A modular machine learning pipeline that generates realistic synthetic METS XML documents for testing and development. Leveraging the SDV framework's generative capabilities, it learns patterns to produce XSD-compliant test data while preserving structural complexity and relationships.

Downloading and storing the TenneT aFRR bid ladders at regular intervals