feat(weight-evolver): DB 통합 진입점 (generate_weekly/apply_today/evaluate_weekly)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

lotto/app/weight_evolver.py

@@ -121,3 +121,179 @@ def decide_base_update(
     if current_base is None:
         return DEFAULT_UNIFORM[:], "cold_start"
     return list(current_base), "unchanged"
+
+
+# ---------- DB-touching entry points ----------
+
+from datetime import datetime, timedelta, timezone
+
+
+KST = timezone(timedelta(hours=9))
+
+
+def _db():
+    from . import db as _db_mod
+    return _db_mod
+
+
+def _today_kst():
+    return datetime.now(KST).date()
+
+
+def get_week_start(d=None) -> str:
+    """주어진 날짜의 월요일 ISO 'YYYY-MM-DD'."""
+    if d is None:
+        d = _today_kst()
+    ws = d - timedelta(days=d.weekday())
+    return ws.isoformat()
+
+
+def get_active_weight() -> Optional[List[float]]:
+    """오늘 적용 중인 W. 없으면 None (균등 폴백)."""
+    today = _today_kst()
+    week_start = get_week_start(today)
+    dow = today.weekday()
+    if dow == 6:
+        dow = 5  # 일요일은 토요일 W 유지
+    trial = _db().get_weight_trial(week_start, dow)
+    if trial:
+        return trial["weight"]
+    return None
+
+
+def generate_weekly_candidates_and_save(seed: Optional[int] = None) -> List[Dict[str, Any]]:
+    """월요일 09:00 cron 진입점. 6 trials 생성 후 DB 저장."""
+    db = _db()
+    base = db.get_current_base()
+    if base is None:
+        base = DEFAULT_UNIFORM[:]
+        db.save_base_history(
+            effective_from=get_week_start(),
+            weight=base,
+            source_trial_id=None,
+            update_reason="cold_start",
+            winner_score=None,
+            winner_max_correct=None,
+        )
+
+    candidates = generate_weekly_candidates(base, seed=seed)
+    week_start = get_week_start()
+    for c in candidates:
+        db.save_weight_trial(
+            week_start=week_start,
+            day_of_week=c["day_of_week"],
+            weight=c["weight"],
+            source=c["source"],
+            base_at_gen=base,
+        )
+    return candidates
+
+
+def apply_today_and_pick(n: int = 5) -> Dict[str, Any]:
+    """매일 09:00 cron 진입점. 오늘 W로 N=5 세트 추출 후 auto_picks 저장."""
+    db = _db()
+    from . import analyzer, recommender
+    today = _today_kst()
+    week_start = get_week_start(today)
+    dow = min(today.weekday(), 5)
+
+    trial = db.get_weight_trial(week_start, dow)
+    if trial is None:
+        return {"ok": False, "reason": "no_trial_for_today"}
+
+    W = trial["weight"]
+    draws = db.get_all_draw_numbers()
+    cache = analyzer.build_analysis_cache(draws)
+
+    picks_saved = []
+    for i in range(1, n + 1):
+        try:
+            r = recommender.recommend_numbers(draws)
+            nums = r["numbers"]
+            s = analyzer.score_combination(nums, cache, weights=W)
+            pid = db.save_auto_pick(trial["id"], i, nums, meta_score=s["score_total"])
+            picks_saved.append({"id": pid, "numbers": nums, "score": s["score_total"]})
+        except Exception:
+            continue
+
+    return {
+        "ok": True,
+        "trial_id": trial["id"],
+        "weight": W,
+        "picks": picks_saved,
+    }
+
+
+def evaluate_weekly() -> Dict[str, Any]:
+    """토 22:00 cron 진입점. 6일 trials × N picks 채점 + base 갱신."""
+    db = _db()
+    today = _today_kst()
+    week_start = get_week_start(today)
+
+    trials = db.get_weekly_trials(week_start)
+    if not trials:
+        return {"ok": False, "reason": "no_trials"}
+
+    latest = db.get_latest_draw()
+    if latest is None:
+        return {"ok": False, "reason": "no_latest_draw"}
+    winning = [
+        latest["drw_num1"], latest["drw_num2"], latest["drw_num3"],
+        latest["drw_num4"], latest["drw_num5"], latest["drw_num6"],
+    ]
+
+    per_day = []
+    for trial in trials:
+        picks = db.get_auto_picks(trial["id"])
+        if not picks:
+            continue
+        day_scores = []
+        max_c = 0
+        for p in picks:
+            correct = count_match(p["numbers"], winning)
+            rank = RANK_BY_CORRECT.get(correct)
+            db.update_auto_pick_grade(p["id"], correct, rank)
+            day_scores.append(calc_pick_score(p["numbers"], winning))
+            if correct > max_c:
+                max_c = correct
+        avg_score = sum(day_scores) / len(day_scores)
+        per_day.append({
+            "trial_id": trial["id"],
+            "day_of_week": trial["day_of_week"],
+            "weight": trial["weight"],
+            "avg_score": avg_score,
+            "max_correct": max_c,
+            "n_picks": len(picks),
+        })
+
+    if not per_day:
+        return {"ok": False, "reason": "no_picks_graded"}
+
+    winner = max(per_day, key=lambda d: d["avg_score"])
+
+    current_base = db.get_current_base()
+    new_base, reason = decide_base_update(
+        winner_max_correct=winner["max_correct"],
+        winner_W=winner["weight"],
+        current_base=current_base,
+    )
+
+    next_monday = today + timedelta(days=(7 - today.weekday()) % 7 or 7)
+    db.save_base_history(
+        effective_from=next_monday.isoformat(),
+        weight=new_base,
+        source_trial_id=winner["trial_id"],
+        update_reason=reason,
+        winner_score=winner["avg_score"],
+        winner_max_correct=winner["max_correct"],
+    )
+
+    return {
+        "ok": True,
+        "draw_no": latest["drw_no"],
+        "week_start": week_start,
+        "winner": winner,
+        "new_base": new_base,
+        "update_reason": reason,
+        "per_day": per_day,
+    }