Python中如何高效收集排序和查找算法案例？

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Python实现几种不同的排序算法，代码来自老男孩Python全栈开发，学习教程！pythonimport randomimport timeimport copyimport sys

def cal_time(func): def wrapper(*args, **kwargs): t1=time.time() result=func(*args, **kwargs) t2=time.time() print(f{func.__name__} 耗时：{t2 - t1}秒) return result return wrapper

@cal_timedef bubble_sort(arr): for i in range(len(arr)): for j in range(len(arr) - 1 - i): if arr[j] > arr[j + 1]: arr[j], arr[j + 1]=arr[j + 1], arr[j] return arr

@cal_timedef selection_sort(arr): for i in range(len(arr)): min_idx=i for j in range(i + 1, len(arr)): if arr[min_idx] > arr[j]: min_idx=j arr[i], arr[min_idx]=arr[min_idx], arr[i] return arr

@cal_timedef insertion_sort(arr): for i in range(1, len(arr)): key=arr[i] j=i - 1 while j >=0 and key

@cal_timedef merge_sort(arr): if len(arr) <=1: return arr mid=len(arr) // 2 left=merge_sort(arr[:mid]) right=merge_sort(arr[mid:]) return merge(left, right)

def merge(left, right): result=[] i=j=0 while i

@cal_timedef quick_sort(arr): if len(arr) <=1: return arr pivot=arr[len(arr) // 2] left=[x for x in arr if x pivot] return quick_sort(left) + middle + quick_sort(right)

if __name__==__main__: arr=[random.randint(0, 1000) for _ in range(1000)] sorted_arr=copy.deepcopy(arr) bubble_sort(sorted_arr) selection_sort(sorted_arr) insertion_sort(sorted_arr) sorted_arr=copy.deepcopy(arr) merge_sort(sorted_arr) sorted_arr=copy.deepcopy(arr) quick_sort(sorted_arr)

Python 语言实现几种不同的排序算法，代码来自于老男孩Python全栈开发，学习教程！

import random
import time
import copy
import sys

def cal_time(func):
def wrapper(*args, **kwargs):
t1 = time.time()
result = func(*args, **kwargs)
t2 = time.time()
print("%s running time: %s secs." % (func.__name__, t2 - t1))
return result
return wrapper

@cal_time
def bubble_sort(li):
for i in range(len(li) - 1):
for j in range(len(li) - i - 1):
if li[j] > li[j+1]:
li[j], li[j+1] = li[j+1], li[j]

@cal_time
def bubble_sort_1(li):
for i in range(len(li) - 1):
exchange = False
for j in range(len(li) - i - 1):
if li[j] > li[j+1]:
li[j], li[j+1] = li[j+1], li[j]
exchange = True
if not exchange:
break

def select_sort(li):
for i in range(len(li) - 1):
min_loc = i
for j in range(i+1,len(li)):
if li[j] < li[min_loc]:
min_loc = j
li[i], li[min_loc] = li[min_loc], li[i]


def insert_sort(li):
for i in range(1, len(li)):
tmp = li[i]
j = i - 1
while j >= 0 and li[j] > tmp:
li[j+1]=li[j]
j = j - 1
li[j + 1] = tmp


def quick_sort_x(data, left, right):
if left < right:
mid = partition(data, left, right)
quick_sort_x(data, left, mid - 1)
quick_sort_x(data, mid + 1, right)

def partition(data, left, right):
tmp = data[left]
while left < right:
while left < right and data[right] >= tmp:
right -= 1
data[left] = data[right]
while left < right and data[left] <= tmp:
left += 1
data[right] = data[left]
data[left] = tmp
return left


@cal_time
def quick_sort(data):
return quick_sort_x(data, 0, len(data) - 1)

@cal_time
def sys_sort(data):
return data.sort()

def sift(data, low, high):
i = low
j = 2 * i + 1
tmp = data[i]
while j <= high: #只要没到子树的最后
if j < high and data[j] < data[j + 1]:
j += 1
if tmp < data[j]:#如果领导不能干
data[i] = data[j] #小领导上位
i = j
j = 2 * i + 1
else:
break
data[i] = tmp

def heap_sort(data):
n = len(data)
for i in range(n // 2 - 1, -1, -1):
sift(data, i, n - 1)
for i in range(n - 1, -1, -1):
data[0], data[i] = data[i], data[0]
sift(data, 0, i - 1)

sys.setrecursionlimit(100000)
data = list(range(1000, 1, -1))
data.sort()
#random.shuffle(data)
data1 = copy.deepcopy(data)
data2 = copy.deepcopy(data)
data3 = copy.deepcopy(data)

bubble_sort(data1)
quick_sort(data2)
sys_sort(data3)

Python语言实现的几种，不同的查找算法。

import time
import random

def cal_time(func):
def wrapper(*args, **kwargs):
t1 = time.time()
result = func(*args, **kwargs)
t2 = time.time()
print("%s running time: %s secs." % (func.__name__, t2 - t1))
return result
return wrapper

@cal_time
def bin_search(data_set, val):
low = 0
high = len(data_set) - 1
while low <= high:
mid = (low+high)//2
if data_set[mid]['id'] == val:
return mid
elif data_set[mid]['id'] < val:
low = mid + 1
else:
high = mid - 1
return


def binary_search(dataset, find_num):
if len(dataset) > 1:
mid = int(len(dataset) / 2)
if dataset[mid] == find_num:
#print("Find it")
return dataset[mid]
elif dataset[mid] > find_num:
return binary_search(dataset[0:mid], find_num)
else:
return binary_search(dataset[mid + 1:], find_num)
else:
if dataset[0] == find_num:
#print("Find it")
return dataset[0]
else:
pass
#print("Cannot find it.")

@cal_time
def binary_search_alex(data_set, val):
return binary_search(data_set, val)

def random_list(n):
result = []
ids = list(range(1001,1001+n))
a1 = ['zhao','qian','sun','li']
a2 = ['li','hao','','']
a3 = ['qiang','guo']
for i in range(n):
age = random.randint(18,60)
id = ids[i]
name = random.choice(a1)+random.choice(a2)+random.choice(a3)

data = list(range(100000000))
print(bin_search(data, 173320))
print(binary_search_alex(data, 173320))

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