Benchmark: Map (Native vs Ramda vs Lodash) new

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.27.1/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);
Ramda 2
R.map(double, data);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Array (native)
Lodash
Ramda 2

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the world of Map() benchmarks.

**What is being tested?**

The provided JSON represents a benchmark test for measuring the performance of different approaches to map over an array:

1. **Array (native)**: The native `map()` function built into JavaScript arrays.
2. **Ramda**: A functional programming library that provides a `map()` function.
3. **Lodash**: Another popular functional programming library that also provides a `map()` function.

The test cases are designed to compare the performance of these three approaches on a simple dataset, where each element is a unique index value.

**Options compared**

Here's what's being compared:

* The native `map()` function (Array)
* Ramda's `map()` function
* Lodash's `map()` function

**Pros and Cons**

1. **Native Array map()**: Fastest execution time, but may not be as readable or maintainable for complex transformations.
2. **Ramda map()**: More expressive and flexible, thanks to its functional programming nature. However, it may come with a performance overhead due to the added abstraction.
3. **Lodash map()**: Similar to Ramda, Lodash's `map()` function offers more expressiveness, but also potentially slower execution times.

In general, the choice between these options depends on:

* Performance-critical applications: Native Array map()
* Code readability and maintainability: Ramda or Lodash
* Balance between performance and expressiveness: Either Ramda or Lodash

**Library descriptions**

1. **Ramda**: A lightweight functional programming library that provides a set of higher-order functions for manipulating arrays, objects, and sets. Its `map()` function takes two arguments: a function to apply to each element, and the array to map over.
2. **Lodash**: Another popular functional programming library that offers a broad range of utility functions for working with data structures like arrays, objects, and more. Its `map()` function is similar to Ramda's.

**Special JS features or syntax**

None are mentioned in this benchmark.

**Alternative approaches**

If you need to optimize map() performance further:

* Use a Just-In-Time (JIT) compiler like V8 (Chrome's engine) to optimize the native Array map() implementation.
* Consider using specialized libraries like `fast-map` or `map-ify`, which aim to improve performance while maintaining readability.
* If using functional programming libraries, explore optimizations specific to those libraries, such as memoization or caching.

Keep in mind that this benchmark is designed for a simple use case. Real-world applications may require more consideration of factors like data size, complexity, and other optimizations.

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36 Edg/94.0.992.31

Browser/OS: Chrome 94 on Windows

View result in a separate tab

Test name	Executions per second
Ramda	1471442.6 Ops/sec
Array (native)	1567176.8 Ops/sec
Lodash	1765978.6 Ops/sec
Ramda 2	1489851.8 Ops/sec

Related benchmarks:

Map (Native vs Ramda vs Lodash) new (version: 1)

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

Comparing performance of: Ramda vs Array (native) vs Lodash vs Ramda 2

Created: 3 years ago by: Registered User

Jump to the latest result

Ramda

Array (native)

Lodash

Ramda 2

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):