describe_dashboard async ¶

async def describe_dashboard(
    self,
    aws_account_id: "capo_quicksight.types.aws_account_id.AwsAccountId",
    dashboard_id: "capo_quicksight.types.short_restrictive_resource_id.ShortRestrictiveResourceId",
    *,
    config_overrides: Optional[AsyncQuickSightClientConfig] = None,
    version_number: Optional[
        "capo_quicksight.types.version_number.VersionNumber"
    ] = None,
    alias_name: Optional["capo_quicksight.types.alias_name.AliasName"] = None,
) -> "capo_quicksight.types.describe_dashboard_response.DescribeDashboardResponse":
    """<p>Provides a summary for a dashboard.</p>

    Args:
        aws_account_id: <p>The ID of the Amazon Web Services account that contains the dashboard that you're describing.</p>
        dashboard_id: <p>The ID for the dashboard.</p>
        version_number: <p>The version number for the dashboard. If a version number isn't passed, the latest published dashboard version is described. </p>
        alias_name: <p>The alias name.</p>

    Raises:
        capo_quicksight.errors.access_denied_exception.AccessDeniedException: <p>You don't have access to this item. The provided credentials couldn't be validated. You might not be authorized to carry out the request. Make sure that your account is authorized to use the Amazon Quick Sight service, that your policies have the correct permissions, and that you are using the correct credentials.</p>
        capo_quicksight.errors.internal_failure_exception.InternalFailureException: <p>An internal failure occurred.</p>
        capo_quicksight.errors.invalid_parameter_value_exception.InvalidParameterValueException: <p>One or more parameters has a value that isn't valid.</p>
        capo_quicksight.errors.resource_not_found_exception.ResourceNotFoundException: <p>One or more resources can't be found.</p>
        capo_quicksight.errors.throttling_exception.ThrottlingException: <p>Access is throttled.</p>
        capo_quicksight.errors.unsupported_user_edition_exception.UnsupportedUserEditionException: <p>This error indicates that you are calling an operation on an Amazon Quick Suite subscription where the edition doesn't include support for that operation. Amazon Quick Suite currently has Standard Edition and Enterprise Edition. Not every operation and capability is available in every edition.</p>
        capo_quicksight.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_quicksight.types.describe_dashboard_request.DescribeDashboardRequest]",
    ) -> AsyncOperationResponse[
        "capo_quicksight.types.describe_dashboard_response.DescribeDashboardResponse"
    ]:
        import capo_quicksight._operations.quick_sight_20180401.describe_dashboard

        (
            output,
            http_response,
        ) = await capo_quicksight._operations.quick_sight_20180401.describe_dashboard.async_describe_dashboard(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_output(
        output: "capo_quicksight.types.describe_dashboard_response.DescribeDashboardResponse",
    ) -> dict[str, Any]:
        import capo_quicksight.types.describe_dashboard_response

        return capo_quicksight.types.describe_dashboard_response.redact_sensitive(
            output
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("DescribeDashboard", redact_output=_redact_output),
    )
    input_: capo_quicksight.types.describe_dashboard_request.DescribeDashboardRequest = {
        "aws_account_id": aws_account_id,
        "dashboard_id": dashboard_id,
    }
    if version_number is not None:
        input_["version_number"] = version_number
    if alias_name is not None:
        input_["alias_name"] = alias_name

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output