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The io-ts npm package is a TypeScript library that allows for the definition of runtime types, and the automatic validation of runtime values against those types. It leverages TypeScript's type system to ensure that data structures conform to specified schemas, providing a bridge between the runtime data and compile-time types.
Runtime type validation
This feature allows you to define a type and then validate an object against that type at runtime. If the object matches the type, the 'Right' branch is executed; otherwise, the 'Left' branch indicates a validation error.
{"const t = require('io-ts');\nconst User = t.type({\n name: t.string,\n age: t.number\n});\nconst result = User.decode({ name: 'Alice', age: 25 });\nif (result._tag === 'Right') {\n console.log('Valid!', result.right);\n} else {\n console.log('Invalid!', result.left);\n}"}
Type composition
io-ts allows for the composition of types, enabling complex type definitions by combining simpler ones. This is useful for building up the shape of data structures from reusable type components.
{"const t = require('io-ts');\nconst Name = t.string;\nconst Age = t.number;\nconst User = t.type({ name: Name, age: Age });\nconst result = User.decode({ name: 'Bob', age: 'not-a-number' });\n// result will be an instance of Left since 'age' is not a number"}
Custom types
io-ts allows the creation of custom types with additional validation logic. In this example, a 'PositiveNumber' type is created that only accepts positive numbers.
{"const t = require('io-ts');\nconst PositiveNumber = t.brand(\n t.number,\n (n): n is t.Branded<number, { readonly PositiveNumber: unique symbol }> => n > 0,\n 'PositiveNumber'\n);\nconst result = PositiveNumber.decode(-5);\n// result will be an instance of Left since the number is not positive"}
Ajv is a JSON schema validator that provides runtime data validation using predefined JSON schemas. It is similar to io-ts in that it validates data structures at runtime, but it uses JSON schema as the basis for validation rather than TypeScript types.
Joi is an object schema validation library that allows for the description and validation of JavaScript objects. It is similar to io-ts in providing runtime validation, but it uses a fluent API for schema definition and does not integrate with TypeScript types in the same way.
Yup is a JavaScript schema builder for value parsing and validation. It defines a schema using a declarative API and validates objects against the schema. Like io-ts, it provides runtime validation, but it does not leverage TypeScript's type system for type definitions.
Class-validator allows for validation of class instances based on decorators. It is similar to io-ts in that it provides runtime validation, but it is designed to work with classes and decorators, offering a different approach to defining validation rules.
Table of contents
Blog post: "Typescript and validations at runtime boundaries" by @lorefnon
A value of type Type<A, O, I>
(called "codec") is the runtime representation of the static type A
.
Also a codec can
I
(through decode
)O
(through encode
)is
)class Type<A, O, I> {
readonly _A: A
readonly _O: O
readonly _I: I
constructor(
/** a unique name for this codec */
readonly name: string,
/** a custom type guard */
readonly is: (u: unknown) => u is A,
/** succeeds if a value of type I can be decoded to a value of type A */
readonly validate: (input: I, context: Context) => Either<Errors, A>,
/** converts a value of type A to a value of type O */
readonly encode: (a: A) => O
) {}
/** a version of `validate` with a default context */
decode(i: I): Either<Errors, A>
}
Note. The Either
type is defined in fp-ts, a library containing implementations of
common algebraic types in TypeScript.
Example
A codec representing string
can be defined as
import * as t from 'io-ts'
const isString = (u: unknown): u is string => typeof u === 'string'
const string = new t.Type<string, string, unknown>(
'string',
isString,
(u, c) => (isString(u) ? t.success(u) : t.failure(u, c)),
t.identity
)
A codec can be used to validate an object in memory (for example an API payload)
import * as t from 'io-ts'
const User = t.type({
userId: t.number,
name: t.string
})
// validation succeeded
User.decode(JSON.parse('{"userId":1,"name":"Giulio"}')) // => Right({ userId: 1, name: "Giulio" })
// validation failed
User.decode(JSON.parse('{"name":"Giulio"}')) // => Left([...])
The stable version is tested against TypeScript 3.2.4.
io-ts version | required TypeScript version |
---|---|
1.6.x+ | 3.2.2+ |
1.5.3 | 3.0.1+ |
1.5.2- | 2.7.2+ |
Note. This library is conceived, tested and is supposed to be consumed by TypeScript with the strict
flag turned on.
Note. If you are running < typescript@3.0.1
you have to polyfill unknown
.
You can use unknown-ts as a polyfill.
