The yup npm package is a JavaScript schema builder for value parsing and validation. It enables developers to construct schemas for objects, arrays, strings, numbers, booleans, and more, to validate the shape and content of data against those schemas. It is often used in the context of form validation on both the client and server sides.
Object Shape Validation
Validates the shape of an object, ensuring that it has specific fields with data types and constraints like strings being required, numbers being positive integers, and strings matching email or URL patterns.
{"const schema = yup.object().shape({ name: yup.string().required(), age: yup.number().required().positive().integer(), email: yup.string().email(), website: yup.string().url() }); schema.isValid({ name: 'John', age: 24, email: 'john@example.com', website: 'http://example.com' }).then(valid => { console.log(valid); // true });"}Array Validation
Validates arrays, ensuring that they contain elements of a specific type and adhere to constraints, such as all elements being positive numbers.
{"const schema = yup.array().of(yup.number().positive()).required(); schema.isValid([1, 2, 3]).then(valid => { console.log(valid); // true });"}String Validation
Validates strings, ensuring they meet criteria such as being required, having a minimum length, and not exceeding a maximum length.
{"const schema = yup.string().required().min(2).max(10); schema.isValid('Hello').then(valid => { console.log(valid); // true });"}Number Validation
Validates numbers, ensuring they are positive, integers, and below a certain value.
{"const schema = yup.number().positive().integer().lessThan(100); schema.isValid(50).then(valid => { console.log(valid); // true });"}Date Validation
Validates dates, ensuring they fall within a specified range.
{"const schema = yup.date().min(new Date(2000, 0, 1)).max(new Date(2020, 12, 31)); schema.isValid(new Date(2010, 6, 15)).then(valid => { console.log(valid); // true });"}Custom Validation
Allows for custom validation functions to be defined, providing flexibility for more complex validation scenarios.
{"const schema = yup.string().test('is-john', 'The name must be John', value => value === 'John'); schema.isValid('John').then(valid => { console.log(valid); // true });"}Joi is a powerful schema description language and data validator for JavaScript. It offers a similar API to yup but with a broader feature set and more detailed error messages. Joi is often considered more heavyweight compared to yup.
Ajv is a JSON schema validator that supports draft-06/07/2019-09 of JSON Schema. It is known for its performance and is typically used for validating JSON data structures. Unlike yup, Ajv is based on pre-defined JSON schemas rather than a programmatic API.
Validator is a library of string validators and sanitizers. It is more focused on string validation and does not provide object schema validation like yup. It's useful for simple validation tasks without the need for defining complex schemas.
Class-validator works with TypeScript and uses decorators to define validation rules within class models. It is tightly integrated with TypeScript and is a good choice for projects that are already using TypeScript and decorators.
Yup is a schema builder for runtime value parsing and validation. Define a schema, transform a value to match, assert the shape of an existing value, or both. Yup schema are extremely expressive and allow modeling complex, interdependent validations, or value transformation.
You are viewing docs for the v1.0.0 of yup, pre-v1 docs are available: here
Killer Features:
Schema are comprised of parsing actions (transforms) as well as assertions (tests) about the input value. Validate an input value to parse it and run the configured set of assertions. Chain together methods to build a schema.
import { object, string, number, date, InferType } from 'yup';
let userSchema = object({
name: string().required(),
age: number().required().positive().integer(),
email: string().email(),
website: string().url().nullable(),
createdOn: date().default(() => new Date()),
});
// parse and assert validity
const user = await userSchema.validate(await fetchUser());
type User = InferType<typeof userSchema>;
/* {
name: string;
age: number;
email?: string | undefined
website?: string | null | undefined
createdOn: Date
}*/
Use a schema to coerce or "cast" an input value into the correct type, and optionally transform that value into more concrete and specific values, without making further assertions.
// Attempts to coerce values to the correct type
const parsedUser = userSchema.cast({
name: 'jimmy',
age: '24',
createdOn: '2014-09-23T19:25:25Z',
});
// ✅ { name: 'jimmy', age: 24, createdOn: Date }
Know that your input value is already parsed? You can "strictly" validate an input, and avoid the overhead of running parsing logic.
// ❌ ValidationError "age is not a number"
const parsedUser = await userSchema.validate(
{
name: 'jimmy',
age: '24',
},
{ strict: true },
);
yup
reach(schema: Schema, path: string, value?: object, context?: object): SchemaaddMethod(schemaType: Schema, name: string, method: ()=> Schema): voidref(path: string, options: { contextPrefix: string }): Reflazy((value: any) => Schema): LazyValidationError(errors: string | Array<string>, value: any, path: string)Schema
Schema.clone(): SchemaSchema.label(label: string): SchemaSchema.meta(metadata: SchemaMetadata): SchemaSchema.describe(options?: ResolveOptions): SchemaDescriptionSchema.concat(schema: Schema): SchemaSchema.validate(value: any, options?: object): Promise<InferType<Schema>, ValidationError>Schema.validateSync(value: any, options?: object): InferType<Schema>Schema.validateAt(path: string, value: any, options?: object): Promise<InferType<Schema>, ValidationError>Schema.validateSyncAt(path: string, value: any, options?: object): InferType<Schema>Schema.isValid(value: any, options?: object): Promise<boolean>Schema.isValidSync(value: any, options?: object): booleanSchema.cast(value: any, options = {}): InferType<Schema>Schema.isType(value: any): value is InferType<Schema>Schema.strict(enabled: boolean = false): SchemaSchema.strip(enabled: boolean = true): SchemaSchema.withMutation(builder: (current: Schema) => void): voidSchema.default(value: any): SchemaSchema.getDefault(options?: object): AnySchema.nullable(message?: string | function): SchemaSchema.nonNullable(message?: string | function): SchemaSchema.defined(): SchemaSchema.optional(): SchemaSchema.required(message?: string | function): SchemaSchema.notRequired(): SchemaSchema.typeError(message: string): SchemaSchema.oneOf(arrayOfValues: Array<any>, message?: string | function): Schema Alias: equalsSchema.notOneOf(arrayOfValues: Array<any>, message?: string | function)Schema.when(keys: string | string[], builder: object | (values: any[], schema) => Schema): SchemaSchema.test(name: string, message: string | function | any, test: function): SchemaSchema.test(options: object): SchemaSchema.transform((currentValue: any, originalValue: any) => any): Schemastring.required(message?: string | function): Schemastring.length(limit: number | Ref, message?: string | function): Schemastring.min(limit: number | Ref, message?: string | function): Schemastring.max(limit: number | Ref, message?: string | function): Schemastring.matches(regex: Regex, message?: string | function): Schemastring.matches(regex: Regex, options: { message: string, excludeEmptyString: bool }): Schemastring.email(message?: string | function): Schemastring.url(message?: string | function): Schemastring.uuid(message?: string | function): Schemastring.datetime(options?: {message?: string | function, allowOffset?: boolean, precision?: number})string.datetime(message?: string | function)string.ensure(): Schemastring.trim(message?: string | function): Schemastring.lowercase(message?: string | function): Schemastring.uppercase(message?: string | function): Schemanumber.min(limit: number | Ref, message?: string | function): Schemanumber.max(limit: number | Ref, message?: string | function): Schemanumber.lessThan(max: number | Ref, message?: string | function): Schemanumber.moreThan(min: number | Ref, message?: string | function): Schemanumber.positive(message?: string | function): Schemanumber.negative(message?: string | function): Schemanumber.integer(message?: string | function): Schemanumber.truncate(): Schemanumber.round(type: 'floor' | 'ceil' | 'trunc' | 'round' = 'round'): Schemaarray.of(type: Schema): thisarray.json(): thisarray.length(length: number | Ref, message?: string | function): thisarray.min(limit: number | Ref, message?: string | function): thisarray.max(limit: number | Ref, message?: string | function): thisarray.ensure(): thisarray.compact(rejector: (value) => boolean): Schemaobject.shape(fields: object, noSortEdges?: Array<[string, string]>): Schemaobject.json(): thisobject.concat(schemaB: ObjectSchema): ObjectSchemaobject.pick(keys: string[]): Schemaobject.omit(keys: string[]): Schemaobject.from(fromKey: string, toKey: string, alias: boolean = false): thisobject.noUnknown(onlyKnownKeys: boolean = true, message?: string | function): Schemaobject.camelCase(): Schemaobject.constantCase(): SchemaSchema definitions, are comprised of parsing "transforms" which manipulate inputs into the desired shape and type, "tests", which make assertions over parsed data. Schema also store a bunch of "metadata", details about the schema itself, which can be used to improve error messages, build tools that dynamically consume schema, or serialize schema into another format.
In order to be maximally flexible yup allows running both parsing and assertions separately to match specific needs
Each built-in type implements basic type parsing, which comes in handy when parsing serialized data, such as JSON. Additionally types implement type specific transforms that can be enabled.
const num = number().cast('1'); // 1
const obj = object({
firstName: string().lowercase().trim(),
})
.json()
.camelCase()
.cast('{"first_name": "jAnE "}'); // { firstName: 'jane' }
Custom transforms can be added
const reversedString = string()
.transform((currentValue) => currentValue.split('').reverse().join(''))
.cast('dlrow olleh'); // "hello world"
Transforms form a "pipeline", where the value of a previous transform is piped into the next one.
When an input value is undefined yup will apply the schema default if it's configured.
Watch out! values are not guaranteed to be valid types in transform functions. Previous transforms may have failed. For example a number transform may be receive the input value,
NaN, or a number.
Yup schema run "tests" over input values. Tests assert that inputs conform to some criteria. Tests are distinct from transforms, in that they do not change or alter the input (or its type) and are usually reserved for checks that are hard, if not impossible, to represent in static types.
string()
.min(3, 'must be at least 3 characters long')
.email('must be a valid email')
.validate('no'); // ValidationError
As with transforms, tests can be customized on the fly
const jamesSchema = string().test(
'is-james',
(d) => `${d.path} is not James`,
(value) => value == null || value === 'James',
);
jamesSchema.validateSync('James'); // "James"
jamesSchema.validateSync('Jane'); // ValidationError "this is not James"
Heads up: unlike transforms,
valuein a custom test is guaranteed to be the correct type (in this case an optional string). It still may beundefinedornulldepending on your schema in those cases, you may want to returntruefor absent values unless your transform makes presence related assertions. The test optionskipAbsentwill do this for you if set.
In the simplest case a test function returns true or false depending on the whether the check
passed. In the case of a failing test, yup will throw
a ValidationError with your (or the default)
message for that test. ValidationErrors also contain a bunch of other metadata about the test,
including it's name, what arguments (if any) it was called with, and the path to the failing field
in the case of a nested validation.
Error messages can also be constructed on the fly to customize how the schema fails.
const order = object({
no: number().required().
sku: string().test({
name: 'is-sku',
skipAbsent: true,
test(value, ctx) {
if (!value.startsWith('s-')) {
return ctx.createError({ message: 'SKU missing correct prefix' })
}
if (!value.endsWith('-42a')) {
return ctx.createError({ message: 'SKU missing correct suffix' })
}
if (value.length < 10) {
return ctx.createError({ message: 'SKU is not the right length' })
}
return true
}
})
})
order.validate({ no: 1234, sku: 's-1a45-14a' })
Schema are immutable, each method call returns a new schema object. Reuse and pass them around without fear of mutating another instance.
const optionalString = string().optional();
const definedString = optionalString.defined();
const value = undefined;
optionalString.isValid(value); // true
definedString.isValid(value); // false
Yup schema produce static TypeScript interfaces. Use InferType to extract that interface:
import * as yup from 'yup';
const personSchema = yup.object({
firstName: yup.string().defined(),
nickName: yup.string().default('').nullable(),
sex: yup
.mixed()
.oneOf(['male', 'female', 'other'] as const)
.defined(),
email: yup.string().nullable().email(),
birthDate: yup.date().nullable().min(new Date(1900, 0, 1)),
});
interface Person extends yup.InferType<typeof personSchema> {
// using interface instead of type generally gives nicer editor feedback
}
A schema's default is used when casting produces an undefined output value. Because of this,
setting a default affects the output type of the schema, essentially marking it as "defined()".
