code: def test_read_column_duplicated_selection(tempdir, version):
      # duplicated columns in the column selection
      table = pa.table(
          [[1, 2, 3], [4, 5, 6], [7, 8, 9]], names=["a", "b", "c"]
      )
      path = str(tempdir / "data.feather")
      write_feather(table, path, version=version)
  
      expected = pa.table(
          [[1, 2, 3], [4, 5, 6], [1, 2, 3]], names=["a", "b", "a"]
      )
      for col_selection in [["a", "b", "a"], [0, 1, 0]]:
          result = read_table(path, columns=col_selection)
          assert result.equals(expected)
  
imports: import io
  import os
  import sys
  import tempfile
  import pytest
  import hypothesis
  import hypothesis.strategies
  import numpy
  import pyarrow
  import pyarrow.tests.strategies
  from pyarrow.feather import read_feather, write_feather, read_table, FeatherDataset
label_desc: Use image node_id 53 for calling a global function with example usage: test_read_column_duplicated_selection(tempdir, version) without return types