python 操作redis数据库

安装redis的python库

pip install redis

普通的redis链接操作

import redis   # 导入redis模块
r = redis.Redis(host='localhost', port=6379, password="pwd@321", db=1,decode_responses=True)   # host是redis主机，password为认证密码，redis默认端口是6379,db表示指定的数据库, decode_responses=True 表示存储的数据是字符串格式,如果没有密码，则去掉password参数即可
r.set('name', 'phyger-from-python-redis')  # key是"name" value是"phyger-from-python-redis" 将键值对存入redis缓存
print(r['name'])  # 第一种：取出键name对应的值
print(r.get('name'))  # 第二种：取出键name对应的值
print(type(r.get('name')))

使用redis连接池

import redis   # 导入redis模块
def client_redis_pool():
    pool = redis.ConnectionPool(host='localhost', port=6379, db=1, decode_responses=True, max_connections=10)
    r = redis.Redis(connection_pool=pool)
    r.set('name', 'phyger-from-python-redis')
    print(r.get('name'))
    print(r['name'])
    print(type(r.get('name')))

存储数据时自定义过期时间

import redis   # 导入redis模块
# 格式： set(name, value, ex=None, px=None, nx=False, xx=False)
# ex	<int>过期时间(m)
# px	<int>过期时间(ms)
# nx	<bool>如果为真，则只有 name 不存在时，当前 set 操作才执行
# xx	<bool>如果为真，则只有 name 存在时，当前 set 操作才执行
def client_redis_pool_ex():
    pool = redis.ConnectionPool(host='localhost', port=6379, db=1, decode_responses=True)
    r = redis.Redis(connection_pool=pool)
    r.set('name', 'phyger-from-python-redis', ex=3)
    print(r['name'])
    time.sleep(3)
    print(r.get('name'))
    print(type(r.get('name')))

多线程连接池测试

import threading
import redis

def redis_pool_test():
    # 使用阻塞连接池 （当连接池中没有空闲的连接时，会等待timeout秒，直到获取到连接或超时报错。）
    # pool = redis.BlockingConnectionPool(host='localhost', port=6379, db=1, max_connections=2, timeout=5)
    # 使用普通连接池
    pool = redis.ConnectionPool(host='localhost', port=6379, db=1, max_connections=2, timeout=5)
    redis_client = redis.Redis(connection_pool=pool)
    thread1 = RedaisExexThread(redis_client)
    thread2 = RedaisExexThread(redis_client)
    thread3 = RedaisExexThread(redis_client)
    thread4 = RedaisExexThread(redis_client)
    thread5 = RedaisExexThread(redis_client)
    thread6 = RedaisExexThread(redis_client)
    thread7 = RedaisExexThread(redis_client)
    thread8 = RedaisExexThread(redis_client)
    thread9 = RedaisExexThread(redis_client)
    thread10 = RedaisExexThread(redis_client)

    thread1.start()
    thread2.start()
    thread3.start()
    thread4.start()
    thread5.start()
    thread6.start()
    thread7.start()
    thread8.start()
    thread9.start()
    thread10.start()
# 使用普通连接池的时候，连接数不够会直接报错
# 使用阻塞连接池的时候，如果连接数不够，会等待，等待时间在设定的超时时间之后，才会舍弃，
# 在实际应用的时候，可以把线程池和超时时间设置的稍微大一些

redis 单例模式作为全局配置连接使用

创建redisPool.py文件

# !/usr/bin/env python3
# -*- coding: utf-8 -*-
import redis

RedisConfig = dict(host='127.0.0.1', port=6379, db=1, decode_responses=True, max_connections=10, timeout=5)


class RedisCache:
    _instance = None

    def __new__(cls, *args, **kwargs):
        if cls._instance is None:
            cls._instance = object.__new__(cls)
        return cls._instance

    _redis_pool_data = redis.BlockingConnectionPool(**RedisConfig)

    # 以管道方式运行redis
    @classmethod
    def get_pipe(cls):
        conn = cls.get_conn()
        return conn.pipeline(transaction=True)

    # 实例化redis
    @classmethod
    def get_conn(cls):
        conn = redis.StrictRedis(connection_pool=cls._redis_pool_data)
        return conn

创建调用主文件

import redisPool
import threading

def redis_clientt():
    redis_client = redisPool.RedisCache.get_conn()
    thread1 = RedaisExexThread(redis_client)
    thread2 = RedaisExexThread(redis_client)
    thread3 = RedaisExexThread(redis_client)
    thread4 = RedaisExexThread(redis_client)
    thread5 = RedaisExexThread(redis_client)
    thread6 = RedaisExexThread(redis_client)
    thread7 = RedaisExexThread(redis_client)
    thread8 = RedaisExexThread(redis_client)
    thread9 = RedaisExexThread(redis_client)
    thread10 = RedaisExexThread(redis_client)

    thread1.start()
    thread2.start()
    thread3.start()
    thread4.start()
    thread5.start()
    thread6.start()
    thread7.start()
    thread8.start()
    thread9.start()
    thread10.start()

redis pip 管道批量提交和普通set参数的区别

def redis_client_set_pip(ss):
    redis_clientt = redisPool.RedisCache.get_pipe()
    for i in range(1, 100000):
        redis_clientt.sadd(ss + str(i), i)
    redis_clientt.execute()
    print(time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime()))
    # 添加10000个key-value  使用管道和不使用管道的区别


def redis_client_set(ss):
    redis_clientt = redisPool.RedisCache.get_conn()
    for i in range(1, 100000):
        redis_clientt.set(ss + str(i), i)
    # redis_clientt.execute()
    print(time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime()))
    # 添加10000个key-value  使用管道和不使用管道的区别


if __name__ == '__main__':
    print(time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime()))
    t1 = threading.Thread(target=redis_client_set_pip, args=['no_pipe1:'])
    t2 = threading.Thread(target=redis_client_set_pip, args=['no_pipe2:'])
    t3 = threading.Thread(target=redis_client_set_pip, args=['no_pipe3:'])
    t1.start()
    t2.start()
    t3.start()
    print(time.strftime("%Y-%m-%d-%H_%M_%S", time.localtime()))

同样是创建相同的数据pip方式比普通一个一个set的方式要提高好多倍