Release 2.6.0

Changes from 2.5.1 to 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).

• Updated to latest C-Blosc2 2.14.0.