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This lesson will introduce you to one of the cornerstones of programming, namely functions. Functions
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go by many names and other programming languages functions have been called subroutines, methods procedures,
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but don't let the jargon get to you.
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The central idea is always the same. In Shakespeare's Romeo and Juliet,
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Juliet famously said "A rose by any other name would smell just as sweet".
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At the time she was talking about Romeo.
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But had she been a programmer, I'm sure she would have said the same thing about functions. And on that
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note,
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I hope you're ready to start your love affair with functions.
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Our goal in this lesson is to explain exactly what's going on with a line of Python code like this  - show,
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followed by the parentheses.
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We're gonna be focusing on the part after the dot.
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That way, we can break down the programming concepts of functions into bite sized lessons and build up
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to the big picture.
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As such,
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this lesson really sets up the next couple of lessons on arguments, return values and on objects, so
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you can think of these videos like a combo - like bread and butter, or burgers and fries or a jab and a cross,
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or Coca-Cola and Mentos.
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You get the point.
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So what's so great about functions?
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Well, imagine I'm your little housekeeping robot because, I don't know, you didn't want to buy a Roomba or
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something. And if I was a human you could tell me "Hey, go and buy me some milk".
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That instruction would make sense to a human.
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A human would understand what to do in order to complete this task.
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However, when we're giving instructions to a robot, it doesn't quite work like that. A robot doesn't know
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what getting milk involves, especially if you've bought the base model with no machine learning capabilities.
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So when you're dealing with a robot, you have to specify every single step of this task, like taking the
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money, opening the door, closing the door, walking to the store etc etc etc. You have to specify every
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single instruction.
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Now, come the next day and you need to get more milk.
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Well, you have to specify all these instructions again and that would be incredibly annoying and you'd
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probably bin your housekeeping robot in short order.
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Here's where functions come to the rescue. With a function you can bundle all these individual instructions
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into a single instruction, and we can also give this function a descriptive name like get_milk.
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Now, every time we want to use get_milk,
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the housekeeping robot knows exactly what to do.
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It will execute all the instructions contained inside this function.
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So there's something to note here - what we just described is actually a two step process.
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First - you have to tell the robot what get_milk means, and second - you have to tell the robot to execute
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this get_milk instruction.
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In other words, step 1 is defining or declaring the function and step 2 is using or calling the function.
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The syntax looks like this - when defining the function you'll always see this keyword - def.
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Def followed by the name of the function, followed by parentheses, followed by a colon. After the colon,
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on the lines below,
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you have the instructions inside the function.
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This group of statements is going to be indented and the indentation tells us what statements are inside
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of the function.
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Now there's actual words for the anatomy of a function.
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While you and I have got a head and a body a function has got a header and a body - and the header is
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this line right. It's the line with the def keyword at the top, and the body are all the statements, all
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the instructions that are inside the function.
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Basically, all the lines that are indented. That's the body.
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Now let's take another look at this line of code where it says plt.show(). The parentheses
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at the end are telling us that show is a very different beast from math.pi, or 
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hitchikersGuide.theAnswer.
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And that's because show is a function, because it had these parentheses at the end.
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Now there's no parentheses after a math.pi, and there's no parentheses after 
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hitchikersGuide.theAnswer.
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These two are not functions.
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So now that we know a little bit about what a function is supposed to look like, let's create our own
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first function. Scrolling to the bottom of our Python intro notebook,
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we can write def get_milk, and then parentheses followed by a colon and when we hit Enter
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we'll get taken to the next line which is indented and here we can print out some instructions like
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"Open door", and then we can hit Enter again,
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get taken to the next line which again is indented and follow up with some more instructions that
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are going to go inside the function, like print("Walk to the store"), and then print("Buy milk on the ground
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floor")
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And we'll finish it up with printing
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"Return
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with milk galore".
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So in our function body, we have for individual print statements.
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Notice that when you hit Enter on your keyboard Jupyter notebook already indents these lines for you
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and we have an indentation of one, two, three, four spaces. In Python,
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this indentation or whitespace actually matters quite a bit. Indentation in Python,
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is like a full stop at the end of an English sentence. Just like the full stop at the end of the sentence,
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the whitespace helps Python determine where one instruction ends and another one begins.
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Now, just like Jupyter notebook has shown us, you also want to have four spaces between the beginning
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of a line and the first print statement.
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Usually, the text editor that you're working in, or Jupyter notebook in this case, will help you indent
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this correctly for you.
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Let's hit Shift+Enter on the cell and see what happens.
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Nothing, right?
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Nothing at all.
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And that's because we've only defined the function - we actually haven't executed it yet.
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Remember how we were talking about the two step process?
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Let's call the get_milk
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function now.
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With me write get_milk() and hit Shift+Enter.
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Now I'm noticing that I made a typo, so let's fix this.
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Gonna hit Shift+Enter again and execute this function again.
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Okay, that was really bothering me.
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Below the cell where we're calling the function, where we wrote get_milk()
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we see the four statements from the function being printed out.
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The other thing I quite like about Jupyter notebook is that the syntax highlighting here actually helps
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us differentiate visually and see at first glance on which part we're defining the function and on which
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part we're calling the function. The part where we're defining the function the function name is highlighted
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in blue, and the part where we're calling the function,
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it's regular black Python code.
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Now let's take it up a step in complexity in the next lesson.