Benchmark: Lodash cloneDeep vs structuredClone vs JSON clone s

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>

Script Preparation code:

var MyObject = {
  description: 'Creates a deep copy of source, which should be an object or an array.',
  myNumber: 123456789,
  myBoolean: true,
  jayson: {
    stringify: 'JSON.stringify() method converts a JavaScript value to a JSON string....',
    parse: 'JSON.parse() method parses a JSON string...'
  }
};

var myCopy = null;

Tests:

Lodash cloneDeep
myCopy = _.cloneDeep(MyObject);
Native structuredClone
myCopy = structuredClone(MyObject);
JSON clone
myCopy = JSON.parse(JSON.stringify(MyObject));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash cloneDeep
Native structuredClone
JSON clone

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

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

**Benchmark Overview**

The benchmark compares three approaches for creating a deep copy of an object:

1. **Lodash cloneDeep**: Uses the `cloneDeep` function from the Lodash library to create a deep copy of the input object.
2. **Native structuredClone**: Utilizes the built-in `structuredClone` API (available in modern browsers) to create a deep copy of the input object.
3. **JSON clone**: Uses the `JSON.parse(JSON.stringify())` method to create a shallow copy of the input object.

**Options Compared**

The benchmark compares the performance of each approach across different browsers and devices.

**Pros and Cons of Each Approach**

1. **Lodash cloneDeep**
	* Pros: Robust, widely supported, and easy to use.
	* Cons: Adds additional dependencies (Lodash library) and may introduce overhead due to its complexity.
2. **Native structuredClone**
	* Pros: Fast, lightweight, and only relies on the browser's API.
	* Cons: Requires modern browsers that support the `structuredClone` API, which might not be universally supported.
3. **JSON clone**
	* Pros: Simple, widely available, and doesn't require additional dependencies.
	* Cons: Creates a shallow copy (only copies property values, not recursive structures), which may lead to unexpected behavior in some cases.

**Libraries Used**

The benchmark uses the Lodash library for its `cloneDeep` function. The `structuredClone` API is built into modern browsers.

**Special JS Features or Syntax**

None of the tested approaches rely on special JavaScript features or syntax that would be unfamiliar to most software engineers.

**Other Considerations**

When choosing an approach, consider the trade-offs between performance, simplicity, and compatibility:

* For simple copying tasks, JSON clone might be sufficient.
* When working with complex objects or requiring a deep copy, Lodash cloneDeep or native structuredClone might be more suitable.
* If targeting modern browsers, native structuredClone is likely the best choice.

**Alternatives**

Other approaches to creating a deep copy of an object include:

1. **Array.prototype.slice() and Object.assign()**: For arrays and simple objects.
2. **For...in loops and Object.keys()**: For more complex objects or when manually handling recursive structures.

Keep in mind that these alternatives might not be as efficient or feature-rich as the Lodash cloneDeep approach, but they can still provide a good starting point for simpler copying tasks.

Related benchmarks:

Lodash cloneDeep vs structuredClone vs JSON clone s (version: 0)

https://developer.mozilla.org/en-US/docs/Web/API/structuredClone

Comparing performance of: Lodash cloneDeep vs Native structuredClone vs JSON clone

Created: 3 years ago by: Guest

Jump to the latest result

Lodash cloneDeep

Native structuredClone

JSON clone

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):