Models

https://docs.sqlalchemy.org/en/14/orm/quickstart.html

Here, we define module-level constructs that will form the structures which we will be querying from the database. This structure, known as a Declarative Mapping, defines at once both a Python object model, as well as database metadata that describes real SQL tables that exist, or will exist, in a particular database

from sqlalchemy import Column
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import String
from sqlalchemy.orm import declarative_base
from sqlalchemy.orm import relationship

Base = declarative_base()

class User(Base):
    __tablename__ = "user_account"
    id = Column(Integer, primary_key=True)
    name = Column(String(30))
    fullname = Column(String)
    addresses = relationship(
        "Address", back_populates="user", cascade="all, delete-orphan"
    )

    def __repr__(self):
        return f"User(id={self.id!r}, name={self.name!r}, fullname={self.fullname!r})"

class Address(Base):
    __tablename__ = "address"
    id = Column(Integer, primary_key=True)
    email_address = Column(String, nullable=False)
    user_id = Column(Integer, ForeignKey("user_account.id"), nullable=False)

    user = relationship("User", back_populates="addresses")

    def __repr__(self):
        return f"Address(id={self.id!r}, email_address={self.email_address!r})"

Above, the declarative mapping makes use of Column objects to define the basic units of data storage that will be in the database. The relationship() construct defines linkages between two mapped classes, UserandAddressabove.

The schema contains necessary elements such as primary key constraints set up by the Column.primary_key parameter, a foreign key constraint configured using ForeignKey(which is used by relationship() as well), and datatypes for columns including Integer and String.