Take the following example script:
class A(object):
#classmethod
def one(cls):
print("I am class")
#staticmethod
def two():
print("I am static")
class B(object):
one = A.one
two = A.two
B.one()
B.two()
When I run this script with Python 2.7.11 I get:
I am class
Traceback (most recent call last):
File "test.py", line 17, in <module>
B.two()
TypeError: unbound method two() must be called with B instance as first argument (got nothing instead)
It appears that the #classmethod decorator is preserved across the classes, but #staticmethod is not.
Python 3.4 behaves as expected:
I am class
I am static
Why does Python2 not preserve #staticmethod, and is there a workaround?
edit: taking two out of a class (and retaining #staticmethod) seems to work, but this still seems strange to me.
classmethod and staticmethod are descriptors, and neither of them are doing what you expect, not just staticmethod.
When you access A.one, it's creating a bound method on A, then making that an attribute of B, but because it's bound to A, the cls argument will always be A, even if you call B.one (this is the case on both Python 2 and Python 3; it's wrong everywhere).
When you access A.two, it's returning the raw function object (the staticmethod descriptor doesn't need to do anything special aside from preventing binding that would pass self or cls, so it just returns what it wrapped). But that raw function object then gets attached to B as an unbound instance method, because without the staticmethod wrapping, it's just like you'd defined it normally.
The reason the latter works in Python 3 is that Python 3 has no concept of unbound methods. It has functions (which if accessed via an instance of a class become bound methods) and bound methods, where Python 2 has functions, unbound methods and bound methods.
Unbound methods check that they're called with an object of the correct type, thus your error. Plain functions just want the correct number of arguments.
The staticmethod decorator in Python 3 is still returning the raw function object, but in Python 3, that's fine; since it's not a special unbound method object, if you call it on the class itself, it's just like a namespaced function, not a method of any sort. You'd see the problem if you tried to do:
B().two()
though, because that will make a bound method out of that instance of B and the two function, passing an extra argument (self) that two does not accept. Basically, on Python 3, staticmethod is a convenience to let you call the function on instances without causing binding, but if you only ever call the function by referencing the class itself, it's not needed, because it's just a plain function, not the Python 2 "unbound method".
If you had some reason to perform this copy (normally, I'd suggest inheriting from A, but whatever), and you want to make sure you get the descriptor wrapped version of the function, not whatever the descriptor gives you when accessed on A, you'd bypass the descriptor protocol by directly accessing A's __dict__:
class B(object):
one = A.__dict__['one']
two = A.__dict__['two']
By directly copying from the class dictionary, the descriptor protocol magic is never invoked, and you get the staticmethod and classmethod wrapped versions of one and two.
DISCLAIMER: This is not really an answer, but it doesn't fit into a comment format either.
Note that with Python2 #classmethod is NOT correctly preserved across classes either. In the code below, the call to B.one() works as though it was invoked through class A:
$ cat test.py
class A(object):
#classmethod
def one(cls):
print("I am class", cls.__name__)
class A2(A):
pass
class B(object):
one = A.one
A.one()
A2.one()
B.one()
$ python2 test.py
('I am class', 'A')
('I am class', 'A2')
('I am class', 'A')
Related
This question already has answers here:
How does `super` interacts with a class's `__mro__` attribute in multiple inheritance?
(2 answers)
Closed 4 years ago.
From Python3's documentation super() "returns a proxy object that delegates method calls to a parent or sibling class of type." What does that mean?
Suppose I have the following code:
class SuperClass():
def __init__(self):
print("__init__ from SuperClass.")
print("self object id from SuperClass: " + str(id(self)))
class SubClass(SuperClass):
def __init__(self):
print("__init__ from SubClass.")
print("self object id from SubClass: " + str(id(self)))
super().__init__()
sc = SubClass()
The output I get from this is:
__init__ from SubClass.
self object id from SubClass: 140690611849200
__init__ from SuperClass.
self object id from SuperClass: 140690611849200
This means that in the line super().__init__(), super() is returning the current object which is then implicitly passed to the superclass' __init__() method. Is this accurate or am I missing something here?
