Saravanan666/pypi-org huggingface dataset:
Package: isoenum
Isotopic (iso) enumerator (enum) - enumerates isotopically resolved
InChI (International Chemical Identifier) for metabolites.TheisoenumPython package provides command-line interface that
allows you to enumerate the possible isotopically-resolvedInChIfrom one of
theChemical Table file(CTfile) formats (i.e.molfile,SDfile)
used to describe chemical molecules and reactions as well as fromInChIitself.SeeTutorialdocumentation for usage examples ofisoenumPython package
as well asisoenumdocker container.Linksisoenum @GitHubisoenum @PyPIisoenum @DockerHubisoenum @ReadTheDocsInstallationTheisoenumpackage runs under Python 2.7 and Python 3.4+. Usepipto install.Install on Linux, Mac OS Xpython3-mpipinstallisoenumInstall on Windowspy-3-mpipinstallisoenumDependenciesTheisoenumPython package requires anon-pip-installabledependency:
theOpen Babelchemistry library version 2.3.90 or later, which relies onInChIlibraryversion 1.0.4 or later to performInChIconversions.Refer to the official documentation to installOpen Babelon your system:Official Installation Instructions:http://openbabel.org/wiki/Category:InstallationDockerIn addition toPyPIpackage,Dockerfileand the automatically builtDockerHubcontainer, which contains theisoenumPython package and all its dependencies, are
also provided.To use theisoenumPython package, you will need to setup docker for your system
andpullorbuildthe docker container.Install dockerInstalldocker:Follow the instructions to install docker on your system:https://docs.docker.com/engine/installationUbuntuDebianCentOSFedoraMacWindowsSetup containerSetup theisoenumcontainer:pullthe built image from theDockerHub:# docker pull moseleybioinformaticslab/isoenum
# docker tag moseleybioinformaticslab/isoenum:latest isoenum:latest  # retag docker image
# docker rmi moseleybioinformaticslab/isoenum  # remove after you have retagged itorbuildan image usingDockerfileat the root of this repo by runningdocker buildfrom the directory containingDockerfile:# docker build -t isoenum .Development version installationInstall development version on Linux, Mac OS Xpython3-mpipinstallgit+git://github.com/MoseleyBioinformaticsLab/isoenum.gitInstall development version on Windowspy-3-mpipinstallgit+git://github.com/MoseleyBioinformaticsLab/isoenum.gitLicenseThis package is distributed under theBSDlicense.
Package: isoenum-webgui
isoenum-webguiisoenum-webguiprovides Flask-based web user interface that usesisoenumpackage
to generate accurate InChI (International Chemical Identifier)
for NMR metabolite features based on standard NMR experimental descriptions (currently1D-1Hand1D-CHSQC) in order to improve data reusability of metabolomics data.Linksisoenum @GitHubisoenum @PyPIisoenum @ReadTheDocsInstallationTheisoenum-webguipackage runs under Python 3.4+. Usepipto install.Install on Linux, Mac OS Xpython3 -m pip install isoenum-webguiInstall on Windowspy -3 -m pip install isoenum-webguiDependenciesTheisoenum-webguirequires anon-pip-installabledependency: theOpen Babelchemistry library version 2.4.1 or later,
which relies onInChIlibraryversion 1.0.4 or later to performInChIconversions.Refer to the official documentation to installOpen Babelon your system:Official Installation Instructions:http://openbabel.org/wiki/Category:InstallationDevelopment version installationInstall development version on Linux, Mac OS Xpython3 -m pip install git+git://github.com/MoseleyBioinformaticsLab/isoenum-webgui.gitInstall development version on Windowspy -3 -m pip install git+git://github.com/MoseleyBioinformaticsLab/isoenum-webgui.gitLicenseThis package is distributed under theBSDlicense.
Package: isoext
isoext: Isosurface Extraction on GPUOverviewWelcome toisoext— a Python library designed for efficient isosurface extraction, leveraging the power of GPU computing and comes withpytorchsupport. Our library attempts to implement a collection of classic isosurface extraction algorithms. Currently, only the following algorithms are supported, but more will come in the future:Marching cubeslorensen: the original marching cubes algorithm from the paperMarching cubes: A high resolution 3D surface construction algorithm.InstallationTo installisoext, make sureCUDA Toolkitis installed and run:pipinstallisoextQuick StartHere's a simple example to get you started:importisoextfromisoext.sdfimport*aabb=[-1,-1,-1,1,1,1]res=128grid=isoext.make_grid(aabb,res)torus_a=TorusSDF(R=0.75,r=0.15)torus_b=RotationOp(sdf=torus_a,axis=[1,0,0],angle=90)torus_c=RotationOp(sdf=torus_a,axis=[0,1,0],angle=90)sphere_a=SphereSDF(radius=0.75)sdf=IntersectionOp([sphere_a,NegationOp(UnionOp([torus_a,torus_b,torus_c]))])sdf_v=sdf(grid)# Only accept a gpu tensor from pytorch for nowisolevel=0v,f=isoext.marching_cubes(sdf_v,aabb,isolevel)isoext.write_obj('test.obj',v,f)Task ListFix docstring.Implement MC33.Addnumpysupport.Licenseisoextis released under theMIT License. Feel free to use it in your projects.AcknowledgmentsWe useThrustfor GPU computing andnanobindfor Python binding.The LUTs forlorensenare borrowed from Paul Bourke (https://paulbourke.net/geometry/polygonise/).
Package: isofit
ISOFIT contains a set of routines and utilities for fitting surface, atmosphere and instrument models to imaging
spectrometer data. It is written primarily in Python, with JSON format configuration files and some dependencies on
widely-available numerical and scientific libraries such as scipy, numpy, and scikit-learn. It is designed for maximum
flexibility, so that users can swap in and evaluate model components based on different radiative transfer models (RTMs)
and various statistical descriptions of surface, instrument, and atmosphere. It can run on individual radiance spectra
in text format, or imaging spectrometer data cubes.Please check thedocumentationfor installation and usage instructions and in depth information.There are two main branches:dev(for activate development)main(in-line with the current release)Information on how tocite the ISOFIT Python packagecan be found in theCITATIONfile.LicenseFree software: Apache License v2All images contained in any (sub-)directory of this repository are licensed under the CC0 license which can be foundhere.Feature overviewutilities for fitting surface, atmosphere and instrument models to imaging spectrometer dataa selection of radiative transfer models (RTMs) incl. MODTRAN, LibRadTran, and 6SsRTMnet emulator for MODTRAN 6 by coupling a neural network with a surrogate RTM (6S v2.1)various statistical descriptions of surface, instrument, and atmosphereapplication to both individual radiance spectra and imaging spectrometer data cubescustom instrument models to handle new sensorsobservation uncertanities to account for model discrepancy errorsprior distribution based on background knowledge of the state vectorStatus
Package: isofits
ISOFITSThis package contains functions for calculating hole/shaft tolerances and fits per ISO 286Installationisofitsis available onPYPI.  Install withpip:pip install isofitsUsageImport the package:from isofits import *DocumentationSee below for a list of function and their usagesisotolupper_tolerance = isotol('hole', '10', 'H7', 'upper') #returns upper tolerance in microns

lower_tolerance = isotol('hole', '10', 'H7', 'lower') #returns lower tolerance in microns

