shaguabijia-app-server/app/admin/repositories/stats.py

"""admin 大盘聚合查询(全局 count/sum/DAU/成功率)。全部只读、不改任何数据。

⚠️ 性能:这些是全表 count/sum,P0 数据量小够用;用户量上来后热点字段(user.created_at /
user.last_login_at / comparison_record.status / withdraw_order.status)要加索引,或改增量统计表。
"""
from __future__ import annotations

from collections import Counter
from datetime import date, datetime, time, timedelta, timezone
from decimal import Decimal, InvalidOperation

from sqlalchemy import case, func, select
from sqlalchemy.orm import Session

from app.admin.repositories.coupon_data import _percentile
from app.models.ad_feed_reward import AdFeedRewardRecord
from app.models.ad_reward import AdRewardRecord
from app.models.analytics_event import AnalyticsEvent
from app.models.comparison import ComparisonRecord
from app.models.coupon_state import (
    CouponClaimRecord,
    CouponPromptEngagement,
    CouponSession,
)
from app.models.cps_order import CpsOrder
from app.models.feedback import Feedback
from app.models.savings import SavingsRecord
from app.models.signin import SigninBoostRecord, SigninRecord
from app.models.user import User
from app.models.wallet import CoinTransaction, WithdrawOrder

_BEIJING = timezone(timedelta(hours=8))
COUPON_REWARD_BIZ_TYPES = ("reward_video", "ad_reward", "coupon", "coupon_reward")
COMPARISON_REWARD_BIZ_TYPES = ("comparison", "compare_reward", "comparison_reward")
EXCLUDED_REWARD_BIZ_TYPES = ("invite_inviter", "invite_invitee", "admin_grant")
UNCLASSIFIED_FEED_BIZ_TYPES = ("feed_ad_reward",)
REGULAR_TASK_EXCLUDED_BIZ_TYPES = (
    *COUPON_REWARD_BIZ_TYPES,
    *COMPARISON_REWARD_BIZ_TYPES,
    *EXCLUDED_REWARD_BIZ_TYPES,
    *UNCLASSIFIED_FEED_BIZ_TYPES,
)
MEITUAN_CPS_INVALID_STATUSES = ("4", "5")
MEITUAN_CPS_SETTLED_STATUS = "6"
COMPARE_START_EVENT = "real_compare_start"
COUPON_START_EVENT = "real_coupon_start"
JD_CPS_INVALID_CODES = {
    "2", "3", "4", "5", "6", "7", "8", "9", "11", "13", "14", "19", "20", "21",
    "22", "23", "25", "26", "27", "28", "29", "30", "31", "34", "35", "36",
}
JD_CPS_UNPAID_CODES = {"15"}


def _beijing_today_start_utc() -> datetime:
    """北京时间今天 0 点对应的 UTC 时刻(DAU / 今日新增按北京时区切天)。"""
    now_bj = datetime.now(_BEIJING)
    start_bj = now_bj.replace(hour=0, minute=0, second=0, microsecond=0)
    return start_bj.astimezone(timezone.utc)


def today_dau(db: Session) -> int:
    """今日活跃用户数(DAU):登录 + 开始比价 + 开始领券,按用户去重。

    = period_active_dau(今天, 今天);历史 / 多天窗口用 period_active_dau 传区间(广告收益报表复用)。
    """
    today_bj = datetime.now(_BEIJING).date()
    return period_active_dau(db, today_bj, today_bj)


def _default_period_end() -> date:
    """新版大盘不含今日,默认窗口结束日=北京时间昨天。"""
    return datetime.now(_BEIJING).date() - timedelta(days=1)


def _normalize_period(date_from: date | None, date_to: date | None) -> tuple[date, date]:
    end = date_to or _default_period_end()
    start = date_from or end
    if start > end:
        start, end = end, start
    return start, end


def _period_bounds(date_from: date, date_to: date) -> tuple[datetime, datetime, datetime, datetime]:
    """返回同一北京自然日窗口的 UTC aware 边界和北京 naive 边界。

    user.created_at / last_login_at 是 UTC aware 口径;比较/金币等历史上有北京 naive
    写入,所以两套边界同时保留。
    """
    start_bj = datetime.combine(date_from, time.min, tzinfo=_BEIJING)
    end_bj = datetime.combine(date_to + timedelta(days=1), time.min, tzinfo=_BEIJING)
    start_utc = start_bj.astimezone(timezone.utc)
    end_utc = end_bj.astimezone(timezone.utc)
    return (
        start_utc,
        end_utc,
        start_bj.replace(tzinfo=None),
        end_bj.replace(tzinfo=None),
    )


