@adamalmqvist/zod

v3.22.4

Published

2 months ago

TypeScript-first schema declaration and validation library with static type inference

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adamalmqvist

typescript schema validation type inference

These docs have been translated into Chinese.

Introduction

Zod is a TypeScript-first schema declaration and validation library. I'm using the term "schema" to broadly refer to any data type, from a simple string to a complex nested object.

Zod is designed to be as developer-friendly as possible. The goal is to eliminate duplicative type declarations. With Zod, you declare a validator once and Zod will automatically infer the static TypeScript type. It's easy to compose simpler types into complex data structures.

Some other great aspects:

Zero dependencies
Works in Node.js and all modern browsers
Tiny: 8kb minified + zipped
Immutable: methods (e.g. .optional()) return a new instance
Concise, chainable interface
Functional approach: parse, don't validate
Works with plain JavaScript too! You don't need to use TypeScript.

Ecosystem

There are a growing number of tools that are built atop or support Zod natively! If you've built a tool or library on top of Zod, tell me about it on Twitter or start a Discussion. I'll add it below and tweet it out.

Resources

API libraries

tRPC: Build end-to-end typesafe APIs without GraphQL.
@anatine/zod-nestjs: Helper methods for using Zod in a NestJS project.
zod-endpoints: Contract-first strictly typed endpoints with Zod. OpenAPI compatible.
zhttp: An OpenAPI compatible, strictly typed http library with Zod input and response validation.
domain-functions: Decouple your business logic from your framework using composable functions. With first-class type inference from end to end powered by Zod schemas.
@zodios/core: A typescript API client with runtime and compile time validation backed by axios and zod.
express-zod-api: Build Express-based APIs with I/O schema validation and custom middlewares.
tapiduck: End-to-end typesafe JSON APIs with Zod and Express; a bit like tRPC, but simpler.
koa-zod-router: Create typesafe routes in Koa with I/O validation using Zod.

Form integrations

react-hook-form: A first-party Zod resolver for React Hook Form.
zod-validation-error: Generate user-friendly error messages from ZodErrors.
zod-formik-adapter: A community-maintained Formik adapter for Zod.
react-zorm: Standalone <form> generation and validation for React using Zod.
zodix: Zod utilities for FormData and URLSearchParams in Remix loaders and actions.
conform: A typesafe form validation library for progressive enhancement of HTML forms. Works with Remix and Next.js.
remix-params-helper: Simplify integration of Zod with standard URLSearchParams and FormData for Remix apps.
formik-validator-zod: Formik-compliant validator library that simplifies using Zod with Formik.
zod-i18n-map: Useful for translating Zod error messages.
@modular-forms/solid: Modular form library for SolidJS that supports Zod for validation.
houseform: A React form library that uses Zod for validation.
sveltekit-superforms: Supercharged form library for SvelteKit with Zod validation.
mobx-zod-form: Data-first form builder based on MobX & Zod.
@vee-validate/zod: Form library for Vue.js with Zod schema validation.

Zod to X

zod-to-ts: Generate TypeScript definitions from Zod schemas.
zod-to-json-schema: Convert your Zod schemas into JSON Schemas.
@anatine/zod-openapi: Converts a Zod schema to an OpenAPI v3.x SchemaObject.
zod-fast-check: Generate fast-check arbitraries from Zod schemas.
zod-dto: Generate Nest.js DTOs from a Zod schema.
fastify-type-provider-zod: Create Fastify type providers from Zod schemas.
zod-to-openapi: Generate full OpenAPI (Swagger) docs from Zod, including schemas, endpoints & parameters.
nestjs-graphql-zod: Generates NestJS GraphQL model classes from Zod schemas. Provides GraphQL method decorators working with Zod schemas.
zod-openapi: Create full OpenAPI v3.x documentation from Zod schemas.
fastify-zod-openapi: Fastify type provider, validation, serialization and @fastify/swagger support for Zod schemas.
typeschema: Universal adapter for schema validation.

X to Zod

ts-to-zod: Convert TypeScript definitions into Zod schemas.
@runtyping/zod: Generate Zod from static types & JSON schema.
json-schema-to-zod: Convert your JSON Schemas into Zod schemas. Live demo.
json-to-zod: Convert JSON objects into Zod schemas. Live demo.
graphql-codegen-typescript-validation-schema: GraphQL Code Generator plugin to generate form validation schema from your GraphQL schema.
zod-prisma: Generate Zod schemas from your Prisma schema.
Supervillain: Generate Zod schemas from your Go structs.
prisma-zod-generator: Emit Zod schemas from your Prisma schema.
prisma-trpc-generator: Emit fully implemented tRPC routers and their validation schemas using Zod.
zod-prisma-types Create Zod types from your Prisma models.
quicktype: Convert JSON objects and JSON schemas into Zod schemas.
@sanity-typed/zod: Generate Zod Schemas from Sanity Schemas.

