Python @staticmethod Decorator – What It Does and How to Use It

Maybe a bit of example code will help: Notice the difference in the call signatures of foo, class_foo and static_foo:

class A(object):
    def foo(self, x):
        print(f"executing foo({self}, {x})")

    @classmethod
    def class_foo(cls, x):
        print(f"executing class_foo({cls}, {x})")

    @staticmethod
    def static_foo(x):
        print(f"executing static_foo({x})")

a = A()

Below is the usual way an object instance calls a method. The object instance, a, is implicitly passed as the first argument.

a.foo(1)
# executing foo(<__main__.A object at 0xb7dbef0c>, 1)

With classmethods, the class of the object instance is implicitly passed as the first argument instead of self.

a.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)

You can also call class_foo using the class. In fact, if you define something to be a classmethod, it is probably because you intend to call it from the class rather than from a class instance. A.foo(1) would have raised a TypeError, but A.class_foo(1) works just fine:

A.class_foo(1)
# executing class_foo(<class '__main__.A'>, 1)

One use people have found for class methods is to create inheritable alternative constructors.

With staticmethods, neither self (the object instance) nor cls (the class) is implicitly passed as the first argument. They behave like plain functions except that you can call them from an instance or the class:

a.static_foo(1)
# executing static_foo(1)

A.static_foo('hi')
# executing static_foo(hi)

Staticmethods are used to group functions which have some logical connection with a class to the class.

foo is just a function, but when you call a.foo you don't just get the function, you get a "partially applied" version of the function with the object instance a bound as the first argument to the function. foo expects 2 arguments, while a.foo only expects 1 argument.

a is bound to foo. That is what is meant by the term "bound" below:

print(a.foo)
# <bound method A.foo of <__main__.A object at 0xb7d52f0c>>

With a.class_foo, a is not bound to class_foo, rather the class A is bound to class_foo.

print(a.class_foo)
# <bound method type.class_foo of <class '__main__.A'>>

Here, with a staticmethod, even though it is a method, a.static_foo just returns a good 'ole function with no arguments bound. static_foo expects 1 argument, and a.static_foo expects 1 argument too.

print(a.static_foo)
# <function static_foo at 0xb7d479cc>

And of course the same thing happens when you call static_foo with the class A instead.

print(A.static_foo)
# <function static_foo at 0xb7d479cc>

A staticmethod object is a descriptor. The magic you are missing is that Python calls the __get__ method when accessing the object as an attribute on a class or instance.

So accessing the object as C.foo results in Python translating that to C.__dict__['foo'].__get__(None, C), while instance_of_C.foo becomes type(instace_of_C).__dict__['foo'].__get__(instance_of_C, type(instance_of_C)).

The staticmethod object is defined in C code, but an equivalent in Python would be:

class staticmethod(object):
    def __init__(self, callable):
        self.f = callable
    def __get__(self, obj, type=None):
        return self.f
    @property
    def __func__(self):
        return self.f

where self.f is the original wrapped function.

All this is needed because functions are themselves descriptors too; it is the descriptor protocol that gives you method objects (see python bound and unbound method object for more details). Since they too have a __get__ method, without a staticmethod object wrapping the function, a functionobj.__get__ call produces a method object instead, passing in a self argument.

There is also a classmethod, which uses the second argument to descriptor.__get__ to bind a function to the class, and then there are property objects, which translate binding into a function call directly. See How does the @property decorator work?.