To put it simply, I want to understand the following:
When super().__init__() is run,
What exactly is being passed to __init__() and how? We are calling it on super() so whatever this is returning should be getting passed to the __init__() method from what I understand about Python so far.
Why don't we have to pass in self to super().__init__()?
returns a proxy object that delegates method calls to a parent or
sibling class of type.
This proxy is an object that acts as the method-calling portion of the parent class. It is not the class itself; rather, it's just enough information so that you can use it to call the parent class methods.
If you call __init__(), you get your own, local, sub-class __init__ function. When you call super(), you get that proxy object, which will redirect you to the parent-class methods. Thus, when you call super().__init__(), that proxy redirects the call to the parent-class __init__ method.
Similarly, if you were to call super().foo, you would get the foo method from the parent class -- again, re-routed by that proxy.
Is that clear to you?
Responses to OP comments
But that must mean that this proxy object is being passed to
__init__() when running super().__init__() right?
Wrong. The proxy object is like a package name, such as calling math.sqrt(). You're not passing math to sqrt, you're using it to denote which sqrt you're using. If you wanted to pass the proxy to __init__, the call would be __init__(super()). That call would be semantically ridiculous, of course.
When we have to actually pass in self which is the sc object in my example.
No, you are not passing in sc; that is the result of the object creation call (internal method __new__), which includes an invocation of init. For __init__, the self object is a new item created for you by the Python run-time system. For most class methods, that first argument (called self out of convention, this in other languages) is the object that invoked the method.
This means that in the line super().__init__(), super() is returning the current object which is then implicitly passed to the superclass' __init__() method. Is this accurate or am I missing something here?
>>> help(super)
super() -> same as super(__class__, <first argument>)
super call returns a proxy/wrapper object which remembers:
The instance invoking super()
The class of the calling object
The class that's invoking super()
This is perfectly sound. super always fetches the attribute of the next class in the hierarchy ( really the MRO) that has the attribute that you're looking for. So it's not returning the current object, but rather and more accurately, it returns an object that remembers enough information to search for attributes higher in the class hierarchy.
What exactly is being passed to __init__() and how? We are calling it on super() so whatever this is returning should be getting passed to the __init__() method from what I understand about Python so far.
You're almost right. But super loves to play tricks on us. super class defines __getattribute__, this method is responsible for attribute search. When you do something like: super().y(), super.__getattribute__ gets called searching for y. Once it finds y it passes the instance that's invoking the super call to y. Also, super has __get__ method, which makes it a descriptor, I'll omit the details of descriptors here, refer to the documentation to know more. This answers your second question as well, as to why self isn't passed explicitly.
*Note: super is a little bit different and relies on some magic. Almost for all other classes, the behavior is the same. That is:
a = A() # A is a class
a.y() # same as A.y(a), self is a
But super is different:
class A:
def y(self):
return self
class B(A):
def y(self)
return super().y() # equivalent to: A.y(self)
b = B()
b.y() is b # True: returns b not super(), self is b not super()
I wrote a simple test to investigate what CPython does for super:
class A:
pass
class B(A):
def f(self):
return super()
#classmethod
def g(cls):
return super()
def h(selfish):
selfish = B()
return super()
class C(B):
pass
c = C()
for method in 'fgh':
super_object = getattr(c, method)()
print(super_object, super_object.__self__, super_object.__self_class__, super_object.__thisclass__) # (These methods were found using dir.)
The zero-argument super call returns an object that stores three things:
__self__ stores the object whose name matches the first parameter of the method—even if that name has been reassigned.
__self_class__ stores its type, or itself in the case of a class method.
__thisclass__ stores the class in which the method is defined.
(It is unfortunate that __thisclass__ was implemented this way rather than fetching an attribute on the method because it makes it impossible to use the zero-argument form of super with meta-programming.)
The object returned by super implements getattribute, which forwards method calls to the type found in the __mro__ of __self_class__ one step after __thisclass__.
