Python是面向对象的编程语言，也支持类继承。
>>> class Base:
... pass
...
>>> class Derived(Base):
... pass
这样就定义了两个类，Derived继承了Base。issubclass(a,b)能够測试继承关系：
>>> issubclass(Derived, Base)
True
在Python中，每一个类有一个__bases__属性，列出其基类
>>> Derived.__bases__
(<class '__main__.Base'>,)
同C++，Python支持多重继承；
>>> class Derived2(Derived,Base):
... pass
...
Derived2继承了Derived和Base（实际中不会这么写）
>>> Derived2.__bases__
(<class '__main__.Derived'>, <class '__main__.Base'>)
这里，Derived,和Base的顺序不能搞反
>>> class Derived2(Base, Derived):
... pass
...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Cannot create a consistent method resolution
order (MRO) for bases Derived, Base
插一段C++
|
C++代码 |
|
class Base{ };
class Derived: public Base{ };
class Derived2: public Base, public Derived{ };
int main(){ } |
|
mulit_inherit.cc:7:7: warning: direct base 'Base' inaccessible in 'Derived2' due to ambiguity [enabled by default] class Derived2: public Base, public Derived{ ^ |
|
mulit_inherit.cc:7:7: warning: direct base 'Base' inaccessible in 'Derived2' due to ambiguity [enabled by default] class Derived2: public Derived, public Base{ ^ |
能够见，C++并没有限制书写顺序。warning指示了Derrived2中不能訪问Base
Derived2 d;
Base &b = d;
error: 'Base' is an ambiguous base of 'Derived2'
Base &b = d;
^
回到Python继承，Derived2是Derived的子类，也是Base的子类
>>> issubclass(Derived2, Base)
True
>>> issubclass(Derived2, Derived)
True
__bases__类似于Javascript中Object对象的__proto__，是实现继承的基础，不同在于：__bases__不可改动，并且__bases__是类的属性而不是对象属性（Javascript是基于对象的语言）；
>>> d = Derived2()
>>> d.__bases__
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Derived2' object has no attribute '__bases__'
>>> d.__class__
<class '__main__.Derived2'>
>>> d.__class__.__bases__
(<class '__main__.Derived'>, <class '__main__.Base'>)
对象的__class__属性指明了所属类型；
>>> [].__class__
<class 'list'>
>>> ().__class__
<class 'tuple'>
>>> 1.__class__
File "<stdin>", line 1
1.__class__
^
SyntaxError: invalid syntax
>>> type(1)
<class 'int'>
在Python中1，是对象还是基本类型？
__mro__
__mro__给出了method resolution order，即解析方法调用的顺序。
>>> Derived.__mro__
(<class '__main__.Derived'>, <class '__main__.Base'>, <class 'object'>)
>>> Derived2.__mro__
(<class '__main__.Derived2'>, <class '__main__.Derived'>, <class '__main__.Base'>, <class 'object'>)
看上去和__bases__相像，仅仅是最后面多了个<class 'object'>
super
super函数能够用于调用父类的方法，而后者可能被子类覆盖；类似在java中的作用，但使用起来更复杂些。
>>> class Base:
... pass
...
>>> class Derived(Base):
... pass
...
>>> class Derived2(Derived)
File "<stdin>", line 1
class Derived2(Derived)
^
SyntaxError: invalid syntax
>>> class Derived2(Derived):
... pass
...
>>> d = Derived2()
>>> super(Derived2, d)
<super: <class 'Derived2'>, <Derived2 object>>
>>> super(Derived, d)
<super: <class 'Derived'>, <Derived2 object>>
>>> super(Base, d)
<super: <class 'Base'>, <Derived2 object>>
參考https://docs.python.org/2/library/functions.html#super，
super(type[, object-or-type])
Return a proxy object that delegates method calls to a parent or sibling class of type. This is useful for accessing inherited methods that have been overridden in a class. The search order is same as that used by getattr() except that the type itself is skipped.
The __mro__ attribute of the type lists the method resolution search order used by both getattr() and super().
>>> isinstance(super(Base, d), Base)
False
>>> isinstance(super(Derived, d), Base)
False
代理对象并非类层次中某个类的实例！
结合多重继承来理解下__mro__和super
class A:
def __init__(self):
print('enter __init__@A')
super(A,self).__init__()
print('exit __init__@A')
class B(A):
def __init__(self):
print('enter __init__@B')
super(B,self).__init__()
print('exit __init__@B')
class C(A):
def __init__(self):
print('enter __init__@C')
super(C,self).__init__()
print('exit __init__@C')
class D(A):
def __init__(self):
print('enter __init__@D')
super(D,self).__init__()
print('exit __init__@D')
class E(B,C):
def __init__(self):
print('enter __init__@E')
super(E,self).__init__()
print('exit __init__@E')
class F(E,D):
def __init__(self):
print('enter __init__@F')
super(F,self).__init__()
print('exit __init__@F')
if __name__ == '__main__':
A()
print(A.__mro__)
B()
print(B.__mro__)
C()
print(C.__mro__)
D()
print(D.__mro__)
E()
print(E.__mro__)
F()
print(F.__mro__)
执行结果
|
enter __init__@A exit __init__@A (<class '__main__.A'>, <class 'object'>) enter __init__@B enter __init__@A exit __init__@A exit __init__@B (<class '__main__.B'>, <class '__main__.A'>, <class 'object'>) enter __init__@C enter __init__@A exit __init__@A exit __init__@C (<class '__main__.C'>, <class '__main__.A'>, <class 'object'>) enter __init__@D enter __init__@A exit __init__@A exit __init__@D (<class '__main__.D'>, <class '__main__.A'>, <class 'object'>) enter __init__@E enter __init__@B enter __init__@C enter __init__@A exit __init__@A exit __init__@C exit __init__@B exit __init__@E (<class '__main__.E'>, <class '__main__.B'>, <class '__main__.C'>, <class '__main__.A'>, <class 'object'>) enter __init__@F enter __init__@E enter __init__@B enter __init__@C enter __init__@D enter __init__@A exit __init__@A exit __init__@D exit __init__@C exit __init__@B exit __init__@E exit __init__@F (<class '__main__.F'>, <class '__main__.E'>, <class '__main__.B'>, <class '__main__.C'>, <class '__main__.D'>, <class '__main__.A'>, <class 'object'>) |
观察到，super的运行路径和类的__mro__列举的类顺序吻合；而__mro__的顺序能够看作是深搜的结果
A
/ |
B C D
/ /
E /
/
F
class E(B, C)中，B和C不是基-派生类关系，E.__mro__中B在C之前，须要注意；
多态
>>> class Base:
... def sayHello(self):
... print("Base says hello")
...
>>> class Derived(Base):
... pass
...
>>> d = Derived()
>>> d.sayHello()
Base says hello
Derived重写sayHello
>>> class Derived(Base):
... def sayHello(self):
... print("Derived says hello");
...
>>> d = Derived()
>>> d.sayHello()
Derived says hello
与參数默认值结合（联想起了C++）
>>> class Base:
... def sayHello(self, str="Base"):
... print("Base says: " + str)
...
>>> class Derived(Base):
... def sayHello(self, str="Derived"):
... print("Dervied says: " + str)
...
>>>
>>> d = Derived()
>>> d.sayHello()
Dervied says: Derived
>>> Base.sayHello(d)
Base says: Base
>>> super(Derived, d).sayHello()
Base says: Base
看一下，在基类构造函数中调用被覆盖方法的行为
>>> class Base:
... def sayHello(self):
... str = self.getStr()
... print("Base says: " + str)
... def getStr(self):
... return "Base"
...
>>> class Derived(Base):
... def getStr(self):
... return "Derived"
...
>>>
>>> d = Derived()
>>> d.sayHello()
Base says: Derived
>>> def Base_init(self):
... self.sayHello()
...
>>> Base.__init__ = Base_init
>>> d = Derived()
Base says: Derived
可见，行为类似Java，调用了子类的覆盖方法；