On 04.06.2013 05:35, Tim Burgess wrote:
My thoughts are:
- try it without any compression. Assuming 32 bit floats, your monthly
5760 x 2880 is only about 65MB. Uncompressed data may perform well and
at the least it will give you a baseline to work from - and will help if
you are
anthony,
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anthony,
where am I going wrong here?
#!/usr/local/bin/python3
import tables
import numpy as np
import datetime, time
encoding = 'UTF-8'
test_file = 'test_select.h5'
handle = tables.openFile(test_file, w)
node = handle.createGroup(handle.root, 'test')
table = handle.createTable(node, 'table',
Hi Jeff,
Have you also updated numexpr to the most recent version? The error is
coming from numexpr not compiling the expression correctly. Also, you might
try making selector a str, rather than bytes:
selector = (column == 'str-2')
rather than
selector = (column == 'str-2').encode(encoding)
Anthony,
I am using numexpr 2.1 (latest)
this is puzzling; doesn't matter what I pass (bytes or str) , same result?
(column == 'str-2')
/mnt/code/arb/test/pytables-3.py(38)module()
- result = handle.root.test.table.readWhere(selector)
(Pdb) handle.root.test.table.readWhere(selector)
***
I think I've seen this in the release notes of 3.0. This is actually
something that I'm looking into as well. So any experience/feedback about
creating files in memory would be much appreciated.
Best regards
Seref
On Tue, Jun 4, 2013 at 2:09 PM, Andreas Hilboll li...@hilboll.de wrote:
On
Anthony,
I created an issue with more info
I am not sure if this is a bug, or just a way both ne/pytables treat strings
that need to touch an encoded value;
I found workaround by specifying the condvars to readWhere. Any more thoughts
on this?
thanks Jeff
I was playing around with in-memory HDF5 prior to the 3.0 release. Here's an example based on what I was doing.I looked over the docs and it does mention that there is an option to throw away the 'file' rather than write it to disk.Not sure how to do that and can't actually think of a use case
