Contributions are welcome from any "array-consuming" library contributors who have found themselves writing private array-agnostic functions in the process of converting code to consume the standard.
Thanks to all contributors so far!
- Open an issue to propose the new function. You may want to wait for initial feedback on the issue before diving into an implementation. Feel free to skip this step if there is already an open issue for the function.
- Add the implementation of your function to
src/array_api_extra/_lib/_funcs.py.- Ensure that your function includes type annotations and a numpydoc-style docstring.
- Add your function to
__all__at the top of the file.
- Import your function to
src/array_api_extra/__init__.pyand add it to__all__there. - Add a test class for your function in
tests/test_funcs.py.- Ensure that
lazy_xp_functionis called on the function if lazy backends are supposed to be tested.
- Ensure that
- Add your function to
docs/api-reference.md. - Make a PR!
See the tracker for adding delegation.
- If you would like to discuss the task before diving into the implementation, click on the three dots next to the function on the tracker issue, and choose "Convert to sub-issue".
- Create a function in
src/array_api_extra/_delegation.pywith a signature matching the function insrc/array_api_extra/_lib/_funcs.py, and move the docstring to the new function. Leave a one-line docstring in_funcs.py, pointing to_delegation.pyto see the full docstring. - Also move the initial
array_namespacecall and any input validation over to the new function. - Add delegation to backends using the
if _delegatepattern. Seesrc/array_api_extra/_lib/_backends.pyfor the full list of backends we have worked with so far. - After all delegation layers, return the result from the implementation in
_funcs. - Simplify the signature in
_funcs.pyto remove impossible arguments now that it is only called internally via_delegation. For example, thexpparameter can be changed from typeModuleType | NonetoModuleType. - Don't worry if you are not sure how to do some of the above steps or think you might have done something wrong - make a PR!
If you are an experienced contributor to Python packages, feel free to develop however you feel comfortable! However, if you would like some guidance, development of array-api-extra is made easy with Pixi:
- Clone the repository at https://github.com/data-apis/array-api-extra.
cd array-api-extra.- Install Pixi.
- To enter a development environment (if you prefer this to the
pixi runinterface):
pixi shell -e dev
- To run the tests:
pixi run tests
- To build the docs locally:
pixi run docs
- To build and preview the docs locally:
pixi run open-docs
- To install pre-commit hooks:
pixi run hooks
- To run pre-commit checks on staged files:
pixi run pre-commit
- To run the full lint suite:
pixi run --environment=lint lint
- To enter an interactive Python prompt:
pixi run ipython
- To run individual parts of the lint suite separately (for example):
pixi run --environment=lint pyright
pixi run --environment=lint dprint
- To generate the coverage report:
pixi run coverage
- To generate and display the coverage report:
pixi run open-coverage
Alternative environments are available with a subset of the dependencies and
tasks available in the dev environment:
pixi shell --environment=docs
pixi shell --environment=tests
pixi shell --environment=tests-backends
pixi shell --environment=lint
If you run on a host with CUDA hardware, you can enable extra tests:
pixi shell --environment=dev-cuda
pixi shell --environment=tests-cuda
pixi run --environment=tests-cuda tests