React Performance Optimizer

Expert in diagnosing and fixing React performance issues to achieve buttery-smooth 60fps experiences.

When to Use

✅ Use for:

• Slow component re-renders
• Large lists (>100 items) causing lag
• Bundle size >500KB (gzipped)
• Time to Interactive >3 seconds
• Janky scrolling or animations
• Memory leaks from unmounted components

❌ NOT for:

• Apps with <10 components (premature optimization)
• Backend API slowness (fix the API)
• Network latency (use caching/CDN)
• Non-React frameworks (use framework-specific tools)

Quick Decision Tree

Is your React app slow?
├── Profiler shows >16ms renders? → Use memoization
├── Lists with >100 items? → Use virtualization
├── Bundle size >500KB? → Code splitting
├── Lighthouse score <70? → Multiple optimizations
└── Feels fast enough? → Don't optimize yet

---

Technology Selection

Performance Tools (2024)

Tool	Purpose	When to Use
React DevTools Profiler	Find slow components	Always start here
Lighthouse	Overall performance score	Before/after comparison
webpack-bundle-analyzer	Identify large dependencies	Bundle >500KB
why-did-you-render	Unnecessary re-renders	Debug re-render storms
React Compiler (2024+)	Automatic memoization	React 19+

Timeline:

• 2018: React.memo, useMemo, useCallback introduced
• 2020: Concurrent Mode (now Concurrent Rendering)
• 2022: Automatic batching in React 18
• 2024: React Compiler (automatic optimization)
• 2025+: React Compiler expected to replace manual memoization

---

Common Anti-Patterns

Anti-Pattern 1: Premature Memoization

Novice thinking: "Wrap everything in useMemo for speed"

Problem: Adds complexity and overhead for negligible gains.

Wrong approach:

// ❌ Over-optimization
function UserCard({ user }) {
  const fullName = useMemo(() => `${user.first} ${user.last}`, [user]);
  const age = useMemo(() => new Date().getFullYear() - user.birthYear, [user]);

  return <div>{fullName}, {age}</div>;
}

Why wrong: String concatenation is faster than useMemo overhead.

Correct approach:

// ✅ Simple is fast
function UserCard({ user }) {
  const fullName = `${user.first} ${user.last}`;
  const age = new Date().getFullYear() - user.birthYear;

  return <div>{fullName}, {age}</div>;
}

Rule of thumb: Only memoize if:

1. Computation takes >5ms (use Profiler to measure)
2. Result used in dependency array
3. Prevents child re-renders

---

Anti-Pattern 2: Not Memoizing Callbacks

Problem: New function instance on every render breaks React.memo.

Wrong approach:

// ❌ Child re-renders on every parent render
function Parent() {
  const [count, setCount] = useState(0);

  return (
    <Child onUpdate={() => setCount(count + 1)} />
  );
}

const Child = React.memo(({ onUpdate }) => {
  return <button onClick={onUpdate}>Update</button>;
});

Why wrong: Arrow function creates new reference → React.memo useless.

Correct approach:

// ✅ Stable callback reference
function Parent() {
  const [count, setCount] = useState(0);

  const handleUpdate = useCallback(() => {
    setCount(c => c + 1);  // Updater function avoids dependency
  }, []);

  return <Child onUpdate={handleUpdate} />;
}

const Child = React.memo(({ onUpdate }) => {
  return <button onClick={onUpdate}>Update</button>;
});

---

Anti-Pattern 3: Rendering Large Lists Without Virtualization

Problem: Rendering 1000+ DOM nodes causes lag.

Symptom: Scrolling feels janky, initial render slow.

Wrong approach:

// ❌ Renders all 10,000 items
function UserList({ users }) {
  return (
    <div>
      {users.map(user => (
        <UserCard key={user.id} user={user} />
      ))}
    </div>
  );
}

Correct approach:

// ✅ Only renders visible items
import { FixedSizeList } from 'react-window';

function UserList({ users }) {
  return (
    <FixedSizeList
      height={600}
      itemCount={users.length}
      itemSize={50}
      width="100%"
    >
      {({ index, style }) => (
        <div style={style}>
          <UserCard user={users[index]} />
        </div>
      )}
    </FixedSizeList>
  );
}

Impact: 10,000 items: 5 seconds → 50ms render time.

---

Anti-Pattern 4: No Code Splitting

Problem: 2MB bundle downloaded upfront, slow initial load.

Wrong approach:

// ❌ Everything in main bundle
import AdminPanel from './AdminPanel';  // 500KB
import Dashboard from './Dashboard';
import Settings from './Settings';

function App() {
  return (
    <Routes>
      <Route path="/admin" element={<AdminPanel />} />
      <Route path="/dashboard" element={<Dashboard />} />
      <Route path="/settings" element={<Settings />} />
    </Routes>
  );
}

Correct approach:

// ✅ Lazy load routes
import { lazy, Suspense } from 'react';

const AdminPanel = lazy(() => import('./AdminPanel'));
const Dashboard = lazy(() => import('./Dashboard'));
const Settings = lazy(() => import('./Settings'));

function App() {
  return (
    <Suspense fallback={<Loading />}>
      <Routes>
        <Route path="/admin" element={<AdminPanel />} />
        <Route path="/dashboard" element={<Dashboard />} />
        <Route path="/settings" element={<Settings />} />
      </Routes>
    </Suspense>
  );
}

Impact: Initial bundle: 2MB → 300KB.

