Previous posts have covered two pillars of Rust’s design:

  • Memory safety without garbage collection
  • Concurrency without data races

This post begins exploring the third pillar:

  • Abstraction without overhead

One of the mantras of C++, one of the qualities that make it a good fit for systems programming, is its principle of zero-cost abstraction:

C++ implementations obey the zero-overhead principle: What you don’t use, you don’t pay for [Stroustrup, 1994]. And further: What you do use, you couldn’t hand code any better.

– Stroustrup

This mantra did not always apply to Rust, which for example used to have mandatory garbage collection. But over time Rust’s ambitions have gotten ever lower-level, and zero-cost abstraction is now a core principle.

The cornerstone of abstraction in Rust is traits:

  • Traits are Rust’s sole notion of interface. A trait can be implemented by multiple types, and in fact new traits can provide implementations for existing types. On the flip side, when you want to abstract over an unknown type, traits are how you specify the few concrete things you need to know about that type.

  • Traits can be statically dispatched. Like C++ templates, you can have the compiler generate a separate copy of an abstraction for each way it is instantiated. This comes back to the C++ mantra of “What you do use, you couldn’t hand code any better” – the abstraction ends up completely erased.

  • Traits can be dynamically dispatched. Sometimes you really do need an indirection, and so it doesn’t make sense to “erase” an abstraction at runtime. The same notion of interface – the trait – can also be used when you want to dispatch at runtime.

  • Traits solve a variety of additional problems beyond simple abstraction. They are used as “markers” for types, like the Send marker described in a previous post. They can be used to define “extension methods” – that is, to add methods to an externally-defined type. They largely obviate the need for traditional method overloading. And they provide a simple scheme for operator overloading.

All told, the trait system is the secret sauce that gives Rust the ergonomic, expressive feel of high-level languages while retaining low-level control over code execution and data representation.

This post will walk through each of the above points at a high level, to give you a sense for how the design achieves these goals, without getting too bogged down in the details.

Background: methods in Rust

Before delving into traits, we need to look at a small but important detail of the language: the difference between methods and functions.

Rust offers both methods and free-standing functions, which are very closely related:

struct Point {
    x: f64,
    y: f64,

// a free-standing function that converts a (borrowed) point to a string
fn point_to_string(point: &Point) -> String { ... }

// an "inherent impl" block defines the methods available directly on a type
impl Point {
    // this method is available on any Point, and automatically borrows the
    // Point value
    fn to_string(&self) -> String { ... }

Methods like to_string above are called “inherent” methods, because they:

  • Are tied to a single concrete “self” type (specified via the impl block header).
  • Are automatically available on any value of that type – that is, unlike functions, inherent methods are always “in scope”.

The first parameter for a method is always an explicit “self”, which is either self, &mut self, or &self depending on the level of ownership required. Methods are invoked using the . notation familiar from object-oriented programming, and the self parameter is implicitly borrowed as per the form of self used in the method:

let p = Point { x: 1.2, y: -3.7 };
let s1 = point_to_string(&p);  // calling a free function, explicit borrow
let s2 = p.to_string();        // calling a method, implicit borrow as &p

Methods and their auto-borrowing are an important aspect of the ergonomics of Rust, supporting “fluent” APIs like the one for spawning processes:

let child = Command::new("/bin/cat")

Traits are interfaces

Interfaces specify the expectations that one piece of code has on another, allowing each to be switched out independently. For traits, this specification largely revolves around methods.

Take, for example, the following simple trait for hashing:

trait Hash {
    fn hash(&self) -> u64;

In order to implement this trait for a given type, you must provide a hash method with matching signature:

impl Hash for bool {
    fn hash(&self) -> u64 {
        if *self { 0 } else { 1 }

impl Hash for i64 {
    fn hash(&self) -> u64 {
        *self as u64

Unlike interfaces in languages like Java, C# or Scala, new traits can be implemented for existing types (as with Hash above). That means abstractions can be created after-the-fact, and applied to existing libraries.

Unlike inherent methods, trait methods are in scope only when their trait is. But assuming Hash is in scope, you can write true.hash(), so implementing a trait extends the set of methods available on a type.

And… that’s it! Defining and implementing a trait is really nothing more than abstracting out a common interface satisfied by more than one type.

Static dispatch

Things get more interesting on the other side – consuming a trait. The most common way of doing so is through generics:

fn print_hash<T: Hash>(t: &T) {
    println!("The hash is {}", t.hash())

The print_hash function is generic over an unknown type T, but requires that T implements the Hash trait. That means we can use it with bool and i64 values:

print_hash(&true);      // instantiates T = bool
print_hash(&12_i64);    // instantiates T = i64

Generics are compiled away, resulting in static dispatch. That is, as with C++ templates, the compiler will generate two copies of the print_hash method to handle the above code, one for each concrete argument type. That in turn means that the internal call to t.hash() – the point where the abstraction is actually used – has zero cost: it will be compiled to a direct, static call to the relevant implementation:

// The compiled code:
__print_hash_bool(&true);  // invoke specialized bool version directly
__print_hash_i64(&12_i64);   // invoke specialized i64 version directly

This compilation model isn’t so useful for a function like print_hash, but it’s very useful for more realistic uses of hashing. Suppose we also introduce a trait for equality comparison:

trait Eq {
    fn eq(&self, other: &Self) -> bool;

(The reference to Self here will resolve to whatever type we implement the trait for; in impl Eq for bool it will refer to bool.)

We can then define a hash map that is generic over a type T implementing both Hash and Eq:

struct HashMap<Key: Hash + Eq, Value> { ... }

The static compilation model for generics will then yield several benefits:

  • Each use of HashMap with concrete Key and Value types will result in a different concrete HashMap type, which means that HashMap can lay out the keys and values in-line (without indirection) in its buckets. This saves on space and indirections, and improves cache locality.

  • Each method on HashMap will likewise generate specialized code. That means there is no extra cost dispatching to calls to hash and eq, as above. It also means that the optimizer gets to work with the fully concrete code – that is, from the point of view of the optimizer, there is no abstraction. In particular, static dispatch allows for inlining across uses of generics.

Altogether, just as in C++ templates, these aspects of generics mean that you can write quite high-level abstractions that are guaranteed to compile down to fully concrete code that “you couldn’t hand code any better”.

But, unlike with C++ templates, clients of traits are fully type-checked in advance. That is, when you compile HashMap in isolation, its code is checked once for type correctness against the abstract Hash and Eq traits, rather than being checked repeatedly when applied to concrete types. That means earlier, clearer compilation errors for library authors, and less typechecking overhead (i.e., faster compilation) for clients.

Dynamic dispatch

We’ve seen one compilation model for traits, where all abstraction is compiled away statically. But sometimes abstraction isn’t just about reuse or modularity – sometimes abstraction plays an essential role at runtime that can’t be compiled away.

For example, GUI frameworks often involve callbacks for responding to events, such as mouse clicks:

trait ClickCallback {
    fn on_click(&self, x: i64, y: i64);

It’s also common for GUI elements to allow multiple callbacks to be registered for a single event. With generics, you might imagine writing:

struct Button<T: ClickCallback> {
    listeners: Vec<T>,

but the problem is immediately apparent: that would mean that each button is specialized to precisely one implementor of ClickCallback, and that the type of the button reflects that type. That’s not at all what we wanted! Instead, we’d like a single Button type with a set of heterogeneous listeners, each potentially a different concrete type, but each one implementing ClickCallback.

One immediate difficulty here is that, if we’re talking about a heterogeneous group of types, each one will have a distinct size – so how can we even lay out the internal vector? The answer is the usual one: indirection. We’ll store pointers to callbacks in the vector:

struct Button {
    listeners: Vec<Box<ClickCallback>>,

Here, we are using the ClickCallback trait as if it were a type. Actually, in Rust, traits are types, but they are “unsized”, which roughly means that they are only allowed to show up behind a pointer like Box (which points onto the heap) or & (which can point anywhere).

In Rust, a type like &ClickCallback or Box<ClickCallback> is called a “trait object”, and includes a pointer to an instance of a type T implementing ClickCallback, and a vtable: a pointer to T’s implementation of each method in the trait (here, just on_click). That information is enough to dispatch calls to methods correctly at runtime, and to ensure uniform representation for all T. So Button is compiled just once, and the abstraction lives on at runtime.

Static and dynamic dispatch are complementary tools, each appropriate for different scenarios. Rust’s traits provide a single, simple notion of interface that can be used in both styles, with minimal, predictable costs. Trait objects satisfy Stroustrup’s “pay as you go” principle: you have vtables when you need them, but the same trait can be compiled away statically when you don’t.

