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Dead simple Object schema validation

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Quick Overview

Yup is a JavaScript schema builder for value parsing and validation. It provides a simple and expressive way to define object schemas and validate data against them. Yup is commonly used in form validation scenarios and can be integrated with popular form libraries like Formik.

Pros

  • Easy to use and intuitive API
  • Supports both synchronous and asynchronous validation
  • Extensible with custom validation methods
  • TypeScript support for improved type safety

Cons

  • Performance can be slower compared to simpler validation libraries
  • Limited built-in localization support
  • Steeper learning curve for complex validation scenarios
  • Larger bundle size compared to more lightweight alternatives

Code Examples

  1. Basic schema definition and validation:
import * as Yup from 'yup';

const schema = Yup.object().shape({
  name: Yup.string().required('Name is required'),
  age: Yup.number().positive().integer().required('Age is required'),
  email: Yup.string().email('Invalid email').required('Email is required'),
});

const data = { name: 'John Doe', age: 30, email: 'john@example.com' };
schema.validate(data)
  .then(() => console.log('Valid'))
  .catch(error => console.log('Invalid:', error.errors));
  1. Custom validation method:
import * as Yup from 'yup';

Yup.addMethod(Yup.string, 'customFormat', function(regex, message) {
  return this.test('format', message, function(value) {
    return regex.test(value);
  });
});

const schema = Yup.object().shape({
  phone: Yup.string().customFormat(/^\d{3}-\d{3}-\d{4}$/, 'Invalid phone format'),
});
  1. Conditional validation:
import * as Yup from 'yup';

const schema = Yup.object().shape({
  isBusiness: Yup.boolean(),
  businessName: Yup.string().when('isBusiness', {
    is: true,
    then: Yup.string().required('Business name is required'),
    otherwise: Yup.string(),
  }),
});

Getting Started

To start using Yup in your project, follow these steps:

  1. Install Yup:
npm install yup
  1. Import and use Yup in your code:
import * as Yup from 'yup';

const schema = Yup.object().shape({
  username: Yup.string().required('Username is required'),
  password: Yup.string().min(8, 'Password must be at least 8 characters').required('Password is required'),
});

const data = { username: 'user123', password: 'securepass' };
schema.validate(data)
  .then(() => console.log('Validation successful'))
  .catch(error => console.log('Validation failed:', error.errors));

This basic example demonstrates how to define a schema, create validation rules, and validate data against the schema.

Competitor Comparisons

colinhacks logo

zod

33,503

TypeScript-first schema validation with static type inference

Pros of Zod

  • TypeScript-first approach with strong type inference
  • More extensive validation features, including object merging and parsing
  • Better performance in large-scale applications

Cons of Zod

  • Steeper learning curve for developers new to TypeScript
  • Larger bundle size compared to Yup

Code Comparison

Zod:

import { z } from "zod";

const UserSchema = z.object({
  name: z.string(),
  age: z.number().min(18),
});

Yup:

import * as Yup from "yup";

const UserSchema = Yup.object().shape({
  name: Yup.string().required(),
  age: Yup.number().min(18).required(),
});

Both Zod and Yup are popular schema validation libraries, but they have different strengths. Zod is designed with TypeScript in mind, offering strong type inference and more advanced validation features. It performs better in large-scale applications but has a steeper learning curve for those new to TypeScript.

Yup, on the other hand, is more straightforward to use and has a smaller bundle size. It's a good choice for simpler projects or when working with JavaScript. However, it lacks some of the more advanced features and type inference capabilities of Zod.

The code comparison shows that both libraries have similar syntax for defining schemas, but Zod's TypeScript-first approach is evident in its more concise and type-safe code.

ajv-validator logo

ajv

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The fastest JSON schema Validator. Supports JSON Schema draft-04/06/07/2019-09/2020-12 and JSON Type Definition (RFC8927)

Pros of ajv

  • Faster performance, especially for large datasets
  • More comprehensive JSON Schema support
  • Supports custom keywords for extended validation

Cons of ajv

  • Steeper learning curve due to more complex API
  • Less intuitive syntax for defining schemas
  • Primarily focused on JSON Schema, less flexible for custom validation scenarios

Code Comparison

ajv:

const Ajv = require('ajv');
const ajv = new Ajv();

const schema = {
  type: 'object',
  properties: {
    name: { type: 'string' },
    age: { type: 'number', minimum: 18 }
  },
  required: ['name', 'age']
};

const validate = ajv.compile(schema);

yup:

import * as Yup from 'yup';

const schema = Yup.object().shape({
  name: Yup.string().required(),
  age: Yup.number().min(18).required()
});

await schema.validate(data);

ajv uses JSON Schema syntax, which can be more verbose but offers greater flexibility. yup provides a more concise and chainable API, making it easier to read and write for simpler validation scenarios. ajv excels in performance and JSON Schema compliance, while yup offers a more user-friendly experience for JavaScript developers.

