Saravanan666/pypi-org huggingface dataset:
Package: pybuilder-docker-build
PyBuilder Docker Build PluginSummaryThis project is a plugin forPyBuilderthat will perform a
docker build for a Python package.PyBuilder Docker Build Pluginattempts to use
sane defaults so that in most cases you only need add aDockerfileto your
project base directory and a docker image will be built when you call
the appropriate task.UsageTo use this plugin in yourbuild.pyfile add the following line to the
plugins section:use_plugin('pypi:pybuilder_docker_build')This will add the following tasks to your build:TaskDescriptiondocker_buildPerforms docker builddocker_saveSaves docker image to dist dirdocker_pushPushes docker image upstream to your repoThe following properties are available:PropertyValueDefaultUsagedocker_cliTrue / FalseFalseUse docker cli to do builddocker_pathstrdockerPath to docker executabledocker_build_pathstrbasedirpropertyPath to docker build directorydocker_build_filestrDockerfileDockerfile to use for build, relative path fromdocker_build_pathdocker_build_force_rmTrue / FalseFalseUse the force rm feature of docker builddocker_image_repostrproject.nameThe name of the image repositorydocker_image_tagstrlatestA tag to apply to the repositorydocker_build_argsdictNoneA dict of build argsdocker_registry_authdictNoneA dict containingusernameandpasswordfor login / authdocker_registrystrNoneA http / https URL of registry for authentication and pushBy default there are several build args that are supplied to the docker build, additional args can
be added with thedocker_build_argsproperty.  The default build args are:ArgumentValuePROJECT_NAMEproject.namePROJECT_VERSIONproject.versionPROJECT_DIST_VERSIONproject.dist_versionPROJECT_DIST_DIRThe relative path from thedocker_build_pathproperty to$dir_distAuthenticationIf you need to push images to a registry then you probably need to set credentials.  Don't
do this directly in your build file but rather look them up from environment or use some other
method for passing secrets to code.  The following is an extract from thehello-worldsample
project in thesamplesdirectory:@initdefset_properties(project:Project):project.set_property("docker_build_args",{"EXTRA_ARG":"Extra build arg"})project.set_property("docker_image_repo","dockerhubusername/hello-world")# Don't put your credentials in code, look them up from environment or# use some other way to pass secrets to your codeproject.set_property("docker_registry_auth",{"username":os.getenv("DOCKER_HUB_USERNAME"),"password":os.getenv("DOCKER_HUB_PASSWORD")})
Package: pybuilder-docstr-coverage
Uses docstr-coverage to check documentation coverage of your project.You can configure the docstr-coverage package using the following properties:docstr_coverage_fail_under: The minimum coverage percentage that must be achieved.
If the coverage is below this value, the build will fail. This will take
precedence over the value set in the configuration file.docstr_coverage_config: The path to the configuration file for docstr-coverage.
Default: .docstr.yaml
Package: pybuilder-git-version
PyBuilder Git Version PluginSummaryThis project is a plugin forPyBuilderthat sets the
project version based on git tags.UsageTo use the plugin put the following in the plugins section ofbuild.py:use_plugin('pybuilder_git_version')The possible properties for use are:PropertyValueDefaultUsageuse_git_versionTrue / FalseTrueTurns off pybuilder_git_versiongit_version_commit_distance_as_build_numberTrue / FalseTrueUses commit count from tag as build numberExamplesThe following table has examples of repo state and corresponding version
number produced.TagBranchClean / DirtyNumber of commits since tagVersion0.0.1masterclean00.0.10.0.1masterdirty00.0.2+build.00.2.2developclean50.2.3+develop.51.2.3developdirty31.2.4+develop.31.0.0-rc.1feature/TICKET-100clean51.0.0-rc.1+ticket100.50.0.1hotfix/BUG-20clean00.0.2+bug20.0
Package: pybuilder-pip-tools
PyBuilder Pip Tools is a PyBuilder plugin which generates*requirements*.txtfiles from your project (build) dependencies and keeps
your virtual env in sync with them. This is achieved withpip-compileandpip-syncfrompip-tools.LinksDocumentationPyPIGitHubInterface stabilityWhile all features are documented (docstrings only) and tested, the API is
changed frequently.  When doing so, themajor versionis bumped
