ⓘ SQLAlchemy

                                     

ⓘ SQLAlchemy

SQLAlchemys philosophy is that relational databases behave less like object collections as the scale gets larger and performance starts being a concern, while object collections behave less like tables and rows as more abstraction is designed into them. For this reason it has adopted the data mapper pattern similar to Hibernate for Java rather than the active record pattern used by a number of other object-relational mappers. However, optional plugins allow users to develop using declarative syntax.

                                     

1. History

SQLAlchemy was first released in February 2006 and has quickly become one of the most widely used object-relational mapping tools in the Python community, alongside Djangos ORM.

                                     

2. Example

The following example represents an n-to-1 relationship between movies and their directors. It is shown how user-defined Python classes create corresponding database tables, how instances with relationships are created from either side of the relationship, and finally how the data can be queried - illustrating automatically-generated SQL queries for both lazy and eager loading.

Schema definition

Creating two Python classes and according database tables in the DBMS:

Data insertion

One can insert a director-movie relationship via either entity:

Querying

SQLAlchemy issues the following query to the DBMS omitting aliases:

The output:

Setting lazy=True default instead, SQLAlchemy would first issue a query to get the list of movies and only when needed lazy for each director a query to get the name of the according director: