Using a variable number of groups with do in function - r

Question

I would like to understand if and how this could be achieved using the tidyverse framework.
Assume I have the following simple function:
my_fn <- function(list_char) {
data.frame(comma_separated = rep(paste0(list_char, collapse = ","),2),
second_col = "test",
stringsAsFactors = FALSE)
}
Given the below list:
list_char <- list(name = "Chris", city = "London", language = "R")
my function works fine if you run:
my_fn(list_char)
However if we change some of the list's elements with a vector of characters we could use the dplyr::do function in the following way to achieve the below:
list_char_mult <- list(name = c("Chris", "Mike"),
city = c("New York", "London"), language = "R")
expand.grid(list_char_mult, stringsAsFactors = FALSE) %>%
tbl_df() %>%
group_by_all() %>%
do(my_fn(list(name = .$name, city = .$city, language = "R")))
The question is how to write a function that could do this for a list with a variable number of elements. For example:
my_fn_generic <- function(list_char_mult) {
expand.grid(list_char_mult, stringsAsFactors = FALSE) %>%
tbl_df() %>%
group_by_all() %>%
do(my_fn(...))
}
Thanks

Answer 1

Regarding how to use the function with variable number of arguments
my_fn_generic <- function(list_char) {
expand.grid(list_char, stringsAsFactors = FALSE) %>%
tbl_df() %>%
group_by_all() %>%
do(do.call(my_fn, list(.)))
}
my_fn_generic(list_char_mult)
# A tibble: 4 x 4
# Groups: name, city, language [4]
# name city language comma_separated
# <chr> <chr> <chr> <chr>
#1 Chris London R Chris,London,R
#2 Chris New York R Chris,New York,R
#3 Mike London R Mike,London,R
#4 Mike New York R Mike,New York,R
Or use the pmap
library(tidyverse)
list_char_mult %>%
expand.grid(., stringsAsFactors = FALSE) %>%
mutate(comma_separated = purrr::pmap_chr(.l = ., .f = paste, sep=", ") )
# name city language comma_separated
#1 Chris New York R Chris, New York, R
#2 Mike New York R Mike, New York, R
#3 Chris London R Chris, London, R
#4 Mike London R Mike, London, R

Answer 2

If I understand your question, you could use apply without grouping:
expand.grid(list_char_mult, stringsAsFactors = FALSE) %>%
mutate(comma_separated = apply(., 1, paste, collapse=","))
expand.grid(list_char_mult, stringsAsFactors = FALSE) %>%
mutate(comma_separated = apply(., 1, my_fn))
name city language comma_separated
1 Chris London R Chris,London,R
2 Chris New York R Chris,New York,R
3 Mike London R Mike,London,R
4 Mike New York R Mike,New York,R