How does Python's super() work with multiple inheritance?

Question

I\'m pretty much new in Python object oriented programming and I have trouble understanding the super() function (new style classes) especially when it comes to

Answer 1

Another not yet covered point is passing parameters for initialization of classes. Since the destination of super depends on the subclass the only good way to pass parameters is packing them all together. Then be careful to not have the same parameter name with different meanings.

Example:

class A(object):
    def __init__(self, **kwargs):
        print('A.__init__')
        super().__init__()

class B(A):
    def __init__(self, **kwargs):
        print('B.__init__ {}'.format(kwargs['x']))
        super().__init__(**kwargs)


class C(A):
    def __init__(self, **kwargs):
        print('C.__init__ with {}, {}'.format(kwargs['a'], kwargs['b']))
        super().__init__(**kwargs)


class D(B, C): # MRO=D, B, C, A
    def __init__(self):
        print('D.__init__')
        super().__init__(a=1, b=2, x=3)

print(D.mro())
D()

gives:

[<class '__main__.D'>, <class '__main__.B'>, <class '__main__.C'>, <class '__main__.A'>, <class 'object'>]
D.__init__
B.__init__ 3
C.__init__ with 1, 2
A.__init__

Calling the super class __init__ directly to more direct assignment of parameters is tempting but fails if there is any super call in a super class and/or the MRO is changed and class A may be called multiple times, depending on the implementation.

To conclude: cooperative inheritance and super and specific parameters for initialization aren't working together very well.

Answer 2

class First(object):
  def __init__(self, a):
    print "first", a
    super(First, self).__init__(20)

class Second(object):
  def __init__(self, a):
    print "second", a
    super(Second, self).__init__()

class Third(First, Second):
  def __init__(self):
    super(Third, self).__init__(10)
    print "that's it"

t = Third()

Output is

first 10
second 20
that's it

Call to Third() locates the init defined in Third. And call to super in that routine invokes init defined in First. MRO=[First, Second]. Now call to super in init defined in First will continue searching MRO and find init defined in Second, and any call to super will hit the default object init. I hope this example clarifies the concept.

If you don't call super from First. The chain stops and you will get the following output.

first 10
that's it

Answer 3

This is detailed with a reasonable amount of detail by Guido himself in his blog post Method Resolution Order (including two earlier attempts).

In your example, Third() will call First.__init__. Python looks for each attribute in the class's parents as they are listed left to right. In this case, we are looking for __init__. So, if you define

class Third(First, Second):
    ...

Python will start by looking at First, and, if First doesn't have the attribute, then it will look at Second.

This situation becomes more complex when inheritance starts crossing paths (for example if First inherited from Second). Read the link above for more details, but, in a nutshell, Python will try to maintain the order in which each class appears on the inheritance list, starting with the child class itself.

So, for instance, if you had:

class First(object):
    def __init__(self):
        print "first"

class Second(First):
    def __init__(self):
        print "second"

class Third(First):
    def __init__(self):
        print "third"

class Fourth(Second, Third):
    def __init__(self):
        super(Fourth, self).__init__()
        print "that's it"

the MRO would be [Fourth, Second, Third, First].

By the way: if Python cannot find a coherent method resolution order, it'll raise an exception, instead of falling back to behavior which might surprise the user.

Edited to add an example of an ambiguous MRO:

class First(object):
    def __init__(self):
        print "first"

class Second(First):
    def __init__(self):
        print "second"

class Third(First, Second):
    def __init__(self):
        print "third"

Should Third's MRO be [First, Second] or [Second, First]? There's no obvious expectation, and Python will raise an error:

TypeError: Error when calling the metaclass bases
    Cannot create a consistent method resolution order (MRO) for bases Second, First

Edit: I see several people arguing that the examples above lack super() calls, so let me explain: The point of the examples is to show how the MRO is constructed. They are not intended to print "first\nsecond\third" or whatever. You can – and should, of course, play around with the example, add super() calls, see what happens, and gain a deeper understanding of Python's inheritance model. But my goal here is to keep it simple and show how the MRO is built. And it is built as I explained:

>>> Fourth.__mro__
(<class '__main__.Fourth'>,
 <class '__main__.Second'>, <class '__main__.Third'>,
 <class '__main__.First'>,
 <type 'object'>)

Answer 4

I wanted to elaborate the answer by lifeless a bit because when I started reading about how to use super() in a multiple inheritance hierarchy in Python, I did't get it immediately.

What you need to understand is that super(MyClass, self).__init__() provides the next __init__ method according to the used Method Resolution Ordering (MRO) algorithm in the context of the complete inheritance hierarchy.

