Saravanan666/pypi-org huggingface dataset:
Package: wp-tinymath
tiny_mathA basic math library for vectors and matrices (just for 2,3, and 4 dimensions)Yet another math libraryThis library is intended mainly for test purposes (integration with PyPi, ReadTheDocs, CI, python-bindings, etc.).
However, we currently use it as a replacement to other more complete libraries likeglmandEigenin some projects that make heavy use of C/C++  and
also require Python support through bindings.SetupC++Clone this package into yourthird_partydependencies:# Replace "third_party" with your own dependencies-folder namegitclonehttps://github.com/wpumacay/tiny_math.gitthird_party/tiny_mathThe library is a template-based header-only library, so just include the headers in theincludefolder, e.g. in your ownCMakeLists.txt:include_directories( third_party/tiny_math/include )Alternatively, you can use the CMake targettinymath_cpp_libas a dependency in your own target:add_library( my_own_awesome_library tinymath_cpp_lib )PythonUse the providedsetup.pyfile:pythonsetup.pyinstallOr via PyPi:pipinstallwp-tinymathAnd import thetinymathpackage in your python files:importtinymathastmUsageC++#include<vector_t.h>#include<matrix_t.h>intmain(){// Create a vec3-float32 and show it on the consoletinymath::Vector3f_vec={1.0f,2.0f,3.0f};std::cout<<"vec: "<<tinymath::toString(vec)<<std::endl;// Create a mat3 float32, show its entries and its inverseautomat=tinymath::Matrix3f({3.0f,9.0f,3.0f,9.0f,0.0f,3.0f,2.0f,3.0f,8.0f});std::cout<<"mat:"<<std::endl;std::cout<<tinymath::toString(mat)<<std::endl;std::cout<<"mat.inverse():"<<std::endl;std::cout<<tinymath::toString(mat.inverse())<<std::endl;return0;}Pythonimporttinymathastm# Create a vec3-float32 and show it on the consolevec=tm.Vector3f([1.0,2.0,3.0])print('vec:{}'.format(vec))# Create a mat3 float32, show its entries and its inversemat=tm.Matrix3f([[3.0,9.0,3.0],[9.0,0.0,3.0],[2.0,3.0,8.0]]);print("mat:")print(mat)print("mat.inverse():")print(mat.inverse())
Package: wptranslate
wptranslateis a command-line translator tool based on Wikipedia.It should be used for concepts and vague topics where a typical translator tool
wouldn’t give an accurate translation, but not for other things. For example,
you won’t be able to translate a whole sentence with it.Installpip install wptranslateUsagewptranslate <source language>:<target language> <word>Example$ wptranslate fr:en jambon
Ham
Package: wpull
Wpull is a Wget-compatible (or remake/clone/replacement/alternative) web
downloader and crawler.Notable Features:Written in Python: lightweight, modifiable, robust, & scriptableGraceful stopping; on-disk database resumePhantomJS & youtube-dl integration (experimental)InstallWpull usesPython 3.Once Python is installed, download Wpull from PyPI using pip:pip3 install wpullFor detailed installation instructions and potential caveats, please seehttps://wpull.readthedocs.io/en/master/install.html.Example CommandsTo download the About page of Google.com:wpull google.com/aboutTo archive a website:wpull billy.blogsite.example \
    --warc-file blogsite-billy \
    --no-check-certificate \
    --no-robots --user-agent "InconspiuousWebBrowser/1.0" \
    --wait 0.5 --random-wait --waitretry 600 \
    --page-requisites --recursive --level inf \
    --span-hosts-allow linked-pages,page-requisites \
    --escaped-fragment --strip-session-id \
    --sitemaps \
    --reject-regex "/login\.php" \
    --tries 3 --retry-connrefused --retry-dns-error \
    --timeout 60 --session-timeout 21600 \
    --delete-after --database blogsite-billy.db \
    --quiet --output-file blogsite-billy.logTo see all options:wpull --helpDocumentationDocumentation is located athttps://wpull.readthedocs.io/. Please have
a look at it before using Wpull’s advanced features.HelpNeed help? Please see ourHelppage which contains
frequently asked questions and support information.The issue tracker is located athttps://github.com/chfoo/wpull/issues.DevContributions and feedback are greatly appreciated.CreditsCopyright 2013-2016 by Christopher Foo and others. License GPL v3.This project contains third-party source code licensed under different terms:wpull.backport.loggingwpull.thirdparty.robotexclusionrulesparserwpull.thirdparty.dammitWe would like to acknowledge the authors of GNU Wget as Wpull uses algorithms
from Wget.
Package: wp-utils
Loco-UtilsA small set of C/C++ helper functions and macros that I used alongside various
projects related to theLocoframework I'm currently developing.Build StatusBuildStatusUbuntuWindowsMacOSHow to UseThis is aCMakebased project, and all dependencies are managed by this tool
itself (i.e., we make use ofFetchContent), so no additional dependencies have
to be installed. So, there are two ways you can use this project alongside yours:Include viaadd_subdirectory: This is the quickest way to integrate the
project alongside yours. You'll have to download the source code to some folder
either by cloning the repo, or by adding it as agit-submodule. Either way,
let's say you placed the source intoSOME_FOLDER/loco_utils. Then you'll just
have to do the following in some part of your CMake setup:# On some part of your CMake configuration rulesadd_subdirectory(SOME_FOLDER/loco_utils)Get it viaFetchContent: This is an option that doesn't require for you to
directly clone or link the repo. You can useFetchContentandFetchContent_MakeAvailableto add this project directly into your CMake build workflow, as shown below:# Set where to place source-code and where to place binaries/logsset(SOME_SRC_PATH"Some-source-path-here")set(SOME_BUILD_PATH"Some-build-path-here")# Define some extra cmake-args to pass to this project (loco_utils)set(SOME_CMAKE_ARGS"-DLOCOUTILS_BUILD_EXAMPLES=OFF -DLOCOUTILS_BUILD_DOCS=OFF")# On some part where you setup third-party dependenciesFetchContent(loco_utilsGIT_REPOSITORY"https://github.com/wpumacay/loco_utils.git"GIT_PROGRESSTRUEUSES_TERMINAL_DOWNLOADTRUEPREFIX"${SOME_SRC_PATH}/loco_utils"DOWNLOAD_DIR"${SOME_SRC_PATH}/loco_utils"SOURCE_DIR"${SOME_SRC_PATH}/loco_utils/source"BINARY_DIR"${SOME_BUILD_PATH}/loco_utils/build"STAMP_DIR"${SOME_BUILD_PATH}/loco_utils/stamp"TMP_DIR"${SOME_BUILD_PATH}/loco_utils/tmp"CMAKE_ARGS-DCMAKE_BUILD_TYPE=Release-DCMAKE_GENERATOR=${CMAKE_GENERATOR}-DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}-DCMAKE_INSTALL_PREFIX=${CMAKE_INSTALL_PREFIX}-DCMAKE_INSTALL_INCLUDEDIR=${CMAKE_INSTALL_INCLUDEDIR}-DCMAKE_INSTALL_LIBDIR=${CMAKE_INSTALL_LIBDIR}-DCMAKE_INSTALL_DOCDIR=${CMAKE_INSTALL_DOCDIR}-DCMAKE_INSTALL_BINDIR=${CMAKE_INSTALL_BINDIR}-DCMAKE_PREFIX_PATH=${CMAKE_PREFIX_PATH}${SOME_CMAKE_ARGS}BUILD_ALWAYSOFF)Install and usefind_package: This last option is not available yet, but once
we add the install rules for the CMake project, you'll be able to justinstallthe library into your system, import it usingfind_package, andlinkingusing the exposedLocoUtilsCpptarget, as shown below:Installing the projectmkdirbuildcmake-S.-Bbuildcmake--buildbuildcmake--installbuildIncluding usingfind_package# Locate the installed project using find_package()find_package(LocoUtilsREQUIRED)Install the Python bindingsThere are some Python bindings (generated using Pybind11), which you can install
using the providedsetup.pyscript. Just run eitherpython setup.py install,
orpip install --verbose .(add verbose just to check if everything went well)# Install python bindings# Option-1pythonsetup.pyinstall# Option-2pipinstall--verbose.
Package: wpwatcher
WPWatcher - AutomatingWPScanto scan and report vulnerable Wordpress sitesWordpress Watcher is a wrapper for WPScan that manages scans on multiple sites and reports by email and/or syslog. 
