Hi List, A new version of PyTables has been released. The reason of this release is to provide improved support for native HDF5 files, so that ViTables, the soon-to-be-released teammate of PyTables, can recognize a broader range of HDF5 files. Also, a problem with row iterators and nested tables has been fixed.
See the official announcement below: =========================== 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. Changes more in depth ===================== 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. What it is ========== **PyTables** is a package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data (with support for full 64-bit file addressing). It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code, makes it a very easy-to-use tool for high performance data storage and retrieval. PyTables runs on top of the HDF5 library and numarray (Numeric is also supported and NumPy support is coming along) package for achieving maximum throughput and convenient use. Besides, PyTables I/O for table objects is buffered, implemented in C and carefully tuned so that you can reach much better performance with PyTables than with your own home-grown wrappings to the HDF5 library. PyTables sports indexing capabilities as well, allowing doing selections in tables exceeding one billion of rows in just seconds. Platforms ========= This version has been extensively checked on quite a few platforms, like Linux on Intel32 (Pentium), Win on Intel32 (Pentium), Linux on Intel64 (Itanium2), FreeBSD on AMD64 (Opteron), Linux on PowerPC and MacOSX on PowerPC. For other platforms, chances are that the code can be easily compiled and run without further issues. Please, contact us in case you are experiencing problems. Resources ========= Go to the PyTables web site for more details: http://pytables.sourceforge.net/ About the HDF5 library: http://hdf.ncsa.uiuc.edu/HDF5/ About numarray: http://www.stsci.edu/resources/software_hardware/numarray To know more about the company behind the PyTables development, see: http://www.carabos.com/ Acknowledgments =============== Thanks to various the users who provided feature improvements, patches, bug reports, support and suggestions. See THANKS file in distribution package for a (incomplete) list of contributors. Many thanks also to SourceForge who have helped to make and distribute this package! And last but not least, a big thank you to THG (http://www.hdfgroup.org/) for sponsoring many of the new features recently introduced in PyTables. Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. ---- **Enjoy data!** -- The PyTables Team -- >0,0< Francesc Altet http://www.carabos.com/ V V Cárabos Coop. V. Enjoy Data "-" ------------------------------------------------------- This SF.Net email is sponsored by xPML, a groundbreaking scripting language that extends applications into web and mobile media. Attend the live webcast and join the prime developer group breaking into this new coding territory! http://sel.as-us.falkag.net/sel?cmd=lnk&kid0944&bid$1720&dat1642 _______________________________________________ Pytables-users mailing list Pytables-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/pytables-users
