Conditional Class Composition: classcat vs classnames vs clsx

When building dynamic UIs, we often need to toggle CSS classes based on component state, props, or theme context. Manually managing this with template literals or ternaries quickly becomes messy:

// Painful manual approach
const buttonClass = 
  'btn ' + 
  (primary ? 'btn--primary ' : '') +
  (disabled ? 'btn--disabled ' : '') +
  (size === 'large' ? 'btn--large' : '');

This is where classcat, classnames, and clsx come in — all three solve the same core problem but with different trade-offs in API design, performance, and predictability.

🧩 Input Handling: Arrays vs Objects vs Both

classnames accepts almost anything:

• Strings, arrays, objects, even nested combinations
• Falsy values (null, undefined, false, 0) are safely ignored
• Object keys become class names when their values are truthy

// classnames example
import cn from 'classnames';

const classes = cn(
  'base',
  { active: isActive, disabled: isDisabled },
  [extraClass, { hidden: shouldHide }]
);
// → 'base active hidden' (if isActive/shouldHide are true)

clsx behaves similarly but with stricter rules:

• Also supports strings, arrays, and objects
• Drops all falsy values consistently
• Doesn’t deeply flatten nested arrays beyond one level (by design)

// clsx example
import clsx from 'clsx';

const classes = clsx(
  'btn',
  { 'btn--primary': primary },
  size && `btn--${size}`
);
// → 'btn btn--primary btn--large'

classcat only accepts arrays:

• No object support — conditions must be pre-resolved
• Forces explicit structure, which can prevent accidental bugs
• Slightly faster because it skips type-checking logic

// classcat example
import cc from 'classcat';

const classes = cc([
  'btn',
  primary && 'btn--primary',
  size && `btn--${size}`,
  disabled && 'btn--disabled'
]);
// → 'btn btn--primary btn--large'

⚡ Performance Characteristics

All three are fast enough for typical use cases, but differences emerge under stress:

• classcat wins in raw speed because it assumes flat arrays and does zero object inspection. No branching on input types means fewer CPU cycles.
• clsx is optimized for common patterns (like { foo: true }) and avoids deep recursion, making it nearly as fast as classcat in practice.
• classnames carries slight overhead from its permissive input handling — it recursively flattens deeply nested structures and checks every value’s truthiness.

In a tight loop rendering thousands of components (e.g., data grids), classcat or clsx may show measurable gains. For most apps, the difference is negligible.

🛠️ Developer Experience & Ecosystem Fit

classnames feels familiar to veterans — it’s been around since the early React days and works everywhere. Its forgiving nature helps during rapid prototyping but can mask logic errors (e.g., accidentally passing 0 as a class).

clsx has become the go-to in modern React/Tailwind stacks. Its name is short, its behavior is predictable, and it plays well with TypeScript. Many UI libraries (like Radix UI) use it internally.

classcat appeals to teams that value explicitness over convenience. Because it rejects objects, you’re forced to handle conditional logic before calling it — which some consider a feature, not a limitation.

🔁 Edge Cases and Gotchas

• Falsy numbers: classnames and clsx both drop 0, but classnames once had quirks with numeric keys in objects (now fixed). classcat never sees this issue since it doesn’t accept objects.
• Nested arrays: classnames deeply flattens [ ['a', ['b']] ] → 'a b'. clsx only flattens one level. classcat expects flat arrays and won’t recurse.
• Boolean classes: With clsx({ active: true }) you get 'active'. With classcat, you’d write active && 'active' — more verbose but clearer in intent.

✅ When to Use Which

• Greenfield React + Tailwind project? → clsx. It’s concise, fast, and widely adopted.
• Maintaining a legacy app with mixed input patterns? → classnames. Its flexibility reduces migration friction.
• Building a high-performance component library or animation system? → classcat. The enforced structure and speed matter here.

💡 Final Recommendation

For most new projects in 2024, clsx strikes the best balance: it’s fast, clean, and integrates seamlessly with modern tooling. Reserve classcat for performance-critical paths where you control all inputs, and lean on classnames only when dealing with unpredictable or legacy data shapes.

Remember — the best class composer is the one that disappears into your workflow. All three do the job; choose based on your team’s style, not hype.