Speeding Up Python Code With Caching 

ahh... lemme cache my hello world program now

More of this content please !! actual real life use-full things thank you for the hard-work

I just found out that the cache decorator was added in Python version 3.9, so those who are in a previous version have to use lru_cache instead.

You can increase the recursion limit using sys module import sys sys.setrecursionlimit(10**12)

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When recommendation is faster than notification

When I saw it I just hoped that it wasn’t an april fools

my python 3.9 functools dont have @cache anymore i think , i get an error whereas @lru_cache works

Me: "How do I do caching in python... I bet there's a module for this." NeuralNine: "yeah 'from functools import cache' " Perfect video, it's rare that you get the exact answer you are looking for with a walk through right away. I love the future!

for me it isnt working. with cache and without cache always shows same time idk why

Thank you for this sir! (Watching from Philippines)

this cache is similar to the idea of dynamic - save some part of the result

I had already tried to import cache from functool in google colab but it got an error, do you know why this happens? So instead i import Cache from cache-decorator

explanation is too clear !!!

Pycharm? Vscode pls!

Ok, so if I have a pyinstaller .exe onefile, will cache speed that up too?

Why did time.time() function is useless for results under one seconds ? In fact, executing code is happening in microseconds and milliseconds.

Thank youuuu

Caching data basically means you're decreasing the amount of calculations you need to do by optimizing the process through which the calculations are done. But heres what im confused about. Why does caching make it THAT much faster? Here you're decreasing the number of calculations u need to do by half (or is that more than half) so why is it so significantly faster Found my answer. The decrease in calculations is significantly more than half. The Fibonacci sequence is super unoptimized

Thank u, and is there anyway u could make a video on Cython, Numba, or any other library helping speed ups?

That is awesome

When caching is used in calculations like this the technique is often called 'memoization'. Also quite handy when writing a prime factor sieve. Love the channel. Long live human 2.0. Go SpaceX.

Awesome as always 👍😀

Amazing thanks

🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥

This is awesome! Learned much about it!

awesome toturial, thanks. but can we know how the cache function acts or not, and can we write a normal function acts like a built-in cache function.

Where can you learn about this caching from first principles?

april first lol

amazing video and content. Straight to the point.

Hello bro can you explain pwntools python library

Cool.....

Does caching have a negative side?

amazing video , just love it.

can you help me 🤦‍♀🚨🚨 TypeError: unhashable type: 'numpy.ndarray'

Actually learned so much from this. Decorators finally make sense and I found a way to speed up my python programs

It was very helpful for me.

But Pycharm is heavy

Do a video about cython

And now should i Cache every function?

Wieso wieder PyCharm?

Good better and best

Loved your intro music! The video as well. You're awesome and unique as always :)

Thank you so much.

that's nice!!

Cool video!

Nice video

Thanks

great

helpful

YES

2nd

when i am working with classes and "@property" can i use the "@cache" too???

1st

Might've been useful to show how to implement caching like that instead of just importing

Where have I seen this video before...? You copied that from someone right?

Hi bro, Thanks for tutorial. but I have problem for this: from functools import cache when I run my code give me error: ImportError: cannot import name 'cache' from 'functools' (/usr/lib/python3.8/functools.py)