pycantonese

PyCantonese: Cantonese Linguistics and NLP in Python

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Full Documentation: https://pycantonese.org

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PyCantonese is a Python library for Cantonese linguistics and natural language processing (NLP). Currently implemented features:

• Accessing and searching corpus data
• Parsing and conversion tools for Jyutping romanization
• Parsing Cantonese text
• Stop words
• Word segmentation
• Part-of-speech tagging

The design of PyCantonese prioritizes ease of use and linguistic knowledge. It has been successfully used by both academic and commercial organizations, including major US tech companies.

Since v4.0.0 (March 2026), PyCantonese depends on Rustling <https://rustling.io>_, a library for efficient CHAT data handling, word segmentation, and part-of-speech tagging.

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Download and Install

Using pip::

pip install --upgrade pycantonese

Using conda::

conda install -c conda-forge pycantonese

PyCantonese also works in JavaScript <https://docs.pycantonese.org/stable/quickstart.html#javascript>_.

Ready for more? Check out Quickstart <https://docs.pycantonese.org/stable/quickstart.html>_.

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Links

• Author: Jackson L. Lee <https://jacksonllee.com>_
• Source code: https://github.com/jacksonllee/pycantonese
• Social media: Facebook <https://www.facebook.com/pycantonese>_

How to Cite

Lee, Jackson L., Litong Chen, Charles Lam, Chaak Ming Lau, and Tsz-Him Tsui. 2022. PyCantonese: Cantonese Linguistics and NLP in Python <https://jacksonllee.com/papers/pycantonese_lrec_2022-05-06.pdf>_. Proceedings of the 13th Language Resources and Evaluation Conference.

… code-block:: latex

  @inproceedings{lee-etal-2022-pycantonese,
     title = "PyCantonese: Cantonese Linguistics and NLP in Python",
     author = "Lee, Jackson L.  and
        Chen, Litong  and
        Lam, Charles  and
        Lau, Chaak Ming  and
        Tsui, Tsz-Him",
     booktitle = "Proceedings of The 13th Language Resources and Evaluation Conference",
     month = jun,
     year = "2022",
     publisher = "European Language Resources Association",
  }

License

MIT License.

Please note that PyCantonese includes data from the following sources, all of which are permissively licensed:

• Hong Kong Cantonese Corpus (CC BY)
• CantoMap (GPL-3.0)
• rime-cantonese (CC BY 4.0)
• Common Voice Cantonese (Mozilla Public License 2.0)
• Cantonese-Traditional Chinese Parallel Corpus (CC0 1.0 Universal)

For details about these datasets, please see their documentation <https://github.com/jacksonllee/pycantonese/tree/main/src/pycantonese/data>_.

Logo

The PyCantonese logo is the Chinese character 粵 meaning Cantonese, with artistic design by albino.snowman (Instagram handle).

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