Benchmark: Array.from() vs Spread with 10K elements

Tests:

Array.from()
let set = new Set(); for (var i = 0; i < 10_000; i++) { set.add(i); } let result = Array.from(set);
Spread
let set = new Set(); for (var i = 0; i < 10_000; i++) { set.add(i); } let result = [...set];

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Array.from()
Spread

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and analyze what's being tested on the provided JSON.

**Benchmark Definition**

The benchmark is defined as an array containing two test cases:

1. `Array.from() vs Spread with 10K elements`
2. `let set = new Set(); for (var i = 0; i < 10_000; i++) { set.add(i); } let result = Array.from(set);` and
3. `let set = new Set(); for (var i = 0; i < 10_000; i++) { set.add(i); } let result = [...set];`

These test cases aim to compare the performance of two approaches: using `Array.from()` with a new `Set` object, and using spread syntax (`...`) with a new `Set` object.

**Options Compared**

The two options being compared are:

1. **Using `Array.from()`**: This method creates a new array from an iterable (in this case, the `Set` object). It's a convenient way to convert sets to arrays.
2. **Using spread syntax (`...`) with a new `Set` object**: This approach creates a new array by spreading the elements of the `Set` object.

**Pros and Cons**

* **Using `Array.from()`**:
	+ Pros: More concise, readable code. It's also more efficient because it avoids creating an intermediate array.
	+ Cons: May have performance overhead due to the creation of an intermediate array.
* **Using spread syntax (`...`) with a new `Set` object**:
	+ Pros: Avoids creating an intermediate array, which can lead to better performance.
	+ Cons: May be less readable and more verbose than using `Array.from()`.

**Library Used**

None are explicitly mentioned in the benchmark definition. However, both approaches use built-in JavaScript features (`Set`, `Array.from()`, spread syntax).

**Special JS Feature/Syntax**

The test case uses a feature introduced in ECMAScript 2015 (ES6): the `let` and `var` declarations with block scope.

In older versions of JavaScript (e.g., ES5), the `var` keyword would have used function scope, which could lead to unexpected behavior. The use of `let` instead of `var` helps avoid this issue by introducing a new scope for each block.

**Other Considerations**

When writing performance benchmarks, it's essential to consider factors like:

* Input size: In this case, the benchmark is testing with 10,000 elements.
* System configuration: The results may vary depending on the system configuration (e.g., CPU architecture, operating system).
* Cache effects: The order of operations and caching behavior can impact performance.

**Alternatives**

Other alternatives to test these scenarios could include:

1. Using `Array.from()` with an existing array instead of a `Set`.
2. Using other spread syntax variants (e.g., using `Array.prototype.slice()` or `Array.prototype.splice()`).
3. Comparing the performance of different JavaScript engines or browsers.

In conclusion, this benchmark helps compare the performance of two approaches for converting sets to arrays: using `Array.from()` and using spread syntax with a new `Set` object. The test results provide insights into which approach is more efficient in terms of execution rate.

Latest run results:

Run details: (Test run date: 2 months ago)

User agent: Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:129.0) Gecko/20100101 Firefox/129.0

Browser/OS: Firefox 129 on Ubuntu

View result in a separate tab

Test name	Executions per second
Array.from()	1341.5 Ops/sec
Spread	1148.4 Ops/sec

Related benchmarks:

Array.from() vs Spread with 10K elements (version: 0)

Comparing performance of: Array.from() vs Spread

Created: 2 months ago by: Guest

Jump to the latest result

Array.from()

Spread

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):