Saravanan666/pypi-org huggingface dataset:
Package: pac-hunter
pac_hunter :wolf:A simple project inspired by frustration over employers attempting to raise money from theiremployeescaptive audiences for the purpose of fueling their purchase of loyalty from politicians via Political Action Committees (PACs) in the United States.pac_hunterprovides a wrapper around the fantastic API provided by the Federal Elections Committee calledOpenFEC. This tool is designed to match a PAC of interest with donations made to specific federal election candidates. The use case that inspired this tool was checking historical donations of a PAC to federal candidates or elected officials that denied the legitimacy of the 2020 election.Getting startedCheck the jupyter notebook provided with this repositorydemo.ipynb. You will have to either request your own self-service API key from the OpenFEC project, or use their"DEMO_KEY"which has a stricter rate limit.If you are not familiar with running jupyter notebooks from a local environment, look forward to a google colab notebook once I've published the package. In the meantime, you can run the demo yourself as long as you have python and git installed on your system.gitclonehttps://github.com/jlwhelan28/pac-hunter.gitcdpac-hunter
python3-mvenv.venvsource.venv/bin/activate
pipinstall-rrequirements.txt
pipinstalljupyter
jupyternotebookExample: Raytheon Technologies' PAC donations to 2020 election deniersFuture releaseI'm hopeful to provide a small service that runs astreamlitapp providing a simple interface to use this tool for non-developers. Beyond that, future plans will depend on interest.
Package: pachyderm
🐘 PachydermPachyderm*provides core functionality for heavy-ion physics analyses. The main
functionality includes a generic histogram projection interface, a recursive configuration determination
module (including overriding (merging) capabilities), and general utilities (especially for histograms). It
provides base functionality to theALICE jet-hadron
analysispackage. This package provides many examples of
how pachyderm can be used in various analysis tasks.For further information on the capabilities, see thedocumentation.InstallationPachyderm requires python 3.6 or above. It is available onPyPIand can
be installed via pip:$pipinstallpachydermDependenciesAll dependencies are specified in thesetup.py(and will be handled automatically when installed via pip)
except for ROOT. The package can be installed without ROOT with limited functionality, but for full
functionality, ROOT must be available.DockerfileThere is a Dockerfile which is used for testing pachyderm with ROOT. It is based on theOverwatchbase docker
imageto allow us to avoid redeveloping another container
just to have ROOT available. It may also be used to run pachyderm if so desired, although such a use case
doesn't seem tremendously useful (which is why the image isn't pushed to docker hub).DevelopmentI recommend setting up the development environment as follows:# Setup$poetryinstall# Setup git pre-commit hooks to reduce errors$pre-commitinstall# develop develop develop...DocumentationAll classes, functions, etc, should be documented, including with typing information.The
docsare built on each new successful commit. They can
also be built locally using:# Setup$poetryinstall# Create the docs$pushddoc&&makehtml&&popd# Open the created docs$opendocs/_build/html/index.htmlName MeaningPACHYDERM:PhysicsAnalysisCore forHeavY-ions withDetermination of (analysis)Elements viaRecursion andMerging.
Package: pachyderm-sdk
Pachyderm's Python SDKOfficial Python client/SDK for Pachyderm.
The successor tohttps://github.com/pachyderm/python-pachyderm.This library provides the autogenerated gRPC/protobuf code for Pachyderm,
generated usinga fork of the betterproto package,
along with higher-level functionality.Installationpipinstallpachyderm_sdkA Small TasteHere's an example that creates a repo and adds a file:frompachyderm_sdkimportClientfrompachyderm_sdk.apiimportpfs# Connects to a pachyderm cluster using your local config#   at ~/.pachyderm/config.jsonclient=Client.from_config()# Creates a pachyderm repo called `test`repo=pfs.Repo(name="test")client.pfs.create_repo(repo=repo)# Create a new commit in `test@master` and upload a file.branch=pfs.Branch.from_uri("test@master")withclient.pfs.commit(branch=branch)ascommit:file=commit.put_file_from_bytes(path="/data/file.dat",data=b"DATA")# Retrieve the uploaded file.withclient.pfs.pfs_file(file)asf:print(f.readall())How to load a CAST file into a pandas dataframefrompachyderm_sdkimportClientfrompachyderm_sdk.apiimportpfsimportpandasaspdclient=Client.from_config()file=pfs.File.from_uri("test@master:/path/to/data.csv")withclient.pfs.pfs_file(file)asf:df=pd.read_csv(f)Changes from Python-PachydermThis package is a successor to the python-pachyderm package.
