Und genau das ist **HTTPS**, es ist einfach **HTTP** innerhalb einer **sicheren TLS-Verbindung**, statt einer puren (unverschlüsselten) TCP-Verbindung.

/// tip | Tipp

Beachten Sie, dass die Verschlüsselung der Kommunikation auf der **TCP-Ebene** und nicht auf der HTTP-Ebene erfolgt.

///

/// 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

/// 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 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 | 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/ ;;

    }

    /*
     * For this packet deconstruction technique to work for
     * other networking protocols the InputStream may need
     * to be passed to the readXxxWireFormat methods. This is
     * actually purer. However, in the case of smb we know the
     * wordCount and byteCount. And since every subclass of
     * ServerMessageBlock would have to perform the same read
     * operation on the input stream, we might as will pull that

/// 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]

            extender.extend(request, configProps, mirrorSelector, proxySelector, authSelector);
        }

        // at this point we have "config" with pure MANDATORY resolver config, so resolver final config properties are
        // mergedProperties + configProperties
        HashMap<String, Object> finalConfigProperties = new HashMap<>();