code: def test_dataset(version):
      num_values = (100, 100)
      num_files = 5
      paths = [random_path() for i in range(num_files)]
      data = {
          "col_" + str(i): np.random.randn(num_values[0])
          for i in range(num_values[1])
      }
      table = pa.table(data)
  
      TEST_FILES.extend(paths)
      for index, path in enumerate(paths):
          rows = (
              index * (num_values[0] // num_files),
              (index + 1) * (num_values[0] // num_files),
          )
  
          write_feather(table[rows[0] : rows[1]], path, version=version)
  
      data = FeatherDataset(paths).read_table()
      assert data.equals(table)
  
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 11 for calling a global function with example usage: test_dataset(version) without return types