Benchmark: Clone tests - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

var biggishObject = {
  name: "Sam Wiseman III",
  address: '1234 Orchid Drive, /n Minneapolis, MN',
  favoriteColors:['blue','green', 'silver'],
  homeTown: "Seattle, WA",
  pets: true,
  petNames: ['Cabbage', 'Nancy','Tom Collins'],
  carDriven: {
    make: 'Toyota',
    model: 'GR 86',
    year: 2024,
    color: 'blue'
  },
  dob: '1972-07-30'
}

copy = null;

Tests:

deep clone
copy = _.cloneDeep(biggishObject)
Spread
copy = { ...biggishObject }
JSON
copy = JSON.parse(JSON.stringify(biggishObject))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
deep clone
Spread
JSON

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and explain what's being tested, along with the pros and cons of each approach.

**Benchmark Overview**

The benchmark compares three methods for creating a deep copy of a complex JavaScript object: `_.cloneDeep` from Lodash, Spread Operator (`{ ... }`), and JSON parsing (`JSON.parse(JSON.stringify())`). The benchmark creates a large object (`biggishObject`) with nested properties and then measures the execution time of each cloning method.

**Cloning Methods**

1. **Lodash's _.cloneDeep**: This method uses recursion to create a deep copy of the object, including all its nested properties.
	* Pros:
		+ Handles complex objects with circular references.
		+ Fast and efficient for large objects.
	* Cons:
		+ Requires Lodash library (included in benchmark via HTML script tag).
		+ May be slower than other methods due to recursion overhead.
2. **Spread Operator (`{ ... }`)**: This method uses the spread operator to create a new object with all properties from the original object, including nested objects.
	* Pros:
		+ Fast and efficient for large objects.
		+ Does not require any external libraries.
	* Cons:
		+ May not work correctly with circular references or deeply nested objects.
		+ Can be slower than other methods due to property iteration overhead.
3. **JSON Parsing (`JSON.parse(JSON.stringify())`)**: This method uses JSON parsing to create a deep copy of the object, including all its nested properties.
	* Pros:
		+ Handles complex objects with circular references.
		+ Fast and efficient for large objects.
	* Cons:
		+ Requires additional JSON parsing step, which can be slower than direct property iteration.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides various functions for tasks like array manipulation, string processing, and object cloning. In this benchmark, the `_.cloneDeep` method is used to create a deep copy of the complex object.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntaxes being tested in this benchmark.

**Other Alternatives**

Some alternative methods for creating deep copies of objects include:

* Using `Object.assign()` and then recursively iterating over properties
* Using a library like `fast-deep-copy` (which is not included in the benchmark)
* Implementing a custom recursive cloning function

Keep in mind that each method has its trade-offs, and the best approach depends on specific use cases and performance requirements.

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 YaBrowser/24.7.0.0 Safari/537.36

Browser/OS: Yandex Browser 24 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
deep clone	589606.2 Ops/sec
Spread	5505852.0 Ops/sec
JSON	595031.5 Ops/sec

Related benchmarks:

Clone tests (version: 0)

Comparing performance of: deep clone vs Spread vs JSON

Created: one month ago by: Guest

Jump to the latest result

deep clone

Spread

JSON

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):