ngff-zarr

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A lean and kind Open Microscopy Environment (OME) Next Generation File Format (NGFF) Zarr implementation.

✨ Features

  • Minimal dependencies
  • Work with arbitrary Zarr store types
  • Lazy, parallel, and web ready -- no local filesystem required
  • Process extremely large datasets
  • Conversion of most bioimaging file formats
  • Multiple downscaling methods
  • Supports Python>=3.10
  • Reads OME-Zarr v0.1 to v0.6 into simple Python data classes with Dask arrays
  • Optional OME-Zarr data model validation during reading
  • Writes OME-Zarr v0.4 to v0.6
  • v0.6 adds RFC-5 coordinate systems and transformations
  • Sharded Zarr stores
  • Optional writing via zarr-python 2, zarr-python 3, tensorstore or zarrita (TypeScript)
  • Anatomical orientation metadata (RFC-4)
  • OME-Zarr Zip (.ozx) file support for single-file OME-Zarr datasets (RFC-9)
  • High Content Screening (HCS) support for plate and well data
  • Model Context Protocol (MCP) server for AI agent integration

Documentation

More information about command line usage, the Python API, library features, and how to contribute can be found in our documentation.

See also

License

ngff-zarr is distributed under the terms of the MIT license.

Project links

Key dates

PyPI data
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  • Released:
Newer release available (0.45.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for thewtex from gravatar.com thewtex

Credits

Author: Matt McCormick

License expression

MIT
View SPDX License List

Requires

Python >=3.10

Provides Extra

all cli dask-image docs itk remote tensorstore test validate

Classifiers

Report project as malware

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