由于性能问题,我想在python中并行运行我的函数:
import multiprocessing as mp
source_nodes = [10413173, 10414530, 10414530, 10437199]
sink_nodes = [10420346, 10438770, 10438711, 10414530, 10436258]
path =[]
def createpath(source,sink):
for i in source:
for j in sink:
path = path + list(nx.all_simple_paths(Directed_G,i,j))
return path
以我的理解,我必须给1迭代应用功能。但我的想法是做类似的事情:
results = [pool.apply(createpath, args=(source_nodes, sink_nodes))]
然后不给任何可迭代对象套用function 我设法使其正常运行,但我认为它不能并行运行。
您认为我应该在第一个循环中包含apply函数吗?
答案 0 :(得分:2)
from multiprocessing import Pool
source_nodes = [1,2,3,4,5,6]
sink_nodes = [1,1,1,1,1,1,1,1,1]
def sum_values(parameter_tuple):
source,sink, start, stop = parameter_tuple
out = 0
for i in range(start, stop):
val_i = source[i]
for j in sink:
out += val_i*j
return out
if __name__ == "__main__":
params = (source_nodes, sink_nodes, 0, 6)
print(sum_values(params))
with Pool(2) as p:
print(p.map(sum_values, [
(source_nodes, sink_nodes, 0, 3),
(source_nodes, sink_nodes, 3, 6),
]))
您可以尝试运行此程序。这与2个线程池上的映射模式并行运行。在这种情况下,您的输出结果是池中每个进程的结果之和。