Benchmark: Ramda map vs Array.map

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>

Script Preparation code:

function double(n) {
	return n*2;
}
var data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30];

Tests:

Ramda
R.map(double, data);
Array (native)
data.map(double);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Array (native)

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!

The provided benchmark compares two approaches: `Array.map` (also known as the native map function) and `R.map` from the Ramda library.

**What are they compared?**

In this benchmark, both `Array.map` and `R.map` are applied to a large array (`data`) with 30 elements. The `map` function takes two arguments: a callback function (in this case, `double(n)`) that returns a new value for each element in the array.

**Options being compared**

Here's a brief overview of what's being tested:

1. **Native Array.map**: This is the built-in map function provided by JavaScript engines like V8 (used by Chrome and Node.js). It's optimized for performance.
2. **R.map from Ramda library**: Ramda is a functional programming library that provides an implementation of the `map` function. While it's based on the native implementation, it adds some extra features and sugar.

**Pros and Cons**

Here are some pros and cons of each approach:

Native Array.map:

Pros:

* Optimized for performance by the JavaScript engine
* Generally faster than Ramda's implementation
* Familiarity and ease of use for developers who already know `Array.map`

Cons:

* Limited to native functions only (no additional features or sugar)
* May not be as readable or expressive as Ramda's implementation

R.map from Ramda library:

Pros:

* Additional features and sugar, such as higher-order functions and currying
* Can lead to more concise and expressive code
* Can improve maintainability and readability in certain situations

Cons:

* Slower than the native `Array.map` function due to overhead from the JavaScript engine
* Requires an additional library (Ramda) which may not be familiar to all developers

**Library explanation**

In this benchmark, Ramda is a functional programming library that provides an implementation of the `map` function. Its purpose is to provide a more expressive and concise way to perform functions on arrays.

**Special JS feature or syntax**

There isn't any special JavaScript feature or syntax being used in this benchmark beyond what's already mentioned (e.g., `Array.map`, Ramda's `R.map`).

Latest run results:

Run details: (Test run date: 3 days ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 18_0 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.0 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 18 on iOS 18.0

View result in a separate tab

Test name	Executions per second
Ramda	1847403.9 Ops/sec
Array (native)	2234207.0 Ops/sec

Related benchmarks:

Ramda map vs Array.map (version: 0)

measures the speed of ramda's map vs Array's native map

Comparing performance of: Ramda vs Array (native)

Created: 6 years ago by: Guest

Jump to the latest result

Ramda

Array (native)

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):