On Feb 21, 2009, at 2:17 PM, Brett Cannon wrote:
The other approach is having pickle contain code known not to be
overridden by anyone, import _pypickle for stuff that may be
overridden, and then import _pickle for whatever is available. This
approach has the perk of using a standard practice for how to pull
in different implementation. But the drawback, thanks to how globals
are bound, is that any code pulled in from _pickle/_pypickle will
not be able to call into other optimized code; it's a take or leave
it once the call chain enters one of those modules as they will
always call the implementations in the module they originate from.
fwiw,
I believe this is the approach that I've been using when I'm faced
with the need to optimize code, but still want to retain a pure-Python
version. Thankfully, I haven't had a need for "implementation
intersections"(well, it almost works. I think. ;) for access to common
module globals as the optimizations tend to be simple transformations
or isolated classes. However, if I were faced with the problem of
needing some common global data/functionality, I'd probably put it in
yet-another-module and just import it explicitly in each
implementation. Sure, it seems like it might be annoying, but so is
maintaining multiple implementations. ;)
Specifically:
pbuffer.py - The python implementation
buffer.c -> cbuffer.so - The c implementation
buffer.py - The "abstraction module", trying to import the contents of
the fast one first.
And in my unittest:
if c_buffer_module is not None:
class c_buffer(buffer_test, unittest.TestCase):
bufferclass = c_buffer_module.pq_message_stream
class p_buffer(buffer_test, unittest.TestCase):
bufferclass = p_buffer_module.pq_message_stream
Of course, "buffer_test" is not invoked because it's not a TestCase.
However, Aahz is probably right about this thread belonging elsewhere.?
Hrm, day old, maybe it's been moved already.. sigh. :)
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