《算法基础》所有算法的Python实现

写这篇文章并不是面向读者的，主要就是当记笔记。

我的编程基础太烂，我之前想我以后要搞工程，也不搞ACM，所以一直没有重视算法。但是现在想来，之前的想法就实在可笑了。算法基础不行，不论是搞工程还是搞学术，都太容易触碰到自己的天花板。一句话：目光短浅！

现在打算每天晚上花1~2个小时用在算法上。看算法书或在网上刷题。

由于个人能力尚且太浅，如果真的有人看我下面的代码的话，还请多多指教！

为了比较性能，我写了个用于函数计时的装饰器：

import time
from functools import wraps

def ftimer(func):
@wraps(func)
def function_timer(*args,**kwargs):
t0=time.time()
result=func(*args,**kwargs)
t1=time.time()
print 'the running time of function "%s" is %.12f seconds' %(func.__name__,t1-t0)
return result
return function_timer

于是每次写代码前要先

from decorators import ftimer

P12 LINEAR-SEARCH(A,n,x)

@ftimer
def linear_search(A,n,x):
ans='NOT_FOUND'
for i in range(n):
if A[i]==x:
ans=i+1
return ans

nums=[0,5,2,3,1,4,6]
n=len(nums)
x=int(raw_input('input a num to search:'))
ans=linear_search(nums,n,x)
print 'the anwser is',ans

P13 BETTER-LINEAR-SEARCH(A,n,x)

@ftimer
def linear_search(A,n,x):
ans='NOT_FOUND'
for i in range(n):
if A[i]==x:
ans=i+1
break
return ans

nums=[0,5,2,3,1,4,6]
n=len(nums)
x=int(raw_input('input a num to search:'))
ans=linear_search(nums,n,x)
print 'the anwser is',ans

P14 SENTINEL-LINEAR-SEARCH(A,n,x)

@ftimer
def linear_search(A,n,x):
last=A[n-1]
A[n-1]=x
i=0
while A[i]!=x:
i+=1
A[n-1]=last
if i<n-1 or A[n-1]==x:
return i+1
return 'NOT_FOUND'

nums=[0,5,2,3,1,4,6]
n=len(nums)
x=int(raw_input('input a num to search:'))
ans=linear_search(nums,n,x)
print 'the anwser is',ans

今天到此为止。打卡，嘀~

2017/9/28

2017/10/5

写完没保存就关了。。今天主要写了查找和排序的几个算法

今天实在不想再码一遍了，在网上找了个写排序比较好的博客http://python.jobbole.com/82270/

借他几段代码，其他几段代码，尤其是几个查找的代码，以后有空了在码一遍，反正这种基本功多码几遍也亏不了

再推荐一篇文章http://blog.jobbole.com/11745/

http://blog.jobbole.com/79288/

插入排序

def insert_sort(lists):
# 插入排序
count = len(lists)
for i in range(1, count):
key = lists[i]
j = i - 1
while j >= 0:
if lists[j] > key:
lists[j + 1] = lists[j]
lists[j] = key
j -= 1
return lists

希尔排序

这个还需要好好研究一下

def shell_sort(lists):
# 希尔排序
count = len(lists)
step = 2
group = count / step
while group > 0:
for i in range(0, group):
j = i + group
while j < count:
k = j - group
key = lists[j]
while k >= 0:
if lists[k] > key:
lists[k + group] = lists[k]
lists[k] = key
k -= group
j += group
group /= step
return lists

冒泡排序

def bubble_sort(lists):
# 冒泡排序
count = len(lists)
for i in range(0, count):
for j in range(i + 1, count):
if lists[i] > lists[j]:
lists[i], lists[j] = lists[j], lists[i]
return lists

快速排序

这个还需要再看看

def quick_sort(lists, left, right):
# 快速排序
if left >= right:
return lists
key = lists[left]
low = left
high = right
while left < right:
while left < right and lists[right] >= key:
right -= 1
lists[left] = lists[right]
while left < right and lists[left] <= key:
left += 1
lists[right] = lists[left]
lists[right] = key
quick_sort(lists, low, left - 1)
quick_sort(lists, left + 1, high)
return lists

选择排序

def select_sort(lists):
# 选择排序
count = len(lists)
for i in range(0, count):
min = i
for j in range(i + 1, count):
if lists[min] > lists[j]:
min = j
lists[min], lists[i] = lists[i], lists[min]
return lists

归并排序

def merge(left, right):
i, j = 0, 0
result = []
while i < len(left) and j < len(right):
if left[i] <= right[j]:
result.append(left[i])
i += 1
else:
result.append(right[j])
j += 1
result += left[i:]
result += right[j:]
return result

def merge_sort(lists):
# 归并排序
if len(lists) <= 1:
return lists
num = len(lists) / 2
left = merge_sort(lists[:num])
right = merge_sort(lists[num:])
return merge(left, right)