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ANN: PyTables 3.3.0

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ANN: PyTables 3.3.0

Tom Kooij
===========================
 Announcing PyTables 3.3.0
===========================

We are happy to announce PyTables 3.3.0.


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

- Single codebase Python 2 and 3 support (PR #493).
- Internal Blosc version updated to 1.11.1 (closes :issue:`541`)
- Full BitShuffle support for new Blosc versions (>= 1.8).
- It is now possible to remove all rows from a table.
- It is now possible to read reference types by dereferencing them as
  numpy array of objects (closes :issue:`518` and :issue:`519`).
  Thanks to Ehsan Azar
- Fixed Windows 32 and 64-bit builds.

In case you want to know more in detail what has changed in this

You can install it via pip or download a source package with generated
PDF and HTML docs from:

For an online version of the manual, visit:


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/



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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j

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