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.
- Faker: we use the Faker API to create fake data
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-
Write a
.jsonmodel in themodelsdirectory. Article Example -
Run the
generatescript 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 yourmodel.jsonfile. - 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- Write a model as explained before. It can be a
.jsonfile or a javascriptObject - Use it in your own module
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. ForobjectinputType values, modelArg behaves like a javascript object, where the model should be defined. - Required
fileName:
- Type:
String - Description when inputType is
jsonfileName 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
requiredorimporton a.jsonfile the returned value behaves like a javascript Object.
-
Create a
modelsdirectory, anoutputdirectory and write a.jsonmodel as explained before.mkdir models mkdir output
-
Run the global npm bin script.
fake-data-generator example 10 example.json
-
Type: (optional)
Object -
Details: general configuration.
-
Properties:
- locale: language used for
faker.locale.
- locale: language used for
-
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.
-
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).
- type one of fake-data-generator types. Example:
- attributeName an attribute of your model. Example:
A valid format would be an object with the following keys:
- type
- value
- options (optional)
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"
}
} 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"]
}
}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"
}
}
}
}
}
}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]
}
}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"
}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"]
}Just another version of randomNumberBetween that accepts a range of numbers, a prefix as a string and a suffix as a string
options:
prefix: Stringa value to be interpolated as the number prefixsuffix: Stringa value to be interpolated as the number suffix
{
"publication": {
"type": "randomNumberBetweenWithString",
"value": [1, 2500000],
"options": {
"prefix": "#",
"suffix": "*"
}
}
}You can get incremental numbers based on the given amount for a model
The
valueattribute is ignored
options:
from: Numberstarts incrementing from a given number
{
"brownies": {
"type": "incrementNumber",
"options": {
"from": 420
}
}
}Output using an amount of 3:
[
{
"brownies": 420
},
{
"brownies": 421
},
{
"brownies": 422
},
]Defines an Array of elements to be created with the same type.
options
size: NumberHow many objects to create. Required, is mutually exclusive with size:Arraysize: ArrayA 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"
}
}
}
}
}
}
}Adds a fixed String in front of another dynamic value generated by one of the other datatypes.
options
text: StringThe text to be prepended. required
{
"issue": {
"type": "prepend",
"options": {"text": "#"},
"value": {
"type": "randomNumberBetween",
"value": [1, 2500]
}
}
}Adds a fixed String at the back of another dynamic value generated by one of the other datatypes.
options
text: StringThe text to be appended. required
{
"fileName": {
"type": "append",
"options": {"text": ".pdf"},
"value": {
"type": "faker",
"value": "random.words"
}
}
}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.
GNU General Public License version 3
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