update config and wildberries_client

config.py

@@ -71,14 +71,14 @@ class Config:
         return self.wildberries_api_token is not None and len(self.wildberries_api_token) > 0
     
     def get_endpoints(self) -> Dict[str, str]:
-        """Get API endpoint configurations based on official documentation"""
+        """Get API endpoint configurations based on working API calls"""
         return {
-            # Statistics API endpoints
-            "sales": f"{self.wildberries_base_url}/api/v1/supplier/sales",
-            "orders": f"{self.wildberries_base_url}/api/v1/supplier/orders", 
-            "stocks": f"{self.wildberries_base_url}/api/v1/supplier/stocks",
-            "incomes": f"{self.wildberries_base_url}/api/v1/supplier/incomes",
-            "reportDetailByPeriod": f"{self.wildberries_base_url}/api/v1/supplier/reportDetailByPeriod",
+            # Statistics API endpoints - Updated to working v5 version
+            "sales": f"{self.wildberries_base_url}/api/v5/supplier/reportDetailByPeriod",
+            "orders": f"{self.wildberries_base_url}/api/v5/supplier/reportDetailByPeriod", 
+            "stocks": f"{self.wildberries_base_url}/api/v5/supplier/reportDetailByPeriod",
+            "incomes": f"{self.wildberries_base_url}/api/v5/supplier/reportDetailByPeriod",
+            "reportDetailByPeriod": f"{self.wildberries_base_url}/api/v5/supplier/reportDetailByPeriod",
             
             # Analytics API endpoints
             "analytics": f"{self.wildberries_analytics_url}/api/v2/nm-report/detail",

wildberries_client.py

@@ -153,18 +153,24 @@ class WildberriesAPI:
         try:
             response = self._make_request("GET", endpoint, params=params)
             
-            if not response or "data" not in response:
+            if not response:
                 logger.warning("No sales data returned from API")
                 return pd.DataFrame()
             
-            # Convert to DataFrame
-            sales_data = pd.DataFrame(response["data"])
+            # Handle direct array response (v5 API format)
+            if isinstance(response, list):
+                sales_data = pd.DataFrame(response)
+            elif isinstance(response, dict) and "data" in response:
+                sales_data = pd.DataFrame(response["data"])
+            else:
+                logger.warning("Unexpected API response format")
+                return pd.DataFrame()
             
             if sales_data.empty:
                 return sales_data
             
             # Process and clean the data
-            sales_data = self._process_sales_data(sales_data)
+            sales_data = self._process_reportdetail_data(sales_data)
             
             return sales_data
             
@@ -187,23 +193,29 @@ class WildberriesAPI:
         if not date_from:
             date_from = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")
         
-        params = {"dateFrom": date_from}
+        params = {"dateFrom": date_from, "limit": 100}
         
         try:
             response = self._make_request("GET", endpoint, params=params)
             
-            if not response or "data" not in response:
+            if not response:
                 logger.warning("No stock data returned from API")
                 return pd.DataFrame()
             
-            # Convert to DataFrame
-            stock_data = pd.DataFrame(response["data"])
+            # Handle direct array response (v5 API format)
+            if isinstance(response, list):
+                stock_data = pd.DataFrame(response)
+            elif isinstance(response, dict) and "data" in response:
+                stock_data = pd.DataFrame(response["data"])
+            else:
+                logger.warning("Unexpected API response format")
+                return pd.DataFrame()
             
             if stock_data.empty:
                 return stock_data
             
             # Process and clean the data
-            stock_data = self._process_stock_data(stock_data)
+            stock_data = self._process_reportdetail_data(stock_data)
             
             return stock_data
             
@@ -224,25 +236,31 @@ class WildberriesAPI:
         """
         endpoint = self.config.get_endpoints()["orders"]
         
-        params = {"dateFrom": date_from}
+        params = {"dateFrom": date_from, "limit": 100}
         if date_to:
             params["dateTo"] = date_to
         
         try:
             response = self._make_request("GET", endpoint, params=params)
             
-            if not response or "data" not in response:
+            if not response:
                 logger.warning("No orders data returned from API")
                 return pd.DataFrame()
             
-            # Convert to DataFrame
-            orders_data = pd.DataFrame(response["data"])
+            # Handle direct array response (v5 API format)
+            if isinstance(response, list):
+                orders_data = pd.DataFrame(response)
+            elif isinstance(response, dict) and "data" in response:
+                orders_data = pd.DataFrame(response["data"])
+            else:
+                logger.warning("Unexpected API response format")
+                return pd.DataFrame()
             
             if orders_data.empty:
                 return orders_data
             
             # Process and clean the data
-            orders_data = self._process_orders_data(orders_data)
+            orders_data = self._process_reportdetail_data(orders_data)
             
             return orders_data
             
@@ -362,13 +380,126 @@ class WildberriesAPI:
         
