Benchmark: Ramda map vs Array.map vs for loop

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);
For loop (native)
let mappedArray = []; for(let i = 0, len = data.length; i < len; i++){ mappedArray.push(data[i]); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Array (native)
For loop (native)

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

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Let's break down the provided benchmark definition and test cases.

**Benchmark Definition**

The website "MeasureThat.net" is testing the speed of three approaches to perform a simple mapping operation on an array:

1. `R.map(double, data)` using Ramda's `map` function
2. `data.map(double)` using the native `map` method of JavaScript arrays
3. A custom implementation using a for loop: `for(let i = 0, len = data.length; i < len; i++){\r\n mappedArray.push(data[i]);\r\n}`

**Options Compared**

The benchmark is comparing the performance of these three approaches:

* Ramda's `map` function
* The native JavaScript array `map` method
* A custom for loop implementation

**Pros and Cons of Each Approach**

1. **Ramda's `map` function**: Pros:
	* Abstraction: provides a high-level, functional programming approach to mapping arrays.
	* Reusability: can be used in other contexts beyond just array mapping.
	Cons:
	* Overhead: requires loading the Ramda library, which may introduce additional latency.
	* Limited control: doesn't provide direct access to the underlying array data structure.
2. **Native JavaScript array `map` method**: Pros:
	* Performance: optimized for native code execution, potentially faster than a library-based implementation.
	* Control: provides direct access to the underlying array data structure.
Cons:
	* Limited flexibility: can only be used with arrays, and may require additional setup.
3. **Custom for loop implementation**: Pros:
	* Control: provides full control over the implementation details, including optimization opportunities.
Cons:
	* Complexity: requires manual iteration and array indexing, which can lead to errors.

**Library Usage**

The benchmark uses Ramda's `map` function from version 0.25.0. This is a functional programming library that provides various higher-order functions for manipulating data structures, including arrays. The purpose of using Ramda is to demonstrate the performance of its `map` function in comparison to the native JavaScript array method.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in this benchmark beyond what's provided by the standard language specification.

Related benchmarks:

Ramda map vs Array.map vs for loop (version: 0)

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

Comparing performance of: Ramda vs Array (native) vs For loop (native)

Created: 7 years ago by: Guest

Jump to the latest result

Ramda

Array (native)

For loop (native)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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