Saravanan666/pypi-org huggingface dataset:
Package: arend
ArendA simple producer-consumer library for the Beanstalkd queue.InstallationHit the command:pipinstallarendBasic UsageIn your code:fromarendimportarend_taskfromarend.backends.mongoimportMongoSettingsfromarend.brokersimportBeanstalkdSettingsfromarend.settingsimportArendSettingsfromarend.workerimportconsumersettings=ArendSettings(beanstalkd=BeanstalkdSettings(host="beanstalkd",port=11300),backend=MongoSettings(mongo_connection="mongodb://user:pass@mongo:27017",mongo_db="db",mongo_collection="Tasks"),)@arend_task(queue="my_queue",settings=settings)defdouble(num:int):return2*numdouble(2)# returns 4task=double.apply_async(args=(4,))# It is sent to the queueconsumer(queue="my_queue",settings=settings)# consume tasks from the queueTask=settings.get_backend()# you can check your backend for the resulttask=Task.get(uuid=task.uuid)asserttask.result==4BackendsThe available backends to store logs areMongoandRedis.
Please read thedocsfor further information.Setting your backend with environment variablesYou can set your backend by defining env vars.
TheAREND__prefix indicates that it belongs to the Arend.# RedisAREND__REDIS_HOST='redis'AREND__REDIS_DB='1'AREND__REDIS_PASSWORD='pass'...# MongoAREND__MONGO_CONNECTION='mongodb://user:pass@mongo:27017'AREND__MONGO_DB='db'AREND__MONGO_COLLECTION='logs'...In your code:fromarendimportarend_taskfromarend.workerimportconsumer@arend_task(queue="my_queue")defdouble(num:int):return2*numdouble.apply_async(args=(4,))# It is sent to the queueconsumer(queue="my_queue")DocumentationPlease visit thislinkfor documentation.
Package: arepa
ArepaArepa-making utilityFree software: MIT licenseDocumentation:https://arepa.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.0 (2018-02-25)Minor release, includes code cleanup0.1.1 (2018-02-15)Second release on PyPI.0.1.0 (2018-02-11)First release on PyPI.
Package: areplay
Apache Replay is a command line tool that reads Apache log files and replays it on a remote server in real time. It’s goal it’s to load test HTTP/HTTPS servers with the same traffic that is received on another server.This tool is written in Python and it usesapache-log-parser,requestsandgeventlibraries.Main FeaturesReal time replay load testingAccept any Apache log formatSupport Basic AuthenticationURL match and ignore filtersInstallationOnLinux, first install python development and libevent packages using system package manager:# Debian-based distributions (eg Ubuntu, ...):$sudoapt-getinstallpython-devlibevent-dev# RPM-based distributions:$yuminstallpython-devellibevent-*Then it can be installed from PyPi usingpip:$pipinstallareplayBasic usage$areplayhttp://test.example.com/var/log/apache2/access.logSynopsis:$areplay--helpusage:areplay[-h][-v][-aAUTH][-wWORKERS][-mMATCH][-iIGNORE][-d][-fFORMAT][-sv][-iuIGNORE_URL]serverlog_filepositionalarguments:serverRemoteServerlog_fileApachelogfilepathoptionalarguments:-h,--helpShowthishelpmessageandexit-v,--versionShowprogram'sversionnumberandexit-aAUTH,--authAUTHBasicauthenticationuser:password-wNUM,--workersNUMWorkerspoolsize-d,--dry-runOnlyprintsURLs-fFORMAT,--formatFORMATApachelogformat-iIGNORE,--ignoreIGNOREIgnorematchingrequests-iuURL,--ignore-urlURLURLtohitwhenURLfromlogisignored-mMATCH,--matchMATCHOnlyprocessmatchingrequests-sv,--skip-verifySkipSSLcertificateverifyExamplesBasic auth:$areplay-ausername:passwordhttp://test.example.comaccess.logURL filtering - ignore js and css- use | (pipe) to separate keywords:$areplay-i'.css|.js'http://test.example.comaccess.logURL filtering - process only js and css- use | (pipe) to separate keywords:$areplay-m'.css|.js'http://test.example.comaccess.logCustom Apache Log format- get LogFormat for Apache configuration file:$cat/etc/apache2/apache2.conf|grepLogFormat|grepcombinedLogFormat"%h %l %u %t \"%r\" %>s %O \"%{Referer}i\" \"%{User-Agent}i\""combined$areplay-f"%h %l %u %t \"%r\" %>s %O \"%{Referer}i\" \"%{User-Agent}i\""http://test.example.comaccess.logChange LogPlease seeCHANGELOG.LicencePlease seeLICENSE.AcknowledgmentsThank you to the people fromBoom!for inspiration and Dinko Korunic for snippet (GeventTail).
