Native classes¶

Classes in compiled modules are native classes by default (some exceptions are discussed below). Native classes are compiled to C extension classes, which have some important differences from normal Python classes. Native classes are similar in many ways to built-in types, such as int, str, and list.

Immutable namespaces¶

The type object namespace of native classes is mostly immutable (but class variables can be assigned to):

class Cls:
    def method1(self) -> None:
        print("method1")

    def method2(self) -> None:
        print("method2")

Cls.method1 = Cls.method2  # Error
Cls.new_method = Cls.method2  # Error

Only attributes defined within a class definition (or in a base class) can be assigned to (similar to using __slots__):

class Cls:
    x: int

    def __init__(self, y: int) -> None:
        self.x = 0
        self.y = y

    def method(self) -> None:
        self.z = "x"

o = Cls(0)
print(o.x, o.y)  # OK
o.z = "y"  # OK
o.extra = 3  # Error: no attribute "extra"

Inheritance¶

Only single inheritance is supported (except for traits). Most non-native classes can’t be used as base classes.

These non-native classes can be used as base classes of native classes:

object
dict (and Dict[k, v])
BaseException
Exception
ValueError
IndexError
LookupError
UserWarning
typing.NamedTuple
enum.Enum

By default, a non-native class can’t inherit a native class, and you can’t inherit from a native class outside the compilation unit that defines the class. You can enable these through mypy_extensions.mypyc_attr:

from mypy_extensions import mypyc_attr

@mypyc_attr(allow_interpreted_subclasses=True)
class Cls:
    ...

Allowing interpreted subclasses has only minor impact on performance of instances of the native class. Accessing methods and attributes of a non-native subclass (or a subclass defined in another compilation unit) will be slower, since it needs to use the normal Python attribute access mechanism.

You need to install mypy-extensions to use @mypyc_attr:

pip install --upgrade mypy-extensions

Class variables¶

Class variables must be explicitly declared using attr: ClassVar or attr: ClassVar[<type>]. You can’t assign to a class variable through an instance. Example:

from typing import ClassVar

class Cls:
    cv: ClassVar = 0

Cls.cv = 2  # OK
o = Cls()
print(o.cv)  # OK (2)
o.cv = 3  # Error!

Tip

Constant class variables can be declared using typing.Final or typing.Final[<type>].

Generic native classes¶

Native classes can be generic. Type variables are erased at runtime, and instances don’t keep track of type variable values.

Compiled code thus can’t check the values of type variables when performing runtime type checks. These checks are delayed to when reading a value with a type variable type:

from typing import TypeVar, Generic, cast

T = TypeVar('T')

class Box(Generic[T]):
    def __init__(self, item: T) -> None:
        self.item = item

x = Box(1)  # Box[int]
y = cast(Box[str], x)  # OK (type variable value not checked)
y.item  # Runtime error: item is "int", but "str" expected

Metaclasses¶

Most metaclasses aren’t supported with native classes, since their behavior is too dynamic. You can use these metaclasses, however:

abc.ABCMeta
typing.GenericMeta (used by typing.Generic)

Note

If a class definition uses an unsupported metaclass, mypyc compiles the class into a regular Python class.

Class decorators¶

Similar to metaclasses, most class decorators aren’t supported with native classes, as they are usually too dynamic. These class decorators can be used with native classes, however:

mypy_extensions.trait (for defining trait types)
mypy_extensions.mypyc_attr (see above)
dataclasses.dataclass
@attr.s(auto_attribs=True)

Dataclasses and attrs classes have partial native support, and they aren’t as efficient as pure native classes.

Note

If a class definition uses an unsupported class decorator, mypyc compiles the class into a regular Python class.

Deleting attributes¶

By default, attributes defined in native classes can’t be deleted. You can explicitly allow certain attributes to be deleted by using __deletable__:

class Cls:
    x: int = 0
    y: int = 0
    other: int = 0

    __deletable__ = ['x', 'y']  # 'x' and 'y' can be deleted

o = Cls()
del o.x  # OK
del o.y  # OK
del o.other  # Error

You must initialize the __deletable__ attribute in the class body, using a list or a tuple expression with only string literal items that refer to attributes. These are not valid:

a = ['x', 'y']

class Cls:
    x: int
    y: int

    __deletable__ = a  # Error: cannot use variable 'a'

__deletable__ = ('a',)  # Error: not in a class body

Other properties¶

Instances of native classes don’t usually have a __dict__ attribute.