{
  "context": "This evaluation criteria assesses how well the engineer uses Kedro's parallel execution and shared memory capabilities to build a data processing pipeline. The focus is on proper usage of Kedro's Pipeline, Node, ParallelRunner, and SharedMemoryDataset APIs.",
  "type": "weighted_checklist",
  "checklist": [
    {
      "name": "Node creation",
      "description": "Uses the `node()` factory function to create computational nodes with proper inputs and outputs specified",
      "max_score": 15
    },
    {
      "name": "Pipeline assembly",
      "description": "Uses the `pipeline()` factory function or `Pipeline` class to assemble nodes into a pipeline with proper dependency resolution",
      "max_score": 15
    },
    {
      "name": "ParallelRunner usage",
      "description": "Uses `ParallelRunner` class to execute the pipeline with multiprocessing enabled",
      "max_score": 20
    },
    {
      "name": "DataCatalog configuration",
      "description": "Creates and configures a `DataCatalog` with dataset entries for pipeline inputs, outputs, and intermediate datasets",
      "max_score": 15
    },
    {
      "name": "SharedMemoryDataset implementation",
      "description": "Uses `SharedMemoryDataset` or configures the catalog to use shared memory for intermediate datasets to enable process-safe memory sharing",
      "max_score": 25
    },
    {
      "name": "Pipeline execution",
      "description": "Calls the runner's `run()` method with the pipeline and catalog to execute the workflow, or uses `KedroSession` to run the pipeline",
      "max_score": 10
    }
  ]
}