# -*- coding: utf-8 -*- import json from redis.asyncio.client import Redis from app.common.enums import RedisInitKeyConfig from app.utils.excel_util import ExcelUtil from app.core.database import async_db_session from app.core.base_schema import BatchSetAvailable from app.core.redis_crud import RedisCURD from app.core.exceptions import CustomException from app.core.logger import log from app.api.v1.module_system.auth.schema import AuthSchema from .schema import ( DictDataCreateSchema, DictDataOutSchema, DictDataUpdateSchema, DictTypeCreateSchema, DictTypeOutSchema, DictTypeUpdateSchema, DictDataQueryParam, DictTypeQueryParam ) from .crud import DictDataCRUD, DictTypeCRUD class DictTypeService: """ 字典类型管理模块服务层 """ @classmethod async def get_obj_detail_service(cls, auth: AuthSchema, id: int) -> dict: """ 获取数据字典类型详情 参数: - auth (AuthSchema): 认证信息模型 - id (int): 数据字典类型ID 返回: - dict: 数据字典类型详情字典 """ obj = await DictTypeCRUD(auth).get_obj_by_id_crud(id=id) return DictTypeOutSchema.model_validate(obj).model_dump() @classmethod async def get_obj_list_service(cls, auth: AuthSchema, search: DictTypeQueryParam | None = None, order_by: list[dict] | None = None) -> list[dict]: """ 获取数据字典类型列表 参数: - auth (AuthSchema): 认证信息模型 - search (DictTypeQueryParam | None): 搜索条件模型 - order_by (list[dict] | None): 排序字段列表 返回: - list[dict]: 数据字典类型详情字典列表 """ obj_list = await DictTypeCRUD(auth).get_obj_list_crud(search=search.__dict__, order_by=order_by) return [DictTypeOutSchema.model_validate(obj).model_dump() for obj in obj_list] @classmethod async def create_obj_service(cls, auth: AuthSchema, redis: Redis, data: DictTypeCreateSchema) -> dict: """ 创建数据字典类型 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - data (DictTypeCreateSchema): 数据字典类型创建模型 返回: - dict: 数据字典类型详情字典 """ exist_obj = await DictTypeCRUD(auth).get(dict_name=data.dict_name) if exist_obj: raise CustomException(msg='创建失败，该数据字典类型已存在') obj = await DictTypeCRUD(auth).create_obj_crud(data=data) new_obj_dict = DictTypeOutSchema.model_validate(obj).model_dump() redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{data.dict_type}" try: await RedisCURD(redis).set( key=redis_key, value="", ) log.info(f"创建字典类型成功: {new_obj_dict}") except Exception as e: log.error(f"创建字典类型失败: {e}") raise CustomException(msg=f"创建字典类型失败 {e}") return new_obj_dict @classmethod async def update_obj_service(cls, auth: AuthSchema, redis: Redis, id:int, data: DictTypeUpdateSchema) -> dict: """ 更新数据字典类型 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - id (int): 数据字典类型ID - data (DictTypeUpdateSchema): 数据字典类型更新模型 返回: - dict: 数据字典类型详情字典 """ exist_obj = await DictTypeCRUD(auth).get_obj_by_id_crud(id=id) if not exist_obj: raise CustomException(msg='更新失败，该数据字典类型不存在') if exist_obj.dict_name != data.dict_name: raise CustomException(msg='更新失败，数据字典类型名称不可以修改') dict_data_list = [] # 如果字典类型修改或状态变更，则修改对应字典数据的类型和状态，并更新Redis缓存 if exist_obj.dict_type != data.dict_type or exist_obj.status != data.status: # 检查字典数据类型是否被修改 exist_obj_type_list = await DictDataCRUD(auth).list(search={'dict_type': exist_obj.dict_type}) if exist_obj_type_list: for item in exist_obj_type_list: item.dict_type = data.dict_type dict_data = DictDataUpdateSchema( dict_sort=item.dict_sort, dict_label=item.dict_label, dict_value=item.dict_value, dict_type=data.dict_type, dict_type_id=item.dict_type_id, css_class=item.css_class, list_class=item.list_class, is_default=item.is_default, status=data.status, description=item.description ) obj = await DictDataCRUD(auth).update_obj_crud(id=item.id, data=dict_data) dict_data_list.append(DictDataOutSchema.model_validate(obj).model_dump()) obj = await DictTypeCRUD(auth).update_obj_crud(id=id, data=data) new_obj_dict = DictTypeOutSchema.model_validate(obj).model_dump() redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{data.dict_type}" try: # 获取当前字典类型的所有字典数据，确保包含最新状态 dict_data_list = await DictDataCRUD(auth).get_obj_list_crud(search={'dict_type': data.dict_type}) dict_data = [DictDataOutSchema.model_validate(row).model_dump() for row in dict_data_list if row] value = json.dumps(dict_data, ensure_ascii=False) await RedisCURD(redis).set( key=redis_key, value=value, ) log.info(f"更新字典类型成功并刷新缓存: {new_obj_dict}") except Exception as e: log.error(f"更新字典类型缓存失败: {e}") raise CustomException(msg=f"更新字典类型缓存失败 {e}") return new_obj_dict @classmethod async def delete_obj_service(cls, auth: AuthSchema, redis: Redis, ids: list[int]) -> None: """ 删除数据字典类型 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - ids (list[int]): 数据字典类型ID列表 返回: - None """ if len(ids) < 1: raise CustomException(msg='删除失败，删除对象不能为空') for id in ids: exist_obj = await DictTypeCRUD(auth).get_obj_by_id_crud(id=id) if not exist_obj: raise CustomException(msg='删除失败，该数据字典类型不存在') # 检查是否有字典数据 exist_obj_type_list = await DictDataCRUD(auth).list(search={'dict_type': id}) if len(exist_obj_type_list) > 0: # 如果有字典数据，不能删除 raise CustomException(msg='删除失败，该数据字典类型下存在字典数据') # 删除Redis缓存 redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{exist_obj.dict_type}" try: await RedisCURD(redis).delete(redis_key) log.info(f"删除字典类型成功: {id}") except Exception as e: log.error(f"删除字典类型失败: {e}") raise CustomException(msg=f"删除字典类型失败") await DictTypeCRUD(auth).delete_obj_crud(ids=ids) @classmethod async def set_obj_available_service(cls, auth: AuthSchema, data: BatchSetAvailable) -> None: """ 设置数据字典类型状态 参数: - auth (AuthSchema): 认证信息模型 - data (BatchSetAvailable): 批量设置状态模型 返回: - None """ await DictTypeCRUD(auth).set_obj_available_crud(ids=data.ids, status=data.status) @classmethod async def export_obj_service(cls, data_list: list[dict]) -> bytes: """ 导出数据字典类型列表 参数: - data_list (list[dict]): 数据字典类型列表 返回: - bytes: Excel文件字节流 """ mapping_dict = { 'id': '编号', 'dict_name': '字典名称', 'dict_type': '字典类型', 'status': '状态', 'description': '备注', 'created_time': '创建时间', 'updated_time': '更新时间', 'created_id': '创建者ID', 'updated_id': '更新者ID', } # 复制数据并转换状态 data = data_list.copy() for item in data: # 处理状态 item['status'] = '启用' if item.get('status') == '0' else '停用' item['creator'] = item.get('creator', {}).get('name', '未知') if isinstance(item.get('creator'), dict) else '未知' return ExcelUtil.export_list2excel(list_data=data, mapping_dict=mapping_dict) class DictDataService: """ 字典数据管理模块服务层 """ @classmethod async def get_obj_detail_service(cls, auth: AuthSchema, id: int) -> dict: """ 获取数据字典数据详情 参数: - auth (AuthSchema): 认证信息模型 - id (int): 数据字典数据ID 返回: - dict: 数据字典数据详情字典 """ obj = await DictDataCRUD(auth).get_obj_by_id_crud(id=id) return DictDataOutSchema.model_validate(obj).model_dump() @classmethod async def get_obj_list_service(cls, auth: AuthSchema, search: DictDataQueryParam | None = None, order_by: list[dict] | None = None) -> list[dict]: """ 获取数据字典数据列表 参数: - auth (AuthSchema): 认证信息模型 - search (DictDataQueryParam | None): 搜索条件模型 - order_by (list[dict] | None): 排序字段列表 返回: - list[dict]: 数据字典数据详情字典列表 """ obj_list = await DictDataCRUD(auth).get_obj_list_crud(search=search.