refactor: backend→lotto 서비스 리네이밍 + lotto.db 레거시 테이블 스키마 제거

- backend/ → lotto/ 디렉토리 이동
- docker-compose: lotto-backend→lotto, lotto-frontend→frontend
- deploy scripts, nginx, agent-office config 네이밍 일괄 반영
- lotto/app/db.py에서 todos·blog_posts CREATE TABLE 제거 (personal로 이관 완료)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

lotto/app/checker.py

@@ -0,0 +1,73 @@
+import json
+from .db import (
+    _conn, get_draw, update_recommendation_result
+)
+
+def _calc_rank(my_nums: list[int], win_nums: list[int], bonus: int) -> tuple[int, int, bool]:
+    """
+    (rank, correct_cnt, has_bonus) 반환
+    rank: 1~5 (1등~5등), 0 (낙첨)
+    """
+    matched = set(my_nums) & set(win_nums)
+    cnt = len(matched)
+    has_bonus = bonus in my_nums
+    
+    if cnt == 6:
+        return 1, cnt, has_bonus
+    if cnt == 5 and has_bonus:
+        return 2, cnt, has_bonus
+    if cnt == 5:
+        return 3, cnt, has_bonus
+    if cnt == 4:
+        return 4, cnt, has_bonus
+    if cnt == 3:
+        return 5, cnt, has_bonus
+        
+    return 0, cnt, has_bonus
+
+def check_results_for_draw(drw_no: int) -> int:
+    """
+    특정 회차(drw_no) 결과가 나왔을 때,
+    해당 회차를 타겟으로 했던(based_on_draw == drw_no - 1) 추천들을 채점한다.
+    반환값: 채점한 개수
+    """
+    win_row = get_draw(drw_no)
+    if not win_row:
+        return 0
+        
+    win_nums = [
+        win_row["n1"], win_row["n2"], win_row["n3"],
+        win_row["n4"], win_row["n5"], win_row["n6"]
+    ]
+    bonus = win_row["bonus"]
+    
+    # based_on_draw가 (이번회차 - 1)인 것들 조회
+    # 즉, 1000회차 추첨 결과로는, 999회차 데이터를 바탕으로 1000회차를 예측한 것들을 채점
+    target_based_on = drw_no - 1
+    
+    with _conn() as conn:
+        rows = conn.execute(
+            """
+            SELECT id, numbers 
+            FROM recommendations 
+            WHERE based_on_draw = ? AND checked = 0
+            """,
+            (target_based_on,)
+        ).fetchall()
+        
+    count = 0
+    for r in rows:
+        my_nums = json.loads(r["numbers"])
+        rank, correct, has_bonus = _calc_rank(my_nums, win_nums, bonus)
+        
+        update_recommendation_result(r["id"], rank, correct, has_bonus)
+        count += 1
+
+    # ── 구매 이력 체크 연동 ──────────────────────────────────────
+    try:
+        from .purchase_manager import check_purchases_for_draw as _check_purchases
+        _check_purchases(drw_no)  # 내부에서 evolve_after_check → recalculate_weights 호출
+    except ImportError:
+        pass  # purchase_manager 미설치 시 무시 (하위호환)
+
+    return count