在 While 循环内刷新 Python 中的数据帧

Refreshing dataframe in Python inside a While loop

我有一个数据框,它从 SQL 获取数据并根据列的条件发送电子邮件。但是 SQL 中不存在这些列,我需要在创建数据框后创建它们。这里的问题是我有一个 while 循环,它每 10 秒检查一次列的状况。我注意到 while 循环在所有条件下都能完美地工作,但数据框不会从 SQL 刷新,因为它在 while 循环之外。如果我将数据框放在 while 循环中,last_email_sent 会被初始化,因为 None 受到影响并给出错误的输出。下面是我的伪代码,其中描述了逻辑。

#initialisation and fetching of the table from SQL
df = pd.read_sql('SELECT * FROM stations', cnxn)
df['Timeflag'] = now - df['last_reported']
df['last_email_sent'] = None

while True:
   for index in df.index:
       if(df['Timeflag'] == 1 and df.loc[df.index[index], "Last_email_sent"] is None:
            print('pass')
            minutes = divmod((now - df.loc[index, "Last_email_sent"]).total_seconds(), 60)[0]

       elif df.loc[index, 'Time flag'] == 1 and minutes < min:
            print('fail')
            minutes = divmod((now - df.loc[index, "Last_email_sent"]).total_seconds(), 60)[0]
               else:
        print('false')
time.sleep(10)  

问题是我不能做类似下面的事情,因为在 for 循环中 last_email_sent 不能是 None 并且必须保留在 while 循环的第一次迭代后普遍存在的最后更新值.

while True:
    #initialisation and fetching of the table from SQL
    df = pd.read_sql('SELECT * FROM stations', cnxn)
    df['Timeflag'] = now - df['last_reported']
    df['last_email_sent'] = None

有没有其他方法可以在for循环中调用数据框,从而同时计算其他列?

如果我以正确的方式理解你的问题,你可以执行以下操作,但请注意,它还没有准备好使用代码,我只是想演示逻辑

First_Start = True  # first time we define db colum to None
Last_Email_Sent = None  # when we sent the last email

while True:

    # read data from db heare and do what you need
    df = pd.read_sql('SELECT * FROM stations', cnxn)
    df['Timeflag'] = now - df['last_reported']
    if First_Start:
        df['last_email_sent'] = None
        First_Start = False  # never again will be True
    else:
        df['last_email_sent'] = Last_Email_Sent

    while True:
       for index in df.index:  # cheack all you want in df
           if(df['Timeflag'] == 1 and df.loc[df.index[index], "Last_email_sent"] is None:
                print('pass')
                minutes = divmod((now - df.loc[index, "Last_email_sent"]).total_seconds(), 60)[0]

           elif df.loc[index, 'Time flag'] == 1 and minutes < min:
                print('fail')
                minutes = divmod((now - df.loc[index, "Last_email_sent"]).total_seconds(), 60)[0]
            else:
                print('false')

        Last_Email_Sent  = ??? # define new value here!
        break # all work is done and you go out of the while loop
    time.sleep(10)

    # now you can apply to db again to get a new df

希望回答对您有用。