Saravanan666/pypi-org huggingface dataset:
Package: isavailable
😻 isavailableCan I haz this Python package onPyPI?Check if Python package names are available onPyPI.Usage$isavailablecheckswhetheryourdesiredpackagenameisavailableonpypi
isis…notavailable😭onPyPI.
onis…notavailable😭onPyPI.
youris…notavailable😭onPyPI.
nameis…available🎉onPyPI.
pypiis…notavailable😭onPyPI.
checksis…notavailable😭onPyPI.
whetheris…available🎉onPyPI.
desiredis…available🎉onPyPI.
packageis…notavailable😭onPyPI.
availableis…available🎉onPyPI.Installation$pipinstallisavailableHelp$isavailable--help
Usage:isavailable[OPTIONS]NAMES...CheckifalistofpackagenamesareavailableonPyPI.

Arguments:NAMES...[required]Options:--install-completion[bash|zsh|fish|powershell|pwsh]Installcompletionforthespecifiedshell.--show-completion[bash|zsh|fish|powershell|pwsh]Showcompletionforthespecifiedshell,tocopyitorcustomizetheinstallation.--helpShowthismessageandexit.
Package: is-bigger
is_biggerNormalfrom is_bigger.functions import *

isBigger(2,1) # True
isSmaller(2,1) # False
isEqual(3,3) # True
isNotBigger(3,1) # False
isNotSmaller(3,1) # True
isNotEqual(3,1) # TrueMachine Learning (slower and doesn't always work)from is_bigger.mlfunctions import *

ml_is_bigger(3,2) # True
ml_is_smaller(2,3) # True
ml_is_equal(1,1) # True
ml_is_not_bigger(2,2) # True
ml_is_not_smaller(3,2) # True
ml_is_not_equal(4,4) # False
Package: isbinary
Lightweight pure Python package to guess whether a file is binary or text,
using a heuristic similar to Perl’spp_fttextand its analysis by @eliben.Free software: BSD licenseDocumentation:https://isbinary.readthedocs.io/StatusIt works, and people are using this package in various places. But it doesn’t cover all edge cases yet.The code could be improved. Pull requests welcome! As of now, it is based on these snippets, but that may change:https://stackoverflow.com/questions/898669/how-can-i-detect-if-a-file-is-binary-non-text-in-pythonhttps://stackoverflow.com/questions/1446549/how-to-identify-binary-and-text-files-using-pythonhttps://code.activestate.com/recipes/173220/https://eli.thegreenplace.net/2011/10/19/perls-guess-if-file-is-text-or-binary-implemented-in-python/FeaturesHas tests for these file types:Text: .txt, .css, .json, .svg, .js, .lua, .pl, .rstBinary: .png, .gif, .jpg, .tiff, .bmp, .DS_Store, .eot, .otf, .ttf, .woff, .rgbHas tests for numerous encodings.Why?You may be thinking, “I can write this in 2 lines of code?!”It’s actually not that easy. Here’s a great article about how Perl’s
heuristic to guess file types works:https://eli.thegreenplace.net/2011/10/19/perls-guess-if-file-is-text-or-binary-implemented-in-python/And that’s just where we started. Over time, we’ve found more edge cases and
our heuristic has gotten more complex.Also, this package saves you from having to write and thoroughly test
your code with all sorts of weird file types and encodings, cross-platform.HistoryThis is a long-term fork ofbinaryornot. It was created in
May 2022 primarily because it appeared that upstream had been abandoned. There were a few other smaller issues:Lack of type annotations.Lack of stricter modern code quality tools used in CI.Improved contributor experience by using Github Actions for CI.Possibility for optimisation with optional dependency oncchardet.Removal of Python 2 support, and explicit support for newer versions of Python 3.CreditsAudrey and Danny Roy Greenfeld, as the previous maintainers of this code.Special thanks to Eli Bendersky (@eliben) for his writeup explaining the heuristic and his implementation, which this is largely based on.Source code from the portion of Perl’spp_fttextthat checks for textiness:https://github.com/Perl/perl5/blob/v5.23.1/pp_sys.c#L3527-L3587
Package: isb-miner3
