Python 多处理进程 ID

Python multiprocessing Process ID

我也在使用 multiprocessing.Pool 运行 不同的进程(例如 4 个进程),我需要对每个进程进行标识,以便我可以在每个进程中做不同的事情。

因为我在 while 循环中有池 运行ning,对于第一次迭代,我可以知道每个进程的 ID,但是对于第二次和更多迭代,这个 ID 会改变,或者至少我可以'找不到一个 属性 似乎对所有迭代中的每个过程都相同。

相关部分代码如下:

     while i <= maxiter:
        print('\n' + 'Iteration: %r'%i + '\n')

        pool = mp.Pool(processes = numprocs)

        swarm = pool.map_async(partial(proxy, costf = costFunc, i=i),Swarm)
        pool.close()
        pool.join()

        Swarm = swarm.get()

我已经尝试使用以下属性来正确标识进程,但它对我不起作用:

print(mp.Process().name)
print(mp.current_process().name)

有了这个输出是:

Iteration: 1

Process-2:1
Process-1:1
ForkPoolWorker-1
ForkPoolWorker-2
Process-3:1
ForkPoolWorker-3
Process-2:2
ForkPoolWorker-2
Process-3:2
Process-2:3
ForkPoolWorker-3
ForkPoolWorker-2
Process-1:2
ForkPoolWorker-1
Process-4:1
Process-3:3
ForkPoolWorker-4
ForkPoolWorker-3
Process-2:4
ForkPoolWorker-2

Iteration: 2

Process-5:1
ForkPoolWorker-5
Process-5:2
Process-7:1
ForkPoolWorker-7
Process-6:1
ForkPoolWorker-5
ForkPoolWorker-6
Process-5:3
ForkPoolWorker-5
Process-7:2
ForkPoolWorker-7
Process-5:4
ForkPoolWorker-5
Process-6:2
ForkPoolWorker-6
Process-7:3
ForkPoolWorker-7
Process-8:1
ForkPoolWorker-8

有什么想法可以让我每次都以相同的方式识别每个进程吗?

编辑 1:

我已经将程序简化为这样,但思路是一样的:

import random, numpy as np,time
import multiprocessing as mp

def costFunc(i):
    print(mp.current_process().name,mp.Process().name)
    return i*1

class PSO():
    def __init__(self,maxiter,numprocs):

        # Begin optimization Loop
        i = 1
        self.Evol = []

        while i <= maxiter:
            print('\n' + 'Iteration: %r'%i + '\n')
            pool = mp.Pool(processes = numprocs)
            swarm = pool.map_async(costFunc,(i,))
            pool.close()
            pool.join()

            Swarm = swarm.get()

            i += 1

if __name__ == "__main__":
    #mp.set_start_method('spawn')
    PSO(10,1)

输出:

Iteration: 1
ForkPoolWorker-1 Process-1:1
Iteration: 2
ForkPoolWorker-2 Process-2:1
Iteration: 3
ForkPoolWorker-3 Process-3:1
Iteration: 4
ForkPoolWorker-4 Process-4:1
Iteration: 5
ForkPoolWorker-5 Process-5:1
Iteration: 6
ForkPoolWorker-6 Process-6:1
Iteration: 7
ForkPoolWorker-7 Process-7:1
Iteration: 8
ForkPoolWorker-8 Process-8:1
Iteration: 9
ForkPoolWorker-9 Process-9:1
Iteration: 10
ForkPoolWorker-10 Process-10:1

您将在循环的每次迭代中创建一个新池,因此永远不会重复使用池中的进程。

pool = mp.Pool(processes = numprocs)(以及 pool.close()pool.join())移出 while 循环以重新使用池中的进程。