Benchmark: Ramda map vs Array.map

HTML Preparation code:

<script src="path/to/yourCopyOf/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

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of the provided benchmark.

**What is being tested?**

The benchmark measures the performance difference between using Ramda's `R.map` function and the native `Array.prototype.map()` method in JavaScript. Specifically, it tests how long it takes to double each element of an array using both approaches.

**Options compared:**

Two options are being compared:

1. **Ramda's `R.map`**: This is a functional programming library that provides a higher-order function for mapping over arrays. In this case, the `R.map` function applies the `double` function to each element of the array.
2. **Array (native) `map()` method**: This is a built-in JavaScript method that applies a given function to each element of an array.

**Pros and cons:**

* **Ramda's `R.map`**:
	+ Pros:
		- Provides a functional programming style for mapping over arrays, which can be more concise and expressive than imperative loops.
		- Can be used with other Ramda functions to create composable pipelines.
	+ Cons:
		- Requires loading an external library (Ramda), which may introduce overhead due to network requests or file loading.
		- May have a steeper learning curve for developers unfamiliar with functional programming concepts.
* **Array (native) `map()` method**:
	+ Pros:
		- No additional libraries are required, making it a simpler and more lightweight option.
		- Well-established and widely supported, with good performance characteristics in most browsers.
	+ Cons:
		- May require more verbose code than Ramda's `R.map` function.

**Library usage:**

The benchmark uses the Ramda library for its `R.map` function. Ramda is a popular functional programming library that provides a wide range of higher-order functions for working with arrays, objects, and other data structures.

**Special JS feature or syntax:**

This benchmark does not use any special JavaScript features or syntax beyond what's available in the standard language specification.

**Other alternatives:**

If you don't want to use Ramda's `R.map`, you can also implement a simple mapping function using an imperative loop, like this:
```javascript
data.map(double);
```
This approach would not be as concise or expressive as Ramda's `R.map`, but it would still achieve the same result.

Additionally, if you're interested in exploring other libraries for functional programming, some alternatives to Ramda include:

* Lodash: A popular utility library that provides a wide range of functions for working with arrays, objects, and more.
* Underscore.js: Another widely used functional programming library that offers many of the same features as Ramda.
* Jest: While not primarily a functional programming library, Jest does provide some functional programming-related features, such as `map` and `filter`, that can be useful for benchmarking.

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: 8 years ago by: Guest

Jump to the latest result

Ramda

Array (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):