feat(analytics): 看板管理化补强——员工活跃排行表+预警行动入口卡片
管理者反馈「纯汇总数字看不到有用信息」:overview 载荷扩 staff_ranking(全员行:msg_total rollup 优先/空表回退 msg_daily_stats 聚合,active_* 两路径统一走 msg_daily_stats 窗内 distinct peer—— stat_daily_staff 的 active_* 是当日快照,跨日 SUM/MAX 语义皆错; call_cnt 按 user_id 落窗直查;环比同期对齐)+ actions(该回未回 2h/ 真流失 30d/敏感词 pending,复用已测试查询路径各取 total)。 前端看板:toolbar 下三张可点行动卡(0 灰显仍可点,直达处置页, 随 channel 切换刷新)+ 趋势卡下员工排行表(max-height 420 滚动, 未映射小 tag,环比色同卡片惯例 None 显 '-')。 测试 574→577 全绿(rollup 聚合/回退/行动计数三新);build 过。 Co-Authored-By: Claude Code <noreply@anthropic.com>
This commit is contained in:
@@ -19,6 +19,7 @@ from app.db.models import (
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Message,
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MsgDailyStats,
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PhoneCall,
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SensitiveHit,
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Staff,
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StatDailyStaff,
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)
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@@ -264,6 +265,189 @@ async def anomaly(session: AsyncSession, channel: str) -> dict | None:
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return None
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async def staff_ranking(
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session: AsyncSession, *, channel: str, scope: str,
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) -> list[dict]:
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"""员工活跃排行(A2 核心子集,2026-09-07 管理者反馈补强)。
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口径:msg_total=stat_daily_staff 聚合(空表回退 msg_daily_stats+映射,
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同 _active_staff 模式);call_cnt=phone_call 按 user_id 落窗直查(3k 行
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小表);环比=与 _prev_scope_days 同期对比(None=前窗无数据);名字取
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staff.name,无 staff 行/未映射账号回退 user_id 原值标 unmapped。
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排序 msg_total desc + user_id asc 决胜。返回全部行(员工 ~41)。
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active_friends/active_rooms 两路径统一从 msg_daily_stats 算窗内
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COUNT(DISTINCT peer)(映射合并到员工后,同 recompute_days 模式):
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stat_daily_staff 的 active_* 是**当日快照**,跨日 SUM 会重复计数、
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MAX 只是峰值,皆非「窗内活跃去重数」——rollup 只供 msg_total,
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避免两路径语义分叉。
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"""
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days = scope_day_keys(scope, today_key())
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amap = await account_map(session, channel)
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# 活跃客户/群 + 回退 msg_total:落窗拉行,Python 侧映射后按 user 去重
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# (COUNT(DISTINCT peer) 必须在「账号合并到员工」之后——同人多账号
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# 跨账号去重,写 SQL 反而绕且踩 only_full_group_by)
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rows = (
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await session.execute(
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sa.select(
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MsgDailyStats.owner_account_id,
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MsgDailyStats.peer_kind,
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MsgDailyStats.peer_id,
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MsgDailyStats.send_cnt,
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MsgDailyStats.recv_cnt,
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).where(
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MsgDailyStats.channel == channel, MsgDailyStats.day.in_(days)
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)
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)
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).all()
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act: dict[str, dict[str, set]] = {}
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msg_fallback: dict[str, int] = {}
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for owner, kind, peer, s, r in rows:
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uid = amap.get(owner, owner)
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a = act.setdefault(uid, {"friends": set(), "rooms": set()})
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if kind == "friend": # 显式分支:未来新 kind 跳过,不误入 rooms
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a["friends"].add(peer)
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elif kind == "room":
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a["rooms"].add(peer)
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msg_fallback[uid] = msg_fallback.get(uid, 0) + int(s or 0) + int(r or 0)
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use_rollup = await _staff_rows(session)
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if use_rollup:
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rollup = (
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await session.execute(
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sa.select(
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StatDailyStaff.user_id,
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sa.func.coalesce(
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sa.func.sum(
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StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
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),
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0,
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),
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)
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.where(
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StatDailyStaff.channel == channel,
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StatDailyStaff.day.in_(days),
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)
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.group_by(StatDailyStaff.user_id)
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)
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).all()
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msg_total = {uid: int(v) for uid, v in rollup}
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else:
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msg_total = msg_fallback
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# 通话:按 user_id 落窗直查(窗口换算同 _call_count 写法)
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calls: dict[str, int] = {}
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if days:
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lo, _ = day_bounds_ms(days[0])
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hi_start, _ = day_bounds_ms(days[-1])
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call_rows = (
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await session.execute(
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sa.select(PhoneCall.user_id, sa.func.count())
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.where(
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PhoneCall.user_id.is_not(None),
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PhoneCall.start_call_time.is_not(None),
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PhoneCall.start_call_time >= lo,
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PhoneCall.start_call_time < hi_start + 86_400_000,
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)
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.group_by(PhoneCall.user_id)
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)
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).all()
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calls = {uid: int(v) for uid, v in call_rows}
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# 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)
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prev_total: dict[str, int] = {}
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if scope in ("week", "month"):
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prev_days = _prev_scope_days(scope, days)
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if use_rollup:
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prev_rows = (
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await session.execute(
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sa.select(
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StatDailyStaff.user_id,
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sa.func.coalesce(
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sa.func.sum(
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StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
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),
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0,
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),
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)
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.where(
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StatDailyStaff.channel == channel,
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StatDailyStaff.day.in_(prev_days),
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)
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.group_by(StatDailyStaff.user_id)
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)
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).all()
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prev_total = {uid: int(v) for uid, v in prev_rows}
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else:
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prev_rows = (
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await session.execute(
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sa.select(
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MsgDailyStats.owner_account_id,
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sa.func.coalesce(
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sa.func.sum(
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MsgDailyStats.send_cnt + MsgDailyStats.recv_cnt
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),
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0,
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),
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)
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.where(
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MsgDailyStats.channel == channel,
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MsgDailyStats.day.in_(prev_days),
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)
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.group_by(MsgDailyStats.owner_account_id)
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)
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).all()
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for owner, v in prev_rows:
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uid = amap.get(owner, owner) # 同人多账号累加,不覆盖
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prev_total[uid] = prev_total.get(uid, 0) + int(v)
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# 名字/未映射:staff 几十行全拉;映射值集=在册员工 user_id 全集
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staff_names = {
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uid: name
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for uid, name in (
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await session.execute(sa.select(Staff.user_id, Staff.name))
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).all()
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}
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mapped_uids = set(amap.values())
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out = []
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for uid in sorted(set(msg_total) | set(act) | set(calls),
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key=lambda u: (-msg_total.get(u, 0), u)):
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cur, prev = msg_total.get(uid, 0), prev_total.get(uid, 0)
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out.append({
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"user_id": uid,
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"name": staff_names.get(uid) or uid,
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"unmapped": uid not in staff_names and uid not in mapped_uids,
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"msg_total": cur,
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"active_friends": len(act[uid]["friends"]) if uid in act else 0,
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"active_rooms": len(act[uid]["rooms"]) if uid in act else 0,
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"call_cnt": calls.get(uid, 0),
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"msg_delta": round((cur - prev) / prev, 3) if cur and prev else None,
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})
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return out
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async def action_counts(session: AsyncSession, *, channel: str) -> dict:
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"""预警行动入口计数(看板顶部卡片):复用已测试的查询路径,各取 total。"""
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un = await unreplied(session, channel=channel, hours=2, page=1, page_size=1)
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ch = await churn(session, channel=channel, kind="real", tier=30, min_msgs=5,
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page=1, page_size=1)
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pending = (
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await session.execute(
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sa.select(sa.func.count()).select_from(SensitiveHit).where(
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SensitiveHit.channel == channel,
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SensitiveHit.disposition == "pending",
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)
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)
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).scalar_one()
