code: def h2oimport_file():
      """
      Python API test: h2o.import_file(path=None, destination_frame=None, parse=True, header=0, sep=None,
      col_names=None, col_types=None, na_strings=None)
      """
      col_types = [
          "enum",
          "numeric",
          "enum",
          "enum",
          "enum",
          "numeric",
          "numeric",
          "numeric",
      ]
      col_headers = [
          "CAPSULE",
          "AGE",
          "RACE",
          "DPROS",
          "DCAPS",
          "PSA",
          "VOL",
          "GLEASON",
      ]
      hex_key = "training_data.hex"
      training_data = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate_cat.csv"),
          destination_frame=hex_key,
          header=1,
          sep=",",
          col_names=col_headers,
          col_types=col_types,
          na_strings=["NA"],
      )
      assert_is_type(training_data, H2OFrame)
      assert training_data.frame_id == hex_key, (
          "frame_id was not assigned correctly.  h2o.import_file() is not"
          " working."
      )
      assert len(
          set(training_data.col_names) & set(col_headers)
      ) == len(col_headers), (
          "column names are incorrect.  "
          "h2o.import_file() not working."
      )
      assert (
          training_data.nrow == 380
      ), "number of rows is incorrect.  h2o.import_file() is not working."
      assert (
          training_data.ncol == 8
      ), "number of columns is incorrect.  h2o.import_file() is not working."
      assert (
          sum(training_data.nacnt()) == 3
      ), "NA count is incorrect.  h2o.import_file() is not working."
  
imports: import sys
  from tests import pyunit_utils
  import h2o
  from h2o.utils.typechecks import assert_is_type
  from h2o.frame import H2OFrame
label_desc: Use image node_id 1 for calling a global function with example usage: h2oimport_file() without return types