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How do I pass attributes of first class to another class inside a class [duplicate]

I have a situation like so...
class Outer(object):
def some_method(self):
# do something
class Inner(object):
def __init__(self):
self.Outer.some_method() # <-- this is the line in question
How can I access the Outer class's method from the Inner class?

You're trying to access Outer's class instance, from inner class instance. So just use factory-method to build Inner instance and pass Outer instance to it.
class Outer(object):
def createInner(self):
return Outer.Inner(self)
class Inner(object):
def __init__(self, outer_instance):
self.outer_instance = outer_instance
self.outer_instance.somemethod()
def inner_method(self):
self.outer_instance.anothermethod()

The methods of a nested class cannot directly access the instance attributes of the outer class.
Note that it is not necessarily the case that an instance of the outer class exists even when you have created an instance of the inner class.
In fact, it is often recommended against using nested classes, since the nesting does not imply any particular relationship between the inner and outer classes.

maybe I'm mad but this seems very easy indeed - the thing is to make your inner class inside a method of the outer class...
def do_sthg(self):
...
def mess_around(self):
outer_class_self = self
class Mooble():
def do_sthg_different(self):
...
outer_class_self.do_sthg()
Plus... "self" is only used by convention, so you could do this:
def do_sthg(self):
...
def mess_around(outer_class_self):
class Mooble():
def do_sthg_different(self):
...
outer_class_self.do_sthg()
It might be objected that you can't then create this inner class from outside the outer class... but this ain't true:
class Bumblebee():
def do_sthg(self):
print "sthg"
def give_me_an_inner_class(outer_class_self):
class Mooble():
def do_sthg_different(self):
print "something diff\n"
outer_class_self.do_sthg()
return Mooble
then, somewhere miles away:
blob = Bumblebee().give_me_an_inner_class()()
blob.do_sthg_different()
even push the boat out a bit and extend this inner class (NB to get super() to work you have to change the class signature of Mooble to class Mooble(object)).
class InnerBumblebeeWithAddedBounce(Bumblebee().give_me_an_inner_class()):
def bounce(self):
print "bounce"
def do_sthg_different(self):
super(InnerBumblebeeWithAddedBounce, self).do_sthg_different()
print "and more different"
ibwab = InnerBumblebeeWithAddedBounce()
ibwab.bounce()
ibwab.do_sthg_different()
later
mrh1997 raised an interesting point about the non-common inheritance of inner classes delivered using this technique. But it seems that the solution is pretty straightforward:
class Fatty():
def do_sthg(self):
pass
class InnerFatty(object):
pass
def give_me_an_inner_fatty_class(self):
class ExtendedInnerFatty(Fatty.InnerFatty):
pass
return ExtendedInnerFatty
fatty1 = Fatty()
fatty2 = Fatty()
innerFattyClass1 = fatty1.give_me_an_inner_fatty_class()
innerFattyClass2 = fatty2.give_me_an_inner_fatty_class()
print (issubclass(innerFattyClass1, Fatty.InnerFatty))
print (issubclass(innerFattyClass2, Fatty.InnerFatty))

I found this.
Tweaked to suite your question:
class Outer(object):
def some_method(self):
# do something
class _Inner(object):
def __init__(self, outer):
outer.some_method()
def Inner(self):
return _Inner(self)
I’m sure you can somehow write a decorator for this or something
related: What is the purpose of python's inner classes?

