Generic Data Types
We use generics to create definitions for items like function signatures or structs, which we can then use with many different concrete data types. Let’s first look at how to define functions, structs, enums, and methods using generics. Then we’ll discuss how generics affect code performance.
In Function Definitions
When defining a function that uses generics, we place the generics in the signature of the function where we would usually specify the data types of the parameters and return value. Doing so makes our code more flexible and provides more functionality to callers of our function while preventing code duplication.
Continuing with our largest function, Listing 10-4 shows two functions that
both find the largest value in a slice. We'll then combine these into a single
function that uses generics.
Filename: src/main.rs
fn largest_i32(list: &[i32]) -> i32 { let mut largest = list[0]; for &item in list { if item > largest { largest = item; } } largest } fn largest_char(list: &[char]) -> char { let mut largest = list[0]; for &item in list { if item > largest { largest = item; } } largest } fn main() { let number_list = vec![34, 50, 25, 100, 65]; let result = largest_i32(&number_list); println!("The largest number is {}", result); assert_eq!(result, 100); let char_list = vec!['y', 'm', 'a', 'q']; let result = largest_char(&char_list); println!("The largest char is {}", result); assert_eq!(result, 'y'); }
Listing 10-4: Two functions that differ only in their names and the types in their signatures
The largest_i32 function is the one we extracted in Listing 10-3 that finds
the largest i32 in a slice. The largest_char function finds the largest
char in a slice. The function bodies have the same code, so let’s eliminate
the duplication by introducing a generic type parameter in a single function.
To parameterize the types in a new single function, we need to name the type
parameter, just as we do for the value parameters to a function. You can use
any identifier as a type parameter name. But we’ll use T because, by
convention, parameter names in Rust are short, often just a letter, and Rust’s
type-naming convention is CamelCase. Short for “type,” T is the default
choice of most Rust programmers.
When we use a parameter in the body of the function, we have to declare the
parameter name in the signature so the compiler knows what that name means.
Similarly, when we use a type parameter name in a function signature, we have
to declare the type parameter name before we use it. To define the generic
largest function, place type name declarations inside angle brackets, <>,
between the name of the function and the parameter list, like this:
fn largest<T>(list: &[T]) -> T {
We read this definition as: the function largest is generic over some type
T. This function has one parameter named list, which is a slice of values
of type T. The largest function will return a value of the
same type T.
Listing 10-5 shows the combined largest function definition using the generic
data type in its signature. The listing also shows how we can call the function
with either a slice of i32 values or char values. Note that this code won’t
compile yet, but we’ll fix it later in this chapter.
Filename: src/main.rs
fn largest<T>(list: &[T]) -> T {
let mut largest = list[0];
for &item in list {
if item > largest {
largest = item;
}
}
largest
}
fn main() {
let number_list = vec![34, 50, 25, 100, 65];
let result = largest(&number_list);
println!("The largest number is {}", result);
let char_list = vec!['y', 'm', 'a', 'q'];
let result = largest(&char_list);
println!("The largest char is {}", result);
}
Listing 10-5: The largest function using generic type
parameters; this doesn’t yet compile
If we compile this code right now, we’ll get this error:
$ cargo run
Compiling chapter10 v0.1.0 (file:///projects/chapter10)
error[E0369]: binary operation `>` cannot be applied to type `T`
--> src/main.rs:5:17
|
5 | if item > largest {
| ---- ^ ------- T
| |
| T
|
help: consider restricting type parameter `T`
|
1 | fn largest<T: std::cmp::PartialOrd>(list: &[T]) -> T {
| ++++++++++++++++++++++
For more information about this error, try `rustc --explain E0369`.
error: could not compile `chapter10` due to previous error
The note mentions std::cmp::PartialOrd, which is a trait. We’ll talk about
traits in the next section. For now, know that this error states that the body
of largest won’t work for all possible types that T could be. Because we
want to compare values of type T in the body, we can only use types whose
values can be ordered. To enable comparisons, the standard library has the
std::cmp::PartialOrd trait that you can implement on types (see Appendix C
for more on this trait). You’ll learn how to specify that a generic type has a
particular trait in the “Traits as Parameters” section. Before we fix this code (in the section “Fixing the
largest Function with Trait Bounds”), let’s first
explore other ways of using generic type parameters.
In Struct Definitions
We can also define structs to use a generic type parameter in one or more
fields using the <> syntax. Listing 10-6 defines a Point<T> struct to hold
x and y coordinate values of any type.
