Thank you for being interested in contributing to
are awesome ✨.
This guideline contains information about our conventions around coding style, pull request workflow, commit messages and more.
This page also contains information to help you get started with development on this project.
Get the source code of this project using git:
git clone https://github.com/hankcs/HanLP --branch master cd HanLP pip install -e plugins/hanlp_trie pip install -e plugins/hanlp_common pip install -e plugins/hanlp_restful pip install -e .
To work on this project, you need Python 3.6 or newer.
This project has a test suite to ensure certain important APIs work properly. The tests can be run using:
python -m unittest discover ./tests
It’s hard to cover every API especially those of deep learning models, due to the limited computation resource of CI. However, we suggest all inference APIs to be tested at least.
This repository is a split into a few critical folders:
The HanLP core package, containing the Python code.
Contains codes shared across several individual packages or non core APIs.
The documentation for HanLP, which is in markdown format mostly.
The build configuration is contained in
Testing infrastructure that uses
unittestto ensure the output of API is what we expect it to be.
Contains Continuous-integration (CI) workflows, run on commits/PRs to the GitHub repository.