This last part is crucial to understand. Let's consider the example again:

#!/usr/bin/env python2

class First(object):
  def __init__(self):
    print "First(): entering"
    super(First, self).__init__()
    print "First(): exiting"

class Second(object):
  def __init__(self):
    print "Second(): entering"
    super(Second, self).__init__()
    print "Second(): exiting"

class Third(First, Second):
  def __init__(self):
    print "Third(): entering"
    super(Third, self).__init__()
    print "Third(): exiting"

According to this article about Method Resolution Order by Guido van Rossum, the order to resolve __init__ is calculated (before Python 2.3) using a "depth-first left-to-right traversal" :

Third --> First --> object --> Second --> object

After removing all duplicates, except for the last one, we get :

Third --> First --> Second --> object

So, lets follow what happens when we instantiate an instance of the Third class, e.g. x = Third().

1. According to MRO Third.__init__ executes.
   • prints Third(): entering
   • then super(Third, self).__init__() executes and MRO returns First.__init__ which is called.
2. First.__init__ executes.
   • prints First(): entering
   • then super(First, self).__init__() executes and MRO returns Second.__init__ which is called.
3. Second.__init__ executes.
   • prints Second(): entering
   • then super(Second, self).__init__() executes and MRO returns object.__init__ which is called.
4. object.__init__ executes (no print statements in the code there)
5. execution goes back to Second.__init__ which then prints Second(): exiting
6. execution goes back to First.__init__ which then prints First(): exiting
7. execution goes back to Third.__init__ which then prints Third(): exiting

This details out why instantiating Third() results in to :

Third(): entering
First(): entering
Second(): entering
Second(): exiting
First(): exiting
Third(): exiting

The MRO algorithm has been improved from Python 2.3 onwards to work well in complex cases, but I guess that using the "depth-first left-to-right traversal" + "removing duplicates expect for the last" still works in most cases (please comment if this is not the case). Be sure to read the blog post by Guido!

Answer 5

I understand this doesn't directly answer the super() question, but I feel it's relevant enough to share.

There is also a way to directly call each inherited class:

class First(object):
    def __init__(self):
        print '1'

class Second(object):
    def __init__(self):
        print '2'

class Third(First, Second):
    def __init__(self):
        Second.__init__(self)

Just note that if you do it this way, you'll have to call each manually as I'm pretty sure First's __init__() won't be called.

Answer 6

I would like to add to what @Visionscaper says at the top:

Third --> First --> object --> Second --> object

In this case the interpreter doesnt filter out the object class because its duplicated, rather its because Second appears in a head position and doesnt appear in the tail position in a hierarchy subset. While object only appears in tail positions and is not considered a strong position in C3 algorithm to determine priority.

The linearisation(mro) of a class C, L(C), is the

• the Class C
• plus the merge of
  • linearisation of its parents P1, P2, .. = L(P1, P2, ...) and
  • the list of its parents P1, P2, ..

Linearised Merge is done by selecting the common classes that appears as the head of lists and not the tail since order matters(will become clear below)

The linearisation of Third can be computed as follows:

    L(O)  := [O]  // the linearization(mro) of O(object), because O has no parents

    L(First)  :=  [First] + merge(L(O), [O])
               =  [First] + merge([O], [O])
               =  [First, O]

    // Similarly, 
    L(Second)  := [Second, O]

    L(Third)   := [Third] + merge(L(First), L(Second), [First, Second])
                = [Third] + merge([First, O], [Second, O], [First, Second])
// class First is a good candidate for the first merge step, because it only appears as the head of the first and last lists
// class O is not a good candidate for the next merge step, because it also appears in the tails of list 1 and 2, 
                = [Third, First] + merge([O], [Second, O], [Second])
// class Second is a good candidate for the second merge step, because it appears as the head of the list 2 and 3
                = [Third, First, Second] + merge([O], [O])            
                = [Third, First, Second, O]

Thus for a super() implementation in the following code:

class First(object):
  def __init__(self):
    super(First, self).__init__()
    print "first"

class Second(object):
  def __init__(self):
    super(Second, self).__init__()
    print "second"

class Third(First, Second):
  def __init__(self):
    super(Third, self).__init__()
    print "that's it"

it becomes obvious how this method will be resolved

Third.__init__() ---> First.__init__() ---> Second.__init__() ---> 
Object.__init__() ---> returns ---> Second.__init__() -
prints "second" - returns ---> First.__init__() -
prints "first" - returns ---> Third.__init__() - prints "that's it"