Benchmark: native find vs underscore _.find

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/underscore.js/1.13.3/underscore-min.js"></script>

Script Preparation code:

var users = [
  { 'user': 'joey',  'age': 32 },
  { 'user': 'ross',    'age': 41 },
  { 'user': 'chandler', 'age': 39 }
]

Tests:

array find
// Native users.find(function (o) { return o.age < 40; })
_.find
_.find(users, function (o) { return o.age < 40; })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array find
_.find

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:148.0) Gecko/20100101 Firefox/148.0

Browser/OS: Firefox 148 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
array find	1255621888.0 Ops/sec
_.find	33130194.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark JSON and explain what is tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark tests two approaches to find an element in an array:

1. **Native Find**: Using the `find()` method on the native JavaScript array object.
2. **Underscore _.find**: Using the `_.find()` function from the Underscore.js library.

**Script Preparation Code**

The script preparation code defines a sample array of objects: `users` with three elements, each containing an `age` property.

**Html Preparation Code**

The HTML preparation code includes a script tag that loads the Underscore.js library (version 1.13.3).

**Individual Test Cases**

There are two test cases:

1. **array find**: This test case uses the native JavaScript array object and calls the `find()` method on it, passing a callback function that returns `true` if the `age` property is less than 40.
2. **_.find**: This test case uses the Underscore.js library and calls the `_.find()` function on the `users` array, passing a callback function that returns `true` if the `age` property is less than 40.

**Pros and Cons of Each Approach**

1. **Native Find**
	* Pros:
		+ Lightweight and efficient
		+ No additional library dependencies
		+ Suitable for most use cases
	* Cons:
		+ May not work well with large arrays or complex data structures
		+ Callback function can be slower than a pure function call
2. **Underscore _.find**
	* Pros:
		+ Can handle larger arrays and more complex data structures
		+ Uses a pure function call, which can be faster than callback-based implementations
	* Cons:
		+ Requires an additional library dependency (Underscore.js)
		+ May add overhead due to the library's presence

**Other Considerations**

1. **ES6 Spread Operator**
Although not directly tested in this benchmark, it's worth noting that some test cases might use the ES6 spread operator (`...`) to create a shallow copy of the array. This could potentially affect performance.
2. **Device and Browser Variability**
The benchmark results are specific to a Chrome 116 browser on a Mac OS X 10.15.7 device. Other devices, browsers, or environments might exhibit different performance characteristics.

**Alternatives**

Some alternative approaches that could be tested in this benchmark include:

1. Using `Array.prototype.findIndex()` instead of `find()`
2. Implementing a custom search algorithm using a data structure like a binary search tree
3. Testing the performance of a library like Lodash or Ramda

By testing these alternatives, developers can gain a better understanding of the trade-offs and optimizations involved in finding elements in arrays.

Related benchmarks:

native find vs underscore _.find (version: 0)

Compare the new ES6 spread operator with the traditional concat() method

Comparing performance of: array find vs _.find

Created: 4 years ago by: Guest

Jump to the latest result

array find

_.find

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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