Benchmark: Lodash benchmark (Anton)

HTML Preparation code:

<script src="https://cdn.jsdelivr.net/npm/lodash@4.17.4/lodash.min.js"></script>

Script Preparation code:

var a = {name: 'a',secondName: 'b', home: {city:'San Diego', zip:'92122',phone:{code:484, number:99999999}}}

Tests:

Lodash
let b = _.cloneDeep(a)
Native JS
let b = JSON.parse(JSON.stringify(a))

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Native JS

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 break down the provided benchmark and its test cases to understand what's being tested.

**Benchmark Definition:**
The benchmark is created on MeasureThat.net, which allows users to create and run JavaScript microbenchmarks. The benchmark definition consists of two parts:

1. **Script Preparation Code**: This section provides a script that sets up the environment for the benchmark. In this case, it creates an object `a` with nested properties, including another object `home`. This object will be used as input for the benchmark.
2. **Html Preparation Code**: This section includes a JavaScript file that needs to be loaded into the test environment. In this case, it loads the Lodash library (version 4.17.4) from a CDN.

**Individual Test Cases:**
The benchmark consists of two test cases:

1. **Lodash**: The first test case uses the `_.cloneDeep()` function from the Lodash library to clone a deep copy of the object `a`. This test case is used to measure the performance of using the Lodash library for cloning.
2. **Native JS**: The second test case uses native JavaScript's `JSON.parse(JSON.stringify(a))` method to create a deep copy of the object `a`. This test case is used to measure the performance of using native JavaScript for cloning.

**Pros and Cons:**

* **Lodash (_.cloneDeep())**:
	+ Pros: Lodash provides a simple and efficient way to clone objects, including nested properties. It handles complex data structures like arrays and objects.
	+ Cons: Using an external library adds overhead due to the need to load and parse JavaScript code. This may impact performance in certain scenarios.
* **Native JS (JSON.parse(JSON.stringify(a)))**:
	+ Pros: Native JavaScript provides a lightweight solution that doesn't require loading additional libraries. It's also a simple approach to clone objects.
	+ Cons: The native method can be less efficient than the Lodash method, especially for complex data structures.

**Library and Purpose:**
The `lodash` library is a popular JavaScript utility library that provides various functions for tasks such as:
	* Iteration (`_.forEach()`, `_reduce()`)
	* String manipulation (`_.trim()`, `_upperCase()`)
	+ Object manipulation (`_.cloneDeep()`, `_map()`)

In this benchmark, Lodash is used to provide a convenient way to clone objects, including nested properties.

**Special JS Feature/Syntax:**
There are no special JavaScript features or syntax being tested in these benchmark cases. Both test cases use standard JavaScript constructs for cloning objects.

**Other Alternatives:**
For deep copying objects, you can also consider using the following alternatives:

* `Array.prototype.slice.call()`: This method creates a shallow copy of an array.
* `Object.assign()`: This method copies properties from one object to another.
* Using a library like `Immutable.js` (which is now deprecated) or other alternatives like `fast-json-stamp`.
* Recursively looping through the object and creating new instances for each property.

Keep in mind that these alternatives may have different performance characteristics and might not be as efficient as the Lodash method.

Related benchmarks:

Lodash benchmark (Anton) (version: 5)

Comparing performance of: Lodash vs Native JS

Created: 6 years ago by: Registered User

Jump to the latest result

Lodash

Native JS

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):