Benchmark: Lodash.js vs Nativexxxxx

HTML Preparation code:

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

Script Preparation code:


var max3 = 100000000; // 100,000,000 (100 Million)

var arr3 = [];
for (var i = 0; i <= max3; i++) { arr3.push(i); }

Tests:

Native
arr3.forEach(function (element, index) { element = element*2; });
Lodash.js filter
_.each(arr3, function (element, index) { element = element*2; });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Lodash.js filter

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 days ago)

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/147.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 147 on Android

View result in a separate tab

Test name	Executions per second
Native	1.0 Ops/sec
Lodash.js filter	1.2 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided JSON benchmark definition and its test cases.

**Benchmark Definition:**

The benchmark measures the performance of two approaches:

1. **Native**: This approach uses the built-in JavaScript `forEach` method to iterate over an array and perform a transformation on each element.
2. **Lodash.js filter**: This approach uses the `_.each` function from the Lodash library to achieve the same result as the Native approach.

**Options being compared:**

* The two approaches being compared are native JavaScript's `forEach` method versus the `_.each` function from the Lodash library.
* The primary metric being measured is the execution speed of each approach, represented by the `ExecutionsPerSecond` value in the benchmark results.

**Pros and Cons:**

* **Native (JavaScript `forEach`)**:
	+ Pros:
		- Typically faster since it's a built-in method optimized for performance.
		- Easier to understand and implement for developers familiar with JavaScript.
	+ Cons:
		- May not be as flexible or powerful as the Lodash library's implementation.
* **Lodash.js filter (`_.each`)**:
	+ Pros:
		- Often more readable and maintainable due to its explicit function signature and callback interface.
		- Can be more flexible, allowing for additional transformations or filtering.
	+ Cons:
		- May be slower than native JavaScript's `forEach` method due to the overhead of the Lodash library.
		- Requires an external dependency (the Lodash library) to be included.

**Library:**

The Lodash library is a popular JavaScript utility library that provides various functional programming functions, including `_.each`. The library aims to provide a convenient and expressive way to perform common tasks, making code more readable and maintainable.

**Special JS feature or syntax:**

There doesn't appear to be any specific special JS features or syntax used in the benchmark definition. Both approaches utilize standard JavaScript methods (`forEach`) and Lodash functions (`_.each`).

**Alternatives:**

If you were to implement this benchmark using a custom approach, some alternatives to consider:

* Using `Array.prototype.map()` instead of `forEach` for the native approach.
* Implementing a custom iterative loop with a callback function for the Native approach.
* Using other Lodash functions (e.g., `_.map()`, `_.filter()`) that provide similar functionality to `_each`.

Keep in mind that any alternative implementation would need to account for potential performance differences and maintainability trade-offs.

When interpreting the benchmark results, note that the `ExecutionsPerSecond` value represents the number of iterations performed by each approach per second on a single execution. The higher value indicates better performance.

Related benchmarks:

Lodash.js vs Nativexxxxx (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 4 years ago by: Guest

Jump to the latest result

Native

Lodash.js filter

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):