I have a class with two class methods (using the classmethod() function) for getting and setting what is essentially a static variable. I tried to use the property() function with these, but it results in an error. I was able to reproduce the error with the following in the interpreter:
class Foo(object):
_var = 5
#classmethod
def getvar(cls):
return cls._var
#classmethod
def setvar(cls, value):
cls._var = value
var = property(getvar, setvar)
I can demonstrate the class methods, but they don't work as properties:
>>> f = Foo()
>>> f.getvar()
5
>>> f.setvar(4)
>>> f.getvar()
4
>>> f.var
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: 'classmethod' object is not callable
>>> f.var=5
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: 'classmethod' object is not callable
Is it possible to use the property() function with #classmethod decorated functions?
3.8 < Python < 3.11
Can use both decorators together. See this answer.
Python < 3.9
A property is created on a class but affects an instance. So if you want a classmethod property, create the property on the metaclass.
>>> class foo(object):
... _var = 5
... class __metaclass__(type): # Python 2 syntax for metaclasses
... pass
... #classmethod
... def getvar(cls):
... return cls._var
... #classmethod
... def setvar(cls, value):
... cls._var = value
...
>>> foo.__metaclass__.var = property(foo.getvar.im_func, foo.setvar.im_func)
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3
But since you're using a metaclass anyway, it will read better if you just move the classmethods in there.
>>> class foo(object):
... _var = 5
... class __metaclass__(type): # Python 2 syntax for metaclasses
... #property
... def var(cls):
... return cls._var
... #var.setter
... def var(cls, value):
... cls._var = value
...
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3
or, using Python 3's metaclass=... syntax, and the metaclass defined outside of the foo class body, and the metaclass responsible for setting the initial value of _var:
>>> class foo_meta(type):
... def __init__(cls, *args, **kwargs):
... cls._var = 5
... #property
... def var(cls):
... return cls._var
... #var.setter
... def var(cls, value):
... cls._var = value
...
>>> class foo(metaclass=foo_meta):
... pass
...
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3
In Python 3.9 You could use them together, but (as noted in #xgt's comment) it was deprecated in Python 3.11, so it is not recommended to use it.
Check the version remarks here:
https://docs.python.org/3.11/library/functions.html#classmethod
However, it used to work like so:
class G:
#classmethod
#property
def __doc__(cls):
return f'A doc for {cls.__name__!r}'
Order matters - due to how the descriptors interact, #classmethod has to be on top.
I hope this dead-simple read-only #classproperty decorator would help somebody looking for classproperties.
class classproperty(property):
def __get__(self, owner_self, owner_cls):
return self.fget(owner_cls)
class C(object):
#classproperty
def x(cls):
return 1
assert C.x == 1
assert C().x == 1
Reading the Python 2.2 release notes, I find the following.
The get method [of a property] won't be called when
the property is accessed as a class
attribute (C.x) instead of as an
instance attribute (C().x). If you
want to override the __get__ operation
for properties when used as a class
attribute, you can subclass property -
it is a new-style type itself - to
extend its __get__ method, or you can
define a descriptor type from scratch
by creating a new-style class that
defines __get__, __set__ and
__delete__ methods.
NOTE: The below method doesn't actually work for setters, only getters.
Therefore, I believe the prescribed solution is to create a ClassProperty as a subclass of property.
class ClassProperty(property):
def __get__(self, cls, owner):
return self.fget.__get__(None, owner)()
class foo(object):
_var=5
def getvar(cls):
return cls._var
getvar=classmethod(getvar)
def setvar(cls,value):
cls._var=value
setvar=classmethod(setvar)
var=ClassProperty(getvar,setvar)
assert foo.getvar() == 5
foo.setvar(4)
assert foo.getvar() == 4
assert foo.var == 4
foo.var = 3
assert foo.var == 3
However, the setters don't actually work:
foo.var = 4
assert foo.var == foo._var # raises AssertionError
foo._var is unchanged, you've simply overwritten the property with a new value.
You can also use ClassProperty as a decorator:
class foo(object):
_var = 5
#ClassProperty
#classmethod
def var(cls):
return cls._var
#var.setter
#classmethod
def var(cls, value):
cls._var = value
assert foo.var == 5
Is it possible to use the property() function with classmethod decorated functions?
No.
However, a classmethod is simply a bound method (a partial function) on a class accessible from instances of that class.