def _date_range(date_from: date, date_to: date) -> list[date]:
    days = (date_to - date_from).days
    return [date_from + timedelta(days=i) for i in range(days + 1)]


def _id_set(db: Session, stmt) -> set[int]:
    return {int(v) for v in db.execute(stmt).scalars().all() if v is not None}


def _event_user_ids(
    db: Session, event_names: tuple[str, ...], start_utc: datetime, end_utc: datetime
) -> set[int]:
    return _id_set(
        db,
        select(AnalyticsEvent.user_id).where(
            AnalyticsEvent.user_id.is_not(None),
            AnalyticsEvent.event.in_(event_names),
            AnalyticsEvent.created_at >= start_utc,
            AnalyticsEvent.created_at < end_utc,
        ),
    )


def _period_active_user_ids(
    db: Session,
    *,
    start_utc: datetime,
    end_utc: datetime,
    period_from: date,
    period_to: date,
) -> set[int]:
    """区间去重活跃用户 id 集合:登录(last_login_at)+ 开始比价(real_compare_start)+
    开始领券(real_coupon_start / claim_started)。

    user / analytics_event 用 UTC aware 边界 [start_utc, end_utc);coupon_prompt_engagement
    的 engage_date 是北京自然日 date 列,用 [period_from, period_to] 闭区间。今日 / 历史 / 多天通用。
    """
    login_user_ids = _id_set(
        db,
        select(User.id).where(User.last_login_at >= start_utc, User.last_login_at < end_utc),
    )
    compare_start_user_ids = _event_user_ids(db, (COMPARE_START_EVENT,), start_utc, end_utc)
    coupon_event_user_ids = _event_user_ids(db, (COUPON_START_EVENT,), start_utc, end_utc)
    coupon_claim_user_ids = _id_set(
        db,
        select(CouponPromptEngagement.user_id).where(
            CouponPromptEngagement.engage_date >= period_from,
            CouponPromptEngagement.engage_date <= period_to,
            CouponPromptEngagement.engage_type == "claim_started",
        ),
    )
    return login_user_ids | compare_start_user_ids | coupon_event_user_ids | coupon_claim_user_ids


def period_active_dau(db: Session, date_from: date, date_to: date) -> int:
    """任意北京自然日区间 [date_from, date_to] 的去重活跃用户数。

    与数据大盘 period.users.active 同口径(登录 + 开始比价 + 开始领券);广告收益报表按所选
    日期区间(含今日)复用,ARPU = 区间预估收益 ÷ 本数。全局口径,不随用户 / 类型 / 场景筛选变化。
    """
    period_from, period_to = _normalize_period(date_from, date_to)
    start_utc, end_utc, _start_local, _end_local = _period_bounds(period_from, period_to)
    return len(
        _period_active_user_ids(
            db,
            start_utc=start_utc,
            end_utc=end_utc,
            period_from=period_from,
            period_to=period_to,
        )
    )


def _commission_rate_percent(raw: str | None) -> Decimal | None:
    """美团 commissionRate 原值: "300"=3%, "10"=0.1%;也兼容 "3%"。"""
    if raw is None:
        return None
    s = str(raw).strip()
    if not s:
        return None
    try:
        if s.endswith("%"):
            return Decimal(s[:-1])
        val = Decimal(s)
    except (InvalidOperation, ValueError):
        return None
    return val / Decimal("100")


def _jd_valid_order(order: CpsOrder) -> bool:
    code = str(order.jd_valid_code).strip() if order.jd_valid_code is not None else ""
    return bool(code and code not in JD_CPS_INVALID_CODES and code not in JD_CPS_UNPAID_CODES)


def dashboard_overview(
    db: Session, *, date_from: date | None = None, date_to: date | None = None
) -> dict:
    today_start = _beijing_today_start_utc()
    period_from, period_to = _normalize_period(date_from, date_to)
    start_utc, end_utc, start_local, end_local = _period_bounds(period_from, period_to)

    def _count(model, *conds) -> int:
        stmt = select(func.count(model.id))
        if conds:
            stmt = stmt.where(*conds)
        return int(db.execute(stmt).scalar_one())

    def _sum(col, *conds) -> int:
        stmt = select(func.coalesce(func.sum(col), 0))
        if conds:
            stmt = stmt.where(*conds)
        return int(db.execute(stmt).scalar_one())

    def _user_id_set(stmt) -> set[int]:
        return {int(v) for v in db.execute(stmt).scalars().all() if v is not None}