upper_tolerance, lower_tolerance = isotol('hole', '10', 'H7', 'both') #returns both tolerances in micronsisofitmmc, lmc = isofit(10, 'H7', 'h6') #returns mmc and lmc of hole/shaft fitisoreportisoreport(10, 'H7', 'h6') #returns printed report of mmc and lmc of hole/shaft fit
Package: iso-forest
# iso_forestThis is a simple package implementation for the isolation forest method described (among other places) in this [paper](icdm08b.pdf) for detecting anomalies and outliers from a data point distribution.## Extended isolation forestFor an extended version of this algorithm that produces more precise scoring maps please visit this repository[https://github.com/sahandha/eif](https://github.com/sahandha/eif)/## Installationpip install iso_forestor directly from the Github repositorypip install git+https://github.com/mgckind/iso_forest.gitIt supports python2 and python3## RequirementsnumpyNo extra requirements are needed for the algorithm.In addition, it also contains means to draw the trees created using the [igraph](http://igraph.org/) library.## Use ExamplesSee these 2 notebooks examples on how to use it[basics](demo_iforest.ipynb)[tree visualization and anomaly PDFs](demo_vis_pdf.ipynb)## Releases### v1.0.3Initial Release
Package: isogeo-export-docx
Isogeo - DOCX ExporterPython package to export Isogeo metadata into Word documents using thePython SDKanddocxtpl.Usage in a nutshellInstall:pipinstallisogeo-export-docxAuthenticate# importfromisogeo_pysdkimportIsogeo# API clientisogeo=Isogeo(auth_mode="group",client_id=ISOGEO_API_GROUP_CLIENT_ID,client_secret=ISOGEO_API_GROUP_CLIENT_SECRET,auto_refresh_url="{}/oauth/token".format(ISOGEO_ID_URL),platform=ISOGEO_PLATFORM,)# getting a tokenisogeo.connect()Make a search:search=isogeo.search(include="all",)# close sessionisogeo.close()Export:# importfromisogeotodocximportIsogeo2docx# output folderPath("_output/").mkdir(exist_ok=True)# templatetemplate_path=Path(r"tests\fixtures\template_Isogeo.docx")# instanciatetoDocx=Isogeo2docx()# parse results and export itformdinsearch_results.results:# load metadata as objectmetadata=Metadata.clean_attributes(md)# prepare the templatetpl=DocxTemplate(template_path.resolve())# fill the templatetoDocx.md2docx(docx_template=tpl,md=metadata)# filenamemd_name=metadata.title_or_name(slugged=1)uuid="{}".format(metadata._id[:5])out_docx_filename="_output/{}_{}.docx".format(md_name,uuid)# save ittpl.save(out_docx_filename)# delete template objectdeltpl
Package: isogeo-export-xl
Isogeo - XLSX ExporterPython package to export Isogeo metadata into Excel workshbook using thePython SDKandOpenpyxl.Usage in a nutshellInstall:pipinstallisogeo-export-xlAuthenticate# importfromisogeo_pysdkimportIsogeo# API clientisogeo=Isogeo(auth_mode="group",client_id=ISOGEO_API_GROUP_CLIENT_ID,client_secret=ISOGEO_API_GROUP_CLIENT_SECRET,auto_refresh_url="{}/oauth/token".format(ISOGEO_ID_URL),platform=ISOGEO_PLATFORM,)# getting a tokenisogeo.connect()Make a search:search=isogeo.search(include="all",)# close sessionisogeo.close()Export:# importfromisogeotoxlsximportIsogeo2xlsx# instanciate the final workbookout_workbook=Isogeo2xlsx(lang=isogeo.lang,url_base_edit=isogeo.app_url,url_base_view=isogeo.oc_url)# add needed worksheetsout_workbook.set_worksheets(auto=search.tags.keys())# parse search resultsformdinmap(Metadata.clean_attributes,search.results):out_workbook.store_metadatas(md)# save fileout_workbook.save("./isogeo_export_to_xlsx.xlsx")
Package: isogeo-pysdk
