Benchmark: Lodash cloneDeep VS mutate

HTML Preparation code:

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

Script Preparation code:

var MyObject = {
  description: 'a',
  myNumber: 123456789,
  myBoolean: true,
};

var myCopy = null;

Tests:

Lodash cloneDeep
myCopy = _.cloneDeep(MyObject);
mutate
myCopy = MyObject.d = 4;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash cloneDeep
mutate

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 dive into the world of JavaScript microbenchmarks.

**Benchmark Overview**

The provided benchmark compares two approaches to modifying an object in JavaScript: using Lodash's `cloneDeep` function versus directly mutating the original object (`MyObject`). The test case creates a sample object with various properties (description, myNumber, and myBoolean) and then attempts to create a copy of it using both methods.

**Options Compared**

The two options being compared are:

1. **Lodash's `cloneDeep` function**: This method creates a deep copy of the original object, which means that all nested objects and arrays within the original object are recursively copied.
2. **Direct Mutation**: This approach modifies the original object by assigning a new value to one of its properties.

**Pros and Cons**

**Lodash's `cloneDeep` function:**

Pros:

* Creates an independent copy of the original object, which can be useful for testing purposes or when working with external dependencies.
* Reduces the risk of unintended side effects on the original data.

Cons:

* Can lead to increased memory usage if the copied objects have a large number of properties.
* May introduce additional overhead due to the recursive copying process.

**Direct Mutation:**

Pros:

* Typically faster and more memory-efficient than creating a deep copy.
* Can be useful when working with simple, immutable data structures.

Cons:

* Modifies the original object, which can lead to unintended side effects if the object is used elsewhere in the codebase.
* May result in slower performance due to the overhead of modifying existing objects.

**Other Considerations**

When choosing between these approaches, consider the following factors:

* **Data complexity**: If the data being copied has a complex structure with nested objects and arrays, using `cloneDeep` may be more suitable. For simpler data structures, direct mutation might be faster.
* **Performance requirements**: In high-performance applications, direct mutation might be preferred to avoid the overhead of copying data. However, this comes at the cost of modifying the original object.
* **Code maintainability**: When working with large codebases or complex systems, using `cloneDeep` can help reduce the risk of unintended side effects by creating a separate copy of the data.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks like array manipulation, string processing, and object modification. In this benchmark, Lodash's `cloneDeep` function is used to create a deep copy of the original object.

**Special JS Features or Syntax**

This benchmark does not utilize any special JavaScript features or syntax. The code uses standard JavaScript features and syntax to test the two approaches being compared.

**Alternatives**

Other alternatives for creating copies of objects in JavaScript include:

* `Array.prototype.slice()` with `Object.assign()`
* `JSON.parse(JSON.stringify(obj))` (note that this method only works for simple data structures)
* Using a library like Immutable.js or Ramda

These alternatives may offer different trade-offs between performance, memory usage, and code complexity.

Related benchmarks:

Lodash cloneDeep VS mutate (version: 0)

Comparing performance of: Lodash cloneDeep vs mutate

Created: 3 years ago by: Guest

Jump to the latest result

Lodash cloneDeep

mutate

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):