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performance-profiling

Performance profiling principles. Measurement, analysis, and optimization techniques.

whodaniel☆ 2 Étoiles du dépôt0 Forks du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

Voir la source ↗Guides

Instructions

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
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.

Exemples

Consultez les exemples du dépôt source.

Voir la source ↗

Historique source

Date d’indexation
2026-01-20
Mise à jour de l’index
2026-01-26
Branch
main

Les dates concernent ce répertoire. Consultez le dépôt pour l’historique du code.

GitHub ↗

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