1-5LeetCode:Python解题
Posted Joe-Han
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1. Two Sum【Easy】
Given an array of integers, return indices of the two numbers such that they add up to a specific target.
You may assume that each input would have exactly one solution, and you may not use the same element twice.
Example:
Given nums = [2, 7, 11, 15], target = 9,
Because nums[0] + nums[1] = 2 + 7 = 9,
return [0, 1].
Solution:
class Solution(object):
def twoSum(self, nums, target):
"""
:type nums: List[int]
:type target: int
:rtype: List[int]
"""
num_map =
for i in range(len(nums)):
result = target - nums[i]
if result in num_map:
return [num_map[result],i]
num_map[nums[i]] = i
Discussion:
使用字典,key是差,value是index。比如例子中的[2,7,11,15],target是9。那么在2的时候就存入7:0,下一位找到7的时候,之前有个差值是7,那么就返回7对应的index,0,以及当前这个7的index,就是1。算法时间复杂度为O(n)
2. Add Two Numbers【Medium】
You are given two non-empty linked lists representing two non-negative integers. The digits are stored in reverse order and each of their nodes contain a single digit. Add the two numbers and return it as a linked list.
You may assume the two numbers do not contain any leading zero, except the number 0 itself.
Input: (2 -> 4 -> 3) + (5 -> 6 -> 4),Output: 7 -> 0 -> 8
Solution:
# Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution(object):
def addTwoNumbers(self, l1, l2):
"""
:type l1: ListNode
:type l2: ListNode
:rtype: ListNode
"""
head = p = ListNode(0)
carry = 0
while l1 or l2 or carry:
if l1:
carry += l1.val
l1 = l1.next
if l2:
carry += l2.val
l2 = l2.next
carry, val = divmod(carry, 10)
p.next = p = ListNode(val)
return head.next
3. Longest Substring Without Repeating Characters【Medium】
Given a string, find the length of the longest substring without repeating characters.
Examples:
Given “abcabcbb”, the answer is “abc”, which the length is 3.
Given “bbbbb”, the answer is “b”, with the length of 1.
Given “pwwkew”, the answer is “wke”, with the length of 3. Note that the answer must be a substring, “pwke” is a subsequence and not a substring.
Solution:
class Solution(object):
def lengthOfLongestSubstring(self, s):
"""
:type s: str
:rtype: int
"""
start = maxlen = 0
dic =
lens= len(s)
for i in range(lens):
if start + maxlen >= lens:
return maxlen
if s[i] in dic and start <= dic[s[i]]:
start = dic[s[i]]+1
else:
maxlen = max(maxlen, i - start +1)
dic[s[i]] = i
return maxlen
Discussion:
声明一个变量start,记录初始索引,一个变量mxlen记录最大长度,然后遍历字串中字符,用字典dic记录该字符和其对应的索引index,若该字符串出现在dic中,且索引位置不小于start,那么将index 减去 start当做该不同字符子串的长度,并与maxlen比较取其大者。否则将start后移,最后更新dic
4. Median of Two Sorted Arrays【Hard】
There are two sorted arrays nums1 and nums2 of size m and n respectively.
Find the median of the two sorted arrays. The overall run time complexity should be O(log (m+n)).
Examples:
nums1 = [1, 3]
nums2 = [2]
The median is 2.0
nums1 = [1, 2]
nums2 = [3, 4]
The median is (2 + 3)/2 = 2.5
Solution:
class Solution(object):
def findMedianSortedArrays(self, nums1, nums2):
"""
:type nums1: List[int]
:type nums2: List[int]
:rtype: float
"""
result = []
i = j = 0
len1, len2 = len(nums1),len(nums2)
while i <len1 and j < len2:
if nums1[i] <= nums2[j]:
result.append(nums1[i])
i += 1
else:
result.append(nums2[j])
j += 1
if j < len2:
result.extend(nums2[j:])
elif i < len1:
result.extend(nums1[i:])
mid = (len1+len2) / 2
if (len1+len2) % 2:
return result[mid]
else:
return (result[mid]+result[mid-1])/2.0
Discussion:
合并两个有序链表,并分奇偶情况得到中间值;另一种思路是分别将nums1和nums2划分成left和right,使得len(left)=len(right)且max(left)<= min(right)。
https://discuss.leetcode.com/topic/4996/share-my-o-log-min-m-n-solution-with-explanation
5. Longest Palindromic Substring【Medium】
Given a string s, find the longest palindromic substring in s. You may assume that the maximum length of s is 1000.
Examples:
Input: "babad"
Output: "bab"
Note: "aba" is also a valid answer.
Input: "cbbd"
Output: "bb"
Solution:
class Solution(object):
def __init__(self):
self.maxlen = 1
self.index = 0
def extendPalindrome(self, start, end, s, lens):
while start >=0 and end < lens and s[start] == s[end]:
start -=1
end += 1
if self.maxlen < end - start - 1:
self.maxlen = end - start - 1
self.index = start +1
def longestPalindrome(self, s):
"""
:type s: str
:rtype: str
"""
lens = len(s)
if lens < 2 :
return s
for i in range(lens-1):
# if i*2 +1 > self.maxlen and (lens - i - 1)*2 + 1 > self.maxlen:
self.extendPalindrome(i, i, s, lens)
# if i*2 +2> self.maxlen and (lens - i - 1)*2 + 2 > self.maxlen:
self.extendPalindrome(i, i+1, s, lens)
return s[self.index : self.index + self.maxlen]
Discussion:
主要有两种思路,思路一:动态规划,S[i~j] 是回文的条件是S[i]=S[j]且S[i+1~j-1]是回文,基本思路是外层循环i从后往前扫,内层循环j从i当前字符扫到结尾处。过程中使用的历史信息是从i+1到n之间的任意子串是否是回文已经被记录下来。思路二:遍历字符串,以每个字符为中心往两边扩张,直到不是回文串为止(主要区分奇偶,即“aabaa”和“abba”)。
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