13 Functional Language Features Iterators and Closures

13-1 Closures Anonymous Functions

Rust’s closures are anonymous functions you can save in a variable or pass as arguments to other functions. We want to define code in one place in our program, but only execute that code where we actually need the result. This is a use case for closures!

13-1-1 Creating an Abstraction of Behavior with Closures

We can define a closure and store the closure in a variable rather than storing the result of the function call:

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fn generate_workout(intensity: u32, random_number: u32) {
    // do not excute here
    let expensive_closure = |num| {
        println!("calculating slowly...");
        thread::sleep(Duration::from_secs(2));
        num
    };

    if intensity < 25 {
        println!(
            "Today, do {} pushups!",
            expensive_closure(intensity)
        );
        println!(
            "Next, do {} situps!",
            expensive_closure(intensity)
        );
    } else {
        if random_number == 3 {
            println!("Take a break today! Remember to stay hydrated!");
        } else {
            println!(
                "Today, run for {} minutes!",
                expensive_closure(intensity)
            );
        }
    }
}

Note that this let statement means expensive_closure contains the definition of an anonymous function, not the resulting value of calling the anonymous function.

Now the expensive calculation is called in only one place, and we’re only executing that code where we need the results.

However, we’re still calling the closure twice in the first if block, which will call the expensive code twice and make the user wait twice as long as they need to.

13-1-2 Closure Type Inference and Annotation

Closures don’t require you to annotate the types of the parameters or the return value like fn functions do. Type annotations are required on functions because they’re 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. But closures 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.

13-1-3 Storing Closures Using Generic Parameters and the Fn Traits

For the problem (still calling the closure twice in the first if block) before, we can create a struct that will hold the closure and the resulting value of calling the closure. The struct will execute the closure only if we need the resulting value, and it will cache the resulting value so the rest of our code doesn’t have to be responsible for saving and reusing the result. You may know this pattern as memoization or lazy evaluation.

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struct Cacher<T>
    where T: Fn(u32) -> u32
{
    calculation: T,
    value: Option<u32>,
}

The Cacher struct has a calculation field of the generic type T. The trait bounds on T specify that it’s a closure by using the Fn trait. Any closure we want to store in the calculation field must have one u32 parameter (specified within the parentheses after Fn) and must return a u32(specified after the ->).

The value field is of type Option<u32>. Before we execute the closure, value will be None. When code using a Cacher asks for the result of the closure, the Cacher will execute the closure at that time and store the result within a Some variant in the value field. Then if the code asks for the result of the closure again, instead of executing the closure again, the Cacher will return the result held in the Some variant.

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impl<T> Cacher<T>
    where T: Fn(u32) -> u32
{
    fn new(calculation: T) -> Cacher<T> {
        Cacher {
            calculation,
            value: None,
        }
    }

    fn value(&mut self, arg: u32) -> u32 {
        match self.value {
            Some(v) => v,
            None => {
                let v = (self.calculation)(arg);
                self.value = Some(v);
                v
            },
        }
    }
}

fn generate_workout(intensity: u32, random_number: u32) {
    let mut expensive_result = Cacher::new(|num| {
        println!("calculating slowly...");
        thread::sleep(Duration::from_secs(2));
        num
    });

    if intensity < 25 {
        println!(
            "Today, do {} pushups!",
            expensive_result.value(intensity)
        );
        println!(
            "Next, do {} situps!",
            expensive_result.value(intensity)
        );
    } else {
        if random_number == 3 {
            println!("Take a break today! Remember to stay hydrated!");
        } else {
            println!(
                "Today, run for {} minutes!",
                expensive_result.value(intensity)
            );
        }
    }
}

Instead of saving the closure in a variable directly, we save a new instance of Cacher that holds the closure. Then, in each place we want the result, we call the value method on the Cacher instance. We can call the value method as many times as we want, or not call it at all, and the expensive calculation will be run a maximum of once.

13-1-4 Limitations of the Cacher Implementation

The first problem is that a Cacher instance assumes it will always get the same value for the parameter arg to the value method. Try modifying Cacher to hold a hash map rather than a single value. The keys of the hash map will be the arg values that are passed in, and the values of the hash map will be the result of calling the closure on that key. Instead of looking at whether self.value directly has a Some or a None value, the value function will look up the arg in the hash map and return the value if it’s present. If it’s not present, the Cacher will call the closure and save the resulting value in the hash map associated with its arg value.

