Then you can declare an `alias`, and that alias is what will be used to find the parameter value:

{* ../../docs_src/query_params_str_validations/tutorial009_an_py310.py hl[9] *}

## Deprecating parameters { #deprecating-parameters }

Now let's say you don't like this parameter anymore.

        reportPlugins = new Xpp3Dom("reportPlugins", location);
        configuration.addChild(reportPlugins);

        boolean hasMavenProjectInfoReportsPlugin = false;

        /* waiting for MSITE-484 before deprecating <reporting> section
        if ( !reporting.getPlugins().isEmpty()
            && request.getValidationLevel() >= ModelBuildingRequest.VALIDATION_LEVEL_MAVEN_3_1 )
        {

    dependentSchemas: Optional[dict[str, "SchemaOrBool"]] = None
    prefixItems: Optional[list["SchemaOrBool"]] = None
    # TODO: uncomment and remove below when deprecating Pydantic v1
    # It generates a list of schemas for tuples, before prefixItems was available
    # items: Optional["SchemaOrBool"] = None
    items: Optional[Union["SchemaOrBool", list["SchemaOrBool"]]] = None

    # This expects that GenerateJsonSchema was already used to generate the definitions
    json_schema = field_mapping[(field, override_mode or field.mode)]
    if "$ref" not in json_schema:
        # TODO remove when deprecating Pydantic v1
        # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207
        json_schema["title"] = field.field_info.title or field_alias.title().replace(

Entonces puedes declarar un `alias`, y ese alias será usado para encontrar el valor del parámetro:

{* ../../docs_src/query_params_str_validations/tutorial009_an_py310.py hl[9] *}

## Declarar parámetros obsoletos { #deprecating-parameters }

Ahora digamos que ya no te gusta este parámetro.

        `tf.data.Dataset.bucket_by_sequence_length` and deprecating the
        experimental endpoint.
    *   Promoting `tf.data.experimental.get_single_element` API to
        `tf.data.Dataset.get_single_element` and deprecating the experimental
        endpoint.
    *   Promoting `tf.data.experimental.group_by_window` API to
        `tf.data.Dataset.group_by_window` and deprecating the experimental
        endpoint.

- Deprecated metrics will be hidden as per the metrics deprecation policy. https://kubernetes.io/docs/reference/using-api/deprecation-policy/#deprecating-a-metric . ([#133436](https://github.com/kubernetes/kubernetes/pull/133436), [@richabanker](https://github.com/richabanker)) [SIG Architecture, Instrumentation and Network]

            # would pass the validation and be returned as is.
            # By being a new field, no inheritance will be passed as is. A new model
            # will always be created.
            # TODO: remove when deprecating Pydantic v1
            self.secure_cloned_response_field: Optional[ModelField] = (
                create_cloned_field(self.response_field)
            )
        else:

    - [RBAC](#rbac-1)
    - [Scheduling](#scheduling-1)
    - [Service Catalog](#service-catalog)
    - [Volumes](#volumes-1)
  - [Deprecations](#deprecations)
    - [Cluster Provisioning Scripts](#cluster-provisioning-scripts)
    - [kubeadm](#kubeadm-1)
    - [Other Deprecations](#other-deprecations)
  - [Changes to API Resources](#changes-to-api-resources)
    - [ABAC](#abac)
    - [Admission Control](#admission-control)

  - [Urgent Upgrade Notes](#urgent-upgrade-notes)
    - [(No, really, you MUST read this before you upgrade)](#no-really-you-must-read-this-before-you-upgrade)
  - [Changes by Kind](#changes-by-kind-3)
    - [Deprecation](#deprecation)
    - [API Change](#api-change)
    - [Feature](#feature-2)
    - [Failing Test](#failing-test)
    - [Bug or Regression](#bug-or-regression-3)
    - [Other (Cleanup or Flake)](#other-cleanup-or-flake-1)