python-peps/pep-0318.txt

PEP: 318
Title: Decorators for Functions and Methods
Version: $Revision$
Last-Modified: $Date$
Author: Kevin D. Smith <Kevin.Smith@theMorgue.org>,
        Jim Jewett <jimjjewett@users.sourceforge.net>,
        Skip Montanaro <skip@pobox.com>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 05-Jun-2003
Python-Version: 2.4
Post-History: 09-Jun-2003, 10-Jun-2003, 27-Feb-2004, 23-Mar-2004


Abstract
========

The current method for declaring class and static methods is awkward
and can lead to code that is difficult to understand.  Ideally, these
transformations should be made at the same point in the code where the
declaration itself is made.  This PEP introduces new syntax for
transformations of a declaration.


Motivation
==========

The current method of applying a transformation to a function or
method places the actual translation after the function body.  For
large functions this separates a key component of the function's
behavior from the definition of the rest of the function's external
interface.  For example::

    def foo(self):
        perform method operation
    foo = classmethod(foo)

This becomes less readable with longer methods.  It also seems less
than pythonic to name the function three times for what is
conceptually a single declaration.  A solution to this problem is to
move the transformation of the method closer to the method's own
declaration.  While the new syntax is not yet final, the intent is to
replace::

    def foo(cls):
        pass
    foo = synchronized(lock)(foo)
    foo = classmethod(foo)

with an alternative that places the decoration in the function's
declaration::

    @classmethod
    @synchronized(lock)
    def foo(cls):
        pass

Modifying classes in this fashion is also possible, though the
benefits are not as immediately apparent.  Almost certainly, anything
which could be done with class decorators could be done using
metaclasses, but using metaclasses is sufficiently obscure that there
is some attraction to having an easier way to make simple
modifications to classes. For Python 2.4, only function decorators 
are being added.


Background
==========

There is general agreement that syntactic support is desirable to the
current state of affairs.  Guido mentioned `syntactic support for
decorators`_ in his DevDay keynote presentation at the `10th Python
Conference`_, though `he later said`_ it was only one of several
extensions he proposed there "semi-jokingly".  `Michael Hudson raised
the topic`_ on ``python-dev`` shortly after the conference,
attributing the bracketed syntax to an earlier proposal on
``comp.lang.python`` by `Gareth McCaughan`_.

.. _syntactic support for decorators:
   http://www.python.org/doc/essays/ppt/python10/py10keynote.pdf
.. _10th python conference:
   http://www.python.org/workshops/2002-02/
.. _michael hudson raised the topic:
   http://mail.python.org/pipermail/python-dev/2002-February/020005.html
.. _he later said:
   http://mail.python.org/pipermail/python-dev/2002-February/020017.html
.. _gareth mccaughan:
   http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&oe=UTF-8&selm=slrna40k88.2h9o.Gareth.McCaughan%40g.local

Class decorations seem like an obvious next step because class
definition and function definition are syntactically similar.

The discussion continued on and off on python-dev from February 2002
through July 2004. Many hundreds of posts were made, with people
proposing many possible syntax variations.  Guido took a list of
proposals to `EuroPython 2004`_, where a discussion took place.
Subsequent to this, he decided that for 2.4a2 we'd have the Java-style
@decorator syntax.  Barry Warsaw named this the 'pie-decorator'
syntax, in honor of the Pie-thon Parrot shootout which was announced
about the same time as the decorator syntax, and because the @ looks a
little like a pie.  Guido `outlined his case`_ on Python-dev,
including `this piece`_ on the various rejected forms.

.. _EuroPython 2004:
    http://www.python.org/doc/essays/ppt/euro2004/euro2004.pdf

.. _outlined his case:
    http://mail.python.org/pipermail/python-dev/2004-August/author.html

.. _this piece:
    http://mail.python.org/pipermail/python-dev/2004-August/046672.html


Design Goals
============

The new syntax should

*  work for arbitrary wrappers, including user-defined callables and
   the existing builtins ``classmethod()`` and ``staticmethod()``

*  work with multiple wrappers per definition

*  make it obvious what is happening; at the very least it should be
   obvious that new users can safely ignore it when writing their own
   code

*  not make future extensions more difficult

*  be easy to type;  programs that use it are expected to use it very
   frequently

*  not make it more difficult to scan through code quickly.  It should
   still be easy to search for all definitions, a particular
   definition, or the arguments that a function accepts

*  not needlessly complicate secondary support tools such as
   language-sensitive editors and other "`toy parser tools out
   there`_"

.. _toy parser tools out there:
   http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&oe=UTF-8&selm=mailman.1010809396.32158.python-list%40python.org

Andrew Kuchling has links to a bunch of the discussions about motivations
`in his blog`_.

