feat(analytics): 管理层指标呈现——首响回复率上墙/客户资产总览/自定义日期/排行五新列

Co-Authored-By: Claude Code <noreply@anthropic.com>

yunke-server/app/analytics/metrics.py

@@ -43,23 +43,43 @@ def _day_date(day: int) -> dt.date:
     return dt.date(day // 10000, (day // 100) % 100, day % 100)
 
 
-def scope_day_keys(scope: str, today: int) -> list[int]:
+def scope_day_keys(
+    scope: str, today: int, start: int | None = None, end: int | None = None
+) -> list[int]:
     """today={今};week=本周一..今天;month=本月1号..今天;last30=近30天
     滚动窗(含端点)。last30 让排行/卡片命中任意有数据的月份(镜像停更期
-    间日历月窗可能全空)。"""
+    间日历月窗可能全空)。
-    end = _day_date(today)
+
+    custom=显式 [start..end] yyyymmdd(C1):start≤end 且跨度≤366 天
+    (router 层已 422 校验,这里防御性同检——metrics 直调也拿到 ValueError
+    而非空窗/怪窗)。
+    """
+    if scope == "custom":
+        if start is None or end is None:
+            raise ValueError("custom scope requires start and end")
+        s, e = _day_date(start), _day_date(end)  # 非法日历值此处抛 ValueError
+        if s > e:
+            raise ValueError("custom scope requires start <= end")
+        if (e - s).days > 365:  # 含端点共 366 天
+            raise ValueError("custom span must be <= 366 days")
+        out, cur = [], s
+        while cur <= e:
+            out.append(_date_key(cur))
+            cur += dt.timedelta(days=1)
+        return out
+    end_d = _day_date(today)
     if scope == "today":
-        start = end
+        start_d = end_d
     elif scope == "week":
-        start = end - dt.timedelta(days=end.weekday())  # 周一=0
+        start_d = end_d - dt.timedelta(days=end_d.weekday())  # 周一=0
     elif scope == "month":
-        start = end.replace(day=1)
+        start_d = end_d.replace(day=1)
     elif scope == "last30":
-        start = end - dt.timedelta(days=29)
+        start_d = end_d - dt.timedelta(days=29)
     else:
         raise ValueError(f"bad scope: {scope!r}")
-    out, cur = [], start
+    out, cur = [], start_d
-    while cur <= end:
+    while cur <= end_d:
         out.append(_date_key(cur))
         cur += dt.timedelta(days=1)
     return out
@@ -69,7 +89,8 @@ def _prev_scope_days(scope: str, days: list[int]) -> list[int]:
     """同期对齐环比窗(与 days 等长逐日对齐;今日 scope 不调用)。
 
     week=各日-7天(本周一..今 vs 上周一..上周同日);month=上月同日
-    (短月钳到上月末,如 3/31→2/28);last30=各日-30天(前一个滚动窗)。
+    (短月钳到上月末,如 3/31→2/28);last30=各日-30天(前一个滚动窗);
+    custom=各日-N 天(等长紧邻前窗,例外不做同期对齐)。
     同期对齐而非滚动紧邻窗——后者周会跨周末、月取上月尾巴,管理者会
     误读成「上周/上月」(spec §8)。
     """
@@ -88,6 +109,11 @@ def _prev_scope_days(scope: str, days: list[int]) -> list[int]:
         return out
     if scope == "last30":
         return [_date_key(_day_date(d) - dt.timedelta(days=30)) for d in days]
+    if scope == "custom":
+        # C1 例外:等长紧邻前窗(各日 -N 天滚动)。custom 不做同期对齐——
+        # 任意起点无「周/月」节律可对,紧邻窗是最不易误读的对照。
+        n = len(days)
+        return [_date_key(_day_date(d) - dt.timedelta(days=n)) for d in days]
     raise ValueError(f"bad scope: {scope!r}")
 
 
@@ -297,8 +323,9 @@ async def anomaly(session: AsyncSession, channel: str | None) -> dict | None:
 
 async def staff_ranking(
     session: AsyncSession, *, channel: str | None, scope: str,
+    start: int | None = None, end: int | None = None,
 ) -> list[dict]:
-    """员工活跃排行(A2 核心子集,2026-09-07 管理者反馈补强)。
+    """员工活跃排行(A2 核心子集,2026-09-07 管理者反馈补强;批2 五新列)。
 
     口径:msg_total=stat_daily_staff 聚合(空表回退 msg_daily_stats+映射,
     同 _active_staff 模式);call_cnt=phone_call 按 user_id 落窗直查(3k 行
@@ -306,6 +333,19 @@ async def staff_ranking(
     staff.name,无 staff 行/未映射账号回退 user_id 原值标 unmapped。
     排序 msg_total desc + user_id asc 决胜。返回全部行(员工 ~41)。
 
+    批2 新列(A3/A4/A5):
+    - fr_avg_ms=Σfr_sum_ms/Σthreads_answered(answered=0→None);
+      reply_rate=Σanswered/Σthreads(threads=0→None)——两路径同源
+      (rollup 三列 / 回退 msg_daily_stats 三列累加,含 room 行,与批1
+      管道口径一致);
+    - first_contact_cnt=该员工当期首沟通客户数:(owner,peer) 全史
+      MIN(day) 落窗的 distinct peer(映射到 user 后跨账号去重);
+    - call_seconds/answer_rate=phone_call 落窗 SUM(call_duration)(秒)
+      与 call_duration>0 占比(count=0→None);
+    - deleted/blocked_friends=customer 表按 user_id 归属的**全库**存量
+      delete_flag=1 / is_block 计数(与 churn handover 同归属口径;
+      不随窗——删粉是存量状态)。
+
     channel=None(全平台):查询去渠道条件+映射合并,同 user 跨渠道量
     自然合到一行(员工排行本就是 user 级)。
 
@@ -315,12 +355,12 @@ async def staff_ranking(
     MAX 只是峰值,皆非「窗内活跃去重数」——rollup 只供 msg_total,
     避免两路径语义分叉。
     """
-    days = scope_day_keys(scope, today_key())
+    days = scope_day_keys(scope, today_key(), start, end)
     amap = await _account_map(session, channel)
 
