Usage Errors

Pydantic attempts to provide useful errors. The following sections provide details on common errors developers may encounter when working with Pydantic, along with suggestions for addressing the error condition.

Class not fully defined¶

This error is raised when a type referenced in an annotation of a pydantic-validated type (such as a subclass of BaseModel, or a pydantic dataclass) is not defined:

from typing import ForwardRef

from pydantic import BaseModel, PydanticUserError

UndefinedType = ForwardRef('UndefinedType')


class Foobar(BaseModel):
    a: UndefinedType


try:
    Foobar(a=1)
except PydanticUserError as exc_info:
    assert exc_info.code == 'class-not-fully-defined'

Or when the type has been defined after usage:

from typing import Optional

from pydantic import BaseModel, PydanticUserError


class Foo(BaseModel):
    a: Optional['Bar'] = None


try:
    # this doesn't work, see raised error
    foo = Foo(a={'b': {'a': None}})
except PydanticUserError as exc_info:
    assert exc_info.code == 'class-not-fully-defined'


class Bar(BaseModel):
    b: 'Foo'


# this works, though
foo = Foo(a={'b': {'a': None}})

For BaseModel subclasses, it can be fixed by defining the type and then calling .model_rebuild():

from typing import Optional

from pydantic import BaseModel


class Foo(BaseModel):
    a: Optional['Bar'] = None


class Bar(BaseModel):
    b: 'Foo'


Foo.model_rebuild()

foo = Foo(a={'b': {'a': None}})

In other cases, the error message should indicate how to rebuild the class with the appropriate type defined.

Custom JSON Schema¶

The __modify_schema__ method is no longer supported in V2. You should use the __get_pydantic_json_schema__ method instead.

The __modify_schema__ used to receive a single argument representing the JSON schema. See the example below:

Old way

from pydantic import BaseModel, PydanticUserError

try:

    class Model(BaseModel):
        @classmethod
        def __modify_schema__(cls, field_schema):
            field_schema.update(examples=['example'])

except PydanticUserError as exc_info:
    assert exc_info.code == 'custom-json-schema'

The new method __get_pydantic_json_schema__ receives two arguments: the first is a dictionary denoted as CoreSchema, and the second a callable handler that receives a CoreSchema as parameter, and returns a JSON schema. See the example below:

Python 3.8 and abovePython 3.9 and above

New way

from typing import Any, Dict

from pydantic_core import CoreSchema

from pydantic import BaseModel, GetJsonSchemaHandler


class Model(BaseModel):
    @classmethod
    def __get_pydantic_json_schema__(
        cls, core_schema: CoreSchema, handler: GetJsonSchemaHandler
    ) -> Dict[str, Any]:
        json_schema = super().__get_pydantic_json_schema__(core_schema, handler)
        json_schema = handler.resolve_ref_schema(json_schema)
        json_schema.update(examples=['example'])
        return json_schema


print(Model.model_json_schema())
"""
{'examples': ['example'], 'properties': {}, 'title': 'Model', 'type': 'object'}
"""

New way

from typing import Any

from pydantic_core import CoreSchema

from pydantic import BaseModel, GetJsonSchemaHandler


class Model(BaseModel):
    @classmethod
    def __get_pydantic_json_schema__(
        cls, core_schema: CoreSchema, handler: GetJsonSchemaHandler
    ) -> dict[str, Any]:
        json_schema = super().__get_pydantic_json_schema__(core_schema, handler)
        json_schema = handler.resolve_ref_schema(json_schema)
        json_schema.update(examples=['example'])
        return json_schema


print(Model.model_json_schema())
"""
{'examples': ['example'], 'properties': {}, 'title': 'Model', 'type': 'object'}
"""

Decorator on missing field¶

This error is raised when you define a decorator with a field that is not valid.

from typing import Any

from pydantic import BaseModel, PydanticUserError, field_validator

try:

    class Model(BaseModel):
        a: str

        @field_validator('b')
        def check_b(cls, v: Any):
            return v

except PydanticUserError as exc_info:
    assert exc_info.code == 'decorator-missing-field'

You can use check_fields=False if you're inheriting from the model and intended this.

from typing import Any

from pydantic import BaseModel, create_model, field_validator


class Model(BaseModel):
    @field_validator('a', check_fields=False)
    def check_a(cls, v: Any):
        return v


model = create_model('FooModel', a=(str, 'cake'), __base__=Model)