diff --git a/README.md b/README.md index 0fc46b1dd..b2e24e4e1 100644 --- a/README.md +++ b/README.md @@ -8,28 +8,28 @@ [![pre-commit Enabled](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://pre-commit.com/) [![Apache 2.0 License](https://img.shields.io/badge/license-Apache%202-cb2533.svg)](https://www.apache.org/licenses/LICENSE-2.0) [![Python Versions](https://img.shields.io/python/required-version-toml?tomlFilePath=https://raw.githubusercontent.com/zarr-developers/VirtualiZarr/main/pyproject.toml&logo=Python&logoColor=gold&label=Python)](https://docs.python.org) - +[![slack](https://img.shields.io/badge/slack-virtualizarr-purple.svg?logo=slack)](https://earthmover-community.slack.com/archives/C08EXCE8ZQX) [![Latest Release](https://img.shields.io/github/v/release/zarr-developers/VirtualiZarr)](https://github.com/zarr-developers/VirtualiZarr/releases) [![PyPI - Downloads](https://img.shields.io/pypi/dm/virtualizarr?label=pypi%7Cdownloads)](https://pypistats.org/packages/virtualizarr) [![Conda - Downloads](https://img.shields.io/conda/d/conda-forge/virtualizarr )](https://anaconda.org/conda-forge/virtualizarr) -[![slack](https://img.shields.io/badge/slack-virtualizarr-purple.svg?logo=slack)](https://earthmover-community.slack.com/archives/C08EXCE8ZQX) -## Cloud-Optimize your Scientific Data as Virtual Zarr stores, using xarray syntax. + +## Cloud-Optimize your Scientific Data as a Virtual Zarr Datacube, using Xarray syntax. The best way to distribute large scientific datasets is via the Cloud, in [Cloud-Optimized formats](https://guide.cloudnativegeo.org/) [^1]. But often this data is stuck in archival pre-Cloud file formats such as netCDF. -**VirtualiZarr[^2] makes it easy to create "Virtual" Zarr stores, allowing performant access to archival data as if it were in the Cloud-Optimized [Zarr format](https://zarr.dev/), _without duplicating any data_.** +**VirtualiZarr[^2] makes it easy to create "Virtual" Zarr datacubes, allowing performant access to archival data as if it were in the Cloud-Optimized [Zarr format](https://zarr.dev/), _without duplicating any data_.** Please see the [documentation](https://virtualizarr.readthedocs.io/en/stable/index.html). ### Features -* Create virtual references pointing to bytes inside a archival file with [`open_virtual_dataset`](https://virtualizarr.readthedocs.io/en/latest/usage.html#opening-files-as-virtual-datasets), -* Supports a [range of archival file formats](https://virtualizarr.readthedocs.io/en/latest/faq.html#how-do-virtualizarr-and-kerchunk-compare), including netCDF4 and HDF5, -* [Combine data from multiple files](https://virtualizarr.readthedocs.io/en/latest/usage.html#combining-virtual-datasets) into one larger store using [xarray's combining functions](https://docs.xarray.dev/en/stable/user-guide/combining.html), such as [`xarray.concat`](https://docs.xarray.dev/en/stable/generated/xarray.concat.html), +* Create virtual references pointing to bytes inside an archival file with [`open_virtual_dataset`](https://virtualizarr.readthedocs.io/en/latest/usage.html#opening-files-as-virtual-datasets). +* Supports a [range of archival file formats](https://virtualizarr.readthedocs.io/en/latest/faq.html#how-do-virtualizarr-and-kerchunk-compare), including netCDF4 and HDF5, and has a pluggable system for supporting new formats. +* [Combine data from multiple files](https://virtualizarr.readthedocs.io/en/latest/usage.html#combining-virtual-datasets) into one larger datacube using [xarray's combining functions](https://docs.xarray.dev/en/stable/user-guide/combining.html), such as [`xarray.concat`](https://docs.xarray.dev/en/stable/generated/xarray.concat.html). * Commit the virtual references to storage either using the [Kerchunk references](https://fsspec.github.io/kerchunk/spec.html) specification or the [Icechunk](https://icechunk.io/) transactional storage engine. -* Users access the virtual dataset using [`xarray.open_dataset`](https://docs.xarray.dev/en/stable/generated/xarray.open_dataset.html#xarray.open_dataset). +* Users access the virtual datacube simply as a single zarr-compatible store using [`xarray.open_zarr`](https://docs.xarray.dev/en/stable/generated/xarray.open_zarr.html). ### Inspired by Kerchunk