA GPUxumx_slicq_v2.visualizationGenerate spectrogramsCPUxumx_slicq_v2.exportExport variants for optimized inference (TorchScript, ONNX)CPUIf you installed the package with pip, run them likepython -m xumx_slicq_v2.$script_name.RunPip: run inference to generate outputs on a folder containing mixed song wav files:$ python -m xumx_slicq_v2 --audio-backend=\"sox_io\" --input-dir=./input/ --output-dir=./output/\nUsing torch device cpu for backend torch-cpu\nDownloading: \"https://github.com/sevagh/xumx-sliCQ/raw/main/pretrained_model/xumx_slicq_v2.pth\" to /home/sevagh/.cache/torch/hub/checkpoints/xumx_slicq_v2_offline.pth\n100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 59.6M/59.6M [00:09<00:00, 6.25MB/s]\nscale=bark, fbins=262, fmin=32.90, fmax=22050.00, sllen=18060, trlen=4516\nsong chunks: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:01<00:00, 1.28s/it]\n100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 1/1 [00:01<00:00, 1.30s/it]\nInference time in s (averaged across tracks): 1.28The appropriate weight files will be automatically downloaded. Runtime options are:ArgumentsModelInference libDevice--runtime-backend=torch-cpuOfflinePyTorchCPU--runtime-backend=torch-cudaOfflinePyTorchCUDA GPU--runtime-backend=torch-cpu --realtimeRealtimePyTorchCPU--runtime-backend=torch-cuda --realtimeRealtimePyTorchCUDA GPU--runtime-backend=onnx-cpuRealtimeONNXRuntimeCPU--runtime-backend=onnx-cudaRealtimeONNXRuntimeCUDA GPUDocker: run inference to generate outputs on a folder containing mixed song wav files:$ docker run --rm -it \\\n -v /path/to/input/songs/:/input \\\n -v /path/to/demixed/outputs:/output \\\n python -m xumx_slicq_v2.inference --help\n\n#add below lines for gpu support\n#--gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \\\n#python -m xumx_slicq_v2.inference --cudaInference time for the realtime variant is2x fasterthan the offline model, and3x faster with ONNX, measuring the average time taken to demix the 50 MUSDB18-HQ test tracks:ModelDeviceInference time (s, avg per track)RealtimeGPU2.08Realtime (ONNXRuntime)CPU6.9RealtimeCPU11.35OfflineCPU23.17Optimizing inferenceThe offline model has to trade off speed and memory usage from the embedded Wiener-EM step, so I only use it for offline CPU inference. The embedded Wiener-EM filtering step from the Norbert library also introduces additional complexity (complex numbers, etc.) for ONNX exporting.The ONNX optimizations could be taken further with more effort and/or modifying the xumx-sliCQ code:Improving the CUDA performanceEnhancing CUDA with the TensorRT providerEnhancing CPU performance with the OpenVino providerTraining$ docker run --rm -it \\\n --gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \\\n -v /path/to/MUSDB18-HQ/dataset:/MUSDB18-HQ \\\n -v /path/to/save/trained/model:/model \\\n -p 6006:6006 \\\n xumx-slicq-v2 \\\n python -m xumx_slicq_v2.training --helpThe Tensorboard training web dashboard is launched by the training script:http://127.0.0.1:6006/.To persist the model, you can volume mount a host volume to:/model(as in the command above). Killing and relaunching the container with a persisted model will continue the training process. If not, the trained model will disappear when the container is killed.The lowest lost achieved (complex cross-target MSE + mask sum MSE loss) was 0.0405 at epoch 198. The average epoch time was around 170 seconds, or just under 3 minutes, with a batch size of 64 (and 8 cpu workers for the dataloader).The lowest lost achieved for the realtime model was 0.0437 at epoch 161. The average epoch time was around 110 seconds, or just under 2 minutes, with a batch size of 64 (and 8 cpu workers for the dataloader).Hyperparameter tuning$ docker run --rm -it \\\n --gpus=all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 \\\n -v /path/to/MUSDB18-HQ/dataset:/MUSDB18-HQ \\\n -p 6006:6006 \\\n xumx-slicq-v2 \\\n python -m xumx_slicq_v2.optuna --helpThe Optuna tuning script runs on a cut-down training and validation dataset, and minimizes the SDR score achieved by the model within 10 epochs per trial. It runs for 100 trials and was used to discover improved hyperparameters for xumx-sliCQ-V2 (read more here).The Optuna tuning web dashboard is launched by the tuning script:http://127.0.0.1:6006/.Evaluation$ docker run --rm -it \\\n -v /path/to/MUSDB18-HQ/dataset:/MUSDB18-HQ \\\n xumx-slicq-v2 \\\n python -m xumx_slicq_v2.evaluation --helpBy default, the pretrained model will be evaluated.Pass different models to evaluateas a path inside the container relative to the source code dir:$ docker run --rm -it \\\n -v /path/to/MUSDB18-HQ/dataset:/MUSDB18-HQ \\\n -v /path/to/xumx-sliCQ/source/code:/xumx-sliCQ-V2/ \\\n xumx-slicq-v2 \\\n python -m xumx_slicq_v2.evaluation \\\n --model-path='/xumx-sliCQ-V2/model-to-evaluate'This takes ~2-3 hours to run on all 50 test tracks of MUSDB18-HQ on my CPU (5950X + 64GB RAM). It will output the BSS scores of each track, and at the end, output the median score across all frames and tracks:loading separator\nscale=bark, fbins=262, fmin=32.90, fmax=22050.00, sllen=18060, trlen=4516\n 0%| | 0/50 [00:00<?, ?it/s]track: AM Contra - Heart Peripheral\ngetting audio\napplying separation\nn chunks: 4\n...\n<output truncated>\n...\nvocals ==> SDR: 4.791 SIR: 7.794 ISR: 8.579 SAR: 4.500\ndrums ==> SDR: 4.846 SIR: 8.062 ISR: 8.649 SAR: 4.953\nbass ==> SDR: 4.690 SIR: 8.778 ISR: 5.558 SAR: 4.193\nother ==> SDR: 3.273 SIR: 2.532 ISR: 8.065 SAR: 4.422To get the total SDR, simply sum the four target SDRs and divide by 4:SDR_tot = (SDR_vocals + SDR_drums + SDR_bass + SDR_other)/4.0Cadenza challenge inference + evaluationCode related to the Cadenza challenge is stored in the./cadenzapackage:$ docker run --rm -it \\\n -v /path/to/MUSDB18-HQ/dataset/:/MUSDB18-HQ \\\n -v /path/to/cadenza/challenge/data/:/CADENZA \\\n -v /path/to/store/cadenza/results/:/exp \\\n xumx-slicq-v2 python -m cadenza.enhanceInference for the Cadenza Challenge task 1 (cad1) usesadapted baseline code from the recipe, as well as custom data downloaded as part of the challenge.The baseline uses Demucs to perform VDBO separation before further processing; I simply replaced Demucs with xumx-sliCQ-V2 in enhance.py.DemixUIThere's a toy UI I implemented using Kivy and asyncio. Install:sevagh@pop-os:~/repos/xumx-sliCQ$ pip install -e .[devel,demixui]\n...\n\n# kivy garden is weird, you need additional steps to install the matplotlib garden\nsevagh@pop-os:~/repos/xumx-sliCQ$ chmod +x /home/sevagh/mambaforge/envs/xumx_v2/bin/garden\nsevagh@pop-os:~/repos/xumx-sliCQ$ garden install matplotlibThe choice of asyncio is... questionable. The latency of the music demixing determines the latency of the user interface. The UI state is only updated after each segment is demixed. The user can control the levels of vocals/drums/bass/other via slides, and also toggle to a spectrogram view of the output audio:sevagh@pop-os:~/repos/xumx-sliCQ$ python -m xumx_slicq_v2.demixui --input-file=./masochist.wav\n`rk, fbins=262, fmin=32.90, fmax=22050.00, sllen=18060, trlen=4516\nONNXRuntime chosen provider: ['CPUExecutionProvider']\n[INFO ] [Logger ] Record log in /home/sevagh/.kivy/logs/kivy_23-04-04_31.txt\n[INFO ] [Kivy ] v2.1.0\n[INFO ] [Kivy ] Installed at \"/home/sevagh/mambaforge/envs/xumx_v2/lib/python3.10/site-packages/kivy/__init__.py\"\n...TheoryMotivationThe sliced Constant-Q Transform (sliCQT) is a realtime implementation of the Nonstationary Gabor Transform (NSGT), which is a generalized nonuniform time-frequency transform with perfect inverse. Nonuniform time-frequency transforms are better suited to representing sounds with time-varying frequencies, such as music and speech. The STFT is limited due to its use of fixed windows and the time-frequency uncertainty principle of Gabor.The NSGT can be used to implement a Constant-Q Transform (logarithmic scale), but it can use any type of frequency scale. In xumx-sliCQ and xumx-sliCQ-V2, the same Bark scale is used (262 Bark frequency bins from 32.9-22050 Hz).Past workIn 2021, I worked on xumx-sliCQ (V1),the first variant, to submit to the MDX 21 (Music Demixing Challenge 2021on AICrowd), and got my paper published tothe MDX 21 workshopat ISMIR 2021 (andarXiv). The time-frequency uncertainty principle aligned with my desired thesis topic at the Music Technology Master's program at McGill.In 2023, I chose to revisit the code of xumx-sliCQ for submission to theFirst Cadenza Challenge (CAD1), which is a music demixing challenge with the additional context of hearing loss and accessibility. Nonuniform time-frequency transforms, like the sliCQT, are related to the nolinear human auditory system, and I had specific auditory motivations for choosing the Bark scale for the sliCQT in xumx-sliCQ.Improvements over xumx-sliCQPerformance tuningFirst, I improved a lot of sloppy non-neural network code. The embeddednsgt library, which provides the sliCQT (and originates fromhttps://github.com/sevagh/nsgt, and before that, the sourcehttps://github.com/grrrr/nsgt), had a lot of calls to NumPy after my initial conversion to PyTorch, leading to unnecessary host-device communication throughout an epoch trained on my GPU.Next, I focused on making my epochs faster. The faster I can train it, the more I can work on xumx-sliCQ-V2 within a given time frame. To get the most out of the PyTorch code and my NVIDIA Ampere GPU (3090), I used two resources:Using the NVIDIA PyTorch Docker container (nvcr.io/nvidia/pytorch:22.12-py3) as the base for my training container to take advantage of implicit speedups provided by NVIDIA (e.g. automatically-enabledTF32)Modifying my PyTorch code according to theperformance tuning guideThe code changes were the following:In the model code:bias=Falsefor every conv layer that was followed by a batch norm:encoder.extend([\n Conv2d(\n hidden_size_1,\n hidden_size_2,\n (freq_filter, time_filter_2),\n bias=False,\n ),\n BatchNorm2d(hidden_size_2),\n ReLU(),\n])In the training code:Set the model.to(memory_format=torch.channels_last)Enable cuDNN benchmarkingtorch.backends.cudnn.benchmark = TrueForcing some additional more TF32-related settings:torch.backends.cudnn.allow_tf32 = TrueUsing AMP (Automatic Mixed Precision) with bfloat16 (on CUDA and CPU) (greatly reduces memory during training, allowing a larger batch size):with torch.autocast(\"cuda\", dtype=torch.bfloat16),\n torch.autocast(\"cpu\", dtype=torch.bfloat16):An epoch takes ~170s (train + validation) on my RTX 3090 with 24GB of GPU memory with--batch-size=64 --nb-workers=8. xumx-sliCQ by contrast took 350s per epoch with a batch size of 32 on an RTX 3080 Ti (which had 12GB GPU memory, half of my 3090). However, the old code used PyTorch 1.10, so the upgrade of V2 to 1.13 may also be contributing to improved performance.Using the full frequency bandwidthIn xumx-sliCQ, I didn't use frequency bins above 16,000 Hz in the neural network; the demixing was only done on the frequency bins lower than that limit, copying theumxpretrained model of UMX. UMX's other pretrained model,umxhq, uses the full spectral bandwidth. In xumx-sliCQ-V2, I removed the bandwidth parameter to pass all the frequency bins of the sliCQT through the neural network.Removing dilations from the convolution layersIn the CDAE of xumx-sliCQ, I used a dilation of 2 in the time axis to arbitrarily increase the receptive field without paying attention to music demixing quality (because dilations sound cool).In xumx-sliCQ-V2, I didn't use any dilations since I had no reason to.Removing the inverse sliCQT and time-domain SDR lossIn xumx-sliCQ, I applied the mixed-domain SDR and MSE loss of X-UMX. However, due to the large computational graph introduced by the inverse sliCQT operation, I was disabling its gradient:X = slicqt(x)\nXmag = torch.abs(X)\nYmag_est = unmix(Xmag)\nYcomplex_est = mix_phase(torch.angle(X), Ymag_est)\n\nwith torch.no_grad():\n y_est = islicqt(Ycomplex_est)Without this, the epoch time goes from 1-5 minutes to 25+ minutes, making training unfeasible. However, by disabling the gradient, the SDR loss can't influence the network performance. In practice, I found that the MSE was an acceptable correlate to SDR performance, and dropped the isliCQT and SDR loss calculation.Replacing the overlap-add with pure convolutional layersA quirk of the sliCQT is that rather than the familiar 2 dimensions of time and frequency, it has 3 dimensions: slice, time-per-slice, and frequency. Adjacent slices have a 50% overlap with one another and must be summed to get the true spectrogram in a destructive operation (50% of the time coefficients are lost, with no inverse).In xumx-sliCQ, an extra transpose convolutional layer with stride 2 is used to grow the time coefficients back to the original size after the 4-layer CDAE, to undo the destruction of the overlap-add.In xumx-sliCQ-V2, the first convolutional layer takes the overlap into account by setting the kernel and stride to the window and hop size of the destructive overlap-add. The result is that the input is downsampled in a way that is recovered by the final transpose convolution layer in the 4-layer CDAE, eliminating the need for an extra upsampling layer.Diagram (shown for one time-frequency block):By this point, I had a model that scored4.1 dBwith 28 MB of weights using magnitude MSE loss.Differentiable Wiener-EM and complex MSEBorrowing fromDanna-Sep, one of thetop performers in the MDX 21 challenge, the differentiable Wiener-EM step is used inside the neural network during training, such that the output of xumx-sliCQ-V2 is a complex sliCQT, and the complex MSE loss function is used instead of the magnitude MSE loss. Wiener-EM is applied separately in each frequency block as shown in thearchitecture diagram at the top of the README.This got the score to4.24 dBwith 28 MB of weights trained with complex MSE loss (0.0395).In xumx-sliCQ, Wiener-EM was only applied in the STFT domain as a post-processing step. The network was trained using magnitude MSE loss. The waveform estimate of xumx-sliCQ combined the estimate of the target magnitude with the phase of the mix (noisy phase or mix phase).Discovering hyperparameters with OptunaUsing the includedOptuna tuning script, new hyperparameters that gave the highest SDR after cut-down training/validation epochs were:Changing the hidden sizes (channels) of the 2-layer CDAE from 25,55 to 50,51 (increased the model size from ~28-30MB to 60MB)Changing the size of the time filter in the 2nd layer from 3 to 4Note that:The time kernel and stride of the first layer uses the window and hop size related to the overlap-add procedure, so it's not a tunable hyperparameterThe ragged nature of the sliCQT makes it tricky to modify frequency kernel sizes (since the time-frequency bins can vary in their frequency bins, from 1 single frequency up to 86), so I kept those fixed from xumx-sliCQThe sliCQT params could be considered a hyperparameter, but the shape of the sliCQT modifies the network architecture, so for simplicity I kept it the same as xumx-sliCQ (262 bins, Bark scale, 32.9-22050 Hz)This got the score to4.35 dBwith 60 MB of weights trained with complex MSE loss of 0.0390.Mask sum MSE lossIn spectrogram masking approaches to music demixing, commonly a ReLU or Sigmoid activation function is applied as the final activation layer to produce a non-negative mask for the mix magnitude spectrogram. In xumx-sliCQ, I used a Sigmoid activation in the final layer (UMX uses a ReLU). The final mask is multiplied with the input mixture:mix = x.clone()\n\n# x is a mask\nx = cdae(x)\n\n# apply the mask, i.e. multiplicative skip connection\nx = x*mixSince the mask for each target is between [0, 1], and the targets must add up to the mix, then the masks must add up to exactly 1:drum_mask*mix + vocals_mask*mix + other_mask*mix + bass_mask*mix = mix\ndrum_mask + vocals_mask + other_mask + bass_mask = 1.0In xumx-sliCQ-V2, I added a second loss term called the mask sum loss, which is the MSE between the sum of the four target masks and a matrix of 1s. This needs a small code change where both the complex slicqt (after Wiener-EM) and the sigmoid masks are returned in the training loop.This got the score to4.4 dBwith 60 MB of weights trained with complex MSE loss + mask sum loss of 0.0405.Realtime variantFor a future realtime demixing project, I decided to create a realtime variant of xumx-sliCQ-V2. To support realtime inputs:I added left padding of the first convolution layer, such that the intermediate representations throughout the autoencoder are only derived from causal inputsI replaced the resource-intensive Wiener-EM target maximization with the naive mix-phase approach, which is computationally much lighter (simply combine the target magnitude slicqt with the phase of the mix)"} +{"package": "xumx-spleeterweb", "pacakge-description": "CrossNet-Open-Unmix (X-UMX) for Spleeter WebThis is a modified version of theofficial X-UMX repomade to be compatible withSpleeter Web!This repository contains the NNabla implementation ofCrossNet-Open-Unmix (X-UMX), an improved version ofOpen-Unmix (UMX)for music source separation. X-UMX achieves an improved performance without additional learnable parameters compared to the original UMX model. Details of X-UMX can be found inour paper.Quick Music Source Separation Demo by X-UMXFrom the Colab link below, you can try using X-UMX to generate and listen to separated audio sources of your audio music file. Please give it a try!Related Projects:x-umx |open-unmix-nnabla|open-unmix-pytorch|musdb|museval|norbertThe ModelAs shown in Figure (b),X-UMXhas almost the same architecture as the original UMX,\nbut only differs by two additional average operations that link the instrument models together.\nSince these operations are not DNN layers, the number of learnable parameters ofX-UMXis\nthe same as for the original UMX and also the computational complexity is almost the same.\nBesides the model, there are two more differences compared to the original UMX. In particular,\nMulti Domain Loss (MDL) and a Combination Loss (CL) are used during training, which are different\nfrom the original loss function of UMX. Hence, these three contributions, i.e., (i) Crossing architecture,\n(ii) MDL and (iii) CL, make the original UMX more effective and successful without additional learnable parameters.Getting startedInstallationFor installation we recommend to use theAnacondapython distribution. To create a conda environment foropen-unmix, simply run:conda env create -f environment-X.ymlwhereXis either [cpu,gpu], depending on your system.Source separation with pretrained modelHow to separate using pre-trained X-UMXDownloadherea pre-trained model of X-UMX which results in the scores given inour paper.\nThe model was trained on theMUSDB18dataset.In order to use it, please use the following command:python-mxumx.test--inputs[Inputmixture(anyaudioformatsupportedbyFFMPEG)]--model{pathtodownloadedx-umx.h5weightsfile}--contextcpu--chunk-dur10--outdir./results/Please note that our X-UMX integrates the different instrument networks of the original UMX by a crossing operation, and thus X-UMX requires more memory. So, it maybe difficult to run the model on smaller GPU. So, though default choice is GPU inference, above example uses the option--context cpu. Also note that because memory requirement is high, we suggest users to set--chunk-durwith values appropriate for each computer. It is used to break audio into smaller chunks, separate sources and stitch them back together. If your inference crashes, kindly reduce chunk duration and try again.Evaluation usingmusevalTo perform evaluation in comparison to other SiSEC systems, you would need to install themusevalpackage usingpip install musevaland then run the evaluation usingpython-mxums.eval--model[pathtodownloadedx-umx.h5model]--root[PathofMUSDB18]--outdir[Pathtosavemusdbestimates]--evaldir[Pathtosavemusevalresults]Training X-UMXX-UMX can be trained using the default parameters of the train.py function.TheMUSDB18is one of the largest freely available datasets for professionally produced music tracks (~10h duration) of different styles. It comes with isolateddrums,bass,vocalsandothersstems.MUSDB18contains two subsets: \"train\", composed of 100 songs, and \"test\", composed of 50 songs.To directly trainx-umx, we first would need to download the dataset and place inunzippedin a directory of your choice (calledroot).ArgumentDescriptionDefault--root <str>path to root of dataset on disk.NoneAlso note that, if--rootis not specified, we automatically download a 7 second preview version of the MUSDB18 dataset. While this is comfortable for testing purposes, we wouldn't recommend to actually train your model on this.Training (Single/Distributed training) can be started using below commands.Single GPU trainingpython-mxumx.train--root[PathofMUSDB18]--output[Pathtosaveweights]Distributed TrainingFor distributed traininginstall NNabla package compatible with Multi-GPU execution. Use the below code to start the distributed training.export CUDA_VISIBLE_DEVICES=0,1,2,3 {device ids that you want to use}mpirun-n{no.ofdevices}python-mxumx.train--root[PathofMUSDB18]--output[Pathtosaveweights]Please note that above sample training scripts will work on high quality 'STEM' or low quality 'MP4 files'. In case you would like faster data loading, kindly look atmore details hereto generate decoded 'WAV' files. In that case, please use--is-wavflag for training.TrainingMUSDB18usingx-umxcomes with several design decisions that we made as part of our defaults to improve efficiency and performance:chunking: we do not feed full audio tracks intoopen-unmixbut instead chunk the audio into 6s excerpts (--seq-dur 6.0).balanced track sampling: to not create a bias for longer audio tracks we randomly yield one track from MUSDB18 and select a random chunk subsequently. In one epoch we select (on average) 64 samples from each track.source augmentation: we apply random gains between0.25and1.25to all sources before mixing. Furthermore, we randomly swap the channels the input mixture.random track mixing: for a given target we select arandom trackwith replacement. To yield a mixture we draw the interfering sources from different tracks (again with replacement) to increase generalization of the model.fixed validation split: we provide a fixed validation split of14 tracks. We evaluate on these tracks in full length instead of using chunking to have evaluation as close as possible to the actual test data.Some of the parameters for the MUSDB sampling can be controlled using the following arguments:ArgumentDescriptionDefault--is-wavloads the decoded WAVs instead of STEMS for faster data loading. Seemore details here.False--samples-per-track <int>sets the number of samples that are randomly drawn from each track64--source-augmentations <list[str]>applies augmentations to each audio source before mixinggain channelswapTraining and Model ParametersAn extensive list of additional training parameters allows researchers to quickly try out different parameterizations such as a different FFT size. The table below, we list the additional training parameters and their default values:ArgumentDescriptionDefault--output <str>path where to save the trained output model as well as checkpoints../x-umx--model <str>path to checkpoint of target model to resume training.not set--epochs <int>Number of epochs to train1000--batch-size <int>Batch size has influence on memory usage and performance of the LSTM layer16--patience <int>Early stopping patience1000--seq-dur <int>Sequence duration in seconds of chunks taken from the dataset. A value of<=0.0results in full/variable length6.0--unidirectionalchanges the bidirectional LSTM to unidirectional (for real-time applications)not set--hidden-size <int>Hidden size parameter of dense bottleneck layers512--nfft <int>STFT FFT window length in samples4096--nhop <int>STFT hop length in samples1024--lr <float>learning rate0.001--lr-decay-patience <int>learning rate decay patience for plateau scheduler80--lr-decay-gamma <float>gamma of learning rate plateau scheduler.0.3--weight-decay <float>weight decay for regularization0.00001--bandwidth <int>maximum bandwidth in Hertz processed by the LSTM. Input and Output is always full bandwidth!16000--nb-channels <int>set number of channels for model (1 for mono (spectral downmix is applied,) 2 for stereo)2--seed <int>Initial seed to set the random initialization42--valid_dur <float>To prevent GPU memory overflow, validation is calculated and averaged pervalid_durseconds.100.0AuthorsRyosuke Sawata(*), Stefan Uhlich(**), Shusuke Takahashi(*) and Yuki Mitsufuji(*)(*) Sony Corporation, Tokyo, Japan(**)Sony Europe B.V., Stuttgart, GermanyReferencesIf you use CrossNet-open-unmix for your research \u2013 Cite CrossNet-Open-Unmix@article{sawata20, \n title={All for One and One for All: Improving Music Separation by Bridging Networks},\n author={Ryosuke Sawata and Stefan Uhlich and Shusuke Takahashi and Yuki Mitsufuji},\n year={2020},\n eprint={2010.04228},\n archivePrefix={arXiv},\n primaryClass={eess.AS}}If you use open-unmix for your research \u2013 Cite Open-Unmix@article{stoter19, \n author={F.-R. St\\\\\"oter and S. Uhlich and A. Liutkus and Y. Mitsufuji}, \n title={Open-Unmix - A Reference Implementation for Music Source Separation}, \n journal={Journal of Open Source Software}, \n year=2019,\n doi ={10.21105/joss.01667},\n url ={https://doi.org/10.21105/joss.01667}}If you use the MUSDB dataset for your research - Cite the MUSDB18 Dataset@misc{MUSDB18,\n author ={Rafii, Zafar and\n Liutkus, Antoine and\n Fabian-Robert St{\\\"o}ter and\n Mimilakis, Stylianos Ioannis and\n Bittner, Rachel},\n title ={The{MUSDB18}corpus for music separation},\n month = dec,\n year = 2017,\n doi ={10.5281/zenodo.1117372},\n url ={https://doi.org/10.5281/zenodo.1117372}}If compare your results with SiSEC 2018 Participants - Cite the SiSEC 2018 LVA/ICA Paper@inproceedings{SiSEC18,\n author=\"St{\\\"o}ter, Fabian-Robert and Liutkus, Antoine and Ito, Nobutaka\",\n title=\"The 2018 Signal Separation Evaluation Campaign\",\n booktitle=\"Latent Variable Analysis and Signal Separation:\n 14th International Conference, LVA/ICA 2018, Surrey, UK\",\n year=\"2018\",\n pages=\"293--305\"}\u26a0\ufe0f Please note that the official acronym forCrossNet-Open-UnmixisX-UMX."} +{"package": "xumx-unofficial", "pacakge-description": "CrossNet-Open-Unmix (X-UMX) for Spleeter WebThis is a modified version of theofficial X-UMX repomade to be compatible withSpleeter Web!This repository contains the NNabla implementation ofCrossNet-Open-Unmix (X-UMX), an improved version ofOpen-Unmix (UMX)for music source separation. X-UMX achieves an improved performance without additional learnable parameters compared to the original UMX model. Details of X-UMX can be found inour paper.Quick Music Source Separation Demo by X-UMXFrom the Colab link below, you can try using X-UMX to generate and listen to separated audio sources of your audio music file. Please give it a try!Related Projects:x-umx |open-unmix-nnabla|open-unmix-pytorch|musdb|museval|norbertThe ModelAs shown in Figure (b),X-UMXhas almost the same architecture as the original UMX,\nbut only differs by two additional average operations that link the instrument models together.\nSince these operations are not DNN layers, the number of learnable parameters ofX-UMXis\nthe same as for the original UMX and also the computational complexity is almost the same.\nBesides the model, there are two more differences compared to the original UMX. In particular,\nMulti Domain Loss (MDL) and a Combination Loss (CL) are used during training, which are different\nfrom the original loss function of UMX. Hence, these three contributions, i.e., (i) Crossing architecture,\n(ii) MDL and (iii) CL, make the original UMX more effective and successful without additional learnable parameters.Getting startedInstallationFor installation we recommend to use theAnacondapython distribution. To create a conda environment foropen-unmix, simply run:conda env create -f environment-X.ymlwhereXis either [cpu,gpu], depending on your system.Source separation with pretrained modelHow to separate using pre-trained X-UMXDownloadherea pre-trained model of X-UMX which results in the scores given inour paper.\nThe model was trained on theMUSDB18dataset.In order to use it, please use the following command:python-mxumx.test--inputs[Inputmixture(anyaudioformatsupportedbyFFMPEG)]--model{pathtodownloadedx-umx.h5weightsfile}--contextcpu--chunk-dur10--outdir./results/Please note that our X-UMX integrates the different instrument networks of the original UMX by a crossing operation, and thus X-UMX requires more memory. So, it maybe difficult to run the model on smaller GPU. So, though default choice is GPU inference, above example uses the option--context cpu. Also note that because memory requirement is high, we suggest users to set--chunk-durwith values appropriate for each computer. It is used to break audio into smaller chunks, separate sources and stitch them back together. If your inference crashes, kindly reduce chunk duration and try again.Evaluation usingmusevalTo perform evaluation in comparison to other SiSEC systems, you would need to install themusevalpackage usingpip install musevaland then run the evaluation usingpython-mxums.eval--model[pathtodownloadedx-umx.h5model]--root[PathofMUSDB18]--outdir[Pathtosavemusdbestimates]--evaldir[Pathtosavemusevalresults]Training X-UMXX-UMX can be trained using the default parameters of the train.py function.TheMUSDB18is one of the largest freely available datasets for professionally produced music tracks (~10h duration) of different styles. It comes with isolateddrums,bass,vocalsandothersstems.MUSDB18contains two subsets: \"train\", composed of 100 songs, and \"test\", composed of 50 songs.To directly trainx-umx, we first would need to download the dataset and place inunzippedin a directory of your choice (calledroot).ArgumentDescriptionDefault--root <str>path to root of dataset on disk.NoneAlso note that, if--rootis not specified, we automatically download a 7 second preview version of the MUSDB18 dataset. While this is comfortable for testing purposes, we wouldn't recommend to actually train your model on this.Training (Single/Distributed training) can be started using below commands.Single GPU trainingpython-mxumx.train--root[PathofMUSDB18]--output[Pathtosaveweights]Distributed TrainingFor distributed traininginstall NNabla package compatible with Multi-GPU execution. Use the below code to start the distributed training.export CUDA_VISIBLE_DEVICES=0,1,2,3 {device ids that you want to use}mpirun-n{no.ofdevices}python-mxumx.train--root[PathofMUSDB18]--output[Pathtosaveweights]Please note that above sample training scripts will work on high quality 'STEM' or low quality 'MP4 files'. In case you would like faster data loading, kindly look atmore details hereto generate decoded 'WAV' files. In that case, please use--is-wavflag for training.TrainingMUSDB18usingx-umxcomes with several design decisions that we made as part of our defaults to improve efficiency and performance:chunking: we do not feed full audio tracks intoopen-unmixbut instead chunk the audio into 6s excerpts (--seq-dur 6.0).balanced track sampling: to not create a bias for longer audio tracks we randomly yield one track from MUSDB18 and select a random chunk subsequently. In one epoch we select (on average) 64 samples from each track.source augmentation: we apply random gains between0.25and1.25to all sources before mixing. Furthermore, we randomly swap the channels the input mixture.random track mixing: for a given target we select arandom trackwith replacement. To yield a mixture we draw the interfering sources from different tracks (again with replacement) to increase generalization of the model.fixed validation split: we provide a fixed validation split of14 tracks. We evaluate on these tracks in full length instead of using chunking to have evaluation as close as possible to the actual test data.Some of the parameters for the MUSDB sampling can be controlled using the following arguments:ArgumentDescriptionDefault--is-wavloads the decoded WAVs instead of STEMS for faster data loading. Seemore details here.False--samples-per-track <int>sets the number of samples that are randomly drawn from each track64--source-augmentations <list[str]>applies augmentations to each audio source before mixinggain channelswapTraining and Model ParametersAn extensive list of additional training parameters allows researchers to quickly try out different parameterizations such as a different FFT size. The table below, we list the additional training parameters and their default values:ArgumentDescriptionDefault--output <str>path where to save the trained output model as well as checkpoints../x-umx--model <str>path to checkpoint of target model to resume training.not set--epochs <int>Number of epochs to train1000--batch-size <int>Batch size has influence on memory usage and performance of the LSTM layer16--patience <int>Early stopping patience1000--seq-dur <int>Sequence duration in seconds of chunks taken from the dataset. A value of<=0.0results in full/variable length6.0--unidirectionalchanges the bidirectional LSTM to unidirectional (for real-time applications)not set--hidden-size <int>Hidden size parameter of dense bottleneck layers512--nfft <int>STFT FFT window length in samples4096--nhop <int>STFT hop length in samples1024--lr <float>learning rate0.001--lr-decay-patience <int>learning rate decay patience for plateau scheduler80--lr-decay-gamma <float>gamma of learning rate plateau scheduler.0.3--weight-decay <float>weight decay for regularization0.00001--bandwidth <int>maximum bandwidth in Hertz processed by the LSTM. Input and Output is always full bandwidth!16000--nb-channels <int>set number of channels for model (1 for mono (spectral downmix is applied,) 2 for stereo)2--seed <int>Initial seed to set the random initialization42--valid_dur <float>To prevent GPU memory overflow, validation is calculated and averaged pervalid_durseconds.100.0AuthorsRyosuke Sawata(*), Stefan Uhlich(**), Shusuke Takahashi(*) and Yuki Mitsufuji(*)(*) Sony Corporation, Tokyo, Japan(**)Sony Europe B.V., Stuttgart, GermanyReferencesIf you use CrossNet-open-unmix for your research \u2013 Cite CrossNet-Open-Unmix@article{sawata20, \n title={All for One and One for All: Improving Music Separation by Bridging Networks},\n author={Ryosuke Sawata and Stefan Uhlich and Shusuke Takahashi and Yuki Mitsufuji},\n year={2020},\n eprint={2010.04228},\n archivePrefix={arXiv},\n primaryClass={eess.AS}}If you use open-unmix for your research \u2013 Cite Open-Unmix@article{stoter19, \n author={F.-R. St\\\\\"oter and S. Uhlich and A. Liutkus and Y. Mitsufuji}, \n title={Open-Unmix - A Reference Implementation for Music Source Separation}, \n journal={Journal of Open Source Software}, \n year=2019,\n doi ={10.21105/joss.01667},\n url ={https://doi.org/10.21105/joss.01667}}If you use the MUSDB dataset for your research - Cite the MUSDB18 Dataset@misc{MUSDB18,\n author ={Rafii, Zafar and\n Liutkus, Antoine and\n Fabian-Robert St{\\\"o}ter and\n Mimilakis, Stylianos Ioannis and\n Bittner, Rachel},\n title ={The{MUSDB18}corpus for music separation},\n month = dec,\n year = 2017,\n doi ={10.5281/zenodo.1117372},\n url ={https://doi.org/10.5281/zenodo.1117372}}If compare your results with SiSEC 2018 Participants - Cite the SiSEC 2018 LVA/ICA Paper@inproceedings{SiSEC18,\n author=\"St{\\\"o}ter, Fabian-Robert and Liutkus, Antoine and Ito, Nobutaka\",\n title=\"The 2018 Signal Separation Evaluation Campaign\",\n booktitle=\"Latent Variable Analysis and Signal Separation:\n 14th International Conference, LVA/ICA 2018, Surrey, UK\",\n year=\"2018\",\n pages=\"293--305\"}\u26a0\ufe0f Please note that the official acronym forCrossNet-Open-UnmixisX-UMX."