How to use R's ellipsis feature when writing your own function?

I read answers and comments and I see that few things weren't mentioned:

1. data.frame uses list(...) version. Fragment of the code:

   object <- as.list(substitute(list(...)))[-1L]
   mrn <- is.null(row.names)
   x <- list(...)
   

   object is used to do some magic with column names, but x is used to create final data.frame.
   For use of unevaluated ... argument look at write.csv code where match.call is used.

2. As you write in comment result in Dirk answer is not a list of lists. Is a list of length 4, which elements are language type. First object is a symbol - list, second is expression 1:10 and so on. That explain why [-1L] is needed: it removes expected symbol from provided arguments in ... (cause it is always a list).
   As Dirk states substitute returns "parse tree the unevaluated expression".
   When you call my_ellipsis_function(a=1:10,b=11:20,c=21:30) then ... "creates" a list of arguments: list(a=1:10,b=11:20,c=21:30) and substitute make it a list of four elements:

   List of 4
   $  : symbol list
   $ a: language 1:10
   $ b: language 11:20
   $ c: language 21:30
   

   First element doesn't have a name and this is [[1]] in Dirk answer. I achieve this results using:

   my_ellipsis_function <- function(...) {
     input_list <- as.list(substitute(list(...)))
     str(input_list)
     NULL
   }
   my_ellipsis_function(a=1:10,b=11:20,c=21:30)
   

3. As above we can use str to check what objects are in a function.

   my_ellipsis_function <- function(...) {
       input_list <- list(...)
       output_list <- lapply(X=input_list, function(x) {str(x);summary(x)})
       return(output_list)
   }
   my_ellipsis_function(a=1:10,b=11:20,c=21:30)
    int [1:10] 1 2 3 4 5 6 7 8 9 10
    int [1:10] 11 12 13 14 15 16 17 18 19 20
    int [1:10] 21 22 23 24 25 26 27 28 29 30
   $a
      Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
      1.00    3.25    5.50    5.50    7.75   10.00 
   $b
      Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
      11.0    13.2    15.5    15.5    17.8    20.0 
   $c
      Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
      21.0    23.2    25.5    25.5    27.8    30.0 
   

   It's ok. Lets see substitute version:

      my_ellipsis_function <- function(...) {
          input_list <- as.list(substitute(list(...)))
          output_list <- lapply(X=input_list, function(x) {str(x);summary(x)})
          return(output_list)
      }
      my_ellipsis_function(a=1:10,b=11:20,c=21:30)
       symbol list
       language 1:10
       language 11:20
       language 21:30
      [[1]]
      Length  Class   Mode 
           1   name   name 
      $a
      Length  Class   Mode 
           3   call   call 
      $b
      Length  Class   Mode 
           3   call   call 
      $c
      Length  Class   Mode 
           3   call   call 
   

   Isn't what we needed. You will need additional tricks to deal with these kind of objects (as in write.csv).

If you want use ... then you should use it as in Shane answer, by list(...).

You can convert the ellipsis into a list with list(), and then perform your operations on it:

> test.func <- function(...) { lapply(list(...), class) }
> test.func(a="b", b=1)
$a
[1] "character"

$b
[1] "numeric"

So your get_list_from_ellipsis function is nothing more than list.

A valid use case for this is in cases where you want to pass in an unknown number of objects for operation (as in your example of c() or data.frame()). It's not a good idea to use the ... when you know each parameter in advance, however, as it adds some ambiguity and further complication to the argument string (and makes the function signature unclear to any other user). The argument list is an important piece of documentation for function users.

Otherwise, it is also useful for cases when you want to pass through parameters to a subfunction without exposing them all in your own function arguments. This can be noted in the function documentation.

Just to add to Shane and Dirk's responses: it is interesting to compare

get_list_from_ellipsis1 <- function(...)
{
  list(...)
}
get_list_from_ellipsis1(a = 1:10, b = 2:20) # returns a list of integer vectors

$a
 [1]  1  2  3  4  5  6  7  8  9 10

$b
 [1]  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20

with

get_list_from_ellipsis2 <- function(...)
{
  as.list(substitute(list(...)))[-1L]
}
get_list_from_ellipsis2(a = 1:10, b = 2:20) # returns a list of calls

$a
1:10

$b
2:20

As it stands, either version appears suitable for your purposes in my_ellipsis_function, though the first is clearly simpler.