Saravanan666/pypi-org huggingface dataset:
Package: vittles
# “Variational inference tools to leverage estimator sensitivity”:vittles.[![image](https://travis-ci.org/rgiordan/vittles.svg?branch=master)](https://travis-ci.org/rgiordan/vittles)[![image](https://codecov.io/gh/rgiordan/vittles/branch/master/graph/badge.svg)](https://codecov.io/gh/rgiordan/vittles)## Description.This is a library (very much still in development) intended to make
sensitivity analysis easier for optimization problems. For background and motivation, see the following papers:A Higher-Order Swiss Army Infinitesimal Jackknife
Ryan Giordano, Michael I. Jordan, Tamara Broderick
<https://arxiv.org/abs/1907.12116>Covariances, Robustness, and Variational Bayes
Ryan Giordano, Tamara Broderick, Michael I. Jordan
<https://arxiv.org/abs/1709.02536>A Swiss Army Infinitesimal Jackknife
Ryan Giordano, Will Stephenson, Runjing Liu, Michael I. Jordan, Tamara
Broderick
<https://arxiv.org/abs/1806.00550>Evaluating Sensitivity to the Stick Breaking Prior in Bayesian
Nonparametrics
Runjing Liu, Ryan Giordano, Michael I. Jordan, Tamara Broderick
<https://arxiv.org/abs/1810.06587>## Using the package.We welcome new users! However, please be aware that the package is
still in development. We encourage users to contact the author (github
userrgiordan) for advice, bugs, or if you’re using the package for
something important.### Installation.To install the latest tagged version, install withpip:python3 -m pip install vittles.Note thatvittlesis under rapid development, so you may want to clone
the respository and use the master branch instead.### Documentation and Examples.For examples and API documentation, see
[readthedocs](https://vittles-python.readthedocs.io/en/latest/index.html).Alternatively, check out the repo and runmake htmlindocs/.
Package: vitya
vityaWARNING: This library is still in development stage.Validators for different russian banking values.Values you can validate:ИННvalidate_innИНН для ИП/Физ.Лицаvalidate_inn_ipИНН для Юр.Лицаvalidate_inn_leКППvalidate_kppБИКvalidate_bicОГРНvalidate_ogrnОГРНИПvalidate_ogrnipСНИЛСvalidate_snilsОКТМОvalidate_oktmoYou should pass value asstr, otherwise exception will be raised.If passed value is wrong, all functions will raiseValidationError.Also, optionally, you can use validators as Pydantic fieldsExamples:validate_inn("3664069397")try:validate_inn("770708389")exceptValidationErrorase:print(f"wrong inn:{e}")validate_kpp("616401001")validate_bic("044525901")validate_ogrn("1027700132195")validate_snils("11223344595")validate_oktmo("69701000001")frompydanticimportBaseModel,ValidationErrorfromvitya.pydantic_fieldsimportINNclassInnModel(BaseModel):inn:INNinn_model=InnModel(inn="302502032671")assertinn_model.inn=="302502032671"try:InnModel(inn="3664069398")exceptValidationErrorase:print(e.errors())Валидация платежей по реквизитам (Russian)Для валидации платежей используется следующий базовый класс,
от которого необходимо наследоваться:classBaseModelCheckerУ наследников этого класса есть переменная класса:__checkers__:ClassVar[List[Tuple[Type[BaseChecker],List[str]]]]=[]В этой переменной содержится список чекеров (наследников BaseChecker),
которые будут вызваны (вызовется метод check)
при инициализации инстансов BaseModelCheckerКласс чекеров наследуется от BaseCheckerclassBaseChecker(ABC):@abstractmethoddefcheck(self)->None:# pragma: no coverpassПри инициализации инстансов класса BaseModelChecker, когда появляется проверка
чекеров не выполняется успешно, выбрасывается ошибка CheckerError,
которая затем оборачивается в pydantic.ValidationErrorclassCheckerError(ValueError):def__init__(self,errors:Sequence[Exception]):self._errors=errors@propertydeferrors(self)->Sequence[Exception]:returnself._errorsПример работыДля примера разберем базовую ситуацию: ключевание номера счёта и БИКа банка.
Чтобы это проверить, нам нужно создать класс наследник BaseModelChecker,
со встроенным чекером ключевания счёта и БИКа.
