import pandas as pd from sqlalchemy import create_engine, exc, text import logging def save_market_data_to_mysql(df: pd.DataFrame, db_url: str): """ 将K线行情数据保存到MySQL的crypto_market_data表 :param df: K线数据DataFrame :param symbol: 交易对 :param bar: K线周期 :param db_url: 数据库连接URL """ if df is None or df.empty: logging.warning("DataFrame为空,无需写入数据库。") return # 按表字段顺序排列 columns = [ 'symbol', 'bar', 'timestamp', 'date_time', 'open', 'high', 'low', 'close', 'volume', 'volCcy', 'volCCyQuote' ] df = df[columns] # 建立数据库连接 try: engine = create_engine(db_url) try: df.to_sql( name='crypto_market_data', con=engine, if_exists='append', index=False, method='multi' ) logging.info("数据已成功写入数据库。") except Exception as e: logging.error(f'插入数据出错: {e}') with engine.begin() as conn: for _, row in df.iterrows(): try: sql = text(""" INSERT INTO crypto_market_data (symbol, bar, timestamp, date_time, open, high, low, close, volume, volCcy, volCCyQuote) VALUES (:symbol, :bar, :timestamp, :date_time, :open, :high, :low, :close, :volume, :volCcy, :volCCyQuote) ON DUPLICATE KEY UPDATE open=VALUES(open), high=VALUES(high), low=VALUES(low), close=VALUES(close), volume=VALUES(volume), volCcy=VALUES(volCcy), volCCyQuote=VALUES(volCCyQuote), date_time=VALUES(date_time) """) conn.execute(sql, row.to_dict()) except exc.IntegrityError as e: logging.error(f'唯一索引冲突: {e}') except Exception as e: logging.error(f'插入数据出错: {e}') logging.info("数据已成功写入数据库。") except Exception as e: logging.error(f'数据库连接或写入失败: {e}')