import logging
from core.biz.quant_trader import QuantTrader
from core.biz.strategy import QuantStrategy

from config import MYSQL_CONFIG
from sqlalchemy import create_engine, exc, text
import pandas as pd

logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s: %(message)s')

def main() -> None:
    """主函数"""
    logging.info("=== 比特币量化交易系统 ===")
    # 导入配置
    try:
        from config import API_KEY, SECRET_KEY, PASSPHRASE, SANDBOX, TRADING_CONFIG, TIME_CONFIG
    except ImportError:
        logging.error("找不到config.py文件，请确保配置文件存在")
        return
    # 检查是否配置了API密钥
    if API_KEY == "your_api_key_here":
        logging.error("请先在config.py中配置你的OKX API密钥！\n1. 登录OKX官网\n2. 进入API管理页面\n3. 创建API Key、Secret Key和Passphrase\n4. 将密钥填入config.py文件中的相应位置")
        return
    # 创建交易器实例
    # sandbox = TRADING_CONFIG.get("sandbox", True)
    symbol = TRADING_CONFIG.get("symbol", "BTC-USDT")
    position_size = TRADING_CONFIG.get("position_size", 0.001)
    trader = QuantTrader(
        API_KEY, SECRET_KEY, PASSPHRASE, 
        sandbox=SANDBOX,
        symbol=symbol,
        position_size=position_size
    )
    strategy = QuantStrategy(
        API_KEY, SECRET_KEY, PASSPHRASE, 
        sandbox=SANDBOX,
        symbol=symbol,
        position_size=position_size
    )
    # 显示菜单
    while True:
        logging.info("\n请选择操作:\n1. 查看账户余额\n2. 查看当前价格\n3. 执行移动平均线策略\n4. 执行RSI策略\n5. 执行网格交易策略\n6. 运行策略循环\n7. 买入测试\n8. 卖出测试\n9. 获取最小交易量\n0. 退出")
        choice = input("请输入选择 (0-9): ").strip()
        if choice == '0':
            logging.info("退出程序")
            break
        elif choice == '1':
            trader.get_account_balance()
        elif choice == '2':
            trader.get_current_price()
        elif choice == '3':
            sma_short_period = TRADING_CONFIG.get("sma_short_period", 5)
            sma_long_period = TRADING_CONFIG.get("sma_long_period", 20)
            strategy.simple_moving_average_strategy(sma_short_period, sma_long_period)
        elif choice == '4':
            period = TRADING_CONFIG.get("rsi_period", 14)
            rsi_oversold = TRADING_CONFIG.get("rsi_oversold", 30)
            rsi_overbought = TRADING_CONFIG.get("rsi_overbought", 70)
            strategy.rsi_strategy(period, rsi_oversold, rsi_overbought)
        elif choice == '5':
            grid_levels = TRADING_CONFIG.get("grid_levels", 5)
            grid_range = TRADING_CONFIG.get("grid_range", 0.02)
            strategy.grid_trading_strategy(grid_levels, grid_range)
        elif choice == '6':
            strategy_name = input("选择策略 (sma/rsi/grid): ").strip()
            interval = TIME_CONFIG.get("strategy_interval", 30)
            strategy.run_strategy_loop(strategy_name, interval, TRADING_CONFIG)
        elif choice == '7':
            defalt_position_size = 0.01
            input_size = input("请输入买入数量: ")
            if input_size:
                try:
                    position_size = float(input_size)
                    logging.info(f"买入{position_size}BTC")
                    trader.place_market_order('buy', position_size)
                except ValueError:
                    logging.warning(f"输入无效，默认买入{defalt_position_size}BTC")
                    trader.place_market_order('buy', defalt_position_size)
            else:
                logging.info(f"默认买入{defalt_position_size}BTC")
                trader.place_market_order('buy', defalt_position_size)
        elif choice == '8':
            defalt_position_size = 0.01
            input_size = input("请输入卖出数量: ")
            if input_size:
                try:
                    position_size = float(input_size)
                    logging.info(f"卖出{position_size}BTC")
                    trader.place_market_order('sell', position_size)
                except ValueError:
                    logging.warning(f"输入无效，默认卖出{defalt_position_size}BTC")
                    trader.place_market_order('sell', defalt_position_size)
            else:
                logging.info(f"默认卖出{defalt_position_size}BTC")
                trader.place_market_order('sell', defalt_position_size)
        elif choice == '9':
            trader.get_minimun_order_size()
        else:
            logging.warning("无效选择，请重新输入")


def test_query():
    mysql_user = MYSQL_CONFIG.get("user", "xch")
    mysql_password = MYSQL_CONFIG.get("password", "")
    if not mysql_password:
        raise ValueError("MySQL password is not set")
    mysql_host = MYSQL_CONFIG.get("host", "localhost")
    mysql_port = MYSQL_CONFIG.get("port", 3306)
    mysql_database = MYSQL_CONFIG.get("database", "okx")
    db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
    db_engine = create_engine(
                db_url,
                pool_size=25,  # 连接池大小
                max_overflow=10,  # 允许的最大溢出连接
                pool_timeout=30,  # 连接超时时间（秒）
                pool_recycle=60,  # 连接回收时间（秒），避免长时间闲置
            )
    sql = "SELECT symbol, min(date_time), max(date_time) FROM okx.crypto_binance_data where bar='5m' group by symbol;"
    condition_dict = {}
    return_multi = True
    try:
        result = query_data(db_engine, sql, condition_dict, return_multi)
        if result is not None and len(result) > 0:
            data = pd.DataFrame(result)
            data.columns = ["symbol", "min_date_time", "max_date_time"]
            print(data)
            # output to excel
            data.to_excel("./data/binance/crypto_binance_data_5m.xlsx", index=False)
    except Exception as e:
        print(f"查询数据出错: {e}")
        return None

def transform_data_type(data: dict):
    """
    遍历字典，将所有Decimal类型的值转换为float类型
    """
    from decimal import Decimal
    for key, value in data.items():
        if isinstance(value, Decimal):
            data[key] = float(value)
    return data


def query_data(db_engine, sql: str, condition_dict: dict, return_multi: bool = True):
    """
    查询数据
    :param sql: 查询SQL
    :param db_url: 数据库连接URL
    """
    try:
        with db_engine.connect() as conn:
            result = conn.execute(text(sql), condition_dict)
            if return_multi:
                result = result.fetchall()
                if result:
                    result_list = [
                        transform_data_type(dict(row._mapping)) for row in result
                    ]
                    return result_list
                else:
                    return None
            else:
                result = result.fetchone()
                if result:
                    result_dict = transform_data_type(dict(result._mapping))
                    return result_dict
                else:
                    return None
    except Exception as e:
        print(f"查询数据出错: {e}")
        return None

if __name__ == "__main__":
    # main()
    test_query()