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Why does the not operator on empty super() object deliver False? [duplicate]

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How does `super` interacts with a class's `__mro__` attribute in multiple inheritance?
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From Python3's documentation super() "returns a proxy object that delegates method calls to a parent or sibling class of type." What does that mean?
Suppose I have the following code:
class SuperClass():
def __init__(self):
print("__init__ from SuperClass.")
print("self object id from SuperClass: " + str(id(self)))
class SubClass(SuperClass):
def __init__(self):
print("__init__ from SubClass.")
print("self object id from SubClass: " + str(id(self)))
super().__init__()
sc = SubClass()
The output I get from this is:
__init__ from SubClass.
self object id from SubClass: 140690611849200
__init__ from SuperClass.
self object id from SuperClass: 140690611849200
This means that in the line super().__init__(), super() is returning the current object which is then implicitly passed to the superclass' __init__() method. Is this accurate or am I missing something here?
To put it simply, I want to understand the following:
When super().__init__() is run,
What exactly is being passed to __init__() and how? We are calling it on super() so whatever this is returning should be getting passed to the __init__() method from what I understand about Python so far.
Why don't we have to pass in self to super().__init__()?

returns a proxy object that delegates method calls to a parent or
sibling class of type.
This proxy is an object that acts as the method-calling portion of the parent class. It is not the class itself; rather, it's just enough information so that you can use it to call the parent class methods.
If you call __init__(), you get your own, local, sub-class __init__ function. When you call super(), you get that proxy object, which will redirect you to the parent-class methods. Thus, when you call super().__init__(), that proxy redirects the call to the parent-class __init__ method.
Similarly, if you were to call super().foo, you would get the foo method from the parent class -- again, re-routed by that proxy.
Is that clear to you?
Responses to OP comments
But that must mean that this proxy object is being passed to
__init__() when running super().__init__() right?
Wrong. The proxy object is like a package name, such as calling math.sqrt(). You're not passing math to sqrt, you're using it to denote which sqrt you're using. If you wanted to pass the proxy to __init__, the call would be __init__(super()). That call would be semantically ridiculous, of course.
When we have to actually pass in self which is the sc object in my example.
No, you are not passing in sc; that is the result of the object creation call (internal method __new__), which includes an invocation of init. For __init__, the self object is a new item created for you by the Python run-time system. For most class methods, that first argument (called self out of convention, this in other languages) is the object that invoked the method.

This means that in the line super().__init__(), super() is returning the current object which is then implicitly passed to the superclass' __init__() method. Is this accurate or am I missing something here?
>>> help(super)
super() -> same as super(__class__, <first argument>)
super call returns a proxy/wrapper object which remembers:
The instance invoking super()
The class of the calling object
The class that's invoking super()
This is perfectly sound. super always fetches the attribute of the next class in the hierarchy ( really the MRO) that has the attribute that you're looking for. So it's not returning the current object, but rather and more accurately, it returns an object that remembers enough information to search for attributes higher in the class hierarchy.
What exactly is being passed to __init__() and how? We are calling it on super() so whatever this is returning should be getting passed to the __init__() method from what I understand about Python so far.
You're almost right. But super loves to play tricks on us. super class defines __getattribute__, this method is responsible for attribute search. When you do something like: super().y(), super.__getattribute__ gets called searching for y. Once it finds y it passes the instance that's invoking the super call to y. Also, super has __get__ method, which makes it a descriptor, I'll omit the details of descriptors here, refer to the documentation to know more. This answers your second question as well, as to why self isn't passed explicitly.
*Note: super is a little bit different and relies on some magic. Almost for all other classes, the behavior is the same. That is:
a = A() # A is a class
a.y() # same as A.y(a), self is a
But super is different:
class A:
def y(self):
return self
class B(A):
def y(self)
return super().y() # equivalent to: A.y(self)
b = B()
b.y() is b # True: returns b not super(), self is b not super()

I wrote a simple test to investigate what CPython does for super:
class A:
pass
class B(A):
def f(self):
return super()
#classmethod
def g(cls):
return super()
def h(selfish):
selfish = B()
return super()
class C(B):
pass
c = C()
for method in 'fgh':
super_object = getattr(c, method)()
print(super_object, super_object.__self__, super_object.__self_class__, super_object.__thisclass__) # (These methods were found using dir.)
The zero-argument super call returns an object that stores three things:
__self__ stores the object whose name matches the first parameter of the method—even if that name has been reassigned.
__self_class__ stores its type, or itself in the case of a class method.
__thisclass__ stores the class in which the method is defined.
(It is unfortunate that __thisclass__ was implemented this way rather than fetching an attribute on the method because it makes it impossible to use the zero-argument form of super with meta-programming.)
The object returned by super implements getattribute, which forwards method calls to the type found in the __mro__ of __self_class__ one step after __thisclass__.

Python's inheritance __init__ which self is this self?

I have a question about the init() and inheritance in Python. The following codes are from thinkbayes:
Suppose we have a parent class Pmf where it has functions such as Set() and Normalize(). Now we want to build another class called Cookie that inherits Pmf class.
class Cookie(Pmf):
def __init__(self, hypos):
Pmf.__init__(self)
for hypo in hypos:
self.Set(hypo, 1)
self.Normalize()
Here my question is that, since this is basically redefining a child class's init() after inheriting the init() from the parent class, we call:
Pmf.__init(self)
But, after this line,
for hypo in hypos:
self.Set(hypo, 1)
self.Normalize()
Is the "self" in self.Set(hypo, 1) and self.Normalize() the "self" from Pmf class or from the new Cookie class?
I am a little bit confused...
Thank you very much!

Is the self in self.Set(hypo, 1) and self.Normalize() the self from Pmf class or from the new Cookie class?
It's a false dichotomy: there is only one self. Its type is the class an instance of which is being created. In your example this is Cookie.

If you wrote c = Cookie, then self in both Cookie.__init__ and Pmf.__init__ refer to the same instance of Cookie. The type of self does not change based on which function is called.
The machinery that gets to __init__ is something like this: c = Cookie() (ignoring a couple of steps) first results in a call to Cookie.__new__(), which will return an instance of Cookie. That new instance is then passed to Cookie.__init__; that instance is what self refers to in Cookie.__init__. The type of that instance does not change when you make the call Pmf.__init__(self); it's still an instance of Cookie being further processed by Pmf.__init__.

First you should use the super function:
super(Cookie, self).__init__()
Second the self always refers to the instance of the object. The fact that you call a method from the self object means that you call the first method of that name found in the inheritance tree travelling upwards. So if the Cookie contains such a method, it will be called, and if it doesn't contain one the one contained in the inherited classes will be used. This is what the super does.
Also, there is a different syntax of super between Python3 and Python2

understanding instance object in reference to self convention in __init__(self) function when defining class

New to Python, trying to understand exactly what the self in the __init_(self) function is referring to.
A few tutorials I'm working with describe self as
referring to the instance whose method was called.
Which is not exactly a trivial statement for someone new to OOP.
I've been reading a lot about the whole backstory as to why you have to actually include an explicit self in Python, but need a simple explanation as to what it means to say that self is used to refer to the instance object ——> Does that mean that self is actually referring to the object that is the class itself you've just created? In other words, self somehow "boots up" the class in memory as an object?

Your second-last sentence is correct, but the last sentence is not. It has nothing to do with "booting up" or creating the object at all - the object already exists by that point.
I think you are missing the fact that self is used in all methods, not just __init__, to refer to the specific object that the method belongs to.
For instance, if you had a simple object with a name property, and a method called print_name, it might look like this:
def print_name(self):
print(self.name)
So here the method is using self to refer to the properties of the object it has been called on.

