Benchmark: Lodash cloneDeep vs freeze vs stringify

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: '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:

Lodash cloneDeep
myCopy = _.cloneDeep(MyObject);
freeze
function deepFreeze(object) { // Retrieve the property names defined on object var propNames = Object.getOwnPropertyNames(object); // Freeze properties before freezing self for (let name of propNames) { let value = object[name]; object[name] = value && typeof value === "object" ? deepFreeze(value) : value; } return Object.freeze(object); } myCopy = deepFreeze(MyObject)
Stringify
myCopy=JSON.stringify(MyObject)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash cloneDeep
freeze
Stringify

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's break down the benchmark and explain what's being tested.

**Benchmark Overview**

The benchmark compares three different approaches to create a deep copy of an object:

1. Lodash `cloneDeep`
2. Custom implementation using `deepFreeze` (a utility function that freezes objects in place)
3. Stringifying the object using `JSON.stringify`

**Lodash `cloneDeep`**

* Library: Lodash.js
* Purpose: Creates a deep copy of an object, cloning all properties and recursively creating new objects for arrays.

Pros:

* Easy to use and well-maintained
* Handles complex data structures, including arrays and nested objects

Cons:

* May not be optimized for performance in certain scenarios
* Adds external dependency (Lodash.js)

**Custom `deepFreeze`**

* Purpose: Freezes an object in place, making it immutable. This implementation is used to create a deep copy of the original object.

Pros:

* Customizable and under-the-hood control over the freezing process
* No external dependencies

Cons:

* More complex to implement and understand
* May not handle all edge cases correctly (e.g., frozen objects can still be modified indirectly)

**Stringifying using `JSON.stringify`**

* Purpose: Converts a JavaScript object to a JSON string, which can be used as a string representation of the original object.

Pros:

* Fast and lightweight
* No external dependencies

Cons:

* Not suitable for creating deep copies, as it only serializes references to objects
* May not handle all data types correctly (e.g., symbols, BigInt)

**Other Considerations**

* The benchmark uses Mobile Safari 14 on an iPhone with iOS 14.4 as the test device.
* The `ExecutionsPerSecond` value represents the number of executions performed per second, which can be used to estimate performance.

**Alternatives**

If you need to create deep copies of objects in JavaScript, you may also consider using:

1. `Object.assign()` and `Array.prototype.slice()`: These methods can be used to create shallow copies of objects and arrays.
2. `immer` library: A popular alternative to Lodash for immutable data structures.
3. `proptypes` library: Provides a way to create predictable, type-safe data structures.

In summary, the benchmark compares three approaches to create deep copies of objects: Lodash `cloneDeep`, custom implementation using `deepFreeze`, and stringifying using `JSON.stringify`. The choice of approach depends on your specific requirements, performance considerations, and personal preference.

Related benchmarks:

Lodash cloneDeep vs freeze vs stringify (version: 0)

Comparing performance of: Lodash cloneDeep vs freeze vs Stringify

Created: 5 years ago by: Guest

Jump to the latest result

Lodash cloneDeep

freeze

Stringify

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):