} +{"package": "xun", "pacakge-description": "No description available on PyPI."} +{"package": "xunbao_models", "pacakge-description": "No description available on PyPI."} +{"package": "xuner", "pacakge-description": "UNKNOWN"} +{"package": "x-unet", "pacakge-description": "No description available on PyPI."} +{"package": "xunfei", "pacakge-description": "No description available on PyPI."} +{"package": "xunfeispark", "pacakge-description": "PySparkAI - WebSocket Chatbot Client for \u661f\u706b\u5927\u6a21\u578bPySparkAI \u662f\u4e00\u4e2a\u57fa\u4e8eWebSocket\u8c03\u7528\u661f\u706b\u5927\u6a21\u578bAPI\u7684\u5ba2\u6237\u7aef\u3002\u5176\u76ee\u7684\u662f\u4e3a\u7528\u6237\u63d0\u4f9b\u9ad8\u5ea6\u5c01\u88c5\u7684\u65b9\u6cd5\uff0c\u4ece\u800c\u7b80\u5316\u4f7f\u7528\u8fc7\u7a0b\u3002\u7279\u6027\u57fa\u4e8eWebSocket\u7684\u5b9e\u65f6\u804a\u5929\uff1a\u786e\u4fdd\u53ca\u65f6\u3001\u6301\u7eed\u7684\u4ea4\u4e92\u661f\u706b\u5927\u6a21\u578bAPI\uff1a\u8c03\u7528\u5148\u8fdb\u7684AI\u6280\u672f\u6765\u63d0\u4f9b\u7cbe\u786e\u7684\u56de\u7b54\u9ad8\u5ea6\u5c01\u88c5\uff1a\u51cf\u5c11\u914d\u7f6e\u548c\u5f15\u5bfc\u65f6\u95f4\uff0c\u5373\u63d2\u5373\u7528\u5feb\u901f\u5f00\u59cb\u5b89\u88c5pipinstallxunfeispark\u4f7f\u7528\u67e5\u770bdemo.py\u811a\u672c\u4ee5\u4e86\u89e3\u5982\u4f55\u4f7f\u7528PySparkAI\u3002\u4ee5\u4e0b\u662fdemo.py\u7684\u7b80\u77ed\u6458\u8981:frompysparkaiimportPySparkAIdefget_credentials_from_user():\"\"\"\u83b7\u53d6\u7528\u6237\u8f93\u5165\u7684\u654f\u611f\u4fe1\u606f\u3002\"\"\"APP_ID=\"\u6b64\u5904\u586b\u5165\u4f60\u7684APP_ID\"API_KEY=\"\u6b64\u5904\u586b\u5165\u4f60\u7684API_KEY\"API_SECRET=\"\u6b64\u5904\u586b\u5165\u4f60\u7684API_SECRET\"SPARK_URL=\"\u6b64\u5904\u586b\u5165\u4f60\u7684SPARK_URL\"DOMAIN=\"\u6b64\u5904\u586b\u5165\u4f60\u7684DOMAIN\"returnAPP_ID,API_KEY,API_SECRET,SPARK_URL,DOMAIN# \u4ee5\u4e0a\u6240\u6709\u4fe1\u606f\u90fd\u53ef\u4ee5\u5728\u4f60\u7684\u8baf\u98de\u5f00\u653e\u5e73\u53f0\u7684\u63a7\u5236\u53f0\u4e2d\u627e\u5230defmain():APP_ID,API_KEY,API_SECRET,SPARK_URL,DOMAIN=get_credentials_from_user()ai=PySparkAI(app_id=APP_ID,api_key=API_KEY,api_secret=API_SECRET,spark_url=SPARK_URL,domain=DOMAIN)prompt_message={\"role\":\"system\",\"content\":\"\u5728\u4e00\u4e2a\u9065\u8fdc\u7684\u661f\u7403\u4e0a\uff0c\u6709\u4e00\u4f4d\u667a\u8005\u540d\u4e3aZarnak\uff0c\u4ed6\u5bf9\u4e8e\u4eba\u7c7b\u4e16\u754c\u6709\u7740\u6df1\u539a\u7684\u4e86\u89e3\u3002\"}question_message={\"role\":\"user\",\"content\":\"Zarnak, \u4f60\u80fd\u544a\u8bc9\u6211\u5730\u7403\u4e0a\u7684\u4eba\u7684\u6027\u683c\u4e3a\u4ec0\u4e48\u591a\u79cd\u591a\u6837\u5417\uff1f\"}format_specification_message={\"role\":\"system\",\"content\":\"\u8bf7\u4f7f\u7528\u7b2c\u4e09\u4eba\u79f0\uff0c\u4ee5\u6545\u4e8b\u7684\u65b9\u5f0f\u56de\u7b54\u3002\"}messages=[prompt_message,format_specification_message,question_message]completion=ai.chat(messages,temperature=0.3,max_tokens=200)formatted_answer=f\"\"\"Prompt:{prompt_message[\"content\"]}\u683c\u5f0f\u8981\u6c42:{format_specification_message[\"content\"]}\u95ee\u9898:{question_message[\"content\"]}\u56de\u7b54:{completion[\"choices\"][0][\"message\"]}\"\"\"print(formatted_answer)print(\"Token \u4f7f\u7528\u60c5\u51b5:\")forkey,valueincompletion[\"usage\"].items():print(f\"{key}:{value}\")if__name__==\"__main__\":main()\u5b8c\u6574\u7684demo.py\u811a\u672c\u5728\u4ed3\u5e93\u4e2d\u53ef\u7528\u3002\u5f00\u53d1\u4f9d\u8d56websocket-client: \u4e3a\u9879\u76ee\u63d0\u4f9bWebSocket\u901a\u4fe1\u529f\u80fd\u3002\u8d21\u732e\u5982\u679c\u60a8\u60f3\u4e3a\u8be5\u9879\u76ee\u505a\u51fa\u8d21\u732e\uff0c\u8bf7\u786e\u4fdd\u9075\u5faa\u4ee5\u4e0b\u6b65\u9aa4\uff1aFork\u8fd9\u4e2a\u4ed3\u5e93:PySparkAI on GitLab\u3002\u5f53\u7136\uff0c\u8fd9\u91cc\u7684GitLab\u662f\u5927\u9646\u672c\u571f\u5316\u7684JihuLab\u3002\u521b\u5efa\u4f60\u7684\u529f\u80fd\u5206\u652f (git checkout -b feature/YourFeature)\u63d0\u4ea4\u4f60\u7684\u66f4\u6539 (git commit -am 'Add some feature')\u63a8\u9001\u5230\u5206\u652f (git push origin feature/YourFeature)\u5728GitLab\u4e0a\u521b\u5efa\u4e00\u4e2a\u65b0\u7684Merge Request\u4f60\u4e5f\u80fd\u591f\u5728PySparkAI on Github\u4e0a\u627e\u5230\u5b83\u3002\u8bb8\u53ef\u8be5\u9879\u76ee\u4f7f\u7528MIT\u8bb8\u53ef\u3002\u8054\u7cfb\u5982\u6709\u4efb\u4f55\u95ee\u9898\u6216\u5efa\u8bae\uff0c\u8bf7\u8054\u7cfbshadow.li981@gmail.com.\u6587\u6863\u66f4\u591a\u5173\u4e8epysparkai\u7684\u8be6\u7ec6\u6587\u6863\uff0c\u5305\u62ec\u5982\u4f55\u5b89\u88c5\u3001\u4f7f\u7528\u548c\u5176\u4ed6\u4fe1\u606f\uff0c\u8bf7\u8bbf\u95ee\u8fd9\u91cc\u3002"} +{"package": "xunionfind", "pacakge-description": "It\u2019s a UnionFind model."} +{"package": "xUnique", "pacakge-description": "xUnique, is a pure Python script to regenerateproject.pbxproj,\na.k.a the Xcode project file, and make it unique and same on any\nmachine.As you may know, the UUID generated by Xcode (a.k.arfc4122) in the file is not\nunique for the same added file( or other entries like groups,build\nphases,etc.) on different machines, which makes it a developer\u2019s\nnightmare to merge and resolve conflicts inproject.pbxproj.xUniqueconvert all the 96bitsUUID(24 alphanumeric chars) to\nMD5 hex digest(32 hex chars), and Xcode do recognize these MD5 digests.What it does & How it worksconvertproject.pbxprojto JSON formatIterate allobjectsin JSON and give every UUID an absolute path,\nand create a new UUID using MD5 hex digest of the pathAll elements in this json object is actually connected as a treeWe give a path attribute to every node of the tree using its\nunique attribute; this path is the absolute path to the root node,Apply MD5 hex digest to the path for the nodeReplace all old UUIDs with the MD5 hex digest and also remove unused\nUUIDs that are not in the current node tree and UUIDs in wrong formatSort the project file inlcudingchildren,files,PBXFileReferenceandPBXBuildFilelist and remove all\nduplicated entries in these listsseesort_pbxprojmethod in xUnique.py if you want to know the\nimplementation;It\u2019s ported from my modifiedsort-Xcode-project-file,\nwith some differences in orderingPBXFileReferenceandPBXBuildFileWith differentoptions, you can usexUniquewith more flexibilityChange LogThechange logcontains the list of changes and latest version information of each\nversion. Please downloadLatest Releasefor production environment\nusage.Installationinstall fromPyPi:$pipinstallxUniqueinstall locally:$pythonsetup.pyinstallIt will install a command line scriptxuniquein dir/usr/local/bin(make sure you have added this dir to your$PATH). So you can invoke xUnique directly from command line:$xunique-hHow to useThere are many ways to use this script after you installedxUnique. I will introduce two:Xcode \u201cbuild post-action\u201d (Recommended)openEdit Schemein Xcode (shortcut:\u2318+Shift+,)choose the scheme you use to run your projectexpandBuild, selectPost-actionsclick symbol+on the left bottom corner of the right panechooseNew Run Script Actionchoose your selected scheme name inProvide build settings frominput commands below:$xunique\"${PROJECT_FILE_PATH}/project.pbxproj\"clickCloseand it\u2019s all done.Next time when you Build or Run the project, xUnique would be\ntriggered after build success. If the build works, you could commit\nall files.Demo gif animation ishereGit hookcreate a git hook in Terminal like:${echo'#!/bin/sh';echo'xunique path/to/MyProject.xcodeproj';}>.git/hooks/pre-commitAdd permissionchmod 755.git/hooks/pre-commitxUnique will be triggered when you trying to commit:Using option-cin command would fail the commit operation if\nproject file is modified. Then you can add the modified project\nfile and commit all the files again.Option-cis not activated by default. The commit operation\nwill proceed successfully even if the project file is modified by\nxUnique. So do not push the commit unless you add the modified\nproject file again and do another commit.CocoaPods usersIf your project uses CocoaPods AND addedPodsdirectory to source control, you may also need to uniquifyPods.xcodeproj:Xcode \u201cbuild post-action\u201d : add extra command below$xunique\"${PODS_ROOT}/Pods.xcodeproj\"Git hook: add one more command in hook script${echo'#!/bin/sh';echo'xunique path/to/MyProject.xcodeproj';echo'xunique path/to/Pods.xcodeproj';}>.git/hooks/pre-commitSupported argument optionsUse options in xUnique:$xunique[options]\"path_to/YourProject.xcodeproj/or_project.pbxproj\"-vprint verbose output, and generatedebug_result.jsonfile for debug.-uuniquify project file, that is, replace UUID to MD5 digest.-ssort project file includingchildren,files,PBXFileReferenceandPBXBuildFilelist and remove all duplicated entries in these lists. Supports both original and uniquified project file.-psortPBXFileReferenceandPBXBuildFilesections in project file ordered by file names. Only works with-s. Before v4.0.0, this was hard-coded in-soption and cannot be turned off. Starting from v4.0.0, without this option along with-s, xUnique will sort these two types by MD5 digests, the same as Xcode does.-cWhen project file was modified, xUnique quit with non-zero status. Without this option, the status code would be zero if so. This option is usually used in Git hook to submit xUnique result combined with your original new commit.Note: If neither-unor-sexists,-u-swill be appended to existing option list.ExamplesAPNS Pusheris a Xcode project which contains a subproject named \u201cFragaria\u201d as git submodule. UsexUniqueto convert it. You can clonemy forked repoand try to open and build it in Xcode. You will find thatxUniquedoes not affect the project at all.The initial diff result could be foundhere.The diff result with my modifiedsort-Xcode-project-filewithPBXBuildFileandPBXFileReferencesort support could be foundhere.Pure python sort result could be foundherePBX sections sorted by MD5 digest result (default in v4.0.0) could be\nfoundbelowadd xUnique to Xcode post actionNOTICEAll project members must add the build post-action or git hook. Thus\nthe project file would be consistent in the repository.Tested supportedisatypes:PBXProjectXCConfigurationListPBXNativeTargetPBXTargetDependencyPBXContainerItemProxyXCBuildConfigurationPBXSourcesBuildPhasePBXFrameworksBuildPhasePBXResourcesBuildPhasePBXFrameworksBuildPhasePBXCopyFilesBuildPhasePBXHeadersBuildPhasePBXShellScriptBuildPhasePBXBuildRulePBXBuildFilePBXReferenceProxyPBXFileReferencePBXGroupPBXVariantGroupAuthorsXiao Wang (seganw)ContributionsI only tested on several single projects and several projects with a\nsubproject, so maybe there should be more unconsidered conditions. If\nyou get any problem, feel free to fire a Pull Request or IssueYou can also buy me a cup of tea:LicenseLicensed under the Apache License, Version 2.0 (the \u201cLicense\u201d); you may\nnot use this file except in compliance with the License. You may obtain\na copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \u201cAS IS\u201d BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License."} +{"package": "xunit2testrail", "pacakge-description": "This reporter helps to send xUnit XML report from automated tests to\nTestRail.Matching rulesFor correct reporting, reporter makesindentifications stringsfor\nall xUnit and TestRail cases. Identification strings are makes by\ntemplates - one for xUnit and one for TestRail Case. Templates are justFormat\nStrings.\nNext reporter searchs xUnit testcase indentification string in all\nTestRail cases indentifications strings.xUnit template variablesclassname (liketempest.api.network.test_routers.RoutersIpV6Test)methodname (from report, liketest_update_router_admin_state[id-a8902683-c788-4246-95c7-ad9c6d63a4d9])id (extracts frommethodname, e.g. fortest_a[(12345)]it\nwill be12345)uuid (extracts frommethodname, e.g. fortest_quotas[network,id-2390f766-836d-40ef-9aeb-e810d78207fb,network]it will be2390f766-836d-40ef-9aeb-e810d78207fb)Argument name:--xunit-name-templateDefault value:{id}xUnit template may looks like'{classname}.{methodname}'or just'{id}'.TestRail template variablescustom_report_label (Report Label in UI)custom_test_group (Test Group in UI)titleArgument name:--testrail-name-templateDefault value:{custom_report_label}Also possible to use other variables (full list here -TestRail Api\nDocumentation)TestRail template may looks like'{custom_report_label}'or'{custom_test_group}.{title}'.CollisionsIf one xUnit case matches to more than one TestRail case or one TestRail\ncase matches to more than one xUnit case - reporter stops work, print\nout this cases and exits with error.Usageusage: report [-h] [--xunit-name-template XUNIT_NAME_TEMPLATE]\n [--testrail-name-template TESTRAIL_NAME_TEMPLATE]\n [--env-description ENV_DESCRIPTION]\n (--iso-id ISO_ID | --testrail-plan-name TESTRAIL_PLAN_NAME)\n [--test-results-link TEST_RESULTS_LINK]\n [--testrail-url TESTRAIL_URL] [--testrail-user TESTRAIL_USER]\n [--testrail-password TESTRAIL_PASSWORD]\n [--testrail-project TESTRAIL_PROJECT]\n [--testrail-milestone TESTRAIL_MILESTONE]\n [--testrail-suite TESTRAIL_SUITE] [--send-skipped]\n [--paste-url PASTE_URL] [--verbose]\n xunit_report\n\nReport to testrail\n\npositional arguments:\n xunit_report xUnit report XML file\n\noptional arguments:\n -h, --help show this help message and exit\n --xunit-name-template XUNIT_NAME_TEMPLATE\n template for xUnit cases to make id string\n --testrail-name-template TESTRAIL_NAME_TEMPLATE\n template for TestRail cases to make id string\n --env-description ENV_DESCRIPTION\n env deploy type description (for TestRun name)\n --iso-id ISO_ID id of build Fuel iso (DEPRECATED)\n --testrail-plan-name TESTRAIL_PLAN_NAME\n name of test plan to be displayed in testrail\n --test-results-link TEST_RESULTS_LINK\n link to test job results\n --testrail-url TESTRAIL_URL\n base url of testrail\n --testrail-user TESTRAIL_USER\n testrail user\n --testrail-password TESTRAIL_PASSWORD\n testrail password\n --testrail-project TESTRAIL_PROJECT\n testrail project name\n --testrail-milestone TESTRAIL_MILESTONE\n testrail project milestone\n --testrail-suite TESTRAIL_SUITE\n testrail project suite name\n --send-skipped send skipped cases to testrail\n --paste-url PASTE_URL\n paste service to send test case logs and trace\n --verbose, -v Verbose mode"} +{"package": "xunitgen", "pacakge-description": "No description available on PyPI."} +{"package": "xunitmerge", "pacakge-description": "Utility for merging multiple XUnit xml reports into a single xml report.The primary purpose of this package is to be able to merge XUnit reports\ngenerated by nosetests (e.g.nosetests--with-xunit). This is especially\nuseful when nosetests needs to be run multiple times for different parts of\na project and then all reports need to be merged to a single report\n(similar to what coverage combine does with multiple coverage reports).InstallingYou can installxunitmergeusing pip:$ pip install xunitmergeOr alternatively you can install thedevelopmentversion:$ pip install xunitmerge==devUsingTo use the plugin, use an executablexunitmergewhich should become\navailable after the installation..\nTo see it\u2019s usage dialog, you can run it with a--helpflag:xunitmerge --helpIn summary, you can provide any number of paths of reports to be merged and\nan output report path:xunitmerge report1.xml report2.xml report3.xml merged.xmlYou can also use it directly in Python:from xunitmerge import merge_xunit\n\nmerge_xunit(files['report1.xml', 'report2.xml'], output='merged.xml)Running testsYou can run tests for this package by using nose:$ nosetests --with-doctestCreditsMiroslav Shubernetskiy -GitHubLicenseThis package is licensed underMIT.The MIT License (MIT)\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in\nall copies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\nTHE SOFTWARE."} +{"package": "xunitparser", "pacakge-description": "Descriptionxunitparser reads a JUnit/XUnit XML file and maps it to Python objects.\nIt tries to use the objects available in the standardunittestmodule.Usageimport xunitparser\nts, tr = xunitparser.parse(open('/path/to/unit.xml'))tsis aTestSuiteclass, containingTestCaseclasses.tris aTestResultclass.You can change the classes used (though they probably would not work unless\nthey inherit from thexunitparserones) by using your ownxunitparser.Parserclass and changing the*_CLASSvariables.Some helpful properties are added to theTestCaseclass:for tc in ts:\n print('Class %s, method %s' % (tc.classname, tc.methodname))\n if tc.good:\n print('went well...', 'but did not run.' if tc.skip else '')\n else:\n print('went wrong.')For more, please read the source code - it is very minimal.\nThe classes also inherit from theunittestmodule so it is actually\na good reference of what you can do withxunitparser.Changes1.3.4fix python 3 compatibilitymain project URL change as maintainer changes1.3.0Multiple results in a single TestCase are seen as one.\nThe previous way was never validated by real-life examples.Handle system-out / system-err at the testsuite levelDevelopmentContributions can be sent tohttps://gitlab.com/woob/xunitparser/"} +{"package": "xunitparserx", "pacakge-description": "Descriptionxunitparserx reads a JUnit/XUnit/MSTest XML file and maps it to Python objects.\nIt tries to use the objects available in the standardunittestmodule.xunitparserx work both for python2 and python3, with addition MSTest trx supportUsageimport xunitparserx\nts, tr = xunitparserx.parse(open('/path/to/unit.xml'))tsis aTestSuiteclass, containingTestCaseclasses.tris aTestResultclass.You can change the classes used (though they probably would not work unless\nthey inherit from thexunitparserxones) by using your ownxunitparserx.Parserclass and changing the*_CLASSvariables.Some helpful properties are added to theTestCaseclass:for tc in ts:\n print('Class %s, method %s' % (tc.classname, tc.methodname))\n if tc.good:\n print('went well...', 'but did not run.' if tc.skip else '')\n else:\n print('went wrong.')For more, please read the source code - it is very minimal.\nThe classes also inherit from theunittestmodule so it is actually\na good reference of what you can do withxunitparserx.Changes1.9.10+use github action to auto publish to pypi1.9.9add fromstring support, ref:https://docs.python.org/3/library/xml.etree.elementtree.html#parsing-xmladd MSTest trx support(parse_trx, fromstring_trx), ref:https://gist.github.com/congzhangzh/92ca9692430a95e3dce98f4ae2c0004e,https://gist.github.com/congzhangzh/30ecfd89fa9f0d4139c585869d2df81f,https://github.com/x97mdr/pickles/blob/master/src/Pickles/Pickles.Test/results-example-mstest.trxadd pytest record_xml_property support, ref:https://github.com/pytest-dev/pytest/issues/31301.3.3add python 3 support1.3.0Multiple results in a single TestCase are seen as one.\nThe previous way was never validated by real-life examples.Handle system-out / system-err at the testsuite levelDevelopment & ContributionPull request is welcome.dev branch is used to accept pull request and do integrationmain branch is used to do release, once push, a release process will happen automateLove My Software:https://www.paypal.me/medlab:)Release Workflowpython setup.py sdistpython -m twine upload dist/*Auto release statusRefs:https://blog.jetbrains.com/pycharm/2017/05/how-to-publish-your-package-on-pypi/https://packaging.python.org/guides/migrating-to-pypi-org/https://packaging.python.org/guides/publishing-package-distribution-releases-using-github-actions-ci-cd-workflows/https://docs.github.com/en/free-pro-team@latest/actions/reference/workflow-syntax-for-github-actions"} +{"package": "xunit-tools", "pacakge-description": "Copyright (c) 2016 Charles ThomasPermission is hereby granted, free of charge, to any person obtaining a copyof this software and associated documentation files (the \"Software\"), to dealin the Software without restriction, including without limitation the rightsto use, copy, modify, merge, publish, distribute, sublicense, and/or sellcopies of the Software, and to permit persons to whom the Software isfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THEAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHERLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THESOFTWARE.Description: ===========xunit_tools===========Turn XUnit XML into HTML, diff two XUnit XMLs & generate HTMLPlatform: UNKNOWNClassifier: Development Status :: 4 - BetaClassifier: License :: OSI Approved :: MIT LicenseClassifier: Operating System :: MacOS :: MacOS XClassifier: Operating System :: POSIXClassifier: Programming Language :: Python :: 2.7"} +{"package": "xunit-wrapper", "pacakge-description": "No description available on PyPI."} +{"package": "xunlei", "pacakge-description": "API UsageCreate a Xunlei object:import xunlei\nxunlei_obj = xunlei.Xunlei(USERNAME, PASSWORD, COOKIE_FILE_PATH)List Xunlei lixian tasks:items = xunlei_obj.dashboard()List a bittorrent task:items = xunlei_obj.list_bt(url, task_id) # url and task_id are from dashboard() functionDownload a task:xunlei_obj.dowload(url, filename)Download a task with file size checking and resume:xunlei_obj.smart_download(url, filename, size)CLI UsageEdit config file at~/xunleirc, add settings forusernameandpasswordList xunlei tasks:xunlei_cli dashboardDownload a task:xunlei_cli download TASK_ID"} +{"package": "xunleipy", "pacakge-description": "xunleipy========[![Build Status](https://travis-ci.org/lazygunner/xunleipy.svg?branch=master)](https://travis-ci.org/lazygunner/xunleipy)### XunLei SDK1. \u6a21\u62df\u767b\u5f55\u8fc5\u96f72. \u67e5\u770b\u8fdc\u7a0b\u4e0b\u8f7d\u9879\u76ee3. \u6dfb\u52a0\u8fdc\u7a0b\u4e0b\u8f7d\u9879\u76ee### \u8fdc\u7a0b\u4e0b\u8f7d\u4f7f\u7528\u65b9\u6cd50. \u5b89\u88c5&\u5f15\u7528 xunleipy```pip install xunleipy``````from xunleipy.remote import XunLeiRemote```1. \u521d\u59cb\u5316\u8fc5\u96f7\u8fdc\u7a0b\u5bf9\u8c61```remote_client = XunLeiRemote(username, password, rk_username, rk_password, proxy=proxy)```* username - \u8fc5\u96f7\u8d26\u53f7* password - \u8fc5\u96f7\u5bc6\u7801* rk_username - \u82e5\u5feb\u8d26\u53f7(\u7528\u6765\u81ea\u52a8\u8bc6\u522b\u9a8c\u8bc1\u7801)* rk_password - \u82e5\u5feb\u5bc6\u7801(\u7528\u6765\u81ea\u52a8\u8bc6\u522b\u9a8c\u8bc1\u7801)* proxy - \u4ee3\u7406\u5730\u5740,\u5982\u679c\u5f02\u5730\u767b\u5f55\u6700\u597d\u4f7f\u7528\u5e38\u7528\u5730\u533aIP\u505a\u4ee3\u7406(eg. http://192.168.1.1:8888)2. \u8fc5\u96f7\u767b\u5f55```remote_client.login() // \u767b\u5f55\u6210\u529f\u8fd4\u56de True```3. \u83b7\u53d6\u8fdc\u7a0b\u7ec8\u7aef\u5217\u8868```peer_list = remote_client.get_remote_peer_list()``````\u8fd4\u56de\u6570\u636e{\"rtn\": 0,\"peerList\": [{\"category\": \"\",\"status\": 0,\"name\": \"GUNNER_NAS\",\"vodPort\": 8002,\"company\": \"XUNLEI_ARM_LE_ARMV5TE\",\"pid\": \"F322***************\",\"lastLoginTime\": 1491282477,\"accesscode\": \"\",\"localIP\": \"192.168.2.153\",\"location\": \"\",\"online\": 1,\"path_list\": \"C:/\",\"type\": 30,\"deviceVersion\": 22153310},{\"category\": \"\",\"status\": 0,\"name\": \"gunner-pc\",\"vodPort\": 0,\"company\": \"\",\"pid\": \"0026***************\",\"lastLoginTime\": 1491121317,\"accesscode\": \"\",\"localIP\": \"192.168.2.42\",\"location\": \"\",\"online\": 0,\"path_list\": \"C:/\u8fc5\u96f7\u4e0b\u8f7d/\",\"type\": 2,\"deviceVersion\": 0}]}```4. \u6dfb\u52a0\u4e0b\u8f7d\u94fe\u63a5```remote_data = {'url': 'ed2k://|file|%E4%BA%BF%E4%B8%87.Billions.S02E01.%E4%B8%AD%E8%8B%B1%E5%AD%97%E5%B9%95.HDTVrip.720p.x264.mp4|633029318|3c85f90ef272d6581475c5c53c0be6f8|h=rilqokejso4mxrz3l2njyu6ee6u76bl3|/','name': \u4ebf\u4e07.Billions.S02E01.\u4e2d\u82f1\u5b57\u5e55.HDTVrip.720p.x264.mp4,'gcid': '','cid': '','file_size': 633029318}rtn = remote_client.add_tasks_to_remote(peer_list[0]['pid'], \u00a0 //\u8981\u4fdd\u8bc1peer\u5728\u7ebf, \u5373peer['online'] == 1'C:/TV/\u4ebf\u4e07 Billions/2/\u4ebf\u4e07.Billions.S02E01.\u4e2d\u82f1\u5b57\u5e55.HDTVrip.720p.x264.mp4', //\u8def\u5f84\u53ef\u4ee5\u81ea\u5b9a\u4e49,\u4f46\u8981\u786e\u4fdd\u5b58\u5728[remote_data])if rtn['rtn'] != 0:print '\u6dfb\u52a0\u4e0b\u8f7d\u6210\u529f'```### \u5199\u5728\u540e\u9762\u8fd9\u4e2a\u9879\u76ee\u65ad\u65ad\u7eed\u7eed\u5199\u4e86\u6709\u51e0\u5e74\u4e86\uff0c\u6700\u4e3b\u8981\u7684\u8fd8\u662f\u4f9b\u81ea\u5df1\u7684NAS\u81ea\u52a8\u4e0b\u8f7d\u66f4\u65b0\u7684\u7f8e\u5267\uff0c\u4ee3\u7801\u5f88\u591a\u5730\u65b9\u5199\u7684\u5f88\u4e11\uff0c\u540e\u7eed\u4f1a\u9010\u6e10\u4f18\u5316"} +{"package": "xunleishare", "pacakge-description": "UNKNOWN"} +{"package": "xunpdf", "pacakge-description": "This is the main page"} +{"package": "xunsearch", "pacakge-description": "xunsearch-sdk-python\u8fc5\u641c( xunsearch ) Python SDK\u5c01\u88c5\u4f7f\u7528\u793a\u4f8b\uff0cPython SDK \u5bf9\u5b98\u65b9 PHP SDK \u5b9e\u73b0\u4e86\u6240\u6709\u63a5\u53e3\u7684\u5c01\u88c5\u7ffb\u8bd1\uff0c\u6240\u4ee5\u4f7f\u7528\u53ef\u4ee5\u53c2\u8003\u5b98\u65b9PHP SDK\u4f7f\u7528\u8bf4\u660e\u4ee5\u4e0b\u4e3a Python \u5f15\u7528\u7684\u7b80\u5355\u793a\u4f8bimport xunsearch\n\nxs = xunsearch.XS('/path/to/demo.ini')"} +{"package": "xuouSubmarine", "pacakge-description": "No description available on PyPI."} +{"package": "xupdate-processor", "pacakge-description": "IntroductionApply xupdate diff on XML documents.TestingTo run tests:python -m unittest discover srcor, usingzc.buildoutandzope.testrunner:buildout\n./bin/testUsagejust like this:>>> from xupdate_processor import applyXUpdate\n>>> from lxml import etree\n>>> xml_doc_string = \"\"\"<?xml version=\"1.0\"?>\n<erp5>\n <object portal_type=\"Test\">\n <title>A\n \n \n A\n \n \n A\n \n\n\"\"\"\n>>> xml_xu_string = \"\"\"\n\n B\n C\n\n\"\"\"\n>>> result_tree = applyXUpdate(xml_xu_string=xml_xu_string, xml_doc_string=xml_doc_string)\n>>> print etree.tostring(result_tree, pretty_print=True)\n\n \n A\n \n \n B\n \n \n C\n \nHistory0.5 (2022-09-14)Support python3 and python2.7 by dropping dependency on PyXML0.4 (2010-01-21)[Fix] sub element might have been append in wrong order[nicolas Delaby]0.3 2010-01-19Update setup.py0.2 (2010-01-19)refactor egg structure directory[nicolas Delaby]Use unittest module instead of DOCTEST[nicolas Delaby]add PyXML dependency to support sax parser with xml.sax.handler.feature_namespace_prefixes feature.[nicolas Delaby]remove zope.interface dependency[Fix] sub element might have been append in wrong order0.1 (2009-12-12)Initial implementation[nicolas Delaby]"} +{"package": "xuper", "pacakge-description": "A pure python sdk for XuperChain"} +{"package": "xuran", "pacakge-description": "UNKNOWN"} +{"package": "xurdfpy", "pacakge-description": "No description available on PyPI."} +{"package": "xurl", "pacakge-description": "xurlextract links (href data) from html files/web pages.Installationpip install xurlOptionsrun thexurl -horxurl --helpfor options-a = append an URL to start of the links\n-c = contain text (REGEX)\n-C = not contain text (REGEX)\n-q = quiet mode (do not print Errors/Warnings/Infos)\n-v = versionUsagesxurl https://example.comand same for the filesxurl path/to/filesearch using regexxurl https://example.com -c \"section\\-[1-10].*.[pdf|xlsx]\""} +{"package": "xurls", "pacakge-description": "DocumentationA high-levelUrlclass to make parsing, looking at and manipulating\nurls much easier.Also allows for easily composable urls.Everything is subject to change!\ud83d\udcc4 Detailed Documentation|\ud83d\udc0d PyPiGetting StartedpoetryinstallxurlsorpipinstallxurlsVery basic example:fromxurlsimportUrlurl=Url(\"http://www.google.com/some/path\")asserturl.host==\"www.google.com\"url.host=\"apple.com\"assertstr(url)==\"http://apple.com/some/path\""} +{"package": "xuru.recipe.android", "pacakge-description": "ContentsIntroductionChangelogIntroductionxuru.recipe.androidallows you to install the android sdk as part of your parts list.\nFor example:[my_android_sdk]\nrecipe = xuru.recipe.android\napis = 16 17\nsystem_images = intel mips\nsdk = http://dl.google.com/android/android-sdk_r22.0.4-macosx.zip\nother_packages =\n Google Play APK Expansion Library\n Google Web DriverThis will install the android sdk into the parts directory, along with\nplatform-tools, build-tools, and tools. It will then install version\n16 and 17 apis. In addition, it will install the intel and mips system images\nfor each of those apis.The format of entries in the buidout section (my_android_sdk in this example)\nis:[section_name]\nrecipe = xuru.recipe.androidWhere options are:apisThe list of api versions on one line seperated by spaces.system_imagesThe list of system images types for each of the apis specified above. Valid\nvalues are intel, mips or arm.sdkThe full url to the downloadable zip file for the android sdk.install_dirOptional absolute directory to install the sdk instead of the default /androidother_packagesOptional list (on seperate lines) of extra packages to install. To see what\npackages there are to install typeandroid list sdk-aon the command\nline after the sdk has been installed. The name must be a unique sub-string\nof the names listed.dryrunSet this to any of True, False, true, false, 1, 0 to set the boolean value.\nThis determines whether or not to include the command line switch\n\u2013dry-mode.forceSet this to any of True, False, true, false, 1, 0 to set the boolean value.\nForces replacement of a package or its parts, even if something has been modified.Binaries InstalledA script will be generated in the bin directory for each of the following binaries:\n- adb\n- android\n- emulator\n- uiautomationviewer\n- lintWhat This Does Not InstallIf you installed theIntel x86 Emulator Accelerator (HAXM)package, you will\nfind the installer in:parts/android/android-sdk-macosx/extras/intel/Hardware_Accelerated_Execution_Manager/IntelHAXM.dmgThis recipe will not run any installers at this time.Changelog0.10.0 - 2013-08-02Rewrote everything to inspect the file system instead of relying on the android app to tell use what needs installing and what doesn\u2019t.Fixed verbose settings: -vv for verbose -vvvv to see the license agreementsAdded two settings: \u201cdryrun\u201d and \u201cforce\u201dCorrected script generation (and now correctly detects if something isn\u2019t\ninstalled based on those).Fixed install order for dependencies.Now much more consistant.0.9.1 - UnreleasedNothing yet\u20260.9.0 - 2013-06-12Cleaned up the source code.Now sets the buildout variable for the sdk_dir that other parts can access\nlike ${android:sdk_dir}Added support for verboseness0.8.9 - 2013-06-11Fixed an error that caused it to never exit the install loop if the api 17\nimage was being installed, and other packages after that one.Terminates the child when it times out after 30 seconds.0.8.8 - 2013-06-10Added new optioninstall_dirto install it in a seperate directory other\nthen the parts directory.0.8.7 - 2013-06-05Rewrote how it finds packages and installs them.0.8.6 - 2013-06-05Initial push to pypi"} +{"package": "xusbboot", "pacakge-description": "No description available on PyPI."} +{"package": "xust1119", "pacakge-description": "UNKNOWN"} +{"package": "xu-test-distributions", "pacakge-description": "No description available on PyPI."} +{"package": "xutil", "pacakge-description": "xutilThis is a Python package containing all the utility functions and libraries that are commonly used.Installpip install xutil\npip install xutil[jdbc] # for JDBC connectivity. Requires JPype1.\npip install xutil[web] # for web scraping. Requires Twisted.\npip install xutil[hive] # for Hive connectivity. Requires SASL libraries.WindowsIf you face the message \u2018error: Microsoft Visual C++ 14.0 is required. Get it with \u201cMicrosoft Visual C++ Build Tools\u201d\u2019, you can quickly install the build tools with chocolatey (https://chocolatey.org/)choco install -y VisualCppBuildToolsCLIAvailable commands:xutil-alias# add useful alias commands, see xutil/alias.shxutil-create-profile# creates ~/profile.yaml from template.exec-etl--help# Execute various ETL operations.exec-sql--help# Execute SQL from command lineipy# launch ipython with pre-defined modules/functions importedipy-spark--help# launch ipython Spark with pre-defined modules/functions importedpykillpattern# will swiftly kill any process with the command string mathing patternDatabasesWhy not use SQLAlchemy (SA)?http://docs.sqlalchemy.org/en/latest/faq/performance.html#i-m-inserting-400-000-rows-with-the-orm-and-it-s-really-slowIt has been demontrated the SA is not performant when it comes to speedy ETL.SQL ServerInstallationMake sure ODBC is installed.brew install unixodbc\napt-get install unixodbcThen, install the drivershttps://docs.microsoft.com/en-us/sql/connect/odbc/linux-mac/installing-the-microsoft-odbc-driver-for-sql-server?view=sql-server-2017odbcinst -jOracleInstall Oracle Client:brew tap InstantClientTap/instantclient\nbrew install instantclient-basicInstalling with conda:condainstalloracle-instantclient-ySpark SQLIt is the user\u2019s responsibility to properly set up the SPARK_HOME environment and configurations.\nThis library uses pyspark and will default to the SPARK_HOME settings.Useful config.pyhttps://github.com/apache/incubator-airflow/blob/master/setup.pyhttps://github.com/dask/dask/blob/master/setup.pyhttps://github.com/tartley/colorama/blob/master/setup.pyDevpip install -e /path/to/xutilTestingpython setup.py testReleaseUpdate version insetup.py.Draft new release on Github:https://github.com/flarco/xutil/releases/newgit clone https://github.com/flarco/xutil.git\ncd xutil\nm2r --overwrite README.md\npython setup.py sdist && twine upload --skip-existing dist/*TODORevampdatabase.basemethods:get_conn\nDBConn\n __init__\n _set_variables\n _do_execute\n _split_schema_table\n _concat_fields\n _template\n\n connect\n check_pk\n execute -- straight SA.connection.execute, return \"fields, rows\"\n query -- use the SQLAlachy and replaces self.select, fields = conn._fields\"\n stream\n insert\n drop_table\n create_table\n get_cursor_fields -> _get_cursor_fields\n get_schemas\n get_objects\n get_tables\n get_views\n get_columns\n get_primary_keys\n get_indexes\n get_ddl\n get_all_columns\n get_all_tables\n analyze_fields\n analyze_tables\n analyze_join_match\n\n remove:\n get_cursor: no need for get_cursor with SA\n execute_multi\n select: use `query` instead, which uses `execute`"} +{"package": "xutilities", "pacakge-description": "xutilitiesSystem utilities.Free software: MIT licenseDocumentation:https://system-utils.readthedocs.io.Featuresnumeric - simple helpers for numbers.sysutils - miscellaneous sstem related helpers.CreditsThis package was created withCookiecutterand thestbraun/cookiecutter-pypackageproject template based onaudreyr/cookiecutter-pypackage.History0.1.2 (2020-11-05)First release on PyPI."} +{"package": "xutils", "pacakge-description": "xutilsA fragmentary Python library, no any third-part dependencies butgunicorn_workers,sqlalchemyandwsgi. If you does\u2019t use them, it\u2019s no need to install them.atexita simple argument parser based on CLI and file.a simple logging configurationcircuit breakerconstgunicorn workers (gunicorn&eventlet)life managermessagernetworkprocess managerresource lockresource poolrate limit based on token.retry callsending emailsqlalchemy (sqlalchemy)utilversionwsgi (falcon)xml2jsonInstall$ pip install xutilsor$ easy_install xutilsor$ python setup.py install"} +{"package": "x-utils", "pacakge-description": "No description available on PyPI."} +{"package": "xutilsV2", "pacakge-description": "Simple little module that allows you to store practical utilities in python"} +{"package": "xuwenjie", "pacakge-description": "UNKNOWN"} +{"package": "xuyangcao", "pacakge-description": "No description available on PyPI."} +{"package": "xuyingying", "pacakge-description": "No description available on PyPI."} +{"package": "xuzhaolin-nester", "pacakge-description": "UNKNOWN"} +{"package": "xuzhao-markdown-editor", "pacakge-description": "xuzhao-markdown-editorInstallationExampleIntroducexuzhao-markdown-editor is a django markdown editor, which is the django implement ofeditormd."} +{"package": "xv", "pacakge-description": "xvAccess to arxiv dataTo install:pip install xvExamplesfromxvimport*Raw storeAt the point of writing this, my attempts enablegrazeto automatically confirm download in the googledrive downloads (which, when downloading too-big files, will tell the user it can't scan the file and ask the user to confirm the download).Therefore, the following files need to be downloaded manually:titles:https://drive.google.com/file/d/1Ul5mPePtoPKHZkH5Rm6dWKAO11dG98GN/view?usp=share_linkabstracts:https://drive.google.com/file/d/1g3K-wlixFxklTSUQNZKpEgN4WNTFTPIZ/view?usp=share_link(If those urls don't work, perhaps they were updated: See here:https://alex.macrocosm.so/download.)You can then copy them over to the place graze will look for by doing:frompathlibimportPathfromxv.utilimportGrazefromxv.data_accessimporturlsg[urls['titles']]=Path('TITLES_DATA_LOCAL_FILEPATH').read_bytes()g[urls['abstracts']]=Path('ABSTRACTS_DATA_LOCAL_FILEPATH').read_bytes()# from imbed.mdat.arxiv import urls# from pathlib import Path# g[urls['titles']] = Path('FILE_WHERE_YOU_DOWNLOADED_TITLES_DATA').read_bytes()# g[urls['abstracts']] = Path('FILE_WHERE_YOU_DOWNLOADED_TITLES_DATA').read_bytes()fromxv.utilimportGrazeg=Graze()list(g)['https://drive.google.com/file/d/1Ul5mPePtoPKHZkH5Rm6dWKAO11dG98GN/view?usp=share_link',\n 'https://drive.google.com/file/d/1g3K-wlixFxklTSUQNZKpEgN4WNTFTPIZ/view?usp=share_link',\n 'https://arxiv.org/pdf/0704.0001']fromxvimportraw_sourceslist(raw_sources)['titles', 'abstracts']raw=raw_sources['titles']list(raw)['titles_7.parquet',\n 'titles_23.parquet',\n 'titles_15.parquet',\n 'verifyResults.py',\n 'titles_14.parquet',\n 'titles_22.parquet',\n 'titles_6.parquet',\n 'titles_16.parquet',\n 'titles_20.parquet',\n 'titles_4.parquet',\n 'titles_5.parquet',\n 'titles_21.parquet',\n 'params.txt',\n 'titles_17.parquet',\n 'exampleEmbed.py',\n 'titles_12.parquet',\n 'README.md',\n 'titles_9.parquet',\n 'titles_1.parquet',\n 'titles_13.parquet',\n 'titles_8.parquet',\n 'titles_18.parquet',\n 'titles_3.parquet',\n 'titles_11.parquet',\n 'titles_10.parquet',\n 'titles_19.parquet',\n 'titles_2.parquet']print(raw['exampleEmbed.py'].decode())from InstructorEmbedding import INSTRUCTOR\n\nmodel = INSTRUCTOR('hkunlp/instructor-xl')\nsentence = \"3D ActionSLAM: wearable person tracking in multi-floor environments\"\ninstruction = \"Represent the Research Paper title for retrieval; Input:\"\nembeddings = model.encode([[instruction,sentence]])\nprint(embeddings)fromInstructorEmbeddingimportINSTRUCTORmodel=INSTRUCTOR('hkunlp/instructor-xl')/Users/thorwhalen/.pyenv/versions/3.10.13/envs/p10/lib/python3.10/site-packages/InstructorEmbedding/instructor.py:7: TqdmExperimentalWarning: Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n from tqdm.autonotebook import trange\n\n\nload INSTRUCTOR_Transformer\nmax_seq_length 512sentence=\"3D ActionSLAM: wearable person tracking in multi-floor environments\"instruction=\"Represent the Research Paper title for retrieval; Input:\"embeddings=model.encode([[instruction,sentence]])print(raw['params.txt'].decode())prompt: Represent the Research Paper title for retrieval; Input:\ntype: title\ntime string: 20230518-185428\nmodel: InstructorXL\nversion: 2.0print(raw['exampleEmbed.py'].decode())from InstructorEmbedding import INSTRUCTOR\n\nmodel = INSTRUCTOR('hkunlp/instructor-xl')\nsentence = \"3D ActionSLAM: wearable person tracking in multi-floor environments\"\ninstruction = \"Represent the Research Paper title for retrieval; Input:\"\nembeddings = model.encode([[instruction,sentence]])\nprint(embeddings)The imbedding data storeAnd now, we'll transform the raw store to get a convenient interface to the actual data of interest.b=raw['titles_1.parquet']len(b)313383694fromxvimportsources# raw store + wrapper. See parquet_codec code.titles_tables=sources['titles']abstract_tables=sources['abstracts']print(list(titles_tables))[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]titles_df=titles_tables[1]titles_dftitleembeddingsdoi0Calculation of prompt diphoton production cros...[-0.050620172, 0.041436385, 0.05363288, -0.029...0704.00011Sparsity-certifying Graph Decompositions[0.014515653, 0.023809524, -0.028145121, -0.04...0704.00022The evolution of the Earth-Moon system based o...[-4.766115e-05, 0.017415706, 0.04146007, -0.03...0704.00033A determinant of Stirling cycle numbers counts...[0.027208889, 0.046175897, 0.0010913888, -0.01...0704.00044From dyadic $\\Lambda_{\\alpha}$ to $\\Lambda_{\\a...[0.0113909235, 0.0042667952, -0.0008565594, -0...0704.0005............99995Multiple Time Dimensions[0.02682626, -0.0015173098, -0.0019915192, -0....0812.386999996Depth Zero Representations of Nonlinear Covers...[-0.02740943, 0.011689809, -0.0105154915, -0.0...0812.387099997Decting Errors in Reversible Circuits With Inv...[0.0072460608, 0.0028085636, -0.015064359, -0....0812.387199998Unveiling the birth and evolution of the HII r...[0.009408689, -0.0047120117, 0.0021392817, -0....0812.387299999The K-Receiver Broadcast Channel with Confiden...[-0.0026305509, -0.006502139, 0.013400236, -0....0812.3873100000 rows \u00d7 3 columnsabstract_df=abstract_tables[1]abstract_dfabstractembeddingsdoi0A fully differential calculation in perturba...[-0.035151865, 0.022851437, 0.025942933, -0.02...0704.00011We describe a new algorithm, the $(k,\\ell)$-...[0.035485767, -0.0015772493, -0.0016615744, -0...0704.00022The evolution of Earth-Moon system is descri...[-0.014510429, 0.010210799, 0.049661566, -0.01...0704.00033We show that a determinant of Stirling cycle...[0.029191103, 0.047992915, -0.0061754594, -0.0...0704.00044In this paper we show how to compute the $\\L...[-0.015174898, 0.01603887, 0.04062805, -0.0246...0704.0005............99995The possibility of physics in multiple time ...[0.016121766, 0.011126887, 0.018650021, -0.044...0812.386999996We generalize the methods of Moy-Prasad, in ...[-7.164341e-05, -0.007114291, -0.008979887, -0...0812.387099997Reversible logic is experience renewed inter...[0.03194286, -0.00771745, 0.015977046, -0.0474...0812.387199998Based on a multiwavelength study, the ISM ar...[-0.012340169, -0.021712925, 0.00806009, -0.00...0812.387299999The secrecy capacity region for the K-receiv...[0.0012416588, 0.0006933478, -0.0057888636, -0...0812.3873100000 rows \u00d7 3 columnsabstract_df['doi'].valuesarray(['0704.0001', '0704.0002', '0704.0003', ..., '0812.3871',\n '0812.3872', '0812.3873'], dtype=object)fromxvimportarxiv_urldoi=abstract_df['doi'].values[0]arxiv_url(doi)'https://arxiv.org/abs/0704.0001'fromxv.data_accessimportresource_descriptionsresource_descriptions{'abs': 'Main page of article. Contains links to all other relevant information.',\n 'pdf': 'Direct link to article pdf',\n 'format': 'Page giving access to other formats',\n 'src': 'Access to the original source files submitted by the authors.',\n 'cits': 'Tracks citations of the article across various platforms and databases.',\n 'html': 'Link to the ar5iv html page for the article.'}doi='0704.0001'forresource,descriptioninresource_descriptions.items():print(f\"{resource}:{description}\")print(f\"Example:{arxiv_url(doi,resource)}\")print(\"\")abs: Main page of article. Contains links to all other relevant information.\nExample: https://arxiv.org/abs/0704.0001\n\npdf: Direct link to article pdf\nExample: https://arxiv.org/pdf/0704.0001\n\nformat: Page giving access to other formats\nExample: https://arxiv.org/format/0704.0001\n\nsrc: Access to the original source files submitted by the authors.\nExample: https://arxiv.org/src/0704.0001\n\ncits: Tracks citations of the article across various platforms and databases.\nExample: https://arxiv.org/cits/0704.0001\n\nhtml: Link to the ar5iv html page for the article.\nExample: https://ar5iv.labs.arxiv.org/html/0704.0001arxiv_url(doi,'pdf')'https://arxiv.org/pdf/0704.0001'pdf_bytes=g[arxiv_url(doi,'pdf')]The contents (~1.647MB) of https://arxiv.org/pdf/0704.0001 are being downloaded...abstract_df.embeddings.values[0].shape(768,)"} +{"package": "xvalidator", "pacakge-description": "XValidatorxvalidatoris a simple Python package for validation. It includes a module for validating Iran National Codes.InstallationYou can installxvalidatorusing pip:pipinstallxvalidatorIran National Code ValidationThe package provides a function is_nationalcode for validating Iran National Codes. The function takes a string representing the National Code and returns True if the code is valid and False otherwise.fromxvalidatorimportis_nationalcode# Validate Iran National Coderesult=is_nationalcode('1234567890')ifresult:print(\"Valid National Code\")else:print(\"Invalid National Code\")ContributingContributions are welcome! If you find issues or have improvements, feel free to open an issue or submit a pull request.LicenseThis project is licensed under the MIT License - see the LICENSE file for details."} +{"package": "xvarnish-python", "pacakge-description": "UNKNOWN"} +{"package": "xvc", "pacakge-description": "xvc.pyPython bindings for XvcInstallation and Usage$ pip install xvc"} +{"package": "xvdl", "pacakge-description": "xvdlExperiment CLI python for collect infomation video."} +{"package": "xvebaoku", "pacakge-description": "UNKNOWN"} +{"package": "xvec", "pacakge-description": "Vector data cubes for XarrayWhere raster data cubes refer to data cubes with raster (x- and y-, or lon- and lat-) dimensions, vector data cubes are n-D arrays that have (at least) a single spatial dimension that maps to a set of (2-D) vector geometries. (Edzer Pebesma)Xvec combinesXarrayn-D arrays andshapely 2planar vector geometries to create a support for vector data cubes in Python. Seethis postby Edzer Pebesma on an introduction of the concept or the introduction of their implementation in Xvec in ourdocumentation.Project statusThe project is in the early stage of development and its API may still change.InstallingYou can install Xvec from PyPI usingpipor from conda-forge usingmambaorconda:pipinstallxvecOr (recommended):mambainstallxvec-cconda-forgeDevelopment versionThe development version can be installed from GitHub.pipinstallgit+https://github.com/xarray-contrib/xvec.gitWe recommend installing its dependencies usingmambaorcondabefore.mambainstallxarrayshapelypyproj-cconda-forge"} +{"package": "xvector-jtubespeech", "pacakge-description": "x-vector extractor for Japanese speechThis repository provides a pre-trained model for extracting thex-vector(speaker representation vector). The model is trained usingJTubeSpeech corpus, a Japanese speech corpus collected from YouTube.\u3053\u306e\u30ea\u30dd\u30b8\u30c8\u30ea\u306f\uff0cx-vector(\u8a71\u8005\u8868\u73fe\u30d9\u30af\u30c8\u30eb) \u3092\u62bd\u51fa\u3059\u308b\u305f\u3081\u306e\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\u3092\u63d0\u4f9b\u3057\u307e\u3059\uff0e\u3053\u306e\u30e2\u30c7\u30eb\u306f\uff0cJTubeSpeech\u30b3\u30fc\u30d1\u30b9\u3068\u547c\u3070\u308c\u308b\uff0cYouTube\u304b\u3089\u53ce\u96c6\u3057\u305f\u65e5\u672c\u8a9e\u97f3\u58f0\u304b\u3089\u5b66\u7fd2\u3055\u308c\u3066\u3044\u307e\u3059\uff0eTraining configures / \u5b66\u7fd2\u6642\u306e\u8a2d\u5b9aThe number of speakers: 1,233Sampling frequency: 16,000HzSpeaker recognition accuracy: 91% (test data)Feature: 24-dimensional MFCCDimensionality of x-vector: 512Other configurations: followed the ASV recipe for VoxCeleb in Kaldi.In the opensourced model, model parameters of recognition layers following to the x-vector layer were randomized to protect data privacy.Installationpipinstallxvector-jtubespeechUsage / \u4f7f\u3044\u65b9import numpy as np\nfrom scipy.io import wavfile\nimport torch\nfrom torchaudio.compliance import kaldi\n\nfrom xvector_jtubespeech import XVector\n\ndef extract_xvector(\n model, # xvector model\n wav # 16kHz mono\n):\n # extract mfcc\n wav = torch.from_numpy(wav.astype(np.float32)).unsqueeze(0)\n mfcc = kaldi.mfcc(wav, num_ceps=24, num_mel_bins=24) # [1, T, 24]\n mfcc = mfcc.unsqueeze(0)\n\n # extract xvector\n xvector = model.vectorize(mfcc) # (1, 512)\n xvector = xvector.to(\"cpu\").detach().numpy().copy()[0] \n\n return xvector\n\n_, wav = wavfile.read(\"sample.wav\") # 16kHz mono\nmodel = XVector(\"xvector.pth\")\nxvector = extract_xvector(model, wav) # (512, )Contributors / \u8ca2\u732e\u8005Takaki Hamada / \u6ff1\u7530 \u8a89\u8f1d (The University of Tokyo / \u6771\u4eac\u5927\u5b66)Shinnosuke Takamichi / \u9ad8\u9053 \u614e\u4e4b\u4ecb (The University of Tokyo / \u6771\u4eac\u5927\u5b66)License / \u30e9\u30a4\u30bb\u30f3\u30b9MITOthers / \u305d\u306e\u4ed6The audio samplesample.wavwas copied fromPJS corpus."} +{"package": "xvenv", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xverif", "pacakge-description": "xverif - A package to perform forecast verification builds upon xarray.The code in this repository provides a scalable and flexible framework to perform forecast verification.\nIt principally builds upon xarray, dask and flox libraries.ATTENTION: The code is subject to changes in the coming months.The foldertutorials(will) provide jupyter notebooks describing various features of xverif.The folderdocs(will) contains slides and notebooks explaining the x-forecasting framework.InstallationFor a local installation, follow the below instructions.Clone this repository.gitclonehttps://github.com/ghiggi/xverif.gitcdxverifInstall manually the following dependencies:condacreate--namexverif-devpython=3.8\ncondainstallxarraydaskcdoh5pyh5netcdfnetcdf4zarrnumcodecsrechunker\ncondainstallnotebookjupyterlab\ncondainstallnumpypandasnumbascipybottleneckAlternatively install the dependencies using one of the appropriate below\nenvironment.yml files:condaenvcreate-fTODO.ymlTutorialsReproducing our resultsContributorsGionata GhiggiYann Yasser HaddadLicenseThe content of this repository is released under the terms of theMIT license."} +{"package": "xverse", "pacakge-description": "xversexverseshort forXuniVerseis a Python module for machine learning in the space of feature engineering, feature transformation and feature selection.Currently, xverse package handles only binary target.InstallationThe package requiresnumpy, pandas, scikit-learn, scipyandstatsmodels. In addition, the package is tested on Python version 3.5 and above.To install the package, download this folder and execute:pythonsetup.pyinstallorpipinstallxverseTo install the development version. you can usepipinstall--upgradegit+https://github.com/Sundar0989/XuniVerseUsageXVerse module is fully compatible with sklearn transformers, so they can be used in pipelines or in your existing scripts. Currently, it supports only Pandas dataframes.ExampleMonotonic Binning (Feature transformation)fromxverse.transformerimportMonotonicBinningclf=MonotonicBinning()clf.fit(X,y)print(clf.bins){'age': array([19., 35., 45., 87.]),\n 'balance': array([-3313. , 174. , 979.33333333, 71188. ]),\n 'campaign': array([ 1., 3., 50.]),\n 'day': array([ 1., 12., 20., 31.]),\n 'duration': array([ 4. , 128. , 261.33333333, 3025. ]),\n 'pdays': array([-1.00e+00, -5.00e-01, 1.00e+00, 8.71e+02]),\n 'previous': array([ 0., 1., 25.])}Weight of Evidence (WOE) and Information Value (IV) (Feature transformation and Selection)fromxverse.transformerimportWOEclf=WOE()clf.fit(X,y)print(clf.woe_df.head())#Weight of Evidence transformation dataset+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| | Variable_Name | Category | Count | Event | Non_Event | Event_Rate | Non_Event_Rate | Event_Distribution | Non_Event_Distribution | WOE | Information_Value |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| 0 | age | (18.999, 35.0] | 1652 | 197 | 1455 | 0.11924939467312348 | 0.8807506053268765 | 0.3781190019193858 | 0.36375 | 0.038742147481056366 | 0.02469286279236605 |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| 1 | age | (35.0, 45.0] | 1388 | 129 | 1259 | 0.09293948126801153 | 0.9070605187319885 | 0.2476007677543186 | 0.31475 | -0.2399610313340142 | 0.02469286279236605 |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| 2 | age | (45.0, 87.0] | 1481 | 195 | 1286 | 0.13166779203241052 | 0.8683322079675895 | 0.3742802303262956 | 0.3215 | 0.15200725211484276 | 0.02469286279236605 |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| 3 | balance | (-3313.001, 174.0] | 1512 | 133 | 1379 | 0.08796296296296297 | 0.9120370370370371 | 0.255278310940499 | 0.34475 | -0.3004651512228873 | 0.06157421302850976 |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+\n| 4 | balance | (174.0, 979.333] | 1502 | 163 | 1339 | 0.1085219707057257 | 0.8914780292942743 | 0.31285988483685223 | 0.33475 | -0.06762854653574929 | 0.06157421302850976 |\n+---+---------------+--------------------+-------+-------+-----------+---------------------+--------------------+---------------------+------------------------+----------------------+---------------------+print(clf.iv_df)#Information value dataset+----+---------------+------------------------+\n| | Variable_Name | Information_Value |\n+----+---------------+------------------------+\n| 6 | duration | 1.1606798895024775 |\n+----+---------------+------------------------+\n| 14 | poutcome | 0.4618899274360784 |\n+----+---------------+------------------------+\n| 12 | month | 0.37953277364723703 |\n+----+---------------+------------------------+\n| 3 | contact | 0.2477624664660033 |\n+----+---------------+------------------------+\n| 13 | pdays | 0.20326698063078097 |\n+----+---------------+------------------------+\n| 15 | previous | 0.1770811514357682 |\n+----+---------------+------------------------+\n| 9 | job | 0.13251854742728092 |\n+----+---------------+------------------------+\n| 8 | housing | 0.10655553101753026 |\n+----+---------------+------------------------+\n| 1 | balance | 0.06157421302850976 |\n+----+---------------+------------------------+\n| 10 | loan | 0.06079091829519839 |\n+----+---------------+------------------------+\n| 11 | marital | 0.04009032555607127 |\n+----+---------------+------------------------+\n| 7 | education | 0.03181211694236827 |\n+----+---------------+------------------------+\n| 0 | age | 0.02469286279236605 |\n+----+---------------+------------------------+\n| 2 | campaign | 0.019350877455830695 |\n+----+---------------+------------------------+\n| 4 | day | 0.0028156288525541884 |\n+----+---------------+------------------------+\n| 5 | default | 1.6450124824351054e-05 |\n+----+---------------+------------------------+Apply this handy rule to select variables based on Information value+-------------------+-----------------------------+\n| Information Value | Variable Predictiveness |\n+-------------------+-----------------------------+\n| Less than 0.02 | Not useful for prediction |\n+-------------------+-----------------------------+\n| 0.02 to 0.1 | Weak predictive Power |\n+-------------------+-----------------------------+\n| 0.1 to 0.3 | Medium predictive Power |\n+-------------------+-----------------------------+\n| 0.3 to 0.5 | Strong predictive Power |\n+-------------------+-----------------------------+\n| >0.5 | Suspicious Predictive Power |\n+-------------------+-----------------------------+clf.transform(X)#apply WOE transformation on the datasetVotingSelector (Feature selection)fromxverse.ensembleimportVotingSelectorclf=VotingSelector()clf.fit(X,y)print(clf.available_techniques)['WOE', 'RF', 'RFE', 'ETC', 'CS', 'L_ONE']clf.feature_importances_+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| | Variable_Name | Information_Value | Random_Forest | Recursive_Feature_Elimination | Extra_Trees | Chi_Square | L_One |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 0 | duration | 1.1606798895024775 | 0.29100016518065835 | 0.0 | 0.24336032789230097 | 62.53045588382914 | 0.0009834060765907017 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 1 | poutcome | 0.4618899274360784 | 0.05975563617541324 | 0.8149539108454378 | 0.07291945099022576 | 209.1788690088815 | 0.27884071686005385 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 2 | month | 0.37953277364723703 | 0.09472524644853274 | 0.6270707318033509 | 0.10303345973615481 | 54.81011477300214 | 0.18763733424335785 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 3 | contact | 0.2477624664660033 | 0.018358265986906014 | 0.45594899004325673 | 0.029325952072445132 | 25.357947712611868 | 0.04876094100065351 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 4 | pdays | 0.20326698063078097 | 0.04927368012222067 | 0.0 | 0.02738001362078519 | 13.808925800391403 | -0.00026932622581396677 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 5 | previous | 0.1770811514357682 | 0.02612886929056733 | 0.0 | 0.027197295919351088 | 13.019278420681164 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 6 | job | 0.13251854742728092 | 0.050024353325485646 | 0.5207956132479409 | 0.05775450997836301 | 13.043319831003855 | 0.11279310830899944 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 7 | housing | 0.10655553101753026 | 0.021126744587568032 | 0.28135643347861894 | 0.020830177741565564 | 28.043094016887064 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 8 | balance | 0.06157421302850976 | 0.0963543249575152 | 0.0 | 0.08429423739161768 | 0.03720300378031974 | -1.3553979494412002e-06 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 9 | loan | 0.06079091829519839 | 0.008783347837152861 | 0.6414812505459246 | 0.013652849211750306 | 3.4361027026756084 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 10 | marital | 0.04009032555607127 | 0.02648832289940045 | 0.9140684291962617 | 0.03929791951230852 | 10.889749514307464 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 11 | education | 0.03181211694236827 | 0.02757205345952717 | 0.21529148795958114 | 0.03980467391633981 | 4.70588768051867 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 12 | age | 0.02469286279236605 | 0.10164634631051869 | 0.0 | 0.08893247762137796 | 0.6818947945319156 | -0.004414426121909251 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 13 | campaign | 0.019350877455830695 | 0.04289312347011537 | 0.0 | 0.05716486374991612 | 1.8596566731099653 | -0.012650844735972498 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 14 | day | 0.0028156288525541884 | 0.083859807784465 | 0.0 | 0.09056623672332145 | 0.08687716739873641 | -0.00231307077371602 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+\n| 15 | default | 1.6450124824351054e-05 | 0.0020097121639531665 | 0.0 | 0.004485553922176626 | 0.007542737902818529 | 0.0 |\n+----+---------------+------------------------+-----------------------+-------------------------------+----------------------+----------------------+-------------------------+clf.feature_votes_+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| | Variable_Name | Information_Value | Random_Forest | Recursive_Feature_Elimination | Extra_Trees | Chi_Square | L_One | Votes |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 1 | poutcome | 1 | 1 | 1 | 1 | 1 | 1 | 6 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 2 | month | 1 | 1 | 1 | 1 | 1 | 1 | 6 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 6 | job | 1 | 1 | 1 | 1 | 1 | 1 | 6 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 0 | duration | 1 | 1 | 0 | 1 | 1 | 1 | 5 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 3 | contact | 1 | 0 | 1 | 0 | 1 | 1 | 4 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 4 | pdays | 1 | 1 | 0 | 0 | 1 | 0 | 3 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 7 | housing | 1 | 0 | 1 | 0 | 1 | 0 | 3 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 12 | age | 0 | 1 | 0 | 1 | 0 | 1 | 3 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 14 | day | 0 | 1 | 0 | 1 | 0 | 1 | 3 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 5 | previous | 1 | 0 | 0 | 0 | 1 | 0 | 2 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 8 | balance | 0 | 1 | 0 | 1 | 0 | 0 | 2 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 13 | campaign | 0 | 0 | 0 | 1 | 0 | 1 | 2 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 9 | loan | 0 | 0 | 1 | 0 | 0 | 0 | 1 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 10 | marital | 0 | 0 | 1 | 0 | 0 | 0 | 1 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 11 | education | 0 | 0 | 1 | 0 | 0 | 0 | 1 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+\n| 15 | default | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n+----+---------------+-------------------+---------------+-------------------------------+-------------+------------+-------+-------+ContributingXuniVerse is under active development, if you'd like to be involved, we'd love to have you. Check out the CONTRIBUTING.md file or open an issue on the github project to get started.Referenceshttps://www.listendata.com/2015/03/weight-of-evidence-woe-and-information.htmlhttps://medium.com/@sundarstyles89/variable-selection-using-python-vote-based-approach-faa42da960f0ContributorsAlessio Tamburro (https://github.com/alessiot)"} +{"package": "xvfbman", "pacakge-description": "A python module focusing on managing Xvfb sessions / ensuring DISPLAY through a simple interface.Why?Xvfb is the X11 Virtual Frame Buffer, and basically implements a display without a monitor, just in memory.This is useful for testing ( such as in conjunction with selenium ), profiling, or other automation task.HowThe xvfbman module provides an interface to start and manage Xvfb sessions, as well as providing a common interface your application can use to ensure a DISPLAY is set (either a real display or start a managed Xvfb which will be closed on exit).Ensuring DISPLAYA common usage would be for your application to use DISPLAY if already set or to start an Xvfb session otherwise.This can be accomplished via theensureDisplayPresentandregisterAtExitCleanup.ensureDisplayPresentwill check if DISPLAY environment variable is set, and if not it will start an Xvfb session and set DISPLAY environment variable to match.registerAtExitCleanupWill register an \u201catexit\u201d handler which will ensure that all Xvfb sessions we opened (if any) will be closed.# Returns True if we setup an Xvfb, False if DISPLAY already setif ensureDisplayPresent():# If we setup an Xvfb, register the cleanup functionregisterAtExitCleanup()Starting Xvfb SessionsYou can start Xvfb instances on-demand viastartXvfborstartXvfbRangestartXvfbtakes an argument, serverNum, which specifies the server ( e.x. serverNum=50 would be DISPLAY :50.0 ). You can also override the default value for \u201cscreenStr\u201d ( 1280x720x24 ) to specify a different resolution and depth.startXvfbRangetakes two arguments, startServerNum and lastServerNum, as well as optional screenStr, and tries to start a server on every server number / display number in that inclusive range. If the display number is already in use, it moves onto the next one.This will return the server num that ended up being used.Use this function if your app can have multiple instances running, or for any condition where there would be contention over server numbers.try:# Start an Xvfb anywhere from :50 to :99 and return the one usedserverNum = startXvfbRange(50, 99)except KeyError:# All servers 50-99 were in useraiseexcept OSError:# Other error occured preventing Xvfb from working properly# (Exception message will contain the output)Stopping Xvfb SessionYou can stop Xvfb instances viastopXvfborstopAllManagedXvfbsstopXvfbTakes a server number (integer) as an argument, and will stop the managed Xvfb running on that display.stopAllManagedXvfbsWill stop ALL the Xvfb sessions being managed by the processUtility FunctionsisUsingXvfb- Tests if we are managing Xvfb sessions. Default / None for an argument will test if we haveanysessions managed, or passing an integer will check on a specific server num.getDisplayStrForServerNum- Will convert a server number into a DISPLAY string (for use in DISPLAY env var, for example)Full PyDocCan be found athttp://htmlpreview.github.io/?https://github.com/kata198/xvfbman/blob/master/doc/xvfbman.html?vers=1.0.0 ."} +{"package": "xvfbwrapper", "pacakge-description": "Manage headless displays with Xvfb (X virtual framebuffer)Info:Dev:https://github.com/cgoldberg/xvfbwrapperReleases:https://pypi.python.org/pypi/xvfbwrapperAuthor:Corey Goldberg- 2012-2016License: MITAbout xvfbwrapper:xvfbwrapper is a python wrapper for controlling Xvfb.About Xvfb:Xvfb (X virtual framebuffer) is a display server implementing the X11 display server protocol. It runs in memory and does not require a physical display. Only a network layer is necessary.Xvfb is especially useful for running acceptance tests on headless servers.Install xvfbwrapper from PyPI:pip install xvfbwrapperSystem Requirements:Xvfb (sudoapt-getinstall xvfb, or similar)Python 2.7 or 3.3+ExamplesBasic Usage:from xvfbwrapper import Xvfb\n\nvdisplay = Xvfb()\nvdisplay.start()\n\n# launch stuff inside\n# virtual display here.\n\nvdisplay.stop()Basic Usage, specifying display geometry:from xvfbwrapper import Xvfb\n\nvdisplay = Xvfb(width=1280, height=740, colordepth=16)\nvdisplay.start()\n\n# launch stuff inside\n# virtual display here.\n\nvdisplay.stop()Usage as a Context Manager:from xvfbwrapper import Xvfb\n\nwith Xvfb() as xvfb:\n # launch stuff inside virtual display here.\n # It starts/stops around this code block.Testing Example: Headless Selenium WebDriver Tests:import unittest\n\nfrom selenium import webdriver\nfrom xvfbwrapper import Xvfb\n\n\nclass TestPages(unittest.TestCase):\n\n def setUp(self):\n self.xvfb = Xvfb(width=1280, height=720)\n self.addCleanup(self.xvfb.stop)\n self.xvfb.start()\n self.browser = webdriver.Firefox()\n self.addCleanup(self.browser.quit)\n\n def testUbuntuHomepage(self):\n self.browser.get('http://www.ubuntu.com')\n self.assertIn('Ubuntu', self.browser.title)\n\n def testGoogleHomepage(self):\n self.browser.get('http://www.google.com')\n self.assertIn('Google', self.browser.title)\n\n\nif __name__ == '__main__':\n unittest.main()The test class above usesseleniumandxvfbwrapperto run each test case with Firefox inside a headless display.virtual display is launchedFirefox launches inside virtual display (headless)browser is not shown while tests are runconditions are asserted in each test casebrowser quits during cleanupvirtual display stops during cleanupLook Ma\u2019, no browser!(You can also take screenshots inside the virtual display for diagnosing test failures)"} +{"package": "xvg", "pacakge-description": "xvgpyA scriptable vector graphics library for PythonInstallpython3 -m pip install xvg(See:PyPI package)Examplefromxvg.applicationimportEnginefromxvg.renderersimportSVGRendererEngine(SVGRenderer()).processFile('image.xvg')(See:XVGPY Index)(See:XVGPY Tests)"} +{"package": "xvideos", "pacakge-description": "Xvideos - lightweight video stream readingXvideos is a lightweight single class library for background video reading. TheVideoReaderclass works in 2 threads,\nwhich allows you to efficiently read the video with its parallel processing.InstallYou can use the Pip package manager to install the package:pip install xvideosOr you can install manually:git clone https://github.com/tam2511/xvideos.git\ncd xvideos\npython setup.py installDocumentationThis library consists of a single VideoReader class and several helper functions.\nTheir signature and description can be found in thedocumentationExamplesTheVideoReaderclass is very easy to use, just pass the source of the video stream to the class constructor\nand then use theget()method to get frames until the video stream endsfromxvideosimportVideoReaderreader=VideoReader(source='./test.mp4')whileTrue:flag,batch=reader.get()ifnotflag:break...# do something"} +{"package": "xvideos-api", "pacakge-description": "XVIDEOS APIDescriptionxvideos API is an API for xvideos.com. It allows you to fetch information from videos using regexes and requests.Disclaimer[!IMPORTANT] The xvideos API is in violation to xvideos's ToS!Copyright Information: I have no intention of stealing copyright protected content or slowing down\na website. Contact me at my E-Mail, and I'll take this Repository immediately offline.EchterAlsFake@proton.meQuickstartHave a look at theDocumentationfor more detailsInstall the library withpip install xvideos_apifromxvideos_api.xvideos_apiimportClient,Quality,threaded# Initialize a Client objectclient=Client()# Fetch a videovideo_object=client.get_video(\"\")# Information from Video objectsprint(video_object.title)print(video_object.likes)# Download the videovideo_object.download(downloader=threaded,quality=Quality.BEST,output_path=\"your_output_path + filename\")# SEE DOCUMENTATION FOR MOREChangelogSeeChangelogfor more details.ContributionDo you see any issues or having some feature requests? Simply open an Issue or talk\nin the discussions.Pull requests are also welcome.LicenseLicensed under the LGPLv3 LicenseCopyright (C) 2023\u20132024 Johannes HabelSupportLeave a star on the repository. That's enough :)"} +{"package": "xvideos-dl", "pacakge-description": "xvideos-dlCLI to download videos fromhttps://xvideos.com\u4e2d\u6587\u6587\u6863FeaturesDownload a single video (requires the URL of the video playback page)Download all videos in the favorites (requires the URL of the favorite page)Download all videos uploaded by the user (requires the URL of the user's homepage)Download all videos published by the channel (requires the URL of the channel homepage)Segmented high-speed download, breakpoint download, progress and status displayDownload high quality videos, 1080p or higherUsage\u26a0\ufe0fRequires:Python: >= 3.6.1ffmpegUbuntu/Debian:sudo apt install ffmpegMacOS:brew install ffmpegCookie: When you run it for the first time, you will be prompted to enter the cookie, log inhttps://xvideos.comwith your account, copy and paste a long string of cookie (must hassession_token=xxx), then enjoy it.Cookie is stored in~/.xvideos/cookie(orC:\\Users.xvideos\\cookie).Install xvideos-dlpipinstall-Uxvideos-dlGet CLI helpxvideos-dl--helpDownload single / favorites / uploaded / published videos in one command:xvideos-dlhttps://www.xvideos.com/video37177493/asian_webcam_2_camsex4u.lifehttps://www.xvideos.com/favorite/71879935/_https://www.xvideos.com/profiles/mypornstationhttps://www.xvideos.com/channels/av69tvRelease History1.3.0Added support for downloading higher quality videos.CLI will download the highest quality video by default, which may be 1080p or higher, depending on the videos provided by XVIDEOS.\nSo the download speed will be slower, if you want to be faster, you can use-q lowor-q middle.1.2.0Support for Python 3.6.1+1.1.2Bugfix:Fixed a bug that would not retry when the network connection failed.1.1.1New Feature:Add parameters to control the start and end of the video in the download list.Others:When running the same command repeatedly, quickly skip the downloaded video.Catch exceptions: 404 not found, forbidden downloading...1.1.0New Features:Download all videos uploaded by users.Download all videos posted by the channel.Download single, playlist, user uploaded and channel posted videos in one command.Optimize download status display.1.0.1New Features:Download videos from favorites.Show download speed.1.0.0Initial release on PyPY.For ContributorsInitialFork and clone this repo:gitclonehttps://github.com/lonsty/xvideos-dlIf you don't havePoetryinstalled run:makedownload-poetryInitialize poetry and installpre-commithooks:makeinstallMakefile usageMakefilecontains many functions for fast assembling and convenient work.1. Download Poetrymakedownload-poetry2. Install all dependencies and pre-commit hooksmakeinstallIf you do not want to install pre-commit hooks, run the command with the NO_PRE_COMMIT flag:makeinstallNO_PRE_COMMIT=13. Check the security of your codemakecheck-safetyThis command launches aPoetryandPipintegrity check as well as identifies security issues withSafetyandBandit. By default, the build will not crash if any of the items fail. But you can setSTRICT=1for the entire build, or you can configure strictness for each item separately.makecheck-safetySTRICT=1or only forsafety:makecheck-safetySAFETY_STRICT=1multiplemakecheck-safetyPIP_STRICT=1SAFETY_STRICT=1List of flags forcheck-safety(can be set to1or0):STRICT,POETRY_STRICT,PIP_STRICT,SAFETY_STRICT,BANDIT_STRICT.4. Check the codestyleThe command is similar tocheck-safetybut to check the code style, obviously. It usesBlack,Darglint,Isort, andMypyinside.makecheck-styleIt may also contain theSTRICTflag.makecheck-styleSTRICT=1List of flags forcheck-style(can be set to1or0):STRICT,BLACK_STRICT,DARGLINT_STRICT,ISORT_STRICT,MYPY_STRICT.5. Run all the codestyle formatersCodestyle usespre-commithooks, so ensure you've runmake installbefore.makecodestyle6. Run testsmaketest7. Run all the lintersmakelintthe same as:maketest&&makecheck-safety&&makecheck-styleList of flags forlint(can be set to1or0):STRICT,POETRY_STRICT,PIP_STRICT,SAFETY_STRICT,BANDIT_STRICT,BLACK_STRICT,DARGLINT_STRICT,ISORT_STRICT,MYPY_STRICT.8. Build dockermakedockerwhich is equivalent to:makedockerVERSION=latestMore informationhere.9. Cleanup dockermakeclean_dockeror to remove all buildmakecleanMore informationhere.\ud83d\udcc8 ReleasesYou can see the list of available releases on theGitHub Releasespage.We followSemantic Versionsspecification.We useRelease Drafter. As pull requests are merged, a draft release is kept up-to-date listing the changes, ready to publish when you\u2019re ready. With the categories option, you can categorize pull requests in release notes using labels.For Pull Request this labels are configured, by default:LabelTitle in Releasesenhancement,feature\ud83d\ude80 Featuresbug,refactoring,bugfix,fix\ud83d\udd27 Fixes & Refactoringbuild,ci,testing\ud83d\udce6 Build System & CI/CDbreaking\ud83d\udca5 Breaking Changesdocumentation\ud83d\udcdd Documentationdependencies\u2b06\ufe0f Dependencies updatesYou can update it inrelease-drafter.yml.GitHub creates thebug,enhancement, anddocumentationlabels for you. Dependabot creates thedependencieslabel. Create the remaining labels on the Issues tab of your GitHub repository, when you need them.\ud83d\udee1 LicenseThis project is licensed under the terms of theMITlicense. SeeLICENSEfor more details.\ud83d\udcc3 Citation@misc{xvideos-dl,\n author = {xvideos-dl},\n title = {CLI to download videos from https://xvideos.com},\n year = {2021},\n publisher = {GitHub},\n journal = {GitHub repository},\n howpublished = {\\url{https://github.com/lonsty/xvideos-dl}}\n}CreditsThis project was generated withpython-package-template."} +{"package": "xvideos-porn", "pacakge-description": "xvideos pornxvideos pornpip3xvideosporn"} +{"package": "xview", "pacakge-description": "Examine memory views/bytes pretty printing it."} +{"package": "xviewer", "pacakge-description": "XViewerpipinstall-e.[test]jupyterlabextensiondevelop.--overwrite\njupyterlabextensionlist\njupyterserverextensionlist# open http://localhost:8686/api/jupyter/lab?token=60c1661cc408f978c309d04157af55c9588ff9557c9380e4fb50785750703da6yarnjupyterlab"} +{"package": "xvision", "pacakge-description": "xvisionPython library of image super resolution algorithmsCreated byBaihan Lin, Columbia University"} +{"package": "xvistaprof", "pacakge-description": "Astropy reader for XVISTA galaxy profile tables.To use:import xvistaprof\nfrom astropy.table import Table\ntbl = Table.read(filename, format='xvistaprof')BSD Licensed. Copyright 2014 Jonathan Sick, @jonathansick"} +{"package": "xviz-avs", "pacakge-description": "xviz_avsPython implementation of XVIZ protocol libraries.RequirementsPython3,websockets,protobuf,numpyGet startedYou can try running the scenario server bypython examples/serve_scenarios.py. Then you can runcd examples/get-started && yarn start-liveunder yourstreetscape.glrepository to see the example scenarios.AcknowledgementsYuanxin Zhongcreatedxviz.pyand allowed us to use it as the base for the official python XVIZ library."} +{"package": "xvr", "pacakge-description": "welcome to my package"} +{"package": "xwacommap", "pacakge-description": "xwacommap - Interactively map Wacom table to screen areaSynopsisxwacommapis a small utility that helps configuring a Wacom\ntablet to map to a selected area of the screen. It allows to\ndraw a rectangular region on the screen, then passes the\ngeometry to thexsetwacomtool. If the selected area is higher\nthan wide, the tablet is also rotated.RequirementsThis tool requires thexsetwacomtool from thexserver-xorg-input-wacompackage (on Debian systems).LicenceThis tool is licenced under the Apache 2.0 licence."} +{"package": "xwavecal", "pacakge-description": "No description available on PyPI."} +{"package": "xwavelet", "pacakge-description": "xwaveletA tool for Xarray-based spectral and wavelet analysisThis package provides a Xarray interface to theTorrence and Compo (1998)wavelet analysis routines.Observed Ni\u00f1o 3.4 sea surface temperature variability fromNOAA OISST"} +{"package": "xw-base-14", "pacakge-description": "utils for xw"} +{"package": "xw-cbase", "pacakge-description": "utils for xw"} +{"package": "xw-customer", "pacakge-description": "utils for xw customer"} +{"package": "xwdMath", "pacakge-description": "No description available on PyPI."} +{"package": "xweb", "pacakge-description": "High performance web framework built with uvloop and httptoolsIn Xweb, everything is asynchronous.FeaturesHigh performance.Asynchronous.Small.RequirementsPython3.6+Installationpip install xwebGet StartedHello WorldfromxwebimportAppapp=App()@app.useasyncdefresponse(ctx):ctx.res.body=\"Hello World\"if__name__=='__main__':app.listen(8000)Example with middleware.A middleware is an async function or an async callable object which looks like:async def logger(ctx, fn)# app.pyimporttimefromxwebimportAppapp=App()@app.useasyncdeflogger(ctx,fn):awaitfn()rt=ctx['X-Response-Time']print(rt)@app.useasyncdefresponse_time(ctx,fn):start=time.time()awaitfn()usage=(time.time()-start)*1000_000ctx['X-Response-Time']=f'{usage:.0f}\u00b5s'@app.useasyncdefresponse(ctx):ctx.res.body=\"Hello World\"if__name__=='__main__':app.listen(8000)Middlewarexweb-routerAppapp.use(fn)app.listen(host='127.0.0.1', port=8000, debug=True)Contextctx.reqctx.resctx.sendctx.abort(self, status, msg=\"\", properties=\"\")ctx.check(self, value, status=400, msg='', properties=\"\")Requestctx.reqis a Request object.ctx.req.headers dictctx.req.method strctx.req.url strctx.req.raw bytesctx.req.ip strResponsectx.resis a Request object.ctx.res.body strctx.res.status intctx.res.msg strctx.res.headers dictBenchmarkBenchmark code in benchmarks/.environment:iMac (Retina 4K, 21.5-inch, 2017),3 GHz Intel Core i5,8 GB 2400 MHz DDR4test command:wrk http://127.0.0.1:8000/ -c 100 -t 10 -d 10 -T 10FrameworksRequests/SecVersionxweb1000000.1.1vibora900000.0.6meinheld + wsgi770000.6.1sanic500000.7.0Deploy and Runpython app.py.Testpip install -r requirement.txtpytest --cov xweb.pyContributingBuild Middleware.XWeb is inspired bykoajs. I need some help for writing middleware as in koa. For example:Body parser. Convert the raw bytes body into dict or file.Data validator. Async data validator with high performance.Router. High performance router like koa-router.etc..Open issue.Suggestion.Bug."} +{"package": "xweb-router", "pacakge-description": "xweb-routerRouter middleware forxwebUsagefromxwebimportAppfromxweb_routerimportRouterapp=App()router=Router()nested=Router()app.use(router)@router.use('/')asyncdefmiddleware(ctx,fn):\"\"\"Router Middleware\"\"\"print('middleware')awaitfn()@router.post('/')asyncdefhome(ctx):ctx.body=\"Home\"@router.get('/{name}')asyncdefhello(ctx):\"\"\"URL parameters\"\"\"ctx.body=f\"Hello{ctx.params.name}\"router.use('/post')(nested)@nested.get('/index')asyncdefindex(ctx):ctx.body=\"Nested Index\"if__name__=='__main__':app.listen(8000)Nested Router"} +{"package": "xweights", "pacakge-description": "xweightsPython \u201cxweights\u201d contains functions to calculate grid weighted area means from predefined regions or from an user-given shapefile. This tool is a wrapper around the python packagexESMF.Free software: MIT licenseDocumentation:https://xweights.readthedocs.ioFeaturesCalculate grid-weighted-means and save the output as CSV fileAs input you need a dataset dictionary. Values are xarray.Datasets and keys correspondin strings.InstallationNote:Before buildingxweightsfrom source, you neddfirstinstallcartopyby using conda:conda install -c conda-forge cartopyYou can install the package directly with pip:pip install xweightsIf you want to contribute, I recommend cloning the repository and installing the package in development mode, e.g.git clone https://github.com/ludwiglierhammer/xweights.git\ncd xweights\npip install -e .In additon you have to install xESMF using _Conda:conda install -c conda-forge xesmfThis will install the package but you can still edit it and you don\u2019t need the package in yourPYTHONPATHRequirementspython3.6 or highernumpypandasgeopandasxarraypy-cordexxesmfContactIn cases of any problems, needs or wishes do not hesitate to contact:ludwig.lierhammer@hereon.deCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2022-03-04)First release on PyPI.0.1.1 (2022-07-01)adjusted to pre-commituse functions from pyhomogenize0.1.2 (2022-07-08)change pyhomogenize version requirements0.2.0 (2022-07-11)rename spatial_averagerkeep geometry attributes0.2.1 (2022-07-11)read and write column name to attributes0.2.2 (2022-07-12)add data and tables via pip install0.2.3 (2023-01-26)remove cartopy from requirements.txt0.2.4 (2023-03-13)using pycordex >= 0.5.10.2.5 (2023-08-23)adding new region: counties_merged (merge counties less than 400m2)0.2.6 (2023-08-30)optionally: wite variable attributes to dataframe0.3.0 (2023-09-15)added new regions: IPCC WG1 Reference Regions v4 from Atlasxweights/_io.py is no longer availablexweights/_domains.py is no longer availablefunctionspatial_averager->spatial_averagingfunctioncompute_weighted_means:optionally: setaverager_dsto calculate a general xesmf.SpatialAveragerparametershp->gdfparameterinput->dataset_dictparameterdataset_dicthas to be a dictionaryparameteroutdir->outputfunctioncompute_weighted_means_ds: parameters are now similar tocompute_weighted_meanscommand-line interface is no longer available"} +{"package": "xwe_nester", "pacakge-description": "UNKNOWN"} +{"package": "xwfintech-robotframework-common", "pacakge-description": "No description available on PyPI."} +{"package": "xwHash", "pacakge-description": "No description available on PyPI."} +{"package": "xwhy", "pacakge-description": "No description available on PyPI."} +{"package": "xwind", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xwinkey", "pacakge-description": "UNKNOWN"} +{"package": "xwire.common", "pacakge-description": "No description available on PyPI."} +{"package": "xwire.rest", "pacakge-description": "No description available on PyPI."} +{"package": "xwire.scientific", "pacakge-description": "No description available on PyPI."} +{"package": "xwire.transport", "pacakge-description": "No description available on PyPI."} +{"package": "xwklwwltestpackage", "pacakge-description": "No description available on PyPI."} +{"package": "xwmodule", "pacakge-description": "No description available on PyPI."} +{"package": "xwmt", "pacakge-description": "xWMTis a Python package that provides a framework for calculating\nwater mass tranformations in an xarray-based environment.More InformationSource code:http://github.com/jetesdal/xwmt"} +{"package": "xword-dl", "pacakge-description": "xword-dlxword-dlis a command-line tool to download .puz files for online crossword puzzles from supported outlets or arbitrary URLs with embedded crossword solvers. For a supported outlet, you can easily download the latest puzzle, or specify one from the archives.Supported outlets:OutletKeywordDownload latestSearch by dateSearch by URLAtlanticatl\u2714\ufe0f\u2714\ufe0fCrossword Clubclub\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fThe Daily Beastdb\u2714\ufe0fDer Standardstd\u2714\ufe0f\u2714\ufe0fThe Globe And Mail cryptictgam\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fGuardian Crypticgrdc\u2714\ufe0f\u2714\ufe0fGuardian Everymangrde\u2714\ufe0f\u2714\ufe0fGuardian Prizegrdp\u2714\ufe0f\u2714\ufe0fGuardian Quickgrdq\u2714\ufe0f\u2714\ufe0fGuardian Quipticgrdu\u2714\ufe0f\u2714\ufe0fGuardian Speedygrds\u2714\ufe0f\u2714\ufe0fGuardian Weekendgrdw\u2714\ufe0f\u2714\ufe0fLos Angeles Timeslat\u2714\ufe0f\u2714\ufe0fThe McKinsey Crosswordmck\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fThe Modern Crosswordmod\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fNew York Timesnyt\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fNew York Times Mininytm\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fNew York Times Varietynytv\u2714\ufe0fThe New Yorkertny\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fNewsdaynd\u2714\ufe0f\u2714\ufe0fSimply Daily Puzzlessdp\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fSimply Daily Puzzles Crypticsdpc\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fSimply Daily Puzzles Quicksdpq\u2714\ufe0f\u2714\ufe0f\u2714\ufe0fUniversaluni\u2714\ufe0f\u2714\ufe0fUSA Todayusa\u2714\ufe0f\u2714\ufe0fVoxvox\u2714\ufe0fWall Street Journalwsj\u2714\ufe0f\u2714\ufe0fWashington Postwp\u2714\ufe0f\u2714\ufe0fTo download a puzzle, installxword-dland run it on the command line.InstallationThe easiest way to installxword-dlis throughpip. Install the latest version with:pip install xword-dlYou can also installxword-dlby downloading or cloning this repository from Github. From a terminal, simply runningpython setup.py installin the downloaded directory may be enough.But in either case, you probably want to installxword-dland its dependencies in a dedicated virtual environment. I usevirtualenvandvirtualenvwrapperpersonally, but that's a matter of preference. If you're already feeling overwhelmed by the thought of managing Python packages, know you're not alone. Theofficial documentation is pretty good, but it's a hard problem, and it's not just you. If it's any consolation, learning how to use virtual environments today on something sort of frivolous like a crossword puzzle downloader will probably save you from serious headaches in the future when the stakes are higher.UsageOnce installed, you can invokexword-dl, providing the short code of the site from which to download. If you runxword-dlwithout providing a site keyword, it will print some usage instructions and then exit.For example, to download the latest Newsday puzzle, you could run:xword-dl nd --latestor simplyxword-dl ndYou can also download puzzles that are embedded in AmuseLabs solvers or on supported sites by providing a URL, such as:xword-dl https://rosswordpuzzles.com/2021/01/03/cover-up/In either case, the resulting .puz file can be opened withcursewordsor any other puz file reader.Specifying puzzle dateSome outlets allow specification of a puzzle to download by date using the--dateor-dflag. For example, to download the Universal puzzle from September 22, 2021, you could run:xword-dl uni --date 9/22/21The argument provided after the flag is parsed pretty liberally, and you can use relative descriptors such as \"yesterday\" or \"monday\". Use quotes if your date contains spaces (such as \"June 16, 2022\").Specifying filenamesBy default, files will be given a descriptive name based on puzzle metadata. If you want to specify a name for a given download, you can do so with the-oor--outputflag. The following tokens are available:TokenValue%outletOutlet name%prefixHardcoded outlet prefix%titlePuzzle title%authorPuzzle author%cmdPuzzle outlet keyword%netlocNetwork location (domain and subdomain)date tokensstrftimetokensConfiguration fileWhen runningxword-dl, a configuration file is created to store persistent settings. By default, this file is located at~/.config/xword-dl/xword-dl.yaml. You can manually edit this file to pass options toxword-dlat runtime.Most settings are specified by the command keyword. For example, if you want to saveUSA Todaypuzzles in this format:USA Today - By Brooke Husic Ed. Erik Agard - Right Turns - 221115.puzyou can specify that by editing your config file to include the following lines:usa:\n filename: '%prefix - %author - %title - %y%m%d'In addition to command keywords, you can also use the keysgeneral(to apply to all puzzles),url(to apply to embedded puzzles selected by URL at runtime) or with a givennetloc(to apply to embedded puzzles at a given domain or subdomain).New York Times authenticationNew York Times puzzles are only available to subscribers. Attempting to download with thenytkeyword without authentication will fail. To authenticate, run:xword-dl nyt --authenticateand you will be prompted for your New York Times username and password. (Those credentials can also be passed at runtime with the--usernameand--passwordflags.)If authentication is successful, an authentication token will be stored in a config file. Once that token is stored, you can download puzzles withxword-dl nyt.In some cases, the authentication may fail because of anti-automation efforts on New York Times servers. If the automatic authentication doesn't work for you, you canmanually find your NYT-S tokenand save it in your config file."} +{"package": "xwordlist", "pacakge-description": "xwordlistxwordlistis a command line Python program designed to help you create, build and organize crossword puzzle word lists. As I started to think about constructing crossword puzzles with heavy themes \u2014 trying to make the entire puzzle themed, not just three or four long entries \u2014 I realized that I would need the ability to acquire and organize large amounts of text on very specific topics. After hacking around with a combination of search-and-replace text editors and Excel, I realized I needed to build someting more custom and thusxwordlistwas born.Besides helping with basic text functions such as deduping, alphabetizing and changing case, this program is able to pull content out of structured web pages and parse large blocks of text, including lists of web pages with similarly structured content. Although I first started using the software to grab the lyrics of songs, I have added regex and better html parsing functionality to make it easier to get data from Wikipedia and less structured sites.For more information, see the project\u2019s main website hosted atxwl.ist. For an example of a themed 5x5 mini puzzle built with a word list assembled using this software, seemy personal website. For one of the original inspirations for this project, see Malaika Handa\u2019sCrosswiftpuzzle using only Taylor Swift\u2019s lyrics.InstallationIt helps to have some familiarity with Python and terminal programs to installxwordlistbut it is not a requirement. If your environment is all set up and you knowpipis both installed and up-to-date, skip down to thepipinstructions below. Most Macs and Linux users will find thatpipis installed but probably needs to be updated. Most Windows users will need to installpipfirst (seeWindows Special Instructionsbelow). In other words, unless you really know what you are doing, you probably need to continue to follow the next paragraph or the special Windows instructions.Search forterminaland your operating system should show you the name and how to launch your default terminal program. The first thing you will need to do is make sure your Python is up-to-date (required) and that you have activated a virtual environment (recommended). SeeInstalling Python Packagesfor helpful instructions on how to do both as well as how to install and upgradepip. Follow the instructions on that page down to the section labeledInstalling from PyPI.From there, you can installxwordlistby typingpip install xwordlistBe sure to typexwordlistas there is other software calledwordlist(without the \u201cx\u201d) which is not what you want. To see if your installation was successful, typexwordlist --versionIf properly installed, the software should respond with its name and the installed version.Windows Special InstructionsRegardless of whether Python is already installed on your Windows computer, I would highly recommend a fresh install of an up-to-date version fromPython.org\u2019s Windows downloads page. In theStable Releasescolumn are a number of Windows installers that are compatible with versions of Windows going back to XP and compatible with 32-bit and 64-bit Intel machines or 64-bit ARM. Find the most recent version of Python that is compatbile with your version of Windows and the type of processor you have and download that.When you launch the installer, select \u201cCustomize Installation\u201d and make sure the boxes next to \u201cPip\u201d and \u201cPy launcher\u201d are selected. Hit the \u201cNext\u201d button and make sure the boxes next to both \u201cCreate shortcuts for installed applications\u201d and \u201cAdd Python to environment variables\u201d are selected. Finally, hit the \u201cInstall\u201d button.From there, you should be able to follow the original instructions above by typingpip install xwordlistManual InstallationTo install the software manually, copy thexwordlistcode to your local working environment by either cloning this repository or downloading and unpacking thezip archiveinto a new directory. To install the dependencies required to makexwordlistwork, use your terminal program to find the directory in which you have copied the files and typepython3 -m pip install -r requirements.txtTo see if your installation was successful, typepython3 xwordlist.py --versionIf properly installed, the software should respond with its name and the installed version.UsageIf you have installed the software usingpip, you should be able to run the program by simply typingxwordlistorxwl. For manual installs, you will need to typepython3 xwordlist.py. The rest of the documentation assumes you have installed viapipand uses the short form.For quick help instructions on the command line, typexwordlist --helpPlease see theproject\u2019s main websitefor more information about using the software including abasic example,recipes for common patternsand areferenceto all options.Find a bug? Please let us knowhere.LicenseThis software is available as open source under the terms of theMIT License."} +{"package": "xwork", "pacakge-description": "long_description"} +{"package": "xworker", "pacakge-description": "No description available on PyPI."} +{"package": "xworkflows", "pacakge-description": "XWorkflows is a library to add workflows, or state machines, to Python objects.It has been fully tested with Python 2.7 and all versions from 3.4 to 3.9LinksPackage on PyPI:http://pypi.python.org/pypi/xworkflowsRepository and issues on GitHub:http://github.com/rbarrois/xworkflowsDoc onhttp://readthedocs.org/docs/xworkflows/ExampleIt allows to easilly define a workflow, attach it to a class, and use its transitions:importxworkflowsclassMyWorkflow(xworkflows.Workflow):# A list of state namesstates=(('foo',\"Foo\"),('bar',\"Bar\"),('baz',\"Baz\"),)# A list of transition definitions; items are (name, source states, target).transitions=(('foobar','foo','bar'),('gobaz',('foo','bar'),'baz'),('bazbar','baz','bar'),)initial_state='foo'classMyObject(xworkflows.WorkflowEnabled):state=MyWorkflow()@xworkflows.transition()deffoobar(self):return42# It is possible to use another method for a given transition.@xworkflows.transition('gobaz')defblah(self):return13>>>o=MyObject()>>>o.state>>>>o.state.is_fooTrue>>>o.state.name'foo'>>>o.state.title'Foo'>>>o.foobar()42>>>o.state>>>>o.state.name'bar'>>>o.state.title'Bar'>>>o.blah()13>>>o.state>>>>o.state.name'baz'>>>o.state.title'Baz'HooksCustom functions can be hooked to transactions, in order to run before/after a transition,\nwhen entering a state, when leaving a state, \u2026:classMyObject(xworkflows.WorkflowEnabled):state=MyWorkflow()@xworkflows.before_transition('foobar')defmy_hook(self,*args,**kwargs):# *args and **kwargs are those passed to MyObject.foobar(...)pass@xworkflows.on_enter_state('bar')defmy_other_hook(self,result,*args,**kwargs):# Will be called just after any transition entering 'bar'# result is the value returned by that transition# *args, **kwargs are the arguments/keyword arguments passed to the# transition.pass"} +{"package": "xwot-dsl", "pacakge-description": "xwot_dsl.py - Python xwot_dsl for the xwot meta model."} +{"package": "xWoTModelTranslator", "pacakge-description": "# Model2Code converterConvert an xWoT meta-model to executable python code.# Installation## End Userspip install xWoTModelTranslator## Developers### Final installationfrom a terminal launchsudo python setup.py install --record files.txtthis will compile and install the project to the pyhton libraries (eg. /usr/local/lib/python2.7/dist-packages/XWoT_Model_Translator-1.1-py2.7.egg). Furthermore it will install three scripts in /usr/local/bin/:* physical2virtualEntities* model2Python* model2WADLThe configuration and logging.conf are copied into /etc/Model2WADL/ but it is possible to overwrite them either by placing a file with the same name (but prefixed with a dot eg. .logging.conf) in the user home directory or a file with the same name in the current working directory.### Development installationfrom a terminal launchsudo python setup.py develop --record files.txtdoes the same as before but, uses links instead of copying files.### Clean Working directoryTo clean the working directorysudo python setup.py clean --allsudo rm -rf build/ dist/ xWoTModelTranslator.egg.egg-info/ files.txt# Uninstall## Method 1cat files.txt |sudo xargs rm -rf## Method 2First find the installed package with pip and the uninstall it~/Documents/Programming/Python/Model2WADL [master|\u271a 1\u20261]12:13 $ pip freeze |grep xWot*3:xWoTModelTranslator==1.1~/Documents/Programming/Python/Model2WADL [master|\u271a 1\u20261]12:13 $ sudo pip uninstall xWoTModelTranslatorUninstalling xWoTModelTranslator:/Library/Python/2.7/site-packages/xWoTModelTranslator-1.1-py2.7.egg/usr/local/bin/model2Python/usr/local/bin/model2WADL/usr/local/bin/physical2virtualEntitiesProceed (y/n)? ySuccessfully uninstalled xWoTModelTranslator~/Documents/Programming/Python/Model2WADL [master|\u271a 1\u20261]12:13 $# UtilisationThe package provide two scripts: _physical2virtualEntities_ and _model2Python_. The first one is used to enhance an xWoT model (created with the according Eclipse plugin see https://github.com/aruppen/architecture4xwot for how to get this eclipse plug-in) containing only the virtual side of a Device with the corresponding virtual side. The second script takes a final xWoT model and translates it into code skeletons. The code sekeltons reflects the chosen hierarchy as a RESTful webservice based on python and autobahn."} +{"package": "xwot-py", "pacakge-description": "xwot.py - Python tools for the extended Web of Things"} +{"package": "xwot-yadp", "pacakge-description": "Yadp is a prototype implementation of a Discovery Protocol.It allows to carry user-defined payload data.It\u2019s line oriented protocol and looks like HTTP.It allows to carry meta headers to encode the content-type of the user-defined payload data,\na location header to retrieve more information about the discovered service."} +{"package": "xwpandas", "pacakge-description": "xwpandasxwpandas is high performance Excel IO tools for pandas DataFrame. xp.save function in xwpandas saves large(100k~ rows) DataFrame to xlsx format 2x~3x faster than xlsxwriter engine in pandas.Installationxwpandas can be installed usingpippackage manager.$pipinstallxwpandasUsageRead data from Excel fileimportxwpandasasxpdf=xp.read('path/to/file.xlsx')dfView data in Excel windowxp.view(df)Save DataFrame to Excel filexp.save(df,'path/to/file.xlsx')"} +{"package": "xwppy", "pacakge-description": "# xwppyThis library is a bridge between python and wordpress. You can upload a files, articles, or create articles on wordpress using this library."} +{"package": "xwrf", "pacakge-description": "xWRFCIDocsPackageLicenseA lightweight interface for working with theWeather Research and Forecasting (WRF)model output in Xarray. The primary objective ofxWRFis to replicate crucial functionality from thewrf-pythonpackage in a way that ismore convenientfor users and providesseamless integrationwith the rest of the Pangeo software stack.Seedocumentationfor more information."} +{"package": "x-wr-timezone", "pacakge-description": "Some calendar providers introduce the non-standardX-WR-TIMEZONEparameter\nto ICS calendar files.\nStrict interpretations according to RFC 5545 ignore theX-WR-TIMEZONEparameter.\nThis causes the times of the events to differ from those\nwhich make use ofX-WR-TIMEZONE.This module aims to bridge the gap by converting calendars\nusingX-WR-TIMEZONEto a strict RFC 5545 calendars.\nSo, let\u2019s put our heads together and solve this problem for everyone!Some features of the module are:Easy install with Python\u2019spip.Command line conversion of calendars.Piping of calendar files withwgetorcurl.Some of the requirements are:Calendars withoutX-WR-TIMEZONEare kept unchanged.Passing calendars twice to this module does not change them.InstallInstall usingpip:python3-mpipinstallx-wr-timezoneSupportDonate using GitHub SponsorsDonate using Open CollectiveDonate using thanks.devCommand Line UsageYou can standardize the calendars using your command line interface.\nThe examples assume thatin.icsis a calendar which may useX-WR-TIMEZONE, whereasout.icsdoes not requireX-WR-TIMEZONEfor proper display.catin.is|x-wr-timezone>out.icsx-wr-timezonein.icsout.icscurlhttps://example.org/in.ics|x-wr-timezone>out.icswget-O-https://example.org/in.ics|x-wr-timezone>out.icsYou can get usage help on the command line:x-wr-timezone--helpPythonAfter you have installed the library, you can import it.importx_wr_timezoneThe functionto_standard()converts anicalendarobject.x_wr_timezone.to_standard(an_icalendar)Here is a full example which does about as much as this module is supposed to do:importicalendar# installed with x_wr_timezoneimportx_wr_timezonewithopen(\"in.ics\",'rb')asfile:calendar=icalendar.from_ical(file.read())new_calendar=x_wr_timezone.to_standard(calendar)# you could use the new_calendar variable nowwithopen('out.ics','wb')asfile:file.write(new_calendar.to_ical())to_standard(calendar, timezone=None)has these parameters:calendaris theicalendar.Calendarobject.timezoneis an optional time zone. By default, the time zone incalendar['X-WR-TIMEZONE']is used to check if the calendar needs\nchanging.\nWhentimezoneis notNonehowever,calendar['X-WR-TIMEZONE']will not be tested and it is assumed that thecalendarshould be\nchanged as ifcalendar['X-WR-TIMEZONE']had the value oftimezone.\nThis does not add or change the value ofcalendar['X-WR-TIMEZONE'].\nYou would need to do that yourself.timezonecan be a string like\"UTC\"or\"Europe/Berlin\"or\napytz.timezoneor something thatdatetimeaccepts as a time zone..Return value: Thecalendarargument is not modified at all. The calendar\nreturned has the attributes and subcomponents of thecalendaronly\nchanged and copied where needed to return the proper value. As such,\nthe returned calendar might be identical to the one passed to the\nfunction as thecalendarargument. Keep that in mind if you modify the\nreturn value.DevelopmentClone therepositoryor its fork andcdx-wr-timezone.Optional: Install virtualenv and Python3 and create a virtual environment:pipinstallvirtualenvvirtualenv-ppython3ENVsourceENV/bin/activate# you need to do this for each shellInstall the packages and this module so it can be edited:pipinstall-rtest-requirements.txt-e.Run the tests:pytestTo test all functions:pytest--x-wr-timezoneallTesting withtoxYou can usetoxto test the package in different Python versions.toxThis tests all the different functionalities:tox----x-wr-timezoneallNew ReleasesTo release new versions,edit the Changelog Sectionedit setup.py, the__version__variablecreate a commit and push itWait forCI teststo finish the build.runpython3setup.pytag_and_deploynotify the issues about their releaseTestingThis project\u2019s development is driven by tests.\nTests assure a consistent interface and less knowledge lost over time.\nIf you like to change the code, tests help that nothing breaks in the future.\nThey are required in that sense.\nExample code and ics files can be transferred into tests and speed up fixing bugs.You can view the tests in thetest folder.\nIf you have a calendar ICS file for which this library does not\ngenerate the desired output, you can add it to thetest/calendarsfolder and write tests for what you expect.\nIf you like,open an issuefirst, e.g. to discuss the changes and\nhow to go about it.Changelogv0.0.6Obsolete Python 3.7Support Python 3.11Fix localization issue for pytz when datetime has no timezoneRun tests on GitHub ActionsRequire icalendar 5.0.11 for testsFix pytz localization issue when dateime is not in UTC and has no time zone.v0.0.5Revisit README and CLI and fix spelling mistakes.Modified behavior to treat events without time zone found in a calendar using the X-WR-TIMEZONE property, seePull Request 7v0.0.4Test automatic deployment with Gitlab CI.v0.0.3Usetzname()function ofdatetimeto test for UTC. This helps support zoneinfo time zones.Split up visitor class and rename it to walker.v0.0.2Implement thetimezoneargument.Do not modify the value of thecalendarargument and only copy it where needed.v0.0.1Initial release supports DTSTART, DTEND, EXDATE, RDATE, RECURRENCE-ID attributes of events.Command line interface asx-wr-timezone.Related WorkThis module was reated beause of these issues:icalendar#343python-recurring-ical-events#71Related SoftwareThis module uses theicalendarlibrary for parsing calendars.\nThis library is used bypython-recurring-ical-eventsto get events at specific dates.LicenseThis software is licensed under LGPLv3, see the LICENSE file."} +{"package": "xwtgzs-lz", "pacakge-description": "\u6b64\u5e93\u4e2d\u6709\u4e24\u4e2a\u6a21\u5757\uff1atext_and_number\uff08\u6587\u5b57\u4e0e\u6570\u5b57\u5904\u7406\u5e93\uff0c\u540e\u6587\u7b80\u79f0\u4e3aTAN\uff091.speak\uff08text\uff09text\u662f\u6587\u672c\u6216\u6570\u5b57\u7c7b\u578b\uff0c\u6b64\u65b9\u6cd5\u5c06\u751f\u6210\u4e00\u4e2a.vbs\u6587\u4ef6\u5728pip\u5b89\u88c5\u4f4d\u7f6e\uff0c\u9ed8\u8ba4\u81ea\u52a8\u8bfb\u51fa\u6587\u4ef6\u3002\n2.remove_quotation_marks\uff08a\uff09a\u662f\u4efb\u610f\u5b57\u7b26\u4e32\uff0c\u5b83\u5c06\u5b57\u7b26\u4e32\u53bb\u6389\u4e24\u4e2a\u201c\u201d\u201d\u201d(\u6b64\u65b9\u6cd5\u5bf9\u4e8e\u6587\u5b57\u4e5f\u6709\u7528)\uff0c\u8fd4\u56de\u503c\u4e3a\u975e\u5b57\u7b26\u4e32\u7684\u6587\u5b57\u6216\u6570\u5b57\u3002\n3.dictionary_value_separation(a, number)a\u662f\u5b57\u5178\uff0cnumber\u662f0\u6216\u80051\uff0c\u5b83\u7528\u4e8e\u5c06\u5b57\u5178\u7684\u952e\u548c\u503c\u5206\u79bb\uff0c\u5e76\u4e14\u8fd4\u56de\u4e00\u4e2a\u5217\u8868\uff0c\u5176\u4e2d\u6709\u6240\u6709\u7684\u503c\u6216\u8005\u952e\uff0cnumber\u662f0\u662f\u53d6\u952e\uff0c1\u53d6\u503c\u3002\n4.power_calculation\uff08a,number\uff09\u6b64\u65b9\u6cd5\u4e2d\uff0ca\u548cnumber\u5747\u4e3a\u6570\u5b57\uff0c\u8ba1\u7b97number\u7684a\u6b21\u65b9\uff0c\u8fd4\u56de\u8ba1\u7b97\u7ed3\u679c\u7684\u6570\u503c\u3002\n5.Solve_the_greatest_common_factor(x, y)\u6c42\u89e3x,y\u7684\u6700\u5927\u56e0\u65706.Solve_the_least_common_multiple\uff08x\uff0cy\uff09\u6c42\u89e3x,y\u7684\u6700\u5c0f\u516c\u500d\u6570;common_methods_in_daily_life(\u65e5\u5e38\u751f\u6d3b\u4e2d\u7684\u5e38\u7528\u65b9\u6cd5,\u540e\u6587\u7b80\u79f0\u4e3aCMIDL)1.weather(a, b, c),a\u662f\u5b57\u7b26\u4e32\u683c\u5f0f\u7684\u7701\u4efd\u62fc\u97f3\uff0cb\u662f\u5b57\u7b26\u4e32\u683c\u5f0f\u7684\u57ce\u5e02\u62fc\u97f3\uff0cc\u662f\u6570\u503c\uff1b\u5f53c = 0\u4e3a\u4eca\u5929\uff0cc = 1\u4e3a\u660e\u5929\uff0cc=3\u4e3a\u540e\u5929\uff08\u5176\u4e2d\u542b\u6709\u5929\u6c14\u3001\u6c14\u6e29\u3001\u7a7f\u8863\u63d0\u9192\u7b49\uff09\n2.be_qr(a,b)\uff0c\u751f\u6210\u4e8c\u7ef4\u7801\uff0ca\u662f\u683c\u5f0f\u968f\u4fbf\u7684\u5185\u5bb9\uff0cb\u662f\u6570\u503c1\u6216\u80050\uff0c\u5982\u679cb= 1 \u5219\u5c55\u793a\u751f\u6210\u7684\u56fe\u7247\uff0cb = 0\u5219\u8fd4\u56de\u56fe\u7247\u540d\uff0c\u53ef\u5168\u76d8\u67e5\u627e\u3002"} +{"package": "xwtools", "pacakge-description": "\u8fd9\u662f\u4e00\u4e2a\u901a\u7528\u7684python\u5de5\u5177\u5305\uff0c\u5e2e\u52a9\u4f60\u5feb\u901f\u7684\u5f00\u53d1\u9879\u76ee"} +{"package": "xw-utils", "pacakge-description": "utils for xw"} +{"package": "xww", "pacakge-description": "No description available on PyPI."} +{"package": "xwy-add", "pacakge-description": "No description available on PyPI."} +{"package": "xwyadd3num", "pacakge-description": "No description available on PyPI."} +{"package": "x_x", "pacakge-description": "x_x is a command line reader that displays either Excel files or CSVs in your terminal. The purpose of this is to not break the workflow of people who live on the command line and need to access a spreadsheet generated using Microsoft Excel.InstallThe easy way:$ pip install x_xOr the hard way:$ git clone https://github.com/krockode/x_x.git && cd x_x && python setup.py installUsageInstalling this package gives you anx_xCLI executable.$ x_x --help\nUsage: x_x [OPTIONS] FILENAME\n\n Display Excel or CSV files directly on your terminal. 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No problem!$ cat dead_guys.csv\nperson;age_at_death\nHarrold Holt;59\nHarry Houdini;52\nHoward Hughes;70\n|Not some guy, but just a string with ; in it|;0$ x_x -h 0 --delimiter=';' --quotechar='|' dead_guys.csv\n+----------------------------------------------+--------------+\n| person | age_at_death |\n+----------------------------------------------+--------------+\n| Harrold Holt | 59 |\n| Harry Houdini | 52 |\n| Howard Hughes | 70 |\n| Not some guy, but just a string with ; in it | 0 |Does your CSV file not end in \u201ccsv\u201d? 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HTTP Status Code: 404"} +{"package": "xxcmd", "pacakge-description": "xxcmdxxis a Linux shell command.xxremembers other shell commands, so you don't have to.InstallationpipRequires Python 3. Installation is simple usingpip.pipinstallxxcmdOrpip3on Ubuntu or Debian based distros.If typingxxat a command prompt gives you \"Command not found\", you likely don't have~/.local/binon your PATH. Either install globally withsudo pip install xxcmdor add~/.local/binto your PATH.Arch LinuxThexxcmdpackage in availabe in the AUR.Basic Usage ExamplesUsingxxyou build up a database of useful commands and search and execute them whenever you like.Adding Command ExamplesMost basic example, adding thetopcommand.xx-atopAdd theducommand to display size of all files and directories in the current directory.xx-adu--max-depth=1-h.Add the same command but with a friendly (searchable) label:xx-a[FileSizes]du--max-depth=1-h.Adding our favourite ssh command:xx-a[SSHBestHost]ssh-i~/.ssh/mykey.pemme@myhost.comAdd the last command you executed:xx-a!!Add the last command you executed with a descriptive label:xx-a[MyCoolLabel]!!If adding commands containing characters that are interpreted by your shell, such as|or&&enclose the command in quotes. You can also use double quotes with bash's last command operator:xx-a[CommandwithPipes]\"!!\"End the label name with an exclamation mark and you will be asked for confirmation before this command is executed.xx-a[DangerousCommand!]echo\"boo\"Browse and Search Commands InteractivelyRunxxwith no options to enter the interactive view.xxQuick Search and Executexxcan search for matching commands and if only one match is found it will be immediately executed.The search looks in labels and commands.So one way to execute theducommand we added above is:xxsizesWhich finds a match on our label \"File Sizes\" and runs the associated command.We could immediately ssh connect with:xxbestWhich would match our label \"SSH Best Host\".Interactive ViewInvokingxxwithout options will open the interactive view. This presents a list of all commands with an interactive search.Keys:Up/Down- navigate the list of commands.Delete- remove the currently selected commandReturn- execute the currently selected commandEscape- exitF1orCTRL+E- Edit the label of the currently selected itemF2orCTRL+I- Edit the label of the currently selected itemF3orCTRL+G- Add a new command.Any other key press is added to the interactive search to filter the command list.Further Usageusage: xx [-h] [-a ...] [-b] [-e] [-i URL] [-c] [-f FILE] [-g] [-l] [-m] [-n]\n [-p PADDING] [-s] [-t] [-v]\n [SEARCH ...]\n\nRemembers other shell commands, so you don't have to.\n\npositional arguments:\n SEARCH Search for a matching command and run it immediately.\n\noptional arguments:\n -h, --help show this help message and exit\n -a ..., --add ... Add the given command to the database. Command may\n begin with a label enclosed in square brackets [label]\n \n -b, --no-border Don't display a window border.\n -e, --no-help Don't display the shortcut key help footer.\n -i URL, --import-url URL\n Import a command database from the given URL. Merge\n into existing database.\n -c, --create-config Create a config file in the users home directory if\n one doesn't already exist.\n -f FILE, --db-file FILE\n Use the command database file specified rather than\n the default.\n -g, --no-global-database\n Don't load the global system database.\n -l, --list Print all commands in the database\n -m, --no-commands Don't show commands in interactive view.\n -n, --no-echo Don't echo the command to the terminal prior to\n execution.\n -p PADDING, --label-padding PADDING\n Add extra padding between labels and commands.\n -s, --search-all Search both labels and commands. Default is to search\n only labels first, and only search in commands if\n searching for labels resulted in no search results.\n -t, --no-labels Don't display command labels.\n -v, --version Display program version.ConfigurationIn addition to the command line switches a configuration file can be used. The file named.xxcmdrcin the current users home directory is loaded if present.Some options are only configurable through the config file.An example file demonstrating all possible options (and the system defaults):[xxcmd]\necho-commands = yes\nshow-labels = yes\nshow-commands = yes\nalign-commands = yes\ndraw-window-border = yes\nlabel-padding = 2\nbracket-labels = no\nbold-labels = yes\nwhole-line-selection = yes\nsearch-labels-only = no\nsearch-labels-first = yes\nshell = default\nsort-by-label = yes\nsort-by-command = no\nsort-case-sensitive = yes\ndisplay-help-footer = yes\nload-global-database = yesCommand line switches take precedence over configuration file options.shellcan be set to the full path of the shell to be used to execute commands, such as/bin/sh. If set todefaultthe environmental variableSHELLis inspected to use the default OS shell."} +{"package": "xxcore", "pacakge-description": "No description available on PyPI."} +{"package": "xxdiff-scripts", "pacakge-description": "This package provides a number of scripts that are used to perform a variety of\ntasks that all involve getting user verification and feedback using the xxdiff\ngraphical differences viewer.For example, there are scripts to perform global renaming of strings within a\nlarge codebase, where each transformed file is viewed by the user with an\nxxdiff, accepted, rejected or merged changes written over the original file\n(file backups are supported). Also, this infrastructure is mostly provided as\nmodules, in order to allow users to write file transformations in Python and to\nleverage this interactive confirmation process.There are also scripts that visualize diffs for a number of SCM systems, like\nCVS, Subversion, etc. This package was born after a number of these useful\nscripts had sprouted, and it became apparent that sharing the common code for\nthe scripts would be a great advantage to tools writers.See documentation for a full list of the scripts and their role:http://furius.ca/xxdiff/doc/xxdiff-scripts.html"} +{"package": "xxe", "pacakge-description": "soon"} +{"package": "xx-framework", "pacakge-description": "Python\u4e0a\u4f4d\u673a\u8f6e\u5b50"} +{"package": "xxgamma", "pacakge-description": "xxgamma is a PyGTK based GUI for xgamma which allows you to load,\nmodify and store multiple gamma correction profiles for XFree86\nand X.org through a GUI and a command line interface."} +{"package": "xxh", "pacakge-description": "Package DescriptionThis package provides a Python interface to the xxHash fast non-cryptographic\nhash algorithm. Inspired byexisting Python wrappers for xxHash, this package exposes both the 32 and\n64-bit versions of the algorithm and leveragesCythonto\nprovide better support for incremental updating of a hash using data\nencapsulated in a range of Python container classes. The package is compatible\nwith Python 2.7 and later.Quick StartMake sure you havepipandCythoninstalled; once you do, install\nthe package as follows:pip install xxhDevelopmentThe latest source code can be obtained from the project website atGitHub.Authors & AcknowledgementsSee the includedAUTHORS.rstfile for\nmore information.LicenseThis software is licensed under theBSD License.\nSee the includedLICENSE.rstfile for\nmore information."} +{"package": "xxh3", "pacakge-description": "xxh3Rust implementation of the XXH3 hash functionLicenseLicensed under either ofApache License, Version 2.0MIT Licenseat your option.ContributionUnless you explicitly state otherwise, any contribution intentionally\nsubmitted for inclusion in the work by you, as defined in the Apache-2.0\nlicense, shall be dual licensed as above, without any additional terms or\nconditions."} +{"package": "xxhash", "pacakge-description": "xxhash is a Python binding for thexxHashlibrary byYann Collet.Installation$pipinstallxxhashYou can also install using conda:$condainstall-cconda-forgepython-xxhashInstalling From Source$pipinstall--no-binaryxxhashxxhashPrerequisitesOn Debian/Ubuntu:$apt-getinstallpython-devgccOn CentOS/Fedora:$yuminstallpython-develgccredhat-rpm-configLinking to libxxhash.soBy default python-xxhash will use bundled xxHash,\nwe can change this by specifying ENV varXXHASH_LINK_SO:$XXHASH_LINK_SO=1pipinstall--no-binaryxxhashxxhashUsageModule version and its backend xxHash library version can be retrieved using\nthe module propertiesVERSIONANDXXHASH_VERSIONrespectively.>>>importxxhash>>>xxhash.VERSION'2.0.0'>>>xxhash.XXHASH_VERSION'0.8.0'This module is hashlib-compliant, which means you can use it in the same way ashashlib.md5.update() \u2013 update the current digest with an additional stringdigest() \u2013 return the current digest valuehexdigest() \u2013 return the current digest as a string of hexadecimal digitsintdigest() \u2013 return the current digest as an integercopy() \u2013 return a copy of the current xxhash objectreset() \u2013 reset statemd5 digest returns bytes, but the original xxh32 and xxh64 C APIs return integers.\nWhile this module is made hashlib-compliant,intdigest()is also provided to\nget the integer digest.Constructors for hash algorithms provided by this module arexxh32()andxxh64().For example, to obtain the digest of the byte stringb'Nobody inspects the spammish repetition':>>>importxxhash>>>x=xxhash.xxh32()>>>x.update(b'Nobody inspects')>>>x.update(b' the spammish repetition')>>>x.digest()b'\\xe2);/'>>>x.digest_size4>>>x.block_size16More condensed:>>>xxhash.xxh32(b'Nobody inspects the spammish repetition').hexdigest()'e2293b2f'>>>xxhash.xxh32(b'Nobody inspects the spammish repetition').digest()==x.digest()TrueAn optional seed (default is 0) can be used to alter the result predictably:>>>importxxhash>>>xxhash.xxh64('xxhash').hexdigest()'32dd38952c4bc720'>>>xxhash.xxh64('xxhash',seed=20141025).hexdigest()'b559b98d844e0635'>>>x=xxhash.xxh64(seed=20141025)>>>x.update('xxhash')>>>x.hexdigest()'b559b98d844e0635'>>>x.intdigest()13067679811253438005Be careful that xxh32 takes an unsigned 32-bit integer as seed, while xxh64\ntakes an unsigned 64-bit integer. Although unsigned integer overflow is\ndefined behavior, it\u2019s better not to make it happen:>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=0).hexdigest()'f7a35af8'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=2**32).hexdigest()'f7a35af8'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=1).hexdigest()'d8d4b4ba'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=2**32+1).hexdigest()'d8d4b4ba'>>>>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=0).hexdigest()'d4cb0a70a2b8c7c1'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=2**64).hexdigest()'d4cb0a70a2b8c7c1'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=1).hexdigest()'ce5087f12470d961'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=2**64+1).hexdigest()'ce5087f12470d961'digest()returns bytes of thebig-endianrepresentation of the integer\ndigest:>>>importxxhash>>>h=xxhash.xxh64()>>>h.digest()b'\\xefF\\xdb7Q\\xd8\\xe9\\x99'>>>h.intdigest().to_bytes(8,'big')b'\\xefF\\xdb7Q\\xd8\\xe9\\x99'>>>h.hexdigest()'ef46db3751d8e999'>>>format(h.intdigest(),'016x')'ef46db3751d8e999'>>>h.intdigest()17241709254077376921>>>int(h.hexdigest(),16)17241709254077376921Besides xxh32/xxh64 mentioned above, oneshot functions are also provided,\nso we can avoid allocating XXH32/64 state on heap:xxh32_digest(bytes, seed=0)xxh32_intdigest(bytes, seed=0)xxh32_hexdigest(bytes, seed=0)xxh64_digest(bytes, seed=0)xxh64_intdigest(bytes, seed=0)xxh64_hexdigest(bytes, seed=0)>>>importxxhash>>>xxhash.xxh64('a').digest()==xxhash.xxh64_digest('a')True>>>xxhash.xxh64('a').intdigest()==xxhash.xxh64_intdigest('a')True>>>xxhash.xxh64('a').hexdigest()==xxhash.xxh64_hexdigest('a')True>>>xxhash.xxh64_hexdigest('xxhash',seed=20141025)'b559b98d844e0635'>>>xxhash.xxh64_intdigest('xxhash',seed=20141025)13067679811253438005L>>>xxhash.xxh64_digest('xxhash',seed=20141025)'\\xb5Y\\xb9\\x8d\\x84N\\x065'In[1]:importxxhashIn[2]:%timeitxxhash.xxh64_hexdigest('xxhash')268ns\u00b124.1nsperloop(mean\u00b1std.dev.of7runs,1000000loopseach)In[3]:%timeitxxhash.xxh64('xxhash').hexdigest()416ns\u00b117.3nsperloop(mean\u00b1std.dev.of7runs,1000000loopseach)XXH3 hashes are available since v2.0.0 (xxHash v0.8.0), they are:Streaming classes:xxh3_64xxh3_128Oneshot functions:xxh3_64_digest(bytes, seed=0)xxh3_64_intdigest(bytes, seed=0)xxh3_64_hexdigest(bytes, seed=0)xxh3_128_digest(bytes, seed=0)xxh3_128_intdigest(bytes, seed=0)xxh3_128_hexdigest(bytes, seed=0)And aliases:xxh128 = xxh3_128xxh128_digest = xxh3_128_digestxxh128_intdigest = xxh3_128_intdigestxxh128_hexdigest = xxh3_128_hexdigestCaveatsSEED OVERFLOWxxh32 takes an unsigned 32-bit integer as seed, and xxh64 takes\nan unsigned 64-bit integer as seed. Make sure that the seed is greater than\nor equal to0.ENDIANNESSAs of python-xxhash 0.3.0,digest()returns bytes of thebig-endianrepresentation of the integer digest. It used\nto be little-endian.DONT USE XXHASH IN HMACThough you can use xxhash as anHMAChash function, but it\u2019s\nhighly recommended not to.xxhash isNOTa cryptographic hash function, it is a\nnon-cryptographic hash algorithm aimed at speed and quality.\nDo not put xxhash in any position where cryptographic hash\nfunctions are required.Copyright and LicenseCopyright (c) 2014-2020 Yue Du -https://github.com/ifduyueLicensed underBSD 2-Clause LicenseCHANGELOGv3.4.1 2023-10-05Remove setuptools_scmv3.4.0 2023-10-05Build wheels for Python 3.12v3.3.0 2023-07-29Upgrade xxHash to v0.8.2Drop support for Python 3.6v3.2.0 2022-12-28This is the last version to support Python 3.6Build Python 3.11 wheels.Remove setup.py test_suites, call unittest directlyv3.1.0 2022-10-19Type annotations.Enabled muslinux wheels building.v3.0.0 2022-02-25New setalgorithms_availablelists all implemented algorithms inxxhashpackage.Upgrade xxHash to v0.8.1.Drop support for EOL Python versions, require python >= 3.6 from now on.Migrate to github actions and build arm64 wheels for macOS.Always release GIL.v2.0.2 2021-04-15Fix Travis CI OSX dpl python2.7 get-pip.py errorv2.0.1 2021-04-15Only to trigger Python 3.9 wheels building.v2.0.0 2020-08-03Require xxHash version >= v0.8.0Upgrade xxHash to v0.8.0XXH3 hashes:xxh3_64,xxh3_128, and their oneshot functionsv1.4.4 2020-06-20Upgrade xxHash to v0.7.3Stop using PEP393 deprecated APIsUse XXH(32|64)_canonicalFromHash to replace u2bytes and ull2bytesv1.4.3 2019-11-12Upgrade xxHash to v0.7.2Python 3.8 wheelsv1.4.2 2019-10-13Fixed: setup.py fails when reading README.rst and the default encoding is not UTF-8v1.4.1 2019-08-27Fixed: xxh3.h in missing from source tarballv1.4.0 2019-08-25Upgrade xxHash to v0.7.1v1.3.0 2018-10-21Wheels are now built automaticallySplit CFFI variant into a separate packageifduyue/python-xxhash-cffiv1.2.0 2018-07-13Add oneshot functions xxh{32,64}_{,int,hex}digestv1.1.0 2018-07-05Allow input larger than 2GBRelease the GIL on sufficiently large inputDrop support for Python 3.2v1.0.1 2017-03-02Free state actively, instead of delegating it to ffi.gcv1.0.0 2017-02-10Fixed copy() segfaultAdded CFFI variantv0.6.3 2017-02-10Fixed copy() segfaultv0.6.2 2017-02-10Upgrade xxHash to v0.6.2v0.6.1 2016-06-26Upgrade xxHash to v0.6.1v0.5.0 2016-03-02Upgrade xxHash to v0.5.0v0.4.3 2015-08-21Upgrade xxHash to r42v0.4.1 2015-08-16Upgrade xxHash to r41v0.4.0 2015-08-05Added method resetUpgrade xxHash to r40v0.3.2 2015-01-27Fixed some typos in docstringsv0.3.1 2015-01-24Upgrade xxHash to r39v0.3.0 2014-11-11Change digest() from little-endian representation to big-endian representation of the integer digest.\nThis change breaks compatibility (digest() results are different).v0.2.0 2014-10-25Make this package hashlib-compliantv0.1.3 2014-10-23Update xxHash to r37v0.1.2 2014-10-19Improve: Check XXHnn_init() return value.Update xxHash to r36v0.1.1 2014-08-07Improve: Can now be built with Visual C++ Compiler.v0.1.0 2014-08-05New: XXH32 and XXH64 type, which support partially update.Fix: build under Python 3.4v0.0.2 2014-08-03NEW: Support Python 3v0.0.1 2014-07-30NEW: xxh32 and xxh64"} +{"package": "xxhash-cffi", "pacakge-description": "xxhash-cffi is a Python binding for thexxHashlibrary byYann Collet.Installation$pipinstallxxhash-cffiInstallation PrerequisitesIf you\u2019re installing xxhash-cffi from source, you probably want to install the following packages.On Debian/Ubuntu:$apt-getinstalllibcffi-devpython-devgccOn CentOS/Fedora:$yuminstalllibcffi-develpython-develgccredhat-rpm-configUsageModule version and its backend xxHash library version can be retrieved using\nthe module propertiesVERSIONANDXXHASH_VERSIONrespectively.>>>importxxhash_cffiasxxhash>>>xxhash.VERSION'1.0.1'>>>xxhash.XXHASH_VERSION'0.6.2'This module is hashlib-compliant, which means you can use it in the same way ashashlib.md5.update() \u2013 update the current digest with an additional stringdigest() \u2013 return the current digest valuehexdigest() \u2013 return the current digest as a string of hexadecimal digitsintdigest() \u2013 return the current digest as an integercopy() \u2013 return a copy of the current xxhash objectreset() \u2013 reset statemd5 digest returns bytes, but the original xxh32 and xxh64 C APIs return integers.\nWhile this module is made hashlib-compliant,intdigest()is also provided to\nget the integer digest.Constructors for hash algorithms provided by this module arexxh32()andxxh64().For example, to obtain the digest of the byte stringb'Nobody inspects the spammish repetition':>>>importxxhash_cffiasxxhash>>>x=xxhash.xxh32()>>>x.update(b'Nobody inspects')>>>x.update(b' the spammish repetition')>>>x.digest()b'\\xe2);/'>>>x.digest_size4>>>x.block_size16More condensed:>>>xxhash.xxh32(b'Nobody inspects the spammish repetition').hexdigest()'e2293b2f'>>>xxhash.xxh32(b'Nobody inspects the spammish repetition').digest()==x.digest()TrueAn optional seed (default is 0) can be used to alter the result predictably:>>>importxxhash_cffiasxxhash>>>xxhash.xxh64('xxhash').hexdigest()'32dd38952c4bc720'>>>xxhash.xxh64('xxhash',seed=20141025).hexdigest()'b559b98d844e0635'>>>x=xxhash.xxh64(seed=20141025)>>>x.update('xxhash')>>>x.hexdigest()'b559b98d844e0635'>>>x.intdigest()13067679811253438005Be careful that xxh32 takes an unsigned 32-bit integer as seed, while xxh64\ntakes an unsigned 64-bit integer. Although unsigned integer overflow is\ndefined behavior, it\u2019s better to not to let it happen:>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=0).hexdigest()'f7a35af8'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=2**32).hexdigest()'f7a35af8'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=1).hexdigest()'d8d4b4ba'>>>xxhash.xxh32('I want an unsigned 32-bit seed!',seed=2**32+1).hexdigest()'d8d4b4ba'>>>>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=0).hexdigest()'d4cb0a70a2b8c7c1'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=2**64).hexdigest()'d4cb0a70a2b8c7c1'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=1).hexdigest()'ce5087f12470d961'>>>xxhash.xxh64('I want an unsigned 64-bit seed!',seed=2**64+1).hexdigest()'ce5087f12470d961'digest()returns bytes of thebig-endianrepresentation of the integer\ndigest:>>>importxxhash_cffiasxxhash>>>h=xxhash.xxh64()>>>h.digest()b'\\xefF\\xdb7Q\\xd8\\xe9\\x99'>>>h.intdigest().to_bytes(8,'big')b'\\xefF\\xdb7Q\\xd8\\xe9\\x99'>>>h.hexdigest()'ef46db3751d8e999'>>>format(h.intdigest(),'016x')'ef46db3751d8e999'>>>h.intdigest()17241709254077376921>>>int(h.hexdigest(),16)17241709254077376921Besides xxh32/xxh64 mentioned above, oneshot functions are also provided.\nBy using oneshot functions we can avoid allocating XXH32/64_state on heap:xxh32_digest(bytes, seed=0)xxh32_intdigest(bytes, seed=0)xxh32_hexdigest(bytes, seed=0)xxh64_digest(bytes, seed=0)xxh64_intdigest(bytes, seed=0)xxh64_hexdigest(bytes, seed=0)>>>importxxhash_cffiasxxhash>>>xxhash.xxh64('a').digest()==xxhash.xxh64_digest('a')True>>>xxhash.xxh64('a').intdigest()==xxhash.xxh64_intdigest('a')True>>>xxhash.xxh64('a').hexdigest()==xxhash.xxh64_hexdigest('a')True>>>xxhash.xxh64_hexdigest('xxhash',seed=20141025)'b559b98d844e0635'>>>xxhash.xxh64_intdigest('xxhash',seed=20141025)13067679811253438005L>>>xxhash.xxh64_digest('xxhash',seed=20141025)'\\xb5Y\\xb9\\x8d\\x84N\\x065'CaveatsSEED OVERFLOWxxh32 takes an unsigned 32-bit integer as seed, and xxh64 takes\nan unsigned 64-bit integer as seed. Make sure that the seed is greater than\nor equal to0.DONT USE XXHASH IN HMACThough you can use xxhash as anHMAChash function, but it\u2019s\nhighly recommended not to.xxhash isNOTa cryptographic hash function, it is a\nnon-cryptographic hash algorithm aimed at speed and quality.\nDo not put xxhash in any position where cryptographic hash\nfunctions are required.Copyright and LicenseCopyright (c) 2014-2018 Yue Du -https://github.com/ifduyueLicensed underBSD 2-Clause Licensev1.3.0 2018-12-16Wheels are now built automaticallySplit CFFI variant into a separate packageifduyue/python-xxhash-cffi"} +{"package": "xxh-xxh", "pacakge-description": "You stuffed command shell with aliases, tools and colors but you lose it all when using ssh. The mission of xxh is to bring your favorite shell wherever you go through ssh without root access and system installations.If you like the idea of xxh click \u2b50 on the repo andtweet.Portable. Preparing portable shells and plugins occurs locally and then xxh uploads the result to the host. No installations or root access on the host required. Security and host environment a prime focus.Hermetic. Deleting~/.xxhdirectory from the remote host will make the remote environment function as if xxh was never there. By default your home is the.xxhdirectory and you canchoose the hermetic level of your xxh session.Careful. No blindfold copying config files from local to remote host. Following privacy and repeatability practices the best way is to fork the xxh plugin or shell example and pack your configs into it.Be open and fork-ready. Every xxh repo could be forked, customized and reused without waiting for a package management system, xxh release or any third party packages. Five shells are currently supported and more could be added by the community.Do more. The xxh packages are not only about shells. Any type of tool or code could be behind an entrypoint. If you want to runbrowshon the remote host, just put its portable version as an entrypoint in the xxh-shell.Chameleon. Switching the shells is as easy as possible and you don't have to be locked in to one shell. Choose your current shell based on the task you want to solve:xxh anyhost +s xonshfor a python environment, osquery for simple querying, fish for modern features or time-tested zsh and bash for speed.Installation methodsPyPi 3pip3installxxh-xxhpipx- good alternative to brew and pip, readcomparisonpipxinstallxxh-xxhConda-forgefeedstockcondaconfig--addchannelsconda-forge\ncondainstallxxh-xxhHomebrewbrewinstallxxhMacportssudoportinstallxxhLinux portable binarymkdir~/xxh&&cd~/xxh\nwgethttps://github.com/xxh/xxh/releases/download/0.8.7/xxh-portable-musl-alpine-Linux-x86_64.tar.gz\ntar-xzfxxh-portable-musl-alpine-Linux-x86_64.tar.gz\n./xxhLinuxAppImagemkdir~/xxh&&cd~/xxh\nwget-Oxxhhttps://github.com/xxh/xxh/releases/download/0.8.7/xxh-x86_64.AppImage\nchmod+xxxh&&./xxhTo run AppImage on Alpine Linuxinstallalpine-pkg-glibcwithlocaledef.ShellsCurrently supported OS for target host is Linux on x86_64.xxh-shellstatusxxh-pluginsseamlessdemoxonshstableautojump,[+]xxh.xshdemozshstableohmyzsh,p10k,[+]xxh.zshdemofishstableohmyfish,fisher,userconfig,[+]todobashstableohmybash,[+]xxh.bashdemoosquerybetafish-appimagealphaelvishalphaSearch xxh shell on GithuborBitbucketorcreate your shell entrypointto use another portable shell.Prerun pluginsPrerun pluginsallow you to bring any portable tools, dotfiles or aliases to xxh session before running shell.Pinned plugins:core(xxh-sudo, xxh-screen, xxh-tmux),dotfiles,docker,python,xxh,vim,zoxide,starship. There iscookiecutter template to create prerun plugin.UsageUsexxhinstead ofsshwhen connecting to Linux hosts without changing ssh arguments:xxh \nxxh [ssh arguments] [user@]host[:port] [xxh arguments]\nxxh local [xxh arguments]Common examples (usexxh --helpto get info about arguments):xxh anyhost# Connect to the hostxxh -i id_rsa -p 2222 anyhost# Using ssh arguments: port and keyxxh user@host +c et# Using EternalTerminal (https://github.com/MisterTea/EternalTerminal)xxh anyhost +s zsh +i# Set the shell and install it without yes/no questionxxh anyhost +s xonsh +hhh \"~\"# Set /home/user as home directory (read Q&A)xxh anyhost +s bash +I xxh-plugin-bash-vim# Preinstall a pluginxxh anyhost +if +q# Force reinstall xxh on the host in quiet modexxh anyhost +hh /tmp/xxh +hhr# Upload xxh to /tmp/xxh and remove when disconnectingsource xxh.zsh anyhost +I xxh-plugin-zsh-ohmyzsh# Connect in seamless mode with ohmyzsh pluginxxh local +s xonsh# Experimental: build xxh environment inplace and without sshFor reusing arguments and simplifying xxh usage (like shortening toxxh anyhost) there is aconfig file.Why the plus sign for the xxh arguments?The xxh is using the plus sign for the xxh arguments to save the ability to use the minus sign for the original ssh arguments. This allows just replace the first two letters in thesshcommand to convert it to thexxhcommand. Also see thediscussion.Installing xxh packagesxxh[+Ixxh-package+I...][+L][+RIxxh-package+RI...][+Rxxh-package+R...]Different ways to set the xxh package source:xxh +I xxh-shell-example# install from https://github.com/xxhxxh +I https://github.com/xxh/xxh-shell-example# short url for github only, for other sources use examples below or add supportxxh +I https://github.com/xxh/xxh-shell-example/tree/mybranch# short url for github only, for other sources use examples below or add supportxxh +I xxh-shell-example+git+https://github.com/xxh/xxh-shell-example# long url for any git repoxxh +I xxh-shell-example+git+https://github.com/xxh/xxh-shell-example/tree/mybranch# github only branch supportxxh +I xxh-shell-example+git+git@github.com:githubuser/xxh-shell-example.git# install from private repository using sshxxh +I xxh-shell-example+path+/home/user/my-xxh-dev/xxh-shell-example# install from local pathUsing xxh inplace without ssh connectionThis is experimental magic. Please read the text below twice.If you have shell access on the host or you're in a docker container and you can't ssh to it\nthen you can download and build hermetic xxh environment inplace. Thexxh localcommand works\nexactly likexxh remote_hostand creates a hermetic environment in~/.xxhby default.At this time we don't have portable build tools likegit,wget,curl,tarand others which\ncould be required by some xxh package build scripts. When runningxxh localit is expected that the tools are present on the host.To run xxh inplace on Linux x86_64 just copy and paste these bash commands:XH=~/.xxh\\&&XD=https://github.com/xxh/xxh-portable/raw/master/result/xxh-portable-musl-alpine-Linux-x86_64.tar.gz\\&&mkdir-p$XH&&cd$XH\\&&([[-x$(command-vcurl)]]&&curl-L$XD||wget-O-$XD)|tarzxf-xxh\\&&echo'Usage: ./xxh local [+s xonsh/zsh/fish/osquery/bash]'Next time you're on host just run~/.xxh/xxh localand you will enter your xxh environment.Examples of use casesPython with pip everywhere without installationWay 1. Using xonshxxh anyhost +s xonsh\n\nanyhost> python --version\nPython 3.8.2You'll get python-poweredxonshshell with portable python and pip on the host without any system installations on the host.\nYou can install PyPi packages manually or bring them with you automatically by usingxxh-plugin-prerun-dotfiles. Also don't forget about xxh-plugins likezoxide.Way 2. Using portable python on any xxh shellxxh +RI xxh-plugin-prerun-python\nxxh anyhost +s zsh\n\nanyhost> python --version\nPython 3.8.2\nanyhost> pip install pandasUsingxxh-plugin-prerun-pythonyou'll get a portable\nPython AppImage which can be used on a host without python and with any xxh shell.Using docker on host without root accessTryxxh-plugin-prerun-docker:xxh +RI xxh-plugin-prerun-docker\nxxh anyhost +if\n\nanyhost> xxh-docker-run\nanyhost> docker ps \nCONTAINER ID IMAGE COMMAND\nanyhost> docker run --rm hello-world | grep Hello\nHello from Docker!\nanyhost> xxh-docker-stopBring dotfiles to xxh sessionThere is thexxh-plugin-prerun-dotfilesplugin which creates config files\nwhen you go to the host using xxh. You can fork it and create your cozy settings once and forever.Seamless Oh My Zsh (demo)sourcexxh.zshanyhost+Ixxh-plugin-zsh-ohmyzsh+if+qThis command brings your current Oh My Zsh session theme to the xxh session. If you need more complex settings just fork\nthexxh-plugin-zsh-ohmyzshand hack it.Read host as a table withosquery$ xxh anyhost +s osquery\nosquery> SELECT * FROM users WHERE username='news';\n+-----+-----+----------+-------------+-----------------+-------------------+\n| uid | gid | username | description | directory | shell |\n+-----+-----+----------+-------------+-----------------+-------------------+\n| 9 | 9 | news | news | /var/spool/news | /usr/sbin/nologin |\n+-----+-----+----------+-------------+-----------------+-------------------+All in one portable homexxh is very agile. You can create your ownxxh-shell(the shell part means it has an entrypoint) which can have any portable tools\nthat could help you on the host.Bashxxh-shell is one of these\nplatforms that could be forked and stuffed.Questions and answersWelcome to xxh familyHow it worksSimple answerDetailed workflow with codePluginsConnection speedSeamless modeConfig filePackages for xxhInstall shells and pluginsAdvancedHow to set /home/user as home on hostUsing sudoUsing xxh in xxh sessionTarget host is behind another hostEnvironment variablesDevelopment and contributionThe easiest way to debug shell and pluginsPrerun pluginsChange plugin run orderNew questionsDevelopmentxxh Development EnvironmentIn thexxh development environmentthere is fulldockerisedenvironment\nfor development, testing and contribution. The process of testing and development is orchestrated byxdetool and is as\neasy as possible.Vagrant based Plugin DevelopmentTo develop plugins,Vagrantsupports startingmany configurationsof virtual machines using Virtualbox.Seethe Plugin Development folderfor more detailsWe have teamsIf you're in a team it does not mean you have an obligation to do something. The main goal of teams is to create groups\nof passionate people who could help or support solving complex problems. Some people could be an expert in one shell and a\nnewbie in another shell and mutual assistance is the key to xxh evolution.Ask join.Thanksniessfor greatpython-appimageprobonopdandTheAssassinfor hard-workingAppImageAnthony Scopatz,Gil Forsyth,Jamie Bliss,David Strobach,Morten Enemark Lundand@xorefor amazingxonsh shellRoman Perepelitsafor incrediblestatically-linked, hermetic, relocatable ZshJohannes AltmanningerandFabian Homborgfor extensive and portablefish shell"} +{"package": "xxj-nameko-dependency", "pacakge-description": "\u85aa\u884c\u5bb6\u4ee3\u4ed8nameko dependencyinstallpipinstallxxj-nameko-dependencyconfig\u901a\u8fc7yaml\u6587\u4ef6\u65b9\u5f0f\u914d\u7f6enameko\u73af\u5883\u53d8\u91cfXXJ:\n MCHNT_NUM: ${XXJ_MCHNT_NUM}\n API_BASE_URL: ${XXJ_API_BASE_URL}\n DES_KEY: ${XXJ_DES_KEY}\n PUBLIC_KEY: ${XXJ_PUBLIC_KEY}\n PRIVATE_KEY: ${XXJ_PRIVATE_KEY}How to use?fromxxjimportXXJclassTestService(Base):xxj=XXJ()@rpcdefcreate_package(self,data):returnself.xxj.call(\"remit/createpackage\",data)"} +{"package": "xxkcd", "pacakge-description": "An (unofficial) Python wrapper around xkcd APIsPython 2 and 3 compatible. Requires an internet connection.ExamplesFor full usage, see thewiki.>>>fromxxkcdimportxkcd,WhatIf>>>x=xkcd(353)>>>xxkcd(353)>>>print(x.transcript)[[Guy1istalkingtoGuy2,whoisfloatinginthesky]]Guy1:You're flying! How?Guy2:Python!Guy2:Ilearneditlastnight!Everythingissosimple!Guy2:Helloworldisjust'print \"Hello, World!\" 'Guy1:Idunno...Dynamictyping?Whitespace?Guy2:Comejoinus!Programmingisfunagain!It's a whole new world up here!Guy1:Buthowareyouflying?Guy2:Ijusttyped'import antigravity'Guy1:That's it?Guy2:...Ialsosampledeverythinginthemedicinecabinetforcomparison.Guy2:Butithinkthisisthepython.{{Iwrote20shortprogramsinPythonyesterday.Itwaswonderful.Perl,I'm leaving you. }}>>>print(x.title)Python>>>print(x.alt)Iwrote20shortprogramsinPythonyesterday.Itwaswonderful.Perl,I'm leaving you.>>>what_if=WhatIf(1)>>>print(what_if.title)RelativisticBaseball>>>print(what_if.question)Whatwouldhappenifyoutriedtohitabaseballpitchedat90%thespeedoflight?>>>print(what_if.attribute)-EllenMcManisfromxxkcdimportxkcd,WhatIf# Get random comicxkcd.random()# Get number of latest comicxkcd.latest()# Get random What If? articleWhatIf.random()# Get number of latest What If? articleWhatIf.latest()InstallingFromPyPI$pipinstallxxkcdFrom source$gitclone'https://github.com/MitalAshok/xxkcd.git'$python./xxkcd/setup.pyinstall"} +{"package": "xxl", "pacakge-description": "No description available on PyPI."} +{"package": "xxl-admin-sh", "pacakge-description": "xxl-admin-sh\u5b89\u88c5\u8981\u6c42python>=3.9pipinstallxxl-admin-sh\u5b89\u88c5\u6210\u529f\u540e\u53ef\u76f4\u63a5\u7528xxl\u8fdb\u5165\u7a0b\u5e8fxxl\u7528\u6cd5\u9996\u6b21\u4f7f\u7528\u4f1a\u4f7f\u7528\u9ed8\u8ba4\u914d\u7f6e\uff0c\u9000\u51fa\u540e\u4f1a\u81ea\u52a8\u4fdd\u5b58\u5230\u914d\u7f6e\u6587\u4ef6\u5e2e\u52a9\u547d\u4ee4help# \u53ef\u663e\u793a\u6240\u6709\u53ef\u7528\u547d\u4ee4# \u6b64\u5916\u4efb\u610f\u547d\u4ee4\u3001\u5b50\u547d\u4ee4\u53ef\u901a\u8fc7-h\u9009\u9879\u663e\u793a\u5e2e\u52a9\u4fe1\u606f\uff0c\u6bd4\u5982job-h\ngroup-h\u914d\u7f6e\u547d\u4ee4configenv-set#\u8bbe\u7f6e\u73af\u5883\u914d\u7f6econfiglist-clusters#\u5f53\u524d\u73af\u5883\u53ef\u7528\u96c6\u7fa4\u5217\u8868configadd-cluster#\u6dfb\u52a0\u96c6\u7fa4\u5230\u5f53\u524d\u73af\u5883configremove-cluster#\u4ece\u5f53\u524d\u73af\u5883\u79fb\u9664\u96c6\u7fa4\u5207\u6362\u547d\u4ee4gotoprod#\u53ef\u5207\u73af\u5883gotoprodcn#\u53ef\u5207\u73af\u5883+\u96c6\u7fa4gotocn#\u53ef\u5728\u5f53\u524d\u73af\u5883\u5207\u96c6\u7fa4\u53ef\u663e\u793a\u6240\u6709\u53ef\u7528\u547d\u4ee4\u6267\u884c\u5668\u5217\u8868grouplist\ngrouplist-a#\u663e\u793a\u6240\u6709\u96c6\u7fa4\u4e0b\u9762\u7684\u4efb\u52a1\u5217\u8868joblist\njoblistxxx#\u6a21\u7cca\u641c\u7d22joblistxxx-a#\u6a21\u7cca\u641c\u7d22\u6240\u6709\u96c6\u7fa4\u4e0b\u9762\u7684joblistDemoJobHanlder#\u7cbe\u786e\u641c\u7d22\u4efb\u52a1\u6267\u884cjobrunDemoJobHanlder\njobrunDemoJobHanlder-a#\u6240\u6709\u96c6\u7fa4\u90fd\u6267\u884cjobdebugDemoJobHanlder# \u81ea\u52a8\u4f7f\u7528\u672c\u5730\u5730\u5740\u89e6\u53d1\u65b0\u589e\u4efb\u52a1jobadd--execDemoJobHanlder--group10--cron\"0 0 0 * * \uff1f\"--title\u793a\u4f8b\u4efb\u52a12\u66f4\u65b0\u4efb\u52a1jobupdateDemoJobHanlder--cron\"0 0 10 * * \uff1f\"--title\u793a\u4f8b\u4efb\u52a12\u5f00\u542f\u3001\u505c\u6b62\u4efb\u52a1jobonDemoJobHanlder#\u5f00\u542fjoboffDemoJobHanlder#\u505c\u6b62"} +{"package": "xxlGsc", "pacakge-description": "#xxlGSC\n\u8fd9\u4e2a\u6a21\u5757\u8001\u725b\u62dc\u4e86\uff0c\u661f\u5bbf\u8001\u4ed9\uff0c\u6cd5\u529b\u65e0\u8fb9"} +{"package": "xxlib", "pacakge-description": "No description available on PyPI."} +{"package": "xx-mail", "pacakge-description": "welcome to my package"} +{"package": "xxmind", "pacakge-description": "** xxmind \u65b0\u7248\u672c\u5df2\u7ecf\u51fa\u6765\u4e86\nxxmind\u662f\u5c06xmind\u56fa\u5b9a\u683c\u5f0f\u8f6c\u4e3axls\u7684\u8f6c\u6362\u5de5\u5177\u3002\u4f7f\u7528\u8bf4\u660e\uff1a\n1\uff09 \u5b89\u88c5\uff1a\npip install xxmind\n2\uff09 \u6267\u884c\nPython -c \"from xxmind.main import Main; Main()\"\n3\uff09 \u6309\u6a21\u677fxmind\u683c\u5f0f\u8981\u6c42\uff0c\u7f16\u5199\u7528\u4f8b\n4\uff09 \u8fd0\u884c\u5de5\u5177\uff0c\u628axmind\u8f6c\u5316\u4e3axls\u3001xlsx\u683c\u5f0f\u7684\u6587\u4ef6\u6ce8\uff1a \u4e3a\u65b9\u4fbf\u540e\u671f\u64cd\u4f5c\u65b9\u4fbf\u53ef\u4ee5 \u628a\u4e0a\u9762\u7684 \u8fd0\u884c\u547d\u4ee4\u653e\u5230bat\u6216shell\u6587\u4ef6\u4e2d\uff0c\u4e0b\u6b21\u76f4\u63a5\u53cc\u51fb\u8fd0\u884c#######################################################################\nLast update time: 2018-11-13\nBy\uff1a 8034.com#######################################################################\n0.3.5 \u4fee\u6539\u4e86\u6a21\u677f\n0.4.0 \u652f\u6301\u4e86python3.7#######################################################################\u6253\u5305 \u68c0\u67e5python setup.py check\u6253\u5305 \u751f\u6210python setup.py sdist\u4e0a\u4f20twine upload dist/*\u4f7f\u7528pip install xxmind\u66f4\u65b0pip install --upgrade xxmind\u5378\u8f7dpip uninstall -y xxmind\n#######################################################################MANIFEST.ininclude pat1 pat2 ... #include all files matching any of the listed patterns\nexclude pat1 pat2 ... #exclude all files matching any of the listed patterns\nrecursive-include dir pat1 pat2 ... #include all files under dir matching any of the listed patterns\nrecursive-exclude dir pat1 pat2 ... #exclude all files under dir matching any of the listed patterns\nglobal-include pat1 pat2 ... #include all files anywhere in the source tree matching \u2014 & any of the listed patterns\nglobal-exclude pat1 pat2 ... #exclude all files anywhere in the source tree matching \u2014 & any of the listed patterns\nprune dir #exclude all files under dir\ngraft dir #include all files under dir"} +{"package": "x-xmlparse", "pacakge-description": "No description available on PyPI."} +{"package": "xxn", "pacakge-description": "No description available on PyPI."} +{"package": "xx-ner-demo", "pacakge-description": "Feature | Description |\u2014 | \u2014 |Name|xx_ner_demo|Version|0.0.0|spaCy|>=3.2.2,<3.3.0|Default Pipeline|tok2vec,ner|Components|tok2vec,ner|Vectors| 0 keys, 0 unique vectors (0 dimensions) |Sources| n/a |License| n/a |Author| [n/a]() |### Label Scheme
          View label scheme (15 labels for 1 components)Component | Labels |\u2014 | \u2014 |`ner`|CARDINAL,DATE,GPE,LANGUAGE,LAW,LOC,MONEY,NORP,ORDINAL,ORG,PERCENT,PERSON,PRODUCT,QUANTITY,TIME|
          ### AccuracyType | Score |\u2014 | \u2014 |ENTS_F| 0.00 |ENTS_P| 0.00 |ENTS_R| 0.00 |TOK2VEC_LOSS| 1600.17 |NER_LOSS| 1439.14 |"} +{"package": "xxnlp", "pacakge-description": "XNLP\u9996\u5148\u662fdocument embedding: \u600e\u4e48\u628a\u539f\u59cb\u7684\u4e00\u4e2a\u6bb5\u843d/\u63a8\u6587\u7ed9\u8f6c\u6362\u6210\u4e00\u4e2aembedding, \u8fd9\u91cc\u6709\u5f88\u591a\u7684Embedding\u6a21\u578b(bert,xlnet,)\u548csentence-embedding\u6a21\u578b\u5728\u5f97\u5230\u4e86\u6bb5\u843d\u7684embedding\u57fa\u7840\u4e0a, \u4e0b\u4e00\u6b65\u662f\u600e\u4e48\u628a\u4fe1\u606f\u7ed9\u6574\u5408\u8d77\u6765, \u8fd9\u91cc\u53ef\u4ee5\u7528attn+lstm\u6216\u8005transformer"} +{"package": "xxp", "pacakge-description": "xxpWhatIt'sxxd(C source), but in Python, so it can also provide an API. Helpful when trying to reverse engineer binary things.WhyPart created for a want of a Python binary-dumper to decode my LoRa messages, part to learn GitHub Actions."} +{"package": "xx-package", "pacakge-description": "No description available on PyPI."} +{"package": "xxpaper", "pacakge-description": "Tools for generating printable files of shares, privates, trains etc for 18xx and like games."} +{"package": "xxprogram", "pacakge-description": "xxprogram\u8fd9\u662f\u4e00\u4e2a\u968f\u673a\u540d\u79f0\u751f\u6210\u5668\uff0c\u4f7f\u7528\u7a0b\u5e8f\u5458\u76f8\u5173\u7684\u6897\uff0c\u53ef\u7528\u4e8e\u751f\u6210\u82e5\u5e72\u7528\u6237\u540d\uff08\u6709\u91cd\u590d\u53ef\u80fd\uff09\uff0ceg:IN[1]: import XXProgram as P\n P.Python.faker(k=3)\nOUT[1]: ['\u81ea\u5e26\u6e38\u6807\u5361\u5c3a\u7684Python\u7a0b\u5e8f\u5458', \n '\u4e0d\u4f1a\u4fee\u7535\u8111\u7684Python\u7a0b\u5e8f\u5458', \n 'import \u522b\u4eba\u7684\u7a0b\u5e8f\u7684Python\u7a0b\u5e8f\u5458']\nIN[2]: P.faker(k=3)\nOUT[2]: ['0 Error 0 Warning\u7684\u7a0b\u5e8f\u5458',\n 'IT\u754c\u9996\u5c48\u4e00\u6307\u7684\u7684C++\u7a0b\u5e8f\u5458',\n '\u4e0d\u5199\u6587\u6863\u7684Shell\u7a0b\u5e8f\u5458']\u5b89\u88c5pip install xxprogram\u6216cd xxprogram\npython setup.py install"} +{"package": "xxradd", "pacakge-description": "xx"} +{"package": "xx-rest-framework", "pacakge-description": "No description available on PyPI."} +{"package": "xxsearchlib", "pacakge-description": "No description available on PyPI."} +{"package": "xx-swahili-spacy", "pacakge-description": "Feature | Description |\u2014 | \u2014 |Name|xx_swahili_spacy|Version|0.0.1|spaCy|>=3.2.2,<3.3.0|Default Pipeline|tok2vec,ner|Components|tok2vec,ner|Vectors| 0 keys, 0 unique vectors (0 dimensions) |Sources| n/a |License| n/a |Author| [n/a]() |### Label Scheme
          View label scheme (15 labels for 1 components)Component | Labels |\u2014 | \u2014 |`ner`|CARDINAL,DATE,GPE,LANGUAGE,LAW,LOC,MONEY,NORP,ORDINAL,ORG,PERCENT,PERSON,PRODUCT,QUANTITY,TIME|
          ### AccuracyType | Score |\u2014 | \u2014 |ENTS_F| 0.00 |ENTS_P| 0.00 |ENTS_R| 0.00 |TOK2VEC_LOSS| 1213.70 |NER_LOSS| 642.62 |"} +{"package": "xxt", "pacakge-description": "XXTXXT is a multifunctional Python library designed to enhance various aspects of programming by providing an extensive set of functions and classes related to time, numbers, and randomization.Additional classes for using the chat and image API of OpenAI included (need your own OpenAPI token)UsesWait functionClear functionFunctions to get time and dateClasses for a chatbot, imagebot, numbers and random choicesInstallationpip install xxtChangelog0.0.1 (17/7/2023)First Release0.0.2 (22/07/2023)Better DocumentationChangelog0.0.3 (22/07/2023)Chatbot Class0.0.4 (26/07/2023)Imagebot ClassBetter Documentation (website)0.0.5 (26/07/2023)QR Code Generator"} +{"package": "xxtea", "pacakge-description": "XXTEAimplemented as a Python extension module, licensed under 2-clause BSD.TheXXTEAalgorithm takes a 128-bit key and operates on an array of 32-bit\nintegers (at least 2 integers), but it doesn\u2019t define the conversions between\nbytes and array. Due to this reason, many XXTEA implementations out there are\nnot compatible with each other.In this implementation, the conversions between bytes and array are\ntaken care of bylongs2bytesandbytes2longs.PKCS#7padding is also used\nto make sure that the input bytes are padded to multiple of 4-byte (the size\nof a 32-bit integer) and at least 8-byte long (the size of two 32-bit integer,\nwhich is required by theXXTEAalgorithm). As a result of these measures,\nyou can encrypt not only texts, but also any binary bytes of any length.Installation$ pip install xxtea -UUsageThis module provides four functions:encrypt(),decrypt(),encrypt_hex(), anddecrypt_hex().>>>importos>>>importxxtea>>>importbinascii>>>>>>key=os.urandom(16)# Key must be a 16-byte string.>>>s=b\"xxtea is good\">>>>>>enc=xxtea.encrypt(s,key)>>>dec=xxtea.decrypt(enc,key)>>>s==decTrue>>>>>>hexenc=xxtea.encrypt_hex(s,key)>>>hexencb'7ad85672d770fb5cf636c49d57e732ae'>>>s==xxtea.decrypt_hex(hexenc,key)True>>>>>>binascii.hexlify(enc)==hexencTrueencrypt_hex()anddecrypt_hex()operate on ciphertext in a hexadecimal\nrepresentation. They are exactly equivalent to:>>>hexenc=binascii.hexlify(xxtea.encrypt(s,key))>>>s==xxtea.decrypt(binascii.unhexlify(hexenc),key)TruePaddingPadding is enabled by default, in this case you can encode any bytes of any length.>>>xxtea.encrypt_hex('',key)b'd63256eb59134f1f'>>>xxtea.decrypt_hex(_,key)b''>>>xxtea.encrypt_hex(' ',key)b'97009bd24074a7a5'>>>xxtea.decrypt_hex(_,key)b' 'You can disable padding by setting padding parameter toFalse.\nIn this case data will not be padded, so data length must be a multiple of 4 bytes and must not be less than 8 bytes.\nOtherwiseValueErrorwill be raised:>>>xxtea.encrypt_hex('',key,padding=False)ValueError:Datalengthmustbeamultipleof4bytesandmustnotbelessthan8bytes>>>xxtea.encrypt_hex('xxtea is good',key,padding=False)ValueError:Datalengthmustbeamultipleof4bytesandmustnotbelessthan8bytes>>>xxtea.encrypt_hex('12345678',key,padding=False)b'64f4e969ba90d386'>>>xxtea.decrypt_hex(_,key,padding=False)b'12345678'RoundsBy default xxtea manipulates the input data for6 + 52 / nrounds,\nwhere n denotes how many 32-bit integers the input data can fit in.\nWe can change this by settingroundsparameter.Do note that the more rounds it is, the more time will be consumed.>>>importxxtea>>>importstring>>>data=string.digits>>>key=string.ascii_letters[:16]>>>xxtea.encrypt_hex(data,key)b'5b80b08a5d1923e4cd992dd5'>>>6+52//((len(data)+(4-1))//4)# 4 means 4 bytes, size of a 32-bit integer23>>>xxtea.encrypt_hex(data,key,rounds=23)b'5b80b08a5d1923e4cd992dd5'>>>xxtea.encrypt_hex(data,key,rounds=1024)b'1577bbf28c43ced93bd50720'Catching ExceptionsWhen callingdecrypt()anddecrypt_hex(), it is possible that aValueErroror aTypeErroris raised:>>>from__future__importprint_function>>>importxxtea>>>>>>deftry_catch(func,*args,**kwargs):...try:...func(*args,**kwargs)...exceptExceptionase:...print(e.__class__.__name__,':',e).........>>>try_catch(xxtea.decrypt,'',key='')ValueError:Needa16-bytekey.>>>try_catch(xxtea.decrypt,'',key=' '*16)ValueError:Invaliddata,datalengthisnotamultipleof4,orlessthan8.>>>try_catch(xxtea.decrypt,' '*8,key=' '*16)ValueError:Invaliddata,illegalPKCS#7 padding. Could be using a wrong key.>>>try_catch(xxtea.decrypt_hex,' '*8,key=' '*16)TypeError:Non-hexadecimaldigitfound>>>try_catch(xxtea.decrypt_hex,'abc',key=' '*16)TypeError:Odd-lengthstring>>>try_catch(xxtea.decrypt_hex,'abcd',key=' '*16)ValueError:Invaliddata,datalengthisnotamultipleof4,orlessthan8."} +{"package": "xxtea-py", "pacakge-description": "IntroductionXXTEA is a fast and secure encryption algorithm. This is a XXTEA library for Python.It is based on CFFI, so it is fast and support both cpython and pypy.It is different from the original XXTEA encryption algorithm. It encrypts and decrypts raw binary data instead of 32bit integer array, and the key is also the raw binary data.Installationpip install xxtea-pyUsagePython2:importxxteatext=\"Hello World! \u4f60\u597d\uff0c\u4e2d\u56fd\uff01\"key=\"1234567890\"encrypt_data=xxtea.encrypt(text,key)decrypt_data=xxtea.decrypt(encrypt_data,key)print(text==decrypt_data);Python3:importxxteatext=\"Hello World! \u4f60\u597d\uff0c\u4e2d\u56fd\uff01\"key=\"1234567890\"encrypt_data=xxtea.encrypt(text,key)decrypt_data=xxtea.decrypt_utf8(encrypt_data,key)print(text==decrypt_data);"} +{"package": "xxtest", "pacakge-description": "LMQLA programming language for large language models.Documentation \u00bbExplore Examples\u00b7Playground IDE\u00b7Report BugLMQL is an open source programming language for large language models (LLMs) based on asuperset of Python. LMQL goes beyond traditional templating languages by providing full Python support, yet a lightweight programming interface.LMQL is designed to make working with language models like OpenAI, \ud83e\udd17 Transformers more efficient and powerful through its advanced functionality, including multi-variable templates, conditional distributions, constraints, datatype constraints and control flow.Features:Python Syntax: Write your queries usingfamiliar Python syntax, fully integrated with your Python environment (classes, variable captures, etc.)Rich Control-Flow: LMQL offers full Python support, enabling powerfulcontrol flow and logicin your prompting logic.Advanced Decoding: Take advantage of advanced decoding techniques likebeam search, best_k, and more.Powerful Constraints Via Logit Masking: Applyconstraints to model output, e.g. to specify token length, character-level constraints, datatype and stopping phrases to get more control of model behavior.Optimizing Runtime:LMQL leverages speculative execution to enable faster inference, constraint short-circuiting, more efficient token use andtree-based caching.Sync and Async API: Execute hundreds of queries in parallel with LMQL'sasynchronous API, which enables cross-query batching.Multi-Model Support: Seamlessly use LMQL withOpenAI API, Azure OpenAI, and \ud83e\udd17 Transformers models.Extensive Applications: Use LMQL to implement advanced applications likeschema-safe JSON decoding,algorithmic prompting,interactive chat interfaces, andinline tool use.Library Integration: Easily employ LMQL in your existing stack leveragingLangChainorLlamaIndex.Flexible Tooling: Enjoy an interactive development experience withLMQL's Interactive Playground IDE, andVisual Studio Code Extension.Output Streaming: Stream model output easily viaWebSocket, REST endpoint, or Server-Sent Event streaming.Explore LMQLA simple example program in LMQL looks like this:argmax\"Greet LMQL:[GREETINGS]\\n\"if\"Hi there\"inGREETINGS:\"Can you reformulate your greeting in the speech of victorian-era English: [VIC_GREETINGS]\\n\"\"Analyse what part of this response makes it typically victorian:\\n\"foriinrange(4):\"-[THOUGHT]\\n\"\"To summarize:[SUMMARY]\"from\"openai/text-davinci-003\"wherestops_at(GREETINGS,\".\")andnot\"\\n\"inGREETINGSandstops_at(VIC_GREETINGS,\".\")andstops_at(THOUGHT,\".\")Program Output:The main body of an LMQL program reads like standard Python (with control-flow), where top-level strings are interpreted as model input with template variables like[GREETINGS].Theargmaxkeyword in the beginning specifies the decoding algorithm used to generate tokens, e.g.argmax,sampleor\neven advanced branching decoders likebeam search andbest_k.Thefromandwhereclauses specify the model and constraints that are employed during decoding.Overall, this style of language model programming facilitates guidance of the model's reasoning process, and constraining\nof intermediate outputs using anexpressive constraint language.Learn more about LMQL by exploring ourExample Showcaseor by running your own programs in ourbrowser-based Playground IDE.Getting StartedTo install the latest version of LMQL run the following command with Python ==3.10 installed.pip install lmqlLocal GPU Support:If you want to run models on a local GPU, make sure to install LMQL in an environment with a GPU-enabled installation of PyTorch >= 1.11 (cf.https://pytorch.org/get-started/locally/) and install viapip install lmql[hf].Running LMQL ProgramsAfter installation, you can launch the LMQL playground IDE with the following command:lmql playgroundUsing the LMQL playground requires an installation of Node.js. If you are in a conda-managed environment you can install node.js viaconda install nodejs=14.20 -c conda-forge. Otherwise, please see the official Node.js websitehttps://nodejs.org/en/download/for instructions how to install it on your system.This launches a browser-based playground IDE, including a showcase of many exemplary LMQL programs. If the IDE does not launch automatically, go tohttp://localhost:3000.Alternatively,lmql runcan be used to execute local.lmqlfiles. Note that when using local HuggingFace Transformers models in the Playground IDE or vialmql run, you have to first launch an instance of the LMQL Inference API for the corresponding model via the commandlmql serve-model.Configuring OpenAI API CredentialsIf you want to use OpenAI models, you have to configure your API credentials. To do so, create a fileapi.envin the active working directory, with the following contents.openai-org: \nopenai-secret: For system-wide configuration, you can also create anapi.envfile at$HOME/.lmql/api.envor at the project root of your LMQL distribution (e.g.src/in a development copy).Installing the Latest Development VersionTo install the latest (bleeding-edge) version of LMQL, you can also run the following command:pip install git+https://github.com/eth-sri/lmqThis will install thelmqlpackage directly from themainbranch of this repository. We do not continously test themainversion, so it may be less stable than the latest PyPI release.Setting Up a Development EnvironmentTo setup acondaenvironment for local LMQL development with GPU support, run the following commands:# prepare conda environment\nconda env create -f scripts/conda/requirements.yml -n lmql\nconda activate lmql\n\n# registers the `lmql` command in the current shell\nsource scripts/activate-dev.shOperating System: The GPU-enabled version of LMQL was tested to work on Ubuntu 22.04 with CUDA 12.0 and Windows 10 via WSL2 and CUDA 11.7. The no-GPU version (see below) was tested to work on Ubuntu 22.04 and macOS 13.2 Ventura or Windows 10 via WSL2.Development without GPUThis section outlines how to setup an LMQL development environment without local GPU support. Note that LMQL without local GPU support only supports the use of API-integrated models likeopenai/text-davinci-003. Please see the OpenAI API documentation (https://platform.openai.com/docs/models/gpt-3-5) to learn more about the set of available models.To setup acondaenvironment for LMQL with no GPU support, run the following commands:# prepare conda environment\nconda env create -f scripts/conda/requirements-no-gpu.yml -n lmql-no-gpu\nconda activate lmql-no-gpu\n\n# registers the `lmql` command in the current shell\nsource scripts/activate-dev.sh"} +{"package": "xxtest0616", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xxtest0616v1", "pacakge-description": "LMQLA programming language for large language models.Documentation \u00bbExplore Examples\u00b7Playground IDE\u00b7Report BugLMQL is an open source programming language for large language models (LLMs) based on asuperset of Python. LMQL goes beyond traditional templating languages by providing full Python support, yet a lightweight programming interface.LMQL is designed to make working with language models like OpenAI, \ud83e\udd17 Transformers more efficient and powerful through its advanced functionality, including multi-variable templates, conditional distributions, constraints, datatype constraints and control flow.Features:Python Syntax: Write your queries usingfamiliar Python syntax, fully integrated with your Python environment (classes, variable captures, etc.)Rich Control-Flow: LMQL offers full Python support, enabling powerfulcontrol flow and logicin your prompting logic.Advanced Decoding: Take advantage of advanced decoding techniques likebeam search, best_k, and more.Powerful Constraints Via Logit Masking: Applyconstraints to model output, e.g. to specify token length, character-level constraints, datatype and stopping phrases to get more control of model behavior.Optimizing Runtime:LMQL leverages speculative execution to enable faster inference, constraint short-circuiting, more efficient token use andtree-based caching.Sync and Async API: Execute hundreds of queries in parallel with LMQL'sasynchronous API, which enables cross-query batching.Multi-Model Support: Seamlessly use LMQL withOpenAI API, Azure OpenAI, and \ud83e\udd17 Transformers models.Extensive Applications: Use LMQL to implement advanced applications likeschema-safe JSON decoding,algorithmic prompting,interactive chat interfaces, andinline tool use.Library Integration: Easily employ LMQL in your existing stack leveragingLangChainorLlamaIndex.Flexible Tooling: Enjoy an interactive development experience withLMQL's Interactive Playground IDE, andVisual Studio Code Extension.Output Streaming: Stream model output easily viaWebSocket, REST endpoint, or Server-Sent Event streaming.Explore LMQLA simple example program in LMQL looks like this:argmax\"Greet LMQL:[GREETINGS]\\n\"if\"Hi there\"inGREETINGS:\"Can you reformulate your greeting in the speech of victorian-era English: [VIC_GREETINGS]\\n\"\"Analyse what part of this response makes it typically victorian:\\n\"foriinrange(4):\"-[THOUGHT]\\n\"\"To summarize:[SUMMARY]\"from\"openai/text-davinci-003\"wherestops_at(GREETINGS,\".\")andnot\"\\n\"inGREETINGSandstops_at(VIC_GREETINGS,\".\")andstops_at(THOUGHT,\".\")Program Output:The main body of an LMQL program reads like standard Python (with control-flow), where top-level strings are interpreted as model input with template variables like[GREETINGS].Theargmaxkeyword in the beginning specifies the decoding algorithm used to generate tokens, e.g.argmax,sampleor\neven advanced branching decoders likebeam search andbest_k.Thefromandwhereclauses specify the model and constraints that are employed during decoding.Overall, this style of language model programming facilitates guidance of the model's reasoning process, and constraining\nof intermediate outputs using anexpressive constraint language.Learn more about LMQL by exploring ourExample Showcaseor by running your own programs in ourbrowser-based Playground IDE.Getting StartedTo install the latest version of LMQL run the following command with Python ==3.10 installed.pip install lmqlLocal GPU Support:If you want to run models on a local GPU, make sure to install LMQL in an environment with a GPU-enabled installation of PyTorch >= 1.11 (cf.https://pytorch.org/get-started/locally/) and install viapip install lmql[hf].Running LMQL ProgramsAfter installation, you can launch the LMQL playground IDE with the following command:lmql playgroundUsing the LMQL playground requires an installation of Node.js. If you are in a conda-managed environment you can install node.js viaconda install nodejs=14.20 -c conda-forge. Otherwise, please see the official Node.js websitehttps://nodejs.org/en/download/for instructions how to install it on your system.This launches a browser-based playground IDE, including a showcase of many exemplary LMQL programs. If the IDE does not launch automatically, go tohttp://localhost:3000.Alternatively,lmql runcan be used to execute local.lmqlfiles. Note that when using local HuggingFace Transformers models in the Playground IDE or vialmql run, you have to first launch an instance of the LMQL Inference API for the corresponding model via the commandlmql serve-model.Configuring OpenAI API CredentialsIf you want to use OpenAI models, you have to configure your API credentials. To do so, create a fileapi.envin the active working directory, with the following contents.openai-org: \nopenai-secret: For system-wide configuration, you can also create anapi.envfile at$HOME/.lmql/api.envor at the project root of your LMQL distribution (e.g.src/in a development copy).Installing the Latest Development VersionTo install the latest (bleeding-edge) version of LMQL, you can also run the following command:pip install git+https://github.com/eth-sri/lmqThis will install thelmqlpackage directly from themainbranch of this repository. We do not continously test themainversion, so it may be less stable than the latest PyPI release.Setting Up a Development EnvironmentTo setup acondaenvironment for local LMQL development with GPU support, run the following commands:# prepare conda environment\nconda env create -f scripts/conda/requirements.yml -n lmql\nconda activate lmql\n\n# registers the `lmql` command in the current shell\nsource scripts/activate-dev.shOperating System: The GPU-enabled version of LMQL was tested to work on Ubuntu 22.04 with CUDA 12.0 and Windows 10 via WSL2 and CUDA 11.7. The no-GPU version (see below) was tested to work on Ubuntu 22.04 and macOS 13.2 Ventura or Windows 10 via WSL2.Development without GPUThis section outlines how to setup an LMQL development environment without local GPU support. Note that LMQL without local GPU support only supports the use of API-integrated models likeopenai/text-davinci-003. Please see the OpenAI API documentation (https://platform.openai.com/docs/models/gpt-3-5) to learn more about the set of available models.To setup acondaenvironment for LMQL with no GPU support, run the following commands:# prepare conda environment\nconda env create -f scripts/conda/requirements-no-gpu.yml -n lmql-no-gpu\nconda activate lmql-no-gpu\n\n# registers the `lmql` command in the current shell\nsource scripts/activate-dev.sh"} +{"package": "xxtrace", "pacakge-description": "No description available on PyPI."} +{"package": "xxurl", "pacakge-description": "refer to .md files inhttps://github.com/ihgazni2/xxurl"} +{"package": "xx_wizard", "pacakge-description": "XX\u7cbe\u70751 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use the following command line to guide you to a specific python version, if you have multiple versions of python locallypython3.x-mpip3installxxxchatFeatures...RequirementsA terminal with Python and pip installed:Installed python environment and python version >= 3.9Installingpip3installxxxchatUninstallpip3uninstallxxxchatFeedback or questions...LicenseMIT"} +{"package": "xxxfree", "pacakge-description": "No description available on PyPI."} +{"package": "xxxjjj", "pacakge-description": "No description available on PyPI."} +{"package": "xxxreport", "pacakge-description": "xxxreportxxxreportis a tools to extract all TODO/XXX comments to generate one plain text or html summary document.xxxreportis inspired by Zope xxxreport tools (http://svn.zope.org/Zope3/trunk/utilities/).How to use :$ easy_install xxxreportExtract comments :$ xxxreport --title=WsgiDAV ~/my_python_projects/\n===================================\nTODO/XXX Comment report for WsgiDAV\n===================================\n\n\nGenerated on Sun, 01 Nov 2009 19:27:33 CET\n\nSummary\n=======\n\nThere are currently 3 TODO/XXX comments.\n\nListing\n=======\n\nFile : wsgidav/addons/virtual_dav_provider.py:220\n\n # TODO: this is just for demonstration:\n self.resourceData = _resourceData\n\n\n\nFile : wsgidav/addons/virtual_dav_provider.py:350\n\n# dict[\"etag\"] = util.getETag(file path), # TODO: should be using the file path here\n dict[\"contentType\"] = res.getContentType()\n dict[\"contentLength\"] = res.getContentLength()\n dict[\"supportRanges\"] = True\n\nFile : wsgidav/addons/mysql_dav_provider.py:335\n\n # TODO: calling exists() makes directory browsing VERY slow.\n # At least compared to PyFileServer, which simply used string\n # functions to get displayType and displayRemarks\n if not self.exists(path):More information :$ xxxreport --help0.1.3 (2009-11-06)FeaturesAdd--file-extensionoptionAdd--marker-prefixoption"} +{"package": "xxx.scraper", "pacakge-description": "1)algoritm - scrap all posts inline2)bin/scraper_worker3) go to 3 folderfrom imagehash import dhashfrom iso8601 import parse_datefrom PIL import Image as PIL_Imagecur_im1 = PIL_Image.open('/home/t/Desktop/videos/3/test.jpg')cur_hash1 = str(dhash(cur_im1))GO TO REDIS select 1set 2f2b0b2b33232323 \"380668111208\"4)import osimport redispath = '/home/t/Desktop/videos/images'two_dir = os.listdir(path)r = redis.StrictRedis(host=\"localhost\", port=6379, charset=\"utf-8\", decode_responses=True, db=0)keys = r.keys('*')redis_values_dict = dict()for key in keys:redis_values_dict[r.get(key)] = Nonecount = 0for image in two_dir:if image not in redis_values_dict:os.remove('{}{}{}'.format(path, '/', image ))count += 10.0---- Initial version"} +{"package": "xxx.server_api", "pacakge-description": "Getting Startedinstall latest nodejs by curl ->\nlook into ansibleneed nodejs to be installed lates is installed via curl\n#sudo apt-get install nodejs npm <\u2013 this installes bad nodejsnpm install # installs from package.json\nnpm run bundle # generates bundle.js filefor dev copy static to container\ndocker cp xxx/server_api/static/. 0efd75c2ae99:/xxx_server_api/static0.0Initial version"} +{"package": "xxxswf", "pacakge-description": "xxxswf.py is a Python script for carving, scanning, compressing, decompressing and analyzing Flash SWF files. The script can be used on an individual SWF, single SWF or multiple SWFs embedded in a file stream or all files in a directory. The tool could be useful for system administrators, incident response, exploit analyst, malware analyst or web developers."} +{"package": "xxxx", "pacakge-description": "Failed to fetch description. HTTP Status Code: 404"} +{"package": "xxxy-cli", "pacakge-description": "No description available on PyPI."} +{"package": "xxxy-test", "pacakge-description": "No description available on PyPI."} +{"package": "xxyy", "pacakge-description": "No description available on PyPI."} +{"package": "xxyy1", "pacakge-description": "No description available on PyPI."} +{"package": "xxyzfpackage", "pacakge-description": "No description available on PyPI."} +{"package": "xxzlib", "pacakge-description": "An feature extraction algorithm, improve the FastICA"} +{"package": "xy12beets", "pacakge-description": "No description available on PyPI."} +{"package": "xyaml", "pacakge-description": "UNKNOWN"} +{"package": "xyapi", "pacakge-description": "xyapibase fastapi"} +{"package": "xy-art", "pacakge-description": "trans the text to art text"} +{"package": "xybase", "pacakge-description": "xybaseutils commons"} +{"package": "xy-bot", "pacakge-description": "smart bot by jisu api"} +{"package": "xy-box", "pacakge-description": "xiaoyuan box"} +{"package": "xybpSdk", "pacakge-description": "No description available on PyPI."} +{"package": "xy-brain", "pacakge-description": "Get The brain test"} +{"package": "xy-carbrand", "pacakge-description": "Get All Cars Brand From juhe API"} +{"package": "xy-carlimit", "pacakge-description": "Get The Car Limit Number"} +{"package": "xyce", "pacakge-description": "Future location of Python enabled Xyce.In the meantime, check out Xyce-PyMi at:https://github.com/xyce/xycewith instruction details at:https://cfwebprod.sandia.gov/cfdocs/CompResearch/docs/Xyce-PyMi-Guide.pdfAbout Xyce:Xyce (rhymes with \"spice\") is an open source, SPICE-compatible, high-performance analog circuit simulator, capable of solving extremely large circuit problems by supporting large-scale parallel computing platforms. It also supports serial execution on all common desktop platforms, and small-scale parallel runs on Unix-like systems. In addition to analog electronic simulation, Xyce has also been used to investigate more general network systems, such as neural networks and power grids. In providing an Open Source version of Xyce to the external community, Sandia hopes to contribute a robust and modern electronic simulator to users and researchers in the field.While designed to be SPICE-compatible, Xyce is not a derivative of SPICE. Xyce was designed from scratch to be a parallel simulation code, written in C++ and using a message-passing implementation (MPI). Xyce also leverages Sandia's open-source solver library, Trilinos, which includes a number of circuit-specific solvers, such as the KLU direct solver. With its modular and flexible design, Xyce applies abstract interfaces to enable easy development of different analysis types, solvers and models.Xyce is compatible with SPICE-based codes, in that it supports a canonical set of SPICE compact models and standard SPICE analysis methods, such as steady-state (.DC), transient (.TRAN), small-signal frequency domain (.AC), and noise (.NOISE). However, Xyce goes beyond most SPICE-based codes in a number of ways, including support for a large number of non-traditional models, such as neuron and reaction network models. Xyce also supports Harmonic Balance analysis (.HB), random sampling analysis, sensitivity calculations, and post processing of the simulation metrics (.FOUR and .MEASURE)."} +{"package": "xycepymi", "pacakge-description": "Future location of Python enabled Xyce.In the meantime, check out Xyce-PyMi at:https://github.com/xyce/xycewith instruction details at:https://cfwebprod.sandia.gov/cfdocs/CompResearch/docs/Xyce-PyMi-Guide.pdfAbout Xyce:Xyce (rhymes with \"spice\") is an open source, SPICE-compatible, high-performance analog circuit simulator, capable of solving extremely large circuit problems by supporting large-scale parallel computing platforms. It also supports serial execution on all common desktop platforms, and small-scale parallel runs on Unix-like systems. In addition to analog electronic simulation, Xyce has also been used to investigate more general network systems, such as neural networks and power grids. In providing an Open Source version of Xyce to the external community, Sandia hopes to contribute a robust and modern electronic simulator to users and researchers in the field.While designed to be SPICE-compatible, Xyce is not a derivative of SPICE. Xyce was designed from scratch to be a parallel simulation code, written in C++ and using a message-passing implementation (MPI). Xyce also leverages Sandia's open-source solver library, Trilinos, which includes a number of circuit-specific solvers, such as the KLU direct solver. With its modular and flexible design, Xyce applies abstract interfaces to enable easy development of different analysis types, solvers and models.Xyce is compatible with SPICE-based codes, in that it supports a canonical set of SPICE compact models and standard SPICE analysis methods, such as steady-state (.DC), transient (.TRAN), small-signal frequency domain (.AC), and noise (.NOISE). However, Xyce goes beyond most SPICE-based codes in a number of ways, including support for a large number of non-traditional models, such as neuron and reaction network models. Xyce also supports Harmonic Balance analysis (.HB), random sampling analysis, sensitivity calculations, and post processing of the simulation metrics (.FOUR and .MEASURE)."} +{"package": "xychan", "pacakge-description": "xychan is a \u201cchan-style\u201d message board system like Wakaba, Kareha,\nFutaba, etc. Unlike these systems it\u2019s written in Python instead of a\nmess of Perl or PHP.