import asyncio from typing import Generator from unittest.mock import AsyncMock, patch import pytest from app.chain.recommend import RecommendChain from app.core.cache import TTLCache SYNC_EMPTY_CACHE_CASES = [ ("tmdb_movies", "app.chain.recommend.TmdbChain", "tmdb_discover"), ("tmdb_tvs", "app.chain.recommend.TmdbChain", "tmdb_discover"), ("tmdb_trending", "app.chain.recommend.TmdbChain", "tmdb_trending"), ("bangumi_calendar", "app.chain.recommend.BangumiChain", "calendar"), ("douban_movie_showing", "app.chain.recommend.DoubanChain", "movie_showing"), ("douban_movies", "app.chain.recommend.DoubanChain", "douban_discover"), ("douban_tvs", "app.chain.recommend.DoubanChain", "douban_discover"), ("douban_movie_top250", "app.chain.recommend.DoubanChain", "movie_top250"), ("douban_tv_weekly_chinese", "app.chain.recommend.DoubanChain", "tv_weekly_chinese"), ("douban_tv_weekly_global", "app.chain.recommend.DoubanChain", "tv_weekly_global"), ("douban_tv_animation", "app.chain.recommend.DoubanChain", "tv_animation"), ("douban_movie_hot", "app.chain.recommend.DoubanChain", "movie_hot"), ("douban_tv_hot", "app.chain.recommend.DoubanChain", "tv_hot"), ] ASYNC_EMPTY_CACHE_CASES = [ ("async_tmdb_movies", "app.chain.recommend.TmdbChain"), ("async_tmdb_tvs", "app.chain.recommend.TmdbChain"), ("async_tmdb_trending", "app.chain.recommend.TmdbChain"), ("async_bangumi_calendar", "app.chain.recommend.BangumiChain"), ("async_douban_movie_showing", "app.chain.recommend.DoubanChain"), ("async_douban_movies", "app.chain.recommend.DoubanChain"), ("async_douban_tvs", "app.chain.recommend.DoubanChain"), ("async_douban_movie_top250", "app.chain.recommend.DoubanChain"), ("async_douban_tv_weekly_chinese", "app.chain.recommend.DoubanChain"), ("async_douban_tv_weekly_global", "app.chain.recommend.DoubanChain"), ("async_douban_tv_animation", "app.chain.recommend.DoubanChain"), ("async_douban_movie_hot", "app.chain.recommend.DoubanChain"), ("async_douban_tv_hot", "app.chain.recommend.DoubanChain"), ] def clear_recommend_cache() -> None: """清理推荐缓存,避免缓存装饰器状态影响用例。""" TTLCache(region=RecommendChain.recommend_cache_region).clear() @pytest.fixture(autouse=True) def isolated_recommend_cache() -> Generator[None, None, None]: """每个用例前后都清空推荐缓存。""" clear_recommend_cache() yield clear_recommend_cache() @pytest.mark.parametrize( ("method_name", "chain_target", "backend_method"), SYNC_EMPTY_CACHE_CASES, ) def test_sync_recommend_methods_do_not_cache_empty_result( method_name: str, chain_target: str, backend_method: str, ) -> None: """同步推荐来源返回空列表时不应缓存。""" chain = RecommendChain() recommend_method = getattr(chain, method_name) with patch(chain_target) as backend_chain: backend_call = getattr(backend_chain.return_value, backend_method) backend_call.side_effect = [[], []] assert recommend_method(page=1) == [] assert recommend_method(page=1) == [] assert backend_call.call_count == 2 @pytest.mark.parametrize(("method_name", "chain_target"), ASYNC_EMPTY_CACHE_CASES) def test_async_recommend_methods_do_not_cache_empty_result( method_name: str, chain_target: str, ) -> None: """异步推荐来源返回空列表时不应缓存。""" chain = RecommendChain() recommend_method = getattr(chain, method_name) with patch(chain_target) as backend_chain: backend_chain.return_value.async_run_module = AsyncMock(side_effect=[[], []]) assert asyncio.run(recommend_method(page=1)) == [] assert asyncio.run(recommend_method(page=1)) == [] assert backend_chain.return_value.async_run_module.call_count == 2