Accelerate the speed of parsing blueprint

[lin344902118]

dsl_parser/framework/parser.py between line 207 to 242
def _calculate_element_graph(self):
self.element_graph = nx.DiGraph(self._element_tree)
for element_type, _elements in self.element_type_to_elements.items():
requires = element_type.requires
for requirement, requirement_values in requires.items():
requirement_values = [
Requirement(r) if isinstance(r, basestring)
else r for r in requirement_values]
if requirement == 'inputs':
continue
if requirement == 'self':
requirement = element_type
dependencies = self.element_type_to_elements.get(
requirement, [])
predicates = [r.predicate for r in requirement_values
if r.predicate is not None]

            if not predicates:
                dep = _BatchDependency(element_type, requirement)
                for dependency in dependencies:
                    self.element_graph.add_edge(dep, dependency)
                for element in _elements:
                    self.element_graph.add_edge(element, dep)
                continue

            for dependency in dependencies:
                for element in _elements:
                    add_dependency = all([
                        predicate(element, dependency)
                        for predicate in predicates])
                    if add_dependency:
                        self.element_graph.add_edge(element, dependency)
    # we reverse the graph because only netorkx 1.9.1 has the reverse
    # flag in the topological sort function, it is only used by it
    # so this should be good
    self.element_graph.reverse(copy=False)

I think can create a map to cache the element which is most used. This can accelerate the speed of parsing blueprint.