mirror of https://github.com/tiangolo/fastapi.git
🐛 Fix handling arbitrary types when using `arbitrary_types_allowed=True` (#14482)
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parent
71a17b5932
commit
42b250d14d
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@ -1,7 +1,7 @@
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import re
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import re
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import warnings
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import warnings
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from copy import copy, deepcopy
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from copy import copy, deepcopy
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from dataclasses import dataclass
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from dataclasses import dataclass, is_dataclass
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from enum import Enum
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from enum import Enum
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from typing import (
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from typing import (
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Any,
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Any,
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@ -18,7 +18,7 @@ from typing import (
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from fastapi._compat import may_v1, shared
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from fastapi._compat import may_v1, shared
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from fastapi.openapi.constants import REF_TEMPLATE
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from fastapi.openapi.constants import REF_TEMPLATE
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from fastapi.types import IncEx, ModelNameMap, UnionType
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from fastapi.types import IncEx, ModelNameMap, UnionType
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from pydantic import BaseModel, TypeAdapter, create_model
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from pydantic import BaseModel, ConfigDict, TypeAdapter, create_model
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from pydantic import PydanticSchemaGenerationError as PydanticSchemaGenerationError
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from pydantic import PydanticSchemaGenerationError as PydanticSchemaGenerationError
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from pydantic import PydanticUndefinedAnnotation as PydanticUndefinedAnnotation
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from pydantic import PydanticUndefinedAnnotation as PydanticUndefinedAnnotation
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from pydantic import ValidationError as ValidationError
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from pydantic import ValidationError as ValidationError
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@ -64,6 +64,7 @@ class ModelField:
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field_info: FieldInfo
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field_info: FieldInfo
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name: str
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name: str
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mode: Literal["validation", "serialization"] = "validation"
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mode: Literal["validation", "serialization"] = "validation"
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config: Union[ConfigDict, None] = None
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@property
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@property
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def alias(self) -> str:
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def alias(self) -> str:
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@ -94,8 +95,14 @@ class ModelField:
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warnings.simplefilter(
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warnings.simplefilter(
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"ignore", category=UnsupportedFieldAttributeWarning
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"ignore", category=UnsupportedFieldAttributeWarning
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)
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)
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annotated_args = (
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self.field_info.annotation,
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*self.field_info.metadata,
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self.field_info,
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)
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self._type_adapter: TypeAdapter[Any] = TypeAdapter(
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self._type_adapter: TypeAdapter[Any] = TypeAdapter(
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Annotated[self.field_info.annotation, self.field_info]
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Annotated[annotated_args],
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config=self.config,
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)
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)
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def get_default(self) -> Any:
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def get_default(self) -> Any:
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@ -412,10 +419,21 @@ def create_body_model(
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def get_model_fields(model: Type[BaseModel]) -> List[ModelField]:
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def get_model_fields(model: Type[BaseModel]) -> List[ModelField]:
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return [
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model_fields: List[ModelField] = []
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ModelField(field_info=field_info, name=name)
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for name, field_info in model.model_fields.items():
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for name, field_info in model.model_fields.items()
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type_ = field_info.annotation
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]
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if lenient_issubclass(type_, (BaseModel, dict)) or is_dataclass(type_):
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model_config = None
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else:
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model_config = model.model_config
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model_fields.append(
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ModelField(
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field_info=field_info,
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name=name,
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config=model_config,
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)
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)
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return model_fields
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# Duplicate of several schema functions from Pydantic v1 to make them compatible with
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# Duplicate of several schema functions from Pydantic v1 to make them compatible with
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@ -0,0 +1,141 @@
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from typing import List
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import pytest
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from fastapi import FastAPI
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from fastapi.testclient import TestClient
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from inline_snapshot import snapshot
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from typing_extensions import Annotated
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from .utils import needs_pydanticv2
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@pytest.fixture(name="client")
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def get_client():
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from pydantic import (
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BaseModel,
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ConfigDict,
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PlainSerializer,
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TypeAdapter,
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WithJsonSchema,
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)
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class FakeNumpyArray:
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def __init__(self):
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self.data = [1.0, 2.0, 3.0]
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FakeNumpyArrayPydantic = Annotated[
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FakeNumpyArray,
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WithJsonSchema(TypeAdapter(List[float]).json_schema()),
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PlainSerializer(lambda v: v.data),
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]
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class MyModel(BaseModel):
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model_config = ConfigDict(arbitrary_types_allowed=True)
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custom_field: FakeNumpyArrayPydantic
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app = FastAPI()
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@app.get("/")
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def test() -> MyModel:
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return MyModel(custom_field=FakeNumpyArray())
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client = TestClient(app)
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return client
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@needs_pydanticv2
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def test_get(client: TestClient):
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response = client.get("/")
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assert response.json() == {"custom_field": [1.0, 2.0, 3.0]}
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@needs_pydanticv2
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def test_typeadapter():
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# This test is only to confirm that Pydantic alone is working as expected
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from pydantic import (
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BaseModel,
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ConfigDict,
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PlainSerializer,
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TypeAdapter,
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WithJsonSchema,
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)
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class FakeNumpyArray:
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def __init__(self):
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self.data = [1.0, 2.0, 3.0]
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FakeNumpyArrayPydantic = Annotated[
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FakeNumpyArray,
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WithJsonSchema(TypeAdapter(List[float]).json_schema()),
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PlainSerializer(lambda v: v.data),
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]
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class MyModel(BaseModel):
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model_config = ConfigDict(arbitrary_types_allowed=True)
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custom_field: FakeNumpyArrayPydantic
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ta = TypeAdapter(MyModel)
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assert ta.dump_python(MyModel(custom_field=FakeNumpyArray())) == {
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"custom_field": [1.0, 2.0, 3.0]
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}
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assert ta.json_schema() == snapshot(
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{
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"properties": {
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"custom_field": {
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"items": {"type": "number"},
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"title": "Custom Field",
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"type": "array",
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}
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},
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"required": ["custom_field"],
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"title": "MyModel",
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"type": "object",
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}
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)
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@needs_pydanticv2
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def test_openapi_schema(client: TestClient):
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response = client.get("openapi.json")
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assert response.json() == snapshot(
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{
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"openapi": "3.1.0",
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"info": {"title": "FastAPI", "version": "0.1.0"},
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"paths": {
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"/": {
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"get": {
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"summary": "Test",
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"operationId": "test__get",
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"responses": {
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"200": {
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"description": "Successful Response",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/MyModel"
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}
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}
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},
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}
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},
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}
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}
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},
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"components": {
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"schemas": {
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"MyModel": {
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"properties": {
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"custom_field": {
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"items": {"type": "number"},
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"type": "array",
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"title": "Custom Field",
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}
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},
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"type": "object",
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"required": ["custom_field"],
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"title": "MyModel",
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}
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}
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},
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}
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)
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