def sorted_ephemeral_ancestors(
self, manifest: Manifest, unique_id: str
) -> Iterable[str]:
"""Get the ephemeral ancestors of unique_id, stopping at the first
non-ephemeral node in each chain, in graph-topological order.
"""
to_check: Set[str] = {unique_id}
ephemerals: Set[str] = set()
visited: Set[str] = set()
while to_check:
# note that this avoids collecting unique_id itself
nextval = to_check.pop()
for pred in self.graph.predecessors(nextval):
if pred in visited:
continue
visited.add(pred)
node = manifest.expect(pred)
if node.resource_type != NodeType.Model:
continue
if node.get_materialization() != 'ephemeral': # type: ignore
continue
# this is an ephemeral model! We have to find everything it
# refs and do it all over again until we exhaust them all
ephemerals.add(pred)
to_check.add(pred)
ephemeral_graph = self.build_subset_graph(ephemerals)
# we can just topo sort this because we know there are no cycles.
return nx.topological_sort(ephemeral_graph)
def write_graph(self, outfile: str, manifest: Manifest):
"""Write the graph to a gpickle file. Before doing so, serialize and
include all nodes in their corresponding graph entries.
"""
out_graph = self.graph.copy()
for node_id in self.graph.nodes():
data = manifest.expect(node_id).to_dict(omit_none=True)
out_graph.add_node(node_id, **data)
nx.write_gpickle(out_graph, outfile)
