{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"}],"enrichment":{"capability":"Parse and manipulate OME-XML microscopy metadata as fully-typed Python objects, and serialize them back to valid OME-XML format without requiring a Java runtime.","skillfed_tags":["microscopy-metadata","ome-xml","schema-validation"],"use_cases":["Extract and inspect microscopy acquisition metadata from OME-TIFF files in Python without external tools.","Programmatically modify OME metadata (e.g., update physical pixel sizes, add instrument details) and write back to OME-XML.","Validate OME-XML documents against the OME schema and convert between XML and Python object representations.","Build OME-compliant metadata from scratch by constructing Instrument, Microscope, Objective, and Image objects.","Integrate OME metadata handling into scientific image processing pipelines written in Python."],"what_it_does":"ome-types is a pure-Python library that converts OME-XML microscopy metadata into fully-typed Python dataclasses and back again. It parses OME-XML files or extracts metadata from OME-TIFF images into an object model where all OME concepts (Image, Plate, Pixels, Channel, etc.) are accessible as snake_case attributes on Python objects. You can then read, modify, or construct new metadata programmatically and serialize it back to valid OME-XML.\n\nThe library depends on pydantic, pydantic-core, pydantic-extra-types, and xsdata for schema validation and XML handling. It does not require a Java virtual machine, making it lightweight for Python-native workflows. Most of the model code is generated at install time from the OME schema, ensuring consistency with the OME-2016-06 specification.","worth_installing":"Yes, if you work with OME-XML or OME-TIFF microscopy data in Python. The library is stable, has no known vulnerabilities, and low install friction. The aging maintenance status (261 days since last release) is a minor concern for long-term schema compatibility, but the package remains functional and the repository is not archived. Install with optional dependencies (lxml, pint) only if you need XML validation or unit quantity support."},"id":"ome-types","links":{"html":"https://skillfed.io/packages/ome-types","md":"https://skillfed.io/packages/ome-types.md","pypi":"https://pypi.org/project/ome-types/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-11-26","license_spdx":null,"license_treatment":"permissive","name":"ome-types","python_support":"supports_current","summary":"Python dataclasses for the OME data model"},"popularity":{"monthly_downloads":178508,"position":10190,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.3"}