Setting Up Async Databases with FastAPI

Asynchronous programming is becoming increasingly popular in Python due to its ability to handle multiple tasks concurrently without blocking the main thread. When working with FastAPI, integrating asynchronous database operations can significantly improve performance and scalability. This guide will walk you through the steps of setting up an asynchronous database with FastAPI, using PostgreSQL as an example.

Prerequisites

Before we begin, ensure you have the following installed:

• Python 3.7 or later
• FastAPI
• uvicorn
• asyncpg (for PostgreSQL) or other appropriate asynchronous database driver

Creating a Database Connection

Import Necessary Modules:

Python

from sqlalchemy.ext.asyncio import create_async_engine
from sqlalchemy.orm import sessionmaker

Define the Database URL:

Python

DATABASE_URL = “postgresql://user:password@host:port/database”

Create the Engine:

Python

engine = create_async_engine(DATABASE_URL)

Create the Session Factory:

Python

async_session = sessionmaker(autocommit=False, autoflush=False, bind=engine)

Creating a Dependency

To inject the database session into your FastAPI endpoints, create a dependency:

Python

from fastapi import Depends

async def get_db():
    async with async_session() as session:
        yield session

Using the Database in Endpoints

Now, you can use the db dependency in your FastAPI endpoints to perform asynchronous database operations:

Python

from fastapi import APIRouter, Depends

router = APIRouter()

@router.post("/users")
async def create_user(user: User, db: Session = Depends(get_db)):
    async with db:
        db.add(user)
        await db.commit()
        await db.refresh(user)
        return user

By following these steps, you can effectively integrate asynchronous databases with your FastAPI applications, improving performance and scalability.