Package: ares-data
Ares Dataares_dataje Python knihovna pro snadné získávání dat o společnostech z Českého obchodního rejstříku ARES.FunkceJednoduché rozhraní pro získávání dat o společnostech podle IČO.Jako objekt AresCompany.InstalacePro instalaciares_datapoužijte následující příkaz:pipinstallares_dataPoužitíPoužití knihovny ares_data je jednoduché. Zde je příklad, jak získat data o společnosti:fromares_dataimportget_company_dataico="60193336"company_data=get_company_data(ico)print(company_data)Tento příklad demonstruje, jak naimportovat a použít funkci get_company_data z knihovny ares_data. Funkce bere jako parametr identifikační číslo organizace (IČO). Pokud chcete rozšířit data o hlavní ekonomickou činnost společnosti podle CZNACE, přidejte parametr main_cz_nace_important=True. To však celý proces významně zpomalí, protože dochází k parsování stránkyhttps://apl.czso.cz.Formát vráceného objektu (pokud není chybový), je:@dataclassclassAresCompany:ico:strname:Optional[str]address:Optional[str]psc:Optional[str]legal_form:Optional[str]business_fields:Optional[List[str]]size:Optional[str]main_cz_nace:Optional[str]=None
Package: ares-util
Ares_utilLatest releaseCIDependenciesPředstaveníJednoduchý nástroj pro validaci1českého IČ. U předaného IČ je nejdříve ověřen jeho kontrolní součet (vizReference) a dle výsledku se následně zasílá požadavek naARES XML API.Pokud je IČ validní, vrací nástrojdictse základními údaji o firmě (obchodní název, adresa).Podmínky provozu ARES APIMinisterstvo financí vyhrazuje právo omezit nebo znemožnit přístup k www aplikaci ARES uživatelům, kteří:odešlou k vyřízení více než 1000 dotazů v době od 8:00 hod. do 18:00 hod.,odešlou k vyřízení více než 5000 dotazů v době od 18:00 hod. do 8:00 hod. rána následujícího dne,opakovaně posílají nesprávně vyplněné dotazy,opakovaně posílají stejné dotazy,mají větší počet současně zadaných dotazů (pro automatizované XML dotazy),obcházejí povolené limity využíváním dotazování z většího množství IP adres, -automatizovaně propátrávají databázi náhodnými údaji nebo generují většinu nesprávných dotazů.—Zdroj:Podmínky provozu ARES API.InstalacePodporované verze Pythonu jsoupypy,pypy3,2.7,3.5,3.6a3.7.pipinstall--upgradeares-utilPoužitípython>>>fromares_util.aresimportcall_ares>>>call_ares(42)False>>>call_ares('68407700'){u'legal':{u'company_vat_id':u'CZ68407700',u'company_name':u'České vysoké učení technické v Praze',u'legal_form':u'601',u'company_id':u'68407700'},u'address':{u'city':u'Praha',u'region':u'Hlavní město Praha',u'street':u'Zikova 1903/4',u'city_part':u'Dejvice',u'zip_code':u'16000'}}Django podporaPodporované verze Djanga jsou1.11.x(LTS),2.0.xa2.1.x.K dispozi jsou dvaDjango validátoryformulářových polí:czech_company_id_numeric_validator- Ověřuje, zda IČ splňuje
statické parametry, tj. 7 nebo 8 číslic a kontrolní součet.czech_company_id_ares_api_validator- Platnost IČ ověřuje pomocí
ARES API. Tento validátor před ARES požadavkem rovněž ověřuje
statické parametry, proto byneměly být použity oba validátory
zároveň.Použití ve formulářifromares_util.validatorsimportczech_company_id_numeric_validator,czech_company_id_ares_api_validatorfromdjangoimportforms# forms.pyclassDemoForm(forms.Form):company_id=forms.IntegerField(required=True,validators=[czech_company_id_ares_api_validator])Referencehttp://www.abclinuxu.cz/blog/bloK/2008/10/kontrola-ic,http://latrine.dgx.cz/jak-overit-platne-ic-a-rodne-cisloLokální vývojChcete-li upravit doplněk lokálně, jednoduše stáhněte zdrojové kódy a nainstalujte závislosti:pipinstall-rrequirements.txt--upgradeTesty spustíte pomocítoxneboinv test. Využít můžete i přibalený Flask server pro lokální testování. Stačí spustit:python.\server.py*Runningonhttp://127.0.0.1:5000/(PressCTRL+Ctoquit)*Restartingwithstata v prohlížeči otevřít např.:http://127.0.0.1:5000/42.Technické informaceXML response z ARESu je zpracována pomocíxmltodict.LicenceThe MIT License (MIT)Copyright (c) 2013–2019 Vašek Dohnal (@illagrenan)
Package: aresy
## Home
Built on popular scientific computing toolkits, aresy aims to make it easy to process large-scale data on a single server. aresy treats the whole data flow as a computation graph, where the input data will be put into placeholders, and you can perform nearly any python-based transformation by extending the graph. aresy was designed with the following principles:Compatible with python data science ecosystem, such as numpy, pytorch, tensorflow modules.Able to process cross-type, cross-domain, cross-granularity data simultaneously.Easy to build a large feature generator, a transformer or even a data loader to feed preprocessed data into deep learning models.## Installation`shell python setup.py install `## Package Referencearesy.formattingaresy.formatting.TSVDataLoaderaresy.formatting.TSVPlaceholderaresy.preprocessingaresy.preprocessing.WrangleFloataresy.preprocessing.WrangleStraresy.preprocessing.WrangleNormalDatetimearesy.aggregatingaresy.aggregating.Sumaresy.aggregating.Meanaresy.aggregating.Stdaresy.aggregating.Maxaresy.aggregating.Minaresy.aggregating.Quantilearesy.utilsaresy.wrap_outputs_to_json
Package: arexecute
arexecuteApplication to record actions on the computer and then execute them in a controlled way.Installationarexecute is in pypi, run the following command to install:python -m pip install arexecuteAfter installation, all commands that are run using the module as a direct application can be run using either one of the following commands:python -m arexecute <arexecute-commands>or:arexecute <arexecute-commands>For the examples we will stick to the second one.RecordingTo record into a file named "example.json", run the following line:arexecute -r exampleHere "example" can be a filename with a path different from the current directory,
or it can be only a filename, either with the .json extension or without it.The instructions for recording are the following:(->) Denotes press first one key, then the nextCommandActionAltStop recording any timeW -> any numberAdd waiting time of seconds equal to the number, floats allowed with a dotIStarts writing anything, commands allowedCaps LockStops any action (for example set the final wait time or stop clicking)CtrlMove mouse to current mouse positionShift n timesClicks n times in the last mouse position or current if there were no movements beforevAdds a variable to be defined laterIn this way, one can record mouse movements, clicks, write variables, etc.ExecutingTo execute, run the following line:arexecute -e exampleThis will execute the recorded example once. In order to run more than one time, add the -i flag. This flag can be used with an integer determining the amount of iterations to be done, or without an integer, in which case it will run in an endless loop.
If the endless option is chosen, have in mind that quickly moving the mouse to the top right corner of the screen will stop the execution as a safe option incorporated on pyautogui.
