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model-mock

v1.3.4

Published

**ModelMock** is a generic class designed to generate mock data based on a provided data model. It uses data containing names, addresses, cities, streets, job, colors,email , credit card numbers and others to populate the model fields, creating realistic

Downloads

1,168

Readme

ModelMock - Mock Data Generator

ModelMock is a generic class designed to generate mock data based on a provided data model. It uses data containing names, addresses, cities, streets, job, colors,email , credit card numbers and others to populate the model fields, creating realistic datasets for testing and prototyping.

Features

  • Realistic Data Injection : ModelMock loads data from JSON files, including names, addresses, cities, streets, etc.
  • Random generation : Creates random values ​​for different data types (string, number, boolean, Date).
  • Flexible and extensible :Compatible with any data model.

You can download these files from our Git repository and place them in assets/data of your project.

Installation

  1. Install the library in your Angular project:

    npm install model-mock
    

To use the ModelMock class, follow these steps:

  1. Create a data model - Define a data model that will represent the structure of your object. For example:

    interface UserModel {
      name: string;
      age: number;
      address: string;
      city: string;
      street: string;
      credit_card: string;
    }
  2. Initialize a ModelMock instance Create an instance of the ModelMock class by passing it the model data, then retrieve mock data by calling the get method:

import { ModelMock } from "model-mock";

// Example of an empty user model
const userData: UserModel = {
  name: "",
  age: 0,
  address: "",
  city: "",
  street: "",
  credit_card: ""
};

// Create an instance of ModelMock
const mock = new ModelMock<UserModel>(userData);

// Retrieve the dummy data
const mockData = mock.dataList;
console.log(mockData);

Possible uses

ModelMock can be used for:

  • Test user interfaces: Generates realistic data, allowing to test interfaces without depending on a database.

  • Automated Test Report Generation: Creates varied scenarios to validate test cases.

  • Rapid Prototyping: Provides consistent data for demonstrations and early development phases.

Main methods

  • dataList : Retrieves a array of generated mock data.
  • dataListReadOnly : Retrieves a readonly array of generated mock data..
  • getKeys : Generates an array of keys from the data model.