Re: [Pytables-users] ANN: PyTables 2.4.0 released

[Jacob B. <jac...@gm...>]

This is great! Much gratitude must go to you all for your hard work.

Thanks,
Jacob Bennett

On Fri, Jul 20, 2012 at 3:38 PM, Anthony Scopatz <sc...@gm...> wrote:

> Excellent!  Congrats Everybody!  Thanks a ton for all of your hard work.
>  I am going to send this out to numpy and scipy.
>
>
> On Fri, Jul 20, 2012 at 3:36 PM, Antonio Valentino <
> ant...@ti...> wrote:
>
>> ==========================
>> Announcing PyTables 2.4.0
>> ==========================
>>
>> We are happy to announce PyTables 2.4.0.
>>
>> 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.
>>
>> Documentation has been improved.
>>
>> 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/2.4.0
>>
>> 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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>
>
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-- 
Jacob Bennett
Massachusetts Institute of Technology
Department of Electrical Engineering and Computer Science
Class of 2014| ben...@mi...