Benchmark: Lodash.js vs Native - plz work

HTML Preparation code:

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

Script Preparation code:

var max1 = 1000; // 100,000 (100 Thousand)
var max2 = 100; // 10,000,000 (10 Million)
var max3 = 10; // 100,000,000 (100 Million)

var items = [];
for (var i = 0; i <= max1; i++) { items.push(i); }

var cells = [];
for (var i = 0; i <= max2; i++) { cells.push({ items : [...items ] }); }

var columns = [];
for (var i = 0; i <= max3; i++) { columns.push({ cells : [...cells] }); }

Tests:

Native
let allItems = []; for (const column of columns) { for (let rowIndex = 0; rowIndex < column.cells.length; rowIndex++) { allItems.push(...column.cells[rowIndex].items); } }
Lodash.js filter
_(columns).map('cells').flatten().map('items').flatten().valueOf()

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:

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 the provided benchmark and explain what's being tested.

**Benchmark Definition**

The benchmark is designed to compare the performance of two approaches:

1. **Native**: This test case uses a simple loop to flatten the array of arrays in the `columns` variable, without using any external libraries.
2. **Lodash.js filter**: This test case uses the Lodash library's `flatten`, `map`, and `valueOf` methods to achieve the same result.

**Options Compared**

The two options being compared are:

* Using a native JavaScript loop to flatten an array of arrays
* Using the Lodash library's `flatten`, `map`, and `valueOf` methods to flatten an array of arrays

**Pros and Cons**

**Native Approach:**

Pros:

* Fastest execution time, since it doesn't involve any external library calls
* Simplest implementation, requiring only basic JavaScript loop constructs

Cons:

* May not be as efficient or concise for large-scale data processing tasks
* Can be more error-prone if not implemented correctly

**Lodash.js filter Approach:**

Pros:

* More concise and readable implementation, leveraging the Lodash library's optimized functions
* May be more efficient than a native loop approach, especially for large datasets

Cons:

* Slower execution time due to external library calls
* Requires including an additional library (Lodash) in the test environment

**Library: Lodash**

The Lodash library 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 `flatten`, `map`, and `valueOf` methods are used to flatten an array of arrays.

**Special JS Feature/Syntax: None mentioned**

There are no special JavaScript features or syntaxes being used in these test cases that would require additional explanation.

**Other Alternatives**

For larger-scale data processing tasks, alternative approaches might include:

* Using a dedicated array library like Apache Arrow or NumJS
* Utilizing parallel processing techniques, such as Web Workers or Node.js clusters
* Leveraging specialized data structures, such as quad trees or grids, for efficient data storage and manipulation

In the context of this benchmark, the focus is on comparing the performance of two basic approaches: a native JavaScript loop versus an Lodash library-based solution.

Related benchmarks:

Lodash.js vs Native - plz work (version: 0)

Comparing performance of: Native vs Lodash.js filter

Created: 3 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

No previous run results

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