class_docstr: An abstract representation of Pipeline Term dependencies.
  
  This class does not keep any additional metadata about any term relations
  other than dependency ordering.  As such it is only useful in contexts
  where you care exclusively about order properties (for example, when
  drawing visualizations of execution order).
  
  Parameters
  ----------
  terms : dict
      A dict mapping names to final output terms.
  
  Attributes
  ----------
  outputs
  
  Methods
  -------
  ordered()
      Return a topologically-sorted iterator over the terms in self.
  execution_order(workspace, refcounts)
      Return a topologically-sorted iterator over the terms in self, skipping
      entries in ``workspace`` and entries with refcounts of zero.
  
  See Also
  --------
  ExecutionPlan
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docstr: Dict mapping names to designated output terms.
docstr_tok: ["Dict","mapping","names","to","designated","output","terms","."]
code: def outputs(self):
      """
      Dict mapping names to designated output terms.
      """
      return self._outputs
  
imports: import uuid
  import networkx
  from six import iteritems, itervalues
  from zipline.utils.memoize import lazyval
  from zipline.pipeline.visualize import display_graph
  from .term import LoadableTerm
label_desc: Use image node_id 4 for calling the TermGraph obj's underlying member method code with example usage: obj.outputs() and returns: self