  Schedule scans and get notified when vulnerabilities, outdated plugins and other risks are found.FeaturesScanmultiple siteswith WPScanParse WPScan outputand divide the results in"Alerts","Warnings"and"Informations"Handled VulnDB API limitDefinereporting emails addressesfor every configured site individually and globallyDefinefalse positives stringsfor every configured site individually and globallyDefineWPScan argumentsfor every configured site individually and globallySend WPScan findings toSyslogserverSave raw WPScan output into filesLog file lists all the findingsSpeed up scans using several asynchronous workersFollow URL redirectionif WPScan fails and propose to ignore main redirectScan sites continuously at defined interval and configure script as a linux serviceAdditionnal alerts depending of finding type (SQL dump, etc.)Keep track of fixed and unfixed issuesDocumentationRead The Docs.Usage exempleScan two sites, add WPScan arguments, follow URL redirection and email report to recepients. If you reach your API limit, it will wait and continue 24h later.wpwatcher--urlexemple.comexemple1.com\--wpscan_args"--force --stealthy --api-token <TOKEN>"\--follow_redirect--api_limit_wait\--send--infos--email_toyou@office.came@office.caWPWatcher must read a configuration file to send mail reports. This exemple assume you have filled your config file with mail server setings.EmailsSample email report.AuthorsFlorian Roth (Original author ofWPWatcher v0.2)Tristan LandesDisclamerUse at your own risks.
Package: wpx
wpx 💻Wpx is a wallpaper downloader. That's it.Supported Wallpaper ProvidersBing.comWallpapersHomeRequirementsPython 3.5+(Linux)python3-gi(when installing throughpipxpass--system-site-packages)UsageGet a random image from a WallpapersHome category:$ FILENAME=$(wpx wallpapershome '{category: art/anime}' --random)Get Bing's image of the day:$ FILENAME=$(wpx bing -d ~/Pictures/wallpapers --daily)Or set up a cron to update your background wallaper every hour:0 1 * * * ~/.local/bin/wpx -d ~/Pictures/wallpapers --set-desktop --daily bing
Package: wpxredisorm
#redis-orm
一个使用redis的key-value的ORM模型的数据操作，使用redis-py作为底层连接。
# 2016-5-14 17:43:04
目前已经实现的功能：
1.创建记录
2.根据id进行查找
3.根据多个条件进行与关系查找
待实现:
多个条件进行或查找
删除记录
优化查找功能# 2016年07月03日17:43:39
实现增删改查基本功能
查询方式使用生成器，只用迭代的时候才会返回具体的记录
Package: wpx-redis-orm
#redis-orm
一个使用redis的key-value的ORM模型的数据操作，使用redis-py作为底层连接。
# 2016-5-14 17:43:04
目前已经实现的功能：
1.创建记录
2.根据id进行查找
3.根据多个条件进行与关系查找
待实现:
多个条件进行或查找
删除记录
优化查找功能
Package: wpydumps
WPyDumpsWPyDumpsis a Python module to work withdumps of Wikipedia.It allows one to parse and extract relevant information from dump files without un-compressing them on-disk.It works with (at least) these dumps:pages-meta-history….xml-….7z(“All pages with complete edit history”)pages-meta-current.xml.bz2Installpip install wpydumpsUsageThe parser usesSAXto read the files as a stream. It takes a reader or a filename and a page callback function. It
parses the file and call that function with each page.Pages are represented aswpydumps.model.Pageobjects. They include the pages’ details as well as their
revisions (wpydumps.model.Revision). Each revision holds a reference to its contributor (wpydumps.model.Contributor)
.importwpydumpsaspdefsimple_page_callback(page):print(page.title)# parse from a local archivep.parse_pages_from_archive_filename("myfile.7z",simple_page_callback)# parse from an uncompressed filewithopen("myfile")asf:p.parse_pages_from_reader(f,simple_page_callback)Revisions always have atext_lengthanddiff_lengthintattributes. You may drop the text content by