and a changelog is kept to help upgrade. Fixes will not be backported. It is
recommended to pin the major version in your build.py, e.g. for 1.x.y:use_plugin('pypi:pybuilder_pip_tools', '==1.*')
Package: pybuilder-radon
pybuilder-radonA pybuilder plugin that checks the cyclomatic complexity of your project usingradon. For more information about radon refer to theradon pypi page.To add this plugin into your pybuilder project, add the following line near the top of your build.py:use_plugin('pypi:pybuilder_radon')NOTEif you are using Pybuilder versionv0.11.x, then specify the following version of the plugin:use_plugin('pypi:pybuilder_radon','~=0.1.2')cyclomatic complexityCyclomatic complexity is a software metric used to indicate the complexity of a program. It is a quantitative measure of the number of linearly independent paths through a program's source code. Cyclomatic complexity can be used to measure code complexity. The higher the complexity score the more complex the code, which typically translates to the code being more difficult to understand, maintain and to test. The number of the Cyclomatic complexity depends on how many different execution paths or control flow of your code can execute depending on various inputs. The metrics for Cyclomatic Complexity are:ScoreComplexityRisk Type1 to 10simplenot much risk11 to 20complexlow risk21 to 50too complexmedium risk, attentionmore than 50very complexunable to test, high riskRefer tocyclomatic complexityfor more information.Pybuilder radon propertiesThe pybuilder taskpyb radonwill use radon to to analyze your project and display the average cyclomatic complexity, verbose mode will display complexity of all classes, functions and methods analyzed. The following plugin properties are available to further configure the plugin's execution.NameTypeDefault ValueDescriptionradon_break_build_average_complexity_thresholdfloatNoneFail build if overall average complexity is greater than the specified thresholdradon_break_build_complexity_thresholdfloatNoneFail build if complexity of any class, function or method exceeds the specified thresholdThe plugin properties are set usingproject.set_property, for example setting the following properties,pyb complexitywill fail if the average overall complexity score of the project exceeds4or if the complexity score ofanyclass, method or function exceeds10:project.set_property('radon_break_build_average_complexity_threshold',4)project.set_property('radon_break_build_complexity_threshold',10)DevelopmentClone the repository and ensure the latest version of Docker is installed on your development server.Build the Docker image:dockerimagebuild\-t\pybradon:latest.Run the Docker container:dockercontainerrun\--rm\-it\-v$PWD:/code\pybradon:latest\bashExecute the build:pyb-X
Package: pybuilder-stubs-package
This plugin adds stubs_publish and stubs_upload tasks that you can use in your
build script.Using MyPy’s stubgen it creates type hinting stubs (*.pyifiles) as a separate
package. This stubs-only package is named with thestubssuffix following PEP
561. For a pybuilder project foo this would create stubs-only package foo-stubs.
Package: pybuildit
BuilditBuildit Actuator を制御する為のPython3用ライブラリInstallWindows$ pip3 install pybuilditUbuntu$ sudo apt-get -y install python3-tk
$ pip3 install pybuilditUsagepybuildit libraryライブラリについてのドキュメントhttps://www.smartrobotics.jp/products/buildit/latest/pybuildit.pdf初期化※ 以下のデバイスファイル名やCOMポート番号は環境に合わせて変更する必要があります>>> from pybuildit import *
>>> buildit = Buildit(port="/dev/ttyXXXX") #for Linux (例: /dev/ttyUSB0)
>>> buildit = Buildit(port="COMX") #for Win (例：COM8)
>>> deviceId = 1現在の位置や速度といった情報の取得>>> qss = buildit.query_servo_status(deviceId)
>>> print("position[deg]: ", qss.position(unit="deg"))
>>> print("velocity[rpm]: ", qss.velocity(unit="rpm"))
>>> print("temperature[℃]: ", qss.temperature())
>>> print("state: ", buildit.last_mcp_status().str_state())速度制御と位置制御の方法>>> buildit.force_ready(deviceId)
>>> buildit.set_ref_velocity(deviceId, 40, unit="rpm")
>>> buildit.set_ref_position(deviceId, 180, unit="deg")builditctlbuilditctl は Buildit の各メソッドをコマンドラインから呼び出す為のツールです。
アクチュエーターの状態を確認する場合は以下のように実行します。$ builditctl query-servo-status -d 1 -p /dev/ttyXXXX
state: STATE_HOLD
pos: -51636
vel: 0
cur: 0
ref: 0
temp: 26
faults: NO_FAULTS速度制御を行う場合は以下のように実行します。$ builditctl ready -d 1 -p /dev/ttyXXXX