-    # 活跃客户/群 + 回退 msg_total:落窗拉行,Python 侧映射后按 user 去重
+    # 活跃客户/群 + 回退 msg_total/首响三列:落窗拉行,Python 侧映射后按
-    # (COUNT(DISTINCT peer) 必须在「账号合并到员工」之后——同人多账号
+    # user 去重(COUNT(DISTINCT peer) 必须在「账号合并到员工」之后——同人
-    # 跨账号去重,写 SQL 反而绕且踩 only_full_group_by)
+    # 多账号跨账号去重,写 SQL 反而绕且踩 only_full_group_by)
     conds = [MsgDailyStats.day.in_(days)]
     if channel is not None:
         conds.append(MsgDailyStats.channel == channel)
@@ -332,12 +372,16 @@ async def staff_ranking(
                 MsgDailyStats.peer_id,
                 MsgDailyStats.send_cnt,
                 MsgDailyStats.recv_cnt,
+                MsgDailyStats.cust_threads,
+                MsgDailyStats.threads_answered,
+                MsgDailyStats.fr_sum_ms,
             ).where(*conds)
         )
     ).all()
     act: dict[str, dict[str, set]] = {}
     msg_fallback: dict[str, int] = {}
-    for owner, kind, peer, s, r in rows:
+    th_fallback: dict[str, list[int]] = {}
+    for owner, kind, peer, s, r, t, a_ns, fr in rows:
         uid = amap.get(owner, owner)
         a = act.setdefault(uid, {"friends": set(), "rooms": set()})
         if kind == "friend":  # 显式分支:未来新 kind 跳过,不误入 rooms
@@ -345,8 +389,13 @@ async def staff_ranking(
         elif kind == "room":
             a["rooms"].add(peer)
         msg_fallback[uid] = msg_fallback.get(uid, 0) + int(s or 0) + int(r or 0)
+        tf = th_fallback.setdefault(uid, [0, 0, 0])
+        tf[0] += int(t or 0)
+        tf[1] += int(a_ns or 0)
+        tf[2] += int(fr or 0)
 
     use_rollup = await _staff_rows(session)
+    th: dict[str, tuple[int, int, int]] = {}
     if use_rollup:
         conds = [StatDailyStaff.day.in_(days)]
         if channel is not None:
@@ -361,23 +410,45 @@ async def staff_ranking(
                         ),
                         0,
                     ),
+                    sa.func.coalesce(sa.func.sum(StatDailyStaff.cust_threads), 0),
+                    sa.func.coalesce(
+                        sa.func.sum(StatDailyStaff.threads_answered), 0
+                    ),
+                    sa.func.coalesce(sa.func.sum(StatDailyStaff.fr_sum_ms), 0),
                 )
                 .where(*conds)
                 .group_by(StatDailyStaff.user_id)
             )
         ).all()
-        msg_total = {uid: int(v) for uid, v in rollup}
+        msg_total = {}
+        for uid, mv, t, a_ns, fr in rollup:
+            msg_total[uid] = int(mv)
+            th[uid] = (int(t), int(a_ns), int(fr))
     else:
         msg_total = msg_fallback
+        th = {uid: (v[0], v[1], v[2]) for uid, v in th_fallback.items()}
 
-    # 通话:按 user_id 落窗直查(窗口换算同 _call_count 写法)
+    # 通话:按 user_id 落窗直查(窗口换算同 _call_count 写法)——量/时长/
+    # 接通率一次取回(call_duration>0 计为接通)
     calls: dict[str, int] = {}
+    call_secs: dict[str, int] = {}
+    call_ans: dict[str, int] = {}
     if days:
         lo, _ = day_bounds_ms(days[0])
         hi_start, _ = day_bounds_ms(days[-1])
         call_rows = (
             await session.execute(
-                sa.select(PhoneCall.user_id, sa.func.count())
+                sa.select(
+                    PhoneCall.user_id,
+                    sa.func.count(),
+                    sa.func.coalesce(sa.func.sum(PhoneCall.call_duration), 0),
+                    sa.func.coalesce(
+                        sa.func.sum(
+                            sa.case((PhoneCall.call_duration > 0, 1), else_=0)
+                        ),
+                        0,
+                    ),
+                )
                 .where(
                     PhoneCall.user_id.is_not(None),
                     PhoneCall.start_call_time.is_not(None),
@@ -387,11 +458,61 @@ async def staff_ranking(
                 .group_by(PhoneCall.user_id)
             )
         ).all()
-        calls = {uid: int(v) for uid, v in call_rows}
+        for uid, cnt, secs, ans in call_rows:
+            calls[uid] = int(cnt)
+            call_secs[uid] = int(secs)
+            call_ans[uid] = int(ans)
+
+    # 首沟通归属:peer 全史 MIN(day) 落窗 → 记到 (channel,)owner 映射后的
+    # user;distinct 在 user 级(同人多账号/客户换跟进人不重复计)
+    fc_conds = [MsgDailyStats.peer_kind == "friend"]
+    if channel is not None:
+        fc_conds.append(MsgDailyStats.channel == channel)
+    fc_rows = (
+        await session.execute(
+            sa.select(
+                MsgDailyStats.owner_account_id,
+                MsgDailyStats.peer_id,
+                sa.func.min(MsgDailyStats.day),
+            )
+            .where(*fc_conds)
+            .group_by(MsgDailyStats.owner_account_id, MsgDailyStats.peer_id)
+        )
+    ).all()
+    dayset = set(days)
+    first_contacts: dict[str, set[str]] = {}
+    for owner, peer, first in fc_rows:
+        if first in dayset:
+            first_contacts.setdefault(amap.get(owner, owner), set()).add(peer)
+
+    # 删粉/拉黑:customer 全库存量按 user_id 归属(NULL user_id 跳过——
+    # 排行是员工视图,无归属客户进 overview 的 customer_assets)
+    del_conds = [Customer.user_id.is_not(None)]
+    if channel is not None:
+        del_conds.append(Customer.channel == channel)
+    del_rows = (
+        await session.execute(
+            sa.select(
+                Customer.user_id,
+                sa.func.coalesce(
+                    sa.func.sum(sa.case((Customer.delete_flag == 1, 1), else_=0)),
+                    0,
+                ),
+                sa.func.coalesce(
+                    sa.func.sum(sa.case((Customer.is_block.is_(True), 1), else_=0)),
+                    0,
+                ),
+            )
+            .where(*del_conds)
+            .group_by(Customer.user_id)
+        )
+    ).all()
+    deleted = {uid: int(d) for uid, d, _b in del_rows}
+    blocked = {uid: int(b) for uid, _d, b in del_rows}
 
