Define shared behavior for types.

A trait is a set of requirements that a type must implement. You can think of it as a contract: a type that conforms to a trait guarantees that it implements all of the features of the trait.

Traits are similar to Java interfaces, C++ concepts, Swift protocols, and Rust traits. If you’re familiar with any of those features, Mojo traits solve the same basic problem.


In dynamically-typed languages like Python, you don’t need to explicitly declare that two classes are similar. This is easiest to show by example:

class Duck:
    def quack(self):

class StealthCow:
    def quack(self):

def make_it_quack_python(maybe_a_duck):
        print("Not a duck.")


The Duck and StealthCow classes aren’t related in any way, but they both define a quack() method, so they work the same in the make_it_quack() function. This works because Python uses dynamic dispatch—it identifies the methods to call at runtime. So make_it_quack_python() doesn’t care what types you’re passing it, only the fact that they implement the quack() method.

In a statically-typed environment, this approach doesn’t work: fn functions require you to specify the type of each argument. If you wanted to write this example in Mojo without traits, you’d need to write a function overload for each input type. All of the examples from here on are in Mojo, so we’ll just call the function make_it_quack() going forward.

struct Duck:
    fn quack(self):

struct StealthCow:
    fn quack(self):

fn make_it_quack(definitely_a_duck: Duck):

fn make_it_quack(not_a_duck: StealthCow):


This isn’t too bad with only two classes. But the more classes you want to support, the less practical this approach is.

You might notice that the Mojo versions dosn’t include the try/except statement. We don’t need it because Mojo’s static type checking ensures that you can only pass instances of Duck or StealthCow into the make_it_quack() function.

Using traits

Traits solve this problem by letting you define a shared set of behaviors that types can implement. Then you can write a function that depends on the trait, rather than individual types. As an example, let’s update the make_it_quack() example using traits. The first step is defining a trait:

trait Quackable:
    fn quack(self):

A trait looks a lot like a struct, except it’s introduced by the trait keyword. Right now, a trait can only contain method signatures, and cannot include method implementations. Each method signature must be followed by three dots (...) to indicate that the method is unimplemented.

TODO: In the future, we plan to support defining fields and default method implementations inside a trait. Right now, though, a trait can only declare method signatures.

Next we create some structs that conform to the Quackable trait. To indicate that a struct conforms to a trait, include the trait name in parenthesis after the struct name. You can also include multiple traits, separated by commas. (If you’re familiar with Python, this looks just like Python’s inheritance syntax.)

struct Duck(Quackable):
    fn quack(self):

struct StealthCow(Quackable):
    fn quack(self):

The struct needs to implement any methods that are declared in the trait. The compiler enforces conformance: if a struct says it conforms to a trait, it must implement everything required by the trait or the code won’t compile.

Finally, you can define a function that takes a Quackable like this:

fn make_it_quack[T: Quackable](maybe_a_duck: T):

This syntax may look a little unfamiliar if you haven’t dealt with Mojo parameters before. What this signature means is that maybe_a_duck is an argument of type T, where T is a type that must conform to the Quackable trait. TODO: This syntax is a little verbose, and we hope to make it more ergonomic in a future release.

Using the method is simple enough:


Note that you don’t need the square brackets when you call make_it_quack(): the compiler infers the type of the argument, and ensures the type has the required trait.

One limitation of traits is that you can’t add traits to existing types. For example, if you define a new Numeric trait, you can’t add it to the standard library Float64 and Int types. However, the standard library already includes a few traits, and we’ll be adding more over time.

Traits can require static methods

In addition to regular instance methods, traits can specify required static methods.

trait HasStaticMethod:
    fn do_stuff(): ...

fn fun_with_traits[T: HasStaticMethod]():

Trait inheritance

Traits can inherit from other traits. A trait that inherits from another trait includes all of the requirements declared by the parent trait. For example:

trait Animal:
    fn make_sound(self):

# Bird inherits from Animal
trait Bird(Animal):
    fn fly(self):

Since Bird inherits from Animal, a struct that conforms to the Bird trait needs to implement both make_sound() and fly(). And since every Bird conforms to Animal, a struct that conforms to Bird can be passed to any function that requires an Animal.

To inherit from multiple traits, add a comma-separated list of traits inside the parenthesis. For example, you could define a NamedAnimal trait that combines the requirements of the Animal trait and a new Named trait:

trait Named:
    fn get_name(self) -> String:

trait NamedAnimal(Animal, Named):

Traits and lifecycle methods

Traits can specify required lifecycle methods, including constructors, copy constructors and move constructors.

