Discussion:
[pytables-users] ANN: PyTables 3.2.0 release candidate 1 is out
Francesc Alted
2015-04-21 13:04:08 UTC
Permalink
===========================
Announcing PyTables 3.2.0rc1
===========================

We are happy to announce PyTables 3.2.0rc1.

*******************************
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 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 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://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/3.2.0rc1

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
--
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Christoph Gohlke
2015-04-21 20:57:17 UTC
Permalink
Post by Francesc Alted
===========================
Announcing PyTables 3.2.0rc1
===========================
We are happy to announce PyTables 3.2.0rc1.
*******************************
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
https://groups.google.com/forum/#!topic/pytables-users/yY2aUa4H7W4
<https://groups.google.com/forum/#%21topic/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 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://pytables.github.io/release_notes.html
You can download a source package with generated PDF and HTML docs, as
http://sourceforge.net/projects/pytables/files/pytables/3.2.0rc1
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
Hi Francesc,

on Windows I sometimes, not always, get a segfault during
test_basics.ThreadingTestCase. The crash is in the hdf5.dll during the
H5Pcreate function call at
<https://github.com/PyTables/PyTables/blob/release-3.2.0/tables/hdf5extension.pyx#L400>.
If there is no segfault, all tests pass. So far I could reproduce this
on Python 2.x, 32 and 64 bit, but not on Python 3.x. Could this be
related to <https://github.com/PyTables/PyTables/issues/359>?

-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
PyTables version: 3.2.0rc1
HDF5 version: 1.8.14
NumPy version: 1.9.2
Numexpr version: 2.4.1 (using VML/MKL 11.1.4)
Zlib version: 1.2.8 (in Python interpreter)
LZO version: 2.06 (Aug 12 2011)
BZIP2 version: 1.0.6 (6-Sept-2010)
Blosc version: 1.4.1 (2014-07-08)
Blosc compressors: blosclz (1.0.2), lz4 (1.2.0), lz4hc (1.2.0), snappy
(1.1.1), zlib (1.2.8)
Cython version: 0.22
Python version: 2.7.9 (default, Dec 10 2014, 12:24:55) [MSC v.1500
32 bit (Intel)]
Platform: Windows-8-6.2.9200
Byte-ordering: little
Detected cores: 8
Default encoding: ascii
Default FS encoding: mbcs
Default locale: (en_US, cp1252)
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
<snip>
test (tables.tests.test_basics.ThreadingTestCase) ... <segfault>

Traceback:

hdf5.dll!5f203778()
[Frames below may be incorrect and/or missing, no symbols loaded
for hdf5.dll]
hdf5.dll!5f20386d()
hdf5.dll!5f209f0d()
hdf5.dll!5f2ddb64()
hdf5.dll!5f2ddc98()
hdf5.dll!5f2cdf48()
Post by Francesc Alted
hdf5extension.pyd!__pyx_pf_6tables_13hdf5extension_4File__g_new(__pyx_obj_6tables_13hdf5extension_File * __pyx_v_self=0x0749a330, _object * __pyx_v_name=0x02943ac8, _object * __pyx_v_pymode=0x01cd42f0, _object * __pyx_v_params=0x047be390) Line 4412 + 0x15 bytes C
hdf5extension.pyd!__pyx_pw_6tables_13hdf5extension_4File_1_g_new(_object
* __pyx_v_self=0x0749a330, _object * __pyx_args=0x074b7738, _object *
__pyx_kwds=0x04be5810) Line 3286 + 0x15 bytes C
python27.dll!PyCFunction_Call(_object * func=0x074983c8, _object *
arg=0x074b7738, _object * kw=0x04be5810) Line 85 + 0xd bytes C
python27.dll!ext_do_call(_object * func=0x074983c8, _object * * *
pp_stack=0x00000000, int flags=2, int na=2, int nk=0) Line 4345 C
<snip>

--
Christoph
--
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