     # 环比:同期对齐前窗(仅周/月;今日 vs 昨日全天会误导,与 overview 同口径)
     prev_total: dict[str, int] = {}
-    if scope in ("week", "month", "last30"):
+    if scope in ("week", "month", "last30", "custom"):
         prev_days = _prev_scope_days(scope, days)
         if use_rollup:
             conds = [StatDailyStaff.day.in_(prev_days)]
@@ -449,6 +570,8 @@ async def staff_ranking(
     for uid in sorted(set(msg_total) | set(act) | set(calls),
                       key=lambda u: (-msg_total.get(u, 0), u)):
         cur, prev = msg_total.get(uid, 0), prev_total.get(uid, 0)
+        t, a_ns, fr = th.get(uid, (0, 0, 0))
+        cnt = calls.get(uid, 0)
         out.append({
             "user_id": uid,
             "name": staff_names.get(uid) or uid,
@@ -456,8 +579,15 @@ async def staff_ranking(
             "msg_total": cur,
             "active_friends": len(act[uid]["friends"]) if uid in act else 0,
             "active_rooms": len(act[uid]["rooms"]) if uid in act else 0,
-            "call_cnt": calls.get(uid, 0),
+            "call_cnt": cnt,
             "msg_delta": round((cur - prev) / prev, 3) if cur and prev else None,
+            "fr_avg_ms": round(fr / a_ns) if a_ns else None,
+            "reply_rate": round(a_ns / t, 4) if t else None,
+            "first_contact_cnt": len(first_contacts.get(uid, ())),
+            "call_seconds": call_secs.get(uid, 0),
+            "answer_rate": round(call_ans[uid] / cnt, 4) if cnt else None,
+            "deleted_friends": deleted.get(uid, 0),
+            "blocked_friends": blocked.get(uid, 0),
         })
     return out
 
@@ -485,11 +615,62 @@ async def action_counts(session: AsyncSession, *, channel: str | None) -> dict:
     }
 
 
+async def _customer_assets(session: AsyncSession) -> dict:
+    """B1 客户资产总览:全库存量快照,不随 scope/channel(分层/删粉是存量
+    状态,与筛选无关)。
+
+    剔除 delete_flag=1 后按 last_chat_time 分层(边界与 churn real 同式:
+    >now-Nd 为近 N 天):active30=≤30 天;silent30_90=(30,90] 天前;
+    sleeping90p=≥90 天前;从未激活(last_chat_time NULL,云客没聊过/新加)
+    单列 never。渠道计数与已删好友单列。customer ~12k 行单条聚合直查。
+    """
+    day_ms = 86_400_000
+    now = _now_ms()
+    not_deleted = sa.or_(Customer.delete_flag.is_(None), Customer.delete_flag == 0)
+    lt = Customer.last_chat_time
+
+    def _n(cond: Any) -> int:
+        return sa.func.coalesce(sa.func.sum(sa.case((cond, 1), else_=0)), 0)
+
+    row = (
+        await session.execute(
+            sa.select(
+                _n(sa.and_(not_deleted, lt.is_(None))),
+                _n(sa.and_(not_deleted, lt.is_not(None), lt > now - 30 * day_ms)),
+                _n(sa.and_(not_deleted, lt.is_not(None),
+                           lt <= now - 30 * day_ms, lt > now - 90 * day_ms)),
+                _n(sa.and_(not_deleted, lt.is_not(None), lt <= now - 90 * day_ms)),
+                _n(sa.and_(not_deleted, Customer.channel == "wechat")),
+                _n(sa.and_(not_deleted, Customer.channel == "whatsapp")),
+                _n(Customer.delete_flag == 1),
+            )
+        )
+    ).one()
+    never, active30, silent, sleeping, wechat, whatsapp, deleted = (
+        int(v) for v in row
+    )
+    return {
+        "total": never + active30 + silent + sleeping,
+        "active30": active30,
+        "silent30_90": silent,
+        "sleeping90p": sleeping,
+        "never": never,
+        "wechat": wechat,
+        "whatsapp": whatsapp,
+        "deleted": deleted,
+    }
+
+
 async def overview(
-    session: AsyncSession, *, channel: str | None, scope: str, trend_days: int = 30
+    session: AsyncSession, *, channel: str | None, scope: str, trend_days: int = 30,
+    start: int | None = None, end: int | None = None,
 ) -> dict[str, Any]:
     """A1:卡片 + 环比(仅周/月,同期对齐) + 近 N 天趋势 + 异常警示。
 
+    批2:C1 自定义日期(scope=custom + start/end yyyymmdd,环比=等长紧邻
+    前窗滚动,不做同期对齐——见 _prev_scope_days);B1 customer_assets
+    客户资产总览(全库存量,不随 scope/channel)。
+
     channel=None(全平台,看板 v2 默认):所有指标跨渠道合并——msg/活跃客户
     直接合计(peer_id 跨渠道不碰撞);活跃员工按 user 去重(跨渠道重复计数
     不拆);通话量本就是 call-type 无渠道语义。此时追加:
@@ -502,7 +683,7 @@ async def overview(
     if trend_days < 1 or trend_days > 90:
         raise ValueError("trend_days must be 1..90")
     today = today_key()
-    days = scope_day_keys(scope, today)
+    days = scope_day_keys(scope, today, start, end)
     rows = await _day_rows(session, channel, days)
     msg_total = sum(int(s or 0) + int(r or 0) for _d, _k, _p, s, r in rows)
     active_customers = len({p for _d, kind, p, _s, _r in rows if kind == "friend"})
@@ -517,8 +698,9 @@ async def overview(
         "first_contact": await _first_contact(session, channel, days),
     }
 
