Benchmark: range generator vs array

Tests:

generator
function* range(a, b) { do { yield a; } while ((a += 1) < b); } let total = 0; for (let ii of range(0,100000)) { total += ii; }
array
function range(a, b) { let arr = []; for (i = a; i < b; i++) { arr.push(i); } return arr; } let total = 0; for (let ii of range(0, 100000)) { total += ii; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
generator
array

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
generator	407.7 Ops/sec
array	731.8 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The test is comparing two approaches to generate an array of numbers from 0 to 100,000: using a traditional for loop with an array (`"array"`), and using a generator function (`"generator"`).

**Options Compared**

In this case, we have only two options:

1. **Traditional Array Generation**: This approach uses a for loop to iterate over the range of numbers, pushing each number onto an array.
2. **Generator Function**: This approach uses a generator function to yield numbers from 0 to 100,000.

**Pros and Cons**

**Traditional Array Generation:**

* Pros:
	+ Easy to understand and implement.
	+ Well-documented and widely used.
* Cons:
	+ Creates an intermediate array in memory, which can be inefficient for large datasets.
	+ Can lead to performance issues if the array is not properly managed.

**Generator Function:**

* Pros:
	+ More memory-efficient than traditional array generation, as it only yields values on demand.
	+ Can be more suitable for large datasets or infinite sequences.
* Cons:
	+ May require additional setup and understanding of generator functions.
	+ Less widely supported or documented than traditional array generation.

**Library/Function Used**

In this benchmark, the `yield` keyword is used to define a generator function. The `do-while` loop is also used in conjunction with `yield`, which is an older syntax for generator functions.

**Special JS Feature/Syntax**

The test case uses a special JavaScript feature: **generators**. Generators are a type of function that can be used to generate a sequence of values, rather than computing them all at once and returning them as an array. This allows generators to work with large datasets without consuming excessive memory.

**Other Alternatives**

Some other alternatives to traditional array generation or generator functions include:

* **NumJS**: A JavaScript library for numerical computations that provides efficient and optimized methods for array operations.
* **Array.prototype.reduce()**: A method that can be used to generate an array by accumulating values in a reduction operation.
* **Async/await** with **Arrays.from()**: An approach that uses async/await syntax to iterate over an array, which can provide better performance than traditional loops.

These alternatives may offer different trade-offs in terms of complexity, performance, and memory usage.

Related benchmarks:

range generator vs array (version: 0)

Comparing performance of: generator vs array

Created: 2 years ago by: Guest

Jump to the latest result

generator

array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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