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super() in a decorated subclass in Python 2

I'm trying to use super in a subclass which is wrapped in another class using a class decorator:
def class_decorator(cls):
class WrapperClass(object):
def make_instance(self):
return cls()
return WrapperClass
class MyClass(object):
def say(self, x):
print(x)
#class_decorator
class MySubclass(MyClass):
def say(self, x):
super(MySubclass, self).say(x.upper())
However, the call to super fails:
>>> MySubclass().make_instance().say('hello')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<stdin>", line 4, in say
TypeError: super(type, obj): obj must be an instance or subtype of type
The problem is that, when say is called, MySubclass doesn't refer to the original class anymore, but to the return value of the decorator.
One possible solution would be to store the value of MySubclass before decorating it:
class MySubclass(MyClass):
def say(self, x):
super(_MySubclass, self).say(x.upper())
_MySubclass = MySubclass
MySubclass = class_decorator(MySubclass)
This works, but isn't intuitive and would need to be repeated for each decorated subclass. I'm looking for a way that doesn't need additional boilerplate for each decorated subclass -- adding more code in one place (say, the decorator) would be OK.
Update: In Python 3 this isn't a problem, since you can use __class__ (or the super variant without arguments), so the following works:
#class_decorator
class MySubclass(MyClass):
def say(self, x):
super().say(x.upper())
Unfortunately, I'm stuck with Python 2.7 for this project.

The problem is that your decorator returns a different class than python (or anyone who uses your code) expects. super not working is just one of the many unfortunate consequences:
>>> isinstance(MySubclass().make_instance(), MySubclass)
False
>>> issubclass(MySubclass, MyClass)
False
>>> pickle.dumps(MySubclass().make_instance())
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
_pickle.PicklingError: Can't pickle <class '__main__.MySubclass'>: it's not the same object as __main__.MySubclass
This is why a class decorator should modify the class instead of returning a different one. The correct implementation would look like this:
def class_decorator(wrapped_cls):
#classmethod
def make_instance(cls):
return cls()
wrapped_cls.make_instance = make_instance
return wrapped_cls
Now super and everything else will work as expected:
>>> MySubclass().make_instance().say('hello')
HELLO

The problem occurs because at the time when MySubclass.say() is called, the global symbol MySubclass no longer refers to what's defined in your code as 'class MySubclass'. It is an instance of WrapperClass, which isn't in any way related to MySubclass.
If you are using Python3, you can get around this by NOT passing any arguments to 'super', like this:
super().say(x.upper())
I don't really know why you use the specific construct that you have, but it does look strange that a sub-class of MyClass that defines 'say()' - and has itself a 'say()' method in the source code would have to end up as something that does not have that method - which is the case in your code.
Note you could change the class WrapperClass line to make it read
class WrapperClass(cls):
this will make your wrapper a sub-class of the one you just decorated. This doesn't help with your super(SubClass, self) call - you still need to remove the args (which is OK only on Python3), but at least an instance created as x=MySubclass() would have a 'say' method, as one would expect at first glance.
EDIT: I've come up with a way around this, but it really looks odd and has the disadvantage of making the 'wrapped' class know that it is being wrapped (and it becomes reliant on that, making it unusable if you remove the decorator):
def class_decorator(cls):
class WrapperClass(object):
def make_instance(self):
i = cls()
i._wrapped = cls
return i
return WrapperClass
class MyClass(object):
def say(self, x):
print(x)
#class_decorator
class MySubclass(MyClass):
def say(self, x):
super(self._wrapped, self).say(x.upper())
# make_instance returns inst of the original class, non-decorated i = MySubclass().make_instance() i.say('hello')
In essence, _wrapped saves a class reference as it was at declaration time, consistent with using the regular super(this_class_name, self) builtin call.

How to use a variable that inside of a function of a class in another class - Python

I am trying to access to another variable that inside a function and also that is from another class, so I coded it in that way
class Helloworld:
def printHello(self):
self.hello = 'Hello World'
print (self.hello)
class Helloworld2(Helloworld):
def printHello2(self)
print(self.hello)
b = Helloworld2()
b.printHello2()
a = Helloworld()
a.printHello()
However, this gives me that error: AttributeError: 'Helloworld2' object has no attribute 'hello'. So, what would be the simplest way to access to that variable?

That's because you never call printHello(self) that declare your self.hello.
To make it work you need to do:
class Helloworld2(Helloworld):
def printHello2(self):
super().printHello()
print(self.hello)
Or move declaration of you self.hello to __init__() which would be more preferred way.

