| Name | blosc2 JSON |
| Version |
2.7.1
JSON |
| download |
| home_page | None |
| Summary | Python wrapper for the C-Blosc2 library |
| upload_time | 2024-07-30 20:18:33 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <4,>=3.10 |
| license | BSD-3-Clause |
| keywords |
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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No Travis.
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| coveralls test coverage |
No coveralls.
|
=============
Python-Blosc2
=============
A Python wrapper for the extremely fast Blosc2 compression library
==================================================================
:Author: The Blosc development team
:Contact: blosc@blosc.org
:Github: https://github.com/Blosc/python-blosc2
:Actions: |actions|
:PyPi: |version|
:NumFOCUS: |numfocus|
:Code of Conduct: |Contributor Covenant|
.. |version| image:: https://img.shields.io/pypi/v/blosc2.svg
:target: https://pypi.python.org/pypi/blosc2
.. |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
.. |numfocus| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A
:target: https://numfocus.org
.. |actions| image:: https://github.com/Blosc/python-blosc2/actions/workflows/build.yml/badge.svg
:target: https://github.com/Blosc/python-blosc2/actions/workflows/build.yml
What it is
==========
`C-Blosc2 <https://github.com/Blosc/c-blosc2>`_ is the new major version of
`C-Blosc <https://github.com/Blosc/c-blosc>`_, and is backward compatible with
both the C-Blosc1 API and its in-memory format. Python-Blosc2 is a Python package
that wraps C-Blosc2, the newest version of the Blosc compressor.
Currently Python-Blosc2 already reproduces the API of
`Python-Blosc <https://github.com/Blosc/python-blosc>`_, so it can be
used as a drop-in replacement. However, there are a `few exceptions
for a full compatibility.
<https://github.com/Blosc/python-blosc2/blob/main/RELEASE_NOTES.md#changes-from-python-blosc-to-python-blosc2>`_
In addition, Python-Blosc2 aims to leverage the full C-Blosc2 functionality to support
super-chunks (`SChunk <https://www.blosc.org/python-blosc2/reference/schunk_api.html>`_),
multi-dimensional arrays
(`NDArray <https://www.blosc.org/python-blosc2/reference/ndarray_api.html>`_),
metadata, serialization and other bells and whistles introduced in C-Blosc2.
**Note:** Python-Blosc2 is meant to be backward compatible with Python-Blosc data.
That means that it can read data generated with Python-Blosc, but the opposite
is not true (i.e. there is no *forward* compatibility).
SChunk: a 64-bit compressed store
=================================
A `SChunk <https://www.blosc.org/python-blosc2/reference/schunk_api.html>`_ is a simple data
container that handles setting, expanding and getting
data and metadata. Contrarily to chunks, a super-chunk can update and resize the data
that it contains, supports user metadata, and it does not have the 2 GB storage limitation.
Additionally, you can convert a SChunk into a contiguous, serialized buffer (aka
`cframe <https://github.com/Blosc/c-blosc2/blob/main/README_CFRAME_FORMAT.rst>`_)
and vice-versa; as a bonus, the serialization/deserialization process also works with NumPy
arrays and PyTorch/TensorFlow tensors at a blazing speed:
.. |compress| image:: https://github.com/Blosc/python-blosc2/blob/main/images/linspace-compress.png?raw=true
:width: 100%
:alt: Compression speed for different codecs
.. |decompress| image:: https://github.com/Blosc/python-blosc2/blob/main/images/linspace-decompress.png?raw=true
:width: 100%
:alt: Decompression speed for different codecs
+----------------+---------------+
| |compress| | |decompress| |
+----------------+---------------+
while reaching excellent compression ratios:
.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/pack-array-cratios.png?raw=true
:width: 75%
:align: center
:alt: Compression ratio for different codecs
Also, if you are a Mac M1/M2 owner, make you a favor and use its native arm64 arch (yes, we are
distributing Mac arm64 wheels too; you are welcome ;-):
.. |pack_arm| image:: https://github.com/Blosc/python-blosc2/blob/main/images/M1-i386-vs-arm64-pack.png?raw=true
:width: 100%
:alt: Compression speed for different codecs on Apple M1
.. |unpack_arm| image:: https://github.com/Blosc/python-blosc2/blob/main/images/M1-i386-vs-arm64-unpack.png?raw=true
:width: 100%
:alt: Decompression speed for different codecs on Apple M1
+------------+--------------+
| |pack_arm| | |unpack_arm| |
+------------+--------------+
Read more about `SChunk` features in our blog entry at: https://www.blosc.org/posts/python-blosc2-improvements
NDArray: an N-Dimensional store
===============================
One of the latest and more exciting additions in Python-Blosc2 is the
`NDArray <https://www.blosc.org/python-blosc2/reference/ndarray_api.html>`_ object.
It can write and read n-dimensional datasets in an extremely efficient way thanks
to a n-dim 2-level partitioning, allowing to slice and dice arbitrary large and
compressed data in a more fine-grained way:
.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/b2nd-2level-parts.png?raw=true
:width: 75%
To wet you appetite, here it is how the `NDArray` object performs on getting slices
orthogonal to the different axis of a 4-dim dataset:
.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/Read-Partial-Slices-B2ND.png?raw=true
:width: 75%
We have blogged about this: https://www.blosc.org/posts/blosc2-ndim-intro
We also have a ~2 min explanatory video on `why slicing in a pineapple-style (aka double partition)
is useful <https://www.youtube.com/watch?v=LvP9zxMGBng>`_:
.. image:: https://github.com/Blosc/blogsite/blob/master/files/images/slicing-pineapple-style.png?raw=true
:width: 50%
:alt: Slicing a dataset in pineapple-style
:target: https://www.youtube.com/watch?v=LvP9zxMGBng
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 blosc2
Documentation
=============
The documentation is here:
https://blosc.org/python-blosc2/python-blosc2.html
Also, some examples are available on:
https://github.com/Blosc/python-blosc2/tree/main/examples
Building from sources
=====================
`python-blosc2` comes with the C-Blosc2 sources with it and can be built in-place:
.. code-block:: console
git clone https://github.com/Blosc/python-blosc2/
cd python-blosc2
git submodule update --init --recursive
python -m pip install -r requirements-build.txt
python setup.py build_ext --inplace
That's all. You can proceed with testing section now.
Testing
=======
After compiling, you can quickly check that the package is sane by
running the tests:
.. code-block:: console
python -m pip install -r requirements-tests.txt
python -m pytest (add -v for verbose mode)
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/pack_compress.py
License
=======
The software is licenses under a 3-Clause BSD license. A copy of the
python-blosc2 license can be found in `LICENSE.txt <https://github.com/Blosc/python-blosc2/tree/main/LICENSE.txt>`_.
Mailing list
============
Discussion about this module is welcome in the Blosc list:
blosc@googlegroups.com
https://groups.google.es/group/blosc
Twitter
=======
Please follow `@Blosc2 <https://twitter.com/Blosc2>`_ to get informed about the latest developments.
Citing Blosc
============
You can cite our work on the different libraries under the Blosc umbrella as:
.. code-block:: console
@ONLINE{blosc,
author = {{Blosc Development Team}},
title = "{A fast, compressed and persistent data store library}",
year = {2009-2023},
note = {https://blosc.org}
}
----
**Enjoy!**
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"description": "=============\nPython-Blosc2\n=============\n\nA Python wrapper for the extremely fast Blosc2 compression library\n==================================================================\n\n:Author: The Blosc development team\n:Contact: blosc@blosc.org\n:Github: https://github.com/Blosc/python-blosc2\n:Actions: |actions|\n:PyPi: |version|\n:NumFOCUS: |numfocus|\n:Code of Conduct: |Contributor Covenant|\n\n.. |version| image:: https://img.shields.io/pypi/v/blosc2.svg\n :target: https://pypi.python.org/pypi/blosc2\n.. |Contributor Covenant| image:: https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg\n :target: https://github.com/Blosc/community/blob/master/code_of_conduct.md\n.. |numfocus| image:: https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A\n :target: https://numfocus.org\n.. |actions| image:: https://github.com/Blosc/python-blosc2/actions/workflows/build.yml/badge.svg\n :target: https://github.com/Blosc/python-blosc2/actions/workflows/build.yml\n\n\nWhat it is\n==========\n\n`C-Blosc2 <https://github.com/Blosc/c-blosc2>`_ is the new major version of\n`C-Blosc <https://github.com/Blosc/c-blosc>`_, and is backward compatible with\nboth the C-Blosc1 API and its in-memory format. Python-Blosc2 is a Python package\nthat wraps C-Blosc2, the newest version of the Blosc compressor.\n\nCurrently Python-Blosc2 already reproduces the API of\n`Python-Blosc <https://github.com/Blosc/python-blosc>`_, so it can be\nused as a drop-in replacement. However, there are a `few exceptions\nfor a full compatibility.\n<https://github.com/Blosc/python-blosc2/blob/main/RELEASE_NOTES.md#changes-from-python-blosc-to-python-blosc2>`_\n\nIn addition, Python-Blosc2 aims to leverage the full C-Blosc2 functionality to support\nsuper-chunks (`SChunk <https://www.blosc.org/python-blosc2/reference/schunk_api.html>`_),\nmulti-dimensional arrays\n(`NDArray <https://www.blosc.org/python-blosc2/reference/ndarray_api.html>`_),\nmetadata, serialization and other bells and whistles introduced in C-Blosc2.\n\n**Note:** Python-Blosc2 is meant to be backward compatible with Python-Blosc data.\nThat means that it can read data generated with Python-Blosc, but the opposite\nis not true (i.e. there is no *forward* compatibility).