-    # 环比仅周/月,同期对齐(今日 vs 昨日全天会误导,spec §8)
+    # 环比仅周/月,同期对齐(今日 vs 昨日全天会误导,spec §8);
-    if scope in ("week", "month", "last30"):
+    # custom=等长紧邻前窗滚动(例外,见 _prev_scope_days)
+    if scope in ("week", "month", "last30", "custom"):
         prev_days = _prev_scope_days(scope, days)
         prev_rows = await _day_rows(session, channel, prev_days)
         prev_total = sum(int(s or 0) + int(r or 0) for _d, _k, _p, s, r in prev_rows)
@@ -528,10 +710,11 @@ async def overview(
         )
 
     # 趋势:近 trend_days 天 每日 消息量/活跃客户/通话量
-    end = _day_date(today)
+    # (t_end 不复用 end 参数名——那是 custom scope 的 yyyymmdd 入参)
+    t_end = _day_date(today)
     t_days = []
-    cur = end - dt.timedelta(days=trend_days - 1)
+    cur = t_end - dt.timedelta(days=trend_days - 1)
-    while cur <= end:
+    while cur <= t_end:
         t_days.append(_date_key(cur))
         cur += dt.timedelta(days=1)
     # 通话趋势:phone_call 拉窗内 (start_call_time) Python 侧按日分桶(3k 行)
@@ -571,9 +754,12 @@ async def overview(
         "channel": "all" if channel is None else channel,
         "days": days,
         "cards": cards,
+        "customer_assets": await _customer_assets(session),
         "trend": trend,
         "anomaly": await anomaly(session, channel),
-        "staff_ranking": await staff_ranking(session, channel=channel, scope=scope),
+        "staff_ranking": await staff_ranking(
+            session, channel=channel, scope=scope, start=start, end=end
+        ),
         "actions": await action_counts(session, channel=channel),
     }
     if channel is None:

yunke-server/app/api/routers/analytics.py

@@ -1,6 +1,7 @@
 """GET /api/analytics/* —— 数据分析板块端组(前缀分组=未来角色权限落点)。"""
 from __future__ import annotations
 
+import datetime as dt
 from typing import Annotated, Any, Literal
 
 import sqlalchemy as sa
@@ -21,7 +22,11 @@ ChannelParam = Annotated[Literal["wechat", "whatsapp"], Query()]
 # 看板 v2(2026-09-07):overview 默认全平台——"all" 在 router 层翻译成
 # metrics 的 channel=None,不把哨兵字符串传进 SQL
 AllChannelParam = Annotated[Literal["all", "wechat", "whatsapp"], Query()]
-ScopeParam = Annotated[Literal["today", "week", "month", "last30"], Query()]
+# C1(批2):custom=自定义日期范围,配合 start/end yyyymmdd
+ScopeParam = Annotated[
+    Literal["today", "week", "month", "last30", "custom"], Query()
+]
+YmdParam = Annotated[int, Query(ge=20000101, le=29991231)]
 
 
 @router.get("/health")
@@ -36,6 +41,8 @@ async def analytics_overview(
     session: SessionDep,
     channel: AllChannelParam = "all",
     scope: ScopeParam = "today",
+    start: YmdParam | None = None,
+    end: YmdParam | None = None,
 ) -> dict[str, Any]:
     """A1 经营总览:卡片+趋势+异常警示一次返回(单往返)。
 
@@ -43,9 +50,27 @@ async def analytics_overview(
     双渠道趋势序列;单渠道行为不变。
     cards 不含 data_as_of——数据截至走 /health(data_as_of 为 ms-epoch int
     与 entities[].last_seen 为 ISO 字符串的双格式)。
+
+    scope=custom(C1):start/end=yyyymmdd(缺一/日历非法/Start>End/跨度
+    >366 天皆 422);环比=等长紧邻前窗滚动(不做同期对齐)。
     """
+    s = e = None
+    if scope == "custom":
+        if start is None or end is None:
+            raise HTTPException(422, "scope=custom requires start and end")
+        try:
+            sd = dt.date(start // 10000, (start // 100) % 100, start % 100)
+            ed = dt.date(end // 10000, (end // 100) % 100, end % 100)
+        except ValueError as exc:  # 如 20260230——Query 只拦范围不拦日历
+            raise HTTPException(422, "invalid start/end calendar date") from exc
+        if sd > ed:
+            raise HTTPException(422, "start must be <= end")
+        if (ed - sd).days > 365:  # 含端点共 366 天
+            raise HTTPException(422, "custom span must be <= 366 days")
+        s, e = start, end
     return await metrics_svc.overview(
-        session, channel=None if channel == "all" else channel, scope=scope
+        session, channel=None if channel == "all" else channel, scope=scope,
+        start=s, end=e,
     )
 
 

yunke-server/tests/test_analytics_api.py

@@ -147,3 +147,51 @@ async def test_overview_unmapped_rollup(make_client, monkeypatch):
     body = r.json()
     assert body["cards"]["active_staff"] == 2
     assert body["cards"]["unmapped_accounts"] == 1
+
+
+async def test_overview_custom_scope_api(make_client, monkeypatch):
+    """C1 自定义日期:正常窗 200 + customer_assets 恒在;缺参/start>end/
+    跨度超 366 天/非法日历 全 422;闰年整 366 天放行。"""
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+
+    async def seed(session):
+        session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
+                                  peer_kind="friend", peer_id="t1", day=20260815,
+                                  send_cnt=10, recv_cnt=0, last_ts=1786000000000,
+                                  last_is_send=True))
+        await session.commit()
+
+    client = await make_client(seed)
+    r = await client.get("/api/analytics/overview", params={
+        "channel": "wechat", "scope": "custom",
+        "start": 20260801, "end": 20260827,
+    })
+    assert r.status_code == 200
+    body = r.json()
+    assert body["scope"] == "custom"
+    assert len(body["days"]) == 27
+    assert body["cards"]["msg_total"] == 10
+    # B1 客户资产总览恒在(全库快照,不随 scope)
+    assert body["customer_assets"]["total"] >= 0
+
+    # 缺 start/end → 422(不让静默落到空窗)
+    r2 = await client.get("/api/analytics/overview",
+                          params={"scope": "custom"})
+    assert r2.status_code == 422
+    # start > end → 422
+    r3 = await client.get("/api/analytics/overview", params={
+        "scope": "custom", "start": 20260827, "end": 20260801})
+    assert r3.status_code == 422
+    # 跨度 367 天 → 422(2024-01-01..2025-01-01 含端点 367 天)
+    r4 = await client.get("/api/analytics/overview", params={
+        "scope": "custom", "start": 20240101, "end": 20250101})
+    assert r4.status_code == 422
+    # 非法日历(2 月 30)→ 422——Query ge/le 只拦数值范围不拦日历
+    r5 = await client.get("/api/analytics/overview", params={
+        "scope": "custom", "start": 20260230, "end": 20260301})
+    assert r5.status_code == 422
+    # 闰年整年 366 天(含端点)→ 放行
+    r6 = await client.get("/api/analytics/overview", params={
+        "scope": "custom", "start": 20240101, "end": 20241231})
+    assert r6.status_code == 200
+    assert len(r6.json()["days"]) == 366