You should initialise the instance of the class via the __init__() function, this means that when it is created, these values are set.
That would make your code look like:
class Helloworld:
def __init__(self):
#sets self.hello on creation of object
self.hello = 'Hello World'
def printHello(self):
print (self.hello)
class Helloworld2(Helloworld):
def printHello2(self):
print(self.hello)
b = Helloworld2()
b.printHello2()
a = Helloworld()
a.printHello()
An alternative, with your current code is to just call printHello(), either at the top level, with b.printHello(), or within printHello2. Note that in this case, you don't actually need to use super().printHello() as you are not re-defining that function in Helloworld2, though it would be required if you did.

Override a function' sub-function from a decorator?

Let's consider this piece of code where I would like to create bar dynamically with a decorator
def foo():
def bar():
print "I am bar from foo"
print bar()
def baz():
def bar():
print "I am bar from baz"
print bar()
I thought I could create bar from the outside with a decorator:
def bar2():
print "I am super bar from foo"
setattr(foo, 'bar', bar2)
But the result is not what I was expecting (I would like to get I am super bar from foo:
>>> foo()
I am bar from foo
Is it possible to override a sub-function on an existing function with a decorator?
The actual use case
I am writing a wrapper for a library and to avoid boilerplate code I would like to simplify my work.
Each library function has a prefix lib_ and returns an error code. I would like to add the prefix to the current function and treat the error code. This could be as simple as this:
def call():
fname = __libprefix__ + inspect.stack()[1][3]
return_code = getattr(__lib__, fname)(*args)
if return_code < 0: raise LibError(fname, return_code)
def foo():
call()
The problem is that call might act differently in certain cases. Some library functions do not return an error_code so it would be easier to write it like
this:
def foo():
call(check_status=True)
Or much better in my opinion (this is the point where I started thinking about decorators):
#LibFunc(check_status=True)
def foo():
call()
In this last example I should declare call inside foo as a sub-function created dynamically by the decorator itself.
The idea was to use something like this:
class LibFunc(object):
def __init__(self,**kwargs):
self.kwargs = kwargs
def __call__(self, original_func):
decorator_self = self
def wrappee( *args, **kwargs):
def call(*args):
fname = __libprefix__ + original_func.__name__
return_code = getattr(__lib__, fname)(*args)
if return_code < 0: raise LibError(fname, return_code)
print original_func
print call
# <<<< The part that does not work
setattr(original_func, 'call', call)
# <<<<
original_func(*args,**kwargs)
return wrappee
Initially I was tempted to call the call inside the decorator itself to minimize the writing:
#LibFunc():
foo(): pass
Unfortunately, this is not an option since other things should sometime be done before and after the call:
#LibFunc():
foo(a,b):
value = c_float()
call(a, pointer(value), b)
return value.value
Another option that I thought about was to use SWIG, but again this is not an option because I will need to rebuild the existing library with the SWIG wrapping functions.
And last but not least, I may get inspiration from SWIG typemaps and declare my wrapper as this:
#LibFunc(check_exit = true, map = ('<a', '>c_float', '<c_int(b)')):
foo(a,b): pass
This looks like the best solution to me, but this is another topic and another question...

Are you married to the idea of a decorator? Because if your goal is bunch of module-level functions each of which wraps somelib.lib_somefunctionname, I don't see why you need one.
Those module-level names don't have to be functions, they just have to be callable. They could be a bunch of class instances, as long as they have a __call__ method.
I used two different subclasses to determine how to treat the return value:
#!/usr/bin/env python3
import libtowrap # Replace with the real library name.
class Wrapper(object):
'''
Parent class for all wrapped functions in libtowrap.
'''
def __init__(self, name):
self.__name__ = str(name)
self.wrapped_name = 'lib_' + self.__name__
self.wrapped_func = getattr(libtowrap, self.wrapped_name)
self.__doc__ = self.wrapped_func.__doc__
return
class CheckedWrapper(Wrapper):
'''
Wraps functions in libtowrap that return an error code that must
be checked. Negative return values indicate an error, and will
raise a LibError. Successful calls return None.
'''
def __call__(self, *args, **kwargs):
error_code = self.wrapped_func(*args, **kwargs)
if error_code < 0:
raise LibError(self.__name__, error_code)
return
class UncheckedWrapper(Wrapper):
'''
Wraps functions in libtowrap that return a useful value, as
opposed to an error code.
'''
def __call__(self, *args, **kwargs):
return self.wrapped_func(*args, **kwargs)
strict = CheckedWrapper('strict')
negative_means_failure = CheckedWrapper('negative_means_failure')
whatever = UncheckedWrapper('whatever')
negative_is_ok = UncheckedWrapper('negative_is_ok')
Note that the wrapper "functions" are assigned while the module is being imported. They are in the top-level module namespace, and not hidden by any if __name__ == '__main__' test.
They will behave like functions for most purposes, but there will be minor differences. For example, I gave each instance a __name__ that matches the name they're assigned to, not the lib_-prefixed name used in libtowrap... but I copied the original __doc__, which might refer to a prefixed name like lib_some_other_function. Also, testing them with isinstance will probably surprise people.
For more about decorators, and for many more annoying little discrepancies like the ones I mentioned above, see Graham Dumpleton's half-hour lecture "Advanced Methods for Creating Decorators" (PyCon US 2014; slides). He is the author of the wrapt module (Python Package Index; Git Hub; Read the Docs), which corrects all(?) of the usual decorator inconsistencies. It might solve your problem entirely (except for the old lib_-style names showing up in __doc__).

