Publisher's Synopsis
What You Will Learn in This Book
- Establish a robust testing foundation by understanding the importance of software testing, the testing pyramid (Unit, Integration, E2E), and core terminology.
- Set up your Python testing environment and choose the right framework for your projects, with a practical comparison of unittest and pytest.
- Master pytest for effective unit testing, including writing clear test functions, utilizing powerful fixtures, parametrizing tests for efficiency, and managing test execution with markers.
- Isolate your code for precise unit tests using mocking and patching techniques with unittest.mock and the pytest-mock library, ensuring your tests focus only on the code under examination.
- Confidently test diverse Python code structures, from functions and classes to decorators, context managers, generators, and command-line interfaces.
- Implement comprehensive integration testing strategies to verify interactions between components, including databases and APIs, learning to manage complex setups and external dependencies.
- Develop and maintain resilient end-to-end (E2E) tests that simulate real user flows, utilizing tools like Selenium and Playwright, and applying design patterns like the Page Object Model.
- Integrate Test-Driven Development (TDD) into your workflow using the Red-Green-Refactor cycle, and apply Behavior-Driven Development (BDD) principles with tools like behave and pytest-bdd.
- Discover property-based testing with Hypothesis to automatically generate diverse test cases, uncover edge cases, and enhance the robustness of your algorithms and data structures.
- Assess and improve your test quality using code coverage tools (pytest-cov) and understand the benefits of mutation testing for truly effective test suites.
- Automate your testing within Continuous Integration (CI) pipelines using platforms like GitHub Actions, ensuring consistent and rapid feedback on code changes.
- Tackle specialized testing scenarios, including asynchronous Python code with asyncio, data science and machine learning applications, and complex microservices architectures.
- Cultivate a strong testing culture within your development lifecycle, understanding the role of testing in Agile and DevOps, and effectively debugging and learning from test failures.
- Stay ahead with emerging trends in the evolving Python testing ecosystem, including the impact of AI and machine learning on test automation.
