[Pytables-users] ANN: PyTables 1.1.1 released

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

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=3D
 Announcing PyTables 1.1.1
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This is a maintenance release of PyTables. On it, several
optimizations and bug fixes has been made. As some of the fixed bugs
were quite important, it's strongly recommended for users to upgrade.

Go to the PyTables web site for downloading the beast:
http://pytables.sourceforge.net/

or keep reading for more info about the improvements and bugs fixed.


Changes more in depth
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Improvements:

=2D Optimized the opening of files with a large number of objects. Now,
  files with table objects opens a 50% faster, and file with arrays
  opens more than twice as fast (up to 2000 objects/s on a Pentium
  4@2GHz). Hence, a file with a combination of both kinds of objects,
  opens between a 50% and 100% faster than 1.1.

=2D Optimized the creation of NestedRecArray objects using NumArray
  objects as columns, so that filling a table with Table.append() method
  achieves the similar performance than PyTables pre-1.1 releases.

Bug fixes:

=2D ``Table.readCoordinates()`` now converts the coords parameter into ``In=
t64``
  indices automatically.

=2D Fixed a bug that prevented appending to tables (though Table.append)
  using a list of numarray objects.

=2D Solved a small bug for creating indexes for first time in tables and
  retain the filter properties for posterior use.

=2D Int32 attributes are dealed correctly in 64-bit platforms now.

=2D Correction for accepting lists of numarrays as input for NestedRecArray=
s.

=2D Fixed problem creating rank 1 multi-dimensional string columns in ``Tab=
le``
  objects.  Closes SF bug #1269023.

=2D Avoid errors when unpickling objects stored in attributes.  See the
  section ``AttributeSet`` in the reference chapter of the User's
  Manual for more information.  Closes SF bug #1254636.

=2D Assignment for *Array slices has been improved in order to solve some
  issues with shapes. Closes SF bug #1288792.

Known bugs:

=2D Classes inheriting from IsDescription subclasses do not
  inherit columns defined in the super-class. See SF bug #1207732 for
  more info.

=2D Time datatypes are non-portable between big-endian and little-endian
  architectures. This is ultimately a consequence of a HDF5
  limitation. See SF bug #1234709 for more info.

Backward-incompatible changes:

=2D None.


Important note for MacOSX users
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UCL compressor seems to work badly on MacOSX platforms. Until the
problem would be isolated and eventually solved, UCL will not be
compiled by default on MacOSX platforms, even if the installer finds
it in the system. However, if you still want to get UCL support on
MacOSX, you can use the --force-ucl flag in setup.py.


Important note for Python 2.4 and Windows users
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If you are willing to use PyTables with Python 2.4 in Windows
platforms, you will need to get the HDF5 library compiled for MSVC
7.1, aka .NET 2003.  It can be found at:
ftp://ftp.ncsa.uiuc.edu/HDF/HDF5/current/bin/windows/5-164-win-net.ZIP

Users of Python 2.3 on Windows will have to download the version of
HDF5 compiled with MSVC 6.0 available in:
ftp://ftp.ncsa.uiuc.edu/HDF/HDF5/current/bin/windows/5-164-win.ZIP


Share your experience
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Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.


=2D---

  **Enjoy data!**

  -- The PyTables Team

=2D-=20
>0,0<   Francesc Altet =A0 =A0 http://www.carabos.com/
V   V   C=E1rabos Coop. V. =A0=A0Enjoy Data
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