A few years late to the party.... but to expand on #mike rodent's wonderful answer, I've provided my own example below that shows just how flexible his solution is, and why it should be (or should have been) the accepted answer.
Python 3.7
class Parent():
def __init__(self, name):
self.name = name
self.children = []
class Inner(object):
pass
def Child(self, name):
parent = self
class Child(Parent.Inner):
def __init__(self, name):
self.name = name
self.parent = parent
parent.children.append(self)
return Child(name)
parent = Parent('Bar')
child1 = parent.Child('Foo')
child2 = parent.Child('World')
print(
# Getting its first childs name
child1.name, # From itself
parent.children[0].name, # From its parent
# Also works with the second child
child2.name,
parent.children[1].name,
# Go nuts if you want
child2.parent.children[0].name,
child1.parent.children[1].name
)
print(
# Getting the parents name
parent.name, # From itself
child1.parent.name, # From its children
child2.parent.name,
# Go nuts again if you want
parent.children[0].parent.name,
parent.children[1].parent.name,
# Or insane
child2.parent.children[0].parent.children[1].parent.name,
child1.parent.children[1].parent.children[0].parent.name
)
# Second parent? No problem
parent2 = Parent('John')
child3 = parent2.Child('Doe')
child4 = parent2.Child('Appleseed')
print(
child3.name, parent2.children[0].name,
child4.name, parent2.children[1].name,
parent2.name # ....
)
Output:
Foo Foo World World Foo World
Bar Bar Bar Bar Bar Bar Bar
Doe Doe Appleseed Appleseed John
Again, a wonderful answer, props to you mike!

You can easily access to outer class using metaclass: after creation of outer class check it's attribute dict for any classes (or apply any logic you need - mine is just trivial example) and set corresponding values:
import six
import inspect
# helper method from `peewee` project to add metaclass
_METACLASS_ = '_metaclass_helper_'
def with_metaclass(meta, base=object):
return meta(_METACLASS_, (base,), {})
class OuterMeta(type):
def __new__(mcs, name, parents, dct):
cls = super(OuterMeta, mcs).__new__(mcs, name, parents, dct)
for klass in dct.values():
if inspect.isclass(klass):
print("Setting outer of '%s' to '%s'" % (klass, cls))
klass.outer = cls
return cls
# #six.add_metaclass(OuterMeta) -- this is alternative to `with_metaclass`
class Outer(with_metaclass(OuterMeta)):
def foo(self):
return "I'm outer class!"
class Inner(object):
outer = None # <-- by default it's None
def bar(self):
return "I'm inner class"
print(Outer.Inner.outer)
>>> <class '__main__.Outer'>
assert isinstance(Outer.Inner.outer(), Outer)
print(Outer().foo())
>>> I'm outer class!
print(Outer.Inner.outer().foo())
>>> I'm outer class!
print(Outer.Inner().outer().foo())
>>> I'm outer class!
print(Outer.Inner().bar())
>>> I'm inner class!
Using this approach, you can easily bind and refer two classes between each other.

I've created some Python code to use an outer class from its inner class, based on a good idea from another answer for this question. I think it's short, simple and easy to understand.
class higher_level__unknown_irrelevant_name__class:
def __init__(self, ...args...):
...other code...
# Important lines to access sub-classes.
subclasses = self._subclass_container()
self.some_subclass = subclasses["some_subclass"]
del subclasses # Free up variable for other use.
def sub_function(self, ...args...):
...other code...
def _subclass_container(self):
_parent_class = self # Create access to parent class.
class some_subclass:
def __init__(self):
self._parent_class = _parent_class # Easy access from self.
# Optional line, clears variable space, but SHOULD NOT BE USED
# IF THERE ARE MULTIPLE SUBCLASSES as would stop their parent access.
# del _parent_class
class subclass_2:
def __init__(self):
self._parent_class = _parent_class
# Return reference(s) to the subclass(es).
return {"some_subclass": some_subclass, "subclass_2": subclass_2}
The main code, "production ready" (without comments, etc.). Remember to replace all of each value in angle brackets (e.g. <x>) with the desired value.
class <higher_level_class>:
def __init__(self):
subclasses = self._subclass_container()
self.<sub_class> = subclasses[<sub_class, type string>]
del subclasses
def _subclass_container(self):
_parent_class = self
class <sub_class>:
def __init__(self):
self._parent_class = _parent_class
return {<sub_class, type string>: <sub_class>}
Explanation of how this method works (the basic steps):
Create a function named _subclass_container to act as a wrapper to access the variable self, a reference to the higher level class (from code running inside the function).
Create a variable named _parent_class which is a reference to the variable self of this function, that the sub-classes of _subclass_container can access (avoids name conflicts with other self variables in subclasses).
Return the sub-class/sub-classes as a dictionary/list so code calling the _subclass_container function can access the sub-classes inside.
In the __init__ function inside the higher level class (or wherever else needed), receive the returned sub-classes from the function _subclass_container into the variable subclasses.
Assign sub-classes stored in the subclasses variable to attributes of the higher level class.
A few tips to make scenarios easier:
Making the code to assign the sub classes to the higher level class easier to copy and be used in classes derived from the higher level class that have their __init__ function changed:
Insert before line 12 in the main code:
def _subclass_init(self):
Then insert into this function lines 5-6 (of the main code) and replace lines 4-7 with the following code:
self._subclass_init(self)
Making subclass assigning to the higher level class possible when there are many/unknown quantities of subclasses.
Replace line 6 with the following code:
for subclass_name in list(subclasses.keys()):
setattr(self, subclass_name, subclasses[subclass_name])
Example scenario of where this solution would be useful and where the higher level class name should be impossible to get:
A class, named "a" (class a:) is created. It has subclasses that need to access it (the parent). One subclass is called "x1". In this subclass, the code a.run_func() is run.
Then another class, named "b" is created, derived from class "a" (class b(a):). After that, some code runs b.x1() (calling the sub function "x1" of b, a derived sub-class). This function runs a.run_func(), calling the function "run_func" of class "a", not the function "run_func" of its parent, "b" (as it should), because the function which was defined in class "a" is set to refer to the function of class "a", as that was its parent.
This would cause problems (e.g. if function a.run_func has been deleted) and the only solution without rewriting the code in class a.x1 would be to redefine the sub-class x1 with updated code for all classes derived from class "a" which would obviously be difficult and not worth it.

