## What Is Ownership?

Rust’s central feature is ownership. Although the feature is straightforward to explain, it has deep implications for the rest of the language.

All programs have to manage the way they use a computer’s memory while running. Some languages have garbage collection that constantly looks for no longer used memory as the program runs; in other languages, the programmer must explicitly allocate and free the memory. Rust uses a third approach: memory is managed through a system of ownership with a set of rules that the compiler checks at compile time. No run-time costs are incurred for any of the ownership features.

Because ownership is a new concept for many programmers, it does take some time to get used to. The good news is that the more experienced you become with Rust and the rules of the ownership system, the more you’ll be able to naturally develop code that is safe and efficient. Keep at it!

When you understand ownership, you’ll have a solid foundation for understanding the features that make Rust unique. In this chapter, you’ll learn ownership by working through some examples that focus on a very common data structure: strings.

> ### The Stack and the Heap

> In many programming languages, we don’t have to think about the stack and the heap very often. But in a systems programming language like Rust, whether a value is on the stack or the heap has more of an effect on how the language behaves and why we have to make certain decisions. We’ll describe parts of ownership in relation to the stack and the heap later in this chapter, so here is a brief explanation in preparation.

> Both the stack and the heap are parts of memory that is available to your code to use at runtime, but they are structured in different ways. The stack stores values in the order it gets them and removes the values in the opposite order. This is referred to as last in, first out. Think of a stack of plates: when you add more plates, you put them on top of the pile, and when you need a plate, you take one off the top. Adding or removing plates from the middle or bottom wouldn’t work as well! Adding data is called pushing onto the stack, and removing data is called popping off the stack.

> The stack is fast because of the way it accesses the data: it never has to search for a place to put new data or a place to get data from because that place is always the top. Another property that makes the stack fast is that all data on the stack must take up a known, fixed size.

> For data with a size unknown to us at compile time or a size that might change, we can store data on the heap instead. The heap is less organized: when we put data on the heap, we ask for some amount of space. The operating system finds an empty spot somewhere in the heap that is big enough, marks it as being in use, and returns to us a pointer to that location. This process is called allocating on the heap, and sometimes we abbreviate the phrase as just “allocating.” Pushing values onto the stack is not considered allocating. Because the pointer is a known, fixed size, we can store the pointer on the stack, but when we want the actual data, we have to follow the pointer.

> Think of being seated at a restaurant. When you enter, you state the number of people in your group, and the staff finds an empty table that fits everyone and leads you there. If someone in your group comes late, they can ask where you’ve been seated to find you.

> Accessing data in the heap is slower than accessing data on the stack because we have to follow a pointer to get there. Contemporary processors are faster if they jump around less in memory. Continuing the analogy, consider a server at a restaurant taking orders from many tables. It’s most efficient to get all the orders at one table before moving on to the next table. Taking an order from table A, then an order from table B, then one from A again, and then one from B again would be a much slower process. By the same token, a processor can do its job better if it works on data that’s close to other data (as it is on the stack) rather than farther away (as it can be on the heap). Allocating a large amount of space on the heap can also take time.

> When our code calls a function, the values passed into the function (including, potentially, pointers to data on the heap) and the function’s local variables get pushed onto the stack. When the function is over, those values get popped off the stack.

> Keeping track of what parts of code are using what data on the heap, minimizing the amount of duplicate data on the heap, and cleaning up unused data on the heap so we don’t run out of space are all problems that ownership addresses. Once you understand ownership, you won’t need to think about the stack and the heap very often, but knowing that managing heap data is why ownership exists can help explain why it works the way it does.

### Ownership Rules

First, let’s take a look at the ownership rules. Keep these rules in mind as we work through the examples that illustrate the rules:

> 1. Each value in Rust has a variable that’s called its owner.
> 2. There can only be one owner at a time.
> 3. When the owner goes out of scope, the value will be dropped.

### Variable Scope

We’ve walked through an example of a Rust program already in Chapter 2. Now that we’re past basic syntax, we won’t include all the `fn main() {` code in examples, so if you’re following along, you’ll have to put the following examples inside a `main` function manually. As a result, our examples will be a bit more concise, letting us focus on the actual details rather than boilerplate code.

As a first example of ownership, we’ll look at the scope of some variables. A scope is the range within a program for which an item is valid. Let’s say we have a variable that looks like this:

    # #![allow(unused_variables)]
    #fn main() {
    let s = "hello";

    #}

The variable `s` refers to a string literal, where the value of the string is hardcoded into the text of our program. The variable is valid from the point at which it’s declared until the end of the current scope. Listing 4-1 has comments annotating where the variable `s` is valid:

    # #![allow(unused_variables)]
    #fn main() {
    {                      // s is not valid here, it’s not yet declared
        let s = "hello";   // s is valid from this point forward

        // do stuff with s
    }                      // this scope is now over, and s is no longer valid

    #}

Listing 4-1: A variable and the scope in which it is valid

In other words, there are two important points in time here:

1. When `s` comes into scope, it is valid.
2. It remains so until it goes out of scope.

At this point, the relationship between scopes and when variables are valid is similar to other programming languages. Now we’ll build on top of this understanding by introducing the `String` type.

