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How to check if method exist from within a Python object

Context and intentions: I want to use an object m_o of type My_object as a way of interfacing with another object called s_o of type Stubborn_object. For the sake of easy understanding, they should behave like if My_object inherited from Stubborn_object, in the way that calling an attribute that doesn't exist in My_object should call the attribute in Stubborn_object.
However, the tricky thing is that I wouldn't be asking this question if I could simply inherit My_object from Stubborn_object. It appears that I can't inherit from it, and, for many reasons, I also can't modify the code of the Stubborn_object class, so I have to use it as it is. Please note that trying to inherit isn't the issue of the question here. I know that other solutions exist for my practical problem, but I really want answers to stay on topic for many reasons. I suspect that other users can have different problems than mine and still be unable to inherit a class. Furthermore, not being able to inherit a class is not the only reason that could make someone read this question. In fact, it's quite a general Python object-oriented problem. I also believe the solution of my problem could be useful in other applications, like custom error handling within the object itself when an attribute is not found, or in thread management to lock the instance as soon as an attribute is called.
In addition to the problem of inheritance, let's suppose that I can't use conditions at higher levels to handle these cases, so everything has to be done inside My_object instance or its parents. That means that I can't use hasattr(m_o, attribute_name) to determine if I should call getattr(m_o, attribute_name) or getattr(s_o, attribute_name). This also means that any try/except blocks and other preconditions must be inside the My_object class or its parents. The point of this question is not about detecting exceptions when calling an attribute from outside the My_object instance. A try/catch block normally has to be outside the My_object class, and I previously stated that this can't be allowed.
For the sake of clarity and to provide a complete verifiable example, here is a sample code of the Stubborn_object class. I know that I said I can't inherit from Stubborn_object and the following code includes an inheritable class. Providing an example of an non-inheritable object would only bring confusion and it would'nt be really helpful to the question anyway, so here is a simple example of an inheritable object. The objective of this is to make an easy to understand question, so please just consider that you can't inherit from it:
class Stubborn_object:
def do_something(self):
print("do_something")
def action_to_override():
print("action_to_override")
def action_a(self):
print("action_a")
def action_b(self):
print("action_b")
Objective: Put it simply, I want my class My_object to detect all by itself that a lacking attribute has been called and run some instructions instead of throwing an AttributeError.
Current attempts: Right now, I manually redirect method calls to the Stubborn_object instance like so (it's successful, but not reliable nor scalable because of the use of hardcoding):
class My_object():
def __init__(self, s_o):
self.stubborn_object = s_o
def action_to_override(self):
# Do stuff. This method "overrides" the Stubborn_object.action_to_override method.
print("Here is stuff getting done instead of action_to_override")
def action_a(self):
return self.stubborn_object.action_a()
def action_b(self):
return self.stubborn_object.action_b()
s_o = Stubborn_object()
m_o = My_object(s_o)
m_o.action_to_override() # Executes Stubborn_object.do_something()
m_o.action_a() # Executes Stubborn_object.action_a()
m_o.action_b() # Executes Stubborn_object.action_b()
Executing this code along with the provided Stubborn_object code sample should print:
Here is stuff getting done instead of action_to_override
action_a
action_b
As you can see from methods action_a and action_b, I have to manually call the Stubborn_object methods from whithin the methods in My_object to mimic the attributes of Stubborn_object. This is ineficient, lacks of robustness and will throw an AttributeError exception if we attempt to make an action that wasn't included in the My_object code.
What if I wanted to automatically send method and attribute calls to the Stubborn_object instance without having to rewrite all of its method and attributes in My_object? I believe this can be achieved with detecting if a lacking attribute of My_object instance is called.
Expectations (or sort of): I am open to any solution that allows the My_object class or its parents to determine if the attribute is lacking or not, all within itself. So I believe I am ready to hear extremely original ideas, so go ahead.
On my part, I believe that something that uses parts of this code is the way to go, but it still lacks the "catch any called attribute" part:
class My_object():
def __init__(self, s_o):
# __init__ stays as it was.
self.stubborn_object = s_o
def action_to_override(self):
# This method also stays as it was.
# Do stuff. This method "overrides" the stubborn_object.action_to_override method.
print("Here is stuff getting done instead of action_to_override")
def run_me_when_method_is_not_found(self, method_name, **kwargs):
print("Method " + method_name + " not in 'My_object' class.")
return getattr(self.stubborn_object, method_name)(**kwargs)
So running those lines with the previous code sample
s_o = Stubborn_object()
m_o = My_object(s_o)
m_o.action_to_override() # Executes Stubborn_object.do_something()
m_o.action_a() # Executes Stubborn_object.action_a()
m_o.action_b() # Executes Stubborn_object.action_b()
will print
Here is stuff getting done instead of action_to_override
Method action_a not in 'My_object' class.
action_a
Method action_b not in 'My_object' class.
action_b
Some similar methods will have to be made for getters and setters, however, the idea stays the same. The thing is that this code lacks the ability to detect that an attribute is missing.
Question: How can I run the run_me_when_method_is_not_found when the method is not found in My_object? Especially, how can a My_object instance detect that the method doesn't exists in its class instead of throwing an AttributeError exception?
Thanks a lot.

Seems like overriding __getattribute__ will do exactly what you want: search for attribute in self.stubborn_object if it is missing in self. Put it into My_object class definition:
def __getattribute__(self, attr):
try:
return object.__getattribute__(self, attr)
except AttributeError:
return object.__getattribute__(self.stubborn_object, attr)

How are Python static methods useful (except as a namespace)? [duplicate]

This question already has answers here:
Difference between #staticmethod and #classmethod
(35 answers)
Why do we use #staticmethod?
(4 answers)
Closed last month.
I ran into unbound method error in python with this code:
import random
class Sample(object):
def drawSample(samplesize, List):
sample = random.sample(List, samplesize)
return sample
Choices=range(100)
print(Sample.drawSample(5, Choices))
I was able to fix the problem by adding #staticmethod to the method. However, I don't really understand the situation.
What is the point of using "static" methods? Why does it solve the problem in this code, and why are they ever necessary? Conversely, why would I ever not want to do it (i.e., why is extra code needed to make the method static)?

See this article for detailed explanation.
TL;DR
1.It eliminates the use of self argument.
2.It reduces memory usage because Python doesn't have to instantiate a bound-method for each object instiantiated:
>>>RandomClass().regular_method is RandomClass().regular_method
False
>>>RandomClass().static_method is RandomClass().static_method
True
>>>RandomClass.static_method is RandomClass().static_method
True
3.It improves code readability, signifying that the method does not depend on state of the object itself.
4.It allows for method overriding in that if the method were defined at the module-level (i.e. outside the class) a subclass would not be able to override that method.

Static methods have limited use, because they don't have access to the attributes of an instance of a class (like a regular method does), and they don't have access to the attributes of the class itself (like a class method does).
So they aren't useful for day-to-day methods.
However, they can be useful to group some utility function together with a class - e.g. a simple conversion from one type to another - that doesn't need access to any information apart from the parameters provided (and perhaps some attributes global to the module.)
They could be put outside the class, but grouping them inside the class may make sense where they are only applicable there.
You can also reference the method via an instance or the class, rather than the module name, which may help the reader understand to what instance the method is related.

