Benchmark: orderBy vs .order x3

HTML Preparation code:

<script src='https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.min.js'></script>

Script Preparation code:

var arr = [{text: 'a'},{text: 'b'},{text: 'c'},{text: 'd'},{text: 'e'},{text: 'f'}];

Tests:

Lodash
_.orderBy(arr, 'text');
Vainilla
arr.sort((a,b) => { if (a.text > b.text) { return 1; } else if (a.text < b.text) { return -1; } else { return 0; } });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Vainilla

Fastest: N/A

Slowest: N/A

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

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I'll explain what's being tested on the provided JSON, compare the options, and discuss pros and cons of each approach.

**What's being tested?**

The benchmark is comparing two sorting algorithms:

1. **Lodash `_.orderBy()`**: This function uses a stable sort algorithm (similar to Timsort) under the hood. It sorts an array in ascending order based on a provided field.
2. **Vanilla JavaScript `sort()` method with a custom compare function**: This is a standard JavaScript sorting algorithm that compares elements using a user-provided callback function.

**Options comparison**

The two algorithms are being compared for their performance. Here's a brief overview of each:

1. **Lodash `_.orderBy()`**:
	* Pros: Lodash provides a simple and concise way to sort arrays, and it's likely to be optimized for performance.
	* Cons: It requires including an additional library (Lodash) in the test environment.
2. **Vanilla JavaScript `sort()` method with a custom compare function**:
	* Pros: This is a standard JavaScript sorting algorithm that doesn't require any external libraries, making it suitable for testing pure JavaScript environments.
	* Cons: Writing a custom comparison function can be more verbose and error-prone than using Lodash.

**Other considerations**

In addition to performance, the choice of algorithm also depends on the specific requirements of the application. For example:

* If the data is mostly sorted or has a limited range of values, the vanilla JavaScript `sort()` method might be sufficient.
* If the data is large and needs to be sorted frequently, Lodash `_.orderBy()` might be more efficient due to its optimized sorting algorithm.

**Library: Lodash**

Lodash is a popular JavaScript utility library that provides a collection of functional programming helpers. In this case, it's being used to provide a simple way to sort arrays using the `_.orderBy()` function.

**Special JS feature or syntax**

There doesn't seem to be any special JavaScript features or syntax being tested in this benchmark.

**Alternatives**

Other alternatives for sorting large datasets in JavaScript include:

1. **Array.prototype.sort() with a custom compare function**: This is the standard way to sort arrays in JavaScript, and it can be used without including any external libraries.
2. **Ponyfilling**: Some modern browsers support newer sorting algorithms like `Array.prototype.sort()` with a custom comparison function. However, these algorithms might not work in older browsers.
3. **External sorting libraries**: There are several external sorting libraries available for JavaScript, such as [Sort](https://github.com/ajoslin/sort) or [Fast Sort](https://github.com/mikaelvelasquez/fast-sort). These libraries can provide optimized sorting algorithms for large datasets.

In summary, the benchmark is comparing two sorting algorithms: Lodash `_.orderBy()` and Vanilla JavaScript `sort()` method with a custom compare function. The choice of algorithm depends on the specific requirements of the application and the trade-offs between performance, readability, and simplicity.

Related benchmarks:

orderBy vs .order x3 (version: 0)

Comparing performance of: Lodash vs Vainilla

Created: 3 years ago by: Guest

Jump to the latest result

Lodash

Vainilla

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):