On 25.08.2011, at 8:42PM, Chris.Barker wrote:
> On 8/24/11 9:22 AM, Anthony Scopatz wrote:
>> You can use Python pickling, if you do *not* have a requirement for:
>
> I can't recall why, but it seem pickling of numpy arrays has been
> fragile and not very performant.
>
Hmm, the pure Python version might be, but, I've used cPickle for a long time
and never noted any stability problems. And it is still noticeably faster than
pytables, in my experience. Still, for the sake of a standardised format I'd
go with HDF5 any time now (and usually prefer h5py now when starting
anything new - my pytables implementation mentioned above likely is not
the most efficient compared to cPickle).
But with the usual disclaimers, you should be able to simply use cPickle
as a drop-in replacement in the example below.
Cheers,
Derek
On 21.08.2011, at 2:24PM, Pauli Virtanen wrote:
> You can use Python pickling, if you do *not* have a requirement for:
>
> - real persistence, i.e., being able to easily read the data years later
> - a standard data format
> - access from non-Python programs
> - safety against malicious parties (unpickling can execute some code
> in the input -- although this is possible to control)
>
> then you can use Python pickling:
>
> import pickle
>
> file = open('out.pck', 'wb')
> pickle.dump(file, tree, protocol=pickle.HIGHEST_PROTOCOL)
> file.close()
>
> file = open('out.pck', 'rb')
> tree = pickle.load(file)
> file.close()
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