数据结构-学习笔记-查找

顺序查找

• 时间复杂度 O(n)

import random

def Linear_search(li,val):
    for index,v in enumerate(li):
        if v == val:
            return index
        
li = list(range(10))
val = 3
random.shuffle(li)  # 打乱顺序
print(li)
Linear_search(li,val)

# [4, 3, 7, 2, 8, 6, 1, 9, 5, 0]
# 1

二分查找

• 时间复杂度 O(logn)
• 必须先排好序
  

def Binear_search(li,val):
    left = 0
    right = len(li) - 1
    while left <= right:
        mid = (right+left)//2
        if li[mid] == val:
            return mid
        elif li[mid] > val:
            right = mid -1
        else:
            left = mid + 1
            
li = list(range(10))
val = 3
random.shuffle(li)
print(li)
Linear_search(li,val)

# [2, 6, 5, 3, 7, 0, 4, 9, 8, 1]
# 3

比较线性查找和二分查找效率

# 封装一个计算时间的函数
import time 

def cal_time(func):
    def warpper(*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 warpper

@cal_time #修饰函数
def Linear_search(li,val):
    for index,v in enumerate(li):
        if v == val:
            return index

@cal_time
def Binear_search(li,val):
    left = 0
    right = len(li) - 1
    while left <= right:
        mid = (right+left)//2
        if li[mid] == val:
            return mid
        elif li[mid] > val:
            right = mid -1
        else:
            left = mid + 1

li = list(range(100000))
val = 3600
random.shuffle(li)
Linear_search(li,val)
Binear_search(li,val)

# Linear_search running time: 0.12470626831054688 secs.
# Binear_search running time: 0.0 secs.