DFS-1

01Matrix.py

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+# Time Complexity : O(m*n)
+# Space Complexity : O(m*n)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+# Approach : First, add all 0s to a queue and mark all 1s as -1 to show they haven't been processed yet.
+# Then, use BFS from the 0s to expand layer by layer and assign the correct distance to each -1.
+# This way, every 1 gets the shortest distance to the nearest 0 as BFS explores in waves.
+
+class Solution:
+    def updateMatrix(self, mat: List[List[int]]) -> List[List[int]]:
+        dirs = [[-1, 0], [1, 0], [0, 1], [0, -1]]
+        rows, cols = len(mat), len(mat[0])
+
+        q = deque()
+
+        for i in range(rows):
+            for j in range(cols):
+                if mat[i][j] == 0:
+                    q.append([i,j])
+                else:
+                    mat[i][j] = -1
+
+        dist = 1
+
+        while q:
+            size = len(q)
+            for _ in range(size):
+                curr = q.popleft()
+                for dx, dy in dirs:
+                    r = curr[0] + dx
+                    c = curr[1] + dy
+
+                    if 0 <= r < rows and 0 <= c < cols and mat[r][c] == -1:
+                        q.append([r, c])
+                        mat[r][c] = dist
+            dist += 1
+
+        return mat

FloodFill.py

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+# Time Complexity : O(m*n)
+# Space Complexity : O(m*n)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+# Approach : Use a queue to visit neighbors with the same old color.
+# Each valid neighbor is colored and added to the queue for further expansion.
+
+class Solution:
+    def floodFill(self, image: List[List[int]], sr: int, sc: int, color: int) -> List[List[int]]:
+        oldColor = image[sr][sc]
+        if oldColor == color:
+            return image
+
+        dirs = [[-1, 0], [1, 0], [0, 1], [0, -1]]
+        rows, cols = len(image), len(image[0])
+
+        q = deque()
+        q.append([sr,sc])
+        image[sr][sc] = color
+
+        while q:
+            curr = q.popleft()
+            for dx, dy in dirs:
+                r = curr[0] + dx
+                c = curr[1] + dy
+
+                if r >= 0 and c >= 0 and r < rows and c < cols and image[r][c] == oldColor:
+                    image[r][c] = color
+                    q.append([r, c])
+
+        return image