Mocking

@anatine/zod-mock: Generate mock data from a Zod schema. Powered by faker.js.
zod-mocking: Generate mock data from your Zod schemas.
zod-fixture: Use your zod schemas to automate the generation of non-relevant test fixtures in a deterministic way.
zocker: Generate plausible mock-data from your schemas.
zodock Generate mock data based on Zod schemas.

Powered by Zod

freerstore: Firestore cost optimizer.
slonik: Node.js Postgres client with strong Zod integration.
soly: Create CLI applications with zod.
pastel: Create CLI applications with react, zod, and ink.
zod-xlsx: A xlsx based resource validator using Zod schemas.
znv: Type-safe environment parsing and validation for Node.js with Zod schemas.
zod-config: Load configurations across multiple sources with flexible adapters, ensuring type safety with Zod.

Utilities for Zod

zod_utilz: Framework agnostic utilities for Zod.
zod-sandbox: Controlled environment for testing zod schemas. Live demo.
zod-dev: Conditionally disables Zod runtime parsing in production.

Installation

Requirements

TypeScript 4.5+!
You must enable strict mode in your tsconfig.json. This is a best practice for all TypeScript projects.
```
// tsconfig.json
{
  // ...
  "compilerOptions": {
    // ...
    "strict": true
  }
}
```

From `npm` (Node/Bun)

npm install zod       # npm
yarn add zod          # yarn
bun add zod           # bun
pnpm add zod          # pnpm

Zod also publishes a canary version on every commit. To install the canary:

npm install zod@canary       # npm
yarn add zod@canary          # yarn
bun add zod@canary           # bun
pnpm add zod@canary          # pnpm

From `deno.land/x` (Deno)

Unlike Node, Deno relies on direct URL imports instead of a package manager like NPM. Zod is available on deno.land/x. The latest version can be imported like so:

import { z } from "https://deno.land/x/zod/mod.ts";

You can also specify a particular version:

import { z } from "https://deno.land/x/[email protected]/mod.ts";

The rest of this README assumes you are using npm and importing directly from the "zod" package.

Basic usage

Creating a simple string schema

import { z } from "zod";

// creating a schema for strings
const mySchema = z.string();

// parsing
mySchema.parse("tuna"); // => "tuna"
mySchema.parse(12); // => throws ZodError

// "safe" parsing (doesn't throw error if validation fails)
mySchema.safeParse("tuna"); // => { success: true; data: "tuna" }
mySchema.safeParse(12); // => { success: false; error: ZodError }

Creating an object schema

import { z } from "zod";

const User = z.object({
  username: z.string(),
});

User.parse({ username: "Ludwig" });

// extract the inferred type
type User = z.infer<typeof User>;
// { username: string }

Primitives

import { z } from "zod";

// primitive values
z.string();
z.number();
z.bigint();
z.boolean();
z.date();
z.symbol();

// empty types
z.undefined();
z.null();
z.void(); // accepts undefined

// catch-all types
// allows any value
z.any();
z.unknown();

// never type
// allows no values
z.never();

Coercion for primitives

Zod now provides a more convenient way to coerce primitive values.

const schema = z.coerce.string();
schema.parse("tuna"); // => "tuna"
schema.parse(12); // => "12"

During the parsing step, the input is passed through the String() function, which is a JavaScript built-in for coercing data into strings.

The returned schema is a normal ZodString instance so you can use all string methods.

z.coerce.string().email().min(5);

How coercion works

All primitive types support coercion. Zod coerces all inputs using the built-in constructors: String(input), Number(input), new Date(input), etc.

z.coerce.string(); // String(input)
z.coerce.number(); // Number(input)
z.coerce.boolean(); // Boolean(input)
z.coerce.bigint(); // BigInt(input)
z.coerce.date(); // new Date(input)

Note that some behavior may not be what you expect.

schema.parse(true); // => "true"
schema.parse(undefined); // => "undefined"
schema.parse(null); // => "null"

For more control over coercion logic, consider using z.preprocess or z.pipe().

Boolean coercion

Zod's approach to coercion is very simple! It passes the value into the Boolean(value) function, that's it. Any truthy value will resolve to true, any falsy value will resolve to false.

z.coerce.boolean().parse("tuna"); // => true
z.coerce.boolean().parse("true"); // => true
z.coerce.boolean().parse("false"); // => true
z.coerce.boolean().parse(1); // => true
z.coerce.boolean().parse([]); // => true

z.coerce.boolean().parse(0); // => false
z.coerce.boolean().parse(undefined); // => false
z.coerce.boolean().parse(null); // => false

Literals

Literal schemas represent a literal type, like "hello world" or 5.

const tuna = z.literal("tuna");
const twelve = z.literal(12);
const twobig = z.literal(2n); // bigint literal
const tru = z.literal(true);

const terrificSymbol = Symbol("terrific");
const terrific = z.literal(terrificSymbol);

// retrieve literal value
tuna.value; // "tuna"

Currently there is no support for Date literals in Zod. If you have a use case for this feature, please file an issue.

