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);

        this(type1, null, null);
    }

    /**
     * Creates a Type-2 message in response to the given Type-1 message.
     *
     * @param type1 The Type-1 message which this represents a response to.
     * @param challenge The challenge from the domain controller/server.
     * @param target The authentication target.
     */

    print(data)
```

### Generische Typen { #generic-types }

Einige Typen können „Typ-Parameter“ in eckigen Klammern annehmen, um ihre inneren Typen zu definieren, z. B. eine „Liste von Strings“ würde als `list[str]` deklariert.

Diese Typen, die Typ-Parameter annehmen können, werden **generische Typen** oder **Generics** genannt.

Sie können dieselben eingebauten Typen als Generics verwenden (mit eckigen Klammern und Typen darin):

                }
                final NtlmMessage type3 = attemptNegotiation(response);
                if (type3 == null) {
                    return;
                }
                this.connection.setRequestProperty(this.authProperty, this.authMethod + ' ' + Base64.toBase64String(type3.toByteArray()));
                this.connection.connect(); // send type 3
                if (this.cachedOutput != null && this.doOutput) {

    static Stream<Arguments> intGetterProvider() {
        return Stream.of(Arguments.of((IntGetter) FileEntry::getType, -1, "negative type"),
                Arguments.of((IntGetter) FileEntry::getType, 0, "zero type"),
                Arguments.of((IntGetter) FileEntry::getType, Integer.MAX_VALUE, "max type"),

                Arguments.of((IntGetter) FileEntry::getAttributes, 0, "no attributes"),

* Sie können alle gültigen Pydantic-Datentypen hier überprüfen: [Pydantic-Datentypen](https://docs.pydantic.dev/latest/usage/types/types/).

## 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] *}

        scriptEngineFactory.add("type1", engine1);
        scriptEngineFactory.add("type2", engine2);

        // Execute with first engine
        Object result1 = scriptExecutor.execute("type1", "script for engine1");
        assertEquals("engine1:processed: script for engine1", result1);

        // Execute with second engine
        Object result2 = scriptExecutor.execute("type2", "script for engine2");

    @Test
    public void test_constructor_withTypeAndMessage() {
        // Test constructor with type and message
        String type = "Bearer";
        String message = "Invalid access token provided";
        InvalidAccessTokenException exception = new InvalidAccessTokenException(type, message);

        assertEquals(type, exception.getType());
        assertEquals(message, exception.getMessage());

  }

  private static class TypeA {}

  private interface TypeB {}

  private static class HasBoth extends TypeA implements TypeB {}

  @GwtIncompatible // Iterables.filter(Iterable, Class)
  public void testFilterByType() throws Exception {
    HasBoth hasBoth = new HasBoth();
    FluentIterable<TypeA> alist =
        FluentIterable.from(asList(new TypeA(), new TypeA(), hasBoth, new TypeA()));

	"github.com/minio/minio/internal/bpool"
	"github.com/tinylib/msgp/msgp"
)

// Recycler will override the internal reuse in typed handlers.
// When this is supported, the handler will not do internal pooling of objects,
// call Recycle() when the object is no longer needed.
// The recycler should handle nil pointers.
type Recycler interface {
	Recycle()
}

// MSS is a map[string]string that can be serialized.