"""
    该代码用于更新日 K 数据
"""
from futu import *
from pymysql import Error
from MySQLHelper import MySQLHelper  # MySQLHelper类保存为单独文件
from datetime import datetime
import logging
from typing import Optional, List, Dict, Union, Tuple
import time
import akshare as ak

def get_market_data(market: Market) -> List[str]:
    """
    从Futu API获取指定市场的股票代码列表
    
    Args:
        market (Market): 市场枚举值，如 Market.SH, Market.SZ
        
    Returns:
        List[str]: 股票代码列表
    """
    quote_ctx = OpenQuoteContext(host='127.0.0.1', port=11111)
    try:
        ret, data = quote_ctx.get_stock_basicinfo(market, SecurityType.STOCK)
        if ret == RET_OK:
            # 提取code列并转换为列表
            codes = data['code'].astype(str).tolist()
            logging.info(f"获取到 {market} 市场 {len(codes)} 个股票代码")
            return codes
        else:
            logging.error(f"获取股票代码失败: {data}")
            return []
    except Exception as e:
        logging.error(f"获取股票代码时发生异常: {str(e)}")
        return []
    finally:
        quote_ctx.close()

def preprocess_quote_data(df: pd.DataFrame) -> List[Dict]:
    """
    预处理行情数据，转换为适合数据库存储的格式
    
    Args:
        df (pd.DataFrame): 原始行情数据DataFrame
        
    Returns:
        List[Dict]: 处理后的数据列表
    """
    processed_data = []
    for _, row in df.iterrows():
        try:
            # 提取市场标识
            # market = row['code'].split('.')[0] if '.' in row['code'] else 'UNKNOWN'
            
            # 转换时间格式
            # trade_time = datetime.strptime(row['date'], '%Y-%m-%d %H:%M:%S')
            
            item = {
                'trade_date': str(row['date']),
                'open_price': float(row['open']),
                'close_price': float(row['close']),
                'high_price': float(row['high']),
                'low_price': float(row['low']),
                'volume': int(row['volume']) if pd.notna(row['volume']) else None,
            }
            processed_data.append(item)
        except Exception as e:
            logging.warning(f"处理行情数据时跳过异常行 {row.get('code', '未知')}: {str(e)}")
            continue
            
    return processed_data

def save_quotes_to_db(db_config: dict, quote_data: pd.DataFrame, table_name: str = 'stock_quotes') -> bool:
    """
    将行情数据保存到数据库
    
    Args:
        db_config (dict): 数据库配置
        quote_data (pd.DataFrame): 行情数据DataFrame
        table_name (str): 目标表名(默认为'stock_quotes')
        
    Returns:
        bool: 是否成功保存
    """
    # 预处理数据
    processed_data = preprocess_quote_data(quote_data)
    if not processed_data:
        logging.error("没有有效数据需要保存")
        return False
    
    # 动态生成SQL插入语句
    insert_sql = f"""
    INSERT INTO {table_name} (
       trade_date, open_price, close_price, high_price, low_price, volume
    ) VALUES (
       %(trade_date)s, %(open_price)s, %(close_price)s, %(high_price)s, %(low_price)s, %(volume)s
    )
    ON DUPLICATE KEY UPDATE
        open_price = VALUES(open_price),
        close_price = VALUES(close_price),
        high_price = VALUES(high_price),
        low_price = VALUES(low_price),
        volume = VALUES(volume)
    """
    
    try:
        with MySQLHelper(**db_config) as db:
            # 检查表是否存在，不存在则创建
            if not db.table_exists(table_name):
                create_table_sql = f"""
                CREATE TABLE IF NOT EXISTS {table_name} (
                    id INT AUTO_INCREMENT PRIMARY KEY,
                    trade_date DATETIME NOT NULL COMMENT '交易日期时间',
                    open_price DECIMAL(10, 3) COMMENT '开盘价',
                    close_price DECIMAL(10, 3) COMMENT '收盘价',
                    high_price DECIMAL(10, 3) COMMENT '最高价',
                    low_price DECIMAL(10, 3) COMMENT '最低价',
                    volume BIGINT COMMENT '成交量(股)',
                    create_time TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
                    UNIQUE KEY idx_trade_date (trade_date)
                ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='股票行情数据表'
                """
                db.execute_update(create_table_sql)
                logging.info(f"创建了新表: {table_name}")
            
            affected_rows = db.execute_many(insert_sql, processed_data)
            logging.info(f"成功插入/更新 {affected_rows} 条行情记录到表 {table_name}")
            return True
    except Exception as e:
        logging.error(f"保存行情数据到表 {table_name} 失败: {str(e)}")
        return False

def read_missing_codes_basic(file_path='data\missing_tables_小航富途.txt'):
    """基础读取方法 - 按行读取所有内容"""
    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            lines = f.readlines()
        # 去除每行末尾的换行符，并过滤空行
        codes = [line.strip() for line in lines if line.strip()]
        return codes
    except FileNotFoundError:
        print(f"文件 {file_path} 不存在")
        return []
    except Exception as e:
        print(f"读取文件失败: {str(e)}")
        return []

def get_stock_codes() -> List[str]:
    """从conditionalselection表获取所有股票代码"""
    try:
        with MySQLHelper(**db_config) as db:
            sql = f"SELECT DISTINCT stock_code FROM conditionalselection"
            results = db.execute_query(sql)
            return [row['stock_code'] for row in results if row['stock_code']]
    except Exception as e:
        logging.error(f"获取股票代码失败: {str(e)}")
        return []
                        
if __name__ == "__main__":
    # 配置日志
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(levelname)s - %(message)s',
        handlers=[
            logging.FileHandler('Debug.log', encoding='utf-8'),  # 关键在这里
            logging.StreamHandler()
        ]
    )

    # 数据库配置
    db_config = {
        'host': 'localhost',
        'user': 'root',
        'password': 'bzskmysql',
        'database': 'klinedata_1d_hk_akshare'
    }


    # market_data = get_market_data(Market.HK)  # 获取香港市场数据,后面需要改成按照筛选来获取

    # # 小航富途
    # market_data_hang = read_missing_codes_basic()
    # 

    # market_data = list(set(market_data_all) - set(market_data_hang))

    nCount = 0    # 记录账号获取多少只股票的数据
    market_data_all = get_stock_codes() 
    for code in market_data_all:
        stock_hk_index_daily_sina_df = ak.stock_hk_index_daily_sina(symbol=code[3:])
        custom_table_name = 'hk_' + code[3:] # 自定义表名
        success = save_quotes_to_db(db_config, stock_hk_index_daily_sina_df, table_name=custom_table_name)
        time.sleep(5)