https://github.com/chartbeat-labs/textacy

NLP, before and after spaCy
https://github.com/chartbeat-labs/textacy

natural-language-processing nlp python spacy

Last synced: 3 days ago
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NLP, before and after spaCy

• Host: GitHub
• URL: https://github.com/chartbeat-labs/textacy
• Owner: chartbeat-labs
• License: other
• Created: 2016-02-03T16:52:45.000Z (almost 9 years ago)
• Default Branch: main
• Last Pushed: 2023-09-22T23:38:28.000Z (over 1 year ago)
• Last Synced: 2025-01-16T05:05:21.139Z (10 days ago)
• Topics: natural-language-processing, nlp, python, spacy
• Language: Python
• Homepage: https://textacy.readthedocs.io
• Size: 31.4 MB
• Stars: 2,214
• Watchers: 87
• Forks: 249
• Open Issues: 35
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGES.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-nlp - textacy - 在spaCy上構建的更高級別的自然與儼處理。 (函式庫 / 書籍)
• awesome-python-machine-learning-resources - GitHub - 11% open · ⏱️ 06.03.2022): (文本数据和NLP)
• awesome-nlp-note - textacy - Higher level NLP built on spaCy (Libraries / Videos and Online Courses)
• awesome-list - textacy - a Python library for performing a variety of natural language processing tasks, based on spaCy. (Natural Language Processing / General Purpose NLP)

README

        
## 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

- Access and extend spaCy's core functionality for working with one or many documents through convenient methods and custom extensions

- Load prepared datasets with both text content and metadata, from Congressional speeches to historical literature to Reddit comments

- Clean, normalize, and explore raw text before processing it with spaCy

- Extract structured information from processed documents, including n-grams, entities, acronyms, keyterms, and SVO triples

- Compare strings and sequences using a variety of similarity metrics

- Tokenize and vectorize documents then train, interpret, and visualize topic models

- Compute text readability and lexical diversity statistics, including Flesch-Kincaid grade level, multilingual Flesch Reading Ease, and Type-Token Ratio

... *and much more!*

### links

- Download: https://pypi.org/project/textacy

- Documentation: https://textacy.readthedocs.io

- Source code: https://github.com/chartbeat-labs/textacy

- Bug Tracker: https://github.com/chartbeat-labs/textacy/issues

### maintainer

Howdy, y'all. 👋

- Burton DeWilde ()