## Универсальная поддержка редактора

И вы получаете поддержку редактора везде.

Даже для элементов внутри списков:

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

Вы не могли бы получить такую поддержку редактора, если бы работали напрямую с `dict`, а не с моделями Pydantic.

images: List[Image]
```

이를 아래처럼:

{* ../../docs_src/body_nested_models/tutorial008.py hl[15] *}

## 어디서나 편집기 지원

그리고 어디서나 편집기 지원을 받을수 있습니다.

리스트 내부 항목의 경우에도:

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

Pydantic 모델 대신에 `dict`를 직접 사용하여 작업할 경우, 이러한 편집기 지원을 받을수 없습니다.

하지만 수신한 딕셔너리가 자동으로 변환되고 출력도 자동으로 JSON으로 변환되므로 걱정할 필요는 없습니다.

## 단독 `dict`의 본문

import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Nested;
import org.junit.jupiter.api.Test;
import org.mockito.Mockito;

import jcifs.smb.SmbPipeHandleInternal;

/**
 * Unit tests for a class that implements the {@link SmbPipeHandle} interface.
 * This test class uses a mock implementation to ensure any class adhering to the
 * SmbPipeHandle contract is tested for correctness.
 */
public class SmbPipeHandleTest {

### Tested { #tested }

* 100% <abbr title="The amount of code that is automatically tested">test coverage</abbr>.
* 100% <abbr title="Python type annotations, with this your editor and external tools can give you better support">type annotated</abbr> code base.

import java.lang.reflect.Field;
import java.util.Arrays;
import java.util.stream.Stream;

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.params.ParameterizedTest;
import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;

  }

  private abstract static class DefaultValueChecker {

    private final Map<Integer, Object> arguments = new HashMap<>();

    @CanIgnoreReturnValue
    final DefaultValueChecker runTester() {
      new NullPointerTester().testInstanceMethods(this, Visibility.PACKAGE);
      return this;
    }

    final void assertNonNullValues(Object... expectedValues) {

computation
[**graphs**](https://developers.google.com/machine-learning/glossary/#graph).
Since models are practically programs that TensorFlow executes, using untrusted
models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are

 * public class Books {
 *   public static Book hardcover(String title) {...}
 *   public static Book paperback(String title) {...}
 * }
 * </pre>
 *
 * <p>And all the created {@code Book} instances can be tested with:
 *
 * <pre>
 * new ClassSanityTester()
 *     .forAllPublicStaticMethods(Books.class)
 *     .thatReturn(Book.class)
 *     .testEquals(); // or testNulls(), testSerializable() etc.
 * </pre>
 *

 * public class Books {
 *   public static Book hardcover(String title) {...}
 *   public static Book paperback(String title) {...}
 * }
 * </pre>
 *
 * <p>And all the created {@code Book} instances can be tested with:
 *
 * <pre>
 * new ClassSanityTester()
 *     .forAllPublicStaticMethods(Books.class)
 *     .thatReturn(Book.class)
 *     .testEquals(); // or testNulls(), testSerializable() etc.
 * </pre>
 *

      "colour": "#43952A",
      "description": "has pull request"
    },
    "not_tested": {
      "name": "type:not tested",
      "colour": "#CF2E1F",
      "description": "not tested"
    },
    "tested": {
      "name": "type:tested",
      "colour": "#00ff00",
      "description": "tested"
    },
    "breaking_change": {
      "name": "type:breaking change",
      "colour": "#CF2E1F",