Inspired by io-ts, but without the functional programming (lingo).
Every type is strict by default (applies no coercion during validation), but can be converted into a looser variant using the autoCast
feature. Also, objects are stripped of unknown properties by default.
Great care has been taken to ensure that (even deeply nested) types emit readable error messages when validation fails.
When integrating in an imperative codebase, using a library that is purely functional programming-oriented is not fun.
In JavaScript, one can create a string
or number
using the constructors String
and Number
. Types created with this library mimic that pattern as you can see in the API examples below.
TypeScript uses structural typing (to match JavaScript's duck-typing). In short, this means that two interfaces or types that look the same are automatically compatible with each-other, even though they might have different names. This is of course very powerful, for example:
interface SomeInterface {
someProperty: string;
}
type SomeOtherInterface = SomeInterface & { partial?: 'property' };
const obj = { someProperty: 'with a value' };
// Now all three of: `SomeInterface`, `SomeOtherInterface` and `typeof obj` are assignable to each other, because they all satisfy each-other's requirements.
Sometimes however, it would be really nice to have nominal types (i.e. types that are different just because they have a different name, even if they look the same). An example from this library is the int
type. A value that is validated by this type is effectively a number
that has been validated to be a whole number (an integer). int
s should be assignable to variables of type number
, because they are in fact numbers. But not the other way round; a number
is not guaranteed to be an int
.
TypeScript currently has limited support for nominal types, but we can work around this limitation with "branding". Without going into too much details, this allows us to do the following:
// This is a built-in type, so you don't need to do this yourself, but it's a good
// example of a branded type. The type `int` defined here is a subtype of number,
// checked by the `Number.isInteger` function and given the brand `int`.
const int = number.withConstraint('int', Number.isInteger);
// This means that all values that are succesfully validated by this type
// (first checked to be a number and then to satisfy `Number.isInteger`)
// receive the brand `int`. This is not a runtime thing, but purely a
// TypeScript design-time aspect of the resulting type.
const myValue = int(1234);
// At runtime the value is still a number (and TypeScript respects that), so
// we can do the following:
const myCalculatedResult = myValue * 2;
// And:
const veryVeryLongString = '*'.repeat(myValue);
// But TypeScript enforces that we don't accidentally assign or use other kind
// of numbers where we explicitly only accept integers. Take for example the
// following function:
function setPageNumber(page: The<typeof int>): void;
// Wait, what's that awkward type? `The<typeof int>` is not something we want to
// write every time, and definitely not something we want to expose to consumers
// of our APIs. This is why we always combine our type-declaration with a
// one-liner that creates a TypeScript type with the same name. The following is
// the actual declaration in this library:
export type int = The<typeof int>;
export const int = number.withConstraint('int', Number.isInteger);
// Now we can simply say:
function setPageNumber(page: int): void;
// This is valid usage of this function:
setPageNumber(myValue);
// But this isn't, because TypeScript knows we have not validated the given number,
// so this will fail design-time:
setPageNumber(1234);
// It is also possible to sub-type branded types. Example:
type uint = The<typeof uint>;
const uint = int.withConstraint('uint', n => n >= 0);
// Valid:
const a: number = uint(123);
const b: int = uint(123);
const c: uint = uint(123);
// Invalid (TypeScript will complain):
const a: uint = 123;
const b: uint = int(123);
Note that brands are string-literals, so make sure to use unique brand-names for your types. io-ts uses unique symbols, which have stronger uniqueness guarentees. In this library we opted to use string-literals to allow for a much easier to use API.
When using the emitDecoratorMetadata
feature of the TypeScript compiler, the compiler will emit some runtime-accessible metadata about all declarations that have decorators. This metadata includes the actual classes that are used as types for parameters or return-types (see https://www.typescriptlang.org/docs/handbook/decorators.html for examples).
It enables libraries that perform automatic type-validation based on TypeScript typings of a method or constructor. This is done in several frameworks/libraries and can be very convenient. It is limited to classes however, because in TypeScript other types have no runtime aspect. When defining types using this library, types do have a runtime aspect. So this library enables the use of any type (even a regexp-validated string, an enum, etc.) as type in a decorated method and makes sure the right metadata is available at runtime for runtime validation. (see this example of Nest.js integration)
When using types in combination with the emitDecoratorMetadata
feature, make sure to always create a TypeScript type with the same name as the runtime type-validator, as follows:
type MyType = The<typeof MyType>;
const MyType = // MyType implementation here
/** An example of a simple constraint without a custom message. */
const SmallString = string.withConstraint('SmallString', s => s.length < 10);
The TypeScript type can be accessed with The<typeof SmallString>
, but that is not something we want to write every time, and definitely not something we want to expose to consumers of our APIs. This, and compatibility with decorator metadata, is why we always combine our type-declaration with a one-liner that creates a TypeScript type with the (exact) same name:
/** An example of a simple constraint without a custom message. */
type SmallString = The<typeof SmallString>;
const SmallString = string.withConstraint('SmallString', s => s.length < 10);
To get a value of that type, simply call the type-constructor:
const mySmallString = SmallString('123456789');
// mySmallString has (branded) type: SmallString, value: '123456789'
SmallString('1234567890');
// throws ValidationError: expected a [SmallString], got: "1234567890"
The error-message is ok, but to get better error messages provide one in your validation-function, for example:
/** A Percentage must be between 0 and 100 inclusive. */
type Percentage = The<typeof Percentage>;
const Percentage = number.withConstraint('Percentage', n => (n >= 0 && n <= 100) || 'should be between 0 and 100 inclusive');
Percentage(123);
// throws ValidationError: error in [Percentage]: should be between 0 and 100 inclusive, got: 123
This is nice and all, but the library really shines once you start combining types into larger structures.
/** User is a basic object type. */
type User = The<typeof User>;
const User = object('User', {
/** The name of the User, split up into a first- and last-name. */
name: object({
/** The first name of the User, should not be longer than 9 characters. */
first: SmallString,
/** The last name, has no restrictions. */
last: string,
}),
/** For reference, we need your shoe size, must be a whole non-negative number. */
shoeSize: int.withValidation(n => n >= 0 || 'reverse running-shoes are not supported yet'),
});
User({ shoeSize: -5 });
// throws ValidationError: errors in [User]:
//
// - missing property <name> [{ first: SmallString, last: string }], got: { shoeSize: -5 }
//
// - at <shoeSize>: reverse running-shoes are not supported yet, got: -5
User({ name: { first: "my name is so incredibly long, you wouldn't believe it" }, shoeSize: -4 });
// throws ValidationError: errors in [User]:
//
// - at <name>: missing property <last> [string], got: { first: "my name is so .. n't believe it" }
//
// - at <shoeSize>: reverse running-shoes are not supported yet, got: -4
//
// - at <name.first>: expected a [SmallString], got: "my name is so incred .. wouldn't believe it"
User({ name: { first: 'Donald', last: 'Duck' }, shoeSize: 1 }); // OK
Optional fields can be added with withOptional()
.
type Name = The<typeof Name>;
const Name = object('Name', {
/** First name */
first: string,
/** Last name */
last: string,
}).withOptional({
/** Optional middle name */
middle: string,
});
Name({ first: 1 });
// throws ValidationError: errors in [Name]:
//
// - missing property <last> [string], got: { first: 1 }
//
// - at <first>: expected a string, got a number (1)
Note that Name
does not complain about a missing middle
property (because that property is optional).
By default, object
validators strip unknown properties. In a future version, this behavior will be configurable.
Name({ first: 'first', last: 'last', middle: 'middle', title: 'title' });
// => { first: 'first', last: 'last', middle: 'middle' }
Note that, by default, undefined
values and omitted fields are interchangeable:
// `or` defines a simple union which is explained below
object({ prop: string.or(undefinedType) }).is({}); // => true
// `partial` is the same as `object`, but all properties are optional
partial({ prop: string }).is({ prop: undefined }); // => true
// This allows us to provide default values for omitted fields and define
// optional fields inline with required fields. (`withParser` will be explained
// later)
type StringOrEmpty = The<typeof StringOrEmpty>;
const StringOrEmpty = string.or(undefinedType).withParser(i => i || 'DEFAULT');
// Now missing properties are automatically converted to the given default value.
// In a future version we might add a convenience method for this.
object({ prop: StringOrEmpty }).construct({}); // => { prop: 'DEFAULT' }
object({ prop: StringOrEmpty }).is({}); // => true
To opt out of this behavior, use the optional options parameter (first):
object({ strictMissingKeys: true }, { prop: StringOrEmpty }).construct({});
// throws ValidationError: error in [{ prop: string | undefined }]: missing property <prop> [string | undefined], got: {}
object({ strictMissingKeys: true }, { prop: StringOrEmpty }).construct({ prop: undefined });
// => { prop: 'DEFAULT' }
Some built-in types provide a number of common extra validations using the withConfig
method. These declarative extra validations are fully supported by the error-reporter and provide nice error messages on error. These error-messages are customizable in most cases.
Another advantage of using the withConfig
method is that the declarative config can be retrieved at runtime by type-analysis tools, such as an OpenAPI / JSON schema generator.
Type | Config option | Docs |
---|---|---|
array(...) |
minLength and maxLength |
ArrayTypeConfig |
number |
max[Exclusive] , min[Exclusive] and multipleOf |
NumberTypeConfig |
string |
minLength , maxLength and pattern |
StringTypeConfig |
Some validations are more complex than the built-in basic validations and need custom logic. To add custom validation to any type, use the methods withValidation
(unbranded) and withConstraint
(branded). The accepted return-value of the validation-callback (ValidationResult
) is very convenient for both simple custom validations and more complex scenario's.
Return type | Interpretation | Example / usage |
---|---|---|
false |
Validation not ok, no custom message | value === 'ok' |
true |
Validation ok, no error | value === 'ok' |
'a string' |
Validation not ok, provided string is custom message | value === 'ok' || 'why it is not ok' |
[] |
Validation ok, no error | Explained below |
['a string', ...] |
Validation not ok, provided strings are custom messages | Explained below |
{ kind: '...', ...} |
Validation not ok, provides structured error details | Explained below |
[{ kind: '...', ...}, ...] |
Validation not ok, provides structured error details | Explained below |
Returning multiple violations:
A common pattern is building up a messages array and returning that, like this:
const messages: string[] = [];
if (...) messages.push('custom message');
if (...) messages.push('other custom message');
return messages;
In this case an empty messages
array means that no errors occurred. That is why an empty array is regarded as a successful validation.
Returning structured error details:
Structured error details (MessageDetails
as used internally by the library) have the advantage that they can provide hints to the error reporter on how to report the errors. This can result in better understandable error messages. For example, when certain properties are only required in certain conditions, return a MessageDetails
object with kind 'missing property'
.
Suppose you have an API that updates salaries for employees, and a special approval is needed for salaries over $200,000, these are some of the options:
/** The basic request type, validations will be added later */
type UpdateSalaryRequest = The<typeof UpdateSalaryRequest>;
const UpdateSalaryRequest = object('UpdateSalaryRequest', {
id: string,
salary: number,
}).withOptional({
salaryApproval: string,
});
//
// The simplest of solutions, only a condition.
//
type SuperBasicValidation = The<typeof SuperBasicValidation>;
const SuperBasicValidation = UpdateSalaryRequest.withValidation(request => request.salary < 200_000 || !!request.salaryApproval);
SuperBasicValidation({ id: 'emp01', salary: 300_000 });
// throws ValidationError: error in [UpdateSalaryRequest]: additional validation failed, got: { id: "emp01", salary: 300000 }
//
// Slightly better, at least provide a name to your type:
//
type ValidatedUpdateSalaryRequest = The<typeof ValidatedUpdateSalaryRequest>;
const ValidatedUpdateSalaryRequest = UpdateSalaryRequest.withConstraint(
'ValidatedUpdateSalaryRequest',
request => request.salary < 200_000 || !!request.salaryApproval,
);
ValidatedUpdateSalaryRequest({ id: 'emp01', salary: 300_000 });
// throws ValidationError: expected a [ValidatedUpdateSalaryRequest], got: { id: "emp01", salary: 300000 }
//
// A better solutions, only a custom message. This is often enough.
