Generics

Strawberry supports using Python's Generic typing to dynamically create reusable types.

Strawberry will automatically generate the correct GraphQL schema from the combination of the generic type and the type arguments. Generics are supported in Object types, Input types, and Arguments to queries, mutations, and scalars.

Let's take a look at an example:

Object Types

from typing import Generic, List, TypeVar

import strawberry
 
T = TypeVar("T")


@strawberry.type
class Page(Generic[T]):
    number: int
    items: List[T]

This example defines a generic type Page that can be used to represent a page of any type. For example, we can create a page of User objects:

import strawberry

@strawberry.type
class User:
    name: str

@strawberry.type
class Query:
    users: Page[User]

type Query {
  users: UserPage!
}

type User {
  name: String!
}

type UserPage {
  number: Int!
  items: [User!]!
}

It is also possible to use a specialized generic type directly. For example, the same example above could be written like this:

import strawberry

@strawberry.type
class User:
    name: str


@strawberry.type
class UserPage(Page[User]):
    ...

@strawberry.type
class Query:
    users: UserPage

type Query {
  users: UserPage!
}

type User {
  name: String!
}

type UserPage {
  number: Int!
  items: [User!]!
}

Input and Argument Types

Arguments to queries and mutations can also be made generic by creating Generic Input types. Here we'll define an input type that can serve as a collection of anything, then create a specialization by using as a filled-in argument on a mutation.

import strawberry
from typing import Generic, List, Optional, TypeVar
 
T = TypeVar("T")

@strawberry.input
class CollectionInput(Generic[T]):
    values: List[T]

@strawberry.input
class PostInput:
    name: str

@strawberry.type
class Post:
    id: int
    name: str

@strawberry.type
class Mutation:
    @strawberry.mutation
    def add_posts(self, posts: CollectionInput[PostInput]) -> bool:
        return True

@strawberry.type
class Query:
    most_recent_post: Optional[Post] = None

schema = strawberry.Schema(query=Query, mutation=Mutation)

input PostInputCollectionInput {
  values: [PostInput!]!
}

input PostInput {
  name: String!
}

type Post {
  id: Int!
  name: String!
}

type Query {
  mostRecentPost: Post
}

type Mutation {
  addPosts(posts: PostInputCollectionInput!): Boolean!
}

Note: Pay attention to the fact that both CollectionInput and PostInput are Input types. Providing posts: CollectionInput[Post] to add_posts (i.e. using the non-input Post type) would have resulted in an error:

PostCollectionInput fields cannot be resolved. Input field type must be a
GraphQL input type

Multiple Specializations

Using multiple specializations of a Generic type will work as expected. Here we define a Point2D type and then specialize it for both ints and floats.

from typing import Generic, TypeVar

import strawberry
 
T = TypeVar('T')

@strawberry.input
class Point2D(Generic[T]):
    x: T
    y: T

@strawberry.type
class Mutation:
    @strawberry.mutation
    def store_line_float(self, a: Point2D[float], b: Point2D[float]) -> bool:
        return True

    @strawberry.mutation
    def store_line_int(self, a: Point2D[int], b: Point2D[int]) -> bool:
        return True

type Mutation {
  storeLineFloat(a: FloatPoint2D!, b: FloatPoint2D!): Boolean!
  storeLineInt(a: IntPoint2D!, b: IntPoint2D!): Boolean!
}

input FloatPoint2D {
  x: Float!
  y: Float!
}

input IntPoint2D {
  x: Int!
  y: Int!
}

Variadic Generics

Variadic Generics, introduced in PEP-646, are currently unsupported.