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
|