feat(management): 只读管理API六端点——dashboard/employees/detail/sections/drilldown白名单/指标定义
Co-Authored-By: Claude Code <noreply@anthropic.com>
This commit is contained in:
浅念
@@ -49,6 +49,7 @@ from app.api.routers import (
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export,
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groups,
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login,
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management,
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media,
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messages,
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moments,
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@@ -101,6 +102,7 @@ app.include_router(sessions.router)
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app.include_router(export.router)
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app.include_router(voice_clips.router)
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app.include_router(analytics.router)
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app.include_router(management.router)
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@app.get("/api/health")
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@@ -0,0 +1,588 @@
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"""GET /api/management/* —— 经营管理后台只读端组(批次B Task B4)。
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六个端点:dashboard(总览)/ employees(列表,一期四视图共用行集)/
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employees/{user_id}(详情)/ employees/{user_id}/metrics(分段指标+趋势)/
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employees/{user_id}/drilldown(白名单下钻)/ metric-definitions(口径字典)。
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惯例同 analytics.py:channel=all 在 router 层翻译为 None 传服务层;
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start/end yyyymmdd 缺一/日历非法/start>end/跨度>366 天皆 422(_window);
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重查询与行构造在 app.management.api_assembly,本文件只做薄编排。
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所有查询共用单 AsyncSession——**顺序 await,不并发**(见 assembly 模块)。
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"""
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from __future__ import annotations
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import datetime as dt
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from typing import Annotated, Any, Literal
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import sqlalchemy as sa
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.analytics import health as health_svc
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from app.analytics import metrics as metrics_svc
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from app.api.deps import get_session
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from app.db.models import (
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FirstReplyFact,
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PhoneCall,
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Staff,
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WechatAccount,
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WhatsappAccount,
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)
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from app.management import api_assembly as asm
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from app.management.anomalies import detect_anomalies
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from app.management.employee_metrics import (
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baseline_window,
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day_range,
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period_metrics,
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prev_window,
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)
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from app.management.metric_definitions import METRIC_DEFINITIONS
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from app.storage.employee_metrics import METRIC_VERSION
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from app.storage.staff_summary import account_map
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from app.storage.summary import day_bounds_ms
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router = APIRouter(prefix="/api/management", tags=["management"])
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SessionDep = Annotated[AsyncSession, Depends(get_session)]
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AllChannelParam = Annotated[Literal["all", "wechat", "whatsapp"], Query()]
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YmdParam = Annotated[int, Query(ge=20000101, le=29991231)]
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CompareParam = Annotated[
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Literal["previous", "personal_baseline", "team_median"], Query()
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]
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ViewParam = Annotated[
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Literal["management", "workload", "service", "customer"], Query()
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]
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StatusParam = Annotated[Literal["all", "on_job", "offline"], Query()]
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SortByParam = Annotated[
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Literal["anomaly_severity", "total_score", "active_friends", "cust_threads"],
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Query(),
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]
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SortOrderParam = Annotated[Literal["asc", "desc"], Query()]
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SectionParam = Annotated[
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Literal["overview", "service", "customer", "workload", "calls"], Query()
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]
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# drilldown 白名单(外 422 "unknown metric_code")
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_DRILLDOWN_CODES = frozenset({
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"first_reply_p50", "first_reply_p90", "unreplied",
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"cooling_customers", "dormant_customers", "call_followup",
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})
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# unreplied 适配:上游无私有 owner 过滤,取全量决赛圈结果再按 owner 过滤。
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# 500 = analytics.metrics._FINALIZE_ALL_MAX 同值(候选 ≤500 时单次调用即
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# 拿到全部已过滤 items;超过则上游本就按候选分页,响应标 truncated)。
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_UNREPLIED_FETCH = 500
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# 三方口径差异说明(硬编码,与 METRIC_DEFINITIONS.caliber 互补的总述)
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CALIBER_NOTES = (
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"管理域指标为 1:1 私聊口径且跨日精确(消息串按会话全历史计算、"
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"归属串末条所在自然日);现有看板为私聊+群聊混合、日切口径"
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"(跨夜串重复计/丢失,回复率分子分母同源近似)。"
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"通话指标(通话数/时长/接通/跟进)无消息渠道维度——"
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"voice_call 与 wa_voice_call 合并计数,不随 channel 参数过滤。"
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)
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# 各 section 的期指标字段(自 PeriodMetrics 挑)与宽表/通话表趋势列
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_SECTION_FIELDS: dict[str, tuple[str, ...]] = {
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"overview": ("days_with_data", "msg_sent", "msg_recv", "active_friends",
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"active_rooms_avg"),
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"service": ("cust_threads", "threads_answered", "fr_sum_ms",
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"fr_p50_ms", "fr_p90_ms", "reply_2h_count", "reply_24h_count"),
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"customer": ("new_customer", "cooling_customer", "dormant_customer",
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"reactivated_customer", "end_active_friends"),
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"workload": ("active_friends", "active_rooms_avg", "cust_threads"),
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"calls": ("call_count", "call_seconds", "answered_call", "call_followup"),
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}
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_SECTION_TREND_COLS: dict[str, tuple[str, ...]] = {
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"overview": ("msg_sent", "msg_recv", "active_friends"),
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"service": ("cust_threads", "threads_answered", "fr_sum_ms",
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"first_reply_p50_ms", "first_reply_p90_ms"),
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"customer": ("new_customer_count", "cooling_customer_count",
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"dormant_customer_count", "reactivated_customer_count"),
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"workload": ("active_friends", "active_rooms"),
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"calls": ("call_count", "call_seconds", "answered_call_count",
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"call_followup_count"),
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}
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def _window(start: int | None, end: int | None) -> tuple[int, int]:
