🚀 Big News: Socket Acquires Coana to Bring Reachability Analysis to Every Appsec Team.Learn more
Socket
Book a DemoInstallSign in
Socket

find-similar

Package Overview
Dependencies
Maintainers
0
Alerts
File Explorer

Advanced tools

Socket logo

Install Socket

Detect and block malicious and high-risk dependencies

Install

find-similar

User-friendly library to find similar objects

2.2.1
Source
PyPI
Maintainers
0

FindSimilar

User-friendly library to find similar objects

You can find Full Project Documentation here

Workflows

Tests Pylint

PyPi

Version Development Status Python version Wheel

Anaconda

Version Last Updated Platforms

License

License

Support

Documentation Discussions Issues

PyPi Downloads

Day Downloads Week Downloads Month Downloads

Anaconda Downloads

Anaconda

Languages

Languages Top Language

Development

  • Release date Last Commit
  • Issues Closed Issues
  • Pull Requests Closed Pull Requests
  • Discussions

Repository Stats

Stars Contributors Forks

Menu

Mission

The mission of the FindSimilar project is to provide a powerful and versatile open source library that empowers developers to efficiently find similar objects and perform comparisons across a variety of data types. Whether dealing with texts, images, audio, or more, our project aims to simplify the process of identifying similarities and enhancing decision-making.

Open Source Project

This is the open source project with MIT license. Be free to use, fork, clone and contribute.

Features

Find similar texts

  • on different languages
  • with or without stopwords
  • using dictionary (or not)
  • using keywords (or not)

Requirements

Development Status

Install

with pip

pip install find-similar

See more in Full Documentation

Quickstart

from find_similar import find_similar

texts = ['one two', 'two three', 'three four']

text_to_compare = 'one four'
find_similar(text_to_compare, texts, count=10)
[TokenText(text="one two", len(tokens)=2, cos=0.5), TokenText(text="three four", len(tokens)=2, cos=0.5), TokenText(text="two three", len(tokens)=2, cos=0)]
  • The result is the list of TokenText instances ordering by cos
  • cos is the mark of texts similarity

See more examples in Full Documentation

Contributing

You are welcome! To easy start please check:

Keywords

python

FAQs

Did you know?

Socket

Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.

Install

Related posts