A reporter implements the following interface
interface Reporter<A> {
report: (validation: Validation<any>) => A
}
This package exports a default PathReporter
reporter
Example
import { PathReporter } from 'io-ts/lib/PathReporter'
const result = User.decode({ name: 'Giulio' })
console.log(PathReporter.report(result))
// => [ 'Invalid value undefined supplied to : { userId: number, name: string }/userId: number' ]
You can define your own reporter. Errors
has the following type
interface ContextEntry {
readonly key: string
readonly type: Decoder<any, any>
}
interface Context extends ReadonlyArray<ContextEntry> {}
interface ValidationError {
readonly value: unknown
readonly context: Context
}
interface Errors extends Array<ValidationError> {}
Example
const getPaths = <A>(v: t.Validation<A>): Array<string> => {
return v.fold(errors => errors.map(error => error.context.map(({ key }) => key).join('.')), () => ['no errors'])
}
console.log(getPaths(User.decode({}))) // => [ '.userId', '.name' ]
You can set your own error message by providing a message
argument to failure
Example
const NumberFromString = new t.Type<number, string, unknown>(
'NumberFromString',
t.number.is,
(u, c) =>
t.string.validate(u, c).chain(s => {
const n = +s
return isNaN(n) ? t.failure(u, c, 'cannot parse to a number') : t.success(n)
}),
String
)
console.log(PathReporter.report(NumberFromString.decode('a')))
// => ['cannot parse to a number']
You can also use the withMessage
helper from io-ts-types
codecs can be inspected
This library uses TypeScript extensively. Its API is defined in a way which automatically infers types for produced values
Note that the type annotation isn't needed, TypeScript infers the type automatically based on a schema (and comments are preserved).
Static types can be extracted from codecs using the TypeOf
operator
type User = t.TypeOf<typeof User>
// same as
type User = {
userId: number
name: string
}
Type | TypeScript | codec / combinator |
---|---|---|
null | null | t.null or t.nullType |
undefined | undefined | t.undefined |
void | void | t.void or t.voidType |
string | string | t.string |
number | number | t.number |
boolean | boolean | t.boolean |
unknown | unknown | t.unknown |
never | never | t.never |
object | object | t.object |
array of unknown | Array<unknown> | t.UnknownArray |
array of type | Array<A> | t.array(A) |
record of unknown | Record<string, unknown> | t.UnknownRecord |
record of type | Record<K, A> | t.record(K, A) |
function | Function | t.Function |
literal | 's' | t.literal('s') |
partial | Partial<{ name: string }> | t.partial({ name: t.string }) |
readonly | Readonly<A> | t.readonly(A) |
readonly array | ReadonlyArray<A> | t.readonlyArray(A) |
type alias | type T = { name: A } | t.type({ name: A }) |
tuple | [ A, B ] | t.tuple([ A, B ]) |
union | A | B | t.union([ A, B ]) or t.taggedUnion(tag, [ A, B ]) |
intersection | A & B | t.intersection([ A, B ]) |
keyof | keyof M | t.keyof(M) (only supports string keys) |
recursive types | ✘ | t.recursion(name, definition) |
branded types / refinements | ✘ | t.brand(A, predicate, brand) |
integer | ✘ | t.Int (built-in branded codec) |
exact types | ✘ | t.exact(type) |
strict | ✘ | t.strict({ name: A }) (an alias of t.exact(t.type({ name: A }))) |
Recursive types can't be inferred by TypeScript so you must provide the static type as a hint
interface Category {
name: string
categories: Array<Category>
}
const Category: t.Type<Category> = t.recursion('Category', () =>
t.type({
name: t.string,
categories: t.array(Category)
})
)
interface Foo {
type: 'Foo'
b: Bar | undefined
}
interface Bar {
type: 'Bar'
a: Foo | undefined
}
const Foo: t.Type<Foo> = t.recursion('Foo', () =>
t.interface({
type: t.literal('Foo'),
b: t.union([Bar, t.undefined])
})
)
const Bar: t.Type<Bar> = t.recursion('Bar', () =>
t.interface({
type: t.literal('Bar'),
a: t.union([Foo, t.undefined])
})
)
If you are encoding tagged unions, instead of the general purpose union
combinator, you may want to use the
taggedUnion
combinator in order to get better performances
const A = t.type({
tag: t.literal('A'),
foo: t.string
})
const B = t.type({
tag: t.literal('B'),
bar: t.number
})
// the actual presence of the tag is statically checked
const U = t.taggedUnion('tag', [A, B])
You can brand / refine a codec (any codec) using the brand
combinator
// a unique brand for positive numbers
interface PositiveBrand {
readonly Positive: unique symbol // use `unique symbol` here to ensure uniqueness across modules / packages
}
const Positive = t.brand(
