To help you get started, we've collected the most common ways that graphene is being used within popular public projects.

flavors / django-graphql-geojson / tests / test_mutations.py View on Github

from django.contrib.gis import geos

import graphene

import graphql_geojson

from . import models, types
from .testcases import SchemaTestCase


class CreatePlace(graphene.Mutation):
    place = graphene.Field(types.PlaceType)

    class Arguments:
        name = graphene.String(required=True)
        location = graphql_geojson.Geometry(required=True)

    @classmethod
    def mutate(cls, root, info, **args):
        place = models.Place.objects.create(**args)
        return cls(place=place)


class MutationsTests(SchemaTestCase):
    query = '''
    mutation CreatePlace($name: String!, $location: Geometry!) {
      createPlace(name: $name, location: $location) {
        place {
          id
          type
          geometry {

View more ways to use graphene

Graphene

���� Join the community on Discord

We are looking for contributors! Please check the current issues to see how you can help ������

Introduction

Graphene is an opinionated Python library for building GraphQL schemas/types fast and easily.

• Easy to use: Graphene helps you use GraphQL in Python without effort.
• Relay: Graphene has builtin support for Relay.
• Data agnostic: Graphene supports any kind of data source: SQL (Django, SQLAlchemy), Mongo, custom Python objects, etc. We believe that by providing a complete API you could plug Graphene anywhere your data lives and make your data available through GraphQL.

Integrations

Graphene has multiple integrations with different frameworks:

Also, Graphene is fully compatible with the GraphQL spec, working seamlessly with all GraphQL clients, such as Relay, Apollo and gql.

Installation

To install graphene, just run this command in your shell

pip install "graphene>=3.1"

Examples

Here is one example for you to get started:

import graphene

class Query(graphene.ObjectType):
    hello = graphene.String(description='A typical hello world')

    def resolve_hello(self, info):
        return 'World'

schema = graphene.Schema(query=Query)

Then Querying graphene.Schema is as simple as:

query = '''
    query SayHello {
      hello
    }
'''
result = schema.execute(query)

If you want to learn even more, you can also check the following examples:

• Basic Schema: Starwars example
• Relay Schema: Starwars Relay example

Documentation

Documentation and links to additional resources are available at https://docs.graphene-python.org/en/latest/

Contributing

After cloning this repo, create a virtualenv and ensure dependencies are installed by running:

virtualenv venv
source venv/bin/activate
pip install -e ".[test]"

Well-written tests and maintaining good test coverage is important to this project. While developing, run new and existing tests with:

pytest graphene/relay/tests/test_node.py # Single file
pytest graphene/relay # All tests in directory

Add the -s flag if you have introduced breakpoints into the code for debugging. Add the -v ("verbose") flag to get more detailed test output. For even more detailed output, use -vv. Check out the pytest documentation for more options and test running controls.

Regularly ensure your pre-commit hooks are up to date and enabled:

pre-commit install

You can also run the benchmarks with:

pytest graphene --benchmark-only

Graphene supports several versions of Python. To make sure that changes do not break compatibility with any of those versions, we use tox to create virtualenvs for each Python version and run tests with that version. To run against all Python versions defined in the tox.ini config file, just run:

tox

If you wish to run against a specific version defined in the tox.ini file:

tox -e py39

Tox can only use whatever versions of Python are installed on your system. When you create a pull request, GitHub Actions pipelines will also be running the same tests and report the results, so there is no need for potential contributors to try to install every single version of Python on their own system ahead of time. We appreciate opening issues and pull requests to make graphene even more stable & useful!

Building Documentation

The documentation is generated using the excellent Sphinx and a custom theme.

An HTML version of the documentation is produced by running:

make docs