The goal of this library is to provide flexible, intuitive, strong type checking that is:
- just javascript
- serializable as JSON (so, e.g. services can tell you their type!)
- incredibly simple and intuitive (most types can be specified using a correct example)
- capable of very fine grained types (Note 1)
- is present at runtime (Note 2)
- allows you to essentially build typesafe "monadic" functions
Note 1: e.g. string properties whose name starts with is[A-Z] are boolean
Note 2: because in the real world, you don't get to update all the client code in lockstep with services
Typescript:
type Person = {
name: string
age: number
date: Date
}
function isOldEnoughToVote(person: Person): boolean {
return !(person.age < 18)
}
type-by-example
// types are just (serializable) Javascript
const personType = {
name: 'Jane Doe',
age: 33,
date: '#instance Date'
}
// you can test types at runtime using matchType and get very clear error messages
matchType({name: 'Fred Dagg', age: 17, date: new Date()}) // returns []
matchType({name: 'Fred Dagg'}, personType) // returns ['.age was undefined, expected number', '.date was undefined, expected #instance Date']
// and you can create type-safe functions that (like monads) pass through errors untouched
export const isOldEnoughToVote = typeSafe(
function(person) {
return !(person.age < 18)
},
personType,
false,
'isOldEnoughToVote'
)
Certain specialized types — enumerations in particular — are supported in a way that still allows types to be encoded as JSON. These types are specified using a string starting with a '#'. (It follows that you shouldn't use strings starting with '#' as examples of strings.)
Ultimately, the goal of this module is to provide a single source of truth for types during static analysis, runtime, for mocks, and for filters.
As a side-benefit, it is also capable of driving mock-data and optimistic rendering. Annotations in example data can provide hints as to how to generate mock data for testing purposes and for rendering user interfaces before live data is available.
General usage is:
matchType(example, subject) // returns empty list if subject has same type as example
// returns a list of problems discovered otherwise
E.g.
matchType(0, 17) // [] -- no errors
matchType('foo', 17) // ["was number, expected string"]
This is most useful when comparing objects, e.g.
matchType({foo: 17, bar: 'hello'}, {foo: 0, bar: 'world'}) // [] -- no errors
matchType({foo: 17, bar: 'hello'}, {bar: 'world'}) // [".foo was undefined, expected number"]
matchType({foo: 17, bar: 'hello'}, {foo: 0, bar: 17}) // [".bar was number, expected string"]
If the example includes arrays, the elements in the array are assumed to be the valid examples for items in the array, e.g.
matchType([{x: 0, y: 0}, {long: 0, lat: 0, alt: 0}], []) // [] -- no errors
matchType([{x: 0, y: 0}, {long: 0, lat: 0, alt: 0}], [{x: 10, y: 10}, {x: -1, y: -1}]) // []
matchType([{x: 0, y: 0}, {long: 0, lat: 0, alt: 0}], [{lat: -20, long: 40, alt: 100}]) // []
matchType([{x: 0, y: 0}, {long: 0, lat: 0, alt: 0}], [{x: 5, y: -5}, {long: 20}])
// ["[1] had no matching type"]
matchType([{x: 0, y: 0}, {long: 0, lat: 0, alt: 0}], [{x: 5}, {long: 20}])
// ["[0] had no matching type", "[1] had no matching type"]
For efficiency, put the most common example elements in example arrays first (since checks are performed in order) and do not include unnecessary elements in example arrays.
Some specific types can be defined using strings that start with '#'. (It follows that you should not use strings starting with '#' as type examples.)
specficTypeMatch
is the function that evaluates values against specific types. (Typically you
won't use it directly, but use matchType instead.)
specificTypeMatch('#int [0,10]', 5) === true // 0 ≤ 5 ≤ 10
specificTypeMatch('#int [0', -5) === false // -5 is less than 0
specificTypeMatch('#int', Math.PI) === false // Math.PI is not a whole number
specificTypeMatch('#enum true|null|false', null) === true
specificTypeMatch('#enum true|null|false', 0) === false
specificTypeMatch('#enum "get"|"post"|"put"|"delete"|"head"', 'head') === true
specificTypeMatch('#enum "get"|"post"|"put"|"delete"|"head"', 'save') === false
You can specify an enum type simply using a bar-delimited sequence of JSON strings (if you're transmitting a type as JSON you'll need to escape the '"' characters).