passingkeep_revisions_text=Falseto the parser.Examplesfromwpydumpsimportparse_pages_from_archive_filenamedefpage_callback(page):pass# do something with the page# use the appropriate filenameparse_pages_from_archive_filename("frwiki-20190901-pages-meta-history1.xml-p3p1630.7z",page_callback)Print all pages and their number of revisionsdefpage_callback(page):print(page.title,len(page.revisions))Print all pages and their number of contributorsdefpage_callback(page):contributors=set()forrevinpage.revisions:contributors.add(rev.contributor.usernameorrev.contributor.ip)print("%s:%dcontributors"%(page.title,len(contributors)))
Package: wq
wqis a modular framework for field data collection and surveys via offline-capable mobile web apps.Getting Startedwq can be installed via PyPI, NPM, or plain<script>tag via CDN.  Seethe documentationfor more information on getting started.Pythonpython3-mvenvvenv
.venv/bin/activate
python-mpipinstallwq
wqcreate-dmyproject.example.commyprojectNodenpxcreate-react-appmyproject--template@wqCDN<scripttype="module">importwqfrom'https://unpkg.com/wq@next';wq.init({});</script>Featureswq is made up of the following submodules, which are maintained as separate packages.ModuleGithubPyPInpmDescriptionwq/wqwqwqTop level package (specifies submodules as dependencies)wq/wq.appwq.app@wq/appA JavaScript+Python library for building robust offline-capable HTML5 data entry apps.wq/wq.buildwq.buildwq command line interface.wq/wq.createwq.createProject template and scaffolding tools.wq/wq.dbwq.dbDjango REST framework extension with design patterns for CRUD APIs.
Package: wq.app
wq.appis a suite of JavaScript modules created to facilitate the rapid deployment of offline-capable mobile and desktop data collection apps.  Potential use cases includesurveys,geographic data capture & management, andcrowdsourcing/citizen science.  wq.app is the client component of thewq framework, and can be used with awq.dbserver or adapted for use with any API.DocumentationInstallationAPI@wq/app•@wq/store•@wq/model•@wq/router•@wq/outboxPlugins@wq/react•@wq/material•@wq/map•@wq/map-gl
Package: wqchartpy
WQChartPy is an open-source python package developed for graphical diagrams
of water geochemistry data. Utilizing the commonly used CSV
as the input data format, WQChartPy can produce
eleven diagrams including not only the traditional Piper trilinear diagram,
Stiff diagram, Durov diagram and Schoeller diagram, but also the recently
proposed new diagrams such as the rectangle Piper, color-coded Piper and HFE-D
that has not implemented in previous software.This is the first release of WQChartPy. As a Python-based cross platform
program, WQChartPy works on Windows, MacOS X and GNU/Linux. We provided a
self-contained Jupyter notebook file to illustrate how to use WQChartPy.
Users with a little Python experience can do the whole process from data to
the graphical diagrams. Buidling on the oldest and most popular Python
plotting library Matplotlib, the figures generated by WQChartPy can be saved
as portable network graphics (PNG), scalable vector graphics (SVG) or portable
document format (PDF). WQChartPy is an open-source project and any
assistance is welcomed. Please email the development team if you want to
contribute.
Package: wq.core
wq.coreprovides the corewqcommand line application for use bywq.appand other modules in thewq framework.Getting Started# Recommended: create virtual environment# python3 -m venv venv# . venv/bin/activate# Install entire wq suite (recommended)python3-mpipinstallwq# Install only wq.corepython3-mpipinstallwq.coreCommand Line Referencewq--helpSeethe documentationfor more information.
