- Update to 2.6.2
* Protection when platforms have just one CPU. This caused the
internal number of threads to be 0, producing a division by zero.
* Updated to latest C-Blosc2 2.14.3.
- Release 2.6.0
* [EXP] New evaluation engine (based on numexpr) for NDArray
instances. Now, you can evaluate expressions like a + b + 1
where a and b are NDArray instances. This is a powerful feature
that allows for efficient computations on compressed data. See
this example to see how this works. Thanks to @omaech for her
help in the pow function.
* As a consequence of the above, there are many new functions to
operate with NDArray instances. See the function section in
NDArray API for more information.
* Support for NumPy 2.0.0 is here! Now, the wheels are built with
NumPy 2.0.0rc1. Please tell us in case you see any issues with
this new version.
* Add **kwargs to load_tensor() function. This allows to pass
additional parameters to the deserialization function. Thanks
to @jasam-sheja.
* Fix vlmeta.to_dict() not honoring tuple encoding. Thanks to
@ivilata.
* Check that chunks/blocks computation does not allow a 0 in
blocks. Thanks to @ivilata.
* Many improvements in ruff rules and others. Thanks to
@DimitriPapadopoulos.
* Remove printing large arrays in notebooks (they use too much
RAM in recent versions of Jupyter notebook). (forwarded request 1170319 from bnavigator)