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FastapiAdmin/backend/app/api/v1/module_system/dict/service.py
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zhangtao 1d54dca76c style: 统一代码格式和字符串引号使用
refactor: 优化代码结构和可读性

feat: 添加http_limit模块实现请求限制功能

fix: 修复异步任务中使用time.sleep的问题

chore: 更新依赖项并添加pytest测试框架

docs: 更新项目描述信息

perf: 优化Redis序列化方式使用JSON替代pickle

test: 添加测试相关配置和依赖
2026-01-17 20:07:25 +08:00

655 lines
24 KiB
Python

import json
from redis.asyncio.client import Redis
from app.api.v1.module_system.auth.schema import AuthSchema
from app.common.enums import RedisInitKeyConfig
from app.core.base_schema import BatchSetAvailable
from app.core.database import async_db_session
from app.core.exceptions import CustomException
from app.core.logger import log
from app.core.redis_crud import RedisCURD
from app.utils.excel_util import ExcelUtil
from .crud import DictDataCRUD, DictTypeCRUD
from .schema import (
DictDataCreateSchema,
DictDataOutSchema,
DictDataQueryParam,
DictDataUpdateSchema,
DictTypeCreateSchema,
DictTypeOutSchema,
DictTypeQueryParam,
DictTypeUpdateSchema,
)
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="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) -> None:
"""
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
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,
)
except Exception as e:
log.error(f"❌ 初始化字典数据失败 [{dict_type}]: {e}")
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: {e!s}")
@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: {e!s}")
raise CustomException(msg=f"获取字典数据失败: {e!s}")
@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
"""
# 检查相同字典类型下dict_label是否已存在
exist_label_obj = await DictDataCRUD(auth).get(
dict_type=data.dict_type, dict_label=data.dict_label
)
if exist_label_obj:
raise CustomException(msg=f'创建失败,该字典类型下的字典标签"{data.dict_label}"已存在')
# 检查相同字典类型下dict_value是否已存在
exist_value_obj = await DictDataCRUD(auth).get(
dict_type=data.dict_type, dict_value=data.dict_value
)
if exist_value_obj:
raise CustomException(msg=f'创建失败,该字典类型下的字典键值"{data.dict_value}"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")
# 检查相同字典类型下dict_label是否已存在(排除当前记录)
if exist_obj.dict_label != data.dict_label:
exist_label_obj = await DictDataCRUD(auth).get(
dict_type=data.dict_type, dict_label=data.dict_label
)
if exist_label_obj:
raise CustomException(
msg=f'更新失败,该字典类型下的字典标签"{data.dict_label}"已存在'
)
# 检查相同字典类型下dict_value是否已存在(排除当前记录)
if exist_obj.dict_value != data.dict_value:
exist_value_obj = await DictDataCRUD(auth).get(
dict_type=data.dict_type, dict_value=data.dict_value
)
if exist_value_obj:
raise CustomException(
msg=f'更新失败,该字典类型下的字典键值"{data.dict_value}"已存在'
)
# 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: {e!s}")
raise CustomException(msg=f"删除字典数据失败: {e!s}")
@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)