Python Test-Driven Development: Mastering Unit, Integration, and E2E Testing with pytest and Modern Tools: A Practical Guide to Build High-Quality Applications with Comprehensive Testing Strategies - Tapa blanda

Sinopsis

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.

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