Saravanan666/pypi-org huggingface dataset:
Package: sigllm
An open source project from Data to AI Lab at MIT.sigllmSignals plus LLMsDocumentation:https://sintel-dev.github.io/sigllmHomepage:https://github.com/sintel-dev/sigllmOverviewTODO: Provide a short overview of the project here.InstallRequirementssigllmhas been developed and tested onPython 3.8, 3.9, 3.10 and 3.11Also, although it is not strictly required, the usage of avirtualenvis highly recommended in order to avoid interfering with other software installed in the system
in whichsigllmis run.These are the minimum commands needed to create a virtualenv using python3.8 forsigllm:pipinstallvirtualenv
virtualenv-p$(whichpython3.6)sigllm-venvAfterwards, you have to execute this command to activate the virtualenv:sourcesigllm-venv/bin/activateRemember to execute it every time you start a new console to work onsigllm!Install from sourceWith your virtualenv activated, you can clone the repository and install it from
source by runningmake installon thestablebranch:gitclonegit@github.com:sintel-dev/sigllm.gitcdsigllm
gitcheckoutstable
makeinstallInstall for DevelopmentIf you want to contribute to the project, a few more steps are required to make the project ready
for development.Please head to theContributing Guidefor more details about this process.QuickstartIn this short tutorial we will guide you through a series of steps that will help you
getting started withsigllm.TODO: Create a step by step guide here.What's next?For more details aboutsigllmand all its possibilities
and features, please check thedocumentation site.History
Package: siglo
Reinvent your input.SigLo is a python program that uses computer vision to use gestures to interact with their computer naturally.UsageSwipe Gesture for switching slides during a presentationNote: During a presentation, the camera view will be hidden and the presentation will be full-screenScrolling gesture for scrolling through a webpageHorizontal and vertical supportedOnline Video SeekingInstallationClone the repoInstall dependenciespipinstallmediapipepynputRun the main python filepython3driver.pyAHackBeanpot2022 SubmissionLicenseMIT
Package: sigma0
CitationNot yetInstallationThis package should be installable through pip:pip install sigma0ContributeWe are happy if you want to contribute. Please raise an issue explaining what
is missing or if you find a bug. We will also gladly accept pull requests
against our master branch for new features or bug fixes.GuidelinesIf you want to contribute please follow these steps:Fork the sigma0 repository to your accountmake a new feature branch from the sigma0 master branchAdd your featurePlease include tests for your contributions in one of the test directories.
We use py.test so a simple function called test_my_feature is enoughsubmit a pull request to our master branchNoteThis project has been set up using PyScaffold 3.2.3. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.
Package: sigma-cli
Sigma Command Line InterfaceThis is the Sigma command line interface using thepySigmalibrary to manage, list
and convert Sigma rules into query languages.Getting StartedInstallationThe easiest way to install the Sigma CLI is viapipxorpip. For this purpose run one of the following:python -m pipx install sigma-cli
python -m pip install sigma-clion macOS usepython3 -m pip install sigma-cliAnother way is to run this from source in a virtual environment managed byPoetry:git clone https://github.com/SigmaHQ/sigma-cli.git
cd sigma-cli
poetry install
poetry shellUsageThe CLI is available assigmacommand. A typical invocation is:sigma convert -t <backend> -p <processing pipeline 1> -p <processing pipeline 2> [...] <directory or file>E.g. to convert process creation Sigma rules from a directory into Splunk queries for Sysmon logs run:sigma convert -t splunk -p sysmon sigma/rules/windows/process_creationRequired backends must be installed using the following command prior to conducting conversions.To list all available plugins run the following command:sigma plugin listInstall a plugin of your choice with:sigma plugin install <backend>E.g. to install the splunk backend run:sigma plugin install splunkAvailable conversion backends and processing pipelines can be listed withsigma list.
Use-Oor--backend-optionfor passing options to the backend as key=value pairs (-O testparam=123) .
