perf

性能分析器

对代码性能进行分析、基准测试和优化。

前提条件

# Node.js for profiling
node --version

# Lighthouse for web perf
npm install -g lighthouse

# Gemini for analysis
pip install google-generativeai
export GEMINI_API_KEY=your_api_key

基准测试

快速基准测试

# Time a Node.js script
time node script.js

# With memory
/usr/bin/time -l node script.js  # macOS
/usr/bin/time -v node script.js  # Linux

Node.js 性能钩子

// benchmark.js
const { performance, PerformanceObserver } = require('perf_hooks');

const obs = new PerformanceObserver((list) => {
  console.log(list.getEntries()[0].duration);
});
obs.observe({ entryTypes: ['measure'] });

performance.mark('start');
// Code to benchmark
yourFunction();
performance.mark('end');
performance.measure('duration', 'start', 'end');

控制台计时

console.time('operation');
// Code to time
console.timeEnd('operation');  // Prints: operation: 123.456ms

Node.js 性能分析

V8 分析器

# Generate profile
node --prof script.js

# Process the log
node --prof-process isolate-*.log > profile.txt

检查模式

# Start with inspector
node --inspect script.js

# Break on start
node --inspect-brk script.js

# Open Chrome DevTools
open chrome://inspect

内存分析

# Heap snapshot
node --heapsnapshot-signal=SIGUSR2 script.js
# Then: kill -USR2 <pid>

# Expose GC for testing
node --expose-gc script.js

Lighthouse 审计

基础审计

# Full audit
lighthouse https://example.com

# Output to JSON
lighthouse https://example.com --output=json --output-path=report.json

# Output to HTML
lighthouse https://example.com --output=html --output-path=report.html

# Specific categories
lighthouse https://example.com --only-categories=performance

# Mobile vs Desktop
lighthouse https://example.com --preset=desktop
lighthouse https://example.com --preset=mobile  # default

仅性能

lighthouse https://example.com \
  --only-categories=performance \
  --output=json \
  --output-path=perf-report.json

Chrome 标志

# Headless
lighthouse https://example.com --chrome-flags="--headless"

# Custom viewport
lighthouse https://example.com --chrome-flags="--window-size=1920,1080"

AI 性能分析

分析代码性能

CODE=$(cat slow-function.ts)

gemini -m pro -o text -e "" "Analyze this code for performance issues:

$CODE

Identify:
1. Time complexity issues
2. Memory leaks or bloat
3. Unnecessary operations
4. Opportunities for optimization
5. Caching opportunities

Provide specific recommendations with code examples."

分析性能分析输出

PROFILE=$(cat profile.txt)

gemini -m pro -o text -e "" "Analyze this Node.js profile:

$PROFILE

Identify:
1. Hot functions (most time spent)
2. Potential bottlenecks
3. Optimization opportunities
4. Priority of fixes"

查找热点

CPU 热点

# Record CPU profile
node --cpu-prof script.js

# Analyze generated .cpuprofile
# Open in Chrome DevTools or use:
npx speedscope *.cpuprofile

内存热点

# Find large objects
node --heapsnapshot-signal=SIGUSR2 app.js

# Use clinic.js
npx clinic doctor -- node script.js
npx clinic flame -- node script.js
npx clinic bubbleprof -- node script.js

打包分析

# Webpack
npx webpack-bundle-analyzer stats.json

# Vite
npx vite build --report

# Generic
du -sh dist/*
ls -lhS dist/*.js

常见模式

需要检查的反模式

gemini -m pro -o text -e "" "Check this code for common performance anti-patterns:

$(cat src/*.ts)

Look for:
- Synchronous I/O in hot paths
- Repeated DOM queries
- Unnecessary re-renders
- N+1 query patterns
- Memory leaks in closures
- Blocking the event loop"

优化清单

gemini -m pro -o text -e "" "Create a performance optimization checklist for:

Application type: [web app / API / CLI]
Stack: [your stack]
Current issues: [symptoms]

Include priority order and estimated impact."

对比基准测试

优化前/优化后

#!/bin/bash
# benchmark-compare.sh

echo "=== Before optimization ==="
git checkout main
npm install
time npm run benchmark

echo "=== After optimization ==="
git checkout optimization-branch
npm install
time npm run benchmark

A/B 脚本

#!/bin/bash
# Run same benchmark multiple times
for i in {1..10}; do
  echo "Run $i:"
  node benchmark.js
done | tee results.txt

# Calculate average
grep "time:" results.txt | awk '{sum+=$2; n++} END {print "Average:", sum/n}'

最佳实践

1. 先测量 - 没有数据就不要优化
2. 在生产环境分析 - 开发环境性能不同
3. 自动化基准测试 - 长期跟踪
4. 聚焦热点路径 - 80/20 法则
5. 在目标设备上测试 - 尤其是移动端
6. 部署后监控 - 验证改进效果
7. 记录基线 - 了解"良好"的标准