2024 day 22.

src/holt59/aoc/2024/day18.py

@@ -1,7 +1,58 @@
 from typing import Any, Iterator
 
 from ..base import BaseSolver
+from ..tools import graphs
 
 
 class Solver(BaseSolver):
-    def solve(self, input: str) -> Iterator[Any]: ...
+    def print_grid(self, grid: list[tuple[int, int]], n_rows: int, n_cols: int):
+        values = set(grid)
+        if self.files:
+            self.files.create(
+                "graph.txt",
+                "\n".join(
+                    "".join(
+                        "#" if (row, col) in values else "." for col in range(n_cols)
+                    )
+                    for row in range(n_rows)
+                ).encode(),
+                text=True,
+            )
+        else:
+            for row in range(n_rows):
+                self.logger.info(
+                    "".join(
+                        "#" if (row, col) in values else "." for col in range(n_cols)
+                    )
+                )
+
+    def dijkstra(self, corrupted: list[tuple[int, int]], n_rows: int, n_cols: int):
+        return graphs.dijkstra(
+            (0, 0),
+            (n_rows - 1, n_cols - 1),
+            graphs.make_neighbors_grid_fn(n_rows, n_cols, set(corrupted)),
+        )
+
+    def solve(self, input: str) -> Iterator[Any]:
+        values = [
+            (int(p[0]), int(p[1])) for r in input.splitlines() if (p := r.split(","))
+        ]
+
+        _is_test = len(values) < 100
+
+        n_rows, n_cols, n_bytes_p1 = (7, 7, 12) if _is_test else (71, 71, 1024)
+
+        bytes_p1 = values[:n_bytes_p1]
+        self.print_grid(bytes_p1, n_rows, n_cols)
+
+        path_p1, cost_p1 = self.dijkstra(bytes_p1, n_rows, n_cols) or ((), -1)
+        yield cost_p1
+
+        path = path_p1
+        for b in range(n_bytes_p1, len(values)):
+            if values[b] not in path:
+                continue
+            path, _ = self.dijkstra(values[: b + 1], n_rows, n_cols) or (None, -1)
+            if path is None:
+                yield ",".join(map(str, values[b]))
+                break

src/holt59/aoc/2024/day19.py

@@ -1,7 +1,42 @@
+from functools import cache
 from typing import Any, Iterator
 
 from ..base import BaseSolver
 
 
+@cache
+def is_valid(design: str, towels: tuple[str, ...]) -> bool:
+    if not design:
+        return True
+
+    return any(
+        design.startswith(towel) and is_valid(design[len(towel) :], towels)
+        for towel in towels
+    )
+
+
+@cache
+def count_valid(design: str, towels: tuple[str, ...]) -> int:
+    if not design:
+        return 1
+
+    return sum(
+        design.startswith(towel) and count_valid(design[len(towel) :], towels)
+        for towel in towels
+    )
+
+
 class Solver(BaseSolver):
-    def solve(self, input: str) -> Iterator[Any]: ...
+    def solve(self, input: str) -> Iterator[Any]:
+        towels_s, designs_s = input.split("\n\n")
+
+        towels = tuple(s.strip() for s in towels_s.split(","))
+
+        designs = [
+            design
+            for design in self.progress.wrap(designs_s.splitlines())
+            if is_valid(design, towels)
+        ]
+
+        yield len(designs)
+        yield sum(count_valid(design, towels) for design in self.progress.wrap(designs))

src/holt59/aoc/2024/day20.py

@@ -1,7 +1,95 @@
-from typing import Any, Iterator
+import itertools
+from collections import Counter
+from typing import Any, Callable, Iterable, Iterator, Sequence, TypeAlias
 
 from ..base import BaseSolver
+from ..tools.graphs import dijkstra, make_neighbors_grid_fn
+
+Node: TypeAlias = tuple[int, int]
+
+
+def make_neighbors_fn(grid: list[str], cheat_length: int):
+    n_rows, n_cols = len(grid), len(grid[0])
+
+    def _fn(node: Node):
+        row, col = node
+        return (
+            ((row_n, col_n), abs(row_n - row) + abs(col_n - col))
+            for row_d in range(-cheat_length, cheat_length + 1)
+            for col_d in range(
+                -cheat_length + abs(row_d), cheat_length - abs(row_d) + 1
+            )
+            if 0 <= (row_n := row + row_d) < n_rows
+            and 0 <= (col_n := col + col_d) < n_cols
+            and grid[row_n][col_n] != "#"
+        )
+
+    return _fn
 
