Hi List,
I was planning to do a maintenance release for a while (mainly to cope with
the API change in HDF5 1.8.3 affecting filters), and finally got some time to
do it. See below the official announcement.
Enjoy!
===========================
Announcing PyTables 2.1.2
===========================
PyTables is a library for managing hierarchical datasets and designed to
efficiently cope with extremely large amounts of data with support for
full 64-bit file addressing. PyTables runs on top of the HDF5 library
and NumPy package for achieving maximum throughput and convenient use.
This is maintenance release. Some bugs has been fixed, and support
for latest HDF5 1.8.3 libraries is there. Also, instructions on how
to find LZO binaries for Windows has been added to the User's Guide.
In case you want to know more in detail what has changed in this
version, have a look at:
http://www.pytables.org/moin/ReleaseNotes/Release_2.1.2
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://www.pytables.org/download/stable
For an on-line version of the manual, visit:
http://www.pytables.org/docs/manual-2.1.2
You may want to fetch an evaluation version for PyTables Pro from:
http://www.pytables.org/download/evaluation
Resources
=========
About PyTables:
http://www.pytables.org
About the HDF5 library:
http://www.hdfgroup.org/HDF5/
About NumPy:
http://numpy.scipy.org/
Acknowledgments
===============
Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions. See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors. Most
specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
makers. Without them, PyTables simply would not exist.
Share your experience
=====================
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.
----
**Enjoy data!**
-- The PyTables Team
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