"application/x-font-otf",
				"application/x-font-pcf",
				"application/x-font-snf",
				"application/x-font-speedo",
				"application/x-font-sunos-news",
				"application/x-font-ttf",
				"application/x-font-type1",
				"application/x-font-adobe-metric",
				"application/x-font-printer-metric",
				"application/x-font-vfont",
				"application/x-foxmail",
				"application/x-futuresplash",
				"application/x-gnucash",

 * <p>
 * Example usage:
 * <pre>
 * {@literal @}Typed(ServiceImpl.class)
 * public class ServiceImpl implements Service {
 *     // Implementation
 * }
 * </pre>
 *
 * @since 4.0.0
 */
@Target({FIELD, METHOD, TYPE})
@Retention(RUNTIME)
@Documented
public @interface Typed {
    /**
     * Specifies the types that should be considered for dependency injection.
     * <p>

        String password = "testpassword";

        // When
        Type3Message type3 = new Type3Message(createMockContext(), type2, null, password, "DOMAIN", "user", "WORKSTATION",
                NtlmFlags.NTLMSSP_NEGOTIATE_NTLM);

        // Then
        assertNotNull(type3.getLMResponse());
        assertNotNull(type3.getNTResponse());
        assertTrue(type3.getLMResponse().length > 0);

        // Test with another type and empty raw data
        int type2 = AvPair.MsvAvEOL;
        byte[] raw2 = new byte[] {};
        AvPair avPair2 = new AvPair(type2, raw2);

        assertEquals(type2, avPair2.getType(), "Type should match the constructor argument for empty raw data.");
        assertArrayEquals(raw2, avPair2.getRaw(), "Raw data should match the constructor argument for empty raw data.");

Diese Typen mit inneren Typen werden „**generische**“ Typen genannt. Es ist möglich, sie mit ihren inneren Typen zu deklarieren.

Um diese Typen und die inneren Typen zu deklarieren, können Sie Pythons Standardmodul `typing` verwenden. Es existiert speziell für die Unterstützung dieser Typhinweise.

#### Neuere Python-Versionen { #newer-versions-of-python }

* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic-Datentypen</a>.

## Beispiel { #example }

Hier ist ein Beispiel für eine *Pfadoperation* mit Parametern, die einige der oben genannten Typen verwenden.

{* ../../docs_src/extra_data_types/tutorial001_an_py310.py hl[1,3,12:16] *}

## **Typer**, das FastAPI der CLIs { #typer-the-fastapi-of-clis }

<a href="https://typer.tiangolo.com" target="_blank"><img src="https://typer.tiangolo.com/img/logo-margin/logo-margin-vector.svg" style="width: 20%;"></a>

        CURRENT = JAVA6;
      }
    }

    abstract Type newArrayType(Type componentType);

    abstract Type usedInGenericType(Type type);

    final ImmutableList<Type> usedInGenericType(Type[] types) {
      ImmutableList.Builder<Type> builder = ImmutableList.builder();
      for (Type type : types) {
        builder.add(usedInGenericType(type));
      }
      return builder.build();
    }

# Introdução aos tipos Python { #python-types-intro }

O Python possui suporte para "dicas de tipo" ou "type hints" (também chamado de "anotações de tipo" ou "type annotations")

Esses **"type hints"** são uma sintaxe especial que permite declarar o <abbr title = "por exemplo: str, int, float, bool">tipo</abbr> de uma variável.

Ao declarar tipos para suas variáveis, editores e ferramentas podem oferecer um melhor suporte.

### Tipos simples { #simple-types }

Puedes declarar todos los tipos estándar de Python, no solo `str`.

Puedes usar, por ejemplo:

* `int`
* `float`
* `bool`
* `bytes`

{* ../../docs_src/python_types/tutorial005_py39.py hl[1] *}

### Tipos genéricos con parámetros de tipo { #generic-types-with-type-parameters }