Release 0.5.1

Changes from 0.5.0 to 0.5.1

• Fixes a bug in 1-dim arrays whose typesize is larger than 1.

Release 0.5.0

Changes from 0.4.1 to 0.5.0

• Workaround for recognizing 1-dim arrays in HDF5. For some reason,
  HDF5-Blosc2 does not add the dim info in cd_values when ndim == 1.
  This adds the dim info manually.

• Upload/download artifact in CI bumped to v4.

• Development status has been bumped to 4 - Beta.

b2h5py v0.4.1

This release fixes the lack of optimization support when iterating over b2h5py.B2Dataset instances (thus fixing issue #2). The readme has been updated and related tests have been adapted.

b2h5py v0.4.0

This release adds a new way to use Blosc2 optimized slicing explicitly on a single dataset. You may use the b2h5py.B2Dataset class to wrap the original h5py.Dataset instance into a new instance where slicing operations may leverage the optimizations. Other operations are transparently forwarded to the wrapped instance. Check the readme and examples for more information.

The feature was initially contributed by Thomas Vincent as PR #1. Thank you!

b2h5py v0.3.0

This release changes the package interface to require explicitly enabling optimizations and use more friendly names.

Functions for doing, undoing and checking patching are now called b2h5py.enable_fast_slicing(), b2h5py.disable_fast_slicing() and b2h5py.is_fast_slicing_enabled(), while the context manager is called b2h5py.fast_slicing(). Please see the updated and fixed example script.

Importing b2h5py no longer enables optimizations until b2h5py.enable_fast_slicing() or b2h5py.fast_slicing() are used. For the previous implicit behaviour you may just import the new b2h5py.auto module.

Finally, the caching of the property that determines whether a dataset is amenable for Blosc2 optimized slicing has been fixed.

b2h5py v0.2.0

This release adds the context manager b2h5py.patching_dataset_class() that patches the h5py.Dataset class on entry and unpatches it on leaving (if it was not already patched). Documentation includes mentions to using API functions to patch/unpatch the class, and help(b2h5py) now shows these functions.

Testing is enhanced by automation using GitHub Actions, and support for running h5py tests with a patched class.

b2h5py now requires at least Python v3.3.

b2h5py v0.1.1

This release only includes minor fixes to allow unit tests to check whether optimizations are actually being applied when they should.

b2h5py v0.1.0

Initial alpha release of b2h5py.