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How to decorate a python class and override a method?

I have a class
class A:
def sample_method():
I would like to decorate class A sample_method() and override the contents of sample_method()
class DecoratedA(A):
def sample_method():
The setup above resembles inheritance, but I need to keep the preexisting instance of class A when the decorated function is used.
a # preexisting instance of class A
decorated_a = DecoratedA(a)
decorated_a.functionInClassA() #functions in Class A called as usual with preexisting instance
decorated_a.sample_method() #should call the overwritten sample_method() defined in DecoratedA
What is the proper way to go about this?

There isn't a straightforward way to do what you're asking. Generally, after an instance has been created, it's too late to mess with the methods its class defines.
There are two options you have, as far as I see it. Either you create a wrapper or proxy object for your pre-existing instance, or you modify the instance to change its behavior.
A proxy defers most behavior to the object itself, while only adding (or overriding) some limited behavior of its own:
class Proxy:
def __init__(self, obj):
self.obj = obj
def overridden_method(self): # add your own limited behavior for a few things
do_stuff()
def __getattr__(self, name): # and hand everything else off to the other object
return getattr(self.obj, name)
__getattr__ isn't perfect here, it can only work for regular methods, not special __dunder__ methods that are often looked up directly in the class itself. If you want your proxy to match all possible behavior, you probably need to add things like __add__ and __getitem__, but that might not be necessary in your specific situation (it depends on what A does).
As for changing the behavior of the existing object, one approach is to write your subclass, and then change the existing object's class to be the subclass. This is a little sketchy, since you won't have ever initialized the object as the new class, but it might work if you're only modifying method behavior.
class ModifiedA(A):
def overridden_method(self): # do the override in a normal subclass
do_stuff()
def modify_obj(obj): # then change an existing object's type in place!
obj.__class__ = ModifiedA # this is not terribly safe, but it can work
You could also consider adding an instance variable that would shadow the method you want to override, rather than modifying __class__. Writing the function could be a little tricky, since it won't get bound to the object automatically when called (that only happens for functions that are attributes of a class, not attributes of an instance), but you could probably do the binding yourself (with partial or lambda if you need to access self.

First, why not just define it from the beginning, how you want it, instead of decorating it?
Second, why not decorate the method itself?
To answer the question:
You can reassign it
class A:
def sample_method(): ...
pass
A.sample_method = DecoratedA.sample_method;
but that affects every instance.
Another solution is to reassign the method for just one object.
import functools;
a.sample_method = functools.partial(DecoratedA.sample_method, a);
Another solution is to (temporarily) change the type of an existing object.
a = A();
a.__class__ = DecoratedA;
a.sample_method();
a.__class__ = A;

python - how to get a list of inner classes?

I'm writing a small Python application that contains a few nested classes, like the example below:
class SuperBar(object):
pass
class Foo(object):
NAME = 'this is foo'
class Bar(SuperBar):
MSG = 'this is how Bar handle stuff'
class AnotherBar(SuperBar):
MSG = 'this is how Another Bar handle stuff'
I'm using nested classes to create some sort of hierarchy and to provide a clean way to implement features for a parser.
At some point, I want to create a list of the inner classes. I'd like to have the following output:
[<class '__main__.Bar'>, <class '__main__.AnotherBar'>]
The question is: What is the recommended method to get a list of inner classes in a pythonic way?

I managed to get a list of inner class objects with the method below:
import inspect
def inner_classes_list(cls):
return [cls_attribute for cls_attribute in cls.__dict__.values()
if inspect.isclass(cls_attribute)
and issubclass(cls_attribute, SuperBar)]
It works, but I'm not sure if using __dict__ directly is a good thing to do. I'm using it because it contains the actual class instances that I need and seems to be portable across Python 2 and 3.

