The Definitive Guide on How to Use Static, Class or Abstract Methods in Python
Doing code reviews is a great way to discover things that people might struggle to comprehend. While proof-reading OpenStack patches recently, I spotted that people were not correctly using the various decorators Python provides for methods. So, here's my attempt at providing me with a link to send in my next code reviews. :-)
How Methods Work in Python
A method is a function that is stored as a class attribute. You can declare and access such a function this way:
>>> class Pizza(object): ... def __init__(self, size): ... self.size = size ... def get_size(self): ... return self.size ... >>> Pizza.get_size <unbound method Pizza.get_size>
What Python tells you here is that the attribute get_size of the class Pizza is a method that is unbound. What does this mean? We'll know as soon as we try to call it:
>>> Pizza.get_size() Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: unbound method get_size() must be called with Pizza instance as first argument (got nothing instead)
We can't call it because it's not bound to any instance of Pizza. A method wants an instance as its first argument (in Python 2 it must be an instance of that class and in Python 3 it could be anything). Let's try to do that, then:
>>> Pizza.get_size(Pizza(42)) 42
It worked! We called the method with an instance as its first argument, so everything's fine. But you will agree with me if I say this is not a very handy way to call methods -- we have to refer to the class each time we want to call a method. And if we don't know what class our object is, this is not going to work for very long.
So what Python does for us is that it binds all the methods from the class Pizza to any instance of this class. This means that the attribute get_size of an instance of Pizza is a bound method: a method for which the first argument will be the instance itself.
>>> Pizza(42).get_size <bound method Pizza.get_size of <__main__.Pizza object at 0x7f3138827910>> >>> Pizza(42).get_size() 42
As expected, we don't have to provide any argument to get_size, since it's bound, its self argument is automatically set to our Pizza instance. Here's an even better proof of that:
>>> m = Pizza(42).get_size >>> m() 42
Indeed, you don't even have to keep a reference to your Pizza object. Its method is bound to the object, so the method is sufficient to itself.
But what if you wanted to know which object this bound method is bound to? Here's a little trick:
>>> m = Pizza(42).get_size >>> m.__self__ <__main__.Pizza object at 0x7f3138827910> >>> # You could guess, look at this: ... >>> m == m.__self__.get_size True
Obviously, we still have a reference to our object, and we can find it back if we want.
In Python 3, the functions attached to a class are not considered an unbound method anymore, but as simple functions that are bound to an object if required. So the principle stays the same, the model is just simplified.
>>> class Pizza(object): ... def __init__(self, size): ... self.size = size ... def get_size(self): ... return self.size ... >>> Pizza.get_size <function Pizza.get_size at 0x7f307f984dd0>
Static methods are a special case of methods. Sometimes, you'll write code that belongs to a class, but that doesn't use the object itself at all. For example:
class Pizza(object): @staticmethod def mix_ingredients(x, y): return x + y def cook(self): return self.mix_ingredients(self.cheese, self.vegetables)
In such a case, writing mix_ingredients as a non-static method would work too, but it would provide a self argument that would not be used. Here, the decorator @staticmethod buys us several things:
- Python doesn't have to instantiate a bound method for each Pizza object we instiantiate. Bound methods are objects too, and creating them has a cost. Having a static method avoids that:
>>> Pizza().cook is Pizza().cook False >>> Pizza().mix_ingredients is Pizza.mix_ingredients True >>> Pizza().mix_ingredients is Pizza().mix_ingredients True
It eases the readability of the code: seeing @staticmethod, we know that the method does not depend on the state of object itself.
It allows us to override the mix_ingredients method in a subclass. If we used a function mix_ingredients defined at the top-level of our module, a class inheriting from Pizza wouln't be able to change the way we mix ingredients for our pizza without overriding cook itself.
Having said that, what are class methods? Class methods are methods that are not bound to an object, but to … a class!
>>> class Pizza(object): ... radius = 42 ... @classmethod ... def get_radius(cls): ... return cls.radius ... >>> >>> Pizza.get_radius <bound method type.get_radius of <class '__main__.Pizza'>> >>> Pizza().get_radius <bound method type.get_radius of <class '__main__.Pizza'>> >>> Pizza.get_radius is Pizza().get_radius True >>> Pizza.get_radius() 42
No matter which way you use to access this method, it will always be bound to the class it is attached too, and its first argument will be the class itself (remember that classes are objects, too).
