如何使用数据类在 Pydantic 中构建自引用模型？

Question

我正在使用 FastAPI 和 pydantic 构建一个 API。

由于我遵循 DDD / clean 架构，它将模型的定义与持久层的定义分开，我在我的模型中使用标准库数据classes，然后使用将它们映射到 SQLAlchemy 表命令式映射（即 classical 映射）。

这非常有效：

@dataclass
class User:
    name: str
    age: int

@pydantic.dataclasses.dataclass
class PydanticUser(User):
     ...

但是，我在使用自引用定义 class 时遇到了问题。

✅ class 继承自 Pydantic 的 BaseModel 可以自引用

继承 pydantic 的 BaseModel 是可行的，但是 this is not compatible 使用 SQLAlchemy 命令式映射，我想用它来坚持干净的架构/DDD 原则。

class BaseModelPerson(BaseModel):
     name: str
     age: int
     parent_person: BaseModelPerson = None

BaseModelPerson.update_forward_refs()
john = BaseModelPerson(name="John", age=49, parent_person=None)
tim = BaseModelPerson(name="Tim", age=14, parent_person=john)

print(john)
# BaseModelPerson(name='John', age=49, parent_person=None)
print(tim)
# BaseModelPerson(name='Tim', age=14, parent_person=BaseModelPerson(name='John', age=49, parent_person=None))

✅ 标准库数据classes也可以自引用

from __future__ import annotations
from dataclasses import dataclass

@dataclass
class StdlibPerson:
    name: str
    age: int
    parent: StdlibPerson


john = StdlibPerson(name="John", age=49, parent=None)
tim = StdlibPerson(name="Tim", age=14, parent=john)

print(john)
# StdlibPerson(name='John', age=49, parent=None)

print(tim)
# StdlibPerson(name='Tim', age=14, parent=StdlibPerson(name='John', age=49, parent=None))

❌ Pydantic 数据class 转换导致递归错误

当我尝试将标准库数据class 转换为 pydantic 数据class 时出现问题。

像这样定义 Pydantic 数据class：

PydanticPerson = pydantic.dataclasses.dataclass(StdlibPerson)

returns一个错误：

# output (hundreds of lines - that is recursive indeed)

    # The name of an attribute on the class where we store the Field
  File "pydantic/main.py", line 990, in pydantic.main.create_model
  File "pydantic/main.py", line 299, in pydantic.main.ModelMetaclass.__new__
  File "pydantic/fields.py", line 411, in pydantic.fields.ModelField.infer
  File "pydantic/fields.py", line 342, in pydantic.fields.ModelField.__init__
  File "pydantic/fields.py", line 456, in pydantic.fields.ModelField.prepare
  File "pydantic/fields.py", line 673, in pydantic.fields.ModelField.populate_validators
  File "pydantic/class_validators.py", line 255, in pydantic.class_validators.prep_validators
  File "pydantic/class_validators.py", line 238, in pydantic.class_validators.make_generic_validator
  File "/usr/lib/python3.9/inspect.py", line 3111, in signature
    return Signature.from_callable(obj, follow_wrapped=follow_wrapped)
  File "/usr/lib/python3.9/inspect.py", line 2860, in from_callable
    return _signature_from_callable(obj, sigcls=cls,
  File "/usr/lib/python3.9/inspect.py", line 2323, in _signature_from_callable
    return _signature_from_function(sigcls, obj,
  File "/usr/lib/python3.9/inspect.py", line 2155, in _signature_from_function
    if _signature_is_functionlike(func):
  File "/usr/lib/python3.9/inspect.py", line 1883, in _signature_is_functionlike
    if not callable(obj) or isclass(obj):
  File "/usr/lib/python3.9/inspect.py", line 79, in isclass
    return isinstance(object, type)
RecursionError: maximum recursion depth exceeded while calling a Python object

这样定义 StdlibPerson 并不能解决问题：

@dataclass
class StdlibPerson
    name: str
    age: int
    parent: "Person" = None

也不使用 pydantic 文档提供的第二种方式：

@pydantic.dataclasses.dataclass
class PydanticPerson(StdlibPerson)
    ...

❌直接使用 Pydantic 数据classes

from __future__ import annotations
from pydantic.dataclasses import dataclass
from typing import Optional

@pydantic.dataclasses.dataclass
class PydanticDataclassPerson:
     name: str
     age: int
     parent: Optional[PydanticDataclassPerson] = None

john = PydanticDataclassPerson(name="John", age=49, parent=None)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<string>", line 6, in __init__
  File "pydantic/dataclasses.py", line 97, in pydantic.dataclasses._generate_pydantic_post_init._pydantic_post_init
    # | False |       |       |
  File "pydantic/main.py", line 1040, in pydantic.main.validate_model
  File "pydantic/fields.py", line 699, in pydantic.fields.ModelField.validate
pydantic.errors.ConfigError: field "parent" not yet prepared so type is still a ForwardRef, you might need to call PydanticDataclassPerson.update_forward_refs().

>>> PydanticDataclassPerson.update_forward_refs()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: type object 'PydanticDataclassPerson' has no attribute 'update_forward_refs'

问题

我如何定义一个带有自引用对象的 pydantic 模型，以便它与 SQLAlchemy 命令式映射兼容？

Answer 1

似乎没有简单的解决方案来构建具有 FastAPI 和 self-referencing 对象的 REST API。

我决定切换到 FastAPI / GraphQL 堆栈，Strawberry library which is explicitly recommended in the FastAPI documentation。

到目前为止没问题，Strawberry 可以轻松构建 GraphQL 服务器，并且可以轻而易举地处理 self-referencing 对象。

#!/usr/bin/env python3.10
# src/my_app/entrypoints/api/schema.py

import typing
import strawberry

@strawberry.type
class Person:
    name: str
    age: int
    parent: Person | None

如何使用数据类在 Pydantic 中构建自引用模型？

How to build a self-referencing model in Pydantic with dataclasses?

python

pydantic

✅ class 继承自 Pydantic 的 BaseModel 可以自引用

✅ 标准库数据classes也可以自引用

❌ Pydantic 数据class 转换导致递归错误

❌直接使用 Pydantic 数据classes

问题