Benchmark: lodash _.cloneDeep vs json.parse(stringify())

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/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);
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
Json Clone

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36

Browser/OS: Chrome 120 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Lodash CloneDeep	1551016.1 Ops/sec
Json Clone	1088538.4 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The benchmark is comparing two approaches to create a deep copy of an object:

1. **Lodash `.cloneDeep`**: This method clones a value by recursively creating new objects or arrays, depending on the original data type.
2. **JSON parsing and stringifying**: This approach uses the `JSON.parse()` and `JSON.stringify()` methods to convert the object to a JSON string and then parse it back into an object.

**Options Compared**

The benchmark is comparing two options:

* Lodash `.cloneDeep`
* JSON parsing and stringifying

**Pros and Cons of Each Approach:**

1. **Lodash `.cloneDeep`**
	* Pros:
		+ Can handle complex data structures, such as arrays and objects with nested properties.
		+ Returns a new object that is independent of the original.
		+ Often faster than manual JSON parsing and stringifying.
	* Cons:
		+ Requires the Lodash library to be included in the test environment.
		+ May have performance overhead due to the library's complexity.
2. **JSON parsing and stringifying**
	* Pros:
		+ Lightweight and easy to implement.
		+ Does not require any external libraries.
	* Cons:
		+ Can lead to shallow copies if the original object is not properly serialized.
		+ May have performance overhead due to the multiple steps involved.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for data manipulation, string manipulation, and more. The `.cloneDeep` method is one of its most useful functions, allowing developers to create deep copies of complex data structures.

**Special JS Feature or Syntax (None)**

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

**Other Alternatives**

If you're interested in exploring alternative approaches, here are a few options:

* **`Object.assign()`**: This method can be used to create a shallow copy of an object.
* **`Array.prototype.slice()` and `JSON.stringify()`**: These methods can be used together to create a deep copy of an array or an object with arrays as values.
* **`for...in` loop and JSON string generation**: A manual implementation using a `for...in` loop to iterate over the object's properties and generate a JSON string.

These alternatives may have different performance characteristics, complexity, or ease of use compared to the Lodash `.cloneDeep` method and the JSON parsing and stringifying approach.

Related benchmarks:

lodash _.cloneDeep vs json.parse(stringify()) (version: 0)

Comparing performance of: Lodash CloneDeep vs Json Clone

Created: 2 years ago by: Guest

Jump to the latest result

Lodash CloneDeep

Json Clone

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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