로또 프리미엄 Phase 2 — 구매 이력 + 개인 패턴 분석 + 주간 리포트 캐싱

- purchase_history 테이블 추가 (draw_no, amount, sets, prize, note)
- weekly_reports 캐시 테이블 추가 (drw_no UNIQUE, report JSON)
- GET  /api/lotto/purchase         구매 이력 조회 (draw_no, days 필터)
- POST /api/lotto/purchase         구매 이력 추가
- PUT  /api/lotto/purchase/:id     구매 이력 수정 (당첨금 업데이트)
- DELETE /api/lotto/purchase/:id   구매 이력 삭제
- GET  /api/lotto/purchase/stats   투자 수익률 통계
- GET  /api/lotto/analysis/personal 개인 패턴 분석 (top/least picks, 홀짝/구간/연속번호)
- GET  /api/lotto/report/history   저장된 주간 리포트 목록
- GET  /api/lotto/report/:drw_no   캐시 우선 조회 + cached 플래그
- 스케줄러: 토요일 09:00 주간 리포트 자동 생성 및 DB 캐싱

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

backend/app/analyzer.py

@@ -355,6 +355,76 @@ def get_statistical_report(draws: List[Tuple[int, List[int]]]) -> Dict[str, Any]
     }
 
 
+def analyze_personal_patterns(
+    all_numbers: List[List[int]],
+    draws: List[Tuple[int, List[int]]],
+) -> Dict[str, Any]:
+    """
+    사용자 추천 이력 기반 개인 패턴 분석.
+    all_numbers: 저장된 모든 추천 번호 리스트 (각 원소는 6개짜리 리스트)
+    draws: 역대 당첨번호 (홀짝/합계 평균 비교용)
+    """
+    if not all_numbers:
+        return {"total_analyzed": 0, "message": "추천 이력이 없습니다"}
+
+    total = len(all_numbers)
+    flat = [n for nums in all_numbers for n in nums]
+    freq = Counter(flat)
+
+    # 번호별 선택 빈도
+    number_frequency = {n: freq.get(n, 0) for n in range(1, 46)}
+    top_picks = sorted(range(1, 46), key=lambda n: -freq.get(n, 0))[:10]
+    least_picks = [n for n in sorted(range(1, 46), key=lambda n: freq.get(n, 0)) if freq.get(n, 0) == 0][:10]
+
+    # 패턴 지표
+    odd_counts = [sum(1 for n in nums if n % 2 == 1) for nums in all_numbers]
+    sums = [sum(nums) for nums in all_numbers]
+    ranges = [max(nums) - min(nums) for nums in all_numbers]
+    consecutive_count = sum(
+        1 for nums in all_numbers
+        if any(sorted(nums)[i + 1] - sorted(nums)[i] == 1 for i in range(5))
+    )
+
+    zone_totals = {k: 0 for k in ["1-9", "10-19", "20-29", "30-39", "40-45"]}
+    zone_ranges = [("1-9", 1, 9), ("10-19", 10, 19), ("20-29", 20, 29), ("30-39", 30, 39), ("40-45", 40, 45)]
+    for nums in all_numbers:
+        for label, lo, hi in zone_ranges:
+            zone_totals[label] += sum(1 for n in nums if lo <= n <= hi)
+    zone_avg = {k: round(v / total, 2) for k, v in zone_totals.items()}
+
+    avg_odd = sum(odd_counts) / total
+    avg_sum = sum(sums) / total
+    avg_range = sum(ranges) / total
+
+    # 역대 당첨번호 평균과 비교
+    if draws:
+        draw_odd_avg = sum(sum(1 for n in nums if n % 2 == 1) for _, nums in draws) / len(draws)
+        draw_sum_avg = sum(sum(nums) for _, nums in draws) / len(draws)
+    else:
+        draw_odd_avg = 3.0
+        draw_sum_avg = 138.0
+
+    return {
+        "total_analyzed": total,
+        "number_frequency": number_frequency,
+        "top_picks": top_picks,
+        "least_picks": least_picks,
+        "pattern": {
+            "avg_odd_count": round(avg_odd, 2),
+            "avg_sum": round(avg_sum, 1),
+            "avg_range": round(avg_range, 1),
+            "consecutive_rate": round(consecutive_count / total, 3),
+            "zone_avg": zone_avg,
+        },
+        "vs_draw_avg": {
+            "odd_diff": round(avg_odd - draw_odd_avg, 2),
+            "sum_diff": round(avg_sum - draw_sum_avg, 1),
+            "odd_tendency": "홀수 선호" if avg_odd > draw_odd_avg + 0.2 else ("짝수 선호" if avg_odd < draw_odd_avg - 0.2 else "균형"),
+            "sum_tendency": "고합계 선호" if avg_sum > draw_sum_avg + 5 else ("저합계 선호" if avg_sum < draw_sum_avg - 5 else "균형"),
+        },
+    }
+
+
 def generate_weekly_report(draws: List[Tuple[int, List[int]]], target_drw_no: int) -> Dict[str, Any]:
     """
     특정 회차 공략 리포트 생성.

backend/app/db.py

@@ -251,6 +251,34 @@ def init_db() -> None:
             "CREATE INDEX IF NOT EXISTS idx_sub_items_created ON subscription_items(created_at DESC);"
         )
 
+        # ── purchase_history 테이블 ────────────────────────────────────────────
+        conn.execute(
+            """
+            CREATE TABLE IF NOT EXISTS purchase_history (
+                id         INTEGER PRIMARY KEY AUTOINCREMENT,
+                draw_no    INTEGER NOT NULL,
+                amount     INTEGER NOT NULL,
+                sets       INTEGER NOT NULL DEFAULT 1,
+                prize      INTEGER NOT NULL DEFAULT 0,
+                note       TEXT    NOT NULL DEFAULT '',
+                created_at TEXT    NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now'))
+            );
+            """
+        )
+        conn.execute("CREATE INDEX IF NOT EXISTS idx_purchase_draw ON purchase_history(draw_no DESC);")
+
+        # ── weekly_reports 캐시 테이블 ──────────────────────────────────────────
+        conn.execute(
+            """
+            CREATE TABLE IF NOT EXISTS weekly_reports (
+                id           INTEGER PRIMARY KEY AUTOINCREMENT,
+                drw_no       INTEGER UNIQUE NOT NULL,
+                report       TEXT    NOT NULL,
+                generated_at TEXT    NOT NULL DEFAULT (strftime('%Y-%m-%dT%H:%M:%fZ','now'))
+            );
+            """
+        )
+
         # ── subscription_profile 테이블 (싱글톤 id=1) ──────────────────────────
         conn.execute(
             """
@@ -1109,6 +1137,144 @@ def get_subscription_profile() -> Optional[Dict[str, Any]]:
     return _profile_row_to_dict(r) if r else None
 
