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initialization order in python class hierarchies

In C++, given a class hierarchy, the most derived class's ctor calls its base class ctor which then initialized the base part of the object, before the derived part is instantiated. In Python I want to understand what's going on in a case where I have the requirement, that Derived subclasses a given class Base which takes a callable in its __init__ method which it then later invokes. The callable features some parameters which I pass in Derived class's __init__, which is where I also define the callable function. My idea then was to pass the Derived class itself to its Base class after having defined the __call__ operator
class Derived(Base):
def __init__(self, a, b):
def _process(c, d):
do_something with a and b
self.__class__.__call__ = _process
super(Derived, self).__init__(self)
Is this a pythonic way of dealing with this problem?
What is the exact order of initialization here? Does one needs to call super as a first instruction in the __init__ method or is it ok to do it the way I did?
I am confused whether it is considered good practice to use super with or without arguments in python > 3.6

What is the exact order of initialization here?
Well, very obviously the one you can see in your code - Base.__init__() is only called when you explicitely ask for it (with the super() call). If Base also has parents and everyone in the chain uses super() calls, the parents initializers will be invoked according to the mro.
Basically, Python is a "runtime language" - except for the bytecode compilation phase, everything happens at runtime - so there's very few "black magic" going on (and much of it is actually documented and fully exposed for those who want to look under the hood or do some metaprogramming).
Does one needs to call super as a first instruction in the init method or is it ok to do it the way I did?
You call the parent's method where you see fit for the concrete use case - you just have to beware of not using instance attributes (directly or - less obvious to spot - indirectly via a method call that depends on those attributes) before they are defined.
I am confused whether it is considered good practice to use super with or without arguments in python > 3.6
If you don't need backward compatibily, use super() without params - unless you want to explicitely skip some class in the MRO, but then chances are there's something debatable with your design (but well - sometimes we can't afford to rewrite a whole code base just to avoid one very special corner case, so that's ok too as long as you understand what you're doing and why).
Now with your core question:
class Derived(Base):
def __init__(self, a, b):
def _process(c, d):
do_something with a and b
self.__class__.__call__ = _process
super(Derived, self).__init__(self)
self.__class__.__call__ is a class attribute and is shared by all instances of the class. This means that you either have to make sure you are only ever using one single instance of the class (which doesn't seem to be the goal here) or are ready to have totally random results, since each new instance will overwrite self.__class__.__call__ with it's own version.
If what you want is to have each instance's __call__ method to call it's own version of process(), then there's a much simpler solution - just make _process an instance attribute and call it from __call__ :
class Derived(Base):
def __init__(self, a, b):
def _process(c, d):
do_something with a and b
self._process = _process
super(Derived, self).__init__(self)
def __call__(self, c, d):
return self._process(c, d)
Or even simpler:
class Derived(Base):
def __init__(self, a, b):
super(Derived, self).__init__(self)
self._a = a
self._b = b
def __call__(self, c, d):
do_something_with(self._a, self._b)
EDIT:
Base requires a callable in ins init method.
This would be better if your example snippet was closer to your real use case.
But when I call super().init() the call method of Derived should not have been instantiated yet or has it?
Now that's a good question... Actually, Python methods are not what you think they are. What you define in a class statement's body using the def statement are still plain functions, as you can see by yourself:
class Foo:
... def bar(self): pass
...
Foo.bar
"Methods" are only instanciated when an attribute lookup resolves to a class attribute that happens to be a function:
Foo().bar
main.Foo object at 0x7f3cef4de908>>
Foo().bar
main.Foo object at 0x7f3cef4de940>>
(if you wonder how this happens, it's documented here)
and they actually are just thin wrappers around a function, instance and class (or function and class for classmethods), which delegate the call to the underlying function, injecting the instance (or class) as first argument. In CS terms, a Python method is the partial application of a function to an instance (or class).
Now as I mentionned upper, Python is a runtime language, and both def and class are executable statements. So by the time you define your Derived class, the class statement creating the Base class object has already been executed (else Base wouldn't exist at all), with all the class statement block being executed first (to define the functions and other class attributes).
So "when you call super().__init()__", the __call__ function of Base HAS been instanciated (assuming it's defined in the class statement for Base of course, but that's by far the most common case).

Why do we pass self when calling the constructor of super class? [duplicate]

This question already has answers here:
What does 'super' do in Python? - difference between super().__init__() and explicit superclass __init__()
(11 answers)
Closed 7 years ago.
Why is super() used?
Is there a difference between using Base.__init__ and super().__init__?
class Base(object):
def __init__(self):
print "Base created"
class ChildA(Base):
def __init__(self):
Base.__init__(self)
class ChildB(Base):
def __init__(self):
super(ChildB, self).__init__()
ChildA()
ChildB()

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.

What is the purpose of using super in class initializer?

I was reading some Python code in a private repository on GitHub and found a class resembling the one below:
class Point(object):
'''Models a point in 2D space. '''
def __init__(self, x, y):
super(Point, self).__init__()
self.x = x
self.y = y
# some methods
def __repr__(self):
return 'Point({}, {})'.format(self.x, self.y)
I do understand the importance and advantages of using the keyword super while initialising classes. Personally, I find the first statement in the __init__ to be redundant as all the Python classes inherit from object. So, I want to know what are the advantages(if any) of initializing a Point object using super when inheriting from the base object class in Python ?

