Python如何快速实现分布式任务

from multiprocessing.managers import BaseManager
import Queue

queue = Queue.Queue() #初始化一个Q，用于消息传递
class QueueManager(BaseManager):
  pass

QueueManager.register('get_queue', callable=lambda:queue) # 在系统中发布get_queue这个业务

if __name__ == '__main__':
  m = QueueManager(address=('10.239.85.193', 50000),authkey='abr' )
 # 监听所有10.239.85.193的50000口
  s = m.get_server()
  s.serve_forever()

from multiprocessing.managers import BaseManager
from multiprocessing import Pool


class QueueManager(BaseManager):
 pass

QueueManager.register('get_queue') 

def feb(i): #经典的'山羊增殖'
  if i < 2: return 1
  if i < 5 : return feb(i-1) + feb(i-2)
  return feb(i-1) + feb(i-2) - feb(i-5)

def worker(i): 
  m = QueueManager(address=('10.239.85.193', 50000), authkey='abr')
#连接server
  m.connect()
  while True:
    queue = m.get_queue()
# 获取Q
   c = queue.get()
 print feb(c)

if __name__ == '__main__':

  p = Pool(8) # 分进程启动8个worker
  p.map(worker, range(8))
producer.py

from multiprocessing.managers import BaseManager


class QueueManager(BaseManager):
  pass
QueueManager.register('get_queue')


if __name__ == '__main__':
 m = QueueManager(address=('10.239.85.193', 50000), authkey='abr')
 m.connect()
 i = 0
 while True:
   queue = m.get_queue()
   queue.put(48)

   i+=1