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Python Unit Test Guide

We use the unit tests to cover internal behavior that can work without the web / backend counterpart. We aim for high unit test coverage (90% or higher) of our Python code in lib/streamlit.

Key Principles

  • Prefer pytest or pytest plugins over unittest.
  • For every new test function, please add a brief docstring comment (numpydoc style).
  • New tests should be fully annotated with types.
  • Skip tests (via pytest.mark.skipif) requiring CI secrets if the environment variables are not set.
  • Parameterized Tests: Use @parameterized.expand whenever it is possible to combine overlapping tests with varying inputs.
  • Include a negative / anti-regression assertion when practical: Don't only test that the “right” behavior happens; also test that a plausible “wrong” behavior does not happen.
    • Examples:
      • If you assert a flag becomes True, also assert a mutually exclusive flag remains False.
      • If you expect a function to return a value, also assert it doesn't return a plausible-but-wrong value.
      • If you expect success, also cover one relevant failure mode (invalid input, boundary condition, or raised exception) when practical.
  • Prefer targeted negatives over exhaustive matrices: Add one high-signal negative check per behavior; don't balloon test cases without a regression history.

Running tests

  • Run all with (execute from repo root):
make python-tests
  • Run a specific test file with:
PYTHONPATH=lib pytest lib/tests/streamlit/my_example_test.py
  • Run a specific test inside a test file with:
PYTHONPATH=lib pytest lib/tests/streamlit/my_example_test.py -k test_that_something_works