Python Language Abstract Base Classes (abc) Why/How to use ABCMeta and @abstractmethod
Example
Abstract base classes (ABCs) enforce what derived classes implement particular methods from the base class.
To understand how this works and why we should use it, let's take a look at an example that Van Rossum would enjoy. Let's say we have a Base class "MontyPython" with two methods (joke & punchline) that must be implemented by all derived classes.
class MontyPython:
def joke(self):
raise NotImplementedError()
def punchline(self):
raise NotImplementedError()
class ArgumentClinic(MontyPython):
def joke(self):
return "Hahahahahah"
When we instantiate an object and call it's two methods, we'll get an error (as expected) with the punchline() method.
>>> sketch = ArgumentClinic()
>>> sketch.punchline()
NotImplementedError
However, this still allows us to instantiate an object of the ArgumentClinic class without getting an error. In fact we don't get an error until we look for the punchline().
This is avoided by using the Abstract Base Class (ABC) module. Let's see how this works with the same example:
from abc import ABCMeta, abstractmethod
class MontyPython(metaclass=ABCMeta):
@abstractmethod
def joke(self):
pass
@abstractmethod
def punchline(self):
pass
class ArgumentClinic(MontyPython):
def joke(self):
return "Hahahahahah"
This time when we try to instantiate an object from the incomplete class, we immediately get a TypeError!
>>> c = ArgumentClinic()
TypeError:
"Can't instantiate abstract class ArgumentClinic with abstract methods punchline"
In this case, it's easy to complete the class to avoid any TypeErrors:
class ArgumentClinic(MontyPython):
def joke(self):
return "Hahahahahah"
def punchline(self):
return "Send in the constable!"
This time when you instantiate an object it works!
