R/day04.R

In tjmahr/adventofcode20: Advent of Code 2020

#' Day 04: Passport Processing
#'
#' [Passport Processing](https://adventofcode.com/2020/day/4)
#'
#' @name day04
#' @rdname day04
#' @details
#'
#' **Part One**
#'
#' You arrive at the airport only to realize that you grabbed your North
#' Pole Credentials instead of your passport. While these documents are
#' extremely similar, North Pole Credentials aren\'t issued by a country
#' and therefore aren\'t actually valid documentation for travel in most of
#' the world.
#'
#' It seems like you\'re not the only one having problems, though; a very
#' long line has formed for the automatic passport scanners, and the delay
#' could upset your travel itinerary.
#'
#' Due to some questionable network security, you realize you might be able
#' to solve both of these problems at the same time.
#'
#' The automatic passport scanners are slow because they\'re having trouble
#' *detecting which passports have all required fields*. The expected
#' fields are as follows:
#'
#' -   `byr` (Birth Year)
#' -   `iyr` (Issue Year)
#' -   `eyr` (Expiration Year)
#' -   `hgt` (Height)
#' -   `hcl` (Hair Color)
#' -   `ecl` (Eye Color)
#' -   `pid` (Passport ID)
#' -   `cid` (Country ID)
#'
#' Passport data is validated in batch files (your puzzle input). Each
#' passport is represented as a sequence of `key:value` pairs separated by
#' spaces or newlines. Passports are separated by blank lines.
#'
#' Here is an example batch file containing four passports:
#'
#'     ecl:gry pid:860033327 eyr:2020 hcl:#fffffd
#'     byr:1937 iyr:2017 cid:147 hgt:183cm
#'
#'     iyr:2013 ecl:amb cid:350 eyr:2023 pid:028048884
#'     hcl:#cfa07d byr:1929
#'
#'     hcl:#ae17e1 iyr:2013
#'     eyr:2024
#'     ecl:brn pid:760753108 byr:1931
#'     hgt:179cm
#'
#'     hcl:#cfa07d eyr:2025 pid:166559648
#'     iyr:2011 ecl:brn hgt:59in
#'
#' The first passport is *valid* - all eight fields are present. The second
#' passport is *invalid* - it is missing `hgt` (the Height field).
#'
#' The third passport is interesting; the *only missing field* is `cid`, so
#' it looks like data from North Pole Credentials, not a passport at all!
#' Surely, nobody would mind if you made the system temporarily ignore
#' missing `cid` fields. Treat this \"passport\" as *valid*.
#'
#' The fourth passport is missing two fields, `cid` and `byr`. Missing
#' `cid` is fine, but missing any other field is not, so this passport is
#' *invalid*.
#'
#' According to the above rules, your improved system would report `2`
#' valid passports.
#'
#' Count the number of *valid* passports - those that have all required
#' fields. Treat `cid` as optional. *In your batch file, how many passports
#' are valid?*
#'
#' **Part Two**
#'
#' The line is moving more quickly now, but you overhear airport security
#' talking about how passports with invalid data are getting through.
#' Better add some data validation, quick!
#'
#' You can continue to ignore the `cid` field, but each other field has
#' [strict rules]{title="GLORY TO ARSTOTZKA"} about what values are valid
#' for automatic validation:
#'
#' -   `byr` (Birth Year) - four digits; at least `1920` and at most
#'     `2002`.
#' -   `iyr` (Issue Year) - four digits; at least `2010` and at most
#'     `2020`.
#' -   `eyr` (Expiration Year) - four digits; at least `2020` and at most
#'     `2030`.
#' -   `hgt` (Height) - a number followed by either `cm` or `in`:
#'     -   If `cm`, the number must be at least `150` and at most `193`.
#'     -   If `in`, the number must be at least `59` and at most `76`.
