I have a class A
class A(object):
a = 1
def __init__(self):
self.b = 10
def foo(self):
print type(self).a
print self.b
Then I want to create a class B, which equivalent as A but with different name and value of class member a:
This is what I have tried:
class A(object):
a = 1
def __init__(self):
self.b = 10
def foo(self):
print type(self).a
print self.b
A_dummy = type('A_dummy',(object,),{})
A_attrs = {attr:getattr(A,attr) for attr in dir(A) if (not attr in dir(A_dummy))}
B = type('B',(object,),A_attrs)
B.a = 2
a = A()
a.foo()
b = B()
b.foo()
However I got an Error:
File "test.py", line 31, in main
b.foo()
TypeError: unbound method foo() must be called with A instance as first argument (got nothing instead)
So How I can cope with this sort of jobs (create a copy of an exists class)? Maybe a meta class is needed? But What I prefer is just a function FooCopyClass, such that:
B = FooCopyClass('B',A)
A.a = 10
B.a = 100
print A.a # get 10 as output
print B.a # get 100 as output
In this case, modifying the class member of B won't influence the A, vice versa.
The problem you're encountering is that looking up a method attribute on a Python 2 class creates an unbound method, it doesn't return the underlying raw function (on Python 3, unbound methods are abolished, and what you're attempting would work just fine). You need to bypass the descriptor protocol machinery that converts from function to unbound method. The easiest way is to use vars to grab the class's attribute dictionary directly:
# Make copy of A's attributes
Bvars = vars(A).copy()
# Modify the desired attribute
Bvars['a'] = 2
# Construct the new class from it
B = type('B', (object,), Bvars)
Equivalently, you could copy and initialize B in one step, then reassign B.a after:
# Still need to copy; can't initialize from the proxy type vars(SOMECLASS)
# returns to protect the class internals
B = type('B', (object,), vars(A).copy())
B.a = 2
Or for slightly non-idiomatic one-liner fun:
B = type('B', (object,), dict(vars(A), a=2))
Either way, when you're done:
B().foo()
will output:
2
10
as expected.
You may be trying to (1) create copies of classes for some reason for some real app:
in that case, try using copy.deepcopy - it includes the mechanisms to copy classes. Just change the copy __name__ attribute afterwards if needed. Works both in Python 2 or Python 3.
(2) Trying to learn and understand about Python internal class organization: in that case, there is no reason to fight with Python 2, as some wrinkles there were fixed for Python 3.
In any case, if you try using dir for fetching a class attributes, you will end up with more than you want - as dir also retrieves the methods and attributes of all superclasses. So, even if your method is made to work (in Python 2 that means getting the .im_func attribute of retrieved unbound methods, to use as raw functions on creating a new class), your class would have more methods than the original one.
Actually, both in Python 2 and Python 3, copying a class __dict__ will suffice. If you want mutable objects that are class attributes not to be shared, you should resort again to deepcopy. In Python 3:
class A(object):
b = []
def foo(self):
print(self.b)
from copy import deepcopy
def copy_class(cls, new_name):
new_cls = type(new_name, cls.__bases__, deepcopy(A.__dict__))
new_cls.__name__ = new_name
return new_cls
In Python 2, it would work almost the same, but there is no convenient way to get the explicit bases of an existing class (i.e. __bases__ is not set). You can use __mro__ for the same effect. The only thing is that all ancestor classes are passed in a hardcoded order as bases of the new class, and in a complex hierarchy you could have differences between the behaviors of B descendants and A descendants if multiple-inheritance is used.
Related
Let's say I have 2 classes A and B, where B inherits from A. B overrides some methods of A and B have a couple more attributes. Once I created an object b of type B, is it possible to convert it into the type A and only A ? This is to get the primitive behavior of the methods
I don't know how safe it is, but you can reassign the __class__ attribute of the object.
class A:
def f(self):
print("A")
class B(A):
def f(self):
print("B")
b = B()
b.f() # prints B
b.__class__ = A
b.f() # prints A
This only changes the class of the object, it doesn't update any of the attributes. In Python, attributes are added dynamically to objects, and nothing intrinsically links them to specific classes, so there's no way to automatically update the attributes if you change the class.
I asked about this yesterday, but I botched writing up my question so much that by the time I realized what I typed, all the replies were solutions to a different miss-worded problem I didn't have. Sorry for the foolish type up last time.
I have two Classes, and I want them to able to share a common list without having to pass it as a parameter. I also want to create a method that will scramble that list, and I want the list to be the same newly scrambled list in both Class A and Class B.
I figured this was a case for inheritance, so I made a Parent Class and set the list as a class attribute and made a method to scramble, but the list variable is oddly enough being now treated as an instance variable of the children.
class A:
lst = []
target = 0
def generateNewLst(self, randomRange, listSize):
self.lst = [random.randint(*randomRange) for i in range(listSize)]
class B(A):
pass
class C(A):
pass
My inherited method works just fine:
a = B()
a.generateNewLst((0, 10), 3)
a.lst # => [2,5,7]
but when I create another B:
b = B()
b.lst # => [] not shared when I want it to be
This CANNOT be solved with a class attribute in B, because that won't solve the more important below issue...
c = C()
c.lst # => [] not shared when I want it to be
TL;DR: I want a Class attribute that shares between every instance of both classes. I want a.lst == b.lst == c.lst every time I run generateNewList on ONE of any of those instances.
How should I reorganize my setup to work the way I want it to?
You need a static variable. To do so make the method generateNewLst static and let him update the static variable lst and not a member variable lst that would belong to the instance of the class and not to the class itself.
class A:
lst = []
#staticmethod
def generateNewLst(randomRange, listSize):
A.lst = [random.randint(*randomRange) for i in range(listSize)]
class B(A):
pass
class C(A):
pass
Then once you generate the lst you will have it for all classes.
a = B()
B.generateNewLst((0, 10), 3)
# the same list is available for all classes
print(A.lst)
print(B.lst)
print(C.lst)
I am learning all about Python classes and I have a lot of ground to cover.
I came across an example that got me a bit confused.
These are the parent classes
Class X
Class Y
Class Z
Child classes are:
Class A (X,Y)
Class B (Y,Z)
Grandchild class is:
Class M (A,B,Z)
Doesn't Class M inherit Class Z through inheriting from Class B or what would the reason be for this type of structure? Class M would just ignore the second time Class Z is inherited wouldn't it be, or am I missing something?
Class M would just inherit the Class Z attributes twice (redundant) wouldn't it be, or am I missing something?
No, there are no "duplicated" attributes, Python performs a linearization they can the Method Resolution Order (MRO) as is, for instance, explained here. You are however correct that here adding Z to the list does not change anything.
They first construct MRO's for the parents, so:
MRO(X) = (X,object)
MRO(Y) = (Y,object)
MRO(Z) = (Z,object)
MRO(A) = (A,X,Y,object)
MRO(B) = (B,Y,Z,object)
and then they construct an MRO for M by merging:
MRO(M) = (M,)+merge((A,X,Y,object),(B,Y,Z,object),(Z,object))
= (M,A,X,B,Y,Z,object)
Now each time you call a method, Python will first check if the attribute is in the internal dictionary self.__dict__ of that object). If not, Python will walk throught the MRO and attempt to find an attribute with that name. From the moment it finds one, it will stop searching.
Finally super() is a proxy-object that does the same resolution, but starts in the MRO at the stage of the class. So in this case if you have:
class B:
def foo():
super().bar()
and you construct an object m = M() and call m.foo() then - given the foo() of B is called, super().bar will first attempt to find a bar in Y, if that fails, it will look for a bar in Z and finally in object.
Attributes are not inherited twice. If you add an attribute like:
self.qux = 1425
then it is simply added to the internal self.__dict__ dictionary of that object.
Stating Z explicitly however can be beneficial: if the designer of B is not sure whether Z is a real requirement. In that case you know for sure that Z will still be in the MRO if B is altered.
Apart from what #Willem has mentioned, I would like to add that, you are talking about multiple inheritance problem. For python, object instantiation is a bit different compared other languages like Java. Here, object instatiation is divided into two parts :- Object creation(using __new__ method) and object initialization(using __init__ method). Moreover, it's not necessary that child class will always have parent class's attributes. Child class get parent class's attribute, only if parent class constructor is invoked from child class(explicitly).
>>> class A(object):
def __init__(self):
self.a = 23
>>> class B(A):
def __init__(self):
self.b = 33
>>> class C(A):
def __init__(self):
self.c = 44
super(C, self).__init__()
>>> a = A()
>>> b = B()
>>> c = C()
>>> print (a.a) 23
>>> print (b.a) Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: 'B' object has no attribute 'a'
>>> print (c.a) 23
In the above code snipped, B is not invoking A's __init__ method and so, it doesn't have a as member variable, despite the fact that it's inheriting from A class. Same thing is not the case for language like Java, where there's a fixed template of attributes, that a class will have. This's how python is different from other languages.
Attributes that an object have, are stored in __dict__ member of object and it's __getattribute__ magic method in object class, which implements attribute lookup according to mro specified by willem. You can use vars() and dir() method for introspection of instance.
Firstly, there is class A with two class variables and two instance variables:
In [1]: def fun(x, y): return x + y
In [2]: class A:
...: cvar = 1
...: cfun = fun
...: def __init__(self):
...: self.ivar = 100
...: self.ifun = fun
We can see that both class variable and instance variable of int type works fine:
In [3]: a = A()
In [4]: a.ivar, a.cvar
Out[4]: (100, 1)
However, things have changed if we check the function type variables:
In [5]: a.ifun, a.cfun
Out[5]:
(<function __main__.fun>,
<bound method A.fun of <__main__.A instance at 0x25f90e0>>)
In [6]: a.ifun(1,2)
Out[6]: 3
In [7]: a.cfun(1,2)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/home/future/<ipython-input-7-39aa8db2389e> in <module>()
----> 1 a.cfun(1,2)
TypeError: fun() takes exactly 2 arguments (3 given)
I known that python has translated a.cfun(1,2) to A.cfun(a,1,2) and then error raised.
My question is: Since both cvar and cfun are class variable, why do python treat them in difference way?
Actually, a function assigned to a class member remains function:
def x():pass
class A:
f = x
e = None
g = None
print(A.__dict__['f'])
# <function x at 0x10e0a6e60>
It's converted on the fly to a method object when you retrieve it from an instance:
print(A().f)
# <bound method A.x of <__main__.A instance at 0x1101ddea8>>
http://docs.python.org/2/reference/datamodel.html#the-standard-type-hierarchy "User-defined methods":
User-defined method objects may be created when getting an attribute of a class (perhaps via an instance of that class), if that attribute is a user-defined function object, an unbound user-defined method object, or a class method object... Note that the transformation from function object to (unbound or bound) method object happens each time the attribute is retrieved from the class or instance.
This conversion only occurs to functions assigned to a class, not to an instance. Note that this has been changed in Python 3, where Class.fun returns a normal function, not an "unbound method".
As to your question why is this needed, a method object are essentially a closure that contains a function along with its execution context ("self"). Imagine you've got an object and use its method as a callback somewhere. In many other languages you have to pass both object and method pointers or to create a closure manually. For example, in javascript:
myListener = new Listener()
something.onSomeEvent = myListener.listen // won't work!
something.onSomeEvent = function() { myListener.listen() } // works
Python manages that for us behind the scenes:
myListener = Listener()
something.onSomeEvent = myListener.listen // works
On the other side, sometimes it's practical to have "bare" functions or "foreign" methods in a class:
def __init__(..., dir, ..):
self.strip = str.lstrip if dir == 'ltr' else str.rstrip
...
def foo(self, arg):
self.strip(arg)
This above convention (class vars => methods, instance vars => functions) provides a convenient way to have both.
