Originally I wanted to ask this question, but then I found it was already thought of before...
Googling around I found this example of extending configparser. The following works with Python 3:
$ python3
Python 3.2.3rc2 (default, Mar 21 2012, 06:59:51)
[GCC 4.6.3] on linux2
>>> from configparser import SafeConfigParser
>>> class AmritaConfigParser(SafeConfigParser):
... def __init__(self):
... super().__init__()
...
>>> cfg = AmritaConfigParser()
But not with Python 2:
>>> class AmritaConfigParser(SafeConfigParser):
... def __init__(self):
... super(SafeConfigParser).init()
...
>>> cfg = AmritaConfigParser()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 3, in __init__
TypeError: must be type, not classob
Then I read a little bit on Python New Class vs. Old Class styles (e.g. here.
And now I am wondering, I can do:
class MyConfigParser(ConfigParser.ConfigParser):
def Write(self, fp):
"""override the module's original write funcition"""
....
def MyWrite(self, fp):
"""Define new function and inherit all others"""
But, shouldn't I call init? Is this in Python 2 the equivalent:
class AmritaConfigParser(ConfigParser.SafeConfigParser):
#def __init__(self):
# super().__init__() # Python3 syntax, or rather, new style class syntax ...
#
# is this the equivalent of the above ?
def __init__(self):
ConfigParser.SafeConfigParser.__init__(self)
super() (without arguments) was introduced in Python 3 (along with __class__):
super() -> same as super(__class__, self)
so that would be the Python 2 equivalent for new-style classes:
super(CurrentClass, self)
for old-style classes you can always use:
class Classname(OldStyleParent):
def __init__(self, *args, **kwargs):
OldStyleParent.__init__(self, *args, **kwargs)
In a single inheritance case (when you subclass one class only), your new class inherits methods of the base class. This includes __init__. So if you don't define it in your class, you will get the one from the base.
Things start being complicated if you introduce multiple inheritance (subclassing more than one class at a time). This is because if more than one base class has __init__, your class will inherit the first one only.
In such cases, you should really use super if you can, I'll explain why. But not always you can. The problem is that all your base classes must also use it (and their base classes as well -- the whole tree).
If that is the case, then this will also work correctly (in Python 3 but you could rework it into Python 2 -- it also has super):
class A:
def __init__(self):
print('A')
super().__init__()
class B:
def __init__(self):
print('B')
super().__init__()
class C(A, B):
pass
C()
#prints:
#A
#B
Notice how both base classes use super even though they don't have their own base classes.
What super does is: it calls the method from the next class in MRO (method resolution order). The MRO for C is: (C, A, B, object). You can print C.__mro__ to see it.
So, C inherits __init__ from A and super in A.__init__ calls B.__init__ (B follows A in MRO).
So by doing nothing in C, you end up calling both, which is what you want.
Now if you were not using super, you would end up inheriting A.__init__ (as before) but this time there's nothing that would call B.__init__ for you.
class A:
def __init__(self):
print('A')
class B:
def __init__(self):
print('B')
class C(A, B):
pass
C()
#prints:
#A
To fix that you have to define C.__init__:
class C(A, B):
def __init__(self):
A.__init__(self)
B.__init__(self)
The problem with that is that in more complicated MI trees, __init__ methods of some classes may end up being called more than once whereas super/MRO guarantee that they're called just once.
In short, they are equivalent.
Let's have a history view:
(1) at first, the function looks like this.
class MySubClass(MySuperClass):
def __init__(self):
MySuperClass.__init__(self)
(2) to make code more abstract (and more portable). A common method to get Super-Class is invented like:
super(<class>, <instance>)
And init function can be:
class MySubClassBetter(MySuperClass):
def __init__(self):
super(MySubClassBetter, self).__init__()
However requiring an explicit passing of both the class and instance break the DRY (Don't Repeat Yourself) rule a bit.
(3) in V3. It is more smart,
super()
is enough in most case. You can refer to http://www.python.org/dev/peps/pep-3135/
Just to have a simple and complete example for Python 3, which most people seem to be using now.
class MySuper(object):
def __init__(self,a):
self.a = a
class MySub(MySuper):
def __init__(self,a,b):
self.b = b
super().__init__(a)
my_sub = MySub(42,'chickenman')
print(my_sub.a)
print(my_sub.b)
gives
42
chickenman
Another python3 implementation that involves the use of Abstract classes with super(). You should remember that
super().__init__(name, 10)
has the same effect as
Person.__init__(self, name, 10)
Remember there's a hidden 'self' in super(), So the same object passes on to the superclass init method and the attributes are added to the object that called it.
Hence super()gets translated to Person and then if you include the hidden self, you get the above code frag.
from abc import ABCMeta, abstractmethod
class Person(metaclass=ABCMeta):
name = ""
age = 0
def __init__(self, personName, personAge):
self.name = personName
self.age = personAge
#abstractmethod
def showName(self):
pass
#abstractmethod
def showAge(self):
pass
class Man(Person):
def __init__(self, name, height):
self.height = height
# Person.__init__(self, name, 10)
super().__init__(name, 10) # same as Person.__init__(self, name, 10)
# basically used to call the superclass init . This is used incase you want to call subclass init
# and then also call superclass's init.
# Since there's a hidden self in the super's parameters, when it's is called,
# the superclasses attributes are a part of the same object that was sent out in the super() method
def showIdentity(self):
return self.name, self.age, self.height
def showName(self):
pass
def showAge(self):
pass
a = Man("piyush", "179")
print(a.showIdentity())
Related
I am trying to write a plugin environment where I need to do multiple inheritances on an unknown number of classes. Therefore, I have opted to use the type class creation:
class A(object):
def __init__(self,s):
self.a="a"
def testA(self,x):
print(x)
class B(object):
def __init__(self,s):
self.b="b"
def testA(self,x):
print(x)
C = type('C', (A,B), {})
x= C("test")
print x.b
When I run the above code, I get the error:
AttributeError: 'C' object has no attribute 'b'
This is because only the init for class A is being run when the instance for class C is initialized. My question is how can I get the class C to have both the init for class A as well as the init for class B to run when an instance of class C is initialized. I do realize that if I had class C like the following it would work:
class C(A,B):
def __init__(self,s):
A.__init__(self,s)
B.__init__(self,s)
However, given that I need to have a dynamic list of classes inherited this will not work.
It seems you're using python 2 so I'm using this old python 2 super() syntax where you have to specify the class and the instance, although it would work in python 3 as well. In python 3 you could also use the shorter super() form without parameters.
For multiple inheritance to work is important that the grandparent class __init__ signature matches the signature of all siblings for that method. To do that, define a common parent class (MyParent in this example) whose __init__ has the same parameter list as all the childs. It will take care of calling the object's __init__ that doesn't take any parameter, for us.
from __future__ import print_function
class MyParent(object):
def __init__(self, s):
super(MyParent, self).__init__()
class A(MyParent):
def __init__(self, s):
self.a = "a"
super(A, self).__init__(s)
def testA(self, x):
print(x)
class B(MyParent):
def __init__(self, s):
self.b = "b"
super(B, self).__init__(s)
def testA(self,x):
print(x)
C = type('C', (A, B), {})
x = C("test")
print(x.b)
You can define as many children to MyParent as you want, and then all __init__ methods will be called, provided you used super() correctly.
I'm writing a code where there is a super classes, called Soft_Constr, made in the following way:
def __init__(self, prop, name, static_init, static_lit, pred, kind):
init_method ...
def evaluate_clause(self):
code here
And there are some subclasses that may invoke the method 'evaluate_clause' defined in the superclass. Is there a way to catch which subclasses invoked the 'evaluate_clause' in Soft_Constr class?
def evaluate_clause(self):
subclasses = method_to_get_subclasses(...)
This is an example for Python 2:
class SuperClass(object):
def callername(self):
print self.__class__.__name__
class ChildClass(SuperClass):
def test(self):
self.callername()
o = ChildClass()
o.test()
I used that a lot in the past to identify test classes for logging purposes. Very useful.
Not much different for Python 3:
class SuperClass():
def callername(self):
print(self.__class__.__name__)
class ChildClass(SuperClass):
def test(self):
self.callername()
o = ChildClass()
o.test()
According to the docs, super(cls, obj) returns
a proxy object that delegates method calls to a parent or sibling
class of type cls
I understand why super() offers this functionality, but I need something slightly different: I need to create a proxy object that delegates methods calls (and attribute lookups) to class cls itself; and as in super, if cls doesn't implement the method/attribute, my proxy should continue looking in the MRO order (of the new not the original class). Is there any function I can write that achieves that?
Example:
class X:
def act():
#...
class Y:
def act():
#...
class A(X, Y):
def act():
#...
class B(X, Y):
def act():
#...
class C(A, B):
def act():
#...
c = C()
b = some_magic_function(B, c)
# `b` needs to delegate calls to `act` to B, and look up attribute `s` in B
# I will pass `b` somewhere else, and have no control over it
Of course, I could do b = super(A, c), but that relies on knowing the exact class hierarchy and the fact that B follows A in the MRO. It would silently break if any of these two assumptions change in the future. (Note that super doesn't make any such assumptions!)
If I just needed to call b.act(), I could use B.act(c). But I am passing b to someone else, and have no idea what they'll do with it. I need to make sure it doesn't betray me and start acting like an instance of class C at some point.
A separate question, the documentation for super() (in Python 3.2) only talks about its method delegation, and does not clarify that attribute lookups for the proxy are also performed the same way. Is it an accidental omission?
EDIT
The updated Delegate approach works in the following example as well:
class A:
def f(self):
print('A.f')
def h(self):
print('A.h')
self.f()
class B(A):
def g(self):
self.f()
print('B.g')
def f(self):
print('B.f')
def t(self):
super().h()
a_true = A()
# instance of A ends up executing A.f
a_true.h()
b = B()
a_proxy = Delegate(A, b)
# *unlike* super(), the updated `Delegate` implementation would call A.f, not B.f
a_proxy.h()
Note that the updated class Delegate is closer to what I want than super() for two reasons:
super() only does it proxying for the first call; subsequent calls will happen as normal, since by then the object is used, not its proxy.
super() does not allow attribute access.
Thus, my question as asked has a (nearly) perfect answer in Python.
It turns out that, at a higher level, I was trying to do something I shouldn't (see my comments here).
This class should cover the most common cases:
class Delegate:
def __init__(self, cls, obj):
self._delegate_cls = cls
self._delegate_obj = obj
def __getattr__(self, name):
x = getattr(self._delegate_cls, name)
if hasattr(x, "__get__"):
return x.__get__(self._delegate_obj)
return x
Use it like this:
b = Delegate(B, c)
(with the names from your example code.)
Restrictions:
You cannot retrieve some special attributes like __class__ etc. from the class you pass in the constructor via this proxy. (This restistions also applies to super.)
This might behave weired if the attribute you want to retrieve is some weired kind of descriptor.
Edit: If you want the code in the update to your question to work as desired, you can use the foloowing code:
class Delegate:
def __init__(self, cls):
self._delegate_cls = cls
def __getattr__(self, name):
x = getattr(self._delegate_cls, name)
if hasattr(x, "__get__"):
return x.__get__(self)
return x
This passes the proxy object as self parameter to any called method, and it doesn't need the original object at all, hence I deleted it from the constructor.
If you also want instance attributes to be accessible you can use this version:
class Delegate:
def __init__(self, cls, obj):
self._delegate_cls = cls
self._delegate_obj = obj
def __getattr__(self, name):
if name in vars(self._delegate_obj):
return getattr(self._delegate_obj, name)
x = getattr(self._delegate_cls, name)
if hasattr(x, "__get__"):
return x.__get__(self)
return x
A separate question, the documentation for super() (in Python 3.2)
only talks about its method delegation, and does not clarify that
attribute lookups for the proxy are also performed the same way. Is it
an accidental omission?
No, this is not accidental. super() does nothing for attribute lookups. The reason is that attributes on an instance are not associated with a particular class, they're just there. Consider the following:
class A:
def __init__(self):
self.foo = 'foo set from A'
class B(A):
def __init__(self):
super().__init__()
self.bar = 'bar set from B'
class C(B):
def method(self):
self.baz = 'baz set from C'
class D(C):
def __init__(self):
super().__init__()
self.foo = 'foo set from D'
self.baz = 'baz set from D'
instance = D()
instance.method()
instance.bar = 'not set from a class at all'
Which class "owns" foo, bar, and baz?
If I wanted to view instance as an instance of C, should it have a baz attribute before method is called? How about afterwards?
If I view instance as an instance of A, what value should foo have? Should bar be invisible because was only added in B, or visible because it was set to a value outside the class?
All of these questions are nonsense in Python. There's no possible way to design a system with the semantics of Python that could give sensible answers to them. __init__ isn't even special in terms of adding attributes to instances of the class; it's just a perfectly ordinary method that happens to be called as part of the instance creation protocol. Any method (or indeed code from another class altogether, or not from any class at all) can create attributes on any instance it has a reference to.
