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shaguabijia-app-server/app/admin/repositories/coupon_data.py
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zhuzihao 78d970f420 feat: 领券数据看板 — coupon_session 流水表 + admin 聚合接口 (#99)
- 新表 coupon_session(一次领券一行,trace_id 唯一):POST /api/v1/coupon/session
  两段 upsert(发起 started / 收尾 completed·failed·abandoned),记全程耗时、各平台耗时、
  机型/ROM、app_env、trace_url、origin_package(发起来源)。
- admin GET /admin/api/coupon-data:发起/完成数 + 平均耗时 + P5/P50/P95/P99(Python 算分位,
  SQLite 无 percentile)+ 按天/小时趋势 + 明细分页 + join 用户手机号/昵称,app_env 默认 prod;
  另加 GET /admin/api/coupon-data/user-records 供「点手机号看该用户全部领券」抽屉。
- 迁移拆 3 个:建表 coupon_session_table + trace_url 加列 + origin_package 加列
  (建表迁移已被某环境应用后改它不重跑,故新列单独加列迁移)。

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: zzhyyyyy <2685922758@qq.com>
Reviewed-on: #99
Co-authored-by: zhuzihao <zhuzihao@wonderable.ai>
Co-committed-by: zhuzihao <zhuzihao@wonderable.ai>
2026-06-30 22:59:36 +08:00

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"""admin「领券数据」看板聚合:发起/完成数、耗时均值与分位、按天/小时趋势、逐条明细。
数据源 coupon_session(一次领券一行,客户端 /api/v1/coupon/session 两段上报)。量级不大,全量拉
区间数据后 Python 聚合(分位 SQLite 无 percentile,统一 Python 算,PG 上也一致)。
- 发起数 = 区间内全部 session(含 started/completed/failed/abandoned),= 流失统计的基数。
- 完成数 / 耗时均值 / 分位 = 仅 status==completed 子集(成功跑完才有可比的"领券耗时")。
- summary/daily/hourly/total 在全量上算,不受分页;items 为排序后当前页。
"""
from __future__ import annotations
from datetime import UTC, date as _date, datetime
from sqlalchemy import func, or_, select
from sqlalchemy.orm import Session
from app.core import rewards
from app.models.coupon_state import CouponSession
from app.models.user import User
def _cn_hour(dt: datetime) -> int:
"""started_at(UTC 口径)→ 北京时间小时(023)。naive 当 UTC(sqlite),tz-aware 直接换算(pg)。"""
if dt.tzinfo is None:
dt = dt.replace(tzinfo=UTC)
return dt.astimezone(rewards.CN_TZ).hour
def _percentile(sorted_vals: list[int], q: float) -> int | None:
"""线性插值分位(q=0..100,numpy 默认法)。sorted_vals 须已升序;空返回 None。"""
if not sorted_vals:
return None
if len(sorted_vals) == 1:
return sorted_vals[0]
idx = (len(sorted_vals) - 1) * q / 100.0
lo = int(idx)
hi = min(lo + 1, len(sorted_vals) - 1)
frac = idx - lo
return round(sorted_vals[lo] * (1 - frac) + sorted_vals[hi] * frac)
def _avg(vals: list[int]) -> int | None:
return round(sum(vals) / len(vals)) if vals else None
def _session_to_row(r, phone: str | None = None, nickname: str | None = None) -> dict:
"""CouponSession ORM → 明细行 dict(主表「领券数据」与「用户全部领券」抽屉共用)。"""
return {
"id": r.id,
"trace_id": r.trace_id,
"user_id": r.user_id,
"user_phone": phone,
"user_nickname": nickname,
"status": r.status,
"platforms": r.platforms,
"origin_package": r.origin_package,
"elapsed_ms": r.elapsed_ms,
"platform_elapsed": r.platform_elapsed,
"device_model": r.device_model,
"rom": r.rom,
"app_env": r.app_env,
"started_at": r.started_at,
"claimed_count": r.claimed_count,
"trace_url": r.trace_url,
}
def _empty_result() -> dict:
return {
"summary": {
"started_count": 0, "completed_count": 0, "avg_elapsed_ms": None,
"p5_ms": None, "p50_ms": None, "p95_ms": None, "p99_ms": None,
},
"daily": [],
"hourly": [],
"total": 0,
"items": [],
}
def coupon_data_report(
db: Session,
*,
date_from: str,
date_to: str,
user: str | None = None,
app_env: str | None = None,
granularity: str = "day",
limit: int = 500,
offset: int = 0,
sort: str = "time",
) -> dict:
"""日期区间(北京自然日 started_date,闭区间)领券数据:汇总卡 + 趋势 + 逐条明细。
- user:手机号/昵称模糊搜(匹配不到任何用户 → 空结果)。
- app_env:prod/dev 精确;None=全部。
- sort:time=发起时刻倒序(默认) / elapsed=全程耗时倒序(None 末尾)。
"""
by_hour = granularity == "hour"
