## Suporte de editor em todo canto { #editor-support-everywhere }

E você obtém suporte do editor em todos os lugares.

Mesmo para itens dentro de listas:

<img src="/img/tutorial/body-nested-models/image01.png">

Você não conseguiria este tipo de suporte de editor se estivesse trabalhando diretamente com `dict` em vez de modelos Pydantic.

# Body – Verschachtelte Modelle { #body-nested-models }

Mit **FastAPI** können Sie (dank Pydantic) beliebig tief verschachtelte Modelle definieren, validieren, dokumentieren und verwenden.

## Listen als Felder { #list-fields }

Sie können ein Attribut als Kindtyp definieren, zum Beispiel eine Python-`list`.

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

## Soporte de editor en todas partes { #editor-support-everywhere }

Y obtienes soporte de editor en todas partes.

Incluso para elementos dentro de listas:

<img src="/img/tutorial/body-nested-models/image01.png">

No podrías obtener este tipo de soporte de editor si estuvieras trabajando directamente con `dict` en lugar de modelos Pydantic.

And it will be annotated / documented accordingly too.

## Nested Models { #nested-models }

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

All that, arbitrarily nested.

### Define a submodel { #define-a-submodel }

# Body - Вложенные модели { #body-nested-models }

С помощью **FastAPI** вы можете определять, валидировать, документировать и использовать модели произвольной глубины вложенности (благодаря Pydantic).

## Поля-списки { #list-fields }

Вы можете определить атрибут как подтип. Например, Python-тип `list`:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

 *   <li>Performance monitoring of nested operations</li>
 * </ul>
 *
 * @param context The context identifier for this request trace, helping to identify the scope or purpose
 *                of the request. May be null if no specific context is needed.
 * @param parent The parent request trace that led to this request, establishing the chain of nested
 *               operations. May be null for top-level requests.

    }

    @Nested
    @DisplayName("Modification Behavior")
    class ModificationBehaviorTests {

        @Test
        @DisplayName("should save modifications to disk")
        void shouldSaveModificationsToDisk() {
            assertTrue(applyGoal.shouldSaveModifications(), "Apply goal should save modifications to disk");
        }
    }

    @Nested
    @DisplayName("Execution")

import java.util.stream.Stream;

import eu.maveniverse.domtrip.Document;
import eu.maveniverse.domtrip.Element;
import eu.maveniverse.domtrip.Parser;
import org.junit.jupiter.api.DisplayName;
import org.junit.jupiter.api.Nested;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.MethodSource;

This way, its schema will show up in the API docs user interface:

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

## Dataclasses in Nested Data Structures { #dataclasses-in-nested-data-structures }

You can also combine `dataclasses` with other type annotations to make nested data structures.

import org.apache.maven.api.cli.mvnup.UpgradeOptions;
import org.apache.maven.cling.invoker.mvnup.UpgradeContext;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.DisplayName;
import org.junit.jupiter.api.Nested;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.io.TempDir;
import org.junit.jupiter.params.ParameterizedTest;
import org.junit.jupiter.params.provider.Arguments;