conn=redis.StrictRedis(connection_pool=config_manager_list[str(app_id)].redis_pool,socket_timeout=5,socket_connect_timeout=5, retry_on_timeout=5) 连接数据库
r = conn.pipeline() 获取管道
使用pipelining 发送命令时，redis server必须部分请求放到队列中（使用内存）执行完毕后一次性发送结果
pipeline期间将“独占”链接，此期间将不能进行非“管道”类型的其他操作，直到pipeline关闭；如果你的pipeline的指令集很庞大，为了不干扰链接中的其他操作，你可以为pipeline操作新建Client链接，让pipeline和其他正常操作分离在2个client中
- r.hset(name, "JWT", new_JWT) 更新key为name的哈希记录里叫做 JWT字段的值为new_JWT
- r.rename(old_name, new_name) 将old_name对应的哈希记录的key更新为new_name
- r.execute() 执行命令
pipeline和 execute合起来相当于使用事务来操作，可以一次性执行多个命令
#!/usr/bin/python2
import redis
import time
def without_pipeline():
r=redis.Redis()
for i in range(10000):
r.ping()
return
def with_pipeline():
r=redis.Redis()
pipeline=r.pipeline()
for i in range(10000):
pipeline.ping()
pipeline.execute()
return
def bench(desc):
start=time.clock()
desc()
stop=time.clock()
diff=stop-start
print "%s has token %s" % (desc.func_name,str(diff))
if __name__=='__main__':
bench(without_pipeline)
bench(with_pipeline)
# 测试结果
without_pipeline has token 4.64443057954
with_pipeline has token 0.098383873589
python 调用lua脚本操作redis
- s = self.conn.register_script(GET_COUNT_SCRIPT)
- res = s(args=patterns)
GET_ALL_RID_SCRIPT = """
local cursor = "0"
local matchKey = ARGV[1]
local matchKeyPrefix = string.sub(matchKey,1,-2)
local ridList = {};
local done = false;
repeat
local result = redis.call("SCAN", cursor, "match", matchKey)
cursor = result[1];
for i, key in ipairs(result[2]) do
local rid = string.gsub(key,matchKeyPrefix,"");
table.insert(ridList,rid);
end
if cursor == "0" then
done = true;
end
until done
return ridList;
"""
s = self.conn.register_script(GET_ALL_RID_SCRIPT)
res = s(args=[match])
scan 命令
通过key '*' 查找所有key
无匹配模式遍历
有匹配模式遍历
