SQLAlchemy is an ORM and general-purpose SQL engine for Python. It can work with many different SQL database backends. Reddit generally uses it to talk to PostgreSQL.


To integrate SQLAlchemy with your application, add the appropriate client declaration to your context configuration:

      "foo": SQLAlchemySession(),

configure it in your application’s configuration file:



# required: sqlalchemy URL describing a database to connect to
foo.url = postgresql://postgres.local:6543/bar

# optional: the name of a CredentialSecret holding credentials for
# authenticating to the database
foo.credentials_secret = secret/my_service/db-foo


and then use the attached Session object in request:

def my_method(request):


class baseplate.clients.sqlalchemy.SQLAlchemySession(secrets=None, **kwargs)[source]

Configure a SQLAlchemy Session.

This is meant to be used with baseplate.Baseplate.configure_context().

See engine_from_config() for available configuration settings.


secrets (Optional[SecretsStore]) – Required if configured to use credentials to talk to the database.

baseplate.clients.sqlalchemy.engine_from_config(app_config, secrets=None, prefix='database.', **kwargs)[source]

Make an Engine from a configuration dictionary.

The keys useful to engine_from_config() should be prefixed, e.g. database.url, etc. The prefix argument specifies the prefix used to filter keys.

Supported keys: :rtype: Engine

  • url: the connection URL to the database, passed to

    make_url() to create the URL used to connect to the database.

  • credentials_secret (optional): the key used to retrieve the database

    credentials from secrets as a CredentialSecret. If this is supplied, any credentials given in url we be replaced by these.

  • pool_recycle (optional): this setting causes the pool to recycle connections after

    the given number of seconds has passed. It defaults to -1, or no timeout.

  • pool_pre_ping (optional): when set to true, this setting causes

    sqlalchemy to perform a liveness-check query each time a connection is checked out of the pool. If the liveness-check fails, the connection is gracefully recycled. This ensures severed connections are handled more gracefully, at the cost of doing a SELECT 1 at the start of each checkout. When used, this obviates most of the reasons you might use pool_recycle, and as such they shouldn’t normally be used simultaneously. Requires SQLAlchemy 1.3.

  • pool_size (optional) : The number of connections that can be saved in the pool.

  • max_overflow (optional) : Max connections that can be opened beyond the pool size.


class baseplate.clients.sqlalchemy.SQLAlchemyEngineContextFactory(engine, name='sqlalchemy')[source]

SQLAlchemy core engine context factory.

This factory will attach a SQLAlchemy sqlalchemy.engine.Engine to an attribute on the RequestContext. All cursor (query) execution will automatically record diagnostic information.

Additionally, the trace and span ID will be added as a comment to the text of the SQL statement. This is to aid correlation of queries with requests.

See also

The engine is the low-level SQLAlchemy API. If you want to use the ORM, consider using SQLAlchemySessionContextFactory instead.


engine (Engine) – A configured SQLAlchemy engine.

class baseplate.clients.sqlalchemy.SQLAlchemySessionContextFactory(engine, name='sqlalchemy')[source]

SQLAlchemy ORM session context factory.

This factory will attach a new SQLAlchemy sqlalchemy.orm.session.Session to an attribute on the RequestContext. All cursor (query) execution will automatically record diagnostic information.

The session will be automatically closed, but not committed or rolled back, at the end of each request.

See also

The session is part of the high-level SQLAlchemy ORM API. If you want to do raw queries, consider using SQLAlchemyEngineContextFactory instead.


engine (Engine) – A configured SQLAlchemy engine.

Runtime Metrics

In addition to request-level metrics reported through spans, this wrapper reports connection pool statistics periodically via the Prometheus Exporter system. All metrics are tagged with client, the name given to configure_context() when registering this context factory.

The following metrics are reported:


The size limit for the connection pool.


How many connections have been established but are sitting available for use in the connection pool.


How many connections have been established and are currently checked out and being used.


How many connections beyond the pool size are currently being used. See sqlalchemy.pool.QueuePool for more information.

Changed in version 2.0: Runtime metrics were changed to use tags.