Saravanan666/pypi-org huggingface dataset:
Package: warpdrive
Thewarpdriveproject provide the scripts for implementing a build and
deployment system for Python web applications using Docker. The scripts can
be integrated into a suitable Docker base image to provide a more
structured way for incorporating a Python web application into a Docker
image, withwarpdrivedoing all the hard work of co-ordinating the
build of the Docker image containing your application. Thewarpdrivescripts will also handle the startup of the Python web application when the
container is run.As well as basic support for working with Docker directly, thewarpdriveproject also providesassembleandrunscripts suitable for use
with theSource-to-Image(S2I) project. This allows a Docker image to be
enabled as a S2I builder for constructing Docker images for your
application without you needing to even know how to build Docker
containers. Any S2I enabled Docker image would also be able to be used as a
S2I builder with any Docker based PaaS with S2I support built in, such as
OpenShift.For additional documentation onwarpdriveincluding examples of use
see:http://warpdrive.readthedocs.ioFor examples of Docker images which incorporate thewarpdrivescripts
see:warp0-debian8-pythonwarp0-centos7-pythonIf you would like to trywarpdrivewith OpenShift, but would like to
use the default OpenShift Python images as a base, templates are provided
which use the standard Python images, but where the existing S2I scripts
will be overridden. To load these templates use the command:oc create -f https://raw.githubusercontent.com/GrahamDumpleton/warpdrive/master/openshift/warpdrive-python.jsonThis will create the following templates in OpenShift:warpdrive-python27
warpdrive-python33
warpdrive-python34
warpdrive-python35
Package: warped
warpedcan be used to execute single Python file and Python modules.
It captures calls to theargparsemodule of Python and renders a web
GUI based on the options and arguments defined. It also displays the
output of the program inside the web GUI and allows you to stop, pause
and resume the program, as well as downloading the output.InstallEither get a stable version from PyPI, or install the current version
from git# Installation from PyPI
pip install warped

# Installation from git
pip install git+https://git.k-fortytwo.de/christofsteel/warped/Usagewarped [-h] [--port PORT] [--host HOST] [--module] file

a Webbased frontend for ARgparse in Python

positional arguments:
file                  File to run

optional arguments:
-h, --help            show this help message and exit
--port PORT, -p PORT  The port to listen on (default 5000)
--host HOST           The host to bind to (default 0.0.0.0)
--module, -m          If set, loads a module instead of a fileSampleTo test the capabilities ofwarpedan example module was included.
You can run it like this:warped -m warped.samples.hookedSincewarpedalso makes use of the argparse module,warpeditself can be //warped//.warped -m warped.hookHow does it work?Whenwarpedis executed, it starts a flask webserver. The javascript
of the website reads the/argumentsresource of the server, where
the configuration of the argparser returned. In a seperate process the
given program is executed using therunpylibrary, redirectingsys.stdinandsys.stdoutto amultiprocessing.Queue, which
can be read by the warp process to display it via the web GUI.Additionally,warpedadds an entry forargparsein thesys.moduleslist. Python looks first looks at this list, everytime a
module is imported, to avoid importing a module multiple times. This
customargparsemodule behaves similar to the originalargparsemodule. In fact with the exception of theArgumentParser.parse_args()method, it works exactly like the
original. Once the program calls theparse_args()method, it blocks
and waits for user interaction via the web GUI. Once the user submits
the data, the process continues.
Package: warplol
A simple yet powerful SDK for warp.lolShort a URLfromwarplolimportWarpLolurl=WarpLol().Shortcut().getrandom(URL,full=True)print(url)URL is the url that you want to short, with or without https://.
Thefullargument is optional; withfull=True, full warp.lol URL is returned (https://warp.lol/BbSg); withfull=False, only the warp.lol redirect key is returned (BbSg).Get a custom redirect URLfromwarplolimportWarpLolurl=WarpLol().Shortcut().getcustom(URL,full=True,name="123abc")print(url)URL is the url that you want to short, with or without https://.
