============
Python-Blosc

A Python wrapper for the extremely fast Blosc compression library

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:target: https://pypi.python.org/pypi/blosc
.. |anaconda| image:: https://anaconda.org/conda-forge/python-blosc/badges/version.svg
:target: https://anaconda.org/conda-forge/python-blosc
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:target: https://gitter.im/Blosc/c-blosc
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What it is

Note: There is a more modern version of this package called Python-Blosc2
which supports many more features and is more actively maintained. Visit it at:
https://github.com/Blosc/python-blosc2

Blosc (https://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 a Python package that wraps Blosc. python-blosc supports
Python 3.9 or higher versions.

Installing

Blosc is now offering Python wheels for the main OS (Win, Mac and Linux) and platforms. You can install binary packages from PyPi using pip:

.. code-block:: console

$ pip install blosc

Documentation

The Sphinx based documentation is here:

https://blosc.org/python-blosc/python-blosc.html

Also, some examples are available on python-blosc wiki page:

https://github.com/blosc/python-blosc/wiki

Lastly, here is the recording <https://www.youtube.com/watch?v=rilU44j_wUU&list=PLNkWzv63CorW83NY3U93gUar645jTXpJF&index=15>_
and the slides <https://www.blosc.org/docs/haenel-ep14-compress-me-stupid.pdf>_ from the talk
"Compress me stupid" at the EuroPython 2014.

Building

If you need more control, there are different ways to compile python-blosc,
depending if you want to link with an already installed Blosc library or not.

Installing via setuptools

python-blosc comes with the Blosc sources with it and can be built with:

.. code-block:: console

$ python -m pip install -r requirements-dev.txt
$ python setup.py build_ext --inplace

Any codec can be enabled (=1) or disabled (=0) on this build-path with the appropriate
OS environment variables INCLUDE_LZ4, INCLUDE_SNAPPY, INCLUDE_ZLIB, and
INCLUDE_ZSTD. By default all the codecs in Blosc are enabled except Snappy
(due to some issues with C++ with the gcc toolchain).

Compiler specific optimisations are automatically enabled by inspecting
the CPU flags building Blosc. They can be manually disabled by setting
the following environmental variables: DISABLE_BLOSC_SSE2 and
DISABLE_BLOSC_AVX2.

setuptools is limited to using the compiler specified in the environment
variable CC which on posix systems is usually gcc. This often causes
trouble with the Snappy codec, which is written in C++, and as a result Snappy
is no longer compiled by default. This problem is not known to affect MSVC or
clang. Snappy is considered optional in Blosc as its compression performance
is below that of the other codecs.

That's all. You can proceed with testing section now.

Compiling with an installed Blosc library

This approach uses pre-built, fully optimized versions of Blosc built via
CMake.

Go to https://github.com/Blosc/c-blosc/releases and download and install
the C-Blosc library. Then, you can tell python-blosc where is the
C-Blosc library in a couple of ways:

Using an environment variable:

.. code-block:: console

$ export USE_SYSTEM_BLOSC=1                 # or "set USE_SYSTEM_BLOSC=1" on Windows
$ export Blosc_ROOT=/usr/local/customprefix # If you installed Blosc into a custom location
$ python setup.py build_ext --inplace

Using flags:

.. code-block:: console

$ python setup.py build_ext --inplace -DUSE_SYSTEM_BLOSC:BOOL=YES -DBlosc_ROOT:PATH=/usr/local/customprefix

Testing

After compiling, you can quickly check that the package is sane by
running the doctests in blosc/test.py:

.. code-block:: console

$ python -m blosc.test  (add -v for verbose mode)

Once installed, you can re-run the tests at any time with:

.. code-block:: console

$ python -c "import blosc; blosc.test()"

Benchmarking

If curious, you may want to run a small benchmark that compares a plain
NumPy array copy against compression through different compressors in
your Blosc build:

.. code-block:: console

$ PYTHONPATH=. python bench/compress_ptr.py

Just to whet your appetite, here are the results for an Intel Xeon
E5-2695 v3 @ 2.30GHz, running Python 3.5, CentOS 7, but YMMV (and
will vary!)::

-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
python-blosc version: 1.5.1.dev0
Blosc version: 1.11.2 ($Date:: 2017-01-27 #$)
Compressors available: ['blosclz', 'lz4', 'lz4hc', 'snappy', 'zlib', 'zstd']
Compressor library versions:
BloscLZ: 1.0.5
LZ4: 1.7.5
Snappy: 1.1.1
Zlib: 1.2.7
Zstd: 1.1.2
Python version: 3.5.2 |Continuum Analytics, Inc.| (default, Jul 2 2016, 17:53:06)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]
Platform: Linux-3.10.0-327.18.2.el7.x86_64-x86_64 (#1 SMP Thu May 12 11:03:55 UTC 2016)
Linux dist: CentOS Linux 7.2.1511
Processor: x86_64
Byte-ordering: little
Detected cores: 56
Number of threads to use by default: 4
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Creating NumPy arrays with 10**8 int64/float64 elements:
*** ctypes.memmove() *** Time for memcpy(): 0.276 s (2.70 GB/s)

Times for compressing/decompressing with clevel=5 and 24 threads

*** the arange linear distribution ***
*** blosclz , noshuffle *** 0.382 s (1.95 GB/s) / 0.300 s (2.48 GB/s) Compr. ratio: 1.0x
*** blosclz , shuffle *** 0.042 s (17.77 GB/s) / 0.027 s (27.18 GB/s) Compr. ratio: 57.1x
*** blosclz , bitshuffle *** 0.094 s (7.94 GB/s) / 0.041 s (18.28 GB/s) Compr. ratio: 74.0x
*** lz4 , noshuffle *** 0.156 s (4.79 GB/s) / 0.052 s (14.30 GB/s) Compr. ratio: 2.0x
*** lz4 , shuffle *** 0.033 s (22.58 GB/s) / 0.034 s (22.03 GB/s) Compr. ratio: 68.6x
*** lz4 , bitshuffle *** 0.059 s (12.63 GB/s) / 0.053 s (14.18 GB/s) Compr. ratio: 33.1x
*** lz4hc , noshuffle *** 0.443 s (1.68 GB/s) / 0.070 s (10.62 GB/s) Compr. ratio: 2.0x
*** lz4hc , shuffle *** 0.102 s (7.31 GB/s) / 0.029 s (25.42 GB/s) Compr. ratio: 97.5x
*** lz4hc , bitshuffle *** 0.206 s (3.62 GB/s) / 0.038 s (19.85 GB/s) Compr. ratio: 180.5x
*** snappy , noshuffle *** 0.154 s (4.84 GB/s) / 0.056 s (13.28 GB/s) Compr. ratio: 2.0x
*** snappy , shuffle *** 0.044 s (16.89 GB/s) / 0.047 s (15.95 GB/s) Compr. ratio: 17.4x
*** snappy , bitshuffle *** 0.064 s (11.58 GB/s) / 0.061 s (12.26 GB/s) Compr. ratio: 18.2x
*** zlib , noshuffle *** 1.172 s (0.64 GB/s) / 0.135 s (5.50 GB/s) Compr. ratio: 5.3x
*** zlib , shuffle *** 0.260 s (2.86 GB/s) / 0.086 s (8.67 GB/s) Compr. ratio: 120.8x
*** zlib , bitshuffle *** 0.262 s (2.84 GB/s) / 0.094 s (7.96 GB/s) Compr. ratio: 260.1x
*** zstd , noshuffle *** 0.973 s (0.77 GB/s) / 0.093 s (8.00 GB/s) Compr. ratio: 7.8x
*** zstd , shuffle *** 0.093 s (7.97 GB/s) / 0.023 s (32.71 GB/s) Compr. ratio: 156.7x
*** zstd , bitshuffle *** 0.115 s (6.46 GB/s) / 0.029 s (25.60 GB/s) Compr. ratio: 320.6x