Filename: src/main.rs
struct Point<T> { x: T, y: T, } fn main() { let integer = Point { x: 5, y: 10 }; let float = Point { x: 1.0, y: 4.0 }; }
Listing 10-6: A Point<T> struct that holds x and y
values of type T
The syntax for using generics in struct definitions is similar to that used in function definitions. First, we declare the name of the type parameter inside angle brackets just after the name of the struct. Then we use the generic type in the struct definition where we would otherwise specify concrete data types.
Note that because we’ve used only one generic type to define Point<T>, this
definition says that the Point<T> struct is generic over some type T, and
the fields x and y are both that same type, whatever that type may be. If
we create an instance of a Point<T> that has values of different types, as in
Listing 10-7, our code won’t compile.
Filename: src/main.rs
struct Point<T> {
x: T,
y: T,
}
fn main() {
let wont_work = Point { x: 5, y: 4.0 };
}
Listing 10-7: The fields x and y must be the same
type because both have the same generic data type T.
In this example, when we assign the integer value 5 to x, we let the compiler
know that the generic type T will be an integer for this instance of
Point<T>. Then when we specify 4.0 for y, which we’ve defined to have the
same type as x, we’ll get a type mismatch error like this:
$ cargo run
Compiling chapter10 v0.1.0 (file:///projects/chapter10)
error[E0308]: mismatched types
--> src/main.rs:7:38
|
7 | let wont_work = Point { x: 5, y: 4.0 };
| ^^^ expected integer, found floating-point number
For more information about this error, try `rustc --explain E0308`.
error: could not compile `chapter10` due to previous error
To define a Point struct where x and y are both generics but could have
different types, we can use multiple generic type parameters. For example, in
Listing 10-8, we change the definition of Point to be generic over types T
and U where x is of type T and y is of type U.
Filename: src/main.rs
struct Point<T, U> { x: T, y: U, } fn main() { let both_integer = Point { x: 5, y: 10 }; let both_float = Point { x: 1.0, y: 4.0 }; let integer_and_float = Point { x: 5, y: 4.0 }; }
Listing 10-8: A Point<T, U> generic over two types so
that x and y can be values of different types
Now all the instances of Point shown are allowed! You can use as many generic
type parameters in a definition as you want, but using more than a few makes
your code hard to read. If you're finding you need lots of generic types in
your code, it could indicate that your code needs restructuring into smaller
pieces.
In Enum Definitions
As we did with structs, we can define enums to hold generic data types in their
variants. Let’s take another look at the Option<T> enum that the standard
library provides, which we used in Chapter 6:
#![allow(unused)] fn main() { enum Option<T> { Some(T), None, } }
This definition should now make more sense to you. As you can see, the
Option<T> enum is generic over type T and has two variants: Some, which
holds one value of type T, and a None variant that doesn’t hold any value.
By using the Option<T> enum, we can express the abstract concept of an
optional value, and because Option<T> is generic, we can use this abstraction
no matter what the type of the optional value is.
Enums can use multiple generic types as well. The definition of the Result
enum that we used in Chapter 9 is one example:
#![allow(unused)] fn main() { enum Result<T, E> { Ok(T), Err(E), } }
The Result enum is generic over two types, T and E, and has two variants:
Ok, which holds a value of type T, and Err, which holds a value of type
E. This definition makes it convenient to use the Result enum anywhere we
have an operation that might succeed (return a value of some type T) or fail
(return an error of some type E). In fact, this is what we used to open a
file in Listing 9-3, where T was filled in with the type std::fs::File when
the file was opened successfully and E was filled in with the type
std::io::Error when there were problems opening the file.
When you recognize situations in your code with multiple struct or enum definitions that differ only in the types of the values they hold, you can avoid duplication by using generic types instead.
In Method Definitions
We can implement methods on structs and enums (as we did in Chapter 5) and use
generic types in their definitions, too. Listing 10-9 shows the Point<T>
struct we defined in Listing 10-6 with a method named x implemented on it.
Filename: src/main.rs
struct Point<T> { x: T, y: T, } impl<T> Point<T> { fn x(&self) -> &T { &self.x } } fn main() { let p = Point { x: 5, y: 10 }; println!("p.x = {}", p.x()); }
Listing 10-9: Implementing a method named x on the
Point<T> struct that will return a reference to the x field of type
T
Here, we’ve defined a method named x on Point<T> that returns a reference
to the data in the field x.
