python-peps/pep-0380.txt

PEP: 380
Title: Syntax for Delegating to a Subgenerator
Version: $Revision$
Last-Modified: $Date$
Author: Gregory Ewing <greg.ewing@canterbury.ac.nz>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 13-Feb-2009
Python-Version: 2.7
Post-History:


Abstract
========

A syntax is proposed for a generator to delegate part of its
operations to another generator. This allows a section of code
containing 'yield' to be factored out and placed in another
generator. Additionally, the subgenerator is allowed to return with a
value, and the value is made available to the delegating generator.

The new syntax also opens up some opportunities for optimisation when
one generator re-yields values produced by another.


Motivation
==========

A Python generator is a form of coroutine, but has the limitation that
it can only yield to its immediate caller.  This means that a piece of
code containing a ``yield`` cannot be factored out and put into a
separate function in the same way as other code.  Performing such a
factoring causes the called function to itself become a generator, and
it is necessary to explicitly iterate over this second generator and
re-yield any values that it produces.

If yielding of values is the only concern, this can be performed without
much difficulty using a loop such as

::

   for v in g:
       yield v

However, if the subgenerator is to interact properly with the caller
in the case of calls to ``send()``, ``throw()`` and ``close()``, things
become considerably more difficult.  As will be seen later, the necessary
code is very complicated, and it is tricky to handle all the corner cases
correctly.

A new syntax will be proposed to address this issue. In the simplest
use cases, it will be equivalent to the above for-loop, but it will also
handle the full range of generator behaviour, and allow generator code
to be refactored in a simple and straightforward way.


Proposal
========

The following new expression syntax will be allowed in the body of a
generator:

::

   yield from <expr>

where <expr> is an expression evaluating to an iterable, from which an
iterator is extracted. The iterator is run to exhaustion, during which
time it yields and receives values directly to or from the caller of
the generator containing the ``yield from`` expression (the
"delegating generator").

Furthermore, when the iterator is another generator, the subgenerator is
allowed to execute a ``return`` statement with a value, and that value
becomes the value of the ``yield from`` expression.

In general, the semantics can be described in terms of the iterator
protocol as follows:

   * Any values that the iterator yields are passed directly to the
     caller.

   * Any values sent to the delegating generator using ``send()``
     are passed directly to the iterator. If the sent value is None,
     the iterator's ``next()`` method is called. If the sent value is
     not None, the iterator's ``send()`` method is called. Any exception
     resulting from attempting to call ``next`` or ``send`` is raised
     in the delegating generator.

   * Exceptions passed to the ``throw()`` method of the delegating
     generator are forwarded to the ``throw()`` method of the iterator.
     If the iterator does not have a  ``throw()`` method, its ``close()``
     method is called if it has one, then the thrown-in exception is
     raised in the delegating generator. Any exception resulting from
     attempting to call these methods (apart from one case noted below)
     is raised in the delegating generator.

   * The value of the ``yield from`` expression is the first argument
     to the ``StopIteration`` exception raised by the iterator when it
     terminates.

   * ``return expr`` in a generator causes ``StopIteration(expr)`` to
     be raised.


Fine Details
------------

The implicit GeneratorExit resulting from closing the delegating
generator is treated as though it were passed in using ``throw()``.
An iterator having a ``throw()`` method is expected to recognize
this as a request to finalize itself.

If a call to the iterator's ``throw()`` method raises a StopIteration
exception, and it is *not* the same exception object that was thrown in,
and the original exception was not GeneratorExit, then the value of the
new exception is returned as the value of the ``yield from`` expression
and the delegating generator is resumed.


Enhancements to StopIteration
-----------------------------

For convenience, the ``StopIteration`` exception will be given a
``value`` attribute that holds its first argument, or None if there
are no arguments.


Formal Semantics
----------------

1. The statement

::

   RESULT = yield from EXPR

is semantically equivalent to

::

   _i = iter(EXPR)
   try:
       _y = _i.next()
   except StopIteration, _e:
       _r = _e.value
   else:
       while 1:
           try:
               _s = yield _y
           except:
               _m = getattr(_i, 'throw', None)
               if _m is not None:
                   _x = sys.exc_info()
                   try:
                       _y = _m(*_x)
                   except StopIteration, _e:
                       if _e is _x[1] or isinstance(_x[1], GeneratorExit):
                           raise
                       else:
                           _r = _e.value
                           break
               else:
                   _m = getattr(_i, 'close', None)
                   if _m is not None:
                       _m()
                   raise
           else:
               try:
                   if _s is None:
                       _y = _i.next()
                   else:
                       _y = _i.send(_s)
               except StopIteration, _e:
                   _r = _e.value
                   break
   RESULT = _r

except that implementations are free to cache bound methods for the 'next',
'send' and 'throw' methods of the iterator upon first use.

2. In a generator, the statement

::

   return value

is semantically equivalent to

::

   raise StopIteration(value)

except that, as currently, the exception cannot be caught by ``except``
clauses within the returning generator.

3. The StopIteration exception behaves as though defined thusly:

::

  class StopIteration(Exception):

      def __init__(self, *args):
          if len(args) > 0:
              self.value = args[0]
          else:
              self.value = None
          Exception.__init__(self, *args)


Rationale
=========

The Refactoring Principle
-------------------------

The rationale behind most of the semantics presented above stems from
the desire to be able to refactor generator code. It should be possible
to take an section of code containing one or more ``yield`` expressions,
move it into a separate function (using the usual techniques to deal
with references to variables in the surrounding scope, etc.), and
call the new function using a ``yield from`` expression.

The behaviour of the resulting compound generator should be, as far as
possible, exactly the same as the original unfactored generator in all
situations, including calls to ``next()``, ``send()``, ``throw()`` and
``close()``.

The semantics in cases of subiterators other than generators has been
chosen as a reasonable generalization of the generator case.


Finalization
------------

There was some debate as to whether explicitly finalizing the delegating
generator by calling its ``close()`` method while it is suspended at a
``yield from`` should also finalize the subiterator. An argument against
doing so is that it would result in premature finalization of the
subiterator if references to it exist elsewhere.

Consideration of non-refcounting Python implementations led to the
decision that this explicit finalization should be performed, so that
explicitly closing a factored generator has the same effect as doing
so to an unfactored one in all Python implementations.

The assumption made is that, in the majority of use cases, the subiterator
will not be shared. The rare case of a shared subiterator can be
accommodated by means of a wrapper that blocks ``throw()`` and ``close()``
calls, or by using a means other than ``yield from`` to call the
subiterator.


Generators as Threads
---------------------

A motivation for generators being able to return values concerns the
use of generators to implement lightweight threads.  When using
generators in that way, it is reasonable to want to spread the
computation performed by the lightweight thread over many functions.
One would like to be able to call a subgenerator as though it were an
ordinary function, passing it parameters and receiving a returned
value.

Using the proposed syntax, a statement such as

::

   y = f(x)

where f is an ordinary function, can be transformed into a delegation
call

::

   y = yield from g(x)

where g is a generator. One can reason about the behaviour of the
resulting code by thinking of g as an ordinary function that can be
suspended using a ``yield`` statement.

When using generators as threads in this way, typically one is not
interested in the values being passed in or out of the yields.
However, there are use cases for this as well, where the thread is
seen as a producer or consumer of items. The ``yield from``
expression allows the logic of the thread to be spread over as
many functions as desired, with the production or consumption of
items occuring in any subfunction, and the items are automatically
routed to or from their ultimate source or destination.

Concerning ``throw()`` and ``close()``, it is reasonable to expect
that if an exception is thrown into the thread from outside, it should
first be raised in the innermost generator where the thread is suspended,
and propagate outwards from there; and that if the thread is terminated
from outside by calling ``close()``, the chain of active generators
should be finalised from the innermost outwards.


Syntax
------

The particular syntax proposed has been chosen as suggestive of its
meaning, while not introducing any new keywords and clearly standing
out as being different from a plain ``yield``.


Optimisations
-------------

Using a specialised syntax opens up possibilities for optimisation
when there is a long chain of generators.  Such chains can arise, for
instance, when recursively traversing a tree structure.  The overhead
of passing ``next()`` calls and yielded values down and up the chain
can cause what ought to be an O(n) operation to become, in the worst
case, O(n\*\*2).

A possible strategy is to add a slot to generator objects to hold a
generator being delegated to.  When a ``next()`` or ``send()`` call is
made on the generator, this slot is checked first, and if it is
nonempty, the generator that it references is resumed instead.  If it
raises StopIteration, the slot is cleared and the main generator is
resumed.

This would reduce the delegation overhead to a chain of C function
calls involving no Python code execution.  A possible enhancement would
be to traverse the whole chain of generators in a loop and directly
resume the one at the end, although the handling of StopIteration is
more complicated then.


Use of StopIteration to return values
-------------------------------------

There are a variety of ways that the return value from the generator
could be passed back. Some alternatives include storing it as an
attribute of the generator-iterator object, or returning it as the
value of the ``close()`` call to the subgenerator. However, the proposed
mechanism is attractive for a couple of reasons:

* Using the StopIteration exception makes it easy for other kinds
  of iterators to participate in the protocol without having to
  grow an extra attribute or a close() method.

* It simplifies the implementation, because the point at which the
  return value from the subgenerator becomes available is the same
  point at which StopIteration is raised. Delaying until any later
  time would require storing the return value somewhere.


Criticisms
==========

Under this proposal, the value of a ``yield from`` expression would
be derived in a very different way from that of an ordinary ``yield``
expression. This suggests that some other syntax not containing the
word ``yield`` might be more appropriate, but no acceptable alternative
has so far been proposed.

It has been suggested that some mechanism other than ``return`` in
the subgenerator should be used to establish the value returned by
the ``yield from`` expression. However, this would interfere with
the goal of being able to think of the subgenerator as a suspendable
function, since it would not be able to return values in the same way
as other functions.

The use of an argument to StopIteration to pass the return value
has been criticised as an "abuse of exceptions", without any
concrete justification of this claim. In any case, this is only
one suggested implementation; another mechanism could be used
without losing any essential features of the proposal.

It has been suggested that a different exception, such as
GeneratorReturn, should be used instead of StopIteration to return a
value. However, no convincing practical reason for this has been put
forward, and the addition of a ``value`` attribute to StopIteration
mitigates any difficulties in extracting a return value from a
StopIteration exception that may or may not have one. Also, using a
different exception would mean that, unlike ordinary functions,
'return' without a value in a generator would not be equivalent to
'return None'.


Alternative Proposals
=====================

Proposals along similar lines have been made before, some using the
syntax ``yield *`` instead of ``yield from``.  While ``yield *`` is
more concise, it could be argued that it looks too similar to an
ordinary ``yield`` and the difference might be overlooked when reading
code.

To the author's knowledge, previous proposals have focused only on
yielding values, and thereby suffered from the criticism that the
two-line for-loop they replace is not sufficiently tiresome to write
to justify a new syntax.  By dealing with the full generator
protocol, this proposal provides considerably more benefit.


Additional Material
===================

Some examples of the use of the proposed syntax are available, and also a
prototype implementation based on the first optimisation outlined above.

`Examples and Implementation`_

.. _Examples and Implementation: http://www.cosc.canterbury.ac.nz/greg.ewing/python/yield-from/


Copyright
=========

This document has been placed in the public domain.



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