feat(feed): 按分类批量已读 + 标已读后弹出分类提示条
后端: - POST /me/reads/by-category:按 category + time window 批量标已读 - GET /me/reads/category-count:查多个分类的 24h 未读数 前端: - 标已读后,查该文章前 2 个 category 的 24h 未读数 - 每个有未读的 category 显示一行提示(独立全部已读/稍后再说按钮) - 全部已读走乐观更新,命中的 article 走累计 delay 滑出 - 过滤变化时清掉提示(上下文变了) - 8 秒自动消失
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xiaji
@@ -1,11 +1,13 @@
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"""/me 当前用户信息 + 翻译配额 + 已读文章。"""
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"""/me 当前用户信息 + 翻译配额 + 已读文章 + 按分类批量已读。"""
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from __future__ import annotations
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from datetime import datetime, timedelta, timezone
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from typing import Literal
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from fastapi import APIRouter, Depends, HTTPException, status
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from pydantic import BaseModel
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from sqlalchemy import and_, delete, select
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from fastapi import APIRouter, Depends, HTTPException, Query, status
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from pydantic import BaseModel, Field
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from sqlalchemy import and_, delete, func, not_, or_, select, text
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from sqlalchemy.dialects.postgresql import insert as pg_insert
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.config import settings
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@@ -13,6 +15,7 @@ from app.core.deps import get_current_user
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from app.database import get_session
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from app.models.article import Article
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from app.models.article_read import ArticleRead
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from app.models.source import Source
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from app.models.user import User
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from app.redis_client import get_redis
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@@ -95,7 +98,6 @@ async def mark_read(
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if not exists:
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raise HTTPException(status.HTTP_404_NOT_FOUND, "Article not found")
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# 用 INSERT ... ON CONFLICT DO NOTHING (PG 原生)— 等价 upsert 跳过
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from sqlalchemy.dialects.postgresql import insert as pg_insert
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stmt = pg_insert(ArticleRead).values(user_id=user.id, article_id=article_id).on_conflict_do_nothing(
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index_elements=["user_id", "article_id"]
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)
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@@ -142,3 +144,208 @@ async def list_reads(
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rows = (await session.execute(stmt)).all()
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ids = [r[0] for r in rows]
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return ReadListResponse(article_ids=ids, total=len(ids))
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# === 按分类批量已读(per-user) ===
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# 用例:用户在 Feed 标了一条《xxx》为已读,该文章 category 含 "美国" "社会" 两个 tag,
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# 前端会同时查这两个分类下"24 小时未读数"展示提示条,点头部的"全部已读"调本接口。
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# 设计要点:
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# - category 用 ilike 模糊匹配(Article.category 是逗号分隔字符串 '美国,社会,紧急')
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# - 默认遵守当前 Feed 过滤(关键词/源)— scope=filtered_unread,避免误杀
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# - 时间窗默认 24h(防"老新闻刷不完"的提示)
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# - 批量插入用 ON CONFLICT DO NOTHING,幂等
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# - 返回 article_ids 给前端做乐观滑出动画
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def _unread_subquery(user_id: int):
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"""未读文章 id 子查询(per-user)— 复用 articles.py 的 NOT EXISTS 模式。"""
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return (
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select(ArticleRead.article_id)
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.where(ArticleRead.user_id == user_id, ArticleRead.article_id == Article.id)
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.exists()
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)
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def _escape_like(term: str) -> str:
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"""转义 ilike 的元字符,避免 category 含 % / _ 时被当通配符。"""
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return term.replace("\\", "\\\\").replace("%", r"\%").replace("_", r"\_")
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class CategoryReadRequest(BaseModel):
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category: str = Field(..., min_length=1, max_length=32, description="要批量已读的分类 tag")
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scope: Literal["all_unread", "filtered_unread"] = Field(
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default="filtered_unread",
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description="过滤范围:filtered_unread=遵守 sources/q;all_unread=忽略",
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)
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window_hours: int = Field(
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default=24, ge=1, le=168, description="只标 published_at 在最近 N 小时内的未读"
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)
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sources: list[str] | None = Field(default=None, description="源 slug 列表,过滤范围")
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q: str | None = Field(default=None, description="关键词过滤(标题/正文模糊)")
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class CategoryReadResponse(BaseModel):
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category: str
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matched: int # 命中的未读数
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marked: int # 实际新标已读数(去重后)
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article_ids: list[int] # 给前端做滑出动画
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class CategoryCountItem(BaseModel):
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category: str
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unread_count: int
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window_hours: int
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def _build_category_filter(
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category: str,
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window_hours: int,
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user_id: int,
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sources: list[str] | None = None,
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q: str | None = None,
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):
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"""构造"分类 + 时间窗 + 未读"三合一 filter。
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- category 用 ilike 模糊匹配(逗号分隔串中含此 tag 即可)
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- window_hours 通过 published_at 过滤
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- 用 NOT EXISTS 排除当前用户已读
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- sources / q 可选,跟 articles.py 列表查询口径一致
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"""
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pattern = f"%{_escape_like(category)}%"
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# 用 text() 拼 interval,避免 make_interval 的 PG 函数参数绑定在某些
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# SQLAlchemy 版本下的兼容性问题。window_hours 是 int,只来自我们自己的
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# endpoint,不是用户原始字符串,安全。
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interval_sql = text(f"interval '{int(window_hours)} hours'")
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filters = [
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Article.category.ilike(pattern, escape="\\"),
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Article.published_at >= func.now() - interval_sql,
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not_(_unread_subquery(user_id)),
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]
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if sources:
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slugs = [s.strip() for s in sources if s.strip()]
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if slugs:
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filters.append(Source.slug.in_(slugs))
