python - python 的 Pool 什么时候分叉？

Question

有人知道python的Pool在哪个阶段分叉了主进程吗？在创建池时，还是在第一次运行作业时？

Answer 1

创建multiprocessing.Pool对象时，它会产生一些线程，但不会分叉。分叉是在调用其他Pool方法时完成的，并且仅在 UNIX 系统上（在 Windows 上没有分叉）。

您可以在阅读该Pool.__init__方法的源代码时看到这一点：

class Pool(object):
    '''
    Class which supports an async version of applying functions to arguments.
    '''
    Process = Process

    def __init__(self, processes=None, initializer=None, initargs=(),
                 maxtasksperchild=None):
        self._setup_queues()
        self._taskqueue = queue.Queue()
        self._cache = {}
        self._state = RUN
        self._maxtasksperchild = maxtasksperchild
        self._initializer = initializer
        self._initargs = initargs

        if processes is None:
            try:
                processes = cpu_count()
            except NotImplementedError:
                processes = 1
        if processes < 1:
            raise ValueError("Number of processes must be at least 1")

        if initializer is not None and not callable(initializer):
            raise TypeError('initializer must be a callable')

        self._processes = processes
        self._pool = []
        self._repopulate_pool()

        self._worker_handler = threading.Thread(
            target=Pool._handle_workers,
            args=(self, )
            )
        self._worker_handler.daemon = True
        self._worker_handler._state = RUN
        self._worker_handler.start()


        self._task_handler = threading.Thread(
            target=Pool._handle_tasks,
            args=(self._taskqueue, self._quick_put, self._outqueue, self._pool)
            )
        self._task_handler.daemon = True
        self._task_handler._state = RUN
        self._task_handler.start()

        self._result_handler = threading.Thread(
            target=Pool._handle_results,
            args=(self._outqueue, self._quick_get, self._cache)
            )
        self._result_handler.daemon = True
        self._result_handler._state = RUN
        self._result_handler.start()

        self._terminate = Finalize(
            self, self._terminate_pool,
            args=(self._taskqueue, self._inqueue, self._outqueue, self._pool,
                  self._worker_handler, self._task_handler,
                  self._result_handler, self._cache),
            exitpriority=15
            )