### The `String` Type

To illustrate the rules of ownership, we need a data type that is more complex than the ones we covered in Chapter 3. All the data types we’ve looked at previously are stored on the stack and popped off the stack when their scope is over, but we want to look at data that is stored on the heap and explore how Rust knows when to clean up that data.

We’ll use `String` as the example here and concentrate on the parts of `String` that relate to ownership. These aspects also apply to other complex data types provided by the standard library and that you create. We’ll discuss `String` in more depth in Chapter 8.

We’ve already seen string literals, where a string value is hardcoded into our program. String literals are convenient, but they aren’t always suitable for every situation in which you want to use text. One reason is that they’re immutable. Another is that not every string value can be known when we write our code: for example, what if we want to take user input and store it? For these situations, Rust has a second string type, `String`. This type is allocated on the heap and as such is able to store an amount of text that is unknown to us at compile time. You can create a `String` from a string literal using the `from` function, like so:

    # #![allow(unused_variables)]
    #fn main() {
    let s = String::from("hello");

    #}

The double colon (`::`) is an operator that allows us to namespace this particular `from` function under the `String` type rather than using some sort of name like `string_from`. We’ll discuss this syntax more in the “Method Syntax” section of Chapter 5 and when we talk about namespacing with modules in Chapter 7.

This kind of string can be mutated:

    # #![allow(unused_variables)]
    #fn main() {
    let mut s = String::from("hello");

    s.push_str(", world!"); // push_str() appends a literal to a String

    println!("{}", s); // This will print `hello, world!`

    #}

So, what’s the difference here? Why can `String` be mutated but literals cannot? The difference is how these two types deal with memory.

### Memory and Allocation

In the case of a string literal, we know the contents at compile time so the text is hardcoded directly into the final executable, making string literals fast and efficient. But these properties only come from its immutability. Unfortunately, we can’t put a blob of memory into the binary for each piece of text whose size is unknown at compile time and whose size might change while running the program.

With the `String` type, in order to support a mutable, growable piece of text, we need to allocate an amount of memory on the heap, unknown at compile time, to hold the contents. This means:

1. The memory must be requested from the operating system at runtime.
2. We need a way of returning this memory to the operating system when we’re done with our `String`.

That first part is done by us: when we call `String::from`, its implementation requests the memory it needs. This is pretty much universal in programming languages.

However, the second part is different. In languages with a garbage collector (GC), the GC keeps track and cleans up memory that isn’t being used anymore, and we, as the programmer, don’t need to think about it. Without a GC, it’s the programmer’s responsibility to identify when memory is no longer being used and call code to explicitly return it, just as we did to request it. Doing this correctly has historically been a difficult programming problem. If we forget, we’ll waste memory. If we do it too early, we’ll have an invalid variable. If we do it twice, that’s a bug too. We need to pair exactly one `allocate` with exactly one `free`.

Rust takes a different path: the memory is automatically returned once the variable that owns it goes out of scope. Here’s a version of our scope example from Listing 4-1 using a `String` instead of a string literal:

    # #![allow(unused_variables)]
    #fn main() {
    {
        let s = String::from("hello"); // s is valid from this point forward

        // do stuff with s
    }                                  // this scope is now over, and s is no
                                       // longer valid

    #}

There is a natural point at which we can return the memory our `String` needs to the operating system: when `s` goes out of scope. When a variable goes out of scope, Rust calls a special function for us. This function is called `drop`, and it’s where the author of `String` can put the code to return the memory. Rust calls `drop` automatically at the closing `}`.

> Note: In C++, this pattern of deallocating resources at the end of an item's lifetime is sometimes called Resource Acquisition Is Initialization (RAII). The `drop` function in Rust will be familiar to you if you’ve used RAII patterns.

This pattern has a profound impact on the way Rust code is written. It may seem simple right now, but the behavior of code can be unexpected in more complicated situations when we want to have multiple variables use the data we’ve allocated on the heap. Let’s explore some of those situations now.

#### Ways Variables and Data Interact: Move

Multiple variables can interact with the same data in different ways in Rust. Let’s look at an example using an integer in Listing 4-2:

    # #![allow(unused_variables)]
    #fn main() {
    let x = 5;
    let y = x;

    #}

Listing 4-2: Assigning the integer value of variable `x` to `y`

We can probably guess what this is doing based on our experience with other languages: “Bind the value `5` to `x`; then make a copy of the value in `x` and bind it to `y`.” We now have two variables, `x` and `y`, and both equal `5`. This is indeed what is happening because integers are simple values with a known, fixed size, and these two `5` values are pushed onto the stack.

