Coding~

数据结构--Python

Python 数据结构笔记

1. STACK

1.1 栈的定义

栈: 官方定义, 一种特殊的串行数据结构, 只允许在一端进行加入数据与取出数据操作.

1.2 栈的例子

两个例子:

  • 桌面上的一摞书

  • 浏览器后退按钮

浏览器有个后退按钮, 每次点击, 跳转到最靠近当前页的 URL. (实际上, 进行的是 URLS 出栈操作).

image

1.3 栈的实现

栈遵循的是规则被称为 LIFO, last-in first-out, 具体的操作比较简单, 使用 Python List 强大的功能实现如下:

class Stack:
    def __init__(self):
        self.items = []

    def push(self, item):
        self.items.append(item)

    def pop(self):
        self.items.pop()

    def get_peek(self):
        return self.items[-1]

    def get_size(self):
        return len(self.items)

    def is_empty(self):
        return 0 == self.get_size()

    def display(self):
        print(self.items)

1.4 栈的应用

1.4.1 校验四则运算表达式

计算机进行四则运算, 会先验证式子的格式正不正确, 下面对括弧判断一下:

{[()]}() --> True
[](} --> False

处理思路非常清晰, 存入左括号, 如果新增的右括号刚好凑对, 就消掉, 和玩连连看一个原理.


def is_right_bracelet_format(s):
    stack = Stack()

    for element in s:
        if element in '{[(':
            stack.push(element)
        else:
            if stack.is_empty() or not bracelet_type_match(stack.get_peek(), element):
                return False
            stack.pop()
    return stack.is_empty()


def bracelet_type_match(left_type, right_type):
    left_type_list = ['(', '[', '{']
    right_type_list = [')', ']', '}']
    return left_type_list.index(left_type) == right_type_list.index(right_type)

1.4.2 进制转换

2. Queue

类比与栈, 队列遵循的是规则被称为 FIFO, first-in first-out. 有个通俗的说法描述如下, 啊哈哈哈.

吃了吐是栈, 吃了拉是队列

2.1 队列的实现

队列分为分为普通队列和双端队列, 普通队列包括 队尾入队 和 队头出队, 双端队列两头都能进行 入队/出队.

普通队列实现, 按照从左到右的顺序, 左边是队尾.

class Queue:
    def __init__(self):
        self.items = []

    def enqueue(self, item):
        self.items.insert(0, item)

    def dequeue(self):
        self.items.pop()

    def get_size(self):
        return len(self.items)

    def is_empty(self):
        return self.get_size() == 0

    def display(self):
        print(self.items)

双端队列, 多了个方法:


class Deque:
    '''
        队列从左到右, 右边是队头
    '''

    def __init__(self):
        self.items = []

    def add_rear(self, item):
        self.items.insert(0, item)

    def remove_rear(self):
        self.items.pop(0)

    def add_front(self, item):
        self.items.append(item)

    def remove_front(self):
        self.items.pop()

    def get_size(self):
        return len(self.items)

    def is_empty(self):
        return self.get_size() == 0

    def display(self):
        print(self.items)

3. TREE

二叉树: Binary tree, 是每个节点最多只有两个分支的树结构.

3.1 二叉树实现


class BinaryTree:
    def __init__(self, root_object):
        self.key = root_object
        self.left_child = None
        self.right_child = None

    def insert_left(self, node):
        if self.left_child is None:
            self.left_child = BinaryTree(node)
        else:
            tmp_node = BinaryTree(node)
            tmp_node.left_child = self.left_child
            self.left_child = tmp_node

    def insert_right(self, node):
        tmp_node = BinaryTree(node)
        if self.right_child is None:
            self.right_child = tmp_node
        else:
            tmp_node.right_child = self.right_child
            self.right_child = tmp_node

    def get_left_child(self):
        return self.left_child

    def get_right_child(self):
        return self.right_child

    def get_root(self):
        return self.key

二叉树的遍历

ft_child():
        pre_order_display(tree.get_left_child())

    if tree.get_right_child():
        pre_order_display(tree.get_right_child())


# 中序遍历
def in_order_display(tree):
    if not isinstance(tree, BinaryTree):
        return False

    if tree.get_left_child():
        in_order_display(tree.get_left_child())

    print(tree.key)

    if tree.get_right_child():
        in_order_display(tree.get_right_child())


# 后序遍历
def post_order_display(tree):
    if not isinstance(tree, BinaryTree):
        return False

    if tree.get_left_child():
        post_order_display(tree.get_left_child())

    if tree.get_right_child():
        post_order_display(tree.get_right_child())

    print(tree.key)

# 翻转

def invert_binary_tree(tree):
    tree.left_child, tree.right_child = tree.right_child, tree.left_child
    if tree.get_left_child() != None:
        invert_binary_tree(tree.get_left_child())
    if tree.get_right_child() != None:
        invert_binary_tree(tree.get_right_child())

@TODO

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Published

23 June 2017

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