http://en.wikipedia.org/wiki/SQLAlchemy
Libraries that bridge the gap between procedural code and SQL are known as object-relational mappers, or ORMs. ORMs typically represent database records as instances of a particular class. In order to represent 50 records, you would need 50 instances of a class, with the state of each instance reflecting the names, types and values of the columns in that record.
There are two basic paradigms for passing data between the object-oriented data structures and the database, both of which were described by Martin Fowler. In the first paradigm, known as Active Record, each instance is tied directly to a row in the database, and the class itself (as well as each object) is responsible for ensuring that the data is saved to the database. In other words, Active Record requires that you create a single class, and that it handles both sides of the object-relational divide. The Active Record class in Ruby on Rails is (not surprisingly) an implementation of this paradigm and provides a great deal of power and flexibility.
A second paradigm is known as Data Mapper, and it requires the use of three different object classes: a class that represents the data itself at the object level, a class that represents the database table and a "mapper" object that acts as a go-between, ensuring that the object and relational parts of the system are appropriately synchronized.
An excellent and popular example of the Data Mapper paradigm can be found in the SQLAlchemy project. SQLAlchemy has been around for a number of years already, and makes it possible to work with relational databases flexibly from within your Python program, without having to write any SQL.
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