delete_forecast_export_job ¶

def delete_forecast_export_job(
    self,
    forecast_export_job_arn: "capo_forecast.types.arn.Arn",
    *,
    config_overrides: Optional[forecastClientConfig] = None,
) -> None:
    """<p>Deletes a forecast export job created using the <a>CreateForecastExportJob</a> operation. You can delete only export jobs that have a status of <code>ACTIVE</code> or <code>CREATE_FAILED</code>. To get the status, use the <a>DescribeForecastExportJob</a> operation.</p>

    Args:
        forecast_export_job_arn: <p>The Amazon Resource Name (ARN) of the forecast export job to delete.</p>

    Raises:
        capo_forecast.errors.invalid_input_exception.InvalidInputException: <p>We can't process the request because it includes an invalid value or a value that exceeds the valid range.</p>
        capo_forecast.errors.resource_in_use_exception.ResourceInUseException: <p>The specified resource is in use.</p>
        capo_forecast.errors.resource_not_found_exception.ResourceNotFoundException: <p>We can't find a resource with that Amazon Resource Name (ARN). Check the ARN and try again.</p>
        capo_forecast.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_forecast.types.delete_forecast_export_job_request.DeleteForecastExportJobRequest]",
    ) -> OperationResponse[None]:
        import capo_forecast._operations.amazon_forecast.delete_forecast_export_job

        output, http_response = (
            capo_forecast._operations.amazon_forecast.delete_forecast_export_job.delete_forecast_export_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteForecastExportJob")
    )
    input_: capo_forecast.types.delete_forecast_export_job_request.DeleteForecastExportJobRequest = {
        "forecast_export_job_arn": forecast_export_job_arn
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output