add py3 soln
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0099_recover-binary-search-tree/README.md
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0099_recover-binary-search-tree/README.md
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You are given the `root` of a binary search tree (BST), where the values of **exactly** two nodes of the tree were swapped by mistake. _Recover the tree without changing its structure_.
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**Example 1:**
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![](https://assets.leetcode.com/uploads/2020/10/28/recover1.jpg)
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Input: root = [1,3,null,null,2]
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Output: [3,1,null,null,2]
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Explanation: 3 cannot be a left child of 1 because 3 > 1. Swapping 1 and 3 makes the BST valid.
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**Example 2:**
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![](https://assets.leetcode.com/uploads/2020/10/28/recover2.jpg)
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Input: root = [3,1,4,null,null,2]
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Output: [2,1,4,null,null,3]
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Explanation: 2 cannot be in the right subtree of 3 because 2 < 3. Swapping 2 and 3 makes the BST valid.
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**Constraints:**
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* The number of nodes in the tree is in the range `[2, 1000]`.
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* `-231 <= Node.val <= 231 - 1`
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**Follow up:** A solution using `O(n)` space is pretty straight-forward. Could you devise a constant `O(1)` space solution?
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0099_recover-binary-search-tree/python3/linear_space.py
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0099_recover-binary-search-tree/python3/linear_space.py
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# Time: O(N)
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# Space: O(N)
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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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items = swaps = None
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def recoverTree(self, root: Optional[TreeNode]) -> None:
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"""
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Do not return anything, modify root in-place instead.
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"""
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# Get the almost-sorted tree as an array
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self.items = self.inorder(root)
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# Find the elements that need to be swapped
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self.swaps = self.identify_swaps(self.items)
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# Walk the tree and fix the matching values
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self.walk_fix(root, 0)
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def inorder(self, node):
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"""
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Return list of elements in almost sorted order (BST property
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implies that in-order traversal produces sorted list)
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"""
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return self.inorder(node.left) + [node.val] + self.inorder(node.right) if node is not None else []
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def identify_swaps(self, items):
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# We need to swap two values so keep two variables
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x = y = None
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for i in range(len(items) - 1):
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# Problem states that we at most need to swap one item
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# at index i to another item at index j to get the sorted
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# list. If this is the case, the larger value to swap will
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# be seen first and later on, the smaller value will be seen
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# e.g. 1 4 3 2
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# and 2 1
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if items[i] < items[i + 1]:
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pass
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else:
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# Condition fails when we see (4, 3) in first e.g and (2, 1)
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# in second example. We immediately assign i+1th value to cover
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# a case like the second example where swaps are right next to each
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# in last iteration
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y = items[i + 1]
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# In (2, 1)'s case, immediately goes to this block and iteration stops
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# when iteration condition becomes False.
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#
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# In first example's case, we get to (4, 3) in which case:
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#
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# y = items[i + 1] = 3
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# x = items[i] = 4
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#
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# We keep looping until we hit (3, 2) and this time, it's the lower value
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# so y is reassigned to 2. x is already set previously to 4 so now we can
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# break and return the values to swap.
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if x is None:
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x = items[i]
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else:
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break
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return {
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x: y,
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y: x
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}
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def walk_fix(self, node, i):
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"""
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Does in-order traversal of BST and if node.val matches
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a key in self.swaps, replaces it with the swapped value
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"""
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if node is None: return
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self.walk_fix(node.left, i)
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if node.val in self.swaps:
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node.val = self.swaps[node.val]
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i += 1
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self.walk_fix(node.right, i)
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0099_recover-binary-search-tree/python3/solution.py
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0099_recover-binary-search-tree/python3/solution.py
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