This actually could use a bit of stating in words, imo. And I don't feel like we need to repeat the function so close to the original code containing it.
6.2 KiB
Structs
struct
s, short for "structures", give us the ability to name and package
together multiple related values that make up a meaningful group. If you come
from an object-oriented language, struct
s are like an object's data
attributes. structs
, along with enum
s that we talked about in the last
chapter, are the building blocks you can use in Rust to create new types in
your program's domain in order to take full advantage of Rust's compile-time
type checking.
Let’s write a program which calculates the distance between two points.
We’ll start off with single variable bindings, and then refactor it to
use struct
s instead.
Let’s make a new project with Cargo:
$ cargo new --bin points
$ cd points
Here’s a short program which calculates the distance between two points. Put
it into your src/main.rs
:
fn main() {
let x1 = 0.0;
let y1 = 5.0;
let x2 = 12.0;
let y2 = 0.0;
let answer = distance(x1, y1, x2, y2);
println!("Point 1: ({}, {})", x1, y1);
println!("Point 2: ({}, {})", x2, y2);
println!("Distance: {}", answer);
}
fn distance(x1: f64, y1: f64, x2: f64, y2: f64) -> f64 {
let x_squared = f64::powi(x2 - x1, 2);
let y_squared = f64::powi(y2 - y1, 2);
f64::sqrt(x_squared + y_squared)
}
Let's try running this program with cargo run
:
$ cargo run
Compiling points v0.1.0 (file:///projects/points)
Running `target/debug/points`
Point 1: (0, 5)
Point 2: (12, 0)
Distance: 13
Let's take a quick look at distance()
before we move forward. To find the
distance between two points, we can use the Pythagorean Theorem. The theorem is
named after Pythagoras, who was the first person to mathematically prove this
formula. The details aren't that important; just know the theorem says that the
formula for the distance between two points is equal to:
- squaring the distance between the points horizontally (the "x" direction)
- squaring the distance between the points vertically (the "y" direction)
- adding those together
- and taking the square root of that.
So that's what we're implementing here.
f64::powi(2.0, 3)
The double colon (::
) here is a namespace operator. We haven’t talked about
modules yet, but you can think of the powi()
function as being scoped inside
of another name. In this case, the name is f64
, the same as the type. The
powi()
function takes two arguments: the first is a number, and the second is
the power that it raises that number to. In this case, the second number is an
integer, hence the ‘i’ in its name. Similarly, sqrt()
is a function under the
f64
module, which takes the square root of its argument.
Why struct
s?
Our little program is okay, but we can do better. The key is in the signature
of distance()
:
fn distance(x1: f64, y1: f64, x2: f64, y2: f64) -> f64 {
The distance function is supposed to calculate the distance between two points.
But our distance function calculates some distance between four numbers. The
first two and last two arguments are related, but that’s not expressed anywhere
in our program itself. We need a way to group (x1, y1)
and (x2, y2)
together.
We’ve already discussed one way to do that: tuples. Here’s a version of our program which uses tuples:
fn main() {
let p1 = (0.0, 5.0);
let p2 = (12.0, 0.0);
let answer = distance(p1, p2);
println!("Point 1: {:?}", p1);
println!("Point 2: {:?}", p2);
println!("Distance: {}", answer);
}
fn distance(p1: (f64, f64), p2: (f64, f64)) -> f64 {
let x_squared = f64::powi(p2.0 - p1.0, 2);
let y_squared = f64::powi(p2.1 - p1.1, 2);
f64::sqrt(x_squared + y_squared)
}
This is a little better, for sure. Tuples let us add a little bit of structure. We’re now passing two arguments, so that’s more clear. But it’s also worse. Tuples don’t give names to their elements, and so our calculation has gotten much more confusing:
p2.0 - p1.0
p2.1 - p1.1
When writing this example, your authors almost got it wrong themselves! Distance
is all about x
and y
points, but now it’s all about 0
and 1
. This isn’t
great.
Enter struct
s. We can transform our tuples into something with a name:
let p1 = (0.0, 5.0);
struct Point {
x: f64,
y: f64,
}
let p1 = Point { x: 0.0, y: 5.0 };
Here’s what declaring a struct
looks like:
struct NAME {
NAME: TYPE,
}
The NAME: TYPE
bit is called a ‘field’, and we can have as many or as few of
them as you’d like. If you have none of them, drop the {}
s:
struct Foo;
struct
s with no fields are called ‘unit structs’, and are used in certain
advanced situations. We will just ignore them for now.
You can access the field of a struct in the same way you access an element of a tuple, except you use its name:
let p1 = (0.0, 5.0);
let x = p1.0;
struct Point {
x: f64,
y: f64,
}
let p1 = Point { x: 0.0, y: 5.0 };
let x = p1.x;
Let’s convert our program to use our Point
struct
. Here’s what it looks
like now:
#[derive(Debug,Copy,Clone)]
struct Point {
x: f64,
y: f64,
}
fn main() {
let p1 = Point { x: 0.0, y: 5.0};
let p2 = Point { x: 12.0, y: 0.0};
let answer = distance(p1, p2);
println!("Point 1: {:?}", p1);
println!("Point 2: {:?}", p2);
println!("Distance: {}", answer);
}
fn distance(p1: Point, p2: Point) -> f64 {
let x_squared = f64::powi(p2.x - p1.x, 2);
let y_squared = f64::powi(p2.y - p1.y, 2);
f64::sqrt(x_squared + y_squared)
}
Our function signature for distance()
now says exactly what we mean: it
calculates the distance between two Point
s. And rather than 0
and 1
,
we’ve got back our x
and y
. This is a win for clarity.
There’s one other thing that’s a bit strange here, this annotation on our
struct
declaration:
#[derive(Debug,Copy,Clone)]
struct Point {
We haven’t yet talked about traits, but we did talk about Debug
when we
discussed arrays. This derive
attribute allows us to tweak the behavior of
our Point
. In this case, we are opting into copy semantics, and everything
that implements Copy
must implement Clone
.