@mnovo323/mrandom

mrandom - Python's Random for Node.js

mrandom is a Node.js module inspired by Python's built-in random module. It's designed to bring the power and flexibility of Python's random number utilities to the TypeScrpt/JavaScript ecosystem. It is built for both ESM and CommonJS.

Features

• Python-inspired Interface: If you're familiar with Python's random, you'll feel right at home.
• Diverse Range of Distributions: Easily generate numbers from uniform, normal, binomial, and more distributions.
• Simple Usage: All utilities accessible from a single import.
• High Performance: Designed to deliver random numbers swiftly, even in bulk.
• Flexible Seed Management: Control the randomness by setting your own seeds.

Installation

npm install @mnovo323/mrandom

Usage

Basic Example

import random from '@mnovo323/mrandom';

const randNumber = random.random();
const randInt = random.randint(1, 10);
const choice = random.choice([1, 2, 3, 4, 5]);

console.log(randNumber); // e.g., 0.123456789
console.log(randInt);    // e.g., 7
console.log(choice);     // e.g., 3

Advanced Example

import { randint } from '@mnovo323/mrandom/randint';
import { choice } from '@mnovo323/mrandom/choice';
import { seed } from '@mnovo323/mrandom/xoshiro128plus';
import { gauss } from '@mnovo323/mrandom/gauss';
import { expovariate } from '@mnovo323/mrandom/expovariate';

// Setting the seed
seed(42);

// Generating random numbers
const randInt = randint(1, 10);
const randChoice = choice([1, 2, 3, 4, 5]);
const randNorm = gauss(0, 1);
const randExp = expovariate(1.5);

console.log(randInt);     // e.g., 7
console.log(randChoice);  // e.g., 3
console.log(randNorm);    // e.g., 0.123456789
console.log(randExp);     // e.g., 0.789012345

Available Functions

• random()
• seed(value)
• getstate()
• setstate(state)
• betavariate(alpha, beta)
• choice(sequence)
• choices(sequence, k)
• expovariate(lambda)
• gammavariate(alpha, beta)
• gauss(mu, sigma)
• getrandbits(k)
• lognormvariate(mu, sigma)
• randbytes(n)
• randint(a, b)
• randrange(start, stop, step)
• sample(population, k)
• shuffle(sequence)
• triangular(low, high, mode)
• uniform(a, b)
• xoshiro128plus()

Coming Soon

• vonmisesvariate(mu, kappa)
• paretovariate(alpha)
• weibullvariate(alpha, beta)

Contribution

Contributions are always welcome! If you'd like to help implement the above functions or improve the existing ones, please raise a pull request.

License

MIT