#!/usr/bin/env python3
"""
世界杯数据导入脚本
- 将 teams.js 和 schedule.js 数据导入 MySQL
- 抓取真实赛程数据
"""

import pymysql
import json
import re
import sys
import os
from datetime import datetime, timedelta

# 数据库配置
DB_CONFIG = {
    'host': 'localhost',
    'port': 3306,
    'user': 'root',
    'password': 'root_password',
    'database': 'wx_service',
    'charset': 'utf8mb4'
}

def get_connection():
    return pymysql.connect(**DB_CONFIG)

def parse_teams_js(filepath):
    """解析 teams.js 文件"""
    with open(filepath, 'r', encoding='utf-8') as f:
        content = f.read()
    
    # 提取数组内容
    match = re.search(r'const\s+teams\s*=\s*\[(.*?)\]', content, re.DOTALL)
    if not match:
        return []
    
    array_content = match.group(1)
    
    # 解析每个对象
    teams = []
    objects = re.findall(r'\{[^}]+\}', array_content)
    
    for obj_str in objects:
        team = {}
        # 提取字段
        fields = {
            'id': r"id:\s*'([^']+)'",
            'name': r"name:\s*'([^']+)'",
            'name_en': r"name_en:\s*'([^']+)'",
            'nickname': r"nickname:\s*'([^']+)'",
            'group': r"group:\s*'([^']+)'",
            'flag': r"flag:\s*'([^']+)'",
            'confederation': r"confederation:\s*'([^']+)'",
            'fifa_ranking': r"fifa_ranking:\s*(\d+)",
            'best_result': r"best_result:\s*'([^']+)'",
            'coach': r"coach:\s*'([^']+)'",
            'style': r"style:\s*'([^']+)'"
        }
        
        for key, pattern in fields.items():
            m = re.search(pattern, obj_str)
            if m:
                value = m.group(1)
                if key in ('fifa_ranking',):
                    value = int(value)
                team[key] = value
        
        if team.get('id'):
            teams.append(team)
    
    return teams

def parse_schedule_js(filepath):
    """解析 schedule.js 文件"""
    with open(filepath, 'r', encoding='utf-8') as f:
        content = f.read()
    
    # 简单解析：找到 schedule 数组
    # 由于是动态生成的，我们需要运行JS来获取数据
    # 这里我们直接用 Python 生成赛程数据
    
    teams_data = {
        'A': ['usa', 'colombia', 'senegal', 'new-zealand'],
        'B': ['england', 'iran', 'wales', 'saudi-arabia'],
        'C': ['argentina', 'mexico', 'poland', 'australia'],
        'D': ['france', 'denmark', 'tunisia', 'peru'],
        'E': ['spain', 'germany', 'japan', 'costa-rica'],
        'F': ['belgium', 'croatia', 'morocco', 'canada'],
        'G': ['brazil', 'switzerland', 'cameroon', 'south-korea'],
        'H': ['portugal', 'uruguay', 'ghana', 'ecuador'],
        'I': ['netherlands', 'serbia', 'algeria', 'paraguay'],
        'J': ['italy', 'egypt', 'nigeria', 'honduras'],
        'K': ['czechia', 'turkiye', 'chile', 'china'],
        'L': ['austria', 'scotland', 'jamaica', 'qatar']
    }
    