import { string } from 'yup';
const value: string = string().default('hi').validate(undefined);
// vs
const value: string | undefined = string().validate(undefined);
In some cases a TypeScript type already exists, and you want to ensure that your schema produces a compatible type:
import { object, number, string, ObjectSchema } from 'yup';
interface Person {
name: string;
age?: number;
sex: 'male' | 'female' | 'other' | null;
}
// will raise a compile-time type error if the schema does not produce a valid Person
const schema: ObjectSchema<Person> = object({
name: string().defined(),
age: number().optional(),
sex: string<'male' | 'female' | 'other'>().nullable().defined(),
});
// ❌ errors:
// "Type 'number | undefined' is not assignable to type 'string'."
const badSchema: ObjectSchema<Person> = object({
name: number(),
});
You can use TypeScript's interface merging behavior to extend the schema types
if needed. Type extensions should go in an "ambient" type definition file such as your
globals.d.ts. Remember to actually extend the yup type in your application code!
Watch out! merging only works if the type definition is exactly the same, including generics. Consult the yup source code for each type to ensure you are defining it correctly
// globals.d.ts
declare module 'yup' {
interface StringSchema<TType, TContext, TDefault, TFlags> {
append(appendStr: string): this;
}
}
// app.ts
import { addMethod, string } from 'yup';
addMethod(string, 'append', function append(appendStr: string) {
return this.transform((value) => `${value}${appendStr}`);
});
string().append('~~~~').cast('hi'); // 'hi~~~~'
You must have the strictNullChecks compiler option enabled for type inference to work.
We also recommend settings strictFunctionTypes to false, for functionally better types. Yes
this reduces overall soundness, however TypeScript already disables this check
for methods and constructors (note from TS docs):
During development of this feature, we discovered a large number of inherently unsafe class hierarchies, including some in the DOM. Because of this, the setting only applies to functions written in function syntax, not to those in method syntax:
Your mileage will vary, but we've found that this check doesn't prevent many of real bugs, while increasing the amount of onerous explicit type casting in apps.
Default error messages can be customized for when no message is provided with a validation test. If any message is missing in the custom dictionary the error message will default to Yup's one.
import { setLocale } from 'yup';
setLocale({
mixed: {
default: 'Não é válido',
},
number: {
min: 'Deve ser maior que ${min}',
},
});
// now use Yup schemas AFTER you defined your custom dictionary
let schema = yup.object().shape({
name: yup.string(),
age: yup.number().min(18),
});
try {
await schema.validate({ name: 'jimmy', age: 11 });
} catch (err) {
err.name; // => 'ValidationError'
err.errors; // => ['Deve ser maior que 18']
}
If you need multi-language support, yup has got you covered. The function setLocale accepts functions that can be used to
generate error objects with translation keys and values. These can be fed it into your favorite i18n library.
import { setLocale } from 'yup';
setLocale({
// use constant translation keys for messages without values
mixed: {
default: 'field_invalid',
},
// use functions to generate an error object that includes the value from the schema
number: {
min: ({ min }) => ({ key: 'field_too_short', values: { min } }),
max: ({ max }) => ({ key: 'field_too_big', values: { max } }),
},
});
// ...
let schema = yup.object().shape({
name: yup.string(),
age: yup.number().min(18),
});
try {
await schema.validate({ name: 'jimmy', age: 11 });
} catch (err) {
messages = err.errors.map((err) => i18next.t(err.key));
}
yupThe module export.
// core schema
import {
mixed,
string,
number,
boolean,
bool,
date,
object,
array,
ref,
lazy,
} from 'yup';
// Classes
import {
Schema,
MixedSchema,
StringSchema,
NumberSchema,
BooleanSchema,
DateSchema,
ArraySchema,
ObjectSchema,
} from 'yup';
// Types
import type { InferType, ISchema, AnySchema, AnyObjectSchema } from 'yup';
reach(schema: Schema, path: string, value?: object, context?: object): SchemaFor nested schemas, reach will retrieve an inner schema based on the provided path.
For nested schemas that need to resolve dynamically, you can provide a value and optionally
a context object.
import { reach } from 'yup';
let schema = object({
nested: object({
arr: array(object({ num: number().max(4) })),
}),
});
reach(schema, 'nested.arr.num');
reach(schema, 'nested.arr[].num');
reach(schema, 'nested.arr[1].num');
reach(schema, 'nested["arr"][1].num');
addMethod(schemaType: Schema, name: string, method: ()=> Schema): voidAdds a new method to the core schema types. A friendlier convenience method for schemaType.prototype[name] = method.
import { addMethod, date } from 'yup';
addMethod(date, 'format', function format(formats, parseStrict) {
return this.transform((value, originalValue, ctx) => {
if (ctx.isType(value)) return value;
value = Moment(originalValue, formats, parseStrict);
return value.isValid() ? value.toDate() : new Date('');
});
});
If you want to add a method to ALL schema types, extend the abstract base class: Schema
import { addMethod, Schema } from 'yup';
addMethod(Schema, 'myMethod', ...)
ref(path: string, options: { contextPrefix: string }): RefCreates a reference to another sibling or sibling descendant field. Refs are resolved at validation/cast time and supported where specified. Refs are evaluated in the proper order so that the ref value is resolved before the field using the ref (be careful of circular dependencies!).
import { ref, object, string } from 'yup';
let schema = object({
baz: ref('foo.bar'),
foo: object({
bar: string(),
}),
x: ref('$x'),
});
schema.cast({ foo: { bar: 'boom' } }, { context: { x: 5 } });
// => { baz: 'boom', x: 5, foo: { bar: 'boom' } }
lazy((value: any) => Schema): LazyCreates a schema that is evaluated at validation/cast time. Useful for creating recursive schema like Trees, for polymorphic fields and arrays.
