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list_collaboration_configured_model_algorithm_associations

list_collaboration_configured_model_algorithm_associations(
    collaboration_identifier: UUID,
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
    next_token: Optional[NextToken] = None,
    max_results: Optional[MaxResults] = None,
) -> ListCollaborationConfiguredModelAlgorithmAssociationsResponse

Returns a list of the configured model algorithm associations in a collaboration.

Parameters:

  • next_token (Optional[NextToken], default: None ) –

    The token value retrieved from a previous call to access the next page of results.

  • max_results (Optional[MaxResults], default: None ) –

    The maximum size of the results that is returned per call.

  • collaboration_identifier (UUID) –

    The collaboration ID of the collaboration that contains the configured model algorithm associations that you are interested in.

Raises:

Source code in docs_src/capo_cleanroomsml/_services/clean_rooms_ml.py
def list_collaboration_configured_model_algorithm_associations(
    self,
    collaboration_identifier: "capo_cleanroomsml.types.uuid.UUID",
    *,
    config_overrides: Optional[CleanRoomsMLClientConfig] = None,
    next_token: Optional["capo_cleanroomsml.types.next_token.NextToken"] = None,
    max_results: Optional["capo_cleanroomsml.types.max_results.MaxResults"] = None,
) -> "capo_cleanroomsml.types.list_collaboration_configured_model_algorithm_associations_response.ListCollaborationConfiguredModelAlgorithmAssociationsResponse":
    """<p>Returns a list of the configured model algorithm associations in a collaboration.</p>

    Args:
        next_token: <p>The token value retrieved from a previous call to access the next page of results.</p>
        max_results: <p>The maximum size of the results that is returned per call.</p>
        collaboration_identifier: <p>The collaboration ID of the collaboration that contains the configured model algorithm associations that you are interested in.</p>

    Raises:
        capo_cleanroomsml.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_cleanroomsml.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_cleanroomsml.errors.validation_exception.ValidationException: <p>The request parameters for this request are incorrect.</p>
        capo_cleanroomsml.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanroomsml.types.list_collaboration_configured_model_algorithm_associations_request.ListCollaborationConfiguredModelAlgorithmAssociationsRequest]",
    ) -> OperationResponse[
        "capo_cleanroomsml.types.list_collaboration_configured_model_algorithm_associations_response.ListCollaborationConfiguredModelAlgorithmAssociationsResponse"
    ]:
        import capo_cleanroomsml._operations.aws_stark_control_service.list_collaboration_configured_model_algorithm_associations

        output, http_response = (
            capo_cleanroomsml._operations.aws_stark_control_service.list_collaboration_configured_model_algorithm_associations.list_collaboration_configured_model_algorithm_associations(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("ListCollaborationConfiguredModelAlgorithmAssociations"),
    )
    input_: capo_cleanroomsml.types.list_collaboration_configured_model_algorithm_associations_request.ListCollaborationConfiguredModelAlgorithmAssociationsRequest = {
        "collaboration_identifier": collaboration_identifier
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results

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