mocking_g v0.2.22

GEN

Intro

In Short

An advanced tool for creating mocked data for server and client.

In Several More Words

A very powerful and flexible framework that allows defining and generating mocked data easily and quickly. The framework is a generic one, and can be extended programmatically with new types. It is used by firstly creating a schema for our data, and then generating as many instances from that schema as needed.

Installation

    npm i mocking_g

Usage

• Just include the library in your project:

    const gen = require('mocking_g');

• Mocking GEN UI will run on localhost on port 5588

• Generate your data like so:

const library = 'examples';
const schema = 'person';
const persons = gen.generate([library,schema], 10);

Or just

const persons = gen.generate('examples.person', 10);

Terminology

• Library - a logical layer for separation of schemas.
• Schema - a JSON schema that describes our data. We can create schemas using the UI or programmatically as shown below.
• Type - Schemas are consisted from types. There are built-in types in the library, but we can define new types as shown below as well.

Examples

An example for a person schema can be something like that:

{
  "uuid": {
    "type": "id"
  },
  "firstName": {
    "type": "firstName"
  },
  "lastName": {
    "type": "lastName"
  },
  "birthDate": {
    "type": "pastDate",
    "value": {
      "dateMask": "DD-MM-YYYY",
      "years": 50
    }
  },
  "country": {
    "type": "country"
  },
  "streetName": {
    "type": "streetName"
  },
  "zipCode": {
    "type": "zipCode"
  },
  "email": {
    "type": "email"
  },
  "company": {
    "type": "company"
  },
  "jobTitle": {
    "type": "jobTitle"
  }
}

While the generated data can be something like this:

{
    "uuid": "7f30a631-12c9-42a1-ad2d-a641b85a5647",
    "firstName": "Scot",
    "lastName": "Goodwin",
    "birthDate": "11-01-2008",
    "country": "Palau",
    "streetName": "O'Connell River",
    "zipCode": "66932-6018",
    "email": "Marlon.Marquardt@example.org",
    "company": "Altenwerth, Waelchi and Ledner",
    "jobTitle": "Lead Markets Analyst"
  }

Features

• Generate

It is possible to generate data from a schema created programmatically:

const schema = {
    name: { type: 'firstName' },
    age: { type: 'number' }
}

const generated = gen.generate(schema, 10);

Or use the intuitive GEN UI and create schemas effortlessly. Then, just reference the schema and generate your data:

gen.generate('examples.person', 10);

You can set the path on which GEN will save your schemas. In addition, GEN will use this path to load the schemas on startup.

gen.schemas.setPath('C:/your/path/to/folder');

• Types

Get existing types by:

gen.types.getTypes()

Or

gen.types.getTypesArrangeByGroups() // types belong in a "group"

You can also create your own types programmatically:

const myRandomNumberType = {
    randomNumber: {
        name: "Random Number",
        generate: (element) => {
            return Math.random();
        },
        group: 'new group'
    }
}

gen.types.addTypes(myRandomNumberType);

• Libraries

As explained earlier, libraries are just logical layers that can contain your schemas. GEN supports various CRUD operations on libraries, few of them are:

gen.schemas.getAllLibraries();
gen.schemas.removeLibrary(libraryName);
gen.schemas.addLibrary(libraryName);

CLIENT usage

• Use a standard get request

axios.get('http://localhost:5588/mocking_G/generate', { library: 'examples', category: 'person', amount: 5 }).then((res)=>{
    console.log(res.data);
})

Or directly from a url

http://localhost:5588/mocking_G/generate?library=examples&category=person&amount=3

Coming soon

• Docs and improvements