Do you mean to use inheritance, rather than nesting classes like this? What you're doing doesn't make a heap of sense in Python.
You can access the Outer's some_method by just referencing Outer.some_method within the inner class's methods, but it's not going to work as you expect it will. For example, if you try this:
class Outer(object):
def some_method(self):
# do something
class Inner(object):
def __init__(self):
Outer.some_method()
...you'll get a TypeError when initialising an Inner object, because Outer.some_method expects to receive an Outer instance as its first argument. (In the example above, you're basically trying to call some_method as a class method of Outer.)

Another possibility:
class _Outer (object):
# Define your static methods here, e.g.
#staticmethod
def subclassRef ():
return Outer
class Outer (_Outer):
class Inner (object):
def outer (self):
return _Outer
def doSomething (self):
outer = self.outer ()
# Call your static mehthods.
cls = outer.subclassRef ()
return cls ()

What we can do is pass the self variable of Outer Class inside the Inner Class as Class Argument and Under Outer init initialise the Inner Class with Outer self passed into Inner
class Outer:
def __init__(self):
self.somevalue=91
self.Inner=self.Inner(self)
def SomeMethod(self):
print('This is Something from Outer Class')
class Inner:
def __init__(self,Outer)
self.SomeMethod=Outer.SomeMethod
self.somevalue=Outer.somevalue
def SomeAnotherMethod(self):
print(self.somevalue)
self.SomeMethod()
>>>f=Outer()
>>>f.Inner.SomeAnotherMethod()
91
This is Something from Outer Class
Now After running this function it Works

Expanding on #tsnorri's cogent thinking, that the outer method may be a static method:
class Outer(object):
#staticmethod
def some_static_method(self):
# do something
class Inner(object):
def __init__(self):
self.some_static_method() # <-- this will work later
Inner.some_static_method = some_static_method
Now the line in question should work by the time it is actually called.
The last line in the above code gives the Inner class a static method that's a clone of the Outer static method.
This takes advantage of two Python features, that functions are objects, and scope is textual.
Usually, the local scope references the local names of the (textually) current function.
...or current class in our case. So objects "local" to the definition of the Outer class (Inner and some_static_method) may be referred to directly within that definition.

