Benchmark: Array.from vs Spread vs Iterate

Script Preparation code:

var fooSet = new Set();
for(var i=0;i<100;i++) {
  fooSet.add(i);
}

Tests:

Array.from
var other = Array.from(fooSet);
Spread
var other = [...fooSet];
Iterate
let other = []; for (const v of fooSet) { other.push(v); }
Iterate with pre-allocated array
let other = new Array(fooSet.size); let i = 0; for (const v of fooSet) { other[i++] = v; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.from
Spread
Iterate
Iterate with pre-allocated array

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what is being tested.

**What is being tested?**

The benchmark compares the performance of three different approaches to convert a Set object (in this case, `fooSet`) into an array:

1. Using `Array.from()`
2. Using the spread operator (`...`)
3. Iterating over the Set elements and pushing them onto an array using a traditional loop.

**Options compared:**

* `Array.from()`: This method creates a new array from an iterable or an array-like object. In this case, it's used to convert the Set `fooSet` into an array.
* Spread operator (`...`): This syntax is used to expand an iterable into individual elements. When applied to a Set, it converts the Set into an array.
* Iterating over the Set using a traditional loop: This approach involves creating an empty array and then pushing each element of the Set onto the array using a `for...of` loop.

**Pros and Cons of each approach:**

* `Array.from()`: Pros:
	+ Concise and readable syntax
	+ Fast execution (average time complexity is O(n))
	+ Can be used with other iterable objects, not just Sets
* Spread operator (`...`): Pros:
	+ Also concise and readable syntax
	+ Fast execution (average time complexity is O(n))
	+ Similar to `Array.from()`, can be used with other iterable objects
* Iterating over the Set using a traditional loop: Pros:
	+ Can be more efficient if memory allocation needs to be optimized (e.g., pre-allocating an array)
	+ Understanding the performance characteristics of this approach is crucial in certain scenarios

Cons:

* `Array.from()`: Can be slower than other approaches due to additional overhead
* Spread operator (`...`): May have slightly higher overhead compared to traditional loops
* Iterating over the Set using a traditional loop: Requires more manual memory management and can lead to performance issues if not optimized correctly

**Library and its purpose:**

The `Set` object is a built-in JavaScript data structure that provides fast lookup, insertion, and deletion operations. It's similar to a hash table but with some additional features.

**Special JS feature or syntax:**

None mentioned in the provided benchmark.

**Other alternatives:**

If you need to convert a Set into an array, you can also use other approaches like:

* Using `Array.prototype.slice()` followed by `set.forEach()`: This approach involves creating a copy of the original Set using `slice()` and then iterating over the copied elements using `forEach()`.
* Using `Array.from()` with `Set.prototype.values()`: This approach involves using `values()` to get an iterator over the Set's values, which can be converted into an array using `Array.from()`.

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36

Browser/OS: Chrome 70 on Windows

View result in a separate tab

Test name	Executions per second
Array.from	41398.3 Ops/sec
Spread	470649.1 Ops/sec
Iterate	461936.1 Ops/sec
Iterate with pre-allocated array	574017.4 Ops/sec

Related benchmarks:

Array.from vs Spread vs Iterate (version: 0)

Comparing performance of: Array.from vs Spread vs Iterate vs Iterate with pre-allocated array

Created: 6 years ago by: Guest

Jump to the latest result

Array.from

Spread

Iterate

Iterate with pre-allocated array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 28 days ago):