Saravanan666/pypi-org huggingface dataset:
Package: wlufqksjez
Wlufqksjez=================This API SDK was automatically generated by [APIMATIC Code Generator](https://apimatic.io/).This SDK uses the Requests library and will work for Python ```2 >=2.7.9``` and Python ```3 >=3.4```.How to configure:=================The generated code might need to be configured with your API credentials.To do that, open the file "Configuration.py" and edit its contents.How to resolve dependencies:===========================The generated code uses Python packages named requests, jsonpickle and dateutil.You can resolve these dependencies using pip ( https://pip.pypa.io/en/stable/ ).1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r requirements.txt```Note: You will need internet access for this step.How  to test:=============You can test the generated SDK and the server with automatically generated testcases. unittest is used as the testing framework and nose is used as the testrunner. You can run the tests as follows:1. From terminal/cmd navigate to the root directory of the SDK.2. Invoke ```pip install -r test-requirements.txt```3. Invoke ```nosetests```How to use:===========After having resolved the dependencies, you can easily use the SDK following these steps.1. Create a "wlufqksjez_test.py" file in the root directory.2. Use any controller as follows:```pythonfrom __future__ import print_functionfrom wlufqksjez.wlufqksjez_client import WlufqksjezClientapi_client = WlufqksjezClient()controller = api_client.clientresponse = controller.get_basic_auth_test(<required parameters if any>)print(response)```
Package: wmainfo-py
wmainfo-py is a library for reading low level information from files
encapsulated in an Advanced Systems Format header. Files of this type
typically have a .wma extension for audio only files and .wmv for video files.wmainfo-py can currently extract the following information:
* Content, size and offset of objects in the ASF_Header_Object
* Meta-tags from the ASF_Content_Description_Object
* Information from the ASF_File_Properties_Object (filesize, bitrate, creation
date etc)
* Additional tags/info from ASF_Extended_Content_Description_ObjectVersion 0.3 can parse Asf_Stream_Property_Object and Asf_Audio_Media objects
Package: wmapi
Python Client for Walmart Canada Marketplace APICurrently works for only Canada Marketplace.Before UsageYou have to get your consumer-id, channel-type and private-key information from:https://seller.walmart.ca/api-keyInstallationpip install wmapiUsageImport the packageimport wmapiCreate an API Class and request as below:items_api = wmapi.Items(client_id = '<your client id>', 
                        private_key='<private key>', 
                        channel_type='<channel type>')

result = items_api.get_all_items()MoreThis library is maintained byhttps://sellerzon.comPlease contact for further inquiries:help@sellerzon.com
Package: wmata
WMATAWMATA is an easy to use Python interface to theWashington Metropolitan Area Transit Authority API.ContentsRequirementsInstallationUsageGetting StartedDesignUsingMetroRailUsingMetroBusTestingDependenciesContactLicenseRequirementsPython 3.8InstallationpipinstallwmataUsageGetting StartedfromwmataimportMetroRail,Stationclient=MetroRail(api_key)trains=client.next_trains(Station["A01"])DesignWMATA breaks the WMATA API into two components:MetroRailandMetroBus.MetroRailProvides access to all MetroRail related endpoints.UsingMetroRailimportwmataclient=wmata.MetroRail(api_key)trains=client.next_trains(wmata.Station["A01"])MetroBusProvides access to all MetroBus related endpoints.UsingMetroBusfromwmataimportMetroBusclient=MetroBus(api_key)routes=client.routes()TestingRunpythonsetup.pytestTests use VCRpy to avoid network requests.DependenciesRequestsDev DependenciesVCRpyContactFeel free to email questions and comments toemma@emma.shLicenseWMATA is released under the MIT license.See LICENSEfor details.
Package: wmath
introduction'wmath' is a simple mathematical package designed by a bored undergraduate who wants to review math and python at the same time.features:wmath use a class called 'Meta' to manage the global meta information, which is not allowed to be instantiated.wmath has its own classFractionas one of its basic data types.param '_new' is a bool data, included in many methods in wmath, that decides whether to return a brand-new data or apply change on {self},'_deepcopy' is another common bool parameter, which decides whether deepcopy or just copy. in most cases,_deepcopyis True default.modulesmeta.py ------ manage the global meta information.number_theory.py ------ handling number theory problems in math.fraction.py ------ the operation in fraction.paradigm.py ------ the basic class of paradigm classes.polynomial.py ------ the related problems in polynomial.matrix.py ------ the problems related to matrix.cross.py ------ define cross functions that involve several classes.reference
Package: wmb-browser
wmb-browserWhole Mouse Brain BrowserGithub repository:https://github.com/lhqing/wmb-browser/Documentationhttps://lhqing.github.io/wmb-browser/Getting started with your projectFirst, create a repository on GitHub with the same name as this project, and then run the following commands:gitinit-bmain
gitadd.
gitcommit-m"init commit"gitremoteaddorigingit@github.com:lhqing/wmb-browser.git
gitpush-uoriginmainFinally, install the environment and the pre-commit hooks withmakeinstallYou are now ready to start development on your project! The CI/CD
pipeline will be triggered when you open a pull request, merge to main,
or when you create a new release.To finalize the set-up for publishing to PyPi or Artifactory, seehere.
For activating the automatic documentation with MkDocs, seehere.
To enable the code coverage reports, seehere.Releasing a new versionCreate an API Token onPypi.Add the API Token to your projects secrets with the namePYPI_TOKENby visitingthis page.Create anew releaseon Github.
Create a new tag in the form*.*.*.For more details, seehere.Repository initiated withfpgmaas/cookiecutter-poetry.
Package: wmbook
wmbookMachine Learning (Watermelon Book) 机器学习（西瓜书）GitHub:https://github.com/iOSDevLog/wmbookPyPI:https://travis-ci.org/iOSDevLog/wmbook代码规范.vscode/settings.json{"python.pythonPath":"/Users/iosdevlog/.Envs/wmbook/bin/python","python.linting.flake8Enabled":true,"python.formatting.provider":"yapf","python.linting.flake8Args":["--max-line-length=248"],"python.linting.pylintEnabled":false}字符串使用双引号：""安装pipinstallwmbook开发本地开发pip3install-e.测试pytest发布python3setup.pysdistbdist_wheel
twineuploaddist/*生成 CHANGELOGnpminstall-gconventional-changelog-cli
./version.sh联系方式网站:http://2019.iosdevlog.com/微信公众号: AI 开发日志Licensewmbook is released under the MIT license. SeeLICENSEfor details.
Package: wm.chimpimport
Why?mailchimpdoes not allow to import so called role addresses via the webinterface.soinfo@,support@,office@and the like can’t be imported but need to be inserted manually.
(seeWhat role addresses does MailChimp block)HOW?this script allows to import subscriptions even though some or all emails are role addresses
using the mailchimp APIMCAPI.typechimpimport--helpfor usage information:chimpimport imports datasets given in csv file FILENAME into mailchimp's subscriber list.

first row contains headers, EMAIL (note capital letters) column is required

example csv content:
"Some Value";"EMAIL";"Some other value";
"ACME Corp.";"john@acme.com";"Sales representative";



