Benchmark: js array copy any type

Script Preparation code:

var arr = Array.from({ length: 65535 }, (_, index) => index);
var identity = value => value;
var index = 0;
while (++index < 10002) {
  arr = arr.map(identity);
  arr = Array.from(arr);
  arr = arr.slice()
}

Tests:

map
((identity, newArr) => newArr = arr.map(e=>e))(identity, [])
array.from
var newArr = Array.from(arr)
for loop
var newArr = []; var i = 0; var length = 65535; for(; i < length; i++) { newArr[i] = arr[i]; }
forIn
var newArr = []; for(var i in arr) { newArr[i] = arr[i]; }
slice
var newArr = arr.slice()
spred
var newArr = [...arr];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
map
array.from
for loop
forIn
slice
spred

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.

**Benchmark Overview**

The benchmark measures the performance of different methods to copy an array in JavaScript, including `Array.from()`, `slice()`, `spred` (using the spread operator), `for loop`, and `map`. The test case starts with a large array of 65535 elements created using `Array.from()`.

**Options Compared**

Here's what each option is being tested:

1. **Array.from()**: This method creates a new array by mapping over an existing array.
2. **slice()**: This method returns a shallow copy of a portion of an array.
3. **spred (Spread Operator)**: The spread operator (`...`) can be used to create a new array by spreading the elements of an existing array.
4. **for loop**: A traditional `for` loop is used to iterate over each element in the original array and assign it to a new array.
5. **map()**: This method applies a given function to every element of an array.

**Pros and Cons**

Here's a brief summary of the pros and cons of each option:

1. **Array.from()**:
	* Pros: Modern, efficient, and concise.
	* Cons: May incur additional overhead due to the need for an intermediate array.
2. **slice()**:
	* Pros: Fast and efficient, with minimal overhead.
	* Cons: Returns a shallow copy, which may not be suitable for all use cases.
3. **spred (Spread Operator)**:
	* Pros: Modern, concise, and flexible.
	* Cons: May incur additional overhead due to the need for an intermediate array.
4. **for loop**:
	* Pros: Classic, efficient, and easy to understand.
	* Cons: Can be verbose and error-prone.
5. **map()**:
	* Pros: Modern, concise, and flexible.
	* Cons: May incur additional overhead due to the need for an intermediate array.

**Library Usage**

None of the options rely on external libraries.

**Special JS Features or Syntax**

The benchmark does not use any special JavaScript features or syntax beyond what's available in modern browsers (ECMAScript 2022).

**Other Alternatives**

If you're interested in exploring other methods to copy arrays, here are a few alternatives:

1. **concat()**: This method concatenates two or more arrays and returns a new array.
2. **reduce()**: This method applies a given function to each element of an array and reduces it to a single value.
3. **filter()**: This method creates a new array with all elements that pass the test implemented by the provided function.

These alternatives may have different performance characteristics, pros, and cons compared to the options being tested in this benchmark.

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36

Browser/OS: Chrome 114 on Linux

View result in a separate tab

Test name	Executions per second
map	1479.7 Ops/sec
array.from	5431.8 Ops/sec
for loop	206.4 Ops/sec
forIn	96.1 Ops/sec
slice	5428.6 Ops/sec
spred	5175.9 Ops/sec

Related benchmarks:

js array copy any type (version: 0)

Comparing performance of: map vs array.from vs for loop vs forIn vs slice vs spred

Created: one year ago by: Guest

Jump to the latest result

map

array.from

for loop

forIn

slice

spred

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):