Saravanan666/pypi-org huggingface dataset:
Package: pi-door-buzz
pi-door-buzzA python package for door buzz detectionVisit Official documentation atpi-door-buzz.nikz.inPlatforms SupportedRaspberry PiLinuxMacOSHardware RequirementsRaspberry Pi (optional)Bread Board (optional)MicrophoneAudio Card (Needed for analog microphones with a jack)DependenciesPython 3.6+gpiozeroRPi.GPIOPyAudioPortAudio(Need to be installed manually)Audio Driver (Automatically loaded by OS after a restart)MunchUpcoming featuresAdding advanced door buzz detection algorithmsAdding support for automation platforms like Amazon Alexa, Google Home, IFTTT etc.Developmentgit clone https://github.com/nikhiljohn10/pi-door-buzz
cd pi-door-buzz
make help # Display the possible options availableVersion number is fetched frompidoorbuzz/__init__.pyPackage -/pidoorbuzzExamples -/exampleDocumentation -/docs/sourceTest Cases -/testGithub Actions -/.github/workflowsLicenseMIT License
Package: pidpromptify
FPromptifyInstallationYou can install FPromptify using pip. First, clone the repository and navigate to the project directory:pipinstallgit+https://github.com/hiendang7613/FPromptify.gitcdFPromptify
pipinstall-rrequirements.txtUsageTo use FPromptify, run the following command in your terminal:main.py--directory_path<path_to_dir>--mode<'CV'or'JD'>mode: This parameter allows you to choose between two modes: Named Entity Recognition on 'CV' for CV or 'JD' for Job Description labeling.path_to_dir: Specify the path to the directory containing your PDF data for NER or text data for JD labeling. ## default: 'data_dir/CV' or 'data_dir/JD'
Package: pidproxyd
A pidproxy for daemonized processes.Usagepidproxyd.py <pidfile name> <command> [<cmdarg1> …]There is an included Dockerfile for running the example.Installationpip install pidproxydCompatibilitypidproxyd is compatible with python 2.7 and python 3LicenceMITAuthorspidproxydwas written byAnfernee Jervis.
Thedaemon.pyscript is fromhttps://gist.github.com/marazmiki/3618191
Package: pidsim
WarningThis package just have the python modules, not any GUI.This package implements a basic toolbox for the study of the Control
Systems and the simulation of PID controllers, using Python.To use the examples, please initialize this package, using:>>> from pidsim.types import *
>>> from pidsim.discretization import *
>>> from pidsim.pid_simulation import *
>>> from pidsim.error import *If you need some help with the use, or can help with the development,
please contact the author via email or visit our project website:http://pidsim.org/All the help is welcome! :)Basic installationTo install, type:# python setup.py installor use pip:# pip install pidsimTo build doc (you’ll need sphinx), type:# make -C doc html
Package: pidsim-models
WarningThis package just have the python modules, not any GUI.This package implements a basic set of reference models for the simulation
of PID controllers, using PIDSIM.If you need some help with the use, or can help with the development,
please contact the author via email or visit our project website:http://pidsim.org/All the help is welcome! :)Basic installationTo install, type:# python setup.py installor use pip:# pip install pidsim-models
Package: pidtune
PID tuning toolIt includes some useful rules for PID controllers tuning and process identification, also it returns the close-loop simulations when the process incorporates delay/dead-time.Developer enviromentInstallvirtualenvvenvsourcevenv/bin/activate

pipinstall-rrequirements.txt
pipinstall-rrequirements-dev.txtRun tests## Alfaro123c an FOM validation testspytesttest/test.py
Package: pidx
pidxDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-npidx--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallpidxnbdev# activate conda environment$condaactivatepidx# make sure the pidx package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the pidx package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/pidx.gitor fromconda$condainstall-cdsm-72pidxor frompypi$pipinstallpidxDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.NumPy Documentation:np.DataSourcePyTorch Documentation:TorchDataHow to Package PyTorch
Modelstorch.monitor.Eventtorchvisiontorchvision.Datasets.VisionDatasettorchvision.utils.flow_to_imagePyTorch Models to Consider:Diffusion Video
AutoEncodersConvLSTM
AutoEncoderRecurrent All Pairs Field Transforms for Optical
FlowOptical Flow Toolbox
(mmflow)torchvision.models.optical_flow.raftChangelog: getdfidx getdfloc getdfiloc getdficatgetcatidx —> getcidx getaidx getiloc dfdsloc —> getloc getcats
getbiloc # dfdsiloccat2bidx —> wherecat cateqidxcats2bidx —> wherecats catseqidxgetcatiloc —> getciloc # getcatsiloc —^geticatidxiloc lociloc getloc —> getsub
Package: pieberry-library-assistant
PIEBERRY (IT’S FOR YOUR LIBRARY)This is a program which I wrote to automate a painful aspect of my
work-life - downloading, storing, cataloguing and referencing
documents from (mainly public sector & government) websites.These websites publish reams of documents in pdf format, usually in a
random range of cryptic CMS-generated filename schemas, with
incomplete or non-existent file metadata.Typically I download these, rename them with an intelligible title, a
six-digit archival date prefix, store then in an appropriate folder,
and enter them into my database of reference materials for use with
LaTeX/BibTex.Actually, scratch that. What I REALLY do is download them, leave them
on my Desktop folder, look at them once, forget them, fill up my disk
quota, delete them, realise I’ve lost them and download them all over
again.Hence, Pieberry, which will do all of the good and none of the bad
described above.It’s mainly for my use, but I hope that someone else will find it
useful. I’m open to requests for features.It’s written in Python, with the PortablePython 2.5.4 distribution
(which contains wxpython) in mind, but also requires Beautiful Soup,
pyPdf and Pybtex, which are all available through easy_install from
setuptools.
Package: piecash
Piecash provides a simple and pythonic interface to GnuCash files stored in SQL (sqlite3, Postgres and MySQL).Documentation:http://piecash.readthedocs.org.Gitter:https://gitter.im/sdementen/piecashGithub:https://github.com/sdementen/piecashPyPI:https://pypi.python.org/pypi/piecashIt is a pure python package, tested on python 3.6 to 3.9, that can be used as an alternative to:the official python bindings (as long as no advanced book modifications and/or engine calculations are needed).
This is specially useful on Windows where the official python bindings may be tricky to install or if you want to work with
python 3.XML parsing/reading of XML GnuCash files if you prefer python over XML/XLST manipulations.piecash test suite runs successfully on Windows and Linux on the three supported SQL backends (sqlite3, Postgres and MySQL).
piecash has also been successfully run on Android (sqlite3 backend) thanks to Kivy buildozer and python-for-android.It allows you to:open existing GnuCash documents and access all objects withinmodify objects or add new objects (accounts, transactions, prices, …)create new GnuCash documents from scratchScripts are also available to:export to ledger-cli format (http://www.ledger-cli.org/)export to QIF formatimport/export prices (CSV format)A simple example of a piecash script:withopen_book("example.gnucash")asbook:# get default currency of bookprint(book.default_currency)# ==> Commodity<CURRENCY:EUR># iterating over all splits in all books and print the transaction description:foraccinbook.accounts:forspinacc.splits:print(sp.transaction.description)The project has reached beta stage.ImportantIf you want to work with python 2.7/3.4 and books from gnucash 2.6.x series, you can use piecash 0.19.0.
Versions of piecash as of 1.0.0 supports python >=3.6 and books from gnucash 3.0.x series.WarningAlways do a backup of your gnucash file/DB before using piecash.Test first your script by opening your file in readonly mode (which is the default mode)
Package: piecelength
Piece LengthCalculate ideal piece length for .torrent files.Piece Length(piecelength) is a simple package that sole purpose is to calculate
the ideal piece length for the Bittorrent protocol based on the total size of
the torrent contents.  Results are returned in integer form, and will always
be a perfect power of 2.InstallThepiecelengthpackage can be installed from git:gitclonehttps://github.com/alexpdev/piecelength.gitcdpiecelength
pipinstall.It is also available on PyPi:pipinstallpiecelengthUsageTo use the package as library:frompiecelengthimportpiece_lengthsize=100000000# some integer valueresult=piece_length(size)It can also be used from the command line:piecelength3456677434645LicenseLicensed with BSD 3 see the LICENSE file for more details.
Package: piecemaker
The Jigsaw Piece MakerA jigsaw puzzle pieces generator that levels the playing field.It creates jigsaw puzzle pieces in multiple formats: svg, jpg, and png.  The
number and size of pieces are set by passing the script different options.  It
takes a while to run if doing a lot of pieces.  Extra JSON files are created
with details on size of pieces and adjacent pieces information which is commonly
used when verifying that two pieces can join together.Try out by running thepiecemaker.shscript that will prompt for necessary options
and run piecemaker inside a docker container. It will use the files in the examples
directory by default.# Build and run using docker./piecemaker.shInstallingRequires:Python Packages:Pillowpixsawbeautifulsoup4svgwritelxmlglue(Only partially included in
piecemaker source)Other Software needed:potraceIf on ubuntu or other debian based distroapt-get--yesinstalllibspatialindex6
apt-get--yesinstalloptipng
apt-get--yesinstallpython3-pil
apt-get--yesinstallpotracelibffi-devlibxml2-devpython3-lxmlpython3-xcffib
apt-get--yesinstalllibrsvg2-bin
apt-get--yesinstallpython3-pipInstall with pip in editable mode for developing and use virtualenv to isolate
python dependenciespython3-mvenv.venvsource.venv/bin/activate
pipinstall--upgrade--upgrade-strategyeager-e.UsageSee the script.py for more.  Not everything has been implemented. Use this
example command to create 100 randomly generated jigsaw puzzle pieces from
test.jpg image. This assumes that the 'test1' directory is empty since that is
where it will be placing all the generated files.  The test.jpg is the source
image that will be used when creating the pieces.  It is not modified.piecemaker--dirtest1--number-of-pieces100test.jpgExample of using an already existing svg file with jigsaw puzzle cut lines. The
'test2' directory should be empty as well. Note that the svg file
(test2-custom-cut-lines.svg) and the image (test.jpg) both need to be the same
width and height. Try this out by using a previously generated
'lines-resized.svg' from a different puzzle and a different image to create
a new puzzle with identical piece cuts.piecemaker--dirtest2--svgtest2-custom-cut-lines.svgtest.jpgContributingPlease contactJake Hickenlooperor create an issue.Any submitted changes to this project require the commits to be signed off with
thegit command option
'--signoff'.
This ensures that the committer has the rights to submit the changes under the
project's license and agrees to theDeveloper Certificate of
Origin.LicenseGNU Lesser General Public License v3.0MaintenanceWhere possible, an upkeep comment has been added to various parts of the source
code. These are known areas that will require updates over time to reduce
software rot. The upkeep comment follows this pattern to make it easier for
commands like grep to find these comments.Example UPKEEP comment has at least a 'due:' or 'label:' or 'interval:' value
surrounded by double quotes (").Example-> # UPKEEP due: "2022-12-14" label: "an example upkeep label" interval: "+4 months"Show only past due UPKEEP comments.makeupkeep
Package: pieceofcake
pieceofcake - a user-friendly cookiecutter wrapperThis is a wrapper around thecookiecuttertool which provides a more user-friendly way of asking questions.Withcookiecutter, the user is not presented with any questions, just the names
of the parameters to set:% cookiecutter gh:astrofrog/fake-template
package_name [example]: test-package
include_example_code [n]: yWithpieceofcake, the user is shown a series of verbose questions which provide
more context as to the meaning/implications of each parameter:% cookiecutter gh:astrofrog/fake-template final-package

Welcome to the pieceofcake, a user-friendly cookiecutter wrapper!

This script will now ask you a series of questions to help you set up
your package.

What is the name of your package? This is the name that will appear on
PyPI and which users will use when installing the package with e.g.
pip or conda.
> Package name [example]: test-package

Should example code be included? This will consist of sample Python
and Cython files in the package, demonstrating how to create different
sub-modules and importing between them.
> Include example code? [n]: y

Running cookiecutter...

You should now be all set! Your generated package is in final-packageInstallingTo install, run:pip install pieceofcakeUsingTo usepieceofcake:pieceofcake template output_directorywheretemplatefollows the same syntax as for cookiecutter, and can be
the path to a local directory, or e.g. gh:astrofrog/fake-template to use
a GitHub repository.Note thatpieceofcakewill work with all cookiecutter templates, but
nice questions will only be shown if thecookiecutter.jsonfile contains
the_parameterskey as described below inFor template creators.For template creatorsTo define questions for each parameter, add a new_parameterskey in
yourcookiecutter.jsonfile, which should then contain a dictionary for
each parameter:"_parameters": {
    "package_name": {
        "default_value": "test-package",
        "prompt": "Package name",
        "help": "What is the name of your package? This is the name that will appear on PyPI and which users will use when installing the package with e.g. pip or conda."
