Skip to content

Latest commit

 

History

History
104 lines (77 loc) · 4.19 KB

README.md

File metadata and controls

104 lines (77 loc) · 4.19 KB

Docs CI Test Coverage PyPIPkgVersion OpenSSF Best Practices fair-software.eu

metador-core

The core library of the Metador framework. It provides:

  • an interface for managing structured and validated metadata (MetadorContainer)
  • an API to manage immutable (but still "patchable") HDF5 files (IH5Record)
  • an extensible entry-points based plugin system for defining plugin groups and plugins
  • core plugin group types and interfaces (schemas, packers, widgets, ...)
  • general semantically aligned schemas that can be used and extended
  • visualization widgets for common data types based on Bokeh and Panel
  • generic dashboard presenting (meta)data for which suitable widgets are installed

Installation

You can install the current stable version of Metador from PyPI:

pip install metador-core

Getting Started

If you successfully installed the package, check out the tutorial notebooks.

These are intended to showcase what Metador has to offer and get you started with usage and development of your own schemas, widgets or other plugins.

To explore the notebooks interactively, clone this repo, install it, and then run:

pip install notebook
jupyter notebook ./docs/notebooks

You can use the metador-extension-cookiecutter template to generate a well-structured Python package repository that you can use to quickly get started with Metador plugin development.

Compatibility and Known Issues

Currently this package supports Python >=3.8.

We will try to support all still officially updated versions of Python, unless forced to drop it for technical reasons.

You can find more information on using and contributing to this repository in the documentation.

How to Cite

If you want to cite this project in your scientific work, please use the citation file in the repository.

Acknowledgements

We kindly thank all authors and contributors.

HMC Logo    FZJ Logo

This project was developed at the Institute for Materials Data Science and Informatics (IAS-9) of the Jülich Research Center and funded by the Helmholtz Metadata Collaboration (HMC), an incubator-platform of the Helmholtz Association within the framework of the Information and Data Science strategic initiative.