Benchmark: lodash uniq vs Set spread operator

HTML Preparation code:

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

Tests:

Spread Operator
var l = new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]); return [...l];
use lodash
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
Spread Operator
use lodash

Fastest: N/A

Slowest: N/A

Latest run results:

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

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I'll break down the provided JSON and explain what's being tested, the different approaches compared, their pros and cons, and other considerations.

**Benchmark Definition**

The benchmark is defined in the following JSON:

```
{
    "Name": "lodash uniq vs Set spread operator",
    "Description": null,
    "Script Preparation Code": null,
    "Html Preparation Code": "\r\n<script src='https://cdn.jsdelivr.net/npm/lodash@4.17.10/lodash.min.js'></script>"
}
```

This benchmark measures the performance of two different approaches:

1. **Use of Lodash's `uniq` function**: This approach uses the `lodash` library to remove duplicate elements from an array.
2. **Using the spread operator (`...`) with a `Set` data structure**: This approach uses a `Set` object and the spread operator to remove duplicate elements from an array.

**Individual Test Cases**

The benchmark consists of two individual test cases:

1. **Spread Operator (Test Case 1)**:
```
{
    "Benchmark Definition": "var l = new Set([1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7]);\r\nreturn [...l];",
    "Test Name": "Spread Operator"
}
```

This test case creates a `Set` object with duplicate elements and then uses the spread operator to create a new array with unique elements.

2. **Use Lodash (Test Case 2)**:
```
{
    "Benchmark Definition": "var l = [1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7];\r\nreturn _.uniq(l);",
    "Test Name": "use lodash"
}
```

This test case creates an array with duplicate elements and then uses Lodash's `uniq` function to remove duplicates.

**Library: Lodash**

Lodash is a popular JavaScript library that provides various utility functions, including the `uniq` function used in Test Case 2. The `uniq` function removes duplicate elements from an array by creating a new array with unique elements.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntaxes being tested in this benchmark.

**Other Alternatives**

If you wanted to test similar approaches, you could consider the following alternatives:

* Using the `Set` data structure without the spread operator (e.g., using `new Set([1, 2, 3, ...]).size` to get the number of unique elements).
* Using a different library or implementation for removing duplicates (e.g., using `Array.prototype.filter()` with a callback function).
* Testing other algorithms for removing duplicates (e.g., sorting the array and then skipping consecutive duplicates).

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Use Lodash's `uniq` function**:
	* Pros: Easy to use, efficient implementation.
	* Cons: Adds external dependency, may not be suitable for all scenarios (e.g., if performance is critical).
2. **Using the spread operator (`...`) with a `Set` data structure**:
	* Pros: Efficient, easy to implement, and doesn't add external dependencies.
	* Cons: May not be supported in older browsers or environments, can be slower for large datasets.

In summary, this benchmark compares two efficient approaches for removing duplicates from an array: using Lodash's `uniq` function and the spread operator with a `Set` data structure. The results will help users determine which approach is best suited for their specific use case.

Related benchmarks:

lodash uniq vs Set spread operator (version: 0)

Comparing performance of: Spread Operator vs use lodash

Created: 7 years ago by: Guest

Jump to the latest result

Spread Operator

use lodash

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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