Benchmark: Lodash cloneDeep vs JSON Clone vs Ramda Clone vs Pvorb Clone Corrected

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/clone/2.1.2/clone.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));
Ramda clone
myCopy = R.clone(MyObject);
Pvorb Clone
myCopy = clone(MyObject, false);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash cloneDeep
Json clone
Ramda clone
Pvorb Clone

Fastest: N/A

Slowest: N/A

Latest run results:

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Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):

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Let's dive into the details of this benchmark test.

**What is being tested?**

The test case is comparing the performance of four different methods for creating a deep copy of an object in JavaScript:

1. `_.cloneDeep` from Lodash
2. Using `JSON.parse(JSON.stringify(object))`
3. `R.clone` from Ramda
4. `clone` function from Pvorb (a library that provides clone functionality)

**Options being compared**

The test case is comparing the execution time of each method, measured in executions per second. The goal is to determine which method is the fastest.

**Pros and cons of each approach**

1. **Lodash's _.cloneDeep**:
	* Pros: A dedicated deep cloning function that handles nested objects and arrays.
	* Cons: Requires Lodash library to be loaded.
2. **JSON.parse(JSON.stringify(object))**:
	* Pros: A simple, built-in solution using standard JavaScript methods.
	* Cons: May not work correctly with circular references or non-serializable data types.
3. **Ramda's R.clone**:
	* Pros: Another dedicated deep cloning function that handles nested objects and arrays.
	* Cons: Requires Ramda library to be loaded.
4. **Pvorb's clone** (with `false` as the second argument):
	* Pros: A lightweight, non-recursive implementation.
	* Cons: May not work correctly with circular references.

**Other considerations**

* The test case uses a specific object (`MyObject`) and measures the performance of each method in creating a copy of it.
* The results are provided for a Chrome 84 browser on a desktop platform (Mac OS X 10.15.6).

**Library usage**

* **Lodash**: A popular JavaScript utility library that provides many useful functions, including `_.cloneDeep`.
* **Ramda**: Another popular JavaScript utility library that provides functional programming helpers, including `R.clone`.
* **Pvorb**: A lightweight JavaScript library that provides clone functionality (likely a non-recursive implementation).

**JavaScript feature or syntax used**

None are explicitly mentioned in the test case. However, the use of `_.cloneDeep`, `JSON.parse(JSON.stringify(object))`, and `R.clone` implies some familiarity with these functions.

**Alternative approaches**

Other ways to create a deep copy of an object include:

* Using a recursive function
* Implementing a non-recursive clone algorithm (like Pvorb's)
* Utilizing a library like Immutable.js or Mori

Keep in mind that this test case focuses on the performance comparison of specific libraries and methods, rather than exploring alternative approaches.

Related benchmarks:

Lodash cloneDeep vs JSON Clone vs Ramda Clone vs Pvorb Clone Corrected (version: 0)

Comparing performance of: Lodash cloneDeep vs Json clone vs Ramda clone vs Pvorb Clone

Created: 6 years ago by: Guest

Jump to the latest result

Lodash cloneDeep

Json clone

Ramda clone

Pvorb Clone

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.1:latest, generated one year ago):