What is the difference between a method decorated with #staticmethod and one decorated with #classmethod?
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 is a method that knows nothing about the class or instance it was called on. It just gets the arguments that were passed, no implicit first argument. It is basically useless in Python -- you can just use a module function instead of a staticmethod.
A classmethod, on the other hand, is a method that gets passed the class it was called on, or the class of the instance it was called on, as first argument. This is useful when you want the method to be a factory for the class: since it gets the actual class it was called on as first argument, you can always instantiate the right class, even when subclasses are involved. Observe for instance how dict.fromkeys(), a classmethod, returns an instance of the subclass when called on a subclass:
>>> class DictSubclass(dict):
... def __repr__(self):
... return "DictSubclass"
...
>>> dict.fromkeys("abc")
{'a': None, 'c': None, 'b': None}
>>> DictSubclass.fromkeys("abc")
DictSubclass
>>>
Basically #classmethod makes a method whose first argument is the class it's called from (rather than the class instance), #staticmethod does not have any implicit arguments.
To decide whether to use #staticmethod or #classmethod you have to look inside your method. If your method accesses other variables/methods in your class then use #classmethod. On the other hand, if your method does not touches any other parts of the class then use #staticmethod.
class Apple:
_counter = 0
#staticmethod
def about_apple():
print('Apple is good for you.')
# note you can still access other member of the class
# but you have to use the class instance
# which is not very nice, because you have repeat yourself
#
# For example:
# #staticmethod
# print('Number of apples have been juiced: %s' % Apple._counter)
#
# #classmethod
# print('Number of apples have been juiced: %s' % cls._counter)
#
# #classmethod is especially useful when you move your function to another class,
# you don't have to rename the referenced class
#classmethod
def make_apple_juice(cls, number_of_apples):
print('Making juice:')
for i in range(number_of_apples):
cls._juice_this(i)
#classmethod
def _juice_this(cls, apple):
print('Juicing apple %d...' % apple)
cls._counter += 1
Official python docs:
#classmethod
A class method receives the class as
implicit first argument, just like an
instance method receives the instance.
To declare a class method, use this
idiom:
class C:
#classmethod
def f(cls, arg1, arg2, ...): ...
The #classmethod 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. If a
class method is called for a derived
class, the derived class object is
passed as the implied first argument.
Class methods are different than C++
or Java static methods. If you want
those, see staticmethod() in this
section.
#staticmethod
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() in this section.
Here is a short article on this question
#staticmethod function is nothing more than a function defined inside a class. It is callable without instantiating the class first. It’s definition is immutable via inheritance.
#classmethod function also callable without instantiating the class, but its definition follows Sub class, not Parent class, via inheritance. That’s because the first argument for #classmethod function must always be cls (class).
What is the difference between #staticmethod and #classmethod in Python?
You may have seen Python code like this pseudocode, which demonstrates the signatures of the various method types and provides a docstring to explain each:
class Foo(object):
def a_normal_instance_method(self, arg_1, kwarg_2=None):
'''
Return a value that is a function of the instance with its
attributes, and other arguments such as arg_1 and kwarg2
'''
#staticmethod
def a_static_method(arg_0):
'''
Return a value that is a function of arg_0. It does not know the
instance or class it is called from.
'''
#classmethod
def a_class_method(cls, arg1):
'''
Return a value that is a function of the class and other arguments.
respects subclassing, it is called with the class it is called from.
'''
The Normal Instance Method
First I'll explain a_normal_instance_method. This is precisely called an "instance method". When an instance method is used, it is used as a partial function (as opposed to a total function, defined for all values when viewed in source code) that is, when used, the first of the arguments is predefined as the instance of the object, with all of its given attributes. It has the instance of the object bound to it, and it must be called from an instance of the object. Typically, it will access various attributes of the instance.
For example, this is an instance of a string:
', '
if we use the instance method, join on this string, to join another iterable,
it quite obviously is a function of the instance, in addition to being a function of the iterable list, ['a', 'b', 'c']:
>>> ', '.join(['a', 'b', 'c'])
'a, b, c'
Bound methods
Instance methods can be bound via a dotted lookup for use later.
For example, this binds the str.join method to the ':' instance:
>>> join_with_colons = ':'.join
And later we can use this as a function that already has the first argument bound to it. In this way, it works like a partial function on the instance:
>>> join_with_colons('abcde')
'a:b:c:d:e'
>>> join_with_colons(['FF', 'FF', 'FF', 'FF', 'FF', 'FF'])
'FF:FF:FF:FF:FF:FF'
Static Method
The static method does not take the instance as an argument.
It is very similar to a module level function.
However, a module level function must live in the module and be specially imported to other places where it is used.
If it is attached to the object, however, it will follow the object conveniently through importing and inheritance as well.
An example of a static method is str.maketrans, moved from the string module in Python 3. It makes a translation table suitable for consumption by str.translate. It does seem rather silly when used from an instance of a string, as demonstrated below, but importing the function from the string module is rather clumsy, and it's nice to be able to call it from the class, as in str.maketrans
# demonstrate same function whether called from instance or not:
>>> ', '.maketrans('ABC', 'abc')
{65: 97, 66: 98, 67: 99}
>>> str.maketrans('ABC', 'abc')
{65: 97, 66: 98, 67: 99}
In python 2, you have to import this function from the increasingly less useful string module:
>>> import string
>>> 'ABCDEFG'.translate(string.maketrans('ABC', 'abc'))
'abcDEFG'
Class Method
A class method is a similar to an instance method in that it takes an implicit first argument, but instead of taking the instance, it takes the class. Frequently these are used as alternative constructors for better semantic usage and it will support inheritance.
The most canonical example of a builtin classmethod is dict.fromkeys. It is used as an alternative constructor of dict, (well suited for when you know what your keys are and want a default value for them.)
>>> dict.fromkeys(['a', 'b', 'c'])
{'c': None, 'b': None, 'a': None}
When we subclass dict, we can use the same constructor, which creates an instance of the subclass.
>>> class MyDict(dict): 'A dict subclass, use to demo classmethods'
>>> md = MyDict.fromkeys(['a', 'b', 'c'])
>>> md
{'a': None, 'c': None, 'b': None}
>>> type(md)
<class '__main__.MyDict'>
See the pandas source code for other similar examples of alternative constructors, and see also the official Python documentation on classmethod and staticmethod.
I started learning programming language with C++ and then Java and then Python and so this question bothered me a lot as well, until I understood the simple usage of each.
Class Method: Python unlike Java and C++ doesn't have constructor overloading. And so to achieve this you could use classmethod. Following example will explain this
Let's consider we have a Person class which takes two arguments first_name and last_name and creates the instance of Person.
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
Now, if the requirement comes where you need to create a class using a single name only, just a first_name, you can't do something like this in Python.
This will give you an error when you will try to create an object (instance).
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
def __init__(self, first_name):
self.first_name = first_name
However, you could achieve the same thing using #classmethod as mentioned below
class Person(object):
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
#classmethod
def get_person(cls, first_name):
return cls(first_name, "")
Static Method: This is rather simple, it's not bound to instance or class and you can simply call that using class name.
So let's say in above example you need a validation that first_name should not exceed 20 characters, you can simply do this.
#staticmethod
def validate_name(name):
return len(name) <= 20
and you could simply call using class name
Person.validate_name("Gaurang Shah")
Only the first argument differs:
normal method: the current object is automatically passed as an (additional) first argument
classmethod: the class of the current object is automatically passed as an (additional) fist argument
staticmethod: no extra arguments are automatically passed. What you passed to the function is what you get.
In more detail...
normal method
The "standard" method, as in every object oriented language. When an object's method is called, it is automatically given an extra argument self as its first argument. That is, method
def f(self, x, y)
must be called with 2 arguments. self is automatically passed, and it is the object itself. Similar to the this that magically appears in eg. java/c++, only in python it is shown explicitly.
actually, the first argument does not have to be called self, but it's the standard convention, so keep it
class method
When the method is decorated
#classmethod
def f(cls, x, y)
the automatically provided argument is not self, but the class of self.
static method
When the method is decorated
#staticmethod
def f(x, y)
the method is not given any automatic argument at all. It is only given the parameters that it is called with.
usages
classmethod is mostly used for alternative constructors.
staticmethod does not use the state of the object, or even the structure of the class itself. It could be a function external to a class. It only put inside the class for grouping functions with similar functionality (for example, like Java's Math class static methods)
class Point
def __init__(self, x, y):
self.x = x
self.y = y
#classmethod
def frompolar(cls, radius, angle):
"""The `cls` argument is the `Point` class itself"""
return cls(radius * cos(angle), radius * sin(angle))
#staticmethod
def angle(x, y):
"""this could be outside the class, but we put it here
just because we think it is logically related to the class."""
return atan(y, x)
p1 = Point(3, 2)
p2 = Point.frompolar(3, pi/4)
angle = Point.angle(3, 2)
I think a better question is "When would you use #classmethod vs #staticmethod?"
#classmethod allows you easy access to private members that are associated to the class definition. this is a great way to do singletons, or factory classes that control the number of instances of the created objects exist.
#staticmethod provides marginal performance gains, but I have yet to see a productive use of a static method within a class that couldn't be achieved as a standalone function outside the class.
Static Methods:
Simple functions with no self argument.
Work on class attributes; not on instance attributes.
Can be called through both class and instance.
The built-in function staticmethod()is used to create them.
Benefits of Static Methods:
It localizes the function name in the classscope
It moves the function code closer to where it is used
More convenient to import versus module-level functions since each method does not have to be specially imported
#staticmethod
def some_static_method(*args, **kwds):
pass
Class Methods:
Functions that have first argument as classname.
Can be called through both class and instance.
These are created with classmethod in-built function.
#classmethod
def some_class_method(cls, *args, **kwds):
pass
#decorators were added in python 2.4 If you're using python < 2.4 you can use the classmethod() and staticmethod() function.
For example, if you want to create a factory method (A function returning an instance of a different implementation of a class depending on what argument it gets) you can do something like:
class Cluster(object):
def _is_cluster_for(cls, name):
"""
see if this class is the cluster with this name
this is a classmethod
"""
return cls.__name__ == name
_is_cluster_for = classmethod(_is_cluster_for)
#static method
def getCluster(name):
"""
static factory method, should be in Cluster class
returns a cluster object for the given name
"""
for cls in Cluster.__subclasses__():
if cls._is_cluster_for(name):
return cls()
getCluster = staticmethod(getCluster)
Also observe that this is a good example for using a classmethod and a static method,
The static method clearly belongs to the class, since it uses the class Cluster internally.
The classmethod only needs information about the class, and no instance of the object.
Another benefit of making the _is_cluster_for method a classmethod is so a subclass can decide to change it's implementation, maybe because it is pretty generic and can handle more than one type of cluster, so just checking the name of the class would not be enough.
