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delete_metric_attribution

delete_metric_attribution(
    metric_attribution_arn: Arn,
    *,
    config_overrides: Optional[PersonalizeClientConfig] = None,
) -> None

Deletes a metric attribution.

Parameters:

  • metric_attribution_arn (Arn) –

    The metric attribution's Amazon Resource Name (ARN).

Raises:

Source code in docs_src/capo_personalize/_services/personalize.py
def delete_metric_attribution(
    self,
    metric_attribution_arn: "capo_personalize.types.arn.Arn",
    *,
    config_overrides: Optional[PersonalizeClientConfig] = None,
) -> None:
    """<p>Deletes a metric attribution.</p>

    Args:
        metric_attribution_arn: <p>The metric attribution's Amazon Resource Name (ARN).</p>

    Raises:
        capo_personalize.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
        capo_personalize.errors.resource_in_use_exception.ResourceInUseException: <p>The specified resource is in use.</p>
        capo_personalize.errors.resource_not_found_exception.ResourceNotFoundException: <p>Could not find the specified resource.</p>
        capo_personalize.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_personalize.types.delete_metric_attribution_request.DeleteMetricAttributionRequest]",
    ) -> OperationResponse[None]:
        import capo_personalize._operations.amazon_personalize.delete_metric_attribution

        output, http_response = (
            capo_personalize._operations.amazon_personalize.delete_metric_attribution.delete_metric_attribution(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteMetricAttribution")
    )
    input_: capo_personalize.types.delete_metric_attribution_request.DeleteMetricAttributionRequest = {
        "metric_attribution_arn": metric_attribution_arn
    }

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