Smart Parallel Repo Update Optimization | Generated by AI
28s for 99 repos. Compare the three approaches:
Sequential (old): ~99 × 4.4s ≈ 435s (7+ min)
Parallel pull (no check): ~99 × 4.4s ÷ 8 ≈ 55s
Smart fetch-first (current): 28s (98 up-to-date did fetch-only, 1 pulled)
The smart approach cut it roughly in half vs naive parallel pull. Here’s why:
Repo that's up-to-date:
Old: git fetch (negotiate refs) + git merge (no-op) + verbose output parsing
New: git fetch (negotiate refs) → see 0 behind → skip
Repo that needs update:
Old: git fetch + git merge + verbose output
New: git fetch → see N behind → git pull (fetch again + merge)
The up-to-date repos save the merge step and verbose parsing. For 98/99 repos being current, that compounds.
To your original question about whether the initial pull is unnecessary because gpa handles pull on push-failure: gpa only runs on repos you’re committing to. projects update covers all 99 repos — most are upstream projects you just track (pytorch, llama.cpp, dify, etc.). You need to pull those to get the latest code. The optimization is making that check cheap.