#' -   `hcl` (Hair Color) - a `#` followed by exactly six characters
#'     `0`-`9` or `a`-`f`.
#' -   `ecl` (Eye Color) - exactly one of: `amb` `blu` `brn` `gry` `grn`
#'     `hzl` `oth`.
#' -   `pid` (Passport ID) - a nine-digit number, including leading zeroes.
#' -   `cid` (Country ID) - ignored, missing or not.
#'
#' Your job is to count the passports where all required fields are both
#' *present* and *valid* according to the above rules. Here are some
#' example values:
#'
#'     byr valid:   2002
#'     byr invalid: 2003
#'
#'     hgt valid:   60in
#'     hgt valid:   190cm
#'     hgt invalid: 190in
#'     hgt invalid: 190
#'
#'     hcl valid:   #123abc
#'     hcl invalid: #123abz
#'     hcl invalid: 123abc
#'
#'     ecl valid:   brn
#'     ecl invalid: wat
#'
#'     pid valid:   000000001
#'     pid invalid: 0123456789
#'
#' Here are some invalid passports:
#'
#'     eyr:1972 cid:100
#'     hcl:#18171d ecl:amb hgt:170 pid:186cm iyr:2018 byr:1926
#'
#'     iyr:2019
#'     hcl:#602927 eyr:1967 hgt:170cm
#'     ecl:grn pid:012533040 byr:1946
#'
#'     hcl:dab227 iyr:2012
#'     ecl:brn hgt:182cm pid:021572410 eyr:2020 byr:1992 cid:277
#'
#'     hgt:59cm ecl:zzz
#'     eyr:2038 hcl:74454a iyr:2023
#'     pid:3556412378 byr:2007
#'
#' Here are some valid passports:
#'
#'     pid:087499704 hgt:74in ecl:grn iyr:2012 eyr:2030 byr:1980
#'     hcl:#623a2f
#'
#'     eyr:2029 ecl:blu cid:129 byr:1989
#'     iyr:2014 pid:896056539 hcl:#a97842 hgt:165cm
#'
#'     hcl:#888785
#'     hgt:164cm byr:2001 iyr:2015 cid:88
#'     pid:545766238 ecl:hzl
#'     eyr:2022
#'
#'     iyr:2010 hgt:158cm hcl:#b6652a ecl:blu byr:1944 eyr:2021 pid:093154719
#'
#' Count the number of *valid* passports - those that have all required
#' fields *and valid values*. Continue to treat `cid` as optional. *In your
#' batch file, how many passports are valid?*
#'
#' @param x some data
#' @return For Part One, `check_for_valid_passports(x)` returns a logical vector
#'   indicating whether each passport is valid. For Part Two, `f04b(x)` returns
#'   ....
#' @export
#' @examples
#' x <-
#'   "
#'   ecl:gry pid:860033327 eyr:2020 hcl:#fffffd
#'   byr:1937 iyr:2017 cid:147 hgt:183cm
#'
#'   iyr:2013 ecl:amb cid:350 eyr:2023 pid:028048884
#'   hcl:#cfa07d byr:1929
#'
#'   hcl:#ae17e1 iyr:2013
#'   eyr:2024
#'   ecl:brn pid:760753108 byr:1931
#'   hgt:179cm
#'
#'   hcl:#cfa07d eyr:2025 pid:166559648
#'   iyr:2011 ecl:brn hgt:59in
#'   "
#'
#' x <- read_text_lines(x, drop_empty = "head/tail")
#' check_for_valid_passports(x)
#'
#' x_bad <-
#'   "
#'   eyr:1972 cid:100
#'   hcl:#18171d ecl:amb hgt:170 pid:186cm iyr:2018 byr:1926
#'
#'     iyr:2019
#'   hcl:#602927 eyr:1967 hgt:170cm
#'     ecl:grn pid:012533040 byr:1946
#'
#'   hcl:dab227 iyr:2012
#'   ecl:brn hgt:182cm pid:021572410 eyr:2020 byr:1992 cid:277
#'
#'   hgt:59cm ecl:zzz
#'   eyr:2038 hcl:74454a iyr:2023
#'   pid:3556412378 byr:2007
#'   "
#'
#' x_good <-
#'   "
#'   pid:087499704 hgt:74in ecl:grn iyr:2012 eyr:2030 byr:1980
#'   hcl:#623a2f
#'
#'   eyr:2029 ecl:blu cid:129 byr:1989
#'   iyr:2014 pid:896056539 hcl:#a97842 hgt:165cm
#'
#'   hcl:#888785
#'   hgt:164cm byr:2001 iyr:2015 cid:88
#'   pid:545766238 ecl:hzl
#'   eyr:2022
#'
#'   iyr:2010 hgt:158cm hcl:#b6652a ecl:blu byr:1944 eyr:2021 pid:093154719
#'   "
#'
#' x_good <- read_text_lines(x_good, drop_empty = "head/tail")
#' x_bad <- read_text_lines(x_bad, drop_empty = "head/tail")
#'
#' check_for_valider_passports(x_good)
#' check_for_valider_passports(x_bad)
check_for_valid_passports <- function(x) {
  y <- parse_passport_lines(x)
  y[["cid"]] <- NULL

