Skip to main content

PyCantonese: Cantonese Linguistics and NLP in Python

Project description

Full Documentation: https://pycantonese.org


PyPI version Supported Python versions Build

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

  • Accessing and searching corpus data

  • Parsing and conversion tools for Jyutping romanization

  • Stop words

  • Word segmentation

  • Part-of-speech tagging

Quick Examples

With PyCantonese imported:

>>> import pycantonese as pc
  1. Word segmentation

>>> pc.segment("廣東話好難學?")  # Is Cantonese difficult to learn?
['廣東話', '好', '難', '學', '?']
  1. Conversion from Cantonese characters to Jyutping

>>> pc.characters_to_jyutping('香港人講廣東話')  # Hongkongers speak Cantonese
[("香港人", "hoeng1gong2jan4"), ("講", "gong2"), ("廣東話", "gwong2dung1waa2")]
  1. Finding all verbs in the HKCanCor corpus

    In this example, we search for the regular expression '^V' for all words whose part-of-speech tag begins with “V” in the original HKCanCor annotations:

>>> corpus = pc.hkcancor() # get HKCanCor
>>> all_verbs = corpus.search(pos='^V')
>>> len(all_verbs)  # number of all verbs
29012
>>> from pprint import pprint
>>> pprint(all_verbs[:10])  # print 10 results
[('去', 'V', 'heoi3', ''),
 ('去', 'V', 'heoi3', ''),
 ('旅行', 'VN', 'leoi5hang4', ''),
 ('有冇', 'V1', 'jau5mou5', ''),
 ('要', 'VU', 'jiu3', ''),
 ('有得', 'VU', 'jau5dak1', ''),
 ('冇得', 'VU', 'mou5dak1', ''),
 ('去', 'V', 'heoi3', ''),
 ('係', 'V', 'hai6', ''),
 ('係', 'V', 'hai6', '')]
  1. Parsing Jyutping for (onset, nucleus, coda, tone)

>>> pc.parse_jyutping('gwong2dung1waa2')  # 廣東話
[('gw', 'o', 'ng', '2'), ('d', 'u', 'ng', '1'), ('w', 'aa', '', '2')]

Download and Install

PyCantonese requires Python 3.6 or above. To download and install the stable, most recent version:

$ pip install --upgrade pycantonese

To test your installation in the Python interpreter:

>>> import pycantonese as pc
>>> pc.__version__  # show version number

How to Cite

PyCantonese is authored and mainteined by Jackson L. Lee.

A talk introducing PyCantonese:

Lee, Jackson L. 2015. PyCantonese: Cantonese linguistic research in the age of big data. Talk at the Childhood Bilingualism Research Centre, Chinese University of Hong Kong. September 15. 2015. Notes+slides

License

MIT License. Please see LICENSE.txt in the GitHub source code for details.

The HKCanCor dataset included in PyCantonese is substantially modified from its source in terms of format. The original dataset has a CC BY license. Please see pycantonese/data/hkcancor/README.md in the GitHub source code for details.

The rime-cantonese data (release 2020.09.09) is incorporated into PyCantonese for word segmentation and characters-to-Jyutping conversion. This data has a CC BY 4.0 license. Please see pycantonese/data/rime_cantonese/README.md in the GitHub source code for details.

Acknowledgments

Individuals who have contributed feedback, bug reports, etc. (in alphabetical order of last names if known):

  • @cathug

  • Litong Chen

  • Jenny Chim

  • @g-traveller

  • Rachel Han

  • Ryan Lai

  • Charles Lam

  • Hill Ma

  • @richielo

  • @rylanchiu

  • Stephan Stiller

  • Tsz-Him Tsui

Changelog

Please see CHANGELOG.md.

Setting up a Development Environment

The latest code under development is available on Github at jacksonllee/pycantonese. You need to have Git LFS installed on your system. To obtain this version for experimental features or for development:

$ git clone https://github.com/jacksonllee/pycantonese.git
$ cd pycantonese
$ git lfs pull
$ pip install -r dev-requirements.txt
$ pip install -e .

To run tests and styling checks:

$ pytest -vv --doctest-modules --cov=pycantonese pycantonese docs
$ flake8 pycantonese
$ black --check pycantonese

To build the documentation website files:

$ python build_docs.py

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pycantonese-3.1.1.tar.gz (3.9 MB view details)

Uploaded Source

Built Distribution

pycantonese-3.1.1-py3-none-any.whl (4.0 MB view details)

Uploaded Python 3

File details

Details for the file pycantonese-3.1.1.tar.gz.

File metadata

  • Download URL: pycantonese-3.1.1.tar.gz
  • Upload date:
  • Size: 3.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.8.3

File hashes

Hashes for pycantonese-3.1.1.tar.gz
Algorithm Hash digest
SHA256 806a0791a5d140c9d0c062a85cb3582e5ce3c887d0acba7ec090919a4e9ce86f
MD5 7253506c5561907575851448e7d76400
BLAKE2b-256 6ed17daf368b9091d06cdb0390e66313b8ea811680fe1061f215badafdf42583

See more details on using hashes here.

File details

Details for the file pycantonese-3.1.1-py3-none-any.whl.

File metadata

  • Download URL: pycantonese-3.1.1-py3-none-any.whl
  • Upload date:
  • Size: 4.0 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.48.0 CPython/3.8.3

File hashes

Hashes for pycantonese-3.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 067da4cd460cbff081883150e678b475ba89cd02d071bfe2f89cdefb52429816
MD5 48b3e14746217be84fac2dffe419553c
BLAKE2b-256 ab4e98fd2693e7f8dc3b02055ef2123a76f9095407960c677a8a11853fea697c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page