         return df
     
-    def _process_orders_data(self, df: pd.DataFrame) -> pd.DataFrame:
-        """Process and clean orders data from API response"""
+    def _process_reportdetail_data(self, df: pd.DataFrame) -> pd.DataFrame:
+        """Process and clean reportDetailByPeriod data from API response (v5)"""
+        
+        # Column mapping based on actual API response structure
+        column_mapping = {
+            'realizationreport_id': 'report_id',
+            'date_from': 'date_from',
+            'date_to': 'date_to',
+            'create_dt': 'create_date',
+            'currency_name': 'currency',
+            'suppliercontract_code': 'contract_code',
+            'rrd_id': 'record_id',
+            'gi_id': 'goods_id',
+            'subject_name': 'category',
+            'nm_id': 'product_id',
+            'brand_name': 'brand',
+            'sa_name': 'supplier_article',
+            'ts_name': 'tech_size',
+            'barcode': 'barcode',
+            'doc_type_name': 'document_type',
+            'quantity': 'quantity',
+            'retail_price': 'retail_price',
+            'retail_amount': 'retail_amount',
+            'sale_percent': 'sale_percent',
+            'commission_percent': 'commission_percent',
+            'office_name': 'office_name',
+            'supplier_oper_name': 'operation_name',
+            'order_dt': 'order_date',
+            'sale_dt': 'sale_date',
+            'rr_dt': 'report_date',
+            'shk_id': 'warehouse_code',
+            'retail_price_withdisc_rub': 'discounted_price',
+            'delivery_amount': 'delivery_amount',
+            'return_amount': 'return_amount',
+            'delivery_rub': 'delivery_cost',
+            'gi_box_type_name': 'box_type',
+            'product_discount_for_report': 'product_discount',
+            'supplier_promo': 'supplier_promo',
+            'rid': 'rid',
+            'ppvz_spp_prc': 'spp_percent',
+            'ppvz_kvw_prc_base': 'kvw_percent_base',
+            'ppvz_kvw_prc': 'kvw_percent',
+            'sup_rating_prc_up': 'rating_bonus',
+            'is_kgvp_v2': 'is_kgvp',
+            'ppvz_sales_commission': 'sales_commission',
+            'ppvz_for_pay': 'amount_for_pay',
+            'ppvz_reward': 'reward',
+            'acquiring_fee': 'acquiring_fee',
+            'acquiring_percent': 'acquiring_percent',
+            'payment_processing': 'payment_processing',
+            'acquiring_bank': 'acquiring_bank',
+            'ppvz_vw': 'warehouse_cost',
+            'ppvz_vw_nds': 'warehouse_cost_vat',
+            'ppvz_office_name': 'pickup_office',
+            'ppvz_office_id': 'pickup_office_id',
+            'ppvz_supplier_id': 'supplier_id',
+            'ppvz_supplier_name': 'supplier_name',
+            'ppvz_inn': 'supplier_inn',
+            'declaration_number': 'declaration_number',
+            'sticker_id': 'sticker_id',
+            'site_country': 'site_country',
+            'penalty': 'penalty',
+            'additional_payment': 'additional_payment',
+            'rebill_logistic_cost': 'logistics_cost',
+            'rebill_logistic_org': 'logistics_company',
+            'storage_fee': 'storage_fee',
+            'deduction': 'deduction',
+            'acceptance': 'acceptance',
+            'assembly_id': 'assembly_id',
+            'srid': 'unique_id',
+            'report_type': 'report_type'
+        }
+        
+        # Rename columns that exist
+        for old_name, new_name in column_mapping.items():
+            if old_name in df.columns:
+                df = df.rename(columns={old_name: new_name})
+        
+        # Convert date columns
+        date_columns = ['create_date', 'order_date', 'sale_date', 'report_date']
+        for col in date_columns:
+            if col in df.columns:
+                df[col] = pd.to_datetime(df[col], errors='coerce')
+        
+        # Convert numeric columns
+        numeric_columns = [
+            'quantity', 'retail_price', 'retail_amount', 'sale_percent', 'commission_percent',
+            'discounted_price', 'delivery_amount', 'return_amount', 'delivery_cost',
+            'product_discount', 'supplier_promo', 'spp_percent', 'kvw_percent_base',
+            'kvw_percent', 'rating_bonus', 'sales_commission', 'amount_for_pay',
+            'reward', 'acquiring_fee', 'acquiring_percent', 'warehouse_cost',
+            'warehouse_cost_vat', 'penalty', 'additional_payment', 'logistics_cost',
+            'storage_fee', 'deduction', 'acceptance'
+        ]
+        
+        for col in numeric_columns:
+            if col in df.columns:
+                df[col] = pd.to_numeric(df[col], errors='coerce')
+        
+        # Add product name (use supplier_article if available)
+        if 'product_name' not in df.columns:
+            if 'supplier_article' in df.columns:
+                df['product_name'] = df['supplier_article']
+            elif 'category' in df.columns:
+                df['product_name'] = df['category']
+            else:
+                df['product_name'] = 'Unknown Product'
+        
+        # Filter out non-sales records (keep only actual sales)
+        if 'operation_name' in df.columns:
+            # Keep records that are actual sales or returns
+            df = df[~df['operation_name'].str.contains('Возмещение', na=False)]
         
-        # Similar processing to sales data
-        # This would be implemented based on the specific orders API response format
         return df
     
+    def _process_orders_data(self, df: pd.DataFrame) -> pd.DataFrame:
+        """Process and clean orders data from API response (legacy method)"""
+        # This is now handled by _process_reportdetail_data
+        return self._process_reportdetail_data(df)
+    
     def test_connection(self) -> Dict[str, Any]:
         """Test API connection and return status"""
         try:
@@ -464,7 +595,7 @@ class WildberriesAPI:
                 "message": f"Failed to fetch seller info: {str(e)}"
             }
     
-    def get_news(self, from_date: str = None, from_id: int = None, limit: int = 100) -> Dict[str, Any]:
+    def get_news(self, from_date: str = None, from_id: int = None, limit: int = 500) -> Dict[str, Any]:
         """
         Get seller portal news