feat: update barcode mappings and improve build script robustness

2026-03-25 20:49:24 +08:00
parent 76f7adddd5
commit 83405a9b8e
7 changed files with 261 additions and 51 deletions
@@ -108,3 +108,77 @@ class OrderService:
            logger.info("OrderService开始合并所有采购单")
        
        return self.order_merger.process(file_paths, progress_cb)
+
+    def validate_unit_price(self, result_path: str) -> List[str]:
+        """
+        校验采购单单价与商品资料进货价的差异
+        
+        Args:
+            result_path: 待校验的采购单路径
+            
+        Returns:
+            差异信息列表，无差异返回空列表
+        """
+        try:
+            import pandas as pd
+            import os
+            
+            def _read_df(path):
+                ap = os.path.abspath(path)
+                if ap.lower().endswith('.xlsx'):
+                    return pd.read_excel(ap, engine='openpyxl')
+                else:
+                    return pd.read_excel(ap, engine='xlrd')
+                    
+            item_path = os.path.join('templates', '商品资料.xlsx')
+            if not os.path.exists(item_path):
+                logger.warning(f"未找到商品资料文件: {item_path}")
+                return []
+                
+            df_item = _read_df(item_path)
+            df_res = _read_df(result_path)
+            
+            def _find_col(df, candidates, contains=None):
+                cols = list(df.columns)
+                for c in candidates:
+                    if c in cols:
+                        return c
+                if contains:
+                    for c in cols:
+                        if contains in str(c):
+                            return c
+                return None
+                
+            item_barcode_col = _find_col(df_item, ['商品条码','商品条码（小条码）','条码','barcode'], contains='条码')
+            item_price_col = _find_col(df_item, ['进货价','进货价（必填）'], contains='进货价')
+            res_barcode_col = _find_col(df_res, ['条码','barcode'], contains='条码')
+            res_price_col = _find_col(df_res, ['采购单价','unit_price','单价'], contains='单价')
+            
+            if not all([item_barcode_col, item_price_col, res_barcode_col, res_price_col]):
+                logger.warning("未能在文件和商品资料中找到完整的校验列（条码、单价）")
+                return []
+                
+            item_map = df_item[[item_barcode_col, item_price_col]].dropna()
+            item_map[item_price_col] = pd.to_numeric(item_map[item_price_col], errors='coerce')
+            item_map = item_map.dropna()
+            imap = dict(zip(item_map[item_barcode_col].astype(str).str.strip(), item_map[item_price_col]))
+            
+            df_res['_bc_'] = df_res[res_barcode_col].astype(str).str.strip()
+            df_res['_res_price_'] = pd.to_numeric(df_res[res_price_col], errors='coerce')
+            df_res['_item_price_'] = df_res['_bc_'].map(imap)
+            
+            df_check = df_res.dropna(subset=['_res_price_','_item_price_'])
+            df_check['_diff_'] = (df_check['_res_price_'] - df_check['_item_price_']).abs()
+            bad = df_check[df_check['_diff_'] > 1.0]
+            
+            results = []
+            if not bad.empty:
+                for i in range(len(bad)):
+                    r = bad.iloc[i]
+                    results.append(f"条码 {r['_bc_']}: 采购单价={r['_res_price_']} vs 进货价={r['_item_price_']} 差异={r['_diff_']:.2f}")
+                    
+            return results
+            
+        except Exception as e:
+            logger.error(f"单价校验过程中发生错误: {e}")
+            return []