In fact, all of the attributes of instance are stored in the same place:
>>> instance.__dict__
{'baz': 'baz set from C', 'foo': 'foo set from D', 'bar': 'not set from a class at all'}
There's no way to tell which of them were originally set by which class, or were last set by which class, or whatever measure of ownership you want. There's certainly no way to get at "the A.foo being shadowed by D.foo", as you would expect from C++; they're the same attribute, and any writes to to it by one class (or from elsewhere) will clobber a value left in it by the other class.
The consequence of this is that super() does not perform attribute lookups the same way it does method lookups; it can't, and neither can any code you write.
In fact, from running some experiments, neither super nor Sven's Delegate actually support direct attribute retrieval at all!
class A:
def __init__(self):
self.spoon = 1
self.fork = 2
def foo(self):
print('A.foo')
class B(A):
def foo(self):
print('B.foo')
b = B()
d = Delegate(A, b)
s = super(B, b)
Then both work as expected for methods:
>>> d.foo()
A.foo
>>> s.foo()
A.foo
But:
>>> d.fork
Traceback (most recent call last):
File "<pyshell#43>", line 1, in <module>
d.fork
File "/tmp/foo.py", line 6, in __getattr__
x = getattr(self._delegate_cls, name)
AttributeError: type object 'A' has no attribute 'fork'
>>> s.spoon
Traceback (most recent call last):
File "<pyshell#45>", line 1, in <module>
s.spoon
AttributeError: 'super' object has no attribute 'spoon'
So they both only really work for calling some methods on, not for passing to arbitrary third party code to pretend to be an instance of the class you want to delegate to.
They don't behave the same way in the presence of multiple inheritance unfortunately. Given:
class Delegate:
def __init__(self, cls, obj):
self._delegate_cls = cls
self._delegate_obj = obj
def __getattr__(self, name):
x = getattr(self._delegate_cls, name)
if hasattr(x, "__get__"):
return x.__get__(self._delegate_obj)
return x
class A:
def foo(self):
print('A.foo')
class B:
pass
class C(B, A):
def foo(self):
print('C.foo')
c = C()
d = Delegate(B, c)
s = super(C, c)
Then:
>>> d.foo()
Traceback (most recent call last):
File "<pyshell#50>", line 1, in <module>
d.foo()
File "/tmp/foo.py", line 6, in __getattr__
x = getattr(self._delegate_cls, name)
AttributeError: type object 'B' has no attribute 'foo'
>>> s.foo()
A.foo
Because Delegate ignores the full MRO of whatever class _delegate_obj is an instance of, only using the MRO of _delegate_cls. Whereas super does what you asked in the question, but the behaviour seems quite strange: it's not wrapping an instance of C to pretend it's an instance of B, because direct instances of B don't have foo defined.
Here's my attempt:
class MROSkipper:
def __init__(self, cls, obj):
self.__cls = cls
self.__obj = obj
def __getattr__(self, name):
mro = self.__obj.__class__.__mro__
i = mro.index(self.__cls)
if i == 0:
# It's at the front anyway, just behave as getattr
return getattr(self.__obj, name)
else:
# Check __dict__ not getattr, otherwise we'd find methods
# on classes we're trying to skip
try:
return self.__obj.__dict__[name]
except KeyError:
return getattr(super(mro[i - 1], self.__obj), name)
I rely on the __mro__ attribute of classes to properly figure out where to start from, then I just use super. You could walk the MRO chain from that point yourself checking class __dict__s for methods instead if the weirdness of going back one step to use super is too much.
I've made no attempt to handle unusual attributes; those implemented with descriptors (including properties), or those magic methods looked up behind the scenes by Python, which often start at the class rather than the instance directly. But this behaves as you asked moderately well (with the caveat expounded on ad nauseum in the first part of my post; looking up attributes this way will not give you any different results than looking them up directly in the instance).
Consider the following code:
class Base(object):
#classmethod
def do(cls, a):
print cls, a
class Derived(Base):
#classmethod
def do(cls, a):
print 'In derived!'
# Base.do(cls, a) -- can't pass `cls`
Base.do(a)
if __name__ == '__main__':
d = Derived()
d.do('hello')
> $ python play.py
> In derived!
> <class '__main__.Base'> msg
From Derived.do, how do I call Base.do?
I would normally use super or even the base class name directly if this is a normal object method, but apparently I can't find a way to call the classmethod in the base class.
In the above example, Base.do(a) prints Base class instead of Derived class.
