The snippet:
class Base:
def superclass_only(self):
return 'yes'
class Foo(Base):
pass
foo = Foo()
>>> foo.superclass_only()
yes
# Expection is to raise error
>>> foo.superclass_only()
traceback
...
AttributeError: 'Foo' object has no attribute 'superclass_only'
How can I do if I just want to define a superclass-only method?
TL;DR: prefix the method name with __ to trigger Python's name mangling mechanism.
answer:
You normally can't do that: it is not how inheritance is supposed to work.
If you need to "hide away" methods in the "subclasses", you should rething your approach.
One first thing is to use the naming convention to indicate the method is private, which in Python we do by adding a "_" prefix to the method name: that should be an indicator to users of your Foo class that the reserved method should be used only by whoever writes the code in Base and be let alone.
Another thing is to think if you would not be better with composition than with inheritance in this case: if your Base class knows to do things that Foo can't do on itself, can you really say that "Foo objects are also Base objects"? (which is what inheritance is about).
Maybe, the better design is:
class Base:
...
class Bar:
def method_foo_cant_do(...):
...
class Foo(Base):
def __init__(self, ...):
self.bar = Bar()
...
And finally, although not designed for that, and rather meant to avoid method-name clashes in complex hierarchies, Python has a "name mangling" mechanism, which will transparently change a method name to one including the class name as prefix. This will avoid casual use of the method in subclasses, and be an even stronger indicator that it should be used in "Base" along - but won't "prevent at all costs" that it be called.
The way to go is simply prefix the method with two underscores. At compilation time, Python translates the method to be f"_{class_name}__{method_name}", at the method declaration and in all references to it inside the class where it is declared. So Foo.__superclass_only will not reach Base.__superclass_only since the later has had its name mangled to Base._Base__superclass_only:
class Base:
def __superclass_only(self):
return 'yes'
class Foo(Base):
pass
And on the interactive interpreter:
In [3]: f= Foo()
In [4]: f.__superclass_only()
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-4-19c8185aa9ad> in <module>
----> 1 f.__superclass_only()
But it is still reachable by using the transformed name: f._Base__superclass_only() would work.
Another thing that Python allows is to customize the way attributes are retrieved for a given class: the somewhat search for attributes and methods in a class is performed by the __getattribute__ method in each class (do not mistake it with __getattr__ which is simpler and designed to be hit only when an attribute is not found).
Reimplementing __getattribute__ is error prone and would likely leave you worse than the way you started with, and given a foo object, one would stil be able to call the superclass_only by doing
Base.superclass_only(foo, ...) (i.e.:retrieving the method as an unbound method (function) from the Base class itself and passing in the foo instance manually to become the "self" argument), and mitigating this would require you to implement a correct __get_attribute__ on the metaclass - (and that would still be ultimately bypassable by one who could read the source code)
You can wrap the superclass-only method with a decorator function that validates the current instance's class name against the method's class name, which can be derived from the method's __qualname__ attribute:
def superclass_only(method):
def wrapper(self, *args, **kwargs):
if self.__class__.__name__ != method.__qualname__.split('.')[-2]:
raise NotImplementedError
return method(self, *args, **kwargs)
return wrapper
so that with:
class Base:
#superclass_only
def method(self):
return 'yes'
class Foo(Base):
pass
Calling Base().method() returns 'yes', while calling Foo().method() raises NotImplementedError.
Demo: https://replit.com/#blhsing/SpringgreenHonorableCharacters
Related
In Python, I can create a class method using the #classmethod decorator:
>>> class C:
... #classmethod
... def f(cls):
... print(f'f called with cls={cls}')
...
>>> C.f()
f called with cls=<class '__main__.C'>
Alternatively, I can use a normal (instance) method on a metaclass:
>>> class M(type):
... def f(cls):
... print(f'f called with cls={cls}')
...
>>> class C(metaclass=M):
... pass
...
>>> C.f()
f called with cls=<class '__main__.C'>
As shown by the output of C.f(), these two approaches provide similar functionality.
