package loggertypes

// TargetType indicates type of the target e.g. console, http, kafka
type TargetType uint8

//go:generate stringer -type=TargetType -trimprefix=Target $GOFILE

// Constants for target types
const (
	_ TargetType = iota
	TargetConsole
	TargetHTTP
	TargetKafka
)

// TargetStats contains statistics for a target.
type TargetStats struct {

# Gelişmiş Python Tipleri { #advanced-python-types }

Python tipleriyle çalışırken işinize yarayabilecek bazı ek fikirler.

## `Union` veya `Optional` Kullanımı { #using-union-or-optional }

Kodunuz herhangi bir nedenle `|` kullanamıyorsa — örneğin bir tip açıklamasında (type annotation) değil de `response_model=` gibi bir yerdeyse — dikey çizgi (`|`) yerine `typing` içindeki `Union`'ı kullanabilirsiniz.

# Tipos Avançados de Python { #advanced-python-types }

Aqui estão algumas ideias adicionais que podem ser úteis ao trabalhar com tipos em Python.

## Usando `Union` ou `Optional` { #using-union-or-optional }

Se, por algum motivo, seu código não puder usar `|`, por exemplo, se não for em uma anotação de tipo, mas em algo como `response_model=`, em vez de usar a barra vertical (`|`) você pode usar `Union` do `typing`.

Steve B <******@****.***> 1557567827 +0200

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]

 */

package jcifs.dcerpc.ndr;

/**
 * NDR representation of a hyper integer (8-byte signed integer).
 */
public class NdrHyper extends NdrObject {

    /**
     * The hyper integer value.
     */
    public long value;

    /**
     * Constructs an NdrHyper with the specified value.
     *
     * @param value the hyper integer value
     */
    public NdrHyper(final long value) {

        NdrHyper hyper = new NdrHyper(5L);
        assertThrows(NullPointerException.class, () -> hyper.encode(null));
    }

    /**
     * Ensure decode throws NPE when passed a null buffer.
     */
    @Test
    @DisplayName("Decode with null buffer throws NullPointerException")
    public void testDecodeNullBuffer() throws NdrException {
        NdrHyper hyper = new NdrHyper(0L);

     * 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.
     *

        // Assert - Verify we got the 401 response (simplified test)
        assertEquals(HTTP_UNAUTHORIZED, responseCode);

        // In a real scenario, the connection would reconnect and send Type1/Type3 messages
        // This simplified test just verifies the initial handshake detection
    }

    /**
     * Test handshake failure when the server does not return an NTLM challenge.
     * @throws IOException

* Datenvalidierung
* Automatische Dokumentation

## Spezielle Typen und Validierungen { #special-types-and-validation }

Abgesehen von normalen einfachen Typen wie `str`, `int`, `float`, usw. können Sie komplexere einfache Typen verwenden, die von `str` erben.

Um alle Optionen kennenzulernen, die Sie haben, schauen Sie sich [Pydantics Typübersicht](https://docs.pydantic.dev/latest/concepts/types/) an. Sie werden einige Beispiele im nächsten Kapitel kennenlernen.