=========================== Announcing PyTables 2.1.1 =========================== 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, so you should not expect API changes. Instead, a handful of bugs, like `File` not being subclassable, incorrectly retrieved default values for data types, a memory leak, and more, have been fixed. Besides, some enhancements have been implemented, like improved Unicode support for filenames, better handling of Unicode attributes, and the possibility to create very large data types exceeding 64 KB in size (with some limitations). Last but not least, this is the first PyTables version fully tested against Python 2.6. It is worth noting that binaries for Windows and Python 2.6 wears the newest HDF5 1.8.2 libraries (instead of the traditional HDF5 1.6.x) now. 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_2.1.1 You can download a source package with generated PDF and HTML docs, as well as 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-2.1.1 You may want to fetch an evaluation version for PyTables Pro from: http://www.pytables.org/download/evaluation Resources ========= About PyTables: http://www.pytables.org About the HDF5 library: http://www.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