attributes.attribute(GradleModuleApiAttribute.attribute as Attribute<GradleModuleApiAttribute>, GradleModuleApiAttribute.API)
        attributes.attribute(Usage.USAGE_ATTRIBUTE as Attribute<Usage>, RUNTIME_ATTRIBUTE)
        attributes.attribute(Category.CATEGORY_ATTRIBUTE as Attribute<Category>, DOCUMENTATION_ATTRIBUTE)
        attributes.attribute(DocsType.DOCS_TYPE_ATTRIBUTE as Attribute<DocsType>, SOURCES_ATTRIBUTE)

        sourcesPath.attributes(a -> {
            a.attribute(Usage.USAGE_ATTRIBUTE, objects.named(Usage.class, Usage.JAVA_RUNTIME));
            a.attribute(Category.CATEGORY_ATTRIBUTE, objects.named(Category.class, Category.DOCUMENTATION));
            a.attribute(DocsType.DOCS_TYPE_ATTRIBUTE, objects.named(DocsType.class, "gradle-source-folders"));
        });

```Python hl_lines="4  7-8  18-19"
{!../../../docs_src/sql_databases/sql_app/models.py!}
```

The `__tablename__` attribute tells SQLAlchemy the name of the table to use in the database for each of these models.

### Create model attributes/columns

Now create all the model (class) attributes.

Each of these attributes represents a column in its corresponding database table.

We use `Column` from SQLAlchemy as the default value.

 * or a {@code pom.xml} containing the {@code root="true"} attribute.
 */
public interface RootLocator {

    String UNABLE_TO_FIND_ROOT_PROJECT_MESSAGE = "Unable to find the root directory. "
            + "Create a .mvn directory in the root directory or add the root=\"true\""
            + " attribute on the root project's model to identify it.";

    @Nonnull

              // Ignore this attribute, it isn't recognizable as a date.
            }
          }
          attributeName.equals("max-age", ignoreCase = true) -> {
            try {
              deltaSeconds = parseMaxAge(attributeValue)
              persistent = true
            } catch (_: NumberFormatException) {
              // Ignore this attribute, it isn't recognizable as a max age.
            }

!!! info
    In Pydantic version 1 the configuration was done in an internal class `Config`, in Pydantic version 2 it's done in an attribute `model_config`. This attribute takes a `dict`, and to get autocompletion and inline errors you can import and use `SettingsConfigDict` to define that `dict`.

And these models are all sharing a lot of the data and duplicating attribute names and types.

We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

All the data conversion, validation, documentation, etc. will still work as normally.

!!! info
    Webhooks are available in OpenAPI 3.1.0 and above, supported by FastAPI `0.99.0` and above.

## An app with webhooks

When you create a **FastAPI** application, there is a `webhooks` attribute that you can use to define *webhooks*, the same way you would define *path operations*, for example with `@app.webhooks.post()`.

```Python hl_lines="9-13  36-53"
{!../../../docs_src/openapi_webhooks/tutorial001.py!}
```

!!! note
    Notice that the input model is still validated.

    So, if you want to receive partial updates that can omit all the attributes, you need to have a model with all the attributes marked as optional (with default values or `None`).

```Python hl_lines="35"
{!../../../docs_src/openapi_callbacks/tutorial001.py!}
```

!!! tip
    Notice that you are not passing the router itself (`invoices_callback_router`) to `callback=`, but the attribute `.routes`, as in `invoices_callback_router.routes`.