zarrs_tools
Various tools for creating and manipulating Zarr v3 data with the zarrs rust crate.
A changelog can be found here.
Tools
All tools support input and output Zarr V3 data. Some tools additionally support input of a V3 compatible subset of Zarr V2.
- zarrs_reencode: reencode an array. Manipulate the chunk size, shard size, codecs, fill value, chunk key encoding separator, and attributes.
- zarrs_filter (feature
filter): apply simple image filters (transformations) to an array. - zarrs_ome (feature
ome): convert an array to an OME-Zarr multi-scale image.- Supports OME-Zarr
0.5-dev(as Zarr V3) and0.5-dev1. The first is recognised by Neuroglancer.
- Supports OME-Zarr
- zarrs_info (feature
info): return metadata related info or the range/histogram of an array. - zarrs_binary2zarr (feature
binary2zarr): create an array from piped binary data. - zarrs_ncvar2zarr (feature
ncvar2zarr): convert a netCDF variable to an array.
See docs/ for tool documentation.
zarrs Benchmarking
- zarrs_reencode: suitable for round trip benchmarking.
- zarrs_benchmark_read_sync (feature
benchmark): benchmark the zarrs sync API. - zarrs_benchmark_read_async (feature
benchmark): benchmark the zarrs async API.
See docs/benchmarks.md for some benchmark measurements.
Install
From crates.io
From source
# cargo install --all-features --git https://github.com/LDeakin/zarrs_tools
Enabling SIMD intrinsics
Encoding and decoding performance may be improved with avx2/sse2 enabled (if supported).
This can be enabled by compiling with either of:
RUSTFLAGS="-C target-cpu=native"RUSTFLAGS="-C target-feature=+avx2,+sse2"
Enabling non-default zarrs codecs
Non-default zarrs codecs (see zarrs crate features) can be enabled by passing them as feature flags.
For example:
Licence
zarrs_tools is licensed under either of
- the Apache License, Version 2.0 LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0 or
- the MIT license LICENSE-MIT or http://opensource.org/licenses/MIT, at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.