fix caching issue #8

biasanalyzer/cohort.py

@@ -63,7 +63,10 @@ def get_concept_stats(self, concept_type='condition_occurrence', filter_count=0,
                                                              vocab=vocab,
                                                              print_concept_hierarchy=print_concept_hierarchy)
         return (cohort_stats,
-                ConceptHierarchy.build_concept_hierarchy_from_results(self.cohort_id, cohort_stats[concept_type]))
+                ConceptHierarchy.build_concept_hierarchy_from_results(self.cohort_id, concept_type,
+                                                                      cohort_stats[concept_type],
+                                                                      filter_count=filter_count,
+                                                                      vocab=vocab))
 
 
     def __del__(self):
@@ -162,7 +165,10 @@ def get_cohorts_concept_stats(self, cohorts: List[int],
                                                                       filter_count=filter_count,
                                                                       vocab=vocab)
                                 for c in cohorts]
-        hierarchies = [ConceptHierarchy.build_concept_hierarchy_from_results(c, c_stats.get(concept_type, []))
+        hierarchies = [ConceptHierarchy.build_concept_hierarchy_from_results(c, concept_type,
+                                                                             c_stats.get(concept_type, []),
+                                                                             filter_count=filter_count,
+                                                                             vocab=vocab)
                        for c, c_stats in zip(cohorts, cohort_concept_stats)]
         return reduce(lambda h1, h2: h1.union(h2), hierarchies).to_dict()
 

biasanalyzer/concept.py

@@ -86,15 +86,20 @@ def _normalize_identifier(identifier: str) -> str:
             return "+".join(parts)
 
     @classmethod
-    def build_concept_hierarchy_from_results(cls, cohort_id: int, results: List[dict]):
+    def build_concept_hierarchy_from_results(cls, cohort_id: int, concept_type: str, results: List[dict],
+                                             filter_count=0, vocab=None):
         """
         build concept hierarchy tree managed by networkx from list of dicts returned from the concept prevalence SQL
-        with cache management
+        with cache management. cohort_id, concept_type, and filter_count are used for caching to uniquely identify
+        a cached concept hierarchy for the specified cohort_id, concept_type, and filter_count.
         :param results: list of dicts from prevalence SQL
         :param cohort_id: cohort id to get concept hierarchy for
+        :param concept_type: concept_type to get concept hierarchy for
+        :param filer_count: filter_count to get concept hierarchy for with default value 0 meaning no filtering
+        :param vocab: vocab to get concept hierarchy for with default value None meaning default vocab will be used
         :return: ConceptHierarchy object
         """
-        identifer = str(cohort_id)
+        identifer = f"{cohort_id}-{concept_type}-{filter_count}-{vocab}"
         if identifer in cls._graph_cache:
             return cls._graph_cache[identifer]
 
@@ -117,7 +122,7 @@ def build_concept_hierarchy_from_results(cls, cohort_id: int, results: List[dict
         graph = nx.DiGraph()
         # add nodes with metadata + metrics
         for cid, meta in node_metadata.items():
-            graph.add_node(cid, **meta, metrics={identifer: metrics_by_concept[cid]})
+            graph.add_node(cid, **meta, metrics={str(cohort_id): metrics_by_concept[cid]})
 
         # add parent-child edges
         for row in results:

tests/query_based/test_hierarchical_prevalence.py

@@ -62,15 +62,24 @@ def test_identifier_normalization_and_cache():
     assert ConceptHierarchy._normalize_identifier("1+2+2") == "1+2"
 
     # fake minimal results to build hierarchy
-    results = [
+    results1 = [
         {"ancestor_concept_id": 1, "descendant_concept_id": 1,
          "concept_name": "Diabetes", "concept_code": "DIA",
          "count_in_cohort": 5, "prevalence": 0.5}
     ]
-    h1 = ConceptHierarchy.build_concept_hierarchy_from_results(1, results)
-    h2 = ConceptHierarchy.build_concept_hierarchy_from_results(1, results)
-    assert h1 is h2  # cache reuse
-    assert h1.identifier == "1"
+    results2 = [
+        {"ancestor_concept_id": 1, "descendant_concept_id": 1,
+         "concept_name": "Diabetes2", "concept_code": "DIA",
+         "count_in_cohort": 15, "prevalence": 0.15}
+    ]
+    h1 = ConceptHierarchy.build_concept_hierarchy_from_results(1, 'condition_occurrence', results1)
+    h2 = ConceptHierarchy.build_concept_hierarchy_from_results(1, 'condition_occurrence', results2)
+    assert h1 is h2  # cache reuse even though results2 is different from results1
+    assert h1.identifier == "1-condition_occurrence-0-None"
+    h2 = ConceptHierarchy.build_concept_hierarchy_from_results(1, 'drug_exposure', results2)
+    assert not h1 is h2  # cache is not used since drug_exposure concept_name is different than the cached
+    # condition_occurrence
+    assert h2.identifier == "1-drug_exposure-0-None"
 
 def test_union_and_cache_behavior():
     ConceptHierarchy.clear_cache()
@@ -85,14 +94,14 @@ def test_union_and_cache_behavior():
          "count_in_cohort": 3, "prevalence": 0.3}
     ]
 
-    h1 = ConceptHierarchy.build_concept_hierarchy_from_results(1, results1)
-    h2 = ConceptHierarchy.build_concept_hierarchy_from_results(2, results2)
-    assert "1" in ConceptHierarchy._graph_cache
-    assert "2" in ConceptHierarchy._graph_cache
+    h1 = ConceptHierarchy.build_concept_hierarchy_from_results(1, 'condition_occurrence', results1)
+    h2 = ConceptHierarchy.build_concept_hierarchy_from_results(2, 'condition_occurrence', results2)
+    assert "1-condition_occurrence-0-None" in ConceptHierarchy._graph_cache
+    assert "2-condition_occurrence-0-None" in ConceptHierarchy._graph_cache
     h12 = h1.union(h2)
     h21 = h2.union(h1)
-    assert h12.identifier == "1+2"
-    assert h21.identifier == "1+2"
+    assert h12.identifier == "1-condition_occurrence-0-None+2-condition_occurrence-0-None"
+    assert h21.identifier == "1-condition_occurrence-0-None+2-condition_occurrence-0-None"
     assert h12 is h21
 
 def test_traversal_and_serialization():
@@ -105,7 +114,7 @@ def test_traversal_and_serialization():
          "concept_name": "Child", "concept_code": "C",
          "count_in_cohort": 2, "prevalence": 0.2}
     ]
-    h = ConceptHierarchy.build_concept_hierarchy_from_results(1, results)
+    h = ConceptHierarchy.build_concept_hierarchy_from_results(1, 'condition_occurrence', results)
 
     # roots
     roots = h.get_root_nodes()