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主要言語: TypeScript
First-class ajv typescript JSON-schema builder inspired from Zod
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- 2026/08/04
gem-hunter主要言語: TypeScript
First-class ajv typescript JSON-schema builder inspired from Zod
any/unknownnevernot/excludecustom shema definitionJSON schema builder like in ZOD-like API
TypeScript schema validation with static type inference!
Reasons to install ajv-ts instead of zod
zod has 4k+ lines of codeajv, which wild spreadable(90M week installations for ajv vs 5M for zod)ajv instance!We inspired API from zod. So you just can reimport you api and that's it!
s.date, s.symbol, s.void, s.void, s.bigint, s.function does not supported. Since JSON-schema doesn't define Date, Symbol, void, function, Set, Map as separate type. For strings you can use s.string().format('date-time') or other JSON-string format compatibility: https://json-schema.org/understanding-json-schema/reference/string.htmls.null === s.undefined - same types, but helps typescript with autocompletionz.enum and z.nativeEnum it's a same as s.enum. We make enums fully compatible, it can be array of strings or structure defined with enum keyword in typescripts isntead of z, since s - is a shorthand for schemaz.custom is not supportedz.literal === s.const.npm install ajv-ts # npm yarn add ajv-ts # yarn bun add ajv-ts # bun pnpm add ajv-ts # pnpm
Creating a simple string schema
import { s } from "ajv-ts"; // creating a schema for strings const mySchema = s.string(); // parsing mySchema.parse("tuna"); // => "tuna" mySchema.parse(12); // => throws Ajv Error // "safe" parsing (doesn't throw error if validation fails) mySchema.safeParse("tuna"); // => { success: true; data: "tuna" } mySchema.safeParse(12); // => { success: false; error: AjvError }
Creating an object schema
import { s } from "ajv-ts"; const User = s.object({ username: s.string(), }); User.parse({ username: "Ludwig" }); // extract the inferred type type User = s.infer<typeof User>; // { username: string }
Every schema inherits these class with next methods/properties
The examples keyword is a place to provide an array of examples that validate against the schema. This isn’t used for validation, but may help with explaining the effect and purpose of the schema to a reader. Each entry should validate against the schema in which it resides, but that isn’t strictly required. There is no need to duplicate the default value in the examples array, since default will be treated as another example.
Note: While it is recommended that the examples validate against the subschema they are defined in, this requirement is not strictly enforced.
Used to demonstrate how data should conform to the schema. examples does not affect data validation but serves as an informative annotation.
s.string().examples(["str1", 'string 2']) // OK s.number().examples(["str1", 'string 2']) // Error s.number().examples([1, 2, 3]) // OK s.number().examples(1, 2, 3) // OK
Add custom schema key-value definition.
set custom JSON-schema field. Useful if you need to declare something but no api founded for built-in solution.
Example: If-Then-Else you cannot declare without custom method.
const myObj = s.object({ foo: s.string(), bar: s.string() }).custom('if', { "properties": { "foo": { "const": "bar" } }, "required": ["foo"] }).custom('then', { "required": ["bar"] })
Adds meta information fields in your schema, such as deprecated, description, $id, title and more!
Example:
const numSchema = s.number().meta({ title: 'my number schema', description: 'Some description', deprecated: true }) numSchema.schema // {type: 'number', title: 'my number schema', description: 'Some description', deprecated: true }
In case of you have alredy defined JSON-schema, you create an any/object/number/string/boolean/null schema and set schema property from your schema.
Example:
import s from 'ajv-ts' const SchemaFromSomewhere = { "title": "Example Schema", "type": "object", "properties": { "name": { "type": "string" }, "age": { "description": "Age in years", "type": "integer", "minimum": 0 }, }, "required": ["name", "age"] } type MySchema = { name: string; age: number } const AnySchema = s.any() AnySchema.schema = SchemaFromSomewhere AnySchema.parse({name: 'hello', age: 18}) // OK, since we override JSON-schema // or using object const Obj = s.object<MySchema>() Obj.schema = SchemaFromSomewhere Obj.parse({name: 'hello', age: 18}) // OK
Option default keywords throws exception during schema compilation when used in:
This means only object() and array() buidlers are supported.