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return {
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"unreplied_2h": int(un["total"]),
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"churn_real_30d": int(ch["total"]),
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"sensitive_pending": int(pending),
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}
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async def overview(
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session: AsyncSession, *, channel: str, scope: str, trend_days: int = 30
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) -> dict[str, Any]:
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@@ -341,6 +525,8 @@ async def overview(
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"cards": cards,
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"trend": trend,
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"anomaly": await anomaly(session, channel),
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"staff_ranking": await staff_ranking(session, channel=channel, scope=scope),
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"actions": await action_counts(session, channel=channel),
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}
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@@ -1,12 +1,19 @@
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"""A1 总览指标:卡片/首沟通口径/环比同期对齐(仅周月)/异常警示。"""
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from __future__ import annotations
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import datetime as dt
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import pytest
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from app.analytics import metrics
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from app.db.models import (
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Customer,
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Message,
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MsgDailyStats,
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PhoneCall,
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SensitiveHit,
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SensitiveWord,
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Staff,
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StatDailyStaff,
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WechatAccount,
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)
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@@ -204,3 +211,136 @@ async def test_anomaly_new_staff_detail_and_sort(make_client, monkeypatch):
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assert "new" not in staff["u1"] # 老员工不带标记
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await make_client(seed)
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async def test_staff_ranking(make_client, monkeypatch):
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"""员工活跃排行:rollup 供 msg_total;active_* 统一走 msg_daily_stats 去重。
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_TODAY=20260904 周五 → 本周 [0831..0904],上周 [0824..0828]。
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rollup 的 active_friends 故意 seed 999——若实现误用 rollup 聚合(跨日
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SUM/MAX 皆错)会立刻暴露;正确值=窗内 distinct peer(u1: f1+f2)。
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"""
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monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
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week = [20260831, 20260901, 20260902, 20260903, 20260904]
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prev_week = [20260824, 20260825, 20260826, 20260827, 20260828]
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async def seed(session):
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session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
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session.add(WechatAccount(wx_id="wx2", user_id="u2", user_name="李四"))
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session.add(Staff(user_id="u1", name="张三"))
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session.add(Staff(user_id="u2", name="李四"))
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# rollup:u1 本周 100(5×20),u2 50(5×10);active_* 999=诱饵(不得被采用)
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for d in week:
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session.add(StatDailyStaff(day=d, channel="wechat", user_id="u1",
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msg_sent=20, msg_recv=0,
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active_friends=999, active_rooms=999))
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session.add(StatDailyStaff(day=d, channel="wechat", user_id="u2",
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msg_sent=10, msg_recv=0,
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active_friends=1, active_rooms=0))
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# u3 仅存在于 rollup(无账号映射/无 staff 行)→ 未映射,名字回退 user_id
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session.add(StatDailyStaff(day=20260904, channel="wechat", user_id="u3",
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msg_sent=10, msg_recv=0,
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active_friends=0, active_rooms=0))
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# 上周 rollup:u1 80(5×16) → msg_delta=(100-80)/80=0.25;u2 无前窗→None
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for d in prev_week:
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session.add(StatDailyStaff(day=d, channel="wechat", user_id="u1",
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msg_sent=16, msg_recv=0,
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active_friends=1, active_rooms=0))
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# 活跃指标真源:wx1→u1 两 friend(f1/f2 不同日)+一 room;wx2→u2 一 friend
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for day, kind, peer, owner in [
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(20260831, "friend", "f1", "wx1"), (20260904, "friend", "f2", "wx1"),
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(20260902, "room", "r1", "wx1"), (20260903, "friend", "f1", "wx2"),
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]:
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session.add(MsgDailyStats(channel="wechat", owner_account_id=owner,
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peer_kind=kind, peer_id=peer, day=day,
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send_cnt=1, recv_cnt=0,
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last_ts=1788500000000, last_is_send=True))
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# 通话:u1 一通落窗(1788500000000=2026-09-04 当日);u2 的在 2025 年不计
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session.add(PhoneCall(call_id="cr1", channel="voice_call", user_id="u1",
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start_call_time=1788500000000, call_duration=60))
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session.add(PhoneCall(call_id="cr2", channel="voice_call", user_id="u2",
