text: 
  #
  # Python script which reads Arrow data from a file; will read the Arrow file written out by our sample "ArrowTestJava" application.
  #
  # This is based on:
  # https://arrow.apache.org/docs/python/ipc.html
  # https://towardsdatascience.com/apache-arrow-read-dataframe-with-zero-memory-69634092b1a
  #
  #
  
  import pyarrow as pa
  
  arrow_file_name = '.\\test.arrow'
  
  print('Reading Arrow data file \"' + arrow_file_name + '\"')
  
  # Read as memory mapped file from disk
  source = pa.memory_map(arrow_file_name,'r')
  # Read entire content
  print('Reading entire file contents:')
  table = pa.ipc.RecordBatchFileReader(source).read_all()
  print(table['int'])
  print(table['varchar'])
  print(table['boolean'])
  # Read one column
  print('Reading one column:')
  str_table = pa.ipc.RecordBatchFileReader(source).read_all().column("varchar")
  print(str_table)
  
  
  print('Reading Arrow data file \"' + arrow_file_name + '\"')
  
  # Read as memory mapped file from disk
  source = pa.memory_map(arrow_file_name,'r')
  # Read entire content
  print('Reading entire file contents:')
  table = pa.ipc.RecordBatchFileReader(source).read_all()
  print(table['int'])
  print(table['varchar'])
  print(table['boolean'])
  # Here's one way to access the data:
  # pl = table['int'].to_pylist()
  # Read entire varchar column, over all batches
  str_table = pa.ipc.RecordBatchFileReader(source).read_all().column("varchar")
  print('All data from varchar column:')
  print(str_table)
  # Read one column from each batch
  print('Reading varchar column from each batch individually:')
  reader = pa.ipc.RecordBatchFileReader(source)
  for i in range(reader.num_record_batches):
      print('Batch ' + str(i) + ':')
      batch = reader.get_batch(i)
      col = batch.column(1)
      # Here's one way to access the data:
      # pl = col.to_pylist()
      # pl[0]
      # pl[1]
      # ...
      # pl[8]
      # For formatted output:
      # for j in range(length of pl):
      #    print('{:.4f}'.format(pl[j]))
      print(col)
  