{
  "context": "This criteria evaluates how well the engineer uses Deep Lake's async operations and concurrency features to build a concurrent dataset manager. The focus is on proper usage of create_async(), query_async(), Future objects, and cancellation mechanisms.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Uses create_async()",
      "description": "Uses deeplake.create_async() function to create datasets asynchronously instead of synchronous deeplake.create()",
      "max_score": 25
    },
    {
      "name": "Uses query_async()",
      "description": "Uses deeplake.query_async() function to execute queries asynchronously instead of synchronous deeplake.query()",
      "max_score": 25
    },
    {
      "name": "Future result handling",
      "description": "Properly uses Future.result() method to retrieve results from completed async operations",
      "max_score": 20
    },
    {
      "name": "Future completion checking",
      "description": "Uses Future.is_completed() method to check if async operations have finished before accessing results",
      "max_score": 15
    },
    {
      "name": "Operation cancellation",
      "description": "Uses Future.cancel() method to cancel pending async operations",
      "max_score": 15
    }
  ]
}