delete_db_cluster ¶

def delete_db_cluster(
    self,
    *,
    config_overrides: Optional[DocDBClientConfig] = None,
    db_cluster_identifier: Optional["capo_docdb.types.string.String"] = None,
    skip_final_snapshot: Optional["capo_docdb.types.boolean.Boolean"] = None,
    final_db_snapshot_identifier: Optional["capo_docdb.types.string.String"] = None,
) -> "capo_docdb.types.delete_db_cluster_result.DeleteDBClusterResult":
    """<p>Deletes a previously provisioned cluster. When you delete a cluster, all automated backups for that cluster are deleted and can't be recovered. Manual DB cluster snapshots of the specified cluster are not deleted.</p> <p></p>

    Args:
        db_cluster_identifier: <p>The cluster identifier for the cluster to be deleted. This parameter isn't case sensitive.</p> <p>Constraints:</p> <ul> <li> <p>Must match an existing <code>DBClusterIdentifier</code>.</p> </li> </ul>
        skip_final_snapshot: <p> Determines whether a final cluster snapshot is created before the cluster is deleted. If <code>true</code> is specified, no cluster snapshot is created. If <code>false</code> is specified, a cluster snapshot is created before the DB cluster is deleted. </p> <note> <p>If <code>SkipFinalSnapshot</code> is <code>false</code>, you must specify a <code>FinalDBSnapshotIdentifier</code> parameter.</p> </note> <p>Default: <code>false</code> </p>
        final_db_snapshot_identifier: <p> The cluster snapshot identifier of the new cluster snapshot created when <code>SkipFinalSnapshot</code> is set to <code>false</code>. </p> <note> <p> Specifying this parameter and also setting the <code>SkipFinalShapshot</code> parameter to <code>true</code> results in an error. </p> </note> <p>Constraints:</p> <ul> <li> <p>Must be from 1 to 255 letters, numbers, or hyphens.</p> </li> <li> <p>The first character must be a letter.</p> </li> <li> <p>Cannot end with a hyphen or contain two consecutive hyphens.</p> </li> </ul>

    Raises:
        capo_docdb.errors.db_cluster_not_found_fault.DBClusterNotFoundFault: <p> <code>DBClusterIdentifier</code> doesn't refer to an existing cluster. </p>
        capo_docdb.errors.db_cluster_snapshot_already_exists_fault.DBClusterSnapshotAlreadyExistsFault: <p>You already have a cluster snapshot with the given identifier.</p>
        capo_docdb.errors.invalid_db_cluster_snapshot_state_fault.InvalidDBClusterSnapshotStateFault: <p>The provided value isn't a valid cluster snapshot state.</p>
        capo_docdb.errors.invalid_db_cluster_state_fault.InvalidDBClusterStateFault: <p>The cluster isn't in a valid state.</p>
        capo_docdb.errors.snapshot_quota_exceeded_fault.SnapshotQuotaExceededFault: <p>The request would cause you to exceed the allowed number of snapshots.</p>
        capo_docdb.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_docdb.types.delete_db_cluster_message.DeleteDBClusterMessage]",
    ) -> OperationResponse[
        "capo_docdb.types.delete_db_cluster_result.DeleteDBClusterResult"
    ]:
        import capo_docdb._operations.amazon_rd_sv19.delete_db_cluster

        output, http_response = (
            capo_docdb._operations.amazon_rd_sv19.delete_db_cluster.delete_db_cluster(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("DeleteDBCluster")
    )
    input_: capo_docdb.types.delete_db_cluster_message.DeleteDBClusterMessage = {}
    if db_cluster_identifier is not None:
        input_["db_cluster_identifier"] = db_cluster_identifier
    if skip_final_snapshot is not None:
        input_["skip_final_snapshot"] = skip_final_snapshot
    if final_db_snapshot_identifier is not None:
        input_["final_db_snapshot_identifier"] = final_db_snapshot_identifier

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