original_docstring: 
          Creates a straighforward graph with up to N=20 (currently) nodes. It
          checks if propagation works correctly, but it also can be used quickly
          to make preliminary timing profiling (increasing hardcoded N). The link
          scheeme looks like this::
  
              +----+     +----+     +----+     +----+     +----+
              | D0 | --> | C1 | --> | D1 | --> | C2 | --> | D2 | --> ...
              +----+     +----+     +----+     +----+     +----+
          
docstring: Creates a straighforward graph with up to N=20 (currently) nodes. It
  checks if propagation works correctly, but it also can be used quickly
  to make preliminary timing profiling (increasing hardcoded N). The link
  scheeme looks like this:.
  
  
docstring_tokens: Creates a straighforward graph with up to N = 20 ( currently ) nodes . It checks if propagation works correctly but it also can be used quickly to make preliminary timing profiling ( increasing hardcoded N ) . The link scheeme looks like this : .
code: def _create_long_graph(self):
          """
          Creates a straighforward graph with up to N=20 (currently) nodes. It
          checks if propagation works correctly, but it also can be used quickly
          to make preliminary timing profiling (increasing hardcoded N). The link
          scheeme looks like this::
  
              +----+     +----+     +----+     +----+     +----+
              | D0 | --> | C1 | --> | D1 | --> | C2 | --> | D2 | --> ...
              +----+     +----+     +----+     +----+     +----+
          """
  
          old_data = orm.Data().store()
          node_list = [old_data]
  
          for ii in range(20):
              new_calc = orm.CalculationNode()
              new_data = orm.Data().store()
              new_calc.add_incoming(old_data, link_type=LinkType.INPUT_CALC, link_label='inp' + str(ii))
              new_calc.store()
              new_data.add_incoming(new_calc, link_type=LinkType.CREATE, link_label='out' + str(ii))
              node_list.append(new_calc)
              node_list.append(new_data)
              old_data = new_data
  
          return node_list
code_tokens: def _create_long_graph ( self ) : old_data = orm . Data ( ) . store ( ) node_list = [ old_data ] for ii in range ( 20 ) : new_calc = orm . CalculationNode ( ) new_data = orm . Data ( ) . store ( ) new_calc . add_incoming ( old_data , link_type = LinkType . INPUT_CALC , link_label = 'inp' + str ( ii ) ) new_calc . store ( ) new_data . add_incoming ( new_calc , link_type = LinkType . CREATE , link_label = 'out' + str ( ii ) ) node_list . append ( new_calc ) node_list . append ( new_data ) old_data = new_data return node_list
short_docstring: Creates a straighforward graph with up to N=20 (currently) nodes.
short_docstring_tokens: Creates a straighforward graph with up to N = 20 ( currently ) nodes .
comment: """
          Creates a straighforward graph with up to N=20 (currently) nodes. It
          checks if propagation works correctly, but it also can be used quickly
          to make preliminary timing profiling (increasing hardcoded N). The link
          scheeme looks like this::
  
              +----+     +----+     +----+     +----+     +----+
              | D0 | --> | C1 | --> | D1 | --> | C2 | --> | D2 | --> ...
              +----+     +----+     +----+     +----+     +----+
          """