This is not quite to the point of your actual question, but since you've said you are a python newbie perhaps it will be helpful, and no one else has quite come out and said it explicitly.
I would never have fixed the above code by making the method a static method. I would either have ditched the class and just written a function:
def drawSample(samplesize,List):
sample=random.sample(List,samplesize)
return sample
Choices=range(100)
print drawSample(5,Choices)
If you have many related functions, you can group them in a module - i.e, put them all in the same file, named sample.py for example; then
import sample
Choices=range(100)
print sample.drawSample(5,Choices)
Or I would have added an __init__ method to the class and created an instance that had useful methods:
class Sample(object):
'''This class defines various methods related to the sample'''
def __init__(self, thelist):
self.list = thelist
def draw_sample(self, samplesize):
sample=random.sample(self.list,samplesize)
return sample
choices=Sample(range(100))
print choices.draw_sample(5)
(I also changed the case conventions in the above example to match the style recommended by PEP 8.)
One of the advantages of Python is that it doesn't force you to use classes for everything. You can use them only when there is data or state that should be associated with the methods, which is what classes are for. Otherwise you can use functions, which is what functions are for.

Why one would want to define static methods?
Suppose we have a class called Math then
nobody will want to create object of class Math
and then invoke methods like ceil and floor and fabs on it.
So we make them static.
For example doing
>> Math.floor(3.14)
is much better than
>> mymath = Math()
>> mymath.floor(3.14)
So they are useful in some way. You need not create an instance of a class to use them.
Why are not all methods defined as static methods?
They don't have access to instance variables.
class Foo(object):
def __init__(self):
self.bar = 'bar'
def too(self):
print self.bar
#staticmethod
def foo():
print self.bar
Foo().too() # works
Foo.foo() # doesn't work
That is why we don't make all the methods static.

The alternatives to a staticmethod are: classmethod, instancemethod, and function. If you don't know what these are, scroll down to the last section. If a staticmethod is better than any of these alternatives, depends on for what purpose it is written.
advantages of the Python static method
If you don't need access to the attributes or methods of the class or instance, a staticmethod is better than a classmethod or instancemethod. That way it is clear (from the #staticmethod decorator) that the class' and instance's state is not read or modified. However, using a function makes that distinction even clearer (see disadvantages).
The call signature of a staticmethod is the same as that of a classmethod or instancemethod, namely <instance>.<method>(<arguments>). Hence it can easily be replaced by one of the three if that is needed later on or in a derived class. You can't do that with a simple function.
A staticmethod can be used instead of a function to make clear that it subjectively belongs to a class and to prevent namespace conflicts.
disadvantages of the Python static method
It cannot access attributes or methods of the instance or class.
The call signature of a staticmethod is the same as that of a classmethod or instancemethod. This masks the fact that the staticmethod does not actually read or modify any object information. This makes code harder to read. Why not just use a function?
A staticmethod is difficult to re-use if you ever need to call it from outside the class/instance where it was defined. If there is any potential for re-use, a function is the better choice.
The staticmethod is seldom used, so people reading code that includes one may take a little longer to read it.
alternatives to a static method in Python
To address discuss the advantages of the staticmethod, we need to know what the alternatives are and how they differ from each other.
The staticmethod belongs to a class but cannot access or modify any instance or class information.
There are three alternatives to it:
The classmethod has access to the caller's class.
The instancemethod has access to the caller's instance and its class.
The function has nothing to do with classes. It is the closest in capability to the staticmethod.
Here's what this looks like in code:
# function
# has nothing to do with a class
def make_cat_noise(asker_name):
print('Hi %s, mieets mieets!' % asker_name)
# Yey, we can make cat noises before we've even defined what a cat is!
make_cat_noise('JOey') # just a function
class Cat:
number_of_legs = 4
# special instance method __init__
def __init__(self, name):
self.name = name
# instancemethod
# the instance (e.g. Cat('Kitty')) is passed as the first method argument
def tell_me_about_this_animal(self, asker_name):
print('Hi %s, This cat has %d legs and is called %s'
% (asker_name, self.number_of_legs, self.name))
# classmethod
# the class (e.g. Cat) is passed as the first method argument
# by convention we call that argument cls
#classmethod
def tell_me_about_cats(cls, asker_name):
print("Hi %s, cats have %d legs."
% (asker_name, cls.number_of_legs))
# cls.name # AttributeError because only the instance has .name
# self.name # NameError because self isn't defined in this namespace
# staticmethod
# no information about the class or the instance is passed to the method
#staticmethod
def make_noise(asker_name):
print('Hi %s, meooow!' % asker_name)
# class and instance are not accessible from here
# one more time for fun!
make_cat_noise('JOey') # just a function
# We just need the class to call a classmethod or staticmethod:
Cat.make_noise('JOey') # staticmethod
Cat.tell_me_about_cats('JOey') # classmethod
# Cat.tell_me_about_this_animal('JOey') # instancemethod -> TypeError
# With an instance we can use instancemethod, classmethod or staticmethod
mycat = Cat('Kitty') # mycat is an instance of the class Cat
mycat.make_noise('JOey') # staticmethod
mycat.tell_me_about_cats('JOey') # classmethod
mycat.tell_me_about_this_animal('JOey') # instancemethod

