Announcing PyTables 3.5.1
We are happy to announce PyTables 3.5.1.
This is a minor version of PyTables. The main feature added is that
the padding in original HDF5 files is respected when copied via PyTables.
Also, when the `description` is a NumPy struct array with padding, this
is honored now. The previous behaviour (i.e. getting rid of paddings) can
be replicated by passing the new `allow_padding` parameter when opening
Also, support for AVX2 has been added on Windows.
In case you want to know more in detail what has changed in this
You can install it via pip or download a source package with generated
PDF and HTML docs from:
For an online version of the manual, visit:
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.
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.
-- The PyTables Developers