First: I can't see how nested classes can be of any use for you. Once you have an instance f of Foo, do you realize that f.Bar and f.AnotherBar will be the same object for all instances? That is - you can't record any attribute specific from f on f.Bar, like f.Bar.speed - or it will collide with an attribute from another instance g.Bar.speed.
To overcome this, and actually, the only thing that makes sense, you'd need to have instances of Bar and AnotherBar attached to the instance f. These instances usually can't be declared on the class body - you have to create them on your Foo's __init__ method.
The only thing that Bar and AntherBar can do doing there is: (1) to have a lot of class and static methods, then they work as namespaces only.
Or, if a metaclass for SuperBar or themselves implement the descriptor protocol - https://docs.python.org/3/reference/datamodel.html#implementing-descriptors - but them, you'd be much better if superbar itself would implement the descriptor prootocol (by having either __get__ or __set__ methods), and attached to Foo's body you'd have instances of these classes, not the classes themselves.
That said, you came with the solution of using __dict__ to getting the inner classes: that won't work if Foo itself inherit from other classes that also have nested classes. The Superclasses of Foo are never searched. You can have a method to either look on all classes on Foo's __mro__, or simply use dir and issubclass :
class Foo:
#classmethod
def inner_classes_list(cls):
results = []
for attrname in dir(cls):
obj = getattr(cls, attrname)
if isinstance(obj, type) and issubclass(obj, SuperBar):
results.append(obj)
return results
(If you want this to work to all classes like Foo that does not share a common base, the same code will work if it is nto declared as a class method, of course - and also, SuperBar can be a parameter to this function, if you have more than one nested-class hierarchy.)
Now you have this, we urge you to ask other questions saying what do you want to actually do - and to read about "descriptors" - and even "properties". Really: there is very little use one can think of to nested subclasses.

Find class in which a method is defined

I want to figure out the type of the class in which a certain method is defined (in essence, the enclosing static scope of the method), from within the method itself, and without specifying it explicitly, e.g.
class SomeClass:
def do_it(self):
cls = enclosing_class() # <-- I need this.
print(cls)
class DerivedClass(SomeClass):
pass
obj = DerivedClass()
# I want this to print 'SomeClass'.
obj.do_it()
Is this possible?

If you need this in Python 3.x, please see my other answer—the closure cell __class__ is all you need.
If you need to do this in CPython 2.6-2.7, RickyA's answer is close, but it doesn't work, because it relies on the fact that this method is not overriding any other method of the same name. Try adding a Foo.do_it method in his answer, and it will print out Foo, not SomeClass
The way to solve that is to find the method whose code object is identical to the current frame's code object:
def do_it(self):
mro = inspect.getmro(self.__class__)
method_code = inspect.currentframe().f_code
method_name = method_code.co_name
for base in reversed(mro):
try:
if getattr(base, method_name).func_code is method_code:
print(base.__name__)
break
except AttributeError:
pass
(Note that the AttributeError could be raised either by base not having something named do_it, or by base having something named do_it that isn't a function, and therefore doesn't have a func_code. But we don't care which; either way, base is not the match we're looking for.)
This may work in other Python 2.6+ implementations. Python does not require frame objects to exist, and if they don't, inspect.currentframe() will return None. And I'm pretty sure it doesn't require code objects to exist either, which means func_code could be None.
Meanwhile, if you want to use this in both 2.7+ and 3.0+, change that func_code to __code__, but that will break compatibility with earlier 2.x.
If you need CPython 2.5 or earlier, you can just replace the inpsect calls with the implementation-specific CPython attributes:
def do_it(self):
mro = self.__class__.mro()
method_code = sys._getframe().f_code
method_name = method_code.co_name
for base in reversed(mro):
try:
if getattr(base, method_name).func_code is method_code:
print(base.__name__)
break
except AttributeError:
pass
Note that this use of mro() will not work on classic classes; if you really want to handle those (which you really shouldn't want to…), you'll have to write your own mro function that just walks the hierarchy old-school… or just copy it from the 2.6 inspect source.
This will only work in Python 2.x implementations that bend over backward to be CPython-compatible… but that includes at least PyPy. inspect should be more portable, but then if an implementation is going to define frame and code objects with the same attributes as CPython's so it can support all of inspect, there's not much good reason not to make them attributes and provide sys._getframe in the first place…

