Pythontartiflette-asyncio 的 SDL 优先的 GraphQL 引擎实现.zip

 [](https://sonarcloud.io/dashboard?id=tartiflette_tartiflette) [](https://lgtm.com/projects/g/tartiflette/tartiflette/alerts/) [](https://lgtm.com/projects/g/tartiflette/tartiflette/context:python) **Tartiflette** is a GraphQL Server implementation built with **Python 3.7+**. **Summary** - [Motivation](#motivation) - [Status](#status) - [Usage](#usage) - [Installation](#installation) - [Building from source](#building-from-source) - [HTTP server implementations](#http-server-implementations) - [Roadmaps](#roadmaps) - [How to contribute to the documentation?](#how-to-contribute-to-the-documentation) - [How to run the website locally?](#how-to-run-the-website-locally) ## Motivation [Read this blogpost about our motivations](https://medium.com/dailymotion/tartiflette-graphql-api-engine-python-open-source-a200c5bbc477) 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](/docs/roadmaps/milestone-1.md) is behind us, we are now [on the road to the milestone 2](/docs/roadmaps/milestone-2.md)**. **DNA** * Define the **GraphQL schema** with the brand new [SDL _(Schema Definition Language)_](https://github.com/facebook/graphql/blob/master/spec/Section%203%20--%20Type%20System.md). * **Performance oriented:** Performance is the core of our work. * **Simple is better than complex:** Built with [the Zen of Python](https://www.python.org/dev/peps/pep-0020/#id3) in mind. No over-engineering. Discover Tartiflette with our fabulous tutorial on [https://tartiflette.io/docs/tutorial/getting-started](https://tartiflette.io/docs/tutorial/getting-started) ## Usage ```python 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 } """ ) result = await engine.execute( query='query { hello(name: "Chuck") }' ) print(result) # {'data': {'hello': 'hello Chuck'}} if __name__ == "__main__": asyncio.run(run()) ``` More details on the [API Documentation](https://tartiflette.io/docs/api/engine/) ## Installation Tartiflette is available on [pypi.org](https://pypi.org/project/tartiflette/). While the project depends on *[libgraphqlparser](https://github.com/graphql/libgraphqlparser)*, wheels are provided since version 1.4.0, ensuring that no system dependency is required. To install the library: ```bash pip install tartiflette ``` ### Building from source If you use a platform incompatible with the provided wheels, you'll need to install `cmake` to build `libgraphqlparser` in order to install the library. *macOS* ```bash brew install cmake ``` *Debian/Ubuntu* ```bash apt-get install cmake ``` ## HTTP server implementations `tartiflette` library itself is transport agnostic, but to simplify integration with existing HTTP servers, two different libraries are available: - [tartiflette-aiohttp](https://github.com/tartiflette/tartiflette-aiohttp): integration with `aiohttp` - [tartiflette-asgi](https://github.com/tartiflette/tartiflette-asgi): integration with ASGI compatible HTTP servers ## Roadmaps * [Milestone 1 _(Released)_](/docs/roadmaps/milestone-1.md) * [Milestone 2 - **Work in progress**](/docs/roadmaps/milestone-2.md) ## 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](https://docusaurus.io/). 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**: - Docker - Docker Compose - Make ```bash make run-docs ``` Every change you will make in the `/docs` folder will be automatically hot reloaded. :tada: