Saravanan666/pypi-org huggingface dataset:
Package: slmethod
slmethodStatistical Learning Method 统计学习方法GitHub:https://github.com/iOSDevLog/slmethod方法precentronkmeans截图感知机 PerceptronKMeansPyPI 境像加速pip3install-ihttps://pypi.tuna.tsinghua.edu.cn/simpleslmethod代码规范参考：https://docs.python.org/3/tutorial.vscode/settings.json{"python.pythonPath":"/Users/iosdevlog/.Envs/slmethod/bin/python","python.linting.flake8Enabled":true,"python.formatting.provider":"yapf","python.linting.flake8Args":["--max-line-length=248"],"python.linting.pylintEnabled":false}字符串使用双引号：""安装pip3installslmethod开发本地开发pip3install-e.测试pytestslmethod-v发布python3setup.pysdistbdist_wheel
twineuploaddist/*生成 CHANGELOGnpminstall-gconventional-changelog-cli
./version.sh联系方式网站:http://2019.iosdevlog.com/微信公众号: AI 开发日志Licenseslmethod is released under the MIT license. SeeLICENSEfor details.
Package: slmpy
Smart local moving (SLM) community detection in Python/C++, modeled on the Java
version onhttps://github.com/mneedham/slm.Development:https://github.com/iosonofabio/slmpyAuthor: Fabio ZaniniLicense: MITRequirements:pybind11>=2.2,numpy,pkgconfig(seerequirements.txt)fromslmpyimportModularityOptimzeredges=[[0,1],[0,2],[0,3],[1,2],[1,3],[2,3],[3,4],[4,5],[4,6],[5,6],[7,8],]mo=ModularityOptimzer(edges)mo.fixed_nodes=[0,4]# This fixes nodes 0 and 4 to be in different communitiescommunities=mo(algorithm='smart_local_moving')# Check answerassert((communities==[0,0,0,0,1,1,1]).all())
Package: slmr
sLMRThis is a scripting system for the Last Millennium Reanalysis project,
orLMR.Package dependenciesp2k: A collection of functions used for PAGES2k dataset analysis (pip install p2k)tqdm: A fast, extensible progress bar for Python and CLI (pip install tqdm)prysm-api: The API for PRoxY System Modeling (PRYSM) (pip install prysm-api)dotmap: Dot access dictionary with dynamic hierarchy creation and ordered iteration (pip install dotmap)xarray: N-D labeled arrays and datasets in Python (pip install xarray)netCDF4: the python interface for netCDF4 format (conda install netCDF4)pyspharm: an  object-oriented python interface to the NCAR SPHEREPACK library (conda install -c conda-forge pyspharm)Features[v0.1] Running LMR withSlurmon a cluster with just one command line[v0.2] Post-processing: pick files with the same filename from different directories[v0.3] LMR Turbo (LMRt): the packaged version of the LMR framework with multiprocessing supporta quickstart notebooka notebook on building Ye filesHow to installSimplypipinstallslmrand there will be an executable commandslmrin yourPATH.Usage examplesBelow are some usage examples ofslmr.
For more details, please checkslmr-hRunning LMR with SlurmWe need to prepare all the data and configurations required for LMR first,
then we are able to run LMR withSlurmon a cluster
with just one command line:slmrjob-cconfig.yml-n4-nnhungus-rp02000-emslmr@gmail.com-xtest_ccsm4# slmr job: use the mode of submitting a slurm job# -c config.yml: use "config.yml" as a configuration template# -n 4 -nn hungus: run LRM with 4 threads on the node "hungus"# -rp 0 2000: reconstruction period to be from 0 to 2000 C.E.# -em slmr@gmail.com: notification will be sent to "slmr@gmail.com"# -x test_ccsm4: the experiment is named as "test_ccsm4"Post-processing: pick filesslmrpppick_files-fgmt.npz-ddir1dir2-s./gmt_files# slmr pp: use the mode of post-processing# pick_files: the post-processing task to be pick_files# -f gmt.npz: pick files named as "gmt.npz"# -d dir1 dir2: pick files from the specified directories dir1 and dir2; more dirs can be followed# -s ./gmt_files: save the found files to the directory "./gmt_files"LicenseMIT LicenseCopyright (c) 2018 Feng Zhu
Package: slmsuite
High-Performance Spatial Light Modulator Control and HolographyInstallationInstall the stable version ofslmsuitefromPyPiusing:$pipinstallslmsuiteInstall the latest version ofslmsuitefrom GitHub using:$pipinstallgit+https://github.com/QPG-MIT/slmsuiteDocumentation and ExamplesExtensivedocumentationandAPI referenceare available through readthedocs.Examples can be found embedded indocumentation,
live throughnbviewer,
or directly insource.