d_from = _date.fromisoformat(date_from)
d_to = _date.fromisoformat(date_to)
# user 模糊 → 先定位匹配用户 id;匹配不到直接空结果(不全表扫)。
user_ids: set[int] | None = None
if user:
like = f"%{user}%"
user_ids = set(db.execute(
select(User.id).where(or_(User.phone.like(like), User.nickname.like(like)))
).scalars().all())
if not user_ids:
return _empty_result()
stmt = select(CouponSession).where(
CouponSession.started_date >= d_from,
CouponSession.started_date <= d_to,
)
if app_env is not None:
stmt = stmt.where(CouponSession.app_env == app_env)
if user_ids is not None:
stmt = stmt.where(CouponSession.user_id.in_(user_ids))
rows = list(db.execute(stmt).scalars())
# ── 汇总卡 ──
completed_elapsed = sorted(
r.elapsed_ms for r in rows if r.status == "completed" and r.elapsed_ms is not None
)
summary = {
"started_count": len(rows),
"completed_count": sum(1 for r in rows if r.status == "completed"),
"avg_elapsed_ms": _avg(completed_elapsed),
"p5_ms": _percentile(completed_elapsed, 5),
"p50_ms": _percentile(completed_elapsed, 50),
"p95_ms": _percentile(completed_elapsed, 95),
"p99_ms": _percentile(completed_elapsed, 99),
}
# ── 按天趋势(柱=发起/完成数,线=平均耗时)──
daily_map: dict[str, dict] = {}
for r in rows:
d = r.started_date.isoformat()
b = daily_map.get(d)
if b is None:
b = {"date": d, "started_count": 0, "completed_count": 0, "_elapsed": []}
daily_map[d] = b
b["started_count"] += 1
if r.status == "completed":
b["completed_count"] += 1
if r.elapsed_ms is not None:
b["_elapsed"].append(r.elapsed_ms)
daily = [
{
"date": b["date"],
"started_count": b["started_count"],
"completed_count": b["completed_count"],
"avg_elapsed_ms": _avg(b["_elapsed"]),
}
for b in sorted(daily_map.values(), key=lambda x: x["date"])
]
# ── 按小时趋势(单日 hour 粒度)──
hourly: list[dict] = []
if by_hour:
hour_map: dict[int, dict] = {}
for r in rows:
h = _cn_hour(r.started_at)
b = hour_map.get(h)
if b is None:
b = {"hour": h, "started_count": 0, "completed_count": 0, "_elapsed": []}
hour_map[h] = b
b["started_count"] += 1
if r.status == "completed":
b["completed_count"] += 1
if r.elapsed_ms is not None:
b["_elapsed"].append(r.elapsed_ms)
hourly = [
{
"hour": b["hour"],
"started_count": b["started_count"],
"completed_count": b["completed_count"],
"avg_elapsed_ms": _avg(b["_elapsed"]),
}
for b in sorted(hour_map.values(), key=lambda x: x["hour"])
]
# ── 明细:排序 + 分页 + 补用户手机号/昵称(批量,防 N+1)──
if sort == "elapsed":
rows.sort(key=lambda r: (r.elapsed_ms is None, -(r.elapsed_ms or 0)))
else: # time:发起时刻倒序
rows.sort(key=lambda r: r.started_at, reverse=True)
page = rows[offset:offset + limit]
uids = {r.user_id for r in page if r.user_id is not None}
user_map: dict[int, tuple[str | None, str | None]] = {}
if uids:
user_map = {
uid: (phone, nickname)
for uid, phone, nickname in db.execute(
select(User.id, User.phone, User.nickname).where(User.id.in_(uids))
).all()
}
items = []
for r in page:
phone, nickname = user_map.get(r.user_id, (None, None)) if r.user_id is not None else (None, None)
items.append(_session_to_row(r, phone, nickname))
return {
"summary": summary,
"daily": daily,
"hourly": hourly,
"total": len(rows),
"items": items,
}
def coupon_user_records(db: Session, *, user_id: int, limit: int = 100) -> dict:
"""某用户全部领券记录(点手机号抽屉用):按发起时刻倒序、不限日期,total=该用户领券总次数。"""
rows = list(db.execute(
select(CouponSession)
.where(CouponSession.user_id == user_id)
.order_by(CouponSession.started_at.desc())
.limit(limit)
).scalars())
total = db.execute(
select(func.count()).select_from(CouponSession).where(CouponSession.user_id == user_id)
).scalar_one()
return {"items": [_session_to_row(r) for r in rows], "total": int(total)}