Benchmark: Map (Native vs Ramda vs Lodash) latest 2021-01-18

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.28.0/ramda.min.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.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);
Array (native)
data.map(double);
Lodash
_.map(data, double);

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):

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Let's break down the benchmark and its test cases.

**Benchmark Overview**

The benchmark measures the performance of three different approaches to map over an array: `Array.prototype.map()` (native JavaScript), Ramda's `R.map()`, and Lodash's `_.map()`.

**Options Compared**

* **Native JavaScript**: Uses the built-in `map()` function on arrays.
	+ Pros:
		- Widely supported and optimized by most browsers.
		- Familiar syntax for developers.
	+ Cons:
		- May not be as efficient as specialized libraries, especially for large datasets.
		- Can be slower due to browser optimizations or caching.
* **Ramda**: A functional programming library that provides a `map()` function.
	+ Pros:
		- Optimized for performance and memory usage.
		- Provides a pure, predictable, and composable API.
	+ Cons:
		- Requires an external library (Ramsda.js).
		- May have a steeper learning curve due to its functional programming nature.
* **Lodash**: A utility library that provides a `map()` function as part of its _.map() method.
	+ Pros:
		- Wide adoption and support from other Lodash functions.
		- Easy to learn for developers familiar with the library.
	+ Cons:
		- May introduce additional overhead due to the larger library size.
		- Not optimized specifically for performance or memory usage.

**Library and Its Purpose**

* **Ramda**: A pure functional programming library designed for predictable, composable code. It provides a set of functions that can be combined to create new functions, allowing for declarative programming.
* **Lodash**: A utility library providing a wide range of helper functions, including `map()`. Its purpose is to provide a collection of small, reusable functions that make common tasks easier.

**Special JS Feature/Syntax**

There is no specific JavaScript feature or syntax being tested in this benchmark. The focus is on comparing the performance of different mapping approaches.

**Other Alternatives**

* **Other functional programming libraries**: Other libraries like Mithril, Ramda (with its own implementations), and Underscore.js might be compared to Ramda for their `map()` functions.
* **Native JavaScript alternatives**: Other native JavaScript methods or techniques, such as using `forEach()`, `reduce()`, or `filter()` with `Array.prototype.slice()`, could be tested for performance.

When choosing between these options, consider the specific requirements of your project, including:

* Performance: If you need raw speed, Native JavaScript might be suitable. However, specialized libraries like Ramda may offer better performance.
* Learning curve: If your team is already familiar with functional programming or has experience with Lodash, that library might be a good choice. Otherwise, Native JavaScript might be more accessible.
* Library size and complexity: If you prioritize simplicity and a smaller footprint, Native JavaScript might be the best option. However, if you need additional utility functions or want a more comprehensive library, Lodash could be suitable.

Ultimately, the choice of mapping approach depends on your project's specific needs and your team's familiarity with these options.

Related benchmarks:

Map (Native vs Ramda vs Lodash) latest 2021-01-18 (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: 4 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):