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construct-binary-tree-from-preorder-and-inorder-traversal
implement-trie-prefix-tree
kth-smallest-element-in-a-bst
5 files changed +122
-0
lines changed Original file line number Diff line number Diff line change
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+ class Solution :
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+ def combinationSum (self , candidates : List [int ], target : int ) -> List [List [int ]]:
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+ dp = [[] for i in range (target + 1 )]
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+ dp [0 ] = [[]]
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+
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+ for num in candidates :
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+ for i in range (num , target + 1 ):
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+ for comb in dp [i - num ]:
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+ dp [i ].append (comb + [num ])
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+
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+ return dp [target ]
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+
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+ ## TC: O(outer loop * 1st inner(target size) * 2nd inner(combination #))
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+ ## SC: O(target size * combination #)
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+ class Solution :
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+ def buildTree (self , preorder : List [int ], inorder : List [int ]) -> Optional [TreeNode ]:
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+ if len (inorder ) == 0 :
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+ return None
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+
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+ if len (preorder ) == 1 :
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+ return TreeNode (preorder [0 ])
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+
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+ idx = inorder .index (preorder .pop (0 ))
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+ node = TreeNode (inorder [idx ])
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+
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+ node .left = self .buildTree (preorder , inorder [:idx ])
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+ node .right = self .buildTree (preorder , inorder [idx + 1 :])
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+
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+ return node
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+
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+
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+ ## TC: O(n^2), SC: O(n)
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+ class TrieNode :
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+ def __init__ (self ):
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+ self .children = {}
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+ self .isEnd = False
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+
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+
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+ class Trie :
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+ def __init__ (self ):
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+ self .root = TrieNode ()
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+
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+ def insert (self , word : str ) -> None :
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+ cur = self .root
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+
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+ for c in word :
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+ if c not in cur .children :
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+ cur .children [c ] = TrieNode ()
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+ cur = cur .children [c ]
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+ cur .isEnd = True
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+
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+ ## TC: O(len(word)), SC: O(len(word))
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+
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+ def search (self , word : str ) -> bool :
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+ cur = self .root
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+
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+ for c in word :
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+ if c not in cur .children :
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+ return False
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+ cur = cur .children [c ]
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+ return cur .isEnd
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+
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+ ## TC: O(len(word)), SC: O(1)
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+
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+ def startsWith (self , prefix : str ) -> bool :
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+ cur = self .root
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+
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+ for c in prefix :
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+ if c not in cur .children :
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+ return False
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+ cur = cur .children [c ]
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+ return True
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+
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+ ## TC: O(len(prefix)). SC: O(1)
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+ class Solution :
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+ def kthSmallest (self , root : Optional [TreeNode ], k : int ) -> int :
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+ ans = []
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+
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+ def helper (node ):
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+ if not node : return
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+ helper (node .left )
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+
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+ if len (ans ) == k :
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+ return
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+
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+ ans .append (node .val )
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+ helper (node .right )
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+
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+ helper (root )
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+ return ans [- 1 ]
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+
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+ ## TC: O(n), SC: O(h+n) where h == heights(tree) and n == element(tree)
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+ class Solution :
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+ def exist (self , board : List [List [str ]], word : str ) -> bool :
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+ rows , cols = len (board ), len (board [0 ])
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+
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+ def backtrack (r , c , index ):
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+ if index == len (word ):
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+ return True
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+ if r < 0 or r >= rows or c < 0 or c >= cols or board [r ][c ] != word [index ]:
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+ return False
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+
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+ temp = board [r ][c ]
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+ board [r ][c ] = "!"
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+
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+ found = (backtrack (r + 1 , c , index + 1 ) or
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+ backtrack (r - 1 , c , index + 1 ) or
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+ backtrack (r , c + 1 , index + 1 ) or
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+ backtrack (r , c - 1 , index + 1 ))
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+
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+ board [r ][c ] = temp
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+ return found
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+
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+ for i in range (rows ):
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+ for j in range (cols ):
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+ if backtrack (i , j , 0 ):
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+ return True
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+
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+ return False
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+
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+ ## TC: O(D of row * D of Cols * 4^L), but amortised could be O(DoR * DoC)
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+ ## SC: O(L)
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