Benchmark: Ramda vs. Lodash vs. Immutable vs. Native array methods

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 src="https://cdnjs.cloudflare.com/ajax/libs/immutable/4.3.4/immutable.min.js"></script>

Script Preparation code:

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

Tests:

Lodash
var result = _.chain(data) .filter(isOdd) .map(square) .filter(lessThanThreeDigits) .value();
Ramda compose
var result = R.compose( R.filter(isOdd), R.map(square), R.filter(lessThanThreeDigits) )(data);
Ramda pipe
var result = R.pipe( R.filter(isOdd), R.map(square), R.filter(lessThanThreeDigits) )(data);
Immutable List
var result = Immutable.List(data) .filter(isOdd) .map(square) .filter(lessThanThreeDigits) .toArray();
Immutable Seq
var result = Immutable.Seq(data) .filter(isOdd) .map(square) .filter(lessThanThreeDigits) .toArray();
Native
var result = data .filter(isOdd) .map(square) .filter(lessThanThreeDigits);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Lodash
Ramda compose
Ramda pipe
Immutable List
Immutable Seq
Native

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (iPhone; CPU iPhone OS 17_1_2 like Mac OS X) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.1.2 Mobile/15E148 Safari/604.1

Browser/OS: Mobile Safari 17 on iOS 17.1.2

View result in a separate tab

Ramda compose

44K/s

Lodash

4K/s

Ramda pipe

4K/s

Immutable Seq

3K/s

Native

3K/s

Immutable List

632/s

View exact numbers

Test name	Executions per second
✓ Ramda compose	43,656 Ops/sec
Lodash	4,370 Ops/sec
Ramda pipe	3,897 Ops/sec
Immutable Seq	3,046 Ops/sec
Native	2,532 Ops/sec
Immutable List	632 Ops/sec

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

LLMs can make mistakes. Check important info.

Measuring the performance of various JavaScript libraries and built-in methods is crucial for optimizing code and making informed decisions about which tools to use.

**Benchmark Overview**

The benchmark measures the execution speed of different approaches for filtering, mapping, and filtering data using Ramda, Lodash, Immutable.js, and native array methods.

**Options Compared**

1. **Ramda**: A functional programming library that provides a pipeline approach (`R.pipe`) or composition-based approach (`R.compose`).
2. **Lodash**: A utility library that uses a chain-based approach (`_.chain`).
3. **Immutable.js**: A library for working with immutable data structures, which can be used to create sequences or lists.
4. **Native Array Methods**: Using built-in JavaScript methods like `filter`, `map`, and `forEach` directly on an array.

**Pros and Cons of Each Approach**

1. **Ramda (Pipeline/Composition)**:
	* Pros: Efficient use of function composition, easy to chain multiple operations together.
	* Cons: Can be less readable for those unfamiliar with functional programming concepts, may require additional setup.
2. **Lodash (Chain-based)**:
	* Pros: Easy to learn and use, provides a familiar chaining syntax.
	* Cons: May not be as efficient as pipeline or composition approaches, can lead to slower performance due to the overhead of method calls.
3. **Immutable.js**:
	* Pros: Provides an immutable data structure approach, which can help prevent side effects and improve code safety.
	* Cons: Requires additional setup for working with sequences or lists, may introduce overhead due to immutability.
4. **Native Array Methods**:
	* Pros: Lightweight, easy to understand, and widely supported.
	* Cons: May not provide the same level of composability as functional libraries like Ramda or Lodash.

**Library Overview**

1. **Ramda**: A functional programming library that provides a range of useful functions for working with data. Its pipeline and composition approaches are particularly well-suited for this benchmark.
2. **Lodash**: A utility library that provides a broad set of helper functions for common tasks, including filtering and mapping data.
3. **Immutable.js**: A library that focuses on creating immutable data structures, which can help improve code safety and predictability.

**Special JavaScript Feature/Syntax**

None mentioned in the provided benchmark definition, but it's worth noting that some libraries may use special features like async/await or Promises to make their APIs more readable.

Ramda vs. Lodash vs. Immutable vs. Native array methods (version: 0) Benchmark.js

Comparing performance of: `Lodash vs Ramda compose vs Ramda pipe vs Immutable List vs Immutable Seq vs Native`

Created: 2 years ago by: Guest

Go to the latest result

Lodash

Ramda compose

Ramda pipe

Immutable List

Immutable Seq

Native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Ramda vs. Lodash vs. Immutable vs. Native array methods (version: 0) Benchmark.js

Comparing performance of: Lodash vs Ramda compose vs Ramda pipe vs Immutable List vs Immutable Seq vs Native

Created: 2 years ago by: Guest

Go to the latest result

Lodash

Ramda compose

Ramda pipe

Immutable List

Immutable Seq

Native

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `Lodash vs Ramda compose vs Ramda pipe vs Immutable List vs Immutable Seq vs Native`