Thefullargument is optional; withfull=True, full warp.lol URL is returned (https://warp.lol/BbSg); withfull=False, only the warp.lol redirect key is returned (BbSg).nameis the custom shortcut URL (likehttps://warp.lol/123abc)Get shorted url redirectfromwarplolimportWarpLolurl=WarpLol.Shortcut().destination(URL)print(url)URLis the warp.lol URL. It can both be the full url (https://warp.lol/BbSg, with or without https://) or the last part (BbSg)
Package: warp-proxy
Simple http transparent proxy made in python 3.4This is proof-of-concept code.Dependencypython >= 3.4.0How to installYou can installwarpusingpip:$pipinstallwarp-proxyOr if you’re interested in bleeding edge of the master branch give it a try:$gitclonegit://github.com.devunt/warp.git$cdwarp/$pipinstall-e.How to userunwarpcommand (or you might need to runwarp.pyinstead
if setuptools isn’t installed in your system)$warpset browser’s proxy setting tohttp proxyhost: 127.0.0.1
port: 8800https proxyhost: 127.0.0.1
port: 8800
(https proxy is not recommended)???PROFIT!Command help$pythonwarp.py--helpLicenseMIT License (included inwarp.py)면책조항WARP를 사용함으로써 생기는 모든 책임은 사용자에게 있습니다.WARP의 코드 기여자들은 사용에 관한 책임을 지지 않습니다.Noticemay not work insome ISPssome company firewallssome school firewallssome browers (will fix it later)Special thanks topeecky (https://github.com/peecky) for lots of improvement code contributes.Young-Ho Cha (https://github.com/ycha) for randomize feed hostname code.Hong Minhee (https://github.com/dahlia) for python syntax and optparse implementaion.Park Jeongmin (https://github.com/pjm0616) for dummy header ideas.EJ Lee (https://github.com/hdformat) for firefox support code.Inseok Lee (https://github.com/dlunch) for english grammers :p
Package: warp-py
Warp! - Your lazy command line ssh helperManage your infrastructure, Never loose/forget passwords again.Key Features:One time setup, Initialize a local database to store all your infrastructure infomationSupports all Linux, Unix, MacOS systems as authentication is via sshRequirementspython3ConfigureVIA GITgit clone https://gitlab.com/adithya3494/warp && cd warp
  pip install -r requirements.txt
  python3 /path/to/warp.pyVIA PIPpip install warp-py
  python3 -m warp (or) warpMANUAL INSTALLgit clone https://gitlab.com/adithya3494/warp && cd warp
  python3 setup.py install
  python3 -m warpDisclaimerThis repository,Is Created to tackle my personal use-case.Is not production ready/safe.Is just a wrapper(quality-of-life improvements)of the existing details which you already have.Assumes you already have available connection for key-based auth and will not create/establish any.Will not take any responsibility of damage-dealt/passwords-leaks etc. It is assumed you are using this package in a controlled environment.ContributingBug reports and pull requests are welcome on GitHub atwarprepository.This project is intended to be a safe, welcoming space for collaboration and contributors are expected to adhere to theContributor Covenantcode of conduct.Fork it (https://gitlab.com/adithya3494/warp)Create your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create a new Pull RequestAuthorgh0s1-Owner-addy3494The project is available as open source under the terms of theMIT License
Package: warp-rna
PyTorch bindings for CUDA-Warp Recurrent Neural Alignerdefrna_loss(log_probs:torch.FloatTensor,labels:torch.IntTensor,frames_lengths:torch.IntTensor,labels_lengths:torch.IntTensor,average_frames:bool=False,reduction:Optional[AnyStr]=None,blank:int=0)->torch.Tensor:"""The CUDA-Warp Recurrent Neural Aligner loss.Args:log_probs (torch.FloatTensor): Input tensor with shape (N, T, U, V)where N is the minibatch size, T is the maximum number ofinput frames, U is the maximum number of output labels and V isthe vocabulary of labels (including the blank).labels (torch.IntTensor): Tensor with shape (N, U-1) representing thereference labels for all samples in the minibatch.frames_lengths (torch.IntTensor): Tensor with shape (N,) representing thenumber of frames for each sample in the minibatch.labels_lengths (torch.IntTensor): Tensor with shape (N,) representing thelength of the transcription for each sample in the minibatch.average_frames (bool, optional): Specifies whether the loss of eachsample should be divided by its number of frames.Default: False.reduction (string, optional): Specifies the type of reduction.Default: None.blank (int, optional): label used to represent the blank symbol.Default: 0."""RequirementsC++11 or C++14 compiler (tested with GCC 5.4).Python: 3.5, 3.6, 3.7 (tested with version 3.6).PyTorch>= 1.0.0 (tested with version 1.1.0).CUDA Toolkit(tested with version 10.0).InstallThe following setup instructions compile the package from the source code locally.From Pypipipinstallwarp_rnaFrom GitHubgitclonehttps://github.com/1ytic/warp-rnacdwarp-rna/pytorch_binding
pythonsetup.pyinstall
Package: warp-rnnt
PyTorch bindings for CUDA-Warp RNN-Transducerdefrnnt_loss(log_probs:torch.FloatTensor,labels:torch.IntTensor,frames_lengths:torch.IntTensor,labels_lengths:torch.IntTensor,average_frames:bool=False,reduction:Optional[AnyStr]=None,blank:int=0,gather:bool=False,fastemit_lambda:float=0.0,compact:bool=False)->torch.Tensor:"""The CUDA-Warp RNN-Transducer loss.Args:log_probs (torch.FloatTensor): Input tensor with shape (N, T, U, V)where N is the minibatch size, T is the maximum number ofinput frames, U is the maximum number of output labels and V isthe vocabulary of labels (including the blank).labels (torch.IntTensor): Tensor with shape (N, U-1) representing thereference labels for all samples in the minibatch.frames_lengths (torch.IntTensor): Tensor with shape (N,) representing thenumber of frames for each sample in the minibatch.labels_lengths (torch.IntTensor): Tensor with shape (N,) representing thelength of the transcription for each sample in the minibatch.average_frames (bool, optional): Specifies whether the loss of eachsample should be divided by its number of frames.Default: False.reduction (string, optional): Specifies the type of reduction.Default: None.blank (int, optional): label used to represent the blank symbol.Default: 0.gather (bool, optional): Reduce memory consumption.Default: False.fastemit_lambda (float, optional): FastEmit regularization(https://arxiv.org/abs/2010.11148).Default: 0.0.compact (bool, optional): Use compact layout, if True, shapes of inputs should be:log_probs: (STU, V)labels:    (SU, )where STU = sum(frames_lengths * (labels_lengths+1))SU  = sum(labels_lengths)"""RequirementsC++11 or C++14 compiler (tested with GCC 5.4).Python: 3.5, 3.6, 3.7 (tested with version 3.6).PyTorch>= 1.0.0 (tested with version 1.1.0).CUDA Toolkit(tested with version 10.0).InstallThe following setup instructions compile the package from the source code locally.From Pypipipinstallwarp_rnntFrom GitHubgitclonehttps://github.com/1ytic/warp-rnntcdwarp-rnnt/pytorch_binding
pythonsetup.pyinstallTestThere is a unittest which includes tests for arguments and outputs as well.python-mwarp_rnnt.test
Package: warpspeed-googlesearch-python
googlesearchgooglesearch is a Python library for searching Google, easily. googlesearch uses requests and BeautifulSoup4 to scrape Google.InstallationTo install, run the following command:python3-mpipinstallgooglesearch-pythonusageTo get results for a search term, simply use the search function in googlesearch. For example, to get results for "Google" in Google, just run the following program:fromgooglesearchimportsearchsearch("Google")Additional optionsgooglesearch supports a few additional options. By default, googlesearch returns 10 results. This can be changed. To get a 100 results on Google for example, run the following program.fromgooglesearchimportsearchsearch("Google",num_results=100)In addition, you can change the language google searches in. For example, to get results in French run the following program:fromgooglesearchimportsearchsearch("Google",lang="fr")googlesearch.searchgooglesearch.search(str:term,int:num_results=10,str:lang="en")->list
