Graphene (Python)

Graphene (Python)
Name	Graphene
Programming language	Python
License	MIT License
Website	graphene-python.org

Graphene (Python) is a Python library for building GraphQL APIs that integrates with frameworks and ORMs to provide schema-first and code-first approaches. It is used to implement GraphQL servers alongside tools and platforms such as Django, Flask, SQLAlchemy, Pyramid, Tornado, Starlette, FastAPI, and AWS Lambda. Major adopters and related projects include GitHub, GitLab, Shopify, Netflix, Airbnb, and Facebook which originated GraphQL.

Overview

Graphene provides a declarative Pythonic mapping from Python classes to GraphQL types and resolvers, enabling integration with libraries such as Django Rest Framework, SQLAlchemy ORM, Pony ORM, MongoDB, Peewee, Tortoise ORM, and Elasticsearch. It supports schema construction compatible with tools like Apollo (software), Relay, and GraphiQL and can be used in conjunction with services like Heroku, Google Cloud Platform, Microsoft Azure, Amazon Web Services, and DigitalOcean. Its development intersects with communities around PyPI, GitHub, Read the Docs, and Travis CI/GitHub Actions for continuous integration.

Features

Graphene implements features expected in modern GraphQL stacks: schema definition via Python classes, input validation, custom scalars, and middleware. It supports integrations with authentication systems like OAuth 2.0, OpenID Connect, and identity providers such as Auth0 and Okta. For pagination and connections it follows conventions used by Relay and supports cursor-based pagination used by platforms like Twitter and Facebook. Graphene also offers caching hooks compatible with Redis, Memcached, and monitoring with Prometheus and Sentry; it can be deployed with orchestration tools like Kubernetes and Docker.

Installation and Usage

Graphene is distributed via PyPI and installed using pip and can be pinned in requirements.txt or used with pipenv and Poetry. Typical usage in a Django project involves adding Graphene to INSTALLED_APPS and defining schema objects tied to Django ORM models; for Flask it integrates via middleware and blueprints similar to Flask-RESTful. Development workflows often include editors such as Visual Studio Code, PyCharm, or Vim and benefit from linters like flake8 and formatters like Black. For testing, Graphene works with frameworks like pytest, unittest, and CI services including CircleCI, Travis CI, and GitHub Actions.

Architecture and Design

Graphene's architecture centers on a schema layer mapping Python classes to GraphQL type system constructs: ObjectType, Interface, Union, Enum, and Scalar. Resolver resolution follows an execution algorithm compatible with the GraphQL specification maintained by organizations such as Meta and overseen by contributor communities including GraphQL Foundation hosted by the Linux Foundation. Graphene's modular design supports adapters for ORMs and web frameworks, mirroring plugin architectures used by projects like Django REST framework and Flask-Admin. Serialization and deserialization routines interact with JSON tools influenced by JSON Schema practices used in OpenAPI Specification implementations like Swagger and gateways like Kong.

Examples and Tutorials

Common tutorials show building a simple query and mutation integrating with Django models and SQLAlchemy sessions, following patterns demonstrated in community tutorials from Real Python, Tutorialspoint, and FreeCodeCamp. Examples often demonstrate schema stitching concepts analogous to approaches used by Apollo Federation and federated services at companies like Netflix and Airbnb. Interactive exploration uses tools like GraphiQL, Insomnia, Postman, and Altair and is showcased in conference talks at PyCon, DjangoCon, GraphQL Summit, JSConf, and Strange Loop.

Development and Community

Graphene's source is hosted on GitHub where contributors collaborate using issues and pull requests; continuous integration and release practices mirror those of projects like Django, Flask, SQLAlchemy, and Pandas. The community communicates via channels such as Slack, Discord, and mailing lists resembling those of Python Software Foundation projects. Documentation and examples are published on Read the Docs and community blogs; maintenance and governance involve contributors linked to organizations including OpenAI, Microsoft, Google, and various independent maintainers. The ecosystem includes extensions and related projects like graphene-django, graphene-sqlalchemy, Ariadne, Strawberry, and graphql-core.

Category:Python libraries