Benchmark: Ramda vs Vanilla

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>

Script Preparation code:

var sports = [{ defaultEventPathId: 1 }, { defaultEventPathId: 2 }, { defaultEventPathId: 3 }, { defaultEventPathId: 4 }];
var event = { sportId: 1 };

Tests:

Ramda
var sportRamda = R.find(R.propEq('defaultEventPathId', +event.sportId))(sports);
Vanilla
var sportVanilla = sports.find(({ defaultEventPathId }) => defaultEventPathId === +event.sportId);

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: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36

Browser/OS: Chrome 123 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Ramda	3663121.2 Ops/sec
Vanilla	13803896.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to explain what's being tested in this benchmark.

**Benchmark Overview**

The benchmark compares the performance of two JavaScript approaches: Ramda and vanilla (i.e., without any external library).

**What is being tested?**

The test cases compare the execution time of finding a specific element in an array using:

1. **Ramda**: A functional programming library that provides a concise way to perform various operations on arrays and objects.
2. **Vanilla**: The standard JavaScript syntax for finding elements in an array.

**Options compared**

In this benchmark, we have two options being compared:

1. Ramda: Uses the `R.find` function from Ramda to find the element that satisfies a certain condition (in this case, the `defaultEventPathId` property of the object matches the value of `event.sportId`).
2. Vanilla: Uses the standard JavaScript `Array.prototype.find` method and a callback function to achieve the same result.

**Pros and Cons**

Here are some pros and cons of each approach:

* **Ramda**:
	+ Pros:
		- More concise and expressive syntax, which can lead to faster code execution.
		- Eliminates the need for explicit loops or conditional statements.
	+ Cons:
		- Requires a separate library (Ramda) to be included in the test environment.
		- May have overhead due to the additional dependency.
* **Vanilla**:
	+ Pros:
		- No external dependencies required.
		- More familiar syntax for many developers.
	+ Cons:
		- Can be more verbose and less concise than Ramda's syntax.

**Library and its purpose**

In this benchmark, the Ramda library is used to provide a concise and expressive way to perform operations on arrays and objects. The `R.find` function is specifically designed to find the first element in an array that satisfies a certain condition.

**Special JS feature or syntax**

There are no special JavaScript features or syntaxes being tested in this benchmark (other than the use of functional programming concepts with Ramda).

**Other alternatives**

If you're interested in exploring other approaches, here are some alternative methods for finding elements in an array:

* **Lodash**: A popular utility library that provides a `_.find` function similar to Ramda's `R.find`.
* **Loose equality check**: Using the `===` operator with loose equality checks (e.g., `+event.sportId`) to compare values.
* **Array.prototype.indexOf()**: Using the `indexOf()` method to find the index of the desired element, and then indexing into the array to retrieve it.

Keep in mind that these alternatives may have different performance characteristics or trade-offs compared to Ramda's syntax.

Related benchmarks:

Ramda vs Vanilla (version: 0)

Comparing performance of: Ramda vs Vanilla

Created: 6 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):