《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！

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为了比较性能，我写了个用于函数计时的装饰器：

import timefrom functools import wrapsdef 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

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P12 LINEAR-SEARCH(A,n,x)

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

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

@ftimerdef 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

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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 resultdef 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)