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Add PEP 3115: Metaclasses in Py3k, by Talin. 

Updated PEP 0 to list PEP 3114: next -> __next__, by Ping.
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Guido van Rossum 2007-03-14 17:52:19 +00:00
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4
pep-0000.txt
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@ -112,6 +112,8 @@ Index by Category
S 754 IEEE 754 Floating Point Special Values Warnes
S 3101 Advanced String Formatting Talin
S 3108 Standard Library Reorganization Cannon
S 3114 Renaming iterator.next() to iterator.__next__() Yee
S 3115 Metaclasses in Python 3000 Talin
Finished PEPs (done, implemented in Subversion)
@ -462,6 +464,8 @@ Numerical Index
SA 3111 Simple input built-in in Python 3000 Roberge
SA 3112 Bytes literals in Python 3000 Orendorff
SA 3113 Removal of Tuple Parameter Unpacking Cannon
S 3114 Renaming iterator.next() to iterator.__next__() Yee
S 3115 Metaclasses in Python 3000 Talin
Key

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pep-3100.txt
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@ -65,7 +65,7 @@ Core language
* True division becomes default behavior [#pep238]_ [done]
* ``exec`` as a statement is not worth it -- make it a function [done]
* (Maybe) add optional declarations for static typing [#pep3107]_ [10]_
* Add optional declarations for static typing [#pep3107]_ [10]_ [done]
* Support only new-style classes; classic classes will be gone [1]_ [done]
* Replace ``print`` by a function [14]_ [#pep3105]_ [done]
* The ``softspace`` attribute of files goes away. [done]

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pep-3115.txt Normal file
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PEP: 3115
Title: Metaclasses in Python 3000
Version: $Revision$
Last-Modified: $Date$
Author: Talin <talin at acm.org>
Status: Draft
Type: Standards
Content-Type: text/plain
Created: 07-Mar-2007
Python-Version: 3.0
Post-History: 11-March-2007, 14-March-2007
Abstract
This PEP proposes changing the syntax for declaring metaclasses,
and alters the semantics for how classes with metaclasses are
constructed.
Rationale
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.
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.
Specification
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=type, **kwargs):
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 [6].)
__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. It does not need to implement the full dictionary interface;
only the ability to insert items and retrieve them are
required. (Note: double check that this is true).
Note that __prepare__ is generally a class method, not 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.
Example:
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 metaclass
class OrderedClass(type):
# 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 prepare function
@classmethod
def __prepare__(metacls, name, bases): # No keywords in this case
return metacls.member_table()
# The metaclass invocation
def __init__(self, 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(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
Alternate Proposals
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
two 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.
Backwards Compatibility
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.
References
[1] [Python-3000] Metaclasses in Py3K (original proposal)
http://mail.python.org/pipermail/python-3000/2006-December/005030.html
[2] [Python-3000] Metaclasses in Py3K (Guido's suggested syntax)
http://mail.python.org/pipermail/python-3000/2006-December/005033.html
[3] [Python-3000] Metaclasses in Py3K (Objections to two-phase init)
http://mail.python.org/pipermail/python-3000/2006-December/005108.html
[4] [Python-3000] Metaclasses in Py3K (Always use an ordered dict)
http://mail.python.org/pipermail/python-3000/2006-December/005118.html
[5] PEP 359: The 'make' statement -
http://www.python.org/dev/peps/pep-0359/
[6] PEP 3102: Keyword-only arguments -
http://www.python.org/dev/peps/pep-3102/
Copyright
This document has been placed in the public domain.
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