<script src="//cdnjs.cloudflare.com/ajax/libs/ramda/0.25.0/ramda.min.js"></script>
function double(n) {
return n*2;
}
var data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30];
R.map(function(n) { return n*2}, data);
data.map(function(n) {return n*2});
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Ramda | |
Array (native) |
Test name | Executions per second |
---|---|
Ramda | 2711647.5 Ops/sec |
Array (native) | 3679058.2 Ops/sec |
Let's dive into the benchmark definition and explain what is being tested.
Benchmark Definition:
The benchmark measures the speed of two different approaches to map over an array:
R.map
: This uses Ramda, a functional programming library for JavaScript. Specifically, it uses R.map
, which applies a given function to each element of an array and returns a new array with the transformed elements.map
(non-arrow): This is the built-in map
method on JavaScript arrays. It takes two arguments: a callback function and an array. The callback function is executed for each element in the array, and its return value becomes the corresponding element in the new array.Options Compared:
The benchmark compares the performance of Ramda's R.map
versus the native map
method on arrays (non-arrow). This allows users to see how a functional programming library performs compared to the built-in JavaScript method.
Pros and Cons:
R.map
:map
(non-arrow):Library:
The library being used here is Ramda, which provides a wide range of utility functions for functional programming. In this case, it's used for its map
function, which applies a given function to each element of an array.
Special JS Feature or Syntax:
There are no special JavaScript features or syntaxes being used in this benchmark. It only involves standard JavaScript methods and libraries (Ramda).
Other Considerations:
Other alternatives to consider when mapping over arrays include:
map
method.map
method or Ramda's R.map
.Keep in mind that the performance differences between these approaches may vary depending on specific use cases, array sizes, and JavaScript environments.