Merge branch 'main' into fix-homelist

merge origin/main 后 coupon_claim_event(main)与 guide_video_user_seq_uq(本分支)
成两个 head,加 no-op merge 节点 d8dd2106e438 收敛为单 head。已在全新库上
alembic upgrade heads 验证整条链可应用。

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

alembic/versions/coupon_claim_event.py

@@ -69,11 +69,7 @@ def upgrade() -> None:
         unique=False,
     )
 
-    # 旧表按 (device, coupon, 自然日) 去重，trace_id 可空且不在唯一键里：同一
-    # (trace_id, coupon_id) 可能散落在多行（如一次会话的 /step 帧跨零点，把同一张券
-    # 写进相邻两天）。新表按 (trace_id, coupon_id) 唯一，整表 1:1 复制会撞
-    # uq_coupon_claim_event_trace_coupon。回填时按 (trace_id, coupon_id) 只取 id 最大
-    # （最近写入）的一行。历史上已被每日去重覆盖的关联仍无法恢复。
+    # 旧表只能回填当前仍保留的 trace；历史上已被每日去重覆盖的关联无法恢复。
     op.execute(
         """
         INSERT INTO coupon_claim_event (
@@ -85,12 +81,6 @@ def upgrade() -> None:
             vendor, coupon_name, claimed_count, reason, extra, created_at, updated_at
         FROM coupon_claim_record
         WHERE trace_id IS NOT NULL
-          AND id IN (
-              SELECT MAX(id)
-              FROM coupon_claim_record
-              WHERE trace_id IS NOT NULL
-              GROUP BY trace_id, coupon_id
-          )
         """
     )
 

app/admin/routers/withdraw.py

@@ -129,11 +129,13 @@ def withdraw_health_check(db: AdminDb) -> WxpayHealthCheckOut:
         issues.append("免确认授权回调地址未配置")
 
     # 实际是否自动对账 = env 部署总闸(worker 起没起)AND 运营后台 DB 开关(本轮跑不跑)。
-    # 自动查单属于非阻断运维能力:状态继续返回给调用方,但关闭时不计入微信提现配置 issues,
-    # 避免把“没有自动扫单”误报成“无法打款”。
     worker_running = settings.WITHDRAW_AUTO_RECONCILE_ENABLED
     daily_on = bool(app_config.get_value(db, "withdraw_auto_reconcile_enabled"))
     auto_reconcile_enabled = worker_running and daily_on
+    if not worker_running:
+        issues.append("自动对账 worker 未启动(部署侧 env WITHDRAW_AUTO_RECONCILE_ENABLED=false)")
+    elif not daily_on:
+        issues.append("自动对账运营开关已关闭(系统配置页可开)")
 
     return WxpayHealthCheckOut(
         ok=not issues,

app/repositories/comparison.py

@@ -55,22 +55,13 @@ def _product_names_from_items(items: list | None) -> str | None:
 def _derive(payload: ComparisonRecordIn) -> dict:
     """从上报 payload 派生结构化列(best/saved/is_source_best/status)。"""
     results = payload.comparison_results
-    _pr = payload.platform_results or {}
 
-    def _is_short(r) -> bool:
-        # 缺菜(漏菜)店: 少买了菜总价虚低, 不参与最优评选。逐平台 skipped 在 platform_results, 行里没有。
-        # platform_results 内层结构宽松(pricebot/老客户端透传, 可伪造), 值非 dict 时按"不缺菜"处理, 不崩。
-        info = _pr.get(r.platform_id) if r.platform_id else None
-        return isinstance(info, dict) and (info.get("skipped_dish_count") or 0) > 0
-
-    # 最优 = 非缺菜里 rank 最小(=最便宜)的一条;协议已升序,但不信顺序,显式按 rank/price 取。
-    # 源平台永远全菜, 故全目标缺菜时回落到源(is_source_best、saved=0), 不把虚低价当最低。
-    priced = [r for r in results if r.price is not None]
-    clean = [r for r in priced if not _is_short(r)]
+    # 最优 = rank 最小的一条;协议已升序,但不信顺序,显式按 rank/price 兜底取最小价。
     best = None
-    if clean:
+    priced = [r for r in results if r.price is not None]
+    if priced:
         best = min(
-            clean,
+            priced,
             key=lambda r: (r.rank if r.rank is not None else 10**9, r.price),
         )
 
@@ -205,29 +196,14 @@ def upsert_record(
 # ============================================================
 
 
-def _derive_from_results(
-    results: list[dict], platform_results: dict | None = None
-) -> dict:
+def _derive_from_results(results: list[dict]) -> dict:
     """从 done 帧 comparison_results(pricebot 原始 dict 列表)派生结构化列。
-    等价 _derive,但吃原始字段(is_source/price/rank/platform_id/store_name...)而非 pydantic 对象。
-
-    platform_results(done.params.platform_results): 逐平台 skipped_dish_count 在这里(行里没有)。
-    传入则派生 best 时排除缺菜(漏菜)店 —— 少买了菜总价虚低, 不能当记录级"最低价"/算虚假省额;
-    源平台永远全菜, 故全目标缺菜时 best 回落到源(is_source_best、不虚报省)。不传→纯 rank/price, 行为不变。"""
-    _pr = platform_results or {}
-
-    def _is_short(r: dict) -> bool:
-        # platform_results 内层结构宽松(pricebot/客户端透传), 值非 dict 时按"不缺菜"处理, 不崩。
-        pid = r.get("platform_id")
-        info = _pr.get(pid) if pid else None
-        return isinstance(info, dict) and (info.get("skipped_dish_count") or 0) > 0
-
+    等价 _derive,但吃原始字段(is_source/price/rank/platform_id/store_name...)而非 pydantic 对象。"""
     priced = [r for r in results if r.get("price") is not None]
-    clean = [r for r in priced if not _is_short(r)]  # 缺菜店排除出最优评选
     best = None
-    if clean:
+    if priced:
         best = min(
-            clean,
+            priced,
             key=lambda r: (r.get("rank") if r.get("rank") is not None else 10**9, r["price"]),
         )
     src_row = next((r for r in results if r.get("is_source")), None)
@@ -413,7 +389,7 @@ def harvest_done(
     返回 (记录, 是否本次**新**落成 success)——供调用方据此幂等发一次邀请奖。
     行不存在(理论上帧0已建;防御)则新建。"""
     results = done_params.get("comparison_results") or []
-    derived = _derive_from_results(results, done_params.get("platform_results"))
+    derived = _derive_from_results(results)
     # 菜品:pricebot 已把源单菜品塞进 comparison_results[源行].items
     items = next((r.get("items") or [] for r in results if r.get("is_source")), [])
     fields = dict(

