It is a natural language processing library in an industry setting. So much so that there are other subprojects written with it.
Written in space. For extracting information from text, including grammatical elements: https://spacy.io/universe/project/lingfeat
A simple NLP package to clean up text data and text preprocessing. Simplifying Text Cleanup for NLP and ML https://pypi.org/project/neattext/
A network analysis-based algorithm: https://github.com/crabcamp/lexrank
Article: Güneş Erkan and Dragomir R. Radev: LexRank: Graph-based Lexical Centrality as Salience in Text Summarization.
A powerful algorithm that uses Facebook transformers but runs quite slowly, apart from text summarization, BM25 also includes a TF.IDF calculator. It also does translation and question creation. https://pypi.org/project/text2text/
A simple algorithm
For those who say it’s enough to do my job: https://towardsdatascience.com/simple-text-summarization-in-python-bdf58bfee77f
It also includes a sentiment tool, visualization and text creation tool: https://pypi.org/project/textcaret/
It’s a nice package that summarizes with algorithms like LexRank and TextRank: https://pypi.org/project/sumy/
It is a package for extracting semantic networks: https://spacy.io/universe/project/textnets/
Package for extracting negation elements https://github.com/jenojp/negspace
Extraction location names from the text