Robert Kern wrote: > On Thu, Dec 4, 2008 at 18:54, Brennan Williams > <[EMAIL PROTECTED]> wrote: > >> Thanks >> >> [EMAIL PROTECTED] wrote: >> >>> I didn't check what this does behind the scenes, but try this >>> >>> >>> >> import hashlib #standard python library >> import numpy as np >> >>> m = hashlib.md5() >>> m.update(np.array(range(100))) >>> m.update(np.array(range(200))) >>> > > I would recommend doing this on the strings before you make arrays > from them. You don't know if the network cut out in the middle of an > 8-byte double. > > Of course, sending the lengths and other metadata first, then the data > would let you check without needing to do expensivish hashes or > checksums. If truncation is your problem rather than corruption, then > that would be sufficient. You may also consider using the NPY format > in numpy 1.2 to implement that. > > Thanks for the ideas. I'm definitely going to add some more basic checks on lengths etc as well. Unfortunately the problem is happening at a client site so (a) I can't reproduce it and (b) most of the time they can't reproduce it either. This is a Windows Python app running on Citrix reading/writing data to a Linux networked drive.
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