<commit_before>gensim – Topic Modelling in Python
==================================

[![Build Status](https://travis-ci.org/RaRe-Technologies/gensim.svg?branch=develop)](https://travis-ci.org/RaRe-Technologies/gensim)
[![GitHub release](https://img.shields.io/github/release/rare-technologies/gensim.svg?maxAge=3600)](https://github.com/RaRe-Technologies/gensim/releases)
[![Downloads](https://img.shields.io/pypi/dm/gensim?color=blue)](https://pepy.tech/project/gensim/month)
[![DOI](https://zenodo.org/badge/DOI/10.13140/2.1.2393.1847.svg)](https://doi.org/10.13140/2.1.2393.1847)
[![Mailing List](https://img.shields.io/badge/-Mailing%20List-blue.svg)](https://groups.google.com/forum/#!forum/gensim)
[![Follow](https://img.shields.io/twitter/follow/gensim_py.svg?style=social&style=flat&logo=twitter&label=Follow&color=blue)](https://twitter.com/gensim_py)

Gensim is a Python library for *topic modelling*, *document indexing*
and *similarity retrieval* with large corpora. Target audience is the
*natural language processing* (NLP) and *information retrieval* (IR)
community.

<!--
## :pizza: Hacktoberfest 2019 :beer:
<commit_msg>Cache badges<commit_after>gensim – Topic Modelling in Python
==================================

[comment]: # (The following image URLs are obfuscated = proxied and cached through Google because of:
              https://github.com/RaRe-Technologies/gensim/issues/2805 )

[![Build Status](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=3600&url=https%3A%2F%2Ftravis-ci.org%2FRaRe-Technologies%2Fgensim.svg%3Fbranch%3Ddevelop)](https://travis-ci.org/RaRe-Technologies/gensim)
[![GitHub release](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=3600&url=https%3A%2F%2Fimg.shields.io%2Fgithub%2Frelease%2Frare-technologies%2Fgensim.svg%3FmaxAge%3D3600)](https://github.com/RaRe-Technologies/gensim/releases)
[![Downloads](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=86400&url=https%3A%2F%2Fimg.shields.io%2Fpypi%2Fdm%2Fgensim%3Fcolor%3Dblue)](https://pepy.tech/project/gensim/month)
[![DOI](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=604800&url=https%3A%2F%2Fzenodo.org%2Fbadge%2FDOI%2F10.13140%2F2.1.2393.1847.svg)](https://doi.org/10.13140/2.1.2393.1847)
[![Mailing List](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=604800&url=https%3A%2F%2Fimg.shields.io%2Fbadge%2F-Mailing%2520List-blue.svg)](https://groups.google.com/forum/#!forum/gensim)
[![Follow](https://images1-focus-opensocial.googleusercontent.com/gadgets/proxy?container=focus&refresh=604800&url=https%3A%2F%2Fimg.shields.io%2Ftwitter%2Ffollow%2Fgensim_py.svg%3Fstyle%3Dsocial%26style%3Dflat%26logo%3Dtwitter%26label%3DFollow%26color%3Dblue)](https://twitter.com/gensim_py)

Gensim is a Python library for *topic modelling*, *document indexing*
and *similarity retrieval* with large corpora. Target audience is the
*natural language processing* (NLP) and *information retrieval* (IR)
community.

<!--
## :pizza: Hacktoberfest 2019 :beer:

{'fraction_non_alphanumeric': 0.18740157480314962, 'fraction_numerical': 0.05889763779527559, 'mean_word_length': 7.701369863013698, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 3, 'https://': 25, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1607707', 'n_tokens_mistral': 1294, 'n_tokens_neox': 1159, 'n_words': 112}