code: def test_assign(setup):
      rs = np.random.RandomState(0)
      raw = pd.DataFrame({"A": rs.rand(10), "B": rs.rand(10)})
  
      df = DataFrame(raw, chunk_size=5)
      result = df.assign(C=df.B / df.A).execute().fetch()
      expected = raw.assign(C=raw.B / raw.A)
      pd.testing.assert_frame_equal(result, expected)
  
      # lambda syntax
      result = df.assign(C=lambda x: x.B / x.A).execute().fetch()
      expected = raw.assign(C=lambda x: x.B / x.A)
      pd.testing.assert_frame_equal(result, expected)
  
      # Non-Series array-like
      row_list = rs.rand(10).tolist()
      result = df.assign(C=row_list).execute().fetch()
      expected = raw.assign(C=row_list)
      pd.testing.assert_frame_equal(result, expected)
  
      # multiple
      row_list = rs.rand(10).tolist()
      result = df.assign(C=row_list, D=df.A, E=lambda x: x.B)
      result["C"] = result["C"].astype("int64")
      expected = raw.assign(C=row_list, D=raw.A, E=lambda x: x.B)
      expected["C"] = expected["C"].astype("int64")
      pd.testing.assert_frame_equal(result.execute().fetch(), expected)
  
file_path: mars/mars/dataframe/tests/test_core.py
imports: import numpy
  import pandas
  import pytest
  from ...core import tile
  from ...lib.groupby_wrapper import wrapped_groupby
  from ...utils import pd_release_version
  from ..None import cut
  from ..initializer import DataFrame, Series, Index
label_desc: Use image node_id 9 for calling a global function with example usage: test_assign(setup) without return types