···
===========================
Announcing PyTables 3.2.0
===========================
We are happy to announce PyTables 3.2.0.
IMPORTANT NOTICE:
If you are a user of PyTables, it needs your help to keep going. Please
read the next thread as it contains important information about the
future (or the lack of it) of the project:
https://groups.google.com/forum/#!topic/pytables-users/yY2aUa4H7W4
Thanks!
What’s new
==========
This is a major release of PyTables and it is the result of more than a
year of accumulated patches, but most specially it fixes a couple of
nasty problem with indexed queries not returning the correct results in
some scenarios. There are many usablity and performance improvements
too.
In case you want to know more in detail what has changed in this
version, please refer to: http://www.pytables.org/release_notes.html
You can install it via pip or download a source package with generated
PDF and HTML docs from:
http://sourceforge.net/projects/pytables/files/pytables/3.2.0
For an online version of the manual, visit:
http://www.pytables.org/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 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 Developers