@arilotter/myzod
Advanced tools
Schema Validation with typescript type inference.
Major Shout-out to zod for the inspiration.
Myzod tries to emulate the typescript type system as much as possible and is even in some ways a little stricter. The goal is that writing a schema feels the same as defining a typescript type, with equivalent & and | operators, and well known Generic types like Record, Pick and Omit. On top of that myzod aims to offer validation within the schemas for such things as number ranges, string patterns and lengths to help enforce business logic.
The resulting package has a similar api to zod with a little bit of inspiration from joi.
The goal is to write schemas from which the type of a successfully parsed value can be inferred. With myzod typescript types and validation logic no longer need to be maintained separately.
When parsing equivalent simple object (with nesting) schemas for myzod, zod and joi, on my machine Linux Ubuntu 18.04 running NodeJS 13.X, the results are as such:
objects parsed per second:
zod: 51861joi: 194325myzod: 1288659myzod vs zod: ~25 X Speedup
myzod vs joi: ~6 X Speedup
npm install --save myzod
Myzod is used by creating a schema, extracting the type by inferring it, and finally by parsing javascript values.
import myzod, { Infer } from 'myzod';
const personSchema = myzod.object({
id: myzod.number(),
name: myzod.string().pattern(/^[A-Z]/),
age: myzod.number().min(0),
birthdate: myzod.number().or(myzod.string()),
employed: myzod.boolean(),
friendIds: myzod.array(myzod.number()).nullable()
});
type Person = Infer<typeof personSchema>;
const person: Person = personSchema.parse({ ... });
Type Root
Primitive Types
Reference Types
Logical Types
Recursive Schemas
All myzod schemas extend the generic myzod.Type class, and as such inherit these methods:
Takes an unknown value, and returns it typed if passed validation. Otherwise throws a myzod.ValidationError
parse(value: unknown): T
Takes an unknown value and returns a result which will either be the parsed value or an instance of ValidationError. This api is useful if you do not want to throw exceptions.
const result = schema.try(data);
if (result instanceof myzod.ValidationError) {
// handle Error
} else {
// result is of type: myzod.Infer<typeof schema>
}
Shorthand for creating intersection types of two schemas.
const nameSchema = myzod.object({ name: myzod.string() });
const ageSchema = myzod.object({ age: myzod.number() });
const personSchema = nameSchema.and(ageSchema); // Same as ageSchema.and(nameSchema);
type Person = Infer<typeof personSchema>; // => { name: string; age: number; }
Shorthand for creating union types of two schemas.
const stringOrBoolSchema = myzod.string().or(myzod.boolean());
type StringOrUndefined = Infer<typeof stringOrBoolSchema>; // => string | boolean
Returns a new schema which is a wrapped OptionalType of the current schema.
const optionalStringSchema = myzod.string().optional(); // => OptionalType<StringType>
type StringOrUndefined = Infer<typeof optionalStringSchema>; // => string | undefined
It is possible to unwrap an optional schema via a call to require:
const optionalSchema = myzod.string().optional();
const schema = optionalSchema.require();
Returns a new schema which is a wrapped NullableType of the current schema.
const nullableStringSchema = myzod.string().nullable(); // => NullableType<StringType>
type StringOrUndefined = Infer<typeof nullableStringSchema>; // => string | null
It is possible to unwrap an optional schema via a call to require:
const optionalSchema = myzod.string().nullable();
const schema = optionalSchema.require();
Returns a new generic schema to the mapped type. Useful for transforming validated input into a new type on parse.
const ObjectIDSchema = myzod
.string()
.withPredicate(ObjectId.isValid, 'must be an object ID')
.map(value => new ObjectId(value));
// Infer<ObjectIDSchema> === ObjectId
const id = ObjectIDSchema.parse('507c7f79bcf86cd7994f6c0e');
id instanceof ObjectId; // true
const id2 = ObjectIDSchema.parse('some string'); // Throws VaidationError with message "must be an object ID"'
options:
number - min length of stringnumber - max length of stringRegExp - regular expression string must matchstring[] - list of valid stringsPredicate<string> - custom predicates to apply to string valuemethods:
min(value: number, errMsg?: string) => StringTypemax(value: number, errMsg?: string) => StringTypepattern(value: RegExp, errMsg?: string) => StringTypevalid(list: string[], errMsg?: string) => StringTypewithPredicate(fn: (val: string) => boolean), errMsg?: string }default(value: string | (() => string)) => StringTypeoptions can be passed as an option object or chained from schema.
myzod.string({ min: 3, max: 10, pattern: /^hey/ });
// same as
myzod.string().min(3).max(10).pattern(/^hey/);
The valid options lets you validate against a set of strings.
const helloworld = myzod.string().valid(['hello', 'world']);
typeof HelloWorld = myzod.Infer<typeof helloworld>; // => string
if however you want the strings to be typed used the literals helper function:
const helloworld = myzod.literals('hello', 'world');
type HelloWorld = myzod.Infer<typeof helloworld>; // => 'hello' | 'world'
Myzod is not interested in reimplementing all possible string validations, ie isUUID, isEmail, isAlphaNumeric, etc. The myzod string validation can be easily extended via the withPredicate API.
const uuidSchema = myzod.string().withPredicate(validator.isUUID, 'expected string to be uuid');
type UUID = Infer<typeof uuidSchema>; // => string
uuidSchema.parse('hello world'); // Throws ValidationError with message 'expected string to be uuid'
// note that if predicate function throws an error that message will be used instead
Note that you can register multiple predicates, and that each invocation will create a new schema:
const greeting = myzod.string().withPredicate(value => value.startsWith('hello'), 'string must start with hello');
const evenGreeting = greeting.withPredicate(value => value.length % 2 === 0, 'string must have even length');
const oddGreeting = greeting.withPredicate(value => value.length % 2 === 1, 'string must have odd length');
You can use default values or functions to create default values for myzod string schemas.
const uuidSchema = z.string().default(() => uuidv4());
const val = uuidSchema.parse(undefined); // val is a valid uuid constructed by uuidv4()
uuid.parse(null); // throws an error
options:
number - min value for numbernumber - max value for numberboolean - when true will attempt to coerce strings to numbers. default falsemethods:
min(value: number, errMsg?: string) => NumberTypemax(value: number, errMsg?: string) => NumberTypewithPredicate(fn: (value: number) => boolean, errMsg?: string) => NumberTypecoerce(flag?: boolean) => NumberTypedefault(value: number | (() => number)) => NumberTypeoptions can be passed as an option object or chained from schema.
myzod.number({ min: 0, max: 10 });
// Same as:
myzod.number().min(0).max(10);
Coercion example:
const schema = myzod.number().coerce(); // same as myzod.number({ coerce: true });
const value = schema.parse('42');
assert.ok(typeof value === 'number'); // succeeds
assert.equal(value, 42); // succeeds
options:
number - min value for numbernumber - max value for numbermethods:
min(value: number | bigint) => BigIntTypemax(value: number | bigint) => BigIntTypewithPredicate(fn: (value: bigint) => boolean, errMsg?: string) => BigIntTypeoptions can be passed as an option object or chained from schema.
myzod.bigint({ min: 0, max: 10 });
// Same as:
myzod.bigint().min(0).max(10);
const integer = myzod.bigint();
type Integer = myzod.Infer<typeof integer>; // => bigint
The bigint schema automatically coerces bigint interpretable numbers and strings into bigint values.
const schema = myzod.bigint();
const value = schema.parse('42');
assert.ok(typeof value === 'bigint'); // succeeds
assert.equal(value, 42n); // succeeds
methods:
default(value: boolean | (() => boolean)) => BooleanTypemyzod.boolean();
myzod.undefined();
methods:
default() => NullTypemyzod.null();
methods:
default() => LiteralTypeJust as in typescript we can type things using literals
const schema = myzod.literal('Value');
type Val = Infer<typeof schema>; // => 'Value'
Sometimes we do not want to go all out and create an enum to represent a combination of literals. Myzod offers a utility function to avoid have to "or" multiple times over many literalTypes.
const schema = myzod.literals('red', 'green', 'blue');
type Schema = myzod.Infer<typeof schema>; // => 'red' | 'green' | 'blue'
// Other equivalent ways of creating the same schema:
const schema = myzod.literal('red').or(myzod.literal('green')).or(myzod.literal('blue'));
const schema = myzod.union([myzod.literal('red'), myzod.literal('green'), myzod.literal('blue')]);
methods:
default(value: any | (() => any)) => UnknownTypemyzod.unknown();
The unknown schema does nothing when parsing by itself. However it is useful to require a key to be present inside an object schema when we don't know or don't care about the type.
const schema = myzod.object({ unknownYetRequiredField: myzod.unknown() });
type Schema = Infer<typeof schema>; // => { unknownYetRequiredField: unknown }
schema.parse({}); // throws a ValidationError
schema.parse({ unknownYetRequiredField: 'hello' }); // succeeds
options:
boolean - allows for object with keys not specified in expected shape to succeed parsing, default falseboolean - suppress the path to the invalid key in thrown validationErrors. This option should stay false for most cases but is used internally to generate appropriate messages when validating nested objects. default falsemyzod.object is the way to construct arbitrary object schemas.
function object(shape: { [key: string]: Type<T> }, opts?: options);
examples:
const strictEmptyObjSchema = myzod.object({});
const emptyObjSchema = myzod.object({}, { allowUnknown: true });
// Both Schemas infer the same type
type Empty = Infer<typeof emptyObjSchema>; // => {}
type StrictEmpty = Infer<typeof strictEmptyObjSchema>; // => {}
emptyObjSchema.parse({ key: 'value' }); // => succeeds
strictEmptyObjSchema.parse({ key: 'value' }); // => throws ValidationError because not expected key: "key"
const personSchema = myzod.object({
name: myzod.string(),
});
const shape = personSchema.shape(); // => returns { name: myzod.string() }
A new schema can be build via fluent syntax to allow for unknown keys
const schema = z.object({ name: z.string(), age: z.number() }).allowUnknownKeys();
const value = schema.try({ name: 'myzod', age: 1, cool: true }); // value is { name: 'myzod', age: 1 }
You can add predicate functions to object schemas. Note that these predicate functions will not be kept around for schemas produces from object.pick/omit/partial as they predicate function signatures need to change for those signatures.
const registrationSchema = myzod
.object({
email: z.string().withPredicate(validator.isEmail, 'expected email'),
password: z.string().min(8),
confirmedPassword: z.string(),
})
.withPredicate(value => value.password === value.confirmedPassword, 'password and confirmed do not match');
You can extract the shape from an ObjectType.
const personSchema = myzod.object({
name: myzod.string(),
});
const shape = personSchema.shape(); // => returns { name: myzod.string() }
The Object type has utility methods pick, omit, and partial for creating new ObjectType schemas based on the current instance. Note once more that predicates do not carry over from base schema.
const profileSchema = myzod.object({
id: myzod.string().predicate(validator.isUUID),
name: myzod.string().pattern(/[A-Z]\w+/)
age: myzod.number().min(0),
});
type Profile = myzod.Infer<typeof profileSchema>; // => { id: string; name: string; age: number }
const putProfileSchema = profileSchema.pick(['name','age']); // Same as profileSchema.omit(['id']);
type PutProfile = myzod.Infer<typeof putProfileSchema>; // => { name: string; age: number }
const patchProfileSchema = putProfileSchema.partial();
type PatchProfile = myzod.Infer<typeof patchProfileSchema>; // => { name?: string; age?: number }
Partial accepts an options object to allow for deeply nested partials:
const schema = myzod
.object({
name: myzod.string(),
birthday: myzod.object({
year: myzod.number(),
month: myzod.number().min(1).max(12),
date: myzod.number().min(1).max(31),
}),
})
.partial({ deep: true });
type DeeplyPartialSchema = myzod.Infer<typeof schema>; // { name?: string; birthday?: { year?: number; month?: number; date?: number; } }
With the default function you can set a default value for the object schema which will be used when trying to parse undefined:
const personSchema = myzod
.object({ name: myzod.string(), lastName: myzod.string() })
.default({ name: 'John', lastName: 'Doe' });
const person = personSchema.parse(undefined); // => { name: 'John', lastName: 'Doe' }
Object schemas have an option to collect all validation errors instead of the default throwing on first error. This is useful for form validation, but does incur a slight performance hit.
const personSchema = myzod.object({ name: myzod.string(), lastName: myzod.string() }).collectErrors();
personSchema.parse({ name: 1, lastName: 2 });
// throws an ValidationError with message:
err.message = `
error parsing object at path: "name" - expected type to be string but got number
error parsing object at path: "lastName" - expected type to be string but got number
`;
err.collectedErrors = {
name: ValidationError,
lastName: ValidationError,
};
In the next section myzod goes over "records" which is the simple and idiomatic way in typescript of describing an object with solely a key signature. However you can use key signatures directly in your object schema definitions if you like using the myzod.keySignature symbol.
const scores = myzod.object({ [myzod.keySignature]: myzod.number() }); // same as: myzod.record(myzod.number());
type Scores = myzod.Infer<typeof scores>; // => { [x: string]: number }
The advantage of this approach is to mix statically known keys with a keysignature without intersecting records and objects.