Isogeo API Python SDKA Python package to use Isogeo REST API.RequirementsIsogeo API requires oAuth2 authentication. To obtain credentials, send us your request by emailprojects+api@isogeo.com.Based on the well knownrequestspackage and the extensionrequests-oauthlib.DocumentationPackage manual and autogenerated modules docIsogeo APIContribution guidelines (FR)Usage in a nutshellpython-mpipinstall--userisogeo-pysdk# or using pipenvpython-mpipenvinstallisogeo-pysdkQuickstartfromisogeo_pysdkimportIsogeo# authenticate your client applicationisogeo=Isogeo(client_id=app_id,client_secret=app_secret)# get the tokenisogeo.connect()# search within catalogs shared to the applicationsearch=isogeo.search()# print some statementsprint("Search query parameters: ",search.query)print("Total count of metadatas shared: ",search.total)print("Count of resources got by request:{}\n".format(len(search.results)))# close the session when you finishisogeo.close()Samples are available inthe source repository <https://github.com/isogeo/isogeo-api-py-minsdk/tree/master/isogeo_pysdk/samples>_.TestsTests are performed for each published commit:byAzure Pipelinespython-mpipinstall--upgrade-rtests/requirements_test.txtpython-mpytestOr using theincluded Powershell script:.\tool_test_coverage.ps1BuildTo package and upload:.\tool_build_upload.ps1To build docs:.\tool_docs_build.ps1
Package: isogeo-scan-metadata-processor
Isogeo Scan - Metadata ProcessorMiddleware used to process metadata issued by Isogeo Scan.Available as:Python packageWindows executableRequirementsPython 3.7DevelopmentQuickstart# create virtual envpy-3.7-mvenv.venv# activate it.\.venv\Scripts\activate# update basic toolingpython-mpipinstall-Upipsetuptoolswheel# install requirementspython-mpipinstall-U-r./requirements.txt# install package for developmentpython-mpipinstall--editable.Try itRename the.env.exampleinto.envand fill the settingsLaunch theCLIFor example, get the help:scan-metadata-processor--helpCheck:# for all default formatsscan-metadata-processor--label"CheckProcessConfig"--settings.\.envcheckProcess metadata:scan-metadata-processor--label"ProcessInputMetadata"--settings.\.envprocessThere is also a clean task to automatically remove outdated logs and output files:scan-metadata-processor--label"CleanLogs"--settings.\.envcleanUsage of the executableJust replacescan-metadata-processorby the executable filename:.\Isogeo_ScanMetadataProcessor.exe--label"ProcessInputMetadata"--settings.\.envprocessDeploymentEvery tagged commit pushed tomastertriggers a deployment to:Azure Storage : Isogeo/isogeoscan/app/isogeo-scan-metadata-processor/Python Package IndexGithub Releases
Package: iso-language-codes
ISO Language CodesGet ISO code for a given languageFree software: MIT licenseDocumentation:https://iso-language-codes.readthedocs.io.UsageImport this package in your script:>>> from iso_language_codes import *Get info about a language via Two-letter ISO code:>>> language('ru')
    {'Name': 'Russian', 'Autonym': 'Р СѓСЃСЃРєРёР№'}Or get name and autonym directly with:>>> language_name('ru')
    'Russian'>>> language_autonym('ru')
    'Р СѓСЃСЃРєРёР№'You can also get entire dictionary of languages:>>> languages = language_dictionary()
>>> languages.keys()
    dict_keys(['', 'aa', 'bn', 'ab', ...])CreditsThis package uses edited iso639-autonyms database frombbqsrc/iso639-autonymsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0Base from filled cookiecutter-pypackage template.0.2.0Basic functionality of the module.0.3.0Added Tests for language, language_name and language_autonym functions.Added Documentation.Fixed bug with path to database.Metadata changes.1.0.0Changes to CONTRIBUTING.rst.Changes to Makefile.Changes to README.rst.Added usage examples and credited database source.Compiled documentation.1.1.0Moved module code into __init__ file.Updated history and tests.
