Metadata-Version: 2.1
Name: vtext
Version: 0.2.0
Summary: Natural Language Processing in Rust with Python bidings
Home-page: https://github.com/rth/vtext
License: Apache License 2.0
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: setuptools
Requires-Dist: setuptools-rust (>=0.10.2)
Requires-Dist: numpy (>=1.15.0)
Requires-Dist: scipy (>=1.1.0)

# 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.

### 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 3.6+, numpy 1.15+ and can be installed with,

```
pip install vtext
```

### Documentation

Project documentation: [vtext.io/doc/latest/index.html](https://vtext.io/doc/latest/index.html)


## License

vtext is released under the [Apache License, Version 2.0](./LICENSE).


