Hi List, After completing the link support, I have taken the opportunity and, together with some other improvements (see below), I released PyTables 2.2b2. I think this is a good way to expose the new functionality to people. After that, I'm planning a third beta with Blosc support shortly followed by Python 2.2 final (in three months or so).
Please have a try at this beta and report your feedback. Enjoy and happy holidays! =========================== Announcing PyTables 2.2b2 =========================== 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 beta version of 2.2 release. The main addition is the support for links. All HDF5 kind of links are supported: hard, soft and external. Hard and soft links are similar to hard and symbolic links in regular UNIX filesystems, while external links are more like mounting external filesystems (in this case, HDF5 files) on top of existing ones. This allows for a considerable degree of flexibility when defining your object tree. See the new tutorial at: http://www.pytables.org/docs/manual-2.2b2/ch03.html#LinksTutorial Also, some other new features (like complete control of HDF5 chunk cache parameters and native compound types in attributes), bug fixes and a couple of (small) API changes happened. In case you want to know more in detail what has changed in this version, have a look at: http://www.pytables.org/moin/ReleaseNotes/Release_2.2b2 You can download a source package with generated PDF and HTML docs, as well as 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-2.2b2 Resources ========= About PyTables: http://www.pytables.org About the HDF5 library: http://hdfgroup.org/HDF5/ About NumPy: http://numpy.scipy.org/ 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. 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. ---- **Enjoy data!** -- The PyTables Team -- Francesc Alted ------------------------------------------------------------------------------ This SF.Net email is sponsored by the Verizon Developer Community Take advantage of Verizon's best-in-class app development support A streamlined, 14 day to market process makes app distribution fast and easy Join now and get one step closer to millions of Verizon customers http://p.sf.net/sfu/verizon-dev2dev _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
