Saravanan666/pypi-org huggingface dataset:
Package: bowerrecipe
ContentsIntroductionSupported optionsExample usageNotesContributorsChangelog0.20.1.10.1DownloadIntroductionThis recipe allows downloading and installing assets such as images, CSS and JavaScript using Twitter Bower.Supported optionsThe recipe supports the following options:packagesPackages that should be installed with bower. Packages specified here are
passed to bower verbatim. They can be specified in any form that is
supported by bower:packages =
    underscore
    git://github.com/components/jquery.git
    bootstrap#2.2.2base-directoryAbsolute path to the bower “project” directory.bower installis run
from this directory and the bower configuration file,.bowerrcis also
placed here.  Optional; defaults to${buildout:parts-directory}/bower.
Requires an absolute path.This directory is not removed when the Buildout part is uninstalled.executableAbsolute path to thebowerexecutable. Packages are installed using
this executable. Optional; defaults toboweronPATH.downloadsRelative path, from thebase-directory, to the directory where bower
will download packages to. This path is written to the.bowerrcfile
prior to running the executable. Optional; defaults todownloads. Thus,
the downloaded packages are placed in${base-directory}/downloadsby
default.This directoryisremoved when the Buildout part is uninstalled.Example usageA sample buildout that uses this recipe could look like:[buildout]
parts = node web

[node]
recipe = gp.recipe.node
url = http://nodejs.org/dist/v0.8.16/node-v0.8.16.tar.gz
npms = bower@0.6.8
scripts = bower

[web]
recipe = bowerrecipe
packages = jquery#1.8.3 normalize-css
executable = ${buildout:bin-directory}/bowerThis would place the downloaded packages inparts/bower/downloads.
Modifying thewebsection to be:[web]
recipe = bowerrecipe
packages = jquery#1.8.3 normalize-css
executable = ${buildout:bin-directory}/bower
base-directory = ${buildout:parts-directory}
downloads = componentswould result in bower placing the downloaded packages inparts/components.NotesBower still looks at the~/.bowerrcfile. Hence, if this file exists, it
may affect the buildout bower configurationBower still uses the cache located in the user’s home directory. For me,
this happens to be~/.bower/cache/ContributorsAnshuman Bhaduri
Sebastian WehrmannChangelog0.2Fix removal of base directory upon uninstall. (#1)Update files on every buildout run, rather loading them once.0.1.1Fixed documentation so it displays correctly on PyPI
[Anshuman Bhaduri]0.1Created initial recipe
[Anshuman Bhaduri]Download
Package: bowl
bowl
===
[![Build Status](https://travis-ci.org/cglewis/bowl.png?branch=master)](https://travis-ci.org/cglewis/bowl)
[![Coverage Status](https://coveralls.io/repos/cglewis/bowl/badge.png?branch=master)](https://coveralls.io/r/cglewis/bowl?branch=master)
[![Docs version](https://readthedocs.org/projects/bowl/badge/?version=latest)](http://bowl.readthedocs.org/en/latest/)
[![PyPI version](https://badge.fury.io/py/bowl.svg)](http://badge.fury.io/py/bowl)
[![downloads](https://pypip.in/d/bowl/badge.png)](https://pypi.python.org/pypi/bowl)Tool for easily building and configuring virtual environments on top of Docker.Main features:Works with multiple Docker hosts.easily add new derives through a simple metadata JSON object and standard Dockerfile.Snapshotting containers.Spin up the same container on multiple Docker hosts in one go.Configure containers at runtime, either in bulk or individually.Provides a way to run multiple services on the same container without having to have a Dockerfile for the combined services i.e. Redis Server and SSH.Provides a friendly end-user interface for running containers, as well as a straightforward way for operators to manage images, hosts, and available services.Services can be easily changed based on environments by changing the path to the metadata for the services.More information coming soon, including getting started, known issues, roadmap, and more.
Package: bowler
Safe code refactoring for modern Python projects.OverviewBowler is a refactoring tool for manipulating Python at the syntax tree level. It enables
safe, large scale code modifications while guaranteeing that the resulting code compiles
and runs. It provides both a simple command line interface and a fluent API in Python for
generating complex code modifications in code.Bowler uses a "fluent"QueryAPI to build refactoring scripts through a series
of selectors, filters, and modifiers.  Many simple modifications are already possible
using the existing API, but you can also provide custom selectors, filters, and
modifiers as needed to build more complex or custom refactorings.  See theQuery Referencefor more details.Using the query API to rename a single function, and generate an interactive diff from
the results, would look something like this:query=(Query(<pathstomodify>).select_function("old_name").rename("new_name").diff(interactive=True))For more details or documentation, check outhttps://pybowler.ioInstalling BowlerBowler supports modifications to code from any version of Python 2 or 3, but it
requires Python 3.6 or higher to run. Bowler can be easily installed using most common
Python packaging tools. We recommend installing the latest stable release fromPyPIwithpip:pipinstallbowlerYou can also install a development version from source by checking out the Git repo:gitclonehttps://github.com/facebookincubator/bowlercdbowler
pythonsetup.pyinstallLicenseBowler is MIT licensed, as found in theLICENSEfile.
Package: bowler-py35
Safe code refactoring for modern Python projects.OverviewBowler is a refactoring tool for manipulating Python at the syntax tree level. It enables
safe, large scale code modifications while guaranteeing that the resulting code compiles
and runs. It provides both a simple command line interface and a fluent API in Python for
generating complex code modifications in code.Bowler uses a “fluent”QueryAPI to build refactoring scripts through a series
of selectors, filters, and modifiers.  Many simple modifications are already possible
using the existing API, but you can also provide custom selectors, filters, and
modifiers as needed to build more complex or custom refactorings.  See theQuery Referencefor more details.Using the query API to rename a single function, and generate an interactive diff from
the results, would look something like this:query=(Query(<pathstomodify>).select_function("old_name").rename("new_name").diff(interactive=True))For more details or documentation, check outhttps://pybowler.ioInstalling BowlerBowler supports modifications to code from any version of Python 2 or 3, but it
requires Python 3.6 or higher to run. Bowler can be easily installed using most common
Python packaging tools. We recommend installing the latest stable release fromPyPIwithpip:pipinstallbowlerYou can also install a development version from source by checking out the Git repo:gitclonehttps://github.com/facebookincubator/bowlercdbowlerpythonsetup.pyinstallLicenseBowler is MIT licensed, as found in theLICENSEfile.
Package: bowline
BowlineConfigurable tools to easily pre and post process your data for data-science and machine learning.QuickstartThis will show you how to install and create a minimal implementation ofBowline. For more in-depth examples visit theOfficial Docs.Installation$ pip install bowlineMinimal implementationfrombowlineimportStandardPreprocessorimportpandasaspdraw_data=pd.read_csv('path/to/your/file')preprocessor=StandardPrepreocessor(data=data,numerical_features=["age","capital-gain"],binary_features=["sex"],categoric_features=["occupation","education"])processed_data=preprocessor.process(target="sex")
Package: bowtie
Installation|Documentation|Gitter Chat|Google GroupBowtieIntroductionBowtie is a library for writing dashboards in Python. No need to know
web frameworks or JavaScript, focus on building functionality in Python.
Interactively explore your data in new ways! Deploy and share with
others!DemoSee a liveexamplegenerated
from thiscode!GalleryFor more examples, check out thegalleryandrepos.
Feel free to add your own creations!InstallationIf you useconda, you can install with:conda install -c conda-forge bowtie-pyIf you usepip, you can install with:pip install bowtieRequirementsBowtie usesYarnto manage node packages.
If you installed Bowtie throughconda, Yarn was also installed as a dependency.
Yarn can be installed through conda:conda install -c conda-forge yarnOtherwise followinstall
instructionsfor Yarn for your
OS.DocumentationAvailablehere.Jupyter IntegrationAn early integration with Jupyter has been prototyped.
I encourage you to try it out and share feedback.
I hope this will make it easier to make Bowtie apps.Read thedocumentationfor more details.DockerDocker images are provided as an alternative way to use Bowtie. They are
available onDocker Hub:docker pull jwkvam/bowtieRead thedocumentationfor more details.The GoalContributingYou can help Bowtie in many ways including:Try itoutand report bugs or what was difficult.Help improve thedocumentation.Write newwidgets.Provide hosting for apps in the gallery.Saythanks!
Package: bowtie-json-schema
Bowtie is ameta-validator of theJSON Schema specification, by which we mean it coordinates executingothervalidator implementations, collecting and reporting on their results.It’s called Bowtie because it fans in lots of JSON then fans out lots of results:>·<.
Looks like a bowtie, no?
Also because it’s elegant – we hope.For more information, seeBowtie’s documentation.
Package: box0
pyBox0Python binding for libbox0DependenciescffinumpyIn C:libbox0Installation$ python setup.py build
$ python setup.py installConfigurationin local.properties
_binding.py, build_path variable to tell where to look for header and libraryUsagelots of demo code in test/ and example/
a generic approch to opening device and module and do something with themimport box0

