[Pytables-announce] ANN: PyTables 2.2.1 released

[Francesc A. <fa...@py...>]

Hi List,

I'm really proud to announce the availability of PyTables and PyTables 
Pro 2.2.1.  This release has been tested pretty toughly, and it is the 
recommended one to use in production.

Also, and due to popular demand, the new evaluation version for PyTables 
Pro is based now on previous Pro 2.2.  I think this way more people will 
be able to check the performance boost that the multi-core additions 
(Numexpr, Blosc) introduced in 2.2 is bringing to Pro.

Thanks for all who have contributed reports, patches and suggestions.  
Without you, PyTables would be much less useful.

And now, the official announcement,

===========================
 Announcing PyTables 2.2.1
===========================

This is maintenance release.  The updgrading is recommended for all that
are running PyTables in production environments.


What's new
==========

Many fixes have been included, as well as a fair bunch of performance
improvements.  Also, the Blosc compression library has been updated to
1.1.2, in order to prevent locks in some scenarios.  Finally, the new
evaluation version of PyTables Pro is based on the previous Pro 2.2.

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_2.2.1

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-2.2.1


What it is?
===========

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.


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