Re: [Pytables-users] [Pytables-announce] ANN: PyTables 2.4.0 beta1

[Francesc A. <fa...@gm...>]

Hey Antonio, this looks great.

BTW, which is the status of the 3.x support?  I vaguely remember you 
asking me for some help on this, but I don't remember well. Not that I 
have a lot of time to spend on it, but perhaps I can use some hours in 
the next days.

Thanks,

Francesc

On 7/7/12 8:47 PM, Antonio Valentino wrote:
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> ===========================
> Announcing PyTables 2.4.0b1
> ===========================
>
> We are happy to announce PyTables 2.4.0b1.
>
> This is an incremental release which includes many changes to prepare
> for future Python 3 support.
>
>
> What's new
> ==========
>
> This release includes support for the float16 data type and read-only
> support for variable length string attributes.
>
> The handling of HDF5 errors has been improved.  The user will no
> longer see HDF5 error stacks dumped to the console.  All HDF5 error
> messages are trapped and attached to a proper Python exception.
>
> Now PyTables only supports HDF5 v1.8.4+. All the code has been updated
> to the new HDF5 API.  Supporting only HDF5 1.8 series is beneficial
> for future development.
>
> 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.com/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/2.4.0b1
>
> For an online version of the manual, visit:
> http://pytables.github.com/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 (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
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-- 
Francesc Alted