data-model

Javascript data schemas. Validate data structures, ensure data types, assign virtual methods, generate virtual properties for a data set.

Installing

Via Bower

bash
bower install data-model --save


Via NPM

bash
npm install data-model --save


If you are using Node.js

javascript
var datamodel = require('data-model');


Creating a Dataset Model

The dataset schema is to define what the expected format of a dataset is to be. There are three patterns that are used: Collections, Schemas (and nested schemas), and primitives. Further, there are two ways to define a schema: Caching, or instance.
Primitive Pattern

Primitives are the most basic element, and end recursive checks. You use primitives to define the type pattern required for proper use.
$3

javascript
datamodel('personName')
.setTemplate(String);

$3

javascript
datamodel('personName')
.setTemplate([String]);

$3

javascript
datamodel('personName')
.setTemplate([{ name:String }]);


Schema Pattern

A schema definition has a similar meaning to what what is understood as the Object javascript primitive. It is a definition of a key/value data structure, and uses the Object primitive syntax for defining the pattern. Nested schemas are supported for complex objects.
$3

javascript
datamodel('person')
.setTemplate({
	name:String,
	age:Number
});

$3

javascript
datamodel('person')
.setTemplate({
	name:String,
	details:{
		age:Number
	}
});



Collection Pattern

A collection defines repetition in a data set. The collection is denoted with the array primitive syntax.
$3

javascript
datamodel('pageHits')
.setTemplate([{
	name:String,
	hits:[Number]
}]);

$3

javascript
datamodel('myHits')
.setTemplate({
	name:String,
	hits:[Number]
});


Validating Against Models

Examples
$3

javascript
datamodel('personName')
.setTemplate(String);
var ValidData = "Jordan";
var InvalidData = 23; //wrong type...
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('personName')
.setTemplate([String]);
var ValidData = ["Jordan", "Chapian"];
var InvalidData = [23, "Jordan"]; //wrong type
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('personName')
.setTemplate([{name:String}]);
var ValidData = [{name:"Jordan"}, {name:"Chapian"}];
var InvalidData = [{name:"Jordan"}, "Jordan"]; //wrong type
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('person')
.setTemplate({
	name:String,
	age:Number
});
var ValidData = {name:'Jordan', age:10};
var InvalidData = {name:'Jordan'}; //missing age..
datamodel('person')
.validate(ValidData); //true

datamodel('person') .validate(InvalidData); //false`

`$3`

javascript
datamodel('person')
.setTemplate({
	name:String,
	details:{
		age:Number
	}
});
var ValidData = {name:'Jordan', details:{age:10}};
var InvalidData = {name:'Jordan', details:{age:"10"}}; //age, wrong type..
datamodel('person')
.validate(ValidData); //true

datamodel('person') .validate(InvalidData); //false`

`$3`

javascript
datamodel('pageHits')
.setTemplate([{
	name:String,
	hits:[Number]
}]);
var ValidDataset = [{name:"Jordan", hits:[5,7,6]}, {name:"Chapian", hits:[]}];
var InvalidDataset = [{name:"Jordan", hits:["5", 7, 6]}, {name:"Chapian", hits:[8]}];
datamodel('pageHits')
.validate(ValidDataset); //true

datamodel('pageHits') .validate(InvalidDataset); //false`

`$3`

javascript
datamodel('myHits')
.setTemplate({
	name:String,
	hits:[Number]
});
var ValidDataset = {name:"Jordan", hits:[5, 10, 15, 20]};
var InvalidDataset =  {name:"Jordan", hits:12};
datamodel('myHits')
.validate(ValidDataset); //true

datamodel('myHits') .validate(InvalidDataset); //false`

`Internal Representation`


A graph is used to represent a data structure, where each node is represented by one of three subclasses of a TemplateNode. Recursive patterns are used to traverse the structures. Consider the below model specification.

`javascript datamodel('users') .setTemplate([{ name:String, email:String, posts:[{ title:String, views:Number, body:Number, posted:Date }], loginPosts:[[Number]] }]);``

This is represented by the following graph structure:

!gs

data-model

Javascript data schemas. Validate data structures, ensure data types, assign virtual methods, generate virtual properties for a data set.

