<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];
data.map(double);
R.map(double, data);
--enable-precise-memory-info
flag.
Test case name | Result |
---|---|
Array (native) | |
Ramda |
Test name | Executions per second |
---|---|
Array (native) | 2307672.0 Ops/sec |
Ramda | 852319.5 Ops/sec |
Let's dive into the benchmark analysis.
The provided JSON represents a JavaScript microbenchmark that compares the performance of native Array methods with those from the Ramda library.
Benchmarked Options
Two options are being compared:
map()
, which is used in the benchmark definition data.map(double);
.map()
with additional features like type checking and currying.Pros and Cons
Native Array methods are:
However, they can be platform-dependent (e.g., performance may vary on different architectures or browsers).
Ramda's R.map() function is:
However, it requires importing the Ramda library, which can add to the benchmark's size and complexity.
Library: Ramda
Ramda is a functional programming library for JavaScript that provides an implementation of map()
among other useful functions. It aims to provide a more expressive and composable way of working with data, while still maintaining performance comparable to native Array methods.
Special JS Feature/Syntax (None)
There are no special JavaScript features or syntax used in this benchmark.
Other Alternatives
If you need to compare the performance of other array manipulation functions, you could consider adding more benchmark cases, such as:
map()
functionKeep in mind that each of these alternatives would require separate benchmark definitions and code.
I hope this explanation helps software engineers understand the JavaScript microbenchmark!