Load the edges for a list of nodes. You must override this method. You will be passed a list of nodes, and should return a dictionary mapping each node to the list of nodes that can be reached by following its the edges which originate at it: for example, the child nodes of an object which has a parent-child relationship to other objects.

The intent of this method is to allow you to issue a single query per graph level for graphs which are stored as edge tables in the database. Generally, you will load all the objects which correspond to the list of nodes, and then return a map from each of their IDs to all their children.

Seed the graph with known nodes. Often, you will provide the candidate edges that a user is trying to create here, or the initial set of edges you know about.

Get the nodes in topological order.

This method requires the graph be acyclic. For graphs which may contain cycles, see getNodesInRoughTopologicalOrder().

Get the nodes in topological order, or some roughly similar order if the graph contains cycles.

This method will return an ordering for cyclic graphs. The method will attempt to make it look like a topological ordering, but since cyclic graphs have no complete toplogical ordering, you might get anything.

If you know the graph is acyclic and want an actual topological order, use getNodesInTopologicalOrder().

Load the graph, building it out so operations can be performed on it. This constructs the graph level-by-level, calling loadEdges() to expand the graph at each stage until it is complete.

Detect if there are any cycles reachable from a given node.

If cycles are reachable, it returns a list of nodes which create a cycle. Note that this list may include nodes which aren't actually part of the cycle, but lie on the graph between the specified node and the cycle. For example, it might return something like this (when passed "A"):

A, B, C, D, E, C

This means you can walk from A to B to C to D to E and then back to C, which forms a cycle. A and B are included even though they are not part of the cycle. When presenting information about graph cycles to users, including these nodes is generally useful. This also shouldn't ever happen if you've vetted prior edges before writing them, because it means there is a preexisting cycle in the graph.

Internal cycle detection implementation. Recursively walks the graph, keeping track of where it's been, and returns the first cycle it finds.