Saravanan666/pypi-org huggingface dataset:
Package: ews-builder
ews_builderews-buildertakes the Exchange Web Services WSDL files and generates EWS SOAP request bodies for each operation/endpoint.Getting StartedTo useews-builderyou can run it directly.  Sinceews-builderis mainly considered a command line tool, once installed, you run it directly:# Will display the help systemews-builder# to build a service typeews-builderbuild# select 'All' or specific services to buildPleaseselect'All'orspecificservicestogenerate*AllFindAvailableMeetingTimesFindMeetingTimeCandidatesUploadItemsExportItemsConvertIdGetFolderCreateFolderCreateFolderPathCreateManagedFolderDeleteFolder......# get show additional paramters use the helpews-builderbuild--help

INFO:Showinghelpwiththecommand'ews-builder build -- --help'.

NAMEews-builderbuild

SYNOPSISews-builderbuild<flags>

FLAGS--service_name=SERVICE_NAME--generate_strings=GENERATE_STRINGS--output=OUTPUTPrerequisitesThis package installs the following packages:pyyaml
fire
pickInstallingIn order to use carcass you can install it viapipor clone this repository.pipinstallews-buildergitclonegit@github.com:swimlane/ews-builder.gitcdews-builder
pipinstall-rrequirements.txtBuilt Withcarcass- Python packaging templateContributingPlease readCONTRIBUTING.mdfor details on our code of conduct, and the process for submitting pull requests to us.VersioningWe useSemVerfor versioning.AuthorsJosh Rickard -Initial work-MSAdministratorSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: ewsgi
Date:2013-05-01 14:22tags:cloud, api, flask, wsgi, eventletcategory:*nixEventlet WSGI ServerThe purpose of this repository is to provide for a general purpose eventlet
server that can power just about any Application. It is my hope that is
used to rapidly spin up a WSGI server which has support for many common
configurations while also being performant enough to server your content
without having to setup a more heavy weight web server.This is a great tool for embedded applications where Apache and or NGINX may
not be an option.UsageTo use ewsgi simply build your application and then pass the application and
the relevant configuration to the server. Everything else is handled from
there on in.For an example on how an app could look like please go here:https://github.com/cloudnull/eventlet_wsgi/tree/master/example_appHowever, if you would like to know how to make the server work, minimally,
you can simply instantiate the server and run it:# Assuming you have a built app import it and pass it to eswgifromewsgiimportrun# This import would be your appimportapp# Run the new application with all of the relevant configuration bitsrun.preload_and_start(app_name=app.APPNAME,# Name of your appload_app=app.APP,# The prebuilt app objectconfig_path=os.getcwd(),# The path to your configuration filesloggers=[app.APPNAME]# List of log handlers for the app)
Package: ews-nmap
ews-nmapExtractWebServers from NmapTable of ContentsOverviewGetting StartedExampleInstall & RunRun without installingPrerequisitesContributingCreditsLicenseOverviewews-nmap(ExtractWebServers from Nmap) is a simple script that allows you to easily find all web servers from the XML output of Nmap.
The script performs a simple scraping of the informations in the XML file and identifies HTTP/S services.Getting StartedRunnmapand save XML output, for example:nmap -sV -oX <nmap_output.xml>ExampleThe output of the tool is like the following:Install & RunTo install it you just need to run:pip install ews-nmapRun without installingPrerequisitesInstall dependencies by using the following command:pip install -r requirements.txt
chmod +x ewsnmap/ewsnmap.pyUsage: ewsnmap.py NMAP_XML_FILE <flags>
  optional flags:        --output-dir | --outputTo run the parser:ewsnmap.py <nmap_output.xml>the script will generate a fileoutput.txtinewsnmap-outputdir. If you want to set the output file and the output dir:ewsnmap.py <nmap_output.xml>  --output <output_csv_file> --dir <output_directory>ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull RequestCreditsews-nmapis proudly developed@SecSIby:Angelo DelicatoLicenseDistributed under Apache 2 License. SeeLICENSEfor more information.
