feat(cache): add cache region support

app/chain/recommend.py

@@ -1,18 +1,15 @@
-import inspect
 import io
 import tempfile
-from functools import wraps
 from pathlib import Path
-from typing import Any, Callable, List
+from typing import Any, List
 
 from PIL import Image
-from cachetools import TTLCache
-from cachetools.keys import hashkey
 
 from app.chain import ChainBase
 from app.chain.bangumi import BangumiChain
 from app.chain.douban import DoubanChain
 from app.chain.tmdb import TmdbChain
+from app.core.cache import cache_backend, cached
 from app.core.config import settings, global_vars
 from app.log import logger
 from app.schemas import MediaType
@@ -23,42 +20,7 @@ from app.utils.singleton import Singleton
 
 # 推荐相关的专用缓存
 recommend_ttl = 24 * 3600
-recommend_cache = TTLCache(maxsize=256, ttl=recommend_ttl)
-
-
-# 推荐缓存装饰器，避免偶发网络获取数据为空时，页面由于缓存为空长时间渲染异常问题
-def cached_with_empty_check(func: Callable):
-    """
-    缓存装饰器，用于缓存函数的返回结果，仅在结果非空时进行缓存
-
-    :param func: 被装饰的函数
-    :return: 包装后的函数
-    """
-
-    @wraps(func)
-    def wrapper(*args, **kwargs):
-        signature = inspect.signature(func)
-        resolved_kwargs = {}
-        # 获取默认值并结合传递的参数（如果有）
-        for param, value in signature.parameters.items():
-            if param in kwargs:
-                # 使用显式传递的参数
-                resolved_kwargs[param] = kwargs[param]
-            elif value.default is not inspect.Parameter.empty:
-                # 没有传递参数时使用默认值
-                resolved_kwargs[param] = value.default
-        # 使用 cachetools 缓存，构造缓存键
-        cache_key = f"{func.__name__}_{hashkey(*args, **resolved_kwargs)}"
-        if cache_key in recommend_cache:
-            return recommend_cache[cache_key]
-        result = func(*args, **kwargs)
-        # 如果返回值为空，则不缓存
-        if result in [None, [], {}]:
-            return result
-        recommend_cache[cache_key] = result
-        return result
-
-    return wrapper
+recommend_cache_region = "recommend"
 
 
 class RecommendChain(ChainBase, metaclass=Singleton):
@@ -78,7 +40,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         刷新推荐
         """
         logger.debug("Starting to refresh Recommend data.")
-        recommend_cache.clear()
+        cache_backend.clear(region=recommend_cache_region)
         logger.debug("Recommend Cache has been cleared.")
 
         # 推荐来源方法
@@ -194,7 +156,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
             logger.debug(f"Failed to write cache file {cache_path} for URL {url}: {e}")
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def tmdb_movies(self, sort_by: str = "popularity.desc", with_genres: str = "",
                     with_original_language: str = "", page: int = 1) -> Any:
         """
@@ -208,7 +170,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [movie.to_dict() for movie in movies] if movies else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def tmdb_tvs(self, sort_by: str = "popularity.desc", with_genres: str = "",
                  with_original_language: str = "zh|en|ja|ko", page: int = 1) -> Any:
         """
@@ -222,7 +184,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [tv.to_dict() for tv in tvs] if tvs else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def tmdb_trending(self, page: int = 1) -> Any:
         """
         TMDB流行趋势
@@ -231,7 +193,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [info.to_dict() for info in infos] if infos else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def bangumi_calendar(self, page: int = 1, count: int = 30) -> Any:
         """
         Bangumi每日放送
@@ -240,7 +202,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in medias[(page - 1) * count: page * count]] if medias else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_movie_showing(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣正在热映
@@ -249,7 +211,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in movies] if movies else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_movies(self, sort: str = "R", tags: str = "", page: int = 1, count: int = 30) -> Any:
         """
         豆瓣最新电影
@@ -259,7 +221,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in movies] if movies else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_tvs(self, sort: str = "R", tags: str = "", page: int = 1, count: int = 30) -> Any:
         """
         豆瓣最新电视剧
@@ -269,7 +231,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in tvs] if tvs else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_movie_top250(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣电影TOP250
@@ -278,7 +240,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in movies] if movies else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_tv_weekly_chinese(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣国产剧集榜
@@ -287,7 +249,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in tvs] if tvs else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_tv_weekly_global(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣全球剧集榜
@@ -296,7 +258,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in tvs] if tvs else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_tv_animation(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣热门动漫
@@ -305,7 +267,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in tvs] if tvs else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_movie_hot(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣热门电影
@@ -314,7 +276,7 @@ class RecommendChain(ChainBase, metaclass=Singleton):
         return [media.to_dict() for media in movies] if movies else []
 
     @log_execution_time(logger=logger)
-    @cached_with_empty_check
+    @cached(maxsize=16, ttl=recommend_ttl, region=recommend_cache_region)
     def douban_tv_hot(self, page: int = 1, count: int = 30) -> Any:
         """
         豆瓣热门电视剧