Python:多处理imap&动态创建的池冻结 [英] Python: Multiprocessing imap & dynamically-created pools freeze

问题描述

有人可以解释为什么此代码冻结(永久挂起)

Could someone explain why this code freezes (hangs forever),

import multiprocessing
def foo(x): return x
def main():
    print(list(multiprocessing.Pool().imap(foo, iter([1, 2, 3]))))
main()

虽然此变体可以正常工作，

While this variant works fine,

import multiprocessing
def foo(x): return x
pool = multiprocessing.Pool()
def main():
    print(list(pool.imap(foo, iter([1, 2, 3]))))
main()

与此一样，

import multiprocessing
def foo(x): return x
def main():
    print(list(multiprocessing.Pool().map(foo, [1, 2, 3])))
main()

顺便说一句，能够在应用程序的非初始化阶段动态创建multiprocessing.Pool()，然后使用imap确实会有所帮助.我尝试在gdb中逐步进行调试，但似乎在PyThread_acquire_lock中冻结了……但是在这样低的水平下，我感觉调试很不合理.

Incidentally, being able to dynamically create multiprocessing.Pool() at a non-initialization stage in the application, and then use imap would be really helpful. I tried stepping through it in gdb, and it seems frozen at PyThread_acquire_lock ... but I feel pretty out-of-element debugging at such a low level.

推荐答案

显然，这是Python 2.6.7的错误，并且至少已由Python 2.7.3修复.

Apparently this is a bug with Python 2.6.7, and has been fixed at least by Python 2.7.3.

这可以通过使用我的vimap包[ https://github.com/gatoatigrado/vimap来解决. ].

This can be worked around by using my vimap package [ https://github.com/gatoatigrado/vimap ].

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