Decorators versus __metaclass__¶
Whenever a __metaclass__ is used, one could also use a decorator to get effectively the same result. This section discusses this topic.
For an example we use the concept of a Bunch, as discussed in Alex Martelli’s excellent book Python in a Nutshell. As he says, a Bunch is similar to the struct type in C.
Bunch using decorators¶
Here we give a construction based on the decorator point of view. First we define a function, which can be used as a decorator, that returns a bunch class.
>>> def bunch_from_dict(a_dict, name='a_bunch'): ... ... __slots__ = sorted(a_dict.keys()) ... defaults = dict(a_dict) ... bases = (BaseBunch,) ... ... def __init__(self, **kwargs): ... for d in defaults, kwargs: ... for key, value in d.items(): ... setattr(self, key, value) ... ... body = dict(__slots__=__slots__, __init__=__init__) ... return type(name, bases, body)
We now need to implement the BaseBunch class, from which the return bunch classes will inherit __repr__ and, if we wish, other attributes.
>>> class BaseBunch(object): ... def __repr__(self): ... body = ', '.join([ ... '%s=%r' % (key, getattr(self, key)) ... for key in self.__slots__ ... ]) ... return '%s(%s)' % (self.__class__.__name__, body)
Here’s an example of the creation of a Point class.
>>> Point = bunch_from_dict(dict(x=0, y=0), 'Point')
And here are examples of its use.
>>> Point(x=1, y=3) Point(x=1, y=3) >>> Point() Point(x=0, y=0)
We can also use bunch_from_dict as a decorator.
>>> from jfine.classtools import dict_from_class >>> @bunch_from_dict ... @dict_from_class ... class RGB(object): ... 'This is a docstring.' ... red = green = blue = 0
We could, of course, introduce a new decorator
bunch_from_class() to make life a little easier for the user.
Here’s an example of the use of the RGB class. It shows that the name of the class is not being properly picked up. This is an interface problem rather than a problem with the decorator approach. The name is available to be used, but the interface is not making it available. Similar remarks apply to the docstring.
>>> RGB(blue=45, green=150) a_bunch(blue=45, green=150, red=0)
Bunch using __metaclass__¶
The code here is based on the __metaclass__ implementation of Bunch, given in Python in a Nutshell. The API is:
class Point(MetaBunch): x = 0.0 y = 0.0
The base class
MetaBunch() is defined by:
class MetaBunch(object): __metaclass__ = metaMetaBunch
The real work is done in
class metaMetaBunch(type): def __new__(cls, name, bases, body): # Creation of new_body similar to bunch_from_dict. # ... but first need to 'clean up' the body. new_body = ... # Computed from body # Creation of new instance similar to bunch_from_dict. # ... but here can't use type(name, bases, new_body) return type.__new__(cls, name, bases, new_body)
where I’ve omitted the crucial code that computes the new_body from the old. (My focus here is on the logic of __metaclass_ and not the construction of the new body.)
How __metaclass__ works¶
In Python the class statement creates the class body from the code you have written, placing it in a dictionary. It also picks up the name and the bases in the first line of the class statement. These three arguments, (name, bases, body) are then passed to a function.
The __metaclass__ attribute is part of determining that function. If __metaclass__ is a key in the body dictionary then the value of that key is used. This value could be anything, although if not callable an exception will be raised.
In the example above, the MetaBunch class body has a key __metaclass__, and so its value metaMetaBunch is used. It is metaMetaBunch that is used to create the value that is stored at MetaBunch.
What is that value? When we instantiate metaMetaBunch we use its __new__ method to create the instance, which is an instance of type. In particular, the code that creates the new_body is run on the body of MetaBunch.
Now what happens when we subclass MetaBunch. One might think that
- because Point inherits from MetaBunch
- and because MetaBunch has a __metaclass__ in its body
- and that __metaclass__ has value metaMetaBunch
it follows that metaMetaBunch is use to construct the Point class.
But this is gotcha. Even though the conclusion is correct the reasoning is not. What happens is that
- Python looks for __metaclass__ in the body of Point
- but it’s not there so it looks at the bases of Point
- and in the bases it finds MetaBunch
- whose type is metaMetaBunch
and so it uses that instead of type when constructing Point.
Here are the main differences between the two approaches.
The decorator approach
- Syntax differs from ordinary class statement.
- Awkward if class decorators are not available.
- As is, the name is not picked up.
- Easier to construct Bunch classes dynamically.
- The Point class is an instance of type.
The __metaclass__ approach
- Syntax the same as ordinary class statement.
- ‘Magic’ takes place behind the scenes.
- Requires more knowledge to implement.
- Awkward to construct Bunch classes dynamically.
- The Point class is an instance of MetaBunch.
My view is that using decorators is simpler than using __metaclass__, particularly if the decorator syntax is available.