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:

tests/test_analytics_health.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 
 from datetime import datetime, timezone
 
-from app.admin.repositories.analytics_health import diff_snapshots
+from app.admin.repositories.analytics_health import _cn_day, _rates, diff_snapshots
 
 
 def _row(device, epoch, event, ts, **cum) -> dict:
@@ -52,3 +52,37 @@ def test_diff_clamps_negative_on_reorder() -> None:
     ]
     out = sorted(diff_snapshots(rows), key=lambda r: r["created_at"])
     assert out[1]["d_attempted"] == 0
+
+
+def test_rates_computes_both_formulas() -> None:
+    out = _rates({"attempted": 150, "drop_capture": 0, "delivered": 140, "drop_undelivered": 10})
+    assert out["track_success_rate"] == 1.0
+    assert out["report_success_rate"] == 140 / 150
+
+
+def test_rates_zero_denominator_yields_none() -> None:
+    out = _rates({"attempted": 0, "drop_capture": 0, "delivered": 0, "drop_undelivered": 0})
+    assert out["track_success_rate"] is None
+    assert out["report_success_rate"] is None
+
+
+def test_cn_day_beijing_boundary() -> None:
+    # UTC 15:59 → 北京 23:59 同日;UTC 16:00 → 北京 次日 00:00
+    assert _cn_day(datetime(2026, 7, 1, 15, 59, tzinfo=timezone.utc)) == "2026-07-01"
+    assert _cn_day(datetime(2026, 7, 1, 16, 0, tzinfo=timezone.utc)) == "2026-07-02"
+
+
+def test_diff_same_timestamp_ordered_by_id() -> None:
+    ts = datetime(2026, 7, 1, 1, 0, tzinfo=timezone.utc)
+    # 相同 created_at,乱序传入(id=2 在前);应按 id 排序 → id=1(cum100) 在前
+    rows = [
+        {"id": 2, "device_id": "d", "epoch_id": "e", "event": "vp", "created_at": ts,
+         "app_ver": "v", "oem": "o", "os": "s",
+         "attempted": 150, "drop_capture": 0, "delivered": 0, "drop_undelivered": 0},
+        {"id": 1, "device_id": "d", "epoch_id": "e", "event": "vp", "created_at": ts,
+         "app_ver": "v", "oem": "o", "os": "s",
+         "attempted": 100, "drop_capture": 0, "delivered": 0, "drop_undelivered": 0},
+    ]
+    out = diff_snapshots(rows)
+    assert out[0]["d_attempted"] == 100  # id=1 sorts first → its cumulative
+    assert out[1]["d_attempted"] == 50   # id=2 second → 150-100