__dict__, order_by=order_by) return [DictDataOutSchema.model_validate(obj).model_dump() for obj in obj_list] @classmethod async def init_dict_service(cls, redis: Redis): """ 应用初始化: 获取所有字典类型对应的字典数据信息并缓存service 参数: - redis (Redis): Redis客户端 返回: - None """ try: async with async_db_session() as session: async with session.begin(): # 在初始化过程中，不需要检查数据权限 auth = AuthSchema(db=session, check_data_scope=False) obj_list = await DictTypeCRUD(auth).get_obj_list_crud() if not obj_list: log.warning("未找到任何字典类型数据") return success_count = 0 fail_count = 0 for obj in obj_list: dict_type = obj.dict_type try: dict_data_list = await DictDataCRUD(auth).get_obj_list_crud(search={'dict_type': dict_type}) dict_data = [DictDataOutSchema.model_validate(row).model_dump() for row in dict_data_list if row] # 保存到Redis并设置过期时间 redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{dict_type}" value = json.dumps(dict_data, ensure_ascii=False) await RedisCURD(redis).set( key=redis_key, value=value, ) success_count += 1 log.info(f"✅ 字典数据缓存成功: {dict_type}") except Exception as e: fail_count += 1 log.error(f"❌ 初始化字典数据失败 [{dict_type}]: {e}") # 继续处理其他字典类型，不中断整个初始化过程 log.info(f"字典数据初始化完成 - 成功: {success_count}, 失败: {fail_count}") except Exception as e: log.error(f"字典初始化过程发生错误: {e}") # 只在严重错误时抛出异常，允许单个字典加载失败 raise CustomException(msg=f"字典数据初始化失败: {str(e)}") @classmethod async def get_init_dict_service(cls, redis: Redis, dict_type: str)->list[dict]: """ 从缓存获取字典数据列表信息service 参数: - redis (Redis): Redis客户端 - dict_type (str): 字典类型 返回: - list[dict]: 字典数据列表 """ try: redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{dict_type}" obj_list_dict = await RedisCURD(redis).get(redis_key) # 确保返回数据正确序列化 if obj_list_dict: if isinstance(obj_list_dict, str): try: return json.loads(obj_list_dict) except json.JSONDecodeError: log.warning(f"字典数据反序列化失败，尝试重新初始化缓存: {dict_type}") elif isinstance(obj_list_dict, list): return obj_list_dict # 缓存不存在或格式错误时重新初始化 await cls.init_dict_service(redis) obj_list_dict = await RedisCURD(redis).get(redis_key) if not obj_list_dict: raise CustomException(msg="数据字典不存在") # 再次确保返回数据正确序列化 if isinstance(obj_list_dict, str): try: return json.loads(obj_list_dict) except json.JSONDecodeError: raise CustomException(msg="字典数据格式错误") return obj_list_dict except CustomException: raise except Exception as e: log.error(f"获取字典缓存失败: {str(e)}") raise CustomException(msg=f"获取字典数据失败: {str(e)}") @classmethod async def create_obj_service(cls, auth: AuthSchema, redis: Redis, data: DictDataCreateSchema) -> dict: """ 创建数据字典数据 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - data (DictDataCreateSchema): 数据字典数据创建模型 返回: - dict: 数据字典数据详情字典 """ exist_obj = await DictDataCRUD(auth).get(dict_label=data.dict_label) if exist_obj: raise CustomException(msg='创建失败，该字典数据已存在') obj = await DictDataCRUD(auth).create_obj_crud(data=data) redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{data.dict_type}" try: # 获取当前字典类型的所有字典数据 dict_data_list = await DictDataCRUD(auth).get_obj_list_crud(search={'dict_type': data.dict_type}) dict_data = [DictDataOutSchema.model_validate(row).model_dump() for row in dict_data_list if row] value = json.dumps(dict_data, ensure_ascii=False) await RedisCURD(redis).set( key=redis_key, value=value, ) log.info(f"创建字典数据写入缓存成功: {obj}") except Exception as e: log.error(f"创建字典数据写入缓存失败: {e}") raise CustomException(msg=f"创建字典数据失败 {e}") return DictDataOutSchema.model_validate(obj).model_dump() @classmethod async def update_obj_service(cls, auth: AuthSchema, redis: Redis, id:int, data: DictDataUpdateSchema) -> dict: """ 更新数据字典数据 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - id (int): 数据字典数据ID - data (DictDataUpdateSchema): 数据字典数据更新模型 返回: - Dict: 数据字典数据详情字典 """ exist_obj = await DictDataCRUD(auth).get_obj_by_id_crud(id=id) if not exist_obj: raise CustomException(msg='更新失败，该字典数据不存在') if exist_obj.id != id: raise CustomException(msg='更新失败，数据字典数据重复') # 如果字典类型变更，仅刷新旧类型缓存，不联动字典类型状态 