The second problem with the current Cacher implementation is that it only accepts closures that take one parameter of type u32 and return a u32. We might want to cache the results of closures that take a string slice and return usize values, for example. To fix this issue, try introducing more generic parameters to increase the flexibility of the Cacher functionality.

13-1-5 Capturing the Environment with Closures

Closures have an additional capability that functions don’t have: they can capture their environment and access variables from the scope in which they’re defined.

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fn main() {
    let x = 4;

    let equal_to_x = |z| z == x;

    let y = 4;

    assert!(equal_to_x(y));
}

fn main() {
    let x = 4;
	// function
    fn equal_to_x(z: i32) -> bool { z == x }

    let y = 4;

    assert!(equal_to_x(y));
}
// can't capture dynamic environment in a fn item; use the || { ...} closure form instead

Closures can capture values from their environment in three ways, which directly map to the three ways a function can take a parameter: taking ownership, borrowing mutably, and borrowing immutably. These are encoded in the three Fn traits as follows:

• FnOnce consumes the variables it captures from its enclosing scope, known as the closure’s environment. To consume the captured variables, the closure must take ownership of these variables and move them into the closure when it is defined. The Once part of the name represents the fact that the closure can’t take ownership of the same variables more than once, so it can be called only once.
• FnMut can change the environment because it mutably borrows values.
• Fn borrows values from the environment immutably.

When you create a closure, Rust infers which trait to use based on how the closure uses the values from the environment. All closures implement FnOnce because they can all be called at least once. Closures that don’t move the captured variables also implement FnMut, and closures that don’t need mutable access to the captured variables also implement Fn.

If you want to force the closure to take ownership of the values it uses in the environment, 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 it’s owned by the new thread.

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

    let equal_to_x = move |z| z == x;

    println!("can't use x here: {:?}", x);

    let y = vec![1, 2, 3];

    assert!(equal_to_x(y));
}

The x value is moved into the closure when the closure is defined, because we added the move keyword. The closure then has ownership of x, and main isn’t allowed to use x anymore in the println! statement. Removing println! will fix this example.

Most of the time when specifying one of the Fn trait bounds, you can start with Fn and the compiler will tell you if you need FnMut or FnOnce based on what happens in the closure body.

13-2 Processing a Series of Items with Iterators

In Rust, iterators are lazy, meaning they have no effect until you call methods that consume the iterator to use it up.

13-2-1 The Iterator Trait and the Next Method

All iterators implement a trait named Iterator that is defined in the standard library.

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trait Iterator {
    type Item;

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

    // methods with default implementations elided
}

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#[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);
}

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.

13-2-2 Methods that Consume the Iterator

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#[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);
}

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

13-2-3 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.

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let v1: Vec<i32> = vec![1, 2, 3];

v1.iter().map(|x| x + 1);
// warning: unused `std::iter::Map` which must be used: iterator adaptors are lazy and do nothing unless consumed

This code 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.

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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]);
// collect consumes the iterator and collects the resulting values into a collection data type.

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.

13-2-4 Using Closures that Capture Their Environment

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

fn shoes_in_my_size(shoes: Vec<Shoe>, shoe_size: u32) -> Vec<Shoe> {
    // filter to adapt that iterator 
    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") },
        ]
    );
}

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.

13-2-5 Creating Our Own Iterators with the Iterator Trait

You can 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!

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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> {
        self.count += 1;

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

13-2-5-1 Using Our Counter Iterator’s next method

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#[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);
}

13-2-5-2 Using Other Iterator Trait Methods

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#[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);
}

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.

13-3 Improving Our IO Project

13-3-1 Removing a clone Using an Iterator

The IO project can be found here, clone is used to make the Config own the values.

Here we change the new function to take ownership of an iterator as its argument instead of borrowing a slice.

13-3-1-1 Using the Returned Iterator Directly

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// modify the src/main.rs
fn main() {
	let config = Config::new(env::args()).unwrap_or_else(|err| {
        eprintln!("Problem parsing arguments: {}", err);
        process::exit(1);
    }
}

The env::args() function returns an iterator! Rather than collecting the iterator values into a vector and then passing a slice to Config::new.

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// update src/lib.rs
impl Config {
    pub fn new(mut args: std::env::Args) -> Result<Config, &'static str> {
        // --snip--

The standard library documentation for the env::args function shows that the type of the iterator it returns is std::env::Args. 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.

13-3-1-2 Using Iterator Trait Methods Instead of Indexing

The standard library documentation also mentions that std::env::Args implements the Iterator trait, so we know we can call the next method on it!

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impl Config {
	pub fn new(mut args: std::env::Args) -> Result<Config, &'static str> {
        // the first value in the return value of env::args is the name of the program.
    	args.next();
        let query = match args.next() {
        	Some(arg) => arg,
            None => return Err("Didn't get a query string"),
        };
        let filename = match args.next() {
        	Some(arg) => arg,
            None => return Err("Didn't get a file name"),
        };
        let case_sensitive = env::var("CASE_INSENSITIVE").is_err();
        Ok(Config {query, filename, case_sensitive})
    }
}

13-3-2 Making Code Clearer with Iterator Adaptors

We can write the search 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.

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pub fn search<'a>(query: &str, contents: &'a str) -> Vec<&'a str> {
	contents.lines()
    	.filter(|line| line.contains(query))
    	.collect()
}

13.4 Comparing Performance: Loop vs. Iterators

The iterator version was slightly faster! 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.

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// another example
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;
}

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.

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.

17 Object Oriented Programming Features of Rust

17-1 Characteristics of Object-Oriented Languages

17-1-1 Objects Contain Data and Behavior

Rust is object oriented: structs and enums have data, and impl blocks provide methods on structs and enums.

17-1-2 Encapsulation that Hides Implementation Details

Rust uses the pub keyword to decide which modules, types, functions, and methods in our code should be public, and by default everything else is private.

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pub struct AveragedCollection {
    list: Vec<i32>,
    average: f64,
}

The struct is marked pub so that other code can use it, but the fields within the struct remain private.

This is important in this case because we want to ensure that whenever a value is added or removed from the list, the average is also updated. We do this by implementing add, remove, and average methods on the struct.

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imple AveragedCollection {
	pub fn add(&mut self, value: i32) {
    	self.list.push(value);
        self.update_average();
    }
    
    pub fn remove(&mut self) -> Option<i32> {
    	let result = self.list.pop();
        match result {
        	Some(value) => {
            	self.update_average();
                Some(value);
            },
            None => None,
        }
    }
    
    pub fn average(&self) -> f64 {
    	self.average
    }
    
    pub fn update_average(&mut self) {
    	let total: i32 = self.list.iter().sum();
        self.average = total as f64 / self.list.len() as f64;
    }
}

The public methods add, remove, and average are the only ways to access or modify data in an instance of AveragedCollection.

We leave the list and average fields private so there is no way for external code to add or remove items to the list field directly; otherwise, the average field might become out of sync when the list changes. The average method returns the value in the average field, allowing external code to read the average but not modify it.

17-1-3 Inheritance as a Type System and as Code Sharing

If a language must have inheritance to be an object-oriented language, then Rust is not one. There is no way to define a struct that inherits the parent struct’s fields and method implementations. However you can use other solutions in Rust, depending on your reason for reaching for inheritance in the first place.

You choose inheritance for two main reasons.

• One is for reuse of code: you can implement particular behavior for one type, and inheritance enables you to reuse that implementation for a different type. You can share Rust code using default trait method implementations instead.
• The other reason to use inheritance relates to the type system: to enable a child type to be used in the same places as the parent type. This is also called polymorphism, which means that you can substitute multiple objects for each other at runtime if they share certain characteristics. Rust instead uses generics to abstract over different possible types and trait bounds to impose constraints on what those types must provide. This is sometimes called bounded parametric polymorphism.

17-2 Using Trait Objects That Allows for Values of Different Types

We could define an enum that had variants to hold different types, so a vector could store different types of data in each cell.

The case: In a language with inheritance, we might define a class named Component that has a method named draw on it. The other classes, such as Button, Image, and SelectBox, would inherit from Component and thus inherit the draw method. They could each override the draw method to define their custom behavior, but the framework could treat all of the types as if they were Component instances and call draw on them.

17-2-1 Defining a Trait for Common Behavior

Trait objects are more like objects in other languages in the sense that they combine data and behavior. But trait objects differ from traditional objects in that we can’t add data to a trait object.

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pub trait Draw {
    fn draw(&self);
}

Next, this vector is of type Box, which is a trait object; it’s a stand-in for any type inside a Box that implements the Draw trait.

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pub struct Screen {
	pub components: Vec<Box<dyn Draw>>,
}

impl Screen {
    pub fn run(&self) {
        for component in self.components.iter() {
            component.draw();
        }
    }
}

This works differently from defining a struct that uses a generic type parameter with trait bounds. A generic type parameter can only be substituted with one concrete type at a time, whereas trait objects allow for multiple concrete types to fill in for the trait object at runtime. For example, we could have defined the Screen struct using a generic type and a trait bound.

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pub struct Screen<T: Draw> {
    pub components: Vec<T>,
}

impl<T> Screen<T>
    where T: Draw {
    pub fn run(&self) {
        for component in self.components.iter() {
            component.draw();
        }
    }
}

This restricts us to a Screen instance that has a list of components all of type Button or all of type TextField. If you’ll only ever have homogeneous collections, using generics and trait bounds is preferable because the definitions will be monomorphized at compile time to use the concrete types.

On the other hand, with the method using trait objects, one Screen instance can hold a Vec that contains a Box<Button> as well as a Box<TextField>.

17-2-2 Implementing the Trait

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pub struct Button {
    pub width: u32,
    pub height: u32,
    pub label: String,
}

impl Draw for Button {
    fn draw(&self) {
        // code to actually draw a button
    }
}

use gui::Draw;

struct SelectBox {
    width: u32,
    height: u32,
    options: Vec<String>,
}

impl Draw for SelectBox {
    fn draw(&self) {
        // code to actually draw a select box
    }
}

Our library’s user can now write their main function to create a Screen instance.

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use gui::{Screen, Button};

fn main() {
    let screen = Screen {
        components: vec![
            Box::new(SelectBox {
                width: 75,
                height: 10,
                options: vec![
                    String::from("Yes"),
                    String::from("Maybe"),
                    String::from("No")
                ],
            }),
            Box::new(Button {
                width: 50,
                height: 10,
                label: String::from("OK"),
            }),
        ],
    };

    screen.run();
}

The code can be found here.

When we wrote the library, we didn’t know that someone might add the SelectBox type, but our Screen implementation was able to operate on the new type and draw it because SelectBox implements the Draw trait, which means it implements the draw method.

This concept—of being concerned only with the messages a value responds to rather than the value’s concrete type—is similar to the concept duck typing in dynamically typed languages: if it walks like a duck and quacks like a duck, then it must be a duck! In the implementation of run on Screen, run doesn’t need to know what the concrete type of each component is. It doesn’t check whether a component is an instance of a Button or a SelectBox, it just calls the draw method on the component. By specifying Box as the type of the values in the components vector, we’ve defined Screen to need values that we can call the draw method on.

The advantage of using trait objects and Rust’s type system to write code similar to code using duck typing is that we never have to check whether a value implements a particular method at runtime or worry about getting errors if a value doesn’t implement a method but we call it anyway.

17-2-3 Trait Objects Perform Dynamic Dispatch

When we use trait objects, Rust must use dynamic dispatch.

• The compiler doesn’t know all the types that might be used with the code that is using trait objects, so it doesn’t know which method implemented on which type to call.
• Instead, at runtime, Rust uses the pointers inside the trait object to know which method to call. There is a runtime cost when this lookup happens that doesn’t occur with static dispatch.
• Dynamic dispatch also prevents the compiler from choosing to inline a method’s code, which in turn prevents some optimizations.

17-2-4 Object Safety Is Required for Trait Objects

You can only make object-safe traits into trait objects. A trait is object safe if all the methods defined in the trait have the following properties:

• The return type isn’t Self
• There are no generic type parameters

Trait objects must be object safe because once you’ve used a trait object, Rust no longer knows the concrete type that’s implementing that trait.

• If a trait method returns the concrete Self type, but a trait object forgets the exact type that Self is, there is no way the method can use the original concrete type.
• The same is true of generic type parameters that are filled in with concrete type parameters when the trait is used: the concrete types become part of the type that implements the trait. When the type is forgotten through the use of a trait object, there is no way to know what types to fill in the generic type parameters with.

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pub struct Screen {
    pub components: Vec<Box<dyn Clone>>,
}
// error[E0038]: the trait `std::clone::Clone` cannot be made into an object

This error means you can’t use this trait as a trait object in this way.

