class A:
def __init__(self):
print("world")
class B(A):
def __init__(self):
print("hello")
B() # output: hello
In all other languages I've worked with the super constructor is invoked implicitly. How does one invoke it in Python? I would expect super(self) but this doesn't work.
In line with the other answers, there are multiple ways to call super class methods (including the constructor), however in Python 3 the process has been simplified:
Python 3
class A(object):
def __init__(self):
print("world")
class B(A):
def __init__(self):
print("hello")
super().__init__()
Python 2
In Python 2, you have to call the slightly more verbose version super(<containing classname>, self), which is equivalent to super()as per the docs.
class A(object):
def __init__(self):
print "world"
class B(A):
def __init__(self):
print "hello"
super(B, self).__init__()
super() returns a parent-like object in new-style classes:
class A(object):
def __init__(self):
print("world")
class B(A):
def __init__(self):
print("hello")
super(B, self).__init__()
B()
With Python 2.x old-style classes it would be this:
class A:
def __init__(self):
print "world"
class B(A):
def __init__(self):
print "hello"
A.__init__(self)
One way is to call A's constructor and pass self as an argument, like so:
class B(A):
def __init__(self):
A.__init__(self)
print "hello"
The advantage of this style is that it's very clear. It call A's initialiser. The downside is that it doesn't handle diamond-shaped inheritance very well, since you may end up calling the shared base class's initialiser twice.
Another way is to use super(), as others have shown. For single-inheritance, it does basically the same thing as letting you call the parent's initialiser.
However, super() is quite a bit more complicated under-the-hood and can sometimes be counter-intuitive in multiple inheritance situations. On the plus side, super() can be used to handle diamond-shaped inheritance. If you want to know the nitty-gritty of what super() does, the best explanation I've found for how super() works is here (though I'm not necessarily endorsing that article's opinions).
Short Answer
super(DerivedClass, self).__init__()
Long Answer
What does super() do?
It takes specified class name, finds its base classes (Python allows multiple inheritance) and looks for the method (__init__ in this case) in each of them from left to right. As soon as it finds method available, it will call it and end the search.
How do I call init of all base classes?
Above works if you have only one base class. But Python does allow multiple inheritance and you might want to make sure all base classes are initialized properly. To do that, you should have each base class call init:
class Base1:
def __init__(self):
super(Base1, self).__init__()
class Base2:
def __init__(self):
super(Base2, self).__init__()
class Derived(Base1, Base2):
def __init__(self):
super(Derived, self).__init__()
What if I forget to call init for super?
The constructor (__new__) gets invoked in a chain (like in C++ and Java). Once the instance is created, only that instance's initialiser (__init__) is called, without any implicit chain to its superclass.
Just to add an example with parameters:
class B(A):
def __init__(self, x, y, z):
A.__init__(self, x, y)
Given a derived class B that requires the variables x, y, z to be defined, and a superclass A that requires x, y to be defined, you can call the static method init of the superclass A with a reference to the current subclass instance (self) and then the list of expected arguments.
I use the following formula that extends previous answers:
class A(object):
def __init__(self):
print "world"
class B(A):
def __init__(self):
print "hello"
super(self.__class__, self).__init__()
B()
This way you don't have to repeat the name of the class in the call to super. It can come handy if you are coding a large number of classes, and want to make your code in the initialiser methods independent of the class name.
Say I have a multiple inheritance scenario:
class A(object):
# code for A here
class B(object):
# code for B here
class C(A, B):
def __init__(self):
# What's the right code to write here to ensure
# A.__init__ and B.__init__ get called?
There's two typical approaches to writing C's __init__:
(old-style) ParentClass.__init__(self)
(newer-style) super(DerivedClass, self).__init__()
However, in either case, if the parent classes (A and B) don't follow the same convention, then the code will not work correctly (some may be missed, or get called multiple times).
So what's the correct way again? It's easy to say "just be consistent, follow one or the other", but if A or B are from a 3rd party library, what then? Is there an approach that can ensure that all parent class constructors get called (and in the correct order, and only once)?
