/// info

Notice how `Offer` has a list of `Item`s, which in turn have an optional list of `Image`s

///

## Bodies of pure lists { #bodies-of-pure-lists }

If the top level value of the JSON body you expect is a JSON `array` (a Python `list`), you can declare the type in the parameter of the function, the same as in Pydantic models:

```Python

import jcifs.smb1.util.Hexdump;

/**
 * Unit test for {@link Trans2QueryFSInformation}. The class contains mostly
 * trivial wire-format helpers and a custom {@code toString()} implementation.
 * All tests are pure unit tests – no network or file system access is
 * required.
 */
class Trans2QueryFSInformationTest {

    /** Small helper to create a byte buffer larger than the maximum expected

/// info | Informação

Observe como `Offer` tem uma lista de `Item`s, que por sua vez têm uma lista opcional de `Image`s

///

## Corpos de listas puras { #bodies-of-pure-lists }

Se o valor de primeiro nível do corpo JSON que você espera for um `array` do JSON (uma` lista` do Python), você pode declarar o tipo no parâmetro da função, da mesma forma que nos modelos do Pydantic:

```Python

import com.google.errorprone.annotations.Immutable;
import java.nio.ByteBuffer;
import java.nio.charset.Charset;
import org.jspecify.annotations.Nullable;

/**
 * A hash function is a collision-averse pure function that maps an arbitrary block of data to a
 * number called a <i>hash code</i>.
 *
 * <h3>Definition</h3>
 *
 * <p>Unpacking this definition:
 *
 * <ul>

import com.google.errorprone.annotations.Immutable;
import java.nio.ByteBuffer;
import java.nio.charset.Charset;
import org.jspecify.annotations.Nullable;

/**
 * A hash function is a collision-averse pure function that maps an arbitrary block of data to a
 * number called a <i>hash code</i>.
 *
 * <h3>Definition</h3>
 *
 * <p>Unpacking this definition:
 *
 * <ul>

/// info | Información

Observa cómo `Offer` tiene una lista de `Item`s, que a su vez tienen una lista opcional de `Image`s

///

## Cuerpos de listas puras { #bodies-of-pure-lists }

Si el valor superior del cuerpo JSON que esperas es un `array` JSON (una `list` en Python), puedes declarar el tipo en el parámetro de la función, al igual que en los modelos Pydantic:

```Python

/// info | Info

Beachten Sie, wie `Offer` eine Liste von `Item`s hat, die ihrerseits eine optionale Liste von `Image`s haben.

///

## Bodys aus reinen Listen { #bodies-of-pure-lists }

Wenn das äußerste Element des JSON-Bodys, das Sie erwarten, ein JSON-`array` (eine Python-`list`) ist, können Sie den Typ im Funktionsparameter deklarieren, mit der gleichen Syntax wie in Pydantic-Modellen:

```Python

  :Darwin*arm64) distributionPlatform=darwin-aarch64 ;;
  :Linux*x86_64*) distributionPlatform=linux-amd64 ;;
  *)
    echo "Cannot detect native platform for mvnd on $(uname)-$(uname -m), use pure java version" >&2
    distributionPlatform=linux-amd64
    ;;
  esac
  distributionUrl="${distributionUrl%-bin.*}-$distributionPlatform.zip"
  ;;
maven-mvnd-*) MVN_CMD=mvnd.sh _MVNW_REPO_PATTERN=/maven/mvnd/ ;;

/// info | Информация

Заметьте, что у объекта `Offer` есть список объектов `Item`, которые, в свою очередь, могут содержать необязательный список объектов `Image`

///

## Тела с чистыми списками элементов { #bodies-of-pure-lists }

Если верхний уровень значения тела JSON-объекта представляет собой JSON `array` (в Python — `list`), вы можете объявить тип в параметре функции, так же как в моделях Pydantic:

```Python
images: list[Image]

            }
            // Make sure (whatever extra priority is set) that resolver file/apache is selected
            configProps.put(FILE_TRANSPORTER_PRIORITY_KEY, RESOLVER_MAX_PRIORITY);
            configProps.put(APACHE_HTTP_TRANSPORTER_PRIORITY_KEY, RESOLVER_MAX_PRIORITY);
        } else if (MAVEN_RESOLVER_TRANSPORT_WAGON.equals(transport)) {
            // Make sure (whatever extra priority is set) that wagon is selected