This backend option parameter can be used multiple times (-O first=123 -O second=456).Backends can support different output formats, e.g. plain queries and a file that can be imported into the target
system. These formats can be listed withsigma list formats <backend>and specified for conversion with the-foption.In addition, an output file can be specified with-o.Example for output formats and files:sigma convert -t splunk -f savedsearches -p sysmon -o savedsearches.conf sigma/rules/windows/process_creationOutputs a Splunk savedsearches.conf containing the converted searches.Integration of Backends and PipelinesBackends and pipelines can be integrated by adding the corresponding packages as dependency with:poetry add <package name>A backend has to be added to thebackendsdict insigma/cli/backends.pyby creation of aBackendnamed tuple with
the following parameters:The backend class.A display name shown to the user in the targets list (sigma list targets).A dict that maps output format names (used in-fparameter) to descriptions of the formats that are shown in the
format list (sigma list formats <backend>). The formats must be supported by the backend!The dict key is the name used in the-tparameter.A processing pipeline is defined in thepipelinesvariable dict insigma/cli/pipelines.py. The variable contains aProcessingPipelineResolverthat is instantiated with a dict that maps identifiers that can
be used in the-pparameter to functions that returnProcessingPipelineobjects. The descriptive text shown in the pipeline list (sigma list pipelines) is provided from
thenameattribute of theProcessingPipelineobject.MaintainersThe project is currently maintained by:Thomas Patzkethomas@patzke.org
Package: sigma.coding
Sigma Coding Python LibraryTable of ContentsOverviewSetupUsageSupport These ProjectsOverviewSetupRight now, the library is not hosted onPyPiso you will need to do a local
install on your system if you plan to use it in other scrips you use.First, clone this repo to your local system. After you clone the repo, make sure
to run thesetup.pyfile, so you can install any dependencies you may need. To
run thesetup.pyfile, run the following command in your terminal.pip install sigma.codingThis will install all the dependencies listed in thesetup.pyfile. Once done
you can use the library wherever you want.UsageHere is a simple example of using thesigmalibrary to grab the index
files for specific quarter.Support These ProjectsPatreon:Help support this project and future projects by donating to myPatreon Page. I'm always looking to add more content for individuals like yourself, unfortuantely some of the APIs I would require me to pay monthly fees.YouTube:If you'd like to watch more of my content, feel free to visit my YouTube channelSigma Coding.
Package: sigmaconf
SigmaConf- A Simple Configuration Library for ScienceThe goal of this library is to provide config dict-like objects with the following features:Easy nested access, e.g.cfg['a.b.c']instead ofcfg['a']['b']['c']Immutability. Implemented as functional datastructures, which prevents unwanted side effectsComposability- Configs can be easily combined, smartly merging nested structures
Package: sigma-envs
Simulation program for the task of learning to rationalizeMulti-Agent  Learning for  Iterative Dominance Elimination: Formal Barriers and New Algorithms### get help on how to specify simulation parameter
python main.py -h

### to start a DIR(20, 40) game simulation of 2 EXP3-DH players
python main.py --num_actions 20 --environment 0 --strategy 4 --iterations 100000000 --std 0.1

### to start an SPA game simulation of 10 EXP3 players and 20 action in [0, 1)
python main.py --num_players 10 --num_actions 20 --unit 0.05 --minx 0 --environment 1 --strategy 0 --iterations 100000 --std 0.1

### to start an Lemon game simulation of 50 EXP3 sellers and 1 EXP3 buyers with 50 action 
python lemon.py --num_sellers 50  --num_actions 50 --unit 1 --minx 25 --strategy 0 --iterations 10000 --std 0.1
Package: sigmaepsilon
SigmaEpsilon- High-Performance Computational Solid Mechanics in PythonWarningThis package is under active development and in analpha stage. Come back later, or star the repo to make sure you don’t miss the first stable release!HighlightsHead over to the Quick Examples page in the docs to explore our gallery of examples showcasing what SigmaEpsilon can do! Want to test-drive SigmaEpsilon? All of the examples from the gallery are live on MyBinder for you to test drive without installing anything locally: Launch on Binder.OverviewAsolidsubmodule to analyze and optimize solid structures of all kinds with theFinite Element Method. The implementations so far only cover linear behaviour, but with practically no limits on the complexity of the shape and topology of the domain under investigation.InstallationThis is optional, but we suggest you to create a dedicated virtual enviroment at all times to avoid conflicts with your other projects. Create a folder, open a command shell in that folder and use the following command>>> python -m venv venv_nameOnce the enviroment is created, activate it via typing>>> .\venv_name\Scripts\activatesigmaepsiloncan be installed (either in a virtual enviroment or globally) from PyPI usingpipon Python >= 3.6:>>> pip install sigmaepsilonDocumentationRefer to thedocsfor further details on installation and usage.TestingTo run all tests, open up a console in the root directory of the project and type the following>>> python -m unittestDependenciesWe use Numba's JIT compiler to speed up heavy computations, and it relies on the C++ redistributable package. It is likely already installed on your system, but if it is not, you can download it from Microsoft's website under "Other Tools, Frameworks, and Redistributables".must haveNumba,NumPy,SciPy,SymPy,awkwardstrongly suggestedPyVista,Plotly,matplotlib,sectionpropertiesoptionalnetworkxLicenseSigmaEpsilon is Copyright(C) 2022: Bence BaloghAll rights reserved.This program is dual-licensed as follows:(1) You may use SigmaEpsilon as free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.In this case the program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License athttp://www.gnu.org/licenses/gpl.txtor in the LICENSE file of this repository for more details.(2) You may use SigmaEpsilon as part of a commercial software. In this case a proper agreement must be reached with the Authors based on a proper licensing contract.
