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Python static method wrapper is unnecessary? [duplicate]

I just can't see why do we need to use #staticmethod. Let's start with an exmaple.
class test1:
def __init__(self,value):
self.value=value
#staticmethod
def static_add_one(value):
return value+1
#property
def new_val(self):
self.value=self.static_add_one(self.value)
return self.value
a=test1(3)
print(a.new_val) ## >>> 4
class test2:
def __init__(self,value):
self.value=value
def static_add_one(self,value):
return value+1
#property
def new_val(self):
self.value=self.static_add_one(self.value)
return self.value
b=test2(3)
print(b.new_val) ## >>> 4
In the example above, the method, static_add_one , in the two classes do not require the instance of the class(self) in calculation.
The method static_add_one in the class test1 is decorated by #staticmethod and work properly.
But at the same time, the method static_add_one in the class test2 which has no #staticmethod decoration also works properly by using a trick that provides a self in the argument but doesn't use it at all.
So what is the benefit of using #staticmethod? Does it improve the performance? Or is it just due to the zen of python which states that "Explicit is better than implicit"?

The reason to use staticmethod is if you have something that could be written as a standalone function (not part of any class), but you want to keep it within the class because it's somehow semantically related to the class. (For instance, it could be a function that doesn't require any information from the class, but whose behavior is specific to the class, so that subclasses might want to override it.) In many cases, it could make just as much sense to write something as a standalone function instead of a staticmethod.
Your example isn't really the same. A key difference is that, even though you don't use self, you still need an instance to call static_add_one --- you can't call it directly on the class with test2.static_add_one(1). So there is a genuine difference in behavior there. The most serious "rival" to a staticmethod isn't a regular method that ignores self, but a standalone function.

Today I suddenly find a benefit of using #staticmethod.
If you created a staticmethod within a class, you don't need to create an instance of the class before using the staticmethod.
For example,
class File1:
def __init__(self, path):
out=self.parse(path)
def parse(self, path):
..parsing works..
return x
class File2:
def __init__(self, path):
out=self.parse(path)
#staticmethod
def parse(path):
..parsing works..
return x
if __name__=='__main__':
path='abc.txt'
File1.parse(path) #TypeError: unbound method parse() ....
File2.parse(path) #Goal!!!!!!!!!!!!!!!!!!!!
Since the method parse is strongly related to the classes File1 and File2, it is more natural to put it inside the class. However, sometimes this parse method may also be used in other classes under some circumstances. If you want to do so using File1, you must create an instance of File1 before calling the method parse. While using staticmethod in the class File2, you may directly call the method by using the syntax File2.parse.
This makes your works more convenient and natural.

I will add something other answers didn't mention. It's not only a matter of modularity, of putting something next to other logically related parts. It's also that the method could be non-static at other point of the hierarchy (i.e. in a subclass or superclass) and thus participate in polymorphism (type based dispatching). So if you put that function outside the class you will be precluding subclasses from effectively overriding it. Now, say you realize you don't need self in function C.f of class C, you have three two options:
Put it outside the class. But we just decided against this.
Do nothing new: while unused, still keep the self parameter.
Declare you are not using the self parameter, while still letting other C methods to call f as self.f, which is required if you wish to keep open the possibility of further overrides of f that do depend on some instance state.
Option 2 demands less conceptual baggage (you already have to know about self and methods-as-bound-functions, because it's the more general case). But you still may prefer to be explicit about self not being using (and the interpreter could even reward you with some optimization, not having to partially apply a function to self). In that case, you pick option 3 and add #staticmethod on top of your function.

Use #staticmethod for methods that don't need to operate on a specific object, but that you still want located in the scope of the class (as opposed to module scope).
Your example in test2.static_add_one wastes its time passing an unused self parameter, but otherwise works the same as test1.static_add_one. Note that this extraneous parameter can't be optimized away.
One example I can think of is in a Django project I have, where a model class represents a database table, and an object of that class represents a record. There are some functions used by the class that are stand-alone and do not need an object to operate on, for example a function that converts a title into a "slug", which is a representation of the title that follows the character set limits imposed by URL syntax. The function that converts a title to a slug is declared as a staticmethod precisely to strongly associate it with the class that uses it.

how can i add data in a class object after i ran def __init__(self) function?