Options:
  -h, --help            show this help message and exit
  -u, --updateExisting  if given, existing subscribers will be updated
  -k APIKEY, --apikey=APIKEY
                        your mailchimp api key. to obtain one:
                        http://kb.mailchimp.com/article/where-can-i-find-my-api-key``StatusSuccessfully used for 1500 subscribers.Supports custom fields (just add headers for them to the import csv)Supports multiple subscriber list. If you have multiple lists, the script will prompt the list to import data into.Changelog1.2 (2012-10-08)existing subscribers get updated when importing with-uflaglogin() api method has been disabled (seeshutdown info)
so we change the help text on how to obtain an api keyrename README.txt to .rst for nice display on github1.1 (2011-11-12)added support for multiple lists (prompt user which one to choose)1.0 (2011-09-20)Initial release
Package: wmd
Fast Word Mover's DistanceCalculates Word Mover's Distance as described inFrom Word Embeddings To Document Distancesby Matt Kusner, Yu Sun, Nicholas Kolkin and Kilian Weinberger.The high level logic is written in Python, the low level functions related to
linear programming are offloaded to the bundled native extension. The native
extension can be built as a generic shared library not related to Python at all.Python 2.7 and older are not supported.The heavy-lifting is done bygoogle/or-tools.Installationpip3 install wmdTested on Linux and macOS.UsageYou should have the embeddings numpy array and the nbow model - that is,
every sample is a weighted set of items, and every item is embedded.importnumpyfromwmdimportWMDembeddings=numpy.array([[0.1,1],[1,0.1]],dtype=numpy.float32)nbow={"first":("#1",[0,1],numpy.array([1.5,0.5],dtype=numpy.float32)),"second":("#2",[0,1],numpy.array([0.75,0.15],dtype=numpy.float32))}calc=WMD(embeddings,nbow,vocabulary_min=2)print(calc.nearest_neighbors("first"))[('second', 0.10606599599123001)]embeddingsmust support__getitem__which returns an item by it's
identifier; particularly,numpy.ndarraymatches that interface.nbowmust be iterable - returns sample identifiers - and support__getitem__by those identifiers which returns tuples of length 3.
The first element is the human-readable name of the sample, the
second is an iterable with item identifiers and the third isnumpy.ndarraywith the corresponding weights. All numpy arrays must be float32. The return
format is the list of tuples with sample identifiers and relevancy
indices (lower the better).It is possible to use this package withspaCy:importspacyimportwmdnlp=spacy.load('en_core_web_md')nlp.add_pipe(wmd.WMD.SpacySimilarityHook(nlp),last=True)doc1=nlp("Politician speaks to the media in Illinois.")doc2=nlp("The president greets the press in Chicago.")print(doc1.similarity(doc2))Besides, see anotherexamplewhich finds similar Wikipedia
pages.Building from sourceEither build it as a Python package:pip3 install git+https://github.com/src-d/wmd-relaxor use CMake:git clone --recursive https://github.com/src-d/wmd-relax
cmake -D CMAKE_BUILD_TYPE=Release .
make -jPlease note the--recursiveflag forgit clone. This project uses source{d}'s
fork ofgoogle/or-toolsas the git submodule.TestsTests are intest.pyand use the stockunittestpackage.Documentationcd doc
make htmlThe files are indoc/doxyhtmlanddoc/htmldirectories.Contributions...are welcome! SeeCONTRIBUTINGandcode of conduct.LicenseApache 2.0README {#ignore_this_doxygen_anchor}
Package: wmf
___# wmf___Este es un modulo orientado al trabajo con cuencas hidrograficasy a la ejecucion de modelos hidrologicos, ademas contiene herramientasde vision de datos y analisis geomorfologico de cuencas.La manera de importar el modulo es:#!/usr/bin/env python>- from wmf import wmf## Modulos___Contiene modulos provenientes de fortran, compilados mediantegfortran e integrados a python mediante f2py.**cuencas**Contiene las herramientas para determinar la cuenca y variosparametros asociados a la misma, cuenta igualmente con herramientaspara determinar el cauce y algunas propiedades geomorfologicas.**modelos**Modulo orientado a la preparación y ejecución del modelo SHIA o bienmodelos que posteriormente se agreguen al sistema.## wmf.py___Reune todo el código y las funciones definicas en **cuencas**y en **modelos**## Instalación:___Para instalar el paquete se deben seguir los siguientes pasos:>1. Anclarse al repositorio: https://github.com/nicolas998/WMF.gito bien descargar el archivo **WMF-master.zip**.>2. En el caso de descargar el .zip este debe ser descomprimido,luego se debe mover la terminal hasta el directorio**cd ~/wmf**>3. se instala el paquete: **sudo python setup.py install**### Requerimientos:>- Compilador de fortran (gfortran probado).>- Python 2.7>- Sistema Unix (puede compilar en Windows con Cwing)>- Debe tener las siguiente dependencias de python.- numpy- glob- mpl_toolkits.basemap- netCDF4- osgeo- gdal- scipy- os- pandas- datetime- matplotlib
Package: wmf_umapi_client