In Python 3.x what can I do with bar() that I cannot do with foo()?
class A:
def foo():
print("some code")
#staticmethod
def bar():
print("some code")
Note: I initially forgot to specify self as an argument to foo(), but I'm leaving the mistake there, since the answers andress that.
a staticmethod is a method that does not require an object as its first parameter. This means it is a method useful to the class itself and all instantiations of it, rather than just instances of it (object initialized as A().
What this means in practical terms, is that Python does not implicitly send the object itself as a parameter. Your first method will break once you call it:
>>> a.foo()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: foo() takes 0 positional arguments but 1 was given
This is because Python supplies object methods with the object itself as a first parameter. Hence the ubiquitous self argument:
def foo(self): #Proper signature
On the other hand,
A.bar()
will work just fine, and so will
a.bar()
The object is not supplied as a first argument. Use staticmethods for methods that are supposed to be helpful to the class and its instances, but do not require knowledge of either. Usually I use these as utility functions.
Note there is a third version, a classmethod, which is similar to a regular method in that it accepts a first parameter by default - the class of the caller. In this case the minimal signature is
#classmethod
def operateOnClass(cls):
Use this to make changes that affect all instances, such as changing class variables.
bar() can be called from an uninstantiated class object. foo() needs to be fed self as an argument, and as such can only be called from an object already declared as an instance of class A
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.
What is the difference between the following class methods?
Is it that one is static and the other is not?
class Test(object):
def method_one(self):
print "Called method_one"
def method_two():
print "Called method_two"
a_test = Test()
a_test.method_one()
a_test.method_two()
In Python, there is a distinction between bound and unbound methods.
Basically, a call to a member function (like method_one), a bound function
a_test.method_one()
is translated to
Test.method_one(a_test)
i.e. a call to an unbound method. Because of that, a call to your version of method_two will fail with a TypeError
>>> a_test = Test()
>>> a_test.method_two()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: method_two() takes no arguments (1 given)
You can change the behavior of a method using a decorator
class Test(object):
def method_one(self):
print "Called method_one"
#staticmethod
def method_two():
print "Called method two"
The decorator tells the built-in default metaclass type (the class of a class, cf. this question) to not create bound methods for method_two.
Now, you can invoke static method both on an instance or on the class directly:
>>> a_test = Test()
>>> a_test.method_one()
Called method_one
>>> a_test.method_two()
Called method_two
>>> Test.method_two()
Called method_two
Methods in Python are a very, very simple thing once you understood the basics of the descriptor system. Imagine the following class:
class C(object):
def foo(self):
pass
Now let's have a look at that class in the shell:
>>> C.foo
<unbound method C.foo>
>>> C.__dict__['foo']
<function foo at 0x17d05b0>
As you can see if you access the foo attribute on the class you get back an unbound method, however inside the class storage (the dict) there is a function. Why's that? The reason for this is that the class of your class implements a __getattribute__ that resolves descriptors. Sounds complex, but is not. C.foo is roughly equivalent to this code in that special case:
>>> C.__dict__['foo'].__get__(None, C)
<unbound method C.foo>
That's because functions have a __get__ method which makes them descriptors. If you have an instance of a class it's nearly the same, just that None is the class instance:
>>> c = C()
>>> C.__dict__['foo'].__get__(c, C)
<bound method C.foo of <__main__.C object at 0x17bd4d0>>
Now why does Python do that? Because the method object binds the first parameter of a function to the instance of the class. That's where self comes from. Now sometimes you don't want your class to make a function a method, that's where staticmethod comes into play:
class C(object):
#staticmethod
def foo():
pass
The staticmethod decorator wraps your class and implements a dummy __get__ that returns the wrapped function as function and not as a method:
>>> C.__dict__['foo'].__get__(None, C)
<function foo at 0x17d0c30>
Hope that explains it.
When you call a class member, Python automatically uses a reference to the object as the first parameter. The variable self actually means nothing, it's just a coding convention. You could call it gargaloo if you wanted. That said, the call to method_two would raise a TypeError, because Python is automatically trying to pass a parameter (the reference to its parent object) to a method that was defined as having no parameters.
