Redis的三种限流方法以及代码详解

Redis 提供了几种不同的方法来实现限流，以下是三种常见的限流方法及其代码示例：

1. 使用 Redis 的 INCR 和 EXPIRE 命令

import redis
 
def is_rate_limited(redis_conn, user_id, max_requests, duration):
    key = f"user:{user_id}:rate_limit"
    requests = redis_conn.incr(key)
    if requests == 1:
        redis_conn.expire(key, duration)
    if requests > max_requests:
        return True
    else:
        return False
 
r = redis.Redis(host='localhost', port=6379, db=0)
user_id = "user123"
max_requests = 10
duration = 60  # 60 seconds
 
if is_rate_limited(r, user_id, max_requests, duration):
    print("User has exceeded the rate limit.")
else:
    print("User is within the rate limit.")

2. 使用 Redis 的 LUA 脚本

import redis
 
rate_limit_script = """
    local key = KEYS[1]
    local limit = tonumber(ARGV[1])
    local current = redis.call('get', key)
    if current and tonumber(current) > limit then
        return true
    else
        if current then
            redis.call('incr', key)
        else
            redis.call('set', key, 1)
            redis.call('expire', key, ARGV[2])
        end
        return false
    end
"""
 
def is_rate_limited(redis_conn, user_id, max_requests, duration):
    key = f"user:{user_id}:rate_limit"
    script = redis_conn.register_script(rate_limit_script)
    return script(keys=[key], args=[max_requests, duration])
 
r = redis.Redis(host='localhost', port=6379, db=0)
user_id = "user123"
max_requests = 10
duration = 60  # 60 seconds
 
if is_rate_limited(r, user_id, max_requests, duration):
    print("User has exceeded the rate limit.")
else:
    print("User is within the rate limit.")

3. 使用 Redis 的 Token Bucket 算法

import redis
import time
 
def token_bucket(redis_conn, user_id, rate, tokens, duration):
    key = f"user:{user_id}:rate_limit"
    now = time.time()
    timestamp = redis_conn.get(key)
    if timestamp:
        timestamp = float(timestamp)
        if now < timestamp:
            return False
        if now > timestamp + duration:
            redis_conn.set(key, now, ex=duration)
            redis_conn.set(f"{key}:tokens", max(tokens - (now - timestamp) * rate, 0))
    else:
        redis_conn.set(key, now, ex=duration)
        redis_conn.set(f"{key}:tokens", tokens)
    if redis_conn.exists(f"{key}:tokens"):
        current_tokens = redis_conn.get(f"{key}:tokens")
        if current_tokens and int(current_tokens) > 0:
            redis_conn.decr(f"{ke