Saravanan666/pypi-org huggingface dataset:
Package: turberfield-ipc
Turberfield is a framework for discrete event simulations and turn-based
games.It is developed by a private individual but released to the public under theGNU General Public License.This package provides an Inter-Process Communications (IPC) framework.RequirementsTurberfield runs on Python 3.5.1 or later. It requires these packages:turberfield-utilsUsageDownload and unpack the source distribution:$ tar -xzvf turberfield-ipc-0.013.0.tar.gz
$ cd turberfield-ipc-0.013.0Run the tests:$ python3.5 -m unittest discover turberfieldConsult the documentation:$ firefox turberfield/ipc/doc/html/index.htmlInstallation$ pip install turberfield-ipcRoadmapTurberfield is aSurPRISE.SemanticTurberfield can be understood by machines or human beings.PersistentTurberfield can be stopped and saved for later.ReusableTurberfield can be turned into something else.InteractiveTurberfield listens to what you say.SimulationTurberfield knows what it’s talking about.forEconomics…or Education, or Entertainment. Turberfield is deadly serious.
And only a game.What’s missing?UR!If you’ve spotted a bug in Turberfield, please let me know so I can fix it.If you think Turberfield lacks a feature, you can help drive development by describing
your Use Case.In either event, please leave a message on the project’smessage board.Author:tundishCopyright:2016 D Haynes
Package: turberfield-machina
Turberfield is aSurPRISE.SemanticTurberfield can be understood by machines or human beings.PersistentTurberfield can be stopped and saved for later.ReusableTurberfield can be turned into something else.InteractiveTurberfield listens to what you say.SimulationTurberfield knows what it’s talking about.forEconomics…or Education, or Entertainment. Turberfield is deadly serious.
And only a game.What’s missing?UR!If you’ve spotted a bug in Turberfield, please let me know so I can fix it.If you think Turberfield lacks a feature, you can help drive development by describing
your Use Case.In either event, please leave a message on the project’smessage board.RoadmapTurberfield’s mission is to provide a validated Pythonic framework for discrete
event simulations and turn-based games.It is developed by a private individual but released to the public under theGNU Affero General Public License.The API may change significantly as the project proceeds. At this early stage,
you should only use the latest release, which may not be compatible with
previous versions.RequirementsTurberfield requires Python 3.4. It usessetuptoolsfor installation.InstallationDownload and unpack the source distribution:$ tar -xzvf turberfield-machina-00.001.tar.gz
$ cd turberfield-machina-00.001Run the tests:$ python3.4 -m unittest discover turberfieldAuthor:tundishCopyright:2015 D Haynes
Package: turberfield-punchline
What worried me recentlyThere aren’t enough jokes on the web. I’d like to see more satire. Urgently.There is indeed, on the web a lot of poetry. But poetry web sites are not poetic places. Or even happy spaces.Also the traditions of personal web sites,web rings, andweb feedsare no longer common practice.
And I felt sad about that.What I did about itI wrotePunchline.Punchline is a static blogging framework. It treats your words as speech, and delivers them as dialogue with
measured timing. It supports multimedia too.Punchline was designed from the ground up to generateJSON Feed. So you can publish your blog as a feed
under the topics you choose.Usagepunchline [-h] [--config CONFIG] [--output OUTPUT] inputs [inputs ...]inputsOne or more search paths.-h,--helpShow a help message and exit.--configCONFIGSpecify a site configuration file.--outputOUTPUTSet directory for output.There is fulldocumentation online.
Package: turberfield-utils
Turberfield is a framework for discrete event simulations and turn-based
games.It is developed by a private individual but released to the public under theGNU General Public License.The API may change as the project proceeds. At this early stage you should
only use the latest release; it may not be compatible with previous
versions.RequirementsTurberfield runs on Python 3.4 or later.Some modules require atomic file renaming and named pipes (ie: a POSIX OS).UsageDownload and unpack the source distribution:$ tar -xzvf turberfield-utils-0.011.0.tar.gz
$ cd turberfield-utils-0.011.0Run the tests:$ python3.4 -m unittest discover turberfieldConsult the documentation:$ firefox turberfield/utils/doc/html/index.htmlInstallation$ pip install turberfield-utilsRoadmapTurberfield is aSurPRISE.SemanticTurberfield can be understood by machines or human beings.PersistentTurberfield can be stopped and saved for later.ReusableTurberfield can be turned into something else.InteractiveTurberfield listens to what you say.SimulationTurberfield knows what it’s talking about.forEconomics…or Education, or Entertainment. Turberfield is deadly serious.
