Release 2.2.0

• New bytedelta filter. We have blogged about this: https://www.blosc.org/posts/bytedelta-enhance-compression-toolset/. See the examples/ndarray/bytedelta_filter.py for a sample script. We also have a short video on how bytedelta works: https://www.youtube.com/watch?v=5OXs7w2x6nw

• The compression defaults are changed to get a better balance between compression ratio, compression speed and decompression speed. The new defaults are:

  • cparams.typesize = 8
  • cparams.clevel = 1
  • cparams.compcode = Codec.ZSTD
  • filters = [Filter.SHUFFLE]
  • splitmode = SplitMode.ALWAYS_SPLIT

  These changes are based on the experiments performed in the blog post above.

• dtype.itemsize will have preference over typesize in cparams (as it was documented).

• blosc2.compressor_list(plugins=False) do not list codec plugins by default now. If you want to list plugins too, you need to pass plugins=True.

• Internal C-Blosc2 updated to latest version (2.8.0).

Release 2.1.1

Changes from 2.0.0 to 2.1.1

• New NDArray class for handling multidimensional arrays using compression. It includes:

  • Data type handling (fully compatible with NumPy)
  • Double partitioning

  See examples at: https://github.com/Blosc/python-blosc2/tree/main/examples/ndarray
  NDarray docs at: https://www.blosc.org/python-blosc2/reference/ndarray_api.html
  Explanatory video on why double partitioning: https://youtu.be/LvP9zxMGBng
  Also, see our blog on C-Blosc2 NDim counterpart: https://www.blosc.org/posts/blosc2-ndim-intro/

• Internal C-Blosc2 bumped to latest 2.7.1 version.

Release 2.0.0

Changes from 0.6.6 to 2.0.0

• Add support for user-defined filters and codecs. See our blog at: https://www.blosc.org/posts/python-blosc2-pipeline/

• API has been frozen.

Release 0.6.6

Changes from 0.6.5 to 0.6.6

• Add arm64 wheels for macosx (this time for real).

Release 0.6.5

Changes from 0.6.4 to 0.6.5

• Add arm64 wheels for macosx.

Release 0.6.4

Changes from 0.6.3 to 0.6.4

• Add arm64 wheels and remove musl builds (NumPy not having them makes the build process too long).

Release 2.6.3

Changes from 0.6.2 to 0.6.3

• Use oldest-supported-numpy for maximum compatibility.

Release 0.6.2

Changes from 0.6.1 to 0.6.2

• Updated C-Blosc2 to 2.6.0.

Release 0.6.1

Changes from 0.5.2 to 0.6.1

• Support for Python prefilters and postfilters. With this, you can pre-process or post-process data in super-chunks automatically. This machinery is handled internally by C-Blosc2, so it is very efficient (although it cannot work in multi-thread mode due to the GIL). See the examples/ directory for different ways of using this.

• Support for fillers. This is a specialization of a prefilter, and it allows to use Python functions to create new super-chunks from different kind of inputs (NumPy, SChunk instances, scalars), allowing computations among them and getting the result automatically compressed. See a sample script in the examples/ directory.

• Lots of small improvements in the style, consistency and other glitches in the code. Thanks to Dimitri Papadopoulos for hist attention to detail.

• No need to compile C-Blosc2 tests, benchs or fuzzers. Compilation time is much shorter now.

• Added cratio, nbytes and cbytes properties to SChunk instances.

• Added setters for dparams and cparams attributes in SChunk.

Release 0.5.2

Changes from 0.5.1 to 0.5.2

• Honor nested cparams properties in kwargs. E.g. you can do:

blosc2.save_tensor(a, "test.bl2", mode="w",
                   filters=[blosc2.Filter.TRUNC_PREC, blosc2.Filter.BITSHUFFLE],
                   filters_meta=[13, 0],
                   codec=blosc2.Codec.LZ4,
                   clevel=9)

without a need to build a proper cparams dict first.

• C-Blosc2 upgraded to 2.4.3. It should improve cratio for BloscLZ in combination with bitshuffle.

• Prefer pack_tensor/save_tensor in benchs and examples