Peewee Cookbook

Below are outlined some of the ways to perform typical database-related tasks with peewee.

Examples will use the following models:

from peewee import *

class User(Model):
    username = CharField()

class Tweet(Model):
    user = ForeignKeyField(User, related_name='tweets')
    message = TextField()
    created_date = DateTimeField(
    is_published = BooleanField(default=True)

Database and Connection Recipes

Creating a database connection and tables

While it is not necessary to explicitly connect to the database before using it, managing connections explicitly is a good practice. This way if the connection fails, the exception can be caught during the “connect” step, rather than some arbitrary time later when a query is executed.

>>> database = SqliteDatabase('stats.db')
>>> database.connect()

To use this database with your models, specify it in an inner “Meta” class:

class MyModel(Model):
    some_field = CharField()

    class Meta:
        database = database

It is possible to use multiple databases (provided that you don’t try and mix models from each):

>>> custom_db = SqliteDatabase('custom.db')

>>> class CustomModel(Model):
...     whatev = CharField()
...     class Meta:
...         database = custom_db

>>> custom_db.connect()
>>> CustomModel.create_table()

Best practice: define a base model class that points at the database object you wish to use, and then all your models will extend it:

custom_db = SqliteDatabase('custom.db')

class CustomModel(Model):
    class Meta:
        database = custom_db

class User(CustomModel):
    username = CharField()

class Tweet(CustomModel):
    # etc, etc


Remember to specify a database in a model class (or its parent class), otherwise peewee will fall back to a default sqlite database named “peewee.db”.

Using with Postgresql

Point models at an instance of PostgresqlDatabase.

psql_db = PostgresqlDatabase('my_database', user='code')

class PostgresqlModel(Model):
    """A base model that will use our Postgresql database"""
    class Meta:
        database = psql_db

class User(PostgresqlModel):
    username = CharField()
    # etc, etc

Using with MySQL

Point models at an instance of MySQLDatabase.

mysql_db = MySQLDatabase('my_database', user='code')

class MySQLModel(Model):
    """A base model that will use our MySQL database"""
    class Meta:
        database = mysql_db

class User(MySQLModel):
    username = CharField()
    # etc, etc

# when you're ready to start querying, remember to connect

Multi-threaded applications

Some database engines may not allow a connection to be shared across threads, notably sqlite. If you would like peewee to maintain a single connection per-thread, instantiate your database with threadlocals=True (recommended):

concurrent_db = SqliteDatabase('stats.db', threadlocals=True)

The above implementation stores connection state in a thread local and will only use that connection for a given thread. Pysqlite can share a connection across threads, so if you would prefer to reuse a connection in multiple threads:

native_concurrent_db = SqliteDatabase('stats.db', check_same_thread=False)

Deferring initialization

Sometimes the database information is not known until run-time, when it might be loaded from a configuration file/etc. In this case, you can “defer” the initialization of the database by passing in None as the database_name.

deferred_db = SqliteDatabase(None)

class SomeModel(Model):
    class Meta:
        database = deferred_db

If you try to connect or issue any queries while your database is uninitialized you will get an exception:

>>> deferred_db.connect()
Exception: Error, database not properly initialized before opening connection

To initialize your database, you simply call the init method with the database_name and any additional kwargs:

database_name = raw_input('What is the name of the db? ')

Creating, Reading, Updating and Deleting

Creating a new record

You can use the Model.create() method on the model:

>>> User.create(username='Charlie')
<__main__.User object at 0x2529350>

This will INSERT a new row into the database. The primary key will automatically be retrieved and stored on the model instance.

Alternatively, you can build up a model instance programmatically and then save it:

>>> user = User()
>>> user.username = 'Charlie'

See also, Model.insert() and InsertQuery

Updating existing records

Once a model instance has a primary key, any attempt to re-save it will result in an UPDATE rather than another INSERT:


If you want to update multiple records, issue an UPDATE query. The following example will update all Entry objects, marking them as “published”, if their pub_date is less than today’s date.

>>> update_query = Tweet.update(is_published=True).where(Tweet.creation_date <
>>> update_query.execute()
4 # <--- number of rows updated

For more information, see the documentation on UpdateQuery.

Deleting a record

To delete a single model instance, you can use the Model.delete_instance() shortcut:

>>> user = User.get( == 1)
>>> user.delete_instance()
1 # <--- number of rows deleted

>>> User.get( == 1)
UserDoesNotExist: instance matching query does not exist:
SQL: SELECT t1."id", t1."username" FROM "user" AS t1 WHERE t1."id" = ?

To delete an arbitrary group of records, you can issue a DELETE query. The following will delete all Tweet objects that are a year old.

>>> delete_query = Tweet.delete().where(Tweet.pub_date < one_year_ago)
>>> delete_query.execute()
7 # <--- number of rows deleted

For more information, see the documentation on DeleteQuery.

Selecting a single record

You can use the Model.get() method to retrieve a single instance matching the given query.

This method is a shortcut that calls with the given query, but limits the result set to 1. Additionally, if no model matches the given query, a DoesNotExist exception will be raised.

>>> User.get( == 1)
<__main__.Blog object at 0x25294d0>

>>> User.get( == 1).username

>>> User.get(User.username == 'Charlie')
<__main__.Blog object at 0x2529410>

>>> User.get(User.username == 'nobody')
UserDoesNotExist: instance matching query does not exist:
SQL: SELECT t1."id", t1."username" FROM "user" AS t1 WHERE t1."username" = ?
PARAMS: ['nobody']

For more information see notes on SelectQuery and Querying API in general.

Selecting multiple records

To simply get all instances in a table, call the method:

>>> for user in
...     print user.username
Peewee Herman

When you iterate over a SelectQuery, it will automatically execute it and start returning results from the database cursor. Subsequent iterations of the same query will not hit the database as the results are cached.

Another useful note is that you can retrieve instances related by ForeignKeyField by iterating. To get all the related instances for an object, you can query the related name. Looking at the example models, we have Users and Tweets. Tweet has a foreign key to User, meaning that any given user may have 0..n tweets. A user’s related tweets are exposed using a SelectQuery, and can be iterated the same as any other SelectQuery:

>>> for tweet in user.tweets:
...     print tweet.message
hello world
this is fun
look at this picture of my food

The tweets attribute is just another select query and any methods available to SelectQuery are available:

>>> for tweet in user.tweets.order_by(Tweet.created_date.desc()):
...     print tweet.message
look at this picture of my food
this is fun
hello world

Filtering records

You can filter for particular records using normal python operators.

>>> user = User.get(User.username == 'Charlie')
>>> for tweet in == user, Tweet.is_published == True):
...     print '%s: %s (%s)' % (tweet.user.username, tweet.message)
Charlie: hello world
Charlie: this is fun

>>> for tweet in < datetime.datetime(2011, 1, 1)):
...     print tweet.message, tweet.created_date
Really old tweet 2010-01-01 00:00:00

You can also filter across joins:

>>> for tweet in == 'Charlie'):
...     print tweet.message
hello world
this is fun
look at this picture of my food

If you want to express a complex query, use parentheses and python’s “or” and “and” operators:

...     (User.username == 'Charlie') |
...     (User.username == 'Peewee Herman')
... )

Check out the table of query operations to see what types of queries are possible.


A lot of fun things can go in the where clause of a query, such as:

  • a field expression, e.g. User.username == 'Charlie'
  • a function expression, e.g. fn.Lower(fn.Substr(User.username, 1, 1)) == 'a'
  • a comparison of one column to another, e.g. Employee.salary < (Employee.tenure * 1000) + 40000

You can also nest queries, for example tweets by users whose username starts with “a”:

# the "<<" operator signifies an "IN" query
    Tweet.user <<, 1, 1)) == 'a')


If you are already familiar with Django’s ORM, you can use the “double underscore” syntax using the SelectQuery.filter() method:

>>> for tweet in Tweet.filter(user__username='Charlie'):
...     print tweet.message
hello world
this is fun
look at this picture of my food

To perform OR lookups, use the special DQ object:

>>> User.filter(DQ(username='Charlie') | DQ(username='Peewee Herman'))


The Zen of Python says “There should be one– and preferably only one –obvious way to do it.” The django-style filtering is supported for backwards compatibility with 1.0, so if you can, its probably best not to use it.

Check the docs for some more example queries.

Sorting records

>>> for t in
...     print t.pub_date
2010-01-01 00:00:00
2011-06-07 14:08:48
2011-06-07 14:12:57

>>> for t in
...     print t.pub_date
2011-06-07 14:12:57
2011-06-07 14:08:48
2010-01-01 00:00:00

You can also order across joins. Assuming you want to order tweets by the username of the author, then by created_date:

>>> qry =, Tweet.created_date.desc())

Paginating records

The paginate method makes it easy to grab a “page” or records – it takes two parameters, page_number, and items_per_page:

>>> for tweet in, 10):
...     print tweet.message
tweet 10
tweet 11
tweet 12
tweet 13
tweet 14
tweet 15
tweet 16
tweet 17
tweet 18
tweet 19

Counting records

You can count the number of rows in any select query:

>>> > 50).count()

Iterating over lots of rows

To limit the amount of memory used by peewee when iterating over a lot of rows (i.e. you may be dumping data to csv), use the iterator() method on the QueryResultWrapper. This method allows you to iterate without caching each model returned, using much less memory when iterating over large result sets:

# let's assume we've got 1M stat objects to dump to csv
stats_qr =

# our imaginary serializer class
serializer = CSVSerializer()

# loop over all the stats and serialize
for stat in stats_qr.iterator():

For simple queries you can see further speed improvements by using the SelectQuery.naive() query method. See the documentation for details on this optimization.

stats_query = # note we are calling "naive()"
stats_qr = stats_query.execute()

for stat in stats_qr.iterator():

Performing atomic updates

>>> Stat.update(counter=Stat.counter + 1).where(Stat.url == request.url)

