feat: 재고량 vs 처방 사용량 이중 Y축 비교 그래프 추가

- /api/stock-analytics/stock-with-usage API 추가
- 일별/주별/월별 분석 기간 선택
- 재고 추세 + 사용량 추세 동시 분석
- 추세 해석 카드 (과잉재고/부족 위험 등 자동 진단)

backend/app.py

@@ -9973,6 +9973,192 @@ def api_stock_level():
         return jsonify({'success': False, 'error': str(e)}), 500
 
 
+@app.route('/api/stock-analytics/stock-with-usage')
+def api_stock_with_usage():
+    """
+    재고 변화 + 처방 기반 사용량 통합 API (이중 Y축 그래프용)
+    GET /api/stock-analytics/stock-with-usage?drug_code=A123456789&start_date=2026-01-01&end_date=2026-03-13&period=daily|weekly|monthly
+    
+    반환:
+    - items: [{ date, stock, inbound, outbound, rx_usage }]
+    - rx_usage: PS_sub_pharm 기반 처방 사용량
+    """
+    conn = None
+    conn_pres = None
+    try:
+        drug_code = request.args.get('drug_code', '').strip()
+        start_date = request.args.get('start_date', '')
+        end_date = request.args.get('end_date', '')
+        period = request.args.get('period', 'daily')  # daily, weekly, monthly
+        
+        if not drug_code:
+            return jsonify({'success': False, 'error': 'drug_code 파라미터 필요'}), 400
+        
+        # 날짜 형식 변환
+        start_date_fmt = start_date.replace('-', '') if start_date else (datetime.now() - timedelta(days=90)).strftime('%Y%m%d')
+        end_date_fmt = end_date.replace('-', '') if end_date else datetime.now().strftime('%Y%m%d')
+        
+        import pyodbc
+        conn_str_drug = (
+            'DRIVER={ODBC Driver 17 for SQL Server};'
+            'SERVER=192.168.0.4\\PM2014;'
+            'DATABASE=PM_DRUG;'
+            'UID=sa;'
+            'PWD=tmddls214!%(;'
+            'TrustServerCertificate=yes'
+        )
+        conn_str_pres = (
+            'DRIVER={ODBC Driver 17 for SQL Server};'
+            'SERVER=192.168.0.4\\PM2014;'
+            'DATABASE=PM_PRES;'
+            'UID=sa;'
+            'PWD=tmddls214!%(;'
+            'TrustServerCertificate=yes'
+        )
+        
+        conn = pyodbc.connect(conn_str_drug, timeout=10)
+        conn_pres = pyodbc.connect(conn_str_pres, timeout=10)
+        cursor = conn.cursor()
+        cursor_pres = conn_pres.cursor()
+        
+        # 1. 현재 재고 및 약품 정보
+        cursor.execute("""
+            SELECT 
+                IT.IM_QT_sale_debit as current_stock,
+                G.GoodsName as product_name,
+                G.SplName as supplier
+            FROM IM_total IT
+            LEFT JOIN CD_GOODS G ON IT.DrugCode = G.DrugCode
+            WHERE IT.DrugCode = ?
+        """, (drug_code,))
+        
+        stock_row = cursor.fetchone()
+        current_stock = int(stock_row.current_stock or 0) if stock_row else 0
+        product_name = stock_row.product_name if stock_row else drug_code
+        supplier = stock_row.supplier if stock_row else ''
+        
+        # 2. 그룹핑 기준 설정
+        if period == 'monthly':
+            date_group_expr = "LEFT(IM_DT_appl, 6)"  # YYYYMM
+            rx_date_group_expr = "LEFT(INSUDATETIME, 6)"
+        elif period == 'weekly':
+            # 주차 계산: YYYYWW
+            date_group_expr = "CAST(YEAR(CONVERT(DATE, IM_DT_appl, 112)) AS VARCHAR) + RIGHT('0' + CAST(DATEPART(WEEK, CONVERT(DATE, IM_DT_appl, 112)) AS VARCHAR), 2)"
+            rx_date_group_expr = "CAST(YEAR(CONVERT(DATE, INSUDATETIME, 112)) AS VARCHAR) + RIGHT('0' + CAST(DATEPART(WEEK, CONVERT(DATE, INSUDATETIME, 112)) AS VARCHAR), 2)"
+        else:  # daily
+            date_group_expr = "IM_DT_appl"
+            rx_date_group_expr = "LEFT(INSUDATETIME, 8)"
+        
+        # 3. 재고 입출고 데이터 (IM_date_total)
+        cursor.execute(f"""
+            SELECT 
+                {date_group_expr} as date_group,
+                SUM(ISNULL(IM_QT_sale_debit, 0)) as inbound,
+                SUM(ISNULL(IM_QT_sale_credit, 0)) as outbound
+            FROM IM_date_total
+            WHERE DrugCode = ?
+              AND IM_DT_appl >= ?
+              AND IM_DT_appl <= ?
