Saravanan666/pypi-org huggingface dataset:
Package: ispcr
ispcrDocumentation:https://pommevilla.github.io/ispcrSource Code:https://github.com/pommevilla/ispcrPyPI:https://pypi.org/project/ispcr/A simple, light-weight package written in base Python to performin silicoPCR to determine primer performance.Currently in developmentInstallationpipinstallispcrDemonstrationFile-basedin silicoPCRThe main function to use in this package isget_pcr_products, which performsin silicoPCR using two files:primer_file- the path to fasta file containing your primersThis is currently limited to a fasta file containing two sequences, with the forward primer coming first and the reverse primer coming secondsequence_filethe path to the fasta file containing the sequences to test your primers againstget_pcr_productswill then iterate through the sequences insequence_fileand find all products amplified by the forward and reverse primer.Refining resultsYou can also refine your results by using themin_product_lengthandmax_product_lengtharguments, and only print out the columns you are interested in by using thecolsargument. For example, if we're only interested in products between 100 and 250 bp and we only want the name of the sequence the product was amplified from, the length of the product, and the start and end position of the product in the sequence:Writing out isPCR results to a fileget_pcr_productsalso takes anoutput_fileargument. If provided, the results of thein silicoPCR (including any product length restrictions or column selections) to that file. This will overwrite the file.Sequence-basedin silicoPCRTheget_pcr_productsfunction is a wrapper aroundcalculate_pcr_product. The following arguments are required to runcalculate_pcr_product:sequence: the target sequence to test the primers againstforward_primer: the forward primer used to amplify the sequencereverse_primer: the reverse primer (5'-3') used to amplify the sequencesequence,forward_primer, andreverse_primershould be entered asFastaSequenceobjects. AFastaSequenceis just a small convenience class to package a sequence with its header. An example run ofcalculate_pcr_productsmight look like:calculate_pcr_productuses all of the same arguments asget_pcr_products, so you can filter results and select columns just as before:This will also work with theoutput_fileargument.
Package: ispec
ispecDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nispec--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallispecnbdev# activate conda environment$condaactivateispec# make sure the ispec package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the ispec 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:$pipinstallgit+https://github.com/dsm-72/ispec.gitor fromconda$condainstall-cdsm-72ispecor frompypi$pipinstallispecDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.
Package: iSpin-data
This package provides access to iSpin data for a specified turbine ID.  Its use is pretty straightforward:>>> import ispin_data.api as ispin

>>> ispin.username = 'your_username'
>>> ispin.password = 'your_password'

>>> df = ispin.request_overview()
# Returns iSpin installations

>>> df = ispin.request_data(6)
# Returns data for the installation with the turbine ID number 6.
# The start and end date can also be specified

>>> t = ispin.request_turbine_type(6)
# Returns the turbine type of the installation with the turbine ID number 6.LicensesNabla Wind HubROMO WindChangelog0.1.0 (2021-08-24)First release0.3.0 (2021-08-30)Second release0.3.1 (2021-08-31)Added author name and company to main codeThird release0.3.1 (2021-09-06)Added a function to request the turbine type of an installation
Package: ispm-django-chronograph
ChronographControldjango-admincommands via the web.Creating cron jobs for Django apps can be a pain, annoying and repetitive. Withdjango-chronographyou simply create a single cron job to run every minute,
point it at your site’s directory and runmanage.py cron. Then from the admin
you can add jobs.Notedjango-chronographsupports Django 1.1+.Installation and UsageRead docs/overview.txt for more information, build the documentation with
Sphinx or view them onlinehere.You can also grab the latest release from PyPI:pip install django-chronograph
Package: iSponsorBlockTV
iSponsorBlockTVSkip sponsor segments in YouTube videos playing on a YouTube TV device (see below for compatibility details).This project is written in asynchronous python and should be pretty quick.InstallationCheck thewikiWarning: docker armv7 builds have been deprecated. Amd64 and arm64 builds are still available.CompatibilityLegend: ✅ = Working, ❌ = Not working, ❔ = Not testedOpen an issue/pull request if you have tested a device that isn't listed here.DeviceStatusApple TV✅Samsung TV (Tizen)✅LG TV (WebOS)✅Android TV✅Chromecast✅Google TV✅Roku✅Fire TV✅CCwGTV✅Nintendo Switch✅Xbox One/Series✅Playstation 4/5✅UsageRun iSponsorBlockTV on a computer that has network access.
