ANN: PyTables 2.0.4 available

Francesc Alted falted at
Mon Jul 7 10:30:56 CEST 2008

 Announcing PyTables 2.0.4

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.

After some months without new versions (I have been busy for a while
doing things not related with PyTables, unfortunately), I'm happy to
announce the availability of PyTables 2.0.4.  It fixes some important
issues, and now it is possible to use table selections in threaded
environments.  Also, ``EArray.truncate(0)`` can be used so that you can
completely void existing EArrays (only enabled if you have a recent
version, i.e. >= 1.8.0, of the HDF5 library installed).  Besides, the
compatibility with native HDF5 files has been improved too.  Finally, 
the usage of recent versions of NumPy (1.1) and HDF5 (1.8.1) has been 
tested and, fortunately, they work just fine.

In case you want to know more in detail what has changed in this
version, have a look at ``RELEASE_NOTES.txt``.  Find the HTML version
for this document at:

You can download a source package of the version 2.0.4 with
generated PDF and HTML docs and binaries for Windows from

For an on-line version of the manual, visit:

*Important note for PyTables Pro users*: due to lack of resources, I'll 
not be delivering a MacOSX binary version of Pro for the time being 
(this is pretty easy to compile, though).  However, I'll continue 
offering the all-in-one binary for Windows (32-bit).

Migration Notes for PyTables 1.x users

If you are a user of PyTables 1.x, probably it is worth for you to look
at ``MIGRATING_TO_2.x.txt`` file where you will find directions on how
to migrate your existing PyTables 1.x apps to the 2.x versions.  You can
find an HTML version of this document at


Go to the PyTables web site for more details:

About the HDF5 library:

About NumPy:


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.  Many
thanks also to SourceForge who have helped to make and distribute this
package!  And last, but not least thanks a lot to the HDF5 and NumPy
(and numarray!) makers. Without them, PyTables simply would not exist.

Share your experience

Let me know of any bugs, suggestions, gripes, kudos, etc. you may


  **Enjoy your data!**

Francesc Alted

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