Package: slmtools
slmtoolsPython code to use a spatial light modulator (SLM).Main Featuressupport for the vortex and top-hat phase masks in stimulated emission
depletion (STED) microscopyaberration control via Zernike polynomialssupport for multiple pupils over the same SLM windowInstallationTheeasiestway to installslmtoolsis to first installAnaconda for
Python 3. After that, open anAnaconda Prompt, typepip install --user --upgrade slmtoolsand hit enter to installslmtools.To start up the GUI, openAnaconda Prompt, typepython -m slmtools.guiand
hit enter.Installation from the GitHub repositoryTo installslmtoolsin Windows, follow the steps below.You should first install the following software requirements:Anaconda for Python 3. This includes
Python as well as some necessary scientific libraries.Git. This is necessary for the
automatic version numbering of this package. Also, make sure you chooseGit from the command line and also 3rd-party softwareinAdjusting
your PATH environment.Clonethis repository using Git. From any folder in File Explorer,
right-click and hitGit Bash here. Pastegit clone https://github.com/jacopoantonello/slmtoolsand hit enter. Do not use GitHub'sDownload ZIPbutton above, as the installation script will not work in that
case.Finally, double-click oninstall.bat.To run the GUI, double-click onrun.bat.
Package: sloancone
sloanconeSDSS conesearching tools via the CL or Python API. Return conesearch results, or simply check whether or not a location in the sky has been covered by SDSS..Documentation for sloancone is hosted byRead the Docs(development versionandmaster version). The code lives ongithub. Please report any issues you findhere.FeaturesHow to cite sloanconeIf you usesloanconein your work, please cite using the following BibTeX entry:@software{Young_sloancone,author={Young, David R.},doi={10.5281/zenodo.8038193},license={GPL-3.0-only},title={{sloancone}},url={https://github.com/thespacedoctor/sloancone}}
Package: slocum
slocumis an open source project which provides weather forecasts
to the bandwidth impaired (primarily sailors).  It includes a weather
specific compression algorithm which results in forecasts attachments
that are the fraction of the size ofsaildocforecasts.Why the nameslocum?Joshua Slocum (February 20, 1844 -on or shortly after November 14, 1909)
was a Canadian-American seaman and adventurer, a noted writer, and the first
man to sail single-handedly around the world. In 1900 he told the story of
this in Sailing Alone Around the World. He disappeared in November 1909
while aboard his boat, the Spray. (wikipedia)In “Sailing Alone Around the World” he talks about his tin clock:“My tin clock and only timepiece had by this time lost its minute-hand,but after I boiled her she told the hours, and that was near enough on
a long stretch.”If Slocum was able to successfully circumnavigate via celestial navigation
using a clock with no minute hand, then modern day sailors should be able
to get by using weather forecasts without floating point precision.
