class Stack(object):def __init__(self, limit=10):self.stack = [] #存放元素self.limit = limit #栈容量极限def push(self, data): #判断栈是否溢出if len(self.stack) >= self.limit:print('StackOverflowError')passself.stack.append(data)def pop(self):if self.stack:return self.stack.pop()else:raise IndexError('pop from an empty stack') #空栈不能被弹出def peek(self): #查看堆栈的最上面的元素if self.stack:return self.stack[-1]def is_empty(self): #判断栈是否为空return not bool(self.stack)def size(self): #返回栈的大小return len(self.stack)

class Node:  def __init__(self, data):self.data = data  self.next = None
class Linked_List:def __init__(self):self.head = Nonedef initlist(self,data_list):    #链表初始化函数self.head=Node(data_list[0])   #创建头结点temp=self.headfor i in data_list[1:]: #逐个为 data 内的数据创建结点, 建立链表node=Node(i)temp.next=nodetemp=temp.nextdef is_empty(self):  #判断链表是否为空if self.head.next==None:print("Linked_list is empty")return Trueelse:return Falsedef get_length(self):  #获取链表的长度temp=self.head #临时变量指向队列头部length=0 #计算链表的长度变量while temp!=None:length=length+1temp=temp.nextreturn length #返回链表的长度def insert(self,key,value): #链表插入数据函数if key<0 or key>self.get_length()-1:print("insert error")temp=self.headi=0while i<=key: #遍历找到索引值为 key 的结点后, 在其后面插入结点pre=temptemp=temp.nexti=i+1node=Node(value)pre.next=nodenode.next=tempdef print_list(self):   #遍历链表，并将元素依次打印出来print("linked_list:")temp=self.headnew_list=[]while temp is not None:new_list.append(temp.data)temp=temp.nextprint(new_list)def remove(self,key):  #链表删除数据函数if key<0 or key>self.get_length()-1:print("insert error")i=0temp=self.headwhile temp !=None:  #遍历找到索引值为 key 的结点pre=temptemp=temp.nexti=i+1if i==key:pre.next=temp.nexttemp=Nonereturn Truepre.next=Nonedef reverse(self): #将链表反转prev = Nonecurrent = self.headwhile current:next_node = current.nextcurrent.next = prevprev = currentcurrent = next_nodeself.head = prev

class Node(object):# 双向链表节点def __init__(self, item):self.item = itemself.next = Noneself.prev = None
class DLinkList(object):# 双向链表def __init__(self):self._head = Nonedef is_empty(self):# 判断链表是否为空return self._head == Nonedef get_length(self):# 返回链表的长度cur = self._headcount = 0while cur != None:count=count+1cur = cur.nextreturn countdef travel(self):# 遍历链表cur = self._headwhile cur != None:print(cur.item)cur = cur.nextprint("")def add(self, item):# 头部插入元素node = Node(item)if self.is_empty():# 如果是空链表，将_head指向nodeself._head = nodeelse:# 将node的next指向_head的头节点node.next = self._head# 将_head的头节点的prev指向nodeself._head.prev = node# 将_head 指向nodeself._head = nodedef append(self, item):# 尾部插入元素node = Node(item)if self.is_empty():# 如果是空链表，将_head指向nodeself._head = nodeelse:# 移动到链表尾部cur = self._headwhile cur.next != None:cur = cur.next# 将尾节点cur的next指向nodecur.next = node# 将node的prev指向curnode.prev = curdef search(self, item):# 查找元素是否存在cur = self._headwhile cur != None:if cur.item == item:return Truecur = cur.nextreturn Falsedef insert(self, pos, item):# 在指定位置添加节点if pos <= 0:self.add(item)elif pos > (self.length()-1):self.append(item)else:node = Node(item)cur = self._headcount = 0# 移动到指定位置的前一个位置while count < (pos-1):count += 1cur = cur.next# 将node的prev指向curnode.prev = cur# 将node的next指向cur的下一个节点node.next = cur.next# 将cur的下一个节点的prev指向nodecur.next.prev = node# 将cur的next指向nodecur.next = nodedef remove(self, item):# 删除元素if self.is_empty():returnelse:cur = self._headif cur.item == item:# 如果首节点的元素即是要删除的元素if cur.next == None:# 如果链表只有这一个节点self._head = Noneelse:# 将第二个节点的prev设置为Nonecur.next.prev = None# 将_head指向第二个节点self._head = cur.nextreturnwhile cur != None:if cur.item == item:# 将cur的前一个节点的next指向cur的后一个节点cur.prev.next = cur.next# 将cur的后一个节点的prev指向cur的前一个节点cur.next.prev = cur.prevbreakcur = cur.next

class Node(object):def __init__(self,elem,next=None):self.elem = elem #表示对应的元素值self.next=next #表示下一个链接的链点
class Queue(object):def __init__(self):self.head = None #头部链点为 Noneself.rear = None #尾部链点为 Nonedef is_empty(self):return self.head is None #判断队列是否为空def enqueue(self, elem):p = Node(elem) #初始化一个新的点if self.is_empty():self.head = p #队列头部为新的链点self.rear = p #队列尾部为新的链点else:self.rear.next = p #队列尾部的后继是这个新的点self.rear =p #然后让队列尾部指针指向这个新的点def dequeue(self):if self.is_empty(): #判断队列是否为空print('Queue_is_empty') #若队列为空，则退出 dequeue 操作else:result = self.head.elem #result为队列头部元素self.head = self.head.next #改变队列头部指针位置return result #返回队列头部元素def peek(self):if self.is_empty(): #判断队列是否为空print('NOT_FOUND') #为空则返回 NOT_FOUNDelse:return self.head.elem #返回队列头部元素def print_queue(self):print("queue:")temp=self.headmyqueue=[] #暂时存放队列数据while temp is not None:myqueue.append(temp.elem)temp=temp.nextprint(myqueue)

