feat(realestate-lab): 청약 가점제 계산 (84점 만점)

- calculate_subscription_points(): 무주택기간(32) + 부양가족(35) + 통장기간(17)
- 프로필 GET/PUT 응답에 subscription_points 포함
- 매칭 결과 API에 my_points 포함 (가점 비교용)

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

realestate-lab/app/db.py

@@ -449,6 +449,81 @@ def upsert_model(data: Dict[str, Any]):
         """, data)
 
 
+# ── 청약 가점 계산 ───────────────────────────────────────────────────────────
+
+def calculate_subscription_points(profile: Dict[str, Any]) -> Dict[str, Any]:
+    """청약 가점제 점수 계산 (총 84점 만점).
+
+    1. 무주택기간 (0~32점): 만 30세부터 기산, 연 2점
+    2. 부양가족 수 (0~35점): 인당 5점, 6명+ 만점
+    3. 청약통장 가입기간 (0~17점): 6개월 미만 1점 ~ 15년+ 17점
+    """
+    result = {
+        "homeless_duration": {"score": 0, "max": 32, "detail": ""},
+        "dependents": {"score": 0, "max": 35, "detail": ""},
+        "subscription_period": {"score": 0, "max": 17, "detail": ""},
+        "total": 0,
+        "max_total": 84,
+    }
+
+    if not profile:
+        return result
+
+    # 1. 무주택기간 (만 30세부터 기산, 연 2점, 최대 32점)
+    age = profile.get("age") or 0
+    is_homeless = profile.get("is_homeless", False)
+    if is_homeless and age >= 30:
+        homeless_years = age - 30
+        score = min(homeless_years * 2, 32)
+        # 1년 미만도 2점
+        if homeless_years == 0:
+            score = 2
+        result["homeless_duration"]["score"] = score
+        result["homeless_duration"]["detail"] = f"만 {age}세, 무주택 약 {homeless_years}년"
+    elif is_homeless and age < 30:
+        result["homeless_duration"]["score"] = 0
+        result["homeless_duration"]["detail"] = f"만 {age}세 (30세 미만, 기간 미산정)"
+    else:
+        result["homeless_duration"]["detail"] = "유주택자"
+
+    # 2. 부양가족 수 (인당 5점, 최대 35점)
+    family_members = profile.get("family_members") or 0
+    dependents = max(family_members - 1, 0)  # 본인 제외
+    dep_score = min(dependents * 5, 35)
+    result["dependents"]["score"] = dep_score
+    result["dependents"]["detail"] = f"{dependents}명" if dependents > 0 else "0명 (본인만)"
+
+    # 3. 청약통장 가입기간 (6개월 미만 1점, 이후 1년마다 +1점, 최대 17점)
+    months = profile.get("subscription_months") or 0
+    if months <= 0:
+        sub_score = 0
+        sub_detail = "미가입"
+    elif months < 6:
+        sub_score = 1
+        sub_detail = f"{months}개월 (6개월 미만)"
+    else:
+        years = months / 12
+        # 6개월~1년 = 2점, 1~2년 = 3점, ..., 14~15년 = 16점, 15년+ = 17점
+        sub_score = min(int(years) + 2, 17)
+        if years < 1:
+            sub_score = 2
+        if years >= 1:
+            y = int(years)
+            sub_detail = f"{y}년 {months - y*12}개월"
+        else:
+            sub_detail = f"{months}개월"
+    result["subscription_period"]["score"] = sub_score
+    result["subscription_period"]["detail"] = sub_detail
+
+    result["total"] = (
+        result["homeless_duration"]["score"]
+        + result["dependents"]["score"]
+        + result["subscription_period"]["score"]
+    )
+
+    return result
+
+
 # ── user_profile CRUD ────────────────────────────────────────────────────────
 
 def _profile_row_to_dict(r) -> Dict[str, Any]:
@@ -468,7 +543,11 @@ def _profile_row_to_dict(r) -> Dict[str, Any]:
 def get_profile() -> Optional[Dict[str, Any]]:
     with _conn() as conn:
         r = conn.execute("SELECT * FROM user_profile WHERE id = 1").fetchone()
-    return _profile_row_to_dict(r) if r else None
+    if not r:
+        return None
+    profile = _profile_row_to_dict(r)
+    profile["subscription_points"] = calculate_subscription_points(profile)
+    return profile
 
 
 PROFILE_COLUMNS = {
@@ -512,7 +591,9 @@ def upsert_profile(data: Dict[str, Any]) -> Dict[str, Any]:
                 vals,
             )
         row = conn.execute("SELECT * FROM user_profile WHERE id = 1").fetchone()
-    return _profile_row_to_dict(row)
+    profile = _profile_row_to_dict(row)
+    profile["subscription_points"] = calculate_subscription_points(profile)
+    return profile
 
 
 # ── match_results CRUD ───────────────────────────────────────────────────────
@@ -536,10 +617,18 @@ def save_match_result(data: Dict[str, Any]):
 def get_matches(page: int = 1, size: int = 20) -> Dict[str, Any]:
     offset = (page - 1) * size
     with _conn() as conn:
+        # 프로필 가점 계산
+        profile_row = conn.execute("SELECT * FROM user_profile WHERE id = 1").fetchone()
+        points = None
+        if profile_row:
+            profile = _profile_row_to_dict(profile_row)
+            points = calculate_subscription_points(profile)
+
         total = conn.execute("SELECT COUNT(*) FROM match_results").fetchone()[0]
         rows = conn.execute("""
             SELECT m.*, a.house_nm, a.region_name, a.address, a.status as ann_status,
-                   a.receipt_start, a.receipt_end, a.winner_date, a.pblanc_url
+                   a.receipt_start, a.receipt_end, a.winner_date, a.pblanc_url,
+                   a.house_secd, a.is_speculative_area
             FROM match_results m
             JOIN announcements a ON a.id = m.announcement_id
             ORDER BY m.is_new DESC, m.match_score DESC
@@ -552,7 +641,13 @@ def get_matches(page: int = 1, size: int = 20) -> Dict[str, Any]:
         d["match_reasons"] = json.loads(d["match_reasons"]) if d["match_reasons"] else []
         d["eligible_types"] = json.loads(d["eligible_types"]) if d["eligible_types"] else []
         items.append(d)
-    return {"items": items, "total": total, "page": page, "size": size}
+    return {
+        "items": items,
+        "total": total,
+        "page": page,
+        "size": size,
+        "my_points": points,
+    }
 
 
 def mark_match_read(match_id: int) -> bool: