Benchmark: Map (Native vs Ramda vs Lodash)333

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js"></script>

Script Preparation code:

function double(n) {
	return n*2;
}
var data = [...Array(2000)].map((v, idx) => idx);

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

Latest run results:

Run details: (Test run date: 5 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/145.0.0.0 Safari/537.36

Browser/OS: Chrome 145 on Windows

View result in a separate tab

Ramda

709K/s

Array (native)

106K/s

View exact numbers

Test name	Executions per second
✓ Ramda	708,674 Ops/sec
Array (native)	106,491 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to help explain the provided benchmark.

**Benchmark Overview**

The MeasureThat.net website allows users to create and run JavaScript microbenchmarks. The provided benchmark compares the speed of `Map` operations using three different approaches:

1. Native `Array.prototype.map()`
2. Ramda's `R.map()`
3. Lodash's `_.map()`

**Options Comparison**

The benchmark is testing two options for each approach:

* **Native Array.prototype.map():**
	+ Pros: Built-in, widely supported, and optimized for performance.
	+ Cons: May have limitations in terms of customization and flexibility.
* **Ramda's R.map():**
	+ Pros: Provides more control over the mapping process and can be more flexible than native `map()`.
	+ Cons: Requires an additional library to be included, which may add overhead.
* **Lodash's _.map():**
	+ Pros: Also provides more control over the mapping process and is widely used in the industry.
	+ Cons: Like Ramda, requires an additional library to be included.

**Library Usage**

The benchmark uses three libraries:

1. Ramda (version 0.25.0): A functional programming library that provides a higher-order function `map()` for mapping over arrays.
2. Lodash (version 4.17.5): A utility library that provides a `map()` function for mapping over arrays.

**Special JavaScript Features**

The benchmark does not explicitly mention any special JavaScript features or syntax, but it's worth noting that the use of functional programming libraries like Ramda and Lodash may imply an interest in functional programming concepts.

**Alternatives**

Other alternatives to consider when performing similar benchmarks might include:

* Using a different mapping function from other popular libraries, such as jQuery's `.map()`
* Comparing the performance of built-in `map()` functions in other languages or frameworks
* Adding additional tests to compare the performance of each approach with other operations, such as filtering or reducing.

**Benchmark Preparation Code**

The provided script preparation code defines a simple function `double(n)` that takes an input `n` and returns its double value. The `data` array is created using an arrow function that maps over an array of numbers from 0 to 1999 (inclusive).

**Html Preparation Code**

The HTML preparation code includes scripts for Ramda and Lodash, which are loaded before the benchmark script is executed.

I hope this explanation helps!

Map (Native vs Ramda vs Lodash)333 (version: 0)

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

Comparing performance of: `Ramda vs Array (native)`

Created: 7 years ago by: Guest

Go to the latest result

Ramda

Array (native)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Map (Native vs Ramda vs Lodash)333 (version: 0)

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

Comparing performance of: Ramda vs Array (native)

Created: 7 years ago by: Guest

Go to the latest result

Ramda

Array (native)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Ramda vs Array (native)`