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Tic Tac Toe\nfrom __future__ import annotations\n\nimport random\nfrom functools import lru_cache\nfrom typing import List\n\n\nclass TicTacToeGame:\n __slots__ = [\"state\", \"search_count\"]\n\n def __init__(self) -> None:\n self.state = TicTacToeState()\n self.search_count = 0\n\n def play(self) -> None:\n while not self.state.is_settled:\n choice = self._nega_scout_strategy(self.state.copy())\n self.state.turn(choice)\n\n def reset(self):\n self.state = TicTacToeState()\n self.search_count = 0\n\n def _evaluate(self, state: TicTacToeState, depth: int) -> int:\n if state.is_win:\n return 10 - depth\n elif state.is_loss:\n return -10 + depth\n return 0\n\n # この探索関数がボトルネックなので、高速化したい\n # 変更点3: サイズを無制限に\n @lru_cache(maxsize=None)\n def _nega_scout_strategy(self, state: TicTacToeState, depth: int = 0, alpha: int = -(1 << 30),\n beta: int = 1 << 30) -> int:\n self.search_count += 1\n\n if state.is_settled:\n return self._evaluate(state, depth)\n\n best_hand = -1\n b = beta\n available_hands = state.available_hands\n random.shuffle(available_hands)\n\n for i, hand in enumerate(available_hands):\n child_state = state.copy()\n child_state.turn(hand)\n child_value = -self._nega_scout_strategy(child_state, depth + 1, -b, -alpha)\n if alpha < child_value < beta and i: # re-search\n child_value = -self._nega_scout_strategy(child_state, depth + 1, -beta, -alpha)\n if child_value > alpha: # update\n alpha = child_value\n best_hand = hand\n if alpha >= beta: # beta pruning\n return alpha\n b = alpha + 1 # set new null window\n\n if depth:\n return alpha # in nodes of search tree\n return best_hand # in root of search tree\n\n\nclass TicTacToeState:\n _winnable_conditions = \\\n {0b111000000, 0b000111000, 0b000000111, 0b100100100, 0b010010010, 0b001001001, 0b100010001, 0b001010100}\n\n __slots__ = [\"_player\", \"_opponent\"]\n\n def __init__(self, player: int = 0b000000000, opponent: int = 0b000000000) -> None:\n self._player = player\n self._opponent = opponent\n\n @staticmethod\n def _popcount(player: int) -> int:\n return bin(player).count(\"1\")\n\n @property\n def is_settled(self) -> bool:\n return self.is_win or self.is_loss or self.is_draw\n\n @property\n def is_draw(self) -> bool:\n return self.field == 0b111111111\n\n @property\n def is_win(self) -> bool:\n return any(self._player & condition == condition for condition in self._winnable_conditions)\n\n @property\n def is_loss(self) -> bool:\n return any(self._opponent & condition == condition for condition in self._winnable_conditions)\n\n @property\n def field(self) -> int:\n return self._player | self._opponent\n\n @property\n def available_hands(self) -> List[int]:\n return [i for i in range(9) if not (self.field & (1 << i))]\n\n def judge(self) -> None:\n if self._popcount(self._player) == self._popcount(self._opponent):\n player, opponent = \"Player\", \"Opponent\"\n else:\n player, opponent = \"Opponent\", \"Player\"\n\n if self.is_win:\n print(f\"{player} win\")\n elif self.is_loss:\n print(f\"{opponent} win\")\n else:\n print(f\"Draw\")\n\n def display(self) -> None:\n visible_field = []\n player_color, opponent_color = \"ox\" if self._popcount(self._player) == self._popcount(self._opponent) else \"xo\"\n\n for i in range(9):\n if self._player & (1 << i):\n visible_field.append(player_color)\n elif self._opponent & (1 << i):\n visible_field.append(opponent_color)\n else:\n visible_field.append(\".