Two great tastes that taste great together.

Use RedPanda to add simple pandas integration into your declarative models.

pip install redpanda

Create a session from a SQLAlchemy engine:

import redpanda

engine = redpanda.create_engine("sqlite://")
# => Engine(sqlite://)

Session = redpanda.orm.sessionmaker(bind=engine)
session = Session()
# => <sqlalchemy.orm.session.Session>

Use the frame() method of RedPanda queries to return a DataFrame representation of the results instead of a collection of models.

query = session.query(MyModel)
# => <redpanda.orm.Query>

query.frame()
# => <pandas.DataFrame>

The frame() method that wraps the pandas.read_sql() function into a dialect-agnostic class-method for declarative SQLAlchemy models and can accept the same keyword arguments as pandas.read_sql():

query = session.query(MyModel).filter_by(my_attr="my_val")

query.frame(index_col="time")

Additionally, a within() method is added to SQLAlchemy's InstrumentedAttribute class that accepts a pandas Index object:

index = pandas.period_range("2016-11-01", "2016-11-30", freq="W")
query = session.query(MyModel).filter(MyModel.timestamp.within(index))