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+<!-- DO NOT EDIT THIS FILE.
+
+This file is periodically generated from the content in the `/src/`
+directory, so all fixes need to be made in `/src/`.
+-->
+
+[TOC]
+
+# Functional Language Features: Iterators and Closures
+
+Rust’s design has taken inspiration from many existing languages and
+techniques, and one significant influence is *functional programming*.
+Programming in a functional style often includes using functions as values by
+passing them in arguments, returning them from other functions, assigning them
+to variables for later execution, and so forth.
+
+In this chapter, we won’t debate the issue of what functional programming is or
+isn’t but will instead discuss some features of Rust that are similar to
+features in many languages often referred to as functional.
+
+More specifically, we’ll cover:
+
+* *Closures*, a function-like construct you can store in a variable
+* *Iterators*, a way of processing a series of elements
+* How to use closures and iterators to improve the I/O project in Chapter 12
+* The performance of closures and iterators (Spoiler alert: they’re faster than
+  you might think!)
+
+We’ve already covered some other Rust features, such as pattern matching and
+enums, that are also influenced by the functional style. Because mastering
+closures and iterators is an important part of writing idiomatic, fast Rust
+code, we’ll devote this entire chapter to them.
+
+## Closures: Anonymous Functions that Capture Their Environment
+
+Rust’s closures are anonymous functions you can save in a variable or pass as
+arguments to other functions. You can create the closure in one place and then
+call the closure elsewhere to evaluate it in a different context. Unlike
+functions, closures can capture values from the scope in which they’re defined.
+We’ll demonstrate how these closure features allow for code reuse and behavior
+customization.
+
+### Capturing the Environment with Closures
+
+We’ll first examine how we can use closures to capture values from the
+environment they’re defined in for later use. Here’s the scenario: Every so
+often, our t-shirt company gives away an exclusive, limited-edition shirt to
+someone on our mailing list as a promotion. People on the mailing list can
+optionally add their favorite color to their profile. If the person chosen for
+a free shirt has their favorite color set, they get that color shirt. If the
+person hasn’t specified a favorite color, they get whatever color the company
+currently has the most of.
+
+There are many ways to implement this. For this example, we’re going to use an
+enum called `ShirtColor` that has the variants `Red` and `Blue` (limiting the
+number of colors available for simplicity). We represent the company’s
+inventory with an `Inventory` struct that has a field named `shirts` that
+contains a `Vec<ShirtColor>` representing the shirt colors currently in stock.
+The method `giveaway` defined on `Inventory` gets the optional shirt
+color preference of the free shirt winner, and returns the shirt color the
+person will get. This setup is shown in Listing 13-1:
+
+Filename: src/main.rs
+
+```
+#[derive(Debug, PartialEq, Copy, Clone)]
+enum ShirtColor {
+    Red,
+    Blue,
+}
+
+struct Inventory {
+    shirts: Vec<ShirtColor>,
+}
+
+impl Inventory {
+    fn giveaway(&self, user_preference: Option<ShirtColor>) -> ShirtColor {
+        user_preference.unwrap_or_else(|| self.most_stocked()) [1]
+    }
+
+    fn most_stocked(&self) -> ShirtColor {
+        let mut num_red = 0;
+        let mut num_blue = 0;
+
+        for color in &self.shirts {
+            match color {
+                ShirtColor::Red => num_red += 1,
+                ShirtColor::Blue => num_blue += 1,
+            }
+        }
+        if num_red > num_blue {
+            ShirtColor::Red
+        } else {
+            ShirtColor::Blue
+        }
+    }
+}
+
+fn main() {
+    let store = Inventory {
+        shirts: vec![ShirtColor::Blue, ShirtColor::Red, ShirtColor::Blue], [2]
+    };
+
+    let user_pref1 = Some(ShirtColor::Red);
+    let giveaway1 = store.giveaway(user_pref1); [3]
+    println!(
+        "The user with preference {:?} gets {:?}",
+        user_pref1, giveaway1
+    );
+
+    let user_pref2 = None;
+    let giveaway2 = store.giveaway(user_pref2); [4]
+    println!(
+        "The user with preference {:?} gets {:?}",
+        user_pref2, giveaway2
+    );
+}
+```
+
+Listing 13-1: Shirt company giveaway situation
+
+The `store` defined in `main` has two blue shirts and one red shirt remaining
+to distribute for this limited-edition promotion [2]. We call the `giveaway`
+method for a user with a preference for a red shirt [3] and a user without any
+preference [4].