t.number, // a codec representing the type to be refined
(n): n is t.Branded<number, PositiveBrand> => n >= 0, // a custom type guard using the build-in helper `Branded`
'Positive' // the name must match the readonly field in the brand
)
type Positive = t.TypeOf<typeof Positive>
/*
same as
type Positive = number & t.Brand<PositiveBrand>
*/
Branded codecs can be merged with t.intersection
// t.Int is a built-in branded codec
const PositiveInt = t.intersection([t.Int, Positive])
type PositiveInt = t.TypeOf<typeof PositiveInt>
/*
same as
type PositiveInt = number & t.Brand<t.IntBrand> & t.Brand<PositiveBrand>
*/
You can make a codec exact (which means that additional properties are stripped) using the exact
combinator
const ExactUser = t.exact(User)
User.decode({ userId: 1, name: 'Giulio', age: 45 }) // ok, result is right({ userId: 1, name: 'Giulio', age: 45 })
ExactUser.decode({ userId: 1, name: 'Giulio', age: 43 }) // ok but result is right({ userId: 1, name: 'Giulio' })
You can mix required and optional props using an intersection
const A = t.type({
foo: t.string
})
const B = t.partial({
bar: t.number
})
const C = t.intersection([A, B])
type C = t.TypeOf<typeof C>
// same as
type C = {
foo: string
} & {
bar?: number | undefined
}
You can apply partial
to an already defined codec via its props
field
const PartialUser = t.partial(User.props)
type PartialUser = t.TypeOf<typeof PartialUser>
// same as
type PartialUser = {
name?: string
age?: number
}
You can define your own types. Let's see an example
// represents a Date from an ISO string
const DateFromString = new t.Type<Date, string, unknown>(
'DateFromString',
(u): u is Date => u instanceof Date,
(u, c) =>
t.string.validate(u, c).chain(s => {
const d = new Date(s)
return isNaN(d.getTime()) ? t.failure(u, c) : t.success(d)
}),
a => a.toISOString()
)
const s = new Date(1973, 10, 30).toISOString()
DateFromString.decode(s)
// right(new Date('1973-11-29T23:00:00.000Z'))
DateFromString.decode('foo')
// left(errors...)
Note that you can deserialize while validating.
Polymorphic codecs are represented using functions. For example, the following typescript:
interface ResponseBody<T> {
result: T
_links: Links
}
interface Links {
previous: string
next: string
}
Would be:
// t.Mixed = t.Type<any, any, unknown>
const ResponseBody = <C extends t.Mixed>(codec: C) =>
t.interface({
result: codec,
_links: Links
})
const Links = t.interface({
previous: t.string,
next: t.string
})
And used like:
const UserModel = t.type({
name: t.string
})
functionThatRequiresRuntimeType(ResponseBody(t.array(UserModel)), ...params)
You can pipe two codecs if their type parameters do align
const NumberCodec = new t.Type<number, string, string>(
'NumberCodec',
t.number.is,
(s, c) => {
const n = parseFloat(s)
return isNaN(n) ? t.failure(s, c) : t.success(n)
},
String
)
const NumberFromString = t.string.pipe(
NumberCodec,
'NumberFromString'
)
No, however you can define your own logic for that (if you really trust the input)
import * as t from 'io-ts'
import { Either, right } from 'fp-ts/lib/Either'
const { NODE_ENV } = process.env
export function unsafeDecode<A, O, I>(value: I, codec: t.Type<A, O, I>): Either<t.Errors, A> {
if (NODE_ENV !== 'production' || codec.encode !== t.identity) {
return codec.decode(value)
} else {
// unsafe cast
return right(value as any)
}
}
// or...
import { failure } from 'io-ts/lib/PathReporter'
export function unsafeGet<A, O, I>(value: I, codec: t.Type<A, O, I>): A {
if (NODE_ENV !== 'production' || type.encode !== t.identity) {
return codec.decode(value).getOrElseL(errors => {
throw new Error(failure(errors).join('\n'))
})
} else {
// unsafe cast
return value as any
}
}
Use keyof
instead of union
when defining a union of string literals
const Bad = t.union([
t.literal('foo'),
t.literal('bar'),
t.literal('baz')
// etc...
])
const Good = t.keyof({
foo: null,
bar: null,
baz: null
// etc...
})
Benefits
O(log(n))
vs O(n)
Beware that keyof
is designed to work with objects containing string keys. If you intend to define a numbers enumeration, you have to use an union
of number literals :
const HttpCode = t.union([
t.literal(200),
t.literal(201),
t.literal(202)
// etc...
])
1.8.6
output ES modules to better support tree-shaking, closes #326 (@gcanti)
FAQs
TypeScript runtime type system for IO decoding/encoding
The npm package io-ts receives a total of 0 weekly downloads. As such, io-ts popularity was classified as not popular.
We found that io-ts demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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