Saravanan666/pypi-org huggingface dataset:
Package: pipw
A wrapper for pip to save packages in requirements files similar to npm.There are better alternatives to pip (likePipenv), but this was created for
those who want or need to continue using pip. For example, those who
collaborate in projects that use pip requirements files.Installing$ pip install pipwUsagepipw (install|uninstall) [-e] <package>... [options]Options:-s, --save           Save packages to the requirements file. This is default
                     unless --no-save. Packages are saved in
                     requirements.txt unless a custom configuration is used.
-n, --no-save        Prevent save packages to the requirements file.
--config <path>      Pass a custom config file. By default it looks for a
                     .pipwrc file in the directory where the command is
                     executed, or in the user's home directory.
-m, --env <name>     Save in a environment previously declared in the config
                     file.
--save-to <path>     Save to a custom file.
--no-detect-version  Do not detect installed version, and save package
                     version only if the version is passed.
--help               Show this message and exit.All pip commands and options are still available.Config fileYou can create a.pipwrcfile to use a custom configuration. By default
it looks for the file in the directory where the command is executed, or in the
user’s home directory. You can also pass a custom file to the--configoption.Example of a config file:requirements:requirements.txtspecifier:~=detect_version:trueenvs:dev:requirements/dev.txtEnvironmentsAs you can see, you can set environment files in the configuration file:requirements:requirements/prod.txtenvs:dev:requirements/dev.txttest:requirements/test.txtUse the-m(or–env) option to save the packages in an environment file:$ pipw install pytest -m testIf no environment is passed, the value defined inrequirementsare used by
default. If this value is not defined, arequirements.txtfile is used by
default. These files are created automatically if they do not exist.Theuninstallcommand will remove the package in all files, unless the-moption is passed.TestsTests are intests/. To run the tests use one of these commands:$maketests$makewip-tests$makereview-testsYou can also pass the environment. For example:$maketestsenv=py35AuthorsDaniel Ramos
Package: pip-wheel-diff
pip-wheel-diffTable of ContentsInstallationLicenseInstallationpipx install pip-wheel-diffUsageImagine you have to review a pull request with a diff like this inrequirements.txt.How do you verify the change is what you expect?To answer this question, you can runpip-wheel-diffwith two pip requirements as
arguments. It will download or build the wheels, unzip them, clean them up a little bit
for comparability and run a diff tool to compare them.Example:pip-wheel-diff \"odoo-addon-stock-release-channel @ git+https://github.com/acsone/wms.git@ede1d6f9aa16cae535d650da3191bb6a6d86f793#subdirectory=setup/stock_release_channel" \"odoo-addon-stock-release-channel==16.0.2.6.5"It tries to find a diff tool in the following order:melddiff -rLicensepip-wheel-diffis distributed under the terms of theMITlicense.
Package: pipwin
pipwinis a complementary tool forpipon Windows.pipwininstalls
unofficial python package binaries for windows provided by Christoph Gohlke herehttp://www.lfd.uci.edu/~gohlke/pythonlibs/Version 0.2.X changes the structure of cache file. Make sure to run `pipwin refresh` if updated.QuickStart>> pip install pipwin
>> pipwin search cv

Did you mean any of these ?

  * cvxopt
  * opencv-python
  * abcview
  * cvxpy

>> pipwin install opencv-python

>> pipwin install numpy>=1.11DetailsOn first run,pipwinbuilds a cache of available package list in~/.pipwinYou can force a cache rebuild using :pipwin refreshList all available packages :pipwin listSearch packages :pipwin search <partial_name/name>Install packages :pipwin install <package>Also works version specifiers, e.g.pipwin install<package>==<version>orpipwin install<package><=<version>Download only (to~/pipwinor<dest>if provided) :pipwin download-d<dest> <package>Install from pipwin requirements file :pipwin install-rrequirements.txtDownload only from pipwin requirements file :pipwin download-rrequirements.txtUninstall packages (Can directly usepipfor this) :pipwin uninstall <package>Free software: BSD licenseChangelogv0.5.0Handles text vs string parsing for beautifulsoup4 for python2 vs python3.Fixes [issue 43](https://github.com/lepisma/pipwin/issues/43)v0.4.9More robust whitespace handling in requirement parsing.v0.4.8Using PySmartDL to handle download and install of packages.Removed progress bar and streaming downloader blocks now handled by PySmartDL.v0.4.7Using postman client type to overcome use of robobrowser to create package
cache.
