listeners.add(new PerListenerQueue<>(listener, executor));
  }

  /**
   * Enqueues an event to be run on currently known listeners.
   *
   * <p>The {@code toString} method of the Event itself will be used to describe the event in the
   * case of an error.
   *
   * @param event the callback to execute on {@link #dispatch}
   */
  public void enqueue(Event<L> event) {
    enqueueHelper(event, event);
  }

  /**

That means that, clients using your API don't have to check if the value exists or not, they can **assume the field will always be there**, but just that in some cases it will have the default value of `None`.

The way to describe this in OpenAPI, is to mark that field as **required**, because it will always be there.

Because of that, the JSON Schema for a model can be different depending on if it's used for **input or output**:

# Vulnerability Management Policy

This document formally describes the process of addressing and managing a
reported vulnerability that has been found in the MinIO server code base,
any directly connected ecosystem component or a direct / indirect dependency
of the code base.

## Scope

The vulnerability management policy described in this document covers the
process of investigating, assessing and resolving a vulnerability report

# Using TensorFlow Securely

This document discusses the TensorFlow security model. It describes the security
risks to consider when using models, checkpoints or input data for training or
serving. We also provide guidelines on what constitutes a vulnerability in
TensorFlow and how to report them.

This document applies to other repositories in the TensorFlow organization,
covering security practices for the entirety of the TensorFlow ecosystem.

Aqui estão várias formas de se fazer isso.

## `schema_extra` do Pydantic

Você pode declarar um `example` para um modelo Pydantic usando `Config` e `schema_extra`, conforme descrito em <a href="https://docs.pydantic.dev/latest/concepts/json_schema/#schema-customization" class="external-link" target="_blank">Documentação do Pydantic: Schema customization</a>:

```Python hl_lines="15-23"

type IdentityManager interface {
	// DescribeIdentity describes an identity by returning its metadata.
	// e.g. which policy is currently assigned and whether its an admin identity.
	DescribeIdentity(ctx context.Context, identity string) (*kes.IdentityInfo, error)

	// DescribeSelfIdentity describes the identity issuing the request.

 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package org.apache.maven.building;

/**
 * Describes a problem that was encountered during settings building. A problem can either be an exception that was
 * thrown or a simple string message. In addition, a problem carries a hint about its source, e.g. the settings file

import "k8s.io/apimachinery/pkg/runtime/schema/generated.proto";

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/rbac/v1";

// AggregationRule describes how to locate ClusterRoles to aggregate into the ClusterRole
message AggregationRule {
  // ClusterRoleSelectors holds a list of selectors which will be used to find ClusterRoles and create the rules.

  optional string subresource = 1;

  // responseKind describes the group, version, and kind of the serialization schema for the object type this endpoint typically returns.
  // Some subresources do not return normal resources, these will have null return types.
  optional k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionKind responseKind = 2;

  // acceptedTypes describes the kinds that this endpoint accepts.

import "k8s.io/apimachinery/pkg/runtime/schema/generated.proto";

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/rbac/v1alpha1";

// AggregationRule describes how to locate ClusterRoles to aggregate into the ClusterRole
message AggregationRule {
  // ClusterRoleSelectors holds a list of selectors which will be used to find ClusterRoles and create the rules.