To actually make it work, you could append this to your class definition:
method_two = staticmethod(method_two)
or you could use the #staticmethod function decorator.
>>> class Class(object):
... def __init__(self):
... self.i = 0
... def instance_method(self):
... self.i += 1
... print self.i
... c = 0
... #classmethod
... def class_method(cls):
... cls.c += 1
... print cls.c
... #staticmethod
... def static_method(s):
... s += 1
... print s
...
>>> a = Class()
>>> a.class_method()
1
>>> Class.class_method() # The class shares this value across instances
2
>>> a.instance_method()
1
>>> Class.instance_method() # The class cannot use an instance method
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unbound method instance_method() must be called with Class instance as first argument (got nothing instead)
>>> Class.instance_method(a)
2
>>> b = 0
>>> a.static_method(b)
1
>>> a.static_method(a.c) # Static method does not have direct access to
>>> # class or instance properties.
3
>>> Class.c # a.c above was passed by value and not by reference.
2
>>> a.c
2
>>> a.c = 5 # The connection between the instance
>>> Class.c # and its class is weak as seen here.
2
>>> Class.class_method()
3
>>> a.c
5
method_two won't work because you're defining a member function but not telling it what the function is a member of. If you execute the last line you'll get:
>>> a_test.method_two()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: method_two() takes no arguments (1 given)
If you're defining member functions for a class the first argument must always be 'self'.
Accurate explanation from Armin Ronacher above, expanding on his answers so that beginners like me understand it well:
Difference in the methods defined in a class, whether static or instance method(there is yet another type - class method - not discussed here so skipping it), lay in the fact whether they are somehow bound to the class instance or not. For example, say whether the method receives a reference to the class instance during runtime
class C:
a = []
def foo(self):
pass
C # this is the class object
C.a # is a list object (class property object)
C.foo # is a function object (class property object)
c = C()
c # this is the class instance
The __dict__ dictionary property of the class object holds the reference to all the properties and methods of a class object and thus
>>> C.__dict__['foo']
<function foo at 0x17d05b0>
the method foo is accessible as above. An important point to note here is that everything in python is an object and so references in the dictionary above are themselves pointing to other objects. Let me call them Class Property Objects - or as CPO within the scope of my answer for brevity.
If a CPO is a descriptor, then python interpretor calls the __get__() method of the CPO to access the value it contains.
In order to determine if a CPO is a descriptor, python interpretor checks if it implements the descriptor protocol. To implement descriptor protocol is to implement 3 methods
def __get__(self, instance, owner)
def __set__(self, instance, value)
def __delete__(self, instance)
for e.g.
>>> C.__dict__['foo'].__get__(c, C)
where
self is the CPO (it could be an instance of list, str, function etc) and is supplied by the runtime
instance is the instance of the class where this CPO is defined (the object 'c' above) and needs to be explicity supplied by us
owner is the class where this CPO is defined(the class object 'C' above) and needs to be supplied by us. However this is because we are calling it on the CPO. when we call it on the instance, we dont need to supply this since the runtime can supply the instance or its class(polymorphism)
value is the intended value for the CPO and needs to be supplied by us
Not all CPO are descriptors. For example
>>> C.__dict__['foo'].__get__(None, C)
<function C.foo at 0x10a72f510>
>>> C.__dict__['a'].__get__(None, C)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'list' object has no attribute '__get__'
This is because the list class doesnt implement the descriptor protocol.
Thus the argument self in c.foo(self) is required because its method signature is actually this C.__dict__['foo'].__get__(c, C) (as explained above, C is not needed as it can be found out or polymorphed)
And this is also why you get a TypeError if you dont pass that required instance argument.
If you notice the method is still referenced via the class Object C and the binding with the class instance is achieved via passing a context in the form of the instance object into this function.
This is pretty awesome since if you chose to keep no context or no binding to the instance, all that was needed was to write a class to wrap the descriptor CPO and override its __get__() method to require no context.
