Programming Terms: Memoization

In this programming terms video, we will be learning the definition of the term memoization. Memoization is a technique of caching results of expensive function calls in order to speed up computer programs when the same input occurs again. Let's take a look at some code examples to get a better understanding of how this works.

The code from this video can be found at:

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[monk_]

Every time I hear "Memoization" I imagine someone saying "Memorization" in a baby voice.

[myles]

My lecturer spent 2 hours trying to explain this to us didn't understand a thing. You done it in 5 and it makes total sense. THANKS!!

[xcxfgpn]

Summary:
Memoization refers to the mechanism that makes a function not having to compute the output using an input, when the function has been executed using the same input before. This is possible because the computer memorizes the input:output pair.


This tool can be demonstrated in python using an if statement and a dictionary outside the function.

[Porous_Dawg]

Awesome. Short, simple, and straight to the point. Thank you.

[corbettknoff]

Whenever I don't understand something and I find a Corey Schafer video I'm always relieved. I know I'm finally going to understand it.

[amr]

Dude you're literally god, I just finished your first class functions, closure, and decorators videos and while watching this I realized how useful it would be to implement memoization using a decorator.

[ryan-tabar]

# You can turn the process into a decorator so you can add it to any function

def
    cache = {}
    def inner_function(arg):
        if arg in cache:
            print(f"Result was retrieved from cache.")
            return cache[arg]
        else:
            print(f"Memoizing result of function
            cache[arg] = original_function(arg)
            return cache[arg]
    return inner_function


@memoization
def square(number):
    return number ** 2

[devworks]

This is the proper video for memoization explained for Python while most use the Fibonacci example

[montywilliams]

been rockin with you for a while now, good content mr chaffer!

[ayizeakono]

All your videos are well organized and delivered....thanks so much for sharing!!!!

[anon-slvp]

another brilliant video :) love learning about programming terms and such... if you could do an advanced playlist of the terms maybe in more detail/other ones would be great :) love learning concepts which like you say are not syntax/prog_lang specific.. act learning the blueprints so to speak of how and why it works

[roy]

Holy Moly! Thanks for that, bro. Really helps me optimized my program!

[monireachtang]

Very clear and easy to understand! Thank you for sharing.

[darshanmm]

Hi Corey
I become your fan!
i never seen anyone teach with such clearity on youtube😊👍

[techfornoobs]

This is an awesome explanation. thank you so much!

[theartist]

A very beautiful playlist ❤️ do more of these please. They're so useful

[ridwankustanto]

very clear and clean explanation, thanks!!!

[davidm.johnston]

I love you man, your videos are just so useful and easy to understand. Thanks

[samwilliams]

Huge fan of your videos Corey!


The functools.lru_cache decorator is also a great way to implement memoization on functions.

[Leonardo-jvls]

When I have a doubt about anything in this world, i go to youtube and write "corey schafer +anything". If not found, i quit of learning it.