python-peps/pep-0318.txt

PEP: 318
Title: Decorators for Functions and Methods
Version: $Revision$
Last-Modified: $Date$
Author: Kevin D. Smith, Jim Jewett, Skip Montanaro, Anthony Baxter
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, 30-Aug-2004


WarningWarningWarning
=====================

The final decision on the syntax for 2.4a3 is not yet made.  This will
be done before 2.4a3, and this document will be updated to match.
Note also that this document does not attempt to cover the huge number
of potential alternative syntaxes, nor is it an attempt to
exhaustively list all the positives and negatives of each form.


Abstract
========

The current method for transforming functions and methods (for
instance, declaring them as a class or static method) 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 function or method 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/method
decorators are being added.


Why Is This So Hard?
--------------------

Two decorators (``classmethod()`` and ``staticmethod()``) have
been available in Python since version 2.2.  It's been assumed since
approximately that time that some syntactic support for them would
eventually be added to the language.  Given this assumption, one might
wonder why it's been so difficult to arrive at a consensus.
Discussions have raged off-and-on at times in both comp.lang.python
and the python-dev mailing list about how best to implement function
decorators.  There is no one clear reason why this should be so, but a
few problems seem to be most problematic.

* Disagreement about where the "declaration of intent" belongs.
  Almost everyone agrees that decorating/transforming a function at
  the end of its definition is suboptimal.  Beyond that there seems to
  be no clear consensus where to place this information.

* Syntactic constraints.  Python is a syntactically simple language
  with fairly strong constraints on what can and can't be done without
  "messing things up" (both visually and with regards to the language
  parser).  There's no obvious way to structure this information so
  that people new to the concept will think, "Oh yeah, I know what
  you're doing."  The best that seems possible is to keep new users
  from creating a wildly incorrect mental model of what the syntax
  means.

* Overall unfamiliarity with the concept.  For people who have a
  passing acquaintance with algebra (or even basic arithmetic) or have
  used at least one other programming language, much of Python is
  intuitive.  Very few people will have had any experience with the
  decorator concept before encountering it in Python.  There's just no
  strong preexisting meme that captures the concept.

* Syntax discussions in general appear to cause more contention than
  almost anything else. Readers are pointed to the ternary operator 
  discussions that were associated with PEP 308 for another example of
  this.


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 initial 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.  Hundreds and 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
..  _Java-style:
    http://java.sun.com/j2se/1.5.0/docs/guide/language/annotations.html


On the name 'Decorator'
=======================

There's been a number of complaints about the choice of the name
'decorator' for this feature.  The major one is that the name is not
consistent with its use in the `GoF book`_.  The name 'decorator'
probably owes more to its use in the compiler area -- a syntax tree is
walked and annotated.  It's quite possible that a better name may turn
up.

.. _GoF book:
    http://patterndigest.com/patterns/Decorator.html


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

The new syntax should

* work for arbitrary wrappers, including user-defined callables and
  the existing builtins ``classmethod()`` and ``staticmethod()``.  This
  requirement also means that a decorator syntax must support passing
  arguments to the wrapper constructor

* 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

* be a syntax "that ... [is] easy to remember once explained"

* 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`_"

* allow future compilers to optimize for decorators.  With the hope of
  a JIT compiler for Python coming into existence at some point this
  tends to require the syntax for decorators to come before the
  function definition

* move from the end of the function, where it's currently hidden, to
  the front where it is more `in your face`_

Andrew Kuchling has links to a bunch of the discussions about
motivations and use cases `in his blog`_.  Particularly notable is `Jim
Huginin's list of use cases`_.

.. _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
.. _in your face:
    http://mail.python.org/pipermail/python-dev/2004-August/047112.html
.. _in his blog:
    http://www.amk.ca/diary/archives/cat_python.html#003255
.. _Jim Huginin's list of use cases:
    http://mail.python.org/pipermail/python-dev/2004-April/044132.html


Current 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


Syntax Alternatives
===================

There have been `a large number`_ of different syntaxes proposed --
rather than attempting to work through these individual syntaxes, it's
worthwhile to break the syntax discussion down into a number of areas.
Attempting to discuss `each possible syntax`_ individually would be an
act of madness, and produce a completely unwieldy PEP.

