Benchmark: Chunk: lodash vs you-dont-need vs youmightnotneed vs ...

HTML Preparation code:

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

Script Preparation code:

var values = new Array(200 * 200 * 4);

Tests:

lodash
const chunks = _.chunk(values, 4);
you-dont-need
const chunk = (input, size) => { return input.reduce((arr, item, idx) => { return idx % size === 0 ? [...arr, [item]] : [...arr.slice(0, -1), [...arr.slice(-1)[0], item]]; }, []); }; const chunks = chunk(values, 4);
youmightnotneed
const chunk = (arr, chunkSize = 1, cache = []) => { const tmp = [...arr] if (chunkSize <= 0) return cache while (tmp.length) cache.push(tmp.splice(0, chunkSize)) return cache } const chunks = chunk(values, 4);
custom
var chunks = []; for (var i = 0; i < values.length; i += 4) { chunks.push(values.slice(i, i + 4)); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lodash
you-dont-need
youmightnotneed
custom

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):

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Let's break down the provided JSON and benchmark information to understand what is being tested.

**Benchmark Definition**

The benchmark aims to compare the performance of different approaches to chunking an array in JavaScript. The `chunk()` function is used to split the input array into smaller subarrays, each with a specified size (in this case, 4).

**Options Compared**

Four options are being compared:

1. **Lodash**: Uses the `_chunk` function from the Lodash library.
2. **You-Dont-Need**: A custom implementation of the `chunk()` function without using any libraries.
3. **YouMightNotNeed**: Another custom implementation of the `chunk()` function, which is similar to the previous one but has some minor differences in its logic.
4. **Custom**: A simple iterative approach to chunking an array, where each iteration manually creates a subarray and pushes it into an array.

**Pros and Cons**

Here's a brief overview of the pros and cons of each approach:

1. **Lodash**:
	* Pros: Easy to use, well-tested, and maintainable.
	* Cons: Requires including an external library, which might be unnecessary for small projects.
2. **You-Dont-Need**:
	* Pros: Custom implementation, no dependencies required.
	* Cons: Requires manual iteration over the array, which can lead to errors if not implemented correctly.
3. **YouMightNotNeed**:
	* Pros: Similar to You-Dont-Need but with some minor optimizations (e.g., using `splice` instead of `slice`).
	* Cons: Still requires manual iteration and might have similar performance issues as the previous implementation.
4. **Custom**:
	* Pros: Extremely lightweight, no dependencies required.
	* Cons: Requires manual iteration over the array, which can lead to errors if not implemented correctly.

**Library Usage**

The `Lodash` library is used for its `_chunk` function, which provides a simple and efficient way to chunk an array. The library's implementation is likely optimized for performance, making it a good choice when speed is crucial.

**Special JS Features or Syntax**

None of the benchmarked implementations explicitly use any special JavaScript features or syntax that would impact their performance significantly (e.g., `async/await`, generators, Web Workers).

**Other Alternatives**

If you're looking for alternative approaches to chunking an array in JavaScript, consider:

1. **Array.prototype.chunk()**: Introduced in ECMAScript 2020, this method provides a built-in way to chunk an array.
2. **Ramda library**: Another popular functional programming library that includes a `chunk` function similar to Lodash's implementation.
3. **Manual iteration with `map()` and `reduce()`**: While not recommended for performance-critical code, this approach can be used as an educational exercise or when working with very small arrays.

In summary, the benchmark provides a comparison of different approaches to chunking an array in JavaScript, highlighting the trade-offs between using a library (Lodash), custom implementations (`You-Dont-Need` and `YouMightNotNeed`), and a simple iterative approach (`Custom`).

Related benchmarks:

Chunk: lodash vs you-dont-need vs youmightnotneed vs ... (version: 0)

chunk() functions comparasion

Comparing performance of: lodash vs you-dont-need vs youmightnotneed vs custom

Created: 4 years ago by: Guest

Jump to the latest result

lodash

you-dont-need

youmightnotneed

custom

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):