Saravanan666/pypi-org huggingface dataset:
Package: pyipx800
pyipx800Package Python pour contrôler le module IPX800v4 de GCE-Electronics.Utilisationfrom pyipx800 import pyipx800

ipx = pyipx800.pyipx800("ipx800_v4", 80, "apikey")
ipx.configure()

d1 = ipx.inputs[0]
print("Input %d : <%s> = %d" % (d1.id, d1.name, d1.state))License InformationREAD LICENSE FILE
Package: pyIPXACT
pyIPXACT - An IP-XACT DOM forIEEE 1685-2014in Python.FeaturesGenerate IP-XACT files forIP-XACT catalogsIP-XACT Resources:Standards:IEEE 1685-2009IEEE 1685-2014Schema files:IPXACT-Schemaat GitHubIP-XACTatAccelleraContributors:Patrick Lehmann(Maintainer)LicenseThis library is licensed underApache License 2.0SPDX-License-Identifier: Apache-2.0
Package: pyiqvia
🌻 pyiqvia: A clean, async-focused Python3 API for IQVIA™pyiqviais an async-focused Python3 library for allergen, asthma, and disease data from
theIQVIA™family of websites (such asPollen.com,FluStar, and more).Python VersionsInstallationUsageContributingPython Versionspyiqviais currently supported on:Python 3.10Python 3.11Python 3.12InstallationpipinstallpyiqviaUsageimportasynciofromaiohttpimportClientSessionfrompyiqviaimportClientasyncdefmain()->None:"""Run!"""# Note that ZIP codes must be provided as strings:client=Client("80012")# Get current allergen information:awaitclient.allergens.current()# Get more information on the current allergen outlook:awaitclient.allergens.outlook()# Get extended forecast allergen information:awaitclient.allergens.extended()# Get historic allergen information:awaitclient.allergens.historic()# Get current asthma information:awaitclient.asthma.current()# Get extended forecast asthma information:awaitclient.asthma.extended()# Get historic asthma information:awaitclient.asthma.historic()# Get current cold and flu information:awaitclient.disease.current()# Get extended forecast cold and flu information:awaitclient.disease.extended()# Get historic cold and flu information:awaitclient.disease.historic()asyncio.run(main())RetriesBy default,pyiqviawill retry appropriate errors 4 times (with an exponentially
increasing delay in-between). This logic can be changed by passing a different value forrequest_retriesto theClientconstructor:importasynciofrompyiqviaimportClientasyncdefmain():client=Client("80012",request_retries=5)# ...asyncio.run(main())Connection PoolingBy default, the library creates a new connection to IQVIA with each coroutine. If you
are calling a large number of coroutines (or merely want to squeeze out every second of
runtime savings possible), anaiohttpClientSessioncan be used for
connection pooling:importasynciofromaiohttpimportClientSessionfrompyiqviaimportClientasyncdefmain()->None:"""Run!"""asyncwithClientSession()assession:client=Client("80012",session=session)# ...asyncio.run(main())ContributingThanks to all ofour contributorsso far!Check for open features/bugsorinitiate a discussion on one.Fork the repository.(optional, but highly recommended) Create a virtual environment:python3 -m venv .venv(optional, but highly recommended) Enter the virtual environment:source ./.venv/bin/activateInstall the dev environment:script/setupCode your new feature or bug fix on a new branch.Write tests that cover your new functionality.Run tests and ensure 100% code coverage:poetry run pytest --cov pyiqvia testsUpdateREADME.mdwith any new documentation.Submit a pull request!
Package: pyircor
pyircoris the Python implementation of the R packageircor.ircorprovides the implementation of various correlation coefficients of common use in Information Retrieval,
such as Kendall and AP correlation coefficients, with and without ties. For this implementation,numbais used for the accelleration.For reference please refer to Julián Urbano and Mónica Marrero, “The Treatment of Ties in AP Correlation”, ACM ICTIR, 2017.Free software: MIT licenseInstallationYou may install the stable release from PyPI usingpippip install pyircorUsagetauandtauapimplement the Kendall tau and Yilmaz tauAP correlation coefficients, where no ties are allowed between items:frompyircor.tauimporttaufrompyircor.tauapimporttauapimportnupmyasnpx=np.array([0.06,0.2,0.27,0.37,0.57,0.63,0.66,0.9,0.91,0.94])y=np.array([0.37,0.06,0.2,0.27,0.57,0.66,0.63,0.91,0.9,0.94])tau(x,y)# 0.7777777777777778tauap(x,y)# 0.7491181657848325Intauapit is important to use the correct sorting order. By default, items are sorted in decreasing order,
