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