Listed below are some of the notable changes:Organization of the APIMethods and Message objects are now organized according to the
service they are associated with, i.e. auth, pfs (pachyderm file-system),
pps (pachyderm pipelining-system).Message objects can be found within their respective submodule of thepachyder_sdk.apimodule, i.e.pachyderm_sdk.api.pfs.Methods can be found within their respective attribute of theClientclass, i.e.client.pps.create_pipeline.Some methods have been renamed to remove redundancy due to this organization, i.e.python_pachyderm.Client.get_enterprise_state->pachyderm_sdk.Client.enterprise.get_stateThe autogenerated code is generated using a fork of the betterproto compiler.Messages are now python dataclasses.Methods require keyword arguments.Pachyderm resources are specified using types.python-pachyderm (old):client.create_repo("test")pachyderm_sdk (new):client.pfs.create_repo(repo=pfs.Repo(name="test"))ContributingPlease seethe contributing guidefor more info (including testing instructions)Developer GuideGenerate python APIs from protobuf:./generate-protos.shGenerate HTML documentation (writes to docs/pachyderm_sdk):makedocsRunning Tests:pytest -vvv tests
Package: pachypy
pachypy - A Python client library for PachydermThis package aims to make interactions withPachydermmore pythonic and user-friendly.It is primarily intended to be used interactively in a Jupyter notebook environment.Key features include:Show Pachyderm objects (such as repositories, pipelines, jobs, etc.) as nicely formatted tables, backed bypandasDataFramesBatch operations using shell-style wildcards on Pachyderm objectsCreate and update pipelines from specifications in YAML format, supporting multiple pipelines per fileBuild and push Docker images before creating and updating pipelinesAdd image digests when creating and updating pipelines to ensure the latest images are used in pipelines without requiring a tag changepachypy uses the protobufs from the officialpython_pachydermpackage to communicate with Pachyderm.Requires Python 3.6 or higherInstallationpipinstallpachypyDocumentationExample notebookExample pipeline specifications in YAML formatAPI referenceGetting helpLet'schat on Gitteror open anissueon GitHub.
Package: pacifica-archiveinterface
Pacifica Archive InterfaceThis code is to provide the archive interface for the rest of the
Pacifica code base. This code consists of some very specific algorithms
and APIs to support data that might exist on tape or spinning disk.DocumentationFor installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.Installationdocumentation.Configurationdocumentation.Examplesdocumentation.
Package: pacifica-cartd
Pacifica Data CartDocker ContainersPacifica data cart for bundling and transfer of data sets.This manages the bundling of data from the [archive interface]
(https://github.com/pacifica/pacifica-archiveinterface) and presents
APIs for users to use.DocumentationFor installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.Installationdocumentation.Configurationdocumentation.Developmentdocumentation.Examplesdocumentation.
Package: pacifica-cli
Pacifica CLI UploaderPython CLI for Pacifica Core Services. This uploader wraps thePacifica Python UploaderandPacifica Python Downloaderlibraries for Windows or Linux command line.DocumentationFor installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.Installationdocumentation.Configurationdocumentation.CLI Optionsdocumentation.Examplesdocumentation.
Package: pacifica-metadata
Pacifica Metadata ServicesThis is the Pacifica Metadata service and provides Pacifica with a single
API endpoint for access to metadata.DocumentationFor installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.Installationdocumentation.Configurationdocumentation.Metadata Modeldocumentation.Examplesdocumentation.ContributionsContributions are accepted on GitHub via the fork and pull request workflow.
GitHub has a goodhelp articleif you are unfamiliar with this method of contributing.
Package: pacifica-notifications
Pacifica Notifications ServiceDocker ImagesPacifica notification service to catch internal state of data and notify on that stateThis service is a (Pacifica Policy)[https://github.com/pacifica/pacifica-policy.git]
based routing mechanism for data subscribers to execute workflows based on the
availability of data in Pacifica.DocumentationFor installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.Installationdocumentation.Configurationdocumentation.Examplesdocumentation.
Package: pacifica-uploader
Pacifica Python UploaderPacifica Python Uploader,PacificaUploader, is a Python programming language
library for managing, serializing and transporting (over a network) archives of
files (referred to as "bundles"), managing both the data and the metadata of the
bundle, and interacting withPacifica IngestandPacifica Policyservers.For installation, configuration and usage documentation please
refer to theRead the Docsdocumentation.
Package: pacifices-cloud
A PacificES Cloud CLI toolAn official CLI tool for managing yourhttps://pacifices.cloud/servers. Currently only supports CSGO in Sydney regions.This tool also exposes the API library used to manage servers, which can be used within your Python projects to pragmatically manage your CSGO servers.RequirementsAhttps://pacifices.cloudaccount is required to be able to create and manage your serversPython 3+Python Requirements:requestspython-dotenvInstallationpip3 install pacifices-cloudUsageUsage of this tool can be done in multiple ways, either via CLI or via the library. Instructions for both can be found in the links below:CLI UsageLIB usage
Package: pack2048
Package 2048 - Projet informatique de 1er semestre ENSAECe module propose une fonction pour résoudre le 2048.
La fonction snake_strategy résout le 2048 en utilisant la stratégie du snake.
Afin de juger l'efficacité de cet algorithme, vous pouvez utiliser la fonction evaluate_strategy
qui prend en argument la fonction snake_strategy et le nombre de parties effectuées.Comment notre programme résout-il le 2048 ?La fonction snake_strategy prend en argument la grille de 2048 et les trois derniers mouvements effectués.
Elle renvoie une direction de jeu en accord avec le principe du programme qui suit.
L'idée est d'agencer les cases de manière décroissante, de façon à organiser un "snake" pour faciliter le repli de toutes ces cases.
En favorisant la fusion sur une même ligne ou à partir d'une ligne supérieure, notre algorithme assouplit le principe du snake.
A partir du score de 512, le programme accorde une grande importance au nombre de zéros présents dans le jeu, pour éviter à tout prix la fin du jeu.
De plus, il essaie de prévoir cinq coups en avance afin de maximiser son score.La fonction evaluate_strategy permet d'évaluer une stratégie de jeu.
Pour cela, elle effectue le nombre de parties donné en argument et renvoie un générateur.
Pour chaque partie, la grille de 2048 est initialisée, puis une direction est choisie grâce à la stratégie donnée en argument.
La grille est alors mise à jour en effectuant un mouvement selon cette direction, et simultanément de nouveaux 2 ou 4 sont générés dans la grille.
Si la grille arrive en situation de gameover, la partie se termine.Quels tests avons nous programmé pour nos fonctions ?Le test test_game_play permet de vérifier si la grille de 2048 réagit correctement à l'annonce d'une direction.Le test test_basic permet de vérifier que la direction renvoyée par la stratégie snake_stratégie est bien un élément de {0, 1, 2, 3}.Le test test_advanced permet de vérifier la cohérence de l'évolution de la grille de 2048 avec la stratégie snake_stratégie.
Il se place dans le cas où l'algorithme n'effectue aucune prévision sur les prochains tours.
Il s'intéresse particulièrement au choix d'effectuer une fusion ou de favoriser une certaine direction.Quelques commandes utiles.Ce module peut être installé avec pip :pip install pack2048Exemple d'usage :>>> from pack2048 import evaluate_strategy, snake_strategy
>>> evaluate_strategy(snake_strategy,10)Les tests doivent être effectués en console à l'aide de la commande suivante :python -m pack2048Si vous souhaitez davantages de détails sur les tests, utilisez la commande suivante :python -m pack2048 -vCe code est sous licence GNU AGPLv3.
Package: packaage
PackaageEver get this feeling that you wrote a bunch of stuff ever and ever and ever and ever and ever ...Don't worry fam', we are here !The AAlmightyAdvanced Analytics Teampresents ...The PackAAgeA way to awesome stuff that allows you to just import a bunch of usefull function to ship your code
to the next stAAge !InstallationUse the package managerpipto install packaage.pipinstallpackaageUsageMeaning of lifeThe most important part of all of this. It contains all the constants you need in you life.No less, no more.AWSconnect_to_rds: a simple wrapper of psycopg2 to connect to an AWS RDS database by interrogating
Secrets Manager to retreive the credentialss3_to_memory: download a file from a bucket s3 directly into memoryNLPclean_text: simple function to deal with accentation and special charactersSetupget_git_branch: retreive the name of the git branch you are in to be used as file keyContributingPull 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: package-Andraziel
M1-2022-gitIntroductionThis repository is a fork from the previous repository.
The bugs in the converter have been fixed and now we want to publish our work as a publicly available python package.Getting startedYou should be working fromyour own repositorythat is a fork of M1-2022-git-workflow.
