How to count rows by group with n() inside dplyr::across()?

In previous versions of dplyr, if I wanted to get row counts in addition to other summary values using summarise(), I could do something like

library(tidyverse)

df <- tibble(
    group = c("A", "A", "B", "B", "C"),
    value = c(1, 2, 3, 4, 5)
)

df %>%
    group_by(group) %>% 
    summarise(total = sum(value), count = n())

`summarise()` ungrouping output (override with `.groups` argument)

# A tibble: 3 x 3
  group total count
  <chr> <dbl> <int>
1 A         3     2
2 B         7     2
3 C         5     1

My instinct to get the same output using the new across() function would be

df %>%
  group_by(group) %>% 
  summarise(across(value, list(sum = sum, count = n)))
Error: Problem with `summarise()` input `..1`.
x unused argument (col)
ℹ Input `..1` is `across(value, list(sum = sum, count = n))`.
ℹ The error occurred in group 1: group = "A".

The issue is specific to the n() function, just calling sum() works as expected:

df %>%
  group_by(group) %>% 
  summarise(across(value, list(sum = sum)))
`summarise()` ungrouping output (override with `.groups` argument)
# A tibble: 3 x 2
  group value_sum
  <chr>     <dbl>
1 A             3
2 B             7
3 C             5

I've tried out various syntactic variations (using lambdas, experimenting with cur_group(), etc.), to no avail. How would I get the desired result within across()?

Solution

We can use the lamdba function for n() while the sum can be invoked just by calling it if there are no other arguments to be specified

library(dplyr)
df %>%
  group_by(group) %>% 
  summarise(across(value, list(sum = sum, count = ~ n())), .groups = 'drop')

-output

# A tibble: 3 x 3
#  group value_sum value_count
#  <chr>     <dbl>       <int>
#1 A             3           2
#2 B             7           2
#3 C             5           1