In order for this command to work, a previous recording named "example.json" in the same
directory, or in the one specified by the filename must exist.Using VariablesWhen recording, typing 'v' will add a new variable in place. In order to define this variable, you have to run the execution script manually, it cant be run using the command line. Also when running it manually you have to specify the variables.Usage on a .py fileTo use this program in a python script, just import recorder and executer and start using the Recorder and Executer classes like in the next example where while recording, two variables where defined:from arexecute import recorder, executer

fname = "testing"
r = recorder.Recorder(fname, verbose=1)
r.start()

e = executer.Executer(fname, variables=["variable 1", "variable 2"], verbose=1)
e.start()
Package: are-you-a-human
SUMMARYDocumentation and latest version:http://portal.areyouahuman.com/helpGet an AYAH publisher key:https://portal.areyouahuman.com/Discussion group:http://support.areyouahuman.com/Copyright (c) 2011 AYAH LLChttp://www.areyouahuman.comBY USING THIS SOFTWARE YOU AGREE TO THE TERMS AND CONDITIONS FOUND AT:http://portal.areyouahuman.com/termsAndConditionsINSTALLATIONThe AYAH Python Integration Library is compatible with Python 2.x and 3.x. (It
was built and tested on versions 2.7.x and 3.2.x.) Python 3.x requires an extra
installation step as described below.Python 2.x Installation:Download and extract the appropriate source distribution for your OS.Install the package:python setup.py installPython 3.x Installation:Download and extract the appropriate source distribution for your OS.Convert the package to Python 3.x:2to3 -wn ./ayahInstall the package:python3 setup.py installINTEGRATIONThe AYAH Python Integration Library is compatible with all web application
frameworks.Get your publisher key and scoring key fromhttps://portal.areyouahuman.com/.Import the ayah module:import ayahConfigure the ayah module when your application initializes:ayah.configure(<your-publisher-key>, <your-scoring-key>)Display the AYAH HTML on any page that requires a human:html = ayah.get_publisher_html()Django: you can pass this HTML to the view through the context or simply call
get_publisher_html() in the template.Allow the alleged human to complete the PlayThru challenge. When they’re
finished, your web page will have a hidden field on it with
id=”session_secret”.Use the value of the hidden session secret field to determine if the alleged
human passed the challenge:passed = ayah.score_result(<session-secret>)Django: the hidden field will be available in your form object:if request.method == 'POST':
    form = LoginForm(request.POST)
    if form.is_valid():
        secret = form.cleaned_data['session_secret']
        passed = ayah.score_result(secret)
        # Redirect...If you’d like to record a conversion with our system, a special bit of HTML
will need to be embedded in your ‘conversion’ page. To get that HTML, call
the following method:html = ayah.record_conversion(<session-secret>)Congratulations, your application detects humans without requiring CAPTCHA!
Package: are_you_sure
Are you sureSimple decorator to ask before evaluating a function (just one very simple function)Usage examplefromare_you_sureimportare_you_sure@are_you_suredefdangerous_function(*args,**kwargs):print(f'Running{dangerous_function.__name__}with{args,kwargs}')if__name__=='__main__':dangerous_function(1,"arg_example",name='lol')
Package: aRez
Async Python HiRez API wrapperThis project was created to simplify access to the API, as well as incorporate some data
pre-processing and consistency. I am aware thatPyRezalready exists, however this project aims to do couple of things differently:It's entirely async from the ground up, built using 'aiohttp'Uses modern objective programming approachUtilizes a local data cache to return data-rich objectsThis library is supposed to be used as a module.As of right now, only PaladinsAPI is supported.Smite support is planned - please read below.Currently supported:getgods / getchampionsandgetitemsregarding god / champion
and card / talent / shop item informationgetplayer(Player stats)getplayerbatch(Multiple player stats at once)getplayeridbyname,getplayeridsbygamertagandsearchplayersunder a single,
intuitive method (Finding the players)getfriends(Player friends)getgodranks / getchampionranks(God / Champion stats)getplayerloadouts(Player loadouts for each god / champion)getplayerstatus(Player status)getmatchhistory(Player's recent matches)getmatchdetails(Match details, by the ID or from player's recent matches)getplayeridbyportaluserid(Finding the player by their Portal ID)getmatchplayerdetails(Information about the current player's match)getplayerachievements(Player overall match stats)getmatchdetailsbatch(Fetching multiple matches at once)getmatchidsbyqueue(Fetching all matches by queue)getqueuestats(Player match stats by queue)There are plans on expanding the existing framework to incorporate the above and below:Adding documentationSupport for SmiteAPI (support Smite endpoint URL)Support for TeamsSupport forgetteamdetailsendpointSupport forgetteamplayersendpointSupport forsearchteamsendpointIf you have some experience with Smite and it's API, and would be interested in working with me
together on expanding this project, please don't hessitate to contact me
(you can find contact information below).RequirementsPython 3.8+aiohttp 2.0+ResourcesaRez DocumentationOfficial HiRez API DocumentationUsagePlease seeexample.pyfor more examples.importasyncioimportarez# import the wrapperDEV_ID=1234# your Developer ID (example)AUTH_KEY="L2U3M60A03662R24UKOMY0FIT4S2IBKU"# your Auth Key (example)asyncdefmain():# create an API instanceapi=arez.PaladinsAPI(DEV_ID,AUTH_KEY)# fetch Player statsplayer=awaitapi.get_player(5959045)# display your rankprint(player.ranked_best.rank.name)# close the API once you're done with itawaitapi.close()loop=asyncio.get_event_loop()loop.run_until_complete(main())# run the async loopSupportContactReddit:https://www.reddit.com/u/DevilXDDiscord:DevilXD#4437NotesThis is an alpha version - as of right now, everything is a subject to change.
