Python 操作redis消息队列 多进程消费

生产端

import json
import redis

# 以下代码是向redis 发命令
QUEUE = "code"  # 队列名称key

# redisPool = redis.ConnectionPool(host=config.get_redis_host(), port=6379, db=config.get_redis_db())
redisPool = redis.ConnectionPool(host='localhost', port=6379, db=8)
client = redis.Redis(connection_pool=redisPool)


def send_cmd(seaweed):
    json_cmd = json.dumps(seaweed, ensure_ascii=False)
    client.rpush(QUEUE, json_cmd)


ll = list(range(100))
# get_weekend('20180325')})
if __name__ == "__main__":
    for k in ll:
        send_cmd({"label": k, 'timd': 20160503, 'timm': 20170430})

 

消费端多进程消费

import chardet
import json
import multiprocessing
import redis

# 以下代码是向redis 发命令
QUEUE = "code"
# redisPool = redis.ConnectionPool(host=config.get_redis_host(), port=6379, db=config.get_redis_db())
redisPool = redis.ConnectionPool(host='localhost', port=6379, db=8)
client = redis.Redis(connection_pool=redisPool)


# 以下代码是向redis 取命令，并且采用多进程来实现计算
def func(a, b, c):
    print(a, b)


def worker(pname):
    client = redis.Redis(connection_pool=redisPool)
    # client_ = redis.ConnectionPool(host='localhost', port=6379, db=8)

    while True:

        # print(client)
        # print(cmd)
        try:
            cmd = client.lpop(QUEUE)
            encode1 = chardet.detect(cmd)["encoding"]
            cmd = cmd.decode(encode1)
        except:
            cmd = None
        if cmd is None:
            return

        else:

            cmd = format_cmd(cmd)
            try:
                func(cmd["label"], cmd['timd'], cmd['timm'])
                # price_fix.update(cmd["city"], cmd["region"], cmd["name"])
                # print(pname + ":", cmd, "计算成功")
            except Exception as ex:
                print(ex)
                print(pname + ":", cmd, "计算失败")


def format_cmd(cmd):
    return json.loads(cmd)


if __name__ == "__main__":
    # 多进程消费
    pro_num = 5
    pool = multiprocessing.Pool(processes=pro_num)
    for pid in range(1, pro_num):
        pid = "PROC" + str(pid).zfill(3)
        pool.apply_async(worker, (pid,))
    pool.close()
    pool.join()