@srhenry/type-utils
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0.5.1 • Public • Published

Type Utils

Type utilities module for Typescript and also Javascript. It can secure your application from invalid data being pushed inside and breaking things as it can shape and model your data to prevent invalid data. Check out the documentation for further details.

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Table of Contents

Installing

With NPM:

npm install @srhenry/type-utils --save

With Yarn:

yarn add @srhenry/type-utils

Docs

See: API - Github Pages

Schema types

It represents a string to typescript's type infers and runtime validation

import { string } from '@srhenry/type-utils'

const isString = string() //any string
const isAvocadoString = string('avocado') //specific string
const isPatternString = string(/goo+gle/) //pattern/RegExp matched string

It represents a number to typescript's type infers and runtime validation

import { number } from '@srhenry/type-utils'

const isNumber = number()

It represents a number to typescript's type infers and runtime validation

import { boolean } from '@srhenry/type-utils'

const isBoolean = boolean()

It represents a well defined object to typescript's type infers and runtime validation, which its properties are also described using the Schema helpers

import { object, string, number } from '@srhenry/type-utils'

const isMyObject = object({
    foo: string(),
    bar: number(),
})

It represents an array to typescript's type infers and runtime validation, which its items can also be described using the Schema helpers

import { array, string, object } from '@srhenry/type-utils'

const isArray = array() // array of anything
const isMyArray = array(string()) // array of strings
const isMyObjArray = array(object({ foo: string('bar') }))
const isMyObjArray2 = array({ foo: string('bar') })

It represents a symbol to typescript's type infers and runtime validation

import { symbol } from '@srhenry/type-utils'

const isSymbol = symbol()

It represents a closed switch values to typescript's type infers and runtime validation. It ensures your value is one of the values given in params.

import { asEnum } from "@srhenry/type-utils"

enum Status {
  ready: 1,
  running: 2,
  stopped: 3,
}

const validStatus = [...Object.keys(Status)] as (keyof typeof Status)[]

const isStatus = asEnum(validStatus)

It represents a null literal to typescript's type infers and runtime validation.

import { asNull } from '@srhenry/type-utils'

const isNull = asNull()

It represents a primitive values (such as string, number, boolean, symbol, null, undefined) to typescript's type infers and runtime validation.

import { primitive } from '@srhenry/type-utils'

const isSymbol = primitive()

It represents a 'any' value to typescript's type infers and runtime validation. It does nothing to validate a narrowed type but can be useful to improve readability in more complex schemas.

import { any, object } from '@srhenry/type-utils'

const isAny = any()
const objectHasFoo = object({ foo: isAny }) //it checks if is object and if has `foo` property but doesn't care checking its type

Schema.optional

Schema.optional.*

It represents a optional value to typescript's type infers and runtime validation. It returns recursive structure of schema helpers to narrow validation.

import { optional, object } from '@srhenry/type-utils'

const maybeString = optional().string()
const objectMaybeHasFoo = object({ foo: maybeString }) //it checks if is object and if has `foo`. if it has `foo` then check if it is string, if it hasn't then pass anyway as it is optional property

Schema helpers

It creates an intersection between two schemas.

import { object, string, and } from '@srhenry/type-utils'

const hasFoo = object({ foo: string() })
const hasBar = object({ bar: string() })
const isSomething = and(hasFoo, hasBar)

It creates an union between two schemas.

import { string, boolean, or } from '@srhenry/type-utils'

const isString = string()
const isBool = boolean()
const isSomething = or(isString, isBool)

It wraps a schema (just to improve readability).

import { object, string, array, useSchema } from '@srhenry/type-utils'

const hasFoo = object({ foo: string() })
const isFooArray = array(useSchema(hasFoo))

Validation rules

It constraints a number to be different from 0.

import { number, NumberRules } from '@srhenry/type-utils'
const isNonZeroNumber = number([NumberRules.nonZero()])

It constraints a number to be lesser than a given number.

import { number, NumberRules } from '@srhenry/type-utils'

const isNonZeroNumber = number([NumberRules.max(255)])

It constraints a number to be greater than a given number.

import { number, NumberRules } from '@srhenry/type-utils'
// or
const isNonZeroNumber = number([NumberRulesmin(1)])

It constraints an array's size to be lesser than a given number.

import { array, any, ArrayRules } from '@srhenry/type-utils'

const isArray = array([max(25)], any())

It constraints an array's size to be greater than a given number.

import { array, any, ArrayRules } from '@srhenry/type-utils'

const isArray = array([ArrayRules.min(1)], any())

It constraints an array to contain only distinct values, failling if a duplicate is found.

import { array, string, ArrayRules } from '@srhenry/type-utils'

const isArray = array([Rules.ArrayRules.unique()], string())

It constraints a string's size to be lesser than a given number.

import { string, StringRules } from '@srhenry/type-utils'

const isString = string([StringRules.max(60)])

