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feat(cache): add cache backend implementations and decorator support
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320
app/core/cache.py
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320
app/core/cache.py
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import inspect
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import os
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from abc import ABC, abstractmethod
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from collections import defaultdict
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from functools import wraps
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from typing import Any, Dict, Optional
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import redis
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from cachetools import TTLCache
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from cachetools.keys import hashkey
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class CacheBackend(ABC):
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"""
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缓存后端基类，定义通用的缓存接口
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"""
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@abstractmethod
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def set(self, key: str, value: Any, ttl: int, region: str = "default", **kwargs) -> None:
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"""
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设置缓存
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:param key: 缓存的键
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:param value: 缓存的值
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:param ttl: 缓存的存活时间，单位秒
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:param region: 缓存的区
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:param kwargs: 其他参数
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"""
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pass
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@abstractmethod
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def get(self, key: str, region: str = "default") -> Any:
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"""
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获取缓存
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:param key: 缓存的键
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:param region: 缓存的区
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:return: 返回缓存的值，如果缓存不存在返回 None
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"""
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pass
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@abstractmethod
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def delete(self, key: str, region: str = "default") -> None:
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"""
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删除缓存
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:param key: 缓存的键
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:param region: 缓存的区
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"""
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pass
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@abstractmethod
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def clear(self, region: Optional[str] = None) -> None:
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"""
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清除指定区域的缓存或全部缓存
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:param region: 缓存的区
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"""
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pass
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@staticmethod
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def get_region(region: str = "default"):
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"""
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获取缓存的区
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"""
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return f"region:{region}" if region else "region:default"
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class CacheToolsBackend(CacheBackend):
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"""
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基于 `cachetools.TTLCache` 实现的缓存后端，支持动态 TTL 和 Maxsize
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"""
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def __init__(self, maxsize: int = 1000, ttl: int = 1800):
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"""
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初始化缓存实例
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:param maxsize: 缓存的最大条目数
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:param ttl: 默认缓存存活时间，单位秒
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"""
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self.maxsize = maxsize
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self.ttl = ttl
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# 存储各个 region 的缓存实例，region -> {key -> TTLCache}
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self._region_caches: Dict[str, Dict[str, TTLCache]] = defaultdict(dict)
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def set(self, key: str, value: Any, ttl: int = None, region: str = "default", **kwargs) -> None:
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"""
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设置缓存值支持每个 key 独立配置 TTL 和 Maxsize
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:param key: 缓存的键
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:param value: 缓存的值
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:param ttl: 缓存的存活时间，单位秒如果未传入则使用默认值
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:param region: 缓存的区
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:param kwargs: maxsize: 缓存的最大条目数如果未传入则使用默认值
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"""
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ttl = ttl or self.ttl
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maxsize = kwargs.get("maxsize", self.maxsize)
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region = self.get_region(region)
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# 如果该 key 尚未有缓存实例，则创建一个新的 TTLCache 实例
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region_cache = self._region_caches[region]
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if key not in region_cache:
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region_cache[key] = TTLCache(maxsize=maxsize, ttl=ttl)
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# 为每个 key 获取独立的缓存实例
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cache = region_cache[key]
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# 设置缓存值
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cache[key] = value
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def get(self, key: str, region: str = "default") -> Any:
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"""
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获取缓存的值
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:param key: 缓存的键
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:param region: 缓存的区
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:return: 返回缓存的值，如果缓存不存在返回 None
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"""
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region = self.get_region(region)
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region_cache = self._region_caches[region]
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if key not in region_cache:
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return None
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# 获取缓存实例并返回缓存值
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cache = region_cache[key]
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return cache.get(key)
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def delete(self, key: str, region: str = "default") -> None:
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"""
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删除缓存
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:param key: 缓存的键
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:param region: 缓存的区
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"""
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region = self.get_region(region)
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region_cache = self._region_caches[region]
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if key not in region_cache:
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return None
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# 获取缓存实例并删除指定的缓存
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cache = region_cache[key]
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del cache[key]
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def clear(self, region: Optional[str] = None) -> None:
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"""
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清除指定区域的缓存或全部缓存
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:param region: 缓存的区
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"""
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if region:
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region_cache = self._region_caches[region]
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for cache in region_cache.values():
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cache.clear()
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else:
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for region_cache in self._region_caches.values():
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for cache in region_cache.values():
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cache.clear()
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class RedisBackend(CacheBackend):
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"""
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基于 Redis 实现的缓存后端，支持通过 Redis 存储缓存
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"""
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def __init__(self, redis_url: str = "redis://localhost", ttl: int = 1800):
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"""
