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@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.  .. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 coding: utf-8 End: -- Greg