query_lineage ¶

def query_lineage(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    start_arns: Optional[
        "capo_sagemaker.types.query_lineage_start_arns.QueryLineageStartArns"
    ] = None,
    direction: Optional["capo_sagemaker.types.direction.Direction"] = None,
    include_edges: Optional["capo_sagemaker.types.boolean.Boolean"] = None,
    filters: Optional["capo_sagemaker.types.query_filters.QueryFilters"] = None,
    max_depth: Optional[
        "capo_sagemaker.types.query_lineage_max_depth.QueryLineageMaxDepth"
    ] = None,
    max_results: Optional[
        "capo_sagemaker.types.query_lineage_max_results.QueryLineageMaxResults"
    ] = None,
    next_token: Optional["capo_sagemaker.types.string8192.String8192"] = None,
) -> "capo_sagemaker.types.query_lineage_response.QueryLineageResponse":
    """<p>Use this action to inspect your lineage and discover relationships between entities. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/querying-lineage-entities.html"> Querying Lineage Entities</a> in the <i>Amazon SageMaker Developer Guide</i>.</p>

    Args:
        start_arns: <p>A list of resource Amazon Resource Name (ARN) that represent the starting point for your lineage query.</p>
        direction: <p>Associations between lineage entities have a direction. This parameter determines the direction from the StartArn(s) that the query traverses.</p>
        include_edges: <p> Setting this value to <code>True</code> retrieves not only the entities of interest but also the <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking-entities.html">Associations</a> and lineage entities on the path. Set to <code>False</code> to only return lineage entities that match your query.</p>
        filters: <p>A set of filtering parameters that allow you to specify which entities should be returned.</p> <ul> <li> <p>Properties - Key-value pairs to match on the lineage entities' properties.</p> </li> <li> <p>LineageTypes - A set of lineage entity types to match on. For example: <code>TrialComponent</code>, <code>Artifact</code>, or <code>Context</code>.</p> </li> <li> <p>CreatedBefore - Filter entities created before this date.</p> </li> <li> <p>ModifiedBefore - Filter entities modified before this date.</p> </li> <li> <p>ModifiedAfter - Filter entities modified after this date.</p> </li> </ul>
        max_depth: <p>The maximum depth in lineage relationships from the <code>StartArns</code> that are traversed. Depth is a measure of the number of <code>Associations</code> from the <code>StartArn</code> entity to the matched results.</p>
        max_results: <p>Limits the number of vertices in the results. Use the <code>NextToken</code> in a response to to retrieve the next page of results.</p>
        next_token: <p>Limits the number of vertices in the request. Use the <code>NextToken</code> in a response to to retrieve the next page of results.</p>

    Raises:
        capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.query_lineage_request.QueryLineageRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.query_lineage_response.QueryLineageResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.query_lineage

        output, http_response = (
            capo_sagemaker._operations.sage_maker.query_lineage.query_lineage(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("QueryLineage")
    )
    input_: capo_sagemaker.types.query_lineage_request.QueryLineageRequest = {}
    if start_arns is not None:
        input_["start_arns"] = start_arns
    if direction is not None:
        input_["direction"] = direction
    if include_edges is not None:
        input_["include_edges"] = include_edges
    if filters is not None:
        input_["filters"] = filters
    if max_depth is not None:
        input_["max_depth"] = max_depth
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token

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