Benchmark: lodash chain vs ramdajs pipe

HTML Preparation code:

<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.27.0/ramda.js"></script>
<script src="//cdnjs.cloudflare.com/ajax/libs/lodash.js/4.17.15/lodash.fp.js"></script>

Script Preparation code:

var numbers = Array(100).fill().map((item, index) => index + 1);
var isEven = number => number % 2 === 0;

Tests:

Ramda PIPE
R.pipe(R.filter(isEven), R.map(x => x + 1))(numbers);
Lodash flow
_.chain(numbers).filter(isEven).map(x => x + 1).value();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Ramda PIPE
Lodash flow

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):

LLMs can make mistakes. Check important info.

Let's break down what is being tested in the provided JSON benchmark.

**What is being tested?**

The benchmark tests two different approaches to create a pipeline of functions using functional programming:

1. **Ramda PIPE**: This approach uses Ramda, a popular JavaScript library for functional programming. Specifically, it uses the `R.pipe` function to chain together three functions:
	* `R.filter(isEven)`: filters out even numbers from the input array.
	* `R.map(x => x + 1)`: applies an increment operation to each remaining number.
2. **Lodash flow**: This approach uses Lodash, another popular JavaScript library for functional programming. Specifically, it uses the `_chain` function to create a chain of functions:
	* `.filter(isEven)` : filters out even numbers from the input array.
	* `.map(x => x + 1)`: applies an increment operation to each remaining number.

**Options compared**

The benchmark compares two approaches:

* Ramda PIPE (using `R.pipe`)
* Lodash flow (using `_chain`)

**Pros and Cons of each approach**

**Ramda PIPE**

Pros:

* More concise syntax: `R.pipe` allows you to chain functions together in a single line.
* Easier to read and maintain, as the order of operations is explicit.

Cons:

* Requires Ramda library, which may have additional dependencies or size considerations.
* May be less intuitive for developers without prior experience with functional programming.

**Lodash flow**

Pros:

* More flexible syntax: `_.chain` allows you to create a chain of functions with multiple lines and indentation.
* Easier to understand and maintain complex pipelines.

Cons:

* Less concise syntax compared to Ramda PIPE.
* May require more code or nesting, which can be harder to read.

**Library considerations**

Both libraries are widely used and well-maintained, but they have different philosophies and use cases. Ramda is designed for functional programming purists, while Lodash is more geared towards JavaScript developers who need a broader range of utilities.

**Special JS feature or syntax**

None mentioned in this benchmark. However, if you're interested in exploring other special features or syntax, we could discuss topics like:

* Arrow functions (`=>`)
* Async/await
* Promises
* Generators

Let me know if you'd like to explore any of these topics!

**Other alternatives**

If you're not familiar with Ramda or Lodash, there are other JavaScript libraries that implement functional programming concepts. Some popular alternatives include:

* Immer: for state management and immutable updates.
* Preact: a lightweight alternative to React for building user interfaces.
* FSA (Flux Standard Action): for state management and event-driven applications.

Keep in mind that each library has its own strengths, weaknesses, and learning curves.

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36

Browser/OS: Chrome 110 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
Ramda PIPE	512943.5 Ops/sec
Lodash flow	245651.5 Ops/sec

Related benchmarks:

lodash chain vs ramdajs pipe (version: 0)

check this out

Comparing performance of: Ramda PIPE vs Lodash flow

Created: one year ago by: Guest

Jump to the latest result

Ramda PIPE

Lodash flow

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 27 days ago):