    },
    "include_example_code": {
        "prompt": "Include example code?",
        "help": "Should example code be included? This will consist of sample Python and Cython files in the package, demonstrating how to create different sub-modules and importing between them."
    }
}Thedefault_value,prompt, andhelpkeys are all optional - ifdefault_valueis not defined, the default value is taken from the maincookiecuttersection. Ifpromptis not included, it is set to the
parameter name, and ifhelpis not included, no help/question is shown.This approach was inspired bycookiecutter/cookiecutter#794
Package: piece-table
About piece_tableEarly implementation of the piece table data structure in Python.A piece table is an efficient data structure to represent a series of edits to a text document. A more detailed discussion can be foundhere. Inspired by the JavaScriptimplementation.InstallationTo install the package, run the following:pipinstallpiece-tableUsageCurrent usage is very basic, but will hopefully improve in the future.Basic use is demonstrated below.frompiece_tableimportPieceTabledocument=PieceTable("Initialize a document with some text.")document.insert("Add some text to the start of the document. ",0)# Delete the inserted textdocument.delete(0,44)text_sequence=document.get_text()# text_sequence == "Initialize a document with some text."sub_string=document[13:21]# sub_string == "document"TestingTo test the package, run the following:python-munittestdiscover-stests
Package: piecewise
PiecewiseWhat is Piecewise?A Michigan-style Learning Classifier System (LCS) library, written in Python.It makes heavy use of object-oriented language features to provide a modular,
extensible framework on which to build LCS algorithms.The currently implemented algorithms are:XCS (ternary rule representation)XCSR (centre-spread rule representation)Project PhilosophyThe primary use case of Piecewise is for LCS researchers who are interested in:Investigating modifications or extensions to existing LCS algorithms.Running experiments with LCS algorithms on common environments, through a
standardised and easy-to-use interface.
Package: piechartocr
pie-chart-ocrA tool to extract tabular data from pie charts, developed as a component of the CryptoSearchTools toolkit.Note: The original repository was moved tohttps://git.ehtec.co/research/pie-chart-ocr.https://github.com/ehtec/pie-chart-ocris a mirror.InstallationInstall via PyPiYou can install all tagged versions ofpiechartocrfrom PyPi:python3 -m pip install --upgrade piechartocrNote: You cannot run tests and examples from the PyPi installation. The required
files need to be downloaded from Gitlab.Build from sourceInstall Boost and Tesseract:sudo apt install libboost-system-dev tesseract-ocr build-essential gitClone this repository including submodules:git clone --recursive https://github.com/ehtec/pie-chart-ocr.git
cd pie-chart-ocrInstall Python requirements:python3 -m pip install -r requirements.txtCompile libraries:python3 setup.py build_extCreate temporary directories:mkdir temp
mkdir temp1
mkdir temp2Unpack test charts:unzip data/charts_steph.zip -d data
unzip data/charts_steph_upsampled.zip -d data
unzip data/generated_pie_charts_legend.zip -d data
unzip data/generated_pie_charts_without_legend.zip -d dataUsageRun unit tests:python3 -m nose2 --start-dir tests/ --with-coverageRun legacy tests / examples:python3 run_examples.pyGenerate test data (mock pie charts):python3 run_generate_test_data.pyTo extract data from any pie chart:frompiechartocrimportpie_chart_ocr# Path to pie chartpath="/path/to/my/chart.png"# Extract datadata=pie_chart_ocr.main(path,interactive=False)# Print the extracted list of tuples of the form [(percentage / 100, label)]print(data["res"])MetricsThese metrics are autogenerated by the CI-pipeline.Metrics for mock pie charts with legend:Metrics for mock pie charts without legend:Metrics for real world pie charts (many of them in awful quality, some even unreadable for humans):
Package: pie-cli
Pie - Powerful control versionA version controlwritten in Pythondesigned to be simple and complete, with many features. Animproved versionofVestory. With it, you can:Create repositories;Tracking files;Ignore files with.ignorefile;Get status of files;Commit of tracked files;Get all commits log;Merge all changes to the committed files;Get the changed lines between files;Creating hooks to execute scripts.To learn how to usePie, see thefull documentation here. InstallPieusing the pip package manager:pip install pie-cliLicenseThis project uses theGNU GPL v3.0license,see the license fileformore information.
