pyexplannotator 0.1.1

Build RDF/PROV-One knowledge graphs from provenance execution traces.

PyExplAnnotator

PyExplAnnotator builds RDF/PROV-One knowledge graphs from provenance execution traces of AI and workflow applications.

The PyPI package name is pyexplannotator; the Python import package is expl_annotator.

Installation

From PyPI, after the package is published:

pip install pyexplannotator

For local development from this directory:

pip install -e ".[dev]"

Usage

from expl_annotator import ProvOneManager

manager = ProvOneManager("config.yaml")

A minimal config file should define the program name and RDF prefixes used by the graph:

program:
  name: my_workflow

ttl:
  save_path: provenance.ttl
  metadata_path: metadata.json
  prefixes:
    - name: my_workflow
      uri: https://example.org/my-workflow/
    - name: prov
      uri: http://www.w3.org/ns/prov#
    - name: provone
      uri: http://purl.org/provone#
    - name: sio
      uri: http://semanticscience.org/resource/
    - name: eo
      uri: https://purl.org/heals/eo#
    - name: xsd
      uri: http://www.w3.org/2001/XMLSchema#

Publishing Checklist

Before publishing, make sure the version in pyproject.toml is unique and the package name pyexplannotator is available on PyPI.

Build the source distribution and wheel:

python -m build

Validate the generated distributions:

python -m twine check dist/*

Upload to TestPyPI first:

python -m twine upload --repository testpypi dist/*

Install from TestPyPI in a clean environment:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple pyexplannotator

When the TestPyPI package looks correct, upload to PyPI:

python -m twine upload dist/*

Use PyPI API tokens for uploads. This repository already ignores .pypirc, so local credentials will not be committed.