Saravanan666/pypi-org huggingface dataset:
Package: pytail-r3ap3rpy
WelcomeThis is a repository that holds my implementation of thetail -fcommand.In order to install it you can use either of these two ways.gitclonehttps://github.com/r3ap3rpy/pytailcdpytail
pythonsetup.pyinstallORpipinstallpytail-r3ap3rpyUsageSimply specify the file or filter to use the tool.╰─>$pytail--filetest.txt############################### Tailing file: test.txt# Use <CTRL + C> to exit##############################2024-02-1513:42:35.747232::line2024-02-1513:42:40.425967::another2024-02-1513:42:44.374841::yetanother############################### End of tailing!# Elapsed time: 15.93 second(s)!# Speed: 0.19 lps (lines per second)##############################NotesIf you install it in a virtualenv it will just work fine!On MacOS systems the module works fine.On linux systems if you install the module withsudoit will work fine, if you install it withoutsudoyou may have to issue the following command after install if you cannot find thepytailexecutable.exportPATH="$HOME/.local/bin:$PATH"On windows in case thepytailexecutable is not available after install you have to use the absolute path to use it.pythonC:\Python\Python310\Scripts\pytail--filetest.txtThere are two arguments:file (The file you want to tail!)filter (Optional, allows you to get only lines that contain the filter, case-insensitive!)ToDoCheck install issues!Add automatic version bump to workflowAdd permission check to see if user has the right to read the file!Change it to useargparseAdd versioningAdd switches
Package: pytailwindcss
Standalone Tailwind CSS CLI, installable via pipUseTailwind CSSwithoutNode.jsand install it via pip.WhyTailwind CSSis notoriously dependent onNode.js. If you're aPythondeveloper, this dependency may not be welcome
in your team, your Docker container, or your inner circle.TheTailwind CSSteam recently announced a new standalone CLI build that gives you the full power ofTailwind CLIin
a self-contained executable — noNode.jsornpmrequired.However, installing such a standalone CLI isn't as easy as runningnpm install, the installation command forNode.js.That's why I decided to make it as simple as runningpip installcommand. As a result you can install the standalone *
Tailwind CLI* viapipby running the following command:pipinstallpytailwindcssNow you can runtailwindcssin your terminal as:tailwindcss -i input.css -o output.css --minifyVoila!Get startedInstalltailwindcssviapipby executing the following command:pip install pytailwindcss[Optional] Preinstalltailwindcssbinary by running the following command:tailwindcss_installIf you skip this step, the binary will be downloaded on the first run oftailwindcsscommand.Thetailwindcsscommand should now be available in your terminal. Try to run it:tailwindcssIf the installation was successful, you should see the message about binary being downloaded on the first run. When download is complete, you should see the help output for thetailwindcsscommand. Usetailwindcssto create a new project or work with an existingTailwind CSSproject.Let's create a new project. Go to the directory where you want to host yourTailwind CSSproject and initialize it
by running:tailwindcss initThis command will create the defaulttailwind.config.jsfile.Start a watcher by running:tailwindcss -i input.css -o output.css --watchCompile and minify your CSS for production by running:tailwindcss -i input.css -o output.css --minifyYou got it. Please refer toofficial Tailwind documentationfor more information on
usingTailwind CSSand its CLI.CaveatsIt's not all roses, though. Giving upNode.jsmeans you won't be able to install plugins or additional dependencies for
yourTailwind CSSsetup. At the same time, that might not be a dealbreaker. You can still customizeTailwind CSSvia
thetailwind.config.jsfile. And the standalone build also comes with all officialTailwind CSSplugins
like@tailwindcss/aspect-ratio,@tailwindcss/forms,@tailwindcss/line-clamp, and@tailwindcss/typography. So in
90% ofTailwind CSSusage cases you should be covered, and the setup is so simplified now.Here is what theTailwind CSSteam says about going the standaloneTailwind CSSroute:If you’re working on a project where you don’t otherwise needNode.jsornpm, the standalone build can be a great choice. If Tailwind was the only reason you had a package.json file, this is probably going to feel like a nicer solution.Bugs and suggestionsIf you have found a bug, please use the issue tracker on GitHub.https://github.com/timonweb/pytailwindcss/issues2021 (c)Tim Kamanin - A Full Stack Django and Wagtail Developer
Package: pytaipit
aioTaipitA  Python API forTaipit cloud meters.InstallationUse pip to install the library:pip install aiotaipitUsagefrompprintimportpprintimportrequestsfrompytaipitimportSimpleTaipitAuth,TaipitApiasyncdefmain(username:str,password:str)->None:"""Create the aiohttp session and run the example."""withrequests.Session()assession:auth=SimpleTaipitAuth(username,password,session)api=TaipitApi(auth)meters=api.get_meters()pprint(meters)if__name__=="__main__":_username="<YOUR_USER_NAME>"_password="<YOUR_PASSWORD>"main(_username,_password)TheSimpleTaipitAuthclient also accept custom client ID and secret (this can be found by sniffing the client).This will return a price object that looks a little like this:[{'address':'Санкт-Петербург, Ворошилова, 2','category':0,'ecometerdata':{'P_aver':0.21986280758339,'P_averSmall':0.15261778589793,'P_averSmall_':109.88480584651,'P_aver_':158.30122146004,'P_aver_TF1':False,'P_aver_TF2':False,'P_aver_TF31':False,'P_aver_TF32':False,'P_aver_TF33':False,'P_norm':0.0066666666666667,'currentTS':1671485359,'ecoStatus':None,'lastReading':{'energy_a':1004.85,'energy_t1_a':794.45,'energy_t2_a':210.4,'energy_t3_a':0,'ts_tz':1671483628,'value':0.02},'meterCategory':0,'time':1671485359,'timezone':3,'trend':-48.41641561353,'trendTF1':False,'trendTF2':False},'id':2147485997,'isLowDataFreq':False,'isOwner':False,'isVirtual':0,'metername':'НЕВА МТ 114 (Wi-Fi) (22001110)','owner':{'peopleNumber':None,'type':0,'typeCode':'person'},'serialNumber':'22001110','usericopath':'/uploads/user/photo/3edba895933a54540fbdb88614f24f480a9eeb68.png','username':'Компания Тайпит','waterHot':False},{'address':'Санкт-Петербург, Ворошилова, 2','category':0,'ecometerdata':{'P_aver':0.25422232030182,'P_averSmall':0.2494024938596,'P_averSmall_':179.56979557891,'P_aver_':183.04007061731,'P_aver_TF1':False,'P_aver_TF2':False,'P_aver_TF31':False,'P_aver_TF32':False,'P_aver_TF33':False,'P_norm':0,'currentTS':1671485359,'ecoStatus':None,'lastReading':{'energy_a':11595.62,'energy_t1_a':10420.94,'energy_t2_a':1174.68,'energy_t3_a':0,'ts_tz':1671483641,'value':0},'meterCategory':0,'time':1671485359,'timezone':3,'trend':-3.4702750384005,'trendTF1':False,'trendTF2':False},'id':2147485996,'isLowDataFreq':False,'isOwner':False,'isVirtual':0,'metername':'НЕВА МТ 114 (Wi-Fi) (22001114)','owner':{'peopleNumber':None,'type':0,'typeCode':'person'},'serialNumber':'22001114','usericopath':'/uploads/user/photo/3edba895933a54540fbdb88614f24f480a9eeb68.png','username':'Компания Тайпит','waterHot':False}]
Package: pytak
Python Team Awareness Kit (PyTAK)PyTAK is a Python Module for creating TAK clients, servers & gateways.PyTAK includes:TAK Protocol support for interconnecting with ATAK, WinTAK, iTAK & TAK Server.Classes for handling TAK, Cursor on Target (CoT) & non-CoT data.Functions for parsing and serializing TAK & CoT data.Functions for sending and receiving TAK & CoT data over a network.DocumentationSeePyTAK documentationfor instructions on getting
started with PyTAK, examples, configuration & troubleshooting options.License & CopyrightCopyright Sensors & Signals LLChttps://www.snstac.comLicensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.asyncio_dgram is Copyright (c) 2019 Justin Bronder and is licensed under the MIT
License, see pytak/asyncio_dgram/LICENSE for details.
