Benchmark: Lodash 3 cloneDeep

HTML Preparation code:

https://cdnjs.cloudflare.com/ajax/libs/lodash.js/3.5.0/lodash.min.js

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:

run1
myCopy = _.cloneDeep(MyObject);
run2
myCopy = _.cloneDeep(MyObject);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
run1
run2

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided JSON data and explain what is being tested, compared, and the pros and cons of different approaches.

**Benchmark Definition**

The benchmark definition consists of two scripts:

1. **Script Preparation Code**: This code defines an object `MyObject` with various properties, including a nested object `jayson`. The script also initializes a variable `myCopy` to null.
2. **Html Preparation Code**: This is a link to a CDN-hosted copy of the Lodash library version 3.5.0.

The benchmark definition uses a JavaScript function from the Lodash library, specifically the `cloneDeep` function, which creates a deep copy of the input object.

**Test Cases**

There are two identical test cases:

1. `run1`
2. `run2`

Both test cases perform the same action: calling the `_.cloneDeep` function with the `MyObject` variable as an argument, assigning the result to the `myCopy` variable.

**Options Compared**

In this benchmark, only one option is being compared:

* The Lodash library's `cloneDeep` function
* A custom implementation (not shown in the benchmark definition)

The comparison is likely between the performance of the built-in Lodash function and a potentially optimized or hand-written equivalent implementation.

**Pros and Cons of Different Approaches**

1. **Lodash's `cloneDeep` function**: Pros:
	* Well-maintained and widely used library
	* Provides a robust and efficient way to create deep copies
	* Has been thoroughly tested and reviewed by the Lodash community
Cons:
	+ May introduce additional overhead due to the size of the library
2. **Custom Implementation**: Pros:
	+ Potentially optimized for specific use cases or performance-critical code
	+ Can be tailored to the specific requirements of the application
Cons:
	+ Requires more development effort and maintenance
	+ May not be as widely tested or reviewed as the Lodash implementation

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functional programming helpers, including functions for working with arrays, objects, strings, and more. The `cloneDeep` function is specifically designed to create deep copies of objects, which can be useful in various scenarios where immutability or performance are crucial.

**Special JS Feature/Syntax**

There is no special JavaScript feature or syntax used in this benchmark.

**Alternatives**

Other alternatives for creating deep copies of objects include:

1. **JSON.parse() + JSON.stringify()**: This method can be used to create a shallow copy, but it may not work correctly with deeply nested objects.
2. **for...in loops**: A manual loop-based approach can be used to iterate through the object's properties and recursively clone them.
3. **other libraries**: Other JavaScript libraries, such as Immutability or DeepClone, may also provide similar functionality for creating deep copies of objects.

Keep in mind that these alternatives might not offer the same level of performance or reliability as the Lodash implementation.

Related benchmarks:

Lodash 3 cloneDeep (version: 0)

Comparing performance of: run1 vs run2

Created: 7 years ago by: Registered User

Jump to the latest result

run1

run2

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):