csdn_spider/blog/ds19991999/原创-- Python数据结构(五)——排序和搜索.md

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2021-02-27 15:01:45 +00:00
# 原创
Python数据结构——排序和搜索
# Python数据结构——排序和搜索
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## 排序和搜索
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```
15 in [3,3,2,1,4]
```
```
False
```
```
3 in [3,4,5,6]
```
```
True
```
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### 顺序查找
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```
# 查找列表中的项,假设列表项无序
def sequence_search(alist,item):
pos = 0
found = False
while pos<len(alist) and not found:
if alist[pos]==item:
found = True
else:
pos += 1
return found
testlist = [1, 2, 32, 8, 17, 19, 42, 13, 0]
print(sequence_search(testlist, 3))
print(sequence_search(testlist, 13))
```
```
False
True
```
```
# 查找列表中的项,假设列表项有序
def order_sequence_search(alist,item):
pos = 0
found = False
stop = False
while pos < len(alist) and not found and not stop:
if alist[pos] == item:
found = True
else:
if alist[pos]>item:
stop = True
else:
pos += 1
return found
testlist = [0, 1, 2, 8, 13, 17, 19, 32, 42,]
print(order_sequence_search(testlist, 3))
print(order_sequence_search(testlist, 13))
```
```
False
True
```
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### 二分法查找
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```
def binary_search(alist,item):
first = 0
last = len(alist)-1
found = False
while first<=last and not found:
mid = (first+last)/2
if alist[mid]==item:
found = True
elif alist[mid]>item:
last = mid - 1
else:
first = mid + 1
return found
testlist = [0, 1, 2, 8, 13, 17, 19, 32, 42,]
print(binary_search(testlist, 3))
print(binary_search(testlist, 13))
```
```
False
True
```
```
# 递归实现
def bianary_search(alist,item):
if len(alist)==0:
return False
else:
mid = len(alist)//2
if alist[mid]==item:
return True
else:
if item<alist[mid]:
return bianary_search(alist[:mid],item)
else:
return bianary_search(alist[mid+1:],item)
testlist = [0, 1, 2, 8, 13, 17, 19, 32, 42,]
print(binary_search(testlist, 3))
print(binary_search(testlist, 13))
```
```
False
True
```
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### Hash查找
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哈希表 是以一种容易找到它们的方式存储的项的集合。哈希表的每个位置,通常称为一个槽,可以容纳一个项,并且由从 0 开始的整数值命名。例如,我们有一个名为 0 的槽,名为 1 的槽,名为 2 的槽以上。最初哈希表不包含项因此每个槽都为空。我们可以通过使用列表来实现一个哈希表每个元素初始化为None 。Figure 4 展示了大小 m = 11 的哈希表。换句话说,在表中有 m 个槽,命名为 0 到 10。 <br/> <img alt="" src="https://raw.githubusercontent.com/ds19991999/githubimg/master/picgo/20180730133625.png" title=""/>
具体介绍见:[Hash查找](https://github.com/facert/python-data-structure-cn/tree/master/5.%E6%8E%92%E5%BA%8F%E5%92%8C%E6%90%9C%E7%B4%A2/5.5.Hash%E6%9F%A5%E6%89%BE)
```
def hash(astring, tablesize):
sum = 0
for pos in range(len(astring)):
sum = sum+ord(astring[pos])
return sum%tablesize
```
冲突解决: <br/> <img alt="" src="https://raw.githubusercontent.com/ds19991999/githubimg/master/picgo/20180730135953.png" title=""/>
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### 排序
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```
# 冒泡排序
def bubble_sort_1(alist):
for j in range(len(alist)-1,0,-1):
for i in range(j):
if alist[i]&gt;alist[i+1]:
alist[i],alist[i+1]=alist[i+1],alist[i]
return alist
alist = [54,26,93,17,77,31,44,55,20]
print bubble_sort_1(alist)
```
```
[17, 20, 26, 31, 44, 54, 55, 77, 93]
```
```
# 优化冒泡排序,识别有序序列,修改冒泡排序提前停止
def bubble_sort_2(alist):
exchange = True
j = len(alist)-1
while j&gt;0 and exchange:
exchange = False
for i in range(j):
if alist[i] &gt; alist[i+1]:
alist[i],alist[i+1]=alist[i+1],alist[i]
exchange = True
j -= 1
return alist
alist=[30,20,40,90,50,60,70,80,100,110]
print bubble_sort_2(alist)
```
```
[20, 30, 40, 50, 60, 70, 80, 90, 100, 110]
```
```
# 简单选择排序
def select_sort(alist):
for i in range(len(alist)):
k = i
for j in range(k,len(alist)):
if alist[k]&gt;alist[j]:
k = j
alist[i],alist[k]=alist[k],alist[i]
return alist
alist = [54,26,93,17,77,31,44,55,20]
print select_sort(alist)
```
```
[17, 20, 26, 31, 44, 54, 55, 77, 93]
```
```
# 插入排序
def insert_sort(alist):
for i in range(0,len(alist)):
for j in range(i+1,len(alist)):
if alist[i]&gt;alist[j]:
tmp = alist[j]
alist.pop(j)
alist.insert(i,tmp)
return alist
alist = [54,26,93,17,77,31,44,55,20]
print insert_sort(alist)
```
```
[17, 20, 26, 31, 44, 54, 55, 77, 93]
```
```
# 插入排序2
def insert_sort_2(A):
length = len(A)
if length &lt; 2:
return A
for i in range(1,length-1):
key = A[i]
j = i-1
while j&gt;=0 and A[j]&gt;key:
A[j+1]=A[j]
j -= 1
A[j+1] = key
return A
alist = [54,26,93,17,77,31,44,55,20]
print insert_sort_2(alist)
```
```
[17, 26, 31, 44, 54, 55, 77, 93, 20]
```
更多排序算法见博客:[Python排序算法](https://blog.csdn.net/ds19991999/article/details/79998011)