Whoo hoo! Thanks for all of your hard work Antonio!
PyTables users, we'd really appreciate it if you could try out this beta
release, run the test suite:
$ python -c "import tables as tb; tb.test()"
And let us know if there are any issues. Additionally, if you are feeling
brave, any help you can give closing out the last remaining issues [1]
would be great!
Be Well
Anthony
1. https://github.com/PyTables/PyTables/issues?milestone=4&state=open
On Sat, Apr 27, 2013 at 6:51 AM, Antonio Valentino <
antonio.valent...@tiscali.it> wrote:
> =============================
> Announcing PyTables 3.0.0b1
> =============================
>
> We are happy to announce PyTables 3.0.0b1.
>
> PyTables 3.0.0b1 comes after about 5 years from the last major release
> (2.0) and 7 months since the last stable release (2.4.0).
>
> This is new major release and an important milestone for the PyTables
> project since it provides the long waited support for Python 3.x that is
> being around for already 4 years now.
>
> Almost all the main numeric/scientific packages for python already
> support Python 3 so we are very happy that now also PyTables can provide
> this important feature.
>
>
> What's new
> ==========
>
> A short summary of main new features:
>
> - Since this release PyTables provides full support to Python 3
> - The entire code base is now more compliant with coding style
> guidelines describe in the PEP8.
> - Basic support for HDF5 drivers. Now it is possible to open/create an
> HDF5 file using one of the SEC2, DIRECT, LOG, WINDOWS, STDIO or CORE
> drivers.
> - Basic support for in-memory image files. An HDF5 file can be set
> from or copied into a memory buffer.
> - Implemented methods to get/set the user block size in a HDF5 file.
> - All read methods now have an optional *out* argument that allows to
> pass a pre-allocated array to store data.
> - Added support for the floating point data types with extended
> precision (Float96, Float128, Complex192 and Complex256).
>
> Please refer to the RELEASE_NOTES document for a more detailed list of
> changes in this release.
>
> As always, a large amount of bugs have been addressed and squashed as well.
>
> In case you want to know more in detail what has changed in this
> version, please refer to:
> http://pytables.github.io/release_notes.html
>
> You can download a source package with generated PDF and HTML docs, as
> well as binaries for Windows, from:
> http://sourceforge.net/projects/pytables/files/pytables/3.0.0b1
>
> For an online version of the manual, visit:
> http://pytables.github.io/usersguide/index.html
>
>
> What it is?
> ===========
>
> 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. PyTables includes OPSI, a new indexing technology,
> allowing to perform data lookups in tables exceeding 10 gigarows
> (10**10 rows) in less than a tenth of a second.
>
>
> 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 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
>
>
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