17-3 Implementing an Object-Oriented Design Pattern

The state pattern is an object-oriented design pattern. The crux of the pattern is that a value has some internal state, which is represented by a set of state objects, and the value’s behavior changes based on the internal state.

We’ll implement a blog post workflow in an incremental way. The blog’s final functionality will look like this:

1. A blog post starts as an empty draft.
2. When the draft is done, a review of the post is requested.
3. When the post is approved, it gets published.
4. Only published blog posts return content to print, so unapproved posts can’t accidentally be published.

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use blog::Post;

fn main() {
    let mut post = Post::new();

    post.add_text("I ate a salad for lunch today");
    assert_eq!("", post.content());

    post.request_review();
    assert_eq!("", post.content());

    post.approve();
    assert_eq!("I ate a salad for lunch today", post.content());
}

Notice that the only type we’re interacting with from the crate is the Post type.

• This type will use the state pattern and will hold a value that will be one of three state objects representing the various states a post can be in—draft, waiting for review, or published.
• Changing from one state to another will be managed internally within the Post type. The states change in response to the methods called by our library’s users on the Post instance, but they don’t have to manage the state changes directly.
• Also, users can’t make a mistake with the states, like publishing a post before it’s reviewed.

17-3-1 Defining Post and Creating a New Instance in the Draft State

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pub struct Post {
    state: Option<Box<dyn State>>,
    content: String,
}

impl Post {
    pub fn new() -> Post {
        Post {
            state: Some(Box::new(Draft {})),
            content: String::new(),
        }
    }
}

trait State {}

struct Draft {}

impl State for Draft {}

The State trait defines the behavior shared by different post states, and the Draft, PendingReview, and Published states will all implement the State trait.

When we create a new Post, we set its state field to a Some value that holds a Box. This Box points to a new instance of the Draft struct. This ensures whenever we create a new instance of Post, it will start out as a draft. Because the state field of Post is private, there is no way to create a Post in any other state!

17-3-2 Storing the Text of the Post Content

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impl Post {
    // --snip--
    pub fn add_text(&mut self, text: &str) {
        self.content.push_str(text);
    }
}

This behavior doesn’t depend on the state the post is in, so it’s not part of the state pattern.

17-3-3 Ensuring the Content of a Draft Post Is Empty

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impl Post {
    // --snip--
    pub fn content(&self) -> &str {
        ""
    }
}

Adding a placeholder implementation for the content method on Post that always returns an empty string slice.

17-3-4 Requesting a Review of the Post Changes Its State

Add functionality to request a review of a post, which should change its state from Draft to PendingReview.

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impl Post {
    // --snip--
    pub fn request_review(&mut self) {
        if let Some(s) = self.state.take() {
            self.state = Some(s.request_review())
        }
    }
}

trait State {
    fn request_review(self: Box<Self>) -> Box<dyn State>;
}

struct Draft {}

impl State for Draft {
    fn request_review(self: Box<Self>) -> Box<dyn State> {
        Box::new(PendingReview {})
    }
}

struct PendingReview {}

impl State for PendingReview {
    fn request_review(self: Box<Self>) -> Box<dyn State> {
        self
    }
}

17-3-5 Adding the approve Method that Changes the Behavior of content

It will set state to the value that the current state says it should have when that state is approved.

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impl Post {
    // --snip--
    pub fn approve(&mut self) {
        if let Some(s) = self.state.take() {
            self.state = Some(s.approve())
        }
    }
}

trait State {
    fn request_review(self: Box<Self>) -> Box<dyn State>;
    fn approve(self: Box<Self>) -> Box<dyn State>;
}

struct Draft {}

impl State for Draft {
    // --snip--
    fn approve(self: Box<Self>) -> Box<dyn State> {
        self
    }
}

struct PendingReview {}

impl State for PendingReview {
    // --snip--
    fn approve(self: Box<Self>) -> Box<dyn State> {
        Box::new(Published {})
    }
}

struct Published {}

impl State for Published {
    fn request_review(self: Box<Self>) -> Box<dyn State> {
        self
    }

    fn approve(self: Box<Self>) -> Box<dyn State> {
        self
    }
}

Because the goal is to keep all these rules inside the structs that implement State, we call a content method on the value in state and pass the post instance (that is, self) as an argument. Then we return the value that is returned from using the content method on the state value.

