<b>An advanced tool for creating mocked data for server and client.</b>
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.
npm i mocking_g
- 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);
* 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.
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"
}
* 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);
- 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