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

Question

I have the following code in python 3:

class Position:

    def __init__(self, x: int, y: int):
        self.x = x
        self.y = y

    def __add__(self,          


        

Answer 1

The name 'Position' is not avalilable at the time the class body itself is parsed. I don't know how you are using the type declarations, but Python's PEP 484 - which is what most mode should use if using these typing hints say that you can simply put the name as a string at this point:

def __add__(self, other: 'Position') -> 'Position':
    return Position(self.x + other.x, self.y + other.y)

Check https://www.python.org/dev/peps/pep-0484/#forward-references - tools conforming to that will know to unwrap the class name from there and make use of it.(It is always important to have in mind that the Python language itself does nothing of these annotations - they are usually meant for static-code analysis, or one could have a library/framework for type checking in run-time - but you have to explicitly set that).

update Also, as of Python 3.7, check pep-563 - as of Python 3.8 it is possible to write from __future__ import annotations to defer the evaluation of annotations - forward referencing classes should work straightforward.

Answer 2

TL;DR: if you are using Python 3.10 or later, it just works. As of today (2019) in 3.7+ you must turn this feature on using a future statement (from __future__ import annotations) - for Python 3.6 or below use a string.

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 3.10 or later.

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 is scheduled to become the default in Python 3.10. 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 if you import typing you will see 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:

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.

...

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 meta programming 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.

Conclusion

If you are using 3.6 or below use a string literal containing the class name, in 3.7 use from __future__ import annotations and it will just work.

Answer 3

If you only care about fixing the NameError: name 'Position' is not defined, you can either specify the class name as a string:

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

Or if you use Python 3.7 or higher, add the following line to the top of your code (just before the other imports)

from __future__ import annotations

However, if you also want this to work for subclasses, and return the specific subclass, you need to use a Generic class, by define a TypeVar.

What is slightly uncommon is that the TypeVar is bound to the type of self. Basically, this typing hinting tells the type checker that the return type of __add__() and copy() are the same type as self.

from __future__ import annotations

from typing import TypeVar

T = TypeVar('T', bound=Position)

class Position:
    
    def __init__(self, x: int, y: int):
        self.x = x
        self.y = y
    
    def __add__(self: T, other: Position) -> T:
        return type(self)(self.x + other.x, self.y + other.y)
    
    def copy(self: T) -> T:
        return type(self)(self.x, self.y)

Answer 4

When a string-based type hint is acceptable, the __qualname__ item can also be used. It holds the name of the class, and it is available in the body of the class definition.

class MyClass:
    @classmethod
    def make_new(cls) -> __qualname__:
        return cls()

By doing this, renaming the class does not imply modifying the type hints. But I personally would not expect smart code editors to handle this form well.

Answer 5

Specifying the type as string is fine, but always grates me a bit that we are basically circumventing the parser. So you better not misspell any one of these literal strings:

def __add__(self, other: 'Position') -> 'Position':
    return Position(self.x + other.x, self.y + other.y)

A slight variation is to use a bound typevar, at least then you have to write the string only once when declaring the typevar:

from typing import TypeVar

T = TypeVar('T', bound='Position')

class Position:

    def __init__(self, x: int, y: int):
        self.x = x
        self.y = y

    def __add__(self, other: T) -> T:
        return Position(self.x + other.x, self.y + other.y)