mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-02-02 18:22:39 +08:00
410 lines
16 KiB
Python
410 lines
16 KiB
Python
import functools
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import inspect
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import threading
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import time
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from collections import deque
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from typing import Any, Tuple, List, Callable, Optional
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from app.log import logger
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from app.schemas import RateLimitExceededException, LimitException
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# 抽象基类
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class BaseRateLimiter:
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"""
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限流器基类,定义了限流器的通用接口,用于子类实现不同的限流策略
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所有限流器都必须实现 can_call、reset 方法
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"""
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def __init__(self, source: str = "", enable_logging: bool = True):
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"""
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初始化 BaseRateLimiter 实例
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:param source: 业务来源或上下文信息,默认为空字符串
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:param enable_logging: 是否启用日志记录,默认为 True
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"""
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self.source = source
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self.enable_logging = enable_logging
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self.lock = threading.Lock()
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@property
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def reset_on_success(self) -> bool:
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"""
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是否在成功调用后自动重置限流器状态,默认为 False
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"""
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return False
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def can_call(self) -> Tuple[bool, str]:
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"""
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检查是否可以进行调用
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:return: 如果允许调用,返回 True 和空消息,否则返回 False 和限流消息
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"""
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raise NotImplementedError
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def reset(self):
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"""
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重置限流状态
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"""
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raise NotImplementedError
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def trigger_limit(self):
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"""
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触发限流
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"""
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pass
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def record_call(self):
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"""
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记录一次调用
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"""
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pass
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def format_log(self, message: str) -> str:
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"""
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格式化日志消息
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:param message: 日志内容
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:return: 格式化后的日志消息
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"""
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return f"[{self.source}] {message}" if self.source else message
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def log(self, level: str, message: str):
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"""
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根据日志级别记录日志
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:param level: 日志级别
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:param message: 日志内容
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"""
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if self.enable_logging:
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log_method = getattr(logger, level, None)
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if not callable(log_method):
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log_method = logger.info
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log_method(self.format_log(message))
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def log_info(self, message: str):
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"""
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记录信息日志
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"""
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self.log("info", message)
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def log_warning(self, message: str):
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"""
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记录警告日志
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"""
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self.log("warning", message)
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# 指数退避限流器
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class ExponentialBackoffRateLimiter(BaseRateLimiter):
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"""
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基于指数退避的限流器,用于处理单次调用频率的控制
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每次触发限流时,等待时间会成倍增加,直到达到最大等待时间
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"""
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def __init__(self, base_wait: float = 60.0, max_wait: float = 600.0, backoff_factor: float = 2.0,
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source: str = "", enable_logging: bool = True):
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"""
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初始化 ExponentialBackoffRateLimiter 实例
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:param base_wait: 基础等待时间(秒),默认值为 60 秒(1 分钟)
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:param max_wait: 最大等待时间(秒),默认值为 600 秒(10 分钟)
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:param backoff_factor: 等待时间的递增倍数,默认值为 2.0,表示指数退避
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:param source: 业务来源或上下文信息,默认值为 ""
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:param enable_logging: 是否启用日志记录,默认为 True
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"""
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super().__init__(source, enable_logging)
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self.next_allowed_time = 0.0
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self.current_wait = base_wait
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self.base_wait = base_wait
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self.max_wait = max_wait
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self.backoff_factor = backoff_factor
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self.source = source
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@property
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def reset_on_success(self) -> bool:
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"""
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指数退避限流器在调用成功后应重置等待时间
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"""
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return True
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def can_call(self) -> Tuple[bool, str]:
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"""
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检查是否可以进行调用,如果当前时间超过下一次允许调用的时间,则允许调用
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:return: 如果允许调用,返回 True 和空消息,否则返回 False 和限流消息
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"""
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current_time = time.time()
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with self.lock:
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if current_time >= self.next_allowed_time:
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return True, ""
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wait_time = self.next_allowed_time - current_time
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message = f"限流期间,跳过调用,将在 {wait_time:.2f} 秒后允许继续调用"
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self.log_info(message)
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return False, self.format_log(message)
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def reset(self):
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"""
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重置等待时间
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当调用成功时调用此方法,重置当前等待时间为基础等待时间
