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| import pandas as pd | |
| import json | |
| def parse_excel_file(file_path): | |
| try: | |
| df = pd.read_excel(file_path, header=2) | |
| except Exception as e: | |
| raise ValueError(f"❌ خطا در خواندن فایل اکسل: {str(e)}") | |
| column_mapping = { | |
| "کد": ["کد فهرست بها", "کد"], | |
| "عنوان": ["عنوان", "شرح کالا", "نام کالا"], | |
| "تعداد": ["تعداد", "تعداد مورد نیاز"], | |
| "واحد": ["واحد", "واحد شمارش", "نوع واحد"] | |
| } | |
| resolved_columns = {} | |
| for key, options in column_mapping.items(): | |
| found = next((col for col in options if col in df.columns), None) | |
| if not found: | |
| raise ValueError(f"❌ ستون «{key}» در فایل پیدا نشد.") | |
| resolved_columns[key] = found | |
| materials = [] | |
| for _, row in df.iterrows(): | |
| try: | |
| quantity = float(row[resolved_columns["تعداد"]]) | |
| if pd.isna(quantity) or quantity <= 0: | |
| continue | |
| except: | |
| continue | |
| material = { | |
| "code": str(row[resolved_columns["کد"]]).strip(), | |
| "description": str(row[resolved_columns["عنوان"]]).strip(), | |
| "quantity": quantity, | |
| "unit": str(row[resolved_columns["واحد"]]).strip() | |
| } | |
| materials.append(material) | |
| return materials | |
| def save_to_json(data, output_path="material_db.json"): | |
| try: | |
| with open(output_path, "w", encoding="utf-8") as f: | |
| json.dump(data, f, indent=2, ensure_ascii=False) | |
| except Exception as e: | |
| raise ValueError(f"❌ خطا در ذخیره فایل JSON: {str(e)}") | |