specificTypeMatch('#int [0,10]', 5) === true // 0 ≤ 5 ≤ 10
specificTypeMatch('#int [0,∞]', -5) === false // -5 is less than 0
specificTypeMatch('#int [0', -5) === false // -5 is less than 0
specificTypeMatch('#int', Math.PI) === false // Math.PI is not a whole number
specificTypeMatch('#number (0,4)', Math.PI) === true // 0 < Math.PI < 4
You can specify whole number types using '#int', and you can restrict #int and #number values to ranges using, for example, '#int [0,10]' to specify any integer from 0 to 10 (inclusive).
Use parens to indicate exclusive bounds, so '#number [0,1)' indicates a number ≥ 0 and < 1. (In case you're wondering, this is standard Mathematical notation.)
You can specify just a lower bound or just an upper bound, e.g. '#number (0' specifies a positive number.
specificTypeMatch('#union string||int', 0) === true
specificTypeMatch('#union string||int', 'hello') === true
specificTypeMatch('#union string||int', true) === false
You can specify a union type using #union followed by a '||'-delimited list of allowed types. (Why '||'? '|' is quite common in regular expressions and you might want to use a regex specified string type as an option.)
This type can be used for forbidding the presence of a property within an object
(it's not the same as undefined
, e.g. Object.assign({foo: 'bar'}, {foo: undefined})
is not the same as Object.assign({foo: 'bar'}, {})
. If nothing else, it can trap
mistyped property names.
It's particularly useful in conjunction with wildcard property specifiers, e.g. pointType
specifies an object with numerical properties x
and y
and nothing else.
pointType = {
x: 1.5,
y: 2.2,
'#.*': '#forbidden'
}
You can also enforce naming conventions, this type only allows properties that are legal javascript variable names, but excludes those starting with underscore or containing a '$' sign.
someType = {
'#(_.*|.*$.*)': '#forbidden',
'#': '#any',
'#.*': #forbidden'
}
You can specify any (non-null, non-undefined) value via '#any'.
You can specify a built-in type, e.g. HTMLElement
value via '#instance ConstructorName', in
this example '#instance HTMLElement'.
matchType('#instance HTMLElement', document.body) // returns [] (no errors)
You can denote an optional type using '#?'. Both null
and undefined
are acceptable.
Inside objects, which applies to most type declarations, you can use the more convenient
and intuitive option of adding a ?
to the key, so:
const mightHaveFooType = {
foo: '#?number'
}
And:
const mightHaveFooType = {
'foo?': 17
}
These two declarations are equivalent.
But, I hear you cry, what if I actually want a property named 'foo?' Well, I pity you, but it's possible to do this using the syntax for declaring maps:
const definitelyHasFooQueryType = {
'#foo\\?': 17
}
This mechanism will likely add new types as the need arises, and similarly may afford a convenient mechanism for defining custom types that require test functions to verify.
You can specify a regular expression test for a string value by providing the string you'd use
to create a RegExp
instance. E.g. '#regexp ^\d{5,5}$' for a simple zipcode type.
matchType('#regexp ^\\d{5,5}$', '90210') // returns [] (no errors)
matchType('#regexp ^\\d{5,5}$', '2350') // returns ["was "2350", expected #regexp \d{5,5}"]
A simple and useful wrapper for typeof
is provided in the form of describe
which
gives the typeof the value passed unless it's an Array
(in which case it returns
'array') or null
(in which case it returns 'null')
describe([]) // 'array'
describe(null) // 'null'
describe(NaN) // 'NaN'
describe(-Infinity) // 'number'
Important Note: key properties are evaluated in the order they appear in the object. This is very important for regex keys.
It's frequently necessary to declare objects which might have any
number of properties. You can declare an object as {}
and it
will be allowed to have any number of crazy properties, or you
can use strings prefixed by #
as the key to denote restrictions
on possible keys.
