GraphQL client for Python
Project description
GQL
This is a GraphQL client for Python 3.6+.
Plays nicely with graphene, graphql-core, graphql-js and any other GraphQL implementation compatible with the spec.
GQL architecture is inspired by React-Relay and Apollo-Client.
WARNING: Please note that the following documentation describes the current version which is currently only available as a pre-release The documentation for the 2.x version compatible with python<3.6 is available in the 2.x branch
Documentation
The complete documentation for GQL can be found at gql.readthedocs.io.
Features
The main features of GQL are:
- Execute GraphQL queries using different protocols (http, websockets, ...)
- Possibility to validate the queries locally using a GraphQL schema provided locally or fetched from the backend using an instrospection query
- Supports GraphQL queries, mutations and subscriptions
- Supports sync or async usage, allowing concurrent requests
- Supports File uploads
- Supports Custom scalars / Enums
- gql-cli script to execute GraphQL queries from the command line
- DSL module to compose GraphQL queries dynamically
Installation
WARNING: Please note that the following documentation describes the current version which is currently only available as a pre-release and needs to be installed with
$ pip install --pre gql[all]
NOTE: See also the documentation to install GQL with less extra dependencies
Usage
Basic usage
from gql import gql, Client
from gql.transport.aiohttp import AIOHTTPTransport
# Select your transport with a defined url endpoint
transport = AIOHTTPTransport(url="https://countries.trevorblades.com/")
# Create a GraphQL client using the defined transport
client = Client(transport=transport, fetch_schema_from_transport=True)
# Provide a GraphQL query
query = gql(
"""
query getContinents {
continents {
code
name
}
}
"""
)
# Execute the query on the transport
result = client.execute(query)
print(result)
WARNING: Please note that this basic example won't work if you have an asyncio event loop running. In some python environments (as with Jupyter which uses IPython) an asyncio event loop is created for you. In that case you should use instead the async usage example.
Contributing
See CONTRIBUTING.md
License
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