code: def _read_hb_data(content, header):
      # XXX: look at a way to reduce memory here (big string creation)
      ptr_string = "".join(
          [content.read(header.pointer_nbytes_full), content.readline()]
      )
      ptr = np.fromstring(ptr_string, dtype=int, sep=" ")
  
      ind_string = "".join(
          [content.read(header.indices_nbytes_full), content.readline()]
      )
      ind = np.fromstring(ind_string, dtype=int, sep=" ")
  
      val_string = "".join(
          [content.read(header.values_nbytes_full), content.readline()]
      )
      val = np.fromstring(
          val_string, dtype=header.values_dtype, sep=" "
      )
  
      try:
          return csc_matrix(
              (val, ind - 1, ptr - 1),
              shape=(header.nrows, header.ncols),
          )
      except ValueError as e:
          raise e
  
imports: import warnings
  import numpy
  from scipy.sparse import csc_matrix
  from scipy.io.harwell_boeing._fortran_format_parser import FortranFormatParser, IntFormat, ExpFormat
label_desc: Use image node_id 3 for calling a global function with example usage: _read_hb_data(content, header) and returns: csc_matrix