@Oddthinking's answer is not wrong, but I think it misses the real, practical reason Python has ABCs in a world of duck-typing.
Abstract methods are neat, but in my opinion they don't really fill any use-cases not already covered by duck typing. Abstract base classes' real power lies in the way they allow you to customise the behaviour of isinstance and issubclass. (__subclasshook__ is basically a friendlier API on top of Python's __instancecheck__ and __subclasscheck__ hooks.) Adapting built-in constructs to work on custom types is very much part of Python's philosophy.
Python's source code is exemplary. Here is how collections.Container is defined in the standard library (at time of writing):
class Container(metaclass=ABCMeta):
__slots__ = ()
@abstractmethod
def __contains__(self, x):
return False
@classmethod
def __subclasshook__(cls, C):
if cls is Container:
if any("__contains__" in B.__dict__ for B in C.__mro__):
return True
return NotImplemented
This definition of __subclasshook__ says that any class with a __contains__ attribute is considered to be a subclass of Container, even if it doesn't subclass it directly. So I can write this:
class ContainAllTheThings(object):
def __contains__(self, item):
return True
>>> issubclass(ContainAllTheThings, collections.Container)
True
>>> isinstance(ContainAllTheThings(), collections.Container)
True
In other words, if you implement the right interface, you're a subclass! ABCs provide a formal way to define interfaces in Python, while staying true to the spirit of duck-typing. Besides, this works in a way that honours the Open-Closed Principle.
Python's object model looks superficially similar to that of a more "traditional" OO system (by which I mean Java*) - we got yer classes, yer objects, yer methods - but when you scratch the surface you'll find something far richer and more flexible. Likewise, Python's notion of abstract base classes may be recognisable to a Java developer, but in practice they are intended for a very different purpose.
I sometimes find myself writing polymorphic functions that can act on a single item or a collection of items, and I find isinstance(x, collections.Iterable) to be much more readable than hasattr(x, '__iter__') or an equivalent try...except block. (If you didn't know Python, which of those three would make the intention of the code clearest?)
That said, I find that I rarely need to write my own ABC and I typically discover the need for one through refactoring. If I see a polymorphic function making a lot of attribute checks, or lots of functions making the same attribute checks, that smell suggests the existence of an ABC waiting to be extracted.
*without getting into the debate over whether Java is a "traditional" OO system...
Addendum: Even though an abstract base class can override the behaviour of isinstance and issubclass, it still doesn't enter the MRO of the virtual subclass. This is a potential pitfall for clients: not every object for which isinstance(x, MyABC) == True has the methods defined on MyABC.
class MyABC(metaclass=abc.ABCMeta):
def abc_method(self):
pass
@classmethod
def __subclasshook__(cls, C):
return True
class C(object):
pass
# typical client code
c = C()
if isinstance(c, MyABC): # will be true
c.abc_method() # raises AttributeError
Unfortunately this one of those "just don't do that" traps (of which Python has relatively few!): avoid defining ABCs with both a __subclasshook__ and non-abstract methods. Moreover, you should make your definition of __subclasshook__ consistent with the set of abstract methods your ABC defines.
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@Oddthinking's answer is not wrong, but I think it misses the real, practical reason Python has ABCs in a world of duck-typing.
Abstract methods are neat, but in my opinion they don't really fill any use-cases not already covered by duck typing. Abstract base classes' real power lies in the way they allow you to customise the behaviour of isinstance and issubclass. (__subclasshook__ is basically a friendlier API on top of Python's __instancecheck__ and __subclasscheck__ hooks.) Adapting built-in constructs to work on custom types is very much part of Python's philosophy.
Python's source code is exemplary. Here is how collections.Container is defined in the standard library (at time of writing):
class Container(metaclass=ABCMeta):
__slots__ = ()
@abstractmethod
def __contains__(self, x):
return False
@classmethod
def __subclasshook__(cls, C):
if cls is Container:
if any("__contains__" in B.__dict__ for B in C.__mro__):
return True
return NotImplemented
This definition of __subclasshook__ says that any class with a __contains__ attribute is considered to be a subclass of Container, even if it doesn't subclass it directly. So I can write this:
class ContainAllTheThings(object):
def __contains__(self, item):
return True
>>> issubclass(ContainAllTheThings, collections.Container)
True
>>> isinstance(ContainAllTheThings(), collections.Container)
True
In other words, if you implement the right interface, you're a subclass! ABCs provide a formal way to define interfaces in Python, while staying true to the spirit of duck-typing. Besides, this works in a way that honours the Open-Closed Principle.
Python's object model looks superficially similar to that of a more "traditional" OO system (by which I mean Java*) - we got yer classes, yer objects, yer methods - but when you scratch the surface you'll find something far richer and more flexible. Likewise, Python's notion of abstract base classes may be recognisable to a Java developer, but in practice they are intended for a very different purpose.
I sometimes find myself writing polymorphic functions that can act on a single item or a collection of items, and I find isinstance(x, collections.Iterable) to be much more readable than hasattr(x, '__iter__') or an equivalent try...except block. (If you didn't know Python, which of those three would make the intention of the code clearest?)
That said, I find that I rarely need to write my own ABC and I typically discover the need for one through refactoring. If I see a polymorphic function making a lot of attribute checks, or lots of functions making the same attribute checks, that smell suggests the existence of an ABC waiting to be extracted.
*without getting into the debate over whether Java is a "traditional" OO system...
Addendum: Even though an abstract base class can override the behaviour of isinstance and issubclass, it still doesn't enter the MRO of the virtual subclass. This is a potential pitfall for clients: not every object for which isinstance(x, MyABC) == True has the methods defined on MyABC.
class MyABC(metaclass=abc.ABCMeta):
def abc_method(self):
pass
@classmethod
def __subclasshook__(cls, C):
return True
class C(object):
pass
# typical client code
c = C()
if isinstance(c, MyABC): # will be true
c.abc_method() # raises AttributeError
Unfortunately this one of those "just don't do that" traps (of which Python has relatively few!): avoid defining ABCs with both a __subclasshook__ and non-abstract methods. Moreover, you should make your definition of __subclasshook__ consistent with the set of abstract methods your ABC defines.
Short version
ABCs offer a higher level of semantic contract between clients and the implemented classes.
Long version
There is a contract between a class and its callers. The class promises to do certain things and have certain properties.
There are different levels to the contract.
At a very low level, the contract might include the name of a method or its number of parameters.
In a staticly-typed language, that contract would actually be enforced by the compiler. In Python, you can use EAFP or type introspection to confirm that the unknown object meets this expected contract.
But there are also higher-level, semantic promises in the contract.
For example, if there is a __str__() method, it is expected to return a string representation of the object. It could delete all contents of the object, commit the transaction and spit a blank page out of the printer... but there is a common understanding of what it should do, described in the Python manual.
That's a special case, where the semantic contract is described in the manual. What should the print() method do? Should it write the object to a printer or a line to the screen, or something else? It depends - you need to read the comments to understand the full contract here. A piece of client code that simply checks that the print() method exists has confirmed part of the contract - that a method call can be made, but not that there is agreement on the higher level semantics of the call.
Defining an Abstract Base Class (ABC) is a way of producing a contract between the class implementers and the callers. It isn't just a list of method names, but a shared understanding of what those methods should do. If you inherit from this ABC, you are promising to follow all the rules described in the comments, including the semantics of the print() method.
Python's duck-typing has many advantages in flexibility over static-typing, but it doesn't solve all the problems. ABCs offer an intermediate solution between the free-form of Python and the bondage-and-discipline of a staticly-typed language.
I am being asked to maintain code that subclasses from abc.ABC. I have read the python documentation, the associated PEP, and even visited pymotw. I do not understand what abstract classes give you.
If I have class A and then I derive subclass B from it wouldn't issubclass(B,A) still be true?
Hello. In this first example, I have a short and straightforward code w/ a class for interface. It doesn't inherit from ABC and doesn't have any abstract methods.
class Abs():
def __init__(self, name, age):
self.name = name
self.age = age
def go_to(self):
return f"{self.name} is going to {self.place}."
class Teacher(Abs):
place = "work"
class Student(Abs):
place = "school"
t1 = Teacher("James", 56)
s1 = Student("Tim", 15)
print(t1.go_to())
print(s1.go_to())In this second example, it's the exact opposite.
from abc import ABC, abstractmethod
class Abs(ABC):
def __init__(self, name, age):
self.name = name
self.age = age
@abstractmethod
def go_to(self):
...
class Teacher(Abs):
place = "work"
def go_to(self):
return f"{self.name} is going to {self.place}."
class Student(Abs):
place = "school"
def go_to(self):
return f"{self.name} is going to {self.place}."
t1 = Teacher("James", 56)
s1 = Student("Tim", 15)
print(t1.go_to())
print(s1.go_to())Both examples have the same output. In the tutorials/articles I've read, most times the second example is preferred. In the abstract class, abstract methods get defined and decorated, and then in the inheriting classes they all get redefined with the rest of the logic. What's the point of creating a class w/ abstract methods which later on we redefine? What issue does that solve? Why not just proceed as in the first example - simple, less code, one parent class for the interface, if we need to add other details, we do so in the base class once and handle the extra logic with that additional info there. Doesn't the first code present a better example of loose coupling - just one connection between parent and child classes, where in the second code, we get connections between parent/child in every method that we redefine? I feel like I'm missing something, because to me, the second example is much more spaghetti-like. If anyone can explain why it's a good practice to redefine abstract methods that would be nice. Also, is it a bad practice to write code as in the first example, w/o ABC+@abstractmethod in the parent class?
Thanks.