Strings

Zod includes a handful of string-specific validations.

// validations
z.string().max(5);
z.string().min(5);
z.string().length(5);
z.string().email();
z.string().url();
z.string().emoji();
z.string().uuid();
z.string().cuid();
z.string().cuid2();
z.string().ulid();
z.string().regex(regex);
z.string().includes(string);
z.string().startsWith(string);
z.string().endsWith(string);
z.string().datetime(); // ISO 8601; default is without UTC offset, see below for options
z.string().ip(); // defaults to IPv4 and IPv6, see below for options

// transformations
z.string().trim(); // trim whitespace
z.string().toLowerCase(); // toLowerCase
z.string().toUpperCase(); // toUpperCase

Check out validator.js for a bunch of other useful string validation functions that can be used in conjunction with Refinements.

You can customize some common error messages when creating a string schema.

const name = z.string({
  required_error: "Name is required",
  invalid_type_error: "Name must be a string",
});

When using validation methods, you can pass in an additional argument to provide a custom error message.

z.string().min(5, { message: "Must be 5 or more characters long" });
z.string().max(5, { message: "Must be 5 or fewer characters long" });
z.string().length(5, { message: "Must be exactly 5 characters long" });
z.string().email({ message: "Invalid email address" });
z.string().url({ message: "Invalid url" });
z.string().emoji({ message: "Contains non-emoji characters" });
z.string().uuid({ message: "Invalid UUID" });
z.string().includes("tuna", { message: "Must include tuna" });
z.string().startsWith("https://", { message: "Must provide secure URL" });
z.string().endsWith(".com", { message: "Only .com domains allowed" });
z.string().datetime({ message: "Invalid datetime string! Must be UTC." });
z.string().ip({ message: "Invalid IP address" });

ISO datetimes

The z.string().datetime() method enforces ISO 8601; default is no timezone offsets and arbitrary sub-second decimal precision.

const datetime = z.string().datetime();

datetime.parse("2020-01-01T00:00:00Z"); // pass
datetime.parse("2020-01-01T00:00:00.123Z"); // pass
datetime.parse("2020-01-01T00:00:00.123456Z"); // pass (arbitrary precision)
datetime.parse("2020-01-01T00:00:00+02:00"); // fail (no offsets allowed)

Timezone offsets can be allowed by setting the offset option to true.

const datetime = z.string().datetime({ offset: true });

datetime.parse("2020-01-01T00:00:00+02:00"); // pass
datetime.parse("2020-01-01T00:00:00.123+02:00"); // pass (millis optional)
datetime.parse("2020-01-01T00:00:00.123+0200"); // pass (millis optional)
datetime.parse("2020-01-01T00:00:00.123+02"); // pass (only offset hours)
datetime.parse("2020-01-01T00:00:00Z"); // pass (Z still supported)

You can additionally constrain the allowable precision. By default, arbitrary sub-second precision is supported (but optional).

const datetime = z.string().datetime({ precision: 3 });

datetime.parse("2020-01-01T00:00:00.123Z"); // pass
datetime.parse("2020-01-01T00:00:00Z"); // fail
datetime.parse("2020-01-01T00:00:00.123456Z"); // fail

IP addresses

The z.string().ip() method by default validate IPv4 and IPv6.

const ip = z.string().ip();

ip.parse("192.168.1.1"); // pass
ip.parse("84d5:51a0:9114:1855:4cfa:f2d7:1f12:7003"); // pass
ip.parse("84d5:51a0:9114:1855:4cfa:f2d7:1f12:192.168.1.1"); // pass

ip.parse("256.1.1.1"); // fail
ip.parse("84d5:51a0:9114:gggg:4cfa:f2d7:1f12:7003"); // fail

You can additionally set the IP version.

const ipv4 = z.string().ip({ version: "v4" });
ipv4.parse("84d5:51a0:9114:1855:4cfa:f2d7:1f12:7003"); // fail

const ipv6 = z.string().ip({ version: "v6" });
ipv6.parse("192.168.1.1"); // fail

Numbers

You can customize certain error messages when creating a number schema.

const age = z.number({
  required_error: "Age is required",
  invalid_type_error: "Age must be a number",
});

Zod includes a handful of number-specific validations.

z.number().gt(5);
z.number().gte(5); // alias .min(5)
z.number().lt(5);
z.number().lte(5); // alias .max(5)

z.number().int(); // value must be an integer

z.number().positive(); //     > 0
z.number().nonnegative(); //  >= 0
z.number().negative(); //     < 0
z.number().nonpositive(); //  <= 0

z.number().multipleOf(5); // Evenly divisible by 5. Alias .step(5)

z.number().finite(); // value must be finite, not Infinity or -Infinity
z.number().safe(); // value must be between Number.MIN_SAFE_INTEGER and Number.MAX_SAFE_INTEGER

Optionally, you can pass in a second argument to provide a custom error message.

z.number().lte(5, { message: "this👏is👏too👏big" });

BigInts

Zod includes a handful of bigint-specific validations.

z.bigint().gt(5n);
z.bigint().gte(5n); // alias `.min(5n)`
z.bigint().lt(5n);
z.bigint().lte(5n); // alias `.max(5n)`

z.bigint().positive(); // > 0n
z.bigint().nonnegative(); // >= 0n
z.bigint().negative(); // < 0n
z.bigint().nonpositive(); // <= 0n

z.bigint().multipleOf(5n); // Evenly divisible by 5n.

