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The next part of the syntax that might be unfamiliar is this @ sign and

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something that comes after the @ sign. Now we sort of know what it does.

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It's basically saying when the user hits up this path

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which is what's called the home route, basically when you go to a website,

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for example, www.google.com

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and you go to the first forward slash well, that is going to be the home.

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And it knows that when you go there you want to see the home page.

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So that's effectively what we're saying here.

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When the user navigates to our URL with just a forward slash they want to see

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the homepage and so we're going to show them hello world.

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But what is this syntax exactly? Well,

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this is code a Python decorator

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and this is something that you'll see in more advanced Python projects.

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So what exactly is a decorator? Well,

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let's imagine that you have a bunch of functions in your class or in your

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module

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and you want to add some functionality to each of these functions. Well then you

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might use a decorator function to do that.

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Essentially you can think of a decorator function as a function

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that's going to give additional functionality to an existing function. In order

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to really understand this,

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we have to understand a couple of other concepts as well.

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So I'm going to do a couple of demos in this Repl.it

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and if you head to this URL or find it in the course resources,

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you'll be able to see all the code that I've written in this file.

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So a long time ago,

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we learned about Python functions and we know that a function allows us to

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have specific packages of functionality,

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allows us to add inputs, to increase the reusability of the function,

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and also allows us to get outputs from the function which we can pass into

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another function or do something with it. As an example,

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we've got four very simple functions, add, subtract, multiply,

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and divide that uses all three components of a function.

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Now, what if we wanted to get a little bit fancier? Well,

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one of the things about Python functions is that they are known as first-class

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objects,

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which basically means that you can pass a function around as an argument,

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just like what you could do with an integer, a string or a float, it's treated

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identically.

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That means we can take these functions and we can build another function that

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uses these functions. Let's say I create a calculate function

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which takes a calc_function

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and then the n1 and n2.

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Inside this calculate function,

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I'm going to call the function that was passed in and give it the values

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n1 and n2 that was also passed in.

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So now when I call the calculate function,

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I'm going to pass in the name of one of these functions and then some numbers.

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Those numbers are gonna become the input for this specified function

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and then we're going to return the result of that calculation.

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So now lower down,

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I can call my calculate function, pass in the name of a function

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so for example our multiply function, and then pass in some numbers,

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for example, two and three. Now let the output that's returned

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be our results

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and let's go ahead and print this result. And you can see we get six.

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So basically it has now multiplied two by three. Now,

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if I change this to one of the other functions, add,

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and I run this again, you can see instead of six, I'm now getting five.

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The ability for us to treat functions as first-class objects basically means

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that we can pass them around as if they were just any other argument

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like a number or a string or a floating point number.

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And then later we can activate them by adding the brackets around them and then

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any necessary inputs. Now, the next concept

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which you might've come across

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but we haven't really used it a lot is the concept of nested functions.

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Functions can also be nested inside other functions.

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For example, if I create a function called outer_function

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and this function is just going to print and say,

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I'm outer. Now inside this outer_function,

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I could create another function. So notice the indentation here

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means that this function is now created inside this function and I'll call it

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the nested_function.

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So this function is simply going to print I'm

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inner.

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And now we have the problem of trying to call this function. Now,

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because this function was declared inside this function,

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its scope means that it's only accessible inside the confines of this function.

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So if we were to go outside of the function, so by

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indenting back to the beginning and we try to call this nested function,

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then it's actually not going to work.

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We're going to get a name error. It's not defined. However,

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if we call this function inside this outer_function,

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then it will now no longer generate an error.

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So let's go ahead and trigger the outer_function by calling it in our main.

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py. And when I run this, you can see it says I'm outer

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and then it says I'm inner.

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So this first gets executed and then this. And this I'm inner is being

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printed when this line is being evaluated. Now,

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one of the other things you could do is you can actually return a function from

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another function.

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Right.

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Functions can actually be returned from other functions.

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So if I make a copy of this previous function right here and comment out this

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other function and all the steps before,

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...

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and we only have this bit of active code,

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then you can see that instead of calling this nested_function here,

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I could also return it as the output.

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But the important part here is I'm going to get rid of the parentheses

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which means I'm no longer activating that function right here.

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So now when I call this outer_function,

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the output that this line is going to evaluate to is going to become the nested_

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function. So you could almost store it inside a variable.

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So let's say I create a variable called inner_function

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which is equal to the output of the outer_function

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which is basically this nested_function that's being returned. Well

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then, not only can I trigger the outer_function

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which is just going to give me I'm outer,

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now I can also trigger the inner_function separately by calling it

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and then adding the activator which is the parentheses.

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So now it says I'm outer after it evaluates this line,

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I'm inner after it evaluates this line. Now,

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if this is confusing to you,

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I recommend heading over to the course resources where I've got a link to this

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Python Tutor where I've entered all the code that we've seen just now

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and we can execute this code line by line.

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So you can see that the first thing that happens is it looks at this outer_

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function and it creates a reference to that function. Now

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next, it's on this line where our outer_function is actually being executed

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because it has the parentheses at the end.

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So now it's actually going to go inside this outer function and go through it

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line by line where it prints I'm outer and then sets up a reference to this second

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function, which is the nested_function.

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The nested_function can now be called by its name

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which is nested_function. But the very end of the outer_function,

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that function is going to be the return value. So it's going to be outputted.

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Finally,

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we get to the end of this line nine and we set up a reference from this variable

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called inner_function to this nested_function. And finally,

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when we get to the line 10 we trigger that function.

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So here is our inner_function which points to this nested function

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and so when we trigger this inner_function,

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it's the same as triggering the nested_function.

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And that is when we end up going into this function

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and printing out what it says inside.

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Have a play around with that to fully get to grips with all the things that you

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can do with a function.

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And once you're happy with all of this and you've reviewed it and you understand

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everything that's going on,

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then you've got the foundations to head over to the next lesson where we're

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going to talk about Python decorators.