Saravanan666/pypi-org huggingface dataset:
Package: baumanecbank-common
Пакет основных функций для ботов БауБанкаДля работы требуются пременные окружения:PG_HOST- значение по-умолчаниюlocalhostPG_PORT- значение по-умолчанию5432PG_USER- значение по-умолчаниюgovernment_appPG_PASSWORD- значение по-умолчаниюgovernment_appPG_DATABASE- значение по-умолчаниюpostgresAPP_NAME- значение по-умолчаниюgovernmentI18N_DIR- значение по-умолчанию../i18nI18N_LOCALE- значение по-умолчаниюru-RU
Package: bautils
python-bautilsbautils is a Python module implementing some useful helper functions for
working with the Pythonbitarraymodule.
Specifically, bautils supports adding (and, coming soon) other basic
arithmetic operations on bitarrays as if they were arbitrary length
binary numbers, something the bitarray package itself doesn’t seem to
support.It also contains helper methods to convert between the binary arrays in
the pure Python bitstring moduleI opted to put these functions in a new module; none are terribly
complicated to implement, so they’re essentially just a set of
convenient wrappers.Unit tests are also a work in progress.Changelog:This logs changes starting from version 0.1.1.Version 0.1.4Fix another namespace issue in minb and maxb functions.Version 0.1.3Add tests for the random, minb, and maxb functions, mostly completing
tests.Fix namespace collision issue between bautils.random and random
module.Version 0.1.2Adds unit tests for left and right shift functions.Fixes bug where left/right shifts modified their input.Credits, Legalbautils is written by Ben Rosserrosser.bjr@gmail.com, and is released
under the MIT License (see LICENSE file).
Package: bauwerk
WarningBauwerk is in a very early stage of development, not stable at the moment and not recommended for general usage at this point. Use at your own risk.bauwerkSuper simple building control environments for reinforcement learning.Free software: MIT licenseDocumentation:https://bauwerk.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.3.2 (2022-12-00)ImprovementsAdd information on evaluation to docs.FixesImprove plotting/widget code to comply with stricter shape testing in newer matplotlib versions0.3.1 (2022-11-03)FeaturesNew building distributions:Building Distribution C: varies battery and solar installation size.Building Distribution D: varies battery, solar installation and load consumption size/scale.Building distribution E: varies same as above, and adds irreducible noise to load and solar traces.Environment & distribution changes (! indicates that the change may affect experimental results)!Parameter default ofgrid_peak_thresholdchanged from 4.0kW to 2.0kW in all environments, including those of building distribution B.The load and solar traces inHouseEnvnow can be augmented with irreducible noise. This is set via thesolar/load_noise_magnitudeparameter of theEnvConfig.ImprovementsUpdate to docs on distributions, wrappers and more.0.3.0 (2022-10-26)FeaturesAdd experiment scriptAdd extensive evaluation featuresAdd support for much slower speed in game widgetAdd benchmarksAdd support for setting tasks in environmentAdd wrappers:that add task parameters to observation space.that clip the rewardthat clip the action spacethat normalise observation spaceImprovementsAdd clock and day to game widgetDesign improvements for game widgetAction spaces dtype can now be set in env cfg0.2.1 (2022-09-12)FeaturesAddtime_of_dayvariable to observation space.ImprovementsThesolvefunction is now directly imported withbauwerk, to simplify usage.Additional sections added to documentation.Add more grid parameters toSolarBatteryHouseEnvconfiguration.Fixes:Ensure solver outputs actions that are valid in environment (i.e. normalised)0.2.0 (2022-09-09)Features:Add game widget based onSolarBatteryHouseEnv.Includes browser-based version of Bauwerk game that can be played by anybody without installing anything.Add support for selling to the grid inSolarBatteryHouseEnv.Improvements:Add explicit CVXPY-based solver inbauwerk.envs.solversforSolarBatteryHouseEnvthat was missing earlier.UpdateSolarBatteryHouseEnvto comply with new gym step API by returningtruncatedvalue.Add automatic github-actions-based testing of package.0.1.0 (2022-08-12)First release on PyPI.Features:SolarBatteryHouseEnv: a simple environment representing a single family home with a solar photovoltaic installations and a home battery that can be controlled.Optional integration with CVXPY to compute optimal actions in Bauwerk environments.
Package: bauxite
BauxiteBauxite is a robust, low-level connector for the Discord API.What is Bauxite for?Bauxite is made for two main purposes:Creating higher-level API wrappers and frameworksCreating things that need high levels of control and low-level access to the Discord APIExamplesBasic HTTP ExamplefromasyncioimportrunfrombauxiteimportHTTPClient,Routeasyncdefmain()->None:client=HTTPClient("your_bot_token")awaitclient.request(Route("POST","/channels/{channel_id}/messages",channel_id=1234),json={"content":"Hello, world!",},)awaitclient.close()run(main())Basic Gateway ExamplefromasyncioimportrunfrombauxiteimportGatewayClient,HTTPClientasyncdefcallback(shard,direction,data)->None:print(f"{shard}[{direction}]:{data['op']ordata['t']}")asyncdefmain()->None:client=HTTPClient("your_bot_token")gateway=GatewayClient(client,32767,callbacks=[callback])awaitgateway.spawn_shards()run(main())
