Python 2.6 : Process local storage while using multiprocessing. 池

Question

我正在尝试构建一个 python 脚本，该脚本具有跨大量数据的工作进程池(使用 mutiprocessing.Pool)。

我希望每个进程都有一个唯一的对象，可以在该进程的多次执行中使用。

伪代码:

def work(data):
    #connection should be unique per process
    connection.put(data)
    print 'work done with connection:', connection

if __name__ == '__main__':
    pPool = Pool() # pool of 4 processes
    datas = [1..1000]
    for process in pPool:
        #this is the part i'm asking about // how do I really do this?
        process.connection = Connection(conargs)
    for data in datas:
       pPool.apply_async(work, (data))

Answer 1

我认为类似的东西应该有效(未经测试)

def init(*args):
    global connection
    connection = Connection(*args)
pPool = Pool(initializer=init, initargs=conargs)