code: def test_dictionary_array_automatically_read():
      # ARROW-3246
  
      # Make a large dictionary, a little over 4MB of data
      dict_length = 4000
      dict_values = pa.array(
          [("x" * 1000 + "_{}".format(i)) for i in range(dict_length)]
      )
  
      num_chunks = 10
      chunk_size = 100
      chunks = []
      for i in range(num_chunks):
          indices = np.random.randint(
              0, dict_length, size=chunk_size
          ).astype(np.int32)
          chunks.append(
              pa.DictionaryArray.from_arrays(
                  pa.array(indices), dict_values
              )
          )
  
      table = pa.table([pa.chunked_array(chunks)], names=["f0"])
      result = _simple_table_write_read(table)
  
      assert result.equals(table)
  
      # The only key in the metadata was the Arrow schema key
      assert result.schema.metadata is None
  
imports: import decimal
  import io
  import numpy
  import pytest
  import pyarrow
  from pyarrow.tests import util
  from pyarrow.tests.parquet.common import _check_roundtrip
label_desc: Use image node_id 6 for calling a global function with example usage: test_dictionary_array_automatically_read() without return types