Benchmark: beniobenio - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

window.foo = ['cat', 'dog', 'bird'];
window.bar = ['cat', 'dog', 'bird'];

Tests:

_.isEqual
_.isEqual(window.foo, window.bar)
JSON.stringify
window.foo.toString() === window.bar.toString();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
_.isEqual
JSON.stringify

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 what's being tested on the provided JSON.

**Benchmark Definition**

The benchmark is testing two individual test cases:

1. `_.isEqual(window.foo, window.bar)`:
	* This tests the performance of the Lodash library's `isEqual` function.
	* The `foo` and `bar` variables are arrays created in the script preparation code, and they contain the same elements (`['cat', 'dog', 'bird']`).
2. `window.foo.toString() === window.bar.toString()`:
	* This tests the performance of a simple string comparison using the `toString()` method.
	* The `foo` and `bar` variables are arrays created in the script preparation code, and they contain the same elements (`['cat', 'dog', 'bird']`). However, the test uses `toString()` to convert these arrays to strings, and then compares them using the `===` operator.

**Options Compared**

The benchmark is comparing two approaches:

1. Using a library function (`_.isEqual(window.foo, window.bar)`):
	* This approach relies on a third-party library (Lodash) to perform the comparison.
	* Pros:
		+ The library provides an optimized implementation of the comparison logic.
		+ It may be faster and more efficient than a simple manual implementation.
	* Cons:
		+ The performance benefits come at the cost of adding external dependencies and potential overhead.
2. Manual string comparison using `toString()` (`window.foo.toString() === window.bar.toString()`):
	* This approach relies on a simple, built-in method to convert arrays to strings and compare them.
	* Pros:
		+ It's a lightweight, minimalistic approach with no external dependencies.
		+ It may be faster for small arrays or specific use cases.
	* Cons:
		+ The performance benefits are limited compared to using a library function.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a wide range of functions for tasks such as array manipulation, string manipulation, and more. In this benchmark, the `isEqual` function is used to compare two arrays for equality.

**Special JS Feature/Syntax**

There isn't any special JavaScript feature or syntax being tested in these benchmarks. The test cases rely on basic JavaScript concepts, such as array creation and comparison using the `===` operator.

**Other Alternatives**

If you want to try similar benchmarks, here are some alternatives:

1. Using a different library function:
	* You could replace Lodash with another popular library like jQuery or Ramda.
2. Manual string comparison using a different method:
	* Instead of `toString()`, you could use `JSON.stringify()` or `Array.prototype.join()` to convert arrays to strings and compare them.
3. Using a different programming paradigm:
	* You could rewrite the benchmarks in a functional programming language like Clojure or Scala, which might provide different performance characteristics.

Keep in mind that the choice of approach depends on your specific use case and requirements. The Lodash `isEqual` function provides a convenient and optimized way to compare arrays, but it may not be the best choice for all scenarios.

Related benchmarks:

beniobenio (version: 0)

Test on isEqual performance

Comparing performance of: _.isEqual vs JSON.stringify

Created: 7 years ago by: Guest

Jump to the latest result

_.isEqual

JSON.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):