我有以下代码段,试图同时从邮箱的不同目录中提取邮件。但是,它显示出以下问题。附加了缩短的堆栈跟踪。

import multiprocessing as mlp
import imaplib as impl

def somefunc(dirc):
    mail.select(dirc)
    result, data = mail.uid("search", None, "All")
    uids = data[0].split()
    print dirc
    for mail_id in uids:
       result, data = mail.uid("fetch", mail_id, "(RFC822)")

if __name__ == '__main__':
    mail = impl.IMAP4_SSL("somedomain")
    mail.login("username","password")

    jobs = []
    p1 = mlp.Process(target = somefunc, args = ("INBOX",))
    jobs.append(p1)
    p1.start()
    p2 = mlp.Process(target = somefunc, args = ("Sent",))
    jobs.append(p2)
    p2.start()
    for i in jobs:
        i.join()


它引发错误:

Process Process-2:
Traceback (most recent call last):
File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
Process Process-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap
    self.run()
File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run
    self._target(*self._args, **self._kwargs)
........
File "/usr/lib/python2.7/imaplib.py", line 859, in _command
    raise self.abort('socket error: %s' % val)
abort: socket error: [Errno 32] Broken pipe
    typ, dat = self._simple_command(name, mailbox)
........
error: [Errno 104] Connection reset by peer


不能同时进行imap连接吗???

谢谢... :)

最佳答案

我的猜测是您有问题,因为您试图跨进程共享邮件套接字连接对象。而是尝试让每个进程创建其连接:

import multiprocessing as mlp
import imaplib as impl

def somefunc(domain, name, password, dirc):
    mail = impl.IMAP4_SSL(domain)
    mail.login(name, password)
    mail.select(dirc)
    result, data = mail.uid("search", None, "All")
    uids = data[0].split()
    print dirc
    for mail_id in uids:
       result, data = mail.uid("fetch", mail_id, "(RFC822)")

if __name__ == '__main__':
    jobs = []

    for box in ("INBOX", "Sent"):
        p = mlp.Process(
                target = somefunc,
                args = ("somedomain", "username", "password", box)
            )
        jobs.append(p)
        p.start()

    for i in jobs:
        i.join()

关于python - Python多处理imaplib引发错误,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/14033929/

10-10 17:16