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Groups > comp.lang.python > #2806
| From | Robert Kern <robert.kern@gmail.com> |
|---|---|
| Subject | Re: Multiprocessing, shared memory vs. pickled copies |
| Date | 2011-04-07 15:01 -0500 |
| Organization | The Church of Last Thursday |
| References | (2 earlier) <cad2405b-378c-43e4-b79e-edf81e5701e2@w7g2000pre.googlegroups.com> <mailman.56.1302026842.9059.python-list@python.org> <5d0fcd63-cebf-4b6e-a176-20cb7bbec389@n12g2000yqc.googlegroups.com> <mailman.115.1302198262.9059.python-list@python.org> <df11f2e9-19e7-4713-a933-aa6161f8bb5d@p16g2000yqb.googlegroups.com> |
| Newsgroups | comp.lang.python |
| Message-ID | <mailman.122.1302206509.9059.python-list@python.org> (permalink) |
On 4/7/11 1:39 PM, John Ladasky wrote: > On Apr 7, 10:44 am, Robert Kern<robert.k...@gmail.com> wrote: >> On 4/7/11 1:40 AM, John Ladasky wrote: >> >>> On Apr 5, 10:43 am, Philip Semanchuk<phi...@semanchuk.com> wrote: >>>> And as Robert Kern pointed out, numpy arrays are also pickle-able. >> >>> OK, but SUBCLASSES of numpy.ndarray are not, in my hands, pickling as >>> I would expect. I already have lots of code that is based on such >>> subclasses, and they do everything I want EXCEPT pickle correctly. I >>> may have to direct this line of questions to the numpy discussion >>> group after all. >> >> Define the __reduce_ex__() method, not __getstate__(), __setstate__(). >> >> http://docs.python.org/release/2.6.6/library/pickle.html#pickling-and... >> >> ndarrays are extension types, so they use that mechanism. > > Thanks, Robert, as you can see, I got on that track shortly after I > posted my code example. This is apparently NOT a numpy issue, it's an > issue for pickling all C extension types. Yes, but seriously, you should ask on the numpy mailing list. You will probably run into more numpy-specific issues. At least, we'd have been able to tell you things like "ndarray is an extension type, so look at that part of the documentation" quicker. > Is there a way to examine a Python object, and determine whether it's > a C extension type or not? For sure? No, not really. Not at the Python level, at least. You may be able to do something at the C level, I don't know. > Or do you have to deduce that from the > documentation and/or the source code? > > I started hunting through the numpy source code last night. It's > complicated. I haven't found the ndarray object definition yet. > Perhaps because I was looking through .py files, when I actually > should have been looking through .c files? Yes. The implementation for __reduce__ is in numpy/core/src/multiarray/methods.c as array_reduce(). You may want to look in numpy/ma/core.py for the definition of MaskedArray. It shows how you would define __reduce__, __getstate__ and __setstate__ for a subclass of ndarray. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco
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Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-04 13:20 -0700
Re: Multiprocessing, shared memory vs. pickled copies Philip Semanchuk <philip@semanchuk.com> - 2011-04-04 19:34 -0400
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-05 09:58 -0700
Re: Multiprocessing, shared memory vs. pickled copies Philip Semanchuk <philip@semanchuk.com> - 2011-04-05 13:43 -0400
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-06 23:40 -0700
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-07 00:41 -0700
Re: Multiprocessing, shared memory vs. pickled copies Philip Semanchuk <philip@semanchuk.com> - 2011-04-07 09:23 -0400
Re: Multiprocessing, shared memory vs. pickled copies Robert Kern <robert.kern@gmail.com> - 2011-04-07 12:44 -0500
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-07 11:39 -0700
Re: Multiprocessing, shared memory vs. pickled copies Robert Kern <robert.kern@gmail.com> - 2011-04-07 15:01 -0500
Re: Multiprocessing, shared memory vs. pickled copies Robert Kern <robert.kern@gmail.com> - 2011-04-04 19:05 -0500
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-07 16:39 -0700
Re: Multiprocessing, shared memory vs. pickled copies Philip Semanchuk <philip@semanchuk.com> - 2011-04-04 21:16 -0400
Re: Multiprocessing, shared memory vs. pickled copies Robert Kern <robert.kern@gmail.com> - 2011-04-05 10:47 -0500
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-07 17:03 -0700
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-07 17:38 -0700
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-07 18:10 -0700
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-09 00:36 -0700
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-09 10:15 -0700
Re: Multiprocessing, shared memory vs. pickled copies John Ladasky <ladasky@my-deja.com> - 2011-04-09 13:18 -0700
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-10 08:01 -0700
Re: Multiprocessing, shared memory vs. pickled copies sturlamolden <sturlamolden@yahoo.no> - 2011-04-10 15:35 -0700
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