Introduction to the ZODB (by Michel Pelletier)

In this article, we cover the very basics of the Zope Object Database (ZODB) for Python programmers. This short article documents almost everything you need to know about using this powerful object database in Python. In a later article, I will cover some of the more advanced features of ZODB for Python programmers.

ZODB is a database for Python objects that comes with Zope. If you’ve ever worked with a relational database, like PostgreSQL, MySQL, or Oracle, than you should be familiar with the role of a database. It’s a long term or short term storage for your application data.

For many tasks, relational databases are clearly a good solution, but sometimes relational databases don’t fit well with your object model. If you have lots of different kinds of interconnected objects with complex relationships, and changing schemas then ZODB might be worth giving a try.

A major feature of ZODB is transparency. You do not need to write any code to explicitly read or write your objects to or from a database. You just put your persistent objects into a container that works just like a Python dictionary. Everything inside this dictionary is saved in the database. This dictionary is said to be the “root” of the database. It’s like a magic bag; any Python object that you put inside it becomes persistent.

Actually there are a few restrictions on what you can store in the ZODB. You can store any objects that can be “pickled” into a standard, cross-platform serial format. Objects like lists, dictionaries, and numbers can be pickled. Objects like files, sockets, and Python code objects, cannot be stored in the database because they cannot be pickled. For more information on “pickling”, see the Python pickle module documentation at

A Simple Example

The first thing you need to do to start working with ZODB is to create a “root object”. This process involves first opening a connection to a “storage”, which is the actual back-end that stores your data.

ZODB supports many pluggable storage back-ends, but for the purposes of this article I’m going to show you how to use the ‘FileStorage’ back-end storage, which stores your object data in a file. Other storages include storing objects in relational databases, Berkeley databases, and a client to server storage that stores objects on a remote storage server.

To set up a ZODB, you must first install it. ZODB comes with Zope, so the easiest way to install ZODB is to install Zope and use the ZODB that comes with your Zope installation. For those of you who don’t want all of Zope, but just ZODB, see the instructions for downloading StandaloneZODB from the ZODB web page.

StandaloneZODB can be installed into your system’s Python libraries using the standard ‘distutils’ Python module.

After installing ZODB, you can start to experiment with it right from the Python command line interpreter. For example, try the following python code in your interpreter:

>>> from ZODB import FileStorage, DB
>>> storage = FileStorage.FileStorage('mydatabase.fs')
>>> db = DB(storage)
>>> connection =
>>> root = connection.root()

Here, you create storage and use the ‘mydatabse.fs’ file to store the object information. Then, you create a database that uses that storage.

Next, the database needs to be “opened” by calling the ‘open()’ method. This will return a connection object to the database. The connection object then gives you access to the ‘root’ of the database with the ‘root()’ method.

The ‘root’ object is the dictionary that holds all of your persistent objects. For example, you can store a simple list of strings in the root object:

>>> root['employees'] = ['Mary', 'Jo', 'Bob']

Now, you have changed the persistent database by adding a new object, but this change is so far only temporary. In order to make the change permanent, you must commit the current transaction:

>>> import transaction
>>> transaction.commit()

Transactions group of lots of changes in one atomic operation. In a later article, I’ll show you how this is a very powerful feature. For now, you can think of committing transactions as “checkpoints” where you save the changes you’ve made to your objects so far. Later on, I’ll show you how to abort those changes, and how to undo them after they are committed.

Now let’s find out if our data was actually saved. First close the database connection:

>>> connection.close()

Then quit Python. Now start the Python interpreter up again, and connect to the database you just created:

>>> from ZODB import FileStorage, DB
>>> storage = FileStorage.FileStorage('mydatabase.fs')
>>> db = DB(storage)
>>> connection =
>>> root = connection.root()

Now, let’s see what’s in the root:

>>> root.items()
[('employees', ['Mary', 'Jo', 'Bob'])]

There’s your list. If you had used a relational database, you would have had to issue a SQL query to save even a simple Python list like the above example. You would have also needed some code to convert a SQL query back into the list when you wanted to use it again. You don’t have to do any of this work when using ZODB. Using ZODB is almost completely transparent, in fact, ZODB based programs often look suspiciously simple!

Keep in mind that ZODB’s persistent dictionary is just the tip of the persistent iceberg. Persistent objects can have attributes that are themselves persistent. In other words, even though you may have only one or two “top level” persistent objects as values in the persistent dictionary, you can still have thousands of sub-objects below them. This is, in fact, how Zope does it. In Zope, there is only one top level object that is the root “application” object for all other objects in Zope.

Detecting Changes

One thing that makes ZODB so easy to use is that it doesn’t require you to keep track of your changes. All you have to do is to make changes to persistent objects and then commit a transaction. Anything that has changed will be stored in the database.

There is one exception to this rule when it comes to simple mutable Python types like lists and dictionaries. If you change a list or dictionary that is already stored in the database, then the change will not take effect. Consider this example:

>>> root['employees'].append('Bill')
>>> transaction.commit()

You would expect this to work, but it doesn’t. The reason for this is that ZODB cannot detect that the ‘employees’ list changed. The ‘employees’ list is a mutable object that does not notify ZODB when it changes.

