Saravanan666/pypi-org huggingface dataset:
Package: python-vtonimat
vton-imaterialistA python package for Binary Segmentation DataSet ( vton_plus and imaterialist [topwear])📚 PyPi Project Documentation 📚Download datasetNote - This step can be performed after installing package as well.Download dataset from following drive and unzip it.gdriveInstall packageInstallation with pypipip3 install python-vtonimatInstallation from sourcegit clone https://github.com/aarti-b/vton-imaterialist
python3 setup.py installSet path to use package outside directoryexport PYTHONPATH="$PYTHONPATH:/path_to_github-clone-package/package/package/"Usage GuideThere are two datasets this package focuses onvtonimaterialistvton datasetdefault option for dataset isvton. Follow the following commands to load data. assign path value to the folder where data is downloaded and unzipped.Load whole datafrom vtonimat import SegData
images, labels = SegData(path='path_to_datafiles').load_training()Load batchwise datasetLoad by batches. Following command returns list of batches. Batch size is input parameter in methodload_training_in_batches.Load whole datafrom vton import SegData
images, labels = SegData().load_training_in_batches(1000)imaterialist'19 topwear datasetfrom vtonimat import SegData
images, labels = SegData(path='path_to_datafiles', dataset='imat19').load_training()Load batchwise datasetLoad by batches. Following command returns list of batches. Batch size is input parameter in methodload_training_in_batches.from vton import SegData
images, labels = SegData().load_training_in_batches(1000)There is a python fileconvert.pyto convert dataset to ubyte format the dataset you downloaded from google drive link. This file converts 3D images and 2D labels images to ubyte format.Usage to convert datapython3 convert.py train 0    #0 is ratio, which means whole data is converted to train. you can add proportions.
python3 convert.py test 0This package is still in progress. If you find any issue please feel free to contact or create a new issue. You are welcome to contribute in this project.
Package: python_vuejs
Gluing Python andVue.jswith a set of scripts that automate the dev and build process.Projects aims to be agnostic, just use it in order to automate the boring stuff to setup a Vue.js project.The point is: you start with SPA app inside your current project and then extract it without having the dependency
with backend framework, simply changing thenpmbuild scripts.Feel free to contribute with PRs and opening issues.Thanks!
Cheers! 🍻RequirementsPython 2.7+ or 3.4+nodejs > 5 and npm > 3Commands referencepython-vuejsis shipped with a nice cli built on top of click.:(env) $ pyvue --help
Usage: pyvue [OPTIONS] COMMAND [ARGS]...

Options:
--help  Show this message and exit.