When you call a function object from an object instance, it becomes a 'bound method' and gets the instance object itself is passed in as a first argument.
When you call a classmethod object (which wraps a function object) on an object instance, the class of the instance object gets passed in as a first argument.
When you call a staticmethod object (which wraps a function object), no implicit first argument is used.
class Foo(object):
def bar(*args):
print args
#classmethod
def baaz(*args):
print args
#staticmethod
def quux(*args):
print args
>>> foo = Foo()
>>> Foo.bar(1,2,3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method bar() must be called with Foo instance as first argument (got int instance instead)
>>> Foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> Foo.quux(1,2,3)
(1, 2, 3)
>>> foo.bar(1,2,3)
(<Foo object at 0x1004a4510>, 1, 2, 3)
>>> foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> foo.quux(1,2,3)
(1, 2, 3)

static methods are great because you don't have to declare an instance of the object to which the method belongs.
python's site has some great documentation on static methods here:
http://docs.python.org/library/functions.html#staticmethod

In my estimation, there is no single performance benefit of using #staticmethods compared to just defining the function outside of and separate from the class it would otherwise be a #staticmethod of.
The only thing I would say justifies their existence is convenience. Static methods are common in other popular programming languages, so why not python? If you want to create a function with behavior that is very closely associated with the class you are creating it for but it doesn't actually access/modify the internal data of an instance of the class in a way that justifies conceptualizing it as a typical method of that class then slap a #staticmethod above it and anyone reading your code will immediately learn a lot about the nature of the method and its relationship to the class.
One thing I occasionally like to do is place functionality that my class uses internally a lot into private #staticmethods. That way I do not clutter the API exposed by my module with methods that no one using my module would ever need to see let alone use.

Static methods have almost no reason-to-be in Python. You use either instance methods or class methods.
def method(self, args):
self.member = something
#classmethod
def method(cls, args):
cls.member = something
#staticmethod
def method(args):
MyClass.member = something
# The above isn't really working
# if you have a subclass

Because namespacing functions is nice (as was previously pointed out):
When I want to be explicit about methods that don't change the state of the object, I use static methods. This discourages people on my team to start changing the object's attributes in those methods.
When i refactor really rotten code, I start by trying to make as many methods #staticmethod as possible. This allows me then to extract these methods into a class - though I agree, this is rarely something I use, it did came in helpful a few times.

Python - how do I force the use of a factory method to instantiate an object?

I have a set of related classes that all inherit from one base class. I would like to use a factory method to instantiate objects for these classes. I want to do this because then I can store the objects in a dictionary keyed by the class name before returning the object to the caller. Then if there is a request for an object of a particular class, I can check to see whether one already exists in my dictionary. If not, I'll instantiate it and add it to the dictionary. If so, then I'll return the existing object from the dictionary. This will essentially turn all the classes in my module into singletons.
I want to do this because the base class that they all inherit from does some automatic wrapping of the functions in the subclasses, and I don't want to the functions to get wrapped more than once, which is what happens currently if two objects of the same class are created.
The only way I can think of doing this is to check the stacktrace in the __init__() method of the base class, which will always be called, and to throw an exception if the stacktrace does not show that the request to make the object is coming from the factory function.
Is this a good idea?
Edit: Here is the source code for my base class. I've been told that I need to figure out metaclasses to accomplish this more elegantly, but this is what I have for now. All Page objects use the same Selenium Webdriver instance, which is in the driver module imported at the top. This driver is very expensive to initialize -- it is initialized the first time a LoginPage is created. After it is initialized the initialize() method will return the existing driver instead of creating a new one. The idea is that the user must begin by creating a LoginPage. There will eventually be dozens of Page classes defined and they will be used by unit testing code to verify that the behavior of a website is correct.
from driver import get_driver, urlpath, initialize
from settings import urlpaths
class DriverPageMismatchException(Exception):
pass
class URLVerifyingPage(object):
# we add logic in __init__() to check the expected urlpath for the page
# against the urlpath that the driver is showing - we only want the page's
# methods to be invokable if the driver is actualy at the appropriate page.
# If the driver shows a different urlpath than the page is supposed to
# have, the method should throw a DriverPageMismatchException
def __init__(self):
self.driver = get_driver()
self._adjust_methods(self.__class__)
def _adjust_methods(self, cls):
for attr, val in cls.__dict__.iteritems():
if callable(val) and not attr.startswith("_"):
print "adjusting:"+str(attr)+" - "+str(val)
setattr(
cls,
attr,
self._add_wrapper_to_confirm_page_matches_driver(val)
)
for base in cls.__bases__:
if base.__name__ == 'URLVerifyingPage': break
self._adjust_methods(base)
def _add_wrapper_to_confirm_page_matches_driver(self, page_method):
def _wrapper(self, *args, **kwargs):
if urlpath() != urlpaths[self.__class__.__name__]:
raise DriverPageMismatchException(
"path is '"+urlpath()+
"' but '"+urlpaths[self.__class.__name__]+"' expected "+
"for "+self.__class.__name__
)
return page_method(self, *args, **kwargs)
return _wrapper
class LoginPage(URLVerifyingPage):
def __init__(self, username=username, password=password, baseurl="http://example.com/"):
self.username = username
self.password = password
self.driver = initialize(baseurl)
super(LoginPage, self).__init__()
def login(self):
driver.find_element_by_id("username").clear()
driver.find_element_by_id("username").send_keys(self.username)
driver.find_element_by_id("password").clear()
driver.find_element_by_id("password").send_keys(self.password)
driver.find_element_by_id("login_button").click()
return HomePage()
class HomePage(URLVerifyingPage):
def some_method(self):
...
return SomePage()
def many_more_methods(self):
...
return ManyMorePages()
It's no big deal if a page gets instantiated a handful of times -- the methods will just get wrapped a handful of times and a handful of unnecessary checks will take place, but everything will still work. But it would be bad if a page was instantiated dozens or hundreds or tens of thousands of times. I could just put a flag in the class definition for each page and check to see if the methods have already been wrapped, but I like the idea of keeping the class definitions pure and clean and shoving all the hocus-pocus into a deep corner of my system where no one can see it and it just works.

In Python, it's almost never worth trying to "force" anything. Whatever you come up with, someone can get around it by monkeypatching your class, copying and editing the source, fooling around with bytecode, etc.
So, just write your factory, and document that as the right way to get an instance of your class, and expect anyone who writes code using your classes to understand TOOWTDI, and not violate it unless she really knows what she's doing and is willing to figure out and deal with the consequences.
If you're just trying to prevent accidents, rather than intentional "misuse", that's a different story. In fact, it's just standard design-by-contract: check the invariant. Of course at this point, SillyBaseClass is already screwed up, and it's too late to repair it, and all you can do is assert, raise, log, or whatever else is appropriate. But that's what you want: it's a logic error in the application, and the only thing to do is get the programmer to fix it, so assert is probably exactly what you want.
So:
class SillyBaseClass:
singletons = {}
class Foo(SillyBaseClass):
def __init__(self):
assert self.__class__ not in SillyBaseClass.singletons
def get_foo():
if Foo not in SillyBaseClass.singletons:
SillyBaseClass.singletons[Foo] = Foo()
return SillyBaseClass.singletons[Foo]
If you really do want to stop things from getting this far, you can check the invariant earlier, in the __new__ method, but unless "SillyBaseClass got screwed up" is equivalent to "launch the nukes", why bother?

