fix(analytics): id-tiebreak snapshot ordering + rates/cn_day tests + breakdown ValueError

app/admin/repositories/analytics_health.py

@@ -9,7 +9,7 @@ from __future__ import annotations
 from collections import defaultdict
 from datetime import UTC, datetime
 
-from sqlalchemy import and_, func, select
+from sqlalchemy import func, select
 from sqlalchemy.orm import Session
 
 from app.core import rewards
@@ -31,7 +31,7 @@ def diff_snapshots(rows: list[dict]) -> list[dict]:
 
     out: list[dict] = []
     for group in parts.values():
-        group.sort(key=lambda r: r["created_at"])
+        group.sort(key=lambda r: (r["created_at"], r.get("id", 0)))
         prev = {k: 0 for k in _COUNTS}
         for r in group:
             deltas = {f"d_{k}": max(0, int(r[k]) - prev[k]) for k in _COUNTS}
@@ -74,7 +74,7 @@ def _sum_deltas(deltas: list[dict]) -> dict:
 def _fetch_rows(db: Session, date_from: datetime, date_to: datetime) -> list[dict]:
     """取 [from, to) 区间行 + 每分区在 from 左侧的最后一条基线行(供第一条区间增量做差)。"""
     cols = (
-        H.device_id, H.epoch_id, E.event, H.created_at,
+        H.id, H.device_id, H.epoch_id, E.event, H.created_at,
         H.app_ver, H.oem, H.os,
         E.attempted, E.drop_capture, E.delivered, E.drop_undelivered,
     )
@@ -83,8 +83,10 @@ def _fetch_rows(db: Session, date_from: datetime, date_to: datetime) -> list[dic
         .where(H.created_at >= date_from, H.created_at < date_to)
     ).mappings().all()
 
+    # 注:基线子查询无下界扫 from 左侧全量(spec §7 已接受的取舍;量级变大再上物化 rollup)。
+    # 用 max(id) 而非 max(created_at) 选"最新一条":id 严格单调,避免 SQLite 秒级时间戳撞车时选歧义。
     sub = (
-        select(H.device_id, H.epoch_id, E.event, func.max(H.created_at).label("mx"))
+        select(H.device_id, H.epoch_id, E.event, func.max(H.id).label("max_id"))
         .join(E, E.snapshot_id == H.id)
         .where(H.created_at < date_from)
         .group_by(H.device_id, H.epoch_id, E.event)
@@ -92,13 +94,7 @@ def _fetch_rows(db: Session, date_from: datetime, date_to: datetime) -> list[dic
     )
     baseline = db.execute(
         select(*cols).join(E, E.snapshot_id == H.id).join(
-            sub,
-            and_(
-                sub.c.device_id == H.device_id,
-                sub.c.epoch_id == H.epoch_id,
-                sub.c.event == E.event,
-                sub.c.mx == H.created_at,
-            ),
+            sub, sub.c.max_id == H.id
         )
     ).mappings().all()
 
@@ -128,7 +124,8 @@ def trend(db: Session, date_from: datetime, date_to: datetime) -> list[dict]:
 
 
 def breakdown(db: Session, date_from: datetime, date_to: datetime, dim: str) -> list[dict]:
-    assert dim in ("event", "app_ver", "oem")
+    if dim not in ("event", "app_ver", "oem"):
+        raise ValueError(f"invalid dim: {dim!r}")
     deltas = _in_range_deltas(db, date_from, date_to)
     by_key: dict[str, list[dict]] = defaultdict(list)
     for d in deltas: