===========================
 Announcing PyTables @VERSION@
===========================

We are happy to announce PyTables @VERSION@.

This is a bug-fix release that addresses a critical bug that make PyTables
unusable on some platforms.


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

- Fixed a critical bug that caused an exception at import time.
  The error was triggered when a bug in long-double detection is detected
  in the HDF5 library (see :issue:`275`) and numpy_ does not expose
  `float96` or `float128`. Closes :issue:`344`.
- The internal Blosc_ library has been updated to version 1.3.5.
  This fixes a false buffer overrun condition that made c-blosc to fail,
  even if the problem was not real.

As always, a large amount of bugs have been addressed and squashed as well.

In case you want to know more in detail what has changed in this
version, please refer to: http://pytables.github.io/release_notes.html

You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/@VERSION@

For an online version of the manual, visit:
http://pytables.github.io/usersguide/index.html


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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