$ builditctl set-ref-velocity 2500 -d 1 -p /dev/ttyXXXX # 指定速度の単位は [rpm/100]
0位置制御を行う場合は以下のように実行します。$ builditctl stop -d 1 -p /dev/ttyXXXX

$ builditctl set-ref-position 2500 -d 1 -p /dev/ttyXXXX # 指定位置の単位は [360/65536 度]
-39775builditct-guibuilditctl は Buildit の各メソッドをコマンドラインから呼び出す為のツールです。$ builditctl-guiポートを選択し、Connectボタンを押した後、各種ボタンを使ってデバイスを操作することが出来ます。
Package: pybuildit2
BuilditBuildit Actuator を制御する為のPython3用ライブラリInstallWindows$ pip3 install pybuildit2Ubuntu$ sudo apt-get -y install python3-tk
$ pip3 install pybuildit2Usagepybuildit2 libraryライブラリについてのドキュメントhttps://www.smartrobotics.jp/-/media/Smartrobotics/document/pybuildit2.pdf初期化※ 以下のデバイスファイル名やCOMポート番号は環境に合わせて変更する必要があります>>> from pybuildit2 import *
>>> buildit = Buildit(port="/dev/ttyXXXX") #for Linux (例: /dev/ttyUSB0)
>>> buildit = Buildit(port="COMX") #for Win (例：COM8)
>>> deviceId = 1現在の位置や速度といった情報の取得>>> qss = buildit.query_servo_status(deviceId)
>>> print("position[deg]: ", qss.position(unit="deg"))
>>> print("velocity[rpm]: ", qss.velocity(unit="rpm"))
>>> print("temperature[℃]: ", qss.temperature())
>>> print("state: ", buildit.last_mcp_status().str_state())速度制御と位置制御の方法>>> buildit.force_ready(deviceId)
>>> buildit.set_ref_velocity(deviceId, 40, unit="rpm")
>>> buildit.set_ref_position(deviceId, 180, unit="deg")builditctlbuilditctl は Buildit の各メソッドをコマンドラインから呼び出す為のツールです。
アクチュエーターの状態を確認する場合は以下のように実行します。$ builditctl query-servo-status -d 1 -p /dev/ttyXXXX
state: STATE_HOLD
pos: -51636
vel: 0
cur: 0
ref: 0
temp: 26
faults: NO_FAULTS速度制御を行う場合は以下のように実行します。$ builditctl ready -d 1 -p /dev/ttyXXXX

$ builditctl set-ref-velocity 2500 -d 1 -p /dev/ttyXXXX # 指定速度の単位は [rpm/100]
0位置制御を行う場合は以下のように実行します。$ builditctl stop -d 1 -p /dev/ttyXXXX