Since the instance is a function of the class and you can derive the class from the instance, you can can get whatever desired behavior you might want from a class-property with property:
class Example(object):
_class_property = None
#property
def class_property(self):
return self._class_property
#class_property.setter
def class_property(self, value):
type(self)._class_property = value
#class_property.deleter
def class_property(self):
del type(self)._class_property
This code can be used to test - it should pass without raising any errors:
ex1 = Example()
ex2 = Example()
ex1.class_property = None
ex2.class_property = 'Example'
assert ex1.class_property is ex2.class_property
del ex2.class_property
assert not hasattr(ex1, 'class_property')
And note that we didn't need metaclasses at all - and you don't directly access a metaclass through its classes' instances anyways.
writing a #classproperty decorator
You can actually create a classproperty decorator in just a few lines of code by subclassing property (it's implemented in C, but you can see equivalent Python here):
class classproperty(property):
def __get__(self, obj, objtype=None):
return super(classproperty, self).__get__(objtype)
def __set__(self, obj, value):
super(classproperty, self).__set__(type(obj), value)
def __delete__(self, obj):
super(classproperty, self).__delete__(type(obj))
Then treat the decorator as if it were a classmethod combined with property:
class Foo(object):
_bar = 5
#classproperty
def bar(cls):
"""this is the bar attribute - each subclass of Foo gets its own.
Lookups should follow the method resolution order.
"""
return cls._bar
#bar.setter
def bar(cls, value):
cls._bar = value
#bar.deleter
def bar(cls):
del cls._bar
And this code should work without errors:
def main():
f = Foo()
print(f.bar)
f.bar = 4
print(f.bar)
del f.bar
try:
f.bar
except AttributeError:
pass
else:
raise RuntimeError('f.bar must have worked - inconceivable!')
help(f) # includes the Foo.bar help.
f.bar = 5
class Bar(Foo):
"a subclass of Foo, nothing more"
help(Bar) # includes the Foo.bar help!
b = Bar()
b.bar = 'baz'
print(b.bar) # prints baz
del b.bar
print(b.bar) # prints 5 - looked up from Foo!
if __name__ == '__main__':
main()
But I'm not sure how well-advised this would be. An old mailing list article suggests it shouldn't work.
Getting the property to work on the class:
The downside of the above is that the "class property" isn't accessible from the class, because it would simply overwrite the data descriptor from the class __dict__.
However, we can override this with a property defined in the metaclass __dict__. For example:
class MetaWithFooClassProperty(type):
#property
def foo(cls):
"""The foo property is a function of the class -
in this case, the trivial case of the identity function.
"""
return cls
And then a class instance of the metaclass could have a property that accesses the class's property using the principle already demonstrated in the prior sections:
class FooClassProperty(metaclass=MetaWithFooClassProperty):
#property
def foo(self):
"""access the class's property"""
return type(self).foo
And now we see both the instance
>>> FooClassProperty().foo
<class '__main__.FooClassProperty'>
and the class
>>> FooClassProperty.foo
<class '__main__.FooClassProperty'>
have access to the class property.
Python 3!
See #Amit Portnoy's answer for an even cleaner method in python >= 3.9
Old question, lots of views, sorely in need of a one-true Python 3 way.
Luckily, it's easy with the metaclass kwarg:
class FooProperties(type):
#property
def var(cls):
return cls._var
class Foo(object, metaclass=FooProperties):
_var = 'FOO!'
Then, >>> Foo.var
'FOO!'
There is no reasonable way to make this "class property" system to work in Python.
Here is one unreasonable way to make it work. You can certainly make it more seamless with increasing amounts of metaclass magic.
class ClassProperty(object):
def __init__(self, getter, setter):
self.getter = getter
self.setter = setter
def __get__(self, cls, owner):
return getattr(cls, self.getter)()
def __set__(self, cls, value):
getattr(cls, self.setter)(value)
class MetaFoo(type):
var = ClassProperty('getvar', 'setvar')
class Foo(object):
__metaclass__ = MetaFoo
_var = 5
#classmethod
def getvar(cls):
print "Getting var =", cls._var
return cls._var
#classmethod
def setvar(cls, value):
print "Setting var =", value
cls._var = value
x = Foo.var
print "Foo.var = ", x
Foo.var = 42
x = Foo.var
print "Foo.var = ", x
The knot of the issue is that properties are what Python calls "descriptors". There is no short and easy way to explain how this sort of metaprogramming works, so I must point you to the descriptor howto.