+
+Again, this code could be implemented in many ways, and here, to focus on
+closures, we’ve stuck to concepts you’ve already learned except for the body of
+the `giveaway` method that uses a closure. In the `giveaway` method, we get the
+user preference as a parameter of type `Option<ShirtColor>` and call the
+`unwrap_or_else` method on `user_preference` [1]. The `unwrap_or_else` method on
+`Option<T>` is defined by the standard library. It takes one argument: a
+closure without any arguments that returns a value `T` (the same type stored in
+the `Some` variant of the `Option<T>`, in this case `ShirtColor`). If the
+`Option<T>` is the `Some` variant, `unwrap_or_else` returns the value from
+within the `Some`. If the `Option<T>` is the `None` variant, `unwrap_or_else`
+calls the closure and returns the value returned by the closure.
+
+We specify the closure expression `|| self.most_stocked()` as the argument to
+`unwrap_or_else`. This is a closure that takes no parameters itself (if the
+closure had parameters, they would appear between the two vertical bars). The
+body of the closure calls `self.most_stocked()`. We’re defining the closure
+here, and the implementation of `unwrap_or_else` will evaluate the closure
+later if the result is needed.
+
+Running this code prints:
+
+```
+$ cargo run
+   Compiling shirt-company v0.1.0 (file:///projects/shirt-company)
+    Finished dev [unoptimized + debuginfo] target(s) in 0.27s
+     Running `target/debug/shirt-company`
+The user with preference Some(Red) gets Red
+The user with preference None gets Blue
+```
+
+One interesting aspect here is that we’ve passed a closure that calls
+`self.most_stocked()` on the current `Inventory` instance. The standard library
+didn’t need to know anything about the `Inventory` or `ShirtColor` types we
+defined, or the logic we want to use in this scenario. The closure captures an
+immutable reference to the `self` `Inventory` instance and passes it with the
+code we specify to the `unwrap_or_else` method. Functions, on the other hand,
+are not able to capture their environment in this way.
+
+### Closure Type Inference and Annotation
+
+There are more differences between functions and closures. Closures don’t
+usually require you to annotate the types of the parameters or the return value
+like `fn` functions do. Type annotations are required on functions because the
+types are part of an explicit interface exposed to your users. Defining this
+interface rigidly is important for ensuring that everyone agrees on what types
+of values a function uses and returns. Closures, on the other hand, aren’t used
+in an exposed interface like this: they’re stored in variables and used without
+naming them and exposing them to users of our library.
+
+Closures are typically short and relevant only within a narrow context rather
+than in any arbitrary scenario. Within these limited contexts, the compiler can
+infer the types of the parameters and the return type, similar to how it’s able
+to infer the types of most variables (there are rare cases where the compiler
+needs closure type annotations too).
+
+As with variables, we can add type annotations if we want to increase
+explicitness and clarity at the cost of being more verbose than is strictly
+necessary. Annotating the types for a closure would look like the definition
+shown in Listing 13-2. In this example, we’re defining a closure and storing it
+in a variable rather than defining the closure in the spot we pass it as an
+argument as we did in Listing 13-1.
+
+Filename: src/main.rs
+
+```
+let expensive_closure = |num: u32| -> u32 {
+    println!("calculating slowly...");
+    thread::sleep(Duration::from_secs(2));
+    num
+};
+```
+
+Listing 13-2: Adding optional type annotations of the parameter and return
+value types in the closure
+
+With type annotations added, the syntax of closures looks more similar to the
+syntax of functions. Here we define a function that adds 1 to its parameter and
+a closure that has the same behavior, for comparison. We’ve added some spaces
+to line up the relevant parts. This illustrates how closure syntax is similar
+to function syntax except for the use of pipes and the amount of syntax that is
+optional:
+
+```
+fn  add_one_v1   (x: u32) -> u32 { x + 1 }
+let add_one_v2 = |x: u32| -> u32 { x + 1 };
+let add_one_v3 = |x|             { x + 1 };
+let add_one_v4 = |x|               x + 1  ;
+```
+
+The first line shows a function definition, and the second line shows a fully
+annotated closure definition. In the third line, we remove the type annotations
+from the closure definition. In the fourth line, we remove the brackets, which
+are optional because the closure body has only one expression. These are all
+valid definitions that will produce the same behavior when they’re called. The
+`add_one_v3` and `add_one_v4` lines require the closures to be evaluated to be
+able to compile because the types will be inferred from their usage. This is
+similar to `let v = Vec::new();` needing either type annotations or values of
+some type to be inserted into the `Vec` for Rust to be able to infer the type.
+
+For closure definitions, the compiler will infer one concrete type for each of
+their parameters and for their return value. For instance, Listing 13-3 shows
+the definition of a short closure that just returns the value it receives as a
+parameter. This closure isn’t very useful except for the purposes of this
+example. Note that we haven’t added any type annotations to the definition.
+Because there are no type annotations, we can call the closure with any type,
+which we’ve done here with `String` the first time. If we then try to call
+`example_closure` with an integer, we’ll get an error.