as should be for instance if the scores represent system effectiveness. When they should be in increasing order,decreasingshould be set toFalse:frompyircor.tauapimporttauap# these two calls are equivalenttauap(x,y)# 0.7491181657848325tauap(-x,-y,decreasing=False)# 0.7491181657848325tau_aandtauap_aare versions to use whenxrepresents a true ranking without ties, andyrepresents a ranking
estimated by an observer who is allowed to produce ties. They can be used as a measure of accuracy of the observer with
respect to the true rankingfrompyircor.tauimporttau_afrompyircor.tauap_aimporttauap_ay=np.round(y*5)/5tau_a(x,y)# 0.7111111111111111tauap_a(x,y)# 0.6074514991181656tau_bandtauap_bare versions to use under the assumption that bothxandyrepresent rankings estimated by two
observers who may produce ties. They can be used as a measure of agreement between the observers:x=np.round(x*5)/5tau_b(x,y)# 0.75tauap_b(x,y)# 0.626984126984127CreditsAlong with the codebase itself, many parts of this package, including docstrings and comments, are directly adopted under the
original authors’ agreement. Please refer to the original work if you want to use this package for any publication.This package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.Reference@inproceedings{urbano2017ties,
  author = {Urbano, Juli{\'{a}}n and Marrero, M{\'{o}}nica},
  booktitle = {ACM SIGIR International Conference on the Theory of Information Retrieval},
  pages = {321--324},
  title = {{The Treatment of Ties in AP Correlation}},
  year = {2017}
}History0.1.0 (2019-12-08)First release on PyPI.
Package: pyird
Free from messy directory and file management of IRD analysis.
Currently under heavily construction. Use develop branch for dev.ExamplesCreating 1D spectra from raw data.
- pyird/examples/python/IRD_stream.py – IRD data; read [the docs](https://secondearths.sakura.ne.jp/pyird/tutorials/IRD_stream.html).
- pyird/examples/python/REACH_stream.py – REACH dataInstall` pip install pyird `or` python setup.py install `Core Pipelinespyird.utils – setting us free from file name managementspyird.image – reducing systematics in the image level and extracting raw spectrapyird.spec – assigning wavelength reference (wavref) to pixel coordinates in the raw spectraClassesfitsset.FitsSet –  sets of fits filesirdstream.Stream2D – 2D fits stream from raw imagesaperture.TraceAperture – aperture class for traceimage_widget.image_1Dand2D – interactive figures of 1D spectrum and 2D detector imageApertureMask: n=42 (H), 102 (YJ) apertures extracted from FLAT for aperture mask.Star:aperture.TraceAperture.mmf2()sets n=21 (H) apertures of star fiber.Comb:aperture.TraceAperture.mmf1()sets n=51 (YJ) apertures of comb fiber.
Package: pyirecovery
pyirecoveryA CLI wrapper of pymobiledevice3 that interacts with Recovery/DFU Apple devicesInstallationInstall with PIP:python3 -m pip install pyirecoveryInstall locally:git clone https://github.com/Mini-Exploit/pyirecovery
cd pyirecovery
bash ./install.shUsageRunpyirecoveryand see the usageCreditsdoronz88-pymobiledevice3
Package: pyirf
pyirfis a python library for the generation of Instrument Response
Functions (IRFs) and sensitivities for theCherenkov Telescope Array (CTA).Thanks to its simple input/output and modular function-based structure,
it can be used to process also data from other Imaging Atmospheric
Cherenkov Telescopes (IACTs).Source code:https://github.com/cta-observatory/pyirfDocumentation:https://cta-observatory.github.io/pyirf/Citing this softwareIf you use a released version of this software for a publication,
please cite it by using the corresponding DOI:latest :all versions:Please visit Zenodoand select the correct version
Package: pyiris
IRISIRIS is an intelligent runtime system for extremely heterogeneous architectures. IRIS discovers available functionality, manage multiple diverse programming
systems (e.g., OpenMP, CUDA, HIP, Level Zero, OpenCL, Hexagon) simultaneously in the same application, represents data dependencies, orchestrates data movement proactively, and allows configurable work schedulers for diverse heterogeneous devices.IRIS is open source software. You may freely distribute it under the terms of the license agreement found in LICENSE.The IRIS source code will be available at this repository on September 2021.https://iris-programming.com
Package: pyirk