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impl Post {
    // --snip--
    pub fn content(&self) -> &str {
        self.state.as_ref().unwrap().content(self)
    }
    // --snip--
}

We call the as_ref method on the Option because we want a reference to the value inside the Option rather than ownership of the value. Because state is an <Option>, when we call as_ref, an Option<&Box> is returned. If we didn’t call as_ref, we would get an error because we can’t move state out of the borrowed &self of the function parameter.

We then call the unwrap method, which we know will never panic, because we know the methods on Post ensure that state will always contain a Some value when those methods are done. A None value is never possible, even though the compiler isn’t able to understand that.

At this point, when we call content on the &Box, deref coercion will take effect on the & and the Box so the content method will ultimately be called on the type that implements the State trait. That means we need to add content to the State trait definition.

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trait State {
    // --snip--
    fn content<'a>(&self, post: &'a Post) -> &'a str {
        ""
    }
}

// --snip--
struct Published {}

impl State for Published {
    // --snip--
    fn content<'a>(&self, post: &'a Post) -> &'a str {
        &post.content
    }
}

We add a default implementation for the content method that returns an empty string slice. That means we don’t need to implement content on the Draft and PendingReview structs. The Published struct will override the content method and return the value in post.content.

Note that we need lifetime annotations on this method. We’re taking a reference to a post as an argument and returning a reference to part of that post, so the lifetime of the returned reference is related to the lifetime of the post argument.

The code can be found here.

17-3-6 Trade-offs of the State Pattern

Rust is capable of implementing the object-oriented state pattern to encapsulate the different kinds of behavior a post should have in each state. The methods on Post know nothing about the various behaviors.

If we were to create an alternative implementation that didn’t use the state pattern, we might instead use match expressions in the methods on Post or even in the main code that checks the state of the post and changes behavior in those places. That would mean we would have to look in several places to understand all the implications of a post being in the published state! This would only increase the more states we added: each of those match expressions would need another arm.

With the state pattern, the Post methods and the places we use Post don’t need match expressions, and to add a new state, we would only need to add a new struct and implement the trait methods on that one struct.

One downside of the state pattern is that, because the states implement the transitions between states, some of the states are coupled to each other.

Another downside is that we’ve duplicated some logic. To eliminate some of the duplication, we might try to make default implementations for the request_review and approve methods on the State trait that return self; however, this would violate object safety, because the trait doesn’t know what the concrete self will be exactly. We want to be able to use State as a trait object, so we need its methods to be object safe.

17-3-6-1 Encoding States and Behavior as Types

Rather than encapsulating the states and transitions completely so outside code has no knowledge of them, we’ll encode the states into different types. Consequently, Rust’s type checking system will prevent attempts to use draft posts where only published posts are allowed by issuing a compiler error.

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fn main() {
    let mut post = Post::new();

    post.add_text("I ate a salad for lunch today");
    assert_eq!("", post.content());
}

Instead of having a content method on a draft post that returns an empty string, we’ll make it so draft posts don’t have the content method at all.

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pub struct Post {
    content: String,
}

pub struct DraftPost {
    content: String,
}

impl Post {
    pub fn new() -> DraftPost {
        DraftPost {
            content: String::new(),
        }
    }

    pub fn content(&self) -> &str {
        &self.content
    }
}

impl DraftPost {
    pub fn add_text(&mut self, text: &str) {
        self.content.push_str(text);
    }
}

Now the program ensures all posts start as draft posts, and draft posts don’t have their content available for display. Any attempt to get around these constraints will result in a compiler error.

17-3-6-2 Implementing Transitions as Transformations into Different Types

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impl DraftPost {
    // --snip--

    pub fn request_review(self) -> PendingReviewPost {
        PendingReviewPost {
            content: self.content,
        }
    }
}

pub struct PendingReviewPost {
    content: String,
}

impl PendingReviewPost {
    pub fn approve(self) -> Post {
        Post {
            content: self.content,
        }
    }
}

The changes we needed to make to main to reassign post mean that this implementation doesn’t quite follow the object-oriented state pattern anymore: the transformations between the states are no longer encapsulated entirely within the Post implementation. However, our gain is that invalid states are now impossible because of the type system and the type checking that happens at compile time!

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use blog::Post;

fn main() {
    let mut post = Post::new();

    post.add_text("I ate a salad for lunch today");

    let post = post.request_review();

    let post = post.approve();

    assert_eq!("I ate a salad for lunch today", post.content());
}

The code can be found here.