+
+Filename: src/main.rs
+
+```
+let example_closure = |x| x;
+
+let s = example_closure(String::from("hello"));
+let n = example_closure(5);
+```
+
+Listing 13-3: Attempting to call a closure whose types are inferred with two
+different types
+
+The compiler gives us this error:
+
+```
+error[E0308]: mismatched types
+ --> src/main.rs:5:29
+  |
+5 |     let n = example_closure(5);
+  |                             ^- help: try using a conversion method: `.to_string()`
+  |                             |
+  |                             expected struct `String`, found integer
+```
+
+The first time we call `example_closure` with the `String` value, the compiler
+infers the type of `x` and the return type of the closure to be `String`. Those
+types are then locked into the closure in `example_closure`, and we get a type
+error when we next try to use a different type with the same closure.
+
+### Capturing References or Moving Ownership
+
+Closures can capture values from their environment in three ways, which
+directly map to the three ways a function can take a parameter: borrowing
+immutably, borrowing mutably, and taking ownership. The closure will decide
+which of these to use based on what the body of the function does with the
+captured values.
+
+In Listing 13-4, we define a closure that captures an immutable reference to
+the vector named `list` because it only needs an immutable reference to print
+the value:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let list = vec![1, 2, 3];
+    println!("Before defining closure: {:?}", list);
+
+    [1] let only_borrows = || println!("From closure: {:?}", list);
+
+    println!("Before calling closure: {:?}", list);
+    only_borrows(); [2]
+    println!("After calling closure: {:?}", list);
+}
+```
+
+Listing 13-4: Defining and calling a closure that captures an immutable
+reference
+
+This example also illustrates that a variable can bind to a closure definition
+[1], and we can later call the closure by using the variable name and
+parentheses as if the variable name were a function name [2].
+
+Because we can have multiple immutable references to `list` at the same time,
+`list` is still accessible from the code before the closure definition, after
+the closure definition but before the closure is called, and after the closure
+is called. This code compiles, runs, and prints:
+
+```
+Before defining closure: [1, 2, 3]
+Before calling closure: [1, 2, 3]
+From closure: [1, 2, 3]
+After calling closure: [1, 2, 3]
+```
+
+Next, in Listing 13-5, we change the closure body so that it adds an element to
+the `list` vector. The closure now captures a mutable reference:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let mut list = vec![1, 2, 3];
+    println!("Before defining closure: {:?}", list);
+
+    let mut borrows_mutably = || list.push(7);
+
+    borrows_mutably();
+    println!("After calling closure: {:?}", list);
+}
+```
+
+Listing 13-5: Defining and calling a closure that captures a mutable reference
+
+This code compiles, runs, and prints:
+
+```
+Before defining closure: [1, 2, 3]
+After calling closure: [1, 2, 3, 7]
+```
+
+Note that there’s no longer a `println!` between the definition and the call of
+the `borrows_mutably` closure: when `borrows_mutably` is defined, it captures a
+mutable reference to `list`. We don’t use the closure again after the closure
+is called, so the mutable borrow ends. Between the closure definition and the
+closure call, an immutable borrow to print isn’t allowed because no other
+borrows are allowed when there’s a mutable borrow. Try adding a `println!`
+there to see what error message you get!
+
+If you want to force the closure to take ownership of the values it uses in the
+environment even though the body of the closure doesn’t strictly need
+ownership, you can use the `move` keyword before the parameter list.
+
+This technique is mostly useful when passing a closure to a new thread to move
+the data so that it’s owned by the new thread. We’ll discuss threads and why
+you would want to use them in detail in Chapter 16 when we talk about
+concurrency, but for now, let’s briefly explore spawning a new thread using a
+closure that needs the `move` keyword. Listing 13-6 shows Listing 13-4 modified
+to print the vector in a new thread rather than in the main thread:
+
+Filename: src/main.rs
+
+```
+use std::thread;
+
+fn main() {
+    let list = vec![1, 2, 3];
+    println!("Before defining closure: {:?}", list);
+
+    [1] thread::spawn(move || {
+        [2] println!("From thread: {:?}", list)
+    }).join().unwrap();
+}
+```
+
+Listing 13-6: Using `move` to force the closure for the thread to take
+ownership of `list`
+
+We spawn a new thread, giving the thread a closure to run as an argument. The
+closure body prints out the list. In Listing 13-4, the closure only captured
+`list` using an immutable reference because that's the least amount of access
+to `list` needed to print it. In this example, even though the closure body
+still only needs an immutable reference, we need to specify that `list` should
+be moved into the closure by putting the `move` keyword at the beginning of the
+closure definition. The new thread might finish before the rest of the main
+thread finishes, or the main thread might finish first. If the main thread
+maintained ownership of `list` but ended before the new thread did and dropped
+`list`, the immutable reference in the thread would be invalid. Therefore, the
+compiler requires that `list` be moved into the closure given to the new thread
+so the reference will be valid. Try removing the `move` keyword or using `list`
+in the main thread after the closure is defined to see what compiler errors you
+get!
+
+### Moving Captured Values Out of Closures and the `Fn` Traits
+
+Once a closure has captured a reference or captured ownership of a value from
+the environment where the closure is defined (thus affecting what, if anything,
+is moved *into* the closure), the code in the body of the closure defines what
+happens to the references or values when the closure is evaluated later (thus
+affecting what, if anything, is moved *out of* the closure). A closure body can
+do any of the following: move a captured value out of the closure, mutate the
+captured value, neither move nor mutate the value, or capture nothing from the
+environment to begin with.
+
+The way a closure captures and handles values from the environment affects
+which traits the closure implements, and traits are how functions and structs
+can specify what kinds of closures they can use. Closures will automatically
+implement one, two, or all three of these `Fn` traits, in an additive fashion,
+depending on how the closure’s body handles the values:
+
+1. `FnOnce` applies to closures that can be called once. All closures implement
+   at least this trait, because all closures can be called. A closure that
+   moves captured values out of its body will only implement `FnOnce` and none
+   of the other `Fn` traits, because it can only be called once.
+2. `FnMut` applies to closures that don’t move captured values out of their
+   body, but that might mutate the captured values. These closures can be
+   called more than once.
+3. `Fn` applies to closures that don’t move captured values out of their body
+   and that don’t mutate captured values, as well as closures that capture
+   nothing from their environment. These closures can be called more than once
+   without mutating their environment, which is important in cases such as
+   calling a closure multiple times concurrently.
+
+Let’s look at the definition of the `unwrap_or_else` method on `Option<T>` that
+we used in Listing 13-1:
+
+```
+impl<T> Option<T> {
+    pub fn unwrap_or_else<F>(self, f: F) -> T
+    where
+        F: FnOnce() -> T
+    {
+        match self {
+            Some(x) => x,
+            None => f(),
+        }
+    }
+}
+```
+
+Recall that `T` is the generic type representing the type of the value in the
+`Some` variant of an `Option`. That type `T` is also the return type of the
+`unwrap_or_else` function: code that calls `unwrap_or_else` on an
+`Option<String>`, for example, will get a `String`.
+
+Next, notice that the `unwrap_or_else` function has the additional generic type
+parameter `F`. The `F` type is the type of the parameter named `f`, which is
+the closure we provide when calling `unwrap_or_else`.
+
+The trait bound specified on the generic type `F` is `FnOnce() -> T`, which
+means `F` must be able to be called once, take no arguments, and return a `T`.
+Using `FnOnce` in the trait bound expresses the constraint that
+`unwrap_or_else` is only going to call `f` at most one time. In the body of
+`unwrap_or_else`, we can see that if the `Option` is `Some`, `f` won’t be
+called. If the `Option` is `None`, `f` will be called once. Because all
+closures implement `FnOnce`, `unwrap_or_else` accepts the most different kinds
+of closures and is as flexible as it can be.
+
+> Note: Functions can implement all three of the `Fn` traits too. If what we
+> want to do doesn’t require capturing a value from the environment, we can use
+> the name of a function rather than a closure where we need something that
+> implements one of the `Fn` traits. For example, on an `Option<Vec<T>>` value,
+> we could call `unwrap_or_else(Vec::new)` to get a new, empty vector if the
+> value is `None`.
+
+Now let’s look at the standard library method `sort_by_key` defined on slices,
+to see how that differs from `unwrap_or_else` and why `sort_by_key` uses
+`FnMut` instead of `FnOnce` for the trait bound. The closure gets one argument
+in the form of a reference to the current item in the slice being considered,
+and returns a value of type `K` that can be ordered. This function is useful
+when you want to sort a slice by a particular attribute of each item. In
+Listing 13-7, we have a list of `Rectangle` instances and we use `sort_by_key`
+to order them by their `width` attribute from low to high:
+
+Filename: src/main.rs
+
+```
+#[derive(Debug)]
+struct Rectangle {
+    width: u32,
+    height: u32,
+}
+
+fn main() {
+    let mut list = [
+        Rectangle { width: 10, height: 1 },
+        Rectangle { width: 3, height: 5 },
+        Rectangle { width: 7, height: 12 },
+    ];
+
+    list.sort_by_key(|r| r.width);
+    println!("{:#?}", list);
+}
+```
+
+Listing 13-7: Using `sort_by_key` to order rectangles by width
+
+This code prints:
+
+```
+[
+    Rectangle {
+        width: 3,
+        height: 5,
+    },
+    Rectangle {
+        width: 7,
+        height: 12,
+    },
+    Rectangle {
+        width: 10,
+        height: 1,
+    },
+]
+```
+
+The reason `sort_by_key` is defined to take an `FnMut` closure is that it calls
+the closure multiple times: once for each item in the slice. The closure `|r|
+r.width` doesn’t capture, mutate, or move out anything from its environment, so
+it meets the trait bound requirements.
+
+In contrast, Listing 13-8 shows an example of a closure that implements just
+the `FnOnce` trait, because it moves a value out of the environment. The
+compiler won’t let us use this closure with `sort_by_key`:
+
+Filename: src/main.rs
+
+```
+#[derive(Debug)]
+struct Rectangle {
+    width: u32,
+    height: u32,
+}
+
+fn main() {
+    let mut list = [
+        Rectangle { width: 10, height: 1 },
+        Rectangle { width: 3, height: 5 },
+        Rectangle { width: 7, height: 12 },
+    ];
+
+    let mut sort_operations = vec![];
+    let value = String::from("by key called");
+
+    list.sort_by_key(|r| {
+        sort_operations.push(value);
+        r.width
+    });
+    println!("{:#?}", list);
+}
+```
+
+Listing 13-8: Attempting to use an `FnOnce` closure with `sort_by_key`
+
+This is a contrived, convoluted way (that doesn’t work) to try and count the
+number of times `sort_by_key` gets called when sorting `list`. This code
+attempts to do this counting by pushing `value`—a `String` from the closure’s
+environment—into the `sort_operations` vector. The closure captures `value`
+then moves `value` out of the closure by transferring ownership of `value` to
+the `sort_operations` vector. This closure can be called once; trying to call
+it a second time wouldn’t work because `value` would no longer be in the
+environment to be pushed into `sort_operations` again! Therefore, this closure
+only implements `FnOnce`. When we try to compile this code, we get this error
+that `value` can’t be moved out of the closure because the closure must
+implement `FnMut`:
+
+```
+error[E0507]: cannot move out of `value`, a captured variable in an `FnMut` closure
+  --> src/main.rs:18:30
+   |
+15 |       let value = String::from("by key called");
+   |           ----- captured outer variable
+16 |
+17 |       list.sort_by_key(|r| {
+   |  ______________________-
+18 | |         sort_operations.push(value);
+   | |                              ^^^^^ move occurs because `value` has type `String`, which does not implement the `Copy` trait
+19 | |         r.width
+20 | |     });
+   | |_____- captured by this `FnMut` closure
+```
+
+The error points to the line in the closure body that moves `value` out of the
+environment. To fix this, we need to change the closure body so that it doesn’t
+move values out of the environment. To count the number of times `sort_by_key`
+is called, keeping a counter in the environment and incrementing its value in
+the closure body is a more straightforward way to calculate that. The closure
+in Listing 13-9 works with `sort_by_key` because it is only capturing a mutable
+reference to the `num_sort_operations` counter and can therefore be called more
+than once:
+
+Filename: src/main.rs
+
+```
+#[derive(Debug)]
+struct Rectangle {
+    width: u32,
+    height: u32,
+}
+
+fn main() {
+    let mut list = [
+        Rectangle { width: 10, height: 1 },
+        Rectangle { width: 3, height: 5 },
+        Rectangle { width: 7, height: 12 },
+    ];
+
+    let mut num_sort_operations = 0;
+    list.sort_by_key(|r| {
+        num_sort_operations += 1;
+        r.width
+    });
+    println!("{:#?}, sorted in {num_sort_operations} operations", list);
+}
+```
+
+Listing 13-9: Using an `FnMut` closure with `sort_by_key` is allowed
+
+The `Fn` traits are important when defining or using functions or types that
+make use of closures. In the next section, we’ll discuss iterators. Many
+iterator methods take closure arguments, so keep these closure details in mind
+as we continue!
+
+## 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 13-10 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.
+
+```
+let v1 = vec![1, 2, 3];
+
+let v1_iter = v1.iter();
+```
+
+Listing 13-10: Creating an iterator
+
+The iterator is stored in the `v1_iter` variable. Once we’ve created an
+iterator, we can use it in a variety of ways. In Listing 3-5 in Chapter 3, we
+iterated over an array using a `for` loop to execute some code on each of its
+items. Under the hood this implicitly created and then consumed an iterator,
+but we glossed over how exactly that works until now.
+
+In the example in Listing 13-11, we separate the creation of the iterator from
+the use of the iterator in the `for` loop. 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.
+
+```
+let v1 = vec![1, 2, 3];
+
+let v1_iter = v1.iter();
+
+for val in v1_iter {
+    println!("Got: {}", val);
+}
+```
+
+Listing 13-11: 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:
+
+```
+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 13-12 demonstrates
+what values are returned from repeated calls to `next` on the iterator created
+from the vector.