Edit: to see what I mean, if I do:
class A(object):
def __init__(self):
print("Entering A")
super(A, self).__init__()
print("Leaving A")
class B(object):
def __init__(self):
print("Entering B")
super(B, self).__init__()
print("Leaving B")
class C(A, B):
def __init__(self):
print("Entering C")
A.__init__(self)
B.__init__(self)
print("Leaving C")
Then I get:
Entering C
Entering A
Entering B
Leaving B
Leaving A
Entering B
Leaving B
Leaving C
Note that B's init gets called twice. If I do:
class A(object):
def __init__(self):
print("Entering A")
print("Leaving A")
class B(object):
def __init__(self):
print("Entering B")
super(B, self).__init__()
print("Leaving B")
class C(A, B):
def __init__(self):
print("Entering C")
super(C, self).__init__()
print("Leaving C")
Then I get:
Entering C
Entering A
Leaving A
Leaving C
Note that B's init never gets called. So it seems that unless I know/control the init's of the classes I inherit from (A and B) I cannot make a safe choice for the class I'm writing (C).
The answer to your question depends on one very important aspect: Are your base classes designed for multiple inheritance?
There are 3 different scenarios:
The base classes are unrelated, standalone classes.
If your base classes are separate entities that are capable of functioning independently and they don't know each other, they're not designed for multiple inheritance. Example:
class Foo:
def __init__(self):
self.foo = 'foo'
class Bar:
def __init__(self, bar):
self.bar = bar
Important: Notice that neither Foo nor Bar calls super().__init__()! This is why your code didn't work correctly. Because of the way diamond inheritance works in python, classes whose base class is object should not call super().__init__(). As you've noticed, doing so would break multiple inheritance because you end up calling another class's __init__ rather than object.__init__(). (Disclaimer: Avoiding super().__init__() in object-subclasses is my personal recommendation and by no means an agreed-upon consensus in the python community. Some people prefer to use super in every class, arguing that you can always write an adapter if the class doesn't behave as you expect.)
This also means that you should never write a class that inherits from object and doesn't have an __init__ method. Not defining a __init__ method at all has the same effect as calling super().__init__(). If your class inherits directly from object, make sure to add an empty constructor like so:
class Base(object):
def __init__(self):
pass
Anyway, in this situation, you will have to call each parent constructor manually. There are two ways to do this:
Without super
class FooBar(Foo, Bar):
def __init__(self, bar='bar'):
Foo.__init__(self) # explicit calls without super
Bar.__init__(self, bar)
With super
class FooBar(Foo, Bar):
def __init__(self, bar='bar'):
super().__init__() # this calls all constructors up to Foo
super(Foo, self).__init__(bar) # this calls all constructors after Foo up
# to Bar
Each of these two methods has its own advantages and disadvantages. If you use super, your class will support dependency injection. On the other hand, it's easier to make mistakes. For example if you change the order of Foo and Bar (like class FooBar(Bar, Foo)), you'd have to update the super calls to match. Without super you don't have to worry about this, and the code is much more readable.
One of the classes is a mixin.
A mixin is a class that's designed to be used with multiple inheritance. This means we don't have to call both parent constructors manually, because the mixin will automatically call the 2nd constructor for us. Since we only have to call a single constructor this time, we can do so with super to avoid having to hard-code the parent class's name.
Example:
class FooMixin:
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs) # forwards all unused arguments
self.foo = 'foo'
class Bar:
def __init__(self, bar):
self.bar = bar
class FooBar(FooMixin, Bar):
def __init__(self, bar='bar'):
super().__init__(bar) # a single call is enough to invoke
# all parent constructors
# NOTE: `FooMixin.__init__(self, bar)` would also work, but isn't
# recommended because we don't want to hard-code the parent class.
The important details here are:
The mixin calls super().__init__() and passes through any arguments it receives.
The subclass inherits from the mixin first: class FooBar(FooMixin, Bar). If the order of the base classes is wrong, the mixin's constructor will never be called.
All base classes are designed for cooperative inheritance.
Classes designed for cooperative inheritance are a lot like mixins: They pass through all unused arguments to the next class. Like before, we just have to call super().__init__() and all parent constructors will be chain-called.
Example:
class CoopFoo:
def __init__(self, **kwargs):
super().__init__(**kwargs) # forwards all unused arguments
self.foo = 'foo'
class CoopBar:
def __init__(self, bar, **kwargs):
super().__init__(**kwargs) # forwards all unused arguments
self.bar = bar
class CoopFooBar(CoopFoo, CoopBar):
def __init__(self, bar='bar'):
super().__init__(bar=bar) # pass all arguments on as keyword
# arguments to avoid problems with
# positional arguments and the order
# of the parent classes
In this case, the order of the parent classes doesn't matter. We might as well inherit from CoopBar first, and the code would still work the same. But that's only true because all arguments are passed as keyword arguments. Using positional arguments would make it easy to get the order of the arguments wrong, so it's customary for cooperative classes to accept only keyword arguments.
