Fake Data Generator

Introduction

This is a tiny package motivated by the need of generating certain amount of fake data to populate backend fixtures. We started implementing and editing a single .js file with specific characteristics of some backend models and the desired amount we wanted to generate until we ended up with something like this. We personally decided to use the output files in the API endpoints of a test server but you could use them any way you like, they're just .json files.

Built-In Dependencies

• Faker: we use the Faker API to create fake data

Installation

There are a few ways you can get this library installed:

• Install as a standalone forked repository

# clone our project or fork your own
git clone https://github.com/Cambalab/fake-data-generator.git
# install dependencies
npm install

• Install as an npm dependency for your own project

# install it as a dependency or dev-dependency of our own project
npm install --save-dev fake-data-generator

• Use it globally from a terminal

# install it globally
npm install -g fake-data-generator

Usage

Usage from a forked or cloned repository

1. Write a .json model in the models directory. Article Example

2. Run the generate script from a terminal

The following command writes a .json file with an array of 50 elements to the output directory, where:

• 1st param example: is the name of your model.json file.
• 2nd param 10: the numbers of models to generate.
• 3rd param example.json: the name of the output file.

npm run generate example 50 example.json

Output Example

Usage as an npm dependency

1. Write a model as explained before. It can be a .json file or a javascript Object
2. Use it in your own module

Params description

amountArg:

• Type: Number
• Description: describes how many elements should be created from a given model
• Required

modelArg:

• Type: Object | Json file
• Description: when inputType param is json, modelArg behaves as a file path to that json file. For object inputType values, modelArg behaves like a javascript object, where the model should be defined.
• Required

fileName:

• Type: String
• Description when inputType is json fileName will describe the output path where the file will be writen to.

inputType:

• Type: String
• Options: object | json
• Description: describes the kind of input the generator will receive and read the model from.

outputType:

• Type: String
• Options: object | json
• Description: describes the kind of output the generator will write or return.

// Requires the package
const { generateModel } = require('fake-data-generator')
// Requires a model
const model = require('./models/example.json')
// Generate the model
const amountArg = 50
const modelArg = model
const inputType = 'object'
const outputType = 'object'
const generatedModel = generateModel({ amountArg, modelArg, inputType, outputType })

Note that when using required or import on a .json file the returned value behaves like a javascript Object.

Usage as a global npm dependency

1. Create a models directory, an output directory and write a .json model as explained before.

   mkdir models
   mkdir output

2. Run the global npm bin script.

   fake-data-generator example 10 example.json

Models Format

config

• Type: (optional) Object

• Details: general configuration.

• Properties:

  • locale: language used for faker.locale.

amount

• Type: (optional) Number

• Details: an amount of objects to generate.

When this value is present, the amount value given from a cli or the generateModel function from the npm package is overwritten.

model

• Type: Object

• Details: A declaration of your object model

• Properties:

  • attributeName an attribute of your model. Example: id
    • type one of fake-data-generator types. Example: faker, randomNumberBetween, Object, Array.
    • value a value corresponding to the specified type.
    • options configuration options for the specified type (required by some types).

Types and Values

A valid format would be an object with the following keys:

• type
• value
• options (optional)

faker

Currently the script supports faker methods that return Date, String or Number data only. It's not ready to handle faker methods that receive arguments yet.

If you're not familiar with faker, take a look at their docs, it's really simple to use.

Any other faker method can be used in the value attribute like this:

suppose we want to generate a company attribute with faker, then we would declare in the model:

{
  "company": {    
    "type": "faker",
    "value": "company.companyName"
  }
}  

Literal

This is simply a pass-through for those occasions when a known value is desired.

value: any

Case with a String

{
  "operating_system": {    
    "type": "Literal",
    "value": "Linux"
  }
}

Case using an Array of elements

{
  "resources": {    
    "type": "Literal",
    "value": ["memory", "disk", "network", "cpu"]
  }
}

Object

This is how the script knows we want to nest objects

say we want to declare a more complex company model:

value: Object an object with a type, value, options structure

{
  "company": {    
    "type": "Object",
    "value": {
      "name": {    
        "type": "faker",
        "value": "company.companyName"
      },
      "address": {
        "type": "Object",
        "value": {
          "street": {
            "type": "faker",
            "value": "address.streetAddress"
          },
          "city": {
            "type": "faker",
            "value": "address.city"
          },
          "state": {
            "type": "faker",
            "value": "address.state"
          }
        }
      }
    }
  }
}

Numbers

randomNumberBetween

The script provides a simple way to get a random number between a range of numbers

value: Array<Number> a range of values to compute the random number

{
  "timesIWatchedNicolasCageMovies": {
    "type": "randomNumberBetween",
    "value": [150, 2587655]
  }
}

randomElementInArray

The script provides a simple way to get a random element from an array of options.

value: Array a list of options to pick from.

