Class basics

Instance and class attributes

Mypy type checker detects if you are trying to access a missing attribute, which is a very common programming error. For this to work correctly, instance and class attributes must be defined or initialized within the class. Mypy infers the types of attributes:

class A:
    def __init__(self, x: int) -> None:
        self.x = x     # Attribute x of type int

a = A(1)
a.x = 2       # OK
a.y = 3       # Error: A has no attribute y

This is a bit like each class having an implicitly defined __slots__ attribute. This is only enforced during type checking and not when your program is running.

You can declare types of variables in the class body explicitly using a type comment:

class A:
    x = None  # type: List[int]  # Declare attribute x of type List[int]

a = A()
a.x = [1]     # OK

As in Python, a variable defined in the class body can used as a class or an instance variable.

Similarly, you can give explicit types to instance variables defined in a method:

class A:
    def __init__(self) -> None:
        self.x = []  # type: List[int]

    def f(self) -> None:
        self.y = 0  # type: Any

You can only define an instance variable within a method if you assign to it explicitly using self:

class A:
    def __init__(self) -> None:
        self.y = 1   # Define y
        a = self
        a.x = 1      # Error: x not defined

Overriding statically typed methods

When overriding a statically typed method, mypy checks that the override has a compatible signature:

class A:
    def f(self, x: int) -> None:
        ...

class B(A):
    def f(self, x: str) -> None:   # Error: type of x incompatible
        ...

class C(A):
    def f(self, x: int, y: int) -> None:  # Error: too many arguments
        ...

class D(A):
    def f(self, x: int) -> None:   # OK
        ...

Note

You can also vary return types covariantly in overriding. For example, you could override the return type object with a subtype such as int.

You can also override a statically typed method with a dynamically typed one. This allows dynamically typed code to override methods defined in library classes without worrying about their type signatures.

There is no runtime enforcement that the method override returns a value that is compatible with the original return type, since annotations have no effect at runtime:

class A:
    def inc(self, x: int) -> int:
        return x + 1

class B(A):
    def inc(self, x):       # Override, dynamically typed
        return 'hello'

b = B()
print(b.inc(1))   # hello
a = b # type: A
print(a.inc(1))   # hello

Abstract base classes and multiple inheritance

Mypy uses Python abstract base classes for protocol types. There are several built-in abstract base classes types (for example, Sequence, Iterable and Iterator). You can define abstract base classes using the abc.ABCMeta metaclass and the abc.abstractmethod function decorator.

from abc import ABCMeta, abstractmethod
import typing

class A(metaclass=ABCMeta):
    @abstractmethod
    def foo(self, x: int) -> None: pass

    @abstractmethod
    def bar(self) -> str: pass

class B(A):
    def foo(self, x: int) -> None: ...
    def bar(self) -> str:
        return 'x'

a = A() # Error: A is abstract
b = B() # OK

Unlike most Python code, abstract base classes are likely to play a significant role in many complex mypy programs.

A class can inherit any number of classes, both abstract and concrete. As with normal overrides, a dynamically typed method can implement a statically typed abstract method defined in an abstract base class.

Note

There are also plans to support more Python-style “duck typing” in the type system. The details are still open.