Testing

Testing is essential for any new contribution to GWPopulation. We have a suite of unit-tests that run on every push to the repository and the example notebooks are run occasionally to ensure that they are still working.

Unit Testing

We use pytest to run our unit tests. These tests are located in the tests directory and are run automatically on every push to the repository. Change will only be accepted without passing unit tests under very rare. circumstances. To run the tests locally, you can use the following commands:

python -m pip install .[test]
python -m pytest --cov gwpopulation

If you are new to writing unit tests, you should begin with the existing tests and see how they can be modified for your purposes. Additionally, the pytest website includes information on how to write and using that framework. If you have any additional questions, please open the pull request and ask for assistance.

Testing with multiple backends

Since we support multiple backends, we have to test that the code works with as many of them as possible. Unfortunately, we do not currently have access to CI machines that have GPUs and so tests are performed with numpy and jax-cpu backends. If you have access to an environment with a suitable GPU we request that you run the tests with the cupy and jax-gpu backends also and report the results in the pull request. If you don’t have access, you can request a maintainer runs the tests on a GPU.

Integration Testing

We do not have a formal process for full-scale integration testing. However, when contributing a new feature, it is recommended to test this feature in a real-world scenario. This can be done by creating a modified version of one of the example notebooks. The result can then either be added to the repository in your pull request, or linked so that we have a record of the test. For testing in a GPU environment, you can use Google Colab.