umapi_client============Client wrapper for Wikipedia User Metrics API.See https://github.com/wikimedia/user_metrics for UMAPI implementation.Usage-----Set the ``UMAPI_USER`` and ``UMAPI_PASS`` in ``umapi_client/config.py``(copied from ``umapi_client/config.py.settings``).  Ensure that``call_client`` is executable and requests are invoked by simplycalling this script followed by the URL path and parameters of a request. Onlycached responses will return a response with JSON, otherwise the request willbe queued by the service.RFaulkner-WMF:umapi_client rfaulkner$ cd umapi_client/RFaulkner-WMF:umapi_client rfaulkner$ ./scripts/call_client "cohorts/\ryan_test_2/bytes_added"{"cohort": "ryan_test_2","group": "default","cohort_last_generated": "2013-03-19 07:43:26","aggregator": "None","metric": "bytes_added","namespace": [0],"project": "enwiki","time_of_response": "2013-03-19 07:43:32","datetime_start": "2010-10-25 08:00:00","datetime_end": "2011-01-01 00:00:00","header": ["user_id","bytes_added_net","bytes_added_absolute","bytes_added_pos","bytes_added_neg","edit_count"],"type": "raw","data": {"15972203": [683,1133,908,-225,5],"13234584": [0,0,0,0,0],"15972135": [0,0,0,0,0]},"interval_hours": 24,"t": 24}To save the contents to a file [-s] and timestamp the file [-t]:RFaulkner-WMF:umapi_client rfaulkner$ ./scripts/call_client "cohorts/\ryan_test_2/bytes_added" -s -tMar-29 12:47:33 DEBUG    __main__ :: Attempting to create cookie jar,logging in ..Mar-29 12:47:34 DEBUG    __main__ :: Login successful. Making request:http://metrics.wikimedia.org/cohorts/ryan_test_2/bytes_addedMar-29 12:47:35 DEBUG    __main__ :: Writing response to file:umapi_client_ryan_test_2_bytes_added_20130329.jsonRFaulkner-WMF:umapi_client rfaulkner$ cat umapi_client_ryan_test_2_bytes_\added_20130329.json{"cohort": "ryan_test_2","group": "default","cohort_last_generated": "2013-03-29 19:40:19","aggregator": "None","metric": "bytes_added","namespace": [0],"project": "enwiki","time_of_response": "2013-03-29 19:40:26","datetime_start": "2010-10-25 08:00:00","datetime_end": "2011-01-01 00:00:00","header": ["user_id","bytes_added_net","bytes_added_absolute","bytes_added_pos","bytes_added_neg","edit_count"],"type": "raw","data": {"15972203": [683,1133,908,-225,5],"13234584": [0,0,0,0,0],"15972135": [0,0,0,0,0]},"interval_hours": 24,"t": 24}To convert the output to csv:RFaulkner-WMF:scripts rfaulkner$ ./json2csv umapi_client_ryan_test_2_bytes_added_20130331.jsonMar-31 23:57:20 DEBUG    __main__ :: Attempting to read file...Mar-31 23:57:20 DEBUG    __main__ :: Writing to file...RFaulkner-WMF:scripts rfaulkner$ cat ../../csv/umapi_client_ryan_test_2_bytes_added_20130331.json.csvuser_id,bytes_added_net,bytes_added_absolute,bytes_added_pos,bytes_added_neg,edit_count13234584,0,0,0,0,015972203,683,1133,908,-225,515972135,0,0,0,0,0
Package: wmf_user_metrics
IntroductionThis package implements log retrieval, metrics generation, and data
analysis tools used by the Editor Engagement Experiment (E3) team at
the Wikimedia Foundation. The modules herein will be used to perform
the ETL and analysis operations necessary to process the experimental
data generated from E3 projects.Installationwmf_user_metricsis packaged with distutils:$ sudo pip install wmf_user_metricsOnce installed you will need to modify the configuration files.  This
can be found in the filesettings.pyunder$site-packages-home$/e3_analysis/config.  Within this file configure
the connections dictionary to point to a replicated production MySQL instance
containing the .  The ‘db’ setting should be an instance which ‘user’ has write
access to.  If you are from outside the Wikimedia Foundation and do not have
access to these credentials contact me atrfaulkner@wikimedi.orgif you’d
like to work with this package.The template configuration file looks like the following:# Project settings
# ================
__home__ = '/Users/rfaulkner/'
__project_home__ = ''.join([__home__, 'projects/E3_analysis/'])
__web_home__ = ''.join([__project_home__, 'web_interface/'])
__sql_home__ = ''.join([__project_home__, 'SQL/'])
__server_log_local_home__ = ''.join([__project_home__, 'logs/'])
__data_file_dir__ = ''.join([__project_home__, 'data/'])

