Leetcode #1559: Detect Cycles in 2D Grid
In this guide, we solve Leetcode #1559 Detect Cycles in 2D Grid 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 a 2D array of characters grid of size m x n, you need to find if there exists any cycle consisting of the same value in grid. A cycle is a path of length 4 or more in the grid that starts and ends at the same cell.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Depth-First Search, Breadth-First Search, Union Find, Array, Matrix
Intuition
We need to explore a structure deeply before backing up, which suits DFS.
DFS keeps local context on the call stack and is easy to implement recursively.
Approach
Define a recursive DFS that carries the necessary state.
Combine child results as the recursion unwinds.
Steps:
- Define a recursive DFS with state.
- Visit children and combine results.
- Return the final aggregation.
Example
Input: grid = [["a","a","a","a"],["a","b","b","a"],["a","b","b","a"],["a","a","a","a"]]
Output: true
Explanation: There are two valid cycles shown in different colors in the image below:
Python Solution
class Solution:
def containsCycle(self, grid: List[List[str]]) -> bool:
m, n = len(grid), len(grid[0])
vis = [[False] * n for _ in range(m)]
dirs = (-1, 0, 1, 0, -1)
for i, row in enumerate(grid):
for j, x in enumerate(row):
if vis[i][j]:
continue
vis[i][j] = True
q = [(i, j, -1, -1)]
while q:
x, y, px, py = q.pop()
for dx, dy in pairwise(dirs):
nx, ny = x + dx, y + dy
if 0 <= nx < m and 0 <= ny < n:
if grid[nx][ny] != grid[i][j] or (nx == px and ny == py):
continue
if vis[nx][ny]:
return True
vis[nx][ny] = True
q.append((nx, ny, x, y))
return False
Complexity
The time complexity is , and the space complexity is . The space complexity is .
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.