yunke-server/tests/test_analytics_overview.py

@@ -280,27 +280,37 @@ async def test_staff_ranking(make_client, monkeypatch):
 
 
 async def test_staff_ranking_fallback_when_rollup_empty(make_client, monkeypatch):
-    """stat_daily_staff 空表 → msg_total 回退 msg_daily_stats 聚合(部署即用)。"""
+    """stat_daily_staff 空表 → msg_total/首响三列回退 msg_daily_stats 聚合(部署即用)。"""
     monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
     async def seed(session):
         session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
         session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
                                   peer_kind="friend", peer_id="t1", day=20260904,
                                   send_cnt=10, recv_cnt=5, last_ts=1788500000000,
-                                  last_is_send=True))
+                                  last_is_send=True,
+                                  cust_threads=2, threads_answered=1,
+                                  fr_sum_ms=60000))
         # wx9 无账号行 → 映射不上按 owner 原值计入并标未映射
         session.add(MsgDailyStats(channel="wechat", owner_account_id="wx9",
                                   peer_kind="friend", peer_id="t2", day=20260904,
                                   send_cnt=2, recv_cnt=0, last_ts=1788500000000,
-                                  last_is_send=True))
+                                  last_is_send=True,
+                                  cust_threads=3, threads_answered=0,
+                                  fr_sum_ms=0))
         await session.commit()
         out = await metrics.staff_ranking(session, channel="wechat", scope="today")
         assert [r["user_id"] for r in out] == ["u1", "wx9"]
         assert out[0]["msg_total"] == 15 and out[0]["active_friends"] == 1
         assert out[0]["unmapped"] is False
         assert out[0]["msg_delta"] is None  # 今日 scope 无环比
+        # 回退路径首响三列:60000/1=60000;回复率 1/2
+        assert out[0]["fr_avg_ms"] == 60000
+        assert out[0]["reply_rate"] == 0.5
         assert out[1]["msg_total"] == 2 and out[1]["unmapped"] is True
         assert out[1]["name"] == "wx9"
+        # threads>0 answered=0 → 回复率 0.0(有串无回);首响 None(无样本)
+        assert out[1]["reply_rate"] == 0.0
+        assert out[1]["fr_avg_ms"] is None
 
     await make_client(seed)
 
@@ -425,3 +435,145 @@ async def test_action_counts_all(make_client, monkeypatch):
                        "sensitive_pending": 2}
 
