Redis梦幻整合：解锁数据的神秘力量

在Redis和梦幻 srv的整合中，我们可以利用Redis的分布式锁特性来保证数据的一致性。

解决方案：

1. 使用Redis的SETNX和EXPIRE命令实现分布式锁。

def acquire_lock(conn, lock_name, acquire_timeout=10, lock_timeout=10):
    identifier = str(uuid.uuid4())
    end = time.time() + acquire_timeout
    lock_name = 'lock:' + lock_name
 
    while time.time() < end:
        if conn.setnx(lock_name, identifier):
            conn.expire(lock_name, lock_timeout)
            return identifier
        time.sleep(0.001)
 
    return False
 
def release_lock(conn, lock_name, identifier):
    lock_name = 'lock:' + lock_name
    pipe = conn.pipeline(True)
    while True:
        try:
            pipe.watch(lock_name)
            if pipe.get(lock_name) == identifier:
                pipe.multi()
                pipe.delete(lock_name)
                pipe.execute()
                return True
            pipe.unwatch()
            break
        except redis.exceptions.WatchError:
            pass
    return False

2. 使用Redlock算法来实现更安全的分布式锁。

import redis
import time
import uuid
 
class Redlock(object):
    def __init__(self, servers, lock_timeout=1000, retry_count=3, retry_delay=100):
        self.servers = servers
        self.lock_timeout = lock_timeout
        self.quorum = len(servers) / 2 + 1
        self.retry_count = retry_count
        self.retry_delay = retry_delay
 
    def _get_redis_client(self, server):
        return redis.StrictRedis(host=server.split(':')[0], port=int(server.split(':')[1]), decode_responses=True)
 
    def _lock(self, client, lock_name):
        identifier = str(uuid.uuid4())
        end = time.time() * 1000 + self.lock_timeout
        lock_name = 'lock:' + lock_name
 
        while time.time() * 1000 < end:
            if client.set(lock_name, identifier, ex=self.lock_timeout, nx=True):
                return identifier
            time.sleep(0.001)
 
        return False
 
    def _unlock(self, client, lock_name, identifier):
        lock_name = 'lock:' + lock_name
        pipe = client.pipeline(True)
        while True:
            try:
                pipe.watch(lock_name)
                if pipe.get(lock_name) == identifier:
                    pipe.multi()
                    pipe.delete(lock_name)
                    pipe.execute()
                    return True
                pipe.unwatch()
                break
            except redis.exceptions.WatchError:
                pas