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https://github.com/graphql-python/graphene-pydantic
Integrate GraphQL with your Pydantic models
https://github.com/graphql-python/graphene-pydantic
Last synced: 7 days ago
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Integrate GraphQL with your Pydantic models
- Host: GitHub
- URL: https://github.com/graphql-python/graphene-pydantic
- Owner: graphql-python
- License: other
- Created: 2019-06-20T00:49:40.000Z (over 5 years ago)
- Default Branch: main
- Last Pushed: 2024-06-11T17:42:15.000Z (6 months ago)
- Last Synced: 2024-11-20T11:14:58.759Z (23 days ago)
- Language: Python
- Homepage:
- Size: 289 KB
- Stars: 230
- Watchers: 8
- Forks: 45
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
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README
#  graphene-pydantic [](https://circleci.com/gh/upsidetravel/graphene-pydantic) [](https://badge.fury.io/py/graphene-pydantic) [](https://coveralls.io/github/upsidetravel/graphene-pydantic?branch=master)
A [Pydantic](https://pydantic-docs.helpmanual.io/) integration for [Graphene](http://graphene-python.org/).
## Installation
```bash
pip install "graphene-pydantic"
```
## Examples
Here is a simple Pydantic model:
```python
import uuid
import pydantic
class PersonModel(pydantic.BaseModel):
id: uuid.UUID
first_name: str
last_name: str
```
To create a GraphQL schema for it you simply have to write the following:
```python
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:
```python
query = """
query {
people {
firstName,
lastName
}
}
"""
result = schema.execute(query)
print(result.data['people'][0])
```
### Input Object Types
You can also create input object types from Pydantic models for mutations and queries:
```python
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:
```python
mutation = '''
mutation {
createPerson(person: {
firstName: "Jerry",
lastName: "Smith"
}) {
firstName
}
}
'''
result = schema.execute(mutation)
print(result.data['createPerson']['firstName'])
```
### Custom resolve functions
Since `PydanticObjectType` inherits from `graphene.ObjectType` you can add custom resolve functions as explained [here](https://docs.graphene-python.org/en/stable/api/#object-types). For instance:
```python
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_name
```
### Forward declarations and circular references
`graphene_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:
``` python
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 work
```
### Full Examples
Please see [the examples directory](./examples) for more.
### License
This project is under the [Apache License](./LICENSE.md).
### Third Party Code
This project depends on third-party code which is subject to the licenses set forth in [Third Party Licenses](./THIRD_PARTY_LICENSES.md).
### Contributing
Please see the [Contributing Guide](./CONTRIBUTING.md).
### Caveats
#### Mappings
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](https://graphql.org/learn/schema/) 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`:
``` python
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 = Person
```
However, note that if you use `exclude_fields` or `only_fields` to exclude those values, there won't be a problem:
``` python
class GraphQLPerson(PydanticObjectType):
class Meta:
model = Person
exclude_fields = ("pets_by_name",)
```
#### Union types
There are some caveats when using Unions. Let's take the following pydantic models as an example for this section:
```python
class EmployeeModel(pydantic.BaseModel):
name: str
class ManagerModel(EmployeeModel):
title: str
class DepartmentModel(pydantic.BaseModel):
employees: T.List[T.Union[ManagerModel, EmployeeModel]]
```
##### You have to implement the class method `is_type_of` in the graphene models
To get the Union between `ManagerModel` and `EmployeeModel` to successfully resolve
in graphene, you need to implement `is_type_of` like this:
```python
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 = DepartmentModel
```
Otherwise GraphQL will throw an error similar to `"[GraphQLError('Abstract type
UnionOfManagerModelEmployeeModel must resolve to an Object type at runtime for
field Department.employees ..."`
##### For unions between subclasses, you need to put the subclass first in the type annotation
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]]`.
##### Unions between subclasses don't work in Python 3.6
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](https://github.com/upsidetravel/graphene-pydantic/issues/11) for more details.
The solution at present is to use Python 3.7.
##### Input Object Types don't support unions as fields
This is a GraphQL limitation. See [this RFC](https://github.com/graphql/graphql-spec/blob/master/rfcs/InputUnion.md) 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.