nixtla_ray.py

from time import time

import pandas as pd
from statsforecast.utils import generate_series
from statsforecast.models import AutoARIMA
from statsforecast.core import StatsForecast

series = generate_series(n_series=1000000, seed=1)

model = StatsForecast(df=series,
                      models=[AutoARIMA()], 
                      freq='D', 
                      n_jobs=-1,
		      ray_address=ray_address)

init = time()
forecasts = model.forecast(7)
print(f'n_series: 1000000 total time: {(time() - init) / 60}')