在项目列表上使用线程

Question

我有一个我想用线程处理的项目列表，每个项目大约需要10分钟，我想一次处理两个

现在我一次做一个，这需要一段时间

old = ["old_item1","old_item2","old_item3","old_item4","old_item5"]
new = ["new_item1","new_item2","new_item3","new_item4","new_item5"]
area = ["area_item1","area_item2","area_item3","area_item4","area_item5"]

def func(x,y,z):
    print (x,y,z)

d = zip(old,new, area)

for e,f, g in d: 
  thread1 = threading.Thread(target=func, args=(e,f,g))
  thread2 = threading.Thread(target=func, args=(e,f,g))
  thread1.start()
  thread2.start()
  thread1.join()
  thread2.join()

所以我想做的是过程

带有thread1的item1 带螺纹2的项目2

项目3与线程1 项目4与螺纹2

最后 项目5与线程1

Answer 1

您可以使用^{}的pool，它将为您处理所有杂乱的工作。使用^{}函数，可以对iterable的所有项运行函数作为其参数

比如：

from multiprocessing import Pool

old = ["old_item1","old_item2","old_item3","old_item4","old_item5"]
new = ["new_item1","new_item2","new_item3","new_item4","new_item5"]
area = ["area_item1","area_item2","area_item3","area_item4","area_item5"]

def func(x,y,z):
    print (x,y,z)

d = zip(old,new, area)

with Pool() as pool:
    res = pool.starmap(func, d)

• 这里实际上不需要保存结果，但通常返回值是与给定iterable对应的所有结果的列表