\n\nSChunk: a 64-bit compressed store\n=================================\n\nA `SChunk <https://www.blosc.org/python-blosc2/reference/schunk_api.html>`_ is a simple data\ncontainer that handles setting, expanding and getting\ndata and metadata. Contrarily to chunks, a super-chunk can update and resize the data\nthat it contains, supports user metadata, and it does not have the 2 GB storage limitation.\n\nAdditionally, you can convert a SChunk into a contiguous, serialized buffer (aka\n`cframe <https://github.com/Blosc/c-blosc2/blob/main/README_CFRAME_FORMAT.rst>`_)\nand vice-versa; as a bonus, the serialization/deserialization process also works with NumPy\narrays and PyTorch/TensorFlow tensors at a blazing speed:\n\n.. |compress| image:: https://github.com/Blosc/python-blosc2/blob/main/images/linspace-compress.png?raw=true\n :width: 100%\n :alt: Compression speed for different codecs\n\n.. |decompress| image:: https://github.com/Blosc/python-blosc2/blob/main/images/linspace-decompress.png?raw=true\n :width: 100%\n :alt: Decompression speed for different codecs\n\n+----------------+---------------+\n| |compress| | |decompress| |\n+----------------+---------------+\n\nwhile reaching excellent compression ratios:\n\n.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/pack-array-cratios.png?raw=true\n :width: 75%\n :align: center\n :alt: Compression ratio for different codecs\n\nAlso, if you are a Mac M1/M2 owner, make you a favor and use its native arm64 arch (yes, we are\ndistributing Mac arm64 wheels too; you are welcome ;-):\n\n.. |pack_arm| image:: https://github.com/Blosc/python-blosc2/blob/main/images/M1-i386-vs-arm64-pack.png?raw=true\n :width: 100%\n :alt: Compression speed for different codecs on Apple M1\n\n.. |unpack_arm| image:: https://github.com/Blosc/python-blosc2/blob/main/images/M1-i386-vs-arm64-unpack.png?raw=true\n :width: 100%\n :alt: Decompression speed for different codecs on Apple M1\n\n+------------+--------------+\n| |pack_arm| | |unpack_arm| |\n+------------+--------------+\n\nRead more about `SChunk` features in our blog entry at: https://www.blosc.org/posts/python-blosc2-improvements\n\nNDArray: an N-Dimensional store\n===============================\n\nOne of the latest and more exciting additions in Python-Blosc2 is the\n`NDArray <https://www.blosc.org/python-blosc2/reference/ndarray_api.html>`_ object.\nIt can write and read n-dimensional datasets in an extremely efficient way thanks\nto a n-dim 2-level partitioning, allowing to slice and dice arbitrary large and\ncompressed data in a more fine-grained way:\n\n.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/b2nd-2level-parts.png?raw=true\n :width: 75%\n\nTo wet you appetite, here it is how the `NDArray` object performs on getting slices\northogonal to the different axis of a 4-dim dataset:\n\n.. image:: https://github.com/Blosc/python-blosc2/blob/main/images/Read-Partial-Slices-B2ND.png?raw=true\n :width: 75%\n\nWe have blogged about this: https://www.blosc.org/posts/blosc2-ndim-intro\n\nWe also have a ~2 min explanatory video on `why slicing in a pineapple-style (aka double partition)\nis useful <https://www.youtube.com/watch?v=LvP9zxMGBng>`_:\n\n.. image:: https://github.com/Blosc/blogsite/blob/master/files/images/slicing-pineapple-style.png?raw=true\n :width: 50%\n :alt: Slicing a dataset in pineapple-style\n :target: https://www.youtube.com/watch?v=LvP9zxMGBng\n\nInstalling\n==========\n\nBlosc is now offering Python wheels for the main OS (Win, Mac and Linux) and platforms.\nYou can install binary packages from PyPi using ``pip``:\n\n.. code-block:: console\n\n pip install blosc2\n\nDocumentation\n=============\n\nThe documentation is here:\n\nhttps://blosc.org/python-blosc2/python-blosc2.html\n\nAlso, some examples are available on:\n\nhttps://github.com/Blosc/python-blosc2/tree/main/examples\n\n\nBuilding from sources\n=====================\n\n`python-blosc2` comes with the C-Blosc2 sources with it and can be built in-place:\n\n.. code-block:: console\n\n git clone https://github.com/Blosc/python-blosc2/\n cd python-blosc2\n git submodule update --init --recursive\n python -m pip install -r requirements-build.txt\n python setup.py build_ext --inplace\n\nThat's all. You can proceed with testing section now.\n\nTesting\n=======\n\nAfter compiling, you can quickly check that the package is sane by\nrunning the tests:\n\n.. code-block:: console\n\n python -m pip install -r requirements-tests.txt\n python -m pytest (add -v for verbose mode)\n\nBenchmarking\n============\n\nIf curious, you may want to run a small benchmark that compares a plain\nNumPy array copy against compression through different compressors in\nyour Blosc build:\n\n.. code-block:: console\n\n PYTHONPATH=. python bench/pack_compress.py\n\nLicense\n=======\n\nThe software is licenses under a 3-Clause BSD license. 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