    # ===== 用户 =====
    by_status = dict(
        db.execute(select(User.status, func.count(User.id)).group_by(User.status)).all()
    )

    # ===== 提现状态分布 =====
    wd_by_status = dict(
        db.execute(
            select(WithdrawOrder.status, func.count(WithdrawOrder.id)).group_by(
                WithdrawOrder.status
            )
        ).all()
    )

    # ===== 比价 =====
    comparison_total = _count(ComparisonRecord)
    comparison_success = _count(ComparisonRecord, ComparisonRecord.status == "success")
    success_rate = round(comparison_success / comparison_total, 4) if comparison_total else 0.0
    period_comparison_conds = (
        ComparisonRecord.created_at >= start_local,
        ComparisonRecord.created_at < end_local,
    )
    period_comparison_total = _count(ComparisonRecord, *period_comparison_conds)
    period_comparison_success = _count(
        ComparisonRecord,
        *period_comparison_conds,
        ComparisonRecord.status == "success",
    )
    period_comparison_success_rate = (
        round(period_comparison_success / period_comparison_total, 4)
        if period_comparison_total
        else 0.0
    )
    period_saved_positive_count = _count(
        ComparisonRecord,
        *period_comparison_conds,
        ComparisonRecord.status == "success",
        ComparisonRecord.saved_amount_cents > 0,
    )
    period_saved_positive_sum = _sum(
        ComparisonRecord.saved_amount_cents,
        *period_comparison_conds,
        ComparisonRecord.status == "success",
        ComparisonRecord.saved_amount_cents > 0,
    )
    period_avg_saved_cents = (
        round(period_saved_positive_sum / period_saved_positive_count)
        if period_saved_positive_count
        else None
    )
    period_avg_duration_ms = db.execute(
        select(func.avg(ComparisonRecord.total_ms)).where(
            *period_comparison_conds,
            ComparisonRecord.total_ms.is_not(None),
            ComparisonRecord.total_ms > 0,
        )
    ).scalar_one()
    period_avg_duration_ms = (
        round(float(period_avg_duration_ms))
        if period_avg_duration_ms is not None
        else None
    )

    ordered_exists = (
        select(SavingsRecord.id)
        .where(
            SavingsRecord.user_id == ComparisonRecord.user_id,
            SavingsRecord.source == "compare",
            SavingsRecord.shop_name.is_not(None),
            SavingsRecord.shop_name == ComparisonRecord.store_name,
        )
        .exists()
    )
    period_ordered_count = _count(
        ComparisonRecord,
        *period_comparison_conds,
        ComparisonRecord.store_name.is_not(None),
        ordered_exists,
    )

    # ===== 日期窗口用户 =====
    period_new_user_ids = _user_id_set(
        select(User.id).where(User.created_at >= start_utc, User.created_at < end_utc)
    )
    period_active_user_ids = _period_active_user_ids(
        db,
        start_utc=start_utc,
        end_utc=end_utc,
        period_from=period_from,
        period_to=period_to,
    )
    # 留存口径(2026-07-05 产品改):次日留存——窗口内每天 D,取 **D-1 日(前日)新增**用户,
    # 统计其 D 日活跃(登录/开始比价/开始领券)比例,逐日累加。默认窗口=昨日单天,即
    # 「前日新增用户的昨日留存」。原口径(窗口内新增∩窗口内活跃)在单日窗口下≈100% 无意义
    # (注册即登录,当天新增必然当天活跃)。逐日 cohort 在下方 trend 循环内顺带累计。
    retention_cohort_total = 0
    retention_retained_total = 0
    trend_points: list[dict] = []
    for cur_date in _date_range(period_from, period_to):
        day_start_utc, day_end_utc, day_start_local, day_end_local = _period_bounds(
            cur_date, cur_date
        )
        daily_comparison_conds = (
            ComparisonRecord.created_at >= day_start_local,
            ComparisonRecord.created_at < day_end_local,
        )
        daily_active_user_ids = _period_active_user_ids(
            db,
            start_utc=day_start_utc,
            end_utc=day_end_utc,
            period_from=cur_date,
            period_to=cur_date,
        )
        # 次日留存:cohort = 前一日(D-1)新增用户,留存 = 其中当日(D)活跃者(口径见上)。
        cohort_ids = _user_id_set(
            select(User.id).where(
                User.created_at >= day_start_utc - timedelta(days=1),
                User.created_at < day_end_utc - timedelta(days=1),
            )
        )
        retention_cohort_total += len(cohort_ids)
        retention_retained_total += len(cohort_ids & daily_active_user_ids)
        trend_points.append(
            {
                "date": cur_date,
                "active_users": len(daily_active_user_ids),
                "new_users": _count(
                    User,
                    User.created_at >= day_start_utc,
                    User.created_at < day_end_utc,
                ),
                "comparisons": _count(ComparisonRecord, *daily_comparison_conds),
            }
        )
    period_retention_rate = (
        round(retention_retained_total / retention_cohort_total, 4)
        if retention_cohort_total
        else None
    )

