I'm developing a package in R which main interface is two classes: a class handling data (let's call it Data) and a class handling a collection of Data instances (we call it Collection). Data instances can be rather larger (50 mb +), which is why the Collection class is a wrapper around an environment.
I want to implement a c() function for Data which will result in a Collection instance. In order to do so the arguments are passed as ... and the Collection instance has to be build up iteratively. I know I can loop through ... by first making it a list by list(...), but this could be potentially expensive. Is there anyway to loop through ... without first copying everything over to a temporary list?
What seems to work is to use the dots function from the pryr package (I can imagine there are other more simple solutions possible):
library(pryr)
fun1 <- function(...) {
l <- dots(...)
result <- list(mode="list", length = length(l))
for (i in seq_along(l)) {
v <- l[[i]]
result[[i]] <- eval(v)
}
result
}
Timing this against an implementation using list and an implementation without ...
fun2 <- function(...) {
l <- list(...)
result <- list(mode="list", length = length(l))
for (i in seq_along(l)) {
v <- l[[i]]
result[[i]] <- v
}
result
}
fun1 <- function(...) {
l <- dots(...)
result <- list(mode="list", length = length(l))
for (i in seq_along(l)) {
v <- l[[i]]
result[[i]] <- eval(v)
}
result
}
fun3 <- function(a, b) {
list(a, b)
}
> system.time(r1 <- fun1(large_object1, large_object2))
user system elapsed
0.060 0.072 0.133
> system.time(r2 <- fun2(large_object1, large_object2))
user system elapsed
0.132 0.132 0.265
> system.time(r3 <- fun3(large_object1, large_object2))
user system elapsed
0.056 0.076 0.132
We see that the implementation using dots performs similar as the implementation without ... and faster than the implementation using list.
If you don't want to depend on pryr: the code of dots is quite 'simple':
dots <- function (...) {
eval(substitute(alist(...)))
}
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