i created this class for my homework:
class sayfa():
isim=" "
def __init__(self,bSayisi,ySayisi,pSayisi,iSayisi,tSayisi):
self.bSayisi=bSayisi
self.ySayisi=ySayisi
self.pSayisi=pSayisi
self.iSayisi=iSayisi
self.tSayisi=tSayisi
if ((((bSayisi+ySayisi+pSayisi)/iSayisi)/tSayisi)*100)>0.2:
print(isim,"başarılı")
else:
print(isim,"başarısız")
then i called it in another .py file:
from eRate import sayfa
ybs1=sayfa(365000,65000,870,500,1125000)
ybs1.isim="YBS-1"
then i tried to work it and it gave me this error:
NameError: name 'isim' is not defined
I think i did something wrong when i'm writing class but i don't know what i actually done wrong.Can you help me?
edit:
My code worked when i put isim variable in def init but it looks weird.It looks like this:
class sayfa():
def __init__(self,bSayisi,ySayisi,pSayisi,iSayisi,tSayisi,isim):
self.isim=str(isim)
self.bSayisi=bSayisi
self.ySayisi=ySayisi
self.pSayisi=pSayisi
self.iSayisi=iSayisi
self.tSayisi=tSayisi
if ((((bSayisi+ySayisi+pSayisi)/iSayisi)/tSayisi)*100)>0.2:
print(isim,"başarılı")
else:
print(isim,"başarısız")
and when i'm adding data in class it gets weirder:
from eRate import sayfa
ybs1=sayfa(365000,65000,870,500,1125000,"YBS-1")

The error isn't with the way you're assigning things, but with the way you're accessing them.
Just as you have to do self.bSayisi to set an attribute, you have to do self.isim to access one. So:
print(self.isim, "başarılı")
(and the same for the other line…)
If you're wondering why you were able to access other values like bSayisi without self.bSayisi—that's just because you happen to have a parameter named bSayisi that happens to have the same value as self.bSayisi (because you just made that true a few lines earlier). If you changed it to, say, self.bSayisi = bSayisi*2, or you renamed the parameter to myBSayisi and did self.bSayisi = myBSayisi, you'd see that just using bSayisi instead of self.bSayisi was no longer correct.
However, while this eliminates the error, I'm not sure it actually does what you want. At the time you're doing this print, you haven't assigned an isim value to the object yet, so it's going to get the class value as a default, so it's always just going to be " ". Is that really what you wanted?
If not, you need to move the print calls to some other method that you can call later, after having assigned isim. For example:
class sayfa():
isim=" "
def __init__(self,bSayisi,ySayisi,pSayisi,iSayisi,tSayisi):
self.bSayisi=bSayisi
self.ySayisi=ySayisi
self.pSayisi=pSayisi
self.iSayisi=iSayisi
self.tSayisi=tSayisi
def displaystuff(self):
if ((((self.bSayisi+self.ySayisi+self.pSayisi)/self.iSayisi)/self.tSayisi)*100)>0.2:
print(self.isim,"başarılı")
else:
print(self.isim,"başarısız")
ybs1=sayfa(365000,65000,870,500,1125000)
ybs1.isim="YBS-1"
ybs1.displaystuff()
Of course moving the isim into the constructor works, by avoiding the problem you were running into. It's not an answer to how to add data after the __init__ method, of course, because you're instead adding the data in the __init__ method. When that's appropriate, it's the simplest answer.
But if it looks weird in this case (I'll take your word for it; I don't know exactly what this code is trying to do), it's probably the wrong answer for this particular class.
In which case, you do need to know how to add data after the __init__ method, as you asked. Or, rather, you need to know how to access that data—because you were already adding it correctly.

This is the difference between class attributes (when it is outside of the __init__ with no self.) and instance attributes (when you added it inside the __init__ with the self.).
Class attributes are a little more complicated since they pertain to all the instances of that class (you could overwrite them within some instances, but then they'd become instance attributes in those cases)... and so if you changed a class attribute, it would affect all other instances you may have created or will create in the future.
For a more in-depth discussion of class attributes vs instance attributes see this answer that summarizes this post.

Normall __init__(..) is used to initialize / instantiate your instance. I would not print in it, nor calculate (unless you calculate some other class-variables and set them).
You need to prefix your variables of the instance by self. and the static class variable with the class name to acess it:
class sayfa():
isim=" " # this is a shared class variabl (aka static)
def __init__(self,bSayisi,ySayisi,pSayisi,iSayisi,tSayisi):
self.bSayisi=bSayisi # these are all instance variables, not shared
self.ySayisi=ySayisi
self.pSayisi=pSayisi
self.iSayisi=iSayisi
self.tSayisi=tSayisi
self.unusedSum = ySayisi + pSayisi + iSayisi
def printMe(self): # lookup __str__() and __repr__() for how to output your instance
if ((((self.bSayisi+self.ySayisi+self.pSayisi)/self.iSayisi)/self.tSayisi)*100)>0.2:
print(sayfa.isim,"some text") # use the static class variable
else:
print(sayfa.isim,"some other text")
sayfa.isim = "Coffee " # you set static class variables by prefixing class name
my_sayfa_instance = sayfa(365000,65000,870,500,1125000)
other_sayfa_instance = sayfa(3600,65000,870,500,10)
my_sayfa_instance.printMe()
other_sayfa_instance.printMe()
Output:
Coffee some other text
Coffee some text

Instance variables in methods outside the constructor (Python) -- why and how?

