Benchmark: Lodash cloneDeep&spread operator

HTML Preparation code:

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

Script Preparation code:

var myObj = {
   margherita: {
      toppings: ['tomato sauce', 'mozzarella cheese'],
      prices: {
         small: '5.00',
         medium: '6.00',
         large: '7.00'
      }
   },
   prosciutto: {
      toppings: ['tomato sauce', 'mozzarella cheese', 'ham'],
      prices: { 
         small: '6.50', 
         medium: '7.50',
         large: '8.50' 
      }
   }
}

var myCopy = null;

Tests:

Lodash
myCopy = _.cloneDeep(myObj);
Spread
myCopy = {...myObj};

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Spread

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark and explain what's being tested, compared, and other considerations.

**Benchmark Overview**

The test compares two approaches to cloning and spreading objects in JavaScript:

1. Using the `_.cloneDeep` function from Lodash (a popular utility library for functional programming).
2. Using the spread operator (`{...}`) to create a shallow copy of an object.

**Lodash CloneDeep**

* Library: Lodash
* Purpose: Provides a deep cloning function that recursively creates new objects and copies nested properties.
* Use case: When you need to create a completely independent copy of an object, including all its properties and nested structures.

Pros:

* Provides a robust and flexible way to clone complex objects.
* Handles circular references, which can be challenging in vanilla JavaScript.

Cons:

* Adds external dependency (Lodash).
* Can be slower due to the overhead of creating new objects and copying properties.

**Spread Operator**

* Purpose: Creates a shallow copy of an object by iterating over its enumerable properties and adding them as new keys to a new object.
* Use case: When you need a simple, lightweight copy of an object that doesn't require deep cloning or handling nested structures.

Pros:

* Fast and efficient, since it only iterates over the top-level properties.
* No external dependency required.

Cons:

* Fails to preserve nested properties or objects.
* Not suitable for cloning complex data structures.

**Other Considerations**

* Performance: The spread operator is generally faster than using Lodash's `cloneDeep` function, especially for simple objects. However, as the object size increases, the difference may become negligible.
* Code readability and maintainability: Using a library like Lodash can make code more readable when working with complex cloning scenarios. In contrast, relying on the spread operator might lead to more verbose and less readable code.

**Special JS Feature/Syntax**

The test case doesn't use any special JavaScript features or syntax beyond the standard `_.cloneDeep` function from Lodash.

**Alternatives**

If you don't want to rely on an external library like Lodash, you can implement a custom cloning function using recursion and object iteration. This approach would be more suitable for simple objects but could become cumbersome for complex ones.

For example:
```javascript
function cloneObject(obj) {
  if (typeof obj !== 'object' || obj === null) return obj;
  const copy = Array.isArray(obj) ? [] : {};
  for (const key in obj) {
    copy[key] = cloneObject(obj[key]);
  }
  return copy;
}
```
This implementation provides a basic way to clone objects but lacks the robustness and performance of using Lodash's `cloneDeep` function.

Related benchmarks:

Lodash cloneDeep&spread operator (version: 0)

Comparing performance of: Lodash vs Spread

Created: 5 years ago by: Guest

Jump to the latest result

Lodash

Spread

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):