tests/test_derive_best_excludes_short.py

@@ -1,102 +0,0 @@
-"""_derive_from_results / _derive: 缺菜(漏菜)店总价虚低, 不当记录级"最低价"。
-
-回归: pricebot comparison_results[].rank 是纯价格排序(含缺菜), server 派生 best 若照单全收,
-会把缺菜店的虚低价当 best_price → 记录页戴"最低"红框 + 虚假省额。
-修复: 派生 best 时按 platform_results[pid].skipped_dish_count 排除缺菜店(源平台永远全菜, 仍可当 best)。
-纯函数, 不碰 DB。
-"""
-from app.repositories.comparison import _derive, _derive_from_results
-from app.schemas.compare_record import ComparisonRecordIn, ComparisonResultIn
-
-
-def test_derive_from_results_excludes_short_ordered_from_best():
-    # jd 缺 2 道菜 → 虚低 ¥25(rank=1); tb 全有 ¥38.5; 源美团 ¥42。best 应是 tb(干净最便宜), 不是 jd。
-    results = [
-        {"platform_id": "meituan", "platform_name": "美团", "price": 42.0, "is_source": True, "rank": 3},
-        {"platform_id": "jd_waimai", "platform_name": "京东外卖", "price": 25.0, "is_source": False, "rank": 1},
-        {"platform_id": "taobao_flash", "platform_name": "淘宝闪购", "price": 38.5, "is_source": False, "rank": 2},
-    ]
-    platform_results = {
-        "jd_waimai": {"skipped_dish_count": 2},
-        "taobao_flash": {"skipped_dish_count": 0},
-        "meituan": {"is_source": True},
-    }
-    d = _derive_from_results(results, platform_results)
-    assert d["best_platform_id"] == "taobao_flash"
-    assert d["best_price_cents"] == 3850
-    assert d["saved_amount_cents"] == 4200 - 3850   # 350, 用干净店算省额, 不是缺菜虚低价 42-25=17元
-    assert d["is_source_best"] is False
-
-
-def test_derive_from_results_all_targets_short_falls_back_to_source():
-    # 唯一比源便宜的都是缺菜 → 不crown缺菜店; 源全菜 → best=源, is_source_best, 不虚报省额。
-    results = [
-        {"platform_id": "meituan", "price": 42.0, "is_source": True, "rank": 2},
-        {"platform_id": "jd_waimai", "price": 25.0, "is_source": False, "rank": 1},
-    ]
-    platform_results = {"jd_waimai": {"skipped_dish_count": 3}}
-    d = _derive_from_results(results, platform_results)
-    assert d["best_platform_id"] == "meituan"
-    assert d["is_source_best"] is True
-    assert d["saved_amount_cents"] == 0
-
-
-def test_derive_from_results_no_platform_results_keeps_old_behavior():
-    # 不传 platform_results(老 harvest / 无缺菜信息)→ 行为不变: 纯 rank/price 选 best。
-    results = [
-        {"platform_id": "meituan", "price": 42.0, "is_source": True, "rank": 2},
-        {"platform_id": "jd_waimai", "price": 25.0, "is_source": False, "rank": 1},
-    ]
-    d = _derive_from_results(results)
-    assert d["best_platform_id"] == "jd_waimai"
-    assert d["best_price_cents"] == 2500
-
-
-def test_derive_from_results_malformed_platform_results_no_crash():
-    # 内层值非 dict(异常/伪造上报)→ 不抛 AttributeError, 按"不缺菜"处理, 照常选最便宜。
-    results = [
-        {"platform_id": "meituan", "price": 42.0, "is_source": True, "rank": 2},
-        {"platform_id": "jd_waimai", "price": 25.0, "is_source": False, "rank": 1},
-    ]
-    d = _derive_from_results(results, {"jd_waimai": "oops"})
-    assert d["best_platform_id"] == "jd_waimai"
-    assert d["best_price_cents"] == 2500
-
-
-def test_derive_pydantic_excludes_short():
-    # _derive(老客户端 POST 路径)同样排除缺菜店: jd 缺菜虚低 ¥25 不当 best, 取干净的淘宝 ¥38.5。
-    payload = ComparisonRecordIn(
-        trace_id="t-short-pyd",
-        source_price=42.0,
-        source_platform_id="meituan",
-        comparison_results=[
-            ComparisonResultIn(platform_id="meituan", platform_name="美团", price=42.0, is_source=True, rank=3),
-            ComparisonResultIn(platform_id="jd_waimai", platform_name="京东外卖", price=25.0, is_source=False, rank=1),
-            ComparisonResultIn(platform_id="taobao_flash", platform_name="淘宝闪购", price=38.5, is_source=False, rank=2),
-        ],
-        platform_results={
-            "jd_waimai": {"skipped_dish_count": 2},
-            "taobao_flash": {"skipped_dish_count": 0},
-        },
-    )
-    d = _derive(payload)
-    assert d["best_platform_id"] == "taobao_flash"
-    assert d["best_price_cents"] == 3850
-    assert d["saved_amount_cents"] == 4200 - 3850
-    assert d["is_source_best"] is False
-
-
-def test_derive_pydantic_malformed_platform_results_no_crash():
-    # _derive 的 platform_results 来自老客户端透传(可伪造): 内层非 dict 不应打 500。
-    payload = ComparisonRecordIn(
-        trace_id="t-malformed-pyd",
-        source_price=42.0,
-        comparison_results=[
-            ComparisonResultIn(platform_id="meituan", price=42.0, is_source=True, rank=2),
-            ComparisonResultIn(platform_id="jd_waimai", price=25.0, is_source=False, rank=1),
-        ],
-        platform_results={"jd_waimai": "oops"},
-    )
-    d = _derive(payload)  # 不抛 AttributeError
-    assert d["best_platform_id"] == "jd_waimai"
-    assert d["best_price_cents"] == 2500