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+In previous Python releases (and still in 1.5), there is something +called the ``Don Beaudry hook'', after its inventor and champion. +This allows C extensions to provide alternate class behavior, thereby +allowing the Python class syntax to be used to define other class-like +entities. Don Beaudry has used this in his infamous MESS package; Jim +Fulton has used it in his Extension +Classes package. (It has also been referred to as the ``Don +Beaudry hack,'' but that's a misnomer. There's nothing hackish +about it -- in fact, it is rather elegant and deep, even though +there's something dark to it.) + +
(On first reading, you may want to skip directly to the examples in +the section "Writing Metaclasses in Python" below, unless you want +your head to explode.) + +
+ +
Documentation of the Don Beaudry hook has purposefully been kept +minimal, since it is a feature of incredible power, and is easily +abused. Basically, it checks whether the type of the base +class is callable, and if so, it is called to create the new +class. + +
Note the two indirection levels. Take a simple example: + +
+class B: + pass + +class C(B): + pass ++ +Take a look at the second class definition, and try to fathom ``the +type of the base class is callable.'' + +
(Types are not classes, by the way. See questions 4.2, 4.19 and in +particular 6.22 in the Python FAQ +for more on this topic.) + +
+ +
+ +
types
has
+been imported.+ +
+ +
So our conclusion is that in our example, the type of the base +class (of C) is not callable. So the Don Beaudry hook does not apply, +and the default class creation mechanism is used (which is also used +when there is no base class). In fact, the Don Beaudry hook never +applies when using only core Python, since the type of a core object +is never callable. + +
So what do Don and Jim do in order to use Don's hook? Write an +extension that defines at least two new Python object types. The +first would be the type for ``class-like'' objects usable as a base +class, to trigger Don's hook. This type must be made callable. +That's why we need a second type. Whether an object is callable +depends on its type. So whether a type object is callable depends on +its type, which is a meta-type. (In core Python there +is only one meta-type, the type ``type'' (types.TypeType), which is +the type of all type objects, even itself.) A new meta-type must +be defined that makes the type of the class-like objects callable. +(Normally, a third type would also be needed, the new ``instance'' +type, but this is not an absolute requirement -- the new class type +could return an object of some existing type when invoked to create an +instance.) + +
Still confused? Here's a simple device due to Don himself to +explain metaclasses. Take a simple class definition; assume B is a +special class that triggers Don's hook: + +
+class C(B): + a = 1 + b = 2 ++ +This can be though of as equivalent to: + +
+C = type(B)('C', (B,), {'a': 1, 'b': 2}) ++ +If that's too dense for you, here's the same thing written out using +temporary variables: + +
+creator = type(B) # The type of the base class +name = 'C' # The name of the new class +bases = (B,) # A tuple containing the base class(es) +namespace = {'a': 1, 'b': 2} # The namespace of the class statement +C = creator(name, bases, namespace) ++ +This is analogous to what happens without the Don Beaudry hook, except +that in that case the creator function is set to the default class +creator. + +
In either case, the creator is called with three arguments. The +first one, name, is the name of the new class (as given at the +top of the class statement). The bases argument is a tuple of +base classes (a singleton tuple if there's only one base class, like +the example). Finally, namespace is a dictionary containing +the local variables collected during execution of the class statement. + +
Note that the contents of the namespace dictionary is simply +whatever names were defined in the class statement. A little-known +fact is that when Python executes a class statement, it enters a new +local namespace, and all assignments and function definitions take +place in this namespace. Thus, after executing the following class +statement: + +
+class C: + a = 1 + def f(s): pass ++ +the class namespace's contents would be {'a': 1, 'f': <function f +...>}. + +
But enough already about writing Python metaclasses in C; read the +documentation of MESS or Extension +Classes for more information. + +
+ +
In Python 1.5, the requirement to write a C extension in order to +write metaclasses has been dropped (though you can still do +it, of course). In addition to the check ``is the type of the base +class callable,'' there's a check ``does the base class have a +__class__ attribute.'' If so, it is assumed that the __class__ +attribute refers to a class. + +
Let's repeat our simple example from above: + +
+class C(B): + a = 1 + b = 2 ++ +Assuming B has a __class__ attribute, this translates into: + +
+C = B.__class__('C', (B,), {'a': 1, 'b': 2}) ++ +This is exactly the same as before except that instead of type(B), +B.__class__ is invoked. If you have read FAQ question 6.22 you will understand that while there is a big +technical difference between type(B) and B.__class__, they play the +same role at different abstraction levels. And perhaps at some point +in the future they will really be the same thing (at which point you +would be able to derive subclasses from built-in types). + +
At this point it may be worth mentioning that C.__class__ is the +same object as B.__class__, i.e., C's metaclass is the same as B's +metaclass. In other words, subclassing an existing class creates a +new (meta)inststance of the base class's metaclass. + +
Going back to the example, the class B.__class__ is instantiated, +passing its constructor the same three arguments that are passed to +the default class constructor or to an extension's metaclass: +name, bases, and namespace. + +
It is easy to be confused by what exactly happens when using a +metaclass, because we lose the absolute distinction between classes +and instances: a class is an instance of a metaclass (a +``metainstance''), but technically (i.e. in the eyes of the python +runtime system), the metaclass is just a class, and the metainstance +is just an instance. At the end of the class statement, the metaclass +whose metainstance is used as a base class is instantiated, yielding a +second metainstance (of the same metaclass). This metainstance is +then used as a (normal, non-meta) class; instantiation of the class +means calling the metainstance, and this will return a real instance. +And what class is that an instance of? Conceptually, it is of course +an instance of our metainstance; but in most cases the Python runtime +system will see it as an instance of a a helper class used by the +metaclass to implement its (non-meta) instances... + +
Hopefully an example will make things clearer. Let's presume we +have a metaclass MetaClass1. It's helper class (for non-meta +instances) is callled HelperClass1. We now (manually) instantiate +MetaClass1 once to get an empty special base class: + +
+BaseClass1 = MetaClass1("BaseClass1", (), {}) ++ +We can now use BaseClass1 as a base class in a class statement: + +
+class MySpecialClass(BaseClass1): + i = 1 + def f(s): pass ++ +At this point, MySpecialClass is defined; it is a metainstance of +MetaClass1 just like BaseClass1, and in fact the expression +``BaseClass1.__class__ == MySpecialClass.__class__ == MetaClass1'' +yields true. + +
We are now ready to create instances of MySpecialClass. Let's +assume that no constructor arguments are required: + +
+x = MySpecialClass() +y = MySpecialClass() +print x.__class__, y.__class__ ++ +The print statement shows that x and y are instances of HelperClass1. +How did this happen? MySpecialClass is an instance of MetaClass1 +(``meta'' is irrelevant here); when an instance is called, its +__call__ method is invoked, and presumably the __call__ method defined +by MetaClass1 returns an instance of HelperClass1. + +
Now let's see how we could use metaclasses -- what can we do +with metaclasses that we can't easily do without them? Here's one +idea: a metaclass could automatically insert trace calls for all +method calls. Let's first develop a simplified example, without +support for inheritance or other ``advanced'' Python features (we'll +add those later). + +
+import types + +class Tracing: + def __init__(self, name, bases, namespace): + """Create a new class.""" + self.__name__ = name + self.__bases__ = bases + self.__namespace__ = namespace + def __call__(self): + """Create a new instance.""" + return Instance(self) + +class Instance: + def __init__(self, klass): + self.__klass__ = klass + def __getattr__(self, name): + try: + value = self.__klass__.__namespace__[name] + except KeyError: + raise AttributeError, name + if type(value) is not types.FunctionType: + return value + return BoundMethod(value, self) + +class BoundMethod: + def __init__(self, function, instance): + self.function = function + self.instance = instance + def __call__(self, *args): + print "calling", self.function, "for", self.instance, "with", args + return apply(self.function, (self.instance,) + args) + +Trace = Tracing('Trace', (), {}) + +class MyTracedClass(Trace): + def method1(self, a): + self.a = a + def method2(self): + return self.a + +aninstance = MyTracedClass() + +aninstance.method1(10) + +print "the answer is %d" % aninstance.method2() ++ +Confused already? The intention is to read this from top down. The +Tracing class is the metaclass we're defining. Its structure is +really simple. + +
