code: def serialize_pandas(df, *, nthreads=None, preserve_index=None):
      """
      Serialize a pandas DataFrame into a buffer protocol compatible object.
  
      Parameters
      ----------
      df : pandas.DataFrame
      nthreads : int, default None
          Number of threads to use for conversion to Arrow, default all CPUs.
      preserve_index : bool, default None
          The default of None will store the index as a column, except for
          RangeIndex which is stored as metadata only. If True, always
          preserve the pandas index data as a column. If False, no index
          information is saved and the result will have a default RangeIndex.
  
      Returns
      -------
      buf : buffer
          An object compatible with the buffer protocol.
      """
      batch = pa.RecordBatch.from_pandas(
          df, nthreads=nthreads, preserve_index=preserve_index
      )
      sink = pa.BufferOutputStream()
      with pa.RecordBatchStreamWriter(sink, batch.schema) as writer:
          writer.write_batch(batch)
      return sink.getvalue()
  
imports: import os
  import pyarrow
  from pyarrow.lib import IpcReadOptions, IpcWriteOptions, ReadStats, WriteStats, Message, MessageReader, RecordBatchReader, _ReadPandasMixin, MetadataVersion, read_message, read_record_batch, read_schema, read_tensor, write_tensor, get_record_batch_size, get_tensor_size
  import pyarrow.lib
label_desc: Use image node_id 7 for calling a global function with example usage: serialize_pandas(df) and returns: sink