I have a case, where I have an instance of a class in python which holds instances of other classes. For my use case, I would like a way to use the methods of the "inner" classes from the outer class without referencing the attribute holding the inner class.
I have made a simplistic example here:
class A:
def __init__(self):
pass
def say_hi(self):
print("Hi")
def say_goodbye(self):
print("Goodbye")
class C:
def __init__(self, other_instance):
self.other_instance= other_instance
def say_good_night(self):
print("Good night")
my_a = A()
my_c = C(other_instance=my_a)
# How to make this possible:
my_c.say_hi()
# Instead of
my_c.other_instance.say_hi()
Class inheritance is not possible, as the object passed to C may be an instance of a range of classes. Is this possible in Python?
I think this is the simplest solution although it is possible with metaprogramming.
class A:
def __init__(self):
pass
def say_hi(self):
print("Hi")
def say_goodbye(self):
print("Goodbye")
class C:
def __init__(self, other_class):
self.other_class = other_class
C._add_methods(other_class)
def say_good_night(self):
print("Good night")
#classmethod
def _add_methods(cls, obj):
type_ = type(obj)
for k, v in type_.__dict__.items():
if not k.startswith('__'):
setattr(cls, k, v)
my_a = A()
my_c = C(other_class=my_a)
my_c.say_hi()
output :
Hi
First we get the type of passed instance, then we iterate through it's attribute (because methods are attributes of the class not the instance).
If self.other_class is only needed for this purpose, you can omit it as well.
So, because you have done:
my_a = A() and my_c = C(other_class=my_a).
my_c.other_class is the same as my_a asthey point to the same location in memory.
Therefore, as you can do my_a.say_hi() you could also do my_c.other_class.say_hi().
Also, just a note, as you are calling A() before you store it into other_classes, I would probably rename the variable other_classes to class_instances.
Personally, I think that would make more sense, as each of those classes would have already been instantiated.
Related
I'd like to be able to extend a class without inheriting one of the class variables.
Given this scenario:
class A:
aliases=['a','ay']
class B(A):
pass
print(B.aliases)
I would rather get an error that B has not defined the aliases variable rather than have B accidentally called ay.
One could imagine a solution where aliases becomes a member of the instantiated object (self.aliases) and is set in __init__ but I really want to be able to access the aliases using the cls object rather than an instance of the class.
Any suggestions?
Python does not have REALY private attributes. But you can define it with a double underscore (__):
class A:
__aliases=['a','ay']
class B(A):
pass
print(B.__aliases) # yields AttributeError
But you still will be able to access it with:
print(B._A__aliases)
This is kindof a ganky work around but here you go:
class K:
def __init__(self):
self.mems = dir(self)
def defaultMembers():
k = K()
return(k.mems)
class A:
aliases=['a','ay']
class B(A):
def __init__(self):
for k in set(dir(self))-set(defaultMembers()):
print("removing "+k)
setattr(self, k, None)
a = A()
b = B()
print(b.aliases)
#None
print(a.aliases)
#['a','ay']
I guess all you really need is the setattr(self, "aliases", None) still this results in a None and not a non-variable. Unfortunately calsses don't support deletion because I tried to use del first.
I have an application with quite a number of classes. The classes have a number of functions as per def's that are common and obviously some that are not.
Is there a way to define the functions that have common function in one place and be available to a number of classes, or do I have to have at least the def's in every class?
Start by defining the func, which is defined outside.
Then to refer that function in different classes, use the same func inside the classes
def func():
print('func')
class B:
def funcB(self):
print('funcB')
def func(self):
func()
class C:
def funcC(self):
print('funcC')
def func(self):
func()
These can be called now as follows.
b = B()
b.func()
#funcA
b.funcB()
#funcB
c = C()
c.func()
#funcA
c.funcC()
#funcC
As pointed out by Amadan in the comments, class inheritance is a good and consistent way of sharing class objects. Below is an example:
class animals:
def __init__(self):
pass
def has_legs(self, type):
if type == "snake":
print(False)
else:
print(True)
class dog(animals):
def __init__(self):
# This is where the magic happens
animals.__init__(self)
pass
def dog_has_legs(self):
self.has_legs("dog")
bofur = dog()
bofur.dog_has_legs()
bofur.has_legs("snake")
Result:
>>> bofur.dog_has_legs()
True
>>> bofur.has_legs("snake")
False
As you can see, the class dog inherits from animals, and so it can call functions and other objects from the animals class as if they belonged to the dog class.
I have a class factory method that is used to instantiate an object. With multiple objects are created through this method, I want to be able to compare the classes of the objects. When using isinstance, the comparison is False, as can be seen in the simple example below. Also running id(a.__class__) and id(b.__class__), gives different ids.
Is there a simple way of achieving this? I know that this does not exactly conform to duck-typing, however this is the easiest solution for the program I am writing.
def factory():
class MyClass(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
return MyClass()
a = factory()
b = factory()
print(a.compare(b))
The reason is that MyClass is created dynamically every time you run factory. If you print(id(MyClass)) inside factory you get different results:
>>> a = factory()
140465711359728
>>> b = factory()
140465712488632
This is because they are actually different classes, dynamically created and locally scoped at the time of the call.
One way to fix this is to return (or yield) multiple instances:
>>> def factory(n):
class MyClass(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
for i in range(n):
yield MyClass()
>>> a, b = factory(2)
>>> a.compare(b)
Comparison Result: True
is a possible implementation.
EDIT: If the instances are created dynamically, then the above solution is invalid. One way to do it is to create a superclass outside, then inside the factory function subclass from that superclass:
>>> class MyClass(object):
pass
>>> def factory():
class SubClass(MyClass):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
return SubClass()
However, this does not work because they are still different classes. So you need to change your comparison method to check against the first superclass:
isinstance(other, self.__class__.__mro__[1])
If your class definition is inside the factory function, than each instance of the class you create will be an instance of a separate class. That's because the class definition is a statement, that's executed just like any other assignment. The name and contents of the different classes will be the same, but their identities will be distinct.
I don't think there's any simple way to get around that without changing the structure of your code in some way. You've said that your actual factory function is a method of a class, which suggests that you might be able to move the class definition somewhere else so that it can be shared by multiple calls to the factory method. Depending on what information you expect the inner class to use from the outer class, you might define it at class level (so there'd be only one class definition used everywhere), or you could define it in another method, like __init__ (which would create a new inner class for every instance of the outer class).
Here's what that last approach might look like:
class Outer(object):
def __init__(self):
class Inner(object):
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
self.Inner = Inner
def factory(self):
return self.Inner()
f = Outer()
a = f.factory()
b = f.factory()
print(a.compare(b)) # True
g = Outer() # create another instance of the outer class
c = g.factory()
print(a.compare(c)) # False
It's not entirely clear what you're asking. It seems to me you want a simpler version of the code you already posted. If that's incorrect, this answer is not relevant.
You can create classes dynamically by explicitly constructing a new instance of the type type.
def compare(self, other):
...
def factory():
return type("MyClass", (object,), { 'compare': compare }()
type takes three arguments: the name, the parents, and the predefined slots. So this will behave the same way as your previous code.
Working off the answer from #rassar, and adding some more detail to represent the actual implementation (e.g. the factory-method existing in a parent class), I have come up with a working example below.
From #rassar's answer, I realised that the class is dynamically created each time, and so defining it within the parent object (or even above that), means that it will be the same class definition each time it is called.
class Parent(object):
class MyClass(object):
def __init__(self, parent):
self.parent = parent
def compare(self, other):
print('Comparison Result: {}'.format(isinstance(other, self.__class__)))
def factory(self):
return self.MyClass(self)
a = Parent()
b = a.factory()
c = a.factory()
b.compare(c)
print(id(b.__class__))
print(id(c.__class__))
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)
I am trying to dynamically create classes in Python and am relatively new to classes and class inheritance. Basically I want my final object to have different types of history depending on different needs. I have a solution but I feel there must be a better way. I dreamed up something like this.
class A:
def __init__(self):
self.history={}
def do_something():
pass
class B:
def __init__(self):
self.history=[]
def do_something_else():
pass
class C(A,B):
def __init__(self, a=False, b=False):
if a:
A.__init__(self)
elif b:
B.__init__(self)
use1 = C(a=True)
use2 = C(b=True)
You probably don't really need that, and this is probably an XY problem, but those happen regularly when you are learning a language. You should be aware that you typically don't need to build huge class hierarchies with Python like you do with some other languages. Python employs "duck typing" -- if a class has the method you want to use, just call it!