Example
import s from 'ajv-ts' const Person = s.object({ age: s.int().default(18) }) Person.parse({}) // { age: 18 }
import { s } from "ajv-ts"; // primitive values s.string(); s.number(); s.boolean(); // empty types s.undefined(); s.null(); // allows any value s.any(); s.unknown();
const tuna = s.const("tuna"); const twelve = s.const(12); const tru = s.const(true); // retrieve literal value tuna.value; // "tuna"
includes a handful of string-specific validations.
// validations s.string().maxLength(5); s.string().minLength(5); s.string().length(5); s.string().format('email'); s.string().format('url'); s.string().regex(regex); s.string().format('date-time'); s.string().format('ipv4'); // transformations s.string().postprocess(v => v.trim()); s.string().postprocess(v => v.toLowerCase()); s.string().postprocess(v => v.toUpperCase());
from >=0.7.x
Unlike zod - we make typescript validation for minLength and maxLength. That means you cannot create schema when expected length are negative number or maxLength < minLength.
Here is few examples:
s.string().minLength(3).maxLength(1) // [never, "RangeError: MaxLength less than MinLength", "MinLength: 3", "MaxLength: 1"] s.string().length(-1) // [never, "TypeError: expected positive integer. Received: '-1'"]
includes a handful of number-specific validations.
s.number().gt(5); s.number().gte(5); // alias .min(5) s.number().lt(5); s.number().lte(5); // alias .max(5) s.number().int(); // value must be an integer s.number().positive(); // > 0 s.number().nonnegative(); // >= 0 s.number().negative(); // < 0 s.number().nonpositive(); // <= 0 s.number().multipleOf(5); // Evenly divisible by 5. Alias .step(5)
Number - any number type
s.number() // same as s.number().number()
Only integers values.
Note: we check in runtime non-integer format (float, double) and give an error.
s.number().int() // or s.number().integer() // or s.int()
Defines in ajv-formats package
Signed 32 bits integer according to the openApi 3.0.0 specification
Signed 64 bits according to the openApi 3.0.0 specification
float: float according to the openApi 3.0.0 specification
double: double according to the openApi 3.0.0 specification
from >= 0.8
We make validation for number type, format, minValue and maxValue fields. That means we handle it in our side so you get an error for invalid values.
Examples:
s.number().format('float').int() // error in type! s.int().const(3.4) // error in type! s.number().int().format('float') // error in format! s.number().int().format('double') // error in format! // ranges are also check for possibility s.number().min(5).max(3) // error in range! s.number().min(3).max(5).const(10) // error in constant!
Not supported
Not supported
Not supported, but you can pass parseDates in your AJV instance.
const FishEnum = s.enum(["Salmon", "Tuna", "Trout"]); type FishEnum = s.infer<typeof FishEnum>; // 'Salmon' | 'Tuna' | 'Trout'
const VALUES = ["Salmon", "Tuna", "Trout"] as const; const FishEnum = s.enum(VALUES);
To get autocompletion with a 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"];
Numeric enums:
enum Fruits { Apple, Banana, } const FruitEnum = s.enum(Fruits); type FruitEnum = s.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 = s.enum(Fruits); type FruitEnum = s.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"); // pass
Const enums:
The .enum() 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 = s.enum(Fruits); type FruitEnum = s.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"
You can make any schema optional with s.optional(). This wraps the schema in a Optional instance and returns the result.