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"""管理端点公共窗口校验(照 analytics custom scope 惯例)。"""
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if start is None or end is None:
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raise HTTPException(422, "start and end are required")
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try:
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sd = dt.date(start // 10000, (start // 100) % 100, start % 100)
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ed = dt.date(end // 10000, (end // 100) % 100, end % 100)
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except ValueError as exc: # 如 20260230——Query 只拦范围不拦日历
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raise HTTPException(422, "invalid start/end calendar date") from exc
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if sd > ed:
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raise HTTPException(422, "start must be <= end")
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if (ed - sd).days > 365: # 含端点共 366 天
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raise HTTPException(422, "span must be <= 366 days")
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return start, end
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def _translate(channel: str) -> str | None:
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return None if channel == "all" else channel
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async def _get_staff(session: AsyncSession, user_id: str) -> Staff:
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staff = (await session.execute(
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sa.select(Staff).where(Staff.user_id == user_id)
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)).scalar_one_or_none()
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if staff is None:
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raise HTTPException(404, f"employee {user_id} not found")
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return staff
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@router.get("/dashboard")
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async def management_dashboard(
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session: SessionDep,
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channel: AllChannelParam = "all",
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start: YmdParam | None = None,
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end: YmdParam | None = None,
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compare: CompareParam = "previous",
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) -> dict[str, Any]:
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"""经营管理总览:KPI + 双趋势 + 生命周期 + 维度分布 + 异常汇总 +
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行动入口计数,单往返。compare 仅回显(对比数值在 employees 行内)。"""
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start, end = _window(start, end)
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ch = _translate(channel)
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config, config_source = await asm.load_score_config(session)
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assembled = await asm.assemble_employees(
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session, config, start, end, ch, with_prev=False
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)
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pms = [a["cur"] for a in assembled.values()]
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# ---- 趋势两查:宽表全员逐日 + 通话小表逐日 + fact 逐日 ----
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wide = await asm.wide_daily_rows(session, start, end, ch)
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wide_by_day = {d["day"]: d for d in wide}
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threads_by_day = {d["day"]: d["cust_threads"] for d in wide}
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calls = await asm.call_daily_rows(session, start, end)
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call_by_day = {d["day"]: d["call_count"] for d in calls}
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comm_trend = []
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for day in day_range(start, end):
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d = wide_by_day.get(day)
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comm_trend.append({
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"day": day,
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"msg_total": (d["msg_sent"] + d["msg_recv"]) if d else 0,
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# 团队合计口径:当日各员工宽表 active_friends 求和
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"active_customers": d["active_friends"] if d else 0,
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"call_cnt": call_by_day.get(day, 0),
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})
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service_trend = await asm.service_daily_trend(
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session, start, end, ch, threads_by_day
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)
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lifecycle = {
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"new": sum(p.new_customer for p in pms),
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"cooling": sum(p.cooling_customer for p in pms),
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"dormant": sum(p.dormant_customer for p in pms),
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"reactivated": sum(p.reactivated_customer for p in pms),
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}
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kpis = {
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# 全员 active_friends 求和:跨员工可能重复计客户(共享客户)
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"active_customers": sum(p.active_friends for p in pms),
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"active_employees": sum(1 for p in pms if p.days_with_data > 0),
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"msg_total": sum(p.msg_sent + p.msg_recv for p in pms),
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"cust_threads": sum(p.cust_threads for p in pms),
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"threads_answered": sum(p.threads_answered for p in pms),
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"call_count": sum(p.call_count for p in pms),
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"call_seconds": sum(p.call_seconds for p in pms),
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"answered_call": sum(p.answered_call for p in pms),
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"lifecycle": lifecycle,
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}
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# ---- 维度分布(全员 score_employee 的维度状态计数) ----
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dim_summary: dict[str, dict] = {}
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for a in assembled.values():
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for key, dim in a["score"]["dimensions"].items():
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e = dim_summary.setdefault(key, {
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"name": dim.get("name"), "weight": dim.get("weight", 0),
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"scored_count": 0, "insufficient_count": 0,
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"pending_count": 0, "_scores": [],
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})
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if dim["status"] == "scored":
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e["scored_count"] += 1
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e["_scores"].append(dim["score"])
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elif dim["status"] == "insufficient":
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e["insufficient_count"] += 1
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else: # pending / pending_data
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e["pending_count"] += 1
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for e in dim_summary.values():
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scores = e.pop("_scores")
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e["avg_score"] = (
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sum(scores) / len(scores) if scores else None
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)
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# ---- 异常汇总:critical 先、warning 后,同 severity 按 affected desc ----
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anomalies = [a for data in assembled.values() for a in data["anomalies"]]
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sev_rank = {"critical": 0, "warning": 1}
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anomalies.sort(key=lambda a: (
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sev_rank.get(a["severity"], 9),
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-a.get("affected_count", 0),
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a["employee_user_id"],
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))
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return {
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"scope": {"channel": channel, "start": start, "end": end,
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"compare": compare},
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"data_as_of": await health_svc.data_as_of(session),
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"metric_version": METRIC_VERSION,
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"config_source": config_source,