NaNs

You can customize certain error messages when creating a nan schema.

const isNaN = z.nan({
  required_error: "isNaN is required",
  invalid_type_error: "isNaN must be 'not a number'",
});

Booleans

You can customize certain error messages when creating a boolean schema.

const isActive = z.boolean({
  required_error: "isActive is required",
  invalid_type_error: "isActive must be a boolean",
});

Dates

Use z.date() to validate Date instances.

z.date().safeParse(new Date()); // success: true
z.date().safeParse("2022-01-12T00:00:00.000Z"); // success: false

You can customize certain error messages when creating a date schema.

const myDateSchema = z.date({
  required_error: "Please select a date and time",
  invalid_type_error: "That's not a date!",
});

Zod provides a handful of date-specific validations.

z.date().min(new Date("1900-01-01"), { message: "Too old" });
z.date().max(new Date(), { message: "Too young!" });

Coercion to Date

Since zod 3.20, use z.coerce.date() to pass the input through new Date(input).

const dateSchema = z.coerce.date();
type DateSchema = z.infer<typeof dateSchema>;
// type DateSchema = Date

/* valid dates */
console.log(dateSchema.safeParse("2023-01-10T00:00:00.000Z").success); // true
console.log(dateSchema.safeParse("2023-01-10").success); // true
console.log(dateSchema.safeParse("1/10/23").success); // true
console.log(dateSchema.safeParse(new Date("1/10/23")).success); // true

/* invalid dates */
console.log(dateSchema.safeParse("2023-13-10").success); // false
console.log(dateSchema.safeParse("0000-00-00").success); // false

For older zod versions, use z.preprocess like described in this thread.

Zod enums

const FishEnum = z.enum(["Salmon", "Tuna", "Trout"]);
type FishEnum = z.infer<typeof FishEnum>;
// 'Salmon' | 'Tuna' | 'Trout'

z.enum is a Zod-native way to declare a schema with a fixed set of allowable string values. Pass the array of values directly into z.enum(). Alternatively, use as const to define your enum values as a tuple of strings. See the const assertion docs for details.

const VALUES = ["Salmon", "Tuna", "Trout"] as const;
const FishEnum = z.enum(VALUES);

This is not allowed, since Zod isn't able to infer the exact values of each element.

const fish = ["Salmon", "Tuna", "Trout"];
const FishEnum = z.enum(fish);

.enum

To get autocompletion with a Zod enum, use the .enum property of your schema:

FishEnum.enum.Salmon; // => autocompletes

FishEnum.enum;
/*
=> {
  Salmon: "Salmon",
  Tuna: "Tuna",
  Trout: "Trout",
}
*/

You can also retrieve the list of options as a tuple with the .options property:

FishEnum.options; // ["Salmon", "Tuna", "Trout"];

.exclude/.extract()

You can create subsets of a Zod enum with the .exclude and .extract methods.

const FishEnum = z.enum(["Salmon", "Tuna", "Trout"]);
const SalmonAndTrout = FishEnum.extract(["Salmon", "Trout"]);
const TunaOnly = FishEnum.exclude(["Salmon", "Trout"]);

Native enums

Zod enums are the recommended approach to defining and validating enums. But if you need to validate against an enum from a third-party library (or you don't want to rewrite your existing enums) you can use z.nativeEnum().

Numeric enums

enum Fruits {
  Apple,
  Banana,
}

const FruitEnum = z.nativeEnum(Fruits);
type FruitEnum = z.infer<typeof FruitEnum>; // Fruits

FruitEnum.parse(Fruits.Apple); // passes
FruitEnum.parse(Fruits.Banana); // passes
FruitEnum.parse(0); // passes
FruitEnum.parse(1); // passes
FruitEnum.parse(3); // fails

String enums

enum Fruits {
  Apple = "apple",
  Banana = "banana",
  Cantaloupe, // you can mix numerical and string enums
}

const FruitEnum = z.nativeEnum(Fruits);
type FruitEnum = z.infer<typeof FruitEnum>; // Fruits

FruitEnum.parse(Fruits.Apple); // passes
FruitEnum.parse(Fruits.Cantaloupe); // passes
FruitEnum.parse("apple"); // passes
FruitEnum.parse("banana"); // passes
FruitEnum.parse(0); // passes
FruitEnum.parse("Cantaloupe"); // fails