First, this is almost certainly a bad idea, and not the way you want to solve whatever you're trying to solve but refuse to tell us about…
That being said, there is a very easy way to do it, at least in Python 3.0+. (If you need 2.x, see my other answer.)
Notice that Python 3.x's super pretty much has to be able to do this somehow. How else could super() mean super(THISCLASS, self), where that THISCLASS is exactly what you're asking for?*
Now, there are lots of ways that super could be implemented… but PEP 3135 spells out a specification for how to implement it:
Every function will have a cell named __class__ that contains the class object that the function is defined in.
This isn't part of the Python reference docs, so some other Python 3.x implementation could do it a different way… but at least as of 3.2+, they still have to have __class__ on functions, because Creating the class object explicitly says:
This class object is the one that will be referenced by the zero-argument form of super(). __class__ is an implicit closure reference created by the compiler if any methods in a class body refer to either __class__ or super. This allows the zero argument form of super() to correctly identify the class being defined based on lexical scoping, while the class or instance that was used to make the current call is identified based on the first argument passed to the method.
(And, needless to say, this is exactly how at least CPython 3.0-3.5 and PyPy3 2.0-2.1 implement super anyway.)
In [1]: class C:
...: def f(self):
...: print(__class__)
In [2]: class D(C):
...: pass
In [3]: D().f()
<class '__main__.C'>
Of course this gets the actual class object, not the name of the class, which is apparently what you were after. But that's easy; you just need to decide whether you mean __class__.__name__ or __class__.__qualname__ (in this simple case they're identical) and print that.
* In fact, this was one of the arguments against it: that the only plausible way to do this without changing the language syntax was to add a new closure cell to every function, or to require some horrible frame hacks which may not even be doable in other implementations of Python. You can't just use compiler magic, because there's no way the compiler can tell that some arbitrary expression will evaluate to the super function at runtime…

If you can use #abarnert's method, do it.
Otherwise, you can use some hardcore introspection (for python2.7):
import inspect
from http://stackoverflow.com/a/22898743/2096752 import getMethodClass
def enclosing_class():
frame = inspect.currentframe().f_back
caller_self = frame.f_locals['self']
caller_method_name = frame.f_code.co_name
return getMethodClass(caller_self.__class__, caller_method_name)
class SomeClass:
def do_it(self):
print(enclosing_class())
class DerivedClass(SomeClass):
pass
DerivedClass().do_it() # prints 'SomeClass'
Obviously, this is likely to raise an error if:
called from a regular function / staticmethod / classmethod
the calling function has a different name for self (as aptly pointed out by #abarnert, this can be solved by using frame.f_code.co_varnames[0])

Sorry for writing yet another answer, but here's how to do what you actually want to do, rather than what you asked for:
this is about adding instrumentation to a code base to be able to generate reports of method invocation counts, for the purpose of checking certain approximate runtime invariants (e.g. "the number of times that method ClassA.x() is executed is approximately equal to the number of times that method ClassB.y() is executed in the course of a run of a complicated program).
The way to do that is to make your instrumentation function inject the information statically. After all, it has to know the class and method it's injecting code into.
I will have to instrument many classes by hand, and to prevent mistakes I want to avoid typing the class names everywhere. In essence, it's the same reason why typing super() is preferable to typing super(ClassX, self).
If your instrumentation function is "do it manually", the very first thing you want to turn it into an actual function instead of doing it manually. Since you obviously only need static injection, using a decorator, either on the class (if you want to instrument every method) or on each method (if you don't) would make this nice and readable. (Or, if you want to instrument every method of every class, you might want to define a metaclass and have your root classes use it, instead of decorating every class.)
For example, here's an easy way to instrument every method of a class:
import collections
import functools
import inspect
_calls = {}
def inject(cls):
cls._calls = collections.Counter()
_calls[cls.__name__] = cls._calls
for name, method in cls.__dict__.items():
if inspect.isfunction(method):
#functools.wraps(method)
def wrapper(*args, **kwargs):
cls._calls[name] += 1
return method(*args, **kwargs)
setattr(cls, name, wrapper)
return cls
#inject
class A(object):
def f(self):
print('A.f here')
#inject
class B(A):
def f(self):
print('B.f here')
#inject
class C(B):
pass
#inject
class D(C):
def f(self):
print('D.f here')
d = D()
d.f()
B.f(d)
print(_calls)
The output:
{'A': Counter(),
'C': Counter(),
'B': Counter({'f': 1}),
'D': Counter({'f': 1})}
Exactly what you wanted, right?