Needless to add, like everything else in python, it's possible to change this behavior, i.e. to write a class that doesn't convert its functions to methods and returns them as is.
The way I usually declare a class variable to be used in instances in Python is the following:
class MyClass(object):
def __init__(self):
self.a_member = 0
my_object = MyClass()
my_object.a_member # evaluates to 0
But the following also works. Is it bad practice? If so, why?
class MyClass(object):
a_member = 0
my_object = MyClass()
my_object.a_member # also evaluates to 0
The second method is used all over Zope, but I haven't seen it anywhere else. Why is that?
Edit: as a response to sr2222's answer. I understand that the two are essentially different. However, if the class is only ever used to instantiate objects, the two will work he same way. So is it bad to use a class variable as an instance variable? It feels like it would be but I can't explain why.
The question is whether this is an attribute of the class itself or of a particular object. If the whole class of things has a certain attribute (possibly with minor exceptions), then by all means, assign an attribute onto the class. If some strange objects, or subclasses differ in this attribute, they can override it as necessary. Also, this is more memory-efficient than assigning an essentially constant attribute onto every object; only the class's __dict__ has a single entry for that attribute, and the __dict__ of each object may remain empty (at least for that particular attribute).
In short, both of your examples are quite idiomatic code, but they mean somewhat different things, both at the machine level, and at the human semantic level.
Let me explain this:
>>> class MyClass(object):
... a_member = 'a'
...
>>> o = MyClass()
>>> p = MyClass()
>>> o.a_member
'a'
>>> p.a_member
'a'
>>> o.a_member = 'b'
>>> p.a_member
'a'
On line two, you're setting a "class attribute". This is litterally an attribute of the object named "MyClass". It is stored as MyClass.__dict__['a_member'] = 'a'. On later lines, you're setting the object attribute o.a_member to be. This is completely equivalent to o.__dict__['a_member'] = 'b'. You can see that this has nothing to do with the separate dictionary of p.__dict__. When accessing a_member of p, it is not found in the object dictionary, and deferred up to its class dictionary: MyClass.a_member. This is why modifying the attributes of o do not affect the attributes of p, because it doesn't affect the attributes of MyClass.
The first is an instance attribute, the second a class attribute. They are not the same at all. An instance attribute is attached to an actual created object of the type whereas the class variable is attached to the class (the type) itself.
>>> class A(object):
... cls_attr = 'a'
... def __init__(self, x):
... self.ins_attr = x
...
>>> a1 = A(1)
>>> a2 = A(2)
>>> a1.cls_attr
'a'
>>> a2.cls_attr
'a'
>>> a1.ins_attr
1
>>> a2.ins_attr
2
>>> a1.__class__.cls_attr = 'b'
>>> a2.cls_attr
'b'
>>> a1.ins_attr = 3
>>> a2.ins_attr
2
Even if you are never modifying the objects' contents, the two are not interchangeable. The way I understand it, accessing class attributes is slightly slower than accessing instance attributes, because the interpreter essentially has to take an extra step to look up the class attribute.
Instance attribute
"What's a.thing?"
Class attribute
"What's a.thing? Oh, a has no instance attribute thing, I'll check its class..."
I have my answer! I owe to #mjgpy3's reference in the comment to the original post. The difference comes if the value assigned to the class variable is MUTABLE! THEN, the two will be changed together. The members split when a new value replaces the old one
>>> class MyClass(object):
... my_str = 'a'
... my_list = []
...
>>> a1, a2 = MyClass(), MyClass()
>>> a1.my_str # This is the CLASS variable.
'a'
>>> a2.my_str # This is the exact same class variable.
'a'
>>> a1.my_str = 'b' # This is a completely new instance variable. Strings are not mutable.
>>> a2.my_str # This is still the old, unchanged class variable.
'a'
>>> a1.my_list.append('w') # We're changing the mutable class variable, but not reassigning it.
>>> a2.my_list # This is the same old class variable, but with a new value.
['w']
Edit: this is pretty much what bukzor wrote. They get the best answer mark.