Saravanan666/pypi-org huggingface dataset:
Package: blp
Aboutblpprovides a simple pythonic interface to theblpapipackage.blpis the next iteration of thepdblppackage.blpwas designed with the following in mindExplicit separation of session management, event parsing and event aggregationExtensibilityInstallationYou can install from PyPI usingpip install blpor from conda-forge usingconda install -c conda-forge blpGetting StartedReading the docs is the best way to get started, take a look atQuickstartor if you are having issuesTroubleshootingContributingPlease refer toContributingfor guidelines on contributing.Bloomberg DocumentationFor documentation on the Bloomberg API check out the Developer's Guide. For documentation on relevant Bloomberg fields
for accessing data, check out the Reference Guide: Services and Schemas. To access these, from a  Bloomberg Terminal
goWAPI <GO>->API Developer's Guide.
Package: blpapipd
blpapipdExtract Bloomberg (BBG) data into pandas timeseries object w/ caching.  Leverages blpapi desktop api in Python
Use accompanying plot_utilities to plot results
See examples/barc_hy_vs_ig.ipynb for a use case of the packageTo install prerequisite blpapi package, use command below:python -m pip install --index-url=https://bcms.bloomberg.com/pip/simpleblpapiFor more detail, see github projecthttps://github.com/tnicolas/blpapipdSend inquiries tot@steinbachs.us
Package: blpapi-stubs
blpapi-stubsMypy stubs forblpapi.NoteThe latest version3.18.0of blpapi (2022-03-03) is typed; you really only need these stubs if using an older version:3.17.1or earlier.Installationpython -m pip install blpapi-stubsIt is not necessary to modify yourconfig.inias the files are placed alongside their.pycounterparts.
Package: blpdecode
=========
blpdecodeBarracuda LinkProtect DecoderFree software: MIT licenseDocumentation:https://blpdecode.readthedocs.io.CreditsThis package was created with Cookiecutter andrstms/cookiecutter-python-cli, a fork of theaudreyr/cookiecutter-pypackageproject template.audreyr/cookiecutteraudreyr/cookiecutter-pypackagerstms/cookiecutter-python-cli
Package: blp-helpers-data-science
What it hasHelpers I use for Data Science projectsAdditional infohttps://pypi.org/project/blp-helpers-data-science/https://github.com/leugh/helpers_data_scienceHow to use itpython pip install blp-helpers-data-scienceHow to develop itEnsure setuptools is installed:pip install --user --upgrade setuptools wheelEnsure twine is installedpip install --user --upgrade twineMake changesUpdate CHANGELOG.mdUpdate setup.pyCreate distribution packagespython setup.py sdist bdist_wheelUpload to pypipython -m twine upload dist/*Source:https://widdowquinn.github.io/coding/update-pypi-package/
Package: bl-predictor
bl-predictorBl-predictor is a simple application for predicting game results for the German 1. Bundesliga.It features a clean graphical user interface (including DarkMode to spare your eyes), automatic data crawling, a variety of
prediction-models to choose from, and a few built-in model evaluation tools.UsageInstall:pipinstallbl-predictorand start the GUI:bl-predictor-guiThe left column shows you the next upcoming matches. These are automatically crawled fromOpenligaDBwhen the application starts.The center column gives you the option to tweak your prediction preferences:choose the seasons used for training the model via the sliderselect amodelto trainchoose a home and guest teamYour result and additional information about the model used will appear in the righthand column.To make another prediction just use one of the reset-options on the bottom-left.You can switch to dark mode or exit the application under "Options" in the top-left corner.Prediction modelsPoissonModelA model that predicts the winning team out of two given teams, based on a poisson regression model.Caution:The model is sensitive to the order of given teams, because the home_team scores better on average!