For example, the following code creates a MassProducible trait. A MassProducible type has a default (no-argument) constructor and can be moved. It uses the built-in Movable trait, which requires the type to have a move constructor.

The factory[]() function returns a newly-constructed instance of a MassProducible type.

trait DefaultConstructible:
    fn __init__(inout self): ...

trait MassProducible(DefaultConstructible, Movable):

fn factory[T: MassProducible]() -> T:
    return T()

struct Thing(MassProducible):
    var id: Int

    fn __init__(inout self): = 0

    fn __moveinit__(inout self, owned existing: Self): =

let thing = factory[Thing]()

Note that @register_passable and @register_passable("trivial") types have restrictions on their lifecycle methods: they define their constructors differently, and trivial types can’t define copy or move constructors.

The compiler implements special rules to ensure that these types can conform to traits that require certain lifecycle methods. For example, trivial types are always considered copyable, although they cannot include a copy constructor. Unlike a standard constructor, a constructor for a register-passable type is static (doesn’t include a self argument) and returns a value. The compiler ignores these differences when comparing a register-passable constructor to the required constructors declared in a trait.

So the following constructor signatures are considered equivalent when determining whether a type conforms to a trait:

# Standard constructor, as declared in a trait
fn __init__(self, i: Int):
# Register-passable constructor
fn __init__(i: Int) -> Self:

For example, the following register-passable type conforms to the DefaultConstructible trait.

struct RegisterPassableType(DefaultConstructible):
    # This is OK: Traits understand different type conventions.
    fn __init__() -> Self:
        return Self {}

Built-in traits

The Mojo standard library currently includes a few traits. They’re implemented by a number of standard library types, and you can also implement these on your own types:

The API reference docs linked above include usage examples for each trait. The following sections discuss a few of these traits.

The Sized trait

The Sized trait identifies types that have a measurable length, like strings and arrays.

Specifically, Sized requires a type to implement the __len__() method. This trait is used by the built-in len() function. For example, if you’re writing a custom vector type, you could implement this trait so your type works with len():

struct MyVector(Sized):
    var size: Int
    # ...

    fn __init__(inout self):
        self.size = 0

    fn __len__(self) -> Int:
        return self.size


The Intable and Stringable traits

The Intable and Stringable traits identify types that can be implicitly converted to Int and String, respectively.

Any type that conforms to Stringable works with the built-in print() and str() functions:

struct Pet(Stringable):
    var name: String
    var type: String

    fn __str__(self) -> String:
        return "This is a " + self.type + " named " +

let spot = Pet("Spot", "dog")
This is a dog named Spot

Similarly, an Intable type works with the built-in int function. You can find an example in the Intable API reference.

The AnyType trait

When building a generic container type, one challenge is knowing how to dispose of the contained items when the container is destroyed. Any type that dynamically allocates memory needs to supply a destructor (__del__() method) that must be called to free the allocated memory. But not all types have a destructor, and your Mojo code has no way to determine which is which.

The AnyType trait solves this issue: every trait implicitly inherits from AnyType, and all structs conform to AnyType, which guarantees that the type has a destructor. For types that don’t have one, Mojo adds a no-op destructor. This means you can call the destructor on any type.

This makes it possible to build generic collections without leaking memory. When the collection’s destructor is called, it can safely call the destructors on every item it contains.

Generic structs with traits

You can also use traits when defining a generic container. A generic container is a container (for example, an array or hashmap) that can hold different data types. In a dynamic language like Python it’s easy to add different types of items to a container. But in a statically-typed environment the compiler needs to be able to identify the types at compile time. For example, if the container needs to copy a value, the compiler needs to verify that the type can be copied.

The DynamicVector type is an example of a generic container. A single DynamicVector can only hold a single type of data. For example, you can create a vector of integer values like this:

from collections.vector import DynamicVector

var vector = DynamicVector[Int]()
for i in range(len(vector)):
    print_no_newline(vector[i], " ")
3  6  9  

You can use traits to define requirements for elements that are stored in a container. For example, DynamicVector requires elements that can be moved and copied. To store a struct in a DynamicVector, the struct needs to conform to the CollectionElement trait, which requires a copy constructor and a move constructor.

Building generic containers is an advanced topic. For an introduction, see the section on parameterized structs.