zozo123 opened a new pull request, #70300: URL: https://github.com/apache/airflow/pull/70300
The E2E flaky-test report currently derives its observation count from `run_ids`, which contains only runs where the test failed. A one-off failure can therefore appear as 100% and incorrectly cross the 30% flaky-candidate threshold. Use all workflow runs with downloadable data as the denominator while counting each failing run once, regardless of how many browsers failed. Update the regression fixtures to cover an exact 60% rate, a one-in-ten non-candidate, and deterministic 80%-then-30% ordering. This keeps the raw browser-level failure count in the report while making the failure rate match the documented fraction of runs. Checks: - `uv run --project scripts pytest scripts/tests/ci/test_analyze_e2e_flaky_tests.py -q` (13 passed) - `uv run --project scripts pytest scripts/tests -q` (957 passed) - `prek run --from-ref upstream/main --stage pre-commit` - `prek run --from-ref upstream/main --stage manual` - `breeze ci selective-check --commit-ref HEAD` (scripts tests selected) --- ##### Was generative AI tooling used to co-author this PR? - [X] Yes — Codex (GPT-5) Generated-by: Codex (GPT-5) following [the guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#gen-ai-assisted-contributions) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