You only ever need to understand this sort of things if you are implementing a fairly advanced framework. Like a transparent object persistence or RPC system, or a kind of domain-specific language.
However, in a comment to a previous answer, you say that you
need to modify an attribute that in such a way that is seen by all instances of a class, and in the scope from which these class methods are called does not have references to all instances of the class.
It seems to me, what you really want is an Observer design pattern.
Setting it only on the meta class doesn't help if you want to access the class property via an instantiated object, in this case you need to install a normal property on the object as well (which dispatches to the class property). I think the following is a bit more clear:
#!/usr/bin/python
class classproperty(property):
def __get__(self, obj, type_):
return self.fget.__get__(None, type_)()
def __set__(self, obj, value):
cls = type(obj)
return self.fset.__get__(None, cls)(value)
class A (object):
_foo = 1
#classproperty
#classmethod
def foo(cls):
return cls._foo
#foo.setter
#classmethod
def foo(cls, value):
cls.foo = value
a = A()
print a.foo
b = A()
print b.foo
b.foo = 5
print a.foo
A.foo = 10
print b.foo
print A.foo
Half a solution, __set__ on the class does not work, still. The solution is a custom property class implementing both a property and a staticmethod
class ClassProperty(object):
def __init__(self, fget, fset):
self.fget = fget
self.fset = fset
def __get__(self, instance, owner):
return self.fget()
def __set__(self, instance, value):
self.fset(value)
class Foo(object):
_bar = 1
def get_bar():
print 'getting'
return Foo._bar
def set_bar(value):
print 'setting'
Foo._bar = value
bar = ClassProperty(get_bar, set_bar)
f = Foo()
#__get__ works
f.bar
Foo.bar
f.bar = 2
Foo.bar = 3 #__set__ does not
Because I need to modify an attribute that in such a way that is seen by all instances of a class, and in the scope from which these class methods are called does not have references to all instances of the class.
Do you have access to at least one instance of the class? I can think of a way to do it then:
class MyClass (object):
__var = None
def _set_var (self, value):
type (self).__var = value
def _get_var (self):
return self.__var
var = property (_get_var, _set_var)
a = MyClass ()
b = MyClass ()
a.var = "foo"
print b.var
Give this a try, it gets the job done without having to change/add a lot of existing code.
>>> class foo(object):
... _var = 5
... def getvar(cls):
... return cls._var
... getvar = classmethod(getvar)
... def setvar(cls, value):
... cls._var = value
... setvar = classmethod(setvar)
... var = property(lambda self: self.getvar(), lambda self, val: self.setvar(val))
...
>>> f = foo()
>>> f.var
5
>>> f.var = 3
>>> f.var
3
The property function needs two callable arguments. give them lambda wrappers (which it passes the instance as its first argument) and all is well.
Here's a solution which should work for both access via the class and access via an instance which uses a metaclass.
In [1]: class ClassPropertyMeta(type):
...: #property
...: def prop(cls):
...: return cls._prop
...: def __new__(cls, name, parents, dct):
...: # This makes overriding __getattr__ and __setattr__ in the class impossible, but should be fixable
...: dct['__getattr__'] = classmethod(lambda cls, attr: getattr(cls, attr))
...: dct['__setattr__'] = classmethod(lambda cls, attr, val: setattr(cls, attr, val))
...: return super(ClassPropertyMeta, cls).__new__(cls, name, parents, dct)
...:
In [2]: class ClassProperty(object):
...: __metaclass__ = ClassPropertyMeta
...: _prop = 42
...: def __getattr__(self, attr):
...: raise Exception('Never gets called')
...:
In [3]: ClassProperty.prop
Out[3]: 42
In [4]: ClassProperty.prop = 1
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-e2e8b423818a> in <module>()
----> 1 ClassProperty.prop = 1
AttributeError: can't set attribute
In [5]: cp = ClassProperty()
In [6]: cp.prop
Out[6]: 42
In [7]: cp.prop = 1
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-7-e8284a3ee950> in <module>()
----> 1 cp.prop = 1
<ipython-input-1-16b7c320d521> in <lambda>(cls, attr, val)
6 # This makes overriding __getattr__ and __setattr__ in the class impossible, but should be fixable
7 dct['__getattr__'] = classmethod(lambda cls, attr: getattr(cls, attr))
----> 8 dct['__setattr__'] = classmethod(lambda cls, attr, val: setattr(cls, attr, val))
9 return super(ClassPropertyMeta, cls).__new__(cls, name, parents, dct)
AttributeError: can't set attribute
This also works with a setter defined in the metaclass.