Note that we have to declare T just after impl so we can use T to specify
that we’re implementing methods on the type Point<T>. By declaring T as a
generic type after impl, Rust can identify that the type in the angle
brackets in Point is a generic type rather than a concrete type. We could
have chosen a different name for this generic parameter than the generic
parameter declared in the struct definition, but using the same name is
conventional. Methods written within an impl that declares the generic type
will be defined on any instance of the type, no matter what concrete type ends
up substituting for the generic type.
We can also specify constraints on generic types when defining methods on the
type. We could, for example, implement methods only on Point<f32> instances
rather than on Point<T> instances with any generic type. In Listing 10-10 we
use the concrete type f32, meaning we don’t declare any types after impl.
Filename: src/main.rs
struct Point<T> { x: T, y: T, } impl<T> Point<T> { fn x(&self) -> &T { &self.x } } impl Point<f32> { fn distance_from_origin(&self) -> f32 { (self.x.powi(2) + self.y.powi(2)).sqrt() } } fn main() { let p = Point { x: 5, y: 10 }; println!("p.x = {}", p.x()); }
Listing 10-10: An impl block that only applies to a
struct with a particular concrete type for the generic type parameter T
This code means the type Point<f32> will have a distance_from_origin
method; other instances of Point<T> where T is not of type f32 will not
have this method defined. The method measures how far our point is from the
point at coordinates (0.0, 0.0) and uses mathematical operations that are
available only for floating point types.
Generic type parameters in a struct definition aren’t always the same as those
you use in that same struct’s method signatures. Listing 10-11 uses the generic
types X1 and Y1 for the Point struct and X2 Y2 for the mixup method
signature to make the example clearer. The method creates a new Point
instance with the x value from the self Point (of type X1) and the y
value from the passed-in Point (of type Y2).
Filename: src/main.rs
struct Point<X1, Y1> { x: X1, y: Y1, } impl<X1, Y1> Point<X1, Y1> { fn mixup<X2, Y2>(self, other: Point<X2, Y2>) -> Point<X1, Y2> { Point { x: self.x, y: other.y, } } } fn main() { let p1 = Point { x: 5, y: 10.4 }; let p2 = Point { x: "Hello", y: 'c' }; let p3 = p1.mixup(p2); println!("p3.x = {}, p3.y = {}", p3.x, p3.y); }
Listing 10-11: A method that uses generic types different from its struct’s definition
In main, we’ve defined a Point that has an i32 for x (with value 5)
and an f64 for y (with value 10.4). The p2 variable is a Point struct
that has a string slice for x (with value "Hello") and a char for y
(with value c). Calling mixup on p1 with the argument p2 gives us p3,
which will have an i32 for x, because x came from p1. The p3 variable
will have a char for y, because y came from p2. The println! macro
call will print p3.x = 5, p3.y = c.
The purpose of this example is to demonstrate a situation in which some generic
parameters are declared with impl and some are declared with the method
definition. Here, the generic parameters X1 and Y1 are declared after
impl because they go with the struct definition. The generic parameters X2
and Y2 are declared after fn mixup, because they’re only relevant to the
method.
Performance of Code Using Generics
You might be wondering whether there is a runtime cost when using generic type parameters. The good news is that using generic types won't make your run any slower than it would with concrete types.
Rust accomplishes this by performing monomorphization of the code using generics at compile time. Monomorphization is the process of turning generic code into specific code by filling in the concrete types that are used when compiled. In this process, the compiler does the opposite of the steps we used to create the generic function in Listing 10-5: the compiler looks at all the places where generic code is called and generates code for the concrete types the generic code is called with.
Let’s look at how this works by using the standard library’s generic
Option<T> enum:
#![allow(unused)] fn main() { let integer = Some(5); let float = Some(5.0); }
When Rust compiles this code, it performs monomorphization. During that
process, the compiler reads the values that have been used in Option<T>
instances and identifies two kinds of Option<T>: one is i32 and the other
is f64. As such, it expands the generic definition of Option<T> into
Option_i32 and Option_f64, thereby replacing the generic definition with
the specific ones.
The monomorphized version of the code looks like the following:
Filename: src/main.rs
enum Option_i32 { Some(i32), None, } enum Option_f64 { Some(f64), None, } fn main() { let integer = Option_i32::Some(5); let float = Option_f64::Some(5.0); }
The generic Option<T> is replaced with the specific definitions created by
the compiler. Because Rust compiles generic code into code that specifies the
type in each instance, we pay no runtime cost for using generics. When the code
runs, it performs just as it would if we had duplicated each definition by
hand. The process of monomorphization makes Rust’s generics extremely efficient
at runtime.