Here is my code.
class A(object):
def __init__(self):
self.a = 1
def x(self):
print("A.x")
def y(self):
print("A.y")
def z(self):
print("A.z")
class B(A):
def __init__(self):
A.__init__(self)
self.a = 2
self.b = 3
def y(self):
print("B.y")
def z(self):
print("B.z")
class C(object):
def __init__(self):
self.a = 4
self.c = 5
def y(self):
print("C.y")
def z(self):
print("C.z")
class D(C, B):
def __init__(self):
C.__init__(self)
B.__init__(self)
self.d = 6
def z(self):
print("D.z")
obj = D()
print(obj.a)
Why does print(obj.a) return 2 and not 4? I thought Python scans inputs from left to right. So with that logic it should refer to the superclass C and find that self.a = 4 and not refer to the superclass B where self.a = 2
The attribute obj.a is found directly in the instance namespace, so the MRO is not really involved here.
>>> print(obj.__dict__)
{'a': 2, 'c': 5, 'b': 3, 'd': 6}
If you're asking why the instance namespace contains a=2 and not a=4, it's because it was set to 4 initially and then overwritten:
C.__init__(self) # sets self.__dict__["a"] = 4
B.__init__(self) # sets self.__dict__["a"] = 2
Why does print(obj.a) return 2 and not 4?
Because the object obj can only have one attribute named a, and its value was most recently set to 2.
I thought Python scans inputs from left to right.
To determine the class' method resolution order, yes. However, the MRO is only relevant when either implicitly looking for attributes that are missing in the current class, or explicitly passing along the chain via super.
So with that logic it should refer to the superclass C
No; when obj.a is looked up at the end, it doesn't look in any classes at all for the attribute, because the object contains the attribute. It doesn't look in C, B or A. It looks in obj, finds the attribute, and stops looking. (It does first look at D, in case it defines some magic that would override the normal process.)
The base classes do not create separate namespaces for attributes. Rather, they are separate objects, whose attributes can be found by the attribute lookup process (and, when they are, those attributes might be automatically converted via the descriptor protocol: e.g. attributes that are functions within the class, will normally become methods when looked up from the instance).
But when e.g. self.a = 2 happens, self means the same object inside that code that obj means outside. Assigning an attribute doesn't do any lookup - there's nothing to look up; there's already a perfectly suitable place to attach the attribute. So it just gets attached there. Where it will subsequently be found.
Because the parent classes were initialized explicitly, the order is clear: D.__init__ calls C.__init__ which sets self.a = 4; then that returns and D.__init__ also calls B.__init__; that calls A.__init__, which sets self.a = 1; then B.__init__ directly sets self.a = 2; then all the calls return (after setting other attributes). In each case, self is naming the same object, so it sets the same attribute in the same namespace (i.e. the attributes of that object, treated as a namespace).
and not refer to the superclass B where self.a = 2
Again, they are not separate namespaces (and unlike some other languages, not separate "parts" of the object), so B isn't a "place where" self.a can have a different value from the one it has "in" C. There's only one self object, with one __dict__, and one a (equivalently, __dict__['a']).
Related
In the following python code (I'm using 3.8), an object of class B derived from class A calls methods bar and foo that access members of the parent class through the super() function. Hence, I would expect the same result as calling bar and foo directly on A. Oddly, what is returned is affected by the parameterization of p of B, which should not happen because A should shielded from its children, shouldn't it?! Here is the code to reproduce:
class A(object):
#property
def p(self):
return 3
def bar(self):
return self.p
def foo(self):
return self.bar()
class B(A):
#property
def p(self):
return 6
def bar(self):
return super().p
def foo(self):
return super().bar()
a, b = A(), B()
print(a.p) # prints 3, OK
print(b.p) # prints 6, OK
print(a.bar()) # prints 3, OK
print(b.bar()) # prints 3, OK, since where accessing super().p
print(a.foo()) # prints 3, OK
print(b.foo()) # prints 6, NOT OK, because we are accessing super().bar() and expect 3
I'm out of my wits here, so if someone could iluminate on the rationale of this behavior and show a way to avoid it, this would be most helpful. Thanks a lot.
Welcome to the intricacies of super!
super() here is a shortcut for super(B, self). It returns a proxy that will look in the class MRO for the class coming before B, so A and super().bar() will actually call:
A.bar(self)
without changing the original b object...
And A.bar(self) is actually... b.p and will give 6
If you are used to other object oriented languages like C++, all happens as if all method in Python were virtual (non final in Java wordings)
super().attr means to look up the attr attribue in the parent. If the attr is a method, it looks up the method's code (instructions to execute). But that does not modify the passed arguments in any way, it just sets the instuctions.
In Python the self is an argument behind the scenes. If c=C(), then c.meth(...) means C.meth(c, ...), i.e. a call of method meth defined in the class C with first argument c (other args follow, if any). The first arg becomes the self argument in the method's implementation. The name self is just a convention, not a special keyword)
Back to the question. Here is a simplified program without properties, it behaves the same:
class A:
P = 3
def bar(self):
return self.P
def foo(self):
return self.bar()
class B(A):
P = 6
def bar(self):
return super().P
def foo(self):
return super().bar()
b.foo() invokes super().bar(), i.e. the bar() in the parent class A. That method contains code that simply returns self.P. But self is b, so the lookup returns 6. (In your original program p is a property that returns 6)
I am not quite sure this is possible (or something similar) in python. I want to access a method (or another object) of a class from an object that is an attribute of such class.
Consider the following code:
class A():
def __init__(self):
self.b = B()
self.c = C()
def print_owner(self):
print('owner')
class B():
def __init__(self):
pass
def call_owner(self):
self.owner().print_owner()
so that b as an object attribute of class A, can refer to a method or attribute of A?
Or similarly, is it possible that b can access c?
It's possible. You can pass a reference to A to B constructor:
...
self.b = B(self)
...
class B:
def __init__(self, a):
self.a = a
So, B.a stores the reference to its owner A.
There can be many references to object B(), not only the one in instance of class A. So it's not possible as it is in your code. (Well you could try a hack, like finding all instances of class A in memory and find the one whose attribute b points to your B instance, but that's a really bad idea).
You should explicitly store in instance of B a reference to the owner.
You have a couple of options here. The better one is probably #Sianur suggests. It's simple, effective, and explicit. Give that answer an upvote.
Another option is to have the owner force itself on its minions. B can do something like
def call_owner(self):
if hasattr(self, 'owner'):
self.owner().print_owner()
else:
print('I am free!')
Meanwhile, A would set the owner attribute to itself:
def __init__(self):
self.b = B()
self.c = C()
self.b.owner = self.c.owner = self
In any case, if you want an object to have access to another object, store the reference into an accessible place. There's no magic here.
I am writing a class that needs to behave as if it were an instance of another class, but have additional methods and attributes. I've tried doing different things within __new__ but to no avail. As an example, here is a half-written class and the desired behavior:
class A(object):
def __new__(self, a):
value = 100 # instances of A need to behave like integers
... # bind A methods and attributes to value?
return value
def __init__(self, a)
self.a = a
def something(self):
return 20 + self.a
Here is the desired behavior:
a = A(10, 5)
print(a + 10) # 110
print(a * 2) # 200
print(a.b) # 5
print(a.something()) # 25
I know that when __new__ returns an instance of a class different than A, then __init__ and other methods are not bound to value. None of the other methods are either. Is this sort of thing possible? Am I thinking about this problem the wrong way?
EDIT
Note that this class doesn't return instances of integer, just for the purpose of the example.
The reason why (I think that) I can't just subclass, in this case, int, is because I need to construct the class when it is called. __init__ doesn't return anything, otherwise, maybe I could do something like:
class A(object):
def __init__(self, a):
self.a = a
... # logic constructing `value`
value = 100 # `value` ends up being an integer
return value
def something(self):
return self.a
In case this is relevant, value is a theano TensorVariable. I would like to add extra methods and attributes to the instance of TensorVariable created for use by other functionality downstream.
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).
Dealing with classes (nested etc) does not look easy in Python, surprisingly! The following problem appeared to me recently and took several hours (try, search ...) without success. I read most of SO related links but none of them has pointed the issue presented here!
#------------------------------------
class A:
def __init__(self):
self.a = 'a'
print self.a
class B(A):
def __init__(self):
self.b = 'b'
A.a = 'a_b'
print self.b, A.a
#------------------------------------
class C:
class A:
def __init__(self):
self.a = 'a'
print self.a
class B(A):
def __init__(self):
self.b = 'b'
A.a = 'a_b'
print self.b, A.a
#------------------------------------
#------------------------------------
>>> c1 = A()
a
>>> c1.a
'a'
>>> c2 = B()
b
>>> c2.a, c2.b
('a_b', 'b')
>>> c3 = C()
>>> c4 = c3.A()
a
>>> c4.a
'a'
>>> c5 = c3.B()
b a_b
>>> c5.b
'b'
>>> c5.a
Traceback (most recent call last):
File "", line 1, in
AttributeError: B instance has no attribute 'a'
Where is the problem in the code?
AND
In both cases it seems that when B(A) is initialized A() is not initialized. What is the solution for this issue? Note that the term A.__init__() being called inside B()'s __init__() does not work!
Updates:
class Geometry:
class Curve:
def __init__(self,c=1):
self.c = c #curvature parameter
print 'Curvature %g'%self.c
pass #some codes
class Line(Curve):
def __init__(self):
Geometry.Curve.__init__(self,0) #the key point
pass #some codes
g = Geometry()
C = g.Curve(0.5)
L = g.Line()
which results in:
Curvature 0.5
Curvature 0
what I was looking for.
The code executed in a method runs in the local scope of that method. If you access an object that is not in this scope, Python will look it up in the global/module scope, NOT in the class scope or the scope of any enclosing class!
This means that:
A.a = 'a_b'
inside C.B.__init__ will set the class attribute of the global A class, not C.A as you probably intended. For that you would have to do this:
C.A.a = 'a_b'
Also, Python will not call parent methods if you override them in subclasses. You have to do it yourself.
The scoping rules mean that if you wanted to call the __init__ method of the parent class inside C.B.__init__, it has to look like this:
C.A.__init__(self)
and NOT like this:
A.__init__(self)
which is probably what you've tried.
Nested classes seems so unpythonic, even if considered as factories. But to answer your question: There simply is no c5.a (instance of C.B). In the init-method of C.B you add to the CLASS C.A an attribute a, but not to C.B! The class A does already have an attribute a, if instantiated! But the object of class B (and even the class) doesn't!
You must also keep in mind, that __init__ is not an constructor like in C++ or Java! The "real constructor" in python would be __new__. __init__ just initializes the instance of a class!
class A:
c = 'class-attribute'
def __init__(self):
self.i = 'instance-attribute'
So in this example c is a class-attribute, where i is an attribute of the instance.
Even more curios, is your attempt to add an attribute to the baseclass at the moment of the instantiation of the child-class. You are not getting a "late" inheritance-attribute that way.
You simply add to the class A an additional attribute, which surprises me to even work. I guess you are using python 3.x?
The reason for this behaviour? Well, i guess it has to do with pythons neat feature that in python definitions are executed(AFAIK).
The same reason why:
def method(lst = []):
is almost ever a bad idea. the deafult-parameter gets bound at the moment of the definition and you won't generate a new list-object every-time you call the method, but reusing the same list-object.