I found one clean solution to this problem. It's a package called classutilities (pip install classutilities), see the documentation here on PyPi.
Consider example:
import classutilities
class SomeClass(classutilities.ClassPropertiesMixin):
_some_variable = 8 # Some encapsulated class variable
#classutilities.classproperty
def some_variable(cls): # class property getter
return cls._some_variable
#some_variable.setter
def some_variable(cls, value): # class property setter
cls._some_variable = value
You can use it on both class level and instance level:
# Getter on class level:
value = SomeClass.some_variable
print(value) # >>> 8
# Getter on instance level
inst = SomeClass()
value = inst.some_variable
print(value) # >>> 8
# Setter on class level:
new_value = 9
SomeClass.some_variable = new_value
print(SomeClass.some_variable) # >>> 9
print(SomeClass._some_variable) # >>> 9
# Setter on instance level
inst = SomeClass()
inst.some_variable = new_value
print(SomeClass.some_variable) # >>> 9
print(SomeClass._some_variable) # >>> 9
print(inst.some_variable) # >>> 9
print(inst._some_variable) # >>> 9
As you can see, it works correctly under all circumstances.
Based on https://stackoverflow.com/a/1800999/2290820
class MetaProperty(type):
def __init__(cls, *args, **kwargs):
super()
#property
def praparty(cls):
return cls._var
#praparty.setter
def praparty(cls, val):
cls._var = val
class A(metaclass=MetaProperty):
_var = 5
print(A.praparty)
A.praparty = 6
print(A.praparty)
For a functional approach pre Python 3.9 you can use this:
def classproperty(fget):
return type(
'classproperty',
(),
{'__get__': lambda self, _, cls: fget(cls), '__module__': None}
)()
class Item:
a = 47
#classproperty
def x(cls):
return cls.a
Item.x
After searching different places, I found a method to define a classproperty
valid with Python 2 and 3.
from future.utils import with_metaclass
class BuilderMetaClass(type):
#property
def load_namespaces(self):
return (self.__sourcepath__)
class BuilderMixin(with_metaclass(BuilderMetaClass, object)):
__sourcepath__ = 'sp'
print(BuilderMixin.load_namespaces)
Hope this can help somebody :)
A code completion friendly solution for Python < 3.9
from typing import (
Callable,
Generic,
TypeVar,
)
T = TypeVar('T')
class classproperty(Generic[T]):
"""Converts a method to a class property.
"""
def __init__(self, f: Callable[..., T]):
self.fget = f
def __get__(self, instance, owner) -> T:
return self.fget(owner)
Here is my solution that also caches the class property
class class_property(object):
# this caches the result of the function call for fn with cls input
# use this as a decorator on function methods that you want converted
# into cached properties
def __init__(self, fn):
self._fn_name = fn.__name__
if not isinstance(fn, (classmethod, staticmethod)):
fn = classmethod(fn)
self._fn = fn
def __get__(self, obj, cls=None):
if cls is None:
cls = type(obj)
if (
self._fn_name in vars(cls) and
type(vars(cls)[self._fn_name]).__name__ != "class_property"
):
return vars(cls)[self._fn_name]
else:
value = self._fn.__get__(obj, cls)()
setattr(cls, self._fn_name, value)
return value
Here's my suggestion. Don't use class methods.
Seriously.
What's the reason for using class methods in this case? Why not have an ordinary object of an ordinary class?
If you simply want to change the value, a property isn't really very helpful is it? Just set the attribute value and be done with it.
A property should only be used if there's something to conceal -- something that might change in a future implementation.
Maybe your example is way stripped down, and there is some hellish calculation you've left off. But it doesn't look like the property adds significant value.
The Java-influenced "privacy" techniques (in Python, attribute names that begin with _) aren't really very helpful. Private from whom? The point of private is a little nebulous when you have the source (as you do in Python.)
The Java-influenced EJB-style getters and setters (often done as properties in Python) are there to facilitate Java's primitive introspection as well as to pass muster with the static language compiler. All those getters and setters aren't as helpful in Python.
I have a complex unpickable object that has properties (defined via getters and setters) that are of complex and unpickable type as well. I want to create a multiprocessing proxy for the object to execute some tasks in parallel.
