Announcing PyTables 1.2.3
I'm glad to announce a new release of PyTables. This is a maintenance version. Several bugs and small improvements (mainly related with improved support of native HDF5 files) have been added.
Go to the PyTables web site for downloading the beast: http://pytables.sourceforge.net/
or keep reading for more info about the new features and bugs fixed in this version.
Improvements
- One can read now native HDF5 attributes of type string with padded nulls or spaces (fortran style), instead of only the null terminated ones (C style). However, these types are not yet well supported in datasets.
Bug fixes
- Fixed problem in Table.whereAppend() with nested tables. The method copies the filtered rows into the destination table field by field. However, Row does not support nested fields, so one must iterate over the flattened column names.
- Solved a problem that appeared when reading attributes of unsupported classes. Now, when an attribute is of unsupported class (like BITFIELD, OPAQUE, COMPOUND, REFERENCE or VLEN), an explicative string is returned instead of raising a TypeError. This will allow a better support of native HDF5 files, while keeping the user informed that this specific attribute cannot be read.
Important notes for Windows users
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/5-165-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/5-165-win.ZIP
Also, note that support for the UCL compressor has not been added in the binary build of PyTables for Windows because of memory problems (perhaps some bad interaction between UCL and something else). Eventually, UCL support might be dropped in the future, so, please, refrain to create datasets compressed with it.
Enjoy!