Benchmark: Lodash vs. Native (remove/filter)

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.21/lodash.min.js"></script>

Script Preparation code:

const limit = 10000000;
var array = [];

for (let i = 0; i < limit; i++) {
  array.push(i);
}

function getRandomIndex() {
  return Math.floor(Math.random() * array.length)
}

var element = array[getRandomIndex()];

Tests:

Native
array.filter(x => x === element);
Lodash
_.remove(array, x => x === element);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 days ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/147.0.0.0 Safari/537.36 Edg/147.0.0.0

Browser/OS: Chrome 147 on Windows

View result in a separate tab

Test name	Executions per second
Native	11.5 Ops/sec
Lodash	95.5 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**Benchmark Overview**

The benchmark is designed to compare the performance of two approaches: using native JavaScript (`array.filter(x => x === element)`) and using the Lodash library (`_.remove(array, x => x === element)`). The benchmark creates a large array with 10 million elements, randomly selects an element from it, and then filters or removes all occurrences of that element.

**Options Compared**

The benchmark compares two options:

1. **Native JavaScript**: This approach uses the built-in `Array.prototype.filter()` method to remove all occurrences of the selected element.
2. **Lodash**: This approach uses the Lodash library's `_.remove()` function to achieve the same result.

**Pros and Cons**

**Native JavaScript:**

Pros:

* Fastest execution time, as it leverages the optimized native implementation of the `Array.prototype.filter()` method.
* Lightweight, as it only requires a single call to the `filter()` method.
* Easy to understand and use for developers familiar with native JavaScript.

Cons:

* May require additional setup or imports if not already included in the project.
* Performance may vary depending on the specific browser or JavaScript engine used.

**Lodash:**

Pros:

* Convenient, as it provides a pre-built function (`_.remove()`) that can be easily imported and used.
* Well-tested and maintained by the Lodash community.
* Can simplify code for developers who are not familiar with native JavaScript implementations.

Cons:

* Slightly slower execution time compared to native JavaScript.
* Requires an additional import, which may add overhead.
* May require additional setup or configuration if not already included in the project.

**Library: Lodash**

Lodash is a popular JavaScript library that provides a collection of utility functions for tasks such as data manipulation, functional programming, and more. In this benchmark, Lodash's `_.remove()` function is used to remove all occurrences of an element from an array.

**Special JS Feature/ Syntax**

None mentioned in the provided benchmark.

**Other Alternatives**

For removing elements from an array, other alternatives could include:

* Using `Array.prototype.map()` and `Array.prototype.filter()`: This approach involves mapping the original array to create a new array with the desired element removed.
* Using `Array.prototype.forEach()` and `splice()`: This approach involves iterating over the array using `forEach()` and removing elements from the array using `splice()`.

However, these alternatives may not be as efficient or convenient as the native JavaScript implementation or Lodash's `_.remove()` function.

Related benchmarks:

Lodash vs. Native (remove/filter) (version: 0)

Comparing performance of: Native vs Lodash

Created: 5 years ago by: Registered User

Jump to the latest result

Native

Lodash

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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