Такой чекер есть в базовых реализациях и называется AccountBicChecker.Пример кода:classMyPayment(BaseModelChecker):account_number:AccountNumberbic:BIC__checkers__=[(AccountBicChecker,['account_number','bic'])]try:payment=MyPayment(account_number='40802810722200035222',bic='045004861')exceptValidationErrorase:print('ой, что-то не так с данными: ',str(e))else:print('все отлично!')Результат выполнения:ой, что-то не так с данными:  1 validation error for TestAccountBicModelChecker
__root__
  [AccountValidationBICValueError()] (type=value_error.checker; _errors=[AccountValidationBICValueError()])Поменяем БИК на корректный (последнюю цифру)try:payment=MyPayment(account_number='40802810722200035222',bic='045004864')exceptValidationErrorase:print('ой, что-то не так с данными: ',str(e))else:print('все отлично!')Результат выполнения:все отлично!
Package: viu
viuA smallless-like Python code viewer with responsive formatting and stylingTODO - GIFInstallationInstall via pip:pip install viuUsage:viu <your_file.py>Aboutviuuses the following packages:Black(for formatting code)pygments(for color support)FeedbackI'd love to hear your feedback. Feel free to open an issue, send ane-mailor reach out on twitter@fkohlgrueber.
Package: viur-core
viur-coreThis is the core library component of theViUR framework.AboutViUR is an application development toolkit for the Google App Engine™.ViUR is an open source software development framework that was created to fulfill both designers and developers needs and requirements. It provides a clear concept for implementing agile data management software. It's written in Python™ and already attracted a steady growing community constantly helping and improving ViUR.Getting startedTo get started with ViUR, check outviur-base. It comes with a pre-configured and well documented project template to immediately start with.ContributingHelp of any kind to extend and improve or enhance this project in any kind or way is always appreciated.We take great interest in your opinion about ViUR. We appreciate your feedback and are looking forward to hear about your ideas. Share your vision or questions with us and participate in ongoing discussions.See ourcontribution guidelinesfor details.LicenseCopyright © 2024 by Mausbrand Informationssysteme GmbH.Mausbrand and ViUR are registered trademarks of Mausbrand Informationssysteme GmbH.You may use, modify and distribute this software under the terms and conditions of the GNU Lesser General Public License (LGPL). See the file LICENSE provided within this package for more information.
Package: viur-datastore
The Datastore wrapper for ViUR-CoreThis repository contains the datastore wrapper for the ViUR framework.
We build our own wrapper around it's REST-API as the original wrapper has significant CPU overhead.
Using a fast JSON-Parser (simdjson) and Cython, we can go directly from the received JSON-encoded protocol-wrapper
representation to the final python objects, without converting that JSON into an intermediate python object
representation which then gets discarded right away.While it has some ViUR specific functions, it's also possible to use this wrapper outside ViUR.UsingJust install it via venv, pipenv or requirements.txt into your appengine project. As by now it's a drop in replacement
for the original library provided by google, but maybe we break api compatibility in a future
release for more performance.DevelopingAs a developer we want to have an editable viur-datastore library. We're going to use pipenv for the job
and install neededcd <path/to/viur-testing-project>
pipenv install
pipenv shell
pipenv install build twine
pipenv install -e <path/to/viur-datastore>Choose a testing project configuration via gcloud if you use configs per projectIds:gcloud config configurations activate <project-config>Or use environment variable which projectId we want to use:export CLOUDSDK_CORE_PROJECT="my-awesome-testing-project"If the env var before does not work please set that one:export GCLOUD_PROJECT="my-awesome-testing-project"Yezzzz - now we build that awesome new stuff!:python -m buildPlease take a cup of tea - oh wait - it has just build in seconds.
If everything worked fine, you should see some builds in the dist subfolder.TestingNow it's time run our test suite before actually releasing our shiny new version:cd <path/to/viur-datastore>
python -m unittest testsIf everything worked fine and all tests passed you can go on with the release procedure.ReleasingAfter buildingandtesting the new version please update changelog, commit everything and tag it with the
same version you used in setup.py.Do you have already installed twine? No? Ok, go back to the developing step!!!Now please manually bump the version in setup.py, safe the file and here we go.We only want to provide and upload the generic build - perhaps we'll provide optimized
builds per python version, OS and arch in a future release.Now it's time to get an api keyexclusivelyfor this project from pypi and save it to your wallet!Now the actual release workflow:cd <path/to/viur-datastore>
twine upload dist/viur-datastore-<version>.tar.gzYou might already have a keyring configured with credentials /api key for pypi or
provide username__token__and password<your api key>in interactive mode.