minermechanistic inference of node-edge relationshipsDocker imageyou can access a Docker image with a full MINER installation at  Docker Hub with the nameweiju/isb-miner3$ docker pull weiju/isb-miner3Tools documentationPlease see command line documentation athttps://baliga-lab.github.io/miner3/tutorial informationA template with instructions and code for performing a miner analysis is provided in the miner/src directory.The template can be opened using Anaconda by selecting jupyter notebook from the user interface, or by simply typing "jupyter notebook" into the command line.what you need to get startedBefore the miner analysis can be performed, the gene expression data to be analyzed must be added to the miner/data directory. Ensure that your expression data is of the form log2(TPM+1) or log2(FPKM+1).If survival analysis is desired, a survival file must added to the miner/data directoryIf causal analysis is desired, a mutation file must added to the miner/data directorywhere to put your dataminer will search for specific filenames in the miner/data folder. Be sure to update the lines that read your files with the appropriate paths and filenames. Consider using the following names for consistency:
1. Name your expression data "expressionData.csv"
2. Name your mutation data "mutations.csv" (only for causal analysis)
3. Name your survival data "survival.csv" (only for survival analysis)Note that the gene names will be converted to Ensembl Gene ID formatcommon mistakes to avoidminer does not yet support expression data in counts format. Ensure that data is in log2(TPM+1) or log2(FPKM+1) format.mechanistic inference includes a step that enforces a minimum correlation coefficient. If your results seem too sparse, try decreasing the minCorrelation parameter.
Package: isbn_hyphenate
isbn_hyphenate is a Python library to add hyphens in the right place to an ISBN (International Standard Book Number). Example:>>> import isbn_hyphenate
>>> isbn_hyphenate.hyphenate("9781590593561")
'978-1-59059-356-1'Most libraries for handling ISBNs can not do hyphenation because it requires using a list of prefixes, available from the International ISBN Agency.isbn_hyphenate can handle both 10 and 13 digit ISBNs, and will keep the number of digits.
If the ISBN is malformed (wrong length or invalid characters) an IsbnMalformedError exception is raised.
If the correct hyphen positions cannot be determined, an IsbnUnableToHyphenateError exception is raised.
This can mean that the input ISBN is wrong, or it is in a range that is not yet in the known list.isbn_hyphenate is compatible with both Python 2 and 3.To update the prefix list:Download a new RangeMessage.xml file fromhttps://www.isbn-international.org/range_file_generationConvert it to Python format: ./isbn_xml2py.py RangeMessage.xml > isbn_lengthmaps.pyThese alternative Python libraries can also hyphenate:python-stdnumhttp://pypi.python.org/pypi/python-stdnumisbnidhttp://code.google.com/p/isbnid/
Package: isbnlib-bnf
A metadata plugin forisbnlib(https://pypi.python.org/pypi/isbnlib) using the service BnF Catalogue Général (for books in french).To install, from the command line, enter (in some cases you have to precede the command withsudo):$pipinstallisbnlib-bnfAfter install, a new metadata provider (bnf) is available in isbnlib.For available pluginscheckhere.
Package: isbnlib-dnb
A metadata plugin forisbnlib(https://pypi.python.org/pypi/isbnlib) using the service from the Deutsche National Bibliothek of Germany (https://portal.dnb.de/opac.htm) for books in German.After install (pip install isbnlib-dnb) a new metadata provider (dnb) is available in isbnlib.For available pluginscheckhere.
Package: isbnlib-sbn
A metadata plugin forisbnlib(https://pypi.python.org/pypi/isbnlib) using the service from the Servizio Bibliotecario Nazionale (Italy) (https://opac.sbn.it/) for books in Italian.After install (pip install isbnlib-sbn) a new metadata provider (sbn) is available in isbnlib.For available pluginscheckhere.