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"kpis": kpis,
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"communication_trend": comm_trend,
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"service_trend": service_trend,
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"lifecycle": lifecycle,
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"dimension_summary": dim_summary,
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"anomalies": anomalies,
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"action_summary": await metrics_svc.action_counts(session, channel=ch),
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"caliber_notes": {
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"active_customers": "kpis.active_customers 为全员周期 distinct "
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"求和,跨员工共享客户可能重复计",
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"trend_active_customers": "communication_trend.active_customers "
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"为宽表日值团队合计(日口径求和)",
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"reply_2h_rate": "分子=fact 当日 ≤2h 计数,分母=宽表当日串数",
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},
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}
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@router.get("/employees")
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async def management_employees(
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session: SessionDep,
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channel: AllChannelParam = "all",
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start: YmdParam | None = None,
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end: YmdParam | None = None,
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view: ViewParam = "management",
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keyword: str | None = None,
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status: StatusParam = "all",
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sort_by: SortByParam = "anomaly_severity",
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sort_order: SortOrderParam = "desc",
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page: int = Query(1, ge=1),
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page_size: int = Query(20, ge=1, le=100),
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) -> dict[str, Any]:
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"""员工列表(一期 management/workload/service/customer 四视图共用
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行集,view 仅回显)。默认 anomaly_severity 排序:含 critical 者 →
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权重和 → 卡片数;total_score 排序 None 恒排最后。"""
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start, end = _window(start, end)
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ch = _translate(channel)
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config, config_source = await asm.load_score_config(session)
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assembled = await asm.assemble_employees(
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session, config, start, end, ch, with_prev=True
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)
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items = list(assembled.items())
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if ch is not None:
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# 渠道过滤=账号归属(该渠道无账号的员工不进列表;有账号无数据仍
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# 展示零值行)
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owners_uids = set((await account_map(session, ch)).values())
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items = [(u, d) for u, d in items if u in owners_uids]
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if keyword:
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kw = keyword.strip().lower()
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items = [
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(u, d) for u, d in items
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if kw in (d["name"] or "").lower() or kw in u.lower()
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]
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if status == "on_job":
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items = [(u, d) for u, d in items if d["is_on_job"] is True]
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elif status == "offline":
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items = [(u, d) for u, d in items if d["is_on_job"] is not True]
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items.sort(key=lambda kv: kv[0]) # 决胜底座:user_id asc(稳定排序)
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if sort_by == "anomaly_severity":
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items.sort(key=lambda kv: (
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any(a["severity"] == "critical" for a in kv[1]["anomalies"]),
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kv[1]["anomaly_weight"], kv[1]["anomaly_count"],
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), reverse=(sort_order == "desc"))
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elif sort_by == "total_score":
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# None(样本不足等)恒排最后,与升降序无关
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if sort_order == "desc":
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items.sort(key=lambda kv: (
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kv[1]["score"]["total_score"] is None,
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-(kv[1]["score"]["total_score"] or 0),
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))
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else:
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items.sort(key=lambda kv: (
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kv[1]["score"]["total_score"] is None,
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kv[1]["score"]["total_score"] or 0,
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))
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else: # active_friends / cust_threads(PeriodMetrics 数值列)
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if sort_order == "desc":
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items.sort(key=lambda kv: -getattr(kv[1]["cur"], sort_by))
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else:
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items.sort(key=lambda kv: getattr(kv[1]["cur"], sort_by))
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total = len(items)
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page_rows = items[(page - 1) * page_size: page * page_size]
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return {
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"total": total,
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"page": page,
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"page_size": page_size,
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"rows": [asm.build_employee_row(u, d) for u, d in page_rows],
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"scope": {"channel": channel, "start": start, "end": end,
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"view": view},
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"data_as_of": await health_svc.data_as_of(session),
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"metric_version": METRIC_VERSION,
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"config_source": config_source,
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}
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@router.get("/employees/{user_id}")
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async def management_employee_detail(
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session: SessionDep,
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user_id: str,
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channel: AllChannelParam = "all",
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start: YmdParam | None = None,
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end: YmdParam | None = None,
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) -> dict[str, Any]:
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"""员工详情:身份+账号清单+期指标全字段+评分完整明细(含逐指标
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metrics_detail)+异常卡片+prev/baseline 原始 PeriodMetrics。"""
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start, end = _window(start, end)
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ch = _translate(channel)
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staff = await _get_staff(session, user_id)
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config, config_source = await asm.load_score_config(session)
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cur_map = await period_metrics(session, start, end, ch, user_ids={user_id})
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bs, be = baseline_window(start)
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base_map = await period_metrics(session, bs, be, ch, user_ids={user_id})
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ps, pe = prev_window(start, end)
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prev_map = await period_metrics(session, ps, pe, ch, user_ids={user_id})
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cur, base, prev = (cur_map.get(user_id), base_map.get(user_id),
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prev_map.get(user_id))
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if cur is None: # 防御:_get_staff 已保证在 staff,period_metrics 必含
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raise HTTPException(404, f"employee {user_id} not found")