Auto discovery will require the computer to be on the same network as the device during setup.
The device can also be manually added to iSponsorBlockTV with a YouTube TV code. This code can be found in the settings page of your YouTube application.It connects to the device, watches its activity and skips any sponsor segment using theSponsorBlockAPI.
It can also skip/mute YouTube ads.Libraries usedpyytloungeUsed to interact with the deviceasyncio andaiohttpasync-cacheTextualUsed for the amazing new graphical configuratorssdpUsed for auto discoveryProjects using this projectHome Assistant AddonContributingFork it (https://github.com/dmunozv04/iSponsorBlockTV/fork)Create your feature branch (git checkout -b my-new-feature)Commit your changes (git commit -am 'Add some feature')Push to the branch (git push origin my-new-feature)Create a new Pull RequestContributorsdmunozv04- creator and maintainerHaltCatchFire- updated dependencies and improved skip logicOxixes- added support for channel whitelist and minor improvementsLicense
Package: ispras-crisp
crispCoding Rules at ISPRead the docs (in Russian)here.Why this existsI'm tired of typingruff check <something>andblack <something>andchecking I'm in the right directory.I need a simple way to enforce a uniform coding style in many projects. Just install
this package and enjoy a carefully crafted set of coding rules being applied
automatically.I hate accidentially fixing somebody else's linting errors in my own commits so this
tool sees only filesyouhave modified. Faster than checking the entire codebase
once again as well.
Package: isp_tensors
isp-tensorsThis is a template repository for Python projects that use Poetry for their dependency management.Github repository:https://github.com/csaybar/isp-tensors/Documentationhttps://csaybar.github.io/isp-tensors/Getting started with your projectFirst, create a repository on GitHub with the same name as this project, and then run the following commands:gitinit-bmain
gitadd.
gitcommit-m"init commit"gitremoteaddorigingit@github.com:csaybar/isp-tensors.git
gitpush-uoriginmainFinally, install the environment and the pre-commit hooks withmakeinstallYou are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.To finalize the set-up for publishing to PyPi or Artifactory, seehere.
For activating the automatic documentation with MkDocs, seehere.
To enable the code coverage reports, seehere.Releasing a new versionCreate an API Token onPypi.Add the API Token to your projects secrets with the namePYPI_TOKENby visitingthis page.Create anew releaseon Github.Create a new tag in the form*.*.*.For more details, seehere.Repository initiated withfpgmaas/cookiecutter-poetry.
Package: isptools
ISPToolsEste genial paquete de herramientas de monitoreo te ofrece realizar de una forma muy facil el monitoreo de tu red
ISP, con esto puedes detectar si alguna ip que este fuera de tus colas esta consumiendo internet.DemoEntre las 4 herramientas tenemos:1°  Detectar ip e informacion del dispositivo actualEn esta opcion se obtienen los datos del ordenador donde se este ejecutando el programa:\
 De esta forma se optiene la ip y tambien el nombre del computador actual:2° Detectar dispositivo en un rango especifico:Para poder escanear los dispositivos en un rango especifico se debe ingresar una ip en la cual se desee obtener la informacion
automatiamente obtenemos el rango y comenzamos a hacer ping en un pool desde 1 a 255:\3° Hacer ping a una IPEn esta parte se hace ping a una unica ip que es especificada por el usuario, es muy parecido
a la parte anterior pero unicamente a una sola direccion IP4° Detectar puertos en una IP:Para la deteccion de los puertos uilizamos el modulo socket, con un rango de puertos de 1 hasta 65535
en los cuales unicamente los puertos abiertos seran mostrados en pantalla:Con esto finalizamos las herramientas disponibles en la version 1.0Author@David MacanchiSupportPara cualquier duda o recomendacion puedes escribirme a:dmmacanchi@utpl.edu.ec
Package: ispy2-mri
