Using the Class as a Type Hint for Arguments in Its Methods

Using the class as a type hint for arguments in its methods

Because when it encounters Translate (while compiling the class body), Vector2 hasn't been defined yet (it is currently compiling, name binding hasn't been performed); Python naturally complains.

Since this is such a common scenario (type-hinting a class in the body of that class), you should use a forward reference to it by enclosing it in quotes:

class Vector2:    
    # __init__ as defined

    def Translate(self, pos: 'Vector2'):    
        self.x += pos.x
        self.y += pos.y

Python (and any checkers complying to PEP 484) will understand your hint and register it appropriately. Python does recognize this when __annotations__ are accessed through typing.get_type_hints:

from typing import get_type_hints

get_type_hints(Vector2(1,2).Translate)
{'pos': __main__.Vector2}

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This has been changed as of Python 3.7; see abarnert's answer below.

How do I type hint a method with the type of the enclosing class?

TL;DR: As of today (2019), in Python 3.7+ you can turn this feature on using a "future" statement, from __future__ import annotations.

(The behaviour enabled by from __future__ import annotations might become the default in future versions of Python, and was going to be made the default in Python 3.10. However, the change in 3.10 was reverted at the last minute, and now may not happen at all.)

In Python 3.6 or below, you should use a string.

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I guess you got this exception:

NameError: name 'Position' is not defined

This is because Position must be defined before you can use it in an annotation, unless you are using Python with PEP 563 changes enabled.

Python 3.7+: from __future__ import annotations

Python 3.7 introduces PEP 563: postponed evaluation of annotations. A module that uses the future statement from __future__ import annotations will store annotations as strings automatically:

from __future__ import annotations

class Position:
    def __add__(self, other: Position) -> Position:
        ...

This had been scheduled to become the default in Python 3.10, but this change has now been postponed. Since Python still is a dynamically typed language so no type-checking is done at runtime, typing annotations should have no performance impact, right? Wrong! Before Python 3.7, the typing module used to be one of the slowest python modules in core so for code that involves importing the typing module, you will see an up to 7 times increase in performance when you upgrade to 3.7.

Python <3.7: use a string

According to PEP 484, you should use a string instead of the class itself:

class Position:
    ...
    def __add__(self, other: 'Position') -> 'Position':
       ...

If you use the Django framework, this may be familiar, as Django models also use strings for forward references (foreign key definitions where the foreign model is self or is not declared yet). This should work with Pycharm and other tools.

Sources

The relevant parts of PEP 484 and PEP 563, to spare you the trip:

Forward references

When a type hint contains names that have not been defined yet, that definition may be expressed as a string literal, to be resolved later.

A situation where this occurs commonly is the definition of a container class, where the class being defined occurs in the signature of some of the methods. For example, the following code (the start of a simple binary tree implementation) does not work:

class Tree:
    def __init__(self, left: Tree, right: Tree):
        self.left = left
        self.right = right

To address this, we write:

class Tree:
    def __init__(self, left: 'Tree', right: 'Tree'):
        self.left = left
        self.right = right

The string literal should contain a valid Python expression (i.e., compile(lit, '', 'eval') should be a valid code object) and it should evaluate without errors once the module has been fully loaded. The local and global namespace in which it is evaluated should be the same namespaces in which default arguments to the same function would be evaluated.

and PEP 563:

Implementation

In Python 3.10, function and variable annotations will no longer be evaluated at definition time. Instead, a string form will be preserved in the respective __annotations__ dictionary. Static type checkers will see no difference in behavior, whereas tools using annotations at runtime will have to perform postponed evaluation.

...

Enabling the future behavior in Python 3.7

The functionality described above can be enabled starting from Python 3.7 using the following special import:

from __future__ import annotations

Things that you may be tempted to do instead

A. Define a dummy Position

Before the class definition, place a dummy definition:

class Position(object):
    pass

class Position(object):
    ...

This will get rid of the NameError and may even look OK:

>>> Position.__add__.__annotations__
{'other': __main__.Position, 'return': __main__.Position}

But is it?

