Benchmark: Ramda uniq vs JS set

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>

Script Preparation code:

const arr = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]

Tests:

js
Array.from(new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]));
ramda
R.uniq([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
js
ramda

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36

Browser/OS: Chrome 131 on Linux

View result in a separate tab

Test name	Executions per second
js	5212773.5 Ops/sec
ramda	2954080.8 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's dive into the benchmark.

**What is being tested?**

The provided JSON represents a JavaScript microbenchmark that compares the performance of two approaches to remove duplicates from an array: using the native `Set` object in JavaScript (`Array.from(new Set(...))`) and using the Ramda library's `uniq` function (`R.uniq(...)`). Both approaches aim to achieve the same result – removing duplicate elements from the input array.

**Options compared**

There are two main options being compared:

1. **Native `Set` object**: This approach uses the native `Set` object in JavaScript, which is a built-in data structure that automatically removes duplicates when used with `Array.from()`. This method leverages the optimized implementation of `Set` in modern browsers.
2. **Ramda library's `uniq` function**: This approach uses the Ramda library's `uniq` function, which provides a more functional programming style for working with arrays and sets.

**Pros and cons**

Here are some pros and cons of each approach:

**Native `Set` object:**

Pros:

* Fast and efficient, as it leverages optimized native implementation
* Easy to use, as it's a built-in feature in JavaScript

Cons:

* Limited control over the iteration process (e.g., no option to skip elements)
* May not be suitable for all edge cases or complex data structures

**Ramda library's `uniq` function:**

Pros:

* More flexible and customizable, as it provides various options for handling duplicates
* Can be used with other Ramda functions to create more complex data processing pipelines
* Often preferred by developers who enjoy functional programming styles

Cons:

* Requires an additional library (Ramda) to be included in the project
* May have slower performance compared to native `Set` object, due to the overhead of loading and executing a JavaScript library

**Other considerations**

In addition to the two main approaches being compared, there are other factors to consider when evaluating these benchmarks:

* **Browser support**: The benchmark should be executed in different browsers to ensure compatibility and optimal performance.
* **Data size and complexity**: Larger input arrays or more complex data structures may affect the performance differences between the two approaches.
* **Optimization techniques**: Other optimization methods, such as using `filter()` instead of `uniq`, could also impact performance.

**Library and syntax**

The test case uses the Ramda library, which is a popular functional programming library for JavaScript. The `uniq` function from Ramda provides a way to remove duplicates from an array while preserving the original order of elements.

There are no special JavaScript features or syntaxes being used in this benchmark, as it focuses solely on comparing the performance of two approaches using standard JavaScript and Ramda functions.

Related benchmarks:

Ramda uniq vs JS set (version: 0)

Comparing performance of: js vs ramda

Created: one year ago by: Guest

Jump to the latest result

js

ramda

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):