There are a couple of very simple ways around this problem. The simplest is to re-assign the changed object:

>>> employees = root['employees']
>>> employees.append('Bill')
>>> root['employees'] = employees
>>> transaction.commit()

Here, you move the employees list to a local variable, change the list, and then reassign the list back into the database and commit the transaction. This reassignment notifies the database that the list changed and needs to be saved to the database.

Later in this article, we’ll show you another technique for notifying the ZODB that your objects have changed. Also, in a later article, we’ll show you how to use simple, ZODB-aware list and dictionary classes that come pre-packaged with ZODB for your convenience.

Persistent Classes

The easiest way to create mutable objects that notify the ZODB of changes is to create a persistent class. Persistent classes let you store your own kinds of objects in the database. For example, consider a class that represents a employee:

import ZODB
from Persistence import Persistent

class Employee(Persistent):

    def setName(self, name): = name

To create a persistent class, simply subclass from ‘Persistent.Persistent’. Because of some special magic that ZODB does, you must first import ZODB before you can import Persistent. The ‘Persistent’ module is actually created when you import ‘ZODB’.

Now, you can put Employee objects in your database:

>>> employees=[]
>>> for name in ['Mary', 'Joe', 'Bob']:
...     employee = Employee()
...     employee.setName(name)
...     employees.append(employee)
>>> root['employees']=employees
>>> transaction.commit()

Don’t forget to call ‘commit()’, so that the changes you have made so far are committed to the database, and a new transaction is begun.

Now you can change your employees and they will be saved in the database. For example you can change Bob’s name to “Robert”:

>>> bob=root['employees'][2]
>>> bob.setName('Robert')
>>> transaction.commit()

You can even change attributes of persistent instaces without calling methods:

>>> bob=root['employees'][2]
>>> bob._coffee_prefs=('Cream', 'Sugar')
>>> transaction.commit()

It doesn’t matter whether you change an attribute directly, or whether it’s changed by a method. As you can tell, all of the normal Python language rules still work as you’d expect.

Mutable Attributes

Earlier you saw how ZODB can’t detect changes to normal mutable objects like Python lists. This issue still affects you when using persistent instances. This is because persistent instances can have attributes which are normal mutable objects. For example, consider this class:

class Employee(Persistent):

    def __init__(self):
        self.tasks = []

    def setName(self, name): = name

    def addTask(self, task):

When you call ‘addTask’, the ZODB won’t know that the mutable attribute ‘self.tasks’ has changed. As you saw earlier, you can reassign ‘self.tasks’ after you change it to get around this problem. However, when you’re using persistent instances, you have another choice. You can signal the ZODB that your instance has changed with the ‘_p_changed’ attribute:

class Employee(Persistent):

    def addTask(self, task):
        self._p_changed = 1

To signal that this object has change, set the ‘_p_changed’ attribute to 1. You only need to signal ZODB once, even if you change many mutable attributes.

The ‘_p_changed’ flag leads us to one of the few rules of you must follow when creating persistent classes: your instances cannot have attributes that begin with ‘_p_’, those names are reserved for use by the ZODB.

A Complete Example

Here’s a complete example program. It builds on the employee examples used so far:

from ZODB import DB
from ZODB.FileStorage import FileStorage
from ZODB.PersistentMapping import PersistentMapping
from Persistence import Persistent
import transaction

class Employee(Persistent):
    """An employee"""

    def __init__(self, name, manager=None):

# setup the database

# get the employees mapping, creating an empty mapping if
# necessary
if not root.has_key("employees"):
    root["employees"] = {}

def listEmployees():
    if len(employees.values())==0:
        print "There are no employees."
    for employee in employees.values():
        print "Name: %s" %
        if employee.manager is not None:
            print "Manager's name: %s" %

def addEmployee(name, manager_name=None):
    if employees.has_key(name):
        print "There is already an employee with this name."
    if manager_name:
        except KeyError:
            print "No such manager"
        employees[name]=Employee(name, manager)

    root['employees'] = employees  # reassign to change
    print "Employee %s added." % name

if __name__=="__main__":
    while 1:
        choice=raw_input("Press 'L' to list employees, 'A' to add"
                         "an employee, or 'Q' to quit:")
        if choice=="l":
        elif choice=="a":
            name=raw_input("Employee name:")
            manager_name=raw_input("Manager name:")
            addEmployee(name, manager_name)
        elif choice=="q":

    # close database

This program demonstrates a couple interesting things. First, this program shows how persistent objects can refer to each other. The ‘self.manager’ attribute of ‘Employee’ instances can refer to other ‘Employee’ instances. Unlike a relational database, there is no need to use indirection such as object ids when referring from one persistent object to another. You can just use normal Python references. In fact, you can even use circular references.

A final trick used by this program is to look for a persistent object and create it if it is not present. This allows you to just run this program without having to run a setup script to build the database first. If there is not database present, the program will create one and initialize it.


ZODB is a very simple, transparent object database for Python that is a freely available component of the Zope application server. As these examples illustrate, only a few lines of code are needed to start storing Python objects in ZODB, with no need to write SQL queries. In the next article on ZODB, we’ll show you some more advanced techniques for using ZODB, like using ZODB’s distributed object protocol to distribute your persistent objects across many machines.

ZODB Resources