When objects are instantiated, the object itself is passed into the self parameter.
Because of this, the object’s data is bound to the object. Below is an example of how you might like to visualize what each object’s data might look. Notice how ‘self’ is replaced with the objects name. I'm not saying this example diagram below is wholly accurate but it hopefully with serve a purpose in visualizing the use of self.
EDIT (due to further question: Could you explain why exactly when objects are instantiated, the object itself is passed into the self parameter?)
The Object is passed into the self parameter so that the object can keep hold of its own data.
Although this may not be wholly accurate, think of the process of instantiating an object like this: When an object is made it uses the class as a template for its own data and methods. Without passing it's own name into the self parameter, the attributes and methods in the class would remain as a general template and would not be referenced to (belong to) the object. So by passing the object's name into the self parameter it means that if 100 objects are instantiated from the one class, they can all keep track of their own data and methods.
See the illustration below:

Every member function of a class, including the constructor (__init__) is invoked for a certain instance (object) of that class. Member functions have to be able to access the object for which they are called.
So e.g. in a.f(), f() has to have acces to a. In f, defined as f (this), this refers to a.
The special thing for a constructor is that there is no object "before the dot" yet, because precisely that object is being constructed. So this refers to the object "just being constructed" in that case.

When you write myClass(), python first creates an instance of your class, then immediately calls __init__() passing this object as the argument. self is a defined object in memory by the time you call __init__().

Behind the scenes, object construction is actually quite complicated.
Classes are objects too, and the type of a class is type (or a subclass, if using metaclasses). type has a __call__ method that is responsible for constructing instances. It works something like:
class type:
def __call__(cls, *args, **kwargs):
self = cls.__new__(cls, *args, **kwargs)
if isinstance(self, cls):
cls.__init__(self, *args, **kwargs)
Note, the above is for demonstrative purposes only.
Remember that, if a function is not defined on a class itself, it is looked up on its parent (as controlled by the mro), and usually.
Ultimately, __new__ must either call object.__new__(cls) to allocate a new instance of a class cls, or else return an existing object. If the existing object is of a different class, __init__ will not be called. Note that if it returns an existing object of the right class (or a subclass), __init__ will be called more than once. For such classes, all of the work is usually done in __new__.
Chances are you'll never use any of this, but it might help you understand what's going on behind the scenes.

Simply, it means you are referring to a method or variable that is local to the object.

You can look at 'self' as referrer or a pointer to class internals which with that you can invoke methods or add/remove/update/delete attributes . Class is somehow an isolated object which has its own representation of data given to it . So basically , self is only explicitly defined as an argument, which with using that you can get access to class internals . Some programming languages does not explicitly include the keyword self. or some uses this ( like C ++ ) . take a look here:
a = 1
b = 2
class test(object):
def __init__(self,a,b):
self.a = a + 1
self.b = b + 1
def show_internals(self):
print self.a, '\t', self.b
def change_internals(self,a,b):
self.a = a
self.b = b
_my_class = test(3,4)
print a , b
_my_class.show_internals()
_my_class.change_internals(5,6)
_my_class.show_internals()
print a , b
the result is :
1 2
4 5
5 6
1 2
As you can see, with using self you can manipulate the data within the object itself. Otherwise you would end up editing global variables.

Python constructors and __init__

Why are constructors indeed called "Constructors"? What is their purpose and how are they different from methods in a class?
Also, can there be more that one __init__ in a class? I tried the following, can someone please explain the result?
>>> class test:
def __init__(self):
print "init 1"
def __init__(self):
print "init 2"
>>> s=test()
init 2
Finally, is __init__ an operator overloader?

There is no function overloading in Python, meaning that you can't have multiple functions with the same name but different arguments.
In your code example, you're not overloading __init__(). What happens is that the second definition rebinds the name __init__ to the new method, rendering the first method inaccessible.
As to your general question about constructors, Wikipedia is a good starting point. For Python-specific stuff, I highly recommend the Python docs.

