Testing pystencils

Testing pystencils#

The pystencils testsuite is located at the tests directory, constructed using pytest, and automated through Nox. On this page, you will find instructions on how to execute and extend it.

Running the Testsuite#

The fastest way to execute the pystencils test suite is through the testsuite Nox session:

nox -s testsuite

There exist several configurations of the testsuite session, from which the above command will select and execute only those that are available on your machine.

  • Python Versions: The testsuite session can be run against all major Python versions between 3.10 and 3.13 (inclusive). To only use a specific Python version, add the -p 3.XX argument to your Nox invocation; e.g. nox -s testsuite -p 3.11.

  • CuPy: There exist three variants of testsuite, including or excluding tests for the CUDA GPU target: cpu, cupy12 and cupy13. To select one, append (<variant>) to the session name; e.g. nox -s "testsuite(cupy12)".

You may also pass options through to pytest via positional arguments after a pair of dashes, e.g.:

nox -s testsuite -- -k "kernelcreation"

During the testsuite run, coverage information is collected using coverage.py, and the results are exported to HTML. You can display a detailed overview of code coverage by opening the generated htmlcov/index.html page.

Extending the Test Suite#

Codegen Configurations via Fixtures#

In the pystencils test suite, it is often necessary to test code generation features against multiple targets. To simplify this process, we provide a number of pytest fixtures you can and should use in your tests:

  • target: Provides code generation targets for your test. Using this fixture will make pytest create a copy of your test for each target available on the current machine (see Target.available_targets).

  • gen_config: Provides default code generation configurations for your test. This fixture depends on target and provides a CreateKernelConfig instance with target-specific optimization options (in particular vectorization) enabled.

  • xp: The xp fixture gives you either the NumPy (np) or the CuPy (cp) module, depending on whether target is a CPU or GPU target.

These fixtures are defined in tests/fixtures.py.

Overriding Fixtures#

Pytest allows you to locally override fixtures, which can be especially handy when you wish to restrict the target selection of a test. For example, the following test overrides target using a parametrization mark, and uses this in combination with the gen_config fixture, which now receives the overridden target parameter as input:

@pytest.mark.parametrize("target", [Target.X86_SSE, Target.X86_AVX])
def test_bogus(gen_config):
    assert gen_config.target.is_vector_cpu()
Contents