Benchmark: Array.From VS Array.Slice

Tests:

array.from
var fooSet = new Array(); for (var i = 0; i < 100; i++) { fooSet.push(i); } var other = Array.from(fooSet);
array.splice
var fooSet = new Array(); for (var i = 0; i < 100; i++) { fooSet.push(i); } var other = fooSet.slice();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
array.from
array.splice

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.5112.79 Safari/537.36

Browser/OS: Chrome 104 on Linux

View result in a separate tab

Test name	Executions per second
array.from	946645.7 Ops/sec
array.splice	1214514.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON data and explain what's being tested, compared, and some considerations.

**Benchmark Overview**

The benchmark is designed to compare two approaches for creating an array from an existing set: `Array.from()` and `Array.slice()`. The goal is to determine which approach is more efficient in terms of execution speed.

**Options Compared**

The options being compared are:

1. **`Array.from()`**: This method creates a new array from an iterable or an array-like object. It's designed to provide a safer alternative to the traditional `for` loop or other methods that can modify the original collection.
2. **`Array.slice()`**: This method returns a shallow copy of a portion of an array. In this case, it's being used to create a new array from the same set as before.

**Pros and Cons**

1. **`Array.from()`**:
	* Pros: Provides a safer alternative to traditional methods, can handle any iterable or array-like object, and is more concise.
	* Cons: May incur a performance overhead due to the creation of an intermediate array (if not using `map()` or other methods that preserve the original order).
2. **`Array.slice()`**:
	* Pros: Can be faster in some cases, as it only creates a new reference to the existing array.
	* Cons: May not handle all types of iterable or array-like objects, and can be less readable for complex use cases.

**Considerations**

* When working with large datasets, `Array.from()` may incur a performance overhead due to the creation of an intermediate array. However, this overhead is usually negligible compared to other factors like memory allocation or network latency.
* In some cases, `Array.slice()` might be faster because it only creates a new reference to the existing array, whereas `Array.from()` creates a new array with its own internal structure.

**Library Usage**

There doesn't appear to be any libraries being used in this benchmark. However, if we were to add libraries like Lodash or Ramda, they could provide additional features and performance optimizations for array manipulation.

**Special JavaScript Features/Syntax**

This benchmark does not use any special JavaScript features or syntax beyond the standard `Array.from()` and `Array.slice()` methods.

**Alternative Approaches**

Some alternative approaches for creating an array from a set include:

1. **`map()`**: Instead of using `Array.from()`, you can use the `map()` method to create a new array from the original set.
2. **`reduce()`**: You can also use the `reduce()` method to create a new array from the original set, although this approach might be less readable for some use cases.
3. **`for...of` loop**: A simple `for...of` loop can be used to iterate over the elements of an iterable and push them into a new array.

These alternative approaches might have different performance characteristics or readability advantages compared to `Array.from()` and `Array.slice()`, depending on the specific use case.

Related benchmarks:

Array.From VS Array.Slice (version: 0)

Comparing performance of: array.from vs array.splice

Created: 3 years ago by: Guest

Jump to the latest result

array.from

array.splice

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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