Package: sigmaepsilon.core
SigmaEpsilon.Core- Common developer utilities for Python projectsThe package contains some usefull stuff for general Python development activites that turned out to be highly reusable during developing projects in the SigmaEpsilon namespace.Some of the most notable contents:MetaprogrammingA collection of meta and abstract base classes.Aclasspropertydecorator.A solution to enforce abstract class properties on a class.Reusable facilities for project configuration, testing, exceptions, etc.WrappingAn extendibleWrapperclass and a few factory functions to help you safely wrap objects.DocumentationThedocumentationis built withSphinxusing thePyData Sphinx Themeand hosted onReadTheDocs.InstallationBefore attempting to install the package, it is suggested to upgrade pip:python -m pip install --upgrade pipsigmaepsilon.corecan be installed (either in a virtual enviroment or globally) from PyPI usingpipon Python >= 3.7:>>> pip install sigmaepsilon.coreor chechkout with the following command using GitHub CLIgh repo clone sigma-epsilon/sigmaepsilon.coreand install from source by typing>>> pip install .If you want to run the tests, you can install the package along with the necessary optional dependencies like this>>> pip install ".[test]"Development modeFor development purposes, it is suggested to install the package in editable mode, with the optional dependencies for both testing, development and documentation>>> pip install -e ".[test, dev, docs]"Testing and coverageTo run the tests, run the following command in the root of the project:python -m pytest --cov-report html --cov-config=.coveragerc --cov sigmaepsilon.coreLicenseThis package is licensed under theMIT license. See the attached LICENSE file for the details.
Package: sigmaepsilon.deepdict
SigmaEpsilon.DeepDict- A lightweight Python library to handle nested dictionariesTheDeepDictclass works very similarly to a regulardict, but makes life easier in sutiations where there are nested levels, especially when such dictionary is to be created dynamically.Motivating examplesConsider the following simple dictionary>>>d={..."a":{"aa":1},..."b":2,..."c":{"cc":{"ccc":3}},...}This is what happens when you iterate through the values of it:>>>list(d.values())[{'aa':1},2,{'cc':{'ccc':3}}]If you wrap it as aDeepDict:>>>fromsigmaepsilon.deepdictimportDeepDict>>>dd=DeepDict.wrap(d)>>>list(dd.values(deep=True))[1,2,3]The class supports array-like indexing, which combined with the default factory creates the possibility to create deep levels without having to create all the parents:>>>data=DeepDict()>>>data["a",0,"b",1,5]=10Each subdirectory is aware about it's parent container>>>data["a",0,"b"].key"b">>>data["a",0,"b"].address['a',0,'b']>>>data["a",0,"b"].parent.key0Given that theasciitreelibrary is installed, it is also possible to print dictionaries (any kind) as a tree:>>>fromsigmaepsilon.deepdictimportasciiprint>>>d={..."a":{"aa":1},..."b":2,..."c":{"cc":{"ccc":3}},...}>>>data=DeepDict.wrap(d)>>>data.name="Data">>>asciiprint(data)Data+--a+--c+--ccSee the documentation for more examples and explanation on behaviour.DocumentationThedocumentationis built withSphinxusing thePyData Sphinx Themeand hosted onReadTheDocs.InstallationThis is optional, but we suggest you to create a dedicated virtual enviroment at all times to avoid conflicts with your other projects. Create a folder, open a command shell in that folder and use the following command>>> python -m venv venv_nameOnce the enviroment is created, activate it via typing>>> .\venv_name\Scripts\activateThe library can be installed (either in a virtual enviroment or globally) from PyPI usingpipon Python >= 3.7:>>> pip install sigmaepsilon.deepdictLicenseThis package is licensed under theMIT license.
