Contributing¶
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¶
Report bugs at https://github.com/hydrologie/xdatasets/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.
Fix Bugs¶
Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.
Implement Features¶
Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.
Write Documentation¶
xdatasets could always use more documentation, whether as part of the official xdatasets docs, in docstrings, or even on the web in blog posts, articles, and such.
Submit Feedback¶
The best way to send feedback is to file an issue at https://github.com/hydrologie/xdatasets/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. :)
Get Started!¶
Note
If you are new to using GitHub and git
, please read this guide first.
Warning
Anaconda Python users: Due to the complexity of some packages, the default dependency solver can take a long time to resolve the environment. Consider running the following commands in order to speed up the process:
conda install -n base conda-libmamba-solver
conda config --set solver libmamba
For more information, please see the following link: https://www.anaconda.com/blog/a-faster-conda-for-a-growing-community
Alternatively, you can use the mamba package manager, which is a drop-in replacement for conda
. If you are already using mamba, replace the following commands with mamba
instead of conda
.
Ready to contribute? Here’s how to set up xdatasets
for local development.
First, clone the
xdatasets
repo locally.If you are not a
xdatasets
collaborator, first fork thexdatasets
repo on GitHub, then clone your fork locally.git clone git@github.com:your_name_here/xdatasets.git
If you are a
xdatasets
collaborator, clone thexdatasets
repo directly.git clone git@github.com:hydrologie/xdatasets.git
Install your local copy into a development environment. You can create a new Anaconda development environment with:
conda env create -f environment-dev.yml conda activate xdatasets make dev
If you are on Windows, replace the
make dev
command with the following:python -m pip install -e .[dev] pre-commit install
This installs
xdatasets
in an “editable” state, meaning that changes to the code are immediately seen by the environment. To ensure a consistent coding style, make dev also installs thepre-commit
hooks to your local clone.On commit,
pre-commit
will check thatblack
,blackdoc
,isort
,flake8
, andruff
checks are passing, perform automatic fixes if possible, and warn of violations that require intervention. If your commit fails the checks initially, simply fix the errors, re-add the files, and re-commit.You can also run the hooks manually with:
pre-commit run -a
If you want to skip the
pre-commit
hooks temporarily, you can pass the –no-verify flag to git commit.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, we strongly suggest running the tests in your environment or with the help of
tox
:make lint python -m pytest # Or, to run multiple build tests python -m tox
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
If
pre-commit
hooks fail, try fixing the issues, re-staging the files to be committed, and re-committing your changes (or, if need be, you can skip them with git commit –no-verify).Submit a Pull Request through the GitHub website.
When pushing your changes to your branch on GitHub, the documentation will automatically be tested to reflect the changes in your Pull Request. This build process can take several minutes at times. If you are actively making changes that affect the documentation and wish to save time, you can compile and test your changes beforehand locally with:
# To generate the html and open it in your browser make docs # To only generate the html make autodoc make -C docs html # To simply test that the docs pass build checks python -m tox -e docs
If changes to your branch are made on GitHub, you can update your local branch with:
git checkout name-of-your-bugfix-or-feature git fetch git pull origin name-of-your-bugfix-or-feature
If you have merge conflicts, you might need to replace git pull with git merge and resolve the conflicts manually. Resolving conflicts from the command line can be tricky. If you are not comfortable with this, you can ignore the last command and instead use a GUI like PyCharm or Visual Studio Code to merge the remote changes and resolve the conflicts.
Before merging, your Pull Request will need to be based on the main branch of the
xdatasets
repository. If your branch is not up-to-date with the main branch, you can perform similar steps as above to update your branch:git checkout name-of-your-bugfix-or-feature git fetch git pull origin main
See the previous step for more information on resolving conflicts.
Once your Pull Request has been accepted and merged to the main branch, several automated workflows will be triggered:
The
bump-version.yml
workflow will automatically bump the patch version when pull requests are pushed to the main branch on GitHub. It is not recommended to manually bump the version in your branch when merging (non-release) pull requests (this will cause the version to be bumped twice).ReadTheDocs will automatically build the documentation and publish it to the latest branch of xdatasets documentation website.
If your branch is not a fork (i.e. you are a maintainer), your branch will be automatically deleted.
You will have contributed to xdatasets
!
Pull Request Guidelines¶
Before you submit a pull request, check that it meets these guidelines:
The pull request should include tests and should aim to provide code coverage for all new lines of code. You can use the –cov-report html –cov xdatasets flags during the call to
pytest
to generate an HTML report and analyse the current test coverage.All functions should be documented with docstrings following the numpydoc format.
If the pull request adds functionality, either update the documentation or create a new notebook that demonstrates the feature. Library-defining features should also be listed in
README.rst
.The pull request should work for all currently supported Python versions. Check the pyproject.toml or tox.ini files for the list of supported versions.
Tips¶
To run a subset of tests:
python -m pytest tests/test_xdatasets.py
You can also directly call a specific test class or test function using:
python -m pytest tests/test_xdatasets.py::TestClassName::test_function_name
For more information on running tests, see the pytest documentation.
To run specific code style checks:
python -m black --check src/xdatasets tests
python -m isort --check src/xdatasets tests
python -m blackdoc --check src/xdatasets docs
python -m ruff check src/xdatasets tests
python -m flake8 src/xdatasets tests
validate-docstrings src/xdatasets/**.py
To get black
, isort
, blackdoc
, ruff
, flake8
(with the flake8-rst-docstrings
plugin), and numpydoc
(for validate-docstrings
), simply install them with pip
(or conda
) into your environment.
Translations¶
If you would like to contribute to the French translation of the documentation, you can do so by running the following command:
make initialize-translations
This will create or update the French translation files in the docs/locales/fr/LC_MESSAGES directory. You can then edit the .po files in this directory to provide translations for the documentation.
Code of Conduct¶
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.