Benchmark: Check my data 2 - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

// 1 level deep

window.foo1 = { a: 'hello', b: 12345, c: [1, 2, 4] };
window.bar1 = { a: 'hello', b: 12345, c: [1, 2, 4] };

// 2 levels deep
window.foo2 = { a: 1, b: 2, c: { a: 'hello', b: 12345, c: [1, 2, 4] } };
window.bar2 = { a: 1, b: 2, c: { a: 'hello', b: 12345, c: [1, 2, 4] } };

// 3 levels deep
window.foo3 = { a: 1, b: 2, c: { a: 'hello', b: 12345, c: { a: 1, b: 2, c: { a: 'hello', b: 12345, c: [1, 2, 4] } } } };
window.bar3 = { a: 1, b: 2, c: { a: 'hello', b: 12345, c: { a: 1, b: 2, c: { a: 'hello', b: 12345, c: [1, 2, 4] } } } };

Tests:

First lodash
_.isEqual(window.foo1, window.bar1)
First json
JSON.stringify(window.foo1) === JSON.stringify(window.bar1);
Second lodash
_.isEqual(window.foo2, window.bar2)
Second json
JSON.stringify(window.foo2) === JSON.stringify(window.bar2);
Third lodash
_.isEqual(window.foo3, window.bar3)
Third json
JSON.stringify(window.foo3) === JSON.stringify(window.bar3);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
First lodash
First json
Second lodash
Second json
Third lodash
Third json

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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 its components.

**Benchmark Definition**

The benchmark tests two approaches to compare objects: using the `isEqual` function from the Lodash library and using the `JSON.stringify` method.

**Options Compared**

1. **Lodash's `isEqual` function**: This function checks if two objects are equal, considering their structure and values.
2. **`JSON.stringify` method**: This method converts an object to a JSON string, which can be compared with another JSON string to determine if they represent the same object.

**Pros and Cons of Each Approach**

1. **Lodash's `isEqual` function**
	* Pros:
		+ Handles complex objects with nested structures.
		+ Fast and efficient.
	* Cons:
		+ May require additional dependencies (e.g., Lodash library).
2. **`JSON.stringify` method**
	* Pros:
		+ Lightweight and easy to implement.
		+ Works well for simple object comparisons.
	* Cons:
		+ May not handle complex objects with nested structures correctly.
		+ Can lead to performance issues if used extensively.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides various functions for working with data structures, such as arrays, objects, and dates. The `isEqual` function is part of this library and is specifically designed to compare objects, including nested structures.

**Special JS Feature/Syntax: None**

There are no special JavaScript features or syntax used in this benchmark.

**Alternative Approaches**

1. **Using a custom comparison function**: You can write your own custom comparison function to compare objects, which might be more efficient for specific use cases.
2. **Using other equality checking libraries**: Other libraries, such as `deep-equal` or `fast-deep-equal`, offer alternative implementations of object comparison.

In summary, the benchmark tests two common approaches to comparing objects in JavaScript: using Lodash's `isEqual` function and using the `JSON.stringify` method. The choice between these approaches depends on the specific requirements and constraints of your use case.

Related benchmarks:

Check my data 2 (version: 1)

Test isEqual vs JSON.stringify

Comparing performance of: First lodash vs First json vs Second lodash vs Second json vs Third lodash vs Third json

Created: 7 years ago by: Registered User

Jump to the latest result

First lodash

First json

Second lodash

Second json

Third lodash

Third json

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):