Package: pip-Win
pip-Win is a tiny Python Package manager for Windows. It automatically installs pip and virtualenv.  Its GUI lets you:switch from one python interpreter (i.e. version) to another (including py and pypy)see all installed packages, and whether they are up-to-dateinstall or upgrade a packages, or upgrade pip itselfcreate and delete virtual environments, and switch between themrun the IDLE or another python script, with the selected interpreterSee the Home page for screen shot and user guide.
Package: pipwrap
pipwrap simplifies handling Python project requirements across multiple
environments. pip freeze > requirements.txt gets your project started,
but do you really want mock, coverage, etc. installed on your production
server? If you’ve ever found yourself sifting through the output of pip
freeze trying to figure out what packages you’ve installed but didn’t yet
add to one of your requirements files, then pipwrap is the tool for you.FeaturesCreate or update requirements files based on installed packagesRemove stray packages in virtualenvList discrepancies between installed packages and requirements filesInstallationYou can get pipwrap from PyPI with:pip install pipwrapThe development version can be installed with:pip install -e git://github.com/jessamynsmith/pipwrap.git#egg=pipwrapIf you are developing locally, your version can be installed from the
working directory with:python setup.py.installUsageNote: You may ignore warnings about “Recursive requirements not supported.” These
are due to current limitations of the requirements-parser library.Getting Started with pipwrap(Optional) Create requirements files with a list of your packagesInteractively populate requirements files from currently installed
packages:pipwrap -rCreate a top-level requirements.txt file that points to your
production requirements, e.g. “-r production.txt”Keeping requirements up to date with pipwrapInteractively update requirements files from currently installed
packages:pipwrap -r  # Adds packages in virtualenvpipwrap -rc  # Adds packages in virtualenv and removes packages not in virtualenvRemove stray packages in virtualenv:pipwrap -xSee discrepancies between installed packages and requirements files:pipwrap -lNOTE: This last option can be used to determine what the other options would do. Any packages
in the “Packages installed but not present in requirements” section would be uninstalled with
the -x option or added to requirements with the -r option. Any packages in the “Packages present
in requirements but not installed” section would be removed from the requirements files with the
-rc option.DevelopmentFork the project on github and git clone your fork, e.g.:git clone https://github.com/<username>/pipwrap.gitCreate a virtualenv and install dependencies:mkvirtualenv pipwrap
pip install -r requirements/package.txt -r requirements/test.txtRun tests with coverage (should be 100%) and check code style:coverage run -m nose
coverage report -m
flake8Verify all supported Python versions:pip install tox
toxInstall your local copy:python setup.py.install
Package: pipx-in-pipx
docsread-the-docslinuxstatic analysislinuxCPython 3.7windowsCPython 3.7pipxis great for keeping your CLI tools isolated and your system Python paths clean.
However, it still requires that you installpipxitselfin your system Python.Butpipxis a CLI tool installed throughpip…why not installpipxwithpipx?
Why not indeed!Withpipx-in-pipx, all you need to do is install :$pipinstallpipx-in-pipxBut wait! You say.
Didn’t you just say that we shouldn’t install things to system Python?Yes.
Whatpipx-in-pipxactually does is slightly (but only slightly) evil.
Rather than actually installing anything when you run “install”,pipx-in-pipxinstead builds a temporary virtual environment,
installspipxthere,
and then usesthatpipxto installpipxin your user local space,
just like any otherpipx-installed tool.What you end up with is apipxinstallation that isitselfmanaged bypipx.Sharp EdgesWhich Python?By default,pipxuses its own Python for each environment that it creates.
Normally, this would be the system Python, whatever it was when you installedpipx.
However, when your are using apipx-in-pipx-installedpipx,
the default Python thatpipxuses for each environment it creates is instead
whatever Python you used to “install”pipx-in-pipx.This has two notable side effects:If you uninstall yourpipx-managedpipx,
then all of the tools that you installed using thatpipxwill stop working
because their Pythons suddenly point to nothing.If you want to change the Python used by all of yourpipx-managed tools,
you only need to reinstall one of them (pipx) rather than reinstalling all of them.Uninstallingpipxhas a handy feature to uninstallallpipx-managed tools.
Because you have now madepipxmanage itself,
runningpipxuninstall-allwill alsouninstallpipx.This is not a bug, but a feature.
By installingpipxusingpipx-in-pipx,
you have expressed an intent that youwantpipxto manage itself.
If that’s not what you want, this is not the tool for you.If you at any point uninstall yourpipx-managedpipx,
you can simplypip installpipx-in-pipxagain to rebuild it.