Now let’s look at the `String` version:

    # #![allow(unused_variables)]
    #fn main() {
    let s1 = String::from("hello");
    let s2 = s1;

    #}

This looks very similar to the previous code, so we might assume that the way it works would be the same: that is, the second line would make a copy of the value in `s1` and bind it to `s2`. But this isn’t quite what happens.

To explain this more thoroughly, let’s look at what `String` looks like under the covers in Figure 4-3. A `String` is made up of three parts, shown on the left: a pointer to the memory that holds the contents of the string, a length, and a capacity. This group of data is stored on the stack. On the right is the memory on the heap that holds the contents.

Figure 4-3: Representation in memory of a `String` holding the value `"hello"` bound to `s1`

The length is how much memory, in bytes, the contents of the `String` is currently using. The capacity is the total amount of memory, in bytes, that the `String` has received from the operating system. The difference between length and capacity matters, but not in this context, so for now, it’s fine to ignore the capacity.

When we assign `s1` to `s2`, the `String` data is copied, meaning we copy the pointer, the length, and the capacity that are on the stack. We do not copy the data on the heap that the pointer refers to. In other words, the data representation in memory looks like Figure 4-4.

Figure 4-4: Representation in memory of the variable `s2` that has a copy of the pointer, length, and capacity of `s1`

The representation does not look like Figure 4-5, which is what memory would look like if Rust instead copied the heap data as well. If Rust did this, the operation `s2 = s1` could potentially be very expensive in terms of runtime performance if the data on the heap was large.

Figure 4-5: Another possibility of what `s2 = s1` might do if Rust copied the heap data as well

Earlier, we said that when a variable goes out of scope, Rust automatically calls the `drop` function and cleans up the heap memory for that variable. But Figure 4-4 shows both data pointers pointing to the same location. This is a problem: when `s2` and `s1` go out of scope, they will both try to free the same memory. This is known as a double free error and is one of the memory safety bugs we mentioned previously. Freeing memory twice can lead to memory corruption, which can potentially lead to security vulnerabilities.

To ensure memory safety, there’s one more detail to what happens in this situation in Rust. Instead of trying to copy the allocated memory, Rust considers `s1` to no longer be valid and therefore, Rust doesn’t need to free anything when `s1` goes out of scope. Check out what happens when you try to use `s1` after `s2` is created:

    let s1 = String::from("hello");
    let s2 = s1;

    println!("{}", s1);

You’ll get an error like this because Rust prevents you from using the invalidated reference:

    error[E0382]: use of moved value: `s1`
     --> src/main.rs:4:27
      |
    3 |     let s2 = s1;
      |         -- value moved here
    4 |     println!("{}, world!",s1);
      |                           ^^ value used here after move
      |
      = note: move occurs because `s1` has type `std::string::String`,
    which does not implement the `Copy` trait

If you’ve heard the terms “shallow copy” and “deep copy” while working with other languages, the concept of copying the pointer, length, and capacity without copying the data probably sounds like a shallow copy. But because Rust also invalidates the first variable, instead of calling this a shallow copy, it’s known as a move. Here we would read this by saying that `s1` was moved into `s2`. So what actually happens is shown in Figure 4-6.

Figure 4-6: Representation in memory after `s1` has been invalidated

That solves our problem! With only `s2` valid, when it goes out of scope, it alone will free the memory, and we’re done.

In addition, there’s a design choice that’s implied by this: Rust will never automatically create “deep” copies of your data. Therefore, any automatic copying can be assumed to be inexpensive in terms of runtime performance.

#### Ways Variables and Data Interact: Clone

If we do want to deeply copy the heap data of the `String`, not just the stack data, we can use a common method called `clone`. We’ll discuss method syntax in Chapter 5, but because methods are a common feature in many programming languages, you’ve probably seen them before.

Here’s an example of the `clone` method in action:

    # #![allow(unused_variables)]
    #fn main() {
    let s1 = String::from("hello");
    let s2 = s1.clone();

    println!("s1 = {}, s2 = {}", s1, s2);

    #}

This works just fine and is how you can explicitly produce the behavior shown in Figure 4-5, where the heap data does get copied.

When you see a call to `clone`, you know that some arbitrary code is being executed and that code may be expensive. It’s a visual indicator that something different is going on.

#### Stack-Only Data: Copy

There’s another wrinkle we haven’t talked about yet. This code using integers, part of which was shown earlier in Listing 4-2, works and is valid:

    # #![allow(unused_variables)]
    #fn main() {
    let x = 5;
    let y = x;

    println!("x = {}, y = {}", x, y);

    #}

But this code seems to contradict what we just learned: we don’t have a call to `clone`, but `x` is still valid and wasn’t moved into `y`.