 
 class Solver(BaseSolver):
-    def solve(self, input: str) -> Iterator[Any]: ...
+    def find_cheats(
+        self,
+        path: Sequence[Node],
+        cost: float,
+        costs_to_target: dict[Node, float],
+        neighbors_fn: Callable[[Node], Iterable[tuple[Node, float]]],
+    ):
+        cheats: dict[tuple[tuple[int, int], tuple[int, int]], float] = {}
+
+        for i_node, node in enumerate(self.progress.wrap(path)):
+            for reach_node, reach_cost in neighbors_fn(node):
+                n_cost = (
+                    i_node + reach_cost + costs_to_target.get(reach_node, float("inf"))
+                )
+                if n_cost < cost:
+                    cheats[node, reach_node] = cost - n_cost
+
+        return cheats
+
+    def solve(self, input: str) -> Iterator[Any]:
+        grid = input.splitlines()
+        n_rows, n_cols = len(grid), len(grid[0])
+        start = next(
+            (i, j) for i in range(n_rows) for j in range(n_cols) if grid[i][j] == "S"
+        )
+        target = next(
+            (i, j) for i in range(n_rows) for j in range(n_cols) if grid[i][j] == "E"
+        )
+
+        reachable = dijkstra(
+            target,
+            None,
+            make_neighbors_grid_fn(
+                n_rows,
+                n_cols,
+                excluded=(
+                    (i, j)
+                    for i in range(n_rows)
+                    for j in range(n_cols)
+                    if grid[i][j] == "#"
+                ),
+            ),
+        )
+
+        # note: path is inverted here
+        path, cost = reachable[start]
+        costs_to_target = {k: c for k, (_, c) in reachable.items()}
+
+        self.logger.info(f"found past from start to target with cost {cost}")
+
+        for cheat_length in (2, 20):
+            cheats = self.find_cheats(
+                list(reversed(path)),
+                cost,
+                costs_to_target,
+                make_neighbors_fn(grid, cheat_length),
+            )
+
+            for saving, count in sorted(Counter(cheats.values()).items()):
+                self.logger.debug(
+                    f"There are {count} cheats that save {saving} picoseconds."
+                )
+
+            target_saving = 100 if len(grid) > 20 else 50
+            yield sum(saving >= target_saving for saving in cheats.values())

src/holt59/aoc/2024/day21.py

@@ -1,7 +1,121 @@
-from typing import Any, Iterator
+import heapq
+from dataclasses import dataclass
+from typing import Any, Iterator, Literal, Sequence, TypeAlias, cast
 
 from ..base import BaseSolver
 
+Action: TypeAlias = Literal[">", "<", "v", "^", "A"]
+
+NUM_PAD = ((7, 8, 9), (4, 5, 6), (1, 2, 3), (None, 0, "A"))
+MOV_PAD: tuple[tuple[Action | None, ...], ...] = ((None, "^", "A"), ("<", "v", ">"))
+
+
+@dataclass(frozen=True, order=True)
+class Node:
+    robot_1: tuple[int, int] = (0, 2)
+    robot_2: tuple[int, int] = (0, 2)
+    robot_3: tuple[int, int] = (3, 2)
+
+    code: str = ""
+
+
+def apply_action(
+    robot: tuple[int, int],
+    action: Action,
+    pad: tuple[tuple[int | str | None, ...], ...],
+):
+    d_row, d_col = {"^": (-1, 0), "v": (1, 0), ">": (0, 1), "<": (0, -1)}[action]
+    row, col = robot[0] + d_row, robot[1] + d_col
+
+    if 0 <= row < len(pad) and 0 <= col < len(pad[row]) and pad[row][col] is not None:
+        return (row, col)
+
+    return None
+
+
+def create_node(node: Node, action: Action) -> Node | None:
+    # main pad moves -> move first robot
+    if action != "A":
+        robot = apply_action(node.robot_1, action, MOV_PAD)
+        if robot is not None:
+            return Node(
+                robot_1=robot,
+                robot_2=node.robot_2,
+                robot_3=node.robot_3,
+                code=node.code,
+            )
+
+        return None
+
+    # activate pad 1 -> action on robot 1
+    robot_1_action = MOV_PAD[node.robot_1[0]][node.robot_1[1]]
+    assert robot_1_action is not None
+
+    if robot_1_action != "A":
+        robot2 = apply_action(node.robot_2, robot_1_action, MOV_PAD)
+        if robot2 is not None:
+            return Node(
+                robot_1=node.robot_1,
+                robot_2=robot2,
+                robot_3=node.robot_3,
+                code=node.code,
+            )
+        return None
+
+    # activate pad 2 -> action on robot 2
+    robot_2_action = MOV_PAD[node.robot_2[0]][node.robot_2[1]]
+    assert robot_2_action is not None
+
+    if robot_2_action != "A":
+        robot3 = apply_action(node.robot_3, robot_2_action, NUM_PAD)
+        if robot3 is not None:
+            return Node(
+                robot_1=node.robot_1,
+                robot_2=node.robot_2,
+                robot_3=robot3,
+                code=node.code,
+            )
+        return None
+
+    value = NUM_PAD[node.robot_3[0]][node.robot_3[1]]
+    assert value is not None
+    return Node(
+        robot_1=node.robot_1,
+        robot_2=node.robot_2,
+        robot_3=node.robot_3,
+        code=node.code + str(value),
+    )
+
 
