SqlAlchemy “Too many connections”
2019-06-12:真 有用的是这个:
https://blog.csdn.net/weiwangchao_/article/details/80185009
1、在使用 create_engine创建引擎时,如果默认不指定连接池设置的话,一般情况下,SQLAlchemy会使用一个 QueuePool绑定在新创建的引擎上。并附上合适的连接池参数。
2、在这种情况下,当你使用了session后就算显式地调用session.close(),也不能把连接关闭。连接会由QueuePool连接池进行管理并复用。
3、如果想禁用SQLAlchemy提供的数据库连接池,只需要在调用create_engine是指定连接池为NullPool,SQLAlchemy就会在执行session.close()后立刻断开数据库连接。当然,如果session对象被析构但是没有被调用session.close(),则数据库连接不会被断开,直到程序终止。
from sqlalchemy.pool import NullPool #连接数据库 def getEngine(): engine = create_engine('mysql://root:123456@127.0.0.1/baa?charset=utf8mb4', poolclass=NullPool, echo=False) #print(engine) return engine def getSession(): engine = getEngine() BaseMode.metadata.create_all(engine)## 数据库生成表 # Session = sessionmaker(bind=engine) # session = Session() DBSession = sessionmaker(bind=engine) session = DBSession() return session
File "C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\pymysql\connections.py", line 393, in check_error err.raise_mysql_exception(self._data) File "C:\Users\user\AppData\Local\Programs\Python\Python36\lib\site-packages\pymysql\err.py", line 107, in raise_mysql_exception raise errorclass(errno, errval) sqlalchemy.exc.OperationalError: (pymysql.err.OperationalError) (1040, 'Too many connections') (Background on this error at: http://sqlalche.me/e/e3q8) Process finished with exit code 1
1、pandas dataframe to_sql()
#连接数据库 def getEngine(): engine = create_engine('mysql://root:123456@127.0.0.1/databaseName?charset=utf8mb4',echo=False) #print(engine) return engine
def getSession(): engine = getEngine() BaseMode.metadata.create_all(engine) Session = sessionmaker(bind=engine) session = Session() return session
def get_stock_daily(ts_code, start_date,end_date,startTime): # print( ts_code + " " + str(start_date) + " " + str(end_date)) api = ts.pro_api(token) try: df = ts.pro_bar(pro_api=api, ts_code=ts_code, start_date=start_date, end_date=end_date) # 【获取数据】 if df is None: print("没有获取到数据") return None print("data count: " + str(len(df))) df['trade_date'] = pd.to_datetime(df['trade_date']) # 交易日期字符串转换成日期格式 conn = cheDbUtil.getEngine() try: df.to_sql('b_stock_daily', con=conn, if_exists='append', index=False) # replace/append/fail 【save】 except Exception as e: traceback.print_exc() print("get_stock_daily() in BaaBusiniessPro.py XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX") return None finally: conn.dispose() except Exception as e: sleepNeed = 60 print("Start to sleep " + str(sleepNeed) + ' 秒') print("当前耗时: " + str(round((time.time() - startTime), 2) / 60) + ' 分钟') time.sleep(sleepNeed) # 休眠 ? 秒
2、SqlAlchemy 操作 mysql
#获取日行情最后一条记录的日期 def getMaxTradeDateForStockDaily(ts_code): try: session = getSession() rows = session.query(func.max(StockDaily.trade_date)).filter(StockDaily.ts_code == ts_code).one() # print(str(len(rows))) # print(type(rows)) # print(str(rows)) if rows is not None and len(rows) == 1: return rows[0] return None except Exception as e: traceback.print_exc() print("getMaxTradeDateForStockDaily() XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX") return None finally: session.close()