python-tables

Edit Package python-tables

PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of
data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface
that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for
interactively save and retrieve large amounts of data.

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Filename Size Changed
_multibuild 0000000122 122 Bytes
python-tables.changes 0000039695 38.8 KB
python-tables.spec 0000004647 4.54 KB
tables-3.9.2.tar.gz 0004683437 4.47 MB
Revision 23 (latest revision is 27)
Ana Guerrero's avatar Ana Guerrero (anag+factory) accepted request 1130124 from Steve Kowalik's avatar Steve Kowalik (StevenK) (revision 23)
- Update to 3.9.2:
  * Minimum supported version for Python is 3.9 (see gh-1062).
  * New features
    + Apply optimized slice read to Blosc2-compressed CArray and EArray
    + Add basic API for column-level attributes as Col._v_col_attrs
  * Bugfixes
    + Fix the assembly of returned slice data in Blosc2 NDim optimized
      slice reads by using Blosc2’s b2nd_copy_buffer
    + Fix crash in Blosc2 optimized path with large tables
    + Fix compatibility with NumExpr v2.8.5
    + Fix ptrepack failures with external links
    + Replace stderr messages with Python warnings
    + Fix Cython slice indexing under Python 3.12
    + Fix unsafe temporary file creation in benchmark
  * Improvements
    + PyTables wheels now use a threadsafe build of the HDF5 library
    + Partial support for the future NumPy 2, with some tests still failing
    + Relax the reading of Blosc2 NDim to cope with datasets stored with
      other tools
    + Use H5Dchunk_iter (when available) to speed up walking over many chunks
      in a very large table, as well as with random reads
    + Improve setup.py (now using pyproject.toml as per PEP 518) and
      blosc2 discovery mechanism
    + Enable compatibility with Cython 3
    + Handle py-cpuinfo missing in some platforms
    + Avoid NumPy >= 1.25 deprecations, use numpy.all, numpy.any, etc. instead.
  * Other changes
    + Drop compatibility with the obsolete HDF5 1.8 API
    + Require python-blosc2 >= 2.3.0 or c-blosc2 >= 2.11.0
    + Assorted fixes to b2nd slicing optimization tips
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