Benchmark: Ramda map latest vs native Array.map

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.27.1/ramda.min.js"></script>

Script Preparation code:

function double(n) {
	return n*2;
}
var data = [...Array(20)].map((v, idx) => idx);

Tests:

Ramda
R.map(double, data);
Native
data.map(double);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
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.

**Benchmark Overview**

The benchmark compares two approaches: using the Ramda library (specifically, its `R.map` function) and using the native `Array.prototype.map()` method in JavaScript. The goal is to measure which approach is faster for a simple transformation task: doubling each element of an array.

**Library: Ramda**

Ramda is a functional programming library for JavaScript that provides a set of higher-order functions, including `map`, for data processing. In this benchmark, `R.map` is used as the first test case, which applies the `double` function to each element in the `data` array using Ramda's `map` function.

**Native Array.prototype.map()**

The second test case uses the native `Array.prototype.map()` method, which also applies the `double` function to each element in the `data` array. This is a built-in JavaScript function that is widely supported across most browsers and platforms.

**Options Compared**

Two options are compared:

1. **Ramda's R.map**: Using Ramda's `R.map` function to apply the transformation.
2. **Native Array.prototype.map()**: Using the native `Array.prototype.map()` method in JavaScript to apply the transformation.

**Pros and Cons of Each Approach**

Here are some pros and cons of each approach:

**Ramda's R.map**

Pros:

* More concise and expressive code
* Simplifies data processing using functional programming principles

Cons:

* Additional overhead due to the use of a library
* May have slower performance compared to native JavaScript methods

**Native Array.prototype.map()**

Pros:

* Fastest execution time, as it's a built-in method optimized for performance
* No additional overhead from a library

Cons:

* More verbose code, especially for complex transformations
* Requires manual handling of edge cases and error handling

**Other Considerations**

When using Ramda or other functional programming libraries, consider the following:

* **Performance**: While some libraries like Lodash provide optimized implementations, others may introduce additional overhead. Always benchmark your specific use case to determine which approach is faster.
* **Code readability**: Choose an approach that balances conciseness with code readability. In this case, Ramda's concise syntax might make it more readable for developers familiar with functional programming principles.
* **Maintainability**: When using external libraries, consider the maintenance overhead. If you're working on a small project or prototype, a simple native implementation might be sufficient.

**Special JS Feature/Syntax**

This benchmark does not use any special JavaScript features or syntax beyond basic array operations and function definitions.

If you'd like to explore other alternatives, here are some options:

* **Lo-Dash**: Another popular functional programming library for JavaScript that provides similar functionality to Ramda.
* **Lodash**: A utility library that includes a `map` function, among many others. Its performance might be competitive with Ramda's `R.map`.
* **Pure-Function**: A small, lightweight library that provides only the `map` function, without additional features or overhead.

Keep in mind that this is just a brief overview of the benchmark. If you have specific questions or would like more information on any of these topics, feel free to ask!

Related benchmarks:

Ramda map latest vs native Array.map (version: 0)

Comparing performance of: Ramda vs Native

Created: 5 years ago by: Guest

Jump to the latest result

Ramda

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):