Package: wq.db
wq.dbis a collection of Python modules for building robust, flexible schemas and REST APIs for use in creating field data collection apps and (more generally) mobile-first websites with progressive enhancement.  wq.db is the backend component ofwqand is geared primarily for use withwq.app, though it can be used separately.  wq.db is built on theDjangoplatform.DocumentationInstallationAPIwq Config Object•URL Structure•Settingswq.db.restModelRouter•ModelSerializer•ModelViewSetGuidesFieldsets•Repeating Nested Forms•Entity-Attribute-Value
Package: wqsketch
wqsketchDeveloped by Benjamin TayImplements Algorithm 1 and 2 from the DDSKetch paper.http://www.vldb.org/pvldb/vol12/p2195-masson.pdfExamplesBasic Usagefromwqsketchimportcreate_sketchfromwqsketchimportcalculate_quantilefromwqsketchimportmerge_sketchimportnumpyasnpdata1=2*np.random.random_sample((100,))-1data2=data1+1data3=data1-1sketch1=create_sketch(data1)sketch2=create_sketch(data2)sketch3=create_sketch(data3)sketch1_median=calculate_quantile(0.5,sketch1)sketch2_median=calculate_quantile(0.5,sketch2)sketch3_median=calculate_quantile(0.5,sketch3)sketch_list=[]sketch_list.append(sketch1)sketch_list.append(sketch2)sketch_list.append(sketch3)merged_sketch=merge_sketch(sketch_list)merged_sketch_median=calculate_quantile(0.5,merged_sketch)Notescreate_sketch takes 3 arguments: the data vector, alpha, and the weight.alpha (accuracy of the quantile) defaults to 0.01.weights default to 1.merge_sketch takes 1 argument: a list of sketchescalculate_quantile takes 2 arguments: the quantile to calculate and the sketch
Package: wq.start
wq.startprovides a simple command-line interface (wq start) for starting a new project with thewq framework, withwq.appfor the front end andwq.dbas the backend component.wq.startalso provides commands for generating a default set of offline-capable list, detail, and edit templates.  The templates can be generated for existing Django models (viawq maketemplates), or both the models and the templates can be generated from an ODK-styleXLSForm(viawq addform).Usage# Recommended: create virtual environment# python3 -m venv venv# . venv/bin/activatepython3-mpipinstallwq

wqstart<projectname>[directory]cd<projectname>/db
wqaddform~/my-odk-form.xlsxSee theGetting Starteddocs for more information.Commandswq start <projectname> [directory]: Create a new Django project (from thewq Django template)wq addform ~/myodk-form.xlsx: Create a new Django app from the provided XLSForm (usesxlsform-converter)wq maketemplates: Create templates for Django models registered withwq.db.rest
Package: wr
wr (Weighted Random)wr is a weighted random implementation in Python.wr.choicecan be fed with a mapping (such as dictionaries) containing a returnable (what to return) and a integer representing their respective weight.
The key can be anything hashable but the weight must be a integer.Optionally you may feedwr.choicewith a sequence of pairs.DocumentationDocumentation is available athttp://wr.readthedocs.org/Example>>> import wr

>>> data = {'cat': 60, 'dog': 30, 'bird': 10}
>>> animal = wr.choice(data)
>>> print animal
cat # well, the cat had a good 60% shot at it.InstallationInstall wr withpip install wror justdownload wr.pyand place it in your project directory.LicenseBSD
Package: wracker
# Wracker(PRE-ALPHA DO NOT USE) A Python clone of bundler.  The wheel racker!## Commandswracker installinstalls packages from arequirements.infile (in your CWD
or parent directories) and writes the specific versions torequirements.txtwracker execsets$PYTHONPATHto use only the packages in your
requirements.txt, nothing more.  It also modifies$PATHto point to a
‘clean’ virtualenv, which wracker manages for you.  These virtualenvs do not
havepipinstalled so hopefully they never become polluted (although there
are no hard locks in place or anything like that).It also adds entrypoints to your$PATH, sowracker exec pep8will use a
frozen pep8 if available.## Todo(Presented in no particular order.)[ ] Support installation with Python 3[ ] VCS URLs[ ]-rincludes[ ] Verification that all versions are compatible (similar to pip-tools)[ ] Tests
Package: wradlib
READMEwradlib is designed to assist you in the most important steps of
processing weather radar data. These may include: reading common data
formats, georeferencing, converting reflectivity to rainfall
intensity, identifying and correcting typical error sources (such as
clutter or attenuation) and visualising the data.To anyone who wants to use a bleeding edge version of wradlib from this repository:wradlib uses GitHub Actions for Continuous Integration. This means that once new code is pushed to the wradlib repository, a suite of tests and checks are run. In case the tests run without failure, a new documentation will be built on readthedocs and is available at thewradlib documentation website.Below you see the status of wradlib. A green status indicates that the current revision of wradlib did pass the tests successfully. You should be aware of that a green status is not a guarantee that the latest revision is bug free. It just means that our tests did not find any bugs. Also, the status of code coverage, of ReadTheDocs documentation builds and of availability of wradlib conda package is displayed.Package StatusItemStatusGithub LatestGithub ReleaseCodecovRTD LatestRTD StableAnaconda LatestAnaconda VersionDocumentationFor further information on wradlib (getting started, library reference, development setup, ...), please see our homepage:https://wradlib.orgSpecific information for developers is available via thewradlib-wiki.Citing wradlibYou can cite wradlib using the DOI below, or select the fitting zenodo DOI if you want to cite a distinct wradlib version by following the link.User forumIn order to stay tuned, we recommend that you register to theopenradar discourse.Found any bugs or want to add wishesCreate an issuehere.