The record function emulates as the equivalent typescript type: Record<string, T>.
const schema = myzod.record(myzod.string());
type Schema = Infer<typeof schema>; // => { [x: string] : string }
One primary use case of the record type is for creating schemas for objects with unknown keys that you want to have typed. This would be the equivalent of passing a pattern to joi. The way this is done in myzod is to intersect a recordSchema with a object schema.
const objSchema = myzod.object({
a: myzod.string(),
b: myzod.boolean(),
c: myzod.number(),
});
const recordSchema = myzod.record(zod.number());
const schema = objSchema.and(recordSchema);
type Schema = Infer<typeof schema>;
// Here Schema is the same as the following type definition:
type Schema = {
a: string;
b: boolean;
c: number;
[key: string]: number;
};
As a utility you can pick directly from a recordSchema and get an equivalent objectSchema:
const recordSchema = z.record(z.string());
type RecordType = z.Infer<typeof recordSchema>; // => { [x: string]: string }
const objSchema = recordSchema.pick(['a', 'b']);
type ObjType = z.Infer<typeof objSchema>; // => { a: string; b: string; }
As a utility for creating records whose values are by default optional, you can use the myzod.dictionary function.
const schema = myzod.dictionary(myzod.string());
// same as
const schema = myzod.record(myzod.string().optional());
type Schema = Infer<typeof schema>; // => { [key: string]: string | undefined }
// Note I have experienced issues with vscode type hints omitting the undefined union
// however when running tsc it evaluates Schema as the type above.
options:
number - the expected length of the arraynumber - the minimum length of the arraynumber - the maximum length of the arrayboolean - should the array be unique. default false(value: string) => T[] - function to coerce string representations to an arraymethods:
length(value: number, errMsg?: string) => ArrayType<T>min(value: number, errMsg?: string) => ArrayType<T>max(value: number, errMsg?: string) => ArrayType<T>unique() => ArrayType<T>withPredicate(fn: (value: T[]) => boolean, errMsg?: string) => ArrayType<T>default(value: T[] | (() => T[])) => ArrayType<T>coerce(fn: (value: string) => T[]) => ArrayType<T>Signature:
function array(schema: Type<T>, opts?: Options);
Example:
const schema = myzod.array(myzod.number()).unique();
type Schema = Infer<typeof schema>; // => string[]
schema.parse([1, 1, 2]); // => throws ValidationError
Myzod allows for string representations to be coerced to the array of your type via a coercion function. A common example is when parsing csv values.
const schema = myzod.array(myzod.string()).coerce((csv: string) => csv.split(','));
const result = schema.try('red,blue,green');
// result === ['red', 'blue', 'green'];
methods:
withPredicate(fn: (value: Infer<TupleType<T>>) => boolean, errMsg?: string) => TupleType<T>default(value: InferTupleType<T>) => TupleType<T>Tuples are similar to arrays but allow for mixed types of static length. Note that myzod does not support intersections of tuple types at this time.
const schema = myzod.tuple([myzod.string(), myzod.object({ key: myzod.boolean() }), myzod.array(myzod.number())]);
type Schema = Infer<typeof schema>; // => [string, { key: boolean; }, number[]];
methods:
default(value: Enum | (() => Enum)) => EnumTypeThe enum implementation differs greatly from the original zod implementation.
In zod you would create an enum schema by passing an array of litteral schemas.
I, however, did not like this since enums are literals they must by typed out in the source code regardless, and I prefer to use actual typescript enum values.
The cost of this approach is that I cannot statically check that you are passing an enum type to the zod.enum function. If you pass another value it won't make sense within the type system. Users beware.
enum Color {
red = 'red',
blue = 'blue',
green = 'green',
}
const colorSchema = zod.enum(Color);
Infer<typeof colorSchema> // => Color -- Redundant
const color = colorSchema.parse('red');
The enum schema provides a check method as a typeguard for enums.
const value: string = 'some string variable';
if (colorSchema.check(value)) {
// value's type is Color within this if block
}
The enum type also accepts an options object as a second parameter.
You can set coerce to 'lower' or 'upper' to ignore string casing when calling check or parse.
z.enum(Colors, { coerce: 'lower' });
const value: string = 'Red';
colorSchema.parse(value);
// parse will return a lowercased value
You can also set a default value in the options object.
z.enum(Colors, { defaultValue: 'red' });
methods:
withPredicate(fn: (value: Date) => boolean, errMsg?: string) => DateTypedefault(value: Date | (() => Date)) => DateTypethe myzod.date function creates a date schema. Values that will be successfully parsed by this schema are Javascript Date instances and valid string representations of dates. The returned parse Date will be an instance of Date.
const schema = myzod.date();
type Schema = myzod.Infer<typeof schema>; // => Date
const date = new Date();
schema.parse(date); // returns date
schema.parse(date.toISOString()); // returns a date instance equal to date
// WithPredicate example
const weekDay = myzod
.date()
.withPredicate(date => date.getUTCDate() !== 6 && date.getUTCDate() !== 0, 'expected weekday');
The myzod.union function accepts an arbitrary number of schemas and creates a union of their inferred types.
const schema = myzod.union([myzod.string(), myzod.array(myzod.string()), myzod.number()]);
type Schema = Infer<typeof schema>; // => string | string[] | number
The myzod.intersection takes two schemas as arguments and creates an intersection between their types.
const a = myzod.object({ a: myzod.string() });
const b = myzod.object({ b: myzod.string() });
const schema = myzod.intersection(a, b);
// same as
const schema = a.and(b);
// or
const schema = b.and(a);
type Schema = Infer<typeof schema>; // => { a: string; b: string }
The myzod.partial function takes a schema and generates a new schema equivalent to typescript's Partial type for that schema.
const personSchema = myzod.object({ name: myzod.string() });
const partialPersonSchema = myzod.partial(personSchema);
type PartialPerson = Infer<typeof partialPersonSchema>; // => Partial<{ name: string }> || { name?: string }
partialPersonSchema.parse({}); // Succeeds
partialPersonSchema.parse({ nickName: 'lil kenny g' }); // throws validation error
The partial function accepts an options object as second argument to create a deeply partial object.
options:
boolean created a deeply partial schema for nested objectsconst schema = myzod.object({
name: myzod.string(),
birthday: myzod.object({
year: myzod.number(),
month: myzod.number().min(1).max(12),
date: myzod.number().min(1).max(31),
}),
});
const partialSchema = myzod.partial(schema);
type PartialSchema = myzod.Infer<typeof partialSchema>; // => { name?: string; birthday?: { year: number; month: number; date: number; } }
const deeplyPartialSchema = myzod.partial(schema, { deep: true });
type DeeplyPartialSchema = myzod.Infer<typeof deeplyPartialSchema>; // { name?: string; birthday?: { year?: number; month?: number; date?: number; } }
The myzod.pick function takes a myzod schema and an array of keys, and generates a new schema equivalent to typescript's Pick<T, keyof T> type.
const personSchema = myzod.object({
name: myzod.string(),
lastName: myzod.string(),
email: myzod.email(),
age: myzod.number(),
});
const nameSchema = myzod.pick(personSchema, ['name', 'lastName']);
type Named = myzod.Infer<typeof nameSchema>; // => { name: string; lastName: string; }
The myzod.pick function takes a myzod schema and an array of keys, and generates a new schema equivalent to typescript's Omit<T, keyof T> type.
const personSchema = myzod.object({
name: myzod.string(),
lastName: myzod.string(),
email: myzod.email(),
age: myzod.number(),
});
const nameSchema = myzod.omit(personSchema, ['email', 'age']);
type Named = myzod.Infer<typeof nameSchema>; // => { name: string; lastName: string; }
The myzod.lazy function takes a function that returns a schema and lazily evaluates it at parse. The advantage with this approach is that you can create schemas that reference themselves. Unfortunately typescript cannot resolve this type and it will be the user's responsibility to provide the corresponding myzod type. Fortunately if the user's provided type is incompatible with the given schema it will fail to compile so there is some hope.
type Person = {
name: string;
friends: Person[];
};
const personSchema: z.Type<Person> = myzod.object({
name: myzod.string(),
friends: myzod.array(myzod.lazy(() => personSchema)),
});
FAQs
Schema Validation with typescript type inference.
The npm package @arilotter/myzod receives a total of 1 weekly downloads. As such, @arilotter/myzod popularity was classified as not popular.
We found that @arilotter/myzod demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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