Algorithm Notes
Summary: Clone Graph — notes not yet curated.
Time: Estimate via loops/recurrences; common classes: O(1), O(log n), O(n), O(n log n), O(n^2)
Space: Count auxiliary structures and recursion depth.
Tip: See the Big-O Guide for how to derive bounds and compare trade-offs.
Big-O Guide
Source
"""
Clone Graph
TODO: Add problem description
"""
from collections import deque
from src.interview_workbook.leetcode._registry import register_problem
from src.interview_workbook.leetcode._types import Category, Difficulty
class Solution:
def solve(self, node):
"""Clone an undirected graph using BFS."""
if not node:
return None
clones = {}
clones[node] = type(node)(node.val)
queue = deque([node])
while queue:
curr = queue.popleft()
for nei in curr.neighbors:
if nei not in clones:
clones[nei] = type(nei)(nei.val)
queue.append(nei)
clones[curr].neighbors.append(clones[nei])
return clones[node]
def demo():
"""Run a demo for the Clone Graph problem."""
class Node:
def __init__(self, val):
self.val = val
self.neighbors = []
def __repr__(self):
return f"Node({self.val})"
# Build a simple graph: 1 -- 2, 1 -- 3
n1 = Node(1)
n2 = Node(2)
n3 = Node(3)
n1.neighbors = [n2, n3]
n2.neighbors = [n1]
n3.neighbors = [n1]
solver = Solution()
clone = solver.solve(n1)
return f"Cloned node val: {clone.val}, neighbors: {[nei.val for nei in clone.neighbors]}"
register_problem(
id=133,
slug="clone_graph",
title="Clone Graph",
category=Category.GRAPHS,
difficulty=Difficulty.MEDIUM,
tags=["hashmap", "dfs", "bfs", "graph"],
url="https://leetcode.com/problems/clone-graph/",
notes="",
)