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Problem solution · Python

Maximum Genetic Difference Query

Maximum Genetic Difference Query: a Python solution using depth-first search. Learn the idea, check the complexity, and read the full code, with credit to walkccc LeetCode Solutions.

Technique
Depth-first search
Source
walkccc LeetCode Solutions
Length
71 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 Maximum Genetic Difference Query, 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

  • 71 lines of Python from the credited upstream file 1938.py.
  • The implementation visibly relies on sequence storage, 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 walkccc LeetCode Solutions by P.-Y. Chen (walkccc) and is used under the MIT licence.

Open problem ↗Original source ↗
Full codeMaximum Genetic Difference Query · PythonPython
Use this to learn the idea, then write your own version.
class TrieNode:  def __init__(self):    self.children: list[TrieNode | None] = [None] * 2    self.count = 0  class Trie:  def __init__(self):    self.root = TrieNode()    self.HEIGHT = 17   def update(self, num: int, val: int) -> None:    node = self.root    for i in range(self.HEIGHT, -1, -1):      bit = (num >> i) & 1      if not node.children[bit]:        node.children[bit] = TrieNode()      node = node.children[bit]      node.count += val   def query(self, num: int) -> int:    ans = 0    node = self.root    for i in range(self.HEIGHT, -1, -1):      bit = (num >> i) & 1      targetBit = bit ^ 1      if node.children[targetBit] and node.children[targetBit].count > 0:        ans += 1 << i        node = node.children[targetBit]      else:        node = node.children[targetBit ^ 1]    return ans  class Solution:  def maxGeneticDifference(      self,      parents: list[int],      queries: list[list[int]],  ) -> list[int]:    n = len(parents)    ans = [0] * len(queries)    rootVal = -1    tree = [[] for _ in range(n)]    nodeToQueries = collections.defaultdict(list)  # {node: (index, val)}    trie = Trie()     for i, parent in enumerate(parents):      if parent == -1:        rootVal = i      else:        tree[parent].append(i)     for i, (node, val) in enumerate(queries):      nodeToQueries[node].append((i, val))     def dfs(node: int) -> None:      trie.update(node, 1)       # Answer queries for node      for i, val in nodeToQueries[node]:        ans[i] = trie.query(val)       for child in tree[node]:        dfs(child)       trie.update(node, -1)     dfs(rootVal)    return ans

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