Meaning of #classmethod and #staticmethod for beginner [duplicate] - python

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Difference between #staticmethod and #classmethod
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What do #classmethod and #staticmethod mean in Python, and how are they different? When should I use them, why should I use them, and how should I use them?
As far as I understand, #classmethod tells a class that it's a method which should be inherited into subclasses, or... something. However, what's the point of that? Why not just define the class method without adding #classmethod or #staticmethod or any # definitions?

Though classmethod and staticmethod are quite similar, there's a slight difference in usage for both entities: classmethod must have a reference to a class object as the first parameter, whereas staticmethod can have no parameters at all.
Example
class Date(object):
def __init__(self, day=0, month=0, year=0):
self.day = day
self.month = month
self.year = year
#classmethod
def from_string(cls, date_as_string):
day, month, year = map(int, date_as_string.split('-'))
date1 = cls(day, month, year)
return date1
#staticmethod
def is_date_valid(date_as_string):
day, month, year = map(int, date_as_string.split('-'))
return day <= 31 and month <= 12 and year <= 3999
date2 = Date.from_string('11-09-2012')
is_date = Date.is_date_valid('11-09-2012')
Explanation
Let's assume an example of a class, dealing with date information (this will be our boilerplate):
class Date(object):
def __init__(self, day=0, month=0, year=0):
self.day = day
self.month = month
self.year = year
This class obviously could be used to store information about certain dates (without timezone information; let's assume all dates are presented in UTC).
Here we have __init__, a typical initializer of Python class instances, which receives arguments as a typical instance method, having the first non-optional argument (self) that holds a reference to a newly created instance.
Class Method
We have some tasks that can be nicely done using classmethods.
Let's assume that we want to create a lot of Date class instances having date information coming from an outer source encoded as a string with format 'dd-mm-yyyy'. Suppose we have to do this in different places in the source code of our project.
So what we must do here is:
Parse a string to receive day, month and year as three integer variables or a 3-item tuple consisting of that variable.
Instantiate Date by passing those values to the initialization call.
This will look like:
day, month, year = map(int, string_date.split('-'))
date1 = Date(day, month, year)
For this purpose, C++ can implement such a feature with overloading, but Python lacks this overloading. Instead, we can use classmethod. Let's create another constructor.
#classmethod
def from_string(cls, date_as_string):
day, month, year = map(int, date_as_string.split('-'))
date1 = cls(day, month, year)
return date1
date2 = Date.from_string('11-09-2012')
Let's look more carefully at the above implementation, and review what advantages we have here:
We've implemented date string parsing in one place and it's reusable now.
Encapsulation works fine here (if you think that you could implement string parsing as a single function elsewhere, this solution fits the OOP paradigm far better).
cls is the class itself, not an instance of the class. It's pretty cool because if we inherit our Date class, all children will have from_string defined also.
Static method
What about staticmethod? It's pretty similar to classmethod but doesn't take any obligatory parameters (like a class method or instance method does).
Let's look at the next use case.
We have a date string that we want to validate somehow. This task is also logically bound to the Date class we've used so far, but doesn't require instantiation of it.
Here is where staticmethod can be useful. Let's look at the next piece of code:
#staticmethod
def is_date_valid(date_as_string):
day, month, year = map(int, date_as_string.split('-'))
return day <= 31 and month <= 12 and year <= 3999
# usage:
is_date = Date.is_date_valid('11-09-2012')
So, as we can see from usage of staticmethod, we don't have any access to what the class is---it's basically just a function, called syntactically like a method, but without access to the object and its internals (fields and other methods), which classmethod does have.