My questions concern instance variables that are initialized in methods outside the class constructor. This is for Python.
I'll first state what I understand:
Classes may define a constructor, and it may also define other methods.
Instance variables are generally defined/initialized within the constructor.
But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
An example of (2) and (3) -- see self.meow and self.roar in the Cat class below:
class Cat():
def __init__(self):
self.meow = "Meow!"
def meow_bigger(self):
self.roar = "Roar!"
My questions:
Why is it best practice to initialize the instance variable within the constructor?
What general/specific mess could arise if instance variables are regularly initialized in methods other than the constructor? (E.g. Having read Mark Lutz's Tkinter guide in his Programming Python, which I thought was excellent, I noticed that the instance variable used to hold the PhotoImage objects/references were initialized in the further methods, not in the constructor. It seemed to work without issue there, but could that practice cause issues in the long run?)
In what scenarios would it be better to initialize instance variables in the other methods, rather than in the constructor?
To my knowledge, instance variables exist not when the class object is created, but after the class object is instantiated. Proceeding upon my code above, I demonstrate this:
>> c = Cat()
>> c.meow
'Meow!'
>> c.roar
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Cat' object has no attribute 'roar'
>>> c.meow_bigger()
>>> c.roar
'Roar!'
As it were:
I cannot access the instance variable (c.roar) at first.
However, after I have called the instance method c.meow_bigger() once, I am suddenly able to access the instance variable c.roar.
Why is the above behaviour so?
Thank you for helping out with my understanding.

Why is it best practice to initialize the instance variable within the
constructor?
Clarity.
Because it makes it easy to see at a glance all of the attributes of the class. If you initialize the variables in multiple methods, it becomes difficult to understand the complete data structure without reading every line of code.
Initializing within the __init__ also makes documentation easier. With your example, you can't write "an instance of Cat has a roar attribute". Instead, you have to add a paragraph explaining that an instance of Cat might have a "roar" attribute, but only after calling the "meow_louder" method.
Clarity is king. One of the smartest programmers I ever met once told me "show me your data structures, and I can tell you how your code works without seeing any of your code". While that's a tiny bit hyperbolic, there's definitely a ring of truth to it. One of the biggest hurdles to learning a code base is understanding the data that it manipulates.
What general/specific mess could arise if instance variables are
regularly initialized in methods other than the constructor?
The most obvious one is that an object may not have an attribute available during all parts of the program, leading to having to add a lot of extra code to handle the case where the attribute is undefined.
In what scenarios would it be better to initialize instance variables
in the other methods, rather than in the constructor?
I don't think there are any.
Note: you don't necessarily have to initialize an attribute with it's final value. In your case it's acceptable to initialize roar to None. The mere fact that it has been initialized to something shows that it's a piece of data that the class maintains. It's fine if the value changes later.

Remember that class members in "pure" Python are just a dictionary. Members aren't added to an instance's dictionary until you run the function in which they are defined. Ideally this is the constructor, because that then guarantees that your members will all exist regardless of the order that your functions are called.
I believe your example above could be translated to:
class Cat():
def __init__(self):
self.__dict__['meow'] = "Meow!"
def meow_bigger(self):
self.__dict__['roar'] = "Roar!"
>>> c = Cat() # c.__dict__ = { 'meow': "Meow!" }
>>> c.meow_bigger() # c.__dict__ = { 'meow': "Meow!", 'roar': "Roar!" }

To initialize instance variables within the constructor, is - as you already pointed out - only recommended in python.
First of all, defining all instance variables within the constructor is a good way to document a class. Everybody, seeing the code, knows what kind of internal state an instance has.
Secondly, order matters. if one defines an instance variable V in a function A and there is another function B also accessing V, it is important to call A before B. Otherwise B will fail since V was never defined. Maybe, A has to be invoked before B, but then it should be ensured by an internal state, which would be an instance variable.
There are many more examples. Generally it is just a good idea to define everything in the __init__ method, and set it to None if it can not / should not be initialized at initialization.
Of course, one could use hasattr method to derive some information of the state. But, also one could check if some instance variable V is for example None, which can imply the same then.
So in my opinion, it is never a good idea to define an instance variable anywhere else as in the constructor.
Your examples state some basic properties of python. An object in Python is basically just a dictionary.
Lets use a dictionary: One can add functions and values to that dictionary and construct some kind of OOP. Using the class statement just brings everything into a clean syntax and provides extra stuff like magic methods.
In other languages all information about instance variables and functions are present before the object was initialized. Python does that at runtime. You can also add new methods to any object outside the class definition: Adding a Method to an Existing Object Instance

3.) But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
I'd recommend providing a default state in initialization, just so its clear what the class should expect. In statically typed languages, you'd have to do this, and it's good practice in python.
Let's convey this by replacing the variable roar with a more meaningful variable like has_roared.
In this case, your meow_bigger() method now has a reason to set has_roar. You'd initialize it to false in __init__, as the cat has not roared yet upon instantiation.
class Cat():
def __init__(self):
self.meow = "Meow!"
self.has_roared = False
def meow_bigger(self):
print self.meow + "!!!"
self.has_roared = True
Now do you see why it often makes sense to initialize attributes with default values?
All that being said, why does python not enforce that we HAVE to define our variables in the __init__ method? Well, being a dynamic language, we can now do things like this.
>>> cat1 = Cat()
>>> cat2 = Cat()
>>> cat1.name = "steve"
>>> cat2.name = "sarah"
>>> print cat1.name
... "steve"
The name attribute was not defined in the __init__ method, but we're able to add it anyway. This is a more realistic use case of setting variables that aren't defaulted in __init__.