Package: bavard
bavard-nluLocal DevelopmentInstall Dependenciespip3 install -e .
pip3 install -r requirements-test.txtTesting LocallyThe tests for this repo consist of functional tests for catching bugs/code regressions, validation tests for catching model performance regressions, and integration tests for testing the NLU docker containers and their interactions. The validation and integration tests take much longer to execute. All are run in CI. To run the tests locally:./test/scripts/lint-and-test.sh <test_suite>Where<test_suitedenotes the type of tests to run, and allows these options:functional- Runs just the functional tests.integration(default) - Runs both the functional and integration tests.all- Runs the functional, integration, and validation tests.To run both the functional and integration tests:The Package CLIThere is a convenience CLI for training, evaluating, predicting, tuning, and interacting with NLU and dialogue policy models. To see the CLI documentation:python3 -m bavard --helpYou can also view the documentation for a sub-command for example:python3 -m bavard nlu evaluate  --helpReleasing The PackageReleasing the package is automatically handled by CI, but three steps must be taken to trigger a successful release:Increment theVERSIONvariable insetup.pyto the new desired version (e.g.VERSION="1.1.1")Commit and tag the repo with theexact samevalue you populated theVERSIONvariable with (e.g.git tag 1.1.1)Push the commit and tag to remote. These can be done together using:git push --atomic origin <branch name> <tag>CI will then release the package to pypi with that version once the commit and tag are pushed.
Package: bavard-ml-utils
bavard-ml-utilsA package of common code and utilities for machine learning and MLOps. Includes classes and methods for:ML model serialization/deserializationGoogle Cloud Storage IO operationsConverting a ML model into a runnable web serviceCommon ML model evaluation utilitiesCommon data structures/models used across the Bavard AI organizationML model artifact persistence and version managementAnd moreThis package maintains common data structures used across our organization. They can all be found in thebavard_ml_utils.typessub-package, and are allPydanticdata models. For example thebavard_ml_utils.types.agent.AgentConfigclass represents a chatbot's configuration and training data, and is used heavily across Bavard.API docs for this package can be foundhere.Getting StartedTo begin using the package, use your favorite package manager to install it from PyPi. For example, using pip:pip install bavard-ml-utilsSome of the features in this repo require more heavy weight dependencies, like Google Cloud Platform related utilities, or utilities specific to machine-learning. If you try to import those features, they will tell you if you do not have the correct package extra installed. For example, many of the features in thebavard_ml_utils.gcpsub-package require thegcpextra. To installbavard-ml-utilswith that extra:pip install bavard-ml-utils[gcp]You can then begin using any package features that require GCP dependencies.Developing LocallyBefore making any new commits or pull requests, please complete these steps.Install the Poetry package manager for Python if you do not already have it. Installation instructions can be foundhere.Clone the project:git clone https://github.com/bavard-ai/bavard-ml-utils.git
cd bavard-ml-utilsInstall the dependencies, including all dev dependencies and extras:poetry install --extras "gcp ml"Install the pre-commit hooks, so they will run before each local commit. This includes linting, auto-formatting, and import sorting:pre-commit installTesting LocallyWith Docker and docker-compose installed, run this script from the project root:./scripts/lint-and-test-package.shReleasing The PackageReleasing the package is automatically handled by CI, but three steps must be taken to trigger a successful release:Use Poetry'sversioncommandto bump the package's version.Commit and tag the repo with the exact same version the package was bumped to, e.g.1.0.0(note there is no precedingv.)Push the commit and tag to remote. These can be done together using:git push --atomic origin <branch name> <tag>CI will then build release the package to pypi with that version once the commit and tag are pushed.
Package: bavard-nlu
