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About ORM

What is it

The Object Relational Membrane is a Python package that provides similar functionality as an Object Relational Layer like EJB and other Persistence Storage Systems. It is an attempt to create an interface between Object Oriented thinking and Relational Database Systems, that is small enough to understand it with relative ease but powerful enough to fully handle standard situations. It is a membrane in the sense, that it is a very thin layer. It does not really attempt to be transparent, it is meant to be opaque. Some basic knowledge of both the Object Oriented and the Relational concept is required to use it. That means you will have to know what a class is and understand the basics of SQL.

At this point in time there are database adapters for PostgreSQL, MySQL, Firebird and Gadfly.

What problem does ORM address?

The problem is, that you think Object Orientated when you write a Python program, but when it comes to storing your data in an efficient manner (i.e. in an RDBMS) you have to switch over to another mode of data representation: the one of the Relational Database. There are several options to prevent this: for one thing, you can change to another storage technology. Most people seem to prefer RDBMSs, though, because they provide great performance and reliability and several very high quality products are freely available (free as in free speech and as in free beer). There are several great tools available for Python that allow you to store Python objects in an RDBMS. However, the ones I found do not reflect the data structures of my Python program as SQL data structures (i.e. tables). This is why I wrote ORM.

How does it work?

An Object Relational Layer or Persistence Storage does in essence one thing: it intercepts changes to Python objects and creates SQL statements to modify the database according to these changes. Also it provides functions to store objects, retrieve objects and delete them. This is just what ORM does. But using it, you will have to create a regular SQL table structure. This may be a disadvantage because

  • you need to know your basic SQL
  • since ORM is opaque rather than transparent you sometimes have to keep in mind that you're actually using SQL

but also has major benefits

  • your program will be able to share the database with other programs that use SQL but are not written in Python and do not use ORM (why ever that happened)
  • you can use PostgreSQL's advanced features like constraints, indexes etc.

ORM wants to be a bridge between Object Oriented and Relational concepts. It does this, by providing the means to

  • describe a Relational design using Object Oriented constructs and
  • let you use the data structure you described like any other Python class and its objects.

An example tells more than 1000 words

Data definition

You want to write a program to store some data on your friends in a database including a picture. The SQL tables look like this (for the PostgreSQL server):

       width INTEGER,
       height INTEGER,
       data BYTEA

       name VARCHAR(100),
       birthday TIMESTAMP,
       image_id INTEGER,
       FOREIGN KEY (image_id) REFERENCES image (id)

Two tables: one for the folks one for the images. The person table's image_id column contains a reference to a row in the image table. This is sometimes referred to as a 'one to one relationship'. The corresponding Python code looks like this:

from orm.dbclass import dbclass
from orm.relationships import one2one
from orm.columns import *

# we have to define the image class first, because we refer to it 
# in the person class' definition

class image(dbclass):
       id = serial() # use PostgreSQL's SERIAL datatype
       width = integer(),
       height = integer(),
       data = bytea() # again, a PostgreSQL specific type

class person(dbclass):
       __primary_key__ = "name"
       name = varchar(100)
       birthday = timestamp()
       image = one2one(image)

For each of our tables we create a class, of which each instance represents one of the table's rows. Since Python is loosely typed there is no language construct to define the attributes of a class (which refer to the table's columns). To describe the data structure of the RDBMS' tables we use instances of Python classes. There is a datatype class for each datatype the SQL backends support. Also there is orm.relationships.relationship, which is the parent of a number of classes that describe table relationships as one2one, one2many and many2many.

Creating records

We can now create objects of our classes as if they were normal Python classes:

swen = person(name="Swen", birthday="1977-06-13")

We have to use named parameters here, so dbclass' constructor knows what to make of each of them. To create a database record we insert the variable swen into the database:

from orm.datasource import datasource

# connect to the database
ds = datasource("dbname=test") # a usual PostgreSQL dsn. See
                               # programmer's manual

# store swen in the db

This will yield the following SQL command to be executed on the test database:

INSERT INTO person (name, birthday) VALUES ('swen', '1977-06-13');

Note that ORM will always state which columns to insert and will never use SELECT * FROM ... so you can safely omit columns in your Python code that you have defined in your database.

Relationship example

Let's store an image and associate it with Swen's record:

# get PIL stuff, load image from filesystem...
swen_pic = image(width=img_width, height=img_width, data=img_data)

# store the image in the database

# assign the image to swen
swen.image = swen_pic

This last line might create an SQL statement like:

UPDATE person SET image_id=1 WHERE id=23213;

and assign the image to swen on SQL level. It is important to commit changes to the database if you want them to take effect:


Querying the database

Ok. how do I get stuff back?

from orm2 import sql

result =, sql.where("name = ", sql.string_literal(name)))
swen = result.fetchone()

This code makes use of orm2's sql module. This module contains classes for representing SQL in Python. The where class used above will turn into an SQL WHERE clause with name as an SQL literal. So the query above will look like:

SELECT name, birthday, image_id FROM person WHERE name = 'Swen'