# 用python实现各种数据结构

## 快速排序

```    def quick_sort(_list):
if len(_list) < 2:
return _list
pivot_index = 0
pivot = _list(pivot_index)
left_list = [i for i in _list[:pivot_index] if i < pivot]
right_list = [i for i in _list[pivot_index:] if i > pivot]
return quick_sort(left) + [pivot] + quick_sort(right)

```

## 选择排序

```    def select_sort(seq):
n = len(seq)
for i in range(n-1)
min_idx = i
for j in range(i+1,n):
if seq[j] < seq[min_inx]:
min_idx = j
if min_idx != i:
seq[i], seq[min_idx] = seq[min_idx],seq[i]

```

## 插入排序

```    def insertion_sort(_list):
n = len(_list)
for i in range(1,n):
value = _list[i]
pos = i
while pos > 0 and value < _list[pos - 1]
_list[pos] = _list[pos - 1]
pos -= 1
_list[pos] = value
print(sql)

```

## 归并排序

``` def merge_sorted_list(_list1,_list2):   #合并有序列表
len_a, len_b = len(_list1),len(_list2)
a = b = 0
sort = []
while len_a > a and len_b > b:
if _list1[a] > _list2[b]:
sort.append(_list2[b])
b += 1
else:
sort.append(_list1[a])
a += 1
if len_a > a:
sort.append(_list1[a:])
if len_b > b:
sort.append(_list2[b:])
return sort

def merge_sort(_list):
if len(list1)<2:
return list1
else:
mid = int(len(list1)/2)
left = mergesort(list1[:mid])
right = mergesort(list1[mid:])
return merge_sorted_list(left,right)

```

## 堆排序heapq模块

```    from heapq import nsmallest
def heap_sort(_list):
return nsmallest(len(_list),_list)

```

## 栈

```    from collections import deque
class Stack:
def __init__(self):
self.s = deque()
def peek(self):
p = self.pop()
self.push(p)
return p
def push(self, el):
self.s.append(el)
def pop(self):
return self.pop()

```

## 队列

```    from collections import deque
class Queue:
def __init__(self):
self.s = deque()
def push(self, el):
self.s.append(el)
def pop(self):
return self.popleft()

```

## 二分查找

```    def binary_search(_list,num):
mid = len(_list)//2
if len(_list) < 1:
return Flase
if num > _list[mid]:
BinarySearch(_list[mid:],num)
elif num < _list[mid]:
BinarySearch(_list[:mid],num)
else:
return _list.index(num)
```