I try to provide a case where you would do so for:
3.) But instance variables can also be defined/initialized outside the constructor, e.g. in the other methods of the same class.
I agree it would be clear and organized to include instance field in the constructor, but sometimes you are inherit other class, which is created by some other people and has many instance fields and api.
But if you inherit it only for certain apis and you want to have your own instance field for your own apis, in this case, it is easier for you to just declare extra instance field in the method instead override the other's constructor without bothering to deep into the source code. This also support Adam Hughes's answer, because in this case, you will always have your defined instance because you will guarantee to call you own api first.
For instance, suppose you inherit a package's handler class for web development, you want to include a new instance field called user for handler, you would probability just declare it directly in the method--initialize without override the constructor, I saw it is more common to do so.
class BlogHandler(webapp2.RequestHandler):
def initialize(self, *a, **kw):
webapp2.RequestHandler.initialize(self, *a, **kw)
uid = self.read_cookie('user_id') #get user_id by read cookie in the browser
self.user = User.by_id(int(uid)) #run query in data base find the user and return user

These are very open questions.
Python is a very "free" language in the sense that it tries to never restrict you from doing anything, even if it looks silly. This is why you can do completely useless things such as replacing a class with a boolean (Yes you can).
The behaviour that you mention follows that same logic: if you wish to add an attribute to an object (or to a function - yes you can, too) dynamically, anywhere, not necessarily in the constructor, well... you can.
But it is not because you can that you should. The main reason for initializing attributes in the constructor is readability, which is a prerequisite for maintenance. As Bryan Oakley explains in his answer, class fields are key to understand the code as their names and types often reveal the intent better than the methods.
That being said, there is now a way to separate attribute definition from constructor initialization: pyfields. I wrote this library to be able to define the "contract" of a class in terms of attributes, while not requiring initialization in the constructor. This allows you in particular to create "mix-in classes" where attributes and methods relying on these attributes are defined, but no constructor is provided.
See this other answer for an example and details.

i think to keep it simple and understandable, better to initialize the class variables in the class constructor, so they can be directly called without the necessity of compiling of a specific class method.
class Cat():
def __init__(self,Meow,Roar):
self.meow = Meow
self.roar = Roar
def meow_bigger(self):
return self.roar
def mix(self):
return self.meow+self.roar
c=Cat("Meow!","Roar!")
print(c.meow_bigger())
print(c.mix())
Output
Roar!
Roar!
Meow!Roar!

In Python, how do you change an instantiated object after a reload?

Let's say you have an object that was instantiated from a class inside a module.
Now, you reload that module.
The next thing you'd like to do is make that reload affect that class.
mymodule.py
---
class ClassChange():
def run(self):
print 'one'
myexperiment.py
---
import mymodule
from mymodule import ClassChange # why is this necessary?
myObject = ClassChange()
myObject.run()
>>> one
### later, i changed this file, so that it says print 'two'
reload(mymodule)
# trick to change myObject needed here
myObject.run()
>>> two
Do you have to make a new ClassChange object, copy myObject into that, and delete the old myObject? Or is there a simpler way?
Edit: The run() method seems like a static class style method but that was only for the sake of brevity. I'd like the run() method to operate on data inside the object, so a static module function wouldn't do...

To update all instances of a class, it is necessary to keep track somewhere about those instances -- typically via weak references (weak value dict is handiest and general) so the "keeping track" functionality won't stop unneeded instances from going away, of course!
You'd normally want to keep such a container in the class object, but, in this case, since you'll be reloading the module, getting the old class object is not trivial; it's simpler to work at module level.
So, let's say that an "upgradable module" needs to define, at its start, a weak value dict (and an auxiliary "next key to use" int) with, say, conventional names:
import weakref
class _List(list): pass # a weakly-referenceable sequence
_objs = weakref.WeakValueDictionary()
_nextkey = 0
def _register(obj):
_objs[_nextkey] = List((obj, type(obj).__name__))
_nextkey += 1
Each class in the module must have, typically in __init__, a call _register(self) to register new instances.
Now the "reload function" can get the roster of all instances of all classes in this module by getting a copy of _objs before it reloads the module.
If all that's needed is to change the code, then life is reasonably easy:
def reload_all(amodule):
objs = getattr(amodule, '_objs', None)
reload(amodule)
if not objs: return # not an upgraable-module, or no objects
newobjs = getattr(amodule, '_objs', None)
for obj, classname in objs.values():
newclass = getattr(amodule, classname)
obj.__class__ = newclass
if newobjs: newobjs._register(obj)
Alas, one typically does want to give the new class a chance to upgrade an object of the old class to itself more finely, e.g. by a suitable class method. That's not too hard either:
def reload_all(amodule):
objs = getattr(amodule, '_objs', None)
reload(amodule)
if not objs: return # not an upgraable-module, or no objects
newobjs = getattr(amodule, '_objs', None)
for obj, classname in objs:
newclass = getattr(amodule, classname)
upgrade = getattr(newclass, '_upgrade', None)
if upgrade:
upgrade(obj)
else:
obj.__class__ = newclass
if newobjs: newobjs._register(obj)
For example, say the new version of class Zap has renamed an attribute from foo to bar. This could be the code of the new Zap:
class Zap(object):
def __init__(self):
_register(self)
self.bar = 23
#classmethod
def _upgrade(cls, obj):
obj.bar = obj.foo
del obj.foo
obj.__class__ = cls
This is NOT all -- there's a LOT more to say on the subject -- but, it IS the gist, and the answer is WAY long enough already (and I, exhausted enough;-).

