Dicts and Mapping Types

dict

dict(v) is used to attempt to convert a dictionary; see typing.Dict below for sub-type constraints

from pydantic import BaseModel, ValidationError


class Model(BaseModel):
    x: dict


m = Model(x={'foo': 1})
print(m.model_dump())
#> {'x': {'foo': 1}}

try:
    Model(x='test')
except ValidationError as e:
    print(e)
    """
    1 validation error for Model
    x
      Input should be a valid dictionary [type=dict_type, input_value='test', input_type=str]
    """

typing.Dict

from typing import Dict

from pydantic import BaseModel, ValidationError


class Model(BaseModel):
    x: Dict[str, int]


m = Model(x={'foo': 1})
print(m.model_dump())
#> {'x': {'foo': 1}}

try:
    Model(x={'foo': '1'})
except ValidationError as e:
    print(e)
    """
    1 validation error for Model
    x
      Input should be a valid dictionary [type=dict_type, input_value='test', input_type=str]
    """

TypedDict

Note

This is a new feature of the Python standard library as of Python 3.8. Prior to Python 3.8, it requires the typing-extensions package. But required and optional fields are properly differentiated only since Python 3.9. We therefore recommend using typing-extensions with Python 3.8 as well.

TypedDict declares a dictionary type that expects all of its instances to have a certain set of keys, where each key is associated with a value of a consistent type.

It is same as dict but Pydantic will validate the dictionary since keys are annotated.

from typing_extensions import TypedDict

from pydantic import TypeAdapter, ValidationError


class User(TypedDict):
    name: str
    id: int


ta = TypeAdapter(User)

print(ta.validate_python({'name': 'foo', 'id': 1}))
#> {'name': 'foo', 'id': 1}

try:
    ta.validate_python({'name': 'foo'})
except ValidationError as e:
    print(e)
    """
    1 validation error for typed-dict
    id
      Field required [type=missing, input_value={'name': 'foo'}, input_type=dict]
    """

You can define __pydantic_config__ to change the model inherited from TypedDict. See Model Config for more details.

from typing import Optional

from typing_extensions import TypedDict

from pydantic import ConfigDict, TypeAdapter, ValidationError


# `total=False` means keys are non-required
class UserIdentity(TypedDict, total=False):
    name: Optional[str]
    surname: str


class User(TypedDict):
    __pydantic_config__ = ConfigDict(extra='forbid')

    identity: UserIdentity
    age: int


ta = TypeAdapter(User)

print(
    ta.validate_python(
        {'identity': {'name': 'Smith', 'surname': 'John'}, 'age': 37}
    )
)
#> {'identity': {'name': 'Smith', 'surname': 'John'}, 'age': 37}

print(
    ta.validate_python(
        {'identity': {'name': None, 'surname': 'John'}, 'age': 37}
    )
)
#> {'identity': {'name': None, 'surname': 'John'}, 'age': 37}

print(ta.validate_python({'identity': {}, 'age': 37}))
#> {'identity': {}, 'age': 37}


try:
    ta.validate_python(
        {'identity': {'name': ['Smith'], 'surname': 'John'}, 'age': 24}
    )
except ValidationError as e:
    print(e)
    """
    1 validation error for typed-dict
    identity.name
      Input should be a valid string [type=string_type, input_value=['Smith'], input_type=list]
    """

try:
    ta.validate_python(
        {
            'identity': {'name': 'Smith', 'surname': 'John'},
            'age': '37',
            'email': '[email protected]',
        }
    )
except ValidationError as e:
    print(e)
    """
    1 validation error for typed-dict
    email
      Extra inputs are not permitted [type=extra_forbidden, input_value='[email protected]', input_type=str]
    """