const schema = s.string().optional(); schema.parse(undefined); // => returns undefined type A = s.infer<typeof schema>; // string | undefined
const nullableString = s.string().nullable(); nullableString.parse("asdf"); // => "asdf" nullableString.parse(null); // => null nullableString.parse(undefined); // throws error
// make object of dog const Dog = s.object({ name: s.string(), age: s.number(), }); // extract the inferred type like this type Dog = s.infer<typeof Dog>; // equivalent to: type Dog = { name?: string; age?: number; };
NOTE: all properties are optional by default. See JSON-Schema spec
Use .keyof to create a Enum schema from the keys of an object schema.
const keySchema = Dog.keyof(); keySchema; // Enum<["name", "age"]>
You can add additional fields to an object schema with the .extend method.
const DogWithBreed = Dog.extend({ breed: s.string(), });
You can use .extend to overwrite fields! Be careful with this power!
Equivalent to A.extend(B.schema).
const BaseTeacher = s.object({ students: s.array(s.string()) }); const HasID = s.object({ id: s.string() }); const Teacher = BaseTeacher.merge(HasID); type Teacher = s.infer<typeof Teacher>; // => { students: string[], id: string }
Inspired by TypeScript's built-in Pick and Omit utility types, all object schemas have .pick and .omit methods that return a modified version. Consider this Recipe schema:
const Recipe = s.object({ id: s.string(), name: s.string(), ingredients: s.array(s.string()), });
To only keep certain keys, use .pick .
const JustTheName = Recipe.pick({ name: true }); type JustTheName = s.infer<typeof JustTheName>; // => { name: string }
To remove certain keys, use .omit .
const NoIDRecipe = Recipe.omit({ id: true }); type NoIDRecipe = s.infer<typeof NoIDRecipe>; // => { name: string, ingredients: string[] }
Inspired by the built-in TypeScript utility type Partial, the .partial method makes all properties optional.
Starting from this object:
const user = s.object({ email: s.string(), username: s.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 } */
Contrary to the .partial method, the .required method makes all properties required.
Starting from this object:
const user = z .object({ email: s.string(), username: s.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; } */
Accepts keys which are required. Set requiredProperties for your JSON-schema
const O = s.object({ first: s.number().optional(), second: s.string().optional() }).requiredFor('first') type O = s.infer<typeof O> // {first: number, second?: string}
Accepts keys which are partial. unset properties from required schema field in your JSON-schema
const O = s.object({ first: s.number().optional(), second: s.string().optional() }).required().partialFor('second') type O = s.infer<typeof O> // {first: number, second?: string}
By default object schemas strip out unrecognized keys during parsing.
const person = s.object({ name: s.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 }
By default JSON object schemas allow to pass unrecognized keys during parsing. You can disallow unknown keys with .strict() . If there are any unknown keys in the input - will throw an error.
const person = z .object({ name: s.string(), }) .strict(); person.parse({ name: "bob dylan", extraKey: 61, }); // => throws ZodError
The dependentRequired keyword conditionally requires that
certain properties must be present if a given property is
present in an object. For example, suppose we have a schema
representing a customer. If you have their "credit card number",
you also want to ensure you have a "billing address".
If you don't have their credit card number, a "billing address"
operty
on another using the dependentRequired keyword.
The value of the dependentRequired keyword is an object.
Each entry in the object maps from the name of a property, p,
to an array of strings listing properties that are required
if p is present.
const Test1 = s.object({ name: s.string(), credit_card: s.number(), billing_address: s.string(), }).requiredFor('name').dependentRequired({ credit_card: ['billing_address'], }) /** Test1.schema === { "type": "object", "properties": { "name": { "type": "string" }, "credit_card": { "type": "number" }, "billing_address": { "type": "string" } }, "required": ["name"], "dependentRequired": { "credit_card": ["billing_address"] } } */
The additionalProperties keyword is used to control the handling of extra stuff, that is, properties whose names are
not listed in the properties keyword or match any of the regular expressions in the patternProperties keyword.
By default any additional properties are allowed.
If you need to set additionalProperties=false use strict method
const Test = s.object({ street_name: s.string(), street_type: s.enum(["Street", "Avenue", "Boulevard"]) }).rest(s.string()) Test.schema === { "type": "object", "properties": { "street_name": { "type": "string" }, "street_type": { "enum": ["Street", "Avenue", "Boulevard"] } }, "additionalProperties": { "type": "string" } }
const stringArray = s.array(s.string()); type StringArray = s.infer<typeof stringArray> // string[]
Or it's invariant
const stringArray = s.string().array(); type StringArray = s.infer<typeof stringArray> // string[]
Or you can pass empty schema
const empty = s.array() type Empty = s.infer<typeof empty> // unknown[]
push(append) schema to array(parent) schema.
Example:
import s from 'ajv-ts' const empty = s.array() const stringArr = empty.addItems(s.string()) stringArr.schema // {type: 'array', items: [{ type: 'string' }]}
Use .element to access the schema for an element of the array.
stringArray.element; // => string schema, not array schema
If you want to ensure that an array contains at least one element, use .nonempty().
const nonEmptyStrings = s.array(s.string()).nonempty(); // the inferred type is now // [string, ...string[]] nonEmptyStrings.parse([]); // throws: "Array cannot be empty" nonEmptyStrings.parse(["Ariana Grande"]); // passes
s.string().array().min(5); // must contain 5 or more items s.string().array().max(5); // must contain 5 or fewer items s.string().array().length(5); // must contain 5 items exactly
Unlike .nonempty() these methods do not change the inferred type.
from >=0.7.x
Unlike zod - we make typescript validation for minLength and maxLength. That means you cannot create schema when expected length are not positive number or maxLength < minLength.
Here is few examples:
s.string().array().minLength(3).maxLength(1) // [never, "RangeError: MaxLength less than MinLength", "MinLength: 2", "MaxLength: 1"] s.string().array().length(-1) // [never, "TypeError: expected positive integer. Received: '-2'"]
Set the uniqueItems keyword to true.
const UniqueNumbers = s.array(s.number()).unique() UniqueNumbers.parse([1,2,3,4]) // Ok UniqueNumbers.parse([1,2,3,3]) // Error
Unlike arrays, tuples have a fixed number of elements and each element can have a different type.
const athleteSchema = s.tuple([ s.string(), // name s.number(), // jersey number s.object({ pointsScored: s.number(), }), // statistics ]); type Athlete = s.infer<typeof athleteSchema>; // type Athlete = [string, number, { pointsScored: number }]
A variadic ("rest") argument can be added with the .rest method.
const variadicTuple = s.tuple([s.string()]).rest(s.number()); const result = variadicTuple.parse(["hello", 1, 2, 3]); // => [string, ...number[]];
includes a built-in s.union method for composing "OR" types.
This function accepts array of schemas by spread argument.
const stringOrNumber = s.union(s.string(), s.number()); stringOrNumber.parse("foo"); // passes stringOrNumber.parse(14); // passes
Or it's invariant - or function:
s.number().or(s.string()) // number | string
Intersections are "logical AND" types. This is useful for intersecting two object types.
const Person = s.object({ name: s.string(), }); const Employee = s.object({ role: s.string(), }); const EmployedPerson = s.intersection(Person, Employee); // equivalent to: const EmployedPerson = Person.and(Employee); // equivalent to: const EmployedPerson = and(Person, Employee);
Though in many cases, it is recommended to use A.merge(B) to merge two objects. The .merge method returns a new Object instance, whereas A.and(B) returns a less useful Intersection instance that lacks common object methods like pick and omit.
const a = s.union(s.number(), s.string()); const b = s.union(s.number(), s.boolean()); const c = s.intersection(a, b); type c = s.infer<typeof c>; // => number
Not supported
Not supported
Any and unknown defines {} (empty object) as JSON-schema. very useful if you need to create something specific
Never defines using {not: {}} (empty not). Any given json schema will be fails.