Package: piecutter
#########piecutter#########.. raw:: html<a href="http://badge.fury.io/py/piecutter"><img src="https://badge.fury.io/py/piecutter.png"></a><a href="https://travis-ci.org/diecutter/piecutter"><img src="https://travis-ci.org/diecutter/piecutter.png?branch=master"></a><a href="https://crate.io/packages/piecutter?version=latest"><img src="https://pypip.in/d/piecutter/badge.png"></a>`piecutter` is a template rendering framework, written in `Python`_.Leitmotiv: **render templates against context**, wherever the templates,whatever the template engine.**************Project status**************`piecutter` is under active development.**Yesterday**, `piecutter` was the core of `diecutter`_.As `diecutter`'s authors, we think `diecutter` has great features related totemplates and file generation. We wanted to share it with a larger audience.So we just packaged it as a standalone library.And we are planning to make it better as soon as possible.`Join us`_ if you like the features ;)Here are some of our motivations:* third-party projects can use `piecutter`. They do not have to depend on`diecutter`, which embeds some specific code related to its web service.* as a standalone library, `piecutter` should be easier to maintain andimprove.* `piecutter` is more open than `diecutter`. It can have a larger community.It also may converge with similar tools.**Today**, `piecutter` is tied to `diecutter` implementation. The APIreflects `diecutter`'s architecture and concepts, which may sound obscure forother usage.**Tomorrow**, we are planning to improve `piecutter`. As an example, we thinkthe API should be refactored, with simplicity in mind.************Key features************* Simple API: render templates against context.* Support multiple template engines: `Jinja2`_ and `Django`_ for now. Later:`Cheetah`_ and even non-Python template engines such as Ruby's `ERB`_.* Render files and directories.* Load templates from almost everywhere: local filesystem and github.com fornow. Later: Django storages...* Do what you want with generated content: write to local filesystem, generatean archive...*********Resources********** Documentation: https://piecutter.readthedocs.org* PyPI page: http://pypi.python.org/pypi/piecutter* Bugtracker: https://github.com/diecutter/piecutter/issues* Changelog: https://piecutter.readthedocs.org/en/latest/about/changelog.html* Roadmap: https://github.com/diecutter/piecutter/issues/milestones* Code repository: https://github.com/diecutter/piecutter* Continuous integration: https://travis-ci.org/diecutter/piecutter.. _`Python`: https://python.org.. _`diecutter`: http://diecutter.io.. _`join us`: https://piecutter.readthedocs.org/en/latest/contributing.html.. _`Jinja2`: http://jinja.pocoo.org/.. _`Django`: https://djangoproject.com.. _`Cheetah`: http://pythonhosted.org/Cheetah/.. _`ERB`: http://ruby-doc.org/
Package: piedpy
Forever Scalablepiedpyis a Python based CLI toolkit for MySQL with auto-completion, key binders and syntax highlighting.Compatibilitypiedpy works flawlessly  with Linux, OSX, and Windows and requires Python3.8or later.FeaturesAuto-completionSyntax highlightingSmart-completion (enabled by default) will suggest context-sensitive completion.SELECT * FROM <tab>will only show table names.SELECT * FROM users WHERE <tab>will only show column names.Support for multiline queries.Favorite queries with optional positional parameters. Save a query using\fs alias queryand execute it with\f aliaswhenever you need.Timing of sql statements and table rendering.Config file is automatically created at~/.piedpyrcat first launch.Log every query and its results to a file (disabled by default).Pretty prints tabular data (with colors!)Support for SSL connectionsGetting StartedInstallationYou can install quo via the Python Package Index (PyPI)pip install -U piedpyUsagepiedpy --helpConfigurationFor more information on using and configuring piedpy,check out
our documentation.Donate🎁In order to for us to maintain this project and grow our community of contributors.DonateGetting HelpCommunityFor discussions about the usage, development, and the future of quo, please join our Google communityCommunity👨‍👩‍👦‍👦ResourcesBug trackerIf you have any suggestions, bug reports, or annoyances please report them
to our issue tracker atBug trackeror send an email to:📥secretum@googlegroups.comLicense📑This software is licensed under theMIT License. See theLicensefile in the top distribution directory for the full license text.Code of ConductCode of Conduct is adapted from the Contributor Covenant,
version 1.2.0 available atCode of Conduct