within Static methods in Python?




static method python (8)

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

ClassName.StaticMethod ( )

In Python 3:

Here is another good to use non-static methods as they were static methods.

class Account:
# here is the main class

# a non-static method
def login(self, url, email, password):
    # as a convention self is passed as a 
    # placeholder for the class Object itself

    self.login_url = url
    self.user_email = email
    self.user_password = password

    print(login_url, user_email, user_password)

Call a non-static method as static

"""
* Referencing the Account.login(self, url, email, password)
* Just call the `Account` object as the self 
"""
Account.login(Account, "https://example.com/login", "[email protected]", "password_example")

:$ https://example.com/login [email protected] password_example

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.


Yep, using the staticmethod decorator

class MyClass(object):
    @staticmethod
    def the_static_method(x):
        print x

MyClass.the_static_method(2) # outputs 2

Note that some code might use the old method of defining a static method, using staticmethod as a function rather than a decorator. This should only be used if you have to support ancient versions of Python (2.2 and 2.3)

class MyClass(object):
    def the_static_method(x):
        print x
    the_static_method = staticmethod(the_static_method)

MyClass.the_static_method(2) # outputs 2

This is entirely identical to the first example (using @staticmethod), just not using the nice decorator syntax

Finally, use staticmethod() sparingly! There are very few situations where static-methods are necessary in Python, and I've seen them used many times where a separate "top-level" function would have been clearer.


The following is verbatim from the documentation::

A static method does not receive an implicit first argument. To declare a static method, use this idiom:

class C:
    @staticmethod
    def f(arg1, arg2, ...): ...

The @staticmethod form is a function decorator – see the description of function definitions in Function definitions for details.

It can be called either on the class (such as C.f()) or on an instance (such as C().f()). The instance is ignored except for its class.

Static methods in Python are similar to those found in Java or C++. For a more advanced concept, see classmethod().

For more information on static methods, consult the documentation on the standard type hierarchy in The standard type hierarchy.

New in version 2.2.

Changed in version 2.4: Function decorator syntax added.


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...


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 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

Yes, check out the staticmethod decorator:

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




static-methods