Motivation

Object Relational Mapping (ORM)

ORM interfaces are a common way (especially in Python) of interacting with relational databases and there are some well-known Python ORMs (e.g., SQLAlchemy and Peewee). Fundamentally all ORMs provide a way of matching rows in a database table (or database view) to Python objects whose member variables correspond to the fields of the database table.

As well as mapping table rows to program objects, ORMs also provide facilities for building SQL queries using high-level primitives; rather than dealing with raw SQL strings.

An ORM Interface for Clingo

While the Clingo Python API is both extensive and flexible, however, it is also fairly low-level when it comes to getting data into, and out of, the solver. As a result there is typically a reasonable amount of boilerplate code that needs to be written in order to carry out even simple translations to and from Clingo. Furthermore without strong discipline such code can become interspersed throughout the Python code base.

This can be especially problematic as the ASP program evolves. Keeping the corresponding Python translation code up to date can be both cumbersome and error prone. For example, simply swapping the position of a parameter in a predicate and accidentally failing to update the corresponding Python code might not cause an immediate error in the program, but instead could cause subtle errors that are difficult to detect and debug.

An ORM interface can help to alleviate these problems. The ORM definitions that map ASP predicates to Python objects are defined in a single location and the ASP to Python translations are all generated automatically from the ORM class definitions.

In short, a Clingo ORM interface can make it easier to integrate Clingo and Python and to write Python code that is more readable and easier to maintain.