Split up `…` arguments and distribute to multiple functions

Question

Using the following function foo() as a simple example, I\'d like to distribute the values given in ... two different functions, if possible.

Answer 1

Separate Lists If you really want to pass different sets of parameters to different functions then it's probably cleaner to specify separate lists:

foo <- function(x, y, sum = list(), grep = list()) {
 list(sum = do.call("sum", c(x, sum)), grep = do.call("grep", c("abc", y, grep)))
}

# test

X <- c(1:5, NA, 6:10)
Y <- "xyzabcxyz"
foo(X, Y, sum = list(na.rm = TRUE), grep = list(value = TRUE))

## $sum
## [1] 55
## 
## $grep
## [1] "xyzabcxyz"

Hybrid list / ... An alternative is that we could use ... for one of these and then specify the other as a list, particularly in the case that one of them is frequently used and the other is infrequently used. The frequently used one would be passed via ... and the infrequently used via a list. e.g.

foo <- function(x, y, sum = list(), ...) {
 list(sum = do.call("sum", c(x, sum)), grep = grep("abc", y, ...))
}

foo(X, Y, sum = list(na.rm = TRUE), value = TRUE)

Here are a couple of examples of the hybrid approach from R itself:

i) The mapply function takes that approach using both ... and a MoreArgs list:

> args(mapply)
function (FUN, ..., MoreArgs = NULL, SIMPLIFY = TRUE, USE.NAMES = TRUE) 
NULL

ii) nls also takes this approach using both ... and the control list:

> args(nls)
function (formula, data = parent.frame(), start, control = nls.control(), 
    algorithm = c("default", "plinear", "port"), trace = FALSE, 
    subset, weights, na.action, model = FALSE, lower = -Inf, 
    upper = Inf, ...) 
NULL