Package: pipyadc
PiPyADCPython module for interfacing Texas Instruments ADS1255 and ADS1256
SPI bus based analog-to-digital converters with the Raspberry Pi.This is a Python-based implementation using the pigpio Python interface
to access the Raspberry Pi hardware through the pigpio system service.On a Raspberry Pi 3, multi-channel ADC reads require a time overhead in
the order of one millisecond per sample which makes this library suitable
for low-speed, high resolution data acquisition.As the ADS125x devices feature a sophisticated, configurable, hardware-based
down-sampling filter, there is no penalty in terms of accuracy.NEW in version 2:Uses the pigpio API instead of the deprecated wiringpi libraryUsing pgpio, the user scripts do not have to be run as root any moreWorking implementation for multiple ADS125x devices on the same SPI busProper configuration of unused chip-select line for the Waveshare exampleSince version 2.1:ADS1256 now supports the Python with statement by acting as a Context Manager,
allowing for automatic clean-up of SPI device and pigpio resources at exit.
(See waveshare_example.py)Many bug-fixes involving initialisation and clean-up and running multiple
devices on the same SPI busLimitation:Same as for version 1: This does not feature high-speed or low delaysDownload:https://github.com/ul-gh/PiPyADCDocumentation of pigpio library:https://abyz.me.uk/rpi/pigpio/python.htmlUses code from:https://github.com/heathsd/PyADS1256License: GNU LGPLv2.1, see:https://www.gnu.org/licenses/old-licenses/lgpl-2.1-standalone.htmlUlrich Lukas, 2022-08-30Run example on Raspberry Pi OS:Install:# numpy is optional for running the Isoflux hardware examples
sudo apt install python3-pip python3-numpy pigpio python3-pigpio git
pip3 install pipyadcEnable pigpio system service (started at boot)sudo systemctl enable pigpiod.serviceActivate SPI bus and reboot system# Using raspi-config or, alternatively, using following command:
sudo sed -E -i s/"(#)(dtparam=spi).*"/"\2=on"/ /boot/config.txt
sudo rebootRun example:git clone https://github.com/ul-gh/PiPyADC
cd PiPyADC/examples/waveshare_board
./waveshare_example.py
Package: piqa
PyTorch Image Quality AssessmentPIQA is a collection of PyTorch metrics for image quality assessment in various image processing tasks such as generation, denoising, super-resolution, interpolation, etc. It focuses on the efficiency, conciseness and understandability of its (sub-)modules, such that anyone can easily reuse and/or adapt them to its needs.PIQA should be pronouncedpika(like Pikachu ⚡️)InstallationThepiqapackage is available onPyPI, which means it is installable viapip.pip install piqaAlternatively, if you need the latest features, you can install it from the repository.pip install git+https://github.com/francois-rozet/piqaGetting startedInpiqa, each metric is associated to a class, child oftorch.nn.Module, which has to be instantiated to evaluate the metric. All metrics are differentiable and support CPU and GPU (CUDA).importtorchimportpiqa# PSNRx=torch.rand(5,3,256,256)y=torch.rand(5,3,256,256)psnr=piqa.PSNR()l=psnr(x,y)# SSIMx=torch.rand(5,3,256,256,requires_grad=True).cuda()y=torch.rand(5,3,256,256).cuda()ssim=piqa.SSIM().cuda()l=1-ssim(x,y)l.backward()Liketorch.nnbuilt-in components, these classes are based on functional definitions of the metrics, which are less user-friendly, but more versatile.frompiqa.ssimimportssimfrompiqa.utils.functionalimportgaussian_kernelkernel=gaussian_kernel(11,sigma=1.5).repeat(3,1,1)ss,cs=ssim(x,y,kernel=kernel)For more information, check out the documentation atpiqa.readthedocs.io.Available metricsClassRangeObjectiveYearMetricTV[0, ∞]/1937Total VariationPSNR[0, ∞]max/Peak Signal-to-Noise RatioSSIM[0, 1]max2004Structural SimilarityMS_SSIM[0, 1]max2004Multi-Scale Structural SimilarityLPIPS[0, ∞]min2018Learned Perceptual Image Patch SimilarityGMSD[0, ∞]min2013Gradient Magnitude Similarity DeviationMS_GMSD[0, ∞]min2017Multi-Scale Gradient Magnitude Similarity DeviationMDSI[0, ∞]min2016Mean Deviation Similarity IndexHaarPSI[0, 1]max2018Haar Perceptual Similarity IndexVSI[0, 1]max2014Visual Saliency-based IndexFSIM[0, 1]max2011Feature SimilarityFID[0, ∞]min2017Fréchet Inception DistanceTracingAll metrics ofpiqasupportPyTorch's tracing, which optimizes their execution, especially on GPU.ssim=piqa.SSIM().cuda()ssim_traced=torch.jit.trace(ssim,(x,y))l=1-ssim_traced(x,y)# should be faster ¯\_(ツ)_/¯AssertPIQA uses type assertions to raise meaningful messages when a metric doesn't receive an input of the expected type. This feature eases a lot early prototyping and debugging, but it might hurt a little the performances. If you need the absolute best performances, the assertions can be disabled with the Python flag-O. For example,python -O your_awesome_code_using_piqa.pyAlternatively, you can disable PIQA's type assertions within your code withpiqa.utils.set_debug(False)ContributingIf you have a question, an issue or would like to contribute, please read ourcontributing guidelines.