Package: viv
viv isn't venvDocumentationTry before you buy!python3<(curl-fsSLviv.dayl.in/viv.py)runpycowsay--"viv isn't venv\!"Vivis a standalone dependency-freevenvcreator [^1].Vivhelps you ignore silly things like managing temporary or rarely used virtual environments,
while still unleashing the full power of Python scripting with its entire ecosystem at your disposal.Viv's uncompromising insistence on portability means that it will always:only use the standard librarynever exceed a single script.For that reason, any usage of the CLI can be accomplished using a remote copy as seen in the below install command.SetupRun the below command to installviv.python3<(curl-fsSLviv.dayl.in/viv.py)manageinstallTo accessvivfrom within scripts you should add its location to yourPYTHONPATH.
By defaultvivwill be installed to$XDG_DATA_HOME/vivor~/.local/share/viv;
you can customize this with--src.exportPYTHONPATH="$PYTHONPATH:$HOME/.local/share/viv"Pypi (Not Recommended)pipinstallvivWhy is thisnot recommended?Mainly becausevivis all about hacking yoursys.path.
Placing it in its own virtual environment or installing in a user site directory may complicate this endeavor.UsageIn any Python script with external dependencies you can add this line
to automatevivenvcreation and installation of dependencies.__import__("viv").use("click")To remove allvivenvsyou can use the below command:vivenvremove$(vivlist-q)To removevivaltogether you can use the includedpurgecommand:python3<(curl-fsSLviv.dayl.in/viv.py)managepurgeEquivalent commands from alternativespip-runpip-runcowsay---mcowsay"moove over, pip-run"python3<(curl-fsSLviv.dayl.in/viv.py)runcowsay--"moove over, pip-run"python-mpip-runrequests---c"import requests; print(requests.get('https://pypi.org/project/pip-run').status_code)"python-mvivrunrequests-bpython---c"import requests; print(requests.get('https://pypi.org/project/viv').status_code)"pipxpipxinstallpycowsay
vivshimpycowsaypipxrunhttps://gist.githubusercontent.com/cs01/fa721a17a326e551ede048c5088f9e0f/raw/6bdfbb6e9c1132b1c38fdd2f195d4a24c540c324/pipx-demo.py
python3<(curl-fsSLviv.dayl.in/viv.py)run\-shttps://gist.githubusercontent.com/cs01/fa721a17a326e551ede048c5088f9e0f/raw/6bdfbb6e9c1132b1c38fdd2f195d4a24c540c324/pipx-demo.pyBonus: usevivwith just standalone snippet (37LOC)--standalonewill auto-generate a mini-function version ofvivto accomplish the same basic task as using a local copy ofviv.
After generating this standalone shim you can freely use this script
across Unix machines which have Python > 3.8.
Seeexamples/blackfor output of the below command.viv freezealso supports--standalone.python3<(curl-fsSLviv.dayl.in/viv.py)shimblack-o./black--standalone--freeze[^1]: You do need to havepipbut surely you havepipalready.
Package: vivacious
vivaciouspriorities:health scan and health advancents,checked with "body_scan" and modules that use "body_scan"limitations (the structure):The idea is that building codependecies (or cyclic depedencies)into the status assertation framework is a recipe for confusion.As in, vivacious perhaps shouldn't include a module thatrequires vivacious for status assertation.Therefore the directed acyclic chart of status check frameworks is:[ unit test, pytest ] -> "body_scan" -> vivaciousdetails:story 3:vivacious:status requires:body_scanrequires:botanical:status: body_scanstory 2:body_scan:status requires:unit testrequires:botanist:status: pyteststory 1:unit test:journal:1:This is module started as a replica of "body_scan",where it uses "body_scan" as the status monitor.In contrast, "body_scan" uses unittest as the statusmonitor.
Package: vivado-xpr-fixer
vivado-xpr-fixerFixes the project path name when using Vivado and Git together.Problem:Vivado uses fully qualified pathnames when describing the location of the project file.
