Defining Models
Map classes to tables.
Defining Models is a free Python Academy lesson on CoddyKit. This is lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Python Academy learning path, and your progress syncs across the web and the CoddyKit app. The Python Academy course includes 4 lessons in total.
Models Map to Tables
In the SQLAlchemy ORM, a model is a Python class that maps to a database table. Each instance becomes a row.
Models inherit from a shared Base class.
from sqlalchemy.orm import DeclarativeBase
class Base(DeclarativeBase):
pass
print('Base class ready')The __tablename__
Every model sets __tablename__ to name its table. SQLAlchemy uses this when generating SQL.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
print(User.__tablename__)Columns with Mapped
Modern SQLAlchemy declares columns with type hints: Mapped[int] and mapped_column(). The type hint sets the Python type and informs the column type.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
age: Mapped[int]
print('User has id, name, age')The Primary Key
Mark a column as the primary key with primary_key=True. Integer primary keys auto-increment by default.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class Product(Base):
__tablename__ = 'products'
id: Mapped[int] = mapped_column(primary_key=True)
title: Mapped[str]
print('id is the primary key')Optional Columns
Use Mapped[str | None] or Optional[str] to allow NULL values. A plain Mapped[str] is NOT NULL.
from typing import Optional
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
nickname: Mapped[Optional[str]]
print('nickname can be NULL')Defaults and Uniqueness
mapped_column() takes options like unique=True and default= to add constraints and fallback values.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
email: Mapped[str] = mapped_column(unique=True)
active: Mapped[bool] = mapped_column(default=True)
print('email is unique, active defaults to True')String Length
For databases that need it, set a string length with mapped_column(String(50)).
from sqlalchemy import String
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str] = mapped_column(String(50))
print('name limited to 50 chars')Creating the Schema
Base.metadata.create_all(engine) creates tables for every model that inherits from Base.
from sqlalchemy import create_engine
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
engine = create_engine('sqlite:///:memory:')
Base.metadata.create_all(engine)
print('Schema created')Creating Instances
Build a row by instantiating the model like a normal Python object, passing column values as keyword arguments.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
u = User(name='Alice')
print(u.name)Adding a __repr__
A custom __repr__ makes debugging easier by showing the object's data clearly.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
def __repr__(self):
return 'User(name=' + self.name + ')'
print(repr(User(name='Bob')))Models Stay Plain Python
A model is still an ordinary class. You can add methods and properties that operate on its data, mixing behavior with persistence.
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
class Base(DeclarativeBase):
pass
class User(Base):
__tablename__ = 'users'
id: Mapped[int] = mapped_column(primary_key=True)
name: Mapped[str]
def greet(self):
return 'Hi, ' + self.name
print(User(name='Carol').greet())Quick Check
Test your model-definition skills.
Recap
You learned to define ORM models.
- Models inherit from a
DeclarativeBaseand set__tablename__ - Columns use
Mapped[type]andmapped_column() primary_key,unique, anddefaultadd constraintscreate_all()builds the tables
Learn Python with an AI tutor — free
Write and run real code in your browser, get instant help from a 24/7 AI tutor, and pick up where you left off on the web or in the app.
- Courses
- 76
- Lessons
- 320
Frequently Asked Questions
Is the “Defining Models” lesson free?
Yes — the full text of “Defining Models” is free to read here on the web. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Python Academy course, upgrade to CoddyKit PRO. The Python Academy course includes 4 lessons in total.
What will I learn in “Defining Models”?
Map classes to tables. You practise Python Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Python Academy?
No prior experience is required. Python Academy on CoddyKit is structured for beginners through advanced learners, so you can start here or from the beginning and move at your own pace. This is lesson 2 of 4.
How long does the “Defining Models” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Python Academy lesson?
Yes. Every Python Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.