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Postponed annotations

Note

Both postponed annotations via the future import and ForwardRef require python 3.7+.

Postponed annotations (as described in PEP563) "just work".

from __future__ import annotations
from typing import List
from pydantic import BaseModel


class Model(BaseModel):
    a: List[int]


print(Model(a=('1', 2, 3)))
#> a=[1, 2, 3]
(This script is complete, it should run "as is")

Internally, pydantic will call a method similar to typing.get_type_hints to resolve annotations.

In cases where the referenced type is not yet defined, ForwardRef can be used (although referencing the type directly or by its string is a simpler solution in the case of self-referencing models).

In some cases, a ForwardRef won't be able to be resolved during model creation. For example, this happens whenever a model references itself as a field type. When this happens, you'll need to call update_forward_refs after the model has been created before it can be used:

from typing import ForwardRef
from pydantic import BaseModel

Foo = ForwardRef('Foo')


class Foo(BaseModel):
    a: int = 123
    b: Foo = None


Foo.update_forward_refs()

print(Foo())
#> a=123 b=None
print(Foo(b={'a': '321'}))
#> a=123 b=Foo(a=321, b=None)
(This script is complete, it should run "as is")

Warning

To resolve strings (type names) into annotations (types), pydantic needs a namespace dict in which to perform the lookup. For this it uses module.__dict__, just like get_type_hints. This means pydantic may not play well with types not defined in the global scope of a module.

For example, this works fine:

from __future__ import annotations
from typing import List  # <-- List is defined in the module's global scope
from pydantic import BaseModel


def this_works():
    class Model(BaseModel):
        a: List[int]

    print(Model(a=(1, 2)))

While this will break:

from __future__ import annotations
from pydantic import BaseModel


def this_is_broken():
    # List is defined inside the function so is not in the module's
    # global scope!
    from typing import List

    class Model(BaseModel):
        a: List[int]

    print(Model(a=(1, 2)))

Resolving this is beyond the call for pydantic: either remove the future import or declare the types globally.

Self-referencing Models🔗

Data structures with self-referencing models are also supported, provided the function update_forward_refs() is called once the model is created (you will be reminded with a friendly error message if you forget).

Within the model, you can refer to the not-yet-constructed model using a string:

from pydantic import BaseModel


class Foo(BaseModel):
    a: int = 123
    #: The sibling of `Foo` is referenced by string
    sibling: 'Foo' = None


Foo.update_forward_refs()

print(Foo())
#> a=123 sibling=None
print(Foo(sibling={'a': '321'}))
#> a=123 sibling=Foo(a=321, sibling=None)
(This script is complete, it should run "as is")

Since python 3.7, you can also refer it by its type, provided you import annotations (see above for support depending on Python and pydantic versions).

from __future__ import annotations
from pydantic import BaseModel


class Foo(BaseModel):
    a: int = 123
    #: The sibling of `Foo` is referenced directly by type
    sibling: Foo = None


Foo.update_forward_refs()

print(Foo())
#> a=123 sibling=None
print(Foo(sibling={'a': '321'}))
#> a=123 sibling=Foo(a=321, sibling=None)
(This script is complete, it should run "as is")