[Actions speak louder than words. You can try it out here.](http://xychan-beta.mike.verdone.ca/)What is this, really?A \u201cchan board\u201d is a message board that allows for Anonymous\nposting. Users can post messages without registering for an account or\neven entering a name. However, there are means for them to\nauthenticate themselves and \u201cprove\u201d their identify if they so desire.Another focus is the ability of users to post images. One image can be\nincluded with every post. A thumbnail of the image appears with the\npost.Design Goalsxychan is designed to be:easily deployed on almosy any web server (via CGI, FastCGI, Passenger, or any WSGI runner)easily configured (uses SQLAlchemy to work with any database, from\nSQLite3 to MySQL, PostgreSQL, etc.)easily extended and customized with CSS or template modificationscalable (at least compared to those other message boards)small yet powerfulStatusThis is BETA quality software. It is not yet stable. It changes a lot.DownloadsThe latest stable version is v0.2The latest stable version in an easily deployable zip file: [v0.2](http://mike.verdone.ca/xychan/xychan.zip)The easiest way to get xychan if you are a Python pro:$ pip install xychanStable source packages are in the [GitHub files section](http://github.com/sixohsix/xychan/downloads)Bleeding edge source for developers is in the [GitHub repository](http://github.com/sixohsix/xychan)How do I run it? - the EASY way (cgi)Your web server needs Python 2.5Your web server needs ImageMagick to support images on the boardDownload the easily deployable zip file, aboveCopy it to your webserver in an empty directory that supports CGIUnzip itModify xychan.cgi in case there\u2019s anything you want to change thereModify htaccess and copy it to .htaccessAccess path/to/xychan.cgi/setup on your webserverHow do I run it? - the SMART wayYour web server needs Python 2.5Your web server needs ImageMagick to support images in the boardYour web server needs the following Python packages installed:\n* bottle\n* sqlalchemy\n* Some kind of database (eg. sqlite3)Untar the xychan codebaseIn your WSGI server:from xychan import app\napp.configure_db(\"postgres://user:password@host/dbname\")\n# (or some similar SQLAlchemy db url)\napp.configure_image_dir(\"/some/safe/path/in/your/filesystem\")Licensexychan is Free Software available under the GPL3 (GNU General Public\nLicense v3).Those wanting to make closed-source commercial forks should contact me.Why is it called xychan?Characters typed at random."} +{"package": "xy-cidian", "pacakge-description": "Get The cidian"} +{"package": "xy-cities", "pacakge-description": "Get ALL Citys"} +{"package": "xy-citys", "pacakge-description": "Get ALL Citys"} +{"package": "xy-cli", "pacakge-description": "xy-cliexiahuang/xy-cliis a xy command tools.installinstall from pippip3installxy-cliinstall from gitgitclonehttps://github.com/exiahuang/xy-cli\npython3setup.pyinstallgreen installxy_cli=`pwd`exportPYTHONPATH=\"$xy_cli:$PYTHONPATH\"python3-mxy_cliUsagexy clone -f from_directory -t to_directory -d DATA1=NewData1 DATA2=NewData2 DATA3=NewData3packagepython3setup.pysdist\npython3setup.pybdist_wininstpy2exe build windows exepy-3.4-mvenv.py34\n.py34\\Scripts\\activate.bat# python -m pip install --upgrade pippipinstallpy2exesetuptools\npipinstallrequestsXlsxWriter\npython-V\npythonsetup.pypy2exeAcknowledgementBasic on OpenSourcehistory2020/08/30 init project"} +{"package": "xycloud", "pacakge-description": "No description available on PyPI."} +{"package": "xycmap", "pacakge-description": "xycmapBivariate colormap solutions.This package makes it easy to create custom two-dimensional colormaps, apply them to your series, and add bivariate color legends to your plots.Installationpip install xycmapUsageMake a custom interpolated colormap by specifying four corner colors (see recognized formatshere), and dimensionsn:importxycmapcorner_colors=(\"lightgrey\",\"green\",\"blue\",\"red\")n=(5,5)# x, ycmap=xycmap.custom_xycmap(corner_colors=corner_colors,n=n)Or make a colormap by mixing two matplotlib colormaps, and specifying dimensionsn:importmatplotlib.pyplotaspltxcmap=plt.cm.rainbowycmap=plt.cm.Greysn=(5,5)# x, ycmap=xycmap.mean_xycmap(xcmap=xcmap,ycmap=ycmap,n=n)With that in place, apply the colormap to two series that are numeric or categorical:colors=xycmap.bivariate_color(sx=sx,sy=sy,cmap=cmap)Note that you can apply limits to the axes, as well as pass custom bins for the axes (if numerical). See the docstring for details.Then simply passcolorsto your plot. To add a legend, create a new ax and runbivariate_legend()into the ax with the same parameters asbivariate_color(), e.g.:cax=fig.add_axes([1,0.25,0.5,0.5])cax=xycmap.bivariate_legend(ax=cax,sx=sx,sy=sy,cmap=cmap)MetaRemco Bastiaan Jansen \u2013r.b.jansen.uu@gmail.com-https://github.com/rbjansenDistributed under the MIT license. SeeLICENSEfor more information."} +{"package": "xy-cnwords", "pacakge-description": "No description available on PyPI."} +{"package": "xyconvert", "pacakge-description": "xyconvertThis is a python package for converting xy coordinates (in lng,lat order) in numpy array between WGS-84, GCJ-02 and BD-09 system.The conversion in numpy is much more efficient (50-70 times speedup) compared with previous Python implementations such aseviltransformandcoordTransform_pythat convert only a single point at each call.Install the packagepipinstallxyconvertUsagefromxyconvertimportgcj2wgsimportnumpyasnpgcj_xy=np.asarray([[104.07008157,30.73199687],[104.07008159,30.73177709],[104.06999188,30.73147758]])wgs_xy=gcj2wgs(gcj_xy)printwgs_xy'''[[104.06756309 30.73437796][104.06756312 30.73415829][104.06747357 30.73385904]]'''ReferenceThe code is partly copied/modified fromhttps://github.com/Argons/nextlocationandhttps://github.com/wandergis/coordTransform_py."} +{"package": "xycrypto", "pacakge-description": "xycryptoInstallationRequire Python 3.6+.pipinstall-UxycryptoCiphersThexycryptoprovides simple and elegant interfaces for ciphers.The cryptography components for ciphers we support:Availablestream cipher:ChaCha20,RC4.Availableblock cipher:AES,Blowfish,Camellia,CAST5,DES,IDEA,SEED,TripleDES.Availablemode:ECB,CBC,CFB,OFB,CTR.Availablepadding:PKCS7,ANSIX923,ISO10126.UsageFirstly, you should import the cipher class from the packagexycrypto.ciphers. The cipher class follows the following naming conventions:Forstream cipher,.Forblock cipher,_.>>>fromxycrypto.ciphersimportAES_CBCSecondly, you should create the instance of the cipher class. In this case, you should provide some arguments:keyfor all ciphers.ivforblock cipherinECB,CBC,OFB,CFBmode.nonceforblock cipherinCTRmode.paddingforblock cipherinECB,CBCmode.# The len(key) is 16 bytes for AES-128, you can use 32 bytes key for AES-256.>>>key=b'0123456789abcdef'# Note len(iv) should be equal to AES_CBC.block_size.>>>iv=b'0123456789abcdef'# We use PKCS7 padding.>>>cipher=AES_CBC(key,iv=iv,padding='PKCS7')Finally, callencryptordecryptmethod to encrypt or decrypt data respectively.>>>plaintext=b'Welcome to xycrypto!'>>>ciphertext=cipher.encrypt(plaintext)>>>ciphertextb'3\\x0f\\xad\\xa6\\x17\\xc4}\\xb9\\t\\x17\\xf8\\xae\\xbb\\xa2t\\xb9o\\xf2\\xf6\\x16\\t\\x0803\\xaci\\x0c\\x19q\\x9d\\xa3O'>>>cipher.decrypt(ciphertext)b'Welcome to xycrypto!'Example>>>fromxycrypto.ciphersimportAES_CBC# The len(key) is 16 bytes for AES-128, you can use 32 bytes key for AES-256.>>>key=b'0123456789abcdef'# Note len(iv) should be equal to AES_CBC.block_size.>>>iv=b'0123456789abcdef'# We use PKCS7 padding.>>>cipher=AES_CBC(key,iv=iv,padding='PKCS7')>>>plaintext=b'Welcome to xycrypto!'>>>ciphertext=cipher.encrypt(plaintext)>>>ciphertextb'3\\x0f\\xad\\xa6\\x17\\xc4}\\xb9\\t\\x17\\xf8\\xae\\xbb\\xa2t\\xb9o\\xf2\\xf6\\x16\\t\\x0803\\xaci\\x0c\\x19q\\x9d\\xa3O'>>>cipher.decrypt(ciphertext)b'Welcome to xycrypto!'"} +{"package": "xyd-05", "pacakge-description": "Just a test.twine upload dist/*python setup.py sdist build"} +{"package": "xyd-05-2", "pacakge-description": "Just a test.twine upload dist/*python setup.py sdist build"} +{"package": "xyd.05.25", "pacakge-description": "Just a test.twine upload dist/*python setup.py sdist build"} +{"package": "xyd.05.26", "pacakge-description": "Just a test.twine upload dist/*python setup.py sdist build"} +{"package": "xy-descpic", "pacakge-description": "picture description"} +{"package": "xy-face", "pacakge-description": "Face Recognition,age,beauty,gender"} +{"package": "xy-faceage", "pacakge-description": "Face Age"} +{"package": "xy-face-cosmetic", "pacakge-description": "Face Cosmetic"} +{"package": "xy-face-decoration", "pacakge-description": "Face Decoration"} +{"package": "xy-facedetect", "pacakge-description": "Get The Face Detect"} +{"package": "xy-face-emotion", "pacakge-description": "Check The Face Emotion With Living Video"} +{"package": "xy-face-glass", "pacakge-description": "Auto Add Glass On Your Face"} +{"package": "xy-facemix", "pacakge-description": "Make The Face Mix More"} +{"package": "xy-face-ps", "pacakge-description": "Recognition The Face And Ps The Face"} +{"package": "xy-face-recognition", "pacakge-description": "Get The Face Recognition"} +{"package": "xy-face-sticker", "pacakge-description": "Face Sticker"} +{"package": "xyfigure", "pacakge-description": "Sandia Injury Biomechanics Laboratory (SIBL)PurposeThe Sandia Injury Biomechanics Laboratory analyzes injury due to blast, ballistics, and blunt trauma to help the nation protect the U.S. warfighter. Our contributions to the science of injury causation and prevention aim to significantly reduce the U.S. warfighter's exposure to serious, severe, and fatal injuries.For more information, see ourwebsite.LibraryxyfiguretpavPrerequisitesGitCondaWorkflow ChoiceThere are two workflows: Client and DeveloperClientDeveloper\"I just want to use the library, I don't want to develop the library.\"\"I want to use the library and develop the library.\"Follow theClient WorkflowFollow theDeveloper WorkflowClient WorkflowSetup with conda environmentSee theClient setupHistorical setup, with pip, now deprecatedInstall from a terminal:$pipinstallxyfigureIf your computer does not have a network connection, install the WHL file (a Python\npackage saved in Wheel format), which must can be obtained from Chad directly, or\nfromhere. Then$pipinstall--userxyfigure-0.0.n-py3-non-any.whl# where n is the version number$pipinstall--userxyfigure-0.0.5-py3-non-any.whl# version 5, for exampleVerify installation: check thatxyfigureis contained in the list generated by$piplistDeveloper WorkflowFor an overview,read the guidefrom GitHub.Get a local copy of the repository usinggit clonewith SSH$cd~# Starting from the home directory is optional, but recommended.$gitclonegit@github.com:sandialabs/sibl.gitDevelopment Cyclepull codeimplementunit test (active now, both local manual testing and automated testing on push to repository)Black code stylecoverage (to come)push code$(base)[~]$cd~/sibl\n$(base)[~/sibl]$condaactivatesiblenv\n$(siblenv)[~/sibl]$# development in python$(siblenv)[~/sibl]$python-munittest# unit tests must pass prior to push to repository$(siblenv)[~/sibl]$python-munittest-v# for more verbose unittest output$(siblenv)[~/sibl]blacksome_specific_file.py\n$(siblenv)[~/sibl]blacksome_folder/\n$(siblenv)[~/sibl]Push to repositoryIf you update the codebase, and wish to have the modifications merged into the main repository, you will need to eitherpush to the repositoryif you are a collaborator (information below), orcreate a pull requestif you have forked the repo (information to come).In the~/sibl/.git/configfile, add the following:[user]name=JamesBond# your first and last nameemail=jb007@company.com# your email addressConfigure ssh keys between your local and the repo. This assumes to you have an existing public key file in~/.ssh/id_rsa/id_rsa.pub. Seethisto create a public key. Seethisfor troubleshooting.Copy the entirepublickey to the GitHub site underSettings > SSH and GPG keys.From within the repo~/sibl/, set the username and email on aper-repobasis:$gitconfiguser.name\"James Bond\"# your first and last name in quotations$gitconfiguser.email\"jb007@company.com\"# your email address in quotationsContactChad B. Hovey, Sandia National Laboratories,chovey@sandia.govLicenseLicenseThird-Party NoticeSandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.CopyrightCopyright 2020 National Technology and Engineering Solutions of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights in this software.NoticeFor five (5) years from the United States Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable worldwide license in this data to reproduce, prepare derivative works, and perform publicly and display publicly, by or on behalf of the Government. There is provision for the possible extension of the term of this license. Subsequent to that period or any extension granted, the United States Government is granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable worldwide license in this data to reproduce, prepare derivative works, distribute copies to the public, perform publicly and display publicly, and to permit others to do so. The specific term of the license can be identified by inquiry made to National Technology and Engineering Solutions of Sandia, LLC or DOE.NEITHER THE UNITED STATES GOVERNMENT, NOR THE UNITED STATES DEPARTMENT OF ENERGY, NOR NATIONAL TECHNOLOGY AND ENGINEERING SOLUTIONS OF SANDIA, LLC, NOR ANY OF THEIR EMPLOYEES, MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY LEGAL RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR USEFULNESS OF ANY INFORMATION, APPARATUS, PRODUCT, OR PROCESS DISCLOSED, OR REPRESENTS THAT ITS USE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS.Any licensee of this software has the obligation and responsibility to abide by the applicable export control laws, regulations, and general prohibitions relating to the export of technical data. Failure to obtain an export control license or other authority from the Government may result in criminal liability under U.S. laws."} +{"package": "xyfny", "pacakge-description": "xyfny - a z-machine intepreterThis is based closely upon theinternetftw'sxyppy.Where that is geared towards an interactive simulation of a good ol'-fashioned Z-machine\nexperience, this is intended to be plugging into event-driven systems (for instance,\nchat systems like Slack).All of the terminal handling is stripped out. Rather, the z-machine runs until it attempts\nto read input from the user. At that point, it'll exit with an interrupt -unlessthere\nis user input pending in its buffer.The basic gist of how this might be used:# Initialise\nenv = make_env(file)\nintro = do_step(env, line)\n\n# Output the introductory text to the user\noutput(intro)\n\n# On receiving an input event from the user:\nresponse = do_step(env, event_text)\noutput(response)Referencesxyppy - infocom's z-machine in python"} +{"package": "xygen", "pacakge-description": "xygenA Python module that generates xy coordinates for various geometric shapes. Pronounced ex-ee-gen.InstallationTo install with pip, run:pip install xygenQuickstart GuideTODO - fill this in laterContributeIf you'd like to contribute to xygen, check outhttps://github.com/asweigart/xygen"} +{"package": "xy-headhat", "pacakge-description": "Auto Add Christmas Hat On Your Head"} +{"package": "xy-history", "pacakge-description": "Get The Today History"} +{"package": "xyhzxh", "pacakge-description": "No description available on PyPI."} +{"package": "xy-idcard", "pacakge-description": "idcard Recognition"} +{"package": "xy-idiom", "pacakge-description": "Get The idiom info"} +{"package": "xy-image", "pacakge-description": "Image Recognition"} +{"package": "xy-imageporn", "pacakge-description": "Image Porn Recognition"} +{"package": "xy-imganimal", "pacakge-description": "Recognition Image Animal"} +{"package": "xy-imgcar", "pacakge-description": "Recognition Image Car Brand"} +{"package": "xy-imgfilter", "pacakge-description": "Image Filter"} +{"package": "xy-imgflowers", "pacakge-description": "Recognition Image Flowers"} +{"package": "xy-imgfood", "pacakge-description": "Recognition Image Food"} +{"package": "xy-imgfuzzy", "pacakge-description": "Recognition Image Fuzzy"} +{"package": "xy-imgtag", "pacakge-description": "Recognition Image Tag"} +{"package": "xy-imgtranslate", "pacakge-description": "Image Translate"} +{"package": "xy-intention", "pacakge-description": "Intention Analyze"} +{"package": "xyj-database", "pacakge-description": "\u5f85\u66f4\u65b0\u8bf4\u660e"} +{"package": "xy-joke", "pacakge-description": "Get The Joke"} +{"package": "xyl1pdf", "pacakge-description": "This is the homepage of out project."} +{"package": "xylem", "pacakge-description": "Convert Python Abstract Syntax Trees (ASTs) to readable source code.Xylem is useful for when you want to make dynamic changes to Python code/ASTs, but also need to write those changes back as source code.It\u2019s also very small (<500 lines), pure-Python, and produces (mostly) readable source code.In writing this, I made heavy use of the unofficial AST documentation atGreen Tree Snakes.InstallationXylem will work on Python 3.4 or later. I\u2019ll eventually get around to testing it on Python 2.7-3.3.From PyPIInstall Xylem by runningpip3 install xylemfrom the command line.NoteOn some Linux systems, installation may require running pip with root permissions, or runningpip3 install xylem--user. The latter may require exporting~/.local/binto PATH.From GitHubClone or download thegit repo, navigate to the directory, and run:python3 setup.py sdist\ncd dist\npip3 install xylem-.tar.gzUsageto_sourceis likely the only method you\u2019ll need to use:>>>fromxylemimportto_source>>>importast>>>tree=ast.parse(\"print('hello world')\")>>>ast.dump(tree)\"Module(body=[Expr(value=Call(func=Name(id='print', ctx=Load()), args=[Str(s='Hello world')], keywords=[]))])\">>>to_source(tree)\"print('hello world')\"compare_astmay also be useful for determining if two ASTs are functionally equivalent.DevelopmentXylem versioning functions on aMAJOR.MINOR.PATCH.[DEVELOP]model. Only stable, non development releases will be published to PyPI. Because Xylem is still a beta project, theMAJORincrement will be 0. Minor increments represent new features. Patch increments represent problems fixed with existing features."} +{"package": "xylem-daq", "pacakge-description": "xylemA modular, parallel-ready data acquisition frameworkXylem systems consist of a collection of software components connected\nto represent the flow of information (data and commands) through\nthe experiment. Each component has a particular relation to data\n(e.g. Producer, Consumer, Aggregator) which determines the available\nconnections and functionality. For example, Producers introduce new data\ninto the xylem system, and Consumers remove data from the system (e.g.\ninto offline storage). The components work together to get data through\nthe pipeline as smoothly as possible.Xylem components are designed to fit into code that you already have\nwhich controls your experimental equipment and processes your data. For\nexample, if you have code which interfaces with an instrument and prints\nthe data to the console, you can replace the print statement with a\ncall toProducer.produce(). Then, the xylem Producer will send off\nthe data to the downstream xylem components while your code continues\nrunning.The xylem Core is a special component which monitors and commmunicates\nwith all of the other components in the system. It determines if a\ncomponent has crashed or otherwise become unresponsive, and it also can\nsend state updates and arbitrary messages to the components.Human operators can access the functionality of the Core component using\nthe Controller component. This component does not participate in the\ndata flow; rather, it allows the human operator to send commands to the\nsystem (via the Core) and query its state (also via the Core). You can\ndesign your system to respond to any set of commands you'd like, such\nas \"Begin run,\" \"Initialize instrumentation,\" \"Perform calibration,\" or\nanything else that makes sense in your system. Internally, your code\nwould translate your commands into state updates that will be sent to\nthe Core. You provide the logic; xylem simply makes sure the messages\nreach their intended destination.DAQ ComponentsFundamental building blocks for basic setups:Data producer: produces data. Example: digitizersData consumer: accepts data inputs and sends no output to other\nxylem components. Examples: offline data storage, live data displayData aggregator: collects data from multiple data producers and\nsupplies the data to multiple data consumersCompound building blocks for more advanced setups:Data producer group: a collection of data producers\nwhose output is aggregated before being\nsent to the data aggregator, so that the collection can be treated as\na single data producer. Example: an array of identical sensorsExample basic architectureData producerData aggregatorData consumerExample complex architectureData producer group 1*Data producerData producer...Data producer group 2*Data producerData producer...Data aggregator 1Data consumer 1+Data consumer 2...Data aggregator 2Data consumer 1+Data consumer 3...*: The data producer groups are located after the data producers in the\ndata flow.+: A single data consumer instance can receive data from multiple data\naggregators."} +{"package": "xy-libcollection", "pacakge-description": "#A long desc"} +{"package": "xylib-py", "pacakge-description": "xylib is a library for reading obscure file formats with data from\npowder diffraction, spectroscopy and other experimental methods.\nFor the list of supported formats seehttps://github.com/wojdyr/xylib.This module includes bindings to xylib and xylib itself.\nThe first two numbers in the version are the version of included xylib.Prerequisites for building: SWIG and Boost libraries (headers only)."} +{"package": "xylib-py-wheels", "pacakge-description": "This package contains built wheels for xylib by Marcin Wojdyr (https://github.com/wojdyr/xylib)\nxylib is a library for reading obscure file formats with data from\npowder diffraction, spectroscopy and other experimental methods.\nFor the list of supported formats seehttps://github.com/wojdyr/xylib.This module includes bindings to xylib and xylib itself.\nThe first two numbers in the version are the version of included xylib."} +{"package": "xyliuuu", "pacakge-description": "No description available on PyPI."} +{"package": "xylose", "pacakge-description": "No description available on PyPI."} +{"package": "xylosim", "pacakge-description": "C++ based simulator for quantized spiking neural network accelarators such as the Xylo chip developed by Synsense."} +{"package": "xym", "pacakge-description": "xym is a simple tool for fetching and extracting YANG modules from IETF RFCs and drafts as local files and from URLs."} +{"package": "xymap", "pacakge-description": "xymapOngoing projectThis is Alpha versionBivariate colormap solutions.Inspired byxycmap.Installationpip install xymaptodo list:provide color ramps optionsadd band palette to tifadd user defined color rampsinterpolate color rampsvector format supporttriangle mesh supportDone"} +{"package": "xymath", "pacakge-description": "XYmath Creates, Documents And Explores Y=f(X) Curve FitsSee the Code at:https://github.com/sonofeft/XYmathSee the Docs at:http://xymath.readthedocs.org/en/latest/See PyPI page at:https://pypi.python.org/pypi/xymathXYmath will find the \u201cbest\u201d curve fit equation in a data set of x,y pairs by minimizingthe sum of the square of the the difference between the data and the equation (i.e. residuals).The user may choose to minimize either percent error or total error.(Percent error is particularly useful for y values spanning several orders of magnitude.)XYmath can search throughcommon equations, an exhaustive search through thousands of equations,splines, smoothed splines, or fit non-linear equations of the user\u2019s choice.After fitting, XYmath will find roots, minima, maxima, derivatives orintegrals of the fitted curve. It will generate source code that documents andevaluates the fit in python, FORTRAN or EXCEL. Configurable plots arecreated using matplotlib that are of publication quality, including plots ofequation residuals."} +{"package": "xy-meiyan", "pacakge-description": "Image beauty"} +{"package": "xymol", "pacakge-description": "eXplain Your MOLecule (XYMOL)XYMOL is A Python package to understand and explain atom/bond contributions of small molecules in machine learning models."} +{"package": "xymon-client", "pacakge-description": "# python-xymon-clientA minimalist [Xymon](https://www.xymon.com/) client library and CLI in Python.Documentation is in the docs directory or [online](http://python-xymon-client.readthedocs.io/en/latest/).Features:Python 3.10;\nbut should work with Python \u2265 3.6 if you remove the annotations\n(a tool such as [python-minifier](https://github.com/dflook/python-minifier) can do it for you)no dependenciescommand line interfaceeasy to use and extend## ExamplesAs CLI:`bash $xymon-client-sxymon01.example.net query--hostnamewww-portal.example.net--testnameinfo 'yellow Message generated byc234d183-069b-447e-73ab-84d5at2019-01-29T16:14:01\\n'`As a Python library:`python from xymon_client import Xymon xymon =Xymon('xymonserver01.example.net')xymon.ping() 'xymond 4.3.18\\n' `## Alternativeshttps://github.com/skurfer/python-xymon"} +{"package": "xy-namecard", "pacakge-description": "namecard Recognition,age,beauty,gender"} +{"package": "xync-bot", "pacakge-description": "No description available on PyPI."} +{"package": "xyndra-function-core", "pacakge-description": "No description available on PyPI."} +{"package": "xy_nester", "pacakge-description": "UNKNOWN"} +{"package": "xy-news", "pacakge-description": "Get News From juhe API, Contain All Type News"} +{"package": "xy-ocrtext", "pacakge-description": "Get constellation Info From juhe API"} +{"package": "xyolo", "pacakge-description": "xyoloxyolo\u662f\u4e00\u4e2aPython\u5b9e\u73b0\u7684\u3001\u9ad8\u5ea6\u5c01\u88c5\u7684YOLO v3\u7c7b\u5e93\u3002\u501f\u52a9xyolo\uff0c\u60a8\u53ef\u4ee5\u53ea\u4f7f\u7528\u51e0\u884cPython\u4ee3\u7801\u8f7b\u677e\u5b8c\u6210yolo3\u76ee\u6807\u68c0\u6d4b\u4efb\u52a1\u7684\u8bad\u7ec3\u548c\u8c03\u7528\u3002xyolo is a highly encapsulated YOLO v3 library implemented in Python.With xyolo, you can easily complete the training and calling of the yolo3 target detection task with just a few lines of Python code.\u8bf7\u6ce8\u610f\uff1a\u6211\u4f7f\u7528\u7684Python\u662fAnaconda\u7684Python 3.7\u53d1\u884c\u7248\u672c\uff0c\u5728shell\u91cc\u9762\u8fdb\u884c\u4e86\u521d\u59cb\u5316(python\u548cpip\u9ed8\u8ba4\u6307\u5411\u5f53\u524d\u6fc0\u6d3b\u73af\u5883\uff0c\u800c\u4e0d\u662f\u9ed8\u8ba4\u7684python2)\uff0c\u6240\u4ee5\u6587\u7ae0\u4e2d\u7684python\u548cpip\u8bf7\u6839\u636e\u81ea\u5df1\u7684\u60c5\u51b5\u5224\u65ad\u662f\u5426\u9700\u8981\u66ff\u6362\u4e3apython3\u548cpip3\u3002PS:\u6b64\u9879\u76ee\u662f\u5bf9tf2-keras-yolo3\u9879\u76ee\u7684\u91cd\u6784\u548c\u5c01\u88c5\u3002\u4e00\u3001\u5b89\u88c51\u3001\u901a\u7528\u5b89\u88c5\u65b9\u6cd5xyolo\u7684\u5b89\u88c5\u975e\u5e38\u7b80\u5355\uff0c\u901a\u8fc7pip\u4e00\u952e\u5b89\u88c5\u5373\u53ef\u3002\u8bf7\u6ce8\u610f\uff0cxyolo\u9700\u8981\u5b89\u88c5\u7684TensorFlow\u7248\u672c>=2.2\uff08\u672a\u5b89\u88c5TensorFlow\u7684\u8bdd\u5219\u4f1a\u81ea\u52a8\u5b89\u88c5\uff09pip install --user xyolo\u5efa\u8bae\u4f7f\u7528--user\u53c2\u6570\uff0c\u907f\u514d\u9047\u5230\u6743\u9650\u95ee\u9898\u3002\u5f53\u7136\uff0c\u5982\u679c\u6709\u6761\u4ef6\u7684\u8bdd\uff0c\u4f7f\u7528conda\u521b\u5efa\u4e00\u4e2a\u65b0\u73af\u5883\uff0c\u5e76\u5728\u65b0\u73af\u5883\u4e2d\u8fdb\u884c\u5b89\u88c5\u4f1a\u66f4\u597d\uff0c\u53ef\u4ee5\u907f\u514d\u610f\u6599\u4e4b\u5916\u7684\u4f9d\u8d56\u51b2\u7a81\u95ee\u9898\u30022\u3001GPU\u7248\u672c\u5b89\u88c5\u65b9\u6cd5\u5982\u679c\u4f60\u60f3\u4f7f\u7528TensorFlow\u7684GPU\u7248\u672c\uff0c\u53ef\u4ee5\u9009\u62e9\u5728\u5b89\u88c5xyolo\u4e4b\u524d\uff0c\u5148\u5b89\u88c52.2\u53ca\u4ee5\u4e0a\u7684tensorflow-gpu\u3002\u4ee5conda\u4e3e\u4f8b\uff0c\u5b89\u88c5GPU\u652f\u6301\u7684\u64cd\u4f5c\u6d41\u7a0b\u5982\u4e0b\uff1a1.\u521b\u5efa\u4e00\u4e2a\u865a\u62df\u73af\u5883\uff0c\u540d\u4e3axyolo\u3002conda create -n xyolo python=3.72.\u5207\u6362\u5230\u521a\u521b\u5efa\u597d\u7684\u73af\u5883\u91ccconda activate xyolo\u5207\u6362\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7pip\u67e5\u770b\u4e00\u4e0b\u73af\u5883\u91cc\u5b89\u88c5\u7684\u5305\uff1apip list\u7ed3\u679c\u4e0d\u51fa\u9884\u6599\uff0c\u5f88\u5e72\u51c0\uff0c\u6bd5\u7adf\u662f\u4e00\u4e2a\u65b0\u73af\u5883\u561b\uff1aPackage Version\n---------- -------------------\ncertifi 2020.6.20\npip 20.2.4\nsetuptools 50.3.0.post20201006\nwheel 0.35.13.\u5728\u65b0\u73af\u5883\u4e2d\u5b89\u88c5tensorflow-gpu\u6ce8\u610f\uff0c\u5b89\u88c5\u524d\u9700\u8981\u5148\u5b89\u88c5\u597d\u548ctensorflow\u7248\u672c\u5bf9\u5e94\u7684\u663e\u5361\u9a71\u52a8\uff0c\u8fd9\u90e8\u5206\u8fd8\u6709\u70b9\u9ebb\u70e6\uff0c\u5c31\u4e0d\u5728\u8fd9\u7bc7\u6587\u7ae0\u4e2d\u8bf4\u660e\u4e86\uff0c\u6211\u89c9\u5f97\u4f1a\u9009\u62e9\u4f7f\u7528GPU\u8dd1xyolo\u7684\u540c\u5b66\u5e94\u8be5\u90fd\u5df2\u7ecf\u638c\u63e1\u4e86\u8fd9\u90e8\u5206\u6280\u80fd\u4e86\u5427\uff1f\u6bd5\u7adf\u5982\u679c\u5b8c\u5168\u6ca1\u6709\u63a5\u89e6\u8fc7tensorflow-gpu\u7684\u8bdd\uff0c\u63a5\u89e6xyolo\u5e94\u8be5\u4e5f\u4f1a\u9009\u62e9cpu\u7248\u672c\u66f4\u597d\u4e0a\u624b\u3002\u6211\u4eec\u901a\u8fc7conda\u6765\u5b89\u88c5tensorflow-gpu\uff0cgpu\u7248\u672c\u7684tensorflow\u5b58\u5728cuda\u548ccudnn\u4f9d\u8d56\uff0c\u4f7f\u7528conda\u53ef\u4ee5\u81ea\u52a8\u89e3\u51b3\u8fd9\u4e24\u8005\u7684\u7248\u672c\u4f9d\u8d56\u548c\u914d\u7f6e\u95ee\u9898\u3002conda install tensorflow-gpu=2.2\u5b89\u9759\u5730\u7b49\u5f85\u4e00\u6bb5\u65f6\u95f4\uff0c\u5373\u53ef\u5b8c\u6210tensorflow-gpu\u7684\u5b89\u88c5\u30024.\u4f7f\u7528pip\u5b89\u88c5xyolopip install --user xyolo\u901a\u8fc7\u518d\u6b21\u6267\u884cpip list\uff0c\u6211\u4eec\u80fd\u591f\u770b\u5230\u6210\u529f\u5b89\u88c5\u7684xyolo\u53ca\u76f8\u5173\u4f9d\u8d56\u3002Package Version\n---------------------- -------------------\nabsl-py 0.11.0\naiohttp 3.6.3\nastunparse 1.6.3\nasync-timeout 3.0.1\nattrs 20.2.0\nblinker 1.4\nbrotlipy 0.7.0\ncachetools 4.1.1\ncertifi 2020.6.20\ncffi 1.14.3\nchardet 3.0.4\nclick 7.1.2\ncryptography 3.1.1\ncycler 0.10.0\ngast 0.3.3\ngoogle-auth 1.23.0\ngoogle-auth-oauthlib 0.4.2\ngoogle-pasta 0.2.0\ngrpcio 1.31.0\nh5py 2.10.0\nidna 2.10\nimportlib-metadata 2.0.0\nKeras-Preprocessing 1.1.0\nkiwisolver 1.3.1\nloguru 0.5.3\nlxml 4.6.1\nMarkdown 3.3.2\nmatplotlib 3.3.2\nmkl-fft 1.2.0\nmkl-random 1.1.1\nmkl-service 2.3.0\nmultidict 4.7.6\nnumpy 1.18.5\noauthlib 3.1.0\nopencv-python 4.4.0.46\nopt-einsum 3.1.0\nPillow 8.0.1\npip 20.2.4\nprotobuf 3.13.0\npyasn1 0.4.8\npyasn1-modules 0.2.8\npycparser 2.20\nPyJWT 1.7.1\npyOpenSSL 19.1.0\npyparsing 2.4.7\nPySocks 1.7.1\npython-dateutil 2.8.1\nrequests 2.24.0\nrequests-oauthlib 1.3.0\nrsa 4.6\nscipy 1.4.1\nsetuptools 50.3.0.post20201006\nsix 1.15.0\ntensorboard 2.2.2\ntensorboard-plugin-wit 1.6.0\ntensorflow 2.2.0\ntensorflow-estimator 2.2.0\ntermcolor 1.1.0\ntqdm 4.51.0\nurllib3 1.25.11\nWerkzeug 1.0.1\nwheel 0.35.1\nwrapt 1.12.1\nxyolo 0.1.3\nyarl 1.6.2\nzipp 3.4.0\u4e8c\u3001\u4f7f\u7528\u65b9\u6cd51\u3001\u4f7f\u7528\u5b98\u65b9\u9884\u8bad\u7ec3\u6743\u91cd\uff0c\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u6d4b\u8bd5yolov3\u5b98\u65b9\u6709\u63d0\u4f9b\u9884\u8bad\u7ec3\u6743\u91cd\uff0c\u5982\u679c\u6211\u4eec\u8981\u5728\u548cVOC\u6570\u636e\u96c6\u540c\u5206\u5e03\u6216\u76f8\u4f3c\u5206\u5e03\u7684\u56fe\u7247\u4e0a\u505a\u76ee\u6807\u68c0\u6d4b\u7684\u8bdd\uff0c\u76f4\u63a5\u4f7f\u7528\u5b98\u65b9\u9884\u8bad\u7ec3\u6743\u91cd\u4e5f\u662f\u53ef\u4ee5\u7684\u3002xyolo\u8c03\u7528\u5b98\u65b9\u9884\u8bad\u7ec3\u6a21\u578b\u7684\u903b\u8f91\u662f\uff1a1.\u4ece\u5b98\u7f51\u4e0b\u8f7d\u9884\u8bad\u7ec3\u6743\u91cd\uff08Darknet\u8f93\u51fa\u683c\u5f0f\uff092.\u5c06Darknet\u7684\u6743\u91cd\u6587\u4ef6\u8f6c\u6210keras\u7684\u6743\u91cd\u6587\u4ef6\uff08\u73b0\u5728TensorFlow\u548cKeras\u5df2\u7ecf\u57fa\u672c\u4e0d\u5206\u5bb6\u5566\uff093.\u6784\u5efa\u6a21\u578b\uff0c\u52a0\u8f7d\u9884\u8bad\u7ec3\u6743\u91cd4.\u5bf9\u9009\u62e9\u7684\u56fe\u7247\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u597d\u9ebb\u70e6\u554a\uff0c\u662f\u4e0d\u662f\u8981\u5199\u5f88\u591a\u4ee3\u7801\uff1f\u5f53\u7136\u4e0d\u662f~\u6b6a\u5634.jpg\u9996\u5148\uff0c\u51c6\u5907\u4e00\u5f20\u7528\u4e8e\u68c0\u6d4b\u7684\u56fe\u7247\uff0c\u5047\u8bbe\u5b83\u7684\u8def\u5f84\u662f./xyolo_data/detect.jpg\uff0c\u56fe\u7247\u5185\u5bb9\u5982\u4e0b\uff1a\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u5982\u4e0b\uff1a# \u5bfc\u5165\u5305fromxyoloimportYOLO,DefaultYolo3Configfromxyoloimportinit_yolo_v3# \u521b\u5efa\u9ed8\u8ba4\u914d\u7f6e\u7c7b\u5bf9\u8c61config=DefaultYolo3Config()# \u521d\u59cb\u5316xyolo\uff08\u4e0b\u8f7d\u9884\u8bad\u7ec3\u6743\u91cd\u3001\u8f6c\u6362\u6743\u91cd\u7b49\u64cd\u4f5c\u90fd\u662f\u5728\u8fd9\u91cc\u5b8c\u6210\u7684\uff09# \u4e0b\u8f7d\u548c\u8f6c\u6362\u53ea\u5728\u7b2c\u4e00\u6b21\u8c03\u7528\u7684\u65f6\u5019\u8fdb\u884c\uff0c\u4e4b\u540e\u518d\u8c03\u7528\u4f1a\u4f7f\u7528\u7f13\u5b58\u7684\u6587\u4ef6init_yolo_v3(config)# \u521b\u5efa\u4e00\u4e2ayolo\u5bf9\u8c61\uff0c\u8fd9\u4e2a\u5bf9\u8c61\u63d0\u4f9b\u4f7f\u7528yolov3\u8fdb\u884c\u68c0\u6d4b\u548c\u8bad\u7ec3\u7684\u63a5\u53e3yolo=YOLO(config)# \u68c0\u6d4b\u5e76\u5728\u56fe\u7247\u4e0a\u6807\u6ce8\u51fa\u7269\u4f53img=yolo.detect_and_draw_image('./xyolo_data/detect.jpg')# \u5c55\u793a\u6807\u6ce8\u540e\u56fe\u7247img.show()\u8f93\u51fa\u5982\u4e0b:2020-11-03 23:33:49.645 | DEBUG | xyolo.yolo3.yolo:detect_image:273 - Found 3 boxes for img\n2020-11-03 23:33:49.648 | DEBUG | xyolo.yolo3.yolo:detect_image:289 - Class dog 0.99,Position (402, 176), (586, 310)\n2020-11-03 23:33:49.650 | DEBUG | xyolo.yolo3.yolo:detect_image:289 - Class bicycle 0.96,Position (0, 80), (383, 412)\n2020-11-03 23:33:49.652 | DEBUG | xyolo.yolo3.yolo:detect_image:289 - Class person 1.00,Position (9, 1), (200, 410)\n2020-11-03 23:33:49.652 | DEBUG | xyolo.yolo3.yolo:detect_image:292 - Cost time 6.65432205500838s\u540c\u65f6\uff0c\u6253\u5f00\u4e86\u4e00\u5f20\u56fe\u7247\uff08\u56fe\u7247\u5c3a\u5bf8\u4e0d\u4e00\u81f4\u662f\u6211\u622a\u56fe\u548c\u6392\u7248\u7684\u95ee\u9898\uff09\uff1a\u8fd9\u6837\uff0c\u4e00\u6b21\u76ee\u6807\u68c0\u6d4b\u5c31\u5b8c\u6210\u4e86\uff0c\u8212\u670d\u5440~\u5f53\u7136\u4e86\uff0c\u6211\u76f8\u4fe1\u80af\u5b9a\u6709\u4e0d\u5c11\u540c\u5b66\u5df2\u7ecf\u5728\u8fd9\u6bb5\u4ee3\u7801\u7684\u6267\u884c\u8fc7\u7a0b\u4e2d\u9047\u5230\u56f0\u96be\u6216\u7591\u60d1\u4e86\uff0c\u6211\u6765\u96c6\u4e2d\u89e3\u7b54\u51e0\u4e2a\u53ef\u80fd\u4f1a\u9047\u5230\u7684\u30021.\u9884\u8bad\u7ec3\u6743\u91cd\u4e0b\u8f7d\u6162\u6216\u65e0\u6cd5\u4e0b\u8f7d\u56e0\u4e3ayolov3\u7684\u5b98\u7f51\u5728\u56fd\u5916\uff0c\u6240\u4ee5\u56fd\u5185\u4e0b\u8f7d\u6162\u4e5f\u5f88\u6b63\u5e38\u3002\u63a8\u8350\u4f7f\u7528\u4ee3\u7406\uff0c\u6216\u4ece\u5907\u4efd\u5730\u5740\u4e0b\u8f7d\u540e\u6307\u5b9a\u9884\u8bad\u7ec3\u6743\u91cd\u7684\u5730\u5740\u3002\u5177\u4f53\u65b9\u6cd5\u53c2\u80032\u3001\u9884\u8bad\u7ec3\u6743\u91cd\u65e0\u6cd5\u4e0b\u8f7d\u6216\u4e0b\u8f7d\u901f\u5ea6\u6162\u7684\u89e3\u51b3\u65b9\u6848\u30022.\u63d0\u793a\u6743\u9650\u95ee\u9898\u56e0\u4e3axyolo\u4f1a\u81ea\u52a8\u4e0b\u8f7d\u9884\u8bad\u7ec3\u6743\u91cd\u5230\u5b89\u88c5\u76ee\u5f55\u4e0b\uff0c\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u53ef\u80fd\u4f1a\u9047\u5230\u6743\u9650\u95ee\u9898\u3002\u89e3\u51b3\u65b9\u6cd5\u5c31\u662f\u5728\u5b89\u88c5\u90e8\u5206\u8bf4\u7684\uff0c\u901a\u8fc7\u6307\u5b9a--user\u53c2\u6570\u6307\u660e\u5c06\u5305\u5b89\u88c5\u5728\u7528\u6237\u76ee\u5f55\u4e0b\uff0c\u4e00\u822c\u5c31\u6ca1\u95ee\u9898\u4e86\u30023.