You may create a class, to decorate inner classes. In this case #inner.
Since this a decorator: Outer.A = inner(Outer.A). Once your code requires Outer.A it will be executed inner.__get__ method, which returns the original class (A) with a new attribute set on it: A.owner = Outer.
A classmethod in class A, in this case def add(cls, y=3), may use new attribute owner at return cls.owner.x + y + 1.
The line setattr(owner, name, self.inner), breaks the descriptor because owner.name => Outer.A => A is no longer an instance of the class inner.
Hope this helps.
class inner:
def __init__(self, inner):
self.inner = inner
def __get__(self, instance, owner):
print('__get__ method executed, only once... ')
name = self.inner.__name__
setattr(self.inner, 'owner', owner)
setattr(owner, name, self.inner) # breaks descriptor
return self.inner #returns Inner
class Outer:
x = 1
#inner
class A:
#classmethod
def add(cls, y=3):
return cls.owner.x + y + 1
print(Outer.A.add(0)) # First time executes inner.__get__ method
print(Outer.A.add(0)) # Second time not necessary.
>> __get__ method executed, only once...
>> 2
>> 2

It can be done by parsing the outer class object into inner class.
class Outer():
def __init__(self,userinput):
self.userinput = userinput
def outer_function(self):
self.a = self.userinput + 2
class Inner():
def inner_function(self):
self.b = self.a + 10
after defining this, it need to run the function
m = Outer(3)
m.outer_function()
print (m.a)
#this will output 5
Now it has the variable of outer class.
and then, it need to run inner class functions.
m.Inner.inner_function(m)
The object m of outer class is parsed into the function of inner class (inside the brackets)
Now, the inner class function is accessing self.a from the outer class.
print (m.b)
#this will output 15

It is too simple:
Input:
class A:
def __init__(self):
pass
def func1(self):
print('class A func1')
class B:
def __init__(self):
a1 = A()
a1.func1()
def func1(self):
print('class B func1')
b = A.B()
b.func1()
Output
class A func1
class B func1

Python pattern for defaulting to a 'grandparent' class's implementation

class Thing(object):
def sound(self):
return '' #Silent
class Animal(Thing):
def sound(self):
return 'Roar!'
class MuteAnimal(Animal):
def sound(self):
return '' #Silent
Is there a pattern in python for MuteAnimal's sound to refer to its grandparent class Thing's implementation? (eg super(MuteAnimal,self).super(Animal.self).sound() ?) Or is Mixin a better use case here?

As said by Alexander Rossa in
Python inheritance - how to call grandparent method? :
There are two ways to go around this:
Either you can use explicitly A.foo(self) method as the others have
suggested - use this when you want to call the method of the A class
with disregard as to whether A is B's parent class or not:
class C(B): def foo(self):
tmp = A.foo(self) # call A's foo and store the result to tmp
return "C"+tmp
Or, if you want to use the .foo() method of B's parent class regardless whether the parent class is A or not, then
use:
class C(B): def foo(self):
tmp = super(B, self).foo() # call B's father's foo and store the result to tmp
return "C"+tmp

Is it sensible to do this?
In MuteAnimal.sound, call super(Animal, self).sound()
because Animal is in fact, gradparent class of MuteAnimal...

Method Inheritance in Python

I have a parent class and two child class. The parent class is an abstract base class that has method combine that gets inherited by the child classes. But each child implements combine differently from a parameter perspective therefore each of their own methods take different number of parameters. In Python, when a child inherits a method and requires re-implementing it, that newly re-implemented method must match parameter by parameter. Is there a way around this? I.e. the inherited method can have dynamic parameter composition?

This code demonstrates that signature of overridden method can easily change.
class Parent(object):
def foo(self, number):
for _ in range(number):
print "Hello from parent"
class Child(Parent):
def foo(self, number, greeting):
for _ in range(number):
print greeting
class GrandChild(Child):
def foo(self):
super(GrandChild,self).foo(1, "hey")
p = Parent()
p.foo(3)
c = Child()
c.foo(2, "Hi")
g = GrandChild()
g.foo()

