import io import tempfile from pathlib import Path from typing import List, Optional import pillow_avif # noqa 用于自动注册AVIF支持 from PIL import Image 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 from app.utils.common import log_execution_time from app.utils.http import RequestUtils from app.utils.security import SecurityUtils from app.utils.singleton import Singleton # 推荐相关的专用缓存 recommend_ttl = 24 * 3600 recommend_cache_region = "recommend" class RecommendChain(ChainBase, metaclass=Singleton): """ 推荐处理链，单例运行 """ # 推荐数据的缓存页数 cache_max_pages = 5 def refresh_recommend(self): """ 刷新推荐 """ logger.debug("Starting to refresh Recommend data.") cache_backend.clear(region=recommend_cache_region) logger.debug("Recommend Cache has been cleared.") # 推荐来源方法 recommend_methods = [ self.tmdb_movies, self.tmdb_tvs, self.tmdb_trending, self.bangumi_calendar, self.douban_movie_showing, self.douban_movies, self.douban_tvs, self.douban_movie_top250, self.douban_tv_weekly_chinese, self.douban_tv_weekly_global, self.douban_tv_animation, self.douban_movie_hot, self.douban_tv_hot, ] # 缓存并刷新所有推荐数据 recommends = [] # 记录哪些方法已完成 methods_finished = set() # 这里避免区间内连续调用相同来源，因此遍历方案为每页遍历所有推荐来源，再进行页数遍历 for page in range(1, self.cache_max_pages + 1): for method in recommend_methods: if global_vars.is_system_stopped: return if method in methods_finished: continue logger.debug(f"Fetch {method.__name__} data for page {page}.") data = method(page=page) if not data: logger.debug("All recommendation methods have finished fetching data. Ending pagination early.") methods_finished.add(method) continue recommends.extend(data) # 如果所有方法都已经完成，提前结束循环 if len(methods_finished) == len(recommend_methods): break # 缓存收集到的海报 self.__cache_posters(recommends) logger.debug("Recommend data refresh completed.") def __cache_posters(self, datas: List[dict]): """ 提取 poster_path 并缓存图片 :param datas: 数据列表 """ if not settings.GLOBAL_IMAGE_CACHE: return for data in datas: if global_vars.is_system_stopped: return poster_path = data.get("poster_path") if poster_path: poster_url = poster_path.replace("original", "w500") logger.debug(f"Caching poster image: {poster_url}") self.__fetch_and_save_image(poster_url) @staticmethod def __fetch_and_save_image(url: str): """ 请求并保存图片 :param url: 图片路径 """ if not settings.GLOBAL_IMAGE_CACHE or not url: return # 生成缓存路径 sanitized_path = SecurityUtils.sanitize_url_path(url) cache_path = settings.CACHE_PATH / "images" / sanitized_path # 没有文件类型，则添加后缀，在恶意文件类型和实际需求下的折衷选择 if not cache_path.suffix: cache_path = cache_path.with_suffix(".jpg") # 确保缓存路径和文件类型合法 if not SecurityUtils.is_safe_path(settings.CACHE_PATH, cache_path, settings.SECURITY_IMAGE_SUFFIXES): logger.debug(f"Invalid cache path or file type for URL: {url}, sanitized path: {sanitized_path}") return # 本地存在缓存图片，则直接跳过 if cache_path.exists(): logger.debug(f"Cache hit: Image already exists at {cache_path}") return # 请求远程图片 referer = "https://movie.douban.com/" if "doubanio.com" in url else None proxies = settings.PROXY if not referer else None response = RequestUtils(ua=settings.NORMAL_USER_AGENT, proxies=proxies, referer=referer).get_res(url=url) if not response: logger.debug(f"Empty response for URL: {url}") return # 验证下载的内容是否为有效图片 try: Image.open(io.BytesIO(response.content)).verify() except Exception as e: logger.debug(f"Invalid image format for URL {url}: {e}") return if not cache_path: return try: if not cache_path.parent.exists(): cache_path.parent.mkdir(parents=True, exist_ok=True) with tempfile.NamedTemporaryFile(dir=cache_path.parent, delete=False) as tmp_file: tmp_file.write(response.content) temp_path = Path(tmp_file.name) temp_path.replace(cache_path) logger.debug(f"Successfully cached image at {cache_path} for URL: {url}") except Exception as e: logger.debug(f"Failed to write cache file {cache_path} for URL {url}: {e}") @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def tmdb_movies(self, sort_by: Optional[str] = "popularity.desc", with_genres: Optional[str] = "", with_original_language: Optional[str] = "", with_keywords: Optional[str] = "", with_watch_providers: Optional[str] = "", vote_average: Optional[float] = 0.0, vote_count: Optional[int] = 0, release_date: Optional[str] = "", page: Optional[int] = 1) -> List[dict]: """ TMDB热门电影 """ movies = TmdbChain().tmdb_discover(mtype=MediaType.MOVIE, sort_by=sort_by, with_genres=with_genres, with_original_language=with_original_language, with_keywords=with_keywords, with_watch_providers=with_watch_providers, vote_average=vote_average, vote_count=vote_count, release_date=release_date, page=page) return [movie.to_dict() for movie in movies] if movies else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def tmdb_tvs(self, sort_by: Optional[str] = "popularity.desc", with_genres: Optional[str] = "", with_original_language: Optional[str] = "zh|en|ja|ko", with_keywords: Optional[str] = "", with_watch_providers: Optional[str] = "", vote_average: Optional[float] = 0.0, vote_count: Optional[int] = 0, release_date: Optional[str] = "", page: Optional[int] = 1) -> List[dict]: """ TMDB热门电视剧 """ tvs = TmdbChain().tmdb_discover(mtype=MediaType.TV, sort_by=sort_by, with_genres=with_genres, with_original_language=with_original_language, with_keywords=with_keywords, with_watch_providers=with_watch_providers, vote_average=vote_average, vote_count=vote_count, release_date=release_date, page=page) return [tv.to_dict() for tv in tvs] if tvs else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def tmdb_trending(self, page: Optional[int] = 1) -> List[dict]: """ TMDB流行趋势 """ infos = TmdbChain().tmdb_trending(page=page) return [info.to_dict() for info in infos] if infos else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def bangumi_calendar(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ Bangumi每日放送 """ medias = BangumiChain().calendar() return [media.to_dict() for media in medias[(page - 1) * count: page * count]] if medias else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_movie_showing(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣正在热映 """ movies = DoubanChain().movie_showing(page=page, count=count) return [media.to_dict() for media in movies] if movies else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_movies(self, sort: Optional[str] = "R", tags: Optional[str] = "", page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣最新电影 """ movies = DoubanChain().douban_discover(mtype=MediaType.MOVIE, sort=sort, tags=tags, page=page, count=count) return [media.to_dict() for media in movies] if movies else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_tvs(self, sort: Optional[str] = "R", tags: Optional[str] = "", page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣最新电视剧 """ tvs = DoubanChain().douban_discover(mtype=MediaType.TV, sort=sort, tags=tags, page=page, count=count) return [media.to_dict() for media in tvs] if tvs else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_movie_top250(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣电影TOP250 """ movies = DoubanChain().movie_top250(page=page, count=count) return [media.to_dict() for media in movies] if movies else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_tv_weekly_chinese(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣国产剧集榜 """ tvs = DoubanChain().tv_weekly_chinese(page=page, count=count) return [media.to_dict() for media in tvs] if tvs else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_tv_weekly_global(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣全球剧集榜 """ tvs = DoubanChain().tv_weekly_global(page=page, count=count) return [media.to_dict() for media in tvs] if tvs else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_tv_animation(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣热门动漫 """ tvs = DoubanChain().tv_animation(page=page, count=count) return [media.to_dict() for media in tvs] if tvs else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_movie_hot(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣热门电影 """ movies = DoubanChain().movie_hot(page=page, count=count) return [media.to_dict() for media in movies] if movies else [] @log_execution_time(logger=logger) @cached(ttl=recommend_ttl, region=recommend_cache_region) def douban_tv_hot(self, page: Optional[int] = 1, count: Optional[int] = 30) -> List[dict]: """ 豆瓣热门电视剧 """ tvs = DoubanChain().tv_hot(page=page, count=count) return [media.to_dict() for media in tvs] if tvs else []