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Hi guys and welcome back.

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In this video, we're going to start learning

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about decorators.

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Decorators are great in Python

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because they allow us to very easily modify functions.

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So let's learn more about them.

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Here we've got a user dictionary that has a username and

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an access level of guest.

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Let's say that guests can't access this function here

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get_admin_password

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which returns the password to your admin panel.

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But as you can see,

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if we print out get_admin_password

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at the moment, even though we're a guest

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we're gonna get out 1234.

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There's nothing in this function

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to prevent us from doing that.

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So, the output of this video should be

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to get this function secured so that

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people that are guests cannot get the value out.

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Now of course, the clear thing that you can do

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is to put an if statement in here.

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If the user's access level is == to admin,

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then you can print out this function.

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Otherwise, you can't.

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So this will work

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if you run that, you don't get anything,

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but of course as you know,

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get_admin_password is still un-secure

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so you can still print that out

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and it'll still work.

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Because what we've done is

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we have protected this specific call to get_admin_password,

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but we haven't protected this one.

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So, this is probably not exactly what we want to do.

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The next thing we can do

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is we can define a secure function.

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For example, secure_get_admin.

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And in this one, if the user's access level is admin

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then we can return the password 1234.

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Now, a couple of things.

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Clearly get_admin_password is still defined,

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so that is not going to work,

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but secure_get_admin does protect the password.

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Running that gives you None, first of all

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when you run secure_get_admin

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because we didn't return 1234.

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Instead, we returned None which is a default.

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Then you get 1234 the next time around.

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So of course, what you may want to do

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is delete this one entirely.

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But, that poses a small problem.

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Which is that all the functions

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where you want it to be secure,

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you're going to have to add this if statement.

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And up 'til now, that is what you would have done

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if you didn't know about decorators.

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But, a decorator will allow us to modify this function

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to secure it without having to replace

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all of our functions by its secure counterparts.

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So, we don't want to do that either.

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Instead what we could do

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is define another function, secure_function

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that takes in a function.

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We've learned about first class functions,

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so we can take it in as a function there,

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and we'll say if the user's access level is == to admin

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then we will return func.

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Otherwise we'll return none.

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And now what you may be tempted to do

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is to do something like

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get_admin_password = secure function(get_admin_password).

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So, will this work?

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Well, let's run through the code.

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We've got secure_function being called

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which takes in get_admin_password,

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and when this line runs,

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we're going to check the user's access level

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and see if it's admin.

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And if it is, we're going to return func.

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So, let's see what happens.

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Now you get an error.

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NoneType object is not callable.

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Because of course, when we ran this code

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i.e., this line here,

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the user's access level was guest not admin.

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So we didn't return func,

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we returned none which is the default.

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So get_admin_password = none.

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Then we're trying to run none as if it were a function,

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but you can't do that so you get an error.

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What you would have to do is

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make sure that your user is an admin

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before you run any of your code.

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And then it will work and you will get 1234.

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So this is a step closer to what we want,

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but alas it requires that our user be an admin

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before we secure our functions.

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Ideally we would like to do something that checks

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the user's access level when you call the function,

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not when you define it.

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So, here's what we're gonna do.

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We're still going to take in a function

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but now we're going to define another function,

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which I'm going to call secure_function.

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This one I'm gonna call make_secure.

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This one doesn't take any parameters,

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and it is the one that checks.

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And, it returns calling the original function.

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Then, here we return secure_function.

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So this is a decorator.

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What happens now, and by the way

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this should be make_secure.

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What happens now is that get_admin_password,

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this function that we want to secure,

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is passed to the make_secure function.

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This one defines another function,

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and by the way, in Python you can define functions

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inside a function, so that's totally fine.

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And this function here, when called,

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will check the user's access level

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and return calling the original function

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which is get_admin_password.

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So it will return 1234 if the user's access level is admin.

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So that's this function here,

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and then we return the function itself.

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Not the function call, but the function itself.

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get_admin_password will be equal to this function.

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Which calls seemingly itself, but this is okay.

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It calls get_admin_password from up here.

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So when you call get_admin_password what you're gonna do

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is you're going to check the user's access level,

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and then you're going to return the result

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of calling the function originally,

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which will give you 1234.

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At the moment you get none, but of course if you

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set the user's access level to admin down here

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and you run it again,

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then you get 1234.

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Which is exactly what we wanted.

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So this is a simple decorator.

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This simple decorator will create a function

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and replace the original function with this secure one.

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So that you can no longer call get_admin_password

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without having the admin access level.

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Now if you wanted to add a little bit of error handling

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you can do an else here

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and you can return something like

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"No admin permissions for {user['username']}."

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and that'll give you a nicer idea of what's going on

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if you don't have admin permissions.

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That's everything for this video.

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This is a simple decorator,

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and now in the next one we're going to learn more

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about using the @ syntax for decorators

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that makes this much simpler, and much easier

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to re-use and secure multiple functions

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if that's what you want to do.

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Thanks for joining me,

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and I'll see you in the next video.