+
+Filename: src/lib.rs
+
+```
+#[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 13-12: 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 13-13 has a
+test illustrating a use of the `sum` method:
+
+Filename: src/lib.rs
+
+```
+#[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 13-13: 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
+
+*Iterator adaptors* are methods defined on the `Iterator` trait that don’t
+consume the iterator. Instead, they produce different iterators by changing
+some aspect of the original iterator.
+
+Listing 13-17 shows an example of calling the iterator adaptor method `map`,
+which takes a closure to call on each item as the items are iterated through.
+The `map` method returns a new iterator that produces the modified items. The
+closure here creates a new iterator in which each item from the vector will be
+incremented by 1:
+
+Filename: src/main.rs
+
+```
+let v1: Vec<i32> = vec![1, 2, 3];
+
+v1.iter().map(|x| x + 1);
+```
+
+Listing 13-14: Calling the iterator adaptor `map` to create a new iterator
+
+However, this code produces a warning:
+
+```
+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
+```
+
+The code in Listing 13-14 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 warning 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 13-15, 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
+
+```
+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 13-15: 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.
+
+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.
+
+### Using Closures that Capture Their Environment
+
+Many iterator adapters take closures as arguments, and commonly the closures
+we’ll specify as arguments to iterator adapters will be closures that capture
+their environment.
+
+For this example, we’ll use the `filter` method that takes a closure. The
+closure gets an item from the iterator and returns a `bool`. If the closure
+returns `true`, the value will be included in the iteration produced by
+`filter`. If the closure returns `false`, the value won’t be included.
+
+In Listing 13-16, 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 13-16: 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.
+
+## Improving Our I/O Project
+
+With this new knowledge about iterators, we can improve the I/O project in
+Chapter 12 by using iterators to make places in the code clearer and more
+concise. Let’s look at how iterators can improve our implementation of the
+`Config::build` function and the `search` function.
+
+### Removing a `clone` Using an Iterator
+
+In Listing 12-6, we added code that took a slice of `String` values and created
+an instance of the `Config` struct by indexing into the slice and cloning the
+values, allowing the `Config` struct to own those values. In Listing 13-17,
+we’ve reproduced the implementation of the `Config::build` function as it was
+in Listing 12-23:
+
+Filename: src/lib.rs
+
+```
+impl Config {
+    pub fn build(args: &[String]) -> Result<Config, &'static str> {
+        if args.len() < 3 {
+            return Err("not enough arguments");
+        }
+
+        let query = args[1].clone();
+        let file_path = args[2].clone();
+
+        let ignore_case = env::var("IGNORE_CASE").is_ok();
+
+        Ok(Config {
+            query,
+            file_path,
+            ignore_case,
+        })
+    }
+}
+```
+
+Listing 13-17: Reproduction of the `Config::build` function from Listing 12-23
+
+At the time, we said not to worry about the inefficient `clone` calls because
+we would remove them in the future. Well, that time is now!
+
+We needed `clone` here because we have a slice with `String` elements in the
+parameter `args`, but the `build` function doesn’t own `args`. To return
+ownership of a `Config` instance, we had to clone the values from the `query`
+and `filename` fields of `Config` so the `Config` instance can own its values.
+
+With our new knowledge about iterators, we can change the `build` function to
+take ownership of an iterator as its argument instead of borrowing a slice.
+We’ll use the iterator functionality instead of the code that checks the length
+of the slice and indexes into specific locations. This will clarify what the
+`Config::build` function is doing because the iterator will access the values.
+
+Once `Config::build` takes ownership of the iterator and stops using indexing
+operations that borrow, we can move the `String` values from the iterator into
+`Config` rather than calling `clone` and making a new allocation.
+
+#### Using the Returned Iterator Directly
+
+Open your I/O project’s *src/main.rs* file, which should look like this:
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let args: Vec<String> = env::args().collect();
+
+    let config = Config::build(&args).unwrap_or_else(|err| {
+        eprintln!("Problem parsing arguments: {err}");
+        process::exit(1);
+    });
+
+    // --snip--
+}
+```
+
+We’ll first change the start of the `main` function that we had in Listing
+12-24 to the code in Listing 13-18, which this time uses an iterator. This
+won’t compile until we update `Config::build` as well.
+
+Filename: src/main.rs
+
+```
+fn main() {
+    let config = Config::build(env::args()).unwrap_or_else(|err| {
+        eprintln!("Problem parsing arguments: {err}");
+        process::exit(1);
+    });
+
+    // --snip--
+}
+```
+
+Listing 13-18: Passing the return value of `env::args` to `Config::build`
+
+The `env::args` function returns an iterator! Rather than collecting the
+iterator values into a vector and then passing a slice to `Config::build`, now
+we’re passing ownership of the iterator returned from `env::args` to
+`Config::build` directly.
+
+Next, we need to update the definition of `Config::build`. In your I/O
+project’s *src/lib.rs* file, let’s change the signature of `Config::build` to
+look like Listing 13-19. This still won’t compile because we need to update the
+function body.
+
+Filename: src/lib.rs
+
+```
+impl Config {
+    pub fn build(
+        mut args: impl Iterator<Item = String>,
+    ) -> Result<Config, &'static str> {
+        // --snip--
+```
+
+Listing 13-19: Updating the signature of `Config::build` to expect an iterator
+
+The standard library documentation for the `env::args` function shows that the
+type of the iterator it returns is `std::env::Args`, and that type implements
+the `Iterator` trait and returns `String` values.
+
+We’ve updated the signature of the `Config::build` function so the parameter
+`args` has a generic type with the trait bounds `impl Iterator<Item = String>`
+instead of `&[String]`. This usage of the `impl Trait` syntax we discussed in
+the “Traits as Parameters” section of Chapter 10 means that `args` can be any
+type that implements the `Iterator` type and returns `String` items.
+
+Because we’re taking ownership of `args` and we’ll be mutating `args` by
+iterating over it, we can add the `mut` keyword into the specification of the
+`args` parameter to make it mutable.
+
+#### Using `Iterator` Trait Methods Instead of Indexing
+
+Next, we’ll fix the body of `Config::build`. Because `args` implements the
+`Iterator` trait, we know we can call the `next` method on it! Listing 13-20
+updates the code from Listing 12-23 to use the `next` method:
+
+Filename: src/lib.rs
+
+```
+impl Config {
+    pub fn build(
+        mut args: impl Iterator<Item = String>,
+    ) -> Result<Config, &'static str> {
+        args.next();
+
+        let query = match args.next() {
+            Some(arg) => arg,
+            None => return Err("Didn't get a query string"),
+        };
+
+        let file_path = match args.next() {
+            Some(arg) => arg,
+            None => return Err("Didn't get a file path"),
+        };
+
+        let ignore_case = env::var("IGNORE_CASE").is_ok();
+
+        Ok(Config {
+            query,
+            file_path,
+            ignore_case,
+        })
+    }
+}
+```
+
+Listing 13-20: Changing the body of `Config::build` to use iterator methods
+
+Remember that the first value in the return value of `env::args` is the name of
+the program. We want to ignore that and get to the next value, so first we call
+`next` and do nothing with the return value. Second, we call `next` to get the
+value we want to put in the `query` field of `Config`. If `next` returns a
+`Some`, we use a `match` to extract the value. If it returns `None`, it means
+not enough arguments were given and we return early with an `Err` value. We do
+the same thing for the `filename` value.
+
+### Making Code Clearer with Iterator Adaptors
+
+We can also take advantage of iterators in the `search` function in our I/O
+project, which is reproduced here in Listing 13-21 as it was in Listing 12-19:
+
+Filename: src/lib.rs
+
+```
+pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
+    let mut results = Vec::new();
+
+    for line in contents.lines() {
+        if line.contains(query) {
+            results.push(line);
+        }
+    }
+
+    results
+}
+```
+
+Listing 13-21: The implementation of the `search` function from Listing 12-19
+
+We can write this code in a more concise way using iterator adaptor methods.
+Doing so also lets us avoid having a mutable intermediate `results` vector. The
+functional programming style prefers to minimize the amount of mutable state to
+make code clearer. Removing the mutable state might enable a future enhancement
+to make searching happen in parallel, because we wouldn’t have to manage
+concurrent access to the `results` vector. Listing 13-22 shows this change:
+
+Filename: src/lib.rs
+
+```
+pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
+    contents
+        .lines()
+        .filter(|line| line.contains(query))
+        .collect()
+}
+```
+
+Listing 13-22: Using iterator adaptor methods in the implementation of the
+`search` function
+
+Recall that the purpose of the `search` function is to return all lines in
+`contents` that contain the `query`. Similar to the `filter` example in Listing
+13-16, this code uses the `filter` adaptor to keep only the lines that
+`line.contains(query)` returns `true` for. We then collect the matching lines
+into another vector with `collect`. Much simpler! Feel free to make the same
+change to use iterator methods in the `search_case_insensitive` function as
+well.