.. _a large number:
    http://www.python.org/moin/PythonDecorators
.. _each possible syntax:
    http://ucsu.colorado.edu/~bethard/py/decorators-output.py


Decorator Location
------------------

The first syntax point is the location of the decorators.  For the
following examples, we use the @syntax used in 2.4a2.

Decorators before the def statement are the first alternative,
and the syntax used in 2.4a2::

    @classmethod
    def foo(arg1,arg2):
        pass

    @accepts(int,int)
    @returns(float)
    def bar(low,high):
        pass

There have been a number of objections raised to this location --
the primary one is that it's the first real Python case where a
line of code has a result on a following line.  The syntax that
will be in 2.4a3 will also require one decorator per line (in a2,
multiple decorators can be specified on the same line).

People also complained that the syntax got unworldly quickly when
multiple decorators were used.  The point was made, though, that the
chances of a large number of decorators being used on a single function
were small and thus this was not a large worry.

Some of the advantages of this form are that the decorators live
outside the method body -- they are obviously executed at the time
the function is defined.

Another advantage is that being prefix to the function definition fit the
idea of knowing about a change to the semantics of the code before the
code itself, thus knowing how to interpret the code's semantics
properly without having to go back and change your initial perceptions
if the syntax did not come before the function definition.

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

The second form is the decorators between the def and the function
name, or the function name and the argument list::

    def @classmethod foo(arg1,arg2):
        pass

    def @accepts(int,int),@returns(float) bar(low,high):
        pass

    def foo @classmethod (arg1,arg2):
        pass

    def bar @accepts(int,int),@returns(float) (low,high):
        pass

There are a couple of objections to this form.  The first is that it
breaks easily 'greppability' of the source -- you can no longer search
for 'def foo(' and find the definition of the function.  The second,
more serious, objection is that in the case of multiple decorators,
the syntax would be extremely unwieldy.

The next form, which has had a number of strong proponents, is to
have the decorators between the argument list and the trailing ``:``
in the 'def' line::

    def foo(arg1,arg2) @classmethod:
        pass

    def bar(low,high) @accepts(int,int),@returns(float):
        pass

Guido `summarized the arguments`_ against this form (many of which
also apply to the previous form) as:

- it hides crucial information (e.g. that it is a static method)
  after the signature, where it is easily missed

- it's easy to miss the transition between a long argument list and a
  long decorator list

- it's cumbersome to cut and paste a decorator list for reuse, because
  it starts and ends in the middle of a line

.. _summarized the arguments:
    http://mail.python.org/pipermail/python-dev/2004-August/047112.html

The next form is that the decorator syntax go inside the method
body at the start, in the same place that docstrings currently
live:

    def foo(arg1,arg2):
        @classmethod
        pass

    def bar(low,high):
        @accepts(int,int)
        @returns(float)
        pass

The primary objection to this form is that it requires "peeking
inside" the method body to determine the decorators.  In addition,
even though the code is inside the method body, it is not executed
when the method is run.  Guido felt that docstrings were not a good
counter-example, and that it was quite possible that a 'docstring'
decorator could help move the docstring to outside the function body.

The final form is a new block that encloses the method's code.  For
this example, we'll use a 'decorate' keyword, as it makes no sense
with the @syntax. ::

    decorate:
        classmethod
        def foo(arg1,arg2):
            pass

    decorate:
        accepts(int,int)
        returns(float)
        def bar(low,high):
            pass

This form would result in inconsistent indentation for decorated and
undecorated methods.  In addition, a decorated method's body would
start three indent levels in.


Syntax forms
------------

* ``@decorator``::

    @classmethod
    def foo(arg1,arg2):
        pass

    @accepts(int,int)
    @returns(float)
    def bar(low,high):
        pass

  The major objections against this syntax are that the @ symbol is
  not currently used in Python (and is used in both IPython and Leo),
  and that the @ symbol is not meaningful. Another objection is that 
  this "wastes" a currently unused character (from a limited set) on
  something that is not perceived as a major use.

* ``|decorator``::

    |classmethod
    def foo(arg1,arg2):
        pass

    |accepts(int,int)
    |returns(float)
    def bar(low,high):
        pass

  This is a variant on the @decorator syntax -- it has the advantage
  that it does not break IPython and Leo.  Its major disadvantage
  compared to the @syntax is that the | symbol looks like both a
  capital I and a lowercase l.

* list syntax::

    [classmethod]
    def foo(arg1,arg2):
        pass

    [accepts(int,int), returns(float)] 
    def bar(low,high): 
        pass 

  The major objection to the list syntax is that it's currently
  meaningful (when used in the form before the method).  It's also
  lacking any indication that the expression is a decorator.

* list syntax using other brackets (``<...>``, ``[[...]]``, ...)::

    <classmethod>
    def foo(arg1,arg2):
        pass

    <accepts(int,int), returns(float)>
    def bar(low,high): 
        pass 

  None of these alternatives 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.

* ``decorate()``

  The ``decorate()`` proposal was that no new syntax be implemented --
  instead a magic function that used introspection to manipulate the
  following function.  Both Jp Calderone and Philip Eby produced
  implementations of functions that did this.  Guido was pretty firmly
  against this -- with no new syntax, the magicness of a function like
  this is extremely high:

    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.

* _`new keyword (and block)`

  This idea was the consensus alternate from comp.lang.python.  Robert
  Brewer wrote up a detailed `J2 proposal`_ document outlining the
  arguments in favor of this.  The issues with this form are:

  - It requires a new keyword, and therefore a ``from __future__
    import decorators`` statement.

  - The choice of keyword is contentious.  However ``using`` emerged
    as the consensus choice, and is used in the proposal and
    implementation.

  - The keyword/block form produces something that looks like a normal
    code block, but isn't.  Attempts to use statements in this block
    will cause a syntax error.  It may confuse users who don't expect
    a block to contain bare expressions.  On the other hand, the ``@``
    syntax is bound to cause at least as much confusion.

  See `Community Consensus`_ below.

  .. _J2 proposal:
     http://www.aminus.org/rbre/python/pydec.html

There are plenty of other variants and proposals on `the wiki page`_.

.. _the wiki page:
    http://www.python.org/moin/PythonDecorators


Why @?
------

There is some history in Java using @ initially as a marker in
`Javadoc comments`_ and later in Java 1.5 for `annotations`_, which
are similar to Python decorators.  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.  It also means that ambiguity
of what is a decorator and what isn't is removed. of 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 ``<...>``.  

.. _Javadoc comments:
    http://java.sun.com/j2se/javadoc/writingdoccomments/
.. _annotations:
    http://java.sun.com/j2se/1.5.0/docs/guide/language/annotations.html


Current Implementation, History
===============================

Guido asked for a volunteer 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

This is equivalent to::

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

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

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

.. _patch: http://www.python.org/sf/979728
.. _previous patch: http://starship.python.net/crew/mwh/hacks/meth-syntax-sugar-3.diff

After 2.4a2 was released, in response to community reaction, Guido
stated that he'd re-examine a community proposal, if the community
could come up with a community consensus, a decent proposal, and an
implementation.  After an amazing number of posts, collecting a vast
number of alternatives in the `Python wiki`_, a community consensus
emerged (below).  As at time of writing, we're waiting for Guido's
decision.

.. _Python wiki:
    http://www.python.org/moin/PythonDecorators


Community Consensus
-------------------

The consensus that emerged was for the proposed J2 syntax: the new
keyword ``using`` prefixing a block of decorators before the ``def``
statement.  For example::

    using:
        classmethod
        synchronized(lock)
    def func(cls):
        pass

The main arguments for this syntax fall under the "readability counts"
doctrine.  In brief, they are:

* A suite is better than multiple @lines.  The ``using`` keyword and
  block transforms the single-block ``def`` statement into a
  multiple-block compound construct, akin to try/finally and others.

* A keyword is better than punctuation for a new token.  A keyword
  matches the existing use of tokens.  No new token category is
  necessary.  A keyword distinguishes Python decorators from Java
  annotations and .Net attributes, which are significantly different
  beasts.

Robert Brewer wrote a `detailed proposal`_ for this form, and Michael
Sparks produced `a patch`_.

.. _detailed proposal:
    http://www.aminus.org/rbre/python/pydec.html
.. _a patch: 
    http://www.python.org/sf/1013835


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():
           ...

   Note that this example is probably not suitable for real usage, but
   is for example purposes only.

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 
   copies the func_name attribute from the old to the new function.
   func_name was made writable in Python 2.4a3::

       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)
               new_f.func_name = f.func_name
               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
               new_f.func_name = f.func_name
               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`_. ::

       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..."""

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

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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