Overview: pyirkPyirk is a Python framework forimperativerepresentation ofknowledge.Designed to formally represent knowledge (including meta levels)Implementation-status: "early alpha"Inspired by OWL, but much more expressive... at the cost of guarantied computabilityInspired by Wikidata, but much simplerInspired by SUO-KIF, but with less bracketsRepresented directly in python: → imperative instead of declarative knowledge representationWhile pyirk aims to be applicable to a wide range of knowledge domains, its origin an its current (2023) main focus is the representation of knowledge from the domain ofcontrol theoryas part of theAutomatic Control Knowledge Repository (ACKREP).
Thus, a subset of theOntology of Control Systems Engineeringis used as test data for pyirk. In fact, both projects are practically co-developed.Not that, originally pyirk (imperative representation of knowledge) was called pyerk (emergent representation of knowledge), in case you come across some old version.Recommended Directory Structure<irk-root>/
├── pyirk-core/                     ← repo with the code of the core package
│  ├── .git/
│  ├── README.md                    ← the currently displayed file (README.md)
│  ├── setup.py                     ← deployment script
│  ├── src/pyirk/auxiliary.py       ← module containing function get_irk_root_dir()
│  └── ...
│
├── django-irk-gui/                 ← repo with the code for the django gui (project and! app)
│  │                                  (this package is optional)
│  ├── .git/
│  ├── manage.py
│  └── ...
└──...DocumentationRudimentary documentation is available athttps://pyirk-core.readthedocs.io(generated from the/docsdirectory). To get an overview of the most important features you might also want to have a look at the source code, especially at the filesbuiltin_entities.pyand the test cases, e.g.,test_core.py.Coding styleWe useblack -l 120 ./to ensure coding style consistency.
Package: pyiron-base
pyiron - an integrated development environment (IDE) for computational materials science. While the general pyiron framework is focused on atomistic simulations, pyiron_base is independent of atomistic simulation. It can be used as a standalone workflow management combining a hierachical storage interface based on HDF5, support for HPC computing clusters and a user interface integrated in the Jupyter environment.InstallationYou can test pyiron onMybinder.org (beta).
For a local installation we recommend to install pyiron inside ananacondaenvironment:conda install -c conda-forge pyiron_baseSee theDocumentation-Installationpage for more details.ExampleAfter the successful configuration you can start your first pyiron calculation. Navigate to the the projects directory and start a jupyter notebook or jupyter lab session correspondingly:cd ~/pyiron/projects
jupyter notebookOpen a new jupyter notebook and inside the notebook you can now validate your pyiron calculation by creating a test project:from pyiron import Project
pr = Project('test')
pr.pathGetting started:Test pyiron with mybinder:License and Acknowledgmentspyiron_baseis licensed under the BSD license.If you use pyiron in your scientific work,please consider citing@article{pyiron-paper,
  title = {pyiron: An integrated development environment for computational materials science},
  journal = {Computational Materials Science},
  volume = {163},
  pages = {24 - 36},
  year = {2019},
  issn = {0927-0256},
  doi = {https://doi.org/10.1016/j.commatsci.2018.07.043},
  url = {http://www.sciencedirect.com/science/article/pii/S0927025618304786},
  author = {Jan Janssen and Sudarsan Surendralal and Yury Lysogorskiy and Mira Todorova and Tilmann Hickel and Ralf Drautz and Jörg Neugebauer},
  keywords = {Modelling workflow, Integrated development environment, Complex simulation protocols},
}
Package: pyirr
Python implementation of the R packageIRR, all credit goes to the original
authors[1]. The package contains functions to calculate coefficients of Interrater Reliability and Agreement for interval,
ordinal and nominal data: intraclass-correlations, Finn-Coefficient, Robinson’s A, Kendall’s W, Cohen’s Kappa, and others.
This is a straight line-for-line port from the R-package, so it is not particularly Pythonic and mainly made as an
exercise to learn more about R. For documentation I highly recommend you head over to the R package page, they put in a
lot of effort for the documentation!How to installThe package is available on the Python Package Index (PyPI). To install it you can run:pip install pyirrHow to useA simple example:from pyirr import read_data, intraclass_correlation

