# My Simple Easy to understand Python Solution, beats 88%.

• ``````class Solution(object):
def generateTreesHelper(self, n, less_than, greater_than):
"""
:type n: int
:type less_than: int
:type greater_than: int
:rtype: List[TreeNode]
"""
rst = []
for i in xrange(1 if greater_than == - 1 else greater_than + 1,
n + 1 if less_than == -1 else less_than):  # Suppose first node value is i.
left_list = self.generateTreesHelper(n, i, greater_than)
right_list = self.generateTreesHelper(n, less_than, i)
if not right_list:
for l_tree in left_list:
new_node = TreeNode(i)
new_node.left = l_tree
rst.append(new_node)
if not left_list:
for r_tree in right_list:
new_node = TreeNode(i)
new_node.right = r_tree
rst.append(new_node)
if left_list and right_list:
for l_tree in left_list:
for r_tree in right_list:
new_node = TreeNode(i)
new_node.left = l_tree
new_node.right = r_tree
rst.append(new_node)
if not left_list and not right_list:
new_node = TreeNode(i)
rst.append(new_node)

return rst

def generateTrees(self, n):
"""
:type n: int
:rtype: List[TreeNode]
"""
return self.generateTreesHelper(n, -1, -1)

``````

The solution is basically using recursion to keep generating new nodes which left child is a BST, and a right child is a BST, but we need to check if left child or right child does not exist such solution. But if both left and right child has a solution, we can simply creating result lists which composed of a new node which left and right child is also a BST.

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