{
  "whichMovieToWatchTonight": {
    "type": "randomElementInArray",
    "value": ["Frozen", "Mulan", "The Lion King", "Aladdin", "Pulp Fiction"]
  }
}

output

{
  "whichMovieToWatchTonight": "Pulp Fiction"
}

randomElementsInArray

This one returns a random group of elements from an array of options.

value: Array a list of options to pick from.

{
  "whichMoviesToWatchTonight": {
    "type": "randomElementsInArray",
    "value": ["Frozen", "Mulan", "The Lion King", "Aladdin", "Pulp Fiction"]
  }
}

output

{
  "whichMoviesToWatchTonight": ["Pulp Fiction", "Aladdin"]
}

randomNumberBetweenWithString

Just another version of randomNumberBetween that accepts a range of numbers, a prefix as a string and a suffix as a string

options:

• prefix: String a value to be interpolated as the number prefix
• suffix: String a value to be interpolated as the number suffix

{
  "publication": {
    "type": "randomNumberBetweenWithString",
    "value": [1, 2500000],
    "options": {
      "prefix": "#",
      "suffix": "*"
    }
  }
}

incrementNumber

You can get incremental numbers based on the given amount for a model

The value attribute is ignored

options:

• from: Number starts incrementing from a given number

{
  "brownies": {
    "type": "incrementNumber",
    "options": {
      "from": 420
    }
  }
}

Output using an amount of 3:

[
  {
    "brownies": 420
  },
  {
    "brownies": 421
  },
  {
    "brownies": 422
  },
]

Array

Defines an Array of elements to be created with the same type.

options

• size: Number How many objects to create. Required, is mutually exclusive with size: Array
• size: Array A two value array where the first value is the minimum number of entries and the second is the maximum. Required, is mutually exclusive with size: Number

Extending the company model a little further:

as a Number

{
  "company": {    
    "type": "Object",
    "value": {
      "name": {    
        "type": "faker",
        "value": "company.companyName"
      },
      "addresses": {
        "type": "Array",
        "options": {
          "size": 10
        },
        "value": {
          "type": "Object",
          "value": {
            "street": {
              "type": "faker",
              "value": "address.streetAddress"
            },
            "city": {
              "type": "faker",
              "value": "address.city"
            },
            "state": {
              "type": "faker",
              "value": "address.state"
            }
          }
        }
      }
    }
  }
}

as an Array

{
  "company": {    
    "type": "Object",
    "value": {
      "name": {    
        "type": "faker",
        "value": "company.companyName"
      },
      "addresses": {
        "type": "Array",
        "options": {
          "size": [5, 20]
        },
        "value": {
          "type": "Object",
          "value": {
            "street": {
              "type": "faker",
              "value": "address.streetAddress"
            },
            "city": {
              "type": "faker",
              "value": "address.city"
            },
            "state": {
              "type": "faker",
              "value": "address.state"
            }
          }
        }
      }
    }
  }
}

Concatenate

prepend

Adds a fixed String in front of another dynamic value generated by one of the other datatypes.

options

• text: String The text to be prepended. required

{
  "issue": {
    "type": "prepend",
    "options": {"text": "#"},
    "value": {
      "type": "randomNumberBetween",
      "value": [1, 2500]
    }
  }
}

append

Adds a fixed String at the back of another dynamic value generated by one of the other datatypes.

options

• text: String The text to be appended. required

{
  "fileName": {
    "type": "append",
    "options": {"text": ".pdf"},
    "value": {
      "type": "faker",
      "value": "random.words"
    }
  }
}

Contribution

Please make sure to read the Contributing Guide before submitting pull requests. There you'll find development environment instructions, common scripts and the project structure summary.

Feel free to open an issue if any faker method is not working as expcected or if you would like support for another data generator module.

License

GNU General Public License version 3