chance

What is chance?

The Chance npm package is a minimalist generator of random strings, numbers, and other utilities. It is designed to help developers create random data for testing, simulations, and more. The package offers a wide range of functionalities, from generating random names, addresses, and phone numbers to creating random numbers, characters, and even custom random generators.

What are chance's main functionalities?

Basic Random Data Generation

This feature demonstrates how to generate basic random data such as names and integers. The 'name' method generates a random full name, while the 'integer' method generates a random integer within a specified range.

const Chance = require('chance');
const chance = new Chance();

// Generate a random name
console.log(chance.name());

// Generate a random integer
console.log(chance.integer({min: 0, max: 100}));

Advanced Random Data Generation

This feature showcases the generation of more complex data types like addresses and geo-coordinates. The 'address' method returns a random address, and the 'coordinates' method returns a random latitude and longitude pair.

const Chance = require('chance');
const chance = new Chance();

// Generate a random address
console.log(chance.address());

// Generate a random geo-coordinate
console.log(chance.coordinates());

Custom Random Data Generation

This feature illustrates how to create custom random data generators using Chance. In this example, a simple dice roll function is created that returns a random integer between 1 and 6.

const Chance = require('chance');
const chance = new Chance();

// Custom random generator for a dice roll
function diceRoll() {
  return chance.integer({min: 1, max: 6});
}

console.log(diceRoll());

Other packages similar to chance

faker

Faker is a popular alternative to Chance that focuses on generating massive amounts of fake data, especially for testing purposes. It supports a wide range of data types similar to Chance but also includes locales for generating data in specific languages and formats.

random-js

Random-js is a mathematically correct random number generator library for JavaScript. It offers a lower-level approach compared to Chance, providing tools to generate random values using various distributions. It's more suited for simulations and games that require specific random behavior.

README

Chance

Chance - Random generator helper for JavaScript

Homepage: http://chancejs.com

Many more details on http://chancejs.com but this single library can generate random numbers, characters, strings, names, addresses, dice, and pretty much anything else.

It includes the basic building blocks for all these items and is built on top of a Mersenne Twister so it can generate these things with repeatibility, if desired.

Usage

Browser

Chance instantiates itself onto the window. This means that in the simplest case you can just include the script tag then use an instance of Chance immediately.

<script src="chance.js"></script>
<script>
    console.log(chance.string());
</script>

More info

Bower

It can also be used with Bower

bower install chance

then in the HTML of your app:

<!-- Load Chance -->
<script type="text/javascript" src="components/chance/chance.min.js"></script>
<script>
    // Use Chance immediately!
    alert(chance.string());
</script>

RequireJS

Chance also includes an AMD define so it can be used with RequireJS.

require(['Chance'], function(Chance) {
    // Instantiate
    var chance = new Chance();
   
    // Then just use it:
    var my_random_integer = chance.integer();
});

Node.js

And it can be used in Node.js.

var Chance = require('chance'),
    chance = new Chance();
    
// Get a random zip code
chance.zip();

Author

Victor Quinn

http://victorquinn.com

Please feel free to reach out to me if you have any questions or suggestions.

Contributors

THANK YOU!

 project  : chancejs
 repo age : 6 weeks
 active   : 35 days
 commits  : 186
 files    : 19
 authors  :
   140	Victor Quinn            75.3%
    11	Tim Petricola           5.9%
    11	davmillar               5.9%
     5	Matt Klaber             2.7%
     5	Michael Cordingley      2.7%
     3	qjcg                    1.6%
     2	dhilipsiva              1.1%
     2	Kevin Garnett           1.1%
     2	path411                 1.1%
     2	Andreas Koeberle        1.1%
     1	Richard Anaya           0.5%
     1	leesei                  0.5%
     1	Ryan Tenney             0.5%

This project is licensed under the MIT License so feel free to hack away :)