Benchmark: array iteration vs _.map vs 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 = ['a', 'b', 'c']

Tests:

_.map
_.map(array, (value, index) => { console.log(value) })
forEach
array.forEach((value, index) => { console.log(value) })
map
array.map((value, index) => { console.log(value) })

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.map
forEach
map

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, compared, and their pros and cons.

**What is being tested:**

The test compares the performance of three different ways to iterate over an array in JavaScript:

1. **_.map` (using Lodash)**: This method creates a new array with the results of applying the provided function to each element in the original array.
2. **Array.forEach**: This method iterates over the elements of an array, executing the provided callback function for each element.
3. **Array.map`: This method creates a new array with the results of applying the provided function to each element in the original array.

**Options compared:**

The test compares the performance of these three methods on the same input data (an array of strings). The goal is to determine which method is fastest.

**Pros and Cons:**

1. **_.map` (using Lodash)**:
	* Pros:
		+ Convenient way to transform arrays using a functional programming style.
		+ Often more readable than traditional loop-based code.
	* Cons:
		+ Creates a new array, which can be memory-intensive for large datasets.
		+ May have performance overhead due to the creation of a new array and the execution of the callback function.
2. **Array.forEach**:
	* Pros:
		+ No memory allocation required, as it operates in-place on the original array.
		+ Can be more efficient than _.map` for large datasets, since it doesn't create a new array.
	* Cons:
		+ Requires more explicit iteration logic, which can make the code harder to read.
3. **Array.map**:
	* Pros:
		+ Similar to _.map`, but creates the new array in-place without the overhead of Lodash.
	* Cons:
		+ May still have performance overhead due to the execution of the callback function.

**Library:**

The test uses Lodash, a popular JavaScript utility library that provides a functional programming style for working with arrays and other data structures. In this case, it's used to wrap the _.map` method, making it easier to use in a test scenario.

**Special JS feature or syntax:**

There are no special JS features or syntaxes being tested here. The focus is on comparing different iteration methods.

**Other alternatives:**

If you wanted to compare other iteration methods, some alternative approaches could include:

* Using `for` loops
* Using `while` loops
* Using recursive functions (although this can lead to performance issues and stack overflows)
* Using `setInterval` or similar timing-based methods

Keep in mind that the choice of iteration method depends on the specific use case, data structure, and performance requirements.

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36

Browser/OS: Chrome 84 on Linux

View result in a separate tab

Test name	Executions per second
_.map	26676.2 Ops/sec
forEach	32689.8 Ops/sec
map	33710.2 Ops/sec

Related benchmarks:

array iteration vs _.map vs map (version: 0)

Comparing performance of: _.map vs forEach vs map

Created: 4 years ago by: Registered User

Jump to the latest result

_.map

forEach

map

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):