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Use tidyselect select helpers in functions that do not implement them

How to use dplyr/tidyselect "select helpers", such as : to select a range of consecutive variables, in functions that do not implement them?
If possible in a simple/elegant manner (of course this is subjective).

Here is an example with dplyr::distinct, note the question is generic though

library(dplyr)

mtcars %>% 
  distinct(vs:gear, 
           .keep_all = TRUE)
#> Warning in vs:gear: numerical expression has 32 elements: only the first used

#> Warning in vs:gear: numerical expression has 32 elements: only the first used
#> Error: Column `vs:gear` must be length 32 (the number of rows) or one, not 5

First attempt with dplyr::select. Can we do better?

mtcars %>% 
  distinct(!!! syms(names(select(., vs:gear))),
           .keep_all = TRUE)
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> 2 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> 3 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 4 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#> 5 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
#> 6 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#> 7 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2

Second attempt based based on https://tidyselect.r-lib.org/articles/tidyselect.html, that actually feels worse

# With tidyselect >= 1.0
mtcars %>% 
  distinct(!!! syms(names(tidyselect::eval_select(quote(vs:gear), .))),
           .keep_all = TRUE)
#>    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
#> 1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
#> 2 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
#> 3 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
#> 4 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
#> 5 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
#> 6 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
#> 7 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2

# Or equivalently
distinct2 <- function(.data, ..., .keep_all = FALSE) {
  expr <- rlang::expr(c(...))
  pos <- tidyselect::eval_select(expr, data = .data)
  dplyr::distinct(.data = .data, .keep_all = .keep_all,
                  !!! syms(names(pos)))
}
mtcars %>% 
  distinct2(vs:gear, .keep_all = TRUE)
Solution

  • Except of already mentioned distinct_at(), you can also try:

    mtcars %>%
 distinct(!!!select(., vs:gear), .keep_all = TRUE)

   mpg cyl  disp  hp drat    wt  qsec vs am gear carb
1 21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
2 22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
3 21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
4 18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
5 24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
6 26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
7 30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2