Dictionary of functions for all function in class

I'm relatively new to python and I have a class that has a bunch of different function. I read in the user input and depending on the user input I call a different function. Instead of having a bunch of if else statements I thought it would be better to have a dictionary of functions so currently my class looks like this:
class Foo:
def func1(self):
#do something
def func2(self, arg1):
#do something else
def func3(self, arg1, arg2):
#do something
def func4(self, arg1):
#do something
def __init__(self):
self.functions = {"FUNC2": func2, "FUNC4":func4}
def run_loop(self):
while 1:
user_input = raw_input()
cmd = user_input.split(' ')[0]
if cmd in self.functions:
self.functions[cmd].__get__(self, type(self))()
else:
#call other functions
I'm calling this in a main.py like so:
c = Class()
c.run_loop()
My issue is that I'm getting the following error NameError: global name 'func2' is not defined`. I'm not really sure why this is happening. I get the error in the constructor. Any ideas?

You need to specify that the function is within the class by adding self before it.
def __init__(self):
self.functions = {"FUNC2": self.func2, "FUNC4":self.func4}

You need to use self to access class functions from other function in same class. The corrected code will be
self.functions = {"FUNC2": self.func2, "FUNC4":self.func4}

The function is not identified within the class. Function "func2" & "func4" are part of the class and can be referred using the self...

How to make sure a class function wont be called until another class function has been called first?

I have a class object that creates some data fields:
class DataFields(object):
_fields_ = ['field_1', 'field_2', 'data_length']
def __init__(self, data=None):
if data != None:
self.create_fields(data)
def create_fields(self, data):
i = 0
for field in self._fields_:
setattr(self, field, data[i])
i += 1
def get_datalength(self):
return self.data_length
What is the best way to make sure that the get_datalength() function cannot be called unless the data_length field has been created (that is, unless the create_fields() function has been called once).
I've thought about either using a variable that gets initialized in the create_fields and is checked in get_datalength() or try-except inside the get_datalength() function. What is the most Pythonic (or the best) way?

I think the most pythonic way would be to throw an exception:
def get_datalength(self):
try:
return self.data_length
except AttributeError:
raise AttributeError("No length call create_fields first")
Simple reason: There is no way to prevent the user to call this function on the object. Either the user would get a AttributeError and would not understand what is going on, or you provide an own Error class or at least error message.
BTW:
It is not pythonic creating getter methods(there are no such things as 'private members')
If you need to do smaller operation on the value returning it have a look at the #property decorator
#property
def datalength(self):
return do_some_stuff(self.data_length)

By using getattr with default value, you can return None or any value if there is no data_length attribute yet in instance:
def get_datalength(self):
return getattr(self, 'data_length', None)

Using an exception is probably the best way for what you are doing however there are alternatives that may be useful if you will be using this object from an interactive console:
def fn2(self):
print("this is fn2")
class test:
def fn1(self):
print("this is fn1")
self.fn2 = fn2
def fn2(self): # omit this if you want fn2 to only exist after fn1 is called
print("Please call fn1 first")
I wouldn't recommend this for every-day use but it can be useful in some cases. If you omit defining fn2 within the class, then the method fn2 will only be present after fn1 is called. For easier code maintenance you can do the same thing like this:
class test:
def fn1(self):
print("this is fn1")
self.fn2 = self._fn2
def _fn2(self):
print("this is fn2")
def fn2(self): # omit this if you want fn2 to only exist after fn1 is called
print("Please call fn1 first")
If this is to be used inside a module that will be imported then you should either raise an exception or return a valid value like the other answers have suggested.

This can be solved by having a dictionary, as a class variable, with method names as keys.
called['method1']
called['method2']
called['method3']
...
And setting the key in that method call
class SomeClass(obj):
def method1():
called['method1'] = 1
def method2():
if method1 in called:
# continue