Benchmark: Lodash & Ramda - MeasureThat.net

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(1000000).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 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);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

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

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.

**Benchmark Overview**

The provided JSON represents a JavaScript microbenchmarking test case created on MeasureThat.net. The benchmark tests two popular functional programming libraries: Lodash and Ramda. It measures the performance of each library in executing specific tasks, showcasing their differences in approach and syntax.

**Test Cases**

There are three individual test cases:

1. **Lodash**: This test case uses the Lodash library to chain a series of operations:
	* `_.chain(data)`: Create a pipeline from the input data.
	* `.pick('counter')`: Select only the 'counter' property from each object in the data.
	* `.filter(isOdd)` : Filter out even numbers using the `isOdd` function.
	* `.map(square)` : Square each remaining number.
	* `.filter(lessThanThreeDigits)` : Keep only numbers with less than 3 digits.
	* `.value()` : Return the final result as a single value.
2. **Ramda without currying or composition**: This test case uses Ramda's functional programming API but does not utilize its currying and composition features:
	* `R.filter(lessThanThreeDigits, R.map(square, R.filter(isOdd, R.pluck('counter', data))))`: Apply a series of functions sequentially using the pipe operator.
3. **Ramda with currying and composition**: This test case leverages Ramda's currying and composition features:
	* `R.pipe(R.pluck('counter'), R.filter(isOdd), R.map(square), R.filter(lessThanThreeDigits))(data)`: Apply a series of functions sequentially, where each function returns the output of the previous one.

**Options Compared**

The three test cases compare different approaches to functional programming:

1. **Lodash**: Uses chaining and method calls to execute the pipeline.
2. **Ramda without currying or composition**: Employs sequential application using the pipe operator, but without leveraging Ramda's advanced features.
3. **Ramda with currying and composition**: Utilizes Ramda's currying and composition features to create a more efficient and expressive pipeline.

**Pros and Cons**

Here are some general pros and cons for each approach:

1. **Lodash**:
	* Pros: Well-known and widely adopted, simple to read and understand.
	* Cons: Can be slower due to method call overhead.
2. **Ramda without currying or composition**:
	* Pros: Still a well-structured and readable API, with some performance benefits from sequential application.
	* Cons: May not leverage Ramda's full capabilities, resulting in less efficient code.
3. **Ramda with currying and composition**:
	* Pros: Can lead to more concise and expressive code, leveraging Ramda's advanced features for better performance.
	* Cons: May require a learning curve for developers unfamiliar with functional programming principles.

**Library Considerations**

The test case uses two popular JavaScript libraries:

1. **Lodash**: A widely used utility library providing a broad range of functions for tasks like array manipulation, string processing, and more.
2. **Ramda**: A functional programming library offering a powerful API for data processing and transformation, with features like currying, composition, and higher-order functions.

**Special JavaScript Features**

None of the test cases explicitly utilize any special JavaScript features or syntax, such as async/await or decorators.

Related benchmarks:

Lodash & Ramda (version: 0)

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

Created: 6 years ago by: Guest

Jump to the latest result

Lodash

Ramda without currying or composition

Ramda with currying and composition

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):