# open any supported usb device
dev = box0.usb.open_supported()

# open the dio0 module (assuming the device support it)
# if you need to iterate over the supported modules using dev
dio0 = dev.dio(0)

# Prepare for basic mode (basic functionality)
dio0.basic_prepare()

# set to output mode
dio0.dir(0, dio0.OUTPUT)

# set value of pin 0
dio0.value(0, dio0.LOW)

#disable hiz mode of pin 0,
# note: all pins are in hiz mode right after opening (for protection)
dio0.hiz(0, dio0.DISABLE)

# start the basic mode
dio0.basic_start()

# wait
try:
	while True:
		time.sleep(.5)
except:
	pass

# Stop basic mode
dio0.basic_stop()

# close resources
dio0.close()
dev.close()NotepyBox0 uses same style as libbox0 and
much of the documentation of libbox0 is applicable to pyBox0int b0_<section>_<func>(<section-object>, params....)in pyBox0:
instead of int, an exception (ResultException is raised) when int-val < 0
so, now the return value is used for other tasks"b0" tag is now replace with "box0." as python have concept of modules

<section> is replace with files.
	for example: <section> = "device" , theirs device.py
		and it contain Device.py


<func> these are under-scored style name in libbox0
	in pyBox0, camelcasing is used
	for example b0_usb_open_supported() is box0.usb.open_supported()

most of the library assumes numpy array.
	numpy is good and you should always use numpy with pyBox0 as
	it much better in long runGetting helpget on to #box0 on IRC freenode
and report bug onhttps://gitlab.com/madresistor/pyBox0Getting involvedget on to #box0 on IRC freenode
and report bug onhttps://gitlab.com/madresistor/pyBox0LicenceGNU/GPLv3 or later (see COPYING)Credits and referenceshttps://www.madresistor.com/MaintainerKuldeep Singh Dhakakuldeep@madresistor.com
Package: box21-api
box21_apiA python package for interacting with your Box21 via the apiInstallpipinstallbox21_apiHow to usefrombox21_api.box21_apiimportBox21Apibox21_api=Box21Api(API_USERNAME,API_PASSWORD,'https://box21.ai',443,API_PROJECT_ID)labels=box21_api.get_labels()print('Number of labels retrieved',len(labels))print('First label',labels[0])Number of labels retrieved 2
First label Label(('Bounding box', 'Chital', 1))annotations=box21_api.get_label_annotations(labels[0])print('Number of annotations retrieved',len(annotations))print('First annotation',annotations[0])Number of annotations retrieved 2
First annotation BoundingBox(Chital, (0.1641, 0.5291, 0.2766, 0.3381))first_annotation=annotations[0]pil_image=box21_api.download_asset(first_annotation.asset_id)pil_imageSee more examples on:https://ramonhollands.github.io/box21_api/
Package: box2csv
box2csvExtract data from shoebox and toolbox projects to CSV files.Installationpip install box2csvUsageAt the moment, there is only one command:box2csv corpus, for collections of glossed texts.
To create a filemytextdatabase.csvfrom a toolbox filemytextdatabase.txt:box2csvcorpusmytoolbox/mytextdatabase.txtProject-specific configuration can be passed via--conf your/config.yaml; to see what options are available, checkthe default configuration fileas well as the default configuration files fortoolboxandshoebox.To create aCLDFversion of the corpus, add the option--cldf.
For more help on how to run the command, usebox2csv corpus --help.Problemsif runningbox2csvproduces warnings, check your database for possible inconsistenciesif that did not solve your problem,open an issue
Package: box51
Box51An image processing library created for manhattan to allow local file storage
without running an instance of hangar51.Installationpip install box51Manhattan setupModify you application config as follows:from manhattan.assets.backends import box51
from werkzeug.contrib.cache import SimpleCache

class Config:

    # Assets
    ASSET_BACKEND = box51
    ASSET_BACKEND_SETTINGS = {
        'asset_root': '/path/to/assets',
        'cache': SimpleCache()
    }
    ASSET_BACKEND_ROOT = 'http://mysite.com/assets'LimitationsBox51 does not support the facial recognition feature provided by Hangar51.
Package: boxberry
# Boxberry API клиентКлиент для работы с API Boxberry### Установкаpip install boxberryили из исходников:pip install git+https://github.com/AlekseevAV/boxberry### Использованиеfrom boxberry.client import BoxberryAPIboxberry_api = BoxberryAPI(token=’test_token’, endpoint=’https://test.boxberry.de/json.php’)
boxberry_api.points_for_parcels()
Package: box-cmd
BOXBox is a command line tool that enables the easy creation of rolling backups using user-defined presets.InstallationPre-InstallationEnsure you have the following tools configured and working on your machine.Python (3.7 or greater)GitFollow these steps to install this utility.Clone the repository using git:git clone https://github.com/InValidFire/backup_cmd.git(https)git clone git@github.com:InValidFire/backup_cmd.git(ssh)Navigate into the root of the repository.Use pip to install the package locally.python -m pip install .Note: Depending on your system's configuration, the exact commands to run may vary.Post-Installation and ConfigurationBOX loads a file in your HOME directory called.box_config.json, it should have the following structure:{"format":1,"presets":{"<preset_name>":{"targets":["C:\\Target\\Path\\One","C:\\Target\\Path\\Two"],"destinations":[{"path":"E:\\Destination\\Path","file_format":"zip","name_separator":"-","date_format":"%d_%m_%y__%H%M%S","max_backup_count":10}]}}}If you'd like to see the JSON Schema used to validate this file, see here:presets.json JSON SchemaUsagebox list- list all presets found in the config file.box pack [--force] [--keep] <preset>- create a backup using thepreset. if theforceflag is set, force the backup creation even if it was already saved. if thekeepflag is set, keep backups beyond the max_backup_count.box unpack --source=<preset|backups_folder> [--destination <destination_path>]- select a backup to restore from thepresetorbackups_folderpath. Thebackups_folderpath should contain completed backups from the utility. If thedestinationis given, the original backup's target will not be used and the backup will instead be restored to the custom destination.Development and ContributionTo run the program in a development environment, first install the program using pip.pip install -e <repo-directory>Then you can run the command under theboxcommand name. :)This program utilizespytestfor testing, withpytest-cov, ensure you have them both installed:pip install pytest pytest-covTo run all tests in the tests directory, run the following command in the repo root directory.pytest --cov=box_cmd ./testsIf you'd like the report to be generated into an HTML document (for detailed information), run this command instead:pytest --cov=box_cmd ./tests --cov-report=html
Package: boxcraft
BoxCraftEste es un proyecto que implementa el moduloBoxCraftpara disponer de un sistema para el procesamiento distribuido, basado en la administración de nodos y tareas que aprovecha la flexibilidad de Python y la velocidad de Redis.CaracterísticasSistema de nodos que permite roles de líder y lector para una gestión eficiente.Gestiona y supervisa tareas a través de un sistema dinámico basado en Redis.Sistema para administrar tareas y su estado.RequisitosPython 3.xRedisinstalado y configuradoInstalaciónClona el repositorio:user@node:gitclonehttps://github.com/Lucho00Cuba/boxcraft.git
user@node:cdboxcraftUsofromboxcraft.controllerimportBoxfromtimeimportsleepastime_sleepfromosimportenvirondefhello(instance=None,action=None):print(f"Action:{action}Instance:{instance}")if__name__=="__main__":try:tasks={'action':'delete','name':'poc-*','instances':str(["node-01","node-02","node-03","node-04","node-05"])}ctx=Box()print(f"Node:{ctx._node_name}- Role:{ctx._role}- ID:{ctx._id}")# publish datactx.publish(tasks)# runnerwhileTrue:# getting datatask=ctx.getting()iftask==None:breakelse:print(f"Task:{task}")# logic to execute the task...ctx.runner(target=hello,kwargs={"instance":task['instances'],"action":task['action']})time_sleep(2)exceptExceptionaserr:print(err)
Package: boxdist
boxdistCythonized geodetic and planar distance functions for R-Trees. The implementation is adapted fromTile38, which is based on the paperGeodetic Distance Queries on R-Trees for Indexing Geographic Data.Geodeticfromboxdistimportgeodetic_box_disttargetlon=-72.946472targetlat=45.154927minlon=-74.19342minlat=45.265222maxlon=-73.157959maxlat=45.704261meters=geodetic_box_dist(targetlon,targetlat,minlon,minlat,maxlon,maxlat,)meters#=> 20612.892322138163Planarfromboxdistimportplanar_box_disttargetx=0targety=0minx=1miny=1maxx=2maxy=2squared_dist=planar_box_dist(targetx,targety,minx,miny,maxx,maxy,)squared_dist#=> 2