Rostyslav Dzinko's answer is very appropriate. I thought I could highlight one other reason you should choose #classmethod over #staticmethod when you are creating an additional constructor.
In the example, Rostyslav used the #classmethod from_string as a Factory to create Date objects from otherwise unacceptable parameters. The same can be done with #staticmethod as is shown in the code below:
class Date:
def __init__(self, month, day, year):
self.month = month
self.day = day
self.year = year
def display(self):
return "{0}-{1}-{2}".format(self.month, self.day, self.year)
#staticmethod
def millenium(month, day):
return Date(month, day, 2000)
new_year = Date(1, 1, 2013) # Creates a new Date object
millenium_new_year = Date.millenium(1, 1) # also creates a Date object.
# Proof:
new_year.display() # "1-1-2013"
millenium_new_year.display() # "1-1-2000"
isinstance(new_year, Date) # True
isinstance(millenium_new_year, Date) # True
Thus both new_year and millenium_new_year are instances of the Date class.
But, if you observe closely, the Factory process is hard-coded to create Date objects no matter what. What this means is that even if the Date class is subclassed, the subclasses will still create plain Date objects (without any properties of the subclass). See that in the example below:
class DateTime(Date):
def display(self):
return "{0}-{1}-{2} - 00:00:00PM".format(self.month, self.day, self.year)
datetime1 = DateTime(10, 10, 1990)
datetime2 = DateTime.millenium(10, 10)
isinstance(datetime1, DateTime) # True
isinstance(datetime2, DateTime) # False
datetime1.display() # returns "10-10-1990 - 00:00:00PM"
datetime2.display() # returns "10-10-2000" because it's not a DateTime object but a Date object. Check the implementation of the millenium method on the Date class for more details.
datetime2 is not an instance of DateTime? WTF? Well, that's because of the #staticmethod decorator used.
In most cases, this is undesired. If what you want is a Factory method that is aware of the class that called it, then #classmethod is what you need.
Rewriting Date.millenium as (that's the only part of the above code that changes):
#classmethod
def millenium(cls, month, day):
return cls(month, day, 2000)
ensures that the class is not hard-coded but rather learnt. cls can be any subclass. The resulting object will rightly be an instance of cls.
Let's test that out:
datetime1 = DateTime(10, 10, 1990)
datetime2 = DateTime.millenium(10, 10)
isinstance(datetime1, DateTime) # True
isinstance(datetime2, DateTime) # True
datetime1.display() # "10-10-1990 - 00:00:00PM"
datetime2.display() # "10-10-2000 - 00:00:00PM"
The reason is, as you know by now, that #classmethod was used instead of #staticmethod

#classmethod means: when this method is called, we pass the class as the first argument instead of the instance of that class (as we normally do with methods). This means you can use the class and its properties inside that method rather than a particular instance.
#staticmethod means: when this method is called, we don't pass an instance of the class to it (as we normally do with methods). This means you can put a function inside a class but you can't access the instance of that class (this is useful when your method does not use the instance).

When to use each
#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: seeing #staticmethod, we know that the method 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
here is good link to this topic.

Meaning of #classmethod and #staticmethod?
A method is a function in an object's namespace, accessible as an attribute.
A regular (i.e. instance) method gets the instance (we usually call it self) as the implicit first argument.
A class method gets the class (we usually call it cls) as the implicit first argument.
A static method gets no implicit first argument (like a regular function).
when should I use them, why should I use them, and how should I use them?
You don't need either decorator. But on the principle that you should minimize the number of arguments to functions (see Clean Coder), they are useful for doing just that.
class Example(object):
def regular_instance_method(self):
"""A function of an instance has access to every attribute of that
instance, including its class (and its attributes.)
Not accepting at least one argument is a TypeError.
Not understanding the semantics of that argument is a user error.
"""
return some_function_f(self)
#classmethod
def a_class_method(cls):
"""A function of a class has access to every attribute of the class.
Not accepting at least one argument is a TypeError.
Not understanding the semantics of that argument is a user error.
"""
return some_function_g(cls)
#staticmethod
def a_static_method():
"""A static method has no information about instances or classes
unless explicitly given. It just lives in the class (and thus its
instances') namespace.
"""
return some_function_h()
For both instance methods and class methods, not accepting at least one argument is a TypeError, but not understanding the semantics of that argument is a user error.
(Define some_function's, e.g.:
some_function_h = some_function_g = some_function_f = lambda x=None: x
and this will work.)
dotted lookups on instances and classes:
A dotted lookup on an instance is performed in this order - we look for:
a data descriptor in the class namespace (like a property)
data in the instance __dict__
a non-data descriptor in the class namespace (methods).
Note, a dotted lookup on an instance is invoked like this:
instance = Example()
instance.regular_instance_method
and methods are callable attributes:
instance.regular_instance_method()
instance methods
The argument, self, is implicitly given via the dotted lookup.
You must access instance methods from instances of the class.
>>> instance = Example()
>>> instance.regular_instance_method()
<__main__.Example object at 0x00000000399524E0>
class methods
The argument, cls, is implicitly given via dotted lookup.
You can access this method via an instance or the class (or subclasses).
>>> instance.a_class_method()
<class '__main__.Example'>
>>> Example.a_class_method()
<class '__main__.Example'>
static methods
No arguments are implicitly given. This method works like any function defined (for example) on a modules' namespace, except it can be looked up
>>> print(instance.a_static_method())
None
Again, when should I use them, why should I use them?
Each of these are progressively more restrictive in the information they pass the method versus instance methods.
Use them when you don't need the information.
This makes your functions and methods easier to reason about and to unittest.
Which is easier to reason about?
def function(x, y, z): ...
or
def function(y, z): ...
or
def function(z): ...
The functions with fewer arguments are easier to reason about. They are also easier to unittest.
These are akin to instance, class, and static methods. Keeping in mind that when we have an instance, we also have its class, again, ask yourself, which is easier to reason about?:
def an_instance_method(self, arg, kwarg=None):
cls = type(self) # Also has the class of instance!
...
#classmethod
def a_class_method(cls, arg, kwarg=None):
...
#staticmethod
def a_static_method(arg, kwarg=None):
...
Builtin examples
Here are a couple of my favorite builtin examples:
The str.maketrans static method was a function in the string module, but it is much more convenient for it to be accessible from the str namespace.
>>> 'abc'.translate(str.maketrans({'a': 'b'}))
'bbc'
The dict.fromkeys class method returns a new dictionary instantiated from an iterable of keys:
>>> dict.fromkeys('abc')
{'a': None, 'c': None, 'b': None}
When subclassed, we see that it gets the class information as a class method, which is very useful:
>>> class MyDict(dict): pass
>>> type(MyDict.fromkeys('abc'))
<class '__main__.MyDict'>
My advice - Conclusion
Use static methods when you don't need the class or instance arguments, but the function is related to the use of the object, and it is convenient for the function to be in the object's namespace.
Use class methods when you don't need instance information, but need the class information perhaps for its other class or static methods, or perhaps itself as a constructor. (You wouldn't hardcode the class so that subclasses could be used here.)

