writing-ratchet-tests

Ratchet tests prevent Python code anti-patterns from accumulating by tracking their occurrences and enforcing improvements via inline snapshots. You define measurable ratchets for patterns like TODO comments or eval usage to establish a baseline and drive continuous code quality improvement.

The best way to track broad exception handling and TODO comments is using ratchet tests with RegexPattern checks. This approach snapshots the current count of these anti-patterns, allowing decreases as improvements while actively preventing any new occurrences from being introduced.

To set up ratchet tests, create a test_ratchets.py file in your project, import the ratchet utilities, and use RegexPattern checks alongside inline-snapshot to capture baseline metrics. This scaffolding integrates directly into your CI and development workflows to enforce standards.

Yes, you can use ratchet tests to enforce standards against inline imports and eval or exec statements. By applying RegexPattern checks across your projects, the test suite detects any increases in these anti-patterns and allows decreases as measurable code improvements.

Inline-snapshot works with ratchet tests by generating and comparing snapshot data to detect increases in anti-patterns and allow decreases as improvements. This mechanism tracks specific code patterns continuously, ensuring any new violations fail the tests and prompt immediate remediation.