新式课程中的方法解决顺序(MRO)？

Question

在Python in a Nutshell(第2版)一书中,有一个示例使用
旧样式类来演示如何以经典分辨率顺序解析方法,
以及它与新顺序的不同之处.

我通过重写新样式的示例尝试了相同的示例,但结果与使用旧样式类获得的结果没有什么不同.我用来运行该示例的python版本是2.5.2.以下是示例:

class Base1(object):  
    def amethod(self): print "Base1"  

class Base2(Base1):  
    pass

class Base3(object):  
    def amethod(self): print "Base3"

class Derived(Base2,Base3):  
    pass

instance = Derived()  
instance.amethod()  
print Derived.__mro__  

调用instance.amethod()打印Base1,但根据我对MRO的理解,新类型的输出应该是Base3.通话Derived.__mro__打印:

(<class '__main__.Derived'>, <class '__main__.Base2'>, <class '__main__.Base1'>, <class '__main__.Base3'>, <type 'object'>)

我不确定我对新样式类的MRO的理解是不正确的还是我做了一个我无法察觉的愚蠢错误.请帮助我更好地了解MRO.

Answer 1

传统与新式类的解析顺序之间的关键区别在于,在"天真",深度优先的方法中,同一祖先类不止一次出现 - 例如,考虑"钻石继承"案例:

>>> class A: x = 'a'
... 
>>> class B(A): pass
... 
>>> class C(A): x = 'c'
... 
>>> class D(B, C): pass
... 
>>> D.x
'a'

在这里,传统风格,分辨率顺序是D - B - A - C - A:所以当查找Dx时,A是解决它的分辨率顺序的第一个基础,从而将定义隐藏在C中.

>>> class A(object): x = 'a'
... 
>>> class B(A): pass
... 
>>> class C(A): x = 'c'
... 
>>> class D(B, C): pass
... 
>>> D.x
'c'
>>> 

在这里,新式,顺序是:

>>> D.__mro__
(<class '__main__.D'>, <class '__main__.B'>, <class '__main__.C'>, 
    <class '__main__.A'>, <type 'object'>)

与A被迫解析顺序进来只有一次,毕竟它的子类,从而使覆盖(即尺寸材料的的覆盖x)实际上有效地工作.

这是应该避免使用旧式类的原因之一:使用"类似钻石"模式的多重继承对它们不起作用,而它与新风格一起使用.

Answer 2

Python的方法解析顺序实际上比仅仅理解菱形模式更复杂.要真正理解它,请看一下C3线性化.我发现在扩展跟踪订单的方法时使用print语句确实很有帮助.例如,您认为这种模式的输出是什么？(注意:'X'假设是两个交叉边,而不是节点,^表示调用super()的方法)

class G():
    def m(self):
        print("G")

class F(G):
    def m(self):
        print("F")
        super().m()

class E(G):
    def m(self):
        print("E")
        super().m()

class D(G):
    def m(self):
        print("D")
        super().m()

class C(E):
    def m(self):
        print("C")
        super().m()

class B(D, E, F):
    def m(self):
        print("B")
        super().m()

class A(B, C):
    def m(self):
        print("A")
        super().m()


#      A^
#     / \
#    B^  C^
#   /| X
# D^ E^ F^
#  \ | /
#    G

你有ABDCEFG吗？

x = A()
x.m()

经过大量的试验错误,我想出了一个非正式的图形理论解释C3线性化如下:(如果这是错误的,请有人告诉我.)

考虑这个例子:

class I(G):
    def m(self):
        print("I")
        super().m()

class H():
    def m(self):
        print("H")

class G(H):
    def m(self):
        print("G")
        super().m()

class F(H):
    def m(self):
        print("F")
        super().m()

class E(H):
    def m(self):
        print("E")
        super().m()

class D(F):
    def m(self):
        print("D")
        super().m()

class C(E, F, G):
    def m(self):
        print("C")
        super().m()

class B():
    def m(self):
        print("B")
        super().m()

class A(B, C, D):
    def m(self):
        print("A")
        super().m()

# Algorithm:

# 1. Build an inheritance graph such that the children point at the parents (you'll have to imagine the arrows are there) and
#    keeping the correct left to right order. (I've marked methods that call super with ^)

#          A^
#       /  |  \
#     /    |    \
#   B^     C^    D^  I^
#        / | \  /   /
#       /  |  X    /   
#      /   |/  \  /     
#    E^    F^   G^
#     \    |    /
#       \  |  / 
#          H
# (In this example, A is a child of B, so imagine an edge going FROM A TO B)

# 2. Remove all classes that aren't eventually inherited by A

#          A^
#       /  |  \
#     /    |    \
#   B^     C^    D^
#        / | \  /  
#       /  |  X    
#      /   |/  \ 
#    E^    F^   G^
#     \    |    /
#       \  |  / 
#          H

# 3. For each level of the graph from bottom to top
#       For each node in the level from right to left
#           Remove all of the edges coming into the node except for the right-most one
#           Remove all of the edges going out of the node except for the left-most one

# Level {H}
#
#          A^
#       /  |  \
#     /    |    \
#   B^     C^    D^
#        / | \  /  
#       /  |  X    
#      /   |/  \ 
#    E^    F^   G^
#               |
#               |
#               H

# Level {G F E}
#
#         A^
#       / |  \
#     /   |    \
#   B^    C^   D^
#         | \ /  
#         |  X    
#         | | \
#         E^F^ G^
#              |
#              |
#              H

# Level {D C B}
#
#      A^
#     /| \
#    / |  \
#   B^ C^ D^
#      |  |  
#      |  |    
#      |  |  
#      E^ F^ G^
#            |
#            |
#            H

# Level {A}
#
#   A^
#   |
#   |
#   B^  C^  D^
#       |   |
#       |   |
#       |   |
#       E^  F^  G^
#               |
#               |
#               H

# The resolution order can now be determined by reading from top to bottom, left to right.  A B C E D F G H

x = A()
x.m()

Answer 3

你得到的结果是正确的.尝试更改Base3to的基类Base1并与经典类的相同层次结构进行比较:

class Base1(object):
    def amethod(self): print "Base1"

class Base2(Base1):
    pass

class Base3(Base1):
    def amethod(self): print "Base3"

class Derived(Base2,Base3):
    pass

instance = Derived()
instance.amethod()


class Base1:
    def amethod(self): print "Base1"

class Base2(Base1):
    pass

class Base3(Base1):
    def amethod(self): print "Base3"

class Derived(Base2,Base3):
    pass

instance = Derived()
instance.amethod()

现在输出:

Base3
Base1

阅读此说明以获取更多信息.