192 lines
8.3 KiB
Plaintext
192 lines
8.3 KiB
Plaintext
PEP: 219
|
||
Title: Stackless Python
|
||
Version: $Revision$
|
||
Last-Modified: $Date$
|
||
Author: gmcm@hypernet.com (Gordon McMillan)
|
||
Status: Deferred
|
||
Type: Standards Track
|
||
Created: 14-Aug-2000
|
||
Python-Version: 2.1
|
||
Post-History:
|
||
|
||
|
||
Introduction
|
||
|
||
This PEP discusses changes required to core Python in order to
|
||
efficiently support generators, microthreads and coroutines. It is
|
||
related to PEP 220, which describes how Python should be extended
|
||
to support these facilities. The focus of this PEP is strictly on
|
||
the changes required to allow these extensions to work.
|
||
|
||
While these PEPs are based on Christian Tismer's Stackless[1]
|
||
implementation, they do not regard Stackless as a reference
|
||
implementation. Stackless (with an extension module) implements
|
||
continuations, and from continuations one can implement
|
||
coroutines, microthreads (as has been done by Will Ware[2]) and
|
||
generators. But in more that a year, no one has found any other
|
||
productive use of continuations, so there seems to be no demand
|
||
for their support.
|
||
|
||
However, Stackless support for continuations is a relatively minor
|
||
piece of the implementation, so one might regard it as "a"
|
||
reference implementation (rather than "the" reference
|
||
implementation).
|
||
|
||
|
||
Background
|
||
|
||
Generators and coroutines have been implemented in a number of
|
||
languages in a number of ways. Indeed, Tim Peters has done pure
|
||
Python implementations of generators[3] and coroutines[4] using
|
||
threads (and a thread-based coroutine implementation exists for
|
||
Java). However, the horrendous overhead of a thread-based
|
||
implementation severely limits the usefulness of this approach.
|
||
|
||
Microthreads (a.k.a "green" or "user" threads) and coroutines
|
||
involve transfers of control that are difficult to accommodate in
|
||
a language implementation based on a single stack. (Generators can
|
||
be done on a single stack, but they can also be regarded as a very
|
||
simple case of coroutines.)
|
||
|
||
Real threads allocate a full-sized stack for each thread of
|
||
control, and this is the major source of overhead. However,
|
||
coroutines and microthreads can be implemented in Python in a way
|
||
that involves almost no overhead. This PEP, therefor, offers a
|
||
way for making Python able to realistically manage thousands of
|
||
separate "threads" of activity (vs. todays limit of perhaps dozens
|
||
of separate threads of activity).
|
||
|
||
Another justification for this PEP (explored in PEP 220) is that
|
||
coroutines and generators often allow a more direct expression of
|
||
an algorithm than is possible in today's Python.
|
||
|
||
|
||
Discussion
|
||
|
||
The first thing to note is that Python, while it mingles
|
||
interpreter data (normal C stack usage) with Python data (the
|
||
state of the interpreted program) on the stack, the two are
|
||
logically separate. They just happen to use the same stack.
|
||
|
||
A real thread gets something approaching a process-sized stack
|
||
because the implementation has no way of knowing how much stack
|
||
space the thread will require. The stack space required for an
|
||
individual frame is likely to be reasonable, but stack switching
|
||
is an arcane and non-portable process, not supported by C.
|
||
|
||
Once Python stops putting Python data on the C stack, however,
|
||
stack switching becomes easy.
|
||
|
||
The fundamental approach of the PEP is based on these two
|
||
ideas. First, separate C's stack usage from Python's stack
|
||
usage. Secondly, associate with each frame enough stack space to
|
||
handle that frame's execution.
|
||
|
||
In the normal usage, Stackless Python has a normal stack
|
||
structure, except that it is broken into chunks. But in the
|
||
presence of a coroutine / microthread extension, this same
|
||
mechanism supports a stack with a tree structure. That is, an
|
||
extension can support transfers of control between frames outside
|
||
the normal "call / return" path.
|
||
|
||
|
||
Problems
|
||
|
||
The major difficulty with this approach is C calling Python. The
|
||
problem is that the C stack now holds a nested execution of the
|
||
byte-code interpreter. In that situation, a coroutine /
|
||
microthread extension cannot be permitted to transfer control to a
|
||
frame in a different invocation of the byte-code interpreter. If a
|
||
frame were to complete and exit back to C from the wrong
|
||
interpreter, the C stack could be trashed.
