valibot-fast-check

Generate fast-check arbitraries from Valibot schemas for property-based testing.

Installation

pnpm add valibot-fast-check

Quick Start

import { vfc } from "valibot-fast-check";
import * as v from "valibot";
import fc from "fast-check";

// Define a Valibot schema
const UserSchema = v.object({
	name: v.pipe(v.string(), v.minLength(1), v.maxLength(50)),
	age: v.pipe(v.number(), v.integer(), v.minValue(0), v.maxValue(120)),
	email: v.pipe(v.string(), v.email()),
});

// Generate fast-check arbitraries
const userArbitrary = vfc().inputOf(UserSchema);

// Use in property-based tests
fc.assert(
	fc.property(userArbitrary, (user) => {
		// Your test logic here
		const result = v.safeParse(UserSchema, user);
		expect(result.success).toBe(true);
	})
);

API Reference

Core Methods

vfc().inputOf(schema)

Generates arbitraries that produce valid input values for the given schema.

const schema = v.pipe(v.string(), v.email());
const arbitrary = vfc().inputOf(schema);
// Generates valid email strings

vfc().outputOf(schema)

Generates arbitraries that produce parsed/transformed output values for schemas with transformations.

const schema = v.pipe(v.string(), v.trim(), v.minLength(1));
const arbitrary = vfc().outputOf(schema);
// Generates trimmed, non-empty strings

vfc().override(schema, arbitrary)

Override generation for specific schemas with custom arbitraries.

const customSchema = v.string();
const customArbitrary = fc.constant("fixed-value");

const generator = vfc().override(customSchema, customArbitrary);
// Will use customArbitrary when encountering customSchema

Supported Schema Types

Primitive Types

• ✅ string - length (minLength, maxLength, length), content (startsWith, endsWith, includes, trim), formats (email, uuid, url), exact values (value, values)
• ✅ number - range (minValue, maxValue, gtValue, ltValue), constraints (integer, finite, safeInteger, multipleOf), exact values (value, values)
• ✅ bigint - range constraints and exact values
• ✅ boolean - with value constraints
• ✅ date - with range constraints and exact values
• ✅ undefined, null, void, any, unknown
• ✅ nan - generates Number.NaN

Composite Types

• ✅ object - recursive object generation
• ✅ array - with length constraints
• ✅ tuple - fixed-length arrays with typed elements
• ✅ map - generates Map instances
• ✅ set - generates Set instances with size constraints

Special Types

• ✅ optional - uses fc.option() with undefined
• ✅ nullable - uses fc.option() with null
• ✅ nullish - generates value, null, or undefined
• ✅ enum / picklist - picks from enum values
• ✅ literal - generates exact literal values
• ✅ union - generates from union alternatives
• ✅ function - generates callable functions
• ✅ symbol - generates unique symbols

Performance Optimizations

This library includes several performance optimizations over naive filtering approaches:

Range Constraints

Instead of generating random numbers and filtering:

// ❌ Slow: generates any number, filters most out
fc.integer().filter((x) => x >= 10 && x <= 20);

// ✅ Fast: generates only valid range
fc.integer({ min: 10, max: 20 });

Discrete Values

Direct generation for exact values:

// Schema: v.pipe(v.number(), v.value(42))
// ✅ Generates: fc.constant(42)

// Schema: v.pipe(v.string(), v.values(["a", "b", "c"]))
// ✅ Generates: fc.constantFrom("a", "b", "c")

String Formats and Content

Built-in optimizations for string constraints:

// Format constraints
// Schema: v.pipe(v.string(), v.email())
// ✅ Generates: fc.emailAddress() with Valibot's email regex

// Schema: v.pipe(v.string(), v.uuid())
// ✅ Generates: fc.uuid()

// Schema: v.pipe(v.string(), v.url())
// ✅ Generates: fc.webUrl()

// Content constraints (when used individually)
// Schema: v.pipe(v.string(), v.startsWith("prefix"))
// ✅ Generates: fc.string().map(s => "prefix" + s)

// Schema: v.pipe(v.string(), v.endsWith("suffix"))
// ✅ Generates: fc.string().map(s => s + "suffix")

// Multiple content constraints fall back to filterBySchema

Complex Validations

For complex or custom constraints, falls back to schema validation with efficiency monitoring:

// Custom validations automatically use filterBySchema
const schema = v.pipe(
	v.number(),
	v.check((x) => isPrime(x)) // Custom validation
);

// Constraints that can't be optimized
const schema2 = v.pipe(
	v.number(),
	v.notValue(5), // Uses filterBySchema
	v.notValues([1, 2, 3]) // Uses filterBySchema
);

// Multiple string content constraints
const schema3 = v.pipe(
	v.string(),
	v.startsWith("hello"),
	v.endsWith("world"),
	v.includes("test") // Falls back to filterBySchema
);

Error Handling

The library provides detailed error messages for unsupported schemas and generation failures:

// Unsupported schema type
try {
	vfc().inputOf(unsupportedSchema);
} catch (error) {
	// VFCUnsupportedSchemaError: Unable to generate valid values for Valibot schema. CustomType schemas are not supported.
}

// Low success rate from filterBySchema
try {
	const restrictiveSchema = v.pipe(
		v.number(),
		v.check((x) => x === Math.PI) // Extremely low success rate
	);
	const samples = fc.sample(vfc().inputOf(restrictiveSchema), 10);
} catch (error) {
	// VFCGenerationError: Unable to generate valid values for the passed Valibot schema.
	// Please provide an override for the schema at path '.'.
}

Examples

Basic Property Testing

import { vfc } from "valibot-fast-check";
import * as v from "valibot";
import fc from "fast-check";

const schema = v.object({
	username: v.pipe(v.string(), v.minLength(3), v.maxLength(20)),
	password: v.pipe(v.string(), v.minLength(8)),
	age: v.pipe(v.number(), v.integer(), v.minValue(13)),
});

fc.assert(
	fc.property(vfc().inputOf(schema), (data) => {
		// Test that all generated data is valid
		const result = v.safeParse(schema, data);
		expect(result.success).toBe(true);

		// Test business logic
		expect(data.username.length).toBeGreaterThanOrEqual(3);
		expect(data.age).toBeGreaterThanOrEqual(13);
	})
);

Complex Nested Schemas

const AddressSchema = v.object({
	street: v.string(),
	city: v.string(),
	zipCode: v.pipe(v.string(), v.regex(/^\d{5}$/)),
});

const PersonSchema = v.object({
	name: v.string(),
	addresses: v.array(AddressSchema),
	primaryAddress: v.optional(AddressSchema),
});

const personArbitrary = vfc().inputOf(PersonSchema);
// Generates complex nested objects with arrays and optional fields

Using Overrides

const schema = v.object({
	id: v.string(), // We want specific ID format
	data: v.any(),
});

const customGenerator = vfc().override(
	v.string(),
	fc.uuid() // All strings will be UUIDs
);

const arbitrary = customGenerator.inputOf(schema);

Current Limitations

• String combinations: Multiple content constraints with length requirements fall back to filterBySchema
• Custom validations: v.check() and v.custom() always use filtering and may have low success rates
• Unsupported constraints: v.notValue(), v.notValues() use filtering (low efficiency for large exclusion sets)
• Date generation: May occasionally produce NaN dates due to fast-check limitations
• Regex constraints: v.regex() not yet optimized (uses filterBySchema)

Acknowledgments

Inspired by zod-fast-check. This library brings the same concept to Valibot, leveraging Valibot's smaller bundle size.