Once both Paladins and Smite (and maybe Realm Royale) APIs are supported, this wrapper is going to
have it's v1.0 release, and I will try to manage the versioning the proper way from there.
Package: arfcnreference
arfcnreference---------------.. image:: https://travis-ci.org/sitch-io/arfcn-reference.svg?branch=master:target: https://travis-ci.org/sitch-io/arfcn-reference.. image:: https://codeclimate.com/github/sitch-io/arfcn-reference/badges/coverage.svg:target: https://codeclimate.com/github/sitch-io/arfcn-reference/coverage:alt: Test Coverage.. image:: https://codeclimate.com/github/sitch-io/arfcn-reference/badges/gpa.svg:target: https://codeclimate.com/github/sitch-io/arfcn-reference:alt: Code Climate.. image:: https://codeclimate.com/github/sitch-io/arfcn-reference/badges/issue_count.svg:target: https://codeclimate.com/github/sitch-io/arfcn-reference:alt: Issue CountARFCN reference Python module=============================This Python module contains a reference for all GSM channels by ARFCN.Installation:_____________pip install arfcnreferenceUsage:______Get a channel by uplink frequency:::>>> import arfcnreference>>> arf_ref = arfcnreference.ArfcnReference()>>> arf_ref.get_for_uplink(890.2){'band': 'GSM-900', 'downlink': 935.2, 'channel': 1}>>> arf_ref.get_for_downlink(887.4){'band': 'EGSM-900', 'uplink': 887.4, 'channel': 1011}Frequencies are returned in MHz.Getting channels for a range of frequencies:::>>> for x in arf_ref.arfcn_for_downlink_range(842, 942):...     print x...{'1853': {'band': 'GSM-1900', 'uplink': 1853, 'channel': 526}}{'1867': {'band': 'GSM-1900', 'uplink': 1867, 'channel': 596}}{'1855': {'band': 'GSM-1900', 'uplink': 1855, 'channel': 536}}{'1868': {'band': 'GSM-1900', 'uplink': 1868, 'channel': 601}}(and so on)Getting all channels in a band:::>>> for x in arf_ref.channels_in_band("GSM-850"):...     print x...{'downlink': 869.2, 'uplink': 824.2, 'channel': 128}{'downlink': 869.4, 'uplink': 824.4, 'channel': 129}{'downlink': 869.6, 'uplink': 824.6, 'channel': 130}{'downlink': 869.8, 'uplink': 824.8, 'channel': 131}{'downlink': 870, 'uplink': 825, 'channel': 132}(and so on)Testing:________run `py.test` from the root of this repo.Special thanks:_______________The reference information was lifted, with gratitude, from http://gnuradio.org/redmine/attachments/115/all_gsm_channels_arfcn.txtChangelog=========v0.1----New~~~- First working commit, provides GSM channel info.  Queryable byfrequency, channel number, band, and range of frequencies. [AshWilson]Other~~~~~- Initial commit. [Ash Wilson]
Package: arff
Weka arff file type reader for python.http://code.google.com/p/arff/http://code.google.com/p/arff/wiki/DocumentationUsage:>>> import arff>>> for row in arff.load('example.arff'):...     print(row.hair_color)...     print(row[-1])...>>> print(list(arff.load('example.arff')))[[Row(hair_color='blonde', age=17.2, patno=1),Row(hair_color='blue', age=27.2, patno=2),Row(hair_color='blue', age=18.2, patno=3)]Where this is the example file:@relation diabetics_data@attribute hair_color {blonde, black, blue}@attribute age real@attribute patno integer@datablonde, 17.2, 1blue, 27.2, 2blue, 18.2, 3----->>> data = [[1,2,'a'], [3, 4, 'john']]>>> arff.dump('result.arff', data, relation="whatever", names=['num', 'day', 'title'])results in the creation of this file:@relation whatever@attribute num integer@attribute day integer@attribute title string@data1,2,'a'3,4,'john'-----supports arff types: numeric, integer, real, stringsupports python types: int, str, floatin the future: datesTested on python 2.7 and 3.2License: BSD, do what you wish with this. Could be awesome to hear if you foundit useful and/or you have suggestions. ubershmekel at gmailBased on http://weka.wikispaces.com/ARFF+%28stable+version%29
