performance-profiling

# 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 improvement ``` ### Profiling 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 |...