Learning Objectives: After this lesson, you'll master pytest with fixtures, parametrization, and mocking, understand test-driven development, achieve meaningful coverage, and write maintainable tests.
Why Testing Matters
Tests are insurance for your codeβthey catch bugs before users do and give you confidence to refactor.
The Testing Pyramid
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pytest Fundamentals
Basic Test Structure
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Test Organization
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Fixtures: Setup and Teardown
Fixtures provide reusable test setup and cleanup.
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Basic Fixtures
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Fixture Scopes
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Parametrization: Test Multiple Cases
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Mocking: Isolate Units
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Patching
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Test-Driven Development (TDD)
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Testing Async Code
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Coverage and Quality
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Best Practices
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Practice Exercises
Exercise 1: Test a Shopping Cart
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Key Takeaways
| Concept | Description |
|---|---|
| Fixtures | Reusable test setup and teardown |
| Parametrize | Run same test with different data |
| Mock | Replace dependencies with fake objects |
| Patch | Temporarily replace module attributes |
| TDD | Red-Green-Refactor cycle |
| Coverage | Measure which code is tested |
| AAA | Arrange, Act, Assert pattern |
Testing Checklist
- Unit tests for business logic
- Edge cases and error handling
- Integration tests for components
- Mocks for external dependencies
- Async tests with pytest-asyncio
- Coverage > 80% for critical code
- Fast test suite (< 1 minute)
- CI pipeline runs all tests
Next Steps
In the next lesson, we'll explore Design Patterns in Pythonβimplement classic patterns like Factory, Strategy, Observer, and Dependency Injection the Pythonic way.
Ready to write elegant code? Design patterns await!