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https://github.com/hiddentao/sjv

:vertical_traffic_light: An easy-to-write schema and deep validator for JSON documents
https://github.com/hiddentao/sjv

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:vertical_traffic_light: An easy-to-write schema and deep validator for JSON documents

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# sjv

[![Build Status](https://secure.travis-ci.org/hiddentao/sjv.png)](http://travis-ci.org/hiddentao/sjv)

An easy-to-write yet powerful schema validator for objects.

## Features

* ES5-compatible, uses Promises
* Elegant, minimal syntax
* Comprehensive error reporting - all validation failures, not just first one
* Asynchronous custom validators
* [Type-matching](#type-matching)
* No other library dependencies (small browser footprint)

## Installation

**This package requires Node 4 or above**

```bash
$ npm install sjv
```

To use in the browser ensure you must have a working Promise implementation
(e.g. [bluebird](http://bluebirdjs.com/)) available at `window.Promise`.

## Usage

Here is a schema with all the possible field types:

```js
var schema = {
name: String, // shorthand for `{ type: String }`
isMarried: Boolean,
numCars: {
type: Number
},
born: {
type: Date
},
// any plain JS object with any keys
jobDetails: {
type: Object
},
// a simple array with any data
favouriteNumbers: {
type: Array
},
// a nested object which adheres to given schema
address: {
type: {
houseNum: {
type: Number
},
// value which must be one of given strings
taxBand: {
type: String,
enum: ['low', 'medium', 'high'],
},
},
},
// an array of nested objects which must adhere to given schema
children: {
type: [{
name: {
type: String,
// custom validators
validate: [
function(value) {
if ('john' === value) {
return Promise.reject(new Error('cannot be john'));
} else {
return Promise.resolve();
}
}
]
},
age: {
type: Number
}
}],
},
}
```

## Example

First we define the schema:

```js
var EmployeeSchema = {
name: {
type: String,
required: true
},
born: {
type: Date,
}
numChildren: {
type: Number,
},
address: {
type: {
houseNum: {
type: Number
},
street: {
type: String
},
country: {
type: String,
required: true
},
},
},
spouse: {
type: {
name: {
type: String,
required: true
}
}
},
};

var CompanySchema = {
name: {
type: String,
required: true
},
employees: {
type: [EmployeeSchema],
required: true
},
};
```

Now we can validate data against it:

```js
var schema = require('sjv')(CompanySchema);

schema.validate({
name: 'my company',
employees: [
{
name: 'john',
born: 'last year',
numChildren: 1,
address: {
houseNum: 12,
street: 'view road',
country: 'uk',
}
},
{
name: 'mark',
born: new Date(),
numChildren: null,
address: {
houseNum: 25,
street: 'view road'
},
spouse: {
name: 23,
age: 23
}
},
]
})
.catch(function(err) {

/*
Error: Validation failed
*/
console.log(err.toString());

/*
[
"/employees/0/born: must be of type Date",
"/employees/1/numChildren: must be a number",
"/employees/1/address/country: missing value",
"/employees/1/spouse/name: must be a string"
]
*/
console.log(err.failures);
});
```

### Type matching

When stringifying JSON you often lose type information (e.g. `Date` instances get converted to strings). When the stringified version gets parsed back into a JSON object you can use the `typeify()` function to help restore type information:

```js
var schema = {
name: {
type: String
},
isMarried: {
type: Boolean
},
numCars: {
type: Number
},
born: {
type: Date
}
};

var object = {
name: 'John',
isMarried: true,
numCars: 3,
born: new Date(2015,0,1)
}

var str = JSON.stringify(object);

/*
"{"name":"John","isMarried":true,"numCars":3,"born":"2014-12-31T16:00:00.000Z"}"
*/

var newObject = JSON.parse(str);

/*
{
name: 'John',
isMarried: true,
numCars: 3,
born: "2014-12-31T16:00:00.000Z"
}
*/

var typedObject = schema.typeify(newObject);

/*
{
name: 'John',
isMarried: true,
numCars: 3,
born: Date("2014-12-31T16:00:00.000Z")
}
*/
```

The type-ification process is quite tolerant of values. For example, for boolean values;

* `false` <- `"false"` or `"FALSE"` or `"no"` or `"NO"` or `"0"` or `0`
* `true` <- `"true"` or `"TRUE"` or `"yes"` or `"YES"` or `"1"` or `1`

To take the previous example again:

```js
var newObject = {
name: 'John'
isMarried: 'no'
numCars: '76'
born: '2014-12-31T16:00:00.000Z'
};

var typedObject = schema.typeify(newObject);

/*
{
name: 'John',
isMarried: false,
numCars: 76,
born: Date("2014-12-31T16:00:00.000Z")
}
*/
```

It is also smart enough to know when a conversion isn't possible. Instead of throwing an error it will simply pass through the original value.

Using the schema from our previous example:

```js
var newObject = {
name: null
isMarried: function() {}
numCars: false,
born: 'blabla'
};

var typedObject = schema.typeify(newObject);

/*
{
name: null,
isMarried: function() {}
numCars: false
born: 'blabla'
}
*/
```

You can limit type-ification to certain types only by setting the
`limitTypes` option:

```js
var newObject = {
name: 23,
isMarried: '0',
numCars: '3',
born: '2018-01-01'
};

var typedObject = schema.typeify(newObject, { limitTypes: [String]});

/*
{
name: '23',
isMarried: '0',
numCars: '3',
born: '2018-01-01'
}
*/
```

## Building

To run the tests:

$ npm install -g gulp
$ npm install
$ npm test

## Contributing

Contributions are welcome! Please see [CONTRIBUTING.md](https://github.com/hiddentao/sjv/blob/master/CONTRIBUTING.md).

## License

MIT - see [LICENSE.md](https://github.com/hiddentao/sjv/blob/master/LICENSE.md)