Benchmark: native slice vs lodash chunk

HTML Preparation code:

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

Script Preparation code:

var test = Array.from({
    length: 100000
}, () => Math.random())

Tests:

native slice
const chunkSize = 80; const chunks = []; for (let i = 0; i <= test.length; i += chunkSize) { chunks.push(test.slice(i, i + chunkSize)); }
lodash chunk
_.chunk(test,80)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
native slice
lodash chunk

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 8 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/137.0.0.0 Safari/537.36

Browser/OS: Chrome 137 on Linux

View result in a separate tab

Test name	Executions per second
native slice	13265.6 Ops/sec
lodash chunk	5795.1 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the explanation of this benchmark.

**What is being tested?**

The provided JSON represents two test cases: "native slice" and "lodash chunk". These test cases are comparing how efficiently JavaScript can slice an array (or more specifically, create multiple chunks from it) using native syntax versus a library function from Lodash.

**Options compared**

In the benchmark, we have two approaches:

1. **Native Slice**: This approach uses the built-in `slice()` method in JavaScript to divide the input array (`test`) into smaller chunks of a specified size (80). The loop iterates over the array, creating a new chunk every 80 elements.
2. **Lodash Chunk**: This approach uses the `_chunk()` function from Lodash library, which is imported via the provided HTML preparation code (`<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js'></script>`). The `_.chunk()` function takes an array and a chunk size as input, returning an array of chunks.

**Pros and Cons**

Here are some pros and cons for each approach:

* **Native Slice**:
	+ Pros: Native syntax, likely faster execution due to optimized compiler optimizations.
	+ Cons: Requires manual loop management, can be more verbose.
* **Lodash Chunk**:
	+ Pros: Easier to read and maintain code, eliminates the need for manual loops.
	+ Cons: Adds overhead of importing an external library, may incur a performance penalty.

**Library used**

The `lodash` library is a popular utility belt that provides various functions for common tasks, such as array manipulation. In this benchmark, `_chunk()` function from Lodash is used to divide the input array into chunks.

**Special JS feature or syntax**

There are no special JavaScript features or syntax mentioned in the provided code snippets. The language itself is standard JavaScript, and the test cases use basic syntax like `for` loops and array manipulation functions (`slice()`).

**Other alternatives**

If you wanted to write this benchmark using alternative approaches, here are some options:

* **Array.prototype.reduce()**: You could use `reduce()` method on the input array to create chunks, which might provide a more concise implementation.
* **Recursive function**: Another approach would be to define a recursive function that creates chunks from the input array, but this might lead to performance issues due to repeated function calls.

Keep in mind that these alternatives are not necessarily better or worse than the original approach; they offer different trade-offs in terms of readability, maintainability, and performance.

Related benchmarks:

native slice vs lodash chunk (version: 0)

native slice vs lodash chunk

Comparing performance of: native slice vs lodash chunk

Created: 3 years ago by: Guest

Jump to the latest result

native slice

lodash chunk

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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