This causes issues when multiple people are working on multiple machines with the same Vivado project as the pathnames are likely to be different.Solution:This script simply modifies the project file so that the pathname is fixed to the directory containing the project file.Installation:This script can be installed using pip with:user@console~$python3-mpipinstall--user--upgradevivado_xpr_fixerInstallation from sourceTo install from source clone this repositry then run:user@console~$python3setup.pyinstallInstalling the Git Hook:This script can operate as a git hook.
This means that it will automatically run whenever you perform agit pull.
You will need to install the git hook on every client machine as hooks aren't stored in the repository.user@console~$vivado-xpr-fixerinstallNote that "python" will need to be installed somewhere where git can execute it.Removing the Git Hook:user@console~$vivado-xpr-fixerinstallManually Updating the XPR File:user@console~$vivado-xpr-fixerupdateNote that you won't need to do this if you have it running via a git hook.
Package: vivainsights
vivainsightsOverviewThis is an Python package for analyzing and visualizing data from Microsoft Viva Insights.Access to the Analyst Experience is required. With this library, you can generate visualizations and compute analyses in a way that adheres to the analysis best practices of the Viva Insights query outputs.For the full package documentation, please seehere. Thevivainsightslibrary is published on thePython Package Index (PyPi).For users who prefer R to Python, we recommend theR library counterpartwhich mirrors the design of the Python package.Example visualization output from the library (create_rank()):InstallationYou can installvivainsightsby running this in Command Line:pip install vivainsightsAlternatively, you can install the development version ofvivainsightsfrom this GitHub repository:pip install -e git+https://github.com/microsoft/vivainsights-py#egg=vivainsightsTo install from a specific branch, run the following command replacing branch name with<remote-branch-name>:pip install -e git+https://github.com/microsoft/vivainsights-py@<remote-branch-name>#egg=vivainsightsFor examples on how to create analyses and visualizations, please see thedocumentation.Related repositoriesViva Insights R libraryViva RMarkdown Report MarketplaceViva Insights Sample CodeViva Insights Zoom IntegrationViva Insights OData Query DownloadViva Insights R library (legacy)ContributingThis project welcomes contributions and suggestions. For feature and complex bug fix contributions, it is recommended that you first discuss the proposed change with vivainsight’s maintainers before submitting the pull request. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visithttps://cla.microsoft.com.When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.This project has adopted theMicrosoft Open Source Code of Conduct. For more information see theCode of Conduct FAQor contactopencode@microsoft.comwith any additional questions or comments.LicenseThis library is licensed under the MIT License. For more information, please see the LICENSE file.
Package: vivaldi-feed-exporter
vivaldi-feed-exporterSinceVivaldidoes not currently have the ability to export feeds,
I created a command line tool to generateOPMLbased on a profile.Disclaimer : It depends on Vivaldi's implementation, so it may stop working at any timeUsageFollowthis pageto identify your Vivaldi profile folderInstallvivaldi-feed-exporterviapipx install vivaldi-feed-exporterRunningvivaldi-feed-exporter <profile folder path>will output OPML to standard outputMapping of Vivaldi feed properties to OPMLoutlineelement attributesVivaldi feed propertyoutlineattributetitletext,titleaddressxmlUrl
Package: viva-parse
viva-parseParse and dump VIVA conversations from json format to raw text and vice versa.Install:pipinstallviva-parseor from source:pipinstallgit+https://github.com/svenschultze/viva-parseParse:importviva_parseconversation="
 I want to book a room for monday at 3am


<[date]> monday<[time]> 3am<!return!> success!
 Success! I have booked a room for you.
"parsed=viva_parse.parse(conversation)Dumpimportviva_parseconversation_json=[{'role':'prompter','message':'I want to book a room for monday at 3am'},{'role':'assistant','message':'Success! I have booked a room for you.','actions':[{'name':'book_room','params':{'date':'monday','time':'3am'},'return':'success!'}]}]dumped=viva_parse.dump(conversation_json)
Package: viva-review-saas
趣维审核视频审核fromreview_saas.video_reviewimportVideovideo_review=Video(client_id,toke)flag,msg=video_review.review(视频编号,视频播放地址,业务码,视频时长,用户id)ifnotflag:print(msg)图片审核fromreview_saas.img_reviewimportImgReviewimg_review=ImgReview(client_id,token)flag,msg=img_review.review(video_id:int,secret_id:str,user_id:str,img_list:List,video_url:str='')ifnotflag:print(msg)
Package: vivarium
Vivarium is a simulation framework written using standard scientific Python
tools.Vivarium requires Python 3.8-3.11 to runYou can installvivariumfrom PyPI with pip:> pip install vivariumor build it from source with> git clonehttps://github.com/ihmeuw/vivarium.git> cd vivarium> conda create-nENVIRONMENT_NAME python=3.11> pip install-e.[dev]This will make thevivariumlibrary available to python and install a
command-line executable calledsimulatethat you can use to verify your
installation with> simulate testCheck out the docs!