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"""
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with self.lock:
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if self.next_allowed_time != 0 or self.current_wait > self.base_wait:
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self.log_info(f"调用成功,重置限流等待时间为 {self.base_wait} 秒")
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self.next_allowed_time = 0.0
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self.current_wait = self.base_wait
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def trigger_limit(self):
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"""
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触发限流
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当触发限流异常时调用此方法,增加下一次允许调用的时间并更新当前等待时间
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"""
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current_time = time.time()
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with self.lock:
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self.next_allowed_time = current_time + self.current_wait
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self.current_wait = min(self.current_wait * self.backoff_factor, self.max_wait)
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wait_time = self.next_allowed_time - current_time
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self.log_warning(f"触发限流,将在 {wait_time:.2f} 秒后允许继续调用")
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# 时间窗口限流器
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class WindowRateLimiter(BaseRateLimiter):
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"""
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基于时间窗口的限流器,用于限制在特定时间窗口内的调用次数
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如果超过允许的最大调用次数,则限流直到窗口期结束
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"""
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def __init__(self, max_calls: int, window_seconds: float,
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source: str = "", enable_logging: bool = True):
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"""
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初始化 WindowRateLimiter 实例
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:param max_calls: 在时间窗口内允许的最大调用次数
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:param window_seconds: 时间窗口的持续时间(秒)
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:param source: 业务来源或上下文信息,默认值为 ""
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:param enable_logging: 是否启用日志记录,默认为 True
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"""
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super().__init__(source, enable_logging)
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self.max_calls = max_calls
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self.window_seconds = window_seconds
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self.call_times = deque()
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def can_call(self) -> Tuple[bool, str]:
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"""
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检查是否可以进行调用,如果在时间窗口内的调用次数少于最大允许次数,则允许调用。
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:return: 如果允许调用,返回 True 和空消息,否则返回 False 和限流消息
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"""
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current_time = time.time()
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with self.lock:
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# 清理超出时间窗口的调用记录
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while self.call_times and current_time - self.call_times[0] > self.window_seconds:
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self.call_times.popleft()
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if len(self.call_times) < self.max_calls:
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return True, ""
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else:
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wait_time = self.window_seconds - (current_time - self.call_times[0])
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message = f"限流期间,跳过调用,将在 {wait_time:.2f} 秒后允许继续调用"
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self.log_info(message)
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return False, self.format_log(message)
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def reset(self):
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"""
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重置时间窗口内的调用记录
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当调用成功时调用此方法,清空时间窗口内的调用记录
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"""
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with self.lock:
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self.call_times.clear()
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def record_call(self):
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"""
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记录当前时间戳,用于限流检查
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"""
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current_time = time.time()
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with self.lock:
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self.call_times.append(current_time)
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# 组合限流器
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class CompositeRateLimiter(BaseRateLimiter):
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"""
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组合限流器,可以组合多个限流策略
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当任意一个限流策略触发限流时,都会阻止调用
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"""
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def __init__(self, limiters: List[BaseRateLimiter], source: str = "", enable_logging: bool = True):
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"""
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初始化 CompositeRateLimiter 实例
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:param limiters: 要组合的限流器列表
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:param source: 业务来源或上下文信息,默认值为 ""
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:param enable_logging: 是否启用日志记录,默认为 True
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"""
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super().__init__(source, enable_logging)
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self.limiters = limiters
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def can_call(self) -> Tuple[bool, str]:
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"""
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检查是否可以进行调用,当组合的任意限流器触发限流时,阻止调用。
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:return: 如果所有限流器都允许调用,返回 True 和空消息,否则返回 False 和限流信息。
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"""
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for limiter in self.limiters:
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can_call, message = limiter.can_call()
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if not can_call:
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return False, message
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return True, ""
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def reset(self):
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"""
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重置所有组合的限流器状态
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"""
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for limiter in self.limiters:
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limiter.reset()
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def record_call(self):
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"""
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记录所有组合的限流器的调用时间
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"""
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for limiter in self.limiters:
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limiter.record_call()
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# 通用装饰器:自定义限流器实例
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def rate_limit_handler(limiter: BaseRateLimiter, raise_on_limit: bool = False) -> Callable:
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"""
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通用装饰器,允许用户传递自定义的限流器实例,用于处理限流逻辑
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该装饰器可灵活支持任意继承自 BaseRateLimiter 的限流器
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:param limiter: 限流器实例,必须继承自 BaseRateLimiter
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:param raise_on_limit: 控制在限流时是否抛出异常,默认为 False
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:return: 装饰器函数
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"""
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def decorator(func: Callable) -> Callable:
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@functools.wraps(func)
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def wrapper(*args, **kwargs) -> Optional[Any]:
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# 检查是否传入了 "raise_exception" 参数,优先使用该参数,否则使用默认的 raise_on_limit 值
