Benchmark: Ramda mapObjIndexed vs Ramda map

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.a*2;
}
var data = [{a:1}, {a:2}, {a:3}, {a:4}, {a:5}, {a:6}, {a:7}, {a:8}, 
            {a:9}, {a:10}, {a:11}, {a:12}, {a:13}, {a:14}, {a:15}, {a:16}, {a:17}, {a:18}, {a:19}, {a:20}, {a:21}, {a:22}, {a:23}, {a:24}, {a:25}, {a:26}, {a:27}, {a:28}, {a:29}, {a:30}];

Tests:

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

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda mapObjIndexed
Ramda map

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 break down the provided benchmarking setup and analyze what is being tested.

**Benchmark Overview**

The benchmark compares two approaches for mapping over an array: Ramda's `map` function with an iterator (Ramda `mapObjIndexed`) versus the native JavaScript `map` function (`Array.prototype.map`).

**What are we comparing?**

1. **Ramda `map`**: This function takes a callback function and returns a new array with each element of the original array mapped to the return value of the callback.
2. **Native `Array.prototype.map`**: This is a built-in JavaScript method that applies a given function to each element in an array, returning a new array with the results.

**Options being compared**

The two approaches are being tested for their performance differences on the same input data: an array of 30 objects with a single property `a`.

**Pros and Cons of each approach**

1. **Ramda `map` (with iterator)**:
	* Pros:
		+ Can handle non-iterable arrays or objects by using a proxy iterator.
		+ Provides more control over the iteration process, which can be beneficial for certain use cases.
	* Cons:
		+ May have additional overhead due to the use of an iterator.
2. **Native `Array.prototype.map`**:
	* Pros:
		+ Much faster performance, as it leverages optimized native code.
		+ Generally easier to understand and use, especially for simple transformations.
	* Cons:
		+ Limited control over the iteration process.

**Library used**

The `ramda` library is being used to provide an implementation of the `map` function with an iterator. Ramda is a functional programming library for JavaScript that provides various utilities and functions for working with data.

**Special JS feature or syntax**

There isn't any special JavaScript feature or syntax explicitly mentioned in this benchmark, but using the `map` function with an iterator (`mapObjIndexed`) does demonstrate some nuances of the language. However, for a wide range of software engineers, understanding of how to use iterators and map functions is already assumed.

**Other alternatives**

If you're interested in exploring other approaches or alternatives, here are a few options:

1. **Lodash's `map` function**: Lodash provides an implementation of the `map` function that can be used as an alternative to Ramda.
2. **Vanilla JavaScript with `forEach` and `Array.prototype.reduce`**: You could implement a mapping function using vanilla JavaScript by combining `forEach` and `Array.prototype.reduce`.
3. **Other functional programming libraries**: There are many other functional programming libraries for JavaScript, such as Immutable.js or Purescript.

Keep in mind that these alternatives may offer different trade-offs in terms of performance, ease of use, and control over the iteration process.

Related benchmarks:

Ramda mapObjIndexed vs Ramda map (version: 0)

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

Comparing performance of: Ramda mapObjIndexed vs Ramda map

Created: 2 years ago by: Guest

Jump to the latest result

Ramda mapObjIndexed

Ramda map

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):