import itertools
import pandas as pd

class Generate_data_set:
    def __init__(self, length=9):
        self.length = length
        self.list = [i for i in range(length)]
        self.board = [0 for i in range(length)]
        self.templist = []
        self.list_f = []
        self.list_s = []
        self.list_d = []
        

    def search(self):
        for i in range(4, self.length):
            print('{}!'.format(i+1))
            for t in itertools.permutations(self.list, r=i+1):
                self.templist = list(t)
                for j in range(len(self.templist)):
                    k = self.templist[j]
                    if j % 2 == 0:
                        self.board[k] = 1
                    else:
                        self.board[k] = 2
                    if self.cheak_board():
                        if j == (len(self.templist)-1):
                            self.temp_recording_fs(j % 2)
                        else:
                            break
                    elif i+1 == 9 and j == (len(self.templist)-1):
                        self.temp_recording_d()
                self.board[:] = [0 for i in range(self.length)]
        self.writing_files()
    

    def cheak_board(self):
        win_cond = ((0,1,2),(3,4,5),(6,7,8),(0,3,6),(1,4,7),(2,5,8),(0,4,8),(2,4,6))
        for each in win_cond:
            if self.board[each[0]] == self.board[each[1]] == self.board[each[2]]:
                if self.board[each[0]] != 0:
                    return True
        return False
    

    def temp_recording_fs(self, turn):
        if turn == 0:
            self.list_f.append(self.templist)
        elif turn == 1:
            self.list_s.append(self.templist)
        

    def temp_recording_d(self):
        self.list_d.append(self.templist)
            

    def writing_files(self):
        df_f = pd.DataFrame(self.list_f)
        df_s = pd.DataFrame(self.list_s)
        df_d = pd.DataFrame(self.list_d)
        df_f.to_csv("dataset_f.csv", header=False, index=False, mode='w')
        df_s.to_csv("dataset_s.csv", header=False, index=False, mode='w')
        df_d.to_csv("dataset_d.csv", header=False, index=False, mode='w')

if __name__ == '__main__':
    dataset = Generate_data_set()
    dataset.search()