Package: e-WTForms
e-WTFormse-WTForms is an unofficial upgrade of WTForms library with more functionality.WTFormsWTForms is a flexible forms validation and rendering library for Python
web development. It can work with whatever web framework and template
engine you choose. It supports data validation, CSRF protection,
internationalization (I18N), and more. There are various community
libraries that provide closer integration with popular frameworks.InstallationInstall and update using pip:pip install -U e-WTFormsLinksDocumentation:https://e-wtforms.readthedocs.io/Releases:https://pypi.org/project/e-WTForms/Code:https://github.com/ennkua/e-wtformsIssue tracker:https://github.com/ennkua/e-wtforms/issues
Package: ewtpy
ewtpy - Empirical wavelet transform in PythonAdaptive decomposition of a signal with the EWT (Gilles, 2013) methodPython translation from theoriginal Matlab toolbox.ewtpy performs the Empirical Wavelet Transform of a 1D signal over N scales. Main function is EWT1D:ewt,  mfb ,boundaries = EWT1D(f, N = 5, log = 0,detect = "locmax", completion = 0, reg = 'average', lengthFilter = 10,sigmaFilter = 5)Other functions include:EWT_Boundaries_DetectEWT_Boundaries_CompletionEWT_Meyer_FilterBankEWT_betaEWT_Meyer_WaveletLocalMaxLocalMaxMinSome functionalities from J.Gilles' MATLAB toolbox have not been implemented, such as EWT of 2D inputs, preprocessing, adaptive/ScaleSpace boundaries_detect.The Example folder contains test signals and scriptsInstallationDowload the project fromhttps://github.com/vrcarva/vmdpy, then run "python setup.py install" from the project folderORpip install ewtpyCitation and ContactPaper available athttps://doi.org/10.1016/j.bspc.2020.102073.If you find this package useful, we kindly ask you to cite it in your work.Vinícius R. Carvalho, Márcio F.D. Moraes, Antônio P. Braga, Eduardo M.A.M. Mendes,
Evaluating five different adaptive decomposition methods for EEG signal seizure detection and classification,
Biomedical Signal Processing and Control,
Volume 62,
2020,
102073,
ISSN 1746-8094,https://doi.org/10.1016/j.bspc.2020.102073.If you developed a new funcionality or fixed anything in the code, just provide me the corresponding files and which credit should I include in this readme file.Any questions, comments, suggestions and/or corrections, please get in contact withvrcarva@ufmg.br@author: Vinícius Rezende Carvalho
Programa de pós graduação em engenharia elétrica - PPGEE UFMG
Universidade Federal de Minas Gerais - Belo Horizonte, Brazil
Núcleo de Neurociências - NNCExample script#%% Example scriptimportnumpyasnpimportmatplotlib.pyplotaspltimportewtpyT=1000t=np.arange(1,T+1)/Tf=np.cos(2*np.pi*0.8*t)+2*np.cos(2*np.pi*10*t)+0.8*np.cos(2*np.pi*100*t)ewt,mfb,boundaries=ewtpy.EWT1D(f,N=3)plt.plot(f)plt.plot(ewt)
Package: ex11
An example package. Generated with cookiecutter-pylibrary.Free software: BSD 2-Clause LicenseInstallationpip install ex11DocumentationTo use the project:importex1ex1.longest()DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2019-04-04)First release on PyPI.
Package: ex4ml
# ex4mlA toolkit for conducting machine learning experiments efficiently.![image](https://gitlab.com/minds-mines/ex4ml/ex4ml/badges/master/pipeline.svg)
![image](https://gitlab.com/minds-mines/ex4ml/ex4ml/badges/master/coverage.svg)## DescriptionThe target audience of ex4ml is researchers conducting experiments in
machine learning. The goal of ex4ml is to allow you to focus on the
machine learning research while minimizing your worrying about designing
and managing experiments.The secondary audience of ex4ml is machine learning practitioners who
want a simple way to test and compare machine learning approaches.### Applicationsex4ml should work for experiments on the following and all combinations
