| 
					
				 | 
			
			
				@@ -96,7 +96,7 @@ def process_month_data(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                     # 根据表格类型处理数据 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                     if table_type == 'country': 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        data = parse_country_table(driver, year, month) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+                        data = parse_page_country_data(driver, year, month) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                         df_country = pd.DataFrame(data) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                         db.bulk_insert( 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                             df_country, 
			 | 
		
	
	
		
			
				| 
					
				 | 
			
			
				@@ -109,7 +109,7 @@ def process_month_data(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                         found_count += 1 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                     else: 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                         data_type = 'export' if table_type == 'export_commodity' else 'import' 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-                        commodity_data[data_type] = parse_commodity_table(driver, data_type, year, month) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+                        commodity_data[data_type] = parse_page_commodity_data(driver, data_type, year, month) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                         found_count += 1 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                 except Exception as e: 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				                     log.info(f"表格处理失败: {e}") 
			 | 
		
	
	
		
			
				| 
					
				 | 
			
			
				@@ -119,7 +119,7 @@ def process_month_data(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-def parse_country_table(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+def parse_page_country_data(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     """解析目标页面的表格数据""" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     data = [] 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
	
		
			
				| 
					
				 | 
			
			
				@@ -221,7 +221,7 @@ def parse_country_table(driver, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-def parse_commodity_table(driver, data_type, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+def parse_page_commodity_data(driver, data_type, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     """解析商品表通用函数""" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     data = [] 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     try: 
			 | 
		
	
	
		
			
				| 
					
				 | 
			
			
				@@ -310,7 +310,8 @@ def merge_commodity_data(import_data, export_data, year, month): 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     merged_df['monthly_total'] = merged_df['monthly_total'].replace(0, np.nan) 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     merged_df['crossborder_year'] = year 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				-    merged_df['crossborder_year_month'] = f"{year}-{month:02d}" 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+    #不为空是填充传入年月,1.2月数据在上级已经构建好 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				+    merged_df['crossborder_year_month'] = merged_df['crossborder_year_month'].fillna(f"{year}-{month:02d}") 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     merged_df['prov_code'] = PROV_CODE 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				     merged_df['prov_name'] = PROV_NAME 
			 | 
		
	
		
			
				 | 
				 | 
			
			
				  
			 |