You have to make a new object. There's no way to magically update the existing objects.
Read the reload builtin documentation - it is very clear. Here's the last paragraph:
If a module instantiates instances of a class, reloading the module that defines the class does not affect the method definitions of the instances — they continue to use the old class definition. The same is true for derived classes.
There are other caveats in the documentation, so you really should read it, and consider alternatives. Maybe you want to start a new question with why you want to use reload and ask for other ways of achieving the same thing.

My approach to this is the following:
Look through all imported modules and reload only those with a new .py file (as compared to the existing .pyc file)
For every function and class method that is reloaded, set old_function.__code__ = new_function.__code__.
For every reloaded class, use gc.get_referrers to list instances of the class and set their __class__ attribute to the new version.
Advantages to this approach are:
Usually no need to reload modules in any particular order
Usually only need to reload the modules with changed code and no more
Don't need to modify classes to keep track of their instances
You can read about the technique (and its limitations) here:
http://luke-campagnola.blogspot.com/2010/12/easy-automated-reloading-in-python.html
And you can download the code here:
http://luke.campagnola.me/code/downloads/reload.py

You have to get the new class from the fresh module and assign it back to the instance.
If you could trigger this operation anytime you use an instance with this mixin:
import sys
class ObjDebug(object):
def __getattribute__(self,k):
ga=object.__getattribute__
sa=object.__setattr__
cls=ga(self,'__class__')
modname=cls.__module__
mod=__import__(modname)
del sys.modules[modname]
reload(mod)
sa(self,'__class__',getattr(mod,cls.__name__))
return ga(self,k)

The following code does what you want, but please don't use it (at least not until you're very sure you're doing the right thing), I'm posting it for explanation purposes only.
mymodule.py:
class ClassChange():
#classmethod
def run(cls,instance):
print 'one',id(instance)
myexperiment.py:
import mymodule
myObject = mymodule.ClassChange()
mymodule.ClassChange.run(myObject)
# change mymodule.py here
reload(mymodule)
mymodule.ClassChange.run(myObject)
When in your code you instanciate myObject, you get an instance of ClassChange. This instance has an instance method called run. The object keeps this instance method (for the reason explained by nosklo) even when reloading, because reloading only reloads the class ClassChange.
In my code above, run is a class method. Class methods are always bound to and operate on the class, not the instance (which is why their first argument is usually called cls, not self). Wenn ClassChange is reloaded, so is this class method.
You can see that I also pass the instance as an argument to work with the correct (same) instance of ClassChange. You can see that because the same object id is printed in both cases.

I'm not sure if this is the best way to do it, or meshes with what you want to do... but this may work for you. If you want to change the behavior of a method, for all objects of a certain type... just use a function variable. For example:
def default_behavior(the_object):
print "one"
def some_other_behavior(the_object):
print "two"
class Foo(object):
# Class variable: a function that has the behavior
# (Takes an instance of a Foo as argument)
behavior = default_behavior
def __init__(self):
print "Foo initialized"
def method_that_changes_behavior(self):
Foo.behavior(self)
if __name__ == "__main__":
foo = Foo()
foo.method_that_changes_behavior() # prints "one"
Foo.behavior = some_other_behavior
foo.method_that_changes_behavior() # prints "two"
# OUTPUT
# Foo initialized
# one
# two
You can now have a class that is responsible for reloading modules, and after reloading, setting Foo.behavior to something new. I tried out this code. It works fine :-).
Does this work for you?

There are tricks to make what you want possible.
Someone already mentioned that you can have a class that keeps a list of its instances, and then changing the class of each instance to the new one upon reload.
However, that is not efficient. A better method is to change the old class so that it is the same as the new class.

What is the purpose of class methods?

I'm teaching myself Python and my most recent lesson was that Python is not Java, and so I've just spent a while turning all my Class methods into functions.
I now realise that I don't need to use Class methods for what I would done with static methods in Java, but now I'm not sure when I would use them. All the advice I can find about Python Class methods is along the lines of newbies like me should steer clear of them, and the standard documentation is at its most opaque when discussing them.
Does anyone have a good example of using a Class method in Python or at least can someone tell me when Class methods can be sensibly used?

Class methods are for when you need to have methods that aren't specific to any particular instance, but still involve the class in some way. The most interesting thing about them is that they can be overridden by subclasses, something that's simply not possible in Java's static methods or Python's module-level functions.
If you have a class MyClass, and a module-level function that operates on MyClass (factory, dependency injection stub, etc), make it a classmethod. Then it'll be available to subclasses.

Factory methods (alternative constructors) are indeed a classic example of class methods.
Basically, class methods are suitable anytime you would like to have a method which naturally fits into the namespace of the class, but is not associated with a particular instance of the class.
As an example, in the excellent unipath module:
Current directory
Path.cwd()
Return the actual current directory; e.g., Path("/tmp/my_temp_dir"). This is a class method.
.chdir()
Make self the current directory.
As the current directory is process wide, the cwd method has no particular instance with which it should be associated. However, changing the cwd to the directory of a given Path instance should indeed be an instance method.
Hmmm... as Path.cwd() does indeed return a Path instance, I guess it could be considered to be a factory method...

Think about it this way: normal methods are useful to hide the details of dispatch: you can type myobj.foo() without worrying about whether the foo() method is implemented by the myobj object's class or one of its parent classes. Class methods are exactly analogous to this, but with the class object instead: they let you call MyClass.foo() without having to worry about whether foo() is implemented specially by MyClass because it needed its own specialized version, or whether it is letting its parent class handle the call.
Class methods are essential when you are doing set-up or computation that precedes the creation of an actual instance, because until the instance exists you obviously cannot use the instance as the dispatch point for your method calls. A good example can be viewed in the SQLAlchemy source code; take a look at the dbapi() class method at the following link:
https://github.com/zzzeek/sqlalchemy/blob/ab6946769742602e40fb9ed9dde5f642885d1906/lib/sqlalchemy/dialects/mssql/pymssql.py#L47
You can see that the dbapi() method, which a database backend uses to import the vendor-specific database library it needs on-demand, is a class method because it needs to run before instances of a particular database connection start getting created — but that it cannot be a simple function or static function, because they want it to be able to call other, supporting methods that might similarly need to be written more specifically in subclasses than in their parent class. And if you dispatch to a function or static class, then you "forget" and lose the knowledge about which class is doing the initializing.

I recently wanted a very light-weight logging class that would output varying amounts of output depending on the logging level that could be programmatically set. But I didn't want to instantiate the class every time I wanted to output a debugging message or error or warning. But I also wanted to encapsulate the functioning of this logging facility and make it reusable without the declaration of any globals.
So I used class variables and the #classmethod decorator to achieve this.
With my simple Logging class, I could do the following:
Logger._level = Logger.DEBUG
Then, in my code, if I wanted to spit out a bunch of debugging information, I simply had to code
Logger.debug( "this is some annoying message I only want to see while debugging" )
Errors could be out put with
Logger.error( "Wow, something really awful happened." )
In the "production" environment, I can specify
Logger._level = Logger.ERROR
and now, only the error message will be output. The debug message will not be printed.
Here's my class:
class Logger :
''' Handles logging of debugging and error messages. '''
DEBUG = 5
INFO = 4
WARN = 3
ERROR = 2
FATAL = 1
_level = DEBUG
def __init__( self ) :
Logger._level = Logger.DEBUG
#classmethod
def isLevel( cls, level ) :
return cls._level >= level
#classmethod
def debug( cls, message ) :
if cls.isLevel( Logger.DEBUG ) :
print "DEBUG: " + message
#classmethod
def info( cls, message ) :
if cls.isLevel( Logger.INFO ) :
print "INFO : " + message
#classmethod
def warn( cls, message ) :
if cls.isLevel( Logger.WARN ) :
print "WARN : " + message
#classmethod
def error( cls, message ) :
if cls.isLevel( Logger.ERROR ) :
print "ERROR: " + message
#classmethod
def fatal( cls, message ) :
if cls.isLevel( Logger.FATAL ) :
print "FATAL: " + message
And some code that tests it just a bit:
def logAll() :
Logger.debug( "This is a Debug message." )
Logger.info ( "This is a Info message." )
Logger.warn ( "This is a Warn message." )
Logger.error( "This is a Error message." )
Logger.fatal( "This is a Fatal message." )
if __name__ == '__main__' :
print "Should see all DEBUG and higher"
Logger._level = Logger.DEBUG
logAll()
print "Should see all ERROR and higher"
Logger._level = Logger.ERROR
logAll()

Alternative constructors are the classic example.