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team = asm.team_derived_medians(
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await period_metrics(session, start, end, ch)
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)
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score = asm.score_with_guards(config, cur, baseline=base, team=team,
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prev=prev)
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||||
anomalies = detect_anomalies(
|
||||
user_id, cur, base, n_days=len(day_range(start, end)), config=config
|
||||
)
|
||||
|
||||
accounts: list[dict] = []
|
||||
for wa in (await session.execute(
|
||||
sa.select(WechatAccount).where(WechatAccount.user_id == user_id)
|
||||
)).scalars():
|
||||
accounts.append({
|
||||
"channel": "wechat", "account_id": wa.wx_id,
|
||||
"nick_name": wa.nick_name, "user_name": wa.user_name,
|
||||
})
|
||||
for wa in (await session.execute(
|
||||
sa.select(WhatsappAccount).where(WhatsappAccount.user_id == user_id)
|
||||
)).scalars():
|
||||
accounts.append({
|
||||
"channel": "whatsapp", "account_id": wa.uid,
|
||||
"nick_name": wa.nick_name, "user_name": wa.user_name,
|
||||
})
|
||||
|
||||
return {
|
||||
"user_id": user_id,
|
||||
"name": staff.name,
|
||||
"is_on_job": staff.is_on_job,
|
||||
"accounts": accounts,
|
||||
"metrics": cur._asdict(),
|
||||
"score": score,
|
||||
"anomalies": anomalies,
|
||||
"prev": prev._asdict() if prev is not None else None,
|
||||
"baseline": base._asdict() if base is not None else None,
|
||||
"scope": {"channel": channel, "start": start, "end": end},
|
||||
"data_as_of": await health_svc.data_as_of(session),
|
||||
"metric_version": METRIC_VERSION,
|
||||
"config_source": config_source,
|
||||
}
|
||||
|
||||
|
||||
@router.get("/employees/{user_id}/metrics")
|
||||
async def management_employee_metrics(
|
||||
session: SessionDep,
|
||||
user_id: str,
|
||||
section: SectionParam = "overview",
|
||||
channel: AllChannelParam = "all",
|
||||
start: YmdParam | None = None,
|
||||
end: YmdParam | None = None,
|
||||
) -> dict[str, Any]:
|
||||
"""员工分段指标:该域期指标 + 窗口逐日趋势 + 四对比
|
||||
(current/prev/baseline/median,派生率走 scoring.derive_metrics 口径)。"""
|
||||
start, end = _window(start, end)
|
||||
ch = _translate(channel)
|
||||
await _get_staff(session, user_id)
|
||||
cur_map = await period_metrics(session, start, end, ch, user_ids={user_id})
|
||||
bs, be = baseline_window(start)
|
||||
base_map = await period_metrics(session, bs, be, ch, user_ids={user_id})
|
||||
ps, pe = prev_window(start, end)
|
||||
prev_map = await period_metrics(session, ps, pe, ch, user_ids={user_id})
|
||||
cur, base, prev = (cur_map.get(user_id), base_map.get(user_id),
|
||||
prev_map.get(user_id))
|
||||
if cur is None:
|
||||
raise HTTPException(404, f"employee {user_id} not found")
|
||||
team = asm.team_derived_medians(
|
||||
await period_metrics(session, start, end, ch)
|
||||
)
|
||||
|
||||
if section == "calls":
|
||||
src_rows = await asm.call_daily_rows(session, start, end,
|
||||
user_id=user_id)
|
||||
else:
|
||||
src_rows = await asm.wide_daily_rows(session, start, end, ch,
|
||||
user_id=user_id)
|
||||
by_day = {r["day"]: r for r in src_rows}
|
||||
cols = _SECTION_TREND_COLS[section]
|
||||
trend = []
|
||||
for day in day_range(start, end):
|
||||
row = by_day.get(day)
|
||||
point: dict[str, Any] = {"day": day}
|
||||
for col in cols:
|
||||
if row is not None:
|
||||
point[col] = row.get(col)
|
||||
else: # 无数据日:计数列补 0,分位列补 None
|
||||
point[col] = None if col.startswith("first_reply") else 0
|
||||
trend.append(point)
|
||||
|
||||
return {
|
||||
"section": section,
|
||||
"metrics": {f: getattr(cur, f) for f in _SECTION_FIELDS[section]},
|
||||
"trend": trend,
|
||||
"comparisons": asm.derived_comparisons(cur, prev, base, team),
|
||||
"scope": {"channel": channel, "start": start, "end": end,
|
||||
"user_id": user_id},
|
||||
"data_as_of": await health_svc.data_as_of(session),
|
||||
"metric_version": METRIC_VERSION,
|
||||
}
|
||||
|
||||
|
||||
@router.get("/employees/{user_id}/drilldown")
|
||||
async def management_employee_drilldown(
|
||||
session: SessionDep,
|
||||
user_id: str,
|
||||
metric_code: str,
|
||||
channel: AllChannelParam = "all",
|
||||
start: YmdParam | None = None,
|
||||
end: YmdParam | None = None,
|
||||
page: int = Query(1, ge=1),
|
||||
page_size: int = Query(20, ge=1, le=100),
|
||||
) -> dict[str, Any]:
|
||||
"""指标下钻(白名单六项,外 422):首响分位逐串证据 / 未回串 /
|
||||
降温·沉睡客户名单 / 通话跟进列表。所有分支按员工 owner 账号过滤。"""
|
||||
if metric_code not in _DRILLDOWN_CODES:
|
||||
raise HTTPException(422, f"unknown metric_code: {metric_code}")
|
||||
start, end = _window(start, end)
|
||||
ch = _translate(channel)
|
||||
await _get_staff(session, user_id)
|
||||
scope = {"user_id": user_id, "metric_code": metric_code,
|
||||
"channel": channel, "start": start, "end": end}
|
||||
owners = await asm.user_owner_accounts(session, user_id, ch)
|
||||
|
||||
def _paged(items: list[dict]) -> dict[str, Any]:
|
||||
ix = (page - 1) * page_size
|
||||
return {"items": items[ix: ix + page_size], "total": len(items),
|
||||
"page": page, "page_size": page_size, "scope": scope}
|
||||
|
||||
if metric_code in ("first_reply_p50", "first_reply_p90"):
|
||||
if not owners:
|
||||
return _paged([])
|
||||
conds = [FirstReplyFact.day.between(start, end),
|
||||
FirstReplyFact.owner_account_id.in_(owners)]
|
||||
if ch is not None:
|
||||
conds.append(FirstReplyFact.channel == ch)
|
||||
total = (await session.execute(
|
||||
sa.select(sa.func.count()).select_from(FirstReplyFact)
|
||||
.where(*conds)
|
||||
)).scalar_one()
|
||||
rows = (await session.execute(
|
||||
sa.select(FirstReplyFact).where(*conds)
|
||||
.order_by(FirstReplyFact.fr_ms.desc(), FirstReplyFact.day.desc(),
|
||||
FirstReplyFact.thread_end_ts.desc())
|
||||
.offset((page - 1) * page_size).limit(page_size)
|
||||
)).scalars().all()
|
||||
items = [{
|
||||
"day": f.day,
|
||||
"owner_account_id": f.owner_account_id,
|
||||
"peer_id": f.peer_id,
|
||||
"thread_end_ts": f.thread_end_ts,
|
||||
"reply_ts": f.reply_ts,
|
||||
"fr_ms": f.fr_ms,
|
||||
# 会话定位参数提示(owner+talker 直达聊天记录)
|
||||
"chat_hint": {"owner_account_id": f.owner_account_id,
|
||||
"talker_id": f.peer_id},
|
||||
} for f in rows]
|
||||
return {"items": items, "total": int(total), "page": page,
|
||||
"page_size": page_size, "scope": scope}
|
||||
|
||||
if metric_code == "unreplied":
|
||||
# 上游无私有 owner 过滤:一次拉全量决赛圈结果(候选 ≤500 时完整),
|
||||
# 按 owner 账号过滤后内存分页;候选超限标 truncated(过滤可能不全)
|
||||
res = await metrics_svc.unreplied(
|
||||
session, channel=ch, hours=24, page=1, page_size=_UNREPLIED_FETCH
|
||||
)
|
||||
owner_set = set(owners)
|
||||
owned = [i for i in res["items"]
|
||||
if i["owner_account_id"] in owner_set]
|
||||
out = _paged(owned)
|
||||
out["note"] = ("按该员工 owner 账号自全量未回清单过滤"
|
||||
"(hours=24,与看板清单同源同判定)")
|
||||
if res["total"] > len(res["items"]):
|
||||
out["truncated"] = True
|
||||
return out
|
||||
|
||||
if metric_code in ("cooling_customers", "dormant_customers"):
|
||||
want = ("cooling" if metric_code == "cooling_customers"
|
||||
else "dormant")
|
||||
if not owners:
|
||||
return _paged([])
|
||||
matches = await asm.lifecycle_customers(session, owners, end, want)
|
||||
return _paged(matches)
|
||||
|
||||
# call_followup:窗口通话列表(start desc)+ 期聚合摘要
|
||||
# (逐通话跟进标记复用批次A _followup_exists 太重,留批次C按需再加)
|
||||
lo, _ = day_bounds_ms(start)
|
||||
_, hi = day_bounds_ms(end)
|
||||
conds = [PhoneCall.user_id == user_id,
|
||||
PhoneCall.start_call_time.is_not(None),
|
||||
PhoneCall.start_call_time >= lo,
|
||||
PhoneCall.start_call_time < hi]
|
||||
total = (await session.execute(
|
||||
sa.select(sa.func.count()).select_from(PhoneCall).where(*conds)
|
||||
)).scalar_one()
|
||||
rows = (await session.execute(
|
||||
sa.select(PhoneCall).where(*conds)
|
||||
.order_by(PhoneCall.start_call_time.desc(), PhoneCall.call_id.desc())
|
||||
.offset((page - 1) * page_size).limit(page_size)
|
||||
)).scalars().all()
|
||||
items = [{
|
||||
"call_id": c.call_id,
|
||||
"channel": c.channel,
|
||||
"call_number": c.call_number,
|
||||
"start_call_time": c.start_call_time,
|
||||
"call_duration": c.call_duration,
|
||||
} for c in rows]
|
||||
summary_rows = await asm.call_daily_rows(session, start, end,
|
||||
user_id=user_id)
|
||||
summary = {col: sum(r[col] for r in summary_rows)
|
||||
for col in ("call_count", "call_seconds",
|
||||
"answered_call_count", "call_followup_count")}
|
||||
return {"items": items, "total": int(total), "page": page,
|
||||
"page_size": page_size, "summary": summary, "scope": scope,
|
||||
"note": "逐通话跟进标记留批次C;此处为窗口通话列表+期聚合"
|
||||
"(followup 为接通后24h内有跟进的通话数)"}
|
||||
|
||||
|
||||
@router.get("/metric-definitions")
|
||||
async def management_metric_definitions(
|
||||
session: SessionDep,
|
||||
) -> dict[str, Any]:
|
||||
"""指标口径字典 + 当前评分配置(含 pending 维度)+ 三方口径差异说明。
|
||||
config_source: "db"=激活配置 / "default"=未种子回退默认。"""
|
||||
config, source = await asm.load_score_config(session)
|
||||
return {
|
||||
"definitions": METRIC_DEFINITIONS,
|
||||
"score_config": {
|
||||
"version": config.get("version"),
|
||||
"name": config.get("name"),
|
||||
"trial": config.get("trial"),
|
||||
"normalization": config.get("normalization"),
|
||||
"sample_guards": config.get("sample_guards"),
|
||||
"grade_bounds": config.get("grade_bounds"),
|
||||
"dimensions": config.get("dimensions"),
|
||||
},
|
||||
"config_source": source,
|
||||
"caliber_notes": CALIBER_NOTES,
|
||||
}
|
||||
@@ -0,0 +1,447 @@
|
||||
"""管理 API 组装层(批次B Task B4)——router 六端点共用的重查询与行构造。
|
||||
|
||||
拆出 router 的原因:employees/dashboard 的组装(多窗聚合 + 评分 + 异常 +
|
||||
对比派生)上百行,放 router 会淹没端点定义;本模块只做数据组装,参数
|
||||
校验/HTTP 语义留在 router。
|
||||
|
||||
查询纪律(与 analytics.metrics 同):**禁止 asyncio.gather**——单
|
||||
AsyncSession 不能并发执行查询,全部顺序 await。重端点不做 N+1:
|
||||
