Benchmark: Ramda vs native map speed vs for loop

HTML Preparation code:

<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/ramda/0.27.1/ramda.js"></script>

Script Preparation code:

var data = [
    1, 2, 3
]

Tests:

native add 1
data.map(item => item + 1)
ramda add 1
R.map(item => item + 1, data)
for loop
for (var i = 0; i < data.length; i++) { data[i] = data[i] + 1; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
native add 1
ramda add 1
for loop

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON and explain what's being tested, along with the pros and cons of each approach.

**Benchmark Definition JSON**

The benchmark is designed to compare the performance of three different methods:

1. **Native JavaScript Map**: The `map()` method built into JavaScript, which applies a given function to each element in an array.
2. **Ramda's `R.map()`**: A functional programming library (Ramda) that provides a `map()` function with additional features and optimizations.
3. **Manual Loop with For Each**: A traditional loop using a for-each construct to iterate over the array.

**Script Preparation Code**

The script preparation code includes:

* An example array `data` defined in JavaScript, which will be used as input for the benchmark tests.
* A script tag that loads Ramda's library (`ramda.js`) into the webpage.

**Individual Test Cases**

Each test case represents a different method for adding 1 to each element of the `data` array:

1. **Native add 1**: Uses the built-in JavaScript `map()` method.
2. **Ramda add 1**: Uses Ramda's `R.map()` function with an arrow function (`item => item + 1`) to transform each element in the array.
3. **For loop**: A traditional loop using a for-each construct (in this case, `for` keyword followed by parentheses containing the loop condition and increment).

**Pros and Cons of Each Approach**

* **Native JavaScript Map**:
	+ Pros: Built-in functionality, easy to use, no external dependencies.
	+ Cons: May not be optimized for performance, can lead to slower execution times due to additional overhead.
* **Ramda's R.map()**:
	+ Pros: Optimized for performance, provides additional features and flexibility (e.g., currying, memoization).
	+ Cons: Additional dependency on Ramda library, potentially introduces additional overhead.
* **Manual Loop with For Each**:
	+ Pros: No external dependencies, direct control over loop iterations and optimizations.
	+ Cons: More verbose code, prone to errors due to manual iteration.

**Library: Ramda**

Ramda is a functional programming library that provides various functions for manipulating arrays, objects, and other data structures. In this benchmark, Ramda's `R.map()` function is used to transform each element in the array using an arrow function (`item => item + 1`). The purpose of using Ramda is likely to provide performance optimizations and additional features compared to the native JavaScript `map()` method.

**Special JS Feature: Arrow Functions**

Arrow functions are a shorthand syntax for defining small, single-expression functions in JavaScript. In this benchmark, arrow functions are used with both the native JavaScript `map()` method (`item => item + 1`) and Ramda's `R.map()` function. The use of arrow functions provides a concise way to define simple transformations without declaring a full-fledged function using the traditional syntax (`function() { ... }`).

**Other Alternatives**

Other alternatives for adding 1 to each element in an array could include:

* Using `Array.prototype.forEach()` or `Array.prototype.reduce()` methods, which provide additional features and flexibility.
* Implementing custom loop logic using JavaScript's built-in `for` keyword with manual iteration.
* Utilizing other libraries or frameworks that provide optimized map functionality (e.g., Lodash).

Note that these alternatives may not be directly comparable to the benchmarked approaches without further modifications.

Latest run results:

Run details: (Test run date: 3 months ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36

Browser/OS: Chrome 126 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
native add 1	13729745.0 Ops/sec
ramda add 1	7127737.0 Ops/sec
for loop	2790938.8 Ops/sec

Related benchmarks:

Ramda vs native map speed vs for loop (version: 0)

Comparing performance of: native add 1 vs ramda add 1 vs for loop

Created: 3 years ago by: Guest

Jump to the latest result

native add 1

ramda add 1

for loop

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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