注意当节点非空，且在右子树高度减去左子树高度前，先给非空节点高度加1。对于本身高度为0的节点，意味着没有左右子树，直接返回平衡因子0。程序中直接使用了binarytree为每个节点的高度值属性height。
from binarytree import bst
def app():
t = bst(height=4, is_perfect=False)
print(t)
print('-----')
factors = []
for n in t.levelorder:
if n is None:
continue
else:
factors.append((n, get_blance_factor(n)))
print(factors)
# 平衡因子的计算，对于一个节点，该节点右子树高度减去左子树高度。
# 有些时候，也可以是左子树高度减去右子树高度。只要在代码系统中约定一致即可。
def get_blance_factor(node):
factor = 0
if node.height == 0:
factor = 0
return factor
left = node.left
right = node.right
lh = 0
rh = 0
if left is not None:
lh = node.left.height + 1
if right is not None:
rh = node.right.height + 1
factor = rh - lh
return factor
if __name__ == '__main__':
app()
输出：
__11____________
/ \
__7 __________26
/ \ / \
3 9 12___ 27___
/ \ \ \
2 6 _23 _30
/ / \ /
0 20 25 29
-----
[(Node(11), 0), (Node(7), -2), (Node(26), 0), (Node(3), -1), (Node(9), 0), (Node(12), 2), (Node(27), 2), (Node(2), -1), (Node(6), 0), (Node(23), 0), (Node(30), -1), (Node(0), 0), (Node(20), 0), (Node(25), 0), (Node(29), 0)]