Package: slogs
BETA VERSIONUsefromslogsimportslogs,parents# initialise# autoprint : write logs to console# log_saving : save logs into "logs" files=slogs(autoprint=True,log_saving=False)# logss.success("started",parents.SYSTEM)s.success("content","parent / title")Contactsemail :deepcaps@outlook.comgithub :deepcaps
Package: slojsonrpc
Universal JSONrpc handler, that maps class-methods to jsonrpc-methods.registers common classmethods and reads their function signaturecheck for jsonrpc compliancechecks parameters against function signaturemethod parameters with defaults are optionalcreates db-sessions for each method callExample:class test:def testmethod(self, session , a, b=1):…regiter with:
SLOJSONrpc.register()Will be mapped to jsonrpcmethod:
{‘jsonrpc’: ‘2.0’, ‘method’: ‘testmethod’, params: {‘a’: 42} }
Package: slokc
suck_lord_kelvin_cockThis is an automated Wi-Fi login program for the Kelvin Building. It has
a store of some passcodes. Beyond this, it has a passcode command line
option.setupsudopipinstallslokcTo set up globally a Linux desktop launcher with icon, execute the
following:sudowget--content-disposition-N-P/usr/share/icons/https://raw.githubusercontent.com/wdbm/suck_lord_kelvin_cock/master/slokc/static/cock.svgsudowget--content-disposition-N-P/usr/share/applications/https://raw.githubusercontent.com/wdbm/suck_lord_kelvin_cock/master/slokc/static/suck_lord_kelvin_cock.desktopusageGeneral usage using stored passcodes is as follows:suck_lord_kelvin_cockManual passcode specification can be made in a way like the following:suck_lord_kelvin_cock--passcode="dfae91"A help message is accessible in the following way:suck_lord_kelvin_cock--helppasscodesA source for passcodes is here:http://www.physics.gla.ac.uk/dept-only/wlesscodes/
Package: sloot.object
Basic usage>>> from sloot.object import dictobj
>>> d = dictobj({'a': 'a', 'b': 'b'}, c='c')
>>> print(d)
dictobj({'a': 'a', 'b': 'b', 'c': 'c'})
>>> d.a
'a'
>>> d['a']
'a'
>>> d.a = 3
>>> d.a
3
>>> d['a'] = 42
>>> d.a
42
>>> print(d)
dictobj({'a': 42, 'c': 'c', 'b': 'b'})
>>> print(dict(d))
{'a': 42, 'c': 'c', 'b': 'b'}Behavior of setattr in inherited objects>>> class T(dictobj):
...   classvar = 'classvar'
...   def f(self):
...     return 'f'
...   @property
...   def prop(self):
...     return getattr(self, '_prop', 'prop')
...   @prop.setter
...   def prop(self, value):
...     self._prop = value
...methods and class attributes are not overwritten and go to the dict:>>> t = T({'classvar': 1, 'f': 2, 'prop': 3})
>>> t.classvar  # access the class attribute
'classvar'
>>> t['classvar']  # access the dict entry
1
>>> t.classvar = 5  # we don't overwrite class attributes, this goes to dict
>>> t.classvar  # this is the class attribute
'classvar'
>>> t['classvar']
5
>>> t.f  # access the class method
<bound method T.f of T({'classvar': 1, 'f': 2, 'prop': 3})>
>>> t['f']  # access the dict entry
2
>>> t.f = 4  # we don't overwrite the method, this goes to the dict
>>> t.f
<bound method T.f of T({'classvar': 1, 'f': 2, 'prop': 3})>
>>> t['f']
4properties getter and setter are used:>>> t.prop  # get the property
'prop'
>>> t['prop']  # get the dict entry
3
>>> t.prop = 'newprop'  # use property setter
>>> t.prop
'newprop'
>>> t['prop']
3otherwise the dict is updated:>>> t.a = 42
>>> t['a']
42
>>> t.a
42
Package: slop
Python bindings for slopJust a quick python extension for region selecting. Readhttps://github.com/naelstrof/slopfor info on what kind of region selecting.Usageimportsloprect=slop.select(border=30,r=1,g=0,b=0,a=0.5)print(rect)returns{'x':308,'y':179,'w':654,'h':447,'id':4199883,'cancelled':0}Available arguments:ArgumentTypeDescriptionborderFloatThe border width in pixels.paddingFloatSpace between the actual selection and the returned pixels, this is visible during selection.toleranceFloatThe distance the mouse has to move in pixels before detecting a drag selection.highlightBoolDraws an overlay over the selection with the given color. Only useful with alpha.noopenglBoolDisables OpenGL accelleration, as well as shaders.nokeyboardBoolDisables being able to cancel a selection with the keyboard.nodecorationsBoolSet to 0, 1 or 2. Enables different methods for removing window frame decorations.shadersListA list of shader names. Example ["wiggle", "blur1", "blur2"]. Requires files, see slop website.rFloatThe red component of the rectangle color.gFloatThe green component of the rectangle color.bFloatThe blue component of the rectangle color.aFloatThe alpha component of the rectangle color.xdisplayStringThe desired X display string.quietBoolIf set to true, keeps slop from printing info to std::cout.InstallationWindows:python setup.py installLinux:sudo python setup.py install