In order to run this project, you will have to follow these stepsClone this projectmove into the project foldercdM1-2022-git-workflowSet up a virtual environmentCreate the virtual environmentpython-mvenvmyvenvActivate venv.venv/bin/activateInstall pytestpipinstall-UpytestExecute main scriptpythonmain.pyInstructionsMerge feature branch into devNow that the converter has no more bugs, we want to merge our branch feature into the dev branch.
We will do a pull request (on your own repo). On GitHub, go to the "Pull requests tab" and click "New pull request".
Selectbaseandcompare. Remember : we want to mergedecimal-binary-converterintodev.
Then,Create the pull request. Add some description of the work you have done and publish the Pull Request.Note: We could have just mergedecimal-binary-converterintodevfrom the command line. However, when working on a real project, you probably won't have the rights to do so. Remember : dev is a public branch. So all the work going down there should be carefully reviewed and tested.Publish your workWe now have an awesome binary/decimal two ways converter ! It's time to publish it so the rest of the world can enjoy it !
We will publish it on PyPI (Python Package Index) which is a public repository of softwares for Python.First, you have to create an account onPypi.orgThen, in your repository, you will find a.github directoryInside this directory, you will find .yml files that defines workflows (using GitHub actions)Open the yml files and take time to understand them. Do not hesitate to ask the teacher about themHands on !We want to create a workflow that will, on publish, test our code and if tests succeed, then publish our package on PyPIIn GitHub, click on theActionstab, then click onnew workflowChoose among the suggestions the template that best suits your use-case and clickConfigureYou may find some useful informations in thePython documentationWhen creating a release on GitHub, do not forget to create a tag corresponding to that releasePull requestOnce the workflow is setup and tested (you have published your package using it) you can open a pull request to theoriginal repository
Package: packagebmi
packagebmiDescription.The package packagebmi is used to:Calculate individual body mass index.Find out what basic category the person is.InstallationUse the package managerpipto install packagebmipipinstallpackagebmiUsagefrompackagebmiimportfilebmifilebmi.bmi(weight,height)filebmi.bmi_category(weight,height)ImportantThe function 'filebmi.bmi(weight, height)' returns bmi result
The function 'filebmi.bmi_category(weight, height)' returns bmi categoryAuthorGlauco MoriLicenseMIT
Package: packagebuilder
===========================================================================================packagebuilder: A library for building python packages into binary or source distributions.===========================================================================================.. image:: https://img.shields.io/pypi/v/packagebuilder.svg:target: https://pypi.org/project/packagebuilder.. image:: https://img.shields.io/pypi/l/packagebuilder.svg:target: https://pypi.org/project/packagebuilder.. image:: https://api.travis-ci.com/sarugaku/packagebuilder.svg?branch=master:target: https://travis-ci.com/sarugaku/packagebuilder.. image:: https://ci.appveyor.com/api/projects/status/y9kpdaqy4di5nhyk/branch/master?svg=true:target: https://ci.appveyor.com/project/sarugaku/packagebuilder.. image:: https://img.shields.io/pypi/pyversions/packagebuilder.svg:target: https://pypi.org/project/packagebuilder.. image:: https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg:target: https://saythanks.io/to/techalchemy.. image:: https://readthedocs.org/projects/packagebuilder/badge/?version=latest:target: https://packagebuilder.readthedocs.io/en/latest/?badge=latest:alt: Documentation StatusSummary=======Packagebuilder_ is a library designed for building packages. It takes `InstallRequirement`objects as inputs and first attempts to build a wheel, but falls back to producing asource distribution if necessary. Invocation is straightforward:::>>> import packagebuilder>>> import pip_shims>>> ireq = pip_shims.shims.InstallRequirement.from_line('vistir')>>> builder = packagebuilder.BuiltDist(ireq, sources=packagebuilder.get_sources())>>> dist = builder.build()>>> dist.metadata.run_requires['requests', 'six', 'backports.weakref; python_version < "3.3"', 'backports.shutil-get-terminal-size; python_version < "3.3"', 'pathlib2; python_version < "3.5"', "yaspin; extra == 'spinner'", "pytest; extra == 'tests'", "pytest-xdist; extra == 'tests'", "pytest-cov; extra == 'tests'", "pytest-timeout; extra == 'tests'", "hypothesis-fspaths; extra == 'tests'", "hypothesis; extra == 'tests'"]`Read the documentation <https://packagebuilder.readthedocs.io/>`__.