\u68c0\u6d4b\u7684\u901f\u5ea6\u6162\u7ec6\u5fc3\u7684\u540c\u5b66\u53ef\u80fd\u53d1\u73b0\u4e86\uff0c\u4e0a\u9762\u5bf9\u56fe\u7247\u505a\u7684\u4e00\u6b21\u68c0\u6d4b\uff0c\u7adf\u7136\u82b1\u4e866\u79d2\uff01\u8fd9\u4e5f\u592a\u6162\u4e86\u5427\uff1f\u4e8b\u5b9e\u4e0a\uff0c\u5e76\u4e0d\u662f\u8fd9\u6837\u7684\u3002TensorFlow 2.x\u7248\u672c\uff0c\u9ed8\u8ba4\u4f7f\u7528\u52a8\u6001\u56fe\uff0c\u6027\u80fd\u4f1a\u7a0d\u5f31\u4e8e1.x\u7684\u9759\u6001\u56fe\u3002\u6240\u4ee5\uff0c\u6211\u8fd9\u91cc\u4f7f\u7528\u4e86tf.function\u5bf9\u901f\u5ea6\u8fdb\u884c\u4e86\u4f18\u5316\uff0c\u5728\u7b2c\u4e00\u6b21\u8fd0\u7b97\u65f6\uff0c\u6a21\u578b\u4f1a\u81ea\u52a8\u751f\u6210\u9759\u6001\u56fe\uff0c\u8fd9\u90e8\u5206\u4f1a\u6bd4\u8f83\u6d88\u8017\u65f6\u95f4\uff0c\u4f46\u540e\u7eed\u5355\u6b21\u8ba1\u7b97\u7684\u65f6\u95f4\u90fd\u4f1a\u6781\u5927\u5730\u7f29\u77ed\u3002\u5047\u5982\u6211\u4eec\u63a5\u7740\u8fdb\u884c\u51e0\u6b21\u8bc6\u522b\uff0c\u5c31\u80fd\u591f\u53d1\u73b0\u5355\u6b21\u8bc6\u522b\u7684\u65f6\u95f4\u6709\u4e86\u660e\u663e\u964d\u4f4e\uff0c\u4e00\u822c\u53ea\u9700\u8981\u96f6\u70b9\u51e0\u79d2\u6216\u51e0\u5341\u6beb\u79d2\u30022\u3001\u9884\u8bad\u7ec3\u6743\u91cd\u65e0\u6cd5\u4e0b\u8f7d\u6216\u4e0b\u8f7d\u901f\u5ea6\u6162\u7684\u89e3\u51b3\u65b9\u6848\u4e3b\u8981\u6709\u4e24\u79cd\u65b9\u6cd5\u80fd\u591f\u89e3\u51b3\uff0c\u5206\u522b\u770b\u4e00\u4e0b\u30021.\u8bbe\u7f6e\u4ee3\u7406\u5982\u679c\u6211\u4eec\u624b\u4e0a\u6709\u80fd\u591f\u52a0\u5feb\u8bbf\u95ee\u901f\u5ea6\u7684\u7f51\u7edc\u4ee3\u7406\uff08\u4f60\u5e94\u8be5\u77e5\u9053\u6211\u5728\u8bf4\u5565~\uff09\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u4ee3\u7406\u7684\u5f62\u5f0f\u52a0\u5feb\u4e0b\u8f7d\u901f\u5ea6\uff0c\u793a\u4f8b\u5982\u4e0b\uff1afromxyoloimportYOLO,DefaultYolo3Configfromxyoloimportinit_yolo_v3# \u521b\u5efa\u4e00\u4e2aDefaultYolo3Config\u7684\u5b50\u7c7b\uff0c\u5728\u5b50\u7c7b\u91cc\u8986\u76d6\u9ed8\u8ba4\u7684\u914d\u7f6eclassMyConfig(DefaultYolo3Config):def__init__(self):super(MyConfig,self).__init__()# \u8fd9\u662f\u66ff\u6362\u6210\u4f60\u7684\u4ee3\u7406\u5730\u5740self.requests_proxies={'https':'http://localhost:7890'}# \u4f7f\u7528\u4fee\u6539\u540e\u7684\u914d\u7f6e\u521b\u5efayolo\u5bf9\u8c61config=MyConfig()init_yolo_v3(config)yolo=YOLO(config)# \u68c0\u6d4bimg=yolo.detect_and_draw_image('./xyolo_data/detect.jpg')img.show()2.\u4ece\u5907\u7528\u94fe\u63a5\u624b\u52a8\u4e0b\u8f7d\u5982\u679c\u6ca1\u6709\u4ee3\u7406\u7684\u8bdd\uff0c\u4e5f\u53ef\u4ee5\u9009\u62e9\u4ece\u5907\u7528\u4e0b\u8f7d\u5730\u5740\u4e0b\u8f7d\u3002\u6211\u628a\u9884\u8bad\u7ec3\u6743\u91cd\u4e0a\u4f20\u5230\u767e\u5ea6\u4e91\u4e0a\u4e86\uff0c\u94fe\u63a5\u5982\u4e0b\uff1a\u94fe\u63a5:https://pan.baidu.com/s/1jXpoXHQHlp6Ra0jImruPXg\u5bc6\u7801: 48ed\u4ece\u5206\u4eab\u9875\u9762\u4e0b\u8f7d\u597d\u6743\u91cd\u6587\u4ef6\u540e\uff0c\u53c8\u6709\u4e24\u79cd\u8bbe\u7f6e\u65b9\u5f0f\u3002\u2460\u5c06\u6587\u4ef6\u590d\u5236\u5230xyolo\u5305\u7684\u5b89\u88c5\u76ee\u5f55\u4e0b\u7684xyolo_data\u76ee\u5f55\u4e0b\u5373\u53ef\uff0c\u5c31\u548c\u81ea\u52a8\u4e0b\u8f7d\u7684\u60c5\u51b5\u662f\u4e00\u6837\u7684\uff0c\u540e\u7eed\u4e0d\u9700\u8981\u518d\u4eba\u4e3a\u505a\u4efb\u4f55\u64cd\u4f5c\u3002\u2461\u5c06\u6587\u4ef6\u4fdd\u5b58\u5728\u4efb\u610f\u4f4d\u7f6e\uff0c\u5e76\u5728\u914d\u7f6e\u7c7b\u4e2d\u8bbe\u7f6e\u5b83\u7684\u8def\u5f84\u3002\u7b2c\u4e00\u79cd\u5c31\u4e0d\u9700\u8981\u591a\u8bf4\u4e86\uff0c\u6765\u770b\u4e00\u4e2a\u7b2c\u4e8c\u79cd\u8bbe\u7f6e\u65b9\u6cd5\u7684\u793a\u4f8b\uff1afromxyoloimportYOLO,DefaultYolo3Configfromxyoloimportinit_yolo_v3# \u521b\u5efa\u4e00\u4e2aDefaultYolo3Config\u7684\u5b50\u7c7b\uff0c\u5728\u5b50\u7c7b\u91cc\u8986\u76d6\u9ed8\u8ba4\u7684\u914d\u7f6eclassMyConfig(DefaultYolo3Config):def__init__(self):super(MyConfig,self).__init__()# \u8fd9\u662f\u66ff\u6362\u6210\u4f60\u7684\u6587\u4ef6\u8def\u5f84\uff0c\u4e3a\u4e86\u907f\u514d\u51fa\u9519\uff0c\u8bf7\u5c3d\u91cf\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._pre_training_weights_darknet_path='/Users/aaron/data/darknet_yolo.weights'# \u4f7f\u7528\u4fee\u6539\u540e\u7684\u914d\u7f6e\u521b\u5efayolo\u5bf9\u8c61config=MyConfig()init_yolo_v3(config)yolo=YOLO(config)# \u68c0\u6d4bimg=yolo.detect_and_draw_image('./xyolo_data/detect.jpg')img.show()3\u3001\u4f7f\u7528\u81ea\u5df1\u7684\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u9996\u5148\u4ecb\u7ecd\u4e00\u4e0bxyolo\u7684\u6570\u636e\u96c6\u7684\u8f93\u5165\u683c\u5f0f\u3002xyolo\u7684\u8f93\u5165\u6570\u636e\u96c6\u53ef\u8868\u793a\u5982\u4e0b\uff1a\u6570\u636e\u96c6\u662f\u4e00\u4e2atxt\u6587\u672c\u6587\u4ef6\uff0c\u5b83\u5305\u542b\u82e5\u5e72\u884c\uff0c\u6bcf\u884c\u662f\u4e00\u6761\u6570\u636e\u3002\u6bcf\u4e00\u884c\u7684\u683c\u5f0f\uff1a \u56fe\u7247\u8def\u5f84 box1 box2 ... boxN\u6bcf\u4e00\u4e2abox\u7684\u683c\u5f0f\uff1a\u6846\u6846\u5de6\u4e0a\u89d2x\u503c,\u6846\u6846\u5de6\u4e0a\u89d2y\u503c,\u6846\u6846\u53f3\u4e0b\u89d2x\u503c,\u6846\u6846\u53f3\u4e0b\u89d2y\u503c,\u6846\u6846\u5185\u7269\u4f53\u7684\u7c7b\u522b\u7f16\u53f7\u7ed9\u51fa\u4e00\u4e2a\u793a\u4f8b\uff1apath/to/img1.jpg 50,100,150,200,0 30,50,200,120,3\npath/to/img2.jpg 120,300,250,600,2\n...\u8fdb\u884c\u56fe\u50cf\u6807\u6ce8\u7684\u5de5\u5177\uff0clabelImg\u7b97\u662f\u7528\u7684\u6bd4\u8f83\u591a\u7684\u3002labelImg\u7684\u6807\u6ce8\u6587\u4ef6\u683c\u5f0f\u9ed8\u8ba4\u662fVOC\u7684\u683c\u5f0f\uff0c\u6587\u4ef6\u7c7b\u578b\u662fxml\uff0c\u4e0exyolo\u7684\u8f93\u5165\u683c\u5f0f\u5e76\u4e0d\u76f8\u540c\u3002\u4e0d\u7528\u62c5\u5fc3\uff0cxyolo\u63d0\u4f9b\u4e86\u4e00\u4e2a\u6570\u636e\u683c\u5f0f\u8f6c\u6362\u7684\u811a\u672c\uff0c\u6211\u4eec\u53ea\u9700\u8981\u8c03\u7528\u5373\u53ef\u3002# \u5f15\u5165\u8f6c\u6362\u811a\u672cfromxyoloimportvoc2xyolo# voc\u683c\u5f0f\u7684\u6807\u6ce8\u6570\u636e\u8def\u5f84\u7684\u6b63\u5219\u8868\u8fbe\u5f0finput_path='/Users/aaron/data/labels_voc/*.xml'# classes\u662f\u6211\u4eec\u8981\u68c0\u6d4b\u7684\u6240\u6709\u6709\u6548\u7c7b\u522b\u540d\u79f0\u6784\u6210\u7684txt\u6587\u4ef6\uff0c\u6bcf\u4e2a\u7c7b\u522b\u4e00\u884cclasses_path='/Users/aaron/code/xyolo/tests/xyolo_data/classes.txt'# \u8f6c\u6362\u540e\u7684xyolo\u6570\u636e\u96c6\u5b58\u653e\u8def\u5f84output_path='/Users/aaron/code/xyolo/tests/xyolo_data/xyolo_label.txt'# \u5f00\u59cb\u8f6c\u6362voc2xyolo(input_path=input_path,classes_path=classes_path,output_path=output_path)\u811a\u672c\u6267\u884c\u540e\uff0c\u4f1a\u6709\u8fdb\u5ea6\u6761\u63d0\u793a\u5904\u7406\u8fdb\u5ea6\uff0c\u5f53\u8fdb\u5ea6\u6761\u8fbe\u5230100%\u65f6\uff0c\u5904\u7406\u5b8c\u6210\u3002100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 106/106 [00:00<00:00, 3076.05it/s]\u6709\u4e86\u6570\u636e\u96c6\u4e4b\u540e\uff0c\u53ef\u4ee5\u51c6\u5907\u8bad\u7ec3\u4e86\u3002\u5728\u6b64\u4e4b\u524d\uff0c\u786e\u8ba4\u4e00\u904d\u6211\u4eec\u9700\u8981\u7684\u4e1c\u897f\uff1axyolo\u652f\u6301\u7684\u6570\u636e\u96c6\u8981\u68c0\u6d4b\u7684\u6240\u6709\u6709\u6548\u7c7b\u522b\u540d\u79f0\u6784\u6210\u7684txt\u6587\u4ef6\uff08classes.txt\uff09\u6211\u4ee5\u68c0\u6d4b\u67d0\u4e2a\u7f51\u7ad9\u7684\u9a8c\u8bc1\u7801\u56fe\u7247\u4e0a\u7684\u6587\u5b57\u4e3e\u4f8b\u3002\u9996\u5148\u786e\u5b9a\u8981\u68c0\u6d4b\u7684\u7c7b\u522b\uff0c\u6211\u53ea\u9700\u8981\u5224\u65ad\u5b57\u7684\u4f4d\u7f6e\uff0c\u4e0d\u5224\u65ad\u6bcf\u4e2a\u5b57\u662f\u4ec0\u4e48\uff0c\u6240\u4ee5\u5c31\u4e00\u4e2a\u7c7b\u522btext\u3002\u6211\u4eec\u521b\u5efa\u4e00\u4e2aclasses.txt\u6587\u4ef6\uff0c\u5728\u91cc\u9762\u5199\u5165\uff1atext\u7136\u540e\uff0c\u6211\u6807\u6ce8\u5e76\u4f7f\u7528xyolo\u8f6c\u6362\u4e86\u6570\u636e\u96c6(xyolo_label.txt)\uff1a/home/aaron/tmp/test_xyolo/images/162.png 47,105,75,141,0 157,52,181,80,0 197,85,229,120,0 265,85,296,117,0 257,131,293,166,0 355,63,386,90,0\n/home/aaron/tmp/test_xyolo/images/88.png 93,46,129,86,0 79,139,114,174,0 209,42,237,72,0 200,68,226,98,0 256,53,295,86,0 209,134,247,171,0\n/home/aaron/tmp/test_xyolo/images/176.png 43,88,76,120,0 123,91,153,127,0 98,155,127,184,0 189,117,224,152,0 289,54,319,86,0 348,123,374,151,0\n/home/aaron/tmp/test_xyolo/images/63.png 36,128,72,161,0 79,130,104,161,0 127,120,160,153,0 305,111,329,138,0 302,125,334,153,0 342,81,380,119,0\n/home/aaron/tmp/test_xyolo/images/77.png 164,114,200,150,0 193,147,225,182,0 309,90,336,120,0 349,89,382,121,0 321,126,352,155,0 298,150,327,177,0\n/home/aaron/tmp/test_xyolo/images/189.png 119,90,148,118,0 122,132,150,159,0 208,44,240,76,0 279,60,314,97,0 299,65,334,98,0 331,93,364,129,0\n/home/aaron/tmp/test_xyolo/images/200.png 232,58,265,91,0 288,58,316,85,0 49,118,78,148,0 55,134,83,163,0 75,148,103,175,0 312,131,343,163,0\n/home/aaron/tmp/test_xyolo/images/76.png 20,61,56,97,0 29,108,57,139,0 76,117,111,154,0 139,117,167,147,0 204,116,242,157,0 336,153,376,191,0\n...\u5f00\u59cb\u8bad\u7ec3\uff1a# \u5bfc\u5165\u5305fromxyoloimportDefaultYolo3Config,YOLOfromxyoloimportinit_yolo_v3# \u521b\u5efa\u4e00\u4e2aDefaultYolo3Config\u7684\u5b50\u7c7b\uff0c\u5728\u5b50\u7c7b\u91cc\u8986\u76d6\u9ed8\u8ba4\u7684\u914d\u7f6eclassMyConfig(DefaultYolo3Config):def__init__(self):super(MyConfig,self).__init__()# \u6570\u636e\u96c6\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._dataset_path='/home/aaron/tmp/test_xyolo/xyolo_data/yolo_label.txt'# \u7c7b\u522b\u540d\u79f0\u6587\u4ef6\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._classes_path='/home/aaron/tmp/test_xyolo/xyolo_data/classes.txt'# \u6a21\u578b\u4fdd\u5b58\u8def\u5f84\uff0c\u9ed8\u8ba4\u662f\u4fdd\u5b58\u5728\u5f53\u524d\u8def\u5f84\u4e0b\u7684xyolo_data\u4e0b\u7684\uff0c\u4e5f\u53ef\u4ee5\u8fdb\u884c\u66f4\u6539# \u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._output_model_path='/home/aaron/tmp/test_xyolo/output_model.h5'# \u4f7f\u7528\u4fee\u6539\u540e\u7684\u914d\u7f6e\u521b\u5efayolo\u5bf9\u8c61config=MyConfig()init_yolo_v3(config)# \u5982\u679c\u662f\u8bad\u7ec3\uff0c\u5728\u521b\u5efayolo\u5bf9\u8c61\u65f6\u8981\u4f20\u9012\u53c2\u6570train=Trueyolo=YOLO(config,train=True)# \u5f00\u59cb\u8bad\u7ec3\uff0c\u8bad\u7ec3\u5b8c\u6210\u540e\u4f1a\u81ea\u52a8\u4fdd\u5b58yolo.fit()\u5982\u679c\u60f3\u8981\u4f7f\u7528\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u8fdb\u884c\u9884\u6d4b\uff0c\u53ef\u4ee5\u8fd9\u6837\u5199\uff1a# \u5bfc\u5165\u5305fromxyoloimportDefaultYolo3Config,YOLOfromxyoloimportinit_yolo_v3# \u521b\u5efa\u4e00\u4e2aDefaultYolo3Config\u7684\u5b50\u7c7b\uff0c\u5728\u5b50\u7c7b\u91cc\u8986\u76d6\u9ed8\u8ba4\u7684\u914d\u7f6eclassMyConfig(DefaultYolo3Config):def__init__(self):super(MyConfig,self).__init__()# \u7c7b\u522b\u540d\u79f0\u6587\u4ef6\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._classes_path='/home/aaron/tmp/test_xyolo/xyolo_data/classes.txt'# yolo\u5bf9\u8c61\u4f7f\u7528\u7684\u6a21\u578b\u8def\u5f84\uff0c\u4e5f\u5c31\u662f\u521a\u521a\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._model_path='/home/aaron/tmp/test_xyolo/output_model.h5'# \u4f7f\u7528\u4fee\u6539\u540e\u7684\u914d\u7f6e\u521b\u5efayolo\u5bf9\u8c61config=MyConfig()init_yolo_v3(config)yolo=YOLO(config)# \u68c0\u6d4bimg=yolo.detect_and_draw_image('./xyolo_data/detect.jpg')img.show()\u89c9\u5f97\u53cd\u590d\u914d\u7f6eConfig\u7c7b\u9ebb\u70e6\uff1f\u5b9e\u9645\u4e0a\uff0c\u5bf9\u4e8e\u4e00\u4e2a\u9879\u76ee\uff0c\u6211\u4eec\u53ea\u9700\u8981\u914d\u7f6e\u4e00\u4e2aConfig\u7c7b\uff0c\u628a\u9879\u76ee\u7528\u5230\u7684\u914d\u7f6e\u90fd\u4e00\u8d77\u914d\u7f6e\u4e86\uff0c\u7136\u540e\u518d\u5f15\u7528\u540c\u4e00\u4e2a\u7c7b\u5373\u53ef\uff0c\u6211\u73b0\u5728\u8fd9\u4e48\u5199\u53ea\u662f\u4e3a\u4e86\u65b9\u4fbf\u6f14\u793a\u3002\u6bd4\u5982\u4e0a\u9762\u8fd9\u4e2a\uff0c\u53ef\u4ee5\u76f4\u63a5\u628a\u8bad\u7ec3\u548c\u8c03\u7528\u7684\u914d\u7f6e\u5199\u5728\u4e00\u8d77\uff1a# \u521b\u5efa\u4e00\u4e2aDefaultYolo3Config\u7684\u5b50\u7c7b\uff0c\u5728\u5b50\u7c7b\u91cc\u8986\u76d6\u9ed8\u8ba4\u7684\u914d\u7f6eclassMyConfig(DefaultYolo3Config):def__init__(self):super(MyConfig,self).__init__()# \u6570\u636e\u96c6\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._dataset_path='/home/aaron/tmp/test_xyolo/xyolo_data/yolo_label.txt'# \u7c7b\u522b\u540d\u79f0\u6587\u4ef6\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._classes_path='/home/aaron/tmp/test_xyolo/xyolo_data/classes.txt'# \u6a21\u578b\u4fdd\u5b58\u8def\u5f84\uff0c\u9ed8\u8ba4\u662f\u4fdd\u5b58\u5728\u5f53\u524d\u8def\u5f84\u4e0b\u7684xyolo_data\u4e0b\u7684\uff0c\u4e5f\u53ef\u4ee5\u8fdb\u884c\u66f4\u6539# \u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._output_model_path='/home/aaron/tmp/test_xyolo/output_model.h5'# yolo\u5bf9\u8c61\u4f7f\u7528\u7684\u6a21\u578b\u8def\u5f84\uff0c\u4e5f\u5c31\u662f\u521a\u521a\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u8def\u5f84\uff0c\u63a8\u8350\u4f7f\u7528\u7edd\u5bf9\u8def\u5f84self._model_path='/home/aaron/tmp/test_xyolo/output_model.h5'4\u3001\u53ef\u9009\u7684\u5168\u90e8\u914d\u7f6e\u9879\u6211\u51b3\u5b9a\u5728xyolo\u5de5\u5177\u91cc\u9762\u7ed9\u7528\u6237\u8db3\u591f\u7684\u5b9a\u5236\u7a7a\u95f4\uff0c\u6240\u4ee5\u53c2\u6570\u4f1a\u8bbe\u7f6e\u7684\u6bd4\u8f83\u591a\uff0c\u8fd9\u6837\u4f7f\u7528\u8d77\u6765\u4f1a\u66f4\u52a0\u7075\u6d3b\u3002\u4f46\u4e5f\u4e0d\u7528\u62c5\u5fc3\u914d\u7f6e\u7e41\u7410\uff0c\u56e0\u4e3a\u5982\u4e0a\u9762\u6240\u89c1\uff0c\u5176\u5b9e\u5e38\u7528\u7684\u914d\u7f6e\u9879\u5c31\u51e0\u4e2a\uff0c\u53ea\u8981\u638c\u63e1\u90a3\u51e0\u4e2a\u5c31\u53ef\u4ee5\u8f7b\u677e\u4e0a\u624b\u4e86\u3002\u4f46\u662f\u5982\u679c\u60f3\u66f4\u7075\u6d3b\u7684\u8bdd\uff0c\u5c31\u9700\u8981\u4e86\u89e3\u66f4\u591a\u53c2\u6570\u3002\u4e0b\u9762\u7ed9\u51fa\u4e00\u4efd\u5b8c\u6574\u7684\u53c2\u6570\u914d\u7f6e\u4fe1\u606f\uff08\u4e5f\u5c31\u662fxyolo\u7684\u9ed8\u8ba4\u914d\u7f6e\uff09\uff1afromos.pathimportabspath,join,dirname,existsfromosimportmkdirclassDefaultYolo3Config:\"\"\"yolo3\u6a21\u578b\u7684\u9ed8\u8ba4\u8bbe\u7f6e\"\"\"def__init__(self):# xyolo\u5404\u79cd\u6570\u636e\u7684\u4fdd\u5b58\u8def\u5f84\uff0c\u5305\u5185\u7f6eself.inner_xyolo_data_dir=abspath(join(dirname(__file__),'./xyolo_data'))# xyolo\u5404\u79cd\u6570\u636e\u7684\u4fdd\u5b58\u8def\u5f84\uff0c\u5305\u5916\uff0c\u9488\u5bf9\u4e8e\u9879\u76eeself.outer_xyolo_data_dir=abspath('./xyolo_data')# yolo3\u9884\u8bad\u7ec3\u6743\u91cd\u4e0b\u8f7d\u5730\u5740self.pre_training_weights_url='https://pjreddie.com/media/files/yolov3.weights'# \u4e0b\u8f7d\u6587\u4ef6\u65f6\u7684http\u4ee3\u7406\uff0c# \u5982\u9700\u8bbe\u7f6e\uff0c\u683c\u5f0f\u4e3a{'https_proxy':'host:port'}\uff0c\u5982{'https_proxy':'http://127.0.0.1:7890'},# \u8be6\u7ec6\u8bbe\u7f6e\u8bf7\u53c2\u8003 https://requests.readthedocs.io/en/master/user/advanced/#proxiesself.requests_proxies=None# Darknet\u683c\u5f0f\u7684\u9884\u8bad\u7ec3\u6743\u91cd\u8def\u5f84,\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8einner_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._pre_training_weights_darknet_path='darknet_yolo.weights'# yolo3\u9884\u8bad\u7ec3\u6743\u91cddarknet md5 hash\u503c\uff0c\u7528\u4e8e\u5904\u7406\u5f02\u5e38\u6570\u636eself.pre_training_weights_darknet_md5='c84e5b99d0e52cd466ae710cadf6d84c'# \u8f6c\u5316\u540e\u7684\u3001Keras\u683c\u5f0f\u7684\u9884\u8bad\u7ec3\u6743\u91cd\u8def\u5f84\uff0c\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8einner_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._pre_training_weights_keras_path='keras_weights.h5'# \u9884\u8bad\u7ec3\u6743\u91cd\u7684\u914d\u7f6e\u8def\u5f84\uff0c\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8einner_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._pre_training_weights_config_path='yolov3.cfg'# \u9ed8\u8ba4\u7684anchors box\u8def\u5f84\uff0c\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8einner_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._anchors_path='yolo_anchors.txt'# \u9ed8\u8ba4\u7684\u7c7b\u522b\u6587\u672c\u8def\u5f84\uff0c\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8einner_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._classes_path='coco_classes.txt'# \u8bad\u7ec3\u8f93\u51fa\u7684\u6a21\u578b\u5730\u5740,\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8eouter_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._output_model_path='output_model.h5'# \u6570\u636e\u96c6\u8def\u5f84,\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8eouter_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._dataset_path='dataset.txt'# \u662f\u5426\u5f00\u542fTensorBoard\uff0c\u9ed8\u8ba4\u5f00\u542fself.use_tensorboard=True# \u8bad\u7ec3\u65f6TensorBoard\u8f93\u51fa\u8def\u5f84\uff0c\u8bf7\u586b\u5199\u76f8\u5bf9\u4e8eouter_xyolo_data_dir\u7684\u76f8\u5bf9\u6216\u7edd\u5bf9\u8def\u5f84self._tensorboard_log_path='./tensorboard/logs'# \u662f\u5426\u5f00\u542fCheckPoint\uff0c\u9ed8\u8ba4\u5f00\u542fself.use_checkpoint=True# \u662f\u5426\u5f00\u542f\u5b66\u4e60\u7387\u8870\u51cfself.use_reduce_lr=True# \u5b66\u4e60\u7387\u8870\u51cf\u76d1\u63a7\u6307\u6807\uff0c\u9ed8\u8ba4\u4e3a\u9a8c\u8bc1lossself.reduce_lr_monitor='val_loss'# \u5b66\u4e60\u7387\u8870\u51cf\u56e0\u5b50\uff0cnew_lr = lr * factorself.reduce_lr_factor=0.1# \u8fde\u7eedpatience\u4e2aepochs\u5185\u7ed3\u679c\u672a\u6539\u5584\uff0c\u5219\u8fdb\u884c\u5b66\u4e60\u7387\u8870\u51cfself.reduce_lr_patience=3# \u662f\u5426\u5f00\u542fearly_stoppingself.use_early_stopping=True# early_stopping\u76d1\u63a7\u6307\u6807\uff0c\u9ed8\u8ba4\u4e3a\u9a8c\u8bc1lossself.early_stopping_monitor='val_loss'# \u6307\u6807\u81f3\u5c11\u53d8\u5316\u591a\u5c11\u8ba4\u4e3a\u7ed3\u679c\u6539\u5584\u4e86self.early_stopping_min_delta=0# \u8fde\u7eedpatience\u4e2aepochs\u5185\u7ed3\u679c\u672a\u6539\u5584\uff0c\u5219\u63d0\u524d\u7ed3\u675f\u8bad\u7ec3self.early_stopping_patience=10# yolo\u9ed8\u8ba4\u52a0\u8f7d\u7684\u6a21\u578b\u8def\u5f84(\u6700\u597d\u586b\u5199\u7edd\u5bf9\u8def\u5f84)\uff0c\u4f18\u5148\u7ea7\u8bbe\u7f6e\u89c1\u4e0b\u65b9model_path\u65b9\u6cd5self._model_path=''# \u76ee\u6807\u68c0\u6d4b\u5206\u6570\u9608\u503cself.score=0.3# \u4ea4\u5e76\u6bd4\u9608\u503cself.iou=0.45# \u6a21\u578b\u56fe\u7247\u5927\u5c0fself.model_image_size=(416,416)# GPU\u6570\u91cfself.gpu_num=1# \u8bad\u7ec3\u65f6\u7684\u9a8c\u8bc1\u96c6\u5206\u5272\u6bd4\u4f8b\uff0c\u9ed8\u8ba4\u4e3a0.1\uff0c# \u5373\u5c06\u6570\u636e\u96c6\u4e2d90%\u7684\u6570\u636e\u7528\u4e8e\u8bad\u7ec3\uff0c10%\u7684\u7528\u4e8e\u6d4b\u8bd5self.val_split=0.1# \u8bad\u7ec3\u5206\u4e3a\u4e24\u6b65\uff0c\u7b2c\u4e00\u6b65\u51bb\u7ed3\u5927\u591a\u6570\u5c42\u8fdb\u884c\u8bad\u7ec3\uff0c\u7b2c\u4e8c\u6b65\u89e3\u51bb\u8fdb\u884c\u5fae\u8c03# \u662f\u5426\u5f00\u542f\u51bb\u7ed3\u8bad\u7ec3\uff0c\u5efa\u8bae\u5f00\u542fself.frozen_train=True# \u51bb\u7ed3\u65f6\uff0c\u8bad\u7ec3\u7684epoch\u6570self.frozen_train_epochs=50# \u51bb\u7ed3\u65f6\uff0c\u8bad\u7ec3\u7684batch_sizeself.frozen_batch_size=32# \u51bb\u7ed3\u65f6\u7684\u521d\u59cb\u5b66\u4e60\u7387self.frozen_lr=1e-3# \u662f\u5426\u5f00\u542f\u89e3\u51bb\u8bad\u7ec3\uff0c\u5efa\u8bae\u5f00\u542fself.unfreeze_train=True# \u89e3\u51bb\u65f6\uff0c\u8bad\u7ec3\u7684epoch\u6570self.unfreeze_train_epochs=50# \u89e3\u51bb\u65f6\uff0c\u8bad\u7ec3\u7684batch_size.\u6ce8\u610f\uff0c\u89e3\u51bb\u65f6\u8bad\u7ec3\u5bf9GPU\u5185\u5b58\u9700\u6c42\u91cf\u975e\u5e38\u5927\uff0c\u8fd9\u91cc\u5efa\u8bae\u8bbe\u7f6e\u5c0f\u4e00\u70b9self.unfreeze_batch_size=1# \u89e3\u51bb\u65f6\u7684\u521d\u59cb\u5b66\u4e60\u7387self.unfreeze_lr=1e-4def__setattr__(self,key,value):_key='_{}'.format(key)ifkeynotinself.__dict__and_keyinself.__dict__:self.__dict__[_key]=valueelse:self.__dict__[key]=value@classmethoddefmake_dir(cls,path):ifnotexists(path):mkdir(path)@classmethoddefjoin_and_abspath(cls,path1,path2):returnabspath(join(path1,path2))definner_abspath(self,filename):self.make_dir(self.inner_xyolo_data_dir)returnself.join_and_abspath(self.inner_xyolo_data_dir,filename)defouter_abspath(self,filename):self.make_dir(self.outer_xyolo_data_dir)returnself.join_and_abspath(self.outer_xyolo_data_dir,filename)@propertydefpre_training_weights_darknet_path(self):returnself.inner_abspath(self._pre_training_weights_darknet_path)@propertydefpre_training_weights_config_path(self):returnself.inner_abspath(self._pre_training_weights_config_path)@propertydefpre_training_weights_keras_path(self):returnself.inner_abspath(self._pre_training_weights_keras_path)@propertydefanchors_path(self):returnself.inner_abspath(self._anchors_path)@propertydefclasses_path(self):returnself.inner_abspath(self._classes_path)@propertydefoutput_model_path(self):returnself.outer_abspath(self._output_model_path)@propertydefdataset_path(self):returnself.outer_abspath(self._dataset_path)@propertydeftensorboard_log_path(self):returnself.outer_abspath(self._tensorboard_log_path)@propertydefmodel_path(self):\"\"\"Yolo\u6a21\u578b\u9ed8\u8ba4\u52a0\u8f7d\u7684\u6743\u91cd\u7684\u8def\u5f84\u3002\u6309\u7167 _model_path > output_model_path > pre_training_weights_keras_path \u7684\u4f18\u5148\u7ea7\u9009\u62e9\uff0c\u5373\uff1a\u5982\u679c\u8bbe\u7f6e\u4e86_model_path,\u9009\u62e9_model_path\u5426\u5219\uff0c\u5982\u679c\u8bbe\u7f6e\u4e86output_model_path\u4e14\u8def\u5f84\u5b58\u5728\uff0c\u9009\u62e9output_model_path\u5426\u5219\uff0c\u9009\u62e9pre_training_weights_keras_path\"\"\"_model_path=getattr(self,'_model_path','')if_model_path:returnabspath(_model_path)ifself._output_model_pathandexists(self.output_model_path):returnself.output_model_pathreturnself.pre_training_weights_keras_path\u914d\u7f6e\u9879\u90fd\u6709\u6ce8\u91ca\u8bf4\u660e\uff0c\u5c31\u4e0d\u518d\u591a\u8bb2\u4e86\u3002\u8fd9\u91cc\u6211\u8fd8\u60f3\u63d0\u4e00\u4e0bmodel_path\u8fd9\u4e2aproperty\u3002model_path\u51b3\u5b9a\u4e86xyolo\u5728\u8fdb\u884c\u68c0\u6d4b\u65f6\uff0c\u4f1a\u52a0\u8f7d\u90a3\u4e2a\u6a21\u578b\u6587\u4ef6\u3002\u5b83\u7684\u9009\u62e9\u903b\u8f91\u5982\u4e0b\uff1a\u6309\u7167_model_path>output_model_path>pre_training_weights_keras_path\u7684\u4f18\u5148\u7ea7\u9009\u62e9\uff0c\u5373\uff1a\u5982\u679c\u8bbe\u7f6e\u4e86_model_path,\u9009\u62e9_model_path(3\u3001\u4f7f\u7528\u81ea\u5df1\u7684\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u4e2d\u68c0\u6d4b\u90e8\u5206\u5c31\u662f\u8fd9\u79cd\u60c5\u51b5)\u5426\u5219\uff0c\u5982\u679c\u8bbe\u7f6e\u4e86output_model_path\u4e14\u8def\u5f84\u5b58\u5728\uff0c\u9009\u62e9output_model_path\uff08\u4e5f\u5c31\u662f\u8bf4\uff0c\u56e0\u4e3a\u8bbe\u7f6e\u4e86_output_model_path\uff0c\u6240\u4ee5\u5047\u8bbe3\u3001\u4f7f\u7528\u81ea\u5df1\u7684\u6570\u636e\u8bad\u7ec3\u6a21\u578b\u4e2d\u6ca1\u914d\u7f6emodel_path\uff0c\u5b83\u5728\u68c0\u6d4b\u65f6\u4e5f\u80fd\u591f\u6b63\u786e\u52a0\u8f7d\u6a21\u578b\uff09\u5426\u5219\uff0c\u9009\u62e9pre_training_weights_keras_path(\u4e5f\u5c31\u662f\u8f6c\u6362\u540e\u7684\u5b98\u65b9\u9884\u8bad\u7ec3\u6a21\u578b\uff0c\u53731\u3001\u4f7f\u7528\u5b98\u65b9\u9884\u8bad\u7ec3\u6743\u91cd\uff0c\u8fdb\u884c\u76ee\u6807\u68c0\u6d4b\u6d4b\u8bd5\u4e2d\u7684\u60c5\u51b5)5\u3001yolo\u5bf9\u8c61\u7684\u51e0\u4e2a\u5e38\u7528\u65b9\u6cd5\u4e0a\u9762\u51e0\u4e2a\u68c0\u6d4b\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u8c03\u7528\u7684\u90fd\u662f\u540c\u4e00\u4e2a\u65b9\u6cd5\uff1aimg=yolo.detect_and_draw_image('./xyolo_data/detect.jpg')img.show()\u5b83\u7684\u8f93\u5165\u662f\u4e00\u4e2aPIL.Image.Image\u7c7b\u7684\u5b9e\u4f8b\uff0c\u6216\u8005\u4e00\u4e2a\u8868\u793a\u56fe\u7247\u8def\u5f84\u7684\u5b57\u7b26\u4e32\uff0c\u8fd4\u56de\u7684\u662f\u68c0\u6d4b\u5e76\u753b\u4e0a\u6846\u6846\u6807\u8bb0\u7684\u56fe\u7247\u5bf9\u8c61\uff0c\u4e5f\u662fPIL.Image.Image\u7c7b\u7684\u5b9e\u4f8b\u3002\u770b\u4e00\u4e0b\u5b83\u7684\u4ee3\u7801\uff1adefdetect_and_draw_image(self,image:typing.Union[Image.Image,str],draw_label=True)->Image.Image:\"\"\"\u5728\u7ed9\u5b9a\u56fe\u7247\u4e0a\u505a\u76ee\u6807\u68c0\u6d4b\uff0c\u5e76\u6839\u636e\u68c0\u6d4b\u7ed3\u679c\u5728\u56fe\u7247\u4e0a\u753b\u51fa\u6846\u6846\u548c\u6807\u7b7eArgs:image: \u8981\u68c0\u6d4b\u7684\u56fe\u7247\u5bf9\u8c61\uff08PIL.Image.Image\uff09\u6216\u8def\u5f84(str)draw_label: \u662f\u5426\u9700\u8981\u4e3a\u6846\u6846\u6807\u6ce8\u7c7b\u522b\u548c\u6982\u7387Returns:\u6dfb\u52a0\u4e86\u68c0\u6d4b\u7ed3\u679c\u7684\u56fe\u7247\u5bf9\u8c61\"\"\"predicted_results=self.detect_image(image)img=self.draw_image(image,predicted_results,draw_label=draw_label)returnimg\u53ef\u4ee5\u770b\u5230\uff0c\u8fd9\u4e2a\u65b9\u6cd5\u5b9e\u9645\u4e0a\u662f\u8c03\u7528\u4e86\u4e24\u4e2a\u65b9\u6cd5\uff0cdetect_image\u7528\u6765\u83b7\u53d6\u68c0\u6d4b\u7ed3\u679c\uff0cdraw_image\u7528\u6765\u5728\u56fe\u7247\u4e0a\u7ed8\u5236\u68c0\u6d4b\u4fe1\u606f\u3002\u5982\u679c\u9700\u8981\u7684\u8bdd\uff0c\u6211\u4eec\u4e5f\u53ef\u4ee5\u76f4\u63a5\u8c03\u7528\u8fd9\u4e24\u4e2a\u65b9\u6cd5\uff0c\u6bd4\u5982\u5f53\u6211\u53ea\u9700\u8981\u83b7\u53d6\u56fe\u7247\u4e0a\u7684\u76ee\u6807\u68c0\u6d4b\u7ed3\u679c\u65f6\uff0c\u6211\u53ea\u9700\u8981\u8c03\u7528detect_image\u5373\u53ef\uff0c\u56e0\u4e3a\u6211\u5e76\u4e0d\u5173\u5fc3\u56fe\u7247\u7684\u7ed8\u5236\u3002\u4e0b\u9762\u9644\u4e0a\u8fd9\u4e24\u4e2a\u65b9\u6cd5\u7684\u63a5\u53e3\u8bf4\u660e\uff1adefdetect_image(self,img:typing.Union[Image.Image,str])->typing.List[typing.Tuple[str,int,float,int,int,int,int]]:\"\"\"\u5728\u7ed9\u5b9a\u56fe\u7247\u4e0a\u505a\u76ee\u6807\u68c0\u6d4b\u5e76\u8fd4\u56de\u68c0\u6d4b\u7ed3\u679cArgs:img: \u8981\u68c0\u6d4b\u7684\u56fe\u7247\u5bf9\u8c61\uff08PIL.Image.Image\uff09\u6216\u8def\u5f84(str)Returns:[[\u7c7b\u522b\u540d\u79f0,\u7c7b\u522b\u7f16\u53f7,\u6982\u7387,\u5de6\u4e0a\u89d2x\u503c,\u5de6\u4e0a\u89d2y\u503c,\u53f3\u4e0b\u89d2x\u503c,\u53f3\u4e0b\u89d2y\u503c],...]\"\"\"passdefdraw_image(self,img:typing.Union[Image.Image,str],predicted_results:typing.List[typing.Tuple[str,int,float,int,int,int,int]],draw_label=True)->Image.Image:\"\"\"\u7ed9\u5b9a\u4e00\u5f20\u56fe\u7247\u548c\u76ee\u6807\u68c0\u6d4b\u7ed3\u679c\uff0c\u5c06\u76ee\u6807\u68c0\u6d4b\u7ed3\u679c\u7ed8\u5236\u5728\u56fe\u7247\u4e0a\uff0c\u5e76\u8fd4\u56de\u7ed8\u5236\u540e\u7684\u56fe\u7247Args:img: \u8981\u68c0\u6d4b\u7684\u56fe\u7247\u5bf9\u8c61\uff08PIL.Image.Image\uff09\u6216\u8def\u5f84(str)predicted_results: \u76ee\u6807\u68c0\u6d4b\u7684\u7ed3\u679c\uff0c[[\u7c7b\u522b\u540d\u79f0,\u7c7b\u522b\u7f16\u53f7,\u6982\u7387,\u5de6\u4e0a\u89d2x\u503c,\u5de6\u4e0a\u89d2y\u503c,\u53f3\u4e0b\u89d2x\u503c,\u53f3\u4e0b\u89d2y\u503c],...]draw_label: \u662f\u5426\u9700\u8981\u4e3a\u6846\u6846\u6807\u6ce8\u7c7b\u522b\u548c\u6982\u7387Returns:\u6dfb\u52a0\u4e86\u68c0\u6d4b\u7ed3\u679c\u7684\u56fe\u7247\u5bf9\u8c61\"\"\"pass\u540e\u8bddxyolo\u5305\u8fd8\u6ca1\u6709\u8fdb\u884c\u8fc7\u5145\u8db3\u7684\u6d4b\u8bd5\uff08\u6211\u81ea\u5df1\u505a\u8fc7\u4f7f\u7528\u6d4b\u8bd5\uff0c\u4f46\u5f88\u660e\u663e\uff0c\u4e0d\u80fd\u8986\u76d6\u5230\u5168\u90e8\u7684\u60c5\u51b5\uff09\uff0c\u6240\u4ee5\u51fa\u4e2a\u4ec0\u4e48bug\u4e5f\u662f\u53ef\u4ee5\u7406\u89e3\u7684\u5427\uff08\u522b\u6253\u6211\uff0c\u522b\u6253\u6211\uff0c\u62b1\u5934\uff09\uff1f\u78b0\u5230\u4ec0\u4e48bug\u7684\u8bdd\u6b22\u8fce\u8054\u7cfb\u6211\u54c8\u3002PS:xyolo\u6700\u4f4e\u652f\u6301\u7684TensorFlow\u7248\u672c\u662f2.2\uff0c\u66f4\u4f4e\u7248\u672c\u7684\u6ca1\u6709\u6d4b\u8bd5\u548c\u9002\u914d\uff0c\u4e0d\u4fdd\u8bc1\u80fd\u7528\u3002\u7cbe\u529b\u6709\u9650\uff0c\u6240\u4ee5\u4f4e\u7248\u672c\u4e5f\u4e0d\u6253\u7b97\u9002\u914d\u4e86\uff0c\u6240\u4ee5\u5982\u679c\u662f\u4f4e\u7248\u672c\u5bfc\u81f4\u7684\u95ee\u9898\uff0c\u6211\u53ef\u80fd\u5c31\u4e0d\u505a\u5904\u7406\u4e86\uff0c\u8bf7\u89c1\u8c05~\u6700\u540e\uff0c\u5982\u679c\u60a8\u559c\u6b22\u8fd9\u4e2a\u9879\u76ee\u7684\u8bdd\uff0c\u7ed9\u4e2astar\u5457~\u611f\u8c22\u652f\u6301~"} +{"package": "xypath", "pacakge-description": "XYPath is aiming to be XPath for spreadsheets: it offers a framework for\nnavigating around and extracting values from tabular data."} +{"package": "xypattern", "pacakge-description": "xypatternDescriptionA simple small library to handle x-y patterns, such as are collected with x-ray diffraction or Raman spectroscopy.InstallationpipinstallxypatternUsage ExamplesReading a filefromxypatternimportPatternimportmatplotlib.pyplotaspltp1=Pattern.from_file('path/to/file')p1.scaling=0.5p1.offset=0.1plt.plot(p1.x,p1.y)plt.show()Use a background patternp2=Pattern.from_file('path/to/file')p2.scaling=0.9p1.background=p2Scale and stitch multiple patternsp1=Pattern.from_file('path/to/file1')p2=Pattern.from_file('path/to/file2')p3=Pattern.from_file('path/to/file3')fromxypattern.combineimportscale_patterns,stitch_patternspatterns=[p1,p2,p3]scale_patterns(patterns)stitched_pattern=stitch_patterns(patterns)"} +{"package": "xy-pic-crawler", "pacakge-description": "Search The Picture From Baidu By The Keywords"} +{"package": "xy-picporn", "pacakge-description": "Picture Porn Info"} +{"package": "xy-pic-search", "pacakge-description": "Search The Picture From Baidu By The Keywords"} +{"package": "xy-pictalk", "pacakge-description": "picture description"} +{"package": "xy-pinyin", "pacakge-description": "get the hanzi to pinyin"} +{"package": "xyplot", "pacakge-description": "xyplot \ud83d\udcc8Plotting with python made easyAre you tired of replicating common steps that are needed to plot even a simple polynomial functions in python's infamous Matplotlib?Worry no more! Presentingxyplot! Plot polynomials easily and, more importantly, pythonically!For example, to plot a polynomial best fit curve you only need to:fromxyplotimportCurve# Our datax,y=[0,2,4,6,8],[0.8,-1.1,1.06,6.75,16.54]# A simple curve object with data and degree of polynomialcurve=Curve(x,y,2)# Set the x, y axis labels and Titlecurve.set(xlabel=\"Labels are fun and easy\",ylabel=\"Oooh see him Go!\",title=\"I am an easy Graph\")# Label our data and curvecurve.createPlot(plotLabel=\"Label for the Curve\",dataLabel=\"Label for our DATA\",)curve.save(\"sample.png\")# Save our graph in high qualityMakes sense right? Seeexamplesfor other examples.Fair WarningThis is just a high level sensible wrapper to the matplotlib and numpy package. Its aim is to reduce the workload necessary to make very basic plots.To make more extensive and customizable plots, refer tomatplotlibWhy this effort?Some of the more inquistive and experienced would be asking why the hell did I create an entire package that can only plot polynomials. Because there was nothing similar in matplotlib and I wanted to help those who have only little knowledge of python plot amazing graphs in as few lines and headaches as possible.For those who still like control, you always have the fig, ax attributes of the curve class available for exploitation! And then, if you are not satisfied, try the OG Matplotlib!InstallationTo install the program run$ pip install xyplotIf you are using Ubuntu run this instead:$ pip3 install xyplotTo check whether the installation was successful, try importing it:fromxyplotimportCurveIf the import worked, the package is most probably installed.Note that you may want to install some other python libraries to fully enjoy theScientific Pythonexperience.These are recommended:$ pip install --user numpy scipy matplotlib ipython jupyter pandas sympy noseDocumentation?Documentation is like sex: when it is good, it is very, very good; and when it is bad, it is better than nothing. \u2014Dick B.With that said, the documentation can be found here:http://www.xypnox.com/xyplot/xyplot/index.htmlContributions?Are welcome!"} +{"package": "xy-pminfo", "pacakge-description": "Get The PM2.5 Info"} +{"package": "xypy", "pacakge-description": "Simulating Supervised Learning DataWithxypy.Xy()you can convienently simulate supervised learning data, e.g. regression and classification problems.\nThe simulation can be very specific, since there are many degrees of freedom for the user. For instance, the functional\nshape of the nonlinearity is user-defined as well. Interactions can be formed and (co)variances altered. For a more\nspecific motivation you can visit ourblog.\nI have adapted this package from my R version, which you can check outhere.UsageYou can can checkout details about the package ontestPYPIor onGitHub.You can convienently install the package via PYPI with the following command.pip install xypyThere is an example test script on myGitHub, which will you get started\nwith the simulation.Simulate dataYou can simulate regression and classification data with interactions and a user-specified non-linearity. With\nthestnargument you can alter the signal to noise ratio of your simulation. I strongly encourage you to\nread thisblog post,\nwhere I've analyzed OLS coefficients with different signal to noise ratios.# load the library\nfrom xypy import Xy\n# simulate regression data\nmy_sim = Xy(n = 1000, \n numvars = [10,10], \n catvars = [3, 2], \n noisevars = 50, \n stn = 100.0)\n\n# get a glimpse of the simulation\nmy_sim\n\n# plot the true underlying effects\nmy_sim.plot()\n\n# extract the data\nX, y = my_sim.data\n\n# extract the true underlying model weights\nmy_sim.coef_Feature SelectionYou can extract a feature importance of your simulation. For instance, to benchmark feature selection algorithms.\nYou can read up on a small benchmark I did with this feature\non ourblog.\nYou can perform the same analysis easily in Python as well.# Feature Importance \nmy_sim.varimp()Feel free tocontactme with input and ideas."} +{"package": "xyq", "pacakge-description": "No description available on PyPI."} +{"package": "xy-qq", "pacakge-description": "Get The QQ Luck From JiSu API"} +{"package": "xy-qrcode", "pacakge-description": "Generate color qrcode"} +{"package": "xy-qrdecode", "pacakge-description": "Get constellation Info From juhe API"} +{"package": "xyqsister", "pacakge-description": "\u7ed9\u8c22\u59b9\u59b9\u5199\u7684\u4e00\u4e2a\u4e13\u5c5e\u5c0f\u63d2\u4ef6"} +{"package": "xy-raokouling", "pacakge-description": "Get The rao kou ling"} +{"package": "xyRemovebg", "pacakge-description": "remove"} +{"package": "xyrha-flush", "pacakge-description": "xyrha-flushA tool runner for C++ development."} +{"package": "xy-riddle", "pacakge-description": "Get The riddle"} +{"package": "xy-scene-object", "pacakge-description": "Scene Object Recognition"} +{"package": "xyscreens", "pacakge-description": "Python library to control XY Screens projector screens and projector lifts.Python library to control XY Screens projector screens and projector lifts\nover the RS-485 interface.XY Screens is an OEM manufacturer of projector screens and projector lifts.HardwareI use a cheap USB RS-485 controler from eBay to talk to the projector screen\nwhere position 5 of the RJ25 connector is connected to D+ and position 6 to\nthe D-.See the documentation of your specific device on how to wire yours correctly.ProtocolThis are the protocol details:2400 baud 8N1Up command : 0xFF 0xAA 0xEE 0xEE 0xDDDown command: 0xFF 0xAA 0xEE 0xEE 0xEEStop command: 0xFF 0xAA 0xEE 0xEE 0xCCKnown to workiVisions Electro M SeriesNot tested but uses the same protocol according to the documentation:iVisions Electro L/XL/Pro/HD SeriesiVisions PL Series projector liftElite ScreensKIMEXDELUXXPlease let me know if your projector screen or projector lift works with this\nlibrary so I can improve the overview of supported devices.InstallationYou can install the Python XY Screens library using the Python package manager\nPIP:pip3 install xyscreensxyscreens CLIYou can use the Python XY Screens library directly from the command line to\nmove your screen up or down or to stop the screen using the following syntax:Move the screen down:python3 -m xyscreens downStop the screen:python3 -m xyscreens stopMove the screen up:python3 -m xyscreens upIf you add the arguments--wait
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