$ builditctl set-ref-position 2500 -d 1 -p /dev/ttyXXXX # 指定位置の単位は [360/65536 度]
-39775builditct-guibuilditctl は Buildit の各メソッドをコマンドラインから呼び出す為のツールです。$ builditctl-guiポートを選択し、Connectボタンを押した後、各種ボタンを使ってデバイスを操作することが出来ます。
Package: pybuildkite
PyBuildkiteAPythonlibrary and client for theBuildkite API.UsageTo get the package, execute:pip install pybuildkiteThen set up an instance of the Buildkite object, set you access token, and make any available requests.frompybuildkite.buildkiteimportBuildkite,BuildStatebuildkite=Buildkite()buildkite.set_access_token('YOUR_API_ACCESS_TOKEN_HERE')# Get all info about particular orgorg=buildkite.organizations().get_org('my-org')# Get all running and scheduled builds for a particular pipelinebuilds=buildkite.builds().list_all_for_pipeline('my-org','my-pipeline',states=[BuildState.RUNNING,BuildState.SCHEDULED])# Create a buildbuildkite.builds().create_build('my-org','my-pipeline','COMMITSHA','master',clean_checkout=True,message="My First Build!")PaginationBuildkite offers pagination for endpoints that return a lot of data. By default this wrapper return100objects. However, any request that may contain more than that offers a pagination option.Whenwith_pagination=True, we return a response object with properties that may havenext_page,last_page,previous_page, orfirst_pagedepending on what page you're on.builds_response=buildkite.builds().list_all(page=1,with_pagination=True)# Keep looping until next_page is not populatedwhilebuilds_response.next_page:builds_response=buildkite.builds().list_all(page=builds_response.next_page,with_pagination=True)ArtifactsArtifacts can be downloaded as binary data. The following example loads the artifact into memory asPython bytesand then writes them to disc:artifacts=buildkite.artifacts()artifact=artifacts.download_artifact("org_slug","pipe_slug","build_no",123,"artifact")withopen('artifact.bin','b')asf:f.write(artifact)Large artifacts should be streamed as chunks of bytes to limit the memory consumption:stream=artifacts.download_artifact("org_slug","pipe_slug","build_no",123,"artifact",as_stream=True)withopen('artifact.bin','b')asf:forchunkinstream:f.write(chunk)A unicode text artifact can be turned into a string easily:text=str(artifact)LicenseThis library is distributed under the BSD-style license found in the LICENSE file.
Package: pybuildme
PyBuildDeveloped by Kyle DarlingPurposePyBuild was developed to aid in quick, robust, procedurally generated build environments where the user can develop scripts quick in setting up their Python environment to their needs. The difference between PyBuild and other build frameworks available in Python is that PyBuild focuses on outside packages that may not be available to pip install or build itself into an executable.PyBuild relies heavily on theEnvironmentclass where initially it uses the Python interpreter used to run a PyBuild script as it's main environment, later this can change with the use ofVirtualEnvwhere a virtual environment can be used instead, effectively swapping the environment to the virtual environment.Basic UsagePyBuild supports quick and easy installations of packages.from pybuild import pip
from pybuild.environment import Environment

environment = Environment('pybuild_demo')
pip.install(environment, 'matplotlib>=1.0.0', 'numpy', 'virtualenv==16.6.0')pybuild_demowould become the name of the virtual environment.Developers may also use thewithcontext in Python to use an environment.from pybuild import pip
from pybuild.environment import environment
from pybuild.virtualenv import VirtualEnv

with Environment('pybuild_demo') as environment:
    Virtualenv(environment)
    pip.install(environment, 'matplotlib')Virtual environments are deleted after completion.The pip package inside PyBuild acts as a wrapper like most things do in PyBuild around the Python interpreter, accessing scripts as needed. This means that PyBuild supports additional arguments for installations and uninstallations.from pybuild import pip
from pybuild.environment import Environment

with Environment('pybuild_demo') as environment:
    pip.install(environment, 'matplotlib', no_cache_dir=True)no_cache_dir will be parsed and used as an argument to pip install.DemonstrationNow that you understand how PyBuild works by using theEnvironmentclass and the general functionality of PyBuild has been demonstrated, how about a more advanced setup?To DoPyBuild is rather new project that always has module integration in mind when developing and with that there exists additional modules that should be added.Common modules class for any class objects created to help guide users.Registering external modules to PyBuild, dynamic module loading would be required.Add more modules! The suite right now has been trimmed down to personal usage of the modules but other virtual environments, documentation, etc are always welcomed.Add master demo.
Package: pybuildtools
python-build-toolsA toolkit containing many powerful utilities, including:OS utilities (buildtools.os_utils)Indented logging with colorama support (buildtools.bt_logging.log)The powerful Maestro build management system (buildtools.maestro)A powerful VCS repository wrapper system (buildtools.repo)A mess of other random things.This is mostly a personal toolkit that grew out of control.os_utilsfrombuildtoolsimportos_utils# Ensure test/ existsos_utils.ensureDirExists('test')# Get copy of current environmental variables.ENV=os_utils.ENV.clone()# Add .bin/ to the beginning of PATH in our virtual environmentENV.prependTo('PATH','.bin/')# Remove any duplicate entries from PATHENV.removeDuplicatedEntries('PATH')# Find gcc in our virtual environment (checks PATHEXT on Windows, too!)# Returns the path to gcc, or None if it couldn't be found.GCC=ENV.which('gcc')# Ensure bash exists before continuing (same rules as above)ENV.assertWhich('bash')# Bring up gcc's help page. Crash if non-0 exit code, echo command to console, and output STDOUT/STDERR to console.os_utils.cmd([GCC,'--help'],critical=True,echo=True,show_output=True)Loggingfrombuildtoolsimportlogdefa():log.info('This will be indented if a() is called in a log block.')log.info('No indentation, yet.')withlog.warning('A warning. Next line will be indented.'):log.error('Error!')withlog.info('The following function\'s log output will be indented by another layer.')a()log.critical('So will%s!','this')MaestroMaestro is currently synchronous, with plans to make it async.frombuildtools.maestroimportBuildMaestrofrombuildtools.maestro.fileioimportReplaceTextTargetfrombuildtools.maestro.coffeescriptimportCoffeeBuildTargetfrombuildtools.maestro.webimportSCSSBuildTarget,SCSSConvertTargetbm=BuildMaestro()# Compile CoffeeScript to JSbm.add(CoffeeBuildTarget('htdocs/js/vgws.js',['coffee/src/vgws.coffee']))bm.add(CoffeeBuildTarget('htdocs/js/editpoll.multichoice.js',['coffee/editpoll.multichoice.coffee'],dependencies=['htdocs/js/vgws.js']))bm.add(CoffeeBuildTarget('htdocs/js/editpoll.option.js',['coffee/editpoll.editpoll.coffee'],dependencies=['htdocs/js/vgws.js']))# Convert CSS to SCSSbm.add(SCSSBuildTarget('htdocs/css/style.css',['style/style.scss'],[],import_paths=['style'],compass=True))# Compile, taking dependencies into count when ordering operations.bm.run()# Same as above, but providing command line arguments such as --clean, and --rebuild.bm.as_app()
Package: pybulk
PyBulk 🚀简体中文| EnglishPyBulk is a Python module that wraps PyMySQL to allow simple and fast bulk data insertion into databases. With PyBulk, you can insert thousands of records into a database table in just a few lines of code.PyBulk builds on top of the PyMySQL library and connection pool to efficiently reuse connections and minimize latency. It handles all the low-level details of executing multiple INSERT statements while protecting your database from overload.Some of the main features of PyBulk include:Simple API: Insert bulk data with just a few function calls. No complicated setup required.Speed: Leverages PyMySQL's connection pool to quickly insert thousands of records.Reliability: Includes error handling and recovery mechanisms to handle transient database errors. Retries failed queries automatically.Support for REPLACE INTO: Upsert support allows you to replace existing records in a table or insert new ones.Compatibility: Works with MySQL, MariaDB and AWS RDS. Compatible with Python 2 and 3.PyBulk allows you to focus on your application's logic rather than spending time building infrastructure to handle database load. It is a robust but lightweight solution ideal for batch data processing applications.💾 Installationpip install pybulk🔧 Usage:import pybulk

cfg = {
'host': 'localhost',
'port':  3306,
'user':  'root',
'password': 'root',
'db': 'info',
'charset': 'utf8',
}

db = pybulk.client(cfg)

my_data = [
{'name': 'Peter', 'age': 21,},
{'name': 'Harry', 'age': 35,},
{'name': 'Mark', 'age': 40,},
]

db.push_data('student', my_data, size=2000)

# You can also run sql in pybulk like:

data = db.excute_sql('select * from school')
Package: pybulldozer
DozerFlattens unstructured data into a relation formatInstallationpip install pybulldozerFeaturespybulldozer aims to make working with non-relation data files as easy as possibleExplore the structure of the filestatisticsstructureattributesFlatten the file to record-arraysReturns a dictionary that contains a {name: record-array} for all layers in the fileFile formatsCurrenty pybulldozer only works with xmlFuture developmentParse more data formatsSpeed optimizationCreate SQL insert statements
Package: pybullet
pybullet is an easy to use Python module for physics simulation, robotics and deep reinforcement learning based on the Bullet Physics SDK. With pybullet you can load articulated bodies from URDF, SDF and other file formats. pybullet provides forward dynamics simulation, inverse dynamics computation, forward and inverse kinematics and collision detection and ray intersection queries. Aside from physics simulation, pybullet supports to rendering, with a CPU renderer and OpenGL visualization and support for virtual reality headsets.
Package: pybulletproofs
Bulletproofs in PythonWARNING: Work-in-progress. Only meant for experimental purposes.We use pyo3 to wrap thebulletproof implementation by dalek-cryptographyin python.QuickstartInstall latest development version from PyPI.pipinstallpybulletproofsTo test the python library, run the following proof and verification.frompybulletproofsimportzkrp_prove,zkrp_verify

proof1,comm1,_=zkrp_prove(2022,32)proof2,comm2,_=zkrp_prove(2023,32)assertzkrp_verify(proof1,comm1)assert!zkrp_verify(proof2,comm1)DevelopmentDependenciesPython 3.8 and upRust 1.62.0-nightly (60e50fc1c 2022-04-04) and upBuildingWe first create a python virtual environment, activate it, and installmaturininto the virtual environment.$python-mvenv.env
$source.env/bin/activate
$pipinstallmaturinTo compile the Rust implementation into a python library, run the following code snippet.$maturininit
$maturindevelopAlternatively, use theDockerfile.
Package: pybullet-rendering
pybullet_renderingExternal rendering forPyBulletsimulator.InstallUsing pippip install pybullet_renderingFrom source codeInstall NumPypip install numpyInstall PyBullet from source codegit clone https://github.com/bulletphysics/bullet3.git
cd bullet3
python setup.py install
export BULLET_ROOT_DIR="$PWD"Install the packagecd ..
git clone https://github.com/ikalevatykh/pybullet_rendering.git
cd pybullet_rendering
python setup.py install --bullet_dir "$BULLET_ROOT_DIR"Run testspython -m unittest discover tests -vRun examplesExample of usingPanda3Dfor rendering in GUI mode:python -m pybullet_rendering.examples.panda3d_gui --multisamples 8Test performance of diferent renderers:python -m pybullet_rendering.examples.performanceRenderersThis package provide example renderers based onPanda3Dandpyrender.Example of usageimportpybulletaspbfrompybullet_renderingimportRenderingPluginfrompybullet_rendering.render.panda3dimportP3dRenderer# panda3d-based rendererfrompybullet_rendering.render.pyrenderimportPyrRenderer# pyrender-based rendererclient_id=pb.connect(pb.DIRECT)# bind your renderer to pybulletrenderer=P3dRenderer(multisamples=4)# or PyrRenderer(platform='egl', egl_device=1)plugin=RenderingPlugin(client_id,renderer)# render thru the standard pybullet APIw,h,rgba,depth,mask=pb.getCameraImage(w,h,projectionMatrix=...,viewMatrix=...)Implement your own renderer in PythonYour renderer should inherit from theBaseRendererclass and implement itsupdate_sceneandrender_framemethods. To get an idea of their parameters, see examples and tests.frompybullet_renderingimportBaseRendererclassMyRenderer(BaseRenderer):def__init__(self):"""The base class initializer have to be called first."""BaseRenderer.__init__(self)defupdate_scene(self,scene_graph,materials_only):"""Update a scene using scene_graph descriptionArguments:scene_graph {SceneGraph} -- scene descriptionmaterials_only {bool} -- update only shape materials"""foruid,pb_nodeinscene_graph.nodes.items():"update nodes of your scene"defrender_frame(self,scene_state,scene_view,frame):"""Render a scene at scene_state with a scene_view settingsArguments:scene_state {SceneState} --  scene state, e.g. transformations of all objectsscene_view {SceneView} -- view settings, e.g. camera, light, viewport parametersframe {FrameData} -- output image buffer"""w,h=scene_view.viewportifreturn_to_bullet:frame.color_img[:]=...# np.uint8, (h,w,4)frame.depth_img[:]=...# np.float32 (h,w)frame.mask_img[:]=...# np.int32 (h,w)returnTruereturnFalseCitationIf you find pybullet_rendering useful in your research, please cite the repository using the following BibTeX entry.@Misc{kalevatykh2020pybullet_rendering,
  author =       {Kalevatykh, Igor et al.},
  title =        {pybullet_rendering - External rendering for the PyBullet simulator},
  howpublished = {Github},
  year =         {2020},
  url =          {https://github.com/ikalevatykh/pybullet_rendering}
}Licensemano_pybullet is released under theGPLv3license.