When to use this kind of method? Well, class methods are mostly useful for two types of methods:
- Factory methods that are used to create an instance for a class using, for example, some sort of pre-processing. If we use a @staticmethod instead, we would have to hard-code the Pizza class name in our function, making any class inheriting from Pizza unable to use our factory for its own use.
class Pizza(object): def __init__(self, ingredients): self.ingredients = ingredients @classmethod def from_fridge(cls, fridge): return cls(fridge.get_cheese() + fridge.get_vegetables())
- Static methods calling static methods: if you split a static method in to several static methods, you shouldn't hard-code the class name but you should use class methods. Using this way to declare your method, the Pizza name is never directly referenced, and inheritance and method overriding will work flawlessly
class Pizza(object): def __init__(self, radius, height): self.radius = radius self.height = height @staticmethod def compute_circumference(radius): return math.pi * (radius ** 2) @classmethod def compute_volume(cls, height, radius): return height * cls.compute_circumference(radius) def get_volume(self): return self.compute_volume(self.height, self.radius)
An abstract method is a method defined in a base class, but that may not provide any implementation. In Java, it would describe the methods of an interface.
So, the simplest way to write an abstract method in Python is:
class Pizza(object): def get_radius(self): raise NotImplementedError
Any class inheriting from Pizza should implement and override the get_radius method, otherwise an exception would be raised.
This particular way of implementing an abstract method has a drawback. If you write a class that inherits from Pizza and forget to implement get_radius, the error will only be raised when you try to use that method.
>>> Pizza() <__main__.Pizza object at 0x7fb747353d90> >>> Pizza().get_radius() Traceback (most recent call last): File "<stdin>", line 1, in <module> File "<stdin>", line 3, in get_radius NotImplementedError
There's a way to trigger this way earlier, when the object is being instantiated, using the ABC module that's provided with Python.
import abc class BasePizza(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def get_radius(self): """Method that should do something."""
Using abc and its special class, as soon as you try to instantiate BasePizza or any class inheriting from it, you'll get a TypeError.
>>> BasePizza() Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: Can't instantiate abstract class BasePizza with abstract methods get_radius
Mixing Static, Class and Abstract Methods
When building classes and inheritances, the time will come when you will have to mix all of these method decorators. So, here's some tips about such a situation.
Keep in mind that declaring a class as abstract doesn't freeze the prototype of that method. That means that it must be implemented, but it can be implemented with any argument list.
import abc class BasePizza(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def get_ingredients(self): """Returns the ingredient list.""" class Calzone(BasePizza): def get_ingredients(self, with_egg=False): egg = Egg() if with_egg else None return self.ingredients + egg
This is valid, since Calzone fulfills the interface requirement we defined for BasePizza objects. That means that we could also implement it as being a class or a static method, for example:
import abc class BasePizza(object): __metaclass__ = abc.ABCMeta @abc.abstractmethod def get_ingredients(self): """Returns the ingredient list.""" class DietPizza(BasePizza): @staticmethod def get_ingredients(): return None
This is also correct and fulfills the contract we have with our abstract BasePizza class. The fact that the get_ingredients method doesn't need to know about the object to return a result is an implementation detail, not a criteria to have our contract fulfilled.
Therefore, you can't force an implementation of your abstract method to be a regular, class or static method, and arguably you shouldn't. Starting with Python 3 (this won't work as you would expect in Python 2, see issue 5867), it's now possible to use the @staticmethod and @classmethod decorators on top of @abstractmethod:
import abc class BasePizza(object): __metaclass__ = abc.ABCMeta ingredient = ['cheese'] @classmethod @abc.abstractmethod def get_ingredients(cls): """Returns the ingredient list.""" return cls.ingredients
Don't misread this: If you think this is going to force your subclasses to implement get_ingredients as a class method, you are wrong. This simply implies that your implementation of get_ingredients in the BasePizza class is a class method.
An implementation in an abstract method? Yes! In Python, contrary to methods in Java interfaces, you can have code in your abstract methods and call it via super():
import abc class BasePizza(object): __metaclass__ = abc.ABCMeta default_ingredients = ['cheese'] @classmethod @abc.abstractmethod def get_ingredients(cls): """Returns the ingredient list.""" return cls.default_ingredients class DietPizza(BasePizza): def get_ingredients(self): return ['egg'] + super(DietPizza, self).get_ingredients()
In such a case, every pizza you will build by inheriting from BasePizza will have to override the get_ingredients method, but will be able to use the default mechanism to get the ingredient list by using super().
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