We’ll be building a simple twitter-like site. The source code for the example
can be found in the
examples/twitter directory. You can also browse the
on github. There is also an example blog app if that’s more
to your liking, however it is not covered in this guide.
The example app uses the flask web framework which is very easy to get started with. If you don’t have flask already, you will need to install it to run the example:
pip install flask
Running the example¶
After ensuring that flask is installed,
cd into the twitter example
directory and execute the
The example app will be accessible at http://localhost:5000/
Diving into the code¶
For simplicity all example code is contained within a single module,
examples/twitter/app.py. For a guide on structuring larger Flask apps with
peewee, check out Structuring Flask Apps.
In the spirit of the popular web framework Django, peewee uses declarative model definitions. If you’re not familiar with Django, the idea is that you declare a model class for each table. The model class then defines one or more field attributes which correspond to the table’s columns. For the twitter clone, there are just three models:
Represents a user account and stores the username and password, an email address for generating avatars using gravatar, and a datetime field indicating when that account was created.
This is a utility model that contains two foreign-keys to the User model and stores which users follow one another.
Analogous to a tweet. The Message model stores the text content of the tweet, when it was created, and who posted it (foreign key to User).
If you like UML, these are the tables and relationships:
In order to create these models we need to instantiate a
SqliteDatabase object. Then we define our model classes, specifying
the columns as
Field instances on the class.
# create a peewee database instance -- our models will use this database to # persist information database = SqliteDatabase(DATABASE) # model definitions -- the standard "pattern" is to define a base model class # that specifies which database to use. then, any subclasses will automatically # use the correct storage. class BaseModel(Model): class Meta: database = database # the user model specifies its fields (or columns) declaratively, like django class User(BaseModel): username = CharField(unique=True) password = CharField() email = CharField() join_date = DateTimeField() # this model contains two foreign keys to user -- it essentially allows us to # model a "many-to-many" relationship between users. by querying and joining # on different columns we can expose who a user is "related to" and who is # "related to" a given user class Relationship(BaseModel): from_user = ForeignKeyField(User, backref='relationships') to_user = ForeignKeyField(User, backref='related_to') class Meta: # `indexes` is a tuple of 2-tuples, where the 2-tuples are # a tuple of column names to index and a boolean indicating # whether the index is unique or not. indexes = ( # Specify a unique multi-column index on from/to-user. (('from_user', 'to_user'), True), ) # a dead simple one-to-many relationship: one user has 0..n messages, exposed by # the foreign key. because we didn't specify, a users messages will be accessible # as a special attribute, User.messages class Message(BaseModel): user = ForeignKeyField(User, backref='messages') content = TextField() pub_date = DateTimeField()
Note that we create a BaseModel class that simply defines what database we would like to use. All other models then extend this class and will also use the correct database connection.
Peewee supports many different field types which map to different column types commonly supported by database engines. Conversion between python types and those used in the database is handled transparently, allowing you to use the following in your application:
Strings (unicode or otherwise)
Integers, floats, and
Dates, times and datetimes
In order to start using the models, its necessary to create the tables. This is a one-time operation and can be done quickly using the interactive interpreter. We can create a small helper function to accomplish this:
def create_tables(): with database: database.create_tables([User, Relationship, Message])
Open a python shell in the directory alongside the example app and execute the following:
>>> from app import * >>> create_tables()
If you encounter an ImportError it means that either flask or peewee was not found and may not be installed correctly. Check the Installing and Testing document for instructions on installing peewee.
Every model has a
create_table() classmethod which runs a SQL
CREATE TABLE statement in the database. This method will create the table,
including all columns, foreign-key constraints, indexes, and sequences. Usually
this is something you’ll only do once, whenever a new model is added.
Peewee provides a helper method
Database.create_tables() which will
resolve inter-model dependencies and call
each model, ensuring the tables are created in order.
Adding fields after the table has been created will require you to either drop the table and re-create it or manually add the columns using an ALTER TABLE query.
Alternatively, you can use the schema migrations extension to alter your database schema using Python.
Establishing a database connection¶
You may have noticed in the above model code that there is a class defined on
the base model named Meta that sets the
database attribute. Peewee allows
every model to specify which database it uses. There are many Meta
options you can specify which control the behavior of your
This is a peewee idiom:
DATABASE = 'tweepee.db' # Create a database instance that will manage the connection and # execute queries database = SqliteDatabase(DATABASE) # Create a base-class all our models will inherit, which defines # the database we'll be using. class BaseModel(Model): class Meta: database = database
When developing a web application, it’s common to open a connection when a
request starts, and close it when the response is returned. You should always
manage your connections explicitly. For instance, if you are using a
connection pool, connections will only be recycled correctly if
We will tell flask that during the request/response cycle we need to create a connection to the database. Flask provides some handy decorators to make this a snap:
@app.before_request def before_request(): database.connect() @app.after_request def after_request(response): database.close() return response
Peewee uses thread local storage to manage connection state, so this pattern can be used with multi-threaded WSGI servers.
In the User model there are a few instance methods that encapsulate some user-specific functionality:
following(): who is this user following?
followers(): who is following this user?
These methods are similar in their implementation but with an important difference in the SQL JOIN and WHERE clauses:
def following(self): # query other users through the "relationship" table return (User .select() .join(Relationship, on=Relationship.to_user) .where(Relationship.from_user == self) .order_by(User.username)) def followers(self): return (User .select() .join(Relationship, on=Relationship.from_user) .where(Relationship.to_user == self) .order_by(User.username))
Creating new objects¶
When a new user wants to join the site we need to make sure the username is
available, and if so, create a new User record. Looking at the join() view,
we can see that our application attempts to create the User using
Model.create(). We defined the User.username field with a unique
constraint, so if the username is taken the database will raise an
try: with database.atomic(): # Attempt to create the user. If the username is taken, due to the # unique constraint, the database will raise an IntegrityError. user = User.create( username=request.form['username'], password=md5(request.form['password']).hexdigest(), email=request.form['email'], join_date=datetime.datetime.now()) # mark the user as being 'authenticated' by setting the session vars auth_user(user) return redirect(url_for('homepage')) except IntegrityError: flash('That username is already taken')
We will use a similar approach when a user wishes to follow someone. To
indicate a following relationship, we create a row in the Relationship table
pointing from one user to another. Due to the unique index on
to_user, we will be sure not to end up with duplicate rows:
user = get_object_or_404(User, username=username) try: with database.atomic(): Relationship.create( from_user=get_current_user(), to_user=user) except IntegrityError: pass
If you are logged-in and visit the twitter homepage, you will see tweets from the users that you follow. In order to implement this cleanly, we can use a subquery:
user.following(), by default would ordinarily select all
the columns on the
User model. Because we’re using it as a subquery,
peewee will only select the primary key.
# python code user = get_current_user() messages = (Message .select() .where(Message.user.in_(user.following())) .order_by(Message.pub_date.desc()))
This code corresponds to the following SQL query:
SELECT t1."id", t1."user_id", t1."content", t1."pub_date" FROM "message" AS t1 WHERE t1."user_id" IN ( SELECT t2."id" FROM "user" AS t2 INNER JOIN "relationship" AS t3 ON t2."id" = t3."to_user_id" WHERE t3."from_user_id" = ? )
Other topics of interest¶
There are a couple other neat things going on in the example app that are worth mentioning briefly.
Support for paginating lists of results is implemented in a simple function called
object_list(after it’s corollary in Django). This function is used by all the views that return lists of objects.
def object_list(template_name, qr, var_name='object_list', **kwargs): kwargs.update( page=int(request.args.get('page', 1)), pages=qr.count() / 20 + 1) kwargs[var_name] = qr.paginate(kwargs['page']) return render_template(template_name, **kwargs)
Simple authentication system with a
login_requireddecorator. The first function simply adds user data into the current session when a user successfully logs in. The decorator
login_requiredcan be used to wrap view functions, checking for whether the session is authenticated and if not redirecting to the login page.
def auth_user(user): session['logged_in'] = True session['user'] = user session['username'] = user.username flash('You are logged in as %s' % (user.username)) def login_required(f): @wraps(f) def inner(*args, **kwargs): if not session.get('logged_in'): return redirect(url_for('login')) return f(*args, **kwargs) return inner
Return a 404 response instead of throwing exceptions when an object is not found in the database.
def get_object_or_404(model, *expressions): try: return model.get(*expressions) except model.DoesNotExist: abort(404)
To avoid having to frequently copy/paste
get_object_or_404(), these functions are included as part of the
playhouse flask extension module.
from playhouse.flask_utils import get_object_or_404, object_list
There are more examples included in the peewee examples directory, including:
Example blog app using Flask and peewee. Also see accompanying blog post.
An encrypted command-line diary. There is a companion blog post you might enjoy as well.
Analytics web-service (like a lite version of Google Analytics). Also check out the companion blog post.
Like these snippets and interested in more? Check out flask-peewee - a flask plugin that provides a django-like Admin interface, RESTful API, Authentication and more for your peewee models.