- 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)

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