如何在 Python 中实现虚方法？

Python methods are always virtual.

Sure, and you don't even have to define a method in the base class. In Python methods are better than virtual - they're completely dynamic, as the typing in Python is duck typing.

class Dog:
def say(self):
print "hau"


class Cat:
def say(self):
print "meow"


pet = Dog()
pet.say() # prints "hau"
another_pet = Cat()
another_pet.say() # prints "meow"


my_pets = [pet, another_pet]
for a_pet in my_pets:
a_pet.say()

Cat and Dog in Python don't even have to derive from a common base class to allow this behavior - you gain it for free. That said, some programmers prefer to define their class hierarchies in a more rigid way to document it better and impose some strictness of typing. This is also possible - see for example the abc standard module.

Actually, in version 2.6 python provides something called abstract base classes and you can explicitly set virtual methods like this:

from abc import ABCMeta
from abc import abstractmethod
...
class C:
__metaclass__ = ABCMeta
@abstractmethod
def my_abstract_method(self, ...):

It works very well, provided the class does not inherit from classes that already use metaclasses.

source: http://docs.python.org/2/library/abc.html

Python methods are always virtual

like Ignacio said yet Somehow class inheritance may be a better approach to implement what you want.

class Animal:
def __init__(self,name,legs):
self.name = name
self.legs = legs


def getLegs(self):
return "{0} has {1} legs".format(self.name, self.legs)


def says(self):
return "I am an unknown animal"


class Dog(Animal): # <Dog inherits from Animal here (all methods as well)


def says(self): # <Called instead of Animal says method
return "I am a dog named {0}".format(self.name)


def somethingOnlyADogCanDo(self):
return "be loyal"


formless = Animal("Animal", 0)
rover = Dog("Rover", 4) #<calls initialization method from animal


print(formless.says()) # <calls animal say method


print(rover.says()) #<calls Dog says method
print(rover.getLegs()) #<calls getLegs method from animal class

Results should be:

I am an unknown animal
I am a dog named Rover
Rover has 4 legs

raise NotImplementedError()

This is the recommended exception to raise on "pure virtual methods" of "abstract" base classes that don't implement a method.

https://docs.python.org/3.5/library/exceptions.html#NotImplementedError says:

This exception is derived from RuntimeError. In user defined base classes, abstract methods should raise this exception when they require derived classes to override the method.

As others said, this is mostly a documentation convention and is not required, but this way you get a more meaningful exception than a missing attribute error.

E.g.:

class Base(object):
def virtualMethod(self):
raise NotImplementedError()
def usesVirtualMethod(self):
return self.virtualMethod() + 1


class Derived(Base):
def virtualMethod(self):
return 1


print Derived().usesVirtualMethod()
Base().usesVirtualMethod()

gives:

2
Traceback (most recent call last):
File "./a.py", line 13, in <module>
Base().usesVirtualMethod()
File "./a.py", line 6, in usesVirtualMethod
return self.virtualMethod() + 1
File "./a.py", line 4, in virtualMethod
raise NotImplementedError()
NotImplementedError

Related: Is it possible to make abstract classes in Python?

Something like a virtual method in C++ (calling method implementation of a derived class through a reference or pointer to the base class) doesn't make sense in Python, as Python doesn't have typing. (I don't know how virtual methods work in Java and PHP though.)

But if by "virtual" you mean calling the bottom-most implementation in the inheritance hierarchy, then that's what you always get in Python, as several answers point out.

Well, almost always...

As dplamp pointed out, not all methods in Python behave like that. Dunder method don't. And I think that's a not so well known feature.

Consider this artificial example

class A:
def prop_a(self):
return 1
def prop_b(self):
return 10 * self.prop_a()


class B(A):
def prop_a(self):
return 2

Now

>>> B().prop_b()
20
>>> A().prob_b()
10

However, consider this one

class A:
def __prop_a(self):
return 1
def prop_b(self):
return 10 * self.__prop_a()


class B(A):
def __prop_a(self):
return 2

Now

>>> B().prop_b()
10
>>> A().prob_b()
10

The only thing we've changes was making prop_a() a dunder method.

A problem with the first behavior can be that you can't change the behavior of prop_a() in the derived class without impacting the behavior of prop_b(). This very nice talk by Raymond Hettinger gives an example for a use case where this is inconvenient.

Python 3.6 introduced __init_subclass__ and this let you simply do this:

class A:


def method(self):
'''method needs to be overwritten'''
return NotImplemented


def __init_subclass__(cls):
if cls.method is A.method:
raise NotImplementedError(
'Subclass has not overwritten method {method}!')

The benefit of this solution is that you avoid the abc metaclass and give the user a direct imperative how to do it right. In addition to another answer here that raises NotImplementedError when calling the method. This solution is checked on runtime and not only IF the user calls the method.