And only a game.What’s missing?UR!If you’ve spotted a bug in Turberfield, please let me know so I can fix it.If you think Turberfield lacks a feature, you can help drive development by describing
your Use Case.In either event, please leave a message on the project’smessage board.Author:tundishCopyright:2015 D Haynes
Package: turbine
TurbineA Python 3 tool to harness the google cloud to run shell scripts. In particular, if you havea docker image andmany independent, idempotent tasks for that image written as shell scripts,Turbine allows you to run those tasks on many VMs in parallel on GCE. Seethis jupyter notebookfor detailed usage.Turbine is a lot likeGoogle Cloud Runexcept you don't need to hit an HTTP endpoint and it supports large machine types and accelerators;Google Cloud Functionsexcept it supports large machine types and accelerators; andBatch on GKEexcept I understand it, it is significantly lighter-weight than Kubernetes, and it provides a path for TPU access.InstallationTurbine consists of two components:A controller on the local machine to setup cloud components, enter tasks, and provision VMs.A small shim to run inside of the docker image and retrieve tasks.For most users, the recommended method to install the controller is via pip:pip install turbineTo attach turbine to a docker image, simply install turbine on the image via pip:RUN pip install turbineNote that theENTRYPOINTof the docker image will be overwritten when used by the Turbine controller.Dependencies:google-cloud-pubsubgoogle-cloud-storagegoogle-cloud-logginggoogle-api-python-clientSeerequirements.txtfor detailed version information, if needed.
Package: turbo
Turbois a web framework for fast building web site and RESTFul api, based on tornado, mongodb, redis.Easily scale up and maintainRapid development for RESTFul api and web siteDjango or flask application structureEasily customizableSimple ORM for mongodbLoggerSession(storage support for redis, disk and so on)support MongoDB, MySQL, PostgreSQL and so onsupport MongoDB asynchronous driverMotorGetting startedpipinstallturboturbo-adminstartproject<project_name>cd<project_name>/app-servertouch__test__pythonmain.pyDocumentationDocumentation and links to additional resources are available athttp://app-turbo.readthedocs.org
Package: turboactivate
Python integration for TurboActivatePython integration forLimeLM'sTurboActivate library. This lets you addhardware-locked licensing (a.k.a. node-locked licensing)to your Python app.UsageWe have a full example app and tutorial here:Using TurboActivate with PythonThat article shows you how to addnode-locked licensingto your app, addverified trialsto your app, and how to package your Python app for distribution.
Package: turbob64
Turbo Base64🚀 Lightning fast base64 encoding for Python✨ Features20-30x faster than the standard libraryBenchmarks faster than any other C base64 libraryFastest implementation of AVX, AVX2, and AVX512 base64 encodingNo other dependencies⚡ How fast is it?Graph generated frombenchmark.py:💻 Usage>>>importturbob64This will automatically detect the fastest algorithm your CPU is capable of and use it.Encoding>>>turbob64.b64encode(b'Hello World!')b'SGVsbG8gV29ybGQh'Decoding>>>turbob64.b64decode(b'SGVsbG8gV29ybGQh')b'Hello World!'Other FunctionsDirectly call CPU-specific algorithmsMemory efficient (small lookup tables) scalar but slower versionturbob64.b64senc(b'Hello World!')turbob64.b64sdec(b'SGVsbG8gV29ybGQh')Fast scalarturbob64.b64xenc(b'Hello World!')turbo64.b64xdec(b'SGVsbG8gV29ybGQh')ssse3 SIMDturbob64.b64v128enc(b'Hello World!')turbob64.b64v128dec(b'SGVsbG8gV29ybGQh')avx SIMDturbob64.b64v128aenc(b'Hello World!')turbob64.b64v128adec(b'SGVsbG8gV29ybGQh')avx2 SIMDturbob64.b64v256enc(b'Hello World!')turbob64.b64v256dec(b'SGVsbG8gV29ybGQh')avx2 SIMD (optimized for short strings)turbob64.b64v256enc_short(b'Hello World!')turbob64.b64v256dec_short(b'SGVsbG8gV29ybGQh')avx512_vbmi SIMDturbob64.b64v512enc(b'Hello World!')turbob64.b64v512dec(b'SGVsbG8gV29ybGQh')
Package: turbobit-api
Unofficial StreamTape API wrapperIt is a simple API wrapper for the streaming service streamtape.com. The API documentation can be found on thedocs page. The whole structure of the API has been split into different classes for easy overview and usage.InstallationInstall withpipinstallturbobit_apiUsageGeneral usageEvery class starts with following initialization:my_var=selectedClass()Ormy_var=selectedClass("API Key")VariablesPut in your environment variableTURBOBIT_APIlike you can see in .env fileAlternatively you can pass the key when class is initializedChangelog1.0.0Initial release