Package: warpwallet
# WarpWallet in pythonImplementation of WarpWallet in python. https://keybase.io/warp/Install the required packages running `pip install -r requirements.txt`## Usage** Import module **```import warpwallet```**Generate PrivateKey**`warpwallet.generate_keypair(passhprase [,salt])`example:```>>> import warpwallet>>> warpwallet.generate_keypair('YqIDBApDYME', salt='G34HqIgjrIc')'da009602a5781a8795d55c6e68a4b4d52969a75955ea70255869dd17c3398592'```**Generate [WIF](https://en.bitcoin.it/wiki/Wallet_import_format) key and Address**```import warpwalletprivate_key = warpwallet.generate_keypair("PuACRv0R")wif = warpwallet.privkey_to_wif(private_key)addr = warpwallet.key_to_addr(private_key)print "WIF: {}, Address: {}".format(wif, addr)```
Package: warpy
WARPYWarpyis a command-line program to getWARP+asWireGuardconfigurationIt requires the Python interpreter, version 3.5+, and it is not platform specific. It should work on your Unix box, on Windows or on macOS.INSTALLATIONTo install it right away for all UNIX users (Linux, macOS, etc.), type:pip3 install warpyHow to useBy using this, you agree thePrivacy PolicyandTerms of Serviceof Cloudflare 1.1.1.1To runwarpy, simply executepython3 -m warpyorwarpyin your terminal.FAQHow doeswarpyget WARP+ quota for free?It currently get quota by faking referrers since there is no way to pay for premium version outside of 1.1.1.1 app, but it is recommended to pay for it on your phone if you think their service is good.
Package: warrant-python
Warrant Python LibraryUseWarrantin Python projects.Installationpipinstallwarrant-pythonUsageimportwarrantwarrant.api_key="api_test_f5dsKVeYnVSLHGje44zAygqgqXiLJBICbFzCiAg1E="warrant.User.create()warrant.Tenant.create(id="dunder_mifflin")Configuring the API EndpointThe API endpoint the SDK makes requests to is configurable via thewarrant.api_endpointattribute:importwarrant# Set api endpoint to http://localhost:8000warrant.api_endpoint='http://localhost:8000'We’ve used a random API key in these code examples. Replace it with youractual publishable API keysto
test this code through your own Warrant account.For more information on how to use the Warrant API, please refer to theWarrant API reference.Note that we may release newminor and patchversions of this library with small but backwards-incompatible fixes to the type declarations. These changes will not affect Warrant itself.Warrant DocumentationWarrant Docs
Package: warren-api
Warren [API]Warren is a visualization platform for learning analytics.⚠️ This project is a Proof Of Concept not suitable for production yet. ⚠️ContributingThis project is intended to be community-driven, so please, do not hesitate to
get in touch if you have any question related to our implementation or design
decisions.We try to raise our code quality standards and expect contributors to follow
the recommandations from ourhandbook.LicenseThis work is released under the MIT License (seeLICENSE).
Package: warrenapp
Welcome to the Warren Lab's extension app forRequirementsThis extension is built off ofSimmate. In order to use it you must have the base Simmate package installed.Tutorials are at:https://jacksund.github.io/simmate/getting_started/overview/How to InstallIf you don't already have Simmate installed, follow the instructions toinstall Simmatecondacreate-nmy_env-cconda-forgepython=3.11simmate
condaactivatemy_env
simmatedatabaseresetInstall the warrenapp using pippipinstallwarrenappRegister the warrenapp with simmate by adding- warrenapp.apps.SimmateWarrenConfigto ~/Home/simmate/my_env-apps.yamlUpdate your database to include custom tables from the warrenappsimmatedatabaseupdate
Package: warriorframework
Warrior Framework is an open source automation framework designed to enable anyone to automate their testing,
processes, and repetitive tasks by simplifying the complex process of building an automation infrastructure.
