A Pydantic integration for Graphene.
pip install "graphene-pydantic"Here is a simple Pydantic model:
import uuid
import pydantic
class PersonModel(pydantic.BaseModel):
id: uuid.UUID
first_name: str
last_name: strTo create a GraphQL schema for it you simply have to write the following:
import graphene
from graphene_pydantic import PydanticObjectType
class Person(PydanticObjectType):
class Meta:
model = PersonModel
# exclude specified fields
exclude_fields = ("id",)
class Query(graphene.ObjectType):
people = graphene.List(Person)
@staticmethod
def resolve_people(parent, info):
# fetch actual PersonModels here
return [PersonModel(id=uuid.uuid4(), first_name="Beth", last_name="Smith")]
schema = graphene.Schema(query=Query)Then you can simply query the schema:
query = """
query {
people {
firstName,
lastName
}
}
"""
result = schema.execute(query)
print(result.data['people'][0])You can also create input object types from Pydantic models for mutations and queries:
from graphene_pydantic import PydanticInputObjectType
class PersonInput(PydanticInputObjectType):
class Meta:
model = PersonModel
# exclude specified fields
exclude_fields = ("id",)
class CreatePerson(graphene.Mutation):
class Arguments:
person = PersonInput()
Output = Person
@staticmethod
def mutate(parent, info, person):
personModel = PersonModel(id=uuid.uuid4(), first_name=person.first_name, last_name=person.last_name)
# save PersonModel here
return person
class Mutation(graphene.ObjectType):
createPerson = CreatePerson.Field()
schema = graphene.Schema(mutation=Mutation)Then execute with the input:
mutation = '''
mutation {
createPerson(person: {
firstName: "Jerry",
lastName: "Smith"
}) {
firstName
}
}
'''
result = schema.execute(mutation)
print(result.data['createPerson']['firstName'])Since PydanticObjectType inherits from graphene.ObjectType you can add custom resolve functions as explained here. For instance:
class Person(PydanticObjectType):
class Meta:
model = PersonModel
# exclude specified fields
exclude_fields = ("id",)
full_name = graphene.String()
def resolve_full_name(self, info, **kwargs):
return self.first_name + ' ' + self.last_namegraphene_pydantic supports forward declarations and circular references, but you will need to call the resolve_placeholders() method to ensure the types are fully updated before you execute a GraphQL query. For instance:
class NodeModel(BaseModel):
id: int
name: str
labels: 'LabelsModel'
class LabelsModel(BaseModel):
node: NodeModel
labels: typing.List[str]
class Node(PydanticObjectType):
class Meta:
model = NodeModel
class Labels(PydanticObjectType):
class Meta:
model = LabelsModel
Node.resolve_placeholders() # make the `labels` field work
Labels.resolve_placeholders() # make the `node` field workPlease see the examples directory for more.
This project is under the Apache License.
This project depends on third-party code which is subject to the licenses set forth in Third Party Licenses.
Please see the Contributing Guide.
Note that even though Pydantic is perfectly happy with fields that hold mappings (e.g. dictionaries), because GraphQL's type system doesn't have them those fields can't be exported to Graphene types. For instance, this will fail with an error Don't know how to handle mappings in Graphene:
import typing
from graphene_pydantic import PydanticObjectType
class Pet:
pass
class Person:
name: str
pets_by_name: typing.Dict[str, Pet]
class GraphQLPerson(PydanticObjectType):
class Meta:
model = PersonHowever, note that if you use exclude_fields or only_fields to exclude those values, there won't be a problem:
class GraphQLPerson(PydanticObjectType):
class Meta:
model = Person
exclude_fields = ("pets_by_name",)There are some caveats when using Unions. Let's take the following pydantic models as an example for this section:
class EmployeeModel(pydantic.BaseModel):
name: str
class ManagerModel(EmployeeModel):
title: str
class DepartmentModel(pydantic.BaseModel):
employees: T.List[T.Union[ManagerModel, EmployeeModel]]To get the Union between ManagerModel and EmployeeModel to successfully resolve
in graphene, you need to implement is_type_of like this:
class Employee(PydanticObjectType):
class Meta:
model = EmployeeModel
@classmethod
def is_type_of(cls, root, info):
return isinstance(root, (cls, EmployeeModel))
class Manager(PydanticObjectType):
class Meta:
model = ManagerModel
@classmethod
def is_type_of(cls, root, info):
return isinstance(root, (cls, ManagerModel))
class Department(PydanticObjectType):
class Meta:
model = DepartmentModelOtherwise GraphQL will throw an error similar to "[GraphQLError('Abstract type UnionOfManagerModelEmployeeModel must resolve to an Object type at runtime for field Department.employees ..."
Looking at the employees field above, if you write the type annotation with Employee first,
employees: T.List[T.Union[EmployeeModel, ManagerModel]], you will not be able to query
manager-related fields (in this case title). In a query containing a spread like this:
...on Employee {
name
}
...on Manager {
name
title
}
... the objects will always resolve to being an Employee. This can be avoided if you put
the subclass first in the list of annotations: employees: T.List[T.Union[ManagerModel, EmployeeModel]].
If a field on a model is a Union between a class and a subclass (as in our example), Python 3.6's typing will not preserve the Union and throws away the annotation for the subclass. See this issue for more details. The solution at present is to use Python 3.7.
This is a GraphQL limitation. See this RFC for the progress on supporting input unions. If you see an error like '{union-type} may only contain Object types', you are most likely encountering this limitation.
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