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用户报 Lily 聊天窗口「聊天好友」列表里 A**郑 显示成 wxid_ir6uxy2li8no22 ——A**郑是 14 个员工共享的客户,档案行(customer 全局单行 last-wins)挂在 别的员工名下,按 owner 查档案查空,三个显示位回退 wxid: - sessions._meta(会话列表名字/头像/delete_flag) - staff_chat_stats._customer_names(五数字弹窗明细) - chat-html-zip 文件名 统一改为优先 customer_account_link per-owner 快照(link 未覆盖回退档案, 空表过渡安全)。staff_stats(统计分析新客户等)仍是档案口径,属分析语义 另行评估。613 测试绿(新增会话共享好友昵称 2 例)。 Co-Authored-By: Claude Code <noreply@anthropic.com>
240 lines
9.5 KiB
Python
240 lines
9.5 KiB
Python
"""GET /api/staff-chat-stats — 微信员工 5 数字 + 客户明细。
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**双路径(2026-09-03 全时段窗 6.9s 超时修复)**:``msg_daily_stats`` 有行时
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读日粒度汇总(窗口对齐到自然日,毫秒级);空表回退旧实时聚合,行为不变。
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窗口语义随之统一为「上海自然日」(旧 SQL 日期函数跟随 DB 会话时区,UTC
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容器下与今日数口径割裂——顺带修复)。
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数据全本地：按 员工微信 wxid × ms-epoch 日期窗 聚合 1:1 私聊（room_id 过滤），
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不访问云客。5 汇总数从 customers 在 Python 侧派生（spec §5）。
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"""
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from __future__ import annotations
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import time
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from collections import namedtuple
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from typing import Annotated
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import sqlalchemy as sa
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.deps import get_session
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from app.api.schemas import StaffChatCustomerOut, StaffChatStatsOut, StaffChatStatsSummary
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from app.db.models import Customer, CustomerAccountLink, Message, MsgDailyStats
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from app.storage.summary import day_key, has_rows as _summary_has_rows
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router = APIRouter(prefix="/api", tags=["staff-chat-stats"])
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SessionDep = Annotated[AsyncSession, Depends(get_session)]
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_MS_PER_DAY = 86_400_000
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def _private_window(msg, owner: str, start: int, end: int):
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"""1:1 私聊 + 窗口过滤条件（channel 固定 wechat），排除 timestamp IS NULL。"""
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return [
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msg.channel == "wechat",
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msg.owner_account_id == owner,
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sa.or_(msg.room_id.is_(None), msg.room_id == ""),
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msg.timestamp.is_not(None),
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msg.timestamp >= start,
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msg.timestamp <= end,
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]
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async def _aggregate(session: AsyncSession, owner: str, start: int, end: int) -> tuple[list, dict[str, bool | None]]:
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"""返回 [(talker_id, send, recv, interaction_days, last_time)] + last_is_send map。"""
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# 跨库日期提取：从 ms-epoch 取日期。镜像 repos.py 方言检测。
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dialect = session.bind.name # 镜像 app/storage/repos.py（.name 等价 .dialect.name）
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if dialect == "sqlite":
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day_expr = sa.func.date(Message.timestamp / 1000, "unixepoch")
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else: # mysql（生产）
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day_expr = sa.func.date(sa.func.from_unixtime(Message.timestamp / 1000))
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base = _private_window(Message, owner, start, end)
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agg_stmt = (
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sa.select(
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Message.talker_id,
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sa.func.sum(sa.case((Message.is_send.is_(True), 1), else_=0)).label("send_count"),
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sa.func.sum(sa.case((Message.is_send.is_(False), 1), else_=0)).label("receive_count"),
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sa.func.count(sa.func.distinct(day_expr)).label("interaction_days"),
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sa.func.max(Message.timestamp).label("last_time"),
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)
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.where(*base)
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.group_by(Message.talker_id)
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.order_by(Message.talker_id)
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)
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agg_rows = (await session.execute(agg_stmt)).all()
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# 每客户最后一条消息方向：ROW_NUMBER 窗口取 rn=1（tie-break msg_id 保证确定性）
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inner = (
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sa.select(
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Message.talker_id,
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Message.is_send,
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sa.func.row_number()
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.over(
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partition_by=Message.talker_id,
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order_by=(Message.timestamp.desc(), Message.msg_id.desc()),
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)
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.label("rn"),
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)
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.where(*base)
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)
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sub = inner.subquery("last_msg")
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last_stmt = sa.select(sub.c.talker_id, sub.c.is_send).where(sub.c.rn == 1)
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last_map = {tid: is_send for tid, is_send in (await session.execute(last_stmt)).all()}
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return agg_rows, last_map
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# ── 汇总路径:msg_daily_stats 日行(namedtuple 与旧 Row 同形)────────────── #
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_AggRow = namedtuple(
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"_AggRow", ["talker_id", "send_count", "receive_count", "interaction_days", "last_time"]
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)
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async def _aggregate_summary(
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session: AsyncSession, owner: str, start: int, end: int
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) -> tuple[list, dict[str, bool | None]]:
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"""窗口 → [day_key(start), day_key(end)] 自然日区间,按日行 Python 聚合。
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interaction_days = 窗内有消息的自然日数;last_time/last_is_send 取窗内
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最后一条(last_ts 最大的日行)。窗口对齐自然日是文档化的语义变化
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(前端日期选择器本就按天取值)。
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"""
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rows = (
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await session.execute(
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sa.select(
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MsgDailyStats.peer_id,
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MsgDailyStats.day,
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MsgDailyStats.send_cnt,
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MsgDailyStats.recv_cnt,
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MsgDailyStats.last_ts,
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MsgDailyStats.last_is_send,
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).where(
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MsgDailyStats.channel == "wechat",
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MsgDailyStats.owner_account_id == owner,
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MsgDailyStats.peer_kind == "friend",
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MsgDailyStats.day >= day_key(start),
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MsgDailyStats.day <= day_key(end),
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)
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)
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).all()
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per: dict[str, dict] = {}
