I read the book “Speed Up Your Django Tests” this week, a few interesting items: 

Background/disclaimer: I’m new to Django,  I use pytest to run many integration Django tests. so the points listed here are purely from my point of view.

  1. Override settings: with @override_settingsin case you want to override a setting for a test method, Django provides the override_settings() decorator (see PEP 318).
  2. Show slow tests with pytest --durations 10
  3. Tests marker, categorize/tag tests so that can run different subsets.  like JUnit categories for more details: https://docs.pytest.org/en/latest/example/markers.html
  4. Reduce pytest test collection by setting norecursedirs
  5. Run in parallel with pytest-xdist
  6. Django’s RequestFactory: This is similar to the test client, but instead of making requests, “provides a way to generate a request instance that can be used as the first argument to any view” Django Doc
  7. Django’s SimpleTestCase:  a subclass of unittest.TestCase, it “disallows database queries by default.”,  however, you till can turn it on.
  8. Avoid Fixture Files[11.1],  “For data you need in individual tests, you’re better off creating it in the test case or test method.” I have to see it’s very easy to set up test data with fixtures, but shortly it becomes unmanageable few valid points: 

    Fixture ˉles are separate from the tests that use them. This makes it hard to determine which tests use which objects. The ˉles tend to become “append-only,”…when a new test needs a new object, it tends to be added to an existing file…if there’s some data that most of your application depends on, using a fixture, causes unnecessary reloading. It will be loaded and then rolled back for each test case, even when the next test case needs the exact same data.

Overall, I would say it’s a good Django testing book for newbies like me, the book also covers many other topics, such as “Profiling”, “Mocking” etc, and many topics and links for me to explore Django. overall, I would say it’s a good Django testing book for newbies like me.

However, slow tests generally indicate design issues. all the techniques mentioned in the book definitely can help to speed up the testing(itself), if we take one steps further, should we start thinking about the design?


from: Architecture Patterns with Python

if we cloud fundamentally resolve some design issues, I believe we’ll get much fewer integration tests.