Benchmark: Ramda groupby vs vanilla reduce

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.29.1/ramda.min.js"></script>

Script Preparation code:

var dag = {
    nodes: [{
        id: '1'
    }, {
        id: '2'
    }, {
        id: '3'
    }, {
        id: '4'
    }],
    links: [{
            fromId: '1',
            fromPort: 'Output',
            toId: '2',
            toPort: 'Input'
        },
        {
            fromId: '1',
            fromPort: 'Output',
            toId: '3',
            toPort: 'Input'
        },
        {
            fromId: '2',
            fromPort: 'Output',
            toId: '4',
            toPort: 'Input'
        },
        {
            fromId: '3',
            fromPort: 'Output',
            toId: '4',
            toPort: 'Input'
        },
    ]
}

Tests:

Ramda
var incomingLinksById = R.groupBy(l => l.toId, dag.links)
Vanilla
var incomingLinksById = dag.links.reduce((acc, link) => { if (!acc[link.toId]) { acc[link.toId] = [link]; } else { acc[link.toId].push(link); } return acc; }, {});

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Vanilla

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Windows

View result in a separate tab

Test name	Executions per second
Ramda	1728042.5 Ops/sec
Vanilla	7469358.5 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 provided benchmark definition and explore what's being tested, compared, and their pros/cons.

**Benchmark Definition Overview**

The provided JSON represents a JavaScript microbenchmark that compares two approaches to group incoming links by ID: Ramda's `groupBy` function and vanilla JavaScript's `reduce` method.

**What is Being Tested?**

* **Ramda's `groupBy` function**: A functional programming library for JavaScript, specifically designed for data transformations.
* **Vanilla JavaScript's `reduce` method**: A built-in method in the JavaScript language that reduces an array to a single value.

**Options Compared**

Two approaches are compared:

1. **Ramda's `groupBy` function**: This approach uses Ramda's `groupBy` function, which is designed for functional programming and provides a concise way to group data by key.
2. **Vanilla JavaScript's `reduce` method**: This approach uses the built-in `reduce` method, which is a more imperative programming style.

**Pros/Cons of Each Approach**

**Ramda's `groupBy` function:**

Pros:

* Concise and readable code
* Designed for functional programming
* Reduces boilerplate code

Cons:

* Requires Ramda library to be included (as shown in the HTML Preparation Code)
* May have a higher memory overhead due to its functional nature

**Vanilla JavaScript's `reduce` method:**

Pros:

* Built-in and doesn't require an additional library
* Can be more efficient for large datasets
* More control over the grouping process

Cons:

* Requires more code and boilerplate compared to Ramda's `groupBy`
* May be less readable for those unfamiliar with functional programming

**Library Used (Ramda)**

Ramda is a JavaScript library designed for functional programming. It provides a set of higher-order functions that can be used to transform and manipulate data in a concise and expressive way.

**Special JS Feature/Syntax**

Neither approach uses any special JavaScript features or syntax, but Ramda's `groupBy` function does rely on functional programming principles (e.g., immutability, higher-order functions).

**Other Alternatives**

If you don't want to use Ramda, you can also consider using other libraries like:

* Lodash (`_groupBy`)
* Array.prototype.filter() and Array.prototype.push()
* D3.js's `groupBy` function

However, keep in mind that each of these alternatives has its own trade-offs and may not provide the same level of conciseness or efficiency as Ramda's `groupBy`.

Overall, this benchmark provides a useful comparison between two approaches to group data by key, allowing developers to choose the most suitable method based on their specific needs.

Related benchmarks:

Ramda groupby vs vanilla reduce (version: 1)

Comparing performance of: Ramda vs Vanilla

Created: 2 years ago by: Registered User

Jump to the latest result

Ramda

Vanilla

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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