Package: isolate
IsolateRun any Python function, with any dependencies, in any machine you want. Isolate offers a
pluggable end-to-end solution for building, managing, and using isolated environments (virtualenv,
conda, remote, and more).MotivationThe fact that nearly every piece of software uses some other libraries or some
other programs is undeniable. Each of these come with their set of dependencies,
and this chain moves forward. Once there are enough 'nodes' in the chain, then
the"dependency mess"starts
to surface and our lives become much harder.Python tried to solve it by recommending the "virtual environment" concept. In
theory it was designed to isolate environments of different projects, so my project
A can depend onpandas==1.0.0while B depends onpandas==2.0.0and whichever
project I choose to work with, I just activate its own environment.Overall this was a very nice solution that did work, and still continues to work
for this use case. But as with every other scoped fix, in time other problems started
to appear that demand a much narrower scope (like defining module-level dependencies,
or even function-level ones for cloud runtimes that allow seamless integration with the
rest of your code running in a different machine).However, unlike "virtual environment" concept, each of the projects that tried to tackle
this problem lacked a universal interface which one can simply define a set of requirements
(this might be dependencies, size of the machine that is needed to run it, or something completely
different) and can change it without any loss. Isolate is working towards a future where this
transititon is as seamless as the transition from your local environment to the remote
environment.
Package: is-online
is_onlineIs Onlineis a Python module meant for cli use which checks whether you are connected to the Internet. By default it creates a request to Cloudflare's DNS at 1.1.1.1Note:Is Onlineis only meant to be used as a CLI tool. If you need something to monitor online reachability in your own Python scripts, useReachabilityInstallationYou can install is_online fromPyPIpipinstallis-onlineHow to useTo use, simply run:$ is_online
You are Online!

$ is_online --host 4.4.4.4 --port 53 --timeout 53
You are Online!By default, this checks connectivity against Cloudflare's 1.1.1.1 DNS Server
Package: isoparser
This python library can parse theISO 9660disk image format includingRock Ridgeextensions. It can load ISOs from the local filesystem or via
HTTP, and will only read and cache sectors as necessary. You list directory
contents, extract files, and retrieve metadata.Installation$pipinstallisoparserUsageimportisoparseriso=isoparser.parse("http://www.microsoft.com/linux.iso")printiso.record("boot","grub").childrenprintiso.record("boot","grub","grub.cfg").content
Package: isopix
IsopixIsopix is a powerful Python library that offers a user-friendly and intuitive approach to automate tasks in Isotropix's Clarisse software. With its Houdini-like syntax,
Isopix serves as a valuable alternative to Clarisse's native Python API, enabling users to easily learn and utilize Python for automating various tasks.InstallationYou can install the package usingpip:Exampleshttps://adetayotyy.github.io/Isopix/
Package: isoplot
Isoplot is a software for the visualisation of MS data from C13 labelling experiments.It takes as input corrected MS data fromIsoCorin csv or tsv format.
Isoplot outputs static and interactive plots that are then used for quality assessment, biological interpretation,
project reports, published papers and so forth.It is one of the routine tools used on theMetaToul platform.The code is open-source, and available onGitHubunder a GPLv3 license.The documentation relative to Isoplot’s installation and usage can be found onReadTheDocs.Key FeaturesCreation of static and interactive plots(barplot, heatmap, clustermap, etc…)Command-line interfaceJupyter Notebook graphical interfaceusing ipywidgetsOpen-source, free and easy to installeverywhere where Python 3 is availableBiologist-friendly
Package: isopsephism
isopsephismFind the numerical value of words.InstallationInstall this library usingpip:pipinstallisopsephismUsagefrom isopsephism.isopsephism import isopsephy
print(isopsephy.convert_word_to_num("ΚΟΥΡΑΙ"))
#prints 601DevelopmentTo contribute to this library, first checkout the code. Then create a new virtual environment:cdisopsephism
python-mvenvvenvsourcevenv/bin/activateNow install the dependencies and test dependencies:pipinstall-e'.[test]'To run the tests:pytest
Package: isoquant-diff
Isoquant_diffIsoquant_diff is a Python library that works with the  Isoquant Software. It can find the differences between two config files.