    period_coin_conds = (
        CoinTransaction.created_at >= start_local,
        CoinTransaction.created_at < end_local,
        CoinTransaction.amount > 0,
    )
    period_reward_video_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type.in_(("reward_video", "ad_reward")),
    )
    period_feed_ad_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type == "feed_ad_reward",
    )
    period_signin_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type == "signin",
    )
    period_signin_boost_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type == "signin_boost",
    )
    period_task_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type.like("task_%"),
    )
    period_coupon_reward_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type.in_(COUPON_REWARD_BIZ_TYPES),
    )
    period_comparison_reward_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type.in_(COMPARISON_REWARD_BIZ_TYPES),
    )
    period_regular_task_coin_total = _sum(
        CoinTransaction.amount,
        *period_coin_conds,
        CoinTransaction.biz_type.notin_(REGULAR_TASK_EXCLUDED_BIZ_TYPES),
    )
    period_cps_orders = list(
        db.execute(
            select(CpsOrder).where(
                CpsOrder.pay_time >= start_utc,
                CpsOrder.pay_time < end_utc,
            )
        ).scalars()
    )
    period_meituan_orders = [
        o for o in period_cps_orders if (o.platform or "meituan") == "meituan"
    ]
    period_meituan_valid_orders = [
        o for o in period_meituan_orders if o.mt_status not in MEITUAN_CPS_INVALID_STATUSES
    ]
    period_jd_orders = [o for o in period_cps_orders if o.platform == "jd"]
    period_jd_valid_orders = [o for o in period_jd_orders if _jd_valid_order(o)]
    period_jd_invalid_orders = [
        o for o in period_jd_orders if o.jd_valid_code and not _jd_valid_order(o)
    ]
    period_meituan_hit_count = 0
    period_meituan_miss_count = 0
    period_meituan_unknown_rate_count = 0
    for order in period_meituan_valid_orders:
        rate = _commission_rate_percent(order.commission_rate)
        if rate is None:
            period_meituan_unknown_rate_count += 1
        elif rate < Decimal("1"):
            period_meituan_miss_count += 1
        else:
            period_meituan_hit_count += 1
    period_meituan_hit_denominator = period_meituan_hit_count + period_meituan_miss_count
    period_meituan_hit_rate = (
        round(period_meituan_hit_count / period_meituan_hit_denominator, 4)
        if period_meituan_hit_denominator
        else None
    )

