python-testing

# Python Testing Patterns Comprehensive testing strategies for Python applications using pytest, TDD methodology, and best practices. ## When to Activate - Writing new Python code (follow TDD: red, green, refactor) - Designing test suites for Python projects - Reviewing Python test coverage - Setting up testing infrastructure ## Core Testing Philosophy ### Test-Driven Development (TDD) Always follow the TDD cycle: 1. **RED**: Write a failing test for the desired behavior 2. **GREEN**: Write minimal code to make the test pass 3. **REFACTOR**: Improve code while keeping tests green ```python # Step 1: Write failing test (RED) def test_add_numbers(): result = add(2, 3) assert result == 5 # Step 2: Write minimal implementation (GREEN) def add(a, b): return a + b # Step 3: Refactor if needed (REFACTOR) ``` ### Coverage Requirements - **Target**: 80%+ code coverage - **Critical paths**: 100% coverage required - Use `pytest --cov` to measure coverage ```bash pytest --cov=mypackage --cov-report=term-missing --cov-report=html ``` ## pytest Fundamentals ### Basic Test Structure ```python import pytest def test_addition(): """Test basic addition.""" assert 2 + 2 == 4 def test_string_uppercase(): """Test string uppercasing.""" text = "hello" assert text.upper() == "HELLO" def test_list_append(): """Test list append.""" items = [1, 2, 3] items.append(4) assert...