python-testing-patterns
Comprehensive testing strategies for Python using pytest, fixtures, mocking, and test-driven development.
- Covers unit, integration, functional, and performance testing with the AAA pattern (Arrange, Act, Assert) for test structure
- Includes 10 fundamental and advanced patterns: basic tests, fixtures with setup/teardown, parameterization, mocking, exception handling, async testing, monkeypatching, temporary files, custom fixtures, and property-based testing
- Provides test design principles, naming conventions, database testing, retry logic, time control with freezegun, markers, and coverage reporting
- Includes CI/CD integration examples and configuration files (pytest.ini, pyproject.toml) for standardized test execution
Python Testing Patterns
Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.
When to Use This Skill
- Writing unit tests for Python code
- Setting up test suites and test infrastructure
- Implementing test-driven development (TDD)
- Creating integration tests for APIs and services
- Mocking external dependencies and services
- Testing async code and concurrent operations
- Setting up continuous testing in CI/CD
- Implementing property-based testing
- Testing database operations
- Debugging failing tests
Core Concepts
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