Let me tell the similarity between a method decorated with #classmethod vs #staticmethod first.
Similarity: Both of them can be called on the Class itself, rather than just the instance of the class. So, both of them in a sense are Class's methods.
Difference: A classmethod will receive the class itself as the first argument, while a staticmethod does not.
So a static method is, in a sense, not bound to the Class itself and is just hanging in there just because it may have a related functionality.
>>> class Klaus:
#classmethod
def classmthd(*args):
return args
#staticmethod
def staticmthd(*args):
return args
# 1. Call classmethod without any arg
>>> Klaus.classmthd()
(__main__.Klaus,) # the class gets passed as the first argument
# 2. Call classmethod with 1 arg
>>> Klaus.classmthd('chumma')
(__main__.Klaus, 'chumma')
# 3. Call staticmethod without any arg
>>> Klaus.staticmthd()
()
# 4. Call staticmethod with 1 arg
>>> Klaus.staticmthd('chumma')
('chumma',)
#staticmethod just disables the default function as method descriptor. classmethod wraps your function in a container callable that passes a reference to the owning class as first argument:
>>> class C(object):
... pass
...
>>> def f():
... pass
...
>>> staticmethod(f).__get__(None, C)
<function f at 0x5c1cf0>
>>> classmethod(f).__get__(None, C)
<bound method type.f of <class '__main__.C'>>
As a matter of fact, classmethod has a runtime overhead but makes it possible to access the owning class. Alternatively I recommend using a metaclass and putting the class methods on that metaclass:
>>> class CMeta(type):
... def foo(cls):
... print cls
...
>>> class C(object):
... __metaclass__ = CMeta
...
>>> C.foo()
<class '__main__.C'>
Another consideration with respect to staticmethod vs classmethod comes up with inheritance. Say you have the following class:
class Foo(object):
#staticmethod
def bar():
return "In Foo"
And you then want to override bar() in a child class:
class Foo2(Foo):
#staticmethod
def bar():
return "In Foo2"
This works, but note that now the bar() implementation in the child class (Foo2) can no longer take advantage of anything specific to that class. For example, say Foo2 had a method called magic() that you want to use in the Foo2 implementation of bar():
class Foo2(Foo):
#staticmethod
def bar():
return "In Foo2"
#staticmethod
def magic():
return "Something useful you'd like to use in bar, but now can't"
The workaround here would be to call Foo2.magic() in bar(), but then you're repeating yourself (if the name of Foo2 changes, you'll have to remember to update that bar() method).
To me, this is a slight violation of the open/closed principle, since a decision made in Foo is impacting your ability to refactor common code in a derived class (ie it's less open to extension). If bar() were a classmethod we'd be fine:
class Foo(object):
#classmethod
def bar(cls):
return "In Foo"
class Foo2(Foo):
#classmethod
def bar(cls):
return "In Foo2 " + cls.magic()
#classmethod
def magic(cls):
return "MAGIC"
print Foo2().bar()
Gives: In Foo2 MAGIC
Also: historical note: Guido Van Rossum (Python's creator) once referred to staticmethod's as "an accident": https://mail.python.org/pipermail/python-ideas/2012-May/014969.html
we all know how limited static methods are. (They're basically an accident -- back in the Python 2.2 days when I was inventing new-style classes and descriptors, I meant to implement class methods but at first I didn't understand them and accidentally implemented static methods first. Then it was too late to remove them and only provide class methods.
Also: https://mail.python.org/pipermail/python-ideas/2016-July/041189.html
Honestly, staticmethod was something of a mistake -- I was trying to do something like Java class methods but once it was released I found what was really needed was classmethod. But it was too late to get rid of staticmethod.
The definitive guide on how to use static, class or abstract methods in Python is one good link for this topic, and summary it as following.
#staticmethod function is nothing more than a function defined inside a class. It is callable without instantiating the class first. It’s definition is immutable via inheritance.
Python does not have to instantiate a bound-method for object.
It eases the readability of the code, and it does not depend on the state of object itself;
#classmethod function also callable without instantiating the class, but its definition follows Sub class, not Parent class, via inheritance, can be overridden by subclass. That’s because the first argument for #classmethod function must always be cls (class).
Factory methods, that are used to create an instance for a class using for example some sort of pre-processing.
Static methods calling static methods: if you split a static methods in several static methods, you shouldn't hard-code the class name but use class methods
I will try to explain the basic difference using an example.
class A(object):
x = 0
def say_hi(self):
pass
#staticmethod
def say_hi_static():
pass
#classmethod
def say_hi_class(cls):
pass
def run_self(self):
self.x += 1
print self.x # outputs 1
self.say_hi()
self.say_hi_static()
self.say_hi_class()
#staticmethod
def run_static():
print A.x # outputs 0
# A.say_hi() # wrong
A.say_hi_static()
A.say_hi_class()
#classmethod
def run_class(cls):
print cls.x # outputs 0
# cls.say_hi() # wrong
cls.say_hi_static()
cls.say_hi_class()
1 - we can directly call static and classmethods without initializing
# A.run_self() # wrong
A.run_static()
A.run_class()
2- Static method cannot call self method but can call other static and classmethod
3- Static method belong to class and will not use object at all.
4- Class method are not bound to an object but to a class.
The difference occurs when there is inheritance.
Suppose that there are two classes-- Parent and Child. If one wants to use #staticmethod, print_name method should be written twice because the name of the class should be written in the print line.
class Parent:
_class_name = "Parent"
#staticmethod
def print_name():
print(Parent._class_name)
class Child(Parent):
_class_name = "Child"
#staticmethod
def print_name():
print(Child._class_name)
Parent.print_name()
Child.print_name()
However, for #classmethod, it is not required to write print_name method twice.
class Parent:
_class_name = "Parent"
#classmethod
def print_name(cls):
print(cls._class_name)
class Child(Parent):
_class_name = "Child"
Parent.print_name()
Child.print_name()
Python comes with several built-in decorators. The big three are:
#classmethod
#staticmethod
#property
First let's note that any function of a class can be called with instance of this class (after we initialized this class).
#classmethod is the way to call function not only as an instance of a class but also directly by the class itself as its first argument.
#staticmethod is a way of putting a function into a class (because it logically belongs there), while indicating that it does not require access to the class (so we don't need to use self in function definition).
Let's consider the following class:
class DecoratorTest(object):
def __init__(self):
pass
def doubler(self, x):
return x*2
#classmethod
def class_doubler(cls, x): # we need to use 'cls' instead of 'self'; 'cls' reference to the class instead of an instance of the class
return x*2
#staticmethod
def static_doubler(x): # no need adding 'self' here; static_doubler() could be just a function not inside the class
return x*2
Let's see how it works:
decor = DecoratorTest()
print(decor.doubler(5))
# 10
print(decor.class_doubler(5)) # a call with an instance of a class
# 10
print(DecoratorTest.class_doubler(5)) # a direct call by the class itself
# 10
# staticmethod could be called in the same way as classmethod.
print(decor.static_doubler(5)) # as an instance of the class
# 10
print(DecoratorTest.static_doubler(5)) # or as a direct call
# 10
Here you can see some use cases for those methods.
Bonus: you can read about #property decorator here
Instance Method:
+ Can modify object instance state
+ Can modify class state
Class Method:
- Can't modify object instance state
+ Can modify class state
Static Method:
- Can't modify object instance state
- Can't modify class state
class MyClass:
'''
Instance method has a mandatory first attribute self which represent the instance itself.
Instance method must be called by a instantiated instance.
'''
def method(self):
return 'instance method called', self
'''
Class method has a mandatory first attribute cls which represent the class itself.
Class method can be called by an instance or by the class directly.
Its most common using scenario is to define a factory method.
'''
#classmethod
def class_method(cls):
return 'class method called', cls
'''
Static method doesn’t have any attributes of instances or the class.
It also can be called by an instance or by the class directly.
Its most common using scenario is to define some helper or utility functions which are closely relative to the class.
'''
#staticmethod
def static_method():
return 'static method called'
obj = MyClass()
print(obj.method())
print(obj.class_method()) # MyClass.class_method()
print(obj.static_method()) # MyClass.static_method()
output:
('instance method called', <__main__.MyClass object at 0x100fb3940>)
('class method called', <class '__main__.MyClass'>)
static method called
The instance method we actually had access to the object instance , right so this was an instance off a my class object whereas with the class method we have access to the class itself. But not to any of the objects, because the class method doesn't really care about an object existing. However you can both call a class method and static method on an object instance. This is going to work it doesn't really make a difference, so again when you call static method here it's going to work and it's going to know which method you want to call.
The Static methods are used to do some utility tasks, and class methods are used for factory methods. The factory methods can return class objects for different use cases.
And finally, a short example for better understanding:
class Student:
def __init__(self, first_name, last_name):
self.first_name = first_name
self.last_name = last_name
#classmethod
def get_from_string(cls, name_string: str):
first_name, last_name = name_string.split()
if Student.validate_name(first_name) and Student.validate_name(last_name):
return cls(first_name, last_name)
else:
print('Invalid Names')
#staticmethod
def validate_name(name):
return len(name) <= 10
stackoverflow_student = Student.get_from_string('Name Surname')
print(stackoverflow_student.first_name) # Name
print(stackoverflow_student.last_name) # Surname
#classmethod : can be used to create a shared global access to all the instances created of that class..... like updating a record by multiple users....
I particulary found it use ful when creating singletons as well..:)
#static method: has nothing to do with the class or instance being associated with ...but for readability can use static method
My contribution demonstrates the difference amongst #classmethod, #staticmethod, and instance methods, including how an instance can indirectly call a #staticmethod. But instead of indirectly calling a #staticmethod from an instance, making it private may be more "pythonic." Getting something from a private method isn't demonstrated here but it's basically the same concept.
#!python3
from os import system
system('cls')
# % % % % % % % % % % % % % % % % % % % %
class DemoClass(object):
# instance methods need a class instance and
# can access the instance through 'self'
def instance_method_1(self):
return 'called from inside the instance_method_1()'
def instance_method_2(self):
# an instance outside the class indirectly calls the static_method
return self.static_method() + ' via instance_method_2()'
# class methods don't need a class instance, they can't access the
# instance (self) but they have access to the class itself via 'cls'
#classmethod
def class_method(cls):
return 'called from inside the class_method()'
# static methods don't have access to 'cls' or 'self', they work like
# regular functions but belong to the class' namespace
#staticmethod
def static_method():
return 'called from inside the static_method()'
# % % % % % % % % % % % % % % % % % % % %
# works even if the class hasn't been instantiated
print(DemoClass.class_method() + '\n')
''' called from inside the class_method() '''
# works even if the class hasn't been instantiated
print(DemoClass.static_method() + '\n')
''' called from inside the static_method() '''
# % % % % % % % % % % % % % % % % % % % %
# >>>>> all methods types can be called on a class instance <<<<<
# instantiate the class
democlassObj = DemoClass()
# call instance_method_1()
print(democlassObj.instance_method_1() + '\n')
''' called from inside the instance_method_1() '''
# # indirectly call static_method through instance_method_2(), there's really no use
# for this since a #staticmethod can be called whether the class has been
# instantiated or not
print(democlassObj.instance_method_2() + '\n')
''' called from inside the static_method() via instance_method_2() '''
# call class_method()
print(democlassObj.class_method() + '\n')
''' called from inside the class_method() '''
# call static_method()
print(democlassObj.static_method())
''' called from inside the static_method() '''
"""
# whether the class is instantiated or not, this doesn't work
print(DemoClass.instance_method_1() + '\n')
'''
TypeError: TypeError: unbound method instancemethod() must be called with
DemoClass instance as first argument (got nothing instead)
'''
"""
A class method receives the class as implicit first argument, just like an instance method receives the instance. It is a method which is bound to the class and not the object of the class.It has access to the state of the class as it takes a class parameter that points to the class and not the object instance. It can modify a class state that would apply across all the instances of the class. For example it can modify a class variable that will be applicable to all the instances.
On the other hand, a static method does not receive an implicit first argument, compared to class methods or instance methods. And can’t access or modify class state. It only belongs to the class because from design point of view that is the correct way. But in terms of functionality is not bound, at runtime, to the class.
as a guideline, use static methods as utilities, use class methods for example as factory . Or maybe to define a singleton. And use instance methods to model the state and behavior of instances.
Hope I was clear !
You might want to consider the difference between:
class A:
def foo(): # no self parameter, no decorator
pass
and
class B:
#staticmethod
def foo(): # no self parameter
pass
This has changed between python2 and python3:
python2:
>>> A.foo()
TypeError
>>> A().foo()
TypeError
>>> B.foo()
>>> B().foo()
python3:
>>> A.foo()
>>> A().foo()
TypeError
>>> B.foo()
>>> B().foo()
So using #staticmethod for methods only called directly from the class has become optional in python3. If you want to call them from both class and instance, you still need to use the #staticmethod decorator.
The other cases have been well covered by unutbus answer.
Class methods, as the name suggests, are used to make changes to classes and not the objects. To make changes to classes, they will modify the class attributes(not object attributes), since that is how you update classes.
This is the reason that class methods take the class(conventionally denoted by 'cls') as the first argument.
class A(object):
m=54
#classmethod
def class_method(cls):
print "m is %d" % cls.m
Static methods on the other hand, are used to perform functionalities that are not bound to the class i.e. they will not read or write class variables. Hence, static methods do not take classes as arguments. They are used so that classes can perform functionalities that are not directly related to the purpose of the class.
class X(object):
m=54 #will not be referenced
#staticmethod
def static_method():
print "Referencing/calling a variable or function outside this class. E.g. Some global variable/function."
I think giving a purely Python version of staticmethod and classmethod would help to understand the difference between them at language level (Refers to Descriptor Howto Guide).
Both of them are non-data descriptors (It would be easier to understand them if you are familiar with descriptors first).
class StaticMethod(object):
"Emulate PyStaticMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, objtype=None):
return self.f
class ClassMethod(object):
"Emulate PyClassMethod_Type() in Objects/funcobject.c"
def __init__(self, f):
self.f = f
def __get__(self, obj, cls=None):
def inner(*args, **kwargs):
if cls is None:
cls = type(obj)
return self.f(cls, *args, **kwargs)
return inner
Analyze #staticmethod literally providing different insights.
A normal method of a class is an implicit dynamic method which takes the instance as first argument.
In contrast, a staticmethod does not take the instance as first argument, so is called 'static'.
A staticmethod is indeed such a normal function the same as those outside a class definition.
It is luckily grouped into the class just in order to stand closer where it is applied, or you might scroll around to find it.
One pretty important practical difference occurs when subclassing. If you don't mind, I'll hijack #unutbu's example:
class A:
def foo(self, x):
print("executing foo(%s, %s)" % (self, x))
#classmethod
def class_foo(cls, x):
print("executing class_foo(%s, %s)" % (cls, x))
#staticmethod
def static_foo(x):
print("executing static_foo(%s)" % x)
class B(A):
pass
In class_foo, the method knows which class it is called on:
A.class_foo(1)
# => executing class_foo(<class '__main__.A'>, 1)
B.class_foo(1)
# => executing class_foo(<class '__main__.B'>, 1)
In static_foo, there is no way to determine whether it is called on A or B:
A.static_foo(1)
# => executing static_foo(1)
B.static_foo(1)
# => executing static_foo(1)
Note that this doesn't mean you can't use other methods in a staticmethod, you just have to reference the class directly, which means subclasses' staticmethods will still reference the parent class:
class A:
#classmethod
def class_qux(cls, x):
print(f"executing class_qux({cls}, {x})")
#classmethod
def class_bar(cls, x):
cls.class_qux(x)
#staticmethod
def static_bar(x):
A.class_qux(x)
class B(A):
pass
A.class_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
B.class_bar(1)
# => executing class_qux(<class '__main__.B'>, 1)
A.static_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
B.static_bar(1)
# => executing class_qux(<class '__main__.A'>, 1)
tldr;
A staticmethod is essentially a function bound to a class (and consequently its instances)
A classmethod is essentially an inheritable staticmethod.
For details, see the excellent answers by others.
First let's start with an example code that we'll use to understand both concepts:
class Employee:
NO_OF_EMPLOYEES = 0
def __init__(self, first_name, last_name, salary):
self.first_name = first_name
self.last_name = last_name
self.salary = salary
self.increment_employees()
def give_raise(self, amount):
self.salary += amount
#classmethod
def employee_from_full_name(cls, full_name, salary):
split_name = full_name.split(' ')
first_name = split_name[0]
last_name = split_name[1]
return cls(first_name, last_name, salary)
#classmethod
def increment_employees(cls):
cls.NO_OF_EMPLOYEES += 1
#staticmethod
def get_employee_legal_obligations_txt():
legal_obligations = """
1. An employee must complete 8 hours per working day
2. ...
"""
return legal_obligations
Class method
A class method accepts the class itself as an implicit argument and -optionally- any other arguments specified in the definition. It’s important to understand that a class method, does not have access to object instances (like instance methods do). Therefore, class methods cannot be used to alter the state of an instantiated object but instead, they are capable of changing the class state which is shared amongst all the instances of that class.
Class methods are typically useful when we need to access the class itself — for example, when we want to create a factory method, that is a method that creates instances of the class. In other words, class methods can serve as alternative constructors.
In our example code, an instance of Employee can be constructed by providing three arguments; first_name , last_name and salary.
employee_1 = Employee('Andrew', 'Brown', 85000)
print(employee_1.first_name)
print(employee_1.salary)
'Andrew'
85000
Now let’s assume that there’s a chance that the name of an Employee can be provided in a single field in which the first and last names are separated by a whitespace. In this case, we could possibly use our class method called employee_from_full_name that accepts three arguments in total. The first one, is the class itself, which is an implicit argument which means that it won’t be provided when calling the method — Python will automatically do this for us:
employee_2 = Employee.employee_from_full_name('John Black', 95000)
print(employee_2.first_name)
print(employee_2.salary)
'John'
95000
Note that it is also possible to call employee_from_full_name from object instances although in this context it doesn’t make a lot of sense:
employee_1 = Employee('Andrew', 'Brown', 85000)
employee_2 = employee_1.employee_from_full_name('John Black', 95000)
Another reason why we might want to create a class method, is when we need to change the state of the class. In our example, the class variable NO_OF_EMPLOYEES keeps track of the number of employees currently working for the company. This method is called every time a new instance of Employee is created and it updates the count accordingly:
employee_1 = Employee('Andrew', 'Brown', 85000)
print(f'Number of employees: {Employee.NO_OF_EMPLOYEES}')
employee_2 = Employee.employee_from_full_name('John Black', 95000)
print(f'Number of employees: {Employee.NO_OF_EMPLOYEES}')
Number of employees: 1
Number of employees: 2
Static methods
On the other hand, in static methods neither the instance (i.e. self) nor the class itself (i.e. cls) is passed as an implicit argument. This means that such methods, are not capable of accessing the class itself or its instances.
Now one could argue that static methods are not useful in the context of classes as they can also be placed in helper modules instead of adding them as members of the class. In object oriented programming, it is important to structure your classes into logical chunks and thus, static methods are quite useful when we need to add a method under a class simply because it logically belongs to the class.
In our example, the static method named get_employee_legal_obligations_txt simply returns a string that contains the legal obligations of every single employee of a company. This function, does not interact with the class itself nor with any instance. It could have been placed into a different helper module however, it is only relevant to this class and therefore we have to place it under the Employee class.
A static method can be access directly from the class itself
print(Employee.get_employee_legal_obligations_txt())
1. An employee must complete 8 hours per working day
2. ...
or from an instance of the class:
employee_1 = Employee('Andrew', 'Brown', 85000)
print(employee_1.get_employee_legal_obligations_txt())
1. An employee must complete 8 hours per working day
2. ...
References
What's the difference between static and class methods in Python?
I have a question in Python that seems very complex to me, that combines inheritance, recursion, and the super() function.
First of all, I am using Python 3, and I have a structure of deep inheritance.
In the very first parent class I declare a method, and I want that method to be called from each child class in the hierarchy, but with different inputs for each of them.
The use of that structure seems very pythonic to me and it really saves me from a lot of code repetition.
A simplified sample of my code is shown below:
class ClassA(object):
def __init__(self):
self.attr = 'a'
#classmethod
def _classname(cls):
return cls.__name__
def method1(self):
if self._classname() != 'ClassA': #don't call it for the very first parent class
super().method1()
print(self.attr)
class ClassB(ClassA):
def __init__(self):
self.attr = 'b'
class ClassC(ClassB):
def __init__(self):
self.attr = 'c'
inst1 = ClassC()
inst1.method1()
I expect that code to print
'a'
'b'
'c'
Instead it raises an attribute error:
super().method1()
AttributeError: 'super' object has no attribute 'method1'
I know that it is a complex problem, but I have tried to divide it. I tried to remove the recursion part, but I do not get any better.
Based on the various attempts I have done, I believe that I am very close to the cause of the problem, and it seems to me like a syntax problem or something that simple.
Thanks!!
I'm afraid you have built up the wrong mental model on how Python instances and classes relate. Classes only provide a series of attributes for instances to 'inherit', not separate namespaces for instance attributes to live in. When you look up an attribute on an instance and the attribute doesn't exist on the instance itself, a search is done of the classes that back the instance, with the 'nearest' class with that attribute winning over others. super() just lets you reach attributes with the same name but defined on a next class in that same layered search space.
In order for super() to work correctly, Python records what class the method1 function was defined on. Here that's ClassA, and super() will only find attributes on the parent classes of ClassA. In your example, ClassC and ClassB had already been searched and they didn't have a method1 attribute, so ClassA.method1 is being used, but there is no further method1 attribute in the rest of the layers that are searched (only object remains, and there is no object.method1).
You don't need to use super() when subclasses are not overriding a method, nor can you do what you want with super() anyway. Note that the ClassB and ClassC subclasses do not get a copy of the method at all, there is no ClassC.method1 direct attribute that needs to account for ClassB.method1 to exist, etc. Again, what happens when looking up attributes on an instance is that all class objects in the inheritance hierarchy of the instance are inspected for that attribute, in a specific order.
Take a look at your subclasses:
>>> inst1
<__main__.ClassC object at 0x109a9dfd0>
>>> type(inst1)
<class '__main__.ClassC'>
>>> type(inst1).__mro__
(<class '__main__.ClassC'>, <class '__main__.ClassB'>, <class '__main__.ClassA'>, <class 'object'>)
The __mro__ attribute gives you the method resolution order of your ClassC class object; it is this order that attributes are searched for, and that super() uses to further search for attributes. To find inst1.method, Python will step through each of the objects in type(inst1).__mro__ and will return the first hit, so ClassA.method1.
In your example, you used super() in the ClassA.method1() definition. Python has attached some information to that function object to help further searches of attributes:
>>> ClassA.method1.__closure__
(<cell at 0x109a3fee8: type object at 0x7fd7f5cd5058>,)
>>> ClassA.method1.__closure__[0].cell_contents
<class '__main__.ClassA'>
>>> ClassA.method1.__closure__[0].cell_contents is ClassA
True
When you call super() the closure I show above is used to start a search along the type(self).__mro__ sequence, starting at the next object past the one named in the closure. It doesn't matter that there are subclasses here, so even for your inst1 object everything is skipped an only object is inspected:
>>> type(inst1).__mro__.index(ClassA) # where is ClassA in the sequence?
2
>>> type(inst1).__mro__[2 + 1:] # `super().method1` will only consider these objects, *past* ClassA
(<class 'object'>,)
At no point are ClassB or ClassC involved here anymore. The MRO depends on the class hierarchy of the current instance, and you can make radical changes when you start using multiple inheritance. Adding in extra classes into a hierarchy can alter the MRO enough to insert something between ClassA and object:
>>> class Mixin(object):
... def method1(self):
... print("I am Mixin.method1!")
...
>>> class ClassD(ClassA, Mixin): pass
...
>>> ClassD.__mro__
(<class '__main__.ClassD'>, <class '__main__.ClassA'>, <class '__main__.Mixin'>, <class 'object'>)
>>> ClassD.__mro__[ClassD.__mro__.index(ClassA) + 1:]
(<class '__main__.Mixin'>, <class 'object'>)
ClassD inherits from ClassA and from Mixin. Mixin inherits from object too. Python follows some complicated rules to put all classes in the hierarchy into a logical linear order, and Mixin ends up between ClassA and object because it inherits from the latter, and not the former.
Because Mixin is injected into the MRO after ClassA, calling Class().method1() changes how super().method1() behaves, and suddenly calling that method will do something different:
>>> ClassD().method1()
I am Mixin.method1!
a
Remember, it helps to see classes as a layered search space for attributes on instances! instance.attribute is searched for along the classes if the attribute doesn't exist on the instance itself. super() just let you search for the same attribute along the remainder of that search space.
This lets you reuse method implementations when implementing a method with the same name in a subclass. That's the whole point of super()!
There are other problems with your code.
When looking up methods, they are bound to the object they were looked up on. instance.method binds the method to instance, so that when you call instance.method(), Python knows what to pass into the method as self. For classmethod objects, self is replaced with type(self), unless you did ClassObject.attribute, at which point ClassObject is used.
So your _classname method will always be producing ClassC for inst1, as the cls object that is passed in is that of the current instance. super() doesn't change what class classmethods are bound to when accessed on an instance! It'll always be type(self).
You also forgot to call super() in the ClassB and ClassC __init__ methods, so for inst1, only ClassC.__init__ is ever actually used. The ClassB.__init__ and ClassC.__init__ implementations are never called. You'd have to add a call to super().__init__() in both for that to happen, at which point there are three self.attr = ... assignments on the same instance, and only the one that executes last will remain. There is no separate self for each of the classes that make up the code for the instance, so there are no separate self.attr attributes with different values.
Again, that's because inst1.__init__() is called, __init__ is bound to inst for the self argument, and even if you used super().__init__() the self that is passed on remains inst1.
What you want to achieve is something entirely different from an attribute search across all of the classes. Printing all class names can be done with a loop over __mro__ instead:
class ClassA(object):
def method2(self):
this_class = __class__ # this uses the same closure as super()!
for cls in type(self).__mro__:
print(cls.__name__)
if cls is this_class:
break
class ClassB(ClassA): pass
class ClassC(ClassB): pass
This then produces:
>>> inst1 = ClassC()
>>> inst1.method2()
ClassC
ClassB
ClassA
If you have to print 'c', 'b', 'a' you can add extra attributes to each class:
class ClassA(object):
_class_attr = 'a'
def method2(self):
this_class = __class__ # this uses the same closure as super()!
for cls in type(self).__mro__:
if hasattr(cls, '_class_attr'):
print(cls._class_attr)
class ClassB(ClassA):
_class_attr = 'b'
class ClassC(ClassB):
_class_attr = 'c'
and you'll get
c
b
a
printed.
Thats because you're trying to access Method1() on Object_class
def method1(self):
# this will print the class name you're calling from, if you are confused.
print(self._classname())
print(self.attr)
You've written an if-else which satisfies when you're instantialize with Class C and access method1().
To print a,b,c, you will need override the method in every class.. and calling super from them.
However, this will still have a problem. Because the self attribute carries the instance of Class C, not Class B or A. So, they can't access the attribute that you're initializing in the init func.
Final code looks like this
class ClassA(object):
def __init__(self):
self.attr = 'a'
#classmethod
def _classname(cls):
return cls.__name__
def method1(self):
print(self._classname())
#don't call it for the very first parent class
#super().method1()
print(self.attr)
class ClassB(ClassA):
def __init__(self):
self.attr = 'b'
def method1(self):
print(self._classname())
print(self.attr)
super().method1()
class ClassC(ClassB):
def __init__(self):
self.attr = 'c'
def method1(self):
print(self._classname())
print(self.attr)
super().method1()
inst1 = ClassC()
inst1.method1()
I know there are a bunch of similar questions out there. But my question is different.
I don't want to make a method which can't be overridden.
I want to protect my newly created class to not accidentally override something.
Using underscore as a prefix is pretty good, but soon I'll get a lot of methods with a lot of underscores. and somewhere in my inherited class, I will override the grand-ancestor's class method.
What I really want is something as simple as this:
class Cat(Mammal):
def walk(self):
if ancestor_has_function('walk'):
parent.walk();
do_something_here();
If any of Cat's ancestor (Either it is Mammal, Animal, or LifeForm) has "walk" method, then the parent method should be executed first.
Is that any possibility to do this in python?
EDIT:
For instance this is the resume of answers I considered as good. Hope this will help others:
class Animal(object):
pass
#def walk(self):
# print('animal walk')
class Mammal(Animal):
def walk(self):
if hasattr(super(Mammal, self), 'walk') and callable(super(Mammal,self).walk):
super(Mammal, self).walk()
print('mammal walk')
class Cat(Mammal):
def walk(self):
super(Cat, self).walk()
print('cat walk')
if __name__ == '__main__':
cat = Cat()
cat.walk()
And here is the output:
mammal walk
cat walk
Try to uncomment Animal's walk method, and you will have it work as well too.
Generally speaking, you'll probably want to provide at least a stub method in whichever superclass is the most generic:
class Mammal(object):
def walk(self):
pass
Then, extend it in subclasses by calling super():
class Cat(Mammal):
def walk(self):
super(Cat, self).walk() # or just super().walk(), in Python 3+
do_something_here()
Making the super() call conditional is not hard, but it's probably a bad idea: it's verbose, fragile, and only encourages bad practices. If you really, really have good reason to do it, you can just use hasattr() on the super object, like you would with any other object:
class Cat(Mammal):
def walk(self):
if hasattr(super(Cat, self), 'walk'):
super(Cat, self).walk()
do_something_here()
You would only want to do this in unusual situations, though, such as subclassing classes from a third-party library where you can't rely on certain methods being present, for some reason.
Yep. hasattr checks if there is an attribute with a specific name.
and callable checks if the specific attribute is callable.
class Mammal(object):
def walk(self):
print "walking"
class Cat(Mammal):
def walk(self):
if hasattr(Mammal,'walk') and callable(Mammal.walk):
Mammal.walk(self);
print "another walking!"
and now:
>>> my_cat = Cat()
>>> my_cat.walk()
walking
another walking!
Note that you can also use super to get your parent class like that:
if hasattr(super(Cat, self),'walk'):
You can use the dir() function to get all the names declared for some module or class. Methods declared in classes higher up in the hierarchy will also be included. Note, however, that this will also include attributes, so check with callable() first.
Also, calling the parent method looks a bit different in python, see the code below.
def walk(self):
if "walk" in dir(Mammal) and callable(Mammal.walk):
Mammal.walk(self)
# do something
you can keep your original method in a field
class MyClass:
def __method(self):
pass
def __init__(self):
self.method = __method
and than check for identity and call the saved method
import inspect
class SomeClass():
def __init__(self):
...
def somefunc(self):
....
def someOtherFunc(self):
....
allmembers = inspect.getmembers(SomeClass, predicate=inspect.ismethod)
getmembers returns a list of all methods define within the given class, it is a list of tuples that contains method names and definitions:
[('__init__', <unbound method SomeClass.__init__>),
('somefunc', <unbound method SomeClass.somefunc>),
('someOtherFunc', <unbound method SomeClass.someOtherFunc>)]
Since first elements of the tuple are strings, you can use string based methods to filter base methods like __init__
allmembers = filter(lambda x: not x.startswith('__'), [x[0] for x in inspect.getmembers(SomeClass, predicate=inspect.ismethod))])
[('somefunc', <unbound method SomeClass.somefunc>),
('someOtherFunc', <unbound method SomeClass.someOtherFunc>)]
You can get a list of all methods defined within the class and check if you have a similarly named method, Sincegetmembers returns you an unbound method instance, you can also reach that function easily.