Benchmark: cloneDeep vs structuredClone vs JSON clone

HTML Preparation code:

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

Script Preparation code:

var obj = [{"value":"64d4ac801e7ca8220d469901","title":"Bonner Carter"},{"value":"64d4ac8023a44301222299b6","title":"Candice Hoffman"},{"value":"64d4ac805d14b4ddca7caa0b","title":"Tamika Sanders"},{"value":"64d4ac807ccfee17f96a49c3","title":"Amie Bray"},{"value":"64d4ac80300d509a539e9352","title":"Giles Weeks"},{"value":"64d4ac805d12705449dc3703","title":"Leonard Salinas"},{"value":"64d4ac80807a84e72f802e54","title":"Hansen Brooks"},{"value":"64d4ac8063359f660571b4f1","title":"Ursula Cherry"},{"value":"64d4ac805d660307afabec7b","title":"Stephens Munoz"},{"value":"64d4ac80f58786476d3987ea","title":"Goldie Mendoza"},{"value":"64d4ac80d11b8f4f25ee15f7","title":"Fitzpatrick Nolan"},{"value":"64d4ac80236858817a1fcea1","title":"Jenkins Ferguson"},{"value":"64d4ac80424663ca6d377ce2","title":"Espinoza Barry"},{"value":"64d4ac80593a15689685bc5d","title":"Decker Erickson"},{"value":"64d4ac8011354f87753aba5d","title":"Kline Bernard"},{"value":"64d4ac80e7fe829b47a12aed","title":"Doyle 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Santiago"},{"value":"64d4ac80faae3a4da999330f","title":"Staci Henry"},{"value":"64d4ac803b7d9833602c2070","title":"Billie Wilson"},{"value":"64d4ac80085e765a600f6493","title":"Mccarty Hester"},{"value":"64d4ac804eb6486ebac6c1aa","title":"Melva Ramirez"},{"value":"64d4ac80dc9ea632842d1fe5","title":"Talley Richards"},{"value":"64d4ac80ebdd65cb42841618","title":"Catherine Cox"},{"value":"64d4ac80206934d10e258d4e","title":"Kellie Knight"},{"value":"64d4ac8038820299f08623f5","title":"Rice Mccarty"},{"value":"64d4ac80e07894987d93e767","title":"Gallagher Coffey"},{"value":"64d4ac80f2dc6b7e205ea236","title":"Rich Dale"},{"value":"64d4ac80393839c556a8f296","title":"Baxter Jordan"},{"value":"64d4ac80b6159f7446f92d44","title":"Chris Marsh"},{"value":"64d4ac80529489bce3e166d1","title":"Nicholson Schmidt"},{"value":"64d4ac8055fe9d8ccdd2d1cf","title":"Juliette Keith"},{"value":"64d4ac80fabd757086545fde","title":"Krista Miller"},{"value":"64d4ac80e7991bea8aed4146","title":"Ofelia 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Hubbard"},{"value":"64d4ac80ebeee6ff28928183","title":"Selena Buckley"},{"value":"64d4ac80031614e0a3fefa47","title":"Mitzi Mathews"},{"value":"64d4ac80f576ee8295c4b477","title":"Gross Bell"},{"value":"64d4ac802f9b38a57dd84dde","title":"Florine Mullins"}];

var result = null;

Tests:

cloneDeep
result = _.cloneDeep(obj);
structuredClone
result = structuredClone(obj);
JSON clone
result = JSON.parse(JSON.stringify(obj));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
cloneDeep
structuredClone
JSON clone

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

The provided information is a combination of benchmarking test cases and results, including:

1. A large JSON object `obj` with multiple properties and values.
2. Three individual test cases for benchmarking:
	* Cloning the object using Lodash's `cloneDeep` function.
	* Cloning the object using the Web API's `structuredClone` function.
	* Cloning the object using the `JSON.parse(JSON.stringify(obj))` method.
3. The raw UA string and browser information for a Chrome 115 browser on a Windows desktop platform, indicating that the benchmarking tests were run in this environment.

To answer the question accurately, I would need more context or specific details about what is being asked, such as:

* What are the expected outputs or results of the benchmarking tests?
* Are there any specific errors or edge cases to consider?
* Is there a particular aspect of the JSON object or benchmarking process that requires attention?

Given the information provided, I'll assume a general approach:

**Solution**

Based on the provided test cases and their respective benchmarking functions, here's a possible approach to resolve the issue:

1.  **Clone the Object using Lodash**: For the `cloneDeep` function from Lodash, you can use it as is:
    ```javascript
const result = _.cloneDeep(obj);
```

2.  **Clone the Object using Structured Clone**: To clone the object using structured clone, you would typically use a library like `structured-cloned`. However, since this library is not mentioned in the provided code snippet, I'll skip implementation details for now.

3.  **Clone the Object using JSON.parse(JSON.stringify())**: For the `JSON parse` method, ensure that your object does not contain any cyclic references or properties with unserializable values (like functions). If necessary, use a custom serialization function to avoid issues:
    ```javascript
const result = JSON.parse(JSON.stringify(obj));
```

**Example Implementation**

Here's an example implementation using Lodash and JavaScript:

```javascript
// Import Lodash
import _ from 'lodash';

function cloneObjectUsingLodash() {
  // Clone the object using Lodash
  const result = _.cloneDeep(obj);
  
  return result;
}

// Example usage:
const obj = {
  a: 1,
  b: [2, 3],
  c: { d: 4 },
};

console.log(cloneObjectUsingLodash());
```

**Note**: This implementation assumes that the `obj` variable is defined and available within the function scope. You should replace this with your actual object definition.

To address the question directly:

*   **What are the expected outputs or results of the benchmarking tests?**

The expected output depends on the specific requirements of your application. For example, if you want to preserve the original structure and values of the `obj` during cloning, use Lodash's `cloneDeep`. If preserving the structure is not a priority but speed is, consider using structured clone.

*   **Are there any specific errors or edge cases to consider?**

Yes:

*   Be cautious when dealing with cyclic references in objects, as they can lead to infinite recursion and errors.
*   JSON parse can fail if the object contains unserializable values (like functions) or cyclic references.
*   Consider using custom serialization techniques for objects that cannot be serialized directly.

For more information about structured clone and its usage, refer to [the official documentation](https://developer.mozilla.org/en-US/docs/Web/API/structuredClone).

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/115.0.0.0 Safari/537.36

Browser/OS: Chrome 115 on Windows

View result in a separate tab

Test name	Executions per second
cloneDeep	12163.4 Ops/sec
structuredClone	12334.8 Ops/sec
JSON clone	17604.4 Ops/sec

Related benchmarks:

cloneDeep vs structuredClone vs JSON clone (version: 0)

Comparing performance of: cloneDeep vs structuredClone vs JSON clone

Created: one year ago by: Guest

Jump to the latest result

cloneDeep

structuredClone

JSON clone

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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