As the other answer demonstrates for plain classes, the signature of an overridden inherited method can be different in the child than in the parent.
The same is true even if the parent is an abstract base class:
import abc
class Foo:
__metaclass__ = abc.ABCMeta
#abc.abstractmethod
def bar(self, x, y):
return x + y
class ChildFoo(Foo):
def bar(self, x):
return super(self.__class__, self).bar(x, 3)
class DumbFoo(Foo):
def bar(self):
return "derp derp derp"
cf = ChildFoo()
print cf.bar(5)
df = DumbFoo()
print df.bar()
Inappropriately complicated detour
It is an interesting exercise in Python metaclasses to try to restrict the ability to override methods, such that their argument signature must match that of the base class. Here is an attempt.
Note: I'm not endorsing this as a good engineering idea, and I did not spend time tying up loose ends so there are likely little caveats about the code below that could make it more efficient or something.
import types
import inspect
def strict(func):
"""Add some info for functions having strict signature.
"""
arg_sig = inspect.getargspec(func)
func.is_strict = True
func.arg_signature = arg_sig
return func
class StrictSignature(type):
def __new__(cls, name, bases, attrs):
func_types = (types.MethodType,) # include types.FunctionType?
# Check each attribute in the class being created.
for attr_name, attr_value in attrs.iteritems():
if isinstance(attr_value, func_types):
# Check every base for #strict functions.
for base in bases:
base_attr = base.__dict__.get(attr_name)
base_attr_is_function = isinstance(base_attr, func_types)
base_attr_is_strict = hasattr(base_attr, "is_strict")
# Assert that inspected signatures match.
if base_attr_is_function and base_attr_is_strict:
assert (inspect.getargspec(attr_value) ==
base_attr.arg_signature)
# If everything passed, create the class.
return super(StrictSignature, cls).__new__(cls, name, bases, attrs)
# Make a base class to try out strictness
class Base:
__metaclass__ = StrictSignature
#strict
def foo(self, a, b, c="blah"):
return a + b + len(c)
def bar(self, x, y, z):
return x
#####
# Now try to make some classes inheriting from Base.
#####
class GoodChild(Base):
# Was declared strict, better match the signature.
def foo(self, a, b, c="blah"):
return c
# Was never declared as strict, so no rules!
def bar(im_a_little, teapot):
return teapot/2
# These below can't even be created. Uncomment and try to run the file
# and see. It's not just that you can't instantiate them, you can't
# even get the *class object* defined at class creation time.
#
#class WrongChild(Base):
# def foo(self, a):
# return super(self.__class__, self).foo(a, 5)
#
#class BadChild(Base):
# def foo(self, a, b, c="halb"):
# return super(self.__class__, self).foo(a, b, c)
Note, like with most "strict" or "private" type ideas in Python, that you are still free to monkey-patch functions onto even a "good class" and those monkey-patched functions don't have to satisfy the signature constraint.
# Instance level
gc = GoodChild()
gc.foo = lambda self=gc: "Haha, I changed the signature!"
# Class level
GoodChild.foo = lambda self: "Haha, I changed the signature!"
and even if you add more complexity to the meta class that checks whenever any method type attributes are updated in the class's __dict__ and keeps making the assert statement when the class is modified, you can still use type.__setattr__ to bypass customized behavior and set an attribute anyway.
In these cases, I imagine Jeff Goldblum as Ian Malcolm from Jurassic Park, looking at you blankly and saying "Consenting adults, uhh, find a way.."

Different behavior of a class-member which could be a type or a factory-function

Whenever I define a class whose instances create objects of other classes, I like defining the types of those other objects as class members:
class Foo(object):
DICT_TYPE = dict # just a trivial example
def __init__(self):
self.mydict = self.DICT_TYPE()
class Bar(Foo):
DICT_TYPE = OrderedDict # no need to override __init__ now
The idea is to allow potential subclasses to easily override it.
I've just found a problem with this habbit, when the "type" I use is not really a type, but a factory function. For example, RLock is confusingly not a class:
def RLock(*args, **kwargs):
return _RLock(*args, **kwargs)
Thus using it the same way is no good:
class Foo(object):
LOCK_TYPE = threading.RLock # alas, RLock() is a function...
def __init__(self):
self.lock = self.LOCK_TYPE()
The problem here is that since RLock is a function, self.LOCK_TYPE gets bound to self, resulting with a bound-method, consequently leading to an error.
Here's a quick demonstration of how things go wrong when a function is used instead of a class (for a case simpler than RLock above):
def dict_factory():
return {}
class Foo(object):
DICT_TYPE1 = dict
DICT_TYPE2 = dict_factory
f = Foo()
f.DICT_TYPE1()
=> {}
f.DICT_TYPE2()
=> TypeError: dict_factory() takes no arguments (1 given)
Does anybody have a good solution for this problem? Is my habbit of defining those class members fundamentally wrong?
I guess I could replace it with a factory method. Would that be a better approach?
class Foo(object);
def __init__(self):
self.lock = self._make_lock()
def _make_lock(self):
return threading.RLock()

