[Numpy-discussion] [ANN] PyTables 2.1.1 released

Francesc Alted faltet@pytables....
Fri Mar 13 12:41:35 CDT 2009


===========================
 Announcing PyTables 2.1.1
===========================

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 a maintenance release, so you should not expect API changes.
Instead, a handful of bugs, like `File` not being subclassable,
incorrectly retrieved default values for data types, a memory leak,
and more, have been fixed.  Besides, some enhancements have been
implemented, like improved Unicode support for filenames, better
handling of Unicode attributes, and the possibility to create very
large data types exceeding 64 KB in size (with some limitations).
Last but not least, this is the first PyTables version fully tested
against Python 2.6.  It is worth noting that binaries for Windows and
Python 2.6 wears the newest HDF5 1.8.2 libraries (instead of the
traditional HDF5 1.6.x) now.

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_2.1.1

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-2.1.1

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

-- 
Francesc Alted


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