Release 0.5.1

Changes from 0.5.0 to 0.5.1

• Remove the testing of packing PyTorch or TensorFlow objects during wheels build.

Release 0.5.0

Changes from 0.4.1 to 0.5.0

• New pack_tensor, unpack_tensor, save_tensor and load_tensor functions for serializing/deserializing PyTorch and TensorFlow tensor objects. They also understand NumPy arrays, so these are the new recommended ones for serialization.

• pack_array2 do not modify the value of a possible cparams parameter anymore.

• The pack_array2 / save_array have changed the serialization format to follow the new standard introduced in pack_tensor. In the future pack_array2 / save_array will probably be deprecated, so please change to pack_tensor / save_tensor as soon as you can.

• The new 'standard' for serialization relies on using the __pack_tensor__ attribute as a vlmeta (variable length) metalayer.

Release 0.4.1

Changes from 0.4.0 to 0.4.1

• Add msgpack as a runtime requirement

Release 0.4.0

Changes from 0.3.2 to 0.4.0

• New pack_array2() and unpack_array2() functions for packing NumPy arrays. Contrarily to pack_array() and unpack_array() counterparts, the new ones allow for compressing arrays larger than 2 GB in size.

• New Scunk.to_cframe() and blosc2.from_cframe() methods for serializing/deserialzing SChunk instances.

• New Schunk.get_slice(), SChunk.__getitem__() and SChunk.__setitem__() methods for getting/setting slices from/to SChunk instances.

• The compcode parameter has been renamed to codec. A NameError exception will be raised when using the old name. Please update your code when you see this exception.

• More doc restructurings. Hopefully, they are more pleasant to read now :-)

Release 0.3.2

Changes from 0.3.1 to 0.3.2

• Several leaks fixed. Thanks to Christoph Gohlke.

• Internal C-Blosc2 updated to 2.3.1

Release 0.3.0

Changes from 0.2.0 to 0.3.0

• Added a new blosc2.open(urlpath, mode) function to be able to open persisted super-chunks.

• Added a new tutorial in notebook format (examples/tutorial-basics.ipynb) about the basics of python-blosc2.

• Internal C-Blosc2 updated to 2.2.0

Release 0.2.0

Release notes

Changes from python-blosc2 0.1.10 to python-blosc2 0.2.0

• Internal C-Blosc updated to 2.0.4.

New super-chunk implementation

• New SChunk class that allows to create super-chunks.
  This includes the capability of storing data in 4
  different ways (sparse/contiguous and in memory/on-disk),
  as well as storing variable length metalayers.

• Also, during the contruction of a SChunk instance,
  an arbitrarily large data buffer can be given so that it is
  automatically split in chunks and those are appended to the
  SChunk.

• See examples/schunk.py and examples/vlmeta.py for some examples.

• Documentation of the new API is here: https://python-blosc2.readthedocs.io

This release is the result of a grant offered by
the Python Software Foundation to Marta Iborra.
A blog entry was written describing the difficulties and relevant
aspects learned during the work:
https://www.blosc.org/posts/python-blosc2-initial-release/

Release 0.1.10

Changes from python-blosc2 0.1.9 to python-blosc2 0.1.10

• Release with C-Blosc 2.0.2 sources and binaries.

Release 0.1.9

Changes from python-blosc2 0.1.8 to python-blosc2 0.1.9

• Release with C-Blosc 2.0.1 sources and binaries.

Release 0.1.7

Changes from python-blosc2 0.1.5 to python-blosc2 0.1.7

• Headers and binaries for the C-Blosc2 library are starting
  to being distributed inside wheels.

• Internal C-Blosc2 submodule updated to 2.0.0-rc2.

• Repeating measurements 4 times in benchs so as to get more
  consistent figures.