class_docstr: ArrowDatasetTest
class_docstr_tok: ["ArrowDatasetTest"]
docstr: test_arrow_list_feather_columns
code: def test_arrow_list_feather_columns(self):
      """test_arrow_list_feather_columns"""
      import tensorflow_io.arrow as arrow_io
  
      from pyarrow.feather import write_feather
  
      # Feather files currently do not support columns of list types
      truth_data = TruthData(
          self.scalar_data, self.scalar_dtypes, self.scalar_shapes
      )
  
      batch = self.make_record_batch(truth_data)
      df = batch.to_pandas()
  
      # Create a tempfile that is deleted after tests run
      with tempfile.NamedTemporaryFile(delete=False) as f:
          write_feather(df, f, version=1)
  
      # test single file
      # prefix "file://" to test scheme file system (e.g., s3, gcs, azfs, ignite)
      columns = arrow_io.list_feather_columns("file://" + f.name)
      for name, dtype in list(
          zip(batch.schema.names, batch.schema.types)
      ):
          assert columns[name].name == name
          assert columns[name].dtype == dtype
          assert columns[name].shape == [4]
  
      # test memory
      with open(f.name, "rb") as ff:
          memory = ff.read()
      # when memory is provided filename doesn't matter:
      columns = arrow_io.list_feather_columns(
          "file:///non_exist", memory=memory
      )
      for name, dtype in list(
          zip(batch.schema.names, batch.schema.types)
      ):
          assert columns[name].name == name
          assert columns[name].dtype == dtype
          assert columns[name].shape == [4]
  
      os.unlink(f.name)
  
imports: from collections import namedtuple
  import io
  import os
  import socket
  import tempfile
  import threading
  import pytest
  import pyarrow
  import numpy.testing
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 30 for calling the ArrowDatasetTest obj's underlying member method code with example usage: obj.test_arrow_list_feather_columns() without return types