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

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/144.0.0.0 Safari/537.36

Browser/OS: Chrome 144 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
native add 1	17478306.0 Ops/sec
ramda add 1	16678512.0 Ops/sec
for loop	43712568.0 Ops/sec

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

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: 4 years ago by: Guest

Jump to the latest result

native add 1

ramda add 1

for loop

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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