it sounds like you want to provide a __new__ implementation: Something like:
class MySingledtonBase(object):
instance_cache = {}
def __new__(cls, arg1, arg2):
if cls in MySingletonBase.instance_cache:
return MySingletonBase.instance_cache[cls]
self = super(MySingletonBase, cls).__new__(arg1, arg2)
MySingletonBase.instance_cache[cls] = self
return self

Rather than adding complex code to catch mistakes at runtime, I'd first try to use convention to guide users of your module to do the right thing on their own.
Give your classes "private" names (prefixed by an underscore), give them names that suggest they shouldn't be instantiated (eg _Internal...) and make your factory function "public".
That is, something like this:
class _InternalSubClassOne(_BaseClass):
...
class _InternalSubClassTwo(_BaseClass):
...
# An example factory function.
def new_object(arg):
return _InternalSubClassOne() if arg == 'one' else _InternalSubClassTwo()
I'd also add docstrings or comments to each class, like "Don't instantiate this class by hand, use the factory method new_object."

You can also just nest classes in factory method, as described here:
https://python-3-patterns-idioms-test.readthedocs.io/en/latest/Factory.html#preventing-direct-creation
Working example from mentioned source:
# Factory/shapefact1/NestedShapeFactory.py
import random
class Shape(object):
types = []
def factory(type):
class Circle(Shape):
def draw(self): print("Circle.draw")
def erase(self): print("Circle.erase")
class Square(Shape):
def draw(self): print("Square.draw")
def erase(self): print("Square.erase")
if type == "Circle": return Circle()
if type == "Square": return Square()
assert 0, "Bad shape creation: " + type
def shapeNameGen(n):
for i in range(n):
yield factory(random.choice(["Circle", "Square"]))
# Circle() # Not defined
for shape in shapeNameGen(7):
shape.draw()
shape.erase()
I'm not fan of this solution, just want to add this as one more option.

Why does "self" outside a function's parameters give a "not defined" error?

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.

What is the purpose of static methods? How do I know when to use one? [duplicate]

This question already has answers here:
Difference between #staticmethod and #classmethod
(35 answers)
Why do we use #staticmethod?
(4 answers)
Closed last month.
I ran into unbound method error in python with this code:
import random
class Sample(object):
def drawSample(samplesize, List):
sample = random.sample(List, samplesize)
return sample
Choices=range(100)
print(Sample.drawSample(5, Choices))
I was able to fix the problem by adding #staticmethod to the method. However, I don't really understand the situation.
What is the point of using "static" methods? Why does it solve the problem in this code, and why are they ever necessary? Conversely, why would I ever not want to do it (i.e., why is extra code needed to make the method static)?

See this article for detailed explanation.
TL;DR
1.It eliminates the use of self argument.
2.It reduces memory usage because Python doesn't have to instantiate a bound-method for each object instiantiated:
>>>RandomClass().regular_method is RandomClass().regular_method
False
>>>RandomClass().static_method is RandomClass().static_method
True
>>>RandomClass.static_method is RandomClass().static_method
True
3.It improves code readability, signifying that the method does not depend on state of the object itself.
4.It allows for method overriding in that if the method were defined at the module-level (i.e. outside the class) a subclass would not be able to override that method.

Static methods have limited use, because they don't have access to the attributes of an instance of a class (like a regular method does), and they don't have access to the attributes of the class itself (like a class method does).
So they aren't useful for day-to-day methods.
However, they can be useful to group some utility function together with a class - e.g. a simple conversion from one type to another - that doesn't need access to any information apart from the parameters provided (and perhaps some attributes global to the module.)
They could be put outside the class, but grouping them inside the class may make sense where they are only applicable there.
You can also reference the method via an instance or the class, rather than the module name, which may help the reader understand to what instance the method is related.

