gistfile1.txt

from dataclasses import dataclass


@dataclass(unsafe_hash=True)
class Team:
    group: str
    rank: int
    name: str
    country: str


class LotterySimulator:
    def __init__(self, teams):
        self.teams = sorted(teams, key=lambda x: -x.rank)
        self.pairs = len(self.teams) // 2
        self.mappings = [[] for _ in range(self.pairs)]
        for i in range(self.pairs):
            team2 = self.teams[i]
            for j in range(self.pairs):
                team1 = self.teams[j + self.pairs]
                if team1.country != team2.country and team1.group != team2.group:
                    self.mappings[i].append(j)
        self.ans = [[0] * self.pairs for i in range(self.pairs)]
        self.cnts = 0

    def draw(self):
        tmp = []
        visited = [0] * self.pairs

        def dfs(x):
            if x >= self.pairs:
                self.cnts += 1
                for i, j in enumerate(tmp):
                    self.ans[i][j] += 1
                return
            for j in self.mappings[x]:
                if not visited[j]:
                    tmp.append(j)
                    visited[j] = 1
                    dfs(x + 1)
                    tmp.pop()
                    visited[j] = 0

            return

        dfs(0)
        return self.ans

if __name__ == "__main__":
    arr = [
        ('A', 1, '巴黎', '法甲'),
        ('A', 2, '皇马', '西甲'),
        ('B', 1, '拜仁', '德甲'),
        ('B', 2, '热刺', '英超'),
        ('C', 1, '曼城', '英超'),
        ('C', 2, '亚特兰大', '意甲'),
        ('D', 1, '尤文', '意甲'),
        ('D', 2, '马竞', '西甲'),
        ('E', 1, '利物浦', '英超'),
        ('E', 2, '那不勒斯', '意甲'),
        ('F', 1, '巴萨', '西甲'),
        ('F', 2, '多特', '德甲'),
        ('G', 1, '莱比锡', '德甲'),
        ('G', 2, '里昂', '法甲'),
        ('H', 1, '瓦伦西亚', '西甲'),
        ('H', 2, '切尔西', '英超')
    ]

    teams = [Team(*i) for i in arr]
    ls = LotterySimulator(teams)
    ans = ls.draw()
    rows = ls.teams[:ls.pairs]
    cols = ls.teams[ls.pairs:]

    import pandas as pd
    df = pd.DataFrame(ans, index=[i.name for i in rows], columns=[i.name for i in cols]) / ls.cnts
    print(df)