     await make_client(seed)
+
+
+# ── 批2(2026-09-07):排行五新列 / B1 客户资产 / C1 自定义日期 ──────────────
+
+
+async def test_staff_ranking_batch2_columns(make_client, monkeypatch):
+    """排行五新列:首响均值+回复率(rollup 三列)、首沟通归属、通话时长+
+    接通率、删粉/拉黑(全库存量按 user_id 归属,不随窗)。"""
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+    async def seed(session):
+        session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
+        session.add(WechatAccount(wx_id="wx2", user_id="u2", user_name="李四"))
+        session.add(Staff(user_id="u1", name="张三"))
+        session.add(Staff(user_id="u2", name="李四"))
+        # rollup 当窗行:u1 threads=10 answered=4 fr=1_200_000(→300000ms/0.4);
+        # u2 三列缺省 0 → 两率皆 None
+        session.add(StatDailyStaff(day=20260904, channel="wechat", user_id="u1",
+                                   msg_sent=20, msg_recv=0, active_friends=1,
+                                   active_rooms=0, cust_threads=10,
+                                   threads_answered=4, fr_sum_ms=1_200_000))
+        session.add(StatDailyStaff(day=20260904, channel="wechat", user_id="u2",
+                                   msg_sent=5, msg_recv=0, active_friends=1,
+                                   active_rooms=0))
+        # 首沟通:f1 全史 MIN=20260831 落窗(计);f2 MIN=20260801 窗外(不计);
+        # r1 是 room 不计;f3 归 wx2→u2(计)
+        for day, kind, peer, owner in [
+            (20260831, "friend", "f1", "wx1"),
+            (20260902, "friend", "f1", "wx1"),  # 同 peer 次日不影响 MIN
+            (20260801, "friend", "f2", "wx1"),
+            (20260903, "room", "r1", "wx1"),
+            (20260903, "friend", "f3", "wx2"),
+        ]:
+            session.add(MsgDailyStats(channel="wechat", owner_account_id=owner,
+                                      peer_kind=kind, peer_id=peer, day=day,
+                                      send_cnt=1, recv_cnt=0,
+                                      last_ts=1788500000000, last_is_send=True))
+        # 通话:u1 三通落窗(60/0/120s → 180s、2/3 接通);u2 通话在 2025 年
+        for cid, uid, ts, dur in [
+            ("c1", "u1", 1788500000000, 60),
+            ("c2", "u1", 1788500001000, 0),
+            ("c3", "u1", 1788500002000, 120),
+            ("c4", "u2", 1756950000000, 60),
+        ]:
+            session.add(PhoneCall(call_id=cid, channel="voice_call", user_id=uid,
+                                  start_call_time=ts, call_duration=dur))
+        # 客户归属存量:u1 删 1 拉黑 1;u2 双属性各 1;无归属(user_id NULL)跳过
+        session.add(Customer(friend_id="d1", channel="wechat", user_id="u1",
+                             delete_flag=1))
+        session.add(Customer(friend_id="b1", channel="wechat", user_id="u1",
+                             is_block=True))
+        session.add(Customer(friend_id="x1", channel="wechat", user_id="u2",
+                             delete_flag=1, is_block=True))
+        session.add(Customer(friend_id="n1", channel="wechat", user_id=None))
+        await session.commit()
+
+        out = await metrics.staff_ranking(session, channel="wechat", scope="week")
+        by = {r["user_id"]: r for r in out}
+        r1, r2 = by["u1"], by["u2"]
+        assert r1["fr_avg_ms"] == 300000  # 1_200_000 / 4
+        assert r1["reply_rate"] == 0.4
+        assert r1["first_contact_cnt"] == 1  # f1;f2 窗外、r1 群不计
+        assert r1["call_seconds"] == 180
+        assert r1["answer_rate"] == round(2 / 3, 4)
+        assert r1["deleted_friends"] == 1 and r1["blocked_friends"] == 1
+        assert r2["fr_avg_ms"] is None and r2["reply_rate"] is None
+        assert r2["first_contact_cnt"] == 1  # f3
+        assert r2["call_seconds"] == 0 and r2["answer_rate"] is None  # 窗外通话
+        assert r2["deleted_friends"] == 1 and r2["blocked_friends"] == 1
+
+    await make_client(seed)
+
+
+async def test_customer_assets_layers(make_client, monkeypatch):
+    """B1:剔除已删后按 last_chat_time 分层(从未激活单列 never);渠道计数;
+    已删单列。全库口径——channel=wechat 也不滤 whatsapp 客户。"""
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+    monkeypatch.setattr(metrics, "_now_ms", lambda: 1788550000000)
+    async def seed(session):
+        now = 1788550000000
+        day_ms = 86_400_000
+        rows = [
+            ("a1", "wechat", now - 5 * day_ms, 0),    # active
+            ("a2", "whatsapp", now - 29 * day_ms, 0),  # active(边界内)
+            ("s1", "whatsapp", now - 45 * day_ms, 0),  # silent
+            ("p1", "wechat", now - 91 * day_ms, 0),    # sleeping
+            ("n1", "whatsapp", None, 0),               # never
+            ("n2", "wechat", None, None),              # never(delete_flag NULL 同未删)
+        ]
+        for fid, ch, lt, df in rows:
+            session.add(Customer(friend_id=fid, channel=ch, last_chat_time=lt,
+                                 delete_flag=df))
+        # 已删不进分层、单列(deleted)
+        session.add(Customer(friend_id="d1", channel="wechat",
+                             last_chat_time=now - 1 * day_ms, delete_flag=1))
+        await session.commit()
+
+        out = await metrics.overview(session, channel="wechat", scope="today")
+        assert out["customer_assets"] == {
+            "total": 6, "active30": 2, "silent30_90": 1, "sleeping90p": 1,
+            "never": 2, "wechat": 3, "whatsapp": 3, "deleted": 1,
+        }
+
+    await make_client(seed)
+
+
+async def test_overview_custom_scope(make_client, monkeypatch):
+    """C1:custom days=[start..end](含端点);环比=等长紧邻前窗滚动(各日 -N);
+    metrics 直调的参数防御(缺参/逆序/超 366 天)。"""
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+    async def seed(session):
+        # 窗内 20260801..20260827:t1 10 条;紧邻前窗 20260705..20260731:t1 20 条
+        for day, sent in [(20260815, 10), (20260710, 20)]:
+            session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
+                                      peer_kind="friend", peer_id="t1", day=day,
+                                      send_cnt=sent, recv_cnt=0,
+                                      last_ts=1786000000000, last_is_send=True))
+        await session.commit()
+
+        out = await metrics.overview(session, channel="wechat", scope="custom",
+                                     start=20260801, end=20260827)
+        assert out["days"][0] == 20260801 and out["days"][-1] == 20260827
+        assert len(out["days"]) == 27
+        assert out["cards"]["msg_total"] == 10
+        assert out["cards"]["prev_msg_total"] == 20  # 紧邻前窗命中 07-10 行
+        assert out["cards"]["msg_total_delta"] == -0.5
+        # 排行吃同一窗(回退路径):wx1 未映射按原值出列
+        assert out["staff_ranking"][0]["user_id"] == "wx1"
+        assert out["staff_ranking"][0]["msg_total"] == 10
+        # 紧邻前窗逐日 -27:08-01→07-05、08-27→07-31
+        prev = metrics._prev_scope_days("custom", out["days"])
+        assert (len(prev), prev[0], prev[-1]) == (27, 20260705, 20260731)
+
+        with pytest.raises(ValueError):
+            await metrics.overview(session, channel="wechat", scope="custom")
+        with pytest.raises(ValueError):
+            await metrics.overview(session, channel="wechat", scope="custom",
+                                   start=20260827, end=20260801)
+        with pytest.raises(ValueError):
+            await metrics.overview(session, channel="wechat", scope="custom",
+                                   start=20240101, end=20250101)  # 367 天
+
+    await make_client(seed)

yunkes/src/api/analytics.ts

@@ -4,7 +4,8 @@ import { getJson, requestJson } from './client'
 import type { Channel, Page } from './types'
 
