Announcing python-blosc 1.9.1
What is new?
We disabled the attempt to include support for SSE2 and AVX2 on
non-Intel platforms, allowing the build on such platforms (see #244).
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?
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 contains 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 datafiles 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.
The sources and documentation are managed through github services at: