Metaclasses: Blueprints of Blueprints - Adding Some Meat
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Now let's add some more substance to the picture, since the purpose of metaclasses is not to just sit there and look pretty. We can start by sticking some variables into our metaclass:
>>> class MetaA ( type ):
x = 4
y = 19
z = ( 1, 2, 3 )
The classes created out of this metaclass will have the same variables:
>>> class A ( object ):
__metaclass__ = MetaA
>>> A.x
4
>>> A.y
19
>>> A.z
(1, 2, 3)
However, this isn't a very good use at all for metaclasses, since a regular class could do the same thing if A were to subclass it, and the process would be a bit simpler. However, just as a normal class can initialize an object, a metaclass can initialize a class:
>>> class MetaB ( type ):
def __init__ ( cls, name, bases, dct ):
print cls
print name
print bases
print dct
As you can see, the __init__ method accepts four variables: cls, name, bases and dct. The cls variable can be compared to self in normal classes. However, since we are dealing with a class instead of an object, it is named a bit differently. The name variable simply contains the name of the class, the bases variable contains a tuple of base classes, and the dct variable contains a dictionary of attributes. Another common name for this last variable is dict, though that gets in the way of the dictionary type since they share the same name in that situation. The __init__ method is called as soon as our class is created:
>>> class B ( object ):
__metaclass__ = MetaB
x = "c"
z = 1
y = z + 3
def __init__ ( self ):
print z + y
def test ( self ):
print x
<class '__main__.B'>
B
(<type 'object'>,)
{'__module__': '__main__', '__metaclass__': <class '__main__.MetaB'>, 'test': <function test at 0x00B4A570>, 'y': 4, 'x': 'c', 'z': 1, '__init__': <function __init__ at 0x00B4A2B0>}
The MetaB class simply displays the name of each variable. As you can see above, the dictionary of attributes provides us with an interesting link to the class's internals. This is a significant feature, and it gives us a lot of power over classes. It allows us to make some pretty interesting modifications to things that would not otherwise be possible. Consider class C:
>>> class C:
def one ( self ):
return True
five = four = three = two = one
Now, suppose that we didn't want to create that chain at the end, which assigns alternate names for the one method. We could use a metaclass to eliminate the need for that. For example, we could define the method as multi_one_two_three_four_five and have a metaclass rip it apart for us, creating methods one through five. It's actually pretty simple:
>>> class MetaD ( type ):
def __init__ ( cls, name, bases, dct ):
# Loop through the dictionary
for key, value in dct.iteritems():
# If the key starts with multi_, perform our work
if key.find ( 'multi_' ) == 0:
# Split the name to get the aliases
aliases = key.split ( '_' ) [ 1: ]
# Define the new names
for alias in aliases:
setattr ( cls, alias, value )
We simply loop through the dictionary, and if the attribute name starts with “multi_”, then we break it apart at each underscore and re-assign the value to each piece of the name. Here's our metaclass in action:
>>> class D ( object ):
__metaclass__ = MetaD
def multi_one_two_three_four_five ( self ):
return True
>>> x = D()
>>> x.one
<bound method D.multi_one_two_three_four_five of <__main__.D object at 0x00B4C3D0>>
>>> x.two
<bound method D.multi_one_two_three_four_five of <__main__.D object at 0x00B4C3D0>>
>>> x.three()
True
Metaclass MetaD might not be completely practical, but it demonstrates the power of metaclasses. We can use metaclasses to alter the behavior of classes, allowing for new levels of control over classes.
Next: Using Metaclasses >>
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