code: def test_eval_query():
      rs = np.random.RandomState(0)
      raw = pd.DataFrame(
          {"a": rs.rand(100), "b": rs.rand(100), "c c": rs.rand(100)}
      )
      df = from_pandas_df(raw, chunk_size=(10, 2))
  
      with pytest.raises(NotImplementedError):
          mars_eval("df.a * 2", engine="numexpr")
      with pytest.raises(NotImplementedError):
          mars_eval("df.a * 2", parser="pandas")
      with pytest.raises(TypeError):
          df.eval(df)
      with pytest.raises(SyntaxError):
          df.query(
              """
          a + b
          a + `c c`
          """
          )
      with pytest.raises(SyntaxError):
          df.eval(
              """
          def a():
              return v
          a()
          """
          )
      with pytest.raises(SyntaxError):
          df.eval("a + `c")
      with pytest.raises(KeyError):
          df.eval("a + c")
      with pytest.raises(ValueError):
          df.eval("p, q = a + c")
      with pytest.raises(ValueError):
          df.query("p = a + c")
  
imports: from typing import List, Union
  import numpy
  import pandas
  import pytest
  from ....None import opcodes
  from ....config import options, option_context
  from ....core import OutputType, tile, Tileable
  from ....core.graph import TileableGraph, TileableGraphBuilder, TileContext, ChunkGraphBuilder
  from ....core.operand import OperandStage
  from ....tensor.core import TENSOR_TYPE
  from ...None import eval, cut, get_dummies, to_numeric
  from ...core import DATAFRAME_TYPE, SERIES_TYPE, SERIES_CHUNK_TYPE, INDEX_TYPE, CATEGORICAL_TYPE, CATEGORICAL_CHUNK_TYPE, DataFrameData, SeriesData
  from ...datasource.dataframe import from_pandas
  from ...datasource.series import from_pandas
  from ...datasource.index import from_pandas
  from ..None import to_gpu, to_cpu, astype
label_desc: Use image node_id 20 for calling a global function with example usage: test_eval_query() without return types