Strawberry-graphql

--------------------

Change `strawberry.auto` to be a type instead of a sentinel.
This not only removes the dependency on sentinel from the project, but also fixes
some related issues, like the fact that only types can be used with `Annotated`.

Also, custom scalars will now trick static type checkers into thinking they
returned their wrapped type. This should fix issues with pyright 1.1.224+ where
it doesn't allow non-type objects to be used as annotations for dataclasses and
dataclass-alike classes (which is strawberry's case). The change to `strawberry.auto`
also fixes this issue for it.

Contributed by [Thiago Bellini Ribeiro](https://github.com/bellini666) [PR #1690](https://github.com/strawberry-graphql/strawberry/pull/1690/)

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This release adds support for flask 2.x and also relaxes the requirements for Django, allowing to install newer version of Django without having to wait for Strawberry to update its supported dependencies list.

Contributed by [Guillaume Andreu Sabater](https://github.com/g-as) [PR #1687](https://github.com/strawberry-graphql/strawberry/pull/1687/)

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This fixes the schema printer to add support for schema
directives on input types.

Contributed by [Patrick Arminio](https://github.com/patrick91) [PR #1697](https://github.com/strawberry-graphql/strawberry/pull/1697/)

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This release fixed a false positive deprecation warning related to our AIOHTTP class based view.

Contributed by [Jonathan Ehwald](https://github.com/DoctorJohn) [PR #1691](https://github.com/strawberry-graphql/strawberry/pull/1691/)

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This release adds the following scalar types:

- `JSON`
- `Base16`
- `Base32`
- `Base64`

they can be used like so:

python
from strawberry.scalar import Base16, Base32, Base64, JSON


strawberry.type
class Example:
a: Base16
b: Base32
c: Base64
d: JSON


Contributed by [Paulo Costa](https://github.com/paulo-raca) [PR #1647](https://github.com/strawberry-graphql/strawberry/pull/1647/)

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Adds support for converting pydantic conlist.
Note that constraint is not enforced in the graphql type.
Thus, we recommend always working on the pydantic type such that the validation is enforced.

python
import strawberry
from pydantic import BaseModel, conlist


class Example(BaseModel):
friends: conlist(str, min_items=1)


strawberry.experimental.pydantic.input(model=Example, all_fields=True)
class ExampleGQL: ...


strawberry.type
class Query:
strawberry.field()
def test(self, example: ExampleGQL) -> None:
friends may be an empty list here
print(example.friends)
calling to_pydantic() runs the validation and raises
an error if friends is empty
print(example.to_pydantic().friends)


schema = strawberry.Schema(query=Query)


The converted graphql type is

input ExampleGQL {
friends: [String!]!
}


Contributed by [James Chua](https://github.com/thejaminator) [PR #1656](https://github.com/strawberry-graphql/strawberry/pull/1656/)