After I made the video, I changed the code in GitHub to use a deque instead of an array for the queue. This allows us to pop the first element in 0(1) time. More here: wiki.python.org/moin/TimeComplexity.
Damn because of your videos, I managed to prepare for the exam tomorrow. I had no idea how I was going to get through so much material in one day, thank you.
Bro, you are a god of explaining and teaching, so quick, so simple, so smart, not like other teachers who sound like broken records and x2 speed you tube videos.
Why do you need "visited" queue? It can still work without it, doesn't it? UPD: just figured out that your algorithm is for general graph, but you apply it to a tree (special case of graph) so "visited" is redundant for tree case.
would be easier if you add what is the front and what is the end of the queue because other examples and other i see the queue is other way. I mean it doesn't matter since i figured it out after a few minutes but i think it would make it easier to understand quickly whats happening lol
what if you have to run more than one search on the same set of nodes? you would have to traverse the entire tree twice to reset your nodes for a single search. with an array you can just clear it. Much easier.
The concept is the same where the abstract data structure is a queue, i.e., FIFO. In the video I used an array and did pop(0), but I later switched the code to use deque and popleft() [same concept as pop(0)] because it's more efficient. See here: github.com/msambol/youtube/blob/master/search/breadth_first_search.py#L17-L19. Let me know if that doesn't make sense!
Confusing how you pop the [0] element yet you show that element as being on the far right of the array order, which would not be the [0] element in actual code...
What happens if the graph in question contains cycles? If we're marking nodes as visited when we pop them, won't that mean there will be multiple instances of a node being enqueued into the queue until they are actually reached and dequeued i.e. marked visited?
You say first in first out like we are supposed to know where you put elements in and out, can't you put them in either at the top or at the bottom? And why do you say vertically and horizontally without showing a tree, the orientation can be different, we have to fast forward to see what tree you have in your mind, but we can't read yours
Hi, the audio is not clear on your videos. It goes on mute in between for a few seconds. Could you please fix this on all your videos. It would be really helpful. Thanks.
you code has issues i think this is the right way for BFS def bfs(graph, node): visited = [] queue = [] visited.append(node) queue.append(node) while queue: s = queue.pop(0) print(s, end=" ") for n in graph[s]: # Corrected indentation if n not in visited: visited.append(n) queue.append(n)
After I made the video, I changed the code in GitHub to use a deque instead of an array for the queue. This allows us to pop the first element in 0(1) time. More here: wiki.python.org/moin/TimeComplexity.
Good video
I love that your slides are so minimalistic, for me it's the perfect amount of content to support what you say
It's good to see that you are back. Your past videos have helped me a lot, thank you.
I have an algorithm test coming up on graphs and this came out at exactly the right time! Thank you!!
Damn because of your videos, I managed to prepare for the exam tomorrow. I had no idea how I was going to get through so much material in one day, thank you.
Wow, you've added so much value in such a short amount of time. Thank you sir!
I was looking for a to-the-point refresher of BFS. This was great. Thanks!
Michael Sambol should take the place of my tenured professor that teaches Algorithms.
Thank you for your quick illustrations! I enjoy your videos a lot.
You are literally saving my life! I’m so glad that you’re uploading again!!
I learned more in 4 minutes than all the 30 years of my life
That is so concise! Perfectly explained!
thanks!
I love your videos so much! Great illustrations, great explanations, many topics, and I can learn something completely new in under 5 minutes!
Thank you!
The Queue in place always go over my head, now with the visualisation it makes it a lot more easier and obvious 😅😅😅
honestly i understand it perfectly in that brief explanation
many thanks to you
Great video. Makes the concept very easy to understand. Thank you for the way you made it.
Best Explanation on youtube so far..Every other video is from 15 to 20 minutes..and here you are doing it in 4 minutes😂
your videos keep me sane i swear
you are literally helping me to survive my exam :) big thanks
such calm voice! Love it
I believe the queue was done in the opposite direction, but overall I learned a lot!
Ive been using recursion in dfs thinking it would work here too
Thank you for helping me realize my mistake
Def easier iteratively for BFS! github.com/msambol/youtube/blob/master/search/breadth_first_search.py
You saved my entire life. Thank you so much.
💪🏼❤️
Clear and straight forward. Thank you.
thank you so much for clear explanation
You deserve more views, thank you for your videos
thank you, so much easier to understand
Bro, you are a god of explaining and teaching, so quick, so simple, so smart, not like other teachers who sound like broken records and x2 speed you tube videos.
Thank you, Marian!
Thanks for your clear explanation
Why do you need "visited" queue? It can still work without it, doesn't it?
UPD: just figured out that your algorithm is for general graph, but you apply it to a tree (special case of graph) so "visited" is redundant for tree case.
very useful and straight to the point, it was useful thanks!
Legit the best explanation out there.
Thank you!
This video is well-explained.Thanks a lot for this ....
Thanks, you literally saved my life.
Dude you are the best, cheers
And what are you searching for in there?
The letter X
This man does not miss 🔥
Thank you for this videos
Love the way you explained the BFS, but is there a way to write the code using recursion?
thank you so much for explaining this in less than 5 min
i love you so much and i hope you live a long happy life
great video my
My lord. Sometimes play back speed 2x just isn't enough
Use revanced there is 5x
Maybe stop watching tik tok so you have an attention span longer than a minute
@@legolorian3271 he does talk pretty slow I won’t lie.
@@legolorian3271 chad
He said first in first out and queue but is demonstrating a last in first out stack data structure.
It's FIFO :)
ty very muchh
Could you please make a video on the Hungarian Method for a bipartite graph, using only the graph? Or is this not a subject you can cover?
I'll add it to my list..
would be easier if you add what is the front and what is the end of the queue because other examples and other i see the queue is other way. I mean it doesn't matter since i figured it out after a few minutes but i think it would make it easier to understand quickly whats happening lol
I should have added that, you're right. Apologies!
@@MichaelSambol no worries just reviewing for algorithms test tomorrow And this really did helped me. Thanks for making these videos!!!
Thank you for the vide! What is the addrd value of the last if statement
Why not make "visited" a property of the node object so you don't have to create a separate 'visited' array?
what if you have to run more than one search on the same set of nodes? you would have to traverse the entire tree twice to reset your nodes for a single search. with an array you can just clear it. Much easier.
Great.
So what is optimal solution of your sample? Path????
Thanks
you mentioned the use of queue, but used a stack with pop function, no?
The concept is the same where the abstract data structure is a queue, i.e., FIFO. In the video I used an array and did pop(0), but I later switched the code to use deque and popleft() [same concept as pop(0)] because it's more efficient. See here: github.com/msambol/youtube/blob/master/search/breadth_first_search.py#L17-L19.
Let me know if that doesn't make sense!
I love you!
Confusing how you pop the [0] element yet you show that element as being on the far right of the array order, which would not be the [0] element in actual code...
Sorry that's confusing! Check the latest code here, I hope it clarifies it: github.com/msambol/dsa/blob/master/search/breadth_first_search.py.
Respect 🫡
🫡
1:31 isn't the que popping 'C' first ?
Muhammad Sumbul 😳😳
What happens if the graph in question contains cycles? If we're marking nodes as visited when we pop them, won't that mean there will be multiple instances of a node being enqueued into the queue until they are actually reached and dequeued i.e. marked visited?
You say first in first out like we are supposed to know where you put elements in and out, can't you put them in either at the top or at the bottom? And why do you say vertically and horizontally without showing a tree, the orientation can be different, we have to fast forward to see what tree you have in your mind, but we can't read yours
Hi, the audio is not clear on your videos. It goes on mute in between for a few seconds. Could you please fix this on all your videos. It would be really helpful. Thanks.
Sorry about that. I'm working on the right settings. Thanks for the feedback.
Is my latest video better, on Fibonacci heaps?
@@MichaelSambol Nope. It isn't any better. Fibonacci heaps also has the same issue.
First
o nanq
you code has issues i think this is the right way for BFS
def bfs(graph, node):
visited = []
queue = []
visited.append(node)
queue.append(node)
while queue:
s = queue.pop(0)
print(s, end=" ")
for n in graph[s]: # Corrected indentation
if n not in visited:
visited.append(n)
queue.append(n)
Definitely a few different ways to do it. See here: github.com/msambol/dsa/blob/master/search/breadth_first_search.py
thank you for your clear explanation
You're welcome!