Merge pull request #1062 from yolophg/main

[Helena] Week 12

Author: TonyKim9401

non-overlapping-intervals/yolophg.py

@@ -0,0 +1,25 @@
+# Time Complexity: O(N log N) 
+# (1) sorting the intervals takes O(N log N), and 
+# (2) iterating through them takes O(N).
+# (3) so the overall complexity is O(N log N).
+# Space Complexity: O(1) - only use a few extra variables (end and res), so the space usage is constant.
+
+class Solution:
+    def eraseOverlapIntervals(self, intervals: List[List[int]]) -> int:
+        # sort intervals by their ending time
+        intervals.sort(key=lambda x: x[1])  
+        
+        # track the last non-overlapping interval's end
+        end = float('-inf') 
+        # count the number of intervals we need to remove
+        res = 0  
+
+        for interval in intervals:
+            # if it overlaps with the last interval
+            if interval[0] < end: 
+                # need to remove this one 
+                res += 1  
+            else:
+                # otherwise, update the end to the current interval's end
+                end = interval[1] 
+        return res

number-of-connected-components-in-an-undirected-graph/yolophg.py

@@ -0,0 +1,36 @@
+# Time Complexity: O(N + E) - go through all nodes & edges.
+# Space Complexity: O(N) - store parent info for each node.
+
+class Solution:
+    def count_components(self, n: int, edges: List[List[int]]) -> int:
+
+        # set up the Union-Find structure
+        parent = [i for i in range(n)]  # initially, each node is its own parent
+        rank = [1] * n  # used for optimization in Union operation
+
+        # find function (with path compression)
+        def find(node):
+            if parent[node] != node:
+                parent[node] = find(parent[node])  # path compression
+            return parent[node]
+
+        # union function (using rank to keep tree flat)
+        def union(node1, node2):
+            root1, root2 = find(node1), find(node2)
+            if root1 != root2:
+                if rank[root1] > rank[root2]:
+                    parent[root2] = root1
+                elif rank[root1] < rank[root2]:
+                    parent[root1] = root2
+                else:
+                    parent[root2] = root1
+                    rank[root1] += 1
+                return True  # union was successful (i.e., we merged two components)
+            return False  # already in the same component
+
+        # connect nodes using Union-Find
+        for a, b in edges:
+            union(a, b)
+
+        # count unique roots (number of connected components)
+        return len(set(find(i) for i in range(n)))

remove-nth-node-from-end-of-list/yolophg.py

@@ -0,0 +1,29 @@
+# Time Complexity: O(N) - go through the list twice (once to count, once to remove).
+# Space Complexity: O(1) - only use a few extra variables.
+
+class Solution:
+    def removeNthFromEnd(self, head: Optional[ListNode], n: int) -> Optional[ListNode]:
+        # count the total number of nodes in the list
+        N = 0
+        curr = head
+        while curr:
+            N += 1
+            curr = curr.next
+        
+        # find the position of the node to remove (from the start)
+        node_to_remove = N - n
+
+        # if need to remove the first node, just return the second node as the new head
+        if node_to_remove == 0:
+            return head.next
+        
+        # traverse again to find the node right before the one we need to remove
+        curr = head
+        for i in range(N - 1):
+            if (i + 1) == node_to_remove:
+                # remove the nth node by skipping it
+                curr.next = curr.next.next
+                break
+            curr = curr.next
+        
+        return head

same-tree/yolophg.py

@@ -0,0 +1,19 @@
+# Time Complexity: O(N) - visit each node once.
+# Space Complexity: O(N) in the worst case (skewed tree), O(log N) in the best case (balanced tree).
+
+class Solution:
+    def isSameTree(self, p: Optional[TreeNode], q: Optional[TreeNode]) -> bool:        
+        # if both trees are empty, they are obviously the same
+        if p is None and q is None:
+            return True  
+        
+        # if one tree is empty but the other is not, they can't be the same
+        if p is None or q is None:
+            return False
+        
+        # if values of the current nodes are different, trees are not the same
+        if p.val != q.val:
+            return False
+        
+        # recursively check both left and right subtrees
+        return self.isSameTree(p.left, q.left) and self.isSameTree(p.right, q.right)

serialize-and-deserialize-binary-tree/yolophg.py

@@ -0,0 +1,58 @@
+# Time Complexity:
+# (1) serialize(): O(N) because traverse all nodes once.
+# (2) deserialize(): O(N) because process each node once.
+    
+# Space Complexity:
+# (1) serialize(): O(N) to store the serialized string.
+# (2) deserialize(): O(N) for the queue and reconstructed tree.
+
+class Codec:
+    def serialize(self, root):
+        # store the tree as a list of values (BFS style)
+        ans = []
+        if not root: 
+            return "" 
+
+        queue = [root]
+        while queue:
+            cur = queue.pop()
+            if not cur:
+                ans.append("n")  # use 'n' to represent null nodes
+                continue
+            ans.append(str(cur.val))  # add node value as string
+            queue.append(cur.right)  # right first (for consistency in deserialization)
+            queue.append(cur.left)  # then left
+        
+        return ",".join(ans)  # convert list to comma-separated string
+
+    def deserialize(self, data):
+        if not data: 
+            return None
+        
+        data = deque(data.split(","))  # convert string back to list
+        root = TreeNode(int(data.popleft()))  # first value is the root
+        queue = [(root, 0)]  # track parent nodes and child positions
+        
+        while data:
+            if not queue:
+                return None  # should never happen unless input is corrupted
+            
+            cur = data.popleft()
+            if cur == "n":
+                val = None  # null node, no need to create a TreeNode
+            else:
+                val = TreeNode(int(cur))  # create a new TreeNode
+            
+            parent, cnt = queue.pop()  # get the parent and which child we’re setting
+            if cnt == 0:
+                parent.left = val  # assign left child
+            else:
+                parent.right = val  # assign right child
+            
+            cnt += 1  # move to the next child
+            if cnt < 2:
+                queue.append((parent, cnt))  # if parent still needs a right child, keep it in the queue
+            if val:
+                queue.append((val, 0))  # add new node to process its children later
+        
+        return root