这篇文章主要为大家展示了“怎么用python实现各种数据结构”，内容简而易懂，条理清晰，希望能够帮助大家解决疑惑，下面让小编带领大家一起研究并学习一下“怎么用python实现各种数据结构”这篇文章吧。
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)以上是“怎么用python实现各种数据结构”这篇文章的所有内容，感谢各位的阅读！相信大家都有了一定的了解，希望分享的内容对大家有所帮助，如果还想学习更多知识，欢迎关注编程网行业资讯频道！
