# 依赖: statsmodels, pandas
import pandas as pd
from statsmodels.tsa.arima.model import ARIMA
from statsmodels.tsa.stattools import adfuller

s = pd.Series([112, 118, 132, 129, 121, 135, 148, 136, 119, 104, 118, 115] * 2)
print('ADF p =', round(adfuller(s)[1], 4))       # p < 0.05 才近似平稳

orders = [(p, d, q) for p in range(3) for d in range(2) for q in range(3)]
best = min(orders, key=lambda o: ARIMA(s, order=o).fit().aic)   # 按 AIC 定阶
model = ARIMA(s, order=best).fit()
print('阶数 =', best, '未来 4 期 =', model.forecast(4).round(2).tolist())