period_metrics 每窗一次调用全员;员工循环(评分/异常)是纯函数。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import copy
|
||||
import statistics
|
||||
from bisect import bisect_right
|
||||
|
||||
import sqlalchemy as sa
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.analytics.lifecycle import classify
|
||||
from app.db.models import (
|
||||
Customer,
|
||||
EmployeeCallDaily,
|
||||
EmployeeMetricDaily,
|
||||
EmployeeScoreConfig,
|
||||
FirstReplyFact,
|
||||
MsgDailyStats,
|
||||
Staff,
|
||||
)
|
||||
from app.management.anomalies import detect_anomalies
|
||||
from app.management.employee_metrics import (
|
||||
PeriodMetrics,
|
||||
baseline_window,
|
||||
day_range,
|
||||
period_metrics,
|
||||
prev_window,
|
||||
team_medians,
|
||||
)
|
||||
from app.management.metric_definitions import DEFAULT_SCORE_CONFIG
|
||||
from app.management.scoring import derive_metrics, score_employee
|
||||
from app.storage.employee_metrics import METRIC_VERSION
|
||||
from app.storage.staff_summary import account_map
|
||||
|
||||
# 异常权重(anomaly_severity 排序/汇总):critical=2 / warning=1
|
||||
SEVERITY_WEIGHT = {"critical": 2, "warning": 1}
|
||||
|
||||
# 派生指标中需对「员工派生值」另取中位的键(scoring.team 键=派生指标名;
|
||||
# 其余如 fr_p90_ms/active_friends/call_count 直接用 team_medians 输出)
|
||||
_DERIVED_MEDIAN_KEYS = ("reply_2h_rate", "reply_24h_rate", "active_share")
|
||||
|
||||
|
||||
async def load_score_config(session: AsyncSession) -> tuple[dict, str]:
|
||||
"""激活评分配置(DB)→ (config_json, "db");无 active 行 →
|
||||
(DEFAULT_SCORE_CONFIG 深拷贝, "default")——未跑种子的环境也能出分。"""
|
||||
row = (await session.execute(
|
||||
sa.select(EmployeeScoreConfig)
|
||||
.where(EmployeeScoreConfig.status == "active")
|
||||
.order_by(EmployeeScoreConfig.id.desc())
|
||||
.limit(1)
|
||||
)).scalar_one_or_none()
|
||||
if row is not None:
|
||||
return row.config_json, "db"
|
||||
return copy.deepcopy(DEFAULT_SCORE_CONFIG), "default"
|
||||
|
||||
|
||||
def percentile_nearest(
|
||||
vals: list[int], q_num: int, q_den: int
|
||||
) -> int | None:
|
||||
"""最近邻秩分位 ceil(q·n)(与批次A/employee_metrics 同口径,自写 5 行
|
||||
避免跨层引私有 _percentile);空列表→None(与 0 严格区分)。"""
|
||||
if not vals:
|
||||
return None
|
||||
s = sorted(vals)
|
||||
rank = max(1, min(len(s), (q_num * len(s) + q_den - 1) // q_den))
|
||||
return s[rank - 1]
|
||||
|
||||
|
||||
def team_derived_medians(metrics: dict[str, PeriodMetrics]) -> dict[str, float | None]:
|
||||
"""评分用团队中位:PeriodMetrics 字段中位 + 派生率/占比的员工级中位
|
||||
(scoring 要求 team 键=派生指标名,见其模块 docstring)。"""
|
||||
team = dict(team_medians(metrics))
|
||||
for key in _DERIVED_MEDIAN_KEYS:
|
||||
vals = [
|
||||
v for v in (derive_metrics(pm).get(key) for pm in metrics.values())
|
||||
if v is not None
|
||||
]
|
||||
team[key] = statistics.median(vals) if vals else None
|
||||
return team
|
||||
|
||||
|
||||
def score_with_guards(
|
||||
config: dict,
|
||||
cur: PeriodMetrics,
|
||||
baseline: PeriodMetrics | None = None,
|
||||
team: dict[str, float] | None = None,
|
||||
prev: PeriodMetrics | None = None,
|
||||
) -> dict:
|
||||
"""score_employee + min_days 接线(B2 评审遗留):当前窗天数 <
|
||||
config.sample_guards.min_days → score_status 覆盖 insufficient_sample,
|
||||
total/明细保留展示(按天稀疏的数据不参与考核但可查看)。"""
|
||||
score = score_employee(config, cur, baseline=baseline, team=team, prev=prev)
|
||||
min_days = config.get("sample_guards", {}).get("min_days", 5)
|
||||
if cur.days_with_data < min_days:
|
||||
score["score_status"] = "insufficient_sample"
|
||||
return score
|
||||
|
||||
|
||||
async def assemble_employees(
|
||||
session: AsyncSession,
|
||||
config: dict,
|
||||
start_day: int,
|
||||
end_day: int,
|
||||
channel: str | None,
|
||||
*,
|
||||
with_prev: bool = True,
|
||||
) -> dict[str, dict]:
|
||||
"""全员组装:staff → 当前/基线(/前)窗 period_metrics → 逐员工
|
||||
score_with_guards + detect_anomalies(纯函数循环)。
|
||||
|
||||
dashboard 传 with_prev=False(只需评分+异常,省一次前窗聚合);
|
||||
employees/detail 需要 prev/团队中位时传 True。返回
|
||||
{uid: {name, is_on_job, cur, prev, baseline, score, anomalies,
|
||||
anomaly_count, anomaly_weight}}——过滤/排序/分页由调用方做。
|
||||
"""
|
||||
staff_rows = (await session.execute(
|
||||
sa.select(Staff.user_id, Staff.name, Staff.is_on_job)
|
||||
)).all()
|
||||
staff = {uid: (name, onjob) for uid, name, onjob in staff_rows if uid}
|
||||
if not staff:
|
||||
return {}
|
||||
|
||||
n_days = len(day_range(start_day, end_day))
|
||||
cur = await period_metrics(session, start_day, end_day, channel)
|
||||
bs, be = baseline_window(start_day)
|
||||
base = await period_metrics(session, bs, be, channel)
|
||||
prev: dict[str, PeriodMetrics] | None = None
|
||||
team: dict[str, float | None] | None = None
|
||||
if with_prev:
|
||||
ps, pe = prev_window(start_day, end_day)
|
||||
prev = await period_metrics(session, ps, pe, channel)
|
||||
team = team_derived_medians(cur)
|
||||
|
||||
out: dict[str, dict] = {}
|
||||
for uid, (name, onjob) in staff.items():
|
||||
c = cur.get(uid)
|
||||
if c is None: # 防御:period_metrics 恒含全员,此处不该走到
|
||||
continue
|
||||
b = base.get(uid)
|
||||
p = prev.get(uid) if prev is not None else None
|
||||
score = score_with_guards(config, c, baseline=b, team=team, prev=p)
|
||||
anomalies = detect_anomalies(uid, c, b, n_days=n_days, config=config)
|
||||
out[uid] = {
|
||||
"name": name,
|
||||
"is_on_job": onjob,
|
||||
"cur": c,
|
||||
"prev": p,
|
||||
"baseline": b,
|
||||
"score": score,
|
||||
"anomalies": anomalies,
|
||||
"anomaly_count": len(anomalies),
|
||||
"anomaly_weight": sum(
|
||||
SEVERITY_WEIGHT.get(a["severity"], 0) for a in anomalies
|
||||
),
|
||||
}
|
||||
return out
|
||||
|
||||
|
||||
def build_employee_row(uid: str, data: dict) -> dict:
|
||||
"""employees 列表行:metrics 全字段 + comparisons 四值(自评分
|
||||
metrics_detail 透传)+ score 摘要 + 异常计数/权重。"""
|
||||
score = data["score"]
|
||||
return {
|
||||
"user_id": uid,
|
||||
"name": data["name"],
|
||||
"is_on_job": data["is_on_job"],
|
||||
"metrics": data["cur"]._asdict(),
|
||||
"comparisons": {
|
||||
code: {
|
||||
"current": d["value"],
|
||||
"prev": d["prev"],
|
||||
"baseline": d["baseline"],
|
||||
"median": d["median"],
|
||||
}
|
||||
for code, d in score["metrics_detail"].items()
|
||||
},
|
||||
"score": {
|
||||
"total_score": score["total_score"],
|
||||
"grade": score["grade"],
|
||||
"score_status": score["score_status"],
|
||||
"trial": score["trial"],
|
||||
"dimensions": {
|
||||
key: {"score": dim["score"], "status": dim["status"]}
|
||||
for key, dim in score["dimensions"].items()
|
||||
},
|
||||
},
|
||||
"anomaly_count": data["anomaly_count"],
|
||||
"anomaly_weight": data["anomaly_weight"],
|
||||
}
|
||||
|
||||
|
||||
def derived_comparisons(
|
||||
cur: PeriodMetrics,
|
||||
prev: PeriodMetrics | None,
|
||||
baseline: PeriodMetrics | None,
|
||||
team: dict[str, float | None] | None,
|
||||
) -> dict[str, dict]:
|
||||
"""四对比(current/prev/baseline/median),派生口径=scoring.derive_metrics
|
||||
——评分、异常、展示三方同一派生式。"""
|
||||
cv = derive_metrics(cur)
|
||||
pv = derive_metrics(prev) if prev is not None else {}
|
||||
bv = derive_metrics(baseline) if baseline is not None else {}
|
||||
return {
|
||||
key: {
|
||||
"current": cv.get(key),
|
||||
"prev": pv.get(key),
|
||||
"baseline": bv.get(key),
|
||||
"median": team.get(key) if team else None,
|
||||
}
|
||||
for key in cv
|
||||
}
|
||||
|
||||
|
||||
async def wide_daily_rows(
|
||||
session: AsyncSession,
|
||||
start_day: int,
|
||||
end_day: int,
|
||||
channel: str | None,
|
||||
user_id: str | None = None,
|
||||
) -> list[dict]:
|
||||
"""宽表逐日聚合(加性列跨渠道求和;user_id=None 为全员合计)。
|
||||
|
||||
first_reply_p50/p90_ms 是 (day,channel,user) 行内单值不可求和:
|
||||
单员工视图(channel=None 双渠道同日)取当日 cust_threads 较大渠道的
|
||||
值(当日主力渠道,并列取 wechat);全员视图不取用这两列(分位由
|
||||
service_daily_trend 从 fact 精确算)。
|
||||
"""
|
||||
conds = [
|
||||
EmployeeMetricDaily.day.between(start_day, end_day),
|
||||
EmployeeMetricDaily.metric_version == METRIC_VERSION,
|
||||
]
|
||||
if channel is not None:
|
||||
conds.append(EmployeeMetricDaily.channel == channel)
|
||||
if user_id is not None:
|
||||
conds.append(EmployeeMetricDaily.user_id == user_id)
|
||||
rows = (await session.execute(
|
||||
sa.select(
|
||||
EmployeeMetricDaily.day.label("day"),
|
||||
EmployeeMetricDaily.channel.label("ch"),
|
||||
sa.func.sum(EmployeeMetricDaily.msg_sent).label("sent"),
|
||||
sa.func.sum(EmployeeMetricDaily.msg_recv).label("recv"),
|
||||
sa.func.sum(EmployeeMetricDaily.active_friends).label("af"),
|
||||
sa.func.sum(EmployeeMetricDaily.active_rooms).label("ar"),
|
||||
sa.func.sum(EmployeeMetricDaily.cust_threads).label("thr"),
|
||||
sa.func.sum(EmployeeMetricDaily.threads_answered).label("ans"),
|
||||
sa.func.sum(EmployeeMetricDaily.fr_sum_ms).label("frs"),
|
||||
sa.func.sum(EmployeeMetricDaily.new_customer_count).label("nw"),
|
||||
sa.func.sum(EmployeeMetricDaily.cooling_customer_count).label("cool"),
|
||||
sa.func.sum(EmployeeMetricDaily.dormant_customer_count).label("dorm"),
|
||||
sa.func.sum(EmployeeMetricDaily.reactivated_customer_count).label("react"),
|
||||
sa.func.max(EmployeeMetricDaily.first_reply_p50_ms).label("p50"),
|
||||
sa.func.max(EmployeeMetricDaily.first_reply_p90_ms).label("p90"),
|
||||
).where(*conds).group_by(EmployeeMetricDaily.day, EmployeeMetricDaily.channel)
|
||||
)).all()
|
||||
|
||||
per_day: dict[int, dict] = {}
|
||||
|
||||
def _blank(day: int) -> dict:
|
||||
return {
|
||||
"day": day, "msg_sent": 0, "msg_recv": 0, "active_friends": 0,
|
||||
"active_rooms": 0, "cust_threads": 0, "threads_answered": 0,
|
||||
"fr_sum_ms": 0, "new_customer_count": 0,
|
||||
"cooling_customer_count": 0, "dormant_customer_count": 0,
|
||||
"reactivated_customer_count": 0,
|
||||
"first_reply_p50_ms": None, "first_reply_p90_ms": None,
|
||||
"_pick": (-1, -1), # 主力渠道追踪 (cust_threads, wechat 加分)
|
||||
}
|
||||
|
||||
for (day, ch, sent, recv, af, ar, thr, ans, frs, nw, cool, dorm,
|
||||
react, p50, p90) in rows:
|
||||
d = per_day.setdefault(day, _blank(day))
|
||||
d["msg_sent"] += int(sent or 0)
|
||||
d["msg_recv"] += int(recv or 0)
|
||||
d["active_friends"] += int(af or 0)
|
||||
d["active_rooms"] += int(ar or 0)
|
||||
d["cust_threads"] += int(thr or 0)
|
||||
d["threads_answered"] += int(ans or 0)
|
||||
d["fr_sum_ms"] += int(frs or 0)
|
||||
d["new_customer_count"] += int(nw or 0)
|
||||
d["cooling_customer_count"] += int(cool or 0)
|
||||
d["dormant_customer_count"] += int(dorm or 0)
|
||||
d["reactivated_customer_count"] += int(react or 0)
|
||||
if user_id is not None:
|
||||
pick = (int(thr or 0), 1 if ch == "wechat" else 0)
|
||||
if pick > d["_pick"]:
|
||||
d["_pick"] = pick
|
||||
d["first_reply_p50_ms"] = p50
|
||||
d["first_reply_p90_ms"] = p90
|
||||
|
||||
out = []
|
||||
for day in sorted(per_day):
|
||||
d = per_day[day]
|
||||
d.pop("_pick", None)
|
||||
out.append(d)
|
||||
return out
|
||||
|
||||
|
||||
async def call_daily_rows(
|
||||
session: AsyncSession,
|
||||
start_day: int,
|
||||
end_day: int,
|
||||
user_id: str | None = None,
|
||||
) -> list[dict]:
|
||||
"""通话小表逐日聚合(恒全渠道——表无渠道维);user_id=None 为全员。"""
|
||||
conds = [EmployeeCallDaily.day.between(start_day, end_day)]
|
||||
if user_id is not None:
|
||||
conds.append(EmployeeCallDaily.user_id == user_id)
|
||||
rows = (await session.execute(
|
||||
sa.select(
|
||||
EmployeeCallDaily.day,
|
||||
sa.func.sum(EmployeeCallDaily.call_count),
|
||||
sa.func.sum(EmployeeCallDaily.call_seconds),
|
||||
sa.func.sum(EmployeeCallDaily.answered_call_count),
|
||||
sa.func.sum(EmployeeCallDaily.call_followup_count),
|
||||
).where(*conds).group_by(EmployeeCallDaily.day)
|
||||
)).all()
|
||||
return [
|
||||
{
|
||||
"day": day, "call_count": int(cc or 0),
|
||||
"call_seconds": int(cs or 0),
|
||||
"answered_call_count": int(ca or 0),
|
||||
"call_followup_count": int(cf or 0),
|
||||
}
|
||||
for day, cc, cs, ca, cf in rows
|
||||
]
|
||||
|
||||
|
||||
async def service_daily_trend(
|
||||
session: AsyncSession,
|
||||
start_day: int,
|
||||
end_day: int,
|
||||
channel: str | None,
|
||||
threads_by_day: dict[int, int],
|
||||
) -> list[dict]:
|
||||
"""服务趋势(dashboard 全团队):fact 逐日 (day, fr_ms) 行拉回 Python
|
||||
最近邻秩分位(跨员工合并样本——团队级分位);reply_2h_rate = fact
|
||||
当日 ≤2h 计数 / 宽表当日 cust_threads 合计(分母 0 → None)。
|
||||
|
||||
输出全窗口逐日(无数据日 p50/p90 为 None),threads_by_day 来自
|
||||
wide_daily_rows 的全员 cust_threads 列。
|
||||
"""
|
||||
conds = [FirstReplyFact.day.between(start_day, end_day)]
|
||||
if channel is not None:
|
||||
conds.append(FirstReplyFact.channel == channel)
|
||||
rows = (await session.execute(
|
||||
sa.select(FirstReplyFact.day, FirstReplyFact.fr_ms).where(*conds)
|
||||
)).all()
|
||||
by_day: dict[int, list[int]] = {}
|
||||
for day, fr in rows:
|
||||
by_day.setdefault(day, []).append(int(fr))
|
||||
out = []
|
||||
for day in day_range(start_day, end_day):
|
||||
frs = by_day.get(day, [])
|
||||
cnt_2h = sum(1 for f in frs if f <= 7_200_000)
|
||||
denom = threads_by_day.get(day, 0)
|
||||
out.append({
|
||||
"day": day,
|
||||
"fr_p50_ms": percentile_nearest(frs, 1, 2),
|
||||
"fr_p90_ms": percentile_nearest(frs, 9, 10),
|
||||
"reply_2h_rate": (cnt_2h / denom) if denom else None,
|
||||
})
|
||||
return out
|
||||
|
||||
|
||||
async def user_owner_accounts(
|
||||
session: AsyncSession, user_id: str, channel: str | None
|
||||
) -> list[str]:
|
||||
"""员工在所选渠道下的 owner 账号(channel=None → 两渠道合并)。"""
|
||||
chs = ("wechat", "whatsapp") if channel is None else (channel,)
|
||||
out: list[str] = []
|
||||
for ch in chs:
|
||||
amap = await account_map(session, ch)
|
||||
out.extend(owner for owner, uid in amap.items() if uid == user_id)
|
||||
return out
|
||||
|
||||
|
||||
async def lifecycle_customers(
|
||||
session: AsyncSession,
|
||||
owner_accounts: list[str],
|
||||
as_of_day: int,
|
||||
want_state: str,
|
||||
) -> list[dict]:
|
||||
"""drilldown cooling/dormant:该员工账号归属客户(delete_flag 过滤)+
|
||||
msg_daily_stats friend 行全历史 → lifecycle.classify(as_of=窗口末日),
|
||||
返回状态匹配行 {friend_id, nickname, last_day, state},按 last_day asc
|
||||
(最陈旧在前)、friend_id asc 排序。
|
||||
|
||||
与批次A _lifecycle_daily 同式:hist 为 ≤as_of 的历史消息数
|
||||
(时点语义,as_of 之后的消息不虚增沉睡门槛)。"""
|
||||
custs = (await session.execute(
|
||||
sa.select(Customer).where(
|
||||
sa.or_(Customer.delete_flag.is_(None), Customer.delete_flag == 0),
|
||||
Customer.owner_account_id.in_(owner_accounts),
|
||||
)
|
||||
)).scalars().all()
|
||||
if not custs:
|
||||
return []
|
||||
ids = [c.friend_id for c in custs]
|
||||
rows = (await session.execute(
|
||||
sa.select(
|
||||
MsgDailyStats.channel,
|
||||
MsgDailyStats.owner_account_id,
|
||||
MsgDailyStats.peer_id,
|
||||
MsgDailyStats.day,
|
||||
MsgDailyStats.send_cnt,
|
||||
MsgDailyStats.recv_cnt,
|
||||
).where(
|
||||
MsgDailyStats.peer_kind == "friend",
|
||||
MsgDailyStats.peer_id.in_(ids),
|
||||
)
|
||||
)).all()
|
||||
hist: dict[tuple[str, str, str], dict[int, int]] = {}
|
||||
for ch, owner, peer, day, snd, rcv in rows:
|
||||
dm = hist.setdefault((ch, owner, peer), {})
|
||||
dm[day] = dm.get(day, 0) + int(snd or 0) + int(rcv or 0)
|
||||
|
||||
matches: list[dict] = []
|
||||
for c in custs:
|
||||
dm = hist.get((c.channel, c.owner_account_id or "", c.friend_id))
|
||||
if not dm:
|
||||
continue
|
||||
days_list = sorted(dm)
|
||||
idx = bisect_right(days_list, as_of_day) - 1
|
||||
if idx < 0:
|
||||
continue # 窗口末日之前从未互动
|
||||
last = days_list[idx]
|
||||
prev_d = days_list[idx - 1] if idx > 0 else None
|
||||
hist_msgs = sum(dm[d] for d in days_list[: idx + 1])
|
||||
state = classify(days_list[0], last, prev_d, as_of_day, hist_msgs)
|
||||
if state == want_state:
|
||||
matches.append({
|
||||
"friend_id": c.friend_id,
|
||||
"nickname": c.friend_nickname or c.friend_remark or c.friend_id,
|
||||
"last_day": last,
|
||||
"state": state,
|
||||
})
|
||||
matches.sort(key=lambda m: (m["last_day"], m["friend_id"]))
|
||||
return matches
|
||||
@@ -0,0 +1,633 @@
|
||||
"""管理 API 六只读端点判别测试(批次B Task B4)。
|
||||
|
||||
覆盖:
|
||||
- 参数校验:422(缺 start / 跨度>366 / 日历非法 / drilldown 白名单外 /
|
||||
page_size>100)、404(employees/{ghost}、drilldown 员工不存在);
|
||||
- dashboard 各段齐全与关键数值(kpis/communication_trend/service_trend/
|
||||
lifecycle/dimension_summary/anomalies/action_summary/data_as_of/
|
||||
metric_version);
|
||||
- employees:默认分页 20/total/critical 优先默认排序/channel=wechat 时
|
||||
whatsapp-only 员工消失/keyword/status/min_days 不足→insufficient_sample;
|
||||
- detail:账号清单+metrics 全字段+score 完整明细+anomalies+prev/baseline;
|
||||
- sections:五段各有 trend 数组与四对比;
|
||||
- drilldown:p90 分页与 fr_ms desc/unreplied 按 owner 过滤/cooling-dormant
|
||||
生命周期判定(已删客户剔除)/call_followup 列表+期聚合摘要;
|
||||
- metric-definitions:trial 标记/口径说明/config_source 回退。
|
||||
"""
|
||||
import datetime as dt
|
||||
from zoneinfo import ZoneInfo
|
||||
|
||||
from app.db.models import (
|
||||
Customer,
|
||||
EmployeeCallDaily,
|
||||
EmployeeMetricDaily,
|
||||
FirstReplyFact,
|
||||
Message,
|
||||
MsgDailyStats,
|
||||
PhoneCall,
|
||||
Staff,
|
||||
WechatAccount,
|
||||
WhatsappAccount,
|
||||
)
|
||||
|
||||
_SH = ZoneInfo("Asia/Shanghai")
|
||||
|
||||
START, END = 20260901, 20260905 # 当前窗 5 天(min_days=5 恰好够)
|
||||
|
||||
|
||||
def _ts(*args) -> int:
|
||||
return int(dt.datetime(*args, tzinfo=_SH).timestamp() * 1000)
|
||||
|
||||
|
||||
def _mday(day, *, channel="wechat", user_id="u1", metric_version="v1", **kw):
|
||||
cols = {
|
||||
"msg_sent": 0, "msg_recv": 0, "active_friends": 0, "active_rooms": 0,
|
||||
"cust_threads": 0, "threads_answered": 0, "fr_sum_ms": 0,
|
||||
"new_customer_count": 0, "cooling_customer_count": 0,
|
||||
"dormant_customer_count": 0, "reactivated_customer_count": 0,
|
||||
"data_complete": True,
|
||||
}
|
||||
cols.update(kw)
|
||||
return EmployeeMetricDaily(
|
||||
day=day, channel=channel, user_id=user_id,
|
||||
metric_version=metric_version, **cols
|
||||
)
|
||||
|
||||
|
||||
def _fact(fr_ms, *, channel="wechat", owner="wx1", peer="p1", day=20260901, i=0):
|
||||
end = _ts(day // 10000, day // 100 % 100, day % 100, 10, 0) + i * 60_000
|
||||
return FirstReplyFact(
|
||||
channel=channel, owner_account_id=owner, peer_id=peer,
|
||||
thread_end_ts=end, reply_ts=end + fr_ms,
|
||||
reply_msg_id=f"{owner}-{peer}-m{i}", day=day, fr_ms=fr_ms,
|
||||
)
|
||||
|
||||
|
||||
async def _seed_common(s):
|
||||
"""三员工全量种子:u1(微信,2 warning)/u2(双渠道,1 critical+1 warning)/
|
||||
u3(仅 WhatsApp,无异常)——支撑 dashboard/employees/detail/sections/
|
||||
drilldown 全部判据。"""
|
||||
for uid, name, onjob in (("u1", "张三", True), ("u2", "李四", True),
|
||||
("u3", "王五", False)):
|
||||
s.add(Staff(user_id=uid, name=name, is_on_job=onjob))
|
||||
s.add(WechatAccount(wx_id="wx1", user_id="u1", nick_name="张三的微信",
|
||||
user_name="张三"))
|
||||
s.add(WechatAccount(wx_id="wx2", user_id="u2"))
|
||||
s.add(WhatsappAccount(uid="wa2", user_id="u2"))
|
||||
s.add(WhatsappAccount(uid="wa3", user_id="u3"))
|
||||
|
||||
# ---- 当前窗宽表(0901-0905)----
|
||||
for d in range(1, 6):
|
||||
s.add(_mday(20260900 + d, user_id="u1", msg_sent=1, cust_threads=2,
|
||||
threads_answered=2, fr_sum_ms=240_000, active_friends=3,
|
||||
active_rooms=1, cooling_customer_count=2,
|
||||
dormant_customer_count=1,
|
||||
first_reply_p50_ms=110_000, first_reply_p90_ms=220_000))
|
||||
s.add(_mday(20260900 + d, user_id="u2", msg_sent=10, msg_recv=10,
|
||||
cust_threads=2, threads_answered=2, fr_sum_ms=1_200_000,
|
||||
active_friends=4, cooling_customer_count=1,
|
||||
reactivated_customer_count=1))
|
||||
s.add(_mday(20260900 + d, channel="whatsapp", user_id="u3",
|
||||
msg_sent=5, msg_recv=5, cust_threads=1, active_friends=1))
|
||||
# ---- 基线窗宽表(0827-0831,u1 高日均触发 activity_drop)----
|
||||
for d in range(27, 32):
|
||||
s.add(_mday(20260800 + d, user_id="u1", msg_sent=14, msg_recv=14))
|
||||
s.add(_mday(20260800 + d, user_id="u2", msg_sent=5, msg_recv=5))
|
||||
|
||||
# ---- fact:当前窗(u1 120s warning / u2 600s critical)+ 基线 60s ----
|
||||