Const enums

The .nativeEnum() function works for as const objects as well. ⚠️ as const requires TypeScript 3.4+!

const Fruits = {
  Apple: "apple",
  Banana: "banana",
  Cantaloupe: 3,
} as const;

const FruitEnum = z.nativeEnum(Fruits);
type FruitEnum = z.infer<typeof FruitEnum>; // "apple" | "banana" | 3

FruitEnum.parse("apple"); // passes
FruitEnum.parse("banana"); // passes
FruitEnum.parse(3); // passes
FruitEnum.parse("Cantaloupe"); // fails

You can access the underlying object with the .enum property:

FruitEnum.enum.Apple; // "apple"

Optionals

You can make any schema optional with z.optional(). This wraps the schema in a ZodOptional instance and returns the result.

const schema = z.optional(z.string());

schema.parse(undefined); // => returns undefined
type A = z.infer<typeof schema>; // string | undefined

For convenience, you can also call the .optional() method on an existing schema.

const user = z.object({
  username: z.string().optional(),
});
type C = z.infer<typeof user>; // { username?: string | undefined };

You can extract the wrapped schema from a ZodOptional instance with .unwrap().

const stringSchema = z.string();
const optionalString = stringSchema.optional();
optionalString.unwrap() === stringSchema; // true

Nullables

Similarly, you can create nullable types with z.nullable().

const nullableString = z.nullable(z.string());
nullableString.parse("asdf"); // => "asdf"
nullableString.parse(null); // => null

Or use the .nullable() method.

const E = z.string().nullable(); // equivalent to nullableString
type E = z.infer<typeof E>; // string | null

Extract the inner schema with .unwrap().

const stringSchema = z.string();
const nullableString = stringSchema.nullable();
nullableString.unwrap() === stringSchema; // true

Objects

// all properties are required by default
const Dog = z.object({
  name: z.string(),
  age: z.number(),
});

// extract the inferred type like this
type Dog = z.infer<typeof Dog>;

// equivalent to:
type Dog = {
  name: string;
  age: number;
};

`.shape`

Use .shape to access the schemas for a particular key.

Dog.shape.name; // => string schema
Dog.shape.age; // => number schema

`.keyof`

Use .keyof to create a ZodEnum schema from the keys of an object schema.

const keySchema = Dog.keyof();
keySchema; // ZodEnum<["name", "age"]>

`.extend`

You can add additional fields to an object schema with the .extend method.

const DogWithBreed = Dog.extend({
  breed: z.string(),
});

You can use .extend to overwrite fields! Be careful with this power!

`.merge`

Equivalent to A.extend(B.shape).

const BaseTeacher = z.object({ students: z.array(z.string()) });
const HasID = z.object({ id: z.string() });

const Teacher = BaseTeacher.merge(HasID);
type Teacher = z.infer<typeof Teacher>; // => { students: string[], id: string }

If the two schemas share keys, the properties of B overrides the property of A. The returned schema also inherits the "unknownKeys" policy (strip/strict/passthrough) and the catchall schema of B.

`.pick/.omit`

Inspired by TypeScript's built-in Pick and Omit utility types, all Zod object schemas have .pick and .omit methods that return a modified version. Consider this Recipe schema:

const Recipe = z.object({
  id: z.string(),
  name: z.string(),
  ingredients: z.array(z.string()),
});

To only keep certain keys, use .pick .

const JustTheName = Recipe.pick({ name: true });
type JustTheName = z.infer<typeof JustTheName>;
// => { name: string }

To remove certain keys, use .omit .

const NoIDRecipe = Recipe.omit({ id: true });

type NoIDRecipe = z.infer<typeof NoIDRecipe>;
// => { name: string, ingredients: string[] }

`.partial`

Inspired by the built-in TypeScript utility type Partial, the .partial method makes all properties optional.

Starting from this object:

const user = z.object({
  email: z.string(),
  username: z.string(),
});
// { email: string; username: string }

We can create a partial version:

const partialUser = user.partial();
// { email?: string | undefined; username?: string | undefined }

You can also specify which properties to make optional:

const optionalEmail = user.partial({
  email: true,
});
/*
{
  email?: string | undefined;
  username: string
}
*/

`.deepPartial`

The .partial method is shallow — it only applies one level deep. There is also a "deep" version:

const user = z.object({
  username: z.string(),
  location: z.object({
    latitude: z.number(),
    longitude: z.number(),
  }),
  strings: z.array(z.object({ value: z.string() })),
});

const deepPartialUser = user.deepPartial();

/*
{
  username?: string | undefined,
  location?: {
    latitude?: number | undefined;
    longitude?: number | undefined;
  } | undefined,
  strings?: { value?: string}[]
}
*/

Important limitation: deep partials only work as expected in hierarchies of objects, arrays, and tuples.

`.required`

Contrary to the .partial method, the .required method makes all properties required.

