Benchmark: Array loop vs foreach vs map with return

Script Preparation code:

   var arr = [];
    for (var i = 0; i < 1000; i++) {
      arr[i] = i;
    }
  
    function someFn(i) {
      return i * 3 * 8;
    }

Tests:

foreach
var newA = [] arr.forEach(function (item){ newA.push(someFn(item)); }) return newA;
for
var newA = [] for (var i = 0, len = arr.length; i < len; i++) { newA.push(someFn(arr[i])); } return newA;
map
var newA = arr.map(item => someFn(item)) return newA;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
foreach
for
map

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36

Browser/OS: Chrome 89 on Mac OS X 10.13.6

View result in a separate tab

Test name	Executions per second
foreach	8909.1 Ops/sec
for	5362.2 Ops/sec
map	10871.5 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON benchmark and its components.

**Benchmark Definition**

The provided JSON defines a JavaScript microbenchmark that tests three different approaches to iterate over an array:

1. **Array Loop**: This approach uses a traditional `for` loop to iterate over the array, performing some calculations on each element.
2. **Foreach**: This approach uses the `forEach` method to iterate over the array, calling a callback function for each element.
3. **Map**: This approach uses the `map` method to create a new array with the results of applying a transformation function to each element.

**Options Compared**

The benchmark compares these three approaches:

* **Array Loop (for)**: The traditional `for` loop approach, which is generally considered a simple and efficient way to iterate over arrays.
* **Foreach**: The `forEach` method approach, which is a more modern and concise way to iterate over arrays, but may be slower due to the overhead of the callback function.
* **Map**: The `map` method approach, which creates a new array with transformed elements, but can be more efficient than `foreach` if the transformation function is expensive.

**Pros and Cons**

Here are some pros and cons for each approach:

* **Array Loop (for)**:
	+ Pros: Simple, efficient, and easy to understand.
	+ Cons: Can be verbose and cumbersome with large arrays.
* **Foreach**:
	+ Pros: More concise and expressive than `for`, but may introduce overhead due to callback functions.
	+ Cons: May be slower due to the additional function call.
* **Map**:
	+ Pros: Efficient if the transformation function is expensive, creates a new array with transformed elements.
	+ Cons: May not be suitable for large datasets due to memory constraints.

**Library and Syntax**

The benchmark uses the following JavaScript library:

* None explicitly mentioned. However, it's likely that the `forEach` and `map` methods are part of the standard ECMAScript API or a library like Lodash.

There are no special JavaScript features or syntaxes used in this benchmark.

**Other Alternatives**

If you're looking for alternative approaches to iterate over arrays, consider:

* **Reduce**: A method that applies a reduction function to all elements of an array.
* **filter()**: A method that creates a new array with only the elements that pass the test implemented by a provided function.
* **forEach** (as used in the benchmark): A method that calls a callback function for each element in an array.

Note that these alternatives may have different performance characteristics and use cases compared to `for`, `foreach`, and `map`.

Related benchmarks:

Array loop vs foreach vs map with return (version: 0)

Comparing performance of: foreach vs for vs map

Created: 3 years ago by: Guest

Jump to the latest result

foreach

for

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):