s.add(_fact(120_000, peer="pA", day=20260901, i=0))
|
||||
s.add(_fact(120_000, peer="pB", day=20260902, i=1))
|
||||
s.add(_fact(600_000, owner="wx2", peer="pC", day=20260901, i=2))
|
||||
s.add(_fact(600_000, owner="wx2", peer="pD", day=20260902, i=3))
|
||||
for owner, peer, day, i in (("wx1", "pA", 20260827, 10),
|
||||
("wx1", "pB", 20260828, 11),
|
||||
("wx2", "pC", 20260827, 12),
|
||||
("wx2", "pD", 20260828, 13)):
|
||||
s.add(_fact(60_000, owner=owner, peer=peer, day=day, i=i))
|
||||
|
||||
# ---- msg_daily_stats:活跃客户 distinct + data_as_of + 未回候选 ----
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
|
||||
peer_kind="friend", peer_id="p1", day=20260901,
|
||||
send_cnt=0, recv_cnt=1, last_ts=_ts(2026, 9, 1, 10, 0),
|
||||
last_is_send=False))
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
|
||||
peer_kind="friend", peer_id="p2", day=20260902,
|
||||
send_cnt=1, recv_cnt=0, last_ts=_ts(2026, 9, 2, 10, 0),
|
||||
last_is_send=True))
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx2",
|
||||
peer_kind="friend", peer_id="p3", day=20260901,
|
||||
send_cnt=2, recv_cnt=0, last_ts=_ts(2026, 9, 1, 11, 0),
|
||||
last_is_send=True))
|
||||
s.add(MsgDailyStats(channel="whatsapp", owner_account_id="wa3",
|
||||
peer_kind="friend", peer_id="p4", day=20260903,
|
||||
send_cnt=1, recv_cnt=0, last_ts=_ts(2026, 9, 3, 9, 0),
|
||||
last_is_send=True))
|
||||
# drilldown cooling/dormant 客户互动史(全历史,窗外):
|
||||
# f1 末次 0801(gap 35, hist 12)→ dormant;f2 末次 0825(gap 11)→ cooling
|
||||
for day, n in ((20260701, 6), (20260801, 6)):
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
|
||||
peer_kind="friend", peer_id="f1", day=day,
|
||||
send_cnt=n, recv_cnt=0,
|
||||
last_ts=_ts(day // 10000, day // 100 % 100,
|
||||
day % 100, 10, 0),
|
||||
last_is_send=True))
|
||||
for day in (20260801, 20260825):
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
|
||||
peer_kind="friend", peer_id="f2", day=day,
|
||||
send_cnt=2, recv_cnt=2,
|
||||
last_ts=_ts(2026, 8, day % 100, 11, 0),
|
||||
last_is_send=True))
|
||||
|
||||
# ---- 客户档案(f9 已删,须被 drilldown 剔除)----
|
||||
s.add(Customer(friend_id="f1", channel="wechat", owner_account_id="wx1",
|
||||
friend_nickname="客户一", user_id="u1", delete_flag=0))
|
||||
s.add(Customer(friend_id="f2", channel="wechat", owner_account_id="wx1",
|
||||
friend_nickname="客户二", user_id="u1", delete_flag=0))
|
||||
s.add(Customer(friend_id="f9", channel="wechat", owner_account_id="wx1",
|
||||
friend_nickname="已删客户", user_id="u1", delete_flag=1))
|
||||
|
||||
# ---- 未回候选 p1 的尾部消息(unreplied 决赛圈点查)----
|
||||
s.add(Message(msg_id="m-p1", channel="wechat", owner_account_id="wx1",
|
||||
talker_id="p1", is_send=False, type="text", text="在吗",
|
||||
timestamp=_ts(2026, 9, 1, 10, 0)))
|
||||
|
||||
# ---- 通话 ----
|
||||
s.add(EmployeeCallDaily(day=20260901, user_id="u1", call_count=2,
|
||||
call_seconds=100, answered_call_count=1,
|
||||
call_followup_count=1))
|
||||
s.add(EmployeeCallDaily(day=20260902, user_id="u2", call_count=1,
|
||||
call_seconds=60, answered_call_count=1,
|
||||
call_followup_count=0))
|
||||
s.add(PhoneCall(call_id="c1", channel="voice_call", user_id="u1",
|
||||
start_call_time=_ts(2026, 9, 1, 15, 0), call_duration=120,
|
||||
call_number="13800000001"))
|
||||
s.add(PhoneCall(call_id="c2", channel="voice_call", user_id="u1",
|
||||
start_call_time=_ts(2026, 9, 2, 15, 0), call_duration=0,
|
||||
call_number="13800000002"))
|
||||
await s.commit()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- 参数与错误
|
||||
|
||||
|
||||
async def test_dashboard_missing_start_422(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/dashboard", params={"end": END})
|
||||
assert r.status_code == 422
|
||||
|
||||
|
||||
async def test_dashboard_span_and_calendar_422(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/dashboard",
|
||||
params={"start": 20250101, "end": 20261231})
|
||||
assert r.status_code == 422
|
||||
r = await client.get("/api/management/dashboard",
|
||||
params={"start": 20260230, "end": 20260905})
|
||||
assert r.status_code == 422 # 日历非法(2 月 30 日)
|
||||
|
||||
|
||||
async def test_drilldown_unknown_metric_422(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/u1/drilldown",
|
||||
params={"metric_code": "bogus",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 422
|
||||
assert "unknown metric_code" in r.json()["detail"]
|
||||
|
||||
|
||||
async def test_employees_page_size_over_100_422(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END,
|
||||
"page_size": 101})
|
||||
assert r.status_code == 422
|
||||
|
||||
|
||||
async def test_employee_detail_404(make_client):
|
||||
async def seed(s):
|
||||
await s.commit()
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/ghost",
|
||||
params={"start": START, "end": END})
|
||||
assert r.status_code == 404
|
||||
|
||||
|
||||
async def test_drilldown_employee_404(make_client):
|
||||
async def seed(s):
|
||||
await s.commit()
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/ghost/drilldown",
|
||||
params={"metric_code": "unreplied",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 404
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- dashboard
|
||||
|
||||
|
||||
async def test_dashboard_structure_and_kpis(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/dashboard",
|
||||
params={"channel": "all", "start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
for key in ("scope", "data_as_of", "metric_version", "kpis",
|
||||
"communication_trend", "service_trend", "lifecycle",
|
||||
"dimension_summary", "anomalies", "action_summary",
|
||||
"config_source", "caliber_notes"):
|
||||
assert key in body, key
|
||||
assert body["metric_version"] == "v1"
|
||||
assert body["config_source"] == "default"
|
||||
assert body["scope"] == {"channel": "all", "start": START, "end": END,
|
||||
"compare": "previous"}
|
||||
assert body["data_as_of"] == _ts(2026, 9, 3, 9, 0)
|
||||
|
||||
k = body["kpis"]
|
||||
# 活跃客户=PM distinct 求和(u1:2 + u2:1 + u3:1)
|
||||
assert k["active_customers"] == 4
|
||||
assert k["active_employees"] == 3
|
||||
assert k["msg_total"] == 155 # u1 5 + u2 100 + u3 50
|
||||
assert k["cust_threads"] == 25 # 10 + 10 + 5
|
||||
assert k["threads_answered"] == 20 # 10 + 10 + 0
|
||||
assert k["call_count"] == 3
|
||||
assert k["call_seconds"] == 160
|
||||
assert k["answered_call"] == 2
|
||||
# 期末存量:u1 cooling2/dormant1 + u2 cooling1;reactivated 期内求和 u2 5
|
||||
assert body["lifecycle"] == {"new": 0, "cooling": 3, "dormant": 1,
|
||||
"reactivated": 5}
|
||||
assert k["lifecycle"] == body["lifecycle"]
|
||||
|
||||
# 趋势逐日 5 点;0901 = u1(1)+u2(20)+u3(10) 消息,宽表 active 合计 8,通话 2
|
||||
trend = body["communication_trend"]
|
||||
assert [t["day"] for t in trend] == [20260901 + i for i in range(5)]
|
||||
assert trend[0]["msg_total"] == 31
|
||||
assert trend[0]["active_customers"] == 8
|
||||
assert trend[0]["call_cnt"] == 2
|
||||
assert trend[1]["call_cnt"] == 1
|
||||
assert trend[4] == {"day": 20260905, "msg_total": 31,
|
||||
"active_customers": 8, "call_cnt": 0}
|
||||
|
||||
# 服务趋势:0901 fact [120k, 600k] → p50=120k/p90=600k;
|
||||
# reply_2h_rate = 2/5(两串均 ≤2h——600s=10min / 宽表当日串 5)
|
||||
st = {t["day"]: t for t in body["service_trend"]}
|
||||
assert st[20260901]["fr_p50_ms"] == 120_000
|
||||
assert st[20260901]["fr_p90_ms"] == 600_000
|
||||
assert st[20260901]["reply_2h_rate"] == 0.4
|
||||
assert st[20260903]["fr_p50_ms"] is None # 无 fact 日
|
||||
assert st[20260903]["reply_2h_rate"] == 0.0 # 分母有串、分子 0
|
||||
|
||||
# 维度摘要:5 维全员计数,总数=员工数 3
|
||||
dims = body["dimension_summary"]
|
||||
assert set(dims) == {"customer", "service", "action", "workload", "risk"}
|
||||
for d in dims.values():
|
||||
assert d["scored_count"] + d["insufficient_count"] + d["pending_count"] == 3
|
||||
assert "avg_score" in d
|
||||
|
||||
# 异常:critical 在前(u2),warning 其后按 affected_count desc
|
||||
anoms = body["anomalies"]
|
||||
assert anoms[0]["severity"] == "critical"
|
||||
assert anoms[0]["employee_user_id"] == "u2"
|
||||
assert all(a["severity"] == "critical" for a in anoms[:1])
|
||||
assert all(a["severity"] == "warning" for a in anoms[1:])
|
||||
|
||||
assert body["action_summary"] == {"unreplied_2h": 1, "churn_real_30d": 0,
|
||||
"sensitive_pending": 0}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- employees
|
||||
|
||||
|
||||
async def test_employees_default_sort_and_paging(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"channel": "all", "start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["total"] == 3
|
||||
assert body["page"] == 1
|
||||
assert body["page_size"] == 20
|
||||
assert body["metric_version"] == "v1"
|
||||
assert body["config_source"] == "default"
|
||||
assert len(body["rows"]) == 3
|
||||
|
||||
# 默认 anomaly_severity 排序:含 critical 的 u2 在最前
|
||||
# (u2=1 critical——基线无串样本率不可算,rate 规则不触发;u1=2 warning)
|
||||
ids = [row["user_id"] for row in body["rows"]]
|
||||
assert ids == ["u2", "u1", "u3"]
|
||||
u2, u1, u3 = body["rows"]
|
||||
assert u2["anomaly_count"] == 1 and u2["anomaly_weight"] == 2
|
||||
assert u1["anomaly_count"] == 2 and u1["anomaly_weight"] == 2
|
||||
assert u3["anomaly_count"] == 0 and u3["anomaly_weight"] == 0
|
||||
|
||||
# 行结构:metrics 全字段 / comparisons 四值 / score 摘要
|
||||
assert u1["name"] == "张三" and u1["is_on_job"] is True
|
||||
assert u1["metrics"]["cust_threads"] == 10
|
||||
assert u1["metrics"]["end_active_friends"] == 3
|
||||
assert set(u1["comparisons"]) >= {
|
||||
"active_share", "reply_2h_rate", "reply_24h_rate", "fr_p90_ms",
|
||||
"active_friends_band", "call_band"}
|
||||
for c in u1["comparisons"].values():
|
||||
assert set(c) == {"current", "prev", "baseline", "median"}
|
||||
assert u1["comparisons"]["fr_p90_ms"]["current"] == 120_000
|
||||
assert u1["comparisons"]["fr_p90_ms"]["baseline"] == 60_000
|
||||
assert set(u1["score"]["dimensions"]) == {
|
||||
"customer", "service", "action", "workload", "risk"}
|
||||