Package: package-cache
Package-cache is a simple caching proxy for package downloads.  Just
configure a list of upstream sources (with the--sourceoption)
and point clients at the package-cache server.  The first time a
package is requested, we download that package from one of the sources
and cache it locally, while also streaming it to the client.  Future
requests for that package are streamed directly from the local cache.
This helps reduce the load on the network and source servers, if you
have a number of local clients that will repeatedly request the same
files (e.g.Gentoo’s distfiles).We don’t do anything fancy withCache-Control headers, since
package source files should include the version stamp in the filename
itself (e.g.my-package-0.1.2.tar.gz).  Files are cached after the
first request, and stored forever.  This means that every package
you’ve ever requested will still be there if you need it later.
That’s nice, but it will end up consuming a fair amount of disk space.
You might want to periodically cull the cache, using access times to
see which files you are unlikely to want in the future.Package-cache is written in Python, and has no dependencies outside
the standard library.Running package-cacheBy default, we’ll usePython’s reference WSGI implementationto run
our application:$ package-cache --source http://distfiles.gentoo.org/For other command-line options, see:$ package-cache --helpIf you need a more perfomant backend, you might tryGunicorn.GentooThere’s anOpenRCinit script incontrib/openrc/init.d, and a
package-cache ebuild in mywtk overlay.  To use package-cache as a
caching proxy for your distfiles downloads, add thewtkoverlay tolaymanand run:# emerge --ask --verbose net-proxy/package-cache
# rc-update add default net-proxy/package-cache
# rc-service package-cache startYou can tweak the parameters by setting variables in/etc/conf.d/package-cache(PC_USER,PC_GROUP,CACHE_DIR,HOST,PORT,SOURCES, andPC_OPTS).  See
the init script for default values.Once you’ve setup your package-cache service, just point your local
package manager to the cache server instead of the usual mirror.  ForPortage, that’s going to be something like:GENTOO_MIRRORS=”http://my-package-cache-server.net:4000/”in your/etc/portage/make.conf.If youdon’twant to tweak your clients (perhaps there are many of
them, or they are out of your direct control), you can add some
firewall rules to your router to transparently proxy specific Gentoo
mirrors.  With an internaleth1and an internal proxy on
192.168.0.11, that looks something like:# CACHE_IP=192.168.0.11
# for SOURCE_IP in $(dig +short distfiles.gentoo.org);
> do
>   iptables --table nat --append PREROUTING --protocol tcp \
>     --in-interface eth1 ! --source "${CACHE_IP}" \
>     --destination "${SOURCE_IP}" \
>     --match tcp --destination-port 80 \
>     --jump DNAT --to-destination "${CACHE_IP}:4000" ;
> doneTo remove those entries later, repeat the command with--deleteinstead of--append.  You may need to list theSOURCE_IPvalues
explicitly if the DNS entries have changed.  Run:# iptables --table nat --list PREROUTING --numericto list the entries.  Seeiptables(8)andiptables-extensions(8)for more details.
Package: packagecake
Package Cake 🎂Package Cakeis a simple utility that takes your package and turns it
into cake 🍰.Installationpython-mpipinstallpackagecakeBake a Package Cakepython-mpackagecakebake[yourpackagename]>>python-mpackagecakebakerequests
🍰PyPI Package Cake StatsIn addition to single package baking,Package Cakecan also bake all
the packages in PyPI and provide the total of each type of cake.>>python-mpackagecakestats
------------------------------|PyPIPackageCakeStats|------------------------------|🍩-Donut|153821|------------------------------|🧁-Cupcake|77134|------------------------------|🍰-Shortcake|38769|------------------------------|🎂-BirthdayCake|20632|------------------------------|🥮-MoonCake|17793|------------------------------|🍥-FishCake|352|------------------------------
Package: package-calculadora
package_nameDescription.
The package package_name is used to:
- Projeto criado para o Bootcamp Geracao Tech Unimed - BH - Ciencias de Dados
- Criacao de uma aplicaÃ§Ã£o em Python de uma calculadora com funcoes basicas.
- Demonstracao da criaÃ§Ã£o de um pacote para o projeto.
- Demonstracao da modularizacao da aplicacao.InstallationUse the package managerpipto install package_namepipinstallpackage_calculadoraUsagefrompackage_calculadoraimportcalculadoracalculadora.sub_numbers()calculadora.add_numbers()calculadora.div_numbers()calculadora.mult_numbers()AuthorAdriana AndradeLicenseMIT