Benchmark: ramda union vs Set for merging array with Object.keys

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/ramda/0.26.1/ramda.min.js'></script>

Tests:

Set
const first = ["andrey", "alexey", "vasya", "misha", "petya"]; const obj = { vasya: true, petya: true, kolya: true }; return new Set([...first, ...Object.keys(obj)]);
R.union
const first = ["andrey", "alexey", "vasya", "misha", "petya"]; const obj = { vasya: true, petya: true, kolya: true }; return R.union(first, Object.keys(obj));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Set
R.union

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/99.0.4844.84 Safari/537.36 HBPC/12.1.3.306

Browser/OS: Chrome 99 on Windows

View result in a separate tab

Test name	Executions per second
Set	2005944.8 Ops/sec
R.union	1325818.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Overview**

The provided JSON represents a benchmark test on MeasureThat.net, which compares two approaches for merging an array with `Object.keys`:

1. Using a built-in `Set` data structure
2. Using the Ramda library's `R.union` function

**Options Compared**

Two options are compared in this benchmark:

* **Set**: Using a built-in `Set` data structure to merge the arrays.
* **R.union**: Using the Ramda library's `R.union` function to merge the arrays.

**Pros and Cons of Each Approach**

### Set

Pros:

* Built-in, no external dependencies required
* Fast and efficient for small datasets
* Easy to implement

Cons:

* Not optimized for large datasets or complex data structures
* May not be as efficient as other approaches for certain data types (e.g., strings)

### R.union

Pros:

* Optimized for performance and efficiency
* Supports various data types, including strings
* Can handle large datasets and complex data structures

Cons:

* Requires an external library dependency (Ramda)
* May have a slight overhead due to the library's implementation

**Library: Ramda**

The Ramda library is a popular functional programming library for JavaScript. It provides a wide range of utility functions for data manipulation, filtering, mapping, and more. In this benchmark, `R.union` is used to merge two arrays.

**Special JS Feature/Syntax**

There doesn't seem to be any special JavaScript feature or syntax that's not part of the standard language. However, the use of a library like Ramda may require some familiarity with functional programming concepts and data manipulation techniques.

**Other Alternatives**

If you're looking for alternatives to `Set` or `R.union`, here are a few options:

* **Array.prototype.concat()**: This method can be used to merge two arrays, but it may not be as efficient as `Set` or `R.union`.
* **Array.prototype.push() + Array.prototype.indexOf()**: Another approach is to use `push()` to add elements from the second array to the first, and then use `indexOf()` to check for duplicates. However, this method can be slower and less efficient than using a built-in data structure like `Set` or `R.union`.

In summary, the benchmark compares two approaches for merging an array with `Object.keys`: using a built-in `Set` data structure versus the Ramda library's `R.union` function. The pros and cons of each approach are discussed, highlighting the benefits and drawbacks of each method.

Related benchmarks:

ramda union vs Set for merging array with Object.keys (version: 0)

123

Comparing performance of: Set vs R.union

Created: one year ago by: Guest

Jump to the latest result

Set

R.union

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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