Question 1

Fastapi-SQLA vs FastAPI-SQLAlchemy: which is better?

Accepted Answer

Fastapi-SQLA focuses on pagination, async support, and SQLModel integration, while FastAPI-SQLAlchemy is more minimal. Choose Fastapi-SQLA for production-ready utilities like testing fixtures, but compare based on your need for async or multi-session features.

Question 2

How to set up async sessions with Fastapi-SQLA?

Accepted Answer

Install asyncpg and set the environment variable sqlalchemy_url to postgresql+asyncpg://. Then use AsyncSession in dependencies or context managers, as shown in the async examples in the README.

Question 3

Does Fastapi-SQLA work with MySQL databases?

Accepted Answer

Yes, for synchronous operations with SQLAlchemy-compatible engines like MySQLdb or PyMySQL. However, async support is only tested and optimized for PostgreSQL via asyncpg, so async with MySQL may require custom setups.

Question 4

How to test database transactions in FastAPI with Fastapi-SQLA?

Accepted Answer

Use the provided Pytest fixtures like session and async_session, which automatically rollback transactions. Ensure sqla_modules is defined and use db_migration for Alembic-based testing, as detailed in the testing section.

Question 5

Can I use Fastapi-SQLA without SQLModel?

Accepted Answer

Yes, it works with standard SQLAlchemy models. SQLModel integration is optional but seamless if you choose to use it, as shown in the SQLModel support examples.

Question 6

What are the performance implications of Fastapi-SQLA pagination?

Accepted Answer

Pagination uses Query.count by default, which can be inefficient for large datasets. You can customize it with query_count for better performance, as mentioned in the pagination customization section.

Fastapi-SQLA

What is Fastapi-SQLA?

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Pros & Cons

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