 
+# ── purchase_history CRUD ─────────────────────────────────────────────────────
+
+def _purchase_row_to_dict(r) -> Dict[str, Any]:
+    return {
+        "id": r["id"],
+        "draw_no": r["draw_no"],
+        "amount": r["amount"],
+        "sets": r["sets"],
+        "prize": r["prize"],
+        "note": r["note"],
+        "created_at": r["created_at"],
+    }
+
+
+def add_purchase(draw_no: int, amount: int, sets: int, prize: int = 0, note: str = "") -> Dict[str, Any]:
+    with _conn() as conn:
+        conn.execute(
+            "INSERT INTO purchase_history (draw_no, amount, sets, prize, note) VALUES (?, ?, ?, ?, ?)",
+            (draw_no, amount, sets, prize, note),
+        )
+        row = conn.execute("SELECT * FROM purchase_history WHERE rowid = last_insert_rowid()").fetchone()
+    return _purchase_row_to_dict(row)
+
+
+def get_purchases(draw_no: int = None, days: int = None) -> List[Dict[str, Any]]:
+    conditions, params = [], []
+    if draw_no is not None:
+        conditions.append("draw_no = ?")
+        params.append(draw_no)
+    if days:
+        conditions.append("created_at >= datetime('now', ? || ' days')")
+        params.append(f"-{days}")
+    where = f"WHERE {' AND '.join(conditions)}" if conditions else ""
+    with _conn() as conn:
+        rows = conn.execute(
+            f"SELECT * FROM purchase_history {where} ORDER BY draw_no DESC, id DESC",
+            params,
+        ).fetchall()
+    return [_purchase_row_to_dict(r) for r in rows]
+
+
+def update_purchase(purchase_id: int, data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+    allowed = {"draw_no", "amount", "sets", "prize", "note"}
+    updates = {k: v for k, v in data.items() if k in allowed}
+    if not updates:
+        with _conn() as conn:
+            row = conn.execute("SELECT * FROM purchase_history WHERE id = ?", (purchase_id,)).fetchone()
+        return _purchase_row_to_dict(row) if row else None
+    set_clause = ", ".join(f"{k} = ?" for k in updates)
+    with _conn() as conn:
+        cur = conn.execute(
+            f"UPDATE purchase_history SET {set_clause} WHERE id = ?",
+            list(updates.values()) + [purchase_id],
+        )
+        if cur.rowcount == 0:
+            return None
+        row = conn.execute("SELECT * FROM purchase_history WHERE id = ?", (purchase_id,)).fetchone()
+    return _purchase_row_to_dict(row)
+
+
+def delete_purchase(purchase_id: int) -> bool:
+    with _conn() as conn:
+        cur = conn.execute("DELETE FROM purchase_history WHERE id = ?", (purchase_id,))
+    return cur.rowcount > 0
+
+
+def get_purchase_stats() -> Dict[str, Any]:
+    with _conn() as conn:
+        rows = conn.execute("SELECT amount, prize FROM purchase_history").fetchall()
+    if not rows:
+        return {
+            "total_records": 0,
+            "total_invested": 0,
+            "total_prize": 0,
+            "net": 0,
+            "return_rate": 0.0,
+            "prize_count": 0,
+            "max_prize": 0,
+        }
+    amounts = [r["amount"] for r in rows]
+    prizes = [r["prize"] for r in rows]
+    total_invested = sum(amounts)
+    total_prize = sum(prizes)
+    return {
+        "total_records": len(rows),
+        "total_invested": total_invested,
+        "total_prize": total_prize,
+        "net": total_prize - total_invested,
+        "return_rate": round((total_prize / total_invested * 100) if total_invested else 0.0, 2),
+        "prize_count": sum(1 for p in prizes if p > 0),
+        "max_prize": max(prizes),
+    }
+
+
+# ── weekly_reports CRUD ───────────────────────────────────────────────────────
+
+def save_weekly_report(drw_no: int, report_json: str) -> None:
+    with _conn() as conn:
+        conn.execute(
+            """
+            INSERT INTO weekly_reports (drw_no, report)
+            VALUES (?, ?)
+            ON CONFLICT(drw_no) DO UPDATE SET
+                report = excluded.report,
+                generated_at = strftime('%Y-%m-%dT%H:%M:%fZ','now')
+            """,
+            (drw_no, report_json),
+        )
+
+
+def get_weekly_report_list(limit: int = 10) -> List[Dict[str, Any]]:
+    with _conn() as conn:
+        rows = conn.execute(
+            "SELECT drw_no, generated_at FROM weekly_reports ORDER BY drw_no DESC LIMIT ?",
+            (limit,),
+        ).fetchall()
+    return [dict(r) for r in rows]
+
+
+def get_weekly_report(drw_no: int) -> Optional[Dict[str, Any]]:
+    with _conn() as conn:
+        row = conn.execute(
+            "SELECT drw_no, report, generated_at FROM weekly_reports WHERE drw_no = ?",
+            (drw_no,),
+        ).fetchone()
+    if not row:
+        return None
+    import json as _json
+    return {"drw_no": row["drw_no"], "generated_at": row["generated_at"], **_json.loads(row["report"])}
+
+
+def get_all_recommendation_numbers() -> List[List[int]]:
+    """개인 패턴 분석용: 저장된 모든 추천 번호 반환"""
+    with _conn() as conn:
+        rows = conn.execute("SELECT numbers FROM recommendations ORDER BY id DESC").fetchall()
+    return [json.loads(r["numbers"]) for r in rows]
+
+
 def upsert_subscription_profile(data: Dict[str, Any]) -> Dict[str, Any]:
     field_map = {
         "isHouseholdHead": "is_household_head",

backend/app/main.py

@@ -22,13 +22,19 @@ from .db import (
     get_subscription_profile, upsert_subscription_profile,
     # 성과 통계
     get_recommendation_performance,
+    # Phase 2: 구매 이력
+    add_purchase, get_purchases, update_purchase, delete_purchase, get_purchase_stats,
+    # Phase 2: 주간 리포트 캐시
+    save_weekly_report, get_weekly_report_list, get_weekly_report,
+    # Phase 2: 개인 패턴 분석
+    get_all_recommendation_numbers,
 )
 from .recommender import recommend_numbers, recommend_with_heatmap
 from .collector import sync_latest, sync_ensure_all
 from .generator import run_simulation, generate_smart_recommendations
 from .checker import check_results_for_draw
 from .utils import calc_metrics, calc_recent_overlap
-from .analyzer import get_statistical_report, generate_weekly_report
+from .analyzer import get_statistical_report, generate_weekly_report, analyze_personal_patterns
 
 app = FastAPI()
 scheduler = BackgroundScheduler(timezone=os.getenv("TZ", "Asia/Seoul"))
@@ -57,6 +63,20 @@ def on_startup():
 
     scheduler.add_job(_run_simulation_job, "cron", hour="0,4,8,12,16,20", minute=5)
 