//
type WithBasicCustomMessage = The<typeof WithBasicCustomMessage>;
const WithBasicCustomMessage = UpdateSalaryRequest.withValidation(
request => request.salary < 200_000 || !!request.salaryApproval || 'approval is needed',
);
WithBasicCustomMessage({ id: 'emp01', salary: 300_000 });
// throws ValidationError: error in [UpdateSalaryRequest]: approval is needed, got: { id: "emp01", salary: 300000 }
//
// Report the error with the correct property to enable better reporting of multiple errors, maybe you want this:
//
type WithReportHint = The<typeof WithReportHint>;
const WithReportHint = UpdateSalaryRequest.withValidation(
request =>
request.salary < 200_000 ||
!!request.salaryApproval || [
{
kind: 'custom message',
path: ['salary'],
message: 'large salaries are only allowed when approved by the boss',
input: request.salary,
},
{
kind: 'custom message',
path: ['salaryApproval'],
message: 'missing approval for large salaries',
input: request.salaryApproval,
},
],
);
WithReportHint({ id: 'emp01', salary: 300_000, salaryApproval: '' });
// throws ValidationError: errors in [UpdateSalaryRequest]:
//
// - at <salary>: large salaries are only allowed when approved by the boss, got: 300000
//
// - at <salaryApproval>: missing approval for large salaries, got: ""
//
// Or report a missing properties like this:
//
type ReportMissingProperties = The<typeof ReportMissingProperties>;
const ReportMissingProperties = UpdateSalaryRequest.withValidation(
request =>
request.salary < 200_000 ||
!!request.salaryApproval || {
kind: 'missing property',
property: 'salaryApproval',
type: string,
},
);
WithReportHint({ id: 'emp01', salary: 300_000 });
// throws error in [UpdateSalaryRequest]: missing property <salaryApproval> [string], got: { id: "emp01", salary: 300000 }
Use union()
and intersection()
to create unions and intersections. When creating unions or intersections of two types, the methods: or()
and and()
might be preferable.
// Example adapted from: https://www.typescriptlang.org/docs/handbook/unions-and-intersections.html#unions-with-common-fields
type NetworkState = The<typeof NetworkState>;
const NetworkState = union('NetworkState', [
object('NetworkLoadingState', { state: literal('loading') }),
object('NetworkFailedState', { state: literal('failed'), code: number }),
object('NetworkSuccessState', { state: literal('success'), response: Response }),
]);
When reporting errors, in case of unions, the library tries to be as helpful as possible. Of course all errors are grouped by union-element for better understandability:
NetworkState({});
// throws ValidationError: error in [NetworkState]: failed every element in union:
// (got: {})
// • error in [NetworkLoadingState]: missing property <state> ["loading"]
// • errors in [NetworkFailedState]:
// ‣ missing properties <state> ["failed"] and <code> [number]
// • errors in [NetworkSuccessState]:
// ‣ missing properties <state> ["success"] and <response> [Response]
But whenever possible, the validation-messages will be limited to the (most likely) intended union-element:
NetworkState({ state: 'failed', code: '500' });
// throws ValidationError: error in [NetworkState]: in union element [NetworkFailedState] at <code>: expected a number, got a string ("500")
// • disregarded 2 union-subtypes due to a mismatch in values of discriminator <state>
// Or based on the type of value:
union([string, boolean, object({ value: number, unit: string })]).check(123);
// throws ValidationError: error in [string | boolean | { value: number, unit: string }]: expected a boolean, an object or a string, got a number (123)
union([string, boolean, object({ value: number, unit: string })]).check({});
// throws ValidationError: error in [string | boolean | { value: number, unit: string }]:
// • missing properties <value> [number] and <unit> [string], got: {}
// • disregarded 2 union-subtypes that do not accept an object
Generic types can be modelled as functions. This is best explained with an example.