of them:Multi-Modal / Multi-View learningMultiple-Instance learningFeature comparisonsFeature visualizations### Development#### SummaryHere is the summary of what you need to do. Read on for more details.Install everything:`bash pipenv install--dev`Run tests:`bash pipenv shell python setup.py test `After you make changes make sure you run autopep8 to fix your code's
syntax and pylint to get feedback on what could be improved in your
code.`bash pipenv shell autopep8--in-place--aggressive--aggressive*.py pylintsrc/ex4ml/*.pypylinttest/*.py`#### PipenvUse [pipenv](http://pipenv.readthedocs.io/en/latest/) to automatically
manage isolated, virtual environments for Python projects.Install/upgradepipenvvia the command line.`bash pip install--upgradepipenv `To install modules or create aPipfilefrom arequirements.txtfile:`bash pipenv install `To install dev-modules:`bash pipenv install--dev`To install or uninstall modules respectively to or from your Python
project:`bash pipenv install module_name pipenv install dev_module_name--devpipenv uninstall module_name `To manually create aPipfile.lockfile from the installed versions:`bash pipenv lock `To load the Python virtual environment into the shell to execute
commands or run a single command using the Python virtual environment
use the following:`bash pipenv shell pipenv run command_name `Useexitto unload the Python virtual environment.To see your project's dependency graph:`bash pipenv graph `#### PyScaffoldThis project has been set up using PyScaffold 3.0.3. For details and
usage information on PyScaffold see <http://pyscaffold.org/>.Use [PyScaffold](http://pyscaffold.org/en/latest/features.html) to
quickly setup and manage Python projects.### InstallationYou will need [Git](https://git-scm.com) withuser.nameanduser.emailsetup to get started.`bash git config--globaluser.name "John Doe" git config--globaluser.email "john.doe@email.com" `Install/upgradesetuptoolsandpyscaffoldvia the command line:`bash pip install--upgradesetuptools pip install--upgradepyscaffold `### TestingTo execute unit tests in thetestsdirectory, use:`bash pipenv shell python setup.py test `
Package: exa
A framework for data engineering and scienceInstallationExa is available throughanaconda$ conda install -c exaanalytics exaorpypi.$ pip install exaGetting StartedSeedocsfor usage.Building the docs requiressphinx. On Linux or Mac:$ ./make-docs.shOn Windows:$ make-docs.batDevelopmentFor a development ready installation:$ git clone https://github.com/exa-analytics/exa.git
$ cd exa
$ python setup.py developReferenceLegalCopyright (c) 2015-2020, Exa Analytics Development TeamDistributed under the terms of the Apache License 2.0
Package: exabel-data-sdk
Exabel Python SDKA Python SDK which provides easy access to Exabel APIs.Installationpip install exabel-data-sdkor download fromPyPI.The SDK requires Python 3.8 or later.Installation with SQL data source supportFor installation with support for exporting data from a various SQL based data sources, add the data source as a pip extra in brackets after the package name:# Install the Exabel Python SDK with Snowflake support:pipinstallexabel-data-sdk[snowflake]# Or install multiple data sources at the same time:pipinstallexabel-data-sdk[snowflake,bigquery,athena]Supported data sources are:Snowflake:snowflakeGoogle BigQuery:bigqueryAWS Athena:athenaGetting startedTo use the SDK against the Data API, Analytics API or Management API, you need an API key provided by Exabel.The Exabel Export API can be used by authenticating with username and password.
The first time you run the script a web browser window is opened where you are asked to provide username and password. The script stores an access token in~/.exabel, so you will not be asked again
until the token expires.Export API Developer guideExamples of usage.Exabel API documentationData APIThe Exabel Data API can be used to upload custom data to the Exabel platform. Custom data may include entities, relationships and time series.Data API Developer guideExport APIThe Exabel Export API can be used to export dashboards and signals from the Exabel Platform.Export API Developer guideAnalytics APIThe Exabel Analytics API can be used to manage derived signals and prediction models on the Exabel Platform.Analytics API Developer guideManagement APIThe Exabel Management API can be used to manage the library on the Exabel Platform.Management API Developer guide
