On Sat, 21 Feb 2009 11:07:07 -0800, Brett Cannon <br...@python.org> wrote:
On Sat, Feb 21, 2009 at 09:17, Jean-Paul Calderone <exar...@divmod.com>wrote:
On Fri, 20 Feb 2009 13:45:26 -0800, Brett Cannon <br...@python.org> wrote:
On Fri, Feb 20, 2009 at 12:53, Aahz <a...@pythoncraft.com> wrote:
On Fri, Feb 20, 2009, Brett Cannon wrote:
> On Fri, Feb 20, 2009 at 12:37, Brett Cannon <br...@python.org> wrote:
>> On Fri, Feb 20, 2009 at 12:31, Daniel Stutzbach <
>> dan...@stutzbachenterprises.com> wrote:
>>>
>>> A slight change would make it work for modules where only key
functions
>>> have been rewritten. For example, pickle.py could read:
>>>
>>> from _pypickle import *
>>> try: from _pickle import *
>>> except ImportError: pass
>>
>> True, although that still suffers from the problem of overwriting
things
>> like __name__, __file__, etc.
>
> Actually, I take that back; the IMPORT_STAR opcode doesn't pull in
anything
> starting with an underscore. So while this alleviates the worry above,
it
> does mean that anything that gets rewritten needs to have a name that
does
> not lead with an underscore for this to work. Is that really an
acceptable
> compromise for a simple solution like this?
Doesn't __all__ control this?
If you define it, yes.
But there is another issue with this: the pure Python code will never call
the extension code because the globals will be bound to _pypickle and not
_pickle. So if you have something like::
# _pypickle
def A(): return _B()
def _B(): return -13
# _pickle
def _B(): return 42
# pickle
from _pypickle import *
try: from _pickle import *
except ImportError: pass
If you import pickle and call pickle.A() you will get -13 which is not
what
you are after.
If pickle and _pypickle are both Python modules, and _pypickle.A is
intended
to be used all the time, regardless of whether _pickle is available, then
there's not really any reason to implement A in _pypickle. Just implement
it
in pickle. Then import whatever optionally fast thing it depends on from
_pickle, if possible, and fall-back to the less fast thing in _pypickle
otherwise.
This is really the same as any other high-level/low-level library split.
It
doesn't matter that in this case, one low-level implementation is provided
as
an extension module. Importing the low-level APIs from another module and
then using them to implement high-level APIs is a pretty common, simple,
well-understood technique which is quite applicable here.
But that doesn't provide a clear way, short of screwing with sys.modules, to
get at just the pure Python implementation for testing when the extensions
are also present. The key point in trying to figure this out is to
facilitate testing since the standard library already uses the import *
trick in a couple of places.
"screwing with sys.modules" isn't a goal. It's a means of achieving a goal,
and not a particularly good one.
I guess I overedited my message, sorry about that. Originally I included
an example of how to parameterize the high-level API to make it easier to
test (or use) with any implementation one wants. It went something like
this:
try:
import _pickle as _lowlevel
except ImportError:
import _pypickle as _lowlevel
class Pickler:
def __init__(self, implementation=None):
if implementation is None:
implementation = _lowlevel
self.dump = implementation.dump
self.load = implementation.load
...
Perhaps this isn't /exactly/ how pickle wants to work - I haven't looked at
how the C extension and the Python code fit together - but the general idea
should apply regardless of those details.
Jean-Paul
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