Package: slopify
SlopifyWelcome to the kitchen of coding chaos, where Slopify takes your meticulously crafted source code and blends it into a fine puree of potential and possibilities. It's like a culinary adventure for your codebase, except the chef is a language model with a taste for the unpredictable.What's Slopify?Slopify is the digital equivalent of a food fight, but with code. It's a tool that slurps up your source code, feeds it to a ravenous Language Learning Model (LLM), and waits for the LLM to regurgitate a new concoction of code suggestions. Then, with the grace of a starved hyena, Slopify gobbles up the LLM's output and smears it back into your project.InstallationInstalling Slopify is as easy as pie, which, coincidentally, might be what your code resembles after using it:# Install via Poetrypoetryaddslopifyor:# Install with pippipinstallslopifyUsageTo copy your codebase into the system clipboard for Slopify, just run:# Copy your code into the system clipboardslopifyslop/path/to/your/codeIf you prefer to dump your code into a Markdown file instead of the clipboard, use the-oflag:# Dump your code into a Markdown fileslopifyslop/path/to/your/code-oslop_bucket.mdTo apply suggestions from the system clipboard back onto your codebase:# Apply suggestions from the clipboardslopifyslatherIf you have suggestions in a file instead of the clipboard, use the-iflag:# Apply suggestions from a Markdown fileslopifyslather-ivomit.mdTODOaccept diffs in apply markdownallow configurable token limit for dump with graceful failure when overbudgetallow specifying sets of interdependent files commonly needed to be assessed jointly.shell command e.g.slopify set create my_set ...config file e.g.slopify dump -c my_setautomatically generate relevant context from dependent modules with some static code analysis? (nice to have)DisclaimerSlopify is not responsible for any indigestion, nausea, or existential dread that may result from its use. It's recommended to keep a defibrillator handy for your codebase, just in case.Bon Appétit!Now go forth and let Slopify turn your code into the ultimate potluck, where every line is a surprise and every function is a mystery dish. Who knows, you might just discover the secret sauce that's been missing all along—or you'll end up with a Franken-code monster. Either way, it'll be a meal to remember!Remember, Slopify is all about embracing the chaos in the quest for coding excellence—or at least some good laughs along the way. Enjoy the mess!
Package: slopping
sloppingA script to make cropping easy when ffmpeg'ing. Needs slop, xdotool, and xwininfo.Usage$ffmpeg-iinput-vfcrop=$(slopping)outputslopping_and_ffmpeg.webmThe window we are hovering with the mouse needs to be of the same size (w, h) of the video to extract the correct values.To generate PIL.Image cropping coordinates, pass 'pil' as argument when executing the script:$sloppingpilCan also be imported as a module to query the coordinates:[ins]In[1]:importslopping[ins]In[2]:ffmpeg_crop=slopping.crop()[nav]In[3]:pil_crop=slopping.crop('pil')[ins]In[4]:ffmpeg_cropOut[4]:(244,210,128,228)[ins]In[5]:pil_cropOut[5]:(309,367,554,484)Installation$pipinstallslopping
Package: sloq