You can either do what #mgilson suggested or take another approach.
class SomeClass:
pass
class DerivedClass(SomeClass):
pass
This makes SomeClass the base class for DerivedClass.
When you normally try to get the __class__.name__ then it will refer to derived class rather than the parent.
When you call do_it(), it's really passing DerivedClass as self, which is why you are most likely getting DerivedClass being printed.
Instead, try this:
class SomeClass:
pass
class DerivedClass(SomeClass):
def do_it(self):
for base in self.__class__.__bases__:
print base.__name__
obj = DerivedClass()
obj.do_it() # Prints SomeClass
Edit:
After reading your question a few more times I think I understand what you want.
class SomeClass:
def do_it(self):
cls = self.__class__.__bases__[0].__name__
print cls
class DerivedClass(SomeClass):
pass
obj = DerivedClass()
obj.do_it() # prints SomeClass

[Edited]
A somewhat more generic solution:
import inspect
class Foo:
pass
class SomeClass(Foo):
def do_it(self):
mro = inspect.getmro(self.__class__)
method_name = inspect.currentframe().f_code.co_name
for base in reversed(mro):
if hasattr(base, method_name):
print(base.__name__)
break
class DerivedClass(SomeClass):
pass
class DerivedClass2(DerivedClass):
pass
DerivedClass().do_it()
>> 'SomeClass'
DerivedClass2().do_it()
>> 'SomeClass'
SomeClass().do_it()
>> 'SomeClass'
This fails when some other class in the stack has attribute "do_it", since this is the signal name for stop walking the mro.

Is there a method like '__getattribute__' for class (not instance) variables?

I have a class sysprops in which I'd like to have a number of constants. However, I'd like to pull the values for those constants from the database, so I'd like some sort of hook any time one of these class constants are accessed (something like the getattribute method for instance variables).
class sysprops(object):
SOME_CONSTANT = 'SOME_VALUE'
sysprops.SOME_CONSTANT # this statement would not return 'SOME_VALUE' but instead a dynamic value pulled from the database.

Although I think it is a very bad idea to do this, it is possible:
class GetAttributeMetaClass(type):
def __getattribute__(self, key):
print 'Getting attribute', key
class sysprops(object):
__metaclass__ = GetAttributeMetaClass

While the other two answers have a valid method. I like to take the route of 'least-magic'.
You can do something similar to the metaclass approach without actually using them. Simply by using a decorator.
def instancer(cls):
return cls()
#instancer
class SysProps(object):
def __getattribute__(self, key):
return key # dummy
This will create an instance of SysProps and then assign it back to the SysProps name. Effectively shadowing the actual class definition and allowing a constant instance.
Since decorators are more common in Python I find this way easier to grasp for other people that have to read your code.

sysprops.SOME_CONSTANT can be the return value of a function if SOME_CONSTANT were a property defined on type(sysprops).
In other words, what you are talking about is commonly done if sysprops were an instance instead of a class.
But here is the kicker -- classes are instances of metaclasses. So everything you know about controlling the behavior of instances through the use of classes applies equally well to controlling the behavior of classes through the use of metaclasses.
Usually the metaclass is type, but you are free to define other metaclasses by subclassing type. If you place a property SOME_CONSTANT in the metaclass, then the instance of that metaclass, e.g. sysprops will have the desired behavior when Python evaluates sysprops.SOME_CONSTANT.
class MetaSysProps(type):
#property
def SOME_CONSTANT(cls):
return 'SOME_VALUE'
class SysProps(object):
__metaclass__ = MetaSysProps
print(SysProps.SOME_CONSTANT)
yields
SOME_VALUE

How can I pickle a dynamically created nested class in python?

I have a nested class:
class WidgetType(object):
class FloatType(object):
pass
class TextType(object):
pass
.. and an object that refers the nested class type (not an instance of it) like this
class ObjectToPickle(object):
def __init__(self):
self.type = WidgetType.TextType
Trying to serialize an instance of the ObjectToPickle class results in:
PicklingError: Can't pickle <class
'setmanager.app.site.widget_data_types.TextType'>
Is there a way to pickle nested classes in python?

