80 lines
2 KiB
Python
Executable file
80 lines
2 KiB
Python
Executable file
#!/usr/bin/env python
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import functools
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import itertools
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import sys
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from typing import Iterable, Iterator, List, NamedTuple, Tuple, TypeVar
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T = TypeVar("T")
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def grouper(iterable: Iterable[T], n: int) -> Iterator[Tuple[T, ...]]:
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args = [iter(iterable)] * n
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return itertools.zip_longest(*args)
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def take(n: int, iterable: Iterable[T]) -> List[T]:
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return list(itertools.islice(iterable, n))
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class PlayerStats(NamedTuple):
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position: int
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score: int
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ROLL_TO_UNIVERSES = {
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3: 1,
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4: 3,
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5: 6,
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6: 7,
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7: 6,
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8: 3,
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9: 1,
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}
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WINNING_SCORE = 21
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def solve(input: List[str]) -> int:
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def parse() -> Tuple[int, int]:
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p1, p2 = input[0].split(" ")[-1], input[1].split(" ")[-1]
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return int(p1), int(p2)
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def do_turn(stats: PlayerStats, roll: int) -> PlayerStats:
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position, score = stats
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position = ((position - 1 + roll) % 10) + 1
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score += position
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return PlayerStats(position, score)
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@functools.cache
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def play_universes(p1: PlayerStats, p2: PlayerStats) -> Tuple[int, int]:
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p1_wins, p2_wins = 0, 0
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# Only 9 different outcomes from a 3d3 roll, with differing probabilities
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for roll, roll_probability in ROLL_TO_UNIVERSES.items():
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new_p1 = do_turn(p1, roll)
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if new_p1.score >= WINNING_SCORE:
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# Account for differing number of split universes when counting a win
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p1_wins += roll_probability
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continue
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# Exchange p1 and p2 roles, count their wins, and account for number of splits
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new_p2_wins, new_p1_wins = play_universes(p2, new_p1)
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p1_wins += new_p1_wins * roll_probability
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p2_wins += new_p2_wins * roll_probability
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return p1_wins, p2_wins
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p1, p2 = parse()
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p1_wins, p2_wins = play_universes(PlayerStats(p1, 0), PlayerStats(p2, 0))
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return max(p1_wins, p2_wins)
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def main() -> None:
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input = [line.strip() for line in sys.stdin.readlines()]
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print(solve(input))
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if __name__ == "__main__":
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main()
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