The many uses of traits

We’ve seen a lot of the mechanics and basic use of traits above, but they also wind up playing a few other important roles in Rust. Here’s a taste:

  • Closures. Somewhat like the ClickCallback trait, closures in Rust are simply particular traits. You can read more about how this works in Huon Wilson’s in-depth post on the topic.

  • Conditional APIs. Generics make it possible to implement a trait conditionally:

  struct Pair<A, B> { first: A, second: B }
  impl<A: Hash, B: Hash> Hash for Pair<A, B> {
      fn hash(&self) -> u64 {
          self.first.hash() ^ self.second.hash()

Here, the Pair type implements Hash if, and only if, its components do – allowing the single Pair type to be used in different contexts, while supporting the largest API available for each context. It’s such a common pattern in Rust that there is built-in support for generating certain kinds of “mechanical” implementations automatically:

  struct Pair<A, B> { .. }
  • Extension methods. Traits can be used to extend an existing type (defined elsewhere) with new methods, for convenience, similarly to C#’s extension methods. This falls directly out of the scoping rules for traits: you just define the new methods in a trait, provide an implementation for the type in question, and voila, the method is available.

  • Markers. Rust has a handful of “markers” that classify types: Send, Sync, Copy, Sized. These markers are just traits with empty bodies, which can then be used in both generics and trait objects. Markers can be defined in libraries, and they automatically provide #[derive]-style implementations: if all of a types components are Send, for example, so is the type. As we saw before, these markers can be very powerful: the Send marker is how Rust guarantees thread safety.

  • Overloading. Rust does not support traditional overloading where the same method is defined with multiple signatures. But traits provide much of the benefit of overloading: if a method is defined generically over a trait, it can be called with any type implementing that trait. Compared to traditional overloading, this has two advantages. First, it means the overloading is less ad hoc: once you understand a trait, you immediately understand the overloading pattern of any APIs using it. Second, it is extensible: you can effectively provide new overloads downstream from a method by providing new trait implementations.

  • Operators. Rust allows you to overload operators like + on your own types. Each of the operators is defined by a corresponding standard library trait, and any type implementing the trait automatically provides the operator as well.

The point: despite their seeming simplicity, traits are a unifying concept that supports a wide range of use cases and patterns, without having to pile on additional language features.

The future

One of the primary ways that languages tend to evolve is in their abstraction facilities, and Rust is no exception: many of our post-1.0 priorities are extensions of the trait system in one direction or another. Here are some highlights.

  • Statically dispatched outputs. Right now, it’s possible for functions to use generics for their parameters, but there’s no equivalent for their results: you cannot say “this function returns a value of some type that implements the Iterator trait” and have that abstraction compiled away. This is particularly problematic when you want to return a closure that you’d like to be statically-dispatched – you simply can’t, in today’s Rust. We want to make this possible, and have some ideas already.

  • Specialization. Rust does not allow overlap between trait implementations, so there is never ambiguity about which code to run. On the other hand, there are some cases where you can give a “blanket” implementation for a wide range of types, but would then like to provide a more specialized implementation for a few cases, often for performance reasons. We hope to propose a design in the near future.

  • Higher-kinded types (HKT). Traits today can only be applied to types, not type constructors – that is, to things like Vec<u8>, not to Vec itself. This limitation makes it difficult to provide a good set of container traits, which are therefore not included in the current standard library. HKT is a major, cross-cutting feature that will represent a big step forward in Rust’s abstraction capabilities.

  • Efficient re-use. Finally, while traits provide some mechanisms for reusing code (which we didn’t cover above), there are still some patterns of reuse that don’t fit well into the language today – notably, object-oriented hierarchies found in things like the DOM, GUI frameworks, and many games. Accommodating these use cases without adding too much overlap or complexity is a very interesting design problem, and one that Niko Matsakis has started a separate blog series about. It’s not yet clear whether this can all be done with traits, or whether some other ingredients are needed.

Of course, we’re at the eve of the 1.0 release, and it will take some time for the dust to settle, and for the community to have enough experience to start landing these extensions. But that makes it an exciting time to get involved: from influencing the design at this early stage, to working on implementation, to trying out different use cases in your own code – we’d love to have your help!