SQLAlchemy calls database drivers "dialects". So if you're using SQLAlchemy with PostgreSQL and using psycopg2 as the driver, then you're using the psycopg2 dialect of PostgreSQL.
I was looking for the same thing as you, and found no existing solution, so I wrote my own and published it. To use the AWS Aurora RDS Data API, I created a SQL dialect package for it, sqlalchemy-aurora-data-api. This in turn required me to write a DB-API compatible Python DB driver for Aurora Data API, aurora-data-api. After installing with pip install sqlalchemy-aurora-data-api
, you can use it like this:
from sqlalchemy import create_engine
cluster_arn = "arn:aws:rds:us-east-1:123456789012:cluster:my-aurora-serverless-cluster"
secret_arn = "arn:aws:secretsmanager:us-east-1:123456789012:secret:MY_DB_CREDENTIALS"
engine = create_engine('postgresql+auroradataapi://:@/my_db_name',
echo=True,
connect_args=dict(aurora_cluster_arn=cluster_arn, secret_arn=secret_arn))
with engine.connect() as conn:
for result in conn.execute("select * from pg_catalog.pg_tables"):
print(result)