Day 3 – Testing with pytest

Today's Focus

Write unit tests with pytest: test the logic you have built, handle edge cases, and understand what good test coverage looks like.

Tasks

• Install pytest and write a tests/ directory alongside your catalogue/ package. Write at least 10 unit tests covering: normal cases, boundary conditions (empty input, single item), and expected exceptions.
• Use pytest.mark.parametrize to test your filter function against a table of inputs and expected outputs instead of writing a separate test for each case.
• Write a test that uses tmp_path (pytest's built-in fixture) to create a temporary CSV file, run your CLI against it, and assert the output. This tests file I/O without touching real files.
• Mock an external call (e.g. pretend your CSV loader calls an HTTP endpoint) using unittest.mock.patch. Assert the mock was called with the correct arguments.
• Run pytest --cov=catalogue --cov-report=term-missing (install pytest-cov) and aim for at least 80% coverage. Identify which branches are untested and add tests for them.
• Configure pytest in pyproject.toml with [tool.pytest.ini_options]: set testpaths = ["tests"], enable warnings as errors, and add a custom marker slow that you can skip with -m "not slow".

Reading / Reference

• pytest documentation — Getting Started, How-to guides for fixtures and parametrize.
• Real Python: Effective Python Testing with pytest.
• Python docs: unittest.mock — the Mock and patch sections.