Understanding Python super() with __init__() methods [duplicate]

super() lets you avoid referring to the base class explicitly, which can be nice. But the main advantage comes with multiple inheritance, where all sorts of fun stuff can happen. See the standard docs on super if you haven't already.

Note that the syntax changed in Python 3.0: you can just say super().__init__() instead of super(ChildB, self).__init__() which IMO is quite a bit nicer. The standard docs also refer to a guide to using super() which is quite explanatory.

I'm trying to understand super()

The reason we use super is so that child classes that may be using cooperative multiple inheritance will call the correct next parent class function in the Method Resolution Order (MRO).

In Python 3, we can call it like this:

class ChildB(Base):
    def __init__(self):
        super().__init__()

In Python 2, we were required to call super like this with the defining class's name and self, but we'll avoid this from now on because it's redundant, slower (due to the name lookups), and more verbose (so update your Python if you haven't already!):

        super(ChildB, self).__init__()

Without super, you are limited in your ability to use multiple inheritance because you hard-wire the next parent's call:

        Base.__init__(self) # Avoid this.

I further explain below.

"What difference is there actually in this code?:"

class ChildA(Base):
    def __init__(self):
        Base.__init__(self)

class ChildB(Base):
    def __init__(self):
        super().__init__()

The primary difference in this code is that in ChildB you get a layer of indirection in the __init__ with super, which uses the class in which it is defined to determine the next class's __init__ to look up in the MRO.

I illustrate this difference in an answer at the canonical question, How to use 'super' in Python?, which demonstrates dependency injection and cooperative multiple inheritance.

If Python didn't have super

Here's code that's actually closely equivalent to super (how it's implemented in C, minus some checking and fallback behavior, and translated to Python):

class ChildB(Base):
    def __init__(self):
        mro = type(self).mro()
        check_next = mro.index(ChildB) + 1 # next after *this* class.
        while check_next < len(mro):
            next_class = mro[check_next]
            if '__init__' in next_class.__dict__:
                next_class.__init__(self)
                break
            check_next += 1

Written a little more like native Python:

class ChildB(Base):
    def __init__(self):
        mro = type(self).mro()
        for next_class in mro[mro.index(ChildB) + 1:]: # slice to end
            if hasattr(next_class, '__init__'):
                next_class.__init__(self)
                break

If we didn't have the super object, we'd have to write this manual code everywhere (or recreate it!) to ensure that we call the proper next method in the Method Resolution Order!

How does super do this in Python 3 without being told explicitly which class and instance from the method it was called from?

It gets the calling stack frame, and finds the class (implicitly stored as a local free variable, __class__, making the calling function a closure over the class) and the first argument to that function, which should be the instance or class that informs it which Method Resolution Order (MRO) to use.

Since it requires that first argument for the MRO, using super with static methods is impossible as they do not have access to the MRO of the class from which they are called.

Criticisms of other answers:

super() lets you avoid referring to the base class explicitly, which can be nice. . But the main advantage comes with multiple inheritance, where all sorts of fun stuff can happen. See the standard docs on super if you haven't already.

It's rather hand-wavey and doesn't tell us much, but the point of super is not to avoid writing the parent class. The point is to ensure that the next method in line in the method resolution order (MRO) is called. This becomes important in multiple inheritance.

I'll explain here.

class Base(object):
    def __init__(self):
        print("Base init'ed")

class ChildA(Base):
    def __init__(self):
        print("ChildA init'ed")
        Base.__init__(self)

class ChildB(Base):
    def __init__(self):
        print("ChildB init'ed")
        super().__init__()

And let's create a dependency that we want to be called after the Child:

class UserDependency(Base):
    def __init__(self):
        print("UserDependency init'ed")
        super().__init__()

Now remember, ChildB uses super, ChildA does not:

class UserA(ChildA, UserDependency):
    def __init__(self):
        print("UserA init'ed")
        super().__init__()

class UserB(ChildB, UserDependency):
    def __init__(self):
        print("UserB init'ed")
        super().__init__()

And UserA does not call the UserDependency method:

>>> UserA()
UserA init'ed
ChildA init'ed
Base init'ed
<__main__.UserA object at 0x0000000003403BA8>

But UserB does in-fact call UserDependency because ChildB invokes super:

>>> UserB()
UserB init'ed
ChildB init'ed
UserDependency init'ed
Base init'ed
<__main__.UserB object at 0x0000000003403438>

Criticism for another answer

In no circumstance should you do the following, which another answer suggests, as you'll definitely get errors when you subclass ChildB:

super(self.__class__, self).__init__()  # DON'T DO THIS! EVER.

