You're NOT Managing Your Memory Properly | Python Generators (Yield)

How using Python generators (aka the yield statement) can be advantageous to program design and memory efficiency and management.

0:00 - Introduction
0:25 - Lists
2:51 - Generators
5:47 - Rolling Returns
8:00 - Outro

[adityashukla]

Wow. I was just studying generators, but was finding it slightly difficult and unnecessary. Now I understand it's importance. Thank you for this video 🙏🏼

[areniyan]

1:59 the graph here actually confuses the viewer: in the first example memory consumption of the whole loop grows quadratically and in the second it grows linearly (like the graph shows for the first one). sys.getsizeof returns linearly growing size because list type stores only references to its values, but the strings themselves also grow linearly, which gives an overall consumption of O(n^2) in the first case

[CaseyFahey]

New subscriber, like your content, REALLY like that you just jump right into it. I think creators sometimes forget that minutes wasted really add up over time, thank you for wasting no time!

[domenicfieldhouse]

This is one of the cleanest edited videos I've seen, and great info

[re.liable]

And if for some reason you want to see all of the content to be generated, you can just cast it to a list e.g. list(your_generator) or [*your_generator]

[williamrich]

Excellent clear and conscise. Looking forward to more content!

[abhishekchoudhury]

Love the video, @DanielBoctor. Would love to see videos on advanced Django!

[TheControlMastr]

Your videos make me want to learn Python all over again 😮 amazing video!

[Darkev]

Very practical insights, thanks a lot for this

[anon_y_mousse]

Okay, so basically, don't process or generate data before you really need to. Good message, just needs some more real world examples.

[darshanrajpattanaik]

Ery informative video... What are your thoughts about using it when using to
(i) receive api get requests followed by a loop on the response data
(ii) to sort the data without using it in any loop?

[Simple_Simon_UK]

Is there an equivalent to Generators in Cobol-72?

Only joking.

Compilers are wonderful things. Their enrichment of capabilities are opening up opportunities beyond our wildest dreams.

[fire]

I almost always use yield generators ! Mostly because it's faster lazyier processing, for better speed performance, and or asynchronousity manipulation. But it's wonderful to see such a clear example of how this is also memory efficient and a must for big data processing.

Thanks for the regular bracket trick! (ftw) didnt know about that! Love this channel! Love python! Subscribed! All the best

[tunafllsh]

In case of list comprehension vs generator, most of the time list comprehension is much faster. If you don't have memory issue and have constant size elements, the speed is worth it.

So in rolling returns, it is fine to use lists for windows and it would be much faster.

[john.dough.]

it seems like you're using the word "residual" to mean "minuscule".

Given that "residual" means "remaining after the greater part or quantity has gone.", I'm not quite clear what greater part of the function's memory you'd be referring to.

[seasong]

Pretty funny how your generator can be using a other generator