for d in u1["score"]["dimensions"].values():
|
||||
assert set(d) == {"score", "status"}
|
||||
assert u1["score"]["trial"] is True
|
||||
assert u1["score"]["score_status"] == "scored" # 5 天数据 ≥ min_days
|
||||
|
||||
|
||||
async def test_employees_channel_filter(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"channel": "wechat", "start": START,
|
||||
"end": END})
|
||||
ids = [row["user_id"] for row in r.json()["rows"]]
|
||||
assert ids == ["u2", "u1"] # u3 仅 WhatsApp,wechat 视图消失
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"channel": "whatsapp", "start": START,
|
||||
"end": END})
|
||||
ids = [row["user_id"] for row in r.json()["rows"]]
|
||||
assert ids == ["u2", "u3"] # u1 无 WA 账号
|
||||
|
||||
|
||||
async def test_employees_keyword(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END, "keyword": "张"})
|
||||
assert [row["user_id"] for row in r.json()["rows"]] == ["u1"]
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END, "keyword": "U3"})
|
||||
assert [row["user_id"] for row in r.json()["rows"]] == ["u3"]
|
||||
|
||||
|
||||
async def test_employees_status_filter(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END,
|
||||
"status": "on_job"})
|
||||
assert [row["user_id"] for row in r.json()["rows"]] == ["u2", "u1"]
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END,
|
||||
"status": "offline"})
|
||||
assert [row["user_id"] for row in r.json()["rows"]] == ["u3"]
|
||||
|
||||
|
||||
async def test_employees_min_days_insufficient(make_client):
|
||||
"""B2 评审遗留接线:days_with_data < min_days → score_status 覆盖
|
||||
insufficient_sample,但可评明细(total_score)保留展示。"""
|
||||
|
||||
async def seed(s):
|
||||
s.add(Staff(user_id="u9", name="赵九", is_on_job=True))
|
||||
s.add(WechatAccount(wx_id="wx9", user_id="u9"))
|
||||
# 仅 2 天宽表数据(< min_days=5),但串样本 30 ≥ min_threads 可评分
|
||||
for d in (1, 2):
|
||||
s.add(_mday(20260900 + d, user_id="u9", cust_threads=15,
|
||||
threads_answered=15, fr_sum_ms=900_000,
|
||||
active_friends=10))
|
||||
s.add(_fact(60_000, owner="wx9", peer="q1", day=20260901, i=0))
|
||||
s.add(_fact(60_000, owner="wx9", peer="q2", day=20260902, i=1))
|
||||
for i in range(6): # 6 个 distinct peer → workload band 可评
|
||||
s.add(MsgDailyStats(channel="wechat", owner_account_id="wx9",
|
||||
peer_kind="friend", peer_id=f"q{i}",
|
||||
day=20260901, send_cnt=1, recv_cnt=0,
|
||||
last_ts=_ts(2026, 9, 1, 12, 0),
|
||||
last_is_send=True))
|
||||
await s.commit()
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees",
|
||||
params={"start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
row = r.json()["rows"][0]
|
||||
assert row["user_id"] == "u9"
|
||||
assert row["metrics"]["days_with_data"] == 2
|
||||
assert row["score"]["score_status"] == "insufficient_sample"
|
||||
assert row["score"]["total_score"] is not None # 明细保留展示
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- detail
|
||||
|
||||
|
||||
async def test_employee_detail_full(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/u1",
|
||||
params={"channel": "all", "start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["user_id"] == "u1"
|
||||
assert body["name"] == "张三"
|
||||
assert body["accounts"] == [
|
||||
{"channel": "wechat", "account_id": "wx1",
|
||||
"nick_name": "张三的微信", "user_name": "张三"}]
|
||||
# metrics 全字段(22 列 namedtuple)
|
||||
assert len(body["metrics"]) == 22
|
||||
assert body["metrics"]["cust_threads"] == 10
|
||||
# score 完整明细:dimensions 含逐指标 metrics;metrics_detail 扁平
|
||||
assert body["score"]["dimensions"]["service"]["metrics"]["fr_p90_ms"][
|
||||
"score"] == 100.0
|
||||
assert body["score"]["metrics_detail"]["fr_p90_ms"]["value"] == 120_000
|
||||
assert body["score"]["metrics_detail"]["reply_2h_rate"]["value"] == 0.2
|
||||
assert body["score"]["metrics_detail"]["fr_p90_ms"]["baseline"] == 60_000
|
||||
# anomalies + prev/baseline 原始值(prev 窗 0827-0831 与基线窗重叠:
|
||||
# 5 天 × msg_sent 14 = 70)
|
||||
assert len(body["anomalies"]) == 2
|
||||
assert all(a["severity"] == "warning" for a in body["anomalies"])
|
||||
assert body["prev"]["msg_sent"] == 70
|
||||
assert body["baseline"]["msg_sent"] == 70
|
||||
assert body["data_as_of"] == _ts(2026, 9, 3, 9, 0)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- sections
|
||||
|
||||
|
||||
async def test_employee_sections(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
base = "/api/management/employees/u1/metrics"
|
||||
for section in ("overview", "service", "customer", "workload", "calls"):
|
||||
r = await client.get(base, params={
|
||||
"section": section, "channel": "wechat",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 200, section
|
||||
body = r.json()
|
||||
assert body["section"] == section
|
||||
assert len(body["trend"]) == 5 # 全窗口逐日(含零填充)
|
||||
assert all("day" in t for t in body["trend"])
|
||||
assert body["comparisons"]["reply_2h_rate"]["current"] == 0.2
|
||||
assert set(body["comparisons"]["reply_2h_rate"]) == {
|
||||
"current", "prev", "baseline", "median"}
|
||||
|
||||
r = await client.get(base, params={"section": "service",
|
||||
"channel": "wechat",
|
||||
"start": START, "end": END})
|
||||
body = r.json()
|
||||
assert body["metrics"]["cust_threads"] == 10
|
||||
assert body["metrics"]["reply_2h_count"] == 2
|
||||
t0 = body["trend"][0]
|
||||
assert t0 == {"day": 20260901, "cust_threads": 2, "threads_answered": 2,
|
||||
"fr_sum_ms": 240_000, "first_reply_p50_ms": 110_000,
|
||||
"first_reply_p90_ms": 220_000}
|
||||
|
||||
r = await client.get(base, params={"section": "calls", "channel": "all",
|
||||
"start": START, "end": END})
|
||||
calls = {t["day"]: t for t in r.json()["trend"]}
|
||||
assert calls[20260901]["call_count"] == 2
|
||||
assert calls[20260901]["call_followup_count"] == 1
|
||||
assert calls[20260905]["call_count"] == 0 # 零填充
|
||||
assert r.json()["metrics"]["call_count"] == 2
|
||||
|
||||
|
||||
# ---------------------------------------------------------------- drilldown
|
||||
|
||||
|
||||
async def test_drilldown_fr_p90(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
url = "/api/management/employees/u2/drilldown"
|
||||
r = await client.get(url, params={
|
||||
"metric_code": "first_reply_p90", "channel": "all",
|
||||
"start": START, "end": END, "page": 1, "page_size": 1})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["total"] == 2
|
||||
assert len(body["items"]) == 1
|
||||
item = body["items"][0]
|
||||
# fr_ms desc + 同值按日 desc 决胜:0902 的 pD 在前
|
||||
assert item["fr_ms"] == 600_000
|
||||
assert item["peer_id"] == "pD"
|
||||
assert item["owner_account_id"] == "wx2"
|
||||
assert item["chat_hint"] == {"owner_account_id": "wx2", "talker_id": "pD"}
|
||||
r = await client.get(url, params={
|
||||
"metric_code": "first_reply_p90", "channel": "all",
|
||||
"start": START, "end": END, "page": 2, "page_size": 1})
|
||||
assert r.json()["items"][0]["peer_id"] == "pC"
|
||||
# u2 的 WA 账号无 fact 行
|
||||
r = await client.get(url, params={
|
||||
"metric_code": "first_reply_p50", "channel": "whatsapp",
|
||||
"start": START, "end": END})
|
||||
assert r.json()["total"] == 0
|
||||
|
||||
|
||||
async def test_drilldown_unreplied(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/u1/drilldown",
|
||||
params={"metric_code": "unreplied",
|
||||
"channel": "wechat",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["total"] == 1 # p1(wx1)进入,u1 过滤后
|
||||
assert body["items"][0]["peer_id"] == "p1"
|
||||
assert body["items"][0]["owner_account_id"] == "wx1"
|
||||
# u2 名下无未回候选(p3 尾部为员工消息)
|
||||
r = await client.get("/api/management/employees/u2/drilldown",
|
||||
params={"metric_code": "unreplied",
|
||||
"channel": "wechat",
|
||||
"start": START, "end": END})
|
||||
assert r.json()["total"] == 0
|
||||
|
||||
|
||||
async def test_drilldown_lifecycle_customers(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/u1/drilldown",
|
||||
params={"metric_code": "cooling_customers",
|
||||
"channel": "all",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["total"] == 1 # f2 降温;f1 沉睡、f9 已删
|
||||
assert body["items"][0] == {"friend_id": "f2", "nickname": "客户二",
|
||||
"last_day": 20260825, "state": "cooling"}
|
||||
|
||||
r = await client.get("/api/management/employees/u1/drilldown",
|
||||
params={"metric_code": "dormant_customers",
|
||||
"channel": "all",
|
||||
"start": START, "end": END})
|
||||
body = r.json()
|
||||
assert body["total"] == 1
|
||||
assert body["items"][0]["friend_id"] == "f1"
|
||||
assert body["items"][0]["state"] == "dormant"
|
||||
|
||||
|
||||
async def test_drilldown_call_followup(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/employees/u1/drilldown",
|
||||
params={"metric_code": "call_followup",
|
||||
"channel": "all",
|
||||
"start": START, "end": END})
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["total"] == 2
|
||||
# start_call_time desc:c2(0902)在前
|
||||
assert [i["call_id"] for i in body["items"]] == ["c2", "c1"]
|
||||
assert set(body["items"][0]) == {
|
||||
"call_id", "channel", "call_number", "start_call_time",
|
||||
"call_duration"}
|
||||
assert body["summary"] == {"call_count": 2, "call_seconds": 100,
|
||||
"answered_call_count": 1,
|
||||
"call_followup_count": 1}
|
||||
|
||||
|
||||
# ------------------------------------------------------- metric-definitions
|
||||
|
||||
|
||||
async def test_metric_definitions(make_client):
|
||||
async def seed(s):
|
||||
await _seed_common(s)
|
||||
|
||||
client = await make_client(seed)
|
||||
r = await client.get("/api/management/metric-definitions")
|
||||
assert r.status_code == 200
|
||||
body = r.json()
|
||||
assert body["definitions"]["cust_threads"]["unit"] == "串"
|
||||
assert body["score_config"]["trial"] is True
|
||||
assert body["score_config"]["dimensions"]["risk"]["status"] == "pending_data"
|
||||
assert body["config_source"] == "default" # 未种子配置→回退默认
|
||||
assert "1:1" in body["caliber_notes"]
|
||||
Reference in New Issue
Block a user