react-performance-optimization

---
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.
keywords:
  - React optimization
  - React performance
  - React.memo
  - bundle size
  - code splitting
  - lazy loading
  - re-render
  - useCallback
  - useMemo
  - virtualization
file_patterns:
  - '**/*.spec.ts'
  - '**/*.test.ts'
  - '**/*.test.tsx'
  - '**/*.ts'
  - '**/*.tsx'
  - '**/package.json'
  - '**/tests/**/*.ts'
  - '**/tests/**/*.tsx'
  - '**/tsconfig.json'
confidence: 0.76
---

# 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
1. **Profile first**: Use React DevTools Profiler to identify actual bottlenecks
2. **Measure impact**: Verify optimization improves performance
3. **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
```bash
# 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 `useCallback` for stable function references
- Check for inline objects/arrays in props

**For expensive computations:**
- Use `useMemo` to 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
```bash
# Record new Profiler session
# Compare before/after metrics
# Ensure optimization actually helped
```

## Common Patterns

### Memoize Expensive Components
```jsx
import { memo } from 'react';

const ExpensiveList = memo(({ items, onItemClick }) => {
  return items.map(item => (
    <Item key={item.id} data={item} onClick={onItemClick} />
  ));
});
```

### Cache Computed Values
```jsx
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
```jsx
import { useCallback } from 'react';

function Parent() {
  const handleClick = useCallback((id) => {
    console.log('Clicked:', id);
  }, []);

  return <MemoizedChild onClick={handleClick} />;
}
```

### Code Split Routes
```jsx
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
```jsx
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

1. **Over-memoization**: Don't memoize simple, fast components (adds overhead)
2. **Inline objects/arrays**: New references break memoization (`config={{ theme: 'dark' }}`)
3. **Missing dependencies**: Stale closures in useCallback/useMemo
4. **Index as key**: Breaks reconciliation when list order changes
5. **Single large context**: Causes widespread re-renders on any update
6. **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

• SKILL.md 7 KB
• references/code-splitting.md 3 KB
• references/common-pitfalls.md 8 KB
• references/concurrent-features.md 3 KB
• references/memoization.md 4 KB
• references/profiling-debugging.md 5 KB
• references/state-management.md 4 KB
• references/virtualization.md 3 KB
• validation/rubric.yaml 2 KB