Declaring Models — Flask-SQLAlchemy 1.0 documentation

# Declaring Models

Generally Flask-SQLAlchemy behaves like a properly configured declarative base from the `declarative` extension. As such we recommend reading the SQLAlchemy docs for a full reference. However the most common use cases are also documented here.

Things to keep in mind:

- The baseclass for all your models is called db.Model. It’s stored on the SQLAlchemy instance you have to create. See Quickstart for more details.
- Some parts that are required in SQLAlchemy are optional in Flask-SQLAlchemy. For instance the table name is automatically set for you unless overridden. It’s derived from the class name converted to lowercase and with “CamelCase” converted to “camel_case”.

## Simple Example

A very simple example:

    class User(db.Model):
        id = db.Column(db.Integer, primary_key=True)
        username = db.Column(db.String(80), unique=True)
        email = db.Column(db.String(120), unique=True)

        def __init__(self, username, email):
            self.username = username
            self.email = email

        def __repr__(self):
            return '<User %r>' % self.username

Use `Column` to define a column. The name of the column is the name you assign it to. If you want to use a different name in the table you can provide an optional first argument which is a string with the desired column name. Primary keys are marked with `primary_key=True`. Multiple keys can be marked as primary keys in which case they become a compound primary key.

The types of the column are the first argument to `Column`. You can either provide them directly or call them to further specify them (like providing a length). The following types are the most common:

Integer | an integer
String (size) | a string with a maximum length
Text | some longer unicode text
DateTime | date and time expressed as Python `datetime` object.
Float | stores floating point values
Boolean | stores a boolean value
PickleType | stores a pickled Python object
LargeBinary | stores large arbitrary binary data

## One-to-Many Relationships

The most common relationships are one-to-many relationships. Because relationships are declared before they are established you can use strings to refer to classes that are not created yet (for instance if Person defines a relationship to Article which is declared later in the file).

Relationships are expressed with the `relationship()` function. However the foreign key has to be separately declared with the `sqlalchemy.schema.ForeignKey` class:

    class Person(db.Model):
        id = db.Column(db.Integer, primary_key=True)
        name = db.Column(db.String(50))
        addresses = db.relationship('Address', backref='person',
                                    lazy='dynamic')

    class Address(db.Model):
        id = db.Column(db.Integer, primary_key=True)
        email = db.Column(db.String(50))
        person_id = db.Column(db.Integer, db.ForeignKey('person.id'))

What does `db.relationship()` do? That function returns a new property that can do multiple things. In this case we told it to point to the Address class and load multiple of those. How does it know that this will return more than one address? Because SQLAlchemy guesses a useful default from your declaration. If you would want to have a one-to-one relationship you can pass `uselist=False` to `relationship()`.

So what do backref and lazy mean? backref is a simple way to also declare a new property on the Address class. You can then also use `my_address.person` to get to the person at that address. lazy defines when SQLAlchemy will load the data from the database:

- `'select'` (which is the default) means that SQLAlchemy will load the data as necessary in one go using a standard select statement.
- `'joined'` tells SQLAlchemy to load the relationship in the same query as the parent using a JOIN statement.
- `'subquery'` works like `'joined'` but instead SQLAlchemy will use a subquery.
- `'dynamic'` is special and useful if you have may items. Instead of loading the items SQLAlchemy will return another query object which you can further refine before loading them items. This is usually what you want if you expect more than a handful of items for this relationship.

How do you define the lazy status for backrefs? By using the `backref()` function:

    class User(db.Model):
        id = db.Column(db.Integer, primary_key=True)
        name = db.Column(db.String(50))
        addresses = db.relationship('Address',
            backref=db.backref('person', lazy='joined'), lazy='dynamic')

## Many-to-Many Relationships

If you want to use many-to-many relationships you will need to define a helper table that is used for the relationship. For this helper table it is strongly recommended to not use a model but an actual table:

    tags = db.Table('tags',
        db.Column('tag_id', db.Integer, db.ForeignKey('tag.id')),
        db.Column('page_id', db.Integer, db.ForeignKey('page.id'))
    )

    class Page(db.Model):
        id = db.Column(db.Integer, primary_key=True)
        tags = db.relationship('Tag', secondary=tags,
            backref=db.backref('pages', lazy='dynamic'))

    class Tag(db.Model):
        id = db.Column(db.Integer, primary_key=True)

Here we configured Page.tags to be a list of tags once loaded because we don’t expect too many tags per page. The list of pages per tag (Tag.pages) however is a dynamic backref. As mentioned above this means that you will get a query object back you can use to fire a select yourself.