code: def test_export_import_parquet(testdata):
      data = h2o.upload_file(pyunit_utils.locate(testdata))
      path = pyunit_utils.locate("results")
      dname = os.path.join(
          path, id_generator() + "_parquet_export_results"
      )
  
      h2o.export_file(data, dname, format="parquet")
      assert os.path.isdir(dname)
  
      imported_file = h2o.import_file(dname, "part-m-")
  
      part_files = glob.glob(os.path.join(dname, "part-m-?????"))
      if len(part_files) == 1:
          # 'check_column_type=False' because all numeric types are exported as doubles
          assert_frame_equal(
              imported_file.as_data_frame(True),
              data.as_data_frame(True),
              check_column_type=False,
          )
      else:
          pd_frame = data.as_data_frame(True)
          imported_file = imported_file.as_data_frame(True)
          assert imported_file.shape == pd_frame.shape
          assert all(imported_file.columns == pd_frame.columns)
          assert all(pd_frame.mean() == imported_file.mean())
          assert all(pd_frame.max() == imported_file.max())
  
file_path: h2o-3/h2o-py/tests/testdir_misc/pyunit_export_parquet_multi.py
imports: from builtins import range
  import sys
  import h2o
  from tests import pyunit_utils
  import string
  import os
  import glob
  import random
  from pandas.util.testing import assert_frame_equal
label_desc: Use image node_id 2 for calling a global function with example usage: test_export_import_parquet(testdata) without return types