*** the linspace linear distribution ***
*** blosclz , noshuffle *** 0.341 s (2.19 GB/s) / 0.291 s (2.56 GB/s) Compr. ratio: 1.0x
*** blosclz , shuffle *** 0.132 s (5.65 GB/s) / 0.023 s (33.10 GB/s) Compr. ratio: 2.0x
*** blosclz , bitshuffle *** 0.166 s (4.50 GB/s) / 0.036 s (20.89 GB/s) Compr. ratio: 2.8x
*** lz4 , noshuffle *** 0.142 s (5.26 GB/s) / 0.028 s (27.07 GB/s) Compr. ratio: 1.0x
*** lz4 , shuffle *** 0.093 s (8.01 GB/s) / 0.030 s (24.87 GB/s) Compr. ratio: 3.4x
*** lz4 , bitshuffle *** 0.102 s (7.31 GB/s) / 0.039 s (19.13 GB/s) Compr. ratio: 5.3x
*** lz4hc , noshuffle *** 0.700 s (1.06 GB/s) / 0.044 s (16.77 GB/s) Compr. ratio: 1.1x
*** lz4hc , shuffle *** 0.203 s (3.67 GB/s) / 0.021 s (36.22 GB/s) Compr. ratio: 8.6x
*** lz4hc , bitshuffle *** 0.342 s (2.18 GB/s) / 0.028 s (26.50 GB/s) Compr. ratio: 14.2x
*** snappy , noshuffle *** 0.271 s (2.75 GB/s) / 0.274 s (2.72 GB/s) Compr. ratio: 1.0x
*** snappy , shuffle *** 0.099 s (7.54 GB/s) / 0.042 s (17.55 GB/s) Compr. ratio: 4.2x
*** snappy , bitshuffle *** 0.127 s (5.86 GB/s) / 0.043 s (17.20 GB/s) Compr. ratio: 6.1x
*** zlib , noshuffle *** 1.525 s (0.49 GB/s) / 0.158 s (4.70 GB/s) Compr. ratio: 1.6x
*** zlib , shuffle *** 0.346 s (2.15 GB/s) / 0.098 s (7.59 GB/s) Compr. ratio: 10.7x
*** zlib , bitshuffle *** 0.420 s (1.78 GB/s) / 0.104 s (7.20 GB/s) Compr. ratio: 18.0x
*** zstd , noshuffle *** 1.061 s (0.70 GB/s) / 0.096 s (7.79 GB/s) Compr. ratio: 1.9x
*** zstd , shuffle *** 0.203 s (3.68 GB/s) / 0.052 s (14.21 GB/s) Compr. ratio: 14.2x
*** zstd , bitshuffle *** 0.251 s (2.97 GB/s) / 0.047 s (15.84 GB/s) Compr. ratio: 22.2x

*** the random distribution ***
*** blosclz , noshuffle *** 0.340 s (2.19 GB/s) / 0.285 s (2.61 GB/s) Compr. ratio: 1.0x
*** blosclz , shuffle *** 0.091 s (8.21 GB/s) / 0.017 s (44.29 GB/s) Compr. ratio: 3.9x
*** blosclz , bitshuffle *** 0.080 s (9.27 GB/s) / 0.029 s (26.12 GB/s) Compr. ratio: 6.1x
*** lz4 , noshuffle *** 0.150 s (4.95 GB/s) / 0.027 s (28.05 GB/s) Compr. ratio: 2.4x
*** lz4 , shuffle *** 0.068 s (11.02 GB/s) / 0.029 s (26.03 GB/s) Compr. ratio: 4.5x
*** lz4 , bitshuffle *** 0.063 s (11.87 GB/s) / 0.054 s (13.70 GB/s) Compr. ratio: 6.2x
*** lz4hc , noshuffle *** 0.645 s (1.15 GB/s) / 0.019 s (39.22 GB/s) Compr. ratio: 3.5x
*** lz4hc , shuffle *** 0.257 s (2.90 GB/s) / 0.022 s (34.62 GB/s) Compr. ratio: 5.1x
*** lz4hc , bitshuffle *** 0.128 s (5.80 GB/s) / 0.029 s (25.52 GB/s) Compr. ratio: 6.2x
*** snappy , noshuffle *** 0.164 s (4.54 GB/s) / 0.048 s (15.46 GB/s) Compr. ratio: 2.2x
*** snappy , shuffle *** 0.082 s (9.09 GB/s) / 0.043 s (17.39 GB/s) Compr. ratio: 4.3x
*** snappy , bitshuffle *** 0.071 s (10.48 GB/s) / 0.046 s (16.08 GB/s) Compr. ratio: 5.0x
*** zlib , noshuffle *** 1.223 s (0.61 GB/s) / 0.093 s (7.97 GB/s) Compr. ratio: 4.0x
*** zlib , shuffle *** 0.636 s (1.17 GB/s) / 0.126 s (5.89 GB/s) Compr. ratio: 5.5x
*** zlib , bitshuffle *** 0.327 s (2.28 GB/s) / 0.109 s (6.81 GB/s) Compr. ratio: 6.2x
*** zstd , noshuffle *** 1.432 s (0.52 GB/s) / 0.103 s (7.27 GB/s) Compr. ratio: 4.2x
*** zstd , shuffle *** 0.388 s (1.92 GB/s) / 0.031 s (23.71 GB/s) Compr. ratio: 5.9x
*** zstd , bitshuffle *** 0.127 s (5.86 GB/s) / 0.033 s (22.77 GB/s) Compr. ratio: 6.4x

