Benchmark: Lodash vs IMMUTABLE COPY vs Manuel

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/immutable/3.8.2/immutable.min.js'></script>
<script>
function copyDeep(value) {
  	if(!value)
  		return value;
    if (value.constructor === Array) {
        return value.map(copyDeep);
    }
    if (value.constructor === Object) {
        const copy = {};
        for (let k in value) {
            copy[k] = copyDeep(value[k]);
        }
        return copy;
    }
    return value;
}
  
function merge(target, src){
 if(!target || !src || target.constructor != Object || src.constructor !== Object) return target; 
 for(var key in src){
 	if(target[key]){
  		if(target[key].constructor === Object && src[key].constructor === Object){
  			target[key] = merge(target[key], src[key]);
  		}else{
  			target[key] = src[key];
  		}
  	}else {
		target[key] = src[key];
  	}
 }  
}
</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:

Immutable
myCopy = Immutable.fromJS(MyObject).mergeDeep({ jayson: {parse: 'JSON.parse() method parses a JSON string... 2'}}).toJS()
Lodash
myCopy = _.merge(_.cloneDeep(MyObject), { jayson: {parse: 'JSON.parse() method parses a JSON string... 2'}})
Manual
myCopy = merge(copyDeep(MyObject), { jayson: {parse: 'JSON.parse() method parses a JSON string... 2'}});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Immutable
Lodash
Manual

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/118.0.0.0 Safari/537.36

Browser/OS: Chrome 118 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Immutable	351615.4 Ops/sec
Lodash	470319.2 Ops/sec
Manual	1403487.8 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down what's being tested on the provided JSON data.

**Benchmark Definition**

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

1. **Immutable Copy**: Using the Immutable library, which creates an immutable copy of the original object using `fromJS()` and then merging with another object using `mergeDeep()`.
2. **Lodash**: Using Lodash's `cloneDeep()` function to create a deep copy of the original object and then merging with another object using `merge()`.
3. **Manual**: Implementing a custom recursive function `copyDeep()` to create a deep copy of the original object and then merging with another object.

**Options Compared**

The three approaches are being compared in terms of:

* Performance: How many executions per second each approach can handle on a specific device and browser configuration.
* Complexity: The number of lines of code required for each implementation.
* Maintainability: How easy it is to understand and modify the code for each approach.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

1. **Immutable Copy**
	* Pros:
		+ Immutable objects are thread-safe and easier to reason about.
		+ Immutable libraries like Immutable can simplify complex merging logic.
	* Cons:
		+ Performance might be slower due to the overhead of creating immutable objects.
		+ Can be less efficient for large datasets or deep copies.
2. **Lodash**
	* Pros:
		+ Well-maintained and widely used library with a large community.
		+ Provides a simple and concise way to create deep copies.
	* Cons:
		+ Might have performance issues due to the overhead of cloning objects.
		+ May not be as efficient for very large datasets or complex merges.
3. **Manual**
	* Pros:
		+ Custom implementation allows for fine-grained control over the copy process.
		+ Can potentially be more efficient than using a library.
	* Cons:
		+ Requires more code and expertise to implement correctly.
		+ May introduce bugs or inconsistencies if not implemented carefully.

**Other Considerations**

When choosing an approach, consider factors such as:

* Performance requirements: If speed is critical, the Manual or Lodash approaches might be suitable. However, Immutable's immutable nature can provide additional safety guarantees.
* Complexity tolerance: If simplicity and ease of maintenance are more important, Lodash or Immutable might be a better choice.
* Library dependencies: Using an external library like Lodash or Immutable requires considering potential dependencies, versioning, and compatibility issues.

**Latest Benchmark Results**

The results show that the Manual approach has the highest execution rate (1403487.75 executions/second), followed by Lodash (470319.15625 executions/second) and then Immutable (351615.4375 executions/second). This suggests that the Manual approach is currently the fastest, but the differences might not be significant enough to justify the complexity of implementing a custom solution.

Other alternatives for creating deep copies include:

* `Array.prototype.slice()` and `JSON.parse(JSON.stringify(obj))` for arrays
* Using native JavaScript features like `Object.assign()` or `Spread Operator`
* Implementing a custom recursive function using bitwise operators (e.g., `copyDeep()`)

Related benchmarks:

Lodash vs IMMUTABLE COPY vs Manuel (version: 0)

Lodash vs Immutable Copying

Comparing performance of: Immutable vs Lodash vs Manual

Created: 3 years ago by: Guest

Jump to the latest result

Immutable

Lodash

Manual

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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