(And, of course, you can declare a property name that actually starts with a '#' symbol by putting it in the regex, so '##foo' defines a property named '#foo'. You can even require a property named '#//' if you want to.)
As a bonus, we can use the same method for embedding comments in serialized types! A property named '#//' is ignored by matchType (and can be treated as a comment -- you could even put an array of string in it for a long comment)
E.g.
const mapType = {
'#//': 'This is an example (and this is a comment)',
'#': 'whatevs'
}
This declares an object which can have any properties that would be allowed as javascript variable names, as long as the values are strings.
If you want to allow absolutely anything to be used as a key you could declare:
const mapType = {
'#.*': '#?any'
}
(This is pretty much the same as just declaring mapType = {}
.)
If the type has anything after the '#' besides '//' (which denotes a comment)
then that will be treated as the body of a RegExp
with ^
at the start and
$
at the end, so '#.*' allows any key that matches /^.*$/
(which is anything,
including an empty string).
(Yeah, it doesn't allow for pathological cases, like undefined
and null
as keys,
but our goal isn't to support programmers who want to declare types that appear as WTF
examples of bad Javascript.)
It follows that the key '#' is equivalent to:
'#[a-zA-Z_$][a-zA-Z_$0-9]*'
So you could declare an object like this:
const namingConventionType = {
'#is\w+': true,
'#_': '#forbidden'
}
Or hell, enforce some variant of Hungarian Notation:
const hungarianObject = {
'#bool[A-Z]\\w+': true,
'#txt[A-Z]\\w+': 'whatevs',
'#int[A-Z]\\w+': '#int',
'#float[A-Z]\\w+': 3.14,
...
}
typeSafe
adds run-time type-checking to functions, verifying the type of both
their inputs and outputs:
import {typeSafe} from 'type-by-example'
const safeFunc = typeSafe(func, paramTypes, resultType, name)
func
is the function you're trying to type-check.paramTypes
is an array of types.resultType
is the type the function is expected to return (it's optional).name
is optional (defaults to func.name || 'anonymous')
For example:
const safeAdd = typeSafe((a, b) => a + b, [1, 2], 3, 'add')
A typeSafe function that is passed an incorrect set of parameters, whose original
function returns an incorrect set of paramters will return an instance of TypeError
.
TypeError
is a simple class to wrap the information associated with a type-check failure.
Its instances five properties and one method:
functionName
is the name of the function (or 'anonymous' if none was provided)isParamFailure
is true if the failure was in the inputs to a function,expected
is what was expected,found
is what was found,errors
is the array of type errors.toString()
renders theTypeError
as a string
A typeSafe function that is passed or more TypeError
instances in its parameters will return
the first error it sees without calling the wrapped function.
typeSafe functions are self-documenting. They have two read-only properties paramTypes
and
resultType
.
typeSafe functions are intended to operate like
monads,
so if you call safe_f(safe_g(...))
and safe_g
fails, safe_f
will short-circuit execution and
return the error directly -- which should help with debugging and prevent code executing
on data known to be bad.
I've done some rough performance testing of typeSafe
and added a simple
optimization. The test code simply performed an add operation 1,000,000
times inline, wrapped in a function, wrapped in a trivial wrapper function, and
using a typeSafe
function.
In essence, the overhead for typeSafe functions (on my recent, pretty fast, Windows laptop) is about 350ms/million calls checked by typeSafe.
Note that many frameworks end up wrapping all your functions several times for various reasons, doing non-trivial work in the wrapper. In any event, if even this much of an overhead is abhorrent, simply don't use typeSafe in performance critical situations, or call it outside a loop rather than inside.
(E.g. if you're iterating across a lot of data in an array, typecheck a function that takes the array, not a function that processes all the elements -- matchType does not check every element of a large array.)
The obvious place to use typeSafe functions is when communicating with services, and here any overhead is insignificant compared with network or I/O.
This library originally started out as part of b8rjs and then was brought across to xinjs. It's now being broken out as a standalone library.
Aside from the usual nodejs toolchain, this project uses bun for speed and as a test runner.