Contribution Guide#
Contributions are highly welcomed and appreciated. Every little help counts,
so do not hesitate! You can make a high impact on climpred
just by using
it and reporting issues.
The following sections cover some general guidelines
regarding development in climpred
for maintainers and contributors.
Please also review our Code of Conduct.
Nothing here is set in stone and can’t be changed. Feel free to suggest improvements or changes in the workflow.
Feature requests and feedback#
We are eager to hear about your requests for new features and any suggestions
about the API, infrastructure, and so on. Feel free to submit these as
issues with the label
"feature request"
.
Please make sure to explain in detail how the feature should work and keep the scope as narrow as possible. This will make it easier to implement in small PRs.
Report bugs#
Report bugs for climpred
in the
issue tracker with the
label “bug”.
If you are reporting a bug, please include:
Any details about your local setup that might be helpful in troubleshooting, specifically the Python interpreter version, installed libraries, and
climpred
version.Detailed steps to reproduce the bug.
If you can write a demonstration test that currently fails but should pass, that is a very useful commit to make as well, even if you cannot fix the bug itself.
Bug Fix#
Look through the GitHub issues for bugs.
Talk to developers to find out how you can fix specific bugs.
Write documentation#
climpred
could always use more documentation. What exactly is needed?
More complementary documentation. Have you perhaps found something unclear?
Example notebooks with different Earth System Models, lead times, etc. – they’re all very appreciated.
You can also edit documentation files directly in the GitHub web interface, without using a local copy. This can be convenient for small fixes.
Our documentation is written in reStructuredText. You can follow our conventions in already written documents. Some helpful guides are located rst-quickref and rst-cheatsheet.
Note
Build the documentation locally with the following command:
$ conda env update -f ci/requirements/climpred-dev.yml
$ cd docs
$ make html
The built documentation should be available in the docs/build/
.
If you need to add new functions to the API, run
sphinx-autogen -o api api.rst
from the docs/source
directory after
adding functions to api.rst
.
Preparing Pull Requests#
Fork the climpred GitHub repository. It’s fine to use
climpred
as your fork repository name because it will live under your user.Clone your fork locally using git, connect your repository to the upstream (main project), and create a branch:
$ git clone git@github.com:YOUR_GITHUB_USERNAME/climpred.git $ cd climpred $ git remote add upstream git@github.com:pangeo-data/climpred.git # now, to fix a bug or add feature create your own branch off "main": $ git checkout -b your-bugfix-feature-branch-name main
If you need some help with Git, follow this quick start guide.
Install dependencies into a new conda environment:
$ conda env create -f ci/requirements/climpred-dev.yml $ conda activate climpred-dev
Make an editable install of
climpred
by running:$ pip install -e .
Install pre-commit and its hook on the
climpred
repo:$ pip install --user pre-commit $ pre-commit install
pre-commit
automatically beautifies the code, makes it more maintainable and catches syntax errors. Afterwardspre-commit
will run whenever you commit.Now you have an environment called
climpred-dev
that you can work in. You’ll need to make sure to activate that environment next time you want to use it after closing the terminal or your system.You can now edit your local working copy and run/add tests as necessary. Please try to follow PEP-8 for naming. When committing,
pre-commit
will modify the files as needed, or will generally be quite clear about what you need to do to pass the commit test.pre-commit
also runs:* `mypy <http://mypy-lang.org/>`_ for static type checking on `type hints <https://docs.python.org/3/library/typing.html>`_. * `isort <https://pycqa.github.io/isort/>`_ sorting imports * `black <https://black.readthedocs.io/en/stable/>`_ code formatting * `flake8 <https://flake8.pycqa.org/en/latest/>`_ code linting * `blackdoc <https://blackdoc.readthedocs.io/en/latest/>`_ docstring code formatter
Break your edits up into reasonably sized commits:
$ git commit -a -m "<commit message>" $ git push -u
Run all tests
Once commits are pushed to
origin
, GitHub Actions runs continuous integration of all tests on all new commits. However, you are already run tests locally:$ pytest climpred
Check that doctests are passing:
$ pytest --doctest-modules climpred --ignore climpred/tests
Check that your contribution is covered by tests and therefore increases the overall test coverage:
$ coverage run --source climpred -m py.test $ coverage report $ coveralls
Please stick to xarray’s testing recommendations.
Running the performance test suite
If you considerably changed to core of code of
climpred
, it is worth considering whether your code has introduced performance regressions.climpred
has a suite of benchmarking tests using asv to enable easy monitoring of the performance of criticalclimpred
operations. These benchmarks are all found in theasv_bench
directory.If you need to run a benchmark, change your directory to
asv_bench/
and run:$ asv continuous -f 1.1 upstream/main HEAD
You can replace
HEAD
with the name of the branch you are working on, and report benchmarks that changed by more than 10%. The command usesconda
by default for creating the benchmark environments.Running the full benchmark suite can take up to half an hour and use up a few GBs of RAM. Usually it is sufficient to paste only a subset of the results into the pull request to show that the committed changes do not cause unexpected performance regressions. If you want to only run a specific group of tests from a file, you can do it using
.
as a separator. For example:$ asv continuous -f 1.1 upstream/main HEAD -b benchmarks_PredictionEnsemble.GenerateHindcastEnsembleSmall.time_bootstrap
will only run the
time_bootstrap
benchmark of classGenerateHindcastEnsembleSmall
defined inbenchmarks_PredictionEnsemble.py
.Create a new changelog entry in CHANGELOG.rst:
The entry should be entered as:
<description>
(:pr:`#<pull request number>`
)`<author's names>`_
where
<description>
is the description of the PR related to the change and<pull request number>
is the pull request number and<author's names>
are your first and last names.Add yourself to list of authors at the end of CHANGELOG.rst file if not there yet, in alphabetical order.
Add yourself to the contributors list via
docs/source/contributors.rst
.Finally, submit a Pull Request through the GitHub website using this data:
head-fork: YOUR_GITHUB_USERNAME/climpred compare: your-branch-name base-fork: pangeo-data/climpred base: main
Note that you can create the Pull Request
while you’re working on this.
The PR will update as you add more commits. climpred
developers and
contributors can then review your code and offer suggestions.