response = execute_low_level('HGET','redis:key','hash:key', host='localhost', port=6379) But as I said before,redis.Redisis the way to go in 99.9% of cases. you dont need worry about it when you use ConnectionP
1 #!/usr/bin/env python 2 # -*- coding:utf-8 -*- 3 4 import redis 5 6 pool = redis.ConnectionPool(host='192.168.22.132', port=6379) 7 r = redis.Redis(connection_pool=pool) 8 9 # pipe = r.pipeline(transaction=False) 10 pipe = r.pipeline(transaction=True) 11 12 pipe.set('...
ConnectionPool(host='192.168.200.196', port=6379, db=0, decode_responses=True, max_connections=10,password="123456") # 从连接池中获取连接 redis_client = redis.StrictRedis(connection_pool=redis_pool) print(redis_client.ping()) 含有用户名的连接 import redis url = f"redis://用户名:密码@地址...
连接创建,调用的是ConnectionPool的get_connection:pool.get_connection(command_name, **options) connection = self ._available_connections.pop()),否则创建一个连接( connection = self .make_connection()): 释放连接:pool.release(conn) 连接池对象调用release方法, 将连接从_in_use_connections 放回 _availab...
PythonRedis的客户端使用了链接池机制,通过复用链接可以减低服务器的压力并在失败时重试。连接池其实是一种很通用的机制,在实现客户端是是一个经常需要(或许其实不需要)重复发明的轮子。 Redis 客户端一共涉及到了三个类: Connection,表示一个到服务器的链接 ...
_lock: try: connection = self._available_connections.pop() # 当可用连接数为空时,pop会抛出IndexError的异常,如果这个时候连接数已达到最大链接数,在创建连接的时候会报错 except IndexError: connection = self.make_connection() self._in_use_connections.add(connection) try: # ensure this connection ...
4.执行Python 代码 (代码来源:极客时间) #!/usr/bin/env python #-*-coding:utf-8-*- # @Author : clover # @Time : 2019/9/17 8: import redis import time print (redis.__file__) #创建redis连接 pool=redis.ConnectionPool(host='localhost',port=6379) ...
1、连接池建立,利用连接池连接 In [8]: connpool = redis.ConnectionPool(host='192.168.8.237',port=6379,decode_responses=True) In [9]: rc = redis.Redis(connection_pool=connpool) In [10]: rc.set('imooccp','1234566') Out[10]: True In [11]: rc.get('imooccp') Out[11]: u'1234566...
/usr/bin/env python # -*- coding:utf-8 -*- __author__ ='shouke' importredis if__name__ =='__main__': pool = redis.ConnectionPool(host='192.168.1.103',port=6379,db=0) r = redis.Redis(connection_pool=pool) result = r.set('name','shouke')...
map() as client: for key in range(100): client.get(key).then(lambda x: results.append(int(x or 0))) print('Sum: %s' % sum(results)) Fanout: with cluster.fanout(hosts=[0, 1, 2, 3]) as client: infos = client.info() Fanout to all: with cluster.fanout(hosts='all') as ...