{
  "context": "This evaluation assesses how effectively the engineer uses the jsons library to serialize and deserialize Python collections (lists, dictionaries, sets) with proper type preservation.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "jsons.dump usage",
      "description": "Uses jsons.dump() or jsons.dumps() to serialize the Inventory object and nested collections to dictionary format",
      "max_score": 20
    },
    {
      "name": "jsons.load usage",
      "description": "Uses jsons.load() or jsons.loads() to deserialize dictionary data back to Inventory object with proper type reconstruction",
      "max_score": 20
    },
    {
      "name": "List[Product] typing",
      "description": "Properly uses List[Product] type hints to ensure jsons correctly deserializes list elements as Product objects rather than plain dictionaries",
      "max_score": 15
    },
    {
      "name": "Dict[str, List[Product]] typing",
      "description": "Properly uses Dict[str, List[Product]] type hints for the categories mapping to ensure nested list deserialization works correctly",
      "max_score": 15
    },
    {
      "name": "Set[str] handling",
      "description": "Properly uses Set[str] type hints to ensure tags are deserialized as sets rather than lists, maintaining set semantics",
      "max_score": 15
    },
    {
      "name": "Dataclass compatibility",
      "description": "Implements Product as a dataclass (or compatible structure) that works seamlessly with jsons serialization without custom serializers",
      "max_score": 10
    },
    {
      "name": "Type preservation",
      "description": "Ensures all collection types (list, dict, set) and their element types are correctly preserved through the serialize-deserialize cycle using jsons type handling",
      "max_score": 5
    }
  ]
}