{
  "context": "This criteria evaluates how well the engineer uses Kedro's data versioning capabilities to implement version control for datasets. The focus is on proper usage of Kedro's Version namedtuple, AbstractVersionedDataset or related versioning APIs, and integration with session.run() for controlling load and save versions at runtime.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Version namedtuple usage",
      "description": "Uses Kedro's Version namedtuple (from kedro.io.core import Version) to represent version specifications with load and save fields, or implements equivalent version specification structure matching Kedro's design.",
      "max_score": 20
    },
    {
      "name": "AbstractVersionedDataset implementation",
      "description": "Extends or uses Kedro's AbstractVersionedDataset base class (from kedro.io import AbstractVersionedDataset) or implements versioned dataset functionality using Kedro's versioning patterns (version parameter in __init__, _version property, etc.).",
      "max_score": 25
    },
    {
      "name": "Load version specification",
      "description": "Implements loading specific dataset versions using Kedro's versioning approach, where version parameter controls which version to load, with None defaulting to latest version.",
      "max_score": 15
    },
    {
      "name": "Save version specification",
      "description": "Implements saving datasets with version control using Kedro's approach, where version parameter specifies the save version, with None generating automatic timestamp-based versions.",
      "max_score": 15
    },
    {
      "name": "Session run integration",
      "description": "Implements or uses functionality similar to KedroSession.run() with load_versions and save_version parameters to control versions at pipeline runtime, demonstrating understanding of how Kedro integrates versioning with pipeline execution.",
      "max_score": 15
    },
    {
      "name": "Consistent versioning",
      "description": "Ensures consistent version handling across multiple datasets when a save_version is specified, mirroring how Kedro applies the same version to all outputs in a pipeline run.",
      "max_score": 10
    }
  ]
}