Pytest Mastery

Deep expertise in the pytest framework, mocking strategies, and Test Driven Development.

Knowledge

• •

  The Testing Standard: Pytest

  code

  *   **Framework:** We strictly use `pytest`. Do not use the legacy 
      `unittest` class-based style unless absolutely necessary for legacy 
      compatibility.
  *   **Discovery:** Test files must be named `test_*.py` or `*_test.py`. 
      Test functions must start with `test_`.
  *   **Structure:** Tests live in a `tests/` directory that mirrors the 
      `src/` package structure.
  

• •

  The "Arrange, Act, Assert" Pattern

  code

  Every test must follow this logical flow:
  1.  **Arrange:** Set up the state (variables, mocks, fixtures).
  2.  **Act:** Call the function/method under test.
  3.  **Assert:** Verify the result matches expectations using simple 
      `assert` statements.
  

• •

  Isolation & Mocking

  code

  *   **Unit Tests must be Hermetic:** They never touch the network, the 
      filesystem, or the database.
  *   **Tools:** Use `unittest.mock` (specifically `patch` and `MagicMock`) 
      to stub out external dependencies.
  *   **Fixtures:** Use `pytest.fixture` in `conftest.py` for shared setup 
      logic to keep test bodies clean.
  

Abilities

• •Utilize pytest.mark.parametrize to test multiple input/output scenarios with a single test function (Data-Driven Testing).
• •Write 'Negative Tests' that verify the code raises specific Exceptions (pytest.raises) when given invalid input.
• •Refactor complex setup code into reusable Fixtures.
• •Achieve high code coverage by targeting edge cases, not just happy paths.