Benchmark: Lodash cloneDeep vs JSON Clone big dict v2

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 = [...Array(150).keys()].reduce((acc,cur)=>{acc[cur]={
  description: 'Creates a deep copy of source, which should be an object or an array.',
  myNumber: 123456789,
  myBoolean: true,
  key:cur,
  jayson: {
    stringify: 'JSON.stringify() method converts a JavaScript value to a JSON string....',
    parse: 'JSON.parse() method parses a JSON string...'
  }
}; return acc;},{});
console.log('MyObject',MyObject);

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:

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

LLMs can make mistakes. Check important info.

Let's dive into the benchmark.

**What is being tested?**

The provided JSON represents a JavaScript microbenchmark that compares two approaches to create a deep copy of an object: using the `_.cloneDeep` function from Lodash and using the `JSON.parse(JSON.stringify())` method.

**Options compared:**

There are two options being compared:

1. **Lodash cloneDeep**: This approach uses the `_cloneDeep` function from Lodash, which is a utility function that creates a deep copy of an object.
2. **JSON Clone**: This approach uses the `JSON.parse(JSON.stringify())` method to create a deep copy of an object.

**Pros and Cons:**

* **Lodash cloneDeep**:
	+ Pros:
		- Specifically designed for creating deep copies, making it efficient and reliable.
		- Handles complex objects with nested arrays and objects.
	+ Cons:
		- Requires the Lodash library to be included in the test environment.
		- May have a slight overhead due to the dependency on the library.
* **JSON Clone**:
	+ Pros:
		- No external dependencies required, making it a lightweight option.
		- Can create copies of objects and arrays using the same method.
	+ Cons:
		- Not specifically designed for creating deep copies, which may lead to issues with complex objects.
		- May not handle certain types of data, such as dates or functions.

**Library:**

* **Lodash**: A utility library that provides a set of functional programming helpers and utilities. In this case, the `_cloneDeep` function is used to create deep copies of objects.

**Special JS feature/syntax:**

There are no special JavaScript features or syntax being tested in this benchmark. The tests only involve standard JavaScript object creation and copying.

**Other considerations:**

* **Performance**: Both approaches have different performance characteristics. Lodash's `_cloneDeep` function is generally faster than the `JSON.parse(JSON.stringify())` method, especially for large objects.
* **Readability**: Using the `JSON.parse(JSON.stringify())` method may be less readable and more prone to errors compared to using a dedicated cloning library like Lodash.

**Other alternatives:**

* **Other cloning libraries**: There are other JavaScript cloning libraries available, such as `lodash-es` (a lightweight version of Lodash), `json-cloner`, or `deep-clone`.
* **Native cloning methods**: Some browsers have native methods for creating deep copies of objects, but these methods may not be supported in all environments.

In summary, the benchmark compares two approaches to create deep copies of objects: using Lodash's `_cloneDeep` function and using the `JSON.parse(JSON.stringify())` method. The choice between these options depends on performance, readability, and the specific requirements of the application.

Related benchmarks:

Lodash cloneDeep vs JSON Clone big dict v2 (version: 0)

Comparing performance of: Lodash cloneDeep vs Json clone

Created: 6 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

No previous run results

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