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+from typing import Optional
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+
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+
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+class DailyRankManagerUtils:
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+ """日榜管理工具类"""
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+
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+ # 默认权重配置
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+ DEFAULT_WEIGHTS = {
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+ "account_user_category_score": 1.0,
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+ "category_score": 1.0,
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+ "flow_ctl_decrease_score": 1.0,
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+ "i2i_recommend_score": 1.0,
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+ "view_count_rate_score": 1.0,
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+ "his_fission_open_rate_score": 1.0,
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+ "crawler_days_decrease_score": 1.0,
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+ "crawler_days_decrease_v2_score": 1.0,
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+ "similarity_score": 1.0,
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+ "publish_times_score": 1.0,
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+ }
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+
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+ @staticmethod
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+ def _build_where(
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+ rank_date: Optional[str] = None,
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+ gh_id: Optional[str] = None,
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+ account_name: Optional[str] = None,
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+ content_pool_type: Optional[str] = None,
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+ strategy: Optional[str] = None,
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+ ):
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+ """构建 WHERE 条件"""
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+ conds, params = [], []
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+
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+ if rank_date:
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+ conds.append("rank_date = %s")
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+ params.append(rank_date)
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+
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+ if gh_id:
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+ conds.append("gh_id = %s")
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+ params.append(gh_id)
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+
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+ if account_name:
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+ conds.append("account_name = %s")
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+ params.append(account_name)
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+
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+ if content_pool_type:
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+ conds.append("content_pool_type = %s")
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+ params.append(content_pool_type)
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+
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+ if strategy:
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+ conds.append("strategy = %s")
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+ params.append(strategy)
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+
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+ where_clause = " AND ".join(conds) if conds else "1=1"
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+ return where_clause, params
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+
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+ @staticmethod
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+ def _calculate_new_score(row: dict, weights: dict) -> float:
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+ """根据权重计算新分数"""
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+ new_score = 0.0
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+ for field, weight in weights.items():
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+ value = row.get(field)
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+ if value is not None:
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+ try:
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+ new_score += float(value) * float(weight)
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+ except (TypeError, ValueError):
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+ pass
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+ return new_score
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+
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+
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+class DailyRankManager(DailyRankManagerUtils):
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+ """日榜数据管理服务"""
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+
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+ def __init__(self, pool, data: dict):
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+ self.pool = pool
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+ self.data = data
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+
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+ async def query_daily_rank(self):
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+ """查询日榜数据（不分页，返回筛选条件下的全量数据）"""
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+ sort_by = self.data.get("sort_by", "new_score")
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+ sort_dir = self.data.get("sort_dir", "desc").lower()
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+
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+ # 过滤条件
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+ rank_date = self.data.get("rank_date")
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+ gh_id = self.data.get("gh_id")
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+ account_name = self.data.get("account_name")
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+ content_pool_type = self.data.get("content_pool_type")
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+ strategy = self.data.get("strategy")
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+
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+ # 权重配置
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+ weights = self.data.get("weights") or self.DEFAULT_WEIGHTS
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+
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+ # 构建 WHERE 子句
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+ where_clause, params = self._build_where(
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+ rank_date, gh_id, account_name, content_pool_type, strategy
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+ )
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+
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+ # 查询全量数据
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+ sql_list = f"""
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+ SELECT
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+ id, rank_date, account_name, gh_id, source_id,
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+ content_pool_type, strategy, title, score, category,
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+ account_user_category_score, category_score,
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+ flow_ctl_decrease_score, i2i_recommend_score,
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+ view_count_rate_score, his_fission_open_rate_score,
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+ crawler_days_decrease_score, crawler_days_decrease_v2_score, similarity_score,
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+ publish_times_score, source_log,
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+ create_timestamp, update_timestamp
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+ FROM long_articles_daily_rank
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+ WHERE {where_clause}
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+ ORDER BY score DESC
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+ LIMIT 1000
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+ """
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+ rows = await self.pool.async_fetch(query=sql_list, params=tuple(params))
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+
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+ # 计算新分数并添加到结果中
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+ items = []
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+ for r in rows:
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+ new_score = self._calculate_new_score(r, weights)
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+ items.append({**r, "new_score": new_score})
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+
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+ # 排序（在内存中排序，因为 new_score 是计算字段）
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+ sort_whitelist = {
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+ "id",
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+ "rank_date",
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+ "score",
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+ "new_score",
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+ "account_user_category_score",
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+ "category_score",
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+ "flow_ctl_decrease_score",
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+ "i2i_recommend_score",
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+ "view_count_rate_score",
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+ "his_fission_open_rate_score",
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+ "crawler_days_decrease_score",
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+ "crawler_days_decrease_v2_score",
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+ "similarity_score",
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+ "publish_times_score",
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+ }
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+ if sort_by in sort_whitelist:
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+ reverse = sort_dir == "desc"
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+ items.sort(
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+ key=lambda x: (
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+ x.get(sort_by) if x.get(sort_by) is not None else float("-inf")
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+ ),
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+ reverse=reverse,
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+ )
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+
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+ return {
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+ "total": len(items),
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+ "items": items,
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+ "weights": weights,
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+ }
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luojunhui