>>> for k, v in Position.__add__.__annotations__.items():
...     print(k, 'is Position:', v is Position)                                                                                                                                                                                                                  
return is Position: False
other is Position: False

B. Monkey-patch in order to add the annotations:

You may want to try some Python metaprogramming magic and write a decorator
to monkey-patch the class definition in order to add annotations:

class Position:
    ...
    def __add__(self, other):
        return self.__class__(self.x + other.x, self.y + other.y)

The decorator should be responsible for the equivalent of this:

Position.__add__.__annotations__['return'] = Position
Position.__add__.__annotations__['other'] = Position

At least it seems right:

>>> for k, v in Position.__add__.__annotations__.items():
...     print(k, 'is Position:', v is Position)                                                                                                                                                                                                                  
return is Position: True
other is Position: True

Probably too much trouble.

Python type hinting own class in method

The name Foo doesn't yet exist, so you need to use 'Foo' instead. (mypy and other type checkers should recognize this as a forward reference.)

def __eq__(self, other: 'Foo'):
    return self.id == other.id

Alternately, you can use

from __future__ import annotations

which prevents evaluation of all annotations and simply stores them as strings for later reference. (This will be the default in Python 3.10.)

Finally, as also pointed out in the comments, __eq__ should not be hinted this way in the first place. The second argument should be an arbitrary object; you'll return NotImplemented if you don't know how to compare your instance to it. (Who knows, maybe it knows how to compare itself to your instance. If Foo.__eq__(Foo(), Bar()) returns NotImplemented, then Python will try Bar.__eq__(Bar(), Foo()).)

from typing import Any

def __eq__(self, other: Any) -> bool:
    if isinstance(other, Foo):
        return self.id == other.id
    return NotImplemented

or using duck-typing,

def __eq__(self, other: Any) -> bool:
    # Compare to anything with an `id` attribute
    try:
        return self.id == other.id
    except AttributeError:
        return NotImplemented

In either case, the Any hint is optional.

How to write the type hint for an argument that can be of either class A or class B?

You can use Union to specify multiple type hintings (for both, arguments and return type). You will have to import Union from standard library typing.

from typing import Union

class A:
    def __init__(self, name) -> None:
        self.name = name

class B:
    def __init__(self, name) -> None:
        self.name = name 

class ObjectInfo:
    def __init__(self) -> None:
        pass 

    def method(self, object:Union[A, B]=None) -> list:
        return dir(object)

obj = ObjectInfo()
print(obj.method())

[External Links]
More on type hinting : https://docs.python.org/3/library/typing.html

Python: How to Type Hint a Class Argument in a Static Method Python?

A possible workaround in this case would be to monkey-patch the method after defining the class:

class Circle:
    def __init__(self, r, _id):
        self.r = r
        self.id =  _id

    def area(self):
        return math.pi * (self.r ** 2)

def compare_circles(circle_1: Circle, circle_2: Circle) -> str:
    if circle_1.r < circle_2.r:
        return circle_1.id
    else:
        return circle_2.id

Circle.compare_circles = staticmethod(compare_circles)
del compare_circles

The usual way would be to provide a string with the type name:

class Circle:
    def __init__(self, r, _id):
        self.r = r
        self.id =  _id

    def area(self):
        return math.pi * (self.r ** 2)

    @staticmethod
    def compare_circles(circle_1: 'Circle', circle_2: 'Circle') -> str:
        if circle_1.r < circle_2.r:
            return circle_1.id
        else:
            return circle_2.id

As an aside, you might also consider turning compare_circles into a method:

def compare(self, other: 'Circle') -> str:
    if self.r < other.r:
        return self.id
    else:
        return other.id

How to type hint an instance-level function (i.e. not a method)?

This is currently broken in mypy as it assumes you are creating a method, here is the relevant issue https://github.com/python/mypy/issues/708.

Typing the function in the init works fine as it won't think it's a method on the class, the following code passes type checking properly and func's type is inferred from the parameter. The attribute assignment can also be typed directly if the parameter is not viable.

from collections.abc import Callable

class Foo:
    def __init__(self, func: Callable[[], int]):
        self.func = func

reveal_type(Foo(lambda: 0).func)
###OUTPUT###
file.py:7: note: Revealed type is "def () -> builtins.int"

An another workaround that can be found in the issue and avoids assigning in the init is to use a callback Protocol like so:

from typing import Protocol

class FuncCallback(Protocol):
    def __call__(self, /) -> int:
        ...

class Foo:
    func: FuncCallback

    def __init__(self, func):
        self.func = func

This makes func a FuncCallback protocol which expects no arguments when called and returns an int like your Callable.

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