Commands:
djangofy       Convert Vue.js webpack project into a django...
djbuild        Called inside `package.json`
djstartvueapp  Run click commands on bash.
installvuecli  Install vue-cli
startvueapp    Init vue project via vue-cli
vuebuild       Build Vue.js project via npm
vuecheck       Check if node > 5 and npm > 3 are installed
vuedev         Run frontend dev server via npmInstallationTo install python-vuejs, simply::$ pip install python-vuejsVue.js - A quick overviewWrappers aroundnpmandvue.
These commands automate the boring stuff of setup vue via vue-cli::$ pyvue startvueapp myapp
$ cd myapp
$ pyvue vuedev
...Before you go on production run::$ cd myapp
$ pyvue vuebuild
...Django - A quick overviewRunpyvue djstartvueappinto your django project directory:(env) $ pyvue djstartvueapp myapp
...
Enjoy!Command installs all dependencies and make themyappa django app.FeaturesVue.js starter via vue-cliDjango integrations with no dependenciesDetach backend and frontend with less effortTODOSupporting Flask, eghttps://github.com/taogeT/flask-vue(without js inside package)Supporting other frameworksCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: python-Wappalyzer
python-WappalyzerPython implementation of theWappalyzerweb application detection utility.Install$ python3 -m pip install python-WappalyzerUsagefromWappalyzerimportWappalyzer,WebPagewappalyzer=Wappalyzer.latest()webpage=WebPage.new_from_url('http://example.com')wappalyzer.analyze(webpage){'Docker', 'Azure CDN', 'Amazon Web Services', 'Amazon ECS'}wappalyzer.analyze_with_categories(webpage){'Amazon ECS': {'categories': ['IaaS']},  'Amazon Web Services': {'categories': ['PaaS']},  'Azure CDN': {'categories': ['CDN']},  'Docker': {'categories': ['Containers']}}webpage=WebPage.new_from_url('http://wordpress-example.com')wappalyzer.analyze_with_versions_and_categories(webpage){'Font Awesome': {'categories': ['Font scripts'], 'versions': ['5.4.2']},  'Google Font API': {'categories': ['Font scripts'], 'versions': []},  'MySQL': {'categories': ['Databases'], 'versions': []},  'Nginx': {'categories': ['Web servers', 'Reverse proxies'], 'versions': []},  'PHP': {'categories': ['Programming languages'], 'versions': ['5.6.40']},  'WordPress': {'categories': ['CMS', 'Blogs'], 'versions': ['5.4.2']},  'Yoast SEO': {'categories': ['SEO'], 'versions': ['14.6.1']}}Last version to support Python2 was0.2.2.
Package: python-watcher
OpenStack Watcher provides a flexible and scalable resource optimization
service for multi-tenant OpenStack-based clouds.
Watcher provides a robust framework to realize a wide range of cloud
optimization goals, including the reduction of data center
operating costs, increased system performance via intelligent virtual machine
migration, increased energy efficiency and more!Free software: Apache licenseWiki:https://wiki.openstack.org/wiki/WatcherSource:https://opendev.org/openstack/watcherBugs:https://bugs.launchpad.net/watcherDocumentation:https://docs.openstack.org/watcher/latest/Release notes:https://docs.openstack.org/releasenotes/watcher/Design specifications:https://specs.openstack.org/openstack/watcher-specs/
Package: python-watcher_metering
Watcher Metering collects system metrics and publishes them to a store.
To do so, it is composed of two elements:TheAgentwho collects the desired metrics and sends it to a publisher.
TheAgentis meant to run on each monitored host (container, VM, …)ThePublisherwho gathers measurements from one or more agent and pushes
them to the desired store. The currently supported stores areRiemann(for CEP), Ceilometer andRiemann.This project is part of theWatchersolution. For more information on Watcher, you can also refer to its OpenStackwikipage.You will another documentation here:ArchitectureInstallation guideAPIDevelopment guide
Package: python-watcher_metering_drivers
IntroductionWatcher Metering Drivers provides a set of metric-pulling drivers extending thepython-watcher_meteringpackage.Watcher Metering collects system metrics and publishes them to a store.
To do so, it is composed of two elements:TheAgentwho collects the desired metrics and sends it to a publisher.
TheAgentis meant to run on each monitored host (container, VM, …)ThePublisherwho gathers measurements from one or more agent and pushes
them to the desired store. The currently supported stores are Riemann
(for CEP) and Ceilometer.This package is part of theWatcherproject.For more information onWatcher, you can also refer to its OpenStackwikipage.Getting startedSystem requirementsAs this package extendspython-watcher_metering, please make sure you
