LeetCode-in-All

138. Copy List with Random Pointer

Medium

A linked list of length n is given such that each node contains an additional random pointer, which could point to any node in the list, or null.

Construct a deep copy of the list. The deep copy should consist of exactly n brand new nodes, where each new node has its value set to the value of its corresponding original node. Both the next and random pointer of the new nodes should point to new nodes in the copied list such that the pointers in the original list and copied list represent the same list state. None of the pointers in the new list should point to nodes in the original list.

For example, if there are two nodes X and Y in the original list, where X.random --> Y, then for the corresponding two nodes x and y in the copied list, x.random --> y.

Return the head of the copied linked list.

The linked list is represented in the input/output as a list of n nodes. Each node is represented as a pair of [val, random_index] where:

• val: an integer representing Node.val
• random_index: the index of the node (range from 0 to n-1) that the random pointer points to, or null if it does not point to any node.

Your code will only be given the head of the original linked list.

Example 1:

Input: head = [[7,null],[13,0],[11,4],[10,2],[1,0]]

Output: [[7,null],[13,0],[11,4],[10,2],[1,0]]

Example 2:

Input: head = [[1,1],[2,1]]

Output: [[1,1],[2,1]]

Example 3:

Input: head = [[3,null],[3,0],[3,null]]

Output: [[3,null],[3,0],[3,null]]

Example 4:

Input: head = []

Output: []

Explanation: The given linked list is empty (null pointer), so return null.

Constraints:

• 0 <= n <= 1000
• -10000 <= Node.val <= 10000
• Node.random is null or is pointing to some node in the linked list.

To solve this problem with the Solution class, we can use a hashmap to keep track of the mapping between original nodes and their corresponding copied nodes. Here are the steps:

1. Define the Solution class with a method copyRandomList that takes the head of the original linked list as input and returns the head of the copied linked list.
2. Within the copyRandomList method, if the input head is None, return None as the copied list is empty.
3. Initialize an empty hashmap to store the mapping between original nodes and copied nodes.
4. Iterate through the original linked list and create a copied node for each original node. Set the value of the copied node to be the same as the original node and set both next and random pointers of the copied node to None.
5. Store the mapping between original nodes and copied nodes in the hashmap.
6. Iterate through the original linked list again and update the next and random pointers of copied nodes according to the mapping stored in the hashmap.
7. Finally, return the head of the copied linked list.

Here’s how the Solution class would look like in Python:

class Solution:
    def copyRandomList(self, head: 'Node') -> 'Node':
        if not head:
            return None
        
        mapping = {}
        
        # Create copies of nodes without pointers
        current = head
        while current:
            mapping[current] = Node(current.val)
            current = current.next
        
        # Assign pointers for each copied node
        current = head
        while current:
            mapping[current].next = mapping.get(current.next)
            mapping[current].random = mapping.get(current.random)
            current = current.next
        
        return mapping[head]

Make sure to define the Node class before using it in the copyRandomList method. This solution constructs a deep copy of the original linked list while maintaining the relationships between nodes as specified.

Solution

"""
# Definition for a Node.
class Node:
    def __init__(self, x: int, next: 'Node' = None, random: 'Node' = None):
        self.val = int(x)
        self.next = next
        self.random = random
"""

class Solution:
    def copyRandomList(self, head: 'Optional[Node]') -> 'Optional[Node]':
        if head is None:
            return None
        
        # First pass: create the cloned nodes and insert them right after the original nodes
        curr = head
        while curr:
            cloned_node = Node(curr.val)
            cloned_node.next = curr.next
            curr.next = cloned_node
            curr = cloned_node.next
        
        # Second pass: update the random pointers of the cloned nodes
        curr = head
        while curr:
            if curr.random:
                curr.next.random = curr.random.next
            curr = curr.next.next
        
        # Third pass: separate the cloned list from the original list
        curr = head
        new_head = head.next
        while curr:
            cloned_node = curr.next
            curr.next = cloned_node.next
            if cloned_node.next:
                cloned_node.next = cloned_node.next.next
            curr = curr.next
        
        return new_head

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