Here is a 2 differences between not and exclude.
not method wrap given schema with notexclude(schema) - add not keyword for incoming schema argumentExample:
import s from 'ajv-ts' // not const notAString = s.string().not() // or s.not(s.string()) notAString.valid('random string') // false, this is a string notAString.valid(123) // true // exclude const notJohn = s.string().exclude(s.const('John')) notJohn.valid('random string') // true notJohn.valid('John') // false, this is John // advanced usage const str = s.string<'John' | 'Mary'>().exclude(s.const('John')) s.infer<typeof str> // 'Mary'
If you need to create a custom AJV Instance, you can use create or new function.
import addKeywords from 'ajv-keywords'; import schemaBuilder from 'ajv-ts' const myAjvInstance = new Ajv({parseDate: true}) export const s = schemaBuilder.create(myAjvInstance) // later: s.string().dateTime().parse(new Date()) // 2023-10-05T19:31:57.610Z
Every schema builder implements the Standard Schema interface (StandardSchemaV1), so schemas can be passed to any Standard Schema-compatible tool (form libraries, tRPC, etc.) without adapters.
import type { StandardSchemaV1 } from '@standard-schema/spec' const schema = s.object({ name: s.string() }) const standard: StandardSchemaV1 = schema // OK standard['~standard'].validate({ name: 'John' }) // { value: { name: 'John' } } standard['~standard'].validate({ name: 42 }) // { issues: [{ message: 'must be string', path: ['name'] }] }
Ajv errors are mapped to Standard Schema issues, instancePath (JSON-pointer) becomes the issue path segments.
If you need to append something specific to you schema, you can use custom method.
const condition = s.any() // schema: {} const withIf = condition.custom('if', {properties: {foo: {type: 'string'}}}) withIf.schema // {if: {properties: {foo: {type: 'string'}}}}
function thant will be applied before calling parse method, It can helps you to modify incomining data
Be careful with this information
const ToString = s.string().preprocess(x => { if(x instanceof Date){ return x.toISOString() } return x }, s.string()) ToString.parse(12) // error: expects a string ToString.parse(new Date()) // 2023-09-26T13:44:46.497Z
function thant will be applied after calling parse method.
const ToString = s.number().postprocess(x => String(x), s.string()) ToString.parse(12) // after parse we get "12" 12 => "12". ToString.parse({}) // error: expects number. Postprocess has not been called
Error handling and error maps based from official package ajv-errors. You can check in out from there.
Defines custom error message for not valid schema.
const S1 = s.string().error('Im fails unexpected') S1.parse({}) // throws: Im fails unexpected
You can define custom error map. In most cases you can pass just a string for invalidation. Also, you can pass error map.
Example:
import s from 'ajv-ts' const s1 = s.string().error({ _: "any error here" }) s.parse(123) // throws "any error here" s.string().error({ _: "any error here", type: "not a string. Custom" }) s.parse(123) // throws "not a string. Custom" const Obj = s .object({ foo: s.string(),}) .strict() .error({ additionalProperties: "Not expected to pass additional props" }); Obj.parse({foo: 'ok', bar: true}) // throws "Not expected to pass additional props"
const Schema = s .object({ foo: s.integer().minimum(2), bar: s.string().minLength(2), }) .strict() .error({ properties: { foo: "data.foo should be integer >= 2", bar: "data.bar should be string with length >= 2", }, }); Schema.parse({ foo: 1, bar: "a" }) // throws: "data.foo should be integer >= 2"
Inspired from zod. Set custom validation. Any result exept undefined will throws(or exposed for safeParse method).
import s from 'ajv-ts' // example: object with only 1 "active element" const Schema = s.object({ active: s.boolean(), name: s.string() }).array().refine((arr) => { const subArr = arr.filter(el => el.active === true) if (subArr.length > 1) throw new Error('Array should contains only 1 "active" element') }) Schema.parse([{ active: true, name: 'some 1' }, { active: true, name: 'some 2' }]) // throws Error