ispy2_mriTable of Contentsispy2_mriPurposeInstallationPrerequisitesProgram SetupLicenseDeveloper NotesPurposeThis package provide a graphical application to enter information about batches of MRI's as they come in from sites.  The information is saved in the ispy2 database, namedbreastdbon the server.  Some of that information is available electronically, and can be pulled from a plain text file of the user's choice instead of entered manually.This is a replacement foroneof the functions currently accessible through a web interface.  That web application can still be used for other things, like generating reports, or even for entering the same information.  However, the web application does not use the information in the plain text files.If you are not in UCSF Radiology, it is very unlikely this package is of interest.InstallationPrerequisitesOnly tested on MS-Windows, might work elsewhere if ODBC doesPython 3.10 or greater installed.  To test, start a terminal (hit the Windows button, type "command prompt", and select that application), and enterpy --versionin the terminal.64-bit ODBC installed with a recent MS SQL Server driver, e.g., 18.An ODBC data source ("DSN") namedbreastdb-newpointing to the breastdb database.You have permission to write to that database.The machine you are using can contact the database (may require firewall changes)You have access to the directory in which the text files summarizing key scan info are available.Program SetupThe main issue is exactly how you get access to the Python Package that uses the program.py -m pip install ispy2_mri  # MS-WindowsThis will create a program that can be launched from a terminal withispy2-mri.  You may want to create a desktop shortcut that will do the same thing.Licenseispy2-mriis distributed under the terms of theGPL-3license.Developer NotesThe application that ships is undersrc, but it is generated by the scripts underbuild.  Make any changes to the code inbuild, and then runpre_fields.pyto regeneratesrc/ispy2_mri/ispy2_gui.py.  Thepreis for pre-processor: the code turns the "specification" in tomcat web application's originalispy2.jsp(which came from theinsertdirectory of thebdbproject) into a Python-based Qt application.There is probably a way to automate that into the regular build process, which useshatch.  But its documentation doesn't spell out how.SeeNotes.mdfor the main developer notes, as well as comments in the code and the version control history.  In time, the issues for the project might have something as well.I do not recommend studying the code inispy2_gui.pydirectly as it has a lot of repetitive, automatically generated code.  And it does not have a lot of the notes and To Do list in the comments forpre_fields.py.
Package: ispyb-models
This provides a set ofSQLAlchemyORM models for theISPyB database.InstallationInstall from pypiispyb-models:pipinstallispyb-modelsBasic UsagefromispybimportmodelsdataCollection=models.DataCollection(...)ses.add(dataCollection)ses.commit()...datacollections=(ses.query(models.DataCollection).filter(models.DataCollection.dataCollectionId==1)).first())Generate a new versionTo update the models you need to run the workflowUpdate Modelsthrough GitHub Actions panel.
This will create a new branch with models matching the latest DB release and create a pull request for merge this branch into main. Before merging there are some things you need to do:Make sure py-ispyb tests still pass with these new modelsUpdateHISTORY.mdto reflect the changesBump version number withbump2version⚠️ Do not edit the output file yourselfThe resulting_auto_db_schema.pyshould not be edited(other than automatic
formatting withblackor sorting of imports withisort). All models are imported
into and accessed via the__init__.py. Any modifications, e.g. injecting additional
relationships between models should be done here.⚠️[for local test]Manually update the DB schemaCheckout the specific tag for a givenispyb-databaseversion:$gitclone-bv1.18.1https://github.com/ispyb/ispyb-database.git
$# or, if you have an existing copy of the repository:$gitcheckoutv1.18.1Apply the schema patch inpatches/circular_references.patchto avoid circular foreign key references:$patch-p1<ispyb-models/patches/circular_references.patchThen run theispyb-databasebuild.shscript to generate the database:$shbuild.shGenerate the models withsqlacodegeninsrc/ispyb/models/:.generate_models.sh
Package: ispyd
The ‘ispyd’ package provides an in process shell for introspecting a
running process. It was primarily intended for investigating running WSGI
application processes, specifically to determine what a process is doing
when it hangs, but has many other features as well. This includes being
able to start an embedded interactive Python interpreter session, set
debugger probe points to record tracebacks for exceptions and then later
run ‘pdb’ in post mortem mode on those exceptions.
