1. implement stack use two queues.
1 #coding:utf-8 2 class MyStack: 3 def __init__(self): 4 self.que1=[] 5 self.que2=[] 6 7 def push(self,val): 8 #始终插入que1 9 self.que1.append(val) 10 11 12 def pop(self): 13 if(len(self.que1)==0): 14 raise("Empty stack!") 15 while(len(self.que1)>1): 16 self.que2.append(self.que1.pop(0)) 17 18 res=self.que1.pop(0) 19 20 while(len(self.que2)>0): 21 self.que1.append(self.que2.pop(0)) 22 23 return res 24 25 26 stack=MyStack() 27 stack.push(1) 28 stack.push(2) 29 print(stack.pop()) 30 stack.push(4) 31 stack.push(5) 32 print(stack.pop()) 33 print(stack.pop()) 34 print(stack.pop()) 35 print(stack.pop())
2. implement que use two stacks.
1 class MyQueue: 2 def __init__(self): 3 self.stack1=[] 4 self.stack2=[] 5 6 def push(self,val): 7 self.stack1.append(val) 8 9 def pop(self): 10 if(len(self.stack1)==0): 11 raise("Empty que!") 12 13 while(len(self.stack1)>1): 14 self.stack2.append(self.stack1.pop()) 15 res=self.stack1.pop() 16 while(len(self.stack2)>0): 17 self.stack1.append(self.stack2.pop()) 18 return res 19 20 que=MyQueue() 21 que.push(1) 22 que.push(2) 23 print(que.pop()) 24 que.push(3) 25 que.push(4) 26 print(que.pop()) 27 print(que.pop()) 28 print(que.pop()) 29 print(que.pop())
3. min_stack
1 class MinStack: 2 def __init__(self): 3 self.stack=[] 4 self.minstk=[] 5 6 def push(self,x): 7 if(len(self.stack)==0): 8 self.stack.append(x) 9 self.minstk.append(x) 10 11 tmp=min(self.minstk[-1],x) 12 self.stack.append(x) 13 self.minstk.append(tmp) 14 15 def pop(self): 16 if(len(self.stack)==0): 17 raise("Empty stack!") 18 19 self.minstk.pop() 20 return self.stack.pop() 21 22 def get_min(self): 23 return self.minstk[-1] 24 25 26 st=MinStack() 27 st.push(-2) 28 print(st.get_min()) 29 st.push(0) 30 print(st.get_min()) 31 st.push(-5) 32 print(st.get_min()) 33 print("pop:",st.pop()) 34 print(st.get_min())
4. valid pop_seq
class Solution: def __init__(self): pass def is_valid(self,push_seq,pop_seq): self.push_st=[] for i in range(len(push_seq)): self.push_st.append(push_seq[i]) while(len(self.push_st) and self.push_st[-1]==pop_seq[0]): self.push_st.pop() pop_seq.pop(0) return len(self.push_st)==0 s=Solution() push_seq=[1,2,3,4,5] pop1=[3,2,5,4,1] print(s.is_valid(push_seq,pop1)) pop2=[3,1,2,4,5] print(s.is_valid(push_seq,pop2))
5. simple cal
1 class Solution: 2 BEGIN_STATE=0 3 NUMBER_STATE=1 4 OP_STATE=2 5 6 def calculate(self,s): 7 self.number_st=[] 8 self.op_st=[] 9 10 num=0; 11 state=BEGIN_STATE 12 compute_flag=0 13 14 for u in range(len(s)): 15 if(s[i]==' '): 16 continue 17 if state==BEGIN_STATE: 18 if(s[i]>='0' and s[i]<='9'): 19 state=NUMBER_STATE 20 else: 21 state=OP_STATE 22 i-=1 23 elif state==NUMBER_STATE: 24 if(0<=int(s[i]<=9)): 25 number=number*10+int(s[i]) 26 else: 27 self.number_st.append(number) 28 if(compute_flag==1): 29 right,left=self.number_st.pop(),self.number_st.pop() 30 res=left+right if(self.op.pop()=="+") else left-right 31 self.number_st.append(res) 32 number=0 33 i-=1 34 state=OP_STATE 35 elif state==OP_STATE: 36 if(s[i]=="+" or s[i]=="-"): 37 self.op_st.append(s[i]) 38 compute_flag=1 39 elif s[i]=='(': 40 state=NUMBER_STATE 41 compute_flag=0 42 elif (0<=int(s[i]<=9)): 43 state=NUMBER_STATE 44 i-=1 45 elif s[i]==')': 46 right,left=self.number_st.pop(),self.number_st.pop() 47 res=left+right if(self.op.pop()=="+") else left-right 48 self.number_st.append(res) 49 if number!=0: 50 self.number_st.append(number) 51 right,left=self.number_st.pop(),self.number_st.pop() 52 res=left+right if(self.op.pop()=="+") else left-right 53 self.number_st.append(res) 54 55 if(number==0 and len(self.number_st)==0): 56 return 0 57 58 return self.number_st[0]
6. topK
python中堆和优先队列（均是小顶堆）的使用：
优先队列（本身带有存储容器）
from queue import PriorityQueue #向队列中添加元素 Queue.put(item[, block[, timeout]]) #从队列中获取元素 Queue.get([block[, timeout]]) #队列判空 Queue.empty() #队列大小 Queue.qsize()
堆（本身不带存储容器，只是定义了一组对容器进行堆相关操作的函数）
1 from heapq import * 2 heap = [] # creates an empty heap 3 heappush(heap, item) # pushes a new item on the heap 4 item = heappop(heap) # pops the smallest item from the heap 5 item = heap[0] # smallest item on the heap without popping it 6 heapify(x) # transforms list into a heap, in-place, in linear time 7 item = heapreplace(heap, item) # pops and returns smallest item, and adds 8 # new item; the heap size is unchanged
topK实现：维持一个k大小的小顶堆
1 from heapq import * 2 3 def get_topK(nums,k): 4 hq=nums[:k] 5 heapify(hq) 6 7 for i in range(k,len(nums)): 8 if(nums[i]>hq[0]): 9 heappop(hq) 10 heappush(hq,nums[i]) 11 12 return hq[0] 13 14 nums=[1,5,9,-2,55,77,2] 15 print(get_topK(nums,2))
7. median in data stream
from heapq import * class Solution: def __init__(self): self.leftq=[] self.rightq=[] def add(self,x): heappush(self.leftq,-x) if(len(self.leftq)!=0): heappush(self.rightq,-heappop(self.leftq)) if( len(self.rightq)-len(self.leftq)>0 ): heappush(self.leftq,-heappop(self.rightq)) def get_median(self): if((len(self.leftq)+len(self.rightq))&1==1): return -self.leftq[0] else: return (-self.leftq[0]+self.rightq[0])/2.0 s=Solution() s.add(1) print(s.get_median()) s.add(2) print(s.get_median()) s.add(3) print(s.get_median()) s.add(4) print(s.get_median())