=========================== Announcing PyTables 2.1rc2 ===========================
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 the second release candidate for 2.1, and I have decided to release it because many bugs have been fixed and some enhancements have been added since 2.1rc1. For details, see the ``RELEASE_NOTES.txt`` at: http://www.pytables.org/moin/ReleaseNotes/Release_2.1rc2
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 UG) and support for multidimensional atoms in EArray/CArray objects.
Regarding the Pro edition, four different kind 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).
You can download a source package of the version 2.1rc2 with generated PDF and HTML docs and binaries for Windows from http://www.pytables.org/download/preliminary
For an on-line version of the manual, visit: http://www.pytables.org/docs/manual-2.1rc2
Go to the PyTables web site for more details:
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. 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.
-- The PyTables Team