To model the following type:
interface MyGenericWrapper<T> {
// Example of an ordinary interface member:
ok: boolean;
// This is the generic part:
inner: T;
}
Create the following function:
function MyGenericWrapper<T>(innerType: Type<T>) {
// The name (first parameter) is of course optional, but it can make life easier when things get more complex.
return object(`MyGenericWrapper<${innerType.name}>`, {
ok: boolean,
inner: innerType,
});
}
An alias in TypeScript...
type WrappedUser = MyGenericWrapper<User>;
... becomes a variable (with the necessary boilerplate) using this library:
type WrappedUser = The<typeof WrappedUser>;
const WrappedUser = MyGenericWrapper(User);
But you can also use it inline inside other combinators.
type UserRequest = The<typeof UserRequest>;
const UserRequest = object('UserRequest', {
method: Method,
url: Url,
body: MyGenericWrapper(User),
});
Note that you cannot extract a generic type out of the generic function, i.e. the following does not work:
// This is not possible because it is not possible to reason about generic functions in TypeScript types:
type GenericWrapper = The<typeof GenericWrapper>;
function GenericWrapper<T>(inner: Type<T>) {
return object({ ok: boolean, inner });
}
If you want to have both the generic GenericWrapper
TypeScript-type and validator, you have to define them both separately. It is not possible to have TypeScript infer the TypeScript-type for you, but you can ask TypeScript to validate the compatibility between the type and the validator, like so:
// Do not use `interface` here, because TypeScript will merge an `interface` and `function`
// of the same name, which would result in a wrong typedef (and TypeScript will complain).
type GenericWrapper<T> = { ok: boolean; inner: T };
function GenericWrapper<T>(inner: Type<T>): ObjectType<GenericWrapper<T>> {
return object({ ok: boolean, inner });
}
When intersecting with the provided generic type-parameter, you may have to use the (exported) Writable
type, as seen in #25:
type AugmentedGeneric<T> = T & { id: string };
// Note the use of Writable here => \vvvvvvvv/
function AugmentedGeneric<T>(inner: ObjectType<T>): ObjectType<AugmentedGeneric<Writable<T>>> {
return intersection([inner, object({ id: string })]);
}
Validation is most likely used to validate incoming data / messages. Sometimes this data looks a lot like your internal type, but is slightly off. For example, maybe, the input has strings instead of numbers, or a "yes"/"no" instead of booleans. In those cases you can "prepend" a parsing step to your validator. For builtin types the most common conversions are available using the autoCast
feature.
Take the following (questionable) definition of Age
:
type Age = The<typeof Age>;
const Age = int.withConstraint('Age', n => (n >= 0 && n < 200) || 'unexpected age');
Age(123); // => 123
Age('123');
// throw ValidationError: error in base type of [Age]: expected a number, got a string ("123")
When we turn on the autoCast
feature, it will accept anything it can reasonably (and safely) convert to number:
type Age = The<typeof Age>;
const Age = autoCast(int.withConstraint('Age', n => (n >= 0 && n < 200) || 'unexpected age'));
Age(123); // => 123
Age('123'); // => 123
This is why we call the default function the "type constructor". It behaves similarly to Number
and String
. This is reflected in the API as follows:
// Age(...) is shorthand for Age.construct(...), it uses the optional parser to
// (try to) construct a valid instance of Age.
Age.construct('123'); // => 123
Age(true);
// throws ValidationError: error in parser of [AutoCast<Age>]: could not autocast value: true
// `is()` is a type-guard, it returns whether the value is already a valid Age.
