The Rust Programming Language

The iterator pattern allows you to perform some task on a sequence of items in turn. An iterator is responsible for the logic of iterating over each item and determining when the sequence has finished. When we use iterators, we don’t have to reimplement that logic ourselves.

In Rust, iterators are lazy, meaning they have no effect until we call methods that consume the iterator to use it up. For example, the code in Listing 13-13 creates an iterator over the items in the vector v1 by calling the iter method defined on Vec. This code by itself doesn’t do anything useful:

# #![allow(unused_variables)]
#fn main() {
let v1 = vec![1, 2, 3];

let v1_iter = v1.iter();
#}

Listing 13-13: Creating an iterator

Once we’ve created an iterator, we can use it in a variety of ways. In Listing 3-4 in Chapter 3, we used iterators with for loops to execute some code on each item, although we glossed over what the call to iter did until now.

The example in Listing 13-14 separates the creation of the iterator from the use of the iterator in the for loop. The iterator is stored in the v1_iter variable, and no iteration takes place at that time. When the for loop is called using the iterator in v1_iter, each element in the iterator is used in one iteration of the loop, which prints out each value:

# #![allow(unused_variables)]
#fn main() {
let v1 = vec![1, 2, 3];

let v1_iter = v1.iter();

for val in v1_iter {
    println!("Got: {}", val);
}
#}

Listing 13-14: Making use of an iterator in a for loop

In languages that don’t have iterators provided by their standard libraries, we would likely write this same functionality by starting a variable at index 0, using that variable to index into the vector to get a value, and incrementing the variable value in a loop until it gets to the total number of items in the vector.

Iterators handle all that logic for us, cutting down on repetitive code we could potentially mess up. Iterators give us more flexibility to use the same logic with many different kinds of sequences, not just data structures we can index into, like vectors. Let’s examine how iterators do that.

All iterators implement a trait named Iterator that is defined in the standard library. The definition of the trait looks like this:

# #![allow(unused_variables)]
#fn main() {
trait Iterator {
    type Item;

    fn next(&mut self) -> Option<Self::Item>;

    // methods with default implementations elided
}
#}

Notice some new syntax that we haven’t covered yet: type Item and Self::Item, which are defining an associated type with this trait. We’ll talk about associated types in depth in Chapter 19. For now, all you need to know is that this code says implementing the Iterator trait requires that you also define an Item type, and this Item type is used in the return type of the next method. In other words, the Item type will be the type returned from the iterator.

The Iterator trait only requires implementors to define one method: the next method, which returns one item of the iterator at a time wrapped in Some and, when iteration is over, it returns None.

We can call the next method on iterators directly; Listing 13-15 demonstrates what values are returned from repeated calls to next on the iterator created from the vector:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
#[test]
fn iterator_demonstration() {
    let v1 = vec![1, 2, 3];

    let mut v1_iter = v1.iter();

    assert_eq!(v1_iter.next(), Some(&1));
    assert_eq!(v1_iter.next(), Some(&2));
    assert_eq!(v1_iter.next(), Some(&3));
    assert_eq!(v1_iter.next(), None);
}
#}

Listing 13-15: Calling the next method on an iterator

Note that we needed to make v1_iter mutable: calling the next method on an iterator changes state that keeps track of where it is in the sequence. In other words, this code consumes, or uses up, the iterator. Each call to next eats up an item from the iterator. We didn’t need to make v1_iter mutable when we used a for loop because the loop took ownership of v1_iter and made it mutable behind the scenes.

Also note that the values we get from the calls to next are immutable references to the values in the vector. The iter method produces an iterator over immutable references. If we want to create an iterator that takes ownership of v1 and returns owned values, we can call into_iter instead of iter. Similarly, if we want to iterate over mutable references, we can call iter_mut instead of iter.

The Iterator trait has a number of different methods with default implementations provided for us by the standard library; you can find out about these methods by looking in the standard library API documentation for the Iterator trait. Some of these methods call the next method in their definition, which is why we’re required to implement the next method when implementing the Iterator trait.

Methods that call next are called consuming adaptors, because calling them uses up the iterator. One example is the sum method, which takes ownership of the iterator and iterates through the items by repeatedly calling next, thus consuming the iterator. As it iterates through, it adds each item to a running total and returns the total when iteration is complete. Listing 13-16 has a test illustrating a use of the sum method:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
#[test]
fn iterator_sum() {
    let v1 = vec![1, 2, 3];

    let v1_iter = v1.iter();

    let total: i32 = v1_iter.sum();

    assert_eq!(total, 6);
}
#}

Listing 13-16: Calling the sum method to get the total of all items in the iterator

We aren’t allowed to use v1_iter after the call to sum because sum takes ownership of the iterator we call it on.

Other methods defined on the Iterator trait, known as iterator adaptors, allow us to change iterators into different kind of iterators. We can chain multiple calls to iterator adaptors to perform complex actions in a readable way. But because all iterators are lazy, we have to call one of the consuming adaptor methods to get results from calls to iterator adaptors.

Listing 13-17 shows an example of calling the iterator adaptor method map, which takes a closure to call on each item to produce a new iterator. The closure here creates a new iterator in which each item from the vector has been incremented by 1. However, this code produces a warning:

Filename: src/main.rs

# #![allow(unused_variables)]
#fn main() {
let v1: Vec<i32> = vec![1, 2, 3];

v1.iter().map(|x| x + 1);
#}

Listing 13-17: Calling the iterator adaptor map to create a new iterator

The warning we get is:

warning: unused `std::iter::Map` which must be used: iterator adaptors are lazy
and do nothing unless consumed
 --> src/main.rs:4:5
  |
4 |     v1.iter().map(|x| x + 1);
  |     ^^^^^^^^^^^^^^^^^^^^^^^^^
  |
  = note: #[warn(unused_must_use)] on by default

The code in Listing 13-17 doesn’t do anything; the closure we’ve specified never gets called. The warning reminds us why: iterator adaptors are lazy, and we need to consume the iterator here.

To fix this and consume the iterator, we’ll use the collect method, which you saw briefly in Chapter 12. This method consumes the iterator and collects the resulting values into a collection data type.

In Listing 13-18, we collect the results of iterating over the iterator that’s returned from the call to map into a vector. This vector will end up containing each item from the original vector incremented by 1:

Filename: src/main.rs

# #![allow(unused_variables)]
#fn main() {
let v1: Vec<i32> = vec![1, 2, 3];

let v2: Vec<_> = v1.iter().map(|x| x + 1).collect();

assert_eq!(v2, vec![2, 3, 4]);
#}

Listing 13-18: Calling the map method to create a new iterator, and then calling the collect method to consume the new iterator and create a vector

Because map takes a closure, we can specify any operation we want to perform on each item. This is a great example of how closures let us customize some behavior while reusing the iteration behavior that the Iterator trait provides.

Now that we’ve introduced iterators, we can demonstrate a common use of closures that capture their environment by using the filter iterator adaptor. The filter method on an iterator takes a closure that takes each item from the iterator and returns a Boolean. If the closure returns true, the value will be included in the iterator produced by filter. If the closure returns false, the value won’t be included in the resulting iterator.

In Listing 13-19 we use filter with a closure that captures the shoe_size variable from its environment to iterate over a collection of Shoe struct instances. It will return only shoes that are the specified size:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
#[derive(PartialEq, Debug)]
struct Shoe {
    size: u32,
    style: String,
}

fn shoes_in_my_size(shoes: Vec<Shoe>, shoe_size: u32) -> Vec<Shoe> {
    shoes.into_iter()
        .filter(|s| s.size == shoe_size)
        .collect()
}

#[test]
fn filters_by_size() {
    let shoes = vec![
        Shoe { size: 10, style: String::from("sneaker") },
        Shoe { size: 13, style: String::from("sandal") },
        Shoe { size: 10, style: String::from("boot") },
    ];

    let in_my_size = shoes_in_my_size(shoes, 10);

    assert_eq!(
        in_my_size,
        vec![
            Shoe { size: 10, style: String::from("sneaker") },
            Shoe { size: 10, style: String::from("boot") },
        ]
    );
}
#}

Listing 13-19: Using the filter method with a closure that captures shoe_size

The shoes_in_my_size function takes ownership of a vector of shoes and a shoe size as parameters. It returns a vector containing only shoes of the specified size.

In the body of shoes_in_my_size, we call into_iter to create an iterator that takes ownership of the vector. Then we call filter to adapt that iterator into a new iterator that only contains elements for which the closure returns true.

The closure captures the shoe_size parameter from the environment and compares the value with each shoe’s size, keeping only shoes of the size specified. Finally, calling collect gathers the values returned by the adapted iterator into a vector that’s returned by the function.

The test shows that when we call shoes_in_my_size, we only get back shoes that have the same size as the value we specified.

We’ve shown that we can create an iterator by calling iter, into_iter, or iter_mut on a vector. We can create iterators from the other collection types in the standard library, such as hash map. We can also create iterators that do anything we want by implementing the Iterator trait on our own types. As previously mentioned, the only method we’re required to provide a definition for is the next method. Once we’ve done that, we can use all other methods that have default implementations provided by the Iterator trait!

To demonstrate, let’s create an iterator that will only ever count from 1 to 5. First, we’ll create a struct to hold some values, and then we’ll make this struct into an iterator by implementing the Iterator trait and use the values in that implementation.

Listing 13-20 has the definition of the Counter struct and an associated new function to create instances of Counter:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
struct Counter {
    count: u32,
}

impl Counter {
    fn new() -> Counter {
        Counter { count: 0 }
    }
}
#}

Listing 13-20: Defining the Counter struct and a new function that creates instances of Counter with an initial value of 0 for count

The Counter struct has one field named count. This field holds a u32 value that will keep track of where we are in the process of iterating from 1 to 5. The count field is private because we want the implementation of Counter to manage its value. The new function enforces the behavior of always starting new instances with a value of 0 in the count field.

Next, we’ll implement the Iterator trait for our Counter type by defining the body of the next method to specify what we want to happen when this iterator is used, as shown in Listing 13-21:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
# struct Counter {
#     count: u32,
# }
#
impl Iterator for Counter {
    type Item = u32;

    fn next(&mut self) -> Option<Self::Item> {
        self.count += 1;

        if self.count < 6 {
            Some(self.count)
        } else {
            None
        }
    }
}
#}

Listing 13-21: Implementing the Iterator trait on our Counter struct

We set the associated Item type for our iterator to u32, meaning the iterator will return u32 values. Again, don’t worry about associated types yet, we’ll cover them in Chapter 19.

We want our iterator to add one to the current state, so we initialized count to 0 so it would return 1 first. If the value of count is less than 6, next will return the current value wrapped in Some, but if count is 6 or higher, our iterator will return None.

Once we’ve implemented the Iterator trait, we have an iterator! Listing 13-22 shows a test demonstrating that we can use the iterator functionality of our Counter struct by calling the next method on it directly, just like we did with the iterator created from a vector in Listing 13-15:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
# struct Counter {
#     count: u32,
# }
#
# impl Iterator for Counter {
#     type Item = u32;
#
#     fn next(&mut self) -> Option<Self::Item> {
#         self.count += 1;
#
#         if self.count < 6 {
#             Some(self.count)
#         } else {
#             None
#         }
#     }
# }
#
#[test]
fn calling_next_directly() {
    let mut counter = Counter::new();

    assert_eq!(counter.next(), Some(1));
    assert_eq!(counter.next(), Some(2));
    assert_eq!(counter.next(), Some(3));
    assert_eq!(counter.next(), Some(4));
    assert_eq!(counter.next(), Some(5));
    assert_eq!(counter.next(), None);
}
#}

Listing 13-22: Testing the functionality of the next method implementation

This test creates a new Counter instance in the counter variable and then calls next repeatedly, verifying that we have implemented the behavior we want this iterator to have: returning the values from 1 to 5.

Because we implemented the Iterator trait by defining the next method, we can now use any Iterator trait method’s default implementations as defined in the standard library, because they all use the next method’s functionality.

For example, if for some reason we wanted to take the values produced by an instance of Counter, pair them with values produced by another Counter instance after skipping the first value, multiply each pair together, keep only those results that are divisible by three, and add all the resulting values together, we could do so, as shown in the test in Listing 13-23:

Filename: src/lib.rs

# #![allow(unused_variables)]
#fn main() {
# struct Counter {
#     count: u32,
# }
#
# impl Counter {
#     fn new() -> Counter {
#         Counter { count: 0 }
#     }
# }
#
# impl Iterator for Counter {
#     // Our iterator will produce u32s
#     type Item = u32;
#
#     fn next(&mut self) -> Option<Self::Item> {
#         // increment our count. This is why we started at zero.
#         self.count += 1;
#
#         // check to see if we've finished counting or not.
#         if self.count < 6 {
#             Some(self.count)
#         } else {
#             None
#         }
#     }
# }
#
#[test]
fn using_other_iterator_trait_methods() {
    let sum: u32 = Counter::new().zip(Counter::new().skip(1))
                                 .map(|(a, b)| a * b)
                                 .filter(|x| x % 3 == 0)
                                 .sum();
    assert_eq!(18, sum);
}
#}

Listing 13-23: Using a variety of Iterator trait methods on our Counter iterator

Note that zip produces only four pairs; the theoretical fifth pair (5, None) is never produced because zip returns None when either of its input iterators return None.

All of these method calls are possible because we specified how the next method works, and the standard library provides default implementations for other methods that call next.