.. _in his blog:
    http://www.amk.ca/diary/archives/cat_python.html#003255

Proposed Syntax
===============

The current syntax for function decorators as implemented in Python
2.4a2 is::

    @dec2
    @dec1
    def func(arg1, arg2, ...):
        pass

This is equivalent to::

    def func(arg1, arg2, ...):
        pass
    func = dec2(dec1(func))

without the intermediate assignment to the variable ``func``.  The
decorators are near the function declaration.  The @ sign makes it
clear that something new is going on here.

The decorator statement is limited in what it can accept - arbitrary
expressions will not work. Guido preferred this because of a `gut feeling`_

.. _gut feeling:
    http://mail.python.org/pipermail/python-dev/2004-August/046711.html


Alternate Proposals
===================

Several other syntaxes have been proposed::

    def func(arg1, arg2, ...) as dec1, dec2, ...:
        pass

The absence of brackets makes it cumbersome to break long lists of
decorators across multiple lines, and the keyword "as" doesn't have
the same meaning as its use in the ``import`` statement.  Plenty of
`alternatives to "as"`_ have been proposed. :-)

.. _alternatives to "as":
   http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&oe=UTF-8&threadm=mailman.236.1079968472.742.python-list%40python.org&rnum=2&prev=/groups%3Fq%3Dpython%2Bpep%2B318%26hl%3Den%26lr%3D%26ie%3DUTF-8%26oe%3DUTF-8%26selm%3Dmailman.236.1079968472.742.python-list%2540python.org%26rnum%3D2

::

    def [dec1, dec2, ...] func(arg1, arg2, ...):
        pass

This form has the disadvantage that the decorators visually assume
higher priority than the function name and argument list.

::

    def func [dec1, dec2, ...] (arg1, arg2, ...):
        pass

Quixote's `Python Template Language`_ uses this form, but only supports a
single decorator chosen from a restricted set.  For short lists it
works okay, but for long list it separates the argument list from the
function name.

.. _Python Template Language:
   http://www.mems-exchange.org/software/quixote/doc/PTL.html

::

    using:
        dec1
        dec2
        ...
    def foo(arg1, arg2, ...):
        pass

The function definition is not nested within the using: block making
it impossible to tell which objects following the block will be
decorated.  Nesting the function definition within the using: block
suggests nesting of namespaces that doesn't exist.  The name ``foo``
would actually exist at the same scope as the using: block.  Finally,
it would require the introduction of a new keyword.

The obvious alternative that nests the function within the block

::

    using:
        dec1
        dec2
        ...
        def foo(arg1, arg2, ...):
            pass

has its own set of drawbacks.  Having the minimal indent level be
three deep for methods is painful for those using limited-width
windows.  The inconsistent indentation between methods of the same
class with and without decorators would be a readability problem.
Finally, adding or removing decorators would require reindenting the
entire function/method body.

Guido proposed and implemented a patch to support interpretation of
a `list of decorators`_ as a prefix to function definitions ::

    [dec1, dec2, ...]
    def foo(arg1, arg2, ...):
        pass

For a while this was Guido's preferred solution, but negative sentiment ran
high, mostly because that syntax, though useless except for side
effects of the list, is already legal and thus creates a special case.

.. _list of decorators:
   http://python.org/sf/926860

Another variant on the list syntax that was initially favored was::

    def func(arg1, arg2, ...) [dec1, dec2]:
        pass

Guido decided `he preferred`_ having the decorators on the line before
the 'def', because it was felt that a long argument list would mean
that the decorators would be 'hidden'

.. _he preferred:
    http://mail.python.org/pipermail/python-dev/2004-March/043756.html

Phillip Eby and Jp Calderone both proposed variants that required
no new syntax, but instead used some fairly advanced introspection
to provide decorator-like behavoiur, but Guido was unimpressed by
these, stating::

    Using functions with "action-at-a-distance" through
    sys.settraceback may be okay for an obscure feature that can't be
    had any other way yet doesn't merit changes to the language, but
    that's not the situation for decorators.  The widely held view
    here is that decorators need to be added as a syntactic feature to
    avoid the problems with the postfix notation used in 2.2 and 2.3.
    Decorators are slated to be an important new language feature and
    their design needs to be forward-looking, not constrained by what
    can be implemented in 2.3.

A `page on the Python Wiki`_ was created to summarize a number of the
proposals.  Once it stabilizes perhaps someone would care to
incorporate its content into this PEP (hint, hint).

.. _page on the Python Wiki:
    http://www.python.org/moin/PythonDecorators


Why @? 
------

There is some history in Java using @ initially as a marker in
`Javadoc comments`_ and later in ... mumble mumble ...  The fact that
@ was previously unused as a token in Python also means it's clear
there is no possibility of such code being parsed by an earlier
version of Python, leading to possibly subtle semantic bugs.  That
said, @ is still a fairly arbitrary choice.  Some have suggested using
| instead.

