|Title:||Metaclasses in Python 3000|
|Author:||Talin <viridia at gmail.com>|
This PEP proposes changing the syntax for declaring metaclasses, and alters the semantics for how classes with metaclasses are constructed.
There are two rationales for this PEP, both of which are somewhat subtle. The primary reason for changing the way metaclasses work, is that there are a number of interesting use cases that require the metaclass to get involved earlier in the class construction process than is currently possible. Currently, the metaclass mechanism is essentially a post-processing step. With the advent of class decorators, much of these post-processing chores can be taken over by the decorator mechanism. In particular, there is an important body of use cases where it would be useful to preserve the order in which a class members are declared. Ordinary Python objects store their members in a dictionary, in which ordering is unimportant, and members are accessed strictly by name. However, Python is often used to interface with external systems in which the members are organized according to an implicit ordering. Examples include declaration of C structs; COM objects; Automatic translation of Python classes into IDL or database schemas, such as used in an ORM; and so on. In such cases, it would be useful for a Python programmer to specify such ordering directly using the declaration order of class members. Currently, such orderings must be specified explicitly, using some other mechanism (see the ctypes module for an example.) Unfortunately, the current method for declaring a metaclass does not allow for this, since the ordering information has already been lost by the time the metaclass comes into play. By allowing the metaclass to get involved in the class construction process earlier, the new system allows the ordering or other early artifacts of construction to be preserved and examined. There proposed metaclass mechanism also supports a number of other interesting use cases beyond preserving the ordering of declarations. One use case is to insert symbols into the namespace of the class body which are only valid during class construction. An example of this might be "field constructors", small functions that are used in the creation of class members. Another interesting possibility is supporting forward references, i.e. references to Python symbols that are declared further down in the class body. The other, weaker, rationale is purely cosmetic: The current method for specifying a metaclass is by assignment to the special variable __metaclass__, which is considered by some to be aesthetically less than ideal. Others disagree strongly with that opinion. This PEP will not address this issue, other than to note it, since aesthetic debates cannot be resolved via logical proofs.
In the new model, the syntax for specifying a metaclass is via a keyword argument in the list of base classes: class Foo(base1, base2, metaclass=mymeta): ... Additional keywords will also be allowed here, and will be passed to the metaclass, as in the following example: class Foo(base1, base2, metaclass=mymeta, private=True): ... Note that this PEP makes no attempt to define what these other keywords might be - that is up to metaclass implementors to determine. More generally, the parameter list passed to a class definition will now support all of the features of a function call, meaning that you can now use *args and **kwargs-style arguments in the class base list: class Foo(*bases, **kwds): ...
Invoking the Metaclass
In the current metaclass system, the metaclass object can be any callable type. This does not change, however in order to fully exploit all of the new features the metaclass will need to have an extra attribute which is used during class pre-construction. This attribute is named __prepare__, which is invoked as a function before the evaluation of the class body. The __prepare__ function takes two positional arguments, and an arbitrary number of keyword arguments. The two positional arguments are: 'name' - the name of the class being created. 'bases' - the list of base classes. The interpreter always tests for the existence of __prepare__ before calling it; If it is not present, then a regular dictionary is used, as illustrated in the following Python snippet. def prepare_class(name, *bases, metaclass=None, **kwargs): if metaclass is None: metaclass = compute_default_metaclass(bases) prepare = getattr(metaclass, '__prepare__', None) if prepare is not None: return prepare(name, bases, **kwargs) else: return dict() The example above illustrates how the arguments to 'class' are interpreted. The class name is the first argument, followed by an arbitrary length list of base classes. After the base classes, there may be one or more keyword arguments, one of which can be 'metaclass'. Note that the 'metaclass' argument is not included in kwargs, since it is filtered out by the normal parameter assignment algorithm. (Note also that 'metaclass' is a keyword- only argument as per PEP 3102 .) Even though __prepare__ is not required, the default metaclass ('type') implements it, for the convenience of subclasses calling it via super(). __prepare__ returns a dictionary-like object which is used to store the class member definitions during evaluation of the class body. In other words, the class body is evaluated as a function block (just like it is now), except that the local variables dictionary is replaced by the dictionary returned from __prepare__. This dictionary object can be a regular dictionary or a custom mapping type. This dictionary-like object is not required to support the full dictionary interface. A dictionary which supports a limited set of dictionary operations will restrict what kinds of actions can occur during evaluation of the class body. A minimal implementation might only support adding and retrieving values from the dictionary - most class bodies will do no more than that during evaluation. For some classes, it may be desirable to support deletion as well. Many metaclasses will need to make a copy of this dictionary afterwards, so iteration or other means for reading out the dictionary contents may also be useful. The __prepare__ method will most often be implemented as a class method rather than an instance method because it is called before the metaclass instance (i.e. the class itself) is created. Once the class body has finished evaluating, the metaclass will be called (as a callable) with the class dictionary, which is no different from the current metaclass mechanism. Typically, a metaclass will create a custom dictionary - either a subclass of dict, or a wrapper around it - that will contain additional properties that are set either before or during the evaluation of the class body. Then in the second phase, the metaclass can use these additional properties to further customize the class. An example would be a metaclass that uses information about the ordering of member declarations to create a C struct. The metaclass would provide a custom dictionary that simply keeps a record of the order of insertions. This does not need to be a full 'ordered dict' implementation, but rather just a Python list of (key,value) pairs that is appended to for each insertion. Note that in such a case, the metaclass would be required to deal with the possibility of duplicate keys, but in most cases that is trivial. The metaclass can use the first declaration, the last, combine them in some fashion, or simply throw an exception. It's up to the metaclass to decide how it wants to handle that case.
