Lesson 2 - Data Types and Functions

Learning Objectives

Concepts - After completing this lesson, students will be able to:

• Distinguish between variables and function arguments
• Identify functions that operate on or modify data
• Compare and contrast common scalar and container data types
• Recognize errors resulting from using functions on datatypes that do not have appropriate methods

Skills - After completing this lesson, students will be able to:

• Use a plain text editor (VS Code) to modify source code
• Execute functions on different types of arguments in the julia REPL
• Use print statements and type introspection methods to investigate a data type
• Assign, modify, and copy variables
• Use github and github CI to check answers to homework

Assignments - This lesson is complete when students have:

• Read Chapter 2 and Chapter 3 of Think Julia.
• Cloned the Assignment 2 repository with github classroom.
• Completed assignment 2 with all tests passing.
• Run all code examples from Lesson 2 on their own computers

Data Types

Programming can be thought of as consiting of 2 things:

1. Data
2. Operations on data

Everything else is just sugar.

Before continuing, be sure to read chapter 2 of Think Julia, which introduces you to different kinds of values.

The next section will expect you do have read chapter 3, which introduces you to the operations part (functions).

These chapters also introduce a number of important concepts like variable assignment, expressions, flow of execution, and arguments. All of these concepts will come up again and again, so if you're still a bit fuzzy on them, that's ok.

Practice

The following examples are intended to reinforce and extend what you've learned. In many cases, they are intended to expose behavior that may be unintuitive, or lead to errors that are worth understanding.

julia> 1,000,000
(1, 0, 0)

julia> 1_000_000
1000000

julia> 2^61
2305843009213693952

julia> 2^62
4611686018427387904

julia> 2^63
-9223372036854775808

julia> 2^64
0

Functions

Before continuing, be sure to read chapter 3

Functions are the parts of a program that do things. Without functions, all you have is data. Actually, most of the time if you want data, you need functions too, unless you're writing literally everything by hand.

Recognizing functions

Functions are bits of code that do things. Remember the video from Lesson 1? (seriously, go back and watch it if you didn't before). The kids are providing dad a list of functions.

get(peanut_butter)
get(jelly)
get(toast)
spread(toast, peanut_butter)
spread(toast, jelly)

In julia, it's typically easy to recognize functions because they have the structure:

1. function_name
2. (
3. arguments, separated, by, commas
4. )

So in the expression

julia> println("Hello", " ", "world!")
Hello world!

The function_name is println and there are 3 arguments (in this case, all Strings).

But functions show up in other ways too. All of the math you were doing in the previous section was calling functions. In julia, 1 + 1 is just a convenient syntax^[1] for +(1,1)

julia> +(42,7)
49

julia> *("BISC", "195")
"BISC195"

When you do even simple things like type something in the REPL, there are functions being called to evaluate the expression and print the result.

[Variables, arguments, and scope]@id scope

In chapter 3 of Think Julia, you read that variables and parameters are local to functions.

The more technical way to say that is that the inside of functions have their own "scope"^[2]. This will start to become familiar as you write more code, but it can be confusing at first.

Also potentially confusing is the difference between a variable and an argument. They are similar in various ways, but treating them in the same way, especially naming them the same thing, is an easy way to get yourself confused.

Let's see an example:

function newprint(my_arg)
    println(my_arg, ", students!")
end

newprint("Hello there")

Hello there, students!

This should seem pretty straightforward. The function newprint() takes a single argument, and prints that, appending ", students!". Inside the function, the value passed as an argument - "Hello there" - is passed in everywhere you see my_arg, but my_arg doesn't exist outside the function.

julia> my_arg
ERROR: UndefVarError: my_arg not defined

We could also have passed a variable as the argument.

gb = "Goodbye"

newprint(gb)

Goodbye, students!

Same thing - the variable gb refers to the value "Goodbye", and will be substituted everywhere that my_arg lives in the function.

Let's look at a slightly more confusing example.

some_arg = "Woah"
other_arg = "Huzzah"

function nelly(some_arg)
    println(some_arg, ", Nelly!")
end

nelly(other_arg)

What do you expect? Try it out and see if you're right.

When we call nelly(other_arg), we're passing the value "Huzzah" as the argument. So inside the scope of the function, some_arg is "Huzzah".

What about some_arg outside of the function?

some_arg

"Woah"

Here, we're outside of the function scope, so some_arg is "Woah".

Because of this possibility for confusion, it's usually a good idea to name your function arguments and your variables different things.

Practice

The following examples are intended to reinforce and extend what you've learned. In many cases, they are intended to expose behavior that may be unintuitive, or lead to errors that are worth understanding.

Key Terms