Simon Willison’s Weblog

inline-snapshot. I'm a big fan of snapshot testing, where expected values are captured the first time a test suite runs and then asserted against in future runs. It's a very productive way to build a robust test suite.

inline-snapshot by Frank Hoffmann is a particularly neat implementation of the pattern. It defines a snapshot() function which you can use in your tests:

assert 1548 * 18489 == snapshot()

When you run that test using pytest --inline-snapshot=create the snapshot() function will be replaced in your code (using AST manipulation) with itself wrapping the repr() of the expected result:

assert 1548 * 18489 == snapshot(28620972)

If you modify the code and need to update the tests you can run pytest --inline-snapshot=fix to regenerate the recorded snapshot values. # 16th April 2024, 4:04 pm

pytest-icdiff (via) This is neat: “pip install pytest-icdiff” provides an instant usability upgrade to the output of failed tests in pytest, especially if the assertions involve comparing larger strings or nested JSON objects. # 3rd June 2023, 4:59 pm

pyfakefs usage (via) New to me pytest fixture library that provides a really easy way to mock Python’s filesystem functions—open(), os.path.listdir() and so on—so a test can run against a fake set of files. This looks incredibly useful. # 1st February 2023, 10:37 pm

mitsuhiko/insta (via) I asked for recommendations on Twitter for testing libraries in other languages that would give me the same level of delight that I get from pytest. Two people pointed me to insta by Armin Ronacher, a Rust testing framework for “snapshot testing” which automatically records reference values to your repository, so future tests can spot if they change. # 31st October 2022, 1:06 am

Running C unit tests with pytest (via) Brilliant, detailed tutorial by Gabriele Tornetta on testing C code using pytest, which also doubles up as a ctypes tutorial. There’s a lot of depth here—in addition to exercising C code through ctypes, Gabriele shows how to run each test in a separate process so that segmentation faults don’t fail the entire suite, then adds code to run the compiler as part of the pytest run, and then shows how to use gdb trickery to generate more useful stack traces. # 12th February 2022, 5:14 pm

Blazing fast CI with pytest-split and GitHub Actions (via) pytest-split is a neat looking variant on the pattern of splitting up a test suite to run different parts of it in parallel on different machines. It involves maintaining a periodically updated JSON file in the repo recording the average runtime of different tests, to enable them to be more fairly divided among test runners. Includes a recipe for running as a matrix in GitHub Actions. # 22nd February 2021, 7:06 pm

parameterized. I love the @parametrize decorator in pytest, which lets you run the same test multiple times against multiple parameters. The only catch is that the decorator in pytest doesn’t work for old-style unittest TestCase tests, which means you can’t easily add it to test suites that were built using the older model. I just found out about parameterized which works with unittest tests whether or not you are running them using the pytest test runner. # 19th February 2019, 9:05 pm