Installing

Via Bower

bash
bower install data-model --save


Via NPM

bash
npm install data-model --save


If you are using Node.js

javascript
var datamodel = require('data-model');


Creating a Dataset Model

The dataset schema is to define what the expected format of a dataset is to be. There are three patterns that are used: Collections, Schemas (and nested schemas), and primitives. Further, there are two ways to define a schema: Caching, or instance.
Primitive Pattern

Primitives are the most basic element, and end recursive checks. You use primitives to define the type pattern required for proper use.
$3

javascript
datamodel('personName')
.setTemplate(String);

$3

javascript
datamodel('personName')
.setTemplate([String]);

$3

javascript
datamodel('personName')
.setTemplate([{ name:String }]);


Schema Pattern

A schema definition has a similar meaning to what what is understood as the Object javascript primitive. It is a definition of a key/value data structure, and uses the Object primitive syntax for defining the pattern. Nested schemas are supported for complex objects.
$3

javascript
datamodel('person')
.setTemplate({
	name:String,
	age:Number
});

$3

javascript
datamodel('person')
.setTemplate({
	name:String,
	details:{
		age:Number
	}
});



Collection Pattern

A collection defines repetition in a data set. The collection is denoted with the array primitive syntax.
$3

javascript
datamodel('pageHits')
.setTemplate([{
	name:String,
	hits:[Number]
}]);

$3

javascript
datamodel('myHits')
.setTemplate({
	name:String,
	hits:[Number]
});


Validating Against Models

Examples
$3

javascript
datamodel('personName')
.setTemplate(String);
var ValidData = "Jordan";
var InvalidData = 23; //wrong type...
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('personName')
.setTemplate([String]);
var ValidData = ["Jordan", "Chapian"];
var InvalidData = [23, "Jordan"]; //wrong type
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('personName')
.setTemplate([{name:String}]);
var ValidData = [{name:"Jordan"}, {name:"Chapian"}];
var InvalidData = [{name:"Jordan"}, "Jordan"]; //wrong type
datamodel('personName')
.validate(ValidData); //true

datamodel('personName') .validate(InvalidData); //false`

`$3`

javascript
datamodel('person')
.setTemplate({
	name:String,
	age:Number
});
var ValidData = {name:'Jordan', age:10};
var InvalidData = {name:'Jordan'}; //missing age..
datamodel('person')
.validate(ValidData); //true

datamodel('person') .validate(InvalidData); //false`

`$3`

javascript
datamodel('person')
.setTemplate({
	name:String,
	details:{
		age:Number
	}
});
var ValidData = {name:'Jordan', details:{age:10}};
var InvalidData = {name:'Jordan', details:{age:"10"}}; //age, wrong type..
datamodel('person')
.validate(ValidData); //true

datamodel('person') .validate(InvalidData); //false`

`$3`

javascript
datamodel('pageHits')
.setTemplate([{
	name:String,
	hits:[Number]
}]);
var ValidDataset = [{name:"Jordan", hits:[5,7,6]}, {name:"Chapian", hits:[]}];
var InvalidDataset = [{name:"Jordan", hits:["5", 7, 6]}, {name:"Chapian", hits:[8]}];
datamodel('pageHits')
.validate(ValidDataset); //true

datamodel('pageHits') .validate(InvalidDataset); //false`

`$3`

javascript
datamodel('myHits')
.setTemplate({
	name:String,
	hits:[Number]
});
var ValidDataset = {name:"Jordan", hits:[5, 10, 15, 20]};
var InvalidDataset =  {name:"Jordan", hits:12};
datamodel('myHits')
.validate(ValidDataset); //true

datamodel('myHits') .validate(InvalidDataset); //false`

`Internal Representation`


A graph is used to represent a data structure, where each node is represented by one of three subclasses of a TemplateNode. Recursive patterns are used to traverse the structures. Consider the below model specification.

`javascript datamodel('users') .setTemplate([{ name:String, email:String, posts:[{ title:String, views:Number, body:Number, posted:Date }], loginPosts:[[Number]] }]);``

This is represented by the following graph structure:

!gs