=========================== 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: http://github.com/PyTables/PyTables.
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 Sphinx
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: http://pytables.github.com/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/2.3
For an on-line version of the manual, visit: http://pytables.github.com/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 1 tenth of a second.
About the HDF5 library:
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.
-- The PyTables Team