Benchmark: ramda pickby vs native

HTML Preparation code:


<script src='https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.1/ramda.js'></script>

Script Preparation code:

data = {
 1: { a: 'b' },
   2: { a: 'b' },
   3: { a: 'v' },
   4: { a: 'b' },
   5: { a: 'n' },
   6: { a: 'e' }
};

Tests:

pickBy
R.pipe(R.pickBy(R.propEq('b', 'a')), R.values, data);
native
const result = []; Object.keys(data).forEach((key) => { if (data[key].a === 'b') { result.push(data[key]); } });

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
pickBy
native

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down the provided benchmark test and explain what's being tested, compared, and their pros and cons.

**Benchmark Definition**

The benchmark is designed to compare two approaches: using Ramda's `pickBy` function with `R.propEq('b', 'a')` (often referred to as "Ramda pickby") and the native JavaScript approach using a simple loop.

**What is being tested?**

The test is comparing the performance of these two approaches when filtering an object array based on a specific property-value pair. The input data is a JSON object `data` with six key-value pairs, where each value has either "a" equal to "b", "v", "n", or "e".

**Options compared**

There are two options being compared:

1. **Ramda pickby**: This approach uses the Ramda library's `pickBy` function, which takes a predicate function (`R.propEq('b', 'a')`) and an object as input. It returns a new object with only the properties that satisfy the predicate.
2. **Native JavaScript**: This approach uses a simple loop to iterate through the keys of the `data` object and push the objects with "a" equal to "b" into an array.

**Pros and Cons**

**Ramda pickby:**

Pros:

* Concise and readable code
* Ramda library provides a robust set of functional programming utilities
* Potential performance benefits from optimized C++ implementation

Cons:

* External dependency on the Ramda library (adds 2KB download size)
* May not be suitable for projects with strict dependencies or size constraints
* Can be less intuitive for developers without experience with functional programming

**Native JavaScript:**

Pros:

* No external dependencies, reducing project size and complexity
* Easy to understand and implement for developers familiar with loops and conditionals
* Potential performance benefits from native code execution

Cons:

* Code is longer and more verbose compared to Ramda pickby
* May not be as efficient due to the loop iteration overhead
* Less readable and maintainable than the concise Ramda code

**Library and its purpose**

The Ramda library is a popular functional programming utility belt for JavaScript. Its `pickBy` function takes a predicate function and an object as input, returning a new object with only the properties that satisfy the predicate.

In this benchmark, Ramda's `pickBy` is used to filter the `data` object based on the "b" property being equal to "a".

**Special JS feature or syntax**

There are no special features or syntaxes mentioned in the benchmark. However, it's worth noting that some newer JavaScript features like async/await and modernized `for...of` loops might be used in the implementation of the native loop approach.

**Alternatives**

Other alternatives for filtering objects based on properties include:

* Using a library like Lodash or Moment.js, which provide similar functionality to Ramda
* Implementing a custom filtering function using vanilla JavaScript (e.g., `forEach`, `filter`)
* Utilizing modern JavaScript features like arrow functions and template literals to create concise and readable code

Keep in mind that these alternatives may introduce additional dependencies, complexity, or performance overhead compared to the Ramda pickby approach.

Related benchmarks:

ramda pickby vs native (version: 0)

Comparing performance of: pickBy vs native

Created: 5 years ago by: Guest

Jump to the latest result

pickBy

native

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):