__web_app_module__ = 'web_interface'
__system_user__ = 'rfaulk'

# Database connection settings
# ============================

connections = {
    'slave': {
        'user' : 'research',
        'host' : '127.0.0.1',
        'db' : 'staging',
        'passwd' : 'xxxx',
        'port' : 3307},
    'slave-2': {
        'user' : 'rfaulk',
        'host' : '127.0.0.1',
        'db' : 'rfaulk',
        'passwd' : 'xxxx',
        'port' : 3307}
}DocumentationOnce the installation is complete and the configuration has been set the
modules can be imported into the Python environment.  The available
operational modules are the following:src.etl.data_loader
src.etl.aggregator
src.etl.table_loader
src.etl.log_parser
src.etl.time_series_process_methods
src.etl.wpapi

src.metrics.blocks
src.metrics.bytes_added
src.metrics.live_account.pyc
src.metrics.edit_count
src.metrics.edit_rate
src.metrics.live_account
src.metrics.metrics_manager
src.metrics.namespace_of_edits
src.metrics.query_calls
src.metrics.revert_rate
src.metrics.survival
src.metrics.time_to_threshold
src.metrics.user_metric
src.metrics.users

src.utils.autovivification
src.utils.multiprocessing_wrapper
src.utils.record_typeMore complete docs can be found at:http://stat1.wikimedia.org/rfaulk/pydocs/_build/
Package: wm.gloeggele
Introductionwm.gloeggele installs a commandline script that parses the online menu ofhttp://www.gloeggele.comand
displays the menu of the day and the weekmenu:frisi@frisi-macbook:~/sandbox/wm.gloeggele$ gloeggele

