{
  "context": "This evaluation assesses the engineer's ability to use Deep Lake's schema and column management API. The criteria focus on correct usage of dataset creation, column addition, column renaming, and column removal functions from the deeplake package.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Dataset Creation",
      "description": "Uses deeplake.create() to initialize a new dataset with the correct path. Properly defines initial columns (id, name, description) with appropriate types using the types module (types.Text()).",
      "max_score": 25
    },
    {
      "name": "Add Column",
      "description": "Uses dataset.add_column() method to add the 'price' column. Correctly specifies the column name and type (types.Float32()).",
      "max_score": 25
    },
    {
      "name": "Rename Column",
      "description": "Uses dataset.rename_column() method to rename 'description' to 'product_details'. Provides both the old column name and new column name as arguments.",
      "max_score": 25
    },
    {
      "name": "Remove Column",
      "description": "Uses dataset.remove_column() method to delete the 'name' column. Correctly specifies the column name to be removed.",
      "max_score": 25
    }
  ]
}