installed its system dependencies before continuing.InstallationTo install this package, just usepip:$pipinstallpython-watcher_metering_driversActivate a driverWithin the your watcher metering configuration file, add the name of the driver
entry point you wish to enable.As an example, if you wish to acticate both thecpu_userand thedisk_freedrivers, just edit the aforementioned configuration file like
this:[agent]driver_names=cpu_user,disk_free# ...Running the applicationTo run our Watcher Metering agent, you can use the following commandDriver configurationTo configure a driver, you can specify it in a separate configuration file.
Please refer to the comments left within the$(ROOT_DIR)/etc/watcher-metering/watcher-metering-drivers.confsample to get more details on the
configuration options.Then, to run the agent using our driver configuration, you can use the
following command:$watcher-metering-agent\--config-file=$(WATCHER_METERING_AGENT_CONFIG_FILE)--config-file=$(WATCHER_METERING_DRIVERS_CONFIG_FILE)
Package: python-watcher_metering_grid5000
IntroductionWatcher Metering Grid5000 provides a set of metric-pulling drivers extending theWatcher Meteringproject which is used to collect system metrics from the
Grid5000 datacenters (seehttp://api.grid5000.fr) before publishing them to a given store.To sum up, Watcher Metering service is composed by 2 modules:TheAgentwho collects the desired metrics and sends it to a publisher.ThePublisherwho gathers measurements from one or more agent and pushes
them to the desired store.Drivers easily extend metrics collecting features of Agent (we usestevedorelibrary for managing plugins).This project is part of theWatcherproject.Getting startedInstallation: :doc:./doc/source/deploy/installation.rst
Package: python-watcher_metering_vsphere
========================Watcher Metering vSphere========================Introduction============Watcher Metering vSphere provides a set of metric-pulling drivers extending the`Watcher Metering`_ project which is used to collect system metrics from a`vSphere datacenter`_ before publishing them to a given store.To sum up, Watcher Metering service is composed by 2 modules:- The ``Agent`` who collects the desired metrics and sends it to a publisher.- The ``Publisher`` who gathers measurements from one or more agent and pushesthem to the desired store.Drivers easily extend metrics collecting features of Agent (we use `stevedore`_ library for managing plugins).This project is part of the Watcher_ project... _Watcher Metering: https://github.com/b-com/watcher-metering.. _Watcher: https://wiki.openstack.org/wiki/Watcher.. _stevedore: http://git.openstack.org/cgit/openstack/stevedore.. _vSphere datacenter: http://pubs.vmware.com/vsphere-60/index.jsp?topic=%2Fcom.vmware.wssdk.apiref.doc%2Fright-pane.htmlGetting started===============System requirements-------------------Watcher Metering packages must be installed before installing the drivers.Please follow the installation procedure of the `Watcher Metering`_ project first.Installation------------To install this package, just use *pip*:.. code-block:: shell# pip install python-watcher_metering_vsphereActivate a driver-----------------Within your Watcher Metering Agent configuration file ``/etc/watcher-metering/watcher-metering-agent.conf``,add the name of the driver entry point, in the ``[agent]`` section,  you wish to enable.As an example, if you wish to acticate both the ``vsphere_mem_usage`` and the``vsphere_cpu_usage`` drivers, just edit the aforementioned configuration file likethis:.. code-block:: ini[agent]driver_names =vsphere_mem_usage,vsphere_cpu_usageAfter updating the configuration file, you have to `restart the Watcher Metering Agent`_... _restart the Watcher Metering Agent: https://github.com/b-com/watcher-metering/blob/master/doc/source/deploy/installation.rst#commandDriver configuration====================To find out about the available drivers, please refer to the `vSphere drivers configuration`_ pageEach driver can be also configurable by adding a dedicated section named``[metrics_driver.driver_name]`` in a configuration file loaded by the WatcherMetering Agent. Such a file is self documented, so you will find in it alldriver configuration documentation.You will find a sample by editing the file `etc/watcher-metering-vsphere/watcher-metering-vsphere.conf.sample`_.. _vSphere drivers configuration: https://forge.b-com.com/www/indeed-ccl/doc/watcher-metering-vsphere/deploy/configuration.html.. _etc/watcher-metering/watcher-metering-vsphere.conf.sample: etc/watcher-metering/watcher-metering-vsphere.conf.sample
Package: python-wax
python-wax - hierarchical configuration format and context object for PythonQuick Example>>> from wax import Wax, parse_wax
>>> w = Wax(server=Wax(host='localhost'))
>>> w.server.port = 1234