Package: piqel
An implementation of PartiQL written in RustDocument(WIP)Installationpip install piqelpoetry add piqelUsageimport piqel as pq

data = {
    "SHELL": "/bin/bash",
    "NAME": "my machine name",
    "PWD": "/home/fuyutarow/piqel",
    "LOGNAME": "fuyutarow",
    "HOME": "/home/fuyutarow",
    "LANG": "C.UTF-8",
    "USER": "fuyutarow",
    "HOSTTYPE": "x86_64",
    "_": "/usr/bin/env",
}
dl = pq.DataLake(data)
dl = dl.query("SELECT NAME, LOGNAME")
output = dl.to("json")
expected = """[{"NAME":"my machine name","LOGNAME":"fuyutarow"}]"""
assert output == expectedTestmakers test:pyFamilycontentlangpackagepqCLI (brew, scoop)piqelRust (cargo)https://crates.io/crates/piqelpiqel-jsJavaScript (npm)https://www.npmjs.com/package/piqelpiqel-pyPython (pip)https://pypi.org/project/piqel
Package: piqmp6988
# InstallingStable library from PyPi:Just runpip install piqmp6988# PiQmp6988’s Methods## Constructor(config={})‘config’ is dictionary type.### ‘address’Configure I2C address of QMP6988.Address.LOW.valueI2C address is 0x70DefaultAddress.HIGH.valueI2C address is 0x56### ‘filter’Configure Infinite Impulse Response(IIR) Filter coefficient of QMP6988.Filter.COEFFECT_OFF.valueDo not use IIR FilterDefaultFilter.COEFFECT_2.valueIIR filter coefficient is 2Filter.COEFFECT_4.valueIIR filter coefficient is 4Filter.COEFFECT_8.valueIIR filter coefficient is 8Filter.COEFFECT_16.valueIIR filter coefficient is 16Filter.COEFFECT_32.valueIIR filter coefficient is 32### ‘mode’Configure Power Mode of QMP6988.Powermode.SLEEP.valuePower Mode is SLEEPDefaultPowermode.FORCE.valuePower Mode is ForcePowermode.NORMAL.valuePower Mode is Normal### ‘pressure’Configure average times for pressure measurement of QMP6988.Oversampling.SKIP.valueDo not measure pressureDefaultOversampling.X1.valueSingle Shot valueOversampling.X2.valueAverage 2 times for mesurment valueOversampling.X4.valueAverage 4 times for mesurment valueOversampling.X8.valueAverage 8 times for mesurment valueOversampling.X16.valueAverage 16 times for mesurment valueOversampling.X32.valueAverage 32 times for mesurment valueOversampling.X64.valueAverage 64 times for mesurment value### ‘temperature’Configure average times for temperature measurement of QMP6988.Oversampling.SKIP.valueDo not measure temperatureUse 25.0 celsius value when ‘pressure’ measureDefaultOversampling.X1.valueSingle Shot valueOversampling.X2.valueAverage 2 times for mesurment valueOversampling.X4.valueAverage 4 times for mesurment valueOversampling.X8.valueAverage 8 times for mesurment valueOversampling.X16.valueAverage 16 times for mesurment valueOversampling.X32.valueAverage 32 times for mesurment valueOversampling.X64.valueAverage 64 times for mesurment value## read()Read temperature and pressure.
