performance-profiling
Skill130 starsChanged 10 months agoMITView on GitHub
Performance profiling principles. Measurement, analysis, and optimization techniques.
Files
Performance Profiling
Measure, analyze, optimize - in that order.
🔧 Runtime Scripts
Execute these for automated profiling:
| Script | Purpose | Usage |
scripts/lighthouse_audit.py | Lighthouse performance audit | python scripts/lighthouse_audit.py https://example.com |
1. Core Web Vitals
Targets
| Metric | Good | Poor | Measures |
| LCP | < 2.5s | > 4.0s | Loading |
| INP | < 200ms | > 500ms | Interactivity |
| CLS | < 0.1 | > 0.25 | Stability |
When to Measure
| Stage | Tool |
| Development | Local Lighthouse |
| CI/CD | Lighthouse CI |
| Production | RUM (Real User Monitoring) |
2. Profiling Workflow
The 4-Step Process
1. BASELINE → Measure current state
2. IDENTIFY → Find the bottleneck
3. FIX → Make targeted change
4. VALIDATE → Confirm improvementProfiling Tool Selection
| Problem | Tool |
| Page load | Lighthouse |
| Bundle size | Bundle analyzer |
| Runtime | DevTools Performance |
| Memory | DevTools Memory |
| Network | DevTools Network |
3. Bundle Analysis
What to Look For
| Issue | Indicator |
| Large dependencies | Top of bundle |
| Duplicate code | Multiple chunks |
| Unused code | Low coverage |
| Missing splits | Single large chunk |
Optimization Actions
| Finding | Action |
| Big library | Import specific modules |
| Duplicate deps | Dedupe, update versions |
| Route in main | Code split |
| Unused exports | Tree shake |
4. Runtime Profiling
Performance Tab Analysis
| Pattern | Meaning |
| Long tasks (>50ms) | UI blocking |
| Many small tasks | Possible batching opportunity |
| Layout/paint | Rendering bottleneck |
| Script | JavaScript execution |
Memory Tab Analysis
| Pattern | Meaning |
| Growing heap | Possible leak |
| Large retained | Check references |
| Detached DOM | Not cleaned up |
5. Common Bottlenecks
By Symptom
| Symptom | Likely Cause |
| Slow initial load | Large JS, render blocking |
| Slow interactions | Heavy event handlers |
| Jank during scroll | Layout thrashing |
| Growing memory | Leaks, retained refs |
6. Quick Win Priorities
| Priority | Action | Impact |
| 1 | Enable compression | High |
| 2 | Lazy load images | High |
| 3 | Code split routes | High |
| 4 | Cache static assets | Medium |
| 5 | Optimize images | Medium |
7. Anti-Patterns
| ❌ Don't | ✅ Do |
| Guess at problems | Profile first |
| Micro-optimize | Fix biggest issue |
| Optimize early | Optimize when needed |
| Ignore real users | Use RUM data |
Remember: The fastest code is code that doesn't run. Remove before optimizing.
Other versions23 projects use a version of this.
Word for word · 5
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Edited · 5
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Wrote their own version · 13
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3 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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