*/
    public void running() {}

    /**
     * Called when the service transitions to the {@linkplain State#STOPPING STOPPING} state. The
     * only valid values for {@code from} are {@linkplain State#STARTING STARTING} or {@linkplain
     * State#RUNNING RUNNING}. This occurs when {@link Service#stopAsync} is called.
     *

        // SmbInfoAllocation.decode() always returns 20 bytes regardless of len parameter
        assertEquals(20, bytesRead);
        assertNotNull(response.getInfo());

        // The info should be created with zero values
        SmbInfoAllocation info = (SmbInfoAllocation) response.getInfo();
        assertEquals(0, info.getCapacity());
        assertEquals(0, info.getFree());
    }

    @Test

        // Can still have more elements
        assertTrue(response.hasMoreElements());
    }

    @Test
    @DisplayName("Test reset method")
    void testReset() {
        // Set some values
        response.setDataCount(50);

        // Call reset
        response.reset();

        // After reset, hasMore should be true
        assertTrue(response.hasMoreElements());
    }

TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you
are working with. When loading untrusted checkpoints, the values of the traced
variables from your model are also going to be untrusted. That means that if
your code interacts with the filesystem, network, etc. and uses checkpointed

		if input == nil && clone != nil {
			t.Errorf("Clone(%#v) return value should be equal to nil slice.", input)
		}

		if input != nil && clone == nil {
			t.Errorf("Clone(%#v) return value should not be equal to nil slice.", input)
		}

		if cap(input) != 0 && unsafe.SliceData(input) == unsafe.SliceData(clone) {
			t.Errorf("Clone(%q) return value should not reference inputs backing memory.", input)
		}
	}

   * boolean) headSet()}) to actually construct the view. Consult these methods for a full
   * description of the returned view's behavior.
   *
   * <p><b>Warning:</b> {@code Range}s always represent a range of values using the values' natural
   * ordering. {@code NavigableSet} on the other hand can specify a custom ordering via a {@link
   * Comparator}, which can violate the natural ordering. Using this method (or in general using

    /**
     * Cache map storing related content configurations organized by virtual host key.
     * The outer map key is the virtual host key, and the value is a pair containing:
     * - First: Map of exact term matches (term -> content)
     * - Second: List of regex pattern matches (Pattern -> content template)
     */

Pasa `*`, como el primer parámetro de la función.

Python no hará nada con ese `*`, pero sabrá que todos los parámetros siguientes deben ser llamados como argumentos de palabras clave (parejas key-value), también conocidos como <abbr title="De: K-ey W-ord Arg-uments"><code>kwargs</code></abbr>. Incluso si no tienen un valor por defecto.

{* ../../docs_src/path_params_numeric_validations/tutorial003_py310.py hl[7] *}

**Pydantic v2**가 릴리스된 이후, 생성되는 OpenAPI는 이전보다 조금 더 정확하고 **올바르게** 만들어집니다. 😎

실제로 어떤 경우에는, 같은 Pydantic 모델에 대해 OpenAPI 안에 **두 개의 JSON Schema**가 생기기도 합니다. **기본값(default value)**이 있는지 여부에 따라, 입력용과 출력용으로 나뉩니다.

이것이 어떻게 동작하는지, 그리고 필요하다면 어떻게 변경할 수 있는지 살펴보겠습니다.

## 입력과 출력을 위한 Pydantic 모델 { #pydantic-models-for-input-and-output }

예를 들어, 다음처럼 기본값이 있는 Pydantic 모델이 있다고 해보겠습니다:

        final SearchResponse response =
                client.prepareSearch().setIndices(index).setQuery(query).setSize(0).execute().actionGet(settings.getSearchTimeout());

        return response.getHits().getTotalHits().value();
    }

    /**
     * A mutable flag to signal stopping a scroll operation.
     */
    public static class StopFlag {
        private boolean stopped = false;

        /**