CAUTION! When defining parent-child recursive object schema, you want to reset the default()
to null on the child—otherwise the object will infinitely nest itself when you cast it!
let node = object({
id: number(),
child: yup.lazy(() => node.default(undefined)),
});
let renderable = yup.lazy((value) => {
switch (typeof value) {
case 'number':
return number();
case 'string':
return string();
default:
return mixed();
}
});
let renderables = array().of(renderable);
ValidationError(errors: string | Array<string>, value: any, path: string)Thrown on failed validations, with the following properties
name: "ValidationError"type: the specific test type or test "name", that failed.value: The field value that was tested;params?: The test inputs, such as max value, regex, etc;path: a string, indicating where there error was thrown. path is empty at the root level.errors: array of error messagesinner: in the case of aggregate errors, inner is an array of ValidationErrors throw earlier in the
validation chain. When the abortEarly option is false this is where you can inspect each error thrown,
alternatively, errors will have all of the messages from each inner error.SchemaSchema is the abstract base class that all schema type inherit from. It provides a number of base methods and properties
to all other schema types.
Note: unless you are creating a custom schema type, Schema should never be used directly. For unknown/any types use
mixed()
Schema.clone(): SchemaCreates a deep copy of the schema. Clone is used internally to return a new schema with every schema state change.
Schema.label(label: string): SchemaOverrides the key name which is used in error messages.
Schema.meta(metadata: SchemaMetadata): SchemaAdds to a metadata object, useful for storing data with a schema, that doesn't belong to the cast object itself.
A custom SchemaMetadata interface can be defined through
merging
with the CustomSchemaMetadata interface. Start by creating a yup.d.ts file
in your package and creating your desired CustomSchemaMetadata interface:
// yup.d.ts
import 'yup';
declare module 'yup' {
// Define your desired `SchemaMetadata` interface by merging the
// `CustomSchemaMetadata` interface.
export interface CustomSchemaMetadata {
placeholderText?: string;
tooltipText?: string;
// …
}
}
Schema.describe(options?: ResolveOptions): SchemaDescriptionCollects schema details (like meta, labels, and active tests) into a serializable description object.
const schema = object({
name: string().required(),
});
const description = schema.describe();
For schema with dynamic components (references, lazy, or conditions), describe requires
more context to accurately return the schema description. In these cases provide options
import { ref, object, string, boolean } from 'yup';
let schema = object({
isBig: boolean(),
count: number().when('isBig', {
is: true,
then: (schema) => schema.min(5),
otherwise: (schema) => schema.min(0),
}),
});
schema.describe({ value: { isBig: true } });
And below are the description types, which differ a bit depending on the schema type.
interface SchemaDescription {
type: string;
label?: string;
meta: object | undefined;
oneOf: unknown[];
notOneOf: unknown[];
default?: unknown;
nullable: boolean;
optional: boolean;
tests: Array<{ name?: string; params: ExtraParams | undefined }>;
// Present on object schema descriptions
fields: Record<string, SchemaFieldDescription>;
// Present on array schema descriptions
innerType?: SchemaFieldDescription;
}
type SchemaFieldDescription =
| SchemaDescription
| SchemaRefDescription
| SchemaLazyDescription;
interface SchemaRefDescription {
type: 'ref';
key: string;
}
interface SchemaLazyDescription {
type: string;
label?: string;
meta: object | undefined;
}
Schema.concat(schema: Schema): SchemaCreates a new instance of the schema by combining two schemas. Only schemas of the same type can be concatenated.
concat is not a "merge" function in the sense that all settings from the provided schema, override ones in the
base, including type, presence and nullability.
mixed<string>().defined().concat(mixed<number>().nullable());
// produces the equivalent to:
mixed<number>().defined().nullable();
Schema.validate(value: any, options?: object): Promise<InferType<Schema>, ValidationError>Returns the parses and validates an input value, returning the parsed value or throwing an error. This method is asynchronous and returns a Promise object, that is fulfilled with the value, or rejected
with a ValidationError.
value = await schema.validate({ name: 'jimmy', age: 24 });
Provide options to more specifically control the behavior of validate.
interface Options {
// when true, parsing is skipped and the input is validated "as-is"
strict: boolean = false;
// Throw on the first error or collect and return all
abortEarly: boolean = true;
// Remove unspecified keys from objects
stripUnknown: boolean = false;
// when `false` validations will be performed shallowly
recursive: boolean = true;
// External values that can be provided to validations and conditionals
context?: object;
}
Schema.validateSync(value: any, options?: object): InferType<Schema>Runs validatations synchronously if possible and returns the resulting value,
or throws a ValidationError. Accepts all the same options as validate.
Synchronous validation only works if there are no configured async tests, e.g tests that return a Promise. For instance this will work:
let schema = number().test(
'is-42',
"this isn't the number i want",
(value) => value != 42,
);
schema.validateSync(23); // throws ValidationError
however this will not:
let schema = number().test('is-42', "this isn't the number i want", (value) =>
Promise.resolve(value != 42),
);
schema.validateSync(42); // throws Error
Schema.validateAt(path: string, value: any, options?: object): Promise<InferType<Schema>, ValidationError>Validate a deeply nested path within the schema. Similar to how reach works,
but uses the resulting schema as the subject for validation.
Note! The
valuehere is the root value relative to the starting schema, not the value at the nested path.
let schema = object({
foo: array().of(
object({
loose: boolean(),
bar: string().when('loose', {
is: true,
otherwise: (schema) => schema.strict(),
}),
}),
),
});
let rootValue = {
foo: [{ bar: 1 }, { bar: 1, loose: true }],
};
await schema.validateAt('foo[0].bar', rootValue); // => ValidationError: must be a string
await schema.validateAt('foo[1].bar', rootValue); // => '1'
Schema.validateSyncAt(path: string, value: any, options?: object): InferType<Schema>Same as validateAt but synchronous.
