GraphQL Engine built with Python 3.6+ / asyncio

Tartiflette is a GraphQL Server implementation built with Python 3.6+.

Summary

Motivation
Status
Usage
Installation
Installation dependencies
Tartiflette over HTTP
Roadmaps
How to contribute to the documentation?
How to run the website locally?
Known issues
Badges

Motivation

Read this blogpost about our motivations TL; DR We reached the limits of Graphene, we wanted to build something which met certain requirements:

Offers a better developer experience that respects the Python mindset
Uses SDL (Schema Definition Language)
Uses asyncio as the sole execution engine
Be 100% open source

Status

The first milestone is behind us, we are now on the road to the milestone 2.

DNA

Define the GraphQL schema with the brand new SDL (Schema Definition Language).
Performance oriented: Performance is the core of our work.
Simple is better than complex: Built with the Zen of Python in mind. No over-engineering.

Discover Tartiflette with our fabulous tutorial on https://tartiflette.io/docs/tutorial/getting-started

Usage

import asyncio

from tartiflette import Resolver, create_engine

@Resolver("Query.hello")
async def resolver_hello(parent, args, ctx, info):
return "hello " + args["name"]

async def run():
engine = await create_engine(
"""
type Query {
hello(name: String): String
}
"""
)

<span class="pl-s1">result</span> <span class="pl-c1">=</span> <span class="pl-k">await</span> <span class="pl-s1">engine</span>.<span class="pl-en">execute</span>(
    <span class="pl-s1">query</span><span class="pl-c1">=</span><span class="pl-s">'query { hello(name: "Chuck") }'</span>
)

<span class="pl-en">print</span>(<span class="pl-s1">result</span>)
<span class="pl-c"># {'data': {'hello': 'hello Chuck'}}</span>

if name == "main":
loop = asyncio.get_event_loop()
loop.run_until_complete(run())

More details on the API Documentation

Installation

Tartiflette is available on pypi.org.

pip install tartiflette

Installation dependencies

1.2.0+

As Tartiflette based its Executor engine on libgraphqlparser. You’ll need these following commands on your environment to use the library. cmake

MacOSX

brew install cmake

Ubuntu

apt-get install cmake

Before 1.2.0

As Tartiflette based its Executor engine on libgraphqlparser. You’ll need these following commands on your environment to use the library. cmake, bison and flex.

MacOSX

brew install cmake flex bison

Ubuntu

apt-get install cmake flex bison

Make sure you have bison in version 3

Note to Mac OS users: Make sure bison in your path is really Bison 3, look here for details.

Tartiflette over HTTP

Discover our implementation of tartiflette over HTTP called tartiflette-aiohttp.

Overview

pip install tartiflette-aiohttpfrom aiohttp import webfrom tartiflette_aiohttp import register_graphql_handlers

sdl = """
type Query {
hello(name: String): String
}
"""

ctx = {
'user_service': user_service
}

web.run_app(
register_graphql_handlers(
app=web.Application(),
engine_sdl=sdl,
engine_schema_name="default",
executor_context=ctx,
executor_http_endpoint='/graphql',
executor_http_methods=['POST', 'GET']
)
)

Roadmaps

How to contribute to the documentation?

As you may know, the documentation is hosted on https://tartiflette.io. This fabulous website is built thanks to another amazing tool, docusaurus.

The content of the documentation is hosted in this repository, to be as close as possible to the code. You will find everything you need/want in the folder /docs.

How to run the website locally?

We built a docker image for the documentation (tartiflette/tartiflette.io on docker hub), which allow us to provide you an easy way to launch the documentation locally, without installing a specific version of node.

prerequisite: