feat(lotto): calibrate_winner + backfill (멱등·청크)

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

lotto/tests/test_backtest_db.py

@@ -65,6 +65,31 @@ def test_winner_calibration_upsert(monkeypatch):
     assert row["score_total"] == 2.00
 
 
+def _seed_draws(db, n=40):
+    rows = []
+    import random as _r; _r.seed(2)
+    for i in range(1, n + 1):
+        s = sorted(_r.sample(range(1, 46), 6))
+        rows.append({"drw_no": i, "drw_date": f"2020-01-{(i%28)+1:02d}",
+                     "n1": s[0], "n2": s[1], "n3": s[2], "n4": s[3],
+                     "n5": s[4], "n6": s[5], "bonus": ((s[5] % 45) + 1)})
+    db.upsert_many_draws(rows)
+
+def test_backfill_calibration_idempotent(monkeypatch):
+    db = _fresh_db(monkeypatch)
+    _seed_draws(db, 40)
+    from app import backtest as bt
+    r1 = bt.backfill_calibration(batch=15, sample_m=200)
+    # 첫 회차는 point-in-time 데이터가 빈약 → min_history 이후만 처리
+    done1 = len(db.get_calibrated_draw_nos())
+    assert done1 > 0
+    r2 = bt.backfill_calibration(batch=100, sample_m=200)  # 나머지
+    done2 = len(db.get_calibrated_draw_nos())
+    assert done2 >= done1
+    r3 = bt.backfill_calibration(batch=100, sample_m=200)  # 재실행 → 추가 0
+    assert r3["calibrated"] == 0
+
+
 def test_get_calibrated_draw_nos(monkeypatch):
     """저장된 draw_no 집합이 get_calibrated_draw_nos에 포함되어야 한다."""
     db = _fresh_db(monkeypatch)