import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_SET;
import static com.google.common.collect.testing.testers.ReflectionFreeAssertThrows.assertThrows;
import static java.util.Arrays.asList;
import static java.util.Collections.emptyList;
import static java.util.Collections.singletonList;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;

Por padrão, tudo **"simplesmente funciona"**.

### Validação { #validation }

* Validação para a maioria dos (ou todos?) **tipos de dados** do Python, incluindo:
    * objetos JSON (`dict`).
    * arrays JSON (`list`), definindo tipos dos itens.
    * campos String (`str`), definindo tamanho mínimo e máximo.
    * Numbers (`int`, `float`) com valores mínimos e máximos, etc.

* Validação de tipos mais exóticos, como:

import static com.google.common.collect.testing.features.ListFeature.SUPPORTS_SET;
import static com.google.common.collect.testing.testers.ReflectionFreeAssertThrows.assertThrows;
import static java.util.Arrays.asList;
import static java.util.Collections.emptyList;
import static java.util.Collections.singletonList;

import com.google.common.annotations.GwtCompatible;
import com.google.common.annotations.GwtIncompatible;

 * whitespace.
 *
 * Instances of this class are immutable. Use [Builder] to create instances.
 */
@Suppress("NAME_SHADOWING")
class Headers internal constructor(
  internal val namesAndValues: Array<String>,
) : Iterable<Pair<String, String>> {
  /** Returns the last value corresponding to the specified field, or null. */
  operator fun get(name: String): String? = commonHeadersGet(namesAndValues, name)

  /**

         * Matcher checking each item is present exactly once in a given iterable, but an any position,
         * and that there are no unexpected items.
         */
        private
        fun <T> inAnyOrder(items: Array<out T>): Matcher<Iterable<T>> = Matchers.containsInAnyOrder(*items)

        fun newApi(thing: String, desc: String): String =
            "$thing ${describe(thing, desc)}: New public API in 2.0 (@Incubating)"

  - [Swift Apps](https://docs.gradle.org/current/samples/sample_building_swift_applications.html)
  - [Swift Libraries](https://docs.gradle.org/current/samples/sample_building_swift_libraries.html)

> 📘 Explore Gradle’s full array of resources through the [Gradle Documentation](https://docs.gradle.org/).

---

### 🛠 **Seamless IDE & CI Integration**

{* ../../docs_src/body_nested_models/tutorial007_py310.py hl[7,12,18,21,25] *}

/// info

请注意 `Offer` 拥有一组 `Item` 而反过来 `Item` 又是一个可选的 `Image` 列表是如何发生的。

///

## 纯列表请求体

如果你期望的 JSON 请求体的最外层是一个 JSON `array`（即 Python `list`），则可以在路径操作函数的参数中声明此类型，就像声明 Pydantic 模型一样：

```Python
images: List[Image]
```

例如：

{* ../../docs_src/body_nested_models/tutorial008_py39.py hl[13] *}

## 无处不在的编辑器支持

        // Then - always returns 0 as this is a request, not response
        assertEquals(0, emptyRead);
        assertEquals(0, fullRead);
    }

    /**
     * Create a test byte array with specified size and pattern
     */
    private byte[] createTestData(int size) {
        byte[] data = new byte[size];
        for (int i = 0; i < size; i++) {
            data[i] = (byte) (i % 256);
        }

Hier simulieren wir den langsamen *Startup*, das Laden des Modells, indem wir die (Fake-)Modellfunktion vor dem `yield` in das <abbr title="Dictionary – Zuordnungstabelle: In anderen Sprachen auch Hash, Map, Objekt, Assoziatives Array genannt">Dictionary</abbr> mit Modellen für maschinelles Lernen einfügen. Dieser Code wird ausgeführt, **bevor** die Anwendung **beginnt, Requests entgegenzunehmen**, während des *Startups*.

    @Mock
    private HttpServletRequest mockRequest;

    @Mock
    private HttpServletResponse mockResponse;

    private NtlmSsp ntlmSsp;

    // A sample challenge array
    private final byte[] challenge = new byte[] { 0x01, 0x23, 0x45, 0x67, (byte) 0x89, (byte) 0xab, (byte) 0xcd, (byte) 0xef };

    // Base64 encoded Type 1 message: NTLMSSP, Type 1, flags=0x00088207