if exist_obj.dict_type != data.dict_type: dict_type = await DictTypeCRUD(auth).get(dict_type=exist_obj.dict_type) if dict_type: redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{dict_type.dict_type}" try: dict_data_list = await DictDataCRUD(auth).get_obj_list_crud(search={'dict_type': dict_type.dict_type}) dict_data = [DictDataOutSchema.model_validate(row).model_dump() for row in dict_data_list if row] value = json.dumps(dict_data, ensure_ascii=False) await RedisCURD(redis).set( key=redis_key, value=value, ) except Exception as e: log.error(f"更新字典数据类型变更时刷新旧缓存失败: {e}") obj = await DictDataCRUD(auth).update_obj_crud(id=id, data=data) redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{data.dict_type}" try: # 获取当前字典类型的所有字典数据 dict_data_list = await DictDataCRUD(auth).get_obj_list_crud(search={'dict_type': data.dict_type}) dict_data = [DictDataOutSchema.model_validate(row).model_dump() for row in dict_data_list if row] value = json.dumps(dict_data, ensure_ascii=False) await RedisCURD(redis).set( key=redis_key, value=value, ) log.info(f"更新字典数据写入缓存成功: {obj}") except Exception as e: log.error(f"更新字典数据写入缓存失败: {e}") raise CustomException(msg=f"更新字典数据失败 {e}") return DictDataOutSchema.model_validate(obj).model_dump() @classmethod async def delete_obj_service(cls, auth: AuthSchema, redis: Redis, ids: list[int]) -> None: """ 删除数据字典数据 参数: - auth (AuthSchema): 认证信息模型 - redis (Redis): Redis客户端 - ids (list[int]): 数据字典数据ID列表 返回: - None """ try: if len(ids) < 1: raise CustomException(msg='删除失败，删除对象不能为空') # 首先检查是否包含系统默认数据 for id in ids: exist_obj = await DictDataCRUD(auth).get_obj_by_id_crud(id=id) if not exist_obj: raise CustomException(msg=f'{id} 删除失败，该字典数据不存在') # 系统默认字典数据不允许删除 if exist_obj.is_default: raise CustomException(msg=f'删除失败，ID为{id}的系统默认字典数据不允许删除') # 获取所有需要清除的缓存键 dict_types_to_clear = set() for id in ids: exist_obj = await DictDataCRUD(auth).get_obj_by_id_crud(id=id) if exist_obj: dict_types_to_clear.add(exist_obj.dict_type) # 执行删除操作 await DictDataCRUD(auth).delete_obj_crud(ids=ids) # 清除缓存 for dict_type in dict_types_to_clear: try: redis_key = f"{RedisInitKeyConfig.SYSTEM_DICT.key}:{dict_type}" await RedisCURD(redis).delete(redis_key) log.info(f"清除字典缓存成功: {dict_type}") except Exception as e: log.warning(f"清除字典缓存失败: {e}") # 缓存清除失败不影响删除操作 log.info(f"删除字典数据成功，ID列表: {ids}") except CustomException: raise except Exception as e: log.error(f"删除字典数据失败: {str(e)}") raise CustomException(msg=f"删除字典数据失败: {str(e)}") @classmethod async def set_obj_available_service(cls, auth: AuthSchema, data: BatchSetAvailable) -> None: """ 批量修改数据字典数据状态 参数: - auth (AuthSchema): 认证信息模型 - data (BatchSetAvailable): 批量修改数据字典数据状态负载模型 返回: - None """ await DictDataCRUD(auth).set_obj_available_crud(ids=data.ids, status=data.status) @classmethod async def export_obj_service(cls, data_list: list[dict]) -> bytes: """ 导出数据字典数据列表 参数: - data_list (list[dict]): 数据字典数据列表 返回: - bytes: Excel文件字节流 """ mapping_dict = { 'id': '编号', 'dict_sort': '字典排序', 'dict_label': '字典标签', 'dict_value': '字典键值', 'dict_type': '字典类型', 'css_class': '样式属性', 'list_class': '表格回显样式', 'is_default': '是否默认', 'status': '状态', 'description': '备注', 'created_time': '创建时间', 'updated_time': '更新时间', 'created_id': '创建者ID', 'updated_id': '更新者ID', } # 复制数据并转换状态 data = data_list.copy() for item in data: # 处理状态 item['status'] = '启用' if item.get('status') == '0' else '停用' # 处理是否默认 item['is_default'] = '是' if item.get('is_default') else '否' item['creator'] = item.get('creator', {}).get('name', '未知') if isinstance(item.get('creator'), dict) else '未知' return ExcelUtil.export_list2excel(list_data=data, mapping_dict=mapping_dict)