Here's a simple example of a metaclass which creates a list of the names of all class members, in the order that they were declared: # The custom dictionary class member_table(dict): def __init__(self): self.member_names =  def __setitem__(self, key, value): # if the key is not already defined, add to the # list of keys. if key not in self: self.member_names.append(key) # Call superclass dict.__setitem__(self, key, value) # The metaclass class OrderedClass(type): # The prepare function @classmethod def __prepare__(metacls, name, bases): # No keywords in this case return member_table() # The metaclass invocation def __new__(cls, name, bases, classdict): # Note that we replace the classdict with a regular # dict before passing it to the superclass, so that we # don't continue to record member names after the class # has been created. result = type.__new__(cls, name, bases, dict(classdict)) result.member_names = classdict.member_names return result class MyClass(metaclass=OrderedClass): # method1 goes in array element 0 def method1(self): pass # method2 goes in array element 1 def method2(self): pass
Guido van Rossum has created a patch which implements the new functionality: http://python.org/sf/1681101
Josiah Carlson proposed using the name 'type' instead of 'metaclass', on the theory that what is really being specified is the type of the type. While this is technically correct, it is also confusing from the point of view of a programmer creating a new class. From the application programmer's point of view, the 'type' that they are interested in is the class that they are writing; the type of that type is the metaclass. There were some objections in the discussion to the 'two-phase' creation process, where the metaclass is invoked twice, once to create the class dictionary and once to 'finish' the class. Some people felt that these two phases should be completely separate, in that there ought to be separate syntax for specifying the custom dict as for specifying the metaclass. However, in most cases, the two will be intimately tied together, and the metaclass will most likely have an intimate knowledge of the internal details of the class dict. Requiring the programmer to insure that the correct dict type and the correct metaclass type are used together creates an additional and unneeded burden on the programmer. Another good suggestion was to simply use an ordered dict for all classes, and skip the whole 'custom dict' mechanism. This was based on the observation that most use cases for a custom dict were for the purposes of preserving order information. However, this idea has several drawbacks, first because it means that an ordered dict implementation would have to be added to the set of built-in types in Python, and second because it would impose a slight speed (and complexity) penalty on all class declarations. Later, several people came up with ideas for use cases for custom dictionaries other than preserving field orderings, so this idea was dropped.
It would be possible to leave the existing __metaclass__ syntax in place. Alternatively, it would not be too difficult to modify the syntax rules of the Py3K translation tool to convert from the old to the new syntax.
 [Python-3000] Metaclasses in Py3K (original proposal) http://mail.python.org/pipermail/python-3000/2006-December/005030.html  [Python-3000] Metaclasses in Py3K (Guido's suggested syntax) http://mail.python.org/pipermail/python-3000/2006-December/005033.html  [Python-3000] Metaclasses in Py3K (Objections to two-phase init) http://mail.python.org/pipermail/python-3000/2006-December/005108.html  [Python-3000] Metaclasses in Py3K (Always use an ordered dict) http://mail.python.org/pipermail/python-3000/2006-December/005118.html  PEP 359: The 'make' statement - http://www.python.org/dev/peps/pep-0359/  PEP 3102: Keyword-only arguments - http://www.python.org/dev/peps/pep-3102/
This document has been placed in the public domain.