[leetcode] 449. Serialize and Deserialize BST @ python

原题

Serialization is the process of converting a data structure or object into a sequence of bits so that it can be stored in a file or memory buffer, or transmitted across a network connection link to be reconstructed later in the same or another computer environment.

Design an algorithm to serialize and deserialize a binary search tree. There is no restriction on how your serialization/deserialization algorithm should work. You just need to ensure that a binary search tree can be serialized to a string and this string can be deserialized to the original tree structure.

The encoded string should be as compact as possible.

Note: Do not use class member/global/static variables to store states. Your serialize and deserialize algorithms should be stateless.

解法

在serialize函数中, 使用前序遍历, 将二叉树的值转化为列表, 然后将列表转化为字符串. 前序遍历的好处是数组的第一个数是根节点, 比根节点小的数是根节点的左子树, 比根节点大的数是右子树.

在deserialize函数中, 将字符串转化为队列, 这里使用双向队列来节省时间, 然后根据队列构造BST. 第一个数是根节点, 比根节点小的数是根节点的左子树, 比根节点大的数是右子树. 如此递归.

Time: O(n) , n为节点的个数
Space: O(n)

代码

# Definition for a binary tree node.
# class TreeNode(object):
#     def __init__(self, x):
#         self.val = x
#         self.left = None
#         self.right = None

class Codec:

    def serialize(self, root):
        """Encodes a tree to a single string.
        
        :type root: TreeNode
        :rtype: str
        """
        l = []
        def preOrder(root):
            if root:
                l.append(root.val)
                preOrder(root.left)
                preOrder(root.right)
        preOrder(root)
        return ' '.join(map(str, l))    
        

    def deserialize(self, data):
        """Decodes your encoded data to tree.
        
        :type data: str
        :rtype: TreeNode
        """
        vals = collections.deque([int(val) for val in data.split()])
        
        def buildTree(vals, minVal, maxVal):
            while vals and minVal < vals[0] < maxVal:
                val = vals.popleft()
                root = TreeNode(val)
                root.left = buildTree(vals, minVal, val)
                root.right = buildTree(vals, val, maxVal)
                return root
        return buildTree(vals, float('-inf'), float('inf'))