Age.is('123'); // => false
Age.is(123); // => true
// `check()` is the check-only variant of `construct()`, it returns the value, but
// does not involve the parser
Age.check('123'); // throws
Age.check(123); // => 123
You can use your own (custom) parser with the withParser()
. For example:
type Answer = The<typeof Answer>;
const Answer = boolean.withParser(
'Answer',
string.andThen(v => v === 'yes'),
);
Answer('yes'); // => true
Answer('no'); // => false
Answer(1);
// throws ValidationError: error in parser precondition of [Answer]: expected a string, got a number (1)
// Or, as an contrived example, if you want to be more rigid:
type Answer = The<typeof Answer>;
const ValidAnswers = keyof({ yes: true, no: false });
const Answer = boolean.withParser('Answer', v => ValidAnswers.translate(v));
Answer('yes'); // => true
Answer('nope');
// throws ValidationError: error in parser of [Answer]: expected a ["yes" | "no"], got: "nope"
All types have an associated autoCast
type that adds a parser that tries to do some default (convenient) conversions where possible.
Type | Input | Output |
---|---|---|
number | Numeric autocasts automatically parse strings without known gotchas s.a. " " and "123 abc" : |
|
number |
123 |
123 |
autoCast(number) |
123 |
123 |
number |
"123" |
error in [number]: expected a number, got a string ("123") |
autoCast(number) |
"123" |
123 |
autoCast(number) |
" 123 " |
123 |
autoCast(number) |
" 123 a" |
error in parser of [AutoCast<number>]: could not autocast value: " 123 a" |
autoCast(number) |
" " |
error in parser of [AutoCast<number>]: could not autocast value: " " |
autoCast(number) |
"Infinity" |
Infinity (use a checked type like int or define a FiniteNumber type to prevent this) |
int | All numeric types (like int ) inherit the same autoCast behaviour: |
|
int |
123 |
123 |
int |
"123" |
error in [int]: expected a number, got a string ("123") |
autoCast(int) |
"123" |
123 |
autoCast(int) |
"123a" |
error in parser of [AutoCast<int>]: could not autocast value: "123a" |
autoCast(int) |
123.4 |
error in [AutoCast<int>]: expected a whole number, got: 123.4 |
autoCast(int) |
"123.4" |
error in [AutoCast<int>]: expected a whole number, got: 123.4, parsed from: "123.4" |
array | Arrays can auto-cast non-array values with the following behavior: | |
array(number) |
[1, 2] |
[1, 2] |
autoCast(array(number)) |
[1, 2] |
[1, 2] |
array(number) |
123 |
error in [number[]]: expected an array, got a number (123) |
autoCast(array(number)) |
123 |
[123] |
array(number) |
undefined |
error in [number[]]: expected an array, got an undefined |
autoCast(array(number)) |
undefined |
[] |
autoCastAll(array(number)) |
[123] |
[123] (autoCastAll is a deeply nested autoCast, all elements are also autoCast) |
autoCastAll(array(number)) |
["123"] |
[123] |
autoCastAll(array(number)) |
123 |
[123] |
autoCastAll(array(number)) |
"123" |
[123] |
unknownArray |
123 |
error in [unknown[]]: expected an array, got a number (123) |
autoCast(unknownArray) |
123 |
[123] |
unknownArray |
undefined |
error in [unknown[]]: expected an array, got an undefined |
autoCast(unknownArray) |
undefined |
[] |
boolean | Booleans can autocast from very specific string values (inspired by XML spec) | |
boolean |
true |
true |
boolean |
false |
false |
boolean |
"true" |
error in [boolean]: expected a boolean, got a string ("true") |
autoCast(boolean) |
"true" |
true |
boolean |
1 |
error in [boolean]: expected a boolean, got a number (1) |
autoCast(boolean) |
1 |
true |
autoCast(boolean) |
"false" |
false |
autoCast(boolean) |
0 |
false |
object and partial | Object types have no autoCast variant, but autoCastAll puts all properties into autoCast mode | |
object({ a: number }) |
{ a: "1" } |
error in [{ a: number }] at <a>: expected a number, got a string ("1") |
autoCastAll(object({ a: number })) |
{ a: "1" } |
{ a: 1 } |
object({ a: array(number) }) |
{ a: "1" } |
error in [{ a: number[] }]: expected an array, got a string ("1") |
autoCastAll(object({ a: array(number) })) |
{ a: "1" } |
{ a: [1] } |
object({ a: array(number) }) |
{} |
