Getting Started
===============
Zarr is a format for the storage of chunked, compressed, N-dimensional arrays
inspired by `HDF5 `_, `h5py
`_ and `bcolz `_.
The project is fiscally sponsored by `NumFOCUS `_, a US
501(c)(3) public charity, and development is supported by the
`MRC Centre for Genomics and Global Health `_
and the `Chan Zuckerberg Initiative `_.
These documents describe the Zarr Python implementation. More information
about the Zarr format can be found on the `main website `_.
Highlights
----------
* Create N-dimensional arrays with any NumPy dtype.
* Chunk arrays along any dimension.
* Compress and/or filter chunks using any NumCodecs_ codec.
* Store arrays in memory, on disk, inside a Zip file, on S3, ...
* Read an array concurrently from multiple threads or processes.
* Write to an array concurrently from multiple threads or processes.
* Organize arrays into hierarchies via groups.
Contributing
------------
Feedback and bug reports are very welcome, please get in touch via
the `GitHub issue tracker `_. See
:doc:`contributing` for further information about contributing to Zarr.
Projects using Zarr
-------------------
If you are using Zarr, we would `love to hear about it
`_.
.. toctree::
:caption: Getting Started
:hidden:
installation
.. _NumCodecs: https://numcodecs.readthedocs.io/