+ +
+ +
+ +
The class Instance is the class used for all instances of classes +built using the Tracing metaclass, e.g. aninstance. It has two +methods: + +
+ +
+ +
+ +
The __getattr__ method looks the name up in the __namespace__ +dictionary. If it isn't found, it raises an AttributeError exception. +(In a more realistic example, it would first have to look through the +base classes as well.) If it is found, there are two possibilities: +it's either a function or it isn't. If it's not a function, it is +assumed to be a class variable, and its value is returned. If it's a +function, we have to ``wrap'' it in instance of yet another helper +class, BoundMethod. + +
The BoundMethod class is needed to implement a familiar feature: +when a method is defined, it has an initial argument, self, which is +automatically bound to the relevant instance when it is called. For +example, aninstance.method1(10) is equivalent to method1(aninstance, +10). In the example if this call, first a temporary BoundMethod +instance is created with the following constructor call: temp = +BoundMethod(method1, aninstance); then this instance is called as +temp(10). After the call, the temporary instance is discarded. + +
+ +
+ +
+ +
In order to be able to support arbitrary argument lists, the +__call__ method first constructs a new argument tuple. Conveniently, +because of the notation *args in __call__'s own argument list, the +arguments to __call__ (except for self) are placed in the tuple args. +To construct the desired argument list, we concatenate a singleton +tuple containing the instance with the args tuple: (self.instance,) + +args. (Note the trailing comma used to construct the singleton +tuple.) In our example, the resulting argument tuple is (aninstance, +10). + +
The intrinsic function apply() takes a function and an argument +tuple and calls the function for it. In our example, we are calling +apply(method1, (aninstance, 10)) which is equivalent to calling +method(aninstance, 10). + +
From here on, things should come together quite easily. The output +of the example code is something like this: + +
+calling <function method1 at ae8d8> for <Instance instance at 95ab0> with (10,) +calling <function method2 at ae900> for <Instance instance at 95ab0> with () +the answer is 10 ++ +
That was about the shortest meaningful example that I could come up +with. A real tracing metaclass (for example, Trace.py discussed below) needs to be more +complicated in two dimensions. + +
First, it needs to support more advanced Python features such as +class variables, inheritance, __init__ methods, and keyword arguments. + +
Second, it needs to provide a more flexible way to handle the +actual tracing information; perhaps it should be possible to write +your own tracing function that gets called, perhaps it should be +possible to enable and disable tracing on a per-class or per-instance +basis, and perhaps a filter so that only interesting calls are traced; +it should also be able to trace the return value of the call (or the +exception it raised if an error occurs). Even the Trace.py example +doesn't support all these features yet. + +
+ +
Have a look at some very preliminary examples that I coded up to +teach myself how to write metaclasses: + +
+class Color(Enum): + red = 1 + green = 2 + blue = 3 +print Color.red ++ +will print the string ``Color.red'', while ``Color.red==1'' is true, +and ``Color.red + 1'' raise a TypeError exception. + +
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A pattern seems to be emerging: almost all these uses of +metaclasses (except for Enum, which is probably more cute than useful) +mostly work by placing wrappers around method calls. An obvious +problem with that is that it's not easy to combine the features of +different metaclasses, while this would actually be quite useful: for +example, I wouldn't mind getting a trace from the test run of the +Synch module, and it would be interesting to add preconditions to it +as well. This needs more research. Perhaps a metaclass could be +provided that allows stackable wrappers... + +
+ +
There are lots of things you could do with metaclasses. Most of +these can also be done with creative use of __getattr__, but +metaclasses make it easier to modify the attribute lookup behavior of +classes. Here's a partial list. + +
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Many thanks to David Ascher and Donald Beaudry for their comments +on earlier draft of this paper. Also thanks to Matt Conway and Tommy +Burnette for putting a seed for the idea of metaclasses in my +mind, nearly three years ago, even though at the time my response was +``you can do that with __getattr__ hooks...'' :-) + +
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