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), stuff);
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 gemma2:9b, generated one year ago):

LLMs can make mistakes. Check important info.

This benchmark compares the performance of applying a series of transformations to an array using three different approaches:

* **Ramda:** A functional programming library known for its concise and expressive syntax. The test uses `R.map(R.compose(double, add4), stuff);` which applies two functions sequentially (`double` then `add4`) to each element of the `stuff` array using Ramda's `map` and `compose` functions.

* **Native JavaScript Array:** This option leverages the built-in `.map()` method available in JavaScript arrays. The test uses `data.map(double).map(add4)` which applies `double` to each element, then maps the result with `add4`, effectively chaining the transformations.

* **Lodash:** Another popular library offering utility functions for working with arrays and objects. The test utilizes `_(data).map(double).map(add4)` which applies the same transformation logic as the native JavaScript approach but using Lodash's syntax for array manipulation.

**Pros/Cons:**

* **Ramda:**  
    * **Pros:** Conciseness, functional paradigm encourages immutability and clear code structure.
    * **Cons:** Can have a steeper learning curve due to its functional nature, potential performance overhead compared to optimized native methods in some cases.

* **Native JavaScript Array:** 
    * **Pros:**  Efficient for basic array operations as it's directly implemented in the language, widely understood and used. 
    * **Cons:** Can lead to more verbose code when applying complex transformations, less functional programming style.

* **Lodash:** 
    * **Pros:** Offers a wide range of utility functions, syntax similar to native JavaScript but with added convenience, good performance for common operations.
    * **Cons:**  Adds an extra dependency to your project, can be slightly slower than optimized native methods in some cases.

**Other Considerations:**

The choice between these approaches often depends on the specific task and the overall project context.

* **Project Size & Complexity:** For smaller projects or simple transformations, the native JavaScript approach might be sufficient.
* **Team Familiarity:** If your team is already familiar with Ramda or Lodash, using them can improve code maintainability and readability.

**Alternatives:**

There are other libraries besides Ramda and Lodash that could be used for similar tasks, such as:

* **Immutable.js:** Focuses on immutability and offers efficient data transformations.
* **Underscore.js:** Similar to Lodash but with a more minimal set of functions.

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 gemma2:9b, generated one year ago):