Benchmark: Ramda map vs Array.map - 100 dataset

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 = [...Array(100)].map((n, 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:

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 dive into the world of JavaScript microbenchmarks on MeasureThat.net.

The provided benchmark compares two approaches to perform a simple transformation operation on an array: using the native `Array.map()` method versus Ramda's `R.map()`. We'll break down what's being tested, the options compared, and their pros and cons, as well as consider other alternatives.

**What's being tested?**

In this benchmark, we're testing the performance difference between two functions:

1. **Native `Array.map()`**: This is a built-in JavaScript method that applies a specified function to each element of an array.
2. **Ramda's `R.map()`**: Ramda is a functional programming library for JavaScript. Its `R.map()` function applies a specified function to each element of a collection.

**Options compared**

The benchmark compares the performance of these two functions on a dataset of 100 elements, where each element is an index (0-99).

**Pros and Cons:**

* **Native `Array.map()`:**
	+ Pros:
		- Fast and efficient, as it's implemented in native JavaScript.
		- Easy to use and understand for developers familiar with the language.
	+ Cons:
		- May not be as expressive or flexible as functional programming approaches like Ramda's `R.map()`.
* **Ramda's `R.map()`**:
	+ Pros:
		- More expressive and flexible than native `Array.map()`, making it easier to write composable code.
		- Can be useful for developers already familiar with functional programming concepts.
	+ Cons:
		- May incur a small performance overhead due to the additional library layer.

**Library: Ramda**

Ramda is a popular JavaScript library for functional programming. Its `R.map()` function applies a specified function to each element of a collection (array, object, or other iterable) while preserving the original structure of the data. In this benchmark, Ramda's `R.map()` is used as a replacement for native `Array.map()`, allowing developers to write more composable and expressive code.

**Special JS feature: None**

This benchmark doesn't involve any special JavaScript features or syntax.

**Other alternatives**

If you prefer not to use Ramda or the native `Array.map()` method, there are alternative approaches:

1. **Using a different functional programming library**, such as Lodash's `map()` function.
2. **Implementing your own mapping function using loops and array indexing**, which would likely be slower than both native `Array.map()` and Ramda's `R.map()`.
3. **Using other JavaScript methods**, like `forEach()` or `reduce()`, although these might not provide the same level of performance as `Array.map()`.

Keep in mind that this benchmark is designed to compare the performance of specific functions, rather than advocating for a particular approach or library.

Related benchmarks:

Ramda map vs Array.map - 100 dataset (version: 0)

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

Comparing performance of: Ramda vs Array (native)

Created: 7 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):