As a keyword and data driven framework, Warrior’s infrastructure is built to maximize on re-usability of  built in keywords.Install:pip install warriorframeworkRequires:Python 3.6 and abovepexpect==4.8.0
requests==2.21.0
selenium==3.8.0
lxml==4.4.1
paramiko==2.7.2
pysnmp==4.4.12
pyvirtualdisplay==0.2.1
kafka-python==1.4.6
pycryptodome==3.6.1
cloudshell-automation-api==9.3.0.175525
xmltodict==0.12.0
xlrd==1.2.0
openpyxl==3.0.3
pandas==1.0.3
gcg==0.2.0
termcolor==1.1.0
pymongo==3.11.0Command Line Usage:Warrior -hLinks:Documentation:http://warriorframework.org/License      :http://www.apache.org/licenses/LICENSE-2.0Source       :https://github.com/warriorframework/warriorframework_py3
Package: warsawbuspy
Bus data readerThis package represents the functionality of reading and analyzing data fromhttps://api.um.warszawa.pl/#.Instalation:This package can be installed by calling:pip install warsawbuspyContents:This package contains four subpackages:1. readers:This subpackage contains a data_readers module, in which DataReader class is stored, that contains the functionality of
reading a various data from the API as well as writing it into the .csv files. This class requires an API key to access data from the API.
You can get it by making an account here:https://api.um.warszawa.pl/#.2. analyzers:This subpackage contains two modules:data_analyzer: this module contains the DataAnalyzer class that contains the functionality of retrieving
data fetched by the DataReader class from the .csv files as well as functionality of analyzing it. This class
also contains the functionality of storing results of the analysis into the .csv files.data_visualizer: this module contains the DataVisualizer class, that contains the functionality of
representing the results of the analysis as charts and maps.3. holders:This subpackage contains the module data_holders, in which are stored all classes used to store data
throughout the project.4. utility:This subpackage contains two modules:data_utility: this module contains utility functions used throughout the project.exceptions: this module contains custom exceptions raised in this project.APIs:This project utilizes two APIs:https://api.um.warszawa.pl: from here, all the data related to the city communication is fetched (bus locations,
schedules etc.)https://services.gugik.gov.pl: from here, the data about the street name for the given coordinates is fetched.Others:This project utilizes maps fromhttps://github.com/ppatrzyk/polska-geojson.
Package: warsaw-data-api
Pythonic way to use Warsaw data APIThis package allow to fetch data from API provided by "UM Warszawa" -https://api.um.warszawa.pl/Current featuresFetch ZTM buses and trams real-time locationFetch Schedule for bus stop for certain bus lineGetting StartedInstallationpip install warsaw-data-apiUsing ZTM moduleGet buses/trams locations:We can fetch all location data for buses:importwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')# you can get API KEY on the https://api.um.warszawa.pl/ after you registerbuses=ztm.get_buses_location()forbusinbuses:print(bus)We can do the same for trams, as a parameter we can set number of tram lineimportwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')trams=ztm.get_trams_location(line=17)fortramintrams:print(tram)Get buses schedule:We can fetch schedule by using bus stop id:importwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')schedule=ztm.get_bus_stop_schedule_by_id("7009","01","182")print(schedule.rides)or we can fetch it by using bus stop name:importwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')schedule=ztm.get_bus_stop_schedule_by_name("Marszałkowska","01","182")print(schedule.rides)if you would like to retrieve all buses for the bus stop you can use this:importwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')lines=ztm.get_lines_for_bus_stop_id("7009","01")print(lines)You can also retrieve bus stop id by passing bus stop name:importwarsaw_data_apiztm=warsaw_data_api.ztm(apikey='your_api_key')bus_stop_id=ztm.get_bus_stop_id_by_bus_stop_name("Marszałkowska")print(bus_stop_id)Passing API KeyWe can pass API Key in two different ways:Pass API Key to factory function (ztm()in this case) as a parameterztm = warsaw_data_api.ztm(apikey='your_api_key')Create environment variable calledWARSAW_DATA_API_KEY
Package: warthog
Warthog is a simple Python client for interacting with A10 load balancers. The target
use case is for safely removing servers from pools in a load balancer during a deployment.