>>> print 'hostname is %(server.host)s using port %(server.port)s' % w
hostname is localhost using port 1234

>>> s = str(w)
>>> print s

[server]
host = "localhost"
port = 1234

>>> w = parse_wax(s)
print w

[server]
host = "localhost"
port = 1234FeaturesContext objects can be serialized to / from stringSimple hierarchical key structureKey order is maintainedValues can be any JSON typeSupports comments and annotationsOverviewEasy to construct in code:>>> w = Wax(message='hello world', num=17)Access values with indexes:>>> w['num'] = 18>>> w.message = 'hello again'>>> w.get('missing.key', 'no problem')
'no problem'This object translates directly to a file format. Reading the format
will reconstruct the context object exactly. This allows for
“round-trip” configuration that can be serialized to utf-8, edited, and
read back in:>>> w = Wax(state='New York', zip=10003)
>>> s = str(w)
>>> print s
state = "New York"
zip = 10003

>>> q = parse_wax(s)
>>> print q
state = "New York"
zip = 10003Key order is preserved when keys are added individually. If you add them
in the constructor, initial order is governed by kwargs (dict) hashing
order:>>> w = Wax(a=1, b=2, c=3)
>>> print w
a = 1
c = 3
b = 2

>>> w = Wax()
>>> w.a = 1
>>> w.b = 2
>>> w.c = 3
>>> print w
a = 1
b = 2
c = 3Create sublevels by attaching a Wax instance to a key:>>> w = Wax(level1=Wax(level2=Wax(property='value')))>>> w = Wax()
>>> w.level1 = Wax()
>>> w.level1.level2 = Wax()
>>> w.level1.level2.property = 'value'Serializing this:>>> print w
[level1.level2]
property = "value"Or you can set dotted keys to create nested values:>>> w = Wax()
>>> w['foo.bar'] = 123
>>> print w.foo.bar
123Dotted access can be used in formatting strings:>>> w = Wax(server=Wax(host='localhost', port=1234))
>>> print 'hostname is %(server.host)s using port %(server.port)s' % w
hostname is localhost using port 1234
Package: python-weather
python-weatherA free and asynchronous weather Python API wrapper made in Python, for Python.Installation$pipinstallpython-weatherExampleFor more information, please read thedocumentation.# import the moduleimportpython_weatherimportasyncioimportosasyncdefgetweather():# declare the client. the measuring unit used defaults to the metric system (celcius, km/h, etc.)asyncwithpython_weather.Client(unit=python_weather.IMPERIAL)asclient:# fetch a weather forecast from a cityweather=awaitclient.get('New York')# returns the current day's forecast temperature (int)print(weather.current.temperature)# get the weather forecast for a few daysforforecastinweather.forecasts:print(forecast)# hourly forecastsforhourlyinforecast.hourly:print(f' -->{hourly!r}')if__name__=='__main__':# see https://stackoverflow.com/questions/45600579/asyncio-event-loop-is-closed-when-getting-loop# for more detailsifos.name=='nt':asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy())asyncio.run(getweather())
Package: python-weave
This is a standalone client for the Weave server API implemented in Python.It supports most of the User API and the read portions of the Sync API,
and has full support for decrypting encrypted browser object data.  Encryption
is not currently implemented.It depends on the M2Crypto module, which is currently hosted at:http://chandlerproject.org/Projects/MeTooCryptoM2Crypto is automatically installed in case you have Setuptools or Distribute
installed in your environment.Discussion and documentation for Weave is found at the Mozilla Wiki:http://wiki.mozilla.org/Labs/WeaveYou’ll also find information there on how to join Weave mailing lists,
file bugs for Weave, and so forth.Distutils layout created and package uploaded at PyPI by
Tarek Ziade <tarek@ziade.org>
Package: python-web-extras
Python Web ExtrasOfficial Documentation-https://tarsil.github.io/python_web_extras/Table of ContentsPython Web ExtrasTable of ContentsAbout Python Web ExtrasTortoise ORMOverviewSupported Django and Python VersionsInstallationDocumentation and SupportLicenseAbout Python Web ExtrasPython Web Extras is a miscellaneous of common utilities for FastAPI, Quart
and future integrations with other frameworks.The aim is to make the life of developers simpler when it comes to
some configurations.Python Web Extrasalso brings extra integrations withTortoise ORM.Tortoise offers a way of integrating models into any application without a lot
of configurations previously faced with others (SQLAlchemy, for instance) and for
those familiar withDjango, then Tortoise is a brise.Tortoise ORMWhen building an application that manages users, Django offers
an out of the box built-in User models that can be very useful within the
whole set of dependencies. Tortoise ORM is a bit less opinionated regarding those
and thereforePython Web Extrasoffers a similar abstraction based Django
where acreate_userandcreate_super_useras well as password
hashing are handled by simply inheriting from the base user model.OverviewSupported Django and Python VersionsPython3.83.93.10InstallationTo install python-web-extras:pipinstallpython-web-extrasDocumentation and SupportFull documentation for the project is available athttps://tarsil.github.io/python-web-extras/LicenseCopyright (c) 2022-present Tiago Silva and contributors under theMIT license.
Package: python-web-io
Python Web I/OGenerate a webpage as a GUI for a Python script, and serve from anywhere.DocumentationCheck out thewiki.QuickstartInstallpython-web-iolocally using:pipinstallpython-web-ioOr viapoetryusing:poetryaddpython_web_ioIf evaluating / testingpython-web-io, install dependencies for the example apps using:poetryaddpython_web_io--withexamplesAfter installing the project, some environment setup is required:Required setupCreate anapp.pyfile containing your script, aconfig.tomlsetting the script filepath and entrypoint, and an.envrcfile to store project secrets. (Note: remember to add.envrcto your.gitignore). Look for example apps in/examples..
├── .envrc