Package: sigmaepsilon.plotting.mpl
SigmaEpsilon.Plotting.Mpl- Utilities for plotting with matplotlibThe library serves as a repo for plots that are not directly available from Matplotlib but might be useful outside the scope of what they were originally created for.Projects using sigmaepsilon.plotting.mplPyAxisVM- The official Python package ofAxisVM, a popular structural analysis and design software.DocumentationThedocumentationis built withSphinxusing thePyData Sphinx Themeand hosted onReadTheDocs. Check it out for an ever growing set of examples, and API Reference.Installationsigmaepsilon.plotting.mpl can be installed from PyPI usingpipon Python >= 3.7:>>> pip install sigmaepsilon.plotting.mplor chechkout with the following command using GitHub CLIgh repo clone sigma-epsilon/sigmaepsilon.plotting.mpland install from source by typing>>> pip install .If you want to run the tests, you can install the package along with the necessary optional dependencies like this>>> pip install ".[test]"Development modeIf you are a developer and want to install the library in development mode, the suggested way is by using this command:>>> pip install "-e .[test, dev]"If you plan to touch the docs, you can install the requirements for that as well:>>> pip install "-e .[test, dev, docs]"How to contribute?Contributions are currently expected in any the following ways:finding bugs
If you run into trouble when using the library and you think it is a bug, feel free to raise an issue.feedback
All kinds of ideas are welcome. For instance if you feel like something is still shady (after reading the user guide), we want to know. Be gentle though, the development of the library is financially not supported yet.feature requests
Tell us what you think is missing (with realistic expectations).examples
If you've done something with the library and you think that it would make for a good example, get in touch with the developers and we will happily inlude it in the documention.sharing is caring
If you like the library, share it with your friends or colleagues so they can like it too.LicenseThis package is licensed under theMIT license.
Package: sigmaepsilon.plotting.plotly
SigmaEpsilon.Plotting.Plotly- Utilities for plotting with PlotlyThe library serves as a repo for plots that are not directly available from Plotly but might be useful outside the scope of what they were originally created for.Projects using sigmaepsilon.plotting.plotlyPyAxisVM- The official Python package ofAxisVM, a popular structural analysis and design software.DocumentationThedocumentationis built withSphinxusing thePyData Sphinx Themeand hosted onReadTheDocs. Check it out for an ever growing set of examples, and API Reference.Installationsigmaepsilon.plotting.plotly can be installed from PyPI usingpipon Python >= 3.7:>>> pip install sigmaepsilon.plotting.plotlyor chechkout with the following command using GitHub CLIgh repo clone sigma-epsilon/sigmaepsilon.plotting.plotlyand install from source by typing>>> pip install .If you want to run the tests, you can install the package along with the necessary optional dependencies like this>>> pip install ".[test]"Development modeIf you are a developer and want to install the library in development mode, the suggested way is by using this command:>>> pip install "-e .[test, dev]"If you plan to touch the docs, you can install the requirements for that as well:>>> pip install "-e .[test, dev, docs]"How to contribute?Contributions are currently expected in any the following ways:finding bugs
If you run into trouble when using the library and you think it is a bug, feel free to raise an issue.feedback
All kinds of ideas are welcome. For instance if you feel like something is still shady (after reading the user guide), we want to know. Be gentle though, the development of the library is financially not supported yet.feature requests
Tell us what you think is missing (with realistic expectations).examples
If you've done something with the library and you think that it would make for a good example, get in touch with the developers and we will happily inlude it in the documention.sharing is caring
If you like the library, share it with your friends or colleagues so they can like it too.LicenseThis package is licensed under theMIT license.
