我是python redis模块的新手，我正在寻找一种在使用python多处理模块时池连接的有效方法。我的代码如下：
gridCoord这里我基本上想在import multiprocessing as mp
import Queue
import os
import time
import redis
def _process_messages_parallel(messages):
processes=[mp.Process(target=_process_message, args=[message]) for message in messages]
for process in processes:
process.daemon=False
process.start()
for process in processes:
process.join()
def _process_message(message):
organization=message['organization']
#get value associated with `organization` key from redis
result=get_val_from_redis(organization)
#process result
#assume local redis instance for now.
def get_val_from_redis(organization,host='localhost',port='6379'):
conn=redis.StrictRedis(host=host,port=port,db=db,retry_on_timeout=retry_on_timeout)
return conn.get(organization)
if __name__=="__main__":
messages=[{'organization':'org1'},{'organization':'org2'},{'organization':'org3'},...{'organization':'orgN'}]
process_articles=mp.Process(target=_process_messages_parallel,args=[messages])
process_articles.daemon=False
process_articles.start()
process_articles.join()
函数创建的不同进程之间重用相同的连接池。有人可以建议一个好方法吗？一个简单的解决方案可能是创建模块范围redis连接池，或函数范围redis连接池，但我关心的是如何在不同进程之间共享python模块/或python函数。如果为每个进程创建了一个单独的对象副本，那么它是否胜过连接池的目的？