Benchmark: Map (Native vs Ramda vs Lodash)

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;
}
function add4(n) {
  return n + 4;
}
var data = [...Array(20)].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):

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

**What is tested?**

The provided JSON represents a benchmark that tests the speed of three different approaches to perform a map operation on an array:

1. **Native JavaScript Array Map**: This approach uses the built-in `map()` method of JavaScript arrays.
2. **Ramda Library's Map Function**: Ramda is a functional programming library for JavaScript, and its `map()` function is used to perform the mapping operation.
3. **Lodash Library's Map Function**: Lodash is another popular functional programming library for JavaScript, and its `map()` function is used to perform the mapping operation.

**Options compared**

The three approaches are compared in terms of their performance, which is measured by the number of executions per second.

**Pros and Cons of each approach**

1. **Native JavaScript Array Map**:
	* Pros: Built-in function, no external dependencies, fast execution.
	* Cons: Limited functionality, may not be suitable for complex data processing tasks.
2. **Ramda Library's Map Function**:
	* Pros: Powerful functional programming features, flexible data handling, well-documented API.
	* Cons: External dependency on Ramda library, may have performance overhead due to indirection.
3. **Lodash Library's Map Function**:
	* Pros: Comprehensive set of utility functions, flexible data handling, large community support.
	* Cons: External dependency on Lodash library, may have performance overhead due to indirection.

**Other considerations**

* The benchmark assumes that the input data is an array of numbers and uses two simple functions `double()` and `add4()` as examples. In a real-world scenario, the input data and function complexity can significantly impact the results.
* The benchmark does not account for the overhead of memory allocation or garbage collection when using external libraries like Ramda or Lodash.

**Special JS features or syntax**

There are no special JavaScript features or syntax mentioned in the provided code snippets. However, it's worth noting that functional programming languages and libraries often rely on concepts like immutability, higher-order functions, and function composition to achieve concise and expressive code.

**Library descriptions**

* **Ramda Library**: Ramda is a lightweight, immutable, and pure functional programming library for JavaScript. Its `map()` function takes a mapping function as an argument and applies it to each element of the input array.
* **Lodash Library**: Lodash is a comprehensive set of utility functions for JavaScript, including data manipulation, functional programming, and more. Its `map()` function takes a callback function as an argument and applies it to each element of the input array.

**Alternatives**

If you're interested in exploring alternative approaches or libraries for mapping arrays, here are a few options:

* **Underscore.js**: A popular utility library that includes a `map()` function similar to Lodash.
* **Lo-Dash**: A lightweight, immutable version of Underscore.js, with a focus on functional programming concepts.
* **Mocha.js**: A simple, in-place array mapping function that can be used as an alternative to Ramda's or Lodash's implementations.

Related benchmarks:

Map (Native vs Ramda vs Lodash) (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):