Hi List, I'm happy to announce the first candidate release for PyTables 2.2 series. Among the most exciting improvements of this release is the support of threads in several parts of PyTables, namely Blosc and, optionally, Numexpr (which is out of the main distribution now and becomes a requisite).
In particular, I'm quite happy of how performs the recent multi-threaded implementation that undergone Blosc in 0.9. It uses a pool of threads technique in order to reduce thread management to a bare minimum. When all the tests would be finished, I expect to release Blosc 1.0 very soon now (hopefully before PyTables 2.2 final). These additions will allow you to make full use of the raw speed of nowadays multi-core processors in the parts of the code that can use parallelism, and are only the beginning of a series of future multi-core improvements inside PyTables. Here it is the official announcement: =========================== Announcing PyTables 2.2rc1 =========================== 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 first release candidate for PyTables 2.2. On it, Numexpr is not included anymore and is now a requisite and the Blosc compressor has been updated to 0.9, which comes with integrated support for threads. Also, Cython is used per default now to build Pyrex extensions. Finally, a handful of bugs have been addressed and squashed. 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_2.2rc1 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-2.2rc1 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!** -- Francesc Alted ------------------------------------------------------------------------------ _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
