[Python-ideas] Revised PEP on yield-from expression

[Greg Ewing]

Here's a revision of the PEP incorporating
the corrections posted earlier. There is also
a new section titled "Generators as Threads"
providing additional motivation.

PEP: XXX
Title: Syntax for Delegating to a Subgenerator
Version: $Revision$
Last-Modified: $Date$
Author: Gregory Ewing <greg.ewing at 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 to allow a generator to easily delegate part of
its operations to another generator, with the subgenerator yielding
directly to the delegating generator's caller and receiving values
sent to the delegating generator using send(). 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.


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 effect is to run the iterator to
exhaustion, with any values that it yields being passed directly to
the caller of the generator containing the ``yield from`` expression
(the "delegating generator"), and any values sent to the delegating
generator using ``send()`` being sent directly to the iterator. (If
the iterator does not have a ``send()`` method, values sent in are
ignored.)

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

Additionally, generators will be allowed to execute a ``return``
statement with a value, and that value will be passed as an argument
to the ``StopIteration`` exception.


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

The statement

::

     result = yield from expr

is semantically equivalent to

::

     _i = iter(expr)
     try:
         _v = yield _i.next()
         while 1:
             if hasattr(_i, 'send'):
                 _v = yield _i.send(_v)
             else:
                 _v = yield _i.next()
     except StopIteration, _e:
         _a = _e.args
         if len(_a) > 0:
             result = _a[0]
         else:
             result = None


Rationale
=========

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 is not very arduous
and can be performed with a loop such as

::

     for v in g:
         yield v

However, if the subgenerator is to receive values sent to the outer
generator using ``send()``, it is considerably more complicated. As
the formal expansion presented above illustrates, the necessary code
is very longwinded, and it is tricky to handle all the corner cases
correctly.  In this case, the advantages of a specialised syntax
should be clear.


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

A motivating use case 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 subgenerators as though they were
ordinary functions, passing them parameters and receiving a returned
value.

Using the proposed syntax, a function call such as

::

     y = f(x)

where f is an ordinary function, can be transformed into an equivalent
generator call

::

     y = yield from g(x)

where g is a generator.


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 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.


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 sent values
as well as yielded ones, this proposal provides considerably more
benefit.


Copyright
=========

This document has been placed in the public domain.



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-- 
Greg