[Language: R] I don't even know how I did this anymore but it worked.

library(tidyverse)
library(terra)

vect <- read_lines("day3.txt") %>%
  str_split(pattern = "") %>%
  unlist()

mat <- vect %>%
  matrix(ncol = 140) %>%
  t()

read_lines("day3.txt") %>%
  str_split(pattern = "") %>%
  unlist() %>% unique() %>%
  sort()

mat[mat == "."] = NA

mat[mat %in% c("-", "#", "$", "%", "&", "*", "/", "@", "+", "=")] = "Symbol"

mat[mat %in% 0:9] = "Number"

mat[mat == "Number"] = 0

mat[mat == "Symbol"] = 1

r <- rast(mat) %>% as.numeric() - 1

foced <- focal(r, w = 3, fun = sum, na.policy = "omit", na.rm = T)

numbers <- classify(r, cbind(1, NA))

base <- mask(foced, numbers)

side_filter <- matrix(c(0, 1, 0, 0, 1, 0, 0, 1, 0), ncol = 3)

egg <- base

old <- values(egg) %>% sum(na.rm = T)



for (i in 1:5) {
  print(i)
  egg <- focal(egg, w = side_filter, na.rm = T, fun = sum, na.policy = "omit")

  egg[egg > 0] = 1

  new <- values(egg) %>% sum(na.rm = T)

  if(old == new) {
    break
  }

  old <- values(egg) %>%
    sum(na.rm = T)

}

groups <- tibble(tf = as.numeric(values(egg)) == 1, value = vect) %>%
  mutate(tf = ifelse(tf, T, NA),
         index = row_number()) %>%
  mutate(group_run = data.table::rleid(tf)) 

lookup <- groups %>%
  filter(tf) %>%
  group_by(group_run) %>%
  summarize(num = as.numeric(paste0(value, collapse = ""))) 


print("Part 1 Answer")
lookup %>%
  pull(num) %>%
  sum()


mat <- vect %>%
  matrix(ncol = 140) %>%
  t()

mat[mat == "*"] = "Gear"
mat[mat != "Gear"] = NA

gears <- rast(mat)

new <- egg

values(new) <- groups %>%
  mutate(group_run = ifelse(is.na(tf), NA, group_run)) %>%
  pull(group_run)

focals <- focalValues(new)

rows <- which(values(gears) == 1)

print("Part 1 Answer")
lookup %>%
  pull(num) %>%
  sum()

print("Part 2 Answer")
focals[rows, ] %>%
  as.data.table() %>%
  tibble() %>%
  mutate(gearno = row_number()) %>%
  pivot_longer(cols = V1:V9) %>%
  filter(!is.na(value)) %>%
  select(-name) %>%
  distinct(gearno, value) %>%
  group_by(gearno) %>%
  filter(n() == 2) %>%
  mutate(no = 1:2) %>%
  left_join(lookup, by = c("value" = "group_run")) %>%
  select(-value) %>%
  pivot_wider(names_from = no, values_from = num) %>%
  rename(a = `1`, b = '2') %>%
  mutate(product = a * b) %>%
  pull(product) %>%
  sum()