Starting from this object:

const user = z
  .object({
    email: z.string(),
    username: z.string(),
  })
  .partial();
// { email?: string | undefined; username?: string | undefined }

We can create a required version:

const requiredUser = user.required();
// { email: string; username: string }

You can also specify which properties to make required:

const requiredEmail = user.required({
  email: true,
});
/*
{
  email: string;
  username?: string | undefined;
}
*/

`.passthrough`

By default Zod object schemas strip out unrecognized keys during parsing.

const person = z.object({
  name: z.string(),
});

person.parse({
  name: "bob dylan",
  extraKey: 61,
});
// => { name: "bob dylan" }
// extraKey has been stripped

Instead, if you want to pass through unknown keys, use .passthrough() .

person.passthrough().parse({
  name: "bob dylan",
  extraKey: 61,
});
// => { name: "bob dylan", extraKey: 61 }

`.strict`

By default Zod object schemas strip out unrecognized keys during parsing. You can disallow unknown keys with .strict() . If there are any unknown keys in the input, Zod will throw an error.

const person = z
  .object({
    name: z.string(),
  })
  .strict();

person.parse({
  name: "bob dylan",
  extraKey: 61,
});
// => throws ZodError

`.strip`

You can use the .strip method to reset an object schema to the default behavior (stripping unrecognized keys).

`.catchall`

You can pass a "catchall" schema into an object schema. All unknown keys will be validated against it.

const person = z
  .object({
    name: z.string(),
  })
  .catchall(z.number());

person.parse({
  name: "bob dylan",
  validExtraKey: 61, // works fine
});

person.parse({
  name: "bob dylan",
  validExtraKey: false, // fails
});
// => throws ZodError

Using .catchall() obviates .passthrough() , .strip() , or .strict(). All keys are now considered "known".

Arrays

const stringArray = z.array(z.string());

// equivalent
const stringArray = z.string().array();

Be careful with the .array() method. It returns a new ZodArray instance. This means the order in which you call methods matters. For instance:

z.string().optional().array(); // (string | undefined)[]
z.string().array().optional(); // string[] | undefined

`.element`

Use .element to access the schema for an element of the array.

stringArray.element; // => string schema

`.nonempty`

If you want to ensure that an array contains at least one element, use .nonempty().

const nonEmptyStrings = z.string().array().nonempty();
// the inferred type is now
// [string, ...string[]]

nonEmptyStrings.parse([]); // throws: "Array cannot be empty"
nonEmptyStrings.parse(["Ariana Grande"]); // passes

You can optionally specify a custom error message:

// optional custom error message
const nonEmptyStrings = z.string().array().nonempty({
  message: "Can't be empty!",
});

`.min/.max/.length`

z.string().array().min(5); // must contain 5 or more items
z.string().array().max(5); // must contain 5 or fewer items
z.string().array().length(5); // must contain 5 items exactly

Unlike .nonempty() these methods do not change the inferred type.

Tuples

Unlike arrays, tuples have a fixed number of elements and each element can have a different type.

const athleteSchema = z.tuple([
  z.string(), // name
  z.number(), // jersey number
  z.object({
    pointsScored: z.number(),
  }), // statistics
]);

type Athlete = z.infer<typeof athleteSchema>;
// type Athlete = [string, number, { pointsScored: number }]

A variadic ("rest") argument can be added with the .rest method.

const variadicTuple = z.tuple([z.string()]).rest(z.number());
const result = variadicTuple.parse(["hello", 1, 2, 3]);
// => [string, ...number[]];

Unions

Zod includes a built-in z.union method for composing "OR" types.

const stringOrNumber = z.union([z.string(), z.number()]);

stringOrNumber.parse("foo"); // passes
stringOrNumber.parse(14); // passes

Zod will test the input against each of the "options" in order and return the first value that validates successfully.

For convenience, you can also use the .or method:

const stringOrNumber = z.string().or(z.number());

Optional string validation:

To validate an optional form input, you can union the desired string validation with an empty string literal.

This example validates an input that is optional but needs to contain a valid URL:

const optionalUrl = z.union([z.string().url().nullish(), z.literal("")]);

console.log(optionalUrl.safeParse(undefined).success); // true
console.log(optionalUrl.safeParse(null).success); // true
console.log(optionalUrl.safeParse("").success); // true
console.log(optionalUrl.safeParse("https://zod.dev").success); // true
console.log(optionalUrl.safeParse("not a valid url").success); // false

Discriminated unions

A discriminated union is a union of object schemas that all share a particular key.

type MyUnion =
  | { status: "success"; data: string }
  | { status: "failed"; error: Error };

Such unions can be represented with the z.discriminatedUnion method. This enables faster evaluation, because Zod can check the discriminator key (status in the example above) to determine which schema should be used to parse the input. This makes parsing more efficient and lets Zod report friendlier errors.

