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