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Welcome to Removing Duplication by Extracting a Function. This lab is a part of the Rust Book. You can practice your Rust skills in LabEx.
In this lab, we will learn how to remove code duplication by extracting a function and using generics to operate on abstract types.
Generics allow us to replace specific types with a placeholder that represents multiple types to remove code duplication. Before diving into generics syntax, let's first look at how to remove duplication in a way that doesn't involve generic types by extracting a function that replaces specific values with a placeholder that represents multiple values. Then we'll apply the same technique to extract a generic function! By looking at how to recognize duplicated code you can extract into a function, you'll start to recognize duplicated code that can use generics.
We'll begin with the short program in Listing 10-1 that finds the largest number in a list.
Filename: src/main.rs
fn main() {
1 let number_list = vec![34, 50, 25, 100, 65];
2 let mut largest = &number_list[0];
3 for number in &number_list {
4 if number > largest {
5 largest = number;
}
}
println!("The largest number is {largest}");
}Listing 10-1: Finding the largest number in a list of numbers
We store a list of integers in the variable number_list [1] and place a reference to the first number in the list in a variable named largest [2]. We then iterate through all the numbers in the list [3], and if the current number is greater than the number stored in largest [4], we replace the reference in that variable [5]. However, if the current number is less than or equal to the largest number seen so far, the variable doesn't change, and the code moves on to the next number in the list. After considering all the numbers in the list, largest should refer to the largest number, which in this case is 100.
We've now been tasked with finding the largest number in two different lists of numbers. To do so, we can choose to duplicate the code in Listing 10-1 and use the same logic at two different places in the program, as shown in Listing 10-2.
Filename: src/main.rs
fn main() {
let number_list = vec![34, 50, 25, 100, 65];
let mut largest = &number_list[0];
for number in &number_list {
if number > largest {
largest = number;
}
}
println!("The largest number is {largest}");
let number_list = vec![102, 34, 6000, 89, 54, 2, 43, 8];
let mut largest = &number_list[0];
for number in &number_list {
if number > largest {
largest = number;
}
}
println!("The largest number is {largest}");
}Listing 10-2: Code to find the largest number in two lists of numbers
Although this code works, duplicating code is tedious and error prone. We also have to remember to update the code in multiple places when we want to change it.
To eliminate this duplication, we'll create an abstraction by defining a function that operates on any list of integers passed in a parameter. This solution makes our code clearer and lets us express the concept of finding the largest number in a list abstractly.
In Listing 10-3, we extract the code that finds the largest number into a function named largest. Then we call the function to find the largest number in the two lists from Listing 10-2. We could also use the function on any other list of i32 values we might have in the future.
Filename: src/main.rs
fn largest(list: &[i32]) -> &i32 {
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 number_list = vec![102, 34, 6000, 89, 54, 2, 43, 8];
let result = largest(&number_list);
println!("The largest number is {result}");
}Listing 10-3: Abstracted code to find the largest number in two lists
The largest function has a parameter called list, which represents any concrete slice of i32 values we might pass into the function. As a result, when we call the function, the code runs on the specific values that we pass in.
In summary, here are the steps we took to change the code from Listing 10-2 to Listing 10-3:
Next, we'll use these same steps with generics to reduce code duplication. In the same way that the function body can operate on an abstract list instead of specific values, generics allow code to operate on abstract types.
For example, say we had two functions: one that finds the largest item in a slice of i32 values and one that finds the largest item in a slice of char values. How would we eliminate that duplication? Let's find out!
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.
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}");
let char_list = vec!['y', 'm', 'a', 'q'];
let result = largest_char(&char_list);
println!("The largest char is {result}");
}Listing 10-4: Two functions that differ only in their names and in 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, type parameter names in Rust are short, often just one 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, we 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 reference to 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 compile yet
If we compile this code right now, we'll get this error:
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 {
| ++++++++++++++++++++++The help text mentions std::cmp::PartialOrd, which is a trait, and we're going to 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). By following the help text's suggestion, we restrict the types valid for T to only those that implement PartialOrd and this example will compile, because the standard library implements PartialOrd on both i32 and char.
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
1 struct Point<T> {
2 x: T,
3 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 [1]. Then we use the generic type in the struct definition where we would otherwise specify concrete data types [23].
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:
error[E0308]: mismatched types
--> src/main.rs:7:38
|
7 | let wont_work = Point { x: 5, y: 4.0 };
| ^^^ expected integer, found floating-
point numberTo 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.
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:
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:
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.
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
impl Point<f32> {
fn distance_from_origin(&self) -> f32 {
(self.x.powi(2) + self.y.powi(2)).sqrt()
}
}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,
}
1 impl<X1, Y1> Point<X1, Y1> {
2 fn mixup<X2, Y2>(
self,
other: Point<X2, Y2>,
) -> Point<X1, Y2> {
Point {
x: self.x,
y: other.y,
}
}
}
fn main() {
3 let p1 = Point { x: 5, y: 10.4 };
4 let p2 = Point { x: "Hello", y: 'c' };
5 let p3 = p1.mixup(p2);
6 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 [3]). 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 [4]). Calling mixup on p1 with the argument p2 gives us p3 [5], 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 [6] 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 [1] because they go with the struct definition. The generic parameters X2 and Y2 are declared after fn mixup [2] because they're only relevant to the method.
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 program 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:
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 two definitions specialized to i32 and f64, thereby replacing the generic definition with the specific ones.
The monomorphized version of the code looks similar to the following (the compiler uses different names than what we're using here for illustration):
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.
Congratulations! You have completed the Removing Duplication by Extracting a Function lab. You can practice more labs in LabEx to improve your skills.
