code: def test_rolling_agg_aggregate():
      df = pd.DataFrame({"A": range(5), "B": range(0, 10, 2)})
      ddf = dd.from_pandas(df, npartitions=3)
  
      assert_eq(
          df.rolling(window=3).agg(["mean", "std"]),
          ddf.rolling(window=3).agg(["mean", "std"]),
      )
  
      assert_eq(
          df.rolling(window=3).agg(
              {"A": "sum", "B": lambda x: np.std(x, ddof=1)}
          ),
          ddf.rolling(window=3).agg(
              {"A": "sum", "B": lambda x: np.std(x, ddof=1)}
          ),
      )
  
      assert_eq(
          df.rolling(window=3).agg(["sum", "mean"]),
          ddf.rolling(window=3).agg(["sum", "mean"]),
      )
  
      assert_eq(
          df.rolling(window=3).agg({"A": ["sum", "mean"]}),
          ddf.rolling(window=3).agg({"A": ["sum", "mean"]}),
      )
  
      kwargs = {"raw": True}
      assert_eq(
          df.rolling(window=3).apply(
              lambda x: np.std(x, ddof=1), **kwargs
          ),
          ddf.rolling(window=3).apply(
              lambda x: np.std(x, ddof=1), **kwargs
          ),
      )
  
imports: from __future__ import annotations
  import contextlib
  import datetime
  import numpy
  import pandas
  import pytest
  import dask.dataframe
  from dask.dataframe._compat import PANDAS_GE_210
  from dask.dataframe.utils import assert_eq
label_desc: Use image node_id 22 for calling a global function with example usage: test_rolling_agg_aggregate() without return types