Meaning of @classmethod and @staticmethod for beginner?
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.
@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).
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 classmethod
s.
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 ourDate
class, all children will havefrom_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