This new class is what we call a decorator and is applied via the keyword #staticmethod
class C(object):
#staticmethod
def foo():
pass
The absence of context in the new wrapped CPO foo doesnt throw an error and can be verified as follows:
>>> C.__dict__['foo'].__get__(None, C)
<function foo at 0x17d0c30>
Use case of a static method is more of a namespacing and code maintainability one(taking it out of a class and making it available throughout the module etc).
It maybe better to write static methods rather than instance methods whenever possible, unless ofcourse you need to contexualise the methods(like access instance variables, class variables etc). One reason is to ease garbage collection by not keeping unwanted reference to objects.
that is an error.
first of all, first line should be like this (be careful of capitals)
class Test(object):
Whenever you call a method of a class, it gets itself as the first argument (hence the name self) and method_two gives this error
>>> a.method_two()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: method_two() takes no arguments (1 given)
The second one won't work because when you call it like that python internally tries to call it with the a_test instance as the first argument, but your method_two doesn't accept any arguments, so it wont work, you'll get a runtime error.
If you want the equivalent of a static method you can use a class method.
There's much less need for class methods in Python than static methods in languages like Java or C#. Most often the best solution is to use a method in the module, outside a class definition, those work more efficiently than class methods.
The call to method_two will throw an exception for not accepting the self parameter the Python runtime will automatically pass it.
If you want to create a static method in a Python class, decorate it with the staticmethod decorator.
Class Test(Object):
#staticmethod
def method_two():
print "Called method_two"
Test.method_two()
Please read this docs from the Guido First Class everything Clearly explained how Unbound, Bound methods are born.
Bound method = instance method
Unbound method = static method.
The definition of method_two is invalid. When you call method_two, you'll get TypeError: method_two() takes 0 positional arguments but 1 was given from the interpreter.
An instance method is a bounded function when you call it like a_test.method_two(). It automatically accepts self, which points to an instance of Test, as its first parameter. Through the self parameter, an instance method can freely access attributes and modify them on the same object.
Unbound Methods
Unbound methods are methods that are not bound to any particular class instance yet.
Bound Methods
Bound methods are the ones which are bound to a specific instance of a class.
As its documented here, self can refer to different things depending on the function is bound, unbound or static.
Take a look at the following example:
class MyClass:
def some_method(self):
return self # For the sake of the example
>>> MyClass().some_method()
<__main__.MyClass object at 0x10e8e43a0># This can also be written as:>>> obj = MyClass()
>>> obj.some_method()
<__main__.MyClass object at 0x10ea12bb0>
# Bound method call:
>>> obj.some_method(10)
TypeError: some_method() takes 1 positional argument but 2 were given
# WHY IT DIDN'T WORK?
# obj.some_method(10) bound call translated as
# MyClass.some_method(obj, 10) unbound method and it takes 2
# arguments now instead of 1
# ----- USING THE UNBOUND METHOD ------
>>> MyClass.some_method(10)
10
Since we did not use the class instance — obj — on the last call, we can kinda say it looks like a static method.
If so, what is the difference between MyClass.some_method(10) call and a call to a static function decorated with a #staticmethod decorator?
By using the decorator, we explicitly make it clear that the method will be used without creating an instance for it first. Normally one would not expect the class member methods to be used without the instance and accesing them can cause possible errors depending on the structure of the method.
Also, by adding the #staticmethod decorator, we are making it possible to be reached through an object as well.
class MyClass:
def some_method(self):
return self
#staticmethod
def some_static_method(number):
return number
>>> MyClass.some_static_method(10) # without an instance
10
>>> MyClass().some_static_method(10) # Calling through an instance
10
You can’t do the above example with the instance methods. You may survive the first one (as we did before) but the second one will be translated into an unbound call MyClass.some_method(obj, 10) which will raise a TypeError since the instance method takes one argument and you unintentionally tried to pass two.
Then, you might say, “if I can call static methods through both an instance and a class, MyClass.some_static_method and MyClass().some_static_method should be the same methods.” Yes!
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.