It constraints a string's size to be greater than a given number.

import { string, StringRules } from '@srhenry/type-utils'

const isString = string([StringRules.min(60)])

It constraints a string to match a given pattern (regular expression).

import { string, StringRules } from '@srhenry/type-utils'

const isNumericString = string([StringRules.regex(/[0-9]+/)])

It constraints a string's size to be greater than 0.

import { string, StringRules } from '@srhenry/type-utils'

const isString = string([StringRules.nonEmpty()])

It constraints a string to be a valid url representation.

import { string, StringRules } from '@srhenry/type-utils'

const isStringUrl = string([StringRules.url()])

It constraints a string to be a valid email representation.

import { string, StringRules } from '@srhenry/type-utils'

const isStringEmail = string([StringRules.email()])

It constrains a record to not be empty.

import { record, RecordRules } from '@srhenry/type-utils'


const isNonEmptyRecord = record([RecordRules.nonEmpty()])

Available validations

)

It checks a given value against a given schema or validator and return true if schema matches the value, otherwise return false.

import { string, is } from '@srhenry/type-utils'

//...
if (is(value, string())) {
    // value is string
} else {
    // value is not a string
}

It checks a given value against a given schema or validator and returns the checked value with schema inferred type if schema matches the value or throws an error if schema didn't match the value. Pretty clean to use with destructuring pattern.

import { object, number, string, ensureInterface } from '@srhenry/type-utils'

//...
const { foo, bar } = ensureInterface(value, object({
    foo: number(),
    bar: string(),
}) //It throws an error if validation fails!

console.log('foo', foo) // foo
console.log('bar', bar) // bar

It validates a value against a given schema and throws or returns the list of mismatches against schema.

import { string, number, object, Experimental } from "@srhenry/type-utils"

const { validate } = Experimental

declare const value: unknown // Mocking external/unknown data

const schema = object({
    foo: string(),
    bar: number(),
})

try {
  const validatedValue = validate(value, schema)

  // do something...
} catch (e) {
  if (e instanceof Experimental.ValidationErrors) {
    // error collection is iterable:
    for (const { parent, path, message, checked, against, context } of e) {
      console.log(parent, path, message, checked, against, context)
      // do something...
    }
  }
}

NOTE: You can use schema directly to validate a value.

import { object, number } from "@srhenry/type-utils"

const hasFoo = object({ foo: number() }))

//...
if (hasFoo(obj)) {
  // obj is object and contains a string property named `foo`
} else {
  // obj don't have a `foo` property of type string
}

Experimental Features

This is intended for partial assertions in schemas, fetching all violations against the schema, like other specialized tools does (yup, joi, etc). Common use cases are in form validations and payload validations, in order to give feedback of where the data is wrong by schema.

import {
    Experimental,
    object,
    string,
    StringRules,
    helpers,
} from '@srhenry/type-utils'

const { ValidationErrors, Validator } = Experimental
const { setValidatorMessage } = helpers

/** A sample schema */
const schema = object({
    name: string(),
    email:string([StringRules.email()]),
    password: string.optional([StringRules.min(6)]),
})

// Set custom messages for validator errors:
Validator.setValidatorMessage({
    name: "name is required"
    email: "email is required"
}, schema)

/** An API request payload or else */
const payload = {
    name: 'Foo',
    email: '',
    password: '1234',
}

// throwable flow:
try {
    const data = Validator.validate(payload, schema)
    //...
} catch (e) {
    if (e instanceof ValidationErrors) {
        // generic function representing some error handling for presenting to requester:
        respondWith({
            errors: e.errors.map(({ path, message }) = ({
                // something like '$', '$.name', '$.email' or '$.password':
                path: path.replace('$', 'payload'),
                message,
            })),
        })
        // procedural handling (ValidationErrors is iterable):
        for (const { parent, path, message, checked, against } of e) {
            //...
        }
    }
}

// not throwable flow (set throw flag to false):
const data = validate(payload, schema, false)
if (data instanceof ValidationErrors) {
    // handle error(s)...
} else {
    //use schema shaped data...
}

This was inspired in C# Lambdas, equivalent to arrow functions in Javascript/Typescript, but this helper adds invoke() method to a function instance. useful to improve readability when you have a function that returns another and you wanna call 'em all in a row, using fluent pattern.

import { Experimental } from '@srhenry/type-utils'

const { lambda } = Experimental

function builder(locales: string | string[] = 'en-US') {
    function formatter(
        options: Intl.DateTimeFormatOptions = {
            dateStyle: 'short',
            timeStyle: 'short',
        }
    ) {
        function format(date: Date | string) {
            return new Intl.DateTimeFormat(locales, options).format(new Date(date))
        }

        return lambda(format)
    }

    return lambda(formatter)
}

console.log(
    '1970-01-01T00:00 =',
    builder('en-UK').invoke({ dateStyle: 'long' }).invoke('1970-01-01')
) // 01 January 1970