It supports .ini and .xlsx files.InstallationUse the package managerpipto install isoquant_diff.pipinstallisoquant_diffUsageOnce the package is installed you can call isoquant_diff from the command line.It will ask for two file in the command prompt and will create an excel file and html file with all differences.Command prompt:isoquant_diff[-h][-c][-r]-h, --help           show this help message and exit-c, --csv            output as csv (default: html-file)-r, --report_unique  compares only parameters which are defined in both config-filesLicenseMIT
Package: isortd
isortdSimple http handler forisortutil. I liked the idea of puttingblack[d]into my docker compose file and usingBlackConnectplugin for auto sort without setting up my dev
env every time, but I was still missing sort formatting tool, that would work the same way. So its here... Mb I'll
releaseIsortConnectand it will be more usable.installpoetry add isortdorpython -m pip install --upgrade isortdusageI'd suggest you to run thisdocker imagewith something like:docker run -d --name isortd --publish "47393:47393" urm8/isortd:latestor just add it to your local docker-compose file _0_/todosocket supportsome kind of filechangelistener daemon runnable from directory
Package: isos-environment-test
Isos Technology Python Atlassian Cloud Automation Environment TestLicense: GPLv3RequirementsPython >= 3.7.7appdirs == 1.4.3argcomplete == 1.11.1atlassian-python-api == 1.15.6blessed == 1.17.5certifi == 2020.4.5.1chardet == 3.0.4colorama == 0.4.3coloredlogs == 14.0cursor == 1.3.4decorator == 4.4.2enlighten == 1.5.1halo == 0.0.29humanfriendly == 8.2idna == 2.9importlib-metadata == 1.6.0log-symbols == 0.0.14milc == 1.0.7oauthlib == 3.1.0requests == 2.23.0requests-futures == 1.0.0requests-oauthlib == 1.3.0six == 1.14.0spinners == 0.0.24termcolor == 1.1.0urllib3 == 1.25.9wcwidth == 0.1.9zipp == 3.1.0To install / test environmentEnsure you have python 3 version 3.7.7 or greater installed.Generate an Atlassian API Token following thesedirections.Install the environment test:# You might have to run as Administrator or sudo depending on your setup.

python3 setup.py install --userConfigure the test:isos-env-test config general.jira_url=[Your Jira Cloud URL] \
general.username=[Your cloud account email address] \
general.api_token=[Your api token] \
general.data_path=[A file path to test access to]Run the test:isos-env-testTo install / test with virtualenvEnsure you have python 3 version 3.7.7 or greater installedGenerate an Atlassian API Token following thesedirectionsInstall virtualenv:pip3 install virtualenvCreate and source a virtualenv:virtualenv env
source env/bin/activateRun the following commands in Terminal or Powershell:python setup.py installConfigure the test:isos-env-test config general.jira_url=[Your Jira Cloud URL] \
general.username=[Your cloud account email address] \
general.api_token=[Your api token] \
general.data_path=[A file path to test access to]Run the test:isos-env-testFor assistance with this, Atlassian Products in general, or agile practices,contact Isos Technology today. Isos can do a deep dive into your organization’s processes, strategies, and goals to determine if Cloud adoption is the right option for your organization and help further prepare you for the switch. To continue that discussion, Isos has a comprehensiveCloud Strategyoffering to help guide you through every step of the adoption process. This starts with a complete cloud readiness assessment and moves you throughmigration planning and implementation, andtraining—topping it off by helping your organization achieve freedom and autonomy via ourmanaged servicesoffering.www.isostech.com
Package: isosolve
IsoSolve is a Python module realizing an integrative framework for isotope labeling measurements. It can provide both symbolic and numeric solutions for integrating and consolidating heterogeneous measurements, e.g. NMR and MS measuring ¹³C labeling, to cite the most wide spread ones. This integrative framework helps toclarify and improve the coverage of the isotopic space;evaluate the complementarity and redundancy of different techniques;consolidate isotopic datasets;design experiments, andguide future analytical developments.This framework can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform.IsoSolve is available as a Python library with a command line interface. It is one of the routine tools that we use at theMetaSys teamandMetaToul platformin isotopic studies of metabolic systems.A paper on this subject is under preparation.If you have an idea on how we could improve IsoSolve please submit a new issue to ourGitHub issue tracker.