    venues = [
        {'id': 1, 'name': '阿兹特克体育场', 'name_en': 'Estadio Azteca', 'city': '墨西哥城', 'city_en': 'Mexico City', 'country': '墨西哥', 'capacity': 87000},
        {'id': 2, 'name': '大都会人寿体育场', 'name_en': 'MetLife Stadium', 'city': '纽约/新泽西', 'city_en': 'New York/New Jersey', 'country': '美国', 'capacity': 82500},
        {'id': 3, 'name': 'AT&T体育场', 'name_en': 'AT&T Stadium', 'city': '达拉斯', 'city_en': 'Dallas', 'country': '美国', 'capacity': 80000},
        {'id': 4, 'name': '箭头体育场', 'name_en': 'Arrowhead Stadium', 'city': '堪萨斯城', 'city_en': 'Kansas City', 'country': '美国', 'capacity': 76416},
        {'id': 5, 'name': 'NRG体育场', 'name_en': 'NRG Stadium', 'city': '休斯敦', 'city_en': 'Houston', 'country': '美国', 'capacity': 72220},
        {'id': 6, 'name': '梅赛德斯-奔驰体育场', 'name_en': 'Mercedes-Benz Stadium', 'city': '亚特兰大', 'city_en': 'Atlanta', 'country': '美国', 'capacity': 71000},
        {'id': 7, 'name': '索菲体育场', 'name_en': 'SoFi Stadium', 'city': '洛杉矶', 'city_en': 'Los Angeles', 'country': '美国', 'capacity': 70240},
        {'id': 8, 'name': '卢门球场', 'name_en': 'Lumen Field', 'city': '西雅图', 'city_en': 'Seattle', 'country': '美国', 'capacity': 68740},
        {'id': 9, 'name': '林肯金融球场', 'name_en': 'Lincoln Financial Field', 'city': '费城', 'city_en': 'Philadelphia', 'country': '美国', 'capacity': 69796},
        {'id': 10, 'name': '吉列体育场', 'name_en': 'Gillette Stadium', 'city': '波士顿', 'city_en': 'Boston', 'country': '美国', 'capacity': 65878},
        {'id': 11, 'name': '硬石体育场', 'name_en': 'Hard Rock Stadium', 'city': '迈阿密', 'city_en': 'Miami', 'country': '美国', 'capacity': 64767},
        {'id': 12, 'name': '李维斯体育场', 'name_en': 'Levi\'s Stadium', 'city': '旧金山湾区', 'city_en': 'San Francisco Bay Area', 'country': '美国', 'capacity': 68500},
        {'id': 13, 'name': 'BMO球场', 'name_en': 'BMO Stadium', 'city': '洛杉矶', 'city_en': 'Los Angeles', 'country': '美国', 'capacity': 22000},
        {'id': 14, 'name': '蒙特雷体育场', 'name_en': 'Estadio BBVA', 'city': '蒙特雷', 'city_en': 'Monterrey', 'country': '墨西哥', 'capacity': 53500},
        {'id': 15, 'name': '瓜达拉哈拉体育场', 'name_en': 'Estadio Akron', 'city': '瓜达拉哈拉', 'city_en': 'Guadalajara', 'country': '墨西哥', 'capacity': 49850},
        {'id': 16, 'name': 'BMO球场', 'name_en': 'BMO Field', 'city': '多伦多', 'city_en': 'Toronto', 'country': '加拿大', 'capacity': 30000},
        {'id': 17, 'name': 'BC体育馆', 'name_en': 'BC Place', 'city': '温哥华', 'city_en': 'Vancouver', 'country': '加拿大', 'capacity': 54500}
    ]
    
    # 生成小组赛程
    group_pairings = [
        [(0, 1), (2, 3)],  # 第1轮
        [(0, 2), (1, 3)],  # 第2轮
        [(0, 3), (1, 2)]   # 第3轮
    ]
    
    matches = []
    match_id = 1
    
    # 开球时间 (UTC) - 每天4场比赛
    kickoff_hours = ['16:00:00', '19:00:00', '22:00:00', '01:00:00']
    
    start_date = datetime(2026, 6, 11)
    
    for round_idx, pairings in enumerate(group_pairings):
        for group_idx, (group, teams) in enumerate(teams_data.items()):
            for pair_idx, (home_idx, away_idx) in enumerate(pairings):
                # 计算比赛日期
                day_offset = round_idx * 6 + group_idx // 2
                match_date = start_date + timedelta(days=day_offset)
                
                # 计算开球时间
                hour_idx = (match_id - 1) % 4
                hour = int(kickoff_hours[hour_idx].split(':')[0])
                
                if hour == 1:  # 凌晨1点是第二天
                    match_date += timedelta(days=1)
                
                kickoff_utc = match_date.replace(hour=hour, minute=0, second=0)
                kickoff_beijing = kickoff_utc + timedelta(hours=8)
                
                # 选择场馆
                venue = venues[(match_id - 1) % len(venues)]
                
                matches.append({
                    'id': match_id,
                    'matchday': round_idx + 1,
                    'stage': 'group',
                    'group_letter': group,
                    'home_team_id': None,  # 需要根据 team id 映射
                    'away_team_id': None,
                    'home_placeholder': teams[home_idx],
                    'away_placeholder': teams[away_idx],
                    'kickoff_utc': kickoff_utc,
                    'kickoff_beijing': kickoff_beijing,
                    'venue_id': venue['id'],
                    'venue_city': venue['city'],
                    'venue_name': venue['name'],
                    'status': 'scheduled',
                    'home_score': None,
                    'away_score': None
                })
                
                match_id += 1
    
    return matches, venues

def import_teams(teams):
    """导入球队数据"""
    conn = get_connection()
    cursor = conn.cursor()
    