This does type-wisely curries a function or lambda, in two flavors: allowing or not partial param applying (default is not allowed). The process of currying a function is traditionally a techique that allows you to call the refered function passing one parameter at a time, returning another function to further apply remaining parameters, then returning whatever the original function returns after all parameters were given to curried function. In Javascript this techinque usually allows partial apply, and in that way you can pass more than one parameter at a time, and everything else remains equal to the traditional currying.

import { Experimental } from '@srhenry/type-utils'

const { lambda, curry } = Experimental

// lets reuse earlier example:
function builder(
    locales: string | string[],
    options: Intl.DateTimeFormatOptions,
    date: Date | string
) {
    return new Intl.DateTimeFormat(locales, options).format(new Date(date))
}

const curried = curry(builder)
const curriedLambda = curry(lambda(builder))

console.log(
    curried('en-GB')({ timeStyle: 'short', timeZone: 'Etc/Greenwich' })(
        new Date('2020-05-10T22:35:08Z')
    )
) // 22:35

console.log(
    curriedLambda('en-US')
        .invoke({ dateStyle: 'short', timeStyle: 'short', timeZone: 'America/New_York' })
        .invoke(new Date('2020-05-10T22:35:08Z'))
) // (EDT) 5/10/20, 6:35 PM

This is a fluent API to create sync/async function pipelines. Inspired in FP pipe operator while it does not comes to Javascript/Typescript yet. It allows only single param functions, piping the return as the parameter to the next function in pipeline.

import { Experimental } from '@srhenry/type-utils'

const { pipe, enpipe, lambda } = Experimental

const addUserFactory =
    (db: Record<string, Record<string, any>[]>) => (user: Record<string, any>) =>
        new Promise<string>(resolve => {
            setTimeout(() => {
                const id = uuid()

                db['users'] ??= []
                db['users']?.push({ id, ...user })
                resolve(id)
            }, 200)
        })
const addPostFactory =
    (db: Record<string, Record<string, any>[]>) => (user_id: string, post: Record<string, any>) =>
        new Promise<boolean>(resolve => {
            setTimeout(() => {
                db['posts'] ??= []
                db['posts']?.push({ user_id, ...post })
                resolve(true)
            }, 300)
        })

const db = {
    users: [] as Record<string, any>[],
    posts: [] as Record<string, any>[],
} as Record<string, Record<string, any>[]>

const len = <T = any>(s: string | ArrayLike<T>) => s.length
const addPostCurried = (post: Record<string, any>) => (id: string) =>
    pipe(addPostFactory).pipe(enpipe(db)).pipe(lambda).invoke(id, post)

const result = await pipe(addUserFactory)
    .pipe(enpipe(db))
    .pipe(
        enpipe({
            name: 'Marcus',
            email: 'example@email.com',
        })
    )
    .pipeAsync(
        addPostCurried({
            title: 'Hello World',
            content: 'Lorem ipsum dolor sit amet',
        })
    )
    .pipeAsync(() => {
        if (len(db['users']!) === 0 || len(db['posts']!) === 0) return false

        db['replies'] = []
        return true
    })
    .depipe() // true | false

This helper enables you to build switch expressions as it is not available in Javascript vanilla. Each branch allows you to define the matchers or values ahead of time with literal values or inline expressions, or define with callbacks to customize handling of each branch, making it a powerfull way to describe a complex switch without if-else-if language syntax. It defines a lambda as the switch runner, so you can define and run it in the row with more readability.

const switcher = $switch()
    .case(4, 'four')
    .case(3, 'three')
    .case(2, 'two')
    .case(1, 'one')
    .default('none of the above') // it does not run yet

console.log(switcher.invoke(1)) // one
console.log(switcher.invoke(3)) // three
console.log(switcher.invoke(10)) // none of the above
const switcher = $switch(5)
    .case(4, 'four')
    .case(3, 'three')
    .case(2, 'two')
    .case(1, 'one')
    .default('none of the above') // it does not run yet

console.log(switcher()) // none of the above
console.log(switcher.invoke()) // none of the above
console.log(switcher.invoke(1)) // none of the above
console.log(switcher(3)) // none of the above
const switcher = $switch<number>()
    .case(
        n => n % 2 === 0,
        () => Math.floor(Math.random() * 10_000) + 1
    )
    .default(n => n ** n)

console.log(switcher(1)) // 1 (1^1)
console.log(switcher(2)) // random number between 1-10000
console.log(switcher(3)) // 27 (3^3)
console.log(switcher(4)) // random number between 1-10000
console.log(switcher(5)) // 3125 (5^5)
console.log(switcher(6)) // random number between 1-10000
console.log(switcher(7)) // 823543 (7^7)

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npm i @srhenry/type-utils

Weekly Downloads

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Version

0.5.1

License

MIT

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  • srhenry