# bavard-nlu## Releasing The PackageReleasing the package is automatically handled by CI, but three steps must be taken to trigger a successful release:Increment theVERSIONvariable insetup.pyto the new desired version (e.g.VERSION=”1.1.1”)Commit and tag the repo with theexact samevalue you populated theVERSIONvariable with (e.g.git tag 1.1.1)Push the commit and tag to remote. These can be done together using:git push –atomic origin <branch name> <tag>CI will then release the package to pypi with that version once the commit and tag are pushed.## Local Development### Install Dependencies` pip3 install-e. pip3 install-rrequirements-test.txt`### NLUModel CLIThere is a convenience CLI for training, evaluating, predicting, tuning, and interacting with NLU models. To see the CLI documentation:` python3-mbavard_nlu.cli--help`You can also view the documentation for a sub-command for example:` python3-mbavard_nlu.cli train--help`## Testing LocallyThe tests for this repo consist of functional tests for catching bugs/code regressions, and validation tests for catching model performance regressions. The validation tests take much longer to execute. Both are run in CI. To run just the functional tests:` python3-munittest discover test/functional `
Package: bavera
A modern, easy to use, feature-rich, and async ready API wrapper for Discord written in Python.Key FeaturesModern Pythonic API usingasyncandawait.Proper rate limit handling.Optimised in both speed and memory.InstallingPython 3.8 or higher is requiredTo install the library without full voice support, you can just run the following command:# Linux/macOSpython3-mpipinstall-Ubavera# Windowspy-3-mpipinstall-UbaveraOtherwise to get voice support you should run the following command:# Linux/macOSpython3-mpipinstall-U"bavera[voice]"# Windowspy-3-mpipinstall-Ubavera[voice]To install the speed version with additional speedups run the following command:# Linux/MacOSpython3-mpipinstall-Ubavera[speed]# Windowspy-3-mpipinstall-Ubavera[speed]To install the development version, do the following:$gitclonehttps://github.com/bavera/bavera$cdbavera$python3-mpipinstall-U.[voice]Optional PackagesPyNaCl(for voice support)Please note that on Linux installing voice you must install the following packages via your favourite package manager (e.g.apt,dnf, etc) before running the above commands:libffi-dev (orlibffi-develon some systems)python-dev (e.g.python3.8-devfor Python 3.8)Quick ExampleimportbaveraclassMyClient(bavera.Plugin):asyncdefon_ready(self):print('Logged on as',self.user)asyncdefon_message(self,message):# don't respond to ourselvesifmessage.author==self.user:returnifmessage.content=='ping':awaitmessage.channel.send('pong')client=MyClient()client.run('token')Bot ExampleimportbaveraimportpluginsfrompluginsimportcommandsPlugger=commands.Plugger(command_prefix='>')@Plugger.command()asyncdefping(ctx):awaitctx.send('pong')Plugger.run('token')You can find more examples in the examples directory.LinksDocumentationOfficial Discord ServerDiscord API
Package: bavest
Bavest Python SDKThe Bavest Finance SDK is an open-source library to create finance products in weeks. Bavest offers:Financial api with 99.95% uptimeEasy to integrate and useFree for open-source projectsGet API keyFirst, you need to create aBavestaccount.
After registration, you will find your api key in the dashboard.Free API key for Open-Source projectsFirst, use theTypeFormto provide all required information.
After, you will receive an API key via E-Mail.TemplateimportosimportdateutilfrombavestimportBavestRESTClient,Resolutionfromdatetimeimportdatetimeimportdateutil.relativedeltaasrelativedeltaBAVEST_API_KEY=os.environ.get('BAVEST_API_KEY')client=BavestRESTClient(BAVEST_API_KEY)if__name__=="__main__":to=datetime.now()frm=to+dateutil.relativedelta.relativedelta(days=-2)to=to+dateutil.relativedelta.relativedelta(days=-1)resolution=Resolution.DAILYcandles=client.candles("AAPL",frm,to,resolution)Install the packageFirst install the python package usingpip:pipinstallbavestDocumentationSeeherefor more information.UsageNow, use the package in your project:frombavestimportBavestRESTClientCreate a financeclient:client=BavestRestClient(apiKey)Now you can use it to get data from the api:quote=client.quote("AAPL")Examplesto=datetime.now()frm=to+dateutil.relativedelta.relativedelta(days=-20)resolution=Resolution.MONTHLYcandles=client.candles(symbol,frm,to,resolution)news=client.news(symbol)search=client.search(symbol)forex=client.forex(frm,to)# ETFetfSector=client.etf.sector(symbol)etfCountry=client.etf.country(symbol)etfHoldings=client.etf.holdings(symbol)etfProfile=client.etf.profile(symbol)# Portfolio ItemstransactionItem=TransactionItem("MSFT",2,frm).get()transactionList=[transactionItem]portfolioRegion=client.portfolio.region(transactionList)portfolioStats=client.portfolio.stats(frm,to,resolution,transactionList,"USD")portfolioChart=client.portfolio.chart(frm,to,resolution,transactionList):octocat: CreditsWilliam Todtwilliam.todt@bavest.co- MaintainerHisham Parveezhisham.parveez@bavest.co- MaintainerContactPlease open a Github issue or send us an email atsupport@bavest.co.
Package: bavli-pages
bavli_pagesList of pages per Masechet at each chapter at the Jewish Talmud/Gemara/Shas Bavli.usage example:
    import bavli_pages as bp

