Pydantic model fields with typing.Optional[] vs. typing.Optional[] = None

Question

What is the distinction between implicitly setting an optional attribute to None with typing.Optional[] versus explicitly assigning typing.Optional[] = None when creating Pydantic models? In both cases, the attribute will eventually have a value of None when the class object is instantiated.

import typing
import pydantic


class Bar(pydantic.BaseModel):
    a: typing.Optional[int]

    @pydantic.validator('a', always=True, pre=True)
    def check_a(cls, v, values, field):
        print("WITHOUT NONE")
        print(values)
        print(field)
        return v


class Baz(pydantic.BaseModel):
    a: typing.Optional[int] = None

    @pydantic.validator('a', always=True, pre=True)
    def check_a(cls, v, values, field):
        print("WITH NONE")
        print(values)
        print(field)
        return v


print(Bar())
print(Baz())

Output:

WITHOUT NONE
{}
name='a' type=Optional[int] required=False default=None
a=None
WITH NONE
{}
name='a' type=Optional[int] required=False default=None
a=None

Answer 1

Whilst the previous answer is correct for pydantic v1, note that pydantic v2, released 2023-06-30, changed this behavior.

As specified in the migration guide:

Pydantic V2 changes some of the logic for specifying whether a field annotated as Optional is required (i.e., has no default value) or not (i.e., has a default value of None or any other value of the corresponding type), and now more closely matches the behavior of dataclasses. Similarly, fields annotated as Any no longer have a default value of None.