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start_call_time=1756950000000, call_duration=60))
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await session.commit()
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out = await metrics.staff_ranking(session, channel="wechat", scope="week")
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assert [r["user_id"] for r in out] == ["u1", "u2", "u3"] # msg_total 降序
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r1, r2, r3 = out
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assert r1["name"] == "张三" and r1["unmapped"] is False
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assert r1["msg_total"] == 100 # rollup 聚合
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assert r1["active_friends"] == 2 # distinct peer,非 rollup 的 999
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assert r1["active_rooms"] == 1
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assert r1["call_cnt"] == 1
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assert r1["msg_delta"] == 0.25 # (100-80)/80
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assert r2["msg_total"] == 50 and r2["active_friends"] == 1
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assert r2["active_rooms"] == 0 and r2["call_cnt"] == 0 # 窗外通话不计
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assert r2["msg_delta"] is None # 前窗无数据
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assert r3["name"] == "u3" and r3["unmapped"] is True
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assert r3["msg_total"] == 10 and r3["active_friends"] == 0
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await make_client(seed)
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async def test_staff_ranking_fallback_when_rollup_empty(make_client, monkeypatch):
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"""stat_daily_staff 空表 → msg_total 回退 msg_daily_stats 聚合(部署即用)。"""
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monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
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async def seed(session):
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session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
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session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
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peer_kind="friend", peer_id="t1", day=20260904,
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send_cnt=10, recv_cnt=5, last_ts=1788500000000,
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last_is_send=True))
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# wx9 无账号行 → 映射不上按 owner 原值计入并标未映射
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session.add(MsgDailyStats(channel="wechat", owner_account_id="wx9",
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peer_kind="friend", peer_id="t2", day=20260904,
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send_cnt=2, recv_cnt=0, last_ts=1788500000000,
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last_is_send=True))
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await session.commit()
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out = await metrics.staff_ranking(session, channel="wechat", scope="today")
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assert [r["user_id"] for r in out] == ["u1", "wx9"]
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assert out[0]["msg_total"] == 15 and out[0]["active_friends"] == 1
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assert out[0]["unmapped"] is False
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assert out[0]["msg_delta"] is None # 今日 scope 无环比
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assert out[1]["msg_total"] == 2 and out[1]["unmapped"] is True
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assert out[1]["name"] == "wx9"
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await make_client(seed)
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async def test_action_counts(make_client, monkeypatch):
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"""预警行动入口:unreplied 走真实路径,churn/sensitive 各计 pending/真流失。"""
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monkeypatch.setattr(metrics, "_now_ms", lambda: 1756950000000)
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async def seed(session):
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now = 1756950000000
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h3 = 3 * 3600 * 1000
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# 该回未回 1 条:客户尾向 3h 前 + 有效 text 消息
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session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
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peer_kind="friend", peer_id="t1", day=20260904,
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send_cnt=5, recv_cnt=3, last_ts=now - h3,
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last_is_send=False))
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session.add(Message(msg_id="t1m", channel="wechat", owner_account_id="wx1",
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talker_id="t1", timestamp=now - h3, is_send=False,
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type="text", text="在吗,方案发我一下",
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fetched_at=dt.datetime(2026, 9, 4, 12, 0)))
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# 真流失 1 条:沉默 45 天 + 历史 ≥5
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day_ms = 86_400_000
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session.add(Customer(friend_id="c_real", channel="wechat",
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owner_account_id="wx1", user_id="u1",
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last_chat_time=now - 45 * day_ms, delete_flag=0))
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session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
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peer_kind="friend", peer_id="c_real", day=20260601,
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send_cnt=6, recv_cnt=0, last_ts=now - 50 * day_ms,
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last_is_send=True))
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# 敏感词:1 pending + 1 confirmed(只计 pending)
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w = SensitiveWord(word="测试词")
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session.add(w)
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await session.flush()
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session.add(SensitiveHit(word_id=w.id, msg_id="m1", channel="wechat",
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disposition="pending"))
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session.add(SensitiveHit(word_id=w.id, msg_id="m2", channel="wechat",
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||||
disposition="confirmed"))
|
||||
await session.commit()
|
||||
|
||||
out = await metrics.action_counts(session, channel="wechat")
|
||||
assert out == {"unreplied_2h": 1, "churn_real_30d": 1,
|
||||
"sensitive_pending": 1}
|
||||
|
||||
await make_client(seed)
|
||||
|
||||
Reference in New Issue
Block a user