Benchmark: lodash _.map vs native map

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 array = [{id: 'a'}, {id: 'c'}, {id: 'b'}]

Tests:

_.map
_.map(array, a => console.log(a.id))
native
array.map(a => console.log(a.id))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.map
native

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):

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Let's dive into the provided JSON to explain what is being tested.

**Benchmark Name**: "_lodash _.map vs native map"

**Description**: This benchmark compares the performance of two different ways to iterate over an array in JavaScript: using the `_.map` function from the Lodash library and using the native `Array.prototype.map()` method.

**Test Case 1**: "_.map"
This test case uses the `_.map` function from Lodash, which is a popular JavaScript utility library. The `_.map` function takes an array as its first argument and a callback function as its second argument. In this test case, the callback function simply logs the `id` property of each object in the array to the console using `console.log(a.id)`.

**Test Case 2**: "native"
This test case uses the native `Array.prototype.map()` method, which is a built-in JavaScript method for iterating over an array. In this test case, the callback function is identical to the one used in Test Case 1: it logs the `id` property of each object in the array to the console using `console.log(a.id)`.

**What's being compared?**
The benchmark is comparing the execution time (measured in executions per second) of these two test cases on a Chrome 100 browser running on Windows. The goal is to see which approach is faster: using Lodash's `_.map` function or the native `Array.prototype.map()` method.

**Pros and Cons**

* **Lodash's _.map**: Pros:
	+ Provides a consistent, predictable API across different JavaScript environments.
	+ Often used in conjunction with other Lodash functions to create complex data transformations.
	+ May be faster than native methods due to optimization techniques used by the library.
* Cons:
	+ Introduces additional dependencies on the Lodash library.
	+ May not work correctly in certain edge cases or with specific JavaScript configurations.

* **Native Array.prototype.map()**: Pros:
	+ Built-in method, so it's always available and doesn't require external libraries.
	+ Often more concise and expressive than equivalent code using `_.map`.
	+ Typically has a lower overhead due to its native implementation.
* Cons:
	+ May not work correctly in certain edge cases or with specific JavaScript configurations.
	+ Performance can vary depending on the environment and platform.

**Other considerations**
The benchmark results show that the native `Array.prototype.map()` method is faster than Lodash's `_.map` function in this particular test case. This might be due to various factors, such as the Chrome browser's optimization techniques or the specific implementation of the native method.

**Alternative approaches**

* **For-each loops**: Instead of using either `_.map` or the native `Array.prototype.map()` method, you could use a for-each loop to iterate over the array. This approach is often more verbose but can be useful in certain situations.
* **Other libraries**: There are other JavaScript libraries that provide similar functionality to Lodash's `_.map`, such as Underscore.js or SugarJS. You could compare their performance with the native method using a similar benchmark.

In summary, this benchmark shows a comparison between using Lodash's `_.map` function and the native `Array.prototype.map()` method in JavaScript. The results indicate that the native method is faster in this particular test case.

Related benchmarks:

lodash _.map vs native map (version: 0)

Comparing performance of: _.map vs native

Created: 5 years ago by: Guest

Jump to the latest result

_.map

native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):