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# Time: O(1)

# Space: O(h), h is height of binary tree

#

# Implement an iterator over a binary search tree (BST).

# Your iterator will be initialized with the root node of a BST.

#

# Calling next() will return the next smallest number in the BST.

#

# Note: next() and hasNext() should run in average O(1) time

# and uses O(h) memory, where h is the height of the tree.

#

# Definition for a binary tree node

class TreeNode:

def __init__(self, x):

self.val = x

self.left = None

self.right = None

class BSTIterator:

# @param root, a binary search tree's root node

def __init__(self, root):

self.stack = []

self.cur = root

# @return a boolean, whether we have a next smallest number

def hasNext(self):

return self.stack or self.cur

# @return an integer, the next smallest number

def next(self):

while self.cur:

self.stack.append(self.cur)

self.cur = self.cur.left

self.cur = self.stack.pop()

node = self.cur

self.cur = self.cur.right

return node.val

if __name__ == "__main__":

root = TreeNode(2)

root.left = TreeNode(1)

# Your BSTIterator will be called like this:

i, v = BSTIterator(root), []

while i.hasNext(): v.append(i.next())

print v