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for peer, _day, send, recv, last_ts, last_is in rows:
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acc = per.setdefault(
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peer, {"send": 0, "recv": 0, "days": 0, "last_ts": None, "last_is": None}
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)
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acc["send"] += int(send or 0)
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acc["recv"] += int(recv or 0)
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acc["days"] += 1
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if acc["last_ts"] is None or (last_ts is not None and last_ts >= acc["last_ts"]):
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acc["last_ts"] = last_ts
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acc["last_is"] = last_is
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agg_rows = [
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_AggRow(talker_id=p, send_count=a["send"], receive_count=a["recv"],
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interaction_days=a["days"], last_time=a["last_ts"])
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for p, a in per.items()
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]
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last_map = {p: a["last_is"] for p, a in per.items()}
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return agg_rows, last_map
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async def _customer_names(session: AsyncSession, owner: str, talker_ids: list[str]) -> dict[str, tuple[str, str, str]]:
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"""客户名/头像解析:优先 customer_account_link per-owner 快照,档案兜底。
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共享客户的档案行(customer 全局单行,last-wins)可能挂在别的员工名下,
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按 owner 查档案会查空、明细列表回退显示 wxid(2026-09-09,同 sessions
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._meta 修复)。
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"""
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if not talker_ids:
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return {}
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info: dict[str, tuple[str, str, str]] = {}
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link_stmt = sa.select(
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CustomerAccountLink.friend_id,
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CustomerAccountLink.friend_remark,
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CustomerAccountLink.friend_nickname,
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CustomerAccountLink.real_name,
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CustomerAccountLink.head_image_url,
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).where(
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CustomerAccountLink.channel == "wechat",
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CustomerAccountLink.owner_account_id == owner,
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CustomerAccountLink.friend_id.in_(talker_ids),
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)
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for fid, remark, nick, real, head in (await session.execute(link_stmt)).all():
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info[fid] = (remark or nick or real or fid, real or "", head or "")
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missing = [t for t in talker_ids if t not in info]
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if missing:
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stmt = sa.select(
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Customer.friend_id,
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Customer.friend_remark,
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Customer.friend_nickname,
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Customer.real_name,
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Customer.head_image_url,
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).where(
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Customer.channel == "wechat",
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Customer.owner_account_id == owner,
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Customer.friend_id.in_(missing),
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)
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for fid, remark, nick, real, head in (await session.execute(stmt)).all():
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info[fid] = (remark or nick or real or fid, real or "", head or "")
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return info
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@router.get("/staff-chat-stats")
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async def get_staff_chat_stats(
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session: SessionDep,
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owner_account_id: Annotated[str, Query(min_length=1)],
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start: Annotated[int | None, Query(ge=0)] = None,
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end: Annotated[int | None, Query(ge=0)] = None,
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) -> StaffChatStatsOut:
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"""微信员工沟通统计：5 数字 + 客户明细（全本地 message 聚合，1:1 私聊）。"""
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if end is None:
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end = int(time.time() * 1000)
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if start is None:
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start = end - 3 * _MS_PER_DAY # 默认近 3 天
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if await _summary_has_rows(session):
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agg_rows, last_map = await _aggregate_summary(session, owner_account_id, start, end)
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else:
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agg_rows, last_map = await _aggregate(session, owner_account_id, start, end)
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talker_ids = [r.talker_id for r in agg_rows]
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names = await _customer_names(session, owner_account_id, talker_ids)
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customers: list[StaffChatCustomerOut] = []
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for r in agg_rows:
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tid = r.talker_id
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last_is_send = last_map.get(tid) # bool | None（None=最后一条方向未知）
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customers.append(
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StaffChatCustomerOut(
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talker_id=tid,
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friend_name=(names.get(tid) or (tid, "", ""))[0],
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real_name=(names.get(tid) or ("", "", ""))[1] or None,
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head_image_url=(names.get(tid) or ("", "", ""))[2] or None,
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send_count=int(r.send_count or 0),
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receive_count=int(r.receive_count or 0),
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interaction_days=int(r.interaction_days or 0),
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# True→1, False→0, None→None（方向未知不计入两率；summary 用 ==1/==0 自动排除 None）
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last_is_send=int(last_is_send) if last_is_send is not None else None,
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last_time=r.last_time,
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)
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)
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summary = StaffChatStatsSummary(
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chat_count=len(customers),
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effective_count=sum(1 for c in customers if c.send_count >= 1 and c.receive_count >= 1),
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follow_count=sum(1 for c in customers if c.interaction_days >= 2),
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last_reply_count=sum(1 for c in customers if c.last_is_send == 1),
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no_reply_count=sum(1 for c in customers if c.last_is_send == 0),
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)
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return StaffChatStatsOut(
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owner_account_id=owner_account_id,
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start=start,
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end=end,
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summary=summary,
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customers=customers,
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)
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