[Numpy-discussion] ANN: PyTables 2.3 released

Antonio Valentino antonio.valentino at tiscali.it
Fri Sep 23 14:39:52 EDT 2011

 Announcing PyTables 2.3

We are happy to announce PyTables 2.3.
This release comes after about 10 months of development and after that
Francesc Altet, the creator of PyTables, ceased activities with the project.

Thank you Francesc.

Also the project has been moved to GitHub:

What's new

The main new features in 2.3 series are:

* PyTables now includes the codebase of PyTables Pro (now release under open
  source license) gaining a lot of performance improvements and some new
  features like:

  - the new and powerful indexing engine: OPSI
  - a fine-tuned LRU cache for both metadata (nodes) and regular data

* The entire documentation set has been converted to ReStructuredTest and

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

In case you want to know more in detail what has changed in this
version, have a look at:

You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:

For an on-line 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 1 tenth of a second.


About PyTables:


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.  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


  **Enjoy data!**

The PyTables Team

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