Static methods in Python?

Yes, check out the staticmethod decorator:

>>> class C:
...     @staticmethod
...     def hello():
...             print "Hello World"
...
>>> C.hello()
Hello World

You don’t really need to use the @staticmethod decorator. Just declaring a method (that doesn’t expect the self parameter) and call it from the class. The decorator is only there in case you want to be able to call it from an instance as well (which was not what you wanted to do)

Mostly, you just use functions though…

I think that Steven is actually right. To answer the original question, then, in order to set up a class method, simply assume that the first argument is not going to be a calling instance, and then make sure that you only call the method from the class.

(Note that this answer refers to Python 3.x. In Python 2.x you’ll get a TypeError for calling the method on the class itself.)

For example:

class Dog:
    count = 0 # this is a class variable
    dogs = [] # this is a class variable

    def __init__(self, name):
        self.name = name #self.name is an instance variable
        Dog.count += 1
        Dog.dogs.append(name)

    def bark(self, n): # this is an instance method
        print("{} says: {}".format(self.name, "woof! " * n))

    def rollCall(n): #this is implicitly a class method (see comments below)
        print("There are {} dogs.".format(Dog.count))
        if n >= len(Dog.dogs) or n < 0:
            print("They are:")
            for dog in Dog.dogs:
                print("  {}".format(dog))
        else:
            print("The dog indexed at {} is {}.".format(n, Dog.dogs[n]))

fido = Dog("Fido")
fido.bark(3)
Dog.rollCall(-1)
rex = Dog("Rex")
Dog.rollCall(0)

In this code, the “rollCall” method assumes that the first argument is not an instance (as it would be if it were called by an instance instead of a class). As long as “rollCall” is called from the class rather than an instance, the code will work fine. If we try to call “rollCall” from an instance, e.g.:

rex.rollCall(-1)

however, it would cause an exception to be raised because it would send two arguments: itself and -1, and “rollCall” is only defined to accept one argument.

Incidentally, rex.rollCall() would send the correct number of arguments, but would also cause an exception to be raised because now n would be representing a Dog instance (i.e., rex) when the function expects n to be numerical.

This is where the decoration comes in:
If we precede the “rollCall” method with

@staticmethod

then, by explicitly stating that the method is static, we can even call it from an instance. Now,

rex.rollCall(-1)

would work. The insertion of @staticmethod before a method definition, then, stops an instance from sending itself as an argument.

You can verify this by trying the following code with and without the @staticmethod line commented out.

class Dog:
    count = 0 # this is a class variable
    dogs = [] # this is a class variable

    def __init__(self, name):
        self.name = name #self.name is an instance variable
        Dog.count += 1
        Dog.dogs.append(name)

    def bark(self, n): # this is an instance method
        print("{} says: {}".format(self.name, "woof! " * n))

    @staticmethod
    def rollCall(n):
        print("There are {} dogs.".format(Dog.count))
        if n >= len(Dog.dogs) or n < 0:
            print("They are:")
            for dog in Dog.dogs:
                print("  {}".format(dog))
        else:
            print("The dog indexed at {} is {}.".format(n, Dog.dogs[n]))


fido = Dog("Fido")
fido.bark(3)
Dog.rollCall(-1)
rex = Dog("Rex")
Dog.rollCall(0)
rex.rollCall(-1)

Aside from the particularities of how static method objects behave, there is a certain kind of beauty you can strike with them when it comes to organizing your module-level code.

# garden.py
def trim(a):
    pass

def strip(a):
    pass

def bunch(a, b):
    pass

def _foo(foo):
    pass

class powertools(object):
    """
    Provides much regarded gardening power tools.
    """
    @staticmethod
    def answer_to_the_ultimate_question_of_life_the_universe_and_everything():
        return 42

    @staticmethod
    def random():
        return 13

    @staticmethod
    def promise():
        return True

def _bar(baz, quux):
    pass

class _Dice(object):
    pass

class _6d(_Dice):
    pass

class _12d(_Dice):
    pass

class _Smarter:
    pass

class _MagicalPonies:
    pass

class _Samurai:
    pass

class Foo(_6d, _Samurai):
    pass

class Bar(_12d, _Smarter, _MagicalPonies):
    pass

…

# tests.py
import unittest
import garden

class GardenTests(unittest.TestCase):
    pass

class PowertoolsTests(unittest.TestCase):
    pass

class FooTests(unittest.TestCase):
    pass

class BarTests(unittest.TestCase):
    pass

…

# interactive.py
from garden import trim, bunch, Foo

f = trim(Foo())
bunch(f, Foo())

…

# my_garden.py
import garden
from garden import powertools

class _Cowboy(garden._Samurai):
    def hit():
        return powertools.promise() and powertools.random() or 0

class Foo(_Cowboy, garden.Foo):
    pass

It now becomes a bit more intuitive and self-documenting in which context certain components are meant to be used and it pans out ideally for naming distinct test cases as well as having a straightforward approach to how test modules map to actual modules under tests for purists.

I frequently find it viable to apply this approach to organizing a project’s utility code. Quite often, people immediately rush and create a utils package and end up with 9 modules of which one has 120 LOC and the rest are two dozen LOC at best. I prefer to start with this and convert it to a package and create modules only for the beasts that truly deserve them:

# utils.py
class socket(object):
    @staticmethod
    def check_if_port_available(port):
        pass

    @staticmethod
    def get_free_port(port)
        pass

class image(object):
    @staticmethod
    def to_rgb(image):
        pass

    @staticmethod
    def to_cmyk(image):
        pass

Perhaps the simplest option is just to put those functions outside of the class:

class Dog(object):
    def __init__(self, name):
        self.name = name

    def bark(self):
        if self.name == "Doggy":
            return barking_sound()
        else:
            return "yip yip"

def barking_sound():
    return "woof woof"

Using this method, functions which modify or use internal object state (have side effects) can be kept in the class, and the reusable utility functions can be moved outside.

Let’s say this file is called dogs.py. To use these, you’d call dogs.barking_sound() instead of dogs.Dog.barking_sound.

If you really need a static method to be part of the class, you can use the staticmethod decorator.

Static methods in Python?

Is it possible to have static methods in Python so I can call them
without initializing a class, like:

ClassName.StaticMethod()

Yes, static methods can be created like this (although it’s a bit more Pythonic to use underscores instead of CamelCase for methods):

class ClassName(object):

    @staticmethod
    def static_method(kwarg1=None):
        '''return a value that is a function of kwarg1'''

The above uses the decorator syntax. This syntax is equivalent to

class ClassName(object):

    def static_method(kwarg1=None):
        '''return a value that is a function of kwarg1'''

    static_method = staticmethod(static_method)

This can be used just as you described:

ClassName.static_method()

A builtin example of a static method is str.maketrans() in Python 3, which was a function in the string module in Python 2.

Another option that can be used as you describe is the classmethod, the difference is that the classmethod gets the class as an implicit first argument, and if subclassed, then it gets the subclass as the implicit first argument.

class ClassName(object):

    @classmethod
    def class_method(cls, kwarg1=None):
        '''return a value that is a function of the class and kwarg1'''

Note that cls is not a required name for the first argument, but most experienced Python coders will consider it badly done if you use anything else.

These are typically used as alternative constructors.

new_instance = ClassName.class_method()

A builtin example is dict.fromkeys():

new_dict = dict.fromkeys(['key1', 'key2'])

I encounter this question from time to time. The use case and example that I am fond of is:

jeffs@jeffs-desktop:/home/jeffs  $ python36
Python 3.6.1 (default, Sep  7 2017, 16:36:03) 
[GCC 6.3.0 20170406] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import cmath
>>> print(cmath.sqrt(-4))
2j
>>>
>>> dir(cmath)
['__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atanh', 'cos', 'cosh', 'e', 'exp', 'inf', 'infj', 'isclose', 'isfinite', 'isinf', 'isnan', 'log', 'log10', 'nan', 'nanj', 'phase', 'pi', 'polar', 'rect', 'sin', 'sinh', 'sqrt', 'tan', 'tanh', 'tau']
>>> 

It does not make sense to create an object of class cmath, because there is no state in a cmath object. However, cmath is a collection of methods that are all related in some way. In my example above, all of the functions in cmath act on complex numbers in some way.

Python Static methods can be created in two ways.

1. Using staticmethod()

   class Arithmetic:
       def add(x, y):
           return x + y
   # create add static method
   Arithmetic.add = staticmethod(Arithmetic.add)
   
   print('Result:', Arithmetic.add(15, 10))
   

Output:

Result: 25

2. Using @staticmethod

   class Arithmetic:
   
   # create add static method
   @staticmethod
   def add(x, y):
       return x + y
   
   print('Result:', Arithmetic.add(15, 10))
   

Output:

Result: 25

So, static methods are the methods which can be called without creating the object of a class.
For Example :-

    @staticmethod
    def add(a, b):
        return a + b

b = A.add(12,12)
print b

In the above example method add is called by the class name A not the object name.

Summarizing others’ answers and adding, there are many ways to declare Static Methods or Variables in python.

1. Using staticmethod() as a decorator:
   One can simply put a decorator above a method(function) declared to make it a static method. For eg.

class Calculator:
    @staticmethod
    def multiply(n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 * n2 * Res

print(Calculator.multiply(1, 2, 3, 4))              # 24

2. Using staticmethod() as a parameter function:
   This method can receive an argument which is of function type, and it returns a static version of the function passed. For eg.

class Calculator:
    def add(n1, n2, *args):
        return n1 + n2 + sum(args)

Calculator.add = staticmethod(Calculator.add)
print(Calculator.add(1, 2, 3, 4))                   # 10

3. Using classmethod() as a decorator:
   @classmethod has similar effect on a function as @staticmethod has, but
   this time, an additional argument is needed to be accepted in the function (similar to self parameter for instance variables). For eg.

class Calculator:
    num = 0
    def __init__(self, digits) -> None:
        Calculator.num = int(''.join(digits))

    @classmethod
    def get_digits(cls, num):
        digits = list(str(num))
        calc = cls(digits)
        return calc.num

print(Calculator.get_digits(314159))                # 314159

4. Using classmethod() as a parameter function:
   @classmethod can also be used as a parameter function, in case one doesn’t want to modify class definition. For eg.

class Calculator:
    def divide(cls, n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 / n2 / Res

Calculator.divide = classmethod(Calculator.divide)

print(Calculator.divide(15, 3, 5))                  # 1.0

5. Direct declaration
   A method/variable declared outside all other methods, but inside a class is automatically static.

class Calculator:   
    def subtract(n1, n2, *args):
        return n1 - n2 - sum(args)

print(Calculator.subtract(10, 2, 3, 4))             # 1

The whole program

class Calculator:
    num = 0
    def __init__(self, digits) -> None:
        Calculator.num = int(''.join(digits))
    
    
    @staticmethod
    def multiply(n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 * n2 * Res


    def add(n1, n2, *args):
        return n1 + n2 + sum(args)
    

    @classmethod
    def get_digits(cls, num):
        digits = list(str(num))
        calc = cls(digits)
        return calc.num


    def divide(cls, n1, n2, *args):
        Res = 1
        for num in args: Res *= num
        return n1 / n2 / Res


    def subtract(n1, n2, *args):
        return n1 - n2 - sum(args)
    



Calculator.add = staticmethod(Calculator.add)
Calculator.divide = classmethod(Calculator.divide)

print(Calculator.multiply(1, 2, 3, 4))              # 24
print(Calculator.add(1, 2, 3, 4))                   # 10
print(Calculator.get_digits(314159))                # 314159
print(Calculator.divide(15, 3, 5))                  # 1.0
print(Calculator.subtract(10, 2, 3, 4))             # 1

Refer to Python Documentation for mastering OOP in python.

You can use @staticmethod decorator to define a static method as shown below. In detail, I explain about @staticmethod decorator and @classmethod decorator in my answer for @classmethod vs @staticmethod in Python and also explain about instance method in my answer for What is an "instance method" in Python?:

class Person:
    @staticmethod # Here
    def test():
        print("Test")