Building Python applications with SQLAlchemy and Aurora DSQL

This article demonstrates building Python applications with SQLAlchemy and Amazon Aurora DSQL, a serverless PostgreSQL-compatible database.

• Use UUID primary keys with server_default=text("gen_random_uuid()") for distributed workloads
• Define relationships with relationship() using primaryjoin and foreign() instead of ForeignKey()
• Configure SQLAlchemy engine in AUTOCOMMIT mode to avoid unsupported SAVEPOINT operations
• Authenticate via AWS IAM using Aurora DSQL Python Connector with short-lived tokens
• Implement retry logic with exponential backoff for optimistic concurrency control conflicts
• Sample veterinary clinic CLI app demonstrates CRUD operations and eager loading patterns
• Pool connections with recycle=3300 to refresh before Aurora DSQL's 1-hour limit

The post provides production-ready patterns for connecting SQLAlchemy to Aurora DSQL, including code examples, prerequisites, and step-by-step deployment instructions.