zarrs is a Rust library for the Zarr storage format for multidimensional arrays and metadata. zarrs can be used as an alternative high-performance codec pipeline in zarr-developers/zarr-python.

This organisation hosts zarrs related repositories and serves zarrs web content:

• The zarrs Website https://zarrs.dev
• The zarrs Book https://book.zarrs.dev

• zarrs: The core library for manipulating Zarr hierarchies.

• zarrs-python: A high-performance codec pipeline for zarr-developers/zarr-python.
• zarrs_ffi: A subset of zarrs exposed as a C/C++ API.
• earth-mover/Zarrs.jl: High-performance Zarr V2 and V3 arrays for Julia, powered by the zarrs Rust library.
• mdsumner/zr: Zarr V2/V3 arrays for R, via the zarrs Rust crate.

• zarrs_metadata: Zarr metadata support (re-exported as zarrs::metadata).
• zarrs_metadata_ext: Zarr extensions metadata support.
• zarrs_data_type: The data type extension API for zarrs (re-exported in zarrs::array::data_type).
• zarrs_storage: The storage API for zarrs (re-exported as zarrs::storage).
• zarrs_plugin: The plugin API for zarrs (re-exported as zarrs::plugin).
• zarrs_registry: The Zarr extension point registry for zarrs (re-exported as zarrs::registry).

• zarrs_filesystem: A filesystem store (re-exported as zarrs::filesystem).
• zarrs_object_store: object_store store support.
• zarrs_opendal: opendal store support.
• zarrs_http: A synchronous http store.
• zarrs_zip: A storage adapter for zip files.
• zarrs_icechunk: icechunk store support.
  • git-like version control for Zarr hierachies.
  • Read "virtual Zarr datacubes" of archival formats (e.g., netCDF4, HDF5, etc.) created by VirtualiZarr and backed by icechunk.
• clbarnes/zarrs_n5: N5 (Not HDF5) storage format support for the zarrs ecosystem.

• ome_zarr_metadata: A library for OME-Zarr (previously OME-NGFF) metadata.
• clbarnes/zarrs_conventions: An implementation of zarr-conventions for zarrs ecosystem.

• zarrs_tools: Various tools for creating and manipulating Zarr V3 data with the zarrs Rust crate
  • A reencoder that can change codecs, chunk shape, convert Zarr V2 to V3, etc.
  • Create an OME-Zarr hierarchy from a Zarr array.
  • Transform arrays: crop, rescale, downsample, gradient magnitude, gaussian, noise filtering, etc.

• zarr_benchmarks: Benchmarks of various Zarr V3 implementations: zarrs, zarr-python, tensorstore