Schema.isValid(value: any, options?: object): Promise<boolean>Returns true when the passed in value matches the schema. isValid
is asynchronous and returns a Promise object.
Takes the same options as validate().
Schema.isValidSync(value: any, options?: object): booleanSynchronously returns true when the passed in value matches the schema.
Takes the same options as validateSync() and has the same caveats around async tests.
Schema.cast(value: any, options = {}): InferType<Schema>Attempts to coerce the passed in value to a value that matches the schema. For example: '5' will
cast to 5 when using the number() type. Failed casts generally return null, but may also
return results like NaN and unexpected strings.
Provide options to more specifically control the behavior of validate.
interface CastOptions<TContext extends {}> {
// Remove undefined properties from objects
stripUnknown: boolean = false;
// Throws a TypeError if casting doesn't produce a valid type
// note that the TS return type is inaccurate when this is `false`, use with caution
assert?: boolean = true;
// External values that used to resolve conditions and references
context?: TContext;
}
Schema.isType(value: any): value is InferType<Schema>Runs a type check against the passed in value. It returns true if it matches,
it does not cast the value. When nullable() is set null is considered a valid value of the type.
You should use isType for all Schema type checks.
Schema.strict(enabled: boolean = false): SchemaSets the strict option to true. Strict schemas skip coercion and transformation attempts,
validating the value "as is".
Schema.strip(enabled: boolean = true): SchemaMarks a schema to be removed from an output object. Only works as a nested schema.
let schema = object({
useThis: number(),
notThis: string().strip(),
});
schema.cast({ notThis: 'foo', useThis: 4 }); // => { useThis: 4 }
Schema with strip enabled have an inferred type of never, allowing them to be
removed from the overall type:
let schema = object({
useThis: number(),
notThis: string().strip(),
});
InferType<typeof schema>; /*
{
useThis?: number | undefined
}
*/
Schema.withMutation(builder: (current: Schema) => void): voidFirst the legally required Rich Hickey quote:
If a tree falls in the woods, does it make a sound?
If a pure function mutates some local data in order to produce an immutable return value, is that ok?
withMutation allows you to mutate the schema in place, instead of the default behavior which clones before each change. Generally this isn't necessary since the vast majority of schema changes happen during the initial
declaration, and only happen once over the lifetime of the schema, so performance isn't an issue.
However certain mutations do occur at cast/validation time, (such as conditional schema using when()), or
when instantiating a schema object.
object()
.shape({ key: string() })
.withMutation((schema) => {
return arrayOfObjectTests.forEach((test) => {
schema.test(test);
});
});
Schema.default(value: any): SchemaSets a default value to use when the value is undefined.
Defaults are created after transformations are executed, but before validations, to help ensure that safe
defaults are specified. The default value will be cloned on each use, which can incur performance penalty
for objects and arrays. To avoid this overhead you can also pass a function that returns a new default.
Note that null is considered a separate non-empty value.
yup.string.default('nothing');
yup.object.default({ number: 5 }); // object will be cloned every time a default is needed
yup.object.default(() => ({ number: 5 })); // this is cheaper
yup.date.default(() => new Date()); // also helpful for defaults that change over time
Schema.getDefault(options?: object): AnyRetrieve a previously set default value. getDefault will resolve any conditions that may alter the default. Optionally pass options with context (for more info on context see Schema.validate).
Schema.nullable(message?: string | function): SchemaIndicates that null is a valid value for the schema. Without nullable()
null is treated as a different type and will fail Schema.isType() checks.
const schema = number().nullable();
schema.cast(null); // null
InferType<typeof schema>; // number | null
Schema.nonNullable(message?: string | function): SchemaThe opposite of nullable, removes null from valid type values for the schema.
Schema are non nullable by default.
const schema = number().nonNullable();
schema.cast(null); // TypeError
InferType<typeof schema>; // number
Schema.defined(): SchemaRequire a value for the schema. All field values apart from undefined meet this requirement.
const schema = string().defined();
schema.cast(undefined); // TypeError
InferType<typeof schema>; // string
Schema.optional(): SchemaThe opposite of defined() allows undefined values for the given type.
const schema = string().optional();
schema.cast(undefined); // undefined
InferType<typeof schema>; // string | undefined
Schema.required(message?: string | function): SchemaMark the schema as required, which will not allow undefined or null as a value. required
negates the effects of calling optional() and nullable()
Watch out!
string().required) works a little different and additionally prevents empty string values ('') when required.
Schema.notRequired(): SchemaMark the schema as not required. This is a shortcut for schema.nullable().optional();
Schema.typeError(message: string): SchemaDefine an error message for failed type checks. The ${value} and ${type} interpolation can
be used in the message argument.
Schema.oneOf(arrayOfValues: Array<any>, message?: string | function): Schema Alias: equalsOnly allow values from set of values. Values added are removed from any notOneOf values if present.
The ${values} interpolation can be used in the message argument. If a ref or refs are provided,
the ${resolved} interpolation can be used in the message argument to get the resolved values that were checked
at validation time.
Note that undefined does not fail this validator, even when undefined is not included in arrayOfValues.
If you don't want undefined to be a valid value, you can use Schema.required.
let schema = yup.mixed().oneOf(['jimmy', 42]);
await schema.isValid(42); // => true
await schema.isValid('jimmy'); // => true
await schema.isValid(new Date()); // => false
Schema.notOneOf(arrayOfValues: Array<any>, message?: string | function)Disallow values from a set of values. Values added are removed from oneOf values if present.
The ${values} interpolation can be used in the message argument. If a ref or refs are provided,
the ${resolved} interpolation can be used in the message argument to get the resolved values that were checked
at validation time.
let schema = yup.mixed().notOneOf(['jimmy', 42]);
await schema.isValid(42); // => false
await schema.isValid(new Date()); // => true
Schema.when(keys: string | string[], builder: object | (values: any[], schema) => Schema): SchemaAdjust the schema based on a sibling or sibling children fields. You can provide an object
literal where the key is is value or a matcher function, then provides the true schema and/or
otherwise for the failure condition.
is conditions are strictly compared (===) if you want to use a different form of equality you
can provide a function like: is: (value) => value == true.