With the basic union method, the input is tested against each of the provided "options", and in the case of invalidity, issues for all the "options" are shown in the zod error. On the other hand, the discriminated union allows for selecting just one of the "options", testing against it, and showing only the issues related to this "option".

const myUnion = z.discriminatedUnion("status", [
  z.object({ status: z.literal("success"), data: z.string() }),
  z.object({ status: z.literal("failed"), error: z.instanceof(Error) }),
]);

myUnion.parse({ status: "success", data: "yippie ki yay" });

Records

Record schemas are used to validate types such as { [k: string]: number }.

If you want to validate the values of an object against some schema but don't care about the keys, use z.record(valueType):

const NumberCache = z.record(z.number());

type NumberCache = z.infer<typeof NumberCache>;
// => { [k: string]: number }

This is particularly useful for storing or caching items by ID.

const userSchema = z.object({ name: z.string() });
const userStoreSchema = z.record(userSchema);

type UserStore = z.infer<typeof userStoreSchema>;
// => type UserStore = { [ x: string ]: { name: string } }

const userStore: UserStore = {};

userStore["77d2586b-9e8e-4ecf-8b21-ea7e0530eadd"] = {
  name: "Carlotta",
}; // passes

userStore["77d2586b-9e8e-4ecf-8b21-ea7e0530eadd"] = {
  whatever: "Ice cream sundae",
}; // TypeError

Record key type

If you want to validate both the keys and the values, use z.record(keyType, valueType):

const NoEmptyKeysSchema = z.record(z.string().min(1), z.number());
NoEmptyKeysSchema.parse({ count: 1 }); // => { 'count': 1 }
NoEmptyKeysSchema.parse({ "": 1 }); // fails

(Notice how when passing two arguments, valueType is the second argument)

A note on numerical keys

While z.record(keyType, valueType) is able to accept numerical key types and TypeScript's built-in Record type is Record<KeyType, ValueType>, it's hard to represent the TypeScript type Record<number, any> in Zod.

As it turns out, TypeScript's behavior surrounding [k: number] is a little unintuitive:

const testMap: { [k: number]: string } = {
  1: "one",
};

for (const key in testMap) {
  console.log(`${key}: ${typeof key}`);
}
// prints: `1: string`

As you can see, JavaScript automatically casts all object keys to strings under the hood. Since Zod is trying to bridge the gap between static and runtime types, it doesn't make sense to provide a way of creating a record schema with numerical keys, since there's no such thing as a numerical key in runtime JavaScript.

Maps

const stringNumberMap = z.map(z.string(), z.number());

type StringNumberMap = z.infer<typeof stringNumberMap>;
// type StringNumberMap = Map<string, number>

Sets

const numberSet = z.set(z.number());
type NumberSet = z.infer<typeof numberSet>;
// type NumberSet = Set<number>

Set schemas can be further constrained with the following utility methods.

z.set(z.string()).nonempty(); // must contain at least one item
z.set(z.string()).min(5); // must contain 5 or more items
z.set(z.string()).max(5); // must contain 5 or fewer items
z.set(z.string()).size(5); // must contain 5 items exactly

Intersections

Intersections are useful for creating "logical AND" types. This is useful for intersecting two object types.

const Person = z.object({
  name: z.string(),
});

const Employee = z.object({
  role: z.string(),
});

const EmployedPerson = z.intersection(Person, Employee);

// equivalent to:
const EmployedPerson = Person.and(Employee);

Though in many cases, it is recommended to use A.merge(B) to merge two objects. The .merge method returns a new ZodObject instance, whereas A.and(B) returns a less useful ZodIntersection instance that lacks common object methods like pick and omit.

const a = z.union([z.number(), z.string()]);
const b = z.union([z.number(), z.boolean()]);
const c = z.intersection(a, b);

type c = z.infer<typeof c>; // => number

Recursive types

You can define a recursive schema in Zod, but because of a limitation of TypeScript, their type can't be statically inferred. Instead you'll need to define the type definition manually, and provide it to Zod as a "type hint".

const baseCategorySchema = z.object({
  name: z.string(),
});

type Category = z.infer<typeof baseCategorySchema> & {
  subcategories: Category[];
};

const categorySchema: z.ZodType<Category> = baseCategorySchema.extend({
  subcategories: z.lazy(() => categorySchema.array()),
});

categorySchema.parse({
  name: "People",
  subcategories: [
    {
      name: "Politicians",
      subcategories: [
        {
          name: "Presidents",
          subcategories: [],
        },
      ],
    },
  ],
}); // passes

Thanks to crasite for this example.

ZodType with ZodEffects

When using z.ZodType with z.ZodEffects ( .refine, .transform, preprocess, etc... ), you will need to define the input and output types of the schema. z.ZodType<Output, z.ZodTypeDef, Input>

const isValidId = (id: string): id is `${string}/${string}` =>
  id.split("/").length === 2;

const baseSchema = z.object({
  id: z.string().refine(isValidId),
});

type Input = z.input<typeof baseSchema> & {
  children: Input[];
};

type Output = z.output<typeof baseSchema> & {
  children: Output[];
};

const schema: z.ZodType<Output, z.ZodTypeDef, Input> = baseSchema.extend({
  children: z.lazy(() => schema.array()),
});

Thanks to marcus13371337 and JoelBeeldi for this example.