It is available under the MIT license.FeaturesWaiting for servers to finish all requests when being disabledGraceful handling of transient errors with optional retry logicSupport for interacting with the load balancer API using SSLWorks with Python 2.6, 2.7, 3.3, 3.4, 3.5, 3.6+Thread safetyInstallationTo install Warthog, simply run:$pipinstallwarthogDependenciesrequestsby Kenneth Reitz, version 2.6 or higherclickby Armin Ronacher, version 3.3 or higherUsageUsing the client is easy!fromwarthog.apiimportWarthogClientdefinstall_my_project(server):passclient=WarthogClient('https://lb.example.com','user','password')client.disable_server('app1.example.com')install_my_project('app1.example.com')client.enable_server('app1.example.com')Seethe docsfor more information.DocumentationThe latest documentation is available athttps://warthog.readthedocs.io/en/latest/SourceThe source code is available athttps://github.com/smarter-travel-media/warthogDownloadPython packages are available athttps://pypi.python.org/pypi/warthogChangesThe change log is available athttps://warthog.readthedocs.io/en/latest/changes.html
Package: warzone-analysis
Call-Of-Duty-Warzone-AnalysisA package for analysis ofCall of Duty Warzonematches.Installationpip install warzone-analysisUsageimportwarzonefromwarzone.call_of_dutyimportCallofDutyuser_input_dict={'repo':'location of saved data','gamertag':'your Ganertag','squad':['squadmate1','squadmate2','etc'],'file_name':'Match_Data.csv'}cod=CallofDuty(user_input_dict=user_input_dict,squad_data=True,hacker_data=False,streamer_mode=False)
Package: wasabi2d
A fast, cutting-edge 2D game engine for Python.Current features include:Sprites, text, and stroked and filled polygons - all rotatable, scalable, and
colorizeableAcoroutine programming modelfor easy animated effects.Particle systemsBuilt-in post-processing effectsusing GLSL shaders.Sound, music and tone generation.Event driven input handlingfor keyboard and mouse.Animation/tweening."Local storage"to easily save state.Wasabi2D is based onmoderngl, withpygame 2.0for some supporting functions, and supporting APIs ported fromPygame Zero.Quick exampleDraw a drop-shadowed circle that follows the mouse:importwasabi2dasw2dscene=w2d.Scene()scene.background=0.9,0.9,1.0scene.layers[0].set_effect('dropshadow')circle=scene.layers[0].add_circle(radius=30,pos=(400,300),color='red',)@w2d.eventdefon_mouse_move(pos):circle.pos=posw2d.run()InstallationUse pip to install Wasabi2d from PyPI:pip install wasabi2dPlease make sure yourrequirements.txtpins a major version, as Wasabi2D may
continue to make breaking API and graphical changes in major versions.DocumentationDocumentation is available athttps://wasabi2d.readthedocs.io/ScreenshotsThis screenshot shows off polygons, sprites, text and particle effects:Roller Knightwas an entry in PyWeek 28, written with Wasabi2D by Daniel Pope and Larry Hastings:Spire of Chaoswas another entry in PyWeek 28 written with Wasabi2D by Daniel Moisset:
Package: wasabicli
WasabiCLICLI application for management of versioned Wasabi S3 buckets. This should also in theory work for AWS S3 buckets.Free software: GNU General Public License v3Documentation:https://wasabi-cli.readthedocs.io/en/latest/index.htmlFeaturesDelete only non-current objectsDelete both current and non-current objectsPurge delete markers from bucketDelete bucket (Runs all commands above to ensure bucket is empty before deletion)History1.0.0 (2023-03-07)First release on PyPI.