R
react-performance-optimization
by @nickcrewv1.0.0
0.0(0)
运用记忆化、上下文等模式优化React应用性能,提升前端用户体验。
安装方式
npx skills add nickcrew/claude-ctx-plugin --skill react-performance-optimizationcompare_arrows
Before / After 效果对比
1 组使用前
React应用加载缓慢,交互卡顿,用户体验不佳。
使用后
通过Memoization、代码分割等策略,显著提升React应用性能和用户体验。
description SKILL.md
name: react-performance-optimization description: React performance optimization patterns using memoization, code splitting, and efficient rendering strategies. Use when optimizing slow React applications, reducing bundle size, or improving user experience with large datasets.
React Performance Optimization
Expert guidance for optimizing React application performance through memoization, code splitting, virtualization, and efficient rendering strategies.
When to Use This Skill
- Optimizing slow-rendering React components
- Reducing bundle size for faster initial load times
- Improving responsiveness for large lists or data tables
- Preventing unnecessary re-renders in complex component trees
- Optimizing state management to reduce render cascades
- Improving perceived performance with code splitting
- Debugging performance issues with React DevTools Profiler
Core Concepts
React Rendering Optimization
React re-renders components when props or state change. Unnecessary re-renders waste CPU cycles and degrade user experience. Key optimization techniques:
- Memoization: Cache component renders and computed values
- Code splitting: Load code on demand for faster initial loads
- Virtualization: Render only visible list items
- State optimization: Structure state to minimize render cascades
When to Optimize
- Profile first: Use React DevTools Profiler to identify actual bottlenecks
- Measure impact: Verify optimization improves performance
- Avoid premature optimization: Don't optimize fast components
Quick Reference
Load detailed patterns and examples as needed:
| Topic | Reference File |
|---|---|
| React.memo, useMemo, useCallback patterns | skills/react-performance-optimization/references/memoization.md |
| Code splitting with lazy/Suspense, bundle optimization | skills/react-performance-optimization/references/code-splitting.md |
| Virtualization for large lists (react-window) | skills/react-performance-optimization/references/virtualization.md |
| State management strategies, context splitting | skills/react-performance-optimization/references/state-management.md |
| useTransition, useDeferredValue (React 18+) | skills/react-performance-optimization/references/concurrent-features.md |
| React DevTools Profiler, performance monitoring | skills/react-performance-optimization/references/profiling-debugging.md |
| Common pitfalls and anti-patterns | skills/react-performance-optimization/references/common-pitfalls.md |
Optimization Workflow
1. Identify Bottlenecks
# Open React DevTools Profiler
# Record interaction → Analyze flame graph → Find slow components
Look for:
- Components with yellow/red bars (slow renders)
- Unnecessary renders (same props/state)
- Expensive computations on every render
2. Apply Targeted Optimizations
For unnecessary re-renders:
- Wrap component with
React.memo - Use
useCallbackfor stable function references - Check for inline objects/arrays in props
For expensive computations:
- Use
useMemoto cache results - Move calculations outside render when possible
For large lists:
- Implement virtualization with react-window
- Ensure proper unique keys (not index)
For slow initial load:
- Add code splitting with
React.lazy - Analyze bundle size with webpack-bundle-analyzer
- Use dynamic imports for heavy dependencies
3. Verify Improvements
# Record new Profiler session
# Compare before/after metrics
# Ensure optimization actually helped
Common Patterns
Memoize Expensive Components
import { memo } from 'react';
const ExpensiveList = memo(({ items, onItemClick }) => {
return items.map(item => (
<Item key={item.id} data={item} onClick={onItemClick} />
));
});
Cache Computed Values
import { useMemo } from 'react';
function DataTable({ items, filters }) {
const filteredItems = useMemo(() => {
return items.filter(item => filters.includes(item.category));
}, [items, filters]);
return <Table data={filteredItems} />;
}
Stable Function References
import { useCallback } from 'react';
function Parent() {
const handleClick = useCallback((id) => {
console.log('Clicked:', id);
}, []);
return <MemoizedChild onClick={handleClick} />;
}
Code Split Routes
import { lazy, Suspense } from 'react';
const Dashboard = lazy(() => import('./Dashboard'));
const Reports = lazy(() => import('./Reports'));
function App() {
return (
<Suspense fallback={<Loading />}>
<Routes>
<Route path="/" element={<Dashboard />} />
<Route path="/reports" element={<Reports />} />
</Routes>
</Suspense>
);
}
Virtualize Large Lists
import { FixedSizeList } from 'react-window';
function VirtualList({ items }) {
return (
<FixedSizeList
height={600}
itemCount={items.length}
itemSize={80}
width="100%"
>
{({ index, style }) => (
<div style={style}>{items[index].name}</div>
)}
</FixedSizeList>
);
}
Common Mistakes
- Over-memoization: Don't memoize simple, fast components (adds overhead)
- Inline objects/arrays: New references break memoization (
config={{ theme: 'dark' }}) - Missing dependencies: Stale closures in useCallback/useMemo
- Index as key: Breaks reconciliation when list order changes
- Single large context: Causes widespread re-renders on any update
- No profiling: Optimizing without measuring wastes time
Performance Checklist
Before optimizing:
- Profile with React DevTools to identify bottlenecks
- Measure baseline performance metrics
Optimization targets:
- Memoize expensive components with stable props
- Cache computed values with useMemo (if actually expensive)
- Use useCallback for functions passed to memoized children
- Implement code splitting for routes and heavy components
- Virtualize lists with >100 items
- Provide stable keys for list items (unique IDs, not index)
- Split state by update frequency
- Use concurrent features (useTransition, useDeferredValue) for responsiveness
After optimizing:
- Profile again to verify improvements
- Check bundle size reduction (if applicable)
- Ensure no regressions in functionality
Resources
- React Docs - Performance: https://react.dev/learn/render-and-commit
- React DevTools: Browser extension for profiling
- react-window: https://github.com/bvaughn/react-window
- Bundle analyzers: webpack-bundle-analyzer, rollup-plugin-visualizer
- Lighthouse: Chrome DevTools performance audit
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版本1.0.0
更新日期2026年3月16日
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创建2026年3月16日
最后更新2026年3月16日