{
  "context": "This criteria evaluates how well the engineer uses h5netcdf's hierarchical group organization features to build a multi-level data structure for climate data. The focus is on correct usage of group creation, nested group structures, parent-child navigation, and group attribute management.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "File creation",
      "description": "Uses h5netcdf.File() to create a netCDF4 file in write mode ('w') and properly manages the file object (with context manager or explicit close).",
      "max_score": 10
    },
    {
      "name": "Group creation",
      "description": "Uses create_group() method to add regional groups to the root file object, demonstrating proper group creation API usage.",
      "max_score": 15
    },
    {
      "name": "Nested group creation",
      "description": "Uses create_group() on a parent group object to create nested station groups within regional groups, demonstrating hierarchical nesting capabilities.",
      "max_score": 20
    },
    {
      "name": "Group navigation",
      "description": "Accesses groups using the groups dictionary property (e.g., file.groups['region_name'] or parent.groups['station_name']) to navigate the hierarchy.",
      "max_score": 15
    },
    {
      "name": "Group attributes",
      "description": "Uses the attrs dictionary on group objects to store and retrieve metadata (latitude, longitude) for station groups.",
      "max_score": 15
    },
    {
      "name": "Dimension and variable",
      "description": "Creates a dimension within a group using dimensions dictionary assignment (e.g., station.dimensions['time'] = len(temps)) and creates a variable using create_variable() method to store temperature data.",
      "max_score": 15
    },
    {
      "name": "Hierarchy enumeration",
      "description": "Uses the groups property to list all child groups within a parent (e.g., file.groups.keys() for regions, region.groups.keys() for stations).",
      "max_score": 10
    }
  ]
}