Package: exabgpctl
ExaBGP Controllerexabgpctl is wrapper arroundExaBGPfunctions.Enable / Disable maintenanceView processes and neigboursCheck neighbours connectivityCheck processes statusesInstallation and documentationFulldocumentationCode repository is onGitHubIf you find any problems please fill out anissue. Thank you!ContributingWant to help build? Check out ourcontributing documentation.
Package: exabyte-api-client
This package provides access to Exabyte.ioRESTful API.InstallationWe recommend creating a virtual environment before installing:virtualenvmy-virtualenvsourcemy-virtualenv/bin/activateInstall using pip:from PyPI:pipinstallexabyte-api-clientfrom source code in development mode:gitclonegit@github.com:Exabyte-io/exabyte-api-client.gitcdexabyte-api-client
pipinstall-e.Examplesexabyte-api-examplesrepository contains examples for performing most-common tasks in the Exabyte.io platform through its RESTful API in Jupyter Notebook format.TestingA Virtualenv environment can be created and the tests run with the includedrun-tests.shscript.
To run the unit tests in Python 3, you can:./run-tests -t=unitTo run the integration tests in Python 2, you can:./run-tests -p=python2 -t=integration(assuming you have apython2binary in your PATH environment).Note that the integration tests require a REST API service against which the live tests will run. Seetests/integration/__init__.pyfor the environment variable details.© 2020 Exabyte Inc.
Package: exabyte-json-include
json-include is an extended way for JSON to support file inclusion, it has two parts:A syntax definition calledinclude syntax.A Python implementation to parse and build JSON file that containsinclude syntax.Syntaxjson-include supports an extended syntax calledinclude syntaxin JSON,
formatted as:{"...":"include(<json file name>)"}or{"<any key>":"include_text(<text file name>)"}The include syntax means that this object (the whole{"...":"include(<jsonfilename>")}) in JSON is a reference to the JSON file named in<json file name>notation, and should be included into its place.The included JSON should always be an object (dict) rather than an array (list), to prevent implicit meaning and make sure we can get a clear view of the structure without looking into the included JSON files.In case multiple include statements are used, passing key insidemakeUniqueadds a random string to each included value at the corresponding key:{"...":"include(<json file name>)","makeUnique":"<key>"}In a normal JSON when we want to include another JSON on an attribute, it should be written as follows:{"username":"alice","profile":{"...":"include(profile_model.json)"}}In this JSON aprofile_model.jsonis included to presentprofileattribute,
if the content ofprofile_model.jsonis like:{"age":18,"gender":"female"}then what we mean by the include syntax is that, when this JSON is being used
as a normal JSON, it should be seen as:{"username":"alice","profile":{"age":18,"gender":"female"}}To ture JSON with include syntax into a normal JSON, a build process is needed,
that’s what the implementation does.Python ImplementationImplementation could be of any language as long as it can understand the include syntax
and output as expected, this repo contains a Python implementation for use.Installationpip install https://github.com/exabyte-io/json_include/archive/master.zipUsageimportjson_includejson_include.build_json(ROOT_DIR,'example.json')
Package: exacheck
