ANN: PyTables 2.1 (final) released

Francesc Alted falted at
Fri Dec 19 17:54:46 CET 2008

 Announcing PyTables 2.1

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.

PyTables 2.1 introduces important improvements, like much faster node
opening, creation or navigation, a file-based way to fine-tune the
different PyTables parameters (fully documented now in a new appendix of
the manual) and support for multidimensional atoms in EArray/CArray

Regarding the Pro edition, four different kinds of indexes are supported
so that the user can choose the best for her needs.  Also, and due to
the introduction of the concept of chunkmaps in OPSI, the responsiveness
of complex queries with low selectivity has improved quite a lot.  And
last but not least, it is possible now to sort tables by a specific
field with no practical limit in size (tables up to 2**48 rows).

Also, a lot of work has gone in the reworking of the "Optimization tips"
chapter of the manual where many benchmarks have been redone using newer
software and machines and a few new sections have been added.  In
particular, see the new "Fine-tuning the chunksize" section where you
will find an in-deep introduction to the subject of chunking and the
"Indexing and Solid State Disks (SSD)" where the advantages of using
low-latency SSD disks have been analysed in the context of indexation.

In case you want to know more in detail what has changed in this
version, have a look at ``RELEASE_NOTES.txt`` in the tarball.  Find the
HTML version for this document at:

You can download a source package of the version 2.1 with
generated PDF and HTML docs and binaries for Windows from

For an on-line version of the manual, visit:

Finally, you can get an evaluation version for PyTables Pro in:


Go to the PyTables web site for more details:

About the HDF5 library:

About NumPy:


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.  Many
thanks also to SourceForge who have helped to make and distribute this
package!  And last, but not least thanks a lot 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


  **Enjoy data!**

  -- The PyTables Team
Francesc Alted

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