如何让函数在 Python 中作为子进程运行? [英] How do I make functions run as subprocesses in Python?

问题描述

我希望我的 Python 脚本能够将其功能之一作为子进程运行.我该怎么做?

I want my Python script to be able to run one of its functions as subprocesses. How should I do that?

这是我的意图的模拟脚本:

Here is a mock-up script of my intention:

#!/urs/bin/env python

def print_mynumber(foo):
    """This function is obviously more complicated in my script.
    It should be run as a subprocess."""
    print(foo)

for foo in [1,2,3]:
    print_mynumber(foo) # Each call of this function should span a new process.
    # subprocess(print_mynumber(foo))

感谢您的建议.对我来说，正确地提出问题，从而进行适当的网络搜索，对我来说有点困难.

Thank you for your suggestions. It is a little hard for me to formulate the problem correctly, and thus to make the appropriate web search.

推荐答案

使用多处理模块:>

import multiprocessing as mp

def print_mynumber(foo):
    """This function is obviously more complicated in my script.
    It should be run as a subprocess."""
    print(foo)

if __name__ == '__main__':
    for foo in [1,2,3]:
        proc = mp.Process(target = print_mynumber, args = (foo, ))
        proc.start()

<小时>

您可能不想为每次对 print_mynumber 的调用创建一个进程，尤其是当 foo 迭代的列表很长时.在这种情况下，更好的方法是使用多处理池:

---

You might not want to be creating one process for each call to print_mynumber, especially if the list foo iterates over is long. A better way in that case would be to use a multiprocessing pool:

import multiprocessing as mp

def print_mynumber(foo):
    """This function is obviously more complicated in my script.
    It should be run as a subprocess."""
    print(foo)

if __name__ == '__main__':
    pool = mp.Pool()
    pool.map(print_mynumber, [1,2,3])

默认情况下，池将创建 N 个工作进程，其中 N 是机器拥有的 CPU(或内核)数量.pool.map 的行为与 Python 内置的 map 命令非常相似，不同之处在于它将任务分给工作池.

The pool, be default, will create N worker processes, where N is the number of cpus (or cores) the machine possesses. pool.map behaves much like the Python builtin map command, except that it farms out tasks to the pool of workers.

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