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What Python tools are available for ODPC?

The ODPC source repository includes Python tools for validating catalogs, generating derived artifacts, searching catalog object records, explaining catalog files, and checking agent-friendly artifacts.

These tools are useful when you want to work with ODPC as machine-readable metadata, not only as documentation.

Where are the tools?

The tools live in the official ODPC repository:

https://github.com/Open-Data-Product-Initiative/odpc-v1.0/tree/main/scripts

Install dependencies

From a local clone of the ODPC repository:

python -m pip install -r scripts/requirements-agent.txt

Validate an ODPC catalog

Use validate_catalog.py to validate an ODPC YAML or JSON catalog against the ODPC schema.

python scripts/validate_catalog.py source/catalog/examples/full.yaml

The script reports whether the file is a valid ODPC catalog and prints schema validation errors when it is not.

Explain a catalog for humans or agents

Use explain_catalog.py to produce a compact summary of a catalog file.

python scripts/explain_catalog.py source/catalog/examples/full.yaml

The output includes the catalog ID, name, status, object counts, graph reference, object IDs, and hints such as missing product references or missing graph references.

Search ODPC object records

Use search_objects.py to search the agent-friendly ODPC object records in source/catalog/objects.jsonl.

python scripts/search_objects.py demand
python scripts/search_objects.py --id ProductReference
python scripts/search_objects.py signal --json

This helps humans and AI agents find the right ODPC object, required fields, use guidance, and example files.

Generate derived catalog artifacts

Use generate_catalog_artifacts.py to generate derived artifacts from canonical ODPC sources.

python scripts/generate_catalog_artifacts.py
python scripts/generate_catalog_artifacts.py --check

The --check option is useful in CI because it fails when generated artifacts are out of date.

Check agent artifacts

Use check_agent_artifacts.py to verify the consistency of agent-facing ODPC artifacts, examples, schema files, object records, and llms.txt references.

python scripts/check_agent_artifacts.py

Summary

Use the ODPC Python tools when you need to validate catalog files, keep generated schema artifacts in sync, search object guidance, or prepare ODPC metadata for AI-assisted catalog and portfolio workflows.

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