ome-zarr
Implementation of images in Zarr files.
What it is and what it does
ome-zarr-py is a Python library for working with multi-resolution images stored in Zarr filesets that conform to the OME NGFF (Open Microscopy Environment Next Generation File Format) specification. It provides tools to read, write, and manipulate imaging data in this standardized format, which is designed for efficient storage and access of large, hierarchical image datasets common in scientific imaging workflows.
The package sits on top of established data-handling libraries—numpy for arrays, dask for distributed computation, zarr for the underlying storage format, and fsspec for flexible file system access. It's intended for developers and researchers working with microscopy or other large-scale imaging data who need to work with standardized, interoperable image formats. The library is in beta status and actively maintained, with support for current Python versions.
Use it for:
- Load and analyze multi-resolution microscopy images stored in OME-NGFF Zarr format for research.
- Convert imaging datasets into standardized Zarr filesets for interoperability across tools.
- Access large imaging datasets efficiently using dask-backed lazy loading and distributed computation.
- Build imaging pipelines that consume or produce OME-NGFF-compliant Zarr data.
- Integrate microscopy image data into scientific computing workflows with numpy and scikit-image.
Worth the install?
AI-flagged interpretation of the facts on this page — verify before relying
Reads and writes multi-resolution images stored in Zarr filesets according to the OME NGFF specification, enabling efficient access to large imaging datasets.
Yes. The package is actively maintained, has low install friction, carries a permissive license, and fills a clear role in the scientific imaging ecosystem. No known vulnerabilities. Suitable for anyone working with OME NGFF Zarr images or building tools that need to read or write them. The beta status is typical for specialized scientific libraries and should not deter adoption.
Install
ome-zarr on PyPI
pip
pip install ome-zarruv
uv add ome-zarrpoetry
poetry add ome-zarrInstalling ome-zarr
Before you install
Low install friction with a pure-Python wheel. Active maintenance with a recent release 58 days ago and ongoing commits. Depends on established libraries (numpy, dask, zarr, fsspec) with no unusual compilation requirements.
License in practice
BSD-2-Clause permissive license allows use in most commercial and open-source projects with minimal restrictions.
Quickstart
pip install ome-zarr
import ome_zarr
# Load an OME-NGFF Zarr image
image = ome_zarr.open_ome_zarr('path/to/image.zarr')
Requires Python >3.11.
Verify before relying
- Specific performance characteristics or scalability limits for very large imaging datasets.
- Whether the package handles all OME NGFF spec versions or only a subset.
- Integration maturity with common microscopy software ecosystems beyond Zarr.
Package facts
| License | BSD-2-Clause (permissive) |
| Python support | supports the current Python release (>3.11) |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 11 — numpy, dask, zarr, fsspec, aiohttp, requests, scikit-image, toolz, rangehttpserver, ome-zarr-models, Deprecated |
| Maintenance | actively maintained — 58 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 581,816/month — #5,907 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: ome_zarr-0.18.0-py3-none-any.whl
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