feat: add material deletion confirmation with checkbox UI
- Add MaterialsToBeDeletedDAO for managing material deletion records by MaterialCode - Add MaterialValidationResult dataclass for enhanced validation results - Add CheckboxTreeview component with selectable checkbox functionality - Refactor material validation UI with new columns: select, material name, code, spec, model, manager - Add double-click to edit manager name functionality - Add select all/deselect all buttons - Add confirm deletion button to write selected records to database - Prioritize MaterialsToBeDeleted.ManagerName over type-based matching when displaying - Export results to Excel with selection state Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Misaka_Company
@@ -9,12 +9,28 @@
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import os
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import pandas as pd
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from typing import List, Dict, Any
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from typing import List, Dict, Any, Optional, Set
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from dataclasses import dataclass
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from utils.离散备料计划维护数据提取 import DiscreteMaterialPlanExtractor
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from db.materials_to_delete import get_all_materials_to_delete
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from db.production_contract_data_dao import ProductionContractDataDAO
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from db.discrete_material_plan_dao import DiscreteMaterialPlanDAO
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from db.materials_to_be_deleted_dao import MaterialsTypeToBeDeletedDAO
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from db.materials_to_be_deleted_records_dao import MaterialsToBeDeletedDAO
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# ==================== DATA STRUCTURES ====================
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@dataclass
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class MaterialValidationResult:
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"""Enhanced material validation result with complete record information"""
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material_name: str
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material_code: str
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specification: Optional[str] = None
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model: Optional[str] = None
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manager_name: Optional[str] = None
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is_marked_for_deletion: bool = False
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matched_type_keyword: Optional[str] = None # Matched keyword from MaterialsTypeToBeDeleted
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class MaterialStatusValidator:
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@@ -346,3 +362,162 @@ class MaterialStatusValidator:
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self._print(f" 未匹配: {len(results) - matched_count}")
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return output_file
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# ==================== ENHANCED VALIDATION METHODS ====================
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def match_materials_detailed(
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self,
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material_records: List[Dict[str, Any]],
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type_keywords: List[Dict[str, Any]],
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marked_codes_dict: Dict[str, str] # Changed: MaterialCode -> ManagerName mapping
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) -> List[MaterialValidationResult]:
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"""
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Match materials with detailed information.
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Args:
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material_records: Complete records from DiscreteMaterialPlanData
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type_keywords: Records from MaterialsTypeToBeDeleted (MaterialName matching)
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marked_codes_dict: MaterialCode -> ManagerName mapping from MaterialsToBeDeleted
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Returns:
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List of MaterialValidationResult objects
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"""
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results = []
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for record in material_records:
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material_name = record.get('MaterialName', '') or ''
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material_code = record.get('MaterialCode', '') or ''
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specification = record.get('Specification', '') or None
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model = record.get('Model', '') or None
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# Priority 1: Check MaterialsToBeDeleted (MaterialCode exact match)
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# This has highest priority - if MaterialCode exists, use its ManagerName
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manager_name = marked_codes_dict.get(material_code) if material_code else None
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is_marked = manager_name is not None
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matched_keyword = None
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# Priority 2: If not in MaterialsToBeDeleted, match with MaterialsTypeToBeDeleted
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# (MaterialName contains match)
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if not manager_name:
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for type_record in type_keywords:
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type_material_name = type_record.get('MaterialName', '')
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if type_material_name and type_material_name in material_name:
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matched_keyword = type_material_name
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manager_name = type_record.get('ManagerName')
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break
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result = MaterialValidationResult(
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material_name=material_name,
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material_code=material_code,
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specification=specification,
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model=model,
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manager_name=manager_name,
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is_marked_for_deletion=is_marked,
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matched_type_keyword=matched_keyword
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)
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results.append(result)
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return results
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def validate_from_database_enhanced(
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self,
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production_id_file: str = None,
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full_table: bool = False,
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output_file: str = None
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) -> tuple:
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"""
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Enhanced database validation with complete record information.
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Args:
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production_id_file: ProductionID.txt path (for filtered mode)
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full_table: Whether to query full table (for full table mode)
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output_file: Output Excel file path
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Returns:
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Tuple of (output_file_path, List[MaterialValidationResult])
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"""
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# Set default output path
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if output_file is None:
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output_file = "D:/python/playwrite/data/物料状态校验结果.xlsx"
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self._print("=" * 60)
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self._print("使用增强数据库校验（完整记录模式）...")
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# Get material records (complete records, not just MaterialName)
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if full_table:
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self._print("\n模式: 全表校验")
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self._print("[INFO] 查询 DiscreteMaterialPlanData 表中的所有完整记录...")
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dao = DiscreteMaterialPlanDAO()
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material_records = dao.query_all()
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self._print(f"[INFO] 获取到 {len(material_records)} 条记录")
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elif production_id_file:
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self._print("\n模式: ProductionID 过滤校验")
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self._print(f"[INFO] 读取 ProductionID 文件: {production_id_file}")
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# 1. Read ProductionID.txt
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production_ids = self._read_production_ids(production_id_file)
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self._print(f"[INFO] 读取到 {len(production_ids)} 个总排号")
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# 2. Query SourceNumbers
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source_numbers = self._get_source_numbers_from_production_ids(production_ids)
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# 3. Get complete material records
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self._print(f"[INFO] 查询 {len(source_numbers)} 个生产订单对应的完整物料记录...")
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dao = DiscreteMaterialPlanDAO()
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material_records = dao.query_by_source_numbers(source_numbers)
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self._print(f"[INFO] 获取到 {len(material_records)} 条记录")
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else:
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raise ValueError("必须指定 full_table=True 或提供 production_id_file 参数")
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# Get type keywords from MaterialsTypeToBeDeleted
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self._print("\n从数据库获取待删除物料类型...")
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type_dao = MaterialsTypeToBeDeletedDAO()
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type_keywords = type_dao.get_all_materials()
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self._print(f"获取到 {len(type_keywords)} 条物料类型记录")
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# Get marked material codes and manager names from MaterialsToBeDeleted
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self._print("从数据库获取已标记删除的物料记录...")
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record_dao = MaterialsToBeDeletedDAO()
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marked_records = record_dao.get_all_records()
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# Build dictionary: MaterialCode -> ManagerName
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marked_codes_dict = {
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r['MaterialCode']: r['ManagerName']
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for r in marked_records
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if r.get('MaterialCode') and r.get('ManagerName')
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}
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self._print(f"获取到 {len(marked_codes_dict)} 个已标记的物料代码")
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# Match materials
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self._print("\n匹配物料...")
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results = self.match_materials_detailed(material_records, type_keywords, marked_codes_dict)
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# Output to Excel
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self._print("\n输出结果...")
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# Convert to DataFrame for Excel export
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df_data = []
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for r in results:
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df_data.append({
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"材料名称": r.material_name,
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"材料代码": r.material_code,
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"规格": r.specification or '',
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"型号": r.model or '',
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"负责人": r.manager_name or '',
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"已标记删除": "是" if r.is_marked_for_deletion else "否",
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"匹配的关键词": r.matched_type_keyword or ''
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})
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result_df = pd.DataFrame(df_data)
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result_df.to_excel(output_file, index=False)
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self._print(f"结果已保存: {output_file}")
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# Print statistics
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marked_count = sum(1 for r in results if r.is_marked_for_deletion)
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matched_count = sum(1 for r in results if r.manager_name)
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self._print(f"\n统计信息:")
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self._print(f" 总记录数: {len(results)}")
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self._print(f" 匹配到负责人: {matched_count}")
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self._print(f" 已标记删除: {marked_count}")
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return output_file, results
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