Natural Language Processing in Rust with Python bidings

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Project description

vtext

This is a Python wrapper for the Rust vtext crate.

This package aims to provide a high performance toolkit for ingesting textual data for machine learning applications.

The API is currently unstable.

Features

Tokenization: Regexp tokenizer, Unicode segmentation + language specific rules
Stemming: Snowball (in Python 15-20x faster than NLTK)
Token counting: converting token counts to sparse matrices for use in machine learning libraries. Similar to CountVectorizer and HashingVectorizer in scikit-learn but will less broad functionality.
Levenshtein edit distance; Sørensen-Dice, Jaro, Jaro Winkler string similarities

Installation

vtext requires Python 3.5+, numpy 1.15+ and can be installed with,

pip install --pre vtext

Documentation

Project documentation: vtext.io/doc/latest/index.html

License

vtext is released under the Apache License, Version 2.0.

Project details

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Release history Release notifications | RSS feed

0.2.0

Jun 15, 2020

This version

0.1.0a3 pre-release

Sep 5, 2019

0.1.0a2 pre-release

May 1, 2019

0.1.0a1 pre-release

Apr 28, 2019

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vtext-0.1.0a3-cp37-cp37m-win_amd64.whl (691.7 kB view hashes)

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