ExaCheck - ExaBGP Service Health CheckerExaCheckworks in conjunction withExaBGPto health check services and announce BGP routes depending on the state of the service.For additional information, deployment instructions and configuration examples please check theExaCheck website.Why ExaCheckExaBGP is packaged with its own health checking script (see here) however it has some limitations which make it not suitable for my requirements. The built in health check works fine for smaller environments where each service may be running its own instance of ExaBGP (so each instance of ExaBGP runs one or only a few processes) however for larger environments where health checks are centralised it becomes unmanageable.Some features from the built in ExaBGP health checking script arenotavailable as they are not relevant to the use case for me:Management of IP address binding; the main use case of ExaCheck is for centralised health checks where the service resides on another server/container/VMFeaturesLive configuration reloads (adding/modifying/removing services)Health checks implemented in pure python where possible; no need to write scripts or use chains of commands to validate outputDetailed logging availableConfiguration validation (if using live configuration reloads, configuration is validated before application)Out of the box sane defaults where possibleJSON schema of configuration (seeschema.jsonfor the current schema)
Package: exact-cover-py
exact cover in Pythonan implementation of Donald Knuth's Dancing Links algorithm in pure PythonUsagepipinstallexact_cover_pyfromexact_cover_pyimportexact_coversproblem=np.array([[1,0,0,1,0,0,1],[1,0,0,1,0,0,0],# <--[0,0,0,1,1,0,1],[0,0,1,0,1,1,0],# <--[0,1,1,0,0,0,1],[0,1,1,0,0,1,1],# <--[0,1,0,0,0,0,1],])# exact_covers returns a generator of solutions# one solutionprint(next(exact_covers(problem)))[1,5,3]# all solutionsprint(list(exact_covers(problem)))[[1,5,3]]# number of solutionsdefmylen(iterable):returnsum(map(lambdax:1,iterable))print(mylen(exact_covers(problem)))2Development# build and install locally with tests dependenciespipinstall-e.[tests]pytestBuilding and publishing# depspipinstallbuildhatchlingtwine# buildpython-mbuild# publishtwineuploaddist/*
Package: exacto
ExactoExacto is a collection of Python tools that simplify splitting strings according to non-trivial business rules. You may find this package useful if:A regular expression is not enough for your use case.You want to avoid writing and maintaining manual parsing code.You don't want to mess around with LLVM or FSMs.However, if performance is your primary goal, these tools may not be for you.Usagefromexactoimportsplit,lift,quote,nest# Simple example with default rules: split on whitespaceresult=split("Hello   World")assertlist(result)==["Hello","World"]# Complicated example with custom separator and quotesresult=split("ENV='Prod-172.0.10.10'.VER='2.1'",quote("'"),".")assertlist(result)==["ENV='Prod Env'","VER='2.1'"]# Extract embedded tokensresult=lift("Hello [FOO] is [BAR]",nest("[","]"))assertlist(result)==["FOO","BAR"]
Package: exalt
exaltprovides a convenient way to dynamically create closures and bind them to a custom namespace. This is primarily useful for preserving an execution-context when calling into a different function.Examplefromexaltimportpromotedefbaz():returnbardeffoo():bar="baz"returnpromote(baz,**locals())()print(foo())——————————————————————————— ↓ ———————————————————————————bazInstallationpip3install--userexaltDisclaimerexaltheavily relies on CPython implementation details and probably shouldn't be used in a production environment.
Package: exam2pptvideo
Installationpip3 install --verbose exam2pptvideoUsagePlease refer toapi docs.Execute usageValidate ppt templateexam_pptx_validate --pptx [pptx file]Convert exam csv file into ppt fileexam_csv2pptx --sourcecsv [exam csv file] --lang [language] --title [title shown in ppt] --destpptx [pptx file]Convert ppt into pdf and imagesexam_pptx2media --sourcepptx [pptx file] --destdir [dest directory storing pdf and images]Convert ppt into videosexam_pptx2video --sourcepptx [pptx file] --destdir [dest directory storing videos] --lang esPackage usagefrom exam2pptvideo import SpanishExamPPT, SpanishExamVideo
from exam2pptvideo.lib import pptx2pdf, pdf2images
 
