The PyData stack has been described as “unreasonably effective,” empowering its users to glean insights and analyze moderate amounts of data with a high level of flexibility and excellent visualization. The large-scale, production data stack using a query engine like Trino sits on the other side of the world, capable of handling petabytes and exabytes, but perhaps not integrating as seamlessly with the Python ecosystem as one would hope. SQL has been a means of bridging this gap, but we...
