============================================ Announcing PyTables and PyTables Pro 2.0.1 ============================================ 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 that mainly fixes (quite a few of) bugs, as well as some small enhancements (support for accessing table rows beyond 2**31 rows in 32-bit platforms and reduced memory footprint in table I/O). Also, binaries have been compiled against the latest stable version of HDF5, 1.6.6, released during the past August. Thanks to the broadening PyTables community for all the valuable feedback. Moreover, the Pro version has received an optimization in the node cache that allows for a 2x improvement in time retrieval of nodes in cache. With this, PyTables Pro can be now up to 20x faster than regular PyTables when handling a large amount of nodes simultaneously. In case you want to know more in detail what has changed in this version, have a look at ``RELEASE_NOTES.txt``. Find the HTML version for this document at: http://www.pytables.org/moin/ReleaseNotes/Release_2.0.1 You can download a source package of the version 2.0.1 with generated PDF and HTML docs and 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-2.0.1 Migration Notes for PyTables 1.x users ====================================== If you are a user of PyTables 1.x, probably it is worth for you to look at ``MIGRATING_TO_2.x.txt`` file where you will find directions on how to migrate your existing PyTables 1.x apps to the 2.x versions. You can find an HTML version of this document at http://www.pytables.org/moin/ReleaseNotes/Migrating_To_2.x Resources ========= Go to the PyTables web site for more details: http://www.pytables.org About the HDF5 library: http://hdfgroup.org/HDF5/ About NumPy: http://numpy.scipy.org/ To know more about the company behind the development of PyTables, see: http://www.carabos.com/ 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. 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 have. ---- **Enjoy data!** -- The PyTables Team