+    # 3. 토요일 오전 9시 — 다음 회차 공략 리포트 자동 캐싱
+    def _save_weekly_report_job():
+        import json as _json
+        draws = get_all_draw_numbers()
+        latest = get_latest_draw()
+        if not draws or not latest:
+            return
+        target = latest["drw_no"] + 1
+        report = generate_weekly_report(draws, target)
+        save_weekly_report(target, _json.dumps(report, ensure_ascii=False))
+        print(f"[WeeklyReport] {target}회차 리포트 저장 완료")
+
+    scheduler.add_job(_save_weekly_report_job, "cron", day_of_week="sat", hour=9, minute=0)
+
     scheduler.start()
 
 
@@ -179,20 +199,95 @@ def api_report_latest():
     return generate_weekly_report(draws, target)
 
 
+@app.get("/api/lotto/report/history")
+def api_report_history(limit: int = 10):
+    """저장된 주간 리포트 목록 (자동 저장된 것만)"""
+    return {"reports": get_weekly_report_list(limit=min(limit, 52))}
+
+
 @app.get("/api/lotto/report/{drw_no}")
 def api_report_by_draw(drw_no: int):
     """
-    특정 회차 공략 리포트 (해당 회차 이전 데이터 기준).
+    특정 회차 공략 리포트 (캐시 우선, 없으면 실시간 생성).
-    drw_no: 공략 대상 회차 번호
     """
+    cached = get_weekly_report(drw_no)
+    if cached:
+        return {**cached, "cached": True}
+
     draws = get_all_draw_numbers()
     if not draws:
         raise HTTPException(status_code=404, detail="No data yet")
-    # drw_no 이전 데이터만 사용
     base_draws = [(no, nums) for no, nums in draws if no < drw_no]
     if not base_draws:
         raise HTTPException(status_code=400, detail=f"{drw_no}회차 이전 데이터가 없습니다")
-    return generate_weekly_report(base_draws, drw_no)
+    return {**generate_weekly_report(base_draws, drw_no), "cached": False}
+
+
+# ── 개인 패턴 분석 (Phase 2) ─────────────────────────────────────────────────
+@app.get("/api/lotto/analysis/personal")
+def api_personal_analysis():
+    """
+    저장된 추천 이력 기반 개인 패턴 분석.
+    - 자주 선택한 번호 TOP 10 / 한 번도 선택 안 한 번호
+    - 홀짝 비율, 합계, 범위, 연속번호 포함률
+    - 구간별 분포, 역대 당첨번호 평균과 비교
+    """
+    all_numbers = get_all_recommendation_numbers()
+    draws = get_all_draw_numbers()
+    return analyze_personal_patterns(all_numbers, draws)
+
+
+# ── 구매 이력 API (Phase 2) ───────────────────────────────────────────────────
+
+class PurchaseCreate(BaseModel):
+    draw_no: int
+    amount: int
+    sets: int = 1
+    prize: int = 0
+    note: str = ""
+
+
+class PurchaseUpdate(BaseModel):
+    draw_no: Optional[int] = None
+    amount: Optional[int] = None
+    sets: Optional[int] = None
+    prize: Optional[int] = None
+    note: Optional[str] = None
+
+
+@app.get("/api/lotto/purchase/stats")
+def api_purchase_stats():
+    """투자 수익률 통계 (총 투자금, 총 당첨금, 수익률 등)"""
+    return get_purchase_stats()
+
+
+@app.get("/api/lotto/purchase")
+def api_purchase_list(draw_no: Optional[int] = None, days: Optional[int] = None):
+    """구매 이력 조회 (draw_no, days 필터 선택)"""
+    return {"records": get_purchases(draw_no=draw_no, days=days)}
+
+
+@app.post("/api/lotto/purchase", status_code=201)
+def api_purchase_create(body: PurchaseCreate):
+    """구매 이력 추가"""
+    return add_purchase(body.draw_no, body.amount, body.sets, body.prize, body.note)
+
+
+@app.put("/api/lotto/purchase/{purchase_id}")
+def api_purchase_update(purchase_id: int, body: PurchaseUpdate):
+    """구매 이력 수정 (당첨금 업데이트 등)"""
+    updated = update_purchase(purchase_id, body.model_dump(exclude_none=True))
+    if updated is None:
+        raise HTTPException(status_code=404, detail="Purchase not found")
+    return updated
+
+
+@app.delete("/api/lotto/purchase/{purchase_id}")
+def api_purchase_delete(purchase_id: int):
+    """구매 이력 삭제"""
+    if not delete_purchase(purchase_id):
+        raise HTTPException(status_code=404, detail="Purchase not found")
+    return {"ok": True}
 
 
 # ── 통계 분석 리포트 ────────────────────────────────────────────────────────