One would use #classmethod when he/she would want to change the behaviour of the method based on which subclass is calling the method. remember we have a reference to the calling class in a class method.
While using static you would want the behaviour to remain unchanged across subclasses
Example:
class Hero:
#staticmethod
def say_hello():
print("Helllo...")
#classmethod
def say_class_hello(cls):
if(cls.__name__=="HeroSon"):
print("Hi Kido")
elif(cls.__name__=="HeroDaughter"):
print("Hi Princess")
class HeroSon(Hero):
def say_son_hello(self):
print("test hello")
class HeroDaughter(Hero):
def say_daughter_hello(self):
print("test hello daughter")
testson = HeroSon()
testson.say_class_hello() #Output: "Hi Kido"
testson.say_hello() #Outputs: "Helllo..."
testdaughter = HeroDaughter()
testdaughter.say_class_hello() #Outputs: "Hi Princess"
testdaughter.say_hello() #Outputs: "Helllo..."

A little compilation
#staticmethod
A way to write a method inside a class without reference to the object it is being called on. So no need to pass implicit argument like self or cls.
It is written exactly the same how written outside the class, but it is not of no use in python because if you need to encapsulate a method inside a class since this method needs to be the part of that class #staticmethod is comes handy in that case.
#classmethod
It is important when you want to write a factory method and by this custom attribute(s) can be attached in a class. This attribute(s) can be overridden in the inherited class.
A comparison between these two methods can be as below

#classmethod
#classmethod may be compared with __init__.
You could think it is another __init__(). It is the way python realize class constructor overloading in c++.
class C:
def __init__(self, parameters):
....
#classmethod
def construct_from_func(cls, parameters):
....
obj1 = C(parameters)
obj2 = C.construct_from_func(parameters)
notice they both has a reference for class as first argument in definitioin while __init__ use self but construct_from_func use cls conventionally.
#staticmethod
#staticmethod may be compared with object method
class C:
def __init__(self):
....
#staticmethod
def static_method(args):
....
def normal_method(parameters):
....
result = C.static_method(parameters)
result = obj.normal_method(parameters)

I'm a beginner on this site, I have read all above answers, and got the information what I want. However, I don't have the right to upvote. So I want to get my start on StackOverflow with the answer as I understand it.
#staticmethod doesn't need self or cls as the first parameter of the method
#staticmethod and #classmethod wrapped function could be called by instance or class variable
#staticmethod decorated function impact some kind 'immutable property' that subclass inheritance can't overwrite its base class function which is wrapped by a #staticmethod decorator.
#classmethod need cls (Class name, you could change the variable name if you want, but it's not advised) as the first parameter of function
#classmethod always used by subclass manner, subclass inheritance may change the effect of base class function, i.e. #classmethod wrapped base class function could be overwritten by different subclasses.

In short, #classmethod turns a normal method to a factory method.
Let's explore it with an example:
class PythonBook:
def __init__(self, name, author):
self.name = name
self.author = author
def __repr__(self):
return f'Book: {self.name}, Author: {self.author}'
Without a #classmethod,you should labor to create instances one by one and they are scattered.
book1 = PythonBook('Learning Python', 'Mark Lutz')
In [20]: book1
Out[20]: Book: Learning Python, Author: Mark Lutz
book2 = PythonBook('Python Think', 'Allen B Dowey')
In [22]: book2
Out[22]: Book: Python Think, Author: Allen B Dowey
As for example with #classmethod
class PythonBook:
def __init__(self, name, author):
self.name = name
self.author = author
def __repr__(self):
return f'Book: {self.name}, Author: {self.author}'
#classmethod
def book1(cls):
return cls('Learning Python', 'Mark Lutz')
#classmethod
def book2(cls):
return cls('Python Think', 'Allen B Dowey')
Test it:
In [31]: PythonBook.book1()
Out[31]: Book: Learning Python, Author: Mark Lutz
In [32]: PythonBook.book2()
Out[32]: Book: Python Think, Author: Allen B Dowey
See? Instances are successfully created inside a class definition and they are collected together.
In conclusion, #classmethod decorator convert a conventional method to a factory method,Using classmethods makes it possible to add as many alternative constructors as necessary.

A slightly different way to think about it that might be useful for someone... A class method is used in a superclass to define how that method should behave when it's called by different child classes. A static method is used when we want to return the same thing regardless of the child class that we are calling.

Class method can modify the class state,it bound to the class and it contain cls as parameter.
Static method can not modify the class state,it bound to the class and it does't know class or instance
class empDetails:
def __init__(self,name,sal):
self.name=name
self.sal=sal
#classmethod
def increment(cls,name,none):
return cls('yarramsetti',6000 + 500)
#staticmethod
def salChecking(sal):
return sal > 6000
emp1=empDetails('durga prasad',6000)
emp2=empDetails.increment('yarramsetti',100)
# output is 'durga prasad'
print emp1.name
# output put is 6000
print emp1.sal
# output is 6500,because it change the sal variable
print emp2.sal
# output is 'yarramsetti' it change the state of name variable
print emp2.name
# output is True, because ,it change the state of sal variable
print empDetails.salChecking(6500)

Related

Deciding to use class itself or class method [duplicate]

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?

Difference between #classmethod and a method in python [duplicate]

This question already has answers here:
What's an example use case for a Python classmethod?
(7 answers)
Closed 9 years ago.
What is the difference between #classmethod and a 'classic' method in python,
When should I use the #classmethod and when should I use a 'classic' method in python.
Is the classmethod must be an method who is referred to the class (I mean it's only a method who handle the class) ?
And I know what is the difference between a #staticmethod and classic method
Thx
Let's assume you have a class Car which represents the Car entity within your system.
A classmethod is a method that works for the class Car not on one of any of Car's instances. The first parameter to a function decorated with #classmethod, usually called cls, is therefore the class itself. Example:
class Car(object):
colour = 'red'
#classmethod
def blue_cars(cls):
# cls is the Car class
# return all blue cars by looping over cls instances
A function acts on a particular instance of the class; the first parameter usually called self is the instance itself:
def get_colour(self):
return self.colour
To sum up:
use classmethod to implement methods that work on a whole class (and not on particular class instances):
Car.blue_cars()
use instance methods to implement methods that work on a particular instance:
my_car = Car(colour='red')
my_car.get_colour() # should return 'red'
If you define a method inside a class, it is handled in a special way: access to it wraps it in a special object which modifies the calling arguments in order to include self, a reference to the referred object:
class A(object):
def f(self):
pass
a = A()
a.f()
This call to a.f actually asks f (via the descriptor protocol) for an object to really return. This object is then called without arguments and deflects the call to the real f, adding a in front.
So what a.f() really does is calling the original f function with (a) as arguments.
In order to prevent this, we can wrap the function
with a #staticmethod decorator,
with a #classmethod decorator,
with one of other, similiar working, self-made decorators.
#staticmethod turns it into an object which, when asked, changes the argument-passing behaviour so that it matches the intentions about calling the original f:
class A(object):
def method(self):
pass
#staticmethod
def stmethod():
pass
#classmethod
def clmethod(cls):
pass
a = A()
a.method() # the "function inside" gets told about a
A.method() # doesn't work because there is no reference to the needed object
a.clmethod() # the "function inside" gets told about a's class, A
A.clmethod() # works as well, because we only need the classgets told about a's class, A
a.stmethod() # the "function inside" gets told nothing about anything
A.stmethod() # works as well
So #classmethod and #staticmethod have in common that they "don't care about" the concrete object they were called with; the difference is that #staticmethod doesn't want to know anything at all about it, while #classmethod wants to know its class.
So the latter gets the class object the used object is an instance of. Just replace self with cls in this case.
Now, when to use what?
Well, that is easy to handle:
If you have an access to self, you clearly need an instance method.
If you don't access self, but want to know about its class, use #classmethod. This may for example be the case with factory methods. datetime.datetime.now() is such an example: you can call it via its class or via an instance, but it creates a new instance with completely different data. I even used them once for automatically generating subclasses of a given class.
If you need neither self nor cls, you use #staticmethod. This can as well be used for factory methods, if they don't need to care about subclassing.
#classmethod takes the class as first argument while function takes instance of the class
>>> class Test(object):
... def func(self):
... print self
... #classmethod
... def meth(self):
... print self
>>> t = Test()
>>> t.func()
<__main__.Test object at 0x00000000027238D0>
>>> t.meth()
<class '__main__.Test'>
I've used self argument in meth intentionally so it would be very close in syntax to the func. But usually you'd better use cls as argument:
... #classmethod
... def meth(cls):
... print cls