Package: turbobus
TurboBusTurboBus is an opinionated implementation of Command Responsibility Segregation pattern in python.Simple usageLet's see an example using python typings. You can omit all the typing stuffs if you want to.God Mode ⚡fromdataclassesimportdataclassfromtypingimportTypeAliasfromturbobus.commandimportCommand,CommandHandler,CommandBus,handler_offromturbobus.injectionimportinjectableLogHandlerType:TypeAlias="ILogHandler"@dataclassclassLogCommand(Command[LogHandlerType]):content:strclassILogHandler(CommandHandler[LogCommand,str]):...@handler_of(LogCommand)classLogHandler(ILogHandler):defexecute(self,cmd:LogCommand)->str:returncmd.contentif__name__=='__main__':bus=CommandBus()result=bus.execute(LogCommand('Hello dude!'))print(result)# Hello dudeHuman Mode 🥱fromdataclassesimportdataclassfromturbobus.commandimportCommand,CommandHandler,handler_offromturbobus.decoratorsimportinjectable@dataclassclassLogCommand(Command):contentclassILogHandler(CommandHandler):...@handler_of(LogCommand)classLogHandler(ILogHandler):defexecute(self,cmd:LogCommand)->str:returncmd.contentif__name__=='__main__':bus=CommandBus()result=bus.execute(LogCommand('Hello dude!'))print(result)# Hello dudeDependency injectionIn many cases we're going to need to inject dependencies to our command handler. To accomplish that we have two important tools:@injectable_ofdecorator andinjectfunction.With the@injectable_ofdecorator we can specify a class that is implementing the functionalities of the dependency. For example:fromturbobus.injectionimportinjectable_of,injectfromlog.axioma.logimportILoggerclassILogger(ABC):@abstractmethoddeflogger(self,text:str)->None:...@injectable_of(ILogger)classLogger:deflogger(self,text:str)->None:print(text)@command(LogCommand)@dataclass(kw_only=True)classLogHandler(ILogHandler):logger=inject(ILogger)defexecute(self,cmd:LogCommand)->str:self.logger.logger(cmd.content)returncmd.contentAs you can see in the example above, we're defining an abstract class with the logger method. Then we're doing the implementation of theILoggerand we're indicating that in the@injectable_of(ILogger).Then, using theinjectfunction, TurboBus is going to map that dependency and inject the instance in the attribute.
Package: turbocharge
TurboChargeOfficial Website :www.turbocharge.devA turbocharged way of installing all the packages you would ever want! Turbocharge automatically tests if the installed packages are working correctly for you on MacOS, Linux And Windows!AvaliabilityTurboCharge currently supports Windows, MacOS And Debian-Based Operating Systems.
It uses a backend of apt, snap, brew and chocolatey, giving you a seamless and enjoyable experience!InstallationTurbocharge can be installed using PyPI:
On Windows:pip install turbochargeOn MacOS And Linux:pip3 install turbochargeWarning: The below line of code is deprecated, and is not recommended:DocumentationInstall a package with TurboCharge usingturbo install <package_name>Install multiple packages with TurboCharge usingturbo install <package1,package2,package3>Uninstall a package with TurboCharge usingturbo remove <package_name>Uninstall multiple packages with TurboCharge usingturbo remove <package1,package2,package3>Note: Make sure that there is no space between each of the package names after and before the,.List all installable packages with TurboCharge usingturbo listList all installed packages with TurboCharge usingturbo localUpdate an installed package with TurboCharge usingturbo update <package_name>Search for a package avaliable in TurboCharge using:turbo search <keyword>Clean unnecesarry data from packages using TurboCharge withturbo cleanGet the current version of TurboCharge withturbo --version
Package: turbodbc
Turbodbc - Turbocharged database access for data scientists.Turbodbc is a Python module to access relational databases via theOpen Database Connectivity (ODBC)interface. Its primary target audience are data scientists
that use databases for which no efficient native Python drivers are available.For maximum compatibility, turbodbc complies with thePython Database API Specification 2.0 (PEP 249).
For maximum performance, turbodbc offers built-inNumPyandApache Arrowsupport
and internally relies on batched data transfer instead of single-record communication as
other popular ODBC modules do.Turbodbc is free to use (MIT license),
open source (GitHub),
works with Python 3.9+, and is available for Linux, macOS, and Windows.Turbodbc is routinely tested withMySQL,PostgreSQL,EXASOL,
andMSSQL, but probably also works with your database.Nice! Where can I find documentation?Follow this link to thelatest turbodbc documentation.
The documentation explains how to install and use turbodbc, and also provides
answers to many questions you might have.Is turbodbc on Twitter?Yes, it is! Just follow@turbodbcfor the latest turbodbc talk and news about related technologies.
Package: turbodif
turbodifOverviewThis is a python library that allows you to build the json format that is required to ingest external metrics intoTurbonomic's Data Ingestion Framework (DIF).  For more information about DIF, please visitturbonomic/data-ingestion-frameworkInstallationpipinstallturbodifUsageFor examples of usage, please seeturbonomic/data-ingestion-framework/example/azure-loganalytics/python
Package: turbo-docs
Turbo Docs 🚀Welcome to Turbo Docs, the cutting-edge documentation generator that empowers developers to create beautiful README files and manage their documentation with ease. Whether you're a user looking to generate your project's documentation, or a contributor aiming to enhance this tool, Turbo Docs is crafted to elevate your project's visibility and collaboration to the next level.Table of Contents 📑Turbo Docs 🚀Table of Contents 📑Installation 🛠️Usage ⚙️CommandsFeatures ✨Contributing 🤝License 📜Acknowledgements 🎉Installation 🛠️Before you can start using Turbo Docs, ensure you have Python installed on your system. Turbo Docs is compatible with Python 3.6 and above.You can install the latest release version from pypi:pipinstallturbo-docsInstall it directly for GitHub (not recommended) but sometimes useful:pipinstall"git+https://github.com/voynow/turbo-docs.git"Or clone the repository for local development:gitclonehttps://github.com/voynow/turbo-docs.git
poetryinstall--all-extrasUsage ⚙️Turbo Docs is designed with a simple command-line interface, making it a breeze to generate your README or copy documentation to your clipboard.CommandsGenerate README:To generate aREADME.mdfile, navigate to your project directory and run:turbo_docs--readmeThis command will generate aREADME.mdfile based on the contents of your current directory, excluding files specified in the.gitignore.Copy to Clipboard:If you want to copy the contents of your current directory's documentation to the clipboard, use:turbo_docs--copyThe text will be copied to the clipboard, and the number of tokens in the text will be displayed.Features ✨Markdown generation forREADME.mdpowered by OpenAI's language modelsClipboard support for easy text manipulationExclusion patterns to prevent certain files from being included in the documentation (supports.gitignorepatterns)Command-line interface for straightforward usageContributing 🤝Contributions are what make the open-source community such a fantastic place to learn, inspire, and create. Any contributions you make aregreatly appreciated.To contribute to Turbo Docs: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 RequestPlease make sure to update tests as appropriate.License 📜Distributed under the MIT License. SeeLICENSEfor more information.Acknowledgements 🎉OpenAI for the language models that power the documentation generationThe Python community for the invaluable libraries used in this projectGive your projects a boost with Turbo Docs and take your documentation to the next level! 🌟
Package: turboengine
===========Turboengine===========Google app engine utilities using some django's ideas.Install-------:git clone git://github.com/carlitux/turboengine.gitcd turboenginepython setup.py InstallUsage-----Create an setting.py file and can add variables settings as you want, butthis is some commons variables::TEMPLATE_PATH = 'templates'# setting DEBUGDEBUG = TrueSITE_TITLE = 'turboengine for GAE'# mapping (parent url, appname)INSTALLED_APPS = [(parent_url, appnane)] # app names shouldn't be standard python libraries and they should be importables into PYTHONPATHTEMPLATE_TAGS_PATHS = [] # not used but it will be used in feature for loading templatetagsERROR_PAGE_PATH = '/error/' # path where will be redirected the errorLOGIN_PATH_REDIRECT = '/'   # path where redirect after login or logoutPROFILE_PATH = '/account/profile/'To import settings do this:from turboengine.conf import settingsIf you want to implement an Website use this:from turboengine.http import RequestHandlerfrom turboengine.decorators import login_requiredclass MyHandler(RequestHandler):def get(self):# you can add headers or common usages of the requestuser = self.user # return authenticated user or None if is not logged in.... codeself.render_template(template, paramaters)@login_requireddef post(self):.... codeAnd use one file like (app.py)::from google.appengine.ext import webappfrom google.appengine.ext.webapp.util import run_wsgi_appfrom turboengine import urlsfrom turboengine.conf import settingsapplication = webapp.WSGIApplication(urls.generate_urls(settings.INSTALLED_APPS), debug=settings.DEBUG)def main():run_wsgi_app(application)if __name__ == "__main__":main()If you want to implement webservices first install ZSI and zope.interface then::from turboengine.webservices.application import SOAPAplicationfrom turboengine.webservices.application import WSGIAplicationfrom EchoServer_server import * # this class is generated by 'python wsdl2py SimpleEcho.wsdl' see http://carlitos-kyo.blogspot.com/2009/12/web-services-python-google-app-engine.html# Implementing servicesclass wsEchoServer(EchoServer):# Make WSDL available for HTTP GETwsdl = "".join(open('SimpleEcho.wsdl').readlines())disco = "".join(open('SimpleEcho.disco').readlines())def soap_Echo(self, ps, **kw):request, response = EchoServer.soap_Echo(self, ps, **kw)return request, requestdef main():application = WSGIApplication()application['EchoServer.asmx'] = SOAPAplication(wsEchoServer())#application['OtherServer.asmx'] = SOAPAplication(wsOtherServer()) # could have many webservicesrun_wsgi_app(application)if __name__ == '__main__':main()Please to see how to use webservices on GAE visit this:http://carlitos-kyo.blogspot.com/2009/12/web-services-python-google-app-engine.htmlTODO----Implement restful and templatetags
Package: turbofloat
Python integration for TurboFloatPython integration forLimeLM'sTurboFloat library. This lets you addfloating licensing (a.k.a. concurrent licensing)to your Python app.UsageWe have a full example app and tutorial here:Using TurboFloat with PythonThat article shows you how to addfloating licensingto your app and how to package your Python app for distribution.
Package: turbofunc
turbofunc2.0 INTRODUCED A BREAKING CHANGE TO standTextOut. FOR MORE INFO, SEE THE DOCS.Simple lines, for powerful functionsDocumentation can be found by doing this in the Python REPL:importturbofunchelp(turbofunc)Which will show you the available submodules. You can findtheirdocs with:importturbofunc.whateverhelp(turbofunc.whatever)For some credits, see source.md
Package: turbogpt
TurboGptA python based wrapper for GPT-4 & GPT-3.5 PLUS.Thank you for:Downloads!Benefits and why.There is currently no way to use GPT-4 outside the online chat.openai.com interface. This wrapper allows you to use GPT-4 in your own projects.the current API is extremely slow and even if you have premium it does not speed up the response time. TurboGpt does not use the API and instead uses the same interfaces as the chat.openai.com website.
This means that you can use GPT-4 and GPT-3.5 PLUS in your own projects without having to wait 20+ seconds for a response.InstallTo use GPT-4 you need to have a GPT PLUS subscription. If you don't, you can get onehere.pipinstallturbogptGetting the PUID & ACCESS_TOKENREMEMBER YOU NEED TO HAVE CHAT GPT PLUS SUBSCRIPTION TO USE THIS LIBRARY1. Head over to https://chat.openai.com/chat
2. Open the developer console (F12)
3. Go to the application tab
4. Go to local cookies
5. Copy the value of the _puid cookie
6. Go to the network tab and click on Fetch/XHR
7. hit refresh and locate the models request
8. Copy the value of the Authorization header after berear (ey....). (this is the ACCESS_TOKEN)
9. Paste the values into the .env file like so:

ACCESS_TOKEN=AUTHORIZATION HEADER
PUID=_puidUsageStart a new sessionfromturbogptimportTurboGptturbogpt=TurboGpt(model="gpt-4")# or "text-davinci-002-render-sha" (default)(AKA GPT-3.5)session=turbogpt.start_session()q=turbogpt.send_message(input(">>> "),session)print(q['message']['content']['parts'][0])Resume existing sessionfromturbogptimportTurboGptturbogpt=TurboGpt(model="gpt-4")# or "text-davinci-002-render-sha" (default)(AKA GPT-3.5)session=turbogpt.resume_session("uuid-uuid-uuid-uuid")q=turbogpt.send_message(input(">>> "),session)print(q['message']['content']['parts'][0])Info✅ - cloudflare bypassed
✅ - automatic refresh of _puid
✅ - GPT-4 Support
✅ - GPT-3.5 PLUS Support
✅ - GPT-3.5 Support (Free)
✅ - Fast
✅ - Easy to use
✅ - No API
✅ - No rate limits
✅ - No waiting
✅ - Back and forth conversation supportTurboGpt-CLICheck out a TurboGpt based CLIhere