Benchmark: lodash uniq vs Array.from(new Set()) vs spread new Set() vs for vs for memory optimized 4

HTML Preparation code:

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

Script Preparation code:

var array = [];
for (let i = 0; i < 100000; i++) {array.push(~~(Math.random() * 2000))}

Tests:

Spread
return [...new Set(array)]
use lodash
return _.uniq(array);
Array.from
return Array.from( new Set(array) );
For
const visited = {}; const uniques = []; const initial = array; for(let i=0;i<initial.lenght;i++){ if(!visited[initial[i]]) { visited[initial[i]] = true; uniques.push(initial[i]); } } return uniques
For memory optimized
const visited = {}; const uniques = []; const initial = array; for(let i=0;i<initial.lenght;i++){ if(!(initial[i] in visited)) { visited[initial[i]] = undefined; uniques.push(initial[i]); } } return uniques

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Spread
use lodash
Array.from
For
For memory optimized

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36

Browser/OS: Chrome 119 on Windows

View result in a separate tab

For memory optimized

15.5M/s

For

15.5M/s

Array.from

559/s

use lodash

539/s

Spread

535/s

View exact numbers

Test name	Executions per second
✓ For memory optimized	15,547,500 Ops/sec
For	15,491,293 Ops/sec
Array.from	559 Ops/sec
use lodash	539 Ops/sec
Spread	535 Ops/sec

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

LLMs can make mistakes. Check important info.

**Benchmark Overview**

The provided benchmark compares the performance of four different approaches to find unique elements in an array:

1. `Array.from(new Set(array))`
2. `_.uniq(array)` (using Lodash library)
3. `for` loop with manual handling of unique elements
4. `for` loop with optimized memory usage

**Options Comparison**

The benchmark tests each approach on a fixed dataset of 100,000 random integers between 0 and 2000.

* **Array.from(new Set(array))**: Uses the `Set` data structure to remove duplicates from the array.
	+ Pros: Simple and efficient, no need to manually handle unique elements.
	+ Cons: Requires modern JavaScript features (ES6+), may not work in older browsers or environments.
* **_.uniq(array)` (using Lodash library)**: Uses the `uniq` function from Lodash to remove duplicates from the array.
	+ Pros: Convenient and efficient, no need to manually handle unique elements.
	+ Cons: Requires external dependency (Lodash), may not work in older browsers or environments.
* **for loop with manual handling**: Manually iterates through the array to find unique elements using a `visited` object.
	+ Pros: Platform-independent, no external dependencies required.
	+ Cons: More complex and error-prone, requires careful handling of edge cases.
* **for loop with optimized memory usage**: Optimized version of the manual loop approach, using `in` operator instead of indexing to check for unique elements.
	+ Pros: Efficient and platform-independent, reduces memory usage compared to the original manual loop.
	+ Cons: Still more complex than the Array.from approach.

**Library Overview**

The Lodash library is a popular utility library that provides various functions for common tasks, including data manipulation. In this benchmark, `_.uniq(array)` is used to remove duplicates from an array.

**Special JS Features or Syntax**

None mentioned in the provided information.

**Benchmark Results**

The latest benchmark results show that:

1. **For memory optimized**: The fastest approach, with approximately 15.5 million executions per second.
2. **For**: The next fastest approach, with around 15.4 million executions per second.
3. **Array.from**: The slowest approach, with about 0.56 million executions per second (likely due to modern JavaScript features and dependencies).
4. **Use Lodash**: The slowest approach among the four, with approximately 0.54 million executions per second.

**Other Alternatives**

Some alternative approaches that could be tested in a benchmark include:

* Using `Map` data structure instead of `Set`
* Using a more optimized algorithm for finding unique elements
* Comparing performance using different array sizes or distributions
* Testing performance on different types of input data (e.g., strings, objects)

lodash uniq vs Array.from(new Set()) vs spread new Set() vs for vs for memory optimized 4 (version: 0)

Comparing performance of: `Spread vs use lodash vs Array.from vs For vs For memory optimized`

Created: 2 years ago by: Guest

Go to the latest result

Spread

use lodash

Array.from

For

For memory optimized

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

lodash uniq vs Array.from(new Set()) vs spread new Set() vs for vs for memory optimized 4 (version: 0)

Comparing performance of: Spread vs use lodash vs Array.from vs For vs For memory optimized

Created: 2 years ago by: Guest

Go to the latest result

Spread

use lodash

Array.from

For

For memory optimized

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Spread vs use lodash vs Array.from vs For vs For memory optimized`