It allows you to write generic class methods that you can use with any compatible class.
For example:
#classmethod
def get_name(cls):
print cls.name
class C:
name = "tester"
C.get_name = get_name
#call it:
C.get_name()
If you don't use #classmethod you can do it with self keyword but it needs an instance of Class:
def get_name(self):
print self.name
class C:
name = "tester"
C.get_name = get_name
#call it:
C().get_name() #<-note the its an instance of class C

When a user logs in on my website, a User() object is instantiated from the username and password.
If I need a user object without the user being there to log in (e.g. an admin user might want to delete another users account, so i need to instantiate that user and call its delete method):
I have class methods to grab the user object.
class User():
#lots of code
#...
# more code
#classmethod
def get_by_username(cls, username):
return cls.query(cls.username == username).get()
#classmethod
def get_by_auth_id(cls, auth_id):
return cls.query(cls.auth_id == auth_id).get()

I think the most clear answer is AmanKow's one. It boils down to how u want to organize your code. You can write everything as module level functions which are wrapped in the namespace of the module i.e
module.py (file 1)
---------
def f1() : pass
def f2() : pass
def f3() : pass
usage.py (file 2)
--------
from module import *
f1()
f2()
f3()
def f4():pass
def f5():pass
usage1.py (file 3)
-------------------
from usage import f4,f5
f4()
f5()
The above procedural code is not well organized, as you can see after only 3 modules it gets confusing, what is each method do ? You can use long descriptive names for functions(like in java) but still your code gets unmanageable very quick.
The object oriented way is to break down your code into manageable blocks i.e Classes & objects and functions can be associated with objects instances or with classes.
With class functions you gain another level of division in your code compared with module level functions.
So you can group related functions within a class to make them more specific to a task that you assigned to that class. For example you can create a file utility class :
class FileUtil ():
def copy(source,dest):pass
def move(source,dest):pass
def copyDir(source,dest):pass
def moveDir(source,dest):pass
//usage
FileUtil.copy("1.txt","2.txt")
FileUtil.moveDir("dir1","dir2")
This way is more flexible and more maintainable, you group functions together and its more obvious to what each function do. Also you prevent name conflicts, for example the function copy may exist in another imported module(for example network copy) that you use in your code, so when you use the full name FileUtil.copy() you remove the problem and both copy functions can be used side by side.

Honestly? I've never found a use for staticmethod or classmethod. I've yet to see an operation that can't be done using a global function or an instance method.
It would be different if python used private and protected members more like Java does. In Java, I need a static method to be able to access an instance's private members to do stuff. In Python, that's rarely necessary.
Usually, I see people using staticmethods and classmethods when all they really need to do is use python's module-level namespaces better.

I used to work with PHP and recently I was asking myself, whats going on with this classmethod? Python manual is very technical and very short in words so it wont help with understanding that feature. I was googling and googling and I found answer -> http://code.anjanesh.net/2007/12/python-classmethods.html.
If you are lazy to click it. My explanation is shorter and below. :)
in PHP (maybe not all of you know PHP, but this language is so straight forward that everybody should understand what I'm talking about) we have static variables like this:
class A
{
static protected $inner_var = null;
static public function echoInnerVar()
{
echo self::$inner_var."\n";
}
static public function setInnerVar($v)
{
self::$inner_var = $v;
}
}
class B extends A
{
}
A::setInnerVar(10);
B::setInnerVar(20);
A::echoInnerVar();
B::echoInnerVar();
The output will be in both cases 20.
However in python we can add #classmethod decorator and thus it is possible to have output 10 and 20 respectively. Example:
class A(object):
inner_var = 0
#classmethod
def setInnerVar(cls, value):
cls.inner_var = value
#classmethod
def echoInnerVar(cls):
print cls.inner_var
class B(A):
pass
A.setInnerVar(10)
B.setInnerVar(20)
A.echoInnerVar()
B.echoInnerVar()
Smart, ain't?

Class methods provide a "semantic sugar" (don't know if this term is widely used) - or "semantic convenience".
Example: you got a set of classes representing objects. You might want to have the class method all() or find() to write User.all() or User.find(firstname='Guido'). That could be done using module level functions of course...

if you are not a "programmer by training", this should help:
I think I have understood the technical explanations above and elsewhere on the net, but I was always left with a question "Nice, but why do I need it? What is a practical, use case?". and now life gave me a good example that clarified all:
I am using it to control the global-shared variable that is shared among instances of a class instantiated by multi-threading module. in humane language, I am running multiple agents that create examples for deep learning IN PARALLEL. (imagine multiple players playing ATARI game at the same time and each saving the results of their game to one common repository (the SHARED VARIABLE))
I instantiate the players/agents with the following code (in Main/Execution Code):
a3c_workers = [A3C_Worker(self.master_model, self.optimizer, i, self.env_name, self.model_dir) for i in range(multiprocessing.cpu_count())]
it creates as many players as there are processor cores on my comp
A3C_Worker - is a class that defines the agent
a3c_workers - is a list of the instances of that class (i.e. each instance is one player/agent)
now i want to know how many games have been played across all players/agents thus within the A3C_Worker definition I define the variable to be shared across all instances:
class A3C_Worker(threading.Thread):
global_shared_total_episodes_across_all_workers = 0
now as the workers finish their games they increase that count by 1 each for each game finished
at the end of my example generation i was closing the instances but the shared variable had assigned the total number of games played. so when I was re-running it again my initial total number of episodes was that of the previous total. but i needed that count to represent that value for each run individually
to fix that i specified :
class A3C_Worker(threading.Thread):
#classmethod
def reset(cls):
A3C_Worker.global_shared_total_episodes_across_all_workers = 0
than in the execution code i just call:
A3C_Worker.reset()
note that it is a call to the CLASS overall not any INSTANCE of it individually. thus it will set my counter to 0 for every new agent I initiate from now on.
using the usual method definition def play(self):, would require us to reset that counter for each instance individually, which would be more computationally demanding and difficult to track.