+            GROUP BY {date_group_expr}
+            ORDER BY {date_group_expr} DESC
+        """, (drug_code, start_date_fmt, end_date_fmt))
+        
+        stock_rows = cursor.fetchall()
+        
+        # 4. 처방 기반 사용량 (PS_sub_pharm)
+        # 컬럼명: PreSerial, Indate, DrugCode, QUAN, Days
+        if period == 'monthly':
+            rx_date_group_expr = "LEFT(CONVERT(VARCHAR, PSP.Indate, 112), 6)"
+        elif period == 'weekly':
+            rx_date_group_expr = "CAST(YEAR(PSP.Indate) AS VARCHAR) + RIGHT('0' + CAST(DATEPART(WEEK, PSP.Indate) AS VARCHAR), 2)"
+        else:  # daily
+            rx_date_group_expr = "CONVERT(VARCHAR, PSP.Indate, 112)"
+        
+        cursor_pres.execute(f"""
+            SELECT 
+                {rx_date_group_expr} as date_group,
+                SUM(ISNULL(PSP.QUAN * PSP.QUAN_TIME * PSP.Days, 0)) as rx_usage,
+                COUNT(DISTINCT PSP.PreSerial) as rx_count
+            FROM PS_sub_pharm PSP
+            WHERE PSP.DrugCode = ?
+              AND PSP.Indate >= ?
+              AND PSP.Indate <= ?
+            GROUP BY {rx_date_group_expr}
+            ORDER BY {rx_date_group_expr}
+        """, (drug_code, start_date_fmt, end_date_fmt))
+        
+        rx_rows = cursor_pres.fetchall()
+        rx_data = {str(row.date_group): {'rx_usage': int(row.rx_usage or 0), 'rx_count': int(row.rx_count or 0)} for row in rx_rows}
+        
+        # 5. 역순 누적 재고 계산 + 처방 사용량 병합
+        items = []
+        running_stock = current_stock
+        
+        for row in stock_rows:
+            date_group = str(row.date_group) if row.date_group else ''
+            
+            # 날짜 포맷팅
+            if period == 'monthly' and len(date_group) == 6:
+                formatted_date = f"{date_group[:4]}-{date_group[4:6]}"
+            elif period == 'weekly':
+                formatted_date = date_group  # YYYYWW
+            else:  # daily
+                formatted_date = f"{date_group[:4]}-{date_group[4:6]}-{date_group[6:8]}" if len(date_group) == 8 else date_group
+            
+            inbound = int(row.inbound or 0)
+            outbound = int(row.outbound or 0)
+            
+            rx_info = rx_data.get(date_group, {'rx_usage': 0, 'rx_count': 0})
+            
+            items.append({
+                'date': formatted_date,
+                'date_group': date_group,
+                'stock': running_stock,
+                'inbound': inbound,
+                'outbound': outbound,
+                'rx_usage': rx_info['rx_usage'],
+                'rx_count': rx_info['rx_count']
+            })
+            
+            running_stock = running_stock - inbound + outbound
+        
+        # 시간순 정렬
+        items.reverse()
+        
+        # 6. 통계 계산
+        total_rx_usage = sum(item['rx_usage'] for item in items)
+        total_rx_count = sum(item['rx_count'] for item in items)
+        avg_rx_usage = total_rx_usage / len(items) if items else 0
+        
+        conn.close()
+        conn_pres.close()
+        
+        return jsonify({
+            'success': True,
+            'drug_code': drug_code,
+            'product_name': product_name,
+            'supplier': supplier,
+            'current_stock': current_stock,
+            'period': period,
+            'items': items,
+            'stats': {
+                'total_rx_usage': total_rx_usage,
+                'total_rx_count': total_rx_count,
+                'avg_rx_usage': round(avg_rx_usage, 1)
+            }
+        })
+        
+    except Exception as e:
+        if conn:
+            conn.close()
+        if conn_pres:
+            conn_pres.close()
+        logging.error(f"stock-with-usage API 오류: {e}")
+        import traceback
+        traceback.print_exc()
+        return jsonify({'success': False, 'error': str(e)}), 500
+
+
 @app.route('/api/stock-analytics/search-drugs')
 def api_search_drugs():
     """