Package: pytakeout
https://github.com/idlesign/pytakeoutDescriptionSimplifies Python code extractionWith this you can easily:extract function/method/class source code;perform basic code transformations;save code into a file.Samplefrompytakeoutimportextract_code,code_to_filedeffunc_to_extract():# This function needs to be extracted.returnTrue# Extract code as a string.code=extract_code(func_to_extract)# Save it into a temporary file.tmp_code_file=code_to_file(code)
Package: pytale
PytaleOverviewThis library makes it easy to create tales that are told on the console.コンソール上で遊べるゲームを作る時に使える会話ライブラリです。Usage 1python onlyimportpytaleps=pytale.Scenario()ps.read("Hi.",sleep=1.5,speaker="King")player_name=ps.input("What your name?")hero_flag=ps.confirm(f"ok{player_name}, You wanna be a hero?")ifhero_flag:ps.read("Yes.",sleep=1.5,speaker=player_name)ps.read("\n-GAME CLEAR-")else:ps.read("\n-GAME OVER-")console[King]
Hi.
What's your name?
: hoge

ok hoge, You wanna be a hero?
choices: ['y', 'n']
: y

[hoge]
Yes.

-GAME CLEAR-Usage 2with json{"setting":{},"scenario":{"intro":[{"speaker":"King","text":"Hi.","sleep":1.5},{"type":"input","text":"What's your name?","var_name":"player_name"},{"type":"select","text":"ok {player_name}, You wanna be a hero?","choices":["y","n"],"var_name":"hero_flag"},{"type":"link","ref":"hero_flag","to":{"y":"yes","n":"no"}}],"yes":[{"speaker":"{player_name}","text":"Yes.","sleep":1.5},{"text":"\n-GAME CLEAR-"}],"no":[{"text":"\n-GAME OVER-"}]}}importpytaleps=pytale.Scenario("path/to/xxxxx.json")ps.read_chapter("intro")console[King]
Hi.
What's your name?
: hoge

ok hoge, You wanna be a hero?
choices: ['y', 'n']
: y

[hoge]
Yes.

-GAME CLEAR-Methodscoming soon ...version0.1.3 (Beta)Githubhttps://github.com/toripppppy/pytale
Package: pytalises
pyTALISESpyTALISES(This Ain't a LInear Schrödinger Equation Solver) is an easy-to-use Python implementation of the Split-Step Fourier Method, for numeric calculation of a wave function's time-propagation under the Schrödinger equation.FeaturesCalculation of a wavefunction's time propagation under a (non)linear Schrödinger equation:the wave-functionmay include an arbitrary number of internal and external degrees of freedomsimple implementation of Hamiltoniansspeed of theFFTW,BLASandnumexprlibaries with multithreadingcrucial functions are just-in-time compiled withnumbaDocumentationRead thedocumentationto learn more about pytalises' capabilities.
The documentation features many examples, among others2D harmonic potentials,BEC scattering,three-level Raman transitions,single-Bragg diffractionandatom interferometry.Installing pytalisesWe recommend installing pytalises via condaUsing condaInstallingpytalisesfrom theconda-forgechannel can be achieved by addingconda-forgeto your channels with:conda config --add channels conda-forgeOnce theconda-forgechannel has been enabled,pytalisescan be installed with:conda install pytalisesUsing pippytalises is available on the Python Package Index and can be installed viapip install pytalisesit has dependencies viascipyandnumbaon BLAS and LAPACK libraries that are not always found on windows systems. For linux they can usually be located.