|
||
|
||
The ideal solution is to create a mechanism where nested
|
||
executions of the byte code interpreter are never needed. The easy
|
||
solution is for the coroutine / microthread extension(s) to
|
||
recognize the situation and refuse to allow transfers outside the
|
||
current invocation.
|
||
|
||
We can categorize code that involves C calling Python into two
|
||
camps: Python's implementation, and C extensions. And hopefully we
|
||
can offer a compromise: Python's internal usage (and C extension
|
||
writers who want to go to the effort) will no longer use a nested
|
||
invocation of the interpreter. Extensions which do not go to the
|
||
effort will still be safe, but will not play well with coroutines
|
||
/ microthreads.
|
||
|
||
Generally, when a recursive call is transformed into a loop, a bit
|
||
of extra bookkeeping is required. The loop will need to keep its
|
||
own "stack" of arguments and results since the real stack can now
|
||
only hold the most recent. The code will be more verbose, because
|
||
it's not quite as obvious when we're done. While Stackless is not
|
||
implemented this way, it has to deal with the same issues.
|
||
|
||
In normal Python, PyEval_EvalCode is used to build a frame and
|
||
execute it. Stackless Python introduces the concept of a
|
||
FrameDispatcher. Like PyEval_EvalCode, it executes one frame. But
|
||
the interpreter may signal the FrameDispatcher that a new frame
|
||
has been swapped in, and the new frame should be executed. When a
|
||
frame completes, the FrameDispatcher follows the back pointer to
|
||
resume the "calling" frame.
|
||
|
||
So Stackless transforms recursions into a loop, but it is not the
|
||
FrameDispatcher that manages the frames. This is done by the
|
||
interpreter (or an extension that knows what it's doing).
|
||
|
||
The general idea is that where C code needs to execute Python
|
||
code, it creates a frame for the Python code, setting its back
|
||
pointer to the current frame. Then it swaps in the frame, signals
|
||
the FrameDispatcher and gets out of the way. The C stack is now
|
||
clean - the Python code can transfer control to any other frame
|
||
(if an extension gives it the means to do so).
|
||
|
||
In the vanilla case, this magic can be hidden from the programmer
|
||
(even, in most cases, from the Python-internals programmer). Many
|
||
situations present another level of difficulty, however.
|
||
|
||
The map builtin function involves two obstacles to this
|
||
approach. It cannot simply construct a frame and get out of the
|
||
way, not just because there's a loop involved, but each pass
|
||
through the loop requires some "post" processing. In order to play
|
||
well with others, Stackless constructs a frame object for map
|
||
itself.
|
||
|
||
Most recursions of the interpreter are not this complex, but
|
||
fairly frequently, some "post" operations are required. Stackless
|
||
does not fix these situations because of amount of code changes
|
||
required. Instead, Stackless prohibits transfers out of a nested
|
||
interpreter. While not ideal (and sometimes puzzling), this
|
||
limitation is hardly crippling.
|
||
|
||
|
||
Advantages
|
||
|
||
For normal Python, the advantage to this approach is that C stack
|
||
usage becomes much smaller and more predictable. Unbounded
|
||
recursion in Python code becomes a memory error, instead of a
|
||
stack error (and thus, in non-Cupertino operating systems,
|
||
something that can be recovered from). The price, of course, is
|
||
the added complexity that comes from transforming recursions of
|
||
the byte-code interpreter loop into a higher order loop (and the
|
||
attendant bookkeeping involved).
|
||
|
||
The big advantage comes from realizing that the Python stack is
|
||
really a tree, and the frame dispatcher can transfer control
|
||
freely between leaf nodes of the tree, thus allowing things like
|
||
microthreads and coroutines.
|
||
|
||
|
||
References
|
||
|
||
[1] http://www.stackless.com
|
||
[2] http://world.std.com/~wware/uthread.html
|
||
[3] Demo/threads/Generator.py in the source distribution
|
||
[4] http://www.stackless.com/coroutines.tim.peters.html
|
||
|
||
|
||
|
||
Local Variables:
|
||
mode: indented-text
|
||
indent-tabs-mode: nil
|
||
End:
|