Resumindo, você declara **uma vez** os tipos dos parâmetros, corpo etc. como parâmetros de função.

Você faz isso com os tipos padrão do Python moderno.

Você não terá que aprender uma nova sintaxe, métodos ou classes de uma biblioteca específica etc.

Apenas **Python** padrão.

Por exemplo, para um `int`:

```Python
item_id: int
```

ou para um modelo mais complexo, `Item`:

```Python

## 0.122.0

### Fixes

* 🐛 Use `401` status code in security classes when credentials are missing. PR [#13786](https://github.com/fastapi/fastapi/pull/13786) by [@YuriiMotov](https://github.com/YuriiMotov).

### Recap { #recap }

In summary, you declare **once** the types of parameters, body, etc. as function parameters.

You do that with standard modern Python types.

You don't have to learn a new syntax, the methods or classes of a specific library, etc.

Just standard **Python**.

For example, for an `int`:

```Python
item_id: int
```

or for a more complex `Item` model:

```Python
item: Item
```

   * natural ordering. The sorted multisets use {@link Ordering#natural()} as the comparator. This
   * method provides more type-safety than {@link #builder}, as it can be called only for classes
   * that implement {@link Comparable}.
   *
   * <p>Note: the type parameter {@code E} extends {@code Comparable<?>} rather than {@code

        TwoArg bar = new TwoArg(first, second);
        verifyBarPass(method, bar); // All args nullable:  anything goes!
      }
    }
  }

  /*
   * This next part consists of several sample classes that provide
   * demonstrations of conditions that cause NullPointerTester
   * to succeed/fail.
   */

  /** Lots of well-behaved methods. */
  @SuppressWarnings("unused") // used by reflection

type itemOrErr[V any] struct {
	Item V
	Err  error
}

func filterStorageClass(ctx context.Context, s string) string {
	// Veeam 14.0 and later clients are not compatible with custom storage classes.
	if globalVeeamForceSC != "" && s != storageclass.STANDARD && s != storageclass.RRS && isVeeamClient(ctx) {
		return globalVeeamForceSC
	}
	return s
}

type ordered interface {

        try {
            Injector injector = Injector.create();
            injector.discover(pluginRealm);
            // Add known classes
            // TODO: get those from the existing plexus scopes ?
            injector.bindInstance(Session.class, sessionV4);
            injector.bindInstance(Project.class, project);

        }
    }

    /**
     * Sets up Guice class loading mode to CHILD, if not already set.
     * Default Guice class loading mode uses a terminally deprecated JDK memory-access classes.
     */
    protected void setupGuiceClassLoading(C context) {
        if (System.getProperty("guice_custom_class_loading", "").isBlank()) {
            System.setProperty("guice_custom_class_loading", "CHILD");

### Recap

In summary, you declare **once** the types of parameters, body, etc. as function parameters.

You do that with standard modern Python types.

You don't have to learn a new syntax, the methods or classes of a specific library, etc.

Just standard **Python**.

For example, for an `int`:

```Python
item_id: int
```

or for a more complex `Item` model:

```Python
item: Item
```

But it was created before there existed Python type hints. So, to define every <abbr title="the definition of how data should be formed">schema</abbr> you need to use specific utils and classes provided by Marshmallow.

/// check | Inspired **FastAPI** to

Use code to define "schemas" that provide data types and validation, automatically.

///