Also, by the time __init__ is called, the instance already exists. You can't (easily) change it out for a different instance at that time (though, really, anything is possible).
if you really want to be able to instantiate a class and receive what are essentially instances of completely different objects depending on what you passed to the constructor, the simple, straightforward thing to do is use a function that returns instances of different classes.
However, for completeness, you should know that classes can define a __new__ method, which gets called before __init__. This method can return an instance of the class, or an instance of a completely different class, or whatever the heck it wants. So, for example, you can do this:
class A(object):
def __init__(self):
self.history={}
def do_something(self):
print("Class A doing something", self.history)
class B(object):
def __init__(self):
self.history=[]
def do_something_else(self):
print("Class B doing something", self.history)
class C(object):
def __new__(cls, a=False, b=False):
if a:
return A()
elif b:
return B()
use1 = C(a=True)
use2 = C(b=True)
use3 = C()
use1.do_something()
use2.do_something_else()
print (use3 is None)
This works with either Python 2 or 3. With 3 it returns:
Class A doing something {}
Class B doing something []
True
I'm assuming that for some reason you can't change A and B, and you need the functionality of both.
Maybe what you need are two different classes:
class CAB(A, B):
'''uses A's __init__'''
class CBA(B, A):
'''uses B's __init__'''
use1 = CAB()
use2 = CBA()
The goal is to dynamically create a class.
I don't really recommend dynamically creating a class. You can use a function to do this, and you can easily do things like pickle the instances because they're available in the global namespace of the module:
def make_C(a=False, b=False):
if a:
return CAB()
elif b:
return CBA()
But if you insist on "dynamically creating the class"
def make_C(a=False, b=False):
if a:
return type('C', (A, B), {})()
elif b:
return type('C', (B, A), {})()
And usage either way is:
use1 = make_C(a=True)
use2 = make_C(b=True)
I was thinking about the very same thing and came up with a helper method for returning a class inheriting from the type provided as an argument.
The helper function defines and returns the class, which is inheriting from the type provided as an argument.
The solution presented itself when I was working on a named value class. I wanted a value, that could have its own name, but that could behave as a regular variable. The idea could be implemented mostly for debugging processes, I think. Here is the code:
def getValueClass(thetype):
"""Helper function for getting the `Value` class
Getting the named value class, based on `thetype`.
"""
# if thetype not in (int, float, complex): # if needed
# raise TypeError("The type is not numeric.")
class Value(thetype):
__text_signature__ = "(value, name: str = "")"
__doc__ = f"A named value of type `{thetype.__name__}`"
def __init__(self, value, name: str = ""):
"""Value(value, name) -- a named value"""
self._name = name
def __new__(cls, value, name: str = ""):
instance = super().__new__(cls, value)
return instance
def __repr__(self):
return f"{super().__repr__()}"
def __str__(self):
return f"{self._name} = {super().__str__()}"
return Value
Some examples:
IValue = getValueClass(int)
FValue = getValueClass(float)
CValue = getValueClass(complex)
iv = IValue(3, "iv")
print(f"{iv!r}")
print(iv)
print()
fv = FValue(4.5, "fv")
print(f"{fv!r}")
print(fv)
print()
cv = CValue(7 + 11j, "cv")
print(f"{cv!r}")
print(cv)
print()
print(f"{iv + fv + cv = }")
The output:
3
iv = 3
4.5
fv = 4.5
(7+11j)
cv = (7+11j)
iv + fv + cv = (14.5+11j)
When working in IDLE, the variables seem to behave as built-in types, except when printing:
>>> vi = IValue(4, "vi")
>>> vi
4
>>> print(vi)
vi = 4
>>> vf = FValue(3.5, 'vf')
>>> vf
3.5
>>> vf + vi
7.5
>>>