This is not quite to the point of your actual question, but since you've said you are a python newbie perhaps it will be helpful, and no one else has quite come out and said it explicitly.
I would never have fixed the above code by making the method a static method. I would either have ditched the class and just written a function:
def drawSample(samplesize,List):
sample=random.sample(List,samplesize)
return sample
Choices=range(100)
print drawSample(5,Choices)
If you have many related functions, you can group them in a module - i.e, put them all in the same file, named sample.py for example; then
import sample
Choices=range(100)
print sample.drawSample(5,Choices)
Or I would have added an __init__ method to the class and created an instance that had useful methods:
class Sample(object):
'''This class defines various methods related to the sample'''
def __init__(self, thelist):
self.list = thelist
def draw_sample(self, samplesize):
sample=random.sample(self.list,samplesize)
return sample
choices=Sample(range(100))
print choices.draw_sample(5)
(I also changed the case conventions in the above example to match the style recommended by PEP 8.)
One of the advantages of Python is that it doesn't force you to use classes for everything. You can use them only when there is data or state that should be associated with the methods, which is what classes are for. Otherwise you can use functions, which is what functions are for.

Why one would want to define static methods?
Suppose we have a class called Math then
nobody will want to create object of class Math
and then invoke methods like ceil and floor and fabs on it.
So we make them static.
For example doing
>> Math.floor(3.14)
is much better than
>> mymath = Math()
>> mymath.floor(3.14)
So they are useful in some way. You need not create an instance of a class to use them.
Why are not all methods defined as static methods?
They don't have access to instance variables.
class Foo(object):
def __init__(self):
self.bar = 'bar'
def too(self):
print self.bar
#staticmethod
def foo():
print self.bar
Foo().too() # works
Foo.foo() # doesn't work
That is why we don't make all the methods static.

The alternatives to a staticmethod are: classmethod, instancemethod, and function. If you don't know what these are, scroll down to the last section. If a staticmethod is better than any of these alternatives, depends on for what purpose it is written.
advantages of the Python static method
If you don't need access to the attributes or methods of the class or instance, a staticmethod is better than a classmethod or instancemethod. That way it is clear (from the #staticmethod decorator) that the class' and instance's state is not read or modified. However, using a function makes that distinction even clearer (see disadvantages).
The call signature of a staticmethod is the same as that of a classmethod or instancemethod, namely <instance>.<method>(<arguments>). Hence it can easily be replaced by one of the three if that is needed later on or in a derived class. You can't do that with a simple function.
A staticmethod can be used instead of a function to make clear that it subjectively belongs to a class and to prevent namespace conflicts.
disadvantages of the Python static method
It cannot access attributes or methods of the instance or class.
The call signature of a staticmethod is the same as that of a classmethod or instancemethod. This masks the fact that the staticmethod does not actually read or modify any object information. This makes code harder to read. Why not just use a function?
A staticmethod is difficult to re-use if you ever need to call it from outside the class/instance where it was defined. If there is any potential for re-use, a function is the better choice.
The staticmethod is seldom used, so people reading code that includes one may take a little longer to read it.
alternatives to a static method in Python
To address discuss the advantages of the staticmethod, we need to know what the alternatives are and how they differ from each other.
The staticmethod belongs to a class but cannot access or modify any instance or class information.
There are three alternatives to it:
The classmethod has access to the caller's class.
The instancemethod has access to the caller's instance and its class.
The function has nothing to do with classes. It is the closest in capability to the staticmethod.
Here's what this looks like in code:
# function
# has nothing to do with a class
def make_cat_noise(asker_name):
print('Hi %s, mieets mieets!' % asker_name)
# Yey, we can make cat noises before we've even defined what a cat is!
make_cat_noise('JOey') # just a function
class Cat:
number_of_legs = 4
# special instance method __init__
def __init__(self, name):
self.name = name
# instancemethod
# the instance (e.g. Cat('Kitty')) is passed as the first method argument
def tell_me_about_this_animal(self, asker_name):
print('Hi %s, This cat has %d legs and is called %s'
% (asker_name, self.number_of_legs, self.name))
# classmethod
# the class (e.g. Cat) is passed as the first method argument
# by convention we call that argument cls
#classmethod
def tell_me_about_cats(cls, asker_name):
print("Hi %s, cats have %d legs."
% (asker_name, cls.number_of_legs))
# cls.name # AttributeError because only the instance has .name
# self.name # NameError because self isn't defined in this namespace
# staticmethod
# no information about the class or the instance is passed to the method
#staticmethod
def make_noise(asker_name):
print('Hi %s, meooow!' % asker_name)
# class and instance are not accessible from here
# one more time for fun!
make_cat_noise('JOey') # just a function
# We just need the class to call a classmethod or staticmethod:
Cat.make_noise('JOey') # staticmethod
Cat.tell_me_about_cats('JOey') # classmethod
# Cat.tell_me_about_this_animal('JOey') # instancemethod -> TypeError
# With an instance we can use instancemethod, classmethod or staticmethod
mycat = Cat('Kitty') # mycat is an instance of the class Cat
mycat.make_noise('JOey') # staticmethod
mycat.tell_me_about_cats('JOey') # classmethod
mycat.tell_me_about_this_animal('JOey') # instancemethod

