code: def test_make_timeseries_keywords():
      df = dd.demo.make_timeseries(
          "2000",
          "2001",
          {"A": int, "B": int, "C": str},
          freq="1D",
          partition_freq=f"6{ME}",
          A_lam=1000000,
          B_lam=2,
      )
      a_cardinality = df.A.nunique()
      b_cardinality = df.B.nunique()
  
      aa, bb = dask.compute(
          a_cardinality, b_cardinality, scheduler="single-threaded"
      )
  
      assert 100 < aa <= 10000000
      assert 1 < bb <= 100
  
imports: from __future__ import annotations
  import pandas
  import pytest
  import dask
  import dask.dataframe
  from dask.blockwise import Blockwise, optimize_blockwise
  from dask.dataframe._compat import PANDAS_GE_200, PANDAS_GE_220, tm
  from dask.dataframe.optimize import optimize_dataframe_getitem
  from dask.dataframe.utils import assert_eq, get_string_dtype
label_desc: Use image node_id 5 for calling a global function with example usage: test_make_timeseries_keywords() without return types