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if q and q.strip():
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like = f"%{q.strip()}%"
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filters.append(
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or_(
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Article.title.ilike(like),
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Article.body_text.ilike(like),
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Article.title_zh.ilike(like),
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Article.body_zh_text.ilike(like),
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Article.summary_zh.ilike(like),
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)
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)
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return filters
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@router.post("/reads/by-category", response_model=CategoryReadResponse)
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async def mark_category_read(
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body: CategoryReadRequest,
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user: User = Depends(get_current_user),
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session: AsyncSession = Depends(get_session),
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):
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"""按分类批量已读。
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- 默认 scope=filtered_unread:只在当前 Feed 过滤范围内标
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- 时间窗默认 24h:防"老新闻刷不完"
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- 幂等:已读的不重复处理
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"""
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cat = body.category.strip()
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if not cat:
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raise HTTPException(status.HTTP_400_BAD_REQUEST, "category 不能为空")
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# scope=all_unread 时,无视 sources/q(传了也忽略,语义更清晰)
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if body.scope == "all_unread":
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eff_sources: list[str] | None = None
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eff_q: str | None = None
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else:
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eff_sources = body.sources
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eff_q = body.q
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filters = _build_category_filter(
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category=cat,
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window_hours=body.window_hours,
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user_id=user.id,
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sources=eff_sources,
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q=eff_q,
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)
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# 1. 查命中 id 列表(返回给前端)
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id_stmt = select(Article.id)
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# sources 过滤需要 join
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if eff_sources:
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id_stmt = id_stmt.join(Source, Source.id == Article.source_id)
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for f in filters:
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id_stmt = id_stmt.where(f)
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article_ids = [r[0] for r in (await session.execute(id_stmt)).all()]
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if not article_ids:
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return CategoryReadResponse(category=cat, matched=0, marked=0, article_ids=[])
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# 2. 批量插入 article_reads(ON CONFLICT DO NOTHING,幂等)
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# 分批:防御性,避免单次 VALUES 太多;500 是经验值,PG 完全能吃更大
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BATCH = 500
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marked_total = 0
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for i in range(0, len(article_ids), BATCH):
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chunk = article_ids[i : i + BATCH]
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rows = [{"user_id": user.id, "article_id": aid} for aid in chunk]
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stmt = pg_insert(ArticleRead).values(rows).on_conflict_do_nothing(
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index_elements=["user_id", "article_id"]
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)
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# PG ON CONFLICT 不直接告诉哪些是"真插入的",通过 result() 或者信任总数;
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# 这里简单信任 chunk 大小,marked 返回 attempt 数(去重由 PK 保证)
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await session.execute(stmt)
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marked_total += len(chunk)
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await session.commit()
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return CategoryReadResponse(
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category=cat,
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matched=len(article_ids),
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marked=marked_total,
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article_ids=article_ids,
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)
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@router.get("/reads/category-count", response_model=list[CategoryCountItem])
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async def count_unread_by_categories(
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categories: str = Query(..., description="逗号分隔的分类列表,例如 '美国,社会'"),
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window_hours: int = Query(default=24, ge=1, le=168),
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sources: str | None = Query(default=None, description="逗号分隔源 slug"),
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q: str | None = Query(default=None, description="关键词过滤"),
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user: User = Depends(get_current_user),
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session: AsyncSession = Depends(get_session),
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):
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"""批量查多个分类的未读数(给前端提示条用,一次拿全,省 round-trip)。
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- categories 必填,逗号分隔
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- 每个分类独立 count(单次请求内是 N 次查询,数据量小,够用)
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- 返回的 unread_count = 0 的分类前端不展示提示行
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"""
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cat_list = [c.strip() for c in categories.split(",") if c.strip()]
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if not cat_list:
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return []
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src_list = [s.strip() for s in sources.split(",") if s.strip()] if sources else None
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eff_q = q.strip() if q and q.strip() else None
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results: list[CategoryCountItem] = []
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for cat in cat_list[:10]: # 防御性:一次最多 10 个分类
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filters = _build_category_filter(
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category=cat,
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window_hours=window_hours,
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user_id=user.id,
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sources=src_list,
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q=eff_q,
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)
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stmt = select(func.count(Article.id))
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if src_list:
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stmt = stmt.join(Source, Source.id == Article.source_id)
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for f in filters:
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stmt = stmt.where(f)
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n = (await session.execute(stmt)).scalar_one()
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if n > 0:
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results.append(
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CategoryCountItem(category=cat, unread_count=int(n), window_hours=window_hours)
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)
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return results
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