Is there a way apply a decorator to a Python method that needs informations about the class?

When you decorate a method, it is not bound yet to the class, and therefor doesn't have the im_class attribute yet. I looking for a way to get the information about the class inside the decorator. I tried this:
import types
def decorator(method):
def set_signal(self, name, value):
print name
if name == 'im_class':
print "I got the class"
method.__setattr__ = types.MethodType(set_signal, method)
return method
class Test(object):
#decorator
def bar(self, foo):
print foo
But it doesn't print anything.
I can imagine doing this:
class Test(object):
#decorator(klass=Test)
def bar(self, foo):
print foo
But if I can avoid it, it would make my day.
__setattr__ is only called on explicit object.attribute = assignments; building a class does not use attribute assignment but builds a dictionary (Test.__dict__) instead.
To access the class you have a few different options though:
Use a class decorator instead; it'll be passed the completed class after building it, you could decorate individual methods on that class by replacing them (decorated) in the class. You could use a combination of a function decorator and a class decorator to mark which methods are to be decorated:
def methoddecoratormarker(func):
func._decorate_me = True
return func
def realmethoddecorator(func):
# do something with func.
# Note: it is still an unbound function here, not a method!
return func
def classdecorator(klass):
for name, item in klass.__dict__.iteritems():
if getattr(item, '_decorate_me', False):
klass.__dict__[name] = realmethoddecorator(item)
You could use a metaclass instead of a class decorator to achieve the same, of course.
Cheat, and use sys._getframe() to retrieve the class from the calling frame:
import sys
def methoddecorator(func):
callingframe = sys._getframe(1)
classname = callingframe.f_code.co_name
Note that all you can retrieve is the name of the class; the class itself is still being built at this time. You can add items to callingframe.f_locals (a mapping) and they'll be made part of the new class object.
Access self whenever the method is called. self is a reference to the instance after all, and self.__class__ is going to be, at the very least, a sub-class of the original class the function was defined in.
My strict answer would be: It's not possible, because the class does not yet exist when the decorator is executed.
The longer answer would depend on your very exact requirements. As I wrote, you cannot access the class if it does not yet exists. One solution would be, to mark the decorated method to be "transformed" later. Then use a metaclass or class decorator to apply your modifications after the class has been created.
Another option involves some magic. Look for the implementation of the implements method in zope.interfaces. It has some access to the information about the class which is just been parsed. Don't know if it will be enough for your use case.
You might want to take a look at descriptors. They let you implement a __get__ that is used when an attribute is accessed, and can return different things depending on the object and its type.
Use method decorators to add some marker attributes to the interesting methods, and use a metaclass which iterates over the methods, finds the marker attributes, and does the logic. The metaclass code is run when the class is created, so it has a reference to the newly created class.
class MyMeta(object):
def __new__(...):
...
cls = ...
... iterate over dir(cls), find methods having .is_decorated, act on them
return cls
def decorator(f):
f.is_decorated = True
return f
class MyBase(object):
__metaclass__ = MyMeta
class MyClass(MyBase):
#decorator
def bar(self, foo):
print foo
If you worry about that the programmer of MyClass forgets to use MyBase, you can forcibly set the metaclass in decorator, by exampining the globals dicitionary of the caller stack frame (sys._getframe()).

When should I use #classmethod and when def method(self)?

While integrating a Django app I have not used before, I found two different ways to define functions inside the class. The author seems to use them both distinctively and intentionally. The first one is the one that I myself use a lot:
class Dummy(object):
def some_function(self, *args, **kwargs):
# do something here
# self is the class instance
The other one is the one I never use, mostly because I do not understand when and what to use it for:
class Dummy(object):
#classmethod
def some_function(cls, *args, **kwargs):
# do something here
# cls refers to what?
The classmethod decorator in the python documentation says:
A class method receives the class as the implicit first argument, just
like an instance method receives the instance.
So I guess cls refers to Dummy itself (the class, not the instance). I do not exactly understand why this exists, because I could always do this:
type(self).do_something_with_the_class
Is this just for the sake of clarity, or did I miss the most important part: spooky and fascinating things that couldn't be done without it?
Your guess is correct - you understand how classmethods work.
The why is that these methods can be called both on an instance OR on the class (in both cases, the class object will be passed as the first argument):
class Dummy(object):
#classmethod
def some_function(cls,*args,**kwargs):
print cls
#both of these will have exactly the same effect
Dummy.some_function()
Dummy().some_function()
On the use of these on instances: There are at least two main uses for calling a classmethod on an instance:
self.some_function() will call the version of some_function on the actual type of self, rather than the class in which that call happens to appear (and won't need attention if the class is renamed); and
In cases where some_function is necessary to implement some protocol, but is useful to call on the class object alone.
The difference with staticmethod: There is another way of defining methods that don't access instance data, called staticmethod. That creates a method which does not receive an implicit first argument at all; accordingly it won't be passed any information about the instance or class on which it was called.
In [6]: class Foo(object): some_static = staticmethod(lambda x: x+1)
In [7]: Foo.some_static(1)
Out[7]: 2
In [8]: Foo().some_static(1)
Out[8]: 2
In [9]: class Bar(Foo): some_static = staticmethod(lambda x: x*2)
In [10]: Bar.some_static(1)
Out[10]: 2
In [11]: Bar().some_static(1)
Out[11]: 2
The main use I've found for it is to adapt an existing function (which doesn't expect to receive a self) to be a method on a class (or object).
One of the most common uses of classmethod in Python is factories, which are one of the most efficient methods to build an object. Because classmethods, like staticmethods, do not need the construction of a class instance. (But then if we use staticmethod, we would have to hardcode the instance class name in the function)
This blog does a great job of explaining it:
https://iscinumpy.gitlab.io/post/factory-classmethods-in-python/
If you add decorator #classmethod, That means you are going to make that method as static method of java or C++. ( static method is a general term I guess ;) )
Python also has #staticmethod. and difference between classmethod and staticmethod is whether you can
access to class or static variable using argument or classname itself.
class TestMethod(object):
cls_var = 1
#classmethod
def class_method(cls):
cls.cls_var += 1
print cls.cls_var
#staticmethod
def static_method():
TestMethod.cls_var += 1
print TestMethod.cls_var
#call each method from class itself.
TestMethod.class_method()
TestMethod.static_method()
#construct instances
testMethodInst1 = TestMethod()
testMethodInst2 = TestMethod()
#call each method from instances
testMethodInst1.class_method()
testMethodInst2.static_method()
all those classes increase cls.cls_var by 1 and print it.
And every classes using same name on same scope or instances constructed with these class is going to share those methods.
There's only one TestMethod.cls_var
and also there's only one TestMethod.class_method() , TestMethod.static_method()
And important question. why these method would be needed.
classmethod or staticmethod is useful when you make that class as a factory
or when you have to initialize your class only once. like open file once, and using feed method to read the file line by line.

How to dynamically change base class of instances at runtime?

This article has a snippet showing usage of __bases__ to dynamically change the inheritance hierarchy of some Python code, by adding a class to an existing classes collection of classes from which it inherits. Ok, that's hard to read, code is probably clearer:
class Friendly:
def hello(self):
print 'Hello'
class Person: pass
p = Person()
Person.__bases__ = (Friendly,)
p.hello() # prints "Hello"
That is, Person doesn't inherit from Friendly at the source level, but rather this inheritance relation is added dynamically at runtime by modification of the __bases__attribute of the Person class. However, if you change Friendly and Person to be new style classes (by inheriting from object), you get the following error:
TypeError: __bases__ assignment: 'Friendly' deallocator differs from 'object'
A bit of Googling on this seems to indicate some incompatibilities between new-style and old style classes in regards to changing the inheritance hierarchy at runtime. Specifically: "New-style class objects don't support assignment to their bases attribute".
My question, is it possible to make the above Friendly/Person example work using new-style classes in Python 2.7+, possibly by use of the __mro__ attribute?
Disclaimer: I fully realise that this is obscure code. I fully realize that in real production code tricks like this tend to border on unreadable, this is purely a thought experiment, and for funzies to learn something about how Python deals with issues related to multiple inheritance.
Ok, again, this is not something you should normally do, this is for informational purposes only.
Where Python looks for a method on an instance object is determined by the __mro__ attribute of the class which defines that object (the M ethod R esolution O rder attribute). Thus, if we could modify the __mro__ of Person, we'd get the desired behaviour. Something like:
setattr(Person, '__mro__', (Person, Friendly, object))
The problem is that __mro__ is a readonly attribute, and thus setattr won't work. Maybe if you're a Python guru there's a way around that, but clearly I fall short of guru status as I cannot think of one.
A possible workaround is to simply redefine the class:
def modify_Person_to_be_friendly():
# so that we're modifying the global identifier 'Person'
global Person
# now just redefine the class using type(), specifying that the new
# class should inherit from Friendly and have all attributes from
# our old Person class
Person = type('Person', (Friendly,), dict(Person.__dict__))
def main():
modify_Person_to_be_friendly()
p = Person()
p.hello() # works!
What this doesn't do is modify any previously created Person instances to have the hello() method. For example (just modifying main()):
def main():
oldperson = Person()
ModifyPersonToBeFriendly()
p = Person()
p.hello()
# works! But:
oldperson.hello()
# does not
If the details of the type call aren't clear, then read e-satis' excellent answer on 'What is a metaclass in Python?'.
I've been struggling with this too, and was intrigued by your solution, but Python 3 takes it away from us:
AttributeError: attribute '__dict__' of 'type' objects is not writable
I actually have a legitimate need for a decorator that replaces the (single) superclass of the decorated class. It would require too lengthy a description to include here (I tried, but couldn't get it to a reasonably length and limited complexity -- it came up in the context of the use by many Python applications of an Python-based enterprise server where different applications needed slightly different variations of some of the code.)
The discussion on this page and others like it provided hints that the problem of assigning to __bases__ only occurs for classes with no superclass defined (i.e., whose only superclass is object). I was able to solve this problem (for both Python 2.7 and 3.2) by defining the classes whose superclass I needed to replace as being subclasses of a trivial class:
## T is used so that the other classes are not direct subclasses of object,
## since classes whose base is object don't allow assignment to their __bases__ attribute.
class T: pass
class A(T):
def __init__(self):
print('Creating instance of {}'.format(self.__class__.__name__))
## ordinary inheritance
class B(A): pass
## dynamically specified inheritance
class C(T): pass
A() # -> Creating instance of A
B() # -> Creating instance of B
C.__bases__ = (A,)
C() # -> Creating instance of C
## attempt at dynamically specified inheritance starting with a direct subclass
## of object doesn't work
class D: pass
D.__bases__ = (A,)
D()
## Result is:
## TypeError: __bases__ assignment: 'A' deallocator differs from 'object'
I can not vouch for the consequences, but that this code does what you want at py2.7.2.
class Friendly(object):
def hello(self):
print 'Hello'
class Person(object): pass
# we can't change the original classes, so we replace them
class newFriendly: pass
newFriendly.__dict__ = dict(Friendly.__dict__)
Friendly = newFriendly
class newPerson: pass
newPerson.__dict__ = dict(Person.__dict__)
Person = newPerson
p = Person()
Person.__bases__ = (Friendly,)
p.hello() # prints "Hello"
We know that this is possible. Cool. But we'll never use it!
Right of the bat, all the caveats of messing with class hierarchy dynamically are in effect.
But if it has to be done then, apparently, there is a hack that get's around the "deallocator differs from 'object" issue when modifying the __bases__ attribute for the new style classes.
You can define a class object