\")\n\n for row in zip(*[iter(visible_field)] * 3):\n print(*row, sep=\"|\")\n print()\n\n def turn(self, choice: int) -> None:\n self._player |= (1 << choice)\n self._player, self._opponent = self._opponent, self._player\n\n def copy(self) -> TicTacToeState:\n return TicTacToeState(self._player, self._opponent)\n\n\n@lru_cache(maxsize=None)\ndef dummy1(self):\n pass\n\n@lru_cache(maxsize=None)\ndef dummy2(state):\n pass\n \n \ndef main():\n \"\"\"\n 各局面での合法手はランダムな順番で探索するので、複数回実行して平均を取った。\n game.search_count は1ゲーム(9ターン)で探索関数が呼び出された回数を指す。\n lru_cacheを使えば過去のターンで探索済みのものはキャッシュを参照して省略されることを期待していた。\n \"\"\"\n # 変更点2: 試行回数を減らす\n game = TicTacToeGame()\n game.play()\n print(f\"{game.search_count=}\")\n # 変更点4: キャッシュの成績を見る\n print(game._nega_scout_strategy.cache_info())\n game.reset()\n\n\nif __name__ == \"__main__\":\n # 変更点1: 乱数列の固定\n random.seed(0)\n main()\n","codes",[],"stdin","compiler","cpython-3.8.0","createdAt",1583164697,"title","description","isPrivate","compilerInfo",{"_11":3387,"_13":3395,"_15":1312,"_17":1327,"_19":3396,"_22":25,"_24":23,"_26":3397,"_28":3398},"3.8.0",[1315],"python3 prog.py",[],"results",[3401,3405,3408,3411],{"_31":3402,"_3403":3404},"Control","data","Start",{"_31":3406,"_3403":3407},"StdOut","game.search_count=21881\nCacheInfo(hits=0, misses=21881, maxsize=None, currsize=21881)\n",{"_31":3409,"_3403":3410},"ExitCode","0",{"_31":3402,"_3403":3412},"Finish","hpplib",[3415,3430,3441,3450,3459,3468,3477,3486,3496,3505,3516,3527,3538,3549,3560,3571],{"_11":3416,"_3417":3418,"_3391":3419,"_3420":3421,"_3422":3423,"_3428":3429},"CLI11","repository","CLIUtils/CLI11","CLI11 is a command line parser for C++11 and beyond that provides a rich feature set with a simple and intuitive interface.","headerDescription","","wandbox",{"_3424":3425,"_3426":3427},"tagName","v2.5.0","publishedAt","2025-02-27T12:29:12Z","clangd",{"_3424":3425,"_3426":3427},{"_11":3431,"_3417":3432,"_3391":3433,"_3420":3434,"_3422":3435,"_3428":3438},"cxxopts","jarro2783/cxxopts","Lightweight C++ command line option parser","",{"_3424":3436,"_3426":3437},"v3.3.1","2025-05-26T08:12:04Z",{"_3424":3439,"_3426":3440},"v3.2.0","2024-02-15T05:32:43Z",{"_11":3442,"_3417":3443,"_3391":3444,"_3420":3445,"_3422":3446,"_3428":3449},"nanobench","martinus/nanobench","Simple, fast, accurate single-header microbenchmarking functionality for C++11/14/17/20","",{"_3424":3447,"_3426":3448},"v4.3.11","2023-02-16T19:06:26Z",{"_3424":3447,"_3426":3448},{"_11":3451,"_3417":3452,"_3391":3453,"_3420":3454,"_3422":3455,"_3428":3458},"toml11","ToruNiina/toml11","TOML for Modern C++","",{"_3424":3456,"_3426":3457},"v4.4.0","2025-02-15T16:20:52Z",{"_3424":3456,"_3426":3457},{"_11":3460,"_3417":3461,"_3391":3462,"_3420":3463,"_3422":3464,"_3428":3467},"toml++","marzer/tomlplusplus","Header-only TOML config file parser and serializer for C++17.","",{"_3424":3465,"_3426":3466},"v3.4.0","2023-10-13T13:45:17Z",{"_3424":3465,"_3426":3466},{"_11":3469,"_3417":3470,"_3391":3471,"_3420":3472,"_3422":3473,"_3428":3476},"rapidjson","Tencent/rapidjson","A fast JSON parser/generator for C++ with both SAX/DOM style API","",{"_3424":3474,"_3426":3475},"v1.1.0","2016-08-25T08:01:22Z",{"_3424":3474,"_3426":3475},{"_11":3478,"_3417":3479,"_3391":3480,"_3420":3481,"_3422":3482,"_3428":3485},"picojson","kazuho/picojson","a header-file-only, JSON parser serializer in C++","",{"_3424":3483,"_3426":3484},"v1.3.0","2015-02-25T04:12:53Z",{"_3424":3483,"_3426":3484},{"_11":3487,"_3417":3487,"_3391":3488,"_3420":3489,"_3422":3490,"_3428":3493},"nlohmann/json","JSON for Modern C++","",{"_3424":3491,"_3426":3492},"v3.12.0","2025-04-11T08:43:39Z",{"_3424":3494,"_3426":3495},"v3.11.3","2023-11-28T21:38:09Z",{"_11":3497,"_3417":3498,"_3391":3499,"_3420":3500,"_3422":3501,"_3428":3504},"csv-parser","vincentlaucsb/csv-parser","A high-performance, fully-featured CSV parser and serializer for modern C++.","",{"_3424":3502,"_3426":3503},"2.3.0","2024-06-15T20:23:18Z",{"_3424":3502,"_3426":3503},{"_11":3506,"_3417":3507,"_3391":3508,"_3420":3509,"_3422":3510,"_3428":3513},"rapidcsv","d99kris/rapidcsv","C++ CSV parser library","",{"_3424":3511,"_3426":3512},"v8.87","2025-05-17T05:37:53Z",{"_3424":3514,"_3426":3515},"v8.84","2024-09-28T05:31:16Z",{"_11":3517,"_3417":3518,"_3391":3519,"_3420":3520,"_3422":3521,"_3428":3524},"fmt","fmtlib/fmt","A modern formatting library","",{"_3424":3522,"_3426":3523},"11.2.0","2025-05-03T16:40:00Z",{"_3424":3525,"_3426":3526},"11.1.4","2025-02-26T18:33:33Z",{"_11":3528,"_3417":3529,"_3391":3530,"_3420":3531,"_3422":3532,"_3428":3535},"NumCpp","dpilger26/NumCpp","C++ implementation of the Python Numpy library","",{"_3424":3533,"_3426":3534},"Version_2.14.1","2025-05-05T03:42:56Z",{"_3424":3536,"_3426":3537},"Version_2.14.0","2025-02-09T04:16:30Z",{"_11":3539,"_3417":3540,"_3391":3541,"_3420":3542,"_3422":3543,"_3428":3546},"spdlog","gabime/spdlog","Fast C++ logging library.","",{"_3424":3544,"_3426":3545},"v1.15.3","2025-05-09T08:59:29Z",{"_3424":3547,"_3426":3548},"v1.15.1","2025-02-01T12:08:58Z",{"_11":3550,"_3417":3551,"_3391":3552,"_3420":3553,"_3422":3554,"_3428":3557},"expected-lite","martinmoene/expected-lite","expected lite - Expected objects in C++11 and later in a single-file header-only library","",{"_3424":3555,"_3426":3556},"v0.9.0","2025-06-24T10:27:34Z",{"_3424":3558,"_3426":3559},"v0.8.0","2024-06-05T21:24:45Z",{"_11":3561,"_3417":3562,"_3391":3563,"_3420":3564,"_3422":3565,"_3428":3568},"gsl-lite","gsl-lite/gsl-lite","ISO C++ Core Guidelines Library implementation for C++98, C++11 up","",{"_3424":3566,"_3426":3567},"v1.0.1","2025-05-19T21:18:08Z",{"_3424":3569,"_3426":3570},"v0.42.0","2024-11-01T20:24:11Z",{"_11":3572,"_3417":3573,"_3391":3574,"_3420":3575,"_3422":3576,"_3428":3579},"ut","boost-ext/ut","C++20 μ(micro)/Unit Testing framework","",{"_3424":3577,"_3426":3578},"v2.3.1","2025-04-02T13:02:52Z",{"_3424":3580,"_3426":3581},"v2.3.0","2025-02-04T11:58:39Z","env",{"_3584":3585,"_3586":3587,"_3588":3589,"_3590":3591,"_3592":3593,"_3594":3595,"_3596":3597,"_3598":3599,"_3600":3601},"KV_CACHE",{},"KV_SESSION",{},"R2_BUCKET",{},"WANDBOX_GITHUB_CLIENT_ID","f9d429d939d997e6b08e","WANDBOX_GITHUB_CLIENT_SECRET","d99b3d12225671cde514d9e2b3d5cc8356f4ed5f","WANDBOX_KV_COOKIE_SECRET","FaCnykHoYzqiXReGkgvmcYGvQdQ4yZUE","WANDBOX_R2_PREFIX","master/","WANDBOX_URL_PREFIX","https://api.wandbox.org","ASSETS",{},"root","actionData","errors"]