class Queue():def __init__(self):self.entries = [] #表示队列内的参数self.length = 0 #表示队列的长度self.front=0 #表示队列头部位置def enqueue(self, item):self.entries.append(item) #添加元素到队列里面self.length = self.length + 1 #队列长度增加 1def dequeue(self):self.length = self.length - 1 #队列的长度减少 1dequeued = self.entries[self.front] #队首元素为dequeuedself.front-=1 #队首的位置减少1self.entries = self.entries[self.front:] #队列的元素更新为退队之后的队列return dequeueddef peek(self):return self.entries[0] #直接返回队列的队首元素

class Node(object):def __init__(self,item):self.item=item #表示对应的元素self.left=None #表示左节点self.right=None #表示右节点def __str__(self):return str(self.item)  #print 一个 Node 类时会打印 __str__ 的返回值
class Tree(object):def __init__(self):self.root=Node('root')  #根节点定义为 root 永不删除，作为哨兵使用。def add(self,item):node = Node(item)if self.root is None:  #如果二叉树为空，那么生成的二叉树最终为新插入树的点self.root = nodeelse:q = [self.root] # 将q列表，添加二叉树的根节点while True:pop_node = q.pop(0)if pop_node.left is None: #左子树为空则将点添加到左子树pop_node.left = nodereturnelif pop_node.right is None: #右子树为空则将点添加到右子树pop_node.right = nodereturnelse:q.append(pop_node.left)q.append(pop_node.right)def get_parent(self, item):if self.root.item == item:return None  # 根节点没有父节点tmp = [self.root] # 将tmp列表，添加二叉树的根节点while tmp:pop_node = tmp.pop(0)if pop_node.left and pop_node.left.item == item: #某点的左子树为寻找的点return pop_node #返回某点，即为寻找点的父节点if pop_node.right and pop_node.right.item == item: #某点的右子树为寻找的点return pop_node #返回某点，即为寻找点的父节点if pop_node.left is not None: #添加tmp 元素tmp.append(pop_node.left)if pop_node.right is not None:tmp.append(pop_node.right)return Nonedef delete(self, item):if self.root is None:  # 如果根为空，就什么也不做return Falseparent = self.get_parent(item)if parent:del_node = parent.left if parent.left.item == item else parent.right  # 待删除节点if del_node.left is None:if parent.left.item == item:parent.left = del_node.rightelse:parent.right = del_node.rightdel del_nodereturn Trueelif del_node.right is None:if parent.left.item == item:parent.left = del_node.leftelse:parent.right = del_node.leftdel del_nodereturn Trueelse:  # 左右子树都不为空tmp_pre = del_nodetmp_next = del_node.rightif tmp_next.left is None:# 替代tmp_pre.right = tmp_next.righttmp_next.left = del_node.lefttmp_next.right = del_node.rightelse:while tmp_next.left:  # 让tmp指向右子树的最后一个叶子tmp_pre = tmp_nexttmp_next = tmp_next.left# 替代tmp_pre.left = tmp_next.righttmp_next.left = del_node.lefttmp_next.right = del_node.rightif parent.left.item == item:parent.left = tmp_nextelse:parent.right = tmp_nextdel del_nodereturn Trueelse:return False

class TrieNode:def __init__(self):self.nodes = dict()  # 构建字典self.is_leaf = Falsedef insert(self, word: str):  curr = selffor char in word:if char not in curr.nodes:curr.nodes[char] = TrieNode()curr = curr.nodes[char]curr.is_leaf = Truedef insert_many(self, words: [str]):for word in words:self.insert(word)def search(self, word: str):curr = selffor char in word:if char not in curr.nodes:return Falsecurr = curr.nodes[char]return curr.is_leaf

class heap(object):def __init__(self):#初始化一个空堆，使用数组来在存放堆元素，节省存储self.data_list = []def get_parent_index(self,index):#返回父节点的下标if index == 0 or index > len(self.data_list) -1:return Noneelse:return (index -1) >> 1def swap(self,index_a,index_b):#交换数组中的两个元素self.data_list[index_a],self.data_list[index_b] = self.data_list[index_b],self.data_list[index_a]def insert(self,data):#先把元素放在最后，然后从后往前依次堆化#这里以大顶堆为例，如果插入元素比父节点大，则交换，直到最后self.data_list.append(data)index = len(self.data_list) -1 parent = self.get_parent_index(index)#循环，直到该元素成为堆顶，或小于父节点（对于大顶堆) while parent is not None and self.data_list[parent] < self.data_list[index]:#交换操作self.swap(parent,index)index = parentparent = self.get_parent_index(parent)def removeMax(self):#删除堆顶元素，然后将最后一个元素放在堆顶，再从上往下依次堆化remove_data = self.data_list[0]self.data_list[0] = self.data_list[-1]del self.data_list[-1]#堆化self.heapify(0)return remove_datadef heapify(self,index):#从上往下堆化，从index 开始堆化操作 (大顶堆)total_index = len(self.data_list) -1while True:maxvalue_index = indexif 2*index +1 <=  total_index and self.data_list[2*index +1] > self.data_list[maxvalue_index]:maxvalue_index = 2*index +1if 2*index +2 <=  total_index and self.data_list[2*index +2] > self.data_list[maxvalue_index]:maxvalue_index = 2*index +2if maxvalue_index == index:breakself.swap(index,maxvalue_index)index = maxvalue_index