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
- What is this?: Here is a post with a large amount of details: https://programming.dev/post/6637268
- Where do I participate?: https://adventofcode.com/
- Is there a leaderboard for the community?: We have a programming.dev leaderboard with the info on how to join in this post: https://programming.dev/post/6631465
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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())