Benchmark: Map + Filter (Native vs Ramda)

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 filter(n) {
    return n % 2 === 0
}

var data = [...Array(20)].map((v, idx) => idx);

Tests:

Ramda
R.pipe(R.filter(filter), R.map(double))(data);
Array (native)
data.map(double).filter(filter);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Array (native)

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 benchmark and its test cases.

**Benchmark Overview**

The benchmark measures the speed of two approaches to filter and map an array: Ramda's `map` and `filter` functions versus Array (native) `map` and `filter` functions, using lodash's `map` function as a control. The benchmark also includes another approach using native JavaScript.

**Options Compared**

1. **Ramda**: Uses Ramda's `map` and `filter` functions.
	* Pros: Ramda is a functional programming library that provides a concise and expressive way to work with arrays. Its API is designed for consistency and readability, making it easy to understand and use.
	* Cons: Ramda requires an additional library dependency (ramda.js), which may slow down the benchmark due to overhead.
2. **Array (native)**: Uses native JavaScript's `map` and `filter` functions.
	* Pros: Native JavaScript functions are built-in and don't require any additional dependencies, making them a good choice for simplicity and performance.
	* Cons: The API is less concise and expressive than Ramda's, requiring more verbose code to achieve the same result.
3. **Lodash**: Uses lodash's `map` function as a control, which is similar to native JavaScript's `map` but with some additional features (e.g., support for partial functions).
	* Pros: Lodash provides a familiar API that's similar to native JavaScript, making it easy to understand and use.
	* Cons: Similar to Ramda, lodash requires an additional library dependency.

**Library and Purpose**

1. **Ramda**: A functional programming library for JavaScript that provides a comprehensive set of tools for working with arrays, functions, and objects.
2. **Lodash**: A utility library for JavaScript that provides a wide range of functions for common tasks, such as string manipulation, array iteration, and object transformation.

**Special JS Feature or Syntax**

None mentioned in the benchmark definition.

**Alternatives**

Other alternatives to these options could include:

1. Other functional programming libraries like Lodash's competitor, `Underscore.js`, or alternative JavaScript libraries like `Simpler` or `Ramda.js` variants.
2. Other array manipulation methods, such as using `forEach`, `reduce`, and `every` functions in combination with arrow functions or closures.

**Considerations**

When choosing between these options, consider the following factors:

1. **Performance**: Native JavaScript's approach may be faster due to the absence of library overhead.
2. **Conciseness and Readability**: Ramda's API is more concise and expressive, making it easier to understand and use for complex transformations.
3. **Simpllicity and Familiarity**: Lodash provides a familiar API that's easy to learn and use, especially for developers already familiar with its functions.
4. **Additional Dependencies**: Be mindful of the additional dependencies required by Ramda or Lodash, which may impact benchmark performance.

These considerations will help you choose the best approach for your specific use case.

Related benchmarks:

Map + Filter (Native vs Ramda) (version: 0)

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

Comparing performance of: Ramda vs Array (native)

Created: 2 years ago by: Guest

Jump to the latest result

Ramda

Array (native)

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):