Profiling and optimizing your Python code | Python tricks

[senajoaop]

Had to do a fast and superficial analysis in a very long code. This video made it possible, thanks a lot pal.

[simonbrecher]

Good video, but it is actually quadratic (polynomial), not exponential. Quadratic is n^2, polynomial n^k, where k is a constant and exponential is k^n. n is length of input. You would not be able to do even near 5000 in exponential problem.

[Drahagoon]

Awesome video! Well explained, with a simple, clear and typical hands-on example illustration.
Great work.

[sheikhakbar]

This channel needs a couple of millions subscribers... I always come back to it to learn those marvellous tips and tricks!

[eilonavizemer]

Great video!
here is another, perhaps easier, solution to make this code's complexity linear:
1. lowercase all the movies
2. convert your movie list into a set (sets in python avoid duplicates)
3. convert the set back into a list and return it.

[mervynwinn]

i love the way you say "popping"

[balmittal]

Nice code optimization. specially the last one.

[mstr_rprochowicz]

It helped me a lot in tracking expensive functions that were unnecessary used 2 million times in a loop. Thanks for this useful tutorial!

[MsSuyash]

I came here to get a glimpse of how cProfile module but leaving here impressed with your final solution...
I loved how you combined the zip() function after sorting the list...


And, a great job in illustrating the importance of why profilers are an important tool in a programmer's armamentarium...

[MrAmbarish]

Man your videos are really really helpful! Best explanation of cProfile, profiling and optimization in python. Please keep posting videos...

[legauk]

Awesome video. It was great watching you go step by step through the ode optimization. Your solution for finding duplicates also was very clever and elegant. Worth a subscribe ^.^

[sailalmishra]

Buddy this is Amazing, You should not be on such low subscriber count.. God bless

[AyushMandowara_xx]

This helped me optimize code by about 50-75% depending on the file contents being scanned. Earlier it was consuming about a minute on a large scan, while now it takes about 20 at max. The average speed is reduced to 10secs from 25secs. All I did after analyzing was change my Pandas Series objects (generated from Google Spreadsheets) to tuples (lists would also have the same effect but my data never changes in a single run).
Using cprofiler I could see that Pandas library was consuming loads of resources just to fetch values based on an index number. Thanks a ton!!

[shivan]

In case anyone in the future reads this
I found that this method executes even faster than the method he ended up with.
from collections import Counter

def
return [movie for movie, count in Counter([movie.lower() for movie in read_movies(src)]).items() if count>1]

[sm_smo]

I initially subbed because of your Biological Psychology videos, but I didn't know you're into programming, very useful video!

[prakharchaurasiya]

Finally some optimization that is not too complex. Thanks.

[Julien-hgjh]

15:30 auto corection !
Nice video BTW :D

[vinitkumar]

Great video and explanation. Thanks for sharing this.

[versun]

More more more videos. Yours video is very helpful! Keep going

[ranelpadon]

Good analysis and build up of improvements. Thanks!