This is also an exception to the rule I mentioned earlier: Both CoopFoo and CoopBar inherit from object, but they still call super().__init__(). If they didn't, there would be no cooperative inheritance.
Bottom line: The correct implementation depends on the classes you're inheriting from.
The constructor is part of a class's public interface. If the class is designed as a mixin or for cooperative inheritance, that must be documented. If the docs don't mention anything of the sort, it's safe to assume that the class isn't designed for cooperative multiple inheritance.
Both ways work fine. The approach using super() leads to greater flexibility for subclasses.
In the direct call approach, C.__init__ can call both A.__init__ and B.__init__.
When using super(), the classes need to be designed for cooperative multiple inheritance where C calls super, which invokes A's code which will also call super which invokes B's code. See http://rhettinger.wordpress.com/2011/05/26/super-considered-super for more detail on what can be done with super.
[Response question as later edited]
So it seems that unless I know/control the init's of the classes I
inherit from (A and B) I cannot make a safe choice for the class I'm
writing (C).
The referenced article shows how to handle this situation by adding a wrapper class around A and B. There is a worked-out example in the section titled "How to Incorporate a Non-cooperative Class".
One might wish that multiple inheritance were easier, letting you effortlessly compose Car and Airplane classes to get a FlyingCar, but the reality is that separately designed components often need adapters or wrappers before fitting together as seamlessly as we would like :-)
One other thought: if you're unhappy with composing functionality using multiple inheritance, you can use composition for complete control over which methods get called on which occasions.
Either approach ("new style" or "old style") will work if you have control over the source code for A and B. Otherwise, use of an adapter class might be necessary.
Source code accessible: Correct use of "new style"
class A(object):
def __init__(self):
print("-> A")
super(A, self).__init__()
print("<- A")
class B(object):
def __init__(self):
print("-> B")
super(B, self).__init__()
print("<- B")
class C(A, B):
def __init__(self):
print("-> C")
# Use super here, instead of explicit calls to __init__
super(C, self).__init__()
print("<- C")
>>> C()
-> C
-> A
-> B
<- B
<- A
<- C
Here, method resolution order (MRO) dictates the following:
C(A, B) dictates A first, then B. MRO is C -> A -> B -> object.
super(A, self).__init__() continues along the MRO chain initiated in C.__init__ to B.__init__.
super(B, self).__init__() continues along the MRO chain initiated in C.__init__ to object.__init__.
You could say that this case is designed for multiple inheritance.
Source code accessible: Correct use of "old style"
class A(object):
def __init__(self):
print("-> A")
print("<- A")
class B(object):
def __init__(self):
print("-> B")
# Don't use super here.
print("<- B")
class C(A, B):
def __init__(self):
print("-> C")
A.__init__(self)
B.__init__(self)
print("<- C")
>>> C()
-> C
-> A
<- A
-> B
<- B
<- C
Here, MRO does not matter, since A.__init__ and B.__init__ are called explicitly. class C(B, A): would work just as well.
Although this case is not "designed" for multiple inheritance in the new style as the previous one was, multiple inheritance is still possible.
Now, what if A and B are from a third party library - i.e., you have no control over the source code for A and B? The short answer: You must design an adapter class that implements the necessary super calls, then use an empty class to define the MRO (see Raymond Hettinger's article on super - especially the section, "How to Incorporate a Non-cooperative Class").
Third-party parents: A does not implement super; B does
class A(object):
def __init__(self):
print("-> A")
print("<- A")
class B(object):
def __init__(self):
print("-> B")
super(B, self).__init__()
print("<- B")
class Adapter(object):
def __init__(self):
print("-> C")
A.__init__(self)
super(Adapter, self).__init__()
print("<- C")
class C(Adapter, B):
pass
>>> C()
-> C
-> A
<- A
-> B
<- B
<- C
Class Adapter implements super so that C can define the MRO, which comes into play when super(Adapter, self).__init__() is executed.
And what if it's the other way around?
Third-party parents: A implements super; B does not
class A(object):
def __init__(self):
print("-> A")
super(A, self).__init__()
print("<- A")
class B(object):
def __init__(self):
print("-> B")
print("<- B")
class Adapter(object):
def __init__(self):
print("-> C")
super(Adapter, self).__init__()
B.__init__(self)
print("<- C")
class C(Adapter, A):
pass
>>> C()
-> C
-> A
<- A
-> B
<- B
<- C
Same pattern here, except the order of execution is switched in Adapter.__init__; super call first, then explicit call. Notice that each case with third-party parents requires a unique adapter class.
