Type Driven Schema Validator.
- Lightweight. Much smaller than other validation libraries.
- Easy to use. You can use any schema as a function or constructor directly.
- Powerful. Schemastery supports some advanced types such as
union
,intersect
andtransform
. - Extensible. You can create your own schema types via
Schema.extend()
. - Serializable. Schema objects can be serialized into JSON and then be hydrated in another environment.
const Schema = require('schemastery')
const validate = Schema.number().default(10)
validate(0) // 0
validate(null) // 10
validate('') // TypeError
import Schema from 'schemastery'
interface Config {
foo: Record<string, string>
bar: string[]
}
const Config = Schema.object({
foo: Schema.dict(Schema.string()).default({}),
bar: Schema.array(Schema.string()).default([]),
})
// config is an instance of Config
// in this case, that is { foo: {}, bar: [] }
const config = new Config()
Assert that the value is of any type.
const validate = Schema.any()
validate() // undefined
validate(0) // 0
validate({}) // {}
Assert that the value is nullable.
const validate = Schema.never()
validate() // undefined
validate(0) // TypeError
validate({}) // TypeError
Assert that the value is equal to the given constant.
const validate = Schema.const(10)
validate(10) // 10
validate(0) // TypeError
Assert that the value is a number.
const validate = Schema.number()
validate() // undefined
validate(1) // 1
validate('') // TypeError
Assert that the value is a string.
const validate = Schema.string()
validate() // undefined
validate(0) // TypeError
validate('foo') // 'foo'
Assert that the value is a boolean.
const validate = Schema.boolean()
validate() // undefined
validate(0) // TypeError
validate(true) // true
Assert that the value is an instance of the given constructor.
const validate = Schema.is(RegExp)
validate() // undefined
validate(/foo/) // /foo/
validate('foo') // TypeError
Assert that the value is an array of inner
. The default value will be []
if not specified.
const validate = Schema.array(Schema.number())
validate() // []
validate(0) // TypeError
validate([0, 1]) // [0, 1]
validate([0, '1']) // TypeError
Assert that the value is a dictionary of inner
. The default value will be {}
if not specified.
const validate = Schema.dict(Schema.number())
validate() // {}
validate(0) // TypeError
validate({ a: 0, b: 1 }) // { a: 0, b: 1 }
validate({ a: 0, b: '1' }) // TypeError
Assert that the value is a tuple whose each element is of corresponding subtype. The default value will be []
if not specified.
const validate = Schema.tuple([
Schema.number(),
Schema.string(),
])
validate() // []
validate([0]) // { a: 0 }
validate([0, 1]) // TypeError
validate([0, '1']) // [0, '1']
Assert that the value is an object whose each property is of corresponding subtype. The default value will be {}
if not specified.
const validate = Schema.object({
a: Schema.number(),
b: Schema.string(),
})
validate() // {}
validate({ a: 0 }) // { a: 0 }
validate({ a: 0, b: 1 }) // TypeError
validate({ a: 0, b: '1' }) // { a: 0, b: '1' }
Assert that the value is one of the specified types.
const validate = Schema.union([
Schema.number(),
Schema.string(),
])
validate() // undefined
validate(0) // 0
validate('1') // '1'
validate(true) // TypeError
Assert that the value should match each specified type.
const validate = Schema.intersect([
Schema.object({ a: Schema.string().required() }),
Schema.object({ b: Schema.number().default(0) }),
])
validate() // TypeError
validate({ a: '' }) // { a: '', b: 0 }
validate({ a: '', b: 1 }) // { a: '', b: 1 }
validate({ a: '', b: '2' }) // TypeError
Assert that the value is of the specified subtype and then transformed by callback
.
const validate = Schema.transform(Schema.number().default(0), n => n + 1)
validate() // 1
validate('0') // TypeError
validate(10) // 11
Note: default
and required
are mutually exclusive.
Assert that the value is not nullable.
Set the fallback value when nullable.
Set the description of the schema.
Some shorthand syntax is available for inner types.
undefined
->Schema.any()
String
->Schema.string()
Number
->Schema.number()
Boolean
->Schema.boolean()
1
->Schema.const(1)
(only for primitive types)Date
->Schema.is(Date)
Schema.array(String) // Schema.array(Schema.string())
Schema.dict(RegExp) // Schema.dict(Schema.is(RegExp))
Schema.union([1, 2]) // Schema.union([Schema.const(1), Schema.const(2)])
You can also use Schema.from()
to get the inferred schema from a shorthand value.
Schema.from() // Schema.any()
Schema.from(Date) // Schema.is(Date)
Schema.from('foo') // Schema.const('foo')
Here are some examples which demonstrate how to define advanced types.
const Enum = Schema.union(['red', 'blue'])
Enum('red') // 'red'
Enum('blue') // 'blue'
Enum('green') // TypeError
const ToString = Schema.transform(Schema.any(), v => String(v))
ToString('') // ''
ToString(0) // '0'
ToString({}) // '{}'
const Listable = Schema.union([
Schema.array(Number),
Schema.transform(Number, n => [n]),
]).default([])
Listable() // []
Listable(0) // [0]
Listable([1, 2]) // [1, 2]
const Config = Schema.dict(Number, Schema.union([
'foo',
Schema.transform('bar', () => 'foo'),
]))
Config({ foo: 1 }) // { foo: 1 }
Config({ bar: 2 }) // { foo: 2 }
Config({ bar: '3' }) // TypeError
const schema1 = Schema.object({
foo: Schema.string(),
bar: Schema.number(),
})
// should have the same effect as schema1
const schema2 = new Schema(JSON.parse(JSON.stringify(schema1)))