A slower queue implementation, guaranteeing that tasks are processsed at a maximum rate.SlowQueueaims to be directly comparable with the Queue API so that it can be dropped in as an alternative implementation, as with LIFOQueue and PriorityQueue, but currently (as this needn’t be the case) will raise additional ValueErrors if you try to passblock=Falseortimeout> 0 togetmethods. Some slamming is possible and is controllable using themax_slamkeyword argument on the TokenBucket or SlowQueue instance.See following example (taken from demo_sloq.py) or the unit tests for more:fromargparseimportArgumentParserfromthreadingimportThread,current_threadimportloggingimporttimefromsloqimportSlowQueuedefmain(args=None):prog=ArgumentParser()prog.add_argument("-n",type=int,default=10,metavar="TASK_COUNT",help="The number of tasks")prog.add_argument("-t",type=float,default=1,metavar="TASK_INTERVAL",help="The tick: seconds between tasks being released")prog.add_argument("-w",type=int,default=3,metavar="WORKER_COUNT",help="Number of workers")prog.add_argument("-d",type=float,default=0,metavar="TASK_DURATION",help="Duration of a single task")prog.add_argument("-s",type=float,default=0,metavar="MAX_SLAM",help="The maximum amount of slam to allow")args=prog.parse_args(args)logger=logging.getLogger(__name__)logger.setLevel(logging.INFO)logger.addHandler(logging.StreamHandler())test_queue(logger,args.t,args.n,args.d,args.w,args.s)deftest_queue(logger,tick=1,tasks=10,task_duration=0,worker_count=3,slam=0):start_time=time.time()sloq=SlowQueue(release_tick=tick,max_slam=slam)# Begin the workersforwinxrange(0,worker_count):Thread(target=test_worker,args=(logger,start_time,sloq)).start()# Populate the queuefortaskinxrange(0,tasks):sloq.put((task,task_duration))forwinxrange(0,worker_count):sloq.put((None,None))sloq.join()deftest_worker(logger,start_time,queue):whileTrue:task,sleep=queue.get()iftaskisNone:logger.info("%s, Done"%current_thread().name)queue.task_done()returnelse:logger.info("%s, Elapsed time:%0.2f, Task:%r",current_thread().name,time.time()-start_time,task)ifsleep:time.sleep(sleep)queue.task_done()if__name__=="__main__":main()
Package: sloris
Slow Loris DoS AttackPython implementation of the Slow Loris denial of service attackhttps://gitlab.com/richardnagy/security/slorisDisclaimerThis tool is intended for demonstrational purposes, so only use against your systems or against ones you have authorization for. I take no responsibility for your actions.IntroductionSlow Loris is a low-bandwidth denial of service attack, utilizing lots of connections to the same host and keeping them alive while sending minimal data.When receiving a GET request, the server will wait until an empty line is sent to transmit the requested resource. We don't want any data in return, only to occupy the given connection.The HTTP standard does not define a limit to the header count, but most frameworks have a limit defined in bytes, after which they will abort the connection. A default NodeJS 14+ setup has an upper limit of 16 kb. Using our current header size (average 15 bytes per header), it will take ~1,000 headers to fill this up.If we consider an average of 5 seconds as a timeout period, one connection can occupy a channel for about 5000 seconds or around 1 hour 23 minutes. This happens while sending only 16kb of data.This attack is most effective if:The host has a hard-limited number of possible connections at a timeThe host has no load balancing or firewallsThe host has no DoS protectionThe attack is carried out by a distributed network of systemsRequirementsPython 3.10+UsageStart an attackslorisHOST_IP[OPTIONS]Help:Use the following command to get a list of options.sloris-hExample runslorislocalhost-p8080-c1000-mGET-u/page-t5-pctrueRepositoryFor more information or contribution please take a look at thegit repository
Package: slot
slotRotates a symlink between multiple different possible options.Powered byHy, a Lisp dialect with full Python interop.InstallationpipinstallslotTerminologyAtargetis the file name that you are going to be turning into a symbolic link.Astoreis a repository of data files that act as potential options for atarget.Anoptionis a data file inside of a store.UsageCreate a new store(and optionally ingest current file as anoption)Usage:sltstorescreate[OPTIONS]NAMETARGET

Options:--helpShowthismessageandexit.Add an option to a storeUsage:sltstoresingest[OPTIONS]STORE_NAMEFILE_NAME

Options:-n,--nameTEXTNameoftheoptionthisfilebecomes-s,--silentBOOLEANDisableuserinteraction--helpShowthismessageandexit.List storesUsage:sltlist[OPTIONS]Options:--helpShowthismessageandexit.See available options for a storeUsage:sltoptions[OPTIONS]STORE_NAME

Options:--helpShowthismessageandexit.
