===========================
 Announcing PyTables 3.2.2
===========================

We are happy to announce PyTables 3.2.2.


Changes from 3.2.1.1 to 3.2.2
=============================

Bug fixed
---------

- Fix AssertionError in Row.__init_loop. See :issue:`477`.
- Fix issues with Cython 0.23. See :issue:`481`.
- Only run `tables.tests.test_basics.UnicodeFilename` if the filesystem
  encoding is utf-8. Closes :issue:`485`.
- Fix missing missing PyErr_Clear. See :issue:`#486`.
- Fix the C type of some numpy attributes. See :issue:`494`.
- Cast selection indices to integer. See :issue:`496`.
- Fix indexesextension._keysort_string. Closes :issue:`497` and
  :issue:`498`.


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.  PyTables includes OPSI, a new indexing technology,
allowing to perform data lookups in tables exceeding 10 gigarows
(10**10 rows) in less than a tenth of a second.


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 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 Developers

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