 class Solver(BaseSolver):
-    def solve(self, input: str) -> Iterator[Any]: ...
+    def dijkstra_for_code(self, target: str):
+        queue: list[tuple[float, Node, tuple[str, ...]]] = [(0, Node(), ())]
+        preds: dict[Node, tuple[str, ...]] = {}
+
+        while queue:
+            dis, node, path = heapq.heappop(queue)
+
+            if not target.startswith(node.code):
+                continue
+
+            if node in preds:
+                continue
+
+            preds[node] = path
+
+            if node.code == target:
+                self.logger.info(f"found [{target}]: {''.join(path)} ({len(path)})")
+                return path
+
+            for action in cast(Sequence[Action], "A^v<>"):
+                node_2 = create_node(node, action)
+                if node_2:
+                    heapq.heappush(queue, (dis + 1, node_2, path + (action,)))
+
+        return None
+
+    def solve(self, input: str) -> Iterator[Any]:
+        yield sum(
+            len(self.dijkstra_for_code(code) or ()) * int(code[:-1], 10)
+            for code in input.splitlines()
+        )

src/holt59/aoc/2024/day22.py

@@ -3,5 +3,57 @@ from typing import Any, Iterator
 from ..base import BaseSolver
 
 
+def mix(secret: int, value: int) -> int:
+    return secret ^ value
+
+
+def prune(secret: int) -> int:
+    return secret % 16777216
+
+
+def next_number(secret: int) -> int:
+    # Calculate the result of multiplying the secret number by 64. Then, mix this
+    # result into the secret number. Finally, prune the secret number.
+    secret = prune(mix(secret, secret * 64))
+
+    # Calculate the result of dividing the secret number by 32. Round the result down
+    # to the nearest integer. Then, mix this result into the secret number. Finally,
+    # prune the secret number.
+    secret = prune(mix(secret, secret // 32))
+
+    # Calculate the result of multiplying the secret number by 2048. Then, mix this
+    # result into the secret number. Finally, prune the secret number.
+    secret = prune(mix(secret, secret * 2048))
+
+    return secret
+
+
 class Solver(BaseSolver):
-    def solve(self, input: str) -> Iterator[Any]: ...
+    def solve(self, input: str) -> Iterator[Any]:
+        starts = [int(r) for r in input.splitlines()]
+
+        ends: list[int] = []
+        prices: list[int] = [0 for _ in range(2**16)]
+
+        for secret in self.progress.wrap(starts):
+            checked: list[bool] = [False] * len(prices)
+            hashed: int = 0
+
+            for i in range(2000):
+                last = secret % 10
+                secret = next_number(secret)
+                next = secret % 10
+
+                hashed = ((hashed << 4) & 0xFFFF) | ((last - next) & 0xF)
+
+                if i >= 3 and not checked[hashed]:
+                    checked[hashed] = True
+                    prices[hashed] += next
+
+            ends.append(secret)
+
+        for start, end in zip(starts, ends, strict=True):
+            self.logger.info(f"{start}: {end}")
+
+        yield sum(ends)
+        yield max(prices)

src/holt59/aoc/inputs/holt59/2024/day19.txt

@@ -0,0 +1,402 @@
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+
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+#############################################################################################################################################

src/holt59/aoc/inputs/holt59/2024/day21.txt

@@ -0,0 +1,5 @@
+129A
+540A
+789A
+596A
+582A

src/holt59/aoc/inputs/tests/2024/day18.txt

@@ -0,0 +1,25 @@
+5,4
+4,2
+4,5
+3,0
+2,1
+6,3
+2,4
+1,5
+0,6
+3,3
+2,6
+5,1
+1,2
+5,5
+2,5
+6,5
+1,4
+0,4
+6,4
+1,1
+6,1
+1,0
+0,5
+1,6
+2,0

src/holt59/aoc/inputs/tests/2024/day19.txt

@@ -0,0 +1,10 @@
+r, wr, b, g, bwu, rb, gb, br
+
+brwrr
+bggr
+gbbr
+rrbgbr
+ubwu
+bwurrg
+brgr
+bbrgwb

src/holt59/aoc/inputs/tests/2024/day20.txt

@@ -0,0 +1,15 @@
+###############
+#...#...#.....#
+#.#.#.#.#.###.#
+#S#...#.#.#...#
+#######.#.#.###
+#######.#.#...#
+#######.#.###.#
+###..E#...#...#
+###.#######.###
+#...###...#...#
+#.#####.#.###.#
+#.#...#.#.#...#
+#.#.#.#.#.#.###
+#...#...#...###
+###############

src/holt59/aoc/inputs/tests/2024/day21.txt

@@ -0,0 +1,5 @@
+029A
+980A
+179A
+456A
+379A

src/holt59/aoc/inputs/tests/2024/day22.txt

@@ -0,0 +1,4 @@
+1
+10
+100
+2024

src/holt59/aoc/inputs/tests/2024/day22_p2.txt

@@ -0,0 +1,4 @@
+1
+2
+3
+2024

src/holt59/aoc/tools/graphs.py

@@ -0,0 +1,118 @@
+import heapq
+from typing import Callable, Iterable, TypeVar, overload
+
+_Node = TypeVar("_Node")
+
+
+def make_neighbors_grid_fn(
+    rows: int | Iterable[int],
+    cols: int | Iterable[int],
+    excluded: Iterable[tuple[int, int]] = set(),
+    diagonals: bool = False,
+):
+    """
+    Create a neighbors function suitable for graph function for a simple grid.
+
+    Args:
+        rows: Rows of the grid. If an int is specified, the rows are assumed to be
+            numbered from 0 to rows - 1, otherwise the iterable should contain the list
+            of valid rows.
+        cols: Columns of the grid. If an int is specified, the columns are assumed to be
+            numbered from 0 to cols - 1, otherwise the iterable should contain the list
+            of valid columns.
+        excluded: Cells of the grid that cannot be used as valid nodes for the graph.
+        diagonals: If True, neighbors will include diagonal cells, otherwise, only
+            horizontal and vertical neighbors will be included.
+
+    """
+    ds = ((-1, 0), (0, 1), (1, 0), (0, -1))
+    if diagonals:
+        ds = ds + ((-1, -1), (-1, 1), (1, -1), (1, 1))
+
+    if isinstance(rows, int):
+        rows = range(rows)
+    elif not isinstance(rows, range):
+        rows = set(rows)
+
+    if isinstance(cols, int):
+        cols = range(cols)
+    elif not isinstance(cols, range):
+        cols = set(cols)
+
+    excluded = set(excluded)
+
+    def _fn(node: tuple[int, int]):
+        return (
+            ((row_n, col_n), 1)
+            for dr, dc in ds
+            if (row_n := node[0] + dr) in rows
+            and (col_n := node[1] + dc) in cols
+            and (row_n, col_n) not in excluded
+        )
+
+    return _fn
+
+
+@overload
+def dijkstra(
+    start: _Node,
+    target: None,
+    neighbors: Callable[[_Node], Iterable[tuple[_Node, float]]],
+) -> dict[_Node, tuple[tuple[_Node, ...], float]]: ...
+
+
+@overload
+def dijkstra(
+    start: _Node,
+    target: _Node,
+    neighbors: Callable[[_Node], Iterable[tuple[_Node, float]]],
+) -> tuple[tuple[_Node, ...], float] | None: ...
+
+
+def dijkstra(
+    start: _Node,
+    target: _Node | None,
+    neighbors: Callable[[_Node], Iterable[tuple[_Node, float]]],
+) -> (
+    dict[_Node, tuple[tuple[_Node, ...], float]]
+    | tuple[tuple[_Node, ...], float]
+    | None
+):
+    """
+    Solve shortest-path problem using simple Dijkstra algorithm from start to target,
+    using the given neighbors function.
+
+    Args:
+        start: Starting node of the path.
+        target: Target node for the path.
+        neighbors: Function that should return, for a given node, the list of
+            its neighbors with the cost to go from the node to the neighbor.
+
+    Returns:
+        One of the shortest-path from start to target with its associated cost, if one
+        is found, otherwise None.
+    """
+    queue: list[tuple[float, _Node, tuple[_Node, ...]]] = [(0, start, (start,))]
+    preds: dict[_Node, tuple[tuple[_Node, ...], float]] = {}
+
+    while queue:
+        dis, node, path = heapq.heappop(queue)
+
+        if node in preds:
+            continue
+
+        preds[node] = (path, dis)
+
+        if node == target:
+            break
+
+        for neighbor, cost in neighbors(node):
+            if neighbor in preds:
+                continue
+
+            heapq.heappush(queue, (dis + cost, neighbor, path + (neighbor,)))
+
+    if target is None:
+        return preds
+
+    return preds.get(target, None)