service.shutdown();
    }
  }

  public void testRejectedExecutionThrownWithMultipleCalls() throws Exception {
    CountDownLatch latch = new CountDownLatch(1);
    SettableFuture<?> future = SettableFuture.create();
    Executor delegate =
        new Executor() {
          @Override
          public void execute(Runnable task) {
            if (future.set(null)) {
              awaitUninterruptibly(latch);

    private boolean useMultiChannelExplicitlySet = false;
    private boolean channelBindingPolicyExplicitlySet = false;

    /**
     * Create a configuration backed by properties
     *
     * @param props properties object containing JCIFS configuration settings
     * @throws CIFSException if configuration initialization fails
     */

        verify(request, times(1)).getOverrideTimeout();
    }

    @Test
    @DisplayName("Test Request with concrete implementation")
    void testConcreteImplementation() {
        // Create a concrete implementation for testing
        TestRequest testRequest = new TestRequest();

        // Test initResponse
        CommonServerMessageBlockResponse testResponse = testRequest.initResponse(context);

## Importe o `BaseModel` do Pydantic { #import-pydantics-basemodel }

Primeiro, você precisa importar `BaseModel` do `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Crie seu modelo de dados { #create-your-data-model }

Então você declara seu modelo de dados como uma classe que herda `BaseModel`.

Utilize os tipos Python padrão para todos os atributos:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

{* ../../docs_src/dependencies/tutorial011_an_py310.py hl[9] *}

Bu durumda **FastAPI**, `__init__` ile asla uğraşmaz veya onu önemsemez; onu doğrudan kendi kodumuzda kullanırız.

## Bir instance oluşturma { #create-an-instance }

Bu class'tan bir instance'ı şöyle oluşturabiliriz:

{* ../../docs_src/dependencies/tutorial011_an_py310.py hl[18] *}

### Создание класса `Enum` { #create-an-enum-class }

Импортируйте `Enum` и создайте подкласс, который наследуется от `str` и `Enum`.

Мы наследуемся от `str`, чтобы документация API могла понять, что значения должны быть типа `string` и отображалась правильно.

{* ../../docs_src/dependencies/tutorial011_an_py310.py hl[9] *}

В этом случае **FastAPI** вовсе не трогает `__init__` и не зависит от него — мы используем его напрямую в нашем коде.

## Создаём экземпляр { #create-an-instance }

Мы можем создать экземпляр этого класса так:

{* ../../docs_src/dependencies/tutorial011_an_py310.py hl[18] *}

func BenchmarkListObjects(b *testing.B) {
	// Make a temporary directory to use as the obj.
	directory := b.TempDir()

	// Create the obj.
	obj := initFSObjectsB(directory, b)

	bucket := "ls-benchmark-bucket"
	// Create a bucket.
	err := obj.MakeBucket(b.Context(), bucket, MakeBucketOptions{})
	if err != nil {
		b.Fatal(err)
	}

                // this is the signature error
                throw new SMBProtocolDowngradeException("Signature error during negotiate validation", e);
            }

            // other errors are treated as success
            return;
        }
        final ValidateNegotiateInfoResponse out = resp.getOutputData(ValidateNegotiateInfoResponse.class);

    assertCorrectSlice(100, 100, 10, 0);
    assertCorrectSlice(100, 101, 10, 0);
  }

  /**
   * Tests that the default slice() behavior is correct when the source is sliced starting at an
   * offset that is greater than the current length of the source, a stream is then opened to that
   * source, and finally additional bytes are appended to the source before the stream is read.
   *