code: def test_column_skip_high_cardinality():
      # generate a big frame with all datatypes and save it to csv.  Load it back with different skipped_columns settings
      tmpdir = os.path.normpath(
          os.path.join(
              os.path.dirname(os.path.realpath("__file__")),
              "..",
              "results",
          )
      )
      if not (os.path.isdir(tmpdir)):
          os.mkdir(tmpdir)
      savefilenamewithpath = os.path.join(tmpdir, "in.csv")
      fwriteFile = open(savefilenamewithpath, "w")
  
      nrow = 10000000
  
      for rowindex in range(nrow):
          writeWords = "a" + str(rowindex) + "," + str(rowindex) + "\n"
          fwriteFile.write(writeWords)
  
      fwriteFile.close()
      try:
          h2o.upload_file(
              savefilenamewithpath, col_types=["enum", "int"]
          )
          assert (
              False
          ), "Test should have thrown an exception due to all columns are skipped"  # should have failed here
      except Exception as ex:
          print(ex)  # print out the error message
          h2o.upload_file(
              savefilenamewithpath,
              col_types=["int"],
              skipped_columns=[0],
          )  # should pass here.
          print("Test passed! Parsed with large enum columns skipped!")
          pass
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  import os
label_desc: Use image node_id 1 for calling a global function with example usage: test_column_skip_high_cardinality() without return types