feat(database/repositories/ai_prediction_repository.py): Added new repository AIPredictionsRepository

2025-10-26 16:09:33 +03:00
parent 64e81aec69
commit 251e1b6e57
2 changed files with 104 additions and 1 deletions
@@ -2,5 +2,6 @@ from .user_repository import UserRepository
 from .robot_repository import RobotRepository
 from .product_repository import ProductRepository
 from .inventory_repository import InventoryRepository
+from .ai_prediction_repository import AIPredictionsRepository

-__all__ = ['UserRepository', 'RobotRepository', 'ProductRepository', 'InventoryRepository']
+__all__ = ['UserRepository', 'RobotRepository', 'ProductRepository', 'InventoryRepository', 'AIPredictionsRepository']
@@ -0,0 +1,102 @@
+from typing import List, Optional
+from datetime import datetime, date
+from database.connection import get_connection
+from model.ai_prediction import AIPrediction
+
+
+class AIPredictionsRepository:
+    def get_all(self) -> List[AIPrediction]:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("SELECT * FROM ai_predictions ORDER BY prediction_date DESC, product_id")
+                    return [
+                        AIPrediction(
+                            id=row[0],
+                            product_id=row[1],
+                            prediction_date=row[2],
+                            days_until_stockout=row[3],
+                            recommended_order=row[4],
+                            confidence_score=row[5],
+                            created_at=row[6]
+                        ) for row in cur.fetchall()
+                    ]
+        except Exception as e:
+            print(f"Ошибка получения прогнозов: {e}")
+            return []
+
+    def get_by_id(self, prediction_id: int) -> Optional[AIPrediction]:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("SELECT * FROM ai_predictions WHERE id = %s", (prediction_id,))
+                    row = cur.fetchone()
+                    return AIPrediction(*row) if row else None
+        except Exception as e:
+            print(f"Ошибка получения прогноза {prediction_id}: {e}")
+            return None
+
+    def get_by_product(self, product_id: str, limit: int = 10) -> List[AIPrediction]:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("""
+                        SELECT * FROM ai_predictions 
+                        WHERE product_id = %s 
+                        ORDER BY prediction_date DESC 
+                        LIMIT %s
+                    """, (product_id, limit))
+                    return [AIPrediction(*row) for row in cur.fetchall()]
+        except Exception as e:
+            print(f"Ошибка получения прогноза по товару {product_id}: {e}")
+            return []
+
+    def get_latest_predictions(self) -> List[AIPrediction]:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("""
+                        SELECT DISTINCT ON (product_id) *
+                        FROM ai_predictions 
+                        ORDER BY product_id, prediction_date DESC
+                    """)
+                    return [AIPrediction(*row) for row in cur.fetchall()]
+        except Exception as e:
+            print(f"Ошибка получения последних прогнозов по товарам: {e}")
+            return []
+
+    def create_prediction(self, product_id: str, prediction_date: date,
+                          days_until_stockout: int, recommended_order: int,
+                          confidence_score: float) -> Optional[int]:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("""
+                        INSERT INTO ai_predictions 
+                        (product_id, prediction_date, days_until_stockout, recommended_order, confidence_score)
+                        VALUES (%s, %s, %s, %s, %s)
+                        RETURNING id
+                    """, (product_id, prediction_date, days_until_stockout, recommended_order, confidence_score))
+
+                    prediction_id = cur.fetchone()[0]
+                    conn.commit()
+                    return prediction_id
+        except Exception as e:
+            print(f"Ошибка создания прогноза: {e}")
+            return None
+
+
+    def delete_old_predictions(self, older_than_days: int = 90) -> int:
+        try:
+            with get_connection() as conn:
+                with conn.cursor() as cur:
+                    cur.execute("""
+                        DELETE FROM ai_predictions 
+                        WHERE prediction_date < CURRENT_DATE - INTERVAL '%s days'
+                    """, (older_than_days,))
+                    deleted_count = cur.rowcount
+                    conn.commit()
+                    return deleted_count
+        except Exception as e:
+            print(f"Ошибка удаления старых прогнозов: {e}")
+            return 0