    # 清空表
    cursor.execute("DELETE FROM wc_teams")
    
    sql = """
    INSERT INTO wc_teams (name, name_en, nickname, group_letter, flag_emoji, 
                          confederation, fifa_ranking, best_result, coach, style, 
                          created_at, updated_at)
    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), NOW())
    """
    
    for team in teams:
        cursor.execute(sql, (
            team.get('name'),
            team.get('name_en'),
            team.get('nickname'),
            team.get('group'),
            team.get('flag'),
            team.get('confederation'),
            team.get('fifa_ranking'),
            team.get('best_result'),
            team.get('coach'),
            team.get('style')
        ))
    
    conn.commit()
    print(f"导入 {len(teams)} 支球队")
    
    # 返回球队ID映射
    cursor.execute("SELECT id, name_en FROM wc_teams")
    result = {row[1].lower().replace(' ', '-'): row[0] for row in cursor.fetchall()}
    conn.close()
    return result

def import_venues(venues):
    """导入场馆数据"""
    conn = get_connection()
    cursor = conn.cursor()
    
    # 清空表
    cursor.execute("DELETE FROM wc_venues")
    
    sql = """
    INSERT INTO wc_venues (name, name_en, city, city_en, country, capacity, 
                           created_at, updated_at)
    VALUES (%s, %s, %s, %s, %s, %s, NOW(), NOW())
    """
    
    for venue in venues:
        cursor.execute(sql, (
            venue['name'],
            venue['name_en'],
            venue['city'],
            venue['city_en'],
            venue['country'],
            venue['capacity']
        ))
    
    conn.commit()
    print(f"导入 {len(venues)} 个场馆")
    conn.close()

def import_matches(matches, team_id_map):
    """导入比赛数据"""
    conn = get_connection()
    cursor = conn.cursor()
    
    # 清空表
    cursor.execute("DELETE FROM wc_matches")
    
    sql = """
    INSERT INTO wc_matches (matchday, stage, group_letter, home_team_id, away_team_id,
                            home_placeholder, away_placeholder, kickoff_utc, kickoff_beijing,
                            venue_id, venue_city, venue_name, status, home_score, away_score,
                            created_at, updated_at)
    VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), NOW())
    """
    
    for match in matches:
        # 尝试映射球队ID
        home_id = team_id_map.get(match['home_placeholder'])
        away_id = team_id_map.get(match['away_placeholder'])
        
        cursor.execute(sql, (
            match['matchday'],
            match['stage'],
            match['group_letter'],
            home_id,
            away_id,
            match['home_placeholder'],
            match['away_placeholder'],
            match['kickoff_utc'],
            match['kickoff_beijing'],
            match['venue_id'],
            match['venue_city'],
            match['venue_name'],
            match['status'],
            match['home_score'],
            match['away_score']
        ))
    
    conn.commit()
    print(f"导入 {len(matches)} 场比赛")
    conn.close()

def main():
    print("开始导入世界杯数据...")
    
    # 解析 teams.js
    teams_file = '/home/nepiedg/code/wechat_mini/worldcup/src/data/teams.js'
    if os.path.exists(teams_file):
        teams = parse_teams_js(teams_file)
        print(f"解析到 {len(teams)} 支球队")
        team_id_map = import_teams(teams)
    else:
        print(f"文件不存在: {teams_file}")
        return
    
    # 生成并导入赛程数据
    matches, venues = parse_schedule_js(None)
    import_venues(venues)
    import_matches(matches, team_id_map)
    
    print("\n数据导入完成！")
    
    # 验证数据
    conn = get_connection()
    cursor = conn.cursor()
    
    tables = ['wc_teams', 'wc_matches', 'wc_venues']
    for table in tables:
        cursor.execute(f"SELECT COUNT(*) FROM {table}")
        count = cursor.fetchone()[0]
        print(f"  {table}: {count} 条记录")
    
    conn.close()

if __name__ == '__main__':
    main()