Benchmark: ramda pickby vs native 2

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 = []; const values = Object.values(data); for (let i = 0; i < values.length; i++) { if (values[i].a === 'b') { result.push(values[i]); } }

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 what's being tested in the provided JSON.

**Benchmark Definition**

The benchmark is comparing two approaches to filter an array of objects:

1. **Ramda `pickBy`**: This approach uses the Ramda library, which provides functional programming utilities for JavaScript. Specifically, it uses the `R.pickBy` function, which takes a predicate (a function that returns a boolean value) and an object as arguments. It returns a new array containing only the properties of the original object for which the predicate returns `true`. In this case, the predicate is `R.propEq('b', 'a')`, which checks if the value of property `'a'` in each object is equal to `'b'`. The resulting array is then passed through `R.values`, which extracts only the values from the objects.
2. **Native JavaScript**: This approach uses native JavaScript, without any library or framework. It uses a simple loop to iterate over the array of objects and push only the objects with property `'a'` equal to `'b'` into a new array.

**Comparison**

The benchmark is comparing these two approaches: Ramda `pickBy` vs Native JavaScript.

**Pros and Cons**

**Ramda `pickBy`**

Pros:

* More concise and expressive code
* Easier to read and maintain, as it avoids the need for explicit loops
* Potential performance benefits due to optimized C++ implementation

Cons:

* Requires the Ramda library to be included in the benchmark
* May have additional overhead due to the library's functionality

**Native JavaScript**

Pros:

* No additional dependencies or libraries required
* Potential performance benefits due to native code execution

Cons:

* More verbose and less expressive code
* Can be error-prone, especially for complex filter conditions

**Other Considerations**

* The benchmark uses a relatively small dataset (6 objects) which may not accurately represent the performance differences between these approaches. Larger datasets or more complex filter conditions could reveal different results.
* The `pickBy` function in Ramda is designed to work with a specific set of predicates, whereas native JavaScript can use any filter condition.
* The benchmark does not account for caching or memoization, which could impact performance.

**Library and Framework**

The benchmark uses the Ramda library, which is a functional programming utility library for JavaScript. Ramda provides a range of functions for data processing, filtering, mapping, reducing, and more.

**Special JS Feature/Syntax**

There are no special JavaScript features or syntax used in these benchmarks beyond the use of the `let` keyword for declaring variables and the `for` loop for iterating over arrays.

Related benchmarks:

ramda pickby vs native 2 (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):