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JVU

Json-schema Validator Utilities

Json-schema is a declaration of document type in a json format. Basic usage of a json schema is validation, but also it might bring a clear picture of protocols used in an application.

What are reasons to use json-schema?

Validation (type checking)
Protocols (database & API description)

Anything else? Lots of things, but this package is about functional programming and awesome techniques, that can be achieved with json-schema usage:

Features

Use any json-schema validator
Expose native environment API

// shorthands for native API

jvu.add('', schema) or env.addSchema
jvu('', object) or validate/is

// new API

jvu.not('', object)
jvu.match({ '': value })
jvu.find([''])
jvu.filter([''])

Terms

validator - a json-schema validator used for internal tasks
validation function - a generated by path or schema function which checks any given argument among with a schema and returns isValid value

Support

List of supported validators

djv
jjv

Adapter required

ajv

The main protocol required by this package is to have addSchema and validate methods inside a created environment. For special cases adapter functions can be defined. Examples of adapters can be found in a support.spec.js.

Usage

Lets have an example schema

jsonSchema = {
  "common": {
    "properties": {
      "type": {
        "enum": ["common"]
      }
    },
    "required": [
      "type"
    ]
  }
};

It defines a common object type, which has a type property with a single value common.

{ type : 'common' } // => valid by '#/common' path

initialize & add

Utils will create an empty environment with a given validator.

jvu = require('jvu')(validator);

In order to support different json-schema validators api the second argument in jvu constructor provides a wrapper function, which is used as an adapter for environment.

jvu = require('jvu')(validator, validator => ({
  validate: nil =>
    nil ? validator.customValidate('any', nil) : false
}))

Validator environment is available with a jvu.env link. However, created jvu environment is extended with validator environment, so you can use it if it does not intercept. This is done for the reason to decrease API changes needed to integrate jvu to existing code.

Use add to add json schema after initialization

jvu.add('', jsonSchema);

jvu('', ?) - validate/is

Use validate/is to check an object by schema reference. jvu('', ?) is a short notation for validate/is.

jvu.validate('#/common', { type: 'common' }) // => true
jvu.is('#/other', { type: 'common' }) // => false
jvu('#/other', { type: 'common' }) // => false

When it's called without a second argument - it returns a validation function, which can be used in further calculations.

const validate = jvu('#/common');
validate({ type: 'common' }) // => true

The generated validation function accepts object as a param and returns the isValid flag.

one argument - partial execution,
two arguments - returns a value.

var testCommon = jvu('#/common');
[commonObj].map(testCommon) // => [true]

var testNotCommon = jvu('#/common', true);
[commonObj].map(testNotCommon) // => [false]

Partial execution is very helpful in each, find and other iterable operations.

jvu.not('', ?) - !jvu.is

Same functionality as jvu.is but with an opposite meaning. Validation function returns the isNotValid flag.

jvu.not('#/common', { type: 'common' }) // => false
jvu.not('#/other', { type: 'common' }) // => true

jvu.match({}, ?)

Use match as a Matching pattern.

jvu.match({ '#/common': () => 1 }, commonObj) // => 1
jvu.match({ '#/common': () => 1 }, unknownObj) // => undefined

// ...
jvu.match({
  '#/0': () => 0,
  '#/other': () => 1
}, 0); // => 1

Factorial

This comes from funcy package

const fact = jvu.match({
  '#/0': () => 1,
  '#/other': n => n * fact(n - 1)
});

fact(5) // => 120

if-less

/**
if(some === null) { throw new Error('#/null') }
else { process() }
*/// =>

jvu.match({
  '#/null': () => throw new Error('#/null'),
  '#/other': process,
}, some)

Declarative Promises

A better example of if-less or Matching Pattern would be a stream (in Reactive Programming) or Promise chain

new Promise((resolve, reject) => resolve({ type: 'common' }))
.then(
  jvu.match({
    '#/null': () => 'so far so good',
    '#/common': () => 'common',
    '#/other': () => 'enough',
  }),
  jvu.match({
    '#/error/system': () => 'this is bad',
    '#/error/common': () => '\_(ツ)_/¯',
  })
)
.then(result => console.log(result)); // => 'common'

jvu.find({}, ?)

Use find to ease a switch condition. A difference between match is that find only returns a given result, when match is also executing found expression. Both find and match method can use either object or array as a param.

jvu.find(['#/common'], commonObj) // => 0
jvu.find({ '#/common': 1 }, unknownObj) // => undefined

When executed with an object it returns a value by found key, but when executed with an array returns an index of founded item. It looks a bit inconsistent, nevertheless it has a reason to output an opposite information comparing to input.

jvu.filter({}, ?)

Filters all appropriate pathes. This pattern does not exist with a function call (like match is a find with call).

jvu.filter({ '#/common': 1, '#/all': 2 }, unknownObj) // => [1, 2]

API

add(String namespace, Object jsonSchema) add schema to existing environment
jvu(String/Object reference[, Object instance]) validate object by schema reference. Shorthands - validate, is
not(String/Object reference[, Object instance]) validate object by schema reference with negative case.
match(Object/Array types[, Object instance]) iterates through an object or array to match appropriate schema for given argument. Executes found function. Returns undefined if not found.
find(Object/Array types[, Object instance]) iterates through an object or array to find appropriate schema for given argument. Returns undefined if not found.
filter(Object/Array types[, Object instance]) iterates through an object or array to filter appropriate schemas for given argument. Returns Array with values.
env original environment