Benchmark: Speed Test : _.filter vs array filter

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.11/lodash.core.js"></script>

Script Preparation code:

var numbers = [11, 41, 233, 17, 22, 55, 1222, 2444]

Tests:

_.filter
_.filter(numbers, num => num % 3 === 0)
array filter
numbers.filter(num => num % 3 === 0)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.filter
array filter

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**What is tested?**

The website MeasureThat.net is running a JavaScript microbenchmark to compare the performance of two approaches:

1. **Array filtering**: `numbers.filter(num => num % 3 === 0)`
2. **Lodash filtering**: `_filter(numbers, num => num % 3 === 0)`

Both approaches are used to filter an array of numbers and return only the elements that meet a certain condition (i.e., if the number is divisible by 3).

**Options compared**

The two options being compared are:

* **Array method**: `numbers.filter(num => num % 3 === 0)`
* **Lodash method**: `_filter(numbers, num => num % 3 === 0)`

Both methods achieve the same result but use different libraries and syntax.

**Pros and Cons of each approach**

**Array method:**

Pros:

* Native JavaScript support
* Easy to understand and implement

Cons:

* May not be as efficient as a specialized library like Lodash
* Requires manual handling of array iteration and indexing

**Lodash method:**

Pros:

* High-performance implementation optimized for specific use cases
* Convenient and concise syntax with `_filter` method
* Built-in support for various iteration and filtering algorithms

Cons:

* Requires an additional library import (`lodash.js`)
* May require more learning and adaptation to the Lodash API

**Other considerations**

* The benchmark uses a simple array of numbers as input, which might not accurately represent real-world scenarios.
* There are no variations in input data or conditions being tested, which could limit the relevance of the results.
* No comparison is made with other filtering libraries like `Array.prototype.forEach` and `map`.

**Library overview**

The Lodash library (`lodash.js`) is a popular JavaScript utility library that provides various functions for iterating over arrays, objects, and more. The `_filter` method is one of its features that allows you to filter an array based on a given predicate function.

**Special JS feature or syntax**

There are no specific JavaScript features or syntax mentioned in the benchmark definition. However, it's worth noting that Lodash methods often rely on ES6+ features like arrow functions (`num => num % 3 === 0`) and template literals (not explicitly used here).

**Alternatives**

Other filtering libraries or methods could be explored for comparison, such as:

* `Array.prototype.forEach` with custom iteration
* `map()` function
* Other Lodash methods like `_some()`, `_every()`, etc.
* Custom JavaScript implementations using loops and bitwise operations

Keep in mind that these alternatives would require additional changes to the benchmark definition and script preparation code.

I hope this explanation helps software engineers understand what's being tested in this benchmark and provides insights into the pros and cons of different approaches!

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Windows

View result in a separate tab

Test name	Executions per second
_.filter	3467492.2 Ops/sec
array filter	12363768.0 Ops/sec

Related benchmarks:

Speed Test : _.filter vs array filter (version: 1)

Comparing performance of: _.filter vs array filter

Created: 2 years ago by: Registered User

Jump to the latest result

_.filter

array filter

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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