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Groups > comp.lang.python.announce > #2998
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| From | Valentin Haenel <valentin@haenel.co> |
| Newsgroups | comp.lang.python.announce |
| Subject | [ANN] python-blosc 1.6.1 |
| Date | Sun, 21 Oct 2018 19:29:39 +0200 |
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============================= Announcing python-blosc 1.6.1 ============================= What is new? ============ C-Blosc has been updated to 1.14.3. Additionally there have been a number of improvments such as not compiling snappy by default and the implementation of the `get_blocksize()` function. For more info, you can have a look at the release notes in: https://github.com/Blosc/python-blosc/blob/master/RELEASE_NOTES.rst More docs and examples are available in the documentation site: http://python-blosc.blosc.org What is it? =========== Blosc (http://www.blosc.org) is a high performance compressor optimized 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. python-blosc (http://python-blosc.blosc.org/) is the Python wrapper for 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 (https://github.com/Blosc/bloscpack). It features a commmand line 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. Sources repository ================== The sources and documentation are managed through github services at: http://github.com/Blosc/python-blosc ---- **Enjoy data!**
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[ANN] python-blosc 1.6.1 Valentin Haenel <valentin@haenel.co> - 2018-10-21 19:29 +0200
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