Re: [Numpy-discussion] py2/py3 pickling

2015-08-25 Thread Antoine Pitrou
On Tue, 25 Aug 2015 19:12:30 +0300 Pauli Virtanen wrote: > 25.08.2015, 01:15, Chris Laumann kirjoitti: > > Would it be possible then (in relatively short order) to create > > a py2 -> py3 numpy pickle converter? > > You probably need to modify the pickle stream directly, replacing > *STRING opc

Re: [Numpy-discussion] py2/py3 pickling

2015-08-25 Thread Pauli Virtanen
25.08.2015, 01:15, Chris Laumann kirjoitti: > Would it be possible then (in relatively short order) to create > a py2 -> py3 numpy pickle converter? You probably need to modify the pickle stream directly, replacing *STRING opcodes with *BYTES opcodes when it comes to objects that are needed for c

Re: [Numpy-discussion] py2/py3 pickling

2015-08-24 Thread Chris Laumann
Hi- Would it be possible then (in relatively short order) to create a py2 -> py3 numpy pickle converter? This would run in py2, np.load or unpickle a pickle in the usual way and then repickle and/or save using a pickler that uses an explicit pickle type for encoding the bytes associated with nu

Re: [Numpy-discussion] py2/py3 pickling

2015-08-24 Thread Nathaniel Smith
On Aug 24, 2015 9:29 AM, "Pauli Virtanen" wrote: > > 24.08.2015, 01:02, Chris Laumann kirjoitti: > [clip] > > Is there documentation about the limits and workarounds for py2/py3 > > pickle/np.save/load compatibility? I haven't found anything except > > developer bug tracking discussions (eg. #4879

Re: [Numpy-discussion] py2/py3 pickling

2015-08-24 Thread Pauli Virtanen
24.08.2015, 01:02, Chris Laumann kirjoitti: [clip] > Is there documentation about the limits and workarounds for py2/py3 > pickle/np.save/load compatibility? I haven't found anything except > developer bug tracking discussions (eg. #4879 in github numpy). Not sure if it's written down somewhere b

[Numpy-discussion] py2/py3 pickling

2015-08-23 Thread Chris Laumann
Hi all- Is there documentation about the limits and workarounds for py2/py3 pickle/np.save/load compatibility? I haven't found anything except developer bug tracking discussions (eg. #4879 in github numpy). The kinds of errors you get can be really obscure when save/loading complicated objects