Package: sigmaepsilon.solid.fem
SigmaEpsilon.Solid- High-Performance Computational Solid Mechanics in PythonWarningThis package is under active development and in analpha stage. Come back later, or star the repo to make sure you don’t miss the first stable release!Installationsigmaepsilon.solid can be installed from PyPI usingpipon Python >= 3.7:>>> pip install sigmaepsilon.solid.femor chechkout with the following command using GitHub CLIgh repo clone sigma-epsilon/sigmaepsilon.solid.femand install from source by typing>>> pip install .If you want to run the tests, you can install the package along with the necessary optional dependencies like this>>> pip install ".[test]"DocumentationRefer to thedocsfor further details on installation and usage.TestingTo run all tests, open up a console in the root directory of the project and type the following>>> python -m unittestDependenciesWe use Numba's JIT compiler to speed up heavy computations, and it relies on the C++ redistributable package. It is likely already installed on your system, but if it is not, you can download it from Microsoft's website under "Other Tools, Frameworks, and Redistributables".must haveNumba,NumPy,SciPy,SymPy,awkwardstrongly suggestedPyVista,Plotly,matplotlib,sectionpropertiesoptionalnetworkxLicenseSigmaEpsilon.Solid is Copyright(C) 2022: Bence BaloghAll rights reserved.This program is dual-licensed as follows:(1) You may use SigmaEpsilon as free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version.In this case the program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License athttp://www.gnu.org/licenses/gpl.txtor in the LICENSE file of this repository for more details.(2) You may use SigmaEpsilon as part of a commercial software. In this case a proper agreement must be reached with the Authors based on a proper licensing contract.
Package: sigmasms
sigmasmsModule provides an interface forhttps://sigmasms.ru/api/http/.UsagefromsigmasmsimportAsyncClient# instantiate clientclient=AsyncClient(username='login',password='password',sender='MessageSender')# authorizeawaitclient.auth()print(client.token)# send messageresp=awaitclient.send_message('TestSender','+79999999999','text','sms')print(resp)# check message statusmsg_id=resp['id']status=awaitclient.check_status(msg_id)print(status)# check balancebalance=awaitclient.get_balance()print(balance)# close clientawaitclient.close()
Package: sigmatch
sigmatch: check function signaturesThis small library allows you to quickly check whether any called object matches the signature you expect. This may be useful to you, for example, if you write libraries that work with callbacks.Install it:pipinstallsigmatchNow to check the signatures of the callable objects, you need to create aSignatureMatcherobject, which will "bake" a description of the parameters you expect. You can pass the following arguments to the constructor of theSignatureMatcherclass (they are all strings):"."- corresponds to an ordinary positional argument without a default value."some_argument_name"- corresponds to an argument with a default value. The content of the string is the name of the argument."*"- corresponds to packing multiple positional arguments without default values (*args)."**"- corresponds to packing several named arguments with default values (**kwargs).Note that the arguments can only go in this order, that is, you cannot specify the packing before the positional argument, otherwise you will get anIncorrectArgumentsOrderError. When you have prepared aSignatureMatcherobject, you can apply it to function objects and get a response (True/False) whether their signatures match the expected ones. As an example, see what a function and aSignatureMatcherobject for it mights look like:fromsigmatchimportSignatureMatcherdeffunction(a,b,c=5,*d,**e):...matcher=SignatureMatcher('.','.','c','*','**')print(matcher.match(function))# TrueYou can also pass all the expected arguments as a single line, separated by commas. Positional arguments do not have to be separated, they can be presented as a fused set of dots. See:matcher=SignatureMatcher('.., c, *, **')Thematch()method works with both regular and coroutine functions, as well as with lambdas, generators, classes, methods, and many other callable objects. By default, thematch()method returns a boolean value, but you can ask the library to immediately raise an exception if the function does not have the signature you need:matcher.match(function,raise_exception=True)To catch this exception, import theSignatureMismatchError:fromsigmatchimportSignatureMatcher,SignatureMismatchErrortry:SignatureMatcher('.').match(lambda:None,raise_exception=True)exceptSignatureMismatchError:print('Deal with it (⌐■_■)')# It'll be printed.