What just hit me, coming from Ruby, is that a so-called class method and a so-called instance method is just a function with semantic meaning applied to its first parameter, which is silently passed when the function is called as a method of an object (i.e. obj.meth()).
Normally that object must be an instance but the #classmethod method decorator changes the rules to pass a class. You can call a class method on an instance (it's just a function) - the first argument will be its class.
Because it's just a function, it can only be declared once in any given scope (i.e. class definition). If follows therefore, as a surprise to a Rubyist, that you can't have a class method and an instance method with the same name.
Consider this:
class Foo():
def foo(x):
print(x)
You can call foo on an instance
Foo().foo()
<__main__.Foo instance at 0x7f4dd3e3bc20>
But not on a class:
Foo.foo()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method foo() must be called with Foo instance as first argument (got nothing instead)
Now add #classmethod:
class Foo():
#classmethod
def foo(x):
print(x)
Calling on an instance now passes its class:
Foo().foo()
__main__.Foo
as does calling on a class:
Foo.foo()
__main__.Foo
It's only convention that dictates that we use self for that first argument on an instance method and cls on a class method. I used neither here to illustrate that it's just an argument. In Ruby, self is a keyword.
Contrast with Ruby:
class Foo
def foo()
puts "instance method #{self}"
end
def self.foo()
puts "class method #{self}"
end
end
Foo.foo()
class method Foo
Foo.new.foo()
instance method #<Foo:0x000000020fe018>
The Python class method is just a decorated function and you can use the same techniques to create your own decorators. A decorated method wraps the real method (in the case of #classmethod it passes the additional class argument). The underlying method is still there, hidden but still accessible.
footnote: I wrote this after a name clash between a class and instance method piqued my curiosity. I am far from a Python expert and would like comments if any of this is wrong.

This is an interesting topic. My take on it is that python classmethod operates like a singleton rather than a factory (which returns a produced an instance of a class). The reason it is a singleton is that there is a common object that is produced (the dictionary) but only once for the class but shared by all instances.
To illustrate this here is an example. Note that all instances have a reference to the single dictionary. This is not Factory pattern as I understand it. This is probably very unique to python.
class M():
#classmethod
def m(cls, arg):
print "arg was", getattr(cls, "arg" , None),
cls.arg = arg
print "arg is" , cls.arg
M.m(1) # prints arg was None arg is 1
M.m(2) # prints arg was 1 arg is 2
m1 = M()
m2 = M()
m1.m(3) # prints arg was 2 arg is 3
m2.m(4) # prints arg was 3 arg is 4 << this breaks the factory pattern theory.
M.m(5) # prints arg was 4 arg is 5

I was asking myself the same question few times. And even though the guys here tried hard to explain it, IMHO the best answer (and simplest) answer I have found is the description of the Class method in the Python Documentation.
There is also reference to the Static method. And in case someone already know instance methods (which I assume), this answer might be the final piece to put it all together...
Further and deeper elaboration on this topic can be found also in the documentation:
The standard type hierarchy (scroll down to Instance methods section)

#classmethod can be useful for easily instantiating objects of that class from outside resources. Consider the following:
import settings
class SomeClass:
#classmethod
def from_settings(cls):
return cls(settings=settings)
def __init__(self, settings=None):
if settings is not None:
self.x = settings['x']
self.y = settings['y']
Then in another file:
from some_package import SomeClass
inst = SomeClass.from_settings()
Accessing inst.x will give the same value as settings['x'].

A class defines a set of instances, of course. And the methods of a class work on the individual instances. The class methods (and variables) a place to hang other information that is related to the set of instances over all.
For example if your class defines a the set of students you might want class variables or methods which define things like the set of grade the students can be members of.
You can also use class methods to define tools for working on the entire set. For example Student.all_of_em() might return all the known students. Obviously if your set of instances have more structure than just a set you can provide class methods to know about that structure. Students.all_of_em(grade='juniors')
Techniques like this tend to lead to storing members of the set of instances into data structures that are rooted in class variables. You need to take care to avoid frustrating the garbage collection then.

Classes and Objects concepts are very useful in organizing things. It's true that all the operations that can be done by a method can also be done using a static function.
Just think of a scenario, to build a Students Databases System to maintain student details.
You need to have details about students, teachers and staff. You need to build functions to calculate fees, salary, marks, etc. Fees and marks are only applicable for students, salary is only applicable for staff and teachers. So if you create separate classes for every type of people, the code will be organized.