79 lines
2.1 KiB
Python
79 lines
2.1 KiB
Python
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#!/usr/bin/env python
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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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def neighbours(self) -> Iterator["Point"]:
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for dx, dy in (
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(-1, 0),
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(1, 0),
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(0, -1),
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(0, 1),
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):
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yield Point(self.x + dx, self.y + dy)
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DIMS = Point(70, 70)
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def solve(input: str) -> str:
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def parse(input: list[str]) -> list[Point]:
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return [Point(*map(int, line.split(","))) for line in input]
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def djikstra(start: Point, end: Point, blocks: set[Point]) -> int | None:
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# Priority queue of (distance, point)
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queue = [(0, start)]
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seen: set[Point] = set()
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while len(queue) > 0:
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cost, p = heapq.heappop(queue)
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if p == end:
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return cost
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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 p.neighbours():
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if p in blocks:
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continue
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if not 0 <= p.x <= DIMS.x:
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continue
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if not 0 <= p.y <= DIMS.y:
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continue
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heapq.heappush(queue, (cost + 1, n))
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return None
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def bisect_cutoff(start: Point, end: Point, blocks: list[Point]) -> Point:
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# Cutting off the path is monotonic: once cut-off, it's never uncut
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low, high = 0, len(blocks)
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while low < high:
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mid = low + (high - low) // 2
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if djikstra(start, end, set(blocks[: mid + 1])) is None:
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high = mid
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else:
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low = mid + 1
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return blocks[low]
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coords = parse(input.splitlines())
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byte = bisect_cutoff(Point(0, 0), DIMS, coords)
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return f"{byte.x},{byte.y}"
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def main() -> None:
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input = sys.stdin.read()
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print(solve(input))
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if __name__ == "__main__":
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main()
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