So it seems that unless I know/control the init's of the classes I inherit from (A and B) I cannot make a safe choice for the class I'm writing (C).
Although you can handle the cases where you don't control the source code of A and B by using an adapter class, it is true that you must know how the init's of the parent classes implement super (if at all) in order to do so.
As Raymond said in his answer, a direct call to A.__init__ and B.__init__ works fine, and your code would be readable.
However, it does not use the inheritance link between C and those classes. Exploiting that link gives you more consistancy and make eventual refactorings easier and less error-prone. An example of how to do that:
class C(A, B):
def __init__(self):
print("entering c")
for base_class in C.__bases__: # (A, B)
base_class.__init__(self)
print("leaving c")
This article helps to explain cooperative multiple inheritance:
The wonders of cooperative inheritance, or using super in Python 3
It mentions the useful method mro() that shows you the method resolution order. In your second example, where you call super in A, the super call continues on in MRO. The next class in the order is B, this is why B's init is called the first time.
Here's a more technical article from the official Python site:
The Python 2.3 Method Resolution Order
If you are multiply sub-classing classes from third party libraries, then no, there is no blind approach to calling the base class __init__ methods (or any other methods) that actually works regardless of how the base classes are programmed.
super makes it possible to write classes designed to cooperatively implement methods as part of complex multiple inheritance trees which need not be known to the class author. But there's no way to use it to correctly inherit from arbitrary classes that may or may not use super.
Essentially, whether a class is designed to be sub-classed using super or with direct calls to the base class is a property which is part of the class' "public interface", and it should be documented as such. If you're using third-party libraries in the way that the library author expected and the library has reasonable documentation, it would normally tell you what you are required to do to subclass particular things. If not, then you'll have to look at the source code for the classes you're sub-classing and see what their base-class-invocation convention is. If you're combining multiple classes from one or more third-party libraries in a way that the library authors didn't expect, then it may not be possible to consistently invoke super-class methods at all; if class A is part of a hierarchy using super and class B is part of a hierarchy that doesn't use super, then neither option is guaranteed to work. You'll have to figure out a strategy that happens to work for each particular case.
I added a small utility library, supers, which makes this kind of scenario simpler to handle. It works as follows:
class A(object):
def __init__(self):
print("Entering A")
print("Leaving A")
class B(object):
def __init__(self):
print("Entering B")
super(B, self).__init__()
print("Leaving B")
class C(A, B):
def __init__(self):
print("Entering C")
supers(self).__init__()
print("Leaving C")
Output when creating C:
Entering C
Entering A
Leaving A
Entering B
Leaving B
Leaving C
Here is how I have implemented the multiple inheritance in Python 3 using super()
class A:
def __init__(self, a, b, **kwargs):
print("Class A initiallised")
self.a = a
self.b = b
super().__init__(**kwargs)
print("Class A initiallisation done")
def __str__(self):
return f"{self.a} and {self.b}"
def display_a(self):
return f"{self.a} and {self.b}"
class C:
def __init__(self, c, d, **kwargs):
print("Class C initiallised")
self.c = c
self.d = d
super().__init__(**kwargs)
print("class c initiallisation done")
def __str__(self):
return f"{self.c} and {self.d}"
def display_c(self):
return f"{self.c} and {self.d}"
class D(A,C):
def __init__(self, e, **kwargs):
print("Class D initiallised")
super().__init__(**kwargs)
self.e = e
print("Class D initiallisation done")
def __str__(self):
return f"{self.e} is e,{self.b} is b,{self.a} is a,{self.d} is d,{self.c} is c"
if __name__ == "__main__":
d = D(a=12, b=13, c=14, d=15, e=16)
print(d)
d.display_c()
d.display_a()
Here is how I have implemented the super method in Python inheritance and achieved the required solution:
class A:
def __init__(self):
print("from A")
class B:
def __init__(self):
print("from B")
class C(A, B):
def __init__(self):
A.__init__(self)
B.__init__(self)
print("from C")
c = C()
Firstly, suppose you got the MRO chain
From the lowest level subclass init method on, any class which using super() method would jump into corresponding chain position, as any class which not using super() method would jump out corresponding chain position.
It follows the MRO rule and A init is called.