data = read_data("anxiety")  # loads example data
intraclass_correlation(data, "twoway", "agreement")Returns:==================================================
          Intraclass Correlation Results
==================================================
Model: twoway
Type: agreement

Subjects = 20
Raters = 3
ICC(A,1) = 0.20

F-Test, H0: r0 = 0 ; H1 : r0 > 0
F(19.00,39.75) = 1.83, p = 0.0543

95%-Confidence Interval for ICC Population Values:
-0.039 < ICC < 0.494
==================================================Another simple example:from pyirr import read_data, kappam_fleiss

data = read_data("anxiety")  # loads example data
kappam_fleiss(data, detail=True)Returns:==================================================
            Fleiss` Kappa for m Raters
==================================================
Subjects = 30
  Raters = 6
   Kappa = 0.430

       z = 17.652
 p-value = 0.000

                         Kappa       z  p.value
1. Depression            0.245   5.192      0.0
2. Personality Disorder  0.245   5.192      0.0
3. Schizophrenia         0.520  11.031      0.0
4. Neurosis              0.471   9.994      0.0
5. Other                 0.566  12.009      0.0
==================================================[1]Gamer, M., Lemon, J., Gamer, M.M., Robinson, A. and Kendall’s, W., 2012. Package ‘irr’. Various coefficients of interrater reliability and agreement, 22.
Package: pyirs
(P)ython (I)nterfaces for (R)eactor (S)imulationsThe package provides Python interface to nuclear reactor simulation codes with the primary
goal to organize data flow.Cuurently implemented are MCNP and SCF interfaces; they can be used to organize
coupled neutronics- and thermohydraulic calculations.Documentation sources are indocs. An HTML version (possibly outdated) can
be found inhttp://travleev.github.io/PIRSdocs/HistoryPIRS evolved from a set of Python scripts helping to read/write MCNP-related files.
It was mainly developed and applied for coupled MCNP-SCF simulations of square PWR
assemblies and parts of the core. Documentation found indocsrefers to large extent
to that state of the code.Occasionally, some modules were modified to meet other needs, without thorough
checking of back compatibility and without reflecting the changes in
documentation.OutlookThe package shall be refactored to fix the mentioned above incompatibilites.
Some code (e.g. for reading meshtal files) was rewritten from scratch in another packages
(seenumjuggler,tovtk). Refactoring should take this into account and extract code with
the same functionality into separate packages.
Package: py-irsend
python-irsendThis is a simple wrapper forlirc's irsend.Install:pip install py_irsendBasic Usage:>>> from py_irsend import irsend
>>> irsend.list_remotes()
['lasko_heater', 'lights.conf', 'dynex_tv', 'logitech_z906', 'sabrent_hdmi_switch']
>>> irsend.list_codes('logitech_z906')
['POWER', 'INPUT', 'MUTE', 'LEVEL', 'EFFECT', 'VOLUME_DOWN', 'VOLUME_UP']
>>> irsend.send_once('logitech_z906', ['POWER'])It makes use ofsubprocessto call irsend. No attempts are made to handle errors (e.g. irsend not being
installed, or lircd not running), and instead leaves those to the caller. See
the documentation for subprocess (specificallycheck_output)
to determine which exceptions may be raised.
Package: py-irtools
irtoolsA collection of useful tools for Automation, Devops, or anything reallyNews:Now hosted on pypi !https://pypi.org/project/py-irtools/Now with a Slack Channel!https://py-irtools.slack.comNow with Travis CIhttps://travis-ci.org/InbarRose/irtoolsWhat is it?A set of tools that I find myself using often.
Compiled over many years of use, gathered here and organized.Installing with pipTo get the most stable version (recommended)pip install py-irtoolsTo get the development versionpip install git+git://github.com/InbarRose/irtools@development#egg=irtoolsUsageTo use the tools, you simply do:from irtools import *This will gauruntee that you have the optimal situation, where you can accessutilsfrom your code.It will also make sure that the logging module has been monkey patched with the newtracelevel. (important when running on commandline or with logging enabled)When running from command line, you should include a call toutils.logging_setup()to make sure the logging is setup to work correctly for all the utils.Examplesret=utils.iexec('ping 