Package: isqlab
Isqlab is a Python library for isQ.Key FeaturesisQ backend.Quantum Machine Learning. Connect to quantum device usingPyTorch.Gradient support.Quantum chemistry.InstallationIsqlab requires Python version 3.8 and above. Installation of isqlab can be done using:pip install isqlabGetting startedSee examples.AuthorsYusheng YangLicenseIsqlab isfreeandopen source, released under the MIT License.
Package: isqlite
WARNING: This project is no longer maintained. It is recommended that you use a proper ORM likeSQLAlchemyorDjango's ORMinstead.isqliteisqlite is an improved Python interface to SQLite. It has a more convenient API, support for schema diffing and migrations, and a command-line interface.fromisqliteimportDatabasewithDatabase(":memory:")asdb:pk=db.insert("employees",{"name":"John Doe","age":30})person=db.get_by_pk("employees",pk)print(person["name"],person["age"])db.update_by_pk("employees",pk,{"age":35})employees=db.select("employees",where="name LIKE :name_pattern AND age > 40",values={"name_pattern":"John%"},)pairs=db.sql("""SELECTteams.name, employees.nameFROMemployeesINNER JOINteamsONemployees.team = teams.id""")FeaturesA convenient Python APIDatabase migrations with automatic schema diffingA command-line interfaceInstallationInstall isqlite with Pip:$pipinstallisqliteDocumentationComprehensive documentation, including an API reference, is available athttps://isqlite.readthedocs.io/en/stable/.Version historyVersion 1.0.0 of isqlite was released on October 17, 2021, after six months of development. isqlite adheres tosemantic versioning, and detailed information about individual releases can be viewed in thechange log.
Package: isqopen
isq-qcis python corisQ-core是为qcis指令集定制化开发的量子编程语言，以python包的形式提供服务。目前isQ-core python包仍在测试阶段，可通过源码进行离线安装。具体的安装使用说明及isQ-core语法说明可详见isQ-core python包使用文档
Package: isqrt
Efficient pure-Python implementation of the integer square root function.PurposeGiven an arbitrarily large non-negative integern, theinteger square rootfunction finds the largest integerrsuch thatr**2<= nand(r +1)**2> n.The built-inmath.isqrtfunction was introduced in Python 3.8 and should normally be used instead of the function defined in this library.To provide the best performance possible while retaining backwards-compatible behavior for this library, the implementation in this library invokesmath.isqrtwhen it is available. Ifmath.isqrtis not available, this library attempts to usemath.sqrtand then (ifmath.sqrtdoes not produce the correct result or the input is outside the range supported bymath.sqrt) defaults to a pure-Python implementation in which the number of executed Python arithmetic operations is linear in the bit length of the input integer.Installation and UsageThis library is available as apackage on PyPI:python-mpipinstallisqrtThe library can be imported in the usual way:fromisqrtimportisqrtExamplesThe exported functionisqrtprovides a pure-Python implementation of theinteger square rootalgorithm:>>>isqrt(4)2>>>isqrt(16)4>>>list(map(isqrt,range(16,26)))[4,4,4,4,4,4,4,4,4,5]>>>isqrt(2**30000)==2**15000TrueDevelopmentAll installation and development dependencies are fully specified inpyproject.toml. Theproject.optional-dependenciesobject is used tospecify optional requirementsfor various development tasks. This makes it possible to specify additional options (such astest,lint, and so on) when performing installation usingpip:python-mpipinstall.[test,lint]Testing and ConventionsAll unit tests are executed and their coverage is measured when usingpytest(see thepyproject.tomlfile for configuration details):python-mpipinstall.[test]python-mpytestAlternatively, all unit tests are included in the module itself and can be executed usingdoctest:pythonsrc/isqrt/isqrt.py-vStyle conventions are enforced usingPylint:python-mpipinstall.[lint]python-mpylintsrc/isqrtAcknowledgmentsThe initial version of this function waspostedon Stack Overflow. Amore efficient versionwas implemented by Alexander Gosselin. The implementation in this package is adapted directly from these previous implementations.ContributionsIn order to contribute to the source code, open an issue or submit a pull request on theGitHub pagefor this library.VersioningBeginning with version 0.10.0, the version number format for this library and the changes to the library associated with version number increments conform withSemantic Versioning 2.0.0.PublishingThis library can be published as apackage on PyPIby a package maintainer. First, install the dependencies required for packaging and publishing:python-mpipinstall.[publish]Ensure that the correct version number appears in thepyproject.tomlfile. Create and push a tag for this version (replacing?.?.?with the version number):gittag?.?.?gitpushorigin?.?.?Remove any old build/distribution files. Then, package the source into a distribution archive:rm-rfbuilddistsrc/*.egg-infopython-mbuild--sdist--wheel.Finally, upload the package distribution archive toPyPI:python-mtwineuploaddist/*
Package: israel-rail-api
Israel Rail APIThis is a unofficial wrapping of the API of Israeli Rail network in Python.Use this script for checking your own train schedule, integrating with Alexa, and so on!InstallingTested with Python 3.11, should probably work fine with other versions too.pip install israel-rail-apiUsageimport israelrailapi
s = israelrailapi.TrainSchedule()
print(s.query('Tel Aviv University', 'Jerusalem Yitzhak Navon'))A simple test, to make sure the script is working is included inschedule.py:python3 schedule.py "tel aviv hahagana" "ben gurion airport" 2023-06-24 0900ContributingWe'd love your contributions! Fire up a (tested!) Pull request, and we'll be happy to approve it.
Package: isrcsubmit
This python script extractsISRCsfrom audio CDs
and submits them toMusicBrainz.This script uses python-musicbrainzngs to access the MusicBrainz API
and python-discid to create an identifier for the disc.The script works for Linux, Mac OS X and Windows.Features:read ISRCs from discsearch for releases with the TOC of the discdisplay release information from MusicBrainzsubmit ISRCssubmit discIds / TOCsduplicate ISRC detection (local and on server)Dependencies:Python 2 >= 2.6 or Python 3 >= 3.1python-discid>= 1.0.0 (orpython-libdiscid>= 0.2.0)python-musicbrainzngs>= 0.4keyring(optional)Usage:isrcsubmit.py [options] [username] [device]All arguments are optional. For detailed usage see:isrcsubmit.py -hWindows Usage:Windows users should use:isrcsubmit.batMac Usage:Mac users should rather use:isrcsubmit.shThis also works on Linux.Duplicate ISRCs:Some cd readers report the same ISRCs for different (adjacent) tracks.
Others don’t, for the same physical disc.
For me my dvd writer worked better.
On Windows the mediatools backend should give correct results either way.Isrcsubmit checks for problems with duplicate ISRCs and prints a warning.
You will always have the choice to cancel the submission if something
seems to be wrong.If the disc is known to MusicBrainz, additional information about it
is fetched from MusicBrainz.
If the disc is unknown, you will be given the chance to submit the ID
to the server.“Installation”:If you downloaded isrcsubmit as a zip package for your platform
then you only need to extract that somewhere and start using it.
You can also stop reading this section.You can install usingpypiwith:pip install isrcsubmitThis handles all python dependencies, but you still need to
install libdiscid (before running pip).The script itself does not need any installation,
but “python setup.py install” might work for you.
However, the backends and libraries should get
installed so that the script has access to them.On Linux you just install the above mentioneed dependencies with
the package manager of your distribution.
For Ubuntu all dependencies should be in the MusicBrainz Stable PPA,
if not in the official repositories.On Windows and Mac you have to put the musicbrainzngs folder of
python-musicbrainzngs, discid of python-discid in the same
directory as this script or adjust the python path.
You also need to put discid.dll (Windows) and libdiscid.dylib.0 (Mac)
into this location or in the PATH.Additional information:In order to submit ISRCs to musicbrainz.org you need to have a user acount.
You can create an account athttp://musicbrainz.org/registerfree of charge.The core of the MusicBrainz dataset including the ISRC contributions is placed
into the Public Domain.For a documentation of the available backends please refer to the manual
or theweb page.You might find additional information about this script at theMusicBrainz forums.Bugs:Please report bugs onGitHub.License:GNU General Public License Version 3 or later