├── config.toml
└── app.pyCreate the following simpleconfig.toml:[script]filepath="app.py"entrypoint="main"# if your app has no entrypoint, remove this parameter.Add the following environment variables to your.envrc. (Note: remember to activate the.envrcin your terminal usingdirenv allow)# server env varsexportPYTHON_WEB_IO_SECRET=""exportPYTHON_WEB_IO_CONFIG=".pythonwebio/config.toml"# defaults to .pythonwebio/config.toml if not setGenerate a random key forPYTHON_WEB_IO_SECRETusing this python command line snippet:python-c'import secrets; print(secrets.token_hex())'If testingwikipedia_assistant.py, an OpenAI API key will also need to be set.exportOPENAI_API_KEY=""Running the webappWe recommend runningpython_web_iousinguvicorn:poetryrunuvicornpython_web_io.main:appLicenseMIT
Package: python-webnoti
Easy-to-use Python Web Push Notification LibraryInstallationInstall with pip:$pipinstallpython-webnotiUsageTo send a notification:fromwebnotiimportsend_notification,get_private_keysend_notification(subscription,"Hello from server")# For Firefoxsend_notification(subscription,"Hello from server",# For Chrome'mailto:admin@example.com',get_private_key('privkey.pem',generate=True))# subscription can be obtained from the client.To manually generate private key:fromwebnotiimportget_private_keyget_private_key('privkey.pem',b'password',generate=True)This will generate private key namedprivkey.pemwith passwordpassword(None if not encrypted) in current working directory.Check outpython-webnoti-examplefor the full example.
Package: python-webpack-boilerplate
Jump start frontend project bundled by WebpackDifference between django-webpack-loaderWhen usingdjango-webpack-loader, you need to createWebpackproject on your own, which is not easy for many newbie Django developers.python-webpack-boilerplatecan let you play with modern frontend tech in Django, even you have no idea how to config Webpack.FeaturesSupports Django and Flask(will support more framework in the future)Automatic multiple entry pointsAutomatic code splittingHot Module Replacement (HMR) (auto reload web page if you edit JS or SCSS)Easy to config and customizeES6 Support viababel(v7)JavaScript Linting viaeslintSCSS Support viasass-loaderAutoprefixing of browserspecific CSS rules viapostcssandpostcss-preset-envStyle Linting viastylelintIf you want to importlightweight modern frontend solutionto your web app, or you do not likeheavy frameworksuch as React, Vue.Please check my bookThe Definitive Guide to Hotwire and DjangoDocumentationSetup With DjangoSetup With FlaskFrontend WorkflowRaising fundsIf you like this project, please consider supporting my work.Open CollectiveSpecial ThanksDefinitive Guide to Django and Webpackdjango-webpack-loaderrails/webpackerwbkd/webpack-starter
Package: python-weewar
Weewar (http://weewar.com) is an “Award winning turn based multiplayer strategy
game”. Apart from being highly addictive, it provides 2 APIs:one read-only API for players anda bot API called ELIZAFurther documentation on both is available athttp://weewar.wikispaces.com/api.This module aims enables you to conveniently call each of these API functions
from within your python script.Available API callsThe following functions are supplied:game(id)returns the status of a game and gives information about the
participating players.open_games()returns all currently available open games as a list of IDs.all_users()returns a list of all users who have been online in the last
7 days, including their current ranking.user(username)Returns detailed information about a single user,
including everything that is visible on the profile page and the games the
user is participating in.latest_maps()returns the latest published maps including urls for
previews, images, and other details.headquarter(username, apikey)returns all games that are listed in your
Headquarters. Includes information about the id, the url, the state, and the
name of the game.  An attribute is added if the game is in need of attention,
e.g: its the users turn or the game is not yet started or the user is invited
to this game (requires authentication).game_state(username, apikey, id)offers more information about the state
of a game (requires authentication).map_layout(id)returns complete map layout.Each game can also be controlled via these commands (which are part of the
ELIZA API):finish_turn(username, apikey, id)finishes turn in game.accept_invitation(username, apikey, id)accepts invitation to a game.decline_invitation(username, apikey, id)declines invitation to a game.send_reminder(username, apikey, id)sends a reminder about the game.surrender_game(username, apikey, id)surrenders!abandon_game(username, apikey, id)abondons a game.remove_game(username, apikey, id)removes a game.chat(username, apikey, game_id, msg)sends a chat message to the game
board.build_unit(username, apikey, game_id, (x, y), unit)sends a chat message
to the game board.unit_move_options(username, apikey, game_id, unit, (x, y))requests unit
movement options. This is pretty much like what you get when you select a
unit in a regular game.unit_attack_options(username, apikey, game_id, unit, (x, y), moved=None)requests possible targets. The ‘moved’ attribute is optional and describes
the number of turns a unit has already moved. This is helpful for Jets and
Battleships.move_unit(username, apikey, game_id, unit, from, to)moves a unit.attack_with(username, apikey, game_id, unit, from, target)attacks target
with unit at specified location.capture_base(username, apikey, game_id, unit, at)captures a base with
unit.  You have to move there first!repair_unit(username, apikey, game_id, unit, at)repairs a unit.AuthenticationSome of the provided functions require a username and a password. Use your
Weewar account username and the API token accessible viahttp://weewar.com/apiToken.LicenseThe code for this module is released under the GNU LESSER GENERAL PUBLIC
LICENSE Version 3.