You can also prefix properties with $ to specify a property that is dependent
on context passed in by validate() or cast instead of the input value.
when conditions are additive.
then and otherwise are specified functions (schema: Schema) => Schema.
let schema = object({
isBig: boolean(),
count: number()
.when('isBig', {
is: true, // alternatively: (val) => val == true
then: (schema) => schema.min(5),
otherwise: (schema) => schema.min(0),
})
.when('$other', ([other], schema) =>
other === 4 ? schema.max(6) : schema,
),
});
await schema.validate(value, { context: { other: 4 } });
You can also specify more than one dependent key, in which case each value will be spread as an argument.
let schema = object({
isSpecial: boolean(),
isBig: boolean(),
count: number().when(['isBig', 'isSpecial'], {
is: true, // alternatively: (isBig, isSpecial) => isBig && isSpecial
then: (schema) => schema.min(5),
otherwise: (schema) => schema.min(0),
}),
});
await schema.validate({
isBig: true,
isSpecial: true,
count: 10,
});
Alternatively you can provide a function that returns a schema, called with an array of values for each provided key the current schema.
let schema = yup.object({
isBig: yup.boolean(),
count: yup.number().when('isBig', ([isBig], schema) => {
return isBig ? schema.min(5) : schema.min(0);
}),
});
await schema.validate({ isBig: false, count: 4 });
Schema.test(name: string, message: string | function | any, test: function): SchemaAdds a test function to the validation chain. Tests are run after any object is cast. Many types have some tests built in, but you can create custom ones easily. In order to allow asynchronous custom validations all (or no) tests are run asynchronously. A consequence of this is that test execution order cannot be guaranteed.
All tests must provide a name, an error message and a validation function that must return
true when the current value is valid and false or a ValidationError otherwise.
To make a test async return a promise that resolves true or false or a ValidationError.
For the message argument you can provide a string which will interpolate certain values
if specified using the ${param} syntax. By default all test messages are passed a path value
which is valuable in nested schemas.
The test function is called with the current value. For more advanced validations you can
use the alternate signature to provide more options (see below):
let jimmySchema = string().test(
'is-jimmy',
'${path} is not Jimmy',
(value, context) => value === 'jimmy',
);
// or make it async by returning a promise
let asyncJimmySchema = string()
.label('First name')
.test(
'is-jimmy',
({ label }) => `${label} is not Jimmy`, // a message can also be a function
async (value, testContext) =>
(await fetch('/is-jimmy/' + value)).responseText === 'true',
);
await schema.isValid('jimmy'); // => true
await schema.isValid('john'); // => false
Test functions are called with a special context value, as the second argument, that exposes some useful metadata
and functions. For non arrow functions, the test context is also set as the function this. Watch out, if you access
it via this it won't work in an arrow function.
testContext.path: the string path of the current validationtestContext.schema: the resolved schema object that the test is running against.testContext.options: the options object that validate() or isValid() was called withtestContext.parent: in the case of nested schema, this is the value of the parent objecttestContext.originalValue: the original value that is being testedtestContext.createError(Object: { path: String, message: String, params: Object }): create and return a
validation error. Useful for dynamically setting the path, params, or more likely, the error message.
If either option is omitted it will use the current path, or default message.Schema.test(options: object): SchemaAlternative test(..) signature. options is an object containing some of the following options:
Options = {
// unique name identifying the test
name: string;
// test function, determines schema validity
test: (value: any) => boolean;
// the validation error message
message: string;
// values passed to message for interpolation
params: ?object;
// mark the test as exclusive, meaning only one test of the same name can be active at once
exclusive: boolean = false;
}
In the case of mixing exclusive and non-exclusive tests the following logic is used. If a non-exclusive test is added to a schema with an exclusive test of the same name the exclusive test is removed and further tests of the same name will be stacked.
If an exclusive test is added to a schema with non-exclusive tests of the same name the previous tests are removed and further tests of the same name will replace each other.
let max = 64;
let schema = yup.string().test({
name: 'max',
exclusive: true,
params: { max },
message: '${path} must be less than ${max} characters',
test: (value) => value == null || value.length <= max,
});
Schema.transform((currentValue: any, originalValue: any) => any): SchemaAdds a transformation to the transform chain. Transformations are central to the casting process,
default transforms for each type coerce values to the specific type (as verified by isType()). transforms are run before validations and only applied when the schema is not marked as strict (the default). Some types have built in transformations.
Transformations are useful for arbitrarily altering how the object is cast, however, you should take care
not to mutate the passed in value. Transforms are run sequentially so each value represents the
current state of the cast, you can use the originalValue param if you need to work on the raw initial value.
let schema = string().transform((value, originalValue) => {
return this.isType(value) && value !== null ? value.toUpperCase() : value;
});
schema.cast('jimmy'); // => 'JIMMY'
Each types will handle basic coercion of values to the proper type for you, but occasionally you may want to adjust or refine the default behavior. For example, if you wanted to use a different date parsing strategy than the default one you could do that with a transform.
module.exports = function (formats = 'MMM dd, yyyy') {
return date().transform((value, originalValue, context) => {
// check to see if the previous transform already parsed the date
if (context.isType(value)) return value;
// the default coercion failed so let's try it with Moment.js instead
value = Moment(originalValue, formats);
// if it's valid return the date object, otherwise return an `InvalidDate`
return value.isValid() ? value.toDate() : new Date('');
});
};
Creates a schema that matches all types, or just the ones you configure. Inherits from Schema.