This model is heavily based on aguideline from David Sheehan.BettingPoissonModelA adaptation of the PoissonModel improved for betting.If no relevant (>10%) difference in the teams winning probabilities is present, "Draw" is returned.FrequencyModelA model that uses all results of the last seasons to predict a winner based on the relative frequency of wins.Model EvaluationThe model evaluation features no graphical user interface.To access it you will need to go into the package source files toprediction_evaluation.pyand call the functions given at the bottom of the file. You can:generate a plot about the accuracy / F1-score of all models with different trainset sizesevaluate a single models performancetrainset informationperformance measures((Betting-)PoissonModel also returns a team-ranking based on the models coefficients)compare two modelsget general statistics about a trainsetThe results will either be given as printout in the console or as plots.png and will look something like this:Licensebl-predictor is made available under theMIT-License
Package: blqs
blqs: Building Blocks for Domain Specific LanguagesBlqs is a framework for building (internal) domain specific language that can be written
in Python. It was inspired by TensorFlow's autograph library, and motivated by the state of
the art (circa 2021) in quantum programming frameworks like Cirq and Qiskit.In short blqs let you define domain specific languages and gives you access to use native
Python features likeif,while, orforin these languages. This fills in a missing
feature for Python, which while they do have operator overloading, does not allow for
overloading these built in constructions.Example:importblqsH,M,CX=blqs.Op('H'),blqs.Op('M'),blqs.Op('CX')@blqs.builddefhello_blqs():a=blqs.Register('a')H(0)M(0,'a')ifa:CX(0,1)else:CX(1,0)Then, if we call this method, we will produce ablqs.Programthat includes both statements,
likeH(0)but also theifandelsestatements.program=hello_blqs()forsinprogram:print(type(s))>prints><class'blqs.instruction.Instruction'>><class'blqs.instruction.Instruction'>><class'blqs.conditional.If'>Where the last statement contains blocks that hold theCXstatements.InstallationTo install blqs one can simply pip install the appropriate packagepip install blqsSeerequirements.txtfor the dependencies that blqs will
pull in.DocumentationA good place to get started is to read theintroduction to blqs.
After that, the ideas and abstractions in blqs are described in theconcepts guide. To learn about support for capturing native
python code, see refer to theprotocols sectionof the docs.
For a quick intro via a jupyter notebook, seehello blqs.
Package: blqs-cirq
blqs_cirq: Taking the pain out of writing Cirq programsBlqs_cirq is a library that uses blqs to make it easier to write Cirq programs.Here is the creation of a simple circuit in Cirqimportcirqcircuit=cirq.Circuit()q0,q1=cirq.LineQubit.range(2)circuit.append(cirq.H(q0))circuit.append(cirq.CX(q0,q1))circuit.append(measure(q0,key='a'))Blqs_cirq makes it so that you can write this more like a normal imperative
programimportblqs_cirqasbcfromblqs_cirqimportCX,H,measure# Write the function imperatively.@bc.builddefmy_circuit():H(0)CX(0,1)measure(q0,key='a')# To create the circuit we simply call the function.circuit=my_circuit()Blqs provides supports for all the gates in Cirq, along with all the various ways to use
these gates to create operations.But wait, there is more.  Blqs_cirq supportsSimplification of qubit specification.  Instead of creatingLineQubitorNamedQubit, etc.,
one can simply use integers (converted toLineQubits), 2-tuples or 2-lists (converted toGridQubits) or strings (converted toNamedQubits). Custom conversions are also possible.Simplification of control flow primitives. For example Cirq currently supports a subcircuit
which can be repeated. For example here we repeat a small circuit within our circuit:@bc.builddefmy_circuit():H(1)withRepeat(repetitions=10):H(0)CX(0,1)As more control operations are added to Cirq these will be added to blqs_cirq.Simple building of Moments.  For example, the code below builds two moments:@bc.builddefmy_circuit():withMoment():bc.H(0)withMoment():bc.H(1)Support for Cirq's insertion strategies:@bc.builddefmy_circuit():withbc.InsertStrategy(cirq.InsertStrategy.NEW):H(0)H(1)InstallationTo install blqs_cirq one can simply pip install the appropriate packagepip install blqs_cirqNote that installing blqs_cirq will also install blqs and cirq.DocumentationA good place to start is with theintroduction, followed by a look
at the importantfeatures. For a quick intro via a jupyter notebook,
seehello blqs_cirq.
Package: bl_scrypture
Scrypture – a standalone event storeInstallTODOConfigureThe application is configured using environment variables.The available configuration variables are:SCRYPTURE_READ_ONLYSCRYPTURE_DSNSCRYPTURE_REDIS_HOSTSCRYPTURE_REDIS_PORTSCRYPTURE_REDIS_DBInitialiseOnce configured, you must initialise the database with the dedicated command:$scryptureinit-dbRunIt requires Redis:docker run --rm --name scrypture-redis -p 6379:6379 redisAs a Flask application, it can be run using any WSGI server,
for instance, withGunicorn:$gunicorn\--access-logfile="-"\--worker-classgevent\--workers4\--bind127.0.0.1:5000\"bl_scrypture.configuration.wsgi:app()"Notice that we are usinggeventworkers as some clients might follow some streams.ContributeSeeCONTRIBUTING.mdto set up a development environment.
Package: bl-seth
SethA setting management library. By grouping all your application settings in one class,
it's easier to document.First, define a class for your settings. It must be adataclass(or even better,
a frozendataclass) and inherit fromseth.Settings.fromdataclassesimportdataclassfromtypingimportOptionalfrombl_sethimportSettings@dataclassclassMySettings(Settings):MANDATORY:str"A mandatory string."DEFAULT:str="default""""A string that defaults to '"default"'."""INTEGER:int=1"An integer that defaults to '1'."OPTIONAL:Optional[str]=None"An optional value."Then instantiate it using itsfrom_dictclass method. Most probably, the dictionary
is built from the environment.importossettings=MySettings.from_dict(os.environ)You can now directly access its attributes.settings.DEFAULT=="default"settings.OPTIONALisNone
Package: bls-lib
BLS SignaturesA simple Python implementation of threshold BLS signatures.A link to the full paper is available at the following address:https://iacr.org/archive/asiacrypt2001/22480516.pdfPre-requisitesThis implementation is built on top ofpetlibandbplib, make sure to followthese instructionsto install all the pre-requisites.InstallIf you havepipinstalled, you can installblswith the following command:$ pip install bls-libotherwise, you can build it manually as below:$ git clone https://github.com/asonnino/bls
$ cd bls
$ pip install -e .TestTests can be run as follows:$ pytest -v --cov=bls tests/or simply using tox:$ toxLicenseThe GPLv3 license
Package: bls.py
An efficient reference implementation of the box least squares algorithm for
transiting exoplanet search in Python.
This will eventually be submitted as a pull request to the core AstroPy package, but
we’re making it available here for now to make it easy to use right away.PrerequisitesTo install and run this package, you will need to have NumPy, Cython, and AstroPy installed.
The recommended installation method is:condainstallnumpycythonastropyInstallationTo install, clone this repository and build the extension as follows:gitclonehttps://github.com/dfm/bls.py.gitcdbls.pypythonsetup.pyinstallor, install usingpip:pipinstallbls.pyOpenMP support: This algorithm can optionally be parallelized using OpenMP.
To enable this feature, you must compile with a compiler that supports OpenMP and the
relevant flags. On macOS, this can be achieved by installing a recentllvm:brewinstallllvmand then building using the following flags:CC=/usr/local/opt/llvm/bin/clang\LDFLAGS="-L/usr/local/opt/llvm/lib -Wl,-rpath,/usr/local/opt/llvm/lib -liomp5"\CFLAGS="-I/usr/local/opt/llvm/include -fopenmp"\pythonsetup.pyinstallOn other platforms, a command like the following might be sufficient:CFLAGS="-lgomp -fopenmp"pythonsetup.pyinstallUsageSeetutorial.ipynbfor a demonstration of how to use the code.