_{(That answer is not clever or particularly interesting, but in spite of direct criticism in the comments and over 17 downvotes, the answerer persisted in suggesting it until a kind editor fixed his problem.)}

Explanation: Using self.__class__ as a substitute for the class name in super() will lead to recursion. super lets us look up the next parent in the MRO (see the first section of this answer) for child classes. If you tell super we're in the child instance's method, it will then lookup the next method in line (probably this one) resulting in recursion, probably causing a logical failure (in the answerer's example, it does) or a RuntimeError when the recursion depth is exceeded.

>>> class Polygon(object):
...     def __init__(self, id):
...         self.id = id
...
>>> class Rectangle(Polygon):
...     def __init__(self, id, width, height):
...         super(self.__class__, self).__init__(id)
...         self.shape = (width, height)
...
>>> class Square(Rectangle):
...     pass
...
>>> Square('a', 10, 10)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in __init__
TypeError: __init__() missing 2 required positional arguments: 'width' and 'height'

Python 3's new super() calling method with no arguments fortunately allows us to sidestep this issue.

It's been noted that in Python 3.0+ you can use

super().__init__()

to make your call, which is concise and does not require you to reference the parent OR class names explicitly, which can be handy. I just want to add that for Python 2.7 or under, some people implement a name-insensitive behaviour by writing self.__class__ instead of the class name, i.e.

super(self.__class__, self).__init__()  # DON'T DO THIS!

HOWEVER, this breaks calls to super for any classes that inherit from your class, where self.__class__ could return a child class. For example:

class Polygon(object):
    def __init__(self, id):
        self.id = id

class Rectangle(Polygon):
    def __init__(self, id, width, height):
        super(self.__class__, self).__init__(id)
        self.shape = (width, height)

class Square(Rectangle):
    pass

Here I have a class Square, which is a sub-class of Rectangle. Say I don't want to write a separate constructor for Square because the constructor for Rectangle is good enough, but for whatever reason I want to implement a Square so I can reimplement some other method.

When I create a Square using mSquare = Square('a', 10,10), Python calls the constructor for Rectangle because I haven't given Square its own constructor. However, in the constructor for Rectangle, the call super(self.__class__,self) is going to return the superclass of mSquare, so it calls the constructor for Rectangle again. This is how the infinite loop happens, as was mentioned by @S_C. In this case, when I run super(...).__init__() I am calling the constructor for Rectangle but since I give it no arguments, I will get an error.

Super has no side effects

Base = ChildB

Base()

works as expected

Base = ChildA

Base()

gets into infinite recursion.

Just a heads up... with Python 2.7, and I believe ever since super() was introduced in version 2.2, you can only call super() if one of the parents inherit from a class that eventually inherits object (new-style classes).

Personally, as for python 2.7 code, I'm going to continue using BaseClassName.__init__(self, args) until I actually get the advantage of using super().

There isn't, really. super() looks at the next class in the MRO (method resolution order, accessed with cls.__mro__) to call the methods. Just calling the base __init__ calls the base __init__. As it happens, the MRO has exactly one item-- the base. So you're really doing the exact same thing, but in a nicer way with super() (particularly if you get into multiple inheritance later).

The main difference is that ChildA.__init__ will unconditionally call Base.__init__ whereas ChildB.__init__ will call __init__ in whatever class happens to be ChildB ancestor in self's line of ancestors (which may differ from what you expect).

If you add a ClassC that uses multiple inheritance:

class Mixin(Base):
  def __init__(self):
    print "Mixin stuff"
    super(Mixin, self).__init__()

class ChildC(ChildB, Mixin):  # Mixin is now between ChildB and Base
  pass

ChildC()
help(ChildC) # shows that the Method Resolution Order is ChildC->ChildB->Mixin->Base

then Base is no longer the parent of ChildB for ChildC instances. Now super(ChildB, self) will point to Mixin if self is a ChildC instance.

You have inserted Mixin in between ChildB and Base. And you can take advantage of it with super()

So if you are designed your classes so that they can be used in a Cooperative Multiple Inheritance scenario, you use super because you don't really know who is going to be the ancestor at runtime.

The super considered super post and pycon 2015 accompanying video explain this pretty well.