code: def main():
      """Download some example data and split it into training and test data."""
      print("Retrieving iris data from servers...", end="")
      iris_data = sklearn.datasets.load_iris()
      print("done")
      sys.stdout.flush()
  
      X = iris_data["data"]
      Y = [
          iris_data["target_names"][label]
          for label in iris_data["target"]
      ]
  
      examples = [
          {
              "id": f"EXAMPLE_{i}",
              "y": y,
              "x": {f"f{j}": x_val for j, x_val in enumerate(x)},
          }
          for i, (x, y) in enumerate(zip(X, Y))
      ]
  
      examples_train, examples_test = train_test_split(
          examples, test_size=0.33, random_state=42
      )
  
      print("Writing training and testing files...", end="")
      for examples, suffix in [
          (examples_train, "train"),
          (examples_test, "test"),
      ]:
          iris_dir = Path("iris") / suffix
          if not iris_dir.exists():
              iris_dir.mkdir(parents=True)
          jsonlines_path = iris_dir / "example_iris_features.jsonlines"
          with open(jsonlines_path, "w") as f:
              for ex in examples:
                  f.write(f"{json.dumps(ex)}\n")
      print("done")
  
imports: import json
  import sys
  from pathlib import Path
  import sklearn.datasets
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types