+
+### Choosing Between Loops or Iterators
+
+The next logical question is which style you should choose in your own code and
+why: the original implementation in Listing 13-21 or the version using
+iterators in Listing 13-22. Most Rust programmers prefer to use the iterator
+style. It’s a bit tougher to get the hang of at first, but once you get a feel
+for the various iterator adaptors and what they do, iterators can be easier to
+understand. Instead of fiddling with the various bits of looping and building
+new vectors, the code focuses on the high-level objective of the loop. This
+abstracts away some of the commonplace code so it’s easier to see the concepts
+that are unique to this code, such as the filtering condition each element in
+the iterator must pass.
+
+But are the two implementations truly equivalent? The intuitive assumption
+might be that the more low-level loop will be faster. Let’s talk about
+performance.
+
+## Comparing Performance: Loops vs. Iterators
+
+To determine whether to use loops or iterators, you need to know which
+implementation is faster: the version of the `search` function with an explicit
+`for` loop or the version with iterators.
+
+We ran a benchmark by loading the entire contents of *The Adventures of
+Sherlock Holmes* by Sir Arthur Conan Doyle into a `String` and looking for the
+word *the* in the contents. Here are the results of the benchmark on the
+version of `search` using the `for` loop and the version using iterators:
+
+```
+test bench_search_for  ... bench:  19,620,300 ns/iter (+/- 915,700)
+test bench_search_iter ... bench:  19,234,900 ns/iter (+/- 657,200)
+```
+
+The iterator version was slightly faster! We won’t explain the benchmark code
+here, because the point is not to prove that the two versions are equivalent
+but to get a general sense of how these two implementations compare
+performance-wise.
+
+For a more comprehensive benchmark, you should check using various texts of
+various sizes as the `contents`, different words and words of different lengths
+as the `query`, and all kinds of other variations. The point is this:
+iterators, although a high-level abstraction, get compiled down to roughly the
+same code as if you’d written the lower-level code yourself. Iterators are one
+of Rust’s *zero-cost abstractions*, by which we mean using the abstraction
+imposes no additional runtime overhead. This is analogous to how Bjarne
+Stroustrup, the original designer and implementor of C++, defines
+*zero-overhead* in “Foundations of C++” (2012):
+
+> In general, C++ implementations obey the zero-overhead principle: What you
+> don’t use, you don’t pay for. And further: What you do use, you couldn’t hand
+> code any better.
+
+As another example, the following code is taken from an audio decoder. The
+decoding algorithm uses the linear prediction mathematical operation to
+estimate future values based on a linear function of the previous samples. This
+code uses an iterator chain to do some math on three variables in scope: a
+`buffer` slice of data, an array of 12 `coefficients`, and an amount by which
+to shift data in `qlp_shift`. We’ve declared the variables within this example
+but not given them any values; although this code doesn’t have much meaning
+outside of its context, it’s still a concise, real-world example of how Rust
+translates high-level ideas to low-level code.
+
+```
+let buffer: &mut [i32];
+let coefficients: [i64; 12];
+let qlp_shift: i16;
+
+for i in 12..buffer.len() {
+    let prediction = coefficients.iter()
+                                 .zip(&buffer[i - 12..i])
+                                 .map(|(&c, &s)| c * s as i64)
+                                 .sum::<i64>() >> qlp_shift;
+    let delta = buffer[i];
+    buffer[i] = prediction as i32 + delta;
+}
+```
+
+To calculate the value of `prediction`, this code iterates through each of the
+12 values in `coefficients` and uses the `zip` method to pair the coefficient
+values with the previous 12 values in `buffer`. Then, for each pair, we
+multiply the values together, sum all the results, and shift the bits in the
+sum `qlp_shift` bits to the right.
+
+Calculations in applications like audio decoders often prioritize performance
+most highly. Here, we’re creating an iterator, using two adaptors, and then
+consuming the value. What assembly code would this Rust code compile to? Well,
+as of this writing, it compiles down to the same assembly you’d write by hand.
+There’s no loop at all corresponding to the iteration over the values in
+`coefficients`: Rust knows that there are 12 iterations, so it “unrolls” the
+loop. *Unrolling* is an optimization that removes the overhead of the loop
+controlling code and instead generates repetitive code for each iteration of
+the loop.
+
+All of the coefficients get stored in registers, which means accessing the
+values is very fast. There are no bounds checks on the array access at runtime.
+All these optimizations that Rust is able to apply make the resulting code
+extremely efficient. Now that you know this, you can use iterators and closures
+without fear! They make code seem like it’s higher level but don’t impose a
+runtime performance penalty for doing so.
+
+## Summary
+
+Closures and iterators are Rust features inspired by functional programming
+language ideas. They contribute to Rust’s capability to clearly express
+high-level ideas at low-level performance. The implementations of closures and
+iterators are such that runtime performance is not affected. This is part of
+Rust’s goal to strive to provide zero-cost abstractions.
+
+Now that we’ve improved the expressiveness of our I/O project, let’s look at
+some more features of `cargo` that will help us share the project with the
+world.