二叉搜索树-增删查Python

树的高度：节点到叶子节点的最大值就是其高度。
树的深度：高度和深度是相反的，高度是从下往上数，深度是从上往下。因此根节点的深度和叶子节点的高度是 0。
树的层：根开始定义，根为第一层，根的孩子为第二层。
二叉树，三叉树，。。。 N 叉树，由其子节点最多可以有几个决定，最多有 N 个就是 N 叉树

二叉搜索树又名有序二叉树，节点元素按特定次序排布，使得我们可以在查找等操作中使用二分查找提高效率

特点：父节点的值大于左子树任意节点的值，小于右子树任意节点的值

class BinarySearchTree(object):
    def __init__(self, item):
        self.item = item
        self.left = None
        self.right = None

    def insert_node(self, value):
        # 插入节点
        if value <= self.item and self.left:
            self.left.insert_node(value)
        elif value <= self.item:
            self.left = BinarySearchTree(value)
        elif value > self.item and self.right:
            self.right.insert_node(value)
        else:
            self.right = BinarySearchTree(value)

    def remove_node(self, value, parent):
        # 删除节点 情况1.叶子节点；情况2.只有左孩子或又孩子；情况3.同时有左右孩子
        if value < self.item and self.left:
            return self.remove_node(value, self)
        elif value < self.item:
            return False
        elif value > self.item and self.right:
            return self.remove_node(value, self)
        elif value > self.item:
            return False
        else:
            # 叶子节点
            if self.left is None and self.right is None and self == parent.left:
                parent.left = None
                self.clear_node()
            elif self.right is None and self.right is None and self == parent.right:
                parent.right = None
                self.clear_node()
            elif self.left and self.right is None and self == parent.left:
                parent.left = self.left
                self.clear_node()
            elif self.left and self.right is None and self == parent.right:
                parent.right =  self.left
                self.clear_node()
            elif self.right and self.left is None and self == parent.left:
                parent.left = self.right
                self.remove_node()
            elif self.right and self.left is None and self == parent.right:
                parent.right = self.right
                self.remove_node()
            else:
                # 将右子树最小值放到该节点
                self.value = self.right.find_minimum_value()
                self.right.clear_node(self.value, self)


    def find_node(self, value):
        # 查找某一节点
        if value < self.item and self.left:
            return self.left.find_node(value)
        if value > self.item and self.right:
            return self.right.find_node(value)
        return value == self.item

    def find_minimum_value(self):
        # 找到最小值
        if self.left:
            return self.left.find_minimum_value()
        else:
            return self.item

    def clear_node(self):
        # 节点清零
        self.item = None
        self.left = None
        self.right = None


if __name__ == '__main__':
    root = BinarySearchTree(50)
    root.insert_node(76)
    root.insert_node(21)
    root.insert_node(4)
    root.insert_node(32)
    root.insert_node(100)
    root.insert_node(64)
    root.insert_node(52)

    print(root.find_node(1000))
    print(root.find_minimum_value())