Return value is dictionary type.### ‘temperature’OKType: floatCelsius temperature value [℃]NGType: False### ‘pressure’OKType: floatAtmospheric pressure value [hPa]NGType: False# SampleRunsudo pigpiodbefore running the sample.## Indoor navigation (from QMP6988 Datasheet)# -*- coding: utf-8 -*-importpiqmp6988asQMP6988importtimeconfig={'temperature':QMP6988.Oversampling.X4.value,'pressure':QMP6988.Oversampling.X32.value,'filter':QMP6988.Filter.COEFFECT_32.value,'mode':QMP6988.Powermode.NORMAL.value}obj=QMP6988.PiQmp6988(config)try:whileTrue:value=obj.read()if(isinstance(value['temperature'],float)):print("%8.2f"%round(valueb['temperature'],2))if(isinstance(valueb['pressure'],float)):print("%8.2f"%round(valueb['pressure'],2))time.sleep(10)exceptKeyboardInterrupt:pass
Package: piqp
PIQPPIQP is a Proximal Interior Point Quadratic Programming solver, which can solve dense and sparse quadratic programs of the form$$
\begin{aligned}
\min_{x} \quad & \frac{1}{2} x^\top P x + c^\top x \
\text {s.t.}\quad & Ax=b, \
& Gx \leq h, \
& x_{lb} \leq x \leq x_{ub},
\end{aligned}
$$Combining an infeasible interior point method with the proximal method of multipliers, the algorithm can handle ill-conditioned convex QP problems without the need for linear independence of the constraints.FeaturesPIQP is written in header only C++ 14 leveraging theEigenlibrary for vectorized linear algebra.Dense and sparse problem formulations are supported. For small dense problems, vectorized instructions and cache locality can be exploited more efficiently.Interface to Python with many more to follow.Allocation free problem updates and re-solves.Open source under the BSD 2-Clause License.InterfacesPIQP support a wide range of interfaces includingC/C++ (with Eigen support)PythonMatlabRJulia (soon)Rust (soon)CreditsPIQP is developed by the following people:Roland Schwan (main developer)Yuning Jiang (methods and maths)Daniel Kuhn (methods and maths)Colin N. Jones (methods and maths)All contributors are affiliated with theLaboratoire d'Automatiqueand/or theRisk Analytics and Optimization ChairatEPFL, Switzerland.This work was supported by theSwiss National Science Foundationunder theNCCR Automation(grant agreement 51NF40_180545).PIQP is an adapted implementation ofworkby Spyridon Pougkakiotis and Jacek Gondzio, and is built on the following open-source libraries:Eigen: It's the work horse under the hood, responsible for producing optimized numerical linear algebra code.ProxSuite: The code structure (folder/namespace structure, etc.), some utility functions/helper macros, and the instruction set optimized python bindings are based on ProxSuite.SuiteSparse - LDL(modified version): Used for solving linear systems in the sparse solver.pybind11: Used for generating the python bindings.cpu_features: Used for run-time instruction set detection in the interface bindings.OSQP: The C and Matlab interface is inspired by OSQP.Clarabel: Parts of the iterative refinement scheme are inspired by Clarabel's implementation.Citing our WorkIf you found PIQP useful in your scientific work, we encourage you to cite our accompanying paper:@misc{schwan2023,
    author = {Schwan, Roland and Jiang, Yuning and Kuhn, Daniel and Jones, Colin N.},
    title = {PIQP: A Proximal Interior-Point Quadratic Programming Solver},
    year = {2023},
    eprint = {arXiv:2304.00290},
}The benchmarks are available in the following repo:piqp_benchmarksLicensePIQP is licensed under the BSD 2-Clause License.
Package: piqtec
PIQTECTHIS PACKAGE IS WORK IN PROGRESSIQtec is a small smart-home vendor based in the Czech Republic.
This package is an unofficial python interface intended to be further used in a Home Assistant integration.
The functionality of the API this package relies on is reverse engineered without any access to official
documentation, your mileage may vary. I am not even sure, that the API calls are universal...
Package: piquasso
PiquassoA Python library for designing and simulating photonic quantum computersPiquasso is a simulator for photonic quantum computations.This is a research project, bugs can be expected. If you encounter any, please report
it in theIssues page.InstallationPiquasso and its dependencies can be installed via pip:pip install piquassoIf you wish to, you can also installpiquassoboostfor
performance improvement.DocumentationThe documentation is avaliable atdocs.piquasso.com.How to contribute?We welcome people who want to make contributions to Piquasso, be it big or small! If you
are considering larger contributions to the source code, please contact us first.We also appreciate bug reports, suggestions, or any kind of idea regarding Piquasso.Development guideTheeigen3C++ library needs to be installed for thethewalrus(dependency ofstrawberryfields).On Ubuntu/Debian you can install it withsudo apt-get install libeigen3-devNow, to install development dependencies, use:pip install -r requirements.txtTestingTests and additional checks can be run usingtox. After installation, run the
following command:tox -e py310Alternatively, you can run only the tests usingpytest. After installation, run the
following command:pytest tests