Package: arff-converter
ARFF ConverterVersion: 0.1.0OverviewARFF Converter is a Python package designed to convert Attribute-Relation File Format (ARFF) files into Excel (XLSX) files. It currently supports the conversion from ARFF to XLSX, with potential for future expansion to other file formats.InstallationTo install ARFF Converter, use pip:pipinstallarff-converterUsageThe package provides a command-line interface for easy conversion of ARFF files to XLSX format.Command-Line UsageTo convert an ARFF file to an XLSX file, run the following command:arff-converter<path_to_arff_file><path_to_output_xlsx_file>Replace <path_to_arff_file> with the path to your ARFF file and <path_to_output_xlsx_file> with the desired output path for the XLSX file.Examplearff-converterdata.arffoutput.xlsxThis command will convert data.arff into an Excel file named output.xlsx.FeaturesConverts ARFF files to XLSX format.Command-line interface for straightforward usage.Validates ARFF file structure and content.RequirementsPython 3pandasopenpyxlDevelopmentThis package is in early development and may include additional features and support for more formats in future releases.ContributingContributions to ARFF Converter are welcome. Please feel free to submit pull requests or report issues on the GitHub repository.LicenseARFF is distributed under the MIT License. See LICENSE file for more details.
Package: arff-format-converter
Convert ARFF files to different formats.Thearff-format-convertertool allows you to convert ARFF files to various output formats. Below are the details:INSTALLpipinstallarff-format-converterSYNOPSISarff-format-converter-f<file>-o<output_folder>-fmt<output_format>EXAMPLESarff-format-converter-fdata.arff-ooutput-fmtjson
arff-format-converter-fdata.arff-ooutput-fmtxml
arff-format-converter-fdata.arff-ooutput-fmtcsv
arff-format-converter-fdata.arff-ooutput-fmtxlsx
arff-format-converter-fdata.arff-ooutput-fmtorcOPTIONS-f, --filePath to the ARFF file.-o, --outputPath to the output folder.-fmt, --formatOutput format: 'xml', 'json', 'csv', 'xlsx', 'orc'.SUPPORTED FORMATSARFF(input)XML(output)JSON(output)CSV(output)XLSX(output)ORC(Apache ORC format) (output)AUTHORWritten byShani Sinojiya.REPORTING BUGS:Report bugs toissue sectionRemember to replace"data.arff"with the actual path to your ARFF file and"output"with the desired output folder. Feel free to adapt this code snippet for other formats like XML, CSV, XLSX, or ORC as needed! ðŸš€
Package: arflow
ARFlowARFlow: A Framework for Simplifying AR Experimentation WorkflowPaper|BibTeX|Project Page|VideoWatch our demo video:Get Started With the ARFlow ServerARFlow server can be simply installed viapip:pipinstallarflowNext, you may integrate ARFlow with your own research prototype via the Python API:"""A simple example of extending the ARFlow server."""importarflowclassCustomService(arflow.ARFlowService):defon_frame_received(self,frame:arflow.DataFrameRequest):"""Called when a frame is received."""print("Frame received!")defmain():arflow.create_server(CustomService,port=8500,path_to_save="./")if__name__=="__main__":main()