"from collections import deque
def updateword(words, startword, end_word):
if end_word not in words:
return None # Early exit if end_word is not in the dictionary
queue = deque([(start_word, 0)]) # (word, steps)
visited = set([start_word]) # Keep track of visited words
while queue:
word, steps = queue.popleft()
if word == end_word:
return steps # Found the target word, return steps
for i in range(len(word)):
"
叶 路. - "from collections import deque
def updateword(words, startword, end_word):
if end_word not in words:
return None # Early exit if end_word is not in the dictionary
queue = deque([(start_word, 0)]) # (word, steps)
visited = set([start_word]) # Keep track of visited words
while queue:
word, steps = queue.popleft()
if word == end_word:
return steps # Found the target word, return steps
for i in range(len(word)):
"See full answer
"Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach.
Iterative approach (JavaScript)
function reverseLL(head){
if(head === null) return head;
let prv = null;
let next = null;
let cur = head;
while(cur){
next = cur.next; //backup
cur.next = prv;
prv = cur;
cur = next;
}
head = prv;
return head;
}
Recursion Approach (JS)
function reverseLLByRecursion("
Satyam S. - "Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach.
Iterative approach (JavaScript)
function reverseLL(head){
if(head === null) return head;
let prv = null;
let next = null;
let cur = head;
while(cur){
next = cur.next; //backup
cur.next = prv;
prv = cur;
cur = next;
}
head = prv;
return head;
}
Recursion Approach (JS)
function reverseLLByRecursion("See full answer
"public static boolean isPalindrome(String str){
boolean flag = true;
int len = str.length()-1;
int j = len;
for(int i=0;i<=len/2;i++){
if(str.charAt(i)!=str.charAt(j--)){
flag = false;
break;
}
}
return flag;
}"
Sravanthi M. - "public static boolean isPalindrome(String str){
boolean flag = true;
int len = str.length()-1;
int j = len;
for(int i=0;i<=len/2;i++){
if(str.charAt(i)!=str.charAt(j--)){
flag = false;
break;
}
}
return flag;
}"See full answer
"
Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between:
Skipping the current house and taking the maximum money stolen up to the previous house.
Robbing the current house and adding its value to the maximum money stolen up to the house two steps back.
package main
import (
"fmt"
)
// rob function calculates the maximum money a robber can steal
func maxRob(nums []int) int {
ln"
VContaineers - "
Compare alternate houses i.e for each house starting from the third, calculate the maximum money that can be stolen up to that house by choosing between:
Skipping the current house and taking the maximum money stolen up to the previous house.
Robbing the current house and adding its value to the maximum money stolen up to the house two steps back.
package main
import (
"fmt"
)
// rob function calculates the maximum money a robber can steal
func maxRob(nums []int) int {
ln"See full answer
Data Engineer
Data Structures & Algorithms
+4 more
🧠 Want an expert answer to a question? Saving questions lets us know what content to make next.
"We can use dictionary to store cache items so that our read / write operations will be O(1).
Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1)
Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"
Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1).
Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1)
Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer
"Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."
Gaston B. - "Use a representative of each, e.g. sort the string and add it to the value of a hashmap> where we put all the words that belong to the same anagram together."See full answer
"we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"
Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer
"#inplace reversal without inbuilt functions
def reverseString(s):
chars = list(s)
l, r = 0, len(s)-1
while l < r:
chars[l],chars[r] = chars[r],chars[l]
l += 1
r -= 1
reversed = "".join(chars)
return reversed
"
Anonymous Possum - "#inplace reversal without inbuilt functions
def reverseString(s):
chars = list(s)
l, r = 0, len(s)-1
while l < r:
chars[l],chars[r] = chars[r],chars[l]
l += 1
r -= 1
reversed = "".join(chars)
return reversed
"See full answer
"Any cycle would cause the prerequisite to be greater than the course. This passes all the tests:
function canFinish(_numCourses, prerequisites) {
for (const [a, b] of prerequisites) {
if (b > a) return false
}
return true
}
`"
Jeremy D. - "Any cycle would cause the prerequisite to be greater than the course. This passes all the tests:
function canFinish(_numCourses, prerequisites) {
for (const [a, b] of prerequisites) {
if (b > a) return false
}
return true
}
`"See full answer
"this solution here is much faster than the exponent reference soln. It is also far more concise and easy to understand
def moveZerosToEnd(arr: List[int]) -> List[int]:
left = 0
for right in range(len(arr)):
if arr[right] == 0:
pass
else:
if left != right:
temp = arr[left]
arr[left] = arr[right]
arr[right] = temp
left += 1
return arr
`"
Devesh K. - "this solution here is much faster than the exponent reference soln. It is also far more concise and easy to understand
def moveZerosToEnd(arr: List[int]) -> List[int]:
left = 0
for right in range(len(arr)):
if arr[right] == 0:
pass
else:
if left != right:
temp = arr[left]
arr[left] = arr[right]
arr[right] = temp
left += 1
return arr
`"See full answer
"There is a faster approach that solves the problem in O(n) time:
def find_duplicates(arr1, arr2):
arr1 = set(arr1)
res = []
for num in arr2:
if num in arr1:
res.append(num)
return res
`"
Victor H. - "There is a faster approach that solves the problem in O(n) time:
def find_duplicates(arr1, arr2):
arr1 = set(arr1)
res = []
for num in arr2:
if num in arr1:
res.append(num)
return res
`"See full answer
"\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"
Jerry O. - "\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"See full answer