bench::workout(total=) #95

options(width = 200)
suppressPackageStartupMessages({
  library(dplyr, warn.conflicts = FALSE)
  library(purrr)
  library(vctrs)
  library(rlang)
})

workout <- function(...) {
  out <- bench::workout(...)
  bind_rows(
    mutate(out, exprs = as.character(exprs)), 
    tibble(exprs = "<total>", process = sum(out$process), real = sum(out$real))
  )
}

m0 <- matrix(0, 50, 2000)
groups <- sample(1:10, 50, replace = TRUE)

m1 <- apply(m0, c(1,2), function(x) sample(c(0,1),1)) %>%
  as.data.frame() %>%
  mutate(groups = groups)

m2 <- m1 %>%
  group_by(groups)

make_sum_expressions <- function(names) {
  map(set_names(names), ~expr(sum(!!sym(.x))))
}

eval_loop <- function(.data) {
  mask <- as_data_mask(.data)
  map(expressions, eval_tidy, data = mask)
}

workout({
  # generate expressions x = sum(x) for all, similar to what _all() does
  expressions <- make_sum_expressions(names(m2)[1:2000]) 
  indices <- group_rows(m2)
  
  # chop the entire data frame at once, this gives a list of all the cur_data_all()
  chops <- vec_chop(m2, indices)
  
  # then we "just" have to eval_tidy() the expression
  out <- map(chops, eval_loop)
  
  # turn them into a tibble
  tibbles <- map(out, as_tibble)
  
  # then bind
  bind_rows(tibbles)
})
#> # A tibble: 7 x 3
#>   exprs                                                   process     real
#>   <chr>                                                  <bch:tm> <bch:tm>
#> 1 expressions <- make_sum_expressions(names(m2)[1:2000])  15.68ms  15.72ms
#> 2 indices <- group_rows(m2)                                 217µs 218.28µs
#> 3 chops <- vec_chop(m2, indices)                          30.42ms  30.51ms
#> 4 out <- map(chops, eval_loop)                            61.21ms  61.27ms
#> 5 tibbles <- map(out, as_tibble)                          81.81ms  82.07ms
#> 6 bind_rows(tibbles)                                       9.46ms   9.48ms
#> 7 <total>                                                198.81ms 199.26ms