Benchmark: Lodash.js vs Native random

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var max1 = 100000; // 100,000 (100 Thousand)
var max2 = 10000000; // 10,000,000 (10 Million)
var max3 = 100000000; // 100,000,000 (100 Million)

var arr1 = [];
//for (var i = 0; i <= max1; i++) { arr1.push(i); }

var arr2 = [];
for (var i = 0; i <= max2; i++) { arr2.push(i); }

var arr3 = [];
//for (var i = 0; i <= max3; i++) { arr3.push(i); }

Tests:

Native
Math.floor(Math.random() * (101)) + 0;
Lodash.js filter
_.random(0, 100);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash.js filter

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:134.0) Gecko/20100101 Firefox/134.0

Browser/OS: Firefox 134 on Ubuntu

View result in a separate tab

Test name	Executions per second
Native	2670686720.0 Ops/sec
Lodash.js filter	50264144.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided JSON and explain what's being tested.

**Benchmark Definition**

The benchmark is comparing two approaches: using native JavaScript functions versus using the `lodash` library.

1. **Native**: This test case uses only native JavaScript functions, specifically the built-in `Math.random()` function.
2. **Lodash.js filter**: This test case uses the `lodash` library's `random(0, 100)` function to generate random numbers.

**Options Compared**

The two options being compared are:

* Native JavaScript functions (using `Math.random()`)
* The `lodash` library's `random(0, 100)` function

**Pros and Cons of Each Approach**

1. **Native**: Using native JavaScript functions has the advantage of:
	* No external dependencies or libraries to load.
	* Potential performance benefits due to direct access to the underlying browser engine.
However, it also has the disadvantage of:
	* Limited functionality compared to a dedicated library like `lodash`.
2. **Lodash.js filter**: Using the `lodash` library's `random(0, 100)` function has the advantage of:
	* More convenient and expressive syntax.
	* Access to a broader range of random number generation options (not limited to the simple `Math.random()` function).
However, it also has the disadvantage of:
	* Adding external dependencies and potential performance overhead due to library loading.

**Library: Lodash**

`Lodash` is a popular JavaScript utility library that provides a wide range of functions for tasks such as:
	* Array manipulation
	* Object manipulation
	* String manipulation
	* Math operations
	* Random number generation

The `random(0, 100)` function in particular generates a random integer between 0 and the specified upper bound (inclusive).

**Special JS Features/Syntax**

There are no special JavaScript features or syntaxes being used in this benchmark. Both test cases only use standard JavaScript functions and syntax.

**Other Alternatives**

If you're interested in alternative approaches to generating random numbers, some other options include:

* The ` crypto` module: This provides a secure way to generate cryptographically strong pseudo-random numbers.
* The ` Web Cryptography API`: This provides a more advanced way of generating random numbers and cryptographic keys.
* Other JavaScript libraries like `random-js`, `seeds-js`, or `fast-stochastic-async-pool`.

These alternatives may offer different trade-offs in terms of performance, security, and convenience compared to the native `Math.random()` function or the `lodash` library's `random(0, 100)` function.

Related benchmarks:

Lodash.js vs Native random (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 6 years ago by: Guest

Jump to the latest result

Native

Lodash.js filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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