What can I say, I like graphs. This problem is from the archives, but I think especially from a pedagogical standpoint these “copy the data structure” (or usually I like, “print the data structure”) are terrific educational exercises.

The approach I took for this problem is the commented helper function. I think I need to review DFS/BFS and make sure I’m using the right number of node-marking (typically I’ve seen it formulated as a node being “marked” done or workset, rather than added to a set — that is more efficient generally.

class Solution:
    def cloneGraph(self, node: 'Node') -> 'Node':
        if node is None:
            return None

        # We want to provide a function to get the
        # "corresponding" node, allocating it if needed.
        cor = {}
        def getCor(u):
            if u not in cor:
                cor[u] = Node(u.val)
            return cor[u]

        workset = set([])
        done = set([])
        workset.add(node)
        while len(workset) > 0:
            n = workset.pop()
            if n in done:
                continue
            m = getCor(n)
            for u in n.neighbors:
                v = getCor(u)
                m.neighbors.append(v)
                if u not in done:
                    if u not in workset:
                        workset.add(u)
            done.add(n)

        return getCor(node)

Notes

• All graph problems (rare) are collected here.