Benchmark: Lodash Chunk vs Native Reduce

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.21/lodash.min.js'></script>

Script Preparation code:

var arrays = [[1, 2, 3, 4, 5], [5, 2, 10]];

function chunk(input, size) {
  return input.reduce((arr, item, idx) => {
    return idx % size === 0
      ? [...arr, [item]]
      : [...arr.slice(0, -1), [...arr.slice(-1)[0], item]];
  }, []);
};

Tests:

Lodash
_.chunk(['a', 'b', 'c', 'd'], 3);
Native
chunk(['a', 'b', 'c', 'd'], 3);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Native

Fastest: N/A

Slowest: N/A

Latest 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 provided benchmark.

**What is being tested?**

The benchmark is designed to compare the performance of two approaches to chunking an array of elements: using Lodash (a popular JavaScript utility library) and the native JavaScript `Array.prototype.chunk()` method.

**Options being compared:**

1. **Lodash Chunk**: The first test case uses the `chunk()` function from Lodash to divide the input array into chunks of a specified size.
2. **Native Reduce**: The second test case uses the native JavaScript `Array.prototype.reduce()` method with a custom implementation for chunking.

**Pros and Cons:**

1. **Lodash Chunk**:
	* Pros:
		+ Easier to implement, as it's a well-established library with a simple API.
		+ Can handle edge cases and errors more robustly than the native approach.
	* Cons:
		+ Adds an extra dependency (the Lodash library) to the benchmark.
		+ May introduce additional overhead due to the library's indirections.
2. **Native Reduce**:
	* Pros:
		+ No extra dependencies or overhead, as it only uses built-in JavaScript functions.
		+ Can be optimized for specific use cases and architectures.
	* Cons:
		+ Requires a custom implementation, which can increase development time and complexity.
		+ May not handle edge cases or errors as robustly as Lodash.

**Library used:**

In this benchmark, the `lodash` library is used to implement the `chunk()` function. The library provides a convenient way to perform common array operations without having to write custom code.

**Special JS feature/syntax:**

There are no special JavaScript features or syntax mentioned in the provided benchmark definition or test cases. Both approaches use standard JavaScript syntax and built-in methods.

**Other alternatives:**

If you want to explore alternative approaches, here are a few options:

1. **Using `Array.prototype.slice()`**: Instead of using `reduce()`, you could use `slice()` to divide the array into chunks. This approach would be simpler but might not handle edge cases as robustly.
2. **Using a custom implementation with `forEach()`**: You could write a custom function using `forEach()` to iterate over the input array and divide it into chunks. This approach would require more development effort but might provide better performance for specific use cases.

These alternatives are not included in this benchmark, so you can consider them as additional options if you want to explore further optimization or implementation variations.

Related benchmarks:

Lodash Chunk vs Native Reduce (version: 0)

Comparing performance of: Lodash vs Native

Created: 3 years ago by: Guest

Jump to the latest result

Lodash

Native

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):