Package: isbn_validator
IntroductionThis module provides basic API for validation of the ISBN-10 and ISBN-13
numbers. It can also compute the checksum digits for incomplete numbers.DocumentationFull module documentation and description can be found at Read the Docs:http://isbn_validator.readthedocs.org/ContributorsBystroushaak <bystrousak@kitakitsune.org>, DeveloperChangelog1.0.0Project created.
Package: is-bot
is-botPython package to detect bots/crawlers/spiders via user-agent string.
This is a port of theisbotJavaScript module.RequirementsPython >= 3.7regex >= 2022.8.17Installationpip install is-botUsageSimple usagefromis_botimportBotsbots=Bots()ua='Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; Googlebot/2.1; +http://www.google.com/bot.html) Chrome/104.0.5112.79 Safari/537.36'assertbots.is_bot(ua)ua='Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.0.0 Safari/537.36'assertnotbots.is_bot(ua)Add/remove parsing rulesfromis_botimportBotsbots=Bots()# Exclude Chrome-Lighthouse from default bot listua='Mozilla/5.0 (Linux; Android 7.0; Moto G (4)) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4695.0 Mobile Safari/537.36 Chrome-Lighthouse'assertbots.is_bot(ua)bots.exclude(['chrome-lighthouse'])assertnotbots.is_bot(ua)# Add some browser to default bot listua='SomeAwesomeBrowser/10.0 (Linux; Android 7.0)'assertnotbots.is_bot(ua)bots.extend(['SomeAwesomeBrowser'])assertbots.is_bot(ua)Get additional parsing informationfromis_botimportBotsbots=Bots()ua='Mozilla/5.0 (X11; Linux x86_64; rv:52.0) Gecko/20100101 Firefox/52.0 SearchRobot/1.0'# view the respective match for bot user agent ruleprint(bots.find(ua))#> Search# list all patterns that match the user agent stringprint(bots.matches(ua))#> ['(?<! (ya|yandex))search', '(?<! cu)bot']
Package: isbtchot
isbtchot: BTC Hotness Index DashboardTheisbtchotpackage provides a minimalist terminal dashboard for BTC's hotness index. It uses historical BTC data to create both BTC's price and Hotness Index visualizations right in your terminal.DemoFeatures:BTC monthly candlestick plot with log scale.Hotness index based on PI with buy/sell signals.Data is cached to speed up subsequent requests.InstallationpipinstallisbtchotUsageYou can run the main dashboard with:isbtchot[-periods_backP][-timeT]-periods_backor--p: Specifies the number of periods (e.g., weeks, months) of data you want to visualize. By default, it uses 85 periods.-timeor--t: Specifies the candlestick time to use (e.g., Daily, Weekly). By default, it uses Weekly.Command Line ArgumentsArgumentShort FormDescriptionDefault--periods_back-pNumber of periods to be processed.85--time-tCandlestick time to use (e.g., D for Daily, W for Weekly).WNotesEnsure the terminal window is maximized for optimal visualization.Data is fetched from CryptoCompare API and cached locally for performance.ContributionsPlease raise an issue or provide a pull request for any enhancements, bug fixes or features you'd like to add.
Package: iscc
ISCC - Spec and Reference CodeTheInternational Standard Content Codeis a proposal for anopen standardfor decentralized content identification. This repository contains the specification of the proposedISCC Standardand a reference implementation in Python3. The latest published version of the specification can be found atiscc.codesNOTE: This is a low level reference implementation. For easy generation of ISCC codes see:iscc-cliInstalling the reference codeThe reference code is published with the package nameisccon Python Package Index. Install it with:pipinstallisccUsing the reference codeA short example on how to create an ISCC Code with the reference implementation.importiscc# Generate ISCC Component Codesmid,title,extra=iscc.meta_id('Title of Content')cid=iscc.content_id_text('some text')did=iscc.data_id('path/to/mediafile.doc')iid,tophash=iscc.instance_id('path/to/mediafile.doc')# Join ISCC Components to fully qualified ISCC Codeiscc_code='-'.join([mid,cid,did,iid])print('ISCC:{}'.format(iscc_code))Working with the specificationThe entireISCC Specificationis written in plain textMarkdown. The markdown content is than built and published with the excellentmkdocsdocumetation tool. If you have some basic command line skills you can build and run the specification site on your own computer. Make sure you have thegitandPythoninstalled on your system and follow these steps on the command line:gitclonehttps://github.com/iscc/iscc-specs.gitcdiscc-specs
pipinstall-rrequirements.txt
mkdocsserveAll specification documents can be found in the./docssubfolder or the repository. The recommended editor for the markdown files isTypora. If you have commit rights to themain repositoryyou can deploy the site with a simplemkdocs gh-deploy.ContributePull requests and other contributions are welcome. Use theGithub Issuessection of this project to discuss ideas for theISCC Specification. You may also want  join our developer chat on Telegram athttps://t.me/iscc_dev.LicenseAll of documentation is licensed under theCC-BY-SA 4.0.Reference code is licensed under BSD-2-Clause.
Package: iscc-index
iscc-index - ISCC Nearest Neighbor SearchA REST OpenAPI Backend for indexingISCC codesfor digital media files.The Webservice is build withFastAPIand makes
use of theISCC reference implementation.
It includes an interactive API documentation:The Docker image is published athttps://hub.docker.com/r/titusz/iscc-indexInstall via pip$pip3installiscc-indexStart webservice via uvicorn$iscc-index
INFO:Startedserverprocess[18800]INFO:Waitingforapplicationstartup.
INFO:Applicationstartupcomplete.
INFO:Uvicornrunningonhttp://127.0.0.1:8090(PressCTRL+Ctoquit)Setup for developmentIf you are usingpoetry:After checkout cd into code directory and run 'poetry install' to install dependencies.Launch dev server with: 'uvicorn iscc_index.main:app --reload' or 'icscc-index'See API docs at:http://127.0.0.1:8090LicenseMIT © 2021 Titusz Pan
Package: iscc-samples
Test data for ISCCInstallation$pipinstalliscc-samplesUsage:importiscc_samplesassamplesforpathinsamples.videos():print(path)DevelopmentMaking a release$poetrybuild-fsdist$poetrypublishMaintainers@tituszContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.You may also want join our developer chat on Telegram athttps://t.me/iscc_dev.Change Log[0.6.0] - 2023-03-11Add more audio examples (WavPack, AAC, AC3, Opus)[0.5.0] - 2022-12-09Add MP3 file with cover artUpdate dependencies[0.4.0] - 2021-03-14Add consistent title metadata to text documentsAdd support to filter files by file extension[0.3.0] - 2021-02-17Add powerpoint sample files[0.2.0] - 2021-01-25Add iscc_samples.all()Return files in sorted order[0.1.0] - 2021-01-25Initial release with basic sample filesLicenseCC-BY-4.0 © 2021 Titusz Pan
Package: iscc-sci
ISCC - Semantic Image-Codeiscc-sciis aproof of concept implementationof a semantic Image-Code for theISCC(International Standard Content Code). Semantic Image-Codes are
designed to capture and represent the semantic content of images for improved similarity detection.[!CAUTION]
This is an early proof of concept. All releases with release numbers below v1.0.0 may
break backward compatibility and produce incompatible Semantic Image-Codes.What is ISCC Semantic Image-CodeThe ISCC framework already comes with an Image-Code that is based on perceptual hashing and can
match near duplicates. The ISCC Semantic Image-Code is planned as a new additional ISCC-UNIT focused
on capturing a more abstract and broad semantic similarity. As such the Semantic Image-Code is
engineered to be robust against a broader range of variations that cannot be matched with the
perceptual Image-Code.FeaturesSemantic Similarity: Leverages deep learning models to generate codes that reflect the
semantic content of images.Bit-Length Flexibility: Supports generating codes of various bit lengths (up to 256 bits),
allowing for adjustable granularity in similarity detection.ISCC Compatible: Generates codes that are fully compatible with the ISCC specification,
facilitating integration with existing ISCC-based systems.InstallationBefore you can installiscc-sci, you need to have Python 3.8 or newer installed on your system.
Install the library as any other python package:pipinstalliscc-sciUsageTo generate a Semantic Image-Code for an image, use thecode_image_semanticfunction. You can
specify the bit length of the code to control the level of granularity in the semantic
representation.importiscc_sciassci# Generate a 64-bit ISCC Semantic Image-Code for an image fileimage_file_path="path/to/your/image.jpg"semantic_code=sci.code_image_semantic(image_file_path,bits=64)print(semantic_code)How It Worksiscc-sciuses a pre-trained deep learning model based on the 1st Place Solution of the Image
Similarity Challenge (ISC21) to create semantic embeddings of images. The model generates a feature
vector that captures the essential characteristics of the image. This vector is then binarized to
produce a Semantic Image-Code that is robust to variations in image presentation but sensitive to
content differences.DevelopmentThis is a proof of concept and welcomes contributions to enhance its capabilities, efficiency, and
compatibility with the broader ISCC ecosystem. For development, you'll need to install the project
in development mode usingPoetry.gitclonehttps://github.com/iscc/iscc-sci.gitcdiscc-sci
poetryinstallContributingContributions are welcome! If you have suggestions for improvements or bug fixes, please open an
issue or pull request. For major changes, please open an issue first to discuss what you would like
to change.
Package: iscc-sdk
ISCC - Software Development Kitiscc-sdkis a Python development kit for creating and managingISCC(International Standard Content Code)What is an ISCCThe ISCC is a similarity preserving identifier for digital media assets.ISCCs are generated algorithmically from digital content, just like cryptographic hashes. However,
instead of using a single cryptographic hash function to identify data only, the ISCC uses various
algorithms to create a composite identifier that exhibits similarity-preserving properties (soft
hash).The component-based structure of the ISCC identifies content at multiple levels of abstraction. Each
component is self-describing, modular, and can be used separately or with others to aid in various
content identification tasks. The algorithmic design supports content deduplication, database
synchronization, indexing, integrity verification, timestamping, versioning, data provenance,
similarity clustering, anomaly detection, usage tracking, allocation of royalties, fact-checking and
general digital asset management use-cases.What isiscc-sdkiscc-sdkis built on top ofiscc-coreand adds high level features for generating and handling
ISCC codes for all the different mediatypes:mediatype detectionmetadata extraction and embeddingmediatype specific content extraction and pre-processingiscc indexing and searchRequirementsPython 3.8 to 3.11 on 64-bit systemsInstallationUse the Python package managerpipto installiscc-sdk.pipinstalliscc-sdkGetting StartedCreate an ISCC-CODE for a media file:importiscc_sdkasidkprint(idk.code_iscc("/path/to/mediafile.jpg"))Using the CLI tool to create an ISCC-CODEidkcreate/path/to/mediafile.jpgBatch creation of ISCC-CODEsidkbatch/folder_with_media_filesDocumentationhttps://sdk.iscc.codesTroubleshootingOn Linux and MacOS you might need to install taglib as a prerequisite. On Ubuntu, Mint and other
Debian-Based distributions do:sudoaptinstalllibtag1-devOn a Mac, use HomeBrew:brewinstalltaglibProject StatusThe ISCC has been accepted by ISO as full work item ISO/AWI 24138 - International Standard Content
Code and is currently being standardized at TC 46/SC 9/WG 18.https://www.iso.org/standard/77899.html!!! attention
Theiscc-sdklibrary and the accompanying documentation is under development. API changes and
other backward incompatible changes are to be expected until the upcoming v1.5 stable release.Maintainers@tituszContributingPull requests are welcome. For significant changes, please open an issue first to discuss your
plans. Please make sure to update tests as appropriate.You may also want join our developer chat on Telegram athttps://t.me/iscc_dev.
