Benchmark: Array.prototype.find vs Lodash find_2

HTML Preparation code:

<script src="lodash.js"></script>

Script Preparation code:

var array = [...Array(100000).keys()];
var rum = Math.floor(100000 * Math.random());

Tests:

Array.prototype.find
array.find(n => n === rum)
Lodash find
_.find(array,n => n === rum)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.prototype.find
Lodash find

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 and explain what's being tested.

**Overview**

The benchmark compares two approaches to find an element in an array: `Array.prototype.find` (native JavaScript) and `_.find` from the Lodash library.

**Native JavaScript Approach (`Array.prototype.find`)**

* **Description**: The native JavaScript approach uses the `find()` method on the `Array.prototype`, which returns the first element that satisfies the provided condition.
* **Options compared**: In this case, only one option is compared: finding an element in an array using the `n === rum` condition.

Pros:

1. **Performance**: Native JavaScript implementations are usually optimized for performance and can be faster than third-party libraries.
2. **Low overhead**: No additional dependencies or overhead beyond the basic DOM API.

Cons:

1. **Browser limitations**: Not all browsers support this method, especially older ones.
2. **Limited control**: The behavior of `find()` can vary across different browsers and environments.

**Lodash Approach (`_.find`)**

* **Description**: Lodash's `_.find()` function is a utility function that searches for the first element in an array that satisfies a given condition.
* **Library purpose**: Lodash provides a set of helper functions to simplify common programming tasks, including array manipulation and filtering.

Pros:

1. **Consistency across browsers**: Lodash's implementation is consistent across different browsers and environments.
2. **Control over behavior**: Developers have more control over the `find()` function's behavior by passing custom options or modifying the underlying algorithm.

Cons:

1. **Overhead**: Using a third-party library like Lodash adds an extra layer of complexity and potential overhead.
2. **Additional dependencies**: Developers need to include Lodash in their project, which can increase bundle sizes.

**Special considerations**

* The `n === rum` condition is used to find the element that satisfies the given equality check. This is a simple yet effective way to test the performance of finding an exact match.
* There's no special JavaScript feature or syntax involved in this benchmark. It focuses solely on the performance comparison between two different approaches.

**Other alternatives**

If you wanted to compare other approaches, some possible alternatives could be:

1. `Array.prototype.indexOf()` instead of `find()`.
2. Using a custom implementation of `find()` without relying on a library.
3. Comparing performance with different array sizes or data distributions (e.g., random vs. sequential numbers).
4. Incorporating additional tests for edge cases, such as finding an element that does not exist in the array.

Keep in mind that adding more test cases would require increasing the benchmark's complexity and potentially leading to more variability in results.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36

Browser/OS: Chrome 71 on Linux

View result in a separate tab

Test name	Executions per second
Array.prototype.find	135.3 Ops/sec
Lodash find	119.7 Ops/sec

Related benchmarks:

Array.prototype.find vs Lodash find_2 (version: 0)

Comparing performance of: Array.prototype.find vs Lodash find

Created: 5 years ago by: Guest

Jump to the latest result

Array.prototype.find

Lodash find

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):