Also, Blosc works quite well on ARM processors (even without NEON support yet)::

-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
python-blosc version: 1.4.4
Blosc version: 1.11.2 ($Date:: 2017-01-27 #$)
Compressors available: ['blosclz', 'lz4', 'lz4hc', 'snappy', 'zlib', 'zstd']
Compressor library versions:
  BloscLZ: 1.0.5
  LZ4: 1.7.5
  Snappy: 1.1.1
  Zlib: 1.2.8
  Zstd: 1.1.2
Python version: 3.6.0 (default, Dec 31 2016, 21:20:16)
[GCC 4.9.2]
Platform: Linux-3.4.113-sun8i-armv7l (#50 SMP PREEMPT Mon Nov 14 08:41:55 CET 2016)
Linux dist: debian 9.0
Processor: not recognized
Byte-ordering: little
Detected cores: 4
Number of threads to use by default: 4
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
  *** ctypes.memmove() *** Time for memcpy():   0.015 s (93.57 MB/s)

Times for compressing/decompressing with clevel=5 and 4 threads

*** user input ***
  *** blosclz , noshuffle  ***  0.015 s (89.93 MB/s) / 0.010 s (138.32 MB/s)    Compr. ratio:   2.7x
  *** blosclz , shuffle    ***  0.023 s (60.25 MB/s) / 0.012 s (112.71 MB/s)    Compr. ratio:   2.3x
  *** blosclz , bitshuffle ***  0.018 s (77.63 MB/s) / 0.021 s (66.76 MB/s)     Compr. ratio:   7.3x
  *** lz4     , noshuffle  ***  0.008 s (177.14 MB/s) / 0.009 s (159.00 MB/s)   Compr. ratio:   3.6x
  *** lz4     , shuffle    ***  0.010 s (131.29 MB/s) / 0.012 s (117.69 MB/s)   Compr. ratio:   3.5x
  *** lz4     , bitshuffle ***  0.015 s (89.97 MB/s) / 0.022 s (63.62 MB/s)     Compr. ratio:   8.4x
  *** lz4hc   , noshuffle  ***  0.071 s (19.30 MB/s) / 0.007 s (186.64 MB/s)    Compr. ratio:   8.6x
  *** lz4hc   , shuffle    ***  0.079 s (17.30 MB/s) / 0.014 s (95.99 MB/s)     Compr. ratio:   6.2x
  *** lz4hc   , bitshuffle ***  0.062 s (22.23 MB/s) / 0.027 s (51.53 MB/s)     Compr. ratio:   9.7x
  *** snappy  , noshuffle  ***  0.008 s (173.87 MB/s) / 0.009 s (148.77 MB/s)   Compr. ratio:   4.4x
  *** snappy  , shuffle    ***  0.011 s (123.22 MB/s) / 0.016 s (85.16 MB/s)    Compr. ratio:   4.4x
  *** snappy  , bitshuffle ***  0.015 s (89.02 MB/s) / 0.021 s (64.87 MB/s)     Compr. ratio:   6.2x
  *** zlib    , noshuffle  ***  0.047 s (29.26 MB/s) / 0.011 s (121.83 MB/s)    Compr. ratio:  14.7x
  *** zlib    , shuffle    ***  0.080 s (17.20 MB/s) / 0.022 s (63.61 MB/s)     Compr. ratio:   9.4x
  *** zlib    , bitshuffle ***  0.059 s (23.50 MB/s) / 0.033 s (41.10 MB/s)     Compr. ratio:  10.5x
  *** zstd    , noshuffle  ***  0.113 s (12.21 MB/s) / 0.011 s (124.64 MB/s)    Compr. ratio:  15.6x
  *** zstd    , shuffle    ***  0.154 s (8.92 MB/s) / 0.026 s (52.56 MB/s)      Compr. ratio:   9.9x
  *** zstd    , bitshuffle ***  0.116 s (11.86 MB/s) / 0.036 s (38.40 MB/s)     Compr. ratio:  11.4x

For details on the ARM benchmark see: https://github.com/Blosc/python-blosc/issues/105

In case you find your own results interesting, please report them back
to the authors!

License

The software is licensed under a 3-Clause BSD license. A copy of the
python-blosc license can be found in
LICENSE.txt <https://github.com/Blosc/python-blosc/blob/main/LICENSE.txt>_.

Mailing list

Discussion about this module is welcome in the Blosc list:

blosc@googlegroups.com

https://groups.google.com/g/blosc

Enjoy data!

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