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update_collaboration

update_collaboration(
    collaboration_identifier: CollaborationIdentifier,
    *,
    config_overrides: Optional[CleanRoomsClientConfig] = None,
    name: Optional[CollaborationName] = None,
    description: Optional[CollaborationDescription] = None,
    analytics_engine: Optional[AnalyticsEngine] = None,
) -> UpdateCollaborationOutput

Updates collaboration metadata and can only be called by the collaboration owner.

Parameters:

  • collaboration_identifier (CollaborationIdentifier) –

    The identifier for the collaboration.

  • name (Optional[CollaborationName], default: None ) –

    A human-readable identifier provided by the collaboration owner. Display names are not unique.

  • description (Optional[CollaborationDescription], default: None ) –

    A description of the collaboration.

  • analytics_engine (Optional[AnalyticsEngine], default: None ) –

    The analytics engine.

    After July 16, 2025, the CLEAN_ROOMS_SQL parameter will no longer be available.

Raises:

Source code in docs_src/capo_cleanrooms/_services/clean_rooms.py
def update_collaboration(
    self,
    collaboration_identifier: "capo_cleanrooms.types.collaboration_identifier.CollaborationIdentifier",
    *,
    config_overrides: Optional[CleanRoomsClientConfig] = None,
    name: Optional[
        "capo_cleanrooms.types.collaboration_name.CollaborationName"
    ] = None,
    description: Optional[
        "capo_cleanrooms.types.collaboration_description.CollaborationDescription"
    ] = None,
    analytics_engine: Optional[
        "capo_cleanrooms.types.analytics_engine.AnalyticsEngine"
    ] = None,
) -> "capo_cleanrooms.types.update_collaboration_output.UpdateCollaborationOutput":
    """<p>Updates collaboration metadata and can only be called by the collaboration owner.</p>

    Args:
        collaboration_identifier: <p>The identifier for the collaboration.</p>
        name: <p>A human-readable identifier provided by the collaboration owner. Display names are not unique.</p>
        description: <p>A description of the collaboration.</p>
        analytics_engine: <p>The analytics engine.</p> <note> <p>After July 16, 2025, the <code>CLEAN_ROOMS_SQL</code> parameter will no longer be available. </p> </note>

    Raises:
        capo_cleanrooms.errors.access_denied_exception.AccessDeniedException: <p>Caller does not have sufficient access to perform this action.</p>
        capo_cleanrooms.errors.internal_server_exception.InternalServerException: <p>Unexpected error during processing of request.</p>
        capo_cleanrooms.errors.throttling_exception.ThrottlingException: <p>Request was denied due to request throttling.</p>
        capo_cleanrooms.errors.validation_exception.ValidationException: <p>The input fails to satisfy the specified constraints.</p>
        capo_cleanrooms.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanrooms.types.update_collaboration_input.UpdateCollaborationInput]",
    ) -> OperationResponse[
        "capo_cleanrooms.types.update_collaboration_output.UpdateCollaborationOutput"
    ]:
        import capo_cleanrooms._operations.aws_bastion_control_plane_service_lambda.update_collaboration

        output, http_response = (
            capo_cleanrooms._operations.aws_bastion_control_plane_service_lambda.update_collaboration.update_collaboration(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateCollaboration")
    )
    input_: capo_cleanrooms.types.update_collaboration_input.UpdateCollaborationInput = {
        "collaboration_identifier": collaboration_identifier
    }
    if name is not None:
        input_["name"] = name
    if description is not None:
        input_["description"] = description
    if analytics_engine is not None:
        input_["analytics_engine"] = analytics_engine

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