python3 分布式进程(跨机器)BaseManager(multiprocessing.managers)

A机器负责发送任务和接受结果：

#task_master.py
import random,time,queue
from multiprocessing.managers import BaseManager

task_queue = queue.Queue()
result_queue = queue.Queue()

class QueueManager(BaseManager):
    pass

if __name__ == '__main__':
    print("master start.")
    QueueManager.register('get_task_queue',callable = lambda:task_queue)
    QueueManager.register('get_result_queue',callable = lambda:result_queue)
    manager = QueueManager(address = ('10.10.100.11',9833),authkey=b'abc')
    manager.start()
    task = manager.get_task_queue()
    result = manager.get_result_queue()

    for i in range(10):
        n = random.randint(0,1000)
        print('put task %d ...' % n)
        task.put(n)
    print('try get results...')

    for i in range(10):
        r = result.get(timeout = 100)
        print('Result:%s' % r)
    manager.shutdown()
    print('master exit.')

B机器负责处理任务和发送结果：

#task_worker.py
import sys,time,queue
from multiprocessing.managers import BaseManager

class QueueManager(BaseManager):
    pass

QueueManager.register('get_task_queue')
QueueManager.register('get_result_queue')

server_addr = '10.10.100.11'
print('connect to server %s...' % server_addr)

m = QueueManager(address=(server_addr,9833),authkey=b'abc')
m.connect()

task = m.get_task_queue()
result = m.get_result_queue()

for i in range(10):
    try:
        n = task.get(timeout = 10)
        print('run task %d * %d' %(n,n))
        r = '%d * %d = %d' %(n,n,n*n)
        time.sleep(1)
        result.put(r)
    except Queue.Empty:
        print('task queue is empty')

print('worker exit'）