分析 python 多处理池

Profiling a python multiprocessing pool(分析 python 多处理池)

问题描述

我正在尝试在多处理池中的每个进程上运行 cProfile.runctx()，以了解我的源中的多处理瓶颈是什么.这是我正在尝试做的一个简化示例:

I'm trying to run cProfile.runctx() on each process in a multiprocessing pool, to get an idea of what the multiprocessing bottlenecks are in my source. Here is a simplified example of what I'm trying to do:

from multiprocessing import Pool
import cProfile

def square(i):
    return i*i

def square_wrapper(i):
    cProfile.runctx("result = square(i)",
        globals(), locals(), "file_"+str(i))
    # NameError happens here - 'result' is not defined.
    return result

if __name__ == "__main__":
    pool = Pool(8)
    results = pool.map_async(square_wrapper, range(15)).get(99999)
    print results

不幸的是，尝试在分析器中执行result = square(i)"不会影响调用范围内的result".我怎样才能在这里完成我想要做的事情?

Unfortunately, trying to execute "result = square(i)" in the profiler does not affect 'result' in the scope it was called from. How can I accomplish what I am trying to do here?

推荐答案

试试这个:

def square_wrapper(i):
    result = [None]
    cProfile.runctx("result[0] = square(i)", globals(), locals(), "file_%d" % i)
    return result[0]

这篇关于分析 python 多处理池的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持编程学习网！