If you're using a new-style class (i.e. derives from object in Python 2, or always in Python 3), you can do it with super() like this:
super(Derived, cls).do(a)
This is how you would invoke the code in the base class's version of the method (i.e. print cls, a), from the derived class, with cls being set to the derived class.
this has been a while, but I think I may have found an answer. When you decorate a method to become a classmethod the original unbound method is stored in a property named 'im_func':
class Base(object):
#classmethod
def do(cls, a):
print cls, a
class Derived(Base):
#classmethod
def do(cls, a):
print 'In derived!'
# Base.do(cls, a) -- can't pass `cls`
Base.do.im_func(cls, a)
if __name__ == '__main__':
d = Derived()
d.do('hello')
Building on the answer from #David Z using:
super(Derived, cls).do(a)
Which can be further simplified to:
super(cls, cls).do(a)
I often use classmethods to provide alternative ways to construct my objects. In the example below I use the super functions as above for the class method load that alters the way that the objects are created:
class Base():
def __init__(self,a):
self.a = a
#classmethod
def load(cls,a):
return cls(a=a)
class SubBase(Base):
#classmethod
def load(cls,b):
a = b-1
return super(cls,cls).load(a=a)
base = Base.load(a=1)
print(base)
print(base.a)
sub = SubBase.load(b=3)
print(sub)
print(sub.a)
Output:
<__main__.Base object at 0x128E48B0>
1
<__main__.SubBase object at 0x128E4710>
2
This works for me:
Base.do('hi')
When creating a simple object hierarchy in Python, I'd like to be able to invoke methods of the parent class from a derived class. In Perl and Java, there is a keyword for this (super). In Perl, I might do this:
package Foo;
sub frotz {
return "Bamf";
}
package Bar;
#ISA = qw(Foo);
sub frotz {
my $str = SUPER::frotz();
return uc($str);
}
In Python, it appears that I have to name the parent class explicitly from the child.
In the example above, I'd have to do something like Foo::frotz().
This doesn't seem right since this behavior makes it hard to make deep hierarchies. If children need to know what class defined an inherited method, then all sorts of information pain is created.
Is this an actual limitation in python, a gap in my understanding or both?
Use the super() function:
class Foo(Bar):
def baz(self, **kwargs):
return super().baz(**kwargs)
For Python < 3, you must explicitly opt in to using new-style classes and use:
class Foo(Bar):
def baz(self, arg):
return super(Foo, self).baz(arg)
Python also has super as well:
super(type[, object-or-type])
Return a proxy object that delegates method calls to a parent or sibling class of type.
This is useful for accessing inherited methods that have been overridden in a class.
The search order is same as that used by getattr() except that the type itself is skipped.
Example:
class A(object): # deriving from 'object' declares A as a 'new-style-class'
def foo(self):
print "foo"
class B(A):
def foo(self):
super(B, self).foo() # calls 'A.foo()'
myB = B()
myB.foo()
ImmediateParentClass.frotz(self)
will be just fine, whether the immediate parent class defined frotz itself or inherited it. super is only needed for proper support of multiple inheritance (and then it only works if every class uses it properly). In general, AnyClass.whatever is going to look up whatever in AnyClass's ancestors if AnyClass doesn't define/override it, and this holds true for "child class calling parent's method" as for any other occurrence!
Python 3 has a different and simpler syntax for calling parent method.
If Foo class inherits from Bar, then from Bar.__init__ can be invoked from Foo via super().__init__():
class Foo(Bar):
def __init__(self, *args, **kwargs):
# invoke Bar.__init__
super().__init__(*args, **kwargs)
Many answers have explained how to call a method from the parent which has been overridden in the child.
However
"how do you call a parent class's method from child class?"
could also just mean:
"how do you call inherited methods?"
You can call methods inherited from a parent class just as if they were methods of the child class, as long as they haven't been overwritten.
e.g. in python 3:
class A():
def bar(self, string):
print("Hi, I'm bar, inherited from A"+string)
class B(A):
def baz(self):
self.bar(" - called by baz in B")
B().baz() # prints out "Hi, I'm bar, inherited from A - called by baz in B"
yes, this may be fairly obvious, but I feel that without pointing this out people may leave this thread with the impression you have to jump through ridiculous hoops just to access inherited methods in python. Especially as this question rates highly in searches for "how to access a parent class's method in Python", and the OP is written from the perspective of someone new to python.
I found:
https://docs.python.org/3/tutorial/classes.html#inheritance
to be useful in understanding how you access inherited methods.
