Benchmark: specific test case - Ramda vs Native

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.26.1/ramda.min.js"></script>

Script Preparation code:

var arr = Array(100).fill({ value: '1' });

Tests:

Ramda
R.sum(R.map(parseFloat, R.map(({ value }) => value, arr)))
Native
arr.reduce((acc, v) => acc + parseFloat(v.value), 0)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda
Native

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.

I'd be happy to help explain the provided benchmark!

**Overview**

The provided benchmark compares the performance of two approaches: using the Ramda library and implementing the calculation manually using native JavaScript.

**Benchmark Definition**

The benchmark definition is in JSON format, which includes:

1. **Name**: A descriptive name for the benchmark (in this case, "Ramda vs Native").
2. **Description**: An optional description of the benchmark.
3. **Script Preparation Code**: The code that sets up the test environment and variables before running the benchmark. In this case, it creates an array `arr` with 100 elements, each containing a string value.
4. **Html Preparation Code**: A link to include in the HTML header to load the Ramda library (version 0.26.1) for the first benchmark.

**Individual Test Cases**

The benchmark defines two individual test cases:

1. **Ramda**
	* The benchmark definition uses the Ramda library to calculate the sum of:
		+ Mapping each element in `arr` to its value using `R.map(({ value }) => value, arr)`.
		+ Converting the result to a numerical value using `parseFloat`.
		+ Summing up all elements using `R.sum`.
2. **Native**
	* The benchmark definition uses native JavaScript to calculate the sum of:
		+ Mapping each element in `arr` to its value using a simple function.
		+ Converting the result to a numerical value using `parseFloat`.
		+ Summing up all elements using the built-in `reduce()` method.

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Ramda**
	* Pros:
		+ More concise and expressive code.
		+ Less prone to errors due to higher-level abstractions.
	* Cons:
		+ May have a performance overhead due to the use of an external library.
		+ Requires additional setup and dependency management.
2. **Native**
	* Pros:
		+ Faster execution times since it doesn't rely on an external library.
		+ No dependencies or setup required.
	* Cons:
		+ More verbose and error-prone code.
		+ May require more expertise in JavaScript to implement correctly.

**Library: Ramda**

Ramda is a functional programming library for JavaScript that provides a set of higher-order functions for data processing. The `R.sum()` function is used to calculate the sum of an array, while `R.map()` is used to apply a transformation to each element in the array. In this benchmark, Ramda is used to simplify the calculation and make it more concise.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax mentioned in the benchmark definition. However, if you're interested in learning more about functional programming concepts and how they apply to JavaScript, I'd be happy to explain!

**Other Alternatives**

If you're looking for alternative libraries or approaches, here are a few options:

1. **Lodash**: Another popular utility library that provides a wide range of functions for data manipulation and processing.
2. **Array.prototype.reduce()**: A built-in method in JavaScript's Array prototype that allows you to calculate the sum of an array using a custom callback function.
3. **Pure-Functional Programming**: An alternative approach that uses pure functions, immutability, and recursion to solve problems without relying on loops or side effects.

Let me know if you have any further questions or if there's anything else I can help with!

Related benchmarks:

specific test case - Ramda vs Native (version: 0)

Comparing performance of: Ramda vs Native

Created: 6 years ago by: Guest

Jump to the latest result

Ramda

Native

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):