Name: Asyncio - コアーチンを使った非同期プログラミング - Pythonプログラミング中級編 p.26 (Asyncio - Asynchronous programming with coroutines - Intermediate Python Programming p.26)
Uploaded: 2021-01-14T10:36:17.000Z
Duration: 28 min 37 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

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And welcome to another intermediate python tutorial.

to 不定詞

In this tutorial, what we're gonna be talking about is a sink io or sink, Yo, depending on which way you want to say it, I won't judge other people will, Uh And what a sink iose for is for a synchronous programming.

And probably the best way to thio kind of understand concurrency.

Um, in basically any programming language is it's often confused with doing something in parallel.

It's kind of like you're handling maybe multiple things in parallel, but you're definitely not doing them.

You're aware of them in parallel, I suppose.

So, for example, like, let's say you're you're out for a jog and you feel like a little tap on your shoe.

Do you have to finish your entire jog to tie your shoe?

I hope not, Right Like that would be That would be unsafe to your very unpleasant and unsafe at the same time.

Eso No, you stop your run, you suspend your run and you bend over entire shoe.

You finish tying your shoe and you get back to your run, okay?

What right to your able to tie your shoe and you're able to run concurrently.

So the same thing is true with programming like, let's say, you got a Web page, and that Web page needs to load a whole bunch of elements.

But, you know, as it's going down the page and it gets to some image that it's requesting from some server, that server just is not responding.

Well, if your pages loading synchronously where your entire Web page will hang.

But if your page loads a synchronously, then the other elements are going to get to load.

And you may or may not ever love that image.

But if it's just taking a long time while you have that Leighton see between the the io had hence a sink, I owe input output.

While you have that delay, you could be doing other things other than just sitting there literally doing nothing and waiting on, um ah, response.

Now, um, what I'd like to do here is, um, just I think we're just gonna start with a really basic function, and then we're gonna turn it into, um ah ko routine.

Um, my first experience with concurrency was actually with go routines and go, and so I just call it co routines.

Anyways, um, let's just say this is the function that we're going to use, So all it is is it's just gonna find some numbers.

And by the way, yes, I'm just I just copy and paste to this function.

Um, e I'll put a link in the description to the text based version, and you can get it.

Grab dysfunction where you can write it as I'm talking if you want.

But basically, the idea of this function is to just in any range we're gonna divide by something.

So, uh, then what we're gonna do when we start the function is we're gonna print out what we're doing.

So anything in that range, that's ah, basically, that's divisible by whatever r div by is, we're gonna add that and then when we're done.

We're gonna have a little thing that says we're done, and it returns.

Whatever we located now to run this, um, I'd probably just put it in a block.

But for the purposes of this tutorial, we're gonna go ahead and we'll use Define.

Um, we'll just have a main main function here, and we'll just say dibs.

And let's just, uh, copy and paste that and that will be just so I match the text based right up.

Let's do 50 8034 1 1133 and then I'm just gonna copy.

Make that 23 uh, 1050 to 30 to 10 and then we'll do 500 three.

Okay, so now we've got our main function here.

And then, um, just for in case someone wanted to import this amazing script of named equals main, we would have just let's just run the main function.

So, um, so with that, you also you know, you can change this function to be anything you want.

You can you can have it doing Ah, Fibonacci stuff.

If you really want to be like everybody or he could do, Um, anything you want.

I will say, if you are interested in doing truly http, eat tasks, you can look into a Iot HDP for doing a synchronous requesting and stuff like that.

So that's why we're not going to use that for this example.

So, uh, now that we have this does want to, um what we want to do is we could even let's just run this real quick.

So as you can see, this whole script runs.

It's about 0.3 seconds, and we can see it runs in the order that we called it.

One it finds it just starts iterating through 508,000 finding all instances where we have a number that is divisible by 34,113.

So it does this one and then it does this one, and then it does, uh, this one.

So what could we do to convert this to be a synchronous?

Well, for example, what if this was instead this right?

It's gonna hang on this one where we actually really could have found the answers to these two and then come back to this one and spent aboutthe same amount of time, right?

We didn't have to waste all this time still waiting on this one, right?

And so So that's kind of what we're trying to solve.

We're trying to figure out a way that we don't need to do this.

And we'd ideally not like to use something like threading or multi processing if we don't have to, because that ads in a whole slew of other things that we might may or may not be interested in dealing with.

So, uh so So at this point, this program is totally synchronised.

And now what we want to do is begin to bring this, uh, Thio, bring a sink.

Io into this summer's gonna bring over the documentation again In the text based version of Suit Auriol.

I do put a Lincoln here, but as you can see, this is a pretty large package.

In my opinion, I always wish in the standard docks they would have like a you know, stupid, simple section, right?

And then you could go through this stuff is that's basically what we have to do every time we find something we have to do.

And then we could maybe come to the docks and see what?

What can we tweak and change and all that, But anyway, there's a whole bunch there for you is basically an a p i over concurrency that you really could use yield from.

You could use the go code routine decorators and stuff like that, and you wouldn't necessarily.

You don't have to use a sink I owe to do concurrency.

It's just it's a very large package to help you do it.

So anyways, getting back to the code, How do we convert something to being a synchronous?

Well, first of all, the main conversion is rather than deaf.

Um, and that basically notifies python A.

So the first step that we're gonna make is actually we're just gonna a sink both of these functions now Uh, the next thing that we want to do is we want to go ahead and bring lips.

We're gonna bring in, um, import a scene guy.

Oh, that way we can use some of these like, helper helper functions, basically with a sink.

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Asyncio - コアーチンを使った非同期プログラミング - Pythonプログラミング中級編 p.26 (Asyncio - Asynchronous programming with coroutines - Intermediate Python Programming p.26)

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