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blosc-1.9.3.dev0
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Blosc data compressor
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | blosc-1.9.3.dev0 |
| نام | blosc |
| نسخه کتابخانه | 1.9.3.dev0 |
| نگهدارنده | ['The Blosc development team'] |
| ایمیل نگهدارنده | ['blosc@blosc.org'] |
| نویسنده | The Blosc development team |
| ایمیل نویسنده | blosc@blosc.org |
| آدرس صفحه اصلی | http://github.com/blosc/python-blosc |
| آدرس اینترنتی | https://pypi.org/project/blosc/ |
| مجوز | https://opensource.org/licenses/BSD-3-Clause |
============
Python-Blosc
============
A Python wrapper for the extremely fast Blosc compression library
=================================================================
:Author: The Blosc development team
:Contact: blosc@blosc.org
:Github: https://github.com/Blosc/python-blosc
:URL: https://www.blosc.org/python-blosc/python-blosc.html
:PyPi: |version|
:Anaconda: |anaconda|
:Gitter: |gitter|
:Code of Conduct: |Contributor Covenant|
.. |version| image:: https://img.shields.io/pypi/v/blosc.png
: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
.. |gitter| image:: https://badges.gitter.im/Blosc/c-blosc.svg
:target: https://gitter.im/Blosc/c-blosc
.. |Contributor Covenant| image:: https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg
:target: https://github.com/Blosc/community/blob/master/code_of_conduct.md
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 3.8 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
<http://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 licenses under a 3-Clause BSD licsense. 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
http://groups.google.es/group/blosc
----
**Enjoy data!**
.. Local Variables:
.. mode: rst
.. coding: utf-8
.. fill-column: 72
.. End:
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl blosc-1.9.3.dev0:
pip install blosc-1.9.3.dev0.whl
نصب پکیج tar.gz blosc-1.9.3.dev0:
pip install blosc-1.9.3.dev0.tar.gz