Benchmark: Spread Operator vs CloneDeep

HTML Preparation code:

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

Script Preparation code:

var arr = new Array(100000000).fill(0);

Tests:

Spread Operator
[...arr];
Lodash CloneDeep
_.cloneDeep(arr);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Spread Operator
Lodash CloneDeep

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/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Spread Operator	2.9 Ops/sec
Lodash CloneDeep	0.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks.

**Benchmark Definition and Preparation**

The provided benchmark definition is a JSON object that outlines the test scenario:

* `Name`: The name of the benchmark, which is "Spread Operator vs CloneDeep".
* `Description`: This field is empty, indicating that there is no detailed description of the test case.
* `Script Preparation Code`: A JavaScript snippet that creates an array with 100 million elements filled with zeros. This is a common practice for benchmarking large data structures in JavaScript.
* `Html Preparation Code`: A link to include the Lodash library (version 4.17.5) in the benchmark test case.

**Test Cases**

The individual test cases are defined as an array of objects:

* Each object represents a single test case with:
	+ `Benchmark Definition`: The code that will be executed for each test case.
	+ `Test Name`: A brief description of what is being tested (in this case, "Spread Operator" and "Lodash CloneDeep").

The first test case uses the spread operator (`[...arr]`) to create a new array with the same elements as the original `arr`. The second test case uses the `cloneDeep` function from Lodash to create a deep copy of the original array.

**Options Compared**

In this benchmark, we are comparing two approaches:

1. **Spread Operator**: Creates a new array by spreading the elements of the original array using the syntax `[...arr]`.
2. **Lodash CloneDeep**: Uses the `cloneDeep` function from Lodash to create a deep copy of the original array.

**Pros and Cons**

* **Spread Operator**:
	+ Pros:
		- Efficient, as it only creates a new array reference.
		- Simple to implement and understand.
	+ Cons:
		- May not be suitable for large datasets due to memory constraints.
		- Can lead to unexpected behavior if the spread operator is used with non-array values.
* **Lodash CloneDeep**:
	+ Pros:
		- Creates a deep copy of the original array, which can be useful in certain scenarios (e.g., preserving nested structures).
		- Reduces the risk of unexpected behavior due to non-array values.
	+ Cons:
		- May consume more memory than the spread operator approach.
		- Adds an external dependency on Lodash.

**Library and Purpose**

The `cloneDeep` function is part of the Lodash library, which provides a set of utility functions for functional programming. The purpose of this function is to create a deep copy of an object or array, preserving its original structure and contents.

**Special JS Features and Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definition that would require additional explanation.

**Alternatives**

If you're looking for alternatives to these approaches, consider the following:

1. **Array.prototype.slice()**: Creates a shallow copy of an array using `arr.slice()`.
2. **Array.prototype.concat()**: Concatenates multiple arrays together using `arr.concat()` or `arr.concat(new Array(...))`.
3. **Object.assign()**: Copies properties from an object to another object using `Object.assign(arr, {})`.

Keep in mind that these alternatives may have different performance characteristics and use cases compared to the spread operator and Lodash CloneDeep approaches.

Related benchmarks:

Spread Operator vs CloneDeep (version: 0)

Comparing performance of: Spread Operator vs Lodash CloneDeep

Created: one year ago by: Guest

Jump to the latest result

Spread Operator

Lodash CloneDeep

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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