trunk/fbfd15846f570ac46ff9e34a533162fb2054dbd9: [MergeRules] Make Metamates group explicit (#176303)
A new script adds top reviewers automatically based on 3+ PRs reviewed in 30 days
PyTorch's latest commit (fbfd158) on the trunk branch introduces a key process improvement: automating the assignment of 'Metamates' as reviewers for pull requests. The change, merged via PR #176303, uses a Python script (`.github/scripts/update_metamates_rules.py`) that scans all recent contributions and adds every Metamate who has reviewed at least 3 PRs in the past 30 days. This replaces a manual, static list with a dynamic, data-driven approach. The commit was tagged on May 1 and approved by albanD.
A follow-up PR is planned to run this script periodically, generating automated PRs that keep the reviewer list up-to-date. This means new contributors will be automatically added after they have shadow-reviewed 3 PRs alongside existing reviewers. For a massive open-source project like PyTorch (99.6k stars, 27.6k forks), this reduces human error and maintenance burden, ensuring that active reviewers are always recognized and that the review process scales efficiently. It's a small but impactful automation that exemplifies how mature projects can use tooling to sustain contributor growth.
- Automated script adds every Metamate with 3+ PR reviews in past 30 days to the reviewer list
- Follow-up PR will run the script periodically to include new contributors after 3 shadow reviews
- Reduces manual maintenance of reviewer lists for PyTorch's 99.6k-star repository
Why It Matters
Streamlines PyTorch's review process by automating contributor onboarding, ensuring faster merge cycles and less manual overhead.