Package: vivarium-bioscrape
Vivarium-BioscrapeVivarium-bioscrape is a python package connecting the multiscale simulation framework Vivarium to the chemical reaction network (CRN) simulator Bioscrape. In particular, this package wraps bioscrape as a vivarium Process and includes a number of Derivers in the form of OneWayMaps to help connect CRNs to eachother and other processes.Visitthe Vivarium Core
documentationto learn how to
use the core Vivarium engine to create computational biology models.Visitthe Bioscrape Wikito learn about the bioscrape simulator and find bioscrape usage examples.InstallationThe easiest way to install this package is via:pip install vivarium-bioscrape(with Python>=3.7)This command will automatically install the package along with vivarium-core and bioscrape and all othe dependencies.Please note that Bioscrape is a cython extension module and requires a C++ compiler to be set up on your computer for installation. Please visit theBioscrape Wikifor more information.You can then run the vivarium-bioscrape process with the module format:$ python -m vivarium_bioscrape.processes.bioscrape
Package: vivarium-cell
vivarium-cellWARNING: This library has been deprecated. Please seehttps://vivarium-collective.github.iofor alternatives.vivarium-cellis a library of configurable
cell process and composites for vivarium projects.Installationvivarium-cell can be used as a python library. To install:$ pip install vivarium-cellSetup in local repositoryClone the repository, make a python environment, and install dependencies.First install numpy:$ pip install numpyThen the remaining requirements:$ pip install -r requirements.txtRun individual processes and compositesEach process file undercell/processescan run on its own. Some of these have their own command line options.
For example, call theconvenience_kineticsprocess with:$ python vivarium_cell/processes/convenience_kinetics.pyComposites with multiple integrated processes can also be executed on their own:$ python vivarium_cell/composites/gene_expression.pyExperimentsTODOTestsTests are performed with pytest. Simply call the following to ensure everything is working properly:$ pytestTo run only the fast tests:$ pytest -m 'not slow'LoggingLogging is done with python logging. To print out logging information, run a simulation with:$ LOGLEVEL=INFO python vivarium_cell/..
Package: vivarium-chemotaxis
Vivarium-chemotaxisVivarium-chemotaxisis a library for the
multi-scale model of chemotaxis described in:Agmon, E.; Spangler, R.K. A Multi-Scale Approach to
Modeling E. coli Chemotaxis. Entropy 2020, 22, 1101.Supplementary materials can be foundhere.Visitthe Vivarium Core documentationto learn how to use the
core Vivarium engine to create multi-scale computational biology models.TheChemotaxis Master Composite, with processes for metabolism (MTB),
transport (TXP), transcription (TSC), translation (TRL), complexation (CXN), degradation (DEG), proton motive
force (PMF), flagella activity (FLG), and chemoreceptor activity (CHE).
This repository includes the processes for CHE, FLG, and PMF; the other processes are imported fromvivarium-cell.SetupPlease refer to the Vivarium Core documentation for more complete instructions.Make a python environment with Python 3 (pyenv is recommended) and install dependencies.First install numpy:$ pip install numpyThen the remaining requirements:$ pip install -r requirements.txtRun individual processes and compositesEach process file underchemotaxis/processescan run on its own. Some of these have their own command line options.
For example, call thechemoreptor_clusterprocess with:$ python chemotaxis/processes/chemoreptor_cluster.pyComposites with multiple integrated processes can also be executed on their own:$ python chemotaxis/composites/chemotaxis_flagella.pyExperimentsAll experiments from the paper are available in the filechemotaxis/experiments/paper_experiments.py. Run them from
the command line by specifying the corresponding figure number.$ python chemotaxis/experiments/paper_experiments.py 7bTestsTests are performed with pytest. Simply call the following to ensure everything is working properly:$ pytestTo run only the fast tests:$ pytest -m 'not slow'LoggingTo print out logging information, run a simulation with:$ LOGLEVEL=INFO python chemotaxis/..