error in [{ a: number[] }]: missing property <a> [number[]], got: {} |
autoCastAll(object({ a: array(number) })) |
{} |
{ a: [] } (object determines that AutoCastAll<array(number)> can handle undefined value) |
keyof and valueof | Converts to String before passing to the base type | |
keyof({ false: "F", true: "T" }) |
"false" |
"false" |
keyof({ false: "F", true: "T" }) |
false |
error in ["false" | "true"]: expected a string, got a boolean (false) |
autoCast(keyof({ false: "F", true: "T" })) |
false |
"false" |
literal | Literals use the autoCast technique that is appropriate for the type of literal | |
literal(123) |
"123" |
expected a number (123), got a string ("123") |
autoCast(literal(123)) |
"123" |
123 |
literal("123") |
123 |
expected a string ("123"), got a number (123) |
autoCast(literal("123")) |
123 |
"123" |
nullType (or literal(null) ) |
undefined |
expected a null, got an undefined |
autoCast(nullType) (or autoCast(literal(null)) ) |
undefined |
null |
string | String can (currently) autoCast everything, this will probably change in the future | |
string |
123 |
error in [string]: expected a string, got a number (123) |
autoCast(string) |
123 |
"123" |
autoCast(string) |
123n |
"123" |
autoCast(string) |
false |
"false" |
string |
null |
error in [string]: expected a string, got a null |
autoCast(string) |
null |
error in parser of [AutoCast<string>]: could not autocast value: null |
string |
undefined |
error in [string]: expected a string, got an undefined |
autoCast(string) |
undefined |
error in parser of [AutoCast<string>]: could not autocast value: undefined |
string |
Symbol.iterator |
error in [string]: expected a string, got a symbol ([Symbol: Symbol.iterator]) |
autoCast(string) |
Symbol.iterator |
error in parser of [AutoCast<string>]: could not autocast value: [Symbol: Symbol.iterator] |
autoCast(string) |
{ prop: "value" } |
error in parser of [AutoCast<string>]: could not autocast value: { prop: "value" } |
autoCast(string) |
function myFunc() {} |
error in parser of [AutoCast<string>]: could not autocast value: [Function: myFunc] |
It is quite common to construct (large) object literals in code or in unit tests. Since the type-constructors accepts
unknown
as an argument, you run the risk of losing code completion. However, each type also has a
.literal
feature
const NonEmptyString = string.withConstraint('NonEmptyString', s => !!s.length);
type User = The<typeof User>;
const User = object('User', {
name: object({
first: NonEmptyString,
last: NonEmptyString,
}),
shoeSize: int,
});
const user = User({
// this would not get code completion as the functions accepts `unknown` :-(
});
const fullUser: User = {
// gets code completion, but requires you to type guard every literal :-(
name: {
first: NonEmptyString('John'),
last: NonEmptyString('Doe'),
},
shoeSize: int(48),
};
const literalUser = User.literal({
// code completion and no need for guarding simple literals :-)
name: {
first: 'John',
last: 'Doe',
},
shoeSize: 48,
});
// constructing a simple object with the same code completion support using DeepUnbranded utility
const simpleUser: DeepUnbranded<User> = {
name: {
first: 'John',
last: 'Doe',
},
shoeSize: 48,
};
One of the frameworks that provides features for runtime validation based on the TypeScript types of parameters is Nest.js. The following is an example of integration with Nest.js using a generic type-validation pipe:
import { ArgumentMetadata, BadRequestException, Injectable, PipeTransform } from '@nestjs/common';
import { boolean, isType, reportError, string, Type } from '@skunkteam/types';
// This pipe performs runtime type-validation, you should register
// it globally, see Nest.js documentation for more details.
@Injectable()
export class TypeValidationPipe implements PipeTransform {
transform(value: unknown, { metatype }: ArgumentMetadata) {
if (!isType(metatype)) {
// You may want to warn or error, instead of skipping
// validation, that is up to you.
return value;
}
const result = metatype.validate(value, { mode: 'construct' });
if (result.ok) {
return result.value;
}
throw new BadRequestException(reportError(result));
}
}