The reason is that types like integers that have a known size at compile time are stored entirely on the stack, so copies of the actual values are quick to make. That means there’s no reason we would want to prevent `x` from being valid after we create the variable `y`. In other words, there’s no difference between deep and shallow copying here, so calling `clone` wouldn’t do anything differently from the usual shallow copying and we can leave it out.

Rust has a special annotation called the `Copy` trait that we can place on types like integers that are stored on the stack (we’ll talk more about traits in Chapter 10). If a type has the `Copy` trait, an older variable is still usable after assignment. Rust won’t let us annotate a type with the `Copy` trait if the type, or any of its parts, has implemented the `Drop` trait. If the type needs something special to happen when the value goes out of scope and we add the `Copy` annotation to that type, we’ll get a compile time error. To learn about how to add the `Copy` annotation to your type, see Appendix C on Derivable Traits.

So what types are `Copy`? You can check the documentation for the given type to be sure, but as a general rule, any group of simple scalar values can be `Copy`, and nothing that requires allocation or is some form of resource is `Copy`. Here are some of the types that are `Copy`:

- All the integer types, like `u32`.
- The boolean type, `bool`, with values `true` and `false`.
- All the floating point types, like `f64`.
- Tuples, but only if they contain types that are also `Copy`. `(i32, i32)` is `Copy`, but `(i32, String)` is not.

### Ownership and Functions

The semantics for passing a value to a function are similar to assigning a value to a variable. Passing a variable to a function will move or copy, just like assignment. Listing 4-7 has an example with some annotations showing where variables go into and out of scope:

Filename: src/main.rs

    fn main() {
        let s = String::from("hello");  // s comes into scope.

        takes_ownership(s);             // s's value moves into the function...
                                        // ... and so is no longer valid here.
        let x = 5;                      // x comes into scope.

        makes_copy(x);                  // x would move into the function,
                                        // but i32 is Copy, so it’s okay to still
                                        // use x afterward.

    } // Here, x goes out of scope, then s. But since s's value was moved, nothing
      // special happens.

    fn takes_ownership(some_string: String) { // some_string comes into scope.
        println!("{}", some_string);
    } // Here, some_string goes out of scope and `drop` is called. The backing
      // memory is freed.

    fn makes_copy(some_integer: i32) { // some_integer comes into scope.
        println!("{}", some_integer);
    } // Here, some_integer goes out of scope. Nothing special happens.

Listing 4-7: Functions with ownership and scope annotated

If we tried to use `s` after the call to `takes_ownership`, Rust would throw a compile time error. These static checks protect us from mistakes. Try adding code to `main` that uses `s` and `x` to see where you can use them and where the ownership rules prevent you from doing so.

### Return Values and Scope

Returning values can also transfer ownership. Here’s an example with similar annotations to those in Listing 4-7:

Filename: src/main.rs

    fn main() {
        let s1 = gives_ownership();         // gives_ownership moves its return
                                            // value into s1.

        let s2 = String::from("hello");     // s2 comes into scope.

        let s3 = takes_and_gives_back(s2);  // s2 is moved into
                                            // takes_and_gives_back, which also
                                            // moves its return value into s3.
    } // Here, s3 goes out of scope and is dropped. s2 goes out of scope but was
      // moved, so nothing happens. s1 goes out of scope and is dropped.

    fn gives_ownership() -> String {             // gives_ownership will move its
                                                 // return value into the function
                                                 // that calls it.

        let some_string = String::from("hello"); // some_string comes into scope.

        some_string                              // some_string is returned and
                                                 // moves out to the calling
                                                 // function.
    }

    // takes_and_gives_back will take a String and return one.
    fn takes_and_gives_back(a_string: String) -> String { // a_string comes into
                                                          // scope.

        a_string  // a_string is returned and moves out to the calling function.
    }

The ownership of a variable follows the same pattern every time: assigning a value to another variable moves it. When a variable that includes data on the heap goes out of scope, the value will be cleaned up by `drop` unless the data has been moved to be owned by another variable.

Taking ownership and then returning ownership with every function is a bit tedious. What if we want to let a function use a value but not take ownership? It’s quite annoying that anything we pass in also needs to be passed back if we want to use it again, in addition to any data resulting from the body of the function that we might want to return as well.

It’s possible to return multiple values using a tuple, like this:

Filename: src/main.rs

    fn main() {
        let s1 = String::from("hello");

        let (s2, len) = calculate_length(s1);

        println!("The length of '{}' is {}.", s2, len);
    }

    fn calculate_length(s: String) -> (String, usize) {
        let length = s.len(); // len() returns the length of a String.

        (s, length)
    }

But this is too much ceremony and a lot of work for a concept that should be common. Luckily for us, Rust has a feature for this concept, and it’s called references.