    masechtot_dict = bp.bavli_pages_as_nested_data()
    hebrew_page = masechtot_dict['ברכות'].chapters[2].start.page_hebrew_string
    print('מסכת ברכות פרק שלישי מתחיל בדף')
    print(hebrew_page)
    
    
        מסכת ברכות פרק שלישי מתחיל בדף
        יז:         
    
    bavli_masechtot_with_chapters = bp.bavli_pages_per_chapter()
    print('רשימה של כל הפרקים בשס עם דף התחלה וסוף')
    print(bavli_masechtot_with_chapters)
    
    
            רשימה של כל הפרקים בשס עם דף התחלה וסוף
         masechet  chapter page chapter_side  page_number  page_first_side
        0    בבא בתרא        1   ב.        start            2             True
        1    בבא בתרא        1  יז.          end           17             True
        2    בבא בתרא        2  יז.        start           17             True
        3    בבא בתרא        2  כז:          end           27            False
        4    בבא בתרא        3  כח.        start           28             True
        ..        ...      ...  ...          ...          ...              ...
        621     תענית        2  יח:          end           18            False
        622     תענית        3  יח:        start           18            False
        623     תענית        3  כו.          end           26             True
        624     תענית        4  כו.        start           26             True
        625     תענית        4  לא:          end           31            False
        
        [626 rows x 6 columns]
        
        
    all_bavli_pages = bp.bavli_per_page()
    print(all_bavli_pages.iloc[10])
    
    
        masechet       בבא בתרא
        chapter               1
        pages                יב
        page_number          12
        Name: 10, dtype: object
        
        
    print('דף יב בכל המסכתות. רשימה של 4 המסכתות האחרונות')
    print(all_bavli_pages.query("pages=='יב'").tail(4).T)