Friday, 12/18/09
  Kartoffelsalat *** Vorarlberger Kaesspaetzle

Weekbeater
  Gemuesespaghettini mit Tomaten, Rucola und gehobeltem Parmesan EUR 8,50Installationeasy_install wm.gloeggeleshould add thegloeggeleexecutable directly to your environment path.Users of this script should add themselves toWe love s’GloeggeleFeedbackFor help or feedback feel free to contact me ;)Changelog1.2 (2009/12/18)added-aoption for displaying all menu items of the week at oncemore compact and readable representation of menuspep8 checkdepending on python2.5 (for datetime.strptime)removed dependency on elementtree (shipped with python2.5)1.1 (2009/11/11)fixed error in case no menu can be found for the current day1.0 (2009/10/01)Initial release
Package: wmgraph
wmgraph Microsoft Graph convenience libraryThis library aids with the Microsoft graph API for Office 365 business.
It uses certificates for the OAuth 2.0 client credentials flow to authenticate a daemon application registered in Azure AD.
This makes it suitable to be used in console applications.Configurationas described inA simple Python daemon console application calling Microsoft Graph with its own identity, client certificate variationRegister an application in Azure ADPrepare a config.json and certificates for a MS ApplicationUpload the server.crt to AADseeClient Credentials for AzureAD msalCreate Certificates:#!/bin/sh
openssl genrsa -out server.pem 2048
openssl req -new -key server.pem -out server.csr
openssl x509 -req -days 365 -in server.csr -signkey server.pem -out server.crt
openssl x509 -noout -fingerprint -sha1 -inform pem -in server.crt |sed -e 's=:==g' > server.fprconfig.json:{
    "authority": "https://login.microsoftonline.com/TENANT_ID",
    "client_id": "CLIENT_ID",
    "scope": [ "https://graph.microsoft.com/.default" ],
    "thumbprint": "SRERVER.CRT.FINGERPRINT",
    "private_key_file": "PATH_TO_CERTS(can be relative)/server.pem",
    "endpoint": "https://graph.microsoft.com/v1.0"
}Usageimportfromwmgraph.apiimportMgraphApifromwmgraph.api.exceptionsimportMgraphApiErrorconnectapi=MgraphApi(params='./config.json')useuserdata = api.get_user(args.user_id)orforuserinapi.list_users():print(user)`Development requirementstwine
wheel
Package: wm.help
Introductionwm.help provides infrastructure to add a help/documentation system to your plonesite
that is based on restructured text files.It registers a browser pageplone/@@helpthat lists all packages
that provide help/documentation and displays the resturctured text
rendered as html.wm.helpis a great way to provideup to datedocumentation on how to
complete certain tasks (eg manage images of the carousel on the front page)
to users of the portal.UsageIn your package create a directory that contains the documentation.One document is the index document that either contains all documentation or links to other documentation files.See wm.help.example for documentation on how to write your own help plugin.TODOSeasier plugin registrationregister resourceDir and docPackage automatically with the plugin(by providing a zcml directive similar to raptus.article.core.zcml)
this requires all rst files to reside directly in the package
the plugin is located in and all images to reside in a folder named img)fix regex for images to handle directives that use options toosupport for placeholders in links(eg.{{portal}},{{index}},{{plugin}}/my.plugin.name)use a separate permision to access helpChangelog0.1.1 (2014-09-01)Import plone.app.portlets to make sure permissionView Dashboardis
available.0.1 (2013-05-08)Initial release
Package: wmi-client-wrapper
# python-wmi-client-wrapperThis is a wrapper around wmi-client for Linux. Apparently the python-wmi moduleuses Windows APIs to access WMI, which isn't something that is going to work onLinux.## installing```pip install wmi-client-wrapper```## usage```import wmi_client_wrapper as wmiwmic = wmi.WmiClientWrapper(username="Administrator",password="password",host="192.168.1.149",)output = wmic.query("SELECT * FROM Win32_Processor")```## testing```nosetests```## licenseBSD
Package: wmi-client-wrapper-py3
python-wmi-client-wrapper (forked for Python3 support)This repo contains a fork frompython-wmi-client-wrapperbykanzure; the changes are roughly as follows:Add Python3 supportNaive approach, just usingfutureto do the hard work (boilerplate at top of each file for
compatibility layer)Add support fordomainparameter inWmiClientWrapperconstructorThanks toArminNaClfor the contribution!Bump version offutureto handleCVE-2022-40899Thanks toyotamc-msfor the contribution!To install this forked version:pip install wmi-client-wrapper-py3The rest of this README is verbatim of the original repo.This is a wrapper around wmi-client for Linux. Apparently the python-wmi module
uses Windows APIs to access WMI, which isn't something that is going to work on
Linux.installingpip install wmi-client-wrapperusageimport wmi_client_wrapper as wmi

wmic = wmi.WmiClientWrapper(
    username="Administrator",
    password="password",
    host="192.168.1.149",
)

output = wmic.query("SELECT * FROM Win32_Processor")

#get FibrePort Info
wmic = wmi.WmiClientWrapper(
    username="Administrator",
    password="password",
    host="192.168.1.1",
    namespace='//./root/WMI'
)
output = wmic.query('Select * FROM MSFC_FibrePortNPIVAttributes')testingnosetestslicenseBSD