    # ===== 领券核心数据(2026-07-05 产品新增)=====
    # 数据源:coupon_session(一次领券一行,started_date 北京自然日)+ coupon_claim_record
    # (一券/点位一天一条终态,claim_date 北京自然日)。点位与 session 不按 trace_id 关联——
    # record_claims 更新路径不覆盖 trace_id(同设备同券同日重跑归第一次的 trace),按
    # (device_id, 自然日) 桶关联才可靠;同桶多次发起共享同一份点位终态。
    period_coupon_sessions = db.execute(
        select(
            CouponSession.device_id,
            CouponSession.started_date,
            CouponSession.status,
            CouponSession.elapsed_ms,
        ).where(
            CouponSession.started_date >= period_from,
            CouponSession.started_date <= period_to,
            # 只统计正式环境,同「领券数据」页默认口径(防 debug 包调试数据串台;
            # 命中 ix_coupon_session_date_env)。点位表无 app_env 列,但点位指标只经
            # 下方 prod session 触达的 (device, 日) 桶进入统计,随之收敛到 prod。
            CouponSession.app_env == "prod",
        )
    ).all()
    coupon_started = len(period_coupon_sessions)
    coupon_completed_elapsed = sorted(
        s.elapsed_ms
        for s in period_coupon_sessions
        if s.status == "completed" and s.elapsed_ms is not None
    )
    # 点位桶:(device, 日) → (点位总数, 成功点位数)。成功口径与「我的」页累计领券一致
    # (sum_claimed_count,2026-06-15 产品定):success + already_claimed(已领过=持有券)都算成功。
    point_buckets: dict[tuple[str, date], tuple[int, int]] = {
        (dev, d): (int(total), int(succ or 0))
        for dev, d, total, succ in db.execute(
            select(
                CouponClaimRecord.device_id,
                CouponClaimRecord.claim_date,
                func.count(),
                func.sum(
                    case(
                        (CouponClaimRecord.status.in_(("success", "already_claimed")), 1),
                        else_=0,
                    )
                ),
            )
            .where(
                CouponClaimRecord.claim_date >= period_from,
                # 上界放宽一天:跨零点场次(23:5x 发起)的点位 claim_date 落在发起日+1,
                # 桶只经下方 session 触达的键参与计数,放宽不会引入无关数据。
                CouponClaimRecord.claim_date <= period_to + timedelta(days=1),
            )
            .group_by(CouponClaimRecord.device_id, CouponClaimRecord.claim_date)
        ).all()
    }
    # 全部领成功的次数:completed 且其 (device, 日) 桶内点位全部成功(桶为空不算)。
    coupon_all_success = 0
    completed_bucket_totals: list[int] = []
    session_bucket_keys: set[tuple[str, date]] = set()
    for s in period_coupon_sessions:
        key = (s.device_id, s.started_date)
        if key not in point_buckets:
            # 跨零点回退:发起日桶不存在(点位终态全部落在次日)时取 (device, 发起日+1)。
            # 仅在发起日桶完全缺失时回退,避免抢占该设备次日 session 自己的桶。
            next_key = (s.device_id, s.started_date + timedelta(days=1))
            if next_key in point_buckets:
                key = next_key
        bucket = point_buckets.get(key)
        if bucket is not None:
            session_bucket_keys.add(key)
        if s.status != "completed" or bucket is None:
            continue
        total, succ = bucket
        completed_bucket_totals.append(total)
        if total > 0 and succ == total:
            coupon_all_success += 1
    # 每次发起的应领点位数:取「完成过的领券」实际点位数的众数(done 帧会给所有点位终态,
    # 完成场的点位数=当前配置的全量点位数;数据自校准,配置改点位数无需改代码)。本期无完成场
    # 时给不出,点位成功率置空。
    coupon_points_per_session = (
        Counter(completed_bucket_totals).most_common(1)[0][0]
        if completed_bucket_totals
        else None
    )
    # 成功点位数:本期 session 触达过的 (device, 日) 桶内成功点位之和(桶级去重,同桶重试不重复计)。
    coupon_point_success = sum(point_buckets[k][1] for k in session_bucket_keys)
    # 点位成功率 = 成功点位数 / (发起数 × 应领点位数):中途退出未跑到的点位不产生记录,
    # 但发起数×点位数把它们计入分母 → 视为失败,符合产品口径;重试会拉低该率(分母按次数计)。
    coupon_point_success_rate = (
        round(
            min(1.0, coupon_point_success / (coupon_started * coupon_points_per_session)), 4
        )
        if coupon_started and coupon_points_per_session
        else None
    )