 export type { Channel }
-export type Scope = 'today' | 'week' | 'month' | 'last30'
+// 批2(2026-09-07):'custom'=自定义日期范围,须配合 start/end yyyymmdd
+export type Scope = 'today' | 'week' | 'month' | 'last30' | 'custom'
 // 看板 v2(2026-09-07):overview 渠道参数支持 'all'=全平台(后端译成
 // channel=None);列表页(churn/unreplied)仍是单渠道,沿用 types.ts 的 Channel
 export type DashboardChannel = 'all' | Channel
@@ -19,15 +20,35 @@ export interface OverviewCards {
   prev_msg_total?: number
   msg_total_delta?: number | null
 }
+// B1 客户资产总览:全库存量快照,不随 scope/channel
+export interface CustomerAssets {
+  total: number
+  active30: number
+  silent30_90: number
+  sleeping90p: number
+  never: number
+  wechat: number
+  whatsapp: number
+  deleted: number
+}
 export interface TrendPoint { day: number; msg: number; active_customers: number; call_cnt: number }
 export interface AnomalyStaff { user_id: string; yesterday: number; prev7_mean: number; new?: boolean }
 export interface Anomaly { total_delta_pct: number; yesterday_total: number; prev7_mean: number; staff: AnomalyStaff[] }
 // 员工活跃排行(2026-09-07 管理者反馈补强):active_*=窗内 distinct peer,
-// msg_delta 仅周/月且当前/前窗均非 0 才有值
+// msg_delta 仅周/月/custom 且当前/前窗均非 0 才有值。
+// 批2 五新列:fr_avg_ms/reply_rate(=null 无样本/无串)、first_contact_cnt、
+// call_seconds/answer_rate(=null 无通话);deleted/blocked_friends=全库存量
 export interface StaffRankingRow {
   user_id: string; name: string; unmapped: boolean
   msg_total: number; active_friends: number; active_rooms: number
   call_cnt: number; msg_delta: number | null
+  fr_avg_ms: number | null
+  reply_rate: number | null
+  first_contact_cnt: number
+  call_seconds: number
+  answer_rate: number | null
+  deleted_friends: number
+  blocked_friends: number
 }
 export interface ActionCounts { unreplied_2h: number; churn_real_30d: number; sensitive_pending: number }
 // by_channel/trend_by_channel 仅 channel='all' 时后端才返回(可选字段);
@@ -38,6 +59,7 @@ export interface OverviewResp {
   channel: Channel | 'all'
   days: number[]
   cards: OverviewCards
+  customer_assets: CustomerAssets
   trend: TrendPoint[]
   anomaly: Anomaly | null
   staff_ranking: StaffRankingRow[]
@@ -64,8 +86,11 @@ export interface SensitiveHitRow {
   room_id: string | null; ts: number | null; snippet: string | null; disposition: string
 }
 
-export const getOverview = (channel: DashboardChannel, scope: Scope) =>
+// scope='custom' 时必须传 start/end(yyyymmdd,后端校验跨度≤366 天)
-  getJson<OverviewResp>('/analytics/overview', { channel, scope })
+export const getOverview = (
+  channel: DashboardChannel, scope: Scope, start?: string, end?: string,
+) =>
+  getJson<OverviewResp>('/analytics/overview', { channel, scope, start, end })
 export const getAnalyticsHealth = () => getJson<HealthResp>('/analytics/health')
 export const getChurn = (params: Record<string, unknown>) =>
   getJson<Page<ChurnRow>>('/analytics/churn', params)

yunkes/src/views/analytics/DashboardView.vue

@@ -11,7 +11,23 @@
         <el-radio-button value="week">本周</el-radio-button>
         <el-radio-button value="month">本月</el-radio-button>
         <el-radio-button value="last30">近30天</el-radio-button>
+        <el-radio-button value="custom">自定义</el-radio-button>
       </el-radio-group>
+      <!-- C1 自定义日期范围:daterange 自保证 start≤end,选完触发 load;
+           跨度>366 天后端 422 走页面 error alert -->
+      <el-date-picker
+        v-if="scope === 'custom'"
+        v-model="customRange"
+        type="daterange"
+        size="small"
+        range-separator="至"
+        start-placeholder="开始日期"
+        end-placeholder="结束日期"
+        value-format="YYYYMMDD"
+        :clearable="false"
+        style="width: 260px"
+        @change="load"
+      />
       <span v-if="asOfText" class="as-of">数据截至 {{ asOfText }}</span>
     </div>
 
@@ -29,6 +45,21 @@
       </el-card>
     </div>
 
+    <!-- B1 客户资产总览:全库存量快照(不随筛选变)——先看客户盘子,再看
+         下方当期经营卡片;分层按最近沟通时间(从未激活=加过没聊过) -->
+    <el-card v-if="assets" shadow="never" class="assets-card">
+      <div class="assets-row">
+        <span class="assets-title">客户资产</span>
+        <span class="asset-item">总客户 <b>{{ fmt(assets.total) }}</b></span>
+        <span class="asset-item">活跃(30天) <b>{{ fmt(assets.active30) }}</b></span>
+        <span class="asset-item">沉默(30-90天) <b>{{ fmt(assets.silent30_90) }}</b></span>
+        <span class="asset-item">沉睡(90天+) <b>{{ fmt(assets.sleeping90p) }}</b></span>
+        <span class="asset-item">从未激活 <b>{{ fmt(assets.never) }}</b></span>
+        <span class="asset-item small">微信 {{ fmt(assets.wechat) }} · WA {{ fmt(assets.whatsapp) }}</span>
+        <span class="asset-item muted">已删好友 {{ fmt(assets.deleted) }}</span>
+      </div>
+    </el-card>
+
     <el-alert v-if="error" type="error" :title="error" :closable="false" class="anomaly" />
 
     <el-alert v-if="anomalyView" type="warning" :closable="false" class="anomaly">
@@ -105,6 +136,27 @@
         <el-table-column label="通话量" align="right">
           <template #default="{ row }">{{ fmt(row.call_cnt) }}</template>
         </el-table-column>
+        <!-- 批2 五新列(2026-09-07 管理者需求):新增客户=当期首沟通;
+             首响/回复率=消息串口径(null=无样本/无串);
+             通话时长/接通率=落窗通话;删粉/拉黑=全库存量(「删/拉」) -->
+        <el-table-column label="新增客户" align="right">
+          <template #default="{ row }">{{ fmt(row.first_contact_cnt) }}</template>
+        </el-table-column>
+        <el-table-column label="首响" align="right">
+          <template #default="{ row }">{{ fmtFr(row.fr_avg_ms) }}</template>
+        </el-table-column>
+        <el-table-column label="回复率" align="right">
+          <template #default="{ row }">{{ fmtPct(row.reply_rate) }}</template>
+        </el-table-column>
+        <el-table-column label="通话时长" align="right">
+          <template #default="{ row }">{{ fmtDur(row.call_seconds) }}</template>
+        </el-table-column>
+        <el-table-column label="接通率" align="right">
+          <template #default="{ row }">{{ fmtPct(row.answer_rate) }}</template>
+        </el-table-column>
+        <el-table-column label="删粉/拉黑" align="right">
+          <template #default="{ row }">{{ fmtDelBlocked(row) }}</template>
+        </el-table-column>
         <el-table-column label="环比" align="right" width="90">
           <template #default="{ row }">
             <span
@@ -121,8 +173,9 @@
 </template>
 