8.8.8.8')# using iexec you can run any commandSee the rest of this example and more in thequickstart examples fileMore examples in theexamples folder.Authors / Creators / CreditsInbar Rose-Owner-InbarRoseNote about code included or copied from external sourcesThroughout the years I have compiled this set of utilities, most of it is written by me (Inbar) But some of it is copied from other sources, everywhere I have copied code I have included a link to the source, and where possible the type of license or a note about the author. If you believe I have made an error, or something I have included is wrong or needs updating, please let me know. It is not my intention to steal or cheat or claim work as my own, and if you dispute my using of your code, I will happily remove it. In some cases I made slight modifications to code mostly for readability, but in some cases I made modifications to enhance capabilities. Again, if anyone has a problem with anything I have done, please let me know. Thanks.Future PlansAdd examples to try to cover each util lib and kit. (Assistance is welcomed)Improve documentation and add additional comments for increased flow readability (Assistance is welcomed)I plan to include additional tools in the future, not just a set of utils, but also powerful classes to manage common DevOps/Automation challanges...TaskManager-To optimize running tasks in parallel or in a specific orderJsonLoader-To make reading and writing class structures from JSON easyRestfulAPI-To enhance the ability to use and debug restful interface using requestsAnd More.. -I have a large collection of tools to releaseLicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: pyirx
IRxIRxaims to provide a translator to LLVM-IR fromASTxobjects.ASTxis a generic project that offers a way to compound in an expressive way
anAST. It is not specific for theArxLangproject, although it is main
focus is to provide all needed feature for it.IRxusesllvmlitein order to generateLLVM-IRsource, in another
words.Free software: BSD 3 ClauseDocumentation:https://arxlang.github.io/irx.FeaturesGenerateLLVM-IRfromASTx
Package: pyisa
pyisa - Python Intent based Structuring ApproachAbout pyisa:PYISA is a a basic intent based project structuring approach which classifies the intents in to 3 basic ISA Zones:Business ObjectivesProblem FormulationSolution DesigningThis classification approach is build to ensure that all the important aspects of the project structuring are covered.Being a beta version of the project, the number of zones are fixed and pre-defined. However in the future versions, a feature to add zones will be incorporated.Current Work in Progress:Creating zone tags for files and folders so to enable zone specific search within your projectThe existing testing is done on Linux environmentFuture Agenda:Enable adding of additional zonesMake the project OS independentHow to install pyisa?:pip install pyisaHow to use pyisa?:Run this command on Linux command prompt:pyisa_build  --project_path=/absolute/path  --project_name=name  --tree=True
Package: pyisaf
Python library for i.SAF VAT report generation.GitHub:https://github.com/versada/pyisafFree software: BSD licenseSupported Python versions: 2.7, 3.5+Featuresi.SAF data validation based on XSDi.SAF XML builderUsageA complete example of i.SAF data dict can be foundin the tests.frompyisafimportschema_v1_2asisaf_schema,ISAF1_2BuilderasBuilderfromschemaimportSchemaError# Prepare i.SAF datadata={'header':{'file_description':{# ...},},'master_files':{'customers':{# ...},'suppliers':{# ...},},'source_documents':{'purchase_invoices':{# ...},'sales_invoices':{# ...},'settlements_and_payments':{# ...},},}# Validate data against i.SAF schemaisaf_data=isaf_schema.validate(data)# Build the XMLbuilder=Builder(isaf_data)isaf_xml=builder.dumps()Historyv0.1.8 (2017-02-01)Updates links after repository transfer.v0.1.7 (2017-01-24)Fixes rendering of elements which are nillable to set xsi:nil attributev0.1.6 (2017-01-06)Adds Python 3.6 buildv0.1.5 (2016-12-05)Fixes to not add empty tags like Customers, Suppliers, PurchaseInvoices if
the underlying collection is empty.v0.1.4 (2016-11-30)Fixes nillable dates renderingv0.1.3 (2016-11-24)Includes packages (fail)Removes docs from the packagesv0.1.2 (2016-11-24)Minor fixes in descriptionv0.1.1 (2016-11-24)Initial version