    return {
        "users": {
            "total": _count(User),
            "active": by_status.get("active", 0),
            "disabled": by_status.get("disabled", 0),
            "deleted": by_status.get("deleted", 0),
            "new_today": _count(User, User.created_at >= today_start),
            "dau": today_dau(db),
        },
        "coins": {
            # 累计发放金币(coin_transaction 里所有 amount>0 之和;负数是兑换/扣减不计)
            "granted_total": _sum(CoinTransaction.amount, CoinTransaction.amount > 0),
            "reward_video_coin_total": _sum(
                CoinTransaction.amount,
                CoinTransaction.amount > 0,
                CoinTransaction.biz_type.in_(("reward_video", "ad_reward")),
            ),
            "reward_video_watch_count": _count(
                AdRewardRecord,
                AdRewardRecord.reward_scene == "reward_video",
                AdRewardRecord.status == "granted",
            ),
            "feed_ad_coin_total": _sum(
                CoinTransaction.amount,
                CoinTransaction.amount > 0,
                CoinTransaction.biz_type == "feed_ad_reward",
            ),
            "feed_ad_watch_count": _count(
                AdFeedRewardRecord,
                AdFeedRewardRecord.status == "granted",
            ),
            "signin_coin_total": _sum(
                CoinTransaction.amount,
                CoinTransaction.amount > 0,
                CoinTransaction.biz_type == "signin",
            ),
            "signin_count": _count(SigninRecord),
            "signin_boost_coin_total": _sum(
                CoinTransaction.amount,
                CoinTransaction.amount > 0,
                CoinTransaction.biz_type == "signin_boost",
            ),
            "signin_boost_watch_count": _count(SigninBoostRecord),
        },
        "cash": {
            "withdraw_success_cents": _sum(
                WithdrawOrder.amount_cents, WithdrawOrder.status == "success"
            ),
            "withdraw_pending_count": wd_by_status.get("pending", 0),
            "withdraw_success_count": wd_by_status.get("success", 0),
            "withdraw_failed_count": wd_by_status.get("failed", 0),
        },
        "comparison": {
            "total": comparison_total,
            "success": comparison_success,
            "success_rate": success_rate,
        },
        "period": {
            "date_from": period_from,
            "date_to": period_to,
            "users": {
                "new": len(period_new_user_ids),
                "active": len(period_active_user_ids),
                "retained_new_users": retention_retained_total,
                "retention_cohort": retention_cohort_total,
                "retention_rate": period_retention_rate,
                "retention_note": (
                    "次日留存:窗口内每天取前一日新增用户,统计其当日活跃"
                    "(登录/开始比价/开始领券,按用户去重)比例,逐日累加;"
                    "默认窗口=昨日,即前日新增用户的昨日留存"
                ),
            },
            "comparison": {
                "total": period_comparison_total,
                "success": period_comparison_success,
                "success_rate": period_comparison_success_rate,
                "ordered": period_ordered_count,
                "average_duration_ms": period_avg_duration_ms,
                "average_saved_cents": period_avg_saved_cents,
            },
            "coupon": {
                "started": coupon_started,
                "all_success": coupon_all_success,
                "success_rate": (
                    round(coupon_all_success / coupon_started, 4) if coupon_started else None
                ),
                "point_success": coupon_point_success,
                "points_per_session": coupon_points_per_session,
                "point_success_rate": coupon_point_success_rate,
                "median_elapsed_ms": _percentile(coupon_completed_elapsed, 50),
            },
            "coins": {
                "granted_total": _sum(CoinTransaction.amount, *period_coin_conds),
                "reward_video_coin_total": period_reward_video_coin_total,
                "feed_ad_coin_total": period_feed_ad_coin_total,
                "signin_coin_total": period_signin_coin_total,
                "signin_boost_coin_total": period_signin_boost_coin_total,
                "task_coin_total": period_task_coin_total,
                "coupon_reward_coin_total": period_coupon_reward_coin_total,
                "comparison_reward_coin_total": period_comparison_reward_coin_total,
                "regular_task_coin_total": period_regular_task_coin_total,
            },
            "cash": {
                "withdraw_success_cents": _sum(
                    WithdrawOrder.amount_cents,
                    WithdrawOrder.status == "success",
                    WithdrawOrder.created_at >= start_local,
                    WithdrawOrder.created_at < end_local,
                ),
            },
            "trend": trend_points,
        },
        "feedback": {
            "new": _count(Feedback, Feedback.status.in_(("pending", "new"))),
        },
        "cps": {
            "available": True,
            "note": "美团/JD CPS 读 cps_order 对账订单;淘宝佣金暂空",
            "meituan_order_count": len(period_meituan_valid_orders),
            "meituan_commission_cents": sum(
                o.commission_cents or 0 for o in period_meituan_valid_orders
            ),
            "meituan_hit_count": period_meituan_hit_count,
            "meituan_miss_count": period_meituan_miss_count,
            "meituan_unknown_rate_count": period_meituan_unknown_rate_count,
            "meituan_hit_rate": period_meituan_hit_rate,
            "jd_order_count": len(period_jd_valid_orders),
            # 数据大盘京东 CPS 只看实际佣金,不再用预估佣金兜底。
            "jd_commission_cents": sum(
                o.actual_commission_cents or 0 for o in period_jd_valid_orders
            ),
            "jd_actual_commission_cents": sum(
                o.actual_commission_cents or 0 for o in period_jd_valid_orders
            ),
            "jd_estimated_commission_cents": sum(
                o.estimated_commission_cents or 0 for o in period_jd_valid_orders
            ),
            "jd_invalid_count": len(period_jd_invalid_orders),
        },
    }