Benchmark: Object Clone Lodash vs structuredClone

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>

Script Preparation code:

var arr = new Array(100000000).fill(0);

Tests:

Lodash
_.clone(arr);
structuredClone
structuredClone(arr)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
structuredClone

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/108.0.0.0 Safari/537.36

Browser/OS: Chrome 108 on Windows

View result in a separate tab

Test name	Executions per second
Lodash	0.3 Ops/sec
structuredClone	0.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark measures the performance of two methods for cloning an object in JavaScript: `lodash.clone` and `structuredClone`.

**Options Compared**

Two options are compared:

1. **Lodash**: The `_.clone()` method from the Lodash library, which is a utility library that provides a wide range of functions for functional programming.
2. **Structured Clone**: The `structuredClone()` function, which is a native JavaScript function introduced in ECMAScript 2020 (ES2020) as part of the WebAssembly specification. It allows cloning objects without creating new objects or allocating memory.

**Pros and Cons**

Here are some pros and cons for each approach:

* **Lodash**: Pros:
	+ Wide range of features beyond object cloning
	+ Easy to use and understand, especially for developers familiar with functional programming
	+ Well-maintained and widely adopted library
*   Cons:
    *   Adds unnecessary overhead due to the complexity of Lodash functions
    *   May not be optimized for performance

**Structured Clone**

Pros:

*   Native implementation, which means it's more likely to be optimized for performance
*   Creates a new object without allocating memory, reducing garbage collection overhead
*   Supports cloning objects with complex references and cyclic dependencies

Cons:

*   Introduced in ES2020, so not supported in older browsers or environments
*   May require additional setup or configuration, especially for developers unfamiliar with the function

**Library and Syntax**

The `structuredClone()` function is part of the ECMAScript standard, which means it's a native JavaScript function. It was introduced as part of the WebAssembly specification to provide a way to clone objects without creating new objects or allocating memory.

There is no special syntax required to use the `structuredClone()` function. You can simply call it on an object, like this:
```javascript
const obj = { foo: 'bar' };
const clonedObj = structuredClone(obj);
```
**Alternative Approaches**

Other alternatives for cloning objects in JavaScript include:

*   **JSON.parse(JSON.stringify(obj))**: This method creates a new object by serializing the original object to JSON and then parsing it back into an object. While it's simple, it can be slower than the `structuredClone()` function.
*   **Object.assign()**: This method creates a new object by copying properties from the original object. It's faster than `JSON.parse(JSON.stringify(obj))` but still may not outperform `structuredClone()` for large objects.

Keep in mind that these alternatives have different trade-offs and may not offer the same level of performance or functionality as the `structuredClone()` function.

Related benchmarks:

Object Clone Lodash vs structuredClone (version: 0)

Compare performence for cloning an object in JS between lodash.clone and structuredClone

Comparing performance of: Lodash vs structuredClone

Created: 2 years ago by: Guest

Jump to the latest result

Lodash

structuredClone

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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