Python

GraphQL server with Python

Python is a programming language that lets you work quickly and integrate systems more effectively. Learn more at the official website.

The following guide covers common backend application tasks, such as creating REST endpoints using FastAPI. We also go over how to integrate your Python app with Hasura.

New to GraphQL? Check out the Introduction to GraphQL tutorial to learn the core concepts quickly.

• You will learn how to create a GraphQL server with Python and Strawberry FastAPI.
• If you have an existing GraphQL API with Python, you can integrate it with Hasura as a Remote Schema to get a unified GraphQL API.
• If you have an existing REST API with Python, you can transform that declaratively to GraphQL without writing any code using Hasura REST Connectors.
• You can also re-use or custom write REST endpoints with Python and map the endpoint to a GraphQL schema in Hasura.

New to Hasura? The Hasura GraphQL Engine makes your data instantly accessible over a real-time GraphQL API so that you can build and ship modern, performant apps and APIs 10x faster. Hasura connects to your databases, REST and GraphQL endpoints, and third-party APIs to provide a unified, connected, real-time, secured GraphQL API for all your data. Check out the Hasura documentation.

Create a Python GraphQL Server with Strawberry

We can make a custom GraphQL server in Python using Strawberry and connect it to Hasura using a remote schema.

1. Run the Strawberry FastAPI quickstart

2. In remoteSchema/remoteSchema.py add the Strawberry code

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   import strawberry
   from strawberry.fastapi import GraphQLRouter
   
   @strawberry.type
   class Query:
       @strawberry.field
       def hello(self) -> str:
         return "Hello World"
   
   schema = strawberry.Schema(Query)
   
   graphql_app = GraphQLRouter(schema)

3. Add the generated GraphQL handler to main.py

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   from remoteSchema.remoteSchema import graphql_app
   
   app.include_router(graphql_app, prefix="/graphql")

Python GraphQL API Federation using Hasura Remote Schema

We can connect our custom GraphQL server to Hasura using remote schemas to unify the GraphQL endpoint as a single endpoint.

1. In the Hasura Console remote schema tab, add your Python server <Python server URL>/graphql

2. In the API Explorer tab, try querying the sample todos.

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   {
     hello
   }

Convert a Python REST API endpoint to GraphQL

In this section, we will write a REST Endpoint in Python using FastAPI and see how to transform that to GraphQL. We will create a login POST endpoint that takes a username and password and returns an access code.

In our main.py, we use FastAPI to create an HTTP server:

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from fastapi import FastAPI
from typing import Generic, TypeVar
from pydantic import BaseModel
from pydantic.generics import GenericModel
from action.loginTypes import LoginResponse, loginArgs
from event.event import Payload
from remoteSchema.remoteSchema import graphql_app
from qlient.aiohttp import AIOHTTPClient, GraphQLResponse

ActionInput = TypeVar("ActionInput", bound=BaseModel | None)


class ActionName(BaseModel):
    name: str


class ActionPayload(GenericModel, Generic[ActionInput]):
    action: ActionName
    input: ActionInput
    request_query: str
    session_variables: dict[str, str]


app = FastAPI()


@app.post("/action")
async def actionHandler(action: ActionPayload[loginArgs]) -> LoginResponse:
    action.input
    return LoginResponse(AccessToken="<sample value>")

In action/action.py, we create the handler:

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from enum import Enum, auto
from pydantic import BaseModel


class LoginResponse(BaseModel):
    AccessToken: str


class Mutation(BaseModel):
    login: LoginResponse | None


class loginArgs(BaseModel):
    username: str
    password: str

Install the dependencies and run the app

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pip install "fastapi[all]"

uvicorn main:app --reload

Add Python REST Endpoint to GraphQL schema using Hasura Actions

When writing a backend we usually have to write around 80% of our code doing boilerplate CRUD operations. Hasura helps us by autogenerating this part.

When we need to write custom business logic we can integrate our Python REST endpoint using Hasura Actions, giving us the best of both worlds.

In the Actions tab on the Hasura Console we will set up a custom login function that calls the REST endpoint we created:

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type Mutation {
  login(username: String!, password: String!): LoginResponse
}

New types definition:

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type LoginResponse {
  AccessToken: String!
}

Create the action, click the Codegen tab, and select python-fast-api.

Copy login.py to main.py and loginTypes.py in your project.

In the Hasura API explorer tab you should now be able to test it

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mutation {
  login(password: "password", username: "username") {
    AccessToken
  }
}

Result:

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{
  "data": {
    "login": {
      "AccessToken": "<sample value>"
    }
  }
}

Run async scheduled events using a Python REST API and Hasura GraphQL

Databases like Postgres can run triggers when data changes, with Hasura event triggers we can easily call an HTTP endpoint whenever we have one of these events.

Let's send a webhook when a new user is created and print out their name.

1. In the Hasura Console add a user table with a Text column name and the frequently used UUID column id.

2. In the event trigger tab, on the user table, check the insert and via console trigger operations.

3. The event trigger payload schema can be found in the docs. We make pydantic classes in Python to represent this

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   from pydantic import BaseModel, Field
   from pydantic.generics import GenericModel
   from typing import Generic, Literal, TypeVar
   
   New = TypeVar("New", bound=BaseModel | None)
   Old = TypeVar("Old", bound=BaseModel | None)
   
   class DeliveryInfo(BaseModel):
       current_retry: int
       max_retries: int
   
   class Data(GenericModel, Generic[New, Old]):
       new: New
       old: Old
   
   class TraceContext(BaseModel):
       span_id: str
       trace_id: str
   
   class Event(GenericModel, Generic[New, Old]):
       data: Data[New, Old]
       op: Literal["INSERT", "UPDATE", "DELETE", "MANUAL"]
       session_variables: dict[str, str]
       trace_context: TraceContext
   
   class Table(BaseModel):
       name: str
       schema_: str = Field("", alias="schema")
   
   class Trigger(BaseModel):
       name: str
   
   class Payload(GenericModel, Generic[New, Old]):
       created_at: str
       delivery_info: DeliveryInfo
       event: Event[New, Old]
       id: str
       table: Table
       trigger: Trigger
   
   

4. Now we make an HTTP handler that handles the event

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   from event import Payload
   class UserTable(BaseModel):
     id: str
     name: str
   
   @app.post("/event")
   async def actionHandler(action: Payload[UserTable, None]):
       return

When you add a user in Hasura your Python server should receive the event.

Example: Querying GraphQL with Python Client qlient

To query a GraphQL endpoint from Python we use the async version of qlient.

1. Install qlient

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   pip install qlient.aiohttp

2. Query all users in the event trigger handler we created earlier,

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   @app.post("/event")
   async def actionHandler(action: Payload   [UserTable, None]):
       async with AIOHTTPClient("http://localhost:8080/v1/graphql") as client:
           result: GraphQLResponse = await client.query.user(["id", "name"])
           print(result.request.query)
           print(result.data)
       return

Summary

When developing backend applications, we may need to write custom business logic. When we use Hasura, it autogenerates most of our API but gives us escape hatches for this custom logic. We've gone over a few ways you can use the power of Python.

See the server source code on Github.

If you use Hasura and are ready to go to production, check out Hasura Cloud for a fully managed Hasura deployment.