Package: box-embeddings
Open-source library for Box Embeddings and Box Representations, built on PyTorch & TensorFlow.StatusInstallationInstalling via pipThe preferred way to install Box Embeddings is viapip. Just runpip install box-embeddingsInstalling from sourceYou can also install Box Embeddings by cloning our git repositorygit clone https://github.com/iesl/box-embeddingsCreate a Python 3.7 or 3.8 virtual environment, and install Box Embeddings in editable mode by running:pip install --editable . --user
pip install -r core_requirements.txtPackage OverviewCommandDescriptionbox_embeddingsAn open-source library for NLP or graph learningbox_embeddings.commonUtility modules that are used across the librarybox_embeddings.initializationsInitialization modulesbox_embeddings.modulesA collection of modules to operate on boxesbox_embeddings.parameterizationsA collection of modules to parameterize boxesCitingIf you use simple hard boxes with surrogate loss then cite the following paper:@inproceedings{vilnis2018probabilistic,
  title={Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures},
  author={Vilnis, Luke and Li, Xiang and Murty, Shikhar and McCallum, Andrew},
  booktitle={Proceedings of the 56th Annual Meeting of the Association for
  Computational Linguistics (Volume 1: Long Papers)},
  pages={263--272},
  year={2018}
}If you use softboxes without any regularizaton the cite the following paper:@inproceedings{
li2018smoothing,
title={Smoothing the Geometry of Probabilistic Box Embeddings},
author={Xiang Li and Luke Vilnis and Dongxu Zhang and Michael Boratko and Andrew McCallum},
booktitle={International Conference on Learning Representations},
year={2019},
url={https://openreview.net/forum?id=H1xSNiRcF7},
}If you use softboxes with regularizations defined in theRegularizationsmodule then cite the following paper:@inproceedings{
patel2020representing,
title={Representing Joint Hierarchies with Box Embeddings},
author={Dhruvesh Patel and Shib Sankar Dasgupta and Michael Boratko and Xiang Li and Luke Vilnis
and Andrew McCallum},
booktitle={Automated Knowledge Base Construction},
year={2020},
url={https://openreview.net/forum?id=J246NSqR_l}
}If you use Gumbel box then cite the following paper:@article{dasgupta2020improving,
  title={Improving Local Identifiability in Probabilistic Box Embeddings},
  author={Dasgupta, Shib Sankar and Boratko, Michael and Zhang, Dongxu and Vilnis, Luke
  and Li, Xiang Lorraine and McCallum, Andrew},
  journal={arXiv preprint arXiv:2010.04831},
  year={2020}
}The code for this library can be foundhere.ContributorsDhruvesh Patel@dhruvdcoderShib Sankar Dasgupta@ssdasguptaMichael Boratko@mboratkoXiang (Lorraine) Li@Lorraine333Trang Tran@trangtran72Purujit Goyal@purujitgoyalTejas Chheda@tejas4888ContributionsWe welcome all contributions from the community to make Box Embeddings a better package.
If you're a first time contributor, we recommend you start by reading ourCONTRIBUTING.mdguide.TeamBox Embeddings is an open-source project developed by the research team from theInformation Extraction and Synthesis Laboratoryat theCollege of Information and Computer Sciences (UMass Amherst).
Package: boxfish
boxfish: lightweight table extraction from HTMLWhat is it?Boxfish is a lightweight tool for table extraction from HTML pages.Main featuresEasy configuration. No knowledge of CSS or Xpaths required.Fast table extraction to CSV files.Integration ofrequestsandselenium.Quick startimportboxfishasbfimportpandasaspd# Define table layout of an url with strings from two rows.aurl=""row1=""row2=""# Build a configurationaconfig=bf.build(url=aurl,rows=[row1,row2])# Extract a tabledata=bf.extract(aconfig,url=aurl)# View resultsdf=pd.DataFrame(data)df.head()Where to get it?Boxfish is available onPypiandGithub.pip install boxfishDependenciesThe main dependencies are:BeautifulSoup4, a Python library for pulling data out of HTML and XML files.lxml, a powerful and Pythonic XML processing library.Requests, a simple, yet elegant, HTTP library.Selenium, automated web browser interaction from Python.LicenseBoxfish is available with anMIT license.LimitationsBoxfish extracts text from HTML. To see if the HTML file contains the
text of interest, open the page in a browser, then access the HTML in the developer tools viaCntrl+Shift+I.DocumentationFull documentation is availablehere.