Benchmark: Ramda VS Loadash

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js"></script>

Script Preparation code:

var data = _.range(10000).map(function(i) {
  return {
    counter: i
  }
});

function isOdd(num) {
  return num % 2 === 1;
}

function square(num) {
  return num * num;
}

function lessThanThreeDigits(num) {
  return num.toString().length < 3;
}

Tests:

Loadash
var result = _.chain(data) .pick('counter') .filter(isOdd) .map(square) .filter(lessThanThreeDigits) .value();
Ramda with currying
var result = R.pipe( R.filter(lessThanThreeDigits), R.map(square), R.filter(isOdd), R.pluck('counter') )(data);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Loadash
Ramda with currying

Fastest: N/A

Slowest: N/A

Latest 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 is tested, along with the pros and cons of different approaches.

**Benchmark Context**

The test case compares the performance of two popular JavaScript library functions: Ramda and Lodash. Specifically, it measures how fast each function can perform a series of operations on a large dataset.

**Script Preparation Code**

The script preparation code defines several functions:

* `isOdd(num)`: checks if a number is odd.
* `square(num)`: squares a number.
* `lessThanThreeDigits(num)`: checks if the number of digits in a number is less than 3.

These functions are used to process the dataset, which consists of 10,000 objects with a single property called "counter".

**Html Preparation Code**

The HTML preparation code includes links to external JavaScript files:

* `ramda.min.js` (version 0.25.0): Ramda library
* `lodash.min.js` (version 4.17.5): Lodash library

These libraries provide the functional programming capabilities used in the benchmark.

**Individual Test Cases**

There are two test cases:

1. **Lodash**: The first test case uses Lodash's pipeline function (`_.chain`) to perform the following operations:
	* `pick('counter')`: selects only the "counter" property from each object.
	* `filter(isOdd)`: filters out objects where the "counter" value is even.
	* `map(square)`: squares the remaining values.
	* `filter(lessThanThreeDigits)`: filters out objects with more than 2 digits.
	* `value()`: returns the final result.
2. **Ramda with currying**: The second test case uses Ramda's pipe function (`R.pipe`) to perform similar operations, but with some differences:
	* `R.filter(lessThanThreeDigits)`, `R.map(square)`, and `R.filter(isOdd)` are chained together in a specific order.
	* `R.pluck('counter')` is used instead of `_.pick('counter')`.

**Pros and Cons**

Here's a brief analysis of the pros and cons of each approach:

1. **Lodash pipeline**: Pros:
	* More concise code
	* Easier to read and understand
	* Can be more efficient due to lazy evaluation
2. **Lodash pipeline**: Cons:
	* May lead to slower performance due to unnecessary function calls
3. **Ramda with currying**:
	* Pros:
		+ Can be more efficient due to reduced number of function calls
		+ Allows for more control over the order of operations
	* Cons:
		+ More verbose code
		+ Requires a better understanding of functional programming concepts

**Library and Syntax Considerations**

In this benchmark, both libraries are used to perform functional programming tasks. Ramda provides a more concise and expressive API, while Lodash offers a more traditional approach.

The use of currying in the second test case allows for more control over the order of operations, but also requires a deeper understanding of functional programming concepts.

**Other Alternatives**

If you were to reimplement this benchmark with other libraries or approaches, some alternatives could include:

1. **Other functional programming libraries**: Such as Immer, FocalJS, or Moo-Tools.
2. **Non-functional programming libraries**: Such as jQuery or Vanilla JavaScript implementations of the same functions.
3. **Custom implementations**: Using a specific approach or data structure (e.g., using arrays instead of objects).

These alternatives would require significant changes to the benchmark code and might produce different results due to differences in library behavior, syntax, or performance characteristics.

Related benchmarks:

Ramda VS Loadash (version: 0)

Comparing performance of: Loadash vs Ramda with currying

Created: 5 years ago by: Guest

Jump to the latest result

Loadash

Ramda with currying

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):