What are the best practices for using Flask with Async SQLAlchemy?

What are the best practices for using Flask with Async SQLAlchemy?

When using Flask with Async SQLAlchemy, it's important to ensure that your database connections are properly managed. Use async context managers to handle sessions and avoid blocking calls.

Can you explain how to set up an async database session?

Sure! You can set up an async database session by using async with to create a session. Here's a basic example:

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

engine = create_async_engine('postgresql+asyncpg://user:password@localhost/dbname')
AsyncSessionLocal = sessionmaker(bind=engine, class_=AsyncSession, expire_on_commit=False)

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

What about handling migrations in an async environment?

For migrations in an async environment, you can use Alembic with an async configuration. Make sure to set up your env.py to use the async engine and run migrations using asyncio.run().

Are there any performance considerations I should be aware of?

Yes, be mindful of connection pooling and the number of concurrent connections. Use a connection pool that suits your application's load to avoid overwhelming the database.