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docs: rename category folders to remove parentheses and update heap meta title
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---
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title: '102. Binary Tree Level Order Traversal'
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description: Given the root of a binary tree, return the level order traversal of its nodes' values. (i.e., from left to right, level by level)
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sidebar:
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label: 'Binary Tree Level Order Traversal'
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badge: 'Medium'
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---
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<Badge variant="accent">Tree</Badge>
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### Example 1:
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- Input: `root = [3,9,20,null,null,15,7]`
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- Output: `[[3],[9,20],[15,7]]`
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### Example 2:
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- Input: `root = [1]`
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- Output: `[[1]]`
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### Example 3:
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- Input: `root = []`
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- Output: `[]`
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### Constraints:
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- The number of nodes in the tree is in the range [0, 2000].
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- `-1000 <= Node.val <= 1000`
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## Approach
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```mermaid
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flowchart TD
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S(["levelOrder(root)"]) --> I["res = [], q = deque(), q.append(root)"]
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I --> W{"q non-empty?"}
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W -- no --> E(["return res"])
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W -- yes --> L["qLen = len(q), level = [] — qLen freezes the current level's size"]
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L --> F{"more i in range(qLen)?"}
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F -- no --> V{"level non-empty?"}
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V -- yes --> A["res.append(level)"]
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A --> W
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V -- no --> W
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F -- yes --> P["node = q.popleft()"]
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P --> N{"node is not None?"}
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N -- no --> F
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N -- yes --> C["level.append(node.val), q.append(node.left), q.append(node.right) — None children are filtered on the next level"]
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C --> F
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```
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## Solution
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```py
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# Definition for a binary tree node.
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# class TreeNode:
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# def __init__(self, val=0, left=None, right=None):
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# self.val = val
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# self.left = left
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# self.right = right
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from collections import deque
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class Solution:
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# T: O(n) S: O(n)
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def levelOrder(self, root: Optional[TreeNode]) -> List[List[int]]:
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res = []
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q = deque()
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q.append(root)
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while q:
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qLen = len(q)
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level = []
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for i in range(qLen):
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node = q.popleft()
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if node:
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level.append(node.val)
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q.append(node.left)
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q.append(node.right)
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if level:
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res.append(level)
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return res
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```
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## Explanation
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<YouTube id="6ZnyEApgFYg" title="Binary Tree Level Order Traversal - BFS - Leetcode 102" />
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---
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title: '1448. Count Good Nodes in Binary Tree'
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description: Given a binary tree root, a node X in the tree is named good if in the path from root to X there are no nodes with a value greater than X
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sidebar:
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label: 'Count Good Nodes in Binary Tree'
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badge: 'Medium'
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---
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<Badge variant="accent">Tree</Badge>
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### Example 1:
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- Input: `root = [3,1,4,3,null,1,5]`
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- Output: `4`
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- Explanation: Nodes in blue are good. Root Node `(3`) is always a good node. Node `4` -> (3,4) is the maximum value in the path starting from the `root`. Node `5` -> (3,4,5) is the maximum value in the path Node `3` -> (3,1,3) is the maximum value in the path.
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### Example 2:
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- Input: `root = [3,3,null,4,2]`
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- Output: `3`
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- Explanation: Node `2` -> `(3`, `3`, `2`) is not good, because `"3`" is higher than it.
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### Example 3:
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- Input: `root = [1]`
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- Output: `1`
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- Explanation: Root is considered as good.
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### Constraints:
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- The number of nodes in the binary tree is in the range [1, 10^5].
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- Each node's value is between [-10^4, 10^4].
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## Approach
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```mermaid
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flowchart TD
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S(["goodNodes(root)"]) --> C["dfs(root, root.val) — the root is always good"]
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C --> E(["return that count"])
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subgraph dfs["dfs(node, max_val)"]
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D1{"node is None?"} -- yes --> D2(["return 0"])
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D1 -- no --> D3["is_good = 1 if node.val >= max_val else 0 — max_val is the largest value on the path so far"]
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D3 --> D4["new_max = max(max_val, node.val)"]
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D4 --> D5["l = dfs(node.left, new_max), r = dfs(node.right, new_max)"]
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D5 --> D6(["return is_good + l + r"])
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end
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C --> dfs
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```
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## Solution
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```py
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# Definition for a binary tree node.
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# class TreeNode:
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# def __init__(self, val=0, left=None, right=None):
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# self.val = val
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# self.left = left
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# self.right = right
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class Solution:
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def goodNodes(self, root: TreeNode) -> int:
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def dfs(node, max_val):
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if not node:
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return 0
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is_good = 1 if node.val >= max_val else 0
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new_max = max(max_val, node.val)
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return is_good + dfs(node.left, new_max) + dfs(node.right, new_max)
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return dfs(root, root.val)
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```
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## Explanation
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<YouTube id="7cp5imvDzl4" title="Microsoft's Most Asked Question 2021 - Count Good Nodes in a Binary Tree - Leetcode 1448 - Python" />
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---
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title: '199. Binary Tree Right Side View'
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description: Given the root of a binary tree, imagine yourself standing on the right side of it, return the values of the nodes you can see ordered from top to bottom
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sidebar:
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label: 'Binary Tree Right Side View'
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badge: 'Medium'
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---
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<Badge variant="accent">Tree</Badge>
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### Example 1:
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- Input: `root = [1,2,3,null,5,null,4]`
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- Output: `[1,3,4]`
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### Example 2:
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- Input: `root = [1,2,3,4,null,null,null,5]`
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- Output: `[1,3,4,5]`
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### Example 3:
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- Input: `root = [1,null,3]`
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- Output: `[1,3]`
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### Example 4:
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- Input: `root = []`
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- Output: `[]`
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### Constraints:
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- The number of nodes in the tree is in the range [0, 100].
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- `-100 <= Node.val <= 100`
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## Approach
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```mermaid
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flowchart TD
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S(["rightSideView(root)"]) --> I["res = [], q = deque([root])"]
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I --> W{"q non-empty?"}
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W -- no --> E(["return res"])
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W -- yes --> L["rightSide = None, qLen = len(q) — qLen freezes the current level's size"]
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L --> F{"more i in range(qLen)?"}
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F -- no --> V{"rightSide is not None?"}
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V -- yes --> A["res.append(rightSide.val) — the last real node popped on this level is the rightmost"]
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A --> W
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V -- no --> W
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F -- yes --> P["node = q.popleft()"]
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P --> N{"node is not None?"}
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N -- no --> F
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N -- yes --> C["rightSide = node, q.append(node.left), q.append(node.right)"]
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C --> F
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```
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## Solution
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```py
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# Definition for a binary tree node.
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# class TreeNode:
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# def __init__(self, val=0, left=None, right=None):
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# self.val = val
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# self.left = left
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# self.right = right
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from collections import deque
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class Solution:
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def rightSideView(self, root: Optional[TreeNode]) -> List[int]:
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res = []
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q = deque([root])
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while q:
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rightSide = None
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qLen = len(q)
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for i in range(qLen):
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node = q.popleft()
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if node:
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rightSide = node
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q.append(node.left)
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q.append(node.right)
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if rightSide:
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res.append(rightSide.val)
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return res
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```
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## Explanation
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<YouTube id="d4zLyf32e3I" title="Binary Tree Right Side View - Breadth First Search - Leetcode 199" />
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@@ -0,0 +1,3 @@
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import { defineMeta } from "blume";
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export default defineMeta({ title: "Tree BFS", order: 12 });
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