        דף יב בכל המסכתות. רשימה של 4 המסכתות האחרונות
        masechet     שבועות  שבת  תמורה  תענית
        chapter           1    1      1      1
        pages            יב   יב     יב     יב
        page_number      12   12     12     12
Package: b-aws-cf
B.AwsCfA python based package that enables convenient interaction with
CloudFormation service boto3 library.DescriptionInteracting with AWS CloudFormation service via boto3 is great.
However, boto3 is far too low-level library giving you great
flexibility but too less productivity. This B.AwsCf library makes
interaction with CloudFormation more object-oriented and more
high-level. It eliminates things like pagination with "NextToken"
and so on.RemarksBiomapasaims to modernise life-science
industry by sharing its IT knowledge with other companies and
the community. This is an open source library intended to be used
by anyone. Improvements and pull requests are welcome.Related technologyPython 3AWS CloudFormationboto3AssumptionsThe project assumes the following:You have basic-good knowledge in python programming.You have basic-good knowledge in AWS.You have basic-good knowledge in AWS CloudFormation.Useful sourcesWhat is CloudFormation?:https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/Welcome.htmlCloudFormation with boto3:https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/cloudformation.htmlInstallThe project is built and uploaded to PyPi. Install it by using pip.pip install b_aws_cfOr directly install it through source.pip install .Usage & ExamplesProgrammatic usageTwo main constructs of this library isStackandStacks. TheStackclass lets you work with a single stack andStacksclass
lets you work with lists of stacks.Stackclass example.fromb_aws_cf.stackimportStack# Create stack object just by knowing its name:stack=Stack.from_name('MyCoolStack')# Gets this stack's outptus:outputs=stack.get_outputs()# Delete this stack:stack.delete()Stacksclass example:fromb_aws_cf.stacksimportStacks# List all of the stacks in your account:stacks=Stacks().list()# Delete all of the stacks with some specific prefix:Stacks().delete('MyPrefix')CLI usageThe library exposes CLI commands. Run (to find about more):cf --helpTestingThis project has integration tests based on pytest. To run tests, simply run:pytestContributionFound a bug? Want to add or suggest a new feature?Contributions of any kind are gladly welcome. You may contact us
directly, create a pull-request or an issue in github platform.
Lets modernize the world together.Release history0.2.1Add printing on deletion action.0.2.0Raise explicit exception if stack is not found.0.0.1Initial build.
Package: b-aws-cf-response
B.AwsCfResponseA python based library to send response back to
AWS Cloud Formation service after processing of
custom resource request.DescriptionSometimes a necessity to write custom AWS resource provisioning logic arises. After processing of
custom resource requests, a resource provider must send the standardized response back to
AWS CloudFormation service. This package makes a response message from a custom resource provider
event and sends a callback to AWS CloudFormation service.RemarksBiomapasaims to modernize life-science
industry by sharing its IT knowledge with other companies and
the community. This is an open source library intended to be used
by anyone. Improvements and pull requests are welcome.Related technologyPython 3AWS CloudFormationAssumptionsThe project assumes the following:You have basic-good knowledge in python programming.You have basic-good knowledge in AWS and CloudFormation.Useful sourcesRead more about Cloud Formation:https://docs.aws.amazon.com/cloudformation/index.htmlInstallThe project is built and uploaded to PyPi. Install it by using pip.pip install b-aws-cf-responseOr directly install it through source.pip install .Usage & ExamplesCreateCfResponseobject using event and context of custom resource provider:fromb_aws_cf_response.cfresponseimportCfResponseresponse=CfResponse(event,context)After successful provision of custom resource, initiate SUCCESS response. The response can include data from the custom resource provider. For example, created resource name.# Custom resource provider defined name-value pairs to send with response.custom_resource_data={'IndexName':'opensearch-index-name'}response.respond(status=CfResponse.CfResponseStatus.SUCCESS,data=custom_resource_data,resource_id=custom_resource_id)Initiate FAILED response if custom resource provisioning failed.response.respond(status=CfResponse.CfResponseStatus.FAILED,status_reason=error_message)TestingThe project has tests that can be run. Simply run:pytestContributionFound a bug? Want to add or suggest a new feature?Contributions of any kind are gladly welcome. You may contact us
directly, create a pull-request or an issue in github platform.
Lets modernize the world together.Release history0.0.2Update of Usage & Examples.0.0.1Initial build.
Package: b-aws-dynamodb-backup
B.AwsDynamoDbBackupA python based package that allows you to back up, restore, and seed dynamodb database tables.DescriptionSometimes you want to make a small modification to your dynamodb table, however it usually requires
destruction of the table itself. This library allows you to do those small modifications without
any headache. You can easily backup all your data to your local computer, delete the table, create
a new one with desired modifications, and then simply restore it!RemarksBiomapasaims to modernise life-science
industry by sharing its IT knowledge with other companies and
the community. This is an open source library intended to be used
by anyone. Improvements and pull requests are welcome.Related technologyPython 3DynamoDBBoto3AssumptionsThe project assumes the following:You have basic knowledge in python programming.You have basic knowledge in DynamoDB.Useful sourcesRead more DynamoDB:https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Programming.SDKOverview.htmlInstallThe project is built and uploaded to PyPi. Install it by using pip.pip install b_aws_dynamodb_backupOr directly install it through source.pip install .Usage & ExamplesThe library uses boto3 AWS SDK for interacting with AWS environment. Hence,
environmental credentials (such asaws_access_key_id,aws_secret_access_key, andregion_name)
are required.The library exposes cli commands. Read more about them down below.dyseedSeeds your table with random data.>dyseedTableNamedybackBackups your whole table(s).# Single table.>dybackTableName# All tables.>dybackdyrestRestores your whole table(s).# Single table.>dyrestTableName# All tables.>dyrestTestingThis project currently has no tests.ContributionFound a bug? Want to add or suggest a new feature?Contributions of any kind are gladly welcome. You may contact us
directly, create a pull-request or an issue in github platform.
Lets modernize the world together.Release history1.1.1Fix DynamoDB backup chunks all being written in the same file.1.1.0Handle byte types.1.0.0Allow to back up all tables.Allow to restore all tables.0.0.2Cleanup.0.0.1Initial build.