What are the differences between using #classmethod and using a normal method on a metaclass?
As classes are instances of a metaclass, it is not unexpected that an "instance method" on the metaclass will behave like a classmethod.
However, yes, there are differences - and some of them are more than semantic:
The most important difference is that a method in the metaclass is not "visible" from a class instance. That happens because the attribute lookup in Python (in a simplified way - descriptors may take precedence) search for an attribute in the instance - if it is not present in the instance, Python then looks in that instance's class, and then the search continues on the superclasses of the class, but not on the classes of the class. The Python stdlib make use of this feature in the abc.ABCMeta.register method.
That feature can be used for good, as methods related with the class themselves are free to be re-used as instance attributes without any conflict (but a method would still conflict).
Another difference, though obvious, is that a method declared in the metaclass can be available in several classes, not otherwise related - if you have different class hierarchies, not related at all in what they deal with, but want some common functionality for all classes, you'd have to come up with a mixin class, that would have to be included as base in both hierarchies (say for including all classes in an application registry). (NB. the mixin may sometimes be a better call than a metaclass)
A classmethod is a specialized "classmethod" object, while a method in the metaclass is an ordinary function.
So, it happens that the mechanism that classmethods use is the "descriptor protocol". While normal functions feature a __get__ method that will insert the self argument when they are retrieved from an instance, and leave that argument empty when retrieved from a class, a classmethod object have a different __get__, that will insert the class itself (the "owner") as the first parameter in both situations.
This makes no practical differences most of the time, but if you want access to the method as a function, for purposes of adding dynamically adding decorator to it, or any other, for a method in the metaclass meta.method retrieves the function, ready to be used, while you have to use cls.my_classmethod.__func__ to retrieve it from a classmethod (and then you have to create another classmethod object and assign it back, if you do some wrapping).
Basically, these are the 2 examples:
class M1(type):
def clsmethod1(cls):
pass
class CLS1(metaclass=M1):
pass
def runtime_wrap(cls, method_name, wrapper):
mcls = type(cls)
setattr(mcls, method_name, wrapper(getatttr(mcls, method_name)))
def wrapper(classmethod):
def new_method(cls):
print("wrapper called")
return classmethod(cls)
return new_method
runtime_wrap(cls1, "clsmethod1", wrapper)
class CLS2:
#classmethod
def classmethod2(cls):
pass
def runtime_wrap2(cls, method_name, wrapper):
setattr(cls, method_name, classmethod(
wrapper(getatttr(cls, method_name).__func__)
)
)
runtime_wrap2(cls1, "clsmethod1", wrapper)
In other words: apart from the important difference that a method defined in the metaclass is visible from the instance and a classmethod object do not, the other differences, at runtime will seem obscure and meaningless - but that happens because the language does not need to go out of its way with special rules for classmethods: Both ways of declaring a classmethod are possible, as a consequence from the language design - one, for the fact that a class is itself an object, and another, as a possibility among many, of the use of the descriptor protocol which allows one to specialize attribute access in an instance and in a class:
The classmethod builtin is defined in native code, but it could just be coded in pure python and would work in the exact same way. The 5 line class bellow can be used as a classmethod decorator with no runtime differences to the built-in #classmethod" at all (though distinguishable through introspection such as calls toisinstance, and evenrepr` of course):
class myclassmethod:
def __init__(self, func):
self.__func__ = func
def __get__(self, instance, owner):
return lambda *args, **kw: self.__func__(owner, *args, **kw)
And, beyond methods, it is interesting to keep in mind that specialized attributes such as a #property on the metaclass will work as specialized class attributes, just the same, with no surprising behavior at all.
When you phrase it like you did in the question, the #classmethod and metaclasses may look similar but they have rather different purposes. The class that is injected in the #classmethod's argument is usually used for constructing an instance (i.e. an alternative constructor). On the other hand, the metaclasses are usually used to modify the class itself (e.g. like what Django does with its models DSL).
That is not to say that you can't modify the class inside a classmethod. But then the question becomes why didn't you define the class in the way you want to modify it in the first place? If not, it might suggest a refactor to use multiple classes.
Let's expand the first example a bit.
class C:
#classmethod
def f(cls):
print(f'f called with cls={cls}')
Borrowing from the Python docs, the above will expand to something like the following:
class ClassMethod(object):
"Emulate PyClassMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, klass=None):
if klass is None:
klass = type(obj)
def newfunc(*args):
return self.f(klass, *args)
return newfunc
class C:
def f(cls):
print(f'f called with cls={cls}')
f = ClassMethod(f)
Note how __get__ can take either an instance or the class (or both), and thus you can do both C.f and C().f. This is unlike the metaclass example you give which will throw an AttributeError for C().f.
Moreover, in the metaclass example, f does not exist in C.__dict__. When looking up the attribute f with C.f, the interpreter looks at C.__dict__ and then after failing to find, looks at type(C).__dict__ (which is M.__dict__). This may matter if you want the flexibility to override f in C, although I doubt this will ever be of practical use.
In your example, the difference would be in some other classes that will have M set as their metaclass.
class M(type):
def f(cls):
pass
class C(metaclass=M):
pass
class C2(metaclass=M):
pass
C.f()
C2.f()
class M(type):
pass
class C(metaclass=M):
#classmethod
def f(cls):
pass
class C2(metaclass=M):
pass
C.f()
# C2 does not have 'f'
Here is more on metaclasses
What are some (concrete) use-cases for metaclasses?
Both #classmethod and Metaclass are different.
Everything in python is an object. Every thing means every thing.
What is Metaclass ?
As said every thing is an object. Classes are also objects in fact classes are instances of other mysterious objects formally called as meta-classes. Default metaclass in python is "type" if not specified
By default all classes defined are instances of type.
Classes are instances of Meta-Classes
Few important points are to understand metioned behaviour
As classes are instances of meta classes.
Like every instantiated object, like objects(instances) get their attributes from class. Class will get it's attributes from Meta-Class
Consider Following Code
class Meta(type):
def foo(self):
print(f'foo is called self={self}')
print('{} is instance of {}: {}'.format(self, Meta, isinstance(self, Meta)))
class C(metaclass=Meta):
pass
C.foo()
Where,
class C is instance of class Meta
"class C" is class object which is instance of "class Meta"
Like any other object(instance) "class C" has access it's attributes/methods defined in it's class "class Meta"
So, decoding "C.foo()" . "C" is instance of "Meta" and "foo" is method calling through instance of "Meta" which is "C".
First argument of method "foo" is reference to instance not class unlike "classmethod"
We can verify as if "class C" is instance of "Class Meta
isinstance(C, Meta)
What is classmethod?
Python methods are said to be bound. As python imposes the restriction that method has to be invoked with instance only.
Sometimes we might want to invoke methods directly through class without any instance (much like static members in java) with out having to create any instance.By default instance is required to call method. As a workaround python provides built-in function classmethod to bind given method to class instead of instance.
As class methods are bound to class. It takes at least one argument which is reference to class itself instead of instance (self)
if built-in function/decorator classmethod is used. First argument
will be reference to class instead of instance
class ClassMethodDemo:
#classmethod
def foo(cls):
print(f'cls is ClassMethodDemo: {cls is ClassMethodDemo}')
As we have used "classmethod" we call method "foo" without creating any instance as follows
ClassMethodDemo.foo()
Above method call will return True. Since first argument cls is indeed reference to "ClassMethodDemo"
Summary:
Classmethod's receive first argument which is "a reference to class(traditionally referred as cls) itself"
Methods of meta-classes are not classmethods. Methods of Meta-classes receive first argument which is "a reference to instance(traditionally referred as self) not class"
Recent I study Python,but I have a question about __slots__. In my opinion, it is for limiting parameters in Class, but also limiting the method in Class?
For example:
from types import MethodType
Class Student(object):
__slots__=('name','age')
When I run the code:
def set_age(self,age):
self.age=age
stu=Student()
stu.set_age=MethodType(set_age,stu,Student)
print stu.age
An error has occurred:
stu.set_age=MethodType(set_age,stu,Student)
AttributeError: 'Student' object has no attribute 'set_age'
I want to know, why not use set_age for this class?
Using __slots__ means you don't get a __dict__ with each class instance, and so each instance is more lightweight. The downside is that you cannot modify the methods and cannot add attributes. And you cannot do what you attempted to do, which is to add methods (which would be adding attributes).
Also, the pythonic approach is not to instantiate a MethodType, but to simply create the function in the class namespace. If you're attempting to add or modify the function on the fly, as in monkey-patching, then you simply assign the function to the class, as in:
Student.set_age = set_age
Assigning it to the instance, of course, you can't do if it uses __slots__.
Here's the __slots__ docs:
https://docs.python.org/2/reference/datamodel.html#slots
In new style classes, methods are not instance attributes. Instead, they're class attributes that follow the descriptor protocol by defining a __get__ method. The method call obj.some_method(arg) is equivalent to obj.__class__.method.__get__(obj)(arg), which is in turn, equivalent to obj.__class__.method(obj, arg). The __get__ implementation does the instance binding (sticking obj in as the first argument to method when it is called).
In your example code, you're instead trying to put a hand-bound method as an instance variable of the already-existing instance. This doesn't work because your __slots__ declaration prevents you from adding new instance attributes. However, if you wrote to the class instead, you'd have no problem:
class Foo(object):
__slots__ = () # no instance variables!
def some_method(self, arg):
print(arg)
Foo.some_method = some_method # this works!
f = Foo()
f.some_method() # so does this
This code would also work if you created the instance before adding the method to its class.
Your attribute indeed doesn't have an attribute set_age since you didn't create a slot for it. What did you expect?
Also, it should be __slots__ not __slots (I imagine this is right in your actual code, otherwise you wouldn't be getting the error you're getting).
Why aren't you just using:
class Student(object):
__slots__ = ('name','age')
def set_age(self,age):
self.age = age
where set_age is a method of the Student class rather than adding the function as a method to an instance of the Student class.
Instead of __slots__, I'm using the following method. It allow the use of only a predefined set of parameters:
class A(object):
def __init__(self):
self.__dict__['a']=''
self.__dict__['b']=''
def __getattr__(self,name):
d=getattr(self,'__dict__')
if d.keys().__contains__(name):
return d.__dict__[attr]
else:
raise AttributeError
def __setattr__(self,name,value):
d=getattr(self,'__dict__')
if d.keys().__contains__(name):
d[name] = value
else:
raise AttributeError
The use of getattr(..) is to avoid recursion.
There are some merits usin __slots__ vs __dict__ in term of memory and perhaps speed but this is easy to implement and read.
When you decorate a method, it is not bound yet to the class, and therefor doesn't have the im_class attribute yet. I looking for a way to get the information about the class inside the decorator. I tried this:
import types
def decorator(method):
def set_signal(self, name, value):
print name
if name == 'im_class':
print "I got the class"
method.__setattr__ = types.MethodType(set_signal, method)
return method
class Test(object):
#decorator
def bar(self, foo):
print foo
But it doesn't print anything.
I can imagine doing this:
class Test(object):
#decorator(klass=Test)
def bar(self, foo):
print foo
But if I can avoid it, it would make my day.
__setattr__ is only called on explicit object.attribute = assignments; building a class does not use attribute assignment but builds a dictionary (Test.__dict__) instead.
To access the class you have a few different options though:
Use a class decorator instead; it'll be passed the completed class after building it, you could decorate individual methods on that class by replacing them (decorated) in the class. You could use a combination of a function decorator and a class decorator to mark which methods are to be decorated:
def methoddecoratormarker(func):
func._decorate_me = True
return func
def realmethoddecorator(func):
# do something with func.
# Note: it is still an unbound function here, not a method!
return func
def classdecorator(klass):
for name, item in klass.__dict__.iteritems():
if getattr(item, '_decorate_me', False):
klass.__dict__[name] = realmethoddecorator(item)
You could use a metaclass instead of a class decorator to achieve the same, of course.
Cheat, and use sys._getframe() to retrieve the class from the calling frame:
import sys
def methoddecorator(func):
callingframe = sys._getframe(1)
classname = callingframe.f_code.co_name
Note that all you can retrieve is the name of the class; the class itself is still being built at this time. You can add items to callingframe.f_locals (a mapping) and they'll be made part of the new class object.
Access self whenever the method is called. self is a reference to the instance after all, and self.__class__ is going to be, at the very least, a sub-class of the original class the function was defined in.
My strict answer would be: It's not possible, because the class does not yet exist when the decorator is executed.
The longer answer would depend on your very exact requirements. As I wrote, you cannot access the class if it does not yet exists. One solution would be, to mark the decorated method to be "transformed" later. Then use a metaclass or class decorator to apply your modifications after the class has been created.
Another option involves some magic. Look for the implementation of the implements method in zope.interfaces. It has some access to the information about the class which is just been parsed. Don't know if it will be enough for your use case.
You might want to take a look at descriptors. They let you implement a __get__ that is used when an attribute is accessed, and can return different things depending on the object and its type.
Use method decorators to add some marker attributes to the interesting methods, and use a metaclass which iterates over the methods, finds the marker attributes, and does the logic. The metaclass code is run when the class is created, so it has a reference to the newly created class.
class MyMeta(object):
def __new__(...):
...
cls = ...
... iterate over dir(cls), find methods having .is_decorated, act on them
return cls
def decorator(f):
f.is_decorated = True
return f
class MyBase(object):
__metaclass__ = MyMeta
class MyClass(MyBase):
#decorator
def bar(self, foo):
print foo
If you worry about that the programmer of MyClass forgets to use MyBase, you can forcibly set the metaclass in decorator, by exampining the globals dicitionary of the caller stack frame (sys._getframe()).
While integrating a Django app I have not used before, I found two different ways to define functions inside the class. The author seems to use them both distinctively and intentionally. The first one is the one that I myself use a lot:
class Dummy(object):
def some_function(self, *args, **kwargs):
# do something here
# self is the class instance
The other one is the one I never use, mostly because I do not understand when and what to use it for:
class Dummy(object):
#classmethod
def some_function(cls, *args, **kwargs):
# do something here
# cls refers to what?
The classmethod decorator in the python documentation says:
A class method receives the class as the implicit first argument, just
like an instance method receives the instance.
So I guess cls refers to Dummy itself (the class, not the instance). I do not exactly understand why this exists, because I could always do this:
type(self).do_something_with_the_class
Is this just for the sake of clarity, or did I miss the most important part: spooky and fascinating things that couldn't be done without it?
Your guess is correct - you understand how classmethods work.
The why is that these methods can be called both on an instance OR on the class (in both cases, the class object will be passed as the first argument):
class Dummy(object):
#classmethod
def some_function(cls,*args,**kwargs):
print cls
#both of these will have exactly the same effect
Dummy.some_function()
Dummy().some_function()
On the use of these on instances: There are at least two main uses for calling a classmethod on an instance:
self.some_function() will call the version of some_function on the actual type of self, rather than the class in which that call happens to appear (and won't need attention if the class is renamed); and
In cases where some_function is necessary to implement some protocol, but is useful to call on the class object alone.
The difference with staticmethod: There is another way of defining methods that don't access instance data, called staticmethod. That creates a method which does not receive an implicit first argument at all; accordingly it won't be passed any information about the instance or class on which it was called.
In [6]: class Foo(object): some_static = staticmethod(lambda x: x+1)
In [7]: Foo.some_static(1)
Out[7]: 2
In [8]: Foo().some_static(1)
Out[8]: 2
In [9]: class Bar(Foo): some_static = staticmethod(lambda x: x*2)
In [10]: Bar.some_static(1)
Out[10]: 2
In [11]: Bar().some_static(1)
Out[11]: 2
The main use I've found for it is to adapt an existing function (which doesn't expect to receive a self) to be a method on a class (or object).
One of the most common uses of classmethod in Python is factories, which are one of the most efficient methods to build an object. Because classmethods, like staticmethods, do not need the construction of a class instance. (But then if we use staticmethod, we would have to hardcode the instance class name in the function)
This blog does a great job of explaining it:
https://iscinumpy.gitlab.io/post/factory-classmethods-in-python/
If you add decorator #classmethod, That means you are going to make that method as static method of java or C++. ( static method is a general term I guess ;) )
Python also has #staticmethod. and difference between classmethod and staticmethod is whether you can
access to class or static variable using argument or classname itself.
class TestMethod(object):
cls_var = 1
#classmethod
def class_method(cls):
cls.cls_var += 1
print cls.cls_var
#staticmethod
def static_method():
TestMethod.cls_var += 1
print TestMethod.cls_var
#call each method from class itself.
TestMethod.class_method()
TestMethod.static_method()
#construct instances
testMethodInst1 = TestMethod()
testMethodInst2 = TestMethod()
#call each method from instances
testMethodInst1.class_method()
testMethodInst2.static_method()
all those classes increase cls.cls_var by 1 and print it.
And every classes using same name on same scope or instances constructed with these class is going to share those methods.
There's only one TestMethod.cls_var
and also there's only one TestMethod.class_method() , TestMethod.static_method()
And important question. why these method would be needed.
classmethod or staticmethod is useful when you make that class as a factory
or when you have to initialize your class only once. like open file once, and using feed method to read the file line by line.
Look at this code:
class MyClass():
# Why does this give me "NameError: name 'self' is not defined":
mySelf = self
# But this does not?
def myFunction(self):
mySelf2 = self
Basically I want a way for a class to refer to itself without needing to name itself specifically, hence I want self to work for the class, not just methods/functions. How can I achieve this?
EDIT: The point of this is that I'm trying to refer to the class name from inside the class itself with something like self.class._name_ so that the class name isn't hardcoded anywhere in the class's code, and thus it's easier to re-use the code.
EDIT 2: From what I've learned from the answers below, what I'm trying to do is impossible. I'll have to find a different way. Mission abandoned.
EDIT 3: Here is specifically what I'm trying to do:
class simpleObject(object):
def __init__(self, request):
self.request = request
#view_defaults(renderer='string')
class Test(simpleObject):
# this line throws an error because of self
myClassName = self.__class__.__name__
#view_config(route_name=myClassName)
def activateTheView(self):
db = self.request.db
foo = 'bar'
return foo
Note that self is not defined at the time when you want the class to refer to itself for the assignment to work. This is because (in addition to being named arbitrarily), self refers to instances and not classes. At the time that the suspect line of code attempts to run, there is as of yet no class for it to refer to. Not that it would refer to the class if there was.
In a method, you can always use type(self). That will get the subclass of MyClass that created the current instance. If you want to hard-code to MyClass, that name will be available in the global scope of the methods. This will allow you to do everything that your example would allow if it actually worked. E.g, you can just do MyClass.some_attribute inside your methods.
You probably want to modify the class attributes after class creation. This can be done with decorators or on an ad-hoc basis. Metaclasses may be a better fit. Without knowing what you actually want to do though, it's impossible to say.
UPDATE:
Here's some code to do what you want. It uses a metaclass AutoViewConfigMeta and a new decorator to mark the methods that you want view_config applied to. I spoofed the view_config decorator. It prints out the class name when it's called though to prove that it has access to it. The metaclass __new__ just loops through the class dictionary and looks for methods that were marked by the auto_view_config decorator. It cleans off the mark and applies the view_config decorator with the appropriate class name.
Here's the code.
