Although my plans were to release PyTables 2.1 final this week, the
relatively high number of fixes done since 2.1rc1 made me to decide
releasing a new candidate before 2.1. Please test it out and report
any problems that you may encounter.
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:
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
Finally, and for the first time, an evaluation version for PyTables Pro
has been made available in:
For an on-line version of the manual, visit:
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
-- The PyTables Team