I am not surprised that my current branch doesn't cover all cases; it was specifically targeted at my exact, singular use case.
I'll work on making something more general, as well as improving test coverage. On Sat, Jul 16, 2016 at 9:29 AM, Matti Picus <matti.pi...@gmail.com> wrote: > So it seems the tests are lacking. Someone should: > - go through all the existing calls to dumps in tests and add "assert > '_numpypy' not in data" > - add tests for scalars > - fix so the tests pass > Matti > > > On 16/07/16 07:40, David Brochart wrote: > > To be more precise, PyPy pickling of Numpy arrays works fine, it is when > PyPy pickles a Numpy scalar that I get the error. > David. > > On Sat, Jul 16, 2016 at 2:04 PM, David Brochart <david.broch...@gmail.com> > wrote: >> >> Hi, >> >> I verified that this version of PyPy can load a Numpy array that was >> pickled by CPython (and do stuff with it), but it looks like a Numpy array >> pickled by PyPy cannot be loaded by CPython, because PyPy still uses >> '_numpypy.multiarray' in the pickle string for dumping: >> ImportError: No module named _numpypy.multiarray >> >> David. >> >> On Sat, Jul 16, 2016 at 12:07 PM, Matti Picus <matti.pi...@gmail.com> >> wrote: >>> >>> The issue with '_numpypy.multiarray' in the pickle string rather than >>> 'numpy.core.multiarray' should be fixed on the numpypy_pickle_compat branch >>> (thanks to Eli) >>> A linux 64 build is available >>> http://buildbot.pypy.org/nightly/numpypy_pickle_compat/pypy-c-jit-85727-6d909c810029-linux64.tar.bz2. >>> Eli or David or anyone who uses numpy pickle, could you check that this >>> works as advertised? I am concerned about how compatible our pickling is >>> with upstream numpy, but do not really use that feature of numpy so another >>> pair of eyes would be nice before merging to default. >>> >>> Note this requires that http://bitbucket.org/pypy/numpy be installed >>> since the Unpickler must be able to import numpy.core.multiarray >>> Matti >>> >>> On 15/07/16 10:47, David Brochart wrote: >>>> >>>> Hi, >>>> >>>> I'd like to use the (numerical) performances of PyPy as an equivalent to >>>> Numba's @jit decorator (https://github.com/davidbrochart/piopio). The only >>>> thing preventing that right now is the passing around (pickling) of Numpy >>>> arrays, so it would be great to have that compatibility. >>>> >>>> David. >>>> >>>> On Mon, Jul 11, 2016 at 6:43 PM, Eli Stevens (Gmail) >>>> <wickedg...@gmail.com <mailto:wickedg...@gmail.com>> wrote: >>>> >>>> FWVLIW, I think that conforming to upstream numpy makes the most >>>> sense. >>>> >>>> I think that the issue would go away if the `_numpypy` module were >>>> renamed to `numpy` (and appropriate things moved into `numpy.core`). >>>> Is there a technical reason to keep the actual implementation in a >>>> separately named module? >>>> >>>> Thinking larger picture, would it be possible and sensible to switch >>>> to using the slow cpyext numpy approach for compatability, then >>>> overlay custom implementation of things on top of that when speed is >>>> needed? I'm imagining a vague inverse of the cpython approach, >>>> where >>>> modules are implemented in C when the python performance isn't >>>> acceptable. >>>> >>>> Eli >>>> >>>> On Wed, Jun 29, 2016 at 10:58 PM, Armin Rigo <ar...@tunes.org >>>> <mailto:ar...@tunes.org>> wrote: >>>> > Hi Eli, hi Matti, >>>> > >>>> > On 29 June 2016 at 21:37, Eli Stevens (Gmail) >>>> <wickedg...@gmail.com <mailto:wickedg...@gmail.com>> wrote: >>>> >> To make sure I'm understanding, are you saying that >>>> upstream/cpython >>>> >> numpy should pick up an alternate way to import multiarray (via >>>> >> _numpypy.multiarray, instead of numpy.core.multiarray) >>>> > >>>> > Hum, in my opinion we should always pickle/unpickle arrays by >>>> > reproducing and expecting the exact same format as CPython's >>>> numpy, >>>> > with no warnings. Any difference (e.g. with complicated dtypes) >>>> is a >>>> > bug that should eventually be fixed. >>>> > >>>> > >>>> > A bientôt, >>>> > >>>> > Armin. >>>> _______________________________________________ >>>> pypy-dev mailing list >>>> pypy-dev@python.org <mailto:pypy-dev@python.org> >>>> https://mail.python.org/mailman/listinfo/pypy-dev >>>> >>>> >>>> >>>> >>>> _______________________________________________ >>>> pypy-dev mailing list >>>> pypy-dev@python.org >>>> https://mail.python.org/mailman/listinfo/pypy-dev >>> >>> >> > > _______________________________________________ pypy-dev mailing list pypy-dev@python.org https://mail.python.org/mailman/listinfo/pypy-dev