Package: iscc-service
iscc-service - ISCC Web Service APIA REST OpenAPI Backend for creatingISCC codesfor digital media files.Note: This is work in progress. Use with care and at your own riskThe Webservice is build withFastAPIand makes
use of theISCC reference implementationand
theISCC Command Line Tooland includes an
interactive API documentation:The Docker image is published athttps://hub.docker.com/r/titusz/iscc-serviceSetup for developmentIf you are usingpoetry:After checkout cd into code directory and run 'poetry install' to install dependencies.Launch dev server with: 'uvicorn iscc_service.main:app --reload'See API docs at:http://127.0.0.1:8000For the 'lookup' endpoint to work you must provide env variables for node connection.
Seeconfig.pyInstall via pip$pip3installiscc-serviceRun webservice via uvicorn$isccservice
INFO:Startedserverprocess[18800]INFO:Waitingforapplicationstartup.
INFO:Applicationstartupcomplete.
INFO:Uvicornrunningonhttp://127.0.0.1:8000(PressCTRL+Ctoquit)Publishing on Docker HUB:dockerlogin
dockerbuild-tiscc-service-fDockerfile.
dockerrun--rm-p8080:8080-itiscc-service
dockertagiscc-serviceusername/iscc-service:0.1.9
dockerpushusername/iscc-service:0.1.9Change Log[0.2.3] - 2020-06-12Use vendorized tika[0.2.2] - 2020-06-12Update to iscc-cli 0.9.11[0.2.1] - 2020-05-13Update to iscc-cli 0.9.8More conservative lookup matching[0.2.0] - 2020-05-01Update to support flac and opus audio files[0.1.9] - 2020-04-27Support updated Content-ID AudioSupport incomplete ISCC codesUpdated dependencies[0.1.8] - 2020-03-02Add support for mobi filesInitial pypi releaseLicenseMIT © 2019-2020 Titusz Pan
Package: iscontain
iscontain基于python3.10，判断A是否为B子集
It can check if A is a subset of B
base on python 3.10usage支持有序与无序两种模式，支持列表，元组，字符串
It supports both ordered and disordered modes
Types such as list tuple strings are also supporteddisorderfromiscontainimportiscontainl1=[2,4]l2=[2,3,4,5,4,6]print(iscontain(l1,l2))#Trueorderfromiscontainimportiscontainl1=[2,4]l2=[2,3,4,5,4,6]print(iscontain(l1,l2,accurate=True))#Falsel1=[4,5,4]l2=[2,3,4,5,4,6]print(iscontain(l1,l2,accurate=True))#True
Package: iscool_e.bellman
IsCool Entertainment Bellman SDK (Pushd Python SDK)This client library is designed to support thePushd API.Pushd is an unified pushd server for server-side notification to mobile native apps, web apps etc. You can read more about Pushd on the link above.RequirementsThis library relies onRequestssince version 0.3.Why Bellman ?The alert sound when receiving a mobile notification is reminiscent to the officer of the court who made public announcements in the streets, back to the Middle Ages.UsageImport the library and instanciate the API class:from iscool_e.bellman import pushd

api = pushd.API('127.0.0.1')
api.create_subscriber('apns', 'token')
api.subscribe('id', 'event_name')
api.send_message('event_name', 'Hello World!')LicenseThis package is released under the MIT License.
Please see LICENSE document for a full description.News0.1Release date: 27-Jan-2014First release0.2Release date: 28-Jan-2014Remove custom method getStats and fix github url0.2.1Release date: 28-Jan-2014Add missing socket import0.3Release date: 29-Jan-2014Use python RequestsFix batch event subscriptions0.4Release date: 3-Mar-2014This release breaks compatibility with previous versions:Remove ugly camelcase function names0.4.1Release date: 3-Mar-2014Update usage on README file