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Major changes in 2.4:
- Improved HDF5 error logging management.
- Added support for the float16 data type.
- Leaf nodes now have attributes for retrieving the size of data in memory
and on disk.
- Configurable maximum number of threads for Blosc and Numexpr.
- ndim (read-only) attribute added to Leaf, Atom and Col objects.
- Added read support for variable length string attributes.
Full changelog for 2.4.0, see:
http://pytables.github.io/release-notes/RELEASE_NOTES_v2.4.x.html
Major changes in 2.3:
- Integrated functionality from PyTablesPro (re-licensed under a BSD license).
- OPSI is a powerful and innovative indexing engine allowing PyTables
to perform fast queries on arbitrarily large tables.
- A fine-tuned LRU cache for both metadata (nodes) and regular data.
Full changelog for 2.3.x, see:
http://pytables.github.io/release-notes/RELEASE_NOTES_v2.3.x.html
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changes:
-misc fixes and feature additions
-space saving / time improvements
-needs py-cython-0.13
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changes:
-new compressor called Blosc (speed-up)
-A new `tables.Expr` module (based on Numexpr) that allows to do
persistent, on-disk computations on many algebraic operations.
-Support for HDF5 hard links, soft links and automatic external links
-Suport for 'fancy' indexing
-bugfixes
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this is a major update, too much to list here
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changes:
-almost complete support for numpy objects
-better hdf5 support
-bugfixes (one important about file flushing)
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This is a major version release.
changes include:
-Undo/Redo
-support for objects (and indexes!) with more than 2**31 rows
-new datatypes
-improved HDF5 support
-compression support
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PyTables 0.9.1:
This release is mainly a maintenance version. In it, some bugs has been
fixed and a few improvements has been made. One important thing is that
chunk sizes in EArrays has been re-tuned to get much better performance
and compression rations. Besides, it has been tested against the latest
Python 2.4 and all test units seems to pass fine.
PyTables 0.9:
In this release you will find a series of quite exciting new features,
the most important being new indexing capabilities, in-kernel selections,
support for complex datatypes and the possibility to modify values in both
tables and arrays (yeah, finally :).
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