python-blosc: a Python wrapper for the extremely fast Blosc compression library
Author: Francesc Alted
Author: Valentin Haenel
Contact: faltet@gmail.com
Contact: valentin@haenel.co
Github: https://github.com/Blosc/python-blosc
URL: http://python-blosc.blosc.org
Travis CI: travis
Appveyor: appveyor
PyPi: version
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anaconda
Gitter: [OBJ]
gitter
Code of Conduct:
[OBJ]
Contributor Covenant
What it is
Blosc (http://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 3.6 or higher versions.
Installing
You can install binary packages with conda:
$ conda install -c conda-forge python-blosc
Or, install it as a typical Python source package (requires c-compiler and
Python headers) from PyPi using pip:
$ pip install blosc
Documentation
The Sphinx based documentation is here:
http://python-blosc.blosc.org
Also, some examples are available on python-blosc wiki page:
http://github.com/blosc/python-blosc/wiki
Lastly, here is the recording and the slides 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:
$ 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_ZLIB. 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:
$ BLOSC_DIR=/usr/local (or "set BLOSC_DIR=\blosc" on Win)
$ export BLOSC_DIR (not needed on Win)
$ python setup.py build_clib
$ python setup.py build_ext --inplace
Using a flag:
$ python setup.py build_clib
$ python setup.py build_ext --inplace --blosc=/usr/local
Testing
After compiling, you can quickly check that the package is sane by running
the doctests in blosc/test.py:
$ PYTHONPATH=. (or "set PYTHONPATH=." on Win)
$ export PYTHONPATH=. (not needed on Win)
$ python blosc/test.py (add -v for verbose mode)
Or alternatively, you can use the third-party nosetests script:
$ nosetests --with-doctest (add -v for verbose mode)
Once installed, you can re-run the tests at any time with:
$ 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:
$ 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!):
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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
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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):
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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
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*** 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 licenses under a 3-Clause BSD licsense. A copy of the
python-blosc license can be found in LICENSE.txt. A copy of all licenses
can be found in LICENSES/.
Mailing list
Discussion about this module is welcome in the Blosc list:
blosc@googlegroups.com
http://groups.google.es/group/blosc
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Enjoy data!
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