you could use the staticmethod decorator to ensure your class does not get passed in
>>> class Foo(object):
... DICT_TYPE = staticmethod(my_dict)
...
>>> f = Foo()
>>> f.DICT_TYPE()
{}

The problem can be bypassed by using a classproperty (e.g. as defined in this answer):
class Foo(object):
#classproperty
def DICT_TYPE(cls):
return dict_factory

Python Method overriding, does signature matter?

Lets say I have
class Super():
def method1():
pass
class Sub(Super):
def method1(param1, param2, param3):
stuff
Is this correct? Will calls to method1 always go to the sub class? My plan is to have 2 sub classes each override method1 with different params

In Python, methods are just key-value pairs in the dictionary attached to the class. When you are deriving a class from a base class, you are essentially saying that method name will be looked into first derived class dictionary and then in the base class dictionary. In order to "override" a method, you simply re-declare the method in the derived class.
So, what if you change the signature of the overridden method in the derived class? Everything works correctly if the call is on the derived instance but if you make the call on the base instance, you will get an error because the base class uses a different signature for that same method name.
There are however frequent scenarios where you want derived class method have additional parameters and you want method call work without error on base as well. This is called "Liskov substitution principle" (or LSP) which guarantees that if person switches from base to derived instance or vice versa, they don't have to revamp their code. To do this in Python, you need to design your base class with the following technique:
class Base:
# simply allow additional args in base class
def hello(self, name, *args, **kwargs):
print("Hello", name)
class Derived(Base):
# derived class also has unused optional args so people can
# derive new class from this class as well while maintaining LSP
def hello(self, name, age=None, *args, **kwargs):
super(Derived, self).hello(name, age, *args, **kwargs)
print('Your age is ', age)
b = Base()
d = Derived()
b.hello('Alice') # works on base, without additional params
b.hello('Bob', age=24) # works on base, with additional params
d.hello('Rick') # works on derived, without additional params
d.hello('John', age=30) # works on derived, with additional params
Above will print:
Hello Alice
Hello Bob
Hello Rick
Your age is None
Hello John
Your age is 30
.
Play with this code

Python will allow this, but if method1() is intended to be executed from external code then you may want to reconsider this, as it violates LSP and so won't always work properly.

You could do something like this if it's ok to use default arguments:
>>> class Super():
... def method1(self):
... print("Super")
...
>>> class Sub(Super):
... def method1(self, param1="X"):
... super(Sub, self).method1()
... print("Sub" + param1)
...
>>> sup = Super()
>>> sub = Sub()
>>> sup.method1()
Super
>>> sub.method1()
Super
SubX

In python, all class methods are "virtual" (in terms of C++). So, in the case of your code, if you'd like to call method1() in super class, it has to be:
class Super():
def method1(self):
pass
class Sub(Super):
def method1(self, param1, param2, param3):
super(Sub, self).method1() # a proxy object, see http://docs.python.org/library/functions.html#super
pass
And the method signature does matter. You can't call a method like this:
sub = Sub()
sub.method1()

It will work:
>>> class Foo(object):
... def Bar(self):
... print 'Foo'
... def Baz(self):
... self.Bar()
...
>>> class Foo2(Foo):
... def Bar(self):
... print 'Foo2'
...
>>> foo = Foo()
>>> foo.Baz()
Foo
>>>
>>> foo2 = Foo2()
>>> foo2.Baz()
Foo2
However, this isn't generally recommended. Take a look at S.Lott's answer: Methods with the same name and different arguments are a code smell.