Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.
You can contribute in many ways:
Types of Contributions¶
Report bugs at https://github.com/rnag/dataclass-wizard/issues.
If you are reporting a bug, please include:
Your operating system name and version.
Any details about your local setup that might be helpful in troubleshooting.
Detailed steps to reproduce the bug.
Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.
Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.
Dataclass Wizard could always use more documentation, whether as part of the official Dataclass Wizard docs, in docstrings, or even on the web in blog posts, articles, and such.
The best way to send feedback is to file an issue at https://github.com/rnag/dataclass-wizard/issues.
If you are proposing a feature:
Explain in detail how it would work.
Keep the scope as narrow as possible, to make it easier to implement.
Remember that this is a volunteer-driven project, and that contributions are welcome :)
Ready to contribute? Here’s how to set up dataclass-wizard for local development.
Fork the dataclass-wizard repo on GitHub.
Clone your fork locally:
$ git clone firstname.lastname@example.org:your_name_here/dataclass-wizard.git
Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
$ mkvirtualenv dataclass-wizard $ cd dataclass-wizard/ $ make init
Create a branch for local development:
$ git checkout -b name-of-your-bugfix-or-feature
Now you can make your changes locally.
When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:
$ make lint $ make test $ tox
To get flake8 and tox, just pip install them into your virtualenv.
Commit your changes and push your branch to GitHub:
$ git add . $ git commit -m "Your detailed description of your changes." $ git push origin name-of-your-bugfix-or-feature
Submit a pull request through the GitHub website.
Pull Request Guidelines¶
Before you submit a pull request, check that it meets these guidelines:
The pull request should include tests.
If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
The pull request should work for Python 3.6, 3.7, 3.8, 3.9 and 3.10, and for PyPy. Check https://github.com/rnag/dataclass-wizard/actions/workflows/dev.yml and make sure that the tests pass for all supported Python versions.
To run a subset of tests:
$ pytest tests/unit/test_dataclass_wizard.py::test_my_func
Tip: The last command below is used to push both the commit and the new tag to the remote branch simultaneously. There is also a simpler alternative as mentioned in this post, which involves running the following command:
$ git config --global push.followTags true
After that, you should be able to simply run the below command to push both the commits and tags simultaneously:
$ git push
A reminder for the maintainers on how to deploy. Make sure all your changes are committed (including an entry in HISTORY.rst). Then run:
$ bump2version patch # possible: major / minor / patch $ git push && git push --tags
GitHub Actions will then deploy to PyPI if tests pass.