assertEquals(type1, type2);

        Map<String, Object> source1 = event.toSource();
        Map<String, Object> source2 = event.toSource();
        assertSame(source1, source2);
    }

    // Test edge cases for version numbers
    @Test
    public void test_versionNumberEdgeCases() {
        TestSearchLogEvent event = new TestSearchLogEvent("id", 0L, "type");

        // Test minimum value

                }
                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) {

                // Expected structure: Type (2 bytes) + Length (2 bytes) + Data (Length bytes)
                // For domain: Type 0x0002 (NetBIOS Domain Name)
                // For server: Type 0x0001 (NetBIOS Computer Name)

                // Verify domain part
                assertEquals(2, Type2Message.readUShort(targetInfo, 0)); // Type 0x0002

    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):

# Fortgeschrittene Python-Typen { #advanced-python-types }

Hier sind einige zusätzliche Ideen, die beim Arbeiten mit Python-Typen nützlich sein könnten.

## `Union` oder `Optional` verwenden { #using-union-or-optional }

Wenn Ihr Code aus irgendeinem Grund nicht `|` verwenden kann, z. B. wenn es nicht in einer Typannotation ist, sondern in etwas wie `response_model=`, können Sie anstelle des senkrechten Strichs (`|`) `Union` aus `typing` verwenden.

import types
from collections.abc import Callable
from enum import Enum
from typing import Any, TypeVar, Union

from pydantic import BaseModel
from pydantic.main import IncEx as IncEx

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[type[BaseModel] | type[Enum], str]

O Python possui suporte para "type hints" opcionais (também chamados de "type annotations").

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

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

  }

  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.

     * Artifact type name for a JAR file containing test sources.
     */
    String TEST_JAVA_SOURCE = "test-java-source";

    /**
     * Returns the dependency type id.
     * The id uniquely identifies this <i>dependency type</i>.
     *
     * @return the id of this type, never {@code null}.
     */
    @Nonnull
    @Override
    String id();

    /**
     * Returns the dependency type language.
     *