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superstruct

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A simple and composable way to validate data in JavaScript (and TypeScript).

Pros of Superstruct

  • More flexible and customizable validation rules
  • Better TypeScript integration with automatic type inference
  • Smaller bundle size and faster performance

Cons of Superstruct

  • Less extensive built-in validation functions compared to Yup
  • Steeper learning curve for complex validations
  • Less mature ecosystem and community support

Code Comparison

Yup:

const schema = yup.object().shape({
  name: yup.string().required(),
  age: yup.number().positive().integer().required(),
});

Superstruct:

const User = struct({
  name: 'string',
  age: 'number',
});

Both libraries offer schema-based validation, but Superstruct's syntax is more concise. Yup provides more built-in validators out of the box, while Superstruct focuses on flexibility and customization.

Superstruct shines in TypeScript environments, automatically inferring types from schemas. It also offers better performance and a smaller footprint, making it suitable for projects where bundle size is a concern.

However, Yup's extensive set of built-in validators and more mature ecosystem make it easier to get started with common validation scenarios. It also has a larger community, which can be beneficial for finding solutions to specific problems.

Choose Superstruct for TypeScript projects or when you need highly customized validations. Opt for Yup when you want a more straightforward API with a wide range of pre-built validators.

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joi

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The most powerful data validation library for JS

Pros of Joi

  • More extensive and feature-rich validation library
  • Better suited for complex server-side validations
  • Supports custom error messages and localization out of the box

Cons of Joi

  • Larger bundle size, which can impact performance in browser environments
  • Steeper learning curve due to its extensive API and features
  • Less TypeScript-friendly compared to Yup

Code Comparison

Joi:

const Joi = require('joi');

const schema = Joi.object({
  username: Joi.string().alphanum().min(3).max(30).required(),
  email: Joi.string().email().required()
});

Yup:

import * as Yup from 'yup';

const schema = Yup.object().shape({
  username: Yup.string().min(3).max(30).required(),
  email: Yup.string().email().required()
});

Both libraries offer similar functionality for basic validations, but Joi provides more built-in validators and options for complex scenarios. Yup, on the other hand, has a more straightforward API and better TypeScript support, making it easier to use in frontend projects. While Joi excels in server-side validations, Yup is often preferred for client-side validations due to its smaller size and simpler API.

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class-validator

10,945

Decorator-based property validation for classes.

Pros of class-validator

  • Decorator-based validation, which integrates well with TypeScript classes
  • Supports both sync and async validation
  • Extensive built-in validation decorators

Cons of class-validator

  • Limited support for custom error messages compared to Yup
  • Requires TypeScript and decorators, which may not be suitable for all projects
  • Less flexible schema definition compared to Yup's chainable API

Code Comparison

class-validator:

import { IsString, MinLength, IsEmail } from 'class-validator';

class User {
  @IsString()
  @MinLength(2)
  name: string;

  @IsEmail()
  email: string;
}

Yup:

import * as Yup from 'yup';

const userSchema = Yup.object().shape({
  name: Yup.string().min(2).required(),
  email: Yup.string().email().required(),
});

Summary

class-validator is well-suited for TypeScript projects using decorators, offering a wide range of built-in validators. It excels in object-oriented validation scenarios. Yup, on the other hand, provides a more flexible and chainable API for schema definition, making it easier to create complex validation rules and custom error messages. Yup is more versatile and can be used in both JavaScript and TypeScript projects without requiring decorators.

gcanti logo

io-ts

6,692

Runtime type system for IO decoding/encoding

Pros of io-ts

  • Strong TypeScript integration with compile-time type inference
  • Supports complex types like unions, intersections, and recursive types
  • Provides runtime type checking and validation

Cons of io-ts

  • Steeper learning curve due to its functional programming approach
  • Less straightforward syntax for defining schemas compared to Yup
  • Smaller community and ecosystem compared to Yup

Code Comparison

io-ts:

import * as t from 'io-ts'

const User = t.type({
  name: t.string,
  age: t.number
})

const result = User.decode({ name: 'John', age: 30 })

Yup:

import * as Yup from 'yup'

const schema = Yup.object().shape({
  name: Yup.string().required(),
  age: Yup.number().required().positive()
})

const result = schema.validate({ name: 'John', age: 30 })

io-ts offers a more type-driven approach, leveraging TypeScript's type system, while Yup provides a more intuitive API for schema definition and validation. io-ts is better suited for projects heavily invested in TypeScript and functional programming, whereas Yup is more accessible for general-purpose validation tasks.

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README

Yup

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:

  • Concise yet expressive schema interface, equipped to model simple to complex data models
  • Powerful TypeScript support. Infer static types from schema, or ensure schema correctly implement a type
  • Built-in async validation support. Model server-side and client-side validation equally well
  • Extensible: add your own type-safe methods and schema
  • Rich error details, make debugging a breeze

Getting Started

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
let 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
let 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"
let parsedUser = await userSchema.validate(
  {
    name: 'jimmy',
    age: '24',
  },
  { strict: true },
);

Table of Contents

Schema basics

Schema 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

Parsing: Transforms

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.

let num = number().cast('1'); // 1

let obj = object({
  firstName: string().lowercase().trim(),
})
  .json()
  .camelCase()
  .cast('{"first_name": "jAnE "}'); // { firstName: 'jane' }

Custom transforms can be added

let 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.

Validation: Tests

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

let 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, value in a custom test is guaranteed to be the correct type (in this case an optional string). It still may be undefined or null depending on your schema in those cases, you may want to return true for absent values unless your transform makes presence related assertions. The test option skipAbsent will do this for you if set.

Customizing errors

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.

let 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' })

Composition and Reuse

Schema are immutable, each method call returns a new schema object. Reuse and pass them around without fear of mutating another instance.

let optionalString = string().optional();

let definedString = optionalString.defined();

let value = undefined;
optionalString.isValid(value); // true
definedString.isValid(value); // false

TypeScript integration

Yup schema produce static TypeScript interfaces. Use InferType to extract that interface:

import * as yup from 'yup';

let 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
}

Schema defaults

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';

let value: string = string().default('hi').validate(undefined);

// vs

let value: string | undefined = string().validate(undefined);

Ensuring a schema matches an existing type

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
let 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'."
let badSchema: ObjectSchema<Person> = object({
  name: number(),
});

Extending built-in schema with new methods

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~~~~'

TypeScript configuration

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.

Error message customization

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']
}

localization and i18n

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));
}

API

yup

The 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): Schema

For 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): void

Adds 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 }): Ref

Creates 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): Lazy

Creates 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 messages
  • inner: 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.

Schema

Schema 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(): Schema

Creates a deep copy of the schema. Clone is used internally to return a new schema with every schema state change.

Schema.label(label: string): Schema

Overrides the key name which is used in error messages.

Schema.meta(metadata: SchemaMetadata): Schema

Adds 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): SchemaDescription

Collects schema details (like meta, labels, and active tests) into a serializable description object.

let schema = object({
  name: string().required(),
});

let 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): Schema

Creates 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 value here 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): boolean

Synchronously 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): Schema

Sets the strict option to true. Strict schemas skip coercion and transformation attempts, validating the value "as is".

Schema.strip(enabled: boolean = true): Schema

Marks 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): void

First 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): Schema

Sets 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): Any

Retrieve 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): Schema

Indicates that null is a valid value for the schema. Without nullable() null is treated as a different type and will fail Schema.isType() checks.

let schema = number().nullable();

schema.cast(null); // null

InferType<typeof schema>; // number | null

Schema.nonNullable(message?: string | function): Schema

The opposite of nullable, removes null from valid type values for the schema. Schema are non nullable by default.

let schema = number().nonNullable();

schema.cast(null); // TypeError

InferType<typeof schema>; // number

Schema.defined(): Schema

Require a value for the schema. All field values apart from undefined meet this requirement.

let schema = string().defined();

schema.cast(undefined); // TypeError

InferType<typeof schema>; // string

Schema.optional(): Schema

The opposite of defined() allows undefined values for the given type.

