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2021/d21/ex1/ex1.py Executable file
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#!/usr/bin/env python
import itertools
import sys
from typing import Iterable, Iterator, List, NamedTuple, Tuple, TypeVar
T = TypeVar("T")
def grouper(iterable: Iterable[T], n: int) -> Iterator[Tuple[T, ...]]:
args = [iter(iterable)] * n
return itertools.zip_longest(*args)
def take(n: int, iterable: Iterable[T]) -> List[T]:
return list(itertools.islice(iterable, n))
class PlayerStats(NamedTuple):
position: int
score: int
class GameState(NamedTuple):
p1: PlayerStats
p2: PlayerStats
total_rolls: int
WINNING_SCORE = 1000
def solve(input: List[str]) -> int:
def parse() -> Tuple[int, int]:
p1, p2 = input[0].split(" ")[-1], input[1].split(" ")[-1]
return int(p1), int(p2)
def deterministic_die() -> Iterator[int]:
return itertools.cycle(range(1, 100 + 1))
def do_turn(stats: PlayerStats, rolls: Iterator[int]) -> PlayerStats:
position, score = stats
roll = sum(take(3, rolls))
position = ((position - 1 + roll) % 10) + 1
score += position
return PlayerStats(position, score)
def play_to_end(intial_state: GameState) -> GameState:
p1, p2, total_rolls = intial_state
die_rolls = deterministic_die()
while True:
p1 = do_turn(p1, die_rolls)
total_rolls += 3
if p1.score >= WINNING_SCORE:
break
p2 = do_turn(p2, die_rolls)
total_rolls += 3
if p2.score >= WINNING_SCORE:
break
return GameState(p1, p2, total_rolls)
position1, position2 = parse()
p1, p2, total_rolls = play_to_end(
GameState(PlayerStats(position1, 0), PlayerStats(position2, 0), 0)
)
# The loser *must* have the lowest score
return min(p1.score, p2.score) * total_rolls
def main() -> None:
input = [line.strip() for line in sys.stdin.readlines()]
print(solve(input))
if __name__ == "__main__":
main()

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2021/d21/ex1/input Normal file
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Player 1 starting position: 8
Player 2 starting position: 5

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2021/d21/ex2/ex2.py Executable file
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#!/usr/bin/env python
import functools
import itertools
import sys
from typing import Iterable, Iterator, List, NamedTuple, Tuple, TypeVar
T = TypeVar("T")
def grouper(iterable: Iterable[T], n: int) -> Iterator[Tuple[T, ...]]:
args = [iter(iterable)] * n
return itertools.zip_longest(*args)
def take(n: int, iterable: Iterable[T]) -> List[T]:
return list(itertools.islice(iterable, n))
class PlayerStats(NamedTuple):
position: int
score: int
ROLL_TO_UNIVERSES = {
3: 1,
4: 3,
5: 6,
6: 7,
7: 6,
8: 3,
9: 1,
}
WINNING_SCORE = 21
def solve(input: List[str]) -> int:
def parse() -> Tuple[int, int]:
p1, p2 = input[0].split(" ")[-1], input[1].split(" ")[-1]
return int(p1), int(p2)
def do_turn(stats: PlayerStats, roll: int) -> PlayerStats:
position, score = stats
position = ((position - 1 + roll) % 10) + 1
score += position
return PlayerStats(position, score)
@functools.cache
def play_universes(p1: PlayerStats, p2: PlayerStats) -> Tuple[int, int]:
p1_wins, p2_wins = 0, 0
# Only 9 different outcomes from a 3d3 roll, with differing probabilities
for roll, roll_probability in ROLL_TO_UNIVERSES.items():
new_p1 = do_turn(p1, roll)
if new_p1.score >= WINNING_SCORE:
# Account for differing number of split universes when counting a win
p1_wins += roll_probability
continue
# Exchange p1 and p2 roles, count their wins, and account for number of splits
new_p2_wins, new_p1_wins = play_universes(p2, new_p1)
p1_wins += new_p1_wins * roll_probability
p2_wins += new_p2_wins * roll_probability
return p1_wins, p2_wins
p1, p2 = parse()
p1_wins, p2_wins = play_universes(PlayerStats(p1, 0), PlayerStats(p2, 0))
return max(p1_wins, p2_wins)
def main() -> None:
input = [line.strip() for line in sys.stdin.readlines()]
print(solve(input))
if __name__ == "__main__":
main()

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2021/d21/ex2/input Normal file
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Player 1 starting position: 8
Player 2 starting position: 5