JSON type

If you want to validate any JSON value, you can use the snippet below.

const literalSchema = z.union([z.string(), z.number(), z.boolean(), z.null()]);
type Literal = z.infer<typeof literalSchema>;
type Json = Literal | { [key: string]: Json } | Json[];
const jsonSchema: z.ZodType<Json> = z.lazy(() =>
  z.union([literalSchema, z.array(jsonSchema), z.record(jsonSchema)])
);

jsonSchema.parse(data);

Thanks to ggoodman for suggesting this.

Cyclical objects

Despite supporting recursive schemas, passing cyclical data into Zod will cause an infinite loop.

Promises

const numberPromise = z.promise(z.number());

"Parsing" works a little differently with promise schemas. Validation happens in two parts:

Zod synchronously checks that the input is an instance of Promise (i.e. an object with .then and .catch methods.).
Zod uses .then to attach an additional validation step onto the existing Promise. You'll have to use .catch on the returned Promise to handle validation failures.

numberPromise.parse("tuna");
// ZodError: Non-Promise type: string

numberPromise.parse(Promise.resolve("tuna"));
// => Promise<number>

const test = async () => {
  await numberPromise.parse(Promise.resolve("tuna"));
  // ZodError: Non-number type: string

  await numberPromise.parse(Promise.resolve(3.14));
  // => 3.14
};

Instanceof

You can use z.instanceof to check that the input is an instance of a class. This is useful to validate inputs against classes that are exported from third-party libraries.

class Test {
  name: string;
}

const TestSchema = z.instanceof(Test);

const blob: any = "whatever";
TestSchema.parse(new Test()); // passes
TestSchema.parse(blob); // throws

Functions

Zod also lets you define "function schemas". This makes it easy to validate the inputs and outputs of a function without intermixing your validation code and "business logic".

You can create a function schema with z.function(args, returnType) .

const myFunction = z.function();

type myFunction = z.infer<typeof myFunction>;
// => ()=>unknown

Define inputs and outputs.

const myFunction = z
  .function()
  .args(z.string(), z.number()) // accepts an arbitrary number of arguments
  .returns(z.boolean());

type myFunction = z.infer<typeof myFunction>;
// => (arg0: string, arg1: number)=>boolean

Function schemas have an .implement() method which accepts a function and returns a new function that automatically validates its inputs and outputs.

const trimmedLength = z
  .function()
  .args(z.string()) // accepts an arbitrary number of arguments
  .returns(z.number())
  .implement((x) => {
    // TypeScript knows x is a string!
    return x.trim().length;
  });

trimmedLength("sandwich"); // => 8
trimmedLength(" asdf "); // => 4

If you only care about validating inputs, just don't call the .returns() method. The output type will be inferred from the implementation.

You can use the special z.void() option if your function doesn't return anything. This will let Zod properly infer the type of void-returning functions. (Void-returning functions actually return undefined.)

const myFunction = z
  .function()
  .args(z.string())
  .implement((arg) => {
    return [arg.length];
  });

myFunction; // (arg: string)=>number[]

Extract the input and output schemas from a function schema.

myFunction.parameters();
// => ZodTuple<[ZodString, ZodNumber]>

myFunction.returnType();
// => ZodBoolean

Preprocess

Zod now supports primitive coercion without the need for .preprocess(). See the coercion docs for more information.

Typically Zod operates under a "parse then transform" paradigm. Zod validates the input first, then passes it through a chain of transformation functions. (For more information about transforms, read the .transform docs.)

But sometimes you want to apply some transform to the input before parsing happens. A common use case: type coercion. Zod enables this with the z.preprocess().

const castToString = z.preprocess((val) => String(val), z.string());

This returns a ZodEffects instance. ZodEffects is a wrapper class that contains all logic pertaining to preprocessing, refinements, and transforms.

Custom schemas

You can create a Zod schema for any TypeScript type by using z.custom(). This is useful for creating schemas for types that are not supported by Zod out of the box, such as template string literals.

const px = z.custom<`${number}px`>((val) => {
  return typeof val === "string" ? /^\d+px$/.test(val) : false;
});

type px = z.infer<typeof px>; // `${number}px`

px.parse("42px"); // "42px"
px.parse("42vw"); // throws;

If you don't provide a validation function, Zod will allow any value. This can be dangerous!

z.custom<{ arg: string }>(); // performs no validation

You can customize the error message and other options by passing a second argument. This parameter works the same way as the params parameter of .refine.

z.custom<...>((val) => ..., "custom error message");

Schema methods

All Zod schemas contain