Travis E. Oliphant wrote:
> I correct my previous statement. Yes, this is true. Pickles generated
> with 1.0.1 cannot be read by version 1.0
>
> However, pickles generated with 1.0 can be read by 1.0.1. It is
> typically not the case that pickles created with newer versions of the
> code wil
Emanuele Olivetti wrote:
> I'm running numpy 1.0 and 1.0.1 on several hosts and
> today I've found that pickling arrays in 1.0.1 generates
> problems to 1.0. An example:
I correct my previous statement. Yes, this is true. Pickles generated
with 1.0.1 cannot be read by version 1.0
However, pick
Emanuele Olivetti wrote:
> I'm running numpy 1.0 and 1.0.1 on several hosts and
> today I've found that pickling arrays in 1.0.1 generates
> problems to 1.0. An example:
> --- numpy 1.0.1 ---
> import numpy
> import pickle
> a = numpy.array([1,2,3])
> f=open('test1.pickle','w')
> pickle.dump(a,f)
>
On Thu, December 7, 2006 6:42 pm, Charles R Harris wrote:
> The 1.0.x versions are supposed to be compatible. I don't see any changes
> to
> pickle in svn since before the 1.0 release, so there might be another
> problem here. Are there other differences between the machines? Python
> version, OS,
On 12/7/06, Keith Goodman <[EMAIL PROTECTED]> wrote:
On 12/7/06, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On 12/7/06, Emanuele Olivetti <[EMAIL PROTECTED]> wrote:
> > How can I let access pickled arrays made in numpy 1.0.1 to numpy 1.0 ?
>
> If you pickle in 1.0.1, I bet you can read it in 1.0
On 12/7/06, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On 12/7/06, Emanuele Olivetti <[EMAIL PROTECTED]> wrote:
> > How can I let access pickled arrays made in numpy 1.0.1 to numpy 1.0 ?
>
> If you pickle in 1.0.1, I bet you can read it in 1.0.
>
> I don't know why the pickle format keeps changing.
On 12/7/06, Emanuele Olivetti <[EMAIL PROTECTED]> wrote:
> How can I let access pickled arrays made in numpy 1.0.1 to numpy 1.0 ?
If you pickle in 1.0.1, I bet you can read it in 1.0.
I don't know why the pickle format keeps changing. But I understand
why an old version of software can't always r
I'm running numpy 1.0 and 1.0.1 on several hosts and
today I've found that pickling arrays in 1.0.1 generates
problems to 1.0. An example:
--- numpy 1.0.1 ---
import numpy
import pickle
a = numpy.array([1,2,3])
f=open('test1.pickle','w')
pickle.dump(a,f)
f.close()
---
If I unpickle test1.pickle in
