ERD 与 DefineSubset
当响应模型应该只暴露实体的部分字段时 — 例如,对外部 API 隐藏 owner_id — DefineSubset 让你可以选择特定字段,同时保持关系声明集中管理。
问题
ERD 实体通常包含不应该出现在 API 响应中的内部字段:
class TaskEntity(BaseModel, BaseEntity):
id: int
title: str
owner_id: int # 内部 FK,不应泄露到 API
sprint_id: int # 内部 FK,不应泄露到 API
internal_notes: str # 内部字段
你可以从头创建单独的响应模型,但这会重复字段定义并失去 ERD 关系连接。
基本用法
DefineSubset 创建一个仅包含你指定字段的新模型:
from typing import Annotated, Optional
from pydantic_resolve import DefineSubset
class TaskSummary(DefineSubset):
__subset__ = (TaskEntity, ('id', 'title'))
owner: Annotated[Optional[UserEntity], AutoLoad()] = None
这创建一个等价于以下的类:
class TaskSummary(BaseModel):
id: int # 继承自 TaskEntity
title: str # 继承自 TaskEntity
owner: Optional[UserEntity] = None # 你通过 AutoLoad 添加
owner_id FK 字段不是响应的一部分,但 AutoLoad 仍然知道如何解析关系,因为 ERD 元数据被保留了。
SubsetConfig 提供更多控制
对于高级情况,使用 SubsetConfig 而不是元组:
from pydantic_resolve import SubsetConfig
class TaskDetail(DefineSubset):
__subset__ = SubsetConfig(
kls=TaskEntity,
fields=['id', 'title', 'sprint_id'],
)
owner: Annotated[Optional[UserEntity], AutoLoad()] = None
sprint: Annotated[Optional[SprintEntity], AutoLoad()] = None
SubsetConfig 参数
| 参数 | 类型 | 描述 |
|---|---|---|
kls |
type[BaseModel] |
源实体类 |
fields |
list[str] \| "all" \| None |
要包含的字段(与 omit_fields 互斥) |
omit_fields |
list[str] \| None |
要排除的字段(与 fields 互斥) |
expose_as |
list[tuple[str, str]] \| None |
ExposeAs 的字段和别名对 |
send_to |
list[tuple[str, tuple[str, ...] \| str]] \| None |
SendTo 的字段和收集器目标对 |
excluded_fields |
list[str] \| None |
标记为 Field(exclude=True) 的字段 |
排除字段
包含除特定字段外的所有字段:
class TaskPublic(DefineSubset):
__subset__ = SubsetConfig(
kls=TaskEntity,
omit_fields=['internal_notes', 'audit_log'],
)
使用 expose_as 和 send_to
class TaskWithAnnotations(DefineSubset):
__subset__ = SubsetConfig(
kls=TaskEntity,
fields=['id', 'title', 'name'],
expose_as=[('name', 'task_name')],
send_to=[('id', 'task_ids')],
)
这等价于给字段添加注解:
class TaskWithAnnotations(BaseModel):
id: Annotated[int, SendTo('task_ids')]
title: str
name: Annotated[str, ExposeAs('task_name')]
DefineSubset vs 常规继承
两种方法都创建新模型,但用途不同:
| 特性 | DefineSubset |
常规继承 |
|---|---|---|
| 字段选择 | 显式列表或排除 | 继承所有字段 |
| FK 字段隐藏 | 自动 | 必须覆盖 |
| ERD 关系访问 | 通过元数据保留 | 必须显式 |
| 源验证 | 内置 | 无 |
常规继承(用于比较)
class TaskView(TaskEntity):
# TaskEntity 的所有字段都被继承,包括 owner_id
owner: Annotated[Optional[UserEntity], AutoLoad()] = None
DefineSubset(隐藏 FK 字段)
class TaskSummary(DefineSubset):
__subset__ = (TaskEntity, ('id', 'title'))
# owner_id 不是响应的一部分
owner: Annotated[Optional[UserEntity], AutoLoad()] = None
完整示例
from typing import Annotated, Optional
from pydantic import BaseModel
from pydantic_resolve import (
DefineSubset,
Relationship,
base_entity,
build_list,
build_object,
config_global_resolver,
)
USERS = {
7: {"id": 7, "name": "Ada"},
8: {"id": 8, "name": "Bob"},
}
TASKS = [
{"id": 10, "title": "Design docs", "sprint_id": 1, "owner_id": 7},
{"id": 11, "title": "Refine examples", "sprint_id": 1, "owner_id": 8},
]
async def user_loader(user_ids: list[int]):
users = [USERS.get(uid) for uid in user_ids]
return build_object(users, user_ids, lambda u: u.id)
async def task_loader(sprint_ids: list[int]):
tasks = [t for t in TASKS if t["sprint_id"] in sprint_ids]
return build_list(tasks, sprint_ids, lambda t: t["sprint_id"])
BaseEntity = base_entity()
class UserEntity(BaseModel, BaseEntity):
id: int
name: str
class TaskEntity(BaseModel, BaseEntity):
__relationships__ = [
Relationship(fk='owner_id', name='owner', target=UserEntity, loader=user_loader)
]
id: int
title: str
owner_id: int
sprint_id: int
class SprintEntity(BaseModel, BaseEntity):
__relationships__ = [
Relationship(fk='id', name='tasks', target=list[TaskEntity], loader=task_loader)
]
id: int
name: str
diagram = BaseEntity.get_diagram()
AutoLoad = diagram.create_auto_load()
config_global_resolver(diagram)
# --- Subsets 隐藏内部 FK 字段 ---
class UserSummary(DefineSubset):
__subset__ = (UserEntity, ('id', 'name'))
class TaskSummary(DefineSubset):
__subset__ = (TaskEntity, ('id', 'title'))
owner: Annotated[Optional[UserSummary], AutoLoad()] = None
class SprintSummary(DefineSubset):
__subset__ = (SprintEntity, ('id', 'name'))
tasks: Annotated[list[TaskSummary], AutoLoad()] = []
task_count: int = 0
def post_task_count(self):
return len(self.tasks)
# --- Resolve ---
raw_sprints = [{"id": 1, "name": "Sprint 24"}]
sprints = [SprintSummary.model_validate(s) for s in raw_sprints]
sprints = await Resolver().resolve(sprints)
print(sprints[0].model_dump())
# {'id': 1, 'name': 'Sprint 24',
# 'tasks': [
# {'id': 10, 'title': 'Design docs', 'owner': {'id': 7, 'name': 'Ada'}},
# {'id': 11, 'title': 'Refine examples', 'owner': {'id': 8, 'name': 'Bob'}},
# ],
# 'task_count': 2}
# 注意:输出中没有 owner_id 或 sprint_id
下一步
继续阅读 ORM 集成 了解如何从 SQLAlchemy、Django 或 Tortoise ORM 自动生成 loader。