When you call a function object from an object instance, it becomes a 'bound method' and gets the instance object itself is passed in as a first argument.
When you call a classmethod object (which wraps a function object) on an object instance, the class of the instance object gets passed in as a first argument.
When you call a staticmethod object (which wraps a function object), no implicit first argument is used.
class Foo(object):
def bar(*args):
print args
#classmethod
def baaz(*args):
print args
#staticmethod
def quux(*args):
print args
>>> foo = Foo()
>>> Foo.bar(1,2,3)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method bar() must be called with Foo instance as first argument (got int instance instead)
>>> Foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> Foo.quux(1,2,3)
(1, 2, 3)
>>> foo.bar(1,2,3)
(<Foo object at 0x1004a4510>, 1, 2, 3)
>>> foo.baaz(1,2,3)
(<class 'Foo'>, 1, 2, 3)
>>> foo.quux(1,2,3)
(1, 2, 3)

static methods are great because you don't have to declare an instance of the object to which the method belongs.
python's site has some great documentation on static methods here:
http://docs.python.org/library/functions.html#staticmethod

In my estimation, there is no single performance benefit of using #staticmethods compared to just defining the function outside of and separate from the class it would otherwise be a #staticmethod of.
The only thing I would say justifies their existence is convenience. Static methods are common in other popular programming languages, so why not python? If you want to create a function with behavior that is very closely associated with the class you are creating it for but it doesn't actually access/modify the internal data of an instance of the class in a way that justifies conceptualizing it as a typical method of that class then slap a #staticmethod above it and anyone reading your code will immediately learn a lot about the nature of the method and its relationship to the class.
One thing I occasionally like to do is place functionality that my class uses internally a lot into private #staticmethods. That way I do not clutter the API exposed by my module with methods that no one using my module would ever need to see let alone use.

Static methods have almost no reason-to-be in Python. You use either instance methods or class methods.
def method(self, args):
self.member = something
#classmethod
def method(cls, args):
cls.member = something
#staticmethod
def method(args):
MyClass.member = something
# The above isn't really working
# if you have a subclass

Because namespacing functions is nice (as was previously pointed out):
When I want to be explicit about methods that don't change the state of the object, I use static methods. This discourages people on my team to start changing the object's attributes in those methods.
When i refactor really rotten code, I start by trying to make as many methods #staticmethod as possible. This allows me then to extract these methods into a class - though I agree, this is rarely something I use, it did came in helpful a few times.