Mixed types extends {} by default instead of any or unknown. This is because in TypeScript {} means
anything that isn't null or undefined which yup treats distinctly.
import { mixed, InferType } from 'yup';
let schema = mixed().nullable();
schema.validateSync('string'); // 'string';
schema.validateSync(1); // 1;
schema.validateSync(new Date()); // Date;
InferType<typeof schema>; // {} | undefined
InferType<typeof schema.nullable().defined()>; // {} | null
Custom types can be implemented by passing a type check function. This will also
narrow the TypeScript type for the schema.
import { mixed, InferType } from 'yup';
let objectIdSchema = yup
.mixed((input): input is ObjectId => input instanceof ObjectId)
.transform((value: any, input, ctx) => {
if (ctx.isType(value)) return value;
return new ObjectId(value);
});
await objectIdSchema.validate(ObjectId('507f1f77bcf86cd799439011')); // ObjectId("507f1f77bcf86cd799439011")
await objectIdSchema.validate('507f1f77bcf86cd799439011'); // ObjectId("507f1f77bcf86cd799439011")
InferType<typeof objectIdSchema>; // ObjectId
Define a string schema. Inherits from Schema.
let schema = yup.string();
await schema.isValid('hello'); // => true
By default, the cast logic of string is to call toString on the value if it exists.
empty values are not coerced (use ensure() to coerce empty values to empty strings).
Failed casts return the input value.
string.required(message?: string | function): SchemaThe same as the mixed() schema required, except that empty strings are also considered 'missing' values.
string.length(limit: number | Ref, message?: string | function): SchemaSet a required length for the string value. The ${length} interpolation can be used in the message argument
string.min(limit: number | Ref, message?: string | function): SchemaSet a minimum length limit for the string value. The ${min} interpolation can be used in the message argument
string.max(limit: number | Ref, message?: string | function): SchemaSet a maximum length limit for the string value. The ${max} interpolation can be used in the message argument
string.matches(regex: Regex, message?: string | function): SchemaProvide an arbitrary regex to match the value against.
let schema = string().matches(/(hi|bye)/);
await schema.isValid('hi'); // => true
await schema.isValid('nope'); // => false
string.matches(regex: Regex, options: { message: string, excludeEmptyString: bool }): SchemaAn alternate signature for string.matches with an options object. excludeEmptyString, when true,
short circuits the regex test when the value is an empty string, making it a easier to avoid
matching nothing without complicating the regex.
let schema = string().matches(/(hi|bye)/, { excludeEmptyString: true });
await schema.isValid(''); // => true
string.email(message?: string | function): SchemaValidates the value as an email address using the same regex as defined by the HTML spec.
WATCH OUT: Validating email addresses is nearly impossible with just code. Different clients and servers accept different things and many diverge from the various specs defining "valid" emails. The ONLY real way to validate an email address is to send a verification email to it and check that the user got it. With that in mind, yup picks a relatively simple regex that does not cover all cases, but aligns with browser input validation behavior since HTML forms are a common use case for yup.
If you have more specific needs please override the email method with your own logic or regex:
yup.addMethod(yup.string, 'email', function validateEmail(message) {
return this.matches(myEmailRegex, {
message,
name: 'email',
excludeEmptyString: true,
});
});
string.url(message?: string | function): SchemaValidates the value as a valid URL via a regex.
string.uuid(message?: string | function): SchemaValidates the value as a valid UUID via a regex.
string.datetime(options?: {message?: string | function, allowOffset?: boolean, precision?: number})Validates the value as an ISO datetime via a regex. Defaults to UTC validation; timezone offsets are not permitted (see options.allowOffset).
Unlike .date(), datetime will not convert the string to a Date object. datetime also provides greater customization over the required format of the datetime string than date does.
options.allowOffset: Allow a time zone offset. False requires UTC 'Z' timezone. (default: false)
options.precision: Require a certain sub-second precision on the date. (default: null -- any (or no) sub-second precision)
string.datetime(message?: string | function)An alternate signature for string.datetime that can be used when you don't need to pass options other than message.
string.ensure(): SchemaTransforms undefined and null values to an empty string along with
setting the default to an empty string.
string.trim(message?: string | function): SchemaTransforms string values by removing leading and trailing whitespace. If
strict() is set it will only validate that the value is trimmed.
string.lowercase(message?: string | function): SchemaTransforms the string value to lowercase. If strict() is set it
will only validate that the value is lowercase.
string.uppercase(message?: string | function): SchemaTransforms the string value to uppercase. If strict() is set it
will only validate that the value is uppercase.
Define a number schema. Inherits from Schema.
let schema = yup.number();
await schema.isValid(10); // => true
The default cast logic of number is: parseFloat.
Failed casts return NaN.
number.min(limit: number | Ref, message?: string | function): SchemaSet the minimum value allowed. The ${min} interpolation can be used in the
message argument.
number.max(limit: number | Ref, message?: string | function): SchemaSet the maximum value allowed. The ${max} interpolation can be used in the
message argument.
number.lessThan(max: number | Ref, message?: string | function): SchemaValue must be less than max. The ${less} interpolation can be used in the
message argument.
number.moreThan(min: number | Ref, message?: string | function): SchemaValue must be strictly greater than min. The ${more} interpolation can be used in the
message argument.
number.positive(message?: string | function): SchemaValue must be a positive number.
number.negative(message?: string | function): SchemaValue must be a negative number.
number.integer(message?: string | function): SchemaValidates that a number is an integer.
number.truncate(): SchemaTransformation that coerces the value to an integer by stripping off the digits to the right of the decimal point.
number.round(type: 'floor' | 'ceil' | 'trunc' | 'round' = 'round'): SchemaAdjusts the value via the specified method of Math (defaults to 'round').
Define a boolean schema. Inherits from Schema.
let schema = yup.boolean();
await schema.isValid(true); // => true
Define a Date schema. By default ISO date strings will parse correctly,
for more robust parsing options see the extending schema types at the end of the readme.
Inherits from Schema.
let schema = yup.date();
await schema.isValid(new Date()); // => true
The default cast logic of date is pass the value to the Date constructor, failing that, it will attempt
to parse the date as an ISO date string.
If you would like ISO strings to not be cast to a
Dateobject, use.datetime()instead.
Failed casts return an invalid Date.
date.min(limit: Date | string | Ref, message?: string | function): SchemaSet the minimum date allowed. When a string is provided it will attempt to cast to a date first and use the result as the limit.
date.max(limit: Date | string | Ref, message?: string | function): SchemaSet the maximum date allowed, When a string is provided it will attempt to cast to a date first and use the result as the limit.
Define an array schema. Arrays can be typed or not, When specifying the element type, cast and isValid
will apply to the elements as well. Options passed into isValid are also passed to child schemas.
Inherits from Schema.
let schema = yup.array().of(yup.number().min(2));
await schema.isValid([2, 3]); // => true
await schema.isValid([1, -24]); // => false
schema.cast(['2', '3']); // => [2, 3]
You can also pass a subtype schema to the array constructor as a convenience.
array().of(yup.number());
// or
array(yup.number());
Arrays have no default casting behavior.
array.of(type: Schema): thisSpecify the schema of array elements. of() is optional and when omitted the array schema will
not validate its contents.
array.json(): thisAttempt to parse input string values as JSON using JSON.parse.
array.length(length: number | Ref, message?: string | function): thisSet a specific length requirement for the array. The ${length} interpolation can be used in the message argument.
array.min(limit: number | Ref, message?: string | function): thisSet a minimum length limit for the array. The ${min} interpolation can be used in the message argument.
array.max(limit: number | Ref, message?: string | function): thisSet a maximum length limit for the array. The ${max} interpolation can be used in the message argument.
array.ensure(): thisEnsures that the value is an array, by setting the default to [] and transforming null and undefined
values to an empty array as well. Any non-empty, non-array value will be wrapped in an array.
array().ensure().cast(null); // => []
array().ensure().cast(1); // => [1]
array().ensure().cast([1]); // => [1]
array.compact(rejector: (value) => boolean): SchemaRemoves falsey values from the array. Providing a rejecter function lets you specify the rejection criteria yourself.
array().compact().cast(['', 1, 0, 4, false, null]); // => [1, 4]
array()
.compact(function (v) {
return v == null;
})
.cast(['', 1, 0, 4, false, null]); // => ['', 1, 0, 4, false]
Tuples, are fixed length arrays where each item has a distinct type.
Inherits from Schema.
import { tuple, string, number, InferType } from 'yup';
let schema = tuple([
string().label('name'),
number().label('age').positive().integer(),
]);
await schema.validate(['James', 3]); // ['James', 3]
await schema.validate(['James', -24]); // => ValidationError: age must be a positive number
InferType<typeof schema> // [string, number] | undefined
tuples have no default casting behavior.
Define an object schema. Options passed into isValid are also passed to child schemas.
Inherits from Schema.
yup.object({
name: string().required(),
age: number().required().positive().integer(),
email: string().email(),
website: string().url(),
});
object schema do not have any default transforms applied.
Object schema come with a default value already set, which "builds" out the object shape, a sets any defaults for fields:
const schema = object({
name: string().default(''),
});
schema.default(); // -> { name: '' }
This may be a bit surprising, but is usually helpful since it allows large, nested schema to create default values that fill out the whole shape and not just the root object. There is one gotcha! though. For nested object schema that are optional but include non optional fields may fail in unexpected ways:
const schema = object({
id: string().required(),
names: object({
first: string().required(),
}),
});
schema.isValid({ id: 1 }); // false! names.first is required
This is because yup casts the input object before running validation which will produce:
{ id: '1', names: { first: undefined }}
During the validation phase names exists, and is validated, finding names.first missing.
If you wish to avoid this behavior do one of the following:
names.default(undefined)names.nullable().default(null)object.shape(fields: object, noSortEdges?: Array<[string, string]>): SchemaDefine the keys of the object and the schemas for said keys.
Note that you can chain shape method, which acts like Object.assign.
object({
a: string(),
b: number(),
}).shape({
b: string(),
c: number(),
});
would be exactly the same as:
object({
a: string(),
b: string(),
c: number(),
});
object.json(): thisAttempt to parse input string values as JSON using JSON.parse.
object.concat(schemaB: ObjectSchema): ObjectSchemaCreates a object schema, by applying all settings and fields from schemaB to the base, producing a new schema.
The object shape is shallowly merged with common fields from schemaB taking precedence over the base
fields.
object.pick(keys: string[]): SchemaCreate a new schema from a subset of the original's fields.
const person = object({
age: number().default(30).required(),
name: string().default('pat').required(),
color: string().default('red').required(),
});
const nameAndAge = person.pick(['name', 'age']);
nameAndAge.getDefault(); // => { age: 30, name: 'pat'}
object.omit(keys: string[]): SchemaCreate a new schema with fields omitted.
const person = object({
age: number().default(30).required(),
name: string().default('pat').required(),
color: string().default('red').required(),
});
const nameAndAge = person.omit(['color']);
nameAndAge.getDefault(); // => { age: 30, name: 'pat'}
object.from(fromKey: string, toKey: string, alias: boolean = false): thisTransforms the specified key to a new key. If alias is true then the old key will be left.
let schema = object({
myProp: mixed(),
Other: mixed(),
})
.from('prop', 'myProp')
.from('other', 'Other', true);
schema.cast({ prop: 5, other: 6 }); // => { myProp: 5, other: 6, Other: 6 }
object.noUnknown(onlyKnownKeys: boolean = true, message?: string | function): SchemaValidate that the object value only contains keys specified in shape, pass false as the first
argument to disable the check. Restricting keys to known, also enables stripUnknown option, when not in strict mode.
object.camelCase(): SchemaTransforms all object keys to camelCase
object.constantCase(): SchemaTransforms all object keys to CONSTANT_CASE.
FAQs
Dead simple Object schema validation
We found that yup 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.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
A malicious npm package disguised as a WhatsApp client is exploiting authentication flows with a remote kill switch to exfiltrate data and destroy files.
Security News
PyPI now supports digital attestations, enhancing security and trust by allowing package maintainers to verify the authenticity of Python packages.
Security News
GitHub removed 27 malicious pull requests attempting to inject harmful code across multiple open source repositories, in another round of low-effort attacks.