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Announcing python-blosc 1.9.2
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What is new?
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This is a maintenance release to better support recent versions of Python
(3.8 and 3.9). Also, and due to the evolution of modern CPUs,
the number of default threads has been raised to 8 (from 4).
Finally, zero-copy decompression is now supported by allowing bytes-like
input. Thanks to Lehman Garrison.
For more info, you can have a look at the release notes in:
More docs and examples are available in the documentation site:
What is it?
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for binary data. 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 works well for compressing
numerical arrays that contain data with relatively low entropy, like
sparse data, time series, grids with regular-spaced values, etc.
the Blosc compression library, with added functions (`compress_ptr()`
and `pack_array()`) for efficiently compressing NumPy arrays, minimizing
the number of memory copies during the process. python-blosc can be
used to compress in-memory data buffers for transmission to other
machines, persistence or just as a compressed cache.
There is also a handy tool built on top of python-blosc called Bloscpack
interface that allows you to compress large binary data files on-disk.
It also comes with a Python API that has built-in support for
serializing and deserializing Numpy arrays both on-disk and in-memory at
speeds that are competitive with regular Pickle/cPickle machinery.
Sources repository
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The sources and documentation are managed through github services at:
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**Enjoy data!**
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The Blosc Development Team