# Models and Tables

Use the `db.Model` class to define models, or the `db.Table` class to create tables. Both handle Flask-SQLAlchemy’s bind keys to associate with a specific engine.

## Initializing the Base Class

`SQLAlchemy` 2.x offers several possible base classes for your models: DeclarativeBase or DeclarativeBaseNoMeta.

Create a subclass of one of those classes:

    from flask import Flask
    from flask_sqlalchemy import SQLAlchemy
    from sqlalchemy.orm import DeclarativeBase

    class Base(DeclarativeBase):
      pass

If desired, you can enable SQLAlchemy’s native support for data classes by adding MappedAsDataclass as an additional parent class.

    from sqlalchemy.orm import DeclarativeBase, MappedAsDataclass

    class Base(DeclarativeBase, MappedAsDataclass):
      pass

You can optionally construct the `SQLAlchemy` object with a custom `MetaData` object. This allows you to specify a custom constraint naming convention. This makes constraint names consistent and predictable, useful when using migrations, as described by Alembic.

    from sqlalchemy import MetaData

    class Base(DeclarativeBase):
        metadata = MetaData(naming_convention={
            "ix": 'ix_%(column_0_label)s',
            "uq": "uq_%(table_name)s_%(column_0_name)s",
            "ck": "ck_%(table_name)s_%(constraint_name)s",
            "fk": "fk_%(table_name)s_%(column_0_name)s_%(referred_table_name)s",
            "pk": "pk_%(table_name)s"
        })

## Initialize the Extension

Once you’ve defined a base class, create the `db` object using the `SQLAlchemy` constructor.

    db = SQLAlchemy(model_class=Base)

## Defining Models

See SQLAlchemy’s declarative documentation for full information about defining model classes declaratively.

Subclass `db.Model` to create a model class. Unlike plain SQLAlchemy, Flask-SQLAlchemy’s model will automatically generate a table name if `__tablename__` is not set and a primary key column is defined.

    from sqlalchemy.orm import Mapped, mapped_column

    class User(db.Model):
        id: Mapped[int] = mapped_column(db.Integer, primary_key=True)
        username: Mapped[str] = mapped_column(db.String, unique=True, nullable=False)
        email: Mapped[str] = mapped_column(db.String)

Defining a model does not create it in the database. Use `create_all()` to create the models and tables after defining them. If you define models in submodules, you must import them so that SQLAlchemy knows about them before calling `create_all`.

    with app.app_context():
        db.create_all()

## Defining Tables

See SQLAlchemy’s table documentation for full information about defining table objects.

Create instances of `db.Table` to define tables. The class takes a table name, then any columns and other table parts such as columns and constraints. Unlike plain SQLAlchemy, the `metadata` argument is not required. A metadata will be chosen based on the `bind_key` argument, or the default will be used.

A common reason to create a table directly is when defining many to many relationships. The association table doesn’t need its own model class, as it will be accessed through the relevant relationship attributes on the related models.

    import sqlalchemy as sa

    user_book_m2m = db.Table(
        "user_book",
        sa.Column("user_id", sa.ForeignKey(User.id), primary_key=True),
        sa.Column("book_id", sa.ForeignKey(Book.id), primary_key=True),
    )

## Reflecting Tables

If you are connecting to a database that already has tables, SQLAlchemy can detect that schema and create tables with columns automatically. This is called reflection. Those tables can also be assigned to model classes with the `__table__` attribute instead of defining the full model.

Call the `reflect()` method on the extension. It will reflect all the tables for each bind key. Each metadata’s `tables` attribute will contain the detected table objects.

    with app.app_context():
        db.reflect()

    class User:
        __table__ = db.metadatas["auth"].tables["user"]

In most cases, it will be more maintainable to define the model classes yourself. You only need to define the models and columns you will actually use, even if you’re connecting to a broader schema. IDEs will know the available attributes, and migration tools like Alembic can detect changes and generate schema migrations.