AI掘金头条新闻系统 (Toutiao News)-缓存相关推荐新闻

1. cache/news_cache.py

RELATED_NEWS_PREFIX = "news:related:"

# 写入缓存-相关新闻 key = news:related:新闻id:分类id + 相关新闻列表 + 过期时间
async def cache_related_news(news_id: int, category_id: int, related_list: List[Dict[str, Any]], expire: int = 1800) -> bool:
    key = f"{RELATED_NEWS_PREFIX}{news_id}:{category_id}"
    return await set_cache(key, related_list, expire)


# 读取缓存-相关新闻 key = news:related:新闻id:分类id
async def get_cached_related_news(news_id: int, category_id: int) -> Optional[List[Dict[str, Any]]]:
    key = f"{RELATED_NEWS_PREFIX}{news_id}:{category_id}"
    return await get_json_cache(key)

2. 改造crud/news.py

# 获取相关推荐新闻
async def get_related_news(db: AsyncSession, news_id: int, category_id: int, limit: int = 5):
    # 先尝试从缓存获取相关新闻
    cached_related = await get_cached_related_news(news_id, category_id)
    if cached_related:
        return cached_related

    # 查询数据库
    stmt = (
        select(News)
        .where(
            News.id != news_id,
            News.category_id == category_id
        )
        .order_by(
            News.views.desc(),
            News.publish_time.desc()
        )
        .limit(limit)
    )

    result = await db.execute(stmt)
    related_news = result.scalars().all()

    related_list = [
        {
            "id": item.id,
            "title": item.title,
            "content": item.content,
            "image": item.image,
            "author": item.author,
            "publishTime": item.publish_time,
            "categoryId": item.category_id,
            "views": item.views
        }
        for item in related_news
    ]

    # 写入缓存
    if related_list:
        await cache_related_news(news_id, category_id, related_list)

    return related_list