Package: blt
# blt: provides simple CLI superpowersbltis a python package that aims to make it easier for application
developers to wrap command line interfaces for the various tools they use day
to day. blt was inspired by Heroku’s toolbelt, fabric, and clint. We hope
to stand on the shoulders of giants.## OverviewAt blt’s root is the concept of atool, blt provides several tools out of
the box. Currently we have support for:AWS (S3)DjangoHerokuSouth (django database migrations)These tools encapsulate commands that you would want to interface with each
system. For example, you might want to be able to push files to an S3 bucket
with the AWS tool, or you might want to run a migration using the South tool.
blt standardizes the interface for running the command and handles things like
configuration injection so you can easily differentiate between dev/staging/prod
settings when running a command.## Real-world ExampleLet’s take a quick look at a practical example of blt in action. Here is a sample
command for running an AWS S3 sync on our staging environment:`bash blt e:staging aws.sync_s3 /path/to/my/dir `That’s it! Running that command will pick up the staging environment
configuration, connect to S3, determine the changed files between the S3 bucket
and the files in /path/to/my/dir, and push them up to AWS. blt is able to
automatically grab things like AWS authentication keys for staging and inject
the settings into the runtime so blt can connect to the bucket. Pretty sweet!## blt Grammarblt has an opinionated command grammar and enforces a strict way of running
commands for tools. blt was designed to have a consistent run style so that no
matter what tool you are running commands for, it will have the same basic
format.  Let’s break down the aws run from above:blt          e:staging     aws       .       sync_s3    /path/to/my/dir^               ^          ^        ^          ^              ^
|               |          |        |          |              |
|               |          |        |          |              |blt executable   environment    tool   separator  command         args## InstallationCurrently blt is not on PyPI, so you’ll need to build/install from the filesystem. Here are the steps to accomplish this:#### Clone the blt rep`bash git clone git@github.com:pubvest/utils.git `#### Run the sdist directive on setup.py`bash cd utils/blt python setup.py sdist `#### Install via pip`bash cd utils/blt/dist pip installblt-VERSION.tar.gz`## More to come!More documentaion/examples to come down the road!
Package: blubber-orm
Hubbub BlubberNotice - this package is only compatible with Hubbub projects.Getting StartedBlubber is an internal object relational mapper for Hubbub's marketplace database. This is important for consistent object structure across all of Hubbub's projects. It's called 'Blubber' because it's a thick layer on raw data (lol)PrerequisitesBlubber requires you to define two variables in your environment: 'BLUBBER_DEBUG' and 'DATABASE_URL'.'DATABASE_URL' must be a postgresql URL formatted as 'postgresql://NAME:PASSWORD@HOST:PORT/USER'.
'BLUBBER_DEBUG' takes a value of '0' for FALSE or '1' for TRUE. Set these before using, and Blubber will run smoothly:export BLUBBER_DEBUG=1
export DATABASE_URL=postgresql://fakeUser:fakePassword@localhost:5432/fakeDBInstallingRun the following command in terminal to install the python package:pip3 install blubber-ormAbout BLUBBER_DEBUGIn debug mode, Blubber will print all of your queries to terminal. In a future release, these outputs will also catch errors and can be configured to log to a file or email to an admin.Developer ToolsCreate a play-version of the Hubbub database and fill it with dummy data under /src/blubber_orm/dev!Built Withpsycopg2- The DBAPI for running posgresql queriesContributingBlubber is currently not taking contributions. This policy may change in the future.LicenseThis project is licensed under the Apache License 2.0 - see theLICENSE.mdfile for details
Package: blu-blade-templating
BLADE TemplatingOne of the many possible benefits to using BLADE is the ability to automatically generate RTL (Register Transfer Language), documentation, SDK support, and more for your design. Generated files can take advantage of the hierarchical description of the design, connectivity information, address maps and much more.The example designs provided with BLADE provide an example of how this templating engine can be integrated with a hardware design flow.BLADE Templating is built on top of Mako - a flexible and powerful Python templating engine. Traditionally it has been used for generating web pages, but it is more than flexible enough to cope with generating Verilog, VHDL, SystemC, and more. Further details can be foundhere.System RequirementsLike BLADE, the templator is a Python based tool and has a few dependencies:Python 3.6 or greaterMako- The underlying templating engineDesignFormat- The interchange format used by BLADE
Package: blueair
Theblueairpackage contains an unofficial Python client for the Blueair air purifiers. It can be used both as a library and as a standalone command line utility. When running the command line utility graphs can be generated showing historical data.InstallationFirst of all, ensure you are running Python 3.7 or newer. Installation of the package is as simple as running:$pipinstallblueairAfter running this command theblueairpackage is available for importing in Python, and the command line interface can be accessed by runningpython -m blueair.CompatibilityThis package is inteded to be used with Python 3.7 or newer. It has been annotated with type extensions and supports PEP 561 typed packages.DisclaimerThe software is provided “as is”, without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. In no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the software or the use or other dealings in the software.This package and its authors are not affiliated by Blueair. For support regarding this package, please do not contact Blueair but instead file an issue using the package repository’s issue tracker.This package has only been tested using a Blueair Classic 280i air purifier located somewhere in Europe. It may or may not work for different models or locations.AcknowledgementsThis package would not exist without the work of @mylesagray, who created a Blueair homebridge plugin that can be found athttps://github.com/mylesagray/homebridge-blueair.LicenseThis package is released under the terms of the MIT license. A copy of the license can be found in the package repository.
Package: blueapi
Lightweight bluesky-as-a-service wrapper application. Also usable as a library.PyPIpip install blueapiSource codehttps://github.com/DiamondLightSource/blueapiDocumentationhttps://DiamondLightSource.github.io/blueapiReleaseshttps://github.com/DiamondLightSource/blueapi/releasesThis module wrapsblueskyplans and devices inside a server and exposes endpoints to send commands/receive data.
Useful for installation at labs where multiple people may control equipment,
possibly from remote locations.The main premise of blueapi is to minimize the boilerplate required to get plans
and devices up and running by generating an API for your lab out of type-annotated
plans. For example, take the following plan:importbluesky.plansasbpfromblueapi.coreimportMsgGeneratordefmy_plan(foo:str,bar:int)->MsgGenerator:yield frombp.scan(...)Blueapi’s job is to detect this plan and automatically add it to the lab’s API so it
can be invoked easily with a few REST calls.Seehttps://DiamondLightSource.github.io/blueapifor more detailed documentation.
Package: blueapps
蓝鲸Python开发框架Blueapps重要提示:master分支是开发分支，可能处于不稳定或者不可用状态。请通过releases而非master去获取稳定的软件包蓝鲸Python开发框架Blueapps可以帮助开发人员快速在蓝鲸 PaaS 平台上开发 SaaS 的Python 框架。该开发框架基于Django 框架架构，并在此基础上进行扩展，增加蓝鲸系统的特有功能，例如：身份验证、ESB 调用及模板渲染等功能，以便开发者可以更专注于 SaaS 的逻辑开发。本次开源的是蓝鲸Python开发框架Blueapps打包编译环境，执行打包构建后开发人员可以直接基于源码提供的功能进行开发。Overview快速开始代码目录配置管理apigw自动注册使用说明Roadmap版本日志Support蓝鲸论坛联系我们，技术交流QQ群：社区版QQ交流群：495299374蓝鲸运维开发交流群：878501914BlueKing CommunityBK-CMDB: 蓝鲸配置平台（蓝鲸 CMDB）是一个面向资产及应用的企业级配置管理平台。BK-CI: 蓝鲸持续集成平台是一个开源的持续集成和持续交付系统，可以轻松将你的研发流程呈现到你面前。BK-BCS: 蓝鲸容器管理平台是以容器技术为基础，为微服务业务提供编排管理的基础服务平台。BK-BCS-SaaS: 蓝鲸容器管理平台 SaaS 基于原生 Kubernetes 和 Mesos 自研的两种模式，提供给用户高度可扩展、灵活易用的容器产品服务。BK-PaaS: 蓝鲸 PaaS 平台是一个开放式的开发平台，让开发者可以方便快捷地创建、开发、部署和管理 SaaS 应用。BK-SOPS: 标准运维（SOPS）是通过可视化的图形界面进行任务流程编排和执行的系统，是蓝鲸体系中一款轻量级的调度编排类 SaaS 产品。BK-JOB: 蓝鲸作业平台(Job)是一套运维脚本管理系统，具备海量任务并发处理能力。Contributing对于项目感兴趣，想一起贡献并完善项目请参阅Contributing Guide。腾讯开源激励计划鼓励开发者的参与和贡献，期待你的加入。FAQ请查看FAQLicense基于 MIT 协议， 详细请参考LICENSE
Package: blueapps-open
# 蓝鲸Python开发框架Blueapps![blueapps](docs/resource/img/blueapps.png)[![license](https://img.shields.io/badge/license-mit-brightgreen.svg?style=flat)](https://github.com/TencentBlueKing/blueapps/blob/master/LICENSE) [![Release Version](https://img.shields.io/badge/release-3.3.3-brightgreen.svg)](https://github.com/TencentBlueKing/blueapps/releases) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/TencentBlueKing/blueapps/pulls)>重要提示:master分支是开发分支，可能处于不稳定或者不可用状态。请通过[releases](https://github.com/TencentBlueKing/blueapps/releases) 而非master去获取稳定的软件包蓝鲸Python开发框架Blueapps可以帮助开发人员快速在蓝鲸 PaaS 平台上开发 SaaS 的Python 框架。该开发框架基于Django 框架架构，并在此基础上进行扩展，增加蓝鲸系统的特有功能，例如：身份验证、ESB 调用及模板渲染等功能，以便开发者可以更专注于 SaaS 的逻辑开发。本次开源的是蓝鲸Python开发框架Blueapps打包编译环境，执行打包构建后开发人员可以直接基于源码提供的功能进行开发。## Overview[快速开始](docs/overview/project_usage.md)[代码目录](docs/overview/project_codes.md)[使用说明](https://bk.tencent.com/docs/document/6.0/130/5949)## Roadmap[版本日志](docs/release.md)## Support[蓝鲸论坛](https://bk.tencent.com/s-mart/community)联系我们，技术交流QQ群：社区版QQ交流群：495299374蓝鲸运维开发交流群：878501914<img src=”docs/resource/img/QR-Code.png” align=center style=”zoom:67%;” />## Contributing
对于项目感兴趣，想一起贡献并完善项目请参阅[Contributing Guide](docs/CONTRIBUTING.md)。[腾讯开源激励计划](https://opensource.tencent.com/contribution) 鼓励开发者的参与和贡献，期待你的加入。## FAQ请查看 [FAQ](docs/faq.md)## License基于 MIT 协议， 详细请参考[LICENSE](LICENSE.txt)
Package: bluebees
# BlueBees![GitHub](https://img.shields.io/github/license/matheuswhite/bluebees.svg?style=popout)
[![Build Status](https://travis-ci.org/matheuswhite/bluebees.svg?branch=master)](https://travis-ci.org/matheuswhite/bluebees)
[![Requirements Status](https://requires.io/github/matheuswhite/bluebees/requirements.svg?branch=master)](https://requires.io/github/matheuswhite/bluebees/requirements/?branch=master)
[![codecov](https://codecov.io/gh/matheuswhite/bluebees/branch/master/graph/badge.svg)](https://codecov.io/gh/matheuswhite/bluebees)
[![Maintainability](https://api.codeclimate.com/v1/badges/47e7df71e0d21bc5b1c4/maintainability)](https://codeclimate.com/github/matheuswhite/bluebees/maintainability)## What is Bluebees?
Bluebees is a complete tool to configure Bluetooth Mesh Networks.## Principles## Why Bluebees?
### Positive Point 1### Positive Point 2### Positive Point 3## Features## Documentation## Getting Started## Dependencies## Questions/Help## Contributing## License
Package: bluebell
bluebellbluebellis a Python package for estimating the uncertainties of
parameters in least-squares problems by computing minimum-volume
bounding ellipsoids (MVBEs). Given a set of pointsxat which someχ²has been evaluated,bluebellcomputes the uncertainties on the
pointsxby computing the MVBE around the points, moved by their
values ofχ²such that, if the problem is exactly linear, all the
points lie on the same ellipsoid.Installbluebellfrom PyPI withpython -m pip install bluebellRead the documentation onRead the Docs.