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@nds-stack/bun-schema

v0.1.0-alpha.0

Published

Zero-dependency schema validation for Bun — TypeScript-first, Zod-like API

Readme

@nds-stack/bun-schema

Zero-dependency schema validation for Bun — TypeScript-first, Zod-like API.

import { s, Infer } from "@nds-stack/bun-schema";

const UserSchema = s.object({
  name: s.string().min(2).max(100),
  email: s.string().email(),
  age: s.number().int().min(0).optional(),
});

type User = Infer<typeof UserSchema>;

const user = UserSchema.parse({ name: "Alice", email: "[email protected]", age: 30 });

Why bun-schema

Bun has no built-in validation library, and existing options (Zod, Valibot, TypeBox) bundle Node.js polyfills that Bun doesn't need. bun-schema is:

  • Zero dependencies — pure TypeScript, uses only Bun built-in APIs
  • Bun-optimized — no polyfills, no Node.js compatibility layer
  • TypeScript-first — full type inference from schemas
  • Familiar API — Zod-like chaining with .parse(), .safeParse(), type inference
  • Tree-shakeable — import only the types you need

Installation

bun add @nds-stack/bun-schema

How It Works

Schema<T> is the abstract base class. Each schema type (StringSchema, NumberSchema, etc.) extends it and implements _safeParse() which recursively validates data and returns a Result<T> discriminated union:

  • { success: true, value: T } on valid input
  • { success: false, error: ValidationError } on invalid input — with an issues array tracking each failure's field path and message

Validation is lazy: checks are accumulated via method chaining (.min(), .email(), etc.) and executed in order when .parse() or .safeParse() is called. This enables tree-shaking — only the checks you use are included in your bundle.

The s builder object is the entry point: s.string(), s.number(), s.object(), etc. Each call creates a new schema instance.

TypeScript types are inferred via the Infer<T> utility type, reading the generic parameter from Schema<T>. Object schemas map each key's schema type to the corresponding property type.

// Flow:
s.string().min(3).email()
  → new StringSchema()
  → adds "min(3)" check to internal list
  → adds "email" check to internal list
  → when .parse() called, runs all checks in order

API

s.string()

| Method | Description | |--------|-------------| | .min(n) | Minimum string length | | .max(n) | Maximum string length | | .length(n) | Exact string length | | .email() | Valid email format | | .url() | Valid URL format | | .regex(pattern) | Match regular expression | | .includes(substr) | Must include substring | | .startsWith(prefix) | Must start with prefix | | .endsWith(suffix) | Must end with suffix | | .coerce() | Coerce input to string |

s.number()

| Method | Description | |--------|-------------| | .min(n) | Minimum value | | .max(n) | Maximum value | | .int() | Must be integer | | .positive() | Must be > 0 | | .negative() | Must be < 0 | | .multipleOf(n) | Must be divisible by n | | .finite() | Must be finite | | .coerce() | Coerce input to number |

s.boolean()

| Method | Description | |--------|-------------| | .coerce() | Coerce "true"/"false" strings |

s.object(shape)

| Method | Description | |--------|-------------| | .strict() | Reject unknown keys | | .passthrough() | Allow unknown keys |

s.array(item)

| Method | Description | |--------|-------------| | .min(n) | Minimum array length | | .max(n) | Maximum array length | | .length(n) | Exact array length |

Modifiers

| Method | Description | |--------|-------------| | .optional() | Allow undefined | | .nullable() | Allow null | | .pipe(schema) | Chain validation | | .parse(value) | Validate and return or throw | | .safeParse(value) | Validate and return Result<T> |

s.union(schemas)

Tries each schema in order, returns first match.

Type Inference

import { s, Infer } from "@nds-stack/bun-schema";

const schema = s.object({ name: s.string(), age: s.number() });
type T = Infer<typeof schema>; // { name: string; age: number }

Error Handling

.parse() throws ValidationError on failure. .safeParse() returns Result<T> — a discriminated union:

const result = schema.safeParse(data);
if (result.success) {
  console.log(result.value); // T
} else {
  console.log(result.error.issues); // ValidationIssue[]
  // [{ path: ["email"], message: "Invalid email" }]
}

Limitations

  • No s.date() support yet
  • No s.record() key-value map support
  • No s.tuple() fixed-length tuple support
  • No s.enum() string literal union support
  • No s.instanceOf() class instance check
  • No lazy/recursive schema support
  • No Standard Schema V1 compatibility yet

Multi-Instance / Cross-Boundary

Each Schema instance is stateless and immutable (once built). Schemas are safe to use across workers, serverless invocations, and concurrent contexts:

import { s } from "@nds-stack/bun-schema";

const schema = s.object({ name: s.string() });

// Safe in multiple workers
new Worker(new URL("./worker.ts", import.meta.url));

// worker.ts
import { s } from "@nds-stack/bun-schema";
const localSchema = s.object({ name: s.string() }); // independent instance

Customization Guide

Custom Validation with .pipe()

const PositiveInt = s.number().int().pipe(s.number().positive());

Wrap in your own class

import { s, Infer } from "@nds-stack/bun-schema";

class ValidatedUser {
  readonly name: string;
  readonly email: string;

  constructor(data: unknown) {
    const parsed = UserSchema.parse(data);
    this.name = parsed.name;
    this.email = parsed.email;
  }
}

Comparison Table

| Aspect | @nds-stack/bun-schema | zod | valibot | typebox | |--------|-------------------------|-------|-----------|-----------| | Dependencies | 0 | 1.5KB | 0 | 0 | | Bun-native | ✅ | ❌ Polyfills | ❌ Polyfills | ❌ Polyfills | | Bundle size | ~3KB | ~12KB | ~2KB (minimal) | ~6KB | | Type inference | ✅ | ✅ | ✅ | ✅ | | Tree-shakeable | ✅ | ⚠️ Partial | ✅ | ❌ | | Zod-like API | ✅ | Native | Similar | ❌ JSON Schema | | Coercion | ✅ | ✅ | ✅ | ❌ |

Benchmarks

bun run bench
Benchmark: @nds-stack/bun-schema (10,000 iterations each)
==================================================================================
  Operation                                                 Throughput
==================================================================================
  native: typeof x === 'string'                              2.512.373 ops/s
  native: typeof x === 'number'                              5.564.830 ops/s
  s.string().parse                                           1.479.421 ops/s
  s.number().parse                                           1.109.004 ops/s
  s.boolean().parse                                          2.118.061 ops/s
  s.object().parse (valid 3 fields)                            299.093 ops/s
  s.array().parse (5 items)                                    516.657 ops/s
  s.union().parse                                              262.655 ops/s
==================================================================================

| Operation | Throughput | Baseline | Overhead | |-----------|-----------|----------|----------| | typeof string (native) | 2,512,373 ops/s | — | — | | s.string().parse | 1,479,421 ops/s | 2.5M ops/s | ~41% | | typeof number (native) | 5,564,830 ops/s | — | — | | s.number().parse | 1,109,004 ops/s | 5.6M ops/s | ~80% | | s.boolean().parse | 2,118,061 ops/s | — | — | | s.object().parse (3 fields) | 299,093 ops/s | — | — | | s.array().parse (5 items) | 516,657 ops/s | — | — | | s.union().parse | 262,655 ops/s | — | — |

Note: Overhead is expected — schema validation includes type checking, constraint validation, error collection, and path tracking. Results vary by hardware — run bun run bench on your machine.

Real-World Example

API Input Validation:

import { s, Infer, ValidationError } from "@nds-stack/bun-schema";

const CreateUserSchema = s.object({
  username: s.string().min(3).max(50).regex(/^[a-zA-Z0-9_]+$/),
  email: s.string().email(),
  age: s.number().int().min(13).max(150).optional(),
});

type CreateUserInput = Infer<typeof CreateUserSchema>;

async function handleRequest(request: Request): Promise<Response> {
  try {
    const body = await request.json();
    const input: CreateUserInput = CreateUserSchema.parse(body);
    // input is fully typed here
    return new Response(JSON.stringify({ ok: true }), { status: 201 });
  } catch (e) {
    if (e instanceof ValidationError) {
      return new Response(JSON.stringify({ error: e.issues }), { status: 400 });
    }
    return new Response("Internal error", { status: 500 });
  }
}

License

MIT