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ragraph.utils

Graph handling utilities

get_up_to_depth 

get_up_to_depth(
    roots: List[Node], depth: int
) -> Generator[Node, None, None]

Get nodes up to a certain depth with bus nodes at the start of child lists.

Source code in src/ragraph/utils.py 
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def get_up_to_depth(roots: List["Node"], depth: int) -> Generator["Node", None, None]:
    """Get nodes up to a certain depth with bus nodes at the start of child lists."""
    for node in roots:
        if node.is_leaf or node.depth == depth:
            yield node
            continue

        children = sorted(node.children, key=lambda n: n.is_bus, reverse=True)

        if node.depth == depth - 1:
            yield from children
        else:
            yield from get_up_to_depth(children, depth)

is_dependent 

is_dependent(
    graph,
    lead_nodes: List[Node],
    node: Node,
    edge_kinds=Set[str],
) -> bool

Check if a node is dependent on the lead node kind.

E.g. an edge of the allowed kinds exists to or from the lead nodes.

Source code in src/ragraph/utils.py 
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def is_dependent(graph, lead_nodes: List["Node"], node: "Node", edge_kinds=Set[str]) -> bool:
    """Check if a node is dependent on the lead node kind.

    E.g. an edge of the allowed kinds exists to or from the lead nodes.
    """
    return any(
        True for e in graph.edges_between_all(lead_nodes, [node]) if e.kind in edge_kinds
    ) or any(True for e in graph.edges_between_all([node], lead_nodes) if e.kind in edge_kinds)

select_nodes 

select_nodes(
    graph: Graph,
    node_kinds: List[str],
    edge_kinds: List[str],
    depth: int,
    selection_mode: str,
) -> List[Node]

Select specific nodes from this graph in a structured order.

Parameters:

Name Type Description Default
graph Graph

Graph to fetch data from.

 required
node_kinds List[str]

The kind of nodes to be selected.

 required
edge_kinds List[str]

The kind of edges to be selected.

 required
depth int

The maximum depth of node to be selected.

 required
selection_mode str

The selection mode. Either 'dependent' or 'independent'.

 required
Note

The selection mode argument determines how nodes of different kinds are selected. If the selection mode is set to 'dependent', the first node kind in the node_kinds list is considered to be the 'lead node kind'. Nodes of different kind than the lead node kind, are only selected if they have a dependency with at least one of the selected nodes of the lead node kind. If the selection mode is set to 'independent' this dependency condition is dropped.

Source code in src/ragraph/utils.py 
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def select_nodes(
    graph: "Graph", node_kinds: List[str], edge_kinds: List[str], depth: int, selection_mode: str
) -> List["Node"]:
    """Select specific nodes from this graph in a structured order.

    Arguments:
        graph: Graph to fetch data from.
        node_kinds: The kind of nodes to be selected.
        edge_kinds: The kind of edges to be selected.
        depth: The maximum depth of node to be selected.
        selection_mode: The selection mode. Either 'dependent' or 'independent'.

    Note:
        The selection mode argument determines how nodes of different kinds are
        selected. If the selection mode is set to 'dependent', the first node kind
        in the `node_kinds` list is considered to be the 'lead node kind'.
        Nodes of different kind than the lead node kind, are only selected if they
        have a dependency with at least one of the selected nodes of the lead node
        kind. If the selection mode is set to 'independent' this dependency
        condition is dropped.
    """
    node_kinds = node_kinds or graph.node_kinds

    if selection_mode not in ["dependent", "independent"]:
        raise ValueError(
            f'Unrecognized selection mode "{selection_mode}", '
            'should be "independent" or "dependent".'
        )

    node_kind_order = {kind: i for i, kind in enumerate(node_kinds)}
    roots = sorted(
        [n for n in graph.roots if n.kind in node_kinds],
        key=lambda n: node_kind_order[n.kind],
    )

    nodes = list(get_up_to_depth(roots, depth))

    if selection_mode == "independent" or len(node_kinds) == 1:
        return nodes

    lead_kind = node_kinds[0]
    i = 0
    while i < len(nodes) and nodes[i].kind == lead_kind:
        i += 1
    lead_nodes, candidate_nodes = nodes[:i], nodes[i:]

    edge_kinds = edge_kinds or graph.edge_kinds
    edge_kindset = set(edge_kinds)
    dependent_nodes = [
        n for n in candidate_nodes if is_dependent(graph, lead_nodes, n, edge_kindset)
    ]

    return lead_nodes + dependent_nodes