Antonio Valentino
2014-03-25 22:48:42 UTC
===========================
Announcing PyTables 3.1.1
===========================
We are happy to announce PyTables 3.1.1.
This is a bug-fix release that addresses a critical bug that make
PyTables unusable on some platforms.
What's new
==========
- Fixed a critical bug that caused an exception at import time.
The error was triggered when a bug in long-double detection is
detected in the HDF5 library (see :issue:`275`) and numpy_ does not
expose `float96` or `float128`. Closes :issue:`344`.
- The internal Blosc_ library has been updated to version 1.3.5.
This fixes a false buffer overrun condition that made c-blosc to fail,
even if the problem was not real.
As always, a large amount of bugs have been addressed and squashed as well.
In case you want to know more in detail what has changed in this
version, please refer to: http://pytables.github.io/release_notes.html
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/3.1.1
For an online version of the manual, visit:
http://pytables.github.io/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
Announcing PyTables 3.1.1
===========================
We are happy to announce PyTables 3.1.1.
This is a bug-fix release that addresses a critical bug that make
PyTables unusable on some platforms.
What's new
==========
- Fixed a critical bug that caused an exception at import time.
The error was triggered when a bug in long-double detection is
detected in the HDF5 library (see :issue:`275`) and numpy_ does not
expose `float96` or `float128`. Closes :issue:`344`.
- The internal Blosc_ library has been updated to version 1.3.5.
This fixes a false buffer overrun condition that made c-blosc to fail,
even if the problem was not real.
As always, a large amount of bugs have been addressed and squashed as well.
In case you want to know more in detail what has changed in this
version, please refer to: http://pytables.github.io/release_notes.html
You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/3.1.1
For an online version of the manual, visit:
http://pytables.github.io/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