Here is an example of using super():
#New-style classes inherit from object, or from another new-style class
class Dog(object):
name = ''
moves = []
def __init__(self, name):
self.name = name
def moves_setup(self):
self.moves.append('walk')
self.moves.append('run')
def get_moves(self):
return self.moves
class Superdog(Dog):
#Let's try to append new fly ability to our Superdog
def moves_setup(self):
#Set default moves by calling method of parent class
super(Superdog, self).moves_setup()
self.moves.append('fly')
dog = Superdog('Freddy')
print dog.name # Freddy
dog.moves_setup()
print dog.get_moves() # ['walk', 'run', 'fly'].
#As you can see our Superdog has all moves defined in the base Dog class
There's a super() in Python too. It's a bit wonky, because of Python's old- and new-style classes, but is quite commonly used e.g. in constructors:
class Foo(Bar):
def __init__(self):
super(Foo, self).__init__()
self.baz = 5
I would recommend using CLASS.__bases__
something like this
class A:
def __init__(self):
print "I am Class %s"%self.__class__.__name__
for parentClass in self.__class__.__bases__:
print " I am inherited from:",parentClass.__name__
#parentClass.foo(self) <- call parents function with self as first param
class B(A):pass
class C(B):pass
a,b,c = A(),B(),C()
If you don't know how many arguments you might get, and want to pass them all through to the child as well:
class Foo(bar)
def baz(self, arg, *args, **kwargs):
# ... Do your thing
return super(Foo, self).baz(arg, *args, **kwargs)
(From: Python - Cleanest way to override __init__ where an optional kwarg must be used after the super() call?)
There is a super() in python also.
Example for how a super class method is called from a sub class method
class Dog(object):
name = ''
moves = []
def __init__(self, name):
self.name = name
def moves_setup(self,x):
self.moves.append('walk')
self.moves.append('run')
self.moves.append(x)
def get_moves(self):
return self.moves
class Superdog(Dog):
#Let's try to append new fly ability to our Superdog
def moves_setup(self):
#Set default moves by calling method of parent class
super().moves_setup("hello world")
self.moves.append('fly')
dog = Superdog('Freddy')
print (dog.name)
dog.moves_setup()
print (dog.get_moves())
This example is similar to the one explained above.However there is one difference that super doesn't have any arguments passed to it.This above code is executable in python 3.4 version.
In this example cafec_param is a base class (parent class) and abc is a child class. abc calls the AWC method in the base class.
class cafec_param:
def __init__(self,precip,pe,awc,nmonths):
self.precip = precip
self.pe = pe
self.awc = awc
self.nmonths = nmonths
def AWC(self):
if self.awc<254:
Ss = self.awc
Su = 0
self.Ss=Ss
else:
Ss = 254; Su = self.awc-254
self.Ss=Ss + Su
AWC = Ss + Su
return self.Ss
def test(self):
return self.Ss
#return self.Ss*4
class abc(cafec_param):
def rr(self):
return self.AWC()
ee=cafec_param('re',34,56,2)
dd=abc('re',34,56,2)
print(dd.rr())
print(ee.AWC())
print(ee.test())
Output
56
56
56
In Python 2, I didn't have a lot luck with super(). I used the answer from
jimifiki on this SO thread how to refer to a parent method in python?.
Then, I added my own little twist to it, which I think is an improvement in usability (Especially if you have long class names).
Define the base class in one module:
# myA.py
class A():
def foo( self ):
print "foo"
Then import the class into another modules as parent:
# myB.py
from myA import A as parent
class B( parent ):
def foo( self ):
parent.foo( self ) # calls 'A.foo()'
class department:
campus_name="attock"
def printer(self):
print(self.campus_name)
class CS_dept(department):
def overr_CS(self):
department.printer(self)
print("i am child class1")
c=CS_dept()
c.overr_CS()
If you want to call the method of any class, you can simply call Class.method on any instance of the class. If your inheritance is relatively clean, this will work on instances of a child class too:
class Foo:
def __init__(self, var):
self.var = var
def baz(self):
return self.var
class Bar(Foo):
pass
bar = Bar(1)
assert Foo.baz(bar) == 1
class a(object):
def my_hello(self):
print "hello ravi"
class b(a):
def my_hello(self):
super(b,self).my_hello()
print "hi"
obj = b()
obj.my_hello()
This is a more abstract method:
super(self.__class__,self).baz(arg)