Benchmark: compare the ways to generate a random array for iteration + while

compare the ways to generate a random array for iteration + while (version: 0)

- Array.apply: Array.apply(null, Array(100)) - Destructuring operator: [...Array(100)] - Array.prototype.fill Array(100).fill(undefined) - Array.from Array.from({ length: 100 })

Comparing performance of: [...Array(n)] vs Array(n).fill(null) vs Array.from({ length: n }) vs Array.from({ length:n }, (item, i) => i) vs while(up--) myArray.push(Math.random());

Created: 9 months ago by: Guest

Jump to the latest result

Tests:

[...Array(n)]
[...Array(1000)].map(() => Math.random());
Array(n).fill(null)
Array(1000).fill(null).map(() => Math.random());
Array.from({ length: n })
Array.from({ length: 1000 }).map(() => Math.random());
Array.from({ length:n }, (item, i) => i)
Array.from({ length:1000 }, () => Math.random());
while(up--) myArray.push(Math.random());
let myArray = []; let up = 1000; while(up--) myArray.push(Math.random());

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
[...Array(n)]
Array(n).fill(null)
Array.from({ length: n })
Array.from({ length:n }, (item, i) => i)
while(up--) myArray.push(Math.random());

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Overview**

The `MeasureThat.net` benchmark compares different ways to generate an array for iteration and while loops. The benchmark has four test cases:

1. `Array.from({ length: n })`
2. `Array.from({ length:n }, (item, i) => i)`
3. `while(up--) myArray.push(Math.random());`
4. `[...Array(n)].map(() => Math.random());` and its variants

**Option Comparison**

Here's a brief explanation of each option:

1. **`Array.from({ length: n })`**: This method creates an array from a specified length using the `from` method. It's concise and efficient.
2. **`Array.from({ length:n }, (item, i) => i)`**: This method adds an additional step by mapping each index to itself. While it might seem unnecessary, it can be beneficial for certain use cases where you need to access both the value and its index.
3. **`while(up--) myArray.push(Math.random());`**: This traditional loop is often less efficient than modern array creation methods like `Array.from`. However, it's useful for demonstrating older JavaScript techniques.
4. **`[...Array(n)].map(() => Math.random())`** (and its variants): These methods create an array and then map over it to generate random values. This approach can be slower due to the overhead of mapping.

**Pros and Cons**

Here are some pros and cons for each option:

1. **`Array.from({ length: n })`**:
	* Pros: Concise, efficient, and modern.
	* Cons: None significant.
2. **`Array.from({ length:n }, (item, i) => i)`**:
	* Pros: Provides access to both value and index, useful for certain use cases.
	* Cons: Adds unnecessary complexity and potential performance overhead.
3. **`while(up--) myArray.push(Math.random());`**:
	* Pros: Traditional loop, easy to understand.
	* Cons: Inefficient compared to modern array creation methods.
4. **`[...Array(n)].map(() => Math.random())` (and its variants)**:
	* Pros: Demonstrates traditional array mapping.
	* Cons: Can be slower due to mapping overhead.

**Library and Special JS Features**

In this benchmark, the following libraries or special JavaScript features are used:

* None explicitly mentioned; however, `Array.from()` is a built-in method, and the destructuring operator (`[...Array(n)]`) is a modern feature introduced in ECMAScript 2015 (ES6).

**Other Alternatives**

If you're interested in exploring alternative array creation methods, consider the following:

* `Array.prototype.fill()`: Fills an existing array with a specified value.
* `new Array(n)`: Creates a new, empty array of length `n`.
* `Array.create()`: Creates a new array object (not as commonly used).

Keep in mind that performance differences between these methods might not be significant for small arrays or simple use cases. However, when working with large datasets or performance-critical code, using efficient array creation methods like `Array.from()` can make a noticeable difference.

I hope this explanation helps you understand the benchmark and the options being compared!

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/121.0.0.0 Safari/537.36

Browser/OS: Chrome 121 on Windows

View result in a separate tab

Test name	Executions per second
[...Array(n)]	9981.4 Ops/sec
Array(n).fill(null)	9944.4 Ops/sec
Array.from({ length: n })	7529.2 Ops/sec
Array.from({ length:n }, (item, i) => i)	7080.2 Ops/sec
while(up--) myArray.push(Math.random());	9672.4 Ops/sec

Related benchmarks:

compare the ways to generate a random array for iteration + while (version: 0)

- Array.apply: Array.apply(null, Array(100)) - Destructuring operator: [...Array(100)] - Array.prototype.fill Array(100).fill(undefined) - Array.from Array.from({ length: 100 })

Comparing performance of: [...Array(n)] vs Array(n).fill(null) vs Array.from({ length: n }) vs Array.from({ length:n }, (item, i) => i) vs while(up--) myArray.push(Math.random());

Created: 9 months ago by: Guest

Jump to the latest result

[...Array(n)]

Array(n).fill(null)

Array.from({ length: n })

Array.from({ length:n }, (item, i) => i)

while(up--) myArray.push(Math.random());

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):