React Component Performance
Overview
Identify render hotspots, isolate expensive updates, and apply targeted optimizations without changing UI behavior.
Workflow
- Reproduce or describe the slowdown.
- Identify what triggers re-renders (state updates, props churn, effects).
- Isolate fast-changing state from heavy subtrees.
- Stabilize props and handlers; memoize where it pays off.
- Reduce expensive work (computation, DOM size, list length).
- Validate: open React DevTools Profiler → record the interaction → inspect the Flamegraph for components rendering longer than ~16 ms → compare against a pre-optimization baseline recording.
Checklist
- Measure: use React DevTools Profiler or log renders; capture baseline.
- Find churn: identify state updated on a timer, scroll, input, or animation.
- Split: move ticking state into a child; keep heavy lists static.
- Memoize: wrap leaf rows with
memoonly when props are stable. - Stabilize props: use
useCallback/useMemofor handlers and derived values. - Avoid derived work in render: precompute, or compute inside memoized helpers.
- Control list size: window/virtualize long lists; avoid rendering hidden items.
- Keys: ensure stable keys; avoid index when order can change.
- Effects: verify dependency arrays; avoid effects that re-run on every render.
- Style/layout: watch for expensive layout thrash or large Markdown/diff renders.
Optimization Patterns
Isolate ticking state
Move a timer or animation counter into a child so the parent list never re-renders on each tick.
// ❌ Before – entire parent (and list) re-renders every second
function Dashboard({ items }: { items: Item[] }) {
const [tick, setTick] = useState(0);
useEffect(() => {
const id = setInterval(() => setTick(t => t + 1), 1000);
return () => clearInterval(id);
}, []);
return (
<>
<Clock tick={tick} />
<ExpensiveList items={items} /> {/* re-renders every second */}
</>
);
}
// ✅ After – only <Clock> re-renders; list is untouched
function Clock() {
const [tick, setTick] = useState(0);
useEffect(() => {
const id = setInterval(() => setTick(t => t + 1), 1000);
return () => clearInterval(id);
}, []);
return <span>{tick}s</span>;
}
function Dashboard({ items }: { items: Item[] }) {
return (
<>
<Clock />
<ExpensiveList items={items} />
</>
);
}
Stabilize callbacks with useCallback + memo
// ❌ Before – new handler reference on every render busts Row memo
function List({ items }: { items: Item[] }) {
const handleClick = (id: string) => console.log(id); // new ref each render
return items.map(item => <Row key={item.id} item={item} onClick={handleClick} />);
}
// ✅ After – stable handler; Row only re-renders when its own item changes
const Row = memo(({ item, onClick }: RowProps) => (
<li onClick={() => onClick(item.id)}>{item.name}</li>
));
function List({ items }: { items: Item[] }) {
const handleClick = useCallback((id: string) => console.log(id), []);
return items.map(item => <Row key={item.id} item={item} onClick={handleClick} />);
}
Prefer derived data outside render
// ❌ Before – recomputes on every render
function Summary({ orders }: { orders: Order[] }) {
const total = orders.reduce((sum, o) => sum + o.amount, 0); // runs every render
return <p>Total: {total}</p>;
}
// ✅ After – recomputes only when orders changes
function Summary({ orders }: { orders: Order[] }) {
const total = useMemo(() => orders.reduce((sum, o) => sum + o.amount, 0), [orders]);
return <p>Total: {total}</p>;
}
Additional patterns
- Split rows: extract list rows into memoized components with narrow props.
- Defer heavy rendering: lazy-render or collapse expensive content until expanded.
Profiling Validation Steps
- Open React DevTools → Profiler tab.
- Click Record, perform the slow interaction, then Stop.
- Switch to Flamegraph view; any bar labeled with a component and time > ~16 ms is a candidate.
- Use Ranked chart to sort by self render time and target the top offenders.
- Apply one optimization at a time, re-record, and compare render counts and durations against the baseline.
Example Reference
Load references/examples.md when the user wants a concrete refactor example.