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raise_exception = kwargs.get("raise_exception", raise_on_limit)
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# 检查是否可以进行调用,调用 limiter.can_call() 方法
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can_call, message = limiter.can_call()
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if not can_call:
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# 如果调用受限,并且 raise_exception 为 True,则抛出限流异常
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if raise_exception:
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raise RateLimitExceededException(message)
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# 如果不抛出异常,则返回 None 表示跳过调用
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return None
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# 如果调用允许,执行目标函数,并记录一次调用
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try:
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result = func(*args, **kwargs)
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limiter.record_call()
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if limiter.reset_on_success:
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limiter.reset()
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return result
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except LimitException as e:
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# 如果目标函数触发了限流相关的异常,执行限流器的触发逻辑(如递增等待时间)
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limiter.trigger_limit()
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logger.error(limiter.format_log(f"触发限流:{str(e)}"))
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# 如果 raise_exception 为 True,则抛出异常,否则返回 None
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if raise_exception:
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raise e
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return None
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@functools.wraps(func)
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async def async_wrapper(*args, **kwargs) -> Optional[Any]:
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# 检查是否传入了 "raise_exception" 参数,优先使用该参数,否则使用默认的 raise_on_limit 值
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raise_exception = kwargs.get("raise_exception", raise_on_limit)
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# 检查是否可以进行调用,调用 limiter.can_call() 方法
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can_call, message = limiter.can_call()
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if not can_call:
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# 如果调用受限,并且 raise_exception 为 True,则抛出限流异常
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if raise_exception:
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raise RateLimitExceededException(message)
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# 如果不抛出异常,则返回 None 表示跳过调用
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return None
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# 如果调用允许,执行目标函数,并记录一次调用
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try:
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result = await func(*args, **kwargs)
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limiter.record_call()
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if limiter.reset_on_success:
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limiter.reset()
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return result
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except LimitException as e:
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# 如果目标函数触发了限流相关的异常,执行限流器的触发逻辑(如递增等待时间)
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limiter.trigger_limit()
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logger.error(limiter.format_log(f"触发限流:{str(e)}"))
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# 如果 raise_exception 为 True,则抛出异常,否则返回 None
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if raise_exception:
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raise e
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return None
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# 根据函数类型返回相应的包装器
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if inspect.iscoroutinefunction(func):
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return async_wrapper
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else:
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return wrapper
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return decorator
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# 装饰器:指数退避限流
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def rate_limit_exponential(base_wait: float = 60.0, max_wait: float = 600.0, backoff_factor: float = 2.0,
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raise_on_limit: bool = False, source: str = "", enable_logging: bool = True) -> Callable:
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"""
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装饰器,用于应用指数退避限流策略
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通过逐渐增加调用等待时间控制调用频率。每次触发限流时,等待时间会成倍增加,直到达到最大等待时间
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:param base_wait: 基础等待时间(秒),默认值为 60 秒(1 分钟)
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:param max_wait: 最大等待时间(秒),默认值为 600 秒(10 分钟)
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:param backoff_factor: 等待时间递增的倍数,默认值为 2.0,表示指数退避
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:param raise_on_limit: 控制在限流时是否抛出异常,默认为 False
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:param source: 业务来源或上下文信息,默认为空字符串
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:param enable_logging: 是否启用日志记录,默认为 True
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:return: 装饰器函数
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"""
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# 实例化 ExponentialBackoffRateLimiter,并传入相关参数
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limiter = ExponentialBackoffRateLimiter(base_wait, max_wait, backoff_factor, source, enable_logging)
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# 使用通用装饰器逻辑包装该限流器
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return rate_limit_handler(limiter, raise_on_limit)
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# 装饰器:时间窗口限流
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def rate_limit_window(max_calls: int, window_seconds: float,
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raise_on_limit: bool = False, source: str = "", enable_logging: bool = True) -> Callable:
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"""
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装饰器,用于应用时间窗口限流策略
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在固定的时间窗口内限制调用次数,当调用次数超过最大值时,触发限流,直到时间窗口结束
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:param max_calls: 时间窗口内允许的最大调用次数
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:param window_seconds: 时间窗口的持续时间(秒)
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:param raise_on_limit: 控制在限流时是否抛出异常,默认为 False
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:param source: 业务来源或上下文信息,默认为空字符串
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:param enable_logging: 是否启用日志记录,默认为 True
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:return: 装饰器函数
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"""
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# 实例化 WindowRateLimiter,并传入相关参数
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limiter = WindowRateLimiter(max_calls, window_seconds, source, enable_logging)
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# 使用通用装饰器逻辑包装该限流器
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return rate_limit_handler(limiter, raise_on_limit)
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class QpsRateLimiter:
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"""
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速率控制器,精确控制 QPS
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"""
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def __init__(self, qps: float | int):
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if qps <= 0:
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qps = float("inf")
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self.interval = 1.0 / qps
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self.lock = threading.Lock()
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self.next_call_time = time.monotonic()
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def acquire(self) -> None:
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"""
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获取调用许可,阻塞直到满足速率限制
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"""
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sleep_duration = 0
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with self.lock:
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now = time.monotonic()
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sleep_duration = self.next_call_time - now
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self.next_call_time = max(now, self.next_call_time) + self.interval
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if sleep_duration > 0:
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time.sleep(sleep_duration)
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