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.


  • 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.


Feedback and bug reports are very welcome, please get in touch via the GitHub issue tracker. See Contributing to Zarr for further information about contributing to Zarr.

Projects using Zarr#

If you are using Zarr, we would love to hear about it.