Build Timing Audit: Data-Driven Optimization Checklist
Stop guessing why your builds are slow. Work through a checklist backed by real timing data from 100+ Python projects, then use a scoring system to fix the bottlenecks that matter most, cutting troubleshooting from days to hours.
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What's Inside
- Build Stage Breakdown Checklist
- Benchmark Comparison Table
- Priority Matrix: Effort vs. Impact
- Quick Fixes Ranked by ROI
- When to Refactor vs. When to Ignore Slowness
- Anti-Patterns Specific to Structured Builds
Fix 1: Enable Docker BuildKit (5 min, 20-40% speedup) Run: ``` DOCKER_BUILDKIT=1 docker build. ``` To make it permanent on your machine: ``` echo '{"features": {"buildkit": true}}' | sudo tee /etc/docker/daemon.json sudo systemctl restart docker ``` Why it works: BuildKit parallelizes layer builds and enables advanced caching. Standard Docker runs layers sequentially. --- Benchmark Comparison: Where Your Build Stands | Project Type | Dependency Install | Linting/Format | Type Check | Tests | Docker Build | Total | |---|---|---|---|---|---|---| | FastAPI-style (30 deps) | 8-12s | 4-6s | 8-15s | 12-20s | 35-50s | 70-100s | | Django (25 deps, DB) | 10-15s | 3-5s | 10-18s | 20-40s | 45-70s | 90-140s | | Data science (numpy, pandas, scikit-learn) | 25-40s | 2-3s | 15-25s | 30-60s | 60-90s | 135-220s | | CLI tool (5-10 deps) | 2-4s | 2-3s | 3-6s | 4-10s | 15-25s | 30-50s | | Async heavy (httpx, aioredis, aiofiles) | 10-15s | 3-5s | 8-12s | 15-30s | 40-60s | 80-125s |
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