Benchmark: lodash uniq vs array.from set

HTML Preparation code:


<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js'></script>

Tests:

Set
var l = new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]); return Array.from(l);
Array
var l = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]; return _.uniq(l);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Set
Array

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36

Browser/OS: Chrome 116 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Set	4002984.2 Ops/sec
Array	10295631.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared options, pros and cons, and other considerations.

**Benchmark Overview**

The benchmark compares two approaches to remove duplicates from an array:

1. Using `Array.from()` and a regular Set (Set Approach)
2. Using Lodash's `uniq` function (Lodash Approach)

**Set Approach (Individual Test Case)**

```javascript
var l = new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);\r\nreturn Array.from(l);
```

In this test case:

* A Set is created with duplicate values (e.g., multiple occurrences of the number `7`).
* The `Array.from()` function is used to convert the Set to an array.
* The resulting array is returned.

**Lodash Approach (Individual Test Case)**

```javascript
var l = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7];\r\nreturn _.uniq(l);
```

In this test case:

* An array is created with duplicate values (e.g., multiple occurrences of the number `7`).
* The Lodash `uniq` function is used to remove duplicates from the array.
* The resulting array without duplicates is returned.

**Comparison and Pros/Cons**

Both approaches achieve similar results: removing duplicates from an array. However, there are differences in their behavior:

1. **Performance:** Set Approach is likely to be faster since it leverages built-in JavaScript functionality (`Array.from()` and `Set`). Lodash Approach uses a custom implementation, which might incur additional overhead.
2. **Memory Usage:** Set Approach requires more memory to store the duplicate values, while Lodash Approach only stores unique values in the resulting array.
3. **Functionality:** Both approaches return an array without duplicates, but Lodash Approach is part of a larger utility library and may offer additional features.

**Other Considerations**

1. **Browser Support:** Set Approach is supported by most modern browsers, while Lodash Approaches may require a polyfill or specific browser versions.
2. **Library Dependence:** Using Lodash requires including the library in your project, which might add unnecessary overhead for smaller projects or those with limited dependencies.

**Alternatives**

For removing duplicates from an array:

1. Using `Array.from()` and a regular Set:
```javascript
var arr = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7];
var uniqueArr = Array.from(new Set(arr));
```

2. Using the `filter()` method:
```javascript
var arr = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7];
var uniqueArr = arr.filter((val, idx) => {
    return arr.indexOf(val) === idx;
});
```

Keep in mind that these alternatives might not be as efficient or feature-rich as the Set Approach or Lodash Approach.

When to use each approach:

* Use Set Approach when performance and memory efficiency are crucial.
* Use Lodash Approach when you need a lightweight, easy-to-use solution with additional utility functions from the Lodash library.

Related benchmarks:

lodash uniq vs array.from set (version: 0)

Comparing performance of: Set vs Array

Created: one year ago by: Guest

Jump to the latest result

Set

Array

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):