fix(lotto): Phase 2 리뷰 반영 (engine_w 회차주 기준·누출제거·N+1제거·테스트 보강)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-31 17:17:09 +09:00
parent 94a94e260c
commit 850638ae58
2 changed files with 66 additions and 8 deletions

View File

@@ -113,10 +113,12 @@ def _db():
return _db_mod
def calibrate_winner(draw_no: int, sample_m: int = 2000) -> Dict[str, Any]:
"""DB 진입점: 회차 1개 캘리브레이션 후 저장 (멱등)."""
def calibrate_winner(draw_no: int, sample_m: int = 2000, draws=None) -> Dict[str, Any]:
"""DB 진입점: 회차 1개 캘리브레이션 후 저장 (멱등).
draws를 외부에서 전달하면 N+1 조회를 방지한다."""
db = _db()
draws = db.get_all_draw_numbers()
if draws is None:
draws = db.get_all_draw_numbers()
row = db.get_draw(draw_no)
if row is None:
return {"ok": False, "reason": "no_draw"}
@@ -142,7 +144,7 @@ def backfill_calibration(batch: int = 50, sample_m: int = 2000) -> Dict[str, Any
todo.sort()
n = 0
for draw_no in todo[:batch]:
r = calibrate_winner(draw_no, sample_m=sample_m)
r = calibrate_winner(draw_no, sample_m=sample_m, draws=draws)
if r.get("ok"):
n += 1
return {"calibrated": n, "remaining": max(0, len(todo) - batch)}
@@ -177,16 +179,18 @@ def run_forward_purchase(draw_no: int, k: int = 5000, pool_n: int = 20000,
hist=graded, best_match=graded["best_match"], avg_meta_score=avg_meta,
)
# 1) engine_w — 그 주 trials(있으면) 아니면 current_base
# 1) engine_w — 그 주 trials(있으면) 아니면 uniform fallback (leak-free)
from datetime import date as _date
from . import weight_evolver as we
week_start = we.get_week_start()
trials = db.get_weekly_trials(week_start) if hasattr(db, "get_weekly_trials") else []
draw_date = _date.fromisoformat(row["drw_date"])
week_start = we.get_week_start(draw_date)
trials = db.get_weekly_trials(week_start)
if trials:
for t in trials:
bought = purchase_tickets(pool, cache, t["weight"], k)
_store("engine_w", f"w{t['day_of_week']}", t["weight"], t["id"], bought)
else:
base = db.get_current_base() or [0.2] * 5
base = [0.2] * 5
bought = purchase_tickets(pool, cache, base, k)
_store("engine_w", "base", base, None, bought)