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@ -1,121 +1,85 @@
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import heapq
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import itertools
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from dataclasses import dataclass
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from functools import cache
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from typing import Any, Iterator, Literal, Sequence, TypeAlias, cast
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from typing import Any, Iterator, Literal
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from ..base import BaseSolver
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from ..base import BaseSolver
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Action: TypeAlias = Literal[">", "<", "v", "^", "A"]
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NUM_PAD_P = {
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v: (i, j)
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NUM_PAD = ((7, 8, 9), (4, 5, 6), (1, 2, 3), (None, 0, "A"))
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for i, r in enumerate(("789", "456", "123", " 0A"))
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MOV_PAD: tuple[tuple[Action | None, ...], ...] = ((None, "^", "A"), ("<", "v", ">"))
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for j, v in enumerate(r)
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if v.strip()
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}
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MOV_PAD_P = {
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v: (i, j)
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for i, r in enumerate((" ^A", "<v>"))
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for j, v in enumerate(r)
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if v.strip()
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}
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@dataclass(frozen=True, order=True)
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def path(start: tuple[int, int], end: tuple[int, int], pad: Literal["num", "mov"]):
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class Node:
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# a move in the grid is composed of at most two straight line: up/down and
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robot_1: tuple[int, int] = (0, 2)
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# left/right, since doing some kind of diagonal moves would create long path for
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robot_2: tuple[int, int] = (0, 2)
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# the robot above (since this involves going back-and-forth to the letter 'A')
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robot_3: tuple[int, int] = (3, 2)
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#
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row_s, col_s = start
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row_e, col_e = end
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code: str = ""
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le, de, ue, re = (
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"<" * max(0, col_s - col_e),
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"v" * max(0, row_e - row_s),
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def apply_action(
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"^" * max(0, row_s - row_e),
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robot: tuple[int, int],
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">" * max(0, col_e - col_s),
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action: Action,
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pad: tuple[tuple[int | str | None, ...], ...],
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):
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d_row, d_col = {"^": (-1, 0), "v": (1, 0), ">": (0, 1), "<": (0, -1)}[action]
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row, col = robot[0] + d_row, robot[1] + d_col
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if 0 <= row < len(pad) and 0 <= col < len(pad[row]) and pad[row][col] is not None:
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return (row, col)
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return None
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def create_node(node: Node, action: Action) -> Node | None:
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# main pad moves -> move first robot
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if action != "A":
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robot = apply_action(node.robot_1, action, MOV_PAD)
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if robot is not None:
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return Node(
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robot_1=robot,
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robot_2=node.robot_2,
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robot_3=node.robot_3,
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code=node.code,
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)
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)
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return None
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# when the robot starts or ends on the row/column with the empty cell, there is
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# only one way to move
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#
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if pad == "num" and (row_s, col_e) == (3, 0):
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return ue + le
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elif pad == "num" and (col_s, row_e) == (0, 3):
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return re + de
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elif pad == "mov" and col_s == 0:
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return re + ue
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elif pad == "mov" and col_e == 0:
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return de + le
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# activate pad 1 -> action on robot 1
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# otherwise, we need to decide if we want to go up/down first, or left/right, and
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robot_1_action = MOV_PAD[node.robot_1[0]][node.robot_1[1]]
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# apparently this is the best way to do it...
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assert robot_1_action is not None
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return le + de + ue + re
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if robot_1_action != "A":
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robot2 = apply_action(node.robot_2, robot_1_action, MOV_PAD)
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@cache
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if robot2 is not None:
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def v_clicks(clicks: str, depth: int) -> int:
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return Node(
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if depth == 0:
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robot_1=node.robot_1,
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return len(clicks)
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robot_2=robot2,
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robot_3=node.robot_3,
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n_clicks = 0
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code=node.code,
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at = "A"
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for _, group in itertools.groupby(clicks):
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group = list(group)
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n_clicks += v_clicks(
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path(MOV_PAD_P[at], MOV_PAD_P[group[0]], "mov") + "A" * len(group),
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depth - 1,
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)
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)
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return None
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at = group[0]
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# activate pad 2 -> action on robot 2
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return n_clicks
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robot_2_action = MOV_PAD[node.robot_2[0]][node.robot_2[1]]
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assert robot_2_action is not None
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if robot_2_action != "A":
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robot3 = apply_action(node.robot_3, robot_2_action, NUM_PAD)
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if robot3 is not None:
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return Node(
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robot_1=node.robot_1,
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robot_2=node.robot_2,
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robot_3=robot3,
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code=node.code,
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)
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return None
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value = NUM_PAD[node.robot_3[0]][node.robot_3[1]]
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def path_length(code: str, depth: int):
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assert value is not None
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return sum(
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return Node(
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v_clicks(path(NUM_PAD_P[start], NUM_PAD_P[end], "num") + "A", depth)
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robot_1=node.robot_1,
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for start, end in zip("A" + code[:-1], code, strict=True)
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robot_2=node.robot_2,
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robot_3=node.robot_3,
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code=node.code + str(value),
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)
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)
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class Solver(BaseSolver):
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class Solver(BaseSolver):
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def dijkstra_for_code(self, target: str):
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queue: list[tuple[float, Node, tuple[str, ...]]] = [(0, Node(), ())]
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preds: dict[Node, tuple[str, ...]] = {}
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while queue:
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dis, node, path = heapq.heappop(queue)
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if not target.startswith(node.code):
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continue
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if node in preds:
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continue
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preds[node] = path
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if node.code == target:
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self.logger.info(f"found [{target}]: {''.join(path)} ({len(path)})")
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return path
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for action in cast(Sequence[Action], "A^v<>"):
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node_2 = create_node(node, action)
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if node_2:
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heapq.heappush(queue, (dis + 1, node_2, path + (action,)))
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return None
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def solve(self, input: str) -> Iterator[Any]:
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def solve(self, input: str) -> Iterator[Any]:
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yield sum(
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yield sum(
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len(self.dijkstra_for_code(code) or ()) * int(code[:-1], 10)
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path_length(code, 2) * int(code[:-1], 10) for code in input.splitlines()
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for code in input.splitlines()
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)
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yield sum(
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path_length(code, 25) * int(code[:-1], 10) for code in input.splitlines()
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)
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)
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