Benchmark: Map (Native vs Ramda vs Lodash) 4x workload

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/4.17.5/lodash.min.js"></script>

Script Preparation code:

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

Tests:

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

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:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:77.0) Gecko/20100101 Firefox/77.0

Browser/OS: Firefox 77 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
Ramda	253825.9 Ops/sec
Array (native)	1533706.9 Ops/sec
Lodash	771794.9 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):

LLMs can make mistakes. Check important info.

Let's break down the benchmark and its components.

**Benchmark Definition**

The test measures the speed of three different approaches to apply a transformation function (`double(n)`) to an array of 20 elements:

1. **Ramda**: Uses the Ramda library to chain four `map` operations.
2. **Array (native)**: Applies four `map` operations directly on the native JavaScript array using the `map()` method.
3. **Lodash**: Uses the Lodash library to chain four `map` operations.

**Options Compared**

The benchmark compares three different approaches:

* Ramda's `map` function, which is a higher-order function that takes a transformation function and an array as input, returning a new array with the transformed values.
* The native JavaScript `map()` method, which applies a given function to each element of an array and returns a new array with the results.
* Lodash's `map` function, which is similar to Ramda's but with additional features like support for iteratees (functions that take multiple arguments) and a more comprehensive set of utility functions.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Ramda**: Pros:
	+ Provides a concise and expressive way to chain operations on arrays.
	+ Offers a rich set of utilities for data manipulation and transformation.
	+ Can be faster than native JavaScript when dealing with large datasets due to its optimized implementation.
* Cons:
	+ Requires an additional library download and import, which can add overhead.
	+ May have compatibility issues if not used correctly.
* **Array (native)**: Pros:
	+ Native JavaScript, so no additional libraries are required.
	+ Simple and familiar API for most developers.
	+ No potential compatibility issues or library dependencies.
* Cons:
	+ Can be slower than Ramda due to the overhead of creating and managing intermediate arrays.
	+ More verbose code may be generated compared to Ramda's concise syntax.
* **Lodash**: Pros:
	+ Offers a comprehensive set of utility functions for data manipulation and transformation.
	+ Provides additional features like iteratees, which can be useful in certain scenarios.
	+ Can be faster than native JavaScript when dealing with large datasets due to its optimized implementation.
* Cons:
	+ Requires an additional library download and import, similar to Ramda.
	+ May have compatibility issues if not used correctly.

**Libraries**

The benchmark uses the following libraries:

* **Ramda**: A functional programming library that provides a concise and expressive way to work with arrays and data structures. Its `map` function is used to apply a transformation function to each element of an array.
* **Lodash**: A utility-first JavaScript library that provides a comprehensive set of functions for data manipulation, transformation, and iteration. Its `map` function is used to apply a transformation function to each element of an array.

**JavaScript Features**

The benchmark does not use any special JavaScript features or syntax beyond the standard language. It only relies on modern JavaScript capabilities like arrays, function composition, and higher-order functions.

**Alternatives**

Other alternatives for data transformation and array operations include:

* **Underscore.js**: A utility-first library that provides a concise and expressive way to work with arrays and data structures.
* **Lo-Dash**: A lightweight alternative to Lodash that provides similar functionality without the additional features and dependencies.
* **Preact**: A virtual DOM library that also provides an array of utility functions for data manipulation and transformation.

These alternatives may offer different trade-offs in terms of performance, conciseness, and compatibility, depending on the specific use case and requirements.

Related benchmarks:

Map (Native vs Ramda vs Lodash) 4x workload (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>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one month ago):