Benchmark: lodash.assignIn vs Class

HTML Preparation code:

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

Script Preparation code:

var obj = {
  foo1: {bar: 1},
  foo2: {bar: 2},
  baz: 3
};

function ClassObj() {
	return {
    	foo1: {bar: 1},
		foo2: {bar: 2},
		baz: 3
    }
};

Tests:

lodash.assignIn
const testObj = _.assignIn({}, obj);
Class
const testObj = new ClassObj();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash.assignIn
Class

Fastest: N/A

Slowest: N/A

Latest run results:

No previous 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 analyze what's being tested.

**What is being tested?**

The benchmark compares two approaches for creating an object with nested properties:

1. Using the `_.assignIn` method from the Lodash library, which recursively merges objects, preserving the keys of the source object.
2. Creating a class that returns an instance with the desired structure using the `ClassObj` function.

**Options being compared**

The two options are:

* **Lodash's _.assignIn**: This method is used to merge objects, allowing for more control over the resulting object structure. It takes two arguments: the source object and the target object.
* **Class-based approach**: This approach creates a class that returns an instance with the desired properties.

**Pros and cons of each approach**

**Lodash's _.assignIn**:

Pros:

* More control over the resulting object structure
* Can be more efficient for large objects, as it avoids creating intermediate objects
* Part of the Lodash library, which is widely used and maintained

Cons:

* Requires importing the Lodash library, adding overhead to the benchmark
* May have slower performance due to the additional function call

**Class-based approach**

Pros:

* Native JavaScript syntax, potentially faster execution
* No external dependency (Lodash), reducing overhead
* Can be more readable for developers familiar with classes

Cons:

* Less control over the resulting object structure
* May require more memory allocation and garbage collection

**Other considerations**

In addition to the performance differences between the two approaches, it's also worth noting that the class-based approach might have advantages in certain scenarios, such as:

* When working with large datasets or complex objects, the recursive nature of `_.assignIn` might lead to slower performance.
* In environments where memory allocation and garbage collection are more expensive (e.g., older browsers or devices with limited resources), the class-based approach might be more suitable.

**Library usage**

The benchmark uses Lodash's `_.assignIn` method, which is a popular utility function for working with objects in JavaScript. The library provides many other useful functions for manipulating objects and arrays, making it a valuable addition to any developer's toolkit.

**Special JS features or syntax**

There are no special JavaScript features or syntax used in this benchmark that would require additional explanation.

**Alternatives**

Other approaches for creating objects with nested properties could include:

* Using the `Object.assign()` method with an object initializer (e.g., `{ foo1: { bar: 1 }, foo2: { bar: 2 } }`)
* Utilizing a factory function to create objects with specific structures
* Leveraging modern JavaScript features like destructuring or template literals for more concise object creation

However, these alternatives might not be as widely used or efficient as the Lodash `_.assignIn` method or the class-based approach.

Related benchmarks:

lodash.assignIn vs Class (version: 0)

Comparing performance of: lodash.assignIn vs Class

Created: 5 years ago by: Guest

Jump to the latest result

lodash.assignIn

Class

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):