PostgreSQL interface

PostgreSQL 1 is a powerful and well-established open source database system. It can be connected to the getML engine using the function connect_postgres(). But first, make sure your database is running, you have the corresponding hostname, port as well as your user name and password ready, and you can reach it from via your command line.

Import from PostgreSQL

By selecting an existing table from your database in the from_db() classmethod, you can create a new DataFrame containing all its data. Alternatively you can use the read_db() and read_query() methods to replace the content of the current DataFrame instance or append further rows based on either a table or a specific query.

Export to PostgreSQL

You can also write your results back into the PostgreSQL database. If you provide a name for the destination table in getml.pipeline.Pipeline.transform(), the features generated from your raw data will be written back. Passing it into getml.pipeline.Pipeline.predict() generates predictions of the target variables to new, unseen data and stores the result into the corresponding table.