For syntax options which use a list-like syntax (no matter where it
appears) to specify the decorators a few alternatives were proposed:
``[|...|]``, ``*[...]*``, and ``<...>``.  None gained much traction.
The alternatives which involve square brackets only serve to make it
obvious that the decorator construct is not a list.  They do nothing
to make parsing any easier.  The '<...>' alternative presents parsing
problems because '<' and '>' already parse as un-paired.  They present
a further parsing ambiguity because a right angle bracket might be a
greater than symbol instead of a closer for the decorators.

.. _Javadoc comments:
    http://java.sun.com/j2se/javadoc/writingdoccomments/

Current Implementation
======================

Guido asked for a voluteer to implement his preferred syntax, and Mark
Russell stepped up and posted a `patch`_ to SF. The syntax accepted
for 2.4a2 is::


    @dec2
    @dec1
    def func(arg1, arg2, ...):
        pass

is equivalent to::

    def func(arg1, arg2, ...):
        pass
    func = dec2(dec1(func))

though without the intermediate creation of a variable named ``func``.

.. _patch: http://www.python.org/sf/979728

A `previous patch`_ from Michael Hudson which implements the
list-after-def syntax is also still kicking around.

.. _previous patch: http://starship.python.net/crew/mwh/hacks/meth-syntax-sugar-3.diff


Examples
========

Much of the discussion on ``comp.lang.python`` and the ``python-dev``
mailing list focuses on the use of decorators as a cleaner way to use
the ``staticmethod()`` and ``classmethod()`` builtins.  This
capability is much more powerful than that.  This section presents
some examples of use.

1. Define a function to be executed at exit.  Note that the function
   isn't actually "wrapped" in the usual sense.

   ::

       def onexit(f):
           import atexit
           atexit.register(f)
           return f

       @onexit
       def func():
           ...

2. Define a class with a singleton instance.  Note that once the class
   disappears enterprising programmers would have to be more creative
   to create more instances.  (From Shane Hathaway on ``python-dev``.)

   ::

       def singleton(cls):
           instances = {}
           def getinstance():
               if cls not in instances:
                   instances[cls] = cls()
               return instances[cls]
           return getinstance

       @singleton
       class MyClass:
           ...

3. Add attributes to a function.  (Based on an example posted by
   Anders Munch on ``python-dev``.)

   ::

       def attrs(**kwds):
           def decorate(f):
               for k in kwds:
                   setattr(f, k, kwds[k])
               return f
           return decorate

       @attrs(versionadded="2.2",
              author="Guido van Rossum")
       def mymethod(f):
           ...

4. Enforce function argument and return types.  (Note that this is not
   exactly correct, as the returned new_f doesn't have "func" as its
   func_name attribute.)

   ::

       def accepts(*types):
           def check_accepts(f):
               assert len(types) == f.func_code.co_argcount
               def new_f(*args, **kwds):
                   for (a, t) in zip(args, types):
                       assert isinstance(a, t), \
                              "arg %r does not match %s" % (a,t)
                   return f(*args, **kwds)
               return new_f
           return check_accepts

       def returns(rtype):
           def check_returns(f):
               def new_f(*args, **kwds):
                   result = f(*args, **kwds)
                   assert isinstance(result, rtype), \
                          "return value %r does not match %s" % (result,rtype)
                   return result
               return new_f
           return check_returns

       @accepts(int, (int,float))
       @returns((int,float))
       def func(arg1, arg2):
           return arg1 * arg2

5. Declare that a class implements a particular (set of) interface(s).
   This is from a posting by Bob Ippolito on ``python-dev`` based on
   experience with `PyProtocols`_.

   .. _PyProtocols: http://peak.telecommunity.com/PyProtocols.html

   ::

       def provides(*interfaces):
            """
            An actual, working, implementation of provides for
            the current implementation of PyProtocols.  Not
            particularly important for the PEP text.
            """
            def provides(typ):
                declareImplementation(typ, instancesProvide=interfaces)
                return typ
            return provides

       class IBar(Interface):
            """Declare something about IBar here"""

       @provides(IBar)
       class Foo(object):
               """Implement something here..."""

Of course, all these examples are possible today, though without
syntactic support.


Open Issues
===========

1. It's not yet certain that class decorators will be incorporated
   into the language at this point.  Guido expressed skepticism about
   the concept, but various people have made some `strong arguments`_
   (search for ``PEP 318 - posting draft``) on their behalf in
   ``python-dev``.

   .. _strong arguments:
      http://mail.python.org/pipermail/python-dev/2004-March/thread.html


Copyright
=========

This document has been placed in the public domain.


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