mirror of
https://github.com/jxxghp/MoviePilot.git
synced 2026-06-15 20:51:07 +08:00
96 lines
3.8 KiB
Python
96 lines
3.8 KiB
Python
import asyncio
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from typing import Generator
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from unittest.mock import AsyncMock, patch
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import pytest
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from app.chain.recommend import RecommendChain
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from app.core.cache import TTLCache
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SYNC_EMPTY_CACHE_CASES = [
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("tmdb_movies", "app.chain.recommend.TmdbChain", "tmdb_discover"),
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("tmdb_tvs", "app.chain.recommend.TmdbChain", "tmdb_discover"),
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("tmdb_trending", "app.chain.recommend.TmdbChain", "tmdb_trending"),
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("bangumi_calendar", "app.chain.recommend.BangumiChain", "calendar"),
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("douban_movie_showing", "app.chain.recommend.DoubanChain", "movie_showing"),
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("douban_movies", "app.chain.recommend.DoubanChain", "douban_discover"),
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("douban_tvs", "app.chain.recommend.DoubanChain", "douban_discover"),
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("douban_movie_top250", "app.chain.recommend.DoubanChain", "movie_top250"),
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("douban_tv_weekly_chinese", "app.chain.recommend.DoubanChain", "tv_weekly_chinese"),
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("douban_tv_weekly_global", "app.chain.recommend.DoubanChain", "tv_weekly_global"),
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("douban_tv_animation", "app.chain.recommend.DoubanChain", "tv_animation"),
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("douban_movie_hot", "app.chain.recommend.DoubanChain", "movie_hot"),
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("douban_tv_hot", "app.chain.recommend.DoubanChain", "tv_hot"),
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]
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ASYNC_EMPTY_CACHE_CASES = [
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("async_tmdb_movies", "app.chain.recommend.TmdbChain"),
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("async_tmdb_tvs", "app.chain.recommend.TmdbChain"),
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("async_tmdb_trending", "app.chain.recommend.TmdbChain"),
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("async_bangumi_calendar", "app.chain.recommend.BangumiChain"),
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("async_douban_movie_showing", "app.chain.recommend.DoubanChain"),
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("async_douban_movies", "app.chain.recommend.DoubanChain"),
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("async_douban_tvs", "app.chain.recommend.DoubanChain"),
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("async_douban_movie_top250", "app.chain.recommend.DoubanChain"),
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("async_douban_tv_weekly_chinese", "app.chain.recommend.DoubanChain"),
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("async_douban_tv_weekly_global", "app.chain.recommend.DoubanChain"),
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("async_douban_tv_animation", "app.chain.recommend.DoubanChain"),
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("async_douban_movie_hot", "app.chain.recommend.DoubanChain"),
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("async_douban_tv_hot", "app.chain.recommend.DoubanChain"),
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]
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def clear_recommend_cache() -> None:
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"""清理推荐缓存，避免缓存装饰器状态影响用例。"""
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TTLCache(region=RecommendChain.recommend_cache_region).clear()
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@pytest.fixture(autouse=True)
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def isolated_recommend_cache() -> Generator[None, None, None]:
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"""每个用例前后都清空推荐缓存。"""
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clear_recommend_cache()
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yield
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clear_recommend_cache()
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@pytest.mark.parametrize(
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("method_name", "chain_target", "backend_method"),
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SYNC_EMPTY_CACHE_CASES,
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)
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def test_sync_recommend_methods_do_not_cache_empty_result(
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method_name: str,
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chain_target: str,
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backend_method: str,
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) -> None:
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"""同步推荐来源返回空列表时不应缓存。"""
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chain = RecommendChain()
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recommend_method = getattr(chain, method_name)
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with patch(chain_target) as backend_chain:
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backend_call = getattr(backend_chain.return_value, backend_method)
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backend_call.side_effect = [[], []]
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assert recommend_method(page=1) == []
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assert recommend_method(page=1) == []
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assert backend_call.call_count == 2
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@pytest.mark.parametrize(("method_name", "chain_target"), ASYNC_EMPTY_CACHE_CASES)
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def test_async_recommend_methods_do_not_cache_empty_result(
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method_name: str,
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chain_target: str,
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) -> None:
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"""异步推荐来源返回空列表时不应缓存。"""
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chain = RecommendChain()
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recommend_method = getattr(chain, method_name)
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with patch(chain_target) as backend_chain:
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backend_chain.return_value.async_run_module = AsyncMock(side_effect=[[], []])
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assert asyncio.run(recommend_method(page=1)) == []
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assert asyncio.run(recommend_method(page=1)) == []
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assert backend_chain.return_value.async_run_module.call_count == 2
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