class Object(object): pass
Which derives a class from the built-in metaclass type.
That's it, now your new style classes can modify the __bases__ without any problem.
In my tests this actually worked very well as all existing (before changing the inheritance) instances of it and its derived classes felt the effect of the change including their mro getting updated.
I needed a solution for this which:
Works with both Python 2 (>= 2.7) and Python 3 (>= 3.2).
Lets the class bases be changed after dynamically importing a dependency.
Lets the class bases be changed from unit test code.
Works with types that have a custom metaclass.
Still allows unittest.mock.patch to function as expected.
Here's what I came up with:
def ensure_class_bases_begin_with(namespace, class_name, base_class):
""" Ensure the named class's bases start with the base class.
:param namespace: The namespace containing the class name.
:param class_name: The name of the class to alter.
:param base_class: The type to be the first base class for the
newly created type.
:return: ``None``.
Call this function after ensuring `base_class` is
available, before using the class named by `class_name`.
"""
existing_class = namespace[class_name]
assert isinstance(existing_class, type)
bases = list(existing_class.__bases__)
if base_class is bases[0]:
# Already bound to a type with the right bases.
return
bases.insert(0, base_class)
new_class_namespace = existing_class.__dict__.copy()
# Type creation will assign the correct ‘__dict__’ attribute.
del new_class_namespace['__dict__']
metaclass = existing_class.__metaclass__
new_class = metaclass(class_name, tuple(bases), new_class_namespace)
namespace[class_name] = new_class
Used like this within the application:
# foo.py
# Type `Bar` is not available at first, so can't inherit from it yet.
class Foo(object):
__metaclass__ = type
def __init__(self):
self.frob = "spam"
def __unicode__(self): return "Foo"
# … later …
import bar
ensure_class_bases_begin_with(
namespace=globals(),
class_name=str('Foo'), # `str` type differs on Python 2 vs. 3.
base_class=bar.Bar)
Use like this from within unit test code:
# test_foo.py
""" Unit test for `foo` module. """
import unittest
import mock
import foo
import bar
ensure_class_bases_begin_with(
namespace=foo.__dict__,
class_name=str('Foo'), # `str` type differs on Python 2 vs. 3.
base_class=bar.Bar)
class Foo_TestCase(unittest.TestCase):
""" Test cases for `Foo` class. """
def setUp(self):
patcher_unicode = mock.patch.object(
foo.Foo, '__unicode__')
patcher_unicode.start()
self.addCleanup(patcher_unicode.stop)
self.test_instance = foo.Foo()
patcher_frob = mock.patch.object(
self.test_instance, 'frob')
patcher_frob.start()
self.addCleanup(patcher_frob.stop)
def test_instantiate(self):
""" Should create an instance of `Foo`. """
instance = foo.Foo()
The above answers are good if you need to change an existing class at runtime. However, if you are just looking to create a new class that inherits by some other class, there is a much cleaner solution. I got this idea from https://stackoverflow.com/a/21060094/3533440, but I think the example below better illustrates a legitimate use case.
def make_default(Map, default_default=None):
"""Returns a class which behaves identically to the given
Map class, except it gives a default value for unknown keys."""
class DefaultMap(Map):
def __init__(self, default=default_default, **kwargs):
self._default = default
super().__init__(**kwargs)
def __missing__(self, key):
return self._default
return DefaultMap
DefaultDict = make_default(dict, default_default='wug')
d = DefaultDict(a=1, b=2)
assert d['a'] is 1
assert d['b'] is 2
assert d['c'] is 'wug'
Correct me if I'm wrong, but this strategy seems very readable to me, and I would use it in production code. This is very similar to functors in OCaml.
This method isn't technically inheriting during runtime, since __mro__ can't be changed. But what I'm doing here is using __getattr__ to be able to access any attributes or methods from a certain class. (Read comments in order of numbers placed before the comments, it makes more sense)
class Sub:
def __init__(self, f, cls):
self.f = f
self.cls = cls
# 6) this method will pass the self parameter
# (which is the original class object we passed)
# and then it will fill in the rest of the arguments
# using *args and **kwargs
def __call__(self, *args, **kwargs):
# 7) the multiple try / except statements
# are for making sure if an attribute was
# accessed instead of a function, the __call__
# method will just return the attribute
try:
return self.f(self.cls, *args, **kwargs)
except TypeError:
try:
return self.f(*args, **kwargs)
except TypeError:
return self.f
# 1) our base class
class S:
def __init__(self, func):
self.cls = func
def __getattr__(self, item):
# 5) we are wrapping the attribute we get in the Sub class
# so we can implement the __call__ method there
# to be able to pass the parameters in the correct order
return Sub(getattr(self.cls, item), self.cls)
# 2) class we want to inherit from
class L:
def run(self, s):
print("run" + s)
# 3) we create an instance of our base class
# and then pass an instance (or just the class object)
# as a parameter to this instance
s = S(L) # 4) in this case, I'm using the class object
s.run("1")
So this sort of substitution and redirection will simulate the inheritance of the class we wanted to inherit from. And it even works with attributes or methods that don't take any parameters.

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