The problem: While I have succeeded to make the getter methods available for the proxy object, I fail to make the getters return proxies for the unpickable return objects.
My setup resembles the following:
from multiprocessing.managers import BaseManager, NamespaceProxy
class A():
#property
def a(self):
return B()
#property
def b(self):
return 2
# unpickable class
class B():
def __init__(self, *args):
self.f = lambda: 1
class ProxyBase(NamespaceProxy):
_exposed_ = ('__getattribute__', '__setattr__', '__delattr__')
class AProxy(ProxyBase): pass
class BProxy(ProxyBase): pass
class MyManager(BaseManager):pass
MyManager.register('A', A, AProxy)
if __name__ == '__main__':
with MyManager() as manager:
myA = manager.A()
print(myA.b) # works great
print(myA.a) # raises error, because the object B is not pickable
I know that I can specify the result type of a method when registering it with the manager. That is, I can do
MyManager.register('A', A, AProxy, method_to_typeid={'__getattribute__':'B'})
MyManager.register('B', B, BProxy)
if __name__ == '__main__':
with MyManager() as manager:
myA = manager.A()
print(myA.a) # works great!
print(myA.b) # returns the same as myA.a ?!
It is clear to me that my solution does not work since the __getattr__ method applies to all properties, whereas I only want it to return a proxy for B when property a is accessed. How could I achieve this?
As a side question: if I remove the *args argument from the __init__ method of B, I get an error that it is called with the wrong number of arguments. Why? How could I resolve this?
I don't this is possible without some hacks, since the choice to return a value or proxy is made based on the method name alone, and not the type of the return value (from Server.serve_client):
try:
res = function(*args, **kwds)
except Exception as e:
msg = ('#ERROR', e)
else:
typeid = gettypeid and gettypeid.get(methodname, None)
if typeid:
rident, rexposed = self.create(conn, typeid, res)
token = Token(typeid, self.address, rident)
msg = ('#PROXY', (rexposed, token))
else:
msg = ('#RETURN', res)
Also keep in mind exposing __getattribute__ in an unpickable class's proxy basically breaks the proxy functionality when calling methods.
But if you're willing to hack it and just need attribute access, here is a working solution (note calling myA.a.f() still won't work, the lambda is an attribute and is not proxied, only methods are, but that's a different problem).
import os
from multiprocessing.managers import BaseManager, NamespaceProxy, Server
class A():
#property
def a(self):
return B()
#property
def b(self):
return 2
# unpickable class
class B():
def __init__(self, *args):
self.f = lambda: 1
self.pid = os.getpid()
class HackedObj:
def __init__(self, obj, gettypeid):
self.obj = obj
self.gettypeid = gettypeid
def __getattribute__(self, attr):
if attr == '__getattribute__':
return object.__getattribute__(self, attr)
obj = object.__getattribute__(self, 'obj')
result = object.__getattribute__(obj, attr)
if isinstance(result, B):
gettypeid = object.__getattribute__(self, 'gettypeid')
# This tells the server that the return value of this method is
# B, for which we've registered a proxy.
gettypeid['__getattribute__'] = 'B'
return result
class HackedDict:
def __init__(self, data):
self.data = data
def __setitem__(self, key, value):
self.data[key] = value
def __getitem__(self, key):
obj, exposed, gettypeid = self.data[key]
if isinstance(obj, A):
gettypeid = gettypeid.copy() if gettypeid else {}
# Now we need getattr to update gettypeid based on the result
# luckily BaseManager queries the typeid info after the function
# has been invoked
obj = HackedObj(obj, gettypeid)
return (obj, exposed, gettypeid)
class HackedServer(Server):
def __init__(self, registry, address, authkey, serializer):
super().__init__(registry, address, authkey, serializer)
self.id_to_obj = HackedDict(self.id_to_obj)
class MyManager(BaseManager):
_Server = HackedServer
class ProxyBase(NamespaceProxy):
_exposed_ = ('__getattribute__', '__setattr__', '__delattr__')
class AProxy(ProxyBase): pass
class BProxy(ProxyBase): pass
MyManager.register('A', callable=A, proxytype=AProxy)
MyManager.register('B', callable=B, proxytype=BProxy)
if __name__ == '__main__':
print("This process: ", os.getpid())
with MyManager() as manager:
myB = manager.B()
print("Proxy process, using B directly: ", myB.pid)
myA = manager.A()
print('myA.b', myA.b)
print("Proxy process, via A: ", myA.a.pid)
The key to the solution is to replace the _Server in our manager, and then wrap the id_to_obj dict with the one that performs the hack for the specific method we need.
