}

    @Test
    @DisplayName("Edge: null is not an instance of the interface")
    void testNullIsNotInstance() {
        // Assert
        assertFalse(SessionSetupHandler.class.isInstance(null));
    }

    @Test
    @DisplayName("Invalid: looking up constructor on interface fails")
    void testNoConstructorLookup() {

import org.junit.Ignore;

/**
 * Tester to make sure the {@code iterator().remove()} implementation of {@code Multiset} works when
 * there are multiple occurrences of elements.
 *
 * @author Louis Wasserman
 */
@GwtCompatible
@Ignore("test runners must not instantiate and run this directly, only via suites we build")
// @Ignore affects the Android test runner, which respects JUnit 4 annotations on JUnit 3 tests.

    public void setGroupCacheExpiry(final long groupCacheExpiry) {
        this.groupCacheExpiry = groupCacheExpiry;
    }

    /**
     * Sets the maximum group depth for nested group processing.
     * @param maxGroupDepth The maximum depth for nested groups.
     */
    public void setMaxGroupDepth(final int maxGroupDepth) {
        this.maxGroupDepth = maxGroupDepth;
    }

    @Override

Dessa forma, seu esquema aparecerá na interface de documentação da API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses em Estruturas de Dados Aninhadas { #dataclasses-in-nested-data-structures }

Você também pode combinar `dataclasses` com outras anotações de tipo para criar estruturas de dados aninhadas.

De esta manera, su esquema aparecerá en la interfaz de usuario de la documentación de la API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses en Estructuras de Datos Anidadas { #dataclasses-in-nested-data-structures }

También puedes combinar `dataclasses` con otras anotaciones de tipos para crear estructuras de datos anidadas.

<div class="termy">

```console
$ fastapi dev main.py

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

## Es testen { #check-it }

Gehen Sie zu der interaktiven Dokumentation unter: <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

Sie werden etwa Folgendes sehen:

You also get error checks for incorrect type operations:

<img src="/img/tutorial/body/image04.png">

This is not by chance, the whole framework was built around that design.

And it was thoroughly tested at the design phase, before any implementation, to ensure it would work with all the editors.

There were even some changes to Pydantic itself to support this.

				continue
			}
			// check the doc https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingMetadata.html
			// For metadata values like "ö", "ÄMÄZÕÑ S3", and "öha, das sollte eigentlich
			// funktionieren", tested against a real AWS S3 bucket, S3 may encode incorrectly. For
			// example, "ö" was encoded as =?UTF-8?B?w4PCtg==?=, producing invalid UTF-8 instead
			// of =?UTF-8?B?w7Y=?=. This mirrors errors like the ä½ in another string.

    }

    @Nested
    @DisplayName("Dispose Tests")
    class DisposeTests {
        @Test
        @DisplayName("dispose delegates to GSSContext")
        void dispose_success() throws Exception {
            assertDoesNotThrow(() -> ctx.dispose());
            verify(gssContext, times(1)).dispose();
        }

        @Test

Таким образом, его схема появится в интерфейсе документации API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses во вложенных структурах данных { #dataclasses-in-nested-data-structures }

Вы также можете комбинировать `dataclasses` с другими аннотациями типов, чтобы создавать вложенные структуры данных.