## Processing a Series of Items with Iterators

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 you use iterators, you don’t have to reimplement that logic yourself.

In Rust, iterators are lazy, meaning they have no effect until you 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<T>`. This code by itself doesn’t do anything useful.

    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 3-5 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.

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

        let v1_iter = v1.iter();

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

Listing 13-14: Using an iterator in a `for` loop

In languages that don’t have iterators provided by their standard libraries, you 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 reached the total number of items in the vector.

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

### The `Iterator` Trait and the `next` Method

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

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

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

        // methods with default implementations elided
    }
    }

Notice this definition uses some new syntax: `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, 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

    #[cfg(test)]
    mod tests {
        #[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 internal state that the iterator uses to keep 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`.

### Methods that Consume the Iterator

The `Iterator` trait has a number of different methods with default implementations provided 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 you’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

    #[cfg(test)]
    mod tests {
        #[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.

### Methods that Produce Other Iterators

Other methods defined on the `Iterator` trait, known as iterator adaptors, allow you to change iterators into different kinds of iterators. You can chain multiple calls to iterator adaptors to perform complex actions in a readable way. But because all iterators are lazy, you 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

    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 this:

    $ cargo run
       Compiling iterators v0.1.0 (file:///projects/iterators)
    warning: unused `Map` that must be used
     --> src/main.rs:4:5
      |
    4 |     v1.iter().map(|x| x + 1);
      |     ^^^^^^^^^^^^^^^^^^^^^^^^^
      |
      = note: `#[warn(unused_must_use)]` on by default
      = note: iterators are lazy and do nothing unless consumed

    warning: 1 warning emitted

        Finished dev [unoptimized + debuginfo] target(s) in 0.47s
         Running `target/debug/iterators`

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 we used in Chapter 12 with `env::args` in Listing 12-1. 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

    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 you customize some behavior while reusing the iteration behavior that the `Iterator` trait provides.

### Using Closures that Capture Their Environment

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

    #[derive(PartialEq, Debug)]
    struct Shoe {
        size: u32,
        style: String,
    }

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

    #[cfg(test)]
    mod tests {
        use super::*;

        #[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_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_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_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_size`, we get back only shoes that have the same size as the value we specified.

### Creating Our Own Iterators with the `Iterator` Trait

We’ve shown that you can create an iterator by calling `iter`, `into_iter`, or `iter_mut` on a vector. You can create iterators from the other collection types in the standard library, such as hash map. You can also create iterators that do anything you want by implementing the `Iterator` trait on your own types. As previously mentioned, the only method you’re required to provide a definition for is the `next` method. Once you’ve done that, you 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. Then we’ll make this struct into an iterator by implementing the `Iterator` trait and using 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

    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

    struct Counter {
        count: u32,
    }

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

    impl Iterator for Counter {
        type Item = u32;

        fn next(&mut self) -> Option<Self::Item> {
            if self.count < 5 {
                self.count += 1;
                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 1 to the current state, so we initialized `count` to 0 so it would return 1 first. If the value of `count` is less than 5, `next` will increment `count` and return the current value wrapped in `Some`. Once `count` is 5, our iterator will stop incrementing `count` and always return `None`.

#### Using Our `Counter` Iterator’s `next` Method

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 as we did with the iterator created from a vector in Listing 13-15.

Filename: src/lib.rs

    struct Counter {
        count: u32,
    }

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

    impl Iterator for Counter {
        type Item = u32;

        fn next(&mut self) -> Option<Self::Item> {
            if self.count < 5 {
                self.count += 1;
                Some(self.count)
            } else {
                None
            }
        }
    }

    #[cfg(test)]
    mod tests {
        use super::*;

        #[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.

#### Using Other `Iterator` Trait Methods

We implemented the `Iterator` trait by defining the `next` method, so 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 3, and add all the resulting values together, we could do so, as shown in the test in Listing 13-23:

Filename: src/lib.rs

    struct Counter {
        count: u32,
    }

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

    impl Iterator for Counter {
        type Item = u32;

        fn next(&mut self) -> Option<Self::Item> {
            if self.count < 5 {
                self.count += 1;
                Some(self.count)
            } else {
                None
            }
        }
    }

    #[cfg(test)]
    mod tests {
        use super::*;

        #[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);
        }

        #[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`.