Cafeteria

library(mistlecode)

options(scipen = 999)

Part 1

Error: cannot allocate vector of size 3238080.8 Gb yeah okay. Just doing %in% would’ve been too easy. But my actual solution isn’t that much more complicated either. I’m not sure I’ve ever actually used dplyr::join_by() before.

input <- readLines('input.txt')

ranges <-
  input[1:(which(input == '')-1)] |>
  purrr::map(\(x) {
    x |>
      stringr::str_split_1('-') |>
      as.numeric()
  }) |>
  do.call(rbind, args = _) |>
  as.data.frame()

input[(which(input == '')+1):length(input)] |>
  as.numeric() |>
  tibble::tibble() |>
  setNames('values') |>
  dplyr::inner_join(
    y = ranges,
    by = dplyr::join_by(dplyr::between(x$values, y$V1, y$V2))
  ) |>
  dplyr::pull(.data$values) |>
  unique() |>
  length()

[1] 607

Part 2

I’m sure there’s a more efficient way. That said, initially I was starting back at row one every time a new range was found and that was taking forever. I realized I can just subtract one from my current index to account for the row I lost and there will always be something new until there isn’t.

downsize <- function(ranges, i = 1) {
  # browser()
  if (i > nrow(ranges)) return(ranges)
  r <- ranges[i,]
  
  new_ranges <-
    ranges[-i,] |>
    dplyr::filter(
      (r$V1 >= .data$V1 & r$V1 <= .data$V2) | (r$V2 >= .data$V1 & r$V1 <= .data$V2)
    ) |>
    purrr::pmap(\(V1, V2) {
      tibble::tibble(
        'V1' = min(r$V1, V1),
        'V2' = max(r$V2, V2)
      )
    }) |>
    purrr::list_rbind()
  
  if (nrow(new_ranges) == 0) {
    downsize(ranges, i + 1) 
  } else {
    ranges <- ranges[-i,]
    ranges |>
      dplyr::bind_rows(new_ranges) |>
      unique() |>
      downsize(i - 1)
  }
}

ranges |>
  downsize() |>
  dplyr::mutate(
    'size' = .data$V2 - .data$V1 + 1
  ) |>
  dplyr::pull(.data$size) |>
  sum()

[1] 342433357244012