Package: pytalite
Pytalite: Model-agnostic diagnostics and evaluation tool for Python and PysparkOverviewEvaluating model performance and diagnosing models are important steps in machine learning model development. Pytalite provides a straightforward wrapper for visualizing model performance and diagnosing machine learning models. It enables users to visualize key snapshots of model performance, e.g. discrete precision-recall curves, probability density plots, model-agnostic feature importance, partial dependence plots, accumulative local effect plots, and feature correlation plots.RequirementsPytalite for python is developed under python 3.7, but is compatible with python 2.7. Pytalite for pyspark is developed to support spark 2.0 and above.matplotlib ≥ 2.2.x (although 1.4.3 also works, higher version is recommended)numpy ≥ 1.9.xscipy ≥ 0.15.xmultiprocess ≥ 0.70.4Package StructureHighlightsPytalite provides the following model evaluation and diagnostic algorithms:Discrete Precision/Recall Plot (Binary-Classification only)Feature Correlation Plot (Binary-Classification only)Probability Density Plot (Binary-Classification only)Feature Importance Plot (Binary-Classification only)Accumulated Local Effect Plot (Binary-Classification / Regression, numerical feature)Partial Dependence Plot (Binary-Classification / Regression)ExamplesSeeexamplesfolder for usage examples.GalleryDiscrete Precision/Recall PlotFeature Importance PlotFeature ALE Plot for numerical features
Package: pytalker
============================================================
pytalker  Copyright (C) 2014  F. Brezo and Y. Rubio, i3visio
============================================================Description:pytalker is a python module designed to wrap the TTS capabilities of the
Google’s TTS service. It easily implements a wrapper for the Google TTS
service.License: GPLv3This is free software, and you are welcome to redistribute it under
certain conditions.This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.For more details on this issue, run:pythonpytalker-launcher.py--licenseInstallation:It requires the installation of gst libraries. You can check if you have
the library installed by typing:python-c"import gst"If no errors
where shown, you can go on with this tutorial. In any other case, try to
install this module manually. In Debian-like Linux distributions as
follows:sudoapt-getinstallpython-gst0.1The installation under Python 2.7 for the development package is as
follows having git installed:git clonehttp://github.com/i3visio/pytalkercd pytalker sudo python setup.py build sudo python setup.py installorwgethttp://github.com/i3visio/pytalker/archive/master.zipunzippytalker-master.zipcdpytalker-mastersudo python setup.py build sudo python setup.py installSuperuser privileges are required so as to complete the installation.
Afterwards, the module will be importable from any python code. You can
check this by typing:python-c"import pytalker"If no error is
displayed, the installation would have been performed correctly.Usage:So as to run the program, navigate to pytalker-master/pytalker and run:pythonpytalker-launcher.py-hThe usage is described as follows:usage:pytalker-launcher.py[-h]-l<language> [<language>...][-o<path_to_output_folder>]-t<text>                             [<text>...](-d|-s)[--version]The functionalities are described as follows: ``` optional arguments:
-h, –help show this help message and exit -d, –download Downloading
and playing the sound. -s, –say Playing the input text.Processing arguments: Configuring the processing parameters.-l [ …], –languages [ …] list of languages to be used. E. g.: en,
es, fr, etc. -o , –output_folder path to the output folder where the
results will be stored. -t [ …], –text [ …] text to be played
between commas.About arguments: Showing additional information about this program.–version shows the version of the program and exists.Note that the gst library should be installed on your system. In
Debian-like OS try: sudo apt-get install python-gst0.10 ```
Package: pytamaro
PyTamarois an educational library for Python designed to teach programming using graphics.📃 Background and Design PrinciplesThisSPLASH-E paperdescribes the design principles underpinning the library.✨ Examples and Online EnvironmentPyTamaro Webis an online platform that provides additional resources for PyTamaro.Run your Python programs with PyTamaro directly in the browser (without the need to create an account or install something on your computer!)100+ activities that showcase what is possible to create with PyTamaroA selection of curricula that guide you through a curated sequence of activities💻 InstallationAs simple aspipinstallpytamaroYou can install PyTamaro using Python 3.9 - 3.12 on all major operating systems and architectures.📚 DocumentationThe full documentation of the public API is available onReadTheDocs.🧑‍💻 ContributingIf you find what looks like a bug, pleasecreate an issueso that we can investigate.The development process, which contributors should follow, is described in theCONTRIBUTING.md file.
Package: pytamp
pytampOur paper named "Perturbation-Based Best Arm Identification for Efficient Task Planning with Monte-Carlo Tree Search", accepted to ICRA 2023.Python Interface for the robot task and motion planning(TAMP) library.
In the future, we are going to update it so that it can be operated in mujoco simulator.
