Benchmark: Lodash.filter vs array.filter

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

function getRandomInt(max) {
  return Math.floor(Math.random() * Math.floor(max));
}

var arr = [];
for(var i = 0; i < 100000; i++){
  arr.push({value:getRandomInt(100)});
}

Tests:

lodash
_.filter(arr, a => a > 50);
arr
arr.filter(a => a >50);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
arr

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lodash	274.1 Ops/sec
arr	256.2 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 benchmark test for you.

**What is being tested?**

The provided JSON represents a JavaScript microbenchmark that tests two approaches to filtering an array: using Lodash's `filter` function and the built-in `array.filter` method.

**Options compared**

The two options being compared are:

1. **Lodash's `filter` function**: This approach uses the Lodash library, which provides a utility function for filtering arrays. The `filter` function takes an array and a predicate function as arguments, returning a new array containing only the elements that satisfy the predicate.
2. **Built-in `array.filter` method**: This approach uses the built-in `filter` method of JavaScript arrays, which is similar to Lodash's `filter` function but without the library.

**Pros and cons**

Here are some pros and cons of each approach:

1. **Lodash's `filter` function**
	* Pros:
		+ Easier to use and more readable, especially for developers familiar with Lodash.
		+ Reduces code duplication, as it provides a standardized filtering interface.
	* Cons:
		+ Adds overhead due to the library's existence and initialization.
		+ May not be suitable for projects that want to avoid dependencies.
2. **Built-in `array.filter` method**
	* Pros:
		+ Faster execution speed, since no additional library is required.
		+ Does not add any runtime dependencies or overhead.

**Library: Lodash**

Lodash is a popular utility library for JavaScript that provides a wide range of functions and helpers for tasks like filtering, mapping, and reducing arrays. It's designed to simplify common programming tasks and improve code readability.

**Special JS feature/syntax**

This benchmark does not use any special JavaScript features or syntax beyond the standard `let`, `var`, and arrow functions used in the test case.

**Alternative approaches**

Other alternatives for implementing filtering logic include:

1. **Using a custom function**: You can create a simple, optimized filtering function without using Lodash or the built-in `array.filter` method.
2. **Using other libraries**: There are many other libraries available that provide filtering functionality, such as Moment.js or jQuery.

Keep in mind that these alternatives may have different trade-offs and performance characteristics compared to Lodash's `filter` function or the built-in `array.filter` method.

**Benchmark result interpretation**

The provided benchmark results show the execution speed of both approaches on a specific test case (the filtering of an array with 100,000 elements). The results indicate that the built-in `array.filter` method is slightly faster than Lodash's `filter` function in this particular scenario.

Related benchmarks:

Lodash.filter vs array.filter (version: 0)

Lodash.filter vs array.filter

Comparing performance of: lodash vs arr

Created: 7 years ago by: Guest

Jump to the latest result

lodash

arr

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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