---

Anti-Pattern 5: Expensive Operations in Render

Problem: Heavy computation on every render.

Wrong approach:

// ❌ Sorts on every render (even when data unchanged)
function ProductList({ products }) {
  const sorted = products.sort((a, b) => b.price - a.price);

  return <div>{sorted.map(p => <Product product={p} />)}</div>;
}

Correct approach:

// ✅ Memoize expensive operation
function ProductList({ products }) {
  const sorted = useMemo(
    () => [...products].sort((a, b) => b.price - a.price),
    [products]
  );

  return <div>{sorted.map(p => <Product product={p} />)}</div>;
}

---

Implementation Patterns

Pattern 1: React.memo for Pure Components

// Prevent re-render when props unchanged
const ExpensiveComponent = React.memo(({ data }) => {
  // Complex rendering logic
  return <div>{/* ... */}</div>;
});

// With custom comparison
const UserCard = React.memo(
  ({ user }) => <div>{user.name}</div>,
  (prevProps, nextProps) => {
    // Return true if props equal (skip re-render)
    return prevProps.user.id === nextProps.user.id;
  }
);

Pattern 2: useMemo for Expensive Calculations

function DataTable({ rows, columns }) {
  const sortedAndFiltered = useMemo(() => {
    console.log('Recomputing...');  // Only logs when rows/columns change

    return rows
      .filter(row => row.visible)
      .sort((a, b) => a.timestamp - b.timestamp);
  }, [rows, columns]);

  return <Table data={sortedAndFiltered} />;
}

Pattern 3: useCallback for Stable References

function SearchBox({ onSearch }) {
  const [query, setQuery] = useState('');

  // Stable reference, doesn't break child memoization
  const handleSubmit = useCallback(() => {
    onSearch(query);
  }, [query, onSearch]);

  return (
    <form onSubmit={handleSubmit}>
      <input value={query} onChange={e => setQuery(e.target.value)} />
    </form>
  );
}

Pattern 4: Virtualization (react-window)

import { VariableSizeList } from 'react-window';

function MessageList({ messages }) {
  const getItemSize = (index) => {
    // Dynamic heights based on content
    return messages[index].text.length > 100 ? 80 : 50;
  };

  return (
    <VariableSizeList
      height={600}
      itemCount={messages.length}
      itemSize={getItemSize}
      width="100%"
    >
      {({ index, style }) => (
        <div style={style}>
          <Message message={messages[index]} />
        </div>
      )}
    </VariableSizeList>
  );
}

Pattern 5: Code Splitting with React.lazy

// Route-based splitting
const routes = [
  { path: '/home', component: lazy(() => import('./Home')) },
  { path: '/about', component: lazy(() => import('./About')) },
  { path: '/contact', component: lazy(() => import('./Contact')) }
];

// Component-based splitting
const HeavyChart = lazy(() => import('./HeavyChart'));

function Dashboard() {
  const [showChart, setShowChart] = useState(false);

  return (
    <div>
      <button onClick={() => setShowChart(true)}>Show Chart</button>

      {showChart && (
        <Suspense fallback={<Spinner />}>
          <HeavyChart />
        </Suspense>
      )}
    </div>
  );
}

---

Production Checklist

□ Profiler analysis completed (identified slow components)
□ Large lists use virtualization (>100 items)
□ Routes code-split with React.lazy
□ Heavy components lazy-loaded
□ Callbacks memoized with useCallback
□ Expensive computations use useMemo
□ Pure components wrapped in React.memo
□ Bundle analyzed (no duplicate dependencies)
□ Tree-shaking enabled (ESM imports)
□ Images optimized and lazy-loaded
□ Lighthouse score >90
□ Time to Interactive <3 seconds

---

When to Use vs Avoid

Scenario	Optimize?
Rendering 1000+ list items	✅ Yes - virtualize
Sorting/filtering large arrays	✅ Yes - useMemo
Passing callbacks to memoized children	✅ Yes - useCallback
String concatenation	❌ No - fast enough
Simple arithmetic	❌ No - don't memoize
10-item list	❌ No - premature optimization

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References

• /references/profiling-guide.md - How to use React DevTools Profiler
• /references/bundle-optimization.md - Reduce bundle size strategies
• /references/memory-leaks.md - Detect and fix memory leaks

Scripts

• scripts/performance_audit.ts - Automated performance checks
• scripts/bundle_analyzer.sh - Analyze and visualize bundle

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This skill guides: React performance optimization | Memoization | Virtualization | Code splitting | Bundle optimization | Profiling