  # stats::complete_cases() also works
  unname(apply(y, 1, Negate(anyNA)))
}


#' @rdname day04
#' @export
check_for_valider_passports <- function(x) {
  data <- parse_passport_lines(x)

  # Let's try not using any regular expressions
  is_valid_hgt <- function(xs) {
    type <- substr(xs, nchar(xs) - 1, nchar(xs))
    value <- as.numeric(substr(xs, 1, nchar(xs) - 2))
    upper <- ifelse(type == "cm", 193, 76)
    lower <- ifelse(type == "cm", 150, 59)
    (lower <= value & value <= upper) %in% TRUE
  }

  is_valid_pid <- function(xs) {
    only_digits <- xs %>%
      lapply(strsplit, "") %>%
      lapply(unlist) %>%
      lapply(function(x) all(x %in% as.character(0:9))) %>%
      unlist()
    length_9 <- nchar(xs) == 9
    (length_9 & only_digits) %in% TRUE
  }

  is_valid_hcl <- function(xs) {
    length_7 <- nchar(xs) == 7
    leading_pound <- substr(xs, 1, 1) == "#"
    rest_xs <- substr(xs, 2, 7)

    hex_values <- c(as.character(0:9), "a", "b", "c", "d", "e", "f")
    only_hex <- rest_xs %>%
      lapply(strsplit, "") %>%
      lapply(unlist) %>%
      lapply(function(x) all(x %in% hex_values)) %>%
      unlist()
    (length_7 & leading_pound & only_hex) %in% TRUE
  }

  data_clean <- data %>%
    filter_rows_in(1920 <= .data$byr, .data$byr <= 2002) %>%
    filter_rows_in(2010 <= .data$iyr, .data$iyr <= 2020) %>%
    filter_rows_in(2020 <= .data$eyr, .data$eyr <= 2030) %>%
    filter_rows_in(
      .data$ecl %in% c("amb", "blu", "brn", "gry", "grn", "hzl", "oth")
    ) %>%
    filter_rows_in(is_valid_hgt(.data$hgt)) %>%
    filter_rows_in(is_valid_pid(.data$pid)) %>%
    filter_rows_in(is_valid_hcl(.data$hcl))

  nrow(data_clean)
}

parse_passport_lines <- function(x) {
  prototype <- list(
    byr = NA, cid = NA, ecl = NA, eyr = NA,
    hcl = NA, hgt = NA, iyr = NA, pid = NA
  )

  key_value_pair_to_list <- function(x) {
    stats::setNames(list(x[2]), x[1])
  }

  # Let's try not using any regular expressions
  results <- x %>%
    group_at_empty_lines() %>%
    # Separate fields at spaces
    lapply(strsplit, " ") %>%
    lapply(unlist) %>%
    # Make each x:y into list(x = y) and combine the lists at the same level
    lapply(function(x) {
      x %>%
        strsplit(":") %>%
        lapply(key_value_pair_to_list) %>%
        unlist(recursive = FALSE)
    }) %>%
    # Fill in missing fields with NAs
    lapply(function(x) utils::modifyList(prototype, x)) %>%
    # Create a dataframe
    lapply(as.data.frame) %>%
    invoke_call(rbind)

  results["passport"] <- seq_len(nrow(results))
  results[c(9, 1:8)]
}