I have the following two superclasses:
class Parent1(object):
def on_start(self):
print('do something')
class Parent2(object):
def on_start(self):
print('do something else')
I would like to have a child class that inherits from both be able to call super for both parents.
class Child(Parent1, Parent2):
def on_start(self):
# super call on both parents
What is the Pythonic way to do this? Thanks.
Exec summary:
Super only executes one method based on the class hierarchy's __mro__
. If you want to execute more than one method by the same name, your parent classes need to written to cooperatively do that (by calling super
implicitly or explicitly) or you need to loop over __bases__
or the __mro__
values of the child classes.
The job of super
is to delegate part or all of a method call to some existing method in the classes ancestor tree. The delegation may go well outside of classes that you control. The method name delegated needs to exist in the group of base classes.
The method presented below using __bases__
with try/except
is closest to a complete answer to your question of how to call each parent's method of the same name.
super
is useful in the situation where you want to call one of your parent's methods, but you don't know which parent:
class Parent1(object):
pass
class Parent2(object):
# if Parent 2 had on_start - it would be called instead
# because Parent 2 is left of Parent 3 in definition of Child class
pass
class Parent3(object):
def on_start(self):
print('the ONLY class that has on_start')
class Child(Parent1, Parent2, Parent3):
def on_start(self):
super(Child, self).on_start()
In this case, Child
has three immediate parents. Only one, Parent3, has an on_start
method. Calling super
resolves that only Parent3
has on_start
and that is the method that is called.
If Child
inherits from more than one class that has an on_start
method, the order is resolved left to right (as listed in the class definition) and bottom to top (as logical inheritance). Only one of the methods is called and the other methods of the same name in the hierarchy of classes have been superseded.
So, more commonly:
class GreatGrandParent(object):
pass
class GrandParent(GreatGrandParent):
def on_start(self):
print('the ONLY class that has on_start')
class Parent(GrandParent):
# if Parent had on_start, it would be used instead
pass
class Child(Parent):
def on_start(self):
super(Child, self).on_start()
If you want to call multiple parents methods by method name, you can use __bases__
instead of super in this case and iterate over the base classes of Child
without knowing the classes by name:
class Parent1(object):
def on_start(self):
print('do something')
class Parent2(object):
def on_start(self):
print('do something else')
class Child(Parent1, Parent2):
def on_start(self):
for base in Child.__bases__:
base.on_start(self)
>>> Child().on_start()
do something
do something else
If there is a possibility one of the base classes does not have on_start
you can use try/except:
class Parent1(object):
def on_start(self):
print('do something')
class Parent2(object):
def on_start(self):
print('do something else')
class Parent3(object):
pass
class Child(Parent1, Parent2, Parent3):
def on_start(self):
for base in Child.__bases__:
try:
base.on_start(self)
except AttributeError:
# handle that one of those does not have that method
print('"{}" does not have an "on_start"'.format(base.__name__))
>>> Child().on_start()
do something
do something else
"Parent3" does not have an "on_start"
Using __bases__
will act similar to super
but for each class hierarchy defined in the Child
definition. ie, it will go though each forbearer class until on_start
is satisfied once for each parent of the class:
class GGP1(object):
def on_start(self):
print('GGP1 do something')
class GP1(GGP1):
def on_start(self):
print('GP1 do something else')
class Parent1(GP1):
pass
class GGP2(object):
def on_start(self):
print('GGP2 do something')
class GP2(GGP2):
pass
class Parent2(GP2):
pass
class Child(Parent1, Parent2):
def on_start(self):
for base in Child.__bases__:
try:
base.on_start(self)
except AttributeError:
# handle that one of those does not have that method
print('"{}" does not have an "on_start"'.format(base.__name__))
>>> Child().on_start()
GP1 do something else
GGP2 do something
# Note that 'GGP1 do something' is NOT printed since on_start was satisfied by
# a descendant class L to R, bottom to top
Now imagine a more complex inheritance structure:
If you want each and every forbearer's on_start
method, you could use __mro__
and filter out the classes that do not have on_start
as part of their __dict__
for that class. Otherwise, you will potentially get a forbearer's on_start
method. In other words, hassattr(c, 'on_start')
is True
for every class that Child
is a descendant from (except object
in this case) since Ghengis
has an on_start
attribute and all classes are descendant classes from Ghengis.
** Warning -- Demo Only **
class Ghengis(object):
def on_start(self):
print('Khan -- father to all')
class GGP1(Ghengis):
def on_start(self):
print('GGP1 do something')
class GP1(GGP1):
pass
class Parent1(GP1):
pass
class GGP2(Ghengis):
pass
class GP2(GGP2):
pass
class Parent2(GP2):
def on_start(self):
print('Parent2 do something')
class Child(Parent1, Parent2):
def on_start(self):
for c in Child.__mro__[1:]:
if 'on_start' in c.__dict__.keys():
c.on_start(self)
>>> Child().on_start()
GGP1 do something
Parent2 do something
Khan -- father to all
But this also has a problem -- if Child
is further subclassed, then the child of Child will also loop over the same __mro__
chain.
As stated by Raymond Hettinger:
super() is in the business of delegating method calls to some class in the instance’s ancestor tree. For reorderable method calls to work, the classes need to be designed cooperatively. This presents three easily solved practical issues:
1) the method being called by super() needs to exist
2) the caller and callee need to have a matching argument signature and
3) every occurrence of the method needs to use super()
The solution is to write cooperative classes that uniformly use super
through the ancestor list or creative use of the adapter pattern to adapt classes you cannot control. These methods are discussed more completely in the article Python’s super() considered super! by Raymond Hettinger.
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