schematics

Declarative data structure validation for Javascript.

Download/install

- Download schematics.js
- Install via NPM: npm install schematics
- Install via Bower: bower install schematics

Overview

Validating data in JavaScript is often a tedious process involving lots of conditional checks and resulting in functions that can be hard to read and that have high cyclomatic complexity.

schematics aims to alleviate this by providing an interface that allows you to describe your data structure declaratively and then check your data against it afterwards.

Each validation step can return a promise, so checks with a database or similar async processes can be integrated. Currently Bluebird is used for promises.

A brief example:

``js
var s = require("schematics");

// declare a schema for objects with numeric x and y properties
// don't allow NaN, Infinity, etc. values for the numbers
var pointSchema = s.obj({
x: s.num().isReal(),
y: s.num().isReal()
});

// run returns a promise, as the validation steps may also be promisified
pointSchema.run({ x: 10, y: 20 })
.then(function (result) {
if (result.valid) {
console.log("That certainly looks like a point!")
} else {
console.log("Something went horribly wrong.");
}
});
`

When validation fails the error value is returned "structurally" so the exact place the error occurred is known. This is useful when validating JSON values that have been POSTed to an endpoint.

For example, the following invalid point value:

`js
pointSchema.run({ x: 10, y: Infinity })
.then(function (result) {
console.log(result);
})
`

Will print:

`js
{
valid: false,
why: {
x: {
valid: true
},
y: {
valid: false,
msg: "Number is not a real"
}
}
}
`

$3

The functions belonging to the schematics object like obj, num, bool create a _schema_.

We add _rules_ to a schema using functions like nonEmpty, isReal, pattern.

A rule returns a _step_ when the schema is run. A step is a function that accepts the value to test, and returns a validation result object of the form { valid: bool, ... }.

API

$3

#### schematics.bool()

Creates a schema for Boolean types.

#### schematics.num()

Creates a schema for Number types.

A num schema can be extended with the following rules:

- .min(n) specifies the minimum allowed value for the number.
- .max(n) specified the maximum allowed value for the number.
- .isReal() ensures the number is finite and not NaN.

#### schematics.str()

Creates a schema for String types.

A str schema can be extended with the following rules:

- .nonEmpty() specified that the string must not be empty.
- .pattern(rx) specifies a regular expression pattern the string must meet.
- .enum([values]) specifies a range of acceptable values for the string.

#### schematics.nil()

Creates a schema for null or undefined types. This is probably only useful when used with or.

#### schematics.date()

Creates a schema for Date types.

A date schema can be extended with the following rules:

- .valid() specifies that a date value must not be Invalid Date.

#### schematics.obj(props)

Creates a schema for Object types. The props argument can either be left empty if only the type check is required, or an object with enumerable keys, where each key have a schema associated with it, and the properties of the object will be checked against these schemas.

#### schematics.arr(schema)

Creates a schema for Array types. The schema argument can either be left empty if only the type check is required, or a schema that will be run against each value of the array.

A arr schema can be extended with the following rules:

- .nonEmpty() specified that the array must not be empty.

#### schematics.or(s1, s2)

Creates a schema that joins two schemas and accepts either of them passing.

#### schematics.msg(msg, s)

Creates a schema that allows custom error messages to be specified. When s fails, the resulting object will use the custom msg.

$3

Schemas can be extended with new rules by using the .extend(stepDefs) function. stepDefs is an object containing step function definitions, with keys as the names of the new rules:

`js
var s = require("schematics");

// add an isPositive rule to the schema
var myNumSchema = s.num().extend({
isPositive: function () {
return function (value) {
return value >= 0 ? { valid: true } : { valid: false, msg: "Value is negative" };
};
}
});

// the isPositive rule is now usable at any point in the rule chain
myNumSchema.isReal().isPositive().run(42)
.then(function (result) {
console.log(result);
});
`

Each value in stepDefs should be a function that returns a step-style function - one that accepts the value to validate and returns an object of the form { valid: bool, ... }.

Note: When extending the rules of a schema this does not modify the existing schema, it returns a copy of the current schema with the newly added rule:

`js
var s = require("schematics");

var numSchema = s.num();

var myNumSchema = numSchema.extend({
isPositive: function () { / ... / }
});

console.log(numSchema.isPositive) // undefined
console.log(myNumSchema.isPositive) // [Function]
`

Compatibility

Currently schematics` has only been tested for Node.js, but should also work in any browser that supports ES5. ES3 support and better test coverage coming soon.