I know this is a very old question, but I have never explicitly seen a satisfactory solution to this question other than the obvious, and most likely correct, answer to re-structure your code.
Unfortunately, it is not always practical to do such a thing, in which case as a very last resort, it is possible to pickle instances of classes which are defined inside another class.
The python documentation for the __reduce__ function states that you can return
A callable object that will be called to create the initial version of the object. The next element of the tuple will provide arguments for this callable.
Therefore, all you need is an object which can return an instance of the appropriate class. This class must itself be picklable (hence, must live on the __main__ level), and could be as simple as:
class _NestedClassGetter(object):
"""
When called with the containing class as the first argument,
and the name of the nested class as the second argument,
returns an instance of the nested class.
"""
def __call__(self, containing_class, class_name):
nested_class = getattr(containing_class, class_name)
# return an instance of a nested_class. Some more intelligence could be
# applied for class construction if necessary.
return nested_class()
All that is left therefore, is to return the appropriate arguments in a __reduce__ method on FloatType:
class WidgetType(object):
class FloatType(object):
def __reduce__(self):
# return a class which can return this class when called with the
# appropriate tuple of arguments
return (_NestedClassGetter(), (WidgetType, self.__class__.__name__, ))
The result is a class which is nested but instances can be pickled (further work is needed to dump/load the __state__ information, but this is relatively straightforward as per the __reduce__ documentation).
This same technique (with slight code modifications) can be applied for deeply nested classes.
A fully worked example:
import pickle
class ParentClass(object):
class NestedClass(object):
def __init__(self, var1):
self.var1 = var1
def __reduce__(self):
state = self.__dict__.copy()
return (_NestedClassGetter(),
(ParentClass, self.__class__.__name__, ),
state,
)
class _NestedClassGetter(object):
"""
When called with the containing class as the first argument,
and the name of the nested class as the second argument,
returns an instance of the nested class.
"""
def __call__(self, containing_class, class_name):
nested_class = getattr(containing_class, class_name)
# make an instance of a simple object (this one will do), for which we can change the
# __class__ later on.
nested_instance = _NestedClassGetter()
# set the class of the instance, the __init__ will never be called on the class
# but the original state will be set later on by pickle.
nested_instance.__class__ = nested_class
return nested_instance
if __name__ == '__main__':
orig = ParentClass.NestedClass(var1=['hello', 'world'])
pickle.dump(orig, open('simple.pickle', 'w'))
pickled = pickle.load(open('simple.pickle', 'r'))
print type(pickled)
print pickled.var1
My final note on this is to remember what the other answers have said:
If you are in a position to do so, consider re-factoring your code to
avoid the nested classes in the first place.

The pickle module is trying to get the TextType class from the module. But since the class is nested it doesn't work. jasonjs's suggestion will work.
Here are the lines in pickle.py responsible for the error message:
try:
__import__(module)
mod = sys.modules[module]
klass = getattr(mod, name)
except (ImportError, KeyError, AttributeError):
raise PicklingError(
"Can't pickle %r: it's not found as %s.%s" %
(obj, module, name))
klass = getattr(mod, name) will not work in the nested class case of course. To demonstrate what is going on try to add these lines before pickling the instance:
import sys
setattr(sys.modules[__name__], 'TextType', WidgetType.TextType)
This code adds TextType as an attribute to the module. The pickling should work just fine. I don't advice you to use this hack though.

If you use dill instead of pickle, it works.
>>> import dill
>>>
>>> class WidgetType(object):
... class FloatType(object):
... pass
... class TextType(object):
... pass
...
>>> class ObjectToPickle(object):
... def __init__(self):
... self.type = WidgetType.TextType
...
>>> x = ObjectToPickle()
>>>
>>> _x = dill.dumps(x)
>>> x_ = dill.loads(_x)
>>> x_
<__main__.ObjectToPickle object at 0x10b20a250>
>>> x_.type
<class '__main__.TextType'>
Get dill here: https://github.com/uqfoundation/dill

In Sage (www.sagemath.org), we have many instances of this pickling issue. The way we decided to systematically solve it is to put the outer class inside a specific metaclass whose goal is to implement and hide the hack. Note that this automatically propagate through nested classes if there are several level of nesting.

Pickle only works with classes defined in module scope (top level). In this case, it looks like you could define the nested classes in module scope and then set them as properties on WidgetType, assuming there's a reason not to just reference TextType and FloatType in your code. Or, import the module they're in and use widget_type.TextType and widget_type.FloatType.

Nadia's answer is pretty complete - it is practically not something you want to be doing; are you sure you can't use inheritance in WidgetTypes instead of nested classes?
The only reason to use nested classes is to encapsulate classes working together closely, your specific example looks like an immediate inheritance candidate to me - there is no benefit in nesting WidgetType classes together; put them in a module and inherit from the base WidgetType instead.

This seems to work fine in newer versions of Python. I tried it in v3.8 and it was able to pickle and unpickle the nested class.