Aggregating records

Suppose you have some users and want to get a list of them along with the count of tweets in each. First I will show you the shortcut:

query =

This is equivalent to the following:

query =
    User, fn.Count('count')

The resulting query will return User objects with all their normal attributes plus an additional attribute ‘count’ which will contain the number of tweets. By default it uses an inner join if the foreign key is not nullable, which means blogs without entries won’t appear in the list. To remedy this, manually specify the type of join to include users with 0 tweets:

query =, JOIN_LEFT_OUTER).annotate(Tweet)

You can also specify a custom aggregator:

query =, fn.Max(Tweet.created_date).alias('latest'))

Let’s assume you have a tagging application and want to find tags that have a certain number of related objects. For this example we’ll use some different models in a Many-To-Many configuration:

class Photo(Model):
    image = CharField()

class Tag(Model):
    name = CharField()

class PhotoTag(Model):
    photo = ForeignKeyField(Photo)
    tag = ForeignKeyField(Tag)

Now say we want to find tags that have at least 5 photos associated with them:

>>> > 5)

Yields the following:

SELECT t1."id", t1."name"
FROM "tag" AS t1
INNER JOIN "phototag" AS t2 ON t1."id" = t2."tag_id"
INNER JOIN "photo" AS t3 ON t2."photo_id" = t3."id"
GROUP BY t1."id", t1."name"
HAVING Count(t3."id") > 5

Suppose we want to grab the associated count and store it on the tag:

...     Tag, fn.Count('count')
... ).join(PhotoTag).join(Photo).group_by(Tag).having(fn.Count( > 5)

SQL Functions, Subqueries and “Raw expressions”

Suppose you need to want to get a list of all users whose username begins with “a”. There are a couple ways to do this, but one method might be to use some SQL functions like LOWER and SUBSTR. To use arbitrary SQL functions, use the special fn() function to construct queries:

# select the users' id, username and the first letter of their username, lower-cased
query =, fn.Lower(fn.Substr(User.username, 1, 1)).alias('first_letter'))

# alternatively we could select only users whose username begins with 'a'
a_users =, 1, 1)) == 'a')

>>> for user in a_users:
...    print user.username

There are times when you may want to simply pass in some arbitrary sql. You can do this using the special R class. One use-case is when referencing an alias:

# we'll query the user table and annotate it with a count of tweets for
# the given user
query =, fn.Count('ct')).join(Tweet).group_by(User)

# now we will order by the count, which was aliased to "ct"
query = query.order_by(R('ct'))

Working with transactions

Context manager

You can execute queries within a transaction using the transaction context manager, which will issue a commit if all goes well, or a rollback if an exception is raised:

db = SqliteDatabase(':memory:')

with db.transaction():
    user.delete_instance(recursive=True) # delete user and associated tweets


Similar to the context manager, you can decorate functions with the commit_on_success decorator:

db = SqliteDatabase(':memory:')

def delete_user(user):

Changing autocommit behavior

By default, databases are initialized with autocommit=True, you can turn this on and off at runtime if you like. The behavior below is roughly the same as the context manager and decorator:


If you would like to manually control every transaction, simply turn autocommit off when instantiating your database:

db = SqliteDatabase(':memory:', autocommit=False)


Non-integer Primary Keys and other Tricks

Non-integer primary keys

If you would like use a non-integer primary key (which I generally don’t recommend), you can override the default column_class of the PrimaryKeyField:

from peewee import *

class UUIDModel(Model):
    id = CharField(primary_key=True)

inst = UUIDModel(id=str(uuid.uuid4())) # <-- WRONG!!  this will try to do an update # <-- CORRECT

# to update the instance after it has been saved once


Any foreign keys to a model with a non-integer primary key will have the ForeignKeyField use the same underlying storage type as the primary key they are related to.

See full documentation on non-integer primary keys.

Bulk loading data or manually specifying primary keys

Sometimes you do not want the database to automatically generate a primary key, for instance when bulk loading relational data. To handle this on a “one-off” basis, you can simply tell peewee to turn off auto_increment during the import:

data = load_user_csv() # load up a bunch of data

User._meta.auto_increment = False # turn off auto incrementing IDs
with db.transaction():
    for row in data:
        u = User(id=row[0], username=row[1]) # <-- force peewee to insert row

User._meta.auto_increment = True

If you always want to have control over the primary key, simply do not use the PrimaryKeyField type:

class User(BaseModel):
    id = IntegerField(primary_key=True)
    username = CharField()

>>> u = User.create(id=999, username='somebody')
>>> User.get(User.username == 'somebody').id

Introspecting databases

If you’d like to generate some models for an existing database, you can try out the database introspection tool “pwiz” that comes with peewee.


python my_postgresql_database

It works with postgresql, mysql and sqlite:

python test.db --engine=sqlite

pwiz will generate code for:

  • database connection object
  • a base model class to use this connection
  • models that were introspected from the database tables

The generated code is written to stdout.

Schema migrations

Currently peewee does not have support for automatic schema migrations.