#!/usr/bin/env python import dataclasses import heapq import sys from collections.abc import Iterator from typing import NamedTuple class Point(NamedTuple): x: int y: int @dataclasses.dataclass class HeightMap: heights: list[list[int]] start: Point end: Point def reachable_neighbours(self, p: Point) -> Iterator[Point]: reachable_height = self.heights[p.x][p.y] + 1 for dx, dy in ((-1, 0), (1, 0), (0, -1), (0, 1)): x, y = p.x + dx, p.y + dy if x < 0 or x >= len(self.heights): continue if y < 0 or y >= len(self.heights[0]): continue if self.heights[x][y] > reachable_height: continue yield Point(x, y) def solve(input: list[str]) -> int: def to_height_map(input: list[str]) -> HeightMap: start, end = None, None heights = [[0 for _ in range(len(input[0]))] for _ in range(len(input))] for i, line in enumerate(input): for j, c in enumerate(line): height = ord(c) if c == "S": height = ord("a") start = Point(i, j) if c == "E": height = ord("z") end = Point(i, j) heights[i][j] = height - ord("a") assert start is not None # Sanity check assert end is not None # Sanity check return HeightMap(heights, start, end) def djikstra(map: HeightMap) -> int: # Priority queue of (distance, point) queue = [(0, map.start)] seen: set[Point] = set() while len(queue) > 0: dist, p = heapq.heappop(queue) if p == map.end: return dist # We must have seen p with a smaller distance before if p in seen: continue # First time encountering p, must be the smallest distance to it seen.add(p) # Add all neighbours to be visited for n in map.reachable_neighbours(p): heapq.heappush(queue, (dist + 1, n)) assert False # Sanity check map = to_height_map(input) return djikstra(map) def main() -> None: input = sys.stdin.read().splitlines() print(solve(input)) if __name__ == "__main__": main()