179
votes

I'm trying to split my huge class into two; well, basically into the "main" class and a mixin with additional functions, like so:

main.py file:

import mymixin.py

class Main(object, MyMixin):
    def func1(self, xxx):
        ...

mymixin.py file:

class MyMixin(object):
    def func2(self: Main, xxx):  # <--- note the type hint
        ...

Now, while this works just fine, the type hint in MyMixin.func2 of course can't work. I can't import main.py, because I'd get a cyclic import and without the hint, my editor (PyCharm) can't tell what self is.

I'm using Python 3.4, willing to move to 3.5 if a solution is available there.

Is there any way I can split my class into two files and keep all the "connections" so that my IDE still offers me auto completion & all the other goodies that come from it knowing the types?

6
I don't think you should normally need to annotate the type of self, since it's always going to be a subclass of the current class (and any type checking system should be able to figure that out on its own). Is func2 trying to call func1, which isn't defined in MyMixin? Perhaps it should be (as an abstractmethod, maybe)?Blckknght
also note that generally more-specific classes (eg your mixin) should go to the left of base classes in the class definition i.e. class Main(MyMixin, SomeBaseClass) so that methods from the more-specific class can override ones from the base classAnentropic
I'm not sure how these comments are useful, since they are tangential to the question being asked. velis wasn't asking for a code review.Jacob Lee
Python type hints with imported class methods provides an elegant solution to your problem.Ben Mares

6 Answers

263
votes

There isn't a hugely elegant way to handle import cycles in general, I'm afraid. Your choices are to either redesign your code to remove the cyclic dependency, or if it isn't feasible, do something like this:

# some_file.py

from typing import TYPE_CHECKING
if TYPE_CHECKING:
    from main import Main

class MyObject(object):
    def func2(self, some_param: 'Main'):
        ...

The TYPE_CHECKING constant is always False at runtime, so the import won't be evaluated, but mypy (and other type-checking tools) will evaluate the contents of that block.

We also need to make the Main type annotation into a string, effectively forward declaring it since the Main symbol isn't available at runtime.

If you are using Python 3.7+, we can at least skip having to provide an explicit string annotation by taking advantage of PEP 563:

# some_file.py

from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
    from main import Main

class MyObject(object):
    # Hooray, cleaner annotations!
    def func2(self, some_param: Main):
        ...

The from __future__ import annotations import will make all type hints be strings and skip evaluating them. This can help make our code here mildly more ergonomic.

All that said, using mixins with mypy will likely require a bit more structure then you currently have. Mypy recommends an approach that's basically what deceze is describing -- to create an ABC that both your Main and MyMixin classes inherit. I wouldn't be surprised if you ended up needing to do something similar in order to make Pycharm's checker happy.

46
votes

For people struggling with cyclic imports when importing class only for Type checking: you will likely want to use a Forward Reference (PEP 484 - Type Hints):

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.

So instead of:

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

you do:

class Tree:
    def __init__(self, left: 'Tree', right: 'Tree'):
        self.left = left
        self.right = right
14
votes

The bigger issue is that your types aren't sane to begin with. MyMixin makes a hardcoded assumption that it will be mixed into Main, whereas it could be mixed into any number of other classes, in which case it would probably break. If your mixin is hardcoded to be mixed into one specific class, you may as well write the methods directly into that class instead of separating them out.

To properly do this with sane typing, MyMixin should be coded against an interface, or abstract class in Python parlance:

import abc


class MixinDependencyInterface(abc.ABC):
    @abc.abstractmethod
    def foo(self):
        pass


class MyMixin:
    def func2(self: MixinDependencyInterface, xxx):
        self.foo()  # ← mixin only depends on the interface


class Main(MixinDependencyInterface, MyMixin):
    def foo(self):
        print('bar')
5
votes

Turns out my original attempt was quite close to the solution as well. This is what I'm currently using:

# main.py
import mymixin.py

class Main(object, MyMixin):
    def func1(self, xxx):
        ...


# mymixin.py
if False:
    from main import Main

class MyMixin(object):
    def func2(self: 'Main', xxx):  # <--- note the type hint
        ...

Note the import within if False statement that never gets imported (but IDE knows about it anyway) and using the Main class as string because it's not known at runtime.

0
votes

I would advice refactoring your code, as some other persons suggested.

I can show you a circular error I recently faced:

BEFORE:

# person.py
from spell import Heal, Lightning

class Person:
    def __init__(self):
        self.life = 100

class Jedi(Person):
    def heal(self, other: Person):
        Heal(self, other)

class Sith(Person):
    def lightning(self, other: Person):
        Lightning(self, other)

# spell.py
from person import Person, Jedi, Sith

class Spell:
    def __init__(self, caster: Person, target: Person):
        self.caster: Person = caster
        self.target: Person = target

class Heal(Spell):
    def __init__(self, caster: Jedi, target: Person):
        super().__init__(caster, target)
        target.life += 10

class Lightning(Spell):
    def __init__(self, caster: Sith, target: Person):
        super().__init__(caster, target)
        target.life -= 10

# main.py
from person import Jedi, Sith

Step by step:

# main starts to import person
from person import Jedi, Sith

# main did not reach end of person but ...
# person starts to import spell
from spell import Heal, Lightning

# Remember: main is still importing person
# spell starts to import person
from person import Person, Jedi, Sith

console:

ImportError: cannot import name 'Person' from partially initialized module
'person' (most likely due to a circular import)

A script/module can be imported only by one and only one script.

AFTER:

# person.py
class Person:
    def __init__(self):
        self.life = 100

# spell.py
from person import Person

class Spell:
    def __init__(self, caster: Person, target: Person):
        self.caster: Person = caster
        self.target: Person = target

# jedi.py
from person import Person
from spell import Spell

class Jedi(Person):
    def heal(self, other: Person):
        Heal(self, other)

class Heal(Spell):
    def __init__(self, caster: Jedi, target: Person):
        super().__init__(caster, target)
        target.life += 10

# sith.py
from person import Person
from spell import Spell

class Sith(Person):
    def lightning(self, other: Person):
        Lightning(self, other)

class Lightning(Spell):
    def __init__(self, caster: Sith, target: Person):
        super().__init__(caster, target)
        target.life -= 10

# main.py
from jedi import Jedi
from sith import Sith

jedi = Jedi()
print(jedi.life)
Sith().lightning(jedi)
print(jedi.life)

order of executed lines:

from jedi import Jedi  # start read of jedi.py
from person import Person  # start AND finish read of person.py
from spell import Spell  # start read of spell.py
from person import Person  # start AND finish read of person.py
# finish read of spell.py

# idem for sith.py

console:

100
90

File composition is key Hope it will help :D

-5
votes

I think the perfect way should be to import all the classes and dependencies in a file (like __init__.py) and then from __init__ import * in all the other files.

In this case you are

  1. avoiding multiple references to those files and classes and
  2. also only have to add one line in each of the other files and
  3. the third would be the pycharm knowing about all of the classes that you might use.