Benchmark: for loop vs. .map

Script Preparation code:

// Create sample data
var array = [1,2,3,4,5,6,7,8,9,0];

var manipulateFn = num => {
	return num * 2 * 3;
}

Tests:

.map
var newArray = array.map( i => manipulateFn(i));
for loop
var newArray = []; for (let i=0; i<array.length; i++) { newArray.push(manipulateFn(array[i])); }

Historical Performance Data aggregated from 134 community runs

Desktop Results:

Chrome 110 runs

.map

5.6M/s

for loop

4.0M/s

Fastest: .map (1.4x faster)

View exact numbers

✓ .map: 5,583,228 ops/sec
• for loop: 3,992,376 ops/sec

Firefox 17 runs

.map

14.6M/s

for loop

14.2M/s

View exact numbers

✓ .map: 14,552,583 ops/sec
• for loop: 14,152,186 ops/sec

Mobile Results:

Chrome 7 runs

.map

6.9M/s

for loop

5.0M/s

Fastest: .map (1.4x faster)

View exact numbers

✓ .map: 6,932,958 ops/sec
• for loop: 5,013,171 ops/sec

Results show median performance across all community submissions. Run this benchmark yourself to verify on your device.

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
.map
for loop

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:148.0) Gecko/20100101 Firefox/148.0

Browser/OS: Firefox 148 on Windows

View result in a separate tab

for loop

2.9M/s

.map

2.6M/s

View exact numbers

Test name	Executions per second
✓ for loop	2,853,180 Ops/sec
.map	2,566,006 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 and explain what's being tested.

**Benchmark Overview**

The benchmark is comparing two approaches: using the `.map()` method versus a traditional `for` loop to perform an operation on an array of numbers. The operation involves multiplying each number by 2 and then by 3, as defined in the `manipulateFn` function.

**Options Compared**

Two options are being compared:

1. **`.map()`**: This is a built-in JavaScript method that applies a transformation to each element of an array and returns a new array with the transformed elements.
2. **Traditional `for` loop**: A classic way to iterate over an array, using a counter variable (`i`) to access each element.

**Pros and Cons**

**`.map()`**:

Pros:

* concise and expressive
* easy to read and understand
* can be more efficient for small arrays

Cons:

* can be slower for large arrays due to the overhead of function calls and array manipulation
* requires an additional function call, which can introduce overhead

**Traditional `for` loop**:

Pros:

* often faster for large arrays due to better caching and fewer function calls
* can be more efficient in terms of memory usage (no need to create a new array)

Cons:

* can be verbose and harder to read, especially for complex loops
* requires manual management of the counter variable and loop termination

**Other Considerations**

In this benchmark, the focus is on measuring the execution speed of each approach. Other factors like memory usage, code readability, and maintainability might also be worth considering in a real-world scenario.

**Library Used (if any)**

None mentioned in the provided JSON.

**Special JS Features or Syntax (if applicable)**

`.map()` uses a feature called **"arrow functions"**, which were introduced in ECMAScript 2015. These are concise ways to define small, anonymous functions using the `=>` operator. Traditional `for` loops do not use this syntax.

**Alternative Approaches**

If you want to explore alternative approaches, here are a few:

1. **Using `forEach()` instead of `.map()```**: While similar to `.map()`, `forEach()` doesn't return a new array and can be faster for large arrays.
2. **Using `reduce()` instead of traditional loops**: If you need to accumulate values or perform more complex operations, `reduce()` can be a good alternative.
3. **Using modern JavaScript features like `async/await` or `Promises```**: These might offer better performance and concurrency advantages in certain scenarios.

Keep in mind that the optimal approach depends on your specific use case and requirements.

for loop vs. .map (version: 0)

Comparing performance of: `.map vs for loop`

Created: 7 years ago by: Guest

Go to the latest result

.map

for loop

Historical Performance Data aggregated from 134 community runs

Desktop Results:

Chrome 110 runs

Firefox 17 runs

Mobile Results:

Chrome 7 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

for loop vs. .map (version: 0)

Comparing performance of: .map vs for loop

Created: 7 years ago by: Guest

Go to the latest result

.map

for loop

Historical Performance Data aggregated from 134 community runs

Desktop Results:

Chrome 110 runs

Firefox 17 runs

Mobile Results:

Chrome 7 runs

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `.map vs for loop`