Benchmark: lodash vs fakerFork random

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>
<script src='https://cdn.jsdelivr.net/npm/mersennetwister@0.2.3/src/MersenneTwister.min.js'></script>

Script Preparation code:

const mt = new MersenneTwister();
const randomInt = (max, min) => {
    const _max = max ?? 32768;
    const _min = min ?? 0;
    return mt.rnd() * (_max - _min) + _min;
};
const randomNumber = ({
    min: _min,
    max: _max,
    precision: _precision,
}) => {
    const min = _min || 0;
    let max = _max || 99999;
    const precision = _precision || 1;
    if (max >= 0) {
        max += precision;
    }

    let randomNumber = Math.floor(randomInt(max / precision, min / precision));
    randomNumber /= 1 / precision;

    return randomNumber;
};

// tests
window.testLodash = () => {
    for (let i = 0; i < 5000; i++) {
        _.random(0, i);
    }
}

window.testFakerFork = () => {
    for (let i = 0; i < 5000; i++) {
        randomNumber({
            min: 0,
            max: i
        });
    }
}

Tests:

_.random
window.testLodash()
randomNumber
window.testFakerFork()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.random
randomNumber

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Overview**

MeasureThat.net provides a web-based platform for comparing the performance of different JavaScript libraries and implementations. The provided benchmark tests two individual test cases: `_.random` from Lodash and `randomNumber` from FakerFork.

**What is being compared?**

The main difference between the two test cases lies in how they generate random numbers.

1. **Lodash's _.random()**: This function uses a pseudo-random number generator (PRNG) to produce a random number within a specified range.
2. **FakerFork's randomNumber()**: This function is designed to mimic the behavior of a Mersenne Twister, which is a widely used PRNG algorithm. It takes into account factors like precision and scale.

**Options compared**

The two functions have different approaches:

1. **Lodash's _.random()**: Uses a simple PRNG with a fixed seed (in this case, a Mersenne Twister). The function returns an integer value between 0 and the specified range.
2. **FakerFork's randomNumber()**: Also uses a PRNG (Mersenne Twister), but with more features:
	* Precision control: allows for fractional numbers
	* Scale control: can produce large or small numbers

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Lodash's _.random()**:
	* Pros: simple, fast, and easy to implement
	* Cons: may not be suitable for applications requiring high-quality randomness (e.g., cryptography)
2. **FakerFork's randomNumber()**:
	* Pros: offers more control over precision and scale, making it suitable for applications where fractional numbers or large/small values are required
	* Cons: more complex, slower due to the additional calculations

**Library/Implementation Notes**

1. **Lodash**: A popular JavaScript utility library that provides a wide range of functions for common tasks.
2. **FakerFork**: A JavaScript implementation of the Mersenne Twister PRNG algorithm. It's designed to be fast and efficient, while also offering more control over the random number generation process.

**Special JS Features/Syntax**

The benchmark doesn't specifically mention any special JavaScript features or syntax. However, it does use the `window.test` object to define test cases, which is a common pattern in browser-based testing.

**Alternatives**

If you're looking for alternatives to these libraries, here are some options:

1. **Math.random()**: The built-in JavaScript function for generating random numbers.
2. **Crypto.getRandomValues()**: A more secure way of generating cryptographically strong random numbers.
3. **Other PRNG implementations**: Such as the `random-js` library or the `Crypto-JS` library, which offer different approaches to PRNG-based random number generation.

Keep in mind that these alternatives may have different performance characteristics and use cases compared to Lodash and FakerFork.

Related benchmarks:

lodash vs fakerFork random (version: 0)

Comparing performance of: _.random vs randomNumber

Created: 4 years ago by: Guest

Jump to the latest result

_.random

randomNumber

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):