} else {
      assertThat(certificateSANs(peerCertificate))
        .containsExactly("*.bar.com", "*.������.co.jp")
    }

    // try the foo.com variations
    assertThat(verifier.verify("foo.com", session)).isFalse()
    assertThat(verifier.verify("www.foo.com", session)).isFalse()
    assertThat(verifier.verify("\u82b1\u5b50.foo.com", session)).isFalse()

container logs, and more. While Kubernetes already validates the proxying address for Nodes, a bug in kube-apiserver made it possible to bypass this validation. Bypassing this validation could allow authenticated requests destined for Nodes to be redirected to the API Server through its private network.

The merged fix enforces validation against the proxying address for a Node. In some cases, the fix can break clients that depend on the `nodes/proxy` subresource, specifically if a kubelet...

### Bug or Regression

- EndpointSlice IP validation now matches Endpoints IP validation. ([#101084](https://github.com/kubernetes/kubernetes/pull/101084), [@robscott](https://github.com/robscott)) [SIG Apps and Network]

## Pydantic models { #pydantic-models }

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> is a Python library to perform data validation.

You declare the "shape" of the data as classes with attributes.

And each attribute has a type.

 * </p>
 * <ul>
 *   <li>Namespace awareness</li>
 *   <li>Coalescing</li>
 *   <li>Entity expansion</li>
 *   <li>Ignoring comments and whitespace</li>
 *   <li>Validation</li>
 *   <li>XInclude awareness</li>
 * </ul>
 *
 * <p>
 * It also allows defining field rules using XPath expressions to extract specific data from the XML document and map it to fields in the ResultData.

    } else {
      return subListUnchecked(fromIndex, toIndex);
    }
  }

  /**
   * Called by the default implementation of {@link #subList} when {@code toIndex - fromIndex > 1},
   * after index validation has already been performed.
   */
  ImmutableList<E> subListUnchecked(int fromIndex, int toIndex) {
    return new SubList(fromIndex, toIndex - fromIndex);
  }

	objAPI := newObjectLayerFn()

	// We must have a global lock for this so nobody else modifies env while we do.
	defer env.LockSetEnv()()

	// Disable merging env values with config for validation.
	env.SetEnvOff()

	// Enable env values to validate KMS.
	defer env.SetEnvOn()
	if subSys != "" {
		return validateSubSysConfig(ctx, s, subSys, objAPI)
	}

                    not include that field, the JSON sent to the client would not have
                    that `password`.
                * Validation: whatever you return will be serialized with the
                    `response_model`, converting any data as necessary to generate the
                    corresponding JSON. But if the data in the object returned is not

/// tip | Consejo

Para entender las variables de entorno, puedes leer [Variables de Entorno](../environment-variables.md){.internal-link target=_blank}.

///

## Tipos y validación { #types-and-validation }

그리고 역시나 모든 에디터 도움을 받게 되겠죠.

<img src="/img/python-types/image06.png">

## Pydantic 모델

<a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>은 데이터 검증(Validation)을 위한 파이썬 라이브러리입니다.

당신은 속성들을 포함한 클래스 형태로 "모양(shape)"을 선언할 수 있습니다.

그리고 각 속성은 타입을 가지고 있습니다.

이 클래스를 활용하여서 값을 가지고 있는 인스턴스를 만들게 되면, 필요한 경우에는 적당한 타입으로 변환까지 시키기도 하여 데이터가 포함된 객체를 반환합니다.