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Problem solution · Python

Clone Binary Tree with Random Pointer

Clone Binary Tree with Random Pointer: a Python solution using depth-first search. Learn the idea, check the complexity, and read the full code, with credit to Kamyu LeetCode Solutions.

Technique
Depth-first search
Source
Kamyu LeetCode Solutions
Length
149 lines
Start with the idea.

Try the problem first. If you get stuck, read the approach below, then write your own solution. The full code is at the bottom.

Approach

Depth-first search

For Clone Binary Tree with Random Pointer, the implementation follows one branch at a time, making it suitable for components, trees, backtracking, or dependency exploration.

  1. Define the state carried into one recursive or stack frame.
  2. Mark or choose the current state before exploring children.
  3. Combine child results or undo the choice when the branch finishes.

Code notes

  • 149 lines of Python from the credited upstream file clone-binary-tree-with-random-pointer.py.
  • The implementation visibly relies on hash lookup.
  • No explicit loop blocks detected, together with recursive traversal.

Complexity

Count unique states for graph traversal; for backtracking, count the branching factor and maximum depth.

Check the problem constraints before deciding whether this complexity will pass.

Source

Code and credit

This code comes from Kamyu LeetCode Solutions by kamyu104 and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeClone Binary Tree with Random Pointer · PythonPython
Use this to learn the idea, then write your own version.
# Time:  O(n)# Space: O(h) # Definition for Node.class Node(object):    def __init__(self, val=0, left=None, right=None, random=None):        self.val = val        self.left = left        self.right = right        self.random = random  # Definition for NodeCopy.class NodeCopy(object):    def __init__(self, val=0, left=None, right=None, random=None):        pass  class Solution(object):    def copyRandomBinaryTree(self, root):        """        :type root: Node        :rtype: NodeCopy        """        def iter_dfs(node, callback):            result = None            stk = [node]            while stk:                node = stk.pop()                if not node:                    continue                left_node, copy = callback(node)                if not result:                    result = copy                stk.append(node.right)                stk.append(left_node)            return result            def merge(node):            copy = NodeCopy(node.val)            node.left, copy.left = copy, node.left            return copy.left, copy                def clone(node):            copy = node.left            node.left.random = node.random.left if node.random else None            node.left.right = node.right.left if node.right else None            return copy.left, copy                def split(node):            copy = node.left            node.left, copy.left = copy.left, copy.left.left if copy.left else None            return node.left, copy            iter_dfs(root, merge)        iter_dfs(root, clone)        return iter_dfs(root, split)  # Time:  O(n)# Space: O(h)class Solution_Recu(object):    def copyRandomBinaryTree(self, root):        """        :type root: Node        :rtype: NodeCopy        """        def dfs(node, callback):            if not node:                return None            left_node, copy = callback(node)            dfs(left_node, callback)            dfs(node.right, callback)             return copy            def merge(node):            copy = NodeCopy(node.val)            node.left, copy.left = copy, node.left            return copy.left, copy                def clone(node):            copy = node.left            node.left.random = node.random.left if node.random else None            node.left.right = node.right.left if node.right else None            return copy.left, copy                def split(node):            copy = node.left            node.left, copy.left = copy.left, copy.left.left if copy.left else None            return node.left, copy            dfs(root, merge)        dfs(root, clone)        return dfs(root, split)  # Time:  O(n)# Space: O(n)import collections  class Solution2(object):    def copyRandomBinaryTree(self, root):        """        :type root: Node        :rtype: NodeCopy        """         lookup = collections.defaultdict(lambda: NodeCopy())        lookup[None] = None        stk = [root]        while stk:            node = stk.pop()            if not node:                continue            lookup[node].val = node.val            lookup[node].left = lookup[node.left]            lookup[node].right = lookup[node.right]            lookup[node].random = lookup[node.random]            stk.append(node.right)            stk.append(node.left)        return lookup[root]  # Time:  O(n)# Space: O(n)import collections  class Solution2_Recu(object):    def copyRandomBinaryTree(self, root):        """        :type root: Node        :rtype: NodeCopy        """         def dfs(node, lookup):            if not node:                return            lookup[node].val = node.val            lookup[node].left = lookup[node.left]            lookup[node].right = lookup[node.right]            lookup[node].random = lookup[node.random]            dfs(node.left, lookup)            dfs(node.right, lookup)            lookup = collections.defaultdict(lambda: NodeCopy())        lookup[None] = None        dfs(root, lookup)        return lookup[root]

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