code: def main(group: str) -> None:
      train = get_data("data/", group)
      train["ds"] = pd.to_datetime(train["ds"])
      train = train.set_index("unique_id")
      print(train.head())
  
      future_xreg = (
          get_data("data/", group, False)
          .drop(["y"], 1)
          .set_index("unique_id")
      )
      print(future_xreg.head())
  
      models = [(auto_arima_pmdarima, 24)]
  
      start = time.time()
      fcst = StatsForecast(train, models=models, freq="H", n_jobs=1)
      forecasts = fcst.forecast(24 * 7, future_xreg)
      end = time.time()
      print(end - start)
  
      forecasts = forecasts.reset_index()
      forecasts.columns = ["unique_id", "ds", "auto_arima_pmdarima"]
      forecasts.to_csv(
          f"data/pmdarima-forecasts-{group}.csv", index=False
      )
  
      time_df = pd.DataFrame(
          {"time": [end - start], "model": ["auto_arima_pmdarima"]}
      )
      time_df.to_csv(f"data/pmdarima-time-{group}.csv", index=False)
  
file_path: statsforecast/experiments/arima_xreg/src/pmdarima.py
imports: import time
  from functools import partial
  from multiprocessing import cpu_count
  import fire
  import numpy
  import pandas
  from pmdarima.arima import auto_arima
  from statsforecast import StatsForecast
  from src.data import get_data
label_desc: Use image node_id 2 for calling a global function with example usage: main(group) without return types