Benchmark: Lodash cloneDeep vs JSON Clone with String

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 = "thisIsAtestString";

var myCopy = null;

Tests:

Lodash cloneDeep
myCopy = _.cloneDeep(MyObject);
Json clone
myCopy = JSON.parse(JSON.stringify(MyObject));

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash cloneDeep
Json clone

Fastest: N/A

Slowest: N/A

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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 on MeasureThat.net.

The benchmark in question is designed to test the performance difference between two approaches: using the `lodash` library for cloning deep objects (`_.cloneDeep`) and using the built-in `JSON.parse(JSON.stringify())` method for cloning simple objects (in this case, a string).

**Options being compared**

1. **Lodash cloneDeep**: This approach uses the `_.cloneDeep()` function from the Lodash library to create a deep copy of the input object (`MyObject`). The resulting cloned object is stored in the variable `myCopy`.
2. **JSON Clone with String**: This approach uses the built-in `JSON.parse(JSON.stringify())` method to create a shallow copy of the input string (`MyObject`) and assigns it to the variable `myCopy`.

**Pros and Cons**

* **Lodash cloneDeep**:
	+ Pros: Provides a deep copy of the object, which can be useful in scenarios where the entire object graph needs to be preserved. Lodash is a well-established library with a wide range of features.
	+ Cons: Adds an external dependency (the Lodash library) and may have a larger overhead due to its complexity.
* **JSON Clone with String**:
	+ Pros: Uses only built-in JavaScript functions, eliminating the need for an additional library. This approach can be faster since it doesn't involve loading another library.
	+ Cons: Only clones simple objects (in this case, a string), which may not be suitable for more complex object graphs.

In general, using `_.cloneDeep()` from Lodash is a good choice when you need to preserve the entire object graph, while `JSON.parse(JSON.stringify())` might be sufficient for simpler cloning tasks.

**Library: JSON**

The `JSON.parse(JSON.stringify())` method uses JavaScript's built-in `JSON` functions to create a shallow copy of the input string. This approach serializes the string into a JSON format, which is then parsed back into a new object. The resulting cloned object contains references to the original data, making it suitable for simple cloning tasks.

**Special JS feature: None**

This benchmark doesn't utilize any special JavaScript features or syntax beyond the standard `_.cloneDeep()` function from Lodash and the built-in `JSON.parse(JSON.stringify())` method.

Now, let's look at other alternatives:

* **Other cloning libraries**: There are other cloning libraries available in JavaScript, such as `deep-clone` (a lightweight alternative to Lodash) or `lodash-es` (Lodash with some features disabled to make it smaller).
* **Native Object Cloning**: Some browsers and Node.js versions have native object cloning mechanisms, like `Object.assign()` or `Object.create()`, which can be used for simple cloning tasks.
* **JSON-based Cloning**: Besides the built-in `JSON.parse(JSON.stringify())` method, you can also use other JSON-based cloning approaches, such as `JSON.parse(JSON.stringify(obj, null, 2))` to clone objects with indentation.

Keep in mind that these alternatives might have trade-offs in terms of performance, readability, or compatibility across different browsers and environments.

Related benchmarks:

Lodash cloneDeep vs JSON Clone with String (version: 0)

Comparing performance of: Lodash cloneDeep vs Json clone

Created: 4 years ago by: Guest

Jump to the latest result

Lodash cloneDeep

Json clone

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):