Please read UPGRADE-v1.0.md to learn how to upgrade to Graphene 1.0.

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Graphene

Graphene is a 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 both Relay.
• Data agnostic: Graphene supports any kind of data source: SQL (Django, SQLAlchemy), NoSQL, 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:

integration	Package
Django	graphene-django
SQLAlchemy	graphene-sqlalchemy
Google App Engine	graphene-gae
Peewee	In progress (Tracking Issue)

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

Installation

For instaling graphene, just run this command in your shell

pip install "graphene>=1.0"

1.0 Upgrade Guide

Please read UPGRADE-v1.0.md to learn how to upgrade.

Examples

Here is one example for you to get started:

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

    def resolve_hello(self, args, context, 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

Contributing

After cloning this repo, ensure dependencies are installed by running:

pip install .[test]

After developing, the full test suite can be evaluated by running:

py.test graphene --cov=graphene --benchmark-skip # Use -v -s for verbose mode

You can also run the benchmarks with:

py.test graphene --benchmark-only

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