blosc2

============= Python-Blosc2

A fast & compressed ndarray library with a flexible compute engine

:Author: The Blosc development team :Contact: [e-mail] :Github: https://github.com/Blosc/python-blosc2 :Actions: |actions| :PyPi: |version| :NumFOCUS: |numfocus| :Code of Conduct: |Contributor Covenant|

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What it is

Python-Blosc2 is a high-performance compressed ndarray library with a flexible compute engine. It uses the C-Blosc2 library as the compression backend. C-Blosc2 <https://github.com/Blosc/c-blosc2>_ is the next generation of Blosc, an award-winning <https://www.blosc.org/posts/prize-push-Blosc2/>_ library that has been around for more than a decade, and that is been used by many projects, including PyTables <https://www.pytables.org/>_ or Zarr <https://zarr.readthedocs.io/en/stable/>_.

Python-Blosc2 is Python wrapper that exposes the C-Blosc2 API, plus an integrated compute engine. This allows to perform complex calculations on compressed data in a way that operands do not need to be in-memory, but can be stored on disk or on the network <https://github.com/ironArray/Caterva2>_. This makes possible to work with data no matter how large it is, and that can be stored in a distributed fashion.

Most importantly, Python-Blosc2 uses the C-Blosc2 simple and open format <https://github.com/Blosc/c-blosc2/blob/main/README_FORMAT.rst>_ for storing compressed data, making it easy to integrate with other systems and tools.

You can find more introductory info about Python-Blosc2 at:

https://www.blosc.org/python-blosc2/getting_started/overview.html

Installing

Blosc2 now provides Python wheels for the major OS (Win, Mac and Linux) and platforms. You can install the binary packages from PyPi using pip:

.. code-block:: console

pip install blosc2 --upgrade

For conda users, you can install the package from the conda-forge channel:

.. code-block:: console

conda install -c conda-forge python-blosc2

Documentation

The documentation is available here:

https://blosc.org/python-blosc2/python-blosc2.html

Additionally, you can find some examples at:

https://github.com/Blosc/python-blosc2/tree/main/examples

Finally, we taught a tutorial at the PyData Global 2024 <https://pydata.org/global2024/>_ that you can find at: https://github.com/Blosc/Python-Blosc2-3.0-tutorial. There you will find different Jupyter notebook that explains the main features of Python-Blosc2.

License

This software is licensed 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>_.

Discussion forum

Discussion about this package is welcome at:

https://github.com/Blosc/python-blosc2/discussions

Social feeds

Stay informed about the latest developments by following us in Mastodon <https://fosstodon.org/@Blosc2>, Bluesky <https://bsky.app/profile/blosc.org> or LinkedIn <https://www.linkedin.com/company/88381936/admin/dashboard/>_.

Thanks

Blosc2 is supported by the NumFOCUS foundation <https://numfocus.org>, the LEAPS-INNOV project <https://www.leaps-innov.eu> and ironArray SLU <https://ironarray.io>_, among many other donors. This allowed the following people have contributed in an important way to the core development of the Blosc2 library:

• Francesc Alted
• Marta Iborra
• Aleix Alcacer
• Oscar Guiñón
• Juan David Ibáñez
• Ivan Vilata i Balaguer
• Oumaima Ech.Chdig

In addition, other people have participated to the project in different aspects:

• Jan Sellner, contributed the mmap support for NDArray/SChunk objects.
• Dimitri Papadopoulos, contributed a large bunch of improvements to the in many aspects of the project. His attention to detail is remarkable.
• And many others that have contributed with bug reports, suggestions and improvements.

Citing Blosc

You can cite our work on the various libraries under the Blosc umbrella as follows:

.. code-block:: console

@ONLINE{blosc, author = {{Blosc Development Team}}, title = "{A fast, compressed and persistent data store library}", year = {2009-2025}, note = {https://blosc.org} }

Donate

If you find Blosc useful and want to support its development, please consider making a donation via the NumFOCUS <https://numfocus.org/donate-to-blosc>_ organization, which is a non-profit that supports many open-source projects. Thank you!

Compress Better, Compute Bigger