Metadata-Version: 2.1
Name: textacy
Version: 0.8.0
Summary: NLP, before and after spaCy
Home-page: https://github.com/chartbeat-labs/textacy
Maintainer: Burton DeWilde
Maintainer-email: burtdewilde@gmail.com
License: Apache
Download-URL: https://pypi.org/project/textacy
Keywords: textacy,spacy,nlp,text processing,linguistics
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Natural Language :: English
Classifier: Topic :: Text Processing :: Linguistic
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Description-Content-Type: text/markdown
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Requires-Dist: joblib (>=0.13.0)
Requires-Dist: networkx (>=1.11)
Requires-Dist: numpy (<2.0.0,>=1.9.0)
Requires-Dist: pyemd (>=0.3.0)
Requires-Dist: pyphen (>=0.9.4)
Requires-Dist: requests (>=2.10.0)
Requires-Dist: scipy (>=0.17.0)
Requires-Dist: scikit-learn (<0.21.0,>=0.18.0)
Requires-Dist: spacy (>=2.0.12)
Requires-Dist: srsly (>=0.0.5)
Requires-Dist: tqdm (>=4.11.1)
Requires-Dist: backports.csv (>=1.0.1) ; python_version=="2.7"
Provides-Extra: all
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Provides-Extra: viz
Requires-Dist: matplotlib (>=1.5.0) ; extra == 'viz'

## textacy: NLP, before and after spaCy

textacy is a Python library for performing a variety of natural language
processing (NLP) tasks, built on the high-performance spaCy library. With the
fundamentals --- tokenization, part-of-speech tagging, dependency parsing, etc. ---
delegated to another library, textacy focuses primarily on the tasks
that come before and follow after.

[![build status](https://img.shields.io/travis/chartbeat-labs/textacy/master.svg?style=flat-square)](https://travis-ci.org/chartbeat-labs/textacy)
[![current release version](https://img.shields.io/github/release/chartbeat-labs/textacy.svg?style=flat-square)](https://github.com/chartbeat-labs/textacy/releases)
[![pypi version](https://img.shields.io/pypi/v/textacy.svg?style=flat-square)](https://pypi.python.org/pypi/textacy)
[![conda version](https://anaconda.org/conda-forge/textacy/badges/version.svg)](https://anaconda.org/conda-forge/textacy)

### Features

- Convenient entry points to working with one or many documents processed by spaCy, with functionality added via custom extensions
- Variety of downloadable datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments
- Easy file I/O for streaming data to and from disk
- Cleaning, normalization, and exploration of raw text — before processing
- Flexible extraction of words, ngrams, noun chunks, entities, acronyms, key terms, and other elements of interest
- Tokenization and vectorization of documents, with functionality for training, interpreting, and visualizing topic models
- String, set, and document similarity comparison by a variety of metrics
- Calculations for common text statistics, including Flesch-Kincaid Grade Level and multilingual Flesch Reading Ease

... *and more!*


### Links

- PyPi project: https://pypi.org/project/textacy
- Source code: https://github.com/chartbeat-labs/textacy
- Documentation: https://chartbeat-labs.github.io/textacy


### Maintainer

Howdy, y'all. 👋

- Burton DeWilde (<burton@chartbeat.com>)


