Hi List,
I'm glad to announce you the third beta version of PyTables 2.2 series. As
you should know by now, I've added support for the high-performance Blosc
compressor, so, if you are using compression (and if you are concerned about
getting the most out of your data, you should) you will see PyTables to be
faster than ever before.
Although I've already tested Blosc quite a lot, it is still in beta, but I'm
confident that if enough people help me in testing the beast, we can make it
stable enough to be marked apt for production in a few months.
And now, the official announcement:
===========================
Announcing PyTables 2.2b3
===========================
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 the third, and most probably last, beta version of 2.2 release.
The main addition in this beta version is the addition of Blosc
(http://blosc.pytables.org), a high-speed compressor that is meant to
work at similar speeds, or higher, than the memory-cache bandwidth in
modern processors. This will allow for very high performance in
internal, in-memory PyTables computations while still using compression.
Remember that Blosc is still in *beta* and it is not meant for
production purposes yet. You have been warned!
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_2.2b3
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://www.pytables.org/download/preliminary
For an on-line version of the manual, visit:
http://www.pytables.org/docs/manual-2.2b3
Resources
=========
About PyTables:
http://www.pytables.org
About the HDF5 library:
http://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!**
--
Francesc Alted
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