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初始化 Redis 缓存实例
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:param redis_url: Redis 服务的 URL
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:param ttl: 缓存的存活时间，单位秒
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"""
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self.redis_url = redis_url
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self.ttl = ttl
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self.client = redis.StrictRedis.from_url(redis_url)
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@staticmethod
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def get_redis_key(region, key):
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"""
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获取缓存 Key
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"""
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# 使用 region 作为缓存键的一部分
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return f"region:{region}:key:{key}"
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def set(self, key: str, value: Any, ttl: int = None, region: str = "default", **kwargs) -> None:
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"""
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设置缓存
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:param key: 缓存的键
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:param value: 缓存的值
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:param ttl: 缓存的存活时间，单位秒如果未传入则使用默认值
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:param region: 缓存的区
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:param kwargs: kwargs
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"""
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ttl = ttl or self.ttl
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redis_key = self.get_redis_key(region, key)
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self.client.setex(redis_key, ttl, value)
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def get(self, key: str, region: str = "default") -> Any:
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"""
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获取缓存的值
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:param key: 缓存的键
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:param region: 缓存的区
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:return: 返回缓存的值，如果缓存不存在返回 None
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"""
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redis_key = self.get_redis_key(region, key)
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value = self.client.get(redis_key)
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return value
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def delete(self, key: str, region: str = "default") -> None:
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"""
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删除缓存
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:param key: 缓存的键
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:param region: 缓存的区
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"""
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redis_key = self.get_redis_key(region, key)
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self.client.delete(redis_key)
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def clear(self, region: Optional[str] = None) -> None:
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"""
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清除 Redis 中指定区域的缓存或全部缓存
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:param region: 缓存的区
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"""
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if region:
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# 清除指定区域的所有键
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pattern = f"{region}:*"
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keys = list(self.client.keys(pattern))
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if keys:
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self.client.delete(*keys)
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else:
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# 清除所有缓存
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self.client.flushdb()
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def get_cache_backend(maxsize: int = 1000, ttl: int = 1800) -> CacheBackend:
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"""
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根据配置获取缓存后端实例
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:param maxsize: 缓存的最大条目数
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:param ttl: 缓存的默认存活时间，单位秒
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:return: 返回缓存后端实例
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"""
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cache_type = os.getenv("CACHE_TYPE", "cachetools").lower()
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if cache_type == "redis":
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return RedisBackend(redis_url=os.getenv("REDIS_URL", "redis://localhost"))
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return CacheToolsBackend(maxsize=maxsize, ttl=ttl)
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# 缓存后端实例
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cache_backend = get_cache_backend()
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def cached(region: str = "default", maxsize: int = 1000, ttl: int = 1800,
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skip_none: bool = True, skip_empty: bool = True):
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"""
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自定义缓存装饰器，支持为每个 key 动态传递 maxsize 和 ttl
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:param region: 缓存的区
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:param maxsize: 缓存的最大条目数，默认值为 1000
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:param ttl: 缓存的存活时间，单位秒，默认值为 1800
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:param skip_none: 跳过 None 缓存，默认为 True
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:param skip_empty: 跳过空值缓存（如 [], {}, "", set()），默认为 True
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:return: 装饰器函数
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"""
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def should_cache(value: Any) -> bool:
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"""
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判断是否应该缓存结果，如果返回值是 None 或空值则不缓存
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:param value: 要判断的缓存值
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:return: 是否缓存结果
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"""
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if skip_none and value is None:
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return False
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# if disable_empty and value in [[], {}, "", set()]:
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if skip_empty and not value:
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return False
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return True
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def get_cache_key(func, args, kwargs):
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"""
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获取缓存的键，通过哈希函数对函数的参数进行处理
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:param func: 被装饰的函数
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:param args: 位置参数
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:param kwargs: 关键字参数
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:return: 缓存键
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"""
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# 获取方法签名
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signature = inspect.signature(func)
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resolved_kwargs = {}
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# 获取默认值并结合传递的参数（如果有）
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for param, value in signature.parameters.items():
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if param in kwargs:
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# 使用显式传递的参数
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resolved_kwargs[param] = kwargs[param]
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elif value.default is not inspect.Parameter.empty:
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# 没有传递参数时使用默认值
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resolved_kwargs[param] = value.default
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# 构造缓存键
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return f"{func.__name__}_{hashkey(*args, **resolved_kwargs)}"
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def decorator(func):
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@wraps(func)
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def wrapper(*args, **kwargs):
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# 获取缓存键
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cache_key = get_cache_key(func, args, kwargs)
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# 尝试获取缓存
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cached_value = cache_backend.get(cache_key, region=region)
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if should_cache(cached_value):
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return cached_value
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# 执行函数并缓存结果
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result = func(*args, **kwargs)
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# 判断是否需要缓存
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if not should_cache(result):
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return result
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# 设置缓存（如果有传入的 maxsize 和 ttl，则覆盖默认值）
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cache_backend.set(cache_key, result, ttl=ttl, maxsize=maxsize, region=region)
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return result
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return wrapper
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return decorator
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