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一.无序表查找def sequential_search(lis, key):
for i in lis:
if i == key:
return lis.index(i)
else:
continue
else:
return False
if __name__ == '__main__':
LIST = [1, 5, 8, 123, 22, 54, 7, 99, 300, 222]
result = sequential_search(LIST,1231)
print(result)
二.有序表查找1.二分查找(Binary Search)
def binary_search(lis,key):
low = 0
high = len(lis) - 1
time = 0
while low < high:
time += 1
mid = int((low + high)/2)
if key < lis[mid]:
high = mid - 1
elif key > lis[mid]:
low = mid + 1
else:
print("times: %s" % time)
return mid
print("times: %s" % time)
return False
if __name__ == '__main__':
LIST = [1, 5, 7, 8, 22, 54, 99, 123, 200, 222, 444]
result = binary_search(LIST,99)
print(result)
2. 插值查找
二分查找法虽然已经很不错了，但还有可以优化的地方。有的时候，对半过滤还不够狠，要是每次都排除十分之九的数据岂不是更好？选择这个值就是关键问题，插值的意义就是：以更快的速度进行缩减。插值的核心就是使用公式：value = (key – list[low])/(list[high] – list[low])
用这个value来代替二分查找中的1/2
def binary_search(lis, key):
low = 0
high = len(lis) - 1
time = 0
while low < high:
time += 1
# 计算mid值是插值算法的核心代码
mid = low + int((high - low) * (key - lis[low]) / (lis[high] - lis[low]))
print("mid=%s, low=%s, high=%s" % (mid, low, high))
if key < lis[mid]:
high = mid - 1
elif key > lis[mid]:
low = mid + 1
else:
# 打印查找的次数
print("times: %s" % time)
return mid
print("times: %s" % time)
return False
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本文转自小白的希望 51CTO博客，原文链接：http://blog.51cto.com/haoyonghui/2055623，如需转载请自行联系原作者