The hack consists on populating the gettypeid dict for the method, but only after it has been evaluated and we know the return type to be one that we would need a proxy for. And we're lucky in the order of evaluations, gettypeid is accessed after the method has been called.
Also luckily gettypeid is used as a local in the serve_client method, so we can return a copy of it and modify it and we don't introduce any concurrency issues.
While this was a fun exercise, I have to say I really advise against this solution, if you're dealing with external code that you cannot modify, you should simply create your own wrapper class that has explicit methods instead of #property accessors, proxy your own class instead, and use method_to_typeid.
I implemented a metaclass that tears down the class attributes for classes created with it and builds methods from the data from those arguments, then attaches those dynamically created methods directly to the class object (the class in question allows for easy definition of web form objects for use in a web testing framework). It has been working just fine, but now I have a need to add a more complex type of method, which, to try to keep things clean, I implemented as a callable class. Unfortunately, when I try to call the callable class on an instance, it is treated as a class attribute instead of an instance method, and when called, only receives its own self. I can see why this happens, but I was hoping someone might have a better solution than the ones I've come up with. Simplified illustration of the problem:
class Foo(object):
def __init__(self, name, val):
self.name = name
self.val = val
self.__name__ = name + '_foo'
self.name = name
# This doesn't work as I'd wish
def __call__(self, instance):
return self.name + str(self.val + instance.val)
def get_methods(name, foo_val):
foo = Foo(name, foo_val)
def bar(self):
return name + str(self.val + 2)
bar.__name__ = name + '_bar'
return foo, bar
class Baz(object):
def __init__(self, val):
self.val = val
for method in get_methods('biff', 1):
setattr(Baz, method.__name__, method)
baz = Baz(10)
# baz.val == 10
# baz.biff_foo() == 'biff11'
# baz.biff_bar() == 'biff12'
I've thought of:
Using a descriptor, but that seems way more complex than is necessary here
Using a closure inside of a factory for foo, but nested closures are ugly and messy replacements for objects most of the time, imo
Wrapping the Foo instance in a method that passes its self down to the Foo instance as instance, basically a decorator, that is what I actually add to Baz, but that seems superfluous and basically just a more complicated way of doing the same thing as (2)
Is there a better way then any of these to try to accomplish what I want, or should I just bite the bullet and use some closure factory type pattern?
One way to do this is to attach the callable objects to the class as unbound methods. The method constructor will work with arbitrary callables (i.e. instances of classes with a __call__() method)—not just functions.
from types import MethodType
class Foo(object):
def __init__(self, name, val):
self.name = name
self.val = val
self.__name__ = name + '_foo'
self.name = name
def __call__(self, instance):
return self.name + str(self.val + instance.val)
class Baz(object):
def __init__(self, val):
self.val = val
Baz.biff = MethodType(Foo("biff", 42), None, Baz)
b = Baz(13)
print b.biff()
>>> biff55
In Python 3, there's no such thing as an unbound instance method (classes just have regular functions attached) so you might instead make your Foo class a descriptor that returns a bound instance method by giving it a __get__() method. (Actually, that approach will work in Python 2.x as well, but the above will perform a little better.)
from types import MethodType
class Foo(object):
def __init__(self, name, val):
self.name = name
self.val = val
self.__name__ = name + '_foo'
self.name = name
def __call__(self, instance):
return self.name + str(self.val + instance.val)
def __get__(self, instance, owner):
return MethodType(self, instance) if instance else self
# Python 2: MethodType(self, instance, owner)
class Baz(object):
def __init__(self, val):
self.val = val
Baz.biff = Foo("biff", 42)
b = Baz(13)
print b.biff()
>>> biff55
The trouble you're running into is that your object is not being bound as a method of the Baz class you're putting it in. This is because it is not a descriptor, which regular functions are!
You can fix this by adding a simple __get__ method to your Foo class that makes it into a method when it's accessed as a descriptor:
import types
class Foo(object):
# your other stuff here
def __get__(self, obj, objtype=None):
if obj is None:
return self # unbound
else:
return types.MethodType(self, obj) # bound to obj