There is none in this particular case as object.__init__() is an empty method. However, if you were to inherit from something else, or if you were to use multiple inheritance, call to the super.__init__() would ensure that your classes get properly initialized (assuming of course they depend on initialization from their parent classes). Without that Python's MRO cannot do its magic, for example.

How to improve a mixin structure in Python?

I have a simple mixin structure in Python. The code should be pretty self-explaining:
class Base:
def __init__(self):
pass
class MixinA:
def __init__(self):
self.x = 0
self.y = 1
def a(self):
print('A: x = ' + str(self.x) + ', y = ' + str(self.y))
class MixinB:
def __init__(self):
self.x = 2
self.z = 3
def b(self):
print('B: x = ' + str(self.x) + ', z = ' + str(self.z))
class MyFirstMix(MixinA, MixinB, Base):
def __init__(self):
Base.__init__(self)
MixinB.__init__(self)
MixinA.__init__(self)
class MySecondMix(MixinA, Base):
def __init__(self):
Base.__init__(self)
MixinA.__init__(self)
I'd like to improve this a bit, so this leads to 3 questions/problems:
MixinA and MixinB both have a member x. Is there a way to make sure, each of the class sees only its own x? As far as I know: No, there isn't.
It's slightly cumbersome to call the constructor for each mixin in the mixed class. Is there a way to automatically call all constructors or to do something with the same effect?
Is there a way to dynamically mixin something in-line, without explicitly creating a class? I'm looking for a syntax like: mix = Base() with MixinA
If my proposed structure is completely wrong, I'm also open for other recommendations on how to handle mixins.

For python class inherent, I believe there are some tricks you need to know:
Class in python2 and python3 are quite different.
Python2 support old-style class, but python3 support new-style class only. Simply speaking: in python3, classes always inherent from a base class object, even though you do not explicitly use it. Check Difference-between-Old-New-Class.
Method Resolution Order (MRO). This determines how derived class search inherent members and functions. See MRO
super function. Combined with MRO, you can easily call parent member or function, without explicitly know the name of parent class. See Super
Now comes to you questions:
MixinA and MixinB both have a member x. Is there a way to make sure, each of the class sees only its own x?
I don't quit understand your meaning. When you refer a class member, you must refer it through its instance or class. So instance_of_MixinA.x and instance_of_MixinB.x are separated. If you are talking about class MyFirstMix(MixinA, MixinB, Base), it depends on how __init__ function is called. In your code, you first populate x by MixinB and then reset its value by MixinA.
It's slightly cumbersome to call the constructor for each mixin in the mixed class. Is there a way to automatically call all constructors or to do something with the same effect.
Your designation make it impossible. You have to call all constructors.
Is there a way to dynamically mixin something in-line, without explicitly creating a class?
I am not sure. But I can give you some suggestions: try outside __init__ members when def class (python3, if you used python2 take care of super):
class Base:
def __init__(self):
pass
class MixinA:
x = 0
y = 1
class MixinB:
x = 2
z = 3
def b(self):
print('B: x = ' + str(self.x) + ', z = ' + str(self.z))
class MyFirstMix(MixinA, MixinB, Base):
def __init__(self):
super().__init__()
class MySecondMix(MixinA, Base):
def __init__(self):
super().__init__()
The variables outside __init__ behaves quit different from inside variables: outside variables belongs to class and will be populated for all instances of this class, while inside variables belongs only to instance (referred by self when you define class), and will be populated only if __init__ is called. That's why you cannot use super to call all the constructors---super only call the priority parent's __init__. See variables-outsite-inside-init
This is a good solution to Mixin class. In above code, MyFirstMix inherents both MixinA and MixinB whose members are all class members (outside __init__). So instances of MyFirstMix will inherent all class members of MixinA and MixinB without call __init__. Here MixinA and MixinB own same class member x, but the MRO determines that when instances of MyFirstMix refer x, x from MixinA should be returned.
Hope this will be helpful. Thanks!

When your inheritance schemes start to suffer from these sorts of issues it's time to consider using a technique called composition instead. A good readable introduction to the topic here. The Wikipedia example is a bit less accessible, but also useful if you can handle the other programming languages. This StackExchange question also offers useful discussion.
At its simplest, rather than a class inheriting from SomeParent and mixing in the Mixin class, you instead have the SomeParent instances each create an instance of Mixin and use that to access the mixin class's functionality.

__init__ function layout in python class [duplicate]

This question already has answers here:
What does 'super' do in Python? - difference between super().__init__() and explicit superclass __init__()
(11 answers)
Closed 7 years ago.
Why is super() used?
Is there a difference between using Base.__init__ and super().__init__?
class Base(object):
def __init__(self):
print "Base created"
class ChildA(Base):
def __init__(self):
Base.__init__(self)
class ChildB(Base):
def __init__(self):
super(ChildB, self).__init__()
ChildA()
ChildB()

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.