 <script setup lang="ts">
-// A1 数据看板:筛选栏(渠道×时间范围) → 预警行动入口 → 异常警示条 → 五卡片
+// A1 数据看板:筛选栏(渠道×时间范围,自定义日期 C1) → 预警行动入口 →
-// → 30 日趋势折线 → 员工活跃排行表。
+// 客户资产总览(B1 全库快照) → 异常警示条 → 五卡片 → 30 日趋势折线 →
+// 员工活跃排行表(批2 五新列:首响/回复率/新增客户/通话时长+接通率/删粉拉黑)。
 // 看板 v2(2026-09-07):渠道默认「全部」=全平台口径——卡片合计+微信/WA
 // 拆分小字,趋势双线(微信蓝/WA 绿)+legend,行动卡跳转带 query 预选目标页。
 // 数据来自 /analytics/overview + /analytics/health(数据截至角标)。
@@ -130,7 +183,8 @@ import { computed, onMounted, ref, watch } from 'vue'
 import { useRouter } from 'vue-router'
 import {
   getAnalyticsHealth, getOverview, type AnomalyStaff, type Channel,
-  type DashboardChannel, type OverviewResp, type Scope,
+  type CustomerAssets, type DashboardChannel, type OverviewResp, type Scope,
+  type StaffRankingRow,
 } from '@/api/analytics'
 import { useChart } from '@/composables/useChart'
 import { formatTimeShort } from '@/utils/format'
@@ -163,6 +217,8 @@ interface AnomalyView {
 // 渠道默认「全部」(看板 v2:管理人员先看全平台,一眼看清再下钻单渠道)
 const channel = ref<DashboardChannel>('all')
 const scope = ref<Scope>('today')
+// C1 自定义日期范围:[start, end] yyyymmdd 字符串(value-format)
+const customRange = ref<[string, string] | null>(null)
 const trendMetric = ref<'msg' | 'active_customers' | 'call_cnt'>('msg')
 const data = ref<OverviewResp | null>(null)
 const asOf = ref<number | null>(null)
@@ -174,11 +230,19 @@ const { render } = useChart(chartEl)
 let seq = 0 // 竞态守卫:channel/scope 快速切换时旧响应作废(项目惯例)
 
 async function load() {
+  // custom 未选完区间不请求——保留上一次数据等选择(daterange 保证 start≤end)
+  if (scope.value === 'custom' && (!customRange.value?.[0] || !customRange.value?.[1])) {
+    return
+  }
   const my = ++seq
   loading.value = true
   error.value = ''
   try {
-    const ov = await getOverview(channel.value, scope.value)
+    const ov = await getOverview(
+      channel.value, scope.value,
+      scope.value === 'custom' ? customRange.value?.[0] : undefined,
+      scope.value === 'custom' ? customRange.value?.[1] : undefined,
+    )
     if (my !== seq) return
     data.value = ov
   } catch (e) {
@@ -227,6 +291,33 @@ const anomalyView = computed<AnomalyView | null>(() => {
 
 const fmt = (n: number | undefined | null) => (n ?? 0).toLocaleString()
 
+// ── B1 客户资产总览(全库存量,随 overview 载荷回来) ──
+const assets = computed<CustomerAssets | null>(() => data.value?.customer_assets ?? null)
+
+// ── 排行新列格式化 ──
+// 首响:<1h 显「X分Y秒」,≥1h 显「X小时Y分」;null(无样本)显 '-'
+const fmtFr = (ms: number | null) => {
+  if (ms == null) return '-'
+  const totalSec = Math.round(ms / 1000)
+  const mins = Math.floor(totalSec / 60)
+  if (mins < 60) return `${mins}分${totalSec % 60}秒`
+  return `${Math.floor(mins / 60)}小时${mins % 60}分`
+}
+// 百分比 1 位小数(回复率/接通率);null 显 '-'
+const fmtPct = (v: number | null) => (v == null ? '-' : `${(v * 100).toFixed(1)}%`)
+// 通话时长(秒):<1h 显「X分」,否则「X小时Y分」;0/null 显 '-'
+const fmtDur = (s: number | null) => {
+  if (!s) return '-'
+  const mins = Math.round(s / 60)
+  if (mins < 60) return `${mins}分`
+  return `${Math.floor(mins / 60)}小时${mins % 60}分`
+}
+// 删粉/拉黑合并一列「删/拉」;都 0 显 '-'
+const fmtDelBlocked = (r: StaffRankingRow) =>
+  r.deleted_friends || r.blocked_friends
+    ? `${r.deleted_friends}/${r.blocked_friends}`
+    : '-'
+
 // 趋势摘要:先给数字再看图(合计/日均/峰值及日期)
 const trendVals = (): number[] =>
   (data.value?.trend ?? []).map((p) => p[trendMetric.value] as number)
@@ -583,6 +674,42 @@ onMounted(() => {
   font-size: 22px;
   font-weight: 600;
 }
+/* B1 客户资产总览:轻量一行条(参照 action-card 的密度) */
+.assets-card {
+  margin-bottom: 16px;
+}
+.assets-card :deep(.el-card__body) {
+  padding: 10px 14px;
+}
+.assets-row {
+  display: flex;
+  align-items: baseline;
+  flex-wrap: wrap;
+  gap: 4px 20px;
+}
+.assets-title {
+  font-size: 13px;
+  font-weight: 600;
+  color: var(--el-text-color-primary);
+  margin-right: 4px;
+}
+.asset-item {
+  font-size: 13px;
+  color: var(--el-text-color-secondary);
+}
+.asset-item b {
+  font-size: 16px;
+  font-weight: 600;
+  color: var(--el-text-color-primary);
+  margin-left: 2px;
+}
+.asset-item.small {
+  font-size: 12px;
+}
+.asset-item.muted {
+  font-size: 12px;
+  color: var(--el-text-color-placeholder);
+}
 .rank-bar {
   height: 480px;
   margin-bottom: 8px;