class_docstr: Reader for the Arrow streaming binary format.
  
  Parameters
  ----------
  source : bytes/buffer-like, pyarrow.NativeFile, or file-like Python object
      Either an in-memory buffer, or a readable file object.
      If you want to use memory map use MemoryMappedFile as source.
  options : pyarrow.ipc.IpcReadOptions
      Options for IPC deserialization.
      If None, default values will be used.
  memory_pool : MemoryPool, default None
      If None, default memory pool is used.
class_docstr_tok: ["Reader","for","the","Arrow","streaming","binary","format",".","Parameters","--","--","--","--","--","source",":","bytes\/buffer-like",",","pyarrow.NativeFile",",","or","file-like","Python","object","Either","an","in-memory","buffer",",","or","a","readable","file","object",".","If","you","want","to","use","memory","map","use","MemoryMappedFile","as","source",".","options",":","pyarrow.ipc.IpcReadOptions","Options","for","IPC","deserialization",".","If","None",",","default","values","will","be","used",".","memory_pool",":","MemoryPool",",","default","None","If","None",",","default","memory","pool","is","used","."]
code: def __init__(self, source, *, options=None, memory_pool=None):
      options = _ensure_default_ipc_read_options(options)
      self._open(source, options=options, memory_pool=memory_pool)
  
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 1 to create a new RecordBatchStreamReader object from inherited base classes: lib with example: obj = RecordBatchStreamReader(source)