Package: slot-filling-ZC
Intent and Slot Filling Bi-Modeltrain(train_file = "data/train_dev",
test_file = "data/test",
vocab_intent_file = "data/vocab.intent",
vocab_slot_file = "data/vocab.slot",
device = torch.device("cuda" if torch.cuda.is_available() else "cpu"),
total_epoch = 50,
max_len = 50,
batch = 16,
learning_rate = 0.001,
DROPOUT = 0.2,
embedding_size = 300,
lstm_hidden_size = 200)5 files would be generated after training:
model_intent_best.pt
model_slot_best.pt
word_dict.pickle
slot_dict.pickle
intent_dict.picklepredict(sentence="find nonstop flights from salt lake city to new york on saturday april ninth.",
data_path="/Users/chenzichu/Desktop/slot-filling/package/slot_ZC",
device = torch.device("cuda" if torch.cuda.is_available() else "cpu"),
max_len = 50,
batch = 16,
DROPOUT = 0.2,
embedding_size = 300,
lstm_hidden_size = 200)
Package: sloth-ci.ext.build_email_notifications
Send email notifications when builds complete or fail.Executing actions of an app is called *build*. A build is considered *completed* if all its actions were completed. If some actions were completed and some failed, it's a *partially completed*; if all actions fail, the build *failed*.This extension sends you emails via SMTP when your builds complete (fully or partially) or fail; just pick the desired notification level, list the recepient emails, and enter your SMTP credentials. Optionally, you can set the subject for each notifcation level... warning::This extension uses `SMTPHandler <https://docs.python.org/3/library/logging.handlers.html#smtphandler>`__ from logging.handlers. SMTPHandler doesn't work with GMail because it creates an smtplib.SMTP object to connect to the host, whereas GMail requires smtplib.SMTP_SSL.Outlook.com works fine.Installation------------.. code-block:: bash$ pip install sloth-ci.ext.build_email_notificationsUsage-----.. code-block:: yaml:caption: build_email_notifications.ymlextensions:notifications:# Use the module sloth_ci.ext.build_email_notifications.module: build_email_notifications# Emails to send the notifications to.emails:- foo@bar.com- admin@example.com# Log level (number or valid Python logging level name).# ERROR includes only build fails, WARNING adds partial completions,# INFO adds completion, and DEBUG adds trigger notifications.# Default is WARNING.level: INFO# The "from" address in the emails. Default is "build@sloth.ci."from: notify@example.com# The email subject on build trigger. You can use the {listen_point} placeholder.# Default is "{listen_point}: Build Triggered."subject_triggered: 'Triggered build on {listen_point}!'# The email subject on build completion.You can use the {listen_point} placeholder.# Default is "{listen_point}: Build Completed."subject_completed: 'Hooray! {listen_point} works!'# The email subject on build partial completion. You can use the {listen_point} placeholder.# Default is "{listen_point}: Build Partially Completed."subject_partially_completed: 'Better than nothing on {listen_point}'# The email subject on build fail. You can use the {listen_point} placeholder.# Default is "{listen_point}: Build Failed."subject_failed: 'Fail on {listen_point}'# SMTP settings.# SMTP mail host and (if not default) port.# Mandatory parameter.mailhost: 'smtp-mail.outlook.com:25'# SMTP login.login: foo@bar.baz# SMTP password.password: bar# If the SMTP server requires TLS, set this to true. Default is false.# If necessary, you can provide a keyfile name or a keyfile and a certificate file names.# This param is used only if the login and password params are supplied.secure: true# secure:#    -   keyfile#    -   cerfile
Package: sloth-ci-ext-devtools
Utilities to help developers create validators and extensions for Sloth CIInstallation$ pip install sloth-ci-ext-devtoolsUsageEnable the extension in the server config:extensions:
    dev:
        # Use the module sloth_ci.ext.devtools.
        module: devtoolsCallsci devwith-eor-vto create an extensions or a validator template:$ sci dev -e spam
Extension "spam" created.
$ sci dev -v eggs
Validator "eggs" created.