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Python如何实现的二分查找算法

作者：Python

在本篇文章里小编给大家分享的是一篇关于Python实现的二分查找算法实例讲解内容，需要的朋友们可以学习下。

先来看个用Python实现的二分查找算法实例

import sys 
def search2(a,m): 
 low = 0 
 high = len(a) - 1 
 while(low <= high): 
  mid = (low + high)/2
  midval = a[mid] 
   
  if midval < m: 
   low = mid + 1 
  elif midval > m: 
   high = mid - 1 
  else: 
   print mid 
   return mid 
 print -1
 return -1
if __name__ == "__main__": 
 a = [int(i) for i in list(sys.argv[1])] 
 m = int(sys.argv[2]) 
 search2(a,m)om/weixin.html#_labeldown

运行:

administrator@ubuntu:~/Python$ python test_search2.py 123456789 4

注:

1.'__'：由于python的类成员都是公有、公开的被存取public，缺少像正统面向对象语言的私有private属性。

于是就用__来将就一下，模拟私有属性。这些__属性往往是内部使用，通常情况下不用改写。也不用读取。

加上2个下划线的目的，一是不和普通公有属性重名冲突，二是不让对象的使用者(非开发者)随意使用。

2.__name__ == "__main__"表示程序脚本是直接被执行的.

如果不等于表示脚本是被其他程序用import引入的.则其__name__属性被设为模块名

Python采用二分查找找出数字的下标

要考虑有重复数字的情况

class Solution(object):
 def searchRange(self, nums, target):
  """
  :type nums: List[int]
  :type target: int
  :rtype: List[int]
  def binary_search(start,end,value):
   while end>=start:
    mid = (start+end)//2
    print(mid)
    if nums[mid]>target:
     end = mid-1
    elif nums[mid]<target: start="mid+1" else:="" if="" value="=-1:" mid-1="">=start and nums[mid+value] == target:
       end = mid+value
      else:
       return mid
     else:
      if mid+1<=end and nums[mid+value] == target:
       start = mid+value
   return -1
  a=binary_search(0,len(nums)-1,-1)
  b=binary_search(0,len(nums)-1,1)
  return [a,b]
a = Solution()
l = [2,2]
print(a.searchRange(l,2))
 
</target:>

二分算法的定义不在多说了

import sys 
source = [1,2,3,4,5,6,7,8,9,10] #must be in order 
des = int(sys.argv[1]) 
low = 0
high = len(source) - 1
targetIndex = -1
print "des=",des 
while low <= high: 
 middle = (low + high)/2
 if des == source[middle]: 
  targetIndex = middle 
  break
 elif des < source[middle]: 
  high = middle -1
  print "middle element[index=",middle,",value=",source[middle],"] is bigger than des, continue search from[",low,"to",high,"]"
 else: 
  low = middle + 1
  print "middle element[index=",middle,",value=",source[middle],"] is smaller than des, continue search from[",low,"to",high,"]"
print "search complete, target element's index in source list is ",targetIndex

最后在分享一个

'fileName--BinarySearch.py'

src = [] 
def BinarySearch(low, high, target, *src): 
 '二分查找'
 while low <= high: 
  mid = (low + high) // 2
  midVal = src[mid] 
  if target < midVal: 
   high = mid - 1
  elif target > midVal: 
   low = mid + 1
  else: 
   return mid 
  BinarySearch(low, high, target, *src) 
print('Please input 10 number:') 
for number in range(10): 
 src.append(int(input('Num %d:' % number))) 
sortList = tuple(src) 
key = int(input('Please input key:')) 
location = BinarySearch(0, len(src) - 1, key, *sortList) 
if location != None: 
 print('Find target at %d' % (location + 1)) 
else: 
 print('No target!')

实例补充

#!/usr/bin/python env
# -*- coding:utf-8 -*-

def half_search(array,target):
 low = 0
 high = len(array) - 1
 while low < high:
   mid = (low + high)/2
   if array[mid] > target:
   high = mid - 1
   elif array[mid] < target:
   low = mid + 1
   elif array[mid] == target:
   print 'I find it! It is in the position of:',mid
   return mid
   else:
   print "please contact the coder!"
 return -1

if __name__ == "__main__":
 array = [1, 2, 2, 4, 4, 5]

运行结果如下：

I find it! It is in the position of: 4
4
-1
I find it! It is in the position of: 0
0
-1

以上就是Python如何实现的二分查找算法的详细内容，更多关于用Python实现的二分查找算法的资料请关注脚本之家其它相关文章！

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