python 常用的排序算法

def insert_sort(ilist):
    for i in range(len(ilist)):
        for j in range(i):
            if ilist[i] < ilist[j]:
                ilist.insert(j, ilist.pop(i))
                break
    return ilist
 
ilist = insert_sort([4,5,6,7,3,2,6,9,8])
print ilist

def bubble_sort(blist):
    count = len(blist)
    for i in range(0, count):
        for j in range(i + 1, count):
            if blist[i] > blist[j]:
                blist[i], blist[j] = blist[j], blist[i]
    return blist
 
blist = bubble_sort([4,5,6,7,3,2,6,9,8])
print blist

def quick_sort(qlist):
    if qlist == []:
        return []
    else:
        qfirst = qlist[0]
        qless = quick_sort([l for l in qlist[1:] if l < qfirst])
        qmore = quick_sort([m for m in qlist[1:] if m >= qfirst])
        return qless + [qfirst] + qmore
 
qlist = quick_sort([4,5,6,7,3,2,6,9,8])
print qlist

def select_sort(slist):
    for i in range(len(slist)):
        x = i
        for j in range(i, len(slist)):
            if slist[j] < slist[x]:
                x = j
        slist[i], slist[x] = slist[x], slist[i]
    return slist
 
slist = select_sort([4,5,6,7,3,2,6,9,8])
print slist

#!/usr/bin/python
# -*- coding: utf-8 -*-
#二分查找，用于在较大的数据列表中查询某个值，考虑到元素比较多，单纯的遍历会造成内存压力过大，考虑使用二分查找
#二分查找的关键在于查询中间值，将需要查找的值与中间值进行比较，然后确定查找方向
def binary_search(data_source,find_n):
    #取中位数
    mid=int(len(data_source)/2)

    if len(data_source)>=1:
        if data_source[mid]>find_n:  #中位数大于要查找的数，则要查找的数在左半部分，继续调用二分算法进行查找
            binary_search(data_source[:mid],find_n)
        elif data_source[mid]<find_n:  #中位数小于要查找的数，则要查找的数在右半部分
            binary_search(data_source[mid:],find_n)
        else:   #中位数等于要查找的数
            print("找到了：",data_source[mid])

    else:
        print("没有找到")


if __name__=="__main__":
    data=list(range(3,1600))
    binary_search(data,400)