This book shows you how to translate essential SQL concepts into the Python language so they can be applied outside the database environment. A database includes features for access controls, persistence, and concurrent updates, none of which may be needed for an extract-transform-load pipeline. This helps restate the SQL design concepts into Python applications that are faster and simpler because they don't rely on a database.

The ideas also apply to data analytic problems where the SQL GROUP-BY is a helpful design pattern. This book provides concrete examples of expressing the concept in Python instead of SQL.