{
  "context": "This evaluation assesses how well the engineer uses Kedro's ParallelRunner and related pipeline classes to implement parallel execution of data processing tasks with proper dependency management and worker control.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "ParallelRunner usage",
      "description": "Uses the ParallelRunner class from kedro.runner to execute the pipeline with multiprocessing capabilities",
      "max_score": 25
    },
    {
      "name": "max_workers configuration",
      "description": "Properly configures the max_workers parameter in ParallelRunner.__init__() to control the number of parallel processes",
      "max_score": 15
    },
    {
      "name": "Node creation",
      "description": "Uses kedro.pipeline.node() function or Node class to create computational units with proper func, inputs, and outputs parameters",
      "max_score": 20
    },
    {
      "name": "Pipeline assembly",
      "description": "Uses kedro.pipeline.Pipeline class or pipeline() function to assemble nodes into a directed acyclic graph",
      "max_score": 15
    },
    {
      "name": "DataCatalog usage",
      "description": "Uses kedro.io.DataCatalog to manage datasets with load() and save() methods for handling pipeline data",
      "max_score": 15
    },
    {
      "name": "Dependency handling",
      "description": "Properly defines node inputs and outputs to establish dependencies, ensuring nodes execute in correct topological order based on data flow",
      "max_score": 10
    }
  ]
}