Benchmark: Map (Native vs Ramda vs Lodash)_2

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/4.17.11/lodash.min.js"></script>

Script Preparation code:

function double(n) {
	return n*2;
}
function add4(n) {
  return n + 4;
}
var data = [...Array(223)].map((v, idx) => idx);

Tests:

Ramda
R.map(R.compose(double, add4), data);
Array (native)
data.map(double).map(add4);
Lodash
_(data).map(double).map(add4);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Array (native)
Lodash

Fastest: N/A

Slowest: N/A

Latest 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 break down the provided benchmark and explain what is being tested.

**Benchmark Overview**

The benchmark measures the speed of three different approaches for mapping over an array: using `Array.prototype.map()` ( native JavaScript), Ramda's `R.map()`, and Lodash's `_map()` functions. The benchmark compares these approaches to see which one is the fastest.

**Test Cases**

There are three test cases:

1. **Ramda**: Uses Ramda's `R.map()` function, which applies a function (in this case, `double`) to each element of the array after applying another function (`add4`).
2. **Array (native)**: Uses JavaScript's native `map()` method, which applies a function (in this case, `double`) to each element of the array.
3. **Lodash**: Uses Lodash's `_map()` function, which is similar to Ramda's `R.map()`, but with some differences in behavior and usage.

**Options Compared**

The benchmark compares two approaches:

* Using native JavaScript's `Array.prototype.map()`
* Using a functional programming library (Ramda or Lodash) for mapping over the array

**Pros and Cons of Each Approach**

1. **Native JavaScript (`Array.prototype.map()`)**
	* Pros:
		+ Fast and efficient, as it is implemented in native code.
		+ Does not require any additional libraries.
	* Cons:
		+ Can be less readable and more verbose than other approaches, especially for complex transformations.
2. **Ramda's `R.map()`**
	* Pros:
		+ Provides a consistent and predictable API for functional programming tasks.
		+ Easy to read and understand, as the code is explicitly expressed in terms of functions.
	* Cons:
		+ Requires an additional library (Ramda) to be included.
		+ May have a slight performance overhead compared to native JavaScript's `map()`.
3. **Lodash's `_map()`**
	* Pros:
		+ Provides a consistent and predictable API for functional programming tasks, similar to Ramda's `R.map()`.
		+ Easy to read and understand, as the code is explicitly expressed in terms of functions.
	* Cons:
		+ Requires an additional library (Lodash) to be included.
		+ May have a slightly different behavior or API compared to Ramda's `R.map()`.

**Library Descriptions**

1. **Ramda**: A functional programming library for JavaScript that provides a consistent and predictable API for common tasks, such as mapping, filtering, and reducing arrays.
2. **Lodash**: A utility library for JavaScript that provides a large collection of functions for tasks such as array manipulation, string manipulation, and object manipulation.

**Special JS Features or Syntax**

There are no special JavaScript features or syntax used in the benchmark that require explanation.

**Other Alternatives**

If you prefer not to use functional programming libraries like Ramda or Lodash, there are other alternatives available:

1. **Underscore.js**: A functional programming library for JavaScript that provides a similar API to Lodash.
2. **JSDOM's `Array.prototype.map()` method**: Some JSDOM implementations provide an optimized version of the `map()` method that can be used instead of native JavaScript's implementation.

In summary, the benchmark tests three approaches for mapping over arrays: using native JavaScript's `Array.prototype.map()`, Ramda's `R.map()`, and Lodash's `_map()` functions. The results show which approach is the fastest, but also highlight the pros and cons of each approach in terms of performance, readability, and maintainability.

Related benchmarks:

Map (Native vs Ramda vs Lodash)_2 (version: 0)

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

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

Created: 7 years ago by: Guest

Jump to the latest result

Ramda

Array (native)

Lodash

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):