def csv2pptx(sourcecsv, title, lang, destpptx):
  _PPTS = {
    "es": SpanishExamPPT
  }

  _PPT = _PPTS[lang]

  vp = _PPT(sourcecsv, title)
  vp.convert_to_ppt(destpptx)

def pptx2video(sourcepptx, lang, destdir):
  _VIDEOS = {
    "es": SpanishExamVideo
  }

  _VIDEO = _VIDEOS[lang]

  ev = _VIDEO(sourcepptx)

  ev.create_videos(destdir)

def pptx2pdf2images(sourcepptx, destdir):
  pdf = pptx2pdf(sourcepptx, destdir)
  images_len = pdf2images(pdf, destdir)DevelopmentClone projectgit clone https://github.com/qishe-ttt/exam2pptvideoInstallpoetryInstall dependenciespoetry updateTestpoetry run pytest -rP --capture=syswhich run tests undertests/*Executepoetry run exam_pptx_validate --help
poetry run exam_csv2pptx --help
poetry run exam_pptx2media --help
poetry run exam_pptx2video --helpCreate sphinx docspoetry shell
cd apidocs
sphinx-apidoc -f -o source ../exam2pptvideo
make html
python -m http.server -d build/htmlHost docs on github pagescp -rf apidocs/build/html/* docs/BuildChangeversioninpyproject.tomlandexam2pptvideo/__init__.pyBuild python package bypoetry buildGit commit and pushPublish from local dev envSet pypi test environment variables in poetry, refer topoetry docPublish to pypi test bypoetry publish -r testPublish through CIGithub action build and publish package totest pypi repogit tag [x.x.x]
git push origin masterManually publish topypi repothroughgithub action
Package: examAnalyserINF219v23
Exam analyzerExam analyzer is a tool that extract data from json files, and the creates visualizations with descriptive texts.Getting startedTo run the exam analyzer you need following libraries:matlab - pip install matlabflask - pip install Flasklatex and pypandocs - go to the followng linkhttps://www.tug.org/mactex/mactex-download.html, and donwload the package. After it is downloaded run  the command line:  pip install pandoc pypandocrunning the websiteIf everthing is donwloaded and updated, you should be able to run the local webpage. When you import the package at run the app the terminal should show up and you can be able to go to the link in the terminal.
Package: exam-analyzer
exam_analyzer使用指南1. 安装 python 运行环境已经安装过 python，且 python 版本>=3.7 可以跳过此步骤python 版本低于 3.7 的，建议先卸载老版本的 python，再安装新版 python推荐下载python3.10如果下载不动，请使用迅雷等下载工具2. 建立班级文件夹，并放入学生的成绩报告单(PDF文件)以班级为单位，新建文件夹，文件夹必须以'班'字结尾，例如：301班、302班、303班、……然后将学生的 pdf 文件放入所在班级的文件夹，pdf 文件必须是官方网站下载的，否则可能出现解析错误，导致信息、分数不一致等情况。3. 双击生成.bat文件本着Pythonic理念，本人已将该工具包发布到 python 官方的 PyPI 上，感兴趣的老师欢迎加入开发。生成.bat文件中，包含了几条命令，双击后会自动下载本人发布的工具库，下载完成后便会运行，老师们只需等待执行完成即可
Package: examAnalyzerINF219h23
Exam analyzerExam analyzer is a tool that extract data from Json files from Inspera, and then creates visualizations with descriptive texts.Getting startedTo run the exam analyzer you need python downloaded and the following libraries:matplotlib - pip install matplotlibflask - pip install flasklatex and pypandocs - go to the followng linkhttps://www.tug.org/mactex/mactex-download.html, and donwload the package. After it is downloaded run  the command line:  pip install pandoc pypandocexamAnalyzerINF219h23 - pip install examAnalyzerINF219h23 (or go to website:https://pypi.org/project/examAnalyzerINF219h23/and copy link)Running the websiteIf everthing is donwloaded and updated, you should be able to import the package and do as you please.How to run appwrite the following in an IDE:From examAnalyzerINF219h23.app import run_app
run_app()This is everything needed to run the website locally