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