Speeding Up Python Code With Caching

That is awesome

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

print([fib(n) for n in range(0, 10000)])
something like that with the cache enables python to bypass the maximum depth recursion

Amazing thanks

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

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

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

Does caching have a negative side?

that's nice!!

🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥🔥

Cool.....

amazing video , just love it.

Cool video!

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

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!

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.

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

great

It was very helpful for me.

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)

april first lol

Thank you so much.

explanation is too clear !!!

helpful

This is awesome! Learned much about it!

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

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?

Thanks

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

Do a video about cython

Nice video

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.

Loved your intro music!





The video as well. You're awesome and unique as always :)

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.

Where can you learn about this caching from first principles?

Search: Emanuel Swedenborg

When recommendation is faster than notification

Pycharm? Vscode pls!

Hello bro can you explain pwntools python library

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

You can increase the recursion limit using sys module

import sys
sys.setrecursionlimit(10**12)

Wieso wieder PyCharm?

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

Awesome as always 👍😀

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

But Pycharm is heavy

And now should i Cache every function?

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

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