feat: add database-driven material validation with multi-mode support

This commit enhances the material validation functionality to support
database-driven workflows alongside the existing Excel-based approach.

## New Features

### DAO Layer
- Add ProductionContractDataDAO for querying production contract data
- Add MaterialsToBeDeletedDAO with full CRUD operations
- Enhance DiscreteMaterialPlanDAO with query_all(), query_by_source_numbers(),
  and get_unique_material_names() methods

### Validation Modes
Support for 4 validation modes in MaterialValidationTab:
1. Database Full - Query all materials from DiscreteMaterialPlanData
2. Database Filtered - Query by ProductionID.txt file
3. Excel Existing - Validate from existing Excel file
4. Excel Full - Complete workflow with ERP extraction

### Configuration
- Add ValidationConfig dataclass with data_source, batch_size, match_mode,
  enable_crud_operations, and default_manager fields
- Update ConfigLoader to support validation configuration
- Add validation settings section in SettingsTab GUI

### Query Chain
Implementation of full query chain:
ProductionID.txt (总排号) → productionContractData (生产订单号) →
DiscreteMaterialPlanData (SourceNumber) → MaterialName →
MaterialsToBeDeleted comparison

## Backward Compatibility
All existing Excel-based validation methods remain unchanged, ensuring
no breaking changes for existing workflows.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

config/schema.py

@@ -97,6 +97,48 @@ class ExtractionConfig:
         return errors
 
 
+@dataclass
+class ValidationConfig:
+    """物料校验配置"""
+
+    data_source: str = "database_full"
+    use_database: bool = True
+    batch_size: int = 2000
+    enable_crud_operations: bool = False
+    default_manager: str = ""
+    match_mode: str = "substring"
+
+    def validate(self) -> list[str]:
+        """验证配置，返回错误列表"""
+        errors = []
+
+        valid_sources = [
+            "database_full",
+            "database_filtered",
+            "excel_existing",
+            "excel_full"
+        ]
+        if self.data_source not in valid_sources:
+            errors.append(
+                f"无效的数据源: {self.data_source}。"
+                f"有效选项: {', '.join(valid_sources)}"
+            )
+
+        if self.batch_size <= 0:
+            errors.append("批次大小必须大于 0")
+        if self.batch_size > 2000:
+            errors.append("批次大小不应超过 2000（SQL Server 参数限制）")
+
+        valid_match_modes = ["substring", "exact"]
+        if self.match_mode not in valid_match_modes:
+            errors.append(
+                f"无效的匹配模式: {self.match_mode}。"
+                f"有效选项: {', '.join(valid_match_modes)}"
+            )
+
+        return errors
+
+
 @dataclass
 class AppConfig:
     """应用总配置"""
@@ -105,6 +147,7 @@ class AppConfig:
     database: DatabaseConfig
     paths: PathConfig
     extraction: ExtractionConfig
+    validation: ValidationConfig
 
     def validate(self) -> list[str]:
         """验证所有配置，返回错误列表"""
@@ -113,6 +156,7 @@ class AppConfig:
         errors.extend(self.database.validate())
         errors.extend(self.paths.validate())
         errors.extend(self.extraction.validate())
+        errors.extend(self.validation.validate())
         return errors
 
     def to_dict(self) -> dict:
@@ -147,4 +191,12 @@ class AppConfig:
                 "merge_batches": self.extraction.merge_batches,
                 "enable_db_persistence": self.extraction.enable_db_persistence,
             },
+            "validation": {
+                "data_source": self.validation.data_source,
+                "use_database": self.validation.use_database,
+                "batch_size": self.validation.batch_size,
+                "enable_crud_operations": self.validation.enable_crud_operations,
+                "default_manager": self.validation.default_manager,
+                "match_mode": self.validation.match_mode,
+            },
         }