Python实现二叉树结构与进行二叉树遍历的方法详解
作者：家威
二叉树是最基本的数据结构,这里我们在Python中使用类的形式来实现二叉树并且用内置的方法来遍历二叉树,下面就让我们一起来看一下Python实现二叉树结构与进行二叉树遍历的方法详解
二叉树的建立
使用类的形式定义二叉树，可读性更好
class BinaryTree:
def __init__(self, root):
self.key = root
self.left_child = None
self.right_child = None
def insert_left(self, new_node):
if self.left_child == None:
self.left_child = BinaryTree(new_node)
else:
t = BinaryTree(new_node)
t.left_child = self.left_child
self.left_child = t
def insert_right(self, new_node):
if self.right_child == None:
self.right_child = BinaryTree(new_node)
else:
t = BinaryTree(new_node)
t.right_child = self.right_child
self.right_child = t
def get_right_child(self):
return self.right_child
def get_left_child(self):
return self.left_child
def set_root_val(self, obj):
self.key = obj
def get_root_val(self):
return self.key
r = BinaryTree('a')
print(r.get_root_val())
print(r.get_left_child())
r.insert_left('b')
print(r.get_left_child())
print(r.get_left_child().get_root_val())
r.insert_right('c')
print(r.get_right_child())
print(r.get_right_child().get_root_val())
r.get_right_child().set_root_val('hello')
print(r.get_right_child().get_root_val())
Python进行二叉树遍历
需求：
python代码实现二叉树的：
1. 前序遍历，打印出遍历结果
2. 中序遍历，打印出遍历结果
3. 后序遍历，打印出遍历结果
4. 按树的level遍历，打印出遍历结果
5. 结点的下一层如果没有子节点，以‘N'代替
方法：
使用defaultdict或者namedtuple表示二叉树
使用StringIO方法，遍历时写入结果，最后打印出结果
打印结点值时，如果为空，StringIO（）写入‘N '
采用递归访问子节点
代码
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# test tree as below:
''' 1 / \ / \ / \ / \ 2 3 / \ / \ / \ / \ 4 5 6 N / \ / \ / \ 7 N N N 8 9 / \ / \ / \ N N N N N N '''
from collections import namedtuple
from io import StringIO
#define the node structure
Node = namedtuple('Node', ['data', 'left', 'right'])
#initialize the tree
tree = Node(1,
Node(2,
Node(4,
Node(7, None, None),
None),
Node(5, None, None)),
Node(3,
Node(6,
Node(8, None, None),
Node(9, None, None)),
None))
#read and write str in memory
output = StringIO()
#read the node and write the node's value
#if node is None, substitute with 'N '
def visitor(node):
if node is not None:
output.write('%i ' % node.data)
else:
output.write('N ')
#traversal the tree with different order
def traversal(node, order):
if node is None:
visitor(node)
else:
op = {
'N': lambda: visitor(node),
'L': lambda: traversal(node.left, order),
'R': lambda: traversal(node.right, order),
}
for x in order:
op[x]()
#traversal the tree level by level
def traversal_level_by_level(node):
if node is not None:
current_level = [node]
while current_level:
next_level = list()
for n in current_level:
if type(n) is str:
output.write('N ')
else:
output.write('%i ' % n.data)
if n.left is not None:
next_level.append(n.left)
else:
next_level.append('N')
if n.right is not None:
next_level.append(n.right)
else:
next_level.append('N ')
output.write('\n')
current_level = next_level
if __name__ == '__main__':
for order in ['NLR', 'LNR', 'LRN']:
if order == 'NLR':
output.write('this is preorder traversal:')
traversal(tree, order)
output.write('\n')
elif order == 'LNR':
output.write('this is inorder traversal:')
traversal(tree, order)
output.write('\n')
else:
output.write('this is postorder traversal:')
traversal(tree, order)
output.write('\n')
output.write('traversal level by level as below:'+'\n')
traversal_level_by_level(tree)
print(output.getvalue())