Benchmark: Ramda vs. Lodash vs. Rambda

Ramda vs. Lodash vs. Rambda (version: 0)

Compares performance on the same task using Lodash vs two styles of Ramda vs two styles of "native" Javascript. In all cases the task is pulling "counter" property from each item in an array, filtering out odd items, squaring them, then returning those squared values that have less than two digits.

Comparing performance of: Lodash vs Ramda without relying on currying or composition vs Ramda with currying and composition vs Rambda

Created: 4 years ago by: Guest

Jump to the latest result

HTML Preparation code:

<script src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.0/ramda.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.5/lodash.min.js"></script>
<script src="https://unpkg.com/rambda@5.0.0/dist/rambda.umd.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:

Lodash
var result = _.chain(data) .pick('counter') .filter(isOdd) .map(square) .filter(lessThanThreeDigits) .value();
Ramda without relying on currying or composition
var result = R.filter(lessThanThreeDigits, R.map(square, R.filter(isOdd, R.pluck('counter', data))));
Ramda with currying and composition
var result = R.pipe( R.pluck('counter'), R.filter(isOdd), R.map(square), R.filter(lessThanThreeDigits) )(data);
Rambda
var result = R.pipe( R.prop('counter'), R.filter(isOdd), R.map(square), R.filter(lessThanThreeDigits) )(data);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Ramda without relying on currying or composition
Ramda with currying and composition
Rambda

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's dive into the benchmark.

**Benchmark Purpose**

The benchmark compares the performance of three JavaScript libraries: Lodash, Ramda, and Rambda (an implementation of Ramda). The test case involves pulling the "counter" property from each item in an array, filtering out odd items, squaring them, and then returning those squared values that have less than two digits.

**Options Compared**

The benchmark compares the performance of three different approaches:

1. **Lodash**: Uses the `_.chain()` method to create a pipeline of functions, where each function is applied in sequence.
2. **Ramda without currying or composition**: Directly calls Ramda functions with the correct arguments, without using the curry or compose methods.
3. **Ramda with currying and composition**: Uses Ramda's curry and compose functions to create a pipeline of functions.

**Pros and Cons**

* **Lodash**:
	+ Pros: Easy to read and write, familiar API.
	+ Cons: May be slower due to the creation of an internal chain.
* **Ramda without currying or composition**:
	+ Pros: Can be faster since it avoids creating an internal chain.
	+ Cons: Requires more manual function calls and arguments.
* **Ramda with currying and composition**:
	+ Pros: Can be more expressive and concise, using Ramda's functional programming features.
	+ Cons: May require a steeper learning curve due to the use of curry and compose.

**Library Descriptions**

* **Lodash**: A popular JavaScript utility library that provides a wide range of functions for tasks like array manipulation, string processing, and more.
* **Ramda**: A functional programming library for JavaScript that aims to provide a more expressive and concise way of writing code. It's designed to be faster than Lodash, but may require more manual function calls.
* **Rambda**: An implementation of Ramda that provides similar functionality, but with a focus on speed and performance.

**Special JS Features**

The benchmark does not use any special JavaScript features or syntax beyond the standard ECMAScript 2015 (ES6) features.

**Alternative Approaches**

Other alternatives for this benchmark could include:

* Using native JavaScript functions instead of the libraries.
* Implementing custom loop constructs to compare performance.
* Adding more complex filtering conditions to test the libraries' ability to handle different use cases.
* Using different data sizes or distributions to see how the libraries perform under varying workloads.

Latest run results:

Run details: (Test run date: 6 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.1 Safari/605.1.15

Browser/OS: Safari 18 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Lodash	489440.8 Ops/sec
Ramda without relying on currying or composition	4877.0 Ops/sec
Ramda with currying and composition	4830.0 Ops/sec
Rambda	1447736.0 Ops/sec

Related benchmarks:

Ramda vs. Lodash vs. Rambda (version: 0)

Compares performance on the same task using Lodash vs two styles of Ramda vs two styles of "native" Javascript. In all cases the task is pulling "counter" property from each item in an array, filtering out odd items, squaring them, then returning those squared values that have less than two digits.

Comparing performance of: Lodash vs Ramda without relying on currying or composition vs Ramda with currying and composition vs Rambda

Created: 4 years ago by: Guest

Jump to the latest result

Lodash

Ramda without relying on currying or composition

Ramda with currying and composition

Rambda

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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