Why are constructors indeed called "Constructors" ?
The constructor (named __new__) creates and returns a new instance of the class. So the C.__new__ class method is the constructor for the class C.
The C.__init__ instance method is called on a specific instance, after it is created, to initialise it before being passed back to the caller. So that method is the initialiser for new instances of C.
How are they different from methods in a class?
As stated in the official documentation __init__ is called after the instance is created. Other methods do not receive this treatment.
What is their purpose?
The purpose of the constructor C.__new__ is to define custom behaviour during construction of a new C instance.
The purpose of the initialiser C.__init__ is to define custom initialisation of each instance of C after it is created.
For example Python allows you to do:
class Test(object):
pass
t = Test()
t.x = 10 # here you're building your object t
print t.x
But if you want every instance of Test to have an attribute x equal to 10, you can put that code inside __init__:
class Test(object):
def __init__(self):
self.x = 10
t = Test()
print t.x
Every instance method (a method called on a specific instance of a class) receives the instance as its first argument. That argument is conventionally named self.
Class methods, such as the constructor __new__, instead receive the class as their first argument.
Now, if you want custom values for the x attribute all you have to do is pass that value as argument to __init__:
class Test(object):
def __init__(self, x):
self.x = x
t = Test(10)
print t.x
z = Test(20)
print t.x
I hope this will help you clear some doubts, and since you've already received good answers to the other questions I will stop here :)

Classes are simply blueprints to create objects from. The constructor is some code that are run every time you create an object. Therefor it does'nt make sense to have two constructors. What happens is that the second over write the first.
What you typically use them for is create variables for that object like this:
>>> class testing:
... def __init__(self, init_value):
... self.some_value = init_value
So what you could do then is to create an object from this class like this:
>>> testobject = testing(5)
The testobject will then have an object called some_value that in this sample will be 5.
>>> testobject.some_value
5
But you don't need to set a value for each object like i did in my sample. You can also do like this:
>>> class testing:
... def __init__(self):
... self.some_value = 5
then the value of some_value will be 5 and you don't have to set it when you create the object.
>>> testobject = testing()
>>> testobject.some_value
5
the >>> and ... in my sample is not what you write. It's how it would look in pyshell...

coonstructors are called automatically when you create a new object, thereby "constructing" the object. The reason you can have more than one init is because names are just references in python, and you are allowed to change what each variable references whenever you want (hence dynamic typing)
def func(): #now func refers to an empty funcion
pass
...
func=5 #now func refers to the number 5
def func():
print "something" #now func refers to a different function
in your class definition, it just keeps the later one

There is no notion of method overloading in Python. But you can achieve a similar effect by specifying optional and keyword arguments

python method as argument

So I know in python everything is an 'object' meaning that it can be passed as an argument to a method. But I'm trying to understand how exactly does this work. So I was trying out the following example:
class A:
def __init__(self):
self.value = 'a'
def my_method(self)
print self.value
class B:
def __init__(self):
self.values = 'b'
def my_method(self, method):
method()
a = A()
b = B()
b.my_method(a.my_method)
Now first this was written just to see how things work. I know I should for example check if my_method 's argument is callable. Now my question is:
How exactly is the method passed here? I mean the output I'm recieving is 'a' so I'm guessing that when a object method is passed as parameter so is the actual object ? In this case when I pass a.my_method the instance a is also passed ?

When you access a.my_method Python sees that it is an attribute of the class and that A.my_method has a method __get__() so it calls A.my_method.__get__(a), that method creates a new object (the 'bound method') which contains both a reference to A.my_method and a reference to a itself. When you call the bound method it passes the call back through to the underlying method.
This happens every time you call any method whether you call it directly or, as in your code, delay the actual call until later. You can find more description of the descriptor protocol as it is known at http://docs.python.org/reference/datamodel.html#descriptors

How exactly is the method passed here?
This is easily answered: in Python, everything is an object :) Also functions/methods, which are specific function objects which can be passed as parameters.
In this case when I pass a.my_method the instance a is also passed?
Yes, in this case the instance a is also passed, though embedded in the function object and cannot be retrieved. On the contrary you could pass the function itself and supply it with an instance. Consider the following example:
b = B()
func = A.my_method # Attention, UPPERCASE A
func(b)
This would call the A classes method my_method with an instance of B.

Functions are 'first-class objects' in Python. What that means is that a function is an object as much as a list or an integer. When you define a function, you are actually binding the function object to the name you use in the def.
Functions can be bound to other names or passed as parameters to functions (or stored in lists, or...).
source: http://mail.python.org/pipermail/tutor/2005-October/042616.html

a.my_method returns not exactly the function you defined in the class A (you can get it via A.my_method) but an object called a 'bound method' which contains both the original function (or 'unbound method' in Python 2, IIRC) and the object from which it was retrieved (the self argument).