Benchmark: sdfgsdfg - MeasureThat.net

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.4/lodash.min.js"></script>

Script Preparation code:

window.obj = {};

for (var i = 0, len = 10000; i < len; i++) {
  var arr = []
  obj['key' + i] = arr
  for (var n = 0, len = 10; n < len; n++) {
    arr.push({ ['key' + n]: n });
  }
}

Tests:

Lodash
const a2 = _.clone(arr)
Native
const a3 = arr.slice()

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Native

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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

LLMs can make mistakes. Check important info.

I'll break down the benchmark explanation for you.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmark created on MeasureThat.net. The benchmark tests two approaches to cloning an array in JavaScript: using Lodash and native JavaScript functions.

**Script Preparation Code**

The Script Preparation Code is used to prepare the test environment:
```javascript
window.obj = {};
for (var i = 0, len = 10000; i < len; i++) {
  var arr = [];
  obj['key' + i] = arr;
  for (var n = 0, len = 10; n < len; n++) {
    arr.push({ ['key' + n]: n });
  }
}
```
This code creates a large array `arr` with 10000 elements, each containing an object with two properties: `key` and `value`. The resulting array is stored in the `obj` object.

**Html Preparation Code**

The Html Preparation Code includes a reference to Lodash:
```html
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.4/lodash.min.js"></script>
```
This script tag loads the Lodash library, which is used in one of the benchmark test cases.

**Benchmark Test Cases**

There are two individual test cases:

1. **Lodash**: `const a2 = _.clone(arr)`
	* This test case uses the `_clone` function from Lodash to clone the `arr` array.
	* The purpose of this test is to measure the performance of Lodash's cloning functionality.
2. **Native**: `const a3 = arr.slice()`
	* This test case uses the built-in `slice()` method to clone the `arr` array.
	* The purpose of this test is to measure the performance of native JavaScript's cloning functionality.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Lodash**:
	* Pros: Lodash provides a simple and efficient way to clone arrays, with a well-documented API.
	* Cons: Using an external library may introduce additional overhead due to the weight of the library itself, as well as potential differences in performance compared to native JavaScript implementations.
2. **Native (slice())**:
	* Pros: This approach is lightweight and does not require loading any external libraries, making it a good choice for pure JavaScript applications.
	* Cons: The `slice()` method may be less efficient than Lodash's cloning functionality, especially for large arrays.

**Library Considerations**

Lodash is a popular utility library that provides various functional programming helpers. In this benchmark, the `_clone` function is used to clone arrays, which is a common use case in JavaScript development.

**Special JS Features or Syntax**

None of the test cases use any special JavaScript features or syntax beyond what is commonly available in modern browsers.

**Alternatives**

If you're interested in exploring alternative cloning approaches, here are some other options:

* `Array.prototype.map()`: This method creates a new array by applying a transformation to each element of the original array.
* `Array.prototype.reduce()`: This method applies a reduction function to each element of the original array and returns a single value.

Keep in mind that these alternatives may have different performance characteristics compared to Lodash's cloning functionality or native JavaScript's `slice()` method.

Related benchmarks:

sdfgsdfg (version: 0)

Comparing performance of: Lodash vs Native

Created: 7 years ago by: Guest

Jump to the latest result

Lodash

Native

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):