I am new to python and trying to understand the inheritance in python. Python has a feature of multiple inheritance. A single class can inherit more than one class at a same time. When we create an object of child class,the init function of child class is called. I want to call the init function of both the parent class of the child, but i am able to call only only one init function.I read the concept of method resolution order, by which the left most class inherited init function will be called. Please correct my code, so that the init function of both parent classes is called.
class A:
def __init__(self):
print("in A Init")
class B:
def __init__(self):
print("in B Init")
class C(B,A):
def __init__(self):
super().__init__()
print("in C Init")
cObj= C()
All the __init__ functions need to call super().__init__(), like this:
class A:
def __init__(self):
super().__init__()
print("in A Init")
class B:
def __init__(self):
super().__init__()
print("in B Init")
class C(B, A):
def __init__(self):
super().__init__()
print("in C Init")
c_obj= C()
When you invoke this you get the following output:
in A Init
in B Init
in C Init
Per the super() function documentation, it returns a reference to "a parent or sibling" of the class, whichever is next in the method resolution order. At the top of the hierarchy, it returns a reference to the implicit parent class object, which has an empty __init__ method which does nothing.
In order for this to work well, it's best for all the inherited __init__ functions to have the same signature, including the common base class; in this case, the signature is just __init__(self) (no additional arguments), and the common base class is object, which also has __init__(self) with no additional arguments, so that's all good. Another common pattern is for them all to take keyword arguments and pass through **kwargs to the next one.
Trying to invoke a method variable of superclass in the subclass.Is this possible, If possible, is it a good practice or design?
I have written an example code to execute the flow. Below is the code
class bar_for_foo_mixin():
def __init__(self):
self.z =0
def bar(self, q):
x=2
y=8
bar_for_foo_mixin.z= x+y+q
print(bar_for_foo_mixin.z)
def extented_bar(self):
self.bar(10)
class myfoo(bar_for_foo_mixin):
def __init__(self):
super(myfoo, self).__init__()
print("hello",self.z)
class oldFoo():
def __init__(self):
self.var = bar_for_foo_mixin()
self.var.bar(10)
Now how can I make the Z value and make it useful in the subclass? But If Call method extended_bar() in the subclass the above code works fine, But is there any way to store the method variable of superclass and use it in the subclass?
A third class call bar method.
Expected output to print. The Z vaue should store the computations done in the superclass method bar.
hello 20
You can make the __init__ method of the subclass call the base class' __init__ method via the super() function:
class myfoo(bar_for_foo_mixin):
def __init__(self):
super().__init__()
print("hello",self.z)
Moreover, since z is initialized as an instance variable, your bar function should update it as a variable bound to self instead of the class:
def bar(self, q):
x=2
y=8
self.z= x+y+q
print(self.z)
I understand that the concept of super().__init__() is to do with inheritance and I have seen code with parameters within init. However, I came across a code sample that had this:
class Maze(tk.Tk, object):
def __init__(self):
super(Maze, self).__init__()
the parameters are now within the super parenthesis. What is the difference and why may one be used over the other? Thank you
This is the original way super() was intended to work:
super(Maze, self).__init__()
This is also the only way that it did work in Python 2.
So, why the arguments?
You want to call __init__() of the class which is the super class if Maze (probably tk.Tk), bound to self. To do that, you have to pass the arguments Maze and self to super, so that it knows what to do.
What does it actually do?
super(Maze, self).__init__ has to determine type(self) to extract the MRO from it, i.e. the order in which classes are inherited from one another.
Then, in that list, it finds the class which is just above Maze and looks for an __init__ in that class or any class above it. When it finds it, it bounds the __init__ init method to self (i.e. fixes its first argument, so you don't have to pass it).
You could implement that version of super yourself. It would be something like this:
class my_super:
def __init__(self, cls, obj):
self.cls = cls
self.obj = obj
def __getattribute__(self, method_name):
cls = object.__getattribute__(self, 'cls')
obj = object.__getattribute__(self, 'obj')
mro = type(obj).__mro__
mro_above_cls = mro[mro.index(cls)+1:]
for super_cls in mro_above_cls:
if hasattr(super_cls, method_name):
method = getattr(super_cls, method_name)
return functools.partial(method, self)
Note that you don't have to call this from a method at all. You could do this:
class A:
def f(self):
print('A')
class B(A):
def f(self):
print('B')
a = A()
b = B()
super(B, b).f() # prints: A
my_super(B, b).f() # prints: A
What about the version without arguments?
super(Maze, self).__init__() was very explicit, but almost all of Python code always used current class and self as arguments, so Python 3 made it easier by providing a magic super() which knows what you want.