Leetcode #212: Word Search II
In this guide, we solve Leetcode #212 Word Search II in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
Given an m x n board of characters and a list of strings words, return all words on the board. Each word must be constructed from letters of sequentially adjacent cells, where adjacent cells are horizontally or vertically neighboring.
Quick Facts
- Difficulty: Hard
- Premium: No
- Tags: Trie, Array, String, Backtracking, Matrix
Intuition
We must explore combinations of choices, but many branches can be pruned early.
Backtracking enumerates valid candidates while keeping the search space under control.
Approach
Use DFS to build candidates step by step, and backtrack when constraints are violated.
Pruning keeps the exploration practical for typical constraints.
Steps:
- Define the decision tree.
- DFS through choices and backtrack.
- Prune invalid paths early.
Example
Input: board = [["o","a","a","n"],["e","t","a","e"],["i","h","k","r"],["i","f","l","v"]], words = ["oath","pea","eat","rain"]
Output: ["eat","oath"]
Python Solution
class Trie:
def __init__(self):
self.children: List[Trie | None] = [None] * 26
self.ref: int = -1
def insert(self, w: str, ref: int):
node = self
for c in w:
idx = ord(c) - ord('a')
if node.children[idx] is None:
node.children[idx] = Trie()
node = node.children[idx]
node.ref = ref
class Solution:
def findWords(self, board: List[List[str]], words: List[str]) -> List[str]:
def dfs(node: Trie, i: int, j: int):
idx = ord(board[i][j]) - ord('a')
if node.children[idx] is None:
return
node = node.children[idx]
if node.ref >= 0:
ans.append(words[node.ref])
node.ref = -1
c = board[i][j]
board[i][j] = '#'
for a, b in pairwise((-1, 0, 1, 0, -1)):
x, y = i + a, j + b
if 0 <= x < m and 0 <= y < n and board[x][y] != '#':
dfs(node, x, y)
board[i][j] = c
tree = Trie()
for i, w in enumerate(words):
tree.insert(w, i)
m, n = len(board), len(board[0])
ans = []
for i in range(m):
for j in range(n):
dfs(tree, i, j)
return ans
Complexity
The time complexity is Exponential (worst case). The space complexity is O(depth).
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.