Package: wrangalytics
wrangalyticsA python package for routine data wrangling and analytics tasks.To InstallPIP via GitHub: pip install -e git+https://github.com/acastrounis/wrangalytics.git#egg=wrangalyticsPIP: pip install wrangalyticsFrom Conda: coming soonNOTE: Currently installing with PIP via GitHub ensures the latest version.UpgradingPIP via GitHub: pip install --upgrade -e git+https://github.com/acastrounis/wrangalytics.git#egg=wrangalyticsPIP: pip install --upgrade wrangalyticsFrom Conda: coming soonMore on its way...
Package: wrangl
WranglParallel data preprocessing and fast experiments for NLP and ML.
Seedocs here.Why?I built this library to prototype ideas quickly.
In essence it combinesHydra,Pytorch Lightning,moolib, andRayfor some fast data processing and (supervised/reinforcement) learning.
The following are supported with command line or config tweaks (e.g. no additional boilerplate code):checkpointingearly stoppingauto git diffslogging to S3 (along with auto-generated seaborn plot), wandbSlurm launcherInstallationpipinstall-e.# add [dev] if you want to run tests and build docs.# for latestpipinstallgit+https://github.com/vzhong/wrangl# pypi releasepipinstallwranglIfmoolibinstall fails because you do not have CUDA you can try installing it yourself withenv USE_CUDA=0 pip install moolib.UsageSeethe documentationfor how to use Wrangl.
Examples of projects using Wrangl are found inwrangl.examples.
In particularwrangl.examples.learn.xor_clfshows an example of using Wrangl to quickly set up a supervised classification task.
For parallel data preprocessingwrangl.examples.preprocess.using_stanzashows an example of using Stanford NLP Stanza to parse text in parallel across CPU cores.If you find this work helpful, please consider citing@misc{zhong2021wrangl,
  author = {Zhong, Victor},
  title = {Wrangl: Parallel data preprocessing for NLP and ML},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/vzhong/wrangl}}
}
Package: wranglepy
wranglepy:A python package containing some easy-to-use functions for cleaning data.
>The package contains functions that allow you explore your data easily to:Find missing/null values visually,Remove missing values,Find categorcial variables in your datatset,Remove highly correlated values,Plot bar graphs and automatically add the percentages of variables,Plot twin axis bar graphs,Adjust size of bars in bar graphs,Model ML classification algorithms.
Package: wrangle-pypes
wrangle_pypesEasy, model based data wrangling.OriginThis project came about thanks to having implemented this concept in a prior project (dfb_predict) and wanting to reuse it. In said previous project it came about, because we wanted to play around with data-oriented design and figured that if we break up the transformations required during data-wrangling/munging into a simple "AST" where each node represents a single transformation. And to further the idea we to some inspiration from one of theUnix philosophycore tenants, i.e. a single transformation should do one simple thing only, and allow for composition to implement more complex behavior.Examplefromdataclassesimportdataclassimportjsonfromwrangle_pypesimportPipelinefromwrangle_pypes.transformationsimportGet,Create,Cast@dataclassclassPoint:x:inty:int@dataclassclassSquare:A:PointB:Pointpipeline=Pipline({Square:{"A":Get("A")|Create(Point),"A":Get("B")|Create(Point),},Point:{"x":Get("x")|Cast(int),"y":Get("y")|Cast(int),}})data="""[{"A": {"x": 0, "y", 0},"B": {"x": 1, "y", 1},}, {"A": {"x": 10, "y", 10},"B": {"x": 11, "y", 11},}]"""squares=list(pipeline.create_multiple(json.loads(data)))