add the flat graph back in with caching, PR feedback

CHANGELOG.md

@@ -1,7 +1,7 @@
 ## dbt 0.14.1
 
 ### Breaking changes
- - the undocumented "graph" variable was removed from the parsing context ([#1615](https://github.com/fishtown-analytics/dbt/pull/1615))
+ - the undocumented "graph" variable's "macros" field was removed from the parsing context ([#1615](https://github.com/fishtown-analytics/dbt/pull/1615))
 
 ## dbt 0.14.0 - Wilt Chamberlain (July 10, 2019)
 

core/dbt/context/common.py

@@ -398,6 +398,7 @@ def generate_base(model, model_dict, config, manifest, source_config,
         "exceptions": dbt.exceptions.wrapped_exports(model),
         "execute": provider.execute,
         "flags": dbt.flags,
+        "graph": manifest.to_flat_graph(),
         "log": log,
         "model": model_dict,
         "modules": get_context_modules(),

core/dbt/contracts/graph/manifest.py

@@ -185,6 +185,7 @@ def __init__(self, nodes, macros, docs, generated_at, disabled,
         self.generated_at = generated_at
         self.metadata = metadata
         self.disabled = disabled
+        self._flat_graph = None
         super(Manifest, self).__init__()
 
     @staticmethod
@@ -223,6 +224,19 @@ def serialize(self):
             'disabled': [v.serialize() for v in self.disabled],
         }
 
+    def to_flat_graph(self):
+        """This function gets called in context.common by each node, so we want
+        to cache it. Make sure you don't call this until you're done with
+        building your manifest!
+        """
+        if self._flat_graph is None:
+            self._flat_graph = {
+                'nodes': {
+                    k: v.serialize() for k, v in self.nodes.items()
+                },
+            }
+        return self._flat_graph
+
     def find_disabled_by_name(self, name, package=None):
         return dbt.utils.find_in_list_by_name(self.disabled, name, package,
                                               NodeType.refable())

core/dbt/graph/selector.py

@@ -325,6 +325,10 @@ def select(self, query):
         selected = self.get_selected(include, exclude, resource_types, tags,
                                      required)
 
+        # if you haven't selected any nodes, return that so we can give the
+        # nice "no models selected" message.
+        if not selected:
+            return selected
         # we used to carefully go through all node ancestors and add those if
         # they were ephemeral. Sadly, the algorithm we used ended up being
         # O(n^2). Instead, since ephemeral nodes are almost free, just add all