"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
"A much better solution than the one in the article, below:
It looks like the ones writing articles here in Javascript do not understand the time/space complexity of javascript methods.
shift, splice, sort, etc... In the solution article you have a shift and a sort being done inside a while, that is, the multiplication of Ns.
My solution, below, iterates through the list once and then sorts it, separately. It´s O(N+Log(N))
class ListNode {
constructor(val = 0, next = null) {
th"
Guilherme F. - "A much better solution than the one in the article, below:
It looks like the ones writing articles here in Javascript do not understand the time/space complexity of javascript methods.
shift, splice, sort, etc... In the solution article you have a shift and a sort being done inside a while, that is, the multiplication of Ns.
My solution, below, iterates through the list once and then sorts it, separately. It´s O(N+Log(N))
class ListNode {
constructor(val = 0, next = null) {
th"See full answer
"The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."
Prashant Y. - "The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."See full answer