Day 8: Haunted Wasteland

Megathread guidelines

  • Keep top level comments as only solutions, if you want to say something other than a solution put it in a new post. (replies to comments can be whatever)
  • Code block support is not fully rolled out yet but likely will be in the middle of the event. Try to share solutions as both code blocks and using something such as https://topaz.github.io/paste/ , pastebin, or github (code blocks to future proof it for when 0.19 comes out and since code blocks currently function in some apps and some instances as well if they are running a 0.19 beta)

FAQ

  • @[email protected]
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    3 months ago

    Python

    import itertools
    import math
    import re
    
    from .solver import Solver
    
    class Day08(Solver):
    
      def __init__(self):
        super().__init__(8)
        self.instructions: str = ''
        self.nodes: dict[str, tuple[str, str]] = {}
    
      def presolve(self, input: str):
        lines = input.rstrip().split('\n')
        self.instructions = lines[0]
        for line in lines[2:]:
          g = re.fullmatch(r'(\w+) = \((\w+), (\w+)\)', line)
          assert g, f"line {line} doesn't match expected format"
          target, left, right = g.groups()
          self.nodes[target] = (left, right)
    
      def solve_first_star(self) -> int:
        instructions = itertools.cycle(self.instructions)
        cur = 'AAA'
        counter = 0
        while cur != 'ZZZ':
          instruction = next(instructions)
          if instruction == 'L':
            cur = self.nodes[cur][0]
          elif instruction == 'R':
            cur = self.nodes[cur][1]
          else:
            raise RuntimeError(f'Unexpected instruction: {instruction}')
          counter += 1
        return counter
    
      def solve_second_star(self) -> int:
        start_nodes: list[str] = [node for node in self.nodes if node.endswith('A')]
        end_nodes: set[str] = set(node for node in self.nodes if node.endswith('Z'))
        loop_offsets: dict[str, int] = {}
        loop_sizes: dict[str, int] = {}
        destination_offset_in_loops: dict[str, list[int]] = {}
        for node in start_nodes:
          cur = node
          path: list[tuple[int, str]] = [(0, cur)]
          for instruction_offset, instruction in itertools.cycle(enumerate(self.instructions)):
            next_node = self.nodes[cur][0] if instruction == 'L' else self.nodes[cur][1]
            next_state = ((instruction_offset + 1) % len(self.instructions), next_node)
            if next_state in path:
              loop_offsets[node] = path.index(next_state)
              loop_sizes[node] = len(path) - loop_offsets[node]
              destination_offset_in_loops[node] = [i for i, [_, n] in enumerate(path) if n in end_nodes]
              break
            path.append(next_state)
            cur = next_node
        return math.lcm(*loop_sizes.values())