8eb881e085
operationName is serialized into the query string as a string. When getting the query value for operationName, we need to convert string "null" into None. |
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bin | ||
docs | ||
examples | ||
graphene_django | ||
.coveragerc | ||
.gitignore | ||
.travis.yml | ||
django_test_settings.py | ||
MANIFEST.in | ||
pytest.ini | ||
README.md | ||
README.rst | ||
setup.cfg | ||
setup.py |
Please read UPGRADE-v1.0.md to learn how to upgrade to Graphene 1.0
.
Graphene-Django
A Django integration for Graphene.
Installation
For instaling graphene, just run this command in your shell
pip install "graphene-django>=1.0"
Settings
INSTALLED_APPS = (
# ...
'graphene_django',
)
GRAPHENE = {
'SCHEMA': 'app.schema.schema' # Where your Graphene schema lives
}
Urls
We need to set up a GraphQL
endpoint in our Django app, so we can serve the queries.
from django.conf.urls import url
from graphene_django.views import GraphQLView
urlpatterns = [
# ...
url(r'^graphql', GraphQLView.as_view(graphiql=True)),
]
Examples
Here is a simple Django model:
from django.db import models
class UserModel(models.Model):
name = models.CharField(max_length=100)
last_name = models.CharField(max_length=100)
To create a GraphQL schema for it you simply have to write the following:
from graphene_django import DjangoObjectType
import graphene
class User(DjangoObjectType):
class Meta:
model = UserModel
class Query(graphene.ObjectType):
users = graphene.List(User)
@graphene.resolve_only_args
def resolve_users(self):
return UserModel.objects.all()
schema = graphene.Schema(query=Query)
Then you can simply query the schema:
query = '''
query {
users {
name,
lastName
}
}
'''
result = schema.execute(query)
To learn more check out the following examples:
- Schema with Filtering: Cookbook example
- Relay Schema: Starwars Relay example
Contributing
After cloning this repo, ensure dependencies are installed by running:
pip install -e ".[test]"
After developing, the full test suite can be evaluated by running:
py.test graphene_django --cov=graphene_django # Use -v -s for verbose mode
Documentation
The documentation is generated using the excellent Sphinx and a custom theme.
The documentation dependencies are installed by running:
cd docs
pip install -r requirements.txt
Then to produce a HTML version of the documentation:
make html