code: def test_parquet_column_types():
      h2oTypes = {"mixed_col": "real", "uniform_col": "int"}
      desiredTypes = {"mixed_col": "real", "uniform_col": "real"}
      parquet = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/parser/parquet/df.parquet"
          )
      )
      pTypes = parquet.types
      parquetForce = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/parser/parquet/df.parquet"
          ),
          force_col_types=True,
      )
      fpTypes = parquetForce.types
      assert (
          h2oTypes == pTypes
      ), "Expected column types: {0}, actual: {1}".format(
          h2oTypes, pTypes
      )
      assert (
          desiredTypes == fpTypes
      ), "Expected column types: {0}, actual: {1}".format(
          desiredTypes, fpTypes
      )
      pyunit_utils.compare_frames_local(
          parquet, parquetForce, prob=1.0, tol=1e-12
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_parquet_column_types() without return types