Validate code changes by intelligently selecting and running the appropriate test suites. Use this when editing code to verify changes work correctly, run tests, validate functionality, or check for regressions. Automatically discovers affected test suites, selects the minimal set of venvs needed for validation, and handles test execution with Docker services as needed.
The 'run-tests' skill is designed to streamline the process of validating code changes by intelligently selecting and executing the appropriate test suites. It solves the problem of having to manually identify which tests are relevant after modifying source code. By automating test discovery and execution, it ensures that only the necessary tests are run, saving time and computational resources. This skill utilizes the 'scripts/run-tests' script to discover the affected test suites based on code changes and selects the minimal set of virtual environments (venvs) required for validation, running tests with Docker services when needed.
The skill uses the 'scripts/run-tests' script to list available test suites that match the changed files and identifies the corresponding venvs needed for testing.
Yes, you can specify specific test files or functions, particularly if only test-related changes are made, by using pytest arguments or direct test file paths.
The skill is compatible with the project's test infrastructure and should be used instead of running pytest directly to ensure the proper testing environment is used.
The skill supports a variety of code changes, including source code edits, bug fixes, feature additions, test infrastructure changes, and regression testing.
The skill intelligently selects minimal venvs for core, integration, or test infrastructure changes, running only the relevant suites to avoid unnecessary overhead.
Quick Setup:
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DataDog/dd-trace-py