SQLAlchemy 2.0 Async Patterns FAQs

Question 1

Why does this skill recommend lazy='raise'?

Accepted Answer

Using 'lazy="raise"' prevents the application from attempting to lazy-load relationships in an async context, which would otherwise block the event loop or cause runtime errors. It forces explicit eager loading for better performance.

Question 2

Can I use this with any database driver?

Accepted Answer

While optimized for async-compatible drivers like asyncpg for PostgreSQL, these patterns apply to any database supported by SQLAlchemy's asynchronous extensions.

Question 3

Does it support bulk data operations?

Accepted Answer

Yes, it includes optimized patterns for bulk inserts using SQLAlchemy 2.0's multi-value features and provides chunking strategies for handling very large datasets without memory exhaustion.

Question 4

How do I handle concurrent database queries?

Accepted Answer

The skill provides guidance on using sequential queries within a single session or spawning multiple sessions for parallel execution using TaskGroups, avoiding session-sharing race conditions.

Question 5

Is this skill compatible with FastAPI dependency injection?

Accepted Answer

Yes, it includes specialized patterns for providing scoped AsyncSession instances to FastAPI routes, ensuring proper commit/rollback cycles and connection management.

SQLAlchemy 2.0 Async Patterns

Key Features

Use Cases

SQLAlchemy 2.0 Async Patterns

Key Features

Use Cases