let schema = string().optional();

schema.cast(undefined); // undefined

InferType<typeof schema>; // string | undefined

Schema.required(message?: string | function): Schema

Mark 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(): Schema

Mark the schema as not required. This is a shortcut for schema.nullable().optional();

Schema.typeError(message: string): Schema

Define 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: equals

Only 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): Schema

Adjust 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): Schema

Adds 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 validation
  • testContext.schema: the resolved schema object that the test is running against.
  • testContext.options: the options object that validate() or isValid() was called with
  • testContext.parent: in the case of nested schema, this is the value of the parent object
  • testContext.originalValue: the original value that is being tested
  • testContext.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): Schema

Alternative 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): Schema

Adds 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('');
  });
};

mixed

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

string

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): Schema

The same as the mixed() schema required, except that empty strings are also considered 'missing' values.

string.length(limit: number | Ref, message?: string | function): Schema

Set 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): Schema

Set 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): Schema

Set 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): Schema

Provide 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 }): Schema

An 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): Schema

Validates 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): Schema

Validates the value as a valid URL via a regex.

string.uuid(message?: string | function): Schema

Validates 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(): Schema

Transforms undefined and null values to an empty string along with setting the default to an empty string.

string.trim(message?: string | function): Schema

Transforms 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): Schema

Transforms the string value to lowercase. If strict() is set it will only validate that the value is lowercase.

string.uppercase(message?: string | function): Schema

Transforms the string value to uppercase. If strict() is set it will only validate that the value is uppercase.

number

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): Schema

Set the minimum value allowed. The ${min} interpolation can be used in the message argument.

number.max(limit: number | Ref, message?: string | function): Schema

Set the maximum value allowed. The ${max} interpolation can be used in the message argument.

number.lessThan(max: number | Ref, message?: string | function): Schema

Value must be less than max. The ${less} interpolation can be used in the message argument.

number.moreThan(min: number | Ref, message?: string | function): Schema

Value must be strictly greater than min. The ${more} interpolation can be used in the message argument.

number.positive(message?: string | function): Schema

Value must be a positive number.

number.negative(message?: string | function): Schema

Value must be a negative number.

number.integer(message?: string | function): Schema

Validates that a number is an integer.

number.truncate(): Schema

Transformation 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'): Schema

Adjusts the value via the specified method of Math (defaults to 'round').

boolean

Define a boolean schema. Inherits from Schema.

let schema = yup.boolean();

await schema.isValid(true); // => true

date

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 Date object, use .datetime() instead.

Failed casts return an invalid Date.

date.min(limit: Date | string | Ref, message?: string | function): Schema

Set 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): Schema

Set 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.

array

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): this

Specify the schema of array elements. of() is optional and when omitted the array schema will not validate its contents.

array.json(): this

Attempt to parse input string values as JSON using JSON.parse.

array.length(length: number | Ref, message?: string | function): this

Set 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): this

Set 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): this

Set a maximum length limit for the array. The ${max} interpolation can be used in the message argument.

array.ensure(): this

Ensures 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): Schema

Removes 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]

tuple

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.

object

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 defaults

Object schema come with a default value already set, which "builds" out the object shape, a sets any defaults for fields:

let 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:

let 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:

  • Set the nested default to undefined: names.default(undefined)
  • mark it nullable and default to null: names.nullable().default(null)

object.shape(fields: object, noSortEdges?: Array<[string, string]>): Schema

Define 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(): this

Attempt to parse input string values as JSON using JSON.parse.

object.concat(schemaB: ObjectSchema): ObjectSchema

Creates 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[]): Schema

Create a new schema from a subset of the original's fields.

let person = object({
  age: number().default(30).required(),
  name: string().default('pat').required(),
  color: string().default('red').required(),
});

let nameAndAge = person.pick(['name', 'age']);
nameAndAge.getDefault(); // => { age: 30, name: 'pat'}

object.omit(keys: string[]): Schema

Create a new schema with fields omitted.

let person = object({
  age: number().default(30).required(),
  name: string().default('pat').required(),
  color: string().default('red').required(),
});

let nameAndAge = person.omit(['color']);
nameAndAge.getDefault(); // => { age: 30, name: 'pat'}

object.from(fromKey: string, toKey: string, alias: boolean = false): this

Transforms 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): Schema

Validate 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(): Schema

Transforms all object keys to camelCase

object.constantCase(): Schema

Transforms all object keys to CONSTANT_CASE.

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