We want to provide an environment for applying reinforcement learning in the robot domain.FeaturesPure python librarySupport only kinematic world, so not consider dynamics in this repoSupport simple motion planning (RRT* , PRM* , Cartesian planning)Render scene using matplotlib or trimesh.SceneSupport Robot Task and Motion Planning examples with MCTS in 4 benchmarksInstallationRequirementsYou needpygraphvizand python3-tk package to see a MCTS Tree.On Ubuntu 18.04 or 20.04, Download graphviz and graphviz-dev and python3-tk usingaptsudo apt install graphviz graphviz-dev python3-tkOn Mac, Download graphviz usingbrewbrew install graphvizInstall pytamppip install pytampUsage# Benchmark 1 with MCTS$shscripts/run_benchmark1.sh# Benchmark 2 with MCTS$shscripts/run_benchmark2.sh# Benchmark 3 with MCTS$shscripts/run_benchmark3.sh# Benchmark 4 with MCTS$shscripts/run_benchmark4.shIf you want to see the result of the output,  Run the benchmark#_result_level_2.ipynb file for that benchmark in theresultsdirectory.BenchmarkWe provide 4 benchmarks.We also show the results when using our algorithm.Benchmark1Benchmark2Benchmark3Benchmark4
Package: pytan3
PyTan: Python API for the Tanium PlatformPyTan is an all-in-one API wrapper forTaniumand is comprised of multiple modular layers that make it easy to extend or add new functionality.Since the inception of PyTan in October of 2014 it has grown in scope, complexity, and adoption. This version marks the fourth redesign, and it has vast improvements over the previous versions.PyTan is actively maintained on GitHub, where the code isalways available.Thedocumentation for PyTanis available online thanks toRead the Docs.InstallingInstalling PyTan viapiporpipenvwill automatically install all of the necessary dependencies.Install into the system site-packages using pip$ pip install pytan3Install into a virtual environment using pipenv$ pipenv install pytan3Clone the pytan3 repository using git$ git clone git://github.com/tanium/pytan3.gitDirectly from GitHubGet themaster branchwhich will always be the most recent stable release, or download a specific version from thereleases page.
Package: pytandem
PyTandemA multi-threaded event manager package for triggering methods in
tandem groups.InstallationRequirements- python>=3.6Install using PIPpython3 -m pip install --upgrade pytandemUsageFirst define the method(s) you would like to attach to the manager.def print_num(num):
  print(num)Then attach the method using the provided decorator - this will take an
event name as a paramaneter. It should look like so:from pytandem import pytandem

@pytandem.attach('event-name-here')
def print_num(num):
  print(num)Whenever the above method (print_num()) is called, instead of being fired
immediately it will be added to the manager threads to be started later on.Next we can fire the method a few times:for i in range(0, 3):
  print_num(i)You'll notice nothing gets printed yet.Now we can initiate the concurrent trigger of the 3 instances of the print_num()
method we added to the threads earlier using thetrigger()method - this, again,
takes the event name as a parameter.pytandem.trigger('event-name-here')We can run the methods synchronously also by passingFalsein thethreadedargument.
This is set to True by default.pytandem.trigger('event-name-here', threaded=False)And lastly, we can also set the maximum number of concurrent threads that pytandem
will use when triggering an event group. The default value for this is 4.pytandem.trigger('event-name-here', max_threads=16)Point to note: if max_threads is set to 4, and there are 20 methods attached on the
same event name, then only 4 will run concurrently until one pops off the queue,
essentially allowing the next in line to run. Methods will be fired according to
the order in which they were first attached.Note that a highmax_threadsvalue can cause out of memory issues if not careful.
Package: pytanga
Welcome to Pytanga’s documentation!Pytanga is a Python library that aims to simplify YANG payload creation, its architecture is based on the Composite and Visitor design patterns.Similar to YANG models where a container can have leaves and other containers, building a part-whole architecture. Pitanga modules define a component with attributes (leaves), and children that represent the inner containers of the module.For the data output, Pytanga implements a Visitor Pattern that is injected in each component and build the desired output, currently implemented only for NETCONF.With that architecture, it is possible to define the YANG models’ logic and syntax tests decoupled of the payload generation.Documentation link:https://pytanga.renatooliveira.eng.br/