# This just spoofs the view_config decorator.
def view_config(route=''):
def dec(f):
def wrapper(*args, **kwargs):
print "route={0}".format(route)
return f(*args, **kwargs)
return wrapper
return dec
# Apply this decorator to methods for which you want to call view_config with
# the class name. It will tag them. The metaclass will apply view_config once it
# has the class name.
def auto_view_config(f):
f.auto_view_config = True
return f
class AutoViewConfigMeta(type):
def __new__(mcls, name, bases, dict_):
#This is called during class creation. _dict is the namespace of the class and
# name is it's name. So the idea is to pull out the methods that need
# view_config applied to them and manually apply them with the class name.
# We'll recognize them because they will have the auto_view_config attribute
# set on them by the `auto_view_config` decorator. Then use type to create
# the class and return it.
for item in dict_:
if hasattr(dict_[item], 'auto_view_config'):
method = dict_[item]
del method.auto_view_config # Clean up after ourselves.
# The next line is the manual form of applying a decorator.
dict_[item] = view_config(route=name)(method)
# Call out to type to actually create the class with the modified dict.
return type.__new__(mcls, name, bases, dict_)
class simpleObject(object):
__metaclass__ = AutoViewConfigMeta
class Test(simpleObject):
#auto_view_config
def activateTheView(self):
foo = 'bar'
print foo
if __name__=='__main__':
t = Test()
t.activateTheView()
Let me know if you have any questions.
Python has an "explict is better than implicit" design philosophy.
Many languages have an implicit pointer or variable in the scope of a method that (e.g. this in C++) that refers to the object through which the method was invoked. Python does not have this. Here, all bound methods will have an extra first argument that is the object through which the method was invoked. You can call it anything you want (self is not a keyword like this in C++). The name self is convention rather than a syntactic rule.
Your method myFunction defines the variable self as a parameter so it works. There's no such variable at the class level so it's erroring out.
So much for the explanation. I'm not aware of a straightforward way for you to do what you want and I've never seen such requirement in Python. Can you detail why you want to do such a thing? Perhaps there's an assumption that you're making which can be handled in another way using Python.
self is just a name, your self in this case is a class variable and not this for the object using which it is called,
self is treated as a normal variable and it is not defined, where as the self in the function comes from the object used for calling.
you want to treat the object reference in self as a class variable which is not possible.
self isn't a keyword, it's just a convention. The methods are attributes of the class object (not the instance), but they receive the instance as their first argument. You could rename the argument to xyzzy if you wanted and it would still work the same way.
But (as should be obvious) you can't refer to a method argument outside the body of the method. Inside a class block but outside of any method, self is undefined. And the concept wouldn't even make sense -- at the time the class block is being evaluated, no instance of the class can possibly exist yet.
Because the name self is explicitly defined as part of the arguments to myFunction. The first argument to a method is the instance that the method was called on; in the class body, there isn't an "instance we're dealing with", because the class body deals with every possible instance of the class (including ones that don't necessarily exist yet) - so, there isn't a particular object that could be called self.
If you want to refer to the class itself, rather than some instance of it, this is spelled self.__class__ (or, for new-style classes in Py2 and all classes in Py3, type(self)) anywhere self exists. If you want to be able to deal with this in situations where self doesn't exist, then you may want to look at class methods which aren't associated with any particular instance, and so take the class itself in place of self. If you really need to do this in the class body (and, you probably don't), you'll just have to call it by name.
You can't refer to the class itself within the class body because the class doesn't exist at the time that the class body is executed. (If the previous sentence is confusing, reading up about metaclasses will either clear this up or make you more confused.)
Within an instance method, you can refer to the class of the instance with self.__class__, but be careful here. This will be the instance's actual class, which through the power of inheritance might not be the class in which the method was defined.
Within a class method, the class is passed in as the first argument, much like instances are the first argument to instance methods:
class MyClass(object):
#classmethod
def foo(cls):
print cls.__name__
MyClass.foo() # Should print "MyClass"
As with instance methods, the actual class might differ due to inheritance.
class OtherClass(MyClass):
pass
OtherClass.foo() # Should print "OtherClass"
If you really need to refer to MyClass within a method of MyClass, you're pretty much going to have to refer to it as MyClass unless you use magic. This sort of magic is more trouble than it is worth.