Announcing Python-Blosc2 2.0.0
==============================
This provides user-defined filters and codecs.
It is a major release, meaning that the API will be frozen.
This is a well tested library and it is ready for being used
in production scenarios.
Now you can define your own filters and codecs for the Blosc2 compression
pipeline. They are very easy to use because they conveniently wrap input
and output data as NumPy arrays. So, you can start experimenting with
different filter/compression algorithms straight from Python. You can
even come with a library of such filters/codecs that can be used in
all your data pipeline processing. Welcome to compression made easy!
We have blogged about the features in this new release:
https://www.blosc.org/posts/python-blosc2-pipeline/See also some notebooks on how to use them:
https://github.com/Blosc/python-blosc2/blob/main/examples/ucodecs-ufilters.ipynbhttps://github.com/Blosc/python-blosc2/blob/main/examples/prefilters.ipynbhttps://github.com/Blosc/python-blosc2/blob/main/examples/postfilters.ipynbFor more info, you can have a look at the release notes in:
https://github.com/Blosc/python-blosc2/releasesMore docs and examples are available in the documentation site:
https://www.blosc.org/python-blosc2/python-blosc2.htmlChanges from python-blosc to python-blosc2
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* The functions `compress_ptr` and `decompress_ptr` are replaced by pack and unpack since Pickle
protocol 5 comes with out-of-band data.
* The function `pack_array` is equivalent to `pack`, which accepts any object with attributes `itemsize`
and `size`.
* On the other hand, the function `unpack` doesn't return a numpy array whereas the `unpack_array`
builds that array.
* The `blosc.NOSHUFFLE` is replaced by the `blosc2.NOFILTER`, but for backward
compatibility `blosc2.NOSHUFFLE` still exists.
* A bytearray or NumPy object can be passed to the `blosc2.decompress` function to store the
decompressed data.
## What is it?
Blosc is an open source high performance compressor optimized for binary data
(i.e. floating point numbers, integers and booleans). It has
been designed to transmit data to the processor cache faster
than the traditional, non-compressed, direct memory fetch approach
via a memcpy() OS call. Blosc main goal is not just to reduce the
size of large datasets
on-disk or in-memory, but also to accelerate memory-bound computations.
python-blosc2 is a pythonic wrapper for the C-Blosc2 library.
## Sources repository
The sources and documentation are managed through github services at:
https://github.com/Blosc/python-blosc2c-blosc2 is distributed using the BSD license, see
[LICENSE.txt](
https://github.com/Blosc/python-blosc2/blob/main/LICENSE.txt)
for details.
## Mailing list
There is an official Blosc mailing list where discussions about
c-blosc2 are welcome:
bl...@googlegroups.comhttps://groups.google.es/group/blosc## Tweeter feed
Please follow @Blosc2 to get informed about the latest developments.
Enjoy Data!
- The Blosc Development Team