testing-patterns

Unit tests using Arrange-Act-Assert (AAA) structure your test into three phases: arrange inputs and dependencies, act by calling the function or method, then assert the expected output. This pattern isolates pure functions and makes tests fast, readable, and maintainable across Python, JavaScript, and other languages.

Standardized test organization groups related tests in files or suites, uses descriptive naming conventions (e.g., test_[function]_[scenario]), and structures setup and teardown logic to handle dependencies. This reduces duplication, improves readability, and ensures tests remain fast and isolated across your codebase.

Mocking replaces external dependencies, database calls, and API requests with controlled stubs during testing. This isolation lets you test units independently, run tests faster without external resources, and verify interactions between components in integration scenarios across multiple frameworks.

Testing patterns—unit, integration, mocking, naming, and organization—